Restoration of chemosensitivity to drug resistant breast cancer cells through peptide activation of Anaphase Promoting Complex

Restoration of chemosensitivity to drug resistant breast cancer cells through peptide activation of Anaphase Promoting Complex | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Restoration of chemosensitivity to drug resistant breast cancer cells through peptide activation of Anaphase Promoting Complex Cordell VanGenderen, Gabby Mercier, Sarah Valentine, Mathew Lubachowski, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7309461/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The primary care of cancer patients involves improving their outcomes, resulting in longer remission periods and, in some cases, cures. However, many cancers eventually return to a state that is too resistant to therapy. Once cancers become multidrug resistant (MDR) and aggressive, palliative care or more toxic therapies are the remaining options for this growing population of cancer survivors. New approaches to resensitize MDR malignancies to nontoxic therapies are critically important to improve patient outcomes. Previously, we reported that activation of the Anaphase Promoting Complex (APC) resensitized recurrent MDR malignancies in vitro , independent of cancer type, chemotherapy exposure, or species. Specifically, the indirect APC chemical activator, M2I-1, resensitized MDR canine lymphoma cells and human breast cancer cells to first-line therapy. In this study, we applied small peptides that were discovered via a yeast 2-hybrid screen for peptides that interact with the Apc10 APC subunit as direct activators of the APC. The tested peptides indeed increased APC activity, as indicated by reduced APC protein substrate levels, increased (activating) phosphorylation of APC1 S355 , and increased E3 ligase activity, as determined via in vitro ubiquitination assays. One peptide significantly restored chemosensitivity to the MDA-MB-231 breast cancer cell line in vitro and in an in vivo mouse model. The peptides induced mitotic catastrophe, increased DNA damage, and activated apoptotic pathways. Taken together, our results demonstrate that direct activation of the APC via a small APC-activating peptide has anticancer effects both in vitro and in vivo in MDR breast cancer cells, suggesting the potential for targeted treatment to improve patient outcomes. Biological sciences/Cancer Biological sciences/Drug discovery Health sciences/Oncology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 INTRODUCTION Breast cancer is the leading cancer diagnosed in women worldwide ( 1 – 3 ), and while many cases are effectively treated in the short term, many cases are more difficult to treat because both innate resistant breast cancers and cancers can reoccur with acquired resistance to previously effective therapies. The classification of different breast cancer subtypes is complicated and varied but can be broadly classified as estrogen receptor positive (ER + ) or lacking estrogen, progesterone, and HER receptors (triple-negative breast cancer; TNBC; 4, 5). ER + cancers are the most common type of cancer at 70% and are typically treated with antiestrogen therapies, which result in a high rate of remission ( 6 , 7 ). However, when endocrine therapy is stopped after 5 years, the risk of recurrence steadily increases from 5–20 years, with recurrence risk ranging from 10–41% depending on the initial grade of the tumor ( 8 , 9 ). Recurrent tumors may be more aggressive and difficult to treat; thus, our understanding of how recurrent drug-resistant cancers develop and the discovery of new therapeutic targets are of extreme interest and need further study. Many mechanisms have been described that support how cancer recurs, often with increased resistance to therapy. The six most common hallmarks described are i) alteration of drug targets, ii) expression of drug efflux pumps, iii) expression of detoxification mechanisms, iv) reduced susceptibility to apoptosis, v) increased DNA repair capability, and vi) altered proliferation ( 10 ). These events can occur alone or in combination, making treating drug resistance a very daunting task. There are few treatment options for individuals who develop drug-resistant cancers, with palliative care potentially the only recourse ( 11 ). On the other hand, TNBC is innately aggressive at first presentation, is molecularly complex, and has a poor prognosis ( 12 – 14 ). Owing to the lack of hormone receptors, antiestrogen therapy cannot be used to treat TNBC. Therefore, more toxic strategies, such as the use of cytotoxic chemotherapies, are frequently considered. Since TNBC is innately resistant to treatment, higher doses are often needed. New methods are clearly needed to treat patients with treatment-resistant cancers, whether acquired or innate. While many proteins that promote tumor development have been identified over the years, the molecular events leading to cancer development and progression are often very diverse, and no simple target that overcomes MDR in breast or other cancers has been identified ( 15 – 17 ). Inhibitors against a variety of overactive oncogenic proteins have been developed ( 18 – 20 ), but over time, resistance to these treatments often develops, or the treatments are ineffective or toxic in clinical trials ( 21 – 24 ). Many studies suggest that inhibiting mitosis might be a general means to control the growth of cancer cells ( 25 , 26 ), yet even normal cells are at risk of bystander toxicity, thereby limiting their use. The Anaphase Promoting Complex (APC) is integral to the regulated progression of the cell cycle through mitosis and, in turn, is negatively regulated by the spindle assembly checkpoint (SAC; 27, 28). Anti-microtubule drugs that disrupt chromosome alignment along the metaphase plate activate the SAC, block mitotic progression and kill cancer cells in vitro ( 25 ). Inappropriate activity of the SAC is associated with aneuploidy in many malignancies, including breast cancer ( 29 – 32 ), resulting in sustained APC inhibition. Interestingly, overactive SAC components are common in drug-resistant cells ( 33 , 34 ). Although antimicrotubule drugs are very effective, cardiotoxicity is a frequent consequence of therapy ( 24 , 35 ), and mitotic arrest due to SAC activation can be bypassed by the process of mitotic slippage, whereby anaphase is initiated despite concurrent activation of the SAC, leading to cancer progression and drug resistance ( 36 ). Mitotic slippage often occurs when the SAC weakens after prolonged mitotic arrest ( 37 , 38 ) and is associated with ATP depletion, TORC1 inactivation, decreased APC CDC20 levels, and inappropriate APC CDH1 -dependent degradation of cyclin B during mitosis ( 39 , 40 ). Therefore, targeting proper and timely APC activation, by inhibiting the SAC, for example, in cancer cells to manipulate mitotic checkpoints without mitotic arrest is a novel approach showing some promise, as APC mutations and impairment are common in aggressive cancers ( 41 – 44 ). The APC is a large and conserved multisubunit E3 ubiquitin ligase that promotes mitotic progression and G1 maintenance by targeting substrates for degradation via the proteasome ( 45 ). Mitotic progression is driven by the CDC20 APC coactivator, with mitotic exit and G1 maintenance controlled by the CDH1 APC coactivator. Once mitosis is initiated, APC CDH1 becomes active, targeting CDC20 for degradation to prevent mitosis. In recent years, the APC has been shown to play an important role in controlling cancer progression ( 46 – 49 ). Many APC substrate RNAs, including CDC20, are elevated in cancer cells. The observation that CDC20 mRNA and protein levels are elevated in many types of cancers ( 48 , 49 ) suggests that the APC is overactive in cancer cells, leading to the generation of inhibitors of the APC and APC substrates, such as CDC20, PLK1 and Aurora kinases ( 50 – 52 ). In some cases, these inhibitors show promise in preclinical in vitro work, but clinical studies have not achieved the same success rates and continue to be evaluated ( 53 ). The CDC20 inhibitors TAME and APCIN also show promise as anticancer agents, with clinical trials underway ( 54 , 55 ). An alternative interpretation of CDC20 overexpression is that this represents APC impairment, since increased CDC20 mRNA is generally accompanied by the accumulation of many APC substrate mRNAs ( 47 , 56 – 60 ). This implies that the APC is dysfunctional in potentially aggressive cancer cells and is not able to properly target its oncogenic substrates for degradation. Recently, many reports have been published that are consistent with the idea that APC mutations and impairment are indeed associated with cancer progression ( 47 , 61 – 63 ). In fact, CDC20 is now considered to be associated with tumor progression, whereas CDH1 is associated with tumor suppression, which is consistent with reports showing that mutation to CDH1 is associated with genomic instability and cancer development ( 61 – 63 ). It has now been established, at least in vitro , that chemicals that inhibit SAC components push aggressive cancer cells into premature mitosis and cell death ( 64 – 67 ). Thus, it has been hypothesized that when cells carrying high loads of chromosome instability (CIN) are prematurely pushed into mitosis, they undergo unsustainable mitosis and experience mitotic catastrophe, inducing cell death ( 47 , 62 ). Similar to inhibitors against mitotic agonists overexpressed in cancer, which have unfortunately been unsuccessful in clinical trials ( 53 ), the recent development of SAC inhibitors, while showing some promise in clinical trials, still require further development ( 68 , 69 ). SAC inhibitors, however, are not expected to block, but rather promote mitosis. It is becoming clear that the APC CDH1 complex is required for genomic stability and cell health in noncycling cells, but we do not fully understand how this occurs. In our published yeast work, we have shown that the yeast APC is required for stress response and a full lifespan ( 70 – 75 ), suggesting that the APC plays an important role in maintaining cell homeostasis. In support of this, we observed that chemical activation of the APC using M2I-1 ( 42 ) in drug-resistant MCF7 human breast cancer and canine OSW lymphoma cells resensitized them to drug treatment ( 76 ). M2I-1 activates the APC indirectly by inhibiting the SAC, prematurely releasing CDC20 to activate the APC, promoting progression through mitosis. However, M2I-1 is not predicted to function in differentiated or senescent cells when APC CDH1 is active. Since CDH1 is required for G1 maintenance and entry into G0 ( 77 , 78 ) and is tightly associated with genome stability ( 79 – 80 ), it is imperative to develop methods to activate the APC CDH1 complex. To identify peptide APC activators, we used a novel dual screen in which random peptides were first selected by recruitment to Apc10 bound to reporter promoters in a yeast 2-hybrid screen. These peptides were then screened for those that could increase the replicative lifespan of yeast (Harris et al., unpublished). In this study, positive peptides identified in the yeast screen were cloned into the human pcDNA3.1 expression vector. These peptides were then stably transfected into human MDA-MB-231 TNBC cells and human MCF7 ER + sensitive and MCF7 cells selected for resistance to tamoxifen (TAM). These cells were used to determine the effects of APC activation on tumor cell progression and the reversal of drug resistance in vitro and in vivo . MATERIALS AND METHODS Cloning yeast peptide sequences into the human expression vector pcDNA3.1 Polymerase chain reaction (PCR) amplification was performed on the peptides shown in Fig. 1 A, using the original yeast plasmids as a template (originally described in 81). The orientation of the peptide-expressing constructs from the N-terminus was as follows: SV40 nuclear localization signal (NLS, sequence PKKKRKV), fatty acid oxidation complex (FadB), hemagglutinin (HA, sequence YPYDVPDYA) tag, thioredoxin N-terminus (TrxA), peptide, and TrxA C-terminus. All PCR reactions utilized the same 3’ primer, which bound to the C-terminus of the TrxA C-terminal sequence. Two 5’ primers were utilized in separate reactions to produce two distinct insert sequences from the same original sequence. One 5’ primer bound 3’ of the FadB sequence (producing a DNA fragment without the NLS or FadB sequences), and the other primer bound 5’ of the NLS (producing a DNA fragment with the NLS and FadB sequences). All the amplified sequences contained the HA-TrxA-peptide-TrxA. After purification, the insert sequences were ligated into the pGEM-T Easy vector (Promega) via TA ligation following the manufacturer’s instructions and transformed into the Escherichia coli ( E. coli ) strain DH5α (Thermo Fisher Canada). The transformed E. coli were then plated onto Luria broth (LB)-agar plates (0.5% w/v yeast extract, 1% w/v tryptone, 171 mM NaCl, 0.2% agar) supplemented with the antibiotic ampicillin (0.1 mg/mL), 20 mg/mL X-gal (5-bromo-4-chloro-3-indolyl-β-D-galactopyranoside) and 100 mM IPTG (isopropyl β-d-1-thiogalactopyranoside) for blue/white screening. White bacterial colonies were selected for plasmid purification via the phenol‒chloroform method. Insert sequences within the pGEM-T Easy vector were verified by restriction digestion using BamHI (Thermo Fisher) and XhoI (Thermo Fisher). The purified DNA bands were then ligated into pcDNA3.1 (Thermo Fisher) previously digested with BamHI and XhoI using T4 ligase. The plasmids were then transformed into DH5α, and the plasmid DNA was purified via the phenol‒chloroform extraction method. Sanger sequencing performed by the National Research Council (Saskatoon, SK, Canada) confirmed proper insertion of the peptides into pcDNA3.1 and confirmed the correct reading frames between epitope tags and proteins. Cell culture and plasmid transfection The TNBC cell line MDA-MB-231 was obtained from the American Type Culture Collection (ATCC). The cells were grown in Dulbecco’s modified Eagle’s medium (DMEM, Invitrogen) supplemented with 10% fetal bovine serum (FBS, Invitrogen) and 1X Ab/Am (100 U/mL penicillin, 100 mg/mL streptomycin, 0.25 µg/mL amphotericin B [Invitrogen]), according to previous methods ( 76 ), unless otherwise stated. Incubators were maintained at 37 ° C and 5% CO 2 . The cells were transfected via Lipofectamine 3000 (Thermo Fisher) following the manufacturer’s protocol. Stable integration of the plasmids was achieved by persistent exposure to the neomycin analog geneticin (Invitrogen) in 2%, 3%, or 4% increments for 48 hr each. Drug-sensitive MCF7 human breast cells and MCF7 cells resistant to tamoxifen (TAM) were obtained from the American Type Culture Collection (CRL-3435; ATCC). TAM resistance was maintained in 1 µM TAM for 8–12 months. The cells were cultured in high-glucose DMEM (Gibco) supplemented with 10% FBS and penicillin–streptomycin (Gibco) in 75 cm tissue culture flasks (Corning) in a humidified atmosphere (5% CO 2 ) at 37°C. Western blotting Western blotting was performed as previously described ( 82 ). The cells were harvested from the cell culture dishes in 1 mL of 1x phosphate-buffered saline (PBS; 0.067 M PO 4 ) with a rubber policeman. The cells were then pelleted at 10,000 rpm for 2 minutes, after which the PBS was removed. The pellet was then resuspended in 100 µL of 1X radioimmunoprecipitation (RIPA) buffer (20 mM Tris-HCl [pH 7.5], 150 mM NaCl, 10% glycerol, 0.5 mM ethylenediaminetetraacetic acid [EDTA], 0.1 mM Egtazic acid [EGTA], 0.1% sodium dodecyl sulfate [SDS] plus 1X mammalian cell anti-protease cocktail [Millipore Sigma]). The cells were then lysed via pulse sonication and centrifuged at 18000 rpm and 4 ° C for 5 minutes. The supernatant was decanted, and the pellet was discarded. The commercial Bradford assay (Bio-Rad) was used to quantify the protein content in the lysate on the basis of a standard curve in a SmartSpec 3000 (Bio-Rad). A lysate aliquot was then diluted into 100 µL of RIPA buffer (to reach the desired concentration), and the protein sample was denatured with 5x loading buffer (5x loading buffer [250 mM Tris HCl pH 6.8, 10% w/v SDS], 15% v/v 2-mercaptoethanol, 30% v/v glycerol, and trace bromophenol blue) and boiled for 2 min. Lysates were then separated through an acrylamide gel between 7.5% and 15% at 150 V. The gel was then transferred onto a nitrocellulose membrane (Bio-Rad) in 1X transfer buffer (0.19 M glycine, 25 mM tris base, 10% v/v methanol) at 90 V for 1.5 hrs. After transfer, the membranes were stained with Ponceau S (0.1% (w/v) Ponceau S (Thermo Fisher) in 1% v/v acetic acid) as a nonspecific protein stain and scanned to document the relative loads. Ponceau S was then washed from the membrane with two washes in 1x PBS with 0.1% Tween 20 (PBST) for 5 min each, with agitation. The membrane was then blocked with 5% w/v skim milk in 1X PBST solution at room temperature (RT) for one hr. The primary antibodies were incubated with either 1:1000 (total protein) or 1:500 (phospho-protein) dilutions in 5% skim milk in PBST overnight at 4 ° C. The membranes were then washed 3 times for 10 min in 5% skim milk in PBST at RT. The membrane was then incubated with a 1:10,000 dilution of secondary antibody-horseradish peroxidase (HRP) conjugates in 5% skim milk/PBST solution for 1 hr at RT. Three 10 min washes were then performed with 1X PBST. This was followed by a 5 min incubation with enhanced chemiluminescent (ECL) reagent (Bio-Rad), imaging with a VersaDoc, and analysis with QuantitiyOne software (Bio-Rad; version 4.6.9). Trypan blue Trypan blue was used to determine the number of viable cells in a cell suspension, as previously described ( 83 ). Six-well culture plates were seeded with 0.3 × 10 6 cells and grown in DMEM. For counting, the medium was removed, replaced with TrypLETM Express and centrifuged at 2000 × g for 3 minutes. The pellet was resuspended in 1X PBS. One part of the cell suspension was combined with one part 0.4% trypan blue and incubated for 3 minutes at RT before being counted via a hemocytometer. A total of 10 µL of the trypan blue cell mixture was added to the hemocytometer, and under a light microscope, the unstained (viable) cells with an intact plasma membrane and the stained (nonviable) cells with a breached membrane were counted separately. The concentrations of viable and nonviable cells in a 1 mL cell suspension were used to determine the percentage of viable cells via the following equation: % viable cells = (number of viable cells per mL/total number of cells per mL) × 100. MTT assay MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide; Millipore Sigma) tetrazolium reduction to formazan crystals was used to determine mitochondrial activity, a proxy for cell viability within a given cell population, as described previously ( 83 ). Triple-negative MDA-MB-231 cells were plated in a 6-well plate at 40% confluence and treated with 1 µM DOX hydrochloride (Pfizer; Brandon, MB, Canada) for 48 hours in FBS-supplemented DMEM. The MTT solution was added to phenol red-free DMEM to a final concentration of 0.45 mg/mL. Phenol red-free medium was used to prevent phenol red and MTT absorption spectra from overlapping during the formazan absorption readings. The MTT solution was supplemented with 10% FBS and incubated at 37°C with 5% CO 2 for 2 hours. The MTT/FBS mixture was then removed and replaced with 1 mL of 99.5% dimethyl sulfoxide (DMSO) for solubilization. The absorbance of the resulting solution was measured at λ570 nm with a SmartSpec 3000 spectrophotometer (Bio-Rad; Bio-Rad Laboratories, Hercules, CA, United States). In vitro ubiquitination assay Coimmunoprecipitation (Co-IP) : Co-IPs were performed as previously described ( 81 ). Whole-cell lysates were prepared by incubating cells with 300 µL of Co-IP lysis buffer (50 mM Tris pH 7.5, 150 mM NaCl, 2 mM MgCl 2 , 0.5% NP-40, 10% glycerol, and 1 mM DTT) for 30 min at 4°C, followed by centrifugation at 15,000 × g for 10 min, with retention of the supernatants. The protein content was then determined via a Bradford assay, with 1 mg of protein diluted in 500 µL of Co-IP lysis buffer. The lysates were then precleared by incubating them with 60 µL of a 50/50 agarose bead mixture (30 L total beads) for 30 min at 4°C with rotation. The lysates were then centrifuged at 2,000 × g for 2 min, after which the supernatant was retained. The lysates were then incubated overnight with 1.5 µL of anti-CDC27 antibody (Abcam, ab10538). A total of 20 µL of a 50/50 Sepharose A bead mixture was added, and the mixture was incubated at 4°C for 2 hr with rotation. The mixture was subsequently centrifuged at 2,000 × g for 2 min, after which the supernatant was retained as the unbound sample. The beads were washed 3 times by resuspending them in 1000 µL of Co-IP lysis buffer, followed by centrifugation at 2,000 × g for 2 min. The Sepharose A bead-antibody conjugates were finally resuspended in 10 µL of 10 mM HEPES, pH 7.4. In vitro ubiquitination : For the ubiquitination reaction, based on a previous method ( 84 ), 50 nM E1 (E-305-025, R&D Systems), 0.05 mg/mL E2 (E2-654-100, R&D Systems), 10 µL of purified APC, 1X energy regeneration system (B-10, R&D Systems), 5 ng/mL securin (ab87664, Abcam), and 1.25 mg/mL ubiquitin (U-115-01 M, R&D Systems) were mixed together in a final volume of 20 µL and then incubated for 1 hr at 37°C. The reaction was stopped by the addition of SDS‒PAGE sample buffer and incubation at 95°C for 5 min. Reverse transcriptase PCR (rtPCR): RNA extraction and cDNA synthesis rtPCR was conducted as previously described ( 85 ). The MDA-MB-231 cells were grown to 90% confluence in 10 cm plates (~ 8 × 10 6 cells), after which the medium was removed, and 350 µL of lysis buffer was added (10 mM Tris pH 7.4, 0.25% IGEPAL CA-630, and 150 mM NaCl). The cells were then scraped into a 1.5 mL microcentrifuge tube via a rubber policeman. RNA was extracted and purified via the EZ Tissue/Cell Total RNA Miniprep Kit (Bio Basic) following the manufacturer’s protocol. Briefly, the lysate was transferred to a gDNA Eliminator Column, kept at RT for 1 minute and centrifuged at 9,000 × g for 1 minute at RT. Next, 250 µL of 95% ethanol was added, and the sample was centrifuged at 9,000 × g for 1 min at RT. A total of 500 µL GT solution was then added to the pellet, followed by centrifugation at 9,000 × g for 1 min at RT. Then, 500 µL of NT solution was added, and the mixture was centrifuged as described. The column mixture was then transferred to an RNase-free centrifuge tube and dried (3–5 minutes). RNase-free water was added, and the mixture was centrifuged at 9,000 × g for 2 minutes. To quantify and determine the integrity of the RNA, the sample concentrations were measured via a NanoDrop Spectrophotometer (NanodropTM One/OneC Microvolume UV‒Vis Spectrophotometer, Thermo Fisher) to determine the A260/280 ratio. For cDNA synthesis, PCR was performed with 5 µg of RNA, 0.2 µg/µL random hexamer primer (Thermo Scientific), 1 µL of 10 mM dNTP mixture (Thermo Fisher), and nuclease-free water for a total volume of 14.5 µL. The mixture was vortexed before the addition of 1X reverse transcriptase buffer, 0.5 µL of RiboLock RNase Inhibitor (Thermo Fisher), and 1 µL of Maxima H Minus Reverse Transcriptase (200 U/µL; Thermo Fisher). The PCR thermal cycler was programmed with the lid temperature held at 95°C, followed by incubation at 25°C for 10 minutes, 50°C for 30 minutes, 85°C for 5 minutes, and 4°C for 5 minutes. The product was removed, and 30 µL of nuclease-free water was added for a final volume of 50 µL. PCR was performed on the cDNA via primers specific for the peptide insert (forward primer: 5’ATCCTCGTCGATTTCTGGGC 3’, reverse primer: 5’AATCGGGGCGATCATTTTGC 3’) and control primers specific for the EFEMP2 extracellular matrix (forward primer: 5’GCCCAAACCTGTGTCAACTTC 3’, reverse primer: 5’CGGTTCTCAGAGACCTGGATG 3’). The PCR was performed with 5X Phusion Hot Start buffer and final concentrations of 200 µM dNTPs, 0.02 U/µL Phusion Hot Start II DNA Polymerase (Thermo Fisher), 100 ng/µL template DNA, and 0.5 µM of each primer. The PCR thermal cycler was programmed as follows: initial denaturation at 98°C for 30 seconds; denaturation at 98°C for 10 seconds; primer annealing at 61°C for 30 seconds; extension at 72°C for 30 seconds; and a final extension at 72°C for 10 minutes. The PCR products were then separated through an 8% polyacrylamide gel to obtain higher resolution bands. Immunofluorescence Immunofluorescence was conducted according to previously described methods ( 86 ). Briefly, the cells were grown on coverslips to 60% confluence. The cells were then fixed by incubation in 4% paraformaldehyde for 10 min at RT, washed twice with 1X PBS and stored at 4°C. The cells were permeabilized by incubation in 0.5% Triton X-100 for 10 min followed by 0.05% Triton X-100 for 5 min. The cells were incubated with a 1:200 primary antibody dilution in 1% bovine serum albumin (BSA) for 1 hour in a humidity chamber at RT. The cells were washed with 0.05% Triton X-100 and then incubated with a 1:200 dilution of secondary fluorescent antibody in 1% BSA for 1 hour in a humidified chamber at RT. The cells were then washed with 0.05% Triton X-100 for 5 min at RT. 4′,6-Diamidino-2-phenylindole (DAPI) droplets were then placed onto coverslips with adhered cells, with the edges sealed with nail polish and stored at 4 ° C. The slides were imaged using an Olympus BX-51 microscope equipped with Infinity software v.5.0.3 (Lumenera, Ottawa, Canada). Wound healing assay As previously described ( 85 ), stably transfected MDA-MB-231 cells were grown in a 6-well plate to 50% confluence and treated for 48 hours with 0, 0.25, 0.50, 0.75 or 1.0 µM DOX or 10 or 20 µM Mad2 