X-Virus-Scanned: clean according to Sophos on Logan.com Return-Path: Sender: To: lml@lancaironline.net Date: Tue, 27 Dec 2011 00:51:52 -0500 Message-ID: X-Original-Return-Path: Received: from nm8-vm1.bullet.mail.ne1.yahoo.com ([98.138.91.65] verified) by logan.com (CommuniGate Pro SMTP 5.4.3) with SMTP id 5326907 for lml@lancaironline.net; Mon, 26 Dec 2011 09:14:00 -0500 Received-SPF: none receiver=logan.com; client-ip=98.138.91.65; envelope-from=casey.gary@yahoo.com Received: from [98.138.90.56] by nm8.bullet.mail.ne1.yahoo.com with NNFMP; 26 Dec 2011 14:13:25 -0000 Received: from [98.138.89.233] by tm9.bullet.mail.ne1.yahoo.com with NNFMP; 26 Dec 2011 14:13:25 -0000 Received: from [127.0.0.1] by omp1048.mail.ne1.yahoo.com with NNFMP; 26 Dec 2011 14:13:25 -0000 X-Yahoo-Newman-Property: ymail-3 X-Yahoo-Newman-Id: 91145.25789.bm@omp1048.mail.ne1.yahoo.com Received: (qmail 58052 invoked by uid 60001); 26 Dec 2011 14:13:25 -0000 DomainKey-Signature:a=rsa-sha1; q=dns; c=nofws; s=s1024; d=yahoo.com; h=X-YMail-OSG:Received:X-Mailer:References:Message-ID:Date:From:Reply-To:Subject:To:In-Reply-To:MIME-Version:Content-Type; b=VjKgkTsmG6EcbVz59h6dpmp74ZYWzg2J6sk24X9wMnjDiZwKjxfUlKKlhDmbojfuRTF3dLccRo79yVJBnWu4rBCBbp7dQvH9SGB6qM2AdmMC+zY2geIvvCU//bM1C/xC7zXaefJlblfY//mlc3hTlffx0fY313W6XXiCGwq5Qrc=; X-YMail-OSG: h256jVkVM1nUyfXM1saQNkq3ZkOnGq9Xtg20NSEXdWR64Pb YPz1JJqOFHFfOx03B05DY7AoxsNcx1EJemCUpS9IIEmsD6oOOqqxG_LR.vUy ZujVDzCVpU1hw7z5HCemZkJ2gZeDcRDJ4bBcLVB6UqsTWx5TCs1EYTOAXIir aaXuJxQsa1qAbudbSyJmuWmexQI4S7tr9zDNzh1hc7nXqxP2Uv7j6eYlr890 DgFj.0ySyYcsO52IQ5WH7rR79FS.a_5283b7DEKAyTMkuqVdXSpl_W9qUrLg ssPrSj8EFFaq3XPGFOelO1Faeqg5JgLcpEZfslL7uaVXVCIRM9vB2X4fVu4M Q8ePviVqmD4mY8KV9kATrcePnSe2irKz_k4nfvhKlyRATLUloellnSeIA4lF 1pxJU4J.j_27wK5WUdrBGI1UxFchXq5Zqwj6s_5Y- Received: from [97.122.155.97] by web125601.mail.ne1.yahoo.com via HTTP; Mon, 26 Dec 2011 06:13:24 PST X-Mailer: YahooMailWebService/0.8.115.331698 References: X-Original-Message-ID: <1324908804.18813.YahooMailNeo@web125601.mail.ne1.yahoo.com> X-Original-Date: Mon, 26 Dec 2011 06:13:24 -0800 (PST) From: Gary Casey Reply-To: Gary Casey Subject: Re: Performance specs X-Original-To: Lancair Mailing List In-Reply-To: MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="-1981468715-2111205188-1324908804=:18813" ---1981468715-2111205188-1324908804=:18813 Content-Type: multipart/alternative; boundary="-1981468715-1141573664-1324908804=:18813" ---1981468715-1141573664-1324908804=:18813 Content-Type: text/plain; charset=iso-8859-1 Content-Transfer-Encoding: quoted-printable Jim,=0AAttached is a spreadsheet that I developed for my (naturally aspirat= ed) ES.=A0 It calculates takeoff roll from the basic forces - rolling resis= tance, propeller thrust, efficiency, etc. and it computes the effect of alt= itude separately=A0on engine power and takeoff speed.=A0 It can compensate = for altitude, temperature and=A0runway slope, but not humidity.=A0 You can = change the values in the green cells to match existing conditions.=A0 The v= alues in the white cells are the fundamental factors used in the calculatio= ns.=A0 The blue cells are calculated intermdediate results.=A0 The graph sh= ows distance vs the "speed remaining" before liftoff, so when it goes to ze= ro it is liftoff time.=A0 I have checked the results for takeoff distance f= rom sea level to 10,000 ft. density altitude and it matches the actual take= off very closely.=0A=A0=0AMy takeoff procedure is to select about 15 degree= s of flap (I don't see much difference from 10 to 20 degrees) and full thro= ttle.=A0 Elevations above 5,000 include leaning to pea power.=A0 At 60 knot= s I lift the nosewheel off and wait until it flies off.=A0 If I get anxious= I can get a brief AOA warning, so I don't get too aggressive.=A0 It flies = off at probably 80 knots.=A0 Like you, I don't see much point in pulling it= off early, only to wait in ground effect for it to pick up climb speed.=A0= So the calculations are for the distance required to get to a speed that a= ctually allows a reasonable climb rate.=0A=A0=0AWith the numbers shown in t= he spreadsheet you can see that the predicted takeoff distance is about 140= 0 ft, longer than the advertising literature would have you believe.=A0 I t= hink the ditances calculated are best described as a "reasonable, conservat= ive" prediction of performance.=0A=0AFrom Jim:=0AGuys,=0AI am trying to twe= ak my Super ES performance information and would like your input on a coupl= e of things.=0A=0AI want to put together some charts/tables that let me cal= culate my plane's performance relative to density altitude.=A0The purpose o= f this information gathering exercise is to put together a chart that can u= se realistic numbers to help me calculate performance at higher elevations = and density altitudes. =A0I want to do some flying out west and feel my too= ls are lacking where performance calculations for my plane are concerned.= =0A=0AMy gray area is take-off distance. =A0I have never actually done my o= wn tests in this area other than paying attention at my home airport about = where down the runway I start flying. If any of you have actual numbers for= your ES I would like to see them if you don't mind.=0A=0AConsensus of info= rmation that I found on the internet and in Lancair publications seems to b= e about a 700 ft ground roll on a standard day at sea level for 3400 pound = gw. =A0This number appears unrealistic to me.=A0=0A=0AThe standard procedur= e that I have seen in a couple of places seems to require lifting the nose = wheel around 55 and climbing at 85. =A0Doesn't mention holding brakes till = full power. =A0Can't seem to find information that indicates when this meth= od causes the plane to break ground. (Might be the 700 feet that is mention= ed).=A0This strikes me as an aggressive method (might not be, just seems so= to me given my experience in my plane). =A0I am not a test pilot and have = no intention of flying at what might be the edge of the envelope. =A0I pref= er a bit of a conservative number, whatever it might be.=0A=0AI have tried = this method on a few occasions and I find it somewhat uncomfortable because= the plane tends to settle in a tail low attitude after becoming airborne a= nd seems quite lazy even while still in ground effect. =A0I prefer crisp pe= rformance and firm response to control inputs. The 55/85 process doesn't se= em to fit these preferences.=0A=0AMy method involves 10 degrees of flaps, d= eliberate, but not speedy, application of power, slight back pressure on st= ick beginning about 65, holding that pressure until plane flies off. =A0Usu= ally flying occurs at about 85-90 with no "sag" feeling and very positive c= ontrol response. Climb out is at 100 till 400 feet then 125-130 to altitude= . =A0=0A=0AOn an approximately standard day this results in wheels off the = runway at about 900 feet at about 3200 pounds. =A0At gross of 3400 the numb= er is about 1100. =A0Again I have done no actual measurements, just judging= by the thousand foot marks on the runway.=0A=0ASo is it possible to put to= gether a chart that can help me figure ground roll and climb rate for vario= us gross weight situations? =A0Is one already available that I just don't k= now about? =A0The Koch Chart only requires ground roll and climb rate for p= erformance calculations relative to density altitude.=0A=0AI appreciate any= input you might have on this subject. =A0I have not seen this subject on L= ML so maybe I am not the only one who could use this information.=0A=0AJust= trying to be safe.=0A=0AThanks,=0A=0AJim Scales =A0(almost 1200 hours and = very happy) ---1981468715-1141573664-1324908804=:18813 Content-Type: text/html; charset=iso-8859-1 Content-Transfer-Encoding: quoted-printable
Jim,
Attached is a spreadsheet that I developed for my (natu= rally aspirated) ES.  It calculates takeoff roll from the basic forces= - rolling resistance, propeller thrust, efficiency, etc. and it computes t= he effect of altitude separately on engine power and takeoff speed.&nb= sp; It can compensate for altitude, temperature and runway slope, but = not humidity.  You can change the values in the green cells to match e= xisting conditions.  The values in the white cells are the fundamental= factors used in the calculations.  The blue cells are calculated inte= rmdediate results.  The graph shows distance vs the "speed remaining" = before liftoff, so when it goes to zero it is liftoff time.  I have ch= ecked the results for takeoff distance from sea level to 10,000 ft. density altitude and it matches the actual takeoff very closely.
 
My takeoff procedure is to sele= ct about 15 degrees of flap (I don't see much difference from 10 to 20 degr= ees) and full throttle.  Elevations above 5,000 include leaning to pea= power.  At 60 knots I lift the nosewheel off and wait until it flies = off.  If I get anxious I can get a brief AOA warning, so I don't get t= oo aggressive.  It flies off at probably 80 knots.  Like you, I d= on't see much point in pulling it off early, only to wait in ground effect = for it to pick up climb speed.  So the calculations are for the distan= ce required to get to a speed that actually allows a reasonable climb rate.=
 
With the numbers show= n in the spreadsheet you can see that the predicted takeoff distance is abo= ut 1400 ft, longer than the advertising literature would have you believe.  I think the ditances calculated are best described as a "re= asonable, conservative" prediction of performance.

=0A= =0A =0A =0AFrom Jim:
=0A
Guys,
I am trying to tweak my Super ES performance information and would like= your input on a couple of things.

I want to put = together some charts/tables that let me calculate my plane's performance re= lative to density altitude. The purpose of this information gathering = exercise is to put together a chart that can use realistic numbers to help = me calculate performance at higher elevations and density altitudes.  = I want to do some flying out west and feel my tools are lacking where perfo= rmance calculations for my plane are concerned.

<= var id=3D"yui-ie-cursor">My gray area is take-off distance.  I h= ave never actually done my own tests in this area other than paying attenti= on at my home airport about where down the runway I start flying. If any of= you have actual numbers for your ES I would like to see them if you don't = mind.

Consensus of information that I found on the internet and = in Lancair publications seems to be about a 700 ft ground roll on a standar= d day at sea level for 3400 pound gw.  This number appears unrealistic= to me. 

The standard procedure that I have = seen in a couple of places seems to require lifting the nose wheel around 5= 5 and climbing at 85.  Doesn't mention holding brakes till full power.=  Can't seem to find information that indicates when this method cause= s the plane to break ground. (Might be the 700 feet that is mentioned).&nbs= p;This strikes me as an aggressive method (might not be, just seems so to m= e given my experience in my plane).  I am not a test pilot and have no= intention of flying at what might be the edge of the envelope.  I pre= fer a bit of a conservative number, whatever it might be.

I have tried this method on a few occasions and I find it somewhat uncomfortable because the plane tends to settle in a tail low att= itude after becoming airborne and seems quite lazy even while still in grou= nd effect.  I prefer crisp performance and firm response to control in= puts. The 55/85 process doesn't seem to fit these preferences.

My method involves 10 degrees of flaps, deliberate, but not s= peedy, application of power, slight back pressure on stick beginning about = 65, holding that pressure until plane flies off.  Usually flying occur= s at about 85-90 with no "sag" feeling and very positive control response. = Climb out is at 100 till 400 feet then 125-130 to altitude.  

