From 39173f831a31dbd4358460fb8707e17b2c4740af Mon Sep 17 00:00:00 2001
From: iulusoy <inga.ulusoy@uni-heidelberg.de>
Date: Wed, 12 Jun 2024 07:54:34 +0000
Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20ssciwr/A?=
 =?UTF-8?q?MMICO@894ad0938b6b95ebca8ecf0c5487adbfc94fbe84=20=F0=9F=9A=80?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 build/doctrees/ammico.doctree                 | Bin 514830 -> 521828 bytes
 build/doctrees/environment.pickle             | Bin 1175128 -> 1193552 bytes
 .../notebooks/DemoNotebook_ammico.ipynb       |  40 +++++++++++++---
 .../notebooks/DemoNotebook_ammico.doctree     | Bin 170162 -> 176368 bytes
 .../notebooks/DemoNotebook_ammico.ipynb.txt   |  40 +++++++++++++---
 build/html/ammico.html                        |  14 +++++-
 build/html/genindex.html                      |   2 +
 build/html/modules.html                       |   1 +
 build/html/notebooks/DemoNotebook_ammico.html |  44 ++++++++++++++----
 .../html/notebooks/DemoNotebook_ammico.ipynb  |  40 +++++++++++++---
 build/html/objects.inv                        | Bin 4433 -> 4485 bytes
 build/html/searchindex.js                     |   2 +-
 source/notebooks/DemoNotebook_ammico.ipynb    |  40 +++++++++++++---
 13 files changed, 184 insertions(+), 39 deletions(-)

diff --git a/build/doctrees/ammico.doctree b/build/doctrees/ammico.doctree
index 029dc39d9b9ee26880920775000d82d77be633fa..fd64ab6b1e658826d3d48df5a349081d5af0b0ab 100644
GIT binary patch
delta 31912
zcmb__cYGGb_P0C9?gq#sL?9GNNa&$QLJKVv0jZ&@)KDZm^rjaSNfbhhv?nk?LJ2h}
z#e@=SAk<(56;R|-ycQ5t@Y=7!`#op&d7j<i{lWcw-u#i--8pmSoHOT~Idf)qpM`rX
zetElM(kyM3m=!Q9FirPp{r9BlRjO(Qa(`8QKv3<7kt4<pA2CT@t*Vy~NEkVSFKQ(W
z8#ZFXl)=MCO&&I8{N$;VM#M%;o-!$-MMU*>&-7~BrF*YFJ)a)jx@*^G+IE-cX6Zw6
zr&QC63oTcksj7GRFGy?u4@j%$o~@zh6_w3u>BY=&KZ#`}o||%PExl-?66*2bDT$Lt
zOimm>W_VhnIWR3TH1)xX*=fmXGtz1#KIuLnqwDM8p2d|y#opIFt$S62An+uH?zGa?
zv<s>}z9iMlwYBw@+70z6qG|(KuZ|uozI@$tw``QRfsohZ^e}l;29%)|`Q@}Itpq>w
z94!~-g$j2-c_Kqg%I}}jD`>S9Wc_PQz`5sZ%7(S{kiaLcfv~Y#--Txn@>=MrpV6lk
z=D0RxMC)0y^#^)&>p>(vU|tgxQT5O2Wwlv~*U1W~#F+-NZXLauHeTj8)l0FsfMrQv
zQ(=)-8|F4$p;>%Z57%aS5@t9+{H*3G)Wj<K_p&<kf6@vb;TnnCqttNfsUZ*OlvfG<
zrp7Ovv$Gz1EU`jjKw_BuHV*uel-`@g>TpGo83!@p38}<w#UGFGd$VLnuYg$Xo`NDd
zmAD!ZDPN3+4FB*8OEnc`XM2((8vqgOg{U@LMy?77lS2k*6)fx`hCzC~2a2W+b&t^=
zd(6jN$p?+Cx|hAbt@AV3hI@*qPDs*o8|Z0b*lZadqpuN(v*q2HT3OHdxh=$`*>cGu
zy|S1xTZS|eowNxuyOUl~Ml9B!6tB*f`3+$iX!mPFeJQom-ZZ0Ji)TZ4;hi;D(+Gex
z(l-f|nf<hya%p2dQEUU;Vc1F5Y`L?$K2U!6w64n`v3e0t(xO1QFwl&3Wf2ONzx%*!
zc|Fx^E6#wb_S!`1ZAmY^ymnGiQa?)+cY=Eo=9Cm0KyR!*NZgz)C&uc1TnGF#Z9>%-
zqNe;SR)0zS2s!*2&_KS|NAK+*#1ucw_T1e(M3^ZudS76JB7rF&Da`#?iYLELsO&aO
z@2jPFmMm^0Dx}CI<Fp2%T#8I>p?9S+VYnU>Oz`2I10aRcDKc}oUK8-iEu&nI`75*(
zsim9M<b)i})P9f&UG*5(CI{;iN9avUqk%g^$G>>GTCJ|+-C|l35^U>TT3fldl|I2I
z<(_f+LNN-sNy;NqWO!@+Um_{R(<7vTcqN6jSS$oBZTJovEHZEhHGCySM!uuB5j#@k
z^@C!%SJdLo6n1E63SANZNbyXpQr|U#*ib|C65wfwK2329k@zG<PV|U6PEa16At^LG
zO=aHGdM)uAz+&~%%iHT+TrVl%knRix42{$4?e$@rChtC{*O5oR)J*wg2YtM_heoez
zBehVfh$&KX4v!8fiSDS+)@m`hCqC8`)#u1_owd?bMt`gK(c%=Q`VBNww3s9BJ{8cf
zMjNztKL)wZb!#Nu-$>4au3EeXvrDX%cnt&rLvlY+iZEsO&?-@R^&k3ERQAXa4MY`S
zTNW54N&@a{5hY5@ky`tJXSC^x#FrF_#X(0CxXHbp^=L7F4yll~NYQj{T7W51=g7WY
zFm5Qd%UT0hacUOc*#H4^tqxwA!-{09L06HxMIDk#^a#CyYp7#zT5CpG(FY*SwD8bA
z#4BslF}h-HItIjcZ5rE6AMVqpzq;vDw9kpcFi+CTaB*=CneC_AkMu~*l;6)`rFv{G
zD;4fYsUF82l<NCA@@PG?xrmtSRE`RBS*ZX_O7-m=R;r7{tWv6*bCgnbD%7t1T%}YF
zP*$ps=8#f#k`aCN$AjEc0>GUcz_EI$oYY%y<+`aPNxJn3KuNc5^wxKZ$#Z=^V3e4E
z7SJm(cdjz~*>hR3Kn)ZtO6vXe0b(^^N(3|zE9WZJLOJoNfI9Ndm!g8mnJcrS;SP3!
zZqlvYKw#G`H{Cy=TR_3Og_3m(C3GuP-g{QBK>e_SEeA?cu-O161$%8SE10;gXbrll
zXib*cqxCYf-Sc`Y@#kFjQQAEAQIFpP#MGe(fvQA&k>ru_&+C!0Vt>7;xCd0EZOMc}
zY1<!GZ#OZHa9g$-^vl`?S+TZ#;utm7w$lJ1Z97fevbM#{!xd{=%si*I83XlKecJZ+
zKz)(uI#2noXXeQngY><wXVBJCi~jSJTDXD4HXVo;=CN7?+d*ZISM-tr?soH(v&k3&
zW1SB;I2*0J%pa(iU!DNH=ug<yeAOPHzPZ6OPw7Raq56y3Vj20OUO`^_N_$#l%~QIu
zi5iBvGv|4ygg#>5JeK!iC2w(H9?uEd0U7d&UdK}+!*pe;-e_Lf3m#}ZH_c-S+iKQB
z0KSP~F*S|}Zf_F;afaA0M~e)-gU3q3cj<~He7BH<o4=qx@00Mc7xd?}qB4J`-b@(t
zJ^2fw<+bj5ZFzK*9whTdLLkO`pSa7;XK`!QW&W$M{}N|<2e`d6aAleNGGYOqfgMfQ
z8nyXK>MxAaBSeS!EOohhl-|fyme4DC2LOoVUDU0Q*Wy(lcMe1C#~V?8s*0vr;9cj_
zl&p<lK)JY-C{tu8Aq#U40wb7~3r1rCo;shM>U0Hlc3ME0qAvl8_5P{lP0e!h=4idV
zJTgWvs=XvzzYN(9QY6u!OeU^silOs)Ol%c{=iA1lE48a5-(Db0R{%9uP7C6~jNK%3
zJ07V)*+Ex4C_Cmm)qe9h#3$assQ!3;vUXYx%5lhiynac$qU1rb=cV}^d)~I5Aoj!)
ziailhVqDbf;?jIIeFraaPTxTb*wdl~JS`S5JZeL>m`}Kl`zb#^UoNR=l#$>46j)To
zSHbkwXo1xF`vWfV)B@#r9gTRX^Q@u%#}vJi=nF6yn9QD{$GXl_2WqH~T0>oFsy<8%
zUZ70tz*PMOF#s*d<xW|k%xdBS9#T+5bGev@YVx+T7btIwk|uJoW`T0F=?j#jU593N
zN86X~A8@p2&5jl&J6e=HiKAp6`x>y3O-=+H`Pgxg0w!_ssYTp*Mcmj0tZ&Vx>)pkT
z1s<(SS-Ek#9xlFHpn}0~7s%hI>m3A2_N!y5newY&TRog#z#3+&L0{}wArSVfM;*h%
zesvc>$gl1q=Gd=Bq<R%BBGsp0J;Ka-vd9d*U1%MuX27~Wz`6=hPIyfZmYsKLP35&2
z`ZcYC?2!r^j~gE@+NP2Uc9orH>QlA8{9M)#G%5xIho$O$Qe}}O{dsK+)p8i1B}#2E
z9Ks#LaH%U+vbOd%tS>E7$u-n1muR>r(=7cgQO5IiDqTIBDhDU)^<90ap;Df>R8Q;e
zPs$-{%_^=qJ3g6N$&3w6r)JD#23@haWfW$zO|=nI5=RY77-P#?)QF0xF=|}I*zv=s
zju{d0Lc*{SlcUm7%ko9t2f^ixs(Q1yxCbk0Jh06C@A;7GGJ1wtQm%VdkI?q`L>`>&
zV=J|fj683)8T>Z{up@*cTjW~<KJg$i-X-AQRryzdCsfyn=w|x6b{{7yAanGQ>FeWv
zUxFuY`5zkh_UDS!^7a420{)UuE5!xq4$?R`_{q|Lgwg}JPMMajSM*RG=K|CbYjzRz
zh9|r4co|<uFDC-uV4tZ#MWr`5lm#FqG(`P3Y|C^Dq$Pv&xB&V6e_W<_;hy4&Wb)k~
z+04o@Xlz#7lv#E2n$;<?1vaa(Z{Uh<Q_|co!s1d(J*YJ`qS9!g(-V`aR|zm1?f_0q
z&@=0`o;-ST#FWGl5mP6Rm=rN(e1y_?eq<qw@Mi<-dUf!BZs%9f$sk(!nr?}*)}H}U
znzD<q|7I5;cfuPoyOQyOnEM7#B|)<Z2N;s)(h*Eg2oa?Q4SK*-BWfUZ85L2dPDF3;
zH!fl9h=}noFk^m(B3?|GG%8^zoJ5V`BVI_DI%Z02M5PB(ot2{GL@7!){hQp9m3sV}
z8b8OY->}vdZ&>S!Hz*O)LF9ldUQ*y5ONuJHX*g}mRUTfN>AHEBsw>~HmJ?`+rE20z
zn=He-aU|5?e`EHGq>KmH{UT{~RNXW`{peM#Q$Q!LQ$Pi;Q*i$~=2VOh&ucr#$*6$o
zc&b$E1t|J;BO>%PvBsYKH@ad^{u`QObxPA!9+v;fTM_U~sG^rD5xCHcC$To1RwYlq
zY$~_DuGbfV3uRng(Lq+4rMIUWPClj0(pQTn3uX8pMt$ktVp)Hag)psZo)Y&0Ma)83
zq`Dq07fZdC98q0=LdK-%m7#XjCC!Vj7+;U>-V0@Pv?wWerRepvVG0D!v=B(GIr?&K
znuP#?+|-5ajF2H<lnCVTgaWx`{6qzEQy21*S=*wZN}TB<6XszZxM3kXCA6R=^TdVn
z{Z0BL`O7wNLiy?fh5M2pH=Ypg8#dep3sr*h4=-+&pcDrd%Iojwq2d?ShiWNGEh5K<
z6nJtLV&Y1RY<|yzsLv4STXuQ_3yPKu5>K>PG$v08tnU;GJF9x2<A`3bxz|~ZfMk`k
z8oUTsbZa>)zV^DN-ZTIzCWr<GT02aL(YuJ@NTGOhmg5$woaKZ?DrboZB}b1~nowR$
zU&I;9VD92g3Oz<Flv*Rbj~ep77VANTiL;ogAj9e@VUeeGcqe&Jm__8`C3?I_Sfn&6
zcqu~oEHt1*+r~wd7h&ybsj`?G35C-0y^EOZwIJyT^b_4~^60gSod!gztL^wP<0r|y
z>RP1y)1y~+?e%w^i3VSYsNCn$^h-jVg><cKWep;^wRnG#OuC?z&b=Y^q5<OSB6)o)
zR`FL90?HY^zlgJ#|6ZhG>pN5v=DxBB;cGd0D_tKW0v7X<HE6MlT=m8BRE9oMprpt(
z*uqr|xHOrc2VIM6UQFD<up=p8tNadP@Ge=2EVlGa>dq?xwKQtB7-DA&Z%$Wi;msGT
z$Q5$Eeo${Gi>=lB`GmZ1EjFe4EI$nG>am!YtBcp^d1B0B%4Z_x1WnaE^<UP-@WnDa
z6N#%?TqBYeb5d&QVoploF8PD%SjJE6XvAoMn9^M2fJLlu!blxbgC<Oi9X2Lm^5it1
z!co$12jN#696$kU67P9&s9@j{G6TMxy#;c^3!-*6D4YKagT)h7WEh~8j8`izqt76P
zUTlffx){}E@@YMsLKNIbmc^nQ_gu+)3N5(WlXR<B`2R(5(<SUBiY;N=@8`q8dod&E
zHjH<kEC8%`txm{*wPXcAyD$K-NM#%Df#I^oau{@_q7f>?lC+|p2?HXvb<`^Sp`>Lj
zQA<b%Dl!bMi!5;j`B2!!qPO&F;^-2Y`<C9pHH`XH=H3ly5Hk0M+w^?x4EHDNmk^=y
zKIIB7ErrXTxm_<IPN5G<3|~<o>)zBti+sL>wH{<^uZeh>vP18#{chEt5uxJeC2GP&
z2`^GxcHgO26pt@evu?4aYJFK^Db&?A>mCJCwZ0^0<(+wf;`&mfrl@YU#(iW1qmp#b
zG>XaDGmR%iW2+`+sk|N>SW8sK{Z3J{M$<>dKRsKI65R{oAN!05mO(jsNioE#8CVGa
z&_~68E(gB;AAbD2UIrh$UPd`)mtLJj#&i9T5O+_+#6N&<J+P`Qzgw4L<5CsKtXrz&
zijoqf%ZI`c_FIVe79#K9Baydmspo9XTH>6A1c)Ks%JTKSdKK}7_3&yT%wIktW)(64
zB{Par=IXr#N@jF5c(54F&Ol<|Hgtu8oX?l2Am>w<FlGCz%a99txMaPn;$gkJxP+4h
zqxZvwHTED`P+A_|uUFKXE6{7-XrZF1N0vMQV@JsegNvlH;hlrvf*N{MPgOkZb8R)~
zlM@Eed3Lwm945+v6|{>J29-$&>~_b4DCKs?12LujmD^3{GECHxTMuD#Yc3I|GXAqX
z%I!*I3D+L+W(j8zbIP|b_oyu4CdE*EQ@!{9>7p_{$`3eD@B}&2<C`Gi2+FALW{%QL
zand74AAw6)PTeY(knHhi1(F@qOr#{-MPig${*<nGruo#*GUZ5I(G*W8CJ@k}S(s;C
zxALK1`I>(1Yx=d-6yYSAmI|!lj$A0m<?GwDpP6mX+2xOWCLGnpj~?0Wm_CC_4nj*E
z*Zbopcj9rqnx<8gtv^@Mq^OkUdB0+`T)WGtB5R)1hiDB|9fgsV(tL!)q{)v@>i^a{
zQ?1%?>5#@@<a7LlCJa2FNN=RPei=&CAx-9<*5eR(qD8#i@eZbz@de1kPEC_bUe;=A
zY3$kCrpX%xdPi-IAMq-Mc$*I~9uVRK3h}BmPBCilDa7>;iCQ8xO+}6cX*}<s0nHk~
z9se$H-|^$Vt#IG-;l=}+P=lB8>iV|AEy9<n^raVX`DKh3z!u(p@9RB9n`OM6*>V{P
zLYDtpuSjCREnys_Ft%JKwTp<%CM=V8M;Q}*l#WptE#Ub+U|!s>SZ15gEs)JVkl=He
zXS&?dOUQbw0@_f27E!t9^nNnsTPqYl!(@ri(GI(;xFf1=DlBJ~DXRWch^k)|RTgmR
z<t!8cGgXzB+o-ZYqJ1C}J7OVH`8>k+Rty(UU0Q_gKaW`I+2t&)-pe^8dI1eV7Ve0w
zDGE*R<%+D7<xXL}ww%QeV2Yo7uuRnsJ5?6CLp~6us_JK;>K%(JfLK%={0uu1|58+4
zRaD(YLr{e~qUydvb9K3*DnvS|a!IBN)f6Xbl7)pkCabBm2@4Msp0<O4tSHfkLE@=5
ziz1G3oL0v%PRT3!Gh&MLWWL%{zI_EVqgO8{NSPF-RTFd3Iq1f1kE;k>mKUNF&oloi
zs);wfV9ee=MX|ThsRtW{Tt%Zxjz%|pjjsO?P)+>es0>`eG62TtngL}zi(V}uo>&2@
zCkMD~6i1&k>NtH1yWOxf*`vBvRX+ZuUOJ>PT#s6cJ+%T?jnibzmwJ>dhCGsTycN?_
zESC1Ao-CTI;6;gNaP=BKS61qYW!hsns)9eONy8Pg#~6{Qtx)TbPQZ+H2wWRSWLaP9
z6Gh?*6*UZBp`r$qNc7i{Y2WBI#Ecax8k@dC<v?Z<X|`yLNp<8v(3~R|lsuuM%(|hs
z6exK@Pe6Axp$}T2BA2l@^%un+i-v5A29&(n@Q&5}X#i8uwiNdW+N!+wP%?ml$w0|u
zpqz9Iy9Owkj2(r@=y+S7hT{&`T}F)f%c24$Q6X;@F>1=ip#jB2$(2qz%C3BvIDmuc
zK*@BVjQ<{v6eZK~M<F_*e$Z32u8NLlR;m%9@;AMMHk2OMk@azgLVg@#M97GK!sV06
z@Q2d!%u0&la4^D$MgTP;xeglkuDqzl+(Jyg@d$_&lfcGIqFnH!-ixp^lkHbJ$9%-U
z^(^g}VlvNSl1gIoqK%SI3Q_XeLn+BqEdF3a0>s3kcx;tY<-ZCc6{{XLhQPpMh?3bu
zdGi+>hC#{f9W2D&)nE0EqVXzaRt;9EL8KD=i7ply&#ZE)Qn!ba(O?w^;lnKiK*)Se
zweBYsLio}nAXIz-6Z3^~@PG8t0wwcRA1v5Swa1_O%VL}2D=-V_J<**)Mb;`A_7^M*
zCAZq7T4{siIm4(Z&(0CWM1QysMD1E9^{hlMt(fSrLT&N=YnAd%*MJbdsr?F$+Hc=O
zO5xwDIBFkxUvDgaTcr{uKd+MK@9RATN{-mulS>QlTnZ8U-Bl`LzqX1ac3Tbl;)osY
zkR$erjxdiScDNQ!g)Sx6!r^PJbX;-xS}R>e><BIS*w^F27)Ws@=QpJ=X3I~)jd0$=
zi%XXgfu<E*?hG)7iC*cPsB*;tofY%;Oqcxwjn~DfbdC>3q;q`mQaaCQBhqEalV)`d
zcR0s`J3bsHah#J5hj}LzPdd-UXi5`lLb|+X81dquLYS)%o>2&KM^pPng)lc=P3<?q
zlRY~7N+ATWg^*`vC(%4J?<``(ijo;la*AiDrG*2Y=eTC+wmGg3iIn$78f4(APr58u
z%&6(=Nup76Tnlhd`G)DmjLD*DhDyA3>uL0mU4;=6q<|WsHzXTmYAvILY_%`2YLU)B
z2jziaqg}>MF$w^*c|9US86QfXPhQPXKH%jHHJv396}IV&sd7wbXvwyZl5GU#_~J%G
z9EP}C15?FNbVMdH81kTXc&!q~G_hCp9+(5{Y$7=s^5+spFD*wk+UakUO>5c#poZ48
zozWL1?mK2E%lHmd(;3Kb6>}Xj*fI*9Fj|PeGT1T}{llmu#A;<3_cLTtNu!>2pL%(!
zc$m8bwF~cT!ZiM4b@6Qmn})3hosns1ji{A%w4#MWRoOf|0Hd7(4@r#8qv2{?v3WFH
z?K2O~BQ7d!^!AxY@la#4=(d_{AY5L175Vf|t9f0^>n~V{F1wa7dWwMz66@*&w3e9+
zSS@dqG2RlBSCg6G(DU6GqoOCNVXzpzTK-ZN`o2Kb;2fQ;W@|ZPfY_jF);eku%NzZ~
zL9P+Gt5wu`X0<J9&0Xz@D-kU&^0RorurZ)FR|T+iN430dwY+C<d0Vv%UPIX81#ZcV
z&~j%O`mDN!4Lx#=>azhuSqF|I*KnV$t(Lg8TCxE;#Q_6sD~7Cb#FyFtnH*=7l5wL%
zd8hQ){+?cKv%kSKW^8{+Yj8DqwY(Q$RC5g=nJd%kuv$h(8efSNkV83dr1@ZaWsDL!
zwCMFUYM(ECjZ(}NKmx17IB__+sj`tM_O4N;m$OEh9!eyko)Pb&Eq2prQ-i2oS4(SG
z<$WT;W`0bR!~D>i%?~A;AIim5jn)DsO*Yz2h3)NGNGEPvqipcmYQ{z_K%Q%d1m)S+
zF#FuMNI^-YXk}F$M|7pvs%iKdI-tn1{Mv_+1T0JvN+t>A%o@f->V--A^KVFcDau%`
z;gt*@NuAd!>7b;&Ms2u_q=Z5wz3@<yfQ3my36d&nYvsaP#<K#qJR^5ptDKZqKx1ng
z>$G$mHPWI6B_#~y^NoxO+S@jgwihBP=b<FYwH#{}*pL7_$C{tno?R$}`140Vtat@B
z7C*{c^)St%WM<O}F?+tgk%>1ywC+ZjT>MjD84<iri5{h&*{TX4qJdUMR9fd$iR$Yf
zrV_#Hh*|k-7w<X&xS7>%Hng1!p^bk8w9Kj&Ec5#qm5K1)F~&$LnbRU*faV_Wu(oMv
ztk!VI-^XdP#VJZZrwE$}Anqek7W)Uhs`Bc7#zQGeW=1iOF%Fg%kTa{tZO@JtLVWTO
z5Gz)b6{|pcxQQ`DpiKB!#DGvQr`eb=wXK#9`3@P}6);CknzWM(zk+OFaX!~C;Hx;)
z>)@DAcrF9KJeOS~_rr5psZ3n)TvjU6H<x)sJwvu^1|RN?_wt(=mqeXR+k_UCX^Z(P
z4#tkdjAr=Pu7%N6G-tqAR}^}%rnP37@=^=qOVKlvCxvdA9Q_T+<meA~6s(QI9iqQ(
znQ~_<qq#`R<U~lTI3vmz0lt#S5g;1Se9<XWP8e!*78@1PbqZ;YLW(;=dQ>4@m#IR^
zk20Mx+y@FFfGvdW+8Tq!FACw03Sr=SrV@9A@Cn?3O5D-DUX}Ig<f1o3jabhFTCgp>
zuxbkIvfeiBS|HDRL3lz;WQcgeZqf5x2TbhA>p2*hA@2?~s*6Qvf-KOC^-Rxdg#dR%
z&(8Hudfrm>Sg>cju!^3Gc6uz3ue=~k&%Z5tP-)RKx-;Yxyn#nCXakR8`3+1D?npj0
za0mI|j_8Tq;H0O~29}Qn+uIAP=oz}fCLarAf)|A8d6gmJ3A;rP2MkU{^GEEfH#kRo
z<pve8JK#BDsFG=m7+R8LaKvzU1Fl+T$`(Bku{R@iRuMzBOck-O>0!Jqj)N!)8xXN4
zilgX)PMChWL4^zFfdSzH^q<3p?Y)e>;@^OwNd1Qm$}6MfIXXy&OtNwvLf@#O^`aX=
zfh}BMiX7nrTJuDRk|zh0U-!X63uO;_SL8OZlgqpbVNke!r?2rGUQIz)F{1fKMFC1$
zE8zTzpMstnm8T5bsG@{^52XZHm=css3Cd5OHR@3>Oi9y?K1#A_4e<2_wFWp34rmSV
z5tN1YwXmpv$%rW;(IG^44)i~7JTKnd=nMZ50x_NZ7R$DcvVDJ}kwD3d<8vhO@XkdL
zyJbO$w8)Sfc?DprL07yu#&EI6tmbf4>@mSNd(1H6n?2?ibj2R?3m~TLEci!n^smc=
zfkt<q$Gkkycw74qk*SWk{<_h>0D!yfhhy>Ql2At*FuxL`YG<g(CV6Bq;-(0yjnOK|
ziLV>gwYqf2yY&?|$;@?u)%l)J6ygDSOX+?Ud51gmjX~rqqZb-wv`uVj6*jS@l-<Ox
zQk$gkj#GG(e0axgBIDH-`Vo)Y#2!<gO#<Tj1{VKbAD5vpqY2p{FtZIhnP3~NJHi;K
zy~8Nwo$mts`7oSPy<PG5c50KPL^ED+^m1y!{NaG1e6x((VT6dF%@3x@frQiK6*jX&
z!Y#wczk{vnnwy=j0F|68Z|Q|)=hX#wa9*h71pD)wo%sT9qj8Q#uQ(gc|1XW!I2vtp
zHahTNBhJcy;B6#1o$e4aJFXvLTfTI9@FplIJFXj>aTUBtb{dDJP7yq|9M?}9*>UA=
z8D~`1#P^$h3!dTP)@F5@Awb?;U_^OJbSzfnu`O(YP)eWk(!#k~Ei%e)QSJjJJFo_-
zjushOeVOkuYRRPBfI3wg0*~E^F?9|n1`O;vP_pYl$xaL<xel!iVS|GIiX>X8EjC9s
z+D6VuiyV~f&5~^7%pe4{MMvPLCC_UQr3grvB9u%KN_J)_nWEuNipZg9A^eO_Ej@<j
z<kSAztbE!@riG<?OiA@m$eaAy`7M6Gc1clO|8uZ;af|Y6DEV~MpBPe%Vo~_DkNy1|
z+rqBRR*4?jwP8Hjwf*GqF6`PM1$J#6Neb-RTv@nc*XGLdxi$_4gI-2N=ZyoCUp6j?
zYFV~8uu_(65$etTeftWcv4&h7>#78lmRF0(lCRD%Zi~)Y95-~x;<(|tEE(O$jM1{#
z^hRc}>2=6b(ciSJ2cy5KS!zo;iyV*97Wk(QmFdTk=U%N4uT+TN0xASZxTAn%ze2n+
zOGSY1W;q?f=`8k>048tNHcQ@l4NUx?5Z+P<|56BXM+l2;WlC>Z2*b8I5tiG^2mx#%
z>^~dxLhG%}dW)^hdUv1zg}5Vx0~Nv+TV;9*m>IwILDolaRj%!I)eyJr+CKQuC?%F`
z#bNU9vcXxL1@ii60I>hq<bw~X6A(omT10i42cnKEqK+t{&M8>j5m8qaQAaGI?*0u?
z-zlOrT}EzI(-WTf=+a8^V;M0Q5v-Rk01#a`x?*d>q@i1jG@eeJ+Cw=Y97>=z&Y7gc
zn<}DnfU{!^%d$Df#-!ft7)QT}tHxRKUki;&t{75L71349QW0JAMMfWOqUwpye4Sc^
zHQBf~ISGW9sF?&laq~JbAv}R@vvaJl#CS!+DuYN|M<=~jzp0!fN_LKWRb6}+EZ}y%
zsiM1mM2#)FW9l4^5v}Qvm-eBpHJ)MlSxFA}AU3#atGEnc+A@3><dT=W{wV0_43_q*
z4GYk-=R?V!59Oz6Mmu7NJfBzvhA5zv=#2u(exDfqMdi0tOk43S#WhOKJ~w$wWuF_q
z<s>ckt%q?A3`_<}CIe;b3r4h7QD*K(=vo0C+Nt>c0z#DW78Ro{Do`>Nvn(o-3sI5s
zP%40dsX%%C2h5p3xXNgtjaEb?79!%-DrE2vT14bpM4%)E5N9nS-Y-PNM-L?e82F^$
z4GRPASpjxtA{G9d_3-CHX#aQ=w0r=s#5OfXK+C+MWQn8PxW;IQPpPoPcNb!I{90p*
zXueI2dy{Qy+)*;KJrqu@n>?3?iJNzAy=vKO+r!2lSeW5a7G=2iGd#^g{o>!Ce)&;Q
zGt*1_sF`VW!Azr!+F(4bHIYm5jHd!{CXTwPN!m_xyhwxT(wgFRSP4z=Nw}vs4&Wlx
zHk)JG<LMTB^K|<znIliP7l}-sZZB?gPPg+m8NGbdZO~?8o4B*hKivl1MnjrZWxbEh
zT66}YiR{0{h!gi2DAwhzhhw_8O@6t>SfZ82=~Haf(XsuI?U-=`YYNwPbsDRVzba}w
zO-x!denRJ)@Bq_*_KX6dmzScp^9-u>r$;aQTzbFlJl_GH{5MeZVXT>c)GsU4ctZnp
z5NbRi)aicIFI%X$J5g^{r~z-G=BdHSBd;|6v)$;6U37HNTE4v#$s_N4^YM0`H?>>7
z&hf;zir|yEg_>v|%j@sMuexONhj23=D_WnFci)2$Nem7IQS|)5K6#GAA!=X%zWV2k
zy3Uc|8S0yDwi!y>4vpX$s^1P=Y1`#XIYw32JsNK{L*3k_W~h&IjPcq)>NiTpuMQ|C
z|N6-2B0Fp`N(CY`d>+X|BN6L7s^@TXJn$)XNZxJi(C~%}wd75Lc{`NRqU3;iy{h9)
zg0(x;6t$7au}x7-o@0taYqlViY(XgV_8N@^N}exLb|_E%`VKW;ypn4S(h%wT$hcsU
zfs)Di!A8byG@>aj7szQ!yZcabfQ89H$>gA9a!@ikAN$E+gH8gYWYFW$jtqLt4z&{*
zvy(G8LD4%|exqgbC8JDk#6hE^COYrrn7z{>q^RR}s;$VbJLSehMh_fhnRwZV2_8*i
zSEp*9k=d7xnnrsdLcsd&L8F44cF<_$X<FAMCfG1dwJ=TEDO=?M(<BEbN@$E@Oj>)H
za1Bm%$Q-S-y`MHzTUoxHj8D8o6G%;$jSBF^>w@PYW%_W(P0N)i-C#!rA+w{(B_Xq;
z+6|hOquRaG>8LIpwK=Ni@{JE<%0Jb4fS@xZF}sthA`cwHUgG7Q<jG=P-g@->`A*sI
zxUoQ%yoy~;a#7#!WIyzn%>M?~hdc5VkJFv9zVCM`CltYt9Ek~JOR~R4sPsKchxbgs
z-O1s+)=nXy4&vUH*JtC9D&voPoAD3v<3}}}J%H?~OCSD(Ie1~6u%kUWBkfyj2<Y8*
zCqL|vjusd*wG4%0!VaWNy$)%`+sYxmtq8y^d!x?p7*A+<ij0V=PtiHr8um7ntH3*%
zO!Nvx^fd)dF3F4K^HxR)u+Nlxb3y#7mA6+RL%vl$*xQ6w5ZEfh<9O!^0s!pAs@R(_
z8Bf`su=tQn1XgyAUbIX}H+tS$PKeN+kd8FImz<$COtyu?1bY1U<j8VA7<~NJOWslk
z3OaJ=7!7u`CwAH#?G@5!cC_2Fadl;<eD@q2?dPPk%F&)ec9D)_RR0LOXgP%6?`VgK
zo!Kf)a+)jH!=3;lrOUh$pm<pOLbYQzdnH@BS(NPGepPksW`D|7ZuWN~#^z?3IER}>
zYxZj>*{`9bcvzrhzxFu@qk#C+Y~^M-Ag-6A!n0aAiUgD#5Vy-wAz$kp<z9nvPwusS
z&cnz61||a~lR+2}5et+|Mh*06k-_fuJQyVRdIIE=d(F>Q?sXp8(Ls+C^a$Y{&8CAM
zxhpPFUTR$qyVs9CM|is_N4eMaIkM4ZoWeoLY2KqGbmd>ySY4*)$bVio62wW>yw5)&
zop-F}r*q`te;Ta>N_%s1s>l7!M_n<7if?Vrf3TY0&XJw2BF;i-Z%)aW8@}eq#Dud`
zcG-xNH~>TZr{r*=##RGKutSDMu|qy(xlN@??2s`m?2v<LSlA)g-GwWT9P94#IpihR
zao)t6qZ#&vu}XB<<qsM~+g-BRzl?m*mmkJPwgnC=Gt-AIq4tiK@MGjFUl=j+{$L|S
zuK5z#kTJVBd6Bq_lNZx>aq<Fp@Xh7t`jB-?r1yOjmi7PnG5+&J52zv%cd4|?s$I@3
z$?{zsH3A8RcEfkcBHthvmbXjhmq*N`I(koabbvb&mvD#N>;Vhm?Lr7|D1-pE5OS>O
zU{$?IhO=DFwB1f>p4iQ4gkU?kOb#+jiI%%;zT;UEKKqVFyK(jGE*W<V9>*(0C_~&X
z<vTXsGWLk(yJg5Ov%fm3y!c;61v*dC6kX8<QIFk9|GNPbM!XNkhF%!E^PQ0*#sG#k
zh!S@zt3}CHo4i|D?W?<$(|DbzusIE;%HcH7lC2dbTPsTa4ib7O*;+@SC$iR|5D2a1
zKf7bh7W=L4_gLMd<nBMPx_=kI6q7B-JvoiD4<!Q_m<*Im2FmY#G`a|sM20j&%m|g-
z1tIJ<27^U1n{H@HZlm*V<u*$0QDQ5xhsD-uH=hsN|C2FXRNmuDq>37Ql-H=bN3QtU
z=qpfWmqb)X!d6Zra*yhu#2&WGPW~En#de92N-kx@6!R&#yASC^NqMw!fI-Z&X)Y(`
z*);ouBxRcYf!o?1vfke*o+j7-3cGZJj%ckGzq~VYkDTzEF;$@Cmv`#^ZnUQxK4H1;
zcjFb2zK7o+7aKq$R6l(WbX&bYE`jF{W1-l$$8YB@NitFUNVyOby)vHuANasi3=~_a
zzVx5SRb1Y~mi_4-w(M`w57LsjgJp}~P&YjW9}c09s$susNmY|R%hX5KxMw`68B(iZ
z)+AW6w@>!aN7aJu6v(?}%#y;rR7OOajbjQ(IBYtN_u`6fy)RwUwfCj#Tw*~@!)bfi
zlsxwbHxkYFs&}rt52-HN@0IIHm``dQiJ)-Low;=o-hq}<azZ1#$Ix@HdhwdO;TNw9
z_IL&)lwGcw&l4Vg<9aw~u)1lwSJr>REF-sS=5(ZWm`VCBR6k+%7fttiU&nq9*J@;5
z4=@L7c<;Na*-R|hOQ#^RTnh-FlKkqu9{MU|3etU%X59dADxcKN+F}P-fJ2c3b+c9Q
zYJdOuuvtyBg8JUfTss<iMXX8aQ9M%Wl}}gf`SXE_)C&}0_c30+Z<w8Z<h3)+c&x67
zyr2sfK9wy<5@yZirdiChZ$k^0w+gQ3hNAeKjpBkJv%2`5DSjsS24PWS^0AHBk1gbk
zK@nRl*Gp_LT`{r2xjtg)HMrn38evOGNkzi>Ex2;NmgRjd%UdmB61)=;S<LL@vyYDD
z%n+GX%uEywa@k0bx=4ryHj0NE<a!MyxE|1{?oxY6O*7ldYawQ7X}Zk1_zD<WsIM*f
z!Q9<*$#hD|r7rAE3{oJpOX~zF{<t|*o1$vz<GK@a<&MYA`r2!X3R-DQAS!C&t3{EG
zOf1%DrQpE9dQvl&^rTVD5MrC{V?ABbt=B&2+G`)(aczx7?OdOI;PVZc4b5^MGLP(B
zWgfc}Z9mMdi`{Zi5J6uhIGn4DgZp6P7?MlIAu~eE0b)z8vW^e^oovh{>sW$Mc|lZG
z82rl<fJH^p1uZn!UDE8KX<w=8q&`|P*O#g_ec)_kF3hL3Y+2guNe$Ss9V(5_cLwd_
zm7oaRN4rPsT!H(%qvQ_V$8x#Pa)JE}0R?5uDx&&6*|&_@))h*iN*lF({+BW}I|ikV
zP4P&XPApxqHpcE#+6Zb`rw*4j2m45aPW2MKEYiB~qwi8hOIQuQ#TR0hkk6GfgJqlY
zF#8wwu|FQV&vWfhyw!#~cum}q*L;oZ$_+)A{P7dff1vHVB}0MzvR1=$CqCHK-A{6Y
zV!G2l%V~h=;0o}r>-Nbe70jq|nS{;yWKIG#Qv&E>6F?U`HWEOXJX{Q)@5;t=C50Ti
zVkzYKrNFPI)}|p-HVN&gwrrF~d`*w~njW>9dX2JQxcM9zWkMaZtGpj>zAi3-Mc=vS
z3;TRE<z%%8GhW=}>e%8JfYR#o1}-I*1ub2UhpY!@StN}@ZV?4+ALf2s-P$J;BhA__
zYU=e(`($RMISYxqkPh$zXP1Y%KJwQV-A~_)sN?#W9w}CDpaFf-s|q3H8N4c8v4pDb
zXFVx4lDt)zn-JlnPNJopR2e!la*rqegryqwtD2#*W)<^gtrc~wPJ1-l?*JHrG&t9h
zA8Ce8EDE~rmqY5B<8cxewJ~DIe$IVNVg@KtiU&|BEr}nnXB)C#&Bj>vf=NlQKZ`I-
z1N1$Wh5I?AMkAV$2kht1oH~1>Z|7=<{-*7|{c0c00nP)^a6db!ka&^}55Q%*ir+8)
zjKUX~yAn4_8=HXq?NPFSO;ghH*E<M}{Sa5JL1;pc)F40vJP5xNQXYgq=!ys74>bry
ztU+kJU*4}}uJla-Cu+lXOCGRkTk!*=ZF@x}ei-X2e!$mH<N+47XmWr9o|pq1@U%a`
zri(i=-QKuEm=$wCeMa_$1M0h<Uil6^!14t!$+!Limanr5{x<RALhVuyDA_tdS++$F
zuxu+-0i8;=Z_^dsdOx34R>svf%ZB<sm=#GZDR~FuQ=gQl`1&bRioHNZhtP5wm_x-b
z^hj%rckzjNT4NVbqcAsQz+aaAGRB-Bt^tPD7?%&IH3mv-+*n_h{rP~TgX`i)utJ}K
z`jyDCEi{-+$3g?mIl@QD5kAU`jm-9ho);RQ0TadZ1%RV?{v?Ko&U)38k-ebEyrWwC
zAd`6lWHvFM6|D~P$2Hq2h->ueg4PG+Z%xctDtQ@xLP>+ZKGWi$>Y(;Pj^}MP=!)Zc
zNQKwg!PH1;A0)!-?4k!%FkciDC@p-6u2>6S0%D4`ydE#48D;?7bZcf_(ePD-UY5<j
zagZMMlljffr*L?epOd}6L0qZs)*e*$j!3H)>^<io+xrP-kn9}~$lgDa+0Sydvh^>y
z-f8RC4zezy0qNq7gRG0ro;VL#JkIQd^lA10Ox|Z*qPl!D&TQ)S7>MaJ|AEkiKdb6!
z%-T5zLP2QKY(0sBEx+y|T+yvpJBtjTI(EX~;V;;}=(d*FRSG&E{J|l7-P)Y0#Sje*
z9(T|4S4SUGE_psZ@(GB&L1*fSy+Iec;&JG5$l;O+k#fmdZOzs`r%<|`c@-}zp)=))
z6ApRq#apg==F{fWh}pP~MkWEct&S%j%5}9j12lX}7S(FEEaean4_;!$6B-^opyAo9
zKq$~m0Sg_?HrhUV#1ii46|UH=px^UD?>?jsxn1&Mv|w&HU??F>FI8*5SXiIXy4bKv
zJ}zO=QbOJxV+FmSg<eUg16pIiJO!l|P;EO9z7teWi&Zf6=^en33cYqn$}VQI)=R-s
z{M!96A*|^~hX;GQA{fL=Nz?<i?ta+Y`cyY_5WeKW<WTEbhgo{d`3Xr64@i1AIq9Vs
zPjE(9!!l!xS3TqV<8!cHhnsVlmE3B0*4|LDdW9Y-RxP00b|Bv;k?`$W1|*6BXz}}L
zPZJ+A$m98-ICAgwy~W5p+Yw|uJlxByCF=3Rcu_ph+cdGa=@uPT({_10mGsTysRVa4
zl?=xnrjmAf@^~M!jd(Fn9VGN}Hc3IvS5TAkSTDp1g~F=b?5p%DgxH;jlR<dP-j7Bp
zgVpH=zD}8!%XVHYkZ-*pqz2+Qi!oGMGU23|!!Fb}u*)2A&V?n9s5#96%3fo@Ar&vY
zNQTQ^qwx`3y?99e+24$CO(vUD?qLuD5t_ex4KN3a7Dv?l_0<5guZRV9de?FI3``CD
z?d9&kff;Nv?2WQyPYp6}iLrp98En)MHG`q#Zy3IIL`_~ZaZi)iEb8Ajc`-eX$!pXR
ze#<!BY6wI)ZO}n%v+lPZQTZ;3d&+n1cm#xMHUuV~4N?A{VCE62JR80M(kbmW44C!6
zD!DC&ne8?4FN>k87DFhRq2DYzelA4E9}lGi7~UCS(yzc|&W4Hcjsu?YS&CMV2ZZ4>
zaQ=$$qfRy}AAOkIuCm<lQC~k2g}sB;$@Z*6A;euC0kM)Fu(ABE9?5+>5i53q2Q0wL
z4gpq`Bi!and{B((;60ZaM`h&2z)<ZdM>X_0C~dioBu^odRy>rX8Ati$t{pZc)CYY?
z;E3(np+boB9|5uA71)?pl$Xb1g^iL~oemcKx>8jh8E1Znslm_ck4KgMqvTJDRhwW|
z6~*$E5d`Hs2i2ATutEKi85NZ+1i;G15M$j(7ed(R5fCZ{fr%MJxpb1bPoQK5e<;M@
zxyj~vF*;uv_sD$39F_Dbfh3EJ8HLDr?V)6h%x5ECVIcrQ=4-2Uzqt^?w;lnZ;tQCV
zFO;vnWO@Wj=4&`uum&!hP7V!$Ia3JS{fG*IyBtv|?eFtdlzt06!pC(!!YS=#)69|L
zUOs;?G2ocWW<PdJj-HN14@wSyJCj!o?;MKo_s@KV{8m1PzqT55!{INSYBcTp53)x+
zD*T0G<6O2Rhr(f3qhq+@u&dEAXZXAI6(k!G{&F%WVusmHbO$xQ1%Kyb>cggIlabNC
z^or?P{wnf4gBT>XcxRxsBCdhBREvJcL!Lw0A5(M45Tb(TkXPtx$T8V)rdicRO|3bk
z<1v2<s3SdAapb^bYE`*_nlVGEbj1v%7GfwV$?V``=-)}^II+pjQ06hYHrY&<XVxLk
zqNp*`-_5RLYEk*lF%BY5ff)SY&8NpW62Kir0$<|}k-({AYEk(cdZ!<g@J``B9pe}W
zz%&CNJH~;$vkPA!FDf19lfL#CUdC-PtH}6HqL`B~mSct`$GyZn%dyRIT<tw3FQu53
zUAu@AH5ae3$#IQ?L5|0JP&1ZePr70`_B`%XjLLIuim_@gvhAaf+Z1EuaithZluw&E
z&+ILxb9Jn1Bv4x8Hto2qFyDMhEI!TxO+C&6U2|NXs}dNa9cO`VJI(@4MfcYNnu|P?
z?X`H%kVcVSp=wywZ9%F%u3BIjG=g9enBqxvp{{tfeuLZl21NUkAS<&(gYA^bgaQ-4
z@G<nbQq5OL4lL536S#Wixa_bHsyU5#Q6e3FT!l9q7Mk<01k2okScXp&KT%z;q0)*F
zLn+!5EOtVjDX6TVcrhFSwD1Oy2(Q^w7n`$jCXuo5@#2^h$}ys(1D7~<#C3eUxYG$0
z`E)1JY>^L>>WF;MnwRY;*@vM_TWa<ZDA|Wa0~7hI2*A;@J?w;9w$HIqI!jSn;RO4w
zl4(c?$`ibF&rndjbYFQwex7Fb5GdJqRiIYtX9|{Coy<DHzROmF?$~!hK;*lEhuc(z
z2Ba(o1R(U0hM~kOtLTSx#VYzC5ZjmT#iaQRnL4)4y2{29Io(~-9H!kQGSzbNE6BlD
znZ3ent^KAdVfn?sB9fJZ`4yMSdpRDm)m;TeST~3KL3FT+gr3CJA1CCOEAgWO)YMXu
zFHZ0Rx#cP|SyVWwKB#-$UtR8`S|EQxkG%aV$JT%_GPf~w#oWf=9TRZt%~=v6wLlKe
zFkARM+|&#+PILukugea81{f6j)Xr*)ByP3YN(^9_SeL)r-T$O4SdI96(n&VYaVOPr
zQuj&rS`I*#M7xtp5`&0Fmc&xJ8gx>YUu%ZD`cucsSlXZT`|<WZdZ<J8Kbh2w*<DXp
z%<g){E-_|pvd-Eg8>};zi){R0n|G6S$4U9uI&+#p$(yW4GR<yu!_!yO_2vxm#Ywfv
z`t3>fD_@+1!%&;7S5B&TTgDwU>&tB$%*NurO>V9$emd_#60~O&w-I|r_(h6SP$!xz
zoFJU*txUBl!BFuOFOj492`!QFfR@Ou6bL04DxOj~pdR$dO5wzHK-m87W;0xLJ;jp;
zn$hI(<S8BoN1r?lpPi&L4AtaYd1g`HSFnqp@{Y-?bVaw`4JW$x?l#;bCe;{ye$uz$
zBwjz|-;jOdl-hB^SDA@#>^O-9r##n(G!-jPsqH52fw!BApW^MNwOh?0go8I@-$Hj*
z7fEQ)NN*#jy=e{;xZzO>ddr-EAFS~THRw3O!yK@KV~&>9x0z$LD@tONcetd4dYhk+
zQ1O6-`iBA`p<Y7A^s&a^)4VDVC-UqcW%lw<A7u_Y%_3GvM77hbBS63_?3mNGY=H&R
z#tXvPhwVGf3L>7t;)xO(rweMFyllY9pFc%MQ`(C0r)hm((fxlBH2Sn!c{`f(Fz21}
z4RbM3{FJ<!joihe(=s^6?BP1^7xK|lYGO*uF<%xdaE@)4xkfBItv++I{j>^3-#iT=
zGi5yeyt><*DUP9QT5#u`R#Oj^6q8>>Tgn!H0(oM=UE?#fwNE>X=$@t>)-uv8l5E~-
zj>qp<je(5gaeOR=k=;A37B06@k41NlfPzOus^&9b<M|Bb^<3;eqU8DPAV{S7?9J0^
zKHGwOI=v6}IXFIQ>6T)hbHgBjKWlrNxL_aDo=9OI)V@GXFi=(APW)xRImV~A3lEqR
z#oz++w6UUp0sS^&w1h9&C0;CG|2e6E!<$(J953RI;>D%7L%cYtK>bq4#sd1KkpEjH
z))lahqRI6qjapg(yMg{7(wa2J7O;NwEpY0`zC5#@I9niZ=9$mA#uB))^JmdD<z=QF
zF{g^p3RGSOzl2zWh;K*n%7p^8zwmv5wQ`}xVeYZGrC+Wans1I40cVu5+%Hhdf|8RN
zWzVSbEqz8QOZhX-aXm}IeLz{zn&T9dJgz8v9>-7pq2zJ>6WD27Zvl?tlp7E`{gzVC
zGm66Q=mivhQ^2PT_nk01Y9jHBT2&1{BO9MW%!866lW&wLXj5Sbh~y>P8IDYBHRymN
z6NrKp=UHl`=4gn46{pS_r8sqnLsp!0x?;si2V#m$pg6n(`?+H-ndset&GI$f>T9~y
zYKlqBn)lv4nX8>K*9-B_Gr61IH3I_cX$#TOJ^ERTA3XSXoBj>QR;D|F{=J3H+*$N5
zhp_HEBQJhvRxMAB=5d303_Onk=K)BDp2e(R`5ig#ta)Elc}HrWndRlYb7m!a*y=O0
zj*OUw7qfmpXa3}?F7h!~=hpeyT&smJF_)9k-S70zi{sZ%6pkm)n<El7%tj6U9;<su
z3jWd0e!4%JgMah`jQDLm{G;F8b8GYQkA4Quok#!ZSHj#aQ}K^}|H-|L{?Sj?D7NXB
zJMj5r{ImKL_?B|mXJ$lD<#$LYQrmg5!>ZFy9E8ci7tEk`-k<uwZ|l^fX7ocG?zM~X
zkA7sq-GzQifW9j4o=H-r?@BAF{zzBF)9}yR5e|J(M}gFloX}jouv2-a_b2A40jUf+
z3ZrK9MOb&Ubo`?)%DJDW?^e;Lu-sKL@sGY);r?+W{?SX|?yxNUqqiR2-)zG_dMCzx
z0tZOlbo|-fau@#5VMaB~w1MiLMgOY2^OzK$ndJmxCA$#XP~g`_w)oTxn#tR(ims*9
zh7NVPQ|R;&9dmM@qknXK$Xyf12HbR{#eJXt(IF0ZC;CSx8{B8<A8qKn8`6$0?JT>C
z(mo>XgSzKn`^HUsPVNDeD5gBJyFD#aJGY?!8T5~q!B}wNA1%b(R}s*<Dcp9qBi*HN
z6S|9kJLu|N`sbDWyC<1DOFMg4BM3{>pAj6zNbWrNdN)m@?!GWycmIOi{hyhAwEqXu
CW^GLX

delta 29662
zcma)Fd3;XC`gbNd=TKg|pcPw5?6su!eW{(qQdI4fzEy<ka;rrVA`yufLu?5`YY!q~
zk65Z&tu9)MqTB6NwY2VSwc6kJd7krbX+J;m$2(`vnR&K(wwXC+^39KxlJ-=ZG257}
zW{1oUU2J*`m9^NcR^1q)bE=!qX3vN)Cn%$bzFEWUp_8IaTj#Dddu0Ds(|q9(J?Ev+
zI=X&4bEG;tOD}F`u2v^!>D$wda-NCvTB)<MJlp0yZhWGzHZsFKH|Nz;AI|bz9o|e`
znx&KL*iqE!#SZ2o>SS~@Yr1aEDo|it#qP$q$K1zedD>NMr(f-8j#kHJ>GT0cEnTpa
zInF4oGn)b0jO7)TJzH<<WWM9FXQNw%aUtWv-Q{QN2B)kr9ev)cYt*2o74?<&c0WRu
z+{b)WRhzA2J*sYSAJ2%nrIebjjZSui{_91vls?kgtggDu)+73wW%M7N&9<)cghXfy
zovlk;Q?>Mu6U<kP7(r6MxC+yix|+|cUb8*7Hw-tPlly6#jIctZsBgG?*lbU3-7wv{
zo7rEzJlm6!+}L<sS`}|*gsE3&>v^$ePb!UzMkCiS!59K*yfj<iUJ_bUjhgM5*}7)n
zli{;<<*$soz^beCFdMl-gJdzHhuJi28*aH*n)umHSF7Yo-!5!4CDFFqWpvPWdYY4b
za(=g`nPj|6l(C!(9&=#olwn3~ePp6pM<3~EntFOqv$(c;o3X}M%!VhqYMA<Rwx?a+
z2;&CdS@bI3Fv>(2ztfE<Jk}$ISnUm$p4k@Qi=S$w>mN|HedAMTj^}o{ngr$SGqu#`
zvpuoZ>btxIK!)c62e=6X(L07ipxyy)G)D$Fs1FbD;lKfo>TA|k1Ln{Gk8qtM24!q>
zow5C`uQ|#XF7WHeg_PA3zqD)Q<GrAC83K%N8e@&A(mJ`cDqCps93F8{oBp9)Q-9Ro
zeAbxnKr0klR>jTHXS*9^s5D%5e`Ae2tK7&at5(j@w;P5GsF4mB?gALCd2WNoYyj02
zUA20vK!K^_YLB}D)c}N<15{~(lo?}GrSk9qvmuo+D^(*k3(!b)CZpYVs-~I<j8BDh
zHO>c6dk&Bx+X-`6KOY-pwpTyQVg39`T3y)~QdV7`qu(E7Hm8#Ha{~3M*xdpV-#bXo
z&0+lvcmi})cB{JZCY5`bQLbD^m1HC{pEt{?-DuIms2H}J*kd)V5{D~R(<*VnYWnry
z0CzCuS@R{;JWd-~Msw9Tj(ouoU2LT3(hG;cXT`*MVoEepJ>y6p)v!3v%=TP^GO8C*
zt3ow>^Xt%-YI>Yb`B}yKbm;XsRzf_!THCB`#IX`K233xi=@RGnGU}atoipM@0fXAJ
z0yY4xfgYv=Q(JJc`=t;td`b`RYli9XN5I*1AzY$ejpD@F3>|51S0Bge5yOl|<Y@Z&
zST#d20v~Flzd25QAE#%oFd7y5h5&@SK`86r>!ZzQ)gK_Nct|7lYn<pF%Gib>b@i=p
zR0UOHuFh;=G%||n62r|(`bgu@W;II91z7<Kc#6j5Zwd%7tbiz40Z~E$!}LqfnH2~Z
zYvElCBx&I{XiQpo6{3I^s_t`z-Y!4|dauN>2JRbcwo!xUk_M{bD4uVmhRoID#+gm1
zB;_k|MI=PZH;760v~5{fb(zch7w`~>NdMG_D9JxIqJ9!9ARJOaBSJSAY*q@3AZ}Uz
zJaonS=b0O<f79INn?5%g@q)QfZ2>*dzanoF0}MCuMLpsTv#*XGZw_+#Z@c%+4N#g>
zbAvR_I8Hn~uA{rD!oht=ag233c7)knmz)5*{$Z{JrNI--XI%RTtLRC_Tz^nfchHFR
zWZ6XXWp#5d1tew96H$lGV^J5F=M6?r8}nGw6;MFZ<>zr2GRo_e=gfx1!rcX^L&feC
zhsw;;Dc#Ll`u1~Xjo>H7Jc&a$=aQVGiulAqd?O4sD+4GZ-e|gF@kY-J7Vpj}<}*I=
zHhsw)q@JHA<~;_~CNx+&)turQL*&Q^zA`UBq;a4v(1_ofCw3Urp6zfrfcot4;>%`b
zV}m|B0xJ971+%2C{)$=6^@{LJnaId_BG?(Pm=o3Zc_P^E304hI)67JJE%R8u#~k_Q
zQrB?zK}Wu?A)<dO0zNMSJ~vO_d(G@*obw9!pdcdwe+-GhPK;cyhy$J-5)m6)s9#;Z
zBSG1&kwL=Xa9<?eD`*#8v7lY?!Gf+Z%^d0z^oD8X6c|D5Bqyz^8m|YuVO}s=(XEOc
z)SJa~Q18xnD5&EG1@%GFB)Syck-+`}-9p53smS2SJ~p15s?kihn`~C{%y_bhdNQ6J
zYgLfx3}{rm4Cs%)gcjD()r_jf5&;)o+pM9l95So;d~`~@3~x|x9^UZyfZ_dVrdd^G
zfi_CyBHuEb7l|TtVl$O=?gX>8UiKDZ{UJhBS0DMtuyy@e=5uO45KvhEgdRi{`iQ!P
zyFsBpqW_!wc%qxz>YI3Rswg?2-xqN88yU8`2kBEl|BJ>Wz@KJO{crvh5Mn<LEn~!s
zJ4Kb_IZF1VR{@MP<Rg+}jnK#39{?k{(k93+$n{6fXF}hPXZy~aYxY*1=X;DE<@BTT
z%!;bVe75qg^Yz4eW@m+xgZcX+74oN@=8Lb6n$ONO;0aK%Glgi_nO34sVv3LpNAr^N
zC7PE66=Lqw>58>*IsiLKXY_n?N?4+=%>rMW1=2<zSY;N;4o@)48*0OR9oxljZmiW$
zzhU;$xrydfl?Aflc3o@H(V<}Xe4X-_RZ1^f0Jcug=iq;GzHZPzw3f=7&zct0nssFr
z;5e?Jpq|mrELb6%Na28dovx@Fx7htMB6MN}!u_bemt+=p?Iy&cMQea~pWVi_hHi;8
zKnrX!T(=!+hlkxGI2>4hrz;l4?|wE9sYenpB(*)0j+n|$(A!p<uTa^xp6aY8tTCUW
z3eSJ8tT9)q776-lgjrv8NZ=HvMFJA#2v6}pLsgRm{nIkLfnM`2bb3O%`J@_{z>;${
zN$^oNAVD{1pi1e#(#<E-a|t5F;O8vG`D@KtYFYwI@zn%Qq2>c4QYh4nGLeR$e>Fie
zs7(pvd?)EG>&<YrA%W8;G^8B<r376**PN_A6kw+X*d+mm8s%fx6ZGwVAyGzxF3~rn
z1&XWhhfY!l6LgiKR+#!t;5lu}CVJcEmN#mu>WTX7_o2;{^R$ugY05FPg=&}RNx2wJ
z4;@lwz7$$NSRSkg4HI-sq)}a;IblB1a-8L!LK)dOh)q;sWTI1bRDmB+2HpoQVE{>2
zR3QosU}or9b*qOO3rf5*;n+l)39BiIB=2y~t$B6T#6+G7zmdpO;UbJ-lVJ7KyHi*H
zce6Q|VDQ9vA@DmWMkiuo+)aP71<`SIqA13|t#Id?8F+KGF_AK1R)ada_*S!+9=^?N
z<=RLfL_2d5iD%eT18qhS%Z1fA48S(bh~7)o6}Ou)MRNQI*Xt4s%?h4d!-{5SY&S0`
z^+}>H39UiOCRhrJ1U^dCGtL=hvZHpHkA$de+_Yg)_f>&M?&YII3YYq{2WckHj(?_S
z;b;PfRbDsAHpeS#0na`P>k&&~MKt>;T5tj8JR`@2CHAX)ZH7m;%{F87#J%Pty5(Zb
zLW^BAs=FK{g@Gh=f%veW6WNCaJh_!9i3$j1AGSVFE@ZV$!&(EC7;GE5VuNi1faJR%
za-J|hz0VxzlmCT%ST-5R#PY&KzXg=7kZhXiG6&2##zcA6wtZRk!UAzgV;AWA2h7n1
zvLo>5p+~b8aFku*+^NEMD9o<oJ4-__IYgV7ms%QG(x&*SD2|F1NqrIvPI|5RsPQAF
zOj+#HPnscSF3`q4Rm)hwA^XEXSei`8xJ0)q>fz5C6$n0IydK!fQzfjF{s~Ww-{^J>
z8tK>*A+?PKV%a5=;3lGsB=!=Olh{iXO=82YhZ-hYMU%*|o2#}-Y}x-Wxh<2}dpH1|
z@d03KAD1N7?mT_j_mr)Db`o1VusP(hwfDmyI-36+gip&uYmP(L*F6L=Ym#*C$&h+Q
z0zt6D=)J(_FxYw)UNFn*)9;#v3W~?bOVS}H&CagpsHd1l%mPUyXPz{3_2LYuKQ9^~
zm8_}L-i5O|1-g-OsH;g5$uB3dVSs4kEfuXlK7~;J2iou?4uYTsgkO`$%hb^;-ZLv1
zCG^!j$YD6?D7sLRj#3Mu!U0J~9)L>HLGI1FiU2T^PMfu`$mWNDduLCZZH(pt_nIu!
zSBr$!RuKzz=5|%9LCc4PPPXg*F0?=aJz}<1+2|7hQqWY@FLqT$^q%{nrHoMlPlpF1
ztTE;x5$f<WVCVG!NWdfW)Ffw~nxyxhF(XNWGDU@C`yim)Nz&~;G!GaXxi2So>lTWz
zQPPZg=}4HufdJ4s`G`F9P(-d<==rEtZR67bKtM3FjP<zw@T^(Q_%`6dH9v;i!$WIF
zJ|qI+7*Kg;j`Hh|&3+0cbDRct9F8+rVp4t+x<r%o%a9aJ(!WfSrJ`Co_AvYdJL||~
z*2xP=I{j04g67G{EX(LZpF#WDNHbo`Y?-WweTL;el$>5(AXTo|y&&9C(`3OCnar*^
z;0f??dI>vV*BldQb&_5}?|88&f&{=h)npJPE_yNm2fFA<pNosW8m?;VyPum+Bd-7>
zvUWT-+3TX~=vQAgU7r2xn!Dx_a}pz$C;O+C#@oUfEhPWHu4{d=%t?aau)BCG`ETwb
zLcN=;voF9$EGM+$BW5Q{E;&1h5{^n2h*4(wOS<By^rfF=WYkZ%qJk1VbPM;S^?Eey
z-@dLt_`3e!bVYKR{J0sWswL=s7tJlkufpq&Qg$hIH(94%GT)$*v(e#~k&~dp+35F|
z%|BGl6wWYJ^%Py@ikYRFrbtFvJ;f)<CMlAaH@s?IQN2<qqcpnd++3L6vnd=ax}|We
zaHED;(Je)Xd~LQ>(^5Q{PxsdMzO^Ft{;$o->eUnu3}{Wc+*2t!>Kn6*N*9Q$1mbpq
zxJn=%6o{)*cxtLXOwpO&n*UM@K`iB!rv)GyI{;UH2Y^2dz?%%vFm#Fc&5AVTy~!|*
zVtm6xQ{I~b*Qi3b0;jxQ1mTOAV)S$ng#KXmF**qZS}bq3h$DVq9}?W4@H@hfq}?KY
z_Fc?=rudN5(3k%Uad?qT6eLbh#2C=a<e?{r_Z4(2+;gOSIN=-dMr2Tvfj?q}Gh3R}
zzY;}F9AZOmm;*4)BzQWym08vhVlVR@lF0i)?2mqU?>of)Nw-)c`G~zI#7a+9&ch>)
zUL4#bJQCcUr%}GAv0X4@nRp9Y+TOzv9xWUq&D-VxHQ2-RlmQ;jK%PfG%u@z<bV@@r
z(hw-9kr-9HM^{lHlYG*f<KZDfSDJ^c^EGCIG97}Pr-yw{nV{HTK+p$55L!3{*>|yq
z^_>uOO$ho$2tti;sKw0mHHV<mi-QR&zL*Je8rSnRW`bHS773yA%-bQ6hVLl|s;LGp
zX5pZ#Lkp)r!KTRR&#>RjuIiP=p7b~S=&!!9YWbuwWwD+SZbYaA0EP%rof&6EsO9-+
z#QpS3Dnf1bHe<&23pL(Or~cll#8>EaDX7zRU#F`#Ln72~fe*0~Q{q1eB7oSS7PerD
zx3G#EW$0c-ed|W(fB>?=adkc8&(MOdAa>dJR!$M$J1O2OQ=&N>lVoU5F2Pmv6g}fF
z>^wFhe<d!sYKo+3SN<|*8Z87HC2F2wku~(BhE{c*df6;pP#QPI`V>+&z3T_>Y^Eo`
zVm1S>$4T3L!-_Rt5GYq_VV7_063Hb{Vxg$6{y|waj2Y4(x(6D(v4j)1YHtyJ0f`&a
zORGh_yh$5Ca7KfY<2%axAy#Wb!SQ`Gh@<#EVu`+LhE~@{L#>yMy#ciBc4$FKi&pxX
z8{mS8cn@7D&sze}$n&aw_&{O+gNZ@O#GpKBS-llXCMGi<F{^CrH5Iy4ve^PlMJOnV
z5LJFD??$MwrNLx8w)8<V0R$!kC6j?Nqmb1{p=2`d=Og3IN31v%?U2#KAp<3n>biP*
zVe3&f#-U|oK3c{;kd_`xDZx{3H~;_@$z5la<kS=L0Ze`ffWjOgF>@%dxU9YkB{SC*
zd;|{ozM|IK>bS#PuEQKkKXVrxT0YN5%f$!Mk}J&JaR2}+GZ&&|<O=BEku&v!MvfrR
zMkY#T4rS|-)<mi^bBFRV7gfqyubOL7pvGDh2&JF7-VQB2^3f9WKw27W9=Wj&06=Bt
zUUlkI^8x(VLjV-!0EwAHxjW2yL7`;k8i5aI<Ytz&($se0D|9m;dm3~LQ=7G(Tn^@h
zk~_TZ?~qBk`%rid%H4ay3@LZ-29u^$;qO2?tqOk)KyXW4m+-1^yGO0j>c5(E_XCew
zP1Nt2SA~Doy4GV>j6%t2dslL16}y*4+Wre93j}2d(A1G*##MS_ag8Nr0iyu@>9e&|
zC09UepyyN`{*hDpszLc6uN1?zob7K_4qHO5h4b2a%W%bcZM|iZ$|Kio_q5ej4-dBn
z_!7^r!>u{0^D;?1J1o=VD`C+Sj=AR2O4d;I^fJjnI{=uI%lBU<8R))B)+9B48RrV)
zmT|7|uVozQP@~X14>e?<<CaOjn7S+|Uo@bAp;l?$5J3luv7?viZdI*lbx45j6QJ)4
zP}B(M1p&HmnIs@TE(?nH2KErVK+(Yg%7HtW0}kAkUa*?$oPt)Zfc+J39$0d@Og@6T
zaR6++EFb_5Bq8(qcH`x^8n{f4iLh$9`jfaMrnOxr0q{hGHAS^tE{lB=BCT<%8Bovy
zMa*(hs$PHqrGk7p)_qXJ8m7jh4J}ZNTh10~jMFiNt-3n7pjA`NTrSSx&E*o}W)TGe
zA&w~u3UPqKP5~v`4a)tstS1RNo52`hBfA;7TteI{wGmZvgoMy6fM?^$TCUsGfuBUl
zy>|M0vGEK8J!Cw+fQ^i&`*Ja!TMnN$gwJlv*?3CVvs$SFscby;UbgBgGnI`;rRw+V
zSx+dGY&_klSH<o&jOR}W!HwlS=M8uQRBR{^EgMSPAhl&fSqe##p)4h7v7t0g#T6S$
z(^S8q(0e==>RbKEP#QF_K2kBMVk13Md9Di+d0h<$akO#L6CfP(7?vvL(YcYeOud}S
z<}o={Rw*Z>>h@7k@FclCUv3wifZkY)-KeW{vciq6R5Vo^q|I7?*WFLTY!AupeW{Y<
zzn>~8?7mb_+u{w>1;`Ey^r(^Q1Kpq|RzLN#^ttKuF;+;Qo6@J)3hslN)93f5z*A!d
zQ(kR_;A!miskVaf=y4UTiXNKZpzicyBMX)T8JVZW<-&UVjnJxU)Cy$CQ$pNc3mdjV
zEG(!GTUeLW01F#Qqr(<9YXz=Grs{4jtq9jJlDJq{w^XsPjV-PHDt?7;OF2d_Z)g>#
zJ>|F+SR`-dDc-E6TD?MyZ3TeA*f3h@t*yN(2gHz_Wr0sx2t<jssjlkG3bC=%E5yb=
zA{qj0jA;t8G4x~`L&-LV@?u-79YGXp0c5hV?JLB_*0;0P8<xIZ+lo?ZrC>)%*p0{N
zwzC3RZl$CEUjr`Xkl`yIL<yiUB`BE^l&3o&e^&Z-Eg<_VA0c@it)*B>WI}p5grGzM
z&>1PYpODe{2zma2ga8T?f|3bAdEqH*pwUYR=?-oKC6d$GN;6gqA*l`_C~2)wx9VwC
zFm?q{vm+lhSr4QpbtNwpo(=#4=#-Hd7X$8{&j<MOLjV>w0gc&2*`&KQ%79ZLdFy;^
zR_S4-t5T~(?~1LGkw@v{Q`J}{%2$0=@X*&<^`N0Iwu&>ZwhjP5<%}!FsrSkUu<t_v
z6y5-dc|)1j+ZwA-vQ`%X-GO766m6|i^Bm@8JItZ<Gq=j2B{d%{YaU3;Y+)|T0RX7X
z+zF?imk;2(4*^h^10-e+Wubo7aD|eYo9Snc1Kbuk0}5~}VCod$mZAO|>TxS1>U0Z=
z1{`%@wH$T6CjY@vr|fE6anvabU8j{+Nzc-JnVD;Vb-}2wt2DQ;p*69hs<Yakoassb
zvMjx2pjB8W543t>wV0dXJziHG0Cr+g>(vsAnhmnf8vU`>3$INJWihLHp==c2p|vO6
zKyqcoN)uX*i&?FIf5vKQ%%WR;b;4jI9A3{oeKjwtpcDE2o~!kNH>~bh;rGE`C-Ad;
z@Nt9S=lS8UTP-iRd`7q0d7>K^llNP^IL-<VbaZee54DD2$IOT0uHdls?JgFtDB=d;
zD8n~+$qsjDcQ2Ce)YSf$UK||8<9cQ{Cj)glw+rmdkxvim1fkJtpVMSWU=s?4SdRew
za1MuP<B*#%(t6gwd&VG6&p3$XzBMfJMSO=uK4Xn%<{2hU))!GHVs}!5e<F4p6YGUV
zoW9Snn9~_+m{{Wi-IB#gz@tY04s68a{#V*i^hO)MbW7{g&sp77u`~|+h0{2r4^QKa
zzHpkZQqG7pP(wzKXCPHK?uE?xZ&Fpw(pWptB{mNWhTblcM~q36+yfv$otol(%2~zp
z{jB1iH5c0x0*5ZnDuOlIm%6L8w4fP<S_zc&HhNHd&L|>R2V@lO$nrR&IFg2|cB^&#
zc;xJ@$!;X0sJU7)ivNs9j&~x>m$S$C&90!d%mYfw;lE6iwBiduL|OsE;~f6C3DzF<
zU$jAPVcgLpVz5qr2UQC0g>~$+P!3)oDwr<mg)1Ed1*8{DU{HF2-W*F&vadq<RgyJ}
zpt7&J3FzdAe@v6~qUB_35HeXt#VclQ(k0TMq{Sg@wEM~EpDux>a=PRg&pePEKw)xF
zGC2f21z9^vCZ}b(j~sTLKctE4`~qx{>-;QDHpSp!Nf^8-mI|zp;iqXlKbYaMI;ySd
zzWD(xgq!ll*!FbYX0g>+q2x)zrzHN0-3uY-+YFJClTJ<NNkYIA;N(dH#*QZmHG>=`
zyK4x5-F0OW0K4mN>5AR;w*c&Q*EC7k_^M12cpIn2Yt|0qPohwK_PuoPWT7VMP9No3
zD>H_B#H4JF6<I4@y5j2?$H&*Q`BhrW=GR~?n;&XqEp1SP`BhrWu35#b<t67J*W7b0
z8y`B50X?>sU9*}hKw|~yECGrd0ZkF0v1?_PzHV)>O|21tXzT!FiwvfoE%IM8tRd<H
zA}JupKZV|dA`L-tYOUr~>6?Nd&j|m0-$P!NPCR9mfN7i^3vIxv^pn9W>HtA2>P97L
zP&v#fOE2Ega(40%s}vR)x#Ns0pv4<W(1(`Sjdp>32({6h?nEgxpmlk?RL`B${$uw2
zTj$unb)FvFdBOkF8OlWL2(^rPdvNE2|J<1t_>HqcoqY@QK_kFE?k-G@Ub^Ci`C@CK
zuJYd9I$RZ7tCz-O)>H(y9Uu3<boO!CKgU~-8^&$H;(di;wE78eNt0u<){A2cS<glZ
zUG+P*D(fYA4PUQwr-p<XsM4IN@p?&H8?6_o))ZX>o!WJxD9EV+0DBRX>_t$rQ$xvK
z<WWE-r&e~o->Iny4tDo?acC%cwR@I>eg+!TqI-ALX~Hz;fn)#zlYx@SAjss*P%;@~
z{baB+D-8z8#e|?AIkN(wfL00Lb!2v2WcJrOza#r%z0Z-UOY3Q&12H@0Wvm%qKxg_+
z=`TnJL-Yt-*f|IO@%8M&0-gX9yD*FryRiQSc@uVFV4Gc7cVe4eSn&*8u?s7n;d5an
zmRiZajPrw~);U!(!`Xz+&{s7UPn%{qo6zX)c&sKF;;}9*v(Bqt8SJsTWw6J3HiJDD
zYGmAQ)T+=1b;>lX@=VM4yTf`lgB=#ylYe<CL!Vt?b=S?OTa`FdT`5qv3DlJ!<rm}>
z3{{~<A3v!x8Nn{=JpqZXevqYf@6}jTxg)gxBv1=%U|N3yH$wpxHF#Il7;5DW!B8t~
zU_#N=fx0mb3&<TeF!OCUF!Ox`AZo<?Z~@qMgZ@4p8x@l`{GIy=8)SztPCBAmVxv`C
zE#APJ_0z8hY$nn(+VFeZ-?VN>O$A&IJxkYvo)bdPQK9EkX^R@sb4}<u>d^DcKhSf_
zp{L+RmJF&)PuRx4(?idQo?8B<L=SK|^l+f49;7tE3qrj%1_z678zp@U>cg(Baz=n_
zYffs+u5H3bTs6<oPi(TPx|$FsNy@5bNcuK!6C(3V8zp@!xfwIM*p0r0p!kjA*x~>L
z*#=aa9ox7q)-<&ql+bEW+D36LDA}{+Y!uJ7XQOzw{X{@Oy2b<rc{cQ<H^J1$PEUe(
z+N`Q~Y_lTOHRtA6csYtZ)fv>uQ+@L=VCju4b<Yo$Jr}^U=R$ca$9hz^-eJ`;kYX)D
zm|F!V$cd%`8|`1-++hvY>ofvWefoy3>f6FAO3n*g=-5;|<Mg!Y+rb33diz0q0}2y_
zk_ke&;I`F(u&^twgqMH<iRpC58e&Wql$@qcaL7T)<jf5qXLdev;vYy3pfEWonH-c2
zez6)UluXVG`N(Oq$C^UlFpvb8oP7>CC^>n@XAC~+e3Xxz&mKq)pz!;F*8`vs2GWe*
z4_I~ad8Z%zulc~=e;DxmzFsMvneH7zfM*GyWC@^zhICXYSpwPlB(Q&<^%7PU7ywJ4
z#XF)OC|Lsi0)WT76RaOkzw;pd02G$Mcs~@p9Z+SRRYoU2t%~VC4p?=JY5s@mwR|Yv
zd>9lgg~b6-fR?3zlBIxh>LII>LdjBS3g)1eSh5?j2)<Xt&Jo}Ze7U&TqOU_{;RaTE
zuuuY%ay}ZW8sy?Q_QH@k_MRa_=Gc3I$mQ63;T>P>ZAa6G&yHX##rqamzg%mJ@iP%D
z(}$a&^ODtH7yHmEtv4RE+A6h4qVY`tbfU4bNuqIwJnKzWZW9G0qqNT4iV#ZQ1r^^U
zuXfevC#udS4ppr;v4=;ELPHPK5c}$ElGrzNQ&8+Po*`(wRfl(DV-NcQ^DAC&3E(#c
zaIye?bCZtgtRf8oj2Z{k9r*xn@dJL-2iPdim%9FNv!pASPXv(h>cS=tq(QIRoZBRU
z^e4fNs&6)-{`lwi{LW4B%`Ap<B8G~nK@35?>uml<Y#jUAa&LTkMl#X$-&Vzf>E+<{
zALy1ZFAv=WJ>cN=%w}ALZqj)lSk+wyZacy2$9E)nRXT&+`r(@;cy;~B>Oo3SRt?!K
zdHK}M622w_48j+5fWue#N7%GYMjHxWiJQe_QF3OSv01{`+RYNaHWCQ|;fqNM3Sa2S
z_JWe_1?3|jTTP5aotcG@5)VY=#p5<hNO|{TV87&GKkr~i$=L5W*l(gSMZ0~dQ?&c#
zfm8qjQ-PAHK*>~`7b?#AsmP?w`&nR*((=jZMrrv(5P-DYXrhgyR=DOb%A>Zh*d}bI
z)I59qIm{hZuPu7!=T=jrue9T@w4=A^Tc2YKA0=n!6G+_h=53EH!hF{)dfOLJ%PCIx
zR|C3F-J%oDqdUsL?zBD;>+6o>9-j-$HOjaGpm*9LOhj$r+&|z6*rD7X(^ZUt<AZ(-
z@&@dKAYS%C`$)X(gR;T1_@Hb64_v~CxESDrGA>$Y@S-AQ)k3`w1HELugA)l*t)y>_
zQWae9ljvmS;xay-q>se*T(({{?lRx}>Ba3W>|;W<vT>nCKBfd}Fs|EM#1%ZgHOR-P
zN?SR<Mq|n!Z)~B7fRnX%-pWaKhph~?zd%KeppFu#9kvS8srjJB3RE<9pi)*^B#;GN
z|CCi$7x~7TuGVb*yQ#0(Dvo6rW5w2K%6nEht-rNOs@$#KS88i`*9-7G<}@<9&xFPm
z0Qga)!6bUS{`G@ZT-_E-K}$DYOy)L{nz#9**R9g3)V9Cp-)MezqZMg*TQlA#xu$@Z
zWYYmP%)T6&8F9=uX7L{pkMV+H78&uBe@4vCZ>|@Y%mbEqtB|zw@?fBtx3Difxh23C
zUL}2GU$}i6uC8v;WpBV2UMBsLME=wk@r6@vV5=-^o6i@HQaiVa8+;GT;`Bn!NkD)b
zghH|#q}*10i#D|GdR1qBgmu@e+r$su+a_M{f7`?h{z1qCydV=3<OR`_{SQj^KPWkw
zMafyiWgsFq_~kZngOtpwhTFvn*TY&5?I@#UH`sZ*pzpX{++Z=($qjbh{va{{fyqG0
zWT50E7A2EW8yFoj*bjaI2FVYe1o`9#k3j&mJdp@EB(r#6gv|1`u@C&_F4lq6y6wC^
zQSpCx5##Ocv_4TZ1I_qTu}J<@?CgK7YDMNOp1BxrEWwRsfGt|K$fE%e$C&QWv3k3%
z`KvWTy(=*5-Lo3#DVHdtrt>e}+pY`!X0@R*5CFNx6Mg_$zgZ*I4L<;NhlzURrkAL?