inhibitor-1 (M2I-1; Cayman Chemicals; Ann Arbor, MI, United States) diluted in DMEM supplemented with 10% FBS. After 48 hours, a scratch was created halfway down the middle of the well via a cell scratcher. The medium was removed, and an image of the well was taken via a light microscope. Fresh medium was added once the initial hour 0 image was captured, and the cells were incubated at 37°C with 5% CO2 for 5 hours. The same process was repeated at hours 5, 10, and 24. The distance traveled by the cells over time was quantified by measuring the width of the scratch at each interval via ImageJ (National Institute of Health; Java 1.8 0_45). Xenotransplantation of cancer cells Transfected MDA-MB-231 cells were seeded in 15 cm plates and grown to 60% confluence in DMEM according to our previous methods ( 85 ). The medium was then removed, and the plate was washed in 1X PBS, which was replaced with TrypLETM Express and incubated at 37°C with 5% CO2 for 5 minutes. The cell mixture was then spun down at 2000 × g for 3 minutes, and the pellet was resuspended in 1 mL of 1X PBS. Centrifugation was repeated, and the pellet was again resuspended in 1 mL of PBS to create the injectate. The number of viable cells from each cell line was counted via Trypan blue prior to injection to ensure that the same number of viable cells caused tumor growth in each treatment group. As previously described ( 85 ), approximately 1.0 × 10 6 live cells were subcutaneously injected into the left lower quadrant of the mammary fat pad of female NOD SCID gamma (NSG) mice (NOD. Cg- Prkdcscid Il2rgtm1Wjl /SzJ; Jackson Laboratory, Sacramento, CA, United States) via a 0.5 mL syringe with a 27 G × ½ hypodermic needle. The mice were used between the ages of 8 and 14 weeks and had ad libitum access to food and water, as monitored by the Lab Animal Service Unit (LASU; University of Saskatchewan). The mice were 22.3–25.5 g according to the Jackson Laboratory web site ( https://www.jax.org/jax-mice-and-services/strain-data-sheet-pages/body-weight-chart-005557 ). The injection site was disinfected prior to injection via antiseptic isopropyl alcohol pads, and the mice were sedated via isoflurane anesthesia. Obvious tumor growth was generally observed beginning at 5 weeks after cell injection. Treatments began once the tumors were palpable, and measurements began once they reached a volume of ~ 50 mm 3 . Measurements were performed via digital calipers and were performed weekly until the mice were euthanized. Body weights were also measured weekly. The equation used for the volumetric tumor measurements considered length, width, and height as follows: 𝑉 = ( 87 ). The treatments included DOX, M2I-1, and APCIN (Millipore Sigma). The mice were euthanized by anaesthetic overdose, with cervical dislocation serving as a secondary method, according to the University Animal Care Committee and the Animal Research Ethics Board at the U of Sask, in accordance with the ARRIVE principles. Once the mice were euthanized, the tumors were excised, placed in 95% fetal bovine serum (FBS)/DMSO and placed in liquid nitrogen for future use. All experiments were approved by the University of Saskatchewan animal ethics office, following the guidelines of the Canadian Council on Animal Care and ARRIVE (Animal Research: Reporting of In Vivo Experiments). Statistical methods Unpaired t tests were performed between the control cell line and individual peptide-expressing cell lines to determine statistical significance. Statistical analysis was performed via GraphPad Prism (version 8.4.1). Parametric testing was performed to determine whether the datasets were normally distributed, followed by one- and two-way analyses of variance (ANOVAs) via GraphPad Prism Software (version 9.3.1). Post hoc testing was subsequently performed via Tukey’s test with an alpha set at 0.05, unless otherwise stated. * = P < 0.05, ** = P < 0.01, *** = P < 0.001. In vitro experiments were performed in triplicate, and in vivo experiments were performed once, with an n of at least 4. RESULTS Yeast APC binding and activating peptides activate the APC in MDA-MB-231 and matched MCF7 drug-sensitive and drug-resistant cells We hypothesized that activating the APC would increase cell health and maintain genomic stability ( 47 ). We previously reported that APC activation via M2I-1 resensitized MDR canine and human cells to drug treatment ( 57 , 76 ). To test whether the APC-binding and activating peptides also resensitized MDR human breast cancer cells to therapy, we cloned the yeast peptides into the human pcDNA3.1 expression vector. Since the APC is highly conserved from yeast to humans, we expected that at least some of these peptides would have conserved activity in human cells. We first tested the ability of the pcDNA-peptide constructs to reduce the protein accumulation of APC substrates in MDA-MB-231 triple-negative breast cancer (TNBC) cells. All 7 cloned peptide constructs were stably expressed in MDA-MB-231 cells. MDA-MB-231 cells are aggressive, metastatic, drug-resistant breast cancer cells and serve as excellent models for studying unresponsive breast cancer ( 86 ). Protein lysates were prepared from the stably transfected cells and examined by western blot analysis of the protein levels of APC substrates. The APC targets substrates for ubiquitin- and proteasome-dependent degradation; APC impairment results in increased substrate protein levels, whereas APC activation results in decreased substrate levels ( 57 , 76 ). We found that cells expressing the 20 amino acid C13-3 and C43-4 peptides displayed from the TrxA backbone presented decreased levels of the APC substrates examined (Fig. 1 A-D; average levels of protein expression are shown in Table 1 ; uncropped blots are shown in Supplemental Fig. 1A ), indicating that these peptides activate the APC in human MDA-MB-231 cells. Both the mRNA and protein levels of APC substrates are often reported to be elevated in cancer cells ( 57 , 76 , 89 , 90 ), suggesting that APC impairment is linked to cancer progression ( 47 ). This is the first example, to our knowledge, of a peptide believed to bind an APC subunit that can activate the APC and provide anticancer activity against an aggressive cancer cell line. To obtain further evidence that the peptides activate the APC, we evaluated the level of APC1 phosphorylated at S355 (APC1 ph ) in cells, as APC1 ph is a marker of active APC ( 76 , 91 , 92 ). MCF7 Sens and MCF7 Res cells stably expressing C13-3, C43-4, or pcDNA3.1 were subjected to western blotting with antibodies against APC1 ph and total APC1 (APC1 tot ; Fig. 1 E, top panel; uncropped blots are shown in Supplemental Fig. 1B ). The ratios of APC1 ph to APC1 tot were determined ( Fig. 1 E, bottom panel), which revealed a more than 5-fold increase in APC1 ph when the peptides were expressed in MCF7 Res cells, strongly indicating that the peptides directly activate the APC. Next, we used a direct in vitro assay that measured the ubiquitination of the APC substrate securin. For this assay, the APC was coimmunoprecipitated from MCF7 Sens and MCF7 Res cells via antibodies against CDC27. A control experiment using APC obtained from MCF7 Sens cells revealed that only when E1, E2, APC, ATP, Ub and securin were added to the reaction did we observe ubiquitinated securin (Fig. 1 F). We then compared APC activity in MCF7 Sens and MCF7 Res cells and observed that the APC was indeed less active in MCF7 Res cells, with approximately 60% more secuirin ubiquitinated in sensitive cells (Fig. 1 G, top panel; quantitation shown in the lower panel). Finally, to determine whether the peptides directly activate the APC, we assessed APC activity in MCF7 Res cells expressing either pcDNA3.1 or cells expressing C13-3 or C43-4. We observed that peptide-expressing cells harbored increased levels of APC activity, particularly when C43-4 was expressed (Fig. 1 H, top panel; quantitation shown in the lower panel). This finding demonstrates the conservation of these peptides. Table 1. Altered protein abundances resulting from peptide expression. Summary of the observed alterations in protein accumulation resulting from C13-3 and C43-4 expression. Peptide activation of the APC resensitizes resistant cells to drug treatment and reduces the expression of markers of drug resistance We next asked whether APC impairment is linked to cancer progression ( 57 , 76 ) and whether APC activation via peptides C13-3 and C43-4 in aggressive cancer cells resensitized them to chemotherapy. Here, we used an MTT assay to show that the MCF7 Res cells are indeed MDR, as the MCF7 Res cells selected against TAM are less sensitive to DOX than the MCF7 Sens cells are (Fig. 2 A). The difference did not reach significance, but trends were consistently observed. We next treated MCF7 Sens and MCF7 Res cells expressing pcDNA, C13-3 or C43-4 with 1 µM DOX for 48 hours and assessed cell viability via an MTT assay (Fig. 2 B). Survival was normalized to that of the pcDNA control, which revealed that, compared with MCF7 Sens cells, MCF7 Res cells are more sensitive to DOX when the peptides are expressed. As above, the difference did not reach significance, but trends were consistently observed. We next assessed the viability of MDA-MB-231 cells expressing the constructs via the trypan blue dye exclusion method (Fig. 2 C). We observed that the peptides alone reduced the viability of MDA-MB-231 cells, with the reduction in C43-4-expressing cells reaching significance. The MDA-MB-231 cells expressing the constructs were then treated with 1 µM DOX for 48 hours. C43-4, but not C13-3, significantly increased the killing of these cells by DOX (Fig. 2 D). MDA-MB-231 cells were next subjected to DOX dose titration in 96-well plates, and survival was measured via an MTT assay. This experiment revealed that 231 cells were more sensitive to most of the DOX doses tested when they expressed C13-3 or C43-4, with C43-4 having the greatest effect (Fig. 2 E). We previously reported that the killing of MDR cells coincided with a reduction in MDR protein markers, such as MDR-1 and BCRP ( 57 , 82 , 83 , 86 ). We show here that C43-3, but not C13-3, modestly reduced both MDR-1 and BCRP protein levels in MDA-MB-231 cells (Figs. 2 F- 2 H; uncropped blots are shown in Supplemental Fig. 1C ). The consistent decreases observed did not reach significance. These observations indicate that peptide-induced activation of the APC that reduces APC substrate levels resensitizes MDR cells to DOX. The C13-3 and C43-4 peptides are expressed in 231 To determine where the peptides were expressed in cells, we used immunofluorescence microscopy to visualize the localization of the HA-tagged peptides. Antibodies against HA did not signal in pcDNA3.1 control cells but did signal in C13-3- and C43-4-expressing cells. In MDA-MB-231 cells, both peptides predominantly localized to perinuclear structures, with some nuclear punctate staining (Fig. 3 A). Notably, these constructs did not contain the NLS that was part of the original yeast construct, as preliminary studies using MDA-MB-231 cells revealed that constructs lacking the NLS were more active at reducing APC substrate levels (data not shown). Nevertheless, nuclear staining, where the APC is localized ( 93 ), was observed, and this appeared sufficient to promote APC activity. We next assessed peptide mRNA expression as a measure of gene expression. mRNA was extracted from MDA-MB-231 cells, converted to cDNA and used in PCRs with primers designed to amplify the thioredoxin backbone from which the peptide is expressed. As a control, plasmid DNA was used as a template in the PCRs. Primers against the EFEMP2 gene were also used as loading controls. Our observations revealed that the peptides were indeed expressed (Fig. 3 B). The peptides inhibited MDA-MB-231 cell migration To investigate whether activation of the APC interferes with cell migration, we performed wound healing assays with metastatic MDA-MB-231 cells expressing C13-3, C43-4 or pcDNA3.1. For this assay, a scratch was made in a lawn of confluent cells. The plate was left to incubate, and over a period of 24 hours, MDA-MB-231 cells with stably integrated pcDNA3.1 migrated into the gap and filled the void (Fig. 4 A, top panels; a representative experiment is shown from 3 biological replicates). The cells stably transfected with C13-3 or C43-4 were also allowed to migrate back into the wound over a 24-hour period. Our results revealed that while MDA-MB-231 cells stably transfected with pcDNA3.1 almost fully migrated into the void space (Fig. 4 A, top panel), cells expressing C43-4 were almost entirely devoid of migratory activity (Fig. 4 A, bottom panel), whereas C13-3 clearly slowed cell migration (Fig. 4 A, middle panel). The quantification of cell migration in the presence or absence of 0.5 µM DOX suggested that the peptides work additively with DOX (Fig. 4 B). This effect was observed with a variety of different DOX doses (Fig. 4 C). Finally, to gain further evidence that APC activation inhibits cell migration, we performed experiments in the presence of 10 or 20 µM M2-1, an indirect APC activator ( 42 ). We observed that M2I-1 alone inhibited MDA-MB-231 cell migration and worked additively with the peptides (Fig. 4 D). Taken together, these observations indicate that the peptides potentially act in a pathway that differs from those impacted by DOX and M2I-1. C13-3 and C43-4 increase the mitotic index of cells, inducing mitotic catastrophe, DNA damage and apoptosis One hypothesis to explain how APC activation could be anti-proliferative for cancer cells is that APC activation pushes aggressive cancer cells with high loads of chromosome instability (CIN) into premature mitosis, which may be unsustainable, leading to death ( 47 , 62 ). We previously tested this hypothesis on MCF7 Res cells arrested in mitosis in the presence or absence of M2I-1 and then released into the cell cycle in fresh media ( 76 ). We observed that cells progressed more rapidly through mitosis when treated with M2I-1, which correlated with cell death. To test whether the peptides induced mitotic errors, we counted the number of mitotic and abnormal cells in populations of DAPI-stained MDA-MB-231 cells. We observed that the peptides slightly increased the number of mitotic cells from approximately 3% in control cells to 4% in peptide-expressing cells (Fig. 5 A). We also observed that there was a greater number of mitotic catastrophe events in cells expressing the peptides (Fig. 5 A), which consisted of a variety of aberrant cells, including tridirectional anaphases and micronuclei formation (Fig. 5 B). We predict that the killing of cells that enter mitosis might be due to increased chromosomal damage resulting from dysregulated mitosis. To assess this possibility, we prepared lysates from pcDNA3.1-, C13-3- and C43-4-expressing cells and measured the level of gH2AX, a measure of DNA damage ( 94 ). The results indicated that gH2AX is elevated in C43-4-expressing cells in particular (Fig. 5 C, top panel; quantitated in lower panel; the uncropped blot is shown in Supplemental Fig. 1D ), suggesting that there is more DNA damage in these cells. To test this hypothesis, we examined markers of apoptosis in these cells. We observed that the level of PARP cleavage (cPARP), a sign of commitment to apoptosis ( 95 ), was elevated in peptide-expressing cells treated with DOX (Fig. 5 D, top panel quantitated in the lower panel; the uncropped blot is shown in Supplemental Fig. 1D ). Consistent with these findings, caspase 3 and 8 activity was also elevated in peptide-expressing cells (caspase 3 activity is shown in Fig. 5 E; caspase 8 activity is shown in Fig. 5 F). These observations provide evidence that the peptides induce premature entry into mitosis, causing increased DNA damage and apoptosis. C43-4, but not C13-3, inhibits the growth of MDA-MB-231 cells in a mouse xenograft model To test whether the C13-3 and C43-4 peptides impact cancer growth in vivo , we subcutaneously injected MDA-MB-231 cells stably expressing pcDNA3.1, C13-3 or C43-4 into the mammary fat pads of female NOD SCID gamma (NSG) mice. Untransfected cells were injected as a control. Measurements of tumors via calipers began once tumor growth was obvious at 4 weeks post injection and continued weekly. We observed that C43-4-expressing tumors were smaller (455.3 mm 3 final volume) than pcDNA3.1-expressing tumors (834.5 mm 3 ), C13-3-expressing tumors (959.5 mm 3 ) and untransfected control tumors (996.5 mm 3 ), as shown in Fig. 6 A and quantitated in Fig. 6 B. We next asked whether the peptides could resensitize cells to DOX treatment in vivo , as observed in vitro (Figs. 2 B, D, E). The recommended cumulative DOX dose for tumor-bearing mice is 20 mg/kg ( 96 ). However, to determine the lowest dose of DOX that reduced MDA-MB-231 tumor growth in untransfected cells, DOX was injected 6 weeks after cell injection at cumulative doses of 5, 7.5 and 10 mg/kg. The control groups received intraperitoneal injections of PBS. Intraperitoneal DOX injections were performed every 2 days for 20 days at 1/10 the concentration to achieve the desired cumulative dose. As shown in Figs. 6 C and 6 D, all three doses reduced tumor growth to the same extent, with no significant differences observed. Therefore, we combined peptide expression with a 5 mg/kg cumulative dose of DOX. MDA-MB-231 cells stably expressing pcDNA3.1, C13-3 or C43-4 were injected into the mammary fat pads of female mice as described above. Four weeks postinjection, tumor measurements began, with DOX dosing beginning at 6 weeks postinjection, with injections every 2 days for 20 days to reach a cumulative dose of 5 mg/kg. We observed that the 5 mg/kg dose partially reduced the growth of pcDNA3.1 and C13-3 tumors after 8 weeks, with no differences between the control and C13-3 groups (Figs. 6 E and 6 F). C43-4 reduced the growth of MDA-MB-231 cells, as observed above, and the addition of DOX significantly reduced their growth. These results indicate that while C13-3 impacts cancer cell growth in vitro , it does not influence the growth of the same cells in vivo . However, the C43-4 peptide continued to synergize with DOX in vivo as it did in vitro . APC activation reduced MDA-MB-231 cell growth in vivo , whereas APC inhibition increased growth We next asked whether the C43-4-mediated reduction in tumor growth in our mouse xenograft model was dependent on the APC. As observed with the wound healing assay (Fig. 4 ), chemical activation of the APC with M2I-1 reduced wound healing, with the combination of M2I-1 and C43-4 reducing it further. These findings suggested that M2I-1 and C43-4 activated the APC via separate mechanisms. Here, the mice were injected with MDA-MB-231 cells expressing pcDNA3.1 or C43-4 as described above (C13-3-expressing cells were not used in this experiment since C13-3 did not impact tumor growth in vivo ). At 6 weeks postinjection, a single intraperitoneal injection of 5, 10 or 25 mg/kg M2I-1 was given. Tumor measurement was performed daily following the M2I-1 dose for 8 days. The control pcDNA3.1-expressing tumor volume following the 25 mg/kg dose was 194.9 mm 3 on day 8, whereas the tumor volume was 341.3 mm 3 in untreated control tumors (Fig. 7 A and 7 C), indicating that M2I-1 did indeed slow tumor growth, similar to that of C43-4. In mice growing C43-4-expressing cells, the average tumor volume of untreated mice was 268.2 mm 3 after 8 days, whereas the average tumor volume was 136.8 mm 3 8 days after receiving a dose of 25 mg/kg M2I-1 (Figs. 7 B and 7 C). As observed with the wound healing assay, C43-4 and M2I-1 combined to slow tumor growth even more than either alone did, providing further evidence that M2I-1 and C43-4 use different mechanisms to activate the APC. Finally, to further validate that APC activation reduces tumor growth, we asked whether APC inhibition would increase tumor growth. Mice growing pcDNA3.1- and C43-4-expressing cells received intraperitoneal injections of cumulative doses of 1 and 10 mg/kg APCIN weekly starting at 6 weeks post cell injection. The mice were injected with 1/10 the APCIN dose every 2 days for 20 days. We observed that the control mice that received 1 mg/kg APCIN had a final average tumor volume of 1061.0 mm 3 after 8 weeks, and those that received 10 mg/kg APCIN had a final average tumor volume of 1167.0 mm 3 , which was greater than that of the tumors derived from the untreated mice, which was 937.1 mm 3 . While both volumes were larger than those of the untreated tumors, ANOVA revealed that the differences were not significant. The results obtained with C43-4-expressing MDA-MB-231 cells from mice were quite different. C43-4-expressing tumors remained smaller when treated with 1 or 10 mg/kg APCIN, with tumor volumes of 326.2 mm 3 and 346.7 mm 3 , respectively, compared to the untreated tumor volume of 305.0 mm 3 (Figs. 7 D and 7 E). The differences were not significant, but the differences in growth between empty vector- and C43-4-expressing tumors were significant. Taken together, our results strongly support the hypothesis that APC activation plays a role in stalling tumor growth both in vitro and in vivo . We identified a small peptide discovered via a 2-hybrid screen using the yeast APC subunit Apc10 as bait that resensitizes MDR breast cancer cells to drug treatment in both in vitro cell culture and in vivo mouse models. DISCUSSION As the mean lifespan of humans increases, so does the incidence of cancer. Cancer treatment has improved over the years, with many patients now experiencing extensive periods of remission. However, in many cases, the cancer recurs later in life, with the only recourse being more toxic therapy or palliative care ( 11 ). We previously reported that the activation of the APC via the small chemical SAC inhibitor Mad2 inhibitor-1 (M2I-1), a chemical that disrupts the binding of CDC20 to the SAC ( 42 ), prematurely activates the APC to resensitize MDR cancer cells to therapy ( 57 , 76 ). The notion that APC activation improves cancer outcomes is gaining traction, as we and others have shown that APC activation, predominantly that of APC CDH1 , promotes cancer cell killing ( 57 , 76 62 , 64 – 67 ). For example, Rev7, a CDH1 inhibitor, results in a poor prognosis for many cancers when it is overexpressed, with better outcomes when it is decreased and when it is combined with platinum-based therapies ( 97 ). REV7 is a dual-function protein that is required for translesion synthesis DNA repair but also behaves similarly to proteins composing the Spindle Assembly Checkpoint (SAC) ( 98 ). REV7 overexpression results in slowed mitotic progression, impaired APC function, elevated APC substrate levels, and increased mitotic slippage upon nocodazole treatment in triple-negative breast cancer cells. REV7 is an APC substrate that is stabilized in TNBC cells ( 99). Several other reports also support that inhibition of the SAC activates the APC, which can resensitize TNBC to therapy ( 42 , 100 ). SAC inhibitors are currently in clinical trials for cancer treatment ( 101 ). In fact, key SAC components (such as MPS1, an APC substrate) that are overexpressed in aggressive cancer cells are being targeted ( 102 ). However, the SAC is involved in many processes that regulate chromosome segregation in both mitotic and meiotic cells ( 103 , 104 ). For example, a BioGRID search for proteins associated with the SAC component MPS1 revealed a network composed of 637 interactors (nodes) and 10,117 edges (unpublished). Therefore, the inhibition of the SAC may have several side effects. In this report, we describe the discovery of novel yeast lifespan-enhancing peptides, which were discovered via a yeast 2-hybrid screen where the APC subunit Apc10 was used as bait that possessed conserved function in MDR breast cancer cells by resensitizing them to therapy in vitro and in vivo . We arrived at these conclusions by first cloning 7 of the small peptides recovered in the yeast 2-hybrid screen into the pcDNA3.1 vector and stably expressing them in human MDA-MB-231 and matched MCF7 Sens and MCF7 Res breast cancer cells. The selected peptides rescued the short replicative lifespan (RLS; 105, 106) of the apc5 ts mutant yeast (Harris et al., unpublished). In human cells, as a measure of direct APC activation, we asked whether the peptides could reduce the asynchronous levels of APC substrates, as reduced substrate levels suggest that the APC increases the turnover of its substrates. Figures 1 A-D shows that peptides C13-3 and C43-4 consistently reduced the protein levels of the substrates tested. These findings indicate that these peptides have conserved activity and are therefore the focus of this study. To assess APC activation when C13-3 and C43-4 were applied to MDA-MB-231 cells, we determined the levels of APC1 phosphorylated at Ser355, a marker of APC activation ( 76 , 91 , 92 ), in peptide-treated cells. Western blotting with APC1 S355ph antibodies revealed that the level of phosphorylated APC1 was elevated in peptide-treated cells (Fig. 1 E), suggesting that C13-3 and C43-4 indeed activate the APC. Finally, to test whether the peptides increased the direct E3 activity of the APC, we performed in vitro Ub assays using APC purified from stably transfected MCF7 Sens and MCF7 Res cells. The results show that APC E3 activity is reduced in MCF7 Res cells and that the peptides can increase E3 activity in MCF7 Res cells, with C43-4 being the most potent (Fig. 1 G, 1 H). Taken together, our data strongly support the hypothesis that the peptides indeed activate the APC, particularly in MCF7 Res cells. Previous work from our group using the APC chemical activator M2I-1 revealed that APC activation in human and canine MDR cells resulted in the killing of these cells ( 57 , 