On an approximately standard day t= his results in wheels off the runway at about 900 feet at about 3200 pounds= .  At gross of 3400 the number is about 1100.  Again I have done = no actual measurements, just judging by the thousand foot marks on the runway.
 
So is it possib= le to put together a chart that can help me figure ground roll and climb ra= te for various gross weight situations?  Is one already available that= I just don't know about?  The Koch Chart only requires ground roll an= d climb rate for performance calculations relative to density altitude.
 
I appreciate any input you = might have on this subject.  I have not seen this subject on LML so ma= ybe I am not the only one who could use this information.

Just trying to be safe.

Thanks,

Jim Scales  (almost 1200 hours and very happy)



=
=09=09 =09 =09=09
=09=09 =09 =09=09
=0A


---1981468715-1141573664-1324908804=:18813-- ---1981468715-2111205188-1324908804=:18813 Content-Type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet; name="Takeoff Performance2.xlsx" Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="Takeoff Performance2.xlsx" UEsDBBQABgAIAAAAIQDSNwszyAEAAGgIAAATAAgCW0NvbnRlbnRfVHlwZXNd LnhtbCCiBAIooAACAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADMVs1O4zAQviPtO0S+rhoX kFYINeUAu8ddJNgHMPa0serYlmco7dszdlsEqG1UtRJc4iT2fD/jeCajm0Xn qjkktME34rweigq8Dsb6aSP+P/4ZXIkKSXmjXPDQiCWguBn/OBs9LiNgxdEe G9ESxWspUbfQKaxDBM8zk5A6RfyYpjIqPVNTkBfD4S+pgyfwNKCMIcajO5io Z0fV7wW/Xil5sl5Ut6t1maoRKkZntSIWKufefCIZhMnEajBBP3cMXWNMoAy2 ANS5OibLjOkBiNgYCrmVM4HDw0jXrmqOLMKwtRF/svUdDHlmt6vdcfO9cf3Z 4Pi7pF7Yexb2j/c7WQPVvUr0V3WcXLlw8iWk2VMIs3q/yn62j7kve1B3yvpN Yvbwl8Uoy3B+YiHZXwE+UMfFN9Fx+UU6iA81yHI9fksKTM8GIC0d4IndrkD7 mFuVwDwQl4vpyQW8x+7RYVaHFeX65vi8r4F6eHXocvXE4/k+1oANbh89p4hQ 6jwcL2Ftmct/AezjVk7ftlylTvzd6Q3uPn5uW/cpRLYeEhwuYNOGcvQgMhAk svDWiLbV2zdGbquHE35qtpD7tgGzhVuW/4TxKwAAAP//AwBQSwMEFAAGAAgA AAAhALVVMCP1AAAATAIAAAsACAJfcmVscy8ucmVscyCiBAIooAACAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAACMks9OwzAMxu9IvEPk++puSAihpbtMSLshVB7AJO4ftY2j JED39oQDgkpj29H2588/W97u5mlUHxxiL07DuihBsTNie9dqeK2fVg+gYiJn aRTHGo4cYVfd3mxfeKSUm2LX+6iyi4saupT8I2I0HU8UC/HscqWRMFHKYWjR kxmoZdyU5T2Gvx5QLTzVwWoIB3sHqj76PPmytzRNb3gv5n1il06MQJ4TO8t2 5UNmC6nP26iaQstJgxXznNMRyfsiYwOeJtpcT/T/tjhxIkuJ0Ejg8zzfinNA 6+uBLp9oqfi9zjzip4ThTWT4YcHFD1RfAAAA//8DAFBLAwQUAAYACAAAACEA 9PUHOxsBAABZBAAAGgAIAXhsL19yZWxzL3dvcmtib29rLnhtbC5yZWxzIKIE ASigAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAvJTPSsQwEMbv gu8Q5m7TdnUV2XQPirBXXR8gpNOmbJuUTPzTtzcUSS0s9VL2EpgZ8n2/TDLZ 7b+7ln2io8YaAVmSAkOjbNmYWsD78eXmARh5aUrZWoMCBiTYF9dXu1dspQ+b SDc9saBiSID2vn/knJTGTlJiezShUlnXSR9CV/NeqpOskedpuuXurwYUM012 KAW4Q7kBdhz64Py/tq2qRuGzVR8dGn/Ggn9ZdyKN6IOodDV6ATFFfKxskkAM /DzM/ZowSrbqScvGTDAxtQSRrwkRjz9BxNRvR/IlmOzCMNkSzHZNGNLSYfnm XRgFmrozSy/B3K0K44c2TF58tTTGS/a3a9r7MM84uY8hH9d4H3z2IRQ/AAAA //8DAFBLAwQUAAYACAAAACEA9K1Y6WwBAAB+AgAADwAAAHhsL3dvcmtib29r LnhtbIxSQW7CMBC8V+ofLN9LQhJQQSRIVVuVS1WpFM5uvCEWjh3ZTgO/79oR EKmXnrzrnR3PTLJanxpJfsBYoVVOp5OYElCl5kIdcvq1fX14pMQ6pjiTWkFO z2Dpuri/W/XaHL+1PhIkUDantXPtMopsWUPD7ES3oHBSadMwh605RLY1wLit AVwjoySO51HDhKIDw9L8h0NXlSjhWZddA8oNJAYkcyjf1qK1tFhVQsJucERY 276zBnWfJCWSWffChQOe0xm2uofbRUaJ6dqnTkicLtI4oVFxNflhCIeKddJt 0d6FHfNKsiSZe6SPYiegt7cl35LTXiiuew/FaM+XboFNHyZ7wV2d0yQLgOHu DcShdriTZlns2aMRfQgQnwknUcHdlh0BoyEtmJC4KgE/m096g26maG0psDAb PvV049VPj0pGaKyv6BDCH3Q6QmN9RadBaoCjvpLJEnPzRxCRzeZJeD26/DrF LwAAAP//AwBQSwMEFAAGAAgAAAAhAPtipW2UBgAApxsAABMAAAB4bC90aGVt ZS90aGVtZTEueG1s7FlPb9s2FL8P2HcgdG9tJ7YbB3WK2LGbrU0bxG6HHmmZ llhTokDSSX0b2uOAAcO6YZcBu+0wbCvQArt0nyZbh60D+hX2SEqyGMtL0gYb 1tWHRCJ/fP/f4yN19dqDiKFDIiTlcdurXa56iMQ+H9M4aHt3hv1LGx6SCsdj zHhM2t6cSO/a1vvvXcWbKiQRQbA+lpu47YVKJZuVivRhGMvLPCExzE24iLCC VxFUxgIfAd2IVdaq1WYlwjT2UIwjIHt7MqE+QUNN0tvKiPcYvMZK6gGfiYEm TZwVBjue1jRCzmWXCXSIWdsDPmN+NCQPlIcYlgom2l7V/LzK1tUK3kwXMbVi bWFd3/zSdemC8XTN8BTBKGda69dbV3Zy+gbA1DKu1+t1e7WcngFg3wdNrSxF mvX+Rq2T0SyA7OMy7W61Ua27+AL99SWZW51Op9FKZbFEDcg+1pfwG9VmfXvN wRuQxTeW8PXOdrfbdPAGZPHNJXz/SqtZd/EGFDIaT5fQ2qH9fko9h0w42y2F bwB8o5rCFyiIhjy6NIsJj9WqWIvwfS76ANBAhhWNkZonZIJ9iOIujkaCYs0A bxJcmLFDvlwa0ryQ9AVNVNv7MMGQEQt6r55//+r5U/Tq+ZPjh8+OH/50/OjR 8cMfLS1n4S6Og+LCl99+9ufXH6M/nn7z8vEX5XhZxP/6wye//Px5ORAyaCHR iy+f/PbsyYuvPv39u8cl8G2BR0X4kEZEolvkCB3wCHQzhnElJyNxvhXDEFNn BQ6Bdgnpngod4K05ZmW4DnGNd1dA8SgDXp/dd2QdhGKmaAnnG2HkAPc4Zx0u Sg1wQ/MqWHg4i4Ny5mJWxB1gfFjGu4tjx7W9WQJVMwtKx/bdkDhi7jMcKxyQ mCik5/iUkBLt7lHq2HWP+oJLPlHoHkUdTEtNMqQjJ5AWi3ZpBH6Zl+kMrnZs s3cXdTgr03qHHLpISAjMSoQfEuaY8TqeKRyVkRziiBUNfhOrsEzIwVz4RVxP KvB0QBhHvTGRsmzNbQH6Fpx+A0O9KnX7HptHLlIoOi2jeRNzXkTu8Gk3xFFS hh3QOCxiP5BTCFGM9rkqg+9xN0P0O/gBxyvdfZcSx92nF4I7NHBEWgSInpmJ El9eJ9yJ38GcTTAxVQZKulOpIxr/XdlmFOq25fCubLe9bdjEypJn90SxXoX7 D5boHTyL9wlkxfIW9a5Cv6vQ3ltfoVfl8sXX5UUphiqtGxLba5vOO1rZeE8o YwM1Z+SmNL23hA1o3IdBvc4cOkl+EEtCeNSZDAwcXCCwWYMEVx9RFQ5CnEDf XvM0kUCmpAOJEi7hvGiGS2lrPPT+yp42G/ocYiuHxGqPj+3wuh7Ojhs5GSNV YM60GaN1TeCszNavpERBt9dhVtNCnZlbzYhmiqLDLVdZm9icy8HkuWowmFsT OhsE/RBYuQnHfs0azjuYkbG2u/VR5hbjhYt0kQzxmKQ+0nov+6hmnJTFypIi Wg8bDPrseIrVCtxamuwbcDuLk4rs6ivYZd57Ey9lEbzwElA7mY4sLiYni9FR 22s11hoe8nHS9iZwVIbHKAGvS91MYhbAfZOvhA37U5PZZPnCm61MMTcJanD7 Ye2+pLBTBxIh1Q6WoQ0NM5WGAIs1Jyv/WgPMelEKlFSjs0mxvgHB8K9JAXZ0 XUsmE+KrorMLI9p29jUtpXymiBiE4yM0YjNxgMH9OlRBnzGVcONhKoJ+ges5 bW0z5RbnNOmKl2IGZ8cxS0KclludolkmW7gpSLkM5q0gHuhWKrtR7vyqmJS/ IFWKYfw/U0XvJ3AFsT7WHvDhdlhgpDOl7XGhQg5VKAmp3xfQOJjaAdECV7ww DUEFd9TmvyCH+r/NOUvDpDWcJNUBDZCgsB+pUBCyD2XJRN8pxGrp3mVJspSQ iaiCuDKxYo/IIWFDXQObem/3UAihbqpJWgYM7mT8ue9pBo0C3eQU882pZPne a3Pgn+58bDKDUm4dNg1NZv9cxLw9WOyqdr1Znu29RUX0xKLNqmdZAcwKW0Er TfvXFOGcW62tWEsarzUy4cCLyxrDYN4QJXCRhPQf2P+o8Jn94KE31CE/gNqK 4PuFJgZhA1F9yTYeSBdIOziCxskO2mDSpKxp09ZJWy3brC+40835njC2luws /j6nsfPmzGXn5OJFGju1sGNrO7bS1ODZkykKQ5PsIGMcY76UFT9m8dF9cPQO fDaYMSVNMMGnKoGhhx6YPIDktxzN0q2/AAAA//8DAFBLAwQUAAYACAAAACEA fsGK5WABAAB0AgAAGAAAAHhsL3dvcmtzaGVldHMvc2hlZXQzLnhtbIySwWrD MAyG74O9g/G9cdqt2xqSlEEp62Ewxra74yiJaWwF213bt5+SkDLopTcJSZ9/ /XK6PpmW/YLzGm3G51HMGViFpbZ1xr+/trMXznyQtpQtWsj4GTxf5/d36RHd 3jcAgRHB+ow3IXSJEF41YKSPsANLlQqdkYFSVwvfOZDlMGRasYjjJ2Gktnwk JO4WBlaVVrBBdTBgwwhx0MpA+n2jOz/RjLoFZ6TbH7qZQtMRotCtDucByplR ya626GTR0t6n+aNUE3tIrvBGK4ceqxARToxCr3deiZUgUp6WmjbobWcOqoy/ zrnI08GcHw1H/y9mvdcF4r4v7MqMx32ruOrdDl5/OFZCJQ9t+MTjG+i6CXTY JWnvV0jK8wa8Iu8IEy2Wl0c3MkiidrKGd+lqbT1roRq6njlzIyaOKA7Y9bPP hCwwBDRT1tB1ga4YRw+cVYhhSnq1l/+S/wEAAP//AwBQSwMEFAAGAAgAAAAh AH7BiuVgAQAAdAIAABgAAAB4bC93b3Jrc2hlZXRzL3NoZWV0Mi54bWyMksFq wzAMhu+DvYPxvXHardsakpRBKethMMa2u+MoiWlsBdtd27efkpAy6KU3CUmf f/1yuj6Zlv2C8xptxudRzBlYhaW2dca/v7azF858kLaULVrI+Bk8X+f3d+kR 3d43AIERwfqMNyF0iRBeNWCkj7ADS5UKnZGBUlcL3zmQ5TBkWrGI4ydhpLZ8 JCTuFgZWlVawQXUwYMMIcdDKQPp9ozs/0Yy6BWek2x+6mULTEaLQrQ7nAcqZ Ucmutuhk0dLep/mjVBN7SK7wRiuHHqsQEU6MQq93XomVIFKelpo26G1nDqqM v865yNPBnB8NR/8vZr3XBeK+L+zKjMd9q7jq3Q5efzhWQiUPbfjE4xvougl0 2CVp71dIyvMGvCLvCBMtlpdHNzJIonayhnfpam09a6Eaup45cyMmjigO2PWz z4QsMAQ0U9bQdYGuGEcPnFWIYUp6tZf/kv8BAAD//wMAUEsDBBQABgAIAAAA IQBg6ORQ/gAAAOsCAAAjAAAAeGwvd29ya3NoZWV0cy9fcmVscy9zaGVldDEu eG1sLnJlbHOskk1OwzAQhfdI3MGaPXZcEEKoTjcVUrdQDmCcSWI1/pFtCr09 gyioqVKxyXLm2e99M/Zy9ekGtseUbfAKJK+AoTehsb5T8Lp9unkAlov2jR6C RwUHzLCqr6+WzzjoQpdyb2Nm5OKzgr6U+ChENj06nXmI6ElpQ3K6UJk6EbXZ 6Q7FoqruRTr1gHrkyTaNgrRpboFtD5GS//cObWsNroN5d+jLRITYu2Gd9AcN R646dVgUcC6an14+0SWnsyCmmRZzMh3Dp4GOouS0xks0ck6amKwvmF6wFNpS HlGdaeKslvzN+kuQd3NCmuC+X3hM99v825UYfdH6CwAA//8DAFBLAwQUAAYA CAAAACEADkT037wAAAAlAQAAIwAAAHhsL2RyYXdpbmdzL19yZWxzL2RyYXdp bmcxLnhtbC5yZWxzhI/NCsIwEITvgu8Q9m7SehCRpr2I0KvUB1jS7Q+2SchG sW9voBcFwdOwO+w3O0X1mifxpMCjsxpymYEga1w72l7DrbnsjiA4om1xcpY0 LMRQldtNcaUJYzriYfQsEsWyhiFGf1KKzUAzsnSebHI6F2aMaQy98mju2JPa Z9lBhU8GlF9MUbcaQt3mIJrFp+T/bNd1o6GzM4+ZbPwRocyAISYghp6iBinX Da+Sy/QsqLJQX+XKNwAAAP//AwBQSwMEFAAGAAgAAAAhAAkPcDUWJwAAYKAA ABgAAAB4bC93b3Jrc2hlZXRzL3NoZWV0MS54bWyUnWtv3Eiypr8vsP/BEISB rW5TvF80bR9M3cuFBQ7OZffbAGq5bAtjWz6S2j3z7/cJMpOqDJJRVd3ttsQq vsyMeDMzbpn87d/++e3rq5/7x6f7h+/vLpIovni1/3738PH+++d3F//9X6u3 9cWrp+fb7x9vvz5837+7+Nf+6eLf3v/v//Xbnw+P/3j6st8/vwLh+9O7iy/P zz9urq+f7r7sv90+RQ8/9t/55NPD47fbZ359/Hz99ONxf/uxvenb1+s0jsvr b7f33y86hJvHUzAePn26v9svHu7++Lb//tyBPO6/3j7T/qcv9z+ePNo/P56E 9/Hx9k/66ttz0MRF90mPl+SD9n27v3t8eHr49BzdPXy77po27GVz3QT9/HY3 ABoR1rfbx3/88eMtwD/o3O/3X++f/9V29+LVt7ub7efvD4+3v39FI/9M8tu7 g1beDuFPbydI73/7eI9shRCvHvef3l38LbnZFfXF9fvfWtX93/v9n08HP796 vv39P/df93fP+48w6OKVMOP3h4d/yBe3XIqBfGq/IJC3d8/3P/fz/dev7y5W Qq7/aR/Cjzzgun/C4c/+aauWS//++Orj/tPtH1+f/+Phz83+/vOXZx5bIAER xM3Hfy32T3dwgwdHaSGodw9fgeD/r77dC8mR4O0/u6bef3z+wk9VVBdFXtYV MHd/PD0/fPt/7hN3f3dn6u7k7z/d51lUJXGTHbkxczfy98uNaV0kRUkTrUeW 7k7+dnc2UVHFWSL3/b5/el7dS/dNjIRB3fWYH/zz49O6nPTSEs12na4iq+nX nbhbTS5un2/f//b48OcrBiMATz9uZapIbgRW9JZmoqMx1WUFtLmT+/4mN3IT f3HHE5d/vo9/u/4JRe74A3r/CBQTPGKcEh6Xb/eASQ/YPnMmSO8uMvWw9rP5 4X1peN/i8L6iCT9cdR8e3p7U4VfW3VfKsedughuL8MZtd2PV3phGef9pIB/4 d4Z8+HYvn7TsETsBCZQXUMZcHn48P7w3ycIPF4f31urOZXCnluDhh6m6c30I qz7bBDcqZW+DD5VGP3SoDYL99H6dXdXX1VVdX5c84JPBxPwsSfPtF0krzc4E ypD04b0vam+VtAhuTZRMlod3poqIq+DDKlTgOu/4GcUvkgx4xpA+nWdzvt33 XtFsIUjvLjpax5ESzfLwzlRz5fDDTPV9LbPLz/d11IT/ZMu3iqzbrgVJMPiU nD9036lbjiyy69cfqr/T2DdXr2fZ9Sx/I7+8XQPcMqZqoqZomjRL6qxokjKf ECJT/ulC/Bvf7oWoujATpHcXrnnl1Ta96lqYZW98m/IiisuyafIybaq8KpTG 54fwiRoiiwA/v6L3SUSn2t5mSRxledKkdRPHdREX6uZtd3Mg30zp+UP3nW4M zrKrNRjW4KvOkhzffpHciy66ae7wQyWTrTyGdemQGbrh7itiAn16//p1Kqp/ O0uvkziO31zLr+giL+NfiubNdfvDIn3jlYI1HvPFtKyyqimrJnmhXTDaGtVd GsXo7eyYzmZqF19ZbzMsAHtRFLB3F4djJ1H9no18RQ2v+chX9MgefkUN4OXw G+mLBFr1rIZfUfPYeviNROl4M/xKqkbQtvvK4ZyYKR5/GPmKQtmNfOWlQ4FK xWQ7Y/Dz9XAt6sjbomBkdfNSEl9V1/VVGV/XCKkdP0XUlEUT9/8mzfKt6tfc gSQC0g6UL7eP+48XnW/ApzfzArk83beG/utVEr/d8ueD/LksIfXsMrvO0ij1 rK6ipCrSrKjSkkmhqpXWFwfPw86TeeRnZ+m1fVoe9mnQHD69Wfrm0OLt6vXr XRK/+cvn57/Gvy4uy6uiiK8Wl8V1e/nwim9eXWR5zpQV53lVZVndqAbQwXaE tEIdNIBPb1a5GKzIg6/QgNllKY+nab/KH371j6qOTLprHjWi1o3ZAj692XgR YL9+uGTCkaW/VbisPTKj5HGTlnVa5Gq4oLq2d+Pa5tObrcfGBkC1V+tLKNxi D0aEiQVBbj54LFZjJIWmOkWtL4urD5fVFRf+nv76NvjVC69hcmziNI9ZP6sk SfN0+VbNvtxuqIpP8WsddTG4Id4vHy79In1IvHBkinIP3Rh7OsVrERUqEs3E mWGa9SMzGYzMnEUzzrImb8qEmT9Ws+fcAQz01I1DnN6f72WgxXlW51lTpXlT ZQpjcYjxnpH8CyLwPInSYJDW6t7lYQcOR4E8PxGnmT4nVRZHVVEncRoneZYo 9awsjLTDOD5EDgXJgPnl9WtRJH1jefVcySJce+RYl1leIo4Di6udVDZWSzLX kiIqk6aoM6ByvG9tbm4PpaklkncYwxHStX5Ui23oQmbAvCrrrElS+S+NiwOb u238zmp86Ro/rc6Q3OJFnkFu4e/P92rFmIlF5Ml9KIk20MOnNzM/Q2LXL5J0 QP4aUddJUdUYyEkRZ7rLc/eEUbnFvssEV7KkydI6resStHAh4bltKwcYbSv5 9GZRyPQBnzGcGW/CKTc6kjzK86KEB2VZFllVqoV+OSWBg9HBslth/TX8RVfL MlcjbGVhnDw6LE2s6ePaawLbek0fZfRIT9OD0UNvWSfiKpWBXNDtUJAbq6F+ 8CTiA1TICru3KhmKIcZ2ShkisMnBM6FAuccNniSqq6ap4zKrsyzNsxdryw2d CfkIhBs6hq7DoSNxgjOGThdaUsSZJV20YWBcSIOqjthJGtUEKpmAsioTO0ot 4XOHMSC2YLwMjoz7szIlkljUcar0sbAw2kgtoz6JyjhpmixnkcrTrFIYS6sv bonImoIVIq+wSYq8wBVWU8nKwjh5EBgybfzETFA1afCA8yRmQGeqLxurHY7j ZRUxRrIKm6TEtopLtdxtLZlOcrxr+6guHcfzKI1zTLqkSFBlUeho285quyO5 ocuQ5GIunUHyLk6kRt0sERRn/ByuD4ckx3jJmRyJRsRZQexAYcwdxqhgXkge