Application of the Technical Survey in the Demining = Process, by J.J. van der Merwe (6.1)

From: Subject: Application of the Technical Survey in the Demining Process, by J.J. van der Merwe (6.1) Date: Wed, 10 Feb 2010 14:02:10 -0500 MIME-Version: 1.0 Content-Type: multipart/related; type="text/html"; boundary="----=_NextPart_000_0000_01CAAA59.A3B5EAA0" X-MimeOLE: Produced By Microsoft MimeOLE V6.00.2900.5579 This is a multi-part message in MIME format. ------=_NextPart_000_0000_01CAAA59.A3B5EAA0 Content-Type: text/html; charset="Windows-1252" Content-Transfer-Encoding: quoted-printable Content-Location: http://maic.jmu.edu/journal/6.1/notes/vandermerwe/vandermerwe.htm Application of the Technical Survey in the Demining = Process, by J.J. van der Merwe (6.1)

Issue 6.1, April=20 2002

Application of the Technical Survey in the Demining = Process

This issue may = be outdated.=20 Click here=20 to view the most recent issue.

The author proposes a way that Technical = Surveys can=20 be used as a step in the process to eliminate the negative=20 socio-economic impact of mines/UXO in the most productive,=20 cost-effective, efficient manner and to guarantee that the = best=20 technology for the task is = applied.

by J. J. van der Merwe, UNOPS

The opinions expressed in = this=20 paper are those of the author and do not necessarily reflect those = of the=20 United Nations Office for Project Services (UNOPS).

Introduction

The mine action = industry=20 has grown out of one very specific technical area of interest = relating to=20 the physical destruction of mines and UXO. From there it has been = forced=20 to expand its horizon to look at the broad implications of what it = does=20 and to encompass peripheral activities that fall under the same = general=20 heading of mines, including survey, awareness and prioritization. = It is=20 also true that mine clearance resources are typically scarce and = should be=20 effectively utilized. This calls for correct application of = available=20 clearance technologies and careful targeting of these resources in = order=20 to have a critical impact on the problem.

Some major developments have been made recently in the field of = demining. The International Mine Clearance Standards for = Humanitarian Mine=20 Clearance Operations have been revised and updated to take into = account=20 the progress in the industry, and the first Level One Impact = Survey was=20 completed in Yemen. The information that has become available as a = result=20 of the survey provides a better definition of the mine problem in = a=20 specific country and also allows for a better method to prioritize = and=20 rank impacted communities.

Many mine clearance organizations have traditionally publicized = their=20 efforts by focusing on the number of mines or unexploded munitions = that=20 have been found. This is in reality as meaningless as assessing = the=20 effectiveness of the clearance operation based purely on its size. = It is=20 becoming better understood that mine clearance is as much or more = about=20 the elimination of the negative socio-economic impact on = communities as it=20 is about clearance of the actual contamination.

Experience over the past few years has indicated that within a = zone of=20 probability for mine contamination in the majority of mine = affected=20 countries, the majority of the ground is not mined. In addition, = most of=20 the areas contain few mines. Out of the 18,000 mine records = received from=20 the former warring factions in Bosnia and Herzegovina, 60 percent = of the=20 records indicated that the mined areas contained less than 10 = mines, and=20 in Yemen the Level One Impact Survey concluded that there was=20 approximately a 40 percent exaggeration of the actual size of the=20 contaminated area. Therefore, the faster the ground that is not = mined is=20 ruled out, the greater productivity and the impact of the = clearance=20 efforts will be. Linked to the need to rapidly rule out mine-free = ground=20 is the need to decide which ground needs to be freed up first. The = size of=20 these areas is a function of the subsequent users=92 requirements. = Defining=20 the minimum areas ensures that mine clearance resources are not = committed=20 to clearing any more ground than what is actually required at the = time.=20 The Technical Survey, if applied in the correct manner, will help = provide=20 answers to the issues raised above.

Mine=20 Free vs. Free From the Effects

Recently, there have been a number of discussions on what can = be=20 achieved practically in addressing a mine-affected country=92s=20 socio-economic problems caused by mines and UXO. There has to be a = balance=20 among the time spent on demining areas, the amount of impact being = reduced=20 and the amount of funds available to carry out the task. At the = strategic=20 level, there are two outcomes that could be sought. These two = options=20 are:

Mine Free: A strict interpretation of the Ottawa = protocols=20 and other mine action documents would suggest that the desired = end-state=20 for all mine action programs is to make mine contaminated = countries=20 =93mine free.=94 This implies that all mines in the entire = country are to be=20 removed from the land and therefore all possible risk related to = mine=20 and UXO contamination is to be removed as well. While such an = idealistic=20 end state may be desirable, a more realistic assessment = indicates that=20 it is not achievable, nor would pursuing it to this end be a = good use of=20 limited resources. The laws of diminishing returns, limitations = on=20 available donor resources and simple cost-benefit analysis all = highlight=20 that a mine free state is practically unobtainable. The cost of = removing=20 the last mine in a country would be considered prohibitively = high and=20 offers very little (if any) benefit as compared to the other = possible=20 uses for the same amount of money.=20
Free from the Effects of Mines: During the planning = process,=20 consideration should be given to adopt a risk management = approach=20 focusing on controlling or mitigating the worst impacts of mines = in=20 order to make a country =93free from their effects.=94 This = approach may=20 result in the occasional unfortunate accident; however, = accidents will=20 be rare, economic impacts will be negligible and the people will = have=20 learned to live with the residual level of contamination. The = effects of=20 mines and UXO can be reduced to a tolerable level through = clearance of=20 the most dangerous areas followed by a continual capacity to = conduct=20 limited clearance and/or Explosive Ordinance Disposal (EOD) = tasks, mine=20 risk reduction education (MRRE) and maintenance of a marking = system.=20

It is clearly beneficial to adopt the second option and address = high-impact areas first and then proceed to address those areas = more=20 moderately impacted. Hazardous areas impacting communities should = also be=20 prioritized, and the solution selected to decrease the impact = should be=20 applicable to provide the greatest relief in the shortest time or = in the=20 most cost-effective manner.

Prioritization/Targeting

Prioritizat= ion=20 is only the first step in the process that will lead to the = eventual=20 selection of sites to be demined. A number of other factors need = to be=20 taken into account before the final selection is made. For = example, there=20 could be seasonal factors to be considered, the security situation = could=20 have an influence and there may be a requirement to cluster tasks = to allow=20 for the efficient use of resources.

The key for humanitarian mine clearance in the future is the = accurate=20 targeting and then the subsequent allocation of resources to = address the=20 problem in a safe, productive and cost-effective manner. Programs = should=20 ask themselves where they could achieve the greatest impact with = the=20 available demining resources. It is no longer an option to tie = resources=20 down for long periods of time if they are only working on one = site. It=20 might be better to work on a number of lower order tasks but have = a high=20 turnover. Targeting should be done at the macro and micro level. = The=20 result of the General Mine Action Assessment (GMAA) Process = includes the=20 socio-economic impact that the mines and UXO have on communities = in an=20 impact-priority list, which should be used to develop a clearance = works=20 program. The same should be done on the micro level. Identified = tasks=20 should be unraveled to reveal the most critical areas that should = be=20 cleared as a first priority and then clearance should expand to = address=20 the other less critical areas. As a first step, the less critical = areas=20 should be marked or fenced off.

The process for prioritization and selection of sites for = demining can=20 be compared to a situation in which a medical doctor arrives at an = accident scene finding a number of injured patients. Before any = patient is=20 treated, a doctor must assess each of their injuries. Patients are = then=20 divided into two groups: those with minor injuries and those with = serious,=20 life-threatening injuries. The injuries on these patients are then = treated=20 in order of priority, meaning some minor injuries might be left = while the=20 doctor moves on to another patient to treat cardiac injuries, loss = of=20 blood and pulmonary injuries. Targeting for mine clearance = operations=20 should follow the same principles. Communities are ranked = according to the=20 presence of mines/UXO, the number of =93blockages=94 and the = number of recent=20 victims. In addition, there might be development priorities that = the=20 government has identified that also have to be taken into account = before=20 the final priority list can be produced. In order to prepare the = work plan=20 there should be another step similar to when the doctor in the = example=20 above takes the pulse of the patient, which is to carry out a = Technical=20 Survey to collect specific information on the suspect = area.

Revision of the International Mine Action=20 Standards

The term technical survey is not = applied=20 universally. Some mine action authorities and demining = organizations=20 consider the detailed examination of known or suspected hazardous = areas=20 and the related documentation and marking as defined in IMAS 08.10 = to be=20 merely the first stage of an integrated survey-clearance = operation.=20 However, as it is described here, technical surveys are an = important part=20 of the demining process, since they provide the information needed = for=20 safe, effective and efficient area reduction, clearance and = marking.

To date, prioritization and clearance have generally been aimed = at=20 individual mined areas. With the introduction of the GMAA process, = which=20 includes an assessment on the socio-economic impact, there has = been a=20 shift in focus towards impacted communities. The old Level Two = Surveys, by=20 default, became associated with area reduction, and only after the = area=20 was reduced was an attempt made to plan the clearance activity. = IMAS now=20 reflects changes to operational procedures, practices and norms = that have=20 occurred over the past three years, and in a number of cases where = new=20 terminology was created, it also included an expansion of the old=20 definitions. The changes in the different surveys and assessments = are one=20 example in which not only were the old terms replaced, but the = definitions=20 have also expanded considerably. The main differences between the = old=20 Level One and Two Surveys and the new Impact Assessments and = Technical=20 Surveys are outlined below:

Old Level One Survey: The objective of the old Level One = General=20 Survey was to collect information on the general locations of = suspected or=20 mined areas. Mined areas were prioritized according to the = following=20 criteria:

Provision of emergency assistance.=20
Settled land with high civilian casualty rates.=20
Land required for the resettlement of refugees/IDPs.=20
Land required for agriculture.=20
Community development.
Access to and free operation of health = services.
Reconstruction and infrastructure = development.=20

Old Level Two Survey: The objective of the = old Level=20 Two survey was to determine and delineate the perimeter of mined = locations=20 initially identified by an old Level One General Survey. The = marked=20 perimeter formed the area for future mine clearance operations. = Where=20 possible, with time and resources permitting, these teams should = also=20 undertake area reduction work in order to accurately define the = outer=20 perimeters of the mine field. Graphically, the old process can be=20 described as shown in Figure 1.

Figure 1: Old Demining=20 Process

New GMAA Process: The purpose of the GMAA = process=20 (IMAS 08.10) is to gather, evaluate, analyze and release = sufficient=20 information to assist the strategic planning of a national mine = action=20 program. The general mine action assessment produces two kinds of=20 estimates:

1) The proportion of communities contaminated = by=20 mines.
2) The levels of socio-economic impact within = contaminated=20 communities.

The focus has also shifted from individual = mined areas to=20 communities impacted by the presence or perceived presence of = mines. The=20 prioritization process in this case is much broader and makes = provision=20 for a number of scenarios. In all cases, three aspects are taken = into=20 consideration to gauge the level of impact:

1) The presence of mines and unexploded = ordnance,
2)=20 The blockage caused by the mines and UXO, and
3) The number = of recent=20 mine incidents that have taken place.

Neither the old Level One Survey nor the IMAS = GMAA=20 process involves entry into the hazardous area or any form of = demining.=20 The aim is purely to collect basic information on the approximate = location=20 and size of the suspect area and to define the impact of these=20 contaminated areas on their respective communities.

New Technical Survey: The Technical Survey = (IMAS=20 08.20) is the detailed technical and topographical investigation = of known=20 or suspected hazardous areas. Such areas may have been previously=20 identified during the GMAA process (formerly called Level One = Surveys) or=20 otherwise reported. The primary aim of a Technical Survey is to = collect=20 sufficient information to more accurately define the clearance=20 requirement, including the area(s) to be cleared, the depth of = clearance,=20 the local soil conditions and the vegetation characteristics.

Figure 2: Proposed Demining = Process

Figure 2 describes graphically the order in = which=20 demining activities could be conducted using the Technical Survey = as the=20 foundation for planning actual operational activities.

The proposed process introduces the Technical = Survey as a=20 step between the National Survey and actual demining activities. = The=20 information obtained from a Technical Survey should be summarized = in a=20 survey report, which should be used as the technical specification = for=20 planning and managing a subsequent demining task. Although = Technical=20 Surveys precede demining activities, the two activities should not = take=20 place in tandem. Normally, once fully implemented, the Technical = Survey=20 teams would work approximately one demining season ahead of the = demining=20 teams. This would allow Mine Action Centers to plan future = operations and=20 prepare programs that would keep demining organizations occupied = for a=20 whole season at a time. It will also ensure that demining = resources are=20 utilized in the most productive, efficient manner and that the = correct=20 resources to manage the problem are used.

The disadvantages of the old process were:

Demining organizations immediately embarked = on demining=20 activities through an attempt to reduce the area without = carrying out a=20 reconnaissance of the suspect area. Only once the outer = perimeter was=20 defined could a plan be developed to address the mined area, or = in most=20 cases, the area reduction capacity would just continue demining = the=20 area. The focus at this time was to eliminate the whole mine = problem in=20 a particular area. Demining assets were tied down for long = periods of=20 time and other high priorities had to wait. A typical example of = this is=20 when mine detection dogs are automatically used for the area = reduction=20 and soon the handlers realize that the dogs are not effective = due to the=20 type of vegetation found in the area, which may have thorns or = grass=20 that pricks the noses of the dogs, causing them to lift their = heads off=20 the ground. This could have been prevented if a proper Technical = Survey=20 had been carried out.
In some cases, demining resources were used = in a manner=20 that did not suit them, and they were not able to perform to = their=20 optimum capacity. One of the strengths of demining lies in the = "Tool=20 Box" approach of using the best tool or combination of tools to = address=20 the problem. The size of some areas and the obstructed view of = the=20 suspect area often mislead demining organizations to use one = type of=20 tool, and during the execution of the task=97often too = late=97they realize=20 that the wrong resources have been used on that particular site. =
The exact area to be addressed was not known, = which led=20 to organizations being unable to estimate how long a particular = task=20 would take to complete.
To date there has been a focus on clearing = mines and=20 UXO instead of on making uncontaminated land available for use.=20 Technical Survey teams may be able to identify whether or not = land=20 contains mines. The mine-free land can often be made available = for=20 immediate use. The cost of making this land available will often = be much=20 less than that of mined land that requires intensive manual = clearance.=20
It was difficult to account for all the = different areas=20 handled in the process, because the initial area identified by = the Level=20 One Survey was an estimation and not an accurately defined area. = This=20 meant that the statistics collected through the process were not = always=20 accurate and some areas remained unaccounted for.

Some might argue that this approach to the = Technical=20 Survey is introducing another step to the process, but in = actuality, the=20 new application will increase output, limit wasted resources due = to=20 decreased down time, and most importantly, provide relief to = impacted=20 communities in a very focused manner. The procedure will actually = enhance=20 the process and provide mine action authorities more control over = demining=20 activities since it will be a calculated step-by-step = approach.

(page 1 | 2)