zy2Ni*Wqs(LRZiUu21QFK*98=|ldD{X17j~6Kx*oCN$~ImE*^V!JW)815eSS|S)gpZ
z%5o~m^Rbu3=&_eAMx)1Gw!scuai-T`N3fTzeBT=7%k;M2w^CKN9kSH&)DHdF^9H|m
zRZTxp(5|3={S&W=4B8>N-ctbSc-(<I$m6b86L+vnd|?N>#5Z=ZqeYF(J^?j2+81_+
zOI)=h$k7^j1?g+#ws_2+b?wkYmHmv$6@Ui?;D-VbH3E1^03LJz-pmIOU$+rJJaz!`
z%s-fDULvOVtyKBUAaYchOquluwP$D1ZinAlR2WQRWoOYW6IWFAen?ziSGjMM4_oa0
zf^;B>OB_gt9pXTKv+OL@CQ}?p@)?_7J!Vl?QY}FMt#tOw6tjo{e3%6!&90<VAv;b@
zL>tPeUdR+<MoGr3f4B~%;wkdXOz|dhL|uS4VQPcC3Hq`bqhvEi`AlKEC&6Yj9tT`x
z#$z(Yo75{}&rt^)0`@utpk!}y7C>;&h&qGDlvFK8oxI5>4<rK+m<*Im2FmtD?H&px
zlab{ogT2W}Fi74c2K~sJ^a2HxRfXx4yH-@8Qaf2{Ju`W&vuJU9w2Ij2TkF(?f3b?|
zw7X>duZ7sE#!h{sxcxMhZ2Ub*=Hfl7VF#4(l-kLOPrwskWOKxTu{m}KG7C0Gu+QeW
zoY-e`916O`9ESq1ll1T>Iwe!||4Q1a#*4&29sXY2y;C1AWlvQo`3s#{rR}Gv!dp9c
zOWV`b>Ye<(IF7hLC)v1Ny%P~nz8O#5snd4ZJ#}&gyOe$|%&uqbr*=G-bET4mByZZc
zQ}buzx5DfO#wlq+Tlc|DIJJ7CtUVm*7h~fCp>~qR<3K37L;J{ILdw|7_+6UN*8P_|
z<tuX6F8PXlT6w#IDzuB!E3~FW=<}WY1%D7ewz(x3kWO~vsM91iHn--xa79(`$J%u5
zHMM=jlbD*`$)@J{Ygl8|25;!l$J)JzN2;#7bo68PW2*Zua%S?icIRF6wRYM50G()0
z9`oEwuT2`Wc*!#t@a`-AmR7K96k)Xd1^4Nl`lC8_Io+dz{R~zl8YsJxp3&bZ>>7*i
z4)T_}=sW2!{YwS=bv0p^*!lW!__db1_yg~5741Q|mXZ9hqCHG4VtSgZq+Rq@#oMkV
zf+oY0wu@yEj~1QmdPSIf{)U~-ET|0ce7Un}tIS<`NoBjQE6q<v0whjn7bFD2lCPli
za7#4u7+rCII0iA1MuIM03cx3JE?vH=-Q7oNa#cH8U2-Trzl)Ob2D*4%kN_1cs@GJt
z3wideYvVfaM|fR`|Mc&~m(?j%?XrcO1CsvOrCU|AySlDZR~f={4*BN-p$Yj#cYDb%
zMpsOJvE4rM`Exl<%HUJ*5#G<`D)_pF`?`iZU13|y`HK;DH=m&`j<QSWUn1;rs_||)
zouTz^j%bZ{`z);?07Tl!s_$-&pst1h?cnaSn~bZpzFY%m;*HoXAvE|oTh@e{c5n5{
zZh0SJ%5HtHrd?mn+0Aiv3Sp|HChlf43F^$MQ5RszOhyq$Y$h3WMOCkv(6!f0`rz7;
z@e{lKX0i!Pc+F(@ZZVTROt6^A&fR>d!I9l^r~#v3lNhy|OyVU40DPdq$A0)5cZ($~
zstZdvzgsM!eLeeGwQ+ZLT0MKLq5jQxag4zC(v42a*|?hz2%KNv?t_M6CIuVV9aP~g
z7ND}TXg7$Jua5o>Ph57EPvqsZSSku_VK5<(gPzvVuBK{b>9q~fv^+Hx9ShA86A2CM
zEjrc`x5PwR(G}}ht1Qtm(1cglJL*TG?4dpap(uUT(?Vd8K0bhnLv+l~c6;5b2K1<R
zlwCw8J!!X4&u6g`jmh#{`6EKTf*QWbLX9$<IsB~r7{K6ER}CJr*q`H$$<k*V+fgn*
z3ioK?xF?W%IUd-=uBFyx>Df)}n&sCMB<Dnn(L|YW-`nB7w~tsrBJRWW6HRTL+J^fg
zf-JgX5oGyAz-IOYjhdJlRNZH0M}1xMd|mULu3j@+*9=||l|P%=AE`@OY&tl)?tU|S
ztnReTDyC<)u-mC0!4$pJd>(KdMAtz#Ci<SXYw8By=5haorO>#-PlTAQ;gLPKqN+DX
zE2q<2*kR>r)bwR(*9p4gcd|U~w${{Pt?a>A`@34zhWZ~Y>-x;!!nH@wc*?HpI!CvJ
zcaX$#<3nL02_MJ%8g#{StFebwr?8vcQn;I->6k>-S|4f+wQ=wCL?3IQhqtvG>X+Nt
zuN&<NaV1^(s8vC=-s62Z4JT6KehXJ?z;!T3?~zrH!(HuX@n$U3d*t<U#vYE$Q{_fm
zoHsFQ4~OPie234Q7`2B(v$2G4$x(}ycggp&DSJ3VqZ7HFVSCv11f%6Fnh)bV{0{*3
z?~zP8s1FZN(>?62O7tb+@Bn>9SAF;BE}iU}u4v*-hN1<Sz))=LWNZ3j-a8b{{VlFJ
zL(zh6$xuKb{-OATAoEb%rz;+c`@us&&}1kQI*USbf>pc=!g5%)Oo>Wnla}_>_qy26
ztLoXJktMTzIICs*2SK&SX0P2On`c8^v)Qzp01~}`h8ku=sPW;1&!ZomYvz^um~56h
zx{}lzWwX?S@%W^!Jo!2=1PXfLET}z8+y#meAWB4nVv+bRx{A!!ANI8CxT+B&BJpDQ
zT9}SMZP?4!DkobU_Mg4%k!la1)5PRVwoFV;Q>Sn@IOj97>POp?)YsYi>~uQ{pB(cd
z!&m6yJB0ApY<>HElb+qid0Ex&5di@+6DBBVW`f>4B|ynj0+f&UK?aPHrvw)PiBj{^
zXh&0kcflkrC^XzF1U|8s2|St2a{wHC3HSRNj+2S*W1HID&wfOAm|&Dt?f3Eld7V)_
z-{_H!=p@Svo-@yv_q8ppI_{OZ!AX%79d^@puMqIWUY;8SJOL>@H-OBl(7}YosFP?X
z<i&FX*It<$xPVX;^j~zv3i>YqrcBK1D2F_4w<ySt12A;EJ9cf!y1swfPEm{ZvWgZ=
zCU%3LhYYk^s&yco{HOOh#%%500Bz0L%i5Z?m$mgIctIdSjRMhUs6kt^_KLQCkA8vL
z`t@GcRx~DU&D_h{8jOdvb?{*1QzdeE)v#5%-OQ`*I4Cx=BU0MHF1kb$yR@1QqDf&h
zNG9we8sy+AW3T?|Sv$PQTH;j{7Dx9qL;{-DAKP?|h9C=Rl0!<{(B)3_H;U5Jp8}o*
zj)+JEx&$JeoZ;1rK(mkNO;<bwy>o)xHNg@e@yk%eBn%Auh!Ml=uhh64@e!kQ^qa%&
zMe3Ct5%_2Ta|Zq891-~V5%w*$AcqAWpTh!Qk;4K<4Il3ts6gJRv@O|Q?az^;vb@eA
zJBJ75Lur(ar}S0zr5s)2zc^k?9$xo7^nF#We#^lsD_(>1!_g(^<p`jmK`yn=K`QUW
zR@o;xsPps*?^7HU^n_})kH5~rGaB(ZIr{6d_DuEkKIW*;K7laWfq=U4JT!E&bn3Iu
z+o_}*X;T7sGUn=-Zg!+v4m8lax%-%;je-<4yxFUA_UYRdjA%I`(91;DKGr>_!zbPj
zLcvvs0_W*X?^EAlN9w-Nga!^H)h5_oRM>uIq~v}9Q*FP90`)=@?b@p0e&)X9es8DU
z6K%KZE}c5>=kXl0pBX`oWIGl$3~1;5x>&5;UcI(oz7O;=F;!YEkXBRo%ZRQJ5O_!`
z;d|yE(Cq!e1B#A3pbpZrKBRoEz*i0z&eI#-r#zs)6H75b;)sDaBmy;8U+rLbG#=IM
zhTGx68A8|r2{(bQp~X0SY}nFHc9RmXkukCDHa~!?*K%~1SM18Jm&q)|c1J*UDcG!e
z#U5g`6%=$Hv*)D|HN?Z69&Q(-Po`P{7lIGI8elqj)2t7m!jfTIyfXIYYxZ?xk^_WZ
zAsK%_q7X{{YG{r;t4zl*zlD1gh2|1v0a1u44T?hJ5AgRntNopg@w&knyNo_^7RRrB
zRK%)gZ1+D@TMo$5SLy*-`pSF=3=-!+C&xLIo!+ny5&azJo(J!=0{0vso1xXR<KMKO
zGK}whoR-6JMI3IgIgI`uK+dnh<kY?YKyt33g>#;hC;G?AMkyWZhNq-uMdO-q9=+A7
zZB+B$S5*!MGaYg8L1MioVr}UM;sx#(Yft|})h!=}-VcF6#0sgfSg#$({$m!_z!Yw<
zT)zsEYjvGD$6k(aB$!)%$7BXxgr&U_l$6Hs$x!&X)GH0OG#^bX9!S%SgRD$g%k%*O
zaQ@iqXu!S0`2Zh#2*AQDpfR&3Ys6!gjgonN11$J;sJbpZ-@bv*SD1{p@8Nq8ht<0W
z$yVy<$q9CK92Y%evNQ6k@S)%lE`I1iBYanQjR*h&=*(-AfO}E-05^LGz``q_F|Q~u
zFR=G2lvmFn!OX{M_(J<LV}fAhVRavpVMPgE<sb-rSmft*Mn00}Jdh-S+VQ$wCjbWS
zFss;J_Q~*_d~mlt3|vlu0gYKjd1jIAQ7Cy>$Ks_hXIL}oU4v2Z0F)B<IUp%<?*p<b
zep{&E?-_mqR=CYx2RJRhy4W78jKh2)BR>0l6^EAal6c5roxKDTAe6i$-V0s<UONoF
z_%Fzfko<Ir)82q5K*wn>yfvr2BZ4v@PJ7`Nc}YB#{1E3{%?{&=bFOBGgVWx-8f%Z<
zRBQY)yQ9AKs$G#kKI?UujzdkySxO+85B+lW0vspZ8h)75EnXi8y3LcJu3(9B%Ta`w
z<I{Ay8g*FDOtq`Kh7%l#Pu&5B7Erqff%Z=>lc*mvv5>BqiG}%?cz=c6*~dhimG%T2
zIL0*N8@kZ-=;nDd^a%-eO;_2yXnN%3h@Lte?GcVNPx3#YCi3arDcrwd;=3)}kT?1d
zQ{G|xAWdlf9ZhJei6wb7;!nA{_)<aRe>(GJTTVSdyAefkm>O<8?%DBVQCBc}Um}lp
z`b*5Be|tcOKnG^?s>%^b2!cAY$k#X`&ml3f$U7auRnB1@vDSXvwTBoLk*7N%PY>eV
zFY<oWk44^}u2|&#j|A(@#B~9B^W8eE(@!9h<sCNn5&h<RJ6$i0vy1D>v+SaDsHe*f
zV2-G#9g$r9^$dHo;h~QBWNx7<YaF5c&cJsHxI<eV3y-j<xAP7D?rk9mxf0S62Yj=H
z=wmd`@WxfV(;ap22<NP5R%MZ@4S@9jFM?6~X7@Oy(+k8uUg~>C#6g`{#AA+#R!=9f
zu!sxi;%fR4?Rf`UJ&hO?5sy70S=Y^X?08ioSEl$|H`#+#(OjA0N94*3`f)&jtAIp!
zivPuCZ2h%B8`^tpk}F;mC4ysD6`d<ve?4<0v+6_G12QY7CMdH)Pj+r7*}0*-vK8k8
zp=9S41xVy)9!EQx-&f9+`Tcx{y17DKrCfGo!?t7XCN-Dm@@r7wu=|y{I&y~{LnZsL
zO4LFAr^PacUCYR27Z&gUNZ5rz6zsyr1}O%+urc7Aj%*l19I`5YOjoRm9|LaS%zeO4
zyDM2g_Th#u-Gx<@A0aNBcdh=NOZQf*-$5JA&i_rc$qK=}T)+1Uy3ON!4IRjP-6xzp
z&gGBd>VB@SpJi8b-6J?M&fj8av+PayI%(z-yRN7BO562~|7nGzvWEF>5MsZfH72Oc
zT@$)u?wTA8niLZ>nG_Gqwp;m}TyD1A7PGa?Wmx6zaa6b2YbP4RsOr42)dTPxR)-!H
zTZ_!GJJ7#aS>m|0*rRen#fwMDM2ZCV(CKUKQX%fnM@0-Hh&UF*61p03R6n=RuIL&{
zI7AFxfdfvwNY?<g1f)gSdg{R}X3!P0m?10@GrTQ3cc-4d-(ITYR)Mrz2aEB>Z01qj
z^??1FLdhGmg%8@jsKRRk*v>1YlMZ4f;@hLLJ9|SIBWL{WQB1UCclIit(iX<Pb9R0G
z>mj=dPC{t69&5W-{e<EZW!^kWJd8!P;`G>&VQ?GXK;qDVlm6d!WLPzi{Z$m-A%BG%
z6dKw~6QZVSo`i;ebSqYuJ!)4}(Ru8n(3oa~74z6f1)*a#ym(ZfJrBZ*=h+3LO6GY7
zVJ2Ns)w}OR*WR561J}-=Tt4dGcZ$pN?>i;u@xGI>h<Js-ah7&c9&bCX%#&>=#=zT7
zCG%t__WCh<xB?K~d)ns5F$)5~f0;UV9Gm~M@?>!Oov<ev@A(C(PUOkEE*OOdy4VTq
z&P+OqCRasBw8ec%<am?skQ{M?<al42kQ^`N$uW+_^zH2u8RcZeibQPS$<1DA(8<k(
zkFlT~Xf>&;?BD|$&D-&UC~nEu(@vvKfsJ@A<G1(h3V1`58`3A#Xh_3$UWV-i2}7L9
z7to}@^H1<~gV0*i=<)xOIpLTD^&nWR0=eM&yxl-y9BO}n)saQV^uQ177}pp6A;`;<
zP;=!2Y-!+Fg6&8z`JXW0rI#1fGDu(ppMzrH-6VRJR$AGGwjKl3;cifjsPi`ddx|{z
zCA6S%Okz&%v4G4SADL6v`t;8jKF0%0>uX#Dh``{pi0Tx4ST{)@X#{eQ@oenp004l@
zr#FNimuLp;{36TEV?3L$VI6-sz!KR2jUyY%x}RVx6D3EsLm-nP+g4zs$hHY}I<aBd
zF$p?(LF2|j2L$lhxHpLt_E}wt6!uwNAtDMoP;%bBZvUA*-ly>wKC@%h$m1Mk3Jygd
zQV98HU(oqo>b2v%<Tdp;uU^eP&Z}2bkL&bx*sMSet5>M;0pA-T3>@A6|EkNn<E+&H
zM|v20oZW{PEk<?Han_wd$60p@v*)1m_!IFK#b<V9=YZ``j_W5c*n?b?h+c8ygFytX
z6&=5TH)1Xxr>tc#`Oc2CJaqoJBrdm)OXBhq^&@1GxNN&<zkow+uAW3H$5TLcLKF!l
zFAY5=&-m4;a=1r26n-Ljs6Qcj|4oMgfs+`NJk%&xU&g9CN*?OJFg83{0%bJR*D(_G
zo>G6o$TPA&zyxalbDR^IX;*Bwo^Zv!jFTLgV*a#z><K;VDv~3VoXh-2BtzQ}qd+iF
z;INz#M{Rj)FyJW=azX<UaY8egI*Lz#cv!dUpAg-uPaLyut)?s1t<?bT=oWAHUJeRQ
zlrHcg#G8FxxA?klak?Tfawt7>G`r_F_FAQ`oXEcYogEVTL}&ug81!=|89z7aXDs$d
z-J|Je8wKUf^piy}cb?FXU$?72N}b}lLp(Q*=Z5iUq(@%2pDq}2lBAi~){`0DcIl6H
zj*2{~jXU<E`m-PHs@|th=_-4Tr*x+q_AkEY{eQBns)&>N&>6hPUO6hXQTF+t>^4RT
zCh+1+knkJ*c)@kJ<p<ZE{wq{_z5SLQK0wVzBl@p}?!)v$|EkX2APztDKf~PX=HiF`
zag=-bJp9oAFLH;+<A?s$je8aS4-xuDCL#-)L{p7^9HexRbNC&*GLiYhZM#oLYC)rk
z1-pjSj{ez)du<|q=wCv(d*hI8Hyx4hev4#FM^}q%@6uJt6#RH0<NY%)<TiKgfzzpl
z1GzG_qoY^dt(W14&Y*L5!J#s4IxEW^xf(xo#)bQCI)3O&aChYl{8Xo(|KL*qH+?nZ
zKDh-y^bWSW-46WF3zjmvw6W!$OFxkqx|;GTuYTl?T|y!I@)FhkXFGbjcMlBgE};(e
z#+W-E?+3Z*eJS^+^g}Nnx$EMs1UJ1X<5t*cchk!u?w<5RFHN{Vp&xpmz}=KKg=vS{
z?V|li+BtR4$6k+{wxry{Xa$>=x7}T7;@Ybf{jQ-On&P_0&{WG!Ki6{cL%BNgQv6W9
z3Vp>-CS9GOAFrIx9A%dLikN=LeyZML$IDTBN9q@;7bRZqT!aHR#b5Uz7_WQi@$6!E
Iaa6|t0r++|EdT%j

diff --git a/build/doctrees/environment.pickle b/build/doctrees/environment.pickle
index 62d6798c5b7dcb8d8fa5cb28bbd476b6cef31010..578d7ae4dbdc6a56b23247a5c770b8fc0f5d0a13 100644
GIT binary patch
delta 149375
zcmeFacX$;=7ckCF%HG|*gd`V2fB>O)Na!6xk=`OrYC`AI0t5sEDIzsM;06X1Awi1t
zgcf>LI!F}+6|jJSBA~CY1?4;E%-(zFmZ<OZzQ5o1&zI-P?(CG)=FFKhXJ+@_{H(>L
z?^<U5P}PxCEs|F)Z{%}?SBog3ju<sy-0*>8(^8Bv0}}^~7}$6C(2>K^Qi6t#958T#
zqhqybr7*uUAWvb(!fK^kObW=AD<z^o)Jz`OH?Cu=zQYDiqz08o3`n!Tfu$NXtUP9H
za+-ZAX5<+@wEw`7V+CNUH_`EXwX%V4LZRdP#*sYf`>=}2bpGD=VP!_zr$O$xl+eBd
zM)e<=2-GBx>YJ39JS1&OT3I_{x6i~2VzR%D7ery7g_ntVnT?kzc$tG2#9^O{m&tgU
zhnMMinU9xgJCz#c1EwO_dFs6{cVuoU7)+q&sTaHNq$dPFPkpdbJRypCYMZ^{3DL|`
zOP>@^2zH)&a(RI)go13$Q^&R~Lr+M?JoWJJ;t5Har<SWz7R$z^I5yR8t|1MJ(#odv
zbY#_Qx}<Kw;9`|4SE*c?C+-S}a@1`w(owT+vn6$d9beXsbQG^YMCpa~9GMM+9X~e8
z7hFJ8zC6;B*Ad#Vmt$@Hf{x63&7eHL<7k6;XxuMv1l6gMIAX-m{-dh&A2oc`n6ZxB
z4O=-_g9u0SMgwg5JSvP!9y)xiqj95G9qa2vDE$Rlxg9Z$@&V+Yj(PP9M&|WskUVfg
za^<9nX(?@?ZVg9Fy#h)fBC=kc!pZ<jEvQ!_))UL1#Qp=vVyje=J4(PZbj09Vm6Jve
zPNQTUN0r7Aj?Wq!C2P7fYlx%<Rb$O;O4o91ZyXU{TPm&UZd6^$HUS_mxwcsavty*%
z)g0e8F5(#3II673O(k7JVsi@-v~AV2dHYwJ0~e?TP{0=)vlitED{~ih%#JHk4f`Lf
z=MmN8o5wY4*BpmJD(U6_gzb7VBmW`Wj#nBNbBt*msl+%wXi{8x!*Q-jVdYK7!zTTe
zNjuv$ty&Il(}vgX4Yz$~TGm!3WizI9OHn4x?y*qG?y-=)wH?x5GzftIK==>J{-Qzf
zlH*FQ-J{h()s@ryW_7ifrDF8pfnZd|@XY#ZWKhNE#K8k8Ss9Z3`wvV??mJ-U*#5&u
zjU6{;VBP4k$z!4$M3-sS>eZ%gJG|N@zIorccI{d<?NElty`zuLUROg62~e{6x7F3Q
zIYO@VA3^3Z`_xg{BkQQ0^Kf2Y4O5G_>8+}Unh$?AQ6pUscNXQ2R4($kSJW8C-RuhN
z>};-d3#y@fW@dehS&nCqYABB|rzbuo4$Q~TH&f%37ot+q-G+Q}bG4cB3qRIeZHX|#
zDp+bNa~#V49@wB$at&5;j^kK&dIDgqs<Vv8eXK<ATP@U5tnnP4buf6Oa+W8xRO5+(
zz(S^os|Msw9L)b{q812*#6XT@v)AVEPH!naSeH3OGaC%|f%J?7vvC4PmpLwi+3Yz>
z@2MmCl;&zv_7)J7(gGS&<qTJ4BzC(X76I4Los7Vfo7i(Ev0eD$u4*h#ZK77KSn)ql
z0-l%^T&PKyPm45riNIXBdZ*cA;g;g3{Oz>qG?mnZa{Je&1n!y=cy3DIE-|I#;?D-D
zk&a8hHf4~LI51ubH*@yC&Q~{Ai?NWoBm}d5MUVO*2&JybNgYfOPz_qjbx<Jrn%n&7
zxF;WeYj|+d)rkmZ(_aD_DR*6RE#@fovK`OUN}a}DpUW4wQjaT>sWML;8W74GEl`@W
zS#$ZZ)@ns%jwraBp%mapuW9wz%(*<vVy)`PJY%uZ)US;hIB3AA5s5=brrDRw<xd*~
zR7bFP+Ni78<heZdiC!;aNIv`8xgg!zAmTQPog_VRF2B@P{aBeOFkGt4D)6t`sgsnW
zE|jmbgLC=0_UdQ0gV?$jc2G220Nh1@yiG5>G+J+{d`=A<m-ct%nMDGN1NLPJY6<q~
zT;AzGKpTH;9nXeFvFy1#BSCG+=O?RSeAH`d5MO;mvGDDkRF(ZPm+$SQ_OxB}rg|UX
z4P<qA-*|PJ63ja#sWJT0G_5$VaZxSHGy8$&5|k$=Gz+i%sS?Zr=JBiq_NG!uR8Ht0
zRLT-LkC@2IJ55##^Oc>!3RIZKN0(EYD>0&4Oxb`^tkOJQX|CECb0T@n{eZf*ywFfc
zF+fPM+&qV}ERIFabHuG^=v$m`9=|+<wNU~DjLZs31KU17vQ)AHO7Ns_v|xTIl@*KV
zk7zPAxD3ElmPk3KZ*RdS&UF-<J%F$6u8#NUx<0R|>B<yDQ-voT3arm2&f~og>a|cN
zE%>7z>LMkLSR<pDI!_qIHD(qV#ngFZ6f-fWCqAK39Q7=qxpG`oLZf&zuU5g?zlZ11
zNCQw=zXY^lDf1k$8J%nskziR<=Ff9$%6Cpk2~Hs2&J#-Frx__p@;p?MvCKN3M<l9)
zZS!3nV5;$W0FMfBCQ%*E^3CU$e+cTtUmn*<8QQV%`8>8)z}u|+d>*%jb+(k5Pdz^$
zdp?RMtWn=)jpp-Wx0TMU-h6)VOQjIrrymQ7<J+29s<O^d^K@`$r4tW(19a<YW4(TO
zSAb#92YoWf9)Udrw8afl3sb|90R{0M`%6$P-aA=YVP1KiS`r^d4-4q5)J8x}Sef~J
zalfEARuYhhvz~0Bpii4G=qoYb5yzwW+nOH6cMnl(u~pC<)RVnGpC>*6V$<jI`9syl
zc+ZGZJB61(nrL_j3&mV1@XQB5pqM_zfH&*`^cu)#bZ(`yZM>gu1Enm<hR)~FO9M(q
z3`GQ_lAmCTRPvMgvP#YxuG&3Rvib;h7W)ARb}&18JRdDde}3s!Xl}lIq`HI;ou$T-
zGO`qYIb5sBvlio&4XVgeNEM4y4nOJ$s;H!J<xj1%QXR9J@w?BpwoVO-Ng*`^AgG4Q
zpQ58Kr3V$WJw{4pUHk)j#%Z<s_=4(@B9zfjJ5t8`AZ*iOm11wE@EyruqW*A6-qgr%
z0SRj4Yva_t%520E@3Kx6iT}_v4@*2Vg>+O|iFMmJ8n4&26)B{qKyPA6R)arzT^*)m
zQ8Dj0G(cxtQ%F~pt$g}iuuTb9EERZkd~hk{q^Oj%04kjTc0N;vho1&uvc3Z4q^|&E
zI_Rqt$fdD?u5{`owY<ph!0(0x2D42mWan0-2(?|7LTU^1aYnjH@*jfar75JjBPXlP
zS?B^`Q}a<R9#fy`xx*L0VzQrb21@dbE@}xrZHk%)=5c^zTG^#Yu&m4>3kdrk02`Fq
zrx>U~WmaaQG}`d=n}NFRTR(kI3Vl08DD-VaLJHjyND>O&a)GSSt*5CoJrp{8x|*RR
zBB7>@?Y)2(o1s3m^+pJ?qK#VMR<t*<fv3(+S|Ak7Pdiey?hAyX{WMdp%2qAlW#3lE
z*+wA}c?RzRNL+K_2E-E256)62v$YGvly?yGghK6u#xQN~UO>G=Gv0Z#cP>*c>K%4*
z0nT`@g8vLH&EDAU!fVcXXGL%916a@-KE-<$h&gYqfI)L!4?hC(n)3n|I{PCCQ)FO*
z7RvomFGWr8=#M)o>M&Mhp)fE77xGS1EHvL$<WEyn3-7xGF6oM8fUO`xl>4XRLRbH=
zdJFmVHGv~Me3x1P41E_r4XK0jLHks72<y3!zniLdvQ<O`a^K{K3fMQb7poK4fQ4dO
zdQ($qT5{7D!V(u!U$Kb`X@b(m10?9EF$<}qhB(w$+1!P~_AdlZ(e}?@$a|!zZSan^
z-!{gD-0Yy)3u(BF2N=*nKE-2!9B@hyHQE0Bex&2oImfUH4VL4WqRu%kb<RMZ$kqNH
zonu)JbL(xhb8al;Mek~6=S*9zTDg6Nx|BT!G2?pY$wIN-$+bwVcb+VyB}~X7T5rLV
z(-&dUi$rJ1j!4uZngIX^IU<i1k|T1%o2!SS&w1uCOGDOLz;Sf^+U2jlvPkr~pN7=u
zS3ulo{YR}<i!=Ko?pUpMu{}gAa>rjYJHC24_#<N%iH=X(sy16TTMgyNdWc*-X_4?x
z<}4E3|Mnv4exQ{M|D-jb;qNUH4$6u}!a;$%+d<g@RD*-Uw!<Bb{Vo6?8+#y>j6F6&
z=LGKLoWR}foWKJ*Cv4dwQk=IJ2`fJX5TkSQok`q7LEQ93q?^GT)GqABB1aZ4!r$1S
zmQfTQ_K{k}@pNO9FeZO4;=gTB+cCJ4o=!*7h<VdT`AwjE2=G8peTo4+`6wVG($i~x
zdX!B1sYSx1pF#wrrPWg*MOs=t)oDT!KWWXs-K6%4h{Hmv*2Gn<3031QcBpx>GdHV)
z6{RO~6U#4Iw7RTYs!M&N_|2{AY{gEcOFpk_>xM97+cGqj$JPpn;#0Z?h43~7S*S>z
zX|7SKv@(t4#Gk4G71`ueer&3x4V#ckO6vz0>0W#)>RtmrrIl(48;%&~sc=ch)bLb(
zCsVCy8;TFIZgmDi)+_yOo&8Yg9^b7Z^%4==u?mSK6H_F)Ot(llh@@Mi(gTx+4DFvd
zT#5;mEf-yO=*Vahu#TqCVY#%FND)Kys?I|X=#hNn7PVR9#$H7bT`KDnIQXl0)2Ihp
z6o0ZsEvKAucT@OBUW}%6;juH+rZ!(}Y5dv8TEV8_eo8#T75*xCtnzQV^uQar{f5wk
zO8-d^r3}BkEV#gb9(RfJ6IbzI#80^gA5SEme3U8{hc774kv^azdz6X>nIE_UE_>tn
z3iu4c7oL4hEdc9&GxQR<nC!5qtJLIix4@q_Yh&o8naFwCo!VpQC0?%czYD!25Lgj*
zdBihL!Z4mT1y*+V#US(3Q#8nqN`ox^7U~iWvgwN<g^#n+>?ttnQu6w0P1$m3<Lu2b
zJ~B+iM{Zzqc`zOaZ2*U0YL&RL!^TD@4;dIeZtTD@(aEFCKr3aLfTP_(*UFw@r~kOM
zM<>r-oQpTTrB<ehi6RC^abIS<Rws+O@<Z@USe;;ha*Us7D?lXRq=1IwEY+uv&)AJF
z3$fyI(UmGicLq*z*C=|_AY#$YTJ-qDF+&sk4Ida?cEG?viQ|SR*Nraj6I(7`j>oPI
zDD+<|c$OeP{V2qBwk~$Ao`59?&+Q0m4+|$^@6sKm6g#olTsUFROAGz!i}|xOO95<e
zE}W>nxp1O%LMRLF*5W^7`pao6ec1kT+I!_Hr+M_=R-`bJKRq7MfNffg6ScAeCP+1Q
z$&4_zY%z~30s-uqq7pgX$GyxU_7}~Uw-@uHSz76c+sGeTed`iPk=3^@!TE9nOoR%A
z%)-9J_}U#vJ>8Tih(GOM1hL2^{F!Pg!1wM{7b=lhCDM`Fyc5sdrN*1joT7=Z>{hoc
zZK(o3TmuH-t6!PsqwNxO)#CWet%}ZCF5!>%s2i1`ShEUG|5&SUYl-y8lj@Kq{AewR
z*i_!D)>d8@H8ITPw<b-$%06|KvH)v}eSo=3gjIVNvwE_*ODM*$QB*)Hg%vQyaDcLS
zXlEsXTMj}PKYIz;H7Jies<%~^II=qD<F^i~<M_o#W(eam6F8Vr1P+g3A6ja<VSl!S
zg4H2B?gv;3PWx49!!APBuSJ>eAmC5|4PsfWAdDvDpwR>~iaBUB%{pL4-F3)l@*j?=
zRneG2K3P2^z@)X<%TE4eL<X<v63608u{`>$nwzJeP%VuoqS(pkjdef@A5Ei2X-^Y3
z1S`uXuK5zN=J~Ug+C`aw)I>@V?HLXc(FP6u0lN9_0;K_)=J<<X_Cf~*v#mtR5p;JZ
zF5xi^1FG>xC)GqY!QqN+rz5d4CF2}CrcuB^N1>4#|KpgZar-H?t1?cI1iD#~2c1?&
zDF+296fWKC!1z=x-se-bB42e%4dFkW(1zLeB4}9=&pJqSI~`8Zg)k)RtXhHHcJSV3
z)o!-4-sJ2CQUh7-?3ZWNubA>RVr|3kR%I&2g+{S^4qoXSR)j-wQ1+RNxQX_osB`oi
zrrMsnz?p6{)TfBH%AdUe5l3HT4Ya^CvdGUJ<eJyKs*Yp%(?s+oN>q!v9@u~tNaL-q
zsUu)B0h-23pbZf<%$G(BfWS2J$laLDVhABqIQyQEBw3l=z7j$!BZsp)0CB?3bi@?d
znT~1XmydH$ID5<uwU5+46?op8>N>Cp#2{>byvhbb^m>Y=Ht+kXdJjBkEO1O~6{0T9
zmrKb7rxq@!)MAs<OlLX`hv>4~;KnaEYktv`rKJf2uwFoI{2Oeuq@~fY+a+q@wi47@
z{FNmFSBZ_x-2Gi~nHY|Gm|{tqShxT1#Ia-3KpP$RUbnI1X*7UMNOxsOG=QIo9NcgM
z*kl%ncoW(5qO6{x^RPq<Skb{^uLvvBQg#9{LbgUJL3Mb{NlP<jso*45WDzGtml7w9
z1SA9wIk-Uvk!yqvURq8Zv|CCXm=K0}KtK~TQRE;8MVIo$F9X4_5lBKJS)irPiY6OS
z+sOu+p@G=>@>qHu`fCh0@-K@9H&Aw&Ky#)ubE#OM`+-AaG9k@1CJnM=bJ1Ii;ENxs
z5n7tCYuA?YVGq@Iw%3ss*<|!f6UHm>k$M((w2(pG@!jCMoPsuB73y2W5V^HfL~Eam
zIyCxzSW2T0_!<43dXnW{CKl}4GO=KXJ1yA1|6VQ2iZ2rj_M&iy1$$J<Wk8AKWLyJS
z_WZc7U@90wd8+2+tIKM|Sv|8gWQKLLROVB5Swi?H`L#&a#w=;Mj4%EMY-_D$JZpPU
zrKooQ41NvP-wSkfMo=EU`I%aPC7UIqy+DuuXQ1=)3(p~BlH!I>kqBUcA`x(>NW{(`
z0Tnz@BqDejKemv?u>dF>5>S~h{YhQV_L_3tWy%%qB-cA3tTek|f<Nm;<i~$UBtXgP
zsMliOm;m4zL|cWQ{kK|){cL9b=mqtce*l%Z1Zc!1+=<KXzpAe=cpxsb1ebhyeoNJ5
zHNy;^dMY58<yuBY_y-tkxJC5cQhu)^>&1(ex0vpCZBFX;cqtkCo4>1ZtPO`aOd($L
zg<4kWD5}yHW;@RJyin^Z?J&;_=srdbBi%Pux)mpHvNrEj#R7X=_X9#~K6QW!im~4k
zYEP!WpPvCu4kqXxZ5q`=DUpNu7LY6q|65!({F`5T8vdp2K=PprfZ~-%u^DGy&Rxd8
z0#8*e$+qPPPqrnSxGSQo>>~j<lI|wtWb$?cK#cGD0Yj$5!Cj^Vr}qZ|meTA~&hrFX
z+SxWCYT0xw1=JX4S?Y%-ubJ>MRw03Whbfu~zjFx$B2>2Kemq|%kkS#qy4wHdYX6&P
z9|`{CCxrvc+G{M~yMis>C>p<488pVrdk=;gQMGJ^y>loPj{CH9cnZ-hiDo8w@7X&w
zONau;C7_yc%300jyozDDptKTs<bKy&?$r-1my75Zw_1Kz`VtAW$=7qan6pNhS>ING
z2wSHbaH!@Dk%KOH&*c>9t&qpk6kK;CA3Cui|2&VSBb&RNW+{L}b4s`6Jg&7C$v+RZ
zv{ZJu@oY2k9ChQ_Ch%Nz<Jl(g(C+qKHy#Qqr$ZU|<(~<308T=epak;Eb$}{7Sd?pp
z;3(Y8f{n{uD`*mq7CFcf<Tzv3N>$8mw(J+Byx2!KF;!kci~%?k6Rj^^<hOKDy1KE&
z3v4`pJqzrb0<L(0Ym6Hg<RlJ^;9qRi>%%$_aq*7NA+~7ZnI`a<?N)iT!)bnt$ibC{
zS!cgoN6hojqAbOEizb!=Zf6B3lL>!N*wTY*aY!Wy>2p&^KM*K>X_Q`35rqHY2L8E3
zcpiSQnHS;4J0u{eg-fJzSV1h2AO{JrC328(vrcoljv)MAaZ9xFD&>nM5>O_SeZ7RG
zhcaBWL&Ar=BYJm|nFSIb@(vL&#|<2EToQi=vpprgOb~9i+vU*?2|q4!kZ`lkCAp3u
z{Nu7f_!pEf2nWh!!cUa5^j7{Y+9BaTnuG`Od#{1TC+F}-LAi~x==2oixF|1W)_gVa
zb*HWrdzVCRwrk|k4k>RZa?m9->-3cC2+Hqv4TuIG9?5WP3y|le9(_W8_Je%FqA`}9
zaQcaONdGpdE8pHxEAJ$4=DXNA5j^Q@r6^1kZbqTt*!;kfj;&+Dluc&7#1<51RkhSm
z4tq4AUOi7)BpVsXEx$krd7~zQMU^KWkc4|r45J4QfEGvVHNd@p*4x<?Gv6h2k(A{`
z*Xg`cQz<QK0kab%K0#P<JiQO>X!{Wr%~i3>`RLk~R$*<>6w~7Um6eccvz(u+ZK+~w
ziP`dWRShgOZcV;Y$1)GXGejDCx=YrT<*EHFrFc?ZOEhb>Qn<N^q5`?OeE=?m{lLU$
z%nlgBzo=)Kh9}pMx1>_60h<6_0Vil+?Jx4WYZZ9D29{U_;$~23$<zjH;Ytx&b0CS5
z*Zay!5n2Nf6k0PuP-x9eV`z=P-_Q~x;F|{%#;p{N;urvoj^fHjmbYP3z)jRgCQ%=`
zi0TEy$w|-cmBL$I4~H+nTMoaQ16=@x=rW-YU1mC=iKT@?X_KVmUL++owaj7p-V<wr
zu=m880Pe0$JbrbUr8&RbFCdJSdC!xcitqWC6E?@~Jh+p433qZY8@ys^hMDAEhP>w~
zo7OEXOIe~xNN<x6xC0?g_{jE_5^Owx!QI5MUSv$jfedI&zVkw}9Xx~Y+>5O?pI3Up
z$;cTFu><Xi9k>%a&)Zm<Gk73&dU&$4teqvBePVKR#pDL=Zf+i%RDA12#rHW-0gZ{9
zfK@^Y@J!s~HJ`&)d3H|3D*v5>L}2H@ow$KJadWnlB@r`;n~y!Y;XlP&cCt3BgqE~e
zCA0+YZgvt(GJ1QF(Ju!wpfRyC!E6W5#Lisvd6pNP`8mTOcA!1619xI)e>Y2S1`ote
zvsIqDcDK7_9y@BXb8r=Znrtb;;7%=HzGjKT2Wq*`-7@SuC60|+Nz0!;FfwuZ(-Rf~
zxC#C5Rbq$yC!i9HP>+?g_?gtpVrS}VTKp)zEsYf`51VIc<_O&q#<bOZMQ=+taD*Yt
zT>JFE@lDn+uUO6pttM<gt)hsRPcdMpWlt-#80OKUYJPlPTK0eup}6{bL_%JEqt%ci
zFTc@hTJ{7lr+C-a1WSL}+vc4UEu1fz1O7V3zgg$ieCi1}F9G&=g)$iF7b_uKX9Os(
zdj_o*{`QCcE%V|0C)5<)>BQB-e}Qv;lm-6F#MLzQz@`D_pmz#6F7I?RX7}bvjD>l)
zryEw2D**6l-X6Ca{q6|9Y_KI>`Phx`oQV%YCr*6l1ir^^e30YvI{q;6bq)x3R301c
zobrAZ=m4CF&Vg=%KeowDnDjEBEi02Q9SRZNE`-a9y#tHcX{!SY`D;xxXNT1^b4CtD
zq0-FRA{|orNMUcj_{Y#fe9j0<h;0y7k!R6PAa|TazZ_wi%-W@ka~`FmAc7Bl*4SKF
zw@#-?lviE>`z17m_5}o>z0hkkg^ozFjAT>N#h{;<E(Sf^T~h;Fl1{crf#VvhEDd;Q
zx!{=aG^A3RJX@rT$rBr*-GMs|RJhY{iymt!gPAzol<_E-CTuLUITaMkZON9m*;$i<
zlj&ld!krpc8VBYV9;o37S3?}8N)kTS=1;f7NyEPBVyyN8I51Y>B*?Li7IE<GPr-1{
zbQ-Q(Ubi%5VHy0{>y}RNmIT%kXGLro{GAElnb|PU9IHK%O_I4P#%i7n8moT-EI2RX
zQw-SYya-60&Wm*NGgfGvZb%p7bOR!waoQ>aQZ!CmWys?+<qhyc#Zr0MWXo4dKP1mw
z4)@8xpu~sDXpu+D;XVjQ9-c`VVt8i0Y1s*fL7}x6o^NG{Q1#RdTJ7a=SZut)R7)s_
zRE)CPUGZI4MP6*WB^h3?alzQ>Dk2zNX21&OV|Ven3|bw1E^=^@aV~=#bH|bI$|{d3
zTdXJ`p9b4hxEBhJ;5%koy246#^d3u3mTL_`3CAa~4V7z+8%i`~3n-9pLLqYW*+5Pm
z0i=ci(!vd-h6JRG1O)P(KycjqmFG6Sr;;o{CEcyW6NV|(oYo@=4zy!j$4@&N@vmhF
zUwJI{6OH(^HINz$+Be@)(UyeS@+j{K-G`$*ImOb24^FX+Qr;27(mMwf8iwIsj(0p7
zmYW}*VhJ_}K3^j?&9{r%v}wKtFu~9Vji8}_ccJBVcrysa%4t{n<Qm~UpTs;m)7w$G
zV`9Ty>Cb>SJmGZ@DV9cm+8QzXp*@a%*vY2$<f1xZq3fKw*iy||NSnwf)`%(lC;&#+
zIb{jxXny|e04!reD`{cO_P(IVhIuAM@J0=mqq7Q2@r>h^!o1_J!Nu55&~fNMSAO3=
zbpVT~Ghq>RPPj<jgrzVeni)u)5^4h902}sB3fC^PtmC^6fn6tw^#zzA4EDE>I@-mD
zrGksPaek<qlmm4L31!z;z#{6*G%Y)(t+2Fq77}&6{7~n3$Fg17E+`=RZ8qh%SwN*z
z+DA56N+};oWFGTF=E)q$1c2z#!MkiOHW}ohSEqdM&Vx7Gd^_fcoM95{CXvLtlVI$a
zZmS^>Wo8iTANXN?T)HJwDan<O!Jg9r_2{)ib)qrPJfKdj*AbQIfO^ff!k>2PPQA7M
zbq9bU+x&-9&Seth5Yzo6Xnnn)4agZ9F>I1X3_Hn0hU>1gyr!5LG)@Yy^&BU?)?2o~
z(F-@TO9iw1%d;@eyL)+?MBHXC;xcm}4nR>4pOo4{9x;1E%Dd(T@6(*&A+v%sWYr`R
z87;io5-%Q!%_VL&$qzrYhGyF>YsB2X5iB;IFyX?y&;~$HKhqt}u+XFA3IBw)ie}id
z>mWrlY}s`lGwe1mPq^B43%D0N>xy%pZLrSe3zy?bcP(Jaj>1;SpP81vu+>5JXzp!*
z805LP!#Xkd{*na{2VqSy_x4*ST;pWQ;xPl2ipn~2jc15T=o&*M*az+mJKoT)8BfZs
zz3QA~QrD433^iz~>a&iI9vB?S+kazeqwIB~*=3@ES274Qc;LGPnroE96B@${e(T&G
z_<cg<6CeH(@HA3eDsFTc`(WzOdB&H5A#hMKo>=lbQok(<=WiglCktLr{FD}TfFG!n
z`jsU=ZfiG$caX3tPk1db!O2tg^~96eF5cA+Az{ETLFAwpVb&Qb*KvCUlLc&i<q>K+
zB}5)U_7Ui@rJ@-`Dj_Q5BKv*J?a3Ce=hGJi)pS9IDsHMz2*@(kM+DW21-GBO+5sS<
z`mxACs?9pT%5_{+Gj#*Ksfz?S`xJy+knjHpmblRy#3}Wt4Wu`$GTia4+^7vGWLAFz
zol=KV=fQ!7to;UBk<jsSGyL9q14-CyG{o5m>15-f3|=KR%Vs*u-1IFm=>sGteY7m{
zr}FM)QI;UWV>P!GctHorPfK!;YJ)OkFfkqn6FEqiH$W<W-Li|87+VL-mHnf-FvQS5
zntahRlik?hxeD?ctxn(Q+6Hmt{ksifLH`gCfL{comHeVSmn|PDDj)sQIh6!_Af}Q4
zzW4>$*N%5!|D^F(N+~4@D|KN7J`jFUkq>}4$uGLRLHI?`p6orfuL`eX0+=E^_chBn
zkv5Oi<@!Ka`9DBH=nX~xX&It)mgwkc($P`S5js%q3DIpLVbBL+B8&Y%I6=d5AO%1W
zDFmV_ST7>wmm8L1B5jh=&P@tg;@?0a;3d<CpkWvhxxYcIvbGU%^uE|;KnODYW&^FV
zUcF_hs=+3&k_-R%=z1)Y9sWQpx=sj=@Leo+^aI}VwxvG2@e6dAi>`05yQzycvFJMZ
z0U`$vV6mdrc09eV+I*@2LA3CKo~4CXT|btXrUj4>O$)IoADR|^#uQBpKYt)k3vpk#
z7GB~o;oUDR$620@yjUg#e2k5_^h&_lU;rz!kzN3@85;qVZ2t>y6!w4AJ<BRq9h%^)
zCNUeuAZ`M89K<mjX%KhZNP`$k(dzS84J{V79%*qA#(PI<<(!7H&qf@^@S1Q~F|D3s
z+Ji7waiiP*vsosZ877)E6U_{PW{p4tPtLdtzY{{J%y(-|W05Ja%y3~*Dq=F;FOxLl
zTR*gnVqa`Tv(w9CNpwqKel9TI0tR7Ag5}yI*f&c<HWB+!3R@8+c*TxdUKX{<1uV>C
z_XTRXc3)VG3y^4<`7$7aHKe8^JS-2i!o3$3?{1*9)M_d&%+8G)Hj-M8l%qn<#xq=v
zsn=3{8?VZ_@ea?%M|~S#^xN3A+rz#T5EM8BfxRCyA<SQgkRc5Qtw2K>jao^D^u;Df
zMQ`LaeukB1Va%2-sRfi3ENS*uC{+{&-<yEVZTA5rT4jQ|+j#0PmSFaBlh~cfFX~Zf
zDeq>o0igA6J6ctg)9y^=&BBgW#yr`MwxCL|I|C>5pOw)@gtr1nvL$`7Nmx>VK<0}e
zR8{C^T2e|2^QBZkD6#zRI2OjrZkDX+REe55OlsZ`)Q~lW<8i<>5&|1WWwZtX_FkKX
zL0y&uMF52;A}CeiC;<Q{!pWdg+N21Ug)&7HzbYm2GPebWvAkg2(6WYY7MAr>K`4p!
z6Cu{n%}&$WnmvT&5C*WGh-!4Q^6_S2OCj2cJ%?Wl2oFW7sgreKOCLx$KLLOc#qy~G
zG>|ccE+%7Y@nhD=n1XD`nD#;}WK4@~ffO0jVq0WmT2$3u^@uj_QMGURxr&+@ZLYb6
zTQzMj9PH>6tC@l3ng~m_rY*M!YuZ=WeuAYi)D+%y&n;w7l@VqZxVb&IkoWn9$U$!!
zDv>u0@4d!qp5FA_E#wzL4f1TdZ9!`q!P^Ye+QBQ&E;L(BG)LTMwhA;C+-M-jX;&e1
zf~b7F>DvMwfb&3iXQbAS1#A^_#7lvTg>B{ch6VLh2oEc|m2BioHx3rN)i>~5iBE5&
z6{f=v0LMf^{_nngT0HAw;^?$h%tQU*j`L8btz^+g3ncJ_jPxw5wPtS-5;E$ZQ_)lc
zA$GwTH{n1gnee^^wES$HN#Dw%?!9woE8M<j`&_LYi#xRdB0LCADg*@IFbTd&*lMtE
z%qCX_!9NOu;mJv`62!w=fO7bqJ{4FLyLRpih>CEU1tP}9;<b_-saDE3+c)Gg;m)SC
z?_N)Cdbyn`aG=pCa5`MzPlqvj*w=}{GkVw)P70xO>__*>rpJPA(oQ?VC7V8V8>HH7
z;XO-eWo<1nTej)dV920%{Ba4bkMcI*6dx;@R#F?pW`HR0#hQ0S0mTS8zym)H#v0l1
zYNfUL%5G6k5wEOm!iHyIo*9ulYXZg?;VIw%V}$3CF3A_3x=mPcZ0|fvs(j^c2qO*T
zUzFedFd&q-D5u5133Tj4JUv#5J>4eU+dJEYHU8J%K*!^riovtGYHc_LdH^k%X_IUU
zxj0$CNJPI1;0Tx*6pPrlO*rG5fgg0nH_p)PaL$JyQhce}b|HvrJgy@MBB{I93(hjQ
zF}B+7Npkz`{sjVXh%yrnQD&wo@E2M|E1{SfL|M#sPs(0Y(S|E;Nt8`BDVr)$28YO8
zvRLXx**iH<25^Wn6An>krirqxRkc!znL(6I_M+_FYT69g4{*!uoJrX^K^X+9I>O5c
zZp!X?QFcEE$`FoAiC#zmpa23@mHGOb(4AI3x|i04X_=lK5t8Y@Bb-1<cS?%3kVhgg
z2__LZiAS|LRU7b_86<+!ULrVIM|%raRzQdumTa3T)TS-wnd4`mK-SNT(7`zniXdFv
zPZ4b)&&@b|Rsk8G=LK)k-@qfrVfBq|0Uj}Kl1Yp^Nk+zhY^c=&btfK(@m86nm9R<!
zTNvv;O8mh#TD)<}#`nb1wuvYntSr!gP!zA4A2UfF28?&|Fz(=ZClBK>GC>~3<4n`T
zfDpVgkhg52b@y;FzHXu&W`ST<aJ`l*i-$JTjxk%7SgPg90x+_35uPQSi{Z_+6|5Xg
z`?ypql_mDbie<Tvda^iCs5IdBCTbM(VjZ$*3Wcn=@mfvRJB#M&23am&fQ`!XnWx#X
zEb==Vz-LwP^F;zl0)vwTh#dA?UGOtZ_=^Pm?E?NH3H~uZ@DB<2i(K$2V&ji<TEE4&
z*M_ji1jn4}r2}uu1EPk`yRnyo9QFVxbuHF%@9@7^6D@19VmpM49ta+)>>wF=fM}32
zi0M;6uAKx3#0wHL52g9xho;KkGsRSy4||%X%3(Vol`o6G*;%V#3&(7Es{A8UOqKuY
ztW98}cZfjJ(JtChHgbmu7tPus!bNWZ9GD_OV`z$ey_+_IW$X|;=<mTnVElv=+}%6q
zdv=J^JUiizbK_njM00(<Y1j@iH)12)J%>B(p2M9s!7ucN)jvGYVU>4w2=mXO5GSTW
zJpug_6a6C-J=|UBA;y$7%bW+{b2+2u!pbPKR&Z{1ZikpmgLa}^e91u|NDkbI9Jss5
zfd?YzftwtP6s7H;NYPt6#Cm2L5Qh8lEr|w-6g3BQAik+Pa5<A5lK_(l>${UH)}SJM
zet)f;GC<Hv0iwj6{O3fi8+`KycrX_=Q&D`>b>?1YZ)B<o>#>s`o51pMqraBGX37xZ
zi*+agf;ej@w+;Y^v;0CdLrybX5bxQ7T88^z?26^J#nFT2J82o^QwLb5WfZ6nEu;QG
z%jIQq$jCuIkdZrwe36kmjXgp}?(|L%BX?x5%gANN4ABgQf3eWHhWdObnz)|4;dCuO
zFJ#v`C{K|^b2arjf|RlUuu~YkpkbPW-%o`Q5T4y-yXZ?;@Gcas3D_=L6BOS?gB6~f
ziyKybm#;yK*+m8oV30xkbEjBH(aNU#E@4tT17!FZCL3g8=qxZK3k>k&!Z6Dd0}m^x
zMJoaW05LI;N%O}Wn6#}dlR)@dGq#1OFc&T#nxsG`nX|jeT0VBg#11F_%LLfXpcvGk
z2-1C53lh&yf_TxsB>ybG77p=~PU}Ho>EN&&y^}G+`4g%{C#0R&X#rA_3h0A|@&d%!
zm=+-LvJ7HyHl}06uXyCq8o09w3Qhxi5ZF&t{c8fpd%$zA>)>=hBL7PQ`A6$fsbDqk
zLH2r2kZwcnrx(eP-vl+nHP3U@U^3)KcSGv=PX6XpFyudAwrt36fnwvD=U-E`O>o+P
zghXL1Fy?J>bQESMc8lQEZBa^5mYV<+%n}TXxEb0N<!4buajWOMh0pdJ^O9j*p=@*7
zQw#5u3HFq}%9nc&P$JpUqq~J!hvwu<J?ED<XjK)u72)L96GSuS{=;rz*uUE?3_JPt
zO$9DmaWvXPWboSCA$UgXjqVa9T?8d$*`xOe%ibdgiU1N)Bp{)0CsHo2UOb{-r_@KV
zVCe=hUHOhDZiRG=El_6<cavXt6SJDI>$`=Se-8=jqP+unL6+BclZo#<U#p?8U3)NO
zRfKO$(W=4wQ6xe#$b0ti>I<~S${x%!P5d?NVcEpP)Z-+BZQmp8eAR{EsD8SKFHY6E
zz=3Kv#M^s#%|%*s<+fjlris7d2V$L6tt<P}gc!g_?+4pTFR|sy<_#BXui*5#-<L)+
zw)Vme5e{J#JE&FV(cM}8a35wMBAKZ*fn_(;G2eFcsRI(l*+V%Y^pM=-TYhXf%^=X<
zG=oHAf71-oBpXsRgEYyO195lKw4okea>`O|3%myfY?+73x@GhF8{nt|#CuEfIxH-b
zfB(Lw@@TI0g>Mc~J=*N<h8W}tWoWjTPzo*wh|`4drVW5ta<&N1!MDCZo@5XvXOn4K
zi8(zPJUNX%L|CYj>r0=e;oX!?Gt1;`VfQCwQ#i}IQtPc;5t#1IaAUgb#&l6&dLl5v
zlM7QWuH5hwoqLhZN890rE;lBO<M?CNwap2;fqp@i-b=xpaNou}<1ARActC}QZ8%Dj
z3|s5HkQ$!Nf6dUU*@j}aY}h)3fCE`wK5>n92-cK<GoH_VUmMNZ?d8QrS!Q95IP%yJ
z;K2BU9w864<vMLC^avJ<voVwR3WGM8kNz0cnQRHX(T(L4Em;DTqoc}^9?7D$-YYB`
zv?q&Zwx`vhnI;=j`~$6#;>;Ke`~7=`X&Vo4(Pu5cQA<-UNCcfR2|6PY^rb}5oxNfW
zzX?t^;2E#4b07@h5Md@9BFsz^VF6pThVX6%aZStClWxk$eI2`(+}D1955w_&L9%%C
zyUae}`j^~Cg6*@HLh)~G)9kF)J_^ON`uoJU@#^g3soS+)4DOdFSmMKxQrVK#*hd&j
z?jx_Uk9RR(q;cO)5Q*bHytB_xLj@`sU<Yx~xZi|OXxxti0>!u=wa+>3#Y>qbmh(Y7
zw5#k*csKR7(pvhQ${YLm;+@($_QpO(Mhn>T*`=+4G#{;5n(&&twS{cEC^%9>jbYh9
zK74_E`#!M*qwl9|-p7Zh=&$mvr?n71^%#8j_?7l>l5YEOy*xV)=wJbE+l++C=HlEw
z@jaE_vf=Y)w?KICjaI+4;9Dx3J>4f3#ozI`d$j0|#yJGT*5B<TTVmzUz6BGO@S0K)
zvcz{(iio_>hJguu#{sPrE4ZJ`2$Yli`0YOW<e4AR$njVYJ$q1V-uN>loyKRI{gA>(
z=Ql|(?fFfTb68m(wIA#g?#T8-FeW-8MdF(zj)SKwu^#&!nZrsdy)Zjgd|tcz{=fJl
z$)Nq>izGw{eUap|eGcPn5kB(>ta&=_cYTm#0#YiI(QZHQ{fQRMyB&pq)KnpuOX=|K
z(@MvnC6vmaE9ncb*Ab!g6`l0s+Gyo{%oxU2@5iH1w{5EtzTBNz`$=Z+?B|JRw1(`n
zef->qT19qzKmYYZ?KNALH$5wXR(xf7r7s}wk9S<dDx}@lF-5c5_5GyX?e;tHTh#Cl
zcW(Z#lUgSay62tJ`oRtv(fw#YE{<yPr+c*W{N)+=Aj_{Ml;O5V-q>FVHokGQk#R;V
z!*U<sXU}LIY%j3BEY=4m8xMQ|d9zXUfRl}AOc5K=2b^r+o7W$p?#M!gF#_{DeaNJA
zL?u`I%C7d6MSB>zD283<wT`Zl+xCtY#$UUjO;TWY^$$=w`T)|D7vPiQX{;8!(@U+1
z`2JDT1N`(w?E_eNLq+rZM@<ojOiTX*V!Rrcz=VzwHOUe1SChVf6nq&d_;gut7>87I
zc$E^Miv!#<570b(__9`Bfo~mPHXg@<Ma4__tn#!2G%WqVB^7IUfQDtGWTcRW<sMAo
zqjOkd+H+X;$0~BiHRiEQughsv9zYVLQTfpU8kMI6lk}aS69@icR9-$HMkUcfqcZsb
zjmi(Mg9aWzuHd}zW)@=m%A1V62XI)v59ehQgLLzgJg?r+`Y|YgPx2Ja{^W+%Ls5P;
zix=sZa2E*kTdPnL$1eZ<Q-}?~?18MnxGk<NHJs;f7T(hOu&9ILGqsTiaj&%&zjR%z
z$PeAtl5CL&z52TRL6Wo$THs(#KEPLfrok7)5AtbW!J9X?J_GlpJT{Ugn(v?((fNF#
zxwP2)x_mpVLL<68rf4X%KS)Di?*UTf_rK5vO3YN?pw0u?V3URZ2k~o|AF)XXX)+pr
zkhb(3>D`O6IgrL_VLY(#s0Ld`HHwZ0G|q26v!1;@KWhffAwbjA(fD>DTYqoj#|csN
z5u#8@>E^1uXP&U47NLE+NGjz@?M56PpWqvZz+@36m?BE>#UhJny;3sbBdkIqI*BO~
z(Mgwx&{{M`MerJ-ZfkMX)&82R{Wa0vv=*=32ao;@UhG>fiI;nz&1X*zidgxhgZ#bU
zv{!j<{KVzYA8Yye`fp(u_zxlc@J9$w#tT1L5~{-?{3=Q(n{T0z-`59e(1yLl#x!UP
z9fH)$gS`JEt*Y$>X3LU#K$0rUFFk?<cQLLM(PMb@Dx-M#eeaq@__6$YTiXL4sz4E3
zAA!P8jOMG27)hjcFhwG*!>32;EiG?=<pqcNKEE8P_v3}W*Iq+A`f+90@q-y7iZ}WJ
zmfT&3vC2I3i8d16;s=7v^-_mJp7qASD>_t4#<2rpl7*FcNUW0jgzB%uYsAPH1>TYm
ziB%GK@kR8WEcp<5HEE&(9$>%<_;I-PA`3n(!eaN+ha%P-BCiH2kXMs*h|H&7%+62G
zU-AKR{*c&t_S1}PL90We0|y{O)PYYiHQ*30|Fc%bmWU5>2et)1*DGb0C0oMyx}UYx
z5Kuv0MJKlLuKlCv#I~64B`wcRjL3Z$s!%6}V2V01<S?2J&FsWBhxpNA5HK$EtJc>w
z8y@~u8_kQB00QXk#uA57#V@j&hlSr+0%6IBYaDiW6Ki`|#4cMN7O~47a7P={@-W$$
zA&1EdVJUPFn{-%2M(LMG%q|*#n7Rn6P!}~jOkLy`tJy_ttsgMyKnNZW@Y9ewsmNi`
zNwtw3>ZA`bRr@giUeT-CYS2TV`xjWEflCaP4P$ybJ9}8{dGra;hp<yng1=gE=df7#
zd<IQnfPh%&tI+oX^{MQq!(z|lDSXTT_dMWEn+})8z_;rv#Ro^id#|Ibg2-tLKN!x<
z;F{7n0u)JW$`65N{G=te#@z<E({2OYX}4j8s@KL$+HLs$FfE=wJ1mxGp8^HAyU<kN
zp#uz!0X|TA^Dr&Z;P)$9vR99A`el{wq8deXx*Xxdb-gisgA_;<Q779?mwe3c+;uua
z=o%lPwVF>cpr;5w2#X^8(b(Qgi$Hx#vLZ*sI;{xuPRctUQ>47}kI=kl8s(w6^*B)4
z>@B%<ivkDkfjHC7WE|m;nIH@@&jVjE*(FNJ&SW4w8THO1ZUx4dyr3V*&YV0V?95Fw
z3&OJ}kC3gok2yWzN!XcRL<Pyt{B(qr7%GqwA3s7$><=@AMz)R7dnv{F;y7KLftom0
zuj4dXMUDzZ_S2XY`Q0Nzk@p~5q{vN<LTb+uo)n>%u<gWb+1jiEZo%5{)LZb@))x`_
zo3P;oh}&@be&KuG)tev1uL!~hBK}UpDnFw0GCF+`IrUotrl{W%j><;oJ?LRHI@Jp3
zE!;+@fc^}=T?d4ieK_tYFI-691g<dUQO}J-h;q-(K1w~8-7iWv6b0Upk2AaOoui`b
z;3OMmLD#)=l)7%e$iZm>Dm^Qr_fXDbmieJi(+HgwmEmWgusK#f4d<@$^B_;$5Fv}c
z5GdDyU6Gpbw#Ts!05E!=($?9F01(e?nM9Pt3IZ<V;42$dMGn6FVAg3Y*TI(y>M89h
zOT54d#FJ_*J4*4r9i{Y{@a{Q*#m%Yy#|Z2=H`xBi=nVy4zl=Ty&cI+z0SO9ZNXyIW
ziSU^g7o_FKgeW(eSs=>g$4HbA4{~w=m0a&rzz~A`W<2Izu#<g!ld+X9&e@rbzm^*l
zt<OaciomRsi$CjPiU|<V#}`8=OArouCgFT~Wjz6oqEU5Zzr=9@SwrL?$P&i|`wyz<
z#lZ+-O#uZ8WcELg(MMpA0TCml?#BiDb~6ju?|z)vhjXe<>Yx&6QUw3Hs@_bQhxz8W
zg-mstC0eX<x0rQYsM8iVShLc8k4mIZrv*e=pP(}8lS#^#?lzEv`t(%fAm?VCKjk{4
zPt1BkyhsD&J4JvIT))H2IoDP=;X7rQfyg_~wSF3siAsWj2GOCgc{qN_M724AsiXWz
zJ-xJTHfGBvY77i(oNEWv*Guzm_4UTA(+M%*KB}+xV(m}Rgv*BwhCYnhrj^$E12~w-
zz#LEzH?5)m8=DTVz~e7PO*tW^T)4xOJCH2{V)3gf4!GkayBtZ8CfPP8#3T##>4O~G
z&HC_+FZQvc=JTNwBF?%Q>S3Jqc+PNWvWE6FS;L(s>x`y)CK5-J^`sLb>iaqr4hg7~
zU7)$%MPdIoS@_Xp0q)2GoYuNL$>}R-A9|7z@}Ylr5XMtA!qK-+QF!;$-5&DkG*qLn
zl+sEKsi3MC;95BYrk5bwNo@ttUP>P+ucsHhgq-1#yZ{Et3+^DVsO<Q*dNGB;6AA38
zhrlZH`t9`(;B__Piw<8d26X3wqxj+p;Ibrj&^y8>rrca_@FHeQ4#WTyV(z%q7V=OL
zl&ezSB`<i_bB2e^@ze==0ZzM#l%jz9ukm_&Q9$ALg&)c)0jsIb`V0Ix)ePhZKj0Mn
zk=U6C#=Iu{co)60Qk2T^+f7j)dFn;6kNoQeKp_rmxmrRF@drP(2)Gbdb1zt}bB2|1
z)lvxC72q*H2N!_tGfGce7!btEy#~`cWth9T0UvpCxUz@-HO5<A9KK<4_y*=R;Un5x
zO2R9iSdLUJ_M&Q84padY;t))&*%ESyLs+MoIs3g}9myFM_8-Iopry&9nI;|`ef76R
zp~>R}H;=Swl6->P<o;khaML6KMmTPoF!-W9{NkPV67Yf{>wAJc^7wxG2o?@=C;pgR
z{*z+UB=1Syr@uas!JU4nr7zkYvYrv*y@k+|gyQ8#<ca$f14{D5!HSY6KE{tzMV>eq
zHrg@Sj0ni1Ykd+@<k7W0DSP762I-w#o?O1cdRNx}q==97J;~px2_NbX9iq=*V}Jt(
z>|FFkFtQsr`Xmn<s*mtjK=VhBlVbiz#)dS1q+%-hBoDId6~ag3gFJuq;-lBVZwkgN
z)9c%M`9bF8vaZG|#9%t6h{1FZ22T&u+qoEgZMZ&-?K2tNeUi5rq3`4cm!m&{-?-oH
zjqub-_ws^$0jDhRxa6&q<W{in;EwC#TPM+{V821%!Ilx0VgSR+W8VXZ7<Oe6osOjC
z6s;_v22I(YoTQb7Kcw!JMNJo&MqFB2@WB~+eR?m-PjeD{rYZQd$P)>^>nTW`J;^sD
z>*c~vVYV!IIKJf){0={I@Dlt$1V(}%geemIpi{DD4H++K)*s{b;b0#?B<3&uym3ls
z7sZ{*PtXS`@Ow`0>BDSqAUIjW7Mv1&P+_7zRaq;<fj{Y^r1Ojq;3szB*d7R)emy1q
z6nS^xf}rSWlPvv|@NVHn*4&OG8L_aDPKD4fjU5SViaGn{qUal_PJOfT6!uNHFEQY>
z=tbz)SYNmRxjOilQ{+tfYnHKHFU-cD5`!TXd89sxIt{5*2*FR)E7%rbw%jKZfOT}H
z=1kR>z#21Shck9QVw#@Fik=q7dum}p7p*#g0{a8vqS(d5>3SL*U8Xj4uBPQ_G3T_z
zJo894{Kg)_q}}j7r-f71A4!s&swi+_F>(Rz$$pycY17$EXU^2y!BRACAHd2y565Pj
zpC&t2{j@NZv8P1<<6S}NazSa#X|j}Av-G}f^Jx*g$P@(8iJ7gZ`S#g*H~4u(0!(Y%
z7$lBFWX3Kw3QWrZ7QE!;Qw*4CpSdW)=n_7`N4Yq548N2w*uuu27DjVC;vm)j3R9%o
zU!9g!`@}rG1KJeW4j#<kn6JO3{DE|v%imv5W5FI~JtJ)9uLwofXajyr32bJ#ZvlUH
z6x8HLkU09>A!nc=sY!WEg`D9_7wYA020qAY@-rv`h6SS6TEn=pNT17M&Y;iTF|Yk!
zE_s<hnpp`-oH2p$pM5AJ0#F>P_?2Ax(W(}RkOa~aQzVd<XXLoRzd&>t7Z|o!Z|X9(
z&ll_QEb)w(O?sc<JC^8cS&}J~-Uvw+%BVA9n1`h4x%r<CupP6`2zxu@j5wbD<{283
zzAc5+y2HmPQEFolGD&ScrpBD%SC;A}ZKLo(mRb)$2wSt^J$xwfD}>!xjfAiVQzV2v
zBm`jC{37)7eY_3VKV}~R)1HS9jstP{TQ2jL>#6Mc89ITGuuJXA=daK^Lxwnp09()+
zulSBWi~TIB&{>2(&(Os3^BFWv=5M(?KO=UxzIa!k$ZTiD;e+SioP?hho0-p7>J3@3
zvqByH)uN3|jMcMRXNAzKofVT@bGYLqSM4lKa<85xTCfy@zyr^^R+Po~rgXgwOFT<+
z98@4XTIDRwaei>pB=!9nuB1Q!rSKX(U*i&IL9WzsOE86x&Yez7du}>~V->kOe}L{p
zTZvnpj00WAg38e0gN(Dd&B@+B>j*moJNrObjz8<Y^{m+8B>c3)S>i11a86sR4?>{M
zANfAwjXmuw{>b+rzIvTLl)(d?DrvhOJg3`2?Ci$bY&dXcQP^`+!cR;I=Q<}O{6t7N
z<Qz#Do}6FsW6|eO%JiOgIFcs+I0g_1KaK&PXgC&ah#-v#r>+YQe)yv0Ir{L0S=QBA
zhOvYQ{&0(4iVZj?0t!GD_1q)Tb2pGvd7M53DZs0J>@6ZnyaJySRa22F^V@)a0Feq@
z0Wp{=klRX~Zl|A<fTc*5URWi4c>f%)lBsvIJ@gj)H6R8%J#Us?gR5C!mA9M|(T0s#
z`e?QhL<?{Jv19P=61wPz&(RbKEYK8LeW$*VeR5938m^oZu?Dz<>X@HteSA)Q6!2SQ
zq^hHFH-kP581+2>lIO_x@tJ;0Li7g%D7bK8f#*fU0-kZ%!t$BV;SjjQACJg&o+1!Y
z`Op77Kw4S@AX-|(ok9_xXY0)n8?LPJqjV^5eAOC0y`1qcy*5uu3eaJ1Ui3p6eE1e*
zLTiU>ema)c4nPw9ra&$vi40y3Op(Fsah|5Zw6nB(y=T8Z#-;4T59n{PvFFLguu<o;
z;WyDk6gCg|MW1=rd0|eL!yV1Ztn*|})}JS3hbQ<26}I<0>iNPPw2AFHPo@Pxk%G=R
zPo`xQ5+^I@bN~&%dT$3z{`9ISPkKMBn9!@Q&!b*N@D<1OR<`K~NVX`$&kN<Md|ZE%
zeSco)75w7)IQ9riaNCGoFqeMN6kM<Az&-wo^r8>-Ni6>bp;xvGLa*RXF|3LgghrHu
zJH)V}DqjG!lDqXak|C=SHpCqxxKq!=oqE36DZMggQcNZEf>=0$TH)IC#d)zd9b^*N
zACLfnzn@2sE4%a=y|=<9Ul5DZ2^aY7voN6HPK(mtU2-s8tYiVZ{{?cfe2M`VElNQs
zq*%kTy=RBu7IjG$cR?st9CA#GwH;HWSlcf+6$|(LfABMrIoBVhBM!RSA9A%nB-+Ew
z3daCL%G&P$gp?5Y4ZNh`iF{;CK*8)A7xfj4eSaZ)%w_#NtCDXCpbp1Nz;d|c!pj6a
zm^2PAN05MncsYqEPF&z4uIZ%;Vxzg#U@ldjOBLrrCBEevtSk#&%&vT0&#SOP7ag&)
zOLO}tdMswX_X+%*nKLu&CS~#qb(KmyX-Qx;{^#1Dkn9~d^#)29QS|g}z?pj%TueBn
zZ|Sj?f)}w5Q<~sUZ8p)<mS#DRy{x&Vmrcx`3)K(eC3zlPCgSD(e7MkWtao1kDf$uY
zd<!8(zqWh@Q}i3W@u`sNhL@vwp`UFefkdKwYT!i>5`^hQN7$Q%dEx7N9w$l7c;XaG
zS^UMQsP3M>X-EKEx&TL0nj$dz(Yc)tNYSr;CE%}{&~FVnIHc&OLZ}ylu~SOm#YB&3
zH+qmPub4-#glD)*O!Y)eO=ZNf2!_7w-eEPQ=sUNs;aAn@3zoIlL5e=r6uc2q^o5()
zEs&x&)PKiUn&<_*n>!&zZ*aupVO2WvOltCmfoiiHFD9*+cGKz<RTGD@t_&WwfFJt%
zTo0LwoB8g+0s>l(8FW<h9XxAC2N1u(6rJH~h=*b5#Fz~ag3yVkKA7r{m#^_cM^jqi
z2?ILgPy{z?X(Rnz+yJDV$RrFKQNX`x4_xU}P$v^p6igV8izHh4{)p=XTBUTyu|S^p
z2^<i|@e#+ElUq!?xy7CVov*~fJuO<-vuCKO+%w-J7;+G=;FLsuf*oxLOd_lA=<y1k
z-sxgQ@sNA^RqH!23WUJYE;`~Ijq!l5&TD<Cx3hAoC_D8_eW_y2lCpU0*LsrmfRy9N
z>RXq0TnJxaef+gvspLK^q6r`nY~=^|R5K7R9zg1UqkruQHcm52c;)~i8y|UJ@0|Pl
z05C%ViNllA>^Cm*kMHaGV=!y1>C0aICm6x!j4S9#(Kd+*KKg;)Ji<-wX1R=xq5t+k
zUtxVNXCui`at>OS_QZR8(7|gL`JEYBlw;Gy3LWoYyQe_2{Vt|*eGHd-keZTa4=-;P
z`LYx2AwU@uy3lb2J<ETPX#;k=%Y9jT?UBCD8i}-!CZ%2E#FCuj!&0MgJmK^rkIB<r
z7f+?VdBP%Jo-7_b$*2TRp5^&u;)o~Da$lZS{gG$BwV~XMc#?B`czWl1y+s6d(R~*?
zZ3R303(bfq>DDmagM1k(k}qpeJ(&g~-LtJP=|8;8^Uyj#ZbqcbIX<Mfdg>(op^Nk}
zCh4nR>N4q857K3*Lh_#Fi838TzGt~F`5WM;!>#k=W<<W6<3s-3fY26VaD3$=f4Lyv
zJvgw)SCK+I*paaac09{x%XAStp5?ym1O|n!wr0xBh#fh{hn*)uPIkU@v2)m)9W3%?
zC)9%-8H-@YvwW*e7qR16?#s?lHFS#g6S*0&Bj@<A6Kip@^M#9@uf5s9B42jGJ=l@4
z2zETnugY{0JD%mf>}=6O?^$2S&4?X2$A_Jpx|5y9E_U=wUX~b(eA&tC!H$eYu;W?&
zt4tTNvotAB;9pKINx$pIti_QQ4@)fP_^{JAx09VaE_PzP*})=Tb|O63k+BGNJj;v9
zbW!hkmizY3t&q@{)|PTJ>K!@9hn={WdP`vnp1auT>dg)o`LYw~!H$eYu;W?YT&9cI
z@htacCp|25n02JwjM$NL{IO%>ixi`V;OU-=r^((tVUaIS1wD9@Q3;+r%ZJItAx}J$
z8Go&EzrbfHt!Z*QVoJ{O&(zBRCsW_Lm|Ek_6c+h173IN{j7l)&S-w~%j+lxL`WvQ(
z1R2k)`{j1Tl$_(AsqA1UQ%_t>o%Uu5i+q_X;=z=RikRXFp&o-jTc(cG&l7-;`ejF3
zjC>0Jv$3Hw(?z3)@HBAvyc|v#L^eL6V5q5e-??~s;>`;d`SKF&!OLBlRPs1I%RiUP
zi51UsA6EDa-T2%ZeA(O1$vOUcs%3Td&m$L4c@d86MPrdKPsKfWl2Hkz^DGaLi6f;;
z&F|5FzD%X(Hb(PBuZZqB*21WiW6z8VadPpsi;KG6Twswe7bQKos3=oOJ>ywkPA(T*
z<oTPSb2E?ejWu3wM?*)>@!vIt!kkQf<6<hon<*^vWva9XQ!*;iHJ;@iWa3EOJj;E1
zrca5`p4JI+GvZ0k@y}BOo0F#pE}mw2^MpmdJeBp}Nk%1j@+==G6GuFGmizKFtyJi{
z)>U#d;z`c&&(rFBPM)5*c-rF46BhaMRNjLp8I|D4v;19|I8wf&5r3_G*_Qmqhl=$>
zxuLQouo=&Ms0SCU=z;y1T!|#+S?(>dO4+N*hfY$WZcFVv1+@Pn?@`F;X#Gm60YQyA
z0roQ&`T2^W&83(|B@bF;n7n6{arv*YOkSF&y7gy&SXNaIt^UujT-<3bWc9#%Z(cxi
z-jNwW1wDzoDIvn}Mx0l<hoBOV!H&nGd=La`P}C?}awEnP`~-32;1C?Y&C8QwLbvfY
z(MF==-r~IE@?&wEkazf4SNZSJ#w$}VLELLfT3P!QxVOn=ze=}pW+0~s#)+;$R(tz(
zx~@h=y$Q*3)6=lkZOSbV)!N%Xqx9!={erG{=z15f_Ir5w5-x2N`&Z)jHQd@ywSR**
z`+d4Tz!GN90xWHU?BC*3ko_SQJ)-MlxX!U}h4LY<*uR4Z`}cTxf|nog^3;|03{%hX
z@*`e;!pm-KSla$CNVgvn+1~#1h3=41(Vl^9t-;H`vB>@lU4NzPZ*={gt}p2N2VMV!