x5g/BUGWrCTQ3oSTzsLC8CSvowqCp1iYRYolUytDbmn1xZGcgEocxdA7k5WC 8aLItbIwTia5IVNH8qJiqMVIgiBPUuSxDuNsrHZ4kjP5JPhtZc3CmmEJKb1s LZlOkrxr+6guHcmrCEO2otVlTBwJpSoZ7qy2e5JP6zIkuUTzziB5F0pUo30m GakjJGfUEdiJ0wSJskAh1JCgc4cxKpie5HFR12maJxg5iCVRZsTCwnAkz4oI QyujGZUYx3WsBsrS6osneVYnEdmsrK7jvBZvI+zLysI4meSGTB3JG4aauLVY +jELfxEromysdjiSF3XEmohi8FrSuB6sbFtLppMk79o+qktvrYgEmyTJc0ko xigzlOHOarsjuaHLkOQSUj2D5F1GSpFrlnSBWctcSYsIUzelOwX2RsVkGHZq 7jBGBfNC8rjOc4zHKhU/Tg+UhYXhSJ4zc+H4CS0YaXgFiqBLqy/eo23qJsKB xBurc6YjHadeWRgnk9yQqSM5jmCUCT8bBj5MLdTks7Ha4UlOhKEkqpzipIOS 5Qpja8l0kuRd20d16UleYmoVVRuBapiwdHxtZ7XdkdzQZUhyCb+fQfIuzaQI Oku6IL5J8iaqKiYLZnFcdQJsauTOHcaoYBzJy0js6LogLJcm2KDanl5YGJ7k Et5LC9qCQc1Ursbr0uqK5zj3RmkiPnOTsL4POW6I42SOGxie41UREQAoyrxO CfDFmicbqy+e40TxahYjbK6CybxU3sXWkugkxbumj2rSUTwl/54xPwgjSHgl iVpPd1bTPcUnNRkyXCpozmC45ABJe4ZT8CwRFNsgz7JI6ADDSeXhK+npYu4w RuXSM1wslQxV4mbBsLAVCwvB8bsoqVpJ4zKtauKTOVZLiLG0euIJTgQtSoqG aCCRoSrT/tLKwjiZ4IZEHcFTJvGkxHgjvpdlGBxqsG6sdjiC5yWOBbHdJpNV CbtBYWwtmU4yvGv7qCY9w2l6UtNmmcgLlhD13J3VdsdwQ5chxSVrdgbFJUv8 870acrOky71Zk3hWYzpmGBlpQmaEkasIOncYo4J5oXhMFp2wNUYGU1ejppyF heFIXlJTluH8sjwzUkrMck1yoy+e5NgoUQzJsYET/E/tp60seZxMcqMdnuQY TDn2X4lYyQAweMO+bKx2eJInEbIoGS/EDzG9MmW5bS2ZTpK8a/uoLh3JMyyV pkiQYFupQQI+bPvOarsjuaHLgOSphJpPJzlfbzMsKu0+a2HsiRzbCVsadsVk hypm0rBTcwcxKpie5OSTEjQhgqkII4YQCwvCcZyISJFLSoOwSs5Q0ZPf0uqJ 5zj2b0R4JwYmlsIVtRisLIxTOW5hOI5nzGRFU0oFKUIlWxeKY2NBOIpnFKBW pCuwUUoyHpn2/LYOY1QrUxS37nEUz/OoTpvW5GSuwNxSbNhZbXcUN1QZUvy8 xGkqfZUkYijNGdeP2SqyKpKpYwqucKMJGCmCzh3GqDR7jksEAYpmRMqotx0E Dy0MT3IKZUshhWRNyNzpSXhp9cWTPIlJv2AFYzI1ZcygC+WxsjBOJrkhU0dy ehEhyzQpcaGJUOgA3MZqh2d5FtX4fSxrcUl4pRoUH1gynWT58RRqwYJK/qdB iZR/kO1QQcud1XbP8mldhiyXjNIZE7kYJLBcLYuz1EhMuTwQmRN8POyDppQc IiWFITPmDsNmucw1LAQyCaNYvTwvLAzH8hqtUjeIS8A0jFU+CKxYffEsZzHC 6aTgpozJw6R6VVpZGCez3JCpYzm+GqsjlltFqIn9AIUyvTZWOxzLpagPD6VM UpykRKpsQr1sLZlOsrxr+6gu3VyOqZGTSMY8ymK8GoQYPndntd2x3NBlyPLz kp1pl+zUntaM68fmcsZuA8vzsigwqol2hZ2aO4hRwfRTOb4RRpw44sS300wN lIWF4UhOWDnPxFmT1RmzXq0oS6snjuM8mzIUiRxmLEkwYzCTG9I4meMGhud4 U7Pnglm4ori0ZO1Xs+HG6ovnOCuseOFY5RAOL0VxbWuJdJLjXdtHVek4XokI 0wpjj0pi4vtKhDur6Y7i05oMGX5epjPtMp0HFbptgcGM60cZTlquIY8uhnBR ELUbUNxIj/UUp7qBEVLklHKWCeIJh8nCtWNUtp7ixFYwdCgxSonSyw6fEGNp 9cVxvCYJRF4RmwcMZiI1fa4siJMpbojUUZzIJXMwKTGpWcGu1SUSG6sdnuIp 0ZmKzG+Tk0UuUU4ojq0l0kmKG6p0FK8x9yiLyIgJYWQRTVaz1c5qu+f4tCpD kp+X6WSnVmusKD9rJju4joQPS0ltUeBBvS+5ePxPRdC5wxglaE9yHD5oWWLV k4pP9eK8sDAcyXFZI1YB/iVyRa5SS3dp9cWTPKXSgxpmlhNy4VSYKXmsLIyT WW7I1LGcWUMCIxKGI+0gZA8ZurHa4Vie1CSS2O5ByXNKaBaTJcTYWjKdZPnx VGdD5Tnir6oSG5ayiFLNFDur7Y7lhi5Dlp+X6ky7VKeOus24fpTlBQ4f3k3T JYGwrUNpzh2GzXJcIyzymOyipJ61w7ewMHqWE3UjDS9TsahXO9FLqy+O5VWN f0GiLpOIPWMlVsxYWRgns9yQqWN5LeYKiWOmQ7KvNQnLUKYbqx2e5XmEj4RE mVILTDDdl60l00mWn5DrpMSTug7ibEx+hdR5hG3fWW3vWT6py5Dlkpc6w/Hs cp26EHOWGpk553iW7JqLsTcgOtZCTtFI2Ku5w7BYzvAnHsywp9SO4DBJ+RBj YWF4lidFJDN5hZNVUVmqd5Isrb54lhP0pyqAFEZSssxXwxiiIQ/P8iMYa6sd juUJtjimrXjzFZE4Ss1CeWwsDM9ybC8KiRmx7BajyksX6m4tmU6y/Hi6M0lJ s2LuSTpN6n90mGtntd2zfFqXIcvPy3emXb5T77Kecf3YXF6RxCXRSZybQCIa iZX9N3cYNsuhVkOQPCERJMaLGv8LC8OzXKrESPBRKSbRyEq79UurL57lWD3E 7nLupqqoqLW7trIwPMuPYKwtDM9yKVxhFq6oM5NKW10LtLEwHMsrzGMse8Ls mPaUJ8hetsMNYluHMaqXSZYfT3km7GEjPkU9AXYfxeQ6zL+z2u5ZPq3LkOWS nDpjLu9SnrrMYJYa+Tk3l1NkISEAJmFcJVZ6HaKZO4xRaTq7PGcTNTtjCI4k sRRsaGtjYWH0LMdlYRomKkFROWNGrfJLqy+O5ZgGEQlPwpgMtZwxFxJjZUE4 kh+BWFsQnuOYXBHpMUKyWNOY5sqN3lgYjuOUZrHphU0roFAaOqhV2zqMUa1M cvx4xpO4PnsLJLWHLgoyUmpV3llt7zk+qcmA47IT+QyO83XxPfWZD7MWxs54 VmwnwniUshUJWpGWD4kxdxij0uw5zo6kHFIR5aa2h3ksxFhYGJ7jGdtRGGc4 rgBQ+RZCLK2ueIrnFEKzDwwbliikROBCjJWF4Tl+BGNtYXiSZ3VKVgqHkdp6 thzosbaxMLy5EokNmcUEEKXAn2qpsC9bhzGqlimSW/e4AAsx8kh2lUnKBLsz 10VyO6vtnuSTqgw5fl7KM5OuysaaUBAzrh+zVoi7UXeYERshnUvBhbbB5g5j VJg9xwn6sZ0IjxGLWlzPsB0LC6PneClmk5j1LASwVM/jVl88yaVkGHs8Ldix WRCjVlbTysLwJD+CsbYwPMkJNUUlISvpCpVvOjaysTAcyd8m5A1wk8gik3zk Rz1itw5kVDGTLD+e84QJEV5Ryf4wHF+ptAiVubMa37N8Upkhzc/LeWZdzlMb sjOuH6U52aC8ImQESUtCiZWixtxhjErT0RwIVlbyMOgDcyPVQ2VhYXiac0IA URWqxGR7KnnLULhLqyue5bFMQ7KTj5IPDEvtG6wsDM/yIxhrC8OznMgEARZ2 rmG6kZJXEt1YEJ7kIlKq4SWbhNWCfa5mjq0DGVXLJMmPpzyZH9hBI8Fgggjx cNPJzmq8J/mkKkOOS3LqdJM86zKe+hyRGdePcrxkYWTqo6KIYgkxy0NyzR3G qDB7jks6HnqSy5biE13KuLAweo5L1IwKcCKJrArU/obtWFp9cSQn2IZZT9UI VR90aBgqtzAcyY9hrC0MT/KqYbM1zjgRFvg+GGwbC8OzHL2UlIWWFJzJjm22 0oUC2TqQUcVMsvx40pNJIkKLbPYgd4I29VFsO6vxPcsnlRnSXBJUZ9C8S3vq gppZZuTonOdJp6gAZDKXyAZ1H3rOmDuMUWn2NCf6iD7ZEiiRbn4INbKwMHqa 19RNEGEWP0sMe4WxtPriaY4bHecE71joY7xpfb7EysLwND+CsbYwPM2x+/AP kCUF5ZhwupxvY2F4msvmNzZaymZLrHzK55TlsHUgo4qZpPnxxCfZtHbbBLsH cSzIZqnhtbMa39N8Upkhzc9LfLZnUWKYq0TfjOvHZnPKDUomQDEfmUNhulpf 5w5jVJo9zYknUEwk1emYCshH09xIuHmaFzifNUFATBYCmmQlQoyl1RdPc7K4 sgmExBvJdc6HUcv8ysLwND+CsbYwHM0lvMM2PIJFbZ3VYC/KxsLwNJd4u9hu bbyI7aI6i7t1IKOKmaS5oQjnfqaSEyLZIEkHooiDIsid1XhP82llhjQ/L/OZ dZlPvb7MuH6U5oQDZIc2Wx+wI2vmwpBec4cxKs2e5mSVQKBWiyMhUK6aeBYW Rk/zIqKyqq1oxMIvFcTS6opnOYWVclQJUQ22ilJTo0bbysLwLD+CsbYwPMsp duMQBFYltjnBT5083FgYPcvRC74Slj37AvFl9RS2dSCjeplk+fHMJ9kgam7l ACvZ2ZTp4pmd1fae5FOqDDl+Xt4z6/Ke2g2fcf0oxwnLUlNOITcRK5L02lWa O4xRWTqOswk5l03p7Cwnp078SS1yCwuj5zi8ICdFhi/lJDfMp3CsLa2+eJKz PYhQKKl9zlKQqOiA5IY8PMmPYKytdniS41wIUZgzZMcpYgn7srEwepKjGKw3 ph5ODJE9q6ozW0uokyQ/nvgkkhvBcMnuEUwkia1mm53V+J7lk8oMaX5e4jPr Ep+6zGrG9aM0lz2FGBlMopzRSChR0WvuMGyay3krWBrkhUW3uiZ8YWF4mpcx iSVq4EpikTjCepvR0upLT3PmcqkwghWYxYN2rCyMnuY2xtrC8DTHXWTyYPNB Qu6SgadkurEwepqjGFZYIgON1OqTIArHytaBjCpmkubHM59YnWz9oHQZv5eC SArnwufurMZ7mk8rM6T5eZnPrMt8akN0xvWjNCc+SlmnGGAUkMjG5LBXc4cx Ks1+NpeYEweeSOWtigEurPt7ilPPzJEfnINALJK0p2rD0uqHpzg5ZfJSmCrs +aesvFaT38rC8BQ/grG2MDzFOc+VChYYjtmV43uqdmwsjJ7iErSWdZF1SXam DH1PI4k5SXHjHm+U50mUcogZyyrHGrFvViliZzW+p/ikMgOK5+clPvm6JIX0 AeazFsZOfDYUW1CfT3Jeto+xFU1NGHOHYVOcmYbFgApRYiMssGqBXlgYPc1L DBYMFdKWGIaDXMTS6ouneYJ02bYqvgGLCvNoOFxXFoan+RGMtYXhaU4fMKlx Hdn5zlYyzdCNhdHTXHb+swpINTTWJLs+w85sHcioYqZobt3T05wjsNgdQJ6v 3amqG7+zGt/TfFKZIc3Py31yDmVLc2VCzdrzKW2aM+9FbJ5giSqoYSaMFApz 7iBGhdlP5BLowhpnk7kc0jYwyy2MnuXEnhrWEZYDOM6ZOmE7llZXPMtJ6ICR EO3B3uElAaovKwvDs/wIRnfk54RIHcuZAqmLZFkUswszVxeCbKx2eJZTFojZ g/vJ7isoxwwQCmRrCXWS5cdTnzQXl4K8sWzhYyHSNf47q/E9yyeVGbL8vNRn 3qU+dfBtxvVRe6U7MTdPOTFXIksc4MmR1u8X+fDIXCYRSo3Z7iwpcwaDLsKa u0fYo4AsDZZIzkLIMOCUllBhPLdt5iiGHwVsB+82+BLsZDTp8rzlVFfbznWn cVKrw7n0bNuh4JtmEKUL27GawujeJIW4Vr24aOvBGex5+isNODyD/diz1uaz +JQjdL1qUC6DS87Q5f8I6+AMXQYRcXU52q3iyFPq+9U8t5l6jIilH1BynC3l m7BajtIdBNm2DmRUP5MDytCpXzZKokics17KEYO4dfoo5Z3VeD+gpnkRDqjz 8qy5O0ZXMWTG9dEB5YZQdz65VLRWchwcUz5GxcDRdSCj4nQLBwFx9jJBVSZ8 TsUcYCwsjH7IUFnanvvA6kWiQE+2S7MzfshIDh63vSY0TwGk7svKxHCrD2kj E2RtgrjlhzAI54cxhchue4n8aVfXAumZzi4twq+cFEXSk2J47VxtHcioaiaZ fjzVikkmexuoRcPEbGupwplnZzW+Z/qkOkOmn5dqzbtUqz7Cesb1E5jOIcGc wEMEosSpYhSH3Zo7kFFx9kynloBCdErEMFs5e2uwOBgpvp7pBPsYcIwVFiqp 8ArbsTQ745hO4pgSSNlEKEUz/BNirEwMz/QjIGsTxDOdzVGMF9ZK2SBK1axq ycYC6ZmOZogGk4Amys+W7EypZutARlUzyXRDFX5OryjbrgvZ4CoOXqYzJTur 8T3TJ9UZMl0WyNOLClhPW1dAkaMzgSbsVswiN6cTkhV/l5OFCF/ipIXsmLeL tbyiQr3NRhYGj4GPVEk1pez2J+Km2rGwIHqiU9xF7ojZC6+EYvSwFUsHIdZg 8E6dQyOIsxhwmdu6QWo+hqFLE6PnuQ3S2S5TMvU8Z1XjqHcWFzx3OThALbYb qyU9z9FLu7GJ0gQp0tdFrltLqpM8PyHdyjZGjCVSxvwn5x2EmthZbe9pPqXM kOXnJVvzLtmqJ40Z10fnc+cKlDcz/1oKznXHFSgHb8+gl7xtIcfipPJArHg1 U8/dI+wxQDhSAChbJXCEExXKjee2zRzF6AeBHDQhZ6exO4Q4h56pl1NdPRwF VPiJH0AKUza0UkMWtmM1heFcgfJm1YuLBfTQFShxBcrAFTjyrLX5LD69WffP YgpjbLWuQIErwHuwXl5Gg0DltYNM+wwnCc6FXdpMPUbE0g8nVCwHiRQ5Oxfl DGDlT2wdyKh+JoeToVO/bNQlOiXWgjFAxo45Lmz8zmp8P54meREOqPMyu3mX 2dV7rmdcHx1QLcucPBknbLmRJB5lfZItV+KcO5BRcfbLBmcFUjoVU8zLIdWD LZwLC6MfMtRLYtkwx0qVDf5AKN6l2RlnILGyS2QSh0aqWrSztjIhHDVyG2Nt Yjiq0AESVuyqZYMu45fFNOzLxgLpeY5ecJk5wBJji6Crnr+3DmRUMZM8PyG1 S5SXM4dYudmnLP6hTghYje95PqnMkOfnpXbzLrWrDcUZ10/gOUOPIASbmUhc EZtThsncgYyKs+e5hOETMj38BYi2HBcWhue57FehHI1T4dlWxfEVaolamp3x PJcT6YhGUByHlTWoXF+ZGD3RbZC1CeKZzkJJ6gsDXvayM60rsmwskJ7pMily bKwU0mP1Dc+bcSCjqplk+gnZ3YaQsxzDKSOUujTd+J3VeM/0aXWGTD8vu5t3 2V0dQZhx/QSmc/4t8Ri2M7EZKWa5DWefuQMZFWfPdIYIhSkYU3h3HE2nRsvC wuiZLm9MkbOmOXZaCrEUxtLsjGN6yZbK9lAldhKVg7NSVyaEJ7qNsTYxPM+J AMpZVZSiUbvI7lQ1ajcWSM9zcl+ch0F5HeFqDlrWHtrWgYwqZpLnx1O8JLx4 MGcIsweL//HokBA7q/E9zyeVGfC8NQNPd3j5uji8uT7Nt4WZcs56y4VFRs5v xL4meMje6bBbcwcyKs6e57IpFtsFExvLo9H1UwsLo+d5Tk6T8UIajYq/Jlbt WJqd8TyXIwzF48DJxIDRp1F2pvyUQHqi2yCdjT4F4pkOwSNSVpRr84cVU9lh G6s3B0zH46T0iHii2MpaJFtLrFNMt+5xjccrYG8uY5RdN5ih5OBCSuysxvdM n1RnyPTzsryF0BCmK3HOuD46o3dOb5Hg9EpIS/JfuM2LYvi+VKLFskmGDQuk Rch/aWdz7h5hjwM5NVOynuT1iVDqIlGe2zZzgNE2k095ZaRvJs4IQ+8Xho5/ Z2TNaTXUJ9I8sqHU1ymtLKdkcOgNU0VFaJ8kEi97480t+vSe1RRG5w3TwFXf QKzIA2+4SH6lAYE3fORZa/NZfIo37IXBOs6wE2+4Fcnhq1l5h4O8N49gOwV6 7G5Ss/Jm6imHzjBHE5M+waKV7W7ECfQcuHUgA70JyORAm9C13NMPNF77gjY5 sZaEHDkgZWPsrMb3A22SFuFAOy/RXHSJZr1nb8b10YHWksw3iUNw2ZQlL77C E2UshNPH3GGMSrNfURLqH4hu8GZC2YyuFoOFBcHLUbpQrhjVDEdxwiiS4/ib sB1Lsy9uReGdd/K+EcItJHo5+kaFLlcmhlvacD1NkLUJ4ioqZPMO9kcOR9mo Wg7qlzYWiF9ROHVAclNYgBwXRV2t3pqwdSCjqpkk+vEEMMfCQHQqcTmYGW2y Vy5Uxc5qvGfVtDpDop+XAC66BLDeYDDj+glE510IOAlibbAfnBrKsFtzBzIq zp7pGF7sy8TsYfZiw4Ni6cLCeKG6vJpRqkhJO7A4aN9+afbGU52DQ9mTxd4E EtrYYSqsuDIxeqrbIGsTxFM9lTdI4d0Ts6WudjBwNxZIT3VUw+ZO5iAsGF7c phPaWwcyqptJqh/PAGOuYTxhtVE8JGzXr3beWY3vqT6pzpDqsj6e4SZ0GWBt OHSm0ZRB65vEW4PF6WEqJHvLYSuKpvN2rbbzYlKOz9YXio0hGIe+UdsVjpfO +pkAeeF6zSk4nKpG/hafY1Al5xpipsYwztmCWLHHFUOPAjO1QnVGzpREeqrb IJ31MgXiqU5ckyI3iflSM8U8ogzbjdWbA6qL8UAAidINpvZGiXVr6WaS6sKt CVV484Wqb5ktqEciwyLLdajOndV4zysS6ePaDJl+Xga46DLAml8zro9O6s5N KHATJOCFhcZ7S3ATimFujJWMSghELUeeEcpQVftz94jBtNI+gk9v5v0j+M7r VVG83fLng/y5JM3zenaZXXNUXJ/uYdQw7mT3rxzGgvWuFhlaOa4p51QUOBW+ UwwKBipOBaP3kzhShHEJyEg0hvmWgIqOxS5NifHpzbIHZyHFIXi9K4o3f/n8 /Nf418VlecVUeLW4LK7by4dX3rgWMDFjfHNGT0pdtry9ZrDsWDpDfLgkvnth gq4ocEmKwCU58qy12Vs+xSXxz5IEHaIUl0QEWhwk6KTAhSwMRR28SUEOQgqH xcZ8Cp/ebPqn4Kx+uCzeQlwnrrfspZHEH+cbEehlt6z2MSGTQQc+vdn26PiY sO1qfenpoCdCWGmA8enNhx6s8wfRfqf89WVx9eGyuuLC39Nf3wa/et1zfheF 15z8R2iUJM9ghyr3to8fzOUttfn0Ztc/HhcRLfzy4RIL/Ri1w6nlvLR70aXd 9aFfM66PTi1uMuk8EjGDKSemEpLAMlEhxYy5AxlMHi2IK8mI2YZPBaVUC8IA QnfaUFuYKK4mg5ojXhJHRow6Kjn7WyfXlmZ/3MpDHIGXs7Gii1fC6zF0Jnpl griV5xjI2gRxS5GcasBeFSqXyWVz9P3gwH4TxK1FMrYofySlJNU/5DP0jsGt QxnXj3M7h2PIyIpz5mfLDPatY8Bzfib2AAXzOjC+M5vvbAlDpSHhz0uLF11a XHN1xvUTCM+uRQpIoLwUcxK9CqfCuQMZF+gL4bEW5bBn3pnMUVmshCHKwkTp CZ9wkAYOKME58dd0hn5p9qcnPFVI8mIIEo/tqx5Vf1YmSE94G2RtgnjCs3ub oAJd4eB9Tq7WOxg3JkhPeNlUyulhuOYUkogtF0p261DG9TNJeCM93hOemBtB baYO/GfZY6YkuTPb3zN+Uqch42XRPsNP6hLkuuiusw0nDHrsRTfFcwIqbMW9 wRnnHXKKq531N2FX8xqxFqQVDS4reXZJh6BcpZfOoptC6RnPCdT4SMR75E3M HBgaKrez3Kb60zOebAg1smiKk9p59ZGy8TvjawqkZ7wN0llVUyCO8QxeCSvK eStSQoznFnanM5qmQA4YzztECSuwDY+aeZJVIUpnHE1JdpLxQrCpm/wUz+qC r0kxCoQnMjCc4zuQgbHTLv494yd12jH++unLfv+8uH2+ff/bj9vP+/9z+/j5 /vvTq6/7T88UqEYMzcf7z1/8z88PP9qr2Fm/Pzw/P3zzv33Z337cP8pvhDw+ PTw8+18gqOD+5/75jx+vHh7v99+fb5/vH76/u/jx8Pj8eHv/zBNu7j++u3jc fmz5/PHx9s/7759frrb8/Lr/fHv3r4X+rKXd9Z8Pj/9oO/L+/wsAAAD//wMA UEsDBBQABgAIAAAAIQCghZlkZAoAALoeAAAUAAAAeGwvY2hhcnRzL2NoYXJ0 MS54bWzEWV1v28gVfS/Q/6AKBvZJ4/n+MGIvEgdJFs12F+tkH/pGS2ObNUWq JJ3Y/fU9l+RQsutx0gWKGggiUbwzc++599wzM69+vN9Wiy+x7cqmPl0KxpeL WK+bTVlfny4/f3q38stF1xf1pqiaOp4uH2K3/PHsz396tT5Z3xRtf7Er1nGB QeruZH26vOn73cnxcbe+iduiY80u1vjtqmm3RY+v7fXxpi2+YvBtdSw5t8fD IMtpgOIPDLAtyjrZt99j31xdlev4tlnfbWPdj6toY1X0iEB3U+665Rmc2xR9 FIHrxZeiOl3y5TE9rIr6enwQ69Xni/Fh29zVm7g5b9oaYTx4f7s+eV31sa0x 1HlT95ht8nP7XZHaFu3t3W61brY7LO6yrMr+YVguFoixz28a+LH4Lf7zrmxj d7pcC50CgY//EYptuW6brrnqGUY8HqOQ0KBh3bE/lhMecFbok65/qOLokOCC vD2e5x2W8K6oqstifUuxOXw5vbr/nQyfBoOsBvjpQ1/2VaQPVfHQ3PVDuBvk Jb4ehPT44MXirm8+kdXbWMU+bg5eW5/sqqZ/3cbiyYjduuiByDllLv00fb/Y O9ptm6a/+Rmhj+2I75eifThvquYRtjCNLY1Qbu4fTdy0m9g+etLfDzP17W/x ij5dnf3wqbiNAGCxi+1QGvU6/vCXow9H4RUcHF7q+va8QBGRwa4/R4r146AD DPRsgZkpMemNL2fXbNHtNou+WfTj2DTSFwBGrw7/7UfEM3wZVoOP4/Io10aH uoftZQNKoLSvUfIDluuT/Qv3vxcVTVrfbb/l0fsjwU+O3h8ZPzsGq9mxkRbO m00848MLA00M35+6rcMIxt7vxd76dPk+ovaKagrGMNje+X20xPSCYtY7K5y3 SlutghaPw7W3kJOF0Mxoz530gktjrMsZqDSFZMaBQKzVghvlVNZCTxbGMae5 sjZoK4zmQubmMJNF4AyL0eQFD54bnp3DJjdkYCpwyYOUcCcYk5vDJQtnmPPe WO2lcIKHbKj8ZCExh7DGe+2sUsZzm5sjJAsfmDaIleJcK+FN1nOR8l0Zy0yw 3hituBBuqJxnIU+Y4z1mOJfCCqWF1jobLJFANwL90EtrHdhRY7KsJyLBboJn 0nAbHBfcGut1znmQ9Vi6NgiGRiM8JVdwzg3F8qwvCXhHJgoL8twrT5bZWRLy nhamrFNKB3y2L5jM0MMFFIq1WJUJTo5V/OzCEvZCEPhKOacVJX7IBzmBL6RR TOJdhwRDTvpsgskEvlAe1WWkkiYIA5SyEZMJfWGEZRZV74wVWiqRxUUm9JHD BiFzUgF4hyrLxVgm8JGGjoFMDGIGY/WCSQJfBK2ZDlYHlIq0ymcDJhP4KF7N rJYWBSOtEDpbwzKBT8XOhFbSexSOUiLvSwJfaq5R+Bw5BivLXwhYAl+CJJgy BhAim7G2bFHKBL50ErAQ6B4xgPtZX1QCX3okPyIMtgMncdRMDheVwFfceBaE BH8rJUHf2YWpBD5e8wyZBZoIYA0wX3aWhD5ImCORkVwGJgptJWuS0FfGKRaQ 94GD+LVQWVxUQl85HZjlGtWC3AfRqOwsCX0VEOQQgnRgb1RMyM+S0Ec5WsYt RwELrwL4PztLQl9LT1AiwRyIHFNlOUkl9DU4lYHLkI8oZkrl3Cw6oa/xJht4 klgJhJHFRSf0tVeOgV1Qw8GCMrJkoRP4hkvFBGKMjIEN0jm7rgS+keBKFApa qvZeupA3SeAbxJWBjTjIEtZoA9lZEvjGeMdQjFwpxcEWWbLQCXuDdsJAsYIo QMEi733CHm0VIoFjc6YhFHyQ2TzWCXuLpspAK4ASHdnLp5QEmbnXfeOXJD+T mnz4flX54YhU5Yf/iaocW7IL6MgIMGSVtJ4kVg6alGRQSUhIgxB7pxHvfNBS kjlETAtnDYXaoclmwUw5ZimN0ZC41CBX6KpsUaYUs5J5YcmHoNDGnM5m5Zxh SEkkMYBHl4S4cNlVzRkGzrcBesIhJaVWT7Hfa+k5wTgTUIch4F3MY7NEkdJL g4u0JAOIdaVRkjk4ZmYZ9JGFFEV8FdIyy5J7RYnKgjiAmkTvFlDs2XIUCXSl UIwalYtOjJhBI+TWNUtKyKOxbYO6UJRIrqxJgh3kjVqUSBF0e/iSj9csKaWE Ancg/ICepCxQyc6SgBceGwPtjEbRSyirPOeJhDz2RNAgHMHV2qAr82x2iQQ9 CWoDPa2wNGgkpE12YQl8xwzqxENbQR1rrXw+yDP6oC/FPRoKCguZ77Pu7yUl U0gwxRFhA4Xh8ujPknIlGPYUKiiDvQttQ2TWmVlTrqjdO4F5jMUC4VmWXGdV ubIoMANxhbbkBTQWz7uTCn9FZYxNpMM/iGX+kqpOGbAitQ/hQixOzRyCNAfO LCxXAkIcAgECGZwBfS3zNikHVsgbRE0GZEEIAqSUt0lJsIJ65x5SwUHGYHlA N7u2lAUr4ZjFFpSgUVTPLyjFJC9WgvauxK4OG32DU68s1czqciWxsbSoADRl qF4Ke25ts7xcSQG2ccZrFAOlgc3Pk3hgRaIEKQ0RFyQCjf11dp45D6RmkH3Y likIM2xKVTZus8JcSQMVT/s97EkCYi6zTKgSFaxAUsoj0EZLJ+hoIW8z54F0 6IDYMnENGYzMy/czNecBVDnaMbZWKCKQ1QvMNqvMFW1JuTPYKKKfCYizbKxn mUk2IDQlcG4Dpe0Nz+borDNXOGBA6wB5AB1LBzh5myQCVgoqAGRj0UCALMRT 3mbOAyXRDq2DM9jKeHBilkP0nAewsQ6bLShUoIRulZ9n5gO0N9oy4BgL0Q5w K5tvs9xcUUukUxyhA50FoCZyOarnPFC0a7QG2zkcMwgQcN5mzgPY4JgIUht9 B50xPN1svaA4k9IcT3oPTlVhMx3qbj5eVh1Jwe6m+foxXsd689d4eA49/gLJ +uikl94+L/q/Fdvp1Hy6NqDnF7F99vmvsV3TxcBw3nrw/pu7y8sqXpT/OhwK K5yXVtz/NB15e+yfuIYYHw7NHz+HIhsGJd+enH1jxtfD0fRji/1IMKhwU0Nx aNoSixyuSMaVbsv65+J+nHFbTEfgEBsHkyXbzXA8/8jB4v7XZropuUxj/KNp 37flBlaxGxzBjuHdtn/2mHfRNXcI28eyvo0b3FodjPGpXN/S6f04H24Spt/K umkf/5YOt+lKYX0LxOc11fG+/9SMhnRn0r2eHKRIp4ji7oJ+ipMfdBvx99ge Wr2J/dcY6xSwDVKDxgQUc+jnD48x2M/x3RiU0zz/NQDVQfC+CQBuB/+Pod+n 5h8MPV1jIM8+12W6TUnhmoAANo9ujobSpwKohk9zhkxXQ9+6qxqtyJ5G/b3s fqmriUamnN2U3e4NrhVvu9dTIl0XuxERYo23RES/4BoMxXZQQVjmfHG2a8u6 v4h9j1IdOOsmFriCeodrrNgOhbQrriNK4rqsu8UlroyYw4nW/g+aYrmgO06G Y+7DPyuXC9yoPvu8z4wzTk4/0rb24A/SB6VMa3r+x3mlcOVuN5bJE9eS18OV 89m/AQAA//8DAFBLAwQUAAYACAAAACEAoTmn86wCAABEBwAAGwAAAHhsL2Ry YXdpbmdzL3ZtbERyYXdpbmcxLnZtbOyVW2+bMBSA3yftP1juQ15CE2iSNg4g VZ36tlXaJu2xcsAJbo0Pwg4h/fU7NuQ2rVOn7nFIxPjcfC4fJG5LRfDWhjUJ 3dSamawQJTdBKbMaDKxskEHJmlLRjx96S/iTJaxWMhOsW44+7Rt8RJsJRVM8 JwZmCl4JxXewsaRhorUJFbm0Xu30Mi95daYhObc8oSEd+RCjsxhp3HQh7a4S ROYJfWzHeD3aaBxRkgHUuZEvIqFROBuPh/6XEoxR4cnOBtMiFbdFQsuh6vR1 Z6u6pRV9cniSreFZkCeQ2tidwqiltKLuMiOYigtE1jXPpdDWlwrPCbXuwAy0 Fpl1eSa0xqd9PScFHKo5rcSE42hKSed4cVZel8SgAiOtBM340oDaWLFwRZW8 XksdKLGybDqfXF5PK7vohRYqNo0unWQrc1uw8Gbid4WQ68LidtbZu0AvgdS5 aFm4aKSRS6mk3bFC5rnQi9JAsK15FfhUmHXeA7KSSmWgoE7oxQovEfo243S1 EbaEHFvANxYOjXUOOCz0iI4uft6uq9jIHLYEtG9lH3ipePaMjV2abFMLHHzf 0MMYfmm5Bi2Og7JI3hJa0nfQlZFLNxVsY8CVZS69gQOOkDiXzd7Q+aFerjVz jR2k8Qi13i4eNawP2+1bdqccB5+QX/KwfMLo3/30v4DtmSJxyz5DI35IW9wJ pUxXsxN/Q2p/I77VWQF1lxgJx0MSzoYkwmWO9+S43sSjlp0aY8hbrOkeO53e c2WEN9hLukJb9hW26cRp3MNeeIdQlTqdO3n/7FR+e6jQWbsWeOpfBXn2TpAn k/Cc4uiM4nmE2j3D0RVu9vBG/p14B8D4Cv+n1327/hm910jrdEiQ4SvHcYg3 snyDOF95Nk9Ifzu80Svwzv4G3hH+daY/AQAA//8DAFBLAwQUAAYACAAAACEA iVvSAq8DAACiDAAADQAAAHhsL3N0eWxlcy54bWzEV11v2zYUfR+w/0Dw3ZHs 2JltSCpmuwIKdEWAeEBfKYmSifJDoOjU7rD/vktSlhXHsZu2wV5iXor38NwP HjLRu53g6JHqhikZ4+FNiBGVuSqYrGL89zodTDFqDJEF4UrSGO9pg98lv/8W NWbP6cOGUoMAQjYx3hhTz4OgyTdUkOZG1VTCl1JpQQyYugqaWlNSNNZJ8GAU hneBIExijzAX+feACKK/bOtBrkRNDMsYZ2bvsDAS+fxDJZUmGQequ+GY5Ads ZzyDFyzXqlGluQG4QJUly+lzlrNgFgBSEsmtSIVpUK620kC2uinkv3woYPJu jJEPeqkKoBFCToMkClrnJCqVPGJMgKDlOf8i1VeZ2k8e2K5KouYbeiQcZoYW I1dcaWQgv4DrZiQR1K9YEs4yzeyykgjG9356ZCdcSdp1gkGCHCG/w/+0j8uJ j4fJgu4opG56EtKabJQgZyMK+uQzG+IhUW8GPLVE3qICLpYGysY473prDL1l J5IIutxQLVMwUDte72toAAkH0hfSrbuyutJkPxxNvt+hUZwVlkW1dG2nqyzG aTobrcKJS3LWfujqB50PKQp6hMHytK6Qe2GvMFyE6av3cltCPjOlCxC2/mn1 U0nEaWmAqmbVxv4aVcPfTBkDKpBEBSOVkoTDMDh4tAOAzSnnD1b8Ppcd9gjy tCt7KgAyajvUCoIdQoHaocfzBuA/cZodnYYvOiFS13yfAriD9hbgH62Fi/to /8lZJQXtO9xrZWhunOa7/Ab9qHyMvfCGtz8UH9qV5wNtNfJafjp/H/Onrcio Tt190srfk/TZnF3N+Ssxz9dxhFG/jieYqauG07In/M5jwewFrF7t7G0DGu9L ib5qUq/pDprAbRTsypNm+qW7bZRm3yC39ipyhwZfJ9DrZsulPQLnUwel67V1 Z/3CRL5UlPNNc3uxKKeN2HJ/FdvLO7zEFrJ3psUvY/0wW/uOaat2uUm9GL1x wz9vQSvPtu2ddoFa9aT5iTB30obsaynGn6yCcHh3teqEsi3jhslOq04d7qnO QT4PHtAyPQ9/o3YuwKLYHS8GJ67GvkfdldHxgoQWtCRbbtbdxxgfx3/Rgm0F HKF21T17VMZBxPg4/mjvr+GdvXVBCj428GCEX7TVLMb/vF/8MVu9T0eDabiY Dsa3dDKYTRarwWS8XKxW6Swchct/e8/jn3gcu0c86M9wPG84PKF1G2xL/uE4 F+Oe4em7NwPQhkIeggia7p+L5D8AAAD//wMAUEsDBBQABgAIAAAAIQDVzRw6 +AEAAKEEAAAUAAAAeGwvc2hhcmVkU3RyaW5ncy54bWxslF1v2jAUhu8n7T8c 5QqQiBlTGZoSqojAWnUrKEm1u0omOSFWHTuzTTf+/ZyGTpPNJe9zPl+fEN3+ aTm8otJMijj4FM4CQFHKioljHDwV2+kyAG2oqCiXAuPgjDq4XX38EGltwOYK HQeNMd1XQnTZYEt1KDsUltRStdTYn+pIdKeQVrpBNC0n89lsQVrKRAClPAkT B58XAZwE+3XC9T9hFWm2isyqSB42u+0W9ptsu8t+JI/rDeyzTXq/Lu53jxEx q4j0kUP0huMrNf0yLimw7VBRc1LoMdOokzZTu6hhpUdzpGDLIoem82CKQjNz BluZSfDwXlk7OEcFWNcebbrJzc1sVJspPxCN5ZiMXoyeLMmXyXJJFj15k8cx P7j7JOsihOIue8oLF+UdYjXaFiTfrMce3Kd9E09PWf/OJbrxtDQh3PmL598N fUFZ11er2Sy4cG/rwWYYTCdXPE3KEnl4Wf557o1asBZHvV3urDm3brtiY0/v NxOVq1sTXOla2PAEbuQxBN1VYOT7lm5Aeha0ZSUUb6fl0m9Kag0/kR0b47Ii 3IUX5Flnz8S/hAclObcfrFvogaKSrmgr1J1+nrv6MOe0OtNhbq91JnkIGeoQ RvzgOZ/YViGkih6v4iLJYWT7jr1E3T8ZVO+J/7Ul9i9m9RcAAP//AwBQSwME FAAGAAgAAAAhACTg2YSlAQAA8QMAABgAAAB4bC9kcmF3aW5ncy9kcmF3aW5n MS54bWycU8FOwzAMvSPxD1Hu0LUbMKq1CG0CcQEO8AFWmq6RmqRywlb+niRN yxgc0C6V89z3bL84q7tetmTH0QitCppezijhiulKqG1B398eLpaUGAuqglYr XtBPbuhdeX626ivM92aDxAkok7tjQRtruzxJDGu4BHOpO65cttYowbojbpMK Ye+kZZtks9l1YjrkUJmGc7sZMjTqwQlqEoSiZejM7vWat+29Yo3GAapRyyFi ui3TdJX4EXwcGC54qesyvUkXi9sp56GQRr0vZwPswxELlGy+zK6mXKAE7e+K Vk9Fymw5qU+g52TLq5uoEnsZi5SL2Oyvyn8UHUttEbpGsAcEyYkEhrqg0Ry1 ezxIvkZ/2PPuFYmoCjqnRDlWQdcNoCUZTWKjz0dEh4dB/xbsa3SGQ67rmvQF dZv16b+OBDnvLWEDyEY0SI2k2L7/N4YbsEA+UJywGMzP4YZneYjiirGTlaLA vzbeTS8Y32j2Ibmyw9ojb8G6B2ca0RlKMPeu41OVenOSHxMfnqPbhzcbL6YV TtsbNN7I0f4Ha/1rLb8AAAD//wMAUEsDBBQABgAIAAAAIQBsM6rIjgEAAMID AAAQAAAAeGwvY29tbWVudHMxLnhtbORSTWvcQAy9F/IfxJxSSHeclIaw2M4h kNDSQw/bH6CM5fWQ+TAj7WbdX195vRtKoLfeCoOR3ryRrPdU3x9igD0V9jk1 5npVGaDkcufTtjE/N4+f7gywYOow5ESNmYjNfXvxoXY5RkrCoAUSN2YQGdfW shsoIq/ySElv+lwiiqZla3kshB0PRBKDvamqWxvRJ9PWuJMhFz4H7ROWCR6Q aartcteeAyWdOn/3LG8JFOob8/TZwML/2jWm0spCByUVPT/082zbmn/BHoOO WhnNXA65gE8dHUif3F3PYHnMSRbWBocccQZ7jD5MC3ozA/ZYUv742XVttZmd u50a/utms9hrHtGpE6omU9mTUTc2A8Gg4r7qJOAZMHCGHVMHksHlUsgJjEVN CYEKUN9759Xn6QrUWhB97jC4XUDRPdA4Qcqv0GVItFVsTzCXZrgU9OEYfnwb 1i4i25Mv7zz59uW/9USN0CNlR8AjqRk+wUvKwleqrsxb5x2K4ujLkbCCv4t6 lndZ+3PG7W8AAAD//wMAUEsDBBQABgAIAAAAIQACTK8vSgcAAAQfAAAnAAAA eGwvcHJpbnRlclNldHRpbmdzL3ByaW50ZXJTZXR0aW5nczEuYmlu7Jl5VFNX HscvoBIWQxDbAZpKgrJYwLCMLBVlSQKkJiQkAUGJQCGBICQYFgkdlG0awEEH aMUCw0C1EBVBKMuMYFhEZHEBVLSMJgIBRKAgiMg+L9jpac+ZnvmjZ/7o6bv3 /O73d3/3d3/3vc877/3zPAANYAAVcKDOBcGADcIhi4FitmAvsIQ6BhCBHaQO gAf5DGhVAGWyQTRQNKVNYMtTYLoDv56kqgSUwEt1PiIEUhUlX2VlSN+N5I2a MRt7N7b9qkHph93KkCpMMV+H2g/hH4VA8vQ2hJYdVSb1ZyqeJP+48F8cxE9i /6n/kxDs/g4I/Oy5QxMGhfmJ4rZRYAb8uveExIuKjXHl8oAblU5hUL3peCKg ExkEMhl487gCdrTCowVFsQUMbgIbkIlMJpEOqAIumxcTFMPl8wCNSmfSXUhM QGdH8yNiN2K2lpYhUVyA50fwBRR+CPudZ/1HQGGHcIOYwig2oJFdSJ7Ag8bg RkZFcDlcdog3CTAFsez/9Tgn9QEgedM8lMA2YCC22dSKO4gvDk9EmPY8wPpC L53CDkJFFOajA4C1HgCTkHZA+jOOv3CQImcmXxngP/anCfihgqBIjBs3gh3t T+EGC/jRfE4MhsrhcIPZ/u/Eytqf6IsnkvcQfYm/UBIOwwR+0wRsNgNgBpl7 DgDxA1MsFhXtrXtS9GFciXNyZo3zEbGbRr9p92xVWI1zcj+B5Ey2zMJaFfv8 a4BW8CJrpFUDN9/epju9onr0Nf0vUr0L68X5Yt3hWzm24TqaB0Lf/O3Zt8N+ rECjPmFRZ8P04oBNqDTxjcNclY2ZoUV00fbnjzPQva8brjn4tsfXOHwzknst YfdovcqDJpFkS7Y0KfErlN7s7ASB/v1bQ0pOpex190Jwe7/6ROV746nrm2yP FhjwVSbdLzJm/HwrbJu2GssKtpPyF1p2ED/VjtN972wTTjBRMO+6/s/6Gxad kYW1Pt/lNkjLO9vOl3uWLusfWHC3q+/CYE98KAgQPrlsdVGy74ZQ9d6RreJg 5YaQav0VpMU+9Su9s+IvzeonLvh0LjdG8nIPjayt4Uz/QOVrWfiHGgXfyMpz CqzPLgrbLlS3ndfy2fkZn1NY6SeUDalKXknjhnObu10pVj4HfRrJi66UkmkQ 5BdW9zRtqv36zpap69pf1C8tSspMxlSzVjNffztob2tn/dXcsKGs9WXgqqWw rw7ZtFrT8TK0jkXtHOj/+GiPO1K2cKJNv2mVVes0RtgcID5rJRVbcFldmZ+F SSqu+E3cfVNas/p3/YIo8xuHJedyUnMer4sGcS0nWk+J1xjzAVcCRHw7VrEs zaC8zL0MaVOtfcdPg2Fo0LLse9fiDn6Vmr5yBlVfsrarNK+M7SdtrjY3c5ms 7Jjw3bNlcYe8svN0fOLBii2Re0oi0JEVxVNm8YlqVys+HejqSnJMiT3atq3f /6953f3meZesjo3naZMucIx0T+sNap47LnQrDbHymD8vpN7rZj8McAvAIbTt CnPVJn0shucC6BX3bn6whjrerPenhcrB6KbiLmKbxihtUuXYFi3O/draFNnp /Z3nEhtNPJkGjFnOtfvVKX5hXpygB5qfaHrdRKE8KedTKZamVoQULKYrvNU+ dRv+rabS4MO03eGuZK/ujYQyY5oOItyVoBN/IDnfmaYTQbG/WawIpXyj1vg+ iYIRq9UZF7JpYrVNe1v60qI11fcmFxvPXMffyQ5BIMqMHamUYmPUw7R0Y7I1 dFImFlOYP4Ne0FHkY79WW7lLR3vd3jhppNYjBYNwvXNzqHXsctp9OmL6S81K hvHO23qxS0UJ86oX38rdhz94ZHfJSSzxe9z7tcR7FTu/IOYzTlUuxc2LHhl4 yUokjMS8pZlLubd3ncK9Pf6slPesVCdbNyZzuehVgYXQoD2UZm2NcrT/AkM4 qeR08tjuUdaC7rpc3oNIdbd3kC9Fdix4Itm6jq2dJSG30PqBM+nKooh/3Nu9 /lzeg4JSYjtikbOhJiI3PUfD5gi5c7m0d/RRKR25dTO6yzqe0JxRd6avGune gEMSY01P71x2EZI5gYv+TaNuzdcisPv96QfKx4ca7A2kWS9WztoTpG2qLO8R VK3JGfvDRGS23au2KlZU+rJTWsurj46nN2bgrp+4hQ3Xwras53q3l2iPrdGq dh3xyDo8Mt5USw5WY6i4OFQ5oYqOFPLMLZy8sKK+nO9a9EpiMhL+XJgxy/2c PHAInYATFC1JLiuqmYm+lxmJxPvlPSr7nqPGcIKO9tSGIZQQj8wofNrr7zaF FWW+uHoejzdynx3PeZo05yGTj2qY668dOqe9PPdEws9DGx7rKBHFdWA/0nLY PvSwzoEpB9PvZ5qINCdljIYK3rP0laIE3atul/TTBIaNlcNJuL5mJxejy21m 9/vQqU1gqq2f+Zv+5sMXDxOACcAEYAIwAZgATAAmABOACcAEYAIwAZgATAAm 8P8loPgH9W8AAAD//wMAUEsDBBQABgAIAAAAIQDl9BPuSwEAAF8CAAARAAgB ZG9jUHJvcHMvY29yZS54bWwgogQBKKAAAQAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAB8ktFKwzAUhu8F36Hkvk3T6hyh7cDJvHEguKF4F5Kzrdik IYl2fXvTdqsdipCbnPPny5dDssVRVsEXGFvWKkckilEAiteiVPscbTercI4C 65gSrKoV5KgFixbF9VXGNeW1gWdTazCuBBt4krKU6xwdnNMUY8sPIJmNfEL5 5q42kjm/NXusGf9ge8BJHM+wBMcEcwx3wFCPRHRCCj4i9aepeoDgGCqQoJzF JCL4J+vASPvngb4zScrStdq/6aQ7ZQs+NMf00ZZjsGmaqEl7De9P8Nv66aV/ aliqblYcUJEJTrkB5mpTPDLTBktmoc3wpNyNsGLWrf20dyWI+7ZPZvh33dN6 +QEJIvA6dJA/d17T5cNmhQpvdBd2a7YhCU3n9Gb23l17cb7TGwrydPm/REJC koSJJ6b0NqZJOiGeAUXvffklim8AAAD//wMAUEsDBBQABgAIAAAAIQDp+Cjs 8AYAADorAAAQAAAAeGwvY2FsY0NoYWluLnhtbHSaW2/bRhSE3wv0Pwh6bxzd 0gviBNh7l6/tDzAcNTZgy4FlFO2/r1p05mB2dV4C5PNwzgxJaSmSHz//9fy0 +vP4en58Od2uN+/er1fH0/3Ll8fT19v177+VH35ar85vd6cvd08vp+Pt+u/j ef350/fffby/e7qPD3ePp9XF4XS+XT+8vX375ebmfP9wfL47v3v5djxd/vLH y+vz3dvlv69fb87fXo93X84Px+Pb89PN9v37DzfPF4P1p4/3q9fb9a+Hw3r1 eAmxXj39++8N+Yf/uZEfJ3LJ+d+21GwuPgPZTmQ3kf1EkMqcpzybKc9mzvPz 6Ly97GxNuJ0yb6fM2ynzdsq8nTJvp8zbKfN2yrydMu+mzLsp827KvJsy76bM uynzbsq8mzLvpsy7KfN+yryfMu+nzPsp837KvJ8y76fM+ynzfsq8nzIfpsyH KfNhynyYMh+mzJvRuY8bLZSsLp9r+yD2sVsfqyUodMPgYM7BR6uT6FdAH/dz phCbNhLdtJBDGUk0ZeI3hvLF4d3h2bh8jxXjslsDORLWiTQSbRcdnjY4N8Yu 13l39MG4dKnkyJxJNGExLq0bORwiiTqkDU7Qsct13h19NS5dAjmSNBKdmMmh LCSqjMZlVtrg86j6xeHd4dW4+AdyJMwkuleLcTku0eFpg8/gmPw6746+0R8J gymlSyWHMpOMXa5niKaXjmlz/QtpcXh3eKM/EgZTDl0wEcrsKItxyRwdnnjt MR4XfDkr746+0R8JqymlSyCHMpOMx+V6hkY9HCKJOiReR2mLxeHd4dX40GVc i7OjLMbluDRy6wLPsQtWee0SNuSSrRmXiQs5JnYSda7kUGYSzVaMy6xoXLIl XrvqxMXh3eHVuPgHciRvJJo8k0NZSDRbNC6zEq+6Vb84vDu8Ghf/QI6EjWTs Ml7jFVPqcTEusxJ/L4xdnHXf0Qfj4t+MS55Kjo55IoVEs0XjMivxl47qF4d3 hwfj4l/JkbmRjMcFVxpQFlPKfojGZVbib7Sxy/Xrge7og3Hxr+RI2EjGLpgI ZTHl0AVKdUj8dTl2ub4Kd0cfjA9d4IOEzVFmcigLiWaLxmVW4u9i1S8O7w4P xsW/kiNhI9G9msmhLCSaLRqXWYm/6FW/OLw7PBgX/0qOhI1k7IJ1H8piyuEc g1IdEu9FjF24topPd/TB+NAFPkiYHWUxLhMbORwiydiF67s4LLy7oh27w4Px oQv8kaQ5ykwOZSHRDNG4zEq8/6P6xeHd4cG4+FdyJGwkulczOZSFRLNF4zIr 8c6V6heHd4cH4+JfyZGwkYxdpnXflHLOROMyK/Ge29jFWfcdfTAu/pXcutBZ lHlSFhLNFo2LQ+LdQtUvDu8OD8bFv5JbF6zv43EBh7JwW80WjcusxPucql8c 3h0ejIt/JUfCRjJ2wWoOZTHlcI5BqQ6Jd2jHLlivlXdHH4wPXeCDhM1RZnIo C4lmiMZlVuK9ZdUvDu8OD8bFv5IjYSPRvZrJoSwkmi0al1mJd8VVvzi8OzwY F/9KjoSNZOyC1RzKYsrhHINSHRLv549dsF4r744+GB+6wAcJs6MsxiV5I4dD JBm7YF3WzAufUCjvDg/Ghy7wR5LmKDM5lIVEM0TjMivxGYrqF4d3hwfj4l/J kbCR6F7N5FAWEs0WjcusxKc/ql8c3h0ejIt/JUfCRjJ2mdZ9U8pZF43LrMTn VmMXrs7i0x19MC7+lRxdMol2KcZlYiOHQyRRh8QnbmMXrMLKu6MPxocu8EGS 5igzOZSFRDNE4zIr8Vmh6heHd4cH4+JfyZGwkehezeRQFhLNFo3LrMSnnKpf HN4dHoyLfyVHwkYydhmvEIop5ayLxmVW4vPZsQvuzyvvjj4YF/9Kbl3oLMo8 KQuJZojGxSHxybLqF4d3hwfj4l/Jrcv1VTtPykKi2aJxmZX4TFz1i8O7w4Nx 8a/k1gVXAuM5Bg5l4baaLRqXWYlP81W/OLw7PBgX/0qOhJlEuxTj8ulo5HCI JOqQ+B7C0MXh3eHBuHYhR5JGokkyOZSFRLNF4zIr8Q0K1S8O7w4PxsW/kiNh JtEuxbgeF3I4RBJ1SHz3Y+zirPuOPhgfusAHSbKjLMalS3R44jsqY3Kszsq7 o2/0R8JgyqELnKFsjjKTQ1lINFU0LrMS37dR/eLw7vBgXPwrORI2Ej1DMjmU hUSzReMyK9n7eHJkg3HRN+OiX8iRpE4kk2iLYlw8Ozk8I4k6pAPXX3EIxocW 1/UL9ZhYJ5JJNEMxLhk6OTwjiTqkA1decViMS4tADudGoke/kkOZSTRDMS4Z OjkcIok6pAPWVs0QjEuLZlwmLuSYWCeSSTRDMS6enRyekYQON3zr9dM/AAAA //8DAFBLAwQUAAYACAAAACEAcHv50p4BAABUAwAAEAAIAWRvY1Byb3BzL2Fw cC54bWwgogQBKKAAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACc k01v2zAMhu8D9h8M3Ru5STEMgaxiSDf00GEB4rZnVaZjIbIkSKyR7NePtpHE 6dpLbxRf4sXDD4nbfWuzDmIy3hXsepazDJz2lXHbgj2Wv66+syyhcpWy3kHB DpDYrfz6RayjDxDRQMrIwqWCNYhhyXnSDbQqzUh2pNQ+tgrpGbfc17XRcOf1 awsO+TzPv3HYI7gKqqtwMmSj47LDz5pWXvd86ak8BAKW4kcI1miF1KX8bXT0 ydeY/dxrsIJPRUF0G9Cv0eBB5oJPn2KjlYUVGcta2QSCnxPiHlQ/tLUyMUnR 4bIDjT5myfylsc1Z9qIS9DgF61Q0yiFh9WXjY4htSBjls4+71ABgEpwKxuQQ TmunsbmRi6GAgsvC3mAEIeESsTRoIf2p1yriO8SLKfHAMPKOOKXaAW0zoxMY Fuw0TeMMe4o2fR/zj6URe9riMDWCfYO38m1Q7kDCKXowbpceQ+nvFMJxI5dJ sWlUhIqWeNTPCXFPy4i2N1k1ym2hOtb8L/T38zR+Enl9M8sXOZ3GJCf4+TvI fwAAAP//AwBQSwECLQAUAAYACAAAACEA0jcLM8gBAABoCAAAEwAAAAAAAAAA AAAAAAAAAAAAW0NvbnRlbnRfVHlwZXNdLnhtbFBLAQItABQABgAIAAAAIQC1 VTAj9QAAAEwCAAALAAAAAAAAAAAAAAAAAAEEAABfcmVscy8ucmVsc1BLAQIt ABQABgAIAAAAIQD09Qc7GwEAAFkEAAAaAAAAAAAAAAAAAAAAACcHAAB4bC9f cmVscy93b3JrYm9vay54bWwucmVsc1BLAQItABQABgAIAAAAIQD0rVjpbAEA AH4CAAAPAAAAAAAAAAAAAAAAAIIJAAB4bC93b3JrYm9vay54bWxQSwECLQAU AAYACAAAACEA+2KlbZQGAACnGwAAEwAAAAAAAAAAAAAAAAAbCwAAeGwvdGhl bWUvdGhlbWUxLnhtbFBLAQItABQABgAIAAAAIQB+wYrlYAEAAHQCAAAYAAAA AAAAAAAAAAAAAOARAAB4bC93b3Jrc2hlZXRzL3NoZWV0My54bWxQSwECLQAU AAYACAAAACEAfsGK5WABAAB0AgAAGAAAAAAAAAAAAAAAAAB2EwAAeGwvd29y a3NoZWV0cy9zaGVldDIueG1sUEsBAi0AFAAGAAgAAAAhAGDo5FD+AAAA6wIA ACMAAAAAAAAAAAAAAAAADBUAAHhsL3dvcmtzaGVldHMvX3JlbHMvc2hlZXQx LnhtbC5yZWxzUEsBAi0AFAAGAAgAAAAhAA5E9N+8AAAAJQEAACMAAAAAAAAA AAAAAAAASxYAAHhsL2RyYXdpbmdzL19yZWxzL2RyYXdpbmcxLnhtbC5yZWxz UEsBAi0AFAAGAAgAAAAhAAkPcDUWJwAAYKAAABgAAAAAAAAAAAAAAAAASBcA AHhsL3dvcmtzaGVldHMvc2hlZXQxLnhtbFBLAQItABQABgAIAAAAIQCghZlk ZAoAALoeAAAUAAAAAAAAAAAAAAAAAJQ+AAB4bC9jaGFydHMvY2hhcnQxLnht bFBLAQItABQABgAIAAAAIQChOafzrAIAAEQHAAAbAAAAAAAAAAAAAAAAACpJ AAB4bC9kcmF3aW5ncy92bWxEcmF3aW5nMS52bWxQSwECLQAUAAYACAAAACEA iVvSAq8DAACiDAAADQAAAAAAAAAAAAAAAAAPTAAAeGwvc3R5bGVzLnhtbFBL AQItABQABgAIAAAAIQDVzRw6+AEAAKEEAAAUAAAAAAAAAAAAAAAAAOlPAAB4 bC9zaGFyZWRTdHJpbmdzLnhtbFBLAQItABQABgAIAAAAIQAk4NmEpQEAAPED AAAYAAAAAAAAAAAAAAAAABNSAAB4bC9kcmF3aW5ncy9kcmF3aW5nMS54bWxQ SwECLQAUAAYACAAAACEAbDOqyI4BAADCAwAAEAAAAAAAAAAAAAAAAADuUwAA eGwvY29tbWVudHMxLnhtbFBLAQItABQABgAIAAAAIQACTK8vSgcAAAQfAAAn AAAAAAAAAAAAAAAAAKpVAAB4bC9wcmludGVyU2V0dGluZ3MvcHJpbnRlclNl dHRpbmdzMS5iaW5QSwECLQAUAAYACAAAACEA5fQT7ksBAABfAgAAEQAAAAAA AAAAAAAAAAA5XQAAZG9jUHJvcHMvY29yZS54bWxQSwECLQAUAAYACAAAACEA 6fgo7PAGAAA6KwAAEAAAAAAAAAAAAAAAAAC7XwAAeGwvY2FsY0NoYWluLnht bFBLAQItABQABgAIAAAAIQBwe/nSngEAAFQDAAAQAAAAAAAAAAAAAAAAANlm AABkb2NQcm9wcy9hcHAueG1sUEsFBgAAAAAUABQAUAUAAK1pAAAAAA== ---1981468715-2111205188-1324908804=:18813--