Publisher: MAIC =20 Contact: http://maic.jmu.edu/contact.asp<= /A> =20 3D"A

------=_NextPart_000_0000_01CAAA59.A3B5EAA0 Content-Type: image/jpeg Content-Transfer-Encoding: base64 Content-Location: http://maic.jmu.edu/journal/6.1/top/61.jpg /9j/4AAQSkZJRgABAgEASABIAAD/7Qv6UGhvdG9zaG9wIDMuMAA4QklNA+0AAAAAABAASAAAAAEA AQBIAAAAAQABOEJJTQQNAAAAAAAEAAAAeDhCSU0EGQAAAAAABAAAAB44QklNA/MAAAAAAAkAAAAA AAAAAAEAOEJJTQQKAAAAAAABAAA4QklNJxAAAAAAAAoAAQAAAAAAAAACOEJJTQP1AAAAAABIAC9m ZgABAGxmZgAGAAAAAAABAC9mZgABAKGZmgAGAAAAAAABADIAAAABAFoAAAAGAAAAAAABADUAAAAB AC0AAAAGAAAAAAABOEJJTQP4AAAAAABwAAD/////////////////////////////A+gAAAAA//// /////////////////////////wPoAAAAAP////////////////////////////8D6AAAAAD///// ////////////////////////A+gAADhCSU0ECAAAAAAAEAAAAAEAAAJAAAACQAAAAAA4QklNBB4A AAAAAAQAAAAAOEJJTQQaAAAAAABxAAAABgAAAAAAAAAAAAAApAAAApsAAAAIAHcAcABlADEANQA4 ADQANQAAAAEAAAAAAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAAAAAACmwAAAKQAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAOEJJTQQRAAAAAAABAQA4QklNBBQAAAAAAAQAAAAOOEJJTQQM AAAAAAlZAAAAAQAAAHAAAAAcAAABUAAAJMAAAAk9ABgAAf/Y/+AAEEpGSUYAAQIBAEgASAAA/+4A DkFkb2JlAGSAAAAAAf/bAIQADAgICAkIDAkJDBELCgsRFQ8MDA8VGBMTFRMTGBEMDAwMDAwRDAwM DAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAENCwsNDg0QDg4QFA4ODhQUDg4ODhQRDAwMDAwREQwM DAwMDBEMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwM/8AAEQgAHABwAwEiAAIRAQMRAf/dAAQA B//EAT8AAAEFAQEBAQEBAAAAAAAAAAMAAQIEBQYHCAkKCwEAAQUBAQEBAQEAAAAAAAAAAQACAwQF BgcICQoLEAABBAEDAgQCBQcGCAUDDDMBAAIRAwQhEjEFQVFhEyJxgTIGFJGhsUIjJBVSwWIzNHKC 0UMHJZJT8OHxY3M1FqKygyZEk1RkRcKjdDYX0lXiZfKzhMPTdePzRieUpIW0lcTU5PSltcXV5fVW ZnaGlqa2xtbm9jdHV2d3h5ent8fX5/cRAAICAQIEBAMEBQYHBwYFNQEAAhEDITESBEFRYXEiEwUy gZEUobFCI8FS0fAzJGLhcoKSQ1MVY3M08SUGFqKygwcmNcLSRJNUoxdkRVU2dGXi8rOEw9N14/NG lKSFtJXE1OT0pbXF1eX1VmZ2hpamtsbW5vYnN0dXZ3eHl6e3x//aAAwDAQACEQMRAD8A124lL6aG iquHV1yQxk/QaT+aiWY2K011OprBsJawem3Ugb9v0f3GqeOSKaAfaPTrjg6bRLv5Kr9e6njYPS77 rgfUq2mojQtslvpWbv5G79J+/Xvq/PVHUmu5dTpdbBdtGPZdZWKav0W1r2hjdC4F2wgM/c9N/wDb T/ZMdnFVcDsGM/6mFn9LzKOoUWfpAHZdzrcto9r/AEwGY+PjU7HWbW+myv18lz2W+l/g67bfVq2z UxpDmtAJPYRwP/MUpAxNFAoi3jmfsVlmc3Oo3WvvsbTYxoIY02WMsfsDqm76v5ypv5/819BRFH1a mTbkhusRj1HTe/bq61v/AGn9L/r3q/4NEpz6sDquRkvo9d4vuaGPcAwsfZbXkVvr2Pc591Tn1fS9 m/6D1Yt6vTVmepl9NP7QYavXfba71C+p1d24Mez9W3tpbT+jZ+hxv0a6zEJe3joSN44HSUP3I/oz /ReVymJyZLMdMkx8sv3pfpR/SaDa+h/Z8ljm2m91jfsdwrZAr/O9erd9P97b/wBb9P3oOYMF+U92 JSK8fQVtc0boa1rXPdJs2usf+l2b/ZvV+/O6cDbVk9J25O3bZY+61twt9/q3vYQKvUc9zH+j6Pps TZFlWZjZA6Z0x+NW1zLbn1ufeK21tsjdY9m+v6brnv8AU/wf/BqWOhsxlr1lKHB+j/WYpCxXFHT9 2MuP9L+q5W2r91n+aP7k/p1/uN/zR/ct/K+tTMq1txwa2XsLvTyGPJtg1249W+6xlj7dnqUPd/p/ s3+if6ddDIzek2VvZj9NbjPcAGO9eyws2knc0Wfv/n7/AMz/ALcToyma4sRj5GElkoQF8OW/MSDn +nX+43/NH9yWysaljf8ANH9yknadrg4jcAQdvjH5qkodmIE3qW39g6ViCs9ZyW4JuaHV1Covs2l2 w2PZXXY5tbPf+Z+k/m6rf5z0x9S6V9jqZa015GLkVudj5VbfY8BoLthI/N3/AL3/AIIy2uu59Yar rLxn1dOZ1enMa1zcpod6rfZ6PpWUVPtbXU1te+hzWenXf/OWepVZUo9T9fG6RX069rcd25+V9jYW uZT6jCPTZYyPZ+cz/r36W6z1L7qGLNOU42b4r4oen0/3f0/R/XdXPy2GOIkCjEXGV7/+jP8A/9Do cWXYlI1EVV6BpJ+iNn0m7W+39JtVTI6dXmvv2OreCRXl49jfVrc4Na6bGNd6lF7WO+myz+b2fzi6 HF+xfZcfd9gn06/pRunY1Eb+zoG39nR+bG35RCqGMNfX+BdGM8laYz/jRea6d0LpvTLg7GxqqbHg gFpeefc9rPV91bfZvV5znuDY95dB9vED8/Vyt5vpb2+h9l2Q3f6P2bb9Ic/a/d9Hd9H/AAX/AAqG +Ps9e37N625n0Ps+6PTb6+/f+r+l627f6f8AhvoIcMb1nr/WEr/5yOOdaY9PCUaczp/1W6pYx+bi XYjHZN78hltlLn3M99n6Flk7Gt192xn0/oK076q9fe59j8nBdZa17bbBjva54teLbvUdW5m/1Nvp e7/Afolfx/tH2XT0o22+n6fpc72+l6fpfoP9L/4J66hj/tWafW2x6g9Xd9m+hPv9T0/zf9H6P+D/ AJa2ofe+GNCPyx4b9ri4OH0/N6nGn934pb/NK/mriv1NP/mp1r1BYX9MP0iWuwy4Eud6jnv3e9z/ ANx272Kn/wAy+o4OHN+VhvxcR7sv9NVa5rSGtFznNa9vq1uqpZvqs9RbeV+0N4+zx9Bs7PQ2bp93 9J/Sbtv87/0P0ibq32n7O70dmyH+t6Gydmwbt3rf9c/m/wBJ6v8ANp4PPVoI/T2v5fvLSOVvU/8A TcXD6VffRXmYmf0pjXkvruFDqrJt34/5z6rmb3ZG2qv/AEnoekp2fVvNsAxzmdLNeS5lYx66SGuf WbLK3NbQ8Oba1lOTXv8A9B9oqR2/sHYz7L+zPXkbv6L6/p+lV9s9f/B/Q/pP/wADqth/YJr/AGX9 h+1e/f6X7O9TZsu59H87f63qf+hH+C3oXzt7RvT/ADP+D/zlVy1b6f4TQ6r9XWusy+p5nV8GsNtZ 9rfW15ZW+/Z6Zs2us9Ft3q1v3v8A0f6RPR9R7MiTR1XEsAIAIDoduDSw1mf0rH+oza+v2Laq/ZP7 Nu+yfs/7N6lW+Ps2z1J/R/S/VP6F9m9P/gP6N+lUOn/sL7aPW/Zfr+m2N32Pdulnp+n9k/WfpfzP /qpSxPxKhwgVWn8zsxSHIcR4j6r1+dy2/VPKxMr7AzrePRkWsdcaQXt9lZY2yx43bWbXWt+n7/8A tuxCf9SbraX2N6pjWOe15aIfufDXasDnb7Poe17V1dn/ADdl3qfsed9m/d6c+pLvtO6f8Jv9T7R/ 1z1UC7/m16dnpfsf7R7/AEvT9L1fW22R6W39J6+71Pofpf5xC/iFmhHi/Sr2OL6riOT4RZPD+jfu 8P0f/9kAOEJJTQQhAAAAAABVAAAAAQEAAAAPAEEAZABvAGIAZQAgAFAAaABvAHQAbwBzAGgAbwBw AAAAEwBBAGQAbwBiAGUAIABQAGgAbwB0AG8AcwBoAG8AcAAgADYALgAwAAAAAQA4QklNBAYAAAAA AAcABAAAAAEBAP/uAA5BZG9iZQBkAAAAAAH/2wCEAAYEBAQFBAYFBQYJBgUGCQsIBgYICwwKCgsK CgwQDAwMDAwMEAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwBBwcHDQwNGBAQGBQODg4UFA4O Dg4UEQwMDAwMEREMDAwMDAwRDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDP/AABEIAKQCmwMB EQACEQEDEQH/3QAEAFT/xAGiAAAABwEBAQEBAAAAAAAAAAAEBQMCBgEABwgJCgsBAAICAwEBAQEB AAAAAAAAAAEAAgMEBQYHCAkKCxAAAgEDAwIEAgYHAwQCBgJzAQIDEQQABSESMUFRBhNhInGBFDKR oQcVsUIjwVLR4TMWYvAkcoLxJUM0U5KismNzwjVEJ5OjszYXVGR0w9LiCCaDCQoYGYSURUaktFbT VSga8uPzxNTk9GV1hZWltcXV5fVmdoaWprbG1ub2N0dXZ3eHl6e3x9fn9zhIWGh4iJiouMjY6Pgp OUlZaXmJmam5ydnp+So6SlpqeoqaqrrK2ur6EQACAgECAwUFBAUGBAgDA20BAAIRAwQhEjFBBVET YSIGcYGRMqGx8BTB0eEjQhVSYnLxMyQ0Q4IWklMlomOywgdz0jXiRIMXVJMICQoYGSY2RRonZHRV N/Kjs8MoKdPj84SUpLTE1OT0ZXWFlaW1xdXl9UZWZnaGlqa2xtbm9kdXZ3eHl6e3x9fn9zhIWGh4 iJiouMjY6Pg5SVlpeYmZqbnJ2en5KjpKWmp6ipqqusra6vr/2gAMAwEAAhEDEQA/ABfkfyJ5JuPJ OgXd1oNhc3FzYW8s0r28buzNGCzMzDck5q8uWQkd3dYMMDAbBNZfy/8AIKDfy3po/wCjWL+mQ8Wf eW4YIfzQsk8geQBGX/w7p1O3+jRf0weNPvXwIfzYoePyR5DdWK+W9P26f6NF/THxpd5T+Xh/NipT eRPI3AFvL+nrXwtox/DCM0u8r+Xh/Nio3HkryLHGqx+X9PZm8beP+mPjSvmkafH/ADYom0/LzySK NLoGnknehtozt92CWed80HBj/mxRi+Qfy/L7eXdNI/l+qxf0wePPvY/l4fzYrj5A8glWI8t6aKdP 9Fi/pj40+8r+Xh3RUh5C8ghany7p1f8AmFi/pj48+9JwY/5sUKfJHkYS+l/hzT9+/wBWi/ph8aXe n8vDui5vInkJZKf4dsCfD6vHT9WDx596/l4fzYq0fkDyKx5Hy7py9qfVov6YPHn3lfAh/NiqP5A8 hAgf4d04e/1aL+mS8efex8CH82K3/AHkHp/h/Tif+YaL+mPjT7ykYMf82K3/AAT+XcNTN5e07fYD 6tF/TEZp95U6fGegU5fI3kS4BS28vacknvbRdPuyXjT70fl4DoFGTyD5Kh2l0DTy5Ha3j/pj40u9 PgY/5sVKP8t/KNxGwGiWCD+cW8Y/hj40u9PgYv5sVSD8vvJnEw/oHTyy/wC7Dbxn+GA5pd6+Bj/m xRX+A/y/ggCzeX7FpK/a+rRd/ox8aXej8vA9Irz5B8hqik+XtNo32f8ARoq/qweNPvY/l4dwWx+S Py+kl9JfLen1HU/Vov6YfFn3p/Lw7oqdx5E8iRyKD5f04cjQD6tF/TD4s+9HgQ/mxYb+Z/lTytY3 Ogx2ejWdqJpLr1xDCiCQJCpUMAN+JNc33s9HxNRwz9UeE9HQ+0P7vT8UPRLi/hYmdA0I/wDSut6d v3S/0zu/yGAfwQ/0rwx1ub+fP/TNf4f0L/q3W/8AyKX+mP5DB/Mh/pV/O5v58v8ATO/w/oX/AFbr f/kUv9MfyGD+ZD/Sr+dzfz5f6Z3+H9C/6t1v/wAil/pj+QwfzIf6Vfzub+fL/TO/w/oX/Vut/wDk Uv8ATH8hg/mQ/wBKv53N/Pl/pnf4f0L/AKt1v/yKX+mP5DB/Mh/pV/O5v58v9M7/AA/oX/Vut/8A kUv9MfyGD+ZD/Sr+dzfz5f6Z3+H9C/6t1v8A8il/pj+QwfzIf6Vfzub+fL/TO/w/oX/Vut/+RS/0 x/IYP5kP9Kv53N/Pl/pnf4f0L/q3W/8AyKX+mP5DB/Mh/pV/O5v58v8ATO/w/oX/AFbrf/kUv9Mf yGD+ZD/Sr+dzfz5f6Z3+H9C/6t1v/wAil/pj+QwfzIf6Vfzub+fL/TO/w/oX/Vut/wDkUv8ATH8h g/mQ/wBKv53N/Pl/pnf4f0L/AKt1v/yKX+mP5DB/Mh/pV/O5v58v9M7/AA/oX/Vut/8AkUv9MfyG D+ZD/Sr+dzfz5f6Z3+H9C/6t1v8A8il/pj+QwfzIf6Vfzub+fL/TO/w/oX/Vut/+RS/0x/IYP5kP 9Kv53N/Pl/pnf4f0L/q3W/8AyKX+mP5DB/Mh/pUfnc38+X+md/h/Qv8Aq3W//Ipf6Y/kMH8yH+lT +dzfz5f6Z3+H9C/6t1v/AMil/pj+QwfzIf6Vfzub+fL/AEzv8P6F/wBW63/5FL/TH8hg/mQ/0q/n c38+X+md/h/Qv+rdb/8AIpf6Y/kMH8yH+lX87m/ny/0zv8P6F/1brf8A5FL/AEx/IYP5kP8ASr+d zfz5f6Z3+H9C/wCrdb/8il/pj+QwfzIf6Vfzub+fL/TO/wAP6F/1brf/AJFL/TH8hg/mQ/0q/nc3 8+X+md/h/Qv+rdb/APIpf6Y/kMH8yH+lX87m/ny/0zv8P6F/1brf/kUv9MfyGD+ZD/Sr+dzfz5f6 Z3+H9C/6t1v/AMil/pj+QwfzIf6Vfzub+fL/AEzv8P6F/wBW63/5FL/TH8hg/mQ/0q/nc38+X+md /h/Qv+rdb/8AIpf6Y/kMH8yH+lX87m/ny/0zv8P6F/1brf8A5FL/AEx/IYP5kP8ASr+dzfz5f6Z3 +H9C/wCrdb/8il/pj+QwfzIf6Vfzub+fL/TO/wAP6F/1brf/AJFL/TH8hg/mQ/0q/nc38+X+md/h /Qv+rdb/APIpf6Y/kMH8yH+lX87m/ny/0zv8P6F/1brf/kUv9MfyGD+ZD/Sr+dzfz5f6Z3+H9C/6 t1v/AMil/pj+QwfzIf6Vfzub+fL/AEzv8P6F/wBW63/5FL/TH8hg/mQ/0q/nc38+X+md/h/Qv+rd b/8AIpf6Y/kMH8yH+lX87m/ny/0zv8P6F/1brf8A5FL/AEx/IYP5kP8ASr+dzfz5f6Z3+H9C/wCr db/8il/pj+QwfzIf6Vfzub+fL/TO/wAP6F/1brf/AJFL/TH8hg/mQ/0q/nc38+X+md/h/Qv+rdb/ APIpf6Y/kMH8yH+lX87m/ny/0zv8P6F/1brf/kUv9MfyGD+ZD/Sr+dzfz5f6Z3+H9C/6t1v/AMil /pj+QwfzIf6Vfzub+fL/AEzv8P6F/wBW63/5FL/TH8hg/mQ/0q/nc38+X+md/h/Qv+rdb/8AIpf6 Y/kMH8yH+lX87m/ny/0zv8P6F/1brf8A5FL/AEx/IYP5kP8ASr+dzfz5f6Z3+H9C/wCrdb/8il/p j+QwfzIf6Vfzub+fL/TO/wAP6F/1brf/AJFL/TH8hg/mQ/0q/nc38+X+md/h/Qv+rdb/APIpf6Y/ kMH8yH+lX87m/ny/0zv8P6F/1brf/kUv9MfyGD+ZD/Sr+dzfz5f6Z3+H9C/6t1v/AMil/pj+Qwfz If6Vfzub+fL/AEzv8P6F/wBW63/5FL/TH8hg/mQ/0q/nc38+X+md/h/Qv+rdb/8AIpf6Y/kMH8yH +lX87m/ny/0zv8P6F/1brf8A5FL/AEx/IYP5kP8ASr+dzfz5f6Z3+H9C/wCrdb/8il/pj+QwfzIf 6Vfzub+fL/TO/wAP6F/1brf/AJFL/TH8hg/mQ/0q/nc38+X+md/h/Qv+rdb/APIpf6Y/kMH8yH+l X87m/ny/0yTfojSv0jw+pw8P0n6XHgKen9S58P8AV5/FT+bNb+VxeJXDGvH4fp/h/L8XD/pnP/NZ fDvil/c8XP8Ai8fh4v8ASv8A/9CUfl4K/l75bUn/AKVttQ/88hmnz/UXf4P7uP8AVTWeMhaP2Oxy st4UXkgbjFyHL+XFVG4uEt3VAv2h0pgpkAhr2URwGRlr3AwhKyxtRdcLhtqH4VOFjaal/TYADc5A o5hfFFxYupqT2xtiS4SM5dQKEYUkKTJI+3QjEpBa9DbkRv8AzYLQtEQDjuD3xtkDsiHjQAeGAsbQ ks/JuAFB45OkrVhUtz5HkO2Koea1a6uF9ZuCpuoGPFShHR20aMGX7eNoK2SFZJgzNRh2wqeS2QSJ SNCFqd/lioUjJEnJYmrNXfEJW35K261HJjSuAc1AaS1YlXeQ07Lkii0WtvxI4bY2hRu4YRSW6fgq kcKeOIKQwT81phJeeXAu/wAd5Rv+eK50fst/jf8AmSea9qB/gv8Anhh/udzTPRA+esy8h+QYdfhv NV1a9Gl+XdPoLu9O7Mx/YSuw+dG/1c12u1/gkQjHjyS+lz9HoxlHFI8MIsr/AEZ/zj/EnCS+uiyD d5PUVm/yqBAPuGa85e0O6LmjHou+SY+f/wAtfy/8veTLjWLWKf6y6olmHkb7c32TxIH2R8WVaDtL UZc4hKuEfV/mtmt0GDHiM43f8LxIAk0A96d/fOm5bvPhr5d++IKG/HbbrsKmg+WN1zSBfJrD70Ox V2KuxV2KuxVMtA8v6r5g1SLTNKgNxdymtNgqoP23b9lRlGo1EMMeKZb8OCeWXDFnPmnyX5M8k6St tq8smq+aLlOUdvE/pQxDpyanxcQfFv3n+Tmq02tzarJ+7HBhj/pnY6jSYtPjqR4speaD5j55uw6g oixitpb2CO6l9C2eRRPNSvCMsAzU+WQyEiJ4fqZYwDIX9L3Rvyn/ACzvvKc+t6fJcJbi2kngvGc0 ogPxlWAqKjOWHaupjmEJV9T0cuzdOcRnEmqeCHqadK7Z1geaLWFDsVdirsVdirsVdirsVdirsVdi rsVdirsVdirsVdirsVdirsVdirsVdirsVdirsVdirsVdirsVdirtu/34Fdt2xV2FXYq7FXYq7FXY qkX/AEs/+3t/3b81X+V/62P+xZ2X+T/5If8AYw//0ZT+X5jX8vfLRJ2/Rlr9/pDNRm+ou+wf3cfc nZQN8RNV7DKm9LbmxjFyJ12YnfFkFS4ijJBO5UbHAUAJWEkuLjg5qgPTCypOlt1jjHD4QBsBkbYr U5sASu52wJ5K9vCyKxc9emLErxEgAbYE9ThVSuK8l9P6aYEgKbmTmSPseGKQ1GXJO1B2xQV0want hQpBE4/ZrTvhspCXnUbV9XSxSUCcDk0Y6kZIRNWVKYXhWEg8eVemRULVjMxEwYinbG6VtafEzbt0 Bx4lU4Ld/VM83+xU4bVzWUXxThN61OC1VFVXj5OK+xwUq62ntn5R1HMbgHDZQQperK6utd+ithCo a4gmeFIbgeovKpb2ySsH/NL0RceXREKKst6DX2gTOj9lv8b/AMyTzftR/iv+eGIjp456J0fPA9S/ Kzzj5PtNHfQPM4KW63n1+2ldS8DvwCcJVUNsrDko48eX2s0PamizSn4mLnKPA7ns7V4hDgycgeNk /m+88medfM3lzRdDEd5eLdrLe3UcZRVtYkLSwsxC8uVFp+yuYWjjn02Oc8mw4fTH+m5eqnh1E4Qh ueL/AGKXf85F66rTaXoMJASMNdTcTv0McYI/1eRy72ewbSyH+q1dt5d4wHRH/kb5NtI9LutT1KyU ald1+qLcAE/UyABII23CSPyXmR8XH4cp7c1hMxGJ9Mfq4f8AVG3sjSjgMpDeX0/1Xius2U9jqt7Z 3CBLi3nkjlUbKGRiDQb/AA/y51GGQnASBuw89lxmEjE7UXuP5JeSbOLy/c3+oWSjWL4MLdbkBqWr LSNvTPxKkjcv9dVzle2tbI5BGJ/dw/mfzv8Ajr0fZWkAxmUh65fTxfzXi9voGoXnmgaGsYjvJbs2 xWmykyUOw7KPi/1c6U5xHF4n8IjxOg8Eyy8HW2ca/wDkuul65o2jQaubu81aZkK+gE9GCMVkmP7x uQX/AGOavTdsnJjnMxoYx/O/2PJ2OfsoQlGIlcp+SX+cfysbRNf0zQdNvzqmpamKiIwiARpUqHLc 5NiVbLdJ2r4uOWSUeCEP85q1XZpxzjCJ4pS/zU7/AOVHaXa3ljpeq+aEtta1BS1tZw2jzBgoqxDc 1oBQ/E4TMf8AluZjKccfFjh/FxcDkfyREERlPhnL+Hh4mE+e/Jl35R1oaZcTpciSMTwzJUVRiV+J T9lqqc2eh1o1EOIDhdbrNJLBPhJtjgzMLivoj8gdGs7Tyg+soo+vX88qu9ByEcLFFUHwqpbOQ9oM 0pZvD/hg9X2PhEcXF/EUk/KtvKfmvWdZ1LzKsdzrt5cEwWt0fs25UFViUkcirckp8XFEXMntQ5sE IxxenEBvKP8AO/pOL2cMWaUjk9WS/pl/vWI/nP5T0fy55rSLSkENreW63P1etRGzMynjXfgeFd82 HY2rlmxEz5xPDbg9qaaOLIBHkQwaztpby6htbf4pbmRYYxsfikYKo+knNpKXDEyPJ18Y8RAfQf5s XcHlf8r4dDtG9Iz+jYR+JjQcpK/NVIb/AFs5DsqJz6o5Jb1c3p+0SMWmEB/VfO36++dk8q7FXYq7 FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7t/n0xVqaWCC P1J5BFGdgzbVPgo3Zj/kqrNkJSEdyW7Fp55DUQnWjeSfOWtRCax0tre0YgC91FhaxmvQqp5yN/q8 VzW5u1ccduruMXYpO8iyUfk3qsFpJe6v5hsrC2gUvPLFbORGo6lmkf8Ahmvl2vImgHYx7Jwx5hEa l+TH1CxN9cecLa3thQrPfW4SI8/sgFJFrX9mmRh2xO64TKky7KwHpSVXP5R+eRbC90wWPmGzdecc unTCN2Qd445TST/kbmTj7aiNsgMS4mXsSJ+ksPkEkN61hdQy2eoJs9jcxmGb6FbZ/wDnmz5tcOph kFgun1HZ+TFzGzqEZkOFs1hV2KuxVIv+ln/29v8Au35qv8r/ANbH/Ys7L/J/8kP+xh//0pL5A4H8 vvLakVrptrv/AM8hmpzfUXfYP7uPuZBJGwjr0UZU32gp1MsbBQSxFFPviUhBxfWIbcpNuwrgkzC7 SrVmlLjcEb4rJNSyGinqOmRLHoqKAGJpQdsCOihOS3w+/bCgBoseIiIPLx+eLKlIuq/AG+LucATS 5GflxYde2FBWXiziINAORHUYFUIzOi8JPtvvTwwpoL4HP1mO33NSS33YeiAxby1bC8/MDVbtQCkC emp8CDl0zWMNd7ssmsWL8+ZI75SztfaQCLcvyTvgtSiJI4ieKipO+BAQ7TiV/qvGjp1OLLhbQyBT Ex6dMKKUWHwPz/brQDFTzUYo7cgcAS6/bOG0r/UWNCG2UdMLEhTuNQiXgq1YkjamFaYB+acT/XdA lJ+B5L3ivh+4TOk9lv8AG/8AMk857U/4r/nhiexP8Poz0To+dhlfkbVfIemyXUvmnS59VaQKttFG EaNB+2WDPGeZ2o2YGuxaiZAxSGMOdosuGFnIDIsv0X8w/wAqvL+oS6poeg6hDfNC0UcTmL0viIPX 1HKnanLj9nNfn7O1eaIhOcOG/Pi+5zsWu02KRnGMuJh8vnK21XzwvmLzLYi+s2f95Yx0osaiiKta B+Hgx+LM/wDJGGDw8R4JfznBOrE83iTFh6Bo/wCbP5YaRqE+oadomoW1zdRrDKEETJwRiwCqZ6Lu f2Rmqy9k6rJERlOBiDxdf+Idnj7T00JcUYyB/H9Jjl/5v/K268w/pttC1G9nmnaa7ju5ovT+Kv2Y 1Zg9D9lGKZmQ0Wr8Lw+PHGMRw+n6nElqtN4nHwyJPqkyXRPze/LLRb64vtN0TULe4ukWOUARFQqE kcVachev2RmFl7H1OSIjKcCB7/8AiXMx9p6eEjKMZWfx/OSaz/ML8uNP82DzJZ6RqdxfyvJJPPcy xDg0ikExxBmDt+z8TLxzIn2fqp4vDM8YiP5vE0R12nhk4xGRl/S4U4k/OjyO3miPXzpGotcx27Wy yO8R9NCeREcPLj8R+03qZjjsXP4Xh8UOG+L+Ju/lXD4nHUrrhSzV/wA1PJj+ZR5r0/StQm19eKoL qWOO2CBQhASNpT9ntmRg7Lz+GcMpQ8P+iPV/vWnL2jh4/EiJcf8AS+lfrX5m/l5rurQa1f2Ws2er QQiBJbGSJFVQSfhJkU9Wb9nI4OzdTiiYRljML/ygXJrsGUicxkE/6BY15n1v8uNQtp57O11m51mQ BY7m/uEKrToSQ8han8uZumwaqBAJxCH9CP8A0i4uozaeQseIZ/02E0+nNpKrp1zP/wAt/wA1bryj G9hc25vNJlk9XirASxsRRilaKa0+yc1HafZQ1B4ompOz0HaRwDhIuKep+YP5Tabq8mv6XoF1JrDk vGJPTSKORurD42EZav7KtmGez9XOAxynHgcoa7TQnxxjLief6/5pvvMHmMazq6iUmSMtar9gQRtX 0VJ7cf8Ahs3OHSDFi8OHd9X9P+c6rLqTkyccmaan+YfkO485aHrVto01vZ6UrmeKKOJZJJCB6Qpy C0hYV5V+LNXj7P1EcU4GYMsn9Z2OTW4TkhIRIGNKfzU/MO384X1lJYwz29lZxuBFccAzSOQS1EZx 0Wn2syOy+z5aaMuIjik0dpa0Z5Dh5RYLm2dYXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7F XYq7FXYq7FXYq7FXYq7FXYq7FXYq7/PfBzVWsLHUdS1KLSdKgN1qU45BDtHDGOs07fsRj/hsxdXq o4xvzdnoOz5ZjZ+l6BBoXlbyPY22sXgbW9Uvme2i14Ri4trW6p8KpCtaR89q/aznZ5smeVfSP5v8 T0+PFHGKip3uu3fmK38u+ZBFNcXWnXEmm69pkUUsoinpyiuFthxY14/By+zywRxiJMSfT9UZNl3u 9B81+XtV81+XbTS4UFrBfSRNrC3fwyLboeTRsi1PNyq8h+zmDhyjHOzuyItLG8k+c7fTvKpurS28 wSeWJ51OntII1uraRClvMTKOHrQg1o+WfmIkyo8An/EjhOyZeY/LH6W8weUdGtbKfQ7S1jn1HUL6 ycw/VUHxfVVmj/d/HIW5/wCr8OVYcvDCUieM/TGMv41kLNIXUNb8lea9F1S785R2y+T4rj6h5b1G Tkb+4kgHCeeFkq5/eg8DEP2Pi5ZOOPJjkBj/ALz6pj+BJAIovKPOPku58sxW+qW15+mPJ99Qafrq 7tHyNFhu+I2IPwian+S/Bs6DQdpcfomOGYdF2h2YCOKDHypBodvH2Gbm9redIo0WsKHYqkX/AEs/ +3t/3b81X+V/62P+xZ2X+T/5If8AYw//05R+XQC+QPLZIqDptr1/4xDNTm+ou/wj93H+qnss3H7W 6HoMqbaUuUZchdqCtMNsqQpjEoen3nIMgaVdM2JAFNjU4CpRYg/ehz26DAxVXidyWHQdsIVYsQ9Q Eiowq1dw8kdlND+OKsG8wecBoHmXTdJuoD9V1KMOt7X4Vcn7Jy3Hi4gssnCaPJmC+lWiNzfahHvl RNJN9VVZQqsApLj7WRpCwRFv3lN/64VJSO+826Tpvmm00CaNjf3ysYXHTZSd8shhMomSDMAgJT+X nNrrX7+nwLctHTxIyzNGgAxgbLL4JJZvi+xG21D3yglnVLGW7HOHhxTqHwKCrWxkmjotAyilT7YF kGmMENGkB9V9jTrioWK8E5MYUpJ2JwgIOyrHAtvbF5iG4/tYUc+SmnoiPlGu0ncd8aZWhp2iicer upO3hhQpz2nK8D1UQgAgYbUFgf5qSI9z5dCbqst6Af8AngmdJ7Lf43/mSec9qf8AFf8APDED0Hv1 z0QPnTVcKl1cFIdhTbsCt1ONBbarjSHf5nGk27GgtuxoLbv1Y0h2NJdhGyt18MFLbqnb26YVa7f5 /dgTbq4UW7AtuxV2FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7 FXYq7FWnM9US2iNxdzyLDaW/eSZ9lX5d2/ycoz5RCBLl6LTnLMDo9IjudP8Ayz0Y21pLbaj5lZ45 9egnk9KedJNv9HY7cIjso+zxzmJmWolZ2j/C9jEDGOGKb+X/ACzFrDaksNtLYeVtWqdZ0S8UxyW9 8lJFurKT7PB68mYfDlWXLw1f1j6ZR/3LIBAebPz30LQJpLDyxbpq+pxKsNxqLmkNY141ZhvM4/ay eHs+c95mgsp1yeW6n+cn5l6jIWbW3tY6njDaKsSCvy3zPhosUelsDIoW0/NP8ybR+dv5kvK1rxkb mp8ag5I6TEf4QjiPe9E8o/8AOT2vWzLZ+brKPVNPk+Ca8tVEc6q2zFo9lk/yhmDm7Kid4emTMZT1 eovpVj5lg8veavy4udOkj0eGe2srO5VxaRfWKcn4RfHFcRU+zT4uTZrhM4+KGUH1HnH6mdXuGP6B 5r8saNb/AODLxUv/AC20d7L5l8x3ymK2uLhn/ex2sf7f751T4PhX9j4/iy3JhnL94DU/4IR/m/0k bDZ5n508oTeUNf8A0UHafSLuM3OgXrb+pbAcmiY/78g5D/Wj+LOi7K1oyxo/UHne1tFwnxIpHm3d E7FUi/6Wf/b2/wC7fmq/yv8A1sf9izsv8n/yQ/7GH//UP/Il9a23kHyz9YlCK2m2oFf+MQzU5vqL 0GAXjj/VZOWVlWm6EAq3scqbGlt04mSm52OBlamVRBxUdcCWrSiNQd+2BSUxNOHIYSxaPMMoXYHq MCqVz66RkxrycdBjaRTUCTzQJJIOEn7a4Flsxrz55Q0/zBosqzVTUrQevZMlAarvTLcUzE2iceJR /LPzPbeYtC9Q0GpW37q7jApQIeOTz46NsYzsbsskjiiPInd9h75QzpTkkjVeNehGw+eBBDxv8wLl 7X83tIuFAb6vE7Bz7xnM3CP3ZDRk/vAyz8oYryXy5qF+TVLi+kLKR1+WQ1FAhsx8mXIly8gkaPjG vQDMdtPJtrxCzCST4q0EZw0gAqcs1jZ241W9uBawBvTAY0Uk7D8cYxJOyzXS3yFhMY+UZHKNgNiK VBxIpNICXzA7hmsLcSSr1qMK0us7i4vIPUvWEaNUGIbUOEhHLkvubu5s7JZYYgyA0UHwxWlWSL61 ZqStHahI8DiQx5FoRyGX0XXZRQN44Al5z+alqbe/8vkH4He9IXwPornR+yv+N/5knm/aj/Ff8+LE znor527CrsVDIfLnkHzV5js7i80iz9e3tdpGLBKsBXilftHMPU67FhkIyO5crBo8mQGURsEgeN43 ZJFKOpKshFGBBpQjMsG9w4xjRpltt+U3n250gapFphMDKHSEsomZSKgiM77jNdLtbTiXDxb/AOxc 6PZmYx4gGJMjo5RxxdSVZT1DDYg5sQbcEiluFDtsC06h+7HdUdBoes3Fm17BYzzWafbuEjZkH00y qWoxxPCZDibRgmRdbIGmXNTsVdirsVdirsVdirsVd2r2xV1R2NR44qXYhWQ+WvIPmrzLbTXOkWfr wQP6buzBBypWi1+1TvTMPUa/DhPDOVFy8GiyZRcRYTdvyX/MRVLHTlIAJ2mjJNPDfMYds6f+c3fy Vn/msKnhlgmkhmUxyxMUkVuqspoQfkc2gNixydeY0aK2n9MUU4gj6emFUXp+j6tqTMun2c12yCri FC1B70yrLmhj+oiLZDDKfIWhZI5I5GjkQxyISGRgVII7EHplgIIsMDEg0VuFDsVdirsVdirsVdir sVdirsVdirsVdirsVdirsVd88VZt+Umhx3nmK91y4oLXQo/Rt2fZRczLWVz7xJVc53tfObEQ9Z2T pxDHxdSz/UvL3lrztDYajYXcNxLp09IL2NUnQof723lRwVZX9/s5qY5J4SQeRdpQLBvzz/MSS0A8 laG/oIsajVJYzQpHSsdsn8o4/ap/q5maDT365MJS6PDQAAABQL9nwGbSg1OG+FLdNvnirjue2Kss /LP8x9T8ieYk1KEmXS7grHq9kPsyRV/vEHaWPqGzG1eljmj/AEkxkQ+s5/K/k7XNWsPPN3S9FpZ8 9OeYg20URHqmZYyP7ylDyP2c5uOXJEHGNrLfQO7EPzMl8ufmJ+W93rXlu7TUbny/M13azRcgfUhB M0RDBTSWHmv+VmXopSwZgJenia80BONPBOUbossZrG4DKR3B3rnbRlYt4bLjMJGJdk2pIv8ApZ/9 vb/u35qv8r/1sf8AYs7P/J/8kP8AsYf/1ZB+XsFjeeRPLkEsPNo9OtSeQ2/uhmpzfUXocBrHH+qy h+NAEHwIKAewyqmwLY39Qcxso2oOmJWltAzU75FlS8ABthuOuAqrxsO/QdsKCFZTy3HUdMCKbQOX PY9sUUpupVwCTybw6DGmSlLZqbkSt8TgEDwocQFt5reWsPkT8xF1eL9xoeuL9XkjXaNJSa1PhmVC XHGj9TVKNG+jL2LXGoPOZeVup5QUNVII7UzHls5ACMsfTeJxIP3zvQDviGMg8U8/s0v5ow29assZ XmT0qpGZ2Eehx8n1h6v5Btf0b5Zgs+YkkMhcgdNxmPqPqZ4xsn5Nwhfm/FXFFHYHMdsoIK8t7Cxs 3vL2RVhj/eTTuaBfapw79FEnlwg1H80fOy3cDSw+SNLKFkqRFLJCamlPtVIzMsY4/wBJxTEzlYPp D11ri2ki/dQhII/ghSmwA2zDlMkuUBSVWdhJFcycFChm5VIoKY2yJbuII5JJYJIyoiX1FcA0PtiD SVmkWt1Jza+Ym2P9zG3QYbYyNI1oCVMPIIv7BB3IxY9HXBeNwiipUbnucFoDzf8ANaQPceXq15Ca 9rUf8u6Z0vst/jf+ZJ5z2oH+C/58WHZ6M+duxVwxpX1v+W2hLoHlLTtNcCO5EImukJ39WT4pP+BL cc8+7Qz+NmlPpfC9xosIxYhF5CfI6XX553enyIGsknOpTLQ8TG9JlXbxZwudD+d4dAJA+r+7/wA5 0f5Ti1nD/DfGz3VPz08l2Et9ZGO5lu7OWSHikalZHjJU8X5fZ5CnKmanF2HnnwkVU3Z5O18MCRvY fOeqX76hqd3fugia7medox0UyMWpXv1zs8eMwiB/NAi8nklxSJ/nFDEeO2SLCmV/lv5IufN2vJaA OmnQfHfXUdPhUfsqxBAdv2a8swO0dcNPjsfX/C52h0ZzTo/T/Elfm/TtK0zzLf6fpcksljaTNArz MrOxj+F/iQKKcw3EgfZy/R5JzxxlPaUmrVQjDJKMeUX0L5U/Mb8v4/KFmf0hDaG1t445rRwVdGRQ GXiAeVTvt9rOP1PZupOY7GVy+p6fTa/B4Q3AoPnLX7uyvNc1C7sYzDZz3EksER/ZRmJH3+H7Odlp 4yjARlvKI9TyueQlMkbAoCh/ty4kBpaphV1KfR1xOy06nT3x3V1N6d+uBW6GtMVdQ0r9OHdXof5I