76 ). We showed here that using the C43-4 peptide to activate the APC in MCF7 Res and MDA-MB-231 breast cancer cells also resulted in slowed cell proliferation when it was combined with 1 µM DOX but that C13-3 was not as effective, particularly in MDA-MB-231 cells (Figs. 2 B-E). Since neither C13-3 nor C43-4 slowed the proliferation of MCF7 Sens cells in the presence of 1 µM DOX, this suggested that C43-4 may specifically impact cells with greater DNA damage, which is often observed in aggressive MDR cancer cells. We also observed a trend toward a reduction in the MDR markers BCRP and MDR-1 when C43-4 was used (Figs. 2 F-H). This finding is consistent with the finding that C43-4 renders MDR cells sensitive to drug treatment. The C43-4 peptide, in particular, appears to have APC-activating ability and to resensitize MDR cells to DOX. This finding is consistent with studies showing that the APC CDH1 complex has anticancer activity ( 46 , 79 ). The APC CDH1 complex works in both replicating and differentiated cells ( 107 , 108 ). Our preliminary data in yeast revealed that C43-4 increased the lifespan of wild-type stationary phase cells and the short lifespan of dividing APC mutant cells. Interestingly, C13-3 only extended the lifespan of dividing APC mutants but not the lifespan of stationary-phase wild-type cells. M2I-1, which specifically releases CDC20 from the SAC to prematurely activate the APC, increases the lifespan of only dividing yeast cells but not that of cells in the stationary phase (Harris et al., unpublished). Therefore, C43-4 appears to possess the unique ability to activate the APC CDH1 complex to preserve genomic stability and defend against cancer progression. We tested whether C13-3 and C43-4 were able to reverse additional cancer cell phenotypes. We show here that the peptides inhibited the mobility of aggressive and metastatic MDA-MB-231 cells (Fig. 4 ). The peptides worked additively with DOX, which also inhibited cell mobility. Interestingly, the SAC inhibitor/APC activator M2I-1 also inhibited cell mobility, and the peptides worked additively with it. These findings indicate that inhibiting the SAC, thereby releasing CDC20 prematurely to activate the APC, works differently from how the peptides work. Consistent with peptides exhibiting anticancer potential, both C13-3 and C43-4 induced mitotic progression and mitotic catastrophe (Figs. 5 A, 5 B). In our previously published work, we showed that activation of the APC via M2I-1 increased the passage rate through mitosis, increased the degradation of mitotic APC substrates, and increased the killing of resistant cells by DOX ( 75 ). This finding is consistent with a model in which aggressive and MDR cancer cells progress slowly through mitosis to provide time to repair enough DNA damage to avoid mitotic catastrophe, whereas pushing MDR cells rapidly through mitosis may block the ability to repair enough damage, leading to elevated levels of mitotic catastrophe ( 47 , 62 ). Consistent with the peptides inducing mitotic catastrophe, we also observed that the peptides increased DNA damage, as indicated by elevated levels of gH2AX, and induced apoptosis, as indicated by increased PARP cleavage and increased caspase 3 and 8 activity (Fig. 5 C- 5 F). Notably, C13-3 and C43-4 appear to have evolutionarily conserved functions from yeast to humans in in vitro cell culture. Not all the peptides cloned into the human pcDNA expression vector were able to consistently reduce APC substrate levels in human breast cancer cells. To further test the conserved nature of the peptides, we injected MDA-MB-231 cells stably expressing pcDNA or pcDNA vectors expressing C13-3 or C43-4 into the mammary fat pads of female NOD SCID gamma (NSG) mice. As shown in Figs. 6 A and 6 B, C43- 4 slowed the growth of MDA-MB-231 cells in mice, whereas C13-3-expressing cells consistently grew at the same rate as the empty vector and untransfected controls. DOX slowed the growth of MDA-MB-231 cells in mice and decreased growth further when it was combined with C43-4, but not with C13-3. M2I-1 also slowed the growth of MDA-MB-231 cells in mice and worked additively with C43-4 (Figs. 6 C- 6 F). This provides further evidence that M2I-1 and C43-4 work independently of one another to activate the APC. Finally, we showed that, compared with M2I-1 and C43-4, the inhibition of APC had the opposite effect on tumor growth in mice. Strikingly, our results revealed that APCIN not only accelerated tumor growth in a dose-dependent manner, but was reversed by C43-4. These findings provide very strong evidence supporting the role of APC activity in suppressing the growth of MDR cancer cells both in vitro and in vivo . This finding also suggests that C43-4 may work in a CDC20-independent manner since APCIN is thought to bind to CDC20 to disrupt the interaction between CDC20 and its substrates. It is also possible that C43-4 may inhibit the interaction between CDC20 and APCIN. Further investigations are ongoing to test this idea. In conclusion, we aimed to test whether the peptides we discovered in a yeast 2-hybrid screen in which the yeast Apc10 subunit was used as bait had conserved functions in human cells. Two of the peptides exhibited conserved APC-activating functions in in vitro cell culture experiments, and one of the peptides continued to have activity in an in vivo mouse xenograft model. These results support the use of the C43-4 peptide to search for small chemicals that directly bind the APC to potentially activate the cell protective APC CDH1 complex and increase cell health. These results also support the use of yeast to screen for peptides and chemicals that can be used as longevity and anticancer therapeutics in human cells. Declarations ETHICAL APPROVAL AND CONSENT TO PARTICIPATE Not applicable. The authors declare that they have no potential conflicts of interest. CONSENT FOR PUBLICATION All authors consent to publication. COMPETING INTERESTS Not applicable. FUNDING This work was supported by grants to T.A.A.H. and T.G.A. from the Canadian Foundation for Innovation (CFI) and the Canadian Breast Cancer Foundation (CBCF). T.A.A.H. was awarded a Natural Sciences and Engineering Research Council (NSERC) of Canada Discovery grant to investigate APC activating peptides. G.M. was supported by an NSERC MSc award and S.V. was supported by an NSERC summer-student award. Author Contribution C.V. contributed Figures 1 (except E), 2E-H, and 5, and helped edit the final draft. G.M. contributed Figures 3, 4, 6 and 7. S.V. contributed Figure 1E. M.L. contributed Figures 2A-D. G.F.D. trained and supervised the mouse work by G.M. T.G.A. cowrote the grants for this work, helped design experiments, supervised C.V. and S.V., and edited the final drafts of the paper. T.A.A.H. wrote the grants supporting this work, planned and designed the experiments, wrote and edited the manuscript, and supervised G.M., M.L. and G.F.D. ACKNOWLEDGEMENTS Not applicable. Data Availability No datasets were generated or analyzed during the current study. Data are however available from the authors upon reasonable request. Please contact Troy Harkness at [email protected] if you have a request for data. References Mubarik, S., et al. Evaluation of lifestyle risk factor differences in global patterns of breast cancer mortality and DALYs during 1990-2017 using hierarchical age-period-cohort analysis. Environ. Sci Pollut. Res. Int . 28 , 49864-49876 (2021). Ahmad, A. Breast cancer Sstatistics: Recent trends. Adv. Exp. Med. Biol . 1152 , 1-7 (2019). Rojas, K. & Stuckey, A. Breast cancer epidemiology and risk factors. Clin. Obstet. Gynecol. 59 , 651-672 (2016). Tsang, J. Y. S. & Tse, G. M. Molecular classification of breast cancer. Adv. Anat. Pathol . 27 , 27-35 (2020). 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1","display":"","copyAsset":false,"role":"figure","size":569288,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAPC-binding peptides reduce APC substrate levels and activate the APC. A) \u003c/strong\u003eMDA-MB-231 cells were stably transfected with pcDNA3.1-based plasmids expressing different peptides isolated from a yeast 2-hybrid screen for those that were recruited to the yeast Apc10 subunit. The cells were grown to 70% confluency, and then protein lysates were prepared and assessed with the antibodies shown. Western blotting was performed with 3 biological replicates. Western bands identified via antibodies against the \u003cstrong\u003eB)\u003c/strong\u003e HURP, \u003cstrong\u003eC)\u003c/strong\u003e CDC20 and \u003cstrong\u003eD)\u003c/strong\u003e Cyclin B1 APC substrates were scanned via ImageJ. Protein abundance was adjusted for the GAPDH loading control and normalized to that of the control (MDA-MB-231 cells stably transfected with an empty pcDNA3.1 vector), which was set to 1.00. n=3 biological replicates. Unpaired t tests between the control and individual peptides were performed to establish statistical significance; *=p\u0026lt;0.05, **=p\u0026lt;0.01, ***=p\u0026lt;0.001, ****=p\u0026lt;0.0001. The error bars represent the standard error of the mean (SEM). All uncropped blot images are shown in Supplementary Figure 1A. \u003cstrong\u003eE)\u003c/strong\u003e Lysates prepared from MCF7\u003csup\u003eRes\u003c/sup\u003e cells stably expressing pcDNA3.1, C13-3, or C43-4 were assessed via antibodies against total APC1 and APC1 phosphorylated at Ser355. The APC1\u003csup\u003eph\u003c/sup\u003e:APC1\u003csup\u003etot\u003c/sup\u003e ratio is shown; n=2, SEM shown. All uncropped blot images are shown in Supplementary Figure 1B. \u003cstrong\u003eF)\u003c/strong\u003e \u003cem\u003eIn vitro\u003c/em\u003e ubiquitination assays were developed and used to measure APC activity in various MCF7 cell lines. Commercially available purified securin was used as bait in the assay. Antibodies against Securin were used to detect ubiquitinated proteins. Control assays were performed with the indicated reagents eliminated from MCF7\u003csup\u003eSens\u003c/sup\u003e cells. The APC was immunoprecipitated using antibodies against CDC27. \u003cstrong\u003eG)\u003c/strong\u003e Assays using APC purified from MCF7\u003csup\u003eSens\u003c/sup\u003e and MCF7\u003csup\u003eRes\u003c/sup\u003e cells were performed. The signals from the Securin\u003csup\u003eUb\u003c/sup\u003e bands were imaged, normalized to those from the MCF7\u003csup\u003eSens\u003c/sup\u003e Securin\u003csup\u003eUb\u003c/sup\u003e bands, and plotted.\u003cstrong\u003e H)\u003c/strong\u003e Assays were performed using MCF7\u003csup\u003eRes\u003c/sup\u003e cells expressing pcDNA3.1, C13-3 or C43-4. The signals from the Securin\u003csup\u003eUb\u003c/sup\u003e bands were imaged, normalized to those of the empty vector control, and plotted. The controls used in \u003cstrong\u003eG)\u003c/strong\u003e and \u003cstrong\u003eH)\u003c/strong\u003e included assays lacking purified APC. n=1.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7309461/v1/3e589308ac9fa489810732bb.png"},{"id":92171907,"identity":"84403cb9-af39-4c0e-815d-8d5db76b2190","added_by":"auto","created_at":"2025-09-25 12:05:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":425786,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAPC-activating peptides sensitize MDA-MB-231 and MCF7\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eRes\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e cells to therapy. A)\u003c/strong\u003e MCF7\u003csup\u003eSens\u003c/sup\u003e and cells selected for resistance to tamoxifen (MCF7\u003csup\u003eRes\u003c/sup\u003e) were treated with 1 mM DOX for 48 hours, followed by MTT chemosensitivity assays. n=3 technical repeats; error bars represent SEM. \u003cstrong\u003eB)\u003c/strong\u003e MCF7\u003csup\u003eSens\u003c/sup\u003e and MCF7\u003csup\u003eRes\u003c/sup\u003e cells were stably transfected with the plasmids shown and treated with doxorubicin (DOX) for 48 hours. Cell viability was determined via an MTT assay. n=4 (MCF7\u003csup\u003eSen\u003c/sup\u003e) and n=3 (MCF7\u003csup\u003eRes\u003c/sup\u003e) biological replicates; error bars represent SEM. The values were normalized to those of pcDNA, which was set to 1.0. \u003cstrong\u003eC)\u003c/strong\u003e MDA-MB-231 cells stably expressing the C13-3 and C43-4 peptides or pcDNA3.1 were treated with trypan blue to determine the number of nonviable cells that had breached the plasma membrane. One-way ANOVA and Tukey’s post hoc tests were performed on each dataset to determine the statistical significance of differences between the experimental groups. This experiment was performed in triplicate (n= 3). The error bars represent the SEM. **, p \u0026lt;0.01. \u003cstrong\u003eD)\u003c/strong\u003e 6-well chemosensitivity assays using 1 μM DOX for 48 hours were performed on MDA-MB-213 cells. Unpaired t tests comparing individual peptide-expressing lines to the pcDNA3.1 control were performed to establish statistical significance, n=9 technical repeats; *=p\u0026lt;0.05, error bars represent SEM. \u003cstrong\u003eE\u003c/strong\u003e) A 96-well chemosensitivity dose‒response assay ranging from 0 to 1 µM DOX for 48 hours was performed. n=3 biological replicates; the error bars represent the SEM. Two-way ANOVA revealed significant differences between C43.4 and pcDNA (p \u0026lt; 0.0001) and between C13.3 and pcDNA (p = 0.0006) in response to DOX treatment. Post hoc multiple-t tests also revealed significant differences in the dose response between C43.4 and pcDNA, ranging from 0.5 to 0.9 µM (p values ranging from 0.0331 to 0.0001), but not between C13.3 and pcDNA. \u003cstrong\u003eF)\u003c/strong\u003e BCRP and MDR-1 protein levels were measured via western blot analysis of whole lysates prepared from MDA-MB-231 cells expressing C13-3 or C43-3. All uncropped blot images are shown in Supplementary Figure 1C. \u003cstrong\u003eG)\u003c/strong\u003e All BCRP bands from the western blot in \u003cstrong\u003eF)\u003c/strong\u003e were imaged, normalized to the pcDNA3.1 control, and plotted. \u003cstrong\u003eH)\u003c/strong\u003e All MDR-1 bands from the western blot in \u003cstrong\u003eF)\u003c/strong\u003e were imaged, normalized to the pcDNA3.1 control, and plotted. Protein abundance in \u003cstrong\u003eF)\u003c/strong\u003e was adjusted for the tubulin load control and normalized to that of the MDA-MB-231 pcDNA3.1 control, which was set to 1.00. n=3 biological replicates. Unpaired t tests between control peptides and individual peptides were performed to establish that the differences were not statistically significant. The error bars represent the SEM.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7309461/v1/13f9d9c4e2c73ebb984e9350.png"},{"id":92169946,"identity":"d5eb6367-1447-45ed-b2f7-147cad096dc6","added_by":"auto","created_at":"2025-09-25 11:41:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":278044,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDetection of peptide expression in MDA-MB-231 cells.\u003c/strong\u003e \u003cstrong\u003eA)\u003c/strong\u003e Stably transfected MDA-MB-231 cell lines were subjected to immunofluorescence using an anti-HA primary antibody in combination with a fluorescent secondary antibody to detect HA-tagged peptides. DAPI was used for nuclear staining. The negative control cell line was transfected with an empty pcDNA vector that did not express the HA epitope. Scale bar: 10 mm. \u003cstrong\u003eB)\u003c/strong\u003e MDA-MB-231 cells stably transfected with the pcDNA plasmid expressing the C13-3 or C43-4 peptide were subjected to RT‒PCR. Primers specific to the thioredoxin backbone (amplicon of 123 base pairs) and control primers specific to the EFEMP2 extracellular matrix protein (amplicon of 89 base pairs) were used. The RT‒PCR amplicons obtained from each stable cell line were compared with the products obtained from a PCR performed on the plasmids used for transfection.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7309461/v1/66aa58c4a0d5f6d3c6e93a20.png"},{"id":92171659,"identity":"89187ed5-fbde-41f4-be22-cd8b2fb0589c","added_by":"auto","created_at":"2025-09-25 11:57:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1057509,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAPC activation impairs the migration of MDA-MB-231 cells. A)\u003c/strong\u003e Wound healing assays were performed in MDA-MB-231 cells stably expressing pcDNA3.1, C13-3 or C43-4. The cells were allowed to migrate into a void created in a lawn of cells over a 24-hour period. Lines highlight the edge of the original void. Cell migration was measured in the same field of view over a 24-hour period via a light microscope and camera. Scale bar: 500 mm. A representative image of three repeats is shown. \u003cstrong\u003eB)\u003c/strong\u003e Percent void closure was determined and plotted for cells in the absence and presence of 0.5 mM DOX. Untreated cells were quantified via ImageJ from the experiment described in \u003cstrong\u003eA)\u003c/strong\u003e. \u003cstrong\u003eC)\u003c/strong\u003eWound healing assays were performed over a series of DOX concentrations. \u003cstrong\u003eD)\u003c/strong\u003eWound healing assays were performed in the presence or absence of 10 and 20 mM M2I-1. For \u003cstrong\u003eC)\u003c/strong\u003e and \u003cstrong\u003eD)\u003c/strong\u003e, percent closure after 24 hours was determined and plotted. Two-way ANOVA and Tukey’s multiple comparisons test were performed on each dataset to determine the statistical significance between the transfected cell lines and drug treatment. The error bars represent the SEM. This experiment was performed with 3 biological replicates.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7309461/v1/d53b6eef33b19ca867244d92.png"},{"id":92169948,"identity":"dcf6aca8-6b6d-406c-9703-d0e910ce09d2","added_by":"auto","created_at":"2025-09-25 11:41:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":503405,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAPC activating peptides increase mitotic catastrophe, DNA damage, and apoptosis. A)\u003c/strong\u003e Asynchronous MDA-MB-231 cells stably expressing pcDNA3.1, C13-3 or C43-4 were stained with DAPI to visualize DNA and observed via fluorescence microscopy. The percentage of cells that experienced regulated mitosis compared with that of cells that experienced mitotic catastrophe was determined for each. Unpaired t tests revealed a statistically significant difference between the peptide-expressing cell lines and the control; n=5 biological replicates; error bars represent SEM. \u003cstrong\u003eB)\u003c/strong\u003eExamples of mitotic catastrophe captured by fluorescence microscopy. Highlighted cells include tridirectional anaphase and micronuclei formation. \u003cstrong\u003eC)\u003c/strong\u003eUpper panel: Qualitative representative Western blot of γH2AX in whole-cell lysates of MDA-MB-231 cells passaged for one month in the presence or absence of APC-activating peptides. Lower panel: Quantitative representation of γH2AX protein abundance adjusted to the tubulin load control and normalized to the MDA-MB-231-pcDNA3.1 control, set to 1.00. n=3 biological replicates. Unpaired t tests between the control cell population and those expressing the individual peptides were performed to establish statistical significance. The error bars represent the SEM. \u003cstrong\u003eD) \u003c/strong\u003eUpper panel: Qualitative representative Western blot of PARP protein cleavage from whole-cell lysates of MDA-MB-231 cells exposed to 1.0 μM DOX for 48 hours. Lower panel: DOX exposure-induced PARP cleavage (cPARP), with the protein abundance adjusted to the load control (Tubulin) and normalized to that of the MDA-MB-231-pcDNA3.1 control, which was set to 1.00. n=3 biological replicates. All uncropped blot images are shown in Supplementary Figure 1D. The activities of \u003cstrong\u003eE)\u003c/strong\u003e Caspase 3 and \u003cstrong\u003eF)\u003c/strong\u003eCaspase 8 were quantified via a caspase activity kit (Abcam). Caspase activity is expressed as relative fluorescence units (RFUs), a measurement of fluorophore activity. Excitation (Ex) and emission (Em) spectra are expressed as Ex/Em for their respective wavelengths. n=3 technical repeats. Unpaired t tests between controls and individual peptides were performed to establish statistical significance. The error bars represent the SEM, *=p\u0026lt;0.05.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7309461/v1/ec47190171512811dd1ac88b.png"},{"id":92170603,"identity":"4f8de7c9-39ff-42c0-8001-730b151e1e6f","added_by":"auto","created_at":"2025-09-25 11:49:02","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":449786,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eC43-4 peptide expression causes a decrease in tumor volume.\u003c/strong\u003e \u003cstrong\u003eA)\u003c/strong\u003e Tumor growth curves of MDA-MB-231 cells expressing the C13-3 and C43-4 peptides. Tumors derived from untransfected MDA-MB-231 cells and those expressing only the pcDNA3.1 empty vector served as negative controls. \u003cstrong\u003eB)\u003c/strong\u003e Comparison of the tumor volume generated from untransfected MDA-MB-231 cells and pcDNA3.1-, C13-3- and C43-4-transfected cells at weeks 7, 8 and 9 post-injection. One-way ANOVA and Tukey’s multiple comparisons test were performed at each time point to determine the statistical significance of differences between peptide-expressing cells and the pcDNA3.1 negative control. The error bars represent the SEM. n=12, *, p \u0026lt;0.05, **, p \u0026lt;0.01, ***, p \u0026lt;0.001. n=4 in each group. \u003cstrong\u003eC)\u003c/strong\u003e Tumor growth curves of untransfected MDA-MB-231 cells treated with cumulative doses of 5, 7.5 and 10 mg/kg DOX injected with a PBS vehicle. Injections of 0.5, 0.75 and 1 mg/kg were administered every two days over a twenty-day period to reach the cumulative doses. \u003cstrong\u003eD)\u003c/strong\u003e Tumor volume after treatment with cumulative doses of 0 and 5, 7.5 and 10 mg/kg DOX at 8 weeks postcell injection. One-way ANOVA and Tukey’s post hoc test were performed on each dataset to determine the statistical significance of differences between the experimental groups. n = 4.\u003cstrong\u003e E)\u003c/strong\u003e Combined graph of untransfected MDA-MB-231 tumors with or without treatment with cumulative doses of 5 mg/kg DOX. Injections were administered every two days over a twenty-day period. \u003cstrong\u003eF)\u003c/strong\u003e Comparison of tumor volume among the MDA-MB-231, pcDNA3.1, C13-3 and C43-4 cell lines at week 8 post-injection. Two-way ANOVA and Tukey’s multiple comparisons test were performed on each dataset to determine the statistical significance of differences between experimental groups. The error bars represent the SEM. *, p \u0026lt;0.05; **, p \u0026lt;0.01; ***, p \u0026lt;0.001. n=4 in each group.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7309461/v1/952197a080b46e73eea0803e.png"},{"id":92169949,"identity":"c314a63e-0e10-4964-9f11-82181dd517a7","added_by":"auto","created_at":"2025-09-25 11:41:02","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":418110,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePeptide-expressing tumors treated with 5, 10 and 25\u003c/strong\u003e \u003cstrong\u003emg/kg M2I-1 displayed slight synergy with C43-4, whereas growth exacerbation with APCIN was inhibited by C43-4.\u003c/strong\u003e Growth curves of \u003cstrong\u003eA)\u003c/strong\u003eMDA-MB-231 pcDNA3.1-transfected or \u003cstrong\u003eB)\u003c/strong\u003e C43-4-transfected 231 cell line-derived tumors treated with single doses of 0, 5, 10 or 25 mg/kg M2I-1 in PBS vehicle 6 weeks after cell injection. The tumor size was measured daily for 8 days. \u003cstrong\u003eC)\u003c/strong\u003eComparison of tumor volume in the MDA-MB-231, pcDNA3.1, and C43-4 cell line groups on day 8 after M2I-1 injection. Two-way ANOVA and Tukey’s multiple comparisons test were performed on a combined dataset to determine the statistical significance of differences between experimental groups. The error bars represent the SEM. *, p \u0026lt;0.05; **, p \u0026lt;0.01; ***, p \u0026lt;0.001. n= 4 in all groups. \u003cstrong\u003eD\u003c/strong\u003e) Growth curves of pcDNA3.1- and C43-4-transfected MDA-MB-231 cell-derived tumors treated with cumulative doses of 1 and 10 mg/kg APCIN in PBS vehicle. APCIN injections were administered every two days over a twenty-day period. \u003cstrong\u003eE)\u003c/strong\u003e Tumor volume of APCIN-treated pcDNA3.1- and C43-4-expressing tumors at week 8 after cell injection. Two-way ANOVA and Tukey’s multiple comparisons test were performed on each dataset to determine the statistical significance and tumor volume. The error bars represent the SEM. n = 4. The error bars represent the SEM.