zt3CD#Twc<1E)a6>H2V&KGRMv?@^))NimCx9`M`_3Q?*cASP(q4u?*=t*B*@7>P3F9
zxM2&iz{6boHfT53u3h9=_d}}W(IKzB-GD2A%zcqJE@2F2^{((Zi#5t|w0ST;|0qvc
zy$)ap^#>yOpO5lHvbtCJqUxcQSR1M0-Rhy`!`v0&J<4(RJOnT@ur{>k%HurwrnZLE
zIC~i2g8-OK-13QADP*xYT*lh-yL0A_wbz4QhuT<VM>QO4PZs6l#ccxIfci<|Hd)->
z6t`*OHbdNICcqsO<88d<vd@B>eGXivz?+`&Y4#LI0-%NBmI}A__Qm4CK@a8<4Puh|
zh>2s9`;HwxZtz&pPkT9_4fLt_75=hbXlr$L+E@q!PQ|cm5gwCn1ZI~mZJblsL?N#w
z8Kt6LM{X!Qnv5xej49Zmr~xtVXr5Ho*k;Ukm%*pRj5fA8?hLAIpM8bTE@#Y!vtfD4
z8(D=mWBFFRY{yF$UUuST_Z5D-yfMAx0eCP6-6}{zug=C|8u8{QZ{Fq8dqKE(Wd)-O
zzdP8_{UW{eic*lXipDsbH~mP`yo$yI;}Zld7!$-_b!RwH^I?^YzJU+n(Q&M6{-SnF
z*-Jo&LqE(2at;6DXdfP4;enNn(#A747=&Aj!>iXSKN@3HgEv&N9vRgfnP)7vsi5a6
z+L(cZ28<e!ICNy1{r4;Uy=q2Pp0A1#8SZ8}zvzX>$aHOb5y-djfhc?mUpFfBwHrI6
zWcjt{&msbB%VLajfrYL*8NyUf3>CV{`^Nx7C9sZLP!dBd`l|c5g%3xSt_qHlV~t3g
zo1;j<QQ@on*;=EaZ$W{pboTgfIpKY)8f608xmdwePOP-M%8ynxN*Y~qW+ncwSm{fw
zw3LV~Ah_t@!-ZMUMsQ*C(;pm^vnG$38W>sFEfuq$WgVn>EUJdlHOh|;1FtkF@;MTF
zROXH24SgyB`@c7jO{IzK|K2>7Koc40{C_czkqF)Mm|X$8`oEdVrg}|fG-u=i@L-<(
z%{OK3mvAIsz{?!e+PC2{&YXHg;an=1JI<Ve%9@q21y;7BE{$_eMpOUu*$9aHZzm&E
zT$pMm2IS&D-PN0OrH)b2n&ldVo3Fa}_};2xw6JcIig?Ch_zdRbI!1NtQ90Y?fAev5
zjcR_HoT+QHwtnol32n4p#3Gv8JkkA{J74zldPWgu{akL0s~FFmXAO+8o;g^@CbuHf
zd*mu#-_RKT536==WDNa>RbMtT2L8jU>l+*0J*&Fia@?lNNf;>mx8jV)R@*g@7Fqwz
zS7{s0GiQ1kmX{xDVl?o~b|K*%o5B(+CoCxPsZEXg%v#O|jYrPC`|v3y?G>Y&Z$+D2
z(JA*euNcGrVbu;Tj6wgf>c3kUBmQC4^)3H#)h?}!a-L9K(kqC&C;o*;vjb~wRAXhY
z@LH{nA`wSidc9fJU*|%{GL<U)zX{^MnIK4n(gaZht?mD3YaLq3oNQ~vvMJa6uX%tT
z*P3T=JEIa?AXSvtJV>~_=9vuRO{{rRAeF<KXE+YZp>T1nc`(Pl=D{L68qxn^&C~sV
zFwKy@CqY-hWI76Hf@y2$HU4{hW3BZ7l1S!j_ciBa6U3i(FoLXmr6R6$G+Odq6OBk7
zd)6q(J5Dqz@buWQps7=EIlK{I_fBh{5}Y_<#L)hu(q^S4+OsLoegmK++V{ajn?U=1
zxV5(*gzH@UA-W!>>k+uZitZ>q9D{4`G|yGe8KgzTHN@0(7Ba^5OSC&qr9>$3p2$d}
zz><!tSn$Y%lfgT44SmXje0e9Mk8QWama|lgH{zxej{i6O|C`}YB9w;z|2_ZEejmH}
zE4aAECg!-uCKlOIQ~uf5>;=OR7PVdhiT}aaM0H$N+9=K&buku2S+4_C<a=qDqJfDi
zh%0n(#ucnQqN`CEJ}VUFfZ+%uv0iC+IKsP`y%55okrT{g-wmn6A9n?hr>q3sbJ*KT
zNkue13SH0M(#=Q-u-2DKsL{-xM!sUTrChVV6QcpXZN2M!e@~+!Yj>Uh*3*cwc95#`
zV((j9vo_axTwkMprPfdaMu52g3!qj3^l>laytSVM3@NILjN1PppxgpbjXp*K8*`oW
zK1RGXSpq1iOA^!-{TrZsWnZIV`I^|A81N%SSt?TJ6?S)?pGG`6!FZ3Yxz3Lbf}l>7
zM5B={-G$^mNPz=X=sKUCXf(CH>nd1&onJ~cDzc30*?%S)#{$`50x(c&d%)Ee9H6>v
z?R6gelVP*&lVMD6ZH?lYgN>MS%Us!hXfzqavvdEPuZcs93D(C5)>LvYHT+g8a&p;Y
zsBz!=t5g6-u0vXsaI1JVA$-rao@AAGi`%mr3DVg|b)XUFVQY;7@IjH$E3A<qN`ASH
zwHk}~gggzl^*X=znNdfQsO=Lco!A@U?%oK60)V&Q2`GEqaN|9NRWTu*xz3Bd@aWfy
zE=bfjk)L??P3R{a`lhgY3uSQ|y6&-2RO+Lg8Oynk{ItnFFv^&qSi1r>&Q9_cc$@!~
zz&qtA@Ub}xJjo>{FM*Hn7Wj~{#yZAQauoPn7bFt+I3IzJ`2R)Ve9!B~XnzKn*PUR@
zu^yH>!eg`q7nMr9Z1A8Q)&D@wjfUsg8@F@pjhikRdiBP2DDY7Ke@`;rSJ+QE_Qo?8
zB<hXNeR|{iU-w4NjCrZQG;ikIrVaeU<7vZ|-S<tSmtrk+LmCX7##oE+Z>AbGttI4a
zn$-&3;OR>4BAyLmSL80n4^K1VtTp^K=r-L*@NDpGQgDlsZu>S(3^z|=LAGF=D$g(`
zvUWGfIKd7@Nt`7-OxjG}wiH6jF7cMpTe0?(2_nWe&4lT?znqPXRltgXG8Sgql)&gp
z4Wm83v*`<G;@d`J>o{*Xtmh3LHp^Jxi5U5n?D=e8nhCl8X~t75Vq%;*+nDZmL`BXq
zW=H*nx1<Sg>DxKRo7RmI@g4&&$hKZ8G6kOf@myo25|!;$;yz#w`_{AP8}qG4q#AS>
z|I(e@D({<O6bwECo@GjT{_JbLDF1lAVdQnLhv<|(c^KI@_@NYImQ}{X6CWyN9O?Um
z_!|q1V%BTk2)<kZ`-9U1@SRD|b`(FFve4+_neC;1OGS5h@=WTN-D;5$2V?p#^lyc4
z<LqathE1`uo6?x_n$h3$ZRM>2(v0p&nTPtn4|MvS(c#N8)6W`({Y>alK$p-WFN;<H
z3ILpYLa&o%)KTE~?g^0Zd|tx^hzwe>o8I$zft!ChpXbb$mqC+!Nk46PA#QB7`O$fP
zn;XlmcBvb@w0y8s<ka%dmKzRcogkI)V{^c~t$f#rwN8_>$sSI)$xE#?ZhAH#JJa?A
z7|<pD8ti`0sO#AP6|%6~9_|v_A(O}Zt}-^+b|N?$CYg|ezS;%9Ve+B1U7^WlTp@=F
zZTY3uhHjNh`Tf;Khd?}-;CR+7Kkt|h*6f~4Eo!XIO;fhO`^8OoC9#%`4m1!Uw*(=d
z-{fJ#1IoY`OpL15U;ZA>zy1bJ(i)?sHP5GBBgmH?>!(PMRi+1CXsl(ui6jt#*9nvL
zsw*S&CV%k0QI36j(-F2dk~t|)xM>9PZflJqf%O3`AK6Hcwl<Urp#HA=so1}C3ud1{
zQ;P_Z1XCT_LJtA>xLvu+^Ym0}5!UNd-f5M!n6-}&+#Wf>?UplK5_s4K<GFQ`4DVQx
zkYYUM1EZ03hMZ00Px_QzJN0aU+9yfYWaxE5Y`7&`op-upL^+;rjIz0<8!Nc<l4ZV4
zMk%)KQ(hnL)=VENw)il6KnQW8H?!*ncogCx5aOGgVUd5y2j2Od;GM}C9trR17UPBW
zdl{aW)|+%a@|Fes5Y#`A1<?$KBQO8{!`z{Pd2WGT9cizZvW7v*wf3Nn$$iUPuMP>3
z=(oHEoC<A)UJ(oPGL7PaRUprC?5k*NtPkKyIRP%8GvH^j!Dad5EMvB{oeYo6+R7b9
zd21Iro9J(MODL8{124rgIciOar6H@{!Xf*&N|k!w8pxA&8AaLjTYT{@*q(dKhm5H{
z+#V5Pob1i*L}=?8o-J7hG~5lo#rr-WSLXzBWzHa}XDVhJo2*A<cqqVSdyUf8Q*tiJ
z@5n9w=3ba#eCqSMg+t0)KlRt3UA5eW{WMs!4=_CT*8tx*_iW(RL#D6}diT)8f7U}I
z4}e+Cf19s>yS2b=ZynEf+grzviOvbX?WN;+pslNOOxsxte((%!XB{87HFAPmHD|ck
zL)mo?8&wr+7a1VwIElQsoK1by<+jjqj|N^6G&zbV%#!iU!!z>2;WaRxhGaZlR>WEb
zjgUFBb2$Cj*t*R%VQt14tR^46-D<JPK7rF^`SX}jQn9AV^twHem2x(*k#?KkI$?b8
z*#Oy)Jdh6sEiyK-s%ra@(N?kUl7W(Y^wCLB-h*;B;o5bZw?Acc@@(LR>tqhN_`1_Z
zGGBh$SZKW_1NL&IPy03}<&hRsk}EB9WXcZ&Pl4o%pmF|P>1VvL#p=(Megbs)b)_Fe
z0e};(bXW!~TFoP)cxEhR23O7-{d12^9#eKeV)FlC?>*q7D8fEqcT-7bZ}%XykWPmL
z5<r?#r9)`aq$VT*a)u<30AeAah(x1;lo1<65W9#a77(#l1Vu$fdT)Y=G==Y(*}c1G
zwj9wnukZK!eIGx)+|A7Mf9mwv+01c;nZ=Xno-ZR4B-@-BUqPD}u~T25vkt?<c6x>2
z!|=1e@L_nQf64PWi@i9fRW)aeIFG_@XlSP`Fbr-5vUoc-(_lLdWqBia_BWAhLrGVZ
zLwV#5`T@qyeQ+|5rmj2b?jK<GE)ekH&W%69aA&j~!FNAKW{Cux1B~{XkbE10@_joZ
z@08<~TxVRwz|Q&ddMPkvAspu)1Mb(02r5!{C$-u5nC``sa<ek?65!T~th|DvX;X6&
zii$Ifb0+8H!}H_Dp+dgu5V+{Qi}f?dT$WNKxM=2>c__;i;76!5Ua3|RFI{(C?+FPr
z3#KK^$jmQJC@x5tIxRmTll_;OH?t_WC}CPrZvMoC;z>CP-6t0m=N9C5%PG#uDlV9s
zknR0aJhLz-nS)HqoSu^~A$Mv~aRUF!@N$X@3-YrWG{EKvCMXeY&@5rdB;aUgo`jry
zR<;NP$t>oq3i9)2f^a!pv<cJl@)EK#3p2;(=H(XWLb-wowlZf<D9)Mc6SX8^d`?b&
z!sN{CoP^97ncxo~%PlTSD4J9-wK%I_GN@kEOmNMJ$~0LCGyFfaS!J56<X_mVVkQ$p
zl$zquw@yT7DX#XYt2w6E9UQlGC7clIJ_X{m2ZS6%Pf;?&QPB+WV$#f<qND^!P0BAw
zV)4a-bbL-;!Hk5$sRfe@i;Z}ikqg05lv7M+Pb9TVX5<!6;wAGlC+8$g%$*JakXe+F
zo1c)8k(rg1Q&>FCAAlJdfWcxog;fiN@6R)sBqvPE2XLM_J#%Vq=J-620zxw%;)m62
zZ}rK`&Cf~5D9I=&YL=5fJ$GtBezU@Y!bTRJ$qD@n@^cy+tP69dPR`5+7>IVA4b%{z
zFPNH}&(IURJi#p4*$}+U5D->VA%=56@9DXj`cJ?Et4t`#&CAKiU{-^K@tH-FroyiY
zkmw8ZM*70%ofdoVoBae>eBbOR88!UKFJRxVZFgSpb&V(I&<7_H(#qKh;!^7x6giYF
zEvH+|m60LT&oZ~Agb4W(hGbny31b2sG;eqZRI<NC-dG*hAoGeqM@}WxOPXd>JTOFs
z8&)u&L{T;&Gk_?x-qWO~V2S?R5|tKyB6nLuTt{CR<EnWB4^tkcqMqU23=wJ@Qbga+
zUbB<(=@4eZ#}e%${4p<Lhw4>9MBZ;kPQj59YSbE`r4v}1#<nLM8n=>gy%RRIF20dL
z0#tZCrgO5Bc{5|~h<O7Co|;fFb#g-HMCgkr=HzEX3z-T1?$pezoaWH&=I3VR7SBw`
z%F8S&%AEk?5Z0GNA6{6(%0fZ-#YBKcVtQ_N4s_U)pue3|ke6N5ECI#{Ch<V1sW~1P
z2r!{|U#t`76y@Y+@qTmyFb2s1IY%EjBs9vMkdR+coG>E?+DRBxWJ1qdbZbdtrlCHV
z$jSCKL%cqY_z!GT6396Jfo;0+QI&&nOtuk%?J|x}(@f};HP`~ogm8yz8YuqZG!v3*
z{pxf~p!%-{2tTxejtNwS4Bu3!w`nRg;xVWPb@6!76mq^A5m6VS5n@K@*oQ*&vz`tz
zA<WpoD!V|BHt)bTCq=JD=1|U=o-=i3LUHb7V-TAK<5X`~OV>>xHDY0K;O|lycRnOA
zdVN-;dI=i_7#%*x*T*5O&yTQlNC_PhlDhT2`KEpYZXP<g`?xOY>Ai0nkOa6DY{?_W
z0fK%Gv6(TTE<uA9>yV;@MTEve`}gln@9o>^{E5W<|7{m^`o}KNYqK$5G-{J|PT$N|
zoA{hQ`d9PTTGd|zZml_2ZquZ`ssG%NGfjGs<k%vNb!-tv`E)StGmgM50y}~9#IKP@
z<r$8~DE0wyV`Ny2F`|-;feuatFor_6)g)1Uz0>s+|Lh>e*IL0r;SR9U14k=6@jqoT
z;v`s{(9t>bBjaL()dTU6!x7qMPvmDYHp?#F#jCygzJ9O0aN6%xu$TQJOw7wDOKkMh
ztI;!6NK|?JzR0N(*@VjR!%_az8tK)IOUFel2oSX5hAb%-!<*OXa2qhNq>B$keoKD9
z9Ql&sqJyxcxC<x4$i1)hD~&l6*<CEpmvkOD1dB$eZOYd^3=8`LJ{zSWjS?!L5vnKw
zG-}{nQEKjT>N=x#Idq+F$nbTYtfEXg8u^W!Y5-YVjT9dcuPC*5nOhC_u7ItEvtp)J
zqhjuDp}RNqMC4CoIEdzrNqvp)`RPh$G7cy6HNN4y=*p9k(ISD#Uu`PQUmcwNHP6vs
z_xQ|gYS?B&hR<IF4|U4lI}`b~L<gKBO8Ez8A~#F&az`&d;e+R1oNw{s?Eln@eRVJP
zJ_pZBePMCeCx*K|!8s;(4XiYG4Rdza8Ao@W^4ZhmuH%s5a~C^QJmNy+b3t;%ZpW4O
z-QJ4IJ#*ILndASdXR`Gc`_sQ8Z;(hD$R<{><g2iY)D9=}3YNB;esnc*mq=jpSZ<|x
ztiai08HSy$M~=t%>}>MbNXQU8wofKwLgbl_9-Hn%VjhFH8)x<*QD|#qB%R&Id26JS
z+rv4`U#rLp>=HJGLp{;FN;7<!v*9;78vY%hxlD#HHyi#7LL$TD9~=$;oezl{ev{eo
z<^QGOm+KYf@#>_9ME(w7{?!#Qf5rMfc(+|mGBehB#Fk!7(uZt|YLOKreviNQnl^M|
zP?l-PwocdU?b>9RL{d;W^N?-5p_hmSH3<#b&;Um)CJfo$at^CLdz=P1JwY_vZPIR#
zf$KBv5liOCSq6}GfRo_^;tg=WJ>~&Uw><#|IL?YW4{)4m(l>Ma(+A^8A96p4=4*dV
zwfd7vGyhl4=3nb*{?$IKnQHY)v-w>~q_6zGqxm=bfVlaevzUM7e`@~kb@Rv9BmKx>
z5Y5T_KUbRh_c)p#t{dN*XM09K+UpSfSIpL5)qrf0Vs#vA>__`>xbZ__#wR}6bmc!a
z{!u;)rVSgD*8;V2>x@>eUK8>x82~DHon&g|`k^dSEB707bG7n8O-VfT_Nbgbk9aJF
zG$J`TnGbWu?4{Ao$PAHS<rp{``Cc>9oXoHz=-!+(6bbmma%pqYnv|Le6ebEZUVIB_
zCe27D`Si(DQd<Nt4Xn->p(v{B*bs}wgogOMb11HJ3dNT|V%v83d0iF%$?uab2)w`h
zbEjDR#0SJ<alIakXk7I?opY!2xXM{AQ!|YEBxjm*Nd^PjpWOM=$rNXO8kpL|(<W2U
zGp)%vS>5L}Cm{R0Hsz+cU@^t%|I!qSqbcMY4Hc}z?RGvDOtxqZ8AA8GyFEEC4|TM~
zU>^{-MaO;SCaU$mfZemRkN;I%L^~VfZbxI3_;fHC<4%(?%D?GIehiWyceKW%J|u39
zxfW~O`JY;&k+U^EbF{|CJ{?Tf_`qZhy1YBtB=2=J#x5TaH^vthV|?(R8l#1?F<kqd
zhOv?Ry;a?0jBv;h>dEllWQ^R<0J3)F^?X3w7}|bwJqh3cU)GZwosBWX(HMh#I+%>n
z-)xMR`jLC($&SYG_<*=EhFOf!zmklBCT`9RO?nS{pg;L0z*2kqZ~Dk*{{S-0_Nk*=
z2a-F<TF}aVs1v&yWtoOL{bYVbuYB?#GF~Qcpo02X=i<$zJ=utp`B>+T{q%t$a5UOV
z@WT+&gnVO1Fk&dVEE2GxivLVwdVg8pq{8CzGr-M~?wpX8)gmpeO^dXg)RwI>bJ}EP
zwam%Po{-%(t3_%~yR6oC`gR)OtutZ6NuK=O7P_E~yB2+LIBA}6EpobZIH@D=-9j%8
zC*A4{m%RfYe)jP&)`s0Bh-4mUD>J)p>hlrgau5kV;P;Ad(Nm+rq68;%iv}N{v&WEF
z8v_3PL!2E!@3CNOfrE6CB+?aQNn?^~N02y<d?*sYaB~>xYFGBD447jI;B07GUNw{S
zk;o7;g~Ccgi^RvK_foiZ`d<3xXyOtP_{rIlEYgWgFayY7fEw9kh)BRk!;7=YJaU_v
zAP6|p<~eF@k-`*HgKho8E*(2KfqX)DOdxy60u0S2(j$H6Y}1F@&~ruG!{s{og!OIB
znk8I2N)u@8a58}Y_P9c#w!@>T2*Gm-!i=WHNpbS;`xm`BwpJa_pDggsvyThx<0AXG
z1RrI!Y2hSNyYph<^7j`&jUvxqtkB=^VLYG5-`vB)_$kQu#x*;Bo<5wq2S+B!=l4_f
z15&H0acQkz_u)>u+ppo^YHQ*&#<{)!;DA%-x5+E7`FzI)$iSUnIe%(Y{>4DD_I^8j
zNW8)S=m32Pu2(}>bZj^fu=jJ;%rr`D=-=CRrb(YD^9SMShJ12`1RVr_88>(EMKsj7
z<k>hte<-4JA!#NNH>TxPg*Ps>aWZRMf}kMX_J|s7p%_M*nhVSBgY@cD5-*nZ*W3<v
z1fM^qG!zL;)6jeyRk#=baV!-($5Qq|r&!7ap>5}(V<AI`rOwmIv=I3&1IZdoxBHNI
zEKN9Q9!ZTo_+Q4-JUy1m@3@OK%d4?(SWAY2=>Z!L@L-~SOUPET-b`BG-w-@#L(0we
z{0?|OWli}N{kc}-(O`Px8YLV(IQ*e*VsCDGOrTuyj9u<_osa36&nB@-3v$vdca&f5
z1%}+m4w|0!I;@N2eGvD7wMr`ze8^N0{ST<7dx0eCK0w+;>9?!vV*?SXbG*`;)Tsbc
zEsmrJNT$b#59m_+A0svlnfeodir8d~*7HbGa1Y>2_Y5Hkq!*TfwE<E$&XEob4hf6$
zUuKp5h+(5H7S%ce1XK;-apDPw^he?*S>Uq+!)FG7=g%(wIiD1hxfqtkFY<v`&^a6l
zTdw0F)6<+c=#rZ(wETY3H24|FqI>44jmfi^7q`%AdleQN7Fuah;VGSuV4+V83w>sR
z|0pp0<^b^ALa#qaTGO=;l7Zv^#x|MBEA3tmht2fVHO(YFN}AJF4?`e@9tJagbD!FX
zgu^#q|D=yp5A%mAQ9WB~SV%f-s%KYh4AkJT9zu;Q!1Ww~6P<y%Y5rPB#*%IrkXgk>
z!Y&*LJqdi}T1Hv2P;EpPEFukqCor3I$qA}Pw=5#n$Rx~;8z$Q#|D%RsGR^Xj1!8mE
znr9ehz6E%$Bk&w&U~ZUEOUa{TH3l>p#w+1U4ul>b9ZRQtOWLAGq%D;SqGgc$$zeL=
zQJ95%hIw#nd}I;&F~b_0%|gFtV~s<GHI7(-4>$tvbq40vxbPTRN`jA|fHqmfE1`6R
z1v0Y6d)KrEfAap5CrCZH!4Z1m30T%|gc)&@)H`CXIZqfSN#qRCT@G<TYz~kfNA#N0
z%L3fZ5x9#pFgMAA%gJJrjR8$2@k*G<fl$qfJ5r%mci2jjBF{TQ?}fi)K4!#CGS?#c
zQ-(?Am?fX(GYOac>s6#~@H3D`Pjm}QB+pu)S35$lyasgYYH~mM2m_jo;+1i;*(kFr
zW|ZI7K%5*pLaRSR>X9Ru5jV;Ki{vW|qwF<Hz6*$rIN7K)r=!=xmR0Ccx^SaXopySW
zR3+g@QMfa7*f-p~i|DU-K;5gCgT!-DB>FjUvu}EqJVokZP-Yt&phOOY0%ljmZ1c$T
zq_N!NDBTEuNiWQZOW(~_`c;N~x|pT!2mogLOu+V;WZ{q<kVB?32X3Fdmq>py7lWGY
z;}vxd2SWDgc+@liyn**k=t2Dt51Jp;f1iyJ^#}FqIL|oy>*qc;yaL<SuOrdK9nsiV
zQI=@}|BNwZeP|t7PCh{8^ffJh@aqel%;Wfjqx82|Nmm<!QR_)6*=a|xe?949L(u;<
z*mFH)N5J0)C5U8N0(#bn4XmDbS+ULd>sw~GOUrDN(=NMJ>$KMGvRhAJX<03^+O?aI
zohd9UZkeexroX;VI#pTh=?)7h9=yaj>{?KZ%R*-4W*1LdTo%+eH5ERmP0d~G`7;P`
z@GJaSg1(AV7T>H{bNcXR5}P!Q-xrYninuNrdJI)<)4JsIwo0>g$x&~Tu%MVEM9X~b
zdsx;3m#WQrn`DqCsD$@YwQ!|hmtnncUJUOAgH@=ybmcAuUhMOu5<)jESHp?_PPL?C
zwD28rm0&hJRF<SFH<C^WT7Q@h%BO4~Y1Z<TN6H{O0&OGdAQJFH+_!H8oGd$np!Yy6
zi$wIn_n=x#vm;2`L{5kVEVM@WCzvnVSedss=GDPF*y`Z5B7}bSKFP2w3o0O)zAWfI
z#+C(Zda5&7Yp{=+?4uU@sC|q+058z(h(qZy$S@WJ>%dpbg5ZOYC@cuRqAv*6IOeb*
z_==OdXb}f3f#C{g;`D~mp6vdB<dYYe0(c1wEj_&B#L{l*p<itJ9g^i<vJFgk@5N<9
z(ZYn0VOd;&fo&sN?_-Froo30<lwzYH*-ytzlb#=Re%{4}P0^t$9k?v0HaS}Xw9_1|
zzW)v^9WBSx4jLSGGX#4J*b<3f6+!28ml~pb$G+1g@h=z{3feCioc)wEATh^Hrbh~H
zG8C+R+@xR)AkzC(-s7G53`PVkD*%+rfzYVB23;AcnD6(hrlXrC?;m{u?f=aIm~1wr
z9cY#|U6l5tFX8Z`rvg9|&C;e<T-s${!?^DL08BnKq`l89?OajXC0oetWMu__o-#{2
zx8l-v+X~w*n*%WU*pT);v$XGu(iUzbBgl>l0DW(k_T7q0`}enGFu4$b$)|?2=giXn
zE=t>QJ8XTaC!8yQ7l@oN%?5w3xU}oPCnHJo08BnNq)p~b(73xX5b3q-%wBRMy>UAU
zr=5Q!)oGu7B+2(PiS(!d_)Q!fjWrveFiqa<YaQ4+j6Su4^d%DlaQV_uA<L{nhEE0F
zP=LX!(;t3<@!ee&K)c;6bH+cDS)*CMkQ>O80a$%)2>zH^aB3rX%06(wqMf82dA$OV
zubQQ&6_ftZ9#V&HT`C9Dgk2#0_5iHDF{IySmVS#*dWf9PwBK%$LylJf=!jY7Eftn|
zB#AufT#>dJl7^o&^&}xc<csk&B&h-z@f-t%a>z**%IJ=>YQEZurcN7<v8hvAdSyQe
zM;D#F&ALqEqBEP}3WbZ#>XgqqKoTV~01L-A+d8O96EYkpvsq6N6x27{1Pa)h??ZCU
zh2;S!_1mq5vK)Q%Vd(Mhup`)cnB<A#@NNHTM_|JIpdG=VN60LZz_dHJ-Efd-0`SZ~
z9@zbC4D4<@Mm{4iV_}$5eDwb&PUZ8&mrv3w$4RoaJmn_-%#L7_s>F)~+`>QGl`Yeh
z`eIp={<|xnKROvInn@T!A9UQElq8zjUa`B=?Fz_jyE%CoGQbJGL$dVhZ{#Apeuv{&
zw<c?z^5XEV$)Ho_t;x$L18z+^t7Y2eu9zuKIh&%VlPS9SR4|?K>H-<q6y;~ml22tR
z!^sw7d_de5y)Cxra;kD{fo_Vnu^&Bpg~XQ6x<H~Navz8!OmomvSW=LF^htyeD`3T}
z9u@>t_D7RfJ6V0D&sZj_KV`Q1=a<P0N!sXS^>=(g-0II*to~FbS-oPj%%~uK&|+=q
zRU(lC*!;f6=mbvXjnRQqOTLC%PKDzBg@r3N<@FX^AmA<d5eYVfwcn7}8H2j4Aoz%%
zlnQ2-f*JP#=@Gzki|CnO)M|9hVc11TGSde^3H{uYz|qvA)vmOFigyesx%Y2Q=Pi1G
z)V599O^_kf<J&`&Q6chp1IgN`jq@S#km~!Jxlz06x5}x=6$_~}J*3JXCrX?|O0jde
z&-r4~LY&Nls`NK{pGzsTA>cjS({=>BhZ8vP9_|ghvb={A%9`S#b*06_jn46~(=i@?
z0-<f=;RnbN;^9bD<$)0SoMSxv?nC17u*(t;Km4chkgmrAZ5OS)PGU}@y3UsU(L&Z>
zCkNOqWTl(W(4+t|n91P`jVaf3hQ`RXEOYTW89zfa+$=X*1sZC|J>;}$>^?{r$-B(O
z&(P#o0O;0h0P!O<_f`PtZVrTI0)tMQHc<NOto#dNhAHe9#KIGmG<n@=dIS6=>#+d(
zAoa9)^LDslnitF(J?k@#|04dar}fR-Z!N%E9D%=d2IkH?R9D$ZPGLaa27O&m8A$%b
z$y|X`r}Yc#tOOhC13~y16ue%7>;_7a$bq#hC_KD2IBs^vv)mcz{J<LBD5iBi(nx71
zw>m?6!e7$bB0`HZW~1L?7`^!!Q#>XEF;o$D7{|90I^+!62_0rZAMA)ez!{xeKD4Rw
zG?|J4{g%HSCv!tiJwxwERuXIoK2BEpkTN@hi7Co0B7w>BUPBacQBgHWK4V(jvA6uW
zW?=cZ&d}86$_?ZlEW*OD&_42;7Tb(6EdQF>HtT@cu)OcR6Fbi6;r=rQ24nP<9C5#M
z#^p9Yn5H~J{=|6P=Bv6ZL&z1J%x(VX89myq1iXvZem6%u5VUQj^b$FkZ0<F|S+mX8
zahs#H_%(W4<iBJ+<+OS4wh5~;`r1RhIPS+YO4HP<VxyGtL43z|X&V@T-i$OgZTJpE
zSw{a1R^eyECmG|M4Q-TO63Ijb%}@G!jIa>FARf@#0h+pq#jvL7h0Y_3S-(4tH17b>
zY)2NiK?X?Sn>?4_aDy@~RHg=!b)>o2hr~w~vwt^_G;jMo;7HS1GiM(<)1=>Lcp&2@
zMUlvR*aJN7X*VU0e1emC+`sp`9`{xPUQu?~5%lk&3=%o8xJPG)%WQnCpB=8>Q<+Lm
zV^B8kK{MNjY)H9d{&9FLb`B5atW$VIoOK9~Fvt+XV@q$Pr6e~nkgVZR*N4QzLp^H_
zkFc|q6CM?-EGwL?akHZ}2Ksa`P4v^v*0_|eT$bcKM{DHzkeD?Z4TYa&p+&`T9qiP_
zrJl3!z(rs0POSg60O^%vA=C&4s6gwC3iQDsrK3a^frP^93kvTyY+{s7xmo#?tTa=h
z$S${``gf7N(b<>pIr{Qlp9f67d<!y!$SxSB43gy^9eugohr}cMeM@A&RY`uUSY&_h
zY>nVQoa(vsheJKTVz$QHqm(g{9BUw1>v^;fiCZJ|4|6@g@}FAcJ7;V3akNHHpAM$j
z=mr@$HmI7Rbds|ijgjF4;>PG_F-EsPDyPvykIDw9(mUTAuWXgb{UDXEF7wXtQkF7;
zJc5&XXL$b~<<Dm;HB1z&b3^rbZ>81a!_K~X+tF8V`b=!{)oYM}eN}#bqEcIuzjbuh
zH$EiptamNWdaaV2Rk3<}*4Y|Y9j)<~PY07VE}E@TB~Mu<$+gbuErPWkS3l=%5x6y^
zbLM({@jtc3-_F+PZs=gWC!?!R2a`2AK?aTuy&jKsG{z_&5I06oi!nN#`!DNpD4nxi
ziJ~i}D!l`pI)zEd>0(zjO(;@E1bT=aPN$|l?n<E_6e+XGqoAs{aS-P_F-uUE5ggw6
z4xw{?QKEvEN$jxQbfrtVGEJ!_bxTedKdo55cpk3%cDgAXUanH4zp%u6gMLDzq8xbH
z%lLxnIgM$;bR~m4gLvzQX8CobFXLq1W<7I`cAcR#776$U@1rdFeKUc^kRcY>e!_@k
zCV#tW%HeU9A$c?LO$CAqrWt}OSl_<DCiWh(O-*apx^;HT)@?GgTeWK2wq3iloHlJU
zv)g2~%bd_QtJMVaA=?7{?0)LtYf#&tt37W%SIZK-=W6MRnM!<JcoQ(6>LvzzXQBLw
zz8%=Wrc<?=t(NRmZP^{lmm%a2Ov^f^@;P%9c=P*TIGua>k8|aN?on=(Y)H!IDkmi3
z`qLlA`We|j&e6;BlmQ|Izh7#`eM)nZU`KG}KBZhFfUT^-q=jACTT3ClEE>@FN@0nr
zn;k*M{mKlHz!Vf!9nCf70VO$@jK-+&-j(qr8>etXjsBAkSfE@K%bNJqaOAUPq4KCq
z?!>5Ueu~EawVh~#qgh=#xmf8j#Q$Oo;hh)o4h-Xk67Y_T<b;e2_7aS7z86|#WUw^-
z9U11-%!#zy66Ikjk29$4$bi;fs?;I(WBK`bXY5j?BY6ZTGh+ooLH+27K*65f4%OwL
z8y{Ap!!+Z^?uV6HWVI7YHM+dFD>Q^b714+LxT*(%!W<x2Vc$6Qn`UY*tkE2m(QUWD
zZQI#Pl+4<~J0%41OwO!h>kzoHA?fW~;B^a=GiN4b<`oqr6v7)uc#F*6u%y3;i@!&q
zgulFtz3F2ryjcrg4r08h!FVkLyuU$zr3fbubV+)%gswBe!4op4<rV9%MDe}_iM>jM
zvCRetTVAoy3SR%>y^X|p%hA*SFO*zt+qW=3hItQRvv(l1v?ykI2a=@(P5V-*C0F^L
zH&{V{sc%$sa4)vW-LX#YmOi9mk1DsN{^N>O`l#{*IfdhrH!XkS6kc1Pj9y!W!v6Xd
ze%{ms2N@Jb&0u6j)Scw2?p(W~D}>=xyOPb+@~J;5ziUAdnVA$ll@M=ZQa(hmeJbHv
zy)%9MamD&n!fxo%^rsT`pVOa8IL!LEBkbcS`#8ovj-R7rpHPxI;inP?flkI#2`8b9
z<*9^jknin~jsBS?J|rc|N6tAsmXPSAul*7u9-^37H4KK9%l7b$Jn6jC(nF3{VDmjC
z;~~R0NRPsov$LVvjnKU;9RQE%y|`S-my;vtwooOdp}D*0a6ME2Xl?x+2uslmH?X{K
zrGw22UmDX_KB!WQE?BOFgj534`W0eIznt%iljj&Vvrf)t`E17LBcAi-$=Uex0p}ym
zJ~XYhqjd#mn)H@z^k1#~@0H4Mi98Fkc_$F&8(G@ggqpq({`1p{hrDSfMF#-d+mQ13
zsL%m`PxV-GH~?VEH5~vjaswOyIAfL@?eKOm<UV!YwBdSO7fCn(5PrdAI~$;o3xR?7
z0f6`l0L5@1wDWoVyy*bI5nX2g0RY1k_6GpQJ+CAM_W{Oq_p-1An!I0$@b+bLuM6gl
z=uU=Rx|`MM3J6f`*+#T)JJfSQ-ww^gYVq;yBuC&JXJEb`8vhdPR?f$OY-o!N?v?Of
zvz@wLFzpa`(nU7y%|G$7k}N-efqnsh$%~i~m;70a<XsGttT9WzO2-#W@`YiNuPnfy
zIRby|49rbZ_^L9J9KnDllXxXOXg0~Jikal<dZmFJagjEBO=&>LMHKAZB;gm$QF4=E
zl8}q0pqGKz7bU&qCP2yF2A^!fY~+Yp-x-rz<I^{kVWbxZG+DzdTz3wHDw2Hh8Uey@
z#kjd#X()Rx(mTtQMkEjO(IeX;cz44XIcCAf`;Fl{yK(<Tbatc6f<E67{a$BuZk8tR
zD9@8;F`&sTUNP60%`*O4X3=Xr*`UP9UtFZg8<a%y6=uZk@|i{Qo`zjMHcS2iwo8Bc
z7&l2na>9an#1Zo#$BgkmQ0T+-KS#*T60%9DPcOWubRyxGP+XgA;}tdJ5{qXPG9O&i
zHk?b|`$|2z$tC&-{3Xel5w}gFOXdpH+ptZ2&JaBxl?22_1@gsApGzoa`dQF>Iih!W
zM(1MR_#yP}lQ5vkE?zNn%yvn-bd9P+IfGw5Qj+BRFVU;;my}^f+%EGilJ_<2a<5tP
zyKU_9Jhsb=7W8Kw(bqVmbFtTcs=P=(!+<8cc*XqKY?r$$W|#S&EA{1Lm*^|-mz=<i
zxLuA|Bu_W&a?mXKJ{!A4Tt@LiE~BvL=;4>m(db1Fxom3A{pj2-BfnDClSUZOWEU?`
zeGY``(Y}h=rOOs2Rqk_{7QtWA4>RJD_p(Snz_3eqv*cZY*j$f1*e-b%^hu8BInL<J
zF6E84DWMXXj}c9V@ydCx*)Ux%n+A8Cc$bZy@%r?<`H0m=Z2V^&v2q^%|Enp(Ft&xU
zHqfpF3D$Qdrhc#VBcCIc#a)TSPf(U=K02DsN6{=6&1M2njpwr&y7>p?P|O|^xb>cg
zBdEkbzUN`jW%|YrXt6LG%9bP0{^~>{@<fS6#n6ckv6!$DFxjx^xu0N#NBzrRT}>7x
zD9dEgB4>*Rpqg0@^TTvGrhy4qu;#H}l`*6lD&e(eSe4-MdAWt`)(raOE~QyF|2-KD
z5G=u;1qn(>@jeRDNZ(8e$WGm@+(B-#VW-N#XYX!Uwa0vD`d+0@6^2*@hvK%-QF~xh
zYJ?4WxRRMSK4*e>$H#&_N=OuJnDA>)0>Mt%3sOzCfeoYW_9-NkUmVh!X1<`p_TOG5
zsY0M{?}JmwciV!_+^@KF&?f9Ql4^9tet0f0kc7YO2MMVeY~2B+_BC+QPDR|%P>9D_
zMr4bTBStpbD;J9iNOPSRo;LpFwD9x}D8W(83s2>c0aEynJ~ltBjFaRa3?%Dv%y&K{
zwj3jEqMK7)QRsf$^1lME#yBhH+_XB=q(7p!UpF69UL$`aN10Ea(n>S`lg{Rk{@cm?
zHUD-ne-vb3^V1F|m3!ot29VYIsXidS7#8z4UkpR<Hi@DOJG<h-e*PX>ykEYjX~!eu
z8!u%)_=cskB~8|^SSUW@Y>Ny>Ta59kU^=KU(qxPBw@)iqC3&W!F{b;FxG~0Cj4`ru
zjDfmRX9K3c%|bD%eAXXIkxW*AXugF(zD-c)JhZaU;$%MhTJbmCcpk=OR)U%r;0*ga
zb_CKz*uxbFOdBQd*+hH!%8SYaGWiw*vhft^ec!hs<Kc;h6%`ANPn-keH^;y@0ixNq
zQAZ)eS4o67m%h==^_KKTeb>iQ#9fQ^5D&lNbjl~>iWi@U%Na|!z+G>ZQFkg9F2CsE
zvN_0=FOlXTnlD`V6QrX<Txp~YPUhj#{0co7;_4<6@c6np)HR9pwj-z(=DO8}00J_S
z9^D^8=%z4NOESt#8U#Y=dvbzwrV-no3dBss401?6=rgH`>y_951G^$)V7Gp-JD$#t
zaJ3`%A<4zjUCdmRWjG%U&9{n9==Sdv>1rU8C8(Ua>o{d-C}KJG++s1I=l;XFR;)Lo
z)_Sh%6%fs~R=fxqzFNUv5c`DciVcy!bd3Mcd`LY0U%z7RJ6@y<$2<2O&Wf4(4m3b_
zrb!P8(cdOgQo~gxnEZ|%z~gy+v}+)_gp+v%`27kUS;sZphTxYvu91XXMHR_Q@L-JV
z9vg!8v92a0&W>P1tgE#RK}?*h9!a$$cr?xxD-ys#iVV`#uI$Ws*I1jfL+r{vp5VG(
zEX!?kDZ$mBOt2$Zk?6WbBmhAg(Uc@tTXLHn!Nw$L94yu^A6(bf0*=DkQS7YedR?S2
zH3<<RdP^)i|KC&?cL-3~?y*X*(uEUUb~j|a3^Lo+mlq&Is4t&3bp0erU+6&Aq1LB9
zAXZ(Z*Jx(GFwlMBYQTZ6s6B26Ow|STsLnL$b)8Ld-pLey_%tw$w9c4JL6;@FI?38~
zbkHJKjBGW90(Z#iHsz+cXg0-}|I`%8j;4@17%Ets(e^$SOtxqP88|HHw&t#z<YA7s
zxY-B9Y?0Ure)^wg@y>dE1MW80(J779I#n8Z97g2ME;ofq#ah+tL-hBB{G8@mLGA+C
ze4`3>PKT~-;p#%}#mTIV41$8ROG{U_NMWkh?JKQXcXoE*i;fO_&S!U%1D}Bm!GZia
zg^wK__<;|IJMd-r8Nh+h{KpRL9YVVtgY(Y&+PGdNCqOoz15JbV{*~sAA<pioBI!+n
zwLXPP-X_81jv&au?kNAFy-SkhBm>FXxWxOAxIf^{o`L)kBvn?0s#v=_&e=Ev9F5b@
zr;^Dyy-miUV4Ume#g4A8<VlVO%JHFb0}Tpnpx%{cAT(@uZl%&abVe6fNuUw?31h_G
zxvOh1c?_iYhO{_XkEJNfG*~Y*28*?Ba_tKy&!U3te0(Bp*bBx<>u@q3`#mest&ga6
zECg|MLvL3&m3q5ckPjTFqWF>4AmBxx?G3}N?dEbkYd{}YBOCaYeOxz^L$(yH`?^-y
zP{{pU!^j0&idXx&X4p`CF&d<bkp1S=Pf{|0FQ&Wd+EDc9?;1^FY$-1HcReOjm|Fj-
zMsp)N2`ak%+JIOLkABi;I@T!ZCOUAD?VzqR2yHv4>i`+JwV_`Pg2jN*I*zrixy6UW
zt5SFP8KCX&AYY@can{n*d84+*nI?U%qh;vPN8yZ|wH2P{)5p}%++(s!`Tav(%Oq))
zlVO(ofVg2E2yB>pD$OuxR1?53i;e1kbcAcEL}Q+E@xxZ|Jj0+!5Y*e8=<)x#EYVh@
zTqU^JK(gPq+@#U2w!U(FX2mPjIorZh#<=SF3Ip$fa5uUg^FCu;H~Y$&YSFSvt3}Hl
zV?}Nj<kV?51%Yj=Q6tFkRU=`AjSkFo<<g#+u32(V1J_!uy7_Q<^rXVi0M)8dP-RuC
zibc=!A@srfB5Trzvs{@m0alg@Y3k#yX0&}abW<}y1#eu5-BjXqlx6Cs)-k7`1`){@
zfa*<S%)TJUwVEtI=;oEEca7)~u|$@rr4fq>ZSZF2=y}O8dY%W-Y@=r_WcZ>7R-)*w
zlUyImpE!oghdv-4F0a7P0O7LsTH)fXr>PaLm^;2S-0`Q!)q|V_*}QRJcE{FAbH@+P
z?uZC>s?1@*4(<qs48a|)MXoM#T?5EkdlP&>+#Ljd25?7k@HJ|0CA(v{;f~u2VA;D5
z$mZmZ1C{2EW6tiF=;)4YpA}7AaVBI4?r8m}>os|{qdV^M0daTa!p{Ki$gDJXpy9r=
z3*lOhk;Sf=ftt~E^tWPHQJ~W<qm2o{i_@T`eFyaOx>RgwW6DvMsinPGUO3$~QX-$B
zBIf#e*$4;`Mr<yT(qb{8xs<51#8s{Q>)TvigUD{olJC{rcqi=D9LC9fRRs#tl@i<!
zDp2rYhH@8lG&gM5$1$w1!peYX{B%bSRd09Y&_m-@mkn*kj>sk?GQ@8+{gKbz!F1y+
zmq#Qp4L?Fd^_5vsRna1-0}+b}7EwZh%64T|ZV}?tVl@Y$Z99-;$N)UwAp|;hj_ah{
z*8sA%SiO8eyo$7fp8={!a>zAWEN4AU9Z1EZr6!A(sB-sQ7_5@1Ae%S5%>f!yY3@jJ
zcE`hx?kMwF(bQs<LI!q6`L6q1k&^tZqd(U8khnh<!p{KyDE*K9k*xdUmHS<V68Q#X
zbMi-8rTL?cvp-Ha`s1k2iY9*?f(+~rI_x3WG&v+xuV>ckA%}YF8F$C2!0tHoAG@P7
zcL!y|D|+>~-UOP~HoI4vBl<c!qPJl`>#Vwm&weIH+yohdBlyT_yrUz=`GA-s68gf=
z0QKS~I;W}{<GfW+$<5Rd=7%e!6ohiB5VusCAI3TR;TcCiJnb`|$qy?aL+}G1Qf+ed
z!v-G^_rtUBGk_mf{I`CXL?3?)MpVwP<V(NECZ>0iGa$CtQ>Ky9DU@XzDdp>}UyCPP
z$0TwUl{5E7g@&_5EHE>g(4xVCSWFlkOlQtURH)kwKsATnzuYw~kR9@AofWRhu~pda
zn(>IZN!fn#qRf%aXy?I^5ptdH>FyP-S|wY**58KpE&S~ZFXH2WrWreRaqxJpXFDYI
z_k7Pkm$S=2cEH!ha~89AX#K)dn?SMto}K*rul#ct|J=<#_rRzAcJ6)ft*_+Sum3r~
za!Wi1*&oj#{&|??$eve$OWzRB5%w#@bChQt<DbXjbH3*#$e+~1a{_*NPO^_v?Bh4~
zaoU%5hJE{;eVk<<f3S}?7-0j?Ir!dxQmy`;KffLU3CW(7Os!Sy<2=jqT;QJ<`R676
zd6|Fy#XtY%pI6{hfBW}U{`<Nu*IhSev1dJ?%=gG!X!<Hwd{_`9dV;smK`pgv?hyFV
zH+<5tQcoyL4uiABNs-lD;qar>^D@wtda7)puO4zWFNuJ({+>wq1V{z`Fk_$J4^&Sb
zfDiu4I`+~z{V{R&p!YP7suwFun2?s$A}y^=i?p27maQ^#+GJ+6%*o82kli+`MQTpF
ztk#P;QdxrYTl5C&?`&Mm8I>hm>%sQLT#RWRH<!RuP5)Ef5c}yL;YPz)I`cDke1o@s
zfbUhO73HL4rWEHC6{lop7H1aa6fgEX&PvtJom^NjwV2NCqecaJvUkv^)voL1mHTPm
z)vku}3%}Ch)vlfmp8gez#u)caq-5t7W#ttVO`DpNQdFE-oHIEmAK+^5p&M7b;^p3Z
z>8{nT9`dsNw80uz->~E`XxyTTY1#@GaCqb#eRz#4w$A<M0Fkhx<t<Vs7i8z;6)pCB
z2&ehW(z5B8{_eCO&+EbTGL)3(T%pm=xVncfhP?<-YRp!5d}t9{p^2tjwz^}&UWAEC
zS#%LCgxi+FJ;zy78l6R7easad<f#`%Pdwv_FR6(PQ|e(RDdp;yg2wFoO7L^3=LOKR
z)WdWw1#Q@8@4f7E8P8>Ul!E*$g-Kt^<t+s{S^69}7*y(EGM0Lnbfq39S1FgLv;+i!
zAJg~?@K{`RgP)%Itl8+!z8zuTda!Trf@q$e?AtTo9ZxUzZ6b*1>CL{S?SyZA*tdD?
zTVM9=Wf0fXk9~^)kv-|`TR#xn)1Q6gjrf2P_LX1LJCJ?jm(&en-}rMSgV{H}40$vA
z#!r+EVc+;B+feq6FNF_d-}p>?IQzzX{}JpPYeT1biuD+ruK&3W{y;^#o&U-8+^PSZ
zrT>|&|G8WLGZ+3q8+9-H1De4f&wTi}3oiK>yx3C)UjgVL{m%mU)8DgD|FMYw@HM>9
z#?PjSLnGrPg-%&UYSFF9Qd7EQXk@#Zgc+D0IL>7Pa}xNrX!iR0w6IYmp&vcxN|sO$
zf!>TFP_XIZ%rKhyylXm{hoI=*zG`=RdO&1I!aXRN4|`{_1a`!)Zxyi{LQHIk$~V5?
zijv8b2#&7Y<my@1j~AuuBod1}n#}mttGZZ>E8-O_8i?#C&+mjeO`gj^Fx?ujmb=pE
z)<jaZ>f=5;zYe(o>YG8AhpuzA3zNSy;H-0mtr)I-;s*E`U`X_O*fplm&dQpm&=oUK
zYexfJ7w%-Bzp+LZ16?v3sLeaBdnCEG0cSN(jc{b|_K7n53}B#3m1ZC`SaLRM-){Vv
zPkG5kSBMn3Bp5cV*gsEN`5hZwumLuIlS?6;L1b^;Glz2T$_nKHj-DFh=&6y|v=&bd
zhg>0)zu4>=5G+r3^i&asYo9m{eg^Q=@bJnC<%)S~f_}_(*Qc(}B;`qv&Fd10ZW~Qv
z>DJF(t;iabPB(Xjw(WgM3Xz`-r=!1c-D*d6<_kExQ0_=}$Cs{rJ2K!FMx(!SrI61Z
zX_tTH8fl_E(<h_{Y6x$wtmv6y7d@Fnl~$5t@SFs>o!h}<kShdFvu|8gWT^^GtE0x+
zoNNrOg3#J0{tn~;V&_<;#m+VQqCMZbMoCI42xp3xobBNDwkRD%OKKJR+jiFtc4R}o
zhw~_X9LbJ+?<ymh8=d_F94;B{NYE@tjW+RNArkBFE9Y86gl3+1RWJYeN7siEDaO#8
z*_}AWUj>S*P|ge!NYoUM^Q_Ex7@!eG#rmBxyLjBzj<l4X)+5NeShND<c8<p<Ay<gU
z(w(kvWNCv_Jid+5+RJOI(9k__O5J}i`jb^EtNE&!MV@lB$T2629L73Wn)d_PBGO9V
z(6NS1?Yu4m*|vS+2_OwnI}cQvX#&?y8h^l5P|a?fy7GXlO9`(7tzoz^-}8U5^iTqG
zbr|0BwTJ(UrH2V<?csm6^uP`2UwZJg2b=!ytv(p53${~yPZJ2lGI!S0g2I%-f}-Lg
zHiw>;m$SIYqfd2tfzl#l!s+P%#XW5FR%Aa-E70d@|LfB<7NbyqXYpwoJ#pBzfec}y
z@d;V~2sVrAL$4fxvy+2xGPKiC<u@O7ZI<NiTWF2rt^uLDVeVJfl5Rcbil_G<ch%^=
z2NFEFj7q<-uT1K+*fRxw7vWp__%w{&nLD19<TJu7%xU3ouILz?!s@&KNqOL2=Y;DP
zo%=AxJ&rzl!qvV9=YG4NyQheKzZ*XOF?)j9(~c)yeVNh^oOJck*<R1s)}+6mbS3C)
zA273B^l#WEVz#`Mo6m5$!6fh*$gt>?YnZ%y3q5|ym7%kK+|2sv|0UL6{pRYctKW{P
z->%nU4>$P>W&vLNrvkv!5N(!dkrB~iR9NFrIpb2~n0FaNBV5JUfO`pApLKO4AEFX$
zmeVeX-JP)EtgBUX{%Ak9XoL`gA}AP}@46>a_wTMGTE1IV2rfYf9#s28iwI_MtJClP
zfCGU$u`JEcxqc>xaSBM+neMqFhs1NCh#=H{TyjvD+J>(C)8(q=uQ(W7x{fX^R%=9w
zX@CboMBRx}B3*DaqCvFC0SjFYbv#TW!I6IR(#$bxpG21+6ei(K$@5$2lt%7Uy60}W
zDowly=ZR}sAXEXOI?6{7X>`HQl18t;<myV2Q4uahv?f3_#`$2HE~fkjIDhk1wHYnE
z>?$TV;bf*<v|E7fjPp6Hm~Vys^)Gm+ZzLw;uvG=v;W(eeiuqR9)>ps?Q!p8WrRyTK
z;2M7a=i>q#x0=A$iaX^h4C3cwGA?eEKz1+AXRu2ORm|1`yW}mkJz0*aIBInP^$DCm
z$fb2hiU^3%9;DKTs;i`146K}$g%(cDnUH(iV%V~XV=HO#@L_Z)&#@kdR~#`qaDcI~
zahGT@0IOnAR?6x^@)1s9!Y9@cgx`$vts#3XNd1HCKt=SBttmi!kMp^+#Qbk@J`36M
zA4Aj#iTsAsxm{}sxF>Kv;9|R4FzL@>YF83UOm#fEwg4G~^SP*Ez5x4g+$Cy`jjOv$
zG``tg&FPsc>MYU}OUZo}EojjQ<y(E$FjDPCI-w%E&*}&eH{yJ52r<7M&gaccHc>~C
zVK|w)EJlF68Rs)tnh+9+YnT=H!YUAVGN$9Wu>!6K=TE66R51ba-}p?_92=MWjINUf
z6-1}0YA$&MOUI<A8JZd#>u=5;Mg<IqElRtuCXMf`)}re)^*-_pDxv!;UNFGZIG_7V
z%wK`?_s-K=&;`}ih=0(|h;Ue7J#ga$aYP%)YI91efg8WXQt-e{5Xe45`DQyT-5unn
zVNq%s*^Nr+wn!9EcH;aqu|hEXg!BH59Yj`GVBHR)LV_K5HJMmLy^Z$GRwHDXbMQz`
z5`>o&)I#wZvY@8W2MLh>CY;3{0gq~E+VkM4TWYDTNnI=kn;J#e6U0ow`D`tVM%7kt
zR?<+iv8KDQw%UZWL+Nalu1|CW0S?pArqOB#BBZcUXQD`f1>m6qN9}h<tApf03VpSi
zy9M3)Rb&;q^?J2hy%n%C<mJZu%!c~x3q$DZac|dAJrc>l!g3ci@sjgdn?MI1h@xv_
z)edr_Z|R{}wJz%1t+wqS2aV+I7@ylVS-_ux^ZEQUIbNMBDf3afVcee+)D~m`O6SI<
z8A(FOU_yFlqS}@SDeot$eaNbR0#bf^k{S;85n>uXGic_l2#>94_0*npQav@3Y{azO
z2&n??J2+qJtj5wkn}VWgVSV*cvJK~P2c-$LTZDWToDVio*OC1=nFnD@fowO<hpMN~
z&BQWR=-5VTDSd33UZFYa^#ba7TU4=(fC>?XM>1bxdKj`br<WV66G$x=YA3i2S_^Ee
z<NR$+)cvFhPT_*K6(}0ue4qMa837dp?LyyA7DCM|Z7PjO0dM!j*j(Cn0`G1@KJ(b=
z6m>hf1t)WnZxG0a;(VXTVi^INi@ddYK#`l%+NtV?%5;Qn)V9zxsBN=Qy55xCD9D8A
z=(B0+EksD+O_@khgb<CUto*hXYMmf?sq30;Sx3Ds!x(x;B=Ru(r8!;LT3tb2My&PT
zsGFe73pjse8}%OYK2G5-=^;>T!1+Fxh-Cy+-gyMKgMNJnCgsq*1nBKJ-v=$05ulm3
zqeX?Rb~xA`<^|_4G>^|d0_)#}d={TC-k`oo!c<fVxy1bhvLKxAlUOVxKy!&j)`G;4
zpGs3pf<x%W4r*=G)d<Zcl!{u~QC-Wrq~|)SgHSo4Z{baHr%vi%(h3X8TjTzMB561u
zTH_B$FPy?HHc+7GF64v7%6oNDCre}`P6w0qN5T!mc|LOucE;uA68Uz;7;rj-n=4dq
zsM3X_)oRgVVL>fsH9Dl5I+U61g>GtdB$?H0@!i$6$~?r(Xd_N{hvCjcC|&Q73wsD{
z4kn~^Cb*-cjH^p=hD0-W1b3pRpI0NIhX_Wv2jhb~TJyp2_@3$`WF5}pAvsJSeG%vT
zY%G>}&Qzw$(%ypf&)|HkjYTj)R$kc`_f}hxtr&yH&j>+IfsDJRUmtZnxMpczb!<S-
zJlz*s>0=lk0vd<eVVuV$8re^Mhg=Yn*%H|(K_UxT`Lc9%s!Sp@b0aWDpbN$MK8uTG
z1Z=MDv4Ltk7Krr+sfhvAePEE9OqyUGy#9_8WN3)<nabri4pvo3X^Ya00G@WU+L?4l
z>2&kWg848Ftv^J)jR+}x9GL0M-8+_RN{0?rpC;o4PHbi{UZ5R|^L^G6%ZxIW>0-hd
zf%Ew+tlx0;U2>0*%vfg$tV?jdkF{9lPE(mKCJZa<QMahe$ZAX`jS}p;0_SCqR8th3
zVtDD@k+AUiCN3EWC1;e{m|zrr9Y0%8_eqQf>UN11^95BPMunEOCW=u@u+gY7YAYHx
zM(t02#!R5v<9cbO`+1C7!gioWjaA3#TQEcDoHt=(B6h6W!n+T1ia{E0%HmsJe?o$F
z>uZvr>=7)7&$nV3K^|TyzZ|EwWKB?p8i({1ItN~^SB9F&dyx$FdQ{LlAFQ9LHX_yB
zr~%=X*CWWP;e1|szs*$P4xzYmKIvGR1$J$W%kXADPryjT`R`?^DV(}$f7ocjn~boL
z6qXGOH8<emY$GWQHj-dT`c}GYk~)|k%~liZ`FE58uwv&`yn^aMCl<EoM!(KcpCdyM
zf3DwXl%S8g^9B7d0qr~yR1i}5s9U7KoQ<_6ww=TGV$|{*CaLQr<#xo?sCd;q>OgWg
zN~cpiLKI^f`n^Z(PK1;Ox5991DW+%UrL*$XDs)SMTBGS=mdDo_FrCe==n^+o3!$r9
zV+WQL8xV(X%v0k<!C;Fnj)qQFXU4pR04?G1_+;q3-$y0*J|hl~Ta$$g&-sc=f#596
zfK68T_FhDcSV+{KZ}HU?(*RT4Ctd<#(ayKR`o<2kfd3N%AGQT+>3N-{Kf)fGSp*-(
z&P-sle^992C7PXgm!jq~FhAB1)6-Lg@mDb}z&A|VPF15NrAk$QLjvc*#*sLBSCM)H
zaies-@=O){f$3<YVzsUbX-db)Bq9`=SF9$ADgN+jg1Fg-PYYB6hfk*7x?G*Asx~ns
z%8a?77!nI%nZ4V@VwxU9Xq#9B2*r}}K2gjUJi+_Kf4F@odLFk)OsOc^=Qg!D>q+jo
zO^pfIlkB`rZALs;T-KA&jG02@OvDBF^zXTu>W$<MoP1`c(4O6f^Pu;MD$l)LT`$Fy
zqI8R!yPShoZXqh+KaH^MPPHlOJ7x%xh(T$>UFr%2r$~zyu5Cci-UaK^Yfaeo=$;3q
zFq$z-ZBlJD$}`$c`s6HimU|XFbyXGyo2tb#3v=M%t*SJ+L~Ve~ikaz0EpZB5CdVoQ
zPNEx2)G1;L?`lM?unE0u)oW&}&&k`XUUPkCrrsA|2)<TLf1Cr>*^gD#&rq+tTWvs&
zqjbH--znG`)6q8fKnMsayipP<%mPG}pT9?qmt+_*)Vdc|P{OMD+a6q}VF7Tinrc&>
zX9)rYVRCt%x<<h%M&G+_9yIOIxFj3t)Nw}A@0_rM+I$}bQL-5-+8Ii>5*A7y&WIFN
zD>W=tTLmfI5GP%kMOPmQr4N*;@D?JJr~7KQU>ZzIn?9)4w?U(>Jz)*V*nfhgJ*4)I
z!Pu5cJnbQ{Q6a`;LzQm&NYFj0xVW&Wee>o;g_&71o8=ZXxAyu0^l0_4I@eAQ_1mCO
zdgNi4(%yp^^AT+TxVa0|o_28O7N|YQl7E8q!a{Y79a4)&pnYBYPmtJci*`uW7lB#d
z{wGN9E>e32c2(SBsKQ@jOy(+n`fJr<wF7Ez0~j%Ai8>}Qn>&}l;BS{Ln+r?SNfl$m
zrUV2Bo?eke!ORt@I;~69{W0eeZ%e!;J*wuDtEdEShicNqok~rccIa-QvS9`^ewjK)
z!6`;N^u;ppVAUwp;PLnjfK>RHT9;rXU1yO((3$uCH6K@RV!i+9$Axan+KYesI5fen
zu|#|xIakoFCC=wP`GZfWQ{<R#DBWVz=;femKU4x6wJv*iP#jJDQ3;`&maE|?0Okp-
zF^lr!%hjzC!AZI`L=r(-ZjDZ>)ZW33;1CprZ`J8H1@6$KNw?|8phQj021=zDSE)CV
zDOe3|p!tH7`8b~&=>4ZvRgNh^=@tVWUjtR|K2*X#)G2sIO|9>rCf_eG6F~XhNP+qM
z{S2(jJ!a-(OuQN}M?}#l*Q(LT2hI%3e_5+`mk5?Y_kl<v7=-&^^>b=p7LjM3Q=6cH
zliA=!WD}N@+qz6pe*@0vwr=!-x=f1s8l_uo{p*V`vHu>Gz`@vny&bDTinSYhNMI~5
z(CscHU1wSkx%d(cI*vH-jMHD9wcuqqX5e?UGei36%j!OY`RQgCDFoYav!|@n&3^kj
zwQ&HmH>XF|L6j)fQPae2zd$fS1kMNBS1*6*Rkf=`>Ims<1^f|bIxbhyYidsx4jW!m
z8#&3v3%XucuV)3jzplokg2IXzFZj^wDrE&5z9H;ev4tw{*=PNj%EmX;dZZ_om}|O3
zkhmMpAM~dBH5q|ZI0Y3bhT?o?8~Sv)x-Vt|O16aM%C}$zE+3V^VF_pU4n)M$ZytyY
zr5SIlRZ*NQ6F6fQbm`mbbRwkiF}X;AWi7w+9d(jS%CHoCTjg<qNh!`}>z+;TV<~)*
zMl6ZJ`J`ojb-MCvwPE?M8`an4Dod_|``Fn(y6}CqxAHW?HG0Y5%}`liK<RvNTjxnZ
z9+8gS5NCqwvJ^U)qz}|;H0lEwfo(M7MLXls^&hCCO>le$hndpeAFAo5LMuyw=VnMJ
zKbqNHQ~YWeoJ9((QPEdEQYVq4W~>0Bm*4lXN+gq5Om<uN?>|w0CYZ0@sEC$Xf!Q<9
z*YkT`EQvj@uR=WZnYvo<dEr}EdfVq}RaA+EO2!uzzWE$>BJ0#ZRhHMZm4fSQ;rwl1
zsC#1?qZCUe+w!H_kEEdzxRRx?N>-aDe5pp+4Dp^8_+l<}(^u-PL`Y%vjL!aAIG>3{
zHR?h+)P*->l8y!9^=*y7tPjpN)i<%E4G&h|8kG0nrrsctYz)L1trZw$;(U{P#gdqj
z?%qk?sgH)TfmK;My5KWdb(-~^+JJW6ehn|v?dpqUF6PU<{G1@y9GuVln$NyhZ<EL)
zLOSbfUT~)K?HQI|_)!g($ukz>mjvRcaXuKMOSG830_XD$!E-;W2b7H{S)ysL!TM?N
zPPHld7^Uko^p^#8n2s*rsrDv93U9eZigz#~7f{T%3b^-Ib%$~Ykr}P*{#~$xbPA>G
z0=^;$i0O0zg%mEJNU<LyaskDBtAHE#sQVPProYY`0{%56q%*0B(scpX2?Am|T|gm)
z3n)?$jK~EP^Q{8DyI-B9v_)iwfLRB?f}K&iF5s(zfS67fP)Gp*@lNLT7>x@jq6xym
zut(TRt!4^Vp$73W()>f}%X)q7M!&hkU7Zd(taf#3kU7Q1!)jADsycR9jYb89Q5Bbi
z-4<5DcUAr`p4ZhM*Dd)!dtO(6TsMQ?74|=SUYDB?J+FH`dw{1>ZVOXQw}sKpbt7xZ
z?Z2hdj;SrBd+4CHT3!0pF||>ZcEA&Y7{(ueA5&|yBDIdIDbgan$evbO6SuDj>($t$
zVjL~_Zirth9apQDJObaGuKMcCMid>`M-e-tTF5>K+nTDvK2q3mnkMX{gnit}KK8SZ
zJ?x_{+ka1BA3?0}b?hUHEm~*rm1_pt3O-6a&DqQ=nSFTJ$3*t=7W;UEeT1@tLF}U$
z`)JBOrn1Ucz&@f_Bj#owcd?J#*+(wRn83C2-ps}HfSa>G{8BD|DVM#J$z1|TOz2WB
za48qIlnYwwX~W5we5G7AxZI0>XEK#?c}lq~rCg3uE<-8jk8b1Q=Hs&<Za#jroSTmy
zDrmw@$Ite0`|<N?+<yFc6t^EgI>hbA&ns~I@qHv_KM$XnbMx`lC2l^xvck>B=l9%v
ze9Fnq$0vu}d@!ynG3>{Ogxr37^uX-rVeL}DtG6oQk?vM-=m2iua=Lnpw_k-2=Imm#
zn?PT<POw9Dn*5!+OGD3eaA@CpJS@vd?|ir}E-x>$IJY2w@qLRuDg<2LWQf$I+uije
zJ*nX1zNsu+X?#8CzoEq4EU7=lEuHe4npEWw`#A)Hmp<{EI<TYxgl^xFJc7$2(sSWy
z_{o`*$7eF=PzF7Yhjdxk@Z9|Df*D0DeF8*wUk?xPvXG%gnG<tZYI`R2G#>0_;XQIP
zi{WZJUc3baQ{U-4^vl#CIky!j!2eS-v$zHdP)=qA=CT?=I~KTWFqz+FN%Ns<(8o@z
zbt0-T>@rqA=<Mg!nyf?`OIiRGg>L=PT`S%*4LsR*39l|?K|Q(*Vj|T9$M&VH;?P-d
zs@)i`*(_-#t3h<YOm|0yl*cHagQ`SdKcfz!2}2`escUb<cjO=o4*r<(Zn*vVtV*lx
zLn(attUozx9JM&UFQUB^b4e&;T7%)+iE=H3>s#Jt+lgq6EeIOCvkZ!#pb$W5hl3IO
z6)}lTsRFQuqer)#S9=a*PyBl#*-k%y^1BX`#5i$OwTY2sJ#pkL3*WHjPkxJK&LbmG
zK5h{6|G@ct+<NJ7#4@ENvW&h-86zYKOIo1Q?z^kREP8%RQ(Z5`r&kxVUM$P1SBPL^
z%*m%0U2qBZo&AnTMH1?Yi6B<RZaEgQM!5x%8Hx!>X2m*Htr9~!{iPb3U4i{x-D4BY
znz1aaW?_P6n3YenXtB&NB%!XDm~U0=slU|+loCW{C?+JC6?^Ptgb{_oK5so})`?|V
zb*duhgt_>263g6)gwu5r^RZ6l5QQ}*Wep-R^bwNG`t&~S)hEoS&ueCVSe8|vNI@UW
z#jlT8W)%`n*GJ69`cPi0*2)@HzC>h(PC}Adr_vzJ@R8)x=_j*JEX%5sBIty<_;jKJ
zZ-S>x{Wa<{B%Q952x3(#I7C~noIzxUQbLkhsZ$|drLOZSb=9mC%d#q^3QA!vKBf56
z>3*F~A>nkLL=3A=xnbH}O3m8-j=|7LNHXh`7Vg#QFJA*upJCu8on={dVwWQL<;7gM
zPBir|mkT*53Q49bBm!6!da;VOSLuMr426UwvqC!}yb4wEIjOH%A(mxTh+UiDR|s?Q
zIZ3~J!C$C7l1^7j1hFbrcsXLTl7+|&rGzB2QsWe@XAR!*{_XS96kRDg`!BUdz3+T?
zAh7Ee{PJN`pAykxnG7Th<ySKJ>8<kr?9#3(rHI6kUq~{`-{opVFI|4s=M?IdU(&Gr
z>{0+fe~jvvUo0~Z38VW!%(v>W!mZt^yn@IK9fTws9jeiXrO4~`k-}A<BR1-auz|OS
zkAPT~HM-d434X;eE5Bl5nHQ0Sx?*C!Rj~_l<a5gRh|Ew-NU~MzYEb0$x`#r29@?)f
zMmr}79;zcKf}#D2h-JP-66uPF`Bp_Hg+!iFE+aBS5h2M|k@8TlBE+Xim1y3e(TBnX
zMPda-FtlG0vCIV|5#?7a_&sV-qC6oyvbv-sGUmn<z|cZSveja8v}VLvginj+x)%O8
zV_DWXW0w>7rNXTIT8U-ikc7H>#C(fp^sk7>UzMJS%uq~7vQ?}N@wzA6r`S+kF}m%F
z(2}v+1^kL&Xul$2nQllT$}c<c(_58Tp+rtmCL<C<2_eZ=i2|3m6_9;O+@UMs_YTXl
zdZ(_S6lUdDN-X0+66)R&^R0^QP$Lg2ix8Qin2=<vSRJ=lu^^vfE6s|rEURMm1;sEc
zzhYvU1xP|&F)`n&*x0(-DCKQLW+)~k*(%ndnpd$9pJJby6=PXe#Tp8VVOD;{#4>Lp
z33bK9e5+!!>uZlIyAhe8n2=<v*z)RL#auqcPMQ^CSysgw3yNV@e#OKxJCTICVq(5U
zvGVYmksnDUq>jG{)Ss+wD)5$ZKA-A~`53o+N)v6Z6cd9;EZd_a>qHJD^-u}_F{H1O
zweDz%Bw3I{0Hvd2BDV(S!;b*AvE}nrGp$tx`F!&li6)q}zGE$lRvUAf(;V(`acJ83
z&c#1GcrPxj;1wzs2~o5#ReOc)m?WlYqY>ZTcm)O?eQiMpd=n8~!Ug;PcTD~#FIV9v
z{BL(mPPNq1<l;Isv6a@xyIXR$rf;|8;Z|CTJeOzJrJmzzWAAne6BTcl6hWZs+a>qF
zH~Z}pPZo>j4EXTflgd*3_oT8c4~s*Gdr~WMP3kQ$CHkMf&Vom{zNYS(05Sm{h_>`b
ztv8+AT5F=-0V933+|G)4rhH4EX{|LanTZqEZ-<=qK+1}}&LGx$-rz{^rXltWhL8L$
zR-16ibU8#X8VW`4#6_P20I?_t#!=;I)6{8Yp~bnyd9ZTMuy3ae+iFR4P8+SZ{9YZp
z@&@g7`Ahz{Bdy;Kw#SY)icF@v+iIcm4kP*JHjvz_omO2wXrw&ZPU|WEZv0rlHq}PA
zb2pW*>M7D}oyU$*?s%ERFdiN0`u0$2*%)^(xwer~kEQIo%YC!lfTwhzi*MAbPPiR3
z^SsA2V%GG0$-b4aZ#&pGW=zjP_U$hA?RWNV4*PbMeVfg`kr?>KOzEl3zA;OA8o;+{
zWx>S-Szaqlxyv1+Uz^imXk-}e-9c-@p4XVtE+|GfPFD~r!#$ktY3HsI$<HtHW%EvS
zTfUa|$iOhtfuZxX_A%6Z3L`qWk*6b2ey!GIaC`63uBQh&YO!*53|%-#>mp?``kr+5
zt?sJysZLrPf*#AVTF`;HS}Xz|<p-}LBj`b|Ypv-Eowa27Ap`mW1bu&Zt>&WGnMyU`
z$S0R}zMoB`Ux#~HY8u@$O?Jz7$FQZoILwVJQr=Z-D!*%Rdkb+Zxk+n+6nVpz!}`D+
zy!vR1v?pA2cQ?%?A2C=RM65uuWW;KpEvwxktHgs^7a8n0XB_+;0p5|-c(ZbgzI-hz
zTz6+;tnR8f>Ym|sRsVikB(2d)(-7}EEZ^d<TCpq`S_fIepjvOOzTDTq?uD>Bj{xjF
zy|vm1ySpD7IjJj4)tw}D;@_9Hc1O|$p9Y1>z&DV7wAK*fRdB8$#2h39C|C#apXKL|
zV(|{H8^3N!h(#V9!_%P(y=*|gfS}|0YmE`~vwmo#+8UN>#NVn|`}i9>Kx-)fVsO}j
zI3x|!8Xyke+j97}0vyH-(o*H{INkptbk97m|C0x6&56Gikl}FiSgk*j|7r!$r{1hJ
zldm_>TOjlfL$nlx-dsmVhEIkwmxCdAoh&nJxaOh{57lbQ;|=(62p$3~ijGc#w_9Wk
z)4~v=(H2IxT$@pS`C)@cnaHCaLN2u+&$|Zl9k*z0<qZb%+X#8!NUaS*e$#^d+BJ}$
z8l^RskH%4Ht=1LcW{=hyA>92I+&$O8eR_=6RH{MGEYrG5)#%EF-dKUwFpTyb0Unt>
zR;!NUQln{)Xai8tD0JbsT3dQLTaI9^<?R&IF>gKQzoB#CzuQ>bE#6tJ$k1Y>5lo6S
zs!ee>qBSzLT8QaT&I85L;CR+RwKX?@wExw}nqhhicn4RCe!3KzH;%b!yq1VCr*TCP
z=2VX9&@gPt(yo`*=yqC#?6e|VYllFWo2~PN-#XGVx^1y$X|(C-9IcfEPh2n;e1o7j
zPte*T=&#JspI;kVo1~>lS9R#W5cIA|+Vu$fq8a+nYeR!UqUiEfQV5N^RnzFzXQfaY
zHvvXm$qBsWksBvaxPP;UK1u*H#rjIuL=oE{fj2_P4RsTEGht&b-n*vf!D!(YgU2w;
zqsC;RdAr$yJkSxDxBXzOs&wF4$xTc0q2r!s@VE!_Xi}iHMAFZ;@VF~5kEf<<ZhE@5
ztkSneX{!91!DAif(RqrNhIqVW;qiQ69`mQd2xpIh{3}KtSR^#jKU<K042-<E7<xw~
zQTJ~|BJ%I3X<9OpIV{oa)!;-YuX5XiU7E}74dgZ$8LSb#bgZmKSqFiwEL_q8bD4Xq
z+{Jb8V)n9Ay^WY?aLmRWpO~o)K)PgFxQq?VWy>6h_4qp=OcxvQ3o-nWJG8zC{viwe
z1A*cD+@<xBHyg<BVdUnsv_1&=T?_JCfsq%KXx-#f2J&%?JY}}l10f%=ARi2j3?}I<
z)uG$o)Vj*Gl2F`$F&fZ4Z^?1hjO#W0!;|Vs<`}A)6d;CfmwM^=-7)@!xmr&ocvlN%
zr$Ct3(_zqpNz-)TsTjE3eOfOBTwnpt3k>||d@WU4r2{X=z&WK_3k3Xx1$bFt;P=b4
z8g#cDRE2(hzotTm!j1kFX7Rv-T0AQfVKw^a7IvRplU+0EFP+In6O&Y=$DbD9vpTT6
zEM6ZoK=;eW2vPy-d%DWd!v`EPeDbi?K<)?+sAjlF&>jo4B-EeXK;561=eKR^+K(7I
zE!5)V%)0t$c`PF|CbpLr3X`-^EXy)c8o^N=#tf+|phKBGGN=~qxJV=N0|t}%h{>iW
zwEC<_b(=Zvy?%~pxOF#6HRc#4b?xUEotJ1G<hKlVZy<KjOSRs}PU~$syizd^O=!YW
zc$WWpswwh8gV#QhR|mRaX;4U2OV!?O%Xeo5_>Nu$Cf&2ZU6cO0OsghWt*84<rD@-L
z{r2EvS}&v{VOhH0kQLz_dEZ~lirjr$e+;VbZqyjw7whjeIvHGVL|nm<T@lxIwp?3R
zfNQO%pyS9hIOHM@d!G`9gA;5yWL1Cz=+#<YW^h=FIPhT98U@#&9am~$NSj5rycSe|
z7x?Q&`4fZJhlm$=sXonLrPZ+s{P%6yZL9#h#jCYe@>zr3X~ZsPjn)|{bkddsyyWeg
zL9yW(?It;)z8-e5G;_B%?4DQ)vm$@*6-_t)B21HNvV?2YTlqO?_|gsVJ_vm8b1+Z$
zgZDIpcdGz6NZy<#d=?x`J0F0LyIz1M>2`zH48#i*>8h8@dr`xyhQ(&CQ!2o<>?K%b
zU2Cvejo1{vtlf-MT4@G<ssi9YzoPY)w;SNw5cvD+w4n%miy8dO3V<iC*U}}4CLRK>
zCCrEC9<Cq;HD1$hK@2XN8C(d=0A@1drDh1bDP4Ko8%YD-5T=xkSeB&$tItxe5l$=K
zgfYe_#AO8HGPzvqh%^{#%Vlr{xCC#6Cb@rMh?^dK3kDqX5x;vyeyMc#TN*qhy+8{`
zobR^fTv7qfhu+beOK%{4>k+^8?`k(7F0a^fd9eaqK))8!KE!1=;sREzPZ!h(t!nM$
zcG`0MsRA5Nd<hmElN(x-hQ13HRq3nep<N&i(YQH&8}MaCY^Ft38nS_NdW|JX#uMBg
z{|b3%Lwya-Y2?8BSHO*<^EYcmx>0A{4zuPhHx#L3!@4zR-5<^7TV8|Vf)BOEQm)Qs
z0%kMpBkg)Le$28UXIuk$)yJ^1wNyu5gpoa;2y1Z*EXWT!BSXdQN#majCG>|+!8IT1
z@b6=IsJ``C5yd*X-e_U<&NWySo(xqLJoY%Pb3AF`2qg*q`U@=_8SR*b-(hEdd>#&=
z*H((9D=))ZR5VQtb+@3ibKMOo#9Qm7S3<++m9K=60o=M1>c*>qQ7qva?NZDZt&P-2
zXVMcfIlV=@302u{X6!B%zy<~C(v13HRRpWe(3uq@W}s0w#B7S0S-!}OFJr=JpHESS
z@{y{4+XChm0p}|D-)Yg(+e`*yd2`=)S`EbfP0mZ)k9)0A!2P(b+qGB;ni%G&pO9Mj
zf3L+O<R7?Ns6Kw@hZS}|_}be0Kf_91!7X7Sboq}`B>i>1i@>U0T9~`59Ml-KKBd2C
zwS48mX{Y`|)Lqw@Pu$UH`)|K3rAss|7PeH;CLj;IH9NGHQcImzD&{rqCt<}cMF&S3
zHEFD`3Rr=?IweaPI`9|_3`*erijfxJ;f}yu;;(mV?WG5G;QKM~>R+|?s1n|10iGKe
z_}nh7k@SuZT#kX?*)1&gzit73H8AkSJz5j#unv3x1HZplgV!#z<JNq0b*}|@mkumn
zYNXHAA&PiK*lO?0`}PB)1nREp?h1{`peVO7r3OCXbl3r5t{%<uEyJ6dELCqtBzq=x
zqjHKT<z{8(jmyq0%E~J!g6HZ?^R#qbf<Ar;Qfk+okeQWJ)XYk2U0&>ID_J+cWb#(S
z98gyS*8jf`YIWhsU9g8y|8GB})kL*)Hpdj}|6NV&*DLzG6;|EY;dn;Z?`gk&G~tM_
z8^6M@0;(}ja%hJ|i{zuwZEn?(zedP^92J&BzVIWXivB4}HCq3Vn%FN+v^}Y*botS+
zNTG%PTjzKQalCv|tH}z6+e{J9+p_<oV(c5pO`7TxxQ0}U^9CodYlwVOk7ZfnGLfbF
z7394Fn3GqA$2fO?uK*ql7!@g}VdW_gM*eICYt3mb8gb9%e8h;D(A3u>2u*k98Eu68
zu%S^I(rDQ4f<~pb8qGr*-P6?GWsA>h_2dl(hqn=j^b4Asp2!H-ti#_oZMnTx5pL(S
z1o<c^%O;|J|Mb2DyavASCN%#~VGOe0meZaJa4I_wdeunQW1$+&Z0wB%(5n&hhQ_ii
zv7oS2BNm)2S9TF}xyj(r8F2t@>LCstY&o>A0EfAkwHUe3;4m3+=<t`8fH-(;IZUho
zhvL6s)AC7!!()g;>J_an;y`UVEUo|t&sE^?g~8!dkprQ5o830?^^q;N%@yF5A-NmM
z=M8RuAZ{tLyD8G=j4g*#A_v|AK+OzT)8k&N5=Bq7ht1KH6ur6+3Wf)|{XK4z6n6Bu
z4Qfdn(m`$9ar|(X&1tMoA?_G?U<wahIXwjp%`Swv;}CEk;3uB(fL_f278(&gqzMjl
zC(E}Ruro01*N}r?i*;Dkr%XxFM`8JNZwH&<omK^GzSclqjghxQ4nkgOL4Ha{mh)5e
zu}9Aoy}9kiIK|l*r^(hTwTx3xdkl`hVva+II{|V0*<zv}1DI&M;;tu0G}D`mFzW6B
zEdW1VP}k+g6*^eYS}_9pWB>FU-dEiN#za@_jWkwuH<H^J*sU<O=Eg_U(rmGtacudD
zVWuCknXKdOV{Uf?xzOM>8S#3lsv93e^4Rj4$azWJ1p+qoMXl-aYVIWYNdx;ag#CP!
zTWm16`Ajxi?1arj^gwlx`wIj6Q-lq2htpSTxbb1ckMw*KgUx{%)O6RB&l?Q>KnxzO
z<;G*SGq%{L0%Cts+x`DkcHRM19a#gHXF&voqo`OwKwazt(m_!yi4BdtBLXhGs1O6j
z62%xBf{H>MqOPckiY*pY6j8C4wIuc=8>4GtG{%@svRS_r_dDmzd-LXT#eCmC=f3%!
znKN@|=H59o@7_C&9ni6e#ZE&@iYA|q+NC?YF*MftrB}y_|9>{=D6cVNwR6>c)C8J2
zyrx-?)vcSGLNm>JUxW2mUv7Q9CwMx{(X7wXt&j2oPtE#tgY}G;TVK`;%f4N+UZh*^
z<84>=O$O^5Uv7P_4|qA;)~w&qtw;LW-7>EltY3M#^|a>TVXE#gZ^kBntwme501vHJ
z{%f%OyR>ZTVYz7i<V9<$>^Z4FM6CuqkT^t&_2Xfr2>Xj&4q^Tk$B|&MVjPYmUR_;{
zxBD@-oIOOeAJj07vy^_cUiyFffv;Bj5&jj25_~Fa9E2OD@;|o1$EX)uEH2P3mbM0c
z$~{k7)JBm^f4MyQHXdK}@b2?A(9yKtVtTJ``a)aKADY=^Fug;Xc6eI^%!Vj_+|*$x
z{kA;1HVCWkDgON&tTAi`9N#0w<k=8mcbcJYsirCc^lkrMV#XZ1%k~f11lmdcYB{O@
za1N1TSP*!>U|{D5;cO4Cx3!pW5e)jo0B4*D5T;pg89=iFFYiKpT)#E_N7>5U9AAyX
zkLvj10bkhYN$*gtyDD-+p;IP5gua!Y?B7PBgv3D-hfv_hbxP^?VG?C1vdl+V9%Xq9
zW#201at<6vX+A;XBne8AA-^(8-;!8FjMoyn1<<P$@#b(W#q501ApzP7|9aJGnXugK
zGx-J>nwo3kr$F#F#n~zW#H3E(skvukxF)p0btHip6B^`3d)&T4qdlqWDSC&yxtp@t
z>Uhl-{%L`=s@Yn=wjAa$rvg_K&LI$~cLFYDc{t7>4p>V0D8#O*iaD{?RJ;ElO%)c$
zt#p%Kwcu9zlzwq5RpVBQ{XezPXPC;;F4eGI&XW;tmy7DmYMHQHJb~S*ST%8{BSaa_
zmS2$g$#S-T_qRLSA1a>h6FytxDg)QsmI&~6s4L=AamF>e6S#}!k#^Qx#l2L!2615^
zpE7j{d~ug~f4Z};WoaZ>nXW4~N7;F1ffY^TSb%vc)9le>;kkEyTS@N>?E+mK617aO
zbb$!1L&aCjWSo`>8m;*BK37UifpZ&6`4?%XXLSYrZGri0N$Xbc1gdp`3U6+()ial!
z`-olLpoYU1&8TY(^wY}wVMU`G*r@#*0A#Lh)1GqK&D*x@=8d1;N>7@cG$q~cF$tW=
zS(>+QfM;_{vi7!Q?QO{nPl%kVSbxWD_2+O@{^r{VmXjN5T_t@YraQE9_{CNdajLsr
zZ}_QVMn6d7<Fic84wcxv(gOyV8g-Jlf9$<=#q^%gSF6niqT5Wn-dj)Hn}fHe7Zmbd
zC_XH>y%!8JMd=2Izk>g&*ye}f6%B?cgWO%Q3s}4B3wxG(Z}iAt*E7iNZRaT`a|T+c
zO6pWur-~l{&Bdc#F4j3#wr=*jKA=Biy||*;1#H&XtwfVh{Jj00zUYf=*X?!b2l^i+
zMHTB|6W0SiNJkYe2NukN>tbG~7vCjJ>9xZx)5Fj7tVYFx{)h3cidkKkRgPvWRx#E{
zH`5=wt=|XORl~0ptKmPk+O>1b_=5d>AoMqR25H@E-fPfX^TZklv6rW{R>L6aH@V}n
zg5Sg@m)5G&(sIsSb;F^9?Iz!y4TdBB#BfSX9bb##1l{o2A)voWG2UQ!?4KA;NK}Rw
z>V}65vorjz!SGz0VZJo5s$be2z8;Q~?)`cee;r|$#a=@eyDV8$*25O8spBpDdt+a|
zt=s)^q@6!~!(jKS%`O)muR-fojp4{@857KN1-|naVi=hDEk%4wj~!CCfw)jgZ~SRp
zrgm_}E>kO5b{R+1JVhV(ucIsXO8J$?NQ?RCF?RlLn89*zu)1{^J9oN=tMv`8Q8t4h
z(&IpXEnv98>JUqLUkf%|f851qdAa_@(i3OvhM$dx)>=i(G#GxXlH&56`EESkng6ES
z%bo!GgTJc{_JpON`FMQMwOE>f9j;tA8JP$^S`m*JOqNz^G7mn)DO?iXFzyG7Wl7-g
z`fV`2VT=wpdH?2ISKMwBVq7NB?h5SpVKm&1+PnIFik9ayt-UCpg%1p4qk_nv2m`fp
z+%=Tri%QEO-#IPo>sr^+1`R`GXJo@s$xvT2>>g6FGeU^$j4!COd*rr<r+~XDLN~cN
z1?p-hLk%W_Y$o|)!e-`+3HwjQW(n9(-BU!wySiA)o}y*cG^a-M4E~m<!AF^B$TPu`
zXJvgfYZ5dt<!IK$vq?}-JB=)Z$%P>=xtPvR22axt-Cpz*yNh$H!QN&|5kJ7=i+X3*
zRGfBQ(M=vowOiV`XfS#HPfQ+310U0my2;Qt>{eW!8ccroCnlq&qRIN9S{FMo)y`zy
z(289QHzDP>4=X$I!*AlUb(n6lQ#v%&+9udwGSFs{yBM~WwTp2WZ-g8UG~Tja+gQz0
z^q2;2rZ@F0cTR&kT9#>sEGLJ)q&v)b3t~-qx;^jdpuZ84Yp}P}atcfE_@eIMaltjl
za#bAA4gWX;dT0eLHW=RhCx$&|!7$UOy2*>PAXYPZ(_r$N%_LVZ)`hitF&rr#h2aQ>
z3tf%uUt6ZN8uSf$XiR$zZ*vuf#yVjYyNYv|>?$=;Lqp^EOlTBNuk`m#=lA*X!vwUB
zg3BfJCO?MgHGVwMJN$j?^9%eKqPO?^)-%5?_GUtNUU(UcYctzvWn?FbT_pC9C?>HV
zMG{-WrJGwgPmj;YahsTepFD_5PmP<JG$A8pQX((!kcs7Jipr47wrn9XY73Ed8S<s5
zl#fkG8QMa(u8UQ3p{L1pRmm4~!O@}dJbWAkUz3`~hm4%632AAZd;c);{2lOaG9b*M
zN?yKY#fgTNSo2^+vF0IRB77cn@)^dV;VfzUnOO4({GDYUi4sq7beLE=51KmBG6#Rt
zp=9qoNOj0On1z**u>{38*(gRXMbTgxifbeW=b|`HB4j0s9wheVp@`2%kuOlRC_oWN
zVqhVPQ5#T%Z$ja?6-D3<6u<9A@o6!N!6hi(KZIfni8ZB}C?Axfh(3(My$nShiLXiY
zIfA0uQ50*Bp?ISl#pp9A_K<k%EQ+7cp%{4{#a$BLlel&P#p@TTed%)$c=FVAc%bfs
z2kJg}pzbraIev>-2C4rbrB6SM&CkflF`4COAI64>&I|A+jmNkJ;L)8rW)>U9FPigj
zGK-%hXGumEv&qHWBeU3GRz`BizEv`kU#FT!L!}EK$YG{<x&YcZ=3x8KCpNqnLYNA~
zErbviSgUJ3UkH9m<Fp9;RiNu4O*3T?1S`$9MG&Y0_ZLB=3bb4d;VO`{ShKcP4_sRe
z-BmQtEC^D85m^xO7t1N&shb}+KoQ&!D<mD?;4oMBz@YUE_hmtQmGEH}^i+YMCD20!
zGM7L%6*#*@i&igNEBerEh*r_oWJ6~a_%d5Nsb)D^wT{ctqHWB9(JD=~r7&CtCM<<v
zDsXHm3{nA)Wm>dp%V4n5e7p>Xs6gB0&_xB(mP3>Z6k|ZIuc9!lpxfcr`YMXh>Z^XP
zR`emc5UZ?g&4r;VP<@3Kh+m-<qilti23BfyJZ7b)*|Snh<B|vcl<BxUt%{E4!6>Ei
z&DS*Z^C3=YzRibt6&Um$B&opB_q4XGwF>$u&1gNaV->ujG{5Saz5)g+%|@Y>8Xsq}
z^_iXpT5nxmpk?~G9`Ji#vo_~_7@$mFM~&V{m*!)u++1L7q|FPpM(VQ~+Sb)BfF`7j
z$rZKNKr`Djo1XdBtAH+&k}MR7c+cgFB&W6Lw$ibIxH8JIzHTX<Zpt^a$x;WMKcM^c
zt4l@yH4v%u5p?UWzD%rM1FaitC8|$1@)IazZeqhU$A)5Vp`(i)=_*AE!W+FM(kD9|
zo5yQL2GJO>Tj@P2eXLJE&vHuSf@6lf8C<5(L$evYQlzYf7Wz4KrzpP)QMeY`>%5r8
zoPqh`&RS@t^YJtcy(@@&iCl-8wc2U+^JsYb4u#BqJ&jSCx_N<^^f&u#0w_v!q3~P>
z9{ikDQ$4`|8sB>3_$KS9vFKI~P4&`@q_MBnCQ9DAiI!6s4TrxJ*%HRzt!bCA##W5r
zvqLOj2R<HJ!T=gQAMch4MQV(bXFa_@zoEu_u2?)<XJ3oAX{e1U5giJlon9e>N|2}G
zz$+^xfW}=dw}L}rVWGXH%`{4PI4sHv?JH_ECB0E9ek+7l`k8)B+#82-Sw#)Rid#+|
z`WbbhVg5P}?i4}zeCFh3cSiMS*pDp}h3oCFs&T~6l!<?=2S2^Wzak!fMAYA4U+&)I
zIn+5S`fdQfDD4!z$eGASXF`^*c1C*2q&GVxW=u|tOPpwTjjkb&V|=;zXah9Sb4(*A
zq|X`g`3CUT`6zNp)}IlzH-eYWcN3p@R&?HIAAcHoFZa)h)Q!+gkN*=nG_Rf)>o-Cp
zz3oPjXLA6BY`f{?<7g-L<$3Y-M*C~y38gr4Ni_Sw{{C^5l8(A4;y!@DXw8HfJtp%m
z+%kxB$S}WyjtTiIb*dv@f`J_8{;7!>lahK)NuN3+KMz$i#m65&L&y8!(uMgR1DTcp
z-RE3!G)r!m+)fsmZ=0I7Hr^?1TE01G+F-mB*tC4@YTD*_q1v?EkuBQ(lyL!eTbr8e
zN=y7DR*ce0&n&0v)Hl=F-yX|n&F-4{!7cI0hq#1*9^0c2@d>a$!iD1|NOG+b;XwcW
znpaa^rU)@>6L>dpL5P3<R@Cj;gby%5gt)Z{Leb@O-3)$C<U(T9`Vk^}Gx#E%uo*`z
zqF814g+yF|Ilmbnp_nNiZbm<l6?n7sE_Q4zqPKvrBzXTy-U6Lu0I%JRTOdFNurqwN
z1;Sl8VInO|B~}v~itxRXUPa)FW``9)G#*wJK{q_yE&_i%IBkV+Japg6q4cfzkK0U9
zycHtx@N_Hmz(deBe41*ecxxNS+#?T<w?RLIVcVfI9;R()(+9Rg2!@_)hgdvB?STGx
zSh559;Niv&hAnoo&6J(+D#E=xp%)(hXD8<n^%0kB&PNPSe*}rBYqJZ+;~{$&#Npxb
zE*Oo6S9UWj+6`kcRDBPO#Y4g#cm)sJ_driP{7W7}_p;3ydto@jPxit%Jop#$VR<p9
zds580p8L4CdHXo@cpvL}?}wq7pm0BzrP={Vz)<o54qZ9`$ruVL0W%&pl)w}`xE<uv
zj5`Q}F;pxMj)!0%hDID>xZ@Cv#88b=&LOdst7lg!*XQr0oV@R0KCC{>F@HV`BQQb#
zG8p0f-rIq+UnsWjOtGbmClvoE!^KB#b#^gIvP7FB(77%Xb|*+I%FpR2{EvXISaSqi
zrILLL5~z%l$~#AJaO0HhSdc(v8>#GY6lzH&dlw{7*-k1a9R(Lz3ic|lE)(;QLQo&J
z#eM_{jNYPS{N%|g38@|M+N=CM0W+s#SAqnl^A=r?fwz0U)UeAy0yP~-<0G0K16Nr9
z_8W@xM8q+CT!js>$1pyhh@V(@%z7H^E091dtwm}%zVV*zT+>~qVYeWlK>X_%1WLlL
zz<@&0u^c)`!ejr)4HU;mq}{DqL*$l&v()kUAGV2Nv#z$pJnGljD(;m-8%cP)57;3F
z9>)(2Mm=|Pt1Zuw2m0T36K^kL@(_Q!SY#cCU`cpzA5<bP9EVnt@Zi1qka&I^LL}i~
zdv&Skdcs;AJYauaDrTRsmVrm;E{8?&3G1oxpj@v^JUIbD(hd*D<H|()li)8255!-U
ziIkJp67mq-`v}GH5Tz(&L>_^?j*2@caS@(dgh$#n$At4K{2z!3kFjaxBJvdem%xNa
z*HLFg+9~`4jR}vdyU&OZR2&{rr=1nIPgyH~$I_q9376COPY|c#QFO$45pf#Y$^Ofu
zBnfQzj-u;nXd%{~hT2leLnR4Rc9P03PXkC>JYJeFir-J;9EZO<>3dcDH`1+-*n0*%
zorvH~-Z4_#K7$ixS}HJKx++RqIs1u-v*6}L1S7aaios{0rHruPn)o3Q``)Uv;N{5Q
ztxUNt4xa^ICkkL}_ek;JEcl!5Ul&Kh-I|C_=b(|PQKX1HhtnzksO9=wqVOE_bEN<#
z@QQSx(&NhCMZotY&x5;+w*RKMl<eG4ymlVvN1U+Wmhg$fNlV#zoZ2yozb(8jz&sgP
zcV9#oVA(HUfXR{+eIZU>c7CNAn(xNudstrcdGSLB@|&CMzrbx#U-nRg7;qk+S=#$|
zXex7Qa92ck$722bcbFteuX`fb!=;zlc@feiS#@9dv~lSprd)#Pnq2hOjt-)5po@pN
zbO~Z)q~-q>U+%(Biw0hXP)Qd3TclmKo=y30;@F$DLqy{%5F>5uspcTkZq#lfGOvJH
zrkL|w{BQ+wq<#gyuD*K^UecRBhMp3oRmIK2V(NGaw@<8SD_V(9L^MmGhcz6;whTlM
zKEZLH%j@GP{IBBL0)LIvua;PL6}mW40Glu_Qrx(Tb5;I6soaijh!X`+ml!Fsu0ac_
zORFvRUBl+&h`bfsw3__ex(}N;dmY+IwcLlzM>M$sBPEeru?-LxZeZWzWZrJ#=?!aw
zDj<As;tCUM#@7`CZ$c{>2&ykKZ{i9QYudSsgEt{c=4;(cP1L;wt)+fH@1@pQjJXAV
zGLm&WHL($qj3l>H>nH=M_+IvH7%L-NH&GM2Zo>eHtedEb9-mrI1vgRq@Ke}XlfUC?
z{o3xv&!A~05v;aCzA7?uYQ;}UoiZtYLeeC;*!Kr|vSt#=?H1zBbLi5U9oetL5IJ}(
zSO*j$!6A1F@f~I;x?32zp%t*Yku{Ww+q|*9sg<ykj0u`4Kz=a-Uj@h&M$l3L@_rGt
zQh@wj1Z@={7Z*VX1;`6Tkm;|;4M!${3Y>Og5Trn;GlLKXN?aI(De$}wg9ruAyE2GU
zU}!xCT`U0iKdkG{q^pWDNrD&!&PdQh0q^>pq?ZC;Nbsrxp}6dbr`Jb;6%zDQfEFef
z=4YB?6`3hpVxR&Zo@`{00=W_lQJ|(5#~7x-TnR=f@JxbH3Jh(*NybQ!iGzTjACqw^
z%9&OS#w!rrhQR~{p0;I>sKB#!3??cN)`3B?0@FJ(Fe`A-A3-MWGpNY30FE+6fv`>t
z(iE5;#9*od2ZI@;D{wr7!88SEK@(eIx&od!2}CfH0gr;FNG5NqD0$Hg<|weV8-uwD
zEb7i+o&xXmWH4WWS+6iysKD613>GVp-M>neOf1O~MV1fdC^-szFqFYE1x^lUkgLG`
zkqlNUP<0H0d<B}1W3Wnr?&BF05Xj_vM8X6nt5uY55*VyiATE)?ItAuWVz6F;c5g7)
zs6b9SgAWz>cp8Jv3b@axl1WWbq==ZwQMM^?au$Of3T(n2i%C9GV9h)RyA{~?E`z-a
z&}u0r*{1+4i6S_FAXDBXX?B9-po&8C5(K3R&|CyTnF2KbKyXw6nsXp1SAZrP2u>(K
z(+mWs6e!P?XLCjonm1sSa|+Oe0l@_YXug2pq5?EYKyX<BnjIkcSOJ<GAh@ak%?%J-
zkD&cuxd+gU0Le`ih2{bXZYw}j0R*2ZKyv^D|4@LY00{0VKr;XYcNL%s0D^xiusRdh
z=a77*2>JgA9w<QWKZ1t}koS+^TLsAZNAR5j<ohG|UIB9b5&WP4IsFKJjL5VOljQUx
z`B_CtD`)VF0_5^zjAsgv$B*Dw1<2t?@Vf%!?<07w0J-}Js^DlZ>phb^eIzDD$h${S
zO#yQ25!4`H@#+~kSpkpe&J?ov^sKI91*~?nhRh4DvAQ0C8C9|WnNzMaX&?!?Bbc2B
zh4}OI_ocdt6|mZqLhLB6zs0G&t$@|O){uGsO;)#5pg_iNB?09hf19JURZ-U6XV5``
zBJ|O*OaTgz(~clWfd+ROgeuVM9)k!4R!O6s6+n-i$Dgi>EdMvB>8`*c33@3|{u{^W
ztpK{@RFHlO%z4f+1}K0|ImH;H0J`J^hBDw5Lyw%u2o(kWaRQ?i@S(Eio5vBbc;pP?
zt$=GifkN!`(yr4Of1(wzI@ucHEt66GdL&){oPf5ZMlwZ3p^d!}yrBT?PmLg50otY-
z!CMM=<Ce(?W-36NRwJ0L0PS6kV6Fl|nX;hoDneUXW0Zvo(2mv!vJ{|=tr6rXK>J%G
zSgrtVbB$o70;#wS1%me!pgqG86hwwvYmD~3MzTglp)IfxtRrA`+X-x7Afg^X?>bMa
z%10>pvV2?Y`34%LQrukg4=6G6UAqXZA%vO-Mhzj<JThtsq2|6(b6<S&4b<aVM6UUt
zGTI$uG(u?Lu~9<^HD4Mvgi!ONQ9}qd_mrj!Ud8gfiJ|JDQYj4~)O>H$d@meq=kT43
z_N_4*AvExnQ9}qdUmG=qQ1gvZLkKnhQku@Hq{LA5%%Y;ZTy74e<L=yXiAm{63F)a*
zJETqdYd*&L#TrMHJ_IkP|ES=-hu|BL9ff^|s-CNtI|El5Hx##~c`-$y@^k6U3n+;F
vK!iQQXPL%6f|jNcQ6=*q!IP>E@8oq0YJ=O7{Ot+!;K}`LypqJDCy@HT6n)A_

delta 140556
zcmeFacX(9A_b|?#l-+yp0!fyH79gQZP3Y1?5hM@@(v+3}p)6fMKsrcC2#~M|BfTR<
zAfbg0p%<kof*=Ss6s4(H5q{^KxqJ8C-HrNvKA-pd{{DEMC%I+HX>;bxnKN@|Fa6N^
z`e&`O9@Qvg@B3y_;^?H_F&$p*JveE6?;(SR4bDhaA+g`kB=P3F+$_{Nyk>-)Y8g7b
z-<TmuqnsUTMmQhUC=wVjXjs3banAWQ%eR{9moHyxm=9>xhW5*FjK^G=N>_Vx)aVSy
zG)yQsWKiFvVWR{dDmTUXXU&R%Z)0XCmyQ(-V~z>Vm|B&jiOwOlDh{0t8Dmm|diNXN
zcUU6OH+p#Q5s9M*W=zVc=s*G-@8AWIIcDMou{dVoWeQ$q<7E<F=HLa<IFj))0WT?d
znTVIUc$vIYs$I!%3W80sTp0e*!cxTo33Q6(!ENz|;8QHy%Y96Fh$6*OHb%T5niLCf
zE8Y-niY0YHEhj=jHc~9lw#CpJl96JOyEmgZBqhbNb}_w;Np)_n*V2MCEXb(nY}%xc
zGon$P^M0c+sk>8Z+`-xU<^0Y94Z@vYzudyPpkYb4_i_H%xV>{tlL5~Djk^~qRIOTd
z_)8o*bWq>n)ki0d8(nS0_>9yfXJn)1&bjr=I&&KrbH3A{nDbP_H=LbcPIJD~sEE{_
zavL=)0I3Mp;vCbUAb@M({GvhOkWdrI{)v5)oPRVL0(AA0dQiom>KAuzZCIpy8c7T2
zPPGmiI-pLq5yJ*#&|?kpC_`#=9p|N{B?7QOJ?G43rOVYa<kd4g*EKvxIj1xYt5jR0
zU{&pr07ko$wK}9og##(KhO>Ip&`JVH8Yu<RmtU~d_SNPs<6di-kw#j88R7is?))Vf
z+^hX*3wO?nDb)m93$qG}Ivrcav}o57bvKQ)=>HVE)&DiSZa$@2&W+7VOXHpAo0X8>
zc7E5auQYXMyXG}sg4@&~^?Jf>-`Upnq^UWKNnKN=sk7ghFXg;3pUv0~&$k=-!M{KJ
z2jtvt6u9u1<iC5QrGG7{C%<0H(j#YOZOartsVy({vZXCw(a56k*mOCV$JO-<<#9Iy
zLwNPi<tjNX>RUP$<j=ZWK4hQF=I47@j!8FpWE)EnzUsc^HUF<?=gY^V+60&35xp!H
z=^kcP=Xd5wjo6p7d3GnYzMTw<{AN=Be#3_*4jPu>cru$mZsb=B;T7#|S;213=7~ks
z24Mq39e#75<JR-fmoHXw)PbAh`fMK6#4m{tPp~+o>jLqmYOFFZk!X2aD#df#0lE=~
z{2SVeW7WD?C&Hh{{A{VpOD?fg;Ya&hLiwaVmVS0)fqeM@S=Bi_X06g)YKTyxc-9*K
z#yqQ}e`zG_Xtt#ct2c+oAMlIyRnz%oP&f;l!xMK{TJ!V$Eag~_IlRMYz-39Yykf8F
z$w!enJldbV%oitFrb<bKaM9y{(tJg-r4!Ovob{Q*vlG~4>1{#Hh##cl&ZZj_c`See
zVn+cjOD$tr${arOC8?#fKoq+(TQ0{^=kQAdEw4$bm{x>GedAZ(K1!#+Pe^hOR19S?
zZ0sCo%;Lu0`J?CX%L7@g)JFixsw_3K7ct1xC9=y7OPjD`n2{yJ<v2cNiznx_?XB4L
z+0Mw>{rK&{mbXj|_U;hND(N!>E*gwopTmcJq14rzDS#IkW?3)&M2tD_<Wy#l=5VQN
zKy4-^JF~xi174j^?$>4olbzE3H>5{AJKhq;6B=4uvdCnfc-#7}-f$(7ow=#4uzvP$
zezENPInL<S@%HPU+}zg`AeMLNYe~~<w@Mbx?xQ?4`$t-{ml<uTEDh#Q`T-e9qb(in
z_Yr|nd#`G(?l;CVgpE$-kvF9_{7wyK;X&Ui70sN7Sw%aIOy<!&{ARLbxF@ns@~mW%
zJkXk0meuCFc3TFs6$GjiTawK0ejyddyY!V@fhRn(wq-k$dG-MRPAm)9_)HoSvKs(6
zLZOA`IKr@<1}F1dIhGPwY1%NqVt9}KEg%~2@itb1Uz%qL;6wLXN@2>#!G4_>hdZjy
ztYn_vCm@E+0Q4cOJA0s!cwdk>J=qz<!};wAme%Yqr~+!rSPD;kD0N~llKIJrmZo?Q
zu55|7Pe-CiRDpu+KQ$cp0SKt4S3ckjz6Wgy;z{fn(8+$)M`KFaer4I2WFC>}S2pYn
zVjvZ*odQp!qP0_uDtdH^hfNta)iR64r8u)cblBQpC2w<*RWi81q7;jT-<W1eVM!_c
zNip^YOH2`pItuE7q9&%0qE1UeMa9g-B1$LbOyTi;Eel*~20b`_BuEOfQAxon!)u9!
zt4l6g;aAvhL{IJCBZZ6=JLCanA64TKWi8cxRU(CL2^45{Di|zWZ~?0$#RBZzN)aYY
zngb@Q2Qq9_-c~8XWI5+p_OfqM49W{eYdHH7vQba}ggff#Z%`lX6wpa}T5+yruoT3j
z$ALkbn&j7r+2)e2N;XVu#)JA=3h=5O1B*!IM4^bMfsLfneA?TVXdbZ-iUqwC7!^`s
zE>LAqULcv27oef?3TQ=n)GvWWUC&eJ`vss9mlX*`_~T=KjU*W%H)Fr02o-(`{D2Be
zy#?}BGg%|K2jBt@eoi4Z-nhWhk`13LtnFw~ENToeGIB0YO|vwTMrvtbZ9{(6g{P_W
zP=T(;T+(K*Y(P)i3_>JrZe`Fmml#Q#>(3S1Tp#5?+Wa0qkv6|K*Qm|!I4$p(3~t*D
z%WCPUCfuK;*Vw_iynCkQJNrR|ps6+?yD(P_gttWDJK?M=@6gykQdiYaMYBv@=~vuW
zZBnwFxkAaRy=$o<{l(jl2CF#sT}y)f0-`f2*1oy=SU8O*O}9kRNchWQ%S7gvN`oLP
zo+^~8NGcInC{+x8l~aXPiAoh#rD`e;e4Sw6BcoCXN()TdnD-Kt2g4;5;Um*6P3&Iz
zp{X?HAzEsNeLf@u<6Ueh0w(GA!zYq{zf?{7Jb0z$gh}#6SAmV5l!|tQjZfu`D_FHr
zF8?}<mG@k28DbxgaExs*H&yiSCBUk|O0Y%njy{Nw3MBT?KsxsAoog)-Y=5fg(D&C`
z8rtXT($IXVw?L@qgS@%UGL9WjHFW67vZRehE()#MXmnI-kn385Tm_)eM=qyQA6c`(
z@*4YAYm^6CqufvB8ShzQ8QiH=F6(q?t@4f5Dpy6Tc;#QwS_N=ZtGwkyR^)|5%yTtM
zBtB8IM9y<}iX^^tv!$=8X_{@Z%w+ZFQPb3!$B!JfyvDQoTY~uKn=L9|`@Urni=QWq
zdb@eTsP~4_VASC?Jtd%yG>?oryyY&E-(XYbnLUpQ^T_jnZ1Ox_okyNW9VE}#+O6kd
zYnR}63b6dntS_V4rg{ACYtk@2;-OXVc5MAT(e^&7Q`<)a@*OaSo#lz|LT~$Ghoz~#
zHKH>1wwm)qs}I`=KFF1MhE}h-3sNpZHk$E!a7Q!#71W0Y1_Isg#xttbiTwsdqPqci
zx4RKMU$`3u<_mYjJ|74$SnRX&gvEwR<Zi&7+zq&UxEqi{?#5HNqr34HNF3dbyMP|u
zjoA5u#MXcTNW3$Tbg=1uOJ~-7zB8Mb<h%D<DzJq4!Z`Gt&ubm9v}155J-nk!Mzhhc
z&lh-F&nF}8l@EByNP~z-4{Q2r#cP4(r1`=|mq*UYN;vU})X_QLWhHXgvNpW*VM~v&
zReHJAdb!m=<aJ9Io_5mGH7DkXB}iiXfu|3n78OwHvpw@sQ*W@dnB=hU!D>czIs=la
z>le;P9D_kMwipW%PYK5?b=c?gg*xAa_Br4e<6QNI!miCHwe$f8^-9X-2|Fx}7oD(J
zgU=%>au#0T)A{+l=m|?5`x$&OYS~VpV1v}xzS9?Jjg_`x1r|UJ5>7#UBH<KVkONG&
zlBAM6a<?UxA7wU$6<@%!KDE3j700w9e8dgQTGum8{JP$>Y?s=L%u=6OqNT3*9OaDK
zUj<w$=yfst#a2mSu?zU0pIJ6ZLomBKPx!>z&>oAZje;AzV9_sfIB#;>QV%9xR1hbV
zz6uHnhkR~XA*Bh7I7LZaKt@7Zp(TBbN$CAa?~9bC9jOp{fYM=1YQaaGQrhyOU%;Gk
z{{pfW0EDc?oCVJ8PNDq!FDzrEFWopk*Kj;><M>?Qc;UtYDTzrPS#TP^yudoldFglr
zy9`Ocmy+`Hn2VMYG@$}Wxw-yzq%^W&P$hnJZ3aQ3+-`3$0g|<H<v}eebkVn#8mw~~
zf6_)71|@VdBVWY(k`Y;@R~9(aFGcfq1+Dp853J%yMo)7h3ZB&Htu*a*R)!<hl{LoE
z5-0A1;Q}3dFcvl{SL+32!ZHU*o!Nvmv^^Dh(|J-e|Cs>H9erT4)3C?ztzXFvq#4L{
zG(Y;iMe&Y6q^D5?!bZd#5mfM~#(p(<haW77h{F|-Sc~KuX&INsSKX7x@(B+tT^PJf
zOOu-M(1(^0><D6a*bZO~O~)_}F-$}sjLF31hiN3OJ!vj!6<`w=@R-Mz%ItO;ANJVN
zHRMB2<a>GI2}?zOXF3bc33_7rlCgWBi~6Jz{PK!?_zQ@7Y=2-Wu;{*Q;oE<<1hTIH
z-ZQx*hbjR%H-5Gh@MFJd^^ShcEcT~59?ddB1&l@TljlH$dL+V<PJ};ABfHz`cgq-7
zEM54=rFigV=)h48nZm-;dG|joL;0BV7I4hLJ67HBRUYwyr7VIhCs}yzCzgg7^)cj&
z$)JC_@XLS>vb=i@GS!5~$ph#JBnhkX8a|O#c`cnxF0@TzIcpMs=Pyf7y`joIhX}(E
zBvuPT3`|G&tS?^>Yz^XDURXAO;y`W`b(bmWZj(77o%&`m$vQw<N=5kNhkjM0bkYAe
zX|<sL^K|O}IU)u7KTpRQV3<DI!+;GqTJWg5fo(%j2UD#h#@FvVByrTJ4CpG(yJPL_
zWICA!4cM1PVAyM=CnDu>Hyz;%V;MfJ6l(xoKmId_Y>oKMuZhG_+|hjMBpARoX2{T#
z=h>fIy0g*?1tYbniu2C5m0>a#{f(s#s5bz?0%%}(2Qax9D(jsW;T;wt;jYTV^vX!|
zL;)O#cICrtRsh${jr1-RBBGHhnjB9M#9vw!5NRKXEp0U7Z>OU(70x?+Y{~D8IvyqE
z2ncyl$)oT36_OST*UASl>Xv=eP2I9*L2G$-Z6S}SWG%!O7qq@?e;cVV8iu5F;b)Z$
zvYwOf5Ct@^A>SH0WkbF)*c!-gE#$$=0%vJFx`KQ^E+n-EPFBzM8_0hOvG!s?PVCy9
zn9V7?F1VA|wQ7)GF>Wbjt;otbh3i$?3E-q5;T4=flfm`622dS^G3KKwmCfnQnp}uy
z#mS{vW34iPjUTI2<99-V#W*c7*2&Yqh8S*rc;6mSHN3;Wf*i_&3R@#se-FqJs{;x;
z7tbil#%dX(P0*_q|5v~Z@sj<3>;-P%<W2(l<W3?R7`^(isI@4Hj66x%$#ds}CmHDE
z(~4O?W(PEp=4c{?yIZ867hvVtB@O(CCK9WLU->5*b5OK(*|%DKfDBTt&c7;Qt;&Aa
z5`QrOtrGapd;<{T5$?nz0!1F*EM<L#!3*)Y%gtl(4^j;CgLL$se_SZM=SK^L_uM!`
zc+U+oNYx%LBrE=7q&0@cWq|iwoOdV<I`vwH@SZzl@Jpqw^%>mBdwz(zMEb7H4BKW1
zJPk6)d-lo)yy!hkw@}rKaEd1<`RKYL%;Dq|w5yL|CNFUokSXl>tPF!aKc<`V0p+dL
zEt&rLq<r85<UWuavX#IF%($0kph>@GUy2Znc4BLWm|`Eypec4<25c{6<BZ!!eKHM;
zGCWN~VP3G3wIKT}1MNdQ`&LA3G!5^9=+QZT*9S#3j6K8*V*3$3(J=N%XB%e@_SW96
zD-MA#@ibM52z#aj_)7=ymjD3%Gyo{!U(r!-0Y6#A`Zcp<3ZH@8Z8?)i)r5h%cr|MV
zlQW&GTNQCupWT&5RJSI;JNY*`C#qWuNUTvNx>qzIc{!6ejkbQs+G3K!{&J>=sADsQ
zyS%Z6^-tC(Q_MhmWr_*)2&e=T>Ry=?C7ql}&M3SkCWZ2bwXMxrS|(10hw_KDtsPiu
zCJls8nSA6oGI{P0If3ogfM#nzj|-sL0_bG{6f$X+{$-|^rLP4fzn5a43y_d&09k}j
zsc&r!UP*LeYZRY4L#iSz5<_ArCE<|B{1(yJUPh$g*zUK8P)M~gsl}q-q)LlMf(xf%
zie7}o^Y{pB4Keb*0c3)UpTDuSv-G+K7p4)NHB<xKs5%Q&W8A19B{3<CKf0(ilx7n;
zKH`!R>%ujIZ~-VHakZ%)4!+w(3VIA$nM1}hGyrqf+*(>XPw8R=2FhGQy8Nm&jQ`%;
z`nvR$sE8AwI~wIbYDplZJA#6I{4#V=p3p(5f=N2*A(X!8vw)_2N;eoTG*K1c)XrMv
zD(1>ae|?d3XS77{aE{g5R7!C0V{2=K)J5PpC^ba_4GavIhKo8!!vm_Y!CbWPBuaCx
z>PJa;U$N9N03OWUv@aKMJ!xMoXor$WRgSqb(tc7T5$#&3k4&Wm?RVmU_PYWH(hl@#
zw3F6++}_$#`a{$s`hU^rxAJM#two%7Qkt`01Px&#<#7U~=(4X!$s8iQUHIf~5Ngtd
zU-n%RzE-)JsWQ^vLDZXiAW+B9%UDPwzl&c4c-KVBrGZ_67M*;YF#56*<hVt3v38dr
zpbtFov=Di!i>lf0@{uj%+R{n^64`^K+`0Z``SY&UU}>wU;>8UVf^|dix5MO8Qm(Nw
zwa-P7g0eAzyY&y?R+aWI1%9_K>e=rSxECgHgg7c#F2(XMCNn2WvEqx#%mKpq52QNm
zrNvxoEDv?w`LncvTWIVUzN(kM;!9RE_|(ee@!8f_gX7TR(uDfe#qboD$v^95t!|IS
zWaH3NCsTN(U3*(oSo_89$>PHG75T7|ayh;%+FHytq%WpeAb;A}YMAyV0s@$%fk`Ld
z^iiU9Dw{%(I<X0hg>MRXS46NlFW=W1%`z5~Zwm9H#75Q<i{?lXVnJsSl56l$UtP>&
zW+=s^#lqDAK;-Jcom`z={j5=l1zjC!9Kqrp-t#NR#z29Ae%1KaB<oD}fkw_5K@Kn5
z+**`(cxLUvJGKB;?hNoRC*9U6{~j30HUV+q)`ooPP0ZaB;6DN!bi4$dOQZa?r-UFD
z$j1(}#)u4BS32o~rfGw$b70LOrVR`vcM^fvLQBNjS0PL*LX=5WwS1tBRazq4Z5LhD
zmv{+@=mI!Mm!!c#%3RMxTig(93s(YC$AXs#2iPU8?nAAaQa=M_2^wVyg0c}i0xI(<
zqpfA6@donV@*r<Q9^@q~K_3{JTyTz@0etX-dq`^xX)8Uzt;-Xf;8vrJxYeGCTfaB0
zEhR01xb5k|ZSW{-j`XR98QbBi#_d&1gV>_Z?Lz~3-+PevI1lo!61OaHshETTY~+*`
z*4_&(HMeQerM}w~>QS3&G!d8DGjVxytTj>65{Szy9$W^Dx9((dOT}cd%~H`J;Z7ZL
z>W+Zo)S#@dMpuFdT}gS+)n+M8XeMaY03flKs=X(BfSI2s7-Ek>ed^c<2j?*7Cs})9
zBF$l1Ej6p@lgVJMjxXgg8~r*%v_)EKEy<2(6@#Y2j0Ik(;z4&socu^{ir$FvC6>5Y
zOn`cUalqw+KY#*U;rJCO1$)+WF-?HxPPaOkvWzA`Av3H^S;1vu0%TjpH_xzkWpKv{
zP)JX-6=Yfqi6E7gj~oETB`ZE4nEkqxCP7|h05>fmv|TI$S#^9k$}|Cjo`3n8Ts~|Q
zVxgHpvt{r^Gl6EyXaWSzIc}^uJj>eG<(TuN*;dZF1NE9;-gOyI`%bQlmi;CE*DQ!>
z-IxP@yaP)(>|GJ0aYi&~nQ+suCR^vSsmp|$K5?0F)8|7aaMLF)!%>bcTSns-WRgd{
z4WxuSZq~whlq*M|C@91XA)b-bKq`*|t>Mx#o<7eykX_LLU(f*G5r8iUzz+prc+<U<
zeEi8!E5ym&&aL#!jp2eDgLtB-kT2fIxu|?fZpVLgc=_g1c^)|&D5XVhAGK+??YK+~
zw?j~JG~BjX4o^dt@v%;8lzk8;8;9FYAW&Rl{mE&a2u>5Q5i9olln;j$R=rgUnkuzh
zPQxy23&ZlX>8lT50Ud?*p)q&zBI__|DrR?P6PJszWFo$5V+qWK5YvcxehLJ(fUQPi
zu;oasVX$ojbzyviM!GxLS{!Z!f=rI~OeQCKv9*FLlLoo*LR5FguweGqa{lCWKr}DA
z#5z;@P|$RCIrUM9YZ5>L(s(IYXDxw%oH7H!{>meU!^DVsP@m<ZxAtBxHfH$q;OW-R
zvb2H((Q7$hz1-TH6<R?ZwZsZ*9jPdm&|=PEEBKZb*4k1SrfECidLi@FI2O@iLsp20
zg|vb?t5-gtriev5!39MuI{D}_)L}QnRN$IiArz5Ne{BntivHSmh1Oq10D8r0>l=E9
zZMep|7aAI<6iZSpaRo*z>ha+vVNql5POF{&c1yPNtUx)CKU{0ACyf?`X;~@}aTq)B
zs1>3E=dQEvlweQEbSp)!`H6|H3FmZ>7)&_3ZUD#)*MmWTrzjYXT}9c7749JSbdXR|
zU>G0%9?bN5y$93b{qBN$%mw2&T8B$l+}RgaP+a<sNWod=g%vz|leLlbkdnl764P)?
z9$?BY4w#N_wswIzcVddQJM&vf5JK@S%83yCRtgAZC`mxTGz|ifP>e@xg{gEy0im9N
z(8dj+o`Arg&9+7@!YLIdi0V$9llYP-t;}bQh3NU??bc{%EI|VgHbL{$rBM(Sv6c{f
zu6zI>%h3a*g^v1L*koim_)2(s3lufmTE#vJlZ}?67qlc=j+r~Go%y&OAlu~vFYXeh
z7&2K8(2$~R$x1Fg3VcV}K_%P^G}{3KSPf7LvKmizS;s;TMQI8*^z2GuI$*y*3iOh+
zL4K8ZP@-I3`a&y&e)8wUoZDgl3duIu5Dq}lM+RWzw`jn~h-lB$|5xW&YvRrX#H96q
zk{WsM$5#sPefeJSU5c#|zDw9D;k&@y9hF7;SoKxH$EvbQ_*B0_BclHvy~;Oj00C)Z
za3`k&?&NeNAAqqFUdVT_uM$p&i<aF7t?OBTjg~%w7M_y{GYRk$<Jbg^hH)M=Ov-}>
zfPgdz2q+!#M6yXgVr?T{$)oG-LCLzK*6nPEM#(l!DsXp8<>H4BtUs+$bi#w8vw2Xo
zZ54TRpKH|sAbE6;wf6@eV1CRKj1Vr=C*dL-^ymhjgwY9JNVr=(SekXpnk7}>xf@-&
zSZ1}*#WMWv3YRV-SGXIS3ZX8(%rCEpAv$W5e}3j_^Tw-vw|SY>H2LV{uFe1lO+H}1
zwGOh650C@$1SwQpqmfixd!}ZLJrA)kN@x#jd;Wni$0d4coOG$x&=0KdgD2$X{9TRn
zcRe}JHjuf^2bnwbAoE?p`B`^$1~`cG8}2menh%hl<q1-7uF*)GYtO`awaeCyuuun0
zr*WQX=A4}Iqryy*GroN#4ezikf{ehbiL9KoL>LDeXM6b=*=U@FW+%t^S2RO3&{kdp
zPvjU^UgO~y2lBNa!?Z#RTk{rItv|39Yjp3p=^EWTuFn0hf#d%gW;*Om5u|Zk?YKsa
ztMYY#Fldc%jFZ*~$9ODM0>?OM4LQa$*N|fjnY6~c;D)s^FZU5x4TxlQ;lmX9C0BsQ
zxrTylP?AQV#5FkB7U2U`IhGyJaO7w>&I%kk0>?Fh12W0^{tj>n=bOUWUkkX9>w=s8
zJq(N=d=Ak<SOMNAd;%t~6~WHpS`tKR<+T*SdP$^UI2#I?m#Q0Jo>;1O@lkgz@u5}j
zY^;m}IDg}iHJXNRt;9%U2{E8gp(HV&14@l<@>I@zZS9R~z%H^gG_p5nNkDdnAbXbp
za@5~iMe-#36y}-9KDL$z`-4j(D#HpbVBn%M`5g}h0`xloXZ%+X1U3{AbSr$?WeBul
za1+WH#61@50A}$l3xr_S2}wtb(ipcawT>j+M5JKovD7-Vq<Q_b)|Rv-z$NE)>qyR8
z)xpN9MDTclk%F=SE&YXm9b*}ym>0ZkElTu43744B@$seduK7}1X_o*UwcRq!MNQT^
zu`K4JA~`$_)(D5EGxjBNcs^bSPo2Tl{28W79WmMH@HB!hh7QlXpRMmmHw3<fvvPgz
znkrEj4c0=F*Vc(S(j!rj_G|wD@WI`IzDn*+#IM$qlER}u0oQu!J{TVZ*NY)05YvqA
zPAO3+!r@n*g|DZz^N`5(K%c?Q`FNdha{vgrIT{eMgxWJ%!jgYj$4FWN4d#C9g<Fvi
z0Aql%$Dh`Lut&{J)@vGBuL-g+ObJ1A$|s5jtrt#Ct@Xmm8I}iS0EZ~k;1FfnGf^f#
zw?;}@0#VjMP$uQ$*-xy|3p-eNl-*xpf2|YKq8~toaJ%Jq>%<H!n`m-A-V{z#(rrKn
zNc-D$7&gi5C)ePkUy_Tk-1Yj5j2F5EgEf7TbbLLpTS;yx9Tz;(7fIiuI*<m)Vm@|c
zJt3C15k359RlfpuuR=f#PRjV@i(pb|sA%NFSkq7e0;8d#77C1pir?{xhKk?Uo91La
z{9*5|Ynb@MUp~e{Ht54dfereUtN~vhD95u%%yifbYyfb^VIpFK7$%Y}@(NaWgBT`i
zZs6G`lsXdB`SuN|CXc*tt;1g1K%)fY>7xWo+JI{Si(DNnaRYUCtd0|u>KhEhL$U^Y
zCRD*MqPPG)QvhEtfI}t?4>^FuFg)xOa3NQNOA{Yoyiot|S5O|#?h<Ln<q25FCq|wM
zT(^jjFpeu7k{_2I;vfTihD0eTm{NFFYcS1VxIX~v*yt^}5PYx)C42IO!BFDpTXH2A
z?*NWgdTQ#B7$i}>tQUS^5GjCq!;CAdE&^zcr?XzoML=IlaS`BNG8##MOlw~zNHe`4
z!4?r<&KuI|e}J^x3)1mCAYINI5-mA>twTbgKqG2vL_V63EU^rd!>MN(R9CXZFW!Tv
zG8=gNaJh;-0+WrFSOqNxOPq5WawQh9(Y;8dPduA3wo&X8F9vsvq88pr<^XztZhTp7
zs@jP~Zxj<bxVxt;G?8nwQLGBJ;?tgkt<b;o32qDEjOG^>)&8;;lcIU{@7Cf75T_ba
z^rAnkPJF{ThExrKG-H)Fx(zLxu8}ZVBLVJ20(}|BHS8GzdlXJ9dP5paC4(3HCSWoV
z5IPxi^`4(8iCrgmzmY01zyQ;ql3aNXYuWHZq)pICBTpEXU7tgY=kazwg%#c?%xoc`
z6vNV=X#)LJ2-LpOY+rxasM}ZeWFv*9A)t~d$&J{<jUqB_N8+eK6=7KK8_<0U@Zfto
zuQGt1BGb^Ww8c{OVcXEE!WU8_{p1Q^y%7l+)v}x5iHvI5O-BDas;c~&Zc|TJmA_?;
zHt9C?<xRXqb$Ksqi%GCy1Yzj%gkdFildz;CqU4|X3t5h)4Vb+)33E3BYT=HNP2_P;
z-bA((GTpW`4N4kpY3e4jrBH-y-W!{EWIeek@0~8U;pzD`=vf-{V*+}XfPP6phfFf2
zUjP<^F}*DSL#_dEUvL0c7nP%U&`e7eX|r(t3Q-d68eyBs`74bn-5J|VkfmCpPE;Xz
zkjo54Z6>mzga(~F;&Tn;j#4)b9BjGhq+#gq#?VP%7%ecs8}6kU(p+vM&C;+mmIt`7
zOy4Yw?Gkr=NFrl9qKRBs+9;~P_Q}S4YfHD0hC;NuO-AXUv9dEgz7>*Xq<UHmP<=xy
z1yp~cQT?sE;wOUYUofRR6ws+=)-9&y^xr}hv+ymX2k@#>%PMUVn}v*&LIIsp*4R~v
zs01=xRMMUVABt#>|FJ$qi)k$E#qXArwWR|es!Ue6)+S+v;}8Q`;pto8DQ*)V@~T|X
z9*fCFD_jS90Q$psUX^>XIa>@yc!mVu3Pbd-EWg!8F2-g8JrMn4%eM$iyad3C9z>S7
zMO%3;+e`I3v0We>{9*_09+vpSEy5C?Lsqoqf{RF?!3UlWwK3GUYYT){v~8o`h<XSS
zA`I1dxAt-r`(+EbqDp53)tG$&B``Sm+uuXO-JDVZ{-hT48(g4Ah!nJgJH?d{1ICp`
z#mjXtlMHLNkUT|Lwm|{(u=j729ejH=fJ1J7o%e}nKDw10w5YZ$i{<wA225?=7aq2Y
z()jm%^9_(Fgr`G7AKML=yzD_+<TCCg^0RBc&!6NEY$j>s<?kX7fo>=m#Z~C(f<S3H
zrfDlUOAX|`>p|Y~Jjeq$Gy%}y&;&p{FWN3wc7Z37rkF{3|8;pf#O~cBUC>CnAV_jY
zhVL2Z`pSc@@A9DQ!uz_qNG}Za0ST#0P7i3%f?GvM*S6K%7QtJ6w}l3j_5fGV>H<I#
zfJQY5KzpXPx!y~zBWVdFhVy1IT<a~*V6SZz(dYJCMOT5lM^_oBp-b{0)sY9O?YHXu
zv#DBLfa>NwO-r2T0dV2p10>!zx&cye0l?H-5CQfU|0KCCgBOazw%zK|L~=u*JEPg6
z^|mEjL_m&<v`ZhuDmGXa@&)SnFp4z8f(}D7tS_)@lQZxTNhW9D;a1lSYgz$V;d*_b
z+)eieo(_}`!z$0+{-Ev=r{SAXzim9yA?Lz+ok)YvlkI-n0F==u2;IgL2g|#qDq5kA
zQgc>un|rmY>^9m8Dzz}=H{B*i-;R_<JK~ydqtQ1(q+sX;3gOrey9EflJIWCuZKDAg
z3eX@SFlakN7a7nj)X+eX0C*xa3k8}TZZuGc(46o@Q;HoGc%X!ahvsCyBtUbrzN6)V
z;Pnx;h7EGkeLkWE^d+{PhQ<3J8`n&W1#Rck7R%f<=0hHhh&WwhWnJaTovN{&+$mG-
zroL<A$j>^tY9sC1RKy46GzdNit;DHF5o}u;1cz;hry|?<g16<$_E1bV4ubi%i9s-M
zf;^6m-fkEK{oa$?@)8r}5^N-FWTgW#;EpqqSpX5nKhPE$|K?1Rhq854wG&&lU36-=
zyQcyBwu_-}4^Qmw8u|_(S%#r+7*xcSa#-8wCKpFI)XU(WJ41d2-)T64HM;K5qi8r<
zvRw>ERi*&}Pc#A^XavArCjh*~n0|6+=9eW*-vyut2TW_0ZyFv58UO^*0C%DR?nJ|V
zGY!<!xk#g)K5M&}aLfRb@W_K$#4ffOv<8eIy6M|-&XE%{OD-p|K3QC{1(f8=lI54A
z0aR9e*VQkJTjt1Jar;<5=*JY(nT}$k2Grto30Wfg)f4XHSSSxqhP~RejUeGWcR(*d
zCTH;yDF8CrCrB+!G}8_8u05c&-3#aISt5YdI*X<{UirW{O?5zV$h_tAVQ9#_K|_#v
zyMSDgc{`6yLgwv!mdU(bnrAR?L*~nOU{5sgr7h~;$wKqiowt8aF3hW>$?f4(8_K0s
z{5uHLXy|^-5|f{>blC|9RiwWui|@|@vV}1#tR+EwC4dJHgF&sFNWq9b6e25A7n2sd
z`g_f6GGvg621b&2{0JGgj%UbmQg=6kt{Q?tZUkKgg0XG{P>2w~;V%XRGX(<3Bnu{G
zlLhm|8d<Q1@5<@YPK4ki`m;S-Oh``aWH3k~Tjr>34TarrP;VH14p70*q3u|P0=hwy
zzSAqhE_V{puap8`t3gPEK$YbWWI2Qd>@ZC%1m-%@4l<xFq&N#=6~L0?M+nAwg$pU!
z!3KIIoe=garD;U4t~<!G3a}ahNxlfE&Bp7%+%ucm|3tx3y^?#jvq?{LTW24wLe}|a
zmaxuGQ6b4XAKw8_PqX-f^<bTU#AKs&z6E-UQ<T6B@@95+huJz0VyAWp!+aa=XqayT
zFt9G5-DH^2O=rJTtxoJI@P-o;xa)S271$|!LUpHz$p`HO0t`m^I8;KT{FINJ0Y(|>
zl0k$!xjyKMV<NdeKkg8Q=n-V%Bmuo}_R3B^a$i7aP((uBY^MQvcMW+r&{F*Ltqi=Q
zRqpAV2nLnO0fReH0e7O}a5p%S3totdCOe4==@DQ3j@*p>0L0;WBscN39v?9R;z8Fz
zA{Yl+1#nPm%K;xq?b;5q$w}F;|DEORq##hv4jAkY?iBkI_wD2@cgjr}-01_YYuI!~
zQ@mT?W;@`Hrnvbo7;`=okPhvEg_gDpV9J#6GJN%Rdna$TTW*PW4_KNFzTp9@%^tZ6
zlXekR1Zz_|4ug0YncptnK1Y59g2I<GUBiT%HZ4N+!VQmXy1Rfjj%)(~;#X|Tcalx_
z$_J^DO$VJLn|{lOO(mNS%}6%A3^pU#^p?BeiEMhyUB>v;<NXkbajgj~KOny^^+Faj
zlm5mo-tI#<t?c1Jc@0<v${=h027)tM^C7#0HLrXaK+M3B!kSOng%%6GEXjmm$CO><
zl)~aRW`iA<rtqVS<nCasFoj1MqC#7Dku8V%WNIgX*kMOkiDPn4u#7tR%LKkQ92`Ih
zE(-)t+z2iU1b#ewgY5O8(hGqDfVgmAbi@~LWX@qzWn0+6?hDdOyTv-8ue#GLQVCdF
zB$seF%8iUpyWQ|Kd>2>F$TjUlFxhByx`H_US$&>zMm_|~S%9)5UvgF+$vW&7OM(M2
zP53iO015gIw7`>d@?Ri)%;6mdK{uPSn_un%M?FA_m~!(oYf)t}@{kE6!}qhnOOOzQ
zy=lkqZiavhRHbR=6j7O`nc6c=GizRun?UmsWSVA9+%0U+cz}zxr@=)zL%L)j=7Zg2
zfTR!H<VatOeB8syzSu2n(AM1|IDOAIVE~2*)4&j6+A|SW=!)Ffg@Xt?>n04{ME2Hh
z(aVwmA1?j%*)42Qr9HwHRoFxFOx%sOh^KxmJK!s<)q6mUxC4_{-VQNUIuonm9=`gj
z+=IcLHcKZW!A4_Lk3ZQB7LOv}74}e{_9_F|u}{OkSrR2J_I35qyQp7-XsBOrMNHJM
z-vnYszkYL%%U9FBd@P^I$6l8|V$=4BF^j%@oV-VT`FP+{Ih9S`qkZ|<h3DLm+rm3+
zRDn<5TiulBvmKPlBj8(lwto+e={xpdN70TN*|vvI+M&G04?mO(@U(lfl~*{X*!j_g
zN+ou2k1Gal--ZMlEyaaBboz*TTdvP;VL6AdGH6XW`)Q9@U3|1h_=FN)eH;x7Y=?NX
zhipkfOz9497#8m&MN$F%RLe+y{4TinCHTl(xiuETelC5F%@WON2el9K$V=D+0C!kw
z@Q855-t=?ifqHFR4m{zj>mUz&HXr110Sg=Z@)po5bRdp?2|eaDo_+}WA{-+c>^yX)
z3hSBU%o>dA4Uily4)N%Y)RusK&1#r4>#WuLAdf*g;vf$qh7R)he2-H-SCVIb4fBrI
za`baNCLpy&Qaa?|nHUj#;5YIN2$i8Q>2v+Y_n;zV!XY0Yf+iA)bnXmm8yvy2?&i1f
z1`jQ5U{w>c2D3FexTWZ3$Qp!iY};Kt{WMHgmjekXyaZXXvCsGL&+f}r*vT9&eQ&Yz
z65q?O*mrqSwlasl77khI8zjFJ8ff8Jn=BQ=u3-t%{p<KdW7_o`(tY3nPQMt*10Tro
zE;dFykmteoYee^h9Gs!l<v~xOGlSmF2zlU%?uFpsTLT9wH9wx{l3JKY-3u;iAyo+4
zEBJZ%NN#9<fpCnHzOV6f-!}pSKc)A&_$h-=#7~*ME`I1U=q;#HMmb;DWB3d@N(T_F
z1Bey?phGAADDToc_Uk`En7qwi?De8!cic-IyUkuh$9`om|MX{hBO9<+@5HYlU?Tzj
z_d+LrgN?x=4!e(R;SCi2RSxE#E(#3h@YIsc-Ajk=%-&0D9v6RwRhGqjMGv1%6vVO_
zd!2Y{sSk+MEo0y?7`<DLMXIPR_Tdx0y1FGko4aLyEMjb-=6l`Uk{yP|{7UY`&g{kR
z$j%Y#)E)W8E3oUs_lY_m?-d=9&{IboyO%Hh6TamHc&@{AzVSqSU@vyUwd}!O!(5`@
zUveKNa!Tdg`wQZ9?3tENr`7zaL($HYgR*!=aHdV^hV{^HXJ#v%VY9)=TXOWmTlHD-
zeYpBqmyZZks`BfSGTdH#pGPxR-G@?zfTZ-L+}IB!$oDd(ENi@v-)73I_NrLkD6=B_
z#5es#ya9=$X*ysAb<TKvB4v)>N6LI)uM@xIIpnV-xd`T<kHLIsr(l&&4^Uo}96Ig&
z_u<)JMEiVc5+-ZkRFB_BGhpYcZl&PkSxl!7m?1fSE)33k!II+v|Cm0GXgFOdm38l#
zF*9Qt9k@;hERV;6bUZ^9XVaU-?fpIZ87Bmj=oZW{8OF675=<D+k`;Toy@<hdhSN9%
zW0Y54O<sMy;foG@X@dlZwqh;`?JPc#(9XJqhUXZxu{X!&H+MjT1^7e<a7_nrO#px)
z9;H6Yru0TD(6E3qoOc<_s_~Kem7ZW1K@Nl2gMFBBf#usz-T46mF(P{bY~V?29jZ(5
zb|1N<ME6iuuLQIGP?<VqNql1a`J^DFhW!P?G>YaviKZe?y8#EL{t=|~V`cYiehQw>
z^qpt<$o+Ua5=36F!-vB6eNl)9t~EfMB+7>PM51iCAN5b33`P{(<nQ+Jqmfb~uWeUe
z2Z`jQ*%hnAx*+G`l!uP{IiwBYzub~T`Rq`o1xpfQ>4*@GV(GVEh$W)5GL}u)FAUk(
z{p6~!WT*tI_ha`{xS8)KI}4fUrm#)>#d(*ta%eB>`u#N5fn1u0jM`5&&=)?KhjeEj
znQLE!S3J7IM|o<PwtVCxxiN3@rECozfILv^{De;f_VX6uN_Bfbd@;68dthw?e7r@i
zb2waC#eO%oPMl}?UyQBO9&<efg{>2G05Yg`g7Jx3C-{J|b>jAGty4<qE4icBODQ8+
zr2~2kl|O*$`Wjavl?m)+On2DJBS0h0dI#K%!>j$Q?S6<oAX=v<)PmNDJwUB9_yDyI
zWK!!)I$&y@@dv1NAeUOF)d6Z9UkIsn-aCLHw3?PoCicrrI}5w}>4bHywbuf8Y%d=W
zXpD;lGF)R^a0BFv8tgPaH8{YZSAgzR4_}N8RtDHbCv##&XsZto7)F-iFDV1rImpK4
zgD>EY@s`h_K6C~U5*>K?V<lw@`;}^SVm|=`7^Q+cMXBiMCH>@LW;-b2Rq{a*uPSg5
zNHNSGPeZj4@NN465h(&F6e)r`MT$08Rq7#ViWEJDI|e*HKOm-Jp8*LN7JB8NAhS8Z
z1~P9Rps5&~u^r6ctFF{#T@H#Pal0QBVWDmZ`J^bNDT6zOa&GG4(av`31Qifb^Mf=C
z^U4Rr6j=c|QDmhI0`O2Lnt??g6f>|$<eF4@K0c8u&p${5on~_1uBpVJfjLwY4a~-a
zy85m=$RRC37?_Q<;h>Nl%yih-AtWQxJs<|OyJTQKJSYsz*@HrbZ$c$d;j;%xg}*yU
zDh!#V!hb^J;DNfD%KdtfR2Xteg-;$N750UX0v$)*g^$<E@sWiU?FRx<7Ar4nuwaTc
zvbfSV#Je&yol=6W019;N-G>~J_O?6(Px}t?X$_S!A$u^{sJ*LsZjkaaf7DQ!3@bH+
z_wgmQw0)Il!PbY|qd>@NFL@ye?ZWyXE^3>;_(W~f_mI)dtU4&nOp7K;E8RK1*hG1P
zU-A})6RhyyOg8QiuNI?hMn417DDX87AsX8#1<sR!Hp&^*Oi?9iwIKfJ@_;JRA!;WG
zi$m@1Z22LYuO6ZT82iE$+_02&7=GB`qNtYzN6fj}?7XP(rO4^905+8pL~Z*i4BZG;
zEA_%u3Zm(CSpLHp^cOpLgc?Zad3I4ae^*e4<nUJ`po!_Q8lVO~V_>xplZ!5>Wz7$h
zRxLk-N1Zfa@rUV5O!!C-;Iw6n4^d3+c&zdcb3hgz3g7=Qff*;j^gk@lNNLwjnZss@
z+E7Gjp;moUoRY{^YSotl(YV!j>tRyvrH4tm4+t_K6O`M1q9FV5Fq&HJ{9sMh&jM!n
z6$Gv3Jy%Vl>Zzbg%kw)z%mGw9Hjo7$5eI(4J9QF`y!Sf6VMCQ554kIUgy7UWLP9Ek
zL~!?8XQecIMXL^p#_A8dC_`Cqt$Oz(T&e{h@g5=Ox*s9tCI~X%4YlFtZc0lw?+Bh}
zI^U%U$)ezDQ7{>R;5jdJ+{$(VN-J?lFF_h`9!i=ufI&grwWgu|T1Smd|C8WK<iX-u
zZd2?Cc#sj$jqNWLq%``X6q1llIKc!|p#h!V@2hLzhzMI&2~<#H|3nu{m5$OF7~)-r
zN0tODGU|}Qip;}4M^+^6C_K$O#4jZ(<?Sh$Y_uX{pey1SIHr$Mo)7G!G?n1HIAFq=
zaHS0Yvkx3o5f3NB!!Rff66vm8{`~<g3^UM`Y0YMRKjjbU9YHj0u9|vOL@uXd8l9jK
z2aFR_^zp(X;0AwmVkwem7z*Q{9&RO@dX&D>gT)yXDOCZG^sU-)L)y`!A^^JWs91zK
znI||A0oBN%2&nc<5zrljlq~pgo@k{A=%k|}H2XFn9q3mzr_x}UD8iXaL=JKIi^kzE
zq85Jp39TLdDp&^!7Ta>oqy^{t=JXfjG?Z5lmLuT9M|XXIPdkC=!`pg>jM^T6>;E0#
zx)9XygxLdpd3Rbb4{&|+1SdqO@k=7qo<W2GIep($A|**nAsPN;l3_L8ZnUxyzSt6|
zaf4e%u27N;Ow&HR!P6Dtz$Q0+n?2~;o(Fvyxuh{C4OIa?Y0M{vw2wT%UC$GoU{|A!
z*wvm%W0dhqoTMcXx9Pb?jj6^X-&UT%XLYN4qCz0I@-e}!jA<ITA5BoINwD9S3gHq%
zsbglXDSOPf*2u?*TZppjRRKP68*4~w?E$V`p5P$(Vl6HxBVIKsiP!p5U`W>zh}Xbl
zW?r{WRldUDsLtzTjn~NnqWb_HZXhnhgSf?c5I0%yy4_F};1jP$4QYowz#YpIoM>5%
zHsV%$CT`cwRAx$A0&zP*a0>^2XSW7lU<4e-D!zysdz4&cslUiLy3AUR^*u`dIBdX3
z90aXQAE2@0WGwp}C7-<S92nn1kBbA5i-}^iI8yjHAD*lvNrkmE{CTE6Xwb-FhlxG=
zcBqJMIXg~nxmP~mr^S(YVU}=lBxH=22ZlpNSw9DuO<Ek;hFHk`YX_tX_pjY?qidd?
zs>JJVU-@}T7k;}h`a$UQ^*N3wsB1CeM)Q^a(ip)(1a8;sgAk4G-)Q*QOAn3s$fX%w
z&*O&CY%GGH(aecYV~_K&G^MhAG`<)|v)%w1&(G}b3nk8`*I)+mxfY+u&0Xu_6XU)~
z{6;#sX|7cr$3kVQ1l~EeB<)Asdz^Q3Dm%d~6luudUQcZ2GzM`F0;lwelDH}H7JS(Q
zt{SZJV;b!Symg#>+`mMrpc7IH_!f@lBLz>G<|FC}a?$_<`AVN2r}>C4-1>Zky$m}F
zachcUF2ZU9Se#1xs7Zp~X%zg2$QlX$^%L;);c>oqiSm;D93~qDzgrXhZeOB6!4Jgh
zB=|x2M1mi5!l+>5m+1=DoEKcK3}(|$=<~nHCkz_aV1?43e?Lws%1OT_BS52mrJWG^
z)o>-u(BC^D+|acrgqOS<fWj1T?Fn)ukDnla7Bb08Zu+H^-+5$pG`o6&Uw+kJp9@|V
zvWH?M`;{k1_P!8PIOB!6<^I$p?xQ?Od^}*+r+-f5h9q9<Bs@7!@Y3r+)zdK9DDerv
zBsy-3*DDKgm)8W)Q2Hu%@&=e2l!j3dowoWSgN#sJfCnBMNQdGVf4rw;NbN;F{q9oi
zNijUdVjBGJ5}x<bPvqlIF0sUu!ei@?bQwIhQcw>)HmFaF%v4|dr6ui|erf6SW~CL(
zREbhDtF2E8OIG)!h-B0{DJ<s-QHF?KDu}Lmk}T)3_aVf!4XWV}+rjo5WST5z)=7SJ
ztI}11jgpjxma`_(Ng~q%8t-fPmI5&N(#b0y@RQ{%Er8In@&q5sML~`6a8f6p!!;hU
zkYay>Po&u2oHQ!-$5~2yG$^q0JAkKVD>LxB+DzAk`PoU#*aMy;rQw7*<QYOTYIFe}
zxj-4_D}D6>@ce&)vjuep3O)suNr9^3Q}8LiVV6?LUI1T=3iLauh#syizFSFwFHnJm
zC{9s?-*n+=zX=p|$`D2P-J3upL|>r`<gp=2nXop9lVlT%Pb8bzQ^ugeZ_sWSS)Q1q
zG}n!;-(IC7Xr5a}38(n+y~;W`PRA{y1cYdm(VHlv61>!YB|k5?Ux|mkqR0+?9ySxc
z@^}5D$+T10c|&~EM;2hyW8xC!mEbW5o}{=5pT?ZxUmj4(+TX+%qZE6dq7f&gr#Csi
zB(fKakwo_46G>zrNd&pqHX$tC!+RW3E^;*kTcfp9o}D};b|5S}tfavavA`Go-bq)!
z><BF2YYDXYT<fT^K>A&jz#lzf(rL7Cko1H@r=}k~d3s7Lay`mb#<Q@~E+cDy>d8as
zX;`r=!OIT`4(6f9VNzQb3p;!jGz8u1pB5Ik&S_zBTSFzVxbPZ(MX4j`!8aP@2A;+d
zDvcjHrIcg+PSX$vd1z+&SBsT~G)wkD7#dFLF}76=UiFL;*0lU-kS8@*CO+Y-Yhe?g
z&5KT<Sj5<jKSDFQ_8YJzKsYXJt~*T&n;S?%w6Mw60BJsdsx<4gSk@%uw5(bFH0>`q
zovS2hTh#zAE^s<m4fPN4B!Hh5KVQ22yy9T+LP7kVA1Kq=ZIU^=aXJUKl|fYWsV3eh
znt1)rka(Y*rU5PZ3=L@T<~k&gl{rI^kq{)!`1=t+ApCv={xs?)g^uK78jMCdjQG)Y
zq%#z^(Xw85Wnpk5jQ?>3T5Z4?5d;E)XmosVnmX7GWYO3`f8b5mDkZsoUKX2mMvt}R
zMci~GPWyh&8z8U@KdyT9G{1aRX{wS2(3XSZa4uVLaXCZi!-g}w=_g88`wyNnzjj(Q
zdbw*#ZC>OWSn2I&^hJQ`9J)soANGNw@*^O4tqtD?n(>>u6K6!UJ@*U^sy{%};*V~&
z{8X9GJ|!rf*wr&MpyHht1>8q$K0G5nEchPT8yfx?fEY*A4fsw!#~|7WAkbvb!V~uc
zO%z=Kpfmw0Vn_=;E9Q=VXDJvGUhM2Y!lfY_DWnAl1d87VJ-h`=c<_P?4)FOGwE=x1
zkb8!PYWRU7N~4c~KqM6Zzvk88prQCfn?Mep*&phM<dE^}iBDwwdh#a+mDZr~wB&mF
zj`F6i{gdv(Q27?Jr~L%Wn`d+2cVG)h68y~8eu(2HpCtnW=YFDCXonLdt-b^2u}}gA
zjFZnoN9YI(E0`jFj>LCAU^!>W_y7db;+bbji{C^_javK;kKP4C?$EQIN>_?czN?gS
zDc!xZsB~d`^F7!T@D2honw#Ngh2}N+7J~O+#eg>2Qv^TuI)*)fOk8&gI44w$og)={
z2aZTX6<c**d7BkGhl<*Xg~3;uxb6gZmx?uJ)z695rYh&iVGEB207mt?hvXR53u@C2
zWw?_Xz@5~f^8=+Cf~IvRJKSmBc}{q1FV2#;#s+C*_7`M6KZ~APPTfbaRL-WH6KhQq
z&hZ}}LyN(k)|#H{0?}Nvu^RCH=g2kl$_HfRnms^SiQk9_8ScAj&<U}!7U#t8M6^KO
zN#}Op6Y1QJbL5_Zm8E?GKY9;)hJ6A@bO1+n07nG?7?rgV`-@XKCw^8AG4}Xe&WvA`
z4_Ngg3sB~G3Cx6xA6_QlmZWibIff{Y;N>g=J#~&x{zEBO3@as5g=8w6Oa+sn5I^*X
zGL@A$pVQ<|rI5r*o_9viF3%@CQ=&0(+cTxDo>=-hCGzJR<f?qcLjRil`MQ7tIme$X
zjig|r=<!UznST~s1f0yeDuUr3_^DO-<ldIzQby)MwPM$>IZ%Xt4ErN|qF*^~nF3Gr
zo3lA{;fa1BbaW~_(a%ms&x0rW5yI^G@I*fwN30h|Nz}uOKpB9~iO%53CE)kgm4b+U
zg`{?CL*?}D276In!8-J7Y<tq+iGCcbFa9_P{T|Pv40xiS-ypHdDCP2a(XimN8B3$u
zu(1a|kuJl(V`_mZRKtj`7S^Wo=Q}QgCpzx62Oc>_$2T@u15b3Wk-Pz(=v<9jo8XDQ
z?S77*IMN4hH*u3WeN53Ax24h!XKHTTP~ljLmy+l6<$K9lYj&9cd^HmZ4bf!^6*ZE!
z39HfG%jLL1jy4j0i%+y6F9vtJ&=#;T+~`5umJ;!a_UYWiC)$P57B?EuwueYuucZa`
z6}Tu!i<6@;P(%w1&3ocho}x25@rl9(<8d}L885%!41ne--BFFnn?8lQd=g*3z>C%f
z_-tkm)U_&(uBCW#fLfpm)i5&p7;BTycNK>e8uy1{XNLjcc!1hb;ve@?Tl1b4b)#)L
zh*8*Qex3(gRc>2iNXgk{RWl{qE<+OUtf(VwhYcyt?B4Zxhxw8}FQ}?j%O1omGS>bu
zTi$|iwExKjBtccbGJ{Plt(GyTOtGm0I^FdHr^_#K$mk5m4FHv@^i3SrZ&1I)(Mh9V
zYn3CU5`f1tqcjKglYfI9yvUfMX6mxB9tjb?)4imWSoC_qa>dL=wz-R(7u(HC7El-4
zo*I*pi*REK4n1)sjyULz*Ut0D8(|-4$%1O-4qsr!uYh*Pm-yuO0lvbMi!IFZW-HJn
zR3j>Mj$?|N^M7;`=Vr@X#G9>2LF#&2aU@3w1Y&i_mNCVPtq%2ot+*yZ8e5<1Y`x^k
z7G`;~Wi_#7L?zfV=NEAkr?bUZg{b~vZhiCSYirY>xwaU0RgEuWiWgsp?P@F0QulS1
z+IzBuS>7xuCYFp?1WV@p#%{WFmWr8+cysi;S<rX30q&X_N5&K{j)sQ0IQmiNXpARE
znB~op&BT!ri{Qwd-_K2#&JkZ#_@5f7We~T`b63?^GNyR3wBVH>t&x7vSz7AJ5@va`
zRKUcN5eu@^GSsb4DQ=o{c8Zy+dpD5MI%uVBr@N-cjWNZGo9e~YR$*iuZtL9S3U2tt
z5^7jkw~Y%jQE!AQ8pNER<)*{Ufw_n`2gBP0O|pIJuBmZgO!4BNZmg?49_k$26CAkB
z8)kX8M~I0dBNoAtIsX$kU2cxdMZ7tBP*S~Xd*QCBab!&K;^=le7e`;}9OeJe!(d~U
zH%Em`92v0)j?DSb+;q7)G8ggY==JtNxwdjhj>%vfQ@l7@RoZ0+p6DFa^yCP$yg9;O
z5_R_rBNoAtIlr`<E;mQ!BHkR`i4S^Vi*?u3+Q^vV#Zjf#f?5kx{hiLy>z*88mN!R5
zOdJ`p2#(D8t=)9#9Mv!vF>*wE!UvZIca?U7Yrmuizoj?r1_X~bbP5`58|j9qacWHQ
z;<QI+7pD(&PN#Tsido*A7Bg{b#6q0%5fxQ`gV7u2CQN6wm>GtVRpAz0?-I1h#@#hF
zmW(N0EPc>5sI@S9k9C&T3zm5Af+nLEZeqa*Rj_cUl8J>3Hz95o%rLxJX#IN76Wbwo
zO^pR(iWdt<s;HX&eW9~(Ua;V{dYI+iDkV)U8L<fcGw1Jj)8*#KT*Ql`Jw1X#CEJ(o
zni@yO6fcevdb;%N8=a#ko*ZG8H%AdBj*M6YN9O!HZn|6?z4W)P+-JRlZrS7uo)*uT
z;>Asq8m{*FUgxGTf-pMWnB~n)X%ja_EP@+zexRE!7dPdKnTvR}51*PCG}2bxT~lix
zV~Q6?4g0v-=Z?-%BTtSn%bTOJCXS3)L?`M{+ti7wxCwK!WQO6*(%!y7U)wsnYicYR
zQ@mLEwx5foZ*`XXda{IB-Yk_jv1G&|8p)jB(M^||BXbcGM<eU0$+ijZN*Xi96fb6!
z0WN0l>C7a1GJ{#(%v3ZnW5gnuG3SqS)8%HyT*Sl-eJnj|V9-+AYIjYIBV&peM?(g=
z%=FhfN81HQd|F+TnXY8wzz9`n*wlt54O`(R#La>kh8GJt-#TE!hwZex>Urnt^DTH<
zAvLgQ6%+mw?lNxh<|3ZptLA*(M15NdzwNFHvuWdW{?K_|e|S&_+c$<1{Bn$1pM7wi
z=WnLAEawh}R5g)fg2@|>2)gw5X#PA}u$Jw2UuZsWuGadOX#N@*RLo|?%;TRiO<HF1
zZn`nKrDZN+lorICVO8agf-3LUQmt6_eGEGIhyWQQORy!lP|n_#YC*~1ZE%lh1$~dq
z6P_v-9@a{IWy(hoAe)p?(Qy^-vH2XI&~1zs`6=lSSg%1+oZ~uOSE7dAgh%0bIc`&G
zB`6l>_?({a(Dg1|zo6@vaCLlzm#^UxD>=Rqw|j7lo8tHuZ;tQidLMI`BO9>91~|UQ
zw*bcvl=XnF58*n;u@&+MzT$WUFOJ7}d4iW8@$!?N_A@>`#mg^v`4um_v0{10Z}1#9
zut=Qa_jBDKp^9TQvb6>;e_)p5Pr5#%>tA$zPS+Q7%?Bclb4V!IS{LEM=-m&lJu@6T
z0LmOkz<HiqC8$)}KrCdz%lnWX=h%!mw&2AIiLus!U6LI#W-EBvLv?pz_Ab1rkeKY)
z29L=O+j)NUrGnK9=7+R6M*+A3vY_)ka$HamKI&DqJ!^cCC$>?`@Xx9SRZtoNVbD8(
zKAyi?P!ZPXBF`KfRF%b1p|-*9eE7O@j3Yz<@^1jucu=*V&?)WUX^f)~;DOj#n79=Y
zw~EMgIk=2+6mzE}k8(5sJ%G}f<v_(8<rpjS$BWwpxB=CZ#BGYWO%t~n;x<#<W+%WM
zRAmm{@;Q>>=9mkYN$~w=#|*~;cmzP{;^u@~oFhZLETR`}&W6Fwq2ou5?mcSAm;n^r
ztOB%whLyXxXhKjM%j}F%5J8-lQ>v}{Kw=X~Hl>|S-zpXUHu69**0K0R@bGD1XliYz
zv_67QwW>DG<J2{_`Gx`*?rq8MjLaWkpKC~_wn(|i*R)q>OVfCz4r+GsZJ3{hmmPT7
zg_k{e*?W=y(m|b8?l8P){ctrrLTjdAHW>l!WSbQiVSTVT&xu#7msp0GM6oZ-mtK*I
z@e&=?G2x#47@%7C6UkPU-|VP1vwe!-G`8Jbg@0m5_Mj=0#|$i3g&%lLt>pg$6m#Zw
zDeUL?;UYiMO)bXYUaFH?-uANr0FNmlmFHtSsrA^Ci((VQG*I?b`OT#M{e}-s95gJ$
z@%$ox-brm^ck^CYaQP5wEVMQD&bWV(_5s`P88B(2F6yGT@Gp7EMO(>Bf;PBM?gF%x
zha8<}H*IC$^b_1*;YC~2C8Vt;PwT1{HqcQ-5Euc~%miu~;g|l7z~cPvZfXVp4my<`
zG%DeKvzuDh*3CDSo%5oy4^dfz-+x^VGf-JnP}$LoN-ZNUZz?%xQym^P#lJ`iuVyhS
z2o6ZRZg;hd-G|cgRo&H?DOCUe-WW862BH6ZV^9JOLZF@h!5Bm$bdNy}f3Sf6r-z{_
z9>WmX{SZJ5=HJ(tQPJ@c_Qp$inTz^62QFi@;X`C5Q%3R_Z4{}f6~-D^*nx^Q#x<Z!
z`Jay{K-_;ipr97RcrnE<ACGLS7UM0)sFitmZ?%eTm)<A0T|#TwhOg+Ywz6d#lb`ff
zU$q@Kr09M%PfJj1nhUQ!42Pb5m7un<UGY_emeDR_4q1E?p4^`;p*cGf)sl=)sjeyv
zC`yF2CjA8t{<rf|{nP|KMbDPE0Z15VjzQn=rw;ks0>hKkL4RAISbsI?Zwuu1SG(y2
zbho(}E~Vwc8cAiv0QGxY*k$0Ih9`|ZbIP;|tPsCGP;F#Rb|cB3HxiQHl0j-i#;epa
z$j|i>JVbSP=NLqHXox!aZwokvs{Q}AK*%t4=-(E|{igyWhN~~>5Zr9z%7ky(lC3T=
zLakY+GH7|KWyqkuNyA1ZWe5*s;5gxTNTeJtwL@*u8v%w$I4S6<Vx4jflmDMh|4(c>
ziO^uv>!BI^zcIDIiNoDDVK2_q%igmKpi-Y*-0SRLLEDd*Mn&~G2J&K@V@!drE9Mvr
z;3<ze#&GQ4L*Sy%F)+nF$G|KHn!W#Ej?wMEFeFeH7zM2Z1K*oK6AUp!F7vQ4>N?wD
zB#}(i-pg(e+IGO09R8Ntnk~NwJEsb>H6ZDw`J3^B6N8m0?*qu58F8tBi9?4D>N`AR
zRz{*@KczWt0DwftL3oMvcN~ISoZ|>wlO0FtnoHMXaD|D}ae6rc*PdEWc4%{n50DHI
zP!MCthmbI)Pom>xoWwalNDXG^E;_S&l`>2$jHJ^z@xf(u1&i^WW7S^adku_fxh@op
zua2|9hgoPH2=V{34*!XDAQ2j@!~Y*WKF4>c4&T5<@4=Yj?!lPlK#lr$J-7#SR+#d8
zgbDr&Js8!N2iFdY;N2#u>0t%009oWz+3<<_uk8wdF+ojW6R3xFEa46g7|W2(m%PF+
zO;qRGDjO@ig8~%|$y)iG)05OxKU)(+jx)yDl&_qohDJ6pq-y1XDC)K<c%qH3@T=3*
z#;n5?9y(o(vUM~R=ke3kHZ1N6?vSlp1FJaNK{gl#;_h!C+XUpm8R`eNBm+bw>wg3&
zzW~(X9gy9aD}2X0YDe2x13*FIC_!S?{|Si&c#KV|&8I%I`BxD9_>inoQr=DHqXJ(r
zOI<Fl=Lv1paQ^CSwW)nAQcLn$1yA7oK>J26RGZsY=ow3|@b71<RoJ>KIYsBFx&BhF
zsQ+s!L@nI)59{@_-?Y_d?_J@mC+4@?4jSQPSF?rl^YhdwK5?w7MEIakV+r@YX&jYz
zD`Vc}V=Ifu&bj#z*?EX4U3#snX88ApWDiw~=9d#xJ5OJrp0hnO6yw>ul~!d-VhX8b
zO(7~XB%h?3i;!GhKwjpFZ>h!oDmvhJ;WV`f$d#vevDIWnKSBp2oMm0%cPAEj*&y1m
zkBm(d;%*u{WB__NYeoRdNm~f*%W7zlK7g+X%G#P3AXV2PQ6m-q$g`2`A8}};5|&%Y
z^KJM6`PXfwL}TU6k?+RJyL{{`B<`FaGu0lF?R6kYZ!Hgb$No3u9iNB1-^x?oqjV`@
zS1`zXgr~e`ELPVuwjfV=r|OVM-s8OFJ>ox;x4}~TkT<`)TpbzyH@zmB$L}prji;_q
z<88UdcF=oG<Y7ayN3ZGcQ}h3(!jL>#;&z@baZ{I{M@w9X43p-EtX9`b?AJV7;%6Na
zwZt8-mbjj0OXSUwLGukQ;iG&`uXXA;$yV}XgRWm5WQ*i}8z3-J-k6M|njaM8Q_mGF
zVXhJXTrJ5z*`T(t)$^>uN`B1Wd{0gAsPK##&DT`Xoy_!s6u|<$x=|g^I(&>4h}H+n
zqG30gt#`aDa|~DHG~T54lx)3B6d|D}H^YG4-;|64cCU|lyDe%79~CmTs7-C-d{wCO
zzB<pNf|;|~-o%l9c#n!^=EZ=wa;rM+@45;6l;2nw9@=kH2itu)L?3QbciG-I60Y|j
z`zAxOCefVx+tp=K_<oNZ_l|E^B3_fN&b1vgl;9&v7l`3+?@)^cegIBkY9$`?tYA6*
zI9m-U<eK@=!Z8iz`#<K_cc`;$MjSlxJ2>iQ)s)~s&UdO2wrd9Hv>pGio$3HK(GNdR
zG*_g6+Pk~d&gNu@x)`-9Q?!AZVbZRge!JBe=$wD2UW>hJlX~&cO}6K@fUAa%<1t7q
z_pWJddxQUACe5VXYx6KorLX2SD3=0~g!*`xrf|qGnx;J)Y%fc!fd<HXOs=N`BFj|v
zs^^#-el@Q#Id6sxmg(OK;C-Rv9S^DL;XZU6#7`cOQ}|g`4y%1^Lye81YkauFknCYY
zcJS4YZT1}d5p^uHO)!+>WZD{BRSWa;xnLY-nDWqUOt{LM9#gNIYmo_cd<P~p(^rK{
z$JP4g3aGLr-2U7yp*lv2`P(Pd%^`ab9QCA~@C2=y!_%W}@cnm}{B?>=)D|uOrciDE
z{Yh1^8B1{Kl-k}Ow+T3(v?weNES+!)OypNa(owfV+yv$bBJT3^ZZ`Z)@DSQ&K!n{A
zgxwK@(fOy-PpdU-fBrML-~JuAxo6bYwvbOedY;{jx`Ln36wGF%4R&|bRc|6GMC^49
zqgB<Dc3$P|ocfaV8IO5aEh-uL7<NuA?cW3t^C?M6ge}HM0!{iFeIiyK-K6Xjc<KvM
z3}UJam7)DK@ON@;(X96;{K<JW(w682w`X2(-}nc(B>pNNsz2H$nSkOr*!lv@NoJao
zQK2V&Lf?OSQ~>=n2w3ClZGl~N3%D+ywpI<tUw;pA3%QnH)hy76OKNTZY{=m~hA3rh
zJH6=G?#1%~A<Or@c-|xs7@O+QW$3b7FM~_+kr(8Pc|rc*-#}JBQlHr#8-ZfqFbGE@
z^MRLeHvMbiP_u#6so)=S4J34Fv{KGi2%hx$2x(i;HBW6jBqWso8Y#X(+Z3qm);0pa
z{u5B<8j$YH{W8K<%L{r`UeK%l8|VSo)j75fCZNyNNWTBNTEW)Ml#Dvp;hNAna|N@`
zX}q-)*bSXpxrUwkpY)A*o_#|t<Npqz=a)Mvk+xZ0giQBh`iKze6fdSHLS?r|p#$4_
zqhIrv^k0YIA9uBuvTg7Jza}s6EB^sJQQzv8y4iNj1Qh#m@!PP2;+!cNWqRxyUwm7Q
z_Noxc3nmn(VEfEhg$up&m+-1kk{|jUFg)~C0lyUYs9<h2O?*eZT5aOLZ?)vR>P!B`
zu7g+|)07IfaCkCzgd*2HJ3_8#wb1LH9U%lNn_4ZJ)xR#xZbL7)_40yS`yb$9bLDjY
zO06N;x|yJ2A0Y83n3A!*x?LB2z+AyBO^vP20==ORgk1L+*lOvv##RGumF6?h=EnE$
zsX=PCKHzQB#=t=S{GMvH8=Vf<#GvT6YFWv~jWoMmoR!98GEDqBfBK#Jz+Az@#W^8J
zGGY_cwgKO(Z6#Zd2`H-htsm4{wj-uw6kE=9KIj323CtBhYzBAgR9?86JXD!vyJiIH
z;l!Wuu1X5z9RxIT;^AIi$is>M`FdVX{1YI_rxX7WGC+StWG#3dOop`$p`{_toH~bx
z{iyb}!xzPgy+<UD9#}1LRPPbPM-3WRkw1N+Mo52?KkG-e6wCjqAjo?%pnU2gh$aKS
zT=$#|JcPdDJ3yDWU<{K1Lzu!xc^>yOxY%`p2EF6!e!abxA=#y{3!bX)1=?B~ayTh$
z-)G>Hw=*V_!nXXBKYRu*uc-pL{;mH4C#kn*h5T3$nt^^CqYYpEE9^TdHs4mj3qWhz
zNYA>g<)=AMo~sjCDDM8HerZMvx@!pSekqEWnFQ3{3TQ53nniw}hXTH<wYPU@HxtPA
zselUw=Xz+D_bF`qj%DYmINNkUq&Q1H^;DdNpXQ}Fc{5~C9K$R!@A9!v#Vm4DG23om
z1`bYSx6QGAX>2N8zrybrk~N`#9@4DyPZ2Pl5^j4_vOO`B^9<1cC0fx8%4aK@ix^w6
zogcqj()Nwbdc)8SNJ*cRvemK$nUc{oT5s@45w@1*3e*iAMc8WEO8cttcBC!RTmkKN
zIekLY&Z->&XQtE5N(J|_h`ES~l>$;88u{vtyiDRNK(0@XYz`TKUudMwXcBoN*tE&F
zjj`qDF=cHDtd9oV+r0JGfs>ZT-tg4Y<~Q=v(!9C!t)+RFZ&wT(xDX#u-u9_2+0;5X
z06Hqzn%dG$$<WGySa3`qXLd@MM;&v!mHMx=Te-a2ZEv3Kwp$miM?7i=5$>zqa!OUP
z?UQ(c3AX$>WvbY6C3ZQ_mb;*Xr<U9A)p9%jH(IWyXt~YRZT)S}fFgaE!r>+GH{z6<
z2p`><<|eB5UumMoc{Nd)n|XDuh?{wItrC!-cP(6K-B-i5$&WSEAbIzrmvu<g8s*?8
zYhkffbuYG-;3I!hOZr&G%e!0rkGoM@YK)wU^=u6!TVJ5aEpY5dS>HoH8f;2NYuWcE
zFIV4oJ5;Zb=|{gm1J!L;@Z%z*6^#F{G*#EUnrdO5O|?K5ut#r7g$z?u)o*0$8NjyW
z*;E^KNYqprUQLzyztB{JM8E0T!ZzP_#n>e1h8sqmVgD6*kIqZpkMflF54w~*<o%te
zyi2#TsTOAaEH4i_;4@bzBY8jZlJ|H23-X>Vy2elKZLdhS>Ohg+H9Q2K`VRs(xLtYo
z+;$6{(@xuY!;ZH8e;0lKQ^f9n=xAGIi#O8b_QB!|$z~s{-Md1CE`60hAg6FATfAiJ
zZ758Rm_d=2XndIg`gC8+MNIC?s=O3wqSpN04)u5-%BTDC7GxMZE??QzHjVv%?7eq<
z6-CrO&fSF6xp#LHT0$zlh7ceGq$5Q_=%OesKoBlS2a(=HqmddIEFjnbrHe$x0)iEk
zrho+rU69_Ze$UKq_MX|2gjZkQ-yc8td?xo!dCob{oawWB7dZOSJOhaP(WKwaQ<X8l
zJ55!bEwb-po%5%y)L1{+jkF=3=EL`z|Ag<2PJI93$oGDOCR4-RXXg8<?j%*Z?8x^8
z1Bmnen}zRv4}$N{G``37ByCB=A?J4c<$uEWw@!Q~A99*Q)B>e!{W}p71pmI%n|vX)
z*MY24h_(h0=R4()*}oGHJpljS!+WmDeaXgXoBasjpRNDW7P+*pYhpjLf=tEL;_JF5
zp=eXrb%0fBc+PtnBvvA`Q9kY1@yb)A5}`sgOjO(~BM{2>9(vNl{YVM=NPp6reqPVx
z5mDwY@x;@T14#|C(u^X_K17!cBo)O1usG~OHrwT$=q2;Syrvn^FS_H2=Gu0wViuue
zJ?!LoM;#sSFsN(mc)x2r89Nm@EuSW#F6oY==iM}rxaS?Wc;4@hp66^5>RHj!*g1dN
zX(tLQ{o&O1%Kza&K^aI8+FqOC<eJn}2eP)kMg|aLz*U9LO(4b4?7a+Kmq6@h@6Ptz
zxBb_g>>uK2{~$wcQ(r&8Y=6pVazlFF(f%0*5VwDr+5Q3l%6>Fwa^@>dqP@q2Mp>_6
zZgez%y`i<q{52-?b1FSc4){qwINJZcfyC|KWVV0J1F&Clu>ZEB{WlD)P4-_k*-vjy
zhM_0?u+tP>Ih@yyxcPU@=3jjP=0`f1-$d8iI<stOXl*jTJ|qaOf8BJ_L+a*eepdsC
znJ+avY#w>*A9fmfo&6cL|HAoyIR^q}IubD5(Az}76f*$<&y(k*HyjCg-2mbQykH?<
z%D*F^a05UBJha2E^>xf7oAX&Vr5)f?l!sm<WAeKgwLzPq+<uX?B)@=t#)8i`L)nj_
zO*53*)U^_3C||uq`by*!%BRgx_SYcw$ps;rZKa$#OpnikePp44I-9g6u3V%6KYD?@
z>t~ZYVqP}4i1F<?CrjG)IaZV(7ABOLkl43woxXh&`}FNow_okVl$!NYlKLdq>C>ln
zo#g&C)BDt(knJrCQ#E*k1>RTNdoCF)?cYI%jZsU{$rnhCxPpq)A1{y+fj8MpL5}aB
zo#v5;OE;GCrY!vMCIXwp-aCL4Pq9;+KjvCyKDpyZl5ttSmEVd2qm6`U#%OXb{e_Zf
zO9A~xMF+bAZ!RKLECpid^+lu_>0?)5+$&_8O@VJ$krXn@uE32~VfAORA!pEQq>YQr
zv@79WOqN(n(4QBRW@M3FfuT!aMrsj3&n+P{$$NGMY8-G!nhJ={RNt;n_=Vv?OUb(~
z@+C%PyCRSK9I>HIS>DGsga`fbLG0Lsgt!7-lg8g6#cAeT(tx_(B5=V6?$06+Zyabs
zYsR=@q;k3NKwzoT-bzfj$}FhDf~qX220>N?ojR99G|d)X|8@vcMtT!irWz3Fw*&bL
zSGnizhR8fu=F6GJ65Sdk#rrb}v}tKlyt-F^U5$@|#!eJi4<vDOHA!k=-^shK()h<o
zw9TU?m-2MwPXVDvAI>w&@=kwXi<;kRg<o2X?+rNC8E(iCJj6@abLpw&q%wLM=zOlz
z80Tz`{TSz*KdpTZbgN-5QU|m#I%MW+sPE`vL$r27;+6MEf{QfAWqo}|su0ckj^;<`
zl;7ON=I2fdv?;_|H<bsG5Q*(_>-isFO=4~G@@6{JPQXKJU@0kTByN~@wXud*+<m!C
zcL%pws8zRhZZsd1wOt&}fduR}Ij^iEql?0CO*{C_Dg%g54Hg|S&yD6Bc>sPhgbl~V
za(>ET9qfKw5hmvuX+yVmZT;<!$!>DoT-0~rAZ@fwQO?zBexuj5LAw`=E*{fHUEM+G
zYVtLWTVIYw`6VV(&trDQ4`|}VTci9Q-1NuXNhJ2Dsp%B+^-*JW6QYiquYW~ADX4b+
zrYPJ&Rq3q9-L*(^A<$|SfW~!urJFmMq!j|KjfRHqa77$tcese}-fRgiOZa}{s+P`d
zt^M=Ww@caGP@cVol<^-6;_2$I<Tx@8E5aN1n4|ov93pF+PS!|^dBdQzk1T#gdC^hr
zuH35@;DwIB^9umxytUs(Mv+Yzm3g#{njctr8^(D<_dlQ3^tSPwo7+iM>EKaX{wq?I
z{EDU3j3cQoiwP5SZuVJB*saOH*SBx#+}y^vob>CCz*h<Y=G=V$4NP`Q9CP;fJT=4N
zx9;JYW8_o23(w7S-;pX($}zeg{*wAw8n+=CQebk6YGjg5PAyF;x^0{YrA?0W_%Y3K
zp0EISbp-BQ05B)#(Ve6x8G}(xj+3Y6NDDcM$4nQ8ogL@TA4nztMIePX&F~AS6@Mh*
z<W($`bF|Q6$`qZW`4&^=Kxq?4AL$%@VgcUd2>d|-z?`FvyU8N5AETN$%2RWng`+uz
z=V<C)aG;x@>31-z{pcZAadI1r)LMeYkZC$YS1g8Hv@%rcxaLKX$5CV8z$K2G-7^n3
z{J41#5P>;E9e*YZNis$?F_ec^OG86V>|)^=iaJ0lN{=6>E#NPC0!!mIbhX$pLno)R
z#fA=0+T=cCb#lg8fX6rjk1PO~lXLPHl1&z3R1-OQYR<Qi)8Tlbo7mdlNOkF><Ma>s
zOFqHUI60dvHq6w?`M_esI)NN+Lxn@6tp7oXr|TOB#*<$$KJWV-;rA5=KJyRqBDs!1
zO%&xRd&NT0y24Y`I+v7_N}ZrX;4g_hVQB*=%x&NWoucp)<~E=}X`laaidG*1?@T#C
zn*_t-0rf5D$&To?3WHwi7_9ueVpJ1DdAfGi&`=9gP88aS{yI)7OJh&a5+`6$Hx5hV
zPBg}1!;3mYBP})zb6{wZ&d{qC^o5S-^9w*9)=XCE*QZDt*@RI|4CU$ifrX)AoFO!I
zd|I1J`mX+8I|3XgQg-#9_^$q6KEnJWS-bdevtFgSr^!@u66@sKHav!+P0RaPe4Rp1
zogr_Kt0<ecYsfEP-4&wQy7TG@+WIW)16d1fJWCRZ=cL)+p+JLkq^V7T<>%n!G|pVW
z50EK;Z?q^v+#i~wdjvKwZ?myq|5_P!`XwjVtlOtn?b>xS`lQsYn~_vExmN9@K7H%e
z>SNw)EKWl&kSD|)$AU2Ujw4<Ap}T0Y<FFwFueajA3wFa#+svW&E|99FskjH3f=xB;
zLC&+YhwnjdyhsB5qPn26tQv*Ky_ZCKdXw%b2YcMRS#aB?T_5S3?S&VE&$<ey%f9Ek
zyPTxoT_yhz460T7&hqXCWH?6REfNaMyiRJ`6yTLU-LAmE8>FF4f!#OY7W4wU0^M(t
z-Zll!J?(BwmfID0@fJC2DgaJ`HUhJ4NaY=>c_VN<+XyVM%3&k0w`KdUF=(c3|203U
zZU41my0&J)BP?jcf>a2yqTq)UNt9{(ZzrVa+ka{B(X##b1w;zle^k=8|Cj`)?LX>d
zxOE=~Hz1Rw#ajQ6a*qrlhd`RJ2Zr_{-gJ`Yv=>o_F8-T@pzVh9%yRKD=`ohar1ebB
zI}Q{6A&rRVlu1$FGoNYi=!%BYxjRS-S_%b0A=5bfMPz_XJG|l-LCO~b5q^Ij5YcED
zbc&6J=o#jsJO|n((9Ln)C3sYFS0L^35x!hEC)I3DYpXe({oG4PMj^oZm@R3|EkO(S
z78<(E!o5OKcO~*%K0;RN8c#E8JlU#og#h<b@_He_UNLJtx$qj_33QhupXMXveO=>^
z%^GjAYJ4NeJ&x=v1lVq~#+wSS@w*}JF62r+LRRY<Uo>lc&Z_a=Q1{~`<WEzJLAwWe
zV1a*{_bkp8UgchHcPCOMA1P~fl`CpeP{S+-rA!So)8p<+nic}Bkwxcnf10MK&aPZc
zaX&%Q^O3S%*SV)f=O?W?kBf2_r%OEUAlg@Tr<1XTz#VPT{>j2?4~z#c40orJMfphj
zK(}Cl#e#WO3xM_FG^LokDOp<x$W<2Q=iRsR3jM0M`ysL`A8{Y*7VNZG@STGNv!kF6
zu9a}tBPR=id(2|ScZD~jb!m5Lx_hDIPp6dvI|5FdS{WLba&$ZVsOyw4E){`7Cie$d
zilA#E+!-Xg5Qvc+5sgblP8YfffB{dChWQBjSXaBgS?#*EYEL3v3IW#9tZ`kgF<LdX
z;5`p|VEX*Yyj4>W?H%I|LQAK=PWqNkrJbib?X)KZb7S1`E;1Es2}gGEG$GDikz@+d
zY$-JLwC~8yTquTKj&oNdubB(^K}PM}T-Fkw$HVZs+FXK(X;j8N*rHbq{izIy_`<Hh
z<7M5GOa;V~zEAbK6FC82yRRAIm)Z>R*K+P}Nv@y=dxVECCjJzn8Ev_zY3~Z4xVeDN
z^KH8VDHYwZmI6A*<P2(Ae7OP=idJ%$Hx&>G_~t($;0ODoPN~)zr(2+jpsnp$XLU#b
z{*8;UG`))Zmef`UvYwGYVgT{8&N^qzXPwp0IGuHhm5x^z_GjeI`P2405b&%c0b>lk
zP4~b?nh410oZ$XOlIA%wFxx=l42-uhF!Dh#a9lg>%}sI_bCHihC1II_9%?!LpLpB_
z2g3I|628x%$wc^WGvQT}-OsqB3yy@JHIO*r2Q7r}eh`G;<%BOEP|ximCH_Ku^XnD7
z(}_XR@LJx+B^Fe1xr(rV-lc&M@QXDi{-V1YxJ!iVkM~=l_*O+Cg5ozX{2-&&g9|12
z6Wb3rfK%#b<`R-7DT@8w^DE4wct_vGE*rlWCE%Ja@Vopp<;5oH>$lP6MKKF*<!OO_
z4i9#Zhj$RzzeRQ|sB7DAjfMo=Z{_T3?0&MSl&vFKJFd9~68EBsf0;Y3(SJRFjw^z?
zM!1XRTy5!&agohJU9ho>?>cQ0qS@HB`7fH=+MQ)7ppRWY+ZEtrmsJ9vADpr)z{f7J
zfH-!={3lLO&dCWpXPulN^sIvu1VMt}1WnW2FBO$4>PS{6C}$vXCs59sognD!18{;m
z+zIHsF7Az_9cUzU-Droaz7ye2J6y@;+cv#4g6wbGSQ0I_ZS)+@dtdyvO{Uodw8m(t
zn=q5E4|n6euj!g*mdiFv3jww`e=vSv#qZkW6as7`2SaO>>1R!QXj6C&w1=kC;=G5J
z{-nF6bo4CEhQH)ER)S3w;kAK`47%ln6o{y5tWyQg5s6g&Dp19*+DPZLvu^)$$b0xC
zw8%Mr&S!&rFMnLlTH~JX&q$mA%DSa${oNf%B_W!1OL6BYe<_%?K=IyCpuSy!&w9H@
znj}CkgZ6&%Xox;%-uwBLR}9(`JfIO{vn80($6ZhAe~vDNzhr<#kA50SNNQ7^{B%t!
z+6(FlrJ;|(?+@gMp)=2EhoLW6&}TTJPc003uMD{G`?i2;)WIqtn$^ME=jc!U-ElSr
zVxDrhA)nh7*z%OSo2h_U2YGBP)AU8}aO_E!MMFFG-9vM(gLVU<4$hpTnFC=T;w;v~
zRbOf&{b^yTxn2h+EG!*`(!M(2Eg<B))&j_Ra|;MMZ$9bH11@@=yA-Ni5tuiDMuXk+
zNF@Q4(SK($Y=9;T(Tx5|=d~taEx?EJW_AVU4so|ONf7DJ)3>~)FQWe_ryuP~9N=vN
z?Mn1w5!zWUdW~Cm*7oc2que;>2^w046>dV;#!q{Iq}y<~*!Uc_)prs+4Mm$ydOGC5
zWC-4-KObc=Ka<}{cM1^(oI&3)K#Gc4gqi2#4wDYoI@+<0+wM;JYS77c;`tsV2y>3?
z(e7RWuJ1G;>y+bb1Bg#KHk>z4Io<<*wSPI9vq7k)(1TOX`O}7K^UjYax?%Zp5%bNL
zFBd1lPR~stntAs{-Mg&?cykE3U~YR*VEGhxN0S8bZgh8jlueCl*N-Pnb&sG`8oK#)
zb9TQ0En~;nl;Ra}Uw$yb!4IUy7n~-a4ZuiSN2mu0f+JL%;jZP99@mkqp75xF#66+u
z1+ypAyYR0(p>R#%1t$ugbEIIJp}1)&KiNz{=NH^}T+$Lp3SKji7zLG{hp$-yBS-bi
z7%?I{(_0?yhNrsp6IkDCfhPYuS_;=d7HJKnbe6l3i+lxo36pZ<zKd-fQFGtJFS|F8
zedeObhu^R%djCHBj#C9*bgaO02JNN_JOc@W4}Uwy-BFT)FKVs9>casS^I8M<;mZ~u
zKJ)J?t8hNN-id-_U2*Hf9<>a`O%x<Tf<QsoLU#|B)ZUSTwgwWXAmyUD87E$R0L^%_
z69p3-DR|aU+(f|`69sh5SWjbVfg=O+3?R<HBnty${v88_Yq8r|iw(~i{JQ%y7x@%a
zGFmJj(mF4JL+0&5Gz@8OmJzC(zaZlt-SxWrZ%UTB-6jASu~57H?mua_yPRt5FUK1D
z(;(VZV<$8#j9vSj4sW_6T$2AKr*`YQB(&RemMS~(@2aeD?e;e(3To<#Tib1dp}2{H
zs*oVG+dl8QUvWuo94TmJAaSp)b;;art6q8l?e>Hd1<yEAFv?KeM8R+q1zNkE<H*3v
z1`uc9SqlTh9|QyE{j^8eZ>@4a679SgN$a5J8?oBmE86D%DKvQgVCpPMTZEKe<DNpk
z2NR8cz_$qb21V-)A+PvV-i;J}{88Acr$4T9H_hq4)*bGmpRIHECI?YD?W!Vw(Ppj?
z&1T96FVVy6-IZ+$ByE60$IIpdZibxK5B*8EZ*ZR~osj)p_S9_S#lNC#aSnZ5?~$-w
zdG}B=YWMG7C#6r{jC$!Qwd-Zn>{F|6zd9MU`qb-_n37(nPrB_r)MB*SA$Mci^8yJJ
zZluN*fJT3~K%z?FyQtUoyQna;i>2|0+_7}lJQ7qo&_8cM#!o>)E~9!fT}r)aXB@wj
zI&71BM^RD%mt}o@PR6Hh_@Sx<A)eJrh08g0K6f{8*%W#03-?(UX<}1^9^UG1FP7l%
zN_z53cMa0XuE5bR-8o_bJ_2pq=B`cp*%fHN9bCm?27Plo?AVMk7jUzTd9KoP;bwO)
zy5=hwvBdJCf82JYu<6(CYW`%FAcXC2H2TH;Fj*)>GX`f}rnPpsZ<z{+!v1y?wqd7x
zkwn&DRJN=`vuT&VcCch|WY+=u_ilGfT6?!Uj!xX|p5p4HMfBVQ&+vbWAzi<^yOZrW
zhVO)adYS&d4-QR)yr!2&_&JJSOm`n}j}3`SAJQ+bckdDDed*YP?$^ohf*6Ci<3cnL
z=LZ?J<2s=PSM|C%v-JCA${&&z@-kH)^F6m()J9eA7q+*G3u?A;ci_!n(BxAsH;Yx!
zPP<uL{IYhlID+XL$%4`>h+;uB1aPx>%ZKjhCc=9KN?$Q97RN#!%f(_3r04Yny!#IH
z*De+_0Ztc-1D$NQF8;A2nIyUW9gZK9t~f3JYvgHbezQO|NHAs}mRId()2&C`(_NM6
zmOq0_1!|K`Bd%$J8ZD*jBCRW|)`mzvNY}o?rzz+?Th(a%OK!XOY&n~bwu{h2%{hNs
zNq_BX61+IGtBZ^Pm5f2v)PSRGszzH5uR7`Wk}2k*=y)r}rYL8%(8pVIwOX)0-m)ZG
zj<@t21src}Hk*Ks4dQhZKDuJwS^iK{&2qlAw-9K%3PAH6aGfp$+DQ!!?IM53Jc$1g
z6WU4Mpk+hHTsl3@$6Phfxy$$$y9(|0pAQ4$ND264xC!rq!>*dQ;>+rU$yd#U5hx8U
z3O_Vm`>M9bpKJk6as;kX05IpS_(gX~8gvm3=Q?3%(<4=Ry0+IK(GelJYP!xCtSK*^
zMD1<^4{i;;<gO}>x=LTa1k=DVSQ=+&gvF5ZIzvM(h78t(V1}}Fh89|Y=Q#q;E&!M_
z)a)wU!rXvSP2}XMxz<9?;6jnZr9A$ny9Ax^HBqFWuF_lA;K76aSR`j?uf>pxIzziG
zhU_#mr2p*FRfyMqcImnW|FR?gg#z%kW_T0sg@;{3o^K*5Ph0t#`8;!H;fX4D+g-`O
zHb|k%-VdxmlCeC_QqnbZORKE2R6~=C4!x>DX<tj@R`3(eF4wdZ&8`;oPLAm93xj_5
zuKPVQ0;8HZ%F}hIg`;ZM3e(cyL@=EG@wYoh%DzVb{@Wc-7Gi0fp?MY?s_G2Qw%Cwm
z%TUmQW}aASBWJ1jg0Y@3vdJQ4gQJwSg^{wx<>^QEVpJ1Tc{=a1FqKs(rg&|)^7E9F
zu3n>0!(Vb8OXEykw%AZzXX=8*hO@RzRg{Wd*L<nOb<{FAdf0Wdr{<x{*Ue*sfWB~B
zfJ#dRcm|Rr3~C}M53Gg;hC1!Dg(qlJpr?$~<vRTp{*ta(8aJVn#e^C<LG3Ljw1v`k
zjct@p&=?E)2uJjxg+ZSd;#oy=_xKLc&~znF&Dj=m+FmbAJA-%Pgwy^6$k}+EzDPXf
z$tH{X8!YPA)X7<EQGb;KIX~&-?6;urbwuA)81y=_X9Ky6QBCfXr|Sg^L#qnK5N}^m
zswYt@c7wKqzof(sOAEMRZUMD)hU6RO7C@l1o%__jp|!7M3wn|xdW}M$=lB=%1h_~i
z3~Qn&Pucbw9BN_Y26G}brwryJT&V9!^SONHx$qPC{mnI}LOtk_iCKL5sXc8T=e#nx
z@0Cn_e{HvMSV_<P{B{wq>Q@=kN_pCn`Ph787qQG76m42tHt~mAvaUw+DbZ3}V$sDB
zo)b~;nUJl|S#Ll&3V6=?y&H5+Y3R5xsQEWaQgx3L6}(>?I{MQ~E>fNDj`F-te!&|0
zNZXI1O{6_$Pg*`DdO&TmA7dUC<EbY_T{J-ptbG;d=|OIy9NLeO4~_Q(YClF^hF&V`
ziJ`B?dkA_+{o)Neth}dqS^au;z9P=VvtJ>)iP|?j0RM=F-iW%&cpA~a%Xoq;=%s@h
z>_~X(Vh2qw3lGtkF<~?dP9NMSqkrB*^kt}A&I3nOJ3tcOJ=K)NFm20$Ds@dTO~Zow
z4jwqHSD*Be84L@yY?A5l8PJE1E9WUoyO%FOx9swsk)*8|v{)zy9W!v$;F`5{*eY~=
zc~2Fa-*mTX`h5k^G~EnJ=T-EC<^4#!Ggf*;=tGr+?V~=rBa2RB>&Rjj0cC*G*3k1e
zowkN%fC(JKyfrix5<tH1Y%ZjVr<Y4wsv}u<d=?u>e8(sArukrM>P@GEDQA=HJ4)yL
zX=C*Ms77@dBEP})!}@=88an<zVSK6+<HsEtKVtA?ItTm1#5gUL=$S6vb0qw>0mKPE
zX(9ZN2SNCYP7GAJ<>Ye}Z#no}IY<zEF1wcJAD7fzN3!}{69b7;Q0<o4=gQrB06w=^
z@6Nl`^^BB=7j*LNAF;jlacw-IH28W^Lf!Q}wa5q|13RAZ-lB`@!z9aE^m2XAJTk+s
z!0!)vYM2U$=NWI>I5_3!Pjef1#z^FKjB08eZ`+jRRb!nS<kJ@4b8?N39bID+C}rCn
zeE<o9Ycy)=dEPI4K~en&%-|g|d`#Kv=qtMnXznYUExz)>gYcCvbYGd@(lf+GZs9uM
zr)^bRdukKcZR|qKLvG!oIjubp+Y~7Oh-Ux^w<~bs5zio-0^p5pNO`*g{P`(SC2%R!
zXKw#b+~RwEE?d8?XKl1Na}!3h$Mk7gtu)W$q$5_?n3hGiL(!&b*=~(#y5*kipHr#5
zM{?zqZ10JK-_Am1%=dKn>K2N)w&SpvMbP}9ljBdg?bIhe3rg8K{uoFQ9DhhBPjpdf
zfsSPD6XzL7+|MW7Hus5RZaejf&L-K9!_N8BPV0W&v70B@pL~ib=YBq;ho=MCE<`gw
z|MWJk*3<KtO@Y-tJx`GRb_II%@=UiB(0_ycPrCxMdV7*B1!Cy=-ms5!+pd5&-4kt7
zU|%0kGaBjf_}(iG>ZkVc^mNEeV(ysRH57QducwYpft`Il?MR|sff4;Y-E0b6>*r}k
zn%NbYodF$zr3!M&_4mM!w|B8CvF0hyMpFr~CpiC~w3BO2?PUBNr*<+H)U|CVqai_P
zC$D%tzqq7q9m(2G<{C)6olLxAZYQJfJb-o*Sk&P(cdH`>pBsvsCXky=6wpCK;R58Z
zjtm?yfH(u&EDUUZ5DX|z3<TbFasvOm4o={L1ndO#u~h$tG<Sq2K#J4Rtd0<Epm7?4
z@0uOKb@u@{LPSx1R!vup@+>8-KqYYwIc7AB{_TZm=r8>sBMlz|yX|5Lv9ZP!)#gTG
zcYVKuS~;hB8sk_`BMoLvo;nN?gnHsvb!R(PQI-M3t7xpHiiSOiDyptm(FfyTZMg~8
zg=zYn^q&x(;zam9N5Xd-Jedgp!9;k@>k~aLmvq*V@zVwpXZ&Xi<3BtI#+y4)5OL3`
zZzyrkp>GI>1i|Nkf;x1^RL@Q+Nk_Bx4K)ljPDAN?=Dr~uo=3HR>`82Gcz%c`Q|OMk
zbN;k;bZd^M80|5`Gbk#b3G;5+;UiBC8vdN8Bk2c<8$F0`zMPJtb)Fy}zroa{sJ1D2
z<~h$%e=-7P)UJ$Pf6<dd#tG4E#x~-f?>#=&LbI|wL3H0so+OgxP%@Gs@E1Ek-uh&T
zIh!AV()gD>m26ZR`Ld@0S!Y`!XqM+qn-V|G@^mF%+Lo9;+w+V~iPztNdDu_3C3ej5
zl(i{QYObd{IcZzshq<0tO(n#xx~txEi1lRKRf}1$f2H+sYBungfWsRqLjHDWHi3{J
zG@B*ap0A_|I*_%+lr?~Oi;@2}x0t}comz~uMX1G~n_tfP(*`&((AklJ4u;~UzBA3l
zKu-5X9=M`E*pY&P1`?;>Q40lW4}yZRdVAjdnr9(AoC-P_{Q+DA?m%9{G3-Ft5Ax7}
zC7#JPnOECpuKxyf2?8=-+wmszg>8xEOJR*Al;FDTvCSN{%+p!SY<i!|#Q&tVOn35?
zn~uJ64fM5Lg<OUNp|!mGmgka7rE`aP?0%}r^G_ZQ_mtZfPr3Z>JOvFe`81YU`tb6u
zCnLZ87#JWre&k7@?&UDPGzZNMe=^3GGEGplX?)2pYTJ$FQ{q*9zO`|Mrv+WU!qba9
zf#A(sH*e_9AOha6%y%4|!S#$*ht@}XMj3Tz>Nkc%g5V1c-}ijwn&adPFB>@A7oPpc
z+;I;7$Eo8KO~ylkeaGpXKW(kf`M0Y*ElEy3bZ`7m=>Eis?w_3K-eb^YqWecP-MK$|
zn!3(8(S63i;dJk}(Ea0spnIE6ciRoHyekHK*+!c(Eh)bJPw4*9fo`d05ju6P5@qwN
zbP1r8ZC6(n5(M`S`pxr!)J6xgP7GQZK%DSeMX0*a6OMkCu4)mQK2a_mT*-TAFLW+{
z?4@cq5=$pM6B-id?6JthQE%s*Kkb0l+cnAYWaKxQ&Su$0M&<LwRueYeo<e5eS~GgW
z=&2~$)Ds@kDm|y`$DWohG7n`m_i2aqS{K1=`!q2N?gP?J=re((n>|ha$Vx1akJq7J
zz?s8(A)3wXR~Dg@zn5dg0$aa;izVC4dEE>Y)Z)*hX3!&_dNSzsBeF*<3&L8HpUq{N
zoY`AFUQ=FiUVP?1A>xvg`@=4ZgZtkCb#2}Mx@NI)K28(2d(KJ4T^f+p{lnlLdKwUS
zf0$~S-2Zw$?(bZ=$o<jG*g1dN9o_kkea)tY4L~cWE~iL<wrwPW-LLZn1UPJPcGIb{
zj;LJ?s!UycXGp+ZPR_dTJ@9k)BOFN|Y9MjapLCf??+m}h?$qaqcH<Ux-=r%6+Jh)l
zfA9=*kyr8|z4(7ZdTA%pH#w62fkBmt^mQiEX{9}$(b6tQ&UYF>ob!(?oUeN@oR`x$
zr+g-JJs-*||0k5!aH2e1a_U<YDX&W~QSOEW?B|qCWu$64khO2AYydIJUB#)g&{GUO
zYvra}U-j5MYxN(xc#2N<sRN!fq%$bw)U7o9Pv~y$ME5X9x}P>!GSTfd)6HfwbSm}4
z*!;TgOap~;J;Kbj_W^L-HbA=#I`t5&*z%d7z(j*zY)t$E_OLeNIx*%cQ6Hgb(>$e9
z&c#1Gf4k_=W!e#^X-e8fuSgNWH$GGww+p6m{8omT1$U)sPXzc%pb;#e5*fPn!;X5=
z^RvE_p3im6(=D2?DP>)M2-qh<gWA&k^d}N%&ubweQp{eu{+OrK<bB_>pCzi~{TcqI
z7V+-qe@5$%fyOYH0}$2Ddyt23z{BF+-{7PE)7F3R*eZ~%o%b;RoXf)_JUq(7V-R|e
zv)}{-sV?tH?awLr({8f&Pxi-qnuljtisW4nQc{b0|6<>Yde8Etb38l`;S1i?kUpTL
z_X2$JUSz=~7F=e*6(jB{`*e*3*I96b1s}446}&g$bGreh+Ieq%|2RZc^Dbj%y~%>x
zEXjL^hj)2+kB5Kr@E;x)fs2{#ye@XTlRxe&@$Y^R!VlAL0F)QJMR(Ax)s)z_0W4D>
z3symVJMVi;#``P?g2>dM0bMh_!7Mq11)F%;4_NX>7KB1%rgsf|%=D5SbW3Hq#$-3d
zwexx)1YrvNVU<@IemC2@n+5y_h1ib)X%7Iir*}tt!?bK!afyBF*6G_fu}|MVb^Fy$
zOsQEfC8<wxoj!eP*GcYQGrbSo4rNGLan8SS)JgkotZXhQE3SaYmeaGj8l%0%xCY)5
z+MiOo+VB1Z!lG%e92Oh5c^`ZZ8$B|kdV2Ly86!tk@0UIbuECDV_AX($BIpq%EW$tA
z`_#|$<VjB*Y2RTQeacf&I`j)|dCJp@r2fuwjU1IRta>dvJ3OqoH2x6%>6E9XwBs<1
z`qPtI<~p?htYV`EWK{2$F)E|)sG%dOKRvYH=)oByv%TBl?G9Nb>CWO|5s{y=&!i7r
z#7$xuG6qBX%W(fUt0tXNBCM7)sR+IFCv0-1-locFPm92wumPSG-JkZF;feP5HvFdu
zop>6aI~r4jE;;RqlRlK_7Wf-@o{2BjpB`DNMox}I3}kwl?U~%pOt6oA-glUVhkjup
zvn<m){tydy@OWlPCf7OB%e2kp`ek}2!Au?U!^MtFFViZMX#?RH9{(XP#ni~0JlgvZ
zv{~jl9zPhsDzQF8W}p6IpA`1#b5P2wvQI0a0=!}DlNXfphO<w#K{anN_9>TrD$YK&
z14X?h*r!RLthXfl#QW@0>=S=;NCf*d?fhg&j$|MCg9D}6Cw|%!#Xj+ScG2t;KPZY}
zpZK0$Ec?XQyK(FjAJXI5C)S0I_CBLI*R$H6@$d&)$VBbWWbMyX?a%aX+TZ82KhMJ-
z=$2k!e~NfB;g9zv2qwboJvwE3XTwJTnydYp4}aQuv$Zb^`4^+Fh3<V4jcpqm<5K9J
zIibzy+VP?FOUjH<J~kvVU3qT!G=Iv5@^ng2D52k<^;DDe>xMDDkwnPN`tfFdF1lwz
zDEuncIZqSP9)ZziPs%N5?r?X}__ipT&$*zKcI=fJ>>Ga2{y{zkWNj*c_`K()i}Xjp
zbZVOXFojC+FKeI|(`*#s?pI=@!wPD;pVQ283Mjz2p_djZH5WGZgoQ0J2%iXvpn|b-
z%^_Dj^#Y~Wbu{br@)ZG%?#>PkmY(x7FQq2JD}kJrQlkA@t!ezDrBvbQPj(>VJ4Z6U
z7SuP9vCT|I!+W0TF6pQv8HWWljf@=@GPeC&GNOGhZ$sXP1Lb%Z9nwn<SnwR2u)T7R
zxJj_TuN~RB;v@fsE4FuFzk<J$E0zVd99=OE5(QWM#b0jkFE!TDtghHVK-1W-<ZpJx
zIJj5#uUs*I_H*`x$j71WW5Tx*xf2<JW1u&H9m3~AL!|!xbdXyfWGN7{&?6_2DUO9+
z^vFXjh04>)vRs|ab1bz+mY)zyb=+v_mj?Y8&M@4;89sJ&hE1TgqceN}iGnjU43mQ;
zX|JO*>=Mv4XV`3Uh7bOio#8@p8TOUjTVRcp<VV2|V(6%nP_M3{Vtdq`;g&!ByQKV(
zSfFnyxd91xEO4WgoFx`m9U&)@^0o#1Zuz@t;sN-ft2~{I`sWh~cG)9!hPD3bkzsQ2
zoS!1)Z7$LfBXg6uz!o^#@NYlJ%>|0Z45_}+aHdr%uX25uFWdl-<=}OLi#l~d13_&^
zuj>zqg4ZpIm3K+fb2^%}3z{aNX<j#^C@o%Au7VCT`omW9zv_YtN5&EdGCpu5W1XPB
zX*67o$#A{R=4%Nydm!Hl7#am17B%<6tN$$p`S-#!p`tuA+-5#V*Hx68PUbVbA~0CL
z;QhZ?%uj|jG0dL%YX1LXG2b7p=KtMdo)hU?%zOQT)Bo-De3H$2USF@<E}FepiqiNh
zaw&ZU314A3H&S2Cc>@AKV>XK#c|WTmZ839yi=py-QRK85V!jGp%{aaqqIasupOR>%
z8ejaBgx#tq<u=q^O|C;CaWwSH#d7*olefC013PH>1i5{{QBW?c7Cl^Dj-{_8$R%1F
zg9vXDE2X`}Fw50A+gl&LkHoJo<6S>{gJD&cldrz2VM$Aq<j5!-!}?9%<H#VrN)5T2
zCcP_@9z&Pckn6YP(wqCFdmFINsSw<^c!I^#v_v_T8U1Ra+(r{yhlwpon}F=r*<LQV
zi&=2@|B2vuESQfM9T_gC%muXuTD)0P?kXMKL2uWTduulLGm9Slza;v%Bso<hpdKTj
zUY_lv%nD4nUj<;4s!Mmvp&^l?V_01<s<!NwqGm9Oy2py{0gr*VNR}IsER=&DStr+*
z;78PVB+IpH@JGKnqalJ5ikLt)KSz$IadqS}v_oClO>hnhGmAEnB7#}l;`C@;xdV9z
ztI{Y%{*|o5F?<S>`?pjymMcXBrB>mb!yg8g)_p98v=lR80laZD%?DHy-he9R0U6*}
zRE>AV(<Yte3Xvk9)sW}v%a_RySQ${eO}s}?78m1stlmLg@5_lacbXJN6C23g$q@^L
zEI|B$(h)=x+OMHpoQ^*yyJ<#4Ii6fY`Pe$MO{5~=T*m3ZTT@f|1)Scok^Ckhfj*bg
z5LE#&7^ibYG2M)qK+iUody}%b7*{k*fQ`fH99B%X!nSBCHzW0NF%BCpz}Cg-99B%X
z!cJ)>w<8^KF%DZyfNh7<Ijop&h5e?vT%QcU#W-wn0X74t18j>DzOg}ognk0N=?OWs
z-2w?VPT4<iEFAD;1q>UJ(SP9BY&bB8X9qrIAkYV$Rcut^O-pnU>}qV9+%!^j#otUW
z0-NE?jrX^Z`;eEh!pxxf5`sZ5qIAKHFSL}ek!2`VbG4E}=_NRwvn-~+hSR}$6LJo<
zmP1_RBOK3ZE+yc8h|@W)m~O$PxoyDLcHv?iHbQ{iiPIS@ozqqEM^z}`=2anixbPJx
znvcoVDo!Ndq2g||l_!y_SXZ#6U9`{BE}=A`(yFzSTach2bN^6UV4)~ZKLRBX0TNDQ
z6-K@7VSgkRM>Aq+Zk13>Tolg0D=bQoX~q5fg#0i`#>IGrMGM7h;q>7homKsx)Ro8z
z=2WYzNI?~cy4v3fdW|Qsn#_#&7@_RrC|$3w`8A&}N!PukL{NBnluEztERQBbQ8ul$
z#R@QkaXKeiOdp8TVJABYX3lcReR!`3hqcxi5v{T?vaqY%m1JWjI2Un(5pz+x9Ty69
zKPG396)2m=MZ5s>4o>G>i0N<Q^#2JLA{^FQ<3hB`%tZoyx|=+f{2*x2O>T#p+V?n(
zTTn)@P=NfO__sJn;3*GHd{WLJXR!jXn8M1P#%XM)i$->rJCoZuns0Q`?y!#|1&cjS
z6T0+WIV7@zV2@C?W)Hcch{k5ARmBom3GOOy!=a3RXP^vKd&&_ssHdDDMF!Jl<JBZM
z+I9!i{bS|ua&JM#JmGvmt*9;EFrv1B_eD?H>mrp+2DG758VLQHP_X6+;A2g1xq(!5
z7d_isE{kf_Omhv|B^^4@=2!q*xJFjX(~qw!o8WZ5f=%ip&v22BIGz)p+ZQ%VyWwbP
zWIEvq0;W)QT0c3(2JLu1xf&UCzi2sAGUOnWa(tB`Dj*mIE?0wAd`ezHW@2%ii$p>1
z={P-os#1?`IVLIeg#q$R@+wYay-Q?Gp)AGe+;8U(l-H3}INHZoEuriRA=7-AW{K%m
z?6QO8OtM`lX4FL;0eg#(iD8TB0ydxGiFRe<@-Qw()5Ja@;k3@va(P<uX}JkGf-`Vp
zk_83+!0DWrvro%Ek}EjcAciVKWjwlH5OOi?Q=GxM_M&jB_I!dW4}%G+5+e2;Z6fOl
z*lwH-ik~KBaEwpqxDkTRF+wh;^Fz+KTxU_PgU+!d<!z)f#^$Y(jDl9#3P&4?MK%!R
z3T4-flDmm$tQp0NB^n@Dy&KG#G+Hk0C-n*`u;Xi_b$l2@8^1&u4%X6V<)!2qBwrhf
z9~LYch10ofeL4<K;xcix!3Lc&UZ|$$gj}qeS{48vG6ALs%Y<S^qiZdcT`Xi`*kZb%
zIJf|w2s;q+*F;!md@kU!PN<C_cQa1sglw23Zz8*Kv_VK@TcPYuArsSCOc$`Z+lsOU
zy&*l3CQkM*O1DjsBhV-%bg_Im3!EyyE5UHKcB<SFWwdtTEvCWA?LDj|@50*&R@}zv
z@h{5Bbl7ewoOYNlKTFh5bA#_7l!Ytm#*UdbMz@<GKkXuAalDVdPD0^WArqrdOc%g8
zeWLJCT>i*RIl0C~FhyUVXOziXpNoYAYdM=wJ}-A+Y_5M^u8}XB<zJAOllE9B?@q42
z0JEycaJ0|hE`q^A**Tf8;UvUBchZCoyA6{uu~=J-4HfhYc^1bQ(rAa5gyuS0$i?{W
zDyTC8r}Igzm_8JzJM$|R5|rib>D4T`HhBeOfyQkj9~X2Hit%dc{Ia~BRZGAuxo5uB
zvT_!5=O18v?&MDh`0H>wSF87I`4h4gM>DnPusH&UmU207%#lY(WS^;^KB?;=2;C)Q
znlJQO0x&oD(tJ6E8C*46j?dTNx!Eueyn?a0!Mz087jZf>IH%bHS#}Zl?`yH#f5$I`
zDM>Jn1|oEO(gjSRY*h+tCLxB;D#a3l7BD@mOE32GQ|Xh7<hMvwdy#zvkrjnZ%!kGF
zayXs)u$Uf?)A=4rr&s08q%Ds2ncG*8-CD@RWQ*x7a5|SQrdwsFzb?N*p2o!t*|fuA
z!SM#-T;9cSEk=mpHMiw;IfU+54A&(l<J^VA9JEBPEMoHd>nBjqALDWp#dN{Myb&zG
zz8@AVM(_;YAb)v7o<`on0>O|rk^KdQti^Jd%9GhSTKY1%mv)TQg}Ro>UGk2Rau}li
z^Jo0*?hA;pp4|-)#H<(8U{x=s3u^GzyZ22wNn+jATXKw3>*X2Sza{r(8P~rh*FhPr
zYtgE2%azFQSP|aLy@H~@;B?;1556szagj4Po;%CCE5T1L<LEp;@gOyXa@*gPt4HA&
z%b}QiIcyC2yHS^tcPJLUUhYaSESKZU`%cCN3#tpi+9ewtr5%NdMJ(3ReJkXZBpNH=
zGqyaA&NDV7a)_XXP`2fJV2%*O+62vgPxePUx>yT+S1bn(q%OKhb1ac7QhGHU)urNS
zpCUsAMTD}yt%ki}A*R|In9B7s0o9{fA3zuI!y37G)gCO3?@!=zHmAKk-PFAnhRh*$
zV8Qg|wQ@x3LW9|y31ac|{92htO+}I{F0^bNOb;?q4&z)ET<Do{KJO9f!kBE4q#a>)
z7BgX0cuf_cu030AH^8>>GOQug;lHAOoh?|>L>4^{PFcP4A<!qX`Bnw}_5*pM=qTW^
zcyq7`7R7sTk)nn;ouB$N`cRH^k-a#cyYjS6aFOp<9PM-E5rQiVWfOAbvLaf155*Ld
zl>>8Op%nL<D@d5F-_TWq<PZt2m#|((dpCJHjbAT!qK!V5OCsM9^~1P^?|7Q|&TOzM
zPJSci0sF<HZ&BhdWC>0GM3@N*HNeMEIEuWVb1bn!aqmR=h|_U1?7PB<Gj+2Zg}Qp{
zh;tM&l3E_roAVK8v{1Q;IDN{eaQF9N9K%bD5lS@0=`cnW%NhEayulUK3B_Bgw?m53
zi9CUFpgNAFuBM@})Ll;rLUsI%AQXes3R~o*ZXDy9KX-WrdTWcEOom|@;L+u1?#r$~
z+JCEDCF*IEX6_qk`Zd4$^yF6gA$1%)uay-DN5!L_9R{!QAMc?_U&<9q`us@{tqpZJ
zit-j=jtQsxzm$6tA({<G@uH!aUGA%I@1^f=lUGWMJq2z!J*y2E7=o|j>7nhgm$V95
zuU-CK{*_#TY{b#NE?|N{zfiW}*U)naF?^~imM|+(Ea%?Wa;!^&t2Z&<!bZ++EY{cF
z6RGkIY@Gc5t&DwPlAz2^Tr}uA`5hv}K<^ey4}K@tCC6|^pK1A^@wZ5r(PHQ~-@`Ua
z^+{UiR45?MkpRRw5=C1%s=iaM?MK`)YO}1fp8wChfcd{1NhHN_ilGP{woh1W2<2<;
zmdjfa>6G12_Z9CSuEZYskti&{($vTAfo50_Bj-&bZ|#wzQ460U)GEfL_4mp%Y?PMw
z`UTMQdttrY7ULI=h!^+Ct!yyw?2}uPp7#&8{wKMI4P464(CH3yhC|&5wiw<~@S8h)
ze(t0|8_d%CfzfHsm}nHhm~`uYxmEskRqg;Z<!p?cS63?z$PEiuSHTD69{EeTvqi2G
zYA59HgYp2hpm25w{nox<9dA%#5p#noPAmT^AB)<8WLw;|(r>U~{w>O3Oj!T;O)iTl
zm?pR@#-!zcm!}dThEK6}{|@!`8-_MKH8LNxF^6D^C7^Lr#S((4d|nXqhukcnD!b<-
z(}WMz5_I(mIVe&byM@u79}E5frN}>6M?U1w5RAQx)A^7;|FAq<igGKyj><x8+)=Q;
zILcuVJL@W`fry<c$ikR8myXK2T?9vI>qxPPpdN71LxSnioD*_o)G(};^II_Wv3}h0
z7X)qU;&g8L*C%CJifWDGEtX&U6IxXVlmkt6%CX-ADn{F#l7nb03l^UihPoF8@mLIh
z#Zmr({m#JNUthCecBysfMYxKbc1jMfmaQ*Dd@C_$kvT`s$Sqt%(1QD-SVSO+`{Mg&
z<u<GmZk&~?<XZ{-&%qM?1*|cvgoWpY@$5OA&MP6|y!?tQY9WfZRKl?ffV>3dFx(Hg
zNJ8#6OJE#hYK-F;i<EyZ!rA_MJ1LVd$yEv`<%di1QG%stJ}&AdaKJgPeMRGV%9R2f
z{rna1iv3te?&xy_yZ7OA;J7&La!t;rt**&y$Z?$Jx-Kk8g>qc4ao6RRtnR<OE?07@
zd!DiQ4Y@YUn0iBwMHz*K49~dWhP;qvtbS8CAS;RQUh>Xt+fBI~QB+^2#2-|MTp(EL
z#_7D+%v<sj+HQq5z2n?ap+pQW!MRy^TRs|914UaLWBDDpDO(riFx;=<UHKv87_SJT
zFeZKdt~`baF}(4KC9rZi)9%RwB=RU0I~8_a7c>#BT6V(eu!&H&Y6lj>Z|l4!sDr`z
zYNVq|hrgwiTo@dxe0WURDAA>U$|Gbj2INCu9e<@bJsqI9DSRqJM&S&gk$xVrSP&+l
z@R_&}bID)nO=jLV(AJ_#cTqvUJQJWHCY%lmQ0j{r*9Rzr$<q6l$W#x<_{=$AKY@N8
zs0<(*?iVj-VUPkRGZ>JsFl|K~4_1B^vvQXai5`emVD(?lSN~#8T>skc!;(<tEp3+3
zm>$`p7NaCCtQu|qg&II#CJI6A*xJtiAj&*)91G`-ZJFQ&M{qiCY}ee%&Zx^M+S1q#
zd6c%~Hp*c%w&Ai;4>h*81W_21{wOPhh!De=ix*2^<;?9N=YXQjl1Pa#)cp((SMcs#
zxR53`ymtiEoCL8et4dDKVoH7Z8Ay!Ant9}M0iy~|H&wHk6HC*od29)VvMyIGsdUJ<
zPTwu5tRiVx60g&hf+lTnI;+#11ErL)F7hOf=N7#0T+TRe%n2;5_)BD{rSNK@@L-(I
zw@StIfjFI?CHluG$H`0_&HJ*jSfv`7g`<5v*cw5kP<Bl$^o&9bZ;E1x=@^zPDW+SM
zycnk(Bx`XouH@x-r4q@((T0+ASQ(-F7YcJNg&3~oTEVVW7?*1)rdze#Synkp4&q{5
z%e%viHX*q<+R!p`ogh*u%as&jxRPRtpD}FH3JShbWL5C{3d$tn3P){~D>$Me&=`!P
z4F&1NiUN&7VXmPN!!=wl*z`Bnkkcrp3tAR%{3`mg(7^bdX;EcmwFC{gRTbq)rv}V3
z{!m4!lEjyde*M#j>#KtSW3}0UICByvTwFi)CbG%=>BIkvCzrJcmnZ+9J-MtsxZIn+
zhwR@yxy&g<PcEmh$CLh--$W*xo?NE!W0g`;!(DVnb)}ZnHk`tHX3Nmusw<U(8-P0C
z$uNZ>2}%UZQ!zoQE_K)Qj7?Cgs74+(F0xmaaXkN2XiHQ{P>N4}5<WS-NGzC*-2p6U
z!0x-&W5LhtaC<KcuCps`S6I-RU4v=Cf>kV7$%3;iIL(5cEc16PsK$1FE3=>o1HA_e
zn91IoY!~Ai3u>_iO(F}XvS1PmcClb53vRIBDhnQB9YG2U4l$TtS<sR-;^r(!VhJ_4
zRe7%iV|HY68#1~6nOyfwruSq>U`l6lg)_ObnOxCKu4E?HFO%z*$@R+QI%RTwGPy4B
zMlmjc>5$3gXZl_Q#_8jWCr%%~HqYtf7YVOSX8iHXhnzotagOuH?`m=W)-e(}fBZrO
z=Z~L1G5)-K2Zhte_ntU?eCLJJ$M*m@eSD?L>EmldP9Mw#C+qz2DJAER&pH@?Ue<lx
z*ZaTz2T#1$(aJbI@y`3Uk>Ka-ooWPFhSwMZqjYdpxlxtpv%QVMB~#0B&&(o^3>i5p
zeemG)Q3Hn#$%e#(;B%?fn6uK!>2etYQMZ8Z)I{)FS|v$I3r+=UQ`>>-(kV$wnc%hT
zYZvfe+A%t;{b26}_WcR&#aSU~1N)8``gHo!ebO2BE{5HUS4&plV*`iu8~V&h7GDFr
zJJrjbJgexVBh#PCV6lEo^U>Vlvw~V?q>mas0$z^?33tHnQ^$b&(^)ZLB|^N(P^Iv0
zl|*>cSxi_&sCNeY{sL<XH0GpSl9{lVMP)&opuJ<mB162l+4ninGU%mRN<?%csJYYy
zym@5#wQSmvNy%m6DKr$?BrdF#?0p0(Hgy?qE?M;-qnAQqoi(SnQYE+!E4&g~4;>dD
zmPVC2ioa_-d)q)1Z818uD(w*%x`M1>zQG^hUJ<Una^Q(%B`y4Y6wN2$+7rZ0bClrF
zdakH#LNb0U0GvJXbI2Vi2ilrL=a6Vq+7CLuPgwze8AAZ4>7k*=2#(?lvltvBu2l|z
z6Vlg6=))bo?8OM)f7n|h`KtkrGZFf|rm!k{lJ#Dbvo_kvH+wvuHhBmpDn6aJU~~Dj
zLqz!ur}K$$j3@LJau-LlHFFe>G22Bit_Y5zF>+|t4%{+{-Fx7cg%mSc#*(a-6%}~K
zqI{M`ikWU<4Y^@ry4A3WO6WVJ3{xo2t+-)0#$s596fmq^V?{UYo>66qX2V#L)v!Rp
zFf582wy=rfL6sGYmE$&v<*hcYZlb(ITH|8eCLCk2>GSZ=R$4s;8THiFYz|AZniDLT
zgQcK)5;L{H%5j^-bgNB&H&afNA-EW~3CCD$db&iOO|oIr1hY*n$!b%mU=x<2RZ$DY
z6U*9@@f*%sXD|pW$n6q=tahz#p-_^Ii*dVfjK!|mEtOU!c$*3_?0QqPi+<iiDN$}e
z>q+?Lom;R2qoTSIGtI@yOl<|LCT6H+pH=^m*2){?6I_Jrk7F$Q*C?G=FL#Zm^R1>o
z8*RP3w_{1xdXWWtuoPsEm?;M<$LmB)7i?<UMtPs);u72(9Ah!3ZmOa;9b#0+d9yhz
z$!d-&n1iJtbHq%CuyWiSF<mf+_uc1WLXVJu;^r<6$5?FoBQ4J+mtj*e27w18mSnYw
zy)nY)F<1(+NzCMjmE$&v=~kP%wO6*1YPcA$Cmdt3X=#}}xAPb_)i>M3lB_lr7i_{(
zkWFHy%2+wDDgS1a+fn(4bizfrJvhc<PnFI}YpojyH0<fE*+XYPEOZ0xO$fd^!Kj-4
ziLGTk<g~|%@cIw|to8A37uYKui;Hpnag0U(?vE<1wIL_e(0`_;zpoo$N!I#^5bVKH
zP<@D*Mq}leP1@@we5_cFI@ncNNtWPp+$bDlF>2>yc}BSnqgI)XVo6q`*eeix>R>6z
zC^6G(SULXo2p@pep4Q!zOJqAP!tKE^7JI&^7OFd05yPInnmx4RBZ8Af3;JVJq`#PH
zD^`ZTQX(JyH+5Hv!^L-8gzJxEEc*BEk=IE44gGKG`sX$k^k*+z@QKH$NPjWYDXa`{
zC}O&`4u0>c93n~yb7zcWEH*Sw3e_7*uwg?CgTS3JOS1Y@ykHZSf@~5qxv_HGCNbS=
z)0A{&I7!CEc)j2li%kvs<kidH#vI^b%_cg#u~08%1sgCbvO&yL3oFAL`>?*k3dm~2
zM}3tOq&qIhjleM$BmV4{*VqG$it%bj_<AswWUZL;f>BrsGD^(U4J*ehMohQb^hQeP
zlVln$#%;ne7Mntz%Co7cVbdJ5O)SZ3Q$@ihECtylW}1wZ<2H%uR-0xHP+lV|a4~KZ
zj<MJ@cwnAQeuhn(%r>zkt4);!o3IpQlbGoptQ>c~rQZCVFXvCMvfV{~#0BA$p-p5}
zLHZ7y&dCzf&16;2IovpOoGa=CDkpLS`ycg(Djmo<l*2eFbvFxbflf-R3A$iR`p__C
zPySNi!e4Dtq$KM0@~#ygZXQ~@a8m9LS4tB>E<aHb^*V|z;T(zS0!ROo%lP6>3Ep|q
z&PhLR5xP3i%a2c5(5ddQmX);YRe1*}E`i1sc*BCd@1FL$77{#}4@3X|0m{Gm9T!gF
z|5pxBu8vV^N)1a=%K^%#;l=^Vf@k0WB~8zR4^WsT_yDB=G$ZW*r7e82KS1$TV{NT6
z1S7rLQ3Q|iy;qhcd71bAi}%X1-`x1Ozp}v_fVRu-tpPd#9;ilL<CRC~$Y+%*^0P2K
zU_0<Ek9X8Ay6Rb_>g35d^20rlG9JpZY!eyAa_=M#1wVSk9^EjCPi3tQ=S-7|YFPsy
z>v)`X1OSLxK{JjjjUG+Aj#E6YDfGxVI1hV%92|hb`@^7a>(VU}@u!t0C>7`vBh}7Q
zHjb`15u)3VR+FS<IC}ngh;BDQDK4$S(Mu;NZKTaO=IA8Im^M+VDt(Ki>$2$2&Uqr}
zh1P0-^fOBH=Wp!gS`MiyH=}P%QUau-C<8q-PI*?kfMXU-R*LnX0#taPXB05{z1i&3
zRQ72Z`^4Dyu3?`hvQL}YrwQ!Sx9rm-_UUK#iE-~e%04k_y%*rq=q&$HL;H@*W>qqU
z=8jTRXqzcY4fYVok#l}g8kwP`*n=%CY1OyXNWyQW@}2geQWQG$x+I_!Ao3W$Qk1=t
zND71$xP!(}=02~~p=YKl(NgtNtV)_nRZ6iR65(hneQTN$iy$kOqUzU5I|NydL)P{4
zikL0uM?b50v{$2QvLDmoyI}a)FDRuTr<*RBp#&j09W8R&m7=aULA%sa6gFvMEGB&R
z9Mtm+UB*-_W7sk!h-S@%N9=smOtRpQ&lkUsv|fi^gP}qF>In6H3+f6VDvX_VX=1p4
zh{PzHC^w)>w@F2%cy3R$e<c%vb>{E*pcozUA~@g~UGym|T6sx{LZXjbL?0<d;nf&*
zEks3RDdnYN5n5fV5vZ<zg%kt{4a8K}p%Gdg1Vzwg#nq+~h$w_1bnz@DQcBY$w!sp?
z2ts?!Rum+*l|}5s5zK2v7fY|8CexmCl*-aGI`AkATz0MkFX(5xy4>%FTQG;{rVNU(
zcc*^yl#0^ZI`lFOU2(or5kW7pK)>b;J^YrEO#5d;``x2M|A?V$E>IE?^bQO3x6aVK
z9gkh8BuIbj(04F&GZ+97^i2!&wF01@Uj%MbHBxh%N|B=55E@*`6&8-~#dF@vN19!z
zOr+*QPP~H{50w*Kp>*-93XvYy1wLvK_}(tnMqnq4!1e_Qocg+wB0Z;znTEwYx>!j;
zlufokPbdKT?Iqxz8+7Qk7<%9vN@WDS$^yNz0O*xVp|?A%L;sGUp|`7wpntJI@ApCb
zx+K=baF^suVMB(IQpB#a;^WY}Zz)mmlIvyT;1{UoD<#-aq|(xFD-lSSn9}C)sB~%8
zM<rW3KN|Xu6771J;iYK5tJAbJa=GpAz>R2M^KMky>}C&@wssl3g(R+4icvR(pH02@
zF5C$of+P&W65d%3SDAeh23RCyl-3-%PigxO<oXJww(B(nzX-#By;7-%;1^in=Q+b4
zc~9x@`W7L7g^`cFuOuVnFD=MlI3wpVRL6BqgOBS8ubjf@KuZjbT_X%V7c3&q<|`tZ
zc3!JgbCsd%r@-<p@j$5Rily;0lvcXatWy$0eauJE^)r<Ap}sjx1dY#Bnn^ai12L^=
zhbt~st_;6hHx=egTJPT;NotEE)!3laMv@*eOKRyTi4!&M1Eq#*0>XY4VGsR8DNTEC
zR7xTNW6T0Z<}YB@he}n~N+jT2B;e6aN&>=u%Z$C$5t|R4ujMF}UHcLCK7`%-Bc(dR
z-fhPI!4W%;7<FM!DNLCD`9*6(N0DgMj)A2lB<P-5(Cz#MeY9CglM;2{>KJ(0r?5%m
zbD}EI<_@A_bpFjZ=yT-}sfP~z1cpBMIoy=@K|f}J?ot4Bhb>BL=|vs-c??~9tCEVK
zXIP-8Izy*_2@8`P9d#o{9kWeog;3X9P}ex4^7;fW;HB&zNzv5vl_E>Wbs<Nv5MZSu
z&HYN4K>lHo^jiUvqP|gDNNNoC6qkppZ{&3f_r6hDBS#5kNlA3+1|=Hx3_&cmCe0l!
zsdn81x25}cN=vDcF5w|0q0#rsBS=Dut%N%HOW@PHH+I1EZjdfv0FnULz-l208MYGo
z<S&8S@bxYjU=K@v!Sur%sE<XutOZEcoZU(s%Muc1nUl@4l{>p|aucMlbZK9T(rO~h
zzOa?>sVKoW!(d~zF~dkHtt~BJX5fo-o_6fqt5lEzV~ypnN>leKWsxra^wK*@&3PRH
z(UO%7H}<oR7C$L5Qk7WE|0=Sg;AAV|IV?V%`R6C0TP(-Y+auigSnH(2bqrj1$`gL2
zgwC*wE~2AZ#M%8ybEJJcE&{oDDvQuu+|`<HU8TfY)^}5WRjSZo2bFMXsxD=cSxW3L
zN*g3)yjjZFLP=>Tt<eR%ZzG@)owLxdsMY;en1#Jlu&_^lR~ksa>B0`0g*7g!R-n5N
z_yy4|hm_LDuAj}K_U0>!R~6tCrxAx0*%d^mtc7_-(Ks|-LG^G^B^Kr?fv8WF;`sQ2
zD(atnMe$}Fa|C8Vbu=kSSjx#G!sM`q296x9S{xs|Y&-yL806}sVfMn9Tyv$8e+la%
zt-A%kn<G9~9I7LX_C5&{oY^OUsM(shEG&-K31q>0E}0fNGxL}8>M5nR^l2R3nxZyy
zVRY}GN>jxCCJXQf`2)8-uhgKIPAkP+r#0PAV)UvPl;#oXgZpIk7asKH3)*8AQMvhx
z3OWluR3cuR`-I0MUpjdfIuGAGLWws|QQYxPwajY)jA$-3*O8lGWH10vei~Yk>*tR=
z@1oL58m1#Zjgd!RQo10Wy%yxB@<-0S46~}mI`XR+`Kv2RSA<M0$l3WLCtZW7;P*Q6
zHyF9}b>#_!yxoGlH9zEJ`tl8>nsh@)zKW6OghIzN=Tmq=@syj2jAUH0$T;sP1Lh1F
zQn@nPkP}bSztX2X3l0MKq=7}ltX*gf%VnAUz<~Kx{zJop5H*ap8&*`Mf8Bw3Lq}a`
zJCjhz5k`N!s|2F1G}TsQ>jFj6v-e;&G)b2<-Y1FX{H-)V0>;`37+s(MuqjD;U&mkJ
z!w32rBlvf0;omF}o+e0YigZxN|JjF6cgavcO(eA>ZS1E8AyIp6MeQnB6z^6!;v9c9
z+*Ooz+^;lqN!0aQ-Ygh;RXj)i$5ztaf+f8XpjLJzY4|k|e!oC98Cg<|C0YEeGK<ZB
z3bNsg02m-%4RF)lK`L?e(j;|9lEwzBDM(T`TS;9DlEfRQN@G_B5PBj+m0ekyq)a3U
z8fkqbX{N2D>4lUu>|B8C##;*?YXUck0xQyW2SKGnZWXto4{SxRD@b%5=7VAM!o7f!
zN+oe)<D@427?KWd*#eoHYb*0m!7{6=YF#P3oHlMLFx53qg#K35hf!bWE@vLMLdxYk
zZgFecmk*2-X2eZ&Q4O&uFs3dYRxvQpI%%nI5nERiE47AMxN+3NrsQmGG3;so06rsw
zm4J2#1B-ydEHEaPP$Q*j<<J7-VhOb*vVStXjz&CWn^4aFknM0uHClQ{xARSG=b}<-
z9D;nqV%zH+Qak|}9-;P;cIj|CG2GBd74P+bXMy`#r)pa{`@PGJrPW%}T^;%shMpd!
z)<&9Mw?JQUh6aUO(sePao1TqUWvOy`&ABR+N6rPRN3cA_k&v?G%^nt4UfaBJ(*O5Z
zwZ7C<$M1~sH^iwAA?OYk=(GZ${mZD8r0F{J6b$`s85Qs8PqaXfbB5+ya>3=)%F;R=
zdNqdrv7Czc^xv~UFZV(Fe4jauv95l_TGb%5mvmZ}chV#;m}XQ|@gDmzi_qNiblDmh
zp|}|RXp{NAA=7!;?q5|cE5%kot!heDwG^tDs0!v*6;Z)y(LS`AT3TvWLGz}@6_7Vo
zsIKC}>jo9fj#RILb;Zsn*Tv7nro!4C9wH6afd^vX+X*T@_w8>1?ps0g(B2j7TUg^H
zRi?Ampdk8aBD959bRi3okcBnXN{Es978!F2mQg|aT1Va{BA23am7rj2x4Ok5<ujiY
zpKCGRjA~AXdSs`;P(!{*=emEXI^0X(H!p%JA_sWCj#?U-TePCt0i=o!b+tGdoT+L>
zt^O;)u1(%h1q}Mr-gVV-2)BGivk#Q1s8v;LMf<9HEk!LSJ+8w)is0#!^@JAR$pYQJ
zAn5vPob;RyJq<&*Zwy2JOCJOgYZXnlh?!7;nE4IBf(^QuwO9;T5JqbRg#|?Shv#K`
z!3$eQTGza*ECN>+B(M?KbyyepI~E9b;VTBeSfKY80R2)EHA*6tw8{>y<g0Ajyr~+G
zDmtK&xuX3l<zLa`o2ju<Jsmn3Lsx47gVvoBs$#8;S{5;h1&A5`Fo@}|i|K0;gI%?^
z1-eH8&`-5gD@yZq=s6s^Md*S?XZa7f7J>Uik*(AQh@+P+5?=I4@U?c<@{HE*+^~OZ
z4O6A>Dxo$FQ>764_#>(t$^5#KxnXasWItbO*aoWltZvO|Ow_eDLce~}V#YBJDbAO8
zzb>^^t4Sp)Ywi<X8M)8*ZG|pfscd#1H!OVE1*DM5_WgvX9gyE#hi-zQ_p}pw@`e`Z
z`aWobb=NVvtUTQIy4X(&k#Z|BnKqY%=tI|oOVPC*;2zrqUG%e9bjOZDqZnfmJ+iVx
zuiCp4bQ<sKm~UasxXwZwUTVQytef+y15@3*z#M9y4!v7|epHy~{9u9p-Un?kB{3Te
z|J10m-Vgh;t6ITD=++8qGby+Vs`&RFQ}KPCfGXyS_p72+yd(1CYFSr34LKPjFYhJ{
zJ+&;zi3K1ZeFAjuuOauv$ZtO>=-k_a+@m1m?rKTbd<}UHMqbcEn1{V=L4L6S<n2Ax
zNY@q(`7?|>u9q;te_}z-DFAs@Z#C9+PD4I}k)KKzmQSZF$j1vnUeZU6c16;y$*|8{
zlJ2RaqB|^)^;Kigg1Q(_rg0vK_1#HO>5+%Pubez2s~>3IO2dEHgx@MdjYIfNZSfoB
zk3Xru8si$J;SV?Ar#z*`BK#q?_=EDtA2L8K<yxlUFEQbl8K_1e{MT&p7jb-7F6+{o
zxwfI6&3QQ4;#H$u2bfS)8*rm2gf<?e%1Go-Ok@f=9@$gXX{j*iUTCR6?NZ2X&72!1
za}Ezy@$unRpE*dtrK%2{=EbMgs<0lK`!HAud%3OPXI*{AhdD!3d}9N4aa*bQVoPay
zq#-y_scQD)%iW=B4Od4E8@6mk>~Dst_#y>t*NWJ!4Q!*^bX}rNTZ5kGIemOn#I=V<
zNl+;~TZd=WM)-V@-}GYlv|X<=J+yi$Gfs^}webp*l!DsELM|FQ8x~IiGLW8`s0w$G
zIWD{C?fQn}(sgsyiu8|3YA^!c&H+#@Y^}zsIYxSO7acYMrV7j8?-;e#WPa~@6}$bu
zngyS*U^5Fog#g}3^BMd6ISamkAk({rhg*60C4{L(yxaJf?GSpuV!_ueU`0l2ZwX*8
zUwDzl@k60Q)!6d}>E3$qK-9!+dcL7rRoi0%4SfUC=hk}VcHiw38mar_9mD!cbkJBe
z3R!>COzSmHs|2WdRTW4Nk5Z%QQn+*{+{Oke(X{;prI=K)x;8ocZnSVuyj*qjlq|lw
zHsr-Xfl+EBO2)%3IJ)4?6(2tyW(b`)WN$RVYi~hoTiv#zGWcb9UQxfWClYu?{mwq|
zit^_b)vi#LbO=i6RpSp;vy*}Fsu=+4!P?Z-mM&|bH<@}wH>&$~U@P|vzew@=A-9b`
zH87jo){<s?CD4^+F)*{bwLjo6f6WSwq+d*i+1VN&mP%u$sL_bA_bq@cbpGF|Zs`j+
z?#3mdWr8#d_h8_+rV3NDA1%N;G+@^|jE`onOhn5}2U&HdLnlxqLGv7-LZv&W3!7;7
zEK+Xk>T8guX)8D2!VEQ0DvLqKJ}1n-;}Xn18J*xj^3PX8+t4*Lf#l{G(EYrchDdH=
z0c@C{IeGmAdy*4gglTGj47v72f!@9r$le7&Ht0+q(d#V}1NY5R@tv}n7U1ax055zQ
z9-di+A)C!o@geX^3*@^#NMlTp7|F&|+Ohf;&QZ%qzhP<P=LjpZgBEE&^V+la`VXBU
zu{tAnFyMi?!tUcu3*fZ`)~N`OH*n9|G!IsxrE4H}tvp}YurF1^>{-R(42-Sp!k`q}
z$O33i!j$g=0$dKxu{v9AEVaR6S}YLO)~zgJ9@fQN=8$%+V&Foxy!12%J+)Av!D|71
zs)j?Wh>7;JqMk+2DqhBbPcKs2pjPps1@L)Y%NaH7Tg8%B)T+`t3|Zz?VR^gS0{LD6
zkPkiQ$?MJbVc-p~3C(S{1^9;ofIoj7TJUuY*?6%4dBp;G(Ff^k6^vxoD)MuP<sTVF
zlutz7*Xa#GVwps<_r)e^-lw^RuyExL-E*m0L28X54=q*ky_yyl$YwrBpAoDD<~42C
zOxE!?pkZ&TakdkNDD;5bltj8`jrtg$k0IBYXc0S36YF}0E*+&drs@>&NwcPtlz!6t
zx*>536xEEl!h-ltqJwvzdk0$i_dcvJn*Od@0%`Y+1#7!b%GN~Y*mljY*K*h#I)_0|
zEEin+j0N<RlY%=|z%1EKmyTCkQLr_Pj$NtZTeu-L&3+JAQ}YA=n)VHE$TYc(K2J>4
zaGP|5mxot*UyVU_SGV9+am1akzFmq|U8SZ;oomu@tJFmKiJI_yE6ileu&4gJh0>2#
zsm+M*SGyn^{77?Ts5bNH%reuO*FqB5A_sPRSF89!QwNJCX^xs`&obt$fo10Nh_lLT
z)ndrD85YE;`65Qs^6S)MuJ;h){B^2|5SLpJ-}WIIO~-YLE*qXVd(_-VXr}Q`1w_-Z
z4QiO{7bI%Z1{L24+HVoHPZ#CvkheC=ieBY+5%P%-)G%bkEe#nhxvtZiW8fAw%xz0s
zX6-+GDwos;+^8h2pW^;m?L!qms}qrA_RkVYntz7F#Szm3n7p4l|A!o@12@LN?`~4@
zgNh9-!1W3MUYVoDOMNh8xsQbTb1w^I_W~d*eGHJ#VaT^W79gitASV|9>A5OL&@G?9
zc)J4Q#%&gMz233lzUjj?98S7k6ZO?wnfEngQ+C4%-?Z(+9t(=5iJz&8bPQ|o>Sx0K
zd#*);LrD&uY{utmJC`5bGcT_XbAKV+KPp1^%ojFZ?&-GNwz>#({?WA27PXbD0s=g|
zMa9>h%W^>E$Z<SE+XJ@&<$iYu-mkAWl1C8q$6u;xX#L#M4BcFW_HobXVB_S)`APtz
zya7Eu0<II7SHFB4WU40c+DKswWRh9dc%LlSSoXOAZTqzvQI9<}o;s30G7b;RvwaKL
zo?s7)!#B1#hCl2v@zi4c8FBc=9uQ9r_l~DazE+zjvI0Hex$re?Ct@87Hn3nL3pTOf
zBM34$Qjcu!uY0Kajas@Z%RL)PvC?yRG2b^<-uI0G`Mxnk-!}&B`v%z4zEN99Ve@mo
z`$i3PMLq|Q-ooQo&+<Q`v;6uF8^#}D|Ev~0^Q{_J`iokwBJ;B=vuCs_@zJE6cN;{t
z^KP$2%YUcVivOB_`-X??#f<H|-@@li?{^S_F*|C}XTMXUg4yl?e>6U4$#?2d*W{8f
zfZ0E>pyi8<fR`W`odrSC%Mfgs1wp;p5VT@J&KwB(&4qwwLr`%61a(-@`E>|-EP<fG
zn-GM&3qhTg5d5<mg5TFc&~+mOuWy3jJr*p<f#7t`WC)vm1VPD<A?U+`KUt9W2?S*}
zL-59@5RCc^f}YzT*vNu$+ab8|6$IVChTs?rF0o+$HxLZ@j#VOitpM1qRXO(&_{Mw$
z{xBbbKky!b81|Pr3H)KN5a^LTdUTfL)m|U)LoJ%H6AotKZ-<>~spic4GC453ESrC3
zu9wMCGdU={%ot)`;E0(VFmv>P8mUD_4;aKq2cY+Ns<q+04!JwkDuH*QYS>E()F0Fo
z<4cDh)MVq!%Q$7{4{Ajt<@OJ1qVc8Xk0_<rk7^ww<+UHxB;(6ZKdKKIUrOv!>lt6V
z?m}oU<1gEHsm+aSp51C~<I5wv)#M7g31GDMuM!Z{DG7v(f=3CxMN7fgJPY61tyVV*
z{<2$bVSFjSM}64%GHj39)cEqz9+b_0FH*hbUbV52Eo-mZ(D<@@FEUEmhiGlT4`rLb
zPkquTb8VmcnDM3aPij}=%etS`PR5tupHa4_epWjhDO-P5yBJ@h_N$GIFX{W$2F91S
z;S1(#MG6pfuwEWtE9xV@0uCV6TO3f^87QwFP#-nET!$}Vs0v<g3K-8cr%V1&tI@m%
zJc<Pw)v)>?LXv(#%>Tc#&ONTGDvRSH>g96b!rlm?fCxSiMTFvliDhO!GMO}oaSDl0
zFuj51t5gcG%*;r1MAuBdKI&A{r<$^d?@B+6n)$+ynUN2|R5TUA_ak)HTARB(#y{t{
zzQ48iIcMK<&-$Ii_3X4t^%rYTnNMO*1!<-y{BH^2_d02)R6}JChW%n0$uE9U&x#Us
z#G*_)qOwFeaztfI(Eq5)mEg0ZmXG}QQ8h%Ap~o!2@?&a{DCew7pW|wnD2t9;K9}0#
zmQyRa%5qW{S6Mc?#~OtGYUyp_uj(o3db?E#uU4U=q*kl$)`1M0g9Ev0KHRBRk+5~F
zEx;;<&~>+bE^Me)NmhQ4xN9CYinsCsbcz1(9eCt~O11L!bk)u&fp<=**mjolVJcn7
zqwqq`U&#`f^@*)xs6|htYy2X-#*+>&eP`>`!*j0CH+n5y{R8mAZ@$q7s03JA_bP?b
z-&ChC3mQl%4Okn@2BV?hMO!E9p01+`GGZY-auV$}{+!F#DvqJbGN+8huDvb2E}>#`
z(bKDY4OJYA+=b$|Y@Urqz`{hINNc}Il<?RxIB-(MTKUsdwT7;M!c!`gemmrE6-QAu
z>%N*Ah5q>$Kh~|MQo+0VK6TRBIu!N~kaxlwXoeyLCiJw2S_eOg>SHa|M;`p*arTHH
zYrl7>a_;^d-;A$1S(_c9VmbheDL3n|+1~lS&nz7k_hhWFyjgb=m08PJEnNqnV29Qn
z{fNqOBGzEDqtWnuAMe(1_p}PM4##rp=;!qiRinCE`5EFJH$X;>in8*4RMZb|g!wh9
zv-Ok=q3S*y7iMd)s=?j{^8czF;nv;ErmS6(6%JAUzU{5u*HA*AO^|v<-FJQsCEuVn
z!=y7RX1wLNqsU6kM=N1A>pyMk_`E6cIn(lA%E}pAX5I7(@*88&Z<x$LlQ|YALC6|A
zJ`X20uqIC-Uy@c1UT0N@!IsTsmLp$-3)4xE>EwmnsaZMMQ?tiT&d$e4zAgD*QvP^!
zHIxs_m-)86Z#ZU<-#Lwb$8^^khWqJ|k(Tz?$O}D*4#*@p&GyDm&7GV*I`95XWspzW
z=t*@KkYlp+bYcfMepg+sA6Xr>*oqV1n9iX(4}WqzVUMpP;=W@zL_KAq_cCcQP`%r?
zEtFRKI^*uk%f}S=7oP5>x$DsdkvVd<M1Jc*sQz8GF5=firK61<7dI}BJ2Zx3n2RkF
zU7hmKYTQ$~d|K21ET{L>59VM4i|UW@J(VwP7PVLDvsRg}Hx`+$H}@LzH_W0g#jn#n
zm50}&;_&V}r^34I<%4Ex=sx=+Tk;aeOOq$QF!3dt;Dh`pxy69<_-9(T3woSaxdHij
z?05s<evgiRq6=1?R~<rTAjFs0{aHJF9{<!>=z@mxDh2JP>w=20)0krF>n_N>prVn^
zy`cKzYR?7ydtWg)YteY}xZ{OAvC`HKa%)wzAzc<jqDuwCnp)M~5WJ9lU#k*LaAL=j
zi|QflqxVJb>eY*?FGgETbmyW<z^G>(r;M-T=)F4i2*S!bm5Qt2di6N2o~_5*_F`CG
z&zXnKN?lSz5k7ZGJ&dbmm$>VrmsB!FL6`A{yBJ1aR%y8U{IVK?tJ?++xx#&xUQvS)
z{(MCZ#8u=~-oogsyr2KR%JAG(m4n)_YwCGit-YqQaHX!R3|!@3XSnaW8ii5!8!8i5
zZ{NV%@?tn}Lk+-Ho147Kyvcp8ys1Vayna(XhpWHc;?>u;xLwd~)?U2LySvdu>JQc?
z{-M&b!S+9RU%EA@F&NEn;OKIL8i&!SJIal#op;m(TqWP-V}J85J~zdI<kjLHdYD)7
z;zB*bk3Y${NqDNnO@cyi?Secn-Nw5N?>FMSG#$k}FHOUB$V(43*)S8cVJ7sut6Z?Y
zO3@4GCN<YI!dsi`XK>ZdTmKzbQ*hNBJNn66)6I;dg?`NRz=kGdE<DphKdgBV*vio2
zt+JAykkvv*!w)TVfDzfx&;rFiM)Yr~!;Q$Mh88GxGh${-?Q2AKHnc!7&WKA}YCp3V
zY-<wVg)dv`BtzKAtep?tTj{Qbuu~aW3R$gmvLS3u)-8Zlt#qOx>_^5dBoY%c1uxz&
z=FY(DKOYx+k|kxN1wp(`w>M4LY9uX&3Y(6ChB-cg{wAHR#?#Bd>4TiChDm3WF=_>+
zKVS&kiPY7U7;g@hjRY<5P@^HrrbA$QPrI{mdt@S#K7v9Y-NO*}4R<~z5)KayP@X+t
z-*Dt}sPoY-lgU;g{VPbc>#k-~Yz1h6n~H}|?YOTcb{$~S*#RtH4<FifqDkl4PYd3&
z4!%0t**H2}{rhczcD|mY;JQx>{=hJ|BfRFT9j0q8_t_hv%vUEE!u7poBUJc$j*Bb%
z&`n@>cyhR=M{R}y4jpA$aqV8Q1tvRmCquYEPx%H`J9MleT$(e>;jlx;7{bN(%X0Ab
z^W<>7o$)^!nNS$%rvptQSJ`XZVTzxQHiV05#tvBJr{fIaVp+EXD*bedAzT*^?SycD
zoodF7D<Ca!EHWX&soOxYzaDJkHz9W3zoZ~=2()$T2s;71Voy$nzD}KFqh}88iv2Lt
zsZ;C}p!P~KY;x+(Mw?p!wXfiRuxxPZ_BMWpV%`CW4$#qd3NX7U8PWoDLi5uHpeR5m
z`OHrCqMdjQvIBKz_%%RB+W0k#Ykq{DuQ{TjYoP9CCxUI?PKJy?-Pa^+I0&l(^(Yf8
z{Snr#a702!r85l4Ike<6hYL0-on}Bq6*#pnGr=#FFzbqA5DagtV_|NP4mWu4QP>;i
z7YRQE={!TGAA^Tm>vbmhz6$o`_zi)_gLPjY-pk9)z2HtM+VeHR`Z1HVtsc$?>k%f{
zSPuh3biN7ZU58B}db(*@(98=ag*w9^y^VGoeef;V8}57@d_(b*;O;XTAR)~e4F#ck
zfFZr_Lcp8ONH~qebTkD!+OiDqW$;)U(HFQ^`&S^^(pL93S?3VNA9sdB$9B56jbC3`
z*AjBt=|}7o;Nb2|hL79nVLtpqOV1o&&@W5}+X-RDo@B@h)17Rb@sJ(nh2aJ{@Js;)
zH^cDA8JQ`-hQi8l-OUi31*{@m&oqIV11#SJXC1ITLdTh4mml1S&@m>6bwZc+x~mBq
z0wKM<e!v7~O0Pa9F!OmmYIepmnHMBP>R6+j$-MfSz|7<o3g1TRHiq;Hf}@c-(*$M~
zuQESA3YxLaI)zs(gh%O-Ceh5|^{EfP_cPY>KG*5dI=qMw4wx;4&h2R>zS$EdPRPq1
zottN#>bcP|xoI&jZcdqd3Pn>r5xFV1u~euPQbY^RoJA2|`^lH0Jlg|Up5uv%*qNgK
zwuiXMj3OuzK>ia!seoR1<BZ@R0?1?{SS)~iC4zqnII)AlQUN(;w~CevIfOUG*k+}G
z?REyM1f)0^tP!x@kHPx_?l>8IC}39rgO3EH2Qm1#5#XeIx;2weB_+>*&jjo+V6A`-
z!QA9a0mlsZT0lw&XRH^n(148s=n3SUvLg3pAv5tF0SDk40ih8Lz7w#(fNcVN+H*#^
zfMNr-3%FsxP66qixXCU9=#h3z43piGvZE`5y#o4nW3XSq#qJCa2)Gf);GlqB@eB?L
znBJ4YVF4Qw5EPZUD}~%h<dh=<dOgVCn1Ja?45|cda51PBuq~OvZvyDaC64MT0TJf>
zu3^A+r+F%;oRySCeHok+K+h_%lM4dg>d)Y!fLQ|=)C(vW#Ne_3dP<3XTov$6TC-+F
zNUjSh9l<F#1*}PDa9cq6NCpi8etU+&T>;*s7<gf^G#7x5&oS^8(EoV`EeV)=*D<4+
z*d(Q93<JA>tQ-ao0kiWM_zNKSjt3JUpkyioy!C0^k&2fY1PN$8qgfHP2^K=89zh!c
z<pm7d3V0vSSj-3$u=I5X5dyw?gF&Q#y|Woa382TE*hfbMMP`iXRscz7Nuiqn1Tg~0
z_#=oFKxQ97cL8MZ5%ds1&K^Ne0c7kEBnlW<YL4bXA>`{Z#U+4jJ%SVg<mC}OB!FBz
zf>Z%y-w`}4fQ&nWz5>X%Bj}e*la6wgAj^)VzogIuKLi5=kX1)8NC0_s1WyPci;mz)
z0c6e*qzNEbj^HT)XNn9NE`-cDri>6kHXK2^0P^1mMhYPNjo=vp<h~JP2q5!~AX5N&
zZv<J%MV^zByf>0;Ng?ZvV2l8A-UxC9knu+Ff&jAI2*wK_$Bp1c0c5xl<O?Vw!;NI3
z5VG0`CJ|`#*bJt602lC=DQdLXEYI)&mJ2+Qdu|2Gg#;Q+HiKCP;Q7Z5-k^|wv3>dg
z>vKGS<+&6!nr)Wf@c@?J^+fIs2U%VqVCjzx7755X#9)a5xP5m;6_bBS$}g1+mI)Yq
zl)*{?(~mJ&E#Q08$NK`%ZqqRSN5HmvZt}5!jRdg%{8z}l>zuMy06K5#<SPM#Z*j(Y
z0T~SpHVNo`m%%pz&~#HDTLqxyCQ#0RKN57@M0OBq^xF(}c>oXcZi?7y(nQ9Xzt00$
zuJA-W1ux161<)kN2!0YkQ$-`F<nKRsNmCvpIVveM^D%-d0W<+Jf)fI09%KZk1kiNI
z2+jzgS&<Q(6F`$ABd8USP-If-h0t8dm~uq`O__|~x&WFv8Nn?9G=VaL1_3k;HG*d7
zsm*|qH%H(tfF@N&&?+SuQ#`Jmh@DajASqry5nt_XegwffeH9nD31QaBrpigk?x}-{
zOj?ym`@LxzA?)B%Q-u&J=bI{oP&wXIA%se;DD-tQyFd)3-$W9H5GwUe6+)<-ZK@DL
z<w8@15Gr*>ffez(RpTHKLghr$HiS?)-Bclj%DJWrAyj^Cst`iuj3{Vu8wY_HN;M*h
zQUi$zIw-`9)hUy9qcQDOn4h4-pdvy0@SXI6lGadn+b`G;ySgShl?gi9MIV5hK5gDH
z_c=Oy=p5mr=E3K4#Z6n_<8{}jc!4WXckr&qe~d`fG0neCS^sLHzTmy+(WLHPg^Ti%
UVql9)NAS%!K3Fe=YL}k)e~lnzEdT%j

diff --git a/build/doctrees/nbsphinx/notebooks/DemoNotebook_ammico.ipynb b/build/doctrees/nbsphinx/notebooks/DemoNotebook_ammico.ipynb
index 292a93d..f6a53da 100644
--- a/build/doctrees/nbsphinx/notebooks/DemoNotebook_ammico.ipynb
+++ b/build/doctrees/nbsphinx/notebooks/DemoNotebook_ammico.ipynb
@@ -166,7 +166,7 @@
    "source": [
     "image_dict = ammico.find_files(\n",
     "    # path=\"/content/drive/MyDrive/misinformation-data/\",\n",
-    "    path=data_path.as_posix(),\n",
+    "    path=str(data_path),\n",
     "    limit=15,\n",
     ")"
    ]
@@ -177,7 +177,30 @@
    "source": [
     "## Step 2: Inspect the input files using the graphical user interface\n",
     "A Dash user interface is to select the most suitable options for the analysis, before running a complete analysis on the whole data set. The options for each detector module are explained below in the corresponding sections; for example, different models can be selected that will provide slightly different results. This way, the user can interactively explore which settings provide the most accurate results. In the interface, the nested `image_dict` is passed through the `AnalysisExplorer` class. The interface is run on a specific port which is passed using the `port` keyword; if a port is already in use, it will return an error message, in which case the user should select a different port number. \n",
-    "The interface opens a dash app inside the Jupyter Notebook and allows selection of the input file in the top left dropdown menu, as well as selection of the detector type in the top right, with options for each detector type as explained below. The output of the detector is shown directly on the right next to the image. This way, the user can directly inspect how updating the options for each detector changes the computed results, and find the best settings for a production run."
+    "The interface opens a dash app inside the Jupyter Notebook and allows selection of the input file in the top left dropdown menu, as well as selection of the detector type in the top right, with options for each detector type as explained below. The output of the detector is shown directly on the right next to the image. This way, the user can directly inspect how updating the options for each detector changes the computed results, and find the best settings for a production run.\n",
+    "\n",
+    "### Ethical disclosure statement\n",
+    "\n",
+    "If you want to run an analysis using the EmotionDetector detector type, you have first have to respond to an ethical disclosure statement. This disclosure statement ensures that you only use the full capabilities of the EmotionDetector after you have been made aware of its shortcomings.\n",
+    "\n",
+    "For this, answer \"yes\" or \"no\" to the below prompt. This will set an environment variable with the name given as in `accept_disclosure`. To re-run the disclosure prompt, unset the variable by uncommenting the line `os.environ.pop(accept_disclosure, None)`. To permanently set this envorinment variable, add it to your shell via your `.profile` or `.bashr` file.\n",
+    "\n",
+    "If the disclosure statement is accepted, the EmotionDetector will perform age, gender and race/ethnicity classification dependend on the provided thresholds. If the disclosure is rejected, only the presence of faces and emotion (if not wearing a mask) is detected."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# respond to the disclosure statement\n",
+    "# this will set an environment variable for you\n",
+    "# if you do not want to re-accept the disclosure every time, you can set this environment variable in your shell\n",
+    "# to re-set the environment variable, uncomment the below line\n",
+    "accept_disclosure = \"DISCLOSURE_AMMICO\"\n",
+    "# os.environ.pop(accept_disclosure, None)\n",
+    "_ = ammico.ethical_disclosure(accept_disclosure=accept_disclosure)"
    ]
   },
   {
@@ -822,7 +845,7 @@
    "metadata": {},
    "source": [
     "## Detection of faces and facial expression analysis\n",
-    "Faces and facial expressions are detected and analyzed using the `EmotionDetector` class from the `faces` module. Initially, it is detected if faces are present on the image using RetinaFace, followed by analysis if face masks are worn (Face-Mask-Detection). The detection of age, gender, race, and emotions is carried out with deepface.\n",
+    "Faces and facial expressions are detected and analyzed using the `EmotionDetector` class from the `faces` module. Initially, it is detected if faces are present on the image using RetinaFace, followed by analysis if face masks are worn (Face-Mask-Detection). The detection of age, gender, race, and emotions is carried out with deepface, but only if the disclosure statement has been accepted (see above).\n",
     "\n",
     "<img src=\"../_static/emotion_detector.png\" width=\"800\" />\n",
     "\n",
@@ -832,10 +855,11 @@
     "\n",
     "From the seven facial expressions, an overall dominating emotion category is identified: negative, positive, or neutral emotion. These are defined with the facial expressions angry, disgust, fear and sad for the negative category, happy for the positive category, and surprise and neutral for the neutral category.\n",
     "\n",
-    "A similar threshold as for the emotion recognition is set for the race detection, `race_threshold`, with the default set to 50% so that a confidence for the race above 0.5 only will return a value in the analysis. \n",
+    "A similar threshold as for the emotion recognition is set for the race/ethnicity, gender and age detection, `race_threshold`, `gender_threshold`, `age_threshold`, with the default set to 50% so that a confidence for the race above 0.5 only will return a value in the analysis. \n",
     "\n",
-    "Summarizing, the face detection is carried out using the following method call and keywords, where `emotion_threshold` and \n",
-    "`race_threshold` are optional:"
+    "You may also pass the name of the environment variable that determines if you accept or reject the ethical disclosure statement. By default, the variable is named `DISCLOSURE_AMMICO`.\n",
+    "\n",
+    "Summarizing, the face detection is carried out using the following method call and keywords, where `emotion_threshold`, `race_threshold`, `gender_threshold`, `age_threshold` are optional:"
    ]
   },
   {
@@ -845,7 +869,9 @@
    "outputs": [],
    "source": [
     "for key in image_dict.keys():\n",
-    "    image_dict[key] = ammico.EmotionDetector(image_dict[key], emotion_threshold=50, race_threshold=50).analyse_image()"
+    "    image_dict[key] = ammico.EmotionDetector(image_dict[key], emotion_threshold=50, race_threshold=50,\n",
+    "                                             gender_threshold=50, age_threshold=50, \n",
+    "                                             accept_disclosure=\"DISCLOSURE_AMMICO\").analyse_image()"
    ]
   },
   {
diff --git a/build/doctrees/notebooks/DemoNotebook_ammico.doctree b/build/doctrees/notebooks/DemoNotebook_ammico.doctree
index 20ea49835b5b72905b4ebb1afbdb1d421c52ca55..46d16f2b52a79062cb1a4e2042c62cb75e01569b 100644
GIT binary patch
delta 21579
zcmd^n30zgx_P={E$|NWtGZzqKo<tCniX6%maVoVkxxhuZ0vEU!jpu;$D$_L6gY9h8
z=4^0EZ=;1;zVw+xT56e6nmyCZA+=}ef9<u;9rfD#{Xc!)=lA*i{P;QNu-Dq(HSD$5
z9?m{@&1#=tI(^({dn^f9?H+LtyI)y#PeroP)RbJQHEAa`Xie2A={_3#S6fq8V=Bt&
zo9>g+UhOrpz52%a#O&|Dyf$g#RDW(VvB=V>!KUh(3T>^Xvc_0ZYcMu9=`==@)}*V`
z)tf93*JpaLy{&y_dvbNG{&g><GcddLRj)2xsx{Sa)p6DF)d|CXY%bS#XI;9aNH&l0
zvG~W(Dou-_Su;&rZ_=0ynx^J@jaK~E*0vaHjGAU+P5oqzsamHQTxT%V80rV<Ou7n_
zp-EF|c`&s!=+X(KT02#zsj6u*nl$3El>l|d219+Nctl*?b&Sl^jIBnA*Ro%us}~M2
zq9R%oi89pJwxDu4Qmv}FwpLT2ZP1q2)Yh14kk3$sgx0H-)>fHxO*UQ2b-H>@owib^
z(N5E%!?9Y8$*3__8=6cNhB`Fen5p{y|HE0W|08ex_0DSjA9?Gqah5Fx-}O?8Pvv_J
zJC5=As+ZE19Wr!$BL>_Mj2(;uV>-rzaT>Npe2dN)uffvzdPBVMf{3<qU9Dl7rlHAD
z*I-fuV_FTivQcNkddj24p{>(uOx46&udUN*Cf7{Gw$vImHT9aZGHpeLuE8|P7E5Ji
zh=Sp*%McMRB-m)Gm~>5Zy?__QsoJI*ZFw!~fl*eEp&)vpr6<(Z)ax{5tz`ydrmlW!
zO_QNMv%%1ie3i^}%?LxiE=3jHplhnr)*}oCt`vj8j`a;qHT44BDia-3S&4BdT!CG)
z3Byr`mQStG%0Ceg{ZiFhQ>!a06Mn;ja;>qt3ID3XLK(5im~m!Y<?HWeKaJl0ZuT>x
z9{y2p5YPXS&xNkSR*SC6v&EiCuG^s9771IFwyKDtkZZPzC9?%x<vlxq9bQV@$ZXvf
zOlQsIXjkc9+?IBtNY|RQvj4nsEf)0t55vJuSSQ(4X|-zv+4YwNik&1fE6q<09f}-_
z-rf{VSY*e3mK1|6UOcFY^<-4Lw~sB(EOk9);Mvvm@D@!KZ8gbL4N1Fb@KSbV7I>bp
zriIq=-f|pr>Xp{fPlFvrhKH^)ow}#<SVXA-{Z?gYs?%sE<8U-tS6_*_MT;X(leR*a
zg#%B0O+}5VMN?6$H5zNGaI6)>84hEu4T2XL@h_nQcCM*4l{y@<s&UAvHq=%cGc`C&
zI;n?BHR<#?77C?kIFglhMqPac4JB157&S*^og6zg$u(7)dV@(bO^5jf$5ky3KE~E5
zDZ)ZIp6V*C1I~ZTE3Mad%YV%)xz~1!vsY{p6zwfW7SCZnix5&8p1d*8X`*vZ=`h|7
z{k@e%%lkutw-VH&59E0(?4_8Z@lRr`C1A^0XC+R}YK=Od1Z;6^7pGz84vaC8hmnkp
zDW*=92HB>T8I&$V2CH+x=%(tLS~RAbI(4>Gf%75DKtKZ;j$F2UFT~S$Wf_v3(k~59
zV#rblCz2*dO))<CT$N8XMVk0QL&pppUOMKE(Ss)ymy`@0SQ?LFEO`s3E7u*zd?q1;
zwyv(G!jP%X<Ln05tB1d$t5mQ|g|FQRz3oQi|GTYF|6gbY*_E*OjPd59@?jv1^i~?z
zrNaPkzNi&~MPFH-mku~<3tBeFsdJUMDM8N;gW0lk&6J(%Z=!R>Dj!VQ4NFzX$0g+b
zDkO5)Ae|N_CH}0rTvr_+)-Hh)+vi(WIT^Nq$gl=PySBPJE~kP8-}P1#$QO!yVH4Y%
zt7EEjg|XJvkf&S@t$nJlH-j&{#abz7r?>rDsiX&6>uzXa&?$0FfmaAafSqX4lSP3}
zoRLb`#shHCTN#xUu3T<RgDzdg5Xden_cYxs%8UC)DepC<LU$^Uy@-Nn7UQj{sl%}f
zR~WX`hU~jC^Sw(nuH_|>{|mcPa?9^Z$*oUU^8YiYcVKi^*`%disY!3>N=?f8DC~g@
zKnp~RI$4mbluzx1mab&Mz0(SyjWi8w>8fhV`rE09e57K5YZZ$~#aE?@FG&@j7b?cA
z9nv!04LVdEH%J{<s5(A>9UX@$pU>3638~nR*Hr9BRk4w-6}wX?#(F5D9=iboeT3_n
zzrvo6U3;WeabxLN9=tdt8&Z78cOgEqJNWxh>|Wb>m1`e(U?77rKIFac9xQ;neMI|<
zl9Gq^i5t1A#<f-k(&~QFs#R(=gS2||;afe}Q>s?V6VE0pv-7&b1FBjxuBTR;^4+74
z!$u#9-iKVvo=>t5k?e1z?ENIW^RZt&F@~i_lx@qU>`qno{_DwpZteF^j9?J!OTu4t
zEqsNt;YouV_BGyUVlhg|QyhwYMQ;qe(bu6ju3DS)^t}v9CE^-^c%v_MMkmI1DDrB3
zsdLo$QVUlteo3SJ{Hz`x^p#!XeyobwuHIKRZ<Q}KF9M3b;RM*B=$4I!H>BWCT?_sv
z3I0q9{!|LyBm~Djp9kNmf)7c-+f>1ut|xe}QvSkN=;}v4Jm6aJVQRo6<@Bl>Ai<Ba
zfyNKJ+7@<`qFpnH4Nw}^Wk9l@v=vDr4PV>Ve<^!k-T<rA)>!+>bI|BVtx@mi&>E-K
zw!fML(CSAazjs9}%<&T;@6(EWl-ll9I$jA?hP*xonRxL!7NwY9PlBbyCF%ve5hrdU
zGmd;C6<)Uz-g;xcAW)AvEsU=Bqh@x}-~t)Fn~dHejsB-FI#zk{t#j-rGW<s}e2;24
zl7-<2CmPuajwzk*4}&m&ikc9Aa$<K(42XCC>Te;(U&c+QKgCUizw{+?xQ6s6$a^K^
z-4b%VguMOj!!S*SG)c%Z6%sjYkV0AAh6(VZ1X(UYo)sW5YkQbG+~7kM<voe=vWkK%
zHWX)DlS#4T67!hEJR&eP%10l(0&W4))-C~L>j@PSIb1{L5@dD&xi2FC-IvD#l$?)r
zFjPewBGGaKq~}rtu7fs!(56Z>qd@Be4FQU_V*xBw;pR)Y`&2ljx>jz8a%tnI?3A)`
z(|-6YfWrCH0EciMzV_f|J+QBoQ9Gg)k6D>;C_qGW%vZ>!4%D<})Fj)Df`U6j`D05Q
zoF;Bj{U7Jys{k3hBLHLf(*WG{3XPASQI%7Xo0C(Jo1@F_lc&`cXe;{Yw3Str{VH;^
zb%hoA%156W!M__n^(yPD`BUb(TL(jIH)ZG6zP{stwsvFnUArlP+j6`{TE&K}ow)6+
z8%tA89~y>(e`9A3q+y*MJ*g-{*)%kc4Ym}I+u2Jketc&F8)qp#x${G{c-i4BC8{$}
zncW#LV3Kzal7zK$b{8`?-BRKAFP=~<tlU$`7Fdd-_Kr}CAKW{WJtvC8(z;pZ7WUI0
z#HOx4+G<DW+GSrp!<ZQ>r7LAdKd(Df(#(B%f9|SX`|j!%fRZdb-umv{_%D$xI5iXt
zwPF%!nI!5XutXmzE>YqVEiN&5QJ&oz)km+vr<v{gcu~3sFGhWWc<hB2oL=hv@s16?
zMcinwy<{Ap9mPTu1fcyyRR4(`i)x9OQ#ys@MCt=Sb)z2jV>jvpN4trHv^MqYcn0o)
zqL&V0fufVLlgh{6qyf@JFTkJ^8O{lC@>;_|Plhv`n@{!gs<rd(wr>*|^bh1Y!yrnj
z-;oKo1k&uKf1uKEI0Pw_<FWl=ED@sn2dWL{DK>B`HFkYMWyZFLDl5v1opAz%nzi1w
z#U`?NK_FQ?FOV#r6G*8p^ZQ92@G@CE5MB@_XRtt-NRY#|%@3`8@?WDF+fFt=VzXJf
z<)<y|YbsqJOZoCLW`q-gT=O}*P29`0>^62n8Fg|hga(Nb*z+;L*+XIHQ_<<8E++An
z<tz;{?1-s$M12Jd=(>b;!Mz6jr)W;a!XP`=V!;Z5L446cmLg`L=M#8oCG$d&S58fi
zHUwc9$#+KXCf$7|I~O+wiPm9tqKdNWXJ607LN7guo-Fm!u`pN|q@4aE3>Hc51&-YF
zY}`u1nJMt5)Qpf;2pUY5nn7id(s6sCGVyFY><CiY@U}}LZnq+~3;A0Kaf?m<DJlQ7
z<UZ-hecZ;a4E}W{_;)7{6Os=Pa%ZWq#ZiGp=i?x&yYe>Pa=McPGI$$fnVyde>8VtQ
z^;TB@aU&~Le)%IDMoF#`JFeSpTuI8bi+4bs6iX0#DYkcaY7vXwPyH4P3%e^H;BAov
zTp$6T5Mt*^z&Rv#C5c@vx!$znT4Cc#Qf6LS2-~Gtg4im>&T$m`_3v>wUj6ZVJe-zz
zCnesKLh5mecT7lyZat`(gL;rp{5kVRpAegmcur6PZ}Vb;HA(5XyZ|zKkfVtq)ye?J
z9K<h4VlhzKW62P_jgr7668LE$|8`rwTYD(0M;3uWD$yu;>+E>-_Po54u~o1@sz6Zl
z9LS<8sE+4lZmbuq?7<%r_tg^kO$q$0P-2Cx<|{&pL|*RBB49@kK1<wp$r{`3YHYo#
z#z+s=1}CLD1bW<_#Xb)BGEWu>-Gcdt;vN)C`O!aE={T3+wM?kv6Rb2|P64lA-l1m$
zAuE{29YycuNX`s9&QvR>)|<TtCBZbiCy?8%B-Imqbyqe448h#bhiRZug4Ic|=Y?3k
ztT9;?yHFLoNOCT)<D6&VBwroyWrN{ODVl&*SjbkZ+1M0Jg9;lP!!P@>VD>Mi<L88~
zTis}s`!s;x<j?BiU@*<54g_PV^(Ax3%lwo-dxibPgTh#ZBG$uaNg*tW?8b^Dp%^?u
zC}w}++q<y=DmU*H$YP-<QNn*hSeku7iv0}Xr(ijhyed3!AXrSW(&A?nl=tmZS(u|O
z&=pqZ<>%xVR_0fUvWh+xg@sj>+8Ol1LLbnL`v<Wq>s0H{s`0HstZ$_K*gr7DGWO4p
z&CJZ=ok1+RTXS_n$x6#iEGvX&Vk@lrg_xD@><aKVVsX^kaGnM5RUvFBj158WCG(s9
z&AfS9C@X^DAzUBIej`3*Qj#y9)syvs8uEr99>uAfg&4py!?0^iw-O%;V+9tXFW(o2
zW77gFu^^n?Wh1^3jxqWi5q*ZEIppLo_@lvW55E$@d?e?g%;bS3Z%89#`{Ln&PjT{M
znM%!{o|&onQ^za2_J#25Aa+xjkB^U~5o{p({17=G>yL^!&c|-V68%l$a<jM;i_0x|
z;fI2lCfB}AHe;ze9~+F1cJnba{;AH#R?7L90CY7U!zQGV67w;qpkBv4quEs08$t>6
zJ!0g`%Gl&?CDWM@xJP!4A9zj-8_Is*(_`5E;2BEY`$NI*7AkTC>%tdhuq3`976U!n
zjvPT`=n^WY1b^^i4Gx1pge?B0guka@(J(|Ze<ZL5O01hD*5o+01SZ;%?~+(IODre~
z6@xh67LOulO12Jx@;8YxO``lQfpKWJBQKID(;QI__retTwq)BRP*zKnw<O9ViL4Q}
z*^&PtQQmSy*_OnH!B3Ly6M^!hL^&!^Uhd6G0eX`2h<rt&9CbwbHl2C#ZOQBwh?l%u
z1XOHKO2$z=Dc3!d!b+gfj+}2H%Uq{A=VUHIeVoc}hY6DRGXZs{<Q*fSKJUXq_{ua^
z1`T#Rbrv26JXCEcJSN$;38)2<ZJt%D5WXP?d;XpbmJP4iF}`SFbjIt+k7u%6*dlqi
z3((Dyx5ExJDi1+F%R<m^?HIqdFgk#u(UJW7Y?cp~CGQRadP(wLv>F}GcV;kmekF&6
zJf6oi*1uxW9YHtXl0vM?sA~5xa{a}g&SFNfzBblfLQ1Y=%?hJdLf1C4;Z7_=Ei6_v
zF)IBKVi}dZd1_zg$G#U`#X2_Oi15hRX!Gp8EQ~=*7}usk6yI<si(zd7J_pNaU4u8=
zuIB**SOQb5lq>OJf<aI=7O+_M5>b3w!qhA|hOh3+#_)!I%-6#Act1oiTM+oke(XL$
zqUFvWVJT{Kjf8T5pDAQJVV@KxGCfxYvkawdmIvF%2j0MXBh60xGg1PU1&(9kmU^VV
zJMXw14MWmX<FJb(Bndy{TKG{~Yo&$LS}QqRthHDoKV8CN`N<;oJq!w$dqBnEv<H+C
zE*D#g;k4L7gTw;UDMS8Dn2i#%USduWm>TnYH{-+)=Bc1_B&bmZonjBl4)D8&VvUCf
zF<-`33&SY9_~GHq1EeRBC$WUx1)ob%+oY&}koxA|hcGRJW2&elQq)dW)IaP+1v%*-
z>}H-a6jxw;@;F@JS%=@y2r*3w2#8Q4z+Id$;`fYWk;Fp-Z8GsdK!k$vBkPy;58&?)
z!wlY^Xc3O})%6?(M?eJ68O}0cII;O!*;uBOfupc@Nw}LejGVQOb)z@k#t3T4h6q|V
z*F}hBvpH}C8|(q|BV=37ji9z{j-a+=I8Cp__aLh@5yGw4XwMvT`B;|3U~L3-2bwgz
zFAZHA!6WWu4<X4Gps?LaqX1Q_i2#K|RuTm$k|;p)U7IyPn&lZuX1PU@SzRK@tb_@y
z*#lxDrCCvtWR`cN3{m6}`vKQBsf52YiG2V=B54pGP2$BMZh~=<a^;VAvGNyx&xm2e
zAK!sXk~YbHhhU$@wR*X#g6WZzxo8*Q2|Jc0SFzw;KnCwMMRabXpC{qGVb4VAjon8@
zv<raZ#jyWUB}>L&|GW~F_$HEO%liaVrsp`J%U&DCZlOyN{5z6XgTG7Oi*~%fI`Jm*
zrB&>02#cb&t)9$o1x*x5!2HsL`v)o|q#7x?M8P8dST(B?Bx*iVA|#43{%&-?SibFu
zq^ZU~YjFIzH;P{t_p&G+bb{sJD*&-xnjlo4AZy(jCD%){qU3sMHnLoBU~I84lCQs+
z!k&bu?R0)IiWeUh(A=*MmwhU!xQ-RWdMjyt9UCJ^q%?_NYC&~SdS5**PQK%z2Ap*N
z5QQO<-t|Znt#=Mf)$bOnACz?uM3KkcqlL$rCtp4rGcZJxiNtrsjxUk_+`#5Sd^CC6
zvyEY5kTv3?>3o%iBsv)zU?siR#BO2nd{-Om=S85g(d6v|QC7vph&T@Wg=L*KmKxf!
zP`h?FDCZ3(Hk`EzIT^~xX!pPw(GDxPYV&0i8_C!L!6Aoty|8@-ihr^w$cei__SF^9
z)K_1LroQ@OH1$>UG&a-|Hbu+6`Z3nW*KTh_%f5;{qOT&VNIy=fbIks&EQG;v>9nHR
ztb(19o;j{MO(h9`f_sdJUZ3M=2rXy&@#k7up|9<|`f=&T`KlebYUD}xvl@tsp;_jm
zuI+0l`&c3GT*!hIjj1=w=c5*|Jm?dHHpZHN`#XzbY_uQ`Vx@xAi{8@S5F^b*Hk+Bw
z&RZtITW#PoBzTJizw!_}!q^iMe2Eo2wk@Vhm-(JX6CQDEYM-l*!adnxVjWVw3)>0n
z+9WzVc9r?UTsDNkN7C?hb`DV<VXwh<S#EaikPoHK$89<vlR6&}I>(q_TEK1qaEqlz
z#|6)><tzhEsNO&xn{LkD_)LaUcB}{`Oqy7;m-5T<KuC=xS8rV;G#{!W4<Tfh%iEr2
zA%ev<@D~zzssuLLfEx&y*A0MVSg7L8m$>&yT;#CfIy>_lbJpW*GlTW9)U^Yiz;(-p
zSP_a?WM1?H3nUt)o=(>uJtoyVD%JbWrrsfGx9?L77+hBMyCn5HCiO!Wn|{s?Ju89J
zG}JefHPkl~HRQ|-&#?O$4ARKHS*(#$J&g=n<Z+GqheU0ZsPz(c3ZY6*&Qn3>NKl+G
z(WxS2aSiI}&X+#Vu9{X>^OMiByMvtGX1ok^V1Q41flY(W8nF$P)S+=mVt($<A3H1+
zXV3Y^FR%!6*^8`@4NBLPH=E?iO+3lx>KGt?$za6O=;CZSohiq2p~*%aelSpOn5s+R
zOJ8E+*lvFMB{m8U;M;!OoZroxUuL~zVFZ8sWt;+?Ad3HP)KTQ8@#&}w@9_#dHtMfX
z!hU~jH*ed7<3)fwCV~!)x;>ViQ<$G$*(bk1TbY;FuU}zdj;^4ewz8n2P+QfnBCpC}
zdn|!J{Td7A8(w8u){U}10}vZ!vAp6n78-27GZPjkcV_s4*I2S|oV)t6(mjs0$O5f8
zhM4_VuuUEi7bp6W`KOi4z#t`#I#OJm`O(!ZpIL~9*0Apx++ZQ{^Kau)J1$O~GPngw
zti|SaY_(d2|9w4fhfT7QzFUtiB1LhH87B*kMDmG4ZE5tlmp}U!o5X)NGatc6-M71)
zvUk73dbz{gINtUF8w-mhF#g%~Lv|L6Wra|?3Zpi##{gc7qp>F3M(`LPAp#+MBO4NK
zJE81wcv(A{&+K4v5oKlaMDrx;q2#i%bn&6XWWKP2&1JQJhH~#loY$Gj!ThyPSYP-^
z>WxL>MW3W}4YtVPL7%W-uRtl3uil6$b{AF1Fk9RN>6Vv&7;B=`SYBOW-5v}Qy6FhU
z%^$T~wULFw_ZFG_-y3lSfkMf-kye+4#=koOkJQ#_TQu5Qqe0VvXSJzo(l;LTRgaF&
z%F?GT;>dIpex-w_tktu)>d9L?qASm4Q{C$w6U@}y(t<~?tF+CvCV95p`soLr{S{Ix
z(aTqzo6W?t@U)#NKC^h?f1k>BuM96?%ZUAXKIa1#+W#s`%E~N<`Gc;a*`c__i{2O}
zz^IQf`=oP8ZO3R^JF-oD)@D}0`)_6;*&<NIDSYSPbs5qVHZuhx<7Ed+Akp|I1uEXe
z{tSh1U!r73#;Zy>M5HKnh{)^3_N|1J@gE{xGqxvK)qD|Od83*b+5<~srAuTJTyqQk
z&vGkmp<7aNnu~pO-#EFC-VNKwaUZ=0mgs}UB}808#ib`+_=MM(rjLELo+TV6&ox9K
zgWW!QBU03T^f-6k7R5pm1fr{rbWHR#_=wel)3Dszoi;3%#M6vqaXigP7RHN-qsRCG
z4AnY42lo{}{*2Z0)uk*e(K$ql`eHO;VzGr1mPppCj++-<<Gedx^cf5LFNw<Bikszc
z#mgDi>+v+h;_-4agf@%G5Dw8|_2cBFKIS{OF+A_MH=ag}eztDKeYP_#d@sxU%W`>o
z;at4j!@xW3Vc^}ehrwca&S9Js6bb&w1X@IfC0O?_aC6p1&UGM*y$jr!wULJsnT7Gk
z4&v@sNP=?u#uPXgzxbDte9bNv8Z|8eBSk&BAU=Pw%OEWR2A7kwJfJy&R?0UCeVU{|
zgV3i4I3nVTdZ~?fi5>4^JKjY8;1}#BwoWQXP-~=e2B};vR>b!n${rl;ze?cm;GONa
z;qH~V#X^VO5_gBx;eyoRHyiJ-cD!focoX@|FLB-%(u<mjpt|=G?qxe1ba>_~e1lWa
zi+>>Qg}rEA)3+D-V4#qnD=TI3T}N4xa%@-_jO(Sa;bAaA^4?*`JKCO?Pv4L4H=3n<
zf@&f%Wc8AJ1gaDG0o)npz4$xgzEpxPk)VTx0*fW+LQ;S~=7sy^X0ADk%<oF(b#}~a
z9GD;chAoG^QUk);Ej3u^sKKuXar$wg7w`5h-hY#zze><sg$8FN=qalP-u&3NIAiFU
z$gg~hFVn*l$!j5r<Ta|&J&|0kR@r-q-3@&csU?V<OJq3ZsK=GV*eAy&@~BR{PmrK@
zNYJ4|kI@pelrKMl@9BgmU|OQwpK6iZ&34>P4%|n-!@jvhsz6|ir3$5q4vi6V1b6Vw
zi9B1}-<6>2B<L`q!Ws#>(oTi1R2BA1?!9*0yB)YM9Az)SuTlj9J0n$C>8L`@F&3ri
znPly&Ug`&GcHK2RNje;lj-1PgDG`cw#|q8mTI+`zOE$0SLjRP`(|AB4Np9yABuRG_
zN`Sru;6(trNtAoKB~k7f^)K9SxFd;LjL4%cWCwSBb{t=ZOiSWt#Jxp=HcQY_p;eQt
zWl+U)Rs2%Pxx|ihv4xYwZ#lvKfOS$l0j;r+t>VS@+BqDY)a^Am9nVi2ai8<rS^G}j
z?-X0;eDcnZ=bXj0(fL#O*8O~vSgHn{6^^%^n7GGXSshXk=u}$HH~qp+f`4zm>OAgn
z(wTvf-cDx*koxc$+<)@tL4MHBYqIdiSu_LRU^~Ip2{qQh0D+JlRM^`=1EbWyskFsh
zcMexaFoskphr8{h54wPxJV<D}fPGXlMDcYOSS2*raSgl3#tZ7QOSpW%`v(`Xk3ML}
zF!VP(_+ZEI+;8}n{YfjsJ@&M>|BYu(R$6J^eC#EBUu##{d<iRWwquy|I~#!v*naWi
zten>@;hw_Yw2SFv>jUmIFFD?uww{jhVmFXmPe-si?(+Fx#sh)imMq8eF3DmnXD4{E
z7lZ(^h@l*T#Zc}9ym-kJcn?yODayHP1)h-#+?q@iqe00uF)B_L!udjgS}0RxPn5EU
z^3@3_8#!#UotyP#iMc>x&XbsP2-AGj9e!l|rDzDj4_<g@G|=}QY@vijCL64?N$;8u
zc)@gF+xh8Gh~N!APz-yMMYizSo~+Kqd-7A>(9_Q@pQzlazAzV#5jSj4=Er;?1@Ceh
zxIuLf{#1Zj=LhuwSES!QcI~%MrHxT3<hSq?@>^(%m{6Jr1VW1&^i7eCmYYJ27Q<KP
zq2rLnwS`}sHwMF02KS`UT4PKoq(Nnhe2<aB*M!227LspIm;_U;q-T4A&O$=J`0|u6
z$cKj|y=RK*9EY_N%AhsyVVjN44*!AYg~RL4J=!P}OF#sa!rLjLTL-R233iF)g!#D$
z$OPD!LeclLkgyuPfYWj(&U4a>hol$3kzU*{y_g>ZULJ5!_2RG6i=EPo$RfOmpcwkj
zpdKFPVZ9*G9b!|-jZ>51R@R$0_J<rS;-`~gl!Y`g1xDc(yCC_*rmAkzbKgYJ``g73
z*1{M1{n;=p$c|LV7GSu+lgB1faikT%JyVlm*`g4?ilXZAR2mdAgB8L%9mZSqAX1x^
z^kX_?SxC7VFc^;tShRmV1IAcLSj&e$oCQ62ekMfWsR0YqLzx&3QmWZA3sUeLyOmav
z4Q~k=HNKCB%ccqPpv?4bDrKgxdE-rx2m4YfD^1UZjf`F3BgI+pbAlw_JseJziwtCQ
z-8=~d%zE+FHv_%cfVed3JuzvNb$aJRGAk0)LC`;q7B5L@5*ImK<EBeoy$yG=#I2OL
zh5aC%{axbDmbkSlE^^p#ouj!gZz_aWVMUtQ6^P>f`a?gqhBpp|3}xAE?xOs~{@58;
zq)C_dckR-frH1=$8h$A?{6cCdUI*aYCbImL)bMLnL*#I+;ZXj35hnZabn0#+Tq`hE
zwrPGkC9OW`<o4`za{H6FKyQBXCfEd}=`wK*PbcU1OP9_^KAQ^8eQuIOo*|K2B=S@%
z@^M(Af-aVzvs6%Iv4J{!Ue6Z|g2~SL=Y-5Zy$8ck*pg29XLGtk{%J6;84SnWVK07I
ziCZ@2+p#wtOs8oj7KvTQz3Jk^gWKU0m4@xb`n0>`u#tmIpA3VW0pC`NH!JvO;c!T>
zpiUbOeV~Vx^zCqX#zK0$1WF*0NIq8RNj&g2n8as|0ACB=gu7rc6j&jmOCiQWy0a9!
z`A{qAU@0sSB<i$HqJcM~A2FXgS>7U>p&^4hZ5=PZS57CGo@>h?jvpKaZ^GORYG3w{
zAZI{RhHPJb1~ml&i=65N{D1^rFM-$EfLC!g5j1AgSirYBJ5=O<O5}G`<W=^_flkQn
zX18(hEQ9kI^uZqgXgnmrWobE<g-?LLInn|%sX375dlxpr`3!1g@?|`c63%C+&FP1m
zxd!~X3;MMfyL|2-E6<8ob2p3-c;w}!uD$#mIfIv0!(tvc5e|SUlRU~d)<6?T2RfU%
zf_qN_t@9MT!9%`KdSVg=^UIkuM}8sGA(&Tr&@A1lbUmL^25-QJnbhUq7rMTXNfF`1
z*dZJ4KqhthuQElK#{;(=)u7>R<v0|amAb<(SRLn<-|*8lI8E7;Nx^`aVs7b#xs4B~
zL{CLzk?@_ag?}l97i5v}ye!H$Ia!o%&gmc(MrO%WQ-WI%qalMo){3%`LF9yM%Ra=@
zCc|);CS@OSE&I5X-7aM>lCmF_vP}=d)9|J$dqox*{<sv59Il0*<@5BQbxugD_$58u
z?Y#cFN2aL<r(nw-%c3-OB+H>?e=`Tx0)DUjtF+~ku;mCUgWcMRlX;p?)WL0T;FnFo
zUfPHg!{BV{2UsMI52}>TMo5Gt3x)S@g8Psp&r9uW!u-<DN{cr_rKm>H?&)b29_S?8
zpLfoLVfbDu=pi{?vwQfc`_;TMfp@fFB>iH7FYzc5atvb4f|>!^Y?)RjWRpYDFp*ZA
zuzPx%_e_On7(ACvu@vQ6jd-cX2R1d{wW+aQs_}IToMU^X8oQ+$8&oyc+pFPhV!HX8
z>2M!|-=!8guC*v2Eg(FHB04mOBDzNoMf8SQa4+QM$cWC$p}{jUM|uHSL|9$h3pac6
zqDmYxCghM42D=tNOp2c>#T%vg1}UC8)IwGKd@24uRXnoT#5-F*mWTZv&cJ#peS&N0
zlce-7r1YIq`gSRuy3`3(`oE;~y{dF%aV@=?N6*2;==7%jH#IT7IR}Tx82r!|R~eDH
z4&A5TocA!CVUV6nUTY9~N9I!ZapIinNh#E+w2fby2NRvUZ9T7k1hkl8lwxC)`Pd`a
zEWQt*;Q0Y~<i*g$*`v_IJo-_1)Gd-e+7zE&%FhMFp?~?pqcNUeS_ILpfA&RfJAL;#
zU-M_5gS3-?`I<j_W7AIJo9BBs>8kJzBIk=?9c&8VBNXTj+r9ZT1#V6H1b+s^`U@u4
z{-qQB4Zi$i1!7@}AMaFP2)rM_Q`%uz!UW-nU_7yqVfhipj5<SQbFI$UuHT?RTF)B(
z$MdXbPyKrFmtT2pO+&6=(bXcyFG>89b|`?(EPlBiqT#I+9=!wxdv)OKYkqVUUp@$;
z-So>c`P?O-f&E$hb#V{N<=e%5R4zZY1ctP3!mp#}>bIj6bM?ZOxu~tUPVp1h_lYX>
zoJ$(bB~9j{Y*EsQ33#slEnKb6)eEU}QJT2!r}8kWHA-BYs{`>zVf0(^xjIk34R3n!
zO{M;yxvhBJD;~Ft!jAzjpNpqC_#uXVhj<b{_oCk^p2V+1>34}I@xv$j-Qr37%!B?5
z@g#l=K)**kiP+cg6;I-Du>MQ&B+jMjzY<R!=t})Q@g%m^`s??LN3q+ZKOmmOidz4*
gcoGvU{Ws!CjMw^u;z{IN{kP&NGS@tj!yWAZ0j0HQ&j0`b

delta 17365
zcmai634ByV(oa?HgWQ1}lVoy{i(C*OAPGbg1i~$fKsY842&0@K2y%lcD9XYMv|xaM
zx_~H(VHuHtpsup+dLS+eA|ig^t$+e52w!#Ao5`DT8T|d6dFiVD*T1T->h3pO_%h&?
z-2q;Uyw`f{_KK~9<yvCpxQOwVnU*orEHi6zEwy8&O|6|YJ40Jl8GCDKQ|zc&t;8Ss
zSQvV@uZKsCxyG|5sV2E5rQ&<dGPf_<d_~f7=!$!MwXlc|xZ778-35tS@w|`lLn@lz
z6W{X{FdW<AK3{EYR3vF=TMFCZ-Bd3c%UnS(H?3Zf4uIOx89CaZc(2f#&PJ~_U0XN@
zAe7|ov=1i-`TSXvXuatxF6Lvgi*A2U4VIk5bU$ry+ZgT2l5EJMS_P1<4PDwp7MFH4
zX|F8Jf>OOW<YAL6KAPLfufHGM8aG%QJGTOB{MhkoKjnCpA3MHw*{iTv3!Ptv3;ft`
ztDo|_%1`-CT$SI>e)W&lMm+i@Zuip;uQQ1X8x+FJl9ei19x1;RtwcAp(iE*vbXp%X
zt)q%oLQ~0Ob3NgL;`O7>>jd*U>Xugr?d>P4G0tC08k7%hv_s3Iu#G=+DRRT5L~*&(
zpF`B$UxlcfzYI}A)2Y8{o;Z@qsB_%suYv?++Tll{u$#ZT81-wKx3(wX5`PNPAbd=5
zl7E$pPvw^i&|o*DhAC3JbyB;S)J~n$BkS+-#&?<2J36T*MQW#8Qj@fko7dq*e{J`k
z&c0LJSf8n^2M2IS0s~Y?`~o;6C$?Pn!E`F4kfa81NJ6#J%~9wV;4UPOHhs2Z0Kfok
zdSj9AN;lTmXnS`~#fod%;DrfVuNMSNqblvRv7NlbCI=XYb^oV8SiXX&rj9T623Vkg
zH%Q>g0X)cD)EkvsPqSNE_~taRXgP%9TIE=x_Vr6v+{1qD*8SS3{94O?5vm#vE~q=S
z(YuGhXUh66H`ezk>%ZyNBX;Q4FX`4}n+h>3P(?L3kfZvCvVO^}^#j_-Jwu^L+r7KU
z_YF7Jk0|T+1agxOAwx6+4h-apAZG7&oWi#6XWKX|P|XAb167mW!u6xt`?iDl6sVSZ
z;nmI1NIX<ag>DRVYN=0}p4itGaaW+4;NIV#2z!-k;{k73nAAMoE_<;#6OI^V0SA(#
zOwNFP4rIYeqioxOl~SgL(+TPQ#z1a)7xP~z?;(i2zro&L)4kvL`mY!pq$1xYi047i
zAm#lv_MSjh!@Gcft3dD4LCXk%LRuQcA)WiiX&lR-qjb<d3|bnbLV63(%L?=f9rQ5<
zeN+eS`Oh=>cLse%2VKRWk2-;dxiCdk>)$aQ^+QH|PoX9>1syr;i9ayxw?V?P33Gr^
z-*bx^%BV4|II68%sQ^T@;sDs*+m7w2h-QhrR@|TCw9@}XVMHsV|E^SH8FY*eTFIcp
zb<jQ^_QKf=TBn0r6zFibps5V{oDRB`K{xB5b3U4a2N`s~4!TW&Zgv87?b5m0ugBho
zPqh6XpTOT*X<vrshhA>w)aeVGj{nz+;G>m(T7kjAYF+ZtUjNjjiej}ZpC+N%UflP@
z6<K_;$hQ+xN50%jTb$oIIeA|GxXvBNjmxhZSJioZVSZ6Tm!kGnojO)k6?W`2p}<mA
zsJ(i!7P|$DDap{$d|TxupOxc)VC`R@bqwr|DmhBD76ps$DNx{B#CDrXPx*Pl2qGP?
zO+1r}Rf=Kkh+q$ox~iIzm0sqVQ_c0u>KE6~ug@T+QZrV&b|wjDDoq>_tPT1yRUyP`
ztG-OZM;ztnzdWFqA3U3fPdUnyzAEGLrbS<s0zR(<0S=SPv`wd%1^vZl{-rM1?7)aR
zKS0M`aDG0%ugcpvARyPdI>otbOPrh5f4vd#e6U&>i}mtZ-xl6JpznS=qN12WlgZ)m
zwwBT#HNK<jYl3BXLg^uVRK2yFN-Z^!^jB;8KblJVP>Hp#{HTy0{p3ggU~TGmiR}l{
z^Za`2U|HlD;^9$i9U>p^rjNRs1Zy|?rnp~`Un;%r-(5TOUF#GHX0hW-#a|5??30=t
z!(6&)IggIm5FW>ELew~p3{m5_>DTtjfE}oe26BD~4`h?J@5gM63{eC5GL0&k9lM|o
zY^wRm2XJJFis?{8tl#=M4PcV?<(XJ*{Fwrr9wG+@P9p5y5Ty%b_gHEdXxA^s=;gA>
z*E-5KUP_{RJpJG6#=}bXuvzzTUx-+}8Vf;rn9!8|>lknRFMIeAdx!@^)B>>At&3Bd
zv_FObUS}6;TU^xcxc&|XgeuSLbY2^#LoLLuxlt@CW<Zd9>Vt8i;^29x!*W)gEmiLf
zUAq`Eu{#wFO4A12%*INCbhuF}7JLIaSZfeZvx|l0Ap+?Zs$DF}gg5~J6TLQtdU&ik
z(FPksRlplU#TJAd--o2t^;~hCv|5Y@L$wQoqVW(bHX9Z985Gk*nkU?kr<j1kIbjzw
z0WDNJ+_#Gu;|0lhBUCJ<Z}89#-)N`Fh5xz^JWn$CooilU1_@!30hsN&U=oc8xjsrY
zX6+)#LZz7|?(%{8(2ewpSlC4uIuZE175Is#eIW)%hl#zukOX5L$d!z|K#~|PE5p4a
z$p_ksRelhS3z*0vhx$B&`W&PB9Dle68Wa(QwO$dqH_VC1#sEmfgJI$zeZwIKXfuN@
zk{tFa(7gr@r<ubUhx#dl`U#`@!XQ`$*A)ka^}FJ**O>zaBMB13%~sSX=5W;)OyS%Y
zmPi6I;i?C=4p)7lBwY1{9<12SsMy7zm?qu~fhVw%D$(Xb;S9Hn4G~E9U+duk9`ZlY
zDh%>*LAdB11_`)`@#pFI4@)9*7+@9?*~CN|S+T*WxZa?cCT@nq<JinZ6wW@o*g&L<
z7#<0!csg7xl;39<^^}hKh%|qKs~wl-)5ORqh>gDyu21eIE4?Q?Fx4{Cu&8*5!J(jc
zY$MF?PB491!(!^pq*~;wti(j9Xde%EBDcN`#3htOIIQ_pPnkJs<{X2$9xdj&MR4ma
zm#n)mUZ)7f`ir>~+tCr?CVj)$mMWFTD#M+sER2D*Fpn83#5s1c6T`1!!Hk<Cgm)a6
zp|J(IK}UW}l3CAH*BQth)X5xbsnTq$vd^i?F%y)-DJG*3PuRr{GB7lgCQ=QCCTM+!
zMq+fRDCk9VA1zBo2`~kNB2{YUA4#!v90>J)QhbvD+b}j#?az}V<tPY<B^{OGWQwpv
z$ZTbZHYpBnYZ6n<)K?0XHpGgz&CpFk(3y>hPoja{%PyIk1g)h+ZA|_qBjFz@^SSKg
zdE+N^sO~tvQ>TK?RUHZoJ6Bf~b?#i<zH_Gzh3%`xb?HzwuU=*k*5Y6h_!^{$xD<#K
z#mSK8$nkCmAdb8Si6S!@B3sv6jj6;8a!;lbA}9qi0);*O8y(5%-x{4}>8aMXCsN=B
z;@n8_L|drFr80yWVqggRiOK*h4w!2X)Om3#1<q>&CI*tSio=5$&;g%Pagg;-XFxWK
z^x!@35G~Av&h}b~m890}5anmV2)n3Z0`$c99U@aUoR=bstoYd*e2VQ2TUTYhO!<yI
z4_i4mH`jdIV2k<fVAMdT{H<Dcl)vO}lc>}=f16At)+zF1s{EKHKc>^iN|Q)R22-JP
z?0+GNp2p3jM?)HSp8nL+I3d%xWQlpJG>#gLx{}zP10|t$$Mwn^#myX;g<er|0`}R;
zitDGtL=l$<!59^#!HsUgv!vyZJ;`LEH7ZJGAN|DPJm`oWRXyM5WWDxLYD&tB5|(@@
z6O|cshWYxQOcwTO5y}*!U6f2Q2wn`XgZ`qa0OGNZv9?L98LU2)if9rY+aA{9N`rWX
zUChJzfhd(Pyw!mQ(+jM&L!#_pwZAh;Z6OGJ(;z-%7dxSx=m>H66|3!(C}&vhb4Gc%
z6HLcH4C1SHu@lN$ouPup`q2WKuwRrYZCb17M7CBQZ7za=P+$<}DlrY(qvbSwr`-X*
zsC#vw3-p1(too8f8o)>ut;O`NFav4~qH0E|_$$gQcfep+&Z@g5$}&b-!hGH-gDCM~
zS4wwY?gsb4W`kk_V=nnCCNc9Br;FiEc%Ai|ByckW?^E=;iVJrV=zArQ562Bk#~5_q
ztwBS@SKXmKT;WRpkjTF<@`V;;FL9;}yu=$l2%h#6B~av}Gy_CIDP?3A{tAD-C*`%L
zN}&_vu)a+qXDNM5Z=)KAf)OM3-wBn}ixsBQDP_!bvA8Ftk$U40++Y~bTKgoDg^@-(
zkm_KrK|Gs5Mms>{G9(At&;$|J3nC$0<o6=x{<e|5h$C)qqo&6N{V4Z(S>kY}u)U4i
z_1MM5HIM>t7{%Jn<Y>Eee{V_}KQ>B5a37dp7q99=mCrkg&-a1ZQcSa@Z~tcL*8iS7
z-VopSg%7C{Z0SvXUCrSk(Q-|sqHg^l-7b;zF-b{GzR~(>>0_Qc!)!4g3FtV|8|+}m
z8P%T>2H$8kbC+}lA7CnBF7w!XyjL3$&AZWI(P}q3G+OOO#n%JiEY?yP?MA0X^I=_O
zwA!l;jh5R{LR~xv%3V>9Gisxbx{*;gDAWYoD}!M-;y#AmtHW+(*bPQl*Gc#PY}4)m
z6A1r)kfSxO3iA23CC084er5`P>J<K93Rl@N+m&H37O-`U^b9B;8V0G_qC$VX$t<oK
zS&)yGd%!Gaj)1FJ9MiJymdB`UzBoqwI1<{}MQU*!W*4arMV070RqUyx0We8P;)`SS
z=JYaKYVD0l9Y&VdikEuJbzEsiJ2ainR0vY_GVpZtGU6F9j8^ikF{&+TG9tGMu^~pb
zWrEFr43vB0es=lQ7MGumQSI3fV`xv;z{l7|Rzq9Bv+TV}624RP0?yhUsTI4bp;kOO
z5d!Ucs{dYRhaGx<?Y}yz?7!mvkq|1T)zDt)Y>XJ)pB5&PDo+zyJaujBR8Mu_+A)?p
zar;=+iSuX~k&c_JQ0I*UsE~SbMJ)H?&auktyjVA0cNCkZK{M0|OO2dAsK0e(4z$kC
z#7AP~60eRI__;TIsRIU@abyiK_G@V6BWt`EtJbjRW92j{4;kPc7mc@!8tR|{PP?dl
zW>?|$a$Bs*1jr<10(I2(@6<si(0P0v6wv%p`XHoe`F{rbbe9CY<lk8caYUdPGR5Ip
z5Chq)o9?2UYS2v+YaWC>cvqa5KA#56KvhHj`QB>k@LX&XVRN7iEDqU<IWU=I+-k~v
znSulmV;>?GH)2)R@y~~7Kl((RxJuu!in%=A!lhL5Ud~*WN#1Ef?XF&o<K5LuTw|w8
zjqOe~{yPsg;J<bD$5f4kf5+(~&sR>QwI24tCl6OiHE98ifOG5&{rS=YxSJ5z8O7;{
zvH;7RoH@D>iXlvdETVKg%0xL~JHH5%O8Y`Y=|V_ZcL{>LrAI;XPg<wM;l=hdj}9ia
z<?m=xD?ov>ey&0PB^+#0v(L@dP=UjhJ{56e=pr>V?{|ormcpH~mKs4lC4m775dBTu
zji@o?QYt&MzN1?jt9Eom@qf+ieLdyvlUTltj>2}C)Lw6=bhKr!H^_E%84Ln!mSO1Z
zJ471YY2u?$7uEZC+@7EuUcM-B+@!|sF%ys5mzP5yAG~A|TZUp8ZQ|9d0-u@GxIJc4
zhoOY44ntjVr`mk}MrWIpjZ9xc3v8#=Fb<RARd{2>e^x^@ORBMhy>R{-=!Y@!GERQ|
zXEJ5EgA|DxOu~wI<;pBKuFO-eP*Q1L4tHR6yz~UB#OmdcXuDVs@qmk|j3%H3@$85-
zUO7?~Z*(Ng#gXNVx{FbFGU|3ly(-`w;5&@^7NaJ<98X&!pW2z@t7pupUtz7F<LnBc
zO-RjAYK84iwnANOJ!QMF0eS)c#LjLs1Yu<Z?7-_>zS&I>o@2T(!ctE`Xq}*%Ga`YT
zbJHd&gZ5Guxh5(f^Ab1^aS19A5ee=Bv73>{Fmfd$4_C;Ewl}vDZ<y^suG5h%j6B>e
z@_t5sj*+)A@@7UBm9Ibs9CQHh*MYY&@Mb4q*Lc2V%h(2Q0iH`xW7c;E48$K3RK{>F
z!S>h=2vsuG<NoC)s2?bT7@5ecIvp<l9a8x!JvdQ@Hqqww0w7>cqRM8nq(Tn1PE=tH
zPIMR6&lr1zjy=qPJv7lq*joT=8Fm`ORx<2Rx3K3Jwo!-OXn@_olvQMLA4BhD=&cOB
z!7cPpo?=ZCl({A-gT(nJ80mT`@}wBN2iD;)iE^GwyO8KKPyOmiXBgphIBGw`xbGhN
zLwvaxN^J}O0TCdM?}cF~55@HtZ_wYY<`59C*yv!2B=RWgqK(q-I3)=Hv%a=`BX<4+
zz796tf|0sv>npOYFC^;cQ`LnNCUh*S8du%LQdHQbx}d7VxbYpUJ5+V4$}h5Xtg<+r
zPfc)~O5LuSJeBGgX*`a)i>RsNsIdKX9Odh!-$r&Y^KsN~IxBe`wPruO;f;fod$y^E
zVJhH#%0DWzg}*8HSGsWATksX2)h-kdy$yYInK=D6omb3ri0*iYl76lxe2-9i`=moO
z;Rr==kXbIhCb8`ZlwhMn7V|GUHlS)MbblB~p7|G~c;Tzu28}0aZaKu2UNws+-iKeL
zNL9LFsC4`TScUkhSxx8Q<!A`_M7;hH^b(23D9^7s1`ojyRS;tyUp=#W+{{T+r?fNX
z3Fp~t_s{4k=O<;>|Gd5FwSu#eV$LzJ1hrh+lD^{NX)w7_^gRKyqs*2m<IQ8o&ajND
z9y7CMMs;n?)Cb0EmJ8Wp<Ovv}oxTu=K1r&hDJO%I)C@vJa;K_G6c4jQLicpwBNl%E
zMP=S>kUReWJhQu9Pnu^Iajy}PxbOV?JDuEhC5Qida#up7&L?+wQi-*v{3w$j<?^E!
zeTdIr19Jys7cEb6oZ9sv1;eRb5lQreH(xL9@OM!u67W{XcGS7$2;-E)Wz@IwQd@<}
zBu+VoC#f~+-Xt}VLcO@Siw<<It;V+N&OmQ*;SAkLt#mCtxCY~}j%w0!J|l@&vC&Ct
zy1h3^O}AuR<s~l0+t|i_1)~8Ql2ivYwe$uNc@8Z2JeMcv{N)`c?oVpjW~k@hRK)j~
z=U6>Ss-I0#TZ}KLNWaItZjk<Nl=3}hM6%+bDu*WPl{qIom87;7WJVn_?)w&E;!BeC
z)}}WSCQx5B9M<<pR$a1NGGB|NNIG2@u@f1g3(nEWD#IPiij_vi;ReMtvFdy1j`NtA
z!kJ?iGqVoKYU{A^2bwT8C5t!YcO#=V=%{JZ{Ccjoj?Eur^M_cm*{HbBpqM5e{Rsx+
zDK@WgPT0jx=C}O}@m@D5AmWF&>CDq3MfrbS$4!?6e&>o;B!LXE=>kMyLW&0cqS4IS
zrWB5r(vC?{@xPKRPbS-nM=nw_+AT%3kCJzB$kjcw9)&HJATechilbcu9;~*^s2wxe
zQhUFlb;h#2O5I+jWH(&l(Z#FfCo)Idszlm()14K4DOcthmFGAqulg0XU;}egSnHYF
zy(vy1x_KF*O$S@Jd0HkKyUZcB)2!RcmZbKv9ZCjtQhws%6}s0sog)0N(zV(du5-#*
z=Y(^et1uF;GdBhKJ9FFX%+3FIy6j6xb;QkQV)Yctmklv9i-OC1Vn_>8*d=`@og-Ps
z$iK6&b!y9wv?P^xq&-?{b#tlJ#i`cMe}DxlrFM~z0v&D_JH;^ZI>eY3wD9zjYlMO2
zq85AeTI}UXmU9?zmVxCaon>Q7tp=A`>z!)B4R{8cnWX~VXBRuMti1^)Je?|5(>I)H
z0YB9OULYx*;M&Ixly2yhJjCE@dbqE<)cW12)_A}j@;3JxT@EPFm^3wTj;A_NI)#{y
zC27Lj6VsuG101`h@tEr%`E=o`ozhwwax`6L>le2=AFMQ18SYf&q!<1vFK#6ng*eA9
zc94-fYdL4@JL^}I_^$L8t3y{&;ft$WUl;n7H{AYy*b@%0FY?vg*V3r}wrsk4cxk(%
zI)}QH_7cba@JIYOO<gR?i`{E<_~W=(l!B)N&_v&yo>a)dyq3lbrwi6#FSYR>7l;~q
zwxxu+AhfL$g<+CHQHXQlDBGeSEJciMD=C=77s1#IlVx>v!Pzr5mh{ynu%|i4m|@u~
z90|ek*x6CRPmB)5`y|}U;TR>qKM2K<*w3I)8HUA1g;&CG7FrAnBf@d0QQ@6%oPx7h
zVN3)LG0NVJpvsRMD$j_-0d%BL>VxWd&9_R1%%d%b%){CF8qPI#x8+=8S6h{9>}+eJ
zS#2WVyYx3@5bw0*45F#6%piacw0tl^d)XWtW`|q5_9+kbpD5T(H<9*YJt3MU>Z0*A
zyx3N)7jxb4S<HNb)0t0Ty5i%Pu5ur-J{BLqbSfiGsp-rqG+lA>6Ne+26OyYkvvF|K
zNj%2TLv`rE3_XCMZ9kjv8^FnoZPl^wW$Xce!FF|UqwW6^aV}zgy09eU2xt(ck(jCV
znBXUieon?L`c@foVG6E*T~6YQDVQn6D*fKd!O`R<XId&wMtGZ*$9@~)`>dPDJ<sla
zrMq{A-TPd*mtgCafpa|ZI=lC~?%p|e@AKQb_qy#r?Qj-gN`~@bR4!&?c7|GqQ!+$z
zE|%CuQF%B9i<KxKB|{%KL&V}79AbQ1GewL|#x(I%CI*S_`4pXjs!Ft@iqk~`nN_iQ
z%iz9i3%n~z3UH_EoI?X%9tB3X$ALIELmdUqCRT=7=|kI&_Lz&fB184fkEDs&89Y{8
zR6kV_7M~<wly+!tx-cb@3+nd*jTy3kCfIs(LSJuuJwtWS<_zwj+cQ)LZ4{P7%t69d
zozn&TTQA!^-7wS(&u7SUY?GiL`IO;L9AhfG)&mEVOoe}9DLs2+s_>KOhf<tx7d?C@
zCSkZkbmC6Tw~JDH(vBciiQ>-NTgEHbc}mkQJl7MuU?-&;;Lt4>hl{aXj48uFJEqd>
z?J#$#4D;-wZsk~xBU~VQh(RUTL;P9Z0+G^-Og-R$_**Zm)*)=6cVQ;r0*7pJZ`>ti
z)E7iZNA!`gl)sz`bBX0;9tqE7@*J`?Q_dlD)s)l;6KxOo#Ww*DQW?!5`!l(Twq>d&
zqO0*cTAC=-1(vQb@5c)KUWfgLVb3X8kw1XOuveBsg)Bz>kx|dNMWq)WC2Bzylg%Xv
z`prOg7EgFR2hmT@`ZDZYI&6n5MK)U;?RRUkF=F0e+>X<;RFCOC1n<B(S*piO&l0<a
z&>$s|8dM41Ej`}V<y0ousFT~s<TmK!<jEuMV{&_Sa$A|)2DjvL#0&S(a&RU~4Y~Gi
z2oy1aKXn3sFoCOCw%x<fpDstURlp;%Ip8<h_*J*YdopCtYz}x2f}q|}EW!q$S$sGQ
z(?$1@*h>`Ohq>};AXc)G;kuFXY#Dwm&Q`l<eK@-YZh&~Y5+}OOMjy)AC{eT@g}w2~
zY&9D_p6xUn4Yf6o!tcDWAzQWE;VK$X&t|K3YasjdHnd$dbQ~7oUL}fdAP|+HpyLFH
z+LS7MFb;d*5l8)=<1xivfAM(ifF~WIZ^q+ByQr}m`{NG|QPKpQVHfS1K%@GGLzF%d
z6YQd~6Y*}k7rj_TyvX#|6LGB+sXlhEY~si1GEe@_(Z%IaB56MMqpL`Dzf#yv_5Xr)
z-2cx{q9H$s%IFHb|GMGS-@CL^;V)>X!cUm$5W@wthTC|)4*C#-KBz#=wuKMiV!(Bb
zswvckjQXHk)Y-OHQ*jgEfp)5KUY$<U(?8ka1MNi0bbQE3^oc_hHG^WU*OC#0Zylmj
zGceIEQh?VSqS{&<AVn&I^W8*nsqz+*1-;uCDOV<X*>CkEEJRZdM=`q&>F`mC%b-Y#
z_(g)$92H7aj=NAkDZ(E_i)&9F>P<b_ES`N3@50GBvL}aGbDVl|y|>EtT}n5Iy4m;w
zKAfXQ{$}ZvHHW)}i{^9e)Rq>fHnCGr>rOrX5blE4*eP3!Q_rwdPqR}5uKI@y_)DVK
zJPPiYOk<B58m}>p8!a@hF^%7J8aL)s_R=O-%|ns7JP&!~s=)r{mcyH(<3j9*CAlgT
zN8E6DUvUuYXW|;MfJUkCo`p8Ng=?RP`Xy*_-DTAa@1^*cyN4cP+ET2+UAby1+L`Or
zfS=o9AEtc-HZ#F5B*C4zyx_X1p7XX{S%$qm@mQ`J8N*jle)w6gnzpD&o&xKV?^j?N
z{%Dtovd3_?UG&Lgl)Bt>h}u0)n<}cMdjEF@<Do9bFRJKZ+dQ5?Qu5RUV$S2P|Hn!^
zj@_w@R{L&w+&me1vU%tfJ!}d6u5G8dI2X&qTu`rh+fF};^b4Q~d8&Opd|KRhW#A*W
zG|&>hRA;b=8O+xioLh~*VgoZ+uQOQ24CWgdxT1#I&TBXu@J%KV<%U2U6F8$2_?!ux
z)Cn9}hokX#CU8Y3aFz+2G!k$PL8_0qYaY@oS|aQ*RPUDfX1XDfr%2F3dh`jNg|KVB
zYKqSJ+!S)8(0Lw-%kb`eZi?>tYNT||ms6156t00N63I{FC7@st4Sr$84Gmh}sWE^O
z5IYUQH0pI4as)vW(|B2@(ZDq7-O=bL(l^sY=<=JU&*emzAZ(jyRzD{h^6&o7<~xn0
zA-0l6ashs63FT1f!`XZuPcG^seAL|OQd%v%pTSYC_lHBojAzh7lfAZhmC1JT8Ctrr
zqQKVU@A$mu!oKwSv-(vSzm_atEaqztd0A1nGQ75~s+N94P$w^s#!RtHuCA58;9Ggy
z-?-JQpQ)`h-{!^hoT_?dc%}JvH#qe~ORRey58<U&;=Y}9Hg?@tEZ#}0i#0&}w3F7z
z4S^!$1v;4du9X<}0#+oL3+OF^$eA_OIeh&!bw<wQspIP&AQ!AZCW=EZV0_#;x=mdf
zRQ155Y3-%3`T>&J=um29!FVy!7YjVC+jB*`7m?mi&JYzZV!7{f%A{7tPY^pRG2YWU
zF-O>5L^C$#iWBnti+piSen%IG_+8j*;U)TU=L+j}`Zpd{SgrIs^cB_(^c&|D*6&og
zWVnL3$WO^+g|fYZY|7_4+JddHN_#8Fj{Iy?<zG<GSz(Qqb?a(EsWq&t>A9xRx`w{2
z@`o~3O+Nh>JQjLb>*eDiq>r`o=}}MmSSO$4zjk32@=5+v4c4dRll+ysb-jF&KL)mL
zkWaEZTc4Is@})~_gM5-NU065DCwVty-6WsnNt<=Ee3C~y)<*f1B{xXcE%H(3U)HVi
aNv^ckXXKNdQLWF)r?dICr(eQ*;Qs-%$$Lux

diff --git a/build/html/_sources/notebooks/DemoNotebook_ammico.ipynb.txt b/build/html/_sources/notebooks/DemoNotebook_ammico.ipynb.txt
index 292a93d..f6a53da 100644
--- a/build/html/_sources/notebooks/DemoNotebook_ammico.ipynb.txt
+++ b/build/html/_sources/notebooks/DemoNotebook_ammico.ipynb.txt
@@ -166,7 +166,7 @@
    "source": [
     "image_dict = ammico.find_files(\n",
     "    # path=\"/content/drive/MyDrive/misinformation-data/\",\n",
-    "    path=data_path.as_posix(),\n",
+    "    path=str(data_path),\n",
     "    limit=15,\n",
     ")"
    ]
@@ -177,7 +177,30 @@
    "source": [
     "## Step 2: Inspect the input files using the graphical user interface\n",
     "A Dash user interface is to select the most suitable options for the analysis, before running a complete analysis on the whole data set. The options for each detector module are explained below in the corresponding sections; for example, different models can be selected that will provide slightly different results. This way, the user can interactively explore which settings provide the most accurate results. In the interface, the nested `image_dict` is passed through the `AnalysisExplorer` class. The interface is run on a specific port which is passed using the `port` keyword; if a port is already in use, it will return an error message, in which case the user should select a different port number. \n",
-    "The interface opens a dash app inside the Jupyter Notebook and allows selection of the input file in the top left dropdown menu, as well as selection of the detector type in the top right, with options for each detector type as explained below. The output of the detector is shown directly on the right next to the image. This way, the user can directly inspect how updating the options for each detector changes the computed results, and find the best settings for a production run."
+    "The interface opens a dash app inside the Jupyter Notebook and allows selection of the input file in the top left dropdown menu, as well as selection of the detector type in the top right, with options for each detector type as explained below. The output of the detector is shown directly on the right next to the image. This way, the user can directly inspect how updating the options for each detector changes the computed results, and find the best settings for a production run.\n",
+    "\n",
+    "### Ethical disclosure statement\n",
+    "\n",
+    "If you want to run an analysis using the EmotionDetector detector type, you have first have to respond to an ethical disclosure statement. This disclosure statement ensures that you only use the full capabilities of the EmotionDetector after you have been made aware of its shortcomings.\n",
+    "\n",
+    "For this, answer \"yes\" or \"no\" to the below prompt. This will set an environment variable with the name given as in `accept_disclosure`. To re-run the disclosure prompt, unset the variable by uncommenting the line `os.environ.pop(accept_disclosure, None)`. To permanently set this envorinment variable, add it to your shell via your `.profile` or `.bashr` file.\n",
+    "\n",
+    "If the disclosure statement is accepted, the EmotionDetector will perform age, gender and race/ethnicity classification dependend on the provided thresholds. If the disclosure is rejected, only the presence of faces and emotion (if not wearing a mask) is detected."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# respond to the disclosure statement\n",
+    "# this will set an environment variable for you\n",
+    "# if you do not want to re-accept the disclosure every time, you can set this environment variable in your shell\n",
+    "# to re-set the environment variable, uncomment the below line\n",
+    "accept_disclosure = \"DISCLOSURE_AMMICO\"\n",
+    "# os.environ.pop(accept_disclosure, None)\n",
+    "_ = ammico.ethical_disclosure(accept_disclosure=accept_disclosure)"
    ]
   },
   {
@@ -822,7 +845,7 @@
    "metadata": {},
    "source": [
     "## Detection of faces and facial expression analysis\n",
-    "Faces and facial expressions are detected and analyzed using the `EmotionDetector` class from the `faces` module. Initially, it is detected if faces are present on the image using RetinaFace, followed by analysis if face masks are worn (Face-Mask-Detection). The detection of age, gender, race, and emotions is carried out with deepface.\n",
+    "Faces and facial expressions are detected and analyzed using the `EmotionDetector` class from the `faces` module. Initially, it is detected if faces are present on the image using RetinaFace, followed by analysis if face masks are worn (Face-Mask-Detection). The detection of age, gender, race, and emotions is carried out with deepface, but only if the disclosure statement has been accepted (see above).\n",
     "\n",
     "<img src=\"../_static/emotion_detector.png\" width=\"800\" />\n",
     "\n",
@@ -832,10 +855,11 @@
     "\n",
     "From the seven facial expressions, an overall dominating emotion category is identified: negative, positive, or neutral emotion. These are defined with the facial expressions angry, disgust, fear and sad for the negative category, happy for the positive category, and surprise and neutral for the neutral category.\n",
     "\n",
-    "A similar threshold as for the emotion recognition is set for the race detection, `race_threshold`, with the default set to 50% so that a confidence for the race above 0.5 only will return a value in the analysis. \n",
+    "A similar threshold as for the emotion recognition is set for the race/ethnicity, gender and age detection, `race_threshold`, `gender_threshold`, `age_threshold`, with the default set to 50% so that a confidence for the race above 0.5 only will return a value in the analysis. \n",
     "\n",
-    "Summarizing, the face detection is carried out using the following method call and keywords, where `emotion_threshold` and \n",
-    "`race_threshold` are optional:"
+    "You may also pass the name of the environment variable that determines if you accept or reject the ethical disclosure statement. By default, the variable is named `DISCLOSURE_AMMICO`.\n",
+    "\n",
+    "Summarizing, the face detection is carried out using the following method call and keywords, where `emotion_threshold`, `race_threshold`, `gender_threshold`, `age_threshold` are optional:"
    ]
   },
   {
@@ -845,7 +869,9 @@
    "outputs": [],
    "source": [
     "for key in image_dict.keys():\n",
-    "    image_dict[key] = ammico.EmotionDetector(image_dict[key], emotion_threshold=50, race_threshold=50).analyse_image()"
+    "    image_dict[key] = ammico.EmotionDetector(image_dict[key], emotion_threshold=50, race_threshold=50,\n",
+    "                                             gender_threshold=50, age_threshold=50, \n",
+    "                                             accept_disclosure=\"DISCLOSURE_AMMICO\").analyse_image()"
    ]
   },
   {
diff --git a/build/html/ammico.html b/build/html/ammico.html
index af6f9aa..a9d88fa 100644
--- a/build/html/ammico.html
+++ b/build/html/ammico.html
@@ -153,6 +153,7 @@
 </ul>
 </li>
 <li class="toctree-l3"><a class="reference internal" href="#faces.deepface_symlink_processor"><code class="docutils literal notranslate"><span class="pre">deepface_symlink_processor()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="#faces.ethical_disclosure"><code class="docutils literal notranslate"><span class="pre">ethical_disclosure()</span></code></a></li>
 </ul>
 </li>
 <li class="toctree-l2"><a class="reference internal" href="#module-colors">color_analysis module</a><ul>
@@ -1187,7 +1188,7 @@
 <span id="faces-module"></span><h1>faces module<a class="headerlink" href="#module-faces" title="Link to this heading"></a></h1>
 <dl class="py class">
 <dt class="sig sig-object py" id="faces.EmotionDetector">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">faces.</span></span><span class="sig-name descname"><span class="pre">EmotionDetector</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">subdict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">emotion_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">race_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50.0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#faces.EmotionDetector" title="Link to this definition"></a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">faces.</span></span><span class="sig-name descname"><span class="pre">EmotionDetector</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">subdict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">emotion_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">race_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gender_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">age_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">accept_disclosure</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'DISCLOSURE_AMMICO'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#faces.EmotionDetector" title="Link to this definition"></a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">AnalysisMethod</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="faces.EmotionDetector.analyse_image">
@@ -1271,6 +1272,17 @@
 <span class="sig-prename descclassname"><span class="pre">faces.</span></span><span class="sig-name descname"><span class="pre">deepface_symlink_processor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#faces.deepface_symlink_processor" title="Link to this definition"></a></dt>
 <dd></dd></dl>
 
+<dl class="py function">
+<dt class="sig sig-object py" id="faces.ethical_disclosure">
+<span class="sig-prename descclassname"><span class="pre">faces.</span></span><span class="sig-name descname"><span class="pre">ethical_disclosure</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">accept_disclosure</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'DISCLOSURE_AMMICO'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#faces.ethical_disclosure" title="Link to this definition"></a></dt>
+<dd><p>Asks the user to accept the ethical disclosure.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>accept_disclosure</strong> (<em>str</em>) – The name of the disclosure variable (default: “DISCLOSURE_AMMICO”).</p>
+</dd>
+</dl>
+</dd></dl>
+
 </section>
 <section id="module-colors">
 <span id="color-analysis-module"></span><h1>color_analysis module<a class="headerlink" href="#module-colors" title="Link to this heading"></a></h1>
diff --git a/build/html/genindex.html b/build/html/genindex.html
index 0fd54ad..fbd88b2 100644
--- a/build/html/genindex.html
+++ b/build/html/genindex.html
@@ -218,6 +218,8 @@
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="ammico.html#faces.EmotionDetector">EmotionDetector (class in faces)</a>
+</li>
+      <li><a href="ammico.html#faces.ethical_disclosure">ethical_disclosure() (in module faces)</a>
 </li>
       <li><a href="ammico.html#multimodal_search.MultimodalSearch.extract_image_features_basic">extract_image_features_basic() (multimodal_search.MultimodalSearch method)</a>
 </li>
diff --git a/build/html/modules.html b/build/html/modules.html
index 5b35c7a..30d56ba 100644
--- a/build/html/modules.html
+++ b/build/html/modules.html
@@ -194,6 +194,7 @@
 </ul>
 </li>
 <li class="toctree-l2"><a class="reference internal" href="ammico.html#faces.deepface_symlink_processor"><code class="docutils literal notranslate"><span class="pre">deepface_symlink_processor()</span></code></a></li>
+<li class="toctree-l2"><a class="reference internal" href="ammico.html#faces.ethical_disclosure"><code class="docutils literal notranslate"><span class="pre">ethical_disclosure()</span></code></a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="ammico.html#module-colors">color_analysis module</a><ul>
diff --git a/build/html/notebooks/DemoNotebook_ammico.html b/build/html/notebooks/DemoNotebook_ammico.html
index 5bd14b0..2b55316 100644
--- a/build/html/notebooks/DemoNotebook_ammico.html
+++ b/build/html/notebooks/DemoNotebook_ammico.html
@@ -60,7 +60,10 @@
 </li>
 <li class="toctree-l1"><a class="reference internal" href="#Step-0:-Create-and-set-a-Google-Cloud-Vision-Key">Step 0: Create and set a Google Cloud Vision Key</a></li>
 <li class="toctree-l1"><a class="reference internal" href="#Step-1:-Read-your-data-into-AMMICO">Step 1: Read your data into AMMICO</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="#Step-2:-Inspect-the-input-files-using-the-graphical-user-interface">Step 2: Inspect the input files using the graphical user interface</a></li>
+<li class="toctree-l2"><a class="reference internal" href="#Step-2:-Inspect-the-input-files-using-the-graphical-user-interface">Step 2: Inspect the input files using the graphical user interface</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="#Ethical-disclosure-statement">Ethical disclosure statement</a></li>
+</ul>
+</li>
 <li class="toctree-l2"><a class="reference internal" href="#Step-3:-Analyze-all-images">Step 3: Analyze all images</a></li>
 <li class="toctree-l2"><a class="reference internal" href="#Step-4:-Convert-analysis-output-to-pandas-dataframe-and-write-csv">Step 4: Convert analysis output to pandas dataframe and write csv</a></li>
 <li class="toctree-l2"><a class="reference internal" href="#Read-in-a-csv-file-containing-text-and-translating/analysing-the-text">Read in a csv file containing text and translating/analysing the text</a></li>
@@ -257,7 +260,7 @@ tf.ones([2, 2])
 </div>
 <div class="input_area highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">image_dict</span> <span class="o">=</span> <span class="n">ammico</span><span class="o">.</span><span class="n">find_files</span><span class="p">(</span>
     <span class="c1"># path=&quot;/content/drive/MyDrive/misinformation-data/&quot;,</span>
-    <span class="n">path</span><span class="o">=</span><span class="n">data_path</span><span class="o">.</span><span class="n">as_posix</span><span class="p">(),</span>
+    <span class="n">path</span><span class="o">=</span><span class="nb">str</span><span class="p">(</span><span class="n">data_path</span><span class="p">),</span>
     <span class="n">limit</span><span class="o">=</span><span class="mi">15</span><span class="p">,</span>
 <span class="p">)</span>
 </pre></div>
@@ -268,6 +271,25 @@ tf.ones([2, 2])
 <p>A Dash user interface is to select the most suitable options for the analysis, before running a complete analysis on the whole data set. The options for each detector module are explained below in the corresponding sections; for example, different models can be selected that will provide slightly different results. This way, the user can interactively explore which settings provide the most accurate results. In the interface, the nested <code class="docutils literal notranslate"><span class="pre">image_dict</span></code> is passed through the <code class="docutils literal notranslate"><span class="pre">AnalysisExplorer</span></code>
 class. The interface is run on a specific port which is passed using the <code class="docutils literal notranslate"><span class="pre">port</span></code> keyword; if a port is already in use, it will return an error message, in which case the user should select a different port number. The interface opens a dash app inside the Jupyter Notebook and allows selection of the input file in the top left dropdown menu, as well as selection of the detector type in the top right, with options for each detector type as explained below. The output of the detector is shown
 directly on the right next to the image. This way, the user can directly inspect how updating the options for each detector changes the computed results, and find the best settings for a production run.</p>
+<section id="Ethical-disclosure-statement">
+<h3>Ethical disclosure statement<a class="headerlink" href="#Ethical-disclosure-statement" title="Link to this heading"></a></h3>
+<p>If you want to run an analysis using the EmotionDetector detector type, you have first have to respond to an ethical disclosure statement. This disclosure statement ensures that you only use the full capabilities of the EmotionDetector after you have been made aware of its shortcomings.</p>
+<p>For this, answer “yes” or “no” to the below prompt. This will set an environment variable with the name given as in <code class="docutils literal notranslate"><span class="pre">accept_disclosure</span></code>. To re-run the disclosure prompt, unset the variable by uncommenting the line <code class="docutils literal notranslate"><span class="pre">os.environ.pop(accept_disclosure,</span> <span class="pre">None)</span></code>. To permanently set this envorinment variable, add it to your shell via your <code class="docutils literal notranslate"><span class="pre">.profile</span></code> or <code class="docutils literal notranslate"><span class="pre">.bashr</span></code> file.</p>
+<p>If the disclosure statement is accepted, the EmotionDetector will perform age, gender and race/ethnicity classification dependend on the provided thresholds. If the disclosure is rejected, only the presence of faces and emotion (if not wearing a mask) is detected.</p>
+<div class="nbinput nblast docutils container">
+<div class="prompt highlight-none notranslate"><div class="highlight"><pre><span></span>[ ]:
+</pre></div>
+</div>
+<div class="input_area highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># respond to the disclosure statement</span>
+<span class="c1"># this will set an environment variable for you</span>
+<span class="c1"># if you do not want to re-accept the disclosure every time, you can set this environment variable in your shell</span>
+<span class="c1"># to re-set the environment variable, uncomment the below line</span>
+<span class="n">accept_disclosure</span> <span class="o">=</span> <span class="s2">&quot;DISCLOSURE_AMMICO&quot;</span>
+<span class="c1"># os.environ.pop(accept_disclosure, None)</span>
+<span class="n">_</span> <span class="o">=</span> <span class="n">ammico</span><span class="o">.</span><span class="n">ethical_disclosure</span><span class="p">(</span><span class="n">accept_disclosure</span><span class="o">=</span><span class="n">accept_disclosure</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
 <div class="nbinput nblast docutils container">
 <div class="prompt highlight-none notranslate"><div class="highlight"><pre><span></span>[ ]:
 </pre></div>
@@ -278,6 +300,7 @@ directly on the right next to the image. This way, the user can directly inspect
 </div>
 </div>
 </section>
+</section>
 <section id="Step-3:-Analyze-all-images">
 <h2>Step 3: Analyze all images<a class="headerlink" href="#Step-3:-Analyze-all-images" title="Link to this heading"></a></h2>
 <p>The analysis can be run in production on all images in the data set. Depending on the size of the data set and the computing resources available, this can take some time.</p>
@@ -470,7 +493,7 @@ directly on the right next to the image. This way, the user can directly inspect
 <section id="The-detector-modules">
 <h1>The detector modules<a class="headerlink" href="#The-detector-modules" title="Link to this heading"></a></h1>
 <p>The different detector modules with their options are explained in more detail in this section. ## Text detector Text on the images can be extracted using the <code class="docutils literal notranslate"><span class="pre">TextDetector</span></code> class (<code class="docutils literal notranslate"><span class="pre">text</span></code> module). The text is initally extracted using the Google Cloud Vision API and then translated into English with googletrans. The translated text is cleaned of whitespace, linebreaks, and numbers using Python syntax and spaCy.</p>
-<p><img alt="0c75cc0bcb7d4081982b65bb456f1ab4" class="no-scaled-link" src="../_images/text_detector.png" style="width: 800px;" /></p>
+<p><img alt="f1c211721e034ae7ac3eadfd8c20e9c6" class="no-scaled-link" src="../_images/text_detector.png" style="width: 800px;" /></p>
 <p>The user can set if the text should be further summarized, and analyzed for sentiment and named entity recognition, by setting the keyword <code class="docutils literal notranslate"><span class="pre">analyse_text</span></code> to <code class="docutils literal notranslate"><span class="pre">True</span></code> (the default is <code class="docutils literal notranslate"><span class="pre">False</span></code>). If set, the transformers pipeline is used for each of these tasks, with the default models as of 03/2023. Other models can be selected by setting the optional keyword <code class="docutils literal notranslate"><span class="pre">model_names</span></code> to a list of selected models, on for each task:
 <code class="docutils literal notranslate"><span class="pre">model_names=[&quot;sshleifer/distilbart-cnn-12-6&quot;,</span> <span class="pre">&quot;distilbert-base-uncased-finetuned-sst-2-english&quot;,</span> <span class="pre">&quot;dbmdz/bert-large-cased-finetuned-conll03-english&quot;]</span></code> for summary, sentiment, and ner. To be even more specific, revision numbers can also be selected by specifying the optional keyword <code class="docutils literal notranslate"><span class="pre">revision_numbers</span></code> to a list of revision numbers for each model, for example <code class="docutils literal notranslate"><span class="pre">revision_numbers=[&quot;a4f8f3e&quot;,</span> <span class="pre">&quot;af0f99b&quot;,</span> <span class="pre">&quot;f2482bf&quot;]</span></code>.</p>
 <p>Please note that for the Google Cloud Vision API (the TextDetector class) you need to set a key in order to process the images. This key is ideally set as an environment variable using for example</p>
@@ -552,7 +575,7 @@ directly on the right next to the image. This way, the user can directly inspect
 <section id="Image-summary-and-query">
 <h2>Image summary and query<a class="headerlink" href="#Image-summary-and-query" title="Link to this heading"></a></h2>
 <p>The <code class="docutils literal notranslate"><span class="pre">SummaryDetector</span></code> can be used to generate image captions (<code class="docutils literal notranslate"><span class="pre">summary</span></code>) as well as visual question answering (<code class="docutils literal notranslate"><span class="pre">VQA</span></code>).</p>
-<p><img alt="df3e5d6617b3447eb877e276342bc93b" class="no-scaled-link" src="../_images/summary_detector.png" style="width: 800px;" /></p>
+<p><img alt="7b53d91a7e9d46169d6f7b53c3c99fda" class="no-scaled-link" src="../_images/summary_detector.png" style="width: 800px;" /></p>
 <p>This module is based on the <a class="reference external" href="https://github.com/salesforce/LAVIS">LAVIS</a> library. Since the models can be quite large, an initial object is created which will load the necessary models into RAM/VRAM and then use them in the analysis. The user can specify the type of analysis to be performed using the <code class="docutils literal notranslate"><span class="pre">analysis_type</span></code> keyword. Setting it to <code class="docutils literal notranslate"><span class="pre">summary</span></code> will generate a caption (summary), <code class="docutils literal notranslate"><span class="pre">questions</span></code> will prepare answers (VQA) to a list of questions as set by the user,
 <code class="docutils literal notranslate"><span class="pre">summary_and_questions</span></code> will do both. Note that the desired analysis type needs to be set here in the initialization of the detector object, and not when running the analysis for each image; the same holds true for the selected model.</p>
 <p>The implemented models are listed below.</p>
@@ -804,22 +827,25 @@ directly on the right next to the image. This way, the user can directly inspect
 </section>
 <section id="Detection-of-faces-and-facial-expression-analysis">
 <h2>Detection of faces and facial expression analysis<a class="headerlink" href="#Detection-of-faces-and-facial-expression-analysis" title="Link to this heading"></a></h2>
-<p>Faces and facial expressions are detected and analyzed using the <code class="docutils literal notranslate"><span class="pre">EmotionDetector</span></code> class from the <code class="docutils literal notranslate"><span class="pre">faces</span></code> module. Initially, it is detected if faces are present on the image using RetinaFace, followed by analysis if face masks are worn (Face-Mask-Detection). The detection of age, gender, race, and emotions is carried out with deepface.</p>
-<p><img alt="e4ff58bce9a849e1b3cd5e3b9b08a5ba" class="no-scaled-link" src="../_images/emotion_detector.png" style="width: 800px;" /></p>
+<p>Faces and facial expressions are detected and analyzed using the <code class="docutils literal notranslate"><span class="pre">EmotionDetector</span></code> class from the <code class="docutils literal notranslate"><span class="pre">faces</span></code> module. Initially, it is detected if faces are present on the image using RetinaFace, followed by analysis if face masks are worn (Face-Mask-Detection). The detection of age, gender, race, and emotions is carried out with deepface, but only if the disclosure statement has been accepted (see above).</p>
+<p><img alt="01966d367ad4488991e78ad7c9af8c4f" class="no-scaled-link" src="../_images/emotion_detector.png" style="width: 800px;" /></p>
 <p>Depending on the features found on the image, the face detection module returns a different analysis content: If no faces are found on the image, all further steps are skipped and the result <code class="docutils literal notranslate"><span class="pre">&quot;face&quot;:</span> <span class="pre">&quot;No&quot;,</span> <span class="pre">&quot;multiple_faces&quot;:</span> <span class="pre">&quot;No&quot;,</span> <span class="pre">&quot;no_faces&quot;:</span> <span class="pre">0,</span> <span class="pre">&quot;wears_mask&quot;:</span> <span class="pre">[&quot;No&quot;],</span> <span class="pre">&quot;age&quot;:</span> <span class="pre">[None],</span> <span class="pre">&quot;gender&quot;:</span> <span class="pre">[None],</span> <span class="pre">&quot;race&quot;:</span> <span class="pre">[None],</span> <span class="pre">&quot;emotion&quot;:</span> <span class="pre">[None],</span> <span class="pre">&quot;emotion</span> <span class="pre">(category)&quot;:</span> <span class="pre">[None]</span></code> is returned. If one or several faces are found, up to three faces are analyzed if they are partially concealed by a face mask. If
 yes, only age and gender are detected; if no, also race, emotion, and dominant emotion are detected. In case of the latter, the output could look like this: <code class="docutils literal notranslate"><span class="pre">&quot;face&quot;:</span> <span class="pre">&quot;Yes&quot;,</span> <span class="pre">&quot;multiple_faces&quot;:</span> <span class="pre">&quot;Yes&quot;,</span> <span class="pre">&quot;no_faces&quot;:</span> <span class="pre">2,</span> <span class="pre">&quot;wears_mask&quot;:</span> <span class="pre">[&quot;No&quot;,</span> <span class="pre">&quot;No&quot;],</span> <span class="pre">&quot;age&quot;:</span> <span class="pre">[27,</span> <span class="pre">28],</span> <span class="pre">&quot;gender&quot;:</span> <span class="pre">[&quot;Man&quot;,</span> <span class="pre">&quot;Man&quot;],</span> <span class="pre">&quot;race&quot;:</span> <span class="pre">[&quot;asian&quot;,</span> <span class="pre">None],</span> <span class="pre">&quot;emotion&quot;:</span> <span class="pre">[&quot;angry&quot;,</span> <span class="pre">&quot;neutral&quot;],</span> <span class="pre">&quot;emotion</span> <span class="pre">(category)&quot;:</span> <span class="pre">[&quot;Negative&quot;,</span> <span class="pre">&quot;Neutral&quot;]</span></code>, where for the two faces that are detected (given by <code class="docutils literal notranslate"><span class="pre">no_faces</span></code>), some of the values are returned as a list
 with the first item for the first (largest) face and the second item for the second (smaller) face (for example, <code class="docutils literal notranslate"><span class="pre">&quot;emotion&quot;</span></code> returns a list <code class="docutils literal notranslate"><span class="pre">[&quot;angry&quot;,</span> <span class="pre">&quot;neutral&quot;]</span></code> signifying the first face expressing anger, and the second face having a neutral expression).</p>
 <p>The emotion detection reports the seven facial expressions angry, fear, neutral, sad, disgust, happy and surprise. These emotions are assigned based on the returned confidence of the model (between 0 and 1), with a high confidence signifying a high likelihood of the detected emotion being correct. Emotion recognition is not an easy task, even for a human; therefore, we have added a keyword <code class="docutils literal notranslate"><span class="pre">emotion_threshold</span></code> signifying the % value above which an emotion is counted as being detected. The
 default is set to 50%, so that a confidence above 0.5 results in an emotion being assigned. If the confidence is lower, no emotion is assigned.</p>
 <p>From the seven facial expressions, an overall dominating emotion category is identified: negative, positive, or neutral emotion. These are defined with the facial expressions angry, disgust, fear and sad for the negative category, happy for the positive category, and surprise and neutral for the neutral category.</p>
-<p>A similar threshold as for the emotion recognition is set for the race detection, <code class="docutils literal notranslate"><span class="pre">race_threshold</span></code>, with the default set to 50% so that a confidence for the race above 0.5 only will return a value in the analysis.</p>
-<p>Summarizing, the face detection is carried out using the following method call and keywords, where <code class="docutils literal notranslate"><span class="pre">emotion_threshold</span></code> and <code class="docutils literal notranslate"><span class="pre">race_threshold</span></code> are optional:</p>
+<p>A similar threshold as for the emotion recognition is set for the race/ethnicity, gender and age detection, <code class="docutils literal notranslate"><span class="pre">race_threshold</span></code>, <code class="docutils literal notranslate"><span class="pre">gender_threshold</span></code>, <code class="docutils literal notranslate"><span class="pre">age_threshold</span></code>, with the default set to 50% so that a confidence for the race above 0.5 only will return a value in the analysis.</p>
+<p>You may also pass the name of the environment variable that determines if you accept or reject the ethical disclosure statement. By default, the variable is named <code class="docutils literal notranslate"><span class="pre">DISCLOSURE_AMMICO</span></code>.</p>
+<p>Summarizing, the face detection is carried out using the following method call and keywords, where <code class="docutils literal notranslate"><span class="pre">emotion_threshold</span></code>, <code class="docutils literal notranslate"><span class="pre">race_threshold</span></code>, <code class="docutils literal notranslate"><span class="pre">gender_threshold</span></code>, <code class="docutils literal notranslate"><span class="pre">age_threshold</span></code> are optional:</p>
 <div class="nbinput nblast docutils container">
 <div class="prompt highlight-none notranslate"><div class="highlight"><pre><span></span>[ ]:
 </pre></div>
 </div>
 <div class="input_area highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">image_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
-    <span class="n">image_dict</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="o">=</span> <span class="n">ammico</span><span class="o">.</span><span class="n">EmotionDetector</span><span class="p">(</span><span class="n">image_dict</span><span class="p">[</span><span class="n">key</span><span class="p">],</span> <span class="n">emotion_threshold</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span> <span class="n">race_threshold</span><span class="o">=</span><span class="mi">50</span><span class="p">)</span><span class="o">.</span><span class="n">analyse_image</span><span class="p">()</span>
+    <span class="n">image_dict</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="o">=</span> <span class="n">ammico</span><span class="o">.</span><span class="n">EmotionDetector</span><span class="p">(</span><span class="n">image_dict</span><span class="p">[</span><span class="n">key</span><span class="p">],</span> <span class="n">emotion_threshold</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span> <span class="n">race_threshold</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span>
+                                             <span class="n">gender_threshold</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span> <span class="n">age_threshold</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span>
+                                             <span class="n">accept_disclosure</span><span class="o">=</span><span class="s2">&quot;DISCLOSURE_AMMICO&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">analyse_image</span><span class="p">()</span>
 </pre></div>
 </div>
 </div>
diff --git a/build/html/notebooks/DemoNotebook_ammico.ipynb b/build/html/notebooks/DemoNotebook_ammico.ipynb
index 292a93d..f6a53da 100644
--- a/build/html/notebooks/DemoNotebook_ammico.ipynb
+++ b/build/html/notebooks/DemoNotebook_ammico.ipynb
@@ -166,7 +166,7 @@
    "source": [
     "image_dict = ammico.find_files(\n",
     "    # path=\"/content/drive/MyDrive/misinformation-data/\",\n",
-    "    path=data_path.as_posix(),\n",
+    "    path=str(data_path),\n",
     "    limit=15,\n",
     ")"
    ]
@@ -177,7 +177,30 @@
    "source": [
     "## Step 2: Inspect the input files using the graphical user interface\n",
     "A Dash user interface is to select the most suitable options for the analysis, before running a complete analysis on the whole data set. The options for each detector module are explained below in the corresponding sections; for example, different models can be selected that will provide slightly different results. This way, the user can interactively explore which settings provide the most accurate results. In the interface, the nested `image_dict` is passed through the `AnalysisExplorer` class. The interface is run on a specific port which is passed using the `port` keyword; if a port is already in use, it will return an error message, in which case the user should select a different port number. \n",
-    "The interface opens a dash app inside the Jupyter Notebook and allows selection of the input file in the top left dropdown menu, as well as selection of the detector type in the top right, with options for each detector type as explained below. The output of the detector is shown directly on the right next to the image. This way, the user can directly inspect how updating the options for each detector changes the computed results, and find the best settings for a production run."
+    "The interface opens a dash app inside the Jupyter Notebook and allows selection of the input file in the top left dropdown menu, as well as selection of the detector type in the top right, with options for each detector type as explained below. The output of the detector is shown directly on the right next to the image. This way, the user can directly inspect how updating the options for each detector changes the computed results, and find the best settings for a production run.\n",
+    "\n",
+    "### Ethical disclosure statement\n",
+    "\n",
+    "If you want to run an analysis using the EmotionDetector detector type, you have first have to respond to an ethical disclosure statement. This disclosure statement ensures that you only use the full capabilities of the EmotionDetector after you have been made aware of its shortcomings.\n",
+    "\n",
+    "For this, answer \"yes\" or \"no\" to the below prompt. This will set an environment variable with the name given as in `accept_disclosure`. To re-run the disclosure prompt, unset the variable by uncommenting the line `os.environ.pop(accept_disclosure, None)`. To permanently set this envorinment variable, add it to your shell via your `.profile` or `.bashr` file.\n",
+    "\n",
+    "If the disclosure statement is accepted, the EmotionDetector will perform age, gender and race/ethnicity classification dependend on the provided thresholds. If the disclosure is rejected, only the presence of faces and emotion (if not wearing a mask) is detected."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# respond to the disclosure statement\n",
+    "# this will set an environment variable for you\n",
+    "# if you do not want to re-accept the disclosure every time, you can set this environment variable in your shell\n",
+    "# to re-set the environment variable, uncomment the below line\n",
+    "accept_disclosure = \"DISCLOSURE_AMMICO\"\n",
+    "# os.environ.pop(accept_disclosure, None)\n",
+    "_ = ammico.ethical_disclosure(accept_disclosure=accept_disclosure)"
    ]
   },
   {
@@ -822,7 +845,7 @@
    "metadata": {},
    "source": [
     "## Detection of faces and facial expression analysis\n",
-    "Faces and facial expressions are detected and analyzed using the `EmotionDetector` class from the `faces` module. Initially, it is detected if faces are present on the image using RetinaFace, followed by analysis if face masks are worn (Face-Mask-Detection). The detection of age, gender, race, and emotions is carried out with deepface.\n",
+    "Faces and facial expressions are detected and analyzed using the `EmotionDetector` class from the `faces` module. Initially, it is detected if faces are present on the image using RetinaFace, followed by analysis if face masks are worn (Face-Mask-Detection). The detection of age, gender, race, and emotions is carried out with deepface, but only if the disclosure statement has been accepted (see above).\n",
     "\n",
     "<img src=\"../_static/emotion_detector.png\" width=\"800\" />\n",
     "\n",
@@ -832,10 +855,11 @@
     "\n",
     "From the seven facial expressions, an overall dominating emotion category is identified: negative, positive, or neutral emotion. These are defined with the facial expressions angry, disgust, fear and sad for the negative category, happy for the positive category, and surprise and neutral for the neutral category.\n",
     "\n",
-    "A similar threshold as for the emotion recognition is set for the race detection, `race_threshold`, with the default set to 50% so that a confidence for the race above 0.5 only will return a value in the analysis. \n",
+    "A similar threshold as for the emotion recognition is set for the race/ethnicity, gender and age detection, `race_threshold`, `gender_threshold`, `age_threshold`, with the default set to 50% so that a confidence for the race above 0.5 only will return a value in the analysis. \n",
     "\n",
-    "Summarizing, the face detection is carried out using the following method call and keywords, where `emotion_threshold` and \n",
-    "`race_threshold` are optional:"
+    "You may also pass the name of the environment variable that determines if you accept or reject the ethical disclosure statement. By default, the variable is named `DISCLOSURE_AMMICO`.\n",
+    "\n",
+    "Summarizing, the face detection is carried out using the following method call and keywords, where `emotion_threshold`, `race_threshold`, `gender_threshold`, `age_threshold` are optional:"
    ]
   },
   {
@@ -845,7 +869,9 @@
    "outputs": [],
    "source": [
     "for key in image_dict.keys():\n",
-    "    image_dict[key] = ammico.EmotionDetector(image_dict[key], emotion_threshold=50, race_threshold=50).analyse_image()"
+    "    image_dict[key] = ammico.EmotionDetector(image_dict[key], emotion_threshold=50, race_threshold=50,\n",
+    "                                             gender_threshold=50, age_threshold=50, \n",
+    "                                             accept_disclosure=\"DISCLOSURE_AMMICO\").analyse_image()"
    ]
   },
   {
diff --git a/build/html/objects.inv b/build/html/objects.inv
index e5b7eaaed8a041eb759aa62c29d1c8647b9116f7..37ebcdd6ea5cdec249f28376da5aad714f80ac32 100644
GIT binary patch
delta 4142
zcmV+}5Yg|^B84N6h6l2pD!!x`N|B8#e*ld;6cuSvF;u?XW<`8VDSC}amL*ZKIn-Ht
zB@^-Q5q=d3$<00g@s8Fss*8&2MJZtny&0(4<ToTI=?kOVBqL8$Sf%x$h<(+or`=6X
zvKg9;*4t<L!lpH=qAUwm`;|u{yorjeJl1r}Q?^l2<x~{R{+LH~Qsh&HHbO^~f5vuS
z71@@jhAC$>PRO>U?XM_)l~yadpQYS>MlZ#<BIj*J>gYiItv#2LVyK>wPx2>Vn&bgR
zQxaCI`ne@}4Bs=$XzuzZal*=!y!g}`CAzs2O(9|Lzm!l>>1127>1?WFzGbvJNp)+*
zw(1|tn1H)w64l3Qx>@Z>M7<h@e-PZf&k9~vK9Rzx5D+RR^nayW29+R%)&)W{P@<F)
zDB|NTh9a7w52*=BxAaR{QN|!=OVl@*0p=CN%&KQfDh7>+J$op}l$QLrEqlq*B!AwP
zRRQU&aK$yL4&X@yPD8DW(t@dqHKCRr(>j3~1Ud|OMhBm2rYUV6+muf&e~PWnxwYG{
z{#21TBH4DwBg$myd4SR{bw#4O3Hg-pcE<plCDEm@)1<t)5OxIEYeCoWON+b|^a+{@
zscWe5<r+{WsiE_cJ<%^mTD>d<mE|a07CjYo!9^9*3WC*Q=sJ_Y5OR2{T>&yJNZfpy
zt@>U?wFMEHZb`bM`-@uGf2~l<oCa<#YJoQt-pc9at(=lNee?BiWoP^L?YFDgs%g%e
zsmKDXo=8kjiR|<t5>&|!g85?1UjMX!WC@)yADfCOu-Ii0kXX}6uh85p3g3edeih_O
zJT0(W2w1B?C)o;~v*cI01`;DDx>lWLhvEz!1cUU&SjSSdwqD$We<@B>tPZ<Mu+vdf
zQaNS=?3iVw@|ub%(ak6M(`T+?QQ44`cZ6wirVZWtrIbx(D)>ym38-eWunyXa#BzFG
z1<ret=R$xW$oTYvEkfy6o=}YFK%-|_D6{mts=iR&-Sj*$RD3APdK;0Fm#&BvJmK5F
z>{hk_qg5DWB>7tCe^%-@Yl8P#uLfLyGbFuFNnU^RC0z}@Wqonv<<Q;{-we_Qs`(J7
zUx)_;pK|$hI$Un^v0$|t1$|a}wjReM-^Q!DC>`qtMs+@=6;s4`zeL%!Bqr3k&YfI~
ztDJuJh2@|wVkbWvKE1al9MA#jx^iu>{qFvXZ3&9?ggK@wf0`9AzD$#x?x2{SS)jhx
zN}{eNNav2lW{Vo5ISlULpDhH4ob8J$qtz?|KAp5dm0L~uYPa)?9qT0ZTIv>p?W+2t
z#G9ypCi#FWXjJ$5lv49uan5-}`;oHZSjnmJG}W;Nuevh~@p+Z_#W_%v`ZASwCVR>k
z$3*mX?cpfZf3l=7#f(W!AUd`&%Bd$uZ+pJPk%&ojTc}Re_?VR{k~(Gg36R?-DfNTq
zkwWZeZfmkjskaVye_yGcQm00eCv`$nKJ)c1FPM`gc}@AUP;&A#!^PcRT&skN)ri&c
zZAx~~_2Pjb5^Y$v#J<9n+WZwi;-*Kip<EgFv`vXle;cD#9At5%>lSgdX*bHlh_q^x
zxo-1qObRpKs!iq&%}?&a+s#j^P3GFnn>O-&?3?tav!@vJPXqW`@9WsJrmT*S68Ksk
z>rH378MqpsUB{kfu{t=+;9+qfZ%(#Y8lQmhFg8}P=2%RQ4^McQ9IIG!EGBK|E<8-z
zRGkt7e=5xxiDt=-Hs>;|46G+PY#Cnm`e!<VP4|^OWc&z?4vB=58Uc994ahkUCRkZH
zHC+M*9#o#La1SudXJL$~ZZp1P44?Bf9x}d!MrUm1&>BH_OL|Zo9^eTiH&phJ@gOvD
zA}EmE1X8Gi2XFV7&T(jII@^Om?+jBQhn}WOf55~;KhNZ_Z_u!14D6|;1v&h+8ySkp
z`C<F%4U?iqzCGURL~bR!-|V=};YSy0BiH=2Bg(UeE<7nE|FvW3oA)kUU874uO^VfC
zvpVIn(#olyc0@7Pb-@WC+pJj0$aO6jl9ZDFny|EO+b+df!0t19ZjnGXmUDayI9d?r
ze=3IhGkJt?iCdGv3-#A>QXJH}gp&ezq5euvibItb@KN9{Q=jYM@NDNAz6}xQDu(*g
zKUTWLi#|@6_#DRi>D8s&b;P-fq5e!AoL%D86z($hU=I!FcNckPz?-KQ>WRm(;U$iF
zz^{U`s@uDz!QG9%2FU6@-(1$|n^nBNe_7S-?#%baT<=V*hO~YWr~~PjEd*s`MXXB|
zgg7z(TNH*cv@+hTLTQdcFLt^C3X~5et=}P7!dyq2qqM+><+Jk5)RKt5Qm7B3YZ6Nw
z7(oSVgi_b<WGrE?qs>tY^}%)xWQiv>%=xM-c_nV4T);DdyG(tShx`i5Vs|)5e}HT_
z(e}2@GO8_1kaQ^B!IhpRga<%@^1-D0cZU{{?gItNhmy8kQd+{_hB;q#u~*9{2NuZL
zn#*01$Mx6sNn*}d9eC9o^;bXLd-%3nVwQ9tW7g|pp(N};Ve-DDO_$Q<a5mxui3c%W
zTErp6yQpZ#*Xm}I)quj}{Yd*Ae@F4V`{yMUM60_IIGb7z!dEhgqI0j<_r9X1oEN$N
zJ;q>S17)|27opz8$Y4HwU8hJO8%Ou;dr{L<ZVoxe1<s|^UGQt5EOdK(t8_(|HRz=X
z!LCkTab4u;H1a}#`F@UX+pgoIhPps`o^RF*zsnu8LoY>`?W%tJcojDdf3QomS99-D
z{w;Jc+(XCI&igL6ub@A_?vnRBc0GMBF@I*=-SK(Mdiq{s17_k9Y}sAko<2xuyqIoE
zblMnQPY<#<(shft+4OI_hjHm^x&%UaOddt|xODFp(b@2SNOKQ=+W6qgzLqi#-QC*v
zx6$d?v&>fAt2g@l09wj4f3)v3*Y&o5Bi})y_troFgPzt@ro*=Bxq<)^CUq|<2QB>#
zgaA^yvWJX=ko$(j#6t}BEQi(hO@;ugt&Tm*$ExK?hfpFGm>_8{x~|n0$9ogg*)9gd
z=O;oq3^iQ>10IvlDOfp7YE5ODY^zmU^<sp>=IAL6Q=-#`Z@~6=e~iN|;%4KH3e(Se
zOy-)*8y>)LeQAS=HOFAm@^*&9szqxm(_lMRPmMG$jJT|7Z=jfyJuHd0Py($99eb9K
z)$S>kP}`lROTffKJ#ykO+K3JQGQjoTL2)4VB*zH`-0_1c4)C$KG1X$Gdt=4JNGEJa
zGZ+{@$>K0E7B{AvLd*<badBB0N}Cc*HkxN&T<DG5@XuG*5e&Ydb0cNKg8(0oJ#Vs6
zSE6L@K0b6Z;-Q#_oYmDalDjyE;*9D7Jy95wP6`+SkCSH#FdOKR$)ezYrfF0_eFyxz
z$H#~Je|*JITtr7cbd$0QR4eGC@&?*hst}Y6R#|pXn}W?&Uet6~6wmBBhPhYs*H*=f
zq<qOoYyO?WJCiXBD1Qd|9_;@1!^6i`S^R;TvAvIN(QV>p2#kw8R<C)4Gr6}zi7eD!
zc`x>;$?{_<XJx$H0aaWe7tut%kAS=P5wQ7b1`qP@f-STf+#PwTorg22fjSM;z1iU7
zs(Nt%cP|cL29b&CkL!4N^?nLWWun0|2`bZ%E1%0B`9v1Kz<)Rt%Tr#MpJPsD)SnNN
zXl*Xyxy`kHmFr3OSk(tw;bx9+j)y)>Z9pmmwac6#k@8ARP<yW#VADka4|)#*r#ozi
z)m43wj=FTz+|TzXr`AqH+c4Zr^(Lp|JoHZ$iI$|UoBEL}i>k&@_ITKXZD#PZLdh%y
zS!y)gbch>omVZ@oq5@mhZsS2;KbAHql_hAZ3e=wJ^<v3~Q!s&-LsWUYi2vDK!Nz>S
z7t7P`ILX0$3U!@AtSr)aysYWt%0hdMz8nm<`l!8Y&h?SHwvfQsQRyS8?^h^%SA!cT
zIASNvC$l&zV8jSBHlWIv@#OGUt?WVKwF>(@`(Sz##DAk`eq6;WN8yeW#CL2s3hGeg
z6C`3BZbA{YNUl=)6ca!AKB|v=EUxV?dHDXx4#l%ZRhy6J#io-N%bJ$>^(~e&H&KL)
z)|PpgHsAB%t_<9d4SXjJh$$MDQ#AZN7~l%%^(~SL;&Xrke6jBgbGq;8OMstmZn3Dm
zqEF>37=KWq+Ue0e&j9jA1Ed-W3t!&c%4#S2YA%Afh#D*hu)nzlY*s>p74<pE%VRAX
z0>j6)mOoXbl;fNugI-yzZs<>&`FaN?ALg4B-rw9J1tHpxfIw<VtZh{-1mX~=g$O8}
zx3^er<6@Gg*mT{?*K2^f)1ibnZ*P&xLXd@;TYp^MEWf_xQR_sjx;HsE*1TA2-n-^8
zVYppe6RqW3CD3kWg$-r#ezry7^ViT8B|>l3A`p0_kqD?;BjgQMAovF%UW*nFL_eEA
zAaUjZ6e=PFshYA{ln$feUDi)J1SCNu<4H&*_1VxbBrDVYgRYay2JfZ#A8uZE3S!yd
z9)JEs!<WyTM#P(>SR|;@3pIOnuOS$S@Bo}y)|2{q{q+xw?jF!1f6iCbu1ARdIiGLI
z1qP^`HJ`&Z+f3+lQKVx-S7Z+{1)nK~xoAl$7&BGL)1k&RKP6R>^NAkMjY!U;Y|R_K
zKJJ~SyONE!8+6Bk(3zqJ2nit61LC;=gntx}VI-~>fwV&sES^RdZ9N;5r5I9imTjo0
zp)6fq&xKv_>&m5@!?6hg+QO*D+N2?tX09O(wP^-RSqaQ`Nt)Cz@S%%cN;8I8k)E`h
z(gvfG%J=<j)MO)-ZJ;7cwHfGp_^c^3#oHz6W_T;-ojqU0(w|_|t!VQ1Dn%@I$z1oi
zM>f=RnJ_$yiYLDF<MhR(p<c#By)@0zp8VoK<`N(7{;6vkp8(U<8?g`VJ6&U-q=GJ?
zjR4|q>^?2d_)ym+!{_t4pIB5+t!z1de@C~z2>Z<jec%9p?!uFk4<vuY9GJ_JY)2fB
zJ;BHJR}GFqmC56-FkWE5FkWubpe;%_8}v!!bj7H$G_zvf>fL_F(&CisM9V!gcb_F?
zeqyE$<9r}BK8SM^3@3Y>;22sQPdZUK&d>Q&F5<^HWv_-=oupzSV4PKH*4MD`GhiTv
zfs#FXK!EWTPdZW5U?6{q0i6x+G#`*a;j<0ZY5sNEc^E2-36NZQsd*OR3&=d0@~upL
zvK-?04D^B1Fbo%SD>+f&`iSrqY#!M87O6gQ_H$R%H$exw>=B#x;MNRB{cue#%2Q-K
zgYRn${rlW#8k|e=xH!8acO&(){Q2sdpHw=Q+Xx0={NNr*nKpl9HHfUab#G*FiJg0k
zAOBYy_q~V`7tz%Js$)2Z&{w<gfeX+O3&+C}Zc-ad@awBiOfj1}gYe&f|3}-O@9&`Z
zaqK(uP(lWB<qK{yr1+zpz)70@DY-J>v;96fMec(w-U-(xr)c<IxMn9{>f9?DN11(m
ssSm(vP;|W@(`O#C=1kYLGo~Jy5YTGJ>m%>s^=95@b=hF{KLs7pO+Y{+N&o-=

delta 4068
zcmV<A4;%1>Bhey|h6j?JD!!x`%8`vLf8f@*DJs&UVyJw%&5HP#QuG>;EK8zdbEvcQ
zN+#mpBm627lAC+}<2|iuR2LQ3i&DZEdNWY7$!|zb(icXzNk*QiuuAJg5&NoFPrI9(
zWHU4wt+&tgg-vT#MOhZC_A8G@coP*_d93M{r);C5%Bd)r{V|W~q{ycXZG?^}e~s<F
zDzYt44O7l&oRDox+h0-qDy>#@KTEm&j9!XyMb6ud)X{<ZTYD}g#ZWyVpX5)#G|2;s
zrX;LZ^>a(|7`|tg(cJY-;)IncdGV<?N_2B4nnJ?9{Zc|jrIT&Rrn9Mz`Igb@B-O1I
z+p2#oV*>7$NmL)J>1MSj5%p>qe?oBcZC3EI^64pz3ISckg#NE|%b*gZ(7Hfq21=At
z0!4h>#ZW{u^dU7N>6U&eE6Nz;Y>D~?Gr+t$F|+EKl8QkiV$UARF{LH{ZOdM=G|8X0
zWmP~rD_s3rc1-I8sseb-z+iOnsV|z+=CMur)S}obk6XL#pPwocM<m<se|Xn0SqvVa
z^h;flsBZdhN_YcefX$NVQrKxy-dqSf0_?S*Yxt!_UJCjIb)M8URNZn7sFKt$ipU}5
zmm{rSmV(N16fTP)2gcH(ifIMC&SK~~lfck-@aDGyWLl88`7~Sgy^3lJA~fBSbVv6W
zwXj>EmN^aFT+{+@D7=-^f6H4rC3X7d-EU=Q`}XZOtJtb(&YGBF0ai~Wrl&-X-p~_N
z$qqX6#hAVEX#vR+MpZt^6urP=mqmxfn$dQJ=3Y_w9()$7AXnmPf!#ufwF-2St>8IJ
zex++5F><17)oFGp&M-hQNMDR~EJbVU^?MMjM8)c`t8{icYDy}{f3%(*vy4<;F_jYC
ze3CzXf)0zyhNOHTOp7yZ=+-Z#Y%)`w&jg%+YG(cGpsh$Or{`7RyrVT20(63mhZk%S
zO26`iVnhcTJ<CFwrQcQch3f96=ZT^EhoY>v5h;1;ioSv;eDjyx$`)X@3X_Z^Uklwz
z{bo(@KI_$h>#v8TfA=ZL>#x70tD(27FOIw%+PlX$gR~vhe2CL8!~=qdTt0&im)m?S
zSgmG3pOv0%#4*XY{Z(C*j&%d0IuB_@h#2peD7)6SggV!`lZ$GV)6c%JoYY0^<Y&WY
z^wxv}1|VHmF7mbC-CwaSL9w1N$8<%r0_K-#lG7a&(=!XyfA?Av)YSy(+_7qGQDZcR
z$sPQ&g$^QT`=ZKdHH(1HAZ<|PR#U!g?fhcLI!V3Otc75^JpL&0ChDI_KA;L3)xAEY
z)O=r@bKax<NLg{LWN181b*#aw?hHdbt`fgECyG*Ert-mLPx<1Q=zU$AF-o;8DTJ6Y
zsR{IsZ6D>-f0MJfJzwHTL=fE;s#7&SW~J&$owEA`$nBGq`a$!aLTpTKYqCqJw+?rI
zU#Trmr$&+|bwW}e`FfWZ#3V^xQ@$*eoIK5Nakm%ODxqREVs(6*k{t}acp!*G8<s7x
zuW+SyamA0g84+wKSH{h0Q=-$xs1*lU9O=46+-%w%fA26Nt=eR++kD$6g_&>FCUb}8
zC%4n><|oxAb8Y5LJMupEO?uPWQw;js`o7ltI`*t7tK%~PzLv*&)7fqYuEuBAv1eJV
z4o)R_SRBZklP#9UM;Sbfja95U7L(&s5FRGSD%Ko}N!tMm57RbPr^J9tbJ(F-a-+=w
z3o8Tbe~}DZhL^qm;f!F@ePs_BKSHC^9^s@$0G@IKa?TS5R#r|;mw<r>mB%F96AbgA
z7GtX0jPD%7=U|M7j4z?lVVOC!MiAbT9u$WsaRSK=l|5uU2u&RA31l~c6sq9C+dZdq
zoIaY)_F&LEj1<VBr|A+H@KB+?oQ~R!4#i}=f7X5qLy*$Qx93Kk$gO1en;o|~Rp>%(
z<eHy$M0tqMg(s!tzjiErGu?%&Yji27NwL~%R*PI#S~>O8jwoVJ7n~5XMX5?gt~0ri
zq?G*Egr#kxb}7yRcAuehiv+T<oU2>F(SkTvG1Q;QBYjKUngm{`zm}8Y;M66Y6u=Ah
ze^+u+9CEyXj{<j@`dkl(XD!$8ZHPEmG1Q;_G0!Dl^l`$(=P=e!lP=}1BhFO}^=IlJ
z>k_Y~aF?kEduTXMyT~&G-aNHXPdtwCE^*8Qeif8e-QF$j+}-GFfUNHG&1IdwS;gy{
zRo(8+U|-Dj&ctd+>lcAKAb#0GP)1h7f4Wpbh!gC;MPUd-E91>7l;&9SVy7FRK>1M8
z`kDSE%yqOmN(+2g9+hvVmPGuOLVXxrTUg@22r5`3l)8RLVhMX4ZH`i?54LL=OFXe*
z&R1Q@D{(920-g!nW$Lp$<X1`-yTd^OWW$NJw_lb~ZDE3>L+K8#*eoGD01A{3e<t0(
z%d?1dA1F{hl(g;A&=USO%=xN|y;>d|SRiL>E_X>DpI_G}i8)_&;8k<<Uj20MsoQRC
zS<-!sS+8$}lCT4X$@`KvT@sta*@zP)9>jQQ5r-7-qM{vNbDK?80}7M(BkgxQ#P2Si
zmsAj~?uOoMYCQ;F$smf(y<*?{e}kTKUgY}s3WJFal-)93gnAbhgZcDzog#s39K*No
z#Ys=OIpiD{Dwk4s!LNa`(CzUp&lO$PpqC;9yE=L0bdjgi$O{4H`#HY-x{i+;>H_6?
zzF9BeE_culy%b@#tNLx=RopbdF411iy-WGG(7|vI9ig4~-D+P!e}3Jif9rYddiq{s
z{>-|&-1C_A^u5Fe%*3VCvb#<_eUQ+2QQVa1v@yCa9%ON(>lSgd>EAvN<I>l3354*N
zJR0tC3EnNDv*G`c=3e}?@xc{(EoB<IyG8GBqtmfxnXS54Z}j{6TFNxEZ<y=4>+i^S
zkm%k04`9&Kn#y$8Ha#B@e?Y>d?j_}*rN2oKKuTBkkZ}-l-&mM<7{Q+9u-d+n5MZ^{
zv1j>MwLGy9O2h&aB<)4lwc6r%|6w}Y#bEdxL<onWrb}SJWAb?eD~Cy~sZ5h?wQ8$g
zaB$chJ#Ar1blULkust5faErLvxO;`^XEr8tP38>`Qn<dfLB*P5e=uoz%feyRqBWIi
zupO(XKbjXmTvoL=NzBO}mc-j6f!2hMJ<G>x_q0i<?M~ArVB(=39dQ_K#0GyE;Ck<p
zI1qc1;{*fl_yH3K_*mSSYBAHjdE#ND6E>t742+*hahMp38&geYhOer)tPG`1i6$G(
zGb}FjMsE1$tLq3RLSHbrkuu?(0H2RNZ?e%)qGawqK6EnT;g*M-)zvYQyEup9jOqeC
zQJCO>I3jtBXfBKr^i&j2@XLK#9Aosagx^<_fC?}H%#*PS83A>Z%L-Hh>XRS~8W7m4
z`D?5CilltWM{E9_!h4fS3n+gk`5x^4_QS)+R$2Uknz_A?Z82=(W(tgpJyx%4gfqFf
zLy0WZUU@I}sLAqUDWfu8?tm&Tkc-|#zE^;|_X@E2sRR%5?}IJ08r&UushxLcQUi4w
zsCz@f$5kF5A9-+yUtn&B<;f|`&ju$mzR8D4v^E#<+~%sh%Jrmstm=OQt#A`JoBJ3a
zrZymzf!d|RklyD?1bw|10<h_Dy$8Jqfzuse!|M9GNJm{dYVN%IlT+&vqP`h!dwP@8
zaUS|7bwuq{S2+F1l|@x!D0@5{6*e>YS)pVWf-E(|YzCQ)H_NIxQGu;$xAE|-A4?mQ
z$`UkH1!_;qda>kF6bOHc<+M-U*x`RR*P1b3M8)z1IZkpgpF&-y(Ek)^JYFjFab=;s
zMqf@aTYc2t-{$&AT?I&BKBn}M)b}eCzEi-B6CAM<<^dv(3YdjK6a-ZH(wLkws?{<`
zyjEQ)&pw#m+3+ZuA6K!;QMls-@m&y(f;trWtcRG}novY7k}H3IKE=cjlaJ~npWkXb
zHXgozvP1E#QPt*iWU-Os#j>U)etnB&G$e|U(b^K*Xfc!zcV*yyY~VX-K!iP5hCTRu
zFu)bi>surh#ODA7_+sA~;-v5COMstmZn3DmVoc?$0#KpakYk=_0QsW<Qq3-fFK=#T
zwG(4C7eQP^O+bGG*x%d&HY=gQiu#=7<*^nGf#G9Y%bzMz9+C(Kx+8;8S*#f7&v*HH
z2PPlpn-t#P+#&@b+K+%hYMH5RRV@VK5U7O+D4n;rSZ$4BlBU>nh051!fV$J6gg0+*
zk;+1lg_@gD-YnnU@?PsitGYMgKGwWgYd*T>F=4n}uM&T)<y<AuZf12G%HsWOi^Au3
z&=w^^FA@+4yr+=}s9SgA4OSrdcS5`tEuM&eHi1Cm%n2w|MChby%4$(MjD`<cKj{#V
z1U(r~LMo}xhJGPgnf4zooeaglmEwQ6dEF_9Q2ZYLM8ns_oJPdEn^+{M(hD_vb*~{9
zi0}?Lv#fv7^z-^_3K-ozphx~>t*Bj((D&y&-jYE(RL+_|3)*bmpwC5-jtyOrJ@hH~
zOfkfFC8=P}R3%S`8q@rgR7K9$k$7%Ia^B0<yy5Hf-f6lk*?7A_cN_?vDQbX_075+=
zo(n)o0U2iEdJ#xFB*EhOU(wdHL0O6^6=&IY6*Yg9rOWHNuq%FDxg2shHeG<W*r>5K
zX^7>HYe++Fn!!?50<&F`CiM$^=wg@BjA2%!C++sJ!RVy&eLovD*+^v@sK`=nCi)&e
zYYI*Ac1gM!-pcu4&sT=@XAN~Ln*6;=5erE2&FPU1^&})r&!Xaq@1{6?F=?pRA5kw&
zv$R4dzc`S&#D}|o>YB!9wRH7H>_hwZ)fgzLU`S|t0CC@RpB86)sOys9^ZDFQEUKqg
zwj94{qg!8u{bqwcaDYE|-IK--B!Bcd5X+KmM;wqn!N>Mj4UR#T$>XjtUSPs7UT)H$
zElM{V^hxA&#i+70vm$QwZogw`adLE`<sO-P%#t!cG1Gu?K9Cw8#MuOflRZvw3@wf)
zov57W=RA~)_|Zr?s$o_qsR#s&QI%$W4GTX522vO(*`o&p7+>+E6GaUMl7AR5*ziH~
z0SOcyZKy%>uhY)MR9OT-a^<DwSuiYPenv`c59+~kh~qQR2TsE@T*Ou~P~rNB@CUtl
z$IiDM^}yNBT~Xfz9T>7lY}&(6GaU89HMuBHX7LQZS1|PNbE9c+F3IEK?CQB2sh{P~
zSJ(XX&#~M_FahI-;YiA~DSxX$WX<hxBZEuqhFkpjzuFA%^(b)>P5sX?hQ0m1+Jz4>
zfQDE&9+q&E+E{{LUv*-N+0?%NfB*d-ZO^;EE8WMj?{-588OW6{xXF;>k1~LhH2WdB
zGT^hNJsBeR!4~f>Yr!cRzQL{82?(8gMdK*5k1zEBSPhD<*U9vmtQ{HYns&z2!wmvj
W?Rb6UBfQ?s`>Zb8nf(tQXi;NJ4gJsn

diff --git a/build/html/searchindex.js b/build/html/searchindex.js
index 39e7acb..4f3508b 100644
--- a/build/html/searchindex.js
+++ b/build/html/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles": {"1. First, install tensorflow (https://www.tensorflow.org/install/pip)": [[7, "first-install-tensorflow-https-www-tensorflow-org-install-pip"]], "2. Second, install pytorch": [[7, "second-install-pytorch"]], "3. After we prepared right environment we can install the ammico package": [[7, "after-we-prepared-right-environment-we-can-install-the-ammico-package"]], "AMMICO - AI Media and Misinformation Content Analysis Tool": [[7, "ammico-ai-media-and-misinformation-content-analysis-tool"]], "AMMICO Demonstration Notebook": [[5, "AMMICO-Demonstration-Notebook"]], "AMMICO package modules": [[4, "ammico-package-modules"]], "BLIP2 models": [[5, "BLIP2-models"]], "Color analysis of pictures": [[5, "Color-analysis-of-pictures"]], "Color/hue detection": [[7, "color-hue-detection"]], "Compatibility problems solving": [[7, "compatibility-problems-solving"]], "Content extraction": [[7, "content-extraction"]], "Contents:": [[2, null]], "Crop posts module": [[6, "Crop-posts-module"]], "Cropping of posts": [[7, "cropping-of-posts"]], "Detection of faces and facial expression analysis": [[5, "Detection-of-faces-and-facial-expression-analysis"]], "Emotion recognition": [[7, "emotion-recognition"]], "FAQ": [[7, "faq"]], "Features": [[7, "features"]], "Formulate your search queries": [[5, "Formulate-your-search-queries"]], "Further detector modules": [[5, "Further-detector-modules"]], "Image Multimodal Search": [[5, "Image-Multimodal-Search"]], "Image summary and query": [[5, "Image-summary-and-query"]], "Import the ammico package.": [[5, "Import-the-ammico-package."]], "Improve the search results": [[5, "Improve-the-search-results"]], "Indexing and extracting features from images in selected folder": [[5, "Indexing-and-extracting-features-from-images-in-selected-folder"]], "Indices and tables": [[2, "indices-and-tables"]], "Installation": [[7, "installation"]], "Instructions how to generate and enable a google Cloud Vision API key": [[1, "instructions-how-to-generate-and-enable-a-google-cloud-vision-api-key"], [8, "instructions-how-to-generate-and-enable-a-google-cloud-vision-api-key"]], "License": [[3, "license"]], "Micromamba": [[7, "micromamba"]], "Read in a csv file containing text and translating/analysing the text": [[5, "Read-in-a-csv-file-containing-text-and-translating/analysing-the-text"]], "Save search results to csv": [[5, "Save-search-results-to-csv"]], "Step 0: Create and set a Google Cloud Vision Key": [[5, "Step-0:-Create-and-set-a-Google-Cloud-Vision-Key"]], "Step 1: Read your data into AMMICO": [[5, "Step-1:-Read-your-data-into-AMMICO"]], "Step 2: Inspect the input files using the graphical user interface": [[5, "Step-2:-Inspect-the-input-files-using-the-graphical-user-interface"]], "Step 3: Analyze all images": [[5, "Step-3:-Analyze-all-images"]], "Step 4: Convert analysis output to pandas dataframe and write csv": [[5, "Step-4:-Convert-analysis-output-to-pandas-dataframe-and-write-csv"]], "Text extraction": [[7, "text-extraction"]], "The detector modules": [[5, "The-detector-modules"]], "Usage": [[7, "usage"]], "Use a test dataset": [[5, "Use-a-test-dataset"]], "Welcome to AMMICO\u2019s documentation!": [[2, "welcome-to-ammico-s-documentation"]], "What happens if I don\u2019t have internet access - can I still use ammico?": [[7, "what-happens-if-i-don-t-have-internet-access-can-i-still-use-ammico"]], "What happens to the images that are sent to google Cloud Vision?": [[7, "what-happens-to-the-images-that-are-sent-to-google-cloud-vision"]], "What happens to the text that is sent to google Translate?": [[7, "what-happens-to-the-text-that-is-sent-to-google-translate"]], "Windows": [[7, "windows"]], "color_analysis module": [[0, "module-colors"]], "cropposts module": [[0, "module-cropposts"]], "display module": [[0, "module-display"]], "faces module": [[0, "module-faces"]], "multimodal search module": [[0, "module-multimodal_search"]], "summary module": [[0, "module-summary"]], "text module": [[0, "module-text"]], "utils module": [[0, "module-utils"]]}, "docnames": ["ammico", "create_API_key_link", "index", "license_link", "modules", "notebooks/DemoNotebook_ammico", "notebooks/Example cropposts", "readme_link", "set_up_credentials"], "envversion": {"nbsphinx": 4, "sphinx": 61, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2}, "filenames": ["ammico.rst", "create_API_key_link.md", "index.rst", "license_link.md", "modules.rst", "notebooks/DemoNotebook_ammico.ipynb", "notebooks/Example cropposts.ipynb", "readme_link.md", "set_up_credentials.md"], "indexentries": {"all_allowed_model_types (summary.summarydetector attribute)": [[0, "summary.SummaryDetector.all_allowed_model_types", false]], "allowed_analysis_types (summary.summarydetector attribute)": [[0, "summary.SummaryDetector.allowed_analysis_types", false]], "allowed_model_types (summary.summarydetector attribute)": [[0, "summary.SummaryDetector.allowed_model_types", false]], "allowed_new_model_types (summary.summarydetector attribute)": [[0, "summary.SummaryDetector.allowed_new_model_types", false]], "ammico_prefetch_models() (in module utils)": [[0, "utils.ammico_prefetch_models", false]], "analyse_image() (colors.colordetector method)": [[0, "colors.ColorDetector.analyse_image", false]], "analyse_image() (faces.emotiondetector method)": [[0, "faces.EmotionDetector.analyse_image", false]], "analyse_image() (summary.summarydetector method)": [[0, "summary.SummaryDetector.analyse_image", false]], "analyse_image() (text.textdetector method)": [[0, "text.TextDetector.analyse_image", false]], "analyse_image() (utils.analysismethod method)": [[0, "utils.AnalysisMethod.analyse_image", false]], "analyse_questions() (summary.summarydetector method)": [[0, "summary.SummaryDetector.analyse_questions", false]], "analyse_summary() (summary.summarydetector method)": [[0, "summary.SummaryDetector.analyse_summary", false]], "analyse_topic() (text.postprocesstext method)": [[0, "text.PostprocessText.analyse_topic", false]], "analysisexplorer (class in display)": [[0, "display.AnalysisExplorer", false]], "analysismethod (class in utils)": [[0, "utils.AnalysisMethod", false]], "analyze_single_face() (faces.emotiondetector method)": [[0, "faces.EmotionDetector.analyze_single_face", false]], "append_data_to_dict() (in module utils)": [[0, "utils.append_data_to_dict", false]], "check_for_missing_keys() (in module utils)": [[0, "utils.check_for_missing_keys", false]], "check_model() (summary.summarydetector method)": [[0, "summary.SummaryDetector.check_model", false]], "clean_subdict() (faces.emotiondetector method)": [[0, "faces.EmotionDetector.clean_subdict", false]], "clean_text() (text.textdetector method)": [[0, "text.TextDetector.clean_text", false]], "colordetector (class in colors)": [[0, "colors.ColorDetector", false]], "colors": [[0, "module-colors", false]], "compute_crop_corner() (in module cropposts)": [[0, "cropposts.compute_crop_corner", false]], "compute_gradcam_batch() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.compute_gradcam_batch", false]], "crop_image_from_post() (in module cropposts)": [[0, "cropposts.crop_image_from_post", false]], "crop_media_posts() (in module cropposts)": [[0, "cropposts.crop_media_posts", false]], "crop_posts_from_refs() (in module cropposts)": [[0, "cropposts.crop_posts_from_refs", false]], "crop_posts_image() (in module cropposts)": [[0, "cropposts.crop_posts_image", false]], "cropposts": [[0, "module-cropposts", false]], "deepface_symlink_processor() (in module faces)": [[0, "faces.deepface_symlink_processor", false]], "display": [[0, "module-display", false]], "downloadresource (class in utils)": [[0, "utils.DownloadResource", false]], "draw_matches() (in module cropposts)": [[0, "cropposts.draw_matches", false]], "dump_df() (in module utils)": [[0, "utils.dump_df", false]], "emotiondetector (class in faces)": [[0, "faces.EmotionDetector", false]], "extract_image_features_basic() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.extract_image_features_basic", false]], "extract_image_features_blip2() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.extract_image_features_blip2", false]], "extract_image_features_clip() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.extract_image_features_clip", false]], "extract_text_features() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.extract_text_features", false]], "faces": [[0, "module-faces", false]], "facial_expression_analysis() (faces.emotiondetector method)": [[0, "faces.EmotionDetector.facial_expression_analysis", false]], "find_files() (in module utils)": [[0, "utils.find_files", false]], "get() (utils.downloadresource method)": [[0, "utils.DownloadResource.get", false]], "get_att_map() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.get_att_map", false]], "get_color_table() (in module utils)": [[0, "utils.get_color_table", false]], "get_dataframe() (in module utils)": [[0, "utils.get_dataframe", false]], "get_pathes_from_query() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.get_pathes_from_query", false]], "get_text_df() (text.postprocesstext method)": [[0, "text.PostprocessText.get_text_df", false]], "get_text_dict() (text.postprocesstext method)": [[0, "text.PostprocessText.get_text_dict", false]], "get_text_from_image() (text.textdetector method)": [[0, "text.TextDetector.get_text_from_image", false]], "image_text_match_reordering() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.image_text_match_reordering", false]], "initialize_dict() (in module utils)": [[0, "utils.initialize_dict", false]], "is_interactive() (in module utils)": [[0, "utils.is_interactive", false]], "iterable() (in module utils)": [[0, "utils.iterable", false]], "itm_text_precessing() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.itm_text_precessing", false]], "kp_from_matches() (in module cropposts)": [[0, "cropposts.kp_from_matches", false]], "load_feature_extractor_model_albef() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_feature_extractor_model_albef", false]], "load_feature_extractor_model_blip() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_feature_extractor_model_blip", false]], "load_feature_extractor_model_blip2() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_feature_extractor_model_blip2", false]], "load_feature_extractor_model_clip_base() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_feature_extractor_model_clip_base", false]], "load_feature_extractor_model_clip_vitl14() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_feature_extractor_model_clip_vitl14", false]], "load_feature_extractor_model_clip_vitl14_336() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_feature_extractor_model_clip_vitl14_336", false]], "load_model() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model", false]], "load_model_base() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_base", false]], "load_model_base_blip2_opt_caption_coco_opt67b() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_base_blip2_opt_caption_coco_opt67b", false]], "load_model_base_blip2_opt_pretrain_opt67b() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_base_blip2_opt_pretrain_opt67b", false]], "load_model_blip2_opt_caption_coco_opt27b() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_blip2_opt_caption_coco_opt27b", false]], "load_model_blip2_opt_pretrain_opt27b() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_blip2_opt_pretrain_opt27b", false]], "load_model_blip2_t5_caption_coco_flant5xl() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_blip2_t5_caption_coco_flant5xl", false]], "load_model_blip2_t5_pretrain_flant5xl() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_blip2_t5_pretrain_flant5xl", false]], "load_model_blip2_t5_pretrain_flant5xxl() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_blip2_t5_pretrain_flant5xxl", false]], "load_model_large() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_large", false]], "load_new_model() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_new_model", false]], "load_tensors() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_tensors", false]], "load_vqa_model() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_vqa_model", false]], "matching_points() (in module cropposts)": [[0, "cropposts.matching_points", false]], "module": [[0, "module-colors", false], [0, "module-cropposts", false], [0, "module-display", false], [0, "module-faces", false], [0, "module-multimodal_search", false], [0, "module-summary", false], [0, "module-text", false], [0, "module-utils", false]], "multimodal_device (multimodal_search.multimodalsearch attribute)": [[0, "multimodal_search.MultimodalSearch.multimodal_device", false]], "multimodal_search": [[0, "module-multimodal_search", false]], "multimodal_search() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.multimodal_search", false]], "multimodalsearch (class in multimodal_search)": [[0, "multimodal_search.MultimodalSearch", false]], "parsing_images() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.parsing_images", false]], "paste_image_and_comment() (in module cropposts)": [[0, "cropposts.paste_image_and_comment", false]], "postprocesstext (class in text)": [[0, "text.PostprocessText", false]], "querys_processing() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.querys_processing", false]], "read_and_process_images() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.read_and_process_images", false]], "read_and_process_images_itm() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.read_and_process_images_itm", false]], "read_csv() (text.textanalyzer method)": [[0, "text.TextAnalyzer.read_csv", false]], "read_img() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.read_img", false]], "remove_linebreaks() (text.textdetector method)": [[0, "text.TextDetector.remove_linebreaks", false]], "resize_img() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.resize_img", false]], "resources (utils.downloadresource attribute)": [[0, "utils.DownloadResource.resources", false]], "rgb2name() (colors.colordetector method)": [[0, "colors.ColorDetector.rgb2name", false]], "run_server() (display.analysisexplorer method)": [[0, "display.AnalysisExplorer.run_server", false]], "save_tensors() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.save_tensors", false]], "set_keys() (colors.colordetector method)": [[0, "colors.ColorDetector.set_keys", false]], "set_keys() (faces.emotiondetector method)": [[0, "faces.EmotionDetector.set_keys", false]], "set_keys() (text.textdetector method)": [[0, "text.TextDetector.set_keys", false]], "set_keys() (utils.analysismethod method)": [[0, "utils.AnalysisMethod.set_keys", false]], "show_results() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.show_results", false]], "summary": [[0, "module-summary", false]], "summarydetector (class in summary)": [[0, "summary.SummaryDetector", false]], "text": [[0, "module-text", false]], "text_ner() (text.textdetector method)": [[0, "text.TextDetector.text_ner", false]], "text_sentiment_transformers() (text.textdetector method)": [[0, "text.TextDetector.text_sentiment_transformers", false]], "text_summary() (text.textdetector method)": [[0, "text.TextDetector.text_summary", false]], "textanalyzer (class in text)": [[0, "text.TextAnalyzer", false]], "textdetector (class in text)": [[0, "text.TextDetector", false]], "translate_text() (text.textdetector method)": [[0, "text.TextDetector.translate_text", false]], "update_picture() (display.analysisexplorer method)": [[0, "display.AnalysisExplorer.update_picture", false]], "upload_model_blip2_coco() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.upload_model_blip2_coco", false]], "upload_model_blip_base() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.upload_model_blip_base", false]], "upload_model_blip_large() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.upload_model_blip_large", false]], "utils": [[0, "module-utils", false]], "wears_mask() (faces.emotiondetector method)": [[0, "faces.EmotionDetector.wears_mask", false]]}, "objects": {"": [[0, 0, 0, "-", "colors"], [0, 0, 0, "-", "cropposts"], [0, 0, 0, "-", "display"], [0, 0, 0, "-", "faces"], [0, 0, 0, "-", "multimodal_search"], [0, 0, 0, "-", "summary"], [0, 0, 0, "-", "text"], [0, 0, 0, "-", "utils"]], "colors": [[0, 1, 1, "", "ColorDetector"]], "colors.ColorDetector": [[0, 2, 1, "", "analyse_image"], [0, 2, 1, "", "rgb2name"], [0, 2, 1, "", "set_keys"]], "cropposts": [[0, 3, 1, "", "compute_crop_corner"], [0, 3, 1, "", "crop_image_from_post"], [0, 3, 1, "", "crop_media_posts"], [0, 3, 1, "", "crop_posts_from_refs"], [0, 3, 1, "", "crop_posts_image"], [0, 3, 1, "", "draw_matches"], [0, 3, 1, "", "kp_from_matches"], [0, 3, 1, "", "matching_points"], [0, 3, 1, "", "paste_image_and_comment"]], "display": [[0, 1, 1, "", "AnalysisExplorer"]], "display.AnalysisExplorer": [[0, 2, 1, "", "run_server"], [0, 2, 1, "", "update_picture"]], "faces": [[0, 1, 1, "", "EmotionDetector"], [0, 3, 1, "", "deepface_symlink_processor"]], "faces.EmotionDetector": [[0, 2, 1, "", "analyse_image"], [0, 2, 1, "", "analyze_single_face"], [0, 2, 1, "", "clean_subdict"], [0, 2, 1, "", "facial_expression_analysis"], [0, 2, 1, "", "set_keys"], [0, 2, 1, "", "wears_mask"]], "multimodal_search": [[0, 1, 1, "", "MultimodalSearch"]], "multimodal_search.MultimodalSearch": [[0, 2, 1, "", "compute_gradcam_batch"], [0, 2, 1, "", "extract_image_features_basic"], [0, 2, 1, "", "extract_image_features_blip2"], [0, 2, 1, "", "extract_image_features_clip"], [0, 2, 1, "", "extract_text_features"], [0, 2, 1, "", "get_att_map"], [0, 2, 1, "", "get_pathes_from_query"], [0, 2, 1, "", "image_text_match_reordering"], [0, 2, 1, "", "itm_text_precessing"], [0, 2, 1, "", "load_feature_extractor_model_albef"], [0, 2, 1, "", "load_feature_extractor_model_blip"], [0, 2, 1, "", "load_feature_extractor_model_blip2"], [0, 2, 1, "", "load_feature_extractor_model_clip_base"], [0, 2, 1, "", "load_feature_extractor_model_clip_vitl14"], [0, 2, 1, "", "load_feature_extractor_model_clip_vitl14_336"], [0, 2, 1, "", "load_tensors"], [0, 4, 1, "", "multimodal_device"], [0, 2, 1, "", "multimodal_search"], [0, 2, 1, "", "parsing_images"], [0, 2, 1, "", "querys_processing"], [0, 2, 1, "", "read_and_process_images"], [0, 2, 1, "", "read_and_process_images_itm"], [0, 2, 1, "", "read_img"], [0, 2, 1, "", "resize_img"], [0, 2, 1, "", "save_tensors"], [0, 2, 1, "", "show_results"], [0, 2, 1, "", "upload_model_blip2_coco"], [0, 2, 1, "", "upload_model_blip_base"], [0, 2, 1, "", "upload_model_blip_large"]], "summary": [[0, 1, 1, "", "SummaryDetector"]], "summary.SummaryDetector": [[0, 4, 1, "", "all_allowed_model_types"], [0, 4, 1, "", "allowed_analysis_types"], [0, 4, 1, "", "allowed_model_types"], [0, 4, 1, "", "allowed_new_model_types"], [0, 2, 1, "", "analyse_image"], [0, 2, 1, "", "analyse_questions"], [0, 2, 1, "", "analyse_summary"], [0, 2, 1, "", "check_model"], [0, 2, 1, "", "load_model"], [0, 2, 1, "", "load_model_base"], [0, 2, 1, "", "load_model_base_blip2_opt_caption_coco_opt67b"], [0, 2, 1, "", "load_model_base_blip2_opt_pretrain_opt67b"], [0, 2, 1, "", "load_model_blip2_opt_caption_coco_opt27b"], [0, 2, 1, "", "load_model_blip2_opt_pretrain_opt27b"], [0, 2, 1, "", "load_model_blip2_t5_caption_coco_flant5xl"], [0, 2, 1, "", "load_model_blip2_t5_pretrain_flant5xl"], [0, 2, 1, "", "load_model_blip2_t5_pretrain_flant5xxl"], [0, 2, 1, "", "load_model_large"], [0, 2, 1, "", "load_new_model"], [0, 2, 1, "", "load_vqa_model"]], "text": [[0, 1, 1, "", "PostprocessText"], [0, 1, 1, "", "TextAnalyzer"], [0, 1, 1, "", "TextDetector"]], "text.PostprocessText": [[0, 2, 1, "", "analyse_topic"], [0, 2, 1, "", "get_text_df"], [0, 2, 1, "", "get_text_dict"]], "text.TextAnalyzer": [[0, 2, 1, "", "read_csv"]], "text.TextDetector": [[0, 2, 1, "", "analyse_image"], [0, 2, 1, "", "clean_text"], [0, 2, 1, "", "get_text_from_image"], [0, 2, 1, "", "remove_linebreaks"], [0, 2, 1, "", "set_keys"], [0, 2, 1, "", "text_ner"], [0, 2, 1, "", "text_sentiment_transformers"], [0, 2, 1, "", "text_summary"], [0, 2, 1, "", "translate_text"]], "utils": [[0, 1, 1, "", "AnalysisMethod"], [0, 1, 1, "", "DownloadResource"], [0, 3, 1, "", "ammico_prefetch_models"], [0, 3, 1, "", "append_data_to_dict"], [0, 3, 1, "", "check_for_missing_keys"], [0, 3, 1, "", "dump_df"], [0, 3, 1, "", "find_files"], [0, 3, 1, "", "get_color_table"], [0, 3, 1, "", "get_dataframe"], [0, 3, 1, "", "initialize_dict"], [0, 3, 1, "", "is_interactive"], [0, 3, 1, "", "iterable"]], "utils.AnalysisMethod": [[0, 2, 1, "", "analyse_image"], [0, 2, 1, "", "set_keys"]], "utils.DownloadResource": [[0, 2, 1, "", "get"], [0, 4, 1, "", "resources"]]}, "objnames": {"0": ["py", "module", "Python module"], "1": ["py", "class", "Python class"], "2": ["py", "method", "Python method"], "3": ["py", "function", "Python function"], "4": ["py", "attribute", "Python attribute"]}, "objtypes": {"0": "py:module", "1": "py:class", "2": "py:method", "3": "py:function", "4": "py:attribute"}, "terms": {"": 5, "0": [0, 2, 7], "00": 6, "03": 5, "1": [0, 1, 2, 8], "10": [5, 6, 7], "100": [0, 5, 6], "1000": [1, 8], "11": 7, "12": [5, 7], "14": 0, "15": [5, 6], "16": 5, "163": 7, "19": 0, "1976": 0, "2": [0, 2], "20": [0, 5], "2022": [3, 7], "2023": 5, "20gb": 5, "23": 7, "240": 0, "240p": 0, "27": 5, "28": 5, "3": [0, 2], "30": [0, 5], "336": 0, "35": 5, "3_non": 5, "4": [2, 7], "5": [0, 5], "50": [0, 1, 5, 8], "5_clip_base_saved_features_imag": 5, "6": [0, 5, 7], "60gb": 5, "61": [5, 6], "7": 7, "7b": [0, 5], "8": [0, 7], "8050": 0, "8055": 5, "8057": 5, "9": 0, "981aa55a3b13": 5, "A": [0, 3, 5], "AND": 3, "AS": 3, "And": 5, "BE": 3, "BUT": 3, "Be": 7, "But": 5, "FOR": 3, "For": [5, 7], "IN": 3, "If": [0, 5, 6, 7], "In": [1, 5, 7, 8], "It": [1, 5, 6, 7, 8], "NO": 3, "NOT": 3, "No": 5, "OF": 3, "OR": 3, "One": 0, "Or": [1, 5, 8], "THE": 3, "TO": 3, "That": 5, "The": [0, 1, 2, 3, 6, 7, 8], "Then": 5, "There": 7, "These": [0, 5, 7], "To": [0, 5, 7], "WITH": 3, "With": 5, "_": 5, "__file__": 7, "_saved_features_imag": 5, "a100": 5, "a4f8f3": 5, "ab": 5, "about": [0, 5, 7], "abov": [3, 5, 7], "abus": 7, "access": 2, "accord": 7, "account": [1, 7, 8], "accur": [5, 7], "action": 3, "activ": 7, "ad": 5, "adapt": 5, "add": [5, 7], "addendum": 7, "addit": 0, "advanc": 5, "af0f99b": 5, "after": [1, 5, 8], "ag": [5, 7], "again": 5, "ai": 2, "albef": 5, "albef_feature_extractor": 0, "algorithm": [0, 5], "all": [0, 2, 3], "all_allowed_model_typ": [0, 4], "allow": [0, 5, 7], "allowed_analysis_typ": [0, 4], "allowed_model_typ": [0, 4], "allowed_new_model_typ": [0, 4], "along": 5, "alreadi": 5, "also": [0, 5, 7], "altern": 5, "american": 5, "ammico": [0, 1, 6, 8], "ammico_data_hom": 5, "ammico_env": 7, "ammico_prefetch_model": [0, 4], "among": 5, "an": [0, 3, 5, 6, 7], "analis": 0, "analys": [0, 2, 7], "analyse_imag": [0, 4, 5], "analyse_quest": [0, 4], "analyse_summari": [0, 4], "analyse_text": [0, 5, 7], "analyse_top": [0, 4], "analysi": [0, 2], "analysis_explor": 5, "analysis_typ": [0, 5], "analysisexplor": [0, 4, 5], "analysismethod": [0, 4], "analyz": [0, 2, 7], "analyze_single_fac": [0, 4], "analyze_text": 0, "anger": 5, "angri": 5, "ani": [0, 1, 3, 5, 7, 8], "anoth": 7, "answer": [0, 5, 7], "api": [0, 2, 5, 7], "app": 5, "append": 0, "append_data_to_dict": [0, 4, 5], "appli": 5, "applic": 6, "approach": 5, "appropri": 0, "approxim": 5, "ar": [0, 2, 5, 6], "architectur": 0, "archiv": 6, "area": 0, "arg": 0, "argument": 5, "aris": 3, "around": [0, 7], "arrai": 0, "art": 7, "as_posix": [5, 6], "asian": 5, "ask": [0, 5], "assign": 5, "associ": [3, 5], "asyncbatchannotatefil": 7, "asyncbatchannotateimag": 7, "asynchron": 7, "att_map": 0, "attent": 0, "author": 3, "automat": [5, 7], "avail": [5, 7], "avif": [0, 5], "avoid": 7, "b": 5, "back": [0, 1, 8], "background": 5, "bar": 5, "base": [0, 5, 7], "base_coco": 0, "batch": [0, 6, 7], "batch_siz": [0, 5], "batchannotatefil": 7, "batchannotateimag": 7, "becaus": [0, 5], "bee": 0, "been": [1, 5, 8], "befor": [0, 5, 7], "being": 5, "below": [0, 5, 6, 7], "bert": 5, "bertop": 0, "best": [5, 7], "best_simularity_value_in_current_search": 5, "better": 5, "between": [0, 5, 7], "beyond": 0, "bigger": 5, "bill": [1, 8], "binari": 0, "bit": 5, "black": [0, 7], "blank": [1, 8], "blip": 5, "blip2": 0, "blip2_coco": [0, 5], "blip2_feature_extractor": 0, "blip2_image_text_match": 0, "blip2_opt_caption_coco_opt2": [0, 5], "blip2_opt_caption_coco_opt6": [0, 5], "blip2_opt_pretrain_opt2": [0, 5], "blip2_opt_pretrain_opt6": [0, 5], "blip2_t5_caption_coco_flant5xl": [0, 5], "blip2_t5_pretrain_flant5xl": [0, 5], "blip2_t5_pretrain_flant5xxl": [0, 5], "blip_bas": 5, "blip_capt": 0, "blip_feature_extractor": 0, "blip_image_text_match": 0, "blip_larg": 5, "blip_vqa": 0, "block": 0, "block_num": 0, "blue": [0, 7], "blur": 0, "bool": [0, 5], "both": [5, 7], "briefli": 7, "bring": [1, 8], "brown": [0, 7], "browser": [1, 8], "build": 7, "c": [0, 3, 7], "calcul": 5, "call": [5, 7], "callback": 0, "campaign": 5, "can": [0, 1, 2, 5, 6, 8], "capabl": 5, "caption": [0, 5, 7], "caption_coco_": 5, "caption_coco_flant5xl": 0, "caption_coco_opt2": 0, "caption_coco_opt6": 0, "card": 5, "care": 7, "carri": [5, 6, 7], "case": 5, "categor": [0, 6], "categori": 5, "cell": [5, 6], "chang": 5, "channel": 7, "charg": [1, 3, 8], "check": [0, 5, 6, 7], "check_for_missing_kei": [0, 4], "check_model": [0, 4], "checkpoint": 5, "choos": [5, 7], "chosen": 0, "cie": 0, "citi": 5, "claim": 3, "class": [0, 5], "classif": 0, "classifi": 7, "clean": [0, 5, 7], "clean_subdict": [0, 4], "clean_text": [0, 4], "cli": [0, 5], "click": [1, 5, 8], "clip_bas": 5, "clip_feature_extractor": 0, "clip_vitl14": 5, "clip_vitl14_336": 5, "closest": 0, "cloud": [0, 2], "cnn": 5, "coco": [0, 5], "code": [5, 6], "colab": [5, 6, 7], "colaboratori": [1, 8], "collect": 7, "color": [0, 2], "color_analysi": [2, 4], "color_bgr2rgb": 6, "colordetector": [0, 4, 5], "colorgram": [0, 5, 7], "colour": [5, 7], "column": [0, 5, 7], "column_kei": [0, 5], "com": [5, 6, 7], "combat": 7, "combin": 5, "come": 5, "command": 7, "comment": [0, 6, 7], "common": 0, "compat": 2, "complet": 5, "compli": 7, "compon": 7, "comput": [0, 1, 5, 8], "computation": 5, "compute_crop_corn": [0, 4], "compute_gradcam_batch": [0, 4], "conceal": 5, "conda": [5, 7], "conda_prefix": 7, "condit": 3, "confer": 5, "confid": 5, "conll03": 5, "connect": [3, 5, 7], "consequenti": 0, "consequential_quest": [0, 5], "consid": [0, 5], "consist": 5, "consol": [1, 8], "const_image_summari": 5, "constant": [0, 5], "contain": [0, 2, 7], "content": [5, 6], "context": 5, "contract": 3, "contrib": 6, "conveni": 5, "convert": [0, 2], "coordin": 0, "copi": 3, "copyright": 3, "corner": [0, 1, 8], "correct": [5, 7], "correspond": 5, "cosequential_quest": 5, "could": 5, "count": 5, "countri": 5, "cover": 5, "cpp": 7, "cpu": [0, 5], "creat": [0, 1, 2, 7, 8], "creation": 5, "crop": [0, 2, 5], "crop_dir": 6, "crop_image_from_post": [0, 4], "crop_media_post": [0, 4, 6], "crop_post": 0, "crop_posts_from_ref": [0, 4, 6], "crop_posts_imag": [0, 4], "crop_view": [0, 6], "croppost": [2, 4, 6, 7], "crpo": 6, "css3": 0, "csv": [0, 2, 7], "csv_encod": 0, "csv_path": [0, 5], "cu11": 7, "cu118": 7, "cuda": [0, 5, 7], "cudatoolkit": 7, "cudnn": 7, "cudnn_path": 7, "current": [0, 1, 7, 8], "current_simularity_valu": 5, "cut": 0, "cv2": [0, 6], "cvtcolor": 6, "cyan": [0, 7], "d": [6, 7], "damag": 3, "dash": [0, 5], "dashboard": [1, 8], "data": [0, 2, 6, 7], "data_out": 5, "data_path": 5, "databas": 7, "datafram": [0, 2], "dataset": 2, "dbmdz": 5, "deactiv": 7, "deal": 3, "deepfac": [5, 7], "deepface_symlink_processor": [0, 4], "default": [0, 5], "defin": 5, "delet": 7, "delta": 0, "delta_e_method": 0, "demand": [0, 5], "demonstr": [2, 7], "depend": [5, 7], "depth": 7, "describ": 7, "descript": [5, 7], "descriptor": 0, "desir": 5, "detail": 5, "detect": [0, 2], "detector": [2, 7], "determin": 0, "determinist": 0, "deterministic_summari": 5, "develop": [5, 7], "devic": 0, "device_typ": [0, 5], "df": 5, "dict": [0, 5], "dictionari": [0, 5], "differ": [5, 6], "directli": [1, 5, 8], "directori": [0, 5], "dirnam": 7, "discard": 5, "disgust": 5, "disk": 7, "displai": [2, 4, 5], "distanc": 7, "distilbart": 5, "distilbert": 5, "distribut": 3, "dmatch": 0, "do": [3, 5, 7], "document": 3, "doe": [0, 5, 7], "doesn": 6, "dog": 5, "domin": 5, "don": 2, "done": [1, 5, 6, 7, 8], "dopamin": 5, "dot": [1, 8], "down": [1, 8], "download": [0, 1, 5, 7, 8], "downloadresourc": [0, 4], "draw_match": [0, 4], "drive": [1, 5, 6, 7, 8], "drop": [1, 8], "dropdown": 5, "due": [5, 6], "dump": [0, 5], "dump_df": [0, 4, 5], "dump_everi": 5, "dump_fil": 5, "e": [0, 7], "each": [0, 5], "easi": 5, "easier": 6, "easili": 5, "echo": 7, "either": [0, 5], "element": [5, 7], "emot": 5, "emotion_threshold": [0, 5], "emotiondetector": [0, 4, 5], "emotitiondetector": 5, "empti": [0, 5], "enabl": [2, 5, 7], "english": [0, 5, 7], "enter": [1, 8], "entiti": [0, 5, 7], "entity_typ": 5, "entri": [0, 5], "enumer": 5, "env_var": 7, "environ": [0, 5], "equip": 5, "error": [0, 5, 7], "estim": 0, "etc": 7, "even": 5, "event": 3, "everi": 5, "everyth": 6, "ex": 7, "exampl": [5, 6], "exclud": 0, "execut": [5, 6], "exist": 5, "exist_ok": 5, "experiment": [5, 7], "explain": 5, "explicitli": 5, "explor": [0, 5], "export": [5, 7], "express": [0, 2, 3, 7], "ext": 0, "extens": [5, 7], "extra": 6, "extrac": 7, "extract": 0, "extract_image_features_bas": [0, 4], "extract_image_features_blip2": [0, 4], "extract_image_features_clip": [0, 4], "extract_text_featur": [0, 4], "f": 6, "f2482bf": 5, "face": [2, 4, 7], "facial": [0, 2, 7], "facial_expression_analysi": [0, 4], "failsaf": 7, "fals": [0, 5, 6], "faq": 2, "fast": 5, "fear": 5, "featur": [0, 2], "feature_extractor": 0, "features_image_stack": [0, 5], "features_text": 0, "few": [5, 7], "field": 0, "figsiz": 6, "figur": 6, "file": [0, 1, 2, 3, 6, 7, 8], "filelist": 0, "filenam": [0, 5], "filepath": 0, "fill": 5, "filter": [0, 5], "filter_number_of_imag": [0, 5], "filter_rel_error": [0, 5], "filter_val_limit": [0, 5], "final_h": 0, "find": [0, 5, 6, 7], "find_fil": [0, 4, 5, 6], "fine": [5, 6], "finetun": 5, "first": [0, 1, 5, 6, 8], "fit": 3, "flag": 5, "flake8": [5, 6], "flan": 0, "flant5": 5, "flant5xl": 5, "flant5xxl": 5, "flex": 5, "float": [0, 5], "folder": [1, 6, 7, 8], "follow": [1, 3, 5, 7, 8], "forg": 7, "form": [0, 5], "format": [0, 5], "found": [0, 5, 6, 7], "fraction": 5, "frame": 0, "framework": 7, "frankfurt": 5, "free": [0, 1, 3, 8], "frequent": 0, "from": [0, 1, 3, 6, 7, 8], "function": [0, 5], "furnish": 3, "further": [2, 7], "g": 7, "gate": 5, "gb": [5, 7], "gbq": 5, "gender": [5, 7], "gener": [0, 2, 5, 7], "get": [0, 1, 4, 5, 7, 8], "get_att_map": [0, 4], "get_color_t": [0, 4], "get_datafram": [0, 4, 5], "get_ipython": [5, 6], "get_pathes_from_queri": [0, 4], "get_text_df": [0, 4], "get_text_dict": [0, 4], "get_text_from_imag": [0, 4], "gif": [0, 5], "git": [5, 6], "github": [5, 6], "give": 5, "given": [0, 5, 6], "global": 0, "go": [1, 8], "googl": [0, 2, 6], "google_application_credenti": [5, 7], "googletran": [5, 7], "gpu": [5, 7], "gradcam": 0, "grant": 3, "graphic": 2, "green": [0, 7], "grei": [0, 7], "h_margin": 0, "ha": [1, 5, 8], "happen": 2, "happi": 5, "have": [2, 5], "head": [5, 6], "heat": 5, "heavi": 5, "held": 7, "here": [1, 5, 7, 8], "herebi": 3, "high": 5, "hold": 5, "holder": 3, "horizont": 0, "hostedtoolcach": 0, "hour": 7, "how": [2, 5], "howev": 5, "hpc": 5, "http": [5, 6], "hug": 7, "huggingfac": 5, "human": 5, "i": [0, 1, 2, 3, 5, 6, 8], "id": [0, 1, 5, 8], "ideal": 5, "identifi": 5, "ignor": [0, 6], "imag": [0, 1, 2, 6, 8], "image_df": 5, "image_dict": 5, "image_example_path": 5, "image_example_queri": 5, "image_gradcam_with_itm": [0, 5], "image_kei": [0, 5], "image_nam": [0, 5], "image_path": 0, "image_summary_detector": 5, "image_summary_vqa_detector": 5, "image_text_match_reord": [0, 4, 5], "images_tensor": 0, "img": [0, 5], "img1": 0, "img2": 0, "img_path": 0, "immedi": 7, "imperfect": 6, "implement": 5, "impli": 3, "import": [2, 6, 7], "importlib_resourc": [5, 6], "improp": 6, "improv": 7, "imread": 6, "imshow": 6, "includ": [0, 3, 5], "incompat": 5, "increment": 5, "index": [0, 2, 7], "indic": 0, "inform": [1, 6, 7, 8], "inherit": 0, "iniati": 5, "init": 5, "initi": [0, 5, 7], "initialize_dict": [0, 4], "input": [0, 2, 7], "insid": 5, "inspect": 2, "instal": [2, 5, 6], "instanc": 5, "instead": 5, "instruct": [2, 5, 7], "int": [0, 5], "intellig": 7, "intens": 5, "interact": [0, 5], "interfac": 2, "internet": 2, "ipynb": 7, "is_interact": [0, 4], "isdir": 6, "item": [5, 6], "iter": [0, 4], "itm": [0, 5], "itm_model": [0, 5], "itm_model_typ": 0, "itm_scor": 5, "itm_scores2": 0, "itm_text_precess": [0, 4], "its": [5, 7], "iulusoi": 5, "jpeg": [0, 5], "jpg": [0, 5], "json": [1, 5, 7, 8], "jupyt": [1, 5, 8], "just": [0, 5, 7], "k": 5, "keep": 6, "kei": [0, 2, 7], "keypoint": 0, "keyword": [5, 7], "kind": 3, "kp1": 0, "kp2": 0, "kp_from_match": [0, 4], "kwarg": 0, "l": [0, 5], "languag": [0, 5, 7], "larg": [0, 5, 7], "large_coco": 0, "largest": 5, "later": 0, "latest": 6, "latter": [5, 7], "launch": 5, "lavi": [0, 5, 7], "ld_library_path": 7, "left": [1, 5, 8], "lemma": 7, "len": 5, "length": 0, "less": 5, "liabil": 3, "liabl": 3, "lib": [0, 7], "librari": [0, 5, 6, 7], "licens": 2, "lida": 5, "like": [1, 5, 8], "likelihood": 5, "limit": [0, 3, 5, 6], "line": 6, "linebreak": [0, 5], "list": [0, 1, 5, 8], "list_of_quest": [0, 5], "live": 7, "llm": 5, "load": [0, 5, 6], "load_dataset": 5, "load_feature_extractor_model_albef": [0, 4], "load_feature_extractor_model_blip": [0, 4], "load_feature_extractor_model_blip2": [0, 4], "load_feature_extractor_model_clip_bas": [0, 4], "load_feature_extractor_model_clip_vitl14": [0, 4], "load_feature_extractor_model_clip_vitl14_336": [0, 4], "load_model": [0, 4], "load_model_bas": [0, 4], "load_model_base_blip2_opt_caption_coco_opt67b": [0, 4], "load_model_base_blip2_opt_pretrain_opt67b": [0, 4], "load_model_blip2_opt_caption_coco_opt27b": [0, 4], "load_model_blip2_opt_pretrain_opt27b": [0, 4], "load_model_blip2_t5_caption_coco_flant5xl": [0, 4], "load_model_blip2_t5_pretrain_flant5xl": [0, 4], "load_model_blip2_t5_pretrain_flant5xxl": [0, 4], "load_model_larg": [0, 4], "load_new_model": [0, 4], "load_tensor": [0, 4], "load_vqa_model": [0, 4], "local": [5, 7], "locat": [5, 7], "log": 7, "login": 5, "look": [0, 1, 5, 6, 8], "loop": 5, "lower": 5, "m": 7, "machin": [5, 7], "made": 7, "mai": [5, 7], "main": [5, 7], "make": [1, 5, 7, 8], "man": 5, "manag": [1, 8], "mani": 5, "manual": 6, "map": [0, 5], "margin": 0, "mask": [0, 5, 7], "match": [0, 5, 6, 7], "matching_point": [0, 4], "matplotlib": 6, "maximum": [0, 5], "mean": 5, "media": [0, 2, 5, 6], "medicin": 5, "memori": [5, 7], "menu": [1, 5, 8], "merchant": 3, "merg": [0, 3], "merge_color": 0, "messag": 5, "metadata": 7, "method": [0, 5], "metric": [0, 7], "microsoft": 7, "might": 0, "min_match": 0, "minimum": [0, 5], "misinform": [2, 5], "miss": 0, "mit": 3, "mkdir": [5, 7], "model": [0, 7], "model_nam": [0, 5], "model_old": 0, "model_typ": [0, 5], "modifi": 3, "modul": [2, 7], "moment": 5, "month": [1, 8], "moral": 6, "more": [1, 5, 7, 8], "most": [0, 5], "mount": [5, 6], "msvc": 7, "much": 5, "multi_features_stack": 0, "multimod": [2, 4, 7], "multimodal_devic": [0, 4], "multimodal_search": [0, 4, 5, 7], "multimodalsearch": [0, 4, 5], "multipl": 5, "multiple_fac": 5, "must": 7, "mv": 6, "my_obj": 5, "mydict": [0, 5], "mydriv": 5, "n": [0, 5, 7], "n_color": 0, "name": [0, 1, 5, 6, 7, 8], "natur": 0, "ndarrai": 0, "necessari": [5, 7], "need": [0, 5, 7], "need_grad_cam": [0, 5], "neg": 5, "ner": 5, "nest": [0, 5], "neutral": 5, "new": [0, 1, 5, 7, 8], "next": 5, "nn": 0, "no_fac": 5, "non": 0, "nondeterministic_summari": 0, "none": [0, 5], "noninfring": 3, "noqa": [5, 6], "note": 5, "notebook": [1, 2, 6, 7, 8], "notic": 3, "now": [1, 5, 6, 8], "np": 0, "num": 5, "number": [0, 5, 7], "number_of_imag": 5, "numer": 5, "numpi": [0, 7], "nvidia": 7, "o": [5, 6, 7], "obj": 5, "object": [0, 5], "obtain": 3, "occur": 0, "off": 0, "offlin": 7, "old": 0, "onc": 5, "one": [0, 5, 7], "ones": 5, "onli": [0, 5, 6, 7], "onlin": 7, "open": 5, "opencv": 6, "oper": 7, "opt": [0, 5], "optim": 5, "option": [0, 5, 7], "orang": [0, 7], "orbax": 5, "order": [5, 7], "origin": [0, 5, 6], "other": [0, 3, 5, 7], "otherwis": [0, 3, 5], "our": [5, 7], "out": [1, 3, 5, 6, 7, 8], "outdict": 5, "output": [0, 2], "outsid": 5, "overal": 5, "overlap": 0, "own": 5, "p": [0, 7], "packag": [0, 2, 6], "page": [1, 2, 7, 8], "paid": 5, "panda": 2, "paper": 7, "paramet": [0, 5], "parent": 5, "pars": 0, "parsing_imag": [0, 4, 5], "part": [0, 6, 7], "parti": 7, "partial": 5, "particular": 3, "pass": 5, "past": 0, "paste_image_and_com": [0, 4], "path": [0, 5, 6], "path_post": 6, "path_ref": 6, "path_to_load_tensor": [0, 5], "path_to_save_tensor": [0, 5], "pathlib": 5, "patient": 5, "pattern": [0, 5], "peopl": 5, "per": [1, 8], "percentag": [0, 5, 7], "perform": [0, 5, 7], "period": 7, "permiss": 3, "permit": 3, "persist": 7, "person": [3, 5, 7], "pick": [1, 8], "pictur": [0, 2], "pil": 0, "pin": 6, "pink": [0, 7], "pip": [5, 6], "pipelin": [0, 5, 7], "pkg": [5, 6], "place": [1, 5, 7, 8], "pleas": [5, 6, 7], "plot": 6, "plt": 6, "plt_crop": [0, 6], "plt_imag": [0, 6], "plt_match": [0, 6], "png": [0, 5, 6], "pngimageplugin": 0, "point": 0, "polar": 7, "politician": 5, "pooch": 0, "pop": [1, 8], "port": [0, 5], "portion": 3, "posit": [0, 5], "possibl": [5, 7], "post": [0, 2, 5], "postprocesstext": [0, 4], "pre": [5, 7], "predict": [5, 7], "prefetch": 0, "prefix": 0, "prepar": 5, "preprocessor": 0, "presenc": 7, "present": [0, 5], "preserv": 5, "press": 5, "pretrain": [0, 5], "pretrain_": 5, "pretrain_opt2": 0, "pretrain_opt6": 0, "prevent": [6, 7], "previou": 5, "primari": 5, "print": [6, 7], "prioriti": 7, "privat": [1, 5, 8], "probabl": 5, "problem": [0, 2], "process": [0, 1, 5, 7, 8], "product": 5, "progress": 5, "project": [1, 7, 8], "prompt": [1, 5, 8], "proper": 7, "proport": 0, "provid": [0, 3, 5, 6, 7], "pt": [0, 5], "public": 7, "publish": 3, "purpl": [0, 7], "purpos": [3, 5], "put": [0, 7], "py": [0, 7], "pycocotool": 7, "pyplot": 6, "python": [0, 1, 5, 6, 7, 8], "python3": 0, "q": 6, "qq": 6, "qqq": [5, 6], "queri": [0, 2, 7], "querys_process": [0, 4], "question": [0, 5, 7], "quit": 5, "race": [5, 7], "race_threshold": [0, 5], "ram": 5, "random": [0, 5], "random_se": [0, 5], "rank": 5, "raw_imag": 0, "raw_img": 0, "re": [5, 6, 7], "read": [0, 2], "read_and_process_imag": [0, 4], "read_and_process_images_itm": [0, 4], "read_csv": [0, 4, 5], "read_img": [0, 4], "receiv": 7, "recogn": 7, "recognit": [0, 5], "recurs": [0, 5], "red": [0, 7], "reduc": [0, 5], "ref": [5, 6], "ref_dir": 6, "ref_fil": [0, 6], "ref_view": [0, 6], "refer": [0, 1, 5, 6, 8], "region": [0, 6], "regist": 0, "rel": 0, "relev": 5, "rememb": 5, "remot": 0, "remov": [0, 6, 7], "remove_linebreak": [0, 4], "reorder": 0, "report": 5, "repositori": 5, "represent": 5, "request": 7, "requir": [0, 5, 7], "rerun": 5, "resiz": 0, "resize_img": [0, 4], "resized_imag": 0, "resourc": [0, 4, 5], "respect": 5, "respons": 7, "restart": 5, "restrict": [3, 7], "result": [0, 7], "retinafac": [5, 7], "return": [0, 5, 7], "return_top": 0, "revis": 5, "revision_numb": [0, 5], "rf": 6, "rgb": 0, "rgb2name": [0, 4], "rgb_ref_view": 6, "rgb_view": 6, "right": [1, 3, 5, 8], "rl": 5, "rm": 6, "row": 5, "run": [0, 1, 5, 6, 7, 8], "run_serv": [0, 4, 5], "runtim": 5, "sad": 5, "same": [5, 6, 7], "sampl": [6, 7], "save": [0, 6], "save_crop_dir": [0, 6], "save_tensor": [0, 4], "saved_features_imag": 0, "saved_tensor": 0, "score": 0, "screen": [1, 8], "screenshot": [1, 8], "script": 7, "sdk": 7, "search": [1, 2, 4, 7, 8], "search_queri": [0, 5], "second": [0, 5], "section": 5, "see": [1, 5, 7, 8], "seed": [0, 5], "seem": 6, "select": [0, 1, 8], "self": 0, "sell": 3, "send": 7, "sent": 2, "sentiment": [0, 5, 7], "sentiment_scor": 5, "separ": 5, "sequenti": 5, "server": [0, 5], "servic": [1, 7, 8], "session": 5, "set": [0, 1, 2, 6, 7, 8], "set_kei": [0, 4], "setuptool": [5, 6], "seven": 5, "sever": [5, 7], "sh": 7, "shade": 0, "shall": 3, "share": 7, "short": 7, "shot": 5, "should": [0, 1, 5, 8], "show": [0, 1, 5, 6, 8], "show_result": [0, 4, 5], "showcas": 5, "shown": 5, "shuffel": 0, "shuffl": [0, 5], "sidebar": 5, "sift": 0, "sign": [1, 8], "signifi": [0, 5], "similar": [0, 5, 7], "simultan": 5, "sinc": 5, "singl": [0, 5], "site": 0, "size": [0, 5, 7], "skip": 5, "skip_extract": [0, 5], "slightli": 5, "slower": 5, "small": 0, "smaller": [0, 5], "so": [0, 3, 5, 7], "social": [0, 5, 6, 7], "softwar": 3, "solv": 2, "some": [5, 6, 7], "someth": [1, 5, 6, 8], "sometim": [0, 5, 6, 7], "sort": 0, "sorted_list": [0, 5], "sourc": [5, 7], "space": 7, "spaci": [5, 7], "special": 5, "specif": [0, 5], "specifi": 5, "speech": 7, "spell": 7, "ssc": 3, "ssciwr": [5, 6], "sshleifer": 5, "sst": 5, "stack": 0, "start": 0, "state": 7, "step": [2, 6, 7], "still": 2, "store": [5, 7], "str": [0, 5, 6], "string": 5, "studio": 7, "style": 5, "subdict": [0, 5], "subdirectori": [0, 5], "subfold": 5, "subject": [3, 7], "sublicens": 3, "subsequ": 5, "substanti": 3, "substitut": 6, "subtract": 0, "suffix": 0, "suitabl": 5, "summar": 5, "summari": [2, 4, 7], "summary_and_quest": [0, 5], "summary_model": 0, "summary_vis_processor": 0, "summary_vqa_model": 0, "summary_vqa_model_new": 0, "summary_vqa_txt_processor": 0, "summary_vqa_txt_processors_new": 0, "summary_vqa_vis_processor": 0, "summary_vqa_vis_processors_new": 0, "summarydetector": [0, 4, 5], "sure": [1, 5, 8], "surpris": 5, "syntax": 5, "system": 0, "t": [2, 6], "t5": 0, "ta": 5, "tab": 5, "tabl": 5, "take": [0, 5], "taken": [0, 5], "task": [5, 7], "tell": 5, "temporarili": 7, "ten": 0, "tensor": [0, 5], "tensorflow": 5, "tesor": 0, "test": [2, 6], "text": [2, 4, 6], "text_clean": [5, 7], "text_df": 5, "text_dict": 5, "text_english": [0, 5, 7], "text_english_correct": 7, "text_input": [0, 5], "text_languag": [5, 7], "text_ner": [0, 4], "text_query_index": 0, "text_sentiment_transform": [0, 4], "text_summari": [0, 4, 5], "textanalyz": [0, 4, 5], "textblob": 7, "textdetector": [0, 4, 5], "textual": 7, "tf": 5, "than": [1, 5, 8], "thei": [0, 5, 7], "them": 5, "therefor": 5, "thi": [0, 1, 3, 5, 6, 7, 8], "third": 7, "three": [1, 5, 8], "threshold": 5, "through": [0, 5], "thrown": 5, "thu": 5, "tiff": [0, 5], "time": [5, 7], "to_csv": 5, "togeth": 0, "toggl": 5, "token": [0, 7], "tokenized_text": 0, "tool": 2, "top": [1, 5, 8], "top1": 5, "topic": [0, 5, 7], "torch": [0, 7], "torchaudio": [5, 7], "torchdata": 5, "torchtext": 5, "torchvis": 7, "tort": 3, "total": 5, "tpu": 5, "tqdm": 5, "train": [0, 5], "transform": [0, 5, 7], "translat": [0, 2], "translate_text": [0, 4], "true": [0, 5, 6, 7], "try": 5, "ttl": 7, "tune": 5, "tupl": 0, "two": [0, 5, 7], "txt_processor": [0, 5], "type": [0, 5, 6], "typic": 7, "ummary_and_quest": 5, "uncas": 5, "uncom": 5, "under": 7, "unecessari": 0, "uninstal": [5, 6], "union": 0, "unrecogn": [0, 7], "unrecogniz": 5, "unzip": 6, "up": [0, 1, 5, 7, 8], "updat": [0, 5], "update_pictur": [0, 4], "upload": [1, 7, 8], "upload_model_blip2_coco": [0, 4], "upload_model_blip_bas": [0, 4], "upload_model_blip_larg": [0, 4], "upon": 5, "url": 7, "us": [0, 1, 2, 3, 8], "usa": 5, "usag": 2, "use_csv": 0, "user": [2, 7], "utf": 0, "util": [2, 4, 6], "v": 7, "v143": 7, "v2": 5, "v_margin": 0, "valu": [0, 5], "variabl": [5, 7], "veri": [5, 7], "version": [5, 6, 7], "vertic": [0, 1, 8], "via": 5, "video": 5, "view": [0, 6], "vis_processor": [0, 5], "vision": [0, 2], "visual": [0, 5, 7], "visual_input": 0, "visualstudio": 7, "vit": [0, 5], "vqa": [0, 5], "vram": 5, "vs_buildtool": 7, "wa": [0, 5, 7], "wai": [5, 6], "want": [5, 7], "warranti": 3, "we": [0, 5, 6], "wear": [0, 5, 7], "wears_mask": [0, 4, 5], "webp": [0, 5], "websit": 7, "well": 5, "wget": 6, "what": [2, 5], "when": [1, 5, 6, 7, 8], "where": [0, 1, 5, 7, 8], "whether": [0, 3], "which": [0, 5, 6, 7], "while": [0, 5], "white": [0, 7], "whitespac": 5, "whl": 7, "whole": 5, "whom": 3, "why": 5, "width": 0, "window": [1, 8], "wish": [1, 8], "without": [0, 3, 5, 7], "won": 7, "word": [0, 5, 7], "work": [0, 5, 6, 7], "world": 5, "worn": 5, "wrapper": 0, "write": [0, 2], "written": [0, 5], "wrong": 6, "x64": [0, 7], "x86": 7, "xl": 0, "xxl": 0, "y": [5, 6], "ye": 5, "yellow": [0, 7], "yet": 0, "you": [1, 5, 6, 7, 8], "your": [1, 2, 6, 7, 8], "zero": 5, "zip": 6}, "titles": ["text module", "Instructions how to generate and enable a google Cloud Vision API key", "Welcome to AMMICO\u2019s documentation!", "License", "AMMICO package modules", "AMMICO Demonstration Notebook", "Crop posts module", "AMMICO - AI Media and Misinformation Content Analysis Tool", "Instructions how to generate and enable a google Cloud Vision API key"], "titleterms": {"": 2, "0": 5, "1": [5, 7], "2": [5, 7], "3": [5, 7], "4": 5, "The": 5, "access": 7, "after": 7, "ai": 7, "all": 5, "ammico": [2, 4, 5, 7], "analys": 5, "analysi": [5, 7], "analyz": 5, "api": [1, 8], "ar": 7, "blip2": 5, "can": 7, "cloud": [1, 5, 7, 8], "color": [5, 7], "color_analysi": 0, "compat": 7, "contain": 5, "content": [2, 7], "convert": 5, "creat": 5, "crop": [6, 7], "croppost": 0, "csv": 5, "data": 5, "datafram": 5, "dataset": 5, "demonstr": 5, "detect": [5, 7], "detector": 5, "displai": 0, "document": 2, "don": 7, "emot": 7, "enabl": [1, 8], "environ": 7, "express": 5, "extract": [5, 7], "face": [0, 5], "facial": 5, "faq": 7, "featur": [5, 7], "file": 5, "first": 7, "folder": 5, "formul": 5, "from": 5, "further": 5, "gener": [1, 8], "googl": [1, 5, 7, 8], "graphic": 5, "happen": 7, "have": 7, "how": [1, 8], "http": 7, "hue": 7, "i": 7, "imag": [5, 7], "import": 5, "improv": 5, "index": 5, "indic": 2, "input": 5, "inspect": 5, "instal": 7, "instruct": [1, 8], "interfac": 5, "internet": 7, "kei": [1, 5, 8], "licens": 3, "media": 7, "micromamba": 7, "misinform": 7, "model": 5, "modul": [0, 4, 5, 6], "multimod": [0, 5], "notebook": 5, "org": 7, "output": 5, "packag": [4, 5, 7], "panda": 5, "pictur": 5, "pip": 7, "post": [6, 7], "prepar": 7, "problem": 7, "pytorch": 7, "queri": 5, "read": 5, "recognit": 7, "result": 5, "right": 7, "save": 5, "search": [0, 5], "second": 7, "select": 5, "sent": 7, "set": 5, "solv": 7, "step": 5, "still": 7, "summari": [0, 5], "t": 7, "tabl": 2, "tensorflow": 7, "test": 5, "text": [0, 5, 7], "tool": 7, "translat": [5, 7], "us": [5, 7], "usag": 7, "user": 5, "util": 0, "vision": [1, 5, 7, 8], "we": 7, "welcom": 2, "what": 7, "window": 7, "write": 5, "www": 7, "your": 5}})