eWYNZ82tNeQJcWFhA0kiyLyT1JPhjqp69GzTdt6k48PpPqmdna9kacTy7i4xX/nk2jweaINL0u0g tlsoAbj0I1jrLKeVDxA6R8P+CyPYYmcRnI8XEf8Acp7YMBkEYiuEPOBm7dSyzQfzO84aFp0Wm6Xd pBaxEsq+lGSWY1JLFSd81+fszBllxTFlzcPaGXHHhjsH0Imu6hpH5cjV9bYS6nBZfWJzxC1lZaql FA/aIX/Wzj/Ajk1PBDaHFwvUjLKGDjlvKuJiH5T/AJVrb258weZYUn1O6HOK1mXn6SyHkXdTUerI TX/I/wBbNh2r2mZfusZqENuJwuzuz6/eZB6pMK86+WrnzX+aV9pfluzREt/ThuZEASJeIHOR6Db7 XH/KZc2ui1A0+kE8h3l9P851urwHNqDGA+lKvzH/ACyuPJX1FpNQS+S85CqxmJlZNz8JZ6j3y/s3 tEamxw8PC067QHBW/FxPRPyT86eTbDykNNvbmKwv4ZZJJzKeJkVmqrg/tbbU/ZzT9s6HPPNxRBlG Q9LtOy9Xihionhk80/NfXNF1vzlc3ukUe24KklwtQJXRQC1CB06V/azddlYJ48IjPm6rtLLGeYmL EKdfbqPDNi69oCpp38MIUuAJ6b4qXUOAbq2Qf64q1hV2KuxV2KuxV2KuxV2KuxV2KuxVfEoaVQ32 SwDfLvkZHa2UI2a73s/5P6KJfy5tWnjMv6Zae8vAARUTEqBUf5OcZr8n74n+a91ijUAGQ6N5a8v+ Q/Ll8NNtTa2Vusl7MrsxLMq9+XYZjyynNIW2VQ2fMOh+XPMnnq91zULILLdW0Mmq3vqEgursTxTY 1b+VM3880cIiDtfpaaMlDyd5O1rzbPew6Qqf6BaPfXUkhIUInRNg37xj9lcOfPHFXF/EeFRElK9K sLrVdQs9Osk53d7MkECAf7sdwvSv35bOQjEyPIBA50jvNnlrUvK3mK80LUwou7MryeOpR1kHJXSv ElWGRw5BkiJR5FSKTjzX+WPmfy5qGjabMIr++12MSWFvZ8mYltgjcgvxeP7P+VlOLVwmJHkIfzkm JDKf+hbPPotgZL7So9RZDINKadzMVAqQGCcT/wARzG/lTH0Eq937WXhl6Z/zjX5gk1DyBe6FeH1T o9y9oI2+KtvLyqhHUry5jMHtPHw5RMfx+psidqZ9puheVfK9gNL02C202xvZivoB/wC9nlqCvxGr ud/h/ZzDlklM2dyE0OQfK0lkbCe609hQ2F1cWoB68IpCqf8AC53GhlxYgXku1ocOb3rT1zKdUkX/ AEs/+3t/3b81f+V/62P+xZ2f+T/5If8AYw//1pJ5CkuF/Lzy29tF6sg062BA2P8AdDrmqy/UXfYB 6I/1U/ZiKchTmKso8e+UkuQEFb6rpUk8llFKVmj+1HQ/ryLKkdG8TKGr02B+WA7JpThmt7h3a2fm 6mjr4UwFCsCwNaf6xxVExuVoexG2DdBCrzMhodiMkil6yKAV8e+FVVVRgKGh8Tihj3n7ylH5j8q3 2m8OUwUzWfiJVyzHPhlbGUbFMW/LPXtCufLUGh3cxXzDpSGG/hIIoVY9Cev0Zdmx36mOKfRGebfO Wi+WHsmLGSOUjm4BJXfvkcWMFnOVDd5yLQ69+akOuv6Z8vM3F7nmp6j+UGvXLyOGFdWgWZ3/AAvZ 7PSbu2WNbSMfVAao+xJGYc7J3ckEAImS2+t3Hpy/BGvxI/YHuTlRSC8m806je/mD5jbyRoRY6JBL x1W+3C1i3IGZeOIxjiPNx8k/E9I5PTrHTrHQNJg0XS1EVhaIPUAG5anxMfHpmNknxG22MABQRFqi C3MnItBIax7fw65BnItalDe3MUcFunwncydCBkgopFLGYoFjdviiFWfxpjLnswQc2o2F2ZLaJi1y oqY6ED9VMkkClCJI3u45yGWaNSoiPQYAsl11HPz+sV5OSKKPDEmygHZ57+b6utx5aD7OZL006bGB M6X2W/xv/Mk857UD/Bf88MI8M9FfO3HbrthVlP5ZeXv075102zdeVvHILm5r9n04fjKn/Xpw/wBl mB2nn8LBKXWv916XN7PweJmA6AvX9E85fXfzr1LTSxe1jtWsrdK7B7c+pIw/1jyznc+i4dDGXXi4 /wDTO+xari1Zj04eH/Ssn88vpflvTta81IAupPZpapXbkysRGK+NX/4XMLRCWacMR+ni4nK1VYoy yfxcPC8o/Kb8q7HzFZvruuvJJaGQrb2ytx9UrTm7t/LyqvEZve1+1JYSMePn/E6bs3s2OUcc+TKP Keg/lv5k1/WdOtvK0MdrpDmN70yOwdgxUAJ8NPst+1mFq82qwQjI5DxZP4XM02PBlnIDHtH+J59+ aNv5R0jztBY6bpscdhp6xtqEELMvrszc3jZmJ4/AAv8Ass23Zks08BlOXqn9P9H+k63tAY4ZhGMd o/7p7rHqeleXPIkmsJpyafDDaLcvp0RC/Gyg+nypu1fg5NnLeHPNn4OLiPFw8b0PiRw4eLhoV9L5 z1e90/zT5js7bRdGi0oXUyxCKJ2kkleRviZmbiOngudljxy0+KRySM+EPLZJxz5AIR4Lem/mr5J8 ieWfJRns9KhXUrh47a2uCW9QN1aTr1om/wDrZouy9Vnz5wJS9A9XD/vXb9o6fDhwmo+r6UB+Vv5U aDf+XR5l8w1nt5leaG25FYkhSvJn4/ESeP2cv7T7WyDJ4WPbz/3rXoOzYGHiZN03/L7Q/wAuvOQv 5IvKkNpbWcnpxzNI7iUmp2Hw02H+VmNrs+p0wjeQky8vpcjSYsGayMdAebHX1HyAnm1vLQ8jwteC 8NkHFy3EuG41+z45mDFqDh8XxjXDx/S4ni4PE8Pwt74fqZp53/KXy3+hPq/lzR7eHU7qRUF8xcLb xdZJmJYj4Rmu0Pa2XxLyTJiP4dvVJztX2fj4KhEX/uVs35Yfl75b8k3t7dW6ahNFavI1/KSSzslE KAGiryK0wDtLUZtQIg8A4vpQdBhxYSSOL0/U8u/Kf8uY/N99cSX0jRaZYhTMIzR3dqlUVj0FFNTm +7V7ROmAEfrm6js7QjNIk/TF6DH5f/Lc+fV8nweV4pmhg9W51AyuRH8BajLuT+yPtftZpjn1IweM chG/DGLtfCweN4Qh75MX/O/QvKXl+XTtP0fTorO8m5z3MqBqmJfgVakkbtmf2JnzZTKc5cQHpcLt fDixgRgKLNfyL0VNJ8kTaxcARtqErzM56iGAFBX25LI3+yzWduZvEziA/gHD/nSc/sjFwYTM/wAX +5eD+ZdYk1rzBqGqSNyN3O8i/wCpyIjH0RhRnWabD4WOMe6LzWpyceQy7yltMuaWQ+QNCOt+cNL0 4ryieYPOP+Ko/jk/4UZidoZ/Cwyl1r/ZOVosPiZYx8301571ry/o2hNqGtIJYrZleG1ND6s67xoA Tv8AFvnEaHDkyZOGHOX8X8z+c9fq8kIY7lyH+yQ/5fS6pf8AlhNZ1WSl9rEjXhj3KRxt8MKR/wCQ IlRv9ZuWS18YQycEPph6f6zHRSlKHHLnNB+Q59Ai1TVNL0BPXtrF2k1XU2PJp72di3EP+1x+Ov7K /Cq5Zro5DCMsn1S+iH8zHFr0koCUo4+Ufrl/Om8a/PDzEdU85yWcb8rbSY/q6jsJWHOU/wDEV/2O dJ2Jp+DBxfxZP9y6LtfNx5eEcoM8sPy78l6N+Wya1rekw3WoQWX1ud5eVWldeax7MOhITNVl1+fJ qTDHIiPE7OGkxY9OJTjvwvMfyq8sW/mPzjb2l3F6unwI9xdRkfAyrsqtQ7cmPjm77W1Jw4biamXT 9m6cZcu49Ieo+bfyb0O91jTbLSrOLSNNjBl1O/Unk/M8UhiDE8n+FmP8uaPSdr5IwJmfFl/BD+b/ AE3c6rsyEpARHAP4p/71Bfm75M8keV/JKJZWEcV/NMkVtOSTNUCruxJ+LZfiy3srV58+ouUvTX+a 09o6bDiw0Bv/ALJD/lX+T+h6loMGva6puVulMlvaFisSxdmelGJbr1+HD2n2vkjk8PH6eH+Jj2f2 ZAw8TJuj/J+jflZ5rbVAPL9vYWVlJ6EV09wQ8v8AlKpI47e7ZDV5NXg4fXKZn6uHhbdNDT5r9IgI +bx7zlpml6X5m1DT9Ln+s2FvKVglry27jkNm4nbOi0eSc8MZT+p0GqhGOQiP0pLmU47sVdirsVdi rsVdirsVdirsVdiq5QeLU68HA+fE5Xl+kt+mA8SN971Bf0NH+WPlG51CLWHhgsPU9bRmEaRgAljO xIX/AFM5L1HNKjHn/E9uT6QnJic/kr5guYItTijurSea2XWHD3ZjIAU7fZRhuqt8WV3+/iNj/USe THv+cd7nS/KvkLX/ADhqgItJ7yCyqACQicEqK0+HnN/wuWdp3kyRhH+bxIx8rZ/5T8veU/y78xto 0BWa787Xt1PbdB6VvFH6giHWq8nZV/1sws2SeeHEf8kAyAp5Z+WHlO38ued/OfmbU1U6b5Je6EAb ZXuHDMgFfBen+UyZsdVlM8cID6srACrLvz0trbzd5J8ufmdpsIT14ktdVQb+msjfDyI/33NWPkf5 lx7PkceSWE/5qz3FvTHS1b83fJRuKGVdAuGta/z0UNT34VzA38Cf/DAz6h86ed9X81WH5paxf3Fx NH5gt7ydYHHNisTVRBEveL0dhm7wQx+CKrhLVIm3pP8AzjFKUTzfI0hRTCjSTdOLUcs+38v2sxO1 Y7wpljTTyX5JudL1vTdYfV9KuoucZjEi3LSM1w7FZYxKQi3U68l5U/yspzagGHCBIfJIG7z3zSVP nPzEV+wdRnoPflvnRdln9yHmu2v7wJbmwdMkX/Sz/wC3t/3b81X+V/62P+xZ2X+T/wCSH/Yw/wD/ 15F5DeeDyD5Y9KTjy021Zl8f3QzU5j6i9DgH7uP9VkF87RQi6ZwI/wBoHtldNwUrHTdLuYzqFug9 dgQZPGmR4VkTyX3DQxxqDUNUAgZFkut7a2t7gxwRGJpRyaX54OaEQNtuW/YYaVtJCrFQv2up8MCV 8f2djvXc4ULxIC2x3GFCoCykMfuxCFt5rUGm2rXtyP3abhK0JPhhY8N8nhNlpdufP195thvFiivp GkGnAEEAilCfozOBMocNNEcfBO7W/mRxv9AhmiIC+uI5+W9Ec02+/JQwcBTlymQT7y7+RWnaPeWO oN5ga409uMv6P4sOTEVpk5R4mmB4T5PY4dQtfSWAKYzGvwqeyAZR4DYMht4l+Y/5oXOt6qPJnk6O SK8nf0ru/G5A77DcYI4Yx9UuiyzE+mPV6H5O0Kx8n+XIdOihBvuAa+vB9qSZt2Yk75g5MwMnKjhI FJwLaa6tQ0jqsxPLmu4K+GPECFJrZfLFOsQELKrKPhBH8MVQHp6idUit/VZGmjNW/ZBpkqVGtp92 LQQTT+qUNWlAoWHhgpAluoT2lusyMielI+xlHWg8cISSqKrLLwO7EH54QN2KCiurhNUntTERGqgp LXY+2GtlrZ5t+a63R1TQ5ppOSvLeBI+nGkCZ0fsr/jf+ZJ532p/xUf1wxHtSnhtnovk+dhm/5e+a fJPl+O5l1vSJtSvZiFjcLC8ccQ7BZHU8mP2s1naGlz5j+7kIQdjodRhxA8ceOTJ5fzl8qaZBdSeU /La2GpXQ4tcypDGPmREXLU/lzAj2NmyEeLk4ox85ObLtXDAHw4cMnnXljzHNonmez1whpngm9WZQ aM6t9sVPQsD3zdajTjJjOMdRwxdRgzmGQTP87iZl+av5rWvm2xs9O02KaG0jf1roz8QWcCiKApbZ etc1nZXZctPIynRP8LsO0u0o5oiMeSN/LX849O8s6GNG1SzluIYXZ7ae341Ac8ijBiv7R65V2l2P LNk44Gvez0HakcMOCQR/lz86vJmhyaiLXy/Pax3twZ627RuWrv8AvBIy0bkW2U8cq1PY2fKI3MS4 Q24O1cMCaiRxJDr/AJ0/K6/vbjUo/Ll5c6ncyerI9zMI4yxpWoWSTw6ccy8Gi1cIiHHAQA7nHzav TSPFwy4veyTXPzs8ia9pLaXqei6g9pKUMiI0QqUYMBUSIaVGYOHsTPjnxRnCx73KydrYckOGUZUx qw86/ljo+sWOo6P5cuxJbSc5JbiVSyihH7tObqz7/tMuZ+TR6rLAxyTjv/NDix1WmxyBhGWxTzzT +bP5ceZ47ePWNF1G4S0LtAqtFGAXpWvGXf7IzE0vZWpwWYThHirv/wCJcjUdo6fNXHGR4UP5f/Or Q7DTrjQLrQ3Hl1laG1ihk5zJDJXkr8ivLqx+Fsnn7GySkMgmPF+qW3pYYe1YRiYGP7v/AGSpY/nB 5S8r6C2leUNKuefN5VkvHXiHkIqSQzs3ED4VwT7HzZ8nHmlH/NZR7UxYocOKMt/5zCPJfmux0nzi PMWuQzXrhpJaQhCxnk/bIdkGxPjm012llkw+Hj9P/Euu0mpjDNxz3ZF54/Oe/wDMMsVpaQvZaIsi Pcw8wJ7hVYHg7LsibfYU5haHsaOGzI8WT/YwcnV9qnKaA4YMk1v87vImt6TLpeo6PqL2k/ESxoYk 2UggVEq7VGYWDsTUY5CcZQse/wD4lzcva+HJHhkJUlnlX83PJflq7mg0nQrm30m4AaV2lV5zKtR9 gsVCcT/vzLtV2TnzjinOPiD/AErTp+0sOEkRjLgKLtvzp8lWnmq81uDy/Okl3CsMlyjRmWTiQfiR mCBdh8XLlkJdi55YhAzj6WUe1cQyGfDzCXeavzF/LDzFevqN/wCX7+4vzGI05yokdF2UfBIafQmX 6bs7VYY8EZwEGrUa3TZTxGMjL3prZ/nj5OTyxHoM+iXkVqLcW0sVu8RXjSjcWLq+/vmPPsTOcpyC cOK+Jvh2rh8MQMZU8681ap5FubeKHy1o9xYuGDTXN1LybiBQKqKzjfv8WbjTYdQDeWUZf1XVajJh IrGJD+sxn9rbb8Mz+rhMz/LDzlovlPVrjUtSs57uV4fRthB6fwVYFj8bJ9od81faejy6iAhEgd7s ez9VjwSMpC0P+YPn+/8AOGtC6lX0NPgPG0sSahV7s1PhMj/tNlnZ+gGnhQ+o/VJhrNac87P0/wAL LPNf51reeV7fQ/L1tLYEwrDdXDkApGqhfThKk9afb/lzXaXsThynJkPF/Rc7UdrcWMQgOFr8tfzd 0Pyl5f8A0Zc6dcPMZXmea3MbBiwAqfUZCDth7S7IyajJxCUapGg7Tx4YcJBu0n1rzP8AlbOJrix8 u3kmpSu0nqXc4EfJzUs3GSUt/q0zIxaXVihKcOGuHk05dRpjvGMuK+9mOt/nf5H17RjpOqaPqDWb 8PUjjaEAmMgjcSKaVGa7F2HnxT44yhf48nNydq4ckeGUZUlXlX80fy68r3N7PpPl69je4VY0dpY3 LKvxfEGc8PjP7Jb4cyNV2Xqc8QJzjs06fX6fCSYRkgE/Oa8vfO1prmtWzSaXZB/qmmW7U9NnXj6l W4q8lCftf7HLj2NGOAwgfXL+OX+5ah2oZZhOQ9Mf4U480fmv+W3mgWx1fRNSmFoHECB4kA50rXjK K/ZGY2l7M1WAHgnCPFX4+lyNT2hpsxHHGR4Vnl389dM0q0bR20Nv0FEvpWcccoaYQ/yvyorGhP7W HP2JKZ4+P94fq9Pp4kYO14xHDw+hJm8xfkqXZh5d1NQxJ4JKirvvsPWzJGn123rx7eX/AB1oOfRk 3wz+aT+ZtZ/LmfT2g8vaHc2t4xFbq6lrxFakKivJyr4nMjTYdSJXknGUf5sQ0ajLpzH93Eg+9iGb J17sVdirsVdirsVdirsVdirsVdiq+JlWVGbdAQSPau+RIsEMoyogvTfKtnpuv/k3p+n6pYajq40W +ksZdL0lykkzq/7szU/3Wq/7HOSzg49SSDGNj6pvdYp8WMFlX5cWhv8ATdZ0Gby9Poml6pbu8Es1 wbt3Ykwukz7rFKjL/dDMLUSoiYlxS/o+lnzfP+s+bNf07ydN+V93aQQWum3j/WLgchPJIkrH4v2a E/EP9jm8jhjKYzA/UGsyrZCx/mJ5rPmPRvMF3ci9vtBRItOWQcUESAgIwXryr8bfaw/lYcEoDYTQ ZG7Trzf+c+v+ZtEvtHfTbLTbbU5kur97TnzmdKU5ch/k75Vg0UcZBuyEmdpXof5k6zpPkrU/Jotb e80bVC5YT8ucLSAcjFTb7QDjllmTSiWQTupRRxbUreZvzW80a9qmiaqFi0zUdAjEVlcWpYkgftPy 2+LoyfZwYtFCAkPq40ylyZVN/wA5LecJbdvV0XSTqHpmL9JFXMiggqWAPz+zXjmOOyoA/VKv5qfE ZB+VMMvln8ndb8xTWpurvXJWNvZgENMrkwom245tI9Mo1ZE88YjYRZRFRTDyfoX5dnVbe70281W1 1DRwt5c6HqDSKqNEpHLhKFPGLk3Bsjmnl4aIjwn+NQIvKBdvemfUH+1fXE92D/kzSFlzp9HDhxgP J9qT4sxbzLdYkX/Sz/7e3/dvzVf5X/rY/wCxZ2f+T/5If9jD/9CR/l8ef5f+W5QOTxaZboq+4iGa jLvMvQYD6I/1UwtVbUdNmTUV9Okh4wrsTv1wcJDadirQx6jCYbSzjEdhX96TuaH3yMQyJ6oy6khh kgEkRkVvhQj9ZGRA3RxOt4dSEEjXjKxLH0uIoQnhgI3SF8EscjuqihX7BOJ5JXgsFb1SC/YjwwDk p5qZuBGoJ+yepwqqxT27pyB+L9j3xtBC171UQq/2u2EIp5L+a3nG9MkOmLJwgrV2H2q5k6XGDuWG afDsGDaVqEyyUV9m8RU5sKHRxgXeatfaLy3JaBg8gkDior0IOAhGQ0HqPk/za+r+X9PkkULeQqFW nQgCmRUDZlEeorMhq1W48eR8T2yJSAh/LnlTyxoOvza5bQE6pdLxdpDVB7qOxyB32XhAT+6cSOTy DCQ8mWu+ajPDhlTsMM7CkklzAvKD4kr8SHw75WJUzIBVby3jvBFfQysjW4J9MdGPvl8ZAtMhS+CO 8uCkt2wVGWoK/aGS5MSiVlJLxI/7pV3J61OBFJaZpLa5ggZwUlr+8bJBl0a1bT7q4iX6pcelPGwY P4jwwsLdLLOoVXAMn7TDqTiUh5n+a95DLe+X4VUh4pb0ufGsCZ0fst/jf+ZJ5z2p/wAV/wA8MQOe ih87awq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXY q7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq7FXYq9G/InzJHpfm650S5YLa+YkVrUk0Av4B9mvj NHybOa7c052mP4fqeq7I1HFj4TzinOh3/nQ+Y7K4uLnVh5igvTL5mS5Bg0Oz05S3NADSJ+Ua8onX 9432s18xj4CKhwmPo4f7yWR2qV/nr+Xtn5ks1/MbyUyahazRV1SO239WNNhcR/5SBeMg/lXLOztS cZ8Kf+aiUb3fPwYMOQNQe4zdNTeKuxVrFDKvy7/L7UvOuupZRK0elwMr6lffspGP91qf9+P/AMRz H1GoGMebIRt7X+YnmCaz0Wzh8sQXK6ZpTiGHXLCVRBaTQ/CUuogPjjUH4/2c1WnhciZ/xfw/zmwn ogvO3mzWYPy8ht9TuLO517zCv1a2u9PB4PauKzT77/BGGJ/ZyzTaaMs1C4xj/Cwy5BjgZF5d8AUB BxjWgVfADYDOujGhTxE5mcjItZJrSL/pZ/8Ab2/7t+ar/K/9bH/Ys7L/ACf/ACQ/7GH/0ZV+XlvC Py+8sn1CGfTbZmHv6QzV5RcjTvtOTwD3J/PHByTkh5D4hIB4DKrbwhLO6Pry3l0xgtZDwghfY8h3 wlK4XjiC5njUz0P7taVocjsmlG2ttcnu1knfhCKOU6CnhgJCRSYubeaKVIG3A4mmxB9sHJFlZbW6 wxrFyLbfEXNTgJSlurTok0EJajO1AMhPk2YwoSEK/KvFhsATTp3ymy20gb3UmSQxSNXkvXvmRjle xa5QrcPFvzD+39YlkJLSfuy2w+nM/Tmw4OpFc2M22oXMUytLUx9Ay9MygXGBTSL6nOj1KlGING3B PfJxplszDRNUso4fRhdYXj+yFNOmRbAyPT9Zlhif15AWY1Wh2yBCWUaNqkd2OZdaL49iMiUFvVVm t9Ss9XV2+qps4r8HxbZqM8rk7LCKj5snRkkVGXZGWoI6b5TTHkvhKQuSo5L+2gyQLEi3JPJMknKM ip4oBsVXMjamoim7OO2src2rPzkYlgzdTXtXDtTE3aA1SZg1sEj9U8qVpUr9OILKkUrcZArAhaVL kbV8MShDNFPI8zORwZaRg9QfHCEW8x/M62nt38urOQ7+vffGOpHoJnSey/8Ajf8AmSed9qD/AIL/ AJ8WJHPRHzt2KuxV2KEbo+j6jrGoQ6dpsJuLyc0SNdunViTsqDxynLmjjiZSPpDdixSyS4YjdlF/ +UHnqxs5ry5s4o7a3Rnmf14zRVFSaDrmDj7X08pCMSeKXk5k+y88QSRtFhVa7+ObR1zsVdirsVVb a2uLmdILeNppnNEjQFmJ8ABkZSERZIAZQiZGgLKtqOlanpsqxahay2srCqrKpUkfM5HHlhMXEiTL JilDaQpCZY1uxV2KuxV2KuxV2Kro45JHWONGkkY0VEBYk+wG5wSIAslMYkmgy7Tvyk/MC/iWWLSX ijYckNwyRlgelATy/DNdk7V08djNzodm55C+FCeY/wAufOHl20+uarYGO0qA06MsioT05U+IZZp+ 0sOU8MZbsM2gy4xxSGzGv9qmZvUuG7CrsVdirsVdirsVdirsVdirsVdirsVdirsVdirsVdirsVdi rsVdirsVdirTiTirQytBcQss1tcL9qOaM8kdf9UjKc2LjiYlytHqDimCHtFxrd3+a3kGWCCaaPzF pKU1Ty3FIkUd1cfCIpXc/E9pWsoT7D/3cn2VzjpYTpcu49J+mb2UMoywuKbeX/NXlfyPq0fk6O9/ SNzcz3F7r+rSmK2s7R1iVnRVQLEjGifuE+z+18WV5cM80fErhA9MI/xTbAQNko82/kJ5T862i+Z/ Jl4umSagDMg9MmynqSOXpfC0XIgnko/2GWYe0smI8ExxcP8ApkHGC8g1n8i/zU0p2D6Kb2IHaazk EoI8Ry4nNpDXYZdeFr4Cl1p+U/5l3Mnpx+XbpG/ml4oo+Zqf1ZYdVhG5kjgLOPLX/OOertJFc+bL 6HT7MsK2tuwaWTwX1Goik/5K5iZe0hREBZZjH3vSLya28u6honkjy7BaaZZ6hFNNNLcVVHiT4ZIk YFD9ZcHkZGb4cwREzBnL1FnLuDHdL0268tyzX1jrkB8hW4dmv5D6k8MUbEy2CA/u5fVkb++4+o32 eWXSmMlAxPi/zf8AfIp51r2vXHmLXJtbni+rQFfR0my7W9pWoFB0eX7Tf8DnQdn6Xw4b/U812rre I8EeSAzZOldiqRf9LP8A7e3/AHb81X+V/wCtj/sWdl/k/wDkh/2MP//Sk/5ZLczeQ/LrTKFePTrZ bdK/aT0hRjmpzfUXoMH93H+qyWyh1cXsgulT6kRWLfflldNp2UbtVkvWtrhQ6KKiu9K+GApi3bRw aaptY2dpLirI1KgYLSQh7ua8h1e1WWqW5B5NX7THtTAGQCnp1pqVrqN3JItYbh6oK14jCSqPuTwd Q2x6AnuMikMP81ara2mqadLO1EMojqOxPfGY2Z4ymE9LkylQG9KjCvUg+GY/JtS68gjkiMh/3oRT xGTElp4t53TXNTtpJZ7MRwxyELEpqxp3zZ4TGJ5ut1AnOPJgdld3UKFaloRUPATv9GZhddGRCOtt T00RgSc0l6kCtPwwANniDqm1nrmk8xDBI7ySihIQ8vkN8keTKOWJ2Tqw836JZRPZyyzG5LfAJEoA T75FsGQXTL/JNxc6nqhRJAsMPxSpWgauYWck7By8VbkvU9aijn0iPT4APUbgfT9gak5r8gouRjPV NLdVjijtwvwogH00yAOyDzV4YeFBHsWPU4RG0Eo0w+mORNFbq/zy4Cg0k2UKkPIEXKqWU8omXwya qN3GzRsIRxkH2QMjJIKm8zi1SG4FZuoA8RhkdkAbqEIeaUzTfBM2wh7CnQ/TjfRBGzzb83pE/SPl 6Ag+skl6ZPAgwrSmdJ7K/wCN/wCZJ532p/xQf1wwv8SM9FD527CrsCr4opJJUiiRnlkYJGifEzMe gUdScZERFksgLL3Tyl5fXyPDYacFEnnTzGyq9KN9Ttursf8AJRftfzyf5KZy2rz/AJoyly0+H/pZ kei02H8uBH/LZf8ApXFNvz5179HeT49LjPGfVHEVOtYY6M5r/wAAMxew9P4mfiPKHqcntfPwYuHr N85Z2jyLsUtoKsq92NAO5+Q74LA5mkgW9C1b8t7HQ/y3TX9YM8eu3UqLa2YZURBIfh5qVJJ4As3x ZpsPaM8uq8OH93H6nbT0UMen45fXJS/JjzJoOgea3udY4xxywNFBeMKiJyQd6dOdPtZPtjTzy4ah zvilFr7Kzwx5bky/89PO/lTV9FtNN0+aO9v1nE3rR7iKMIwPx/5RYfCM1/Ymjy45mUhwxMXO7X1W OcRGJ4pXxPEs6Z552FXYq7FXA19/bBdrTsKqttbT3VzFbW6GSeZ1jiQdWZjQL9ORnMRFnomESTQ6 vo/y95Q8tflx5Ul1rUI1n1SKL1bq6NCwbtFFUbfEeG2cXqNXl1mYY4n0E+n/AIp6zBpoaXFxyHre WWn5yeZn85W2uajPK+nRO1dLiYrGsTqVoBUc2WoNX/azfy7Hx+AccR6v5/8AFxOmj2pPxROR9P8A N/hZl+YX50eWdV8p3OmaXHLcXl+ojYyxhVjWoJLVJq23bNZ2f2NljlEp7Ri5+t7VxzxmMf4nhm3b oc6m7ecdhV2KuxV23j92AUtMj8h+T7zzZ5ig02AMLYENfXCjaKIbk8txyPRP8rMPXayOnxykTv8A wuXo9LLNIRDvzA0bRtE81Xmk6Q8sltaUjd5nV2MgUcx8Kr9lvhx0GaeXFGc/ql+IrrcUMeQxh9IY 6evv3pma4jQ6jAVZD5X8h+afMwkfR7IzQwnjJO7KkYb+UE/azE1Ovw4NpndytPo8mYekbJZrej3m japcaZe8Prds3CYRtyUEdq5dgzRyR4o8i05cZgTE8wgR1y5qR+i6NqGs6nb6Zp8LT3Vw3FVUdBXd 2PZVynNmhigZSLdiwyySqKaed/JGqeUNVSwv5I5jNGJYpoieJFdxRgPDKdFro6iBlEf0W7V6Q4ZC MmOZmOI7FXYq7FXYq7FXYq7FXYq7FXYqr6ffalpepW+r6RdNY6pa7Q3K7qyk1MUq9JIW/aQ5iarS Ryxouw0WvlhNfwvTl8zeQfzF0uPRdftbTyz5pdm9K4lTlaTGZ0a4lgeqRtLOq/7v/epnM5dNm0sr Fzg9Vizwyj0lkPmRPPEHnXyxF9Tey8oafqUNnptrbSeosqCFl9a74bomyrCn2f5/izGxHGccjd5C OJtN2i31rzDF5y86y22uzSaP5ftVnFhKkbJ9ZmieQIJAAypHxHw/awRxwMMdj1TKkmykWoee/NV3 a6FC2uwaHNe6A2tS30iIY7q6Sp9BTIeKqBuePx5ZHTwHFtxVPh/zV4ki8wx+evNSaX9QmMcXmXTI dRWxnRjBDqFpRqI4+K3L/aTl8LcsyIDFAGx9B4f9MiiWSeddb8oDQLRfPMEbX7oko0lSZLwXJX41 i9Ihl5H9v4VynDjyGZ4ORTKYA3eSeYNdvNfe2jntk0/RLHbTNBi/u4wOjzlf7yb9r+Vf8rOh0mhE PVLeTz+v7Uu4w/0yXk1JJ3J65s3QOwq7FUi/6Wf/AG9v+7fmq/yv/Wx/2LOy/wAn/wAkP+xh/9OW /lwkFp5D8tXU03FpdLtFjVv+MS0pmpzD1F3+D+7j/VT68e/jtlS2YSys4Ys2wCnKyW/hV3WJCJZj xbiBK56ZG0tXE3ptE4i9SBuj96HwxCCofo+aOc3N1J9YiJrbxNsU8OuKQVVuXB0MoNw4+EdhgpNo GVLqdQlxQPH0K+AwMmGee/Ksus6YZLaU291G3KJiK1K5OJHVBNDZLfJnmeCb0tLvZRHrVgPTeNv9 3D+uU5YEGxyboy6MuaOF5fUU0mfYxkdMqbEj1PyxFcTEp8Eqkse4PthiaTdvMPMP5TGa6lvLGf0J Xcs0ZFFA9sz8WtIFEOBm0EZGwaY5d+QNdgFHiWeMivwihy+Gsieezjy0Mhy5IfTtK1LQNXtr6ayL xIaktvQeFKZZLNEjYsIYJRO4ei6j5V8p+dEtNRr+itQWgmRV+FgN65R+YLkHSA79WYeWfIWj2jPd Wd2zoKRy1BFaZjHMRzcjhFVTNbHS0glWVpDJIo/d18MxibLO9qRyeoTx4gb7nwwAbsSibaJZJBVu LR14175dj3apJfr13rUUUcdlEsyF6SpWhA9snSI0ihcEQxB0IlI3A3pixU5q3CtFFPwm7su5WuAj dIQEMklnWC/kBhB+C8bYlj0FMMhfJfcimELSqwerHfl/TGkPOfzoI+s+WfhHxSXrcu/9yozpPZX/ ABv/ADJPOe0/+K/58WBnrnowD54zv8ufyp1PzerXssv1HR4m4vcleTyMNysa7ffmp1/asdOOGuOb s9D2cc+59MWR63F+TPk68l0x9Nn17UYaCfm4KRt1ozEqtf8AIVXzCwHW6iPHxDFAuXlGlwHho5Js jgufJXlny9F5uv8Aytb6PqRJ/RdkCGuXqPgO4Hpnufh+BcwjHPmy+FHIckf45/wOXxYcWMZJQ4Jf wR/iTP8ALjzDpXnLVr/zD+g47K+tQlt+kDJ6src1qU6LQBAmUdo4J6aAxcfFE+rgbtBnjnkcnDwy /nJF5689eWtS87Dy/ceWYdbuLeZLOG5lkK/G9C4UBW2Rm+LMzRaHJDAcoySxcQ4uFxdVrMcs3AYC delO/OnlT8t/K3lmbWp/LtpO8fFIrUfCZJWNOCsfbk32f2cxtHqdVnyCAyScnVYMGHHxGISfzVoH 5Pz+QLnVbBLO0uXtzLZvbuBN6/Gqxca1+38LDjmRps+tjqBCXFIfxcX0uPqMWlOHiFRJ+lIf+cfj ps+qXltLpcdxdxoLgahJRjEtQqoqkftN8WZftBxRjEiXp+ngcbsWMTIgiyP4mQfnX550a0v10GfR INXuYohMstwx4wyyCn2AKt8FG+0uYXY+hySj4kZnHZ4fS5XamthGXAY8X+9SH8jvIei67Bquq61Z R3trEy29qkgJQSU5OQPkyZmdta+WIxjjkYy/icXsjSRyCUpjZJNQ8raX5j/NSby/ocMWn6ZA/oyG AbBYFrK4Fftl+SZk49VPDpPFyHjmf999LRk08cup4IDhiGY+atG/LvydPpOjQ+W49Z1DUjxQzyH1 PtBFLNQj4mb+XNbpc2p1IlPxDjjBz9TDBp+GAhxykmH5h6F5D8oaTBqQ8qWl6kk3oypy9IpUVU9G 5VynQZ9RqJmPiSjs263HhwREuAFU/Lny75B846Rcak3lO2sIo5jBEGPqc+IBLVAXueOHtHNqNNMR 8WU9k6LHhzxMuARQ2k/k7oF75tv77UbaO00xGrp2hx1BMaARmWYfspI6syL+1ksva+SOERiTKf8A Hl/3sP6rDH2ZCWUykOGP8MP+KYL+d1j5d07zRb6fo9nFam3tla69IcQzSH4KjxVVzbdi5MuTEZTP Fv6XV9rQxwycMBw7POs3Dq2V/lY9ovn/AEY3R/d+t+79paHhX/ZZr+1Afy86c7s4jx429q/Pqzu7 jyCzQoZI7e4gmn49o15Ak08CRXOY7DnEagcXc9D2xEnDt3vmuh+dd6521F5G2Sfl/wCTpfNnmSHS /UMMAUy3Mq7sI08B4saLmHr9X+Xx8fNytFp/GnwvVvNWgflz5Rk0fSY/LkGp3+pS+kv1iXi4UUXm zsGH2mp0zn9Jn1OoE5cZhHGL9LvNRiwafhjw8Zl/OSb84vJ/kPTNCiv9FEFrqHrJGtvbyArIjfbJ Sp+yN+QzI7J1monk4Z3KNfxBo7T02CMOKNcTX5H+QtD1nTtR1TW7KO8h9Vbe0WUcgpReUjAVH2ua j/Y5LtzXZMUowgeE1xSR2Po4TiZTFp9Yfk3oV75wvr2+t4bLSI2I03RYzRpY46K00orVY2evFf2s xMnbGSGERjcp/wAeX+b/AEYuRDsyEspMvTH+GH4/hYV+ddh5Y0vzHYWGl2MVqsFvzvlgHDkJGHAG lfiVUb/gs2fY88uTFKUzxb+l1/asMePIIwHD/Oe0eWNR0nTfIKa3FpkelWq2n1x7SKmycOQBYAVJ HjnNanHOeo8OUuM8XDxO+wThDBxiIiOHieEXd1ZfmD5tstP0vR7fRnvJnlvLpD6k0hf4pZHPwr8P 2lT+bOqjCWjxGU5HJQ9Mf4XnpSjqsojGPA9C82+VPy48h+X7WWXRE1i9uJlgijuJP3rlhUvWhFF2 rRf2s0+k1ep1WQjj8MAcXpdpqNPg00AeHjJ/nFBfmP5M/LyDyZLqlnDbaZqkUcbRwW0oblIxUGMq D8f2j0GW9nazUnMIyucf6Q/2TXrdLp/C4hUJf0St/JHzdLpflHW2uoVGmaMGuRMGo7SSivo8e/Kn wth7a0onnhR9WX0/8eY9k6kxwysemHqZD5L0fyR510yfzFe+Wba29a4lLs59RpOB+N2NFpVqjMPV 5tRppDFHJKTl6aGHPA5JQAeAa9PYXGs30+nwJb2DzubSGMEKsXI8Bv8A5OddghMY48W8qeXzSiZm tovWfyKg0rSLpby61S1e/wBaBgstMhdJZgIwZGeQoW9L4R9ls5/tzIcg4Yxlw4/rnJ3nZGOMCCZD in9MVD/nIrRDDqmlawpJW6ga2lB6K0Tc0pX+b1G/4HJezua4Sh58THt3FUozeOj8PHOjBdA7CrsV dirsVdirsVdirsVdirsVdgVqRI5YzFMiyxH7Ubio/s+jIzgJCm3FllA3E0nWgedPOfl5BHo2u3EN oo+CxuKXkAH8qo5DIP8AZZrs/ZWLJuQLdth7akNpBksX51ebPSnjvtG0e9S6BF3w9aF5gRxPqURl b4TT7WYJ7Fo2JcnPHbWI80Pf/mxe3tlb2TeVNGFtaAC0iuWllSIKKDgBHsMYdkSBvil9iZdsYaS3 U/zI8/6lE0MmqR6fbuOLwabCIxx8BK/xr/wGZOPsfHdncuLk7aFekMZjjijkeZQXuJD+8uZWMkrf N2/41zZwwRh0dTqNZkyczsurTLnEt2KuxV2KpF/0s/8At7f92/NV/lf+tj/sWdl/k/8Akh/2MP8A /9Q//LpLGbyR5cN5zunj060Eca7LGPSWlc1mYeo077Cf3cfcyy702xv4Xs1naNjRqqd6Dwyk+Tce a+K3drNLZwWii2NTuVHvgiL5skPeWN7fJbmKc2wtz8KAdVHY5A82USshXWpdSMV7KrW3GsUY2II7 nJHyUKH+mHzK1okNbTgClzX9qnTDYpbTV0dnKcSHUUc9jkCoKDe3E8VFIYhqemv9MDK3mnnD8tZo r658y6afR1OD95Fx/nHt3y0SNV/CjhBN/wAST+XvzN1SC/jtPMtuQ/T6zGKUHiRkZ4IkekpjlkDR D0mC6tLlI5bWRZxIfiZSNq+2YhFN4N8l8tjbNOsUiBg21cFpt02kaeoA4cmXZQcNrxOuvLOkX1mY ri2BV6cvbGyx4ltj5S0Cwh4W9tSrfaJrv7YTMotMo7IQRlIgE5nbYUwc0WjYkWMEyuS0Y+KnTJ13 tdqtlJFd27TQbxBiGXvUe+WCDAyQF5qmi6UUa/uPTnlb91GT+FMtjAnkxtMi0MyowNY3XnyrSv04 LooQsgluIZTZSAvEfhI33HY4nn5IHmttLdUIdgI55BWU9at8sJpSp3OnaZcuyXEnrUPNoQdgw6Hb CNltD3E2m6ZbCa4LMqVKgE9PDBxWii8+/N1jJN5YuFesFw97JChG6j0EFDnR+y4/wv8AzJPPe1H+ K/58WFfRTvnog5vnb2/8rfzc8qaV5YtdE1kyWc1oGVJkjaRJFZy1aqDQ75y/afZGaeUzh6uJ6TQd qY4YxCXp4Us1Hzj+Umj6rc6xoOmS6vrM0hlSW65iGKQmvIer/lfyLy/ysux6PWZYCE5DHjj/AKZq yazSwkZxHHPzec+ZfNGteZNSbUNVm9WY/DHEuyRr2SMdhm70+lx4YCMB/WdRqNTPNPiLPvIP5vaB 5U8tJpQ0y6nu+Uss1wpiCNI5PE7sDsvEdP2c0+u7Jy6jLxmUadppO0ceHFw0becLrOorrP6aElNR FybsSdf3hfmfvJzdnDE4+D+Hh4P811HjS4+LrfE9Sv8A86vLWv6OmneafL8tyFdZeMEi+mJFBAdS zI6nc5oYdiZcM+LHMR/rO6l2tjyw4ckb/qpIPM35MdP8K31K7D1+hPgPWzL/AC2tv+9h/pf+OuP4 +k/mS/0yaeVPzZ8l+Wbq9OmeXJ7a2uShVklWSUlBvy9RqKtfs8WzH1fZGfNEcc4yMfJu03aWHETw xIBQ+uefvyr1rUpdT1LyzfXF7cFfUl9dVrxHEbCTjSg7DJ4dBq8cRGOSHD/V/Ywy6zTZJEyhK/6y ZeVPzt8taDpb6bb6DPb2wld4o4JEccWpuzOytzynVdiZcs+IzjfubdN2rixxoRNJMn5k+StJvxq/ lny5NDrBdjJPdzsUKykmQFVd+XKvw5ky7Nz5I8GScTD+hH+a0DXYccuLHE8X9KSc3P5sfl7qWrWP mDU9BvDrOnqBAUkUxkqeQ25ANRunIZjR7K1OOEscJxEJ/wCmb5dp4JyE5RPHFiX5j/mbe+cZoYRb /U9NtWLxQE85GcinKQjbp0XM/s3swaayTcpOFr9ec9DlEMj8v/nXYeXfJ9touk6VMb23Q8pZ3UQm VzydzwJcjkTRfhzCz9jTzZjOcvSf9M5eHtWOLEIxj6kP5E/OZNFfU7nXLW41PUtTkV3u43QfCooq cXICqtduOWa7sY5BEQMYQiw0fagx2Z3KRUPMPnv8tNXubvUZvLF1Nq1zv6s9xxj5BeIJCuaUp9nj ktPoNVACInHw4/0WOfWaeZMuA8cv6TzZqciQAASaAdBm6Ap05LaSPG4dCVdCGVlNCCO498SLCQXq mgfn/rVvZCx16xTV4AvB5eXF3WlKOpHF9v2jmhzdhQJ4oE4y7nD2xIR4ZgTQdz5v/Ju6lMknlC4i dt2WGRI1qfZZFH4ZOGi1kRQyx/3X6ES1WlluYH5tWn5j+TvL93Hf+UfLklrffYmkup2KmI/aUKHf 4vBslPs3NliY5cglH+gP4kR1+HEeLFGpf0kz1/8ANb8vfMxtp9e8tXU91bKUSRJlBCsa0BV4yRXx yjT9lajDYx5IgHybc3aODLRnA7eaUN5n/JviaeVL5m7Brg0r8/VOZA0ut/1WH+l/460/mNJ/Ml/p k90388tA0Py6NK8v+X5bWROTRLLKpi5OSSXYVkbrmJl7DyZcvFkmDfk5GLtbHix8MIpb5G/OZdGu dVvdetbjU7/VHRmuYmQcUj5cUCsQEVeWwXLtf2P4kYRxkQjBq0naghKUp+qUlPzJ59/LXWrm61K4 8sXc+pzqP3s1xwSqrxWvBzRdv2VyWn7P1OMCMckOEf0Vz63T5JGRhLi96f3n55eT9Q0RtHvtDuzZ yxLFNbxPGqcVFOKsHVuOYsew80MnHGceK+rkS7WwyhwyiaYsfPfkbSZ4tQ8qeW5rTVoGBjuLqcmI KftqUV3J5DM4aDPkBhlyCUP6MXD/ADeGBEscSJDzT3Wfzg8k+ZbO2h8yeXLieW2JeMxSrRSwAPFu Ub0PHMXB2PnwSJxZIi/JyMvaeHMAMkTt5pKfM/5N7f8AOq37eANwev8AyOzJ/Kazpkh/pf8AjrR4 +k/mS/0xY/rXnF57G40bRIP0V5cmlWYaeD6kjON6ySn4mWoDcK8cy8OjqQnk9eUeni/h/wBK4ubV 3Ewh6cZ/H1M38qfnPoeleTrfy7faPcSCOJoZpbd41Dq1ampZHDNXNXqexsmTMcgkB/Wdhpu1ccMX BIJPB51/LLT9Rs77SvKMnqW8qvI1zNyHAdQic5E5/wAvLMmWh1WSJEskfV/RaRq9NCQMYHbzZPL+ dnkGXVINVl8tTnUbapiulECyLyUqaMG32OYX8i6gRMPEHCf4fU5f8q4OIS4PUhfM/wCbnkDzMkC6 voF9dC25GCMzJGo5UBrwfrt3XLNL2RqMN8E4Di/o/sYajtLT5a44y283k+oz2txfTzWluLO2kYtB bBi/pp2BY7sc3uOMhGpG5OjmYk+nkhstYOxV2KuxV2KuxV2KuxV2KuxV2KuxV3amBbdhW3YrbqnF XVOBXYVdirsVdiqRf9LP/t7f92/NV/lf+tj/ALFnZf5P/kh/2MP/1TnyrHct5Q8im0vobAfo62+s QSUVrgektKZrZy3k73APRFkum6pd3mr3HLTXsltlZPWYfDIK9RlZFNzV1NHerc6fa3Xp6vbL6iwV pUncZHerZkqr2OrXlhFBdT+hcFR6jqeNCMjsFBTBAQgQKeaRheZ/ap7++C7ShbR5bnS5h6TWs/xK vPrWtA2IFc1MlDQNLv7G1uE1C69eaRuQavRaYSQV5ITVfh0d30tZHkuGKOy7NGO71GICgqmh6elp owia4N471LzMS257b5GRZJTrvkyz1W4R5BHE4ShQgAsPEZCmcZsU1H8q9TghaTSryWFQahFYj9WP F3hn6V9vH+YOjWSRx2z3zn7LAcjt41yIos5ck1s/NPm1YoxqGhTFx1KqdsiY7sYxHejY/NnmSeYR DQpkibYMynbHhQQB1TS11C/YRwXKLa3BPwwSfaI8RXJeGejCwrC38xvMfWQCIH4ePh45YICmBkmh vrN1FtC372H++c9K98NMBaGtdUK3UcCQGVJGPGWEUQe5wqQhp/L1hdeZJrq+VbhUUCKA78G8d8kJ bITC6a2aRLSUcEUVQLsTToBTIq1FcwCMQpGbaUksYyKEjAWK2vqK5kBQdPff5YOabCWWOg/oa1uH s3e4u52Ljm3I0bsK5aZWjZMLcpJaIt1Cvqj7YcA0xIADE83mn5wSIknlx6H01nvQCiltvQToqAnN 97OZY49TxSIiOAui9o8csmm4YizxME+uW/b1Kj/iqb/mjO5Hamm/1SLwv8naj+ZJ31yHwk/5FS/8 0Y/yppv9Uiv8m6j+ZJv65B4Sf8ipv+aMf5T0v+qRT/J2o/mSa+uQeEn/ACKl/wCaMf5T0v8APij+ TtR/Mk39ch22l26fupf+aMf5T0v8+K/ybqP5kmjdw+Ev/Iqb/mjH+VNN/qkV/k7UfzJOF3AOgl/5 FTf80Y/ynpf58U/ydqP5h+Tf1yGtaSf8ipf+aMf5U0v+qRX+TtR/Mk19bg8JP+RMv/NGP8p6X+fF H8m6j+ZJv65B4S/8ipv+aMT2npT/ABx+a/ydqP5kvk43kHhJ/wAiZf8AmjH+U9L/AD4p/k7UfzJN fXIPCT/kVN/zRj/Kel/1SKP5O1H8yTvrcHWkletfRl/5ox/lPS/z4p/k7UfzJN/XIPCT5ejL/wA0 Y/yppf58UfydqP5knfXIPCT/AJFTf80Y/wAp6Xrkj80/ydqP5knfXIdqiU0/4ql/5ox/lPS/6pH5 o/k3UfzJO+uQUpSQj3il/wCaMf5T03+qR+af5O1H8yXya+tw+En/ACKl/wCaMf5U0v8APij+TtR/ Mk763B4Sf8iZf+aMf5U03+qRX+TdR/Mk763BTpJ/yJl/5ow/yppf58V/k7UfzJNm8hPaT/kVL/zR g/lPS/z4r/Juo/mSa+uQeEg8KQy/80Y/ynpf58V/k7UfzJO+tweEn/IqX/mjH+U9N/qkV/k3UfzJ O+uQeEn/ACJl/wCaMf5T0v8APiv8m6j+ZJ31uDwk/wCRU3/NGE9qaX/VIpHZ2o/mSb+uQ/8AFv8A yKl/5owfynpf58fmv8naj+ZJ31yHbaU06Vim/wCaMT2npT/HFf5O1H8w/Jr65D4Sf8iZf+aMf5T0 v8+KP5N1H8yTvrcHhJ/yKl/5ox/lPS/z4r/Juo/mSb+uQ+En/ImX/mjH+VNL/Piv8m6j+ZJr63B4 S/8AIqb/AJox/lPTf6pFP8naj+ZL5O+tweEv0xS/80Y/ynpf58V/k7UfzJO+tw7bS1/4xS/80Y/y ppf9Uiv8naj+ZJv65B4Sf8ipv+aMf5T0v8+K/wAnaj+ZL5NfXIfCSvSvoy/80Y/ynpf58UfydqP5 km/rkPhJv/xTL/zRj/Kel/nxX+TtR/Mk19ch7iU06fupf+aMR2ppv9Uiv8m6j+ZJ31uHwk/5FS/8 0Y/yppv9Uiv8m6j+ZJ31uDwk/wCRMv8AzRj/ACppv9Uiv8m6j+ZJ31uDwk/5Ey/80Y/yppv9Uiv8 m6j+ZJ31uDwk/wCRMv8AzRj/ACppv9Uiv8m6j+ZJ31uDwk/5Ey/80Y/yppv9Uiv8m6j+ZJ31uDwk /wCRMv8AzRj/ACppv9Uiv8m6j+ZJ31uDwk/5Ey/80Y/yppv9Uiv8m6j+ZJ31uDwk/wCRMv8AzRj/ ACppv9Uiv8m6j+ZJ31uDwk/5Ey/80Y/yppv9Uiv8m6j+ZJ31uDwk/wCRMv8AzRj/ACppv9Uiv8m6 j+ZJ31uDwk/5Ey/80Y/yppv9Uiv8m6j+ZJ31uDwk/wCRMv8AzRj/ACppv9Uiv8m6j+ZJ31uDwk/5 Ey/80Y/yppv9Uiv8m6j+ZJ31uDwk/wCRMv8AzRj/ACppv9Uiv8m6j+ZJ31uDwk/5Ey/80Y/yppv9 Uiv8m6j+ZJ31uDwk/wCRMv8AzRj/ACppv9Uiv8m6j+ZJ31uDwk/5Ey/80Y/yppv9Uiv8m6j+ZJ31 uDwk/wCRMv8AzRj/ACppv9Uiv8m6j+ZJ31uDwk/5Ey/80Y/yppv9Uiv8m6j+ZJ31uDwk/wCRMv8A zRj/ACppv9Uiv8m6j+ZJ31uDwk/5Ey/80Y/yppv9Uiv8m6j+ZJI/rEX6TrR6fpXl/dydPqFOnHr7 fazXfn8HiXxxrx+P/M8Dg4v9P6XO/JZuCuE34PB/neNx8P8ApX//1jny35UsNX8i+TL26kMUljpl o0Dj3iXbNdOREpebvcH0R9zNrV9Ve7Elyq/Uo1AiINeVBSuVSNtoaC6fFPPqLxBbgirzADlxGVkm qZgbL7bVLbUbczQowUHiOfenU4FUr69tooDcPIVghI9Qjr9GIFpBWXeo6hJpJudMiFwZlpbF/wBZ wjuKlALqF1DaR2V/Cx1G9AUyQjkkfzONBSV2sXOoWSQaZptv69/NRbhyKJ6J674ilR1pp31URwDa NRVoxuOR65DmU2iJbSGaUSzFVlQcUZjQYFBaq9rFydTJU7Kv68NLzWWuoC7SSSAGP09mXpgMUUri 5N1ASk45DYtXavhjSCGud0rBWb5b9seFKV6nYR3+rQSuQLiMAJIT2HbLATVKEyu7gQRBZpOIG3Xd vlkCGI5rbSPT5o/WiQKDUSKev05IbJkWg8dtIsMS+mWI9MDp9JxpB5Ia8u7PT9S9W4VvrF0OPNRU GmGlAVZoopryCRl2Qcg3zwRNLalb6hcySXT3UNBCaQSEbkZI0qWX8+r3s8EungRxW+956m1QelMR SaC2K01M6gk73AUAH00B2J7VwiS7I2BZmtJoL4j63Lyq67ih6b5BioaDbG28/eUIS3Pimqb/APPC PM7SncuB2hyD2Pvma6t2KuxV2KuxV2KuxV2KuxV2KuxV2KuxV2KuxV2KuxV2KuxV2KuxV23fFXYq 1Xx+nFXYq3irsVdirsVdirsVdirX6u+Ku8NuuKt4q7FXfdirsVdirsVd7U38MVa7Vp9GKuxVvFXY q7FXYq7FWv1DqcVdXFXYq737Yq7x9sVb+j/PtirVRSuKt4q7FXYq8pqf8d8u/wDj/hX/ACf8Icaf dir/AP/XOPyxs73VPy+0q3lkkjtxY20YJFKL6YoU9s1uX6i73BtjHuZZDNHZaQ1tHdGW1thQzndg ffK6b1trpv15Rqv1p5Le4jMZgAopA2OQITxq62sMdrHBaykQKd6dVp2ORLIFdGIbyB47q3Cxqd0J 2anfBdbqQ1bfXbaQCID9G1pFF3XG73UhuXUp4rgQLagrKCfUNeS/LbJDZFWwLXvzdsNA1RbeOP8A SKlgjTb/AAkncbeGXY9PxC2uWWtmeaNrFnq+nRXtuamQcmQdjlJiQWXRZqOmQa2TC87272rch6fR j74xDInhFo1TemFBchQfsll7DpiEE9yGs7KK1kmt7arq9W33LHwyJJKVKHT0ltXWdfqhWXnxQ/aP h2wqmHIOByHGmwwWxJQtzpvqsLk1pCOXzpvkgoKT3XmPTtRaMyWzqIGJLUpSmJZRiQmOmpAy/XYH JhuBzKt1H+dMiNxay2NFVe/jk09r+FfWZH9NUO24wxlaDGipwanHezsl1b8Ht0DAMNgW8DhIKDsi JnmMDG1QPKPsA/Z+nAhDXtxfR2iXU6BAhpNGorjSdlUWgvFiMb+lCw5EAbuOu+SjEMSVptVDsCSV /ZORAtbakRBGFFNj9o9aY8kBCacgH5leU2Q/u/T1MAe/oRnfM3SHcuDr/pHveu9zmc6x2KuxV2Ku xV2KuxV2KuxV2KuxV2KuxV2KuxV2KuxV2KuxV2KuxVi/5n+b5/J/kPV/MVvCtxcWUaCCJzRDJPIs KFv8lWkDNir5+0a0h87eaU0TUfzc1JvNcqktBYwvFY+pTm0FvIHjRuA/a4Jy/YxVR/J/Ttfv/wA9 bvSoPM2p6t5f8svJJNPNcOFmaI+mgZObo0bSH/ZJir6v7Yq7FXYqxix/Mnydf+cLjyhY3xuddtFd ruCOORki4faDyhfTDDp9r7Xw/axVk+KuxV2KuxV59+eH5mT/AJe+Szq9kkM+qT3EVtY28/IozMeU hIUq3wxq3Q/axVkvkbU9Z1XyhpGp61FHBqd/bR3FxDEGVEMihgtGLGoB+LfFU8OKuxV5N+a/5r+Y 9A85+XPJnlO1trzWdZYG4FyrssUTuERvgdCvSR2J/ZXFXrC8uI5ULUHIjYV70xVh35leRNV846fa 2Vn5kuvL1vbyGW4ayX95KQPhDPzQqqdf8rFXzH+V/njUNC8/a9rWqeZNR1Lyx5YiuxCZppCL2VmM VtFwJkUNPxaZf5fS5fs4q9Y/KT8+tX1ny75l82+eXttN8vWE0UenGFCpLtzYwJUsZpABH/lftfZ+ yqzfRvzFk/MD8udW1zyJDPBqarcW+nJfokZ+sxpVOjtHxJK/t/63HFWN/wDOPn/K6/8Acx/ysMz/ AFSqfo8XnD1/VqfU4cP91cafa/2GKvY8Vb74q1irsVdirTMFBZjRVqSTsB74q+WP+cgPzT8warph vtA1CbTfK8F2bLS7m3dopdTuowfrE8bjiWtLYAR8vsySTfBz44q97/KfRtU0f8vdFs9WnludUNus 15LM7yP6kvxkFn+L4QwWmKstH3YqwvzF+ZtnpnnzQvJljbjUdV1Zma8SN+Js7ZF5etJQNuf5D+zi rBvz9/5XsNZ0hvy+9f8ARPp/6T9U9Ln9aMjf3vqb+lw4U/3X9rlir2LSBqX6Isv0pT9JiCL66Epx 9fgPVpTanPliqLxV2KuxV5TX/neen/lQa/8Aho4q/wD/0J7+XEZP5beV2JAH6LtRQd6RCtaZrcv1 F3eE+gJimm2ohZUgX0ZD+8ir9qvfKzbfxBXtLS6tpnhiCx6cF/cxCmxI3/HBSOIKdwkVmDMtETrK pPU4KbBvyXQyxTW4agLyAkfLAYoEqO64/Bbs3QqK8Pce2IitglL9K1K/vfrVxcwCOKAlIgQKstNy MJHkmVBiv+AfJS2M+oW+nB7iSUt+8YmjEkk0ycMkkSiCy/S7C0sNPiFrEsCstSqnYbZCV2qNs/qT erPbKQ3+7q9z7YCi7Q9vPdXGoOXQx6aEp/ssNKSByV5bYtE4tHETmhSataDI0vEoxSW91IYixZod nfxcd8SCvEuuluYkBFDIfsZGiEiQQHo6v6ouZ5yrE8TEPsle+SCbCvd2toyBbaJGLbygY80RKHW7 srW5ismhMcsgPpn9kAY8JSZWuikd4Xe2QIgJrEOhP82DhK2DzQS6brCajBM10BYThvrUbU5V/Zpl vRiSE5iMbJwSUR8T9rxyFIsLL5bpLSd0HrOqFljO9Tgo2okEDpdxfzWMM16wtpjskXT6MnwqSEyd DQtXfoT2xNjkxtCBIipe5BJjb92OnXxwEd6khStBIPzK8qVWkfDU+BHvbx5l6UUS4OtNgPWQCczX WB1D4Ypd8t8VdxOKu4nFXcTiruJxV1COvzxV3E4q4gjrirX8MVbpirqHFXcTiruJxV3E4q6h+7FX cT4Yq6hxVwBPQV+WKuoTiqUebh5b/wANagPM/ojQTERfm5IEXpnbc+NfsU+Ln9n4sVeA22g/kL5S 8p6z+ZPkq8fUb7S4pINP9SdnEN7cKY4P3LrG4PJuSs/7HJ1+ziqQ+VND87+Rv+ceNX82aRFLD5i8 wXEc0tyq1ng07cCVe4LVaTn+wsnL9nFWPSQw65d+RNF8p6rqGteYdUVbrzTcJdzMq+q4LxOOkHoI JObf7LFUd/zkLo1j5T846H5e8v3moabDeQrLfXkt3PLGRNMYlpyb/dIRmbf9tcVTDR/zA0eX8/xd 6xrsuneVfLlstrZrcPKgn9CL04+SH9ppZDMar9nFU3/MHyRpVtov5gfmjJZ3Ni17JGvlz6vPJCzi VkjN7IoowWeZ/W9OT/df+tiqh5W/Nfy95Y/5x9u7WDXzd+db2KVnhLySyxz3LlItzsvpw8P2vt4q 891zWPzV8t/lPpllf3Vxpmn+YbyeZPVkk+uXKJHGh5s28Nsq8OMfL943J/s4q9B/Mr82p9J/KHy7 pPkXWJJ+CRWmt6xCZHeBxEG9H1yPhaRvU+yefCLjirD7rVvK9l+a/lq1svMN9beVoI7S71TULqe4 AndB60tFk4lVk4+ktBirJ/8AnIPzr5b82+fPJujnUhH5UjKXN7fMrLGBM4DSKWAZ1WJe2Kvpvy15 i0HX9LTUNCuFudNJ4RyqCEPHb4agVAxV4b+f+u+YV/Mryz5e1LU59B8g3oQ6hqEMhhSRjIxkWSZe lFSOgb7PP1MVY9+U/lCx87/mH5onQ6k35f2XKPSbj65Oq+sroq8ZOVXDIJn6/D8HLFXmF1o003nO 113TpbqbRLvXRpGkxzzu15NAr8WCy7txAPpk/wDFmKvrKH8hPIkckcldRbgQ3B7+4Kmm/Fhy6Hvi qM/OHzNH5P8Ayv1m/gYQzR231SwU1P72UekgHeoB5f7HFXyj5X8gXugflPq/n/Vo5Ekvgll5bsiC Q0sxKNdsvtGZYoK/zv8A5OKu84/l5q/kz8pNMuPM00hv9VuCdI0Tf07JZFEk9xKR8P1l1jij4fsI /wDrcVXp2o+efKXlb/nHOfQ/J+qpeatHbQ299cWiyAJPeOouHd6AK3FnVPi/lxVKrP8ANTRNB/5x 0bSbDXGv/OepRmOZA8jzxveSHl8ZrxMULcB8XLnirBvNmq/mfof5d+W9B1e9l0mx1iSWeWF5HN1M jOvGa4Y7pEAQscHL/dfqt9rFXpP5wfmJq58meWtP8i61NN5dtlWy8wa9YrKSrRokaq8tOSqV9WQj 9r/Y4qo6Hq3knQfzDsNb0P8AMmG18qxRRi70uaa7nuLgiIhzIsiekOch5fb+D7S4q+nNPv7TUbGC +tH52tyglhcgrVD0NGoRir52/Nj83/MM35px+QLfWB5N0KB0Go641FmcMgcsrttGn7Me/wAX2nf9 nFVOz/LzSfzA1eK38r3utTeWoZeeuebtQvJyb0D4Ta2Ub8OYYg+pPw9NP8v4OSrD/NH5beWdT/Pz R/y70BZ49C09EbUommeUR0U3E4Qty9PlH6Uf/GRsVRn5neWLHyr+bui6ZdXWo6N5BmSFrm+a4uJI 5KEmVRJVivRY+P7H2vs4qyj8rNa8jeUvOmsXY/MaPVNDvl9LS9KZ7maYfHyUyck4841+FWj+1irz b8n3/K6fz5ruuecNRaws4Zi2i29xPMJX5yMaSso5uFTgPi+1irL/ADf+Zelat/zkRpb3esvp3k7R Y4SZWMsMM1IjOCY9iecsoj3X7CYq7zP54h1/84r1POWt3OneQLSzkvNEtY5JLSK+WOMcODjgXaZz Iwf9rh6S/s4qhPy28sxXX5Z+avPHm06klhaiWfy+7Xk8RkRVaiAV+JWk9ONXI+L9nFWH6VrX5q6F +Umra4lzcWGl6xdw20WozySNczpRqxWwavpx/aZ5/h9T+7xV9D/841+ZfL835f6ZoEGrnUtbghe7 1COruYvXkL8Hc1AMfPjxriqJ/wCm8r/3/nD6f8HUr8sVf//R6T+WP5a/l3f/AJb+Vby88s6bcXNx pVnLPPLaxNI8jQLzdm41dmP7TYCLTZ5MmH5T/lf/ANSnpPL/AJhI6fqxX4uP5T/lf/1Kelf9Isf9 MVtr/lU35XUp/hPSqHr/AKLF/TDS2Xf8qm/K/f8A51LSadKfVIv6Y0tlcfyp/LEih8qaSf8AoygB +8LXBQWy1/yqj8sKU/wnpNB0/wBDh/XxrjQWy7/lU/5XUp/hLSaDen1SL+mNBbLv+VT/AJX/APUp aT7f6JF/TGgiy0Pyn/K8dPKek/8ASJF/TGgmy7/lU35X/wDUp6V/0iRf0w0F4iuH5U/liBQeU9Jo On+hQV+/jXBQWyt/5VP+V+//ADqek79f9Ei/phoLxFsflR+WKmo8p6TX3s4T+tTitlADyR+Tfr6l GPLmj+tpCq2pD6jF+6Dx+spPwUP7v4vgxWyiLL8tPymv7O3v7XyvpM1tdRJNBKLOJQ0cihkYDiOq mvTFFlW/5VN+V3/UpaTt/wAukX9MaCbLf/Kp/wArv+pS0n/pEj/pjQWy0fym/K49fKWk+3+iRf0x oLZQmq/l7+Uej6Zc6neeVtKjs7SNpZ3FlE9EXckLxav0Y0Fsoz/lU/5X1r/hPSa+P1SL9XGmNLZS XXPLX5IaHe29pqPlvTUvbqN5oIIdLNw7RxFUduFvDJRFaRB8Q+02K2U1sfy2/Ku7tYru28qaX6M6 iSMvp8cbUYV3SSNXT/VZVwUFsqv/ACqn8saEf4T0mh6/6HB+vjXCFsuH5T/leB/yielfP6rFXfr2 wUgls/lT+WLGreVNJJ9rOEfqUYVQWsfl5+UWkaTe6tf+VtLjsdOglu7qQWaMVigQyOQqryNFU7DF UaPyp/LEVp5U0rfY1tIT+tTiqS695X/JDQbi0ttT8tabHc3yyvaww6a9w7rBwErcYIpSAnqx15fz 4qmNh+Wv5T39nFeW3lTTDBMvKMyWIianukiI6/7JcVRH/Kp/yv8A+pT0r/pEi/piqF078uvyg1K1 +tWHlrSLi39SWH1UtY6epBI0Mq9OqSxujf6uKosflX+WY2HlTSRTp/oUB/ErXFWv+VUflgSSfKek 1O5/0SIfqGKuH5Uflh/1Kelf9IsX9MVd/wAqn/K//qU9K/6RIv6YKVC6Z5A/KbUoppLPyvpTpbXE 1rITYwgiW3kMUi/ElSA6/wCywqpa75F/JvQtKuNX1fy3pFrp9qAbic2SEKGYIvwxoT9plHwrgpWr XyP+S91eW9nbeXdHluLq0GoW6JaIQ9qWVRKrcePEl174VVtS/Lr8oNMs3vb/AMtaRb2sZRXme1j4 gyOI0HT9p2VcVRX/ACqf8r/+pT0r/pEi/piq7/lVf5Z9P8KaTt0/0K3NPpKYqt/5VR+WB3PlPSv+ kSIfqGKoOx/Lz8or251C2t/K2ltNpdwtreA2cY4zNBFcgAlfi/c3ETVX+bjiq7U/y6/KDS9Pn1DU fLej2tlaoZJ7iS2iCqo8dvuxBVJLfS/yElivJpPLljaR2Nu13cm/0iexpbpQNMouoITJGOS/FHyx VONa/JP8rdV0q505/LdjaLcJx+s2kKQzoa1DJIoqpBGKvNNJ/IH8mPKHmJINYnv9cu1i+vNa3MbS WlvbqWAmuvQjEax8kcBp34Nwf4fhbCr0bQfIf5Q65pq31l5PsUtJD+6Nzpv1UupUMHWOZEb02Vvh bjgVWu/y7/KGzvbG0m8qaSlxqTvDaKtjCAzRxNMwJRAF+CNjviqNb8qvyxY1byno7HxNjbn9aYqx 3VdG/IXSdQm0+68taZJd2qq95HbaM16LdJByRrl7e3mW3DL8S+u0fwfF9nFU9g/K78qbiCOeHyrp EkEqq8Ti0iKsrCqkVWlCMVSax8tfkbe38Fjb+WNJa5up760iQ6bEAZdLk9G6WpjoOD/Zb9v9jFVf y/5O/JrzHatd6d5S06azQhYbmXTBDFMvZ4DJGizRmn95H8LfzYqmv/Kpfys48f8ACGj8T1H1KD9f GuKsc0jQ/wDnH7V9QjsbDQdIkupTKsCSab6SzGAkSrC80SRzGPi3NYmf4VxVkbflL+Vrfa8o6QfD /QoB+pRiq5Pyp/LFBxTyppKgdB9SgPX5riq1vyl/K5/t+UtIb52cNPuC4qgtZ/Jr8vLzRb+w0/y/ pWmXd3BJDDfR2MLtC8iFRKq/B8SVqtHTBSsS8g/84xeTvLtwLvXXi8zXMcQht457SOG1Qd3NvylE sx/37K74VZhafl7+Ud5e31nD5W0trjTpEiu1NnGAryRLMoB4gH93Ip+HFVe5/K/8rILWWWbynpRg iVpJALGKQ0UVNFCM5NB9lcVQeh+SPyb17T/r2l+WdIuLT1JISW06KOkkLtHIjRyxIyskgZWqmKpi fyq/LE9fKekGnStjbnrt/Jiq3/lU/wCV3Er/AIR0fieo+o2/y/kxVw/Kb8rtv+dR0fb/AJcbf/mj f6cVQmtfl5+UWl6Te6tqPlXSFstOt5bq6kFhCxWKBDI5AVOTUVT8OKoiD8qvyqlhSWLylpBjkVXT /QoehFQaFcVX/wDKpvyurX/COjf9IFt/zRiq7/lVX5ZUA/wppNB0AsoANvkmKtN+U/5Xsat5R0cn xNjb/wDNGKu/5VT+WPHiPKekBfBbKBf+IqMVcfyn/K8tyPlLSeX8ws4VP/CqMVd/yqj8sP8AqUtI NP5rKBv+JKcVcPyo/K8EEeUdHBG4P1C2/wCaMVaH5TflcDX/AAjo3/SBbfq4Yq2fyo/LA7nylo9e lfqNt0/4DFXH8p/yvJ38o6OabCtjbUHy+DFXD8qPyxp/yiekUPY2UBH0AqQPoxVx/Kf8rz18paQa DYfUoKVHSg48fwxVtfyp/LBWqvlLR1J2JFjbjb6ExV5r/gLyP/jP6v8A4f0/6v8A43+pej9Wi4+h /hb6x6dOP919Y/0j0vser8WKv//S7b+Uf/kq/J//AGx7L/kyuKssxV2KuxV2KuxV2KuxV2KuxV2K uxV2KuxV5bqflLWr/X/zAuo7zU9PiuIbcWkVqsYiuyunhSB6sMrS/H+7PpP/AJP2sVY/c6XNFpqQ +YtN1OeZfLOnQeVEtILt2t79IHW4RfQWlre+v6H72f0/3a/3nCKbiqqa55T8yXul+bb3UrS8ufMV tBpDaXcQG4qLuO1h+syWPpELy9YP6jwD/JfFUR5q8seYNNufNVl5ZtLm20eYaDPKkUVzOkqfWbka kYUjkhlnlMKW/wBbit5455Yvh5epKvNVlH5T6cbSPV3hvTcWE8sTW9pHpd7pNrA6x0k+rxX0s7sJ PgaT029JZP8Aiz1MVTb80f8AyXfmH/mCl/4jirKMVYJ5k8vanqn5m6RPBc32m2kOi6gkuo2SoB6j 3dkUgeSWKaMeoqvIEpzb0vh+FXxViOu6XqaahrcMkGpXXnc6ja/4U1URXDRCyVbcKfrESCzhiVlu Tfxyen6jM/NH9WDkqj9O0+1kuNYg1fT7+Tz9LdamLS+9C7MX1eRpvqXpXar9WS0Fq0MfB5VVZ/hd PXxVD6Ndapq36MiVdZsobTyXe2WpXos7yOWHUD9SFIhIi+tex8JmiEfNnZW9Pl8WKp5+T8Mluuq2 yaekNnCLVYdVhtb3T0vH4v6hNpelnSWL4fVlRmWVpePLlF8Kqffmp/5LDzh/2xNR/wCoSTFWUYqw Xzj5f1LVfzC8rSW1xfWFtbWGri41GxVPgaR7H043eWOaNfV4OVUjk/ptx+y2KsE81eX/ADFJ5o1i DUdTuLecNar5Z1f9EahqlysUdvEvO2uLK4t7a3n+tLM9zHJbLyZ+b87ZkSNVVvodbuPzAg1C106W wv7fzHHBPHbadftM+neoY2ubjUi/1Vra4h/eegkXCJW4/bjZkVWaLpUOg+WkhtNOv7bU9I8zC411 I7e8Y/o/9LzvE6UVkuI/q0kcjfVvV/d/G+Kpj9R1jXdQ5va6ouk3nnX1zzju7Rjpv6A4cyCIpY7V 7kcPi4xtL8DfH8OKpZ5q8uayfNGsWs93Jpixtap5SvItI1PVZYLaO3iVRZ3NrdRQwSpcLL68c8PJ +XqSyS27L6aqe+XrOa0/NKYx20uq/Wr2/lu9TuLO/tLmxjKv6cbXMh+p3tpXjBaJHx/dtHIiv6Ty Yq9YxVi/5ff8c/Vv+23qv/UbJiqn+alleXvke9trOCS5uHmsikMKNI5CXsLMQqgn4VUs3+TirzrW PLnnXT9e1/TNIsroWNloc0Wh3tqrLys7i+hnezhlHwpdQRC5t7eNW9T0kt3XFVPzF5fg1LSPMqeW tKvl8qLa6ZL9Re3vITJfwXhkuHtredUnZ1swouPTT97JwX95Oj4qo+Y9IkvNYvBDLPp/l6WyhTyr cNo2sahNAfjE7W31ee2e0vBcfvF9eD1Jo/R4O8KcMVTwWF5afmRbTmKbXry5urUTvdWN/bT2US2q pJNBeg/UWs+SGV7f/f0skPOSXFXr+KsX8n/8pD54/wC23D/3RdNxVGeeLLTb3yrqFrqdvd3VlIqe rFp6u90KSKVkhWOsjPE4WX4AzfB9h/s4q8t8wR+aNf8AKnmzQrG71PzRokuhzyW0+o2BsrpdQjdW gt4mWCy+tF0Du/7jkrpGnL97wxVT86QabqMcNloWkywaWNMnm0u+l0vVby5kuzLIGtrdA0LWUsZV JfrMyty9X91xWJnxVWuvJt7qj6vqWp6Xd3Gpz+RrFBM6Th5NSMd4k0VBTlcUMXOGnNeS/B8eKvUv JekwaT5U0qxhga2EdtEZIX5clkZAXB5ksDzJ+HFUD5o/5S3yb/zG3f8A3TrjFWUYq870LWIvKOq+ ZbHWbK+Mt/qk2pWF3a2V1eR3cNyicFV7eOXjNBw+rtFJw+FI3X922KsQ1hdbv/OtvqVppU+majB5 g09Ghh02+kun08zQpNPPqKyGzS2e3aTnbpHwjXnz5OrOiqb+XvLuqN5l0wXmnXC2Z1Xze1w7xSIg hvLwmFmag4pcIeUL1/eL8UeKpJ5Y8sW2j+XfJkPmbSL7/Dx0Z2vrBLe8nMessIAHubaFXmR/QSRI OSenFJz/ALuaSPkqn3kjy1r93rmjv5ogvnjtNChaP15JwgnW+leBZyrCOW7jtvR9USc35faxVB6P 5P8AMsfkKPUtRjm1B9COq32keVFtzaSyXMjXUSCWYlp5OcU8npLEsP8Aeq37z4MVYzd2+p6donm6 ezM0OjT6JbSCWz07UNItRdi7IYQpcvJI04ib45Y25v8AD/J8Kqc65pmqzLrUvkW0vrTy1KmlrqUU lrfK08iXbtevBayNa3czfVTGt56EkT3K/uVkedWxVfpnlm7uJNLgtLm6u9EuPMEEl3aWOnalo1rb wrpl4svBbiaWX0JZDb+twdLf1vg/vJGxVMtT0kad+ZVs1jZy6sDc6dBFaT2moI2n20USI0tnqKn6 o1tGoM08Mn95N60Tu7yKmKvXcVYv5X/5S3zl/wAxtp/3TrfFU+1TU7TS7GS+u/UFvDx5mGKWd/jY IKRwrJI27b8U+Ffib4cVeOWWnODY3nmbTr6Tybe3/mG9azW2unYXF5qPrafNdWsKG4VGtWn9L1I/ 3csic+Enp4qidBuPMmiyaTPrlvqbQ3OiajaWaCG5u5Vc34ksYbgRLI8dz9RaJec/H4kl5yclfFUb 5A8t6nc6toM+vW18FsPKWgFRcNcxRrqUT3DTCRSVR7qL936iyhpE5fF9vFUs8ueXta0ix8n6vBpF 9NrD2uqrrkchnWWYfV5JIILl5K+mHmSNYPU/u2/usVSG00nXZrHzEun2M4tdU8maqlxY2elahYwf pEiJYIP9KeVru84yToJF/eSfvP8AVRV7/piMmnWqOCrrDGGUihBCioIxVE4q7FXYq7FXYq7FXYq7 FXYq7FXYq7FXYq8q/wCm5/8AOg/+Kjir/9OTfl7/ANDFf4E8t/on/Cv6J/Rlp9S+tfXvX+r+gvo+ tw+H1OHHn6fw8sVT4/8AQ0ldv8H07U+u/wAd8Vd/1lJ/36H/AE+Yq7/rKT/v0P8Ap8xVtf8AoaHf n/g/2r+kP+NMVXf9ZO/9+b/3M8Vd/wBZO/8Afm/9zPFXf9ZO/wDfm/8AczxV3/WTv/fm/wDczxV3 /WTv/fm/9zPFXf8AWTv/AH5v/czxV3/WTn/fm/T+k8Vcf+hnK/8ATG/9zPFXf9ZO/wDfm/8AczxV 3/WTv/fm/wDczxV3/WTv/fm/9zPFXf8AWTv/AH5v/czxV3/WTv8A35v/AHM8Vd/1k7/35v8A3M8V QWs/9DD/AKKuv0v/AII/Rfpt9c+sfpL0vTp8XOu3HFUb/wBZO/8Afm/9zPFWz/0M5X/pjf8AuZ4q 1/1k7/35v/czxV3/AFk7/wB+b/3M8Vd/1k7/AN+b/wBzPFXf9ZO/9+b/ANzPFUFrX/Qw/wChr/8A TH+CP0R9Xl/SP1j9Jej9W4H1vUrt6fp8udf2cVRv/WTv/fm/9zPFXf8AWTv/AH5v/czxV3/WTv8A 35v/AHM8Vd/1k7/35v8A3M8Vd/1k7/35v/czxVsf9DOVH/KG0/7eeKtf9ZO/9+b/ANzPFXf9ZO/9 +b/3M8Vd/wBZO/8Afm/9zPFUFpf/AEMP6U/6M/wR6X1if6x6P6Sp9Z9Q+vyp/uz1eXqf5WKo3/rJ 3/vzf+5nirv+snf+/N/7meKu/wCsnf8Avzf+5nirv+snf+/N/wC5nirf/WTn/fm/T+k8VaP/AEM5 /wB+b/3M8VQVh/0MP9a1L6j/AII+s/WF/Snp/pLl9Z+rw8fVp/uz6r9W6/7q9PFUb/1k7/35v/cz xV3/AFk7/wB+b/3M8Vd/1k7/AN+b/wBzPFXf9ZO/9+b/ANzPFXf9ZO/9+b/3M8VQV5/0MP8AXtP+ uf4I+u+o/wCjfU/SPP1PSf1PSr+16PqcqfscsVRx/wChnNv+UN9/+OnirX/WTv8A35v/AHM8Vd/1 k7/35v8A3M8Vd/1k7/35v/czxV3/AFk7/wB+b/3M8Vd/1k7/AN+b/wBzPFXf9ZO/9+b/ANzPFUs8 y/8AK/8A9B3f6f8A8E/ofgPrnrfpP0+PIU5U/wAqmKpn/wBZO/8Afm/9zPFXf9ZO/wDfm/8AczxV 3/WTv/fm/wDczxVv/rJyh/5Q3/uZ4lCBsv8AoYf69qH1T/BH131E/SXp/pHn6npJ6fq0/a9H0+Nf 2OOKUb/1k7/35v8A3M8Vd/1k7/35v/czxV3/AFk7/wB+b/3M8Vd/1k7/AN+b/wBzPFWz/wBDOf8A fm/9zPFWv+snf+/N/wC5nirv+snf+/N/7meKu/6yd/783/uZ4q7/AKyd/wC/N/7meKu/6yd/783/ ALmeKu/6yd/783/uZ4q7/rJ3/vzf+5nirv8ArJ3/AL83/uZ4q7/rJ3/vzf8AuZ4q03/Qz+3H/B1a 9v0j/wAbbYqp/wDWUu1P8H0/a/3t64qu/wCspP8Av0P+nzFXf9ZSf9+h/wBPmKu/6yk/79D/AKfM VcP+ho67/wCD6d/97f4b4qwT/kOP+Lf+mc/SX+Kv+X30f0j/AIb/AOC+qfo3/nv9c/4qxV//2Q== ------=_NextPart_000_0000_01CAAA59.A3B5EAA0 Content-Type: image/gif Content-Transfer-Encoding: base64 Content-Location: http://maic.jmu.edu/journal/6.1/notes/vandermerwe/table1.gif R0lGODlhUgFAAOYAAJCMjbWys+De3wABAAEBABMTEiEhIC4tLC0sKzk4Nzo4N0dFREZEQ1JQT05M S19dXFZUU2BeXa+trKKgn8rIx1NQT09MS2FeXW9sa398e6OgnxMSEi4sLGFdXUhFRUdEREZDQ3Bs bG9ra1NQUFJPT05LS397e1dUVDo4ODk3Nx4dHYB8fG1qamFeXmBdXUZERCEgIH98fHh1dW9sbJCN jY+MjC0sLLazs7Wysq+srKOgoKKfn8rHx+Xj4+Hf3+De3srIyLWzs+Tj4+Df3/////v7+yEhISAg IBUVFRMTExISEgEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwA AAAAUgFAAAAH/4BEgoOEhYaHiImKi4yNjo+QkZKTlJWWl5iZmpucnZ6foKGio6SNQjg3Nzioqqg4 QamxqrCrq7Sxta4BqjdBu66rvKsBsK2pvrPHrkKLQqnAsQG2rK3Ts9Ssrr3C2LWywdnHv8/LzUHg 4ujZudDgwK633ee558XJN9L0qsyKp6/fvK4F6zXPGK5s0mSRK4ZtW65nwu7h6FHogo2LHGwgQKDx gMePHm14RHBAZEkOJQ8gyGiy5MoDGT+u5LhRpcmLGDlkXMmBJEcbLRZZpGlyJsuUHG3i1Ijx4kil KT9qpPmTZFGRKG3EdLpRZFBFFkVq7TgSJ0yVMktqTcpSLFqSUv+tujTLFGNSkXCvfk3UQefYqne1 ulTbdu1alm2RWnWKdidVsWY5HkW5VxCTUqQGLLqMWRTnRJo7h/qMiLToTqZDn/Zk2lDr1ZleE5IN 2xJty7U7ESh0O7ek3Yp6+4bUW/hwR8WPZ1rCWzmm3qqdU0ouvRL06pWiEzGO/ZB2190n9WYePhLw RNzLDzKdXv32ze4fUY/PaD794M3vw8evX9H3/P2Vtl+Ah7CXCQU/+PbfbJtQMERt1xFY4ICY8PAg bAYWogEGkcywwyA+0JBCITEokIINOLC2yHmF6DBDhx8KgoMCB7w4SAwppIBAipvY14gGMKSggAiO mHBDITfEwAn/eeghokEIMA4ShAIJpODDjVUewKMm2rW2A4eC/BAClKkQMUQNROwwQ4oY6DAIBTMo UIgNIFLwoQZAUKDBDDTQIEgMQ8yAARBEKEkEDQIcwuKEh+w5yBAYkHmkAGiqGQQRGMRopiB0DnLA o3qmSYGdGNTgZ6FEADEDmjQ8WCYhC64XyZOCRGBCqnwSQQENGMTAgwhH7sADEACE4KedhcZgIw8h xKCpfBQSQqsgPoRAJCpm+rlDCEeGoGmCRLjgJqeDCECBmzvk6WINaBKxQqoY+AlAgrAAiFshXw4y Aq8h8PACESGYEEADO6Qg5rNEjEiIAhHEQEGaL2aqAQI0UPAp/w4VUFDDxEQ0cOSnjDbZKJSCkFDD mDwwQMQMMQTRgAZWZlrIDyAs7EIMhKq5sgY62EADD5/eMAIRCexAcAxEMvAwg/w9sq0gQ8iZggYk aKDBAQCAwADHIegwcQ0p3KCzEitE8CLFIYBJXLSDPC1IBTSEMAMQKs8gcNUJ+OAhITxEoDYRCrhg wsOOetgzDUAEPXQKOlSwQwwcgsBDIV0asgORghSQQJVEMDDEiDMgoMAR22pQSAKGBBGCAjQ8bTjJ xrqAA90pFKBrAyYY6hoTvPfuO+9Oql2AAsQTAcLnRIhgQwJHbDgu1ApsKcgNM6DQ+oshWG1jvC6I bYQCNnCoAP8FFYDXtCNuR62DASd6iL3poO9QuPYJQ+yo28T97vsABMiWryBKyBHqPjAE1GHgAAqA wZOeJYAdKIBQgwjADFJQg8utbAc6w1QNHiC2I+joRSkAAgnMJysN2YgInXrQClzggpUZagjeKgQK 8CWIk+2ghS7YgYsEQbd/5Qp1gGMAuEiIiEUNwlGCANmVYhCBBwDMUD/AgOnChALpEWECgqDBDDQQ ASJEAINgosAHVIaDBkANYArAIm94NwAmtJF3/QMeJDZUqxhgDGqF+1D8niYCHegASiPa0A3Kl0FI GNFehPgfEUCmwge0UAQvjGGYaqWpGNVgBjrAIRgFkTKV3cD/jJta3RSZVsJEGiFHMYiBDVLQRSIo IUVDQIGJcCBJItwgBRtQmCAYYAMFfOAHP8iRDTBIss69KAgH+AAMBGGCFgrIP4jYAQyolMoDsDJz R4oa8XAgxUHMgH0oONIuEZACzwkABSk4wCZ3STIX9FJJFOgUIonYiB14MAU2eoA1Y0BHmckpUzoT AQZBmCYONSAFIDghtBRxyDSxLwHVvCYRkpAiH+QoBdwc5Qo40spdLo8BPhBAClBwAKupjQFgisDy MpAqkCGyPb5pwNJC9kz9xOBd9MxpblpHMEn4KD6ppOl77nMr0LDNPbqbp1JrE7dTRaI3DS2PDGoq iFgF6KcS/xqqyLJKSqpylQhMEkRUA2RVrX7VrIo6aym9ytUMqRWrEoIrgeR61aUSaKxobetR47rX uVJOrffa6lnp2h/C6sc0DqhGQNyxDYPUYh7aQAUyGkJZfKQiH9yAiEOq4YFFlOAhA0EIMOZBC8gG wR7VgGwy3OENhXDjFa84RysW4NnIDqSx3TDGMLiRD9UGBCLvAO1iGQKPVXRWEZ8dh26DodzGyjYW pyVHcKGh2MVSFgcBSIhjjzsICdTlJiEpTF1SYpa3hMQsWQnJSDKSGLqElyl3ickJFiGBkRCFKTLx iXqbIhi3bAQBKoALTLLSEbdE5SI/cQlKbOIXkcxXEd7FSv9S1OIUyFRlLBrJilUWgxQEw4QmIHEv SXrylqWEBAKLyIFY5HLeCm/kKEupyU8qzBSUHOW+KlmMXL5rE7X8BMWA7Q5Mg0zkIhvZNkdOspKX fIkhM/nJUA6yk6NM5SoX1spYzrKUtczlLtfVy2AOs5DFTOYy+2bKZk6zmp+65jaL2RkP4QVDlBGO dTA3F0yYMzsOMox/LBYXAUkIP9xM6OpcAMdyQclMDgwTBLdEJihBQo4dPWKMnBctNHY0XaxygUJ7 2jlork6oP03q52y51Kg+zahBnepWY2bVyimrq2fd5CDLmta4lsSt6QPrXPuaCLuOT7B/TWyhUqII RXjEpVD/U+xm/yYRBVCoIwKIgHYdAoiIcGYGrHg+Z3u724PIAAYQ8CfqpSkEl1LdDBI1CDmJ9E8z SJAPMGCCEbEUVVEMARBg4K0dPExN/9YAC7jd62+jWjYgjcCRUtCmTzqwgTuggco8pSYOzYBPNfuA CQAgNUGMCAQx6BMChAVQBuzABgKYwQvsqVODuzyvRPABAp7UwhmuTHRG0EDBODcII4xbEFVSQBIA Jwg5yal+2AaiFGW2xRjqcq0vj/ohZ0CCi9NJYSLA6ece9PQRxaCFSiNCoshdwIQBc0RHj5ogvMUy IpCAem56emCjHvXX6DJeRxcA8TBqggM04OhFF8TNcMCBjxwRIQMcOGihbMAAr68ScjYQgQg08AMG BA5THwI81Olu8IKfmfN093xuRA96NZMeQ6V/+elXs/rUi7n1ooG9670s+1fP/tu1L0Xub49lCyi2 tbftBXXtrNmCKISxtjjGQQAt3WBwl/fEru+kaXxeo5BYLZiOyUkmbOKQsJgoE25LW3ZsAyBD//zo T7/6bx8IADs= ------=_NextPart_000_0000_01CAAA59.A3B5EAA0 Content-Type: image/gif Content-Transfer-Encoding: base64 Content-Location: http://maic.jmu.edu/journal/6.1/notes/vandermerwe/table2.gif R0lGODlhUgFAANUAALWyswABAAEBAC4tLC0sK0dFRE5MS1ZUU6+trGFeXS4sLGFdXUhFRU5LS1dU VB4dHWFeXi0sLLazs7Wysq+srOXj47Wzs+Tj4/////7+/v39/fz8/Pv7++7u7t3d3dzc3MzMzLu7 u6qqqpmZmYiIiHd3d2ZmZmRkZFVVVURERENDQzMzMyIiIhEREQEBAQAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAUgFAAAAG/0CMcEgsGo/IpHLJ bDqf0Kh0Sq1ar9isdsvter/gsHhMbl4mEskErUZPLOm4Gr5e0+N1N0Atsezda3xrAHBtaX5zh24X SxdpgHEAdmxtk3OUbG59gph1coGZh3+Pi40WoKKomXmQoIBud52neaeFiRKStGqMSmdvn3yXgX2z hniZknKkhZibeY+CtxMVRQkR1woRBATaA97f3hHeBAPi5QrlAwTZ5uXrA9nf69zb6ubX2ArZ6wrk 3BEQllijZ24eu3Tc7OHThu3aOIXpvmmj949cQXHoIsRzuE1cQCXWxGnsNg4fPHXyymlMyE4kSnIS LbozyRBbQnEwL35MskDfyP+KNzW6U9ly5Up2LRFadIhyH0WRJrkdRLdTyIsyZAIsuYpVDNckWruG +YqErNguZsOe9WLWSNu1Wd4SkQvXCl2rdbsIKHI3r5S9Svr6hdJX8GAnhcOA6OqC7+G4S9Q+rpJ4 st3IR0KwSIGiQ5IRi4d0QJFiBQkMKbpKxmDYMtitrikvaRx7CuAkb0OcFnF6BAnPHkj8TmFixBAU oRen7iBciPAQGDzo1k0CugfeIoToNh48+xGzrWs7DixeSuXyT84T0Y2hhG8SIlKvCCHCgwkSoTGs KJLaBO/eISAXwgr1jRAgCAPGBwIIKbDXoAnQuTXeGPmBoR4TFULhgWdhrCb/IXrpwWaEZimclhpq GKCAwm/VEXHiEKm1kMKMGJiQAgshsFfjjTmeVl2LGJBo2ncTwnjii0OUIISSQ2SwBJIlzLifFh6O N8KNK6SQIYyfbTkEkBgwWJpxkClRJYhliViEjil6oB8GngkHZorJoThlByEoWR17eWKwp48hjGBc ByCYIASHRbJmhAotpsabcZqR4AGZvnlm4G8YPCrEi33CGaSb3FG3WAfZ6bYYmSIg2tdtfkLH3GnR CddBg5he6lkIoFb3qptgpsChpdFBN4IIggqR6qthjuqdouS5OCNyTjBJhLRY0YZbZrCGOaNxWWo5 oKGHkjZkaiNkWcKsKMzH/x666gI6K40lZElmEau15SsKKIpAnQfzzeonfKmVOAK++jb3YgcswBcn dKkl6AG+JIAGoa8nLDalEKwS+SV0/jVHIGgC4xtyqySUoNt1A7b65YqhNXxaCxJbXON/D/s575lD mHUiv0JUisGlk8JqnK0/B2lqz835ycWFaF47lxGpVRd1aSZuiiKKR/pJ9dVD6LZCcAwHCWtnUWeJ o33F5qymyjLOyGbWWUs9xMMptKDy3COYoKTLV4NQAm8YtN2fB0he+KLJwokgMnwwG4xaxCL7iYJm fprMgnNLr930a0/zBydpbzpoNQpu7pf1fqIL4YGb7YEAX+hCl6AnmZ5xhv8oay/krvvuuRPR4p32 HQq31dWZ4CZz2UUdYZDhvgn4iyuY4NmdQZbYudNcLhnCjHVfzXfAViuPtdVs8b57AAKEByJ4UDvX H2enkba9tikYl7WNK3LN74xKgmC22ENowai4dypqMSsJrGpRuVKgpHhpaXgoqo7/GOg/FFwOTCTo 1mJsZL0XkQBfPzOXEFhwO90F4AUnzF36euci1e2HdJ7KmuiG16g2cY0LGfvQ5pqlth0OwXiJMsKZ OKCBDBgRA0Z0EhKHoIEldiV410uTszizmAkGzEnfQw0WIxi2Cl7ugGVCYGY2Yz0wgMYIZwTBvJjA Ph/2TIdSdCOugkjHL1z/R3FfYBoA28MdIG2naNL5mW+6ox38GM2QxBnBrlBTnECCLTrYgSMYQaRE JOAML26MoybF8KrbbWFV2BJeB+YzOQaJjj2NIxByCrU95kzucvcBAcr2E0vdjDJAOSKQlhJ1SR/q MZOTlCQwMYm99cBqVnx6DpdOCagM8qiGLaKb3Vo0ndNU825DsBbGhilEzXETlHXpAOuwoEcduadQ P4vYoJxXNfb8iHbQhM7rxGcqQ/nGncsjpj65Gcw6ZrIvvRRCC7L1BBkRCAlsOgKTzsjDTWqHjLCK Umfe9b4OAlBXBKzht7wYpOixR6J4AlSi1IeeHPrTjb8kgm+mBJreYEpT/y30F7Ji1ZxQwUk4HkhY jtx0skOGRpsa4+c+A7q5lKLUm0boTAmU8yP4EIw6RJhPczp2GgI5jj0oGJYI5gM2XK7AlZTrZxT5 aRYDVCIYrtiEMeowC02gARHNiCsu0pALTkDDGZVgwBIa8IxhIAMQs6BDWy1gi0q0NRGu8IQyOPGG N5yiDQXQ3LZEI9W9bWpG09zaEBI2JcElE0Wpu9qP5Dmdq/WFr6MwhCdSq9bHxoGwpHhFWs+K1rhO AADJWKteiYCAmtwjHEWpSTpM8pJwmCQj4RhHNpJCE+Ay5CbxcMASEDAOgjBEHv5IbkOE4pJtEOAB MIFHRrrhkohc4x/uQP+HPXwiDuk29AgkuE8GrwbD6e3RaiNQ0p3QCbj9PE94zvmjCVwXNrEOgQIi kYlxHTKRgyykHv9gMEPQcRDrqmMpMvGtPVTyjwMI9cNk6IsH4yMEK+4of9lzzwKVhL/TcLA38srg c0bDQJWdyKQgzrGOy0DS8vR4x0AOchR+XBsiC/nISBbmErx0GCMn+clHFsyVSkM48TgZyljWMY6H AAIQivNEPoPpsIYVsZ7Z8qaSmullsszmNo/VCK/jUuKe2hyYgaBgJoJcirRK1Stc2c2A9uFqJhvg FnIvs+NyX6LHJ1Du+TnQkH5yX7p8qCrXF3ZXQ13VGD3KQ10BqJEOdY7/pSylKpu4xVdDddYWKCgR rlnUsAbxnx8z61jbOi+1Hkyub83rrpB0A5UUQrDrsuVeGzs2vz5CBjrwgSMesYlFdGIej01tEPUy BC/gKV3YxFCs7Lra4NZCX0JgAkPZKEyy+hmBd4Mg6RxNbCMY5xZAHe5612XcH+RNw+izuB7ljWSv 1BYu2WLvgvtFZ/XrWnVI2DBHnyhAJxotF7H5SYNbfC34DhPWane1ABWHZGEr85zEffGSe3sJbwvh uR8ev3vWkF351EKxTU5zcnbFQL4ieM13jpauCIfJj+a50MMo1G8P3eRGh0vSj27xme9w6UwvONTF MvWoh7vqJ7e61puAXHUeb/3rSuArY197V9UCYhSDmIRfgSFbT2hCGrBYw27BTnfeOqQf92jueffO jneQdykIOS886AGO5pKjHy9ZSDg8XPfGO/7xkI+85CdP+cpb/vKYz7zmN8/5egcBADs= ------=_NextPart_000_0000_01CAAA59.A3B5EAA0 Content-Type: text/css; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable Content-Location: http://maic.jmu.edu/journal/6.1/index.css FONT { FONT-VARIANT: normal; FONT-FAMILY: verdana, arial, helvetica, = sans-serif; TEXT-DECORATION: none } BODY { FONT-FAMILY: verdana, arial, helvetica, sans-serif; FONT-SIZE: 10pt } A { FONT-VARIANT: normal; FONT-FAMILY: verdana, arial, helvetica, = sans-serif; COLOR: #000080; TEXT-DECORATION: none } A:hover { FONT-VARIANT: normal; FONT-FAMILY: verdana, arial, helvetica, = sans-serif; COLOR: #000080; TEXT-DECORATION: underline } B { FONT-VARIANT: normal; FONT-FAMILY: verdana, arial, helvetica, = sans-serif; FONT-WEIGHT: bold; TEXT-DECORATION: none } LI { FONT-SIZE: 10pt } P { FONT-VARIANT: normal; FONT-FAMILY: verdana, arial, helvetica, = sans-serif; COLOR: #000000; FONT-SIZE: 10pt; TEXT-DECORATION: none } BLOCKQUOTE { FONT-VARIANT: normal; FONT-FAMILY: verdana, arial, helvetica, = sans-serif; COLOR: #000000; FONT-SIZE: 10pt; TEXT-DECORATION: none } H1 { FONT-VARIANT: normal; FONT-FAMILY: verdana, arial, helvetica, = sans-serif; COLOR: #000000; FONT-SIZE: 14pt; TEXT-DECORATION: none } H2 { FONT-VARIANT: normal; FONT-FAMILY: verdana, arial, helvetica, = sans-serif; FONT-SIZE: 12pt; TEXT-DECORATION: none } H3 { FONT-VARIANT: normal; FONT-FAMILY: verdana, arial, helvetica, = sans-serif; FONT-SIZE: 10pt; TEXT-DECORATION: none } ------=_NextPart_000_0000_01CAAA59.A3B5EAA0--