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7309461/v1/2e2410b7e306eb5c3821cb95.png"},{"id":102245597,"identity":"805e204c-126a-45e9-bc06-24a5143d4574","added_by":"auto","created_at":"2026-02-09 17:55:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4983660,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7309461/v1/202ad70f-774c-4658-b1c1-2574f49809bf.pdf"},{"id":92169947,"identity":"374d845f-b717-4616-9b99-0c88b229e5c3","added_by":"auto","created_at":"2025-09-25 11:41:02","extension":"pptx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1093317,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalFigure1.250825pptx.pptx","url":"https://assets-eu.researchsquare.com/files/rs-7309461/v1/22baa1da80668c0c053cc200.pptx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Restoration of chemosensitivity to drug resistant breast cancer cells through peptide activation of Anaphase Promoting Complex","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eBreast cancer is the leading cancer diagnosed in women worldwide (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), and while many cases are effectively treated in the short term, many cases are more difficult to treat because both innate resistant breast cancers and cancers can reoccur with acquired resistance to previously effective therapies. The classification of different breast cancer subtypes is complicated and varied but can be broadly classified as estrogen receptor positive (ER\u003csup\u003e+\u003c/sup\u003e) or lacking estrogen, progesterone, and HER receptors (triple-negative breast cancer; TNBC; 4, 5). ER\u003csup\u003e+\u003c/sup\u003e cancers are the most common type of cancer at 70% and are typically treated with antiestrogen therapies, which result in a high rate of remission (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). However, when endocrine therapy is stopped after 5 years, the risk of recurrence steadily increases from 5\u0026ndash;20 years, with recurrence risk ranging from 10\u0026ndash;41% depending on the initial grade of the tumor (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Recurrent tumors may be more aggressive and difficult to treat; thus, our understanding of how recurrent drug-resistant cancers develop and the discovery of new therapeutic targets are of extreme interest and need further study.\u003c/p\u003e\u003cp\u003eMany mechanisms have been described that support how cancer recurs, often with increased resistance to therapy. The six most common hallmarks described are i) alteration of drug targets, ii) expression of drug efflux pumps, iii) expression of detoxification mechanisms, iv) reduced susceptibility to apoptosis, v) increased DNA repair capability, and vi) altered proliferation (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). These events can occur alone or in combination, making treating drug resistance a very daunting task. There are few treatment options for individuals who develop drug-resistant cancers, with palliative care potentially the only recourse (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). On the other hand, TNBC is innately aggressive at first presentation, is molecularly complex, and has a poor prognosis (\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Owing to the lack of hormone receptors, antiestrogen therapy cannot be used to treat TNBC. Therefore, more toxic strategies, such as the use of cytotoxic chemotherapies, are frequently considered. Since TNBC is innately resistant to treatment, higher doses are often needed. New methods are clearly needed to treat patients with treatment-resistant cancers, whether acquired or innate.\u003c/p\u003e\u003cp\u003eWhile many proteins that promote tumor development have been identified over the years, the molecular events leading to cancer development and progression are often very diverse, and no simple target that overcomes MDR in breast or other cancers has been identified (\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Inhibitors against a variety of overactive oncogenic proteins have been developed (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), but over time, resistance to these treatments often develops, or the treatments are ineffective or toxic in clinical trials (\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Many studies suggest that inhibiting mitosis might be a general means to control the growth of cancer cells (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), yet even normal cells are at risk of bystander toxicity, thereby limiting their use. The Anaphase Promoting Complex (APC) is integral to the regulated progression of the cell cycle through mitosis and, in turn, is negatively regulated by the spindle assembly checkpoint (SAC; 27, 28). Anti-microtubule drugs that disrupt chromosome alignment along the metaphase plate activate the SAC, block mitotic progression and kill cancer cells \u003cem\u003ein vitro\u003c/em\u003e (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Inappropriate activity of the SAC is associated with aneuploidy in many malignancies, including breast cancer (\u003cspan additionalcitationids=\"CR30 CR31\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), resulting in sustained APC inhibition. Interestingly, overactive SAC components are common in drug-resistant cells (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Although antimicrotubule drugs are very effective, cardiotoxicity is a frequent consequence of therapy (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), and mitotic arrest due to SAC activation can be bypassed by the process of mitotic slippage, whereby anaphase is initiated despite concurrent activation of the SAC, leading to cancer progression and drug resistance (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Mitotic slippage often occurs when the SAC weakens after prolonged mitotic arrest (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) and is associated with ATP depletion, TORC1 inactivation, decreased APC\u003csup\u003eCDC20\u003c/sup\u003e levels, and inappropriate APC\u003csup\u003eCDH1\u003c/sup\u003e-dependent degradation of cyclin B during mitosis (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Therefore, targeting proper and timely APC activation, by inhibiting the SAC, for example, in cancer cells to manipulate mitotic checkpoints without mitotic arrest is a novel approach showing some promise, as APC mutations and impairment are common in aggressive cancers (\u003cspan additionalcitationids=\"CR42 CR43\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe APC is a large and conserved multisubunit E3 ubiquitin ligase that promotes mitotic progression and G1 maintenance by targeting substrates for degradation via the proteasome (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Mitotic progression is driven by the CDC20 APC coactivator, with mitotic exit and G1 maintenance controlled by the CDH1 APC coactivator. Once mitosis is initiated, APC\u003csup\u003eCDH1\u003c/sup\u003e becomes active, targeting CDC20 for degradation to prevent mitosis. In recent years, the APC has been shown to play an important role in controlling cancer progression (\u003cspan additionalcitationids=\"CR47 CR48\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). Many APC substrate RNAs, including CDC20, are elevated in cancer cells. The observation that CDC20 mRNA and protein levels are elevated in many types of cancers (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e) suggests that the APC is overactive in cancer cells, leading to the generation of inhibitors of the APC and APC substrates, such as CDC20, PLK1 and Aurora kinases (\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). In some cases, these inhibitors show promise in preclinical \u003cem\u003ein vitro\u003c/em\u003e work, but clinical studies have not achieved the same success rates and continue to be evaluated (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). The CDC20 inhibitors TAME and APCIN also show promise as anticancer agents, with clinical trials underway (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAn alternative interpretation of CDC20 overexpression is that this represents APC impairment, since increased CDC20 mRNA is generally accompanied by the accumulation of many APC substrate mRNAs (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan additionalcitationids=\"CR57 CR58 CR59\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). This implies that the APC is dysfunctional in potentially aggressive cancer cells and is not able to properly target its oncogenic substrates for degradation. Recently, many reports have been published that are consistent with the idea that APC mutations and impairment are indeed associated with cancer progression (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e). In fact, CDC20 is now considered to be associated with tumor progression, whereas CDH1 is associated with tumor suppression, which is consistent with reports showing that mutation to CDH1 is associated with genomic instability and cancer development (\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e). It has now been established, at least \u003cem\u003ein vitro\u003c/em\u003e, that chemicals that inhibit SAC components push aggressive cancer cells into premature mitosis and cell death (\u003cspan additionalcitationids=\"CR65 CR66\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). Thus, it has been hypothesized that when cells carrying high loads of chromosome instability (CIN) are prematurely pushed into mitosis, they undergo unsustainable mitosis and experience mitotic catastrophe, inducing cell death (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). Similar to inhibitors against mitotic agonists overexpressed in cancer, which have unfortunately been unsuccessful in clinical trials (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e), the recent development of SAC inhibitors, while showing some promise in clinical trials, still require further development (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e). SAC inhibitors, however, are not expected to block, but rather promote mitosis.\u003c/p\u003e\u003cp\u003eIt is becoming clear that the APC\u003csup\u003eCDH1\u003c/sup\u003e complex is required for genomic stability and cell health in noncycling cells, but we do not fully understand how this occurs. In our published yeast work, we have shown that the yeast APC is required for stress response and a full lifespan (\u003cspan additionalcitationids=\"CR71 CR72 CR73 CR74\" citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e), suggesting that the APC plays an important role in maintaining cell homeostasis. In support of this, we observed that chemical activation of the APC using M2I-1 (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e) in drug-resistant MCF7 human breast cancer and canine OSW lymphoma cells resensitized them to drug treatment (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). M2I-1 activates the APC indirectly by inhibiting the SAC, prematurely releasing CDC20 to activate the APC, promoting progression through mitosis. However, M2I-1 is not predicted to function in differentiated or senescent cells when APC\u003csup\u003eCDH1\u003c/sup\u003e is active. Since CDH1 is required for G1 maintenance and entry into G0 (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e) and is tightly associated with genome stability (\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e), it is imperative to develop methods to activate the APC\u003csup\u003eCDH1\u003c/sup\u003e complex.\u003c/p\u003e\u003cp\u003eTo identify peptide APC activators, we used a novel dual screen in which random peptides were first selected by recruitment to Apc10 bound to reporter promoters in a yeast 2-hybrid screen. These peptides were then screened for those that could increase the replicative lifespan of yeast (Harris et al., unpublished). In this study, positive peptides identified in the yeast screen were cloned into the human pcDNA3.1 expression vector. These peptides were then stably transfected into human MDA-MB-231 TNBC cells and human MCF7 ER\u003csup\u003e+\u003c/sup\u003e sensitive and MCF7 cells selected for resistance to tamoxifen (TAM). These cells were used to determine the effects of APC activation on tumor cell progression and the reversal of drug resistance \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eCloning yeast peptide sequences into the human expression vector pcDNA3.1\u003c/h2\u003e\u003cp\u003ePolymerase chain reaction (PCR) amplification was performed on the peptides shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, using the original yeast plasmids as a template (originally described in 81). The orientation of the peptide-expressing constructs from the N-terminus was as follows: SV40 nuclear localization signal (NLS, sequence PKKKRKV), fatty acid oxidation complex (FadB), hemagglutinin (HA, sequence YPYDVPDYA) tag, thioredoxin N-terminus (TrxA), peptide, and TrxA C-terminus. All PCR reactions utilized the same 3\u0026rsquo; primer, which bound to the C-terminus of the TrxA C-terminal sequence. Two 5\u0026rsquo; primers were utilized in separate reactions to produce two distinct insert sequences from the same original sequence. One 5\u0026rsquo; primer bound 3\u0026rsquo; of the FadB sequence (producing a DNA fragment without the NLS or FadB sequences), and the other primer bound 5\u0026rsquo; of the NLS (producing a DNA fragment with the NLS and FadB sequences). All the amplified sequences contained the HA-TrxA-peptide-TrxA. After purification, the insert sequences were ligated into the pGEM-T Easy vector (Promega) via TA ligation following the manufacturer\u0026rsquo;s instructions and transformed into the \u003cem\u003eEscherichia coli\u003c/em\u003e (\u003cem\u003eE. coli\u003c/em\u003e) strain DH5α (Thermo Fisher Canada). The transformed \u003cem\u003eE. coli\u003c/em\u003e were then plated onto Luria broth (LB)-agar plates (0.5% w/v yeast extract, 1% w/v tryptone, 171 mM NaCl, 0.2% agar) supplemented with the antibiotic ampicillin (0.1 mg/mL), 20 mg/mL X-gal (5-bromo-4-chloro-3-indolyl-β-D-galactopyranoside) and 100 mM IPTG (isopropyl β-d-1-thiogalactopyranoside) for blue/white screening. White bacterial colonies were selected for plasmid purification via the phenol‒chloroform method. Insert sequences within the pGEM-T Easy vector were verified by restriction digestion using BamHI (Thermo Fisher) and XhoI (Thermo Fisher). The purified DNA bands were then ligated into pcDNA3.1 (Thermo Fisher) previously digested with BamHI and XhoI using T4 ligase. The plasmids were then transformed into DH5α, and the plasmid DNA was purified via the phenol‒chloroform extraction method. Sanger sequencing performed by the National Research Council (Saskatoon, SK, Canada) confirmed proper insertion of the peptides into pcDNA3.1 and confirmed the correct reading frames between epitope tags and proteins.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCell culture and plasmid transfection\u003c/h3\u003e\n\u003cp\u003eThe TNBC cell line MDA-MB-231 was obtained from the American Type Culture Collection (ATCC). The cells were grown in Dulbecco\u0026rsquo;s modified Eagle\u0026rsquo;s medium (DMEM, Invitrogen) supplemented with 10% fetal bovine serum (FBS, Invitrogen) and 1X Ab/Am (100 U/mL penicillin, 100 mg/mL streptomycin, 0.25 \u0026micro;g/mL amphotericin B [Invitrogen]), according to previous methods (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e), unless otherwise stated. Incubators were maintained at 37\u003csup\u003e\u0026deg;\u003c/sup\u003eC and 5% CO\u003csub\u003e2\u003c/sub\u003e. The cells were transfected via Lipofectamine 3000 (Thermo Fisher) following the manufacturer\u0026rsquo;s protocol. Stable integration of the plasmids was achieved by persistent exposure to the neomycin analog geneticin (Invitrogen) in 2%, 3%, or 4% increments for 48 hr each. Drug-sensitive MCF7 human breast cells and MCF7 cells resistant to tamoxifen (TAM) were obtained from the American Type Culture Collection (CRL-3435; ATCC). TAM resistance was maintained in 1 \u0026micro;M TAM for 8\u0026ndash;12 months. The cells were cultured in high-glucose DMEM (Gibco) supplemented with 10% FBS and penicillin\u0026ndash;streptomycin (Gibco) in 75 cm tissue culture flasks (Corning) in a humidified atmosphere (5% CO\u003csub\u003e2\u003c/sub\u003e) at 37\u0026deg;C.\u003c/p\u003e\n\u003ch3\u003eWestern blotting\u003c/h3\u003e\u003cp\u003eWestern blotting was performed as previously described (\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e). The cells were harvested from the cell culture dishes in 1 mL of 1x phosphate-buffered saline (PBS; 0.067 M PO\u003csub\u003e4\u003c/sub\u003e) with a rubber policeman. The cells were then pelleted at 10,000 rpm for 2 minutes, after which the PBS was removed. The pellet was then resuspended in 100 \u0026micro;L of 1X radioimmunoprecipitation (RIPA) buffer (20 mM Tris-HCl [pH 7.5], 150 mM NaCl, 10% glycerol, 0.5 mM ethylenediaminetetraacetic acid [EDTA], 0.1 mM Egtazic acid [EGTA], 0.1% sodium dodecyl sulfate [SDS] plus 1X mammalian cell anti-protease cocktail [Millipore Sigma]). The cells were then lysed via pulse sonication and centrifuged at 18000 rpm and 4\u003csup\u003e\u0026deg;\u003c/sup\u003eC for 5 minutes. The supernatant was decanted, and the pellet was discarded. The commercial Bradford assay (Bio-Rad) was used to quantify the protein content in the lysate on the basis of a standard curve in a SmartSpec 3000 (Bio-Rad). A lysate aliquot was then diluted into 100 \u0026micro;L of RIPA buffer (to reach the desired concentration), and the protein sample was denatured with 5x loading buffer (5x loading buffer [250 mM Tris HCl pH 6.8, 10% w/v SDS], 15% v/v 2-mercaptoethanol, 30% v/v glycerol, and trace bromophenol blue) and boiled for 2 min. Lysates were then separated through an acrylamide gel between 7.5% and 15% at 150 V. The gel was then transferred onto a nitrocellulose membrane (Bio-Rad) in 1X transfer buffer (0.19 M glycine, 25 mM tris base, 10% v/v methanol) at 90 V for 1.5 hrs. After transfer, the membranes were stained with Ponceau S (0.1% (w/v) Ponceau S (Thermo Fisher) in 1% v/v acetic acid) as a nonspecific protein stain and scanned to document the relative loads. Ponceau S was then washed from the membrane with two washes in 1x PBS with 0.1% Tween 20 (PBST) for 5 min each, with agitation. The membrane was then blocked with 5% w/v skim milk in 1X PBST solution at room temperature (RT) for one hr. The primary antibodies were incubated with either 1:1000 (total protein) or 1:500 (phospho-protein) dilutions in 5% skim milk in PBST overnight at 4\u003csup\u003e\u0026deg;\u003c/sup\u003eC. The membranes were then washed 3 times for 10 min in 5% skim milk in PBST at RT. The membrane was then incubated with a 1:10,000 dilution of secondary antibody-horseradish peroxidase (HRP) conjugates in 5% skim milk/PBST solution for 1 hr at RT. Three 10 min washes were then performed with 1X PBST. This was followed by a 5 min incubation with enhanced chemiluminescent (ECL) reagent (Bio-Rad), imaging with a VersaDoc, and analysis with QuantitiyOne software (Bio-Rad; version 4.6.9).\u003c/p\u003e\n\u003ch3\u003eTrypan blue\u003c/h3\u003e\n\u003cp\u003eTrypan blue was used to determine the number of viable cells in a cell suspension, as previously described (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e). Six-well culture plates were seeded with 0.3 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells and grown in DMEM. For counting, the medium was removed, replaced with TrypLETM Express and centrifuged at 2000 \u0026times; g for 3 minutes. The pellet was resuspended in 1X PBS. One part of the cell suspension was combined with one part 0.4% trypan blue and incubated for 3 minutes at RT before being counted via a hemocytometer. A total of 10 \u0026micro;L of the trypan blue cell mixture was added to the hemocytometer, and under a light microscope, the unstained (viable) cells with an intact plasma membrane and the stained (nonviable) cells with a breached membrane were counted separately. The concentrations of viable and nonviable cells in a 1 mL cell suspension were used to determine the percentage of viable cells via the following equation: % viable cells = (number of viable cells per mL/total number of cells per mL) \u0026times; 100.\u003c/p\u003e\n\u003ch3\u003eMTT assay\u003c/h3\u003e\n\u003cp\u003eMTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide; Millipore Sigma) tetrazolium reduction to formazan crystals was used to determine mitochondrial activity, a proxy for cell viability within a given cell population, as described previously (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e). Triple-negative MDA-MB-231 cells were plated in a 6-well plate at 40% confluence and treated with 1 \u0026micro;M DOX hydrochloride (Pfizer; Brandon, MB, Canada) for 48 hours in FBS-supplemented DMEM. The MTT solution was added to phenol red-free DMEM to a final concentration of 0.45 mg/mL. Phenol red-free medium was used to prevent phenol red and MTT absorption spectra from overlapping during the formazan absorption readings. The MTT solution was supplemented with 10% FBS and incubated at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e for 2 hours. The MTT/FBS mixture was then removed and replaced with 1 mL of 99.5% dimethyl sulfoxide (DMSO) for solubilization. The absorbance of the resulting solution was measured at λ570 nm with a SmartSpec 3000 spectrophotometer (Bio-Rad; Bio-Rad Laboratories, Hercules, CA, United States).\u003c/p\u003e\u003cp\u003e\u003cb\u003eIn vitro\u003c/b\u003e \u003cb\u003eubiquitination assay\u003c/b\u003e\u003c/p\u003e\u003cb\u003eCoimmunoprecipitation (Co-IP)\u003c/b\u003e: Co-IPs were performed as previously described (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Whole-cell lysates were prepared by incubating cells with 300 \u0026micro;L of Co-IP lysis buffer (50 mM Tris pH 7.5, 150 mM NaCl, 2 mM MgCl\u003csub\u003e2\u003c/sub\u003e, 0.5% NP-40, 10% glycerol, and 1 mM DTT) for 30 min at 4\u0026deg;C, followed by centrifugation at 15,000 \u0026times; g for 10 min, with retention of the supernatants. The protein content was then determined via a Bradford assay, with 1 mg of protein diluted in 500 \u0026micro;L of Co-IP lysis buffer. The lysates were then precleared by incubating them with 60 \u0026micro;L of a 50/50 agarose bead mixture (30 L total beads) for 30 min at 4\u0026deg;C with rotation. The lysates were then centrifuged at 2,000 \u0026times; g for 2 min, after which the supernatant was retained. The lysates were then incubated overnight with 1.5 \u0026micro;L of anti-CDC27 antibody (Abcam, ab10538). A total of 20 \u0026micro;L of a 50/50 Sepharose A bead mixture was added, and the mixture was incubated at 4\u0026deg;C for 2 hr with rotation. The mixture was subsequently centrifuged at 2,000 \u0026times; g for 2 min, after which the supernatant was retained as the unbound sample. The beads were washed 3 times by resuspending them in 1000 \u0026micro;L of Co-IP lysis buffer, followed by centrifugation at 2,000 \u0026times; g for 2 min. The Sepharose A bead-antibody conjugates were finally resuspended in 10 \u0026micro;L of 10 mM HEPES, pH 7.4.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eIn\u003c/em\u003e \u003cb\u003evitro\u003c/b\u003e \u003cb\u003eubiquitination\u003c/b\u003e: For the ubiquitination reaction, based on a previous method (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e), 50 nM E1 (E-305-025, R\u0026amp;D Systems), 0.05 mg/mL E2 (E2-654-100, R\u0026amp;D Systems), 10 \u0026micro;L of purified APC, 1X energy regeneration system (B-10, R\u0026amp;D Systems), 5 ng/mL securin (ab87664, Abcam), and 1.25 mg/mL ubiquitin (U-115-01 M, R\u0026amp;D Systems) were mixed together in a final volume of 20 \u0026micro;L and then incubated for 1 hr at 37\u0026deg;C. The reaction was stopped by the addition of SDS‒PAGE sample buffer and incubation at 95\u0026deg;C for 5 min.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eReverse transcriptase PCR (rtPCR): RNA extraction and cDNA synthesis\u003c/h2\u003e\u003cp\u003ertPCR was conducted as previously described (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). The MDA-MB-231 cells were grown to 90% confluence in 10 cm plates (~\u0026thinsp;8 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells), after which the medium was removed, and 350 \u0026micro;L of lysis buffer was added (10 mM Tris pH 7.4, 0.25% IGEPAL CA-630, and 150 mM NaCl). The cells were then scraped into a 1.5 mL microcentrifuge tube via a rubber policeman. RNA was extracted and purified via the EZ Tissue/Cell Total RNA Miniprep Kit (Bio Basic) following the manufacturer\u0026rsquo;s protocol. Briefly, the lysate was transferred to a gDNA Eliminator Column, kept at RT for 1 minute and centrifuged at 9,000 \u0026times; g for 1 minute at RT. Next, 250 \u0026micro;L of 95% ethanol was added, and the sample was centrifuged at 9,000 \u0026times; g for 1 min at RT. A total of 500 \u0026micro;L GT solution was then added to the pellet, followed by centrifugation at 9,000 \u0026times; g for 1 min at RT. Then, 500 \u0026micro;L of NT solution was added, and the mixture was centrifuged as described. The column mixture was then transferred to an RNase-free centrifuge tube and dried (3\u0026ndash;5 minutes). RNase-free water was added, and the mixture was centrifuged at 9,000 \u0026times; g for 2 minutes. To quantify and determine the integrity of the RNA, the sample concentrations were measured via a NanoDrop Spectrophotometer (NanodropTM One/OneC Microvolume UV‒Vis Spectrophotometer, Thermo Fisher) to determine the A260/280 ratio. For cDNA synthesis, PCR was performed with 5 \u0026micro;g of RNA, 0.2 \u0026micro;g/\u0026micro;L random hexamer primer (Thermo Scientific), 1 \u0026micro;L of 10 mM dNTP mixture (Thermo Fisher), and nuclease-free water for a total volume of 14.5 \u0026micro;L. The mixture was vortexed before the addition of 1X reverse transcriptase buffer, 0.5 \u0026micro;L of RiboLock RNase Inhibitor (Thermo Fisher), and 1 \u0026micro;L of Maxima H Minus Reverse Transcriptase (200 U/\u0026micro;L; Thermo Fisher). The PCR thermal cycler was programmed with the lid temperature held at 95\u0026deg;C, followed by incubation at 25\u0026deg;C for 10 minutes, 50\u0026deg;C for 30 minutes, 85\u0026deg;C for 5 minutes, and 4\u0026deg;C for 5 minutes. The product was removed, and 30 \u0026micro;L of nuclease-free water was added for a final volume of 50 \u0026micro;L. PCR was performed on the cDNA via primers specific for the peptide insert (forward primer: 5\u0026rsquo;ATCCTCGTCGATTTCTGGGC 3\u0026rsquo;, reverse primer: 5\u0026rsquo;AATCGGGGCGATCATTTTGC 3\u0026rsquo;) and control primers specific for the EFEMP2 extracellular matrix (forward primer: 5\u0026rsquo;GCCCAAACCTGTGTCAACTTC 3\u0026rsquo;, reverse primer: 5\u0026rsquo;CGGTTCTCAGAGACCTGGATG 3\u0026rsquo;). The PCR was performed with 5X Phusion Hot Start buffer and final concentrations of 200 \u0026micro;M dNTPs, 0.02 U/\u0026micro;L Phusion Hot Start II DNA Polymerase (Thermo Fisher), 100 ng/\u0026micro;L template DNA, and 0.5 \u0026micro;M of each primer. The PCR thermal cycler was programmed as follows: initial denaturation at 98\u0026deg;C for 30 seconds; denaturation at 98\u0026deg;C for 10 seconds; primer annealing at 61\u0026deg;C for 30 seconds; extension at 72\u0026deg;C for 30 seconds; and a final extension at 72\u0026deg;C for 10 minutes. The PCR products were then separated through an 8% polyacrylamide gel to obtain higher resolution bands.