Return-Path: Received: from post.thorcom.com (post.thorcom.com [195.171.43.25]) by klubnl.pl (8.14.4/8.14.4/Debian-8+deb8u2) with ESMTP id w8BDJIeM007906 for ; Tue, 11 Sep 2018 15:19:19 +0200 Received: from majordom by post.thorcom.com with local (Exim 4.14) id 1fziTT-0002vE-F9 for rs_out_1@blacksheep.org; Tue, 11 Sep 2018 14:12:59 +0100 Received: from [195.171.43.32] (helo=relay1.thorcom.net) by post.thorcom.com with esmtp (Exim 4.14) id 1fziTM-0002ux-3c for rsgb_lf_group@blacksheep.org; Tue, 11 Sep 2018 14:12:52 +0100 Received: from mout02.posteo.de ([185.67.36.66]) by relay1.thorcom.net with esmtps (TLSv1.2:ECDHE-RSA-AES256-GCM-SHA384:256) (Exim 4.91_59-0488984) (envelope-from ) id 1fziTJ-0003aQ-Aq for rsgb_lf_group@blacksheep.org; Tue, 11 Sep 2018 14:12:51 +0100 Received: from submission (posteo.de [89.146.220.130]) by mout02.posteo.de (Postfix) with ESMTPS id 96E70211F3 for ; Tue, 11 Sep 2018 15:12:46 +0200 (CEST) X-DKIM-Result: Domain=posteo.de Result=Signature OK DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=posteo.de; s=2017; t=1536671566; bh=8ZRR+T9egBM088RckhOd0ODRw70dC8DqHgVTXT/FByM=; h=Date:From:To:Subject:From; b=aovH4PPK0pMdBNY9vYlv8ZnuK7jBHQBVS6s+AYjxbEpiHad/sprJb7CDdYFonXUBD A6nU1JEGGeGTPr1wabctwdSQZm2Jw0ZxDdzTTq1bPgPeP2S7mVH8tX9hTz5RRoKTtc mg2XOc6zqkmPHtROycd7wCtNlcN4PyauRDHseNmf90V2b8ZbFjciLRvrOG9X2Pja2/ 3PnESK9JmemkV1OsgERQKMEPc3o6TB8o/J/3rARNZHjDvSJb0Hapy55WQlHDeSjD0Z FpnquEVuGX8W+SKeI5sWLtzZspbU514jEYR3/C2/9yd7Fh8eoJwpZRylmIXVWDher8 FfNd3w+Jg833w== Received: from customer (localhost [127.0.0.1]) by submission (posteo.de) with ESMTPSA id 428lhF3VSkz9rxK for ; Tue, 11 Sep 2018 15:12:45 +0200 (CEST) Message-ID: <5B97BF4C.5070102@posteo.de> Date: Tue, 11 Sep 2018 15:12:44 +0200 From: DK7FC User-Agent: Mozilla/5.0 (Windows; U; Windows NT 6.1; de; rv:1.9.1.8) Gecko/20100227 Thunderbird/3.0.3 MIME-Version: 1.0 To: rsgb_lf_group@blacksheep.org References: <6DB8451D7F3D3947A5918808A59621EA08609AB5@servigilant.vigilant.local> <5B96A252.1010507@posteo.de> <6DB8451D7F3D3947A5918808A59621EA0860A197@servigilant.vigilant.local> In-Reply-To: <6DB8451D7F3D3947A5918808A59621EA0860A197@servigilant.vigilant.local> X-Spam-Score: -2.3 (--) X-Spam-Report: Spam detection software, running on the system "relay1.thorcom.net", has NOT identified this incoming email as spam. The original message has been attached to this so you can view it or label similar future email. If you have any questions, see @@CONTACT_ADDRESS@@ for details. Content preview: Hi Luis, As Markus mentioned... And see the attachment. In the example i set the sample rate to 44100 Hz. If you have a downconverter with an LO of 120 kHz, and expect a message on 137 kHz exactly, set the internal frequency shift to a center frequency of 17 kHz, like shown in the image. [...] Content analysis details: (-2.3 points, 5.0 required) pts rule name description ---- ---------------------- -------------------------------------------------- -2.3 RCVD_IN_DNSWL_MED RBL: Sender listed at http://www.dnswl.org/, medium trust [185.67.36.66 listed in list.dnswl.org] -0.0 SPF_PASS SPF: sender matches SPF record -0.0 T_RP_MATCHES_RCVD Envelope sender domain matches handover relay domain 0.0 T_KAM_HTML_FONT_INVALID BODY: Test for Invalidly Named or Formatted Colors in HTML 0.0 HTML_MESSAGE BODY: HTML included in message 0.0 DC_PNG_UNO_LARGO Message contains a single large inline gif 0.0 T_DKIM_INVALID DKIM-Signature header exists but is not valid X-Scan-Signature: 96ac01fec607a24c3eb4802275242fd7 Subject: Re: LF: The return of EbNaut for Dummies Content-Type: multipart/mixed; boundary="------------030108070500050007040507" X-Spam-Checker-Version: SpamAssassin 2.63 (2004-01-11) on post.thorcom.com X-Spam-Level: X-Spam-Status: No, hits=0.5 required=5.0 tests=HTML_40_50,HTML_MESSAGE autolearn=no version=2.63 X-SA-Exim-Scanned: Yes Sender: owner-rsgb_lf_group@blacksheep.org Precedence: bulk Reply-To: rsgb_lf_group@blacksheep.org X-Listname: rsgb_lf_group X-SA-Exim-Rcpt-To: rs_out_1@blacksheep.org X-SA-Exim-Scanned: No; SAEximRunCond expanded to false This is a multi-part message in MIME format. --------------030108070500050007040507 Content-Type: multipart/alternative; boundary="------------080104020104070500040403" --------------080104020104070500040403 Content-Type: text/plain; charset=UTF-8; format=flowed Content-Transfer-Encoding: 8bit Hi Luis, As Markus mentioned... And see the attachment. In the example i set the sample rate to 44100 Hz. If you have a downconverter with an LO of 120 kHz, and expect a message on 137 kHz exactly, set the internal frequency shift to a center frequency of 17 kHz, like shown in the image. Also remember that the number of exported FFT bins in the FFT export register card should be set to the half of the FFT input size shown in the FFT register card. Keep us informed about the success :-) I'm waiting for your first message to receive here. I'm monitoring permanently, however only in the range 137.5 kHz +- 50 Hz and only about 30 minutes message length. Other parameters would work too, but i need to prepare a special SL instance then... 73, Stefan Am 11.09.2018 13:40, schrieb VIGILANT Luis Fernández: > > Hi Stefan > > Thank you for the detailed explanation. I prefer to understand the > process rather than getting a working .usr > > So, excuse me again for dumming again J > > All understood about the length and relation to FFT windows time > (length) in SL. Width was un unknown parameter for me > > And I’m afraid the problem is about the width: > > >> Choose the FFT width and length to suit your settings. The width is > maybe 10 * 1/(symbol length) or more > > Lets say 1Hz minimum for a 10 sec symbol leght, right ? > > So, in the FFT configuration window the only way to get >1Hz(1.3Hz) > for “Width of one FFT-bin” is to reduce decimation to 1 > > and then set FFT length to 32768 to get some “FFT window time > (length)”. But then, the indows time is just 743ms > > which will not cover the length of the message at all > > I’m stucked here. Can’t get >width with 30 minutes FFT lenghts. I’m > using 44.100Hz sample rate L > > The FFT input type is “Complex ith internal frequency shift”. But even > using “Real FFT starting at 0Hz” doesn’t improve much > > Decimation at 1536 and FFT length 65535 produces “Width of one FFT” at > 438uHz and FFT windows time 38 min. So this time > > good length but small width > > What I’m doing wrong ? > > 73 de Luis > > EA5DOM > > *De:* owner-rsgb_lf_group@blacksheep.org > [mailto:owner-rsgb_lf_group@blacksheep.org] *En nombre de *DK7FC > *Enviado el:* lunes, 10 de septiembre de 2018 18:57 > *Para:* rsgb_lf_group@blacksheep.org > *Asunto:* Re: LF: The return of EbNaut for Dummies > > Hi Luis, > > Am 10.09.2018 17:47, schrieb VIGILANT Luis Fernández: > > The fact of getting windows timestamped files which really start at a > > different time and no aparent indication of when they end ….. > doesn´t help at all > > Well, the FFT settings must be so that you cover enough width (in Hz) > and length (in seconds). The necessary width depends on your symbol > length. The length is mentioned in the FFT settings register card (FFT > window time). Choose a rectangular window for EbNaut decodes. > Convert the txt files into wav using Markus tools. Load the wav file > in the EbNaut decoder and press RUN. Then you will see the start time > of the file. The end is start time + length. Simple, isn't it? :-) > > A new txt file is generated in the interval of the scroll time > (Spectrum (1) ) register card. Usually 30 minutes is fine, or even 1 > hour on VLF. Then you get a file each 30 minutes. If the FFT length is > longer than 30 minutes. Your FFT length should be 30 minutes longer > than the transmission length, just to avoid an incomplete set of data > in a txt file. > > Choose the FFT width and length to suit your settings. The width is > maybe 10 * 1/(symbol length) or more. > > > Is there any way of “fast” EbNaut when signals are strong ? > > I think there are no limits, you can run 0.1 second symbol length. But > usually it is used for weak signals and stable paths. > > I really don’t know what to test next. > > Send me your .usr file and the EbNaut settings you want to try. > > 73, Stefan > > > May be to run ebnaut_tx in test mode, which just changes the phase > every symbol length > > And then, analyze the recorded file with a different tool to > determine if this phase changes are there ? Can this be easily done ? > > 73 de Luis > > EA5DOM > > PS: Congratulations for your amazing test with the guard rails. > And yes, this is much much harder than EME ! J > > *De:* owner-rsgb_lf_group@blacksheep.org > > [mailto:owner-rsgb_lf_group@blacksheep.org] *En nombre de *DK7FC > *Enviado el:* viernes, 07 de septiembre de 2018 22:10 > *Para:* rsgb_lf_group@blacksheep.org > > *Asunto:* Re: LF: EbNaut transmission test in LF > > Hello Luis, > > Another hint: Try to use 4K19A and a shorter message, like EA5 or > so. Use long symbols, like 10 seconds or longer. Then, timing is > less critical and you may get a decode and can tune to the best > Eb/N0 and find out what the timing offset it. It would guess it is > a timing problem. > > 73 Stefan > > Am 07.09.2018 13:36, schrieb VIGILANT Luis Fernández: > > Hi Domenico > > Sorry, I’m not transmitting this weekend. Very stormy weather > here, so the wires are down > > I will notice in the reflector any transmission in advance. > But first want to confirm that all is working ok > > So that was the goal of yesterday test > > Yes, the XOR is AFTER the 1/10 divider, and working at the > final frequency 137485 Hz > > Your auto-decoder is a great tool. EbNaut is quite tricky for > average use and needs a lot of details to care about > > Of course the reward is great when you get decodes with > miserable signal levels. There is never free lunch ! ;-) > > 73 de Luis > > EA5DOM > > *De:* owner-rsgb_lf_group@blacksheep.org > > [mailto:owner-rsgb_lf_group@blacksheep.org] *En nombre de > *Domenico IZ7SLZ > *Enviado el:* viernes, 07 de septiembre de 2018 13:18 > *Para:* rsgb_lf_group@blacksheep.org > > *Asunto:* Re: LF: EbNaut transmission test in LF > > Hello Luis, > > thanks for sharing your experiment. My auto-decoder > https://www.qsl.net/iz7slz/ is already retuned for your > transmissions. > > BTW QRM is large here in the morning time (urban location). I > will try to catch your signal later in the night. > > /At least the decoder is detecting the carrier but may be > there is no proper phase modulation or probably other failures/ > > /What I’m doing wrong ? Can anybody decode the message from > the file ?/ > > I also suspect some issues on modulator circuit. Of course > the XOR gate is following the /10 divider, is it? > > Good luck. > > 73 all, > > Domenico/IZ7SLZ > > On Fri, 7 Sep 2018 at 11:38, VIGILANT Luis Fernández > > wrote: > > Hi LF EbNauters > > I have been building a disciplined Rx for LF, based in a > GPS LO at 120KHz and a NE602 downconverter to 17KHz > > Then feeding the signal to the soundcard, also disciplined > with 1pps from the same GPS > > At Tx side a GPS LO at 1374850 Hz divided by 10 provides > 0.1Hz steps at LF. Then an XOR gate is used for > > EbNaut modulation from the DTR of a COM port under > Windows. The PA is just a mosfet driver (mic4452 AT 12v) > > Just about 100mW to antenna but good enough to get a 20dB > S/N in my Rx 7Km away > > Stability looks pretty good and also phase modulation as > seen in SL spectrogram. Also monitoring phase changes > > with the SL plot display window. So, yesterday I tried an > EbNaut transmission with the following setup > > Coding: 8K19A > > CRC 16 > > Symbol period: 1s > > Characters: 6 Transmission time: 9.3 minutes > > Transmitting at minute 00 and 30 every hour > > I got the FFT files from SL and converted them to WAV > files. The configuration file (SR) included the corrected > sample rate > > of the soundcard as well as decimation , FFT length and > center frequency > > Attached is a WAV file starting at 16:22 which should > contain the transmission started at 16:30 untill about 16:40 > > The rawsym graphic shows a clear peak centered in > frequency, but I haven’t been able to get a decode other > than “******” > > At least the decoder is detecting the carrier but may be > there is no proper phase modulation or probably other failures > > What I’m doing wrong ? Can anybody decode the message from > the file ? > > BTW, I have used a list length of 47274 and also 141823, > but nill L > > 73 de Luis > > EA5DOM > --------------080104020104070500040403 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: 8bit Hi Luis,

As Markus mentioned...
And see the attachment. In the example i set the sample rate to 44100 Hz. If you have a downconverter with an LO of 120 kHz, and expect a message on 137 kHz exactly, set the internal frequency shift to a center frequency of 17 kHz, like shown in the image.

Also remember that the number of exported FFT bins in the FFT export register card should be set to the half of the FFT input size shown in the FFT register card.

Keep us informed about the success :-)

I'm waiting for your first message to receive here. I'm monitoring permanently, however only in the range 137.5 kHz +- 50 Hz and only about 30 minutes message length. Other parameters would work too, but i need to prepare a special SL instance then...

73, Stefan



Am 11.09.2018 13:40, schrieb VIGILANT Luis Fernández:

Hi Stefan

 

Thank you for the detailed explanation. I prefer to understand the process rather than getting a working .usr

So, excuse me again for dumming again  J

 

All understood about the length and relation to FFT windows time (length) in SL. Width was un unknown parameter for me

And I’m afraid the problem is about the width:

 

>> Choose the FFT width and length to suit your settings. The width is maybe 10 * 1/(symbol length) or more

Lets say 1Hz minimum for a 10 sec symbol leght, right ?

 

So, in the FFT configuration window the only way to get >1Hz(1.3Hz) for “Width of one FFT-bin” is to reduce decimation to 1

and then set FFT length to 32768 to get some “FFT window time (length)”. But then, the indows time is just 743ms

which will not cover the length of the message at all

 

I’m stucked here. Can’t get >width with 30 minutes FFT lenghts. I’m using 44.100Hz sample rate L

 

The FFT input type is “Complex ith internal frequency shift”. But even using “Real FFT starting at 0Hz” doesn’t improve much

Decimation at 1536 and FFT length 65535 produces “Width of one FFT” at 438uHz and FFT windows time 38 min. So this time

good length but small width

What I’m doing wrong ?

 

73 de Luis

EA5DOM

 

De: owner-rsgb_lf_group@blacksheep.org [mailto:owner-rsgb_lf_group@blacksheep.org] En nombre de DK7FC
Enviado el: lunes, 10 de septiembre de 2018 18:57
Para: rsgb_lf_group@blacksheep.org
Asunto: Re: LF: The return of EbNaut for Dummies

 

Hi Luis,

Am 10.09.2018 17:47, schrieb VIGILANT Luis Fernández:

The fact of getting windows timestamped files which really start at a

different time and no aparent indication of when they end ….. doesn´t help at all

Well, the FFT settings must be so that you cover enough width (in Hz) and length (in seconds). The necessary width depends on your symbol length. The length is mentioned in the FFT settings register card (FFT window time). Choose a rectangular window for EbNaut decodes.
Convert the txt files into wav using Markus tools. Load the wav file in the EbNaut decoder and press RUN. Then you will see the start time of the file. The end is start time + length. Simple, isn't it? :-)

A new txt file is generated in the interval of the scroll time (Spectrum (1) ) register card. Usually 30 minutes is fine, or even 1 hour on VLF. Then you get a file each 30 minutes. If the FFT length is longer than 30 minutes. Your FFT length should be 30 minutes longer than the transmission length, just to avoid an incomplete set of data in a txt file.

Choose the FFT width and length to suit your settings. The width is maybe 10 * 1/(symbol length) or more.


Is there any way of “fast” EbNaut when signals are strong ?

I think there are no limits, you can run 0.1 second symbol length. But usually it is used for weak signals and stable paths.

 

I really don’t know what to test next.

Send me your .usr file and the EbNaut settings you want to try.

73, Stefan


May be to run ebnaut_tx in test mode, which just changes the phase every symbol length

And then, analyze the recorded file with a different tool to determine if this phase changes are there ? Can this be easily done ?

 

73 de Luis

EA5DOM

 

PS: Congratulations for your amazing test with the guard rails. And yes, this is much much harder than EME ! J

 

De: owner-rsgb_lf_group@blacksheep.org [mailto:owner-rsgb_lf_group@blacksheep.org] En nombre de DK7FC
Enviado el: viernes,
07 de septiembre de 2018 22:10
Para: rsgb_lf_group@blacksheep.org
Asunto: Re: LF: EbNaut transmission test in LF

 

Hello Luis,

Another hint: Try to use 4K19A and a shorter message, like EA5 or so. Use long symbols, like 10 seconds or longer. Then, timing is less critical and you may get a decode and can tune to the best Eb/N0 and find out what the timing offset it. It would guess it is a timing problem.

73 Stefan

Am 07.09.2018 13:36, schrieb VIGILANT Luis Fernández:

Hi Domenico

 

Sorry, I’m not transmitting this weekend. Very stormy weather here, so the wires are down

I will notice in the reflector any transmission in advance. But first want to confirm that all is working ok

So that was the goal of yesterday test

 

Yes, the XOR is AFTER the 1/10 divider, and working at the final frequency 137485 Hz

 

Your auto-decoder is a great tool. EbNaut is quite tricky for average use and needs a lot of details to care about

Of course the reward is great when you get decodes with miserable signal levels. There is never free lunch ! ;-)

 

73 de Luis

EA5DOM

 

De: owner-rsgb_lf_group@blacksheep.org [mailto:owner-rsgb_lf_group@blacksheep.org] En nombre de Domenico IZ7SLZ
Enviado el: viernes, 07 de septiembre de 2018 13:18
Para: rsgb_lf_group@blacksheep.org
Asunto: Re: LF: EbNaut transmission test in LF

 

Hello Luis,

 

thanks for sharing your experiment. My auto-decoder  https://www.qsl.net/iz7slz/  is already retuned for your transmissions.

 

BTW QRM is large here in the morning time (urban location). I will try to catch your signal later in the night.

 

At least the decoder is detecting the carrier but may be there is no proper phase modulation or probably other failures

What I’m doing wrong ? Can anybody decode the message from the file ?

 

 I also suspect some issues on modulator circuit. Of course the XOR gate is following the /10 divider, is it?

 

Good luck.

 

73 all,

Domenico/IZ7SLZ

 

 

 

On Fri, 7 Sep 2018 at 11:38, VIGILANT Luis Fernández <luis@vigilant.es> wrote:

Hi LF EbNauters

 

I have been building a disciplined Rx for LF, based in a GPS LO at 120KHz and a NE602 downconverter to 17KHz

Then feeding the signal to the soundcard, also disciplined with 1pps from the same GPS

 

At Tx side a GPS LO at 1374850 Hz divided by 10 provides 0.1Hz steps at LF. Then an XOR gate is used for

EbNaut modulation from the DTR of  a COM port under Windows. The PA is just a mosfet driver (mic4452 AT 12v)

Just about 100mW to antenna but good enough to get a 20dB S/N in my Rx 7Km away

 

Stability looks pretty good and also phase modulation as seen in SL spectrogram. Also monitoring phase changes

with the SL plot display window. So, yesterday I tried an EbNaut transmission with the following setup

 

Coding: 8K19A

CRC 16

Symbol period: 1s

Characters: 6          Transmission time: 9.3 minutes

Transmitting at minute 00 and 30 every hour

 

I got the FFT files from SL and converted them to WAV files. The configuration file (SR) included the corrected sample rate

of the soundcard as well as decimation , FFT length and center frequency

 

Attached is a WAV file starting at 16:22 which should contain the transmission started at 16:30 untill about 16:40

 

The rawsym graphic shows a clear peak centered in frequency, but I haven’t been able to get a decode other than “******”

At least the decoder is detecting the carrier but may be there is no proper phase modulation or probably other failures

What I’m doing wrong ? Can anybody decode the message from the file ?