\ No newline at end of file
+Search.setIndex({"alltitles": {"1. First, install tensorflow (https://www.tensorflow.org/install/pip)": [[7, "first-install-tensorflow-https-www-tensorflow-org-install-pip"]], "2. Second, install pytorch": [[7, "second-install-pytorch"]], "3. After we prepared right environment we can install the ammico package": [[7, "after-we-prepared-right-environment-we-can-install-the-ammico-package"]], "AMMICO - AI Media and Misinformation Content Analysis Tool": [[7, "ammico-ai-media-and-misinformation-content-analysis-tool"]], "AMMICO Demonstration Notebook": [[5, "AMMICO-Demonstration-Notebook"]], "AMMICO package modules": [[4, "ammico-package-modules"]], "BLIP2 models": [[5, "BLIP2-models"]], "Color analysis of pictures": [[5, "Color-analysis-of-pictures"]], "Color/hue detection": [[7, "color-hue-detection"]], "Compatibility problems solving": [[7, "compatibility-problems-solving"]], "Content extraction": [[7, "content-extraction"]], "Contents:": [[2, null]], "Crop posts module": [[6, "Crop-posts-module"]], "Cropping of posts": [[7, "cropping-of-posts"]], "Detection of faces and facial expression analysis": [[5, "Detection-of-faces-and-facial-expression-analysis"]], "Emotion recognition": [[7, "emotion-recognition"]], "Ethical disclosure statement": [[5, "Ethical-disclosure-statement"]], "FAQ": [[7, "faq"]], "Features": [[7, "features"]], "Formulate your search queries": [[5, "Formulate-your-search-queries"]], "Further detector modules": [[5, "Further-detector-modules"]], "Image Multimodal Search": [[5, "Image-Multimodal-Search"]], "Image summary and query": [[5, "Image-summary-and-query"]], "Import the ammico package.": [[5, "Import-the-ammico-package."]], "Improve the search results": [[5, "Improve-the-search-results"]], "Indexing and extracting features from images in selected folder": [[5, "Indexing-and-extracting-features-from-images-in-selected-folder"]], "Indices and tables": [[2, "indices-and-tables"]], "Installation": [[7, "installation"]], "Instructions how to generate and enable a google Cloud Vision API key": [[1, "instructions-how-to-generate-and-enable-a-google-cloud-vision-api-key"], [8, "instructions-how-to-generate-and-enable-a-google-cloud-vision-api-key"]], "License": [[3, "license"]], "Micromamba": [[7, "micromamba"]], "Read in a csv file containing text and translating/analysing the text": [[5, "Read-in-a-csv-file-containing-text-and-translating/analysing-the-text"]], "Save search results to csv": [[5, "Save-search-results-to-csv"]], "Step 0: Create and set a Google Cloud Vision Key": [[5, "Step-0:-Create-and-set-a-Google-Cloud-Vision-Key"]], "Step 1: Read your data into AMMICO": [[5, "Step-1:-Read-your-data-into-AMMICO"]], "Step 2: Inspect the input files using the graphical user interface": [[5, "Step-2:-Inspect-the-input-files-using-the-graphical-user-interface"]], "Step 3: Analyze all images": [[5, "Step-3:-Analyze-all-images"]], "Step 4: Convert analysis output to pandas dataframe and write csv": [[5, "Step-4:-Convert-analysis-output-to-pandas-dataframe-and-write-csv"]], "Text extraction": [[7, "text-extraction"]], "The detector modules": [[5, "The-detector-modules"]], "Usage": [[7, "usage"]], "Use a test dataset": [[5, "Use-a-test-dataset"]], "Welcome to AMMICO\u2019s documentation!": [[2, "welcome-to-ammico-s-documentation"]], "What happens if I don\u2019t have internet access - can I still use ammico?": [[7, "what-happens-if-i-don-t-have-internet-access-can-i-still-use-ammico"]], "What happens to the images that are sent to google Cloud Vision?": [[7, "what-happens-to-the-images-that-are-sent-to-google-cloud-vision"]], "What happens to the text that is sent to google Translate?": [[7, "what-happens-to-the-text-that-is-sent-to-google-translate"]], "Windows": [[7, "windows"]], "color_analysis module": [[0, "module-colors"]], "cropposts module": [[0, "module-cropposts"]], "display module": [[0, "module-display"]], "faces module": [[0, "module-faces"]], "multimodal search module": [[0, "module-multimodal_search"]], "summary module": [[0, "module-summary"]], "text module": [[0, "module-text"]], "utils module": [[0, "module-utils"]]}, "docnames": ["ammico", "create_API_key_link", "index", "license_link", "modules", "notebooks/DemoNotebook_ammico", "notebooks/Example cropposts", "readme_link", "set_up_credentials"], "envversion": {"nbsphinx": 4, "sphinx": 61, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2}, "filenames": ["ammico.rst", "create_API_key_link.md", "index.rst", "license_link.md", "modules.rst", "notebooks/DemoNotebook_ammico.ipynb", "notebooks/Example cropposts.ipynb", "readme_link.md", "set_up_credentials.md"], "indexentries": {"all_allowed_model_types (summary.summarydetector attribute)": [[0, "summary.SummaryDetector.all_allowed_model_types", false]], "allowed_analysis_types (summary.summarydetector attribute)": [[0, "summary.SummaryDetector.allowed_analysis_types", false]], "allowed_model_types (summary.summarydetector attribute)": [[0, "summary.SummaryDetector.allowed_model_types", false]], "allowed_new_model_types (summary.summarydetector attribute)": [[0, "summary.SummaryDetector.allowed_new_model_types", false]], "ammico_prefetch_models() (in module utils)": [[0, "utils.ammico_prefetch_models", false]], "analyse_image() (colors.colordetector method)": [[0, "colors.ColorDetector.analyse_image", false]], "analyse_image() (faces.emotiondetector method)": [[0, "faces.EmotionDetector.analyse_image", false]], "analyse_image() (summary.summarydetector method)": [[0, "summary.SummaryDetector.analyse_image", false]], "analyse_image() (text.textdetector method)": [[0, "text.TextDetector.analyse_image", false]], "analyse_image() (utils.analysismethod method)": [[0, "utils.AnalysisMethod.analyse_image", false]], "analyse_questions() (summary.summarydetector method)": [[0, "summary.SummaryDetector.analyse_questions", false]], "analyse_summary() (summary.summarydetector method)": [[0, "summary.SummaryDetector.analyse_summary", false]], "analyse_topic() (text.postprocesstext method)": [[0, "text.PostprocessText.analyse_topic", false]], "analysisexplorer (class in display)": [[0, "display.AnalysisExplorer", false]], "analysismethod (class in utils)": [[0, "utils.AnalysisMethod", false]], "analyze_single_face() (faces.emotiondetector method)": [[0, "faces.EmotionDetector.analyze_single_face", false]], "append_data_to_dict() (in module utils)": [[0, "utils.append_data_to_dict", false]], "check_for_missing_keys() (in module utils)": [[0, "utils.check_for_missing_keys", false]], "check_model() (summary.summarydetector method)": [[0, "summary.SummaryDetector.check_model", false]], "clean_subdict() (faces.emotiondetector method)": [[0, "faces.EmotionDetector.clean_subdict", false]], "clean_text() (text.textdetector method)": [[0, "text.TextDetector.clean_text", false]], "colordetector (class in colors)": [[0, "colors.ColorDetector", false]], "colors": [[0, "module-colors", false]], "compute_crop_corner() (in module cropposts)": [[0, "cropposts.compute_crop_corner", false]], "compute_gradcam_batch() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.compute_gradcam_batch", false]], "crop_image_from_post() (in module cropposts)": [[0, "cropposts.crop_image_from_post", false]], "crop_media_posts() (in module cropposts)": [[0, "cropposts.crop_media_posts", false]], "crop_posts_from_refs() (in module cropposts)": [[0, "cropposts.crop_posts_from_refs", false]], "crop_posts_image() (in module cropposts)": [[0, "cropposts.crop_posts_image", false]], "cropposts": [[0, "module-cropposts", false]], "deepface_symlink_processor() (in module faces)": [[0, "faces.deepface_symlink_processor", false]], "display": [[0, "module-display", false]], "downloadresource (class in utils)": [[0, "utils.DownloadResource", false]], "draw_matches() (in module cropposts)": [[0, "cropposts.draw_matches", false]], "dump_df() (in module utils)": [[0, "utils.dump_df", false]], "emotiondetector (class in faces)": [[0, "faces.EmotionDetector", false]], "ethical_disclosure() (in module faces)": [[0, "faces.ethical_disclosure", false]], "extract_image_features_basic() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.extract_image_features_basic", false]], "extract_image_features_blip2() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.extract_image_features_blip2", false]], "extract_image_features_clip() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.extract_image_features_clip", false]], "extract_text_features() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.extract_text_features", false]], "faces": [[0, "module-faces", false]], "facial_expression_analysis() (faces.emotiondetector method)": [[0, "faces.EmotionDetector.facial_expression_analysis", false]], "find_files() (in module utils)": [[0, "utils.find_files", false]], "get() (utils.downloadresource method)": [[0, "utils.DownloadResource.get", false]], "get_att_map() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.get_att_map", false]], "get_color_table() (in module utils)": [[0, "utils.get_color_table", false]], "get_dataframe() (in module utils)": [[0, "utils.get_dataframe", false]], "get_pathes_from_query() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.get_pathes_from_query", false]], "get_text_df() (text.postprocesstext method)": [[0, "text.PostprocessText.get_text_df", false]], "get_text_dict() (text.postprocesstext method)": [[0, "text.PostprocessText.get_text_dict", false]], "get_text_from_image() (text.textdetector method)": [[0, "text.TextDetector.get_text_from_image", false]], "image_text_match_reordering() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.image_text_match_reordering", false]], "initialize_dict() (in module utils)": [[0, "utils.initialize_dict", false]], "is_interactive() (in module utils)": [[0, "utils.is_interactive", false]], "iterable() (in module utils)": [[0, "utils.iterable", false]], "itm_text_precessing() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.itm_text_precessing", false]], "kp_from_matches() (in module cropposts)": [[0, "cropposts.kp_from_matches", false]], "load_feature_extractor_model_albef() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_feature_extractor_model_albef", false]], "load_feature_extractor_model_blip() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_feature_extractor_model_blip", false]], "load_feature_extractor_model_blip2() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_feature_extractor_model_blip2", false]], "load_feature_extractor_model_clip_base() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_feature_extractor_model_clip_base", false]], "load_feature_extractor_model_clip_vitl14() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_feature_extractor_model_clip_vitl14", false]], "load_feature_extractor_model_clip_vitl14_336() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_feature_extractor_model_clip_vitl14_336", false]], "load_model() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model", false]], "load_model_base() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_base", false]], "load_model_base_blip2_opt_caption_coco_opt67b() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_base_blip2_opt_caption_coco_opt67b", false]], "load_model_base_blip2_opt_pretrain_opt67b() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_base_blip2_opt_pretrain_opt67b", false]], "load_model_blip2_opt_caption_coco_opt27b() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_blip2_opt_caption_coco_opt27b", false]], "load_model_blip2_opt_pretrain_opt27b() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_blip2_opt_pretrain_opt27b", false]], "load_model_blip2_t5_caption_coco_flant5xl() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_blip2_t5_caption_coco_flant5xl", false]], "load_model_blip2_t5_pretrain_flant5xl() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_blip2_t5_pretrain_flant5xl", false]], "load_model_blip2_t5_pretrain_flant5xxl() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_blip2_t5_pretrain_flant5xxl", false]], "load_model_large() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_model_large", false]], "load_new_model() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_new_model", false]], "load_tensors() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.load_tensors", false]], "load_vqa_model() (summary.summarydetector method)": [[0, "summary.SummaryDetector.load_vqa_model", false]], "matching_points() (in module cropposts)": [[0, "cropposts.matching_points", false]], "module": [[0, "module-colors", false], [0, "module-cropposts", false], [0, "module-display", false], [0, "module-faces", false], [0, "module-multimodal_search", false], [0, "module-summary", false], [0, "module-text", false], [0, "module-utils", false]], "multimodal_device (multimodal_search.multimodalsearch attribute)": [[0, "multimodal_search.MultimodalSearch.multimodal_device", false]], "multimodal_search": [[0, "module-multimodal_search", false]], "multimodal_search() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.multimodal_search", false]], "multimodalsearch (class in multimodal_search)": [[0, "multimodal_search.MultimodalSearch", false]], "parsing_images() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.parsing_images", false]], "paste_image_and_comment() (in module cropposts)": [[0, "cropposts.paste_image_and_comment", false]], "postprocesstext (class in text)": [[0, "text.PostprocessText", false]], "querys_processing() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.querys_processing", false]], "read_and_process_images() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.read_and_process_images", false]], "read_and_process_images_itm() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.read_and_process_images_itm", false]], "read_csv() (text.textanalyzer method)": [[0, "text.TextAnalyzer.read_csv", false]], "read_img() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.read_img", false]], "remove_linebreaks() (text.textdetector method)": [[0, "text.TextDetector.remove_linebreaks", false]], "resize_img() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.resize_img", false]], "resources (utils.downloadresource attribute)": [[0, "utils.DownloadResource.resources", false]], "rgb2name() (colors.colordetector method)": [[0, "colors.ColorDetector.rgb2name", false]], "run_server() (display.analysisexplorer method)": [[0, "display.AnalysisExplorer.run_server", false]], "save_tensors() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.save_tensors", false]], "set_keys() (colors.colordetector method)": [[0, "colors.ColorDetector.set_keys", false]], "set_keys() (faces.emotiondetector method)": [[0, "faces.EmotionDetector.set_keys", false]], "set_keys() (text.textdetector method)": [[0, "text.TextDetector.set_keys", false]], "set_keys() (utils.analysismethod method)": [[0, "utils.AnalysisMethod.set_keys", false]], "show_results() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.show_results", false]], "summary": [[0, "module-summary", false]], "summarydetector (class in summary)": [[0, "summary.SummaryDetector", false]], "text": [[0, "module-text", false]], "text_ner() (text.textdetector method)": [[0, "text.TextDetector.text_ner", false]], "text_sentiment_transformers() (text.textdetector method)": [[0, "text.TextDetector.text_sentiment_transformers", false]], "text_summary() (text.textdetector method)": [[0, "text.TextDetector.text_summary", false]], "textanalyzer (class in text)": [[0, "text.TextAnalyzer", false]], "textdetector (class in text)": [[0, "text.TextDetector", false]], "translate_text() (text.textdetector method)": [[0, "text.TextDetector.translate_text", false]], "update_picture() (display.analysisexplorer method)": [[0, "display.AnalysisExplorer.update_picture", false]], "upload_model_blip2_coco() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.upload_model_blip2_coco", false]], "upload_model_blip_base() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.upload_model_blip_base", false]], "upload_model_blip_large() (multimodal_search.multimodalsearch method)": [[0, "multimodal_search.MultimodalSearch.upload_model_blip_large", false]], "utils": [[0, "module-utils", false]], "wears_mask() (faces.emotiondetector method)": [[0, "faces.EmotionDetector.wears_mask", false]]}, "objects": {"": [[0, 0, 0, "-", "colors"], [0, 0, 0, "-", "cropposts"], [0, 0, 0, "-", "display"], [0, 0, 0, "-", "faces"], [0, 0, 0, "-", "multimodal_search"], [0, 0, 0, "-", "summary"], [0, 0, 0, "-", "text"], [0, 0, 0, "-", "utils"]], "colors": [[0, 1, 1, "", "ColorDetector"]], "colors.ColorDetector": [[0, 2, 1, "", "analyse_image"], [0, 2, 1, "", "rgb2name"], [0, 2, 1, "", "set_keys"]], "cropposts": [[0, 3, 1, "", "compute_crop_corner"], [0, 3, 1, "", "crop_image_from_post"], [0, 3, 1, "", "crop_media_posts"], [0, 3, 1, "", "crop_posts_from_refs"], [0, 3, 1, "", "crop_posts_image"], [0, 3, 1, "", "draw_matches"], [0, 3, 1, "", "kp_from_matches"], [0, 3, 1, "", "matching_points"], [0, 3, 1, "", "paste_image_and_comment"]], "display": [[0, 1, 1, "", "AnalysisExplorer"]], "display.AnalysisExplorer": [[0, 2, 1, "", "run_server"], [0, 2, 1, "", "update_picture"]], "faces": [[0, 1, 1, "", "EmotionDetector"], [0, 3, 1, "", "deepface_symlink_processor"], [0, 3, 1, "", "ethical_disclosure"]], "faces.EmotionDetector": [[0, 2, 1, "", "analyse_image"], [0, 2, 1, "", "analyze_single_face"], [0, 2, 1, "", "clean_subdict"], [0, 2, 1, "", "facial_expression_analysis"], [0, 2, 1, "", "set_keys"], [0, 2, 1, "", "wears_mask"]], "multimodal_search": [[0, 1, 1, "", "MultimodalSearch"]], "multimodal_search.MultimodalSearch": [[0, 2, 1, "", "compute_gradcam_batch"], [0, 2, 1, "", "extract_image_features_basic"], [0, 2, 1, "", "extract_image_features_blip2"], [0, 2, 1, "", "extract_image_features_clip"], [0, 2, 1, "", "extract_text_features"], [0, 2, 1, "", "get_att_map"], [0, 2, 1, "", "get_pathes_from_query"], [0, 2, 1, "", "image_text_match_reordering"], [0, 2, 1, "", "itm_text_precessing"], [0, 2, 1, "", "load_feature_extractor_model_albef"], [0, 2, 1, "", "load_feature_extractor_model_blip"], [0, 2, 1, "", "load_feature_extractor_model_blip2"], [0, 2, 1, "", "load_feature_extractor_model_clip_base"], [0, 2, 1, "", "load_feature_extractor_model_clip_vitl14"], [0, 2, 1, "", "load_feature_extractor_model_clip_vitl14_336"], [0, 2, 1, "", "load_tensors"], [0, 4, 1, "", "multimodal_device"], [0, 2, 1, "", "multimodal_search"], [0, 2, 1, "", "parsing_images"], [0, 2, 1, "", "querys_processing"], [0, 2, 1, "", "read_and_process_images"], [0, 2, 1, "", "read_and_process_images_itm"], [0, 2, 1, "", "read_img"], [0, 2, 1, "", "resize_img"], [0, 2, 1, "", "save_tensors"], [0, 2, 1, "", "show_results"], [0, 2, 1, "", "upload_model_blip2_coco"], [0, 2, 1, "", "upload_model_blip_base"], [0, 2, 1, "", "upload_model_blip_large"]], "summary": [[0, 1, 1, "", "SummaryDetector"]], "summary.SummaryDetector": [[0, 4, 1, "", "all_allowed_model_types"], [0, 4, 1, "", "allowed_analysis_types"], [0, 4, 1, "", "allowed_model_types"], [0, 4, 1, "", "allowed_new_model_types"], [0, 2, 1, "", "analyse_image"], [0, 2, 1, "", "analyse_questions"], [0, 2, 1, "", "analyse_summary"], [0, 2, 1, "", "check_model"], [0, 2, 1, "", "load_model"], [0, 2, 1, "", "load_model_base"], [0, 2, 1, "", "load_model_base_blip2_opt_caption_coco_opt67b"], [0, 2, 1, "", "load_model_base_blip2_opt_pretrain_opt67b"], [0, 2, 1, "", "load_model_blip2_opt_caption_coco_opt27b"], [0, 2, 1, "", "load_model_blip2_opt_pretrain_opt27b"], [0, 2, 1, "", "load_model_blip2_t5_caption_coco_flant5xl"], [0, 2, 1, "", "load_model_blip2_t5_pretrain_flant5xl"], [0, 2, 1, "", "load_model_blip2_t5_pretrain_flant5xxl"], [0, 2, 1, "", "load_model_large"], [0, 2, 1, "", "load_new_model"], [0, 2, 1, "", "load_vqa_model"]], "text": [[0, 1, 1, "", "PostprocessText"], [0, 1, 1, "", "TextAnalyzer"], [0, 1, 1, "", "TextDetector"]], "text.PostprocessText": [[0, 2, 1, "", "analyse_topic"], [0, 2, 1, "", "get_text_df"], [0, 2, 1, "", "get_text_dict"]], "text.TextAnalyzer": [[0, 2, 1, "", "read_csv"]], "text.TextDetector": [[0, 2, 1, "", "analyse_image"], [0, 2, 1, "", "clean_text"], [0, 2, 1, "", "get_text_from_image"], [0, 2, 1, "", "remove_linebreaks"], [0, 2, 1, "", "set_keys"], [0, 2, 1, "", "text_ner"], [0, 2, 1, "", "text_sentiment_transformers"], [0, 2, 1, "", "text_summary"], [0, 2, 1, "", "translate_text"]], "utils": [[0, 1, 1, "", "AnalysisMethod"], [0, 1, 1, "", "DownloadResource"], [0, 3, 1, "", "ammico_prefetch_models"], [0, 3, 1, "", "append_data_to_dict"], [0, 3, 1, "", "check_for_missing_keys"], [0, 3, 1, "", "dump_df"], [0, 3, 1, "", "find_files"], [0, 3, 1, "", "get_color_table"], [0, 3, 1, "", "get_dataframe"], [0, 3, 1, "", "initialize_dict"], [0, 3, 1, "", "is_interactive"], [0, 3, 1, "", "iterable"]], "utils.AnalysisMethod": [[0, 2, 1, "", "analyse_image"], [0, 2, 1, "", "set_keys"]], "utils.DownloadResource": [[0, 2, 1, "", "get"], [0, 4, 1, "", "resources"]]}, "objnames": {"0": ["py", "module", "Python module"], "1": ["py", "class", "Python class"], "2": ["py", "method", "Python method"], "3": ["py", "function", "Python function"], "4": ["py", "attribute", "Python attribute"]}, "objtypes": {"0": "py:module", "1": "py:class", "2": "py:method", "3": "py:function", "4": "py:attribute"}, "terms": {"": 5, "0": [0, 2, 7], "00": 6, "03": 5, "1": [0, 1, 2, 8], "10": [5, 6, 7], "100": [0, 5, 6], "1000": [1, 8], "11": 7, "12": [5, 7], "14": 0, "15": [5, 6], "16": 5, "163": 7, "19": 0, "1976": 0, "2": [0, 2], "20": [0, 5], "2022": [3, 7], "2023": 5, "20gb": 5, "23": 7, "240": 0, "240p": 0, "27": 5, "28": 5, "3": [0, 2], "30": [0, 5], "336": 0, "35": 5, "3_non": 5, "4": [2, 7], "5": [0, 5], "50": [0, 1, 5, 8], "5_clip_base_saved_features_imag": 5, "6": [0, 5, 7], "60gb": 5, "61": [5, 6], "7": 7, "7b": [0, 5], "8": [0, 7], "8050": 0, "8055": 5, "8057": 5, "9": 0, "981aa55a3b13": 5, "A": [0, 3, 5], "AND": 3, "AS": 3, "And": 5, "BE": 3, "BUT": 3, "Be": 7, "But": 5, "By": 5, "FOR": 3, "For": [5, 7], "IN": 3, "If": [0, 5, 6, 7], "In": [1, 5, 7, 8], "It": [1, 5, 6, 7, 8], "NO": 3, "NOT": 3, "No": 5, "OF": 3, "OR": 3, "One": 0, "Or": [1, 5, 8], "THE": 3, "TO": 3, "That": 5, "The": [0, 1, 2, 3, 6, 7, 8], "Then": 5, "There": 7, "These": [0, 5, 7], "To": [0, 5, 7], "WITH": 3, "With": 5, "_": 5, "__file__": 7, "_saved_features_imag": 5, "a100": 5, "a4f8f3": 5, "ab": 5, "about": [0, 5, 7], "abov": [3, 5, 7], "abus": 7, "accept": [0, 5], "accept_disclosur": [0, 5], "access": 2, "accord": 7, "account": [1, 7, 8], "accur": [5, 7], "action": 3, "activ": 7, "ad": 5, "adapt": 5, "add": [5, 7], "addendum": 7, "addit": 0, "advanc": 5, "af0f99b": 5, "after": [1, 5, 8], "ag": [5, 7], "again": 5, "age_threshold": [0, 5], "ai": 2, "albef": 5, "albef_feature_extractor": 0, "algorithm": [0, 5], "all": [0, 2, 3], "all_allowed_model_typ": [0, 4], "allow": [0, 5, 7], "allowed_analysis_typ": [0, 4], "allowed_model_typ": [0, 4], "allowed_new_model_typ": [0, 4], "along": 5, "alreadi": 5, "also": [0, 5, 7], "altern": 5, "american": 5, "ammico": [0, 1, 6, 8], "ammico_data_hom": 5, "ammico_env": 7, "ammico_prefetch_model": [0, 4], "among": 5, "an": [0, 3, 5, 6, 7], "analis": 0, "analys": [0, 2, 7], "analyse_imag": [0, 4, 5], "analyse_quest": [0, 4], "analyse_summari": [0, 4], "analyse_text": [0, 5, 7], "analyse_top": [0, 4], "analysi": [0, 2], "analysis_explor": 5, "analysis_typ": [0, 5], "analysisexplor": [0, 4, 5], "analysismethod": [0, 4], "analyz": [0, 2, 7], "analyze_single_fac": [0, 4], "analyze_text": 0, "anger": 5, "angri": 5, "ani": [0, 1, 3, 5, 7, 8], "anoth": 7, "answer": [0, 5, 7], "api": [0, 2, 5, 7], "app": 5, "append": 0, "append_data_to_dict": [0, 4, 5], "appli": 5, "applic": 6, "approach": 5, "appropri": 0, "approxim": 5, "ar": [0, 2, 5, 6], "architectur": 0, "archiv": 6, "area": 0, "arg": 0, "argument": 5, "aris": 3, "around": [0, 7], "arrai": 0, "art": 7, "as_posix": 6, "asian": 5, "ask": [0, 5], "assign": 5, "associ": [3, 5], "asyncbatchannotatefil": 7, "asyncbatchannotateimag": 7, "asynchron": 7, "att_map": 0, "attent": 0, "author": 3, "automat": [5, 7], "avail": [5, 7], "avif": [0, 5], "avoid": 7, "awar": 5, "b": 5, "back": [0, 1, 8], "background": 5, "bar": 5, "base": [0, 5, 7], "base_coco": 0, "bashr": 5, "batch": [0, 6, 7], "batch_siz": [0, 5], "batchannotatefil": 7, "batchannotateimag": 7, "becaus": [0, 5], "bee": 0, "been": [1, 5, 8], "befor": [0, 5, 7], "being": 5, "below": [0, 5, 6, 7], "bert": 5, "bertop": 0, "best": [5, 7], "best_simularity_value_in_current_search": 5, "better": 5, "between": [0, 5, 7], "beyond": 0, "bigger": 5, "bill": [1, 8], "binari": 0, "bit": 5, "black": [0, 7], "blank": [1, 8], "blip": 5, "blip2": 0, "blip2_coco": [0, 5], "blip2_feature_extractor": 0, "blip2_image_text_match": 0, "blip2_opt_caption_coco_opt2": [0, 5], "blip2_opt_caption_coco_opt6": [0, 5], "blip2_opt_pretrain_opt2": [0, 5], "blip2_opt_pretrain_opt6": [0, 5], "blip2_t5_caption_coco_flant5xl": [0, 5], "blip2_t5_pretrain_flant5xl": [0, 5], "blip2_t5_pretrain_flant5xxl": [0, 5], "blip_bas": 5, "blip_capt": 0, "blip_feature_extractor": 0, "blip_image_text_match": 0, "blip_larg": 5, "blip_vqa": 0, "block": 0, "block_num": 0, "blue": [0, 7], "blur": 0, "bool": [0, 5], "both": [5, 7], "briefli": 7, "bring": [1, 8], "brown": [0, 7], "browser": [1, 8], "build": 7, "c": [0, 3, 7], "calcul": 5, "call": [5, 7], "callback": 0, "campaign": 5, "can": [0, 1, 2, 5, 6, 8], "capabl": 5, "caption": [0, 5, 7], "caption_coco_": 5, "caption_coco_flant5xl": 0, "caption_coco_opt2": 0, "caption_coco_opt6": 0, "card": 5, "care": 7, "carri": [5, 6, 7], "case": 5, "categor": [0, 6], "categori": 5, "cell": [5, 6], "chang": 5, "channel": 7, "charg": [1, 3, 8], "check": [0, 5, 6, 7], "check_for_missing_kei": [0, 4], "check_model": [0, 4], "checkpoint": 5, "choos": [5, 7], "chosen": 0, "cie": 0, "citi": 5, "claim": 3, "class": [0, 5], "classif": [0, 5], "classifi": 7, "clean": [0, 5, 7], "clean_subdict": [0, 4], "clean_text": [0, 4], "cli": [0, 5], "click": [1, 5, 8], "clip_bas": 5, "clip_feature_extractor": 0, "clip_vitl14": 5, "clip_vitl14_336": 5, "closest": 0, "cloud": [0, 2], "cnn": 5, "coco": [0, 5], "code": [5, 6], "colab": [5, 6, 7], "colaboratori": [1, 8], "collect": 7, "color": [0, 2], "color_analysi": [2, 4], "color_bgr2rgb": 6, "colordetector": [0, 4, 5], "colorgram": [0, 5, 7], "colour": [5, 7], "column": [0, 5, 7], "column_kei": [0, 5], "com": [5, 6, 7], "combat": 7, "combin": 5, "come": 5, "command": 7, "comment": [0, 6, 7], "common": 0, "compat": 2, "complet": 5, "compli": 7, "compon": 7, "comput": [0, 1, 5, 8], "computation": 5, "compute_crop_corn": [0, 4], "compute_gradcam_batch": [0, 4], "conceal": 5, "conda": [5, 7], "conda_prefix": 7, "condit": 3, "confer": 5, "confid": 5, "conll03": 5, "connect": [3, 5, 7], "consequenti": 0, "consequential_quest": [0, 5], "consid": [0, 5], "consist": 5, "consol": [1, 8], "const_image_summari": 5, "constant": [0, 5], "contain": [0, 2, 7], "content": [5, 6], "context": 5, "contract": 3, "contrib": 6, "conveni": 5, "convert": [0, 2], "coordin": 0, "copi": 3, "copyright": 3, "corner": [0, 1, 8], "correct": [5, 7], "correspond": 5, "cosequential_quest": 5, "could": 5, "count": 5, "countri": 5, "cover": 5, "cpp": 7, "cpu": [0, 5], "creat": [0, 1, 2, 7, 8], "creation": 5, "crop": [0, 2, 5], "crop_dir": 6, "crop_image_from_post": [0, 4], "crop_media_post": [0, 4, 6], "crop_post": 0, "crop_posts_from_ref": [0, 4, 6], "crop_posts_imag": [0, 4], "crop_view": [0, 6], "croppost": [2, 4, 6, 7], "crpo": 6, "css3": 0, "csv": [0, 2, 7], "csv_encod": 0, "csv_path": [0, 5], "cu11": 7, "cu118": 7, "cuda": [0, 5, 7], "cudatoolkit": 7, "cudnn": 7, "cudnn_path": 7, "current": [0, 1, 7, 8], "current_simularity_valu": 5, "cut": 0, "cv2": [0, 6], "cvtcolor": 6, "cyan": [0, 7], "d": [6, 7], "damag": 3, "dash": [0, 5], "dashboard": [1, 8], "data": [0, 2, 6, 7], "data_out": 5, "data_path": 5, "databas": 7, "datafram": [0, 2], "dataset": 2, "dbmdz": 5, "deactiv": 7, "deal": 3, "deepfac": [5, 7], "deepface_symlink_processor": [0, 4], "default": [0, 5], "defin": 5, "delet": 7, "delta": 0, "delta_e_method": 0, "demand": [0, 5], "demonstr": [2, 7], "depend": [5, 7], "dependend": 5, "depth": 7, "describ": 7, "descript": [5, 7], "descriptor": 0, "desir": 5, "detail": 5, "detect": [0, 2], "detector": [2, 7], "determin": [0, 5], "determinist": 0, "deterministic_summari": 5, "develop": [5, 7], "devic": 0, "device_typ": [0, 5], "df": 5, "dict": [0, 5], "dictionari": [0, 5], "differ": [5, 6], "directli": [1, 5, 8], "directori": [0, 5], "dirnam": 7, "discard": 5, "disclosur": 0, "disclosure_ammico": [0, 5], "disgust": 5, "disk": 7, "displai": [2, 4, 5], "distanc": 7, "distilbart": 5, "distilbert": 5, "distribut": 3, "dmatch": 0, "do": [3, 5, 7], "document": 3, "doe": [0, 5, 7], "doesn": 6, "dog": 5, "domin": 5, "don": 2, "done": [1, 5, 6, 7, 8], "dopamin": 5, "dot": [1, 8], "down": [1, 8], "download": [0, 1, 5, 7, 8], "downloadresourc": [0, 4], "draw_match": [0, 4], "drive": [1, 5, 6, 7, 8], "drop": [1, 8], "dropdown": 5, "due": [5, 6], "dump": [0, 5], "dump_df": [0, 4, 5], "dump_everi": 5, "dump_fil": 5, "e": [0, 7], "each": [0, 5], "easi": 5, "easier": 6, "easili": 5, "echo": 7, "either": [0, 5], "element": [5, 7], "emot": 5, "emotion_threshold": [0, 5], "emotiondetector": [0, 4, 5], "emotitiondetector": 5, "empti": [0, 5], "enabl": [2, 5, 7], "english": [0, 5, 7], "ensur": 5, "enter": [1, 8], "entiti": [0, 5, 7], "entity_typ": 5, "entri": [0, 5], "enumer": 5, "env_var": 7, "environ": [0, 5], "envorin": 5, "equip": 5, "error": [0, 5, 7], "estim": 0, "etc": 7, "ethic": 0, "ethical_disclosur": [0, 4, 5], "ethnic": 5, "even": 5, "event": 3, "everi": 5, "everyth": 6, "ex": 7, "exampl": [5, 6], "exclud": 0, "execut": [5, 6], "exist": 5, "exist_ok": 5, "experiment": [5, 7], "explain": 5, "explicitli": 5, "explor": [0, 5], "export": [5, 7], "express": [0, 2, 3, 7], "ext": 0, "extens": [5, 7], "extra": 6, "extrac": 7, "extract": 0, "extract_image_features_bas": [0, 4], "extract_image_features_blip2": [0, 4], "extract_image_features_clip": [0, 4], "extract_text_featur": [0, 4], "f": 6, "f2482bf": 5, "face": [2, 4, 7], "facial": [0, 2, 7], "facial_expression_analysi": [0, 4], "failsaf": 7, "fals": [0, 5, 6], "faq": 2, "fast": 5, "fear": 5, "featur": [0, 2], "feature_extractor": 0, "features_image_stack": [0, 5], "features_text": 0, "few": [5, 7], "field": 0, "figsiz": 6, "figur": 6, "file": [0, 1, 2, 3, 6, 7, 8], "filelist": 0, "filenam": [0, 5], "filepath": 0, "fill": 5, "filter": [0, 5], "filter_number_of_imag": [0, 5], "filter_rel_error": [0, 5], "filter_val_limit": [0, 5], "final_h": 0, "find": [0, 5, 6, 7], "find_fil": [0, 4, 5, 6], "fine": [5, 6], "finetun": 5, "first": [0, 1, 5, 6, 8], "fit": 3, "flag": 5, "flake8": [5, 6], "flan": 0, "flant5": 5, "flant5xl": 5, "flant5xxl": 5, "flex": 5, "float": [0, 5], "folder": [1, 6, 7, 8], "follow": [1, 3, 5, 7, 8], "forg": 7, "form": [0, 5], "format": [0, 5], "found": [0, 5, 6, 7], "fraction": 5, "frame": 0, "framework": 7, "frankfurt": 5, "free": [0, 1, 3, 8], "frequent": 0, "from": [0, 1, 3, 6, 7, 8], "full": 5, "function": [0, 5], "furnish": 3, "further": [2, 7], "g": 7, "gate": 5, "gb": [5, 7], "gbq": 5, "gender": [5, 7], "gender_threshold": [0, 5], "gener": [0, 2, 5, 7], "get": [0, 1, 4, 5, 7, 8], "get_att_map": [0, 4], "get_color_t": [0, 4], "get_datafram": [0, 4, 5], "get_ipython": [5, 6], "get_pathes_from_queri": [0, 4], "get_text_df": [0, 4], "get_text_dict": [0, 4], "get_text_from_imag": [0, 4], "gif": [0, 5], "git": [5, 6], "github": [5, 6], "give": 5, "given": [0, 5, 6], "global": 0, "go": [1, 8], "googl": [0, 2, 6], "google_application_credenti": [5, 7], "googletran": [5, 7], "gpu": [5, 7], "gradcam": 0, "grant": 3, "graphic": 2, "green": [0, 7], "grei": [0, 7], "h_margin": 0, "ha": [1, 5, 8], "happen": 2, "happi": 5, "have": [2, 5], "head": [5, 6], "heat": 5, "heavi": 5, "held": 7, "here": [1, 5, 7, 8], "herebi": 3, "high": 5, "hold": 5, "holder": 3, "horizont": 0, "hostedtoolcach": 0, "hour": 7, "how": [2, 5], "howev": 5, "hpc": 5, "http": [5, 6], "hug": 7, "huggingfac": 5, "human": 5, "i": [0, 1, 2, 3, 5, 6, 8], "id": [0, 1, 5, 8], "ideal": 5, "identifi": 5, "ignor": [0, 6], "imag": [0, 1, 2, 6, 8], "image_df": 5, "image_dict": 5, "image_example_path": 5, "image_example_queri": 5, "image_gradcam_with_itm": [0, 5], "image_kei": [0, 5], "image_nam": [0, 5], "image_path": 0, "image_summary_detector": 5, "image_summary_vqa_detector": 5, "image_text_match_reord": [0, 4, 5], "images_tensor": 0, "img": [0, 5], "img1": 0, "img2": 0, "img_path": 0, "immedi": 7, "imperfect": 6, "implement": 5, "impli": 3, "import": [2, 6, 7], "importlib_resourc": [5, 6], "improp": 6, "improv": 7, "imread": 6, "imshow": 6, "includ": [0, 3, 5], "incompat": 5, "increment": 5, "index": [0, 2, 7], "indic": 0, "inform": [1, 6, 7, 8], "inherit": 0, "iniati": 5, "init": 5, "initi": [0, 5, 7], "initialize_dict": [0, 4], "input": [0, 2, 7], "insid": 5, "inspect": 2, "instal": [2, 5, 6], "instanc": 5, "instead": 5, "instruct": [2, 5, 7], "int": [0, 5], "intellig": 7, "intens": 5, "interact": [0, 5], "interfac": 2, "internet": 2, "ipynb": 7, "is_interact": [0, 4], "isdir": 6, "item": [5, 6], "iter": [0, 4], "itm": [0, 5], "itm_model": [0, 5], "itm_model_typ": 0, "itm_scor": 5, "itm_scores2": 0, "itm_text_precess": [0, 4], "its": [5, 7], "iulusoi": 5, "jpeg": [0, 5], "jpg": [0, 5], "json": [1, 5, 7, 8], "jupyt": [1, 5, 8], "just": [0, 5, 7], "k": 5, "keep": 6, "kei": [0, 2, 7], "keypoint": 0, "keyword": [5, 7], "kind": 3, "kp1": 0, "kp2": 0, "kp_from_match": [0, 4], "kwarg": 0, "l": [0, 5], "languag": [0, 5, 7], "larg": [0, 5, 7], "large_coco": 0, "largest": 5, "later": 0, "latest": 6, "latter": [5, 7], "launch": 5, "lavi": [0, 5, 7], "ld_library_path": 7, "left": [1, 5, 8], "lemma": 7, "len": 5, "length": 0, "less": 5, "liabil": 3, "liabl": 3, "lib": [0, 7], "librari": [0, 5, 6, 7], "licens": 2, "lida": 5, "like": [1, 5, 8], "likelihood": 5, "limit": [0, 3, 5, 6], "line": [5, 6], "linebreak": [0, 5], "list": [0, 1, 5, 8], "list_of_quest": [0, 5], "live": 7, "llm": 5, "load": [0, 5, 6], "load_dataset": 5, "load_feature_extractor_model_albef": [0, 4], "load_feature_extractor_model_blip": [0, 4], "load_feature_extractor_model_blip2": [0, 4], "load_feature_extractor_model_clip_bas": [0, 4], "load_feature_extractor_model_clip_vitl14": [0, 4], "load_feature_extractor_model_clip_vitl14_336": [0, 4], "load_model": [0, 4], "load_model_bas": [0, 4], "load_model_base_blip2_opt_caption_coco_opt67b": [0, 4], "load_model_base_blip2_opt_pretrain_opt67b": [0, 4], "load_model_blip2_opt_caption_coco_opt27b": [0, 4], "load_model_blip2_opt_pretrain_opt27b": [0, 4], "load_model_blip2_t5_caption_coco_flant5xl": [0, 4], "load_model_blip2_t5_pretrain_flant5xl": [0, 4], "load_model_blip2_t5_pretrain_flant5xxl": [0, 4], "load_model_larg": [0, 4], "load_new_model": [0, 4], "load_tensor": [0, 4], "load_vqa_model": [0, 4], "local": [5, 7], "locat": [5, 7], "log": 7, "login": 5, "look": [0, 1, 5, 6, 8], "loop": 5, "lower": 5, "m": 7, "machin": [5, 7], "made": [5, 7], "mai": [5, 7], "main": [5, 7], "make": [1, 5, 7, 8], "man": 5, "manag": [1, 8], "mani": 5, "manual": 6, "map": [0, 5], "margin": 0, "mask": [0, 5, 7], "match": [0, 5, 6, 7], "matching_point": [0, 4], "matplotlib": 6, "maximum": [0, 5], "mean": 5, "media": [0, 2, 5, 6], "medicin": 5, "memori": [5, 7], "menu": [1, 5, 8], "merchant": 3, "merg": [0, 3], "merge_color": 0, "messag": 5, "metadata": 7, "method": [0, 5], "metric": [0, 7], "microsoft": 7, "might": 0, "min_match": 0, "minimum": [0, 5], "misinform": [2, 5], "miss": 0, "mit": 3, "mkdir": [5, 7], "model": [0, 7], "model_nam": [0, 5], "model_old": 0, "model_typ": [0, 5], "modifi": 3, "modul": [2, 7], "moment": 5, "month": [1, 8], "moral": 6, "more": [1, 5, 7, 8], "most": [0, 5], "mount": [5, 6], "msvc": 7, "much": 5, "multi_features_stack": 0, "multimod": [2, 4, 7], "multimodal_devic": [0, 4], "multimodal_search": [0, 4, 5, 7], "multimodalsearch": [0, 4, 5], "multipl": 5, "multiple_fac": 5, "must": 7, "mv": 6, "my_obj": 5, "mydict": [0, 5], "mydriv": 5, "n": [0, 5, 7], "n_color": 0, "name": [0, 1, 5, 6, 7, 8], "natur": 0, "ndarrai": 0, "necessari": [5, 7], "need": [0, 5, 7], "need_grad_cam": [0, 5], "neg": 5, "ner": 5, "nest": [0, 5], "neutral": 5, "new": [0, 1, 5, 7, 8], "next": 5, "nn": 0, "no_fac": 5, "non": 0, "nondeterministic_summari": 0, "none": [0, 5], "noninfring": 3, "noqa": [5, 6], "note": 5, "notebook": [1, 2, 6, 7, 8], "notic": 3, "now": [1, 5, 6, 8], "np": 0, "num": 5, "number": [0, 5, 7], "number_of_imag": 5, "numer": 5, "numpi": [0, 7], "nvidia": 7, "o": [5, 6, 7], "obj": 5, "object": [0, 5], "obtain": 3, "occur": 0, "off": 0, "offlin": 7, "old": 0, "onc": 5, "one": [0, 5, 7], "ones": 5, "onli": [0, 5, 6, 7], "onlin": 7, "open": 5, "opencv": 6, "oper": 7, "opt": [0, 5], "optim": 5, "option": [0, 5, 7], "orang": [0, 7], "orbax": 5, "order": [5, 7], "origin": [0, 5, 6], "other": [0, 3, 5, 7], "otherwis": [0, 3, 5], "our": [5, 7], "out": [1, 3, 5, 6, 7, 8], "outdict": 5, "output": [0, 2], "outsid": 5, "overal": 5, "overlap": 0, "own": 5, "p": [0, 7], "packag": [0, 2, 6], "page": [1, 2, 7, 8], "paid": 5, "panda": 2, "paper": 7, "paramet": [0, 5], "parent": 5, "pars": 0, "parsing_imag": [0, 4, 5], "part": [0, 6, 7], "parti": 7, "partial": 5, "particular": 3, "pass": 5, "past": 0, "paste_image_and_com": [0, 4], "path": [0, 5, 6], "path_post": 6, "path_ref": 6, "path_to_load_tensor": [0, 5], "path_to_save_tensor": [0, 5], "pathlib": 5, "patient": 5, "pattern": [0, 5], "peopl": 5, "per": [1, 8], "percentag": [0, 5, 7], "perform": [0, 5, 7], "period": 7, "perman": 5, "permiss": 3, "permit": 3, "persist": 7, "person": [3, 5, 7], "pick": [1, 8], "pictur": [0, 2], "pil": 0, "pin": 6, "pink": [0, 7], "pip": [5, 6], "pipelin": [0, 5, 7], "pkg": [5, 6], "place": [1, 5, 7, 8], "pleas": [5, 6, 7], "plot": 6, "plt": 6, "plt_crop": [0, 6], "plt_imag": [0, 6], "plt_match": [0, 6], "png": [0, 5, 6], "pngimageplugin": 0, "point": 0, "polar": 7, "politician": 5, "pooch": 0, "pop": [1, 5, 8], "port": [0, 5], "portion": 3, "posit": [0, 5], "possibl": [5, 7], "post": [0, 2, 5], "postprocesstext": [0, 4], "pre": [5, 7], "predict": [5, 7], "prefetch": 0, "prefix": 0, "prepar": 5, "preprocessor": 0, "presenc": [5, 7], "present": [0, 5], "preserv": 5, "press": 5, "pretrain": [0, 5], "pretrain_": 5, "pretrain_opt2": 0, "pretrain_opt6": 0, "prevent": [6, 7], "previou": 5, "primari": 5, "print": [6, 7], "prioriti": 7, "privat": [1, 5, 8], "probabl": 5, "problem": [0, 2], "process": [0, 1, 5, 7, 8], "product": 5, "profil": 5, "progress": 5, "project": [1, 7, 8], "prompt": [1, 5, 8], "proper": 7, "proport": 0, "provid": [0, 3, 5, 6, 7], "pt": [0, 5], "public": 7, "publish": 3, "purpl": [0, 7], "purpos": [3, 5], "put": [0, 7], "py": [0, 7], "pycocotool": 7, "pyplot": 6, "python": [0, 1, 5, 6, 7, 8], "python3": 0, "q": 6, "qq": 6, "qqq": [5, 6], "queri": [0, 2, 7], "querys_process": [0, 4], "question": [0, 5, 7], "quit": 5, "race": [5, 7], "race_threshold": [0, 5], "ram": 5, "random": [0, 5], "random_se": [0, 5], "rank": 5, "raw_imag": 0, "raw_img": 0, "re": [5, 6, 7], "read": [0, 2], "read_and_process_imag": [0, 4], "read_and_process_images_itm": [0, 4], "read_csv": [0, 4, 5], "read_img": [0, 4], "receiv": 7, "recogn": 7, "recognit": [0, 5], "recurs": [0, 5], "red": [0, 7], "reduc": [0, 5], "ref": [5, 6], "ref_dir": 6, "ref_fil": [0, 6], "ref_view": [0, 6], "refer": [0, 1, 5, 6, 8], "region": [0, 6], "regist": 0, "reject": 5, "rel": 0, "relev": 5, "rememb": 5, "remot": 0, "remov": [0, 6, 7], "remove_linebreak": [0, 4], "reorder": 0, "report": 5, "repositori": 5, "represent": 5, "request": 7, "requir": [0, 5, 7], "rerun": 5, "resiz": 0, "resize_img": [0, 4], "resized_imag": 0, "resourc": [0, 4, 5], "respect": 5, "respond": 5, "respons": 7, "restart": 5, "restrict": [3, 7], "result": [0, 7], "retinafac": [5, 7], "return": [0, 5, 7], "return_top": 0, "revis": 5, "revision_numb": [0, 5], "rf": 6, "rgb": 0, "rgb2name": [0, 4], "rgb_ref_view": 6, "rgb_view": 6, "right": [1, 3, 5, 8], "rl": 5, "rm": 6, "row": 5, "run": [0, 1, 5, 6, 7, 8], "run_serv": [0, 4, 5], "runtim": 5, "sad": 5, "same": [5, 6, 7], "sampl": [6, 7], "save": [0, 6], "save_crop_dir": [0, 6], "save_tensor": [0, 4], "saved_features_imag": 0, "saved_tensor": 0, "score": 0, "screen": [1, 8], "screenshot": [1, 8], "script": 7, "sdk": 7, "search": [1, 2, 4, 7, 8], "search_queri": [0, 5], "second": [0, 5], "section": 5, "see": [1, 5, 7, 8], "seed": [0, 5], "seem": 6, "select": [0, 1, 8], "self": 0, "sell": 3, "send": 7, "sent": 2, "sentiment": [0, 5, 7], "sentiment_scor": 5, "separ": 5, "sequenti": 5, "server": [0, 5], "servic": [1, 7, 8], "session": 5, "set": [0, 1, 2, 6, 7, 8], "set_kei": [0, 4], "setuptool": [5, 6], "seven": 5, "sever": [5, 7], "sh": 7, "shade": 0, "shall": 3, "share": 7, "shell": 5, "short": 7, "shortcom": 5, "shot": 5, "should": [0, 1, 5, 8], "show": [0, 1, 5, 6, 8], "show_result": [0, 4, 5], "showcas": 5, "shown": 5, "shuffel": 0, "shuffl": [0, 5], "sidebar": 5, "sift": 0, "sign": [1, 8], "signifi": [0, 5], "similar": [0, 5, 7], "simultan": 5, "sinc": 5, "singl": [0, 5], "site": 0, "size": [0, 5, 7], "skip": 5, "skip_extract": [0, 5], "slightli": 5, "slower": 5, "small": 0, "smaller": [0, 5], "so": [0, 3, 5, 7], "social": [0, 5, 6, 7], "softwar": 3, "solv": 2, "some": [5, 6, 7], "someth": [1, 5, 6, 8], "sometim": [0, 5, 6, 7], "sort": 0, "sorted_list": [0, 5], "sourc": [5, 7], "space": 7, "spaci": [5, 7], "special": 5, "specif": [0, 5], "specifi": 5, "speech": 7, "spell": 7, "ssc": 3, "ssciwr": [5, 6], "sshleifer": 5, "sst": 5, "stack": 0, "start": 0, "state": 7, "step": [2, 6, 7], "still": 2, "store": [5, 7], "str": [0, 5, 6], "string": 5, "studio": 7, "style": 5, "subdict": [0, 5], "subdirectori": [0, 5], "subfold": 5, "subject": [3, 7], "sublicens": 3, "subsequ": 5, "substanti": 3, "substitut": 6, "subtract": 0, "suffix": 0, "suitabl": 5, "summar": 5, "summari": [2, 4, 7], "summary_and_quest": [0, 5], "summary_model": 0, "summary_vis_processor": 0, "summary_vqa_model": 0, "summary_vqa_model_new": 0, "summary_vqa_txt_processor": 0, "summary_vqa_txt_processors_new": 0, "summary_vqa_vis_processor": 0, "summary_vqa_vis_processors_new": 0, "summarydetector": [0, 4, 5], "sure": [1, 5, 8], "surpris": 5, "syntax": 5, "system": 0, "t": [2, 6], "t5": 0, "ta": 5, "tab": 5, "tabl": 5, "take": [0, 5], "taken": [0, 5], "task": [5, 7], "tell": 5, "temporarili": 7, "ten": 0, "tensor": [0, 5], "tensorflow": 5, "tesor": 0, "test": [2, 6], "text": [2, 4, 6], "text_clean": [5, 7], "text_df": 5, "text_dict": 5, "text_english": [0, 5, 7], "text_english_correct": 7, "text_input": [0, 5], "text_languag": [5, 7], "text_ner": [0, 4], "text_query_index": 0, "text_sentiment_transform": [0, 4], "text_summari": [0, 4, 5], "textanalyz": [0, 4, 5], "textblob": 7, "textdetector": [0, 4, 5], "textual": 7, "tf": 5, "than": [1, 5, 8], "thei": [0, 5, 7], "them": 5, "therefor": 5, "thi": [0, 1, 3, 5, 6, 7, 8], "third": 7, "three": [1, 5, 8], "threshold": 5, "through": [0, 5], "thrown": 5, "thu": 5, "tiff": [0, 5], "time": [5, 7], "to_csv": 5, "togeth": 0, "toggl": 5, "token": [0, 7], "tokenized_text": 0, "tool": 2, "top": [1, 5, 8], "top1": 5, "topic": [0, 5, 7], "torch": [0, 7], "torchaudio": [5, 7], "torchdata": 5, "torchtext": 5, "torchvis": 7, "tort": 3, "total": 5, "tpu": 5, "tqdm": 5, "train": [0, 5], "transform": [0, 5, 7], "translat": [0, 2], "translate_text": [0, 4], "true": [0, 5, 6, 7], "try": 5, "ttl": 7, "tune": 5, "tupl": 0, "two": [0, 5, 7], "txt_processor": [0, 5], "type": [0, 5, 6], "typic": 7, "ummary_and_quest": 5, "uncas": 5, "uncom": 5, "under": 7, "unecessari": 0, "uninstal": [5, 6], "union": 0, "unrecogn": [0, 7], "unrecogniz": 5, "unset": 5, "unzip": 6, "up": [0, 1, 5, 7, 8], "updat": [0, 5], "update_pictur": [0, 4], "upload": [1, 7, 8], "upload_model_blip2_coco": [0, 4], "upload_model_blip_bas": [0, 4], "upload_model_blip_larg": [0, 4], "upon": 5, "url": 7, "us": [0, 1, 2, 3, 8], "usa": 5, "usag": 2, "use_csv": 0, "user": [0, 2, 7], "utf": 0, "util": [2, 4, 6], "v": 7, "v143": 7, "v2": 5, "v_margin": 0, "valu": [0, 5], "variabl": [0, 5, 7], "veri": [5, 7], "version": [5, 6, 7], "vertic": [0, 1, 8], "via": 5, "video": 5, "view": [0, 6], "vis_processor": [0, 5], "vision": [0, 2], "visual": [0, 5, 7], "visual_input": 0, "visualstudio": 7, "vit": [0, 5], "vqa": [0, 5], "vram": 5, "vs_buildtool": 7, "wa": [0, 5, 7], "wai": [5, 6], "want": [5, 7], "warranti": 3, "we": [0, 5, 6], "wear": [0, 5, 7], "wears_mask": [0, 4, 5], "webp": [0, 5], "websit": 7, "well": 5, "wget": 6, "what": [2, 5], "when": [1, 5, 6, 7, 8], "where": [0, 1, 5, 7, 8], "whether": [0, 3], "which": [0, 5, 6, 7], "while": [0, 5], "white": [0, 7], "whitespac": 5, "whl": 7, "whole": 5, "whom": 3, "why": 5, "width": 0, "window": [1, 8], "wish": [1, 8], "without": [0, 3, 5, 7], "won": 7, "word": [0, 5, 7], "work": [0, 5, 6, 7], "world": 5, "worn": 5, "wrapper": 0, "write": [0, 2], "written": [0, 5], "wrong": 6, "x64": [0, 7], "x86": 7, "xl": 0, "xxl": 0, "y": [5, 6], "ye": 5, "yellow": [0, 7], "yet": 0, "you": [1, 5, 6, 7, 8], "your": [1, 2, 6, 7, 8], "zero": 5, "zip": 6}, "titles": ["text module", "Instructions how to generate and enable a google Cloud Vision API key", "Welcome to AMMICO\u2019s documentation!", "License", "AMMICO package modules", "AMMICO Demonstration Notebook", "Crop posts module", "AMMICO - AI Media and Misinformation Content Analysis Tool", "Instructions how to generate and enable a google Cloud Vision API key"], "titleterms": {"": 2, "0": 5, "1": [5, 7], "2": [5, 7], "3": [5, 7], "4": 5, "The": 5, "access": 7, "after": 7, "ai": 7, "all": 5, "ammico": [2, 4, 5, 7], "analys": 5, "analysi": [5, 7], "analyz": 5, "api": [1, 8], "ar": 7, "blip2": 5, "can": 7, "cloud": [1, 5, 7, 8], "color": [5, 7], "color_analysi": 0, "compat": 7, "contain": 5, "content": [2, 7], "convert": 5, "creat": 5, "crop": [6, 7], "croppost": 0, "csv": 5, "data": 5, "datafram": 5, "dataset": 5, "demonstr": 5, "detect": [5, 7], "detector": 5, "disclosur": 5, "displai": 0, "document": 2, "don": 7, "emot": 7, "enabl": [1, 8], "environ": 7, "ethic": 5, "express": 5, "extract": [5, 7], "face": [0, 5], "facial": 5, "faq": 7, "featur": [5, 7], "file": 5, "first": 7, "folder": 5, "formul": 5, "from": 5, "further": 5, "gener": [1, 8], "googl": [1, 5, 7, 8], "graphic": 5, "happen": 7, "have": 7, "how": [1, 8], "http": 7, "hue": 7, "i": 7, "imag": [5, 7], "import": 5, "improv": 5, "index": 5, "indic": 2, "input": 5, "inspect": 5, "instal": 7, "instruct": [1, 8], "interfac": 5, "internet": 7, "kei": [1, 5, 8], "licens": 3, "media": 7, "micromamba": 7, "misinform": 7, "model": 5, "modul": [0, 4, 5, 6], "multimod": [0, 5], "notebook": 5, "org": 7, "output": 5, "packag": [4, 5, 7], "panda": 5, "pictur": 5, "pip": 7, "post": [6, 7], "prepar": 7, "problem": 7, "pytorch": 7, "queri": 5, "read": 5, "recognit": 7, "result": 5, "right": 7, "save": 5, "search": [0, 5], "second": 7, "select": 5, "sent": 7, "set": 5, "solv": 7, "statement": 5, "step": 5, "still": 7, "summari": [0, 5], "t": 7, "tabl": 2, "tensorflow": 7, "test": 5, "text": [0, 5, 7], "tool": 7, "translat": [5, 7], "us": [5, 7], "usag": 7, "user": 5, "util": 0, "vision": [1, 5, 7, 8], "we": 7, "welcom": 2, "what": 7, "window": 7, "write": 5, "www": 7, "your": 5}})
\ No newline at end of file
diff --git a/source/notebooks/DemoNotebook_ammico.ipynb b/source/notebooks/DemoNotebook_ammico.ipynb
index 292a93d..f6a53da 100644
--- a/source/notebooks/DemoNotebook_ammico.ipynb
+++ b/source/notebooks/DemoNotebook_ammico.ipynb
@@ -166,7 +166,7 @@
    "source": [
     "image_dict = ammico.find_files(\n",
     "    # path=\"/content/drive/MyDrive/misinformation-data/\",\n",
-    "    path=data_path.as_posix(),\n",
+    "    path=str(data_path),\n",
     "    limit=15,\n",
     ")"
    ]
@@ -177,7 +177,30 @@
    "source": [
     "## Step 2: Inspect the input files using the graphical user interface\n",
     "A Dash user interface is to select the most suitable options for the analysis, before running a complete analysis on the whole data set. The options for each detector module are explained below in the corresponding sections; for example, different models can be selected that will provide slightly different results. This way, the user can interactively explore which settings provide the most accurate results. In the interface, the nested `image_dict` is passed through the `AnalysisExplorer` class. The interface is run on a specific port which is passed using the `port` keyword; if a port is already in use, it will return an error message, in which case the user should select a different port number. \n",
-    "The interface opens a dash app inside the Jupyter Notebook and allows selection of the input file in the top left dropdown menu, as well as selection of the detector type in the top right, with options for each detector type as explained below. The output of the detector is shown directly on the right next to the image. This way, the user can directly inspect how updating the options for each detector changes the computed results, and find the best settings for a production run."
+    "The interface opens a dash app inside the Jupyter Notebook and allows selection of the input file in the top left dropdown menu, as well as selection of the detector type in the top right, with options for each detector type as explained below. The output of the detector is shown directly on the right next to the image. This way, the user can directly inspect how updating the options for each detector changes the computed results, and find the best settings for a production run.\n",
+    "\n",
+    "### Ethical disclosure statement\n",
+    "\n",
+    "If you want to run an analysis using the EmotionDetector detector type, you have first have to respond to an ethical disclosure statement. This disclosure statement ensures that you only use the full capabilities of the EmotionDetector after you have been made aware of its shortcomings.\n",
+    "\n",
+    "For this, answer \"yes\" or \"no\" to the below prompt. This will set an environment variable with the name given as in `accept_disclosure`. To re-run the disclosure prompt, unset the variable by uncommenting the line `os.environ.pop(accept_disclosure, None)`. To permanently set this envorinment variable, add it to your shell via your `.profile` or `.bashr` file.\n",
+    "\n",
+    "If the disclosure statement is accepted, the EmotionDetector will perform age, gender and race/ethnicity classification dependend on the provided thresholds. If the disclosure is rejected, only the presence of faces and emotion (if not wearing a mask) is detected."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# respond to the disclosure statement\n",
+    "# this will set an environment variable for you\n",
+    "# if you do not want to re-accept the disclosure every time, you can set this environment variable in your shell\n",
+    "# to re-set the environment variable, uncomment the below line\n",
+    "accept_disclosure = \"DISCLOSURE_AMMICO\"\n",
+    "# os.environ.pop(accept_disclosure, None)\n",
+    "_ = ammico.ethical_disclosure(accept_disclosure=accept_disclosure)"
    ]
   },
   {
@@ -822,7 +845,7 @@
    "metadata": {},
    "source": [
     "## Detection of faces and facial expression analysis\n",
-    "Faces and facial expressions are detected and analyzed using the `EmotionDetector` class from the `faces` module. Initially, it is detected if faces are present on the image using RetinaFace, followed by analysis if face masks are worn (Face-Mask-Detection). The detection of age, gender, race, and emotions is carried out with deepface.\n",
+    "Faces and facial expressions are detected and analyzed using the `EmotionDetector` class from the `faces` module. Initially, it is detected if faces are present on the image using RetinaFace, followed by analysis if face masks are worn (Face-Mask-Detection). The detection of age, gender, race, and emotions is carried out with deepface, but only if the disclosure statement has been accepted (see above).\n",
     "\n",
     "<img src=\"../_static/emotion_detector.png\" width=\"800\" />\n",
     "\n",
@@ -832,10 +855,11 @@
     "\n",
     "From the seven facial expressions, an overall dominating emotion category is identified: negative, positive, or neutral emotion. These are defined with the facial expressions angry, disgust, fear and sad for the negative category, happy for the positive category, and surprise and neutral for the neutral category.\n",
     "\n",
-    "A similar threshold as for the emotion recognition is set for the race detection, `race_threshold`, with the default set to 50% so that a confidence for the race above 0.5 only will return a value in the analysis. \n",
+    "A similar threshold as for the emotion recognition is set for the race/ethnicity, gender and age detection, `race_threshold`, `gender_threshold`, `age_threshold`, with the default set to 50% so that a confidence for the race above 0.5 only will return a value in the analysis. \n",
     "\n",
-    "Summarizing, the face detection is carried out using the following method call and keywords, where `emotion_threshold` and \n",
-    "`race_threshold` are optional:"
+    "You may also pass the name of the environment variable that determines if you accept or reject the ethical disclosure statement. By default, the variable is named `DISCLOSURE_AMMICO`.\n",
+    "\n",
+    "Summarizing, the face detection is carried out using the following method call and keywords, where `emotion_threshold`, `race_threshold`, `gender_threshold`, `age_threshold` are optional:"
    ]
   },
   {
@@ -845,7 +869,9 @@
    "outputs": [],
    "source": [
     "for key in image_dict.keys():\n",
-    "    image_dict[key] = ammico.EmotionDetector(image_dict[key], emotion_threshold=50, race_threshold=50).analyse_image()"
+    "    image_dict[key] = ammico.EmotionDetector(image_dict[key], emotion_threshold=50, race_threshold=50,\n",
+    "                                             gender_threshold=50, age_threshold=50, \n",
+    "                                             accept_disclosure=\"DISCLOSURE_AMMICO\").analyse_image()"
    ]
   },
   {