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eImmunofluorescence\u003c/h3\u003e\n\u003cp\u003eImmunofluorescence was conducted according to previously described methods (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e). Briefly, the cells were grown on coverslips to 60% confluence. The cells were then fixed by incubation in 4% paraformaldehyde for 10 min at RT, washed twice with 1X PBS and stored at 4\u0026deg;C. The cells were permeabilized by incubation in 0.5% Triton X-100 for 10 min followed by 0.05% Triton X-100 for 5 min. The cells were incubated with a 1:200 primary antibody dilution in 1% bovine serum albumin (BSA) for 1 hour in a humidity chamber at RT. The cells were washed with 0.05% Triton X-100 and then incubated with a 1:200 dilution of secondary fluorescent antibody in 1% BSA for 1 hour in a humidified chamber at RT. The cells were then washed with 0.05% Triton X-100 for 5 min at RT. 4\u0026prime;,6-Diamidino-2-phenylindole (DAPI) droplets were then placed onto coverslips with adhered cells, with the edges sealed with nail polish and stored at 4\u003csup\u003e\u0026deg;\u003c/sup\u003eC. The slides were imaged using an Olympus BX-51 microscope equipped with Infinity software v.5.0.3 (Lumenera, Ottawa, Canada).\u003c/p\u003e\n\u003ch3\u003eWound healing assay\u003c/h3\u003e\n\u003cp\u003eAs previously described (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e), stably transfected MDA-MB-231 cells were grown in a 6-well plate to 50% confluence and treated for 48 hours with 0, 0.25, 0.50, 0.75 or 1.0 \u0026micro;M DOX or 10 or 20 \u0026micro;M Mad2 inhibitor-1 (M2I-1; Cayman Chemicals; Ann Arbor, MI, United States) diluted in DMEM supplemented with 10% FBS. After 48 hours, a scratch was created halfway down the middle of the well via a cell scratcher. The medium was removed, and an image of the well was taken via a light microscope. Fresh medium was added once the initial hour 0 image was captured, and the cells were incubated at 37\u0026deg;C with 5% CO2 for 5 hours. The same process was repeated at hours 5, 10, and 24. The distance traveled by the cells over time was quantified by measuring the width of the scratch at each interval via ImageJ (National Institute of Health; Java 1.8 0_45).\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eXenotransplantation of cancer cells\u003c/h2\u003e\u003cp\u003eTransfected MDA-MB-231 cells were seeded in 15 cm plates and grown to 60% confluence in DMEM according to our previous methods (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). The medium was then removed, and the plate was washed in 1X PBS, which was replaced with TrypLETM Express and incubated at 37\u0026deg;C with 5% CO2 for 5 minutes. The cell mixture was then spun down at 2000 \u0026times; g for 3 minutes, and the pellet was resuspended in 1 mL of 1X PBS. Centrifugation was repeated, and the pellet was again resuspended in 1 mL of PBS to create the injectate. The number of viable cells from each cell line was counted via Trypan blue prior to injection to ensure that the same number of viable cells caused tumor growth in each treatment group. As previously described (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e), approximately 1.0 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e live cells were subcutaneously injected into the left lower quadrant of the mammary fat pad of female NOD \u003cem\u003eSCID\u003c/em\u003e gamma (NSG) mice (NOD. Cg-\u003cem\u003ePrkdcscid Il2rgtm1Wjl\u003c/em\u003e/SzJ; Jackson Laboratory, Sacramento, CA, United States) via a 0.5 mL syringe with a 27 G \u0026times; \u0026frac12; hypodermic needle. The mice were used between the ages of 8 and 14 weeks and had \u003cem\u003ead libitum\u003c/em\u003e access to food and water, as monitored by the Lab Animal Service Unit (LASU; University of Saskatchewan). The mice were 22.3\u0026ndash;25.5 g according to the Jackson Laboratory web site (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.jax.org/jax-mice-and-services/strain-data-sheet-pages/body-weight-chart-005557\u003c/span\u003e\u003cspan address=\"https://www.jax.org/jax-mice-and-services/strain-data-sheet-pages/body-weight-chart-005557\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The injection site was disinfected prior to injection via antiseptic isopropyl alcohol pads, and the mice were sedated via isoflurane anesthesia. Obvious tumor growth was generally observed beginning at 5 weeks after cell injection. Treatments began once the tumors were palpable, and measurements began once they reached a volume of ~\u0026thinsp;50 mm\u003csup\u003e3\u003c/sup\u003e. Measurements were performed via digital calipers and were performed weekly until the mice were euthanized. Body weights were also measured weekly. The equation used for the volumetric tumor measurements considered length, width, and height as follows: \u0026#119881; = \u003cimg 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\" style=\"width: 90px; height: 32.5301px;\" width=\"90\" height=\"32.5301\"\u003e (\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e). The treatments included DOX, M2I-1, and APCIN (Millipore Sigma). The mice were euthanized by anaesthetic overdose, with cervical dislocation serving as a secondary method, according to the University Animal Care Committee and the Animal Research Ethics Board at the U of Sask, in accordance with the ARRIVE principles. Once the mice were euthanized, the tumors were excised, placed in 95% fetal bovine serum (FBS)/DMSO and placed in liquid nitrogen for future use. All experiments were approved by the University of Saskatchewan animal ethics office, following the guidelines of the Canadian Council on Animal Care and ARRIVE (Animal Research: Reporting of In Vivo Experiments).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eStatistical methods\u003c/h2\u003e\u003cp\u003eUnpaired t tests were performed between the control cell line and individual peptide-expressing cell lines to determine statistical significance. Statistical analysis was performed via GraphPad Prism (version 8.4.1). Parametric testing was performed to determine whether the datasets were normally distributed, followed by one- and two-way analyses of variance (ANOVAs) via GraphPad Prism Software (version 9.3.1). Post hoc testing was subsequently performed via Tukey\u0026rsquo;s test with an alpha set at 0.05, unless otherwise stated. * = P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** = P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** = P\u0026thinsp;\u0026lt;\u0026thinsp;0.001. \u003cem\u003eIn vitro\u003c/em\u003e experiments were performed in triplicate, and \u003cem\u003ein vivo\u003c/em\u003e experiments were performed once, with an n of at least 4.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cb\u003eYeast APC binding and activating peptides activate the APC in MDA-MB-231 and matched MCF7 drug-sensitive and drug-resistant cells\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe hypothesized that activating the APC would increase cell health and maintain genomic stability (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). We previously reported that APC activation via M2I-1 resensitized MDR canine and human cells to drug treatment (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). To test whether the APC-binding and activating peptides also resensitized MDR human breast cancer cells to therapy, we cloned the yeast peptides into the human pcDNA3.1 expression vector. Since the APC is highly conserved from yeast to humans, we expected that at least some of these peptides would have conserved activity in human cells. We first tested the ability of the pcDNA-peptide constructs to reduce the protein accumulation of APC substrates in MDA-MB-231 triple-negative breast cancer (TNBC) cells. All 7 cloned peptide constructs were stably expressed in MDA-MB-231 cells. MDA-MB-231 cells are aggressive, metastatic, drug-resistant breast cancer cells and serve as excellent models for studying unresponsive breast cancer (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e). Protein lysates were prepared from the stably transfected cells and examined by western blot analysis of the protein levels of APC substrates. The APC targets substrates for ubiquitin- and proteasome-dependent degradation; APC impairment results in increased substrate protein levels, whereas APC activation results in decreased substrate levels (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). We found that cells expressing the 20 amino acid C13-3 and C43-4 peptides displayed from the TrxA backbone presented decreased levels of the APC substrates examined (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-D; average levels of protein expression are shown in \u003cb\u003eTable\u0026nbsp;1\u003c/b\u003e; uncropped blots are shown in \u003cb\u003eSupplemental Fig.\u0026nbsp;1A\u003c/b\u003e), indicating that these peptides activate the APC in human MDA-MB-231 cells. Both the mRNA and protein levels of APC substrates are often reported to be elevated in cancer cells (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e), suggesting that APC impairment is linked to cancer progression (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). This is the first example, to our knowledge, of a peptide believed to bind an APC subunit that can activate the APC and provide anticancer activity against an aggressive cancer cell line.\u003c/p\u003e\u003cp\u003eTo obtain further evidence that the peptides activate the APC, we evaluated the level of APC1 phosphorylated at S355 (APC1\u003csup\u003eph\u003c/sup\u003e) in cells, as APC1\u003csup\u003eph\u003c/sup\u003e is a marker of active APC (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e). MCF7\u003csup\u003eSens\u003c/sup\u003e and MCF7\u003csup\u003eRes\u003c/sup\u003e cells stably expressing C13-3, C43-4, or pcDNA3.1 were subjected to western blotting with antibodies against APC1\u003csup\u003eph\u003c/sup\u003e and total APC1 (APC1\u003csup\u003etot\u003c/sup\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE, top panel; uncropped blots are shown in \u003cb\u003eSupplemental Fig.\u0026nbsp;1B\u003c/b\u003e). The ratios of APC1\u003csup\u003eph\u003c/sup\u003e to APC1\u003csup\u003etot\u003c/sup\u003e were determined \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE, bottom panel), which revealed a more than 5-fold increase in APC1\u003csup\u003eph\u003c/sup\u003e when the peptides were expressed in MCF7\u003csup\u003eRes\u003c/sup\u003e cells, strongly indicating that the peptides directly activate the APC. Next, we used a direct \u003cem\u003ein vitro\u003c/em\u003e assay that measured the ubiquitination of the APC substrate securin. For this assay, the APC was coimmunoprecipitated from MCF7\u003csup\u003eSens\u003c/sup\u003e and MCF7\u003csup\u003eRes\u003c/sup\u003e cells via antibodies against CDC27. A control experiment using APC obtained from MCF7\u003csup\u003eSens\u003c/sup\u003e cells revealed that only when E1, E2, APC, ATP, Ub and securin were added to the reaction did we observe ubiquitinated securin (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). We then compared APC activity in MCF7\u003csup\u003eSens\u003c/sup\u003e and MCF7\u003csup\u003eRes\u003c/sup\u003e cells and observed that the APC was indeed less active in MCF7\u003csup\u003eRes\u003c/sup\u003e cells, with approximately 60% more secuirin ubiquitinated in sensitive cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG, top panel; quantitation shown in the lower panel). Finally, to determine whether the peptides directly activate the APC, we assessed APC activity in MCF7\u003csup\u003eRes\u003c/sup\u003e cells expressing either pcDNA3.1 or cells expressing C13-3 or C43-4. We observed that peptide-expressing cells harbored increased levels of APC activity, particularly when C43-4 was expressed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH, top panel; quantitation shown in the lower panel). This finding demonstrates the conservation of these peptides.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTable\u0026nbsp;1. Altered protein abundances resulting from peptide expression.\u003c/b\u003e Summary of the observed alterations in protein accumulation resulting from C13-3 and C43-4 expression.\u003c/p\u003e\u003cp\u003e\u003cimg 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0yDz4gvy43L2n47ExgMhWLD5GuISUqQgFBQmRyAdbWjVoKNyrNfkpf4fEgGNJhnZ9rTqj4hJRuD1OAmrL5GRNg0K0crEmcgJ/zgApD+v/G8nHgC1jkWAOAy4XWxopQjrh9q1iK+j7AON38hPfUADFSnLWb07CBv2B+PohRgZm/sNn3D7cr1SSyQfyoO+iXjRN51zGbLPpF7St/q/FwI8LnnVWa6IC8qT+98LXshPE5IVb8aT25Rx53x4DHIYQc2X0mU8lx70xX7s6FT+W895jKc66Z3pS+ZLEblHGYhvsSzh8qkHyXip4RbqSxRJ+mT9ZY2XVejdwjjHjC6rtM+Ln4CQ45Xvx0Dy2qDT5DXfP/tZHY/FiNgUXAtLlAvLAFp4FCCZnRrZQmZkBxQi05SmAWeuxJIsAJmUAXsiy/Y0zjn97Xly3oK/KMB65Mt0Jz1TryiKLIrrZ2ugDkEe3H6poTnjm6osNaY8fxLMCIlMwg3CMygiCZeDErD1SBi2HgrF0h03kGTk2CTZ6Cb11C62NJdRUxEGljRH6DWdbgAAEABJREFU98yg0iHjv+BIaR6CjuzoIDWxei31KjVnyPmU86YiqCCO9WQcdYknk/ETzdWKEhWy81g4fhx7FLPWX6GGMcOOWD/bYVnL0uGjomj8hi8x2CL4nsxMTIYc7fR4i1ht+0ZF0e3T4vihcVE0rJEf3rQqL0cq0Xqv5pN58GrhS1rdN6vtDxa+BUl1/lVdf/zUpBi54mj+TkFwOVQF+Z+QZJKqUI0a/uVSHtKsxQK7Ka0yulAaLue1Cp4ZuoBMpr4eBoG09t98MBSdxhzFjLWXEZ9oAv8CNq/UeDC9WNwNbT8ojJ+bFkfnj4uBVdUuDnqyRRtIY+OHr9/1x5ukieMwjvMlta23my1Kknm0ViUf2ZZ6kgTN3w2Q2kImvvxr2fzDjwYa9DwwC+VzRIv3AtCFymAzZlFfp/S74XAuj/tTJ+pjXWWcwuBVE6+W0iOqk0wI8O9c+eexpwnLXpJFJjI8brldbv9dKiYo+Tzs8FJJd7Apmc+5a7DgLExtUybABS6OernwcSQNUGlqW9YK8XjmRU1ZCvdwtgH/UjmbRUqSeZQnRW47ztuBFjulA5xkm3FbazyDZqgt512SFlbVynjiVXKcnvd1cVpPFxuULeQKrhMT8ZdotVyxmBu4vAxZIK+HLSqR2YXz4P5jSxMyl899mc2lLEsqFnGFD/VN9s+YFsj5V9xerA1tVb8QaVP95Vj7sUlxGlPF0LRWAfD+t9vvm/HdThMy/+yZm6MBxWhxIpuGZG8JakM3ZwPOXo0jF4vaL3qTBrgIujUrTvK+BL6h8cq4itskMZfxzst58X2jImAtvSYg5X4zkt9tGxSBHy2mWONY0McB7MfzQJemxfAVzQNs+qGic2RjBF6PR/dJJ/DtkINoPfQQ1u4NkvcRl5gCO70Gvi/eHtKMzMasQef77kBzKWvUm9T0Q5H8Tvjm3YJoR348rjj+q2U90YFw/OD1/PD1ssdnb/nh2/cL0Tzri67NSuAdsr5we5X0c5btwfL3x0+K4zMyEfNYlxV4Al/aE8jzqWbJwjDRaEZkrJGEI7NNkHADKpCAqFvVB1+QpqfuSz6oQgKRBU3D6vmlipMHQbECTmR68sIXNNE1+p+vbLiKRV2g12mwJ0H3KqnxeHIqSESnORGfT2oWQNlCzmChxgSpHZlSfEgIsSbgLSrjjUresLXRwAOOr1uSmvWTWr54pawHapOJpQ1pHjguD5qnCtJzWhhPjEnU9lHU9ikpZnmXLABfoEmFB9e7NKgCaNKrUtKNBGlBfELC050E4etkcmxIZkpuj1fLe6BaGQ+5z+ZrEly8KiwT4Cw1PjqSeK/RwC1HZso8NKnWJTMGE1gWfB40mbVvWBiNiChXK+OOt6ivVS3tIevAAtyOVpJfvu0PzrMKTXSFyPTyLgnTliRsuW/KiOrrDgR0JJFKkBB0JxJyMzyRJqw4sBbn5dLuoPknU3wWrNyGncmE/RO5n2nyKeXvDG7jb2nsdaXFTCXqC0xQyxVykZNdKxK6PO4/JeHNi50OHxXBT5SOFyNdPy2BBiSgbfRCkmKO+zMJ586fFJWEmQkSV4DHr5uTAa3eL0zCuzg6Uh7sWJCzidXeVo/qFbyovOK0MCoGXux0+rioPLYk80oeIjjcd1+hfteFSPCPtBjq2LgIEfNiYJnDBKjFewUpfQn8QP48wfBEU476IZfNdXhuHA0W1trVquyFxv8rAB4zPB5fJ/zYTPk+LT4lAcxww9zurLVhjb4dmbWLU5vbGnSwoc7DY4ux3XcqkkwwGlrQYoU1gwVJ28P4fVg9vzRFOpBmGBk+VA1ULe0mTZVlCWchhFz01qjoiXdezgNvd1s40WKJF7lN3ywAJrksyxv9L79c+DK5ZcKUIcsccWqghRvLMm+ax7xdbeFAygAm3yzrXi7jAV6wsYxjglehqKvcr/Y2yTFulxdJrub3tEUtmvfefyWvxEvQXfM+qjo0H75K814ewu318l7S7PgFkZ5Xy3mgOM27xXydwWOiPllRihRwlCbHpkQsm9K45LHF7UFZPdZ/7bHm9gwy44mHV+31aGKzoVURr75vhCWB+qqsDTNIXgVMX31Zdv73X89LDarDil1B6D7xBP6how0x2Jq0yr8SnIA5668hMdmEiOhk/LnkPMb+fR7F/ZxQqbgrQqOS0WvqKQyedxYhdF62sDPKFXGV5fCX4C+kfvMpN9r6fSGYveEqmIxxZypX2FWSMQ5X7tEQCMhrj/okDOu9kg/OtIKPI+0O/1I1kxkWbntPRpDm5wjmEv48eJiApk40FuoLQrbJiIXnsY1WiVyTGhW9EB5lxJLtN8D9yEgEatTiQMzbdA2xlLcQqW1rIl5VmfoDb5LneH/vuIkpKy6RypxLAZFuoBhpeZgYsTZiMoV1m3Ac58jkxir3KkS8n6Z2h+/tYVzq3T5MyodPwySxdIAzHEnoHj4XhX923gRP8CVpQmPiamI2m5a9EAKsNYlLMMn2ZyH7brU8kqjw5ONDApw1JDwJ8aqTSQTv6bCnBQkLeN6zwRoXLos3tvp62aFmJS9wG7GA5j1gnEd8khmepPnl8cxFU/OD0zMBS0o2Y8vhUFwkUzqvSrkPFaKJ1ZX6o7ebjZwceL+X2QR4U324vLKk8eEJ/rsPC6NMgAuMJgvO0wqbV9ClCrqAF2I8gXDd1+8PIVmTRIs3F7SsVxAOtjquwnPpWCPHGpnRJHdPX46V2lXW2HGbCRpa3B/ZgWRsVJwRO4+FSRNVcRprTHD9SCPIC9PY+BTsOx2JFMKV8Rsw+yw6jDqCkYvPg7oMilJ8VyIu3C9wtw8VRP9gx0tolgW88K1a2h3XQhPx6/TT6EEakYgYI8oROWKCzhqnu2WXXf1ZTrJmhfe79m1RGkxouH+n1lfQwsGGiJ0zhBAYtiAQI8iF09xoTLFg1rqrYJkLBik1wZ3faWEaLRxjE1Lw15rL2HQwBO+/mhdsGTlxKVpqlsb+fUHK5HK0KPHzcaB8qMHp+3H+53iy81JpD7Qjc0VJUlEnkuBZszcYxy9E0SBIRZltkKOok8/ffI0azgBXBwNukn1yLcU7fSUGf5NdkleQPFhYS3T8YrQUPpwX78U5dSmWhJSNVGnyBPVRjfz4+I0CYPWpRh2AyRYfs2qUU5djMGbpeawiQnU9JEFG4Uk5Jw4KWfls9sUTEq+oS9PkmEBmxCVbr+PCjTjwANao+XnQfFuvMF4hDR0LUhdqe3Ys5JikTCMCvHzndazdF4RoEp4cR0+r+sBrcUih5aGJHAvNs1djYSLBmXr7FtACUponuAwmvYu3XpOE9m8iSalxANbkMPlmTV+tyt5S3c0ToI4S8aSp12nWqOqYAQEmFzxxmExmSUJP0Hjk8crjk1eFFgs1bFp8C8lDJpKdyYy9+0SE9GWtjRtphThMetz+RWkyevGk2pWI6MR/LkpvR3s9ERlbvFTandpZ4By1fc8pJ/H7X6cRQ5MoR9LRuL8cHI8u446ToD6JmeuuYOn2m5IgMxlxczZwNOl4gcSTROdxx+R+Pu4TPkSCePOsD5EfJudjl16QC6+Ofx6TE3h5WkAx6dt8MAR/E9nbfzoKPLn453FEfk97sJySmT9nX6yhn0MLkyXbrmPToWB5d06kgXmbNCuTu7yAmT1exOxfXkTPL0pIjcMeWszwItLPxw5+PvaoSpoGNi2yXL9BWkGeXFf+e1Oatz+s7iu1+zSkYdAJqYW4rSvI8m7/ssYRQqBQPifS+gsi4jqpHeKHGFyINLEmkIkuy4vb02f3a8bCg/qrF2l1uN9y/71VZwst3AgB+ue5j8k4xyERBiabl4LiU8NvJUg9o/ipJ5m/5264hgnLL+Hg2ShJdDjUh8r9oo4/3n4pD19KRQTXB/dkUHioT46XuNeCE8HsfdGW6xgw+wymr74EXilZ0Ygl2yMLKRYyvLGV+iySU8zE+s1gtsnsnx3H58mO/QRdcDyN0GEVuj2ZJMgLnIcPmTP4cdhLJOyOX4jBtTQSw+G3uwRaEbLQtcBCq/7UUM479Sy7fee8+vBgW0cr34VEZAfQ6o0nHW4vJhh8NzxA83jYQE+jkzcyHwmMRixpAbhtecJgE5hGF2YiMiwEOQ2n1zI0ko4uqBtQkIUcaW3om/1sSYvI49FEaZOMFkmumXBRsPxnocHZUPZSMLM6NzzaCCbTl4ISqD+k5icjqy+JABPMkv5OyEuqcZ44WHPGj8OCgQZQncyPbk6pe3DoUv6z1pYJw6lLqZvGuW1YgMvA9C8agVnAzWPz2IVoXLgZh3NEcDk6NTf4nVmOaRqUKzS+LwXF4UhgFJgEcxx2OmrYkqRtYrI98NuyZNIqBCbKnJ4dx2EXHJGEQ+ciEUST7zXWOJMn98v8nnZ0BkSSZuAyaZRZBjGxC4pIpMlUL8NYSzSkTVk0eD0fdKTQ4UUSkyASJzL8efvicWgk2cz4GWlM8f1phLNO0xBPspQXoKlHC+Eh5EMDF27ESzlelyZL3hNlJI3DKdIK8YMrrDno07yUNJe8XsFTPkXJYzKLrsBF0cQtD3IsszaRr4SgFJSA+xVv6GU/O9IMehNh9SJtH2v0jtE8cIMW0FxXDs9J7ippqYYvDETPySfRd8YZIiKR0NJvQJCVw4wY0sjwWPmGTKut61M/12nYfCgE3HeFIHzS4gshiIgDdMDtH5aTN6lv66kfOznopBYHAlKJkIfMuozpiYsxOEnjOJw0RxR0exaPfH3rvh45q2eTwYGzERhNas9pRHJY8CVTZxfiFlSCEOVLvtHQyGQ5ybAKmgcCm69YoLLKO4E0A0yKWJBQ35YM08vFFrwxlVV17Md7QybRCvA3WuUNnXdOEqvdJ8PveuPiriEq4HEgsPtEOEbQQJ1OqlFWafMEyZNGTFyKzP4MrcoHzT0nV+V/knZv0oqL4BUfCyWDXgNvSvX3cUAxP+d08wAPNJmYvvQ6Id9Hwat9TUttTf7mMpg0cV9hAs19iDdZVi7hTqlS/zkf7jPcr5aTZo81A3/MOgPWIPCTe0YS6qkx1bcVAR6jVUp5gMeljUGHxjV90eh/+ZGPyA/HYYyLkr2fceVrdow/H3k/BR9ZKLNgTaWlgA2RUo0EAAtYDs/Kcbh1cuNwokbpEx+n15Nwt6MFD29Y5nAmyjyxfv2eP9h0xmTlX+qLRpI9HJ7JUYcRQoD+SfaYU4PoBqzkWk+aRL5f7rtMoG0Nt153cfR8NJZuu4F5pO1gDdbE5RdxJSSe8hKp+Txn3zYGAca1UF5H8Jji2+Pxs+NoGIYvPIcBc85g4JyzmLPhijSfsHb2wJlIcNuxaZjTRMQk4yRNmknJFhrf7iiSzxGXyMQ4bP45SneVFrkEPrL4kLd10ZKPJl8/bwdUK+sJJjQguFNI08h5c8ogIrCT/rkkTVmDaR6YsvISDpyNlASMw3OSY1nJi0Cu/yG6h2iWndxZ5U1YSMtpA54fk0hecbxdx8Mxd+NVLMEo6gsAABAASURBVNx8HUbyMxEuPOY4OmskS9BipaivI3QagcaeGZwgIIUQ4IdJWBHA8vPizQSMWXIBPKeyLGfNnnXhkSHpYzll+fJAGWW3yCm0sk4komIkQcMTkrhLBTnsGK3ieKXl6mjAl2+nbgBs/o6/3HjGrPI6sfP4pBTZiByHd+bzRscbYQngPTx5SKvDG575CS/ePMc70D1IDcfC7y7FKu8niEAKtTkLQ+4DQqS2PA8k3hvDfryvhjef86TZ/N2CaPw/X/Cj6CTX5GDkPTy9vyopN8/xno6rvIonwZhkNMs+YCBC1K5hYbmxmTU1nA40YPl45lqsFJzupAJu9X4h9P6yJE18zrB+WJXOewd438V71fLIPHiD+9fvBIA3wQvKxxpXHSHNhH55HMBPTDH+f++8gZGLzmM0kdR5m65JtTkL0GpkttbS2poP/IQk79niiYlxjCBNCZs2eGsPh79KE9ZnpCZ/r1peDr6rE2khfEwkLUJErFH6sEmt3it58flbfmTGcJB+LEv8yHTiaKcHk1omJOfJfMrkWEa4j69rIYkyFu8b4j06vB+kXcMi4P1m0fGpZbMMYhK1cncQmWfjSSNtkatsvi+Z+Dn74vHWqHo+9KSxxO944Un0KuF0kcbkuatx8lFyHlc8Tpng8O2fvByDcGpzO9K28Gblm+FJuETmFfAmH4rAWLHphTcpf/SGL2xoTJP3Hf+sNbtM2nqOz/tWepFcaEEyg8cvR+Y2P0zaPR7ThfI6SDPWR2/kx2e1/fA1xXNzsuG5m6PmKMf3q6NFHTt+pUtmsSSk1ozvnU11/CQjm4nZnPxpHT+wtpq1PnFkPQF9Wr0fgG7NSsh9apwveWX5n0wkiU2QHKe4nyM+ebMAPqJFzedv+Us56ULaW277LBM/gmeOJTtJyWbwRMfsHoQa/WeCgf0TSGglJZtkJ+Tw8JgkjF9+ATxY2C74Uik3MjEYwKqzWbR64onyCg0uNk8lUjo/H3sU8HYk1V4U1uwJptVECkoWdAKrTFk4sVrTRGTLSI3HdUkwmmlFaJETpSybrrlSvIrj/DgOr+DYT7mHRcAiXzHAWCYR2eF2zZgTD6Q1NDnw5mRAgCfHt6rkkStFHkBWIcntFk+DlNuYJ60gUrGOW3oBkXFGqR4/S8KVy8jvaY+87rZSUcDXCdQvOB+2O/+z6yZ4YuTNq0x6WCDHkso3hVY7vJocs+wCmFznJ5MFT2g1K3mDJzeTibNjygT1SUOA0eAnp7zJPHCVzDpLtt7Ash3XsXT7DczbeA0XyVzBUdl0xBhyG/BYqlbOA2xKKpTXXo67XaRhuURmQl4dcpzyRVzkZORPY5mvOY+MjslNxms+TyGmxJsomXTxpmZ+hQE/NcJh7Ljv3AhNkuUV8LZH/1Zl0O6DItTbOPQujgqif3AkIQT2nY7AWTKdMfn+iEh4v5al8fZLPlKjzKvnKOqHXPfxnV6Q+1T4pZk8wVBSPK8fxpV1X4ypRjPTVdJi8f4dHlNZ3Tf7XaG2PksaXB6b8TT2TpAZJCQqCUw8Nx8KI4IUR2ZBHd6s7APW2IRRGC+OqYlhJPnM6XiuYEw3Hwql+LF8Cm8yUTFpvk5mnkSaa5hgHzoXhSXbryM6PgWlCznjnap5UbW0O5wd9FLuy/aVqbP3F9eT5STfe6o849EH7posmOTeMw5LMppkH+f5jSdR9mNc+eELXjx8S4s8xuff4xESE5aj9rY68IM+TIIYNzZNJhF+8aSQkEoBLhwAj2vWcNMpeFHKWPJDQLakibVwJ+CAx+yoSz3mHJ9wdtzBuRNOWXUJf8w8g1U0sTErz1gsXy/fdQP9yWwwdfVlqebkcJ2mYfvRcPCGQ97jMWx+IH6fcRp9ySx1lFg7580T4Li/L2DQ3LMYtSQQY5edR3BkEmasu4xfppwk/3PSdMLhXcYfx7XQBPx7IkL6T6B03Kg8aFjlOo3KZoHMg/WvtZfRj+rDT2fpdTkOdoYvW7j4RJPc0d+P2m3jgWBoaYPHWjm+vEyT5eD5Z8Gq0eELAjF8wTnZxn8uPQ9uH25nHuzTVl0htfg5Gd5zyinsOhkhhSQTlFGLAzGEVN8jFwVi4ZbrOHMtDoPnnsFw6jNHL0SRScKCSSsuofe0k7I//Dr9FHpMPiHLnM3EmQb3un3B6D7pBJVxFsOt9aB6bye1fFYTr/UecuORV5YWWhXwhnDGJ5zMEXYGnXzhGK8ctxwOI4IQicu0amct6yFSuf9DZJPH/2GahNicwU+H8HtCEpJT5As+txwOBU9Q/xIBmk5jccexMBwl7S7v8WFN7v4zEWCtAQtyFs57T0XI+FGxKeCV54TlF7H/dCSOBEZj5b9BmLX+qqwDC/h9lPavNVfAq/1zNNluPBiCdftCcJDqEhZtBPdBvhcuJ4UWQzy5cj6cH08GrDkaOPuMXEQdOR8FjreZJudNB0Kwgdx0ypvrcPJytNxPtJfqwQTwee43iTS5Tibz0DAad2we+mXyKdlePF5xl09kXDJ4Lug387ScD5YROWasNUp0MzwR7M9bDkaQDOg28QT6TD+NkTS2g4n0rN4TROFnsIjGNxPcq6TZ/YPmFJbtPD/w01a9p56Ucc6RJpfzZDNLL5oHBs89S5rHQJL7Z8EmapYZd6litvPm+1i+46bEaxqZ4CJIM8ZykyualGKSD+3w/bO5qrifk9z8HRKVLO+Xn0TmPVHcD3mvjZEWnGxW7Ef4s7z8fcYp9JpyAgNorvtrzWUi9LFSwdCPcGWlgo7ahcuPSTBiKLVzL5K7g+eewyjS4LKZf+TCQPnUM0Xj6jxWpz3W3J5SZrxy5g2J20l4XSWykVWxLMRYuJ0mNWfGcG5UFpjbjoRKocKC8CapPjPG4VX+FhKuq3cH48SlaGLtILZrwTGyofOL7NbtC8YWWgXwplfWFHBH53yOX4yWxIofTeTV2ZkrqZsmU0wWnCQ78g6a5NhU9iQaMmP9n+dzJo/cpjvIdnyD2k0IbtHMd8xevL9qz8lwrN8fjPU0eXD7BEcmg8M4hYCQJHYDEab1+0MQKIXZrXyYxG46EIq1e4NpsomVWj2evHafCgcLB01Arnr2n4mkSS4YPNmyP0+YXD+up44isYZnK/UlLoM3U7MplQnXrZLUGSNAcGINjau+RAbnb7omtbbsb3Wrdt8Eh/EjquupzViwjqfFBS9MWJD2nXFG7sngx9A1amQe/zwhsT/v81iw+boknZzm/I14zF5/hfI7AyYp1BWoLyTjd8pjBJFbNknxmF1OprS+JMRZkI8jLd0cSvMHCe0tRKLiiHRzPftSfftRnNE0gTJBHkaTKmsatlIcDmOSxStiMxE5Fv48ibDs4QUZ14P3G/ajcjmPoQvO4vQV6msJJvnIPadPDTtDE9NpcH2seDxXR258bgRy3G7rqB9sOhhKGoL4OxYzt983E5vztBDZcSwcO4nUhkQmgppfRuPjFdIObaS81tIYP0FanxMko3kcs7aB5TTPEYHXY0luA1yNyxR/C5FObiMmpYFknmQ5Eh2XAs4vmSZ3zmfzwTApG7akzQM83pFDPnwfLN+20/zJ92JMuaVKYTx5wz7jwtsBkkiTzWOBTaqNSAP5UQ1fsJaUtTR7aHGYQv2aF/OsSd9IcpY13tfCErGT5DM/jRxLfZkXI7y3lffEctkME4/RxGQzLQ4iselQCFYT8eT5kQkn581xHrfLkWSHQdA0IfddaFb0kPnD/jzZcLzMIUi3Q3LS1DiZY3BaTUB2bo0jAfLcGpe9OF++Bn34ms/Z0aUcoHzOcfiaHZ9LP8qXr5V7eATuB0shhOwfdABDzmk0OjGSsOJBF0WqaFZn80qD43A4Mnw08tRodNABQggICuP2Y0eXdJX6b73WNAH252uNT1KD0/oaZJgmkF4nqM8dCBhJ6LKGJZmOtweywOUwJopGasNYIht85EkrjLRAUfFGsJC0Qs/HJDJTRMQmy30uHMZp40jjxguURArj/DhfLovJRxyZNeMoXw7n9Lx6jaZ+EhqdDK4TyXXEUhwj1U9QIs4zItYIXvVyWew4PU98nC/nn0iTRaqRANL8KtPT4oeSSzmRRHlx/WUeJPzZP7VsC7iuqWFJVK5J3h+HP2+OyWA84cqLBcZZ0LjjscJj6n7ulePxuGMnBLfMrVQaXdO/xJrDrXE5hkZRrX58zU6jyBqXrwlo7Oia49AB/KEkcgxrFIf9NIrD4RyWk5xGled6c/1vr7c1TK8J8OJtAS0+QmihWIK0PCX8ncGLzPF/X8TirdfBeAgh0rBCKjZ0bc2bTmUYX/M5Mnz4mv01OqF/GS+r+mRI8kin1GSPlF4lVgjkGAR4QN0k1faPY4/hi377cIxWeWw+yUY3kOurIu6BAIex4yjWo/U84zX7WR37s+NrPrK7/Zyv2XEYOz63Or5ml/Haes5HDmPH5+zuds5h7DKGW6/Zjx1fZ3Tsl9FlDHteznlMsmmv+YADaDHwAM5fjyNiwnf9vNxhzr6PcDLJ8haM5gP2o0mffWj62160G3GYTPvXwMSe2y+n3KEiOzmlpVQ9HxsCcuXNy/THlqPKSCGgEHgUBIykrWOTyKPkodI+fgSYzLD2hXNONJrkE6hWPz6yf05xiuzklJbKWE91/sgIqLXjI0OoMlAIPDYEeOJUY/KxwflEMuI2eiIZP6VMFdl5SkCrYhQCCgGFgEJAIaAQePwI3E+OiuzcD0oqjkJAIaAQUAgoBBQCORYBRXZybNOpiisEFAIKAYXA/SOgYuZmBBTZyc2tr+5dIZCNEeBHu/nx72xcxSdaNX4cPjff/xMFV2We6xBQZCfXNbm6YYVA9kdACAF3Jxv5qv/7qS2TAnb3E/e/4jyr8BSTGfxeHj5yHfj1+y4OevUoNoOhnELgERFQZOcRAVTJFQIKgceLAL/U7+XS7hjcuiy++6AweMLnEvh3c/gHWfn3efja6oQQ8HK1QV4PO9Cp1fupHVkD86iF8esQalbyQc8vSoJ/y43fWNvxo6L49evSqFjU9VGzV+kVArkeAUV2cn0XUAA8HAIq1ZNAgLUzLo4GvF01DwLyOcDORpPv9njzRR8M+LYsRneogC5Ni6NIfkf5My78xtX/VfDCsLbl0e3T4uDf07K+sfhJ1C9jnlxXJlnli7giv5edrE/G8Ac5Z4JXqbgbatN9MrlJMprl77SVLuiEqkT8bPTag2Sn4ioEFAK3IaBG0G2AqEuFgELg2SJQMK8DAshxLfacjISXmy0++p8vfL3tcDEoHlVLuaNOlTzy5xcKUbwPqueDrUGAf6uKfxIiq/e1mEwWMKHgd0myFsVKiJiwpHAYebA/n7Mfl80aG762+vORfzuIjxzOv+3zallP/PhJMbzzcl4kJZvkD8RyGTId5ctx+ZrzAn34msPYj1+ix9fknfmf1FNGMmltPRzGv1GKsoVc4O5iyBxHXSkEFAIPhIAiOw8E14NHVikUAgqB+0eA39YuQz7bAAAQAElEQVRa1NcRrN3h36U6eiEKni42cHXU4+yVWPyz4wYiY41SkyIo249rFkChfI5Ytv0G+McbiSeQ761/4jDyN3dKBTjj/VfzoXENX1Qp4UYaIE2SHyd7HV4p64FGNfLjg9fzozKF2ZI2iTdH856hmpW8USbABfy7QPVfy4/6r+UF149ZSOlCzihf1AX5PO1QuqAzalb2RkBeRzKn2YLTVSzmRmW54+M3fGUdjSlm+HrZ483KPtLvnZfyorifEyDA2SHjh3+zbd/pCIRFJ8PX2x7FfZ0kkcoYR50rBBQC94+Adv9RVUyFgEJAIfBkEdCRRCpAhMDeRgf+1Wn+cUjWirC2xdFeD0d7A5l3NLmRtyERlBpkwjpwJhIr/r0pSc3ttTPoBN5/JS/6tSiN9g2L4Jt6BfHLF6XwUikPuDnb4OdmJdDnq1JoWS9A7g/6/evSaPFuALj8kkRgupDJrOeXJfFHS0r/YWGZR4/PSsI/jwNa1w/A6+W8ZJGsfeH9Nu9Wy4MqJd3RoVER/N6iJJVVQuZdrrALXiDy04/yYXPb1+8WROdPiqLfN6XxVhUf6G5jaXzJPwR66WaCNOX5+tiDtVOyMPWlEMi5CDyzmpNoeWZlq4IVAgoBhUAmBGwMGlyd9ERcgCjS4LBp6GZ4Iq4GJ6CkvxOYJFg3Kn/5tj+uhiRgw/5gONjq4e5syJQXE6QAMnO9Wy0vXJwMOHI+Cqv3BONaaAKZvTR8Uddf7odh7cmq3UHYdSxMllv7RW9UKOIK1u5wht6uNkhMMmPX8TDEJKSgAJnTXivviY0HQnE5OJ6jICgiCVsOheHExZh0UsJ1MqZYpJ9e09CxUVHkJy3Q2auxWL7zJs5di6U62xAZy4e85M+kTmaW9sVmt8iYZOg0AS8XG6pPWoA6KAQUAg+MgPbAKVQChYBCQCHwhBDQ6zTSZOhk7myuSjZaJJGYuvoS5m68hp1Hw7B2XzDYdGRvq5fE5a2X8qDrp8XR+eNiKF/ERablL94PwxuZfdxtERaVjJELAzFm6XkMmnuWiEYcar7gBaPRjE0HQjBh+UUMXRCICzfi4UQaJDYv8f4cziecTElTV1+W6Q6eiSJCJIic2GLJtuvYfSKCo+A0mdiGLTiHnUSYrCSJ9+bM23QVv04/JX8h2j+vPRG4FLm3aOyyC5iy4hJiiTyxlsjL1faODc5cf8aAC3B1NJD2h89yiVO3qRB4zAgosvOYAVXZKQQUAg+PAJtvNP6iLIwmC2kzLJIEsMZkOhGOeZuuwcFOR2TDDmtIS+NJWpfC+R0Rn2gi05S71JI4O+hlGiYdTCJYE3QjLJGIUSKZv8w4fz2OcrfA0U6PZJMZF4LiiYykECFKQlB4EoUBTC5YM8QXkbEpOENkJjLGiBuhiewFvSaQlGxGcopZXqdQPkxcuM7Sg77iEkzYfzoS16ls1laRlyQ3bJ4zUjomSLHxKbDRC9JM3SmKLZQghTCgA/QUR9MJeV98rZxCQCHwYAjcOcIeLL2KrRBQCCgEHhsC/ISSlUC4Emlhs5aVdLA/v3+H9+kw+Zm55hLyedjh1KUYzNlwFQlJJkiNj41ObvgVVCtOw+ldHfUw6DUiCxYyYenkZl82E+mIWDkT6dHoqGkCjvapWqW4xBSQF+WQ4Z8yJOolPegUgv7kBX1xPvKSChN0zf9MtugSlC0SiBixn8EgYE9kjct2I9OaLdWV7zmRNEwcntFxnq6k0WE/Jj2s6bmjThyonEJAIfCfCCiy858QqQgKAYXA00KAzUqsIWGS4OZsSDNpWcDkoKS/M5q+6YfImGRMJ7NWDGlzmFA4ktmJXyio0zSpbZGkgCqsEcu4GpKIGNKe+Pk4oPm7BfHuy3nJ3FUUxQs44eLNeJk/PzlVq5I3mtX2Qykqgx9fP3M1Dv9JLATkO4C4riX8nNDw9fwoW8iV0lEAlW/9F0JIbRK/O4efLHuvWl688YK33DPE+4x4P1JYZDKls6ZIPZJFD25pj5zz/iXGIDVEfSsEFAIPioAiOw+KmIqf8xBQNc4xCLAGIzgiSZqH8nnag01SZCECb+Bt+2FhuJCGZvnOIJy8FCvjsIaHHwVv/IYvbEhrcuxitCQ3IL6hI7Jz+nKMNCWlUCb8VNa39QuBHzUXQmD6mssIikhECX8ntPmgMJq9WUDux9lyKBRHz0eBNSu3A8fEhv2EEBQOXCLCFEHki+vHm6dfKukm80Dah6oBigrelMyboFNSLKhRwRP8duTXynkiIjoZa/YG4ybVIy1J+sGg18kNzWzyYtOXTlPiOh0cdaIQeEAE7jl6eNXEjzvySkk5i1R9P484sBqd74v7DgtzPk8xPb/3y/enXNbty+1u1SDw0WTCU+33rP1gYsDaHX4KqmAeB1m+h7MNksnUs3jLdazafROJySYwceCNxYu2XAM/fj56yQW5+Zc1M7LuZgtCopIwacVFjKGwVf8GYfPBEIxbdgG7T4Zj+9Ew9Jt5BjPXXcGG/SH4Z1cQRiwMxKR/LoI3JZ+/EYc5669g+c4bCCdCw2Nj7+lIzF5/FZuJEOnJLLb3VITc3PzPrpvYcCAEe05F4viFaCykes7bdBXBUclkOoM0sU34+4Lc5Lxk2w1spHrMJtPbwDlnsWzHTfB9bzsSBjbH7TgaCr6HgHz2yOdpB37f0HEicSDm9HT7bWrbs01Q4qlkguyLT7MNeDwST2fRDAv156dZdo4vize9ceeV6AH3JDtsDy9XxJVUsy65weXaeyxXyAVsItBRb+B9BGXpmt8LwkflclffL1fERb4Az0ATeX6aaMs95fFfhvqena1OTv6syOAX9VUs5gpBfXPG2svYdyZSvuOG+yc/eeVop8duIhj8hBZrYwr42IPDMvZbLzdbnLwSQyQpiFwwzlyLky/q4zgs0HcdD8f6/cGS8Fy8GYf83vYoT/fNJqadFHaStENMutiPSdaWw6EIJY3MC1SvQvkccTkoQT7SzmTKSDOTrY0Gfkrr0Nko+KfVh+tUlExnrMHZdDAU60ibw2SLiUyxAo7y96/4fDORqNBooxyPDV7NB1uDRtofIzxcbVC+8NPti1xnPx8H0php1CccULawmgu4zzxNx+OPn9bTkZayQFq/fJrl59SyylFfZY0vy7E0rnNvstPg9XwY3rYcBrUuq9xzjMHgNmXR68sScv/CC8VcMKBVGdXez3F732s8849vsqnH3cmABtXzY+h3T3fsD6G+yD+/kMfdVsqoWpW8MKgV1YHcHy1T+yX3V+s9DKH6sYwaRnJqZPvy8sdDrWHWI+c5ol15DKU41vh8nxw+9LtykGF0HN6uHIZTPGvYEPLjPEewH9WL41vL4TL5musyjNINpXpw/kMpDbsR7cthBNcnLR3HZTe8bXkqo5ysC+fN+VnL4zzZj4/sz0SPQeDfCOv5eUlw+qfpGLemZNrjfUb8MsahdI9Ps3xVVllwG3xR109uav+kVgFwv3h6uJR96n3ucd0b49apcVG4khzjMcSO1kt8yNrpdUKuLHh1oZz2XGNhQyt57gUarSBUWz/fbf1f7WugcS8E8CzHP69kZX+kivxXfZ/XcI3unTF4lu3AZXM1DDrtuZZ/2bkPyfFIHUFP4zI71zO71Y21OoJws/5r1hN1VAgoBBQCCgGFwIMioOIrBHICAvckO7wpjTdIKWdBbsDA2mF5I6ZyQG7GgPuChb5yMwbq3lPHAHWDXD0WskM/UG2Q2hcftC0YN6u7J9nhJwv4raX8tIJyV+RTG88jDjPWXsGiLdfBj7gmJJoQFBqPm8rlWgzCoxPlUycxscmEQRy5x9EfVB45cUxFxSTBZDIjgvpETqx/zq9zHCKpDfjJ6GgejyFqPN5vm4ZFJsr3c90X2dl/JlJO8HPWX4Vyzy8Gs9dfweJt15GcYkFicgqCwuIRFBqnXC7FICIqSU5wMXHJ1AdUX8i9YyEe0THJUqvNfeImTbS5F4tnJQ/jwYTTYgaimOzQIlS1wf21RXhkAi3aCLg0tnNPzQ4/os6mLGaVWTkT6ZSSjCawSzGbYY1jonP2S6YwU9q7Afg9EuzHaW7Fs8i07G9Nn5xiQlIGl5xipgpbMuRNaTKFm2gwmtPDrXmr4y3M/gsLakappk7rE/d9EEJAp9PBYDBA01Jfs4/bPjoKZ3ebN4QQ0Ov1lNZG5mENv9tR0zSKa5COz6E+TxABNmCx2thC/SL1/AkWprLOpghYSDCo1n+2jUNNQGMwrQ58wZNy2qU63B0Bhur2vntvssN5Cf6603FmtnoNr5b1RPUK3vBytU1vBncnG7xWzguvl/eSP9rH76t4vTzFo2vesc1pOUeDXsj0NSi9h7MN9DShvVTKA9UpHqdlV6Goq3yLKsfnyrs5GVCttKfMm8OrlvaAr5c9rE8ucDzlng4CiUmJOH3yGHbt3IIrl87DTCRXiNQOI4SQ12dOncDFi4HyPGOtYqKjsX/vLmzdvAaBZ08jJcWYMTjTOQvd4KAb2Ll9E3Zs24jr166QAODekCmaulAIKAQUAgoBhUCWCPw32ckyGcDaAiYxPzYpho6NiqBcIRcZk6egEn7OaN+wMLp+WgK+3vYo4e+M7ykOX3u52Mi0PIHxuzw6fVwUnT8pCn6xVqH8DujxWQl0+7R4uvv1y5Lo81UpVC3lThOiGbUqe+OXz4ujO+XN7pfPS4Dfv/HV2/5wstfTJCirob6eIAKJiQlYs3IJvv3qQ3Tu8DV+6/kD2rZqgt97dUZERBiZQEw4e/oEBvbtjjYtG2PerMlIImJkrdK+PTvx0w8t8Hvvzhjc/xd0aPsZJo0bRu1LhIdIkjUeH00pKfhn2Xz80O5LDP7jF/T79Sd0bPs5Vq9YDFIPQX0UAg+DgMlkgtHIbzdmiXVnDiZTiuyP1oXZnTEy+1jjI33JlzlcXd0/AkII0hRrEv/k5CSS6RYa6qmLKGTxEUJAkD/H5Tal00z/QggpkxITE6nNScbI2JmiQAghyzEajfKYORQUrkn/5KQksLOodkZO+2iPUmFNE/JFdDqdAGtpuMMJC8gsQY7C+E2iOjrq2VEcOxuNOrFIL5LT2xp0ZM4Q0t/eRgdHOx11LIGDZ6Kw40g42OJWvogLPng9P4XppZbHwU6PmHgjthwKxdmrccjraYsPqucHa4RSTJwC6vOEEGCSytqVkUN/h62tHVp91xlduv+Bho0/x40bV3Dj2lWcPHEYA//ojvOBp6WAiI2JlkeuEmt/oqMjUK58JfzUtS9+6t4PhQoXw9LFs3Eh8Cx0msbR0p3JbEJcfCxqv1UP3XoOQLsO3UEdBIsXzkAc5avdFh/qoxC4BwJCCERFRmDxghkY/+dgnD93mrqTSE8hhMDNG9cwe8ZETB43HKEhNzOFp0dMOxFCIDjoOubMnIgpE0eS1vEqybLMfTgtqjrcBwJCCLkw2rZlHSaOHYrRw/vh78VzER4emiWuQgi5wFr5zyKMGdkf40YPwqb1XW6KfwAAEABJREFUq2QeQjDJScGxI/sxffIoDBvUm9p8EHZt30hEKkXWRggBNrOHh4Vi/pypWDhvOqKjIpHxI4TAxQtnMYf6xKgRfTFy2O+02Fpyz36RMf1TOVeF/CcCjzQqedXDDJcd781hosGOz7lkDscdDJjYEAdm4VLjA3GJKVi6/QYGzDmLtXuDZUzWEGXU3PAP401YfgEjFwXi4o14+cKrMoWcZVz19WQQEEIgJiYKK5cvhLOLK3r0HoJ36jXCq6/XQtPPWuLXfqNQqEgxIq8GfNCwGXr+Ngz58/uBCY61RkxOXqteG9+0/gEvVauOqi9Xx0svv47k5GSEhQbfIdAMBhvK61M0/fxbvPDiy3i9Rm2UKl0e4WFhSIiPt2arjgqB+0KA++LmTasxcdxQzPprHBHzI5TuFtnhfsiaxMnjh+OvaWNw7eqle05qKaQJ+OfvBZTfMEyf8icu0KTIfZwyVf8PgQBrVpYtmYu+fX7Elk1rcerkUYz9cyARlT5Sjghxq604++joKIn94AE9idQcwL49O9C/789YNG8GeC/hxQuBMu3qlUtx8+ZVrF65GP1//xl792yXciqFNMe7d23Dz51bYhSRmFUrFiEyMjy9zYUQOHxoL7p3aY3pU6l9A88gkAjyutV/Z1kfrpNy2ROBRyI71luyI41MuUKucp/Oa+U9Ubqgs/w9FWv4wx0tMJA2yPq65/hEk3w0mvqezI6JkdFkQVSsEQnJJulnNlvA5jV5ob4eOwJCaAi+eQPnz5/Gy6/8DwUDCsNsNpPWxgwW8D558sHe3gGly1TA+x80gZeXT5Z1sLGxkaspFjShoSHYv3cnnJycUaRYyfQVlzWhEAK2trYQQkhV9MWL53D61FEEFC4KNw8PKttijaqOCoH/RCA46AZWLFsAFxcXSbBTyFxlTSSEwHmazNauXgZPL2+pHTCTTLGG334UQiCQtJebNqyCu7sHksi8yz/WeHu8bHSdvatCeLJW7Z+l81CiRBnMWbQOE6YsxLu0oFq/ZhmOHt4PkUGTK4TAqRNHsGHNcjT5tAVmzl+LkeNmycXQ4gXTERJ8E66ubhT2DabM+BvjpyxCjz5DkESmqF3bN0kydOP6VYwjMsXEqNKL1cDklbXXVqBYyzNr+nhaXIVgxJ8zMXHaUkyavgT9Bo2TMiljXGsadcyeCGiPo1q2Bg3vvJwHPT4vQa4kPnrDV+6fedi8XRwMaFW/MMZ2qohalbwRm5CCzWSyiiBiY82TNyrz5mj+vZCivk5INppx6kosNKFZo6jjY0ZAkDkyklY9sTExKOBXkIhOZqLBA5+dmQgQExkLa/UyL8RAEoKETSKpjKehK62m2rRohD3/bkODD5vCxyfvHeRFCEEanxCMHTUAnb7/Ch3afEaCJxT16n8MGxvbO+JDfRQCd0GACfkK0komJSfhw48+zxRLCAEzmcAXzZ8OJu2169bPFJ7VBff1JQtmwt3NE++81ygtSuYxkeapDveBgEZtcJ7IY2hIEFhjbGtrD01nwGvVa8HJ2RUbN6yEXqdPz4nxP37sEOzs7fFmnXrgPTtubh545dWapMW5jhPHjyC/rz/eeqcBXN3cYSTtsZOTC2zt7KRWh+WTq5sb2nbohoHDJqNo0ZLpeVtPLl++gLNnTuDTL9ugbPkXEBsbTeUkw8HBwRpFHXMIAo+FGRhTzDh3LQ67T4RLF0jnbM6yYmCd76gvk5f1ik7v8s/x3Bz14F9d5t8DuRaSiB1HwyDz5EBKVzCvA9p9WBgNa/iCtTlbDodh+5EwGgz/nT8lV/8PgQAjazKZaFIwkRDSga8fOBtSyQmhwdPTG/4BRVC+YhXkzeeLnTs24djRQ6TxuSXMOG+KDr1BjzykNSpcuBgqVnoJdiQE15EaOTwsBCLDSo/jK/cYEHgOs9Dr9Th35iRW/rOQJsb3yNxaPNNd8r6N7dvWY8/u7Xjv/Y/AxDtThNsuOD8m6f/u2oJ33m8EJki3RVGXD4qA4P1PN2CwsYFvgYIk71NkDm7unnJhE3TjGi1uzNLP+sWaoDx5fUlT50phFgiSLT558pLWxgaREWEyWkhwEA4d2ENmsTWYNX2cDHv5lRpSi+NMJOqFyi9LszzLNpkgw1cIaYfCw0IRThroMSMH4M8Rf2De7Cm4evkimDxniKpOszkCj4XsJCabsWr3TQydf066JdtuICbBlH7rKaQKpsW+vOZ9N3xCXnKzsU4HMk9YYA3nsJj4FIxffhGz1l/hS+T3skPqfpxb02skaXm2ErmZte4KBsw+g/F/X0BUnBE0XmQa9fX4EeCVFO/VsXd0xPWrlyG0W+3xIKXZkDCrWftdtG77E7p064cW33Yk4XEBSxbNhIkfQRcZ87XA1dUdHzb+HG3a/YzuvQZJtfa2LWvx766t0GmPpQs/SPVV3ByIAD9ByBtLeXKr+84HsNHbpN8FT1rBNKmNHPIbmU/Kovobb+FeJJrjh4YGY/igPiharBSq/68ONJ0uPT918nAI8KiPjYmmxAJ2dvYg9kLnFlrsGMDkMjExkQhKKgGiAAq2yD2EdrZ2FG6Q15QINnSt6XSIj4vjaNhLBPbXnj+gd4/vsXnjahQuUhwBhYrRnJNKnCw0+Vh4QpKxM3/FkCYnITFekuRDB/fg1MljmDppJH7r3QlRUZHgvpA5hbrKrgg8lpmCJ8EkMiPFJZoQRyQnMdkEa+fhlXl4TDLYj0Go86IPHGx1sLPR8L+K3nTUgckNOw5nR30PIZFJWLj5GlhL5OygxytlPWQ6cIYU6cKNOIxYGIjJKy5iG5GeKCI65K3+nyACbJ7y9s6DvHl8seffrdK8xEKIBzw7fiTTZEohwilICAjwH+gbQkAjJ4QAf7gJOZ2BVtusgi5ctASpqV0QER5GqzkTOBaXxXGtjuPrKD6TrSLFS0JvsKGVW4Q1WB0VAndFQNN0WL92BbZuXodGjT+DN5lLjSYjG1lJS2mGic4XzftLbi5u8unXZKJwBL/ygDPk/mxhgcQXaY775rLFs3Hm7Al89MlXUqtwK74pfRJNi64OD4AAj2uLxSxNRanJSBpYiMKQ0xsM0OlvkUohBGlpDDDSAslkIrlB15zGwgKGWteWzFV8XaXqa/jl16Ho03cU3qvfGDu3b8TY0QORMQ3Hy8pZKF9HB0d06NwLk/9ahglTF6HRx19KTdGef7dDl8GsllV65Zd9ENAepSrUDWliSv3OKh/uexx6MywJgdfjSAhYUPflPPK9OP2+KYMPqueTb0c+dTkW10ITQZlBfigRT468V2fdvmDwRuTyRVxRwt8JVgLO4TYGDQa9Bp1GCaA+TxoBFiKeXj54690PcPXqJfTs1g5rVi3FLjJB8WObbVs1xeFD+8iuHYNjRw7S+V658mJz0yHyv3D+LIxGI1b8PR8c/9jR1Dh/L5mLiIhwvPjSK7ClVdmObRsx6I8euHzpPKWPJtXzeKxcvgj8AkM2HaxcvpDIlIYKFStbue+TvnWVfw5FQAiBuLgYOcHpdBpWUD/6scPXmDBmCCwkTBYt+ItMEwOwfet6SXKmTR6Nzh2aY9H8GWBSM3HcMPCTPGZz6mSqaTrZv7dsXEOyx4B5syahY9svsGDuNBmf07OpzESkP4dC9syqzfLF1dUNTBwjIsOg6XSg5gNre5KTE8GmRcZfCEH+QtbT1c2DNCzhSEiIT/eLCA9FSooJbh6eMo6Xtw8qv1gNb9R6G+06dMdL1Wpgy8ZVcgOzlqYZFoLyo39OkHbgUzg4OgFCA8s9blOOX7x4adiS5olfoaGpuQc55fPQZIc7BJun2JwUl5hCmps0lSAx6qQ0LQ8/KZVisiCCNDsLSEvDZqc4MlEVzu+IYr5OiI03YcP+EMzfdJVMUMnypyOiKTyWnNFkBnek3ScjcJ6IEpP14n5OpDlKAZMgLpMHR04B+nmpp44EUJ267+OrFu1Js0Oq/MG/on/fbpg7ezL8AwrD37+QJCUjhvTB0EG95TsreNPhYCIvc2dNBmtoYmNj5Pssfv2lI37r2Qm8X+fd9xrhHXL8JmV+p8XuXVsQTpoeLu/G9SuYNH4Yenf/HgP6dsX161el6at4iTI0wZieF2jVfTwBBFhGcJ/7X826aP7N9yhfoTKKFC0JX19/mhwB1lTyU4X89CC/3qBkqXIoWrQUeN8HVydf/gLw8PIiqQZcuhgI7pvcJ9//4BN8+XU7FCtRGsWKc/x8FF0gX74C8PT0gaA/8lD/D4AAt1UB/wBoOh0O7vuXyKhZEp+jR/YhnkxSr7xWkzQ+Sbhw/hxYJghNQyEyR/G+nTOnjkPTdJKIHj60V25ILkomxgiSITdvXkdyUiJMpKVhLRBlDFtaVOnStDLWtuLywe0myIccyPHeQltbWxw5uBf8SU5OxsWL5wCakPLmzU/yx8LeyuUABB6a7GjEaMOjk9Ft4nH0nHISB86mvohJCIHjF2PQZ9op/DjmKC4HJ1AnFDh5KUaanTqNOYaek0+i+6Tj6Ezhfy45j7PX4qBRugs34vHj2GPoPe2k3PCs0wSuk8an71+n0OnPo9h8KASs6en05zHwnp5EMpflAIyfqyqyQHCj1VSTZi0wYswMDB4xBb1/G45ho6ajc5df4eWdByVLl0P33oMxYMgETJq+FGMnLcDg4ZOJILWjvqChQcOmGDxiKjp1/R0/deuL4aOno037n+Hm7kHyReCdeh9h+J8zUbp0eTiQCrlV258wcNgktO/0C37pMxRDR05Do8afg9XaXJ/nCmB1M48dAQOZPHlV/+13P6Jlm85o1e4n1GvQWPa1Gm+8JU0bH37UDC1bd5Lh37b9EdXfqCP7ar36H+Plav+TpJ3f/TJkQE/SNkahQaNm8l1RnF9r6rs1iEyxTGSt58uv1ICm0z32+3jeM+SxzOSlTNkX5GJo+OA+GPfnIMz+ayLKV3wRL1V7Xb73aNigXtIMpSNyw+Q1b15fDB/yK6ZMGA5+2enmDavw9jsfwt8vADu2bUCXji0wclhfzJ05Cdx+/Ab3mm++Cy8vb0RFRuDvpXMxYewQHDywG6GhQZg/Zxr+mjoWrGEqGFAEpUgO8Usjx4waIMtdNP8vqk8VVHrxFdIgGR+4WVSCZ4PAQ5Mdrq6J1MBMZpik8Htw2I8dk5BLQfG4SESHn9QiHsPeUiNzOTgehwKjcOxCNK6EJCA+yQQhQwGOe/FmvCRI/Cg5e/OTVjfCk3DuehyiYlPk/p7AG3EIjkhics1RlHvKCLBQ0pP93NsnH3glXLHSS/AjjY7cVEh1YYLC1wGFioKFBbuAwsWQh1ZCnJbj8aPrVV9+HWxP9/MvDDt7e2rP1FWSm5s7/AsWgg2tqCg7uZ+nSNESePX1muCyOB8un/PicOUUAv+FgBACmqalOjq3d3CCm6u77FvsL0RaGMehc97IzM7BwQEgAWXQG8AaInu6NuhtyEuA07ETdOXs7AIPTy84SrOHgPo8HALuHp5oTc6d+9gAABAASURBVGSUTU0LyZTI5sFyZK7u3mswbIi06phEklbFycmFCrCA9/t16NxbatOYsGzbvFa+VuDLFu1oPjGiZJny8CNZwnushg/9lQjNv/ioyVdEajsB1A/4JamrVy3BzOnjEHTzumzTVSsWYv7sKTCSFseTzPZMkosUK0UEaAx4b1fFF6qi6y9/wD6DzIL6ZHsEHons8N3xsKY+w6eZHPtxWCbPtAtS2FA/u1sokFVIRr+M51CfZ4oAEw52D1MJs9lMamBzOsm5Vx5cBquhOc294qkwhcB/IcB9qGy5F/DP+v3gFT5fZ0xjsZhRq3Y9rNxwAKVosuQVPm+MHzbqL/QdMAY8IVtowrWmYdMr5/P36j1ybwjHt4Y9/DF3pmRceZHUf/A4LF+zF0tX7sJvf4xGft8CUlbkIS2O1AqTFjklJUWCVJU0PhOnLwbjv/DvbaQl7kIaYQcpVwoWLIw+fUdi6ap/sXj5diz5Zwfad+xOWmRPGZ4vvx9GjZ2N9VuPYdWGg1ixbj/WbTmGJSt3pi/AWLPz5/i5WLbyXyxbtQu//jFSPhp/e7+RlXmOv4QQECLV3c9tCpEaVwhxP9GfeJxHJjtPvIaqAIWAQkAh8JgREELQytwRUlOQRd46nSbDhUgVkTwJs6ZRl7bP4/YkGmmE7O0dIET2EOy31y8nXVtJhKurK1xc3WTVrX5CCPkeHsZbBtAXh/E1v/XawdFRkhhuLwqS53zkjc958/nKNuUwCxFa9mfHaXWkMbrdcRg7mb9Og5e3zx314fDc4IQQiImOxM7tm3D0yAGY/mMDvhBCmhy3bVmP84Fn09vhWWKVOpKfZQ1U2QoBhcBDI6ASPgoCqWbTu+fwX+GZU1oyaHsyh6irh0GA8WR3v2k5Lrus4rO/1WUVfj9+j5r+fsrIrnGYCM6cPh49u7bFuNEDEX+P3yUUQsi35Pf/7Wfwu40WL/gLJrPpmd+aIjvPvAlUBRQCCgGFgEJAIZA9EWBt5sEDezB/7jTExsUgmjQ8FnPq09dZ1ViQNnTpotnY/e828GsD4uJiIR9nzCryU/RTZOcpgv3sinrwkomcQznkOgwgrTDyS54KIUD/yonc1xdkuyP1I89zKwbZ4L5TW+HpfwshwD+7MXn8MBQo4I/ab9W/ZyU0MueeOXUU/PQa/+xKufL8LrQH05Des4BHCFRk5xHAe56SapqAoBuys9XBx8OenINyHrkTA3cXW+g0DU5OtvDxzJ0Y+OTSts9039T2Ls420Os0uDmrvpAJm6fVP6gNXAl7UpaQdH76/yaTCevWLMeZU8fxbZvOyJs3/z0rwVqcJaTVsbOzBz8RZ2dvf8/4TzNQy1iYOs+9COhE6r3b2eqRx8tBuVyKQV66bw9XW+ioQ7g42oCvVX/IneOB254nWu4L7q52qi/Q2HjaY4HbgImmRhqWVAn99L6FELh27TJWLF+A6m+8hVervwnzPfbeCCFw9PB+7NqxGU0+/QYF/ALuGf/p3UlqSYrspOKQ679TTBZpVk1ONiE8KlG5XIxBdFwyCSkL4hKMCMvFOKhxkIjY+GTw+9Ri4pJyo0zIFvccQ+ORN0c/7UmKn0Jbu2qp3HfzVYv28j1TkPp/QCPNrxACGT/8kx2LF8xAkaIlUOedBrCYzRAiNU5W8TOmfRrniuw8DZRzQBnpVlU6sZgtcrIzq2OuxIGfyqVuABawZiLBqh/k3vEgHzCjzkDzVq4cC9mh7xP8ciH6tKeR2NhorFmxRL5vaCVpdyZPGIEjh/fJ3xSbMX0crl6+CJFGevR6g/yZoH93boaJTF/zZk7CtCl/4uqVS9IENm/WZMTHx4HYD57VR5GdZ4W8KlchoBB4PhBQd6EQeA4REEJD0RKl4erqjkMH9+DAvl3g3yGLjY3BoQO7ERERBjMRG77mI7+HqnzFKkR2UnBg/784tH+3/JmV0JAgSZKSk5KQqud5NmApsvNscH8uShVCgN+/oNfrwWpKZPERQkj15+3hQqT6GwwGmUcWSbP0EiI13e35ZRlZeSoEFAIKAYXAQyHg6OiE7r0Goe/AMfh9wJ/yyL8l5+9fCD1/G4ZSZSrIx8v79fkJTIZKlymPfgPHyrgcv88fI8E/lFul6qv4uUd/+UJG1hY/VGUeQyJFdh4DiLkxCyEEMXgTzp8PxMEDe4nxX4cQQjorHkIIxMXG4vSpkwghdp/RPyEhAUeOHMa/u3bg8uVLpCI3W4PvehRCIDIyEqdOnUBEeHimsu6aKPsEqJooBBQCCoEcg4AQQv7Wm7OzK6zOzt4BNrZ2cHZyoUWsDmzK2rd3B4KCrkNvsIGTswuscTmOra0t7Owc4Ojk/MzltSI7UJ8HRSCJ1JFrVv2Dph9/gM+aNsK333yJjxvXR49uPxIZiZCdWggB/u2aP/r1QaOG72H0yGHphGbP7n/RquWXaNOqOTq0b4VPmzTE2D9H4l6/KSQEE6c4/NipHT5u9D7+mj7lgTRCD3qPKv7zhwBrA3n/g9FolH2Tr4UQmW5UCAHec8Auq3BrZF6hms1m2advP1rjqONDIkBNwthzG7AMoUspU+6WmxBChnNcU4pJnmeMK4SQmuf0/OhaCIGsPta2TA+zWLJsY46XHifXnFjQ4MOm6NK9H5EXJxA0qFX7XQwdOR3VXnkDKTSuMkKhI41/u46/4NOvWmcLWa3ITsbWyQ7nOaAOWzdvRK+eXREbF4uW336Hbj364L16DXD40EFcuHBBChY2b61etQKLFs4D23RDQ0Pl4LBYzLhx4xoKFiyEbt17oUfPX5E3bz5MmTIe5wLP3nNQzJo5DVs2b0B4RDhCw0LuEGo5ADpVxWeEgBACgYHnMPOvqRg0sC9GDh+MdWtWITExUfYjIYQkQOvXriZiPlS6FcuXgV+LL0TmiVEIgeNHj0qCPnH8GFjdpIljZf6B584+o7vM+cUKIWBMSsaO7VsxbuxoDBs6AEuXLkZkRISUK7ffoRACUZGRWLVyOUYMG4zRo4Zi86YNMCYny6hCCMTHxWEdt+uoYbLdWS7xZlkhbrUrk6vgoCBMnjQeCxfMRUxMjOwXJ08cx+SJ49LbmNt60oSxmDZ1Iq5euUx10slycsMXkxs//wCUKVuR5LRe3rKHpxfKV6wMZxcXku+8lJDe8ksIgRIly6Jw4WISS+n5DL8U2XmG4Oe0ooUQiI6KwoIFc2CwscWQoaPx2RfNUe/9D/B9hx8xesxEFCtWXN7W1StX0K9vb1SoWAmVKlWRfvwlhIbadd5GVyI6b9V9F+xq1qqDRDJr3bh+DSx0OF5Gx8Tp2JEjGEWC7K233kWJ4iVxS0xljKnOFQJ3IiAETYg0WX77zRcYMXwQdu3YhpkzpqJjhzZYvHiBFNK8Uh81Ygg6keZw6dJFYNeZzsfThMuazNtzPXHiKCZO+BNTJo+XbuqUCXKiHTpkAA4fPnh7dHV9nwiwdmbxovmybebMmoZNG9ahd6+uYA2xhWZbITKPfCYlo0cPw0+dO2DN6n/w97LF6NSxLebNnQWDwSDJ7NQpE6VGePHi+VhNGukuP35P5GUs+BEnIVLzE0JgzJgR6E+a6GkUP4wWZ0IInDp9UhIbaztPpvYeOWKwjHfy5HHo9br7vLPnIxqPE9aQWe+G24Sv+Wj1y3g0m01SM5bR70HPH1d8RXYeF5K5IB9+zPD6jevg1U7Nmm+idJmycqLgjs6blAMKFYaTkxOSaVX111+TERwcRCSoMzyJ/WeEx97enuy4dtKLydOBA3thT7bgYsVKSBOCDEj7EoLMV7Qymzx5HPQ6Pdq27wg7+9S0aVHUQSHwnwhYiB7XqlUbCxevwNoNOzBl2myEhARjCWkeub+eOH4MA/r/hter/w+r1mwitxnlylfE/PmzcJomvIwknPt740+aYf+hU9j57yHpdu89iho1asLR0YFWskUgROok+p8VUxHSERBC4Pq1q5g5cxoKkgZh4+bd+HvFOrmYmjtnJg6T5jhjOwghcPToYSwiTUyTpp9i87a9mDN/GYoULQbWsoWFhYG1bPPmzkT1/9XCVgpfsmw1mVxew7hxo3Dt2hW5uGLZtXPnNtLqjIOzs7MkSNzGXLEPPvwI23bsl228a/dhrN+wHTUoLzc3d5QrV+EOecVplMueCCiykz3bJVvWit/iGR4ehujoKDCxYZafsaKp1xYcOrgfK1f8jbZtO6J8hRekeSA9HgkoXinPnjkd7du2xCcff4CNtHpr2uxz+Bbwu2MVwEJn29ZN2Lv3XzKX9Ube/N53xEnPW50oBLJAgPuQm5sb9Z8+KFq0uOyPBfz8iWDby8mOacm6daslQWna5HMi7M5wIbX8F1+2kJrMUydPZNnneJLUG/SwsbXB8eNHSbOwEpWrVEXxEqWyqIXy+i8EhBA4c+YUWMP7cZNPyTTiDFtbO9R96x3ZHitWLCPzyS1NCrfroQP7Sctsgw8bfUztaoRPnjyoXfstXCUic/ToIbAGjuXV5583l23N5hbWLJtSjNiz51/pd/PGDWkCe/HFqmjUqElqGaRFstZXR9obbmd2586dIdJ1QBIw/4IBiuxYQcoBR0V2ckAjZZ8qkj3dmAwjCQqDwYa0OnfWLDY2DvPnzUYen7z48qsWpCq2yEgCggQLf0N+bMgMxoInIKAQvL29sXv3Lpyg1TWbrGQE+hJCIDQ0BLyqK1euohQwpBXlEIDC6B/qoxC4LwQE5P6bo0cOgsnz8CEDJYF56+33iKzYSg2Ag4MjEe4C1K8tSDGZUIJICxOasLAQGff2cniyZT8m74tJQ5SYmID36zeEE2kHrGEcrtz9ISCEIG3LVUleChUqAjZpcUpvHx/Y2tnhyuVLJE/Y55a7cuUSfH0LwN3dQ7abTtPktUFvINkRitCQUDg5OSNfvnzpxMSvgD9phx1w6eIFKsOE5cuX4iyRrJ+69IBP3ryUT+YnQ7kt2fFibsP6tVJz/X6DhpQ25VZF1Fm2R0CRnWzfRNmnghaLGa4urnCkSeHqVd6cJzJVjokKE5ZNG9fT6kiPubP/woRxo8GroVOnjmPyxLEIIdMWm7E+aPgRevXui8FDR6H9951xiuzfM/6aIgWSEKn56klg7d+3F1u3bJLlTCV7+eSJE+TK7yCt6KZMmoDEhEQZpr4UAvdCgPvm5UsX0bbNN2jbpgW4r5UpUw6vv15D9jneRM8mDL3BJjUbWtkzaQEEEuIT7pgAkfYRQuDC+UBs2LAWL7xQWeZnMWeeLNOiqsN/IiAQEx0NIQQcyBxooTZgxwsrvcEgySo/SWfNhsOioiJJQ+cAGxsb3oJD7QTYkpmc2zsmKgoxMdGUlyPJI501GewdHKDTdFJrd+FCoDSDvff+B3jt9deoL2RNYNh8xmb5Ff8sw0tVq4FN7kx+0jNVJ9keAUV2sn0TZZ8K8uDOmycfrZLyY/u2LYiMjIBen/pCQRYGXNPExHjYklqf370zdNhAjBkzEmdOn8IxUvMgQZQvAAAQAElEQVT/OXoYeM+PTqeTmwdtWLvj7IIKFSvCjWzgN65fBwszIQQJPJATtHoywo5WdZs3rcMwym88kafr169h397dGDt2FPg9PtayoT4KgbsgwJso85MGoGefvpJkN2rcBIcOHUCfXt1o9R8i+zHv3bGkqg7Tc9E0QWEGuhbk7vznfDdvWi/fFdW2XUc4OjrShGu5M6LyuQ8ELNDp9LCYSbOWbJTxhSDcyQmClAmPjkxKMoC+hEhtG37kmduBYpIvIOgP9GG5wfKJw81EnMgr7Z8yozM7IkVLFs0nTU0Svvj8azB5oi8KsRBxSo1DF/LfQGRr+bIl4H1ederUpXZ2kP7qK+cgoMhOzmmrZ15TFgbeeXzAq6CzZ06jU4e2WL9+DfaS7Xvhgrlo2uRDaDodVq7ZjB27D0Fu6Nu0E2+++Rbee7c+1m/6F8WKlsCihfOxYP4cnDp1EsePHcPSJYsRFhaKKlVfhp29HZkZNqPvb71x9uxp1CUzw9Yd+7B910GZ36q1m+U+oE8/+xJr12+Bh5dnliaGRwNLpX7eEOC5jjU3b9aui8afNMOgISPQ4INGcoPr6dPH4erqBtYqxMbGQggBJtDXr16hlb4J7h4e8loImkbJIe0jhEBw0E1sINNG6dJl8Vr1N1RfTMPmYQ4WSuTm7oYUUwrCI8IIcx35QP4QZVJSIvLkyQNeKAlxqx3c3d3B2h1+SamMTF8sS3jR5OnlBWdaTEWRhoef9hRCUCjAT1olJyeRxscJW7duQiRphwYM+B1tWrWQT+dduXIFfXp3x5ZNG6g8PdVDw40b1zF71nRp2nyxSlXKJzUvOlH/OQQBRXZySENll2rqybTETyi0aNkGJ8k01fmH9vi+fWsMGfwHnJ1cUZhs7W5uHvDy8paOn8RycnKCi6srPD09oTfowCYwfidG2zYt0O67Fli2dBHeJlLT+ONmSDGm4MjhQ0SAFoA3KtrZ2VM6L5kX58n5OZMN3o00Qe5kpxdCQH0UAvdCQAghJ0zuT8lJSZLACKGB+5YQAkxsyleoKCfZvXt3S8JiNpmxdu0qMo/YokiRojLO1SuXwXtEzGlmKp54Of5p0lzWb9AQrtTHrWFQnwdGwEK4FixYCEIIWkDtkUfG8/Chg2ASWr16TamF4TeuBxHJ1IQmn7y6Qu3C2mM9aZnj42Nx4MA+2RbFipdE3nz5kWxMlppgPckuYzKd79sj61b1pZfl+8Hqvv2u3DfoQfKJ921xu3Jb2pBpDKTjEULIzee8eboWLdzy5fclBRBTM5mN+sohCCiy8wgNlRuTsnbHxycPWGU/Y+ZCjP5zIn7/fQAmTvoL/QcOBQsCE63MWEixsycT1A+df8Z37X8gsQEyX9mAn4wYP3EaOv/YDT/93AOTpswAmxd8fHykgGvY6GNMnTaXzFsvICXFmDr5kCDk/JycXPBb34GUx9dk8krJjU2g7vkBEdA0HXbt2oEmHzdA/36/Ys6sGXLl/veyRShesjSKlygttY/5aRIbT6bRP0cNx4A/fpPvz3nl1ddRrnwF+fMk/Pbunj26IiQ4GJqmUf8z4p/ly4iMe6Jmrdry+gGrpqJnQIBlS7FixVGubHlMmzoew4b0x7gxozBx4hiUJb833qiFy5cuodcvXTBoQF9oOk2+w8uH5FHf33th2pRJlGYgVv6zDO/Wa4CAgEKkBa6AQoUKY+hQMqmPHo6RI4Zg7pwZqPVmHbxQqTK+at4Sv/Tqi19690XP3r+jNpmomCC1a98JVau9KmVPcHAQ5s2bJRdcTIx0Ol2GWqvTnIKAllMqquqZfRBgoWRHJKZQ4cKo9sqrqEmCowwJI35c9/ZaajodCtPKuBAJHqsOxsnZWb6j5+133gO/VJDTOpO6mfPl9Pz4aNny5eXGQ6sf+7PT0+qtZKnS8PUroFZXDIhy/4mA2WxC2XLlUaxYCUlgOndqi+lTJ6F6jZro228Q8tBkWcC/ICZNnSVfg8/v25k48U/UqvUWevzyK9zc3CE0gRgycRmNSdCI6AghEB4ejj27d+GNmnVQwM9P9Uc8+seb2qLzT91RplwFDB7Uj1xfFPQvhEFDR8mNxRZaMkVHx6RhLUiOlEPX7r3ldbeunTBzxlTUq/cBfvihCy2UUuDvH4BuFO7m6kqLsp4YR2T2lVero3uPX+VTX9yWBpIp7PR6Gzg6OoLlmK2trWxnDj996oR8W3Kjjz6RmiRedD36nT6XOWTrm1JkJ1s3T/avHJMRHvx8fJDacnxOx47Pb0+blZ81zr3CrHHUUSFgRYD7Cz+ePI60ibv3HcXW7fuw/9BJTJw8AyVKlARvXjWbTHjxxZewbPla/LvnCPbsO47RYyciT968ctJ0dXXD3LlLMXHSDHiTBtJE8T083LFpy7/4sUs3ae6ylqeOD48At1XpMuUwY+YC2QY7/j2EydNmoWjRYtL86OdXENNnzEO//kOoXYxSE1znrbflSyB3/nsQO8j92ncA2GxurcXL1V7DUm7X3UfkywGHjRgj25VljzWOPFosaPbpl5g5ayGRV39wOLczP321fuMOdPm5pyxPxlVfOQ4BRXZyXJOpCisEFAIPigBPXEJo8PL0RqHCRcj05AVetfNkZs2Lz1ljmd/XV25KFkLICc8a7uTiLLUL1mvOz83dnYiOjdVLHe8Hgf+IY7GYydxtkISEfzePn4Ti9uNkQgjwHkDWvPA1SNNjIZLC7eZH2jl3dw8IIaSmJzWcYlB+HN+3QAF4eXuDzVCcxhqe8cj7dJxdXGTfsPqzxofz1Rv0mfK1hqtjzkBAkZ2c0U6qlgoBhcBjQMBMEx9PnHeb7Nj/buEcxi5jNW6/zhimzh8eAcaVXVZtwf7sMubO11nFtcbJGM7nVv+sjneGWxTJyQqoHOZ3T7JDhBlm+lLOkitwyGF9V1X3+UZA3Z1CQCGgEHhEBKw7RYF7kh1fbzu8UNQNFYu4KvecY1A2wBk66g0aOYNBg41yuRYDvV6DIBGj0wky0Wi5Fgc1BjRwHyCrEPR66gtKJjz1scCyWE/jUNB4tLPVwcnBhpxBOYf/xsDBTg/uu0j7aGnHLA81K3uja7Pi6NykmHLPMQY/0r21aVAYtgYddHoaUI62cMopTtXzsbeVPQkJTROwszXAWeH72PHNSWPLzlYPjWYMe+oLOanez0tdefzZUxsIIeDhaoeC+Z3hn0+5/8KAccrr5QidpqVzm1tn6V63TvafisSMtVcwe/1V5Z5zDBZvvYHkFDMSElNwIyQO14NjlculGIRFJCLFZEZUTJLqA7m0D1jHf2R0kuwL4VGJuBYUq/rDM+gP4VFJMJstiIpLxo2weNxU7r4wCKM+y7hZGc09yc6xC1FYsv06/t5xI6c7Vf97tOEyCluzN4iEmgXJRhPCIhKUy8UYRMWmCtdYEq6h4fGqL+TSvsBtHxtrhIknWiK+Si48fbkYGp6AmLgkWCxAbGwywtR4xP30Q8YtismOxWzlOrgn2dFpGmzIfq/c84+DgdrZ2iuEEGTrVE6I3IpBak+g21f9gEAQIrf2A5oehLUvCNUXnlE/AAT4I4SAEI/LPf/5QBMMW7qj3px+/sgnRD4lA+Xjo2TGLDbFZJGaBs6H82N1FDu+fhjHeXC+8vgfGXC8/4iigjMgIETmTpUhSA7OjNeZzimdEHdPmykuXQhx/3EpuvpXCCgEFAIKAYWAROCxkB3ro+k6YlIGvZCE6lGISaF8Dvj6nYL4+A1fmiwBZ3s9KhZ1ReH8jkSmmK7ggT6cQkBAo/ppNGEKQNpAWT1Lp+n/THK43nwfGkdKD1EntyMghIDBYEOYpnYhnU4PHbmM8XQ6HYSmQYjMYAohwD/7wL78TgtNp4Om02VMmulcozw4b47LAZwv+/G5cgoBhcCTQ0DlrBB4XhDQHvVGLLCggDeTkwAMb1ceM7q/iIGtyqLOS3mge0jGUNTXCY2J6DSuWYDMaDq8+3IeDGxdFj0+KwE7Gz0RngerdZmCLjJtv2/KoF+L0vi1eSm0rFcIpQo6S9LDuZFZmvLW0ORNP4xsXx4dPioKB1vdA5fFeT3vTgiBhPh4bFi3AkMH9ELXH1th/JhBOHPqOJjcAAI6vR7nA89g2MDe+HvJXBiNybB+4uJisW7NP+jVvT06tvsCY0b+gYvnz1Iw0x863PYfEhKE+XOnokunlvjphxaYPWMCwsJCIETW8W9Lri4VAgoBhYBCIJcj8EhkhzUj5Qq5ovtnxdGkli+KkEbG1qChNJGIb+sFIJ+nHUxkjmKNiRVnPmftCR/Zj4+sGSLOBCYcfJ15CrMgMdmMkMhkBEcmgfkTr/BT87BQGoskJJyOHeeZ0fF8WDi/A6qUdEPl4qwdckD5Iq6STP1GpKdKSXeZvnxhF/T5qpTUKJXwd0JAXkfSPjwSPBmr8dycCyFw4/pVDOjXDT27tsX+fbsQHHQDq1YsRueOXyPw3GnExERhzoyJ+KHdl5gzcwIOUBwr2eG227D2H0wgcsTpUoxGLJg7Hb/36oyY6Mg7CExychLlNQEL5kxBclIiIsPDMHb0IEwaN5T6lum5wTVn30j2r31yUhKCbl6/w3EfjCfizneQYkxBSPBNXLxwDtevXUFSYiKoQ+LuH4GoqAhcuXyB3EXEx8XdO/rdM1IhD4hAfHwcrl27jKtXLiEuNuY/U3N8btOrVy4iNjY6U3yWSbExMbINOU5CQnymcL7gtr127RKuXaXyaLHGflYnROqMxQsw7j8mk5JLVmyy0/GhZ3MmJs4OBnxWxw/FCzghLNqIORuuYsTCQMzdeA3nr8ehpL8zKpVwQx4PW3nPTEbyetqiUnE3+HrZSZLh7mQgEuKG6hW85NHFkTQ3MnbqF5dz7GI0NuwPwYYDIYhPMiGvhx1eKOYGbzdbFCJS8lo5T7xYwh2unJZtVqlJ7/hOTDZh9JLzmLbqEoLCk+DhYoPXy3tJDc5bpIkqRvcRFJHEvAupX3dkkes9kpOTsXzpPOzYugGfftEKw0ZPx4gxM9B/8Hi8934j6MgcdeL4IWzbsg516taHr18AmJgCqQIB9ClWvDQ6//w7Bo+Yij8GjUO9+h/j3NmTOHPmhExPUdL/NU2Haq+8gT59R6L/kAn4rf+feKFSVezbuwtRkeHQyMSVHlmdKASyQEBHffLwob3o2a3dHe63Xj9g57b1kmhPGDuYtI3fo0eXNviFiPyo4f0QFhIMIcRtuab+9tK2LWslSe/VrT16/NwGA//oTtrMs1nEvy25unxgBIQQElcmJseOHsDQgb3wy89t0YvadOjA3jh96thdZIEFJ08cofi98UvX72T7D+7/C04ePyzjm80m7Pl3Gwb264Zffk4N/3PEH0SiLspwLu/I4X0YPOAX/NKlLaVvj2GDeuPsmZMyXAhBJDcWa1ctQ58eHTBm1ABEhIfKuj7wTaoETxSBhyY73AmKF3AEa0mSjWas2RMEJjmbDoUQ6bmCP5dewIfVyIVdtQAAEABJREFU8+OnJsXwwev5YW+j0UrcTOTIH12aFseblX3AGpefmxWjOMXRvmFhOhYjDZEfWDvExMh654XzO+LNF71R+0Ufqdl5pZwHfm5WHN0+LYluZNrq8FER/NikKFo3KAwnByJLdyE8xhQz9p6KwM7j4QiPSZbZG3QCJips59EwDJx9Bmv3BhMJu0sGMkXu/RJCICw0GDt3bESZchXx2Zet4ZMnH5ycXFC8RBl80bwt/PwCwGTm5x790eyLb+Hi7Ep4miVo/CWEQMnS5fDSy6/B1dUdLq5ucHRygqbTYNDb4PaPnsxhlV96hcqrJMtxc/eArZ0d9Do9NO3u+3xuz0dd514EWFbly++HWrXfS3d13m6AvHny49CBPYiJicY10uSsWbUUVV56FZ83/w5eXt5kOp2Clf8svGPi0uk0OVmyNjIiIgyNm3yF6v97C6v+WYQZU8eAzbRCiNwL+D3uXAhBGnMeu5pc2NjY2EBvMNyBccYsWAawZjiGtC+hITcxZcIIHDq4Bx80bIY6b9fH4UN78OfwP5CSknJHPqGhIRR/OA7u30WLscao+86HOH70EEYToWFtz1XSDI0fMxhXSWPzSbPmeO31Wti6eS2mTx4t8wq6eQ2Txw2nNAfw4Uef403qQwf2/YuxI/vDTBqcCNI0jyJSPGLob3IBdpYWbEmkRRRCtX/GNswO5w9NdrjyhfM70aQjJHHYdzoSTCY0auQUMl1dDU7AmSsx8CHtC5uIPFxtScNjl6q9cdAjnrQszd8uiMqkkbEl09cVim9rEChGBMqWiJElg2rF0VZPWhwbeJImBtSH+NrL1QblCjsjP5nKWJixhujNyt6oQOYoaRbDnR87Ww1fv1sQnRoXo3KcZH03HwpFAmmLth8LwyY6j0ugAXNnUuVDCGikRQkNDZKq/gqVXoKdgz1pbcxEZqi1iDCyUOI4np7e8C9YGDpNo1a8kziazWZSGV/A/n07MW/2FCxfMhcVKlZB2bIVpcCiojL9G8nUxUJk7+7tmDhmKHbv3EKTS214eHrJ8jNFVhcKgdsQ4P7mX7AQaSK/TXcfE0GJiYtBnry+qPBCFUnW5y7ehJbfdUb9D5qgddsuYBPr2dMnbutjgvqoCTu3bwKbLVq26YT6HzbDd+1/Rs0336GJd6/UCtxWBXWZhkBiYgKOHT0INv9dJZMSE8wDpKVNIhN1WpT0gxBCypb9e3eiQ5vPMfCPbqQ5O4fDB/eh9Xc/4eOmzfFJsxZ4t95HEveD+/+FjhZB1gxYFp08dkiW902rzmj6WUty36Beg4/BpnVu2317dkgzfLuO3YnMfEZEtw1eee0NrCFNTUhwEE6dOIajpElq074bkdovKH1LvP3uB9hP5Ik1Pmyyj4mNQu++I4gIvWstWh2zIQLaw9aJ+iF83G1kcmOKBQlEXuRF2peRtCjbjoQhKdksCUlR0s6w+crDxYDrYYlgUlEqwBmsFfp75030nHISP449jnkbriEu0QQhiNWk5XW3Q2SsEf1mnkb/2WdxLTRRRsvvZU/an6zTGnQ61KrkQ+Y1J+g0ik5l8L4iexsdXQtJ3MhX/d8FASE0sG2b7dfubp4kiLKOyOSTJxgQvrfHEEIgiQTeonkz0Ld3Z0wYOwRxZH8vV/5FJKckU5LMbSeEkKYEjvd7n85YOH86XN08UJRMYUyCoD4KgftAgPtjMplg2aWkmLBvz05soxX8i6TJkcScZIOdnT0SqC+ytubokYOyL7IZViPSbi2CuiNpqFMQQSZU1vB4efkQ+UkmPxNer1Fbjg/eB8RjwJpGHa0I0FgOC8HwwX3wW8/Ock8fa0T4oYMBfbuBiVAq1kJqx/bt3YHfSUb0JDNhVFQ43iQyefrUUbh7eKJQkeIyviCZVLhoCeio/fiBCD6ml0aNdelSIDjPsuUrgvfimEgbU6x4KTg6Oknz1rlzp+Dl7YNChYohPj6e5g4NxYuXIdlmxpnTxxEYeBrcxoUKF6XyEqHpNBSh8gQELpw/i4BCRdG95yDU+F8dWGgRZy1bHbMfAtpDV4kW7LHxJpncoNfgQNoXeWH9EsDRC9E4czVWmpZeLu2BauQ4+NLNeCQSOdJpNPGRCezExRhEEHE5S3H3nA4nwWGhrsQx7+0uBcWDCdVlOjLx4dh2pBXiY1aOy5yw/AImr7yE41Smju7+ozd8UTifA+6mDcoqn9zqxwLcYCC1s95AgiGW2oga+QHB4DxsaVJ5/4NP0KV7P3T9pT9erPIK5s6ehDUrl0LLMLFw1hyfNThfkomsa4/+6NTlV3h6emHUsN9x7uwpKeQ4nnIKgftBQAiBxIR4/PP3fDKH2uOtt+vD1tYOmk4nJzc2aQz6ozvGjxmIsuUrk+njo0zZcn80GPTIly8/kZwUbN+6QWoGLl86j4sXAmFMMYIn7UyJ1EU6AhazBbyh+OjhfWjQsCl+6zdamhbXrFqKbVvW00IokTBdD95Xw3tgQoJuknn8OwwaPgX/q/kOQkOC4OTsAicnZ3BbcMbOLq7SFMZaFnOGN+ZyeFxsLFxc3GBra89RIYSAK5nP9WQ647xio6PhmnbNEYSmgyuZyvUk45j0RkaGyfSOjqnlkQIbzpSfnvpADKXVSJNkb0/zhzl1LuQ8HrtTGT4WBGi6f7h8LJTsUlAcfQPuzgaUL+IiCYPRZIaZOrSbk4G0NhZsPRxGnRKoVtaDTFZu0u84EY2ouBSZlvgOpNmKehH9w5aIE/VHGfZfX9Z+LYQAFUkmE+Be06+RiNWmg6FYvPU6NtPRSBopBzsd3Mk8xmWnkPnNzCcA5WWRpMt6TV65/t9CgHt4eMLVzY3Uu0cJDwuESEVcCAEDESEdTRoUcM9/nV6PgCLF8OJLr+HNOvXQ7PNvYUfCaPtWEna0+mbCo2m69Dxs7e1Rskx5VKn6mlRBf9CoGdhWfmj/blAFoD4KgftFQAiBs2dPYD+ZRl6qWh3lKrwIM63IBVibEI3z504j8Oxp8EQWRhNrIBFqDs+YvxAaarxRF2XLVcLUSSPxXctP5CsUliyeBSEEtNsIO9QnEwIWuqpd931pEqpYqao0G7q6umHXzs2ScI4c9hsOHdiNtt93x28D/gSP93z5C0iZnJycBI0wFkJQLvxvgZ4IhxBCkk8mU+zLzkKynDV5sj2s0SlAR0RGCA1JSQlg7bDI0F6UDfQynPMzwijlkYAQglKm/utIxglB4aYUmtvM5NiMnxqmvrMvAg9NdrjpWSNzncxHtgYNvBn58zr+pL3xRNM3/dC/ZRm5AXnX8TCERiXDkUgFEwt+murYxWiERCaByYW9rQ61K/vIJ7Q+qVUAX78bACd7He6bZHBF7hNfnV6QCcsZrGV6ubQ75OZkIjjxZDbzcbNFucKuYLMWZ8f14vfw8NNemvYAhXDi59Sx0M+TzxfFS5TF1i1rsWXjahIMeqldMaWkYP3a5bh4MVBes0BgIcPICSHA5+wsNLHw4+MsRIRI9TeR0DCZU+BEKzYDESFeoV26cBYmo5EIZwoiwsJgNpmlwBHUFiygzLSScnVzB+cP9VEI3CcC3Hd2bNsotTGff90GdnZ2crJKIY3Mi1VexahxszFrwToMGjYJUdFRmDR+KK5fuwwhbvU0HgcFA4pg3JSF6Ni5N2rVeQ9NP22BL75qQws3WzKRuFBtbsWni6fxn6PK4LGro7FukQsoL9jY2CI8JBgupGXx9PCWr7fYsG45mYrO0H1p6fg72DuBCYxRvreLMKZ2SSYCxG3i7OwsZQ8lkP9MYuwdHEjTlggLyQvpSV/JyYlg+eHlnZfa3x7JiYngelAQHS2SBJmpXi4u7rAnrU1SUhJSywPVAzASATKTHGPtkk7ToD45A4GHbimNJp3giCTMXHcF/Lg2k5kv6vqj95clwUcP1paYgYiYZBw4EwnWvDAkF2/Egx0/+s3alWTSrrxUyg2/NS+NFu8FoIA3qxupE4Mdp2Bn4a/7ckTm74jHfpwDvySw91cl0ZPq+EJxN8QkpGDLoRDw5mh+W/Og1mXwbrW8EELAP489enxeAvw0Gd8b53FHxrnQw8HBCR989Kl86qr3Lx3ki/5Y5dy2VRP57p1wsslfungef00dg8njR+D69atytTZlwkisXrEYPKlMnjAc37duhqkTR2HiuGFguz0gUPedDyCEkC8hbN/mMxw9dgDRUVFkt++Ebj+2wszp48l81Q8zpo8DP/FV6cWXwUIH6qMQuE8EgoNuyA3urFGoWLEKkWmTTGmhAc59yWhMkX5VXn4dlal/RUVFgp0QmuxrJtOt+Gza+OiTL9G+Yw/wkzr8lI+Hlzd8C/iDurHMV31ljQDvnyFmQTgJIpWRkkB458mDgEJF5CsmuvcahBAiPz27tkPPbm2xbfM6xMXFwssnD8LDQ8mcFSyJDbfb9WtXwIut/L7+so24HflJKQEBZ2dXar8I8GZjTdNRkRZcvXyRCE0iChUuDn66MzQ0mORMJDic25ffm0RqJPj7F4KnpzfCwoLJhUDT6cAk6BqRXy6DtU1mmtiEoJJoPqTi+B9CCLppdnRQ/9kGgYcmO3wHOp3ApoMhGLkoEH/vuIldx8Nx9HwUNhOBYBJ0IzwRTGb4qazEpFQhsf1oGJKSTUg0mjB7wxXpdh4Lx4lLMTKvFf/eROC1WGw9Eopth0PBLy68HJwAJkacP8kknL8RR3FDsZ9IFHepRMrvwOlIbCHT1LnrqaY1rh87jh9Ifhv2B2Pd/hD52PlWyvfvHTcwdukFTF9zBdFxRgRej6ewMGyhsLX7guU7fXYcC8OBs5E0QTNV4tyUA0mBSpVfxk/d+kn1MwuZa1cukYAvSKvcXihZqjyZACLl01Y3b15F1WrVUaxEady4cQU3b1yTK7jXqr8Jv4KFcGD/vzhycC9KlCyLH7v+jpdogmFh4+tbUKZzc/MkYeWCmrXfhY2tLXbt2ISLpPGp8b+30Pnn3+Rj72ZaYalWeQAEcnFUPWkS9u7ZgcuXL0hibTAY5OQnhMChA3uIZM+R/TYyIgz87hXeoMr7xdzdPeXkuHzpPPkoemJCAng/B79Pip9OvHjhHGZMHYvNm1aj2iv/Q568+XIxyvd365s3rMK6NctxlWTH+jV/S8JTperrMrEbmcrrf9gUg4ZPxjetfiB5EoV+v/2ERQtmkOnwBYpjAb/ENDjoOs6dOYFNG1YS5vnxQuVqiIuNpkXVEtlOTIRY9jg6OmHp4tngx8h5E/PG9SvkpuOy5V5A6bIVER0diZXLFxGJCsGJ44exkzR/pctWQEDhIqTFLiOJFL9WICT4Js6cPI7NG1eBZVQFIsvJpFVi8hV087p80MJI2mjuE+zH5VNl1X82QUB71HqkkBloz8kITPznIobMO4uBc88S+TmPVbuDkEgkhOQI3J1tYEOmLtby7DsdIYvUKCA82oj5m65h6PxzGDTnDIYvCMS/J8Jx7GIMRi8+j4krLsJMzPnwuSgMXxiIWe7BwhYAABAASURBVKRF4sT8rpxhC85h0dbr0GkCsfEpWLiF8iE/DqOsOVq6O3MlFuP/voiRlId0RM4mUX35JYUxlDaFymAyNGrR+Vtx0uLOWHNFPml2e57pmefCE03TULZ8JXzXvit69BmCXr8Pl+Sj9lvvw9bWDiVKlUWHzj3BTymkO1qpNfnsG6JKkHtvfvipj3xckx/Z5PPX/1dbroiEEHjl9ZoyfcGChaGnCYk1Pj/3+EO+WLDXr8PQpn0XKaSUMMmFne8hb1kIgQQiKevXLJNaycpkskpJSd03KIQAvxl35JDf0Z40ji2bN0Tv7t+D36j8cdMWyJuvgFz5z5k5EUsXzkJcXAxOnzyGHzt8jZZffij37EyZNAK13nwHTcicxSYZ1Tfv3lC8QI2ICAe/yI81wvNmT8Grr9cCL4LMtHixkDOT2YmfgnqvfmP0/G0Yvu/UE+7uHihesowkqmtXL0Orrz9C5++b4xKZzr9p1YnCPUmLE4V/ls3DssVzaZFqRClafNWpWx8b161A628a44d2X+DcudNo2aazfHVF5SrV8HK1Gpg3ezK+/aqh1CAnJiWixbcdodMZUKpMRdSp20CSp1bNG+HHjl9TX7mClq07wdXNA/Jt8r93lf2AX43BdeGnx/r0+J7qEgGWlXdHQoU8TQQemexYK2tMMSOaiENEjBH83hozEQgLBbo6GlCxmCt0REoOnInCjbBEOalREB0B/jmJWDIn8dNYTI5YE8NpOY+kZDNHk9odeW1MvWaCxddcJkfgcpKpfPZjTRD7ZXRmypTDkyg9u2Q6GomkcRySc3wAEx4Ou90ZTallyki55+u+7pSJiCOtmvhpCCY5qYksNMB1sCXSY2tnB6uzs7OXG5hBHyEEeEJwc3MngeEOW4orICgk9Z9X4Byfbe7soxG5Yts5P3LKZRkMNuytnELggRAwmVJQ992GaNuhG2kC8kmtDmfA8uHt9xph4PBJaEAaheo16uDrVh0wecbfeK9eI1B3leaOb0jL8HXLDnJfSekyFfBtm05yguYJ+ff+f+KPwePh6eWTni/nrVxmBFhWs/vo4y/RpXt/8Ev6WEvcs89QsCzJSBL5XAgBDw8vvP3uh9Q2zWBv7yiJym9/jAZvcmYyOnDoJNSq/Q7NJSkkT9zQ9POW+OqbdiRvDHBwdJTaIX7z+tvvfCjfzTNgyAQiMPVpIW2WZqrOXX4Dm83eILL6ZYu26D94AipXeYXCTTK/1u1+ooXWKLxJizl+V8/AYZNRo+ZbqeW5uqHO2w3wSbOv0YkWcPyE6edftgb3CXt7B9UXkH0+2hOtCvXqFCIVbGJauu0GlpHpiMkN9d8nWqzKXCGgEFAIZESAJ06efOp/8Ik0lzKhTg+nxZBer8NLtMJv3vJ7tOvYDU0//QYBhYoihQgSp+X4b737gZzkDKRtdCWi/uFHn1HcHjSZdpSkx2QyqcktHdSsT6xLGoONAW+/9wERz+6o16AxnJyd74kdY8v7/SwWMxEeB/yPyEbrtj/hsy+/Bb+RnaYaWSAvnP5X823UeIPJSGp78IKLycm33/1I8VuDiaqMTF8WansXNze89U4Dqan+uElz8L4h9qdgIjxUnoMjar75NtoQ6WlGRKpEydLpdXVydkHddz4gstOCiNTX0jWhvvM2kWpesFnz4byeB8e/F2dMTr6vWzGTho7fqWbVoN5XoicY6dHIzn9UjEkNa23+WnsFo5cE4vjFaPA+n/9IpoIVAgoBhcBjR4AnHqPRCBa+fJ6xAL5OMSZTmJFW7Cb5xI+JiI41Tmq4EZye/ViQJ5PQZ3ML+xkpLfsrd28EpJaWtLw2NrbgSZMxNlKbMJ73TnkrlNuCsed25LR8tIZyGJMi9s/ox2VZ/TPG5zhcNudnrYuJSCv7Wx3nyeGcjvPlY+awJLmnK4nMX1aXnJyUToiscXPyUafTyf1MI4f9jgXzpsn7vdf9cDvz07nDB/+KTRtWSdJ4r/hPI+yJkh3rDTDp0ciMpfGJ1VMdFQIKAYWAQiAXIWCRZr4uPfqTVqchmDg8bzf/PN4PbyeIiYnGn8P7Yv6cKVi35m8iO0l3vVVN0yHw3GkM6f8L+I33u3dtgZk0cndN8JQCngrZeUr3oopRCCgEFAIKgWyMgI2NDYoWKyWfhmKNSTauqqpaGgKspFi+dD4OHdyLwkVKSM0nqa3SQjMfhBBEhBIxfuwQ+XBJ3rz50+JnjvcsrhTZeRaoZ8MyrbZ07tgGvQYb5XIlBtz2ep0GIQT4aKPX5UocbJ5o/88h48ugUR8QGfqC9pj6gnhM+Tyu+mTjfNLaAALP5COEwJlTxzHrr3Fy0/Urr9W8Zz2YwG7euBr792xHy9adUYjI0T0TPMVA7SmWpYrKxgjodEKOJycHPQJ8nVHQ10W5XIhBAN1zXi9HOcl5uNkhoIDqB7l1LHBf8PKwh56IXx4ve9UXaGw87b7AbeDj6QBehD6L6SM+LhZLFs0Cv0z2i+ZtoTcY7lmNoBvX5fuq+G3kdd6uD3654z0TPMVA7SmWpYrKxghYrI8zEOXhgaXTBJR7thg8K/w1KRUE9YTcef/PCvfsWK4QAvwiUY2O2bF+uaFOQlAb0D81xFP9F0Lg6JED4Je5ftG8DQoGFIHFbJZ1EKlCQp6nf1EdN21cidDgIHze/Dv51Jx1WuH+kx7vGZ1IsfaMylbFZiME+D1D3DFTUkyIjk1ClHK5FoO4eCPMxH4TklIQGaP6Qm4eCwmJRprggLiElFw7Hp51+8dzG9B4fNrTRVJSEpaSVqeAXwBefqUG+DcLjcZkuQcnIT4ObLKy1kkj8sMvWFy6aLZ8+z2/EDYmOkpqdlJSUpCQmAAhiA1ZEzyDoyI7zwD0x1vk48ntVjcUslMKoY5C5F4MuFfR7au+QCAIkXv7gRCCuwL1A5ATyhEeQjx9HPAMPgnxsThyaB/451C6/PAN2rdqKp/EunThHDp3aE5h+6HT6WSf0On08k3WVy5fwK6dm9Hhu8/Qsd3nOHHiMHZt34juP7VGRHiYjPsMbkUWqciOhEF9KQQUAgoBhYBCQCFgRcDO3gHftP4BjZs0R4036qJGzbrw8y8Mfov969XfhJe3D/hHVPfv24XwsFAUKlQM7Tp2l7+ZyPGr/+8t+fZr/rmVV159Q75N35r3Ez3eJXNFdu4CjPK+NwJCCPk6dn6zLLN76/H2VJqmg47YPx+tYUIIWONrpP7kcz5aw+915LzY3W/8e+WlwhQCCgGFgEIgawT4bdT8g6z81uhmX3yLTz9vhTJlK4J/s6xx0+bwLVAQ27esR79ff8K+PdvB5q5PmrWQP9fB8Zt82gJMdIoWKwl+2zi/wTyj6SvrUp+cr/bkslY5P68IMNFg2+3O7dswZFB//NipPSZPHEdqzIuS2Fjvm3fu79u3B31/64XVq5ZbvZGYmIitWzahe7cf0bZNC4z9cySuXb36nypOJjmbNqyX+e3YtgVcj/RM1YlCQCGgELh/BFTMB0VAWJAvfwEUK14GBr0BEICHpzcCChaBt3deWG57caAQGooULQG/goWQ5YZmPN2PIjtPF+8cX5oQAjeuX0OvX37Gp80aYdnShTh8+CDGjh2JZk0+xJkzp8AkhN3NG9fRtUtHDB82EMv/Xio3tlksFvy9bAm6de2MwwcP4MqVyxg6pD9+6NAG0VFREIJGUBYocX5nz5zBDx3bYPiwQVi9ZkUmYpVFEuWlELgrAll1MyGE7LvcR9kJweIx6/4I+gghIIQgIW+Rjvsoeav//0BACJEeQwgBxk2IW374j48QQqbhp8RInIAnUiHunl6IW/FBn9ufDBJCyPy4zUEfITLnJYRIb2cKlnH5mNEJkRqH65TR/3k6Z6wbN/kKvX4fDgdHJ7pVC16rXgtDR/+F8i+8CN6InPF+WWP/Y9e+aPHtD9lCVvNozlg/da4QuCcCrNFZMH8O/lm+DF982QLTZszFrDmLMGbsFLxV912YTWYpGLjjjx41DDduXENAocJpeQp5LFKkCH7p9Rumz5yHiZNnotFHTSRhOnnyWJaDQgiBmJgYDOj/Kww2NsibNy8EVNeF+jwwAkIIxMfHYcP6dZg3ZyauXr0CIYScwNh/y+aNmPHXFMyeNR2HDu6HOe1RW9z2EWR+TUxIkBrKmTOmYuaMaTh4YJ8k9EKk9vPbkqhLiYAF586dkYufpUsW0sJnMbZv34rw8DDZBjLKPb6EEEgizfCB/fswZ/YMzKF22r93911/ekIIgajISGqnzZg+bTIWLZyH06dPSXLKxQghEBcXi3937cAsasN5c2fh2LGj1I5mDpZ9IyI8HNwvpk2dhCWLF1D9z8ow6xeTNc5j3dpVWLtmNeUXJ9NZw5+nIxNCSwYNjoUYkNlsAv++WFb3aaG47LIKe9p+asZ42ojn4PKEEAgJDsH6dWvIdlse33fojICAwvD09ELlF6ug849dUaRIUXmHu3Zux9w5M9Ck6RcoW6a89OMvIQReqPQiatd5m1SfPsiTx5uO3mmC7u6TxOpV/4CFSctv2qBgwQDKykJO/SsEHgwBCwnnbVu3SM1k717dsGf3Ltn3mOj07tmNNIffYcqk8Rg6eABatfyC+txKGZ6xFCEEEuLi0K9fH3Tq+B0mU/wRpG1s1fJLrFm9In0izZhGnaciYDSm4J+/l+KX7j/i197d0bNHF7Rr04JwbIcb167dgTWnEkLAYDDIMGNyMubPm432bVti6JABGD16GNrR+aKFc+U+QI6f0UVGRWLkiCHo0L4VJo4fg4H9f0enH9qCzet6MsVwu0+aMI7y+5byGo5hQwfSeUsiNxto4aVHeFgYhgzuj47ft6Z2Hov+/X5Fpw7f4fixI7I+XNZZ0mZ3/ekH6jttMWH86Gf+1BHXSbk7EdDu9FI+CoGsEeAVTFDwDVy/fhUvV3sVzi4uktHzBMLOxtYWOr0eoaGhNOj/REH/Qvi6xbfQGfR3ZBh04waOkcBYuHCBFF5ly1WQJIg1QhkjCyHkfp7JE8fizTfrokHDhsiGNCdjldV5NkYgnFbps2ZOQ0REOCIjI8DvEuF+vXLFclr5T0KDBo2wdsN2TJ8xD1HR0bIfBwcFZVqp6zQdkaDVGD9uNN5+532sWbcFc+YtAWsfx/w5EsHBmeNnYzieetVYTnAbODk5Y/mK9diyfS8+afoZNm9ajz/6/5oJZ64ct43JZMK//+7ENSJDgYHnMGnSOBQvXgrbduzHgoXL4etbAIMH9ZfERAjByaTjtNu2biYN0F/47Ivm2LZzP/4cO1m2++QJY2Ehrd3hQwcxdcp4vFn7LWyn8Ol/zQP/ftfgQX+QdicFW7ZuxLy5M9C6zfcUfgDDRozBzZs3MG7sKKllPn8+EO3btcKRo4fg6OiI2NgYmEmbISugvrIVAorsZKvmyN6VYeERFRlFAzoOXl7eYMF1e41Znblh/RqcO3sGvfr8DhcXZ1jMFinENE3IY0J8vJxEvv31lLo8AAAQAElEQVTmC3T7+Qepwq5Z801wfkKITFkajUYsXbpQbmr+4cefabWVFkzx6D/tQh0UAv+NgE6nw1rSvPCesy+/+iY1AWl6+GT3v7uob+nIpPqJnLRY+9io0ce4euUKLl++KPstxxNCINmYjCNHDkFP+TWkOI6OTihbrjyaNPscISFBuHTxAkdV7h4ICCFIW2NDcsQHn33eHPny58c+MkclJyVLrIUQiI2JxdbNm8BamdYtv8SZ0ydx/PhRMktFoDktopydnVHA3x/v1/8QEWQG2759C+VpSC+VZdG+PbvhW8APn3zSTGpiyleoiNderY5dpHm+GXQDu4lEOTm7SJO8nZ0dihUvhpq1alNZJ8jcdRLbSQtYpmx5NPigoewfFV+ojJeqvizrevP6dTg5OeHLr1pi4aLleOmlaullq5Psh4CW/ar0HNcoh98akxFWJ+v1OiQkJNDdZCYmQgjcIAEwd85MMnOVQ8GAQnJPBO9tiI+PQ1DQTaQQebElofJBw4/Qo+fv+PW3AahSpSomThgj1ds6TUf5pv4zuWLSxHbyV1+rATdXN1rdXUdychIRrhgE0Qorba5KTaC+FQJ3QUBHxOTatauY8ddUvFGzttQiZoxqMhnlJGtM4SPIJKKhWLESRLITEBERkUmbyOPAZEqRyVNkfB4HFlSo8ALiybwVFhYqibuMoL6yREAIQeRDEOYAywcLaVlcXFyhN+glmWFzYJefvkdXWgyFkSmpPZnMWU4EnjsDfr9Lfl9fuSFWExr8/PzBRMW6/wppHyOR0osXz5NpvRiREmfZJqy18Se5FBUdiRjS3HGfyJMnD3zIsVZZp9OjcKGi4P5y/lwgLl26iAIF/GnR5kKaHhNsSXsdUKgIyZ9Y3LhxHfny+aLxx03gV7AgTCmpfSKteHXIZgho2aw+qjrZGAFeKXl6esLVzQ0naIVF8iq9tkII2NnbIpCE0amTx7B/3x60bPE5vmvdAnv27MK2bZvR5tuvEBh4FiyYytJqqU6duvj4k6Zo07Y9dGT+4n05SUmJYJKjaTroye/UyeNgt3HDWnz9VTN8364Nzp45jdUr/0HbNt8ikswRQoj0eqgThUBWCHDfHTl8CHgj6UeNP4G9vX2maC9WeVlOnqNGDMXqVSswa8Z0LJg/S06QPAnSiYzPRIcJf7nyFWX8MX+OAPfFeXNnY+rUieByUoxq0pNg3eWLh2sijfNTp05iw/q1ck/MdVokNWnyOY4dOYwfO32P7l07S3P4j126Y+jwP9Hs0y/h6OxM4z0CDvYO6e1noTLs7R2JnOgleWH8yUv+m0xmRJKpkrUvLF+kJ305krmJr3njcWxMDGnynGBdZAkh6NoRmk6HINL88CKN+wpvSKekMp6jgyOYSMXFxkIjbTX3CbOJaqLEEEP0QO5pRtaeZmGqrJyNAAsSVgmXLFUGa9asBL8rh4mLXm+gGxPYtGEj9AYbtGvfmezwn+N/b7yJ6tXfkKumPD55UKNGTbi6uoEfMee8NE2TwkOvtwEvne1oAtIbDPJpmWvXrpAGJxmly5RDp85d8cGHjfA/MnW99lp1uFIevJqr8b83YO/gQGWrf4XA3RHQ0cTF5pApk8fhq+YtUb5CBdnvOAWHCSHQsGFjfPNNa2zetA7NmjTEz106kUkqlCYzTe7hEEJwdOl4cnvn3ffR/vtO2LJ5o3wFQ+cf2iI0OFjG15N2QkZUX1kiwJjfuH4NHzV8T7pNG9ehQ8cf8WXzFlhPJvAVK/6mNqqE2XMXSa1J3rz5SQNE+LMal9rBxE//EJHhzMmXMBcUDuhpccR+t5wFgi5MJhNxVQudpf6z3BEUoidZI4TA7eGCCAyHMyESlITL46LpFJQMTHyE0CB0GtQn5yCgWivntFW2qKmTkzOaNfsCPkRe2rRujg7ft8HA/r/hqy8+QWvS3Oj1Gjp26owev/Qh9yt+7PIzypQuh8qVX0JnOndzdwdv/mMtzZTJ46X5qt/vfYjYJKHe+w0gSLqwGexTmnDY3s4r6C5df0H3X36V+XXq9AP8/P3xyquv44fOP8gVHk8+2QIcVYlsh4AQQpqWFi+eD+5c/Dh5zx7dSAszQU6Ay5YuwuKF88ET2K99B2LNuu1Yv3EnNm/9V+4FYQLu7uEO/gghKAsh0zHJ79ajD9Zt3EHxd1H83fjo46ZkLnGCN40NIQQnUS4LBFjjkidPXkyY+BdWrdmM1Wu3oMMPP0mtWL33P8DnXzQHv4bi3bo1wRu+z58/R5oUNi8KuLq6Su0ca1yESMU4OjpKhnt4eEKjBZQQQrYTkypXN3daXEWSFs4oa8KyIoK0waDVFWupHZ2cwBvL2RzJEXgRFhEeQfFTEEDmLl5MsWnSTASLw1nLx9pkOzt7eLh7Up1vkSioT7ZGQJGdbN082bNyr1f/H36jiaHu2/Vw7epl7N69S5qmfurSA2XLVkBCQpJ8yiUpKYlWTQJly5WXGprkJBOtvgx4+ZVX4UCq4L+XLsY///wN3pzYq3c/1KxVh4SMCbz5uSyZuZxdnCl9SnpenJ8ZNqhCJoeixUpQOZlXbNkTLVWr7IBAuXIV0KBBQySS+YQ3HIeGhMhqhYeHISwshPoZ9009ipcsCX6NghAC69atRkDBwvD3D5AEJyI8nOLe2o+jaToUL14SlSq/KDWMSxcvgH/BQuD4MnP1lSUCTDgcSCNb7ZXXUPXlanJvH0dk/yJFi6FXn34YOWo8hb2C2TOno/1334Df2RUeFobChYsiNCQY/K4eA2lmmKQcP3ZUkpwyJGeYjERERCCc2srGxgYFCwbgzJlTZBILIdmjl0Tp5InjKFSoKNyJHPn6FsDNG9dx4cIFqcFjGXNUPlnlhJIlS8Of0p8PDEQwae24vOjoaJw6dQK+BQqggJ8fkR2TLFunE3QLqU4jzRA78lD/2QgBRXayUWPklKrodDq8+urr+PW3/hg5egJGj5mIgYNHkOnqUziQPZyFlvVe7Ozs8NXXLdHssy8hSAhw2lpEavoPHIbRYyfhT0o7gM7r1f8AHKZpGurUeQe//zEYxWgiYeFlzYuPrFnq8EMXfPBBIzlBsZ9yCgFGICvHfZE3xH/62VcYMuxPDB46GsNGjEbr79rL1f/HnzTDp9Q3eUIcN3Y0+FHlRQvnyXemXDh/Dp9+/iW8vX0QFRWJ7t064/dfeyIyMkzuIxszeji2b92MJYvmoWOH73Dm7Gl80uQzeHl7S3KUVX2UXyoC3C6sLUlJMWUax+zPMuOlqtXQjTRnw0eMRRU6XzB/Nvjx7govVCKtcl6MHD4YK2ihxFrgBfPnyAVQpRcqSzL6R9/e+K1PDypIyFdkxMbGYsjAP8jkuEm+a2fH9q14r14DuJOWuWq1V6HpNAwd/AfWrlmFv6ZNAu/Zeu+9+sibL580vfOLUYcPHYjNmzZS+j/lk1gffviR3NsTFxeHHTu24Z/lf8un9rifbN64Adu3bZXaJiGYAFFV1P8zR0CRnWfeBDm3AnZEZNzdPUj45CH1vbOcPFhYZbwjIQQcSIvjQCs5q79GhMaRSFHevPmQN19+sCqZ/azhNrY2cHZ2RkY/pH2EEFSWE9i8kOalDgqB/0SA+xT3uVTnAgd7R9lf7ewdqC85IPjmTfzS4yfUf6+23Ah/8cJ5jPxzIplWP5B5G5ON8rHns2fP0ORsREjITfTp3Q3v16uN5l81A2sLhg8fi4aNGkNNbxKyu37xuNY0HUBjGVl8WIawOYmffCpf8QX89vsAzJ23FKVI08JPyHWkxc7NoJv4tGlDuZnZ19cPrGnmPTbJycm4cD4QgYFnSOtiBi+svvjqG6xesxINP3gbI0cMwbvvNUCLlq3JdJ4szevfftsWBw7swyeN66Pv773IRP4ameK7wGyx4M0330KzT78Ev+2Z00+aOAYfNW6CpmTKT0lJAe896t2zK5p+8iH27vkX3G9+7Pw9Ov/QDhFkLtNI1kF9sgUCiuxki2bI2ZVg4fSwd/AoaR+uTJUqtyPAG1IrvVgFW3fsJzLTgEynKajxRi3s3XcM/6zciE1bdmPV2s1Se8hYcXxPT0/MnrsEU6bOgqdnXlR7pQb2Hjgp42+k+GvXbUPjT5oqjQ4Ddg/HpqB233fC7HlLwOZqJjX3iA4ONxqNKFS4CHzy5CN+JEgrUx/r1m+XbvPW3Zg8bRaZlPyJhKaawFljPGnKLLlYYq1e23YdsG3HPqxcvVkee/XpKxdMXK6NjQGff/k1tmzbi9Vrt2Lz1j2k/RsFTy8vWMxmuRDr9GNX+ULBlas3YfO2Pfi5W09ptmTZVTCgEGbMWoB91Bf2HTwJ6Q6cwOKlK+X9cd/hcpR79ggosvPs20DVQCGgEHjKCNiRVrJ4iZI06aW+f4Wf5CkYUBhsPuGXyPFmV16584Qmq0ZaiAIF/JCHf5eNznU6Hfz9/WX8suXKy8kxU3yZSH3djoAQgsiiJ/z8/CUZScf39oi3XTNpsFjMsJC2RQgBNhVWqFQZxUuUkuYkC4VxEtaksMaYN0BbKC47vd4AX2q7F6tUhX/BQvJdOezP8fnIbcntWqlyFRQuUgx2dvayHGs4E7QCVF9+PYGfX0EYDDbp4Xq9Hlyef8GC8PdPcwUDkC+/r7w/zkO57IGAIjt3aQflrRBQCDy/CPAkZ77tkWSz2USaBKsz33HzrGVgZw3gc5mG8uFzq7863hsBiT1pTe4d6+6hFgpivLn9GH/Oj7zS/2VYhvw53Bo3q/gynOJzGDu+Ts+MTvia/VNdKuEi7/R/Lo/J2O0uPYI6yRYIKLKTLZpBVUIhoBBQCCgEFALZFoEcX7F7kh2DXsDeVqfcc4+BBjsbDXJjJX+RmlgIASGUEyI3YgAIgJyAEMoJkXsxAH8EqB+wE3RUToinhwGhDv4I+qJiyTQmoOOnWpX7TxwIIgCMHORHk993+apewRMdGhVFuw8LK/dcY1AEX79TEDYGDXq9BmdHG+VyMQb2dnoIIWBnq4eLk+oLuXk8cF/QqC/Y2xnuTybk4nHzJPoJjz97Goc0IOHhaocCeZ3hq9x/YlAgnzN8vBwlIULa555kx9XRAF9vO+TzslfuOcYgv7c98nja8XgC7/Mzkf1aOTNyKwZm3hQBC8zUGXIrBuq+zdT/LTBTZ0jds2Kha7NyT1k2plB5ZgsNSPrX6XWwtdHBhrTwymn/jQMt3IUQsH4060lWx2U7bqDT6KPoMvaYcs8xBj+NOYbfp51CUrIZsfHJCLwcjXOXopTLpRhcC4qFMcWMkPAEnL0Y+ST6gcozB/Qtbvug0HjZF64Hx1JfUDLhqcvFi1G4GRIvSWdIWDyNm0gEUt9RLuqeOJwj3K7cjEWKyZRObe5JdlJSLEgwmpFoNCn3vGNAkxstHmg9D/BKTjlLrsaBJYTqA7m7D6S2P/cElgnsFB6pmDx9HLgVnlXZOblcxs3q7kl2hBDQSAukySOfK/c8Y4Hs9lH1UQgoBBQCCgGFtYv/DwAAEABJREFUwGNA4J5k537zZ5OiiWy7bN9lx+fsOH3Ga/azOk7D4Rkd2yat4RnTcVwyXZK92CLVedY4zDit6VkrYfW3puU01nB1fLwICCHAL9RKdTp5rt32anQhtLv4C/CLvGRanY7O9RAUF3f5CCFkHD3ZrNlxWiEE1EchoBB4PhHgMS7lA415Phfi7uNdCEHyQSdljVU+IO3DMik1H31a+K2jEELGEkLcNT3oo2m6tLSpR+02OUdR1H8OQEB71DoyQXFx1KNetXzo/VVp/NmxAn5uWhyVirmRVkigYQ1f/PRJcXT+uJh0/NTPy6U94Gink+TFWr7JZIGrgwEf/68AfmteGqPaV6B0xVC6oDMMeoGyAU7o9FExyr8ihrcth89q+8GF4pstFjI3AHqdhtqVfdDry1IY0b482tQvjIJ57MD5WstQx8eDgBCCMDfj9KnjmDNjIoYN+hX/LFsgf4RPSxME/JbRqKgIzJ01BVs2rQW/XdZauiklBcePHsKfI/uj769dsGTRTERGhkEIYY2S6ZiYEI/tW9djUP+eGPjHL9i0YRUSExMzxVEXCgGFwPOAQKoMCDx3GtMm/4nhg3/Djq0bYTQmZykfhBAy7MD+fzFqeF+M/3MIjh45SEAIGf9C4FnMnz0Vs/+akMnNmj4ewUE3oOl0SEpOwt49OzBi6G+YMHYYTp44Sulv/d+8cQ3z50zD731+wtRJo3HxwrlbgeosxyCgPUpNWXNSNL8TenxWAu0bFcYrZd1RKJ8j3qzsjS5EeEoHuOC9anlQt6oPar/ojTfJNXmTyMzXpfD716VRpYQ7mCwJqsSLJd0xoFUZfFs/AC+XcUdRP0fUeSmPJC8NXsuPrp+WwNuUV7ECjihfxBVfvVMQPzYpDic7PexsNXxauwA6fVIUr5b1QJH8jkSy8uO3FmVQ3M9JlgH1eSwICCGI1IRgxJDf0fyzepg9cxK2b1svBUXrFh/h8qULSExIwMp/FqHNN40xoF9XbFz3D5KTU8kJa+nWrvkbPX7+Dts2r8XRowcwZEAv9O7+PeLjYqWAylhR/mG/aVP+xMB+3XD4wF7s3rkVvbq1x+QJwyE3GGWMrM4VAveBAGuE46ivRUaEI8VovJWC+jb33fCwEESEh9EkaryjP96KnHomhCDinYCoyAhaALB+OdVffT8cAiZTCv5ZNh8sS5Ytno1dO7egR9fvSEb0BL8F+fZcY2OjieAMxo8dvpakaM3qZXT+FZbSAoo1OmfPnsTihTOxcP5f0i2YPx3jxgwmudQNx48dRGxMNEYP+x1dO7XEru2bsWrFYnRq9wVWr1hE2h49zp87g+5dWmPGtDFS/kyfPAodvvuM0h6CdWF3e52e/bWqQVYIPDTZ4UnLnkhGM9KwvFDcDXEJJqz4NwiTV1zCyt1BCIlKkhoZLpQsXNh+NBxTV1IYxQmLTkbZwi5o06AQCnjbw8vNFo3f8EVRXydExVFnpzhTVl7G2j3BiIhNBpcTHJWMFbuCMH/TNVwPTZ04KxV3RUA+BxT0cUCNCl6w0WvYeCAEs9Zfwc2IRPh62eHdl/NKDRPXQ7lHR4A1NKv+WYwVfy/Ae+83xpCRUzFq7Gz8+scoVHrxZSQlJUoCs2DuVJQqXQH58/ulkU2RVrgFPj750Oq7nzD8zxkYMnwq6r7zAQ4f2oczZ06QgNGlxUs90FyC4iXK4Oce/Sn+dPwxaCxKli5Pgm09TTDhSuCkwqS+7xMBIQSuXL5AE1xf9PmlIw4f3keEhsWgwEHSDgwd1Bu9e3wv3QSaFINo9S+Ete9mLoQnu9Mnj9JkOwj9f/8ZrMlkP6jPQyEghMCN61exaMFfNObLYsSYmRg2ahrefvdDsMw5cmR/JvkghMDJY0eweuUSNPigCUaNm43+g8ahWPHSpFGeTJqbm3i9xpsYNGIKyY4Z0vUfNB4vVKqKvHl9qYxyRGD2SM1zo4+/xOjxc9B34BgU8A/A9KljEB8fCxtbW9SpWx9/DJ6A0RPm4OuWHeRibwMt4HR6/UPdp0r0bBDgUf5QJbNGpgiRk5dLu0tT0YYDIZj0z0Us2XYdE5ZfxNB553AjLJEEiZArnqPno7Fwy3WMX3YBczdcRUx8CgrmdUAtMj0VL+CE4gUcKS6I4ARh4vILWLTlGsYuO0/5BGLt3mAMm38O48l/1ror2HsqQtaZyY2djQ6F8jvA08UGkbFGLNh8nepwA6cuxVC5QDHSEDnZ6+W5TKS+HhoBIQTCw0NJOKxB4WIliLD8iKLFSiJvPl+8VPU1tOvYAwEBRVDAryA6/tgL37X/GR4eXrCwChCpHyEEXqhcFXXefp/SFUB+31QnhMhk6kqNDbA57H816+KV196At09e+PkXAv9acorJBJPFbI2mjgqB+0LAmJwsJ86lpDXYunmNJD5MUALPncIvP7fFsaMHULnKq+Bf2J5OGsU5MyaQVjIpy7yXL52LXj06kIljKrZtWY/ExASSYSLLuNnRM/vVSeB84GmEBAfhHSI4AYWKknzwA49/GxsbbN20JhPZ4QX38WOH5H6atyi+l7cPipA8erlaDSJNV3Dm9DE4O7vKPFgm+RGJ4cXa5UvnUaNWXRQMKIz9+3bBzs4eb7/XEJ5e3ihatCSqvPw69YuLCDx7muRNABp+9BlKlS4HH5I/FUl2eXnlIc1fKFRLZ78edK8aafcK/K+wYr6O4LfusqZm57EwxCeaZJKEJBPOX48jW6g5U4ewUGhCshn/nojAxaB4ugKY6Pj52INJC7/b4++dN8HpOTCe8jl7NRY3w5NwJSSB8jPRSl4gn6cdByOMtEfBpMHxcLKh9BqCwhMRSn6JlC40MllqFPjtk7w/SCZQX4+EAE8KocE3pSCpQhOCi6s7zERk2LFpwJ6EBq92fH39Ua58ZdjSqsiSha1JCIGoyHBcphU27+dZuXwRChcuhnLlKhFxTu1DGSvKZIkF4KWLgVi2ZA527thME9IrRHp8ZPkZ46pzhcDdEBBCyMl0PZlRq73yRno0IQTWrFoq+3WHTj3Rum0XdOs5EC9Xq04kZp2c+LjvWxMIIZAQH4+F8/5C5crV8BFpBQwGA8k6Nf1ZMXqYoxACrEljLP1p0cTExExmAU8vH9Kw2OH6tavIJE6I7dy4cRV5SEvj7uEpZYHQNOSlBZSm09PCLExWg+WHmeQUy6itZDqPjorAO+81kmGhoUHw9s4DN3detJskmSrgWxB6Sn+T8tZ0Omg6HTgt5xEcfIM0O8FEikqBF/wyE/WVIxDQHraW1C+JdNjL5MlGM2ITUuS59UvcJWdOx/ET04iRvY2GPO521MkEjCkWRMQYMwkN6rvgNNZ8eT9Q+SIuMJrMWL8/BFdDEmFvp4OmUXqaJ/mJLJDMoTEiBwadQkdh1vTq+PAICKEhOjpS7q1hASQBziI7Fgomah9kbLi0eEKkThTTp4xBx+8+J3t4G1I330DN2u9BR0IlLVr6QQiBYCJYQwb0RPvWn2LowF5wodXaq6/VBJeTHlGdPCEEno9shRBywpo/dxry5i+AWm+9m+nGgm5eJw2BAWx2TU4mmWLvgJeqvY64uFiEhQZnissTn529PfqSyaRT11/h7kXaS5p4M0VSFw+MADUR4mNjZDux+ShVvlioXfTSJVG7GFOM6fny4pn33LDWh8mJbAL6sjHYQNM0IqRxlJdZxhdCIDwslMjrWrzwYjUUKVpCmtyZtNrY2ELQH0cUQkhixaQpjsxYGf25LDbfe3r4SE0zP2jBaZTLGQhoD11N6mkJySaZXK8TsDXo6Jw86Zv/qc/x4Q7H/ga9Rqt+TYax9iYuMYU6JWiyE5K43MqFujtd0D806oS1KnmD9wjpdRp2n4zAYjKZcSZmYjacr56qoNMEe6U6OmX2LQlQqo/6fgQEWMjraMUjSJAkJ2Wt2v+v7DkPG1sbvFHrbbRo1QFtv++K0mUqkI19kjSPaZR3xjw4vqubO+p/2AQt23TCN607wcHRCWNG9seli+elUMsYX50rBLJCQNPpyAyyDvv37kK9+h+TSSJfpmjeZKJIoYn08KG9iIqKlAQ8OipKmlZ5QuR+mDGBEAIFChSEEESiSP5kDFPnD4kACXqd3kBzgUVuDk/NhfAl4c74s8Yn04KI5LveYJBtZCKzNjWFTGJm8zalYRIDUCQAnG7LptW4du0yXqv+JuztHaXs0JE8YwJl1UBTMlpE8bxmoTnKjlJaIISQxGjq5NE4duQAPm7WHP5kAuM6UQT1n0MQSGUcD1FZC6W5kmaKcnMyoIS/E8zUU5hYsLPRacjIOzgsxWQBhxUh85fVFMWaGd5MnEKaAN6DU7UUqxPNSKG47GwNGgyU0WvlPPDV2wXh7mzA4cBoTFt1GcGRSbLMRDKNcb7uzjbSnKVR53Rx1FMnBZm+zIhjLZKA+jwiAhYSIkw8nF1cERh4SgoLa5YMtp4ElXYbWUkPz3DC8cqWr4Q6dRugcZOv8OXX7WAmNfM6Mi8Yk5NlvhnzcXBwRFUyKfBG5s+/aoMPG31KpoXzNHHtgLiP8jIUrU5zIQLcl0LJ/DBy2K8oU7Yiqr9RR2oKGApNaNR1BWq/VU8SoDGj+uPnTi3x0w8tsHjBDAj+E4Kj3uHMZpoUWRDeEaI8HgYBhtLZxYVM2SmIIjM3txtDHx8fB5YLnp7eYD92QghqGcCFZBFrm3m/lCyT/KMjI2E0GuFKiyS6lGn4ybsF86ajgF8hVHyhCvkJMAGyd3RETDSRWooP+rCMi4wIA5vQ2LxFXpRXMmZNH4eFc6dJ89e79RpRWj0HKZeDENAepa4nLsVIs5O9rU4+6l23Sh4Uze+IOpV90Kd5KRTM6whe9AgqxNvFBmUKOuGdqnnQ6v0A+LjZgrU66/cF48L1eETGpoA75md1/MBPUJUo4IS6VXzQv2UZ1H8tP76sWxB5PGzlU18bDwSDK17K3xmeLra4FpYoNzzncbcFP3pevrALSlIYk57A63GIjqe8qQ7q/9EQYEKSL18BFC5cHJs3rsbBA7thR+p8ueLSdDhyeL80ObEw0un10Gl6CP6jhtVROPtbiBAnJiZCCAFNE9DRysrR2RmaTgcdnWs6Ha2iksh0ECJXeBYiQUkUn9OCPjY2NmABRRnAYLCFID/1rxC4FwImWvXPnzsd58+flU/nREZEgJ/64b4YFhaC0JAglCLt4tRZy/Fe/cY0gbqhUuVqqPtuQ+ipH9sT2RZC9bR7Yfw4wiy0mPL3L0xkx4TjpEGxIfMS58tPvMXGRuPV12rJsMjICMQTARJCoBDJosuk4b129SLJAwNY43z86EG4uXmAn8rithdCI/PVepw+dQys1SngF5AqW4hd+fsHICjoOi5S3+A9hsnJSVJ74+joTBrnijDS4msh9Z3JE0eCF1vfff8z3D28wPINVD7UJ8cgoD1sTXU0UV0LTcC8TdeIqBjh7WqLTh8Xw8BWZfHDx0VR3I/VhJCdiie1Bq/nxzCFub8AABAASURBVB/flkWnT4rBh0hJUEQSpq68jLPXYnGOCMnWI6HphKXDR0UwoFUZdKa4+bzsZF756ch15c3G37wXgIGty2IgldW0VgEiS3FgUsPEqsV7hdD9s5Lw87FHSFQyVu8OokpwSuUeBwJOREzqf9AETk7O6Nq5JQb07YapE0eh64+t0Pn7L3HpQiCCbt6Q78pYvGgmgkNu4tKl8+CnX3Zu3wSjMRmTxg1Fjy7fYfnS+Vi6aBbGjhqAhLg4/I9MWzoiO/8sm4cO332GE8cOgQXb731+xMC+3bFm5VLM+msiZtIqy8cnn3yqy8yN/jhuTOXxXCIghJB7N/gFcm600p84fhi+b9MMY0cPkLJp7sxJmDFtLPgdT75klvq+U08MHTUV35F5NS4mCi5ubvD2ySOxsRBRzyhMhBA037GTwerrERFgfAsWKoIKL7yEhaRVmzRuOLh95lAblSpdES+9XB3Xrl7Gr790xIghv4FlRdnyLyCgcFGMGtYPS0iWTJkwHNu3bUCt2u+SFicAZlossaZmxfIFcHVxw//eeAualjrtWYhcVan6Ovm7Y9TwfqTJm4VJ1D/279uJDz/6DA5OTjhMZs0ZJG+oleHp7QOuy5SJIzB/9hRERYTL9n/E21bJnxICqa3+kIVpRHhW7LqB8csvYsvhUJy8HIMgMi0dOR+NpdtvIpCIzMFzUdh3OhInKOwkaYK2HArB4q03MHjeOSzfeRM6yiMx2YT5G69h6urL2HU8HGeuxOJGeBIOUNql229g76lImcdeymf/2SgiSHHSnb4aK01ZN8MTMWvdFWw+GIJz1+LAZrEdx8IwYmEgTlG52iPd5UOC89wmE3Jz3g8/9UGlF1/FiaOHsHHDCposYsAmplJlytOqmdpiw0ps27QGAQFF4ejoBLaX7929HbxaK1m6PBIS4jFvzhTwy75sbe3wXYdueKNWXfmSN15J583nC4ONDRyJVJUsVQ4XL57FjOljsW7NMvDj7p27/pYmzEzPLdLqxh4dAQsRFFs7e3z08Rfo0Xsw2rTrgtZtf8J7DRrLiapGzbfwZp33wNrDK1cuypfMBQfdpInvL2zatBov0WTITxcm0wp/6+Y12Lp5HfhdUkIIqV1gEwi/iJDLiY2NkRuaWZvw6DXPnTl4eHjhy6/b4pXXa2LD+n+wlkzb5StWwY9dfyctsp0kKl7eeeDhmbopnLXM37T6Afl9/bBw7jQcOrhHPkb+GZm7TaYUCWJ4eCgcyFzF79IpWqykJEAcwG1WvHhptGzTCfzABb8bjLVC9Wkx17jJl2kvMRQoVqI0yld8EYdIk72DiNTO7Rux+99tiImJhnjUyYUrotxTQeCRaICgKiYmm7FxfwiGLQhE/1lnpBs45yzmb76GiFgjaW8u4Q/pfxoDZp/BcCIgf625jENnI2Ei1k1ZgPOJpLgrdt0Ep02Nf0bG5/ftMJEaOOcM5X06k/tj5hlJmFJMFhy/EI0Ri27VYTjVZ8+J8ExPKnJZyj06AgYbG1Ip10S3X/qj78Ax6DdwHHr3HYHGTZpLYlOKTAJdew4EP63Sd+BYsOs3aByaf9NeFs7vzfjl16GUjsIGjEHP34aiXv2PoNMbpPD4X8230a3XQBQpWlKSo8affIlf+41G3wEcfyy6dP8DVV+uQXmRHpq+1b9C4F4I6EhbyH3yzTr1iNjUQ+2676Ny5VcghECZsi+gbIXK4Pfr/ND2C3T+/it0bPcFRg7ri7JlK+GTZl/Dlky1/MLASeOGSa1iJK3oeaIcNqgP2rduJrWYcXGxUuPQgzSWp04euVd1VNh/IMCLm04/9gHLjL4kHzp07omixUtKExYTnTbtf8anX7SS1zoyM776ei107zWI5Mw4/Nb/TylnrGSI2ym/rz9+JpnBJOp2cqI3GPA/WmT1JHnEcuq3/qPBRMnN3VNq/sqUewF9+o6kvEn2kJzrS47r1aP3IOTPXyCNEP3HDangbIHAI5Ed6x3w5uP4xBTSqCThSnACwmOSkZJilsG8Lyc6zojouBRppopPNMGYFiYjpH2R3CHGbZGPsN8kE9fVkAREEQFiIsPx+SWEnEdmZwRrhTgLnvY475sRifINy7EJKYroMDBPwLEAoZkCrIFh4ZOPBr0LqYg1WuVwmIEEiKurG9nN3TM4D6ml4erw5MMbCwv4FSTtTEGkptWBpAsHw87ODq6u7uB45AkWSO4envAvWAj58vtKQsX9RUZWXwqB+0CA+yWbNNilmEzIR5qAjz75CkVLlKIJy0yr9zJ45bWacHBwpn5WGN//8AtGjZsFNm3xzxRwH+U9PG+/1xCurm4QVGbhIsVQplxF1CISxVrNipVeonxKw8nRmUIf63+uy8zewQF58uRDnrz5YW/vkH7/LGNYdvBDC1ZP9nNydqG28oenp7dcIFnD+MjyyIP87Yi08vXtTtN04PQsjzw8vGEw2JDY4RkFdG6AK7W3G5lAbzmPVJlFJPr2vNR19kVAe5xVE5QZT0J8pNOH/uf0nM/DZPAoaR+mPJWG5UKqYHhQLHgCYne/6Tguu/uNr+IpBLJCgDe9+/kFgFfz5cpXpkWWCXlpUu3882/oP2Q8reRH4IOPPoWm0xH/tkhnQ9pM1gw0JoJk7+AoF1JfNP+ONAqD8XOPP/BTt77o+ssAtP+hBwoVLZFVscrvIRB4kPH+IHGzqsqjps8qz+fNj59SM/NTiPdzY2RC5viWbLKv8rGSnfu5fxVHIaAQeEIIqGzvGwHW8CQnJ5FWxyTTWK+FENI8YkxOliRHBtIXT4S8uZ4dn5MXkpKS5E9E8GPPVsd7f1gTxOHKKQSeFwQ0nQ6XLp7DjGljsHrFkrv+hIr1fjXS8u/ZvR3TJo/C7n+3ZBpL1jhP+6jIztNGXJWnEFAIZFsErEQm21ZQVUwh8JQREEKASfzYUQMxcdxQLF44k0h+4l1rwUTn+rUrGPB7V0yZMAKbNqyC6X61QXfN9dEDFNl5dAxzWg7/WV8W+Mqlmi9yJw6pXYSNk7nz/nNz22e8dzOkvY66g+oHGXF5uufpjUDt8Cz+daTVWbfmb2zdsha8pymZNKKkqsmyKkIIqS2dOnEEIqPC5T7NZNKSWvtRlomekqciO08J6OxejCYgN13aGnTwcLWDh5u9crkUAxcnG2jUIZzsDfB0c1D9IJf2A257J0cDdNQXuE945lIcPJ7hfXu628PJ0QbEIfAsPkIIMl8FYjqZo6rXqIs3ar39n9XYtWMzNq5fhS+bt0XJkmX/M/7TinB3svO0aqDKyRYIsEDjitjb6VEgrxP8lMu1GHiTgNXrNLi52MEvn+oLuXYsUNt7uNlBr9fgRX1C9YVnMxY8afHJiw+Wz0/bsfnq78VzwdqZb1p3zPRk3J11EfLN9/wC2ZKly6JBw2ak0GH98J0xn4WP9iwKVWVmPwRSzKSapWoZU0yIiklSLhdjEJdghJn6Q0KiEZHRqi/k5vEQT32A+0I89YncjAPf+7NwPP7iE1PIavT0SYMgjd7Jk0ewaeMqfNz0axQvWQamtHfjZalqEsD2revkz7J8QVodJxfXW/WmMJpenum/IjvPFP7sU7glbSxZyEzP70jidxspZ5bvhMptOJhMqcTXRIQnt927ut/MfV72BZIN1vedKXwy4/Ok8UgxmYlgWEhD8vTnCmOyUb4wk98u/V79xjBTXaychY9C3KIPmqYhPDQYSxfOwksvvYYXXnwZ/Ng5wDEBjcxhQgg8y8+t2j7LWqiyFQIKAYXAc4GAugmFwPOBQFxsNHZu2wj+Xbne3b9Hp/ZfYsPaf3Dp4nl0/bE1jh87CN68LISQx7NnTuL48cPybeRdOn6DLh1b4PTJo/h35xb06t4BUZEREOLZER5FdqA+j4IAM3ru8HzMKh8hBDRNR508c1cTQsgBotPpKTxzGO7xEULI+EI8u0ED9VEIKASeOAIaaQt0OpYd/z3WU+PeXZZYw2/PTwgh5QmH3+6Q4cNhqbLq/uqTIWmOPeXfLOQfRH29Rm34yrfd+8PJxQU2BgN8ff3km+6jo6Nw7twpxMTEIF9+PzT7/Fup1eE3j/sW8IetnR0cHR2RL58vNJ3umWJx/7PMM62mKjy7IWAVGlevXCE2fxShoSHQ6/VEam4JJiEE+GVrvBKICA9LvwUWHEajEadPn8ShQ/tx88YN3EqVHu2OEyEE4mJjcPHCecRER98RnpM8VF0VAgqBrBFg+cAhly9dxIkTxxFLE6nVj/0zOiGElB0shw4e2IdLlMZsNkMIIaMJIeT59WvXcIDCz507KzfbCiFkOOd99epVXCE5duXqFVgdx7eQTV8IkZr++jUcPLhPyh42zwghZPrn+cvO3gFftmiHdh26o33HHuR64sUqryIPEZdWbX9C4SIlsH3LOvzaowP27tlG18XwXfuuaPc9xf+hB9p+3w0FCxYG//7c1992hJOT8609PM8AOEV2ngHoOb1IFjxHDh/CJx81QO1ar+Kdt/6HOrVex4D+v4PtvEKwIBAwGGwwYthgvE3hw4YMAAshvvcTx4/h66+a4d26NVH/vTqoX68OZs38C5wvh2flhBBS6HTv9hPef682pk6eIMlVVnGVn0JAIZAzEWAZcPXKZbRq+RXqvPka6r1bC40b1SNTyI4sx3tYaCh69+yGunVq4L13aqLeO2+i/x+/Ij4+DvzhRdGA/r/h7bo18GH9t/DuW2+g608dERkRAV6wTZo4lmTXa6hd8xVyr6JOzVdlnIYfvoPzgYGIJs3FH337oG7t6njv7ZqyjN/69EBMDC+2BBfxXDvGSKfXSaw0OvJviLl7eEFP2h1AQAhNynVbGzu6FNBRHOlIi8NHV3dPuLi5Q6/T41l/tGddAVX+vRDInmE7d25H62+/whmy0Tb+uCl+6PQzqrxUFfPnzcLhQwfAAkun07B1y0ZMmzZRCobwiHDJ6pnw7NmziwaICT916Y4ev/SBs7Mzhg3tjwvnz8u0Wd21EAJLFs3HksULEBYWRi4UQoisoio/hUCWCPDjs3GxsaQdvOX4Jx+skYUQSE5KkhNhBE2GHCbEvfsYT6oR4eE0KUZTn76lUbDmqY4PhkAEyYlBA/th585taN6iNcmIHvLnOzp2aIPgoKBMY14IgTNnT+HI0cP48MOP0J1kSZGiRTGZCMya1StpsWUgjc1lnKTFVcOGH6P/wGGo/r83sHTZIixcOJfC9ahStRq+av4NuZZo3rwlmjb7HM4uzogIj4CjgyMCz53Dgf178V69BlJWlS5TDtOmTsTfyxZDTxP7g91dDo9tseCrFu0wfPRfJLNd6GYsqF33fUybvRIvvfw6UkhbT57p/3q9Ab/3/xMdO/eELhtgpaXXTJ0oBO4DAZ4sFhCpSUpOwtDhY9D71z/QsVMXDBn2J4YNH4uChQrJXEKCg9GfVlQBAYVRoWIl6QcIIjMC7777PoaPHIdWrdvh65bfon6DhoiLiyMV9AW5gsBtH41fgZPQAAAQAElEQVRs9+fOnsWQwf1Ro0ZNFClSFCBBB/VRCDwAApMmjkfXLj+g68+d0t3cOTNoMk2h7iRwlCbN/v1+Recf2uIHmlx5RX/82JE7ShBCkHk2EUuXLkL3bj+iQ/tW+KlTO0ybMhFRkZEyrzsSKY//REAIIcnFvr278fnnzdG9e2982+o7Ij2tpJl89eoV0JOp3JqRhSbf0qXLYuiw0ejZpy/ad/gBbdp2ILLiikMH95Os0RAQUAj9/hiCbj36oNmnX6Btuw7w8fbBxQuBMvy116qjS9df0LV7L/zcrRc+/qQZ7Ozs8Vbdd+Hr54eiRYth4OCRYDnX7vsf0K79D/D2yYMD+/ZRep21KrnmyLJYR1ob6w0LITK1idXfeuT20jSd9fLRj4+QgyI7jwBebkuqEem4efMG2b73o3r1N1DjfzUlBLz/xtHREa+S4PDy8pYMf+GCOTh+9AjatfsB+fMXkPFSvwS8SNj4kMCwkEdsTDwCA89KAVOggD9NPP9n7yoAozi68Dd7d3FPIBDc3b0UK1KBUigUilPc3d3d3d1di7e4u7sHSYh7zv735hJIIFDgbyGQ3dysjO83s2++eW92YyTfVz8hLAPL0iUL5Oy5TduOcCG1KD7Ly5iv6qWefXkIrKfZ/CkaSK3IvGprawsbaxvqdzZy0GJy3rljG2zfvgWZMmdFRiLUrKmcQOZXNpUI8UrDoyFhf+vmdYwYOlBqgni2z+s+RgwfhK1bN0kN5peHzuevsRACd+/eRrQ+GsVLlIRR/j8lASY0Dg4OOHPmJLWVEq+iTk7OSJ8ho5wk6aONsk0VocCO5BGTIVs7O6ROm5a0ODoYDSbcunkToaFhYFljMpmlNs5gMMjXpE1U3r59e+Dv9wLVf60hSasDaZ0zZMwo00dHG2BtbQ2Wg3YODlQPMzn1xzi/DYV3hb0tzX/lH7/n/FelqPl+FQjwQ/7ihQ+peP2RI2cuKQxiOzMfzXJBn0Kq5ZtYtWoZ6jf4A2XLfUcCJT6B4a9yrl61HN1oNvxbjSrYsmUTmrdsi8xZslJc0xtYnSM18p/bN6NTl+7ImYfimOPn90YC1UNFIAEEDIZolPimJMZOmEyaxZmYNHUW6tf/Q85MeR3ZZdLs1KXZ/8DBIzBq9Fhpurh69TKePvWWfT02S6PRiHTpMmD5qg2YPnM+Bg8djqHDRyMqKhJsoo2ICI8XPzadenw3AkII+Pu/gJbIpLu7x0tZwBMpnc5amhcNesMbmZhJw8NOCIFjx44gKCgA335bRhIYIQSY4A7s34u0RbXRo3tn5M9fAL/Vqiu1c7GZsWwLCgrCju1bkTt3XhQoVESm53DOm50QCk6eOI5nT5+ShrksuB9wuOq+DAS+WLLzZcD79dUyPDxSCnU7W7sEZ7CRJOjXrVlJMyErtGnbASYSRLEokNyBEEIKicePHuHmjRskcCLg7OSE69eu4PHjh2ChExufIkttzooVS+Vs+7ff6sCop9kU/SxxXp5YLtW9isA7ERCIioyimbs/goOCweTEYDTIfuzk7AxrGxvwm37Pnj3Bjes3cenieSQjLaSrm7uME5s1D3zOLi7Inj2H9OJnIiAgQPZ1N1c3SZ5kgLr7QAR4zZReYi2ERZPGWAvSKCsalhsmwvjNyZAQQsqNY0cOg03sv5BZPG++/DCZLHED/P1x48Z1PKd2daZ2DggMwIWL52QaxGwaIlj7/9qLG9evocL3P8LB3iEmxHLQKBrw2p2VKxajcpWqKFKk+Mv8LTHUfWJHQCU7ib2FElH9WPA4OTuRithOznbjEROqp4YExu1bN7FzxzakTOmF48ePYNuWTfD2foxHDx/gTzIR8KDAKuZWbdpj0ZKVWL5yAxo2aordu/7E4oXzKBcQx7EIOrb3nj93Gn/9tQcpU3jhr327sX3bdvACZS5nx5/bwYtOhbDEh7qpCLwDAe6fPMvv26cbBvTviTmzp4Nfb+YkrKls0aINjhw+iO5dO6Bzpzayn7Uhs6mXVyo5AHO8uO7Ro4dgDeWM6ZMwftxIZEifEb9Uq0mmDpsE48dNq54nhIAZ9g72ZL4yISwsVMoBIQT0ZNbixa+8cFin0yWQUEiNS5/eXZE2bXo0bdYa/NIDR2SZVaZsOcyaswgrSBM3eswEhFPeo0cMQSCRHpZhQgiEhoZg4YLZSJs+Pb755tt4RIjj8NunvXt1gZubB1gL7ezinNjamG9Xde9AQCU77wBHDYqPAM+UPJOnADtWF4eEhJAGRycFAxMTVuIEBPgDxD2uXrmEMaOGY8rkcbh+/SrOnz+LyRPHkgr4iUzDwsjFxZWEU1pU/P578Fqf27duQB8dLfNjAaNRFKnZETDj6NGDGDN6GKZNnSg1QCdOHMW0KeNJKIZB3VQE3geBJk2ak/miDjJlygIfn+cYOWKwdHzu4OCIqr/8Kvsmk/XDhw7AwcEBadKkletBXs+f+ycT+EWL5tEgORfnz52BPWkDTGTK5QH29fjq9T8jwLixbGGN20OaHOmsdBBCkEbmGSIiI5Ejey7KRLyUD6CN2+HihbOSvPLEp3e/QciTNz+lUygUdBTgBceurq5wd0+GkqXKIneefLhz57b8fo8QQrbvgf1/4ezZ0yhTuhzJpPQviQznf420zn36dJXm+159BqBgoSKUryV/qNsXg4DaYl9MU33+irIwSpEyJb4r/z1OHD+Gvr264c7tW3jx4gWOk628ccPaMJiM2PvXEfx14Dh27N6P9Rv/BL9B9eOPVbBh8w5kyJCRND/bcfTwIbm4Mzw8AseOHoOvrw8yZc4CG1tbnDlzCtOnTQQLvJ8q/4xjJy9iD+W5Y/cBrFm3BWxTr1WrHtas3wYWYlyvz4+OWoPEjsAfTVui34Ah0i1ctBJsFj165BCuXr6Im0TI69WpARs7W6xeu0W+pvzo0QPwouVbN2/Q4EYMPs4N8nqNosVKYOOmHdj39zGMmzAN165dxuABfSShFyJ+/DhJP+9pIi7dRLOlrGQa9CBSwqZwn+c+pF17gfXrViMyIgLVqtdEQIAfli6ej21bN0uScu/eXfTv1xN3797ByFETkCVLNpJHPuDv6AghcOXyJYq7Cb4+PjCbzOA1WLw+K2PGTHBydpFoBAUGgt/K02g1+IlMVLx4XQbQ7hGZ23m9z+VLFzFsxDiSPfmoTr4yf1XuEEBf0E8lO19QYyWGqrIa+fe69Uld/yv27duFmjWq4LdfK6NF80bSVJU6dRrY2dmTGtlJOgcHJ9ja2sHO3oFmvo6kowGOHDqItm2ayrQ1q1fGzOmTaDaWDw0bN5NmqUMH/sacWdOl/dza2oZm2I4yL0dHJzg4OsTkZ0f52UPdVATeBwEheM2HUfavqKgo2NrZyHUXer0ekVERckG9D2l7Bg8eie/KV0TzFm0xYNBwPCJTFZPvhAY2NovZ2dnBxcUFjcgUW7JkaTBpf/r06ftUSY3zOgJEdliTVvO3OlIbXLP6T6hTqzppdQ+hc5eeSJsuHZ49eyrbit/2ZK3L+bNnJKFhajls2AD8+suPJI9+RquWf+DJE29qvwcYNnQAatWsipokp9q1boaw8DC0atNBthu36xXSQl8iMvP995WlHGIiG1s1XrR+8cJ5MBEaP24Efq1G+Vf/GU3+qId7RLA0ZLqPjaseEzcCSuKunlq7xIYAC4c0adNhyLDRmDBpOprQbJnV/737DMSCRSuQOXNWuQCZ47GztrFCjRq1JDmi8QY2NjZo2rwlevYeiJLflkHpMuXofAAmTp6JtGnTydv9rnwl9Ok3CLly5ZZvRHA+sc7O1h5/NGmBSt//JMuRCdTdv43AV5WfEEKSkIvnzyMkOFj2Kf5Y3LZtm8ALjb1SpUFIaKi8ZyY/7KKjo8BffWXzLBN8o9GAgwf349Ch/USYonCXzCCH6JoXv/Ki51tkgn1KA7EtkR8nJyeZl7r7cARYPjRs1ARjx0/Fz79Ul4uBx4ydQjKjlXzePT1ToEXLdmjazHKdN18BSUp79e4vNXV16jaQHwasVq0G2AxZisxSI0aMJ61QDWl+atqsJabPmC9NlkajUS4ydnN3R5s2HdGpcw8yY1qBZU1szXPmzIW+/Yegb9/B8fL/tcZvcHVzixc3No16TJwIqGQncbZLoq6V2WQi85Gb/PBWq9bt0b5jV/CXlNOmS/9GvXU6K5Sv+L38Jo8QPP8CUpH2p+ZvtdGla090ohkbf8iLZ3S8JkgIQariPJRfPfD3eNgvbqb8xkyVqtXAJoTXw+LGU89VBGIR4Nk3/9+kli0ayRl/uzbN0LxZQxw68Jck4tmy5gCbWZ2dXTBoQG9weOsWf2Dc2BHIkjU7ChUqSuaTAIwZORTTJk+Av78fzp09hY7tW0qNZlvKr2WLxrh/9zaqVKmG1GnSxhatHj8QASYa9g4OqEAyo137LvIjgeW+Kw9r0vBymEPM2qpvS5WRRCVjpkxo1Lgp2ETZrEVrsGvesg1+J9LjSJpg1ryVpfT8scFuPfqgafPWKFS4iDSBcX5cPZ6g8aQtG5nQXpcpLNMaNPyD8m8h847Nnz+r4ebmLuvAeagu8SOgkp3E30aJsoYsKExEerhyrE7ma3Z8/bpjf3ax/nzOjgchjUaRAoOvX4bTCV+zo9M3fuzP7o0A1UNFIAEEeAZfrHhJNCBTk5WVFfh7Kry2Y+nydejavS+srK0lGef1Zd+ULAV+2y8iIhy1f69PWoC5SJ8xozSjli1XHuXIxOXk6Iwff6oqiToPqKEhwciaNRtpNleiS7ce4DLU/plAQ7ynF2PHpEMIIddK8TmkAdySAYez4ys+cnhCjsPZcZgQAqyli73mY1xnpvw5r7h+fM5+nD4hx2EcR3VfBgIq2fky2kmtpYqAisBHIsCDkrOzMzp26opFi1dh2Yp1mDFrPsp+V4FypGHObJaEO0++/Bg/cZoMX7xsDZlHhsIrVWqYyNzB5pVeZKpt36ErWPPAjs2pbLpdSvnxq83f/1iZzBqUpfpTEVARSHQIfAqyk+huWq2QioCKQNJCgAkPL0w20wyeZ/j8mjL/m4C4KDCpYX9NzKLTyMgoSYI4Dqc3Gg3Q66OJ0FAuRJD43GQySo0Bp9Pr9RxVdSoCKgKJEAGV7CTCRlGrpCKgIvDfIMCkhd27cudwdq/HSciP47zNn8NUpyLwJgKqz+dA4J1kx2wy08xGdaYkgsPn6IBqmSoCKgIqAioC/4yAmaKozrJ6631wILji/d5JdlJ62CBPBmfkUt1XjoETsqd1hIZ6gyCn1WqgU12SxUBDHUGQmOCjTqdJsjh87mcgMZSv0QiAflrqE4mhPkmtDiyLNYrgJoCNlQYOdjpyWtXZ/QMG9lrYWmsJN4HYTYk9Sej4fdHkGPRHDvRrmE11XzEG/RtlR6ffMsFap4EVOSdHHVSXdDGwt9VCIQHLwtVZ7QtJ+lmwtbH0BTvqE6pM+PQygZ8/fh6FEPBwtUWGVM5I76W6cmyg6QAAEABJREFUf8IgA2HkldweGq2C2O3VWaxPnOOJq/6Yt/0+Fu14oLqvGIOFfz7A6r+8EW0wITzCAO9nYar7YjD499vqRUAEDEYTgkKi8fhpqNoXkmhfePw0DAGBUTCSXOA+wdeqbAj7pM/DY+p7LwIj5XKSwJAoPPEJw1Nf1f0TBk8II19/ws3IBi8LqXkn2bn2IBQ7TzzH7lOq+9ox2H/elwY4M6L0RvgHR8EvKFJ1SRSD4LBoKVzDIqLVPpBE+wA///5076HhehhNZgSH6dW+QHgwLp/SyTYg7M00ZnNb+AVFqO3wPu1ABDE4LAr8/9YsVAd4J9kRQkBQDCHo+IkdyNqGT1ymEJ/+PoX4NGUK8c/lIGYTdFQdkFQxQJwtqWKg3necTkCnKh74LPIARHIQs6ltgA9qA8jtFYBEZaTP/71jBsUzAAOpjfjITPRjM+UFWXY2GthYvaqeQoP1x+YXNx2/WcX142Ncfz5nWDiM74Ed3xP7q+7tCCiKAo1GA8GsOIFoHJ5Q2wkhwGHvSos4mxBClmOJz4891E1FQEVARUBFQEXgvRB4xSZk9I/cEUtwdbRCjnSOKJzNBVlSO8CaiAp5f1SGeTI6oX/DbOhSKzM0ikCGlHaoVzE1fijq+VH5xSbi72Gkp7y4nmk97WiwfTVokqYWOo0i6144uwvyZ3ZBMhdrqcKNTa8eXyGgEMlRNBq88PXBg/t3EBISBP5YmxCxmAowMfH38yW7v7/8EBtiNk5rNBrh/fgB7ty+jsBAPwgRmy4mUpyDomgQGRmJ+/du497dWwgPC6W2U+LEUE9VBFQEVARUBFQE3o7A/z1i8BhVOr8HhjXLiTEtc2Nki1wY2yq3JCr2pJ15e9FvD/FwtkbeTM7In8kFOq2CUnk9iOykQe3vUoFXpjNpeXvqhENYS5MmuR2GN8uFca3zYFDj7EhL16zJYaKTjsjPwEbZMbY13UPzXBjdMif4Pr7N7UEDdcJ5JlVfhYjO/Xu30KtrczSuVxmN61ZGs4ZVsXTRLJhMJklyQPrXDWuXoXmjX7Fk4UxERUVKuIQQYNIyqF8n/FHvZzRt8AvaNK+FXTs2E4F5k/BwW586eRid2jSguFXRpEFVdO/cFJcunIGgeshM1Z2KwD8gIISgfqlN0Anxqt8JISRpj0/c8c6NnwetVgedzor68P8tUt9ZVlIJFELItmJchXjVPkhgE0JQXI3EX6PRvnXiFNtOWp0OcWWHEHHSa7WIt9GFQpMtzjeuAwTU7ctC4P96MpkofF8kuSQ22Uibw2/z+ARESW1IsRyu8HK3pSEvAUDi9BMzBZPyBlqNgBDiZXxB/qAdk5RHz8NxxzsMl+4EIyraCCEEBIVzWjpAQxko5GKv2e91x2a1MvmTIYWbNWytFaRLYYeiOVyIyJhBSVEwizMKZHWGwWCSi/E4vzTJbdGsSlp4UhpO/3qeSfNa4OL5M+jZpSVOnziCQkW+QdXqdZDcMxWRmhm4fOksHj96gAG922PG1FHwfvIQ/i98iAQZJVys0Tlx7CCePX2MX2s2QN0GLRAdFYXpk4fjifcjCCV+l2SStH/fDlhZW6Fh4zao/PNvuHH9CubNnoioyAgIIWS+6k5F4G0ICCEQGOCPUycOkzv00p0mEn329FH4+jyTSc1E1J94P8Thg/tw6MBe6sf3wf0VSLiPCSEQGREu++Nfe7dj985NuH3rekwaqNtHIsAy39fnOU4cO4C/9/2Ju3duyH/TIcSb7cCTIX/SHp+ktt2xfYNM84LkjfnlSGKpBMsKlht/79uOfbu34e7tGzIGp/d7mX69lGmBgf6WRLQ3GPS4dfMquK+cOnEopu8cBpcpxJv1oSTqL5EiEH9k+YBKcof0dLVBrXKpwRqcu0/CMGndHfSffw2T6fj3uRcoltMVNUp7ISeZt5hQmEiFkodMVDVKeSFvRmdJUnKkdUR1itOwUhoZNwOREO5DscTFbAK8/SJxkYjOjceh0BvMyJrGAdUoj/yZnS1anwppULOMFzJ72RN5efMmuK5uZGYrks0ZfB4RZaQjUJY0UnbWWpnG+0Ukdp30wfjVt2X97z8Nlw+Do50OyUnT9GauSdMnIiIMWzetQnBQAPoMGIMBQyagS4/BGDF2BvoOGI2UKVPDmwYMWzs79Ow7EhkyZIaJBhHEDBhCCJT57gcMGzUdbTr2RLNWnfFjlZoIDg4mc9hd6hMaxN2srKzwe71mGDpyKv5o0QGt2/dA0WKl8OjhfapDIIRQBU5cvNTzNxFQaGZ+9coFjBrWi1xvjB7eB2NG9MWwQd0wsG8HHNy/R/6zz31EWPr2aI3J44dg8oQh6NaxCXhgNNKA93quQgiEBAdh1vSxGNS3A+bPmYTF86dj1rQxNBC+UPvl64C957WZBP5pIi4D+rTD2JH9CM+xcuK0fs3SBHN49PAexeuPcSP7Y9H8qbJNx1G6Z0+9ZRsIIeDz/Cmm08SL23bOzPFyosTtFhkeBtYyjxraE+xmTh2NgX3aU/sPxfNnT6WW7gURJ560DR3YVfaZ0SP6YPSI3jh/7iSFx5dVCVZQ9Uw0CHw02WFNB5MO1n6ERhiw/fgzHLnsh/vPwnD4kh+W7nqIEkR2mlVOj2pETOxttNT5gPoV06Bp5XQomNUFJXK5o2fdrGjyUzrU+i41HdPidzraWmskAZEo0ViWlbRGVb7xxI/FPKmDgbQwLmheJR261c6CDjUyom7F1Gj8Q1p0rpUZKd1taHCNpUoyB7nLREQoLZmqwiKMOHYlAGFU54wp7ZEzvSOYAF24E4Q5W+/h+DV/XL4XjIDQaDDbMRFBi9KbZB5JfaeQ1sWHZsEXLpxG0eKlUKbcD9QeCmnD9HB0dEapshXhkcwTuXLnR8euA/BNyXKwsrKmtnzVHkIIeHqmhFeqNBLOyIhI0vJ4Uzwr0g6lpLjxsVZooEqTNj3c3JNRfEEEJ4gGE1+69oC9vQPFf5U3RVB/KgJvIGAyGZGT+mRvIuPS9R+FvgPHokixb4lkB8HJyZkI+iM5mNlRn+rZdwR69R0FDZlEli2ehcePH5DsUuLlK4TA4gXTsfPPTajwfVX0HzQeA4dORP1GreDg6ET9Ml509eI9EWAty8plc4lIBqNnv1E0oRqNVKnTYcHcyXhw746UN7FZCSHAmt90GTLJCdcQmhBV+qEajh75mzQ8B6Gh9osk8/kGMqfv2LYBVarWojaaJCdorFHWkWwKCwslWZSO5NVAmoDNQLESZbB31xaw6VxLJi19dDT8fH1Q6cdf0G/QWPTuPxp9yBUoVAzcr2Lroh4TPwLxn+APqC9xEGRMaSdTBIUZcOtxmCQHCqlwqA/CP0SPE9cCodMKZPSygyeRkExeDsic2h5RejOCww34vXxqpE5mg2d+UVi88xEuEcmwIaJDWVC+rwYxrUaBlU6BNTkKgIYi6LQKUpB5KSBUj3O3AqnjAdlI45MngxNHiee0ikLkypnMVxo89o3E7lM+YHObhkxnJfO60wMkSGNkonqZIOhPEiMyYfF9PPKNwBN/y3qTeJkmwQs2MQWQyjcwwA9Zs+cm3BQS6pZ2MhP7pZ9ExdbWDg4OjsQVWZlsCZcBMTsWILtJoEyeMBRd2jfErj83omatRsiUKWsCJgAyQQQGYM2qxRg7qh86t62Pu3duog5pe2QZsYXG5J2oD2rlPgsC3DednV1QsFBxiytcAtmy5yLTxBGk9EqDAoWLk3ZnN/xoFl+nfgsULloSRUuUQp0GzcGL6G9cu0z93PSy7goR8IcP7mHj+uVEmEqiXsMWyJ4zDzJmzoZ8BYrA1taW4r7Z78lT/b0DASEE7t6+SWbBS/j1t/oo8U0Z5MlXWJrJTUYjdu/aDA0RmNgsuF2zZM2J1u16omjxb5E5c3Z8W/o7SV59aVKmkNx//swbhw/tRdnvfkCLtt2onfJS2+dGfmonJjO5cuVDp24DUKpMBSLE+VDll1rUfvZkUn9IbR5bEpCBZBP3C+5D+QoWg6urO4WrbfwKocR/pnx0FQXgZK+TyVn7oTe+EgbsaSSNyFHS9ASH6cHaluxERAplc4ETmYUe+YQjJJz9rcEmpfUHn2DZnofoM+cqpq6/g7BIIxTq+JzPu9xjIiK9Z1/FlPV38YDy5LgezlYQgirHF+S4O7o5Wck3xXhd0J2nYVL79CIomgZjIE96J6Qk0sTaHaoyeH3Ob+VS0dEGgUSkVu3zRgjdQ5wsKdek+WNUIyLCERUZKbUq70LhrRyEgIw26HHj6iUcP3oAT54+gh2ZvF74+cD3ha8kUHHzpegIDwvDhbMn5OAUTKYDG1tbGoQeIoLqQY0dN7p6riLwVgR4cGQHCOz/axeYNFeo9DOSJUsh12XorHRInz6THMSMBgNy5MgDjVZL/fI5TaZeyTeNRqG0NxDg/wIZMmbF7ZvXJFm6deMqwkhTAHX7KASEUMAmcJ3OGhkzZZcaY37+PVN4wdrGlszctyEES6H42UdGhiOQJkRsruJ2jYqOQt58hajNjPB+9BBBgf7IQaTmzMkjOLBvJ65fvUjtFCbzEkSIODdLvwBYs6Q3RJOGOjmFc4jFcdsePvgXrhPx5clebHxLqLr/EhBQPrqSxCJYO8Lp2ezkToSCvPiShAVkR7nzJAwX7wbDirQw/EZViVxucvHyvafhiI42QaF+azCa4RsYBd743IfO3zpQcqQ4zjcwGs8CIsHpIqMswogJTZwooCKQPoUdUrrbSu9c6RzJ9JUJmbzsZVhyV2tkJSLGZXo4WaEZmdgKZHGBf3A0Fu54gDM3A6BwRWXqT7JLtIXwA25v7wgb0tz4+j4HEhA8+KeNgLYlwdWwSVtMnr4MU2Ysx8/VfpfanfWrF1tSx8mXy0zumQJdew3FlJnLMW7yAuTJWxAL5k3GeSJAGo1qN7eApu7fBwEhBHiw+nPbOhrQPFGu/A9yUAwLDYGTowu0Op2UX9zvnJxdqYsrYILP17H588QowN+P4pmxZeMq8NoSXu/RpX0jucbE309dsxOL1QcdSViHhgRDKApphi0masbdysoKrIWJCA+HQa+Pl6XJZMKxw/sxckgPdO/UBBvWLkHhIt8ge868MFNYUFAgQkNDsWr5PDJT9sHMaaPRp0dreYwItxAezlAIgXC6ZhOWR7IUyJ2noNQy63RWZF73wuEDezFp7CD06d4Kg/p2xMXzp2lc+Pjhk8tU3adF4KNby0z1vEtaEjrAxUEHJjO8UJkFgR2ZogpndYGdjRb7zvpKMpI7oyOyp3VAFJGcS3eD4BdCmhXKhMlJchdrUD8Hf0QwTTI7sB8FcdbvdJyG+qiMw/HZyYs4O4Ui5MrgKOvI2iY2fRXI4iz/ayxrcvjjhfyauxeZ2Vr/kgGl83qA1yDx/4raedKHBCGZYhLKOE4ZSeWUBYu7RzK4u3mAF+jxjIqFkELCidXLfIzFQlEEtamgS3LUBgo5IeicfJigONNAkiyZp5wZ8wUU68EAABAASURBVOzazS0Zbt64Aj3ZyDWKAo4jhCW+jgYgNzd3moF7kqq5AFglbabG42/uWGJQpupPReA9Ebh86Syu0eye13ewZob7NQ+qRhoc+RibDQ+6CnUwhXpyrJ88EmHX66MhhEDJb8uhR5/hGDRsCkqVqYTtW9fSs3ECFEVGVXfvjwBBTbiRvKVnm9skNqUQgrBWQDsIbhC82oQQSJbcE7nzFiBTVilkIlPipQtnsZ80OBqtDgbS0vD6ilKlK6K3fKFiIgqRGXPzhhVEWM6AZZYQQh7XrFyIM6eP4eeqtZCRNHZGoxEeHsnRvnMfDB89AwOGTkTtOk3Ab3LNnTleyiohBNTtv0bg38mfetDHZcR9jhfynr0ZBCYnFQsnw+iWudCpRmaMpGOfBtmQ2sMGV0izc49IEWt3dKThCSCT0JX7IfAhDU5IuEGuo6lZNhWaV8mAUS1zo92vGWBvq5Gd/uNq9ioVCxwHOy1ykqmK1w5tOfwUjUaewR+jz6L52LO4eCcIGrqRXOmcUL9iWpTI7QaNRoC1RKz56fBrJnT6LQuK53R7lWkSPuOBwNPTC8VLlsWp44cwdeII+aZDCM3Gbly/jIF9OuIsCQsmKgYyVUXro4gsGsmZEE2DAwsw9j998iiuXblAWj4j9BTn2tULCCRVc6pUaaS6+sb1K1i3egmZCfxothWOIwf3ybevuPzQkCBcuXweYWEhSJcuYxJuDfXWPwaBSDJ9HvhrJyLJHNugcSsaPwVpDXSwJVMqv12lj9aTH+csEBTgB5682Ts4kp9gT+mEENRPbaRfARo48+Yvgmw5cqF2vWbyMwpPnzwGD7C0U38fhIBZmsfNZiM936GEr0JOICoqiuRENBydnEk+a+PlKIQgolMQjZu2B78UMWDIRLi6uWPNqoXgD51aWdnA2toW33z7nXxxgtdWlSfTpZWVNW7evAIqQLpNG1ZixpRRKEGyrUatBtBZWYE3LU200qTNgExZslMb50bVX39HsW/K4Nat63hKJniFJmYcT3WJHwHlY6sohEB4pFGaei4RoYkkjQ1/Ofmn4p7InMpeLkAOjzIiiAjNhdvBMBFb57JuPQzFU79IuUB4w8EnCAjRy4XGv5X1QtbU9qRVMdLAaIaBzFt6g8U0ZaS0eoMZ7DgPvpbhNBPja1a8GI0mUjtyOvaxOBOxnRRu1shAZixef3P8WgCe+0fBNyAKD30icPiiH/jbQLxOhxdO82CqpzLdnXUoV9ADlYokQ4VCHsiRzoGeiVfCDkl401lZ4Zdf66B02UrYtmU1mjb8Ba2b/YYOrevh0qUzcHZxxYVzp9CzSwt07fAHHj64i7OnjqJz20aYPnmkHAP2/7UDXTo0RruWdaSbPWM8EZdMqPF7YxhoJnbw713g1z1v3LiM6OhIrFg2V8br1LoB2reqiz+3rsMPlWsgX6Gi1ObGJNwa6q1/CAJCCDx+SP3xzHGUr/gzUqVOS3LJRM82kCFDZupLBty+fVVmyYMYE3e+SJU6HQ2yGmnO4k8vsJ87zfiF4LU7N6nP6tmLzGMvQEXIAVt6qLsPQoDHiBQpUxGxMUgtr0ZrmfQ+uH9bktN8+YpQGxkRQeamqKhImTebtaKIDBmNRhhIE8Pyx8XFTZJOPWmJ3d09wNrnGzQZUxRLfsFk2uI1WW6koebj7j83kmwaId/Eat+pL5ycXV5Ots00xpjICSGoPEHyKBqRkRGwtbUhU5vzy3gUqP4SOQIfTXb4vrSkBbn2IATjVt3CrM33sObvx9hE2pMlux5hwurbktSYiKh4v4hABJEh4h7Yf/4FzejN1EmAbcefYfya21i1Lybd7kdYsfeR1Lis+sub8vOGgUjPtQfB5P8YmylvzoM1Msv3PJLfxSHFjHyNfOfJ51hBfuduBwDcLwEo1EGZTG089ASLdz7EdaqrTqdAUYT81xAHL77AUiqTTVYbiXgtpXov2vEQcR2Hn7oeSPVlSkWZJvEfE8K0pFHp1W+kfA3zx8q/onDRb9G4WXuMm7QAmTJlk8IiX4EiKE4zIJ5x1arzB52XRpasOWBlbQ2+bty0HTJmyorMWXLgj2btMHjEZKRLx4tDQUKnNFq07irzYnNX63Y9UK1GHXilToN8BYqiY7eB6NR1AOxs7dV2SeL98UNuX6PR4MD+PTTjD8Z3FSu/TMp9mk1QzjRIriVTxn7S/OzYth6rVsxHjpx5yeUhDWMYZs8YhwVzpiCAND7ZsuUCm0yYuO/euVl+hHDW9DHwSpUW2XPkhRDiZf7qyfshwO2QKXN2pCfiuXnjCuzdtRUHaOKzfs1S8Cctypb/ES98n2H+nMlgkxO3J39McA61yyFq13Onj8s35G7euIp8+QvDmUzlqdKkR9p0GbB102r8vfdPHD64F5s3rpTanwKFiuPC2ZOYO2uCJL38JteVS+dkuUcO/SVly0Uyia1ePl++yn6OSPK6VYtw7swJklFl4e6eTKZ7v7tTY31uBP4vssOV52fa+0Ukdpx4jiVEHOb/+QBr9z+W36phDQybrtKTZoXX4zzyDcfV+8EkCCAdE5njV/yxlEgKp1tNZOne03A8eB6O1X89xpYjT2WHu+0dhpVEgnadeg7erhJpYbJzgIiTQhXgN7r4I4acz3XSHMWKGQqSi5+ZTG079gysaYob5h+sl0SLSdru0z5Y/bf3G24N+bG5jstVnQUBFko8s/3hp1/RnEhJ2w69JIHJkDELuGHTEhni7400a9kZfxAJ+qN5B7Ro0w0/EDEy0SyJ1cI1ajVChy79yB7el9I2QTr5FgzPsgVy5SmA30jLwwJOCAH+RkqDxm3QiUhOGyqr8s814e6RTPYNqJuKwHsgoCgKkZwQnDpxSC4+zZUnn9QScFLuk2ym6NpjMPz8XmDk0F7gzyLw96Cateoi14RER0fhDGkor1w+TzP7SCT3TEn9cQBYnkwYPVB+zC4wIIBIejdkzppd7ZsM7Ee45J4pUL9RS2g1OmqHnuCPP+r1esJ6INzc3Mm8FYZzZ0+Q5ucqhBCktdHhJJnURw7rhf6922HdqsVygXKDP9rAZDYhefIUqF23KbWHidqoK+XZC2HhoejQtT9p9tLh7t1b8HvhCz1pgZYsmGH54OTIvmSiH0b9w0DlhWDLplUYMqALBvRpj43rl0uTGE/WOP+PuEU1yWdCQPk3yqU+Rx0P1DnMZGoyUceCvGYtjIu9DvkyOUOjCBy/HEDkI1pqXEAbCwpOayLtD5uP+F1wvqagN36v61Vev34jQRyPt8WNLSs2nK/f5uJkp54SAkx4zCRMhBDgGRY3upkbHJaNzxNyHMr+bM/SanVSWPE1Ow5LyMWGsf2cy+JrdgnFVf1UBBJCwEQk25q0iiPGziIt4hS4unpQl4198kHaXgU/V6uNhcu3Yta8tVi4bCsmz1yOPHkLwkTyibUEU2etwJiJ88GLVo1Goxz05i7aiBlz12Duwg1YuHwbKlSqIvt0QnVQ/f4ZAUXR4NvS5TFn0QbMXbwJMwlbxp3X3JioDfljpBOmLkafAWNgMBjA39eZvWA9tcFqjBo/B0vX7AJ/XDBd+syyfRUiufxCw4KlWynOGsycR47yLPfdj9SuRlT55Tds3nkcW3adwMr1+7Bqw19Ys3G/LJvlU4mSZTCP6jF5xjJq+3lYumonabRHkQYvjcz/n+/oy44hhCD5rpV9mvFgp5HfOhJ428aY63RWsLKygoa0qW+L96n9/xWy87ZKE04ICtdj6sa76DX7KtYe8Kabf1ts1V9FIPEgoNbk60OAhTCv07C3d0jw5ngwtbd3RPqMmZGcNDcs2OOSav6QnKOjI03kLIKe49tRXpmyZEOqNOlgY2MDdbafILQf5MlzJhsbW6RNmwFp02eENeFqpokVZ8Jt6OziCltbW76Ujr+7lZ5MX7lJI8ymJY7DkykZSDszZWjv4EAatxxgrbO1tc1LosKDMn/93cnJRZrfeb2OdE7OlBLU1grsHZ2QhUzwOXPlg4urG/mJl+nxlW/8iQX+6OtqMunGus1kYgzw5/VplucgLgShoSE4cfwgmQbHY+qkEdi7eysCA/3jRvls5/8p2eG7itabcO5mIE5c80dASLTsKOyvOhUBFQEVgU+NAA987yqTw5nE8PH1eOzH7nX/2PgJhb0eV71+PwQYS8aVHTGL+ImIvMT3IGpDfhyX070extfs/7ZwDkvIcTrpYvJ+W3oZ5yvcCSFw5/YNTJk4DGtXLcK2LWuwdfNq+U00Pz+fN8dywmnLhpUYPayP/C7R4QN7yHTYDfNnT5Jr3oA3yRE+4fafkx2+F42GbKvkhPi8N8t1+XedmpuKgIqAioCKgIrA14mA0Wgga4xGvtY/ctxssOs/eALSkZnQRGbFuHdtpou0pImT3yUaMwtDR01Hrtz5wQv+n3g/pHw+Cd2gWiT8+7ylJ1wn1fczI8CUVHWQ85CkigNoS6r3rt434vV9xGwqLoiHy6fEA59rIwYjFAUpvFIhTZoMSJ0mPVKkTAX+0OvrVRJCoFSZiihb/ieK44V0GTIhT97CUqsTHhYGIRix11N9umuV7Hw6rBN1SfwZAe6KTg5WyJrBBdkyuqouiWKQJqUjdFoNknvYI3smN7UfJNF+kD2TK1Imt4eVToM0KR2oL6gy4VPLRW4DL097KIr4POMHFcvfItq+eQ1WLpsL/gaa9+MHZFkkFpRAjaQ5MEbjo4+Kxt27N+WX73kt1euaoASS/6deyn+au5r5F4MAmVtf1ZUZuOpAU5Gk6UASDrDs1X5AQBAeSRYHWLZ/9/4BNb/3xkAI7n/4LJurmzvyFygiX/Xfu3sbRg7tKV/xv3zxHBEwzVvrxG9hHTu6HxfOncQ335aDZwovqGTnrXCpAZ8SAf4mEnN1g8GEkNBo1SVhDMIjDTAR+42MMiI4JFrtC0m4L0REGWRfiIjQq/3gM/QDfv4i6HkkVcqnHA5kWaylyZAhCzr3GIwhI6dh2KhpaN2uJ54/e4pNG5bDQl6IiMnYr3aKosGVyxcwefxQpEqdDj9X+x06K6tXET7TmarZ+UzAJ9pimfHQQMcdXXVmkjFJz9FNy+5Jd06ntP9c/UEt97Pjz98+Y0dN8dnrkhTlEQh8KZLlE/npd1qdDi4ubuRckSx5CpQgLU2atBlw/84tREaEkXZHgNf0xNaMic7D+3cwuF9HhIeFol3HPuAv5XPbxcb5XEeV7Hwu5NVyVQRUBFQEVARUBBIxAlGRkYiOjqIaWiY9vj7PERjgh5Sp0sDWzp4ITRi8Hz1AVGQEWSaF/F+I40b1xws/HwwYMgH8b4OMBtIOxqzjoYw+208lO58N+i+7YCEENBqt7ODM2oXgaw1e34QQr3vJNBqNRs4UWRUqhKAZwvt1RSHeyA/qpiKgIqAioCLw7yJgMhqxdfMaTBo3BBvWLpP/j2z65BEIDQ1Ghe9/hobk/9HDf2Nw/844d+4kyXWF4iwAr9VJlSotblw/X7fYAAAQAElEQVS/jHmzJmLe7Ek4fmT/e8v4f/cuXuX2fiPMq/jqmYqA7LTR0dE4cewIFi2Yi0kTRmPt6hW4f/+eDIuFSKvV4uKF85gzazoOH9pP3mZyQEREBI4eOYSpUyZi9MihWLl8KZ54P6aH5d1EhgnSsaNHMHf2dJw9czpeWTJjdaci8AEICCHAfVSIN/sdq+Y5jJ0Q8cMVRQH3xbhOiPhxPqAaatQEEBBCQEPyg/FnvPGeG6fR0EQKSLg9OIwd4mxCCNmeOjLZcJgQCaflenB92PE5vvKN75H/B+Hjxw+waf0KbN+6FjY2dujYdSBKfvsd+Bs8OisdHBwcYWNtC5PZBP5Hz/y/DXU6Kxw/egD8j1pPnjiEe/duQYiEcf1UMCYdsvOpEP3KyxFCICQkBOPGjkSd2tXRr18PTJ40Dl06t0X9OjVw985tSUL4QQkjm+2gQX0wZHBfrFuzih4OE6FjxpbNG9CiWUPMmjEZa1YvR/duHdC3d3dSl0ZTeMI/zs/Pzw9dOrXB4EF9sW3rRigaTcKRVV8VgXcgIISAlZUVfHx8sHfPLvj6+lLsV4KY+5ovhW3ZvBHbt22R4exHkagPG3H71i0cOXxIusOHDhJxP4wnT7wRG4fjqe7jEWDCERYWhgN/78WG9Wvx4F78SdTbcmYN8zGaRJ04dhRRUZEJRjtz+hRNvA7QhCtchnObhYeH49DB/ViyeL4M42shFBnOO44jhCBNxTVsWLcG69auwsOHDyDEqz7D8b46R/f3XYWfMGnaUkybtRIz5q7G2EnzUL5SFbngmPH+tnQFjJu8AAUKFQOp6tG+cz8sWr5N/j+xuYs30nEjFizdgvqNWsln53NipHzOwtWyvzwEjKTaXLd2JZYtWYBy5SvgwMGTuHD5DpYsW4tMWbIgKDhICgEz3dr8ubNx8fxZuLq6wShttgJE/unaFb36DMTJ05ewb/9x1KpdB0ePHsLFC+fkTJuSxvsJISQRGjViEIKCAmFvbw9+0L5yURMPA/Xi30PA398fixfNx/cVSqF92+Y4d/YUlJjvmLDGctnShfihUmn0JyLfq0cnVK/6PXbt3C5n/wEB/kTMu6F+3Rpo1aKRdC2aN8SmjetgbW0Ndfv/EDCTgPjrrz346YeyaNO6GYbQZKnqzxUxc/pkKVfeljsTpCWLFqBWzZ/Rtk1TeD9+FC8+h+/ZvRO/VvsJLVs0xtUrl8FaoGvXrqBBvZrUjo0xZtRwOv8NbVtTeu9H1CcUmcfDBw/QqUNrVP7xOwwfPhAjRwxGZ7o2m8wyHF/o9j7VNpvNhIOAs6sraXCcpNyl3cukQgiJAcdjTzPJeV6a8LqLDec4n8spn6tgtdwvDwEhBPz8XuDP7VuROUtWjBw1AVmzZYeLiwvKV6iEKVNmI2fO3PQsmHHh3BnMmT0Nv9aojUKFir68WUGDSoWKP6B+g8bgbzi4u7shY8bMciDhgUYI8TJu3JP9f1lmeX80aYEsWbPLMuKGq+cqAu+DQGRkJBbOn4OlRNYzZ80q+1GsIBZC4NbNG5g7ZwaKFC2ORYtXYPLUmfDwSIbpUychODiYijBBr49G1V9+xbwFizFzziLMIvdLtRqkTeCFnBRF/X00As+fPcOcWdNgZ2ePmbMXYM68xSjxzbeYPm0SaVauQ1E0b+StIQ0vk5fZs6bAzc0dPNDGtilHVhQFjx49JG30CNg72ENL8TkOS5qIsHDkL1AI4yZMw/yFy/BrzVo4sP8vqelhc1UYaafnzZuJQ2SG79V7ABYuXknxlqNrj96AMMv+gySwMZ7svuRbVcnOl9x6n7juLDT4GwuPHt4nm21pJEueHAaDQT7wrPFxdHKS5gHWvsyfNxtu7u5o1rw1bGxt3qjps6dPcOXKJez4cyv+JJc9Ry7kzJVb5hc3shACz58/w6JFc4k0FUHt338nYqR227gYqefvj4AQAnnz5seo0ePRsGGTeAm5f587dxphoaH444/mKFioCMqULY8fK1fBzZvXcfHieRooAUGEPVPmzCj3XQWULfsdSpUqg9Sp08hBFl/d9uluSAhBON/A7du3ULdeQ3xXvhKKFvsGNX/7XWK7ffsW0vzGJztCCGqvMCJDEylMR5OrWuB2jK21EILIqR4sj1jm/FarLmxt7QAz/UhrkSt3XnTr1hvf//ATlVUc1arXhK2dLTgu5/Hg/j0cJPJTs+bvaNm6DQoQMWJXsmRpCma6RAf190UgoI4aX0QzJY5KshDx8/NDYFAQ0qRJJ0lO3Jox82fHi4gP7N8HngmlTpNaCqrYeEKwcArFuDEj8OsvP5H6+A8weapfvxHc3DzeyNNEAmnXju00476JHr36w9klRpUam6F6VBH4AATY1FTx+x9oYPtGDo5xkwohcPfuHaRI4QWvVKmJeBtJRa8gXfqMcgD1ef6UrkH92Uz98QZ27tiJSxcvgNewCaEOfHGx/JhzIQTJgodQhAY5c9DER6+X8iBVqrQ0YbLFnds3CP/4OAshsJ9kzb69u9Ghc3fS+maTaWLLF0LgLJkpN6xfjRYt2qFgwcIy3BwTgRfY2tjaSj8jmaWCAgIRFRkFN9LmCSHg7f0Yvr4+yJ+/IE6eOIFtWzfj+vVrcv2JEPHrEpOlekikCKhkJ5E2TGKsFvEOKfQVesgt316IX0shBPyJDC1fugiFixRD8RLf0kAQDKPBSM6AiMhwGI0mKbiqk3mrd7+BaNehK/hT4kMG98O+vbtoANK+zJTJ1cMH97Fm9QpUqPA9cubMTvmFyDz0pFGKiAgBz9BeJlBPPhsCX1LBTMhjXdx6CyEQ4O8nZ/bWVq/W39iRJoBNGkFBwVA0WiQnjeaRwwfRsX0rVP/lB+l4oTObU+Lmp55/GAJCCAQFB0LQqGTn4CAJCLeTtbUVrHQ6qcGJjtbHy/QpaYiXL1tEsqYkatWqQ7LBSOkoihCSGAUEBGDRgnnIkCETmjRvQQGWHwVbTmL2QtAkLCQE64kUpU6TBkVJfrHWOigwkMyXQejRvSOaN2sIXsNV+YdyGNivl1xHKISIyUE9JHYEqFsl9iqq9UssCLCd293dA87OLrh54/ob1bKy0uHGjWs4d/4MHj9+iEH9e2HwwH5S/X+GZldDB/YFLxy0sbGRZrDGjZujZ+++6NmrnxRM/MaWnmZzQggw0eEB5tLF87h8+QJu3LxGgqYrhg0ZAlYtHzr4N50PRmhYqEwLdVMR+BcQEEKhAdMEk9lkGTTj5Mlkxtk5OWksB2LpinVYunwtBg4eAV4HNG7sCDkocr+Nk0Q9/UAEmDqYScNioslM3KRmumD8FYVj0EXMj0kmT4gak9nRYIiWBIQJEr+NxROrQwf+li8+NP6jGWxsrEhrE0ntapbxDEaDzEUIIU1d8+bMwNkzp1CnTkNkzJSZ+oGR/A3QEfGtS5rn5SvWYtHS1fjxp5+xes0K0vQcjzc5k5mpu0SLgEp2Em3TJL6KmWkASOnlJVXF+/btxqkTx8HfpmBSQhIEx44dgcFoRD2yt7Nmx87BHvb2DlIgaBQN7BwcIEhYhQSHkBCJlgMKq6xd3dxIoFiRksYMIYR8LZRf5Y2Ojka6dOnRoGET5MiRC/aOjrCnGZ9Go0Cn1clzIeILP6ibisBHIsCaS2cnZ/Ci1MiICOqLnJFAaKilv7q4uIL7e4aMGZErVx7kzpMXNWrWRvnyFXHt6mXSCvlTGrU/Mmof6xzpGTeZjKThCYJQFIlnRGQE9CQLXFxdoSHNmhBC+pupwTauXwOe8GzYsAZ9e/fA5k3rERDgj4njR+Pvv/Zgz+4d8A/ww949O9GnV3esWbMcL174gl+e2Lh+LTQaDQwGvXztfNasqfipclXU+r2uXHvI98ATM2srK5QrVwF58haQZrAKFb8Hy7v79+9CIVnE8VSX+BFQEn8V1RomFgRYuLi6uqEmqYvDw8LQuNHv8ps3C+bNRquWTVCnVnUSAkYMHDQUo0ZPlG7w0CHIl6+AfLtl8JChcHfzwLCh/dG2VVPs3vkntm/dgnFjRuLZs6dgIaLRKli9chnq/f4rTp08jkKFi2LEqPEYOXqCzG9A/75Inz4jypT9DgNIaxT7GnpiwUitR+JHQAhBgxw7y2JXIfhcofHLhPQZMkrNIS+K1xKh5oGXtZjW1jbInDkLeGPCw0d+HhQakKNoIGZSr7OyYm/VfSQCrDlOkyYdTXYicP3aVdhY6ySpuXvnDhHQMBQrUVK2EZuXOC4XwxoYr5SpcOfWTVy5fBFPvL3BWh1uMzapp0mXDpkyZsb9e3cp/BIeP3oYE34Dz589kfnxd3PGjRlBhKYi+vYfgmTJPKl/aGTZbu5uVIzZspZI0dCEDODv8BhpUufo6ETyjoLV3xeBQKIkO18Eckm4kj/+WIUIyATw6+ebN67D1CnjcZPMTM1atEaBgkURFW2g2ZLFmYwa+eoum79YM60j+3vuPPlw585t9OjWEb17d8ELXx/06jUAv1SrCX2UnpAVNLOyhsLChWZvLNxinQnW8PRMCWdnV+j1Woqr/lQE3h8BHiS57x06eAhXrlykPhRNWpkrOHbkCIKCglCwcBFwX+VXnU+eOIotm9ZLbUFxGmjz5M2H46S9nDRhLI4cOojLly5i3pyZ2LPrT3xXvhKSJ/cE5//+tVFjxkWAySN/ViJHztxYsmQ+tm3ZAl54PH/eLPnm548/VJYfbxzQrycmTxwLrVaLCZOmY+eeA9ix+wB27T2ETl26I2VKLyxZtga169QjE3l/GRYb3qfvYKRJkxbTZ8ynuD1x6OABymscaaDtUbHSjzh29DD+3L6FtEJ7ZVumT58JOXLkxtw50/D3vj1ygsbfGEtLGufixb+h/qOPewvqeSJGQEnEdVOrlkgRYCFT5edqWLRkFVat2YxlK9Zh5epN6Na9D1gNzUILMZudnR0JlR5o264TkRcF/I2LWrXrYtnK9VhM9u8lS9fI8xat2tBsSoGi0UjTwIJFK0gjlP8NYeLk5Iyhw8egUeOmZFM3QN1UBD4EgWjSwrD5om+fbvhz2xYk90yBzZs3YMiQfrh54xoNbLnQuk0H+Pv7oWvn9mDSw4Nvx07dSAtgRiSZVP76azf69u2Gjh1agj+wWap0ObRr31kOvnH7/ofUS41rQSBFipRo2aqdnNAMHdIfw8ixKWnosDFwdnEB/6sZ1gKz5o1TGGgGxev8Yh1r2NKmzSC1Mkw8WQMTG8Ztb0vyKG3a9GQ215H8MEqNsp29PRzIfDZj+iSMHD4Io0YOAf8LHM47VerUaNykOWxt7dG7VxcZznH7kQbIK1UqSYi4Hv+xU7P/FxBQyc6/AGJSy8Ii0M3gD3hlItU+DwYpaTYlhCIHhLh4sN2dv8fjkSzZS28mSylSpEDefPnJDp4PnDZWi8OR+Hs9LGS0Oh1fxnMKmQ143RCv87HUI16weqEi8E4EeP1F3foNMGnKDEybORfzFi7DdDqOGz8Z2bLnlGtyyG1LAAAAEABJREFU2Ew7feY8jBw1DuMnTpfkmsN40CxEZtUJ5Ddy1ATw4uSp0+diwKBhch0bD6zvLFwN/EcEFI0GZcp9h4mTZ8gP/Y0ZOxkTSXtTukxZSU5YVvQbMBQdO3d/g2iwPChNxHP02IlIQfKIr+MWyNe8lnDo8LFSK83tVaFCJcycPR+z5izElOmzMXXGHNkfRo+dJMkry6ofSJM9ZdpsjBozEWPGTZbapLLlykvtddz81fPEjYBKdhJ3+yTq2vHMKa57mwGbhQy72Jvh87jp+Dw2jI+x4XyekOP4HCehMNVPReBdCDD5TpkyFdg0kT17LmTPllOeZ6Pz2PVf/H+z0qXLgBIlS0ky7ubG6zYsuXJYmrTpUIxMGKVKlUX2HDnB2kZL6GfefxXFm6Eh87WXVyoUIpNiQXKepO3hiRTfno4mQBkzZpITpNdlAF+7uLpKIsPtxPFfd05OTkRMs5KmxlZOzJxdXJE1aw5wX+A+EevYnCaEkHGY8KRNlx7fUH/gD02yGV0I8XrW6nUiR0BJ5PVTq6cioCKgIvCvI8AD4+subiEc9i5SzeGxLm469fzfQSAWWz6+niP7sXvd/32vX0/L1wm51/N7V394Pa56nfgQeCfZMVN9zbSjn1yFrh4tuouvDwcztS/fFTW4+vvaEVDvT0VARUBFIMkh8E6yo6FQK62ATqO6rxsDRbbxS8UsnbCWVnVAUsQA1P6I2ZLi/av3DMRigDhbrJ96xEt8/mssELPxIynLgoAQqhPiPTCAIPTY0YF+RGdo/5bfj0U9MfiPHBjQMLvqvmIMBjbKji6/ZYG1ToGOnJODNZxUh6SKg72tDgoJE1trHZwdrZMsDkm1/ePet52tFooiwH0irr96/mmeC37+7Gy0AD2PHq62yJDWCRlSO6ruHzDImMYRXp720JCiBjGbEnNM8ODiqEM6Tzuk8bRV3VeOQapkNhAk1BLsCKpn0kRAqKbNpNnwr+6alzHIq1cTZHmp7j4tAgy/TqvAxkoLa9W9FwZWOg0E/cW21DvJzqZDT9Fp2iV0n3H5bU71/wqw6Ub3MHjRdURGGxESpsedh0G4/SBQdUkUA+/noTAYTXjhH4Fb99V+kGSfBWr75y/CoTcY8YT6hNoXPs+z8OxFGIwmM577havP4wfI5EdPQ6Qcey+yExppgE9gFHyDolX3VWMQBb9gPXgWZ6JdtN5EAk51ekPSwyCa7pmJDr+dwkc9DXRJEQf1nk2Ipr5gNJqlXDDQUcXE9B5y8d+Nw7LYYCANK/24LaL1xk9ehy+x3S24mYjnEHC05987NTusAhICUN1XjgEEuI0Rs8U9j/FSD0kEAZFE7lO9TRWBLxEBVTZ/QKu9JszeSXbeJ1sGnxcBvb7cg6+1tOPFbZxPbDyOG9cpFMB10igi3mIi0MZ+Wo2QAzHPNDkvrUYB2y41FB8JbIL8uFxOx/HpUv39RwgIwV9MNoH/WSLzZyEY/VeFCWH5KBe33Stfy5kQglSzRvlVVA4XIn5aSyzLXghLmNFoiQ9waZYwda8i8CUioNZZRUBF4NMi8NFkh6wd8u2dn79JiT9+TIcaZVLBzVEnVZ5MMormcEOzKulRIpcbmHiUyOWORj+kQ+M4rslP6VA0hyuSuVijTvnUaPpTeqRws6bB04z0KezQ6Pu04Di50jshaxpH1CqXCh1rZETHmpkor7TImd4RQlgGQoaN65QmuS0aU74tfs6AysU8JYFifw5X3b+DgBAC4WGhOHH0AFYum4+5syZi0/rluHP7hixACCHb5f6921i7aiGOHf4bBv2rf5gXRmmPHtmPRfOmYdb0Mdi4bhkePbwn08gMXtvxPwrds3ML5lE5c2aOx64dmxEY4PfW+K8lVy9VBF5DQEBRFOmEEOBNCCH7kxBvHjn8bU4IEZPPR4tSqFvCCAghYrAVeJ9NCCHbMKG4QoiYvN7eTtwnBPULJLAJIWR6GYfOoW5fHAJvb/l/uBWejTs76FCvYhrUKO2FBpXSoFopL0l2NKR1KZjVBVW/TYniOd1ga61BmbweMl6NMl6oGeM4XZHsLkjuao0fiZhUp/heHrZwstehVtlUqFnWCxUKJUM6Ij6cf/0KafADxfu+SHL8RuSqa60syJzKgTQElpm+wWhCxSKespxfSqZAox/TwsvNhupkCf+HW1KD3wMBIQT8Xvhg1rQxGNSvIzZvWI4jB/dh0dypGNC7HZjgRESEY9vmtejXqy2mTRqJA3/vgl4fLXPnfnPgr52YPH4IThw7iEsXzkgSM2XCUISFhr4hrKKjo7CGCNOcWRNw+dJZHCeCNWnsYKxaPh9mk+mN+LKQr2an3si/jYBCg5nJZEQAkWVfn2eIioyUfchgMEgCzyQ+ngsPo8mXKYFqCGh1OnBff+H7HMHBATSx0lA8QU79/T8ICCEklmGhIfD3fyG1v9xueMemKBpwG4aEBL/WXoLy0lI7RcDX5ylCgoPALSQE7yE3hfoEnwRQWcFBgXQqIISgo+Wn0WigN+hJ7vnCz89XlhObxhJD3X8JCHw82aG7U6hD2ForUnNjS4TmJyIiWdJYyIeWnnuF+ouGdgICOh05Mkl5+0Zg0to7mLyOHB13nvShziiINQvLUQDfkDaoRG43sLlq1ykfXHsQAg9nK1x9EIylux7i5qNQaLUCaT1tUTirMxSqh8lkBpOvYqQp0lI5iiLgTKSpGOWlUh38axsPFLtJy7KBNDnfliqPmfPWYf7SLRgzcS6y58yL6KgonDh+CLOmj0amzNnh7pEMkVGRrwxPpGZL6ZUG7Tv1wYy5qzFx2lJ8V7EKTp08iuvXLlEf0MarqxACOXPlw6ChEzF55nKMm7QAmbLkkAQqIMAfQlCHiZdCvVARSBgBjUaLu3duYvTw3mjb4ne0bFITI4f2xNMnj7GbtIXtW9dDp/aNXrquHf/AwD4dcP7cScowfj/j52D7lnXo2uEPtGpaEx0o7eIF0xEdHan2SULrY39CKAilSc/CuVPQoU19tG1eG6OG9sKjR/fApOP1fIUQNBZo8eTJQwwb1A0jh/TAE+9HEMLSXjzJ2r1jE3p2boYWTWqgU7uGWL1yIbVTlMxKCAGeoI0a1gttqE90bFMPi+ZPRTiRXCEseVy5dA5D+ndB6+a/Scf9h8tQlI8ePmXZ6u7TIvCvtBaNX1K7wmSjJml57Ij4sF+8W4lhHL6BUdh2/Cm2HXuKLUefEZEJhqVLgRg5m6/sUT0mj+NX/LF09yM88onAqOU30X/+Nczf/gBbKV1ElFFmb0NlcZ8kroMCmV3AZqyAED18AqLAdShJZMfBVivPZYKvcPepbkkIAX+/F9i3ZztyErHp3HMwkiX3hE6nQ87cBdBv0FhkzpoDGTNmwagJc9Gr30i4urrDTBqY2DoKEhCFinyDst/9INPZWNvA0zMFNIpC7c8z6JiOEpNAp7PCdxUqI1+BIjKOg6MjPDw8KK4RZjPHj4moHlQE3oGAomhw784N9OneSmoUs2XLhTLffS9T8MBmZWUFa+qL1lbWYGdjbUuD4B2cO3sCQUyqX9F1aIg03bh+mbSWw0CdEAUKFkdkZAQmjh2ErZtWk1f8PiwLUXfvhUBERBgWzJmERQumwcnJBVmz5cbhQ3sxoFd7sPlbiNjRwpJdFE2utm9dhw6t6hFh3YRrNGEKCwuBEEK6e0Ruly+ZTQQqGDly5ENgwAtMnzwSO//cCG5zJrqjh/fBwb93IwvJLpZXC+dNoTpMhkIyiUnN+NEDcYomcPkLFEWePIXw974dGDe6v9rOlib4YvbKv1HT4HA97j0Jg8Folmtw8mVyemu2Xu42aFghLRpWTCtNVbbWRERiYwvgZzI/ZUxph1veYZi77T4iidTwq2/3n0fI78DYWGnkuh6dVpHl3XsaRmpOs1w/9A1pg6h/4uLdYBy84Ac9mbVSetgga2oHElWqAIqF+WOPQijwIdX/82feKFSkJOzsSYtntJBOo9EAQeEsINKmy4h8+QpLYWCKQ3RiyzWQSvjB/bu4evk8Eadt2Ld3O7LlyC2dMSa/2Lh8jCSz2O1bN8iMdU4OJpdoplWiZDm4EJFKKH9OozoVgbgIGKl/ziTTa3h4OAYMmYBBwyejS/dB6D94AtJnyIwK3/+M6XNWYcrM5Zg6ayWGj5mBFCm8kNIrNQ24uQAaPBGzmcgMliJFKspnIsZPWYSBwyZRXkOgIXPH1SvnX5rGYqKrh/dEQAiBRw/u4fDBvaj4/S+k9V1M2E5E/UatcPPmVRw9/BcUjSZebkGBATh76hi+/6k6ypOGWID+KB+OZKbZbjKaSLXr1BeTZizD6Alz0L33cPCEidOA4p4+dURq+zp06UdtPov6xRR8W7oCmECxCY01Rvfu3UKTFh0xePgUdO0xGMWKl8KtG1cRFBQInrxB3RIbAgnW518hO6ERRuw7+wJMeuxtNShfKLlcd0MM441CUxLZqf99GtSrlAZ8tLFSaFC0RNOQ6YnJkELHR0RunviRSpjOOZQPrL3hRcnlCiSTprNL94Jx5lYQqM/C080G+TM7IyrahHO3ArH/vK88Z61O7oxOYHIEdfu/EBDUCMFBAWBbumdKL5i5QeLkyMKFL/loJKLJ59w28hi7EwJRZNbasHYpBvfvjFHDe+P+3dsoTOTJnsgTp42NykchhLSTz505HoP7dcK0ySMQHRkJnmXx4MJxVKci8C4EFEUBE/SD+3ej+DdlwObWAH8/8HobnbUVODxuv1Oon586flCSax74vFKnRdxwPnd1c0eJb8rC0cmJxJwZrE1gf9ZGaLXad1VHDXsLAkIIMLEIDwtF6bIVoSEcNURu8uUvApYNJ08chkaJT3ZcXF3RpGUnNGvVWRJTmXWcea0rTYgKFSlBWiJn8Joej2SesLW1l9EEtfP1q5eQLFlyFCn2LQz6aEmE8tJEjdf23Ll1HQ72jnBwcADH8/PzlSYyb++HSJM2A/k7xusXMlN1l2gR+FfIjqDbu3o/GIdJm6KhDpSHyAVrU6jvUkj832PfSExedxdTNpBbdwfhpLmJjWekwZPX9HCKIjlckTOdE2ltLKYKA2mNmCi1r5EJrK15TmaquVvvIygkWo6nrE1yttdxUqRwtUH2tI7gAGudglzpHeFIpiyo2/+FALezQsKGhYQ+mnD/mH8nQLMtKysbVK76G7r0GIROXQeAZ9aLF07Hgb92kf3d0oaxFeUBxM3dA/Ubt0S3nkPQsnVXaMiMMGXSCHg/fgCuT2xc9agikBACQgg8enhfkps7t6+je6cmaPHHr2jfsg52bl9PJlGLjIlNGx4WJjWIikbB9z9Wg0YTf4DleEIIPHvqjQ1rl2HK+KGYNG4wkif3ws/VfofOykodBBmkD3WEqT+ZybVaHTySpYCJtLwkLuDg6ASdzkqa0E2vaYrZ39MzpTQ9mt5i1mYZwk5RFNy8cYUmTz7Iki0nBA0QQTR5Yw2xNZkwZRyhwN0jOVVsM8cAABAASURBVJho+fo+R+YsOVCJ+sDuXZvRvlVd9O3ZFtw/WrbtTrJKK82YH3qbavzPg8C/Qna46gYiKusOPsFz/yi4OOjgReYjhYgPh8V1zwMiseXYU2w98hR7zvhAbzBTl7PE4I69+cgz3HgUCmd7LVr+nB7uTtagrMGvovdtkE0en/tHYs6W+7j+MARCCNgTkcmbyZkeCAEbMnPV+s4LbaoT8+Z/oEZZp/W0Azs6VX//BwIsaFxc3eDo6AweNLi9hGAKBNkOQljOQVucU7oCXoWABIkGmck+XrJUBfxaqwE6du0PBwcn7NqxSS4cFCRwhBCI3VgQ5aHZVskyFdCwaTs0bNIWPmRKO370IBLqY7Hp1KOKACMghCDNS6gkII8f3oerqwcKFi4BXuA+ftRAHDm0j6NJJ4TAhfOncPXqRVT7tR7Spc8k08nAODseOG/fuQ5ezLptyxrwG4oZMmUh7YCeJmgW026c6OrpeyDATzxr28ykK9ORVseSxCzJJpMPg56wNRgs3h+45/Z69vQJ1q1ehIyZspHJ62e5CDkyIlKSllhzlBCCxhEdFDrym3rWtrakZfoeyYlQ3b97iwjuY6RJlwEuLq4J9osPrJYa/RMi8K+RHR50HvlEYtuxZ2AtzNvugTUs+TI6Iy85PqZwtaaubYmtUQRYs7Pj+HOEhBvAb3bVLpcKqZPZgF89z5bGgfI24dKdYPC/suAFyVnJLxWFZ0hpJzvomZuB2Hb0uXT8JldEtBEeTlakJXIE9V9LQer+oxDgmU9yTy9kyZoTx47sx6kTh+Qr5UyC+JXPU6Rm9vV5BqEosk05PkkEWZaZ9kIIujTJgSEowJ/aUi8HB04vBAkZKx04bXBwAPgNiejoKLDq2ef5M4SGBMNIgk5PGiWaThHJUWBlZU25qj8VgXcjwKRcQ9oZIQRqELkeMnIq+g+ZgN79R1M/Ncu1Y9zPOJeIiAhJflirUK1GPR4Iqc9y7+XQV85IWof8BYph4rQl0rXv3I/MXmcxddJwvCCNgBDiVWT17L0RsLGxlXjzgm9LIgHGmtvD1s4WWp3W4v0Be4Xkka+vDyaNHwSWJXUbtCTykkKSKGsba0SSWZxlEGfJMotlDGuJHEmjdPP6ZUwaNwjJk6cA95uWbbvh7u0bGDGkB1jzw3lzOtUlfgT+L7LDz7MQloea99SnsO+Mr3w1PPbWZTAHsiPP9Cnt0bNuFvSIcVVLpoSJVTcUBhI9JpJMhy/5yXU33PHKF0qGX0t5IWd6J2iIDLHjb/h0qpkJ3X/PjFZVM6BAFhckd7FGeJQJS3Y9xLSNdzBj810yl93G7cdh0GgECmR1hrVOQw+SLEjdfQQC3B5OTs6o8kstajMThg3qjgljBmHurAkYTudDB3aTNu0nZF5au2oRVi6bh2fPnuLunZtYsXQO/tr7J5EbA9ZRGL/yu2b5AqxYMgfz50ySJobyFStDEQr27dqGIQO6gN94YZIzfcpITKRy1q9egkXzpmLNyoVg0lWgUDGqx5sD0UfcmprkK0aANQXONBMHhCTPCgklXiSfKnU6uRYkKiqK5IIZQghw3+XvPxX7pgz4kwexJIgCSY5opANtCgk7e3t7ZMiYFTly5kXtek2RO29BMpfdAxN+iqL+PhABli+8FiqaJjnPnz8Fa3OoSRBIE6OoqEikTpOBmkGAsWeHOJsQAiLmWgg+YwcIodDkyhfTiIQe2r8XTVt0RJmyFcHp2Tk6OiPA/wUi5KvmipQnz0hrzOQqVZr0OHL4L9merdv1RJly36NWnSZEmBviyqVzOHfmBNjkBnX7IhBQ/p9a6g0m+AZEISTCAP7HW9zHXgRFYeOhJ3jwPAKBoXrc9g5DRJSRNDaR8AuORhjFtbPWgJ2DLZEPqkBktAmBIdHwC9FTuBEcb+Php3joEwHmQWwWk+GUnl8rpySw0irQkWMi40DmKiNFPH3dH3eehMFoAs0GzOB89xD5CgozENFRYG/D5Zmhbh+PgBACpcicNHj4ZKQnFf+enZuxikjNgwd30KRFB+TMnU9qZdhv1fJ5MJGN3cfnKZYvno3dOzfB2sYG2bLnxuNH9zBtygjMnD4GgYEB8i2HMuV+oHYzwGA00GwrQgoSBycnZM2SAyePH8TE8YOxbPFMaVPvN2gsCb90lH8iMRl8PKRqyv8YATP1wfTpM0vzKy9yZfOVVqvF6ZNH8OKFD7xSpaG+ppVEhr8R9eTJI/zwU3Wq1StZwXmcPnWM0hyVffThg3u4fu0KmDTxoBnAi1cfP4S1tQ0cSCNAidXfByJgIhnO5NHW1g5HDu6BUW8gzbFevoUVGhKCCpWqECkJl21w7eolSVi4CCGY2AgirHzFