=20

On Tuesday, January 14, 2020, 6:15:04 PM GMT+1, Min Jae= Kim kjh950429 _ gmail.com <owner-chemistry-$-ccl.net> wrote:

Sent to CC= L by: "Min Jae Kim" [kjh950429%%gmail.com]

= Dear all,

I am current= ly trying to set up GAMESS on a super computer, and was

encountering errors trying to link an executable form of GAMESS. I= am

currently working in a linux64 machine. My F= ORTRAN Compiler setup is gfortran

(ver. 4.8) wit= h openmpi and using a atlas-so library.

I have located the atlas libraries on the machine I'm wo= rking with, but they

seemed to be divided into t= wo: libsatlas.so.3.10, libtatlas.so.3.10. There

= were also pre-made links to these libraries in the same directory--

libsatlas.so.3 and libtatlas.so.3 respectively.

When I run the lked command, = I get the following lked.log file:

GAMESS will be linked into the binary file gamess.01.x.

The name of the linker on t= his machine is gfortran,

and the linker options a= re " ".

Object code l= ist begins "gamess.o unport.o",

followed by = BLAS object code " ",

followed by LAPACK object= code "dgeev.o dgesvd.o zheev.o",

followed by VEC= TOR object code " ",

followed by memory object co= de "zunix.o",

followed by the standard GAMESS obj= ect code list,

aldeci= .o algnci.o ... (I deleted rest of the list in this email to save

length)

Choices for some optional plug-in codes are

= Tinker/SIMOMM code skipped, using dummy file qmmm.o

Both VB programs skipped, using dummy file vbdum.o

Nuclear Electron Orbital code skipped, using d= ummy file neostb.o

Natural Bond Orbital (= NBO) code skipped, using dummy file nbostb.o

&nbs= p; MPQC code skipped, using dummy file mpqcst.o

The message passing libraries searched = are

/scratch/user330/gamess/ddi/libddi.a -L/usr/i= nclude/openmpi-x86_64/lib -lmpi

-lpthread

Other libraries, in= cluding math libraries, to be searched are

-L/usr= /lib64/atlas -lf77blas -latlas

Linker messages (if any) follow...

dgee= v.o dgesvd.o zheev.o

gfortran -L/scratch/user330/= gamess/libcchem/boost/lib -o

/scratch/user330/ga= mess/gamess.01.x -I/scratch/user330/gamess/object gamess.o

unport.o dgeev.o dgesvd.o zheev.o zunix.o aldeci.o algnci.o basc= cn.o basecp.o

basext.o basg3l.o bashuz.o bashz2.= o baskar.o basminix.o basn21.o basn31.o

baspcn.o= basg3x.o bassto.o casino.o ccaux.o ccddi.o ccqaux.o ccquad.o ccsdt.o
<= /div>

ceeis.o cepa.o cnglob.o chgpen.o cimf.o ciminf.o cimi= .o cimlib.o cimsub.o

cisgrd.o comp.o cosmo.o cos= prt.o cphf.o cpmchf.o cprohf.o cpuhf.o dccc.o

dc= grd.o dcgues.o dcint2.o dclib.o dcmp2.o dcscf.o dctran.o ddilib.o delocl.o =

demrpt.o dft.o dftaux.o dftbfo.o dftbgr.o dftbhs= .o dftblb.o dftbsk.o dftbtd.o

dftbx.o dftdis.o d= ftfun.o dftgrd.o dftint.o dftxca.o dftxcb.o dftxcc.o

dftxcd.o dftxce.o dftxcf.o dftxcg.o diab.o dmulti.o drc.o eaipcc.o ecp= .o

ecpder.o ecplib.o ecppot.o efpmodule.o efchtr= .o efdrvr.o efelec.o efgrd2.o

efgrda.o efgrdb.o = efgrdc.o efinp.o efinta.o efintb.o efmo.o efmograd.o

efmograd_es.o efmograd_exrep.o efmograd_disp.o efmograd_pol.o efpaul.o=

efpcm.o efpcov.o efpfmo.o eftei.o eigen.o elgli= b.o elgloc.o elgscf.o eomcc.o

ewald.o excorr.o f= field.o fmo.o fmoafo.o fmocp.o fmoesd.o fmogrd.o fmoh1a.o

fmoh2a.o fmoh2b.o fmoh2c.o fmohss.o fmoint.o fmoio.o fmoio_read.o= fmolib.o

fmomm.o fmopbc.o fmoprp.o frfmt.o fsod= ci.o g3.o globop.o gmcpt.o gradex.o

guess.o grd1= .o grd2a.o grd2b.o grd2c.o gugdga.o gugdgb.o gugdm.o gugdm2.o

gugdrt.o gugem.o gugsrt.o gvb.o hess.o hss1a.o hss1b.o hss1c.= o hss2a.o

hss2b.o hss2c.o inputa.o inputb.o inpu= tc.o int1.o int2a.o int2b.o int2c.o

int2d.o int2= f.o int2g.o int2r.o int2s.o iolib.o ivocas.o lagran.o local.o

locatd.o loccd.o locpol.o locsvd.o lrd.o lut.o modmcpdft.o mc= pdft.o mcpgrd.o

mcpinp.o mcpint.o mcpl10.o mcpl2= 0.o mcpl30.o mcpl40.o mcpl50.o mcpl60.o

mcpl70.o= mcpl80.o mccas.o mcjac.o mcqdpt.o mcqdwt.o mcqud.o mcscf.o mctwo.o

mdefp.o mexing.o mltfmo.o mm23.o modmnfun.o morokm.o mn= sol.o mp2.o mp2ddi.o

mp2grd.o mp2gr2.o mp2ims.o = mpcdat.o mpcdatpm6.o mpcgrd.o mpchbond.o mpcint.o

mpcmol.o mpcmsc.o mpcpcm.o mthlib.o nameio.o nebpath.o nmr.o optcix.o

ordint.o ormas1.o ormpt2.o parley.o pcm.o pcmcav.o = pcmcv2.o pcmder.o pcmdis.o

pcmhss.o pcmief.o pcm= pol.o pcmvch.o prpamm.o prpel.o prplib.o prppop.o

qeigen.o qfmm.o qmfm.o qrel.o quanpo.o raman.o reorg.o rhfuhf.o ricab.o <= br>

riint.o rimp2.o rimp2omp.o rimp2grd.o rmd.o rmdda= t.o rmdgen.o rmdwrk.o

rmdrun.o roeom.o rohfcc.o = rxncrd.o ryspol.o scflib.o scfmi.o scrf.o secor.o

sfdft.o sfgrad.o sobrt.o soffac.o solib.o sozeff.o statpt.o hrmrst.o surf= .o

svpchg.o svpinp.o svpleb.o symhi.o symorb.o s= ymslc.o tddft.o tddefp.o

tddfun.o tddfxc.o tddgr= d.o tddint.o tddnlr.o tddxca.o tddxcc.o tddxcd_m05.o

tddxcd_m06.o tddxcd_m08.o tddxcd_pkzb.o tddxcd_revtpss.o tddxcd_tpss.o=

tddxcd_vs98.o tddxce.o tdhf.o tdx.o tdxio.o tdx= itr.o tdxni.o tdxprp.o trans.o

trfdm2.o trnstn.o= trudge.o umpddi.o utddft.o utdgrd.o vibanl.o vscf.o vvos.o

zapddi.o zmatrx.o mod_nosp_basis.o mod_grid_storage.o mod_dft_p= artfunc.o

mod_dft_molgrid.o mod_dft_fuzzycell.o = mod_dft_gridint.o ccsd3aacgreorder.o

ccsd3aacgsu= m.o ccsd3aacgt1A00.o ccsd3aacgt1A01.o ccsd3aacgt1A10.o

ccsd3aacgt1A11.o ccsd3aacgt1A.o ccsd3aacgt1B00.o ccsd3aacgt1B01.o =

ccsd3aacgt1B10.o ccsd3aacgt1B11.o ccsd3aacgt1B.o= ccsd3aacgt2A0000.o

ccsd3aacgt2A0010.o ccsd3aacg= t2A0011.o ccsd3aacgt2A1000.o ccsd3aacgt2A1010.o

= ccsd3aacgt2A1011.o ccsd3aacgt2A1100.o ccsd3aacgt2A1110.o ccsd3aacgt2A1111.o=

ccsd3aacgt2A1.o ccsd3aacgt2A.o ccsd3aacgt2B0000= .o ccsd3aacgt2B0001.o

ccsd3aacgt2B0010.o ccsd3aa= cgt2B0011.o ccsd3aacgt2B0100.o ccsd3aacgt2B0101.o

ccsd3aacgt2B0110.o ccsd3aacgt2B0111.o ccsd3aacgt2B1000.o ccsd3aacgt2B1001= .o

ccsd3aacgt2B1010.o ccsd3aacgt2B1011.o ccsd3aa= cgt2B1100.o ccsd3aacgt2B1101.o

ccsd3aacgt2B1110.= o ccsd3aacgt2B1111.o ccsd3aacgt2B1.o ccsd3aacgt2B.o

ccsd3aacgt2C0000.o ccsd3aacgt2C0010.o ccsd3aacgt2C0011.o ccsd3aacgt2C10= 00.o

ccsd3aacgt2C1010.o ccsd3aacgt2C1011.o ccsd3= aacgt2C1100.o ccsd3aacgt2C1110.o

ccsd3aacgt2C111= 1.o ccsd3aacgt2C1.o ccsd3aacgt2C.o ccsd3aacgt3A100100.o

ccsd3aacgt3A100110.o ccsd3aacgt3A100111.o ccsd3aacgt3A110100.o

ccsd3aacgt3A110110.o ccsd3aacgt3A110111.o ccsd3aacg= t3A111100.o

ccsd3aacgt3A111110.o ccsd3aacgt3A111= 111.o ccsd3aacgt3AB.o

ccsd3aacgt3B001001.o ccsd3= aacgt3B001100.o ccsd3aacgt3B001101.o

ccsd3aacgt3= B001110.o ccsd3aacgt3B001111.o ccsd3aacgt3B100001.o

ccsd3aacgt3B100100.o ccsd3aacgt3B100101.o ccsd3aacgt3B100110.o

ccsd3aacgt3B100111.o ccsd3aacgt3B101001.o ccsd3aacgt3B10= 1100.o

ccsd3aacgt3B101101.o ccsd3aacgt3B101110.o= ccsd3aacgt3B101111.o

ccsd3aacgt3B110001.o ccsd3= aacgt3B110100.o ccsd3aacgt3B110101.o

ccsd3aacgt3= B110110.o ccsd3aacgt3B110111.o ccsd3aacgt3B111001.o

ccsd3aacgt3B111100.o ccsd3aacgt3B111101.o ccsd3aacgt3B111110.o

ccsd3aacgt3B111111.o ccsd3aacgt3BC.o ccsd3aacgt3C010010.= o

ccsd3aacgt3C010011.o ccsd3aacgt3C010100.o ccsd= 3aacgt3C010110.o

ccsd3aacgt3C010111.o ccsd3aacgt= 3C011010.o ccsd3aacgt3C011011.o

ccsd3aacgt3C0111= 00.o ccsd3aacgt3C011110.o ccsd3aacgt3C011111.o

c= csd3aacgt3C100010.o ccsd3aacgt3C100011.o ccsd3aacgt3C100100.o

ccsd3aacgt3C100110.o ccsd3aacgt3C100111.o ccsd3aacgt3C110010.= o

ccsd3aacgt3C110011.o ccsd3aacgt3C110100.o ccsd= 3aacgt3C110110.o

ccsd3aacgt3C110111.o ccsd3aacgt= 3C111010.o ccsd3aacgt3C111011.o

ccsd3aacgt3C1111= 00.o ccsd3aacgt3C111110.o ccsd3aacgt3C111111.o

c= csd3aacgt3CD.o ccsd3aacgt3D100100.o ccsd3aacgt3D100110.o

ccsd3aacgt3D100111.o ccsd3aacgt3D110100.o ccsd3aacgt3D110110.o

ccsd3aacgt3D110111.o ccsd3aacgt3D111100.o ccsd3aacg= t3D111110.o

ccsd3aacgt3D111111.o ccsd3amain.o qm= mm.o vbdum.o neostb.o nbostb.o cchdmy.o

prec.o p= arams.o mpqcst.o -L/usr/lib64/atlas -lf77blas -latlas -

L/usr/lib64/atlas -lf77blas -latlas /scratch/user330/gamess/ddi/li= bddi.a -

L/usr/include/openmpi-x86_64/lib -lmpi -= lpthread

/usr/bin/ld: cannot find -lf77blas

/usr/bin/ld: cannot find -latlas

/usr/bin/ld: cannot find -lf77blas

/usr/bin/= ld: cannot find -latlas

/usr/bin/ld: cannot find = -lmpi

collect2: error: ld returned 1 exit status<= br>

set rc=3D1

unset echo

Unfortunately, there w= as an error while linking GAMESS.

0.379u 0.553s 0= :01.19 77.3% 0+0k 0+40io 0pf+0w

I would really appreciate any advice or help on= this issue. Thank you.

-=3D This is automa= tically added to each message by the mailing script =3D-

To recover the email address of the author of the message, please = change

the strange characters on the top line to = the -$- sign. You can also

look up the X-Original-F= rom: line in the mail header.

E-mail to subscribers: CHEMISTRY-$-ccl.net or use:

http://www.ccl.net/cgi-b= in/ccl/send_ccl_message

E-mail to administrators: CHEMISTRY-REQUEST-$-ccl.net or use

http://ww= w.ccl.net/cgi-bin/ccl/send_ccl_message

&nbs= p; http://www.ccl.net/chemistry/sub_unsub.sh= tml

Before posting= , check wait time at: http://www.ccl.net

Job: http://www.ccl.net/jobs

Conf= erences: http://server.ccl.net/chemistry/ann= ouncements/conferences/

Search Messages: http://www.ccl.net/chemistry/= searchccl/index.shtml

http://www.ccl.net/spammers.txt
<= /div>

RTFI: http://www.ccl.net/chemistry/aboutccl/instructions/

------=_Part_7554992_1765309511.1579022677713-- From owner-chemistry@ccl.net Tue Jan 14 17:03:00 2020 From: "Marcos Verissimo Alves marcos_verissimo^-^id.uff.br" To: CCL Subject: CCL:G: Generating NBO archive deck from GAMESS Message-Id: <-53957-200114132726-3505-tZy5oQnUiPuFIxSF0Biq8A-.-server.ccl.net> X-Original-From: Marcos Verissimo Alves Content-Type: multipart/related; boundary="000000000000d5bb2e059c1dbdf0" Date: Tue, 14 Jan 2020 15:27:03 -0300 MIME-Version: 1.0 Sent to CCL by: Marcos Verissimo Alves [marcos_verissimo[a]id.uff.br] --000000000000d5bb2e059c1dbdf0 Content-Type: multipart/alternative; boundary="000000000000d5bb2d059c1dbdef" --000000000000d5bb2d059c1dbdef Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable If you're not very fluent in Linux, and you don't want to leave Windows altogether, perhaps a good solution would be to install a virtual Linux machine, compile Molden there, and then copy the Molden output to wherever you need on Windows. Apart from one pathological case, I've never had any trouble installing VMs with Linux and working with them. Cheers, Marcos Em ter, 14 de jan de 2020 13:52, Gijs.Schaftenaar~~radboudumc.nl < owner-chemistry[A]ccl.net> escreveu: > From the Author of Molden, > > > The windows version of Molden is less stable than the linux > > version. It uses the SDL library instead of the Xwindows graphical > library. The source to the windows version I do not > > distribute. Besides the SDL version, there is also the cygwin > > version, but this has not been updated since the inception of > > the SDL version. Be sure to use the SDL version, URL: > > > > ftp://ftp.cmbi.ru.nl/pub/molgraph/molden/bin/Windows/molden_native_window= s.rar > =E2=80=8B > > > Best Regards, > > > Dr Gijs Schaftenaar > > > ------------------------------ > *From:* owner-chemistry+gijs.schaftenaar=3D=3Dradboudumc.nl\a/ccl.net > on behalf= of > Mark Zottola mzottola]|[gmail.com > *Sent:* 13 January 2020 20:17 > *To:* Schaftenaar, Gijs > *Subject:* CCL:G: Generating NBO archive deck from GAMESS > > May, > > Thanks for your reply... But I am encountering a few problems... > I am trying to use MOLDEN on a windows laptop. MOLDEN does not seem to b= e > stable. It will create a shell (assuming it is a command line interprete= r > for MOLDEN) but then immediately shuts down. Would it be better to run > MOLDEN on linux? Or is there something unique to the WIndows version tha= t > I am missing? > > Second - though I have yet to reach this point (see above) - which file d= o > I convert to a .molden file? Is it the file in the restart directory or > the actual log file? > > Thank you for your help... > > On Mon, Jan 13, 2020 at 3:02 AM may abdelghani may01dz:yahoo.fr < > owner-chemistry%ccl.net> wrote: > >> Hi, >> >> 1/Convert the GAMESS output file to .molden file with MOLDEN program, >> 2/Use Molden2AIM (https://github.com/zorkzou/Molden2AIM) to convert >> .molden file to NBO-47 files >> [image: Image en ligne] >> >> De informatie in dit bericht is uitsluitend bestemd voor de > geadresseerde. Aan dit bericht en de bijlagen kunnen geen rechten worden > ontleend. Heeft u deze e-mail onbedoeld ontvangen? Dan verzoeken wij u he= t > te vernietigen en de afzender te informeren. Openbaar maken, kopi=C3=ABre= n en > verspreiden van deze e-mail of informatie uit deze e-mail is alleen > toegestaan met voorafgaande schriftelijke toestemming van de afzender. He= t > Radboudumc staat geregistreerd bij de Kamer van Koophandel in het > handelsregister onder nummer 41055629. > > The content of this message is intended solely for the addressee. No > rights can be derived from this message or its attachments. If you are no= t > the intended recipient, we kindly request you to delete the message and > inform the sender. It is strictly prohibited to disclose, copy or > distribute this email or the information inside it, without a written > consent from the sender. Radboud university medical center is registered > with the Dutch Chamber of Commerce trade register with number 41055629. > --000000000000d5bb2d059c1dbdef Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable

If you're not very fluent in Linux, and you don't= want to leave Windows altogether, perhaps a good solution would be to inst= all a virtual Linux machine, compile Molden there, and then copy the Molden= output to wherever you need on Windows. Apart from one pathological case, = I've never had any trouble installing VMs with Linux and working with t= hem.

Cheers,=C2=A0

Marcos

Em ter, 14 de jan de 20= 20 13:52, Gijs.Schaftenaar~~radboudumc.nl<= /a> <owner-chemistry[A]ccl.net<= /a>> escreveu:

From the Author of Molden,

The windows version of Molden is less stable than the linux

version. It uses the SDL library instead of the Xwindows graphical libra= ry. The source to the windows version I do not

distribute. Besides the SDL version, there is also the cygwin=C2=A0

version, but this has not been updated since the inception of

the SDL version. Be sure to use the SDL version, URL:

= ftp://ftp.cmbi.ru.nl/pub/molgraph/molden/bin/Windows/molden_native_windows.= rar=E2=80=8B

Best Regards,

Dr Gijs Schaftenaar

From: = owner-chemistry+gijs.schaftenaar=3D=3Dradboudumc.nl\a/ccl.net <owner-chemistry+g= ijs.schaftenaar=3D=3Dradboudumc.nl\a/ccl.net> on behalf of Mark Zottola mzottola]|[gmail.com <owner-chemistry\a/ccl.net>
Sent: 13 January 2020 20:17
To: Schaftenaar, Gijs
Subject: CCL:G: Generating NBO archive deck from GAMESS
=C2=A0

May,

Thanks for your repl= y... But I am encountering a few problems...

I am trying to use M= OLDEN on a windows laptop.=C2=A0 MOLDEN does not seem to be stable.=C2=A0 I= t will create a shell (assuming it is a command line interpreter for MOLDEN= ) but then immediately shuts down.=C2=A0 Would it be better to run MOLDEN on linux?=C2=A0 Or is there something unique to the W= Indows version that I am missing?

Second - though I ha= ve yet to reach this point (see above) - which file do I convert to a .mold= en file?=C2=A0 Is it the file in the restart directory or the actual log fi= le?=C2=A0=C2=A0

Thank you for your h= elp...

On Mon, Jan 13, 2020 at 3:02 AM may a= bdelghani may01dz:yahoo.fr <owner-chemistry%ccl.net> wrote:

Hi,

1/Convert the GAMESS output file to .molden file wi= th MOLDEN program,

2/Use Molden2AIM (https://github.com/= zorkzou/Molden2AIM) to convert .molden file to NBO-47 files

De informat= ie in dit bericht is uitsluitend bestemd voor de geadresseerde. Aan dit ber= icht en de bijlagen kunnen geen rechten worden ontleend. Heeft u deze e-mai= l onbedoeld ontvangen? Dan verzoeken wij u het te vernietigen en de afzender te informeren. Openbaar maken, kop= i=C3=ABren en verspreiden van deze e-mail of informatie uit deze e-mail is = alleen toegestaan met voorafgaande schriftelijke toestemming van de afzende= r. Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het handelsregister onder nummer 41055629.<= br>
The content of this message is intended solely for the addressee. No rights= can be derived from this message or its attachments. If you are not the in= tended recipient, we kindly request you to delete the message and inform th= e sender. It is strictly prohibited to disclose, copy or distribute this email or the information inside it, w= ithout a written consent from the sender. Radboud university medical center= is registered with the Dutch Chamber of Commerce trade register with numbe= r 41055629.

--000000000000d5bb2d059c1dbdef-- --000000000000d5bb2e059c1dbdf0 Content-Type: image/jpeg; name="1578829593090blob.jpg" Content-Disposition: inline; filename="1578829593090blob.jpg" Content-Transfer-Encoding: base64 Content-ID: <16fa549c1da9d92a9c21> X-Attachment-Id: 16fa549c1da9d92a9c21 iVBORw0KGgoAAAANSUhEUgAAAq4AAABgCAYAAADcgvDrAAAgAElEQVR4AexdB4AURdNFchBUMpKR rIAECZJBgkgOIgoKiIISJYqgiCg5Z0kHSBbJ+W5vyVGMKKhk/QyoiCLpbmfqf69me2/uPOD0FwGd WZpJ3dXVNX09b15XdycSb/Ms4FnAs4BnAc8CngU8C3gWuLYFoqOd+ytXitxxh0ju3CL584vkyydy 331euFE2oH2NjZMnl0TXfkreXc8CngU8C3gW8CzgWcCzgGcBiYpyjLB4sUgiwKd580T27hXx+0W2 bUtwsBHX3rpVuI8vnblv7pnzq8U38bj/M3FD8a+ih1tuQo81/+vIS0icWPnBVsKwY4d+HHjA1ftb 9CzgWcCzgGcBzwKeBTwLXM8ChnFdutQBrmFhIrt2iUREiERGXjPYrvuWzyc8N9fi25trlGviMp05 d+dn4nJ/NdlXix8N3d3p3fEScuzWLSo8XPM36YzcuOe8/qfyZbkZCF7BvHrA9XoV1bvvWcCzgGcB zwKeBTwLeBb4fwDXWOBt+3YRBrKuAHG8Z/YajwCNrGXwngK2YBr7GuDVJvNLIM24PDbpXXloPrin cpjP++9rXrHyj5MurhxzbtKoLOp78KDInj1/LI9LnqZhXOaL/Am0qSuvG3lGfmjPOAzU1wOu3t+h ZwHPAp4FPAt4FvAs4FkgARaIC1znzhXZvdsBVQBfChavsicoiwYjKQcOyJTu3eWBvHnl62XLxN65 UwIEZUhHFlL275eVQ4ZI9ZIlHaAG+c/Vry/FAdgOTJsmNoBhgPFMPkHAZ2FvARC2qFZNiiHuVwsW iLhka3zE4V7BIrrdL+O4X6tWsn38eHV50PyN3ATuKYv5/rxunQxu21ZKIO9vly/Xbn3NxyVH5cO1 YseECdL3iSfkEu9Bj1C8oH6hspm0vM5AwAs/2kQJeFReFM8CngU8C3gW8CzgWcCzwH/bAn8RuBK0 EpxZYAx/AsDLnjEjXGQTSaeGDRWoKqBDHHa1k7V8u2dPSZc6tQPUAPSqlCih8es89FAIuCo7GQR2 BMT2vn2yCoCXchk+nDlTQXVcMEo9AtDjN4DfhwoXVkB86r33JArXrjB/yHTLjgsizT2CZ+ZLnaMB KAnEWa4pffvKL2vXSjTyYVwNlIlwZcsWzedr5PcgAGjpggXlN6SnPtQrbl6hc4JWBg+4/rf//rzS exbwLOBZwLOAZwHPAn/CAn8RuBKAKSj94AOZ9tJLkjtLFln+xhuSIlkyOb9hgw6oInBTkIku9DkA f/dmyOAwrgCkD99/vzSpVEmB4Zfz54sNdwDD0hIYKpMLwEtg26hiRY13YPp0Ba7ueBqXbC1Y3xoP PihlAVy1e5+AkIPMkJd2+xNoEihiz/RuGQomcU1dApjm0CGhTsmSJnWA5ddfq3wyx24wqsd0D6Ar AfODvuWLFJFqAOXUh2VXkBvMNwRaoUPIZcADrn+isnpRPQt4FvAs4FnAs4Bngf+2Bf4KcAUQIyAj cAug675QzpwysmNHBXx3pUkjw59/XmwAOmUuyXgC0BG4Zk2f3gF4AHX358kjE7p0kWZVq8rj1auL AAAzvgGiBLIfzJghyZIkkb1Tpypb+/7bbytINKCTQFDBIcDpjokTJSWmlfrfihVioauejOnEbt1k wSuvKIA1rggKYukzC7BpAC3vWThf89ZbqvvkXr2kbtmyKu8FMMjdmjaVQU8/LWH9+oVkqTyA3Ild u8rUHj0kgPyY77eYVox6bKOrAvSKyw6HwCvBLIMHXP/bf39e6T0LeBbwLOBZwLOAZ4E/YYG/AlwJ GAkyAcwI0BJj/tfT8G21PvpI3nr2Wclyzz06oIrAVlnZuMAVzCWB6wiA3X1TpsgdcAP4HoDPxgCs UBoA2YYPPyw14Bd7afNmSZw4sQJZ+t8a4EqQqwAS8si0tqtbV+Tjj+Xixo0KhId16CB3A0hfZrc9 dGY6+t9+NGuW7J48OeSLGyC4BtCma0Cfli3lteeek2I4Jmiu+MAD0gB6vPvmm+qusHDgQIfJBWhl 2enCsGnUKAXClzZt0vw71KsnZQoVUpcJ6kc9Q4CVbCuDB1z/RCX1onoW8CzgWcCzgGcBzwL/OQvY tq1l5j4UrlwRG+DVXrRIp8Oyw8KuOTiLIExZ0SDYIzOpgPHDD9UN4Bf4u7KLfS3YSwJbgk6yr3EZ Vw7MeuWpp0SOHFEXgmEAi2Rd6TNqAcCegU8p3Q52YtCTAleAY/Vx5UAuAFCCP4JcMpa/rFkjKZCn b8wYZU6VucX13wAk6Ve7Gn6yNsAtZdN9gACVgJasrAJLMLCfo9z33Hmn/MCFGL78UnZNmiR3pkrl uAHQHQDuA5PB4BJk/44y/Ya8M951l/THQDD55BMF8mRXydz6x42T5NDn7OrVOhuC6kmw6g4ecP3P /f15BfYs4FnAs4BnAc8CngWuZwGCVRMsS4QMqwlBIKsiABRBH4okYFYBw1yeXLJEkga78i0woQpS 4QbQulYtKQdfT7KYvBafq0AJDGTi6H/r2DEZ0r69pE+bVgc1adc6AGz/J59Uv9ZoyP0eA5+YT1zg qqAT4HgzGE+CzItkPMGuElgr0wsGmG4IjeFLSx24SMCX77wj6QBaCSx3wb2ADCzv0R1AdYa8AIDs +uHDJU3KlPI7/HWjIU8HeeEefW6rw5e2CfxuSxUooL6sUQSsBPQE0gCnl1HmtADMm0aOVPAer7uA B1yvV3O9+54FPAt4FvAs4FnAs8B/wgJuQBoIiBCwXm07c0aE7Cl8UBW4zplzXcZVQSEA6uuYKopd 5RnTpZO7wVbSv/VuHKcEU3oHGNIjGOBE9pQDlWb36RPLx9Uwrja69n9H1z79Que9/LLYAJFRAJjZ M2WSSfAfJZv5DdwQyOLGBa7qrgAmdcOIEZIaIJOA0QBXBbUAve9jQBdB6v8wnZX96acysHVraVHV 8at9pk4dsQFufwcTexf0X4XBZer7CtZ0I2QSuLL7n4CX8jhF1nnEZVkJTM/jHmdVMIyqcQmgfZiW PrNketVeALQe43q1Suhd9yzgWcCzgGcBzwKeBf7bFnCDV1rit99EvvpKZNUqEYAyeewxEXTzC7q7 FbCSbWUITjmlk+PHAVsEZmQWCdYuACQS7LG7/z3IWzZokCwfPFiWvfaarEKXfZHcueWZ2rWdSfnB VMZ1FSDjOgAgUiftx/3WjzyiXfjskg8DiCbD+iNcAGyAT86hejXGlV3/2+BOQMb1HNwUCDIJJBnI DAeQnroMhb+rHD4sBTGQbAUA6gYwqgSgBMpL4Lea5e675SLic8orDqoiW0qZCoYhU90AMPjqBFjm DADnqVKkkPcxeIz6GUaVeTL/c2Cv6UbAwWXqkwvQGwu00q4e4/rf/vv0Su9ZwLOAZwHPAp4FPAsE LUDQalhWAEopU0YE4A00aGyQasAq9+XLO/cwcOlaCxAoSAPYm4sR9mQduSCAgk8wi2RWdWqoL76Q WRiZT9bx7Pr1YqPrn4yrDtoCsGM8Alf1cYUsMpkn4WOrc7Ui/5Logu/erJl24RPwfY+ZAuJjXJXh BIhmNz79YZe9/rpYLoZTmU7kPa5zZymcK5cujkCwehbA8jewvJT5WViY1IZ9ujRpIgL2Vd0NICMW cGUeBJ9BvZ+qWVP6YbEBTu8VxRkMCOYBWpmfhTgE8ZkxQI3l4lyvhomNBV494Or9uXoW8CzgWcCz gGcBzwKeBWABAlfjIoBR8bEYVYzOF7CZgq55vQ7mUJYuFTE+rgByVwOuhnGlX2ierFmlR/PmOvCK 3ekEtAwEb/T5jAJgI+vIkf0CP9aZvXtLDnT/6xKnAIb0D321TRsdkKWsJpjTysWLS4WiRSUz2M+T ixeLDVDIwVcErmQ4zQIEZFIJAqkP8+Tgr5bwZS2ZP7+CS+rAe4xHGScAinMi71Y1akj9ChV0gJaN /DhrAedc5SIDR+H7ynIZX9bNYFwJcqmb+q4C1LIs1I2rc3Hqq6wAp71gAzM4Swd/YZAa/WDJIBOw qy6IHwu08twDrqio3uZZwLOAZwHPAp4FPAv89yxAoOoOliVy6ZJjB7KgHB0PdjEEYAlcybJmziyC wUe6LVzoXLvG4CxdFADy3oU7ANnRH+F2QGBIttENzAjWBACOrGla5H0FAI6LFJDh1HlLIYMLFhD4 GpaTQJJzsVJusypVdFBTFGcBgHy6CvC6LkAA/1NlfYNg0MwKwC58xuFKW5TJtASvqguALYEk73Pe Vc52wGVmuQwtrz1arlxozlWND2BN/1Teo/8tdVszdKieb4OOBPZ0EeDMA4yzHq4SVnCQ17pgvC9h TwJh1Y8gNahvaO8B1//e36lXYs8CngU8C3gW8CzgWQAWMKCVLCuD2b7/XgRTOAFdxbgJGNBKJpYr QnHjLAMAfhrvGoyrgjAAvrUAZ5O7d1dQaRkAFgRmIVYWg7IIbAeCVf0VbO4hDPoagYUJlHHFqH1O 2h8BX1i6FqhcdscDbA5u106OgSE1oI9AlytxDcZAMAJYAlnN05WfAaejOnVSIOkLTv7P+VmVdUV+ nyJ/DibjfLPCAWOQy2Vcee0QymxW7lI2F4DzqwUL5E3MSauMLuKPhuwFAwaEFiCwwPTSv3Y6lrKd hrLQjeAIWGL64nKWBM5UQL1ojxBYdYNXYzfoIXCbwBPyNs8CngU8C3gW8CzgWcCzwL/UAgasck+w SvBptpMnRQim0K0tDRqIwMdTQalxD8BUU/LDD07sixedvQGu12BcFYCRXQXYJFC7KigjQCMwIygD 26pgFYBTfWENYAOrGcslwQA8AD6CUzO1lMoBqCUQVHkmngsEUg8FnACofVG2JPDl/QC+smRF9Tp1 DjKiIRmUY+S68zO6G33NOcob75KvYG/J8H44e7YkB2jtBd9XgR4KmOPRNQRieY/BA66m1np7zwKe BTwLeBbwLOBZ4F9lATdYNYDVsmKKSBDF1aPoGsBlVAmKuGGRAXULIPNK1tNsbsCbAOBqgCpBmTKR AHXxDT4y8ciMGtbRDF4ywI3pFVRSRhDgcc/4xvUg7nX3uZHjvqbp4KKwCV33H5oR/QStyIP3VHYw L16LLz8jz607y0h9Q2WGDMbj9ctgiQMAuR9hNgbOVEAXCaY1csze6BvaUw8GD7ia2ujtPQt4FvAs 4FnAs4BngX+VBQxwJeDksdnIXj76qEj69CJcyYld4WYjaGVcDr7iHK3cmJ6BW1SUs+cALQLb6zGu AGsh8HWLHBtwyD3BJbvwlWENgtYbri/zIUOLDwcFtwSksI3RK978/wBc+Ty94NnAqwO3Vx1wmk/v f88CngU8C3gWMBYwAJV7ugOYc97ngCr6qmJaJuGSqXQRMJsbnLrT8Nicc29cDAxwDQvTrm4hADTg 6jbZEygy0GeWDCv1V/B4A/U38pmfGYhlrl3TftSPge4KWP42kVjmyXl7zwKeBW4LC5i/WX5seJtn Ac8CngX+yxYw4NLsDbg0NmG3/v33i2BuUh18dfy4ueMAUcPImvS8y2sG+Lqvm2sGuN6GjGu8jKbf L7f0dQOmPVeBmLrrHXkWuNUtYGu3yK2upaefZwHPAp4F/kELGFBp4WveDVh//VXkzTdF8uQRyZFD ZNSomCmvqB7jMg03ykjoZvIgGOaMAxhNz0FI6nvJ7m8v3Bgb0J2DAQO5pGBBMK4P44nlRsiCkA0h qxc8G3h14FarA3Y2NK7Z8VzyIoxFwGZH/4kG10ni/e9ZwLOAZ4Hb3wJXA6xcqhVLqUo2gBnMfaqA 1cwEwFL/VcBqLEYfV+bNaaLo44rVriRNGhGuiuWFG28D2hp2588BqzWxr4RQ2QueDbw6cKvVAbsS Gss6eC5pEbC6HzfrSpAxcE69/z0LeBbwLPDvtYABq9wHu/JDn+5YNlVeeUXk3ntFSpcWWb06ZiAV LULA6k7/V61ElpZyCJCxLKsO7uKUTi1beuGfsgFW5EokifEE2yEcQwDjLZhG7M8G+wN0ZCL8mXR/ Jc2fke/Fjf853ii73yi5CXmOf2fef6eshOie0DjWfjSYp/BM+YEZBK52VKjZxkVv8yzgWcCzwL/U AgZ0ErCaLn4U1SJgfeoph/l88EGRlStjG8AAVl6lDG/7V1jAYVzxsSCY0kw2IURcO9gRAKkM4bYE NgckenO0WFssPY7aFKXHvGfiUZ455nXGN/F4bNIbmdfL37t/7efjto/b7oEtAYna7DwfY/fQc+Lz QmBaPlM+HxNCz8f1TGPJDcanfJW7yakP5nlyT7lGPusKZZtzs3frfa1jd97M73p1ScvtKo8plxUO IBjUizKNXoxv0vBaqBxB+/Aa89W0wb8DI8ddLiPD5Mc0vMbymjJcq5xx79mbYEfMKa29Ih5whSG8 zbOAZ4F/swVsA1a5J2BlMBsn9ccqUzYXDcBSqTqlk7lHYMu47vTm3v9375ZJUOyFm2IDB7i2wtPk SzEcwR9/sCPxwkXgfctnaVCG9kPERx0KHcN3NhCBF3QwbmjvC6Y/gLgmDfMkwwuf5ugIVAI/6po/ Jp+r6eJdh81gq2sFY3c+Kz4P/TCh3Xcj8BnQ7n7nWYXkROIapnTTex9hz8BnFOeZMj7lU7Y+d8Zj HXgfgXnsdJ4nn6WJq3vUAT5rlYlZLYT5+R1Z3F8vmDLZCaxLKh+6xyqPKRf0oDyG6HDUPeis5WX5 GRiP9RL3TL7iwzXKo/2CuqvOPGZ5aKttCCYebWzy4zFsFPrb8Se83MxDAf7HkFEZwQOuMIK3eRbw LPCvtICN94QJBIbubfNmkYcxMCcxuooBWK2P2SgGN8u6cYDV5OHtbwkLJBy4BkGIFYHKwZc8GNo1 w9ZItybdpEqJKtKkUhMZ8vwQ+XLBl3ov4IsBrwpw+ELHi3vRq4ukf6v+UqNUDencuLOM7jJaTi8/ raBHAZYf8a4TDOC4Vrz44sR3LT4ZCYkXX5z4rl1Nftzr10p7rXtx5fCc8blXuxMoAmhtGbNF+rTs I1UerCLt67aXyT0ny2XfZQWetLvGxXNd89YaeaPdG9L/yf7Sr1U/mdlrphxZdMQBqABnqguAowI1 1IFVb66SV556RR4p84g8X/95GdppqBxddFSfJ2UaXbQ+7LLl87mfy4iOI+Tc2nNibwP4jbSu+7xj lYn1D4MLCcAXDFggL7d6WaqXqi5dmnSRsV3HyjfvfaPljQqPUpC5d+peGdphqNY5lofx+7bqKycW nxB7B3oNUE8JbI8uPCqvtX1NHi33qDR4uIG8/uzrcnop6iXuUUeNhzwPvn1Qpr80XXUIPRfU7XPr zsmoTqPkzMozCnx3T97t5Bu04+hOo+WD2RDGDweCZtoQzyihwQOusJW3eRbwLPDvtoALsKKFdDaC 13Xr0NtUSSRjRpH+/UUOH9Z7Gof3DcNq0nj7f7UFEgxc+YJVYAnw+dmCzxSslixQUt56/i3Z8/Ye Wf7Gcnnp8Zck/Z3ppUeLHgoeon3oHiWABUA4t+mclC1SVh4q9JCM6TpGds3YJe+89o40r9ZcstyT Rd7u/bYCXgJjA3bMnvkquAKAICChTDK0DCHwAP0IlHiNcc096s04eh3p9J6LRTPpyQ4yvVs+4/I+ r3F/NfkENiadWz6v8R51MHqZeDw3wM7oxj2D6mQ+FIJl0jjQx5TH6M3z+ILK3mnL6fdOS62Hakml YpVkSt8psvPtnbJq+Cpp+2hbKZK7iCx7A6MjAUAvbwaIBWNY6YFKUjBHQRn43EB5uc3L8sxjz8h9 994nrWu3lgvhF8Tyg23fasmVrVekVpla8kCeB2RYp2Gya/ouWfrGUnmq1lOS6a5MMqLTCAVw7jLa e21pVLERBgUmkjl952h+V7Zcic1eXqU8LKN+NAH0nd1wVkoXKi3lCpeTsd3Gal2a9+o8aVqlqdal 2S/PdgAiytPr8V6SKnkqGdhhoILxAU8NUKB9YtEJsXYAkG4NSOdmneW+bPfJoPaDZNfkXbJj0g7p 36a/5MuaT3q36q1AU/UE7hzZcaSkS51O5bMe8nnzQ+7YomNarg9ngnJGm9qjWQ9JnSK1vNrhVenf ur+82OxFtVX1ktXl5PKTTt5IH9+zi++aB1xRz73Ns4BngX+fBQhWuVkWXpQxDKvF48mTnems6BLQ r5/Izz87cfl/AO0n0zC9kRFz1zv6F1sgwcCVL2hrpyUnlp+Qu++8W5kr7X7GyzzkKgDW/sjiI5Ix XUbp2aKnw3z5ouSS/5IUy1tMGlRooNe065bMU9BtYPf03frSX/b6MiG4MeBNX+A+xGPXLQCzMm3s euU5u6WRPtRtHIlzMsGUCSCm98GEKbAg20s9eZ33eexHnQco1DxwrPHITsaVD8CqstgVfDX5ZADZ Re6ST2Cp6XiPujFf6s143FMH3vMHj5kWQItplI1DGpXBrulgWZnO6Hwt4EqwTHAZtS1K7s1wrzKs 9h7oQ/m0OwfhoZyrh69Wu4ePDXfsCx1rlKyhYE9ANqrOiHfqvVNyV5q7ZHDbwapL9PZoqVysslS8 v6JYu2BDlskl99CCQ5I0SVKZ0mOK2uRK+BWxAaKPLjgqebPllVdbv6ogLmqH8xFiwL15FvHtTZku RF6QIrmKSLNK6C+nXWhHV13aPmW7lund198V+UKkd8veCsblOOKx/NSVz9iPgLRt67ZVgPq/tf9z rrOeMSDOiRUnJOvdWaV7s+5OXrDb5O6TJV+2fMrmqk6sQ6g3J5eclJTJU8qncz4V+Rz5Pt5bbaT5 Uk/ke3HrRSlxXwlpWKGhcLBVLDcEP+JcI3jAFfbxNs8CngX+PRaw8U7i5gKseoVzsE6ZInbevDpn p0yYIPLTT05c/k9A6wHWGHv8B48SBFwJkggmCRQeK/eYlC5YWgTvZzJOyiri5U3gp6wdwA+7ismq sVtVDokMenqQ5M+eX4FDdGS0kL0iAKNM9S8EICBTtWcyEAPAnAFllE9Qsm7YOtkwfIP8uOpHBcxk BZtVbibL3gRbiPsKfAAqKYNM3vrR6+WRUo/IrklAfQAMv238TcZ2HitVS1SV+uXry6guo5yubuRF PRS0QoeTS0+q/IoPVFT5K4atUF3GvjhWzm84r6Bkdp/Zsn6USz7A+g8rfpDXnnktJH9MtzEKQiZ1 m6SAhoBk6ktTJXJcpLz29GtSrUQ1eaHRC3JmzRmJ8kfJuK7jpGrxqvLso8/KwkELQ6CITPWn8z+V dnXbSYsqLWTHNCAkAFwdWEQwzhCJAPkm6LMKd57Viw3B8uV9QAEaGeU/PKvPRMZ3Hq8M6bmN59RW 1O25x56TqPej5OLGi3Jp0yURlJEuAxnuyiD2J7Z2lWe8K6PY6Ppnd795nrRj1BZ00UPHw/MOy9bx W/U+8yVoZDnqlq2rstOnTS/rh64Xe3+wbrnKYMpi9iyTkUHGlEwxQefV6tLBGQdlx0TYCnWU7hGl 8peSS7suye8bfpeLmy7qs7T2WlqnUqVIJd+s+EZ1Zv1lfWDQcqO+f7HgC0meLLn4x0NBAFLaK3eW 3KF6x7j8oCFwJVg3wJVMb5mCZSRqLz7cYMNLm2FH1LGPZ30sie5IJD+tQkOM+qd1/BplD9mAg8Pw HDwfV9jA2zwLeBa4PS1AsGoCGVOCULN9951Y3bqJ3HmnSKFCYs2ebe44e8Y1abn3tv+sBRIEXPXl DJDEFz+7SQlIAnsc0GpAptmbLtUaD9ZQ0GB/aUuBHAVkao+pYh90QA5fxoxvXsoKHA3TFYlngfsM KgvA85nazyjjVyhnIenctLOsfGulTHppkgISdr3+vuV3nY6L4IqA+e40d2sX76nVp+T9Oe9Lzsw5 pVlVAN0hy2Rm35lSvkh5KVWwlPy0/icJ+PHHA6C1dsRayXR3JunavKusGrpKJvaYqPJbVmupMglM Fg5YGK/8ezPeK40rNVb5M/rNkIcKPqTAl7psHLFRAQqPCZIGtx8sO2bskEfLPiol8pWQ2g/VFtpq +dDlMr3fdGXz2N0e2AmGe7sl+e/NrwzowiFO3hFjI8T+3JaXmr8kHR7r4DCg/KgI2kyfFY5Zrsx3 Z9b8rX2OKwPj6HMCiCXYpysHwRPjrXlzjciXwEVgUjs26Cj2h7aCPAI966Al016aJrS/fdiWCkUr KADnR4E+IyM3+Ey1S59McZAhtrfacjn8sjL1O8bvEOuIJS82elFql6kd0t9dH0xZzJ5lIsAja8y6 xI8H1iUFycG8TdxQXQJuJbgl48rnLUdxjo8qZV3xvMmoNq3cVJ6t96wCQv3o8gftg3JQnyub4cYA sNisSjN5uvbTIidExrw45vrA9bBojwPdYuwDKDsAMYFrYHdADkw7IPekvUd+3fCr0C7meRn9r7b/ NzCuNv7kvXBzbYCaf9tt+Gv0fjfZAn9LpTF//ASsDGb79luR7t1F7rlH7JIlRbiMKjY0F84fCwGr ZcX84fD6zd5MWbx9zHP5B22RIOCqbCte9hFjIoRMGV/EZPAUBEU6bBgBg77s0S1sfWDJq0+/ql20 F8Mvqq/fx7M/VoZOAQjS8AVt0vOY1w37xOtkEpVlA+tF1ozAb+UbK9V/ULva2e0LIFIoRyHpUA8A DqBrbr+5kiZlGtk7DYgJ7Bi7tHNlyqW+jYLxRZqO4OUTALTileWx8o8py/j9mu/VN3fRgEXwdQjG o3yIIbtMJo1s7/LXl6v8fdNhDJd8soDslg7JByiqV76eJL4jseydAiEAUWTthrQf4sQDS0zQVzRP UcmWPpsCZ+2+B0NI1jdJ4iTy48of5cjcI1hVLonaiXotfW2pfDILyoMpJTtL1lmZRxdwVRtC/kez PpI7U92pbLC93QGqalc/8kbgsTKwAKVkpwkk5Th8XOELy0FWtJG6Phg7A7QOf264sob8ePGN8alb h3nulGnkup8n87Dft2VMpzFSMj8aJYBJMvdkHOl7emTeEadeoP4YGXH3BHdkn79Z/o2kSZVGB3iR 7dXrqIcmX1M+2kAZTuQ1sPVAyZU5l0x9eYH8c0cAACAASURBVKpM6jpJJnebLHNfnqtMMD9oFryy QKwDDvtv0ht5rPcE7XQPoJ8v7T6hy4QEAVfDuKo7A4Ey6x3SN6/SXBpXbKx2UNsE/xbiljnuuQdc b0r7+K8C2nz3c7PxJ3M7bISr3NAHgiPvdzMt8JfrCyubCQSgboZ1HxrGVq2cAVc1auA9CVLDnZFh WHntVqm0Rg83kDbl8/Yxz/oG2yJBwFVfsOjSZZd92tRptSs75J8JUKY+g6iDBBJkqQhcB7cbrKDv wroLCjo/m/vZH4ArX84GLHBPFtB9jfkS4NEPkQNxCKYImgmWTNerb6xPgd7v23+XWb1nSY5MORRw Re2OksUDFiu7dcV/RaIiMTcp5DG9tdtS8EMw/OO6H2Vi14mS7958ysaRQSRgUfkoE7ucGY+jxee9 PE+yZ8zuyN8TJQS66dOllz/Ih9/nl+98qYB3+wRQmvhH/0ceR++OVuba+tCSZx97VgcrGXZT3SbA VObMlFPeeeUdubj3omRNn1U/AL5b9526XbBbmj6wLIub7aTdGKg7mcl90/ZJimQp5KfVP4kBriYO 93xW+lyxcESt0rWkbZ22Iicw08gDD+tsD7/6fpVhzw3Tkfql7islVR+sKhd8F+TihouSLEky2TZ+ 2zWBK59n6GME2L1A9gL6AbJ3/l7ZOWGn7A/br8+KjCjBrOqCNG4dzbGyqCj3sYXH5I477tCZK0LA 1ZXGXZcub7msz3PQM4MkQ7oM0q5hO2VNn67ztLzU4iWtaxxEtvjVxcqKqt1cspi3XgOzS7ZZPzDg 9sK6oq4CeE6sr7QjnwlnKXC7CtDHu2zhsvq8R78wWsZ1Hyd1HqqjrPXRxUe9wVnibZ4F/oIFHCz7 FxJ6Sf5RC9guwEp2ledmI2B9DKQRB1xVqwa3PQ4gcTabcQ1gNTLMTW/vWSBogQQBV305A3x9t/w7 BW7t67XXQSZlCpdxupbrd5RNIzcp4xiIRMUDECGrxOmuAu8HtJt/+eDlEtjnuBcYQGKAhsr3QyMA ALfPJsEMQTG7acmORh/EhPO4RraXaehf+fPqnyVxosRyetFp7con0GM3uf2RLT2a95ByRQB4wRoa YMI8NT1AB0d975+6XzrU7yANKzaU6A8c+dRP5YOpJNN6R6I75Nvl3yqYJIDhSHSCze7Nu0v5ouUd +VtiZjigfIKtNCnSKEtNxpUgcvPIzQp6CYqZni4B9Pnkak1aVuYL9wB23c/qM0uB+kdhH0mdcnXU /aFjo44S2AFmGjY2tnPby+jNqaoubLqgcjgtE7uoWX633ZlerwGAsft9/svzRb6SEOMa/XG0uinc lfouWTkSTDfKwK7tK9uvSJ6seWRK9ylivQ/wS59W6K12hUw9BrDWvOBewsF2W0ZuUeBeo0wNHdBF H+JKxSvJw/c/rP61v6z/RZ+lqQeUpfaHHc0xB5v9uvlX/RDhlF2sSwr0kbfJn3uVwXaQAfWQg6TU VeA4zsH08kNI2W3UCbppcHos2t/9EWDKwrLxOXVq0Emne7OPgzl+YYwyuByURuBqQPXxxcf1A+qT 2fi6CroKlCpQSuzPbHm86uP68TO973S5FHnJsWXQRsyLAJ97dznUfn7oGgy3M+PKdxG3QwD+xYqJ 5MsnkiePF/4pG9De999vy/LlznOIjkZduw02jIBQLSfLZCmCXz788th5xPv9MxagvUvi9x1+3Mh8 X3ezUbdMMADUJFqyBI1ubZH06UWee07k1Clzx3EdMACX6W/VzTRm+zFggSt15c/vNWT/VENm8rn/ fiz5mgg1BGy9+v6FY+//Y9CXK4AYQQj9G8lgHV58WA69c0j2TNsjA9oOUJBEEMbu+c/nfa4v6i2j tmjXOLu1qxSvoowhR5gbEEmQoYANgJV5fL3sawVHPGbQewAaz9R5RujLahhXAgaCisCugBAoEFie 3XRWXQWyZUDXOwATQQq7hdlNbO8GMEG+BBnMO3pbtHahk707teyUzlvKqb2YRhlZ6EUgQ/mfhX2m ZeEArPn95+sofWWbg/LJvoXkA4BQZ8o/s+KMJE+aXLaOA4La7jCu4aNhYHxsKpsLQN6mdhudN5Rg ygBXxuX0YGF9wxR4qfsB0mydtFXBL7uqtduZwIxsdySCPybQbgpIoV/t0rWFDCPdGpSpDgIkxuE5 gR2BOxnU/y3/n/pzVi2BQWJggumacHTJUWV8N47cqLa5sOGCAr/X2rwmRXMX1fhqz3AHtOtz4ccG ysBnwCmiWDY+O7p7sKtcdYYrg07kDx0L5Sokb/d8W+sfbUDd9PkxTrBs7rpAZviR0o+oLMOO8767 LvH4+KLj+tGjg7MAIM0gKaah3y6f9fQe00XrC9ogfuyYUf6aH0ErPoz4McVZNOhSQHcUuhvoQEOw yNSXdSqwLaD2I6vOeWppb7oK6CBGlP9y5GVn2jAw2PSZvbwJtvc75dPysqywlx7zejzhdgaufH9x 241yovNCOnbEdGE9RDgOwws31gZdu4ou4Z42rSUvveQ8hytXLOfgFv//ilxRDRtLY8mO30D8uthd pJv3u6EW6CpdpRd+T+FHgHASP25o6XQf73822kpu3Js/eOeKyOLF/HISSZcOPm54t5w4Ye78AbDq alkxd2+9oyi837i9847TmLVujca+lwj/0LzG7MbbgC+ONGkSBlz5IuULmt2zXyz8QgHUOwPw4MAs qS8kmJTzkeelVc1WUqdMHWU5W9ZoqSCN7OR3q79TxlB9PPHi1umGCLwACghszm4+K4VzFtYBXAR2 BtgqmAMz1q1pN2Wzvlr4lb74FdiAKSS4qleuno7SJ6hgly6BKsGRtc2SM+vOKKu6eCD+cL5AfAJa 5ot0r7Z5Ve7PjT8myGeZCH7Zha1lYhyCCQAQDsyhqwCZ3Xf6v6Pd+HHlLxmIL0kjH3lTPtlepts3 FQVCvvS9VeAKwKPAFeUmIFc/WwDIuMB11ZBVsm7kOnmh4QtqRzku6stLH1SO7P9m2Tfyv3cBNuMB PGTwOEfptyu/lZTJUsqM3jN0hL2WyQ/9qCPyP/neSfVZ5sA5ZSEB4GqWqql5clARr3HBCPrcHn8X CuzBs8GArl/Df5V709+rz0XdRFAmtSvloixkZTminnOe/rD6B60vxxceV50IDgks2ZVP31J+XGjX O2TzOuvLuQ3n5P2335dofwyLrWUCG/3Nym8kbaq0Mvz54U7dQzoFeqxL+Bj4ceOP6pYwrcc0BZoE ruyyJ9jXOhzpfBSxHPY+W1nfppWaOh9uKK+Wg/UE8VkXHyn5iLLitAWB7PElxyV1ytTqGkAbBsLR mON5v93rbc2XjDlt0PeJvsr0Mg/a/ZO5n2h90I8ApIsOMvR8fh/N/EjOrj6rz5LgX8vjR/6ucDsD 10DwfbcX9SRZMhQTZeaCNwfxt/cBbOWFG2MD2vcA6vFx/OkWKWJL376oU9iiolAnb4MNzl2qZQtp ITXwO4Xffms//ry83420wPv4qv8Mv/fwS47faZ0bEe0zfrE2glQTLNxzA9bff3fmYGUXS86cIqNH Y5WWczHJGZdpTHrub4fNlHHZMmf1LnZjfAZG5n0wIddpyOzgfRt/mFaw8eO10HXXfcYx8kz8uPHM fe5D94KyQ+dBme64seK7014lbty0cc/decXS+yryYsUPxjHX4soOndMeDB/hJY8ZJxLEuIofNSrS efHzJbxl3BYFiI0qNRJOGfXtu9/KqRWndN5OgjUG+mhe3nrZAWTBFzeZKwK1rVO2yrnN5+TzBZ/L sI7DJEfGHA4zCPDBF7dhngxw5WTuBH6cJH7R4EVy6t1TcmDmAXm61tPKmJE1JZgb32W8DkgiINa0 aLQXDFygfrkjXhwhx5cel29WfSNDnh2i7gufzvtUu+bJvnFKKg48m9hrok7av3/mfmlds7UCMHbz Eyiy+556kC008gng6fdL+ceWHpND8w/pVFcP5n9Q7RA+CiwrGEjahFN6EQwp44cXNyfM5yAxAi7T VU1QSaaW9jux7ISm2zZxmxxecljSpUqnI+rlmEjDhxs684QibQj08jkFA0Ea2dqI8RHKEnMBgT2z 9uhCEMfePSYTumOQUebc0ucJMKGIpz6hABEEnG1qtdEPBGVYIZ+DtfJkySM/b/5ZfYU5J+uJd0+o XOofPj5cOJ3WV0u+kvFdx+u8qI9VeExltKzeMgTO3YwmQaq6eqyHqwcGsXFqLP2gwbMgc8+Vpjio y6RhubRMAKpcgYouDHTv2D51u9Ylsv9cDCN7huzS/rH26tdLu3JFLQ7g4zM2oJmymD9B5pm1Z3Rh jOL5isvakWt1Bayza8/KiqEr1B2mconKWjZ+CKmdAWD5MUGXkd0zd8t533mZN3CelmHZYMxDDHaf H0NdGnfRjzEeX9p4CUo74JbP9tDCQwrQCY4532yZQmXk8g74brtdQILP0TzPfwtw5UqNq1ahmqJ8 4fjTiIj450M4phYzISLCvik6/BPlpn03b8b3J+ps/vy29MGfOrfbDbg2l+ZSEb+D+G2yN0mE97uh FtgiW/DK2i6z8UuKX7zA1QBOgk8D5li5OAfr4ME6Q4BkyoQVW0bihXeRd5zNAFae3S5gNai67kxZ ly51GNfZs/F+xwt+y5YENWQ2/ygjAabQAOpx3IbA3GccHptzE5/ncdMEz1Wez+c0rtxfJa4djG9B 5wD1vkbcq+VlrhtZATQ0lKcN+1X0M2l0T92QL/PXdEhjZMWKZ2QxPgPtAt+nhANXPx4bgoIHgK/z W84LR9MTZHDaHzKfjas2lg0jN8iGERv0/L3B7yko0mmFAF45EIoDY7g8bOmipXUgUMtHWupUVHyJ u0Grdtey2xnsFIEUgdq2qdt0BHzhXIV1hHqPlj0UeJC1UkAN1wTOQUqgyPSqK/IlyH282uM6pynn AGX+p5edDs2X+tv63+S3zb/J7im7pX7Z+lIwZ0EFLU/We1IHWdE14uc1P+uAJJ3BAOAyJB9A6sAM R/79ee9XQE//Xg7mIqPKeTup3xM1nnCOAXoVpOJlMqHrBHnz2TcVzGr3Pm2MuO0fbe/4xgLsTOk1 RQdn0UVjYLuBOncp2T+CdJNWy8m0wWCAv3lWP679UWd5YLlLFSml7gnt67fXOWIJ6AjiTFzOMzu9 53RlW6MisPIXFzLAc6D9t4xAxQTIVb9WlEPrQOsBOsCs3APlpFzRctK0WlPhQhLKUGImAIJezqfL AWMhPVH3Qh9CKAuZWQ4Esw/ZsnrIap1tIAoLV9Cn1iyNGqtMsPkPa3+Qbs266bNkmeg326pWK51j l2VSkIl6SvcOdVNAGuZPOUYWy63sMz506K7QtGpTlUO3lmbVmunyt/zQ4DMxC10oI4qyj+48WqoU qyKlCpfSwW3rhq/T56i2QRoO5CPrSjBOtljLjmPaY2KXic4HTORF4Xy4nOWAwDa+D5DQM72N53F1 M66YJEPWrnXa+mD7rW2dH3XXHSLxnBh4LQLuPeGog5H4qOW5uW7ix8QlCDVxnbTuezzmfR+eB2Ux mHM//Klj4jp5xJcn4xgdeD9uiEAd8/mo5x/lGd3+mCY6JNPEcedj8nP2VtAWMXoYO8Td075s90lq FChwmwNXuyK8bD6WLdYWibQjNfjFH9rz2G/r/6H7jPeHOHrFiWf+d8dzyzb3Q/u/KD+UPp683fdU D+TBfUQgQiKtYDmD10zcq+nrvs64PHdfi3tu5Jm4Zh9hR8gue5fMxS+JnSQGuNoBNIS2EywrNmA9 c0bkjTdE7r0XU/GUFgkLw4vOcfUQbgR8Ji33t+sWF7hy6i76QPl8on/Efv9V93ZkJN5pWzH+ZJP8 wkYQXU+8xnR6j8e4/9v69SBQ8D4JyuL5j/zax71QvDj5qBzcjwK4Y1zujVwjx31usWEg4MZXbTSO 7aAO7rgJPbZ9PrzP8NLbA2KM5XKVKT4ZWgbkx3z1qxp6qD7X0oEyGdhdd999CQeuNhpsBsFz0Zcw 0pNNYvhl7S96nS9ffdHzZY/AF7GNBpxpdG5P2EnTAKxwuicFawCmjGtABeOafPRFjvucuJ7znrJL lnHPrjkrCiCYFjIVgKBMCkJw3/hGhvIFYKBuBKiqK4ANWVll8zAAi93ZGdJmUH9Z+Qby0W2rOuBv kaPIORiJgE0BMvfMy+8ELZdLPvPQMrKs1IV7xkeZQ8d+HPsQUN+VZeSxPxgYl+kIjn22MoXsvlZb wNaq19XSBmUwjrGhPivqwGcD3Wn3kO0AwNx2Vz1ZFuoV1MnIIRg0HwTUVW1u6gA+OuhKoX6zfCYo K++r/kEb6DHSGXmmXuh15onnQf3C+oXp9FM8JuAzZTF75h0qE+sf5LNMjMuPHJ7rfdqRAWXUZ8dj f0wweqierNcsH+SdW3tO64k+Q8gK3Q+mZTq1H/OGXZm3Pi+TL+PRdnHzRf5aVtYDPlvUu9NLTisj fH79eQXplGv0cuvK438L45pQ4OpHmRnYVtHFgL1EbGcjYX/nurM38bj3oc6x/YyJ68jgvQgASu55 jwwk3zUMBHXc836MbCddfHIogzpRF97/EHWOvVcMPGb+mNUH4DLaJc/Rld327vgmHa9TJmWzx5HB Aemxy+rO1+jB/dUC4/Pd8G8ArpWkEjpQPpJwOxzN4dY/ADK/+GNdYxy9hkaA++v9APE0zvXSJTTe 9fJz31dwaTv6R0RHaPn2oxHdgZ/P8sUqV1zwaWxh9DJy3efmOBTXdspqQK0fefNnzhl/N35h+Cnj ap9CA4S20A6gcQ0GCW5H8FJ+8kmR1KlFSpVyulPMPe7jAlYbgm7n7S8AVwM2Az6fgruamKs2E2ZU +HXjRgWyFq/7/Q7YRAPRuXFjLJRU3mmo0Ph1rF8f7mkp0eOLLhM0XgSlClSRxsimDAuNUg3IToO4 27jaGNIqOEQ8yjdpLDYKu3bJT8i/caVKGNQ+QH2KTFwTL27DYvIysniuuu/cKZvhClK+aFF5EIPV CM5NXI3DeAh6DXpoPmj0Fg8cCNKrovy4AT3R0Ef1cukZK3+k10byzwJXQdkZzIuVex2YAwZDARnu EQjyGoGDggemQX4mLV/M5r6mASBjGsYlkDFgxsRXZhKEZfOq6CoCoxb4IDgNFoEYZDOtgggc85wg Q8Fw8Jw6UiZBjV4n0EJaHjOukUHQ8maHN5Xpm9J3inDu2bPrzsqc/nNC/rz0VSR4vK585KHyg2U1 9uI1c2z21EsBF/Q111Qn6of05ph7tGYO0EaZeH61tBqX8RGMTMpi/pqX23awgdqddrqGXN6LT38j l/fcz9Mdl8/W2NrkYXQ056E4PugNkEIgaICuiWv2Jo151lrPXGUK1aVgeRhP47jsYWSZvSmfloN1 JPgMVRZtE/z4ihtfdUHe+ixQTt536xc3X5MP7aZ/F8yLABjP1v13YvJx729p4GqjTjJcZQvANNwI QBMKXCNhdx/+PtAmYnDRO9IazP5yDCDcARbfh2fq98PcwcA2jdfQ9smAAQsQ9xVZhoGeBJC8HoFn AzIAhEW09O49FTMbVJGsWfNKtmz5MCvPcxIW9omCRcpjfLS76GK/JE+j92EJFh4xcsx9ni9d+rU8 9dQr0gSuKI0adZbGjV+UlvCnHoP5jVes+F7BIuVQnkn3AqZFa4blg018J+2LGDQ1VXVneZ97bqg8 //wIBcZMSzs4trBUj8WLT6pe1I/yDQttbOHe0y63NHC9Rp1BdYGHK3rcsKmrQJBx3RQNV4EguDNA yy8xP14jQGMcBt6JL15Mipj7kVakhEeFXz2+7aSiPHe868l353WtY5/lQ8fjAdl8abMM3zBcVny/ As3hXjRH28Rn+1ylhM748Xp8tjD6qA0CQRsEyxYXvFIfytI0wfJtjtocm3G1TylgtSy082b78kvB H5ozQ0CTJiJr1pg7eBFbeFkhrnm+Zh8T49Y9oq7X0pfl4mZcBRLIuBKs2WgAN48YgRl2kks6DDAa 9Mwz+pVqgOgVdrXja7bdo49KNc5YwC9afAm3why3SdFw5suWTS5CjuX3453qE21YcKzpEW/d0KHq WpgYg8430UUD1wzzauIyXTTA3w9gdAvkyAFCsKz8D88uCnKuB1wpw0bgniCc8aMBlr9a6CyO1BX1 4KMFC/ReAPdMHG3MEI95a0DDFIAO3yLfeuXKYbBzdvkeTC314n2ja6w9GzOGvwpcBXprgAy+iHnM vfv4atfw9xErftw0IdnBPBRIgB3hSPrBbQcroAmBCVfecdPFOmee18iXOiigw0t1Zr+ZUrpAaSl+ X3FdHICrSHGVLgIpK8Jyyh3ULZTHdeSH4sVNl4Bzt33cx39Wpjstj93nf1ZWrPhBu/La/1eu0YnP QoEvwKJec+URX94mX5Pe7GPFvZ6tkYdJZ+SZMpm645YXN6773B3vasfu+NorkYC6fMsBV9uG0RC4 cc8GnQjVspxz1/2/AlwJ2tilTna0NGaRoI/4o3Ch2YcPSF6PjLRD7RoBHwHtO5g72fjYT5q0U4Hy FswOQUD79tt7JTfchO7FQhIt4WLUo8d46QJ3m7Jla0sq+I4/+ugzAHkXITNa28a18HOmrHHj/CqH Xfh+P4FgtILgCROc+Z2LwoWnOPy8i2HQ5IMPVsXiP1kwAC0l5lXvDfD7K2RZCl6pYwpMj0ewXKpU ZXkAH+IlSlRFusryBFxKCKy3YMaLtFhVjfkSrJPRpf4mXwL/sWP9en8ternI+lIu78cX2M7j/XFr Ma7uOsOKgVHa9lXqjRu4VoiqIEfxa9G3hWTOmVkm7piooM6AU7/4xRfwyU57pyz7eplkzpVZHm70 MDpydsawljZAmh2p8RiXxwzslt+D35Q9UyR7weyy8feNCn4VzEGuScO8ttnbZM0vayT7fdllxocz lJl0y+IxAaiR7ZbhvqauAMibehv5BKmdRnWSXEVzSflHy0vBhwpKzSdqSvg5sMzRW1WuH2Vg2t32 bpnxwQzJkC2DvDTtJdlv7w8BdYJq+gPXbV9XGr3YCB2VR2T4+uFqt3ZvtFNwHB7tAHTVCaCWOtN2 ZeuWlUw5M8m679bJAvySR8FVwDop/Eu3EATd3EI2kDMENGvmjLLkdW4WYvBZmr9986ydu7fu/249 qT/bMgaWJ25Z/iRwNcxjNLvuAUrrAig+BwZ1EVjOTHfdhRUyd0og0mEuFWSCce2AOW5rkr1m4wfw +hjs/Xj16pjJJ7e8R/9hXHODTJWNxoIg9Jk6dRTgrn7zTU3vjkddCCj5lV4JszxU5sC5Tz9VFwTt doIu2u3v9+N9GKkglekJQNnAGNDKe0EmAAOgv8Qy6J0x0D23yMmTWkaVwcaKXVnI61eA5J/5YcNG DtcsyNM4BKHIv1qJEpitqqjGpX7GZrEaNebJ8P8Grn7Uw38iwGbadc3uZOj9d+ZpAARlWj4LhoN8 5PPDyh/UR1W7gFF3QsyZAVOI/3fq4cny7Hm9OnDLAVc8sqtubPANkEXDH+C8odjvhZ9zksR2gn1c CRLZdpfHgM78GOxIUEg2czvcLAjYCF4ZCO7YBd8C/vPZs+fHNJFZZQIW+yBgJaCdN8+Z0q4xBsyx K5+AkIFd8kw3b97HkhSD5qrBD54khx9/5+vWnQOgvVMmwT+b7a0BiNzznNd5n+0oZ0igLMrcvPki WNf1eK9nhitWCdwn8HSY07vgzzwS812jrddyGT3YxrNNpmzqX7FiI0mMUWxhYR+jnY/xw2W+Eyc6 +a5bR1DMdBbkU+c/Bsrke+q2cRUwgCEIfqJs+Eii6jS3m0n5K+XlOH6PtHU+Yko/Ulp2BXY5vqC2 A0AJ2MhYNunaRMF9kXJF4LHjxPFZPgV2iIlmfZ8CVT/+6AgCCeJ4bWzkWEl0RyJZ/9t6BagmDePx PmWR5VzxwwqVP3nP5BB4phzGI/hkNzsBIYGuAkPkyXv8MR4HPtEVwDDDzJ/As/fM3pIydUqZfWC2 As/Ic5FSoWEFqdq8Kl5N74fKyvg8r/lkTcmSN4sUrVBUdloA6ADNzG/LlS3wmvpQHqrzkFRqUkmO 4jdgwQDVOXXa1PLu6Xdlu7U9BghDz332Phm61mHsEiXGKpUnV8oiANdEkkROyI/4ggLoqfiw6ICr Dh0wTconMX/+rr/1ENCLuXt7HNmoaPFtvG7KZ1n6oaVl5Jy0+MDU5WkJ0Hw+ifeP0O9X4GcDFH6B KbTIhn4xf75ciIhQFnXxq6+KjUaOADEqyLiGgCsbIzQsBLF9scLYW+3bK0tqoSEgmDRA1EZD9+HM mZgZKZF8Ons2ptO8R9a+9ZYyrga4Ujcek/XdOXEiepeTy/fwhQ2g+4gs7pOPPCLLBg1ywC5BNuIr QKUOKB+BpuaHPRvAbk2byiAwxk/UqoWByukx008qKVOkCMYSVdN8uN8AdplluRP3yDKXwWwAB2bM 0K43ZWSRbwBf3z8C1KZOkUK2jx+v+rl1DtmUjRnD7QBcDbAkC8cgfrRjkahI2P/dgd3BZPoUwKIr kF3fmm9EMF/c/7vz9OT9/c/x32rTGOCKetgUAQ2qzfk42bDerMAGnXlznfFOnZyGhYM04myBy4iH uHsBwpIksbVXkWwh2yG/P/5AQErgSnBXFIP+2mD6ujJlaoGd7KdAjKwr0/p87Nq3QAT9KgSGAwdi NTvM+DBunF8B5s6dATCtRaVGjVYKMH2YBo1pKZuBLCfb5oULj+qLfTAWSjmI1dJWw2c7OeblNcwt QaWTX0AZWALXZJhtZBWWLiZLG455oimPZaLOGzacgT6ZwLz213PeS4tZS6jf7t1XoO8FTcN0piws c5o0d8koDDKtXbsdQGzBIGh29HWA607Vi8DVsaGlesVnR+qCd0MQuFrSpzeeFZ5X1M2sN5bl1Jkf AYbw8uMIdJu+FxyN7t6oZzRGo6PetLCaSYUrFXQ+0YrNK0q5R8tJ3gfyyrQD05R5JBgkyFQ29Owa yXN/HqnZqqYUKFlAAaq5T7BH0DhhkJ0Z0AAAIABJREFUxwSZfmC6HhOQbonaosB0/NbxkiJ1Ctlw foOCSnbPk7n04zfGN0ZmfzxbgSnjJ0ueTKbum6ryCZgpZ2tgq0zcOVHmHJqjIJcgmnoxPUEl97y2 8sxKGbl5pLoEEMAyPXXLXSS3gtdDckg2Xtyoeb333XuS6s5UsuTUEmWPCYZ32Dtk+TdYfjxdGpmx f4ayy4PeHRRiXSmP02UR9FZrWU0IXHvP6i05C+eUMrXKCFnXD+wPQu4OlEm9ytUrJ4889Yikvze9 rDi6XMIAXdvNuEN+K5RTAhkzi92vH9bq/inmKRlAh2d109qgvytvUy/ZljFwcNTp0zFlNUeXLztA lnPTEriGhTnMos8n4vf/IRDsGUDaq0ULDBDPK1Go7xYaHYI6gjk2EApcCRjBysYCrohXu0wZDDp/ TH1SCU73TJoUAnjK0iINgWLl4sVVF4LA9cOG/YFxVWYWQLgSmNYWiM+8LsDPlV/vzJOMrgVgG42y KMsKQDwFtvCNGYPB1XvgqgjfWgDHn2EbAt+IUaNkBOZVJVtK9rgnfJ1H4T1wCTMMEKymwNyHz9ar J7sBVvcitKhSRf1vjwL0W2SakY/aBl/+T4BRfphz/UI/zSfuy4HnDLcDcMXfOSqCE24UYI0rn/m4 A+/f6LyNDt4+5nl7tohtCzvcQkODa5XxkrgVgCtZMY4a5oujdm2nEWdDnjGjACWK9O/vdA2dPy+A rSTOZDcGQnE6LB1Qm0DgSiazMObhbdv2dWCcFQoWN206r2CVoJWgj0CzXbshWEEys6xf/yuAXSoF rlypi2nIjG7GrCFbMUcw/V39fraBDlvL481YphptuPqOZsfSxASyazAAlMD0esB1zZpf0JY6DLCR u2nTJWVyCVIJRMm6Elzfeec9MmTISgXQBJ1khBncID5NmrsxOPs96GCp3m3bvqHxKZPMLF0UCKgT DlxtBc4FCtwiwNV87Bw+HKozFusN/PfUZ5KMDGlwbKhdWm8ayePKuHIe1zL1ykiz7s2kzWttpHrL 6sosEkgqWAMYe27Yc1KxUUXpM6ePZMubTcGfgj0MdOo7o6+C2UKlC0n+B/Nrd//r776ugHCPvUcI XJOlShZiXNk933lMZ8lbIq8UKYOVu4pjLami+WTQskGSMk1KdS1glz2Z2AGLBki+B+AGUqOUlKhc QgqVKiT95/RXhvaAfUB6vt1TipYvKlWbVZXStUrLg1UelIw5M0q/Of0UQHMUf5tX28jcw3Nlh7XD 8V0FEF53bl0IJJPNpf8r2dTmPZrLAxUfELLQT/V/SkpULaHXycbSFoxToQGA6+PV5Bh+ZHNzFMwh o32jJUvuLMq4RlqO24TOIIB86SIwde9USZYyqaw6sVLmyxKZ+WQiudyjuwR+xtLh+lTwH9w7Qm5B BvCxHbhdA9syUw4uM8f6yEB3CPhgCrvdCZp++cVYQGTlSifONXxcCVotgDMLzuhnARDTQ576nrKx QdfP8UWLJFnSpPL+9OmYRnG3Ar4/AFc0gHUfeghz5NfUrvjq8H1tUrmy/o3QJ1aBJBrUVACrm4YP 1zaXoHI9/F3ZrWPYS+rBQVMcEHYX/GvX4r4FHVQGQOQx6JIEbDAZWzZKjEsmlG5LZQsXVn0vA5Dy K3jMCy/AnfI+vSbHjmFWoI7yIM+PHlUQTpkcINYMQFXnuGUjx69usPQcvNUBYJZyCLqpH8HyBuie DgP8zmGgFstEfbWhZqPKcLsCV4HuXvBs8F+tAyHGtRLqQAsEbJazu/n/kznjqCuuLmAafbPPnl0C GCUri+bIwVUn0SVPxtXW7n62RX5//IHAkiwlgev9WBq4KRYhYXt/J+aC7o8pznidLgJkQndj7tws WXLJiy+O0wFMSaALGVdio3KYpq9mzScVCzG+G7CaY8rYgQU7li49rS4D8+cfUUCcNGmyawJXAsi1 mIXCMJ9GntN9bwFE/wbwmRauA351UaD/alfMUrJy5VFhHmR5Fyw4Ku9iIRFnoJWtrOyAAQtV92HD 1umLY+LE7eytw/vEhqvATgXUCQGuPtg3PMJhXHPnF3npZaeqEBDe9I3LfeKlzWDhhRmr3vAcL+uo Lp0xCGa1PHv6MSkf/bAyrmUblJW6bevK8lPLJX3W9LLhF7CjljMYi+CTTOzI8JHS6+1eki1fthDz 2X5Ie0mbPq1Mjpyso/X90X4Zvmq4JE+ZXF6Z/4pOuD8mYoyer/1lrQK/Bp0aSNY8WWXOvjkO23k5 Ql6Z94okTZZU7kh8hzKuZEd7Tu8pyVKAgd0x1Yl3KULGbhir7O3zI55XxvPFsS/qs2z7RluJOB+h rgITIyaqrKFrhipjS39cHTwF1wJ293MWhbaD28rdme+W7YHtQqDJsDVqq9ydCR84K9+Qg1EHZf7h +ZI8RXKZ9fEsZaC3XN7iMK5B4ErGte+cvnJXprtkZ/ROyVEohwzfOFzdA9xAmHYlG0ywsvLUKvCt GHQDV4HjApYRG+Ddv3/DqHxTL2PVSbZn/CjHwCk4zPML0qmzc+Zck3FVRhSM6lyw1WnAQh6aN08H M32B/XGA3wewjOnT/PBH43bRxX6qjyu/oNHQ1YHv6lPoyre/+EI2ofudK34egbuBRfYRsge3bYv5 7DNIFBoigkaynRyo5QauBIgEx3QpSIb28TssnMCeDgJE4/daDl39fVq2FBv50qVgDmYxoNtBZsyA QGBrQ74FGUXAzL4JtwV1cQD4HdimjZYjCveYD3XgLAgbAUYDuE/AyxBAWTgzQnbYka4TzJuBcn9Y AVICbcFBfLgquws5sV4OHnDF357fC54Nbq86YIeDt0QXtDyGL/30YAEefljsstiTEbhZAQ2q5o3G LdTIE3QQxOKrX18AaPBthAAbfoT5aTrKO6ts2YmloQn0rgdc0S7rQKaGDTvJiRO21K/fEV3oBQDi AgouOVhr8OCVYHKTABD/hC74S8g2uYwfv1U+/5zzl5aC72svAFeys1fizY9Ak++ADRt+C7KsO1S3 JEmS/ingasriAFhnzEM6zAE9cOBCvENsuAfmUN9VAmLqSz2ZR8WKDRXYEkCTlR00aBnYVVv9YBs2 fFF9e32+C4hjqe8umeCEAFfVA+DfDz9hf+mecjJbObErPCzWza43rK8YkGHqDOsH3sbOhw/rDWl5 XON1vYd92KL6AJNHpWL98spafiVfqUtAh2EdtJudzOfwTcMlzV1p9LzjyI5y7333alf/0pNL1e4T tk2QT/EjK0n3gcP49ZnVRwEm00/YPkGBJLv153wyR/1dF3y1QEEs07DbnytKvTT9JaiXSGZ/Mlsi L0ZKuvTphPHICLPLnd3+3+JHd4R0GdLJ3it75YXRL0jW3FlVFsHppkubdNBUvWfryUO1H9I0my9v VmBKBplyKJ/5UG8OHuP9g/ZBZW/vK3GfloXxTuBXuUllqd+xvoLdjRc2aj5uxrVfWD+58547sdDl J9J6QGuh/y/TRkZHyqZzm4S+r3S9ePebdzXPVfBxnU/o2iKRXCn5gATKlRX7ZrUz/2S+nNYLNtfg bsvi+yhnPABB/ar0+fBHBmDhCsYnlCPv2Z3OZ5kC9TsJ6jdDUgC1ZNinT5tWvgdw4yAtMpHsXo8F XPER9zR8SdXnB8xlPsyVSx9Tgl2Ozs+dJQsW7IGrFs7Z9Z8WZYjrKqDMaxC4JkWeBK78yidwJLgm WH130CBlY6NYFoBMdt1PxFK2FbF/E0v1WmACdsE/Njn0/gVsrEV90UAPgq9rMbhAaIOF8hOkEjyT RbUBXJm3AucgcM0Kn1jmbRhpfvkTuHLmhIP8KKBbAtK4bYkG+fZ0FRDUCS94Nviv1oGQq0C1s1iH 9mMdEWQfBAXJkUE3I6CR1IaUecM/SYGHC3SEGn801oFM8I97qrkc6ztViifHUpKrybg6A5bQzsVq n8w5QRcZVwJXMq5NmnSWQ1igYhkWDiHoG4qV1vZgsBdJieJYMKJ27TY6XmT16p8APlOGGFeO3m/U 6EWoailD64DKGMDsnAe0u99Jm0KmT38fTK6FF8ufY1ypuyPPKRv1J0NM9wDqSVB6fcbVAa4clBYR cUXZ5KxZ84Do6SAgXDCrQKS6CriZXmOzuHvHhgDAsGHdwsdkTNuPxcbzirqZ9YZuAKwz9CHEC5TB xotQjw1g4B51KRovTPsZLNgxo7Q0/19VQNUTUr5ROanctLIct45Lr5m9JHuB7MpGEizSR5Ms6Qn7 hJBhJeNKcNp5fGfJmjerkJFlNzoBKENkIFIioiJ0QNSEXRNk5ocY4AKwwsFVrV5uJYUfKqzAl+wn mU4CWjK1HLyVOElimXdknoyOGC3JUyWX2m1qS9UWVaX649W1e54DqnhMsLL619WqQ86COWWvtdcZ EHYFI/8DBxXQUk+6AVAn5kW/13cOvaMsbsfhHVUHBdscRIUfXQSy3ZdN6rWqJ1WaVZE6j9fRmQhS pMEHzY/rFIzSx7U8QL5xFSDjmi5jOmVk3/sWfrNpU8ncI3PlE+sT6Tmjp2TPn13BLv1z70iSSAhc F+KX+Uxi+ebYdrE//ECsD1GRbkZbc6PzZFvGwHwKFnTqIoEq66e7TvKYLi2PP45Vkdo492bPvipw VbAG4LYT7CzB3u7Jk7G65BIsavSOfIVpo7j/HOcZ4EJAYKiNBMBdLB9XnHMmgjZkZdEYkgmdBDDJ bnXOSMA5WAn4vsNAKzKol4OMa1zgqoO5cP8E8qMP7KdgisnAkm0lALXQeHDAWGaQECuwkMQFgE92 97Pr/o127eR+MMMcVdqialXHVQF6XeQMEwDacYGrcRUwOhiXAOo/s3dvZYc5zyFBs84iAFeCT2BH zm370+rV6jvFe7FeDB5wFRjEC54Nbq86EMtVAO0mN8vZ3fz/+fXvbuDvvBNIqa6z9CP9mH4C2Ma2 EwxoIrwL1q61Zdt25wPa74/dPplzB3Q5wJXgs2nTruoeQEBXsmQNHahFH9ZZsz5RcECwSVaTvqnJ k6cIAddOWDqYU1AxHf1hKdedB485QAvtMJjOdxVcbtsWrb6yyZIl/1OMq5HNfMiYTp68S1KmTI3y ngXBYIdALN+PIBnUvzWujysHcL322lJ9h3GuVoLzGTM+0DLOnPm+zJlzCO/TJAliXH0gKYyrQA64 CnTvz6fg+I46Rzfxfw58CdYZ9XHlMeaVxIS4gtFp6ht35coFVbCutJLSdjms4HRKyjUGGGtRTZlF ugmwG33q/qnC7vHU6VLrwKhD9iHpMLSDglVOBdVucDvJXTS3AsLwgGsaKNuZjeDOu+7UrnN2tRNo EuA2eqGRlKxeUgcxkQHV2QEAXumWsO63dQpc5x+ZLyM2j5A0d6dRF4I+s/tolzz9VnvP7i2vLHhF xvnHyT5rn9BlgD6me20HoJoBVM++9awOmiIg3XR5k+q44LMFkjRFUunwVgctJ+PST5dpx20dp6zy K2GviMmPAH7o4qE6uIsgnSCebGpcxpWuAizH+7YD8pt1a4ZPgRPqu9tpdCeh3cjy3pH0DlkFV4EF sliav3OH/Hxwq7Y11k2sLv9Y1hwg5G7LCGDpU8rJ//mxxUGF3HjMePH4uJJJZNDBUAB2DSpUkDpg TfHlHfsPn908uPYyZgzIlTmzXPT5FECTceVCAgbIKnAl44qPPoLhK5BN8Mkptaqi54ILFvAewd4V tLfxMa4hdhPAl3n1x0Aqgk51ZUAjqHs0TMybvqlLX3tNitHfF9c+njVLB2MdDgtTP91wLDZAJlWB K/KND7gaxpUNL3VWBhXAla4CdGswjCtBLj8aBrRurf6vLLOCWZQx1FBDv9uScbXxsjFBUIZbJdxK Ov3dulDe32nnv1u/+HT7u3WOL4+bdU2BK0gBZ3CWBdRqiX05oHsdWIDzf3RvBmcxX8xLiD55p3Hn oAXO5+faoCVG4mI0/s4osAMWwCXbbw6Oit02+f0x55Gof4ZxJXBt0qSbsq87d1oyZcpeBRirVn2n /qtFipTTrnamX7v2V+3unzBhm7b769b9pIOcBg5crKTKpk2XIddZlpWsKv1eOXCKYwfy5CmKRQUG KvHC2QLow0qXg507OfsA0zn7PXssANqYWQUiI2NmFaA8v99SMvrBB6tjDtpaesy07lkFNm68oICZ oJmBurPMjENXATK0Tn4OeH/66dfhMpBVhg1br36zHBRG8JuQ6bDIWhcsEJC+vfGs8Lyibma9iYbL C3SQEydE8AKlq4nNgXxkb37/XdwblnvREdyPRzeVh684swqUB3Alk0lgxhH/j/d+XOo8XUc6juoo ZWqXCYE2AkW6CnCZWE5bRYb0vf+9p2wqu9wJEgkW5x2ep3Vp/bn1Mnn3ZEmSNIkOqHpr7VuSKk0q ibiI6avs7cqE0h+UoJDzvdLHddZHs8R30afd7Bz1/yV+ZE4ply4F7LKni8CBwAF5frgDXHmPzKoZ QMXBZDkxap+uCkw7/9B8MJ53SLvXMfIfv00XN6lrA8EzfV4J2uleQL9VMrO0Afd0neg1Aww05pfd emmrpq1QP2ZwFl0FCPL9Nvyt8Zu0a5KyrPTrzZg9ow76ImAP+yxMEidNLKtPrJI5AK5zMDgrGgAt GoOD6IsY2vj3HxVnkBaf6+0YWBZTLzmgiHOKYm5SOKCLOpuHCo0DG+9FxoXPpwLXsLB4GVcFamA0 6YtKFn8bpnoK4JwA0fL5NDBOgAO3AILJmi5//XXhYKf28KOtxWVz+bWNhoCT9LfF/KwEpwoW8ZXN yf7pK3oP3Ay+RB70GbXRiFD+3SAONnBWgWA3veC6AdJ0CeC8q/RBvQw9mD/1UbCIRpBTZeXIlElK oT0f/vzzYiOvaMSh20Bh+LaWASPNKbR0RgDkxcbtdfjYlrjvPmewFvIiGOUAMPq4Gh3UHpA1u29f lU/GlTKuIETjmGB6AvSy0VgZME29Q4EvCwaCfeSVCD/BB63jPwc9BHH/v8EAiAB8tjjBuhVpqUxz nfLNMffuFal4rsHv7DlFlU5TBRnm2H2fx5QXmsoqKNtc557y3YHzslInToGl4XpxjE7cu/RSOT68 CCCfZVW9gnGvZUOjG3UwaY1NzL2QLOTHsjHeH+4hr5CNoQePzWpiRk+ThrpSjsnH6OfOh8fGxlaw XGpXYytX2YxcE8+cx7c3ZaQs6mh0MHGNLmZvrnPPtO4Q69nhPtMYOxpduDey4ubJ63Hlu3Uy6W61 fYhxrSyY+BsBmx2F8t+szUbeDNy++cZ5iTlnzv+W5TTweCkEonCMuGQhdR5XHZzltEN+Px5VPCES z5bAjUwoJ/fnilNotxXkEWRyvtN69TpgvEQOzI26WWVTDn0/U6RIjUFMO5TRRNuN1bSclV1GjFin pAfeH7oiF9pfBcOUV7x4NV1Na9u2SwqqOcF/ihSpJCzskL67qAfaaNWHxxwklTJlGm1HyaASHJrA KbiqVGmhzOicOR/qoCof6mRaLCs9YsQm+eorh0yhPAaQICEQny5dRgWuDkNMP2ALdnAWYuBiBZkz 50KZswP8/6x5JwS4Mo8CBWwljfhwom52vaES3H7+WXexajHqiwERzjyuts7jygUITuJXvgmAK2YT IGDj9FMLjy5UppUDpkaFj9IVnwguCVwVEAKqkqmkG0GxysVkd9RuTctR9xyoRF/Rhi80lM/x45RX nA6LrgB7A3slf6n8Uv2JGJDMNGv+t0ZdEAiE6cNKgNqqXytduCDiZ2daKYLqree3SqYcmaRS00ry hf2Fsqe5CudScGqAK4EpgSuZWMomaL0n2z3SY1IPOYYfgSxlEZjSfYG+uilSpZCZH89U3ckyk4lV 94dogOHL4Tq4bNiGYQpkWWYzHRaB6z1Z7lFQTpeH7dHbpXiV4jo7whN9nlAwy6nC5n4+V5IkS6KM K10FODjr5JcAC50xs0AG+Cayy5pLdJqNbYABfTw2wdy/XfbUmxtnDjDHzhXnnGVkMDOpoMv9asCV IJHgy8YfXmsMquKKVwSgBG+85w7KyqLhqA9WtnCuXEJ/oCcwKwsHSunXKxobTl/VnIAaDQ2nmqJL AH1C2TvQEGMdCA4V7AFgEjTy+qohQxT4ukEg87XQSEYh3r3wM+0eXECCehnwysboIcwiQBkf0X+X HyvQfQRmDuC16T176jnlKluKRrkfGOM88LNVoA359HFlXLMIAuOqHijnFEyfRRcEMq5adgxE6APX i8yYTutyUD9jn1gvBty74cBV/HjiPgS8INBKACUjIF9eN6BB4+CanuNFgL/PUBzeI0AJ3aOMnQjc Iy6v877KQFyVTRmM40PwB0MwT6ZBuwBKOhiYF55HLBlXiUPgQ3kEgtzr+Vakx8sA7Qn6+xAoGy9I BVV4QWl86Mj9VQN14wcsywQ7mSVOjX1Cex/k4MUWnx1Vf95j/tQDOugx7G301vx9uM54vM9jfzBA B5OPRb1NuagT5bGMPIY8YyvGN2lUZ7z8NQ7Tskz+GJl6n9epH/OnPJTVLSukix/33CEo63rPTvWm HflsAUA0L9QDKwLloQw+a5bFh+BHMHKx13IE7R+6zzi3YLjlgCvM9IfNNO4WbM/GPxiIRbgRoHHc FqfDcthCmNoff/D5zFRXzgCrBg06BhnTi2inLXn11cXaOObMWQgyLgsHNvFjnL6fbDTJlDI/spnc P/FEb+SdDP6undCFvxUzCBwHaXIMYG665MpVVDJkyIaVtz5XQEudCFwphy4KvXpN1FW2unWbpPuV K0/LtGn79T6XZ+3e3dwfL1WrNga4zK3s7bRpuzTvCNTFSPzdcIaBWrXaIM+JIHTGCeXR5/Wtt1az HVeQyoFXnEYL7wp1baAuEWjrduwIqM5kb6jXbbtyFupBrI11xTB3rjrDuuNeOYsLEHDwU+lHS0ul RpWUfeQAJwLYkjVK6gApTiNluuDbv9lep3fioKZt1jZZ9/M6qdigouQplkead2kubfq3kbzF8kqt 1rXEd9mnc6CSfaRtOQUVp7giSKWvav6S+aVVr1ZS68laylrSDSFZymS6ehdZSo74b9mzpY7Wb9ih oTz35nOS+/7cUr1FdfFd8Snry9kBuJoX2U4ODDOLBPA6/W93RO2Q1Hel1vyrNa0mXGCBDDIXEeDc q+vOrNNBVcUqFUMT96GysOq+YDvuDiw3bcEBWkXKFlHgWqpmKZ0ajFNmcTos+rWSPWZcgnszyIwu D1w1awd+9HGlDVZiOqxF+CWNSgwXjTP6yKyvTwum7hB8sYlw/lEwfbE2/v3zGXIze+fs1v4/Pl2v 0pYpeGVprrHkqwFeZKi3wO3l49mzQyP4ec/d6BEwmlH1ugAAGjGO/N8B5lMbSTQMuzBvK6fMYuPE +Arg0DBwSqtvXbMDkHHl/TVYfOC7997T9Fac/BQ8o0HcAZl8zgPRRW9YUaalLocx48EqTAGmLCnS 8xrl8ZoCZwBfBcHUBTp9DneJCMz1qvpeRQfVA2U5gflv14OJ1XP4SZGBpR6RYKSNHm77hI5ZDoYb ybgqgwWwEDE6Qt569i0Y91s8OIcdFD8eOoICoCB7OarTKJnaY6oCJ15XYEMQAgAS1j9MOjXoJJVK VJIXGr4gcwfMdYAI7jOegg+Ao/Gdx+OBAyEhX4IZvY58yNaN6zJO+mJZxZ4temp4F75s36/+XsEU 410JvyLj8CKJG+eH1T8oUDaMnOqFF8r5zedldJfR0rpWa6lUvJL0bN5TNo/erHHxt6/5azlhZ1Ne 917BFuKdXHwSTtlvyjZ0a7oBnYmr8QD0VmJwB+P9jEnRQ4AbSdBOyXZMldP78d5SsVhFaVm9pQzt NBQTBCMegDj1Vd1hq1VvrpLFry3WfFQubGPAuJYL+VwIvyCjO4+Gz0xnqfJgFbXV9F7T5ZeNvyhI 13hIR/0o18b0PIfASA1pP0TOwrfQxnyWZD9535TxArpEBzw9AHPR1ZWOAB/73gZ6BuBXYBmUZcpr 9ubZXUb37NgXxzrPBTbm81v++nI5swYNKcBIIByICHqfWXlGerfsLbVL10YXSlc5PP+wA5Rho2kv TZOdWP5T7etie1VP1BvWz/DR4bHuGz1upf0tDVwtC5XJRsWIf/srwDUSf5dkXMk81q3bTjp2HKls J/1HOW/q5s2X8e58SNit7rCTvE4y6Dx6+sqrXyiZ1Qj8DRDUknmdOXMflnitpXOrJoPvGkf1Z8mS B7KHI95FZWgZn3I4lRWXZOUSsZkz50G83Ooryz3dBJYsOYnVvEriWl69x+tZs+aF68JTYHjnKQBm /uHhGNXvF9WhQoUGcOMsoHm65XEpW4Jr6lmiRDVdgIDnLD/TMlAOwWyfPrMxfqS0bNz4u+p52zGu poqwvlyn3riBa0WrIiaegg/m57OFQIvsoDKHWAFq6aml2uVPUKbXcG/ZN8tkxsEZDsNoYXEC/Mhc vn3gbXmi7xPSqHMj9T/lNT9+HOlPwEo3AMrg4gMEcgS+XFSAc8c279lcZn4wE03Jbu1qJzOr01dZ kcqMzvtknjzZ/0l1W5hzcI6CVL/t17y5DC2XaKUexl+WZeB1DgoLt8Jl0s5JGt5a85YMWz8sVuCC BGGHwmThsYWhOVipt/lRJhdgWPfrOgXUlE03CNqKIJyrfU3bP03jM+5We6sutMBFFKgj4K+Whe4N E3dPlG2Xt8k8/JLYzpKvBGyWeXbffutMB8UBO+xWJ4A9d87cjWFgY67cPkemTl6tPYMddLsGcA39 0RJoseFBQ2D7fBK67vfHPmY8gEP9A+cxGw52A/GYgce85pKhAJgNH9KFZDMuZQevG4Abyhf3mY5u AZS5Dr6q6dClv3TQIJ1VwDDC2hCysTF6Uq7Rj9dMPuaYjvpssNzX49OB9/mFTnvg/rtYfITs65qR IzV9gCw14mjZTN5mz7QMNxK4XgHLQVDVuVFnRdMvNnpRmS+CSANKeGyBOVkPny0i7pyZc0Ip1Hk0 0GTOtk/ZLqXRQDep0kSWvLl44+blAAAgAElEQVRE9s3ZJ4uHLJbGlRtjtYkysnOaA0Y0PmyRImkK 0NBTlNVT2T5L5RE4Uf4T1Z+Q159/XQa1GyRNqjaRrBmyytLBS5WF/A0vqXjjYOnIIR2GqD7RW6AX ns3cV+ZKAUzH07FhR9k4dqPsn71fpvebDjq/ktQoXUO+fu9rBekW88czNuXlsQnUj+znJnQbMt/c eOldirykoI+AimmY3sI65wRpKcDCMN5nYZ8pmA9gIvWf4LtXr0I9KVuorEzqNUn2z8Ja1eMjpFuz buiayCeTekxSfS9heiB88kujio1URzKT7ueg4A+6fDDrA/ie5FD7zn9tvuyfs1+m9ZkmNUvXxPQb +bSs1FnBK+oPGV0bXb8NHm6gus3oPUOfOZ899Q9EBuSi/6JUeqCSAsrIaZHS54k+WPotpRyYiXni MPemGwgb23CvtkNdMM/lSczD+fpzzrNrXKWxPrvlQzAPHaZCOrP+DOaVK4KulOaybcY2aQeQkxEr KH21+CtlXzNh9aKBbQYqI6v1EvKj4IfI+jm5+2TVnYCYbLC579blVjm+pYErqva1tr8CXP1+p91k W8U2k+0Vj3ndacMwpRaaAAafzw5d5322jSAFYsUnIGX7z+78Vat+xDKvR3QuVcrmNcb34W/OyDdy +L6IG6jL1e6zW55tfiT+BghEHXmOfsyLbXxceSyDKdsfdWdaJz31Y1rGd+vJ4/gCZfIddUu5CkjC NzdwrSQOy0rgRyBGoOXHzwBMXuMxr/GeAZ0mHsEamU4CUTKW9Bc17KcCSaShbHbPU4bKtgBgEXiN 8ZmO6c01BaHMLSibgJZx6ALAY+ZnZMfVh/KNnozLc+bDH90D4v4IkBmPc72Gyol8VY5rb8pA2bSJ 2kXgGoAfdQ/ZA0eUyfyoo9HH5MO4Yfglxe+0fQoPDe8kC+9AA9z4GNltTqaMg+o4WT8GC8nZszEP mHEtC0ntmBBz9/Y8MuW/BnB1gy+CxIDPJ/wDdV/nubnGvRWJwVz8Y8Ux45s0cc8NqOOe8S3EdcsJ Xcd99/W4xwpe4YbwLZjUI2BY2agYWdyHQGxQT6OfO39zzPgqLxg3Ph3ccdVtAPnR/5eMMRvguOmp b6zA8jDcSOCqwAwNeJcmXaRgjoKSC5ODn8bk3oZ1VWCDFwn+ZqQaGIZi+YrBGbgUFEX9Bot3bMkx SZoYcyh2B/iCHPwVOywr9zif0BXz7eH+if9r7zzgpKiy/a8oJtTVp6uIWTHiGldFEFF0wbSIoGIG EVd5a86uuyCuKGsAzJEkRpLhIUpsERVXZUUEFHXBHP6u6Ft9zjBM9fn/vqf6NjXNwBIcHODWfO5U d9VN9auanm+fe+65g2d7fn3e2Na/3tr6XdXPLY0OVfrHob9LmbbLFDpiQ3vjPhUWy3hdM0y+Gvcp EG9dKxtT5sCywXobyBwvM2XIM1WWzh5pMOZXZGFR0DwbfsNwd7Qe02eMwyAgp08GhyD9nVvHlh1t K/ncVU6otCQ33+rLdWWTD+Or7AgFGN9Cy1M22KSBDbxKD4+ad+2U3yFKBuTrOlzn4Lj5xpsrZMTU 9HrV5h7b7WGtD2ptFZrw4hrpHxp6AqmTHpikYL51Uz30pYx6z2x1pkMmeYMbAeCYvJLYzMdn6ptP PbvpnJv8OrGI+nWpnD6v7WEFfAecZzw8Q07gqd8p9+n9h9+37etvb907dLfdttnN5r40V39wqV8z Og+6ZpCcrrdJ9aF/7+vLjKy5TRs19WN86eBZyGrjz0Dh3v0oq9IGGl6d8qA6obLh3t2pIVbu3bzX 51nPzj3TZ0dM764iM01+P63thOYnyF9II1pb7WI9z+npGqEt1ww0Txs4Tc7tW/rzibUWXYL2pf2p De9XNXAF/Ei5HJ9XVV/PP5ZkYDObN6mmbAqSACwACQACkdSFZTNtq2o7WDOrT2m+6s5R18Lro1x1 dS687/OvNc0DDKd1zC9DnuoSn/P8L1wZwLVpvqkPuY+qHOXgmDOBX368fgtek3FuJc0eGy8rKJbT cMwBUvk5xlA5idfheMgXYJP3bolcSJlsvlAH/aBe/E4XqLua/nibhePUQZ0LS5z361QbXk7v2Ycf zvvxTDtV8meOF/MW2gzvvbyOja4c7b7CA0z+rlhc9WP6mE7y+p+d50VSFWBx9WAJVOKt1q9v8nUx +/xzfSAXtpUJYBcDXKv9Y8zlrDYcByADRGLh9G/5gsii1XY59dP7oHZp3/uhdrN9W0Ar9VsffMsB XMUaDKWfdsRp1unoTnbNadcU4SDAw6S7Jtk+Gm6768K7HDz1pdDmvTrP9tcQIJYz+b37MD6Ak4zT 5CztHS50/AzFbWy8W2OrnKQ/JoFrfc247Xtl3xSIsAbqnx3Hf3rhJ4eykT1HWsWrFf5+ntYr53y9 devZKE3sAHiwBIY85Zp5DPDS/hH7HWFnHXWWlb1WphAU61lfDdVpxMrIA6TRL/qU5BIHRKx/Fx1/ UQrQ6q/3Q8+sZZKDo+AQFwCso7hJHNToIC19lk5Ao0wyPpGzcrnWD97dBl490K2Ikx+QaUhtA7MO hIJlhueBXPpBf9zCKujGNYBr+mjIR14Gq+XRjY92K2QAe9+/kbcWe7fQ6h1nmuYnyLG63MHW9ZaO 7IFyhtvfHyR6lDXLoVqg16FVB814PNrmTZ7n/Xu2x7Macsi7xoDgX874i18X9WLlLBtbZt/I2vXq XRoqyOn+SJPq9PFjunc/aNgXzUdr7faKV+bfO/q9lkIVvf3Q23aBfBDbNmtrinrj145mnw7+1Cbd o04LnneRD+SNnW/0Z49+u/b60gBo89y1O6Sd4uZ1dkCP4KrntAa2Sv2JsjGaRGhEQvVh4QSqxo1b nAR0kkrzLt1xfE5Dqr7e0E6of0n3oXzpflH1hLwhT3hfuv9P5+fnR1+izTCZrGHDWjI5K30UFut3 1uLa1Jq6NXNUXuAaf2pUAWG9W3aLFlfAVVuiH9+AVzb2AeTSI/jYpACrcE0e75QQUGEjLx8GlAt1 hHMryj5cb7C49u/v1kr58sz/w1vwg6rWnXNQFQgm+pAgAYV+bDn0fanapo+kXM5MYbpqJKqAA4Cs hWdoIgJ+l1gst5cvWPKq4Gp8ZQo+AluAkGHaZ254xsEHS9+sx2YpVMN6cgb+0ipfko+mLCSmvgbA 4X2lJip8NuQzq7d2Pfv4iY/d0riZ1ilfFLgyLA8YAmYacdHKD98pJtl/2axHZnmf1tUMYgCJPMCf A6CuoYViRt7U+Sab2Gei1ZfrAGUD+AFfoV8Or68n9owmWmyhiR6JAqxzLhmnP3b1P5sCPAF6G2sZ yG+e+cYtr+8OeNetgQ6G0mLkTSN9GPyr4V+5hdktrm/lbUf53QHQea3R7nkL+oT+uPuEoA04u/MC Wa1nmd+HLLh6vwSH32kSChZp6q7UakSlenMNALFbcwX4if7puyV7dJlCXmgJQc2uTt5L3Le0xb4t HNjpE5bZDx/70OvGT7biRX0rx4KLVVgaokeA16w2flxt8qUjgCu+0olCEIV7B/yi29fDv3YXB+DW XQcUYsnbELMC2LS16za7uh+r/utpSb2fHNzxa8XdQ7HJrdmezey81uf58Qiu0qwGtiy4MjmLyEcM 2zMszpfumGpGA/RlZO0djRbtvPOKDa7NrJm+/87wOKoMl8efmlMAtwJcFR7Rj7sKlIJr+IzIFwCU fYDScI4/cs2OVwy3FGBZxi5sif6HZAGW8ivKVgquhMzCN4hhnPhBVnMa8GFGYqisYcMaBFeBacdW HRWP7Hdu8WNYdrAmUuCXmOQSY+ITw/OfDvnUHrn2EcMXUavR+fA2Pp+4FTArHXAKcBhe+3FBCu4B DGMznE356sAVyylg89LterA0jI51tWximVZ/IA7alg43AA2wDNxSlw+V68N+5iMzfYj8s6c/0xJr F9pRBx5liVbgKQUc+gUI0meuB6AGQhlud+jLqc5McnAVmI64cYRbRfG37HhkRzulxSluMabPeQVT b6xJJrece4u3x1A9Fs85I+Z4GSZFMVxP/UGf0AaTzRItcYlF9NiDjjWbrVnVLU6uYnF1+FYbz//t ea3coXWOZTUO4Fusb3zab94DtFyj53szbzdrssx+O+3nwAcs8kVg3bXWtXf7C77VL/cjFTgO/+tw xZXbSOsdb2antzzd3hkgYQMAS5NiWxl9/Jj+4eIqQJ1YaMO9++mlnxTQ+fcKv7Fd6s4gALr30nu1 xNz61mDTBnZO63O0OskH+iBR3QreDri6xVV95MvE+4+8r1VM1rIp/aZYfnremipGaJfjukSLq251 TW1ZcMXiSsxuJr0OHhxTTWtA1B4YYvvt84qOkN7huXNXDFCYa3O9w22tre2vHyyBj+cft8Hxp0YV eNKetGf001s/iwTX8IEBeIbEHztgGjaAVeGSTOGOFFIjDSkSzpEPEAxl2df2DbcIthDHtXfvdAgJ C2xN/zHH+s3wid122xoGV8EYFsv8rLy7CjCBCShM3ki0tu6ttucOe/oQLzO/ARv8SO+55J50opag z2FwvB7mnB6UQgJqOA78AJ4+KUhAuqniH1YHrkzOAswabdfIIxMcvPfB7h964O4H2oQ7JzjcBECa ePtEm9x3svU4p4ddefqVtvWmW9sVp1zhvpJAJRAIEJaCK33zvgpcvxj2hYPRVK3o49ZZuSWEvod9 EVx7jHA3BoB3ygNT3IL5/YjvvU/vPfyewxiTs7C4Egbng0c+0JJo/1IszDUUsiIFxGrBFdcB9RMY PmLfI6oFVwdQDesPuW6IW0VdU11HKUiG94lcF8gTrK8NFUcTa/nEfhMt1ytnLz/4st+Pi0+42Ifl 3a2DSVC6jz+O+tGG9hjqkAiAP93jaX8O3DJcuK9BG/YBXJmchWV1j+338OgN4d41btTYXr5bll75 57pLh+B1znNzbFDXQbb3jnu7Vi/fpQdEt6Bhg4ZuccU6jW8rrhfXnnqtt18xqcItrkQ7CF9IwvVm +1MbXq/IPq7BSMFEU91+D4kFwMa0fDRgJd7VVsubJhH79ovGcU27sFi/g6vAhXah/6Na29a2Ovk6 Fn9qXoE1FL81tEIYMraiq8Ci7h7wSQJgwx8++QHY9u3NFD/UfWFZeSq7BYDlGOVr6xauKaycxXLF DCPFD7Plp4H+idScq4Asl1j88BHNa41xdwGQ5XPmwJluVcR14J6L7rH8B3n38fRheFncp/Wd5rDy rQJsM3vewSz4Q2rPeyY/+XCx1v52y6b+IS7KVYAJPncoXuLf+//dXr3zVfPZ+QwnC6qwMgI/WPYm 9Jlgs5+a7VbW5ns2t2mPyz+HPAK8/lf292F7/D3dWimABnIC6HAMf9txvca5S0H52HKvO8BeyMe+ CK6yuNK34BqAf+zNf7jZQRO/y5a/bekwP/vx2e4q8E6/d6zyjUrbrv52Nvi6wVb5emEiVE59zPQn uAocqBWF3No4e0FXAQdQXRv6EbWANkpdM8JQvrsPyIKJiwBD9limca34nUILNVNQdIbbm+/d3A7Z 8xD/kjBHS1zmX9SHj3xJsXw6+OkeAZLXnHqNRy/4cfyPluTmw3BWH39dcBVYf5317e6L7vaoEty7 GQP0Aci9e1XXLIu8uwaoX/TNJ2/JJQBL/1477mXJlMQnX11/1vVm/zR3+aCv+MO6VX22RrPk3nDJ iZf4sbmjZOHJ6RoF6KUgn+1fOEdejvszqn117zV5N71+5eX80qYVGVzzkobtp598JU9fBADXt5iW nwbTNbpQJrd9tny4IenbWvtbn67etx/sB003mC73fv1oWdL4s/wUwD0jfIEI92OxHpjwjAWraihE 2CwtJ6qYcKbYdGlYrfLycFaLqsjYQRmVr5XPabguwPxdjarGD7Hlr8H06TULrlj8Wu3fKgUKDdWe 2PxE635Wd5v58Ey3qhI3FEvY/Zfe7zPrfeKPZqbjAsDEGX1Cua8poAAgsHff0+mKwnF+Hx8u9ln1 giMmZz14+YM+0xxfSCyKlTlNViq4CmBNxaILiAI91OUAKUAKE7gIzcXs9Yf/9LD7qc4ZOcfmvijr pcJSfTbsM5/J/tb9IiMN7QM5iayQAVwcPsVU7Zq3s+ObHp9OEhtTmNyk9nzoWtcAuGTBFf9Sdw2Q Do9qhR+iK8x9RRooPBiT19DnI8WMXHONNW3KQ/o2oGvvpLiPh+59qOtDu9RHP0juBypIBESxzE7t J1pUv5ichatD5ZuVnge4DcC81w572dWnXZ1OztKks6A3QOYQrCH/7xXY/dMnP3X4bL5Xc7v61DS/ 6wlIkjQhC4smoAk0PtFVyyDKvaFigiZmyW8YP9cfnvvB6qxex6Y+qH6pjFuvS/ThOvBxDZZwdAB6 w72jX/QRLZ/4yxPu71yRK0ze0vKcWKax7M59fq5b1/+mIPHlL5X7Mb4Q9Lmij93a5Va7/YrbbSfF 1SQG7pRHp8wHdz0q3tZ47dVGMfEeEOcZ4jUJYKb/OSXeq99V3nP8Z0grMrhKgbhFBaICq6IC+bxD qCVJVQssAEv0AZb93XZbs1699M9A7mpBIyyblGGjjrhFBTIK1JzFVXwHYAFLWMXwe2RIGf9VZtB7 CCJZWLHKAZw+Sx4oECS9crfWAa9T18bfLhIIwAIgAAx6P7rXaLdATrpXQKP8wMKWm2ypQLpPpmGT OEbdSkApcEj0gMrX0olhAcwckFQv4EgeAtHTTwAM0APCsMwRhYBrwGrLhK6Pn/o49e0EcOgX0CZ3 hVu63OLD+98+9637U7qlUnkAzs+HfO7QA+w6uOq6n7vxOdtYVmMAEgslCxswC75NkzZa8u1Ad4cA lJglj1V0Wj/5tcpv88cxP9rmG21ufzrtT6nvJ9dLP9BPun898mu3anbt0LX4pYEoDPj12ofKo7bd UsleaeKdEx1yn77x6ap6c12C/dcfeN02rrexvdH3Dftk6Ce2Tt11bPZjstBqkpx/QRBIAsy4gNx3 yX0O/QB2k92b+KQwrJ1uHdW9w9cY6zpfWtCCe0e4qy+GfFHUJ9yXEA5r3G2KEydrNjqFe+cWY/Wd 58khWm24roJ0fKZxZcBdAh9X3FKA5ktOuMQnYp3V6iyPWtHpuE7+BWF3rVE/9s6xVqmlOhOtWw+g M1kNPb2POfW/ANMstAAYm46hOc/Xe4oJ6m3rWnBv4IuZ5w/lyLuMaUUG1/B/hz2Giph+GQ2y90FP ZK3fgoWPvcbZ4s8vpEC4D8v0wPDwhRSG26mQDwMmODVqZFrCzvLdupl98ok3pRIp7JInlPUzteAX /YkfZL+YBjUCrm7JE8ideOiJ1qRRE5/44pZAARa+pljD8AUFEgAoZr4TRxS/VbfwCUgeuvohrafb wC475TL7x8B/2Dcjv7HJAyb7eybm9PtTP4cuzy/AADyxpg27dZhPAmOFpbG9xjqU0p5bU4FQWRoD RABBgBPwUcyjtsvHaOhCVjRg+vTDT3dYZMITgIrPK9DY+4Le9sGT8jkd+S978Z4XrX2L9h7a6tV7 VVD5fNhZdU26e5LPYP9u1Hd+vbTpVkb15anr0zix6OWQKy2wSNOXR//8qE/Qon9ETuDY230lqjQi vTPwHY8ucOQBR9rYO8YasEzoq3svu9djq7JAAvnKNPsfmD3psJNs5613tuG9hrs+w7oPMxKTqrAg D7t+mN+Dc487117r+5pfF4tAnHf8eW7N7nleT49xizWZOKnAPVoCaCQHSoXmwteUvo67dZzNGjrL /X2vOu0qY4LbpAcnuXa4C/gXC+lEmC1i/X4/+vuiPuG+EFWAujxkmbTM3ju3MmuiX65PzqG+xx96 2Ff/85WNun2Uf3ngSwZRA5i0R1gu/wKkOui3T8CT1rhuHbDbAWlUAXmwcF+w3NIf3Ea4j35fcgXL sHRkUhruHX4f6L+iKtDHL4d+6fU+XliK1MsJbP1aVD48c0u7X5HBVVcft6hAVCAqkAIoOpRaYDk2 aJAlO+1ktoE+X7t0saQAsJwqQmIAWPZxW2UVqBFwdeuTwIxJV+5jKWBwq6JWWnrsz4/ZZe0vs+Tl guVRMDv2trHpzG4BKBDkgCKwIDD+5adcbscffLztu9u+1ubgNgYEfTPiG7eEAgfBsnXZSZf5eWac A1ZMpGL5Tyxz+No69IkpsyDhZQUXQGk2T4BUlpClTZYUzSuKgV+XIG/CXROsc+vOHsN031339VWb cF3AJxfgZTUqrLQVr1V4SKpuHbq5ZdSBfrzOq0/km3z/ZLf8OYTpugkhxdA6MVWZhEWMVsCV16ce cap9MljfRGXBdX0ETfjRslwuq0bts8s+1nL/ltbh6A42+SF1UvphLfS80njA1QM8KP9xTY5zbdCH hDXXv0Aoz8zHZlrnYztb20Paut74J5/f7nx7e4CAWVUmucQXEPA4rLL8+nXk9LdD4rp0P7BQs3wu gIcVGit764Nb+8SsNk3b+JKyriX6aHIUkHh9p+ur6BPuC5ZwtMDSjLU9e+9o00NzSUfCih11wFE+ 5A9YP3DFAw6W6MkEMuLlEs2C+hxOBajuTqLYsN06dvMJfvNe0RcaWeivbH+l+8cC+2gXni+/Vmn0 ws0v+MIabt3WFwOsr8QrxpUC6/XrWsP+7KPPLvY1lF9aYA3lIrjqGYtbVCAqsHIpAIBigS2AqN7p f6M+1I880vJM5BLA+rKp4aqDlZP8hTLhVNyvOgrUCLj6P9txElHPnw/l8zqn52ycHjaOCW6K/9DH 670AwCfL8DqXJocgjgsgOO+WQVwFsJgJcP18Tq9JlMOahhVNgFVMasfPC0gcNDL1h3a8bE7nS/J4 X3EFoD7OU1bJ4VXQ6P3Sce9XaFvvizAt4CRCAMPTDIMDa1XAi/p0HX7dKldsg2P0haH/Qpv+mmOq M/TXoY086KFz9MPhCr2kcbEfOb2nHnQv1YdrU53cC9cz6Kvr8+sK+uu4n6cerlV9dH1yel2S/LgA D2ul97GgFVZt7wMALKszUE4MWaIQELO3Wn2ou+S+hPbCxDHXlD5JB1wLvH8q489X6C/XNU4pV5I4 T191nr7iJnLD2Td4PF9cMqpoSFnqyD6rlOee0EfuBed5ZnifU+I8+58hRXCVjnGLCkQFVi4FAoCy F8BmJ2QlAGzLlmkoksMP12cvH76FjfxAbLZ8OBf3K70CNQKuAUoBKQeeXAEktOeYWxhz6RAz/9SB DwdCveZ9KO/HZfXCcggshXz+PpOPMpQvTQE8OF5dGcqF9sgT2g370F54zx5g8mtQv7y8+kU72fJ+ HGgBZgpwmIWYUB99KpYrQE6VY/+hf9RDeZJDsPJjJaTf9NOT8tCfoHvIH/ahL+Qp6q3yrnfBYhvq Iw/leM/rbNnse/SgPY6FdtHC6w86L0IfyoX6aC+0E/bF84VrDPoDkaG9kHdh/Q3ns331ewR06vOy FMxD/nANxT4U7kHxfPaeFq4j5F2WfQRX3Ze4RQWiAiuvAnn9ryIVrKp6lW4sudepk2JebprGggVo C5uDroC3CLDhRNyv1ArUCLguyz/obNkAA+xD4nw4ns27PF+H9kOfsu9D/wI0MjRdev7n6mu23tCX 0P7StFET9ZXWGfr3c+lTWn/2/eJqQJlQDtAN0J09vrh11VS+CK4r9edwvLioQFRACjiIlgBsUZjP PktdB3AhwBdWK5kkxZN6AcAmhSOhjuz5+HqlUSAF1/a6HobVX1AaG1PUID4Dte0ZyL8g+wNuIQcr tVPSlq8o2iTSA/F3VCAqEBVYGRQQeBYhFgssUBo2Jm1ddRXLwVl+t90Uv/Lh1OIazmctsADsz7kF IGYf+kV7MS1XDVJwPVN3VvFL8Ut0/zyGS2OKGsRnoNY8Ayz8YLP0d3mYUlslbRFcUx3i76hAVGAl ViDAJ9bULMDOVXjE22/3MFq21VZm116rJRTnzBeCvJQJsDn/zLK/Cn1a9ppiDUuhQAquWHE0Cdy6 KnWPKWoQn4Ha9gzku+obfi/dl92VTlTSll9B1pxPext/RwWiAlGBZVAgAGgGYPWp6AsXGAC7117p ilwsbPDdd/MbKgXYZYHO0AdqHzfObMgQs6FDY1qeGjzzjFbOWls3YLWYogbxGajNz0Bea80X+/dH 3SttSYWsCXGLCkQFogKrkgIBHtlnLbBoMHJkupRs/fpaRejUdI3poA15Gd7Plg/nFndPHZQfMyaN dqAY3grkHdNy1mA1X0mJEEpTYooaxGegtj4D+Sn6sFRcXPdzLRgTsqFjdCZuUYGoQFRg1VEAgGQL ABsmZnFsxIgUYNdZR6vvnFQVYMmXBVjyL+6mZWl9e/RRs9VXN+vRwxdOsIceMuvbt9akvPqSTbWp b8vUl/79tVzmtm7DWdxbFvNFBaICUYGoQFQgKhAVqBUKFCdwBSsqQEoK2z80o/WUU8x+9at0n8uF M6n/a7CghvIBhoFbUunxkP/JJ1Mr62OPyZigNl5RMPBJmiRUTcrrGIlz8xSLtkIpvF9gr1Bffp6Q X8pfqXorJk70Y2HPsbzOh3pL97QxT3mIg0vivZcp9CO0WV1fOZatL7QVjmf3SaFvHm9X5Tjn15ft L68Lyfus/ixJX6jTk8r5whR/V9D2hg0Frro3xn2OKWoQn4EV4xkoGBos7Od/FMdXUYGoQFRg1VQg C5nAa9YCO2OGWXuFT1pjjdQS+9xzVTUKQMrRAK+8zkIw78nHFsC1X790YQRcB/B5XVQaOzZdBeyN NyzPa1I2P+9zOU0I1qzo8eNTdwTBob2plYOAY9JkBYYH5nTe61D5fKGORH3wY8Dd6woTRVkS9QGM o0dbUmgzlKnSfqYu6qE+h8UXX1ygrTznXlIQe+rWea6l2Hboa9jTZ/JxbVyX+l/sa6bN0r5UeU+/ SdSxww7R4qpHMG5RgahAVCAqEBWICqxMCgCgwGuATa5t1iyzbt3Mfv1rs8aN08lV5eXzrxpXAMoR M5a8bFmoDXUFcFUsWffwckAAAA30SURBVIc7AZhDFWBVkvJAJsA2YYL1Of98+yuLKShPUjjOuYTy AsGvhg+3rmeeqVUl/0erOr5mL/ztb3a1LMYXtW2rpcaP1xLmJ9q4226zckEo+R1AqQuoA1IFqIP/ +lc75sADbYcttrDtlU4+7DAtU39XCrOZMqX9DO/pTyX9FWxO0KS3j594QitCTkz7qLYqaUvtvDtw oP35jDNsFlZnnac/d1xwgffzwkJ/z2/Txi7Qa/L9S5Oq/lfXNeqWW/za8qor9D+0vdA9/SFJQ9tx xwiu/mDGX1GBqEBUICoQFYgKrDwKZC2wSVLVevr992ZEH9h4YzPBnfXqZabwWsXtgAPM1l3XDChj C/C6FOAKlJIAu+00aWw1TWS666KLtGz8W1YBgArg5hVg8K0HH/Tz/6TdadPs7KOPttWV/5D99rOD GjWyZvvsY/+1wQa2y9Zb2/8+/7wlArl5WD8Fjh8OHmyH6vyWm2xinX7/e+t94YXWWyDZ7tBDbVOV Oeagg+xrwWOifnh/AEdgUPuQeD+Pvspq2/nYY22jevXsw8cftzzuBjoObFdoP0/t7cOQvfo2ugCi 1AuwNt1jD2u2557WRPsmv/mN/XaXXTzfjP797Uf1dfONNrLfN2nidc5T26EvoQ/V7uknKYKrP47x V1QgKhAViApEBaICK7MCAWKTpKoFlrBZ991nJij0WLD332+GhZFZ8ky+Yo87ABvQGqyzIc+SWFwF dr/RognHCiDr1Kljr9x9t/uTAp5AIRbTd9TWumutZR9RP+B6zDF2DJbhf/4zdTMQ7H4/apRtsuGG 1k2WWayiwN8cRVOot/ba1lKAWwbcBbcChulV5vNnn7VtZWXeW9ZKrKW0l4VWXju0AsGq81yBb31B /adPP120tnLeQVt1X6uIDfW1glkDQfLInj29bxWUxU2BNkm4K6jfdwig9915Z/e7rZRbwRzB+h7b bZdel/JjwQ3tVwutuj6H1giu/hjGX1GBqEBUICoQFYgKrCoKALBs7IP1ND2SRgcgFizAmk3A6znn pLkAX9LSuArIarmFQG9wt252+QknuGW0QjBbISBzi2sBXOvKDzeAaydZXA/be28rk9vAD4LTfxMt YepUu7BdOztw990tj++o4K9N06a2D8vgChbzgkMAkzpJcwW6wOp32m+43np2w9lnu98soAkwBlj0 Psj/dKrgGUvqW0RJkH+tW3QFj5xnghXHOf/cTTfZlptuas8SWUHtch4gZk/dWGa/l1V47bp17W4s zALecvqia/niqadsDcH7qJu1gABlgV61sdBEPyO4hic17qMCUYGoQFQgKhAVWGUUCNbXsAdgA8R+ +KGZLJcyiabWVqA1vG7d2uyLL1KZHnkkPa/hb6DQJxItBLyK1kSBaQOB3v2XXurwuZmGzC8WgNrb b1v5Cy94PVMFhUVwnT7dOh51lB2J2wL+tlgwsWQqfyNZLE9u0cLDfE0rgOb7LH2rvgQILLarfs3F JUFlB3ftauvLBeIHvU8EuGGYnrwAZyIQbrX//nb6737n7QC9oR53IVD9DRs0sLNatfL+rCPrcLC4 OtgWQNjbE6jecu65ttH661u5jifqB3U5SOsarj39dPuNJlpVCpZLLcALACz1kqKrwCrzZxovNCoQ FYgKRAWiAlGBUgVK4RWQBFbXXDNNRCEgyWrox3Ep+PRTM6ISkG9JXAVkcd1Kw/V3aeg8efdde0kT n7BcjmCoXVbIvPxGcRVYU6DsFtd33rEuxx1nO225pfW5/HK7rUsX6ykQbC6rMH6jH2vVrrysr0ze 2k9D8e42IPgE+gDELPwBqImOlWuPj+zw7t2LVlLycT4v6y8TqFaXtXmsJoAl6hMwynl3EZDLQVdN svqV/F7/T8fKda6e4uRieQ0W19C2g6iAFF/cW9VvoDkANa4BibR4V9px/eyD+0K2z1VeR3AtfXLj +6hAVCAqEBWICkQFVkkFgNckSS+9Zcv5vq2AaTYFy6ssjvbf/52eYzh9CSyuDK3fJ4trHl9QWVCv EXRuIAvod0y0Eii+rYUM6gZwFZReLJcCrJo7bbONT+zacautfMIUE6C+xW1AfrBYR7GSJrJwup+p oLIK9Ok9IAuc4ke79Wab2Z0aus8LJkN+B1T1Z6iA9teKeVsmuGTWP7Dr53SNU2VdBjSJdIALwf+p z1hv3eLKcH+AXMrq+oaprjUEwd8J8vOylHr7hX4AtpWqc2ddT+8//rFKX0r77u8juK6Sf5rxoqMC UYGoQFQgKhAVqE4B4JWNcFi4CwB599xjJgunaVa+L2CAFTYLsrxWFIAlAVcsroAr4OchrQR8TFQ6 4ZBDzBRr9h8PPGBrysI7WzP5Ta4CZ8lVoOVvf2smC62HnJIVs0yW2TYHH+yW2EoNuZ8nFwassHn8 UQvwmLW4OrQGYBRA4mfb98orU//VAJv4uwpkH7jsMttCk65C+Ctgcx5lCy4ChNbCsouv6o9MCJPF FR/XYJ2lLe+D6tpXPrcdjzzSra1Zf9qQB//cveQqgMWYCWTuXiBYjuDqT2L8FRWICkQFogJRgahA VKAaBQK0VnOqeOjbbx0sbdgwM4b2Dz98qSyugOu9l1ziMFcm+GP1qffkL4slc4yG578YOtRfZydn tVCIq0RQOldw6cPtKsNELcJk/V1w/ZoSVlnOM2vfLZsCQACRBAgCk8DnNFlN8aH9RKGzcE3wmKw6 72Ap2Hzwiis8UkAAV7fIypLbvUMHayiXBfexnTLFjCToxuL6KjFiZR3GncAjBGCdlSWaPn1MO4VQ WvQj9MnhVuBKSK0bO3e2/CKsxdHiWnwK44uoQFQgKhAViApEBaICUiDAa3AbYMUsrK9M2kqSBSVa Gh9XAWfW4gq8zWPSlKC0j4bLN5TvKDFRgUEP6i83AI8qIHCtECT+pAlcgKTDpAAVX1P3VRU0bq/4 sN0Elya/WKyhDqpYSmUxJf9cLKuCzdaKn0oEAgCU4wFsHWDVv+nysa0ry/IsWXwTgS0AO3PQIIfp QxXd4Eq1cancFy4/+WS7RIshEDGgnazFLwpegfAwCYwQXrgzhKgE3k4BpOkT8Wf/pcUINpa/7ZuE I5Ml2WFWcOugWroHwElxctaCz2I8EhWICkQFogJRgajAqq1AXgBbJQle86SyMssLZvMsECCLZ14W zMV1FcDyuI38S93HtTCsD9A5iMrieLRWu9pKPrCbyscUcM3LVQBw5bjHcRW8Mkxv771nT2l1rDry H/3g0Ud9iH+SYsJitcV3Fb9XXxa2AJ4ejUBD8X9QTFjcEL5WTFcWC8DPNECiwyR90XEiH1zF8L36 SL43FduWyAa4I+yn4X8mhpGYEAa44qc6SIs5JIJP8s9W3+nLK3fcYfnMBK8AyX69AufHVAZwnStI TUiZ/oR+FfcRXFftP8h49VGBqEBUICoQFYgKLIUCIWzWEsRxBcgcymSRZEb/nYoqECyegBkAOU/A 96WC/a+nUFxAX9ZVANi9+5prfBLTnfKPvbh9e8/D8q/uKysLK3B6h6AV9wHCZI2U28FsDdN/pH4+ ef31dpigE3/UUbfe6nFfK2Vtpe0Ak0WAFqz2l/8rUPxv6gV+lc8XFgCcdd7hWeAJHJMv17u3h84q 02QtYrWyeEFjxZgln7sOCDpDO+jgPrO6XiaqEaUgaBHyFGGVdkOK4LoUD2ssEhWICkQFogJRgajA qq3AUoArQOZQJghsqdn/Q667bn74qAKQue+qwJDFCfD7/BJfWkFgL0UvIGYrrgDbbr65p+ZaTnUA Fk4Nm1cW6vahfs3kf19D/O3lf8vKWnVlDWXYnxWwLj7pJPt/GpoHNj2vgJCoAUUw5L3qIlYrs/0b 77abHbDrrj78T5gsrKSUI9FXYLtMrgssQzuhTx/3n6UvPwh2WeqVCVt5XU92+J/63corS3KXwspc P6ndSqVE57J9WeA150nRVWDV/vuLVx8ViApEBaICUYGowBIosBTgWoQwwEsQaPJPdQgrAcdglS1a OQOoycXA3REElL4vWD4dhslTqMeBVFZdgPff8sGdofioJIdHHaPtIrRmyoXy7DmPS8NHihEL8B4g l4B/A6wFuKTNkLwcFlldj/elUD5cYzgW8gO25crbVj6x7tuq0F9ZkM72Y4HX9JcUwXUJHtaYNSoQ FYgKRAWiAlGBVVuBZQFXgV2AuFIwC5CHRRLrY3gf8mf37loAYJIvU6fHXVV5B1UAL4CuYJFj1Eu7 oe6F9SFRXhO8srrWaUccYW8pRBd1ubVU5UO5bJ+y9YbjIR97h3LV+YlcF9o2a2ZfasnXLLQurE/F Oug7KYLrqv33F68+KhAViApEBaICUYElUKCGwDUAWoC+AHLZ99nXIX/p3kEWUBTkAZokLwewZqCz tFx4H9p10MQ6LOtuKF+dlTj0KVu+9FjxXABYLMaC2KL1dzH65W1HcF2CBzVmjQpEBaICUYGoQFQg KrCM4Bogrrbus9Dp8Iv1FegFGhcHMBeWR+VDHcC0g3Gh3nB8kfXTfgTX+PcXFYgKRAWiAlGBqEBU YAkUKAVXlnzFMskMfGbqryQpX7gO9tnXS3t92Tqyrxe7PuLdkgS9ptW2tGZZ3KICUYGoQFQgKhAV iApEBRapQCm4ahKTx00lviohomKqGQ0Iw0VSPFpTLNkIrot8SuPJqEBUICoQFYgKRAWiAlKgFFwV 1N9OO81MsVVNq0nFVEMaoC+JhRE22iiCa/xjjApEBaICUYGoQFQgKvAfFQjgiu+nVqHSSgAx/QIa /H9P5dcqqtuh3wAAAABJRU5ErkJggg== --000000000000d5bb2e059c1dbdf0 Content-Type: image/jpeg; name="1578829593090blob.jpg" Content-Disposition: inline; filename="1578829593090blob.jpg" Content-Transfer-Encoding: base64 Content-ID: <> X-Attachment-Id: iVBORw0KGgoAAAANSUhEUgAAAq4AAABgCAYAAADcgvDrAAAgAElEQVR4AexdB4AURdNFchBUMpKR rIAECZJBgkgOIgoKiIISJYqgiCg5Z0kHSBbJ+W5vyVGMKKhk/QyoiCLpbmfqf69me2/uPOD0FwGd WZpJ3dXVNX09b15XdycSb/Ms4FnAs4BnAc8CngU8C3gWuLYFoqOd+ytXitxxh0ju3CL584vkyydy 331euFE2oH2NjZMnl0TXfkreXc8CngU8C3gW8CzgWcCzgGcBiYpyjLB4sUgiwKd580T27hXx+0W2 bUtwsBHX3rpVuI8vnblv7pnzq8U38bj/M3FD8a+ih1tuQo81/+vIS0icWPnBVsKwY4d+HHjA1ftb 9CzgWcCzgGcBzwKeBTwLXM8ChnFdutQBrmFhIrt2iUREiERGXjPYrvuWzyc8N9fi25trlGviMp05 d+dn4nJ/NdlXix8N3d3p3fEScuzWLSo8XPM36YzcuOe8/qfyZbkZCF7BvHrA9XoV1bvvWcCzgGcB zwKeBTwLeBb4fwDXWOBt+3YRBrKuAHG8Z/YajwCNrGXwngK2YBr7GuDVJvNLIM24PDbpXXloPrin cpjP++9rXrHyj5MurhxzbtKoLOp78KDInj1/LI9LnqZhXOaL/Am0qSuvG3lGfmjPOAzU1wOu3t+h ZwHPAp4FPAt4FvAs4FkgARaIC1znzhXZvdsBVQBfChavsicoiwYjKQcOyJTu3eWBvHnl62XLxN65 UwIEZUhHFlL275eVQ4ZI9ZIlHaAG+c/Vry/FAdgOTJsmNoBhgPFMPkHAZ2FvARC2qFZNiiHuVwsW iLhka3zE4V7BIrrdL+O4X6tWsn38eHV50PyN3ATuKYv5/rxunQxu21ZKIO9vly/Xbn3NxyVH5cO1 YseECdL3iSfkEu9Bj1C8oH6hspm0vM5AwAs/2kQJeFReFM8CngU8C3gW8CzgWcCzwH/bAn8RuBK0 EpxZYAx/AsDLnjEjXGQTSaeGDRWoKqBDHHa1k7V8u2dPSZc6tQPUAPSqlCih8es89FAIuCo7GQR2 BMT2vn2yCoCXchk+nDlTQXVcMEo9AtDjN4DfhwoXVkB86r33JArXrjB/yHTLjgsizT2CZ+ZLnaMB KAnEWa4pffvKL2vXSjTyYVwNlIlwZcsWzedr5PcgAGjpggXlN6SnPtQrbl6hc4JWBg+4/rf//rzS exbwLOBZwLOAZwHPAn/CAn8RuBKAKSj94AOZ9tJLkjtLFln+xhuSIlkyOb9hgw6oInBTkIku9DkA f/dmyOAwrgCkD99/vzSpVEmB4Zfz54sNdwDD0hIYKpMLwEtg26hiRY13YPp0Ba7ueBqXbC1Y3xoP PihlAVy1e5+AkIPMkJd2+xNoEihiz/RuGQomcU1dApjm0CGhTsmSJnWA5ddfq3wyx24wqsd0D6Ar AfODvuWLFJFqAOXUh2VXkBvMNwRaoUPIZcADrn+isnpRPQt4FvAs4FnAs4Bngf+2Bf4KcAUQIyAj cAug675QzpwysmNHBXx3pUkjw59/XmwAOmUuyXgC0BG4Zk2f3gF4AHX358kjE7p0kWZVq8rj1auL AAAzvgGiBLIfzJghyZIkkb1Tpypb+/7bbytINKCTQFDBIcDpjokTJSWmlfrfihVioauejOnEbt1k wSuvKIA1rggKYukzC7BpAC3vWThf89ZbqvvkXr2kbtmyKu8FMMjdmjaVQU8/LWH9+oVkqTyA3Ild u8rUHj0kgPyY77eYVox6bKOrAvSKyw6HwCvBLIMHXP/bf39e6T0LeBbwLOBZwLOAZ4E/YYG/AlwJ GAkyAcwI0BJj/tfT8G21PvpI3nr2Wclyzz06oIrAVlnZuMAVzCWB6wiA3X1TpsgdcAP4HoDPxgCs UBoA2YYPPyw14Bd7afNmSZw4sQJZ+t8a4EqQqwAS8si0tqtbV+Tjj+Xixo0KhId16CB3A0hfZrc9 dGY6+t9+NGuW7J48OeSLGyC4BtCma0Cfli3lteeek2I4Jmiu+MAD0gB6vPvmm+qusHDgQIfJBWhl 2enCsGnUKAXClzZt0vw71KsnZQoVUpcJ6kc9Q4CVbCuDB1z/RCX1onoW8CzgWcCzgGcBzwL/OQvY tq1l5j4UrlwRG+DVXrRIp8Oyw8KuOTiLIExZ0SDYIzOpgPHDD9UN4Bf4u7KLfS3YSwJbgk6yr3EZ Vw7MeuWpp0SOHFEXgmEAi2Rd6TNqAcCegU8p3Q52YtCTAleAY/Vx5UAuAFCCP4JcMpa/rFkjKZCn b8wYZU6VucX13wAk6Ve7Gn6yNsAtZdN9gACVgJasrAJLMLCfo9z33Hmn/MCFGL78UnZNmiR3pkrl uAHQHQDuA5PB4BJk/44y/Ya8M951l/THQDD55BMF8mRXydz6x42T5NDn7OrVOhuC6kmw6g4ecP3P /f15BfYs4FnAs4BnAc8CngWuZwGCVRMsS4QMqwlBIKsiABRBH4okYFYBw1yeXLJEkga78i0woQpS 4QbQulYtKQdfT7KYvBafq0AJDGTi6H/r2DEZ0r69pE+bVgc1adc6AGz/J59Uv9ZoyP0eA5+YT1zg qqAT4HgzGE+CzItkPMGuElgr0wsGmG4IjeFLSx24SMCX77wj6QBaCSx3wb2ADCzv0R1AdYa8AIDs +uHDJU3KlPI7/HWjIU8HeeEefW6rw5e2CfxuSxUooL6sUQSsBPQE0gCnl1HmtADMm0aOVPAer7uA B1yvV3O9+54FPAt4FvAs4FnAs8B/wgJuQBoIiBCwXm07c0aE7Cl8UBW4zplzXcZVQSEA6uuYKopd 5RnTpZO7wVbSv/VuHKcEU3oHGNIjGOBE9pQDlWb36RPLx9Uwrja69n9H1z79Que9/LLYAJFRAJjZ M2WSSfAfJZv5DdwQyOLGBa7qrgAmdcOIEZIaIJOA0QBXBbUAve9jQBdB6v8wnZX96acysHVraVHV 8at9pk4dsQFufwcTexf0X4XBZer7CtZ0I2QSuLL7n4CX8jhF1nnEZVkJTM/jHmdVMIyqcQmgfZiW PrNketVeALQe43q1Suhd9yzgWcCzgGcBzwKeBf7bFnCDV1rit99EvvpKZNUqEYAyeewxEXTzC7q7 FbCSbWUITjmlk+PHAVsEZmQWCdYuACQS7LG7/z3IWzZokCwfPFiWvfaarEKXfZHcueWZ2rWdSfnB VMZ1FSDjOgAgUiftx/3WjzyiXfjskg8DiCbD+iNcAGyAT86hejXGlV3/2+BOQMb1HNwUCDIJJBnI DAeQnroMhb+rHD4sBTGQbAUA6gYwqgSgBMpL4Lea5e675SLic8orDqoiW0qZCoYhU90AMPjqBFjm DADnqVKkkPcxeIz6GUaVeTL/c2Cv6UbAwWXqkwvQGwu00q4e4/rf/vv0Su9ZwLOAZwHPAp4FPAsE LUDQalhWAEopU0YE4A00aGyQasAq9+XLO/cwcOlaCxAoSAPYm4sR9mQduSCAgk8wi2RWdWqoL76Q WRiZT9bx7Pr1YqPrn4yrDtoCsGM8Alf1cYUsMpkn4WOrc7Ui/5Logu/erJl24RPwfY+ZAuJjXJXh BIhmNz79YZe9/rpYLoZTmU7kPa5zZymcK5cujkCwehbA8jewvJT5WViY1IZ9ujRpIgL2Vd0NICMW cGUeBJ9BvZ+qWVP6YbEBTu8VxRkMCOYBWpmfhTgE8ZkxQI3l4lyvhomNBV494Or9uXoW8CzgWcCz gGcBzwKeBWABAlfjIoBR8bEYVYzOF7CZgq55vQ7mUJYuFTE+rgByVwOuhnGlX2ierFmlR/PmOvCK 3ekEtAwEb/T5jAJgI+vIkf0CP9aZvXtLDnT/6xKnAIb0D321TRsdkKWsJpjTysWLS4WiRSUz2M+T ixeLDVDIwVcErmQ4zQIEZFIJAqkP8+Tgr5bwZS2ZP7+CS+rAe4xHGScAinMi71Y1akj9ChV0gJaN /DhrAedc5SIDR+H7ynIZX9bNYFwJcqmb+q4C1LIs1I2rc3Hqq6wAp71gAzM4Swd/YZAa/WDJIBOw qy6IHwu08twDrqio3uZZwLOAZwHPAp4FPAv89yxAoOoOliVy6ZJjB7KgHB0PdjEEYAlcybJmziyC wUe6LVzoXLvG4CxdFADy3oU7ANnRH+F2QGBIttENzAjWBACOrGla5H0FAI6LFJDh1HlLIYMLFhD4 GpaTQJJzsVJusypVdFBTFGcBgHy6CvC6LkAA/1NlfYNg0MwKwC58xuFKW5TJtASvqguALYEk73Pe Vc52wGVmuQwtrz1arlxozlWND2BN/1Teo/8tdVszdKieb4OOBPZ0EeDMA4yzHq4SVnCQ17pgvC9h TwJh1Y8gNahvaO8B1//e36lXYs8CngU8C3gW8CzgWQAWMKCVLCuD2b7/XgRTOAFdxbgJGNBKJpYr QnHjLAMAfhrvGoyrgjAAvrUAZ5O7d1dQaRkAFgRmIVYWg7IIbAeCVf0VbO4hDPoagYUJlHHFqH1O 2h8BX1i6FqhcdscDbA5u106OgSE1oI9AlytxDcZAMAJYAlnN05WfAaejOnVSIOkLTv7P+VmVdUV+ nyJ/DibjfLPCAWOQy2Vcee0QymxW7lI2F4DzqwUL5E3MSauMLuKPhuwFAwaEFiCwwPTSv3Y6lrKd hrLQjeAIWGL64nKWBM5UQL1ojxBYdYNXYzfoIXCbwBPyNs8CngU8C3gW8CzgWcCzwL/UAgasck+w SvBptpMnRQim0K0tDRqIwMdTQalxD8BUU/LDD07sixedvQGu12BcFYCRXQXYJFC7KigjQCMwIygD 26pgFYBTfWENYAOrGcslwQA8AD6CUzO1lMoBqCUQVHkmngsEUg8FnACofVG2JPDl/QC+smRF9Tp1 DjKiIRmUY+S68zO6G33NOcob75KvYG/J8H44e7YkB2jtBd9XgR4KmOPRNQRieY/BA66m1np7zwKe BTwLeBbwLOBZ4F9lATdYNYDVsmKKSBDF1aPoGsBlVAmKuGGRAXULIPNK1tNsbsCbAOBqgCpBmTKR AHXxDT4y8ciMGtbRDF4ywI3pFVRSRhDgcc/4xvUg7nX3uZHjvqbp4KKwCV33H5oR/QStyIP3VHYw L16LLz8jz607y0h9Q2WGDMbj9ctgiQMAuR9hNgbOVEAXCaY1csze6BvaUw8GD7ia2ujtPQt4FvAs 4FnAs4BngX+VBQxwJeDksdnIXj76qEj69CJcyYld4WYjaGVcDr7iHK3cmJ6BW1SUs+cALQLb6zGu AGsh8HWLHBtwyD3BJbvwlWENgtYbri/zIUOLDwcFtwSksI3RK978/wBc+Ty94NnAqwO3Vx1wmk/v f88CngU8C3gWMBYwAJV7ugOYc97ngCr6qmJaJuGSqXQRMJsbnLrT8Nicc29cDAxwDQvTrm4hADTg 6jbZEygy0GeWDCv1V/B4A/U38pmfGYhlrl3TftSPge4KWP42kVjmyXl7zwKeBW4LC5i/WX5seJtn Ac8CngX+yxYw4NLsDbg0NmG3/v33i2BuUh18dfy4ueMAUcPImvS8y2sG+Lqvm2sGuN6GjGu8jKbf L7f0dQOmPVeBmLrrHXkWuNUtYGu3yK2upaefZwHPAp4F/kELGFBp4WveDVh//VXkzTdF8uQRyZFD ZNSomCmvqB7jMg03ykjoZvIgGOaMAxhNz0FI6nvJ7m8v3Bgb0J2DAQO5pGBBMK4P44nlRsiCkA0h qxc8G3h14FarA3Y2NK7Z8VzyIoxFwGZH/4kG10ni/e9ZwLOAZ4Hb3wJXA6xcqhVLqUo2gBnMfaqA 1cwEwFL/VcBqLEYfV+bNaaLo44rVriRNGhGuiuWFG28D2hp2588BqzWxr4RQ2QueDbw6cKvVAbsS Gss6eC5pEbC6HzfrSpAxcE69/z0LeBbwLPDvtYABq9wHu/JDn+5YNlVeeUXk3ntFSpcWWb06ZiAV LULA6k7/V61ElpZyCJCxLKsO7uKUTi1beuGfsgFW5EokifEE2yEcQwDjLZhG7M8G+wN0ZCL8mXR/ Jc2fke/Fjf853ii73yi5CXmOf2fef6eshOie0DjWfjSYp/BM+YEZBK52VKjZxkVv8yzgWcCzwL/U AgZ0ErCaLn4U1SJgfeoph/l88EGRlStjG8AAVl6lDG/7V1jAYVzxsSCY0kw2IURcO9gRAKkM4bYE NgckenO0WFssPY7aFKXHvGfiUZ455nXGN/F4bNIbmdfL37t/7efjto/b7oEtAYna7DwfY/fQc+Lz QmBaPlM+HxNCz8f1TGPJDcanfJW7yakP5nlyT7lGPusKZZtzs3frfa1jd97M73p1ScvtKo8plxUO IBjUizKNXoxv0vBaqBxB+/Aa89W0wb8DI8ddLiPD5Mc0vMbymjJcq5xx79mbYEfMKa29Ih5whSG8 zbOAZ4F/swVsA1a5J2BlMBsn9ccqUzYXDcBSqTqlk7lHYMu47vTm3v9375ZJUOyFm2IDB7i2wtPk SzEcwR9/sCPxwkXgfctnaVCG9kPERx0KHcN3NhCBF3QwbmjvC6Y/gLgmDfMkwwuf5ugIVAI/6po/ Jp+r6eJdh81gq2sFY3c+Kz4P/TCh3Xcj8BnQ7n7nWYXkROIapnTTex9hz8BnFOeZMj7lU7Y+d8Zj HXgfgXnsdJ4nn6WJq3vUAT5rlYlZLYT5+R1Z3F8vmDLZCaxLKh+6xyqPKRf0oDyG6HDUPeis5WX5 GRiP9RL3TL7iwzXKo/2CuqvOPGZ5aKttCCYebWzy4zFsFPrb8Se83MxDAf7HkFEZwQOuMIK3eRbw LPCvtICN94QJBIbubfNmkYcxMCcxuooBWK2P2SgGN8u6cYDV5OHtbwkLJBy4BkGIFYHKwZc8GNo1 w9ZItybdpEqJKtKkUhMZ8vwQ+XLBl3ov4IsBrwpw+ELHi3vRq4ukf6v+UqNUDencuLOM7jJaTi8/ raBHAZYf8a4TDOC4Vrz44sR3LT4ZCYkXX5z4rl1Nftzr10p7rXtx5fCc8blXuxMoAmhtGbNF+rTs I1UerCLt67aXyT0ny2XfZQWetLvGxXNd89YaeaPdG9L/yf7Sr1U/mdlrphxZdMQBqABnqguAowI1 1IFVb66SV556RR4p84g8X/95GdppqBxddFSfJ2UaXbQ+7LLl87mfy4iOI+Tc2nNibwP4jbSu+7xj lYn1D4MLCcAXDFggL7d6WaqXqi5dmnSRsV3HyjfvfaPljQqPUpC5d+peGdphqNY5lofx+7bqKycW nxB7B3oNUE8JbI8uPCqvtX1NHi33qDR4uIG8/uzrcnop6iXuUUeNhzwPvn1Qpr80XXUIPRfU7XPr zsmoTqPkzMozCnx3T97t5Bu04+hOo+WD2RDGDweCZtoQzyihwQOusJW3eRbwLPDvtoALsKKFdDaC 13Xr0NtUSSRjRpH+/UUOH9Z7Gof3DcNq0nj7f7UFEgxc+YJVYAnw+dmCzxSslixQUt56/i3Z8/Ye Wf7Gcnnp8Zck/Z3ppUeLHgoeon3oHiWABUA4t+mclC1SVh4q9JCM6TpGds3YJe+89o40r9ZcstyT Rd7u/bYCXgJjA3bMnvkquAKAICChTDK0DCHwAP0IlHiNcc096s04eh3p9J6LRTPpyQ4yvVs+4/I+ r3F/NfkENiadWz6v8R51MHqZeDw3wM7oxj2D6mQ+FIJl0jjQx5TH6M3z+ILK3mnL6fdOS62Hakml YpVkSt8psvPtnbJq+Cpp+2hbKZK7iCx7A6MjAUAvbwaIBWNY6YFKUjBHQRn43EB5uc3L8sxjz8h9 994nrWu3lgvhF8Tyg23fasmVrVekVpla8kCeB2RYp2Gya/ouWfrGUnmq1lOS6a5MMqLTCAVw7jLa e21pVLERBgUmkjl952h+V7Zcic1eXqU8LKN+NAH0nd1wVkoXKi3lCpeTsd3Gal2a9+o8aVqlqdal 2S/PdgAiytPr8V6SKnkqGdhhoILxAU8NUKB9YtEJsXYAkG4NSOdmneW+bPfJoPaDZNfkXbJj0g7p 36a/5MuaT3q36q1AU/UE7hzZcaSkS51O5bMe8nnzQ+7YomNarg9ngnJGm9qjWQ9JnSK1vNrhVenf ur+82OxFtVX1ktXl5PKTTt5IH9+zi++aB1xRz73Ns4BngX+fBQhWuVkWXpQxDKvF48mTnems6BLQ r5/Izz87cfl/AO0n0zC9kRFz1zv6F1sgwcCVL2hrpyUnlp+Qu++8W5kr7X7GyzzkKgDW/sjiI5Ix XUbp2aKnw3z5ouSS/5IUy1tMGlRooNe065bMU9BtYPf03frSX/b6MiG4MeBNX+A+xGPXLQCzMm3s euU5u6WRPtRtHIlzMsGUCSCm98GEKbAg20s9eZ33eexHnQco1DxwrPHITsaVD8CqstgVfDX5ZADZ Re6ST2Cp6XiPujFf6s143FMH3vMHj5kWQItplI1DGpXBrulgWZnO6Hwt4EqwTHAZtS1K7s1wrzKs 9h7oQ/m0OwfhoZyrh69Wu4ePDXfsCx1rlKyhYE9ANqrOiHfqvVNyV5q7ZHDbwapL9PZoqVysslS8 v6JYu2BDlskl99CCQ5I0SVKZ0mOK2uRK+BWxAaKPLjgqebPllVdbv6ogLmqH8xFiwL15FvHtTZku RF6QIrmKSLNK6C+nXWhHV13aPmW7lund198V+UKkd8veCsblOOKx/NSVz9iPgLRt67ZVgPq/tf9z rrOeMSDOiRUnJOvdWaV7s+5OXrDb5O6TJV+2fMrmqk6sQ6g3J5eclJTJU8qncz4V+Rz5Pt5bbaT5 Uk/ke3HrRSlxXwlpWKGhcLBVLDcEP+JcI3jAFfbxNs8CngX+PRaw8U7i5gKseoVzsE6ZInbevDpn p0yYIPLTT05c/k9A6wHWGHv8B48SBFwJkggmCRQeK/eYlC5YWgTvZzJOyiri5U3gp6wdwA+7ismq sVtVDokMenqQ5M+eX4FDdGS0kL0iAKNM9S8EICBTtWcyEAPAnAFllE9Qsm7YOtkwfIP8uOpHBcxk BZtVbibL3gRbiPsKfAAqKYNM3vrR6+WRUo/IrklAfQAMv238TcZ2HitVS1SV+uXry6guo5yubuRF PRS0QoeTS0+q/IoPVFT5K4atUF3GvjhWzm84r6Bkdp/Zsn6USz7A+g8rfpDXnnktJH9MtzEKQiZ1 m6SAhoBk6ktTJXJcpLz29GtSrUQ1eaHRC3JmzRmJ8kfJuK7jpGrxqvLso8/KwkELQ6CITPWn8z+V dnXbSYsqLWTHNCAkAFwdWEQwzhCJAPkm6LMKd57Viw3B8uV9QAEaGeU/PKvPRMZ3Hq8M6bmN59RW 1O25x56TqPej5OLGi3Jp0yURlJEuAxnuyiD2J7Z2lWe8K6PY6Ppnd795nrRj1BZ00UPHw/MOy9bx W/U+8yVoZDnqlq2rstOnTS/rh64Xe3+wbrnKYMpi9iyTkUHGlEwxQefV6tLBGQdlx0TYCnWU7hGl 8peSS7suye8bfpeLmy7qs7T2WlqnUqVIJd+s+EZ1Zv1lfWDQcqO+f7HgC0meLLn4x0NBAFLaK3eW 3KF6x7j8oCFwJVg3wJVMb5mCZSRqLz7cYMNLm2FH1LGPZ30sie5IJD+tQkOM+qd1/BplD9mAg8Pw HDwfV9jA2zwLeBa4PS1AsGoCGVOCULN9951Y3bqJ3HmnSKFCYs2ebe44e8Y1abn3tv+sBRIEXPXl DJDEFz+7SQlIAnsc0GpAptmbLtUaD9ZQ0GB/aUuBHAVkao+pYh90QA5fxoxvXsoKHA3TFYlngfsM KgvA85nazyjjVyhnIenctLOsfGulTHppkgISdr3+vuV3nY6L4IqA+e40d2sX76nVp+T9Oe9Lzsw5 pVlVAN0hy2Rm35lSvkh5KVWwlPy0/icJ+PHHA6C1dsRayXR3JunavKusGrpKJvaYqPJbVmupMglM Fg5YGK/8ezPeK40rNVb5M/rNkIcKPqTAl7psHLFRAQqPCZIGtx8sO2bskEfLPiol8pWQ2g/VFtpq +dDlMr3fdGXz2N0e2AmGe7sl+e/NrwzowiFO3hFjI8T+3JaXmr8kHR7r4DCg/KgI2kyfFY5Zrsx3 Z9b8rX2OKwPj6HMCiCXYpysHwRPjrXlzjciXwEVgUjs26Cj2h7aCPAI966Al016aJrS/fdiWCkUr KADnR4E+IyM3+Ey1S59McZAhtrfacjn8sjL1O8bvEOuIJS82elFql6kd0t9dH0xZzJ5lIsAja8y6 xI8H1iUFycG8TdxQXQJuJbgl48rnLUdxjo8qZV3xvMmoNq3cVJ6t96wCQv3o8gftg3JQnyub4cYA sNisSjN5uvbTIidExrw45vrA9bBojwPdYuwDKDsAMYFrYHdADkw7IPekvUd+3fCr0C7meRn9r7b/ NzCuNv7kvXBzbYCaf9tt+Gv0fjfZAn9LpTF//ASsDGb79luR7t1F7rlH7JIlRbiMKjY0F84fCwGr ZcX84fD6zd5MWbx9zHP5B22RIOCqbCte9hFjIoRMGV/EZPAUBEU6bBgBg77s0S1sfWDJq0+/ql20 F8Mvqq/fx7M/VoZOAQjS8AVt0vOY1w37xOtkEpVlA+tF1ozAb+UbK9V/ULva2e0LIFIoRyHpUA8A DqBrbr+5kiZlGtk7DYgJ7Bi7tHNlyqW+jYLxRZqO4OUTALTileWx8o8py/j9mu/VN3fRgEXwdQjG o3yIIbtMJo1s7/LXl6v8fdNhDJd8soDslg7JByiqV76eJL4jseydAiEAUWTthrQf4sQDS0zQVzRP UcmWPpsCZ+2+B0NI1jdJ4iTy48of5cjcI1hVLonaiXotfW2pfDILyoMpJTtL1lmZRxdwVRtC/kez PpI7U92pbLC93QGqalc/8kbgsTKwAKVkpwkk5Th8XOELy0FWtJG6Phg7A7QOf264sob8ePGN8alb h3nulGnkup8n87Dft2VMpzFSMj8aJYBJMvdkHOl7emTeEadeoP4YGXH3BHdkn79Z/o2kSZVGB3iR 7dXrqIcmX1M+2kAZTuQ1sPVAyZU5l0x9eYH8c0cAACAASURBVKpM6jpJJnebLHNfnqtMMD9oFryy QKwDDvtv0ht5rPcE7XQPoJ8v7T6hy4QEAVfDuKo7A4Ey6x3SN6/SXBpXbKx2UNsE/xbiljnuuQdc b0r7+K8C2nz3c7PxJ3M7bISr3NAHgiPvdzMt8JfrCyubCQSgboZ1HxrGVq2cAVc1auA9CVLDnZFh WHntVqm0Rg83kDbl8/Yxz/oG2yJBwFVfsOjSZZd92tRptSs75J8JUKY+g6iDBBJkqQhcB7cbrKDv wroLCjo/m/vZH4ArX84GLHBPFtB9jfkS4NEPkQNxCKYImgmWTNerb6xPgd7v23+XWb1nSY5MORRw Re2OksUDFiu7dcV/RaIiMTcp5DG9tdtS8EMw/OO6H2Vi14mS7958ysaRQSRgUfkoE7ucGY+jxee9 PE+yZ8zuyN8TJQS66dOllz/Ih9/nl+98qYB3+wRQmvhH/0ceR++OVuba+tCSZx97VgcrGXZT3SbA VObMlFPeeeUdubj3omRNn1U/AL5b9526XbBbmj6wLIub7aTdGKg7mcl90/ZJimQp5KfVP4kBriYO 93xW+lyxcESt0rWkbZ22Iicw08gDD+tsD7/6fpVhzw3Tkfql7islVR+sKhd8F+TihouSLEky2TZ+ 2zWBK59n6GME2L1A9gL6AbJ3/l7ZOWGn7A/br8+KjCjBrOqCNG4dzbGyqCj3sYXH5I477tCZK0LA 1ZXGXZcub7msz3PQM4MkQ7oM0q5hO2VNn67ztLzU4iWtaxxEtvjVxcqKqt1cspi3XgOzS7ZZPzDg 9sK6oq4CeE6sr7QjnwlnKXC7CtDHu2zhsvq8R78wWsZ1Hyd1HqqjrPXRxUe9wVnibZ4F/oIFHCz7 FxJ6Sf5RC9guwEp2ledmI2B9DKQRB1xVqwa3PQ4gcTabcQ1gNTLMTW/vWSBogQQBV305A3x9t/w7 BW7t67XXQSZlCpdxupbrd5RNIzcp4xiIRMUDECGrxOmuAu8HtJt/+eDlEtjnuBcYQGKAhsr3QyMA ALfPJsEMQTG7acmORh/EhPO4RraXaehf+fPqnyVxosRyetFp7con0GM3uf2RLT2a95ByRQB4wRoa YMI8NT1AB0d975+6XzrU7yANKzaU6A8c+dRP5YOpJNN6R6I75Nvl3yqYJIDhSHSCze7Nu0v5ouUd +VtiZjigfIKtNCnSKEtNxpUgcvPIzQp6CYqZni4B9Pnkak1aVuYL9wB23c/qM0uB+kdhH0mdcnXU /aFjo44S2AFmGjY2tnPby+jNqaoubLqgcjgtE7uoWX633ZlerwGAsft9/svzRb6SEOMa/XG0uinc lfouWTkSTDfKwK7tK9uvSJ6seWRK9ylivQ/wS59W6K12hUw9BrDWvOBewsF2W0ZuUeBeo0wNHdBF H+JKxSvJw/c/rP61v6z/RZ+lqQeUpfaHHc0xB5v9uvlX/RDhlF2sSwr0kbfJn3uVwXaQAfWQg6TU VeA4zsH08kNI2W3UCbppcHos2t/9EWDKwrLxOXVq0Emne7OPgzl+YYwyuByURuBqQPXxxcf1A+qT 2fi6CroKlCpQSuzPbHm86uP68TO973S5FHnJsWXQRsyLAJ97dznUfn7oGgy3M+PKdxG3QwD+xYqJ 5MsnkiePF/4pG9De999vy/LlznOIjkZduw02jIBQLSfLZCmCXz788th5xPv9MxagvUvi9x1+3Mh8 X3ezUbdMMADUJFqyBI1ubZH06UWee07k1Clzx3EdMACX6W/VzTRm+zFggSt15c/vNWT/VENm8rn/ fiz5mgg1BGy9+v6FY+//Y9CXK4AYQQj9G8lgHV58WA69c0j2TNsjA9oOUJBEEMbu+c/nfa4v6i2j tmjXOLu1qxSvoowhR5gbEEmQoYANgJV5fL3sawVHPGbQewAaz9R5RujLahhXAgaCisCugBAoEFie 3XRWXQWyZUDXOwATQQq7hdlNbO8GMEG+BBnMO3pbtHahk707teyUzlvKqb2YRhlZ6EUgQ/mfhX2m ZeEArPn95+sofWWbg/LJvoXkA4BQZ8o/s+KMJE+aXLaOA4La7jCu4aNhYHxsKpsLQN6mdhudN5Rg ygBXxuX0YGF9wxR4qfsB0mydtFXBL7uqtduZwIxsdySCPybQbgpIoV/t0rWFDCPdGpSpDgIkxuE5 gR2BOxnU/y3/n/pzVi2BQWJggumacHTJUWV8N47cqLa5sOGCAr/X2rwmRXMX1fhqz3AHtOtz4ccG ysBnwCmiWDY+O7p7sKtcdYYrg07kDx0L5Sokb/d8W+sfbUDd9PkxTrBs7rpAZviR0o+oLMOO8767 LvH4+KLj+tGjg7MAIM0gKaah3y6f9fQe00XrC9ogfuyYUf6aH0ErPoz4McVZNOhSQHcUuhvoQEOw yNSXdSqwLaD2I6vOeWppb7oK6CBGlP9y5GVn2jAw2PSZvbwJtvc75dPysqywlx7zejzhdgaufH9x 241yovNCOnbEdGE9RDgOwws31gZdu4ou4Z42rSUvveQ8hytXLOfgFv//ilxRDRtLY8mO30D8uthd pJv3u6EW6CpdpRd+T+FHgHASP25o6XQf73822kpu3Js/eOeKyOLF/HISSZcOPm54t5w4Ye78AbDq alkxd2+9oyi837i9847TmLVujca+lwj/0LzG7MbbgC+ONGkSBlz5IuULmt2zXyz8QgHUOwPw4MAs qS8kmJTzkeelVc1WUqdMHWU5W9ZoqSCN7OR3q79TxlB9PPHi1umGCLwACghszm4+K4VzFtYBXAR2 BtgqmAMz1q1pN2Wzvlr4lb74FdiAKSS4qleuno7SJ6hgly6BKsGRtc2SM+vOKKu6eCD+cL5AfAJa 5ot0r7Z5Ve7PjT8myGeZCH7Zha1lYhyCCQAQDsyhqwCZ3Xf6v6Pd+HHlLxmIL0kjH3lTPtlepts3 FQVCvvS9VeAKwKPAFeUmIFc/WwDIuMB11ZBVsm7kOnmh4QtqRzku6stLH1SO7P9m2Tfyv3cBNuMB PGTwOEfptyu/lZTJUsqM3jN0hL2WyQ/9qCPyP/neSfVZ5sA5ZSEB4GqWqql5clARr3HBCPrcHn8X CuzBs8GArl/Df5V709+rz0XdRFAmtSvloixkZTminnOe/rD6B60vxxceV50IDgks2ZVP31J+XGjX O2TzOuvLuQ3n5P2335dofwyLrWUCG/3Nym8kbaq0Mvz54U7dQzoFeqxL+Bj4ceOP6pYwrcc0BZoE ruyyJ9jXOhzpfBSxHPY+W1nfppWaOh9uKK+Wg/UE8VkXHyn5iLLitAWB7PElxyV1ytTqGkAbBsLR mON5v93rbc2XjDlt0PeJvsr0Mg/a/ZO5n2h90I8ApIsOMvR8fh/N/EjOrj6rz5LgX8vjR/6ucDsD 10DwfbcX9SRZMhQTZeaCNwfxt/cBbOWFG2MD2vcA6vFx/OkWKWJL376oU9iiolAnb4MNzl2qZQtp ITXwO4Xffms//ry83420wPv4qv8Mv/fwS47faZ0bEe0zfrE2glQTLNxzA9bff3fmYGUXS86cIqNH Y5WWczHJGZdpTHrub4fNlHHZMmf1LnZjfAZG5n0wIddpyOzgfRt/mFaw8eO10HXXfcYx8kz8uPHM fe5D94KyQ+dBme64seK7014lbty0cc/decXS+yryYsUPxjHX4soOndMeDB/hJY8ZJxLEuIofNSrS efHzJbxl3BYFiI0qNRJOGfXtu9/KqRWndN5OgjUG+mhe3nrZAWTBFzeZKwK1rVO2yrnN5+TzBZ/L sI7DJEfGHA4zCPDBF7dhngxw5WTuBH6cJH7R4EVy6t1TcmDmAXm61tPKmJE1JZgb32W8DkgiINa0 aLQXDFygfrkjXhwhx5cel29WfSNDnh2i7gufzvtUu+bJvnFKKg48m9hrok7av3/mfmlds7UCMHbz Eyiy+556kC008gng6fdL+ceWHpND8w/pVFcP5n9Q7RA+CiwrGEjahFN6EQwp44cXNyfM5yAxAi7T VU1QSaaW9jux7ISm2zZxmxxecljSpUqnI+rlmEjDhxs684QibQj08jkFA0Ea2dqI8RHKEnMBgT2z 9uhCEMfePSYTumOQUebc0ucJMKGIpz6hABEEnG1qtdEPBGVYIZ+DtfJkySM/b/5ZfYU5J+uJd0+o XOofPj5cOJ3WV0u+kvFdx+u8qI9VeExltKzeMgTO3YwmQaq6eqyHqwcGsXFqLP2gwbMgc8+Vpjio y6RhubRMAKpcgYouDHTv2D51u9Ylsv9cDCN7huzS/rH26tdLu3JFLQ7g4zM2oJmymD9B5pm1Z3Rh jOL5isvakWt1Bayza8/KiqEr1B2mconKWjZ+CKmdAWD5MUGXkd0zd8t533mZN3CelmHZYMxDDHaf H0NdGnfRjzEeX9p4CUo74JbP9tDCQwrQCY4532yZQmXk8g74brtdQILP0TzPfwtw5UqNq1ahmqJ8 4fjTiIj450M4phYzISLCvik6/BPlpn03b8b3J+ps/vy29MGfOrfbDbg2l+ZSEb+D+G2yN0mE97uh FtgiW/DK2i6z8UuKX7zA1QBOgk8D5li5OAfr4ME6Q4BkyoQVW0bihXeRd5zNAFae3S5gNai67kxZ ly51GNfZs/F+xwt+y5YENWQ2/ygjAabQAOpx3IbA3GccHptzE5/ncdMEz1Wez+c0rtxfJa4djG9B 5wD1vkbcq+VlrhtZATQ0lKcN+1X0M2l0T92QL/PXdEhjZMWKZ2QxPgPtAt+nhANXPx4bgoIHgK/z W84LR9MTZHDaHzKfjas2lg0jN8iGERv0/L3B7yko0mmFAF45EIoDY7g8bOmipXUgUMtHWupUVHyJ u0Grdtey2xnsFIEUgdq2qdt0BHzhXIV1hHqPlj0UeJC1UkAN1wTOQUqgyPSqK/IlyH282uM6pynn AGX+p5edDs2X+tv63+S3zb/J7im7pX7Z+lIwZ0EFLU/We1IHWdE14uc1P+uAJJ3BAOAyJB9A6sAM R/79ee9XQE//Xg7mIqPKeTup3xM1nnCOAXoVpOJlMqHrBHnz2TcVzGr3Pm2MuO0fbe/4xgLsTOk1 RQdn0UVjYLuBOncp2T+CdJNWy8m0wWCAv3lWP679UWd5YLlLFSml7gnt67fXOWIJ6AjiTFzOMzu9 53RlW6MisPIXFzLAc6D9t4xAxQTIVb9WlEPrQOsBOsCs3APlpFzRctK0WlPhQhLKUGImAIJezqfL AWMhPVH3Qh9CKAuZWQ4Esw/ZsnrIap1tIAoLV9Cn1iyNGqtMsPkPa3+Qbs266bNkmeg326pWK51j l2VSkIl6SvcOdVNAGuZPOUYWy63sMz506K7QtGpTlUO3lmbVmunyt/zQ4DMxC10oI4qyj+48WqoU qyKlCpfSwW3rhq/T56i2QRoO5CPrSjBOtljLjmPaY2KXic4HTORF4Xy4nOWAwDa+D5DQM72N53F1 M66YJEPWrnXa+mD7rW2dH3XXHSLxnBh4LQLuPeGog5H4qOW5uW7ix8QlCDVxnbTuezzmfR+eB2Ux mHM//Klj4jp5xJcn4xgdeD9uiEAd8/mo5x/lGd3+mCY6JNPEcedj8nP2VtAWMXoYO8Td075s90lq FChwmwNXuyK8bD6WLdYWibQjNfjFH9rz2G/r/6H7jPeHOHrFiWf+d8dzyzb3Q/u/KD+UPp683fdU D+TBfUQgQiKtYDmD10zcq+nrvs64PHdfi3tu5Jm4Zh9hR8gue5fMxS+JnSQGuNoBNIS2EywrNmA9 c0bkjTdE7r0XU/GUFgkLw4vOcfUQbgR8Ji33t+sWF7hy6i76QPl8on/Efv9V93ZkJN5pWzH+ZJP8 wkYQXU+8xnR6j8e4/9v69SBQ8D4JyuL5j/zax71QvDj5qBzcjwK4Y1zujVwjx31usWEg4MZXbTSO 7aAO7rgJPbZ9PrzP8NLbA2KM5XKVKT4ZWgbkx3z1qxp6qD7X0oEyGdhdd999CQeuNhpsBsFz0Zcw 0pNNYvhl7S96nS9ffdHzZY/AF7GNBpxpdG5P2EnTAKxwuicFawCmjGtABeOafPRFjvucuJ7znrJL lnHPrjkrCiCYFjIVgKBMCkJw3/hGhvIFYKBuBKiqK4ANWVll8zAAi93ZGdJmUH9Z+Qby0W2rOuBv kaPIORiJgE0BMvfMy+8ELZdLPvPQMrKs1IV7xkeZQ8d+HPsQUN+VZeSxPxgYl+kIjn22MoXsvlZb wNaq19XSBmUwjrGhPivqwGcD3Wn3kO0AwNx2Vz1ZFuoV1MnIIRg0HwTUVW1u6gA+OuhKoX6zfCYo K++r/kEb6DHSGXmmXuh15onnQf3C+oXp9FM8JuAzZTF75h0qE+sf5LNMjMuPHJ7rfdqRAWXUZ8dj f0wweqierNcsH+SdW3tO64k+Q8gK3Q+mZTq1H/OGXZm3Pi+TL+PRdnHzRf5aVtYDPlvUu9NLTisj fH79eQXplGv0cuvK438L45pQ4OpHmRnYVtHFgL1EbGcjYX/nurM38bj3oc6x/YyJ68jgvQgASu55 jwwk3zUMBHXc836MbCddfHIogzpRF97/EHWOvVcMPGb+mNUH4DLaJc/Rld327vgmHa9TJmWzx5HB Aemxy+rO1+jB/dUC4/Pd8G8ArpWkEjpQPpJwOxzN4dY/ADK/+GNdYxy9hkaA++v9APE0zvXSJTTe 9fJz31dwaTv6R0RHaPn2oxHdgZ/P8sUqV1zwaWxh9DJy3efmOBTXdspqQK0fefNnzhl/N35h+Cnj ap9CA4S20A6gcQ0GCW5H8FJ+8kmR1KlFSpVyulPMPe7jAlYbgm7n7S8AVwM2Az6fgruamKs2E2ZU +HXjRgWyFq/7/Q7YRAPRuXFjLJRU3mmo0Ph1rF8f7mkp0eOLLhM0XgSlClSRxsimDAuNUg3IToO4 27jaGNIqOEQ8yjdpLDYKu3bJT8i/caVKGNQ+QH2KTFwTL27DYvIysniuuu/cKZvhClK+aFF5EIPV CM5NXI3DeAh6DXpoPmj0Fg8cCNKrovy4AT3R0Ef1cukZK3+k10byzwJXQdkZzIuVex2YAwZDARnu EQjyGoGDggemQX4mLV/M5r6mASBjGsYlkDFgxsRXZhKEZfOq6CoCoxb4IDgNFoEYZDOtgggc85wg Q8Fw8Jw6UiZBjV4n0EJaHjOukUHQ8maHN5Xpm9J3inDu2bPrzsqc/nNC/rz0VSR4vK585KHyg2U1 9uI1c2z21EsBF/Q111Qn6of05ph7tGYO0EaZeH61tBqX8RGMTMpi/pqX23awgdqddrqGXN6LT38j l/fcz9Mdl8/W2NrkYXQ056E4PugNkEIgaICuiWv2Jo151lrPXGUK1aVgeRhP47jsYWSZvSmfloN1 JPgMVRZtE/z4ihtfdUHe+ixQTt536xc3X5MP7aZ/F8yLABjP1v13YvJx729p4GqjTjJcZQvANNwI QBMKXCNhdx/+PtAmYnDRO9IazP5yDCDcARbfh2fq98PcwcA2jdfQ9smAAQsQ9xVZhoGeBJC8HoFn AzIAhEW09O49FTMbVJGsWfNKtmz5MCvPcxIW9omCRcpjfLS76GK/JE+j92EJFh4xcsx9ni9d+rU8 9dQr0gSuKI0adZbGjV+UlvCnHoP5jVes+F7BIuVQnkn3AqZFa4blg018J+2LGDQ1VXVneZ97bqg8 //wIBcZMSzs4trBUj8WLT6pe1I/yDQttbOHe0y63NHC9Rp1BdYGHK3rcsKmrQJBx3RQNV4EguDNA yy8xP14jQGMcBt6JL15Mipj7kVakhEeFXz2+7aSiPHe868l353WtY5/lQ8fjAdl8abMM3zBcVny/ As3hXjRH28Rn+1ylhM748Xp8tjD6qA0CQRsEyxYXvFIfytI0wfJtjtocm3G1TylgtSy082b78kvB H5ozQ0CTJiJr1pg7eBFbeFkhrnm+Zh8T49Y9oq7X0pfl4mZcBRLIuBKs2WgAN48YgRl2kks6DDAa 9Mwz+pVqgOgVdrXja7bdo49KNc5YwC9afAm3why3SdFw5suWTS5CjuX3453qE21YcKzpEW/d0KHq WpgYg8430UUD1wzzauIyXTTA3w9gdAvkyAFCsKz8D88uCnKuB1wpw0bgniCc8aMBlr9a6CyO1BX1 4KMFC/ReAPdMHG3MEI95a0DDFIAO3yLfeuXKYbBzdvkeTC314n2ja6w9GzOGvwpcBXprgAy+iHnM vfv4atfw9xErftw0IdnBPBRIgB3hSPrBbQcroAmBCVfecdPFOmee18iXOiigw0t1Zr+ZUrpAaSl+ X3FdHICrSHGVLgIpK8Jyyh3ULZTHdeSH4sVNl4Bzt33cx39Wpjstj93nf1ZWrPhBu/La/1eu0YnP QoEvwKJec+URX94mX5Pe7GPFvZ6tkYdJZ+SZMpm645YXN6773B3vasfu+NorkYC6fMsBV9uG0RC4 cc8GnQjVspxz1/2/AlwJ2tilTna0NGaRoI/4o3Ch2YcPSF6PjLRD7RoBHwHtO5g72fjYT5q0U4Hy FswOQUD79tt7JTfchO7FQhIt4WLUo8d46QJ3m7Jla0sq+I4/+ugzAHkXITNa28a18HOmrHHj/CqH Xfh+P4FgtILgCROc+Z2LwoWnOPy8i2HQ5IMPVsXiP1kwAC0l5lXvDfD7K2RZCl6pYwpMj0ewXKpU ZXkAH+IlSlRFusryBFxKCKy3YMaLtFhVjfkSrJPRpf4mXwL/sWP9en8ternI+lIu78cX2M7j/XFr Ma7uOsOKgVHa9lXqjRu4VoiqIEfxa9G3hWTOmVkm7piooM6AU7/4xRfwyU57pyz7eplkzpVZHm70 MDpydsawljZAmh2p8RiXxwzslt+D35Q9UyR7weyy8feNCn4VzEGuScO8ttnbZM0vayT7fdllxocz lJl0y+IxAaiR7ZbhvqauAMibehv5BKmdRnWSXEVzSflHy0vBhwpKzSdqSvg5sMzRW1WuH2Vg2t32 bpnxwQzJkC2DvDTtJdlv7w8BdYJq+gPXbV9XGr3YCB2VR2T4+uFqt3ZvtFNwHB7tAHTVCaCWOtN2 ZeuWlUw5M8m679bJAvySR8FVwDop/Eu3EATd3EI2kDMENGvmjLLkdW4WYvBZmr9986ydu7fu/249 qT/bMgaWJ25Z/iRwNcxjNLvuAUrrAig+BwZ1EVjOTHfdhRUyd0og0mEuFWSCce2AOW5rkr1m4wfw +hjs/Xj16pjJJ7e8R/9hXHODTJWNxoIg9Jk6dRTgrn7zTU3vjkddCCj5lV4JszxU5sC5Tz9VFwTt doIu2u3v9+N9GKkglekJQNnAGNDKe0EmAAOgv8Qy6J0x0D23yMmTWkaVwcaKXVnI61eA5J/5YcNG DtcsyNM4BKHIv1qJEpitqqjGpX7GZrEaNebJ8P8Grn7Uw38iwGbadc3uZOj9d+ZpAARlWj4LhoN8 5PPDyh/UR1W7gFF3QsyZAVOI/3fq4cny7Hm9OnDLAVc8sqtubPANkEXDH+C8odjvhZ9zksR2gn1c CRLZdpfHgM78GOxIUEg2czvcLAjYCF4ZCO7YBd8C/vPZs+fHNJFZZQIW+yBgJaCdN8+Z0q4xBsyx K5+AkIFd8kw3b97HkhSD5qrBD54khx9/5+vWnQOgvVMmwT+b7a0BiNzznNd5n+0oZ0igLMrcvPki WNf1eK9nhitWCdwn8HSY07vgzzwS812jrddyGT3YxrNNpmzqX7FiI0mMUWxhYR+jnY/xw2W+Eyc6 +a5bR1DMdBbkU+c/Bsrke+q2cRUwgCEIfqJs+Eii6jS3m0n5K+XlOH6PtHU+Yko/Ulp2BXY5vqC2 A0AJ2MhYNunaRMF9kXJF4LHjxPFZPgV2iIlmfZ8CVT/+6AgCCeJ4bWzkWEl0RyJZ/9t6BagmDePx PmWR5VzxwwqVP3nP5BB4phzGI/hkNzsBIYGuAkPkyXv8MR4HPtEVwDDDzJ/As/fM3pIydUqZfWC2 As/Ic5FSoWEFqdq8Kl5N74fKyvg8r/lkTcmSN4sUrVBUdloA6ADNzG/LlS3wmvpQHqrzkFRqUkmO 4jdgwQDVOXXa1PLu6Xdlu7U9BghDz332Phm61mHsEiXGKpUnV8oiANdEkkROyI/4ggLoqfiw6ICr Dh0wTconMX/+rr/1ENCLuXt7HNmoaPFtvG7KZ1n6oaVl5Jy0+MDU5WkJ0Hw+ifeP0O9X4GcDFH6B KbTIhn4xf75ciIhQFnXxq6+KjUaOADEqyLiGgCsbIzQsBLF9scLYW+3bK0tqoSEgmDRA1EZD9+HM mZgZKZF8Ons2ptO8R9a+9ZYyrga4Ujcek/XdOXEiepeTy/fwhQ2g+4gs7pOPPCLLBg1ywC5BNuIr QKUOKB+BpuaHPRvAbk2byiAwxk/UqoWByukx008qKVOkCMYSVdN8uN8AdplluRP3yDKXwWwAB2bM 0K43ZWSRbwBf3z8C1KZOkUK2jx+v+rl1DtmUjRnD7QBcDbAkC8cgfrRjkahI2P/dgd3BZPoUwKIr kF3fmm9EMF/c/7vz9OT9/c/x32rTGOCKetgUAQ2qzfk42bDerMAGnXlznfFOnZyGhYM04myBy4iH uHsBwpIksbVXkWwh2yG/P/5AQErgSnBXFIP+2mD6ujJlaoGd7KdAjKwr0/p87Nq3QAT9KgSGAwdi NTvM+DBunF8B5s6dATCtRaVGjVYKMH2YBo1pKZuBLCfb5oULj+qLfTAWSjmI1dJWw2c7OeblNcwt QaWTX0AZWALXZJhtZBWWLiZLG455oimPZaLOGzacgT6ZwLz213PeS4tZS6jf7t1XoO8FTcN0piws c5o0d8koDDKtXbsdQGzBIGh29HWA607Vi8DVsaGlesVnR+qCd0MQuFrSpzeeFZ5X1M2sN5bl1Jkf AYbw8uMIdJu+FxyN7t6oZzRGo6PetLCaSYUrFXQ+0YrNK0q5R8tJ3gfyyrQD05R5JBgkyFQ29Owa yXN/HqnZqqYUKFlAAaq5T7BH0DhhkJ0Z0AAAIABJREFUxwSZfmC6HhOQbonaosB0/NbxkiJ1Ctlw foOCSnbPk7n04zfGN0ZmfzxbgSnjJ0ueTKbum6ryCZgpZ2tgq0zcOVHmHJqjIJcgmnoxPUEl97y2 8sxKGbl5pLoEEMAyPXXLXSS3gtdDckg2Xtyoeb333XuS6s5UsuTUEmWPCYZ32Dtk+TdYfjxdGpmx f4ayy4PeHRRiXSmP02UR9FZrWU0IXHvP6i05C+eUMrXKCFnXD+wPQu4OlEm9ytUrJ4889Yikvze9 rDi6XMIAXdvNuEN+K5RTAhkzi92vH9bq/inmKRlAh2d109qgvytvUy/ZljFwcNTp0zFlNUeXLztA lnPTEriGhTnMos8n4vf/IRDsGUDaq0ULDBDPK1Go7xYaHYI6gjk2EApcCRjBysYCrohXu0wZDDp/ TH1SCU73TJoUAnjK0iINgWLl4sVVF4LA9cOG/YFxVWYWQLgSmNYWiM+8LsDPlV/vzJOMrgVgG42y KMsKQDwFtvCNGYPB1XvgqgjfWgDHn2EbAt+IUaNkBOZVJVtK9rgnfJ1H4T1wCTMMEKymwNyHz9ar J7sBVvcitKhSRf1vjwL0W2SakY/aBl/+T4BRfphz/UI/zSfuy4HnDLcDcMXfOSqCE24UYI0rn/m4 A+/f6LyNDt4+5nl7tohtCzvcQkODa5XxkrgVgCtZMY4a5oujdm2nEWdDnjGjACWK9O/vdA2dPy+A rSTOZDcGQnE6LB1Qm0DgSiazMObhbdv2dWCcFQoWN206r2CVoJWgj0CzXbshWEEys6xf/yuAXSoF rlypi2nIjG7GrCFbMUcw/V39fraBDlvL481YphptuPqOZsfSxASyazAAlMD0esB1zZpf0JY6DLCR u2nTJWVyCVIJRMm6Elzfeec9MmTISgXQBJ1khBncID5NmrsxOPs96GCp3m3bvqHxKZPMLF0UCKgT DlxtBc4FCtwiwNV87Bw+HKozFusN/PfUZ5KMDGlwbKhdWm8ayePKuHIe1zL1ykiz7s2kzWttpHrL 6sosEkgqWAMYe27Yc1KxUUXpM6ePZMubTcGfgj0MdOo7o6+C2UKlC0n+B/Nrd//r776ugHCPvUcI XJOlShZiXNk933lMZ8lbIq8UKYOVu4pjLami+WTQskGSMk1KdS1glz2Z2AGLBki+B+AGUqOUlKhc QgqVKiT95/RXhvaAfUB6vt1TipYvKlWbVZXStUrLg1UelIw5M0q/Of0UQHMUf5tX28jcw3Nlh7XD 8V0FEF53bl0IJJPNpf8r2dTmPZrLAxUfELLQT/V/SkpULaHXycbSFoxToQGA6+PV5Bh+ZHNzFMwh o32jJUvuLMq4RlqO24TOIIB86SIwde9USZYyqaw6sVLmyxKZ+WQiudyjuwR+xtLh+lTwH9w7Qm5B BvCxHbhdA9syUw4uM8f6yEB3CPhgCrvdCZp++cVYQGTlSifONXxcCVotgDMLzuhnARDTQ576nrKx QdfP8UWLJFnSpPL+9OmYRnG3Ar4/AFc0gHUfeghz5NfUrvjq8H1tUrmy/o3QJ1aBJBrUVACrm4YP 1zaXoHI9/F3ZrWPYS+rBQVMcEHYX/GvX4r4FHVQGQOQx6JIEbDAZWzZKjEsmlG5LZQsXVn0vA5Dy K3jMCy/AnfI+vSbHjmFWoI7yIM+PHlUQTpkcINYMQFXnuGUjx69usPQcvNUBYJZyCLqpH8HyBuie DgP8zmGgFstEfbWhZqPKcLsCV4HuXvBs8F+tAyHGtRLqQAsEbJazu/n/kznjqCuuLmAafbPPnl0C GCUri+bIwVUn0SVPxtXW7n62RX5//IHAkiwlgev9WBq4KRYhYXt/J+aC7o8pznidLgJkQndj7tws WXLJiy+O0wFMSaALGVdio3KYpq9mzScVCzG+G7CaY8rYgQU7li49rS4D8+cfUUCcNGmyawJXAsi1 mIXCMJ9GntN9bwFE/wbwmRauA351UaD/alfMUrJy5VFhHmR5Fyw4Ku9iIRFnoJWtrOyAAQtV92HD 1umLY+LE7eytw/vEhqvATgXUCQGuPtg3PMJhXHPnF3npZaeqEBDe9I3LfeKlzWDhhRmr3vAcL+uo Lp0xCGa1PHv6MSkf/bAyrmUblJW6bevK8lPLJX3W9LLhF7CjljMYi+CTTOzI8JHS6+1eki1fthDz 2X5Ie0mbPq1Mjpyso/X90X4Zvmq4JE+ZXF6Z/4pOuD8mYoyer/1lrQK/Bp0aSNY8WWXOvjkO23k5 Ql6Z94okTZZU7kh8hzKuZEd7Tu8pyVKAgd0x1Yl3KULGbhir7O3zI55XxvPFsS/qs2z7RluJOB+h rgITIyaqrKFrhipjS39cHTwF1wJ293MWhbaD28rdme+W7YHtQqDJsDVqq9ydCR84K9+Qg1EHZf7h +ZI8RXKZ9fEsZaC3XN7iMK5B4ErGte+cvnJXprtkZ/ROyVEohwzfOFzdA9xAmHYlG0ywsvLUKvCt GHQDV4HjApYRG+Ddv3/DqHxTL2PVSbZn/CjHwCk4zPML0qmzc+Zck3FVRhSM6lyw1WnAQh6aN08H M32B/XGA3wewjOnT/PBH43bRxX6qjyu/oNHQ1YHv6lPoyre/+EI2ofudK34egbuBRfYRsge3bYv5 7DNIFBoigkaynRyo5QauBIgEx3QpSIb28TssnMCeDgJE4/daDl39fVq2FBv50qVgDmYxoNtBZsyA QGBrQ74FGUXAzL4JtwV1cQD4HdimjZYjCveYD3XgLAgbAUYDuE/AyxBAWTgzQnbYka4TzJuBcn9Y AVICbcFBfLgquws5sV4OHnDF357fC54Nbq86YIeDt0QXtDyGL/30YAEefljsstiTEbhZAQ2q5o3G LdTIE3QQxOKrX18AaPBthAAbfoT5aTrKO6ts2YmloQn0rgdc0S7rQKaGDTvJiRO21K/fEV3oBQDi AgouOVhr8OCVYHKTABD/hC74S8g2uYwfv1U+/5zzl5aC72svAFeys1fizY9Ak++ADRt+C7KsO1S3 JEmS/ingasriAFhnzEM6zAE9cOBCvENsuAfmUN9VAmLqSz2ZR8WKDRXYEkCTlR00aBnYVVv9YBs2 fFF9e32+C4hjqe8umeCEAFfVA+DfDz9hf+mecjJbObErPCzWza43rK8YkGHqDOsH3sbOhw/rDWl5 XON1vYd92KL6AJNHpWL98spafiVfqUtAh2EdtJudzOfwTcMlzV1p9LzjyI5y7333alf/0pNL1e4T tk2QT/EjK0n3gcP49ZnVRwEm00/YPkGBJLv153wyR/1dF3y1QEEs07DbnytKvTT9JaiXSGZ/Mlsi L0ZKuvTphPHICLPLnd3+3+JHd4R0GdLJ3it75YXRL0jW3FlVFsHppkubdNBUvWfryUO1H9I0my9v VmBKBplyKJ/5UG8OHuP9g/ZBZW/vK3GfloXxTuBXuUllqd+xvoLdjRc2aj5uxrVfWD+58547sdDl J9J6QGuh/y/TRkZHyqZzm4S+r3S9ePebdzXPVfBxnU/o2iKRXCn5gATKlRX7ZrUz/2S+nNYLNtfg bsvi+yhnPABB/ar0+fBHBmDhCsYnlCPv2Z3OZ5kC9TsJ6jdDUgC1ZNinT5tWvgdw4yAtMpHsXo8F XPER9zR8SdXnB8xlPsyVSx9Tgl2Ozs+dJQsW7IGrFs7Z9Z8WZYjrKqDMaxC4JkWeBK78yidwJLgm WH130CBlY6NYFoBMdt1PxFK2FbF/E0v1WmACdsE/Njn0/gVsrEV90UAPgq9rMbhAaIOF8hOkEjyT RbUBXJm3AucgcM0Kn1jmbRhpfvkTuHLmhIP8KKBbAtK4bYkG+fZ0FRDUCS94Nviv1oGQq0C1s1iH 9mMdEWQfBAXJkUE3I6CR1IaUecM/SYGHC3SEGn801oFM8I97qrkc6ztViifHUpKrybg6A5bQzsVq n8w5QRcZVwJXMq5NmnSWQ1igYhkWDiHoG4qV1vZgsBdJieJYMKJ27TY6XmT16p8APlOGGFeO3m/U 6EWoailD64DKGMDsnAe0u99Jm0KmT38fTK6FF8ufY1ypuyPPKRv1J0NM9wDqSVB6fcbVAa4clBYR cUXZ5KxZ84Do6SAgXDCrQKS6CriZXmOzuHvHhgDAsGHdwsdkTNuPxcbzirqZ9YZuAKwz9CHEC5TB xotQjw1g4B51KRovTPsZLNgxo7Q0/19VQNUTUr5ROanctLIct45Lr5m9JHuB7MpGEizSR5Ms6Qn7 hJBhJeNKcNp5fGfJmjerkJFlNzoBKENkIFIioiJ0QNSEXRNk5ocY4AKwwsFVrV5uJYUfKqzAl+wn mU4CWjK1HLyVOElimXdknoyOGC3JUyWX2m1qS9UWVaX649W1e54DqnhMsLL619WqQ86COWWvtdcZ EHYFI/8DBxXQUk+6AVAn5kW/13cOvaMsbsfhHVUHBdscRIUfXQSy3ZdN6rWqJ1WaVZE6j9fRmQhS pMEHzY/rFIzSx7U8QL5xFSDjmi5jOmVk3/sWfrNpU8ncI3PlE+sT6Tmjp2TPn13BLv1z70iSSAhc F+KX+Uxi+ebYdrE//ECsD1GRbkZbc6PzZFvGwHwKFnTqIoEq66e7TvKYLi2PP45Vkdo492bPvipw VbAG4LYT7CzB3u7Jk7G65BIsavSOfIVpo7j/HOcZ4EJAYKiNBMBdLB9XnHMmgjZkZdEYkgmdBDDJ bnXOSMA5WAn4vsNAKzKol4OMa1zgqoO5cP8E8qMP7KdgisnAkm0lALXQeHDAWGaQECuwkMQFgE92 97Pr/o127eR+MMMcVdqialXHVQF6XeQMEwDacYGrcRUwOhiXAOo/s3dvZYc5zyFBs84iAFeCT2BH zm370+rV6jvFe7FeDB5wFRjEC54Nbq86EMtVAO0mN8vZ3fz/+fXvbuDvvBNIqa6z9CP9mH4C2Ma2 EwxoIrwL1q61Zdt25wPa74/dPplzB3Q5wJXgs2nTruoeQEBXsmQNHahFH9ZZsz5RcECwSVaTvqnJ k6cIAddOWDqYU1AxHf1hKdedB485QAvtMJjOdxVcbtsWrb6yyZIl/1OMq5HNfMiYTp68S1KmTI3y ngXBYIdALN+PIBnUvzWujysHcL322lJ9h3GuVoLzGTM+0DLOnPm+zJlzCO/TJAliXH0gKYyrQA64 CnTvz6fg+I46Rzfxfw58CdYZ9XHlMeaVxIS4gtFp6ht35coFVbCutJLSdjms4HRKyjUGGGtRTZlF ugmwG33q/qnC7vHU6VLrwKhD9iHpMLSDglVOBdVucDvJXTS3AsLwgGsaKNuZjeDOu+7UrnN2tRNo EuA2eqGRlKxeUgcxkQHV2QEAXumWsO63dQpc5x+ZLyM2j5A0d6dRF4I+s/tolzz9VnvP7i2vLHhF xvnHyT5rn9BlgD6me20HoJoBVM++9awOmiIg3XR5k+q44LMFkjRFUunwVgctJ+PST5dpx20dp6zy K2GviMmPAH7o4qE6uIsgnSCebGpcxpWuAizH+7YD8pt1a4ZPgRPqu9tpdCeh3cjy3pH0DlkFV4EF sliav3OH/Hxwq7Y11k2sLv9Y1hwg5G7LCGDpU8rJ//mxxUGF3HjMePH4uJJJZNDBUAB2DSpUkDpg TfHlHfsPn908uPYyZgzIlTmzXPT5FECTceVCAgbIKnAl44qPPoLhK5BN8Mkptaqi54ILFvAewd4V tLfxMa4hdhPAl3n1x0Aqgk51ZUAjqHs0TMybvqlLX3tNitHfF9c+njVLB2MdDgtTP91wLDZAJlWB K/KND7gaxpUNL3VWBhXAla4CdGswjCtBLj8aBrRurf6vLLOCWZQx1FBDv9uScbXxsjFBUIZbJdxK Ov3dulDe32nnv1u/+HT7u3WOL4+bdU2BK0gBZ3CWBdRqiX05oHsdWIDzf3RvBmcxX8xLiD55p3Hn oAXO5+faoCVG4mI0/s4osAMWwCXbbw6Oit02+f0x55Gof4ZxJXBt0qSbsq87d1oyZcpeBRirVn2n /qtFipTTrnamX7v2V+3unzBhm7b769b9pIOcBg5crKTKpk2XIddZlpWsKv1eOXCKYwfy5CmKRQUG KvHC2QLow0qXg507OfsA0zn7PXssANqYWQUiI2NmFaA8v99SMvrBB6tjDtpaesy07lkFNm68oICZ oJmBurPMjENXATK0Tn4OeH/66dfhMpBVhg1br36zHBRG8JuQ6bDIWhcsEJC+vfGs8Lyibma9iYbL C3SQEydE8AKlq4nNgXxkb37/XdwblnvREdyPRzeVh684swqUB3Alk0lgxhH/j/d+XOo8XUc6juoo ZWqXCYE2AkW6CnCZWE5bRYb0vf+9p2wqu9wJEgkW5x2ep3Vp/bn1Mnn3ZEmSNIkOqHpr7VuSKk0q ibiI6avs7cqE0h+UoJDzvdLHddZHs8R30afd7Bz1/yV+ZE4ply4F7LKni8CBwAF5frgDXHmPzKoZ QMXBZDkxap+uCkw7/9B8MJ53SLvXMfIfv00XN6lrA8EzfV4J2uleQL9VMrO0Afd0neg1Aww05pfd emmrpq1QP2ZwFl0FCPL9Nvyt8Zu0a5KyrPTrzZg9ow76ImAP+yxMEidNLKtPrJI5AK5zMDgrGgAt GoOD6IsY2vj3HxVnkBaf6+0YWBZTLzmgiHOKYm5SOKCLOpuHCo0DG+9FxoXPpwLXsLB4GVcFamA0 6YtKFn8bpnoK4JwA0fL5NDBOgAO3AILJmi5//XXhYKf28KOtxWVz+bWNhoCT9LfF/KwEpwoW8ZXN yf7pK3oP3Ay+RB70GbXRiFD+3SAONnBWgWA3veC6AdJ0CeC8q/RBvQw9mD/1UbCIRpBTZeXIlElK oT0f/vzzYiOvaMSh20Bh+LaWASPNKbR0RgDkxcbtdfjYlrjvPmewFvIiGOUAMPq4Gh3UHpA1u29f lU/GlTKuIETjmGB6AvSy0VgZME29Q4EvCwaCfeSVCD/BB63jPwc9BHH/v8EAiAB8tjjBuhVpqUxz nfLNMffuFal4rsHv7DlFlU5TBRnm2H2fx5QXmsoqKNtc557y3YHzslInToGl4XpxjE7cu/RSOT68 CCCfZVW9gnGvZUOjG3UwaY1NzL2QLOTHsjHeH+4hr5CNoQePzWpiRk+ThrpSjsnH6OfOh8fGxlaw XGpXYytX2YxcE8+cx7c3ZaQs6mh0MHGNLmZvrnPPtO4Q69nhPtMYOxpduDey4ubJ63Hlu3Uy6W61 fYhxrSyY+BsBmx2F8t+szUbeDNy++cZ5iTlnzv+W5TTweCkEonCMuGQhdR5XHZzltEN+Px5VPCES z5bAjUwoJ/fnilNotxXkEWRyvtN69TpgvEQOzI26WWVTDn0/U6RIjUFMO5TRRNuN1bSclV1GjFin pAfeH7oiF9pfBcOUV7x4NV1Na9u2SwqqOcF/ihSpJCzskL67qAfaaNWHxxwklTJlGm1HyaASHJrA KbiqVGmhzOicOR/qoCof6mRaLCs9YsQm+eorh0yhPAaQICEQny5dRgWuDkNMP2ALdnAWYuBiBZkz 50KZswP8/6x5JwS4Mo8CBWwljfhwom52vaES3H7+WXexajHqiwERzjyuts7jygUITuJXvgmAK2YT IGDj9FMLjy5UppUDpkaFj9IVnwguCVwVEAKqkqmkG0GxysVkd9RuTctR9xyoRF/Rhi80lM/x45RX nA6LrgB7A3slf6n8Uv2JGJDMNGv+t0ZdEAiE6cNKgNqqXytduCDiZ2daKYLqree3SqYcmaRS00ry hf2Fsqe5CudScGqAK4EpgSuZWMomaL0n2z3SY1IPOYYfgSxlEZjSfYG+uilSpZCZH89U3ckyk4lV 94dogOHL4Tq4bNiGYQpkWWYzHRaB6z1Z7lFQTpeH7dHbpXiV4jo7whN9nlAwy6nC5n4+V5IkS6KM K10FODjr5JcAC50xs0AG+Cayy5pLdJqNbYABfTw2wdy/XfbUmxtnDjDHzhXnnGVkMDOpoMv9asCV IJHgy8YfXmsMquKKVwSgBG+85w7KyqLhqA9WtnCuXEJ/oCcwKwsHSunXKxobTl/VnIAaDQ2nmqJL AH1C2TvQEGMdCA4V7AFgEjTy+qohQxT4ukEg87XQSEYh3r3wM+0eXECCehnwysboIcwiQBkf0X+X HyvQfQRmDuC16T176jnlKluKRrkfGOM88LNVoA359HFlXLMIAuOqHijnFEyfRRcEMq5adgxE6APX i8yYTutyUD9jn1gvBty74cBV/HjiPgS8INBKACUjIF9eN6BB4+CanuNFgL/PUBzeI0AJ3aOMnQjc Iy6v877KQFyVTRmM40PwB0MwT6ZBuwBKOhiYF55HLBlXiUPgQ3kEgtzr+Vakx8sA7Qn6+xAoGy9I BVV4QWl86Mj9VQN14wcsywQ7mSVOjX1Cex/k4MUWnx1Vf95j/tQDOugx7G301vx9uM54vM9jfzBA B5OPRb1NuagT5bGMPIY8YyvGN2lUZ7z8NQ7Tskz+GJl6n9epH/OnPJTVLSukix/33CEo63rPTvWm HflsAUA0L9QDKwLloQw+a5bFh+BHMHKx13IE7R+6zzi3YLjlgCvM9IfNNO4WbM/GPxiIRbgRoHHc FqfDcthCmNoff/D5zFRXzgCrBg06BhnTi2inLXn11cXaOObMWQgyLgsHNvFjnL6fbDTJlDI/spnc P/FEb+SdDP6undCFvxUzCBwHaXIMYG665MpVVDJkyIaVtz5XQEudCFwphy4KvXpN1FW2unWbpPuV K0/LtGn79T6XZ+3e3dwfL1WrNga4zK3s7bRpuzTvCNTFSPzdcIaBWrXaIM+JIHTGCeXR5/Wtt1az HVeQyoFXnEYL7wp1baAuEWjrduwIqM5kb6jXbbtyFupBrI11xTB3rjrDuuNeOYsLEHDwU+lHS0ul RpWUfeQAJwLYkjVK6gApTiNluuDbv9lep3fioKZt1jZZ9/M6qdigouQplkead2kubfq3kbzF8kqt 1rXEd9mnc6CSfaRtOQUVp7giSKWvav6S+aVVr1ZS68laylrSDSFZymS6ehdZSo74b9mzpY7Wb9ih oTz35nOS+/7cUr1FdfFd8Snry9kBuJoX2U4ODDOLBPA6/W93RO2Q1Hel1vyrNa0mXGCBDDIXEeDc q+vOrNNBVcUqFUMT96GysOq+YDvuDiw3bcEBWkXKFlHgWqpmKZ0ajFNmcTos+rWSPWZcgnszyIwu D1w1awd+9HGlDVZiOqxF+CWNSgwXjTP6yKyvTwum7hB8sYlw/lEwfbE2/v3zGXIze+fs1v4/Pl2v 0pYpeGVprrHkqwFeZKi3wO3l49mzQyP4ec/d6BEwmlH1ugAAGjGO/N8B5lMbSTQMuzBvK6fMYuPE +Arg0DBwSqtvXbMDkHHl/TVYfOC7997T9Fac/BQ8o0HcAZl8zgPRRW9YUaalLocx48EqTAGmLCnS 8xrl8ZoCZwBfBcHUBTp9DneJCMz1qvpeRQfVA2U5gflv14OJ1XP4SZGBpR6RYKSNHm77hI5ZDoYb ybgqgwWwEDE6Qt569i0Y91s8OIcdFD8eOoICoCB7OarTKJnaY6oCJ15XYEMQAgAS1j9MOjXoJJVK VJIXGr4gcwfMdYAI7jOegg+Ao/Gdx+OBAyEhX4IZvY58yNaN6zJO+mJZxZ4temp4F75s36/+XsEU 410JvyLj8CKJG+eH1T8oUDaMnOqFF8r5zedldJfR0rpWa6lUvJL0bN5TNo/erHHxt6/5azlhZ1Ne 917BFuKdXHwSTtlvyjZ0a7oBnYmr8QD0VmJwB+P9jEnRQ4AbSdBOyXZMldP78d5SsVhFaVm9pQzt NBQTBCMegDj1Vd1hq1VvrpLFry3WfFQubGPAuJYL+VwIvyCjO4+Gz0xnqfJgFbXV9F7T5ZeNvyhI 13hIR/0o18b0PIfASA1pP0TOwrfQxnyWZD9535TxArpEBzw9AHPR1ZWOAB/73gZ6BuBXYBmUZcpr 9ubZXUb37NgXxzrPBTbm81v++nI5swYNKcBIIByICHqfWXlGerfsLbVL10YXSlc5PP+wA5Rho2kv TZOdWP5T7etie1VP1BvWz/DR4bHuGz1upf0tDVwtC5XJRsWIf/srwDUSf5dkXMk81q3bTjp2HKls J/1HOW/q5s2X8e58SNit7rCTvE4y6Dx6+sqrXyiZ1Qj8DRDUknmdOXMflnitpXOrJoPvGkf1Z8mS B7KHI95FZWgZn3I4lRWXZOUSsZkz50G83Ooryz3dBJYsOYnVvEriWl69x+tZs+aF68JTYHjnKQBm /uHhGNXvF9WhQoUGcOMsoHm65XEpW4Jr6lmiRDVdgIDnLD/TMlAOwWyfPrMxfqS0bNz4u+p52zGu poqwvlyn3riBa0WrIiaegg/m57OFQIvsoDKHWAFq6aml2uVPUKbXcG/ZN8tkxsEZDsNoYXEC/Mhc vn3gbXmi7xPSqHMj9T/lNT9+HOlPwEo3AMrg4gMEcgS+XFSAc8c279lcZn4wE03Jbu1qJzOr01dZ kcqMzvtknjzZ/0l1W5hzcI6CVL/t17y5DC2XaKUexl+WZeB1DgoLt8Jl0s5JGt5a85YMWz8sVuCC BGGHwmThsYWhOVipt/lRJhdgWPfrOgXUlE03CNqKIJyrfU3bP03jM+5We6sutMBFFKgj4K+Whe4N E3dPlG2Xt8k8/JLYzpKvBGyWeXbffutMB8UBO+xWJ4A9d87cjWFgY67cPkemTl6tPYMddLsGcA39 0RJoseFBQ2D7fBK67vfHPmY8gEP9A+cxGw52A/GYgce85pKhAJgNH9KFZDMuZQevG4Abyhf3mY5u AZS5Dr6q6dClv3TQIJ1VwDDC2hCysTF6Uq7Rj9dMPuaYjvpssNzX49OB9/mFTnvg/rtYfITs65qR IzV9gCw14mjZTN5mz7QMNxK4XgHLQVDVuVFnRdMvNnpRmS+CSANKeGyBOVkPny0i7pyZc0Ip1Hk0 0GTOtk/ZLqXRQDep0kSWvLl44+blAAAgAElEQVRE9s3ZJ4uHLJbGlRtjtYkysnOaA0Y0PmyRImkK 0NBTlNVT2T5L5RE4Uf4T1Z+Q159/XQa1GyRNqjaRrBmyytLBS5WF/A0vqXjjYOnIIR2GqD7RW6AX ns3cV+ZKAUzH07FhR9k4dqPsn71fpvebDjq/ktQoXUO+fu9rBekW88czNuXlsQnUj+znJnQbMt/c eOldirykoI+AimmY3sI65wRpKcDCMN5nYZ8pmA9gIvWf4LtXr0I9KVuorEzqNUn2z8Ja1eMjpFuz buiayCeTekxSfS9heiB88kujio1URzKT7ueg4A+6fDDrA/ie5FD7zn9tvuyfs1+m9ZkmNUvXxPQb +bSs1FnBK+oPGV0bXb8NHm6gus3oPUOfOZ899Q9EBuSi/6JUeqCSAsrIaZHS54k+WPotpRyYiXni MPemGwgb23CvtkNdMM/lSczD+fpzzrNrXKWxPrvlQzAPHaZCOrP+DOaVK4KulOaybcY2aQeQkxEr KH21+CtlXzNh9aKBbQYqI6v1EvKj4IfI+jm5+2TVnYCYbLC579blVjm+pYErqva1tr8CXP1+p91k W8U2k+0Vj3ndacMwpRaaAAafzw5d5322jSAFYsUnIGX7z+78Vat+xDKvR3QuVcrmNcb34W/OyDdy +L6IG6jL1e6zW55tfiT+BghEHXmOfsyLbXxceSyDKdsfdWdaJz31Y1rGd+vJ4/gCZfIddUu5CkjC NzdwrSQOy0rgRyBGoOXHzwBMXuMxr/GeAZ0mHsEamU4CUTKW9Bc17KcCSaShbHbPU4bKtgBgEXiN 8ZmO6c01BaHMLSibgJZx6ALAY+ZnZMfVh/KNnozLc+bDH90D4v4IkBmPc72Gyol8VY5rb8pA2bSJ 2kXgGoAfdQ/ZA0eUyfyoo9HH5MO4Yfglxe+0fQoPDe8kC+9AA9z4GNltTqaMg+o4WT8GC8nZszEP mHEtC0ntmBBz9/Y8MuW/BnB1gy+CxIDPJ/wDdV/nubnGvRWJwVz8Y8Ux45s0cc8NqOOe8S3EdcsJ Xcd99/W4xwpe4YbwLZjUI2BY2agYWdyHQGxQT6OfO39zzPgqLxg3Ph3ccdVtAPnR/5eMMRvguOmp b6zA8jDcSOCqwAwNeJcmXaRgjoKSC5ODn8bk3oZ1VWCDFwn+ZqQaGIZi+YrBGbgUFEX9Bot3bMkx SZoYcyh2B/iCHPwVOywr9zif0BXz7eH+if9r7zzgpKiy/a8oJtTVp6uIWTHiGldFEFF0wbSIoGIG EVd5a86uuyCuKGsAzJEkRpLhIUpsERVXZUUEFHXBHP6u6Ft9zjBM9fn/vqf6NjXNwBIcHODWfO5U d9VN9auanm+fe+65g2d7fn3e2Na/3tr6XdXPLY0OVfrHob9LmbbLFDpiQ3vjPhUWy3hdM0y+Gvcp EG9dKxtT5sCywXobyBwvM2XIM1WWzh5pMOZXZGFR0DwbfsNwd7Qe02eMwyAgp08GhyD9nVvHlh1t K/ncVU6otCQ33+rLdWWTD+Or7AgFGN9Cy1M22KSBDbxKD4+ad+2U3yFKBuTrOlzn4Lj5xpsrZMTU 9HrV5h7b7WGtD2ptFZrw4hrpHxp6AqmTHpikYL51Uz30pYx6z2x1pkMmeYMbAeCYvJLYzMdn6ptP PbvpnJv8OrGI+nWpnD6v7WEFfAecZzw8Q07gqd8p9+n9h9+37etvb907dLfdttnN5r40V39wqV8z Og+6ZpCcrrdJ9aF/7+vLjKy5TRs19WN86eBZyGrjz0Dh3v0oq9IGGl6d8qA6obLh3t2pIVbu3bzX 51nPzj3TZ0dM764iM01+P63thOYnyF9II1pb7WI9z+npGqEt1ww0Txs4Tc7tW/rzibUWXYL2pf2p De9XNXAF/Ei5HJ9XVV/PP5ZkYDObN6mmbAqSACwACQACkdSFZTNtq2o7WDOrT2m+6s5R18Lro1x1 dS687/OvNc0DDKd1zC9DnuoSn/P8L1wZwLVpvqkPuY+qHOXgmDOBX368fgtek3FuJc0eGy8rKJbT cMwBUvk5xlA5idfheMgXYJP3bolcSJlsvlAH/aBe/E4XqLua/nibhePUQZ0LS5z361QbXk7v2Ycf zvvxTDtV8meOF/MW2gzvvbyOja4c7b7CA0z+rlhc9WP6mE7y+p+d50VSFWBx9WAJVOKt1q9v8nUx +/xzfSAXtpUJYBcDXKv9Y8zlrDYcByADRGLh9G/5gsii1XY59dP7oHZp3/uhdrN9W0Ar9VsffMsB XMUaDKWfdsRp1unoTnbNadcU4SDAw6S7Jtk+Gm6768K7HDz1pdDmvTrP9tcQIJYz+b37MD6Ak4zT 5CztHS50/AzFbWy8W2OrnKQ/JoFrfc247Xtl3xSIsAbqnx3Hf3rhJ4eykT1HWsWrFf5+ntYr53y9 devZKE3sAHiwBIY85Zp5DPDS/hH7HWFnHXWWlb1WphAU61lfDdVpxMrIA6TRL/qU5BIHRKx/Fx1/ UQrQ6q/3Q8+sZZKDo+AQFwCso7hJHNToIC19lk5Ao0wyPpGzcrnWD97dBl490K2Ikx+QaUhtA7MO hIJlhueBXPpBf9zCKujGNYBr+mjIR14Gq+XRjY92K2QAe9+/kbcWe7fQ6h1nmuYnyLG63MHW9ZaO 7IFyhtvfHyR6lDXLoVqg16FVB814PNrmTZ7n/Xu2x7Macsi7xoDgX874i18X9WLlLBtbZt/I2vXq XRoqyOn+SJPq9PFjunc/aNgXzUdr7faKV+bfO/q9lkIVvf3Q23aBfBDbNmtrinrj145mnw7+1Cbd o04LnneRD+SNnW/0Z49+u/b60gBo89y1O6Sd4uZ1dkCP4KrntAa2Sv2JsjGaRGhEQvVh4QSqxo1b nAR0kkrzLt1xfE5Dqr7e0E6of0n3oXzpflH1hLwhT3hfuv9P5+fnR1+izTCZrGHDWjI5K30UFut3 1uLa1Jq6NXNUXuAaf2pUAWG9W3aLFlfAVVuiH9+AVzb2AeTSI/jYpACrcE0e75QQUGEjLx8GlAt1 hHMryj5cb7C49u/v1kr58sz/w1vwg6rWnXNQFQgm+pAgAYV+bDn0fanapo+kXM5MYbpqJKqAA4Cs hWdoIgJ+l1gst5cvWPKq4Gp8ZQo+AluAkGHaZ254xsEHS9+sx2YpVMN6cgb+0ipfko+mLCSmvgbA 4X2lJip8NuQzq7d2Pfv4iY/d0riZ1ilfFLgyLA8YAmYacdHKD98pJtl/2axHZnmf1tUMYgCJPMCf A6CuoYViRt7U+Sab2Gei1ZfrAGUD+AFfoV8Or68n9owmWmyhiR6JAqxzLhmnP3b1P5sCPAF6G2sZ yG+e+cYtr+8OeNetgQ6G0mLkTSN9GPyr4V+5hdktrm/lbUf53QHQea3R7nkL+oT+uPuEoA04u/MC Wa1nmd+HLLh6vwSH32kSChZp6q7UakSlenMNALFbcwX4if7puyV7dJlCXmgJQc2uTt5L3Le0xb4t HNjpE5bZDx/70OvGT7biRX0rx4KLVVgaokeA16w2flxt8qUjgCu+0olCEIV7B/yi29fDv3YXB+DW XQcUYsnbELMC2LS16za7uh+r/utpSb2fHNzxa8XdQ7HJrdmezey81uf58Qiu0qwGtiy4MjmLyEcM 2zMszpfumGpGA/RlZO0djRbtvPOKDa7NrJm+/87wOKoMl8efmlMAtwJcFR7Rj7sKlIJr+IzIFwCU fYDScI4/cs2OVwy3FGBZxi5sif6HZAGW8ivKVgquhMzCN4hhnPhBVnMa8GFGYqisYcMaBFeBacdW HRWP7Hdu8WNYdrAmUuCXmOQSY+ITw/OfDvnUHrn2EcMXUavR+fA2Pp+4FTArHXAKcBhe+3FBCu4B DGMznE356sAVyylg89LterA0jI51tWximVZ/IA7alg43AA2wDNxSlw+V68N+5iMzfYj8s6c/0xJr F9pRBx5liVbgKQUc+gUI0meuB6AGQhlud+jLqc5McnAVmI64cYRbRfG37HhkRzulxSluMabPeQVT b6xJJrece4u3x1A9Fs85I+Z4GSZFMVxP/UGf0AaTzRItcYlF9NiDjjWbrVnVLU6uYnF1+FYbz//t ea3coXWOZTUO4Fusb3zab94DtFyj53szbzdrssx+O+3nwAcs8kVg3bXWtXf7C77VL/cjFTgO/+tw xZXbSOsdb2antzzd3hkgYQMAS5NiWxl9/Jj+4eIqQJ1YaMO9++mlnxTQ+fcKv7Fd6s4gALr30nu1 xNz61mDTBnZO63O0OskH+iBR3QreDri6xVV95MvE+4+8r1VM1rIp/aZYfnremipGaJfjukSLq251 TW1ZcMXiSsxuJr0OHhxTTWtA1B4YYvvt84qOkN7huXNXDFCYa3O9w22tre2vHyyBj+cft8Hxp0YV eNKetGf001s/iwTX8IEBeIbEHztgGjaAVeGSTOGOFFIjDSkSzpEPEAxl2df2DbcIthDHtXfvdAgJ C2xN/zHH+s3wid122xoGV8EYFsv8rLy7CjCBCShM3ki0tu6ttucOe/oQLzO/ARv8SO+55J50opag z2FwvB7mnB6UQgJqOA78AJ4+KUhAuqniH1YHrkzOAswabdfIIxMcvPfB7h964O4H2oQ7JzjcBECa ePtEm9x3svU4p4ddefqVtvWmW9sVp1zhvpJAJRAIEJaCK33zvgpcvxj2hYPRVK3o49ZZuSWEvod9 EVx7jHA3BoB3ygNT3IL5/YjvvU/vPfyewxiTs7C4Egbng0c+0JJo/1IszDUUsiIFxGrBFdcB9RMY PmLfI6oFVwdQDesPuW6IW0VdU11HKUiG94lcF8gTrK8NFUcTa/nEfhMt1ytnLz/4st+Pi0+42Ifl 3a2DSVC6jz+O+tGG9hjqkAiAP93jaX8O3DJcuK9BG/YBXJmchWV1j+338OgN4d41btTYXr5bll75 57pLh+B1znNzbFDXQbb3jnu7Vi/fpQdEt6Bhg4ZuccU6jW8rrhfXnnqtt18xqcItrkQ7CF9IwvVm +1MbXq/IPq7BSMFEU91+D4kFwMa0fDRgJd7VVsubJhH79ovGcU27sFi/g6vAhXah/6Na29a2Ovk6 Fn9qXoE1FL81tEIYMraiq8Ci7h7wSQJgwx8++QHY9u3NFD/UfWFZeSq7BYDlGOVr6xauKaycxXLF DCPFD7Plp4H+idScq4Asl1j88BHNa41xdwGQ5XPmwJluVcR14J6L7rH8B3n38fRheFncp/Wd5rDy rQJsM3vewSz4Q2rPeyY/+XCx1v52y6b+IS7KVYAJPncoXuLf+//dXr3zVfPZ+QwnC6qwMgI/WPYm 9Jlgs5+a7VbW5ns2t2mPyz+HPAK8/lf292F7/D3dWimABnIC6HAMf9txvca5S0H52HKvO8BeyMe+ CK6yuNK34BqAf+zNf7jZQRO/y5a/bekwP/vx2e4q8E6/d6zyjUrbrv52Nvi6wVb5emEiVE59zPQn uAocqBWF3No4e0FXAQdQXRv6EbWANkpdM8JQvrsPyIKJiwBD9limca34nUILNVNQdIbbm+/d3A7Z 8xD/kjBHS1zmX9SHj3xJsXw6+OkeAZLXnHqNRy/4cfyPluTmw3BWH39dcBVYf5317e6L7vaoEty7 GQP0Aci9e1XXLIu8uwaoX/TNJ2/JJQBL/1477mXJlMQnX11/1vVm/zR3+aCv+MO6VX22RrPk3nDJ iZf4sbmjZOHJ6RoF6KUgn+1fOEdejvszqn117zV5N71+5eX80qYVGVzzkobtp598JU9fBADXt5iW nwbTNbpQJrd9tny4IenbWvtbn67etx/sB003mC73fv1oWdL4s/wUwD0jfIEI92OxHpjwjAWraihE 2CwtJ6qYcKbYdGlYrfLycFaLqsjYQRmVr5XPabguwPxdjarGD7Hlr8H06TULrlj8Wu3fKgUKDdWe 2PxE635Wd5v58Ey3qhI3FEvY/Zfe7zPrfeKPZqbjAsDEGX1Cua8poAAgsHff0+mKwnF+Hx8u9ln1 giMmZz14+YM+0xxfSCyKlTlNViq4CmBNxaILiAI91OUAKUAKE7gIzcXs9Yf/9LD7qc4ZOcfmvijr pcJSfTbsM5/J/tb9IiMN7QM5iayQAVwcPsVU7Zq3s+ObHp9OEhtTmNyk9nzoWtcAuGTBFf9Sdw2Q Do9qhR+iK8x9RRooPBiT19DnI8WMXHONNW3KQ/o2oGvvpLiPh+59qOtDu9RHP0juBypIBESxzE7t J1pUv5ichatD5ZuVnge4DcC81w572dWnXZ1OztKks6A3QOYQrCH/7xXY/dMnP3X4bL5Xc7v61DS/ 6wlIkjQhC4smoAk0PtFVyyDKvaFigiZmyW8YP9cfnvvB6qxex6Y+qH6pjFuvS/ThOvBxDZZwdAB6 w72jX/QRLZ/4yxPu71yRK0ze0vKcWKax7M59fq5b1/+mIPHlL5X7Mb4Q9Lmij93a5Va7/YrbbSfF 1SQG7pRHp8wHdz0q3tZ47dVGMfEeEOcZ4jUJYKb/OSXeq99V3nP8Z0grMrhKgbhFBaICq6IC+bxD qCVJVQssAEv0AZb93XZbs1699M9A7mpBIyyblGGjjrhFBTIK1JzFVXwHYAFLWMXwe2RIGf9VZtB7 CCJZWLHKAZw+Sx4oECS9crfWAa9T18bfLhIIwAIgAAx6P7rXaLdATrpXQKP8wMKWm2ypQLpPpmGT OEbdSkApcEj0gMrX0olhAcwckFQv4EgeAtHTTwAM0APCsMwRhYBrwGrLhK6Pn/o49e0EcOgX0CZ3 hVu63OLD+98+9637U7qlUnkAzs+HfO7QA+w6uOq6n7vxOdtYVmMAEgslCxswC75NkzZa8u1Ad4cA lJglj1V0Wj/5tcpv88cxP9rmG21ufzrtT6nvJ9dLP9BPun898mu3anbt0LX4pYEoDPj12ofKo7bd UsleaeKdEx1yn77x6ap6c12C/dcfeN02rrexvdH3Dftk6Ce2Tt11bPZjstBqkpx/QRBIAsy4gNx3 yX0O/QB2k92b+KQwrJ1uHdW9w9cY6zpfWtCCe0e4qy+GfFHUJ9yXEA5r3G2KEydrNjqFe+cWY/Wd 58khWm24roJ0fKZxZcBdAh9X3FKA5ktOuMQnYp3V6iyPWtHpuE7+BWF3rVE/9s6xVqmlOhOtWw+g M1kNPb2POfW/ANMstAAYm46hOc/Xe4oJ6m3rWnBv4IuZ5w/lyLuMaUUG1/B/hz2Giph+GQ2y90FP ZK3fgoWPvcbZ4s8vpEC4D8v0wPDwhRSG26mQDwMmODVqZFrCzvLdupl98ok3pRIp7JInlPUzteAX /YkfZL+YBjUCrm7JE8ideOiJ1qRRE5/44pZAARa+pljD8AUFEgAoZr4TRxS/VbfwCUgeuvohrafb wC475TL7x8B/2Dcjv7HJAyb7eybm9PtTP4cuzy/AADyxpg27dZhPAmOFpbG9xjqU0p5bU4FQWRoD RABBgBPwUcyjtsvHaOhCVjRg+vTDT3dYZMITgIrPK9DY+4Le9sGT8jkd+S978Z4XrX2L9h7a6tV7 VVD5fNhZdU26e5LPYP9u1Hd+vbTpVkb15anr0zix6OWQKy2wSNOXR//8qE/Qon9ETuDY230lqjQi vTPwHY8ucOQBR9rYO8YasEzoq3svu9djq7JAAvnKNPsfmD3psJNs5613tuG9hrs+w7oPMxKTqrAg D7t+mN+Dc487117r+5pfF4tAnHf8eW7N7nleT49xizWZOKnAPVoCaCQHSoXmwteUvo67dZzNGjrL /X2vOu0qY4LbpAcnuXa4C/gXC+lEmC1i/X4/+vuiPuG+EFWAujxkmbTM3ju3MmuiX65PzqG+xx96 2Ff/85WNun2Uf3ngSwZRA5i0R1gu/wKkOui3T8CT1rhuHbDbAWlUAXmwcF+w3NIf3Ea4j35fcgXL sHRkUhruHX4f6L+iKtDHL4d+6fU+XliK1MsJbP1aVD48c0u7X5HBVVcft6hAVCAqkAIoOpRaYDk2 aJAlO+1ktoE+X7t0saQAsJwqQmIAWPZxW2UVqBFwdeuTwIxJV+5jKWBwq6JWWnrsz4/ZZe0vs+Tl guVRMDv2trHpzG4BKBDkgCKwIDD+5adcbscffLztu9u+1ubgNgYEfTPiG7eEAgfBsnXZSZf5eWac A1ZMpGL5Tyxz+No69IkpsyDhZQUXQGk2T4BUlpClTZYUzSuKgV+XIG/CXROsc+vOHsN031339VWb cF3AJxfgZTUqrLQVr1V4SKpuHbq5ZdSBfrzOq0/km3z/ZLf8OYTpugkhxdA6MVWZhEWMVsCV16ce cap9MljfRGXBdX0ETfjRslwuq0bts8s+1nL/ltbh6A42+SF1UvphLfS80njA1QM8KP9xTY5zbdCH hDXXv0Aoz8zHZlrnYztb20Paut74J5/f7nx7e4CAWVUmucQXEPA4rLL8+nXk9LdD4rp0P7BQs3wu gIcVGit764Nb+8SsNk3b+JKyriX6aHIUkHh9p+ur6BPuC5ZwtMDSjLU9e+9o00NzSUfCih11wFE+ 5A9YP3DFAw6W6MkEMuLlEs2C+hxOBajuTqLYsN06dvMJfvNe0RcaWeivbH+l+8cC+2gXni+/Vmn0 ws0v+MIabt3WFwOsr8QrxpUC6/XrWsP+7KPPLvY1lF9aYA3lIrjqGYtbVCAqsHIpAIBigS2AqN7p f6M+1I880vJM5BLA+rKp4aqDlZP8hTLhVNyvOgrUCLj6P9txElHPnw/l8zqn52ycHjaOCW6K/9DH 670AwCfL8DqXJocgjgsgOO+WQVwFsJgJcP18Tq9JlMOahhVNgFVMasfPC0gcNDL1h3a8bE7nS/J4 X3EFoD7OU1bJ4VXQ6P3Sce9XaFvvizAt4CRCAMPTDIMDa1XAi/p0HX7dKldsg2P0haH/Qpv+mmOq M/TXoY086KFz9MPhCr2kcbEfOb2nHnQv1YdrU53cC9cz6Kvr8+sK+uu4n6cerlV9dH1yel2S/LgA D2ul97GgFVZt7wMALKszUE4MWaIQELO3Wn2ou+S+hPbCxDHXlD5JB1wLvH8q489X6C/XNU4pV5I4 T191nr7iJnLD2Td4PF9cMqpoSFnqyD6rlOee0EfuBed5ZnifU+I8+58hRXCVjnGLCkQFVi4FAoCy F8BmJ2QlAGzLlmkoksMP12cvH76FjfxAbLZ8OBf3K70CNQKuAUoBKQeeXAEktOeYWxhz6RAz/9SB DwdCveZ9KO/HZfXCcggshXz+PpOPMpQvTQE8OF5dGcqF9sgT2g370F54zx5g8mtQv7y8+kU72fJ+ HGgBZgpwmIWYUB99KpYrQE6VY/+hf9RDeZJDsPJjJaTf9NOT8tCfoHvIH/ahL+Qp6q3yrnfBYhvq Iw/leM/rbNnse/SgPY6FdtHC6w86L0IfyoX6aC+0E/bF84VrDPoDkaG9kHdh/Q3ns331ewR06vOy FMxD/nANxT4U7kHxfPaeFq4j5F2WfQRX3Ze4RQWiAiuvAnn9ryIVrKp6lW4sudepk2JebprGggVo C5uDroC3CLDhRNyv1ArUCLguyz/obNkAA+xD4nw4ns27PF+H9kOfsu9D/wI0MjRdev7n6mu23tCX 0P7StFET9ZXWGfr3c+lTWn/2/eJqQJlQDtAN0J09vrh11VS+CK4r9edwvLioQFRACjiIlgBsUZjP PktdB3AhwBdWK5kkxZN6AcAmhSOhjuz5+HqlUSAF1/a6HobVX1AaG1PUID4Dte0ZyL8g+wNuIQcr tVPSlq8o2iTSA/F3VCAqEBVYGRQQeBYhFgssUBo2Jm1ddRXLwVl+t90Uv/Lh1OIazmctsADsz7kF IGYf+kV7MS1XDVJwPVN3VvFL8Ut0/zyGS2OKGsRnoNY8Ayz8YLP0d3mYUlslbRFcUx3i76hAVGAl ViDAJ9bULMDOVXjE22/3MFq21VZm116rJRTnzBeCvJQJsDn/zLK/Cn1a9ppiDUuhQAquWHE0Cdy6 KnWPKWoQn4Ha9gzku+obfi/dl92VTlTSll9B1pxPext/RwWiAlGBZVAgAGgGYPWp6AsXGAC7117p ilwsbPDdd/MbKgXYZYHO0AdqHzfObMgQs6FDY1qeGjzzjFbOWls3YLWYogbxGajNz0Bea80X+/dH 3SttSYWsCXGLCkQFogKrkgIBHtlnLbBoMHJkupRs/fpaRejUdI3poA15Gd7Plg/nFndPHZQfMyaN dqAY3grkHdNy1mA1X0mJEEpTYooaxGegtj4D+Sn6sFRcXPdzLRgTsqFjdCZuUYGoQFRg1VEAgGQL ABsmZnFsxIgUYNdZR6vvnFQVYMmXBVjyL+6mZWl9e/RRs9VXN+vRwxdOsIceMuvbt9akvPqSTbWp b8vUl/79tVzmtm7DWdxbFvNFBaICUYGoQFQgKhAVqBUKFCdwBSsqQEoK2z80o/WUU8x+9at0n8uF M6n/a7CghvIBhoFbUunxkP/JJ1Mr62OPyZigNl5RMPBJmiRUTcrrGIlz8xSLtkIpvF9gr1Bffp6Q X8pfqXorJk70Y2HPsbzOh3pL97QxT3mIg0vivZcp9CO0WV1fOZatL7QVjmf3SaFvHm9X5Tjn15ft L68Lyfus/ixJX6jTk8r5whR/V9D2hg0Frro3xn2OKWoQn4EV4xkoGBos7Od/FMdXUYGoQFRg1VQg C5nAa9YCO2OGWXuFT1pjjdQS+9xzVTUKQMrRAK+8zkIw78nHFsC1X790YQRcB/B5XVQaOzZdBeyN NyzPa1I2P+9zOU0I1qzo8eNTdwTBob2plYOAY9JkBYYH5nTe61D5fKGORH3wY8Dd6woTRVkS9QGM o0dbUmgzlKnSfqYu6qE+h8UXX1ygrTznXlIQe+rWea6l2Hboa9jTZ/JxbVyX+l/sa6bN0r5UeU+/ SdSxww7R4qpHMG5RgahAVCAqEBWICqxMCgCgwGuATa5t1iyzbt3Mfv1rs8aN08lV5eXzrxpXAMoR M5a8bFmoDXUFcFUsWffwckAAAA30SURBVIc7AZhDFWBVkvJAJsA2YYL1Of98+yuLKShPUjjOuYTy AsGvhg+3rmeeqVUl/0erOr5mL/ztb3a1LMYXtW2rpcaP1xLmJ9q4226zckEo+R1AqQuoA1IFqIP/ +lc75sADbYcttrDtlU4+7DAtU39XCrOZMqX9DO/pTyX9FWxO0KS3j594QitCTkz7qLYqaUvtvDtw oP35jDNsFlZnnac/d1xwgffzwkJ/z2/Txi7Qa/L9S5Oq/lfXNeqWW/za8qor9D+0vdA9/SFJQ9tx xwiu/mDGX1GBqEBUICoQFYgKrDwKZC2wSVLVevr992ZEH9h4YzPBnfXqZabwWsXtgAPM1l3XDChj C/C6FOAKlJIAu+00aWw1TWS666KLtGz8W1YBgArg5hVg8K0HH/Tz/6TdadPs7KOPttWV/5D99rOD GjWyZvvsY/+1wQa2y9Zb2/8+/7wlArl5WD8Fjh8OHmyH6vyWm2xinX7/e+t94YXWWyDZ7tBDbVOV Oeagg+xrwWOifnh/AEdgUPuQeD+Pvspq2/nYY22jevXsw8cftzzuBjoObFdoP0/t7cOQvfo2ugCi 1AuwNt1jD2u2557WRPsmv/mN/XaXXTzfjP797Uf1dfONNrLfN2nidc5T26EvoQ/V7uknKYKrP47x V1QgKhAViApEBaICK7MCAWKTpKoFlrBZ991nJij0WLD332+GhZFZ8ky+Yo87ABvQGqyzIc+SWFwF dr/RognHCiDr1Kljr9x9t/uTAp5AIRbTd9TWumutZR9RP+B6zDF2DJbhf/4zdTMQ7H4/apRtsuGG 1k2WWayiwN8cRVOot/ba1lKAWwbcBbcChulV5vNnn7VtZWXeW9ZKrKW0l4VWXju0AsGq81yBb31B /adPP120tnLeQVt1X6uIDfW1glkDQfLInj29bxWUxU2BNkm4K6jfdwig9915Z/e7rZRbwRzB+h7b bZdel/JjwQ3tVwutuj6H1giu/hjGX1GBqEBUICoQFYgKrCoKALBs7IP1ND2SRgcgFizAmk3A6znn pLkAX9LSuArIarmFQG9wt252+QknuGW0QjBbISBzi2sBXOvKDzeAaydZXA/be28rk9vAD4LTfxMt YepUu7BdOztw990tj++o4K9N06a2D8vgChbzgkMAkzpJcwW6wOp32m+43np2w9lnu98soAkwBlj0 Psj/dKrgGUvqW0RJkH+tW3QFj5xnghXHOf/cTTfZlptuas8SWUHtch4gZk/dWGa/l1V47bp17W4s zALecvqia/niqadsDcH7qJu1gABlgV61sdBEPyO4hic17qMCUYGoQFQgKhAVWGUUCNbXsAdgA8R+ +KGZLJcyiabWVqA1vG7d2uyLL1KZHnkkPa/hb6DQJxItBLyK1kSBaQOB3v2XXurwuZmGzC8WgNrb b1v5Cy94PVMFhUVwnT7dOh51lB2J2wL+tlgwsWQqfyNZLE9u0cLDfE0rgOb7LH2rvgQILLarfs3F JUFlB3ftauvLBeIHvU8EuGGYnrwAZyIQbrX//nb6737n7QC9oR53IVD9DRs0sLNatfL+rCPrcLC4 OtgWQNjbE6jecu65ttH661u5jifqB3U5SOsarj39dPuNJlpVCpZLLcALACz1kqKrwCrzZxovNCoQ FYgKRAWiAlGBUgVK4RWQBFbXXDNNRCEgyWrox3Ep+PRTM6ISkG9JXAVkcd1Kw/V3aeg8efdde0kT n7BcjmCoXVbIvPxGcRVYU6DsFtd33rEuxx1nO225pfW5/HK7rUsX6ykQbC6rMH6jH2vVrrysr0ze 2k9D8e42IPgE+gDELPwBqImOlWuPj+zw7t2LVlLycT4v6y8TqFaXtXmsJoAl6hMwynl3EZDLQVdN svqV/F7/T8fKda6e4uRieQ0W19C2g6iAFF/cW9VvoDkANa4BibR4V9px/eyD+0K2z1VeR3AtfXLj +6hAVCAqEBWICkQFVkkFgNckSS+9Zcv5vq2AaTYFy6ssjvbf/52eYzh9CSyuDK3fJ4trHl9QWVCv EXRuIAvod0y0Eii+rYUM6gZwFZReLJcCrJo7bbONT+zacautfMIUE6C+xW1AfrBYR7GSJrJwup+p oLIK9Ok9IAuc4ke79Wab2Z0aus8LJkN+B1T1Z6iA9teKeVsmuGTWP7Dr53SNU2VdBjSJdIALwf+p z1hv3eLKcH+AXMrq+oaprjUEwd8J8vOylHr7hX4AtpWqc2ddT+8//rFKX0r77u8juK6Sf5rxoqMC UYGoQFQgKhAVqE4B4JWNcFi4CwB599xjJgunaVa+L2CAFTYLsrxWFIAlAVcsroAr4OchrQR8TFQ6 4ZBDzBRr9h8PPGBrysI7WzP5Ta4CZ8lVoOVvf2smC62HnJIVs0yW2TYHH+yW2EoNuZ8nFwassHn8 UQvwmLW4OrQGYBRA4mfb98orU//VAJv4uwpkH7jsMttCk65C+Ctgcx5lCy4ChNbCsouv6o9MCJPF FR/XYJ2lLe+D6tpXPrcdjzzSra1Zf9qQB//cveQqgMWYCWTuXiBYjuDqT2L8FRWICkQFogJRgahA VKAaBQK0VnOqeOjbbx0sbdgwM4b2Dz98qSyugOu9l1ziMFcm+GP1qffkL4slc4yG578YOtRfZydn tVCIq0RQOldw6cPtKsNELcJk/V1w/ZoSVlnOM2vfLZsCQACRBAgCk8DnNFlN8aH9RKGzcE3wmKw6 72Ap2Hzwiis8UkAAV7fIypLbvUMHayiXBfexnTLFjCToxuL6KjFiZR3GncAjBGCdlSWaPn1MO4VQ WvQj9MnhVuBKSK0bO3e2/CKsxdHiWnwK44uoQFQgKhAViApEBaICUiDAa3AbYMUsrK9M2kqSBSVa Gh9XAWfW4gq8zWPSlKC0j4bLN5TvKDFRgUEP6i83AI8qIHCtECT+pAlcgKTDpAAVX1P3VRU0bq/4 sN0Elya/WKyhDqpYSmUxJf9cLKuCzdaKn0oEAgCU4wFsHWDVv+nysa0ry/IsWXwTgS0AO3PQIIfp QxXd4Eq1cancFy4/+WS7RIshEDGgnazFLwpegfAwCYwQXrgzhKgE3k4BpOkT8Wf/pcUINpa/7ZuE I5Ml2WFWcOugWroHwElxctaCz2I8EhWICkQFogJRgajAqq1AXgBbJQle86SyMssLZvMsECCLZ14W zMV1FcDyuI38S93HtTCsD9A5iMrieLRWu9pKPrCbyscUcM3LVQBw5bjHcRW8Mkxv771nT2l1rDry H/3g0Ud9iH+SYsJitcV3Fb9XXxa2AJ4ejUBD8X9QTFjcEL5WTFcWC8DPNECiwyR90XEiH1zF8L36 SL43FduWyAa4I+yn4X8mhpGYEAa44qc6SIs5JIJP8s9W3+nLK3fcYfnMBK8AyX69AufHVAZwnStI TUiZ/oR+FfcRXFftP8h49VGBqEBUICoQFYgKLIUCIWzWEsRxBcgcymSRZEb/nYoqECyegBkAOU/A 96WC/a+nUFxAX9ZVANi9+5prfBLTnfKPvbh9e8/D8q/uKysLK3B6h6AV9wHCZI2U28FsDdN/pH4+ ef31dpigE3/UUbfe6nFfK2Vtpe0Ak0WAFqz2l/8rUPxv6gV+lc8XFgCcdd7hWeAJHJMv17u3h84q 02QtYrWyeEFjxZgln7sOCDpDO+jgPrO6XiaqEaUgaBHyFGGVdkOK4LoUD2ssEhWICkQFogJRgajA qq3AUoArQOZQJghsqdn/Q667bn74qAKQue+qwJDFCfD7/BJfWkFgL0UvIGYrrgDbbr65p+ZaTnUA Fk4Nm1cW6vahfs3kf19D/O3lf8vKWnVlDWXYnxWwLj7pJPt/GpoHNj2vgJCoAUUw5L3qIlYrs/0b 77abHbDrrj78T5gsrKSUI9FXYLtMrgssQzuhTx/3n6UvPwh2WeqVCVt5XU92+J/63corS3KXwspc P6ndSqVE57J9WeA150nRVWDV/vuLVx8ViApEBaICUYGowBIosBTgWoQwwEsQaPJPdQgrAcdglS1a OQOoycXA3REElL4vWD4dhslTqMeBVFZdgPff8sGdofioJIdHHaPtIrRmyoXy7DmPS8NHihEL8B4g l4B/A6wFuKTNkLwcFlldj/elUD5cYzgW8gO25crbVj6x7tuq0F9ZkM72Y4HX9JcUwXUJHtaYNSoQ FYgKRAWiAlGBVVuBZQFXgV2AuFIwC5CHRRLrY3gf8mf37loAYJIvU6fHXVV5B1UAL4CuYJFj1Eu7 oe6F9SFRXhO8srrWaUccYW8pRBd1ubVU5UO5bJ+y9YbjIR97h3LV+YlcF9o2a2ZfasnXLLQurE/F Oug7KYLrqv33F68+KhAViApEBaICUYElUKCGwDUAWoC+AHLZ99nXIX/p3kEWUBTkAZokLwewZqCz tFx4H9p10MQ6LOtuKF+dlTj0KVu+9FjxXABYLMaC2KL1dzH65W1HcF2CBzVmjQpEBaICUYGoQFQg KrCM4Bogrrbus9Dp8Iv1FegFGhcHMBeWR+VDHcC0g3Gh3nB8kfXTfgTX+PcXFYgKRAWiAlGBqEBU YAkUKAVXlnzFMskMfGbqryQpX7gO9tnXS3t92Tqyrxe7PuLdkgS9ptW2tGZZ3KICUYGoQFQgKhAV iApEBRapQCm4ahKTx00lviohomKqGQ0Iw0VSPFpTLNkIrot8SuPJqEBUICoQFYgKRAWiAlKgFFwV 1N9OO81MsVVNq0nFVEMaoC+JhRE22iiCa/xjjApEBaICUYGoQFQgKvAfFQjgiu+nVqHSSgAx/QIa /H9P5dcqqtuh3wAAAABJRU5ErkJggg== --000000000000d5bb2e059c1dbdf0-- From owner-chemistry@ccl.net Tue Jan 14 17:38:00 2020 From: "Salter-Duke, Brian James - brian.james.duke#%#gmail.com" To: CCL Subject: CCL: GAMESS Linking Error (Atlas) Message-Id: <-53958-200114152649-8965-vVbHBel6tzNtxpHD/CYtqA=server.ccl.net> X-Original-From: "Salter-Duke, Brian James -" Content-Disposition: inline Content-Type: text/plain; charset=us-ascii Date: Wed, 15 Jan 2020 07:26:32 +1100 MIME-Version: 1.0 Sent to CCL by: "Salter-Duke, Brian James -" [brian.james.duke!^!gmail.com] In these lines:- > prec.o params.o mpqcst.o -L/usr/lib64/atlas -lf77blas -latlas - > L/usr/lib64/atlas -lf77blas -latlas /scratch/user330/gamess/ddi/libddi.a - you appear to be repeating -L/usr/lib64/atlas -lf77blas -latlas. Are blas and atlas in -L/usr/lib64/atlas? Or do your need something like:- -L/usr/lib64/blas -lf77blas -L/usr/lib64/atlas -latlas ? Brian. On Tue, Jan 14, 2020 at 08:09:21AM -0500, Min Jae Kim kjh950429 _ gmail.com wrote: > > Sent to CCL by: "Min Jae Kim" [kjh950429%%gmail.com] > Dear all, > > I am currently trying to set up GAMESS on a super computer, and was > encountering errors trying to link an executable form of GAMESS. I am > currently working in a linux64 machine. My FORTRAN Compiler setup is gfortran > (ver. 4.8) with openmpi and using a atlas-so library. > > I have located the atlas libraries on the machine I'm working with, but they > seemed to be divided into two: libsatlas.so.3.10, libtatlas.so.3.10. There > were also pre-made links to these libraries in the same directory-- > libsatlas.so.3 and libtatlas.so.3 respectively. > > When I run the lked command, I get the following lked.log file: > > GAMESS will be linked into the binary file gamess.01.x. > > The name of the linker on this machine is gfortran, > and the linker options are " ". > > Object code list begins "gamess.o unport.o", > followed by BLAS object code " ", > followed by LAPACK object code "dgeev.o dgesvd.o zheev.o", > followed by VECTOR object code " ", > followed by memory object code "zunix.o", > followed by the standard GAMESS object code list, > > aldeci.o algnci.o ... (I deleted rest of the list in this email to save > length) > > Choices for some optional plug-in codes are > Tinker/SIMOMM code skipped, using dummy file qmmm.o > Both VB programs skipped, using dummy file vbdum.o > Nuclear Electron Orbital code skipped, using dummy file neostb.o > Natural Bond Orbital (NBO) code skipped, using dummy file nbostb.o > MPQC code skipped, using dummy file mpqcst.o > > The message passing libraries searched are > /scratch/user330/gamess/ddi/libddi.a -L/usr/include/openmpi-x86_64/lib -lmpi > -lpthread > > Other libraries, including math libraries, to be searched are > -L/usr/lib64/atlas -lf77blas -latlas > > Linker messages (if any) follow... > dgeev.o dgesvd.o zheev.o > gfortran -L/scratch/user330/gamess/libcchem/boost/lib -o > /scratch/user330/gamess/gamess.01.x -I/scratch/user330/gamess/object gamess.o > unport.o dgeev.o dgesvd.o zheev.o zunix.o aldeci.o algnci.o basccn.o basecp.o > basext.o basg3l.o bashuz.o bashz2.o baskar.o basminix.o basn21.o basn31.o > baspcn.o basg3x.o bassto.o casino.o ccaux.o ccddi.o ccqaux.o ccquad.o ccsdt.o > ceeis.o cepa.o cnglob.o chgpen.o cimf.o ciminf.o cimi.o cimlib.o cimsub.o > cisgrd.o comp.o cosmo.o cosprt.o cphf.o cpmchf.o cprohf.o cpuhf.o dccc.o > dcgrd.o dcgues.o dcint2.o dclib.o dcmp2.o dcscf.o dctran.o ddilib.o delocl.o > demrpt.o dft.o dftaux.o dftbfo.o dftbgr.o dftbhs.o dftblb.o dftbsk.o dftbtd.o > dftbx.o dftdis.o dftfun.o dftgrd.o dftint.o dftxca.o dftxcb.o dftxcc.o > dftxcd.o dftxce.o dftxcf.o dftxcg.o diab.o dmulti.o drc.o eaipcc.o ecp.o > ecpder.o ecplib.o ecppot.o efpmodule.o efchtr.o efdrvr.o efelec.o efgrd2.o > efgrda.o efgrdb.o efgrdc.o efinp.o efinta.o efintb.o efmo.o efmograd.o > efmograd_es.o efmograd_exrep.o efmograd_disp.o efmograd_pol.o efpaul.o > efpcm.o efpcov.o efpfmo.o eftei.o eigen.o elglib.o elgloc.o elgscf.o eomcc.o > ewald.o excorr.o ffield.o fmo.o fmoafo.o fmocp.o fmoesd.o fmogrd.o fmoh1a.o > fmoh2a.o fmoh2b.o fmoh2c.o fmohss.o fmoint.o fmoio.o fmoio_read.o fmolib.o > fmomm.o fmopbc.o fmoprp.o frfmt.o fsodci.o g3.o globop.o gmcpt.o gradex.o > guess.o grd1.o grd2a.o grd2b.o grd2c.o gugdga.o gugdgb.o gugdm.o gugdm2.o > gugdrt.o gugem.o gugsrt.o gvb.o hess.o hss1a.o hss1b.o hss1c.o hss2a.o > hss2b.o hss2c.o inputa.o inputb.o inputc.o int1.o int2a.o int2b.o int2c.o > int2d.o int2f.o int2g.o int2r.o int2s.o iolib.o ivocas.o lagran.o local.o > locatd.o loccd.o locpol.o locsvd.o lrd.o lut.o modmcpdft.o mcpdft.o mcpgrd.o > mcpinp.o mcpint.o mcpl10.o mcpl20.o mcpl30.o mcpl40.o mcpl50.o mcpl60.o > mcpl70.o mcpl80.o mccas.o mcjac.o mcqdpt.o mcqdwt.o mcqud.o mcscf.o mctwo.o > mdefp.o mexing.o mltfmo.o mm23.o modmnfun.o morokm.o mnsol.o mp2.o mp2ddi.o > mp2grd.o mp2gr2.o mp2ims.o mpcdat.o mpcdatpm6.o mpcgrd.o mpchbond.o mpcint.o > mpcmol.o mpcmsc.o mpcpcm.o mthlib.o nameio.o nebpath.o nmr.o optcix.o > ordint.o ormas1.o ormpt2.o parley.o pcm.o pcmcav.o pcmcv2.o pcmder.o pcmdis.o > pcmhss.o pcmief.o pcmpol.o pcmvch.o prpamm.o prpel.o prplib.o prppop.o > qeigen.o qfmm.o qmfm.o qrel.o quanpo.o raman.o reorg.o rhfuhf.o ricab.o > riint.o rimp2.o rimp2omp.o rimp2grd.o rmd.o rmddat.o rmdgen.o rmdwrk.o > rmdrun.o roeom.o rohfcc.o rxncrd.o ryspol.o scflib.o scfmi.o scrf.o secor.o > sfdft.o sfgrad.o sobrt.o soffac.o solib.o sozeff.o statpt.o hrmrst.o surf.o > svpchg.o svpinp.o svpleb.o symhi.o symorb.o symslc.o tddft.o tddefp.o > tddfun.o tddfxc.o tddgrd.o tddint.o tddnlr.o tddxca.o tddxcc.o tddxcd_m05.o > tddxcd_m06.o tddxcd_m08.o tddxcd_pkzb.o tddxcd_revtpss.o tddxcd_tpss.o > tddxcd_vs98.o tddxce.o tdhf.o tdx.o tdxio.o tdxitr.o tdxni.o tdxprp.o trans.o > trfdm2.o trnstn.o trudge.o umpddi.o utddft.o utdgrd.o vibanl.o vscf.o vvos.o > zapddi.o zmatrx.o mod_nosp_basis.o mod_grid_storage.o mod_dft_partfunc.o > mod_dft_molgrid.o mod_dft_fuzzycell.o mod_dft_gridint.o ccsd3aacgreorder.o > ccsd3aacgsum.o ccsd3aacgt1A00.o ccsd3aacgt1A01.o ccsd3aacgt1A10.o > ccsd3aacgt1A11.o ccsd3aacgt1A.o ccsd3aacgt1B00.o ccsd3aacgt1B01.o > ccsd3aacgt1B10.o ccsd3aacgt1B11.o ccsd3aacgt1B.o ccsd3aacgt2A0000.o > ccsd3aacgt2A0010.o ccsd3aacgt2A0011.o ccsd3aacgt2A1000.o ccsd3aacgt2A1010.o > ccsd3aacgt2A1011.o ccsd3aacgt2A1100.o ccsd3aacgt2A1110.o ccsd3aacgt2A1111.o > ccsd3aacgt2A1.o ccsd3aacgt2A.o ccsd3aacgt2B0000.o ccsd3aacgt2B0001.o > ccsd3aacgt2B0010.o ccsd3aacgt2B0011.o ccsd3aacgt2B0100.o ccsd3aacgt2B0101.o > ccsd3aacgt2B0110.o ccsd3aacgt2B0111.o ccsd3aacgt2B1000.o ccsd3aacgt2B1001.o > ccsd3aacgt2B1010.o ccsd3aacgt2B1011.o ccsd3aacgt2B1100.o ccsd3aacgt2B1101.o > ccsd3aacgt2B1110.o ccsd3aacgt2B1111.o ccsd3aacgt2B1.o ccsd3aacgt2B.o > ccsd3aacgt2C0000.o ccsd3aacgt2C0010.o ccsd3aacgt2C0011.o ccsd3aacgt2C1000.o > ccsd3aacgt2C1010.o ccsd3aacgt2C1011.o ccsd3aacgt2C1100.o ccsd3aacgt2C1110.o > ccsd3aacgt2C1111.o ccsd3aacgt2C1.o ccsd3aacgt2C.o ccsd3aacgt3A100100.o > ccsd3aacgt3A100110.o ccsd3aacgt3A100111.o ccsd3aacgt3A110100.o > ccsd3aacgt3A110110.o ccsd3aacgt3A110111.o ccsd3aacgt3A111100.o > ccsd3aacgt3A111110.o ccsd3aacgt3A111111.o ccsd3aacgt3AB.o > ccsd3aacgt3B001001.o ccsd3aacgt3B001100.o ccsd3aacgt3B001101.o > ccsd3aacgt3B001110.o ccsd3aacgt3B001111.o ccsd3aacgt3B100001.o > ccsd3aacgt3B100100.o ccsd3aacgt3B100101.o ccsd3aacgt3B100110.o > ccsd3aacgt3B100111.o ccsd3aacgt3B101001.o ccsd3aacgt3B101100.o > ccsd3aacgt3B101101.o ccsd3aacgt3B101110.o ccsd3aacgt3B101111.o > ccsd3aacgt3B110001.o ccsd3aacgt3B110100.o ccsd3aacgt3B110101.o > ccsd3aacgt3B110110.o ccsd3aacgt3B110111.o ccsd3aacgt3B111001.o > ccsd3aacgt3B111100.o ccsd3aacgt3B111101.o ccsd3aacgt3B111110.o > ccsd3aacgt3B111111.o ccsd3aacgt3BC.o ccsd3aacgt3C010010.o > ccsd3aacgt3C010011.o ccsd3aacgt3C010100.o ccsd3aacgt3C010110.o > ccsd3aacgt3C010111.o ccsd3aacgt3C011010.o ccsd3aacgt3C011011.o > ccsd3aacgt3C011100.o ccsd3aacgt3C011110.o ccsd3aacgt3C011111.o > ccsd3aacgt3C100010.o ccsd3aacgt3C100011.o ccsd3aacgt3C100100.o > ccsd3aacgt3C100110.o ccsd3aacgt3C100111.o ccsd3aacgt3C110010.o > ccsd3aacgt3C110011.o ccsd3aacgt3C110100.o ccsd3aacgt3C110110.o > ccsd3aacgt3C110111.o ccsd3aacgt3C111010.o ccsd3aacgt3C111011.o > ccsd3aacgt3C111100.o ccsd3aacgt3C111110.o ccsd3aacgt3C111111.o > ccsd3aacgt3CD.o ccsd3aacgt3D100100.o ccsd3aacgt3D100110.o > ccsd3aacgt3D100111.o ccsd3aacgt3D110100.o ccsd3aacgt3D110110.o > ccsd3aacgt3D110111.o ccsd3aacgt3D111100.o ccsd3aacgt3D111110.o > ccsd3aacgt3D111111.o ccsd3amain.o qmmm.o vbdum.o neostb.o nbostb.o cchdmy.o > prec.o params.o mpqcst.o -L/usr/lib64/atlas -lf77blas -latlas - > L/usr/lib64/atlas -lf77blas -latlas /scratch/user330/gamess/ddi/libddi.a - > L/usr/include/openmpi-x86_64/lib -lmpi -lpthread > /usr/bin/ld: cannot find -lf77blas > /usr/bin/ld: cannot find -latlas > /usr/bin/ld: cannot find -lf77blas > /usr/bin/ld: cannot find -latlas > /usr/bin/ld: cannot find -lmpi > collect2: error: ld returned 1 exit status > set rc=1 > unset echo > > Unfortunately, there was an error while linking GAMESS. > 0.379u 0.553s 0:01.19 77.3% 0+0k 0+40io 0pf+0w > > I would really appreciate any advice or help on this issue. Thank you.> -- Brian Salter-Duke (Brian Duke) Brian.Salter-Duke^monash.edu Adjunct Associate Professor Monash Institute of Pharmaceutical Sciences Monash University Parkville Campus, VIC 3052, Australia

Google Groups