%PDF-1.4 % 9 0 obj<>endobj 8 0 obj<> stream x[w۸  ˣh$nUvǖv))m}b@C >597䴥'߂*J/Ox?O֜9糟)+]2m"[o w>i⋍?O3鲰سnԾ<Æw뻇Gvaݬ6d4'+]'vOmno?.-kWiUؿw׫ڀ?߲_?0KrQx^)59\qy%+2N"t ](&/ hNUc6f1;mB LKQJF>VyY\ 5F6A6DI6&Vi+ ٬B6+k:.%thltN,MdL"Ȥӎl6Dc>?tkUXf#J 0UtdUj՜j*Ũ?23(>|Lk{$pn6Kn?͠!,.l6v_ڵun>o+zqb7BHl&dԦnW63NSuIL;Ċ]_hOjS?3ϏXIش&Lh'4OZIT@,{璹;g"S gaL/d|j/?t~\4`5@p{/5-Ы"\(+d I$=KmB4D-v*kJ>wh$CE"H QG}nlC @X 4kS9}O|Z8ȴ33| g 2@Iy LrQL`6 v)f(-+;Ӥ)ziKvӹo4:fƍ1;S.G*I= cXRaKtLD;GQ66M' & *n 6J{#[ӓnKʬ5X9I(=OӡIc8ylF?ECh!fw&QM7\ #)9&ijtSR<+B'Mi^4ɤVœQ.%Ċ,B"U|!jb$in2'*"k dQ$qHM3]3cJ3I(&LU[3(kT5E&$oU0=J3v9mlu۞[A(S> 3W%Cy%U&,]fQ*eU[E5FE ZEzԪ.i(D%3ͪBUݩև]}-C^ Z`*TUJxrbMlJBy&(d\ XS 4v*D")Rd=5O\bQJ5%͌P;[]ch| IX%P.%AK" .(X%/2x#5fdTX[]I!`B8(i?f#eV B$K[/5MJWOKdBH#!hΞhziI#yVL [~KGvֲf?i.A Hڇ@L +4(J$勆1J42ZEYH Lv/-**[MSOCS?U`vƃ&آ6آDR& ag|23i pg`4 v(fqЂ~`>M}ooÀsxд7PLبL* DeӡIBAs!z2Dn0CFqtcvPoSkʝo+!ia<3E2& j DK(eX^eF'dD{͵Ȍ.݋>ia s`xX\SH{j%8]'<',υ% QnL\ 9UoHdF{+IQsg~햙1]wKE 1(I=I i2Aip˘I&҄ '>DGu9WUܫi8 Z^6HG F r$ aM|2&i d30D0|԰B:KN{]Ž f^l 9x4s췷4OrxZ!_@=ePGϳA*@ifı(TtKoPk]xI8XU֞bOݮۣ|펏}wu&$J$~*IQ%EVqskX#҈FF5,&Sz4j%xxœ4"`@hU5>yqD;U4.C7?[5P+Uۡo6W_Зhd{!Mo Z1dJNPYYUYZw_I(+[8d&J3\>"z9\8Ie1"+KSr T,A$Ԓ:DB|CcWBQ1 b endstream endobj 23 0 obj <>stream SAS Institute Inc. 9.03.01M2P08152012 2017-10-27T17:49:52-05:00 2017-10-27T17:49:52-05:00 uuid:656C6606-5EDB-1E41-9275-A9D4E5A1523A uuid:999CDCF0-927D-774E-A9BE-83613D6D0FCB endstream endobj 1 0 obj <> endobj 24 0 obj << /Dests 25 0 R >> endobj 25 0 obj << /Names [(IDX) 19 0 R ] >> endobj 2 0 obj <> endobj 3 0 obj << /Type /Pages /Count 1 /Kids [7 0 R] >> endobj 4 0 obj <> endobj 5 0 obj <> endobj 6 0 obj<> stream xU=0 # (*K~D-ۓ`K{OYVlyck Z2Y#4YaR׽dLuBޣ:`u4Aԭea Yd m*uM$v:WYQgYiH_&V?s(D.s*?#95iit endstream endobj 26 0 obj<> stream xxTU0kzȄC^ @* $I&ХD Q@& A,X@E_̙={~sΰ^^{3B1>w϶_wm@7A(bao_PVhK9tX/#u vҮ_::F2k}nU~5ByTXQTIP̛Pd@0?tJau9wW۬umPo,ϻC},[UOK@q௺Ԟoޕe>Y+rk ^_a0j!; XQi(^{ y]0_D C'\]1û^scO6b4 k~^9Rz$z`kMCԃZll6 JQBvTlR7V=۲_nc<-w}m:u-= zJ0!A=E/hH_lV f_z gN\g>[%wj'SD8g]~ƮikZ:WӺွџ[/}c?_d=FO/4u \:klsuOMR}>^φ8C6߆޸maݕq|]Z~T䫞ӯ\Bۻ\VOnz2w^J^#^In'ް4ݵW\/z/JW_y7/3e[!/zl㸈+[f͛5^ْ'ճܒ~bK5RV[m6cuUU|"';݁*ϛ\q~F/k)zӧ-{ީ=űkU;gt"3E=ܳ2Z3x_0sA-:.YTnU.tyoW- /oZ9mŎN߱&W[o2?~Em~C3uj{9w/xXV~܃Yм <]5+}N}Y}IS[BT\v7_}4} %oSm߱񵘼sOmk9틨]} '_UײC(. e醑ɗ9W0܍&qHwL+VUtA5y%A%e)ڪb{eI&u:KU~@|C#\Z5V=^9^Emq f*˪TBUMMeVIvY9iҤG ªjVtJ6S4{M1Ѫ?x3~~צi {ϧgFSꐅ?i+嵷lm]zvmۅg[{g]yxM5oݢԼszoem ^nä>q[g퇿+Y|E;; h eߵ]=w;_-:. U=x)!luّ9}'O'ωsq&^.3tnݟ6ӏ^Zox1G]PuO+L潆C9_׃FY.XWns{d`H*g 8ɿZ=`\sU U[u j"a=̥&Ssjs3uM:a;ҜJs `,7tZ`^|f䭗kRϞ%')I7[۷cmPžkm>9wo#6ςa77읲d'ֱ Dμ^|@{nW?y;jy供[}rq:.G>h5R~3h{은 _w}z֦! RjwX̑˲O>*dEj/֪S#y50IYr{ wH-:!!Z.X__iVB6ZiS 8,iV%7,0S=V)U9)BY={_}E~O0xc7>W9ɘ[~nV3jƁ[,_m7zL)׵RP|ƨtȈ?PZ9ӠVca>a~Z{t,/P7mqퟥ^TwmtX3aM4Tsc2׭xiv#d qJEf\]"su O!sx1YDY6F\@忋~&=#K;mF)[_FO 뒱*{uz1鋞39hJjXS7xV#%[?ܫY`Rm 7^ [d⩋1Zy} k'^BޫOT;iN`AFVNϾm27薬yu鏣k.E?I*~?uAW}굇ݶݻoȐ q֬gll˖5aÎ-r{ƕ[$Բ.Ӂzo#w>[6XIaBhaT~? +;s,D aA- ݱ䕔A[n|4I/ ӤKP *CyȆ*Q)rTT(G_ fE2cgyMZ畵o}xjKko|'AG_dCǍDgqSF_1=~EٳFߙpyST^`)tooW~7ݮd!+ZN>_3ҝ3,{ipѬ j}*<44 SMZgC䶨TpM|JfQ7FÚ>-.$eՁZ6>`ͶĻ<bϕ|/jS^nGorRgvr{vf3GpK?o}Um[3v []*q✯,^x!_VYVjzF˟˖4T fKeZ|GRcKCM[Je5ݦ#w.^xE"Shz7/}Z~Æ ԓϗ[=kʣwwA: 0Ͼ{=e+_en| owF΃cD8 `= y419 (c8qOa)~Jz}[+y jj=^1ЬrMjhEJwaI[IyI5J/>r>Ȋ JPnwI+9Q)Q :5Z 3o}kp+'xtfR%=%6C|_)ags|[aC#i,-i[#L,Cб4r:ΣRїt}oѷ=M?s??z)5xւjcg^/|sx.gi%Y!5Ofsy{/|˟cM|  dMimM;Q5Q=5P#.t&}.3t]C_/.&Ow1>=?/%*(քXsQ y/y9Ol<*T> >MeS|)=|[ȞbKYkZo/𭠩%pV86^Yݎ3S4O:n/ +ޤ?_X b, k.,ueX2Ke,`XoևeX6d/S:t-fK3l[V%[Zֳ(f_?lQ N{PSLG¥MVvX^x$iBƐYd9E>^`w-@f+]վ!y*Pj6#к|5_h:DM;B~q̥PL K}4 6 @a(.Zt9S sgi,t,t,{ DןNK6%QYrLҍUֺI,_ ow@#EAs1 ǟdo<_@R(+,Hh,ۊC}d VcQ+/,q88eM$a'[HBd{%%C Л#ڧ@M!捃v>DO=۞X39(G 1lB@:4DS!ZCPRiWnAC~&C'\yrk>Ƴxp#5vUWO\O/JOByhåx""Et)]Qߥk)r.%M tTG6G#wWaNPctv1CnFJhp; tN gL9I;Á>y/ Wh8o(ߕs r3=ma2?~~ 11a,h M }]Px I_8L^c_5Fb?>jT o$ܢQ'4h.Ul{հi4ZOfo,DH ߽H7Iw0{eϡWa?}WI}E.EFx2K&th2β'L-` M( (b=Lxƭ-GjDMPrG)Z)X#P||/x3 rE>M<瘜ѣFһW.-fѠi5N;Ol׶MV-[$4W5k$6&:*2"<,4$8(0ӃKO8>*-+c\}tZn_BzBoQHl|BJ)2'֣оa@zĿPO[ݎcU%Kc-o3$+>!Xџ scҲcIK_>h:ZzףAYR9>!Y͜cr/῰9NKGa;߷(\vˌQR}D`$ TnzX~4k `\BFA h ץ[ƫTuCuL?>8kOZBG4> دyA^ )O^ @B:hzB]={/tB0 : zzOdk=Zp=A(/7ѯ ::ZaD[fg7;h$4)H*iLZ>UF\ҥeؖ+ MH>ﴬycC̨N zN>ܳ3ƥ:$E6ݱ9˺оܴ~ǃ>r&<,pL({i)iԒT޸/n[srPNN6 a!(8NX4s梌-lC{5~݌L<aM%z8(=9"( Tq՝q.XuuxPyup!x2nM(z8z\7K,Q5I Yj49N' DR7T$\s҂9Yc1Y'IIK}9 / Bj0Qq$5 Zt:5 [v:2`V响$8($T +a>ӫV]r aO _6ýp|3mh|l)@aPr T8^A~`ఐ`j<< Ka%x_J}C0($9dPHE BA!t4'G 6I'HmwCK'M-,~AG΋(hcGGu/GƔbS]xA XN[7a$<^&DC4ܶ/@@Qg5̃{, hg'4hiXH0fQ . |944;K60fD QrhṪ>bPY=+ 0D͹}^NqC,];MpSrt:EI qmqHp iRB {- {(U{8:mhВPq8Lș - %%44>{~x{U ?Xw16Jܑ`3A5peA!+R8F)oSAMP1 DE#`k7n> N7#-](&ACGS&_S|w"-uvK{V:بF4g6/|a:?eZ闚> lZbc>ez!݉pOV>M>x+;rUK^${ _:w+tK0 +gpd0YA|h%ow/7 :FEHCbb1&A>;;*:_ɂDBsOX/ aADFb !&OT0#7e$:2e(7((2ěh2+Ii$D:`MMIb˞H|>sAv$^J.NuMΙ;r|+AʩԁK|jxBI.0Bg$Ϲ8obq9a q_n_f7|԰ݣOe}/&A}荷3'jts J78I VrAƷ3v4΄oCJIHC〉8 UH[^<٧@ 2ARJ!ic:N!{OY) }@y% ]@%5}Cߣ ~@?k:nF;z {c?8p8(cp,nf8pm|w{>O}O|?OY) y% _%5 ?k:oƿ;>~H|B(a>z@8 ċxˆ'$`BBI '$DhCbIҔ4#qpO҂$Hk҆%H"iO:Q 1KB:.$t%HwLRH*I#$ =I/қ!}I?ҟ  2 !CI&FCEH2&9d Kr|R@lbRBƑ񤔔rb'd$UԐdLdN#3L2&q2ԑ!۶ٞ"&S|AΑK@.Kk |G'r@~$ur$?- M~%;Ëȏ/ޗ`$ ")+iF9 bF@i !+4FHi MhS UÁ4-i+ښmi;QAqXN ՊWlV8k(bX,kšfpxm+`-Y+֚amW:S3 2:YXgZWwRX*KS^o5f9y YxV*V׾il:{I/=y5l{-fKR4{=+B=Ǟ_ 6Ml3{ma/%^a5Vvl{v7c/C0{aﰣ];Ǝ${_z}ΰGc ;>eϥy%]`%5}˾cK/#&nf;`؟>{( IsOŽ~ܟ@ăyaCɇ|$G>x>/E紥ܰ˭P(ь"+/=Ѓ]ðr?Z۳᭩<8xt0ĝJw8xtCwԘ鎭[MC#VK;̱5HUH5!U\a%EF="a{sb5>$78 =F:d*>#]=U{ :y'Eb1*@ϔ Gi97ZU.cDQĝ(F8'Ʌ<ȅ|IAٿVYoO#GR`e\^H[>x3o|p0JXպ rgJK**pUbUU.xm%E~Ű[poaD'W˕XZk_IyWT}mjJ&ZKm6^lۥ|k)>`By~'2Q :k>VX)C5>rY) vt';<{u2O@yU6B?(ȳOIKc6A<+KE5R;BJmDfK'j rt+lJcUY 0oͷ& )(_jcRƫ*6_ZNjmV ZP"߲*E7khx%@j蜀 蝀 X AN 83LEHℌ"8WYmhSII:.I׬mu3k$VuQuAN9λ ]!AbYӊqf$$!ŢV H# t -O#4ur` pfk :u't>N`69w)X;9ggrЫ];JF,vhƨ5F#ڄ3|bMxG^Ydu>kM`rk>?hsh\F\ၵ$x1 ^LMpo:0 ]iL.&fz |3@+d3xZj ׅşЁ&k?kY,?MpjQ,SqJuש]3:/u'T \dr[ .nv- +\FWIY#Śݛ5b=gaafafXṄ֊sFR~R~R~R+nPJETTE?>,r*|*mQբS?SRz ߩ ߩ>p+URR|)}9术5E3EȓMSNS=M9M;]#M '^ҝzqS%ٯ\t|tENqʑ;C~2=:PuPf(t3 nCWFsMⱍe4=Dji|+\w:OZ'`r>I1i` Ӱ7X-@L:f r$X`lp ڝSsq&˘nZֹiYe!AQFunչiTQFuntHWxNH=tnӹiO=tnӹiO=IѤsӔMSz7MhnһiJ)nһiJ)Alh6iJ)nһiJ)nһiJpb1 HD"rӸ"Ui"bԊQ+"FS2hiMѡNĄ: gQbA0$](8 f YP^IM/u椦^DzgEt^^/4 vd'$=KWNHt^- O/WzO/WbUb-{NHk)vB8u腿JX^^|+h&AM؆^؆^؆,{[/E k+vAXA\AXAXA5 Hve{ , vAXAؕA'huz :0^6dc l , AؐAXjZZZZbXAz7 ֌b_֌BkF/BWF+ؗF+؍FzEKؗF]ЮQh(vQ(lz6j7 w FDDE{g>Ǐ>glA.PN> 亇-9u dP>ׯ`b}5>іo/&lIREujRjR\u&g?liӣ? +@;-#bxu%߽P9_>2&,I8 K ,ֽڊ]15-:~ $B6wIEg2K*}rwNN03 L8ȻCZ~T0!I-e샖}ҝAIwl_sJ ݅s, P<cr1\肝]Sϐ7B" ڝ=Zʀ)I8[삖hZ \W?Ch_k}ܾaU|[CpYJ9ߩ;K|=̈́|r>S)vpwR-@)DBme0#hj @K[.Ӟrڣ BC{POԥ'3=N R3chOҁtPԲzH䖱τtGb4 8'Q FAOWd$˘R* 0'$$!OR2Ar!q=08fKiKyûXC-d09.?6r}㒏icMZoHcv~܈Kr҄ސ,%$ʽ[}-4P_$&/˗Do,먱EZ*<= D= EO'O o|,Ԯעb,r(}|y U@%Պ3%v3~}Boo`nXSsI9au>M'IY$v~Xya`  1%ǠN +77'989S㑨bQ oa5G !@]6[QV1nl;C94^wU &4*kOeCk=z6"$m䨬=8Z~"v/OW@ _:)88Х'kR..?͟墜={٣vYƧq19|]ҳoGʆjvS-}^,,UxXa9=4Mܮ-nۖw|~-qTzuR}xQyfHѣ&2#qat(q#F)ml~}E1ԓ ZP,!> endobj 11 0 obj <> endobj 12 0 obj<> stream xUK0{>C{Vh2CLqOgnn5䗟Uce~xh,h92N%a;V{s{5zcOl6@U!}t\u8vWgΎeTPEhHsu$9*QfD>瞸D씜3rG|bg|a_W\Joc`ᕇzxX_S4rP_ endstream endobj 27 0 obj<> stream x |MW?s<7㽙$Br3J$!D QCD̡jJjj$uν+O}s}{i{s BZTܽ};ɕ%) 3%=)w]Z٧$!d.C(h=۸-=d(fH6CzU`?*sjx;PBM ˰ܡx> ,+*ɀ{ (|?B[\;2]0VjOK Iy! z#6@,!,l9I3Ly--kd/~h$B+c<K?<٣mʮZ^~VJ+!4-jϼI44U&,4eV&@Kz۴\B4`da:jɣ]0dȀ% #?wLo'!E  k抩*( -,6Ȓcۢ""m6eGpɨȨ^n=h;WPTн`а&EB]Y}@Frb?w`RD/!>tdMG) <ӻ863s^9BcY;ix¾>ʿ;dOӛnLmyo}zwjKvI;v~}Kh׵)Q 5K4;oriƟϲNk/ /aC>Uw^L2gw oԪѷ>coW?U~.iGry*c~{\7%rS7Z|4݄7'۔h e3 [@mچ ?0l4}$=xk1aD6F\/g-.fsU_4N[q7a[w #IjGAE6b``V3`6c}S,{k0Mc :e "f[h_&|«aGY:*.]p[]+ka?fMڵQ|Q?mg#W>}vw>~S?Twvu-==p\uc adKGϨGV_ۚ:; WreܚzSMGTA5-T=FըNK%=Ӛ{{^50->KeRGw9})w6J/uj#9roNI8&;6̉~J-_oQEߦteoOK[:Hn>Z_fnfۗl aS¥;~?Zdw˫~:J'& wP}<}cH67}V 6\MNRMkIM$euKؐ-ʹۂ˃h1ٴ. (G+0 <}l.q_*v}:}*N<\Ϧ^7]nn)IٛvAڶXܚZev֫v`v4,)+s%6rރ7x[z#dDQOXn81UeG/;P#hin1aUk2ۘ{+C;ޮOP8f]3ߖ7zDg˻XУ_B詹 '4}{w N!?yw>-ƹI% 9eIoHAKZQܢqnږ֣ ,"%cj`ʶ8 AѨŖ. /z%-1hHQ#Xr-]3f̳YTk b7k'4^ۀo塏 <p{39h_!q]~gʪ&*۵8>PN鿵iF_WTJN{Ko|0hT|zҡv0I*ߦC .=O0vߓ-l=V(+7)\]56y;:<׆LHKq9Hdy{y2gaZ8IsiRH9χ?2+-$?EڳJ0$ǪS^q.͞/M9䇋6C'dz6;ڇ\3泰7_lm\aU ;-4jFf;.^tyc|Ov=b~kODK-+Y9J|gR0R&`l?d|J e8BHA!"4B< iJ?;{փYUd"4gͯ/~Yv̶uqcEmʽ&{ "4 \qFQJ^%wܡ.eSݘ),J̎Μ6h&:s>~[~_+ }\K O,}ǎyڄ?/y]@,gt{ޕ_Pǣ`ѦF^G}h˵Q ~ڼM,iYw' x3VŠ*ŏ BQo@5Θ<hóMҧB1hP{d\d\DlTLLT4LrqwΧ@)FEHo9-x$zL^UqmTHսoy2ͦ;RϾ87}_Ǵ|֜y^ߩz{nҧ}4l.l7{R.|\'7Ϭ}A?FM `IEuZyόʷuF~a -jubl8BC AO?B|? ~=AJHcH,I ĩ+I&Ľ 瑷!^FAl@l$0rlЛɇ@;<S! MnJ"B*ߣHAZA?t;Пн@cz dz#a]=Pf< @0,f5k.D>+ m0vBv+t7e{NdC-D=ғ-ܷ 55UNN ?ǀW }e+1G: ;$"+x;!)XK>Ar%!33$>k"^P_EEA :^3@ڝ&^ ʌ`Ff$SAF q0,f1.`)ukPSv{`#@i \p0T ` H 6 A!Bsvm!t!X΃`FCp@X Zv@ a!W<6au|N_E99ReUzϹǵ4bF~fq"}'0quqs3מƮ|h"|>vZӘuzyE|>G^'X%X',&%|'8)8',.-/x"$BP! =a0R'l%Lv { { Äi7+v~W# +;j#T"K' EEvQ[Q'Q(S- FJDrZ&V^QbX#6}b8V n#Nwg{sCEI2<"r*:f6.q;I9eum} $ N!H$M$8I+I$MS[O/&)LL̖)Y,Y!Y- qHKHK\\ܐܑG?P?D_///ׯүooWӟԟ__?1Ƞ0 !i32$: = abxd4lÛņՆ aaa+qi C1J*e3ÌF1ݘi6 %R \RcqqqqqxxxxxxxxȄL̤1L>SckJ012LL9!"X$TSiiiiiiiitt鉙EfYg0[A&Hs9fimg73Ǜ'g4/606o0;{_O/o=֣GGGG`B%O5+`j  G+Յx?σe &7-Ȁ4ϳ:[C=z^@9_ ?m<33k<~l/t 8~]*^V%çgv?G~˳}JC?5HcOQ4oξm҅ө; }Smߧb~Hvܩl7;x>kǻ$oJi9կ/759E;z)<=ύgK5NOuݰ{.3.|sϺVn^K aWv.)汮ۮ鱷qË?oܱϵ>@Kұ:C>#|ҭ??N&;^Zѝ걹q?ݳҰ|7?w8-<_/םy#dN7p֨婿׻/jqF\?8S-ϳ{Ko ӎy,ݠ?,P;."طwGN.<J?lv7|ɺh:<}8ȷܡi!7\~ N9v/pCoAA!yD*RC9lDim ع{7_b2,23e1y2zeg1뙍&t{A?@7BtCn V,BB83.B9*, `!Bc64n!BzAȁ0ECVwLGBPgY/P@^( DC-ǢIh**C]Uh ȹ U3I:ENJl=0W̗6D?D|>r_8+gS=~=ǽeؽ}=3kb,EHj)ӟ9 @}߽Ch̽U&#jjwnn︵;m=OTȀta(}Np|ѡ6no@7!Rc7VQP fH;sƽh!a|\7`*X0,ah./(9|Z!A[+@;xoN%%Aڷ0YX3n-|,pEXLI {i,iqddFqN' հ^v^X2l&#c9=_gR ۙ 9["jJL,me殕fR#JFhKhmEdJ;4A3i/ڛfGZHXZB'өtMt1]J{ÔV0ϙJ %ǘo z9|K/q+HgN;.ϜbNGO,s9\`~f.20טߘ[Fc0r1a1&VxbVXY%jX=kb=YؘH6m3P%ȴf 6e3ɤ3lƳt;0HFC ԃzQ 4Fڌ-ikDю+N_Yeڇ NG1t}FY }.;]^2gt?V/%zyz^ zNo?>cVjZa! eed$1*FcdL`|_0LӘ e0M0&`h&eZ0 L+δaL;=ӁtbҘnLwf(3|lf>dlk3ʠzjԟͩhN{~t L":h)F\&]V7 =Bc2Iz9|O/+ s\gn2t3Q2U2J,+bY)`Y5X#z?Q=ۘ)f6mr2x}: tTJsNPOnZ $nޅzQ5QGWxHSh{ڙv=h.@ P~D:Ng9t>]c^] 5=LefOQ;3^g.1W_`?CFE=`wiAG/FQ: e=PFoY( 3LOS*ܺ1C\ŠۍzS` L4vDhs$w^5pz9v!5?GsT"Wr@}aow^{M/?~1:]DtzL_{A+! a\WK"a+zr~ZgK TݱBΞ;93uYPᑔiz:H kEC%ϡJ|3eraG8Dq,3>ɬzT[ddmAn!Jp@T@pq`;Ð킫v! O+gIɷÁ?S3yr8C9P&NʜnthP:[=!7+#+Kƀ7epNuzͭ}/}\crNʝ]k2Cv @MKRy9 f2R6k? -)UF=v̔|¼Zs(W,bn9d(x:~=C1'ao(1hMrezqո,SNg-e\@.TeM:g${w̖7M7VMS~);vs*96pPRX`u6yۜe9e;j&˶de)9~ic5vvC9sjѡ2\'$[y 8(ΥpmR&$.xRB%8|EN&e*1*&eVx&dYTj@0\g11Hr6pEGpjºOхy xT0UO'Z_.`l˭,OCCCq`~IXx’b$鞽BN2q0deg^nM|Le0evV~bQGgN\f\;FNZb*pɲG9@[?9.'g!o_68QKgu}gb):=rPYvْJa'O-LN Qo/H0 ᇏUmUB'KMv~wQݖLd )J Dz yb,!p}!6jYݧOdvx3fAR'   V_^X^6.n;_MpS|u^{U3T?~WoH%#VjlvPKɷHDڎipQ&U窛Ȕ] +J"dfƂg((&:6*|@pxb^~+5=mXI O$ &R_Ư`F`,6XbwY|YūY<,NfOf1)dqXlgjY\ ,><߫,3uo̢>#}"lc%UO~j.x"E/m8P!M $Zr'a13L8srbB9?#*}JL:}b%W vΣ5?`#mh&\C5e*EFlIfZB3vx12 f\n9f In#FbN7]704iM(rj.08pgHpQ4Z7;w*0jq&TٸwGp[ ‰ջzg ;`!dLnzK:~L`W 2nȈ/q1$kgC~328ة YZg0DіUFy5n;hcNS^ )tY|pDxܔPa] r@Sv"E]{\$XK%% /zT{x٥ēx0pIuCu75(*2f% 8V)V35>Qc*1"`V b]+ 1Qt;^xޟVS^]z^e%UW6vD%ꀙZ2M /,^K-B8_덴AH& &Ht؃1 qy0 Ɛte8c|xx8O4U\s4Kt:"Ld2} B̈)Q#& GbYozϝ`p.)`̜k2B{/|˻lɦN Vy^GB3퓙i[gj ˕w<ETj2ART*e{Lz%EG K JȊ "tHR멼 ,cҮҦ*&L p C)PՉ>W"df 2i7=,}^g;M9QV5MXU^Uu=Zzu!ta -~̩-RXA{{=ܰ\Ag4 Ȩ.#DnHJ]T\d6fD5{%S7]x0|FͤRÙVD=a\jF0& r,pA~;րeu*=kV~>缅׹ 4FeWf-cY N䁁,lfy/&f 0/0Y\9!&,c)Sb=kLYB! DkH q&2Ug֘ 6{ / &:0οc]+`A+,ǖG>A:uMoVos ?ico<^㑅w'}`S )KdJώӪ}7ö5op߷'BNŭܪªTz- aeYa5J`U ~UicCmB pz&D*)Q̋a8ve h@^(AB֘Xي4kMb#7uӵ'j3\kr (~];\H_ Xw:8lE5*тíbűԴ>xֳ< IMk!LW}@Rʽ$ vOJ;"qw`ۅP|,WbG(.ʼn.v@5n*2Gu8T̀VXQU)3a5} /&++ëkT^/BQ^ Uλo,魐ƠI@xßP]{dv= R+OoWgEe٭:33$0*|cʫ!QIUGE'4ͩ\f~u~o@ u)1kBBn X-j5:.$P(||ZW_F+Фto[X d0wB?@esf)uLfq_<a#;XL`WBiS"p, Ǻp̄x8 ǫpqt8wR(V[;+CȵwkuU|QFmź .p㱇cb (N#9@Wa#\p ?ؽ;4'BP㧇OZUәJ(ATej˔^^DZ MT }lfn+БN.|N2ØSgʹad^gIPEZ!{qkfTmjuN.hιYv4{EDㄚQQ֯EDEz[f䄛?U&C+hN=g?xrj"Y7WhNA/I>dU[wkG6i2 a`zGRe\kt:xmv@h !/tW~D.fo@!A(؞( B'KFBKgZ[&qu|=:<Mdvў 3n5.{*S;w:kF t2,' ]oooQbup4Ό`16BUI"$A ;A7!^0--7DX R gp0 r4A H9i#E w ݠtQ I%Q:MzqOl-?Q0N!XIɐf@4 ,Ȋ? @0F(aMPS‘ EH8EH3Qs%`4 %C=:N0.+JC`a.=PODYzeVr`P4$ ` `(Hc8*D#@.#Q1j4Ƣqh ځv]h7ڃh/ڇ*gh?J:D_A :#(:b=:~@'Џ$:NtC3.t]EnF;{#%XeXXU U8a-a=6`#6a3 {c*,؊`qnc8b9 8 G)pq [r_a;n`8é=;N34 8=K8g^e\yx|\W<Ex$.ƣh<x<x~O#n)~ Oůix:g2< s\7[x^b/r^x%^jux=ހ7M.ނ61zoǟx'ޅw=S ޏ?Ǖ |_A >owp?'$>O|3/8_:z |¿|{> ?#?UPHȈ(h舞xOE%b%~$%H*iO:@IiDIiLBIҔpb#$DH4!#9iAHKҊ$;iMڐ$L:N3B4ҍ$ =K$d^eқ!٤/!O2 " &!d(FB2"2#RB&IU2L!52NdI,2!sdO$od!YD&,#;dy}NJGV5d-y#l"p#ql#$n|J}::9@$_A 9D#(9F%ߑq9A~$')rDΐ9O.Er\&+*F~%oInmC$w=r_[._sPJRRS RSURUS RS5R5SI7BԏwaBiڔpj4FhCcOc&GUe[=tH20`4z2U$IC2@Owt$@APoL" ]_ >ު:u̬?6Wuνs=gV&Xp)Mf \A p9l-pl+-plp5쀝 v[p-\opE) T& 5:4`n& sApNy #pw1~<Ca|GQ|>'Si | n <]8 p>OS4_ysK?/%x _)|~ ߁_ ~?OKxM-~??n,ܣ]VՋnӮegsNy|>Y]6._aY&3. ]ƙ7oaWml'v/KC%Vf 7Te77ygͬ}lgAv{a6v`wyva]^n^vgCC#a{}}}=Frx6O_-j%߂VQ-p'j\Wi "Jܻ(1zȽUJ^IKj$XWQ:mk8hي4xi=4=4Ay5)!-b]ھvvvۍr:(gw(m7ڭ¡k9O@x@NL7\ 's& KL~owe*5^y6|sr͖WNT+3/ɩ5gFɇϩh)jf11x dYRܢgZmVm@"5B#r*#j*qVhYq(qC)LզBlc#={\ԕ>'RAR*`3ќ ,BPE &B ECGXr]\<9,EWʡ^9+zPˡ~9/P<ϣ<ϣ<ϣ<ϣ<ϣpbս],C"$<#e&am%<=v3 @ uȂ00F]N)$j|6-VdDgr!i`B3UTiDԢ2L-*iPhf٤\9F5JQr)ƔBcJ1`L)%7(A1m 6FѦ`*4 C=f 9OyT˔\UzU^UWUJRԫ*zU^UWUURԫ*^UH`Oq$SEtVm*$TtJR稡sV`k .PR(K)R c)m鐠'z F{߂&}؞kT F;nCHwe>O 4is}*řDojR&' pyӿӵӵ3ˠh9azFDM\0p`W    AmP38)tR0`IkeuAdmfZ$C"J&3d&mmmmIII0tl5jұĮhҮh5k<'Uӥ8u9%eal ealY60,TB5-TB7[_\"[(F6:F6ʵ6M-oSۨåMK6.ml=V }m4ĦK`ʡC+W] VCաjw:uU븫qW;؛fp߭~[w33.r]XvQ[C]tLU.];.;.x.\-ti ]ls9la@,8y~\=]#Љ9xl~p.V6Uf9 8i8i8i8i8i8i_jjjjjjjjjfrqlÏÏf\444 ͎νE7d0 2 A&`YzY(6 #8x^$y92رd<ב\G]+iHpq?GL =tB\l*֢ :tnIƠsAwI8AV6tn1bIW+3KhL1eJFc]Q2r4BϤ6FnQ ,jQZԢXDOk&Z[TQH-QX?EcQX?=SE[ Ȑ:6M}jS6]. %mzzqmۋM`S/ 6M`S/Լ65MP:ԢC-P:Ԣ X.BQ:ԢCܡkSGd^1'+(±ʴ8[y㯙Y5kǴp󬱹7װՕ몷r*V\Ѵf۽cs)Ǹֳ݈ɫߴágw?+,ZYM3ǿjt*>ɟӲ볧xBf45ʰô6O>±<.l|}Xp3J_.,6( r7X?_3ư։<#Rxl4(k˟8|GxBT{aa43"<[I,yrayP:xIZ8wt}.[ǟ cp.;w@Ϳ99 !}yz3G[xF/: i2p48hqy-#:@eMs*ȿQ?spS\{8&Wiߟ_;cC}A}O ֩}oX?`,y1j^Zm, s|Yeױ__??s'y pU#'?qWyϗ__:ڗ~X^(9GLn_+~X,}+_YY{d>/y"yčϳ׮#:R@$F6|ㅩ/γsҗѥV&ӥ%IX/rGX,n$O[-.gZAgT\Z)W_kUg5݋9ߐv!pvgyBzM^ endstream endobj 13 0 obj <> endobj 14 0 obj <> endobj 15 0 obj<> stream xU͎0}.ua@cBH&ɘyꐌT\1&>{n7F|9Q:woqΝ˕nf|MRJ'1}_GwSB%_q:͓к:Ur ï8?TnI%[=)طq*]]qg4-uaץv2axj~XbKU񣊌M$/+ lQ&GM3pNlB0{S xM^+rސ7-y ޑw bpC77C77C77C77} QpFaV gaV,nB7eO>>}G }6~Hs !4`B:C;.mn endstream endobj 28 0 obj<> stream xy`T0~s﬙Y2kLIf I%$@! YXDE JK huVVRZQkmݵjV Lշopyg=Ϲ3\f,i57dV?g^B#85mނo{mv͙\=:9W͜Ll&KWmUNzq\s/%DɰwZ&bZ{Yp>kJeX"`WG{k?Jȴ;AMQѱv`v{!lYѺc9!ӷ{KOֵ ^goz{^ Bw7[儴Cn%<4DP61DNnA6r01yW0{w@A  <r0 g0~]?pQ*#@t4s? `^J'b~ y?݌*̯0! Qz{!|?E\// a#JIc 狚t]D|+E&h_7 tŊDչފsii[d&YHZj2@ -PЀ\ 0ja=e4BbJO@8D_Cnz=~ ?#|}GB:7na jQ*Sa֎b>I+vҏ8$ӟӟ/4&5e"^53<7#tT+w$FH@!$]<@'q R/qI06RnId LfQ`2ATg֜s#[ ?o!w樬&(=Y;T{=}m]mQ3 rK@@c5j:ҥ g0߈XS5w d"$='HRJPgESP#3=sIP.@4Ѻ҇EFгr%ZԲrz:G5VN҃>೾(2}(Y +F]=IBG#'TI$` y( B~E$x]Dn&? G(2 |! ~ڻNh[Oϊu44 >7x[ծN4$lIrl"HqL)Q&# :ۂ7XωSw"$bʫ qh5JڳG4m޶%Q'Lfuhj]"lBTZ:\#BƋUڃu~l / :[xEoTUCSæ][=^\ Vܟn[u_\{nd? g %Nwzkv}Q!]ի#|'z8{Qcuz !҅y\;jچcOU4<_(|ň1ii|OK-FCk"3jqT~^]Ccu!PUX#'cG"yBg-E Pii45ޚ={j=-{ZOn]uq=5=-.Z:`" Wqb^<5VTx)>%CBF i9NN= 4|G+-}B0w4eVwΓXpUwmsV\d0YֹbE;"a,{{[(-kݼ5zkp=5iGyTY. X8QCjzQOz|QYU)&G uVh;͗*(.S;s]{Z$]O:NyT8^oԾ(/1gp#f4Ej?2QBW;W\ծ^QWKDp M'Fm>qHJ[Qkx1'-D8~TSyD zD zDfOWrEсu1lFvڽ|KjWTسm߃>9.WooSk$i-]\8IOFԏS/R'0:0ŋ2|Si!+*ԻnRٴs+s9ljgeI2 D|?.5bvH& (v+7k駋x?4ä&`d(&d2W$l>|۷+ p Gceqya=R;#ӈoh*% LlR}uZA6-m:\Φ7CBCTT| PrBJz k>1IاԪ&ıJMɰXFCX(6et2Ȑ˚oi8gBI0xCiL9wkC8ݕ=|f,;ކWA+I-ϋn>Q>j1YaIrtFghtDG5L`B.TejRҘT6^PMXVi5vPUHH! !߷+wWk!no +h.#1A,PZZ<^˘cu27\<*lo[K,K$ V1CGJMeA g%wmGÄzVqa!sf*ZXQVWӾ抑y-!/IV{ 2q5 nQN27;ȸx3}dl^+xuZVs2VfS0_w\y(mO[2A//x~l&jZe< 눓P!I͠v40 +%$l3c%+FWhX UK\ F@uTHxNTR0&$C蓷&MQ=m͡KuREjM~HUa91MLpy-ne2JJVPX3%Ta6Iu:7c:N냁!:uj<(;u 6QZYҪ,LAq̎DJ9x~qťY!Clq^sb!Xzl$]>سڰ䱹FǵҜAڴ儰'=-B8>2Ի'v5B6ռ RA8S˦3]PkY]O蟟F*{ F|"λS ViZbsT#Kfʖd<9 s}!#4t/o9tY(?K#߬P̱N]sm_<ɸ ;lnYguC tÚt)60J8,Ņ X"i7*@&_ GB^gRr=RnHi]w0@ ރZ/*v؟R{?2₎>9E9 C ȫ-9mhXEܼn՟)ggp"*mgoAG*k.c>I05 S' SVfG*7 :]f*GZڶSVNZReeitZ=]=Wpxd .s dA&j@ChcyB+L7.^aj t'., h̭ F}]Kk4!9?~k;*i!tP 6(!F5BCئ3tyL\+t0ϰ$g$.K:uy:^肺mʠx L7f` \g ԌC٪\);dږ4:1 ;mRU{v YH]Cņr^[Ù爗Q5~VAh^'*$&FC9>jY%QrR)Q; D$Tg7 iDݖ65{\W}ޟӎps3snjG՜H?wf~Bi7fF;݌Lcc;- ;LB6pHVoj^5 5*ImK\kkY[ #)Js$pY` w;3<>.-#gE;"{Tcx*l R8oY!g4n)M2SeIJL%Kb2e.[Cbm C#T8={"g{]$Dq^S/yMp[mL4uWjWaQ<M㴙29>3Cefdl3LFA&0'|coT0H-gr 't;4GJZlm1]g>۰ʘ=eJOw])aWtU'5;+Udsz+Sf#!HQTIMzћ-1>UBx&7o:I}JxXg?-YC-ⓇnGdeQu_4 xi3qqꭟ ޳X\]i'&)dŰߞel 9"sy TރtXn;lrB!yɶSMv{**x8SUv%cO-{ە{1/BB.^8& p+Nt 98]刍5x TP Hc;7R5%NL6zR:%V/Róga_=roWwo!V&ҜiT!€1Sj6C`Hq AerCJcXC[ף[S/~thy'P٭ggf>qb8>&;߻r'Z'0?xh6* }Q1IQX`9sEe)R'Cr!q6Z\P`6oKwgsnef%~l&#@ϹцL`_l6LݗѼ`ṇSí|{ E+4n%-`C:|'\RTmx\y!×DZV"y/cO]-cpxkHB{ s8)OЂ'(鲰Ėz< =Ĺ]2dZR qcd5cA`pք %mls{n+훦&9*W}-]GupjJyܪ].6O[v]W:8p͏].[7+֭?p矙#BD?EWo2LJZ0vm7J3P##>er@vC1= .r tm78:#Oqo&>5NMeE3}z[?#7>= ob;.=/k<'_6#ό'ߌT摳bb<Z&\.,ˇ90) ]>':ȇ xg>$僈awWķw9zuF//ő{ãc;wŝ$pKb:n/hb:HƭZ$X8t\`8M}G 6#0qTKPz NT|J|kaAj$_|_0OY,q./.o^OFr)7V]`-gPw-i1Y:u=67?8lAx.11bxd} ,'Iڕibf /2O+SG+(-316[@?򣘱H9 on^A۲׽s8~*n䯕ˎ<{ɼ\c׎60;2sN f59FNcbK͛23-p2#V^`ʬea?*'y++SW&0!w<А9$Wb(3:x!r0 U$ -gs &h7rz]FDS}5?p9=$܃Ԭ/h0\wv_T$ OavZr ġB;gY7z.pi´4;xϫ'K [GVIf)- VH:wd[Lޢөb_s k[5 FͤO,mdfmlEu̻dRMlQ@^}z:»-ܫ3\WȰxYe s]*ry2ΗJrd8f7K>hj~,ቡp|X1/}C8K`/L~S8TtIFх(.f #9M^ioT7hV&wXU*WWLYXb4%YgNIωmTlsBk}ҷ28%KA=nXgZs1#*^ye5e2 -B\hr@旔WQ7sVk2'O?GESt~muŪնܲ@K^Ʌ5^ukQl|Ww2䯉C)z/_ZpùOSSTE*DUKU'߾:I?fy>1i],bkcy1}ג%މmBlͿC^KS YBůHMɏ"[8ځqB/{/,闇FgF5FW>&{|)~~@~gpi6lǶ(EC ,=G&90_"-%O8GMC^-X1a>Ђؗ}qcF$(:3ۿ#gI ߅ZӇ:CHR!FBL%cbj>띄/L\Lbr[CH_SAB7E)2).1 mD*?Ya_*[C kV0%f0K& #'n\tvRIfaTl6NNTQ{%f}s4Ǟu_~frIuK,rCCITDq?zb^cƨJlW8H*Iԉxu1ș'^"$%$|jRCZ u1l2 i$MdYLf%ׂ.GJې+*N'c ҿyCz:V?d'F\F6rl%v\EvEv=d/Gkȵ:r= 7A-GarI"^%c>8C~L (9N">g1;&"Ogs2B _/o+5;@ P ԐDΓTK->x # `+H4H' -9^e0 r |P~ ("@J !aLK` T@*a*TAA-LP3ă9Ps|X Rh&Xa 4RX- aA;U@n^X}0alMpla \WVa\;j]^87Mp~7n#Gvp0 G8 1 p'Sxp~?8<Ix ~ O[< ^x ^Wބ[# | OS |_Y _w/_!P22* *ITC(G@DSZڨ:h*MI]M=K3h&@h6͡Gh>-~ZHhbZBKi-!:N%t aZI*մNt:AL:Φsh=K<:. 饴6Et1]BRVmhEnC{:Gnr^A[6Wѝj:DwtKz-^Oo&zLHotwһaz7=BG «Qz>D??G z>ƿ.>.>EI_gsy5}/ї+UzF_o7[m}GߧGc' ~FL?# %=K¿~EEAIs}])^;N)F ӥS,[gI3ơ[=kopU}]({UؙL3{vhgW1ݫDDzz$zaZ}ך7q|mo"Hx%< D<"H|ˤKǭa44PgWw1iMjlmʤ9]"3/]׊; Bui\T␼II(ɇ Ƀm}+zۖw%D7&_-d+UWy( brw< e:ZE4FH:JER흫::4<"ܟs}㎺ 󦯯gCW .vl=*iX[&-oW tmtvX1Љޡ}`֮ddPWϪ]xծ|@9'@&`ā8PBq4Ł (O/(cuJ[-ƷHq~ UGQ@_9jqbp|~tW.O/IXGhsdyWϊ5 !_ZJh7m2!WJή.TZdNYP^[T^R,%Ej@1ٺjW,z[Xv.LĘ{A;Cb[j_ۉںl}vW򙬿Ȯ\.hoEmkK׮Kw2 o|:1wB,wrС a>͇ˠ zC1>ݲ!ٰ!&ْy'T1̬Ø̳RDU@}P ~l| oWiB66Mr?F4?n8 /m爯9>Ϸ<>@[gy>e|\'w|탽վ=vg}qWnSآm _؞+TmH9$j,w};侤!ǐo!Qb-MI)I1)@(E^SHAʄ,mv.ק<^mWԺ:רIBaXș6gh01CQ^f@-1*P#5-٪'pdkJΛ;9{=]';&['L6LMVMOf&AHQ#`9oj4;_]TQ85MNewX-n<6{$ ѺS25 y|u:)Lmjj7|i6[Ӛ.E'΍:S}Yڿ`,h72/W,}b6u<>q#%7_3xUI|Qk49( +HDp`/y<* SLv/VJ)V4ީ( yagI"g 2$3ǓT'!I͔h:ZYME8/;TTX}dX/?^'DإNm? endstream endobj 16 0 obj <> endobj 17 0 obj <> endobj 18 0 obj<> stream xUj0E -E=5` i!Δ F6W7Hrs)ov]fıGOC0C7-ݹ2e]8_Zf^q1igfS6?fyNڳ7riקa=3ˎֱ|lɛ(jSMm|ev#cƌ[YU޹H&^W\فω-[o߮k%[d3"2.2mCn[J~ { z nB7M&t nB7GW+|E2_W+ʻtݕݕݕ;twtspstspstspstspstspsqqI?YTaC0?]cLe1C?j' +>V endstream endobj 29 0 obj<> stream x xM?^kydNd:DbAb"B$Ĕ4bVB E[V4UCqEUUTUUUUUU$'my=kwy}'0BH Eeu[m2,풞ڳ@xʎt7>@ȼc]xW"`~q o  SFp-,1MdOB(96,2p|!1 cH'½[M $7~1(\ -.2')V!Trc 'Ij `qcpt|%|0Fre۬V} A+2̀+WDlC@bn׹ȱmEC@aX9 (xv+,G#ڧo}P41h8Ԟ:Mǣ_~ Nze> UVr& T3^K鏯v8 ܚf-:ҟ zieO _1|SaxC C M,3fxFRV]\8bxH:O% +JJ8j5xK,cJƍwG 4ĄĖ-S:,xC_1`xyI rDz& ৲%Æ&|YDfc%r 3c-5G7Izvü 7ʽ# ?'x6g¯FRoNQv;oYz]!VfݸѶ?X^k9|3gwNϧ}¼LK^]~,~_Ҽy|qܺZFt]6/Jv՜?; /M}gWWAۥrːjےK_Sſ?4`KG7ΟNozW\Qybr:H@aYV1p9Bxu\\eJŸ09:pe#ő\T0>|Lq]UNbTԯ PEBWSXD+-%&>eCVAfBGStgl _ϣqDo:%KxJq]狽 #U`_{ʕzx;ԍ([c?L׻imgyn֏fl南QɲZSH6\cQ7NoJ`'؎+9:R|9i#3i_M /Kܒϋ17UuZ1] ?̄߳\gŵ O۾;qǿ|Fዬ/ʶ >*=~kf_8;ԪgGɱ 㬴mYoDSoY\KyUFw>??շ-ԲԯRڴ=7"?ٱv%ʲÆ+׷,»$r$z1QV27qX1~|̰B qC [rR7l,ltq?g;γS׿ʴ78^];Mn>5J?1a3-/L3qMg͇ 'r=#NLԷUL 9_}Zsngl,`E.l mufѺiMo>c6 ) _=0uO s!`ߴV'iLD{愡cJ3KOi&TTL *>;s-`ֿo | {JGǷqz$d/;^:>ap{a񠘓&MjeaXx m~JÁNÑww/sRN,|/41kjC`?6X"'Cqߘ(Iy>96ܫV?rĕz'}7ղm{wL1;#'&<;X|9=&/ ;_ p^7Ƕ}OY7OoXeQmT)zD˾ކ}f;5kiO^3-}tN98I vsd`pxR 6+9= ]AAsa<{"C׀?LEgq+a8956_a莚WNLA T'{v튒:h }1SV)lUK3ISO#Gvm&ڸw_u\aɫ+ݽ)?ʙ?N83?ϟݚy_kx b~)#C.̍__u1Y}пjg?u0?nXl_=|&i־!nsf*ǹ)UNy1}#c#9'`>pG&&ě':67崥cڱZ0z,gϻ߱ԗzgc锰®Rֳ󳦲γ:Dơ%:1аݳ79囷ʷj+Ưξi[<񼣝=`_ˇ9M@Xpz'ղ::~nq:I7i?|dcO\W7㺴VGvSXRU hFe80R(Qc / rs1]Ϗo8&Vkv{tm2#-^gz}emtoQaQg^*L.ū%8 ֟{_L챧mк5#|ͬݝ{+dyĨs~9fN~xk)m-Ȩx+haܯ3VפwSwƿO`dRⳟZvkk^#~H嫛_5Ot9)_vi}j]KCkO% ͔6,M;AL` 7y2U '@Չ/$ ~ܠb/}xx'埝5A-:x Urrk8n\s9>e]*CP6*FCEfGP/(նJ?p*9px.=stV尋C {}ͰAi-OYZה+v3eiv4c'QcsG~Leԉ[׭ӾbM*j[ng&<_8qc>RZϕ]oXϧRNY=lk6Al|pj50GMe pE1ȶW2%!%>9e|Gd{3>oݳ|jOa el/ONv{g$9)cUߖ|[: [*싛o*fɻ+a˝Ϳnᮮ ވRɚDqo.A'8%8=z?9vkB'|5Nuw6[uG?Q83ʷWq@}7~AM'lݐsS\1&7g]aW/?w>9װġ$DZǗ??ݦҩդJտ4!Ⱬyst3%, btlVCVm8 y$Y|/Yȿ!߀&;}aFĄA@$@t+~L/a^5-DZfza`6h7 BpDHbHYt5y 7wVmd7~l:::z$b: tГdЩ@Oz ut?Cw@O߇=DOmf۱vg݃tOн>@g@gYp payP$;?+νgr2PS8F>;hԂ< +EEPu` T%<]ls gPdÁg<y~𻏆jH %)T$#oD{hocq -8>Iq(px9nt/=)wumG߲(vp!HǀteHW!݄tB!I @O p)( RkHNH!)R>)(He&tΆ|.rHՐj|\@i v!7P&g{ޒe| W!;=-6ZEC :-Mi#|hO'uߢ<-)sny\|/3?ϷYE udVFVQUSOpPpDpBpZp^pIྐ Nhڅaha0E^.. +S¹…W k.vn~!1IYEeUM[DEJdDXQ),)EEQ2Dtl|"RrQVAECGt@tXt\tJtNbX#6mq C,n+(*-GLjœ3sU%e5}#K7ķ%D$QHt. DK$)tIwIdddX2NR!*̕, yERR#Y'qIKvKKIINJJ.J.KJnJHR*HURO$JNigiOi4G/-I'JKgKKIJK -=SsoWץweH&dIfZdY[YGYWYoYl@6B6FV.,!#--mm]$!-/g"B[vyA iy%Oۦf,2+:l7 s{s9<<<\lg0O5W_0b^i13ͻ͇'g͗W7wn H,*g DXb-I%˒cɷYFY,-.aVJp9G3a|a3/7- rwm6'eſ^{#鴥/ٰڍ˽뾱&tīy/i\"QzO%^c ҾknJ?u<{͋+ܗn?0}RC>k.jN^&8샥0 FqXb_вtSn~ȼҀ vwsSV5K?=Ǧ0Ysi㡛M7Яߡ~^K?ӷ1^z)7qwh[>:ޠo}n8 oC}]/Ǎ y:18!z#yy,S6k͋!E6~{i}zc*N|.O|cNziۏz6E}hn.y6Sh"!޸34xƫ89 zaE}۸~_n{ķe|#{w?|b??>~j O/ǿ }q|N#Fק@ytn͊>_Sj_k84#ЙwGrWqcEM߁c@Y}4D{Nl7$kwH"P2r(bTF=΁ o it]B? mt3XL@ `8 GcFpk)⎸+ Tw(\' Mx^,$5x-ވn=>uy2 |°^|glpCWpvEd7]QGRũ%6I8j(UoM˹x|y3xh?̢ǔ7CV 9ڻNo_9l K8~ˏӹ<~q{in=??rnr^i0??}g %a$=O'hͥEZ@rHJKCߠ5MZKҷIㅁX,B t)H } nAC  R$@}쀔!uR6 4R9!/A6_CxzRDhh9@sPZAkF@Νh:4L/Nba9w2S|吧Vdo̅>p4"~oG:>%Ki+ ?~&:X w N E ȃL+wGԂ-@QGT=ޚ{^'D*d@~(<],J΃ȗ/A<:llCˑ )i k6nأ)˸ vH!FzذeyEјhqh6/WRҒcr>7)6m;=80 !%F>g}rON}rON\1-9a4bxzop%2[O4lg8V2uȰ,D !Bȭ-@=QO1/ ԙ,O1nS|Pw:S֮ty^;!OōJw#4@}@]n~h4P? ڤAdGO\ s[W{9mngナ f%Ff+nf7R2{H|Gs|~Q9 ÿ0 ׀z莆yח14Nqļ˼g>m?`F`sB* )L!|?^w-q?|_Āۓp+"%2u,I=ח&{Z8, *#&b!6DbH'%I%mH@2H7ҋ%$ "y '%d,yL SSdy۱ᖐd,'+μ?Q9>'咯95.U\'ow$=< nRGAJ(,gDTL%TATKuTO HMԏS 4FHڂFhCh43j~7Gx?B{~'?BG~.ĵ*@ui6P^Jzd@V͇!^K}n=KM}?n%|;iZy|C|{ q;rf#"< k\& \# fFD,ˀC-ס^}zHώvwƉ@ bZ1Znv+;Ka[uD(|\QEvq}]{wt8[OJ .x~_kaV}ÝYiBAJpfB|iY<5%h\+R!VJ|?(uF]PW db',}Qt@9(A`iPT M 8|~pZ5AnzNl5[398 ܆CzJ~h}G!{{dNmXMNW7ngU1u5u?3j뎢oP?:Gv8Q|c=1Ep6Ew&4 N x|>C`38M,w'MB@= / o2?ާ/ע(}Eȣs46'@ =j[ eMCu_Dv- @F4ڀQis12Qu"Fߑ~7X6Ϸ |ߗ>ϣ̄^w]F7x Xluck9׽QNlB2V-W+^u}'l¡85v"]neGh2^CGo0@X; &:a x!j:LF'@o1t` 6h',qz@3Zb1~ %E@?)L焑#wuqX/Q& w;\Q:9G!X: \ EW~]”Ay5+jU(aA-]`eo"Dz'鎡t<-?oum߮m֩)[&%&;bcZDFl~Vd4uZZTeRX$ܿ߄eꔓ1eT.Y\Hc Vrc\l i{t93%%zIo U ν  "rU ehu1_7ڋ\L(zJPfv}(%067E2{*fS 6#ٷ.HA. Qŏ\XwӅ.Kn:bJ3<(QT-*h GUu"{,t 4\P6KP""(B0Hf,kye Q. ӁsPmQoonCyfu :eK\BZ`jZ%+ .*"`3".TPlg*@ΉIyQNQpAp:ԉ; guiRG@.S/Y47+mƨ«["vWQ*\XU*v =^NV4E({ՂN+gJs23'}AB2Gq2%=KsJo°N.g6A\zޯ3\Ȇgp%.qpQ%*)[,{u%^Jm֡)vsӚ {_GDAr!6U ".=y@u(d؏F'@wQMx3<DN-R T`B`w@~^^Jv-ށCZBFOpK,Y|w<ƌcp,cҽs_S0W%GN-`>?9bPtAT'OKؖ\2f[?q^d"?O?L?cBIݺo4$2D0!FX&Nu;E{?aj^^.Isw_f7ZSwd;[ȈF8C5+PR`^&ƯT(1Q>Kf2?+vӘ(l1z]^|궿+W%u۝r $!c, >8tpVi <-P _??>1[{<ػ_\q7p==yP`:4Kߖ):m[^(pJAP°-QܵS -Ia@JT S-:/*__Nd^jxN 9sO޹gh3R)kra33[م:T%eL5f<0(/4qq`8Υ];M2.%F %jV؆)gUZ"MKXs0\&$L$%gsvVg7ށq;TyF5gW.Nj؞H8%DzWD*]DDȫN!Z3S*Q&,<[*b=N`u q'~rwߙ8{":xL huZd7Rw-&]p`t ,]RĈ$2oוYqF%vF&?8c/E"gC55\1r "-L Ak#m'ebf 9&^9cj8s_BM <'y1࠰I $rbcA81 :6),\ ?C_|գmw}էAټ#GL%t~لMM:b))HeYH4TDJiӌe\xI X/// \4K('N޻q8.ae%a]7(CpZU|rOObAFlSiaQ~^>YԗTX}9r-! sٸkyԼ|NdE!"cLv+16,o"~:?"EV`k(`䔛 *qF20†]z0Wm3/Čb1e g?`劙wBlffseݜc7Kg-[h73\4l:;*f*+B"+f" XL#FYTXVFMlRF: ep =LSAv͘Ww-Y<8Lĵ9v-,.cbWj蹬`Σ#32$ʽ=?ӟF)>5łu9?A/Trݰ]mgڹq( GCZRDĵB uRFʚZhg:5r|4Ӡ9> SN0K'8s8 lG6 Rq8F繷=x#i|US_u=ݯ?v~AFj/؆ B^"m~N,ٲn _tZu2{@ ,Vh_ "S5 EQ錊,O8šՂ(\3 3أ@05!%pY皁!Q.Y\g;Ψ(m65u0:+Jnx)ЮNu0>1b{oy];uvE:VcEz]p5CkF/pm KRK!Q-xQQZbHm(1Yk- i gĘȔȄMPĺ: <`4s<"<$E/DMxI.l|#"b})%TA]?֧{&n ;PDߣ&X,E5gA IEeH7(]׹;]guKOv;cWj灜i+0HуW U8rb*ŦzRlzKl*#U[g*8R7$R!8(9 c"qY$vFbe$/F ]:/Ux;o`;)д.WWFLn?n^^X:5$r~H<#jH&=TaP_Bҡ]{gg~?oж0ۮv7m }3fOO-wg `Z,@DE$@Na Z3d TYS2M :LX;ʫNr6Q;)H( puL$aq=N=HHzz $GpT'&w\+Aάn>AU-J32H0Y %=ggw3yhFգK,Hڈ)*pʈ dZfLdt8.>3.3c;ߺ̸Ҍ([ר/'.{:tWywϺ?VXk~.+VZհl:k?D X?`T2Vgw)1kMONlF/ o LF{E>J䎶τQ-r 8T' >"Co3>v_/Z ʘAl/]{ri#>xߐr2~ 2 i~a)β;eLpyRc/eRE g_`we]L&5[X Pa|X?0d0ubơ9cGS=YB*@ňY㎺S-FMD#NHpe95cIɉMdOl Xӽdik,ۡC;vڠf{ys-;_9psNqNݮʇt*ZUꊡYu,2:cKyT)g\,EFVHVZ0SmqI;XeȊoX>+^bŕV\fřV v+Ɵ\7uʫ G!Jt?#6U`yv-?J]UC(ӼJWi|>k9p9/`RK3LihBVjSQhw" , NՁaibSR;pY 0^n${<.k8$/ B>!(&<"fK!܌5+c<+t ;1g?yG`~ña[a~jg֔Mj5h5p:ErJj ɂRLS)ChuiuJi+cd)52D,:c6\cE6Æl elx /96<چmϤ6|φ/0rp5ߠw6Ԇ?Q.l[d!6bïpE}n?B]`i>+ ݳK3g kf> α6<3R{w+A>l ~!|y;(Z}@ZiÙ6a xYSɳ6lM }})}joKƗ|D-(|7Ax<48U#!D߱L8?Ɉ'g:16q2y=zu?c\f[K'$p<4 g@o7SIuX@f*ZmuYЪX,},C,A[}WbLYB`MYA BFC`b :6(5uܠ%bPJɏP'_ WmNh͵_h~|uf4v:lxέ1aI4?:]49j{V{i| ʤnI52H` `܆TiSSʑbPÈ,%t~¸%0@ -N *Knœv ɛAB\6!;%T^Whd ZG+V@'K+{y6UNiedNkKLOl21~1ʇχPMܹgu6q:Ʀ R͟_'on2Ip /LL'T|H=/vL[ 2bC'} ޯ+p kc6xwfl368mY:L8ᡫz6XⰭf5۳+zұ9Oы'<ƪϨf/%ӹ?Q7r-NI*O)]Tey`J!aɨ!;zUPT\˵,Ҍqg$kR}ҔmIz猩 ʥ @>3Du ԩhaWKF8m98*UWt܅VGY6+[!^n.TBzЮe_ (A5HJ]&/sΥ݂uI3Ĺi^/rַIJRҡZ73ng ؞2`j3@Y x7mPa]ns_ͮ3v<:0o_j'ҶV!Hm86}g1cKF?4ڒwG%%-:N_z0Xbl/L)1?Le+u}>cKԤeZ N /?msz2( TFvm]6:ȫ::^'@Y7:hu0uPU:ެcuCSqfD@};e V[3ݮF<2!55e5t顓>[CcxIWwd㳔Y󺍃5[c[Z|&newvj+P|TMikj,lٱcGyP熭W'P&yͺpMVşXp .TzSI%n.Ou(a}nd1eMVئM$Cp&CәmXm9p:s r8s>>Ҳq!i vX;z341Cإ%sG MOEZߡrׂƑ* [F(_QRL1zKK,Q-6t6dbH..yu]݆>'ϧN[anX)np{n)~ryqXRne 8 &oˣ2fӘ.s5ˑ-KJ[|cIˢ\pesox.͢m=c ƴH$uk/oЭIEHvD_8IH5'諞us{e% ~<%<:%ͤ'L-`UN6N1Ʉ;Pvj eUg᤬KAu)9Ncyn՟{nrp222LG&̥֓xn#EG:9/ 6@sD VR.cpO3}Xg)G3{^&+6QyaxT߼\0aRJm_P+=tĿTe +ü2h'jJࣣ\෶1W)W"hvZEhܒ6.zNL>|Ej4 ֤ E#*FMye#9fђ`4rv;+QH_ǚ'HTQzq:Nm^mmmM2۬6l)|9)ʝ{4m, 樜s(rۄLfX8m :RŲk S v;ߜqx7;v8N|e~u?KgXìf5.dNJPy8AּGY(iIn'ἜhڜjucK4>p1oYt:`: \b9 pG=pU,".2쫹w ۱[Cx4ScD1/|Λ7O'M_U5*)Io4fddHOJ2ddg3*vpTiaKi4Za JdETTc߅cbCd&6 Hy/>Q'6y\&_ fVX{F^>ҔӰ^0"<_]V;/vEch@G (3Aeu N`sH&S*ͫ2WQ#m2g囌&sL3y.UTx T#MTM6LX .d؞5820(j÷;`4k$˥7L!җevhl;LCb1ų ahg=x^A|{2AF;KPjVe3ֻU߯p`ڡv8o; @Ɗt Cp0Z(#`oC"޵I;Cahi -"e(XZL>Ϩr!^h 'ǔ>|']?/xv|RhћTo>8 hr=|=CgA;O5nۮ0vd`NV\>>zȋHom֨[vVlZ7=0f|GsktWsYT~ &2A&OK Pk /l@W&N_ (C 4 !D72hMFZ6<rH5KhrhM4ihGZ@h~/?2AU48r**QJ['zR7QG:J(5J)D:n/i|H- NW ~hB3ʡgʦƫxi* ^&M+2@ݙ4XhCxh Kȍ-/Bto BA_B(KR!d;KB:mRfieS漢ZP "dC 0O<ШdN_*F9B}>O#4P muTVi#UCC5B7?hQm?WRa*kȐ~=L+3FB24/BAB(" a0@KoyH}Ջʴz~JF)ȈR AT_:F9wy쥃BTDeb=,}+F1Ka/Ck= 6ieht᥃9쥃yh>bZZDR~9KuTBݨhZ֠h]E]6ͨ]n@[Ѝ&t3ڊnAߎnC?Bh'Fw{Џѽ 'hڏ A:9:#hF_z=~z4zEFs =CϣЋ%2zG$$):zBFowл=>FEw) }@_?t )`T0C<],ِPP# PP6(NZ}P)?Ip )PG~XP㡞\"] `"\R & 4 W, s`.\`>ݶ-&XbZ`),vXNX] = +a5p \ al`l>n-p#7Vnmnv.vÝp ^{'>Axa) ~8 = x #_S4<G-g9t</nx ^W8 '$~)xހ?M/ C'w> _? ?5|wp|?>!0){?a(~ ?'/W)<|Ty+"~ _>_ç G&~ |?O39gYn˱*oA| B$"'I 1Tb"fb!i$dLEI%y$BRDF+)&%TxTQN." դ8xI%H-#I=  H.&Dr D.%d J.'d:Af+,2!sUdO,"I3%6,#d9 qIV.MzH/YIVd YK֑5Zl udL^PJn!md;Nvd&wcr/C}d?O {g'r!g3+YlU>->->->O(4>_x5~_x5~_x4G@x4C3 0ԏ!* 4j.-b-b>-bP=C}35=xwjs[+Rɡ&54u{b&cCgw[{e'5q3NYFͣZn! 'OYkQ(0^2%c=MMZ9i"<$<勚exr/զ625._ֲLoVm$B6DfH'7i7mKt7wxU3HL9Ӥ紤J%u]RG/^ݦ!]q]ҙCNڟ4ФWlekyƸ8:ĵч7)H&Du-]=:eP<92 ,֢^;B]HnӢ) ZahQ"$R&tZ҄EM]R+ӵ1:Qmk L | 'jM/mKS.-' \6,u7YlT,iҥN'8b_;:=]ih!:y3`&i]!t[tEn=frU6|f|zUrUaʕUB|_3NP8%ѤE6LݪCqݕ-]METpÕ`Xfk`Qq ͱX *}5떷u0+0Clb:})F] *nlvƺg5N_x5. ź{>Ě Tz֞VcO+5ޝme"n즍xWO"vc[G=mkvRi-mک1OVhg{:袞؊޶M1KЙʸ$bTHV$R#Q⮮ؒ=v&3إR :آxO5wآaI[{;|nu}.݄ǭOMZE;jkjTaO7w}NѲHzi%%;c<{ym|J-A{;tKukI9&-n]$ƚ(润T#RvsiLBHtH TkW"LD܉? $"DėxxĝLT$Xx] :D3L$N pjwg=.-(r'XhL5ew=n_ DuAˡezG Tvt5t$e*Tw>O7lY WsXáCn^}9 p0aU|#opQ^Q^MvEy]Qޮ(oW+␷/Ey8οo8οo8οot9FNmt67j06pبBɡC79 p8_ܜqsnN}rnN9}7r'V[;UyzP_Ga{x}:^/|o"šC^}9 p␷5&Ҝ%mMZGK,5~C&ib=7rPȡ@&hP#lEF=1rlx8T7JUrutlje?,ȡgL7t3DDDD>ip1;" H/ 4B<3$4B"0 a=,QqFDѣ<3*GEΕ)*STbNQFj#bf Ϭ3D-pq-p&Phb ..":GDK)S.Q\\\>'Dtm.Q\Dmsqms%Nw8]\]D=tz#ib&t>vnѝ":U8nqT⨺QuGG-[U8n>nqT⨺QuQu"gJAtuV͇- 788nqpXxol뎷P  1\bx.\CABEhC26=c&ӨUxWPZ\٨p4IR)ܓȫ۰i֦kttsԾ<մ; n_|!J8>@x=_?s_8-}G'Oy8-}|y˃O\|^{->n}'nT^IE"Yg_~q,/r8| |>E+_~>)soϽ=?|yGDdb&~ p p x3@.w q!7%%%% q gH4!px/B|x/B!ދoHtRB,{| +WX\70WְaQYâﯽ|k/_{<W >a1|'cDdD\|#᭍1"z>gUD\"|DĹ/".h>ÈY\0{r |#7^~r#*zQ>Qˏ%>DˏˏĖ75xQ5xQ5xQ5xQ7~G ^~m8Fy|Q#:>̫܌ok&!u̪6Pfs?&òј07<܄y~n<ܔy)pSM27en<܄yB/MˍOÍVJ{;~5j>|WseT͕ z5^ WpKxx6pzɗ'?/r'?q"'NN~:Nu裍|Iaz3>)玵<g5ʙwWijO6'z>qi+O%"?nyB\Q| h~Ѩ.Ž)GDͧ~N[@\bK0[%%=@hxbЀ"8Nq8q ) KĝGADvU=$଄g 1b.]047H{LoWs/OXBh|ͅǵATq/H @\5ZF9S[eM+c)?bUJz.SOvλ9^]]\g :oV\E,ϲseP1cAYֱ+73e)A&%KlKȱ%^rf.hűkk}+wb_p}l[gZOʱ־yk#y%khG%{!n^0bd'|׿4~<8ꢀkTa%Dfd=|wؒ!3|ҀQ?y89Ӏ)5'dSB@4l/t i;n5rؒ$F@^$GeJާpSXDsya%O5O"'kQC{sysrT LJ7YeNk> !Eiߧ,*2ic5?E:'GRCFrvSyCJh$(MN(‡uY֣O3)T(}Ip882}|E%vHFL}@c9}Ns:4ӡs;g3m8IBiC%fJ U א$,ORͽ va)PB@Ir+ùJS#:u,hŵlJ3x+#QZ>)pj>|ٮ$WnU~,XxKyEo2oڪ߼Uo# +K&mQ41ޫ76Xظ>~z~ i>a~b-}~Cn|>}&} }c}>ߡ>奻̮,3P",4&兩?5˒.e^T;vdvDmAmnmVmzP%v 'I@~}R> endobj 21 0 obj << /Title (\376\377\000\103\000\162\000\157\000\163\000\163\000\055\000\164\000\141\000\142\000\165\000\154\000\141\000\162\000\040\000\163\000\165\000\155\000\155\000\141\000\162\000\171\000\040\000\162\000\145\000\160\000\157\000\162\000\164) /Dest [7 0 R /XYZ 0 576 null] /Parent 20 0 R /First 22 0 R /Last 22 0 R /Count 1 >> endobj 22 0 obj << /Title (\376\377\000\124\000\141\000\142\000\154\000\145\000\040\000\061) /Dest [7 0 R /XYZ 0 576 null] /Parent 21 0 R >> endobj 19 0 obj << /D [7 0 R /XYZ 0 576 null] >> endobj 7 0 obj << /Type /Page /Parent 3 0 R /Resources << /ProcSet [/PDF /Text ] /Font<< /TT1 4 0 R /TT2 10 0 R /TT3 13 0 R /TT4 16 0 R >> /ExtGState <> >> /MediaBox [0 0 792 612] /Contents 8 0 R >> endobj xref 0 30 0000000000 65535 f 0000006549 00000 n 0000006797 00000 n 0000006867 00000 n 0000006924 00000 n 0000007082 00000 n 0000007277 00000 n 0000104084 00000 n 0000000064 00000 n 0000000016 00000 n 0000026805 00000 n 0000027116 00000 n 0000027312 00000 n 0000051746 00000 n 0000052235 00000 n 0000052434 00000 n 0000069244 00000 n 0000069754 00000 n 0000069947 00000 n 0000104035 00000 n 0000103253 00000 n 0000103549 00000 n 0000103894 00000 n 0000002912 00000 n 0000006715 00000 n 0000006751 00000 n 0000007556 00000 n 0000027655 00000 n 0000052881 00000 n 0000070450 00000 n trailer << /Size 30 /Root 1 0 R >> startxref 104295 %%EOF

SAS Log

1                                                                                                                        The SAS System                                                                                           17:49 Friday, October 27, 2017

NOTE: Copyright (c) 2002-2010 by SAS Institute Inc., Cary, NC, USA. 
NOTE: SAS (r) Proprietary Software 9.3 (TS1M2) 
      Licensed to LOUISIANA STATE UNIV / ITS-ADMIN, Site 70074566.
NOTE: This session is executing on the X64_S08R2  platform.



NOTE: Enhanced analytical products:

SAS/STAT 12.1

NOTE: SAS Initialization used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      
NOTE: The autoexec file, D:\SAS\EnterpriseSAS\Lev1\SASApp\StoredProcessServer\autoexec.sas, was executed at server initialization.

>>> SAS Macro Variables:

 EFFDTE=20170831
 SYSDBMSG=
 SYSDBRC=0
 _APSLIST=_url,_htua,EFFDTE,_client,_htcook,_result,_ODSDEST,_grafloc,_program,_reqmeth,_rmtaddr,_rmthost,_srvname,_srvport,_version,_metauser,_password,_username,_metafolder,_metaperson,_userloc
     ale,_SECUREUSERNAME
 _CLIENT=StoredProcessService 9.3; JVM 1.6.0_30; Windows Server 2008 R2 (amd64) 6.1
 _GRAFLOC=/sasweb/graph
 _HTCOOK=_ga=GA1.2.833841193.1398869373; JSESSIONID=B12F5390566265A18F266CE484550363; sso-logout-time="Sat Oct 28 2017 00:21:51 GMT-0500 (Central Daylight Time)"; LtpaToken=AAECAzU5RjNBMzMzNTlGND
     EzRUZrdHdlZWRAbHN1LmVkdcdWf3QzOoQT/y0rCsn2UmWdnyJL; __unam=7ac2274-151253bf750-b2127a8-1774
 _HTUA=Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.91 Safari/537.36
 _METAFOLDER=/FSS/
 _METAPERSON=FSSGuest
 _METAUSER=FSSGuest@saspw
 _ODSDEST=PDF
 _PASSWORD=XXXXXX
 _PROGRAM=/FSS/FUNDCOL2
 _REPLAY="&_URL?_sessionid=0A58D994-E234-43A5-AAF2-F6B803893ADE&_program=replay&_entry=&_TMPCAT.."
 _REQMETH=POST
 _RESULT=STREAM
 _RMTADDR=130.39.74.10
 _RMTHOST=130.39.74.10
 _SECUREUSERNAME=FSSGuest
 _SRVNAME=sasdreporting.lsu.edu
 _SRVPORT=8443
 _TMPCAT=APSWORK.TCAT0012
 _URL=/SASStoredProcess/do
 _USERLOCALE=en_US
 _USERNAME=FSSGuest@saspw
 _VERSION=Version 9.3 (Build 478)

NOTE: %INCLUDE (level 1) file D:\SAS Stored Processes\FSS\FUNDCOL2.sas is file D:\SAS Stored Processes\FSS\FUNDCOL2.sas.
2         +*  Begin EG generated code (do not edit this line);
3         +*
4         +*  Stored process registered by
5         +*  Enterprise Guide Stored Process Manager V5.1
6         +*
7         +*  ====================================================================
8         +*  Stored process name: FUNDCOL2
9         +*  ====================================================================
10        +*
11        +*  Stored process prompt dictionary:
12        +*  ____________________________________
13        +*  _ODSDEST
14        +*       Type: Text
15        +*      Label: _ODSDEST
16        +*       Attr: Visible
17        +*  ____________________________________
18        +*  EFFDTE
19        +*       Type: Text
20        +*      Label: EFFDTE
21        +*       Attr: Visible
22        +*  ____________________________________
23        +*;
24        +
25        +
26        +*ProcessBody;
27        +
28        +%global _ODSDEST
29        +        EFFDTE;
30        +
31        +OPTIONS VALIDVARNAME=ANY;
32        +
33        +%macro ExtendValidMemName;
34        +
35        +%if %sysevalf(&sysver>=9.3) %then options validmemname=extend;
36        +
37        +%mend ExtendValidMemName;
38        +
                                                                                          The SAS System

39        +%ExtendValidMemName;
40        +
41        +*  End EG generated code (do not edit this line);
42        +
43        +OPTIONS MISSING = ' '
44        +     LINESIZE=145 symbolgen;
45        +
46        +%GetLSUUser
SYMBOLGEN:  Macro variable _METAUSER resolves to FSSGuest@saspw
SYMBOLGEN:  Macro variable _METAUSER resolves to FSSGuest@saspw
SYMBOLGEN:  Macro variable _HTCOOK resolves to _ga=GA1.2.833841193.1398869373; JSESSIONID=B12F5390566265A18F266CE484550363; sso-logout-time="Sat 
            Oct 28 2017 00:21:51 GMT-0500 (Central Daylight Time)"; 
            LtpaToken=AAECAzU5RjNBMzMzNTlGNDEzRUZrdHdlZWRAbHN1LmVkdcdWf3QzOoQT/y0rCsn2UmWdnyJL; __unam=7ac2274-151253bf750-b2127a8-1774
SYMBOLGEN:  Some characters in the above value which were subject to macro quoting have been unquoted for printing.

NOTE: DATA statement used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

SYMBOLGEN:  Macro variable VALUE resolves to AAECAzU5RjNBMzMzNTlGNDEzRUZrdHdlZWRAbHN1LmVkdcdWf3QzOoQT/y0rCsn2UmWdnyJL
SYMBOLGEN:  Macro variable _METAUSER resolves to FSSGuest@saspw
SYMBOLGEN:  Macro variable _METAUSER resolves to FSSGuest@saspw

NOTE: Numeric values have been converted to character values at the places given by: (Line):(Column).
      46:118   46:240   
NOTE: The infile LSU is:
      Filename=http://cgi.lsu.edu:8080/eis/servlet/getuser?LtpaToken=AAECAzU5RjNBMzMzNTlGNDEzRUZrdHdlZWRAbHN1LmVkdcdWf3QzOoQT/y0rCsn2UmWdnyJL,
      Local Host Name=SASDCOMPUTE,
      Local Host IP addr=fe80::602f:416e:d266:b362%11,
      Service Hostname Name=cgi.uis.lsu.edu,
      Service IP addr=130.39.20.36,Service Name=N/A,
      Service Portno=8080,Lrecl=2000,Recfm=Stream

NOTE: 1 record was read from the infile LSU.
      The minimum record length was 33.
      The maximum record length was 33.
NOTE: DATA statement used (Total process time):
                                                                 The SAS System

      real time           0.01 seconds
      cpu time            0.00 seconds
      

**END*USEREND*USER**


SYMBOLGEN:  Macro variable _LSUPERSON resolves to Keri M Tweed
SYMBOLGEN:  Macro variable _LSUUSER resolves to ktweed
****  This stored process was requested by Keri M Tweed with LSUUSERID: ktweed


**END*USEREND*USER**
SYMBOLGEN:  Macro variable _INFILE resolves to            0
SYMBOLGEN:  Macro variable _INUSER resolves to            1
47        +  *** ENTER EFFECTIVE DATE ***;
48        +*%LET EFFDTE = 20170626;
49        +
50        +DATA DATE;
51        +  EFFDTE  = "&EFFDTE";
SYMBOLGEN:  Macro variable EFFDTE resolves to 20170831
52        +  EFFDTEX = INPUT(PUT(EFFDTE,8.),$8.);
53        +  FORMAT EFFYR $4.;
54        +  EFFYR = SUBSTR(EFFDTEX,1,4);
55        +  EFFMN = SUBSTR(EFFDTEX,5,2);
56        +  IF EFFMN < 7 THEN FISCAL = EFFYR;
57        +   ELSE FISCAL = EFFYR + 1;
58        +     FYEARX = COMPRESS("'"||TRIM(FISCAL)||"'");
59        +     FYRX = "'"||SUBSTR(FYEARX,4,2)||"'";
60        +     PDATE = COMPRESS(EFFYR) || COMPRESS(EFFMN);
61        +/*PFILE = "'ACGR14.PROD.PDF(V" || COMPRESS(PDATE) || ")'";
62        +     CALL SYMPUT('PFILE',PFILE);
63        +HFILE = "'ACGR14.PROD.HTML(V" || COMPRESS(PDATE) || ")'";
64        +     CALL SYMPUT ('HFILE', HFILE);*/
65        +     CALL SYMPUT('FYR',FYRX);
66        +     CALL SYMPUT('FYEAR',FYEARX);
67        +     CALL SYMPUT('EFFMN',EFFMN);
68        +     CALL SYMPUT('EFFYR',EFFYR);
                                                                 The SAS System

69        +     CALL SYMPUT('FISCAL',FISCAL);
70        +	 	 TME = TIME();
71        +	CALL SYMPUT('TME',TME);
72        +
73        +if EFFMN > 6 then begfy = effyr; else begfy = effyr - 1;	
74        +	format begdte yymmddn.;
75        +begdte = begfy||'0701';
76        +begdte1 = INPUT(PUT(begdte,$8.),8.);
WARNING: Variable begdte has already been defined as numeric.
77        +CALL SYMPUT('begdte1',begdte1);
78        +
79        +
80        +IF EFFMN = 01 THEN MON = 'JANUARY  ';
81        +IF EFFMN = 02 THEN MON = 'FEBRUARY ';
82        +IF EFFMN = 03 THEN MON = 'MARCH    ';
83        +IF EFFMN = 04 THEN MON = 'APRIL    ';
84        +IF EFFMN = 05 THEN MON = 'MAY      ';
85        +IF EFFMN = 06 THEN MON = 'JUNE     ';
86        +IF EFFMN = 07 THEN MON = 'JULY     ';
87        +IF EFFMN = 08 THEN MON = 'AUGUST   ';
88        +IF EFFMN = 09 THEN MON = 'SEPTEMBER';
89        +IF EFFMN = 10 THEN MON = 'OCTOBER  ';
90        +IF EFFMN = 11 THEN MON = 'NOVEMBER ';
91        +IF EFFMN = 12 THEN MON = 'DECEMBER ';
92        + CALL SYMPUT('MON',MON);
93        +
94        +BEGFY=FISCAL-1;
95        +BEGFX = INPUT(PUT(BEGFY,4.),$4.);
96        +FISX = INPUT(PUT(FISCAL,4.),$4.);
97        +FORMAT BEGYR ENDYR $2.;
98        +BEGYR = SUBSTR(BEGFX,3,2);
99        +ENDYR = SUBSTR(FISX,3,2);
100       +CALL SYMPUT('BEGYR',BEGYR);
101       +CALL SYMPUT('ENDYR',ENDYR);
102       +
103       +     IF EFFMN = 01 THEN HEADER = '  JANUARY';
104       +ELSE IF EFFMN = 02 THEN HEADER = ' FEBRUARY';
105       +ELSE IF EFFMN = 03 THEN HEADER = '    MARCH';
                                                                 The SAS System

106       +ELSE IF EFFMN = 04 THEN HEADER = '    APRIL';
107       +ELSE IF EFFMN = 05 THEN HEADER = '      MAY';
108       +ELSE IF EFFMN = 06 THEN HEADER = '     JUNE';
109       +ELSE IF EFFMN = 07 THEN HEADER = '     JULY';
110       +ELSE IF EFFMN = 08 THEN HEADER = '   AUGUST';
111       +ELSE IF EFFMN = 09 THEN HEADER = 'SEPTEMBER';
112       +ELSE IF EFFMN = 10 THEN HEADER = '  OCTOBER';
113       +ELSE IF EFFMN = 11 THEN HEADER = ' NOVEMBER';
114       +ELSE IF EFFMN = 12 THEN HEADER = ' DECEMBER';
115       +CALL SYMPUT('HEADER',HEADER);

NOTE: Character values have been converted to numeric values at the places given by: (Line):(Column).
      56:6    57:18   73:4    73:47   75:15   80:4    81:4    82:4    83:4    84:4    85:4    86:4    87:4    88:4    89:4    90:4    91:4
      94:7    103:9   104:9   105:9   106:9   107:9   108:9   109:9   110:9   111:9   112:9   113:9   114:9   
NOTE: Numeric values have been converted to character values at the places given by: (Line):(Column).
      57:24   71:20   73:53   77:23   94:13   
NOTE: The data set WORK.DATE has 1 observations and 18 variables.
NOTE: Compressing data set WORK.DATE increased size by 100.00 percent. 
      Compressed is 2 pages; un-compressed would require 1 pages.
NOTE: DATA statement used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

116       +proc sort; by effmn;
117       +
118       +/*LIBNAME COA DB2 AUTHID=COA SSID=DB2;
119       +LIBNAME SPM DB2 AUTHID=SPM SSID=DB2;
120       +LIBNAME DIR DB2 AUTHID=DIR SSID=DB2;*/
121       +
122       +/ LEGACY COA INFORMATION ****
123       +PROC SQL;
124       + CREATE TABLE COAFILE AS
125       + SELECT P_I_LSU_ID          AS PIID
126       +       ,ACCT_CODE           AS ACCT
127       +       ,AGENCY_CD           AS AGENCY
128       +       ,GRANT_EXPIRE_DATE   AS EXPIRE
129       +       ,PROPOSAL_NBR        AS PROPNBR
                                                                 The SAS System

130       +       ,GRANT_NAME          AS STITLE
131       +       ,TOTAL_AWARD_AMT     AS TOTAWARD
132       +       ,CO_P_I_LSU_ID       AS COPIID
133       +       ,INTERNAL_COMP_FLAG  AS INTFLAG
134       +       ,TASK_NBR            AS TASK
135       +FROM COA.SPONSORED_PROGRAMS
136       +WHERE SUBSTR(ACCT_CODE,1,1) = '1'
137       +AND SUBSTR(ACCT_CODE,6,1) IN ('3','4','5','6') AND PROPOSAL_NBR <> 0
138       +AND AGENCY_CD NOT IN ('A1','C','Z','XF') AND BILL_CYCLE_CD <> 'G'
139       +AND SUBSTR(ACCT_CODE,1,7) NOT IN ('1801054','1814054','190047','190057',
140       +'190067') AND FISCAL_YEAR = &FYEAR;
141       +PROC SORT; BY ACCT;*/
142       +

NOTE: There were 1 observations read from the data set WORK.DATE.
NOTE: The data set WORK.DATE has 1 observations and 18 variables.
NOTE: Compressing data set WORK.DATE increased size by 100.00 percent. 
      Compressed is 2 pages; un-compressed would require 1 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

143       +PROC SQL;
144       +CREATE TABLE FUND1 AS
145       +SELECT ORG_ID AS GRANT_ID,
146       +FUND
147       +FROM WDM.fin_fdm_DRIVERTAG
148       +WHERE FUND IN ('FD250','FD251','FD252');
NOTE: Compressing data set WORK.FUND1 decreased size by 48.11 percent. 
      Compressed is 55 pages; un-compressed would require 106 pages.
NOTE: Table WORK.FUND1 created, with 6101 rows and 2 columns.

NOTE: PROCEDURE SQL used (Total process time):
      real time           0.03 seconds
      cpu time            0.01 seconds
      

                                                                 The SAS System

149       +PROC SORT; BY GRANT_ID;
150       +

NOTE: There were 6101 observations read from the data set WORK.FUND1.
NOTE: The data set WORK.FUND1 has 6101 observations and 2 variables.
NOTE: Compressing data set WORK.FUND1 decreased size by 48.11 percent. 
      Compressed is 55 pages; un-compressed would require 106 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

151       +PROC SQL;
152       +CREATE TABLE GRANT1 AS
153       +SELECT GRANT_ID,
154       +AWARD_NUMBER as award_budg,
155       +TO_DATE AS GRANT_EXP_DATE,
156       +sponsor_id,
157       +cont_line_status,
158       +workday_id,
159       +CONT_STATUS,
160       +is_primary
161       +FROM WDM.FIN_AWD_LINE
162       +where company = '10' and cont_status NE ' ';
NOTE: Compressing data set WORK.GRANT1 decreased size by 36.36 percent. 
      Compressed is 49 pages; un-compressed would require 77 pages.
NOTE: Table WORK.GRANT1 created, with 3498 rows and 8 columns.

NOTE: PROCEDURE SQL used (Total process time):
      real time           0.04 seconds
      cpu time            0.03 seconds
      

163       +PROC SORT; BY GRANT_ID;
164       +

NOTE: There were 3498 observations read from the data set WORK.GRANT1.
NOTE: The data set WORK.GRANT1 has 3498 observations and 8 variables.
                                                                 The SAS System

NOTE: Compressing data set WORK.GRANT1 decreased size by 36.36 percent. 
      Compressed is 49 pages; un-compressed would require 77 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

165       +DATA MRG1; MERGE FUND1(IN=A) GRANT1(IN=B); BY GRANT_ID; IF A AND B;

NOTE: There were 6101 observations read from the data set WORK.FUND1.
NOTE: There were 3498 observations read from the data set WORK.GRANT1.
NOTE: The data set WORK.MRG1 has 3042 observations and 9 variables.
NOTE: Compressing data set WORK.MRG1 decreased size by 43.64 percent. 
      Compressed is 31 pages; un-compressed would require 55 pages.
NOTE: DATA statement used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

166       +PROC SORT; BY sponsor_id;
167       +

NOTE: There were 3042 observations read from the data set WORK.MRG1.
NOTE: The data set WORK.MRG1 has 3042 observations and 9 variables.
NOTE: Compressing data set WORK.MRG1 decreased size by 43.64 percent. 
      Compressed is 31 pages; un-compressed would require 55 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

168       +proc sql;
169       +create table SPON as
170       +select sponsor_id,
171       +SPONSOR_NAME,
172       +sponsor_type
173       +from wdm.fin_awd_sponsor;
NOTE: Compressing data set WORK.SPON decreased size by 67.65 percent. 
                                                                 The SAS System

      Compressed is 11 pages; un-compressed would require 34 pages.
NOTE: Table WORK.SPON created, with 1609 rows and 3 columns.

NOTE: PROCEDURE SQL used (Total process time):
      real time           0.03 seconds
      cpu time            0.01 seconds
      

174       +proc sort; by sponsor_id;
175       +

NOTE: There were 1609 observations read from the data set WORK.SPON.
NOTE: The data set WORK.SPON has 1609 observations and 3 variables.
NOTE: Compressing data set WORK.SPON decreased size by 67.65 percent. 
      Compressed is 11 pages; un-compressed would require 34 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

176       +data mrgspon; merge mrg1(in=a) spon(in=b); by sponsor_id; if a;

NOTE: There were 3042 observations read from the data set WORK.MRG1.
NOTE: There were 1609 observations read from the data set WORK.SPON.
NOTE: The data set WORK.MRGSPON has 3042 observations and 11 variables.
NOTE: Compressing data set WORK.MRGSPON decreased size by 63.73 percent. 
      Compressed is 37 pages; un-compressed would require 102 pages.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

177       +PROC SORT; BY award_budg grant_id cont_line_status descending is_primary ;
178       +

NOTE: There were 3042 observations read from the data set WORK.MRGSPON.
NOTE: The data set WORK.MRGSPON has 3042 observations and 11 variables.
NOTE: Compressing data set WORK.MRGSPON decreased size by 63.73 percent. 
                                                                 The SAS System

      Compressed is 37 pages; un-compressed would require 102 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

179       +data setspon; set mrgspon; BY award_budg grant_id cont_line_status descending is_primary ;
180       +if first.grant_id then output;

NOTE: There were 3042 observations read from the data set WORK.MRGSPON.
NOTE: The data set WORK.SETSPON has 3038 observations and 11 variables.
NOTE: Compressing data set WORK.SETSPON decreased size by 63.73 percent. 
      Compressed is 37 pages; un-compressed would require 102 pages.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

181       +proc sort; by workday_id;
182       +

NOTE: There were 3038 observations read from the data set WORK.SETSPON.
NOTE: The data set WORK.SETSPON has 3038 observations and 11 variables.
NOTE: Compressing data set WORK.SETSPON decreased size by 63.73 percent. 
      Compressed is 37 pages; un-compressed would require 102 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

183       +proc sql;
184       +create table task as
185       +select workday_id,
186       +org_id as tasknbr
187       +from WDM.FIN_AWD_LINE_ORG
188       +where substr(org_id,1,2) = 'TA';
NOTE: Compressing data set WORK.TASK decreased size by 22.22 percent. 
      Compressed is 84 pages; un-compressed would require 108 pages.
                                                                 The SAS System

NOTE: Table WORK.TASK created, with 6223 rows and 2 columns.

NOTE: PROCEDURE SQL used (Total process time):
      real time           0.03 seconds
      cpu time            0.03 seconds
      

189       +proc sort; by workday_id;
190       +

NOTE: There were 6223 observations read from the data set WORK.TASK.
NOTE: The data set WORK.TASK has 6223 observations and 2 variables.
NOTE: Compressing data set WORK.TASK decreased size by 22.22 percent. 
      Compressed is 84 pages; un-compressed would require 108 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

191       +data mrggrnt; merge task(in=a) setspon(in=b); by workday_id;
192       +if b;

NOTE: There were 6223 observations read from the data set WORK.TASK.
NOTE: There were 3038 observations read from the data set WORK.SETSPON.
NOTE: The data set WORK.MRGGRNT has 3038 observations and 12 variables.
NOTE: Compressing data set WORK.MRGGRNT decreased size by 64.22 percent. 
      Compressed is 39 pages; un-compressed would require 109 pages.
NOTE: DATA statement used (Total process time):
      real time           0.03 seconds
      cpu time            0.01 seconds
      

193       +proc sort; by award_budg;
194       +

NOTE: There were 3038 observations read from the data set WORK.MRGGRNT.
NOTE: The data set WORK.MRGGRNT has 3038 observations and 12 variables.
NOTE: Compressing data set WORK.MRGGRNT decreased size by 64.22 percent. 
                                                                 The SAS System

      Compressed is 39 pages; un-compressed would require 109 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

195       +PROC SQL;
196       +CREATE TABLE AWARD1 AS
197       +SELECT AWARD_NUMBER as award_budg,
198       +PROPOSAL_ID as propnbr,
199       +AWARD_NAME,
200       +signed_date,
201       +TOTAL_AMOUNT AS AWD_TOTAL,
202       +award_date
203       +FROM WDM.FIN_AWD
204       +WHERE PROPOSAL_ID NE 0 and
205       +award_type not in ('SPN_AWD_Type_Disaster_Relief','SPN_AWD_Type_Pell_SEOG_CWS','SPN_AWD_Type_Federal_Appropriations');
NOTE: Compressing data set WORK.AWARD1 decreased size by 76.12 percent. 
      Compressed is 16 pages; un-compressed would require 67 pages.
NOTE: Table WORK.AWARD1 created, with 1917 rows and 6 columns.

NOTE: PROCEDURE SQL used (Total process time):
      real time           0.01 seconds
      cpu time            0.00 seconds
      

206       +PROC SORT; BY award_budg;
207       +

NOTE: There were 1917 observations read from the data set WORK.AWARD1.
NOTE: The data set WORK.AWARD1 has 1917 observations and 6 variables.
NOTE: Compressing data set WORK.AWARD1 decreased size by 76.12 percent. 
      Compressed is 16 pages; un-compressed would require 67 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

                                                                 The SAS System

208       +DATA MRG2; MERGE mrggrnt(IN=A) AWARD1(IN=B); BY award_budg; IF A AND B;
209       +format TASK 2.;
210       +task = substr(taskNBR,3,2);
211       +if task = 0 then task = 1;

NOTE: Character values have been converted to numeric values at the places given by: (Line):(Column).
      210:8   
NOTE: There were 3038 observations read from the data set WORK.MRGGRNT.
NOTE: There were 1917 observations read from the data set WORK.AWARD1.
NOTE: The data set WORK.MRG2 has 2734 observations and 18 variables.
NOTE: Compressing data set WORK.MRG2 decreased size by 73.47 percent. 
      Compressed is 52 pages; un-compressed would require 196 pages.
NOTE: DATA statement used (Total process time):
      real time           0.03 seconds
      cpu time            0.03 seconds
      

212       +PROC SORT; BY award_budg;
213       +
214       +/*PROC SQL;
215       +CREATE TABLE LEADPI AS
216       +SELECT EMPLOYEE_ID AS WD_PIID,
217       +ORG_ID AS GRANT_ID,
218       +ROLE_NAME AS ROLE1
219       +FROM WDM.WORKER_ROLE
220       +WHERE role_name = 'Principal_Investigator';
221       +PROC SORT; BY WD_PIID;
222       +
223       +PROC SQL;
224       +CREATE TABLE LSUPIID AS
225       +SELECT EMPLOYEE_ID AS WD_PIID,
226       +LSU_ID AS LSU_PIID
227       +FROM WDM.KEYS;
228       +PROC SORT; BY WD_PIID;
229       +
230       +DATA MRGPI;
231       +MERGE LEADPI(IN=A) LSUPIID(IN=B); BY WD_PIID; IF A;
232       +PROC SORT; BY GRANT_ID;
                                                                 The SAS System

233       +
234       +DATA MRG3; MERGE MRG2(IN=A) MRGPI(IN=B); BY GRANT_ID; IF A;
235       +PROC SORT; BY award_budg;*/
236       +
237       +/*PROC SQL;
238       +CREATE TABLE COPI AS
239       +SELECT EMPLOYEE_ID AS WD_COPIID,
240       +ORG_ID AS GRANT_ID,
241       +ROLE_NAME AS ROLE2
242       +FROM WDM.WORKER_ROLE
243       +WHERE role_name = 'Co-Principal_Investigator';
244       +PROC SORT; BY WD_COPIID;
245       +
246       +PROC SQL;
247       +CREATE TABLE LSUCOPIID AS
248       +SELECT EMPLOYEE_ID AS WD_COPIID,
249       +LSU_ID AS LSU_COPIID
250       +FROM WDM.KEYS;
251       +PROC SORT; BY WD_COPIID;
252       +
253       +DATA MRGCOPI;
254       +MERGE COPI(IN=A) LSUCOPIID(IN=B); BY WD_COPIID; IF A;
255       +PROC SORT; BY GRANT_ID;
256       +
257       +DATA MRG4; MERGE MRG3(IN=A) MRGCOPI(IN=B); BY GRANT_ID; IF A;
258       +PROC SORT; BY award_budg;*/
259       +

NOTE: There were 2734 observations read from the data set WORK.MRG2.
NOTE: The data set WORK.MRG2 has 2734 observations and 18 variables.
NOTE: Compressing data set WORK.MRG2 decreased size by 73.47 percent. 
      Compressed is 52 pages; un-compressed would require 196 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

260       +proc sql;
                                                                 The SAS System

261       +CREATE TABLE SPEC AS
262       +SELECT AWARD_NUMBER as award_budg,
263       +REF_ID
264       +FROM WDM.FIN_AWD_SPEC_COND
265       +WHERE REF_ID = 'Special_Condition_Type_Internal_Competition';
NOTE: Compressing data set WORK.SPEC decreased size by 0.00 percent. 
      Compressed is 2 pages; un-compressed would require 2 pages.
NOTE: Table WORK.SPEC created, with 52 rows and 2 columns.

NOTE: PROCEDURE SQL used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

266       +PROC SORT; BY award_budg;
267       +

NOTE: There were 52 observations read from the data set WORK.SPEC.
NOTE: The data set WORK.SPEC has 52 observations and 2 variables.
NOTE: Compressing data set WORK.SPEC decreased size by 0.00 percent. 
      Compressed is 2 pages; un-compressed would require 2 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

268       +DATA MRG5; MERGE MRG2(IN=A) SPEC(IN=B); BY award_budg; IF A;

NOTE: There were 2734 observations read from the data set WORK.MRG2.
NOTE: There were 52 observations read from the data set WORK.SPEC.
NOTE: The data set WORK.MRG5 has 2734 observations and 19 variables.
NOTE: Compressing data set WORK.MRG5 decreased size by 78.71 percent. 
      Compressed is 53 pages; un-compressed would require 249 pages.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

                                                                 The SAS System

269       +PROC SORT; BY award_budg grant_id;
270       +

NOTE: There were 2734 observations read from the data set WORK.MRG5.
NOTE: The data set WORK.MRG5 has 2734 observations and 19 variables.
NOTE: Compressing data set WORK.MRG5 decreased size by 78.71 percent. 
      Compressed is 53 pages; un-compressed would require 249 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

271       +data setmrg5; set mrg5; by award_budg grant_id;
272       +if first.grant_id ne last.grant_id then output;

NOTE: There were 2734 observations read from the data set WORK.MRG5.
NOTE: The data set WORK.SETMRG5 has 0 observations and 19 variables.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

273       +proc sort; by award_budg grant_id;
274       +
275       +
276       +
277       +/*PROC SQL;
278       + CREATE TABLE SPAFILE AS
279       + SELECT ACCT_CODE       AS ACCT
280       +       ,BEGIN_DATE      AS BEGIN
281       +       ,INIT_TIMESTAMP  AS IADD
282       +       ,LONG_TITLE      AS LONG
283       +FROM COA.ACCOUNTS
284       +WHERE CAMPUS_CD = '1' AND ACCT_TYPE = 'S'
285       +AND SUBSTR(ACCT_CODE,6,1) IN ('3','4','5','6')
286       +AND SUBSTR(ACCT_CODE,1,7) NOT IN ('1801054','1814054','190047','190057',
287       +'190067') AND FISCAL_YEAR = &FYEAR;
288       +
                                                                 The SAS System

289       +PROC SORT; BY ACCT;
290       +
291       +DATA COAS;
292       +  MERGE COAFILE(IN=A) SPAFILE(IN=B);
293       +  BY ACCT;
294       +  IF A AND B;
295       +
296       +PROC SORT DATA = COAS;  BY ACCT;
297       +
298       +DATA COA1(KEEP=STITLE LONG ACCT AGENCY EXPIRE BEGIN ADDTE TOTAWARD
299       +          PIID COPIID PROPNBR INTFLAG TASK);
300       + SET COAS;
301       +  FORMAT STITLE $60.;
302       +  FORMAT ADATE YYMMDDN8.;
303       +  ADATE = DATEPART(IADD);
304       +  FORMAT BEGIN YYMMDDN8.;
305       +  FORMAT EXPIRE YYMMDDN8.;
306       +  AYR = YEAR(ADATE);
307       +  AMTH= MONTH(ADATE);
308       +    MONA = INPUT(PUT(AMTH,Z2.),$2.);
309       +    YEARA = INPUT(PUT(AYR,4.),$4.);
310       +  ADDTE = YEARA||MONA;
311       +  *IF BEGIN <= &DATE;*/
312       +

NOTE: Input data set is empty.
NOTE: The data set WORK.SETMRG5 has 0 observations and 19 variables.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

313       +PROC SQL;
314       +CREATE TABLE BUDG AS
315       +SELECT grant_id,
316       +grant_name,
317       +ledger_account,
318       +budget_revenue as AMT,
                                                                 The SAS System

319       +budget_obj,
320       +award_name,
321       +award_report_code as BAADJCD,
322       +budget_amendment_date,
323       +budget_date_from
324       +from workday.award_budget
325       +where ledger_account in ('4200:Federal Grants and Contracts Revenue','4210:State and Local Grants and Contracts Revenue',
326       +'4220:Non-governmental Grants and Contracts Revenue','4230:Grants and Contracts Revenue') and budget_amendment_status not in
326      !+('Canceled','Draft','Denied')
327       +and company_code = 'LSUAM' and
328       +award_report_code in ('New','Continuation') ;
NOTE: Compressing data set WORK.BUDG decreased size by 63.53 percent. 
      Compressed is 31 pages; un-compressed would require 85 pages.
NOTE: Table WORK.BUDG created, with 1349 rows and 9 columns.

NOTE: PROCEDURE SQL used (Total process time):
      real time           0.10 seconds
      cpu time            0.09 seconds
      

329       +proc sort; by grant_id;
330       +

NOTE: There were 1349 observations read from the data set WORK.BUDG.
NOTE: The data set WORK.BUDG has 1349 observations and 9 variables.
NOTE: Compressing data set WORK.BUDG decreased size by 63.53 percent. 
      Compressed is 31 pages; un-compressed would require 85 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

331       +data set1; set budg; by grant_id;
332       +format BUDGET_DATE1 yymmddn.;
333       +budget_date1 = budget_amendment_date;
334       +award_budg = scan(budget_obj,1,":");

NOTE: There were 1349 observations read from the data set WORK.BUDG.
                                                                 The SAS System

NOTE: The data set WORK.SET1 has 1349 observations and 11 variables.
NOTE: Compressing data set WORK.SET1 decreased size by 68.27 percent. 
      Compressed is 33 pages; un-compressed would require 104 pages.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

335       +proc sort; by award_budg grant_id;
336       +

NOTE: There were 1349 observations read from the data set WORK.SET1.
NOTE: The data set WORK.SET1 has 1349 observations and 11 variables.
NOTE: Compressing data set WORK.SET1 decreased size by 68.27 percent. 
      Compressed is 33 pages; un-compressed would require 104 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

337       +data MARGE; merge mrg5(in=a) set1(in=b); by award_budg grant_id; if a and b;
338       +format budget_date yymmddn.;
339       +if budget_date1 = ' ' then budget_date = signed_date; else budget_date = budget_date1;
340       +if budget_date = ' ' then delete;

NOTE: Character values have been converted to numeric values at the places given by: (Line):(Column).
      339:19   340:18   
WARNING: Multiple lengths were specified for the BY variable award_budg by input data sets. This may cause unexpected results.
NOTE: There were 2734 observations read from the data set WORK.MRG5.
NOTE: There were 1349 observations read from the data set WORK.SET1.
NOTE: The data set WORK.MARGE has 1346 observations and 28 variables.
NOTE: Compressing data set WORK.MARGE decreased size by 74.61 percent. 
      Compressed is 49 pages; un-compressed would require 193 pages.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

                                                                 The SAS System

341       +proc sort; by grant_id budget_date;
342       +

NOTE: There were 1346 observations read from the data set WORK.MARGE.
NOTE: The data set WORK.MARGE has 1346 observations and 28 variables.
NOTE: Compressing data set WORK.MARGE decreased size by 74.61 percent. 
      Compressed is 49 pages; un-compressed would require 193 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

343       +data marge1; set marge; by grant_id budget_date;
344       +effdte = INPUT(PUT(budget_date,yymmddn.),8.);
345       +
346       +*if effdte <= 20160930 then output;

NOTE: There were 1346 observations read from the data set WORK.MARGE.
NOTE: The data set WORK.MARGE1 has 1346 observations and 29 variables.
NOTE: Compressing data set WORK.MARGE1 decreased size by 74.09 percent. 
      Compressed is 50 pages; un-compressed would require 193 pages.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

347       +proc sort; by grant_id;
348       +
349       +/*
350       +DATA GLSD;
351       +  INFILE GLSD;
352       +  INPUT  @1   FY       $2.
353       +         @3   ENTRY   PD5.
354       +         @10  ACCT       $9.
355       +         @19  TT         $1.
356       +         @20  OBJ      $4.
357       +         @24  SUBOBJ   $1.
358       +         @29  AMT        PD6.2
                                                                 The SAS System

359       +         @168 BAADJCD  $1.;
360       +  IF TT = 'I' AND SUBSTR(ACCT,1,1) = '1' AND
361       +    SUBSTR(ACCT,6,1) IN ('4','5','6') AND FY = &FYR
362       +    AND BAADJCD IN ('N','C');
363       +  IF AMT = 0 THEN DELETE;
364       +  SF = SUBSTR(ACCT,6,1);
365       +
366       +PROC SORT DATA=GLSD; BY FY ENTRY;
367       +
368       +DATA GLSUSRS;
369       +  INFILE GLSUSR;
370       +   INPUT  @   1  FY        $2.
371       +          @   3  ENTRY     PD5.
372       +          @   8  ENTRYTYP  $2.
373       +          @  57  VCHRTYPE  $2.
374       +          @  64  EFFDTE    PD5.
375       +          @  69  STATUS    $1.;
376       +          IF STATUS = 'C';
377       +          IF FY = &FYR ;
378       +          IF ENTRYTYP = 'GE';
379       +
380       +PROC SORT DATA=GLSUSRS;  BY FY ENTRY;
381       +
382       +DATA GLS;
383       +  MERGE GLSUSRS(IN=A) GLSD(IN=B);
384       +  BY FY ENTRY;
385       +  IF A AND B;
386       +
387       +
388       +PROC SORT; BY ACCT;
389       +
390       +DATA GLSCOA;
391       +  MERGE COA1(IN=A) GLS(IN=B);
392       +  BY ACCT;
393       +  IF A AND B;
394       +
395       +PROC SORT DATA = GLSCOA;  BY FY ACCT ENTRY;*/
396       +
                                                                 The SAS System


NOTE: There were 1346 observations read from the data set WORK.MARGE1.
NOTE: The data set WORK.MARGE1 has 1346 observations and 29 variables.
NOTE: Compressing data set WORK.MARGE1 decreased size by 74.09 percent. 
      Compressed is 50 pages; un-compressed would require 193 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

397       +DATA BUDG1 (DROP= EMTH ENDYRX BEGYRX END BEG);
398       + SET marge1; by grant_id effdte;
399       +  *BY FY ACCT ENTRY;
400       + *edate = effdte;
401       +  EDATE = INPUT(PUT(effdte,8.),YYMMDD8.);
402       +  EMTH= MONTH(EDATE);
403       +
404       +  IF effdte <= &EFFDTE and effdte >= &begdte1;
SYMBOLGEN:  Macro variable EFFDTE resolves to 20170831
SYMBOLGEN:  Macro variable BEGDTE1 resolves to     20170701
405       +
406       +  EMNX = INPUT(PUT(EMTH,Z2.),$2.);
407       +  ENDYRX = &ENDYR;
SYMBOLGEN:  Macro variable ENDYR resolves to 18
408       +  BEGYRX = &BEGYR;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
409       +  END = INPUT(PUT(ENDYRX,Z2.),$2.);
410       +  BEG = INPUT(PUT(BEGYRX,Z2.),$2.);
411       +  IF EMTH > 6 THEN ACTDTE = BEG||EMNX;
412       +   ELSE ACTDTE = END||EMNX;
413       +
414       +  IF EMNX = &EFFMN THEN MONAMT = AMT;
SYMBOLGEN:  Macro variable EFFMN resolves to 08      
415       +  ELSE MONAMT = 0;
416       +

NOTE: Character values have been converted to numeric values at the places given by: (Line):(Column).
      414:6   
                                                                 The SAS System

NOTE: There were 1346 observations read from the data set WORK.MARGE1.
NOTE: The data set WORK.BUDG1 has 147 observations and 33 variables.
NOTE: Compressing data set WORK.BUDG1 decreased size by 68.18 percent. 
      Compressed is 7 pages; un-compressed would require 22 pages.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

417       +PROC SORT DATA = budg1; BY ACTDTE grant_id;
418       +

NOTE: There were 147 observations read from the data set WORK.BUDG1.
NOTE: The data set WORK.BUDG1 has 147 observations and 33 variables.
NOTE: Compressing data set WORK.BUDG1 decreased size by 68.18 percent. 
      Compressed is 7 pages; un-compressed would require 22 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

419       +DATA GLSCOA15(DROP=AMT MONAMT); SET budg1;
420       + BY ACTDTE grant_id;
421       + IF FIRST.grant_id THEN DO;
422       +         IF BAADJCD = 'New' THEN DO;
423       +                   NACCTAMT = AMT; NTOTMON = MONAMT;
424       +                   CACCTAMT = 0; CTOTMON = 0;
425       +         END;
426       +         IF BAADJCD = 'Continuation' THEN DO;
427       +                   NACCTAMT = 0; NTOTMON = 0;
428       +                   CACCTAMT = AMT; CTOTMON = MONAMT;
429       +         END;
430       + END;
431       + ELSE DO;
432       +           IF BAADJCD = 'New' THEN DO;
433       +                     NACCTAMT + AMT; NTOTMON + MONAMT;
434       +                     CACCTAMT + 0; CTOTMON + 0;
435       +           END;
                                                                 The SAS System

436       +           IF BAADJCD = 'Continuation' THEN DO;
437       +                     NACCTAMT + 0; NTOTMON + 0;
438       +                     CACCTAMT + AMT; CTOTMON + MONAMT;
439       +           END;
440       + END;
441       + IF LAST.grant_id THEN OUTPUT;

NOTE: There were 147 observations read from the data set WORK.BUDG1.
NOTE: The data set WORK.GLSCOA15 has 141 observations and 35 variables.
NOTE: Compressing data set WORK.GLSCOA15 decreased size by 66.67 percent. 
      Compressed is 7 pages; un-compressed would require 21 pages.
NOTE: DATA statement used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

442       + proc sort; by grant_id;
443       +

NOTE: There were 141 observations read from the data set WORK.GLSCOA15.
NOTE: The data set WORK.GLSCOA15 has 141 observations and 35 variables.
NOTE: Compressing data set WORK.GLSCOA15 decreased size by 66.67 percent. 
      Compressed is 7 pages; un-compressed would require 21 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

444       + data glscoa16; set glscoa15; by grant_id;
445       + if (NACCTAMT = 0 and NTOTMON = 0 and CACCTAMT = 0 and CTOTMON = 0) then delete;

NOTE: There were 141 observations read from the data set WORK.GLSCOA15.
NOTE: The data set WORK.GLSCOA16 has 136 observations and 35 variables.
NOTE: Compressing data set WORK.GLSCOA16 decreased size by 65.00 percent. 
      Compressed is 7 pages; un-compressed would require 20 pages.
NOTE: DATA statement used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
                                                                 The SAS System

      

446       + proc sort; by grant_id;
447       +
448       +

NOTE: There were 136 observations read from the data set WORK.GLSCOA16.
NOTE: The data set WORK.GLSCOA16 has 136 observations and 35 variables.
NOTE: Compressing data set WORK.GLSCOA16 decreased size by 65.00 percent. 
      Compressed is 7 pages; un-compressed would require 20 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

449       +PROC SQL;
450       +  CREATE TABLE PROJTRAN AS
451       +SELECT PROPOSAL_NBR     AS PROPNBR
452       +      ,TRX_NBR          AS TRXNBR
453       +      ,TRX_TYPE         AS TRXTYPE
454       +      ,TRX_STATUS       AS TRXSTAT
455       +      ,TO_SPA_DATE      AS RELDATE
456       +FROM SPM.PROJ_TRANSACTION
457       + WHERE TRX_STATUS IN ('AC','TE','CO');
NOTE: Compressing data set WORK.PROJTRAN decreased size by 1.39 percent. 
      Compressed is 142 pages; un-compressed would require 144 pages.
NOTE: Table WORK.PROJTRAN created, with 18085 rows and 5 columns.

458       +
NOTE: PROCEDURE SQL used (Total process time):
      real time           0.06 seconds
      cpu time            0.01 seconds
      

459       +PROC SORT; BY PROPNBR TRXNBR RELDATE;
460       +

NOTE: There were 18085 observations read from the data set WORK.PROJTRAN.
                                                                 The SAS System

NOTE: The data set WORK.PROJTRAN has 18085 observations and 5 variables.
NOTE: Compressing data set WORK.PROJTRAN decreased size by 1.39 percent. 
      Compressed is 142 pages; un-compressed would require 144 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

461       +DATA SPS2;
462       + SET PROJTRAN; BY PROPNBR TRXNBR;
463       +    LENGTH MO YY $2.;
464       +    LENGTH YR $4.;
465       +    MO=MONTH(RELDATE);
466       +    YR=YEAR(RELDATE);
467       +    YY=SUBSTR(YR,3,2);
468       +    LENGTH EFFMY $4.;
469       +    EFFMY=YY||MO;
470       +    IF SUBSTR(EFFMY,3,1)=' ' THEN SUBSTR(EFFMY,3,1)='0';

NOTE: Numeric values have been converted to character values at the places given by: (Line):(Column).
      465:8   466:8   
NOTE: Missing values were generated as a result of performing an operation on missing values.
      Each place is given by: (Number of times) at (Line):(Column).
      212 at 465:8   212 at 466:8   
NOTE: There were 18085 observations read from the data set WORK.PROJTRAN.
NOTE: The data set WORK.SPS2 has 18085 observations and 9 variables.
NOTE: Compressing data set WORK.SPS2 increased size by 8.33 percent. 
      Compressed is 195 pages; un-compressed would require 180 pages.
NOTE: DATA statement used (Total process time):
      real time           0.03 seconds
      cpu time            0.03 seconds
      

471       +    PROC SORT; BY PROPNBR EFFMY RELDATE;
472       +

NOTE: There were 18085 observations read from the data set WORK.SPS2.
NOTE: The data set WORK.SPS2 has 18085 observations and 9 variables.
                                                                 The SAS System

NOTE: Compressing data set WORK.SPS2 increased size by 8.33 percent. 
      Compressed is 195 pages; un-compressed would require 180 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

473       + PROC SORT; BY PROPNBR TRXNBR;
474       +

NOTE: There were 18085 observations read from the data set WORK.SPS2.
NOTE: The data set WORK.SPS2 has 18085 observations and 9 variables.
NOTE: Compressing data set WORK.SPS2 increased size by 8.33 percent. 
      Compressed is 195 pages; un-compressed would require 180 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

475       +PROC SQL;
476       +    CREATE TABLE PISHR AS
477       +    SELECT PROPOSAL_NBR    AS PROPNBR,
478       +           TRX_NBR         AS TRXNBR,
479       +           TASK_NBR        AS TASK,
480       +           LSU_ID          AS LSUID,
481       +           INVESTIGATOR_TYPE AS INVTYPE,
482       +           DEPT_CD         AS DEPT,
483       +           PROJECT_SHARE   AS SHARE
484       +    FROM SPM.PROJ_INVESTIGATOR
485       +    WHERE PROJECT_SHARE > 0;
NOTE: Compressing data set WORK.PISHR decreased size by 6.66 percent. 
      Compressed is 827 pages; un-compressed would require 886 pages.
NOTE: Table WORK.PISHR created, with 74364 rows and 7 columns.

NOTE: PROCEDURE SQL used (Total process time):
      real time           0.21 seconds
      cpu time            0.07 seconds
      
                                                                 The SAS System


486       +    PROC SORT; BY PROPNBR TRXNBR TASK;
487       +

NOTE: There were 74364 observations read from the data set WORK.PISHR.
NOTE: The data set WORK.PISHR has 74364 observations and 7 variables.
NOTE: Compressing data set WORK.PISHR decreased size by 6.55 percent. 
      Compressed is 828 pages; un-compressed would require 886 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.07 seconds
      cpu time            0.07 seconds
      

488       +DATA SPS4;
489       +  MERGE SPS2(IN=A) PISHR(IN=B); BY PROPNBR TRXNBR; IF A & B;
490       +

NOTE: There were 18085 observations read from the data set WORK.SPS2.
NOTE: There were 74364 observations read from the data set WORK.PISHR.
NOTE: The data set WORK.SPS4 has 31770 observations and 14 variables.
NOTE: Compressing data set WORK.SPS4 decreased size by 7.22 percent. 
      Compressed is 527 pages; un-compressed would require 568 pages.
NOTE: DATA statement used (Total process time):
      real time           0.06 seconds
      cpu time            0.06 seconds
      

491       +PROC SORT;  BY PROPNBR EFFMY RELDATE;
492       +

NOTE: There were 31770 observations read from the data set WORK.SPS4.
NOTE: The data set WORK.SPS4 has 31770 observations and 14 variables.
NOTE: Compressing data set WORK.SPS4 decreased size by 7.22 percent. 
      Compressed is 527 pages; un-compressed would require 568 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.04 seconds
      cpu time            0.04 seconds
      
                                                                 The SAS System


493       +    PROC SORT; BY PROPNBR TRXNBR;
494       +

NOTE: There were 31770 observations read from the data set WORK.SPS4.
NOTE: The data set WORK.SPS4 has 31770 observations and 14 variables.
NOTE: Compressing data set WORK.SPS4 decreased size by 7.22 percent. 
      Compressed is 527 pages; un-compressed would require 568 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.04 seconds
      cpu time            0.04 seconds
      

495       +DATA SPSFM1(DROP= MO YR YY BEGYRX ENDYRX END BEG)
496       +     SPSFM2(DROP= MO YR YY BEGYRX ENDYRX END BEG)
497       +     SPSFM3(DROP= MO YR YY BEGYRX ENDYRX END BEG)
498       +     SPSFM4(DROP= MO YR YY BEGYRX ENDYRX END BEG)
499       +     SPSFM5(DROP= MO YR YY BEGYRX ENDYRX END BEG)
500       +     SPSFM6(DROP= MO YR YY BEGYRX ENDYRX END BEG)
501       +     SPSFM7(DROP= MO YR YY BEGYRX ENDYRX END BEG)
502       +     SPSFM8(DROP= MO YR YY BEGYRX ENDYRX END BEG)
503       +     SPSFM9(DROP= MO YR YY BEGYRX ENDYRX END BEG)
504       +     SPSFM10(DROP= MO YR YY BEGYRX ENDYRX END BEG)
505       +     SPSFM11(DROP= MO YR YY BEGYRX ENDYRX END BEG)
506       +     SPSFM12(DROP= MO YR YY BEGYRX ENDYRX END BEG);
507       +     SET SPS4;
508       +  ENDYRX = &ENDYR;
SYMBOLGEN:  Macro variable ENDYR resolves to 18
509       +  BEGYRX = &BEGYR;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
510       +  END = INPUT(PUT(ENDYRX,Z2.),$2.);
511       +  BEG = INPUT(PUT(BEGYRX,Z2.),$2.);
512       +     IF (YY=&BEGYR AND MO <= 07) OR YY < &BEGYR THEN DO;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
SYMBOLGEN:  Macro variable BEGYR resolves to 17
513       +         ACTDTE = BEG||'07';
514       +         OUTPUT SPSFM1;
515       +         END;
                                                                 The SAS System

516       +     IF (YY=&BEGYR AND MO <= 08) OR YY < &BEGYR THEN DO;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
SYMBOLGEN:  Macro variable BEGYR resolves to 17
517       +         ACTDTE = BEG||'08';
518       +         OUTPUT SPSFM2;
519       +         END;
520       +     IF (YY=&BEGYR AND MO <= 09) OR YY < &BEGYR THEN DO;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
SYMBOLGEN:  Macro variable BEGYR resolves to 17
521       +         ACTDTE = BEG||'09';
522       +         OUTPUT SPSFM3;
523       +         END;
524       +     IF (YY=&BEGYR AND MO <= 10) OR YY < &BEGYR THEN DO;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
SYMBOLGEN:  Macro variable BEGYR resolves to 17
525       +         ACTDTE = BEG||'10';
526       +         OUTPUT SPSFM4;
527       +         END;
528       +     IF (YY=&BEGYR AND MO <= 11) OR YY < &BEGYR THEN DO;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
SYMBOLGEN:  Macro variable BEGYR resolves to 17
529       +         ACTDTE = BEG||'11';
530       +         OUTPUT SPSFM5;
531       +         END;
532       +     IF (YY=&BEGYR AND MO <= 12) OR YY < &BEGYR THEN DO;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
SYMBOLGEN:  Macro variable BEGYR resolves to 17
533       +         ACTDTE = BEG||'12';
534       +         OUTPUT SPSFM6;
535       +         END;
536       +     IF YY <= &BEGYR OR (YY=&ENDYR AND MO <= 1) THEN DO;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
SYMBOLGEN:  Macro variable ENDYR resolves to 18
537       +         ACTDTE = END||'01';
538       +         OUTPUT SPSFM7;
539       +         END;
540       +     IF YY <= &BEGYR OR (YY=&ENDYR AND MO <= 2) THEN DO;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
                                                                 The SAS System

SYMBOLGEN:  Macro variable ENDYR resolves to 18
541       +         ACTDTE = END||'02';
542       +         OUTPUT SPSFM8;
543       +         END;
544       +     IF YY <= &BEGYR OR (YY=&ENDYR AND MO <= 3) THEN DO;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
SYMBOLGEN:  Macro variable ENDYR resolves to 18
545       +         ACTDTE = END||'03';
546       +         OUTPUT SPSFM9;
547       +         END;
548       +     IF YY <= &BEGYR OR (YY=&ENDYR AND MO <=4) THEN DO;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
SYMBOLGEN:  Macro variable ENDYR resolves to 18
549       +         ACTDTE = END||'04';
550       +         OUTPUT SPSFM10;
551       +         END;
552       +     IF YY <= &BEGYR OR (YY=&ENDYR AND MO <=5) THEN DO;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
SYMBOLGEN:  Macro variable ENDYR resolves to 18
553       +         ACTDTE = END||'05';
554       +         OUTPUT SPSFM11;
555       +         END;
556       +     IF YY <= &BEGYR OR (YY=&ENDYR AND MO <=6) THEN DO;
SYMBOLGEN:  Macro variable BEGYR resolves to 17
SYMBOLGEN:  Macro variable ENDYR resolves to 18
557       +         ACTDTE = END||'06';
558       +         OUTPUT SPSFM12;
559       +         END;
560       +

NOTE: Character values have been converted to numeric values at the places given by: (Line):(Column).
      512:10   512:24   512:37   516:10   516:24   516:37   520:10   520:24   520:37   524:10   524:24   524:37   528:10   528:24   528:37
      532:10   532:24   532:37   536:9    536:26   536:40   540:9    540:26   540:40   544:9    544:26   544:40   548:9    548:26   548:40
      552:9    552:26   552:40   556:9    556:26   556:40   
NOTE: There were 31770 observations read from the data set WORK.SPS4.
NOTE: The data set WORK.SPSFM1 has 31172 observations and 12 variables.
NOTE: Compressing data set WORK.SPSFM1 decreased size by 12.72 percent. 
      Compressed is 487 pages; un-compressed would require 558 pages.
                                                                 The SAS System

NOTE: The data set WORK.SPSFM2 has 31351 observations and 12 variables.
NOTE: Compressing data set WORK.SPSFM2 decreased size by 12.66 percent. 
      Compressed is 490 pages; un-compressed would require 561 pages.
NOTE: The data set WORK.SPSFM3 has 31503 observations and 12 variables.
NOTE: Compressing data set WORK.SPSFM3 decreased size by 12.59 percent. 
      Compressed is 493 pages; un-compressed would require 564 pages.
NOTE: The data set WORK.SPSFM4 has 31759 observations and 12 variables.
NOTE: Compressing data set WORK.SPSFM4 decreased size by 12.50 percent. 
      Compressed is 497 pages; un-compressed would require 568 pages.
NOTE: The data set WORK.SPSFM5 has 31759 observations and 12 variables.
NOTE: Compressing data set WORK.SPSFM5 decreased size by 12.50 percent. 
      Compressed is 497 pages; un-compressed would require 568 pages.
NOTE: The data set WORK.SPSFM6 has 31759 observations and 12 variables.
NOTE: Compressing data set WORK.SPSFM6 decreased size by 12.50 percent. 
      Compressed is 497 pages; un-compressed would require 568 pages.
NOTE: The data set WORK.SPSFM7 has 31759 observations and 12 variables.
NOTE: Compressing data set WORK.SPSFM7 decreased size by 12.50 percent. 
      Compressed is 497 pages; un-compressed would require 568 pages.
NOTE: The data set WORK.SPSFM8 has 31759 observations and 12 variables.
NOTE: Compressing data set WORK.SPSFM8 decreased size by 12.50 percent. 
      Compressed is 497 pages; un-compressed would require 568 pages.
NOTE: The data set WORK.SPSFM9 has 31759 observations and 12 variables.
NOTE: Compressing data set WORK.SPSFM9 decreased size by 12.50 percent. 
      Compressed is 497 pages; un-compressed would require 568 pages.
NOTE: The data set WORK.SPSFM10 has 31759 observations and 12 variables.
NOTE: Compressing data set WORK.SPSFM10 decreased size by 12.50 percent. 
      Compressed is 497 pages; un-compressed would require 568 pages.
NOTE: The data set WORK.SPSFM11 has 31759 observations and 12 variables.
NOTE: Compressing data set WORK.SPSFM11 decreased size by 12.50 percent. 
      Compressed is 497 pages; un-compressed would require 568 pages.
NOTE: The data set WORK.SPSFM12 has 31759 observations and 12 variables.
NOTE: Compressing data set WORK.SPSFM12 decreased size by 12.50 percent. 
      Compressed is 497 pages; un-compressed would require 568 pages.
NOTE: DATA statement used (Total process time):
      real time           0.28 seconds
      cpu time            0.26 seconds
      

                                                                 The SAS System

561       +DATA SPS6;
562       +    SET SPSFM1
563       +        SPSFM2
564       +        SPSFM3
565       +        SPSFM4
566       +        SPSFM5
567       +        SPSFM6
568       +        SPSFM7
569       +        SPSFM8
570       +        SPSFM9
571       +        SPSFM10
572       +        SPSFM11
573       +        SPSFM12;

NOTE: There were 31172 observations read from the data set WORK.SPSFM1.
NOTE: There were 31351 observations read from the data set WORK.SPSFM2.
NOTE: There were 31503 observations read from the data set WORK.SPSFM3.
NOTE: There were 31759 observations read from the data set WORK.SPSFM4.
NOTE: There were 31759 observations read from the data set WORK.SPSFM5.
NOTE: There were 31759 observations read from the data set WORK.SPSFM6.
NOTE: There were 31759 observations read from the data set WORK.SPSFM7.
NOTE: There were 31759 observations read from the data set WORK.SPSFM8.
NOTE: There were 31759 observations read from the data set WORK.SPSFM9.
NOTE: There were 31759 observations read from the data set WORK.SPSFM10.
NOTE: There were 31759 observations read from the data set WORK.SPSFM11.
NOTE: There were 31759 observations read from the data set WORK.SPSFM12.
NOTE: The data set WORK.SPS6 has 379857 observations and 12 variables.
NOTE: Compressing data set WORK.SPS6 decreased size by 12.91 percent. 
      Compressed is 5908 pages; un-compressed would require 6784 pages.
NOTE: DATA statement used (Total process time):
      real time           0.37 seconds
      cpu time            0.37 seconds
      

574       +    PROC SORT; BY PROPNBR ACTDTE TRXNBR EFFMY;
575       +
576       +

                                                                 The SAS System

NOTE: There were 379857 observations read from the data set WORK.SPS6.
NOTE: The data set WORK.SPS6 has 379857 observations and 12 variables.
NOTE: Compressing data set WORK.SPS6 decreased size by 12.84 percent. 
      Compressed is 5913 pages; un-compressed would require 6784 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.35 seconds
      cpu time            0.57 seconds
      

577       +DATA SPS7X(KEEP=PROPNBR ACTDTE TRXNBR);
578       +  SET SPS6; BY PROPNBR ACTDTE TRXNBR EFFMY;
579       +    IF LAST.ACTDTE THEN OUTPUT SPS7X;
580       +

NOTE: There were 379857 observations read from the data set WORK.SPS6.
NOTE: The data set WORK.SPS7X has 92744 observations and 3 variables.
NOTE: Compressing data set WORK.SPS7X increased size by 6.69 percent. 
      Compressed is 590 pages; un-compressed would require 553 pages.
NOTE: DATA statement used (Total process time):
      real time           0.18 seconds
      cpu time            0.18 seconds
      

581       +PROC SORT; BY PROPNBR ACTDTE TRXNBR;
582       +

NOTE: There were 92744 observations read from the data set WORK.SPS7X.
NOTE: The data set WORK.SPS7X has 92744 observations and 3 variables.
NOTE: Compressing data set WORK.SPS7X increased size by 6.69 percent. 
      Compressed is 590 pages; un-compressed would require 553 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.06 seconds
      cpu time            0.06 seconds
      

583       +DATA SPS7;
584       + MERGE SPS7X(IN=A) SPS6(IN=B);
585       + BY PROPNBR ACTDTE TRXNBR;
                                                                 The SAS System

586       + IF A AND B;
587       +

NOTE: There were 92744 observations read from the data set WORK.SPS7X.
NOTE: There were 379857 observations read from the data set WORK.SPS6.
NOTE: The data set WORK.SPS7 has 135749 observations and 12 variables.
NOTE: Compressing data set WORK.SPS7 decreased size by 12.99 percent. 
      Compressed is 2110 pages; un-compressed would require 2425 pages.
NOTE: DATA statement used (Total process time):
      real time           0.26 seconds
      cpu time            0.26 seconds
      

588       +PROC SORT DATA = SPS7;  BY LSUID;
589       +

NOTE: There were 135749 observations read from the data set WORK.SPS7.
NOTE: The data set WORK.SPS7 has 135749 observations and 12 variables.
NOTE: Compressing data set WORK.SPS7 decreased size by 12.99 percent. 
      Compressed is 2110 pages; un-compressed would require 2425 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.12 seconds
      cpu time            0.15 seconds
      

590       +PROC SQL;
591       +  CREATE TABLE DIRFILE AS
592       + SELECT INDIV_NAME     AS PI
593       +       ,LSU_ID         AS LSUID
594       + FROM DIR.NAME;
NOTE: Compressing data set WORK.DIRFILE decreased size by 1.52 percent. 
      Compressed is 12522 pages; un-compressed would require 12715 pages.
NOTE: Table WORK.DIRFILE created, with 1169663 rows and 2 columns.

595       +
NOTE: PROCEDURE SQL used (Total process time):
      real time           2.35 seconds
      cpu time            1.63 seconds
                                                                 The SAS System

      

596       +PROC SORT; BY LSUID;
597       +

NOTE: There were 1169663 observations read from the data set WORK.DIRFILE.
NOTE: The data set WORK.DIRFILE has 1169663 observations and 2 variables.
NOTE: Compressing data set WORK.DIRFILE decreased size by 1.52 percent. 
      Compressed is 12522 pages; un-compressed would require 12715 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.74 seconds
      cpu time            1.06 seconds
      

598       +DATA SPS8(KEEP=PI LSUID DEPT PROPNBR ACTDTE SHARE TASK INVTYPE);
599       +  MERGE DIRFILE(IN=A) SPS7(IN=B);
600       +  BY LSUID;
601       +  IF B;
602       +
603       +/*PROC SQL;
604       +CREATE TABLE CODES AS
605       +SELECT CODE_TYPE AS CDTYPE
606       +      ,CODE_VALUE AS CODE
607       +      ,CODE_DESC AS CODENAME
608       +FROM COA.CODES
609       +WHERE CODE_TYPE = 'DA';
610       +
611       +PROC SORT DATA = CODES;
612       +  BY CODE;
613       +
614       +DATA NAMES(KEEP=DPT DPTNAME) COLNAME(KEEP=COLLEGE COLNAME);
615       + SET CODES;
616       +FORMAT COLLEGE DPT $5.;
617       +FORMAT COLNAME DPTNAME $35.;
618       + IF SUBSTR(CODE,4,2) = '  ' THEN DO;
619       +  COLLEGE = CODE;
620       +  COLNAME = CODENAME;
621       +  OUTPUT COLNAME;
                                                                 The SAS System

622       + END;
623       + ELSE DO;
624       +  DPT = CODE;
625       +  DPTNAME = CODENAME;
626       +  OUTPUT NAMES;
627       + END;
628       +
629       +PROC SORT DATA = NAMES;
630       +  BY DPT;
631       +
632       +PROC SORT DATA = SPS8;
633       +  BY DPT;
634       +
635       +DATA SPS9;
636       + MERGE NAMES(IN=A) SPS8(IN=B);
637       + BY DPT;
638       + IF B;
639       +  FORMAT DPTNAME $35.;
640       +  FORMAT COL $3.;
641       +  COL = SUBSTR(DPT,1,3);
642       +  COL1 = COL||'  ';
643       +  FORMAT COLLEGE $5.;
644       +  COLLEGE = COMPRESS(COL1);
645       +
646       +PROC SORT DATA = SPS9;
647       +  BY COLLEGE;
648       +
649       +PROC SORT DATA = COLNAME;
650       +  BY COLLEGE;
651       +
652       +DATA SPS10A;
653       + MERGE COLNAME(IN=A) SPS9(IN=B);
654       + BY COLLEGE;
655       + IF B;
656       +
657       +*DATA TEST; *SET SPS10A; *IF SUBSTR(COLLEGE,1,1) IN('3','9');
658       +
659       +DATA SPS10; SET SPS10A;
                                                                 The SAS System

660       +  IF SUBSTR(COLLEGE,1,1) = '3' THEN DO;
661       +    COLLEGE = '300';
662       +    COLNAME = 'PBRC';
663       +  END;
664       +  IF SUBSTR(COLLEGE,1,1) = '9' THEN DO;
665       +    COLLEGE = '900';
666       +    COLNAME = 'AG CENTER';
667       +  END;*/
668       +

NOTE: There were 1169663 observations read from the data set WORK.DIRFILE.
NOTE: There were 135749 observations read from the data set WORK.SPS7.
NOTE: The data set WORK.SPS8 has 135749 observations and 8 variables.
NOTE: Compressing data set WORK.SPS8 decreased size by 19.41 percent. 
      Compressed is 1084 pages; un-compressed would require 1345 pages.
NOTE: DATA statement used (Total process time):
      real time           0.49 seconds
      cpu time            0.49 seconds
      

669       +  proc sql;
670       +  create table ccdept as
671       +  select code_value1 as dept,
672       +  code_value2 as CC
673       +  from spm.codes
674       +where code_type = 'CCDEPT';
NOTE: Compressing data set WORK.CCDEPT increased size by 14.29 percent. 
      Compressed is 16 pages; un-compressed would require 14 pages.
NOTE: Table WORK.CCDEPT created, with 2587 rows and 2 columns.

NOTE: PROCEDURE SQL used (Total process time):
      real time           0.01 seconds
      cpu time            0.00 seconds
      

675       +proc sort; by  dept;
676       +

                                                                 The SAS System

NOTE: There were 2587 observations read from the data set WORK.CCDEPT.
NOTE: The data set WORK.CCDEPT has 2587 observations and 2 variables.
NOTE: Compressing data set WORK.CCDEPT increased size by 14.29 percent. 
      Compressed is 16 pages; un-compressed would require 14 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

677       +PROC SORT DATA = SPS8;
678       + BY dept;
679       +

NOTE: There were 135749 observations read from the data set WORK.SPS8.
NOTE: The data set WORK.SPS8 has 135749 observations and 8 variables.
NOTE: Compressing data set WORK.SPS8 decreased size by 19.41 percent. 
      Compressed is 1084 pages; un-compressed would require 1345 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.12 seconds
      cpu time            0.17 seconds
      

680       +data mrgcc; merge sps8(in=a) ccdept(in=b); by dept; if a;

WARNING: Multiple lengths were specified for the BY variable DEPT by input data sets. This may cause unexpected results.
NOTE: There were 135749 observations read from the data set WORK.SPS8.
NOTE: There were 2587 observations read from the data set WORK.CCDEPT.
NOTE: The data set WORK.MRGCC has 135749 observations and 9 variables.
NOTE: Compressing data set WORK.MRGCC decreased size by 17.68 percent. 
      Compressed is 1215 pages; un-compressed would require 1476 pages.
NOTE: DATA statement used (Total process time):
      real time           0.12 seconds
      cpu time            0.12 seconds
      

681       +proc sort; by cc;
682       +

                                                                 The SAS System

NOTE: There were 135749 observations read from the data set WORK.MRGCC.
NOTE: The data set WORK.MRGCC has 135749 observations and 9 variables.
NOTE: Compressing data set WORK.MRGCC decreased size by 17.68 percent. 
      Compressed is 1215 pages; un-compressed would require 1476 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.12 seconds
      cpu time            0.17 seconds
      

683       +proc sql;
684       +create table org as
685       +select org_id as CC,
686       +org_name as Cost_Center,
687       +superior_org as CC_Hier
688       +from wdm.organization
689       +where org_type = 'Cost_Center';
NOTE: Compressing data set WORK.ORG decreased size by 88.24 percent. 
      Compressed is 8 pages; un-compressed would require 68 pages.
NOTE: Table WORK.ORG created, with 1079 rows and 3 columns.

NOTE: PROCEDURE SQL used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

690       +proc sort;  BY CC;
691       +

NOTE: There were 1079 observations read from the data set WORK.ORG.
NOTE: The data set WORK.ORG has 1079 observations and 3 variables.
NOTE: Compressing data set WORK.ORG decreased size by 88.24 percent. 
      Compressed is 8 pages; un-compressed would require 68 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

692       +data mrgcc2; merge mrgcc(in=a) org(in=b); by cc; if a;
                                                                 The SAS System


WARNING: Multiple lengths were specified for the BY variable CC by input data sets. This may cause unexpected results.
NOTE: There were 135749 observations read from the data set WORK.MRGCC.
NOTE: There were 1079 observations read from the data set WORK.ORG.
NOTE: The data set WORK.MRGCC2 has 135749 observations and 11 variables.
NOTE: Compressing data set WORK.MRGCC2 decreased size by 81.27 percent. 
      Compressed is 1338 pages; un-compressed would require 7145 pages.
NOTE: DATA statement used (Total process time):
      real time           0.23 seconds
      cpu time            0.23 seconds
      

693       +proc sort;  BY CC_Hier;
694       +

NOTE: There were 135749 observations read from the data set WORK.MRGCC2.
NOTE: The data set WORK.MRGCC2 has 135749 observations and 11 variables.
NOTE: Compressing data set WORK.MRGCC2 decreased size by 81.27 percent. 
      Compressed is 1338 pages; un-compressed would require 7145 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.28 seconds
      cpu time            0.48 seconds
      

695       +proc sql;
696       +create table org as
697       +select org_id as CC_Hier,
698       +org_name as Cost_Center_Hierarchy
699       +from wdm.organization
700       +where org_type = 'Cost_Center_Hierarchy';
NOTE: Compressing data set WORK.ORG decreased size by 75.00 percent. 
      Compressed is 2 pages; un-compressed would require 8 pages.
NOTE: Table WORK.ORG created, with 149 rows and 2 columns.

NOTE: PROCEDURE SQL used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      
                                                                 The SAS System


701       +proc sort;  BY CC_Hier;
702       +

NOTE: There were 149 observations read from the data set WORK.ORG.
NOTE: The data set WORK.ORG has 149 observations and 2 variables.
NOTE: Compressing data set WORK.ORG decreased size by 75.00 percent. 
      Compressed is 2 pages; un-compressed would require 8 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

703       +data mrgcc2; merge mrgcc2(in=a) org(in=b); by CC_Hier; if a;
704       +Cost_Center_Hierarchy = scan(Cost_Center_Hierarchy,-1,'|');

NOTE: There were 135749 observations read from the data set WORK.MRGCC2.
NOTE: There were 149 observations read from the data set WORK.ORG.
NOTE: The data set WORK.MRGCC2 has 135749 observations and 12 variables.
NOTE: Compressing data set WORK.MRGCC2 decreased size by 86.08 percent. 
      Compressed is 1575 pages; un-compressed would require 11313 pages.
NOTE: DATA statement used (Total process time):
      real time           0.34 seconds
      cpu time            0.34 seconds
      

705       +proc sort;  BY PROPNBR ACTDTE TASK;
706       +
707       +
708       +/*PROC SORT DATA = SPS10;
709       + BY PROPNBR ACTDTE TASK;*/
710       +

NOTE: There were 135749 observations read from the data set WORK.MRGCC2.
NOTE: The data set WORK.MRGCC2 has 135749 observations and 12 variables.
NOTE: Compressing data set WORK.MRGCC2 decreased size by 86.08 percent. 
      Compressed is 1575 pages; un-compressed would require 11313 pages.
NOTE: PROCEDURE SORT used (Total process time):
                                                                 The SAS System

      real time           0.38 seconds
      cpu time            0.54 seconds
      

711       +PROC SORT DATA = GLSCOA16;
712       + BY PROPNBR ACTDTE TASK;
713       +

NOTE: There were 136 observations read from the data set WORK.GLSCOA16.
NOTE: The data set WORK.GLSCOA16 has 136 observations and 35 variables.
NOTE: Compressing data set WORK.GLSCOA16 decreased size by 65.00 percent. 
      Compressed is 7 pages; un-compressed would require 20 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

714       +PROC SQL;
715       + CREATE TABLE GLSSPS1 AS
716       + SELECT A.*,
717       +        B.PI,
718       +        B.LSUID,
719       +        B.INVTYPE,
720       +        B.SHARE,
721       +        B.Cost_Center_Hierarchy,
722       +        B.CC,
723       +        B.Cost_Center
724       +FROM GLSCOA16 A,
725       +     mrgcc2  B
726       +WHERE A.PROPNBR = B.PROPNBR AND
727       +      A.ACTDTE  = B.ACTDTE AND
728       +      A.TASK    = B.TASK;
NOTE: Compressing data set WORK.GLSSPS1 decreased size by 74.51 percent. 
      Compressed is 13 pages; un-compressed would require 51 pages.
NOTE: Table WORK.GLSSPS1 created, with 249 rows and 42 columns.

729       +
730       +
                                                                 The SAS System

NOTE: PROCEDURE SQL used (Total process time):
      real time           0.07 seconds
      cpu time            0.07 seconds
      

731       +DATA GLSSPS10(KEEP=PROPNBR ACTDTE); SET GLSSPS1; BY PROPNBR ACTDTE;
732       + IF FIRST.ACTDTE THEN OUTPUT;

NOTE: Compression was disabled for data set WORK.GLSSPS10 because compression overhead would increase the size of the data set.
NOTE: There were 249 observations read from the data set WORK.GLSSPS1.
NOTE: The data set WORK.GLSSPS10 has 116 observations and 2 variables.
NOTE: DATA statement used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

733       + proc sort; by propnbr actdte;
734       +

NOTE: There were 116 observations read from the data set WORK.GLSSPS10.
NOTE: The data set WORK.GLSSPS10 has 116 observations and 2 variables.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

735       + proc sort data=glscoa16; by propnbr actdte;

NOTE: Input data set is already sorted, no sorting done.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

736       +DATA GLSCOA10;
737       + MERGE GLSCOA16(IN=A) GLSSPS10(IN=B);
738       + BY PROPNBR ACTDTE;
739       + IF A AND NOT B;
                                                                 The SAS System

740       +

NOTE: There were 136 observations read from the data set WORK.GLSCOA16.
NOTE: There were 116 observations read from the data set WORK.GLSSPS10.
NOTE: The data set WORK.GLSCOA10 has 0 observations and 35 variables.
NOTE: DATA statement used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

741       +DATA GLSSPS;
742       + SET GLSSPS1 GLSCOA10;
743       +
744       +IF SHARE = '.' THEN DO; CLSUIDTOT = CACCTAMT; NLSUIDTOT = NACCTAMT;
745       +                        CLSUIDMON = CTOTMON ; NLSUIDMON = NTOTMON ;
746       +END;
747       + ELSE DO; CLSUIDTOT = CACCTAMT * SHARE / 100;
748       +          NLSUIDTOT = NACCTAMT * SHARE / 100;
749       +          CLSUIDMON = CTOTMON * SHARE / 100;
750       +          NLSUIDMON = NTOTMON * SHARE / 100;
751       +END;
752       +

NOTE: Character values have been converted to numeric values at the places given by: (Line):(Column).
      744:12   
NOTE: There were 249 observations read from the data set WORK.GLSSPS1.
NOTE: There were 0 observations read from the data set WORK.GLSCOA10.
NOTE: The data set WORK.GLSSPS has 249 observations and 46 variables.
NOTE: Compressing data set WORK.GLSSPS decreased size by 74.51 percent. 
      Compressed is 13 pages; un-compressed would require 51 pages.
NOTE: DATA statement used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

753       +PROC SORT DATA = GLSSPS; BY Cost_Center_Hierarchy;
754       +

                                                                 The SAS System

NOTE: There were 249 observations read from the data set WORK.GLSSPS.
NOTE: The data set WORK.GLSSPS has 249 observations and 46 variables.
NOTE: Compressing data set WORK.GLSSPS decreased size by 74.51 percent. 
      Compressed is 13 pages; un-compressed would require 51 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

755       +DATA GLSSPS10; SET GLSSPS; BY Cost_Center_Hierarchy;
756       + IF FIRST.Cost_Center_Hierarchy THEN DO;
757       +  NCOLYTD = NLSUIDTOT;
758       +  NCOLMON = NLSUIDMON;
759       +  CCOLYTD = CLSUIDTOT;
760       +  CCOLMON = CLSUIDMON;
761       + END;
762       + ELSE DO;
763       +  NCOLYTD + NLSUIDTOT;
764       +  NCOLMON + NLSUIDMON;
765       +  CCOLYTD + CLSUIDTOT;
766       +  CCOLMON + CLSUIDMON;
767       + END;
768       + IF LAST.Cost_Center_Hierarchy THEN DO;
769       +   NCOLYTD = ROUND(NCOLYTD,1.);
770       +   NCOLMON = ROUND(NCOLMON,1.);
771       +   CCOLYTD = ROUND(CCOLYTD,1.);
772       +   CCOLMON = ROUND(CCOLMON,1.);
773       +   OUTPUT;
774       + END;

NOTE: There were 249 observations read from the data set WORK.GLSSPS.
NOTE: The data set WORK.GLSSPS10 has 22 observations and 50 variables.
NOTE: Compressing data set WORK.GLSSPS10 decreased size by 40.00 percent. 
      Compressed is 3 pages; un-compressed would require 5 pages.
NOTE: DATA statement used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      
                                                                 The SAS System


775       + proc sort; by Cost_Center_Hierarchy;
776       +

NOTE: There were 22 observations read from the data set WORK.GLSSPS10.
NOTE: The data set WORK.GLSSPS10 has 22 observations and 50 variables.
NOTE: Compressing data set WORK.GLSSPS10 decreased size by 40.00 percent. 
      Compressed is 3 pages; un-compressed would require 5 pages.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

777       +DATA BAD; SET GLSSPS10;
778       + IF Cost_Center_Hierarchy = ' ' THEN OUTPUT;

NOTE: There were 22 observations read from the data set WORK.GLSSPS10.
NOTE: The data set WORK.BAD has 0 observations and 50 variables.
NOTE: DATA statement used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

779       +proc sort; by grant_id;
780       +/*PROC PRINT;
781       +TITLE1 'COULD NOT MERGE WITH SPM';
782       +TITLE2 '  ';
783       +VAR GRANT_ID FUND AWARD_NUMBER TASK_NUMBER	GRANT_EXP_DATE	SPONSOR_ID	SPONSOR_NAME propnbr LSU_PIID;*/
784       +
785       +
786       +
787       +%global _ODSDEST;
788       +%global _ODSSTYLE;
789       +
790       +%MACRO PRINT;
791       +OPTIONS ORIENTATION=LANDSCAPE;
792       +
793       +%IF (%UPCASE("&_ODSDEST") eq "PHTML")+ (%UPCASE("&_ODSDEST") eq "PDF") %THEN %DO;
                                                                 The SAS System

794       +%IF (%UPCASE("&_ODSDEST") eq "PHTML") %THEN %DO;
795       +data _null_ ;
796       +	rc = stpsrv_header('Content-type','text/html');
797       +run ;
798       +ods listing close;
799       +ods html body=_webout style=default;
800       +%END;
801       +
802       +%IF (%UPCASE("&_ODSDEST") eq "PDF") %THEN %DO;
803       +data _null_ ;
804       +	rc = stpsrv_header('Content-type','application/pdf') ;
805       +	rc = stpsrv_header('Content-disposition',"attachment; filename=&TME..pdf");
806       +run ;
807       +ods listing close;
808       +ods pdf file=_webout style=FSS;
809       +%END;
810       +
811       +PROC TABULATE DATA = GLSSPS10  FORMAT=COMMA16.;
812       +TITLE " MONTHLY REPORT OF SPONSORED AGREEMENTS ";
813       +TITLE2 " BY Cost Center Hierarchy ";
814       +TITLE3 " PROCESSED IN &MON &EFFYR  ";
815       + CLASS Cost_Center_Hierarchy;
816       + VAR NCOLMON CCOLMON NCOLYTD CCOLYTD;
817       + TABLE Cost_Center_Hierarchy='  ' ALL='TOTAL',
818       +        (NCOLMON="&HEADER &EFFYR NEW"
819       +        CCOLMON="&HEADER &EFFYR CONT"
820       +        NCOLYTD ="FY &FISCAL YTD NEW"
821       +        CCOLYTD="FY &FISCAL YTD CONT")
822       +        * SUM=' ' /
823       +        BOX='COST CENTER HIERARCHY';
824       +RUN;
825       +/*PROC TABULATE DATA = GLSSPS10  FORMAT=COMMA16.;
826       +TITLE " MONTHLY REPORT OF SPONSORED AGREEMENTS ";
827       +TITLE2 " BY COLLEGE ";
828       +TITLE3 " PROCESSED IN &MON &EFFYR  ";
829       + CLASS COLNAME;
830       + VAR NCOLMON CCOLMON NCOLYTD CCOLYTD;
831       + TABLE COLNAME='  ' ALL='TOTAL',
                                                                 The SAS System

832       +        (NCOLMON="&HEADER &EFFYR NEW"
833       +        CCOLMON="&HEADER &EFFYR CONT"
834       +        NCOLYTD ="FY &FISCAL YTD NEW"
835       +        CCOLYTD="FY &FISCAL YTD CONT")
836       +        * SUM=' ' /
837       +        BOX='COLLEGES';
838       +RUN;*/
839       +
840       +%IF (%UPCASE("&_ODSDEST") eq "PHTML") %THEN %DO;
841       +ods html close;
842       +%END;
843       +%IF (%UPCASE("&_ODSDEST") eq "PDF") %THEN %DO;
844       +ods pdf close;
845       +%END;
846       +
847       +%END;
848       +%MEND PRINT;
849       +%PRINT;
SYMBOLGEN:  Macro variable _ODSDEST resolves to PDF
SYMBOLGEN:  Macro variable _ODSDEST resolves to PDF
SYMBOLGEN:  Macro variable _ODSDEST resolves to PDF
SYMBOLGEN:  Macro variable _ODSDEST resolves to PDF

NOTE: Input data set is empty.
NOTE: The data set WORK.BAD has 0 observations and 50 variables.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds
      

SYMBOLGEN:  Macro variable TME resolves to    64184.011

NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

WARNING: Style FSS not found; Printer style will be used instead.
                                                                 The SAS System

NOTE: Writing ODS PDF output to DISK destination "_WEBOUT", printer "PDF".
SYMBOLGEN:  Macro variable MON resolves to AUGUST   
SYMBOLGEN:  Macro variable EFFYR resolves to 2017
SYMBOLGEN:  Macro variable HEADER resolves to    AUGUST
SYMBOLGEN:  Macro variable EFFYR resolves to 2017
SYMBOLGEN:  Macro variable HEADER resolves to    AUGUST
SYMBOLGEN:  Macro variable EFFYR resolves to 2017
SYMBOLGEN:  Macro variable FISCAL resolves to 2018
SYMBOLGEN:  Macro variable FISCAL resolves to 2018

NOTE: There were 22 observations read from the data set WORK.GLSSPS10.
NOTE: PROCEDURE TABULATE used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds
      

SYMBOLGEN:  Macro variable _ODSDEST resolves to PDF
SYMBOLGEN:  Macro variable _ODSDEST resolves to PDF
NOTE: ODS PDF printed 1 page to 01B71C45-D0C8-4E2C-A700-13ED0828A869.
850       +
851       +*  Begin EG generated code (do not edit this line);
852       +;*';*";*/;quit;
853       +
854       +*  End EG generated code (do not edit this line);
855       +
NOTE: %INCLUDE (level 1) ending.