BTW, I have used a list length of 47274 and also 141823, but nill L

 

73 de Luis

EA5DOM

--------------080104020104070500040403-- --------------030108070500050007040507 Content-Type: image/png; name="FFTforever.png" Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="FFTforever.png" iVBORw0KGgoAAAANSUhEUgAAAiAAAAHUCAIAAAH7BzRPAAAAB3RJTUUH4gkLDQk3LO54TAAA IABJREFUeJzsvX10G2eZN/y7nb77vgfYpewDC5TIybZy6CbTZCiFKJ6kSbrZtrIJTSGNAMtK k0WetxAqu2BcEoMjcEpFAGtKoChhW2LZyyoNxKwbKymhcWMpVrcLKEENNB6aRDJdnuVj6bM8 e56z5z1n3j/umXtG0ujLkm3Zmd9x09HM/f153dd9fRBFUbBYQN5g/8Td3GtrRv74tRWrGpYs WbKk4Q+H7nh714UlSxqWLGloWNKwpGHJklu3NLw6vmRJw5IlSxqWNCxpaKAhWYAXhu7ZsvvH aoCGhme/9cEPdUYbDAEeOXDfN37wm6c/9Cbxy+cbGhr0pGiYBkNq6m9DAEN2H9/8zpcvvPiz /2pqWNKw5v9+JacyNwAYGblxDf7IXr3t4Z82LFmSFWrq+W+P933y7gOFmuSunT9qWNJAn28G 7vvUs0uyU5C+MNqwpAEf2lhd0wPA8ZFTt9zdRB9yPpFUMlF9BnODPZ2PHgo+XiRAA3tKAxzv 4PonJwA/HwDg9kRoEgCQiSATCWcwQZ8N4HiH2xMBJicAtyfC9U9m5ZCJhD1eGiUNAJjQSmZM luaVkywwPQFM9Dto9E2bNtFPbt7rjwGAn/ciFghn1Cile6Zke8wYq9aszX/58oUXC4U/PnJq +7Z7iySo9gzHO+hDWvuQHvYCWW1sfMPK4R6e9uc1qjGdXMQCbt5BU3j5wovRCy++nP0H2hUA bfuwx8uisppwvNdY5tzKsP5p1D7svbIbWGcMmv8GwFDb0r6Oq/ll3js8bV6Z9T1DhrHQaBZk Q28CQN96AGgfPJIfIJU8Yiwzw0JaAEojlUwoisKv7kolE6lkYqz7NvXf0S5+dRcPpJIJfnUX 332cX90FoGc00bMaqdEuAKlD94+Ndo0lEw8cSihFQXOhWaRGu1KjXWPJhNaOt6VGu1LJBLYP pJIJ4DaaI80LAA/w3ceLp08TJ6lkgg7feWzQWuEG+j+Od+SMtzQb0JkIbC4A/pg6jin2dD56 9uzZqEhaDsOUJnr5wovGlTAniz2dj6747NmQEwBkwK69Nz6XhChID3/LwVa53AWAoZGtSDYX 3SiMNWFwhpQyqbv8LGhNIEvG0pdfEwChuM/4czEOMzfvSALAbXTVAybZKuwenh5qW8oisOG3 p/PRI9v+2+6LSwLxxUsPsxzQUVqTOvj9/qxhNkTXmSRb1PX9hNWEUg3GDcTuiwMwrUkhhD3e dN5+J0gyAEAWJFkQJMiSDAiEiIQQQoonaAwwb8OsVj2zefNmALT/Z16ZckqzefPmWaLrTKEO M0a0uoen05kIgIl+RzgDnaTNRHKIZdDhQYeEICG7x/N/GkHpLrpahj25JBYMpN2ezkdXrVl7 5o1rO/inVq1Zm16zdpXhLyfWLPaMcQCUxES/g5JkFeWSU2y9MrNH6s8Z9MPZ+Pg4AM4TULs4 E+E8ET/vcHsilCZPa/Q/HSSIBTjegUyE6w+ki9D8BpgeYCjyD2cUdJjljK7aD7O5wQyHmVal yQmsC3kiQ4MuZCLpc2f2HsRQcrfbkx46ANga6YN7HwA0XbzaN7o8DTTaXHTQu3nvUHI3TSG5 ojHVm3v+mVXMac/M9rRUyZkio7l6sJY6e/bsyxdedHsiyYsDWH3/Ax09fevh5wN9yR4AHO8Y G+2CzdVoIKYApIe9jXdu4bYOaKTqtD+21JTqVXsGAGSJHFyhqES5JNt9lIAVo0j1SwDicZ8Y BYDuJukkfD47CCGKogCySA52B1NTl847Q+ZEWq3apTgMlZk1zFllbmBPhIhAakqJQxLgix+M qucNQZCwo5U71tQdV+wAPY2NdYB2gigI3fF4OYeQfAZkbbF9272V9YwgSPG4D4CB7I8CzuLH w0U4zPQ1MxbAsuVpm2uvJ/KzC1+vYS56ZaIAROIMKXT27yRCrxIfIUJIiQMQJSm04pLsDIF2 gizBbjiyRkU4QyIRQ0oo99Oi7BkAHO9l579CDI0ZJJ7L0AAgCJJ+0JMEAHQhlrWvACRZfQAA WVL/lSVZllAGUskjRhIul6GRl4h6AC0bi3RppkvwUey0t+6A3UcImVIU2maEkObmIHApHg8B UOdGdZhFhgaAeNwX99ntvjidvopWE/ocj/toTQDMuCbqiVUDHcaCIBExSnkagiTT0yuhrIyo WHKgmTA0Zla4MmE6zGaRoVF9okUwZ3OmoXSQWYPbE9EvqvK4JdAuABmT7cwbC54xKRZSzxjL aZrmDfmv6hYlG2UhVaZkz8zrnOHVO3F/DGGPl97FajeyJleipZfpRThn6pbVZETJQjaUE2ih YD7nTM1hVaZeQZio0CIASSUTqrTUnGBW2bNMdmZyAus2YBKAP7YOewK7kj17eUcTbutL7g5n 1mGfo/1A14TNhX7Hhp1dAGBzuT2RoQOAzTUBPM97+w7ZJ9b3LAP28t4m2PuSPRPA83ygb3Q5 FYvQkYlM2FzPe7x3DR7ZAIAedS5eHUreOYF1GzKRMFztiPi3Xu0bXY5rV9Pre+gVt5/39lHG PB8YSvYUqsysg/b/rPaMtgBkImmA659MD3sBMGk+es0ETcTPnSfiVT4OBR+f7Zu5+RTR4kYc qW25uVNe4XHesb1wwbiRUwBSeVKB87Y0qzWJBeiFtp/35ocJexz06jvnRjq17d7UtnuRibh5 r9sQcR56psjieSj4+Ko1a/1+v+nX7dvuLcJ9VxnnNShgfYAsJvH5G/74xz8GgyP79z/4F7c+ rAmwNyR+9tUN7//c0X/5snf9F3KE3LctaThpEHJv+cyefeTM3x66sqSh4blPNbWGrjIp+Ee/ 7vpaz/eX3L7uq++4/OTZP/06T+ieZVdIKj8rQEPDkiUNjrdcA5D8Pyv4/+cyq8PF/7519Z/9 ck/no2Tjxp1+/64W77H//dx9b2kdy4nMBPIfXdHwtSvFJPa/+7TX2/FdY4AlDWpRhh+7/8H9 z5Yoa3mVmX4hBMB+78PyqSdYZVa0dF4eC46Pj898ztShRIe+NDMhdLqB5khoIxZQxdgzEbpQ 6sLsnog/prNes6TjAWQiE8AE4OYdJsL1sYCfD6RjAX8sL0e6d2ciesHoSyqtn4m4PZG0JulP MfOeKS7MXrLfKpWdLwdFNs28dsqmZWhN8mXYAbiHp2lN6LZAw1CJG473uoenablfvvDiy88+ Ev3saqPsfBY0dibbXjjeER4O5AbToPWMJu9bW5RURahtOotn0zw+cqoBxuFLpz7tXMax1h6Y lksaqnzWRL8j7PFy/ZPAtKkIFWNyr1qzlglhpanCh7rMqHo7yERU8UBKjKl5TdMxWSRxIx99 jnpmDmSNjo+cUpmA4QzabarMctqgCZI20wrxeyJ9g65Va9ZqsjMmyC+68aoZwKo1/8PkjlmW YPdRNiz9JggS1+tTr3INEAQpHm99+cLvjS/VyrTbAK3cxtKb6rcwhZmK6Dp61WxI0Oy23O7L +RDPFpDPe29Wmcqwvgcz2hOMTTMbo04Tnx+eTh7cnhrt0hdobbHWxeczkfS5M41t6lBZtWat JBDf0SAT5jKiZFlryK1neWni821LU8kEbC79Ok6rla4IYHOxmlD44grMamIKjg+oK1gsAEAQ JJGIAAghVDJaECR6baFJ04MGKF4NY6vN22pWk54xXjXrq9kMUE5pigy2msyZHPIvlzZzD0+H PV7EAnS3ojsX/WTUMgQgaCoUhJAsmRqtrIWLW0BRUAPHO5gmxxO8o4N/atWaP5x549on+EeK CDWjmmFWvGdyZOfL3zTDHm9gxe5U7zoqW1wkl5wEj4+cUisz2+zGuaEA9GFGhT8m+h0c7+B4 Bx1U/hiodDwyEboKQaWmvADcnojbE/HzDlWgviioIHzOy5yzGmOgMuSPrlkZZhXBtGfSQEu2 imC+UmJFw0ztmT2dj9IJx06/HO/gPOq9tpv3Tmi6B/RUTHXPqX562ONgh9sJwM0HgEl/TA1Z BI15KoL5LftynvJzwZPcXPZMReo0M4C6z9RQjs0UOeLz4QxO74s8ds+ZloM/H0smXvA4lg8m HuIDqdHl3NFGHO8a677NSGqEPQ7gtvbB3RzfhdVdD1wc2JVMmFLA6s3Z2bNnKfnNJJchS/LJ Y1TfTwZOyqB0iyTj2E4pHvcZ6f+oSJwhRZYEGj6/MnOzmhkqM2uYs8qo5AzVXuDOd4a0xpaB JjGqsGORLMG+gpAWAIoyBjj1YIWPaAyFGPu1AmV3qJUJOQGnD9BPQnaA1USMIuT0ATIVQZUl AT7nSUHwHd1ht/sURSkpmFwTHk1ppJKJTZs2KYrSMVZS5X6GyDE5kEomelbflkomekZLWBGo KIv9+/erPSPJCDmjgBOyFD3Y6QwpgiDF4yvEqDPkVGV/qTKDLAk7j+04f76T9hL9FNXk7oWd YJ9yMDSo8+WoMYl2W43Pm3O3ABCStaeZMzQ00fZCR//8lNlzFm2mpiVFZSAqElDpdVmiUu3a SVCXYJMEIaplX46Ye97ubD7L4nFfXk3KlaJfjEszgySQ1riyUyDxuAKoWmWCIJ3nLimhkCwJ TZ3nAShlrGDFMYsMDQZfXLEDcU3FX1EUAPG4TwmFANh9cbp6oPKa0OsUpqWhyssLkiSDnVhl KlMfFamyCCFE/bdwNXIZGvMyzOqLoVEl5oKhUVdQz7wZQDuoFpGdR70KaU8DS2F2ViuO+qzM 0vxXh4KPLx7xeeMqVahW8zxn1Mv0TCSdiaQ1NoPbE3HzDncho2KFMc89o1Gf6xoNP4cGXcBM bosX1TXgHA2zuZHQr+t9plJYlalXLCrx+TldmmdbPu0GAJ993+/3nt4yNOhyeyJNF8/00Qv7 TIQalKEy8mmbqxFAJpK2uV7IYPlRx4begSwLNTbX09ROCb2Ftbn28t6h0S0TNtdVj6N9MMHk nzg+8ADQl2xze+JDgy7K+U8D14CH+idTvev8vLcveYSmeS1bAJ/rn+Qvp4cGG2nW4qBrg6Ey ZNOmTXMg0DcHsvPIXgCmYbBa6/ZEmCh9/h1QpZgD2XlkV2YpqKlUm0pTUFZ8qnedqbGumsMo gH08TybPePHGFRDVnp+lmRtxcLxaIHpXZRrMzzv8vNfk634AoFJdxhvIOZozRhQXny8kID8+ Pn727NkikvVYTJKAoAbb/0t+G+25Pmw+2LSygRBCGkgDaSCEqD/U/xoaqAkFoj5oobICN2hB 9DCEVJRC8cBZYYgxfr0V+O83vYM19NDkH2jgj73/RtOe+N5Lr3/0fW+mz5s3b1YJgKef/i4h 5MqDAJB85dAtV5/Dld+8Zc9P3d8YGH74kd8+cfvdV/5u5c1/9fCduBl41/s/ByA9eWCZ0Pud e/C3m2+7ZV8KTXfh5re98rlbAWByZHziF986i4MPvu352O+uXMEX99363i+/go1bW5vtY1+R jn3srecmf/9kGvc88skG4Lngt8d9t+C9W/DT53H7XRnABiB5ruXbVwA8+632D+4Z+tbWGz95 8nUAuF24c83SdbfhqwO/wG8uAcCatbj40le2/MWjP/7PRuCLfa34nYy3vsN7wORKco5huC1o om8KH4ZunQcBLQuVogY75gwUVqsxdFalfuzcqNdWb8nNpGPSAOcJQL16mHQPT1Np8LDHSyVp NPcMZshEKK+L6580Cq6XLIfbwySmplURqUzE7YlQmfZC1kbDHlXIyu/xGiXkGe+teHSttJN+ 3pHWpOjpF1NlDeMnSnvTWKyy5VSQ0zxhUOExAJwn4s8zvluDpax8LYyaM85moAAyq8y7Wimk IG/GTCITSQ972TDXxto0vb7T3mQJ7lHbu0aY6HdViUyEjm56UjSFOvp4h3t42h8D1z/pj6kz oND8ZsO8SLLZmM5KPBOh0nQ5KmQUNCR9oMVID3vZAXdCW3gm+lWPIDmFrMGMKV8f0Jox5SNr xtDbEHqDyJmpf2uYNHbvoeDjJeWtKUxlTVGewWpTFGqF3IoYVn9qvhnFZkluXdJa9II7a6ny VApdNtt8HBk1A6vVEpw2vaCsOYpNiOwquPsnh+bWJHb5KCXKYOyJanU39V6poUHDyrhJNpcx 9589M7sWwyoCs5nJkLWUUZMm+s6vaUBzvO7CI52JUI8eMDykh1VvY25PhG56dE9jJlByFgGm lBIVSXkiajpevvAiIaTUPqFRK9TIfzYItdoJQJYEQZJlSZYEOSoSQiRBlTQSJJnK2MkAlXKT ZUkSBBkghFCROyq3pNZFlhAVVUElWZIEgYou0SiArHqyEKM0Is26SF2KLmWzgypnDJVeosif MSUrMttiWxWhUF3mUyprxmDNaqxV+ShH7GbOUGQpzuoYN73FY8hE0jZXYyaSPncGbUcaMxHY XBzvSI12wdaI2DluzwlGbXO8g+8+PtQGtyfe1OHqWxYJ7zvTPngkPezN0ec0QiTito7DTSub TXUgTPHyhRfztYSyEAv40WPq9wDAns5H//u/t8XjvnzTzEQTQTUK7IqCRL10CZIc99mh2akn hCjKVHWSqTqZmk9nW0uZOYzdE2V6G7VGoY4pRS4vQCyOiuTuMW7ege7jyYPbARicz5mbZwBg cjop47izp/PR/x4fP98xxtRxcmTVcxaTHLB2rwcLRDOe/WVZmmUYSiaoGYBsR3qFegUmZ8by jjtxRVEMVjCy12m5TO2SikAVcxmbPG1gT2lHAsdEv8aKjgWoajiztwyNhUzNJ2XLdKjEtwwY 6GNVD2DGsJayqjBLM8ZEuJSKoxgOZdPUnzYFHUR+XnXi5vZENP3mST1YJkJPprrQRybi570q C9bwiVnxosy3dCbi570ltZ+vEyzOGcMGsrFS/hhuXoZ2GxALYH0P3Ti5/skcJ3Ju3pHcPkBf FvK0yLCn89EjZ8/aAUGQdhz1lWvUpYwZk9sx7OZ13vfVmWHRLmXQRLjoM8c7ci56kXe/5PYE AHD9Ad1whiGw+kB3Ud6h2jzUbnMND/qVLfvp9kTCGTXlcAaAeuNU7LZ4bkH5CDP4K5nydbGU ufmAmOzZoLI2BDc/3HRIZQ0wJkLY420fPAJMpoefomyONPDCvgEcSGy0oTETcW+9es9oD7WR loNwBjSMf+vVXcmeRvXMMAmsSwONmHR70jnSycWRtZRt3rxZnSjUE5fmX81ob4Jaf7PTh2xb EoIgHY0XXmNlSdhpqmWtarSr2cmStLOzNa7YZUna2Vm+F2s2quZ4hM1YGqb4lVqBjqkapAxz E7XFfHXMLMFkj5ElAYhSZWh2RBKIKMnqAUokQhSALFHDAIQQgdqHk2RQXWpZGmOmQ6jvPSIK VN9aEIAsr3v03kIG2DHNAsWszJi5xyKYJUaYU2VilDrmiwqCOi3o0KYP9KqOBSZElGQAsiDJ YhRRSZAEgc6J4uYzBEnW54gsiUSQAblyz5KmyJcqYUfmOiHnSmKxzZhFs8fk3mDKkjDli7eI IrAN1B6TLMHuI2IUh1voPRJ3vhNjSsgpI3pQROhwC+lAR0gJiUTsDqYoqSZGcbhFJQHYBdTR o7ADpKmzOTgV902JZITGCo0BzhCLNdaBlsNAx5gScubFqupiCnV2tcyQL4wByktWFIWal1IU pbk5qChKc3Aq335TsBklLDxNBWl0hubshIJTiqKMNaODBkbHWE0MWjGTVYbn4/zqrrFkInXo flZNakULLMupYHNzcGoqOBVsnhrrAEAr2NwcbG4OAmgOTgFQn5uDNDx97hhTmpuDwSmF/gw2 Y6pAoxUvNi3b/v37WQnpz9ldygx08+xdAwKVLGV1NWMqEMYghDQDRxVlpyTHfXZJRqsddlmK 2n1OWRKaOnsVxQlZFHamsCMe9wFRQbhM+XcCEdC8Ix5fIZB+biwecqIjGNQSdgqExBVFEsgx BGfjxqVMLBRhjMW5+dMbMKYebrzoozPGuAWaQb1TpTNejILd6lHbegViVbwqFLnzX3jiS+VA l/XJ7hWGkBOqAU3GDcqCSmLQnjN6HCjKJarlWr04O6YI8pYyB+pgZctnnV13HTMHKERfVLS3 LSqDMuVD9VrD7ooykbDHy7xdc7wjS59IMwBOtaKQiVANJuO9FJXSZia9qmdfLM7Nf34LU/2M WbSb//yiJhT5dbqUmSNL7ZRhUpfpKQ97Oh8988ayHEcUgdUxBthcyJFuzESAdfQSOkvcvhSq ZulZVFlxzEiPriZLmbr5V2/JYd5BjwILvSKsFpYtmXrE3NlftVAprI6pU1gdU6ew9pg6RQPm yoSXhYqgL2X+GDg+YHCnOK16+VR91wPQ7Rm4PY607lfdMdHvCGeQzkS4/kmOd1BjLUa7XshE 3NpPmni++Dnz1c6seKnS5ZoaTRqTft7BeSJM3twok14cusk1JhdvsBLFCkDTV4XZ+YBRet0f Q5pZSGNJZTTTwR4zy2yqeSatspjWUnYYnSZqBciyYaO6klHvODMR2Fw5Gpdhj6N9MGFUrmRa 5+qnubITc10he/PP50kA7YMJ9omCMSfUT3XWKzPjTeWAHVRnkA7dGqoswPVIlXEjumpretiL TITrn/QXNmbNcJx3HDdYx0lnJtOAapoyzzGuWb4aVyITYc553Zr1yBwsQl5ZcT4Vx58yEqKa PXYAlVGnbNkYaluKtgSAVEkjW/upFKW2/NhoOj2mYUkqWcz59ELHvF+azRhzrchioUwQQO+Y N9g/mWNDXTeYnmUcvSE7DCFZVtxNAhuNvjfoFtcrSCEvO5ZM/RZ498a3s7YdSvwH/WK0E2+0 JGW8jf7eS683ANi0aTPPvwco4FH4gw+yxzWG1/tWZIWa6r/NNLb0bHfxofFYM9B8N2l8X9bb tXdlh1qWE8toW2m47V14+60Ajvq3AnjqCy3Fc5wzMFVYo7MIo34stSJHzc/RB2ZX7gYAJ06c OHr0aGfnCLASwHtXbf3Zu9/xx8dWv4Xr/N59+BgAYPLhd57+0W9++Iqe64HLeCDwpe+/cOlX vSsBIDPxype4W/texpbt99357o51+Oyx37+78X8AwOb7ftrVBAAvjp1LXP5OY/stS/+y730A EPvmt2hqSvol0nw3CPnR+6489M0rV4Bo6EHgdeDNWz859Ndbb7v2bPqE9FEA+Pnkv1zMJJL4 p8+sxF/9DQBceomV6sN7WmehhasCxzv2799faSwCKH19+69duwbgWOwNhJCG2z5ILj07s5Xh lec//zd/d6DKlcFOyBUthcPf3vnQJ4dKL2Xv+JvOt7/yxMtqCk99ocV74NS8L2WZ8W+zhr7l nofpl8tjqjz3+Pg4899lfAawoqXTYmLWKRqq52DOMbVdZXb1fzagPbLk2ZF/qjKh3/7PX1ca ZdWatTOINePsqoy+p/PRlnu3VBSlmgr+1//5/1beas9iyVD+RK5ZfmYUKRNx8143HzA1ZU8x MRwIewJpLXBas7tUxKaSm3fovmP5wAQATLp5bzgDzU5TQVYHtQOlZeeg2UETbS0Z3Vhaxo9x 816jwSmTWICbpxz3SdWIMK1s0QpScNlGqVS7Z5lIOM8bhimvbB1zb8DxDthcOHRkGQBbI1Zv eaxbNjXbQbGsrQdAC2Uord5C4260YVkRrwaruyjblOMdWL38agZc/zms3rLRhqGOq33rwfFd haL2JXsaY4EWWsjVoNlBcz1dMnpWaRnrfvWWJ9GVS54b8BDvGEr20JSbLg7olS2jgk+uGGCv 0zbXQxigfLaA4T3F/Gz+8yhhXP4eU42Nx2oqSJWY5q5jZsPNzKx28Bz3BwNtKMNSZrypVGG+ Ok+UNmMwzaxbFYepw9B8S9ea54rCfHXN1xLNnckZG+9G86NgJvYY9MTTAK2paTjqNobjvYB6 L8AqW8SdE4OhY9b3PLMnkG2qM+3W7llVG4nsxqLInpGJAEt7dq4rFoYW3RPZ0Jvwx1DaU3zb kTQAlOKrq4os+sVdKplwD09XuSpQhzzaZbbxVnCS68+kes233KG2pQBSySN+fpgWgxkLfICp 2kAdUvktkLuUFbbkmwX38DTNuPwwJktZAVvA+WtIIZci18dSBqC8XoE2HKoNU7bIdt06epk9 WCyZOkW2/xje4eYd7n4TnytG5G+Y5exmJlB3rMnydYLKRE5FcgpcfMPPrUsmUjw8Lby/1lVQ 7/wpdZ9KJtyeyFCvy/3XbaD7TSaCa1cnxk8s6000xgLcnhNjyQQ03xfJKxl60c1ePnAoAaBv /TTHb2fOMaghBCoY1aI601AXsTTQmEmzGt5zwPX4B2bCy2JGckwrgkwkvO/MxsEjjdqDOiZs LjfvGBrtcu/DYx1XW/acSCUTtC5URIt+hS6xNY1MPAxXu23a7Ynfc8AV2OrgV3dx/ZOpQVf1 XDijqZ9iS5mREChEFEz0Bzb0ZokT+GPIdxESzqAIv6B6lHNIKpOumSFiAaw3F6soH8ZaFBNf aizwbEROrwAmvQLMbq+UiVnsFaD6XsnBPIgv1ZDxPgPatH7Y/i9feJEVJr8iuZu//iNL+m3S 7KX63rg3uoen2dm4yJYuSwK130gIoQZNy0dJm9IlKRF6x55TIPNyUrutegBzi6rM5VyZEASJ 3fMXqktWx6SSCf3Yb2CnI5Nmp1Pmxo+yBgBcA1hnDLUtVc/G1MRE/6Tq/Ra5x3sysk2MAmhu OrZDNK/vDMF3H6fi6qqHwjwoioKoGBUJtYtLrVjQlmIWLQRJFiQZ8mVoZjplAPJlQpgbQhmy amX3GILU219UJGqyUZEQNX1Q47qAoA4IGcCUJjVWaBjN6BxTnbPSKhcTUyMYOZt/2ONtP7DF tJD5uee4FarS4l1UJM5QrqieJAi+eK4TtvyJYqzFjPaYap2VzhxG/mYRAyvtgwXd1eUjRyW/ SttW+b0CIL9XkK2WlM/7WSQn/xp6n55HVD1jqsP8UmULBVkdw/EOHsD2+5PHT6SSiZwTGfuZ 8949PI3TcaNFD78nsmvQhWFvY9tuE159VBRbQH1QCkQ8qoQqcrFg3GPKq2PdEzzWAAAgAElE QVQWFiS5nEomsLprqLeH7z4OZHlTDnu89A0NOaGRE25PhHKRDep3mAKgajiYcYWdoe5gSiAC gLgSsgPyyWO+3o6a1BYVMu50RwOQRcGcaNYDa2bUKQlXvVH1csllaGoftK0bbS51F7W52geP NEJXOdvABB4OqLFSycTQoKvdBmB6aNDcEiWD3RePK3HjT2oQuyZIJQcQ09QnNfGX4r1FCIF8 MgXA4I3P6JaPEb4AooCiKFHAhxIdWQ5qSi5Xh2oWkxyqrIhL3NnIvbaYBXK5OlSzYxvJyoW+ 8xcnlxehql9x1E93Fr+3tsjlOkUxcll9qzFgNK3+rPDGLYpSyeVw10mWr6zKmCBVksu1xczK UM54KkYuu4enKfmbBtLD3uWaCpl7eJpyJMeSCWbtAZRKjgXK9YWos/kua9xAWRAkMQoDo7Bm yCZ+siTB8qTpzJHW5ZuzuLEaAzYqqD6OogIRgYIc6zJRjFwealvablOtsDe2HWFiUUNtS1V6 GgCWalQyhgZdjet7NvQmSk4aRVHgDCmKYgdg98FOfa7a43HfyiYoilK9n5gcZDHODcxyAH3L IswUi9EWiXqG0xjnhkrlSv+IRIR8eUdzqtUO+gAA9qp02647crm2qO1SZpHLCwC5HUOJ6wXq aHnuMXuDI3ePGR8fHx8fp8/M9JSqAZSJ+KlikerrXf1EncfTHZV6f1edyvPUE3OERoGu7wM/ 7+X6de0kGoD+6+fNbavUJ/KtXpfzV07KuR1DfWfRZ3HFAACO76IaQLA1AidUDSYAANd/DkDT xYHnY1n6QS2aBhD9+ZBGET3WLQPgeEff6JYne9dR7SQaPa0Fu3l1DegxY/3dfIAOkUKgY2um WdWGBsvH4rwoo73C1pn0sHfv6S24p3Fo2TlVzigTSZ87Qy380F65B2faO+xY30Pl4phNtuJY 9caEtPOYLx7Pu6EuhnI2/8XZMaWhnZqLSgGWNpA3e1RZ7lK2p/PR68JEpia2UPTINZ8G8opt /prybrYOcSbCeSLZB+lpbf/XA+uKv5risvrVo+lxZSJU51jd9mMB9hMadUDDa2WgCs105Slh sm3OwG66KvorJ+Vimz9V3s3RIQaQGnSNGRZAjt9ON3AYAuuKv5riMjRiAZqi8M2rZfqwbNiL 9T3PrF7OFIhV6gA2LWWbqtCsqu4VVEReNFice0ydn8YK7YjlCpUvXJw9e5ZJndGlTz05GfRJ 2bJMbVNS0K9+PpDOqAH0JReTBcjuab/Hy1KmgdWVPBNxU9sV2hpuqgxsCv3kXw9c9JmhjFXb 1je65S7bOvR3XYWL23omdciO9UAGqUEX1PuLAWDd6a2O9uQAMAB04bADB7pgawQGWjzLcXGA X226hC7dNXikUZXhVgM/uWJgGRLUZMXVDB46eu6BiycA1/ObEhvKq5S+lK1as5aIUSXkpAe8 fJpcBuyyBLvPnGI39/RpiAsAEATJ6M+XELEDqW1K3JktytQaV+yaCEtJ/78vX3hxvpiYM3ZX U3IpK8bEZI1IxGjHNme32W2WQMj5jjEl5NTCtwrCSa7Xl2ohcUURBAk7VsRbL8Pu03tHljB1 ibQcVhSlA0g171gpw2lHXAkBiB7sbN3RbOx4U8HfOsHsjYasGVOTFEVCQnNrAHUeZ0xtMbub /xz3ymJFVseIRERUjAICEcUoIEsi5dAhSpl0Uagv6T4kECIb9YBkSRKIrMcCU3yhN8UsJA1A pehyFFMsUGTtMSFlG+B0Ak3B1EFABlY2pwAQ0qJMBQG0EKJMBVc2p5qoNEVz0K658Kbo5MZa cXllc4oKWKQuy6SlSVGUzoPRFdTJd1RkQpdNhChTQWUqSAhpDk7V5Dp5oTuPY6j9HjP3WDR7 jBFZSxmpROdOyBXBzlqN6Eqo/oiKonZpYVRXjAJEW/QgSzW/0ljQMN/8VXnqqNpqVKmQahfq O8r5S4IkA1FN+NoOWaJRmPCRJAiALt6fLdUfdQIdLH0g97EK5FjGMBg21LmfNbdlUVsstqWM XZGppi00C1Bhj5daxnDvA+4RqMmOn134+jwXPRtGyxiLTXaZsWeMAnJgWpk2F6Aq9AwNuupZ ziZrKRMESZCigiBFgahIoK1pdCkTdPX4qKBuR1EqO8mg075RURJIljK1JKuil3na8vp2FRVp vtAWtSKxZoaKfFnPI3JnTNzXJHa2jERbQ5r2basdlDjmOg7TN0QcaW5eeVlGS9OIMpYreCwS 8TAOK4pyCSFyMKqEkLosw2mPrzgoKwoo8a0oRoHleNzHYo0g1EKIKqQJ5MSqvsL1s2IXV/Vb bHsMRY60uxGr1qzNFmkHkMuBFSS55KEqhxsLQBSkUCl+a06xc94UZMnkUcAlUFZ4WYJOp8kw qC5GtTc1R3HjGCUtY9BeIYRQaXdCCBGjAq2DLBnk3XXjGJAr6xWGQqp+JXhlYhSSDFmWVMI3 KkZFQrcitWiyJAiSrBHW0A9DMtt+JEE4ip0AALssCa3qWIw6AUm2Q+PN6LlUjaG2pTcf9gJo bDtiPnWcIWdIE2kHYPfROWScJoqiUGl3RVGUkDNOu0uVf5fjcR9g135Cgg+GRigfhWZ2jZcy 4yJgZDNXIHRVOSo6+dfPim0UkKe34LMoVG5cmo1s5tnrlUpRPyRycZGE7D0mh1sMWRQEQZAo w1hjLQsqAQ1oqjr6qiWoa5yuD0/EqBhFVCQ0gYq4PtczsmdMLrfY3h2P2wFZllY2pygVizFf 60nh5LHzvrhyNJiy20HEKaX3EiV+ufOdI1FfS0tTBzqo7Qtl2wicTjiVZoP1gnl0JVg/S9n1 SC4zpDHZmG2dY9WatYAskCZuTAk5zSljMYqQE4AsSIj7YFyJtU8mqHQfrYBcXlSgZlYypvqg djQH0SJA3RRlytQghBKcMjRbGXGfnbY2W+FDUFVHVWJaEJjZOFRoqpCitGWMRTlj8jF71Szn WGpE3VnGWKyo9AbWsoyRhQVJLluoH1x3M2YOYLqNGWdqOQ5QrBmThXJseqSHvX4+QB3y0Dts SlkZ7qo1xcwqcJ12jCqcr9nKoP3B8aoVQyq3z6xnUOOF/phG2rYduXm0BwD10DCUTKSSCa5/ so9dwTHjGFXgOl3K1HtMW08qqdvkTyU1c4YA4EolXdr7BIBwRn3Yq7p/Uo0dqmF61+l+F+w+ 34yuAIy4TmfMDMD8RhR0/1RTvwvX6YyZVZSkyMtRdbNmTJ3CmjG1R0lyuRwGkjVjVPg1d9bG l+7h6Yk8fytliHBa5PJMQRVlqRYrtTs0pX1STQ/0OwAMtS1dNuzFxavuYdWQYRZZXAilyOVy +K3XHXe5TIQ93oIuNUq5I5vxUnZ93MdUh2KOTmrtjswU1uZfe5Qkl8uZ3HrH1A8/3AJYxywa DblFU5FFYktm8cHa/OsUVsfUKayOqVNYHVOnsDqmTmF1TJ3C6pg6Bdm0adN8l8FCLg4FH7cO mHWKG5AtRLuYQK/WjU7M6xxGQcAbUMdmcKvBQmeaqZu/nw8gFmB2yalZcM04uGYYJxOhSie6 VxHAzQfCGeieygxegN2q3yn6ZjI97NXclwRMDaC7eYeacr/qlYoKPEKzuqvZN1eNmMNg8Vyz kw6YaZzQBDXzu95wRo+oBoChGJo5YH8MzPcK87RCrfcyjyrpTES1IJSJTPQ7qEF2o6cV3bwv qzXNSGtYPx+gV9c5rtLUjulL3on1PRs0U+PULLhmHPycnw+EPQHYXLC5XtX8idB/H+uW223g PMNNFwde3eegAVo8EdhcWI0W3gHVL/C6loN21RA5TTbHALrNhdV4iHfA5noIAxxzWWJrBEAN nbfwDtgamRFzGCyeLxvWLSLn75rL/vo29/D0RptmNv2c9wWPGpH26EO8gxYjrXpgsfUdssNg Ep15WulL9jTGApqvlhOwudoHE5xW7I2a7BntG+qrRavs8qsZADZm8J3iru0yLg5w/ZN3GV5i 8XGX85VOFugek9UxaYAajsq3hFPEnQd1uGKhtlCXMiYsQqE5rwAAo4V1VZDH+EZzWkhfGiV9 yvQvacEUi20pYxIqzChbEYM/RTCzWFUil1xeTDDdTvJbmeNPpZIFJSJMNYmPay+3z6jDuJFT AFJly1gtNl5ZOZ7zuBEH7RVKRvs9DmQiXP9kuN9hXKVLI0MdHE27h6cLaYUzGLuEauRQtZtC Ea+LGcPAjTgApLapQ35DbyLs8d58IAFEei53bRxMTABlequgeDKZSA97xSs/vzpaYhpxI6dy pksqedztiaeSx03DL7aOKQ7WJQyaYJ+rfTBLEaks2FwbALQdaaywO7VclhaxA3lddMymTZsq 4gdu2rSJOWrTWTv79+e+KQBKdOQE218hl4ikkomFK7VcHAvlXGmKG7DAK7BYQd5g/0TR7yDU vA0hhgf6C0T9H32A+jsrNIjhW270rARg+JWdshq9QMrZBcspk3kZWJzyy1BN7UwLxrK0Wni2 W7imaADwX/I3hw/+3bd637/iTf/Xf8nf7G775n/Jf9UtX6oy6fi/BtbMKOLU2b7nvG+vMvfy cU/XQ481lx167V2nPnFz7QuxZu1w27sA4O23hr/0Qd9t5qH+4fPO7/RWRP8tWuy+8+3vf/OV 9/3Fq+/781fveNOv3vumX733jfKrzx3KD7n6z36Z/3f4s9tW/9kvP/b+G41/9H2RKGDn/k2b Nr35zW/u69t09uw4IX6W2f++/M0/XT6U/Oy7yKqt/+vUB97bve+nn7npJ5ckAP+RCuK+3b9/ toXgpvd88MHfPnE7i9V34it9t6rPr72UezmanjygPt370SuP37b9y188cg9+dc7PAfL4fjTd hczE3Vc3vvIl7pUffx7AL37Uiy3bL/lX3bd/7zf/Fs+e+tyz0UfvAwB0hno6b4b0bPdWAJvv ++m+W3/6w08D+NeRR7Bx60vfaG7t6fzqnXrWnwh+6hPLcD6ypwmIfe+TEO6deMRgyar57nHf LQCeP9qBdX/340/dcubpj9Mv//APf38LcPrIbkM93jL27W1436ZnO5bffN8He+8AgM0fb9t7 h/r5hPRRAD8Y+AhuF4733Hbngzu634Purz6wHsA7V/3TZ+7+p4Dje49/CMA/fvl+Y/v82wvj 0s8B4Kh/ayMA/PnTO2566gstAP7+S5Y90SwwrklJvkshpJIJ+lc8fQZ1wgSDwWBwZPny5Tfe eOP4+PjICG8Se/ndz+9+++1ffe2O7c/9x8tBAPjhU1i25XcXPwMAG9t+m/wqj/f8z58eZGyH U/8awLl/ykmmcV3k2vn+a/F+nPoe1j9wcD28pwEgX5f0HzL45ZleADhzDuu2PaaZo+h2Pv5D rLw41nMXAODbz/zhi6PdWwEAH/v+H34y8un09wcBYPr3LCkFKxLPPLxR+6nqwcZfwh1377sD Ot675exR0bvzMHtx5qmP3wIAePI7u5Ecpy/7Qg+OfXsjALw0/jXc+cTbL/b/KwCc/c4wdraN PPGxkb9f1vXc//pB8CO//lEUAP79dRrx2I//8+GD29cDwPRHehKPnv3P7335Q6+d/XF+Y/u+ uBXAF/d/APjPXcdeyw9gAYar6pL3ANQcU/4EKPS+ULLkDfZPdMuXgPFNGzeOv6ATfJtwtdXe YlHY1hlmwbdwTbHYLi8tWJhV1MXd5dxI5x4fOTUvHPT5lT2es9znIKP56kEYLmuKTZj0sGoc Mg0Ak+GMejvO9avSslQs1M97TSKrsbLgrtTnZCbi7p8Ept2eSu7gK4exYBUXshpkImGzqhk8 duqocSGLtK1Z31WTERUlzhKG01Cr1i4zHVUM2XTElodydxg//1S7DRt2dqUx/cAm9fR9Gl0A +pJHqFDJRL+DtnXY4zWWj06wmcn9PdaLsGf4HhikCzORNE05E0ln50vz0mUPK4exwNrP6XAG HB+gS4aaL+D2RFgwAG7eUXkFJ7mtA4GLJzgtTT/vpYvU8hXIql3RQs4096y2naDDSGvGa8Ne 5LbDTDOiEhE21+lz04gF0pp0uZ6Uac9WXBsYi8pKTrOgln+1l5M3jx7JEoOiUk6ZSJptEoVR F2eYcgx2l4VYgBu/M1XAuOvxkVN9fX1zf31es9rVd+7lZFSlWOuMe7AsqfpMJG1zFZKOYhbk 1Akzv+IxtAlqWIaaJzgbac5GIYtkVFvMWbHrRHCLteENOb/nBXRxqmEZZmMzWRCFzIf5gMtE uK0DAFKjXfSBB5IAgJ7RBDPEXgSbN2+e7Y1rvigCU7AdxvwMox+hMhG/RyX+GBXo5h0cHwh7 HJwn4vYEOFWlczqcgdsT4HhH2ONgBwmqLjuBSarhaHrGLQfsyEipzBmnwzDRz6hVWrbpicKB ywQtZNjjpdWfSSE18t0fA3MOnR72cp6APwa3J9tjtEaI008V5TOmXW/Th6FkYqz7tlSyrNlS CP6YemZg46FgyelxZXhaK/Zk+Y0/0e9QTxqG6qeHvcafxsKw7FTEArQY6tAdngbVuct+Xyh3 8wmTvHgVGq/m5gOJnstdyER6RhM9l7uAyXtGE6lD2Higa2zQBSxPJXtw8SoycQDA8tRo18bB BE7Tn5PLbQCWMvmn5StOlN0yRkwut6n8lsa2I1Wko+P543aop8N1z8cALH2+WnVEWlndGvDM C5mJ3LUeLVd2pw7dH85g70F7alCV8Nl70J5KDmRxnDKRuypVe2XEuoFqpw07Y3D9k33r0bd+ OpwBGw9FSv5Cv2Oobek9GAAw0d9VroRcLLChN9HYdoQxlmj1n152xPgzqzAArl29BgDT/hjc e+RU8rg/Bjp0h9oyfk9gqG1pzvtC+S+uQ7+G2SPJapjgnJFks5HFHPAS6pMkq4sJY8FC/YPO mbq46bdgYaGg4ITR76qMF8zsTpAxAzIRv8cxQZXUh6dNmASZiN/jcKscggg7WoU9uSKift7B 8QH1yKUFm+h3cJ6IdqidZr4qAbj71Qd68TShFU+9nzIUjOufBKaz3FgOTyMTSWvXrBoDQz+Y 6onXDUr2SDoT8RvanD4YK0gDUjaMsTX0bhqepLU2XPOp/aK3jOFMzOKm2ama9YUnoHMssptU b1v9nB0xjIcacF9mD1kTpiKet8oMAHYNJjZkIk8mE00H/TBhEmDXYGJI5RDoR67AioFUMmG8 le8b7RpL9tAjFwv20OWu1GAjoJ8j9cPZ5eWp5PFwBv6tZ1LJxEOeyFBbxu0JsItLWjBajPSw P5VMiFe2w1BUANeA0xfRrhVPP5hqic8xchTMK72F2JVM9Fx+Cobeyakg5UzorRELpJIJHH8K wK7BBE6nU6NdaUPfQesXw5FdOxMb4jKwvgDUBmSsC71JtQfDOds4HqrnvtQGpsr+WWeYBWRg bbEix1eZ1SPziJy+oD+vC/MkdWir+OzZs3MzE+qw7vWMkqy/62LCADh79ux8ZZ0/MeZ4EM9j 3esWpqtVOQaXCh766ZlPlefPvuNXz5d5Z0T1ZBkLZF3olnMS1T6pkrnalS29jDfeFrN7WeMx Me88WujUKIuiAEAQJECWZAiSDECQZPoweyiuB1sO3MPTeuOYiV8UhyBIAGQ5CoAQIkgyZEkU iCBFCSH0mYhRyJJMNRfFaFQkMiAJBo1FWZKBqEgASIKgxhIkQRB1xUZZkmVJJISIUUkgRJAQ Vb8KgkiIKIjqT1kStPcSACBKCInKkiiQqFYGWlpJJDRrSRDAPmm5ABDoK5EAQFT1Zy0JxJCv mpFICCECKy3rl/K7pgRbOXT8/vw7fsoP0c+I2uGPniyNJzmKMk6iQEei53LXht6En/dOaM5x 6WW88baY3cvCcEzMO48WOjXau1cCAHf+GOSTK+w4f2kKstTrs5+/NAVAnDULE8UtLZQJY+Pk c1aKYwc6ARxsaoEsjSkK17kTQHdcwbHLylRQBlYeVYKpFgCQpeCUEky1OENTB6PoRFBPxe47 KQgIKYIotsbjALqPBqfiPmClokwZ15xuRQmm+n1Hg1Nxn9CSUpQpMQpgpaKEkFIDN13qVcY6 DLGczc1BJ9AdV5xaGRAVpxTl0mEAmAKOndeLx3IBojumFGUMTSFFJELUGaLJdXJjiqIIkmws XmgqOKXEm5vVSrF+Kb9rrotD/57OR+uNJCt0hqn5oX9+6163KKfxr99D//yOmHzW8FyWx5ot pjDl19OXxVeo62LCbN68eb6LkIs5G8eLkmSYR1wXEwbXMZfMYitXhJmzld2eCLUuzx4AuIen 6YGbcrqe3jrwzPaB1M60f9/AMysGUjvTaZvrBY8X+HkAXalBFzDN8dv57uNDd8bTtsYWvgtA KpngeAe2D9Ar+Yl+74beI5RJMHU4MtRxldtzIpVMuPsDyeMnUskEYgFuDx441PbMnu1jo11P 07w2nQOA9T1hT6B9sKAwthGyJBxcEQ85AUAkYkgJQZZku29KJP2Hcb5jTAk5BUJ2TCk+e6m0 KgRjwsyLqKtFleWj9mzlclCS/aWLYADAugcOJVLJRA5vh7LC+tarWtcmki975FTyTmApv7qr Edg1mOi5/BTW92B9DyrROWnqPJ+6LEdFQgg5jMMAyMEVdsAZUs4DzSubAJwHOg/WnllWJZfM KDymC8JRYyOayJzK8S/AaNZYt5AEUSSi6SfG/2W8V1kLwHjBRhYtZSGzYFr6AuXRswcaWJYE yhqmkCUBkFUG9/xhBmzlgjsM21WMXkzU7QW64hFVlmoHMJgAsAHYkDwCzQkK1Una0Jugb1RD BDYXCw+gz6CsMzToAlygIde7ALTbgOQR45tGg4YWS7wcKIqi/j+kvaHbjf5Jf6grMH2+9gNd TyYTz/Ne3LlFXZuAXYOJRkxeHU0MXQtQMTDscwDmzeKLh3ImDAPj/4amgt12305B0jdajReM 8xqP+PwlyAB8zc1B437si8ePSbLxgeJgJ0IrLk3ZYYcsRu1YEe+WBEVRoiIB5q3NZ7CEXRds 5ToxpJADi608j7DYysWwKFeBMmHNFlNYbOViqENO0ZwJX17Pi8Vs4LqYMLiO2cr1jDluh5oY IaiCrWxzXet3UJe37Qe26Fzm3nUc73hgNfoGExzv0HjKhsCDRwD4ecczuJ9fvXxoUAhnlp4+ qjGRMxFu68CTyeMP8dvHRrtgc7Voifi19GdWVUGQ4nFfVCTOkEIIgcZHPo+OYPPhTgSndhxr 6jyvKIogiucPH1YUBVGRtKBjLJTql+K9l0jL4ZlxBeaXrVzPmMuFrCab7UzZyvS+pTfh7g9s 1HhWKpc5E3kymcBF6LqNZoFV/UpmnylXfTJOmchGBUnGxa4G/Yc7DAJ8qtxe69HgVNyniwNq TCGxJaUo22hEgxBhxaiJ8GU5oAzodCZbRdxMltygaTzJ8Y6JXI1ucLwjnG0sOydBaLzsHBlz JpCuGYx2UFZ4vpFoDVG1USnfOSqCykTnPwAAqITy7EnKFsdM2coab3dDbw+Qy2XeAGxIZnGZ swJT2FyNwFCyB0A7QP1+MyZySsu0EWg0sKqNDOVKEY/7AMSVEAD6BMBnB+whyhhVQk7A6QN8 cZ/6SYkDYK/V5zrGPRgAXE9v7eob7dL4y127kombPd72A10bbS437zVY36KNvI5f3bUBWDaY aGRc6dj9Y8nE07wDO7W7NZ1hrSYI4B7Ky16f8PPeu5JHTG2L3bUdfb0JABP9JQpPDq5QQoAz RAjpGFOcTuQ+IBqFU9k2QkjLfF0AWGzlecPcsJXrGXPM8q60JS22soX6whxzYmqy+pSYMMY1 gJDqrP4VcCdgZCrkQ/1KaeIC3giKpjDtjy0t7eqgvMJYqC3mWIp8drlkDEyfU1EU4wR1eyJD g43hzLp2G9y8o+lQ4pnxSZ2FFQtMrO95nvf2jW6hEpntB7bQWMmLA9g+gOPnUsk7w5l12sur 9CdLTR/lBkvSXL+aRe7IjgWwvmei37FhZxebloynlx+LHo6HDiBtc+015K5md+1qoyG1FzTO 3vwihwk7jz5naoh6JslMcV2cYRYQipxhcih+Y09N9DseOn5/KtkDTIczS1/d5901eGSvJ0JX hGvazKcPYbiwz9E+mIBxKeEdSQCrqYw5/J5I36ArnEHg6GSqFxNYF/JEhgZd/hiwx9uXPML1 Tz6JrvIF+Uyxp/PRs59dAWeI8voBEDGqhJxidFaYKzU5w1imYhcDlv31bcAJagVv4znvrsEj L3gcQ4Mueov1EAb0B+DVfY7AioHcJFZ3pZIJHqo1ymcuDoQ93nYbnkQXx3ctA4Y6rnK8o289 +ka3cLzjScNtmL+wc4jScIYIISPbFMpcVraNEELqmRVp7TD1BYtLNnuYix1mT+ejq9aspX8z txJkMLzLTiMlvW+WiZKOhNzUpnNxVO6FtCIHRnPqmXnhYO65ZNUnUpokIxryr4qoI9ySHoZL go4n9/B0VlIwT5nlqyPPl7IxrjGY0Vdw2OPV39AozAMzdaub7d3XWFQNeQ6WVTdsmu/l7EaY ma/jRYyXL7w4x3/Vl7kuSLK6YOYW9cA8Z7iuSLI5Rk7bVhq+jg798z9bAKzvmffZUhxG8jiH ujAl+fJeTufub1mE6HSWs5BCMAiJFfxaPfLT0XximrzMqzt7owq85cSqDib3MJbw+bygynsV tyeiyn3vM0iXa3dlp8/lXknlIhN/rM0F4IHj58ACsLtmw60aHabXAAx7G+/ckra5Go1ftSz8 MUwdroBwcHsiTR2uqWuT99y5rh0AEPZ42zvsxpRpFXKv6QDKTA9sDeiXaQAAWgyjAGT1MCHJ LKXWeQElvSySbPYw6yQZPevL0OSuZUnWjIyIUYhEAEDEKDM7IhARiEoydPsgskQIIYKkP6gW Q7QsxChlwLNkBUFiGdEEo6B5RcWoHl5NXYYoCGqpZEmmEYlgCANBkKh8uEhEahhFt5xNX+ZL jGtWtwXNLHfOg1ZfwioFQGTmVyzUJSqaLYVQ+gyTY3Uo3nuJXi2FpiBO2osAACAASURBVHYQ QsZCTu58J50eR4MpQlpyjHpNKYoS9xkfjBhDCyEtTYZkufOdsn1FEx18zSuBpssyQmMcISPG 8AAAe+tJoTsePykQKroPGrF5B42lwxkihBxuXglnSFGUfHYfuy9T50+2+aX8BzVac1BRlGao BooOn+80TlQLixIWSVYvsEiyekPFJJkgyUBUEkXtmUI2Ek4mKPQ+P31GyxmIGT2j4uloVBYl 8CSBuRBRyS3qS4QlFQWAKMk3yWWgNi1YKIliE+YodorCZV+oOxoV4z67IEiCJANZJBcblyaK o0yzlHnDiZqbkMsBPWgAmKIHHu1wkjUHnCEA3cGU3RcXiOCLK/LJY3bA19tBv/vicWhzPmr3 OQHA2cGiy5KsHo2MsOaNhRKwSLJ6gSlJZqF+UEcXlxYsLBSUxVamfGH16EK9QwoSe1YhS1HK pVUfBMiSzPi5BveIAARC9LMQZStrHGSBiDQvSRCAaC6XmRVDliQZOWaCZUlgNCH9JBDCSkgE 3bkhOzXpKTCqj3LAdRvbUYtMs8BQFlt5jOskTZcA9HKdRDhI38fjPiJO+ew6I7UJWNmcgt3X QgjG4oCBn2v3NRHSgjE1aHMHIU2UiUzEkZGozkE+GkyRpmMAfPE4ES7H463CyVZ6bGKfKCO7 1Y6VzSkjJzffPr9mjT8aBca482q4qBjPY3DTEl4CQDngU0GoS0bLzvo42TCJD6MwiC73oYmT +KnXXoPbXbeHmVaiUqHT1binvc5hnWHqBSXZyiVMK2LaPYyhtqVc/2RqZ3rC5grx3qHRLWmb ay/vHUr2+WNLp/YEhkaXh+Eyis9YKITK2coC5dgKRS7jhFm53lb5v5TqU6msqMhYbUaOmUBE /SLfWKRy+cUGXrPKfQaVV2CCC4KRec0ynUleVaGUpbil9DnVuw421wZgKHlEM/52BFjatx5D yR7YXO22+pB2XZgobgRjhyhK2+JHARAiKso2SXb6IJGmY4oS10PJkmz32aMiZfVS/WympU0N tLLox3ZK8XirJNuP7ZTicZ8YxeGRqJKrk+rswAgArtcHIHVZhtMOZ8gOrODOwxlXHwCRiHHN 20t3MMXiC5IcbzUmSItoWkc1LwP3GZAvt9qdaE5BXkkfKPM6rig5mVaY1zzAEqWtCCVFYGeL JGMTphBEQg7XqwOjecEs3fRbBLYpZuwfZrbYysVnC4CQmUyXheLQLRTHAtRZH7ODXFyPhZKO shwFoDrKkyVRIIIUJYTQZyJGKVVJNElTo+REVBSguuwTmXM/WRIMHvxUKQ1BkKhnP0kggiSz MIiKhIiUycl8ABpSEAkRaQpEjALyHEjlzcBlX9EzjMZdFQxsVqOMTL6wsJGzLBCis5hzAtOk tFiSDIHoN/qM+yxqJxldljlPfjmHxWwUhUZUVIWLs61ZI+vopVvCzioGq0udYUNvws97J9b3 gLkWzfYZaood6ARwsKkFsjSmKFznTgDdcQXHLitTQRlYeZRaZwez1O4MTR2MohNBmsLIYQ4A sFJRQswuu26+PRcrlalga1zBsZMsjNGyOzP3bkhhpaKE4r4pQRCVkBOwj8z+jGFG4su3UFn0 DNMcVOWL2UMW7K0nhVZVWFiBLEHnLIdaCGluBmUxd4wpALICA1C5w0EArXYca94BqLxd0AjA tg71WEJlmRVFEbLllzvGqKx0sNUONKcAnDzG+XzRKJxOAM7QeRxuXtmk27dGNAqnMyrG4yFo Ngqbg1NOnz2rGIBel3oCPdb3JY8AWa5CjT5DTeGLKwBCigLACTiVOAC7ZqDdbrDObnwOORFy qv0eUkLQDbrHta9Z5tvjPjsLY0yfhsm27A4APjt82QbgAWc8rh4k69PYksVWrhfM0hmmPg2x 1zNYg1dsjJwyuIwPoEyh8nhAkkB88apOKcZ8C3xtFaN2tAihqR0qj0uWZLvvpJY1EaPBVL8v 3qvuOdcfLO2A2qIq6/2CIHG9vtTl6I5Wpw+SDMDuOykIrTtg98VXcEBUZIZAswLbAaNdUIjR kcPOkELfwDBVsvnRPuN01ZnOzTtgb6XM5+jBTmfI17qjmYZRQk7Il2X5cpN9tgyQ1jkstnJF mDe2cs1RfLdZBLDYynOJumMr1xyLe7aUA9WIoSeiO82jnOUyzGrKkkAEUZN21c0PaMxiVY5W EoiBBaxze1l09l4khPKI9U8AZU9HNcY0ECXE8DPnqyyJmoEEgRAqb6FFhCTMBX9yBmzl68Kh 0uJA08UzgCu5ohFIa07ztuw60LXLVlrOZWcnpyjbdPW+81TKFCOHOWcIOH8JMgBfJzemxJ2C JKOTOfRcqSg+gYg0OmMoh6aC3XafHRBaslLujit2WQpOKdhJAKW5OejUfwazvwa7FWWlIADY MaXEp0TZEHEFdxgI5Vaj1piBv6MFQ5Itelgk2VxixiSZtcMsclizxRSm3Hb6svgKZU2YRQ6L rVxbWBPGwgJARcxxyhrO30M2b95cvZ9Da8JYWBgon7akmyr9l7K/qnJmnI0Fw1a2UD3cnoi7 n6orT3O8I83EnDMRv8cxwbjVhvdU7Tk97FWVnIen1X9jTO05wPEBFgCxAMcH/DGwABThDPwa Azdd2MFW2MM4vNMTOaXPk6AtjuMjp46PnNq/f//+/fvpc8XtZQZrh7nOcHl5Knk8nFnKr+5q zER6RhPY5wC6dg0mGjORZZRbHTuXSiY43oudW2ikliu7U4fOhTMYasv4PcNDgz1uXk4lj/tj AJanki6uf5IGeHWPnEru9sfg3qMG6FsPYHK5bV37aNcuW+M1rGss7BUjsGIgNbiO6l0/H8MG o4l+XYK2LORbqxofH6+kpcxhsZXrBZap2CKoaEwWarE9nY9WdIax2MoWFioqWsFXrVm7efPm WSqJNWEsLABUus1Wzw0rBGvCWFgAqAlb2e/3V2+G15owFhYGLLayhbkGY9pSW5hhj8M9PM04 wtrDNOX8qhY2MpF0Nrs5PKx6aZ/o9wKTqrRvtn1NjXldlE1cKSy2soU5BmPaAstTo11pm+u0 J7L3oj2V3B3O4PRB+rCUX93VCOwaVAWiAWjC0egZTby61YE2AHj+uH1D7zp+dVfTxat9gy43 79AYzYx5XZRNXCmqZivXZM5YbOV6gcVWLoKasJVr4hTW2mEsLADUiq1sHfotXBeoa7byoeDj FhlgwYIpSA05bhYsLGIsMCMYFizUA6wJY8FCBbAmjAULFcCaMBYsVABrwliwUAGsCWPBQgWw JowFCxXAmjAWLFQA6+LSgoUKYO0wFixUAHXCWG536har1qzN+cvX67D88s0GTCdF7g7jHp4G JsP9Ae15RshEwp5A/uuwpywvHG5ThyfZxqzKTGrGKDP99LAXha1sAbnFNq9aUbx84cWcv0Ih 3XwAgJsvVaQC5ZwAkImEM9mlLTupglUrMBjop7LLOcnx5olU1KQssJ936BqgmYjxE2IFSgsg f8I8Br/fk27vbZuIBYbalnJ8AJgMZwzefDBNfxqfAaiqdrRuWwcCF09wWnP7eS+1a7h8BZCJ pGMBAKq/eYDqvvpjNJ1JtcMykbRhOPp5L0tdT8pQMa5/0h8D1adNm1WblTarRplIGnB7IkYn 9znpT/Q7spLKRDjeQSOGPd7GtiPGT2k2yGKBCUOxszt1Wq0jC6OlRiuSv06V6fdnKNkD4LFu 9WfY44Whqd2eiD8G9/BkOANjjipsrg0AbK7T56aNrcHKb9rdbt5h6HdDi+kzIXcw0FIZG0ev Mm1b1tpZ02ndA3lFMvzK61m9qNPhDPJr1Jcc0JPal/1tfU+RrUI99Fdq48wIP+94pqZ2BgAg E0nbXI21THEhIBbgxu9M9a4rHipfc3AuFTNr3N3lVZkhPDzZ3lZu4PJBlajps98T6Rt0ocCk qMGEsTDvWLVmrd/vn+9SLDaMj4/nT4pcBTI3HxhK3hnOrGuHtsZnImmbay/vHUrunsC6kCcy NOhSbeZmIhM2V4h3DI12pW2ua/2ODTu70jbXXi0M9nj7kke4/kn+cnroAFgYNVYyoeY4utx/ zTV1WI01dTgyNCiEM0tP74s0XTyjpzDo8sfwzPhkqhcTWLdhbpptIeDlCy9Wr3xrIQemTZo7 YR7rljn+RCqZADv82RpbPBF+9RbAdjWDoY6rHO9Qd2Sb6yHewa8GbK4W3oHtAykbWjyRFAsz uoXjHU8mE8/zXWlbQguzTo3FctwqP3DIpae83sX1T6Z6l54G+rQUNsTO0a93jXdxPMaSCT8f 6Ev2zFZrLShwvENRlLnJixATwymznamRApoz+tMiyRYJ8s8wdCnRF7LZAcc7qJmvkhMmhzlR fakqmjCcxmRPVe0etDRJZqGuUOh+bAYEGDfiAJDaljV2jYfdLFTHdNkP7Nd2vP0kx/TeNMdv f+BQom9Z7fk63MgpACntmduPVFJrKFqj7Hq5PZGhwdI+qI2wJkxdw3TbL9MgHTfioNPDdKpA my3+GOjYxbC38c4t7AGY9seW0oPlDEqeN0+0UvVn1A0nA8QCWN8z0e/YsLOL2zqQSiYQC3B7 TmCmm1Jq271g02bbvdhmHoxugHz3cWhzpuDCkQdrwiwMzMBGcGpbgk4V7N+vL7QG0CHStx70 vNrYdoRe4dHLpUbg5sPevsEj+RGrgc5BtrkabQCwoTcBIJV0AcD6nlTV59KU6fZLNxabq9HY jG0uep9T5myBNWEWCsqZKvlh1F2lwEKrg1Ep2TRSe/ZsSSUTZW5u2+dVopcbOWU+Z8xQ6f5p HfrrGoXOMFZnzRcs8X4LFiqAJd5vwUIFIHN24WXBwiIAeYP9E8U+EwICAkII9H8Ie00fAUIM DzB5R8CiGtIxpGyMnp+yMXp+yrUqQ/HalVGGimqnJ2K18Oy0MCnA2p4xVv/ZL2/olt/mx36o fwzffYP9pdpmZsFCDbHrzr/Kf7l58+a///L3jW8++r43V5Ts9156vVCU7730Oihbua9v/+uv v87zRx98cNnGjZv27x/fvPlaRdmY4NZ7/+3LuOnDz1Uaj+v45ImPvnXFXV+stgBl49zwQxvd T5YZ+NThXU7xuzUvw/Bj29z7RgB8pf++dwKeL4yaBOLe85373zF2+NSJ39Y8/4WH8sXJ8kMe HznV19f38oUXjSI8lGm+oqWzUBT6ST30v/nNbx4ZGdm2Tdq0af/+/VfVUB/q+NO37yinTL+7 8LUySw+sTp/3Ffn89Y++dcXmCmYLwd8kR0teNJSF8fD/C2DwaMffzTSFvd9o89xU5HvjsYOl dTk8n/9n4F1H/Vu/+6l30zdP9bU+teMmpH7mj/1ppkWzYIJUMsH+8r/S6ZQjF9cAwO/Hgw8+ eOONN65Zs+bChQsvvPCC/v2uB//0yiEAP/vlN24HXv/FE2Rl608+fRPu2/3SIzf94ecDtwP+ b7QYU1Twzt/85DP0ec2nHol96p3Grzu+4jrzRYk+X419CcCrE1/EPa5fhe/68GP7D98NAKsI Lj//BWx54Jdf4u7/Yu+3tuDSc/sAvHx6L27emPpOx8+jHwIAvO3CyY+zlH/2z5/Bpg/+ZO+t H/jcI1/fiJd+0PVu4F++32nI/K2Tx9qwviX+dce9n/7k4wIm/tHk/Lbz21c+9/AtP/6u95YP P/D0h98CALb3Ptd/+y33f+g79/8lC/bg/p0Pvgsnn/QAGP1mO325Fhh8DQDw3vUndjdu3P2R ntvx/a+7lgPPfG0Hizvwle1fD3x4Pe/4XvtSwX3/I2vyS/Hrncf/jT59+JOtu3/wm/wQFmYb pvKsdIfZf+ONN/b19V27dg3AyIi2YP/g8JtW7HnTh577z9NbWYTbW9YAwA+fet/XXwPwU6Dv U2Ps67//7CDBv7GfF1797c3L327M7xdXf3vLzVlvVGT+PefF/RtvPftCyqwir9zm/MHFsR4g lzT5QHPTufO/fPa8fOe6dwN4xfAp8czDwO/UH7/+g1myKm55142Z1/4DwK++/4yt9cM/ekqd k7967Y+2m24EcPO2+49se0v6NwDwqVOvf75j4/TpXApqI2978UL6hQuZ9/ONAK7m5SL1fB+r 3/WvP5+Op16747Z3FS7OX3zgrXjqQ+/ArbytSKEtzAKYDLjxZQOAjRvxlre8B0BfX9+yZcvG x8eBcQA7Q9/80+VDf/rB3X9+zyiA8V88gbNHf/LVx7D7s/+RCr70yE1/2fvz31/8+u9GWwD8 NvnVf/+h8zngf/5UUypvvOu1/atu+nTSmN/PvxX8lftT1873X338tg8M//ZK7ItXhr9pWtwT nz+8+XOf/3IzADyVwaXn9hq/vgBcHPs4AAW/AJp+NroNwLOPfe3Ork//pMt+x+Ov5KR2Dpg8 5s55OfwaJoazNpmzg+KRO67uPP4HALd8+AEA+E0SAN7Bn/748nu++SqAV0cuLHXe95F3AMCr P/zhWr7xoX/+I41+36diP3ziYyNPfOyFf/je2vaP/qDd9uGnjGYe0sDSiEaVxQa/f8dHPvSP rps+NvTr/5+9dw9vK6vvvb/7PDz9o29POaVQKFiyk0ouBMUjLn1H9rbjJDUEOaQk4NjlWFYm GWwRGpBN63qaUXF0UAZE2toqKVPZNDPxpRx5DDENscaQ5mbL1pxOYeMRLkQisSUPBV56Pf1/ v3+sfd9bsiTLsmyvz5Mnz/bW2uu219pr79/6XXStf8f1tt/Em62fsf3nWf+tc9/4KX7IZXSJ KHmSzSNCbmcJZG3RrDDMIAYx+BTwot/P2O3c8HAvgMOHX/xlyy9DIbzjfvTlp9/1me+VVeh5 8Ed/fwr4l3d94K+3Wehpfv93Poljf/pdgzq8w37rE8yJz3OlEitfET/6DXr44Hv/RvzoL1EP 72CxcubeX+uH+L17957+wteVYuWP/84bDY23BwcHDc/XtvZmu6S2tbful37I3EUNmpsB3Luv koxdsRxAoQ0u8YTZwbczn9YZThjawyXsYXKuhNT90g+pLhmFUgBUl4xCKYDtnzDl9FJbfpeq 2+uDt2yl7x1Xw/9t293yHj58uDx1uND7TNm83UmUrXXbW3p5CtrGaSkVvf0rDIWyg8g1YYiH WcGXrr1bOCM7Gl4XPJcbbRAYuIgu3EO2y90NYNzdPb9h0s2grFgRbrw3gSsQMWrausphMaHU lczRt0V4TM9VkOQiXU+pejvPfIRkxiM2TwpbYSaqJ/0QfRQsTE50VgH1XSbSKUvjGeFgXqwf 8Xs9r/YmXggt4xnMHTsHyD6wiXd6wSG6XG43hHtjNNo2otXukLxlk/+JR+15wG8Pig7Rg0K5 xH24lGwhCPJrwSx5fB1hjZd3exCZGDkjtS5XJYsvXdO3S/OKYe2aXFf2w3gGRRfkabthswcn uFHSn+NubZ0N72yhpUidI7laJ52TBlxGm5JSobbAkqLtGw+ePCfM0v6bowBcIzX7R8Tiq2uk ac21HQLqH60BdTXEQSah2QSsrTYBR9tey68gLY+uRzydJgBcrRnExUldi5CzqtwWABNXkZ70 DzYWXMosF09IzhDWVs2iK5NqYH9dCmurawCQEsqta1ElaxxAJvISbhRaqN/ed97u4JaHxG7M AEB/J0xCTeTW5ahksaVD2bfLqwBWM2LTNEWQVhdbUJMvnuAG0pPdMHWcDyzNHZvWZGV4ZwtF 6hwy5EjN5+/dMAOeNswH5L18v/1al0kuNOGrd9n77iyQ0quSaxuEeMlzwtTXXHf43Y6JsY6u sbiNPABMHS+IOgWz+67Z7A7lSLVK46BxwGZ33Dlc5G7P2X23iQ/lxOEHev0FbbmNA62PzxVX kEzjgM3uUAVIaDx03u4AXsuWzHZiCHV9BRazflTUk20NLHlqh2zuBwCeg98mPub1vVq60gFF 357GDVvggTQzAUxUT6Z1/VBcQenJbpvdcRGDAGb3XSMOjYSsTOZWd8Twzm4KseZNvrjN7rgj TFphBA5yozZFofMBBwecbQSwarM7NvS3xPA8X37ZkRLJOGHzWeX2lbotnnFK2LpKLj2vggqM bKGnuDs4H3CQdTI3ub1gSkXvKr9kVGtBzw++/0rJBb5FzsDGgUThb8ubJ5/ZgrwdlDEJLr69 WzGk90tbh5LnuSMqmaOU0kLWk5Jnq6E8/ZMnUjfuqlcyZZ6ljZeyFZUsZ9iw0lLy7jWkovpH qszu3Li8d+/edldhY44cObJdRbvsDpvd4ZpcFw4CQdEspDjp/5awjf2jR6qM8YTZMP4oAH9+ wnKy+0mE7nleki2fcbdQq83kI0GCv9qEsKZLJdlBI40lORdXSTKC9UFMx90O/fYcuU1k5yGf WyZT15fg4hOdVcKBbyDBxe390wluU67HDWOpGtZc2neS7mn+yOGEpeYD4+5u5Z/ayiwEbZr4 tcViNGEykVnRLYDLHRTasyAeZCI2u2Me6y8tD6UzEb/bMS9Fx81E/G6Ha3JJ6oL5QPdEZ5UU dXpwjC1uz57k0zUWT3Bx1+R60fkouX9oFEROcCEI1N/PFhq7wEoC6y88BopubF1fgos/jz6Q AUEEx3bHI/F3sjIIf7QNJbh4zXUHyEbEtso85gOO5+AHVCGas9YcSE/6uxBpHosnuHhB+6F3 DseFoa9o/tyxQeWfcmUAAK6RmgQXJwJ6oVczEb/bMT7ZDcWjUzqf48YZTRhTh1kOZF5DxiiJ 2uGaXHc9iwQXb0KVva7PDJwdiytjTZ4di2MunbjZR54o4YctALrGpAAGVeHsAZ1zQPIB4LeT QVlkPjKZiLRBdrTtBoDmY6lNZShW0uWOnd1HThRVyeUhm90R3jcNwA5g+lp6sjvBxY/WAgAW ggku7nncpryiet/BTda8JIT3TZs7R5VP8dw1f+GKhewwguwO50d6snuwEUfvyYtS9b6DwJJH 3D8hvaGpzMRYB7BkswcFxa7pPgBnx+JdnaPjGVx8fE5zPkf4VKMJsxCcBwa56TsLwPJtYN1a XWXHwQQ3ba2usi7fBmBTv2+sAXPLBjlZl1e1Z6rzDcShz8dlDw6K7wzF5SNjMq8BCr04rD0u UhdBglRSKZ0sppJ1fQkujiuTWAiSoLnmQy3zwJ1pAEB1zTxwZ1o1Qy5esRRaiFRJZW3zj5Fi wEKQXL5/pBvieNig5lcH0NhJ1pxgbb7bzWRjusk3Lb16XbximQ/0SUP84hWLpjIAbPYgUD9Q dwPVNQM34wN1coaPng16fPX689nYQEpWREwzFZmIpOgBCBGnNEnyEkDlkY+SfHa4XIGlCcUm Wu4YVNtVycqkPFKyiuofqTIbSMk2NVsA1QACcg+gcuSjYEK95byp5ythCypJqTR2p1iZQtki qBMMCiUvyFsZXWEolAKgE4ZCKYAsE0baORYPXKJHzeLMO/2SqWB2xt2l2YvNE6VZXz7V22Y2 uiO5rRSVageG+/E52PC+uNwRbekFdaYqcWlULraOrCuMtHNMDia4+Gz/wQQX7zIBCg0Alzto sweJkRCMNANc7qDN3v2SaE8m7l6va/Z9gaXgMo5WC/usyk3u8YBDs3ks7MiKaVx2h80eFDQm xK0VUjGpGpIKhlRVyAoa68rqEetcv5F+yvaS+44AICphUN0dbQNF3Qttb5BLxt0O4rZBoa6y FFzG0UZFz4gb4cqelCD3AsALbvkOqu6Xom8VSkDSeCiBysWWItvDKHW2f5DZUA9K0AAAahJc hy2wlODq/Qvyee6KoBkA1CS4AZc7YgbS0n7qmT5oJbn19rq+JqB6LG4Wk80DCS4u6Q4BgCKH s1x8v7sbmfRzXNwMAJ3+BSRHaiYapRp2CKNhch3LQNsQgNbH58SqSghaC+mFoFDcISHzdz+h jJZRJqTdngLvCPCwJsGRHT3p7hCEBgIIP2xpIrvMbUMAzIdacOU14ZKbfWlTx5w7YlsW7h3x 2WCv62tS9swY6W3ltSKZiHAvMpGzY/H97m6g3g5w09dwpkW4XxAPFh4A4mDIxCCOh+ZjqQpR 6YeRccQbcv+cleXbAGutrkoCAOzTD+DD/ur6pHgeODjBDfoXhAQC1TUDN+N41pF+cJvcAGPj HjFZ0+FTaeDONJrOCJvHXeJPcmKT+X4GXWvBdOMALnR71OqDdrEaL7UNJXz1rsl1uaoAlleR AdAhlUt2o5vOFN4hJUIzVoqsgHR3NA0U1RE4sTe4x+bE1VPj6qulTpNP6XoGgO267lrpXlTX CGcWghNc3FgJWnEr1xTjYe3xaxWi1W84b2WxckHbt9k0AIrQDJgHcqjuIG8TUwDj7u6usU3p 2247SiOQojfUc90FjTpC5ZFb5aKcaAxyNiVWznY/itAMyD1bkLeJKYCdPltKRa67UNmzBSVR udhKqFiZQimAXeUEw5DpmZcrzQCzbDqFFdj2Cufu3bu5v6B2/4QBcPfu3W0p19Bji2F0q61j u9q+E8nHKHpPTJhtpEIEPhQ9xd2aLN8wC8EcLhGybSrrrdjz3H7OlozYjkJvF55rIznXVjEb SgFgGMYTheZAOKo8NqljQQixecWvY9lQ/nmybMjDhpAKpdQnpWNPPrnJl6dKHmFPlX8qlAJC LOOJbupGZ/3oT3DxBDfqX9Bb8wPqjWFxx1fYTtb4cMhn+5l46YSotSFdTszuJbvwNYUFtlJX QL0JnXWrOMSyAJAKJXn+QIBNhVie5/sfCgd82FlUB25M7lC9GyLt6M89EDrHwNFCblKh4zGe 5/lUCqkQS8Yly3oYhgmxDBtKkWMhcVQ4ZtgQkGIV04FMBsYTFYfhyshibwq4wqoeN6yH5JAi vwoPo1TIwzLRVMgjPps0DykPYwV6WNbDMB6pDlEPw7AhT5QUnQql5OqJpQCpEMMwUelpKOSZ YhiGnFFUL9q7iESgVSq0iPuygZQsuaa35ifUJG72NY/FMRczH2oBMJ6pstf1mRW20QJ5bD9j GeSnY3NtyERmiWlXJtJsUtmFV0sW2IC8N6wwFifW2MbW+anQlEIlfgAAIABJREFU8VgMAJIr FqDWtmjxxhiGubKC5MoiuRH591pBSDtdm7SkUHSO1tHCBlcmV4gRs8UC64qP53lPFMABPjl8 PMZj6hZwgOd5YcC1jgBgQyk+dpxhb8W8sv3z9fYpRD2zCKRCZ7wWAAcaGoYtQH+MH04EFA0+ wPPJUMrS0DBsiXoAYKQVQH+MdwL9vJC4AcCIfFU4OZzkw8ABng9LdZg5yfMxr7Ip0k9iKWDP gOd5J9A+ZUUqlCQPvtQtAKTyiuo5GxqGY9eH5ZoaBRbPTc4Jk4l4Ojew5oe44yv8kcM2WnQP gOVVMtwV3CA/dY0NuZ4VHCMQs3uVXbhkga3YG9Ybixtb51vEO+88GUohMNKDqIfn+cSIzXmy p2Cj+AJJlMKli9w5OkcLG1zp7GdDKSDKhlINIzNA9IBVnWBxCkjZai0AGtDA80lbrSXEWnnf ivLZY/FeZwNw9rdfmWrPt9LWA8NJfrhBdz7qifF8toukOowEQkAUABZXyByQfpIS2xanADBs yBubZc8Ij4bUrSme5/N5CBZ6X4rc6S+C/JQA1sczVQptwqWJwn1Xa7aKy+PX1BDDz8rc/Zxz p1/onPzVKfJsO8uGYuoHuZKox+MMh/MpbovwRJHf+3IqlLJ483746e/Ohd5nlGLlUu70F0F+ 91ieLdCZ3edbUGVvFW8CoXM262hBR47ZAmB7ZwuQ52yB4i1iC6Fi5S0kWxDTMrhcoeSmaD+0 u3/CbNf7GHJuGpZnf2Yb217hFL2fu/snzF7eOtzLbd8idv+EqUB9qsrxT0cplN0/YbC3dcko pWVPTJhtZNuDVVXa6lrhFKutnInYTgwBSNzsIwd2gAMADNyMb7gV4HdHBtW/5kgvKYyZD7Wk TR3mrFVdSqP+opgP2d62zsUG8wxN6InyYUThbPVE+bDVE7WEnUAqFLV4A2woFjvuiVoSAeFg y7RktgGqrZw/m9JWnhW9GQgHQHqy29wpmzS6AkFu+kaCi7vcQW6ZHEQmxtjxDF5aHjqLDjMw 7nYEl4XNVL/d8RJg75+eqJ60XbghbZjePzTatSZrf9nsDrQNJc6k/SeGiCG+ze4Y6D+IudeC 6LNjlYRKJtvbJAbLhjabAPiwk2EYUWcsetJpAcCeQSyGmXYwjJXneVjBMGd4PrZhbgWhVFWi fkYrh5JqK+dDHkpikncSAINc/DROTXRWqTSgSJyWxgHBdbcyTAcXH3h4jczYmsevdV3umx3r AIRCBxsx2IiCYrAI6lKpUCjldAJA1Ec27Gq95Cf21nGej5VcbXnzumRFK24KqBSK1cq6al1j AlHpTWVPoCCq+TUVYjUHcg5RSfFSVITdgZRipz+7kpjknQTAfMAxyA0AUGlAkTgtEnpVNJP5 fkbWJdOTZwyWqIdhGCbmtTDW3l4rw4ZSiM6QN6/+hyz5ybdiZRhmK9SWN6VLpggIp3AjJoS8 E9yvSYrkG+gvp3I8DET1YUGl1yop50sqxqmQhxUOUkCIZUOsIhkApK6saA7EzD1RNnBAUgqf ar+ep8XBllKEtnKWVzLpW0LxUaF8H5M+SLpMmKtrAaoGGwFuAEAX0CX+mvDVg+iqdHZIzn4m uFGArA8A6sOBpSaiAmPqMANdAMbiAMyiU4suE8brDpJfSbmy+sxCcDC/qBLOMM+HAYCXdf4E jQ+LN8Z7VWkqCzEg3FEuft7AqVpNgutwuSNkRkmrdxb9IIsTSeM5I6kVh/mGhuHYdaQssr5M P88fYFmgvT/G94dYQFC+9F4fPq5IxrK3rrerDghWxsPzYcAJRBlmhudP+rzOQC/QM1tEf5SQ BBcnb/j5X1KCFWaTqk35KIxldQezF2KwKALC2acfAEv7q6FZzCVF8nz1l/VkUytWcyuFW1OL AJLA1KL2V0knTaOcluRPhlJgGA/gHG4YiXpancBizywfdrK53/i2nsrVVt4utlFbOZvUJcfG ZUn8kkmUuO1ZtIG3XZ25OIrTVt79+zB7WZesxGTRBt6Js6Vodv+E2ZFDk7LFUG1ligFUWzkb VFuZYgBdXUvO7p8wFahPRbWVdy67f8KAaitTSseemDDbCH0pykb5V/4NNZHzoUhtZQ06ZeR1 /0KVuJdvzLjb8agnnj2NSje5BKRCjLUXqp1+GQ8bCudwBFGYNxJKvuxETeqiY1xGILioXBeC kooeLtOT3Tb3JLSKT6rEUkRLIXKlLmDluLuv1R1RZRLIz8tjdpI8L/iwi2qcJup8NCq8M4ZE JcKi3clu0vMlpaIoUjXmuWO3sRB8HtfSk35hwRGVly9iMDE2ACGaZNy/YJRYjGgpIekmP8fF E9yAqJssZ6JQji4SK8MwDBN2yt4TRaeJFuLBUfLFKHhnTIWSPF+7sggoVK0Kp1SeL/NBivaq R+/5WmS9lDN5IWgTgyorXWZnD8UcZRiPcJgKRQEPw2Y7IOlDKbDSJWWnyAlj7hx0jaDpTMsL cy3a365MAkuArPiUIzGJXCljMt/PAAtByaG4rD21aZI8zyeHowrviZLTRMDIF6Ol9lYKMyMA 8lW1ykZJPF9uTCbSPBZPcPF0RhHFWliZ1Z6vFcGQ/fY24JQm6PR8wGFzR/wLslq0LkPZ17bG I3ZC9Ra9RJbWrrFszXf2iEfsGTiBkR4fLN6ZqMEBAERnvBb4ekZK23P5U6S2MlA1MTYAYHAM UCsvd3EDIMrIRHnZpE1MIJc0AU3cKNS6yTANmKHLVqOnXCjkI8TidQJOPgbiHo6PAVB67yXW YxbAG4sB8FoQamgg13oBxLJ6N60I1lbNJgAwm2A7IRodCSuz2vP1GTkY8uDNvrOmjovuiDLo tPVwPOGDck2QrZjEpX7uWWHNXJ1rw6G+WZ/h12Z9ghuaRz4OGQXzpIbEQ8B6wGrRHwCA9UAK eJho2C6jWBqybwPIzNkZNHa6JteBJdfkurHacg7P1wAUpkovjUTIa4KkFq3PUFKRVnnE1uFf qM/HJFYyT4r5VhjG6rUYHHgYDyxeK8Os+LbtplBt5S1k27WVN4l/AblFnSIKj9gLwWw2F5rc tuW+FCRWptrK5WanayvnN1ug8oid3UIp79wqmt0/YXbE0KTsFOg3DGV72KGa1LlWGL3yQkmU CygU7NiVf4NXshIqLxj78stEcjnvE38lW2DGajI5cxh359gBKCwrSmnZXbpkOogXPPnvTCRt 6rjv7u7qsaBxwG8PDt6sSZs61gKOJl8cwvQwz6M+bA9OcIcESbw0IjORtKnjBXtw8GaNEBKZ /HkVQm6c/O0obxhnIkIRZ/rG0aHck3HZgxPcofFM/dyJbuKVBpnIvKljbhld0lW+ofFMffOD bvOhljRwHx1zJ7onbrbIpd+sEYpbXhVzEyqfl2CUUiC7SpdMgmEY7WwRebQMNA4gE3kJN7C2 agbIbAHALa8CWM0AdTWAaVVUabkfcNjsDqytrgGA6DFE+lPKzRBFEc3qHUyu7RBQ/2gNqBOU CdIPbjcBnjbFVZl0s0nefm02iYk1lVHlpqr8NjI98/KF3meU//SGA5QysPGE4XneYLaYOlrt DtQBgO3EEOr60DigDDh+GjdsgQePFF76rMtDaaDZF09wcTQeOm93AGL0VsWfQm46rMtDaXUR Smb3XbPZHUrBpblz1GZ3hB9Crpip46LdYbPrgpJLpZvMRONTn1slcFeN/EMmMg8gEylY0W5B 7AqyyJP/Fdmm9ZcoyKIbVhgVpSeWD7k2LvVnNFs5lJKTbePScJtPSmmzO57n4k3AuLu7a+yc y52euIy0qYPYR/gXkBwRDy50T3CDgvGFtMkoWnOIfrSX0qhfC3Q3Hda/b4uvtZ2jeW9rGkNa xHiifNgphH2NeuAMRz2MM7xVKkib37jMtcLot5npbKlMEly8CXBNrnddbpmfvDbRszr+7G0z wNWaAQw2ygeoawGqkmtah9SzXDxxkyzs6+OZejNwHucM3rfVr7WbpyHxEEgJYdBFPbFSZb4V 0H2Y3QDRCJ7orIKp4/xcCxo7544NAkgcfkD0KaUDYFVImTWrtuAJh2tyaeBMPfTv2wavtUvz m6h5RemJ5cPu3+nfNWiWd+VHv9J2gGjXT3QCABoHEkTeKB2gRpnY5o4kxjoEnXRTh1lntKM3 5png4gDG3Q70kDObEyGKDq3DfBhZ7GErCjphdgalej1W7WU1DiSK/QgpYHdrd0F3+imUAtjg GyarKLMQpJ1Hpc2qK+9ASLnYSPSJTCS9YRp1xUpTbtGJ9ww7VJcs349+beybhSAAvz1IRgM5 GM/AZe+Wxuh8QLQUXx6y2R1p5YGSTGQ8g3G3Q5OVcc5SuQpc9iCwJKQR80zrk7kj5AuVpJ9X nBEzWfcvEFNb6Vf4FxTZYmk8IwTlvJ/RNn9edyB3glG19zg/+P4r5f+3+WoXu9OvEDhK2+TK vXPlrj/q+hJEwC8dqGk2ofnYQW1WhjkbqQLot/n1m/cwUj6QzwATV5Ge9A82IuGrd9n77ixo RLEAoBSqNpuwvy6lLKga2F+nOFB2Qm4NBsrOodidflngqN6zJ2TfkjfkBbej9fG5HNv/BuUq MNiYN7pWr3ygOtM40Pr4HID5gIMDzjYqRbEieqFqlkqSDJWdkE2DgbKzqICd/srQES40dNsW UVEmyltK+bVGyFZ9/ukLNlEu005/BcwWVHxAcCqxrBDoTv+OIYfypYEUTndy3K311qdxtAel nCYLeg992TLcDPp8XO4IkbVok+nbLp1ZCCKPFhUKnTC7Akk0p5DjkaFDPPHOE4eJ2aSXQLB2 CECTT+Vb1G/vBmALLKnEie4IloeIRJHID5W/ijXpLkh7etzdDSzJE2D5tl6Mae4cNRQ2asWV Eo0DAM5jKN9K5If2lawCo6nsETb5iiWI5jI1zaZ6c+coMsJD+tEy0g9uN3V2oE3w9GdWSi/F jX/7wzRQD2RqTLKaWbKuBUDCV2+zPwDMCrugU4IGZ10LBPGj+OvaapMJaHsNaGnO2+uiqDNq GX821TXWgboWhRhTUa4obByEbF/YbALqUljDmglACqiRfpoPOBK+Er9pG3zD7EQ7OIqAqeOi 3cHhVOJmDbFZOl13kJgG2evQ5Buw2R1oG0qoQr0vzaN+YowVf4Jk8TpxWTAcOI0btgBOHxav qhNkJK45QBA24vTheuvyULox3mp3nL4ab0Ihr2emjvNzSIyxc2voUpxW5YwOs1rYaF0eSkMU PDYeOm93nAZgOtdKFOS2Bq2UbBvd3lFIAKZs9jC7zDZp10nJoh44hXDSLBuKxbzkf20yo9gp Ukr9AQA2lIpli7aSCqUs3jOGBeUBy4Zi16GqT87QLh6GOcnzTkRDKeeU1RPjw9JVUYs3wIZi seOeqCUR0B6EnWLO5Qodsyttk6ZnXt7uKhRMLrEywzBoGFb66iajJOlhnOHZUMp5/BZrOd4u /RS1eGcYNswr7BkWexmmN8nz0oFqbEU9cIY9jCecPCBk2z8sFwQkLd4ZxhPmT4ZSzhUrE57t EdLzYQAhlvXGfCz7kEySM8QJP3ArhRWrkEZoiCfKhxGFs5VhAPTM8mEnAIT52SiA6IzX6azt GQHEB8QZxGKYaQfDWHme9zzUHpBkVoYBkORJ/0RTcNKgS/nzg++/UuZdppIUl0tKxvM8r3nS J1csgDPMI/XwuAUWb0z5kxM42bOoSt8wzJNJIh0ocYaRCo1gRM5WjRU40JAgZZ3sUaQHAHiv t0dDgZhvJXRmSpnzcQsONCRUDQk7WaZ1Jls0JK2hn+BGHrVenufZUMrggLSY5/kkmeGpUIrO lj1BrglDtMhUp5xhIRCXxXuGYRjGA0utlTzanWGGYWZOFmYAxFh70TCsyLbWyoZsi70qJTCL 18owM8r04vnWqXY4+6far5MT2gtFoh5mEeh3Cmo+YU2oBNnQL0oWHPJ7/0OWYZiY16I/0HWU tdfKsKGUp7IdOFA2z4746I8yTGvDcDLrl89uIcdHP6X87Fzv/c7Kt1yl7BHoTj+FUgBZJ0wq xALwsKGoeEwIsQwRYbGiVEpDtvP6AlKaA3VBufNhPFHyycF4okDKEyXpU2KcY0WmEHzDeRhG /9lPSsm3zpQ9T9YJY/H6ogB83kAodaXXhlQolQpFgSlJDLY4JXwlQxH/VgHLeBS+DKNRcVxK sbutDEMCskoHKhZ7pZkg5SDBh50M0+oE+LATSJ50InYdDHNG+KCPXpmyilHCU6Hrgl+SWblu bEiYVIu9DMNIbfLQmUPJSY5XMudMNNrvRPvUlcRwP4DkrSkn4JOC3ja0A9aH5EFuJFNe7DkJ OFeSQMMBknLRVgsSjZVcJIqtk2r5tSAxQw9gSZACxByUCBLeVCiUcjoB9tZxno8Jk8QZjvF8 8kAAgMe6kkVWkAQEeTeRKIdYNlzUhill75Dzo7+11cLzXh9qnRakYPXGGIZpaIDTUmtlQyr/ hM4wwzA9s7xSYJs8EGCYVp7n2YBwhj85Q87krhNJwCZmiGk0OyX/JO1aRj1M6wh4nmeYXqB3 ajjpW7EyDHieJ2kYhmkYTsaAkZ6TYV0RPlsvw/YMX1fUN+rpXVzszeJ2fbvYiXvhuwZDd+87 Qqy8V9CIlSkVxca+lSkUigY6YSiUAsg+YaJbpuWhEvkaEGKZXD9lEWpTQTOlDGykS8aGEPWk AJYRRmqIZYmIWTgWkWXHkjSZDUmDWCNQvhKVh76H8YhSaeFgahFkfHtYVpgbuYXaAKigmVIW NtZWjs6MWBTS5BUylCxeqyeqikwgyY4labJCTVgjUD7pxPH2BiRJqgRExeSULLm2TJ0JwRc7 E4q2X/cit1BbUeFdK2jOREhMC+nAZXeQA9F0fl3vC85v7JViibquLZqNtZWdYZ4hysIWr5Vh IIqTZ9EadkKvn5s8EGAYhswNWU345IxS8XmGZawrPjhPtjIMIO/eWLwxhmECCQC43j7V70T7 VCtRubRKP0n60QAgVyDqYYgqMWPtJbrDvhUrwzB82EnSMAxzBtcBjPSc1DfWZ+tl2BnVqain d3FRq6+9fcxycSLSJAcTXHy2/2CCi5PguC53LMHFEz6IviPWxzPrLy0PpTMRv9thCyxJPjHG 3X2tJXLvsgfJV6y8pYHUKAS9trJ0L37wrc8qA1ATT27pyW4pGJgtsJTw1QPr45mquWcjE2Os cHAZaVMHJrvNh1qEwNeXW9KmDieNKZsHxWsr09myLeS/JzPwsA+IzwfaunzxueVVZAAIjiDu Z4C517oOtawBc8uClwm627MhhhuXO0K9n6LwD6pwFKqMNUkiHBHf5xPcAIAuoGusA5lIswlm 8ivQxI0CqARXozuU7N8wqRDriQIpls0uX95IQFwcgrRXEMQJnxCMKMWSDkgFogqBsrJKeUqH lZJlKeC1FAtbOpBE1VKhRZS1PVSGJ95dQ66Pft+BGUSvtAOy/BdgQynGo9q9YBkWCsExw4aQ CkljK5SCgfgY0VAKHlFUHfWoPqyJtDd6pfcMw/TaZpU/Td1KKQ/YM3AqBMoCZAcpP+mwLFkW Zc0ARnp8sHhnovKBJKqWCi2iLMouINcrmdV7MkQER8mVpAVE/ote63BS/T3T0A4oBcdeWAQJ LYDjFiAqXX5A9Gtx4LjFWdsDJFcsFliyfCDFeD4VYgEnAKLObKtFTDyQvVWIAmViw5x8mLA4 QfzdkGkcYtlwbIPYvB7rilSLhsRDwHrAapEOkAqF4PVaVIUWXVbZoH5MC2VD/6O5v2GcU+3W 9qkrRP7bA4RYJsbzUQ8D3RCXNJFPzjBMa0/PrEJFWLwcEH0yWbxWhunpgdMZZhgGPbPEDZJS 2ZmIsxuGkzFEo3BCVE+W9JQRnXE6nVBoLpMLrd4Yo1SmVqshexhPmD+pKQuyUnM0CmfMt8Iw vTzPe8UDSSc6VisUmk9ZlQD1Y5o/R44c2TDNVmkre6LQOmdRsVf8WhREyZ1gUN3zHOhXkgu9 zyhXGEMnGFulfJlztoD4taCzJX90+/qFEWJ1HrOMyCG3UFqP639LGR5vmDgr0a0QJpUEqq28 M5D29ecerEMIQREUIgouBLWhBTWkQsdjPM/zqRRSIZbMHJb1MAwTYhk2lCLHQuKocEykkZLX wlvHY0iFPCwTlU1i5QNyoVSch2XYUFTIR5E4RGZdKuTR5JAKeVjGQ2Q/UQ/gvJVDNls6bOJj KP9LcomVczup2IiUWpaWPf/ssJ7oBsk0mstqDWtJN1SSDss5Mx7Slhya0ZXJsbk2ZCKzvnqg JsHFXZPrtgs3kDuMe1LQnbNYYF3x8TzviQI4wCeHj8d4TN0CDkgePZnWEQBsKMXHjjPsLeEt IBU6bgGA/hjvJJ080gqgAcBIABC+I6VZ1x/jMfWQTw6npDSpUJLnawVNRPTz/HAioMyhP8aH w0lPFGzgAIDj7SrfpVsE+R4pKPhcrhUmt5OKEMsCUUGVGCpXFSzjQeoWFJrLmsQSLBtiGZZI n1k2pFZqjvrIi50ketZLpQmS5rIzrJylvWK0dEk6LJAKXefDxM/tyqKgzqmpht7tRoXQNTbk enbVDBJ1aN1aXWXHwQQ3ba2uynqNs58NpYAoG0o1jMwA0QNWdYLFKSBlq7UAaEADzydttZYQ a+V9K8LNstQmpcTWA8NJfrgBiHpikmzDGeZnewxEHVIaS+2tFGZGsvwqYEErS4SQyRW1z+Et o9BQjbmkZILv8FRI60QcgOza2BY6k/ASSavkqmK4HxYLkrLmclifWKKhHcBxC6agVmpOPbRa nIBC9JwKaaXScg7Whyk4LUg8lH2C87EYADaUkqXDABQSZJZhY5LrdEU1lG2pHJfJ4r6+6djl AYAEQ68abAS4UZDw6FmxxLzi/94wAK8F5C5YgFjMy7IALGEn4PQCXpBb4ORJAgCAM+CJOsNe CwCL1wsgJgx0no8JyUisBzGWAZH+WyxyGq8FoYYGKYFXFL7LOQAHGoQ9rsCB5AZfwdvEJr5h dK6NJa7jDMOwUGou6xOrlY4JKqVmi1fYpZQ8LyuKFrwtazNJ+bwWvf5yzLfCMFavRdh7JdrK UQ+ziApSRs6bKqKePFG6mEH5BBeJbSTGyQfvRjtUUoKKFQhVtBOMVIhVBQiQMZZKe9hQpZiv FAUVK5eNbFsuG4qVK1r5MstsQTZvyzt6tmwFdLZko+j93IqeMJRNQnX4S872iZU3zmBjgXKI ZRTeaAGoHV9EPYJvABq2hVIitk+srNCfl31riOJjSXtfUnMOpVR7JrIuc3TGa4GvRxBY2trB MFbhA9XZzzBWL0L9vN73JYVSDNsnVk6uOC1AzyIsMasn2uOLIemRxMfHLUBKqSV94LgFaFe5 pxV0ma3tJOCeIMSp9fK8V9RctvA8z7IhIOSz9e5Bo1GqrVwom9RWzonF2zoFPnZ86iE039rX cYZh0DMbk9wrA7rECnfMs2h1OnlA1FzuFzNSqDlfYZkR2yyPKFE0lnWZLRYrw/TM8kTRuP8h y7QuyiKBqCcWC0c9TGtieM9NFwBUW7kQ8tFWzj5hpGjairDaGrEVsVEhC4Yky/daAG9MCC3s FA/UiYUz4rCWnv3iGadFLFc4kwr1i0HBnbrLpaucUBQtZk3y35uzhZKD4iQiO0T50lKp+1hl IxNJS/+LuNyRLJ7HDCCeEzWBfvOX4miU7kIsw4qqetn18VLF7QtXssnqDpkwFAWugKSevPrS 8lA+lzAMswKAhOLhZyXxI9FBFp2YphiGEVQwFUrEUcXlospFtHcRPp9NmTMEDWiPpO/sYaxA j/Sn5lfWI6pIp0IM8awg/hSOHS+PFl9JtZUpFcvDmgQ3PZ4BUGOv69sweSrE8jx/0iafuSUK IY8rF+7ULRCdFIU+cn+Mt0qXy+edDQ3DTmdYl/MBng9L+s7h5HBS8afmVyQO8HwylAJ7BjzP OxWK0oAlsCXuVbSUWFuZUkGYzPczSD+4XYQLGMvx9ihUmsK1grq/oIOcBKYWkbo1RSzAZX1k zeXq84Y5Q6HvnM+fAGyLUwAYNqT8SZlgSylUW7midcn2GuXXJWM90ZJoVZaYqEfQfd5KKstE mbIjqMTZApRhthQN1SWj7EXy2XIxhE6Y3Qx9u84G1VamGEC1lUsO/YahUAqAThgKpQDoKxml 0ilU59rw+8Tv929SRk+gE4ayAyjiG32Lvt/oKxllN1OQnlg+0AmzZ1BpOucVSNlVutixrsl1 YGke8C8IfqJdk+vCQSAoKkF256ie3n1pPhSq+bIhdMLsJTIRv91hCywJgZRFp8wud9BmD0pK 0OnJbs2DmQQ0T092k1+lM8hE/G7HvPQnYLM7xpUJAADzge6JzozN3nfe7nhpJIK6vgQXn+is Eg58Awkubu+fTnCDZCIB9ffdQU3dte5Lc+L3+6dnXlb+21zHydBvmL3FWS6+393ddbmv2dQh zJbJdaAmwXW43BGiBN11qAVXXlOGCbAD3PQ1Mzc6nsHc43MTC0EAmO7Dmb6zY3GzmABn0rNc fC3ggJTAFwcQftjShPqBuoPNx2Du7Mi6cGViACY6qwA0H9NqK2vcl+amJN/3htAVZu+SzSmz 7bo5cfWU/PdCcEJ8sXn0bNDjq0d1zcDN+ECdLoHJfD+DO9PQJLAurwKYQ8sLV3IN9/SD2wku Ph9wAFh7/JrmV8l9aT7oAyCXapGh2soVRMm1lbeFcXd319io6lQmAlNhjm1dk+tkqUGx/js1 UrIiOpNqK1PKgXa2AIXOFogvZpuHSskolAIouZSMfvRTKp0i3scMtffpTj9lT1DEnv3V4S9u RU1AX8kolIKgE4ZCKQD6SkapdEqirQzgyJEjm39VoxOGsgOg2soUSjmg+zCUrWYprdBTzqGw TLQw/fbgfMAhq0KrvT8r89wkVFuZUmbWBV3gTMTvdrgml8jTV1QQFg4ERWasSs9m2ZXzQtBm D/oXhOzuHxr12x0v4cb5aaSBF9yierKoEy2XaKR9XCgR1nJlAAAgAElEQVSb1FYulS4Z/YbZ M0i6wBmcHYtfdEcSN/vSC0FB33HhFDloutzXbOq4KGouA7Ir57mRmgTXIUyYTKTZ1NHFTe/P VM09WDcjdnQsfnayG2iBqBONTAuyax8Xyua1lUsSW4quMHsFpS6wTHXNPHBn+qB8kB3r8m1A MHGBybwGIBNrNi15OqsA3FnA/TmVinFu7eNC2aS2cqmgK8xewdw5CqDJFwdgBibGOsiBGWji RgE0iQfSr10mdI0JepNdJoAbBdb3V5MT9eHAUpOvg+QAU8egCWgUModCBZOUGN433bTJBjjD fAXEKqUrDKUgqrpMwtGErz7/y0qlfVwoVEpGoRQA1Vam7DlKpa1cEuiEoVQ6VFuZQtmpGKww 1OX7trB1klBKCdGuMDvR68LugD6ndgSqFaaE/s4oxaFZZ+gd2UYM13x5wtC1pRJQrjP0jmwv hms+/einUAqAThgKpQDohKFQCoBOGAqlAOiEoVAKgE4YCqUA6IShUAqAThgKpQDohKFQCoBO GAqlAOiEoVAKgE4YCqUA6IShUAqAThgKpQDohKFQCoBOGAqlAN5wofeZ7a4DhbJjYEru6YxC 2cXQVzIKpQDohKFQCuANKDzoJmXbuXv3LnXLtKVMz7xs6IRE8Bqzda41KZvB0NPP1jkOpmwI 9a1c6dCVpKJQfcMIYT7dkXnxuDhcgci8wel1KTxiLoyjimqik+aXVfHkm79rcj1H2FRoqp2l aaUhE5kHkImMZ3JFcs2Gyx4E4LIrbnomks4ZFFZTeramZRkMQP6ZA367wziTgrpUTrxks8sx N12BJWU+JOJnNlQTxtx5bh5AT0d4cv2FKxaSi98eJLeB3BLyZ1o6xtJ4Bn5V2Jolj68j7I5A 6JH18Qxc9iCJsehyR1ziVaQN84Df3k3KGncLN8xl7yajVspBbp4iKwDKNC53xG/vBmALLEm/ KkoJalrkIuVmImlAimUn5y/WU8rKFlgClubFn+bVcYJIbiS9yx0hCUiHjGeEB9D9DOk0iPVX 5eayB7PN1Y0DA5k6ztsd86aOLhOwfFuZ83iGdOySyx0RpoFYooSn7YbNHpzgRqHuDdJ7Brd7 IQjIbZG7jvSYPPEUg0FqpqJzpCbLfSvdVsXsHeSG1K3Vdanizs7rDrQtQv1pRVYedWSo5+DP 0c0aKVn9nYWls404NjeZ7O/E2uoaAKQANJsAoBrYXydE9xSOM+lmE462yVn47X3n7Q5ueUic shkA6O+ESQj+xrUdAuofrQEA1labgKNtQgDER8tiLnUtQFVybV3OQULMiqs1AxhsxETP6nyg jUTGSta1AEj46qVfVbXVtKiuhdTBLEaWU+Uv1lPKKuGrd9n77iwAdTWAaVVdL5Ib6ShueRWA kCCTbjYJEfOaTXIHymnE3CauIj3pl+osIYU71v6gJsHFm8gDsq6FZCg1oetyy/zktYme1fFn b5thUP8mXzzBDaQnu7W9IaK93Y0DyERewg1lGvnOko7VDAaxUGXnSE2W+la+cWImBui7VHFn pVEq3XTDFklZVefuVjU6sfKFPjPQ1QNPZxUaD523O4Cc4TxNHa12xx1AfGasH+XiCS6e4OKt gSVP7ZDN/QDAc/DbxAfG7L5rNrtDGBaNAza7487hOMkHdYDJLIW9nuisknKwijNQyipx+IEw hhoHzkN4Ak1chs3umFf+qsSwRY0DNrsYMluRv1RPKav5gIMDzqoHtFV+NMicxg1b4MGjNViX h9Kmjot2h039MFamUdak9fE5fR8nxC7V/6TEZneQTpPOyF1t6jg/14LGzrljquBE0hKRnuy2 2R0XMSj3hsnc6o5oWyffbthODKGuT/mj6s4CmsFg3HCxyVLfGt84AXFV1HdpjrGqvr9aTB33 MwDQaneQcu/P5Qo8yyS4eDYJWn4s2ex99v7p0gYxdLkjE2I40r2Dze7QzIp3P/Gk/qP/Qu8z 2ydWLvHt1jc5J+tA6WNlpie7yWIFAFhKo968oVh5E9RvhXLNHpwtMArIWHkS5BLf7gJz25LI sorZAqDenDMxFStXNHfv3s0nGY2KUTayThjppcjljkxcRtrUkWXmrfsXqqTXVuNXqUxEd7nq qnG3o2uM6oAWDw2MUTbUH/2SkFeHUnhnIIFVy3DFNLLsDypxoXCVVOLcsuIqSb6ciaSlHKRf jaSZFErZUE8YtZBXiSS8M5bAKmW4UhqF7E+VRiFiTj+43QR42hRXmTpaA0uPekYBhfRQ+tVI mkmhlA31K1njgM3uOH013qQ4Z10eSqNPmQBtQwlfPQQJLE5fHU0cfmCz9yW4uHV5KN0YbxXS dFy0OzicSnCHWt2RRM8qSSNdBcDcOWqzO+x1aPLJOT+PvqbGODKC9JDDqQQn/ypKM5fmUd8E ClDGgLJHjhwpv9rh5qS4JS5082JlyhaSTflSI1Y2lD5vBRd6n9njE4ZKySqdEs4E2xOOxPe3 XLii33Yss1Wv7YknASS25glCJ8xewfaEA37gZDnKupTleKuxPfEk/H7MvAzABiS2YF2iE6ai KdXGpTBbLl1STpj5gCObhtXmNS0u8TyASwyjOT/udgSXkeDiW6LM4ffjEhLch4SZo4AUpyrU YLdjY6iJckVz14hCM5FmS4JTPXHvHI6TnQCXO0jeo6QDiFruWVWwNuISw+hnCzKR5rF4goun M4CowAZg3C3ocWEhuKGOaQ4SJz8kz5ZLWZPJqmWZiN+dXc3MCDphKp0ffP8Vzb98rrI94bA9 4UD22ZKe7B5sxNF7ZHTWJLi4a3JdcYBjc23IRGbVqu+FMsir/15bJU90swkAWh+fS3Bx/wLm loG2IQC2CzewkUVKbqTZommvzEIQAKYFwe/Zsfjsvmv5508nzC6FuQS/OFtgMHqIjnCTb3o8 Q+xn1q3VVfIB0DU25Hp2tdA3Fg1+zRrT2OmaXAeWyJSwTz8AlvZXg2sbSvjqXZPrdhxMcNOk AsUW6YdRe2WqawZuxgfqhL/uZ3B/Lqc+vhr6DbMDkN5S8hc3JbgP2ewgn9yJkwZXJYSlo6rL hLm6FqBqsBEu8QCNHcD6scsDJai9iqqJTvH/TuFbosuELl89iDVe5ygUVkxFkO1Dn3y6kP+7 AIzFAZgzkWYTzIWoZdEVZgdA5kmhwtkE9yFcumQ4WzRI38Hqr/AqYpO3s7A98aQtf1XUwj/6 6QqzMyhuKyPXm8mWoalqW7Z0W1T691+xbWX+dMLsBrbRbKb8lgUblnhpK2tFJ0xFk+dM2Ea3 cuVXWtleNS4mwcXLprpHKSHUX9m28AbQrqdQ8oZKySiUAqAThkIpABpQiUKhUChbAvPLlk/d Sv3gHg7necFhXD9uaRWvBgNGPND+LWgRMYzqIEs6BoD0u3ygv94gS+NLmWxJDSur+FtTej51 1hRaUJ2Nesy4H7QdUkg/SEny7wcpcf79oOqQAvtB2yGF3LsNe0xXeTlXOobpGN6ZY1iuUKVS 90s/fAOAezjsxyXg0uAgGIa5d+/evXvNRoZyLwJrQE15K0mhUCi7hHOH3prnJh4JC/n0c1/P nezjv/PGgjLM38c0Sd/zpZkiSiFXQakXMziI3t7eU6dOPfXUU089BeA6x3HDwx8ZHITff2Rw 8K7fv6bN7KM9//XFJ6S/fvw3X7Bf+Uk+lTDm9576xecP4v7kW7zfy5XsnR+KTR7dn77zoY/O LedKp6Tu2mKHHDlhfqrmmfztHw6G7370aGb+1Jm76P7UjY+/efVrI8e++rO8L98YBu8a/taJ ZiQ/d2LmJvBO97mvtb1pbfrFU+P/UsJScnCs7/yz78fCV55/dlE81fDBe+f3yyn++Xvdz/zD j4Hfajs9+uFfy3xr+qmv/1teWT959OWnq8E9cD7/qKiqVV/8cqOshLIcO/U3+UdPMvf/2ZO/ g/W/7I/HNk4MAHjiycmOt2PlH1yTrwtn3vrOL336t3H/3sDt/5ST/cY7v/gH1t/8RfJzV3+k rI2j/XjPu4Afck9PCbPAdKRpsBGzIws3/r+8a02hlIUcds25903Ihco0+jMS8gJz7x56e3Hj xo3e3t59+/bV1NR85CMfeeMb733zm98EnvL772uufP/An97/xNtSX/2C/Uuvyx9tthPf+/oH f0tKtPrto85b32XAnHz6354TDdxWv9Py4dnvAvjIuX8JHBROrt3+wFd1tXunM/6135Wec4+u DzX85T8Lf5iPvvzqUQBI33V+LNdKc/BTvbe63vJ44svVX/kZIH9h2s5/5ludbyFpHk/+1e/+ 9c9xrOPHzx5A+hePzW/eByD94JT7F5++99GjAExNN+6866tf+wXw5hrzW4Cfnfr8n36xQS7l bvDyp9C2MvDbWJo5MLjykUsXn6vHvS994cJq87e+0lCzvtj+tTdP9cP3B7/o/qsGKXrP2kvX fu/6L0786YlmALD+r5v9/wvJzw39C/CmatObgX95p/vs337sTSRx+utjH534BZpP/EOvBa// a/odbzIDeP2Vrs8sPRQz5KvrX/qz/1ey70jPfO33v/YLNLYufvq38JN/Tb/9TWYAP3n17B++ kgSOffZTvvdn7zgA/3j7SOjHYGBpax+9/p7Mt6bPvP7vwK+Z3v4m4N9aPv2JZ94rJMzc+sa5 f9j/N5fssvXMT7lP/en35FXlHe8Z/dwTkhHl+st/5/kmnhr8vdNv+4+XLn/z+uvAO+zPP3uw 6qeveQPffwwA2Hfiw6EPvvH1b9/6yLf+QyleqDl+fOiDv0pOvP6d6Gdm/wPvZb/uqsLP/vP1 t/7qOwD8fOWPvpQwP/Xk7wBA1WeutH0Gr3956D8/1veut//8nwb+/leDH8fVgfj6sQ988ch/ J/n85O7f/9F3FEtIbt76K7+pPfPbX/ik5Z//6afA2/LNhEJRh3opMOxLCTAsLp+gbZpkOaot a8Xcv3/p0qVLAC5dulRdXf348ePV1VWy0rz44mG7ndNc+Wrw8/9P7Qs//sSf/NfDq//1o6v/ 90dX/+9fi4+r1W8fftdn3nhxGTUfvPOV973vjy7KqwuAmg/cvvpe15eH/jVw8Nu+z/563Wd/ ve6zbz4xa/DZ8sPoJ1/8ufTX/jOdg+8U/0jf+dD7B95+6QcwH4n+uT1Hd7yr5i0AfvxI9c3R 9sXPf6vzLX//+c/ta/zcvsDKvs4/ePQFcanL3GtpvjQQA8yHPv3B1zzd848BZOZPHf3Kl1aF JGR1ufuFz7+zJfAni9iYql+vvfONg85vfPPRgz+ekr9Lqk+f7N2Pm5+/eR8Akp87ceU9J2Zu ir9++OIf/u3H3vRg6M/fd/LP3zeUMn/M/eozvy38th7/2EeH/P8HeMeT3Yfkcpi1Jd+Nf5X+ NJ889ilpNXv91Y///tXPvwq8/f1Pszj22T/wvR8Lf/WVps6vXH51g+r/+PV/B2B6+69JZ37r Y6cVq8vXz31D/KD5KXf+E9eOfXUVb7N/5Q8U30Cvf+8L0f+Q++NDzU+9499f9D+I442nnz18 BP/jzNMHq5D+i89/X1qTat76RgDr//zvypo0P/3xoQ/+6ivjX/to7//+6HjmHR9wfv2cuJ7+ /AfeP5z6y9eA3zjQ/h7Mv/jKPwDA+l/2T3f0LwkxQ3/jV01c/PcH4nB/7ItH/vur//sbH/+T b/zPyE/efuR3/9b1jg16IQumo4de+OSv/J3/1pf/qbgMKHsRmxjsjhwoj7e7aqVEpXbJccMn Tw4DOHz4MBGTSf6ventPPvXUqu7yVz9We+FXai/8yjPf12fd9YE6AN/+zj9+N0Ue7suffnfv r9l6f83W+6YL3524/RqAD3a3vhdg8Hb/l1vfo8vhfw7/2bef+o1HL/7Fb7z3L76ik88B+P2j 7wbwnTvaxU/J1B9HbgMtn/M+WyufnL63AuB3jxwE0Hb4AIC/v1eA05CH6V8A2LfvrQa/Vb3l gP7k+r+Qj4yPDD4Taf/1talrda3XXtjIi9C3FpMADjW8E8CHGywAHiz9KPclzn7v2Kk3pW/8 bX37347nlFY++sm/ATCbfn2DSgCM+Xeuf3If/vl73X/5Y+nkj7/+UsvZr7ac+2rLIIfjH/vO hf3KS373/TUAll6VP2COnn/qr5xvXI9+s/WTfzf1U+n06ucDy+sw/+FXTpx+239MP3df6W3t 7lcXXgGePPNh99vlk/e5DIAnnzADaH7CBOD/cIVEcf/5f5IYuAvLrwN4/8EqAKzt7QBefe31 XBdmJ3PnwVn/PxbpuI2yV5Hi1Spj1+YTxDYH0lqlXLRKDslZqnaCi+coi/lly6f6U2/x49Lg IPz+fc3N1YcPH753b/Wppw7b7fKXwf379zmOe/HF1UHgikV8hOqUNwQR2eq3Dzu/JXyR7HIN nLf2v9DztOmHFz/w9Rt7XAPH9L5rl+ymn3Lnfd99VEA//I+nBn/v9NvwygvjgVeNSs+nzlun RabZgylwDJu1ezCVOYZzDpg9NYa1HVJgP2g7xCDpuebCN/mzVZ5hUNmb/IIWGQDgRaCmubn6 8OGngNX79/fdv78GrAEA7olpDgM1ij8N4H9w8z3vvKmeyLubn185G/gz6ebvZTL/+PTT/6iY CHny79f/19h11XOkkvjZD//Y98OiFUIzd+c/cQ8o+nrKrqPkjp0KzbC4ChRdbeaXLZ8q7kpg o7c/Ic3u/oKhb3/le/vLWuet+4IxrAkdw3QM565zWcZw5b+21P3SD6klP4VCoVC2BFlNeS87 vdSEId7GmpSEXdac3OypxmrYfW3fNS3aNQ0pCP0+jeBPeY97iC10+6vC2WXNyc30zMuDg4PY k16Od1/bd02Lpmdebjv5ob32aCWtVp6h3mEpO55tjIiz7ey+tu+aFl3ofWa7q7ANaFpd4AKT ibi0qtbd4wvqk4ElkKDr7ohkoTAf0Mc/Xyfx2G12h38h/xos+RXZ5qpnPsk2QybiUtQ8Pdlt swfnt7TELUV9Z12T60IflqEnt4/5gCPvoObr426HfyGPoVXhPVncuK2QymdjISh1eOkfJmVD P3JKl5vu8VsmClxgTB0TXDzBxWf7D9r7pxNcPMGNdlUDdX2zotHN8+jzL8DcOZoYM79gD85j fdwdhC8uBrYGQMZrrHlMuORs9VI6AwjDXdG5mYgrEPTLHbQ+7u57aXmoVZiuQb/bQaaH9sLy UNe3f40M0KUXHrdIsd7l4U5uqlxVh2tyadwt19OgvWKj/Mpn30KwHONDcRMnOqu0v+obpbo1 UDZnw4Zrc1O8bZTtDs4HHHcOx5+DX34kyY/R9XF397hyTLonNc7Ucg25gnqy/G3PMm6z3z55 BUpPdgu/Zh3kZMqXsUWZiGukRupwEqR+3mD6aGqleJjkao5u6G4pmpGjuQXakYP5gMNmd9jc kfGA0cqqeyzDIBPdzVK0ffOPnRKJyJaHWsWlMrxvmtxjoP5sf+pOYDJYe6hJk35tlas1Sy6z zKZ6swlYCLY+Pke6w/O4TeiOhzVnuXiCmx54eG08U9V1uc9e1zc7RsKp15wdiye4gSbDC8tC c/XqCwtITz7Yf4YVTi0EbRduCMfTfeKgrDk7Fk/c7MNculk4iKWNqy00atA3fWyuTXhlHqmZ VS7P5cewUapbAwDmQy2Cae60cCZbw7W5ZWKCO7m2IYMn8haQnuwmA9XcOXr0XtbX3vRk90UM Jrh4YmzgqMIThPFYzYcKaDsMx22O28cNNIHM8eBa52jCV59rkHMDTWVukaljQnggLPntwrO4 ST99tLVSPEzyn7Nb3hg98lNOU0nyhpTg4omxjhrDS/WP5XyHHyk0Prvv2iaX1RItMNJSebMP VybnAfIOeP/Q6KBvIHEm7dJ8hjd2DjyUbuSSnyye1TX26QfzALB0Z/rg/mpdKdko+sLN09i5 /173xceHuiQvj9U1dhwcuBlPcNMDdbBWZ59gG1S7qmtsCBe6Xc+ueoT5s33k06iFoO26eYKL J66eKjS39IPbXNtQgosnfPWFiK2KZSHY+vicNJ2afNP7R4TvFSyvrgHSrDMfahHH89KdaXUT ih6r29t2gn7cbnj76vpmuUN37N3jmQ3GQ/nvpviNVT/ITQ/U3bizAP30yVWr/OfsNqKrZNPh Uy+NCF+iqsEpoX8s5zn8lm/fzwBYvz/32iZ7g2qRAZWrdrU+7vbj8qj8FMiPSm3OlrCnGqth 97W9pC0qcvqUhDLfGvI1I4qONkcm4noWzxX1UktafXX4i9KZN+RITdluqrrGRre7DhTKDmUP TZ8mX1y7DVE0po6JsVLlRdWUKZSdjPJtscLZm2q7exzBVYzeQGZPcaH3GTJRK1laSCtZKnZE JfNkBzVBLz/Zoeym8VNapJ6R+G8A3v3Ek3t5dQFw+PDhC73PVPhwoZUsFTuikpSKhY6fbJCe UZ6hIjIKZW+gN5bMYj6Znuwuqz0ZZfeS9wKTiciqxpmIyy6qdRZBCa2CMxGXbAoka8ELLATL PU/E+sj2aJIF+LbUxxCp02T7zSW/1G+VVknpT7vKdK5MlVSN1SX/xsNecbtzozSelSbXVhvM S4YRUin6M5VAJuIKRMbdebrGyLvPpe4VDtbH3fKgMvI2UiL0zTG8+1LFsv1qmJXyp1I9oktH 3guMqcPTduM8eYKbOia40S6TshkGjjTmBeNSeVoqHrsA1L2gN6KWflUeqKbBkv/Eqke2QKwf 5IZOK+vcOKCy095y5PqYiT0aAGQeLZ862rgt9TFE0WmNAwlffXqy22bvw9UBQQul0ipJXqgf sM/1H5R/395KyuNQXJjlFUI0W5PcwwhzPufiZOp4rj8VFkwQtvKJLxlGSEqo+jPbD7n7HV2X a8JSJxg/H4rs8/nrt49d7jAvTAZrh5TmUJLJ8JY3R4ni7gsVy/LrBllle0RrHsgbPnVzpC+c AtSUm3zxhE84JhbOE4eAupZmE4Cq5mMH59bWgVWu9pBZTN8EIJNO1rWcNQHksQsgo+gZ4XIl mUfL2K/8NaM4UCVMJ+tqzm5U7eTaOhrLYjmlqU8m4jpx+9jN0UFOZYRfvvoYous0c+doohPp yW7X2qA02SqnkunJ7tYrrwFtrQDQ5sL0NlVyyW+/tv/maJcJWFjllrEGmAEgtZpB9YPb6B9s ApnkQ3eki9ZWuTbixqL+aFvfnTUgi03G2uPXrIerAEB2VLE3WfLb+14CXrILBuetbqg7RHg+ pIvu84XgeZxLmADU2B+m06g3yzlbjpbYaGbD5gDS3Zcqtmb0ax5ZGTyiq/UPZMVT19Qx0RO0 BZaeR9+jnvggGds50hdOAQuMONUBwN4/PdFZhQyA1RfcjpeWgbahhK8KGEggaLP3AeRMPUwd E5cjLruDA4BTz3MDTSazdbmv1Y3Zy4rcTR2eWkerfQh1p07XaYs2xtThqe2+n+nIbki1fn/O 4hkr7TNoyW9/cJQbaJIPDOozH3CcnwYA7oQjKHXXltSn+EoCcj3FGqLSKknWP0gTptyVlKgf 5OrnAw7bw77ZsUOn0XfefgNtp07jtUdr6OocfW6y22Z/DThor4P1sHhR48DsWjeZDqev6uzg pvtsggH2wYGb8UH9K1Rp0ds3ZLF4MHeOTmxlRbKzPu5+cJSLDyrPLQRtgaWET/t8MBfX51h9 YSQ1cHkAIM1fH3c7gqKvlAQ3UKbmHNbf/fVxt1gxGP6arWfk91eDR7T+gayhceD5e47zGEqI UpYN0hfI5iz5N2HzWSrUzx0lS353+mx+dSuh2W1J6mMIraRIBVVy29lBuky7Rk15N42f0lJq S/6S2nwWR/a3rfrBsW1wEFlp9TGEVpJCoZQBhuf57a4DhUIpnp3yHi29+G93RShbzpEjR8h3 jGDJT6FQKBTK5lEKyqihJYVCoVC2BLrAUCgUCmVLKHCBqXBvE6UyhK7wCOSbJFvrdnery8Ym 58hm7oLhtRqfCFvB5keOZCOZO5+tG6I5cq4Q3xY7E2MtsumZlw3Pt72PWBoPAQqLMP2ZbIi2 h12m9XF326Oe+GC1dIb8uuoRDCOu7b852gWj9KJitBBjR5mDsqBn8dxlXNQkRtB271DCVw+9 7cUGFVbpZMu5jdTMjnWYMxHXiSHrVWX1xGBHMKyw1EzJEEQw4ktPdrc+Ppc4kxbTiA1vzLtK mgYa9Kqii1RV1fWewe1Q1fxnWcbJbiKbH9itmiOEjG6QGM6dbHdQZsl/YtXDdQDAgtHYEHLQ lQLFgeFUMoxtlWsKq5NpyjXuBf28IMEWO7pMuZug7zrdGe2shHEXAWgceG6t278w+u5f7P7R nj95+kfOqqY8ODhooJ2SiRjMkIJsjzWW/9UKM1G9CW51Pp4CshuarukSYyDRSKbBEAdgYaBp wxhwyuqpc5sP3DjdEzdDZ0sMyP4I9HXIAHU11QBg2l+XWs2gCTpnB6ifuBq0BZZm912bOzY9 oalk9ioZNBBGvWpYVX3vGdwOVc27drsT7umZl3MYmmzVHBEu0QwSo7kjFml8B6F23NBoNDbU LgnkUjTuMwxGmhG5prA6mb5c48rrnIAIuYndYpiVQdepzxjOSsMuEqdecm19sHOXj/b8yT0v lJR/D2b1BbfDZncog6ILNA7M7rtmsztsduUrkjp940Di8AOSxsAznclsXR5qlT51jRLPBxw2 Mnrq+s42QuXnMTe63Jp88aP3HDa7w2YPCquLqcNTO9Rqd9jcD1CXtQ66andMXMZFu5DVvKI3 DHopZ5UMGmjcq0ZV1fWe8YWUbUM9Fza8gyB3mcRXBwzGxqHTuHHe7rAFHgCvPVrTlyiSzzBG 3mMmz3IN50VxWeXdHN3zAYLbiBzTkJIdYzXl6ZmXjd/ONkmhlv/l8BSwPj6Z6ercrOFeKWNi A1gI2i7cKImrBspmyDERtmqOZGMTcyG7TwTKhmzWbcSuJPfgV6opb86Sv1AKtfwvh6eAqq5S TLxSxsQG0DhQardIlB3OJubC9vkW2wVQtxGbolESkA8AACAASURBVLwLDGVryLbhTNFQ1m+O rYfed8pWs8kpQxeYXcIedMJR0LjXRwvfHezB+04pmvJPGWpoSdnBvPuJJ/NJRt/0KRRCmacM XWAoFAqFsiUUuMDkCBZdWrbaqjxvc+tcOWj1NfOODV4oRdgSp0Isw7ChFAAg6iGHqRDLeKKK E0AqxIo/yWdIIkphbI/3CplUiNXd8U3mt+k88sq/iIJKWDd9Vlvd8NKSo7bqHi5vtQQ28QUj BYvWh3FWRMNOT3bbAkuKcNlSPG1FCGh9kHMJg8zVP6lCcEsB0knp4hNfH3rakOWhFxbUVwk5 61cORdD4HLHBDeNdy4u0LqK71G+aONgFhqBPhVj21vHrww3C39GZkR6f1wJYvL6ekRnt4rE4 dSsVvdJra8cZhmEYa69tNuzMt6zKQTBrEP9tZ1X0IyfXmNQN7OKIXum1zca8FgCAM8zHvBbl 24LyJUN3wIZS8vKkfsNQPL+iHlVeUQ+T/U1EuizqYVntQqJ/Ji5O3UopS1Bno2qFUQJl9ZTr rP5COb0uK8NGKLPSFCQt4qkQy4hFZ31vU1ZP0xbV6x7jiSrS6N725For6q/pvbwXyDJMmU1t 8gvBog3MYo1McAnZ7ISzWfbmY0JcEptnADh1tFFxVWNHVnN6ZdD4bLHB9fGus1kLGxrb6+yf 8wxBnwqx1t5FwGoFACuLZOz4gYbEwxScFqQeJhoO9AOWMC8sIZZaG2y1FqwAtd4Y74UwPq3i o2rHQCy6bHbH9kegMOlGTiYPnxSbxCrdZQXJlcWek04AcJ7saZ1JAlagof24BUgpDgjkT1iO tzdMPUzBKuZgOymtWmTUOPuHA1ZrKxqGk9neRCze6+3smVBt+xR8sRg8bCjaPjXVfj1mPKqE og3bQBIcsCobqWygpnpSuwwvTK4sLiIJWABAnVWuihkUFPWM9Ph4C8h7W++M6rLkyiIOZK2e pi0PEw3t/RbSazEeAJyxWQ/jiSYPBKbakzFlFUku4iRHNOy06novd4sUlGHKFP4FM90nrnjd q2fig41GZrH5mOAq0ZvjSjbJeZoQaync5hlAHe5ovAxkM6dXGEibO0efg590SPihpl0Dz6Pv PIY0Bpj5GtvLFGBLbPHGeJ7neT453NAwnIx5LbB4Y74VK8MwjHXFJywcUQ9DmDnJh51whvn+ hyw5cwbXd9zqIrH9qwvBYOQU4pOiCCzeWKz2inBXxVdiZzh5IKC80TlZucKqRwkAZ5g/OSNk Kr6BM1dqYzzP87HaK4z4Mq/7GrB4r7dPtU619zsBZ3/7VOtU+3XVsLLU2hZ7rcUJo6RrtdXb COfJHoy0MgzjmQEWV5J5l6grSHHCI6wuFq/P1mtlGIadQYPxVUZt8cauE+GBIpEznDwQUN0I kaiHYcjq0jDcn+diYqm1LfZm+3FLp0x5LfnLQ6ns/zcypy+XgfTGtsR7M1bgD77/Sp4OkSTT 4kIj2Bdpya8fOVvjk6KU9z0VYot/s0iFQkmvdwfKVUtE1JPP+l1Idq0j6JktXY4CpZoylWrJ Xx5KZf+/kTl9uQykqS1xVvx+/3ZXwQj9yCmHT4rNYfHGYpu4eMd+8pYESXhYsuz4cAnzU1Lm KbMbF5g9ydXhL+7UL85NkKfP8IJS7iz25n2nFE2Zpwy1g9kN7NanZ8nZZc9iet8pW80mpwz9 gtkNUEv1PNnBO4sUyg6ELjC7hL25yZ9/4t3qi4xCqWToAkPZweSvElOGypSf3douSuVAvSlT VBAVR0DScpSMsoRTir8BgNjKyCf1l22BuiSlVOzBL1dK0VS8N+W8XXiV3i/T1nknE72KCXUm jr82U5x0rS4TVREoysnYRjjDxM5yFq3EaEuyvOSTBwJsKCX9PduDnlmerC5ncF1IRNaSVOjM VHuS2GsmAjvHMROFQslFxXtTXh5qJebH0qNTfyYbpfUeZujUS1WHJb/uQa/z+yR7FTN3jhIT a9l2Un+hvvKy47Ulv13nVGqZGPwLibVFFOhkrBCcJ1Vux6Iehr11PCYZ0kU9TOBAkqwmyZVF wZuRZJOdXJG/cQoyeN4+KsgXGYVCAVDMAlPXN8vFE1w8IZkl689snInKexig8tSUXFO+1Gce LWfJpHEg4atHJuKy972EG3dUj2myLNUPkiqtrXK1Zsnv06DOq1g1smB4oabymXRSqHz90TZ9 S8lPipbqULd3c+h9dgju8kTvh+LJQGJYctzhPNkDW20WSzlLrQ2JhzvgEybBxYlbCumgfCg9 i2sclZYNYxeHxCVQdicqeTpGzOGncjO+hze8VuUUPMsZfT5KF5FZHFZSykPl2MEU4z1M69SL sBC02duCy68FTzhsdodrcj2X3yeFVzED8nEYZeqY6FlttTts9qDg6dLQ0ZkxBTgZywtnWNov EQ4t3ph+C8XijSmdguivUqxH6qWp0tkeX2SmDk/bjfPE856pY4Ib7TJlcZKtd7Atr0ZZfJAD KN7jsjPMz/ZIf0ke6HI4xzJyn7wx/397Z/fSVtb2/2/g/jOM2iHxwCfjBH4Htxpt75aCE8uA BVsP1EgHNAwUUg8kN20gDaTlCR5oYGCIQgffDmyFCkN1hFLa0Wie31FuZz8emNCq8R/4/QX5 Haz9vtfe2Xk1xutDmdmuvV6utffOuvbLtb6Lq1usk2c2ig2XqlIjCs5L0bAbFCt1hSIzS8Os i65QWrp+d+ffPl4JubiCxDeS5lNTNipemGhg8GVUpMxSkbbJ1WWAyQx3PlnNRFV5ByMZIaIu 3BfNajJw8kj1cyRezHVfBiPLHRvTEzpVMblfuoJKfyXjcRR7+h4A8D53i4kuK6YaMqthImPh 2upTEVeC+lIUReo6eCLZIipVb1k226hBfvBXjRWX7cCTT7aFUfCYK88stoFuy8qMouArmNLL hGvve3KngrytFlsRVda65ocRKbokKXG1IPFNDWFpgJpyc0SRXbVSU3WqYhzPZ7cgiYxVR/No kV1sTA/P/822vXNb6+NtQHjnfNrjnQXw6Ff2fnUs2NU77F1Az8NHPYYqnGPrrzYnvL1ZAHj4 WzY8OBAWkGA1WIiuKhw+czsk0Vxu7J9R5CpvLJUqIuhwDPMrcXV5Doc5ozufk3mfY+mQ1eMC QhGPw+14hv6ZmX5dbV3zWrlIl7h2hFqE05iiwR1Kp3eDDl93Lh2CKlSyf5ElCIsrYt/lSMsy BIlbF1JTJkqwtf0nqYbYoUFqyo2iqVW0y5Nnvul6zI2B1JSJSiDvYhO6Z2oc5ckz33Q95oZB asoEQdiF1JSJsiA1ZYIgbEFPrkS9ITVlgjSp7HLlX00I4kZBDqZFaN6PvXWD1JQJoskhB0Nc Y264mjJRGTfhemiSh3VyMARB3Dha+4m/GVwL4/qoKQOKFGY1VKnKXD9R51qhkeHYDRp0m+wV rLJdgiCIBqspK9LIR7HAtF7T3kprmW2k95jwpVHlybpmLnxhKDOlZEkeSlecqzelr6QJ4AhM Kb5HrQ2ozazWldIqTSnFd4NqVavKlKxqAakpE5WiXKr5pE8t16b8DnTqbXZSYGNXq9NgNeW2 yVf3915s7m+8wczy+szZ842jtRcfh15pC2rlii/++oi58UEwSUEAwLla5envr+e2a+ajEmw2 VUpG+/gyR6uDYwlPK/pqYJL86ZCLCUx1yQJTKT+QPxVEqSiDHmbu5FBR6JeUlLVKU6ri/hFF TJHXUKO4SjXlunC5FuiVXgMoNzqlqeAhu5mfy+VVOdRGWhpcjjBoPunTDPvG1ZKQT/ri3Tll QSXYSlG3YLbrBtDweTDOsddDH3/Zu/9kABgYH9qb3RuKTjqtSrSPL79GzOPt9XinU6cAgIHw zq037Eb1078kFf1yazYKNvPyrL/Cc/GmOLEPg1Iy15JmwZ8qprvmHQ5fMu9PFUe2NSK6rlB6 BVPqJFeX5/CZ25fM+0dmsDTscDiC26aLwbhC6ciJ2yFm0rSpa6ixtIRrAQAcbCS6FiQB1r6o rNBceoEiCX5mS0elzmAsfpDwyO8GvCbrNpW3hJJKN1rcZfkaXH5ZwjTUNUiLP5WHK5Tm3AWp V0tS3TO5ujyHJzl7KTIWu24AjVVTlnYJ42yzbXI1M2moyqhArCpirMRGzSYGGwSbjUrJgHNs PTumymNQStZZwpFbbixaiQ5/qlhUtlL6nEw+EPocStYU+79cp1z7blDUC1wSunNpvyqPsSGi Ajo6vacXF+jTPIKfn+n1lQv6J+bBEpkl8WYz5AyG4vvx949mMu1g7xIWPmmKSfrQtiw06Eaj b/3XhCd+tHPrzd4QkyTn2ja7w16TFDYnXsipl2uBGF4t10w6lq2WlJKka/wjM8Px5Jw/hGR8 aSaSAmAnBebFbxAURUZURlO4keZRU649zrH11aOYt/cdAFmh2Y6+srPdfTw7HMDOaplizDoM bQ1GMoj3ep4CePhoVDRSrw9ty0KDbjSAgfDO+fTwt5+FSDnLIx0kPGyxjJ96E4qOdblo1yXQ q6jJe0Ppov0Ui+I3CFJTbgVITdkmLaamfIXsx2v6Tpj5Ca5DYrvkZ5cSXK4FRhPH8voIfJpa hboW2FdNrgxSU75ZkHexyY31BzWnxgugma8HaLWLg/m7ceIqIAdDEMSNg1SoG0PlDsaO3MJN fodAEERzchOe+Jtk4K3qCcb6PebV9ZCtdT/WXticeIHX1q9uWZ5XeF4yJwfphe/cbG5PrqT9 d9Z6BfVYvjg2K/h1xl4pO0dDQzmHkSCuD6RF1jBq/4rM4XAAKBZNAiaU0UoMLpx0isMr1EEg cnCI4bufsvg521XYnFg5c2+9fyemONcCs++O8S6AnVec9vXFS+zl2SZyFPPOvgOAh/duI7fH Es9+DyyIra+Otet6UdiceHHmxvt3x1LkjK6eAcUAsTl+ESlbz8NHsjnGI1bYnBCnC6jKKhXC O7cwtDebOBbb0vadcxg5tmmOfI2CRAmi/rT8R/6rNkGkBhMt2aQ69Yapd+EiC8CMLui9C4Ct WZ2mWfvt+15x1xtxRthp55NsRshuhU/frBXaJl/Nes1jTjjFLfYabVPoi/4x6+2Z3VGN+0Dn E7l1fi86n6xmBE0RVT0HieFvP7OJ6MFvo9J0M32Ri43p54gK2YywGr7XBf4RY46cKSxompMq /GMWexd3xI30hb7vhsPItU1z5HmH++axtf1nyX//9cM/r9pMgmgENXAwzJ3IrqW0dzk+O4cy dl/89TE7uiBkM0Kkbz/eO7FxiY5OL74P/5ERslvhHrg7VCP7QcKz0r6ezQi/PqzEVuvihr0c 2+xj0QuLIlt/sanOn7a+/66Dn6v99n3Mb0jZTNpytruPP34pSP0qOcm55IG1ZxsB4PPnz1Fz TD8AHCRkIbVqFV3twJpTXxi2tVhU0n/lcrkWaFQHbUIaYvWk8nkwJWPJ6x2LTRD1poJ5MBX+ LrgfulSJ+/HeXyC/tmXvlnnvRU3fyhpeYx4kPJ9va1LUNijb8itcAMrb1OeIro/D1sttw6ta wxyao5j3r3v65+w6opyjfNI3hRVRcUzcErHY1fQ0zzyYyp9gotGo9UtMeg9AEHZxjq2L3uUo pgjfjb0e+vh84xIHidStrd/wZq2Ai42YKLJnfC9q9VY2s3PrTUUraPRFsxkhu/AID3/LZtbH 24Cj3+ddwfE2Wy+3rV7VqptonHfRQBpidabyj/z0aEIQNeMg4XmK37LhQfRFs1vfBUY/HYQH B9A+Hh0KxCbgCq62DRbup1YSX0/vv15tA8T3okN/iGEyXzvaOCkAjj9+KYxNOi+/7P3tnqlA RkV64Mj2SX/O4tfMoPwCOdLH8qRuba3fNhjgbHcfv/lSGBM94lLnzuqYZWuNxUIo7GZriNUK mmhJEE3AQFhQ9IHbJlczqu1lcWq6c2xdrc2qyLDK+Q0pirqluk4T1MK1Wk1Y9eOF/KekU6lO NJrUJ3smDISFAQA4L2FHIyENsfpCDoYgagn7km+RoaGvjk3EzgFluG88NZaZIZoYmslPELWE LniCkGmVmfxKpArAYlpupzUpow+x9V67SNH34T+Wrdc6qz8Vz+GXqEqJgFdVXWfs168Jkhsg yoG0yBpD7Ve0lKdbmiAGwnu8yrSSi41pcQaAsjZqIhZgeY7WAqrM8lwBllONvHKzGOuiTYmE 17MZIZvZmfveO7clZDNCVuVdVC3KNZtbldgvw2ZOfyWOYl4W5SnO4ddk0zYno2/XBI558UTM a9lBAMAX9XQfcbVaXhd0J8LEWrb0obIeKACc/V7yOOtM5RlvciVYHG2CECEtsobR8Jn8vLnx vNn1vNnmljP8q0YfzWlqVTY8aN9mm1oA9ubwm1jFoZTegWlVdyJbQ3uj4kq3S507kT7bUgsG a/khqiybpRlGgQBditmVYHW0CYJoNI2eyc+ZG29/cn4Fc+PtI857v/yy97e7o63cOf9mnNvU ArA5T95mu3aymeZpm1xdwNPpiRdnwdWx9nKlFtTYUROoTJrBxAC7R5sgiIZAM/kB0Bt8Haq5 4jcbWtGyJbkJc8Dv3r3L5tLXg0asaNlc4ZhVYhHNeRNpm1xdvmobrisUXXktaO3j3zzrEdBM foKoMZVEV9p/hi6d08YqQcaoS+WTlbJERbWrMKhDHMsOdJSWI6q8+Zpi6wSJNkPUarN4h1/W YkucQ7Ef7/2FCd0290oZtY8iIwiiQrjxcpxIPLXasSJsLMbjBTa+ytnKiroUq03fWRXThQhi urBAnbVaw0qFOGoDCK3CMi/XArPvjheGA5sXsBtgWS0qAen9uNwFtW60dQCkYjM6XO6ONvOY Rk3v7Fer/oQ5GBHP0W+oebhTLSn9BNM8T1sE0Riu8hXWaeeTbCaKy7VAbK3QNwkxEq/kjby0 SlAbgP34+08wxNrd2iodWXd+lu26rWrL+V1P/qyAQePXuALHsPbb973zf2cBbL1Zm+qb1BU5 xr1sJgpcbExPbDjXb4OFFIrv2TVllydfze6xW/uDhOfbz0JWVDyLHWSiHdqCtcI59npo+vmG b71jI3Vr67dvsbVC352/YntD0XUnUJAblU6NU9dflc1AFBYxjW1KzsJmWdWqudiYHv72s9Dc sgi2XpG19upvBKGmud79GsUi5XVaj8/OgfZCeu8YQ2yVoJ829sfDg2yVoH/x1DBLMjAeXhqd 2BBd0X58NNG1IHBjPYyGzZwNf74tZDM4SHie5nll3n86CA8O8GQ32doB3LIswDLSN8gCLKdK d6JirKRFjVjYDIArBmondL5UtSprFS24pqV0FFnJaDGCaCXU0Y+NWw+GaCAtf/zVcVx1qr+e 68FIC705HA6Hw5cUvWw+6ZNXf1Nv26hOrsMKQ51igsoOXUowqP5Ta63troolpI180lduHeUi NmGzxbIOtY7doLqcyfp92oPqkI1yaHPbSdF20LDdEtA6SQQhU2kU2cxOMeVX/b0bdAwvAcDM iF+9rd4jFcknfe5nh2LS3KlveOkQSz7ktKvJsSz9iyxZW6eMtFsqZkhJpQCzFekUO5RCGmvd SdG2kxksiUauSEXnTzxLS0vqfollZxYXhZOudMrPq19uWTJoN+gYBqtBSgWAk3nfM1WLJ/M+ x9Kh9WE3b45DPumb70qPaBLi3bli0cWGfLdSgSuULobExrZHiim/aGix6FKXLplSCrkvchdy UoPXida+NW4N7t69e9Um3BRqJdfvT+UWBWnQ9Mvb6kFjadjXnUs/+KAbePwri291w/9u0H0S KRb9EO+xiym/pv7akP/w9hAAMLOj9y6ytbJt+W6x9XxSzCB0zxWLKeSTvqlk3h+CPEBjN+g4 6eLVL+MKrTz2TSUfpLvm4925nZOpZN7/4MPU28craReQB9A9t7KoarF7Lq1qS6lMdVjyybhZ cxxcoXQK2N2WE3Inh54Ref2+7RygrWM36Ih359J+Me+h8CEfEh3k9khxxEZKKUfhTxWLKU1e l7QgB0HUkvq9OyJ01DlM2d3dj/7FXLFYzC32w9PlgqvLc/j2A3snshvkv7Jyd/cvbe8CwO72 Un+3uy6m5T+8PZzZKRaLxZRfNMRorX2Ufu1uL5nUr84eWnn8dsoXRyTk8s89fjsfnH/7eKUK 72ndXGn8IzNL8WQeyCfjS9rHRAD5ZFxYlM3zj8zojo6dlJLsBh3BXX/quj2yEARhBn3krzkm L+SIa0KVH/kJouVphFQMYYIrlE5ftQ0EQRBXD83kJwiCIOpCJQ5GHdy6G9QGKvuSeX3gaT7p Y/krjvStJhLXor5K45uN9pfTIznG2xjNWzrAVxMiHtw1iSGWMto4YC0dMUwQxNVSiYPxzy0K 7Bt8Prndncs9fjvPvshrv1OLY59v/kT8a3jp8JlbHMJO5n38AVQeMaWxbjfoYNG3mi/P+mz5 pC8Y1M/jMIzlCuxbfrFYLBbFryXqlFQqXSyyb/1Ssu6bCs9+jg2cUd6fYo3sYJjtcoXSYru5 7jjzdlNvH+dY+0JcM+Tnk/El9im/WCym/KrCOzOY2WFW5pM+E9eiuBBrZ8Kf6EQQBFEWFb0i c4UiiCfz+eTUyUjIJf8VR0QehXPiNIhiMZ0a8QBwhVYW+5UJGt1zad4AKgYoF4vFYuTEHdwF i8Tt71/MqYOLONnEuGGlTl3McW1HyUOMpFUuQUZnAyxiovwjM2KonNglh+/Dg3Q65ELu5FDV 0klOVcgVSufmWFSd2o2wGGKpJVcoXWUgFnOCzGfpXStBEIRNKvwG4597fDI19fbxnF/8663b Lf0FAHA/eIxn81Kose16bQYo28lWTcxxaVjz+Q9vD8ur2fhII75B9Kc4I7mrywPhNK8pPp/T 59LGEJeAOSx5jo6VmRQxTBBEVVCYMkFosBmmDBJ9IW42FKZMEHWEJsEQhDUUpkwQBEHUhRqq KZeihlGwFVRVbetysHVZrVQYok2hzARBtACVPsHIsbJFRSiSjV7JoDSq8SJicyUHK17AsSF2 WZesSrcITTbEFuvHaIumxWBrjdG7QTkbz7HYDdGmUGaCIFqT2rwiYxK4zN10WeZ0h9KRkykm qjh1EuGHwBoCjjlBybAhh6wb9Qyxxa4Hj/vFzNIYrW06rw+2llQqk3nsBuPduR3EpdF+pdIQ bQplJgiiNamNg5GleDVBySYRsf5U5GQqGJw6idgc4kyCknNlyyFrY4t3g475rjQbJE1w8YKt SwohVxiiLUOhzNeawuZEYPPCOgWAuDT9pSH5ci3QK6fvx3s98SO7DZVlFUHUn9qHKdtb/IMg mhT7asrc4qP/5/9N/LSQZX/0zO6sjrUXNvUpAICLjenniOrXaWdLskf6pL8v1wIxvFqexObE C7xeHWs3phQ2J376OPTH8qTzci0w+nUmE+0wzfx/TcwmiLIYHfnRbFd9w5T9tEoUcTPg+57C ptqLiBhTzOjo9J5eXKBPylz4euy65wQKSgNfj/GdrlTP/TtOAG13hr7fO79Eh2lmi3GBIGyy tf2nfBNmDc2DIYhmwjm2vnq5FuhNHAMARheEbJilB7t6h70L6Hn4qIflbHcfzw4HsPMKwNnv gd53x8DoghBpA0wzC6tjV9Mv4kZS0TeYfNKnitLS/lV+RTWUSa4vmm8jdqKEzVQ3uXHDpuFv umCu2gcNK/0yD2jWdEOxUJ+iD6e2qrDu/boinGPruocVYwoAoH18Wf9+TKRtcjUjZDNCNqN6 V4bBSEbIZoTVcHR1edIJoC+azQhizZ1PVjX5zTLXqpcEYYdKP/L3L3afil/1508eL4rBWPph VyXmn0/6dAOWSibZnfSJEvlyMc24pY+BlslrCtoJO5bqCiblCCt9c9yP7PpmxTgxMRJYsyve Leoyz52KyxfoUnhxw8bQZD2WM3EqnpqkqZFrmKFjUhSeMcUQTm1VYR37dcMwcWAEceVU/ors QdfJ/C7mTre75+YwJc4ScT143P/s8BDAUjw55w+likXkkz7HMyzm0sWQpgJ/KrcosMWF88k4 uufSxRQMocbduciJe3ukWEwBwG7w2YneEKkgAF3rEMOOU8gnfVPJvD8EcUx0AbtBx0kXp7l0 yPgVyRVKp4Ddbenv3MnhofAhHwq5DEENrlA6EnQ4HAD6Z2aAbk4Kg8UNp/UfrPwjM8Pbuym/ Ov3wmdtxslNMFwHkT3lnw58qFlNlB1jo+2VlWO7k0DPiAgBXl+dwOwfAkOLSVJB2WVZYx37d FMwCDQiiVlS5LngV32D8c91B3xQi6RCSLEWaDoPdoGNYAADkkz73SaRYRNDhS+bsTJdwd/ej /3EuHXLlkz73SZfL3zUzHE/O+UMuFvU7YlKQ07oBV5fnMP4hHwq5pKoMzdnq+sgMYJJ1NziM nWLRL3XdxUmBFDecUo3BFkNo/2Iu3TXv8J3m0iF+DqmC6gMsdIbJ+EfE04BkfGkmkgJgSBE7 mNKYYVZhg/vVopAQLWGfslzF02f/ZpFg1XDN1JRrdyvL3nLRBEFCj/0w5Spv7qqnqX6bRPOj vratkUONufmtL/5rrKZcuxhoVyidrk1NBEEQBA9SUyaI2mMyS7+uqONoRGmLauuroA5zlbu6 NNdgJNFawiaVhylrYnt0KSywS0MNRZftCRtbUZ62sYUdYt8rr8TCkhLXsk4yWZ3EEZrRnwmO PHMJrsXvvwkpbE54E/sA04CJHbCU6bWCNkXScdmP98YOKmpod/6ZRxLlk1WFlN+K5HJkN6Te YMGODvla1Mbjq7yWui6V2KtiRNAtSUCp/Z2xEiWFJ+mtvvZ15hnN1tcjO1fJQKUGOYMURK8r q7NZNa1ANNGfWsHUNZlWURqPt1f9rx5NVB6mnNPJKatTUikWnZpb7JeSVV877AgS2xE2Nqos 25I61mkbq2OdHb7krtiIfOGZjMK7QUl3UpVUZpC0tcqyP5V+8MGn/UmoOqGTTOYFDYvwYoUN 8szqw2N2NMw6RVjgHFv/Fb/Ejy42YntDN1L7qAAAFThJREFUW9EBAJqJ97nzS5yfZbvaWZzx YCQj5ikXd3e/RpMOAJA7OZwZYeuaj8xIoqj9jx+4tBtQ/+l68FhVU+5EXhVcFp7zzy3imXt4 qX9xTvvGOn8qqFcwl+s3VpI7OVQ0Wo128+CabawnfyqIGfwjOpVB0TbpSHFtkCt3hdI7GA7u MuFy9Xdfe+ZeA9hcK/VGzbmKV2Q2BIkBG8LGRpVlWzXrtI0Z3XPpYjG3iLenD8SND3kLbeZ8 Mi5of5zczDpZaMUHpLpODkupLANwPXjM/jBoSholk5XfsKvLo9VXlgxUqSnLaQY3aXY0TM4L UZqB8M6tN8PfflZNqzz7PdDr8faKiQNh4V9/iTeSZtKWJXGF0umued0bA38q1x1nKTaiY8Rb HLda5tyfKo5sq+6c8kmfQ1SJLaa75rX3Ga5QxKO+VmBSCRv8l4YdDkdwWy8HDsCfsht+Y6zH FUpHTtwOMam8sgazc91xzdFA/sNbT6S1QoPq5FoYV/OR3xVaeeyb8sETSbv8+cfx+eCJ8Hgl bXXaXA8ewz2/G0r5oYowXmIzRna3l/q75yqs2RSLCGbdxA/rzJpS2iDpUiiTT3SI4XSqXZww YhW6WGFuPDFRO9rHl9fZ1kHC8/Q9RhfUc/LZxPuousBAWJSEqQo2bUiDK6SdgCZHt+g28knN lDJ1Bm2t6vr8qWJRb0HanfT5sJIOacNo9Kap/k6lxIq5YTeSGXyzAUM9u0HxVm9JEGdfaWvg dsxoA7tlnNlRueXdoO90Ls2NuCf4XLMw5SYin/TNd1W6qIq9IGl2PbfW7VLzQ2HKRKvyv//5 H/uTc29imHITwWbBV17YRpC0P8WZ/U4QKn5d/O+rdXLE9cK+nHZNhLcpTJkgriukvU/Umypv X25mmHLVVB3frA9OM4kw5mfW7VFH2VFkF0EQTcMNDFPmFORLxRvDjtWSz9p6DHlMtZk5Sszm EcYWss1s3oMczbUbdExhhQQhCYJoHq7iGwyL9Eo+SHfNx7tzOydTybz/wYeptyzaSx5etULI Dz6wodYFYDe4tA05TNkPcRQvpvyWNcsYC4bSkaAvmU+HkJw6iaRTLo7K8gMoYTb5ZJx1xajf LOXJJ32+pNuozcxRYjaVJbaSbZZlc0LpNNsV2XY4HExBkgIDbgSkpkzUm6tTU66CKw5T5hX0 pyLbvmAQiDBhXzthx1z95sO3H/KhkCv/4e2hJ8IpxVFiNo8wtpJtFhEfclJI+oTFXDGUCzrY YSJuAhRFRtiH1JSvOaTRfP2hMGWiVSE15WsOaTQTBEFIUJgyQdQUlXKlZrtk5pohhRNqolt4 +soVKx/bad1sp0qp0m4py6oaB0kplw85GIKoP4qm8lGMbdTctchDdP7D20Mp8fCZWwxzHF6a 0WloaZWPdYGYSvCjUXtYpYhs1B6WW+fJMMu4Qul0yMW3WemOuRizLqe1YZy9Og1ZxfuKO7kt tpaUMppaTZkgiLLo6ewAAOd3PfmzQu2rz394CyZu7ApFZBVh1eSBHQxr4+W1ysciuRM20DN5 1XzS5xhewtL2Ll9WWdYe5rTOzW/HZhkLMWadyeaGmezVyiorAsxwhdLFlN+ixZaRUkbLqikT RAvjHFufORtmd4Uv8Hp1rN0qc7v7eGE4sFl9s65QegVTbHJXXAppVD3BGNSU1crHrlDE88zt cDh82+gX9+8GHQ73s0MATJXfqIhs3bplfiubjVhXVc1egx1iJn6pFpRSRp3VlCmKjCA03Kgo Mgp7tE0rSM9SFBlBEI2Dwh5t0yLSs7FYrJHNkYMhiGsMqSkTZUFqygRB2ILUlIl6cxVqygRB EARRCnIwBEEQRF2gbzAEQRDVUm9l67JCFmuiU1kTyMEQBEHUgPpN55Bdi50g46ZaxIFekREE QVxX6iTxUivIwRAEQdQU8xXQa05d5+FXDzkYgrgx1FBhsy460NVR2JyIHynbgc0LXK4FTKRF Tey/2Jie2Lg0beIgYbWXYb4C+g2EHAxBtBxs9DRKOOsyAAD2472xA6b3PL1WkPaaaj8bqtJX aCxyuRaYXivYaFTfxFFM3HsU80r5dTUoHMV+OgtG+tgfF399xJCv/WAj0XV7kCUdL4gCcbJf MaaoOUh4RHel6vJA+DVi2nYNKEKZri7P4UnOMnM5PH3277t37z599m/rf58/f65Zk1VDH/kJ onXRSjgPyunnZ9mu20yFczCSGQRQAHru33GaFDw/yx7jHGgHAG1VcoW6DM6x9ZmEJ370G2a/ zmSiTuDAslFOExe5nvtPnAD67o3iE9dsmcJFrqfzCQAcxbyz7wBg1AMA7z2nszuvgJ7ZHZ3w qDFFzUBYGAAKmxM/LWQBHIQHB8Q9ufNLDLSZlbNYAb1KmDJYyWyxWKx5fAw5GIK4MTjb3cez wwHsrIYFJDzeWQAYXRCkG39TBm4/wuwv3vcYffgIf389BzpKZXACA+HfPvf+ggWBDc0Dlo0a axgYW59JeLy9wMNHo6VqcI4Fu6a/FMYmnX3RXx/mzsfXb6cnZDXrQiV61fvx3l+2AAA9s09E 73L5Zc8VXDX3LgDgTxWZalkoXayg2RJcL2UgUlMmCA3XSE251ZGfReCd21oftx7WAeBiY/o5 onZyVmhP4OKJyUNPXcdJ+ZrUhSnLIWTqYVwtZlwnSE2ZIIjrTl80m4mWU6B9fHm9XsYA6Iuu lnrUayxNHkIGcjAEQRA1oQHK1g0W268ecjAEQRDVUm9la+a6bLbSPDLbFKZMEARB1AVyMARB EERdoFdkBEEQ1dJUaspoGkFlcjAEQRA1oEnUlNFMgsr0iowgCOK6QmrKBEEQNwlSU5YgB0MQ hCWyxGStFJTLkj0uCztqx/WG1JRVkIMhiJbDqAQs6xarN/SKy3IGnZixiuOPXwrQSyZzZJsN QsgKpWWPfz8AcLkWUCkoG5uoWO243ly1mnJTCSrTR36CaDmMSsAdkm5xQbUB4PwsO8pG9r57 o7OfzgEYUtS6lqL4sUGeWS/bbBBClikpe4yH9wYAtN0Z+n7v/FJpXddExWrH9eaq1ZTRTILK 5GAIogXRKwEXTPINhHfOp5k+8aNfM9EBAMYUSYP5le3mnQYhZNWuErLHPfgU6P3lmOklt5la Xrnacb0hNWUFcjAE0YIMRjJCRPW3c2x91WRjfFkY15Rt16coopNiEbRNri4DAMRKDOlHsafv AQDvc7e21gfUtWEwstyxMT2B6Pp4eH1AqURlVVjRuHSaNWHoo6h2HDZd4qXl4KopNxXkYAiC qDklhJDrI3vcdGrH9aZp/YoMORiCIIgaQGrKRsjBEARBVEtTqSmXlbOuUJgyQRAEURfIwRAE QRB1obSDiUajdVJwI4gmxOZUA4IgSlL6G8z1CrsmCIIgmgS+g2EfiOhWjrjhWPwE6DdC3Fjs X/amTzD04EIQ1tBvhCCsoY/8BEEQRF0gB0MQBEHUBXIwBEEQRF0gB0MQBEHUBXIwBEEQRF0g B0MQBEHUBXIwBEEQRF0gB0MQBEHUBXIwBEEQRF0gB0MQBEHUBXIwBEEQRF0gB0MQBEHUBXIw BEEQRF0gB0MQBEHUBXIwBEEQRF34x9b2n1dtA0EQBNGCOIRs5qptIAiCIFoQekVGEARB1AVy MARBEERd+Ie8RR9jCKLeRKPR//3P/3B3/dcP/2ywMQRRGXfv3v118b/t5PyH+o/Pnz/bLEYQ RFk8ffbvkj8uM99DEM1DWY8i9IqMICrH5mMHvR4gbiZWDmY/3hs7ULY9gc0L9kdhc0Letk9l pbT2TGxc2st7uRbojR3UoFEAwFGsjEosMktW2aE2lteWcuy3wcXG9MTGZZmHV4d52WY8gLY5 SHi8veyfeMAb1h1j0xzkwy5t1My8y7WAddMcyhkZJOp1PI9i3sT+1ZthVrOpeeKPkVOqmp+n pYMZnJrNfT5itn66tbUz9PH3AwDYX/k49GqsHbjYmBavxfiR1KVELNDr8Sb2C5sT8URMvZfB TRev6cTaxnTsgH8U9uO9n/6VeY2YcuUpx+JyLTC9VgBkkwIbX7XFZVONF6J+l77ay7XA7Lvj heHA5oXSQXWXTTIbm1BbJf+M40dQhlrotsUmxB+8dEy0Za2Prfk56p3YOFoLqDpuVi3Pfs7x 1BcXRwrNgdWa197hcneAc8TMjdR2R3u0jQcKZ78HLHukPixa2zRj1kHCWIMZHm+vzZymFDYn ljp3shkhmxGymeiAvEPfHfNLF/tx9YmYXitwLw/DD82sac3JlQ97IqY7d7Z+3YYLQ+Eo5h1N HAN4eG+A2ztpeFGV4Y8MJX8IAIAvnLPMM093bfMtuVwL2HAtNq7Skhen5XHmXO0lzduPT3+5 vbw+3sbb2Rdd9X2x0zUelq/InGNBvFkrXK69OLs33tY+/jOWNi8Kmyn8POkEgPbb970s59Yb Nr4DnU9WM0I2PAjgtPNJNiNkt8Kn8l7AmK5c0+HOb3+LXWI1SFxsTKdubUUH0D6+fO+z6d3N xcb0c0SFbEZYDd/rUu04SAx/+5n9ZoLfRjXFLXaJtE2+mvX2zO6sjrUrHczs3HrDu2nSZTax 6iDhefpe3L01O7Fx2T6+HPwWY0fj+beflTNd2Jx4gdfiDz48yCurad9wzE3P0R+z2Lu4I26k L8yr5dqvP2jG4oX03jEAYHRB6Y7OvIFwdIBzxEyN1HdHVdZ4oJSTZbgCuYdFa9tgZGtob1R8 CF7q3In0Gc61HvbzVm9UiHNsXTwaRzHNSKTtjvEsOMdeD318vnGJg0Tq1tZveLNWwMVGbG8o yn6whstD/0PjN60/uZAOezhqPHclf93cC0OkL/rHrLdndicbHuT/MFXDCwCLkcHWDwF3jGfZ aB7/p6G3BGibXNUeTCP2rtKSFycnxXpYsDavsJk6vX/HaWF3252hfKrcZ0QAJb/BDE7d//oi tjc0PggAfU+GPg7/9HFoqg8ADhKelfb1bEb49WEFDSs4293HH78UABx92uJlOEgMq8bcwcjW d0vi8wqOz86hXLLtt+9jfmMfhqo6Or1bf0np33/XUWqXtloNoqmXX/b+dne0lcgME6s6Or34 PvxHRshuhXvA6hmM/Pz1RSL24iyoHsuUgwMcJDyBzQteWVPsnyPzavn26w6aofjFXx+zowtC NiNE+ip5g1Fud4wHqrJ6FNomVxfwdHrixVlQ7/z4CNKNP/tno4S5eaJT6Ytmt8I97z9x76h4 l277eHRoLzaxhOB42+DU/b2VxO9791/z70xtN13WJafD8Ou2e2FY/GZV1pqODMZ+8c+4/ixz zKum+zrsXKWVjavVnqOzc8ss59/+rqzjykz+re0/rzqK7HItEMOr5UkrX3qlsBsQe8MNcf0p fUH+1w//tBP6Jf+4LPLbrOra0rS/7joath9PIFLqsaYZKGxOrLSvmz2mHyQmzsdlR16Wp/hH 6SyNo21ydfmqbbDEOba+etU2EI2j9AUZi8UaY8r1p2l/3XU0bDASrlPNNcY5th4x3zsQXh8w 32tJUzkYgrhOsBhl9uRR8r+jIz9etb0E0WgqcDCXa4HRxDEe/SoHmRzFAhdP5A+tZb9BulwL jH6dUUfLyEg126rHTmaLtix2GaB3ZUStuXv37lWbQBA1poSDudiYHp7/G4B3bmt9vA04inln 3wEsjhCAFLOIdwHsvAILuXt3DIwuCBEpFoCFN8gpusp7Hj6SkzSZnUrNq2PtxnoKmxM/LWQB 4OFv2fEzy8yctuya0cfCqNgrSHH7tpRTY4M2yktsWvTHqmNIEBxIRINoPSyjyDiRgqo4QjET N4q3dPCcjeBdKDVzomB1AX9tFplNw5cbEENsFZRJEATRylg+wbBIwUjfIIsUnCq/+o5OL74f +mN50nm5Fhj9qgt+/Wljfzw8yOIX/2WVmbPL2e4+fvOlMDbpBA4SnqXOnVemmds7DG2VacZg 5OdPgUQMCK6OKYU5NujLilGPkT4A+/He1C16iCH41GCGZrNiEbTdShKfZhKQrdRHhn2xy6YK UyaIloWJXVrEInu8vcVisZUildmQ8vnzZ2sH0xpdthg/W6aPjLI8BYldEkTl1E/sUhYFuKb/ JQhQmDJBNCfsrr/i/3p+6MVLeLZ7q6yn4v/WFo+396X53pf1abQZ8LA7GMN0K+GaRL2TgyGI ymnCiZaeH3oRA7YBAC9fYuSK7aktL4tFzZ8Ox1VZUm88P/wTsRjYs+9LKVXa8Hj/FLLXwMeQ gyGIyrE/ffLz58/1NAQwuBYh+6OpdylsTqxg6PSss6Q+o67UNZv+dbkWGN0bkqdYvPnuj+VJ XI9eCP/5H89LAJDPo+hyrFGfI4vz1ahTSd9gCKJyrmTBMc8P+o8cnh96Pdu9YIPPy5fCSMby 9vYo9tNZMDI2+aozpVba9zKlSNVaSroUJScTxKzx+kB2eOlwqP+VyH2wkeiSpwf0RbMqwTGl F0cx1k1lUQZpFQPt8gcN7ikAIfsjO4+eH/7p2f5T9C4vIYz8aHV+jxeGmW6/OEXPvCNmp7h2 0BMMQVwnPNu92IYHvYhC+E+mjKcWEXGu9DuvOGFrmM1NBtDDNNvb7gx9v3d+iQ5eCgDn2Pqv CU/8aOfWm72hrYpVqhpBR6f39OICfZz79POz7OhtJhJ/b3T20zkwEBYGVFOnD8KDOMt23WZl ByOZq9KsVB5cXsLG+QXkWYmFzYkXAIBzQ0dkzWndKR6o8SQKcjAEUQO4oVP1+PIsjGQ83j/x 8iVi8KBXdC2QvEsp1gJ/3ctmouqkg4QnfiRMQSvD0YYCNwUAMBDeOZ8e/vazEGnuSV3OsfXV o5i39x0AnZTGQHjnfNrjnQUU1av9eO8vbEGKntknAwDCAhIsj1GIpGHI78qULzHlMmDREe0p rjXkYAiiBjBfIruZugY1CdkfgR9FNwObDy4ik6sGfV/xzv2CyXBofI8uhamJM7mKqxtwy6Qv qnOosib6+LIwrsk6GMkIOlHhgbCQbQJF5GK09NcXAIDnpwUAw94FOWXYuyBkM/qOsINQ2OSd 9FpC32AIombUYLUxiZJzTYTsj3gJYSTD7myrnbniHMseL7Rbp7D/DoQBCJG+Bs+DeWn+r7Xx bP8JR8xmP3Wr3pW4GpUFTOsFzeQniMqp4YJjbCZ/E8Y9VwPN5EcL9ZFxfRccI4hrRm39gaN1 Z3WYcRMWKbgJfTRD8wRDayIRRF1psZtZgrDG0aoSCwRBEMTVQh/5CYIgiLpADoYgCIKoC/+o rYgFQRAEQTD+PxRJv2vAbf5gAAAAAElFTkSuQmCC --------------030108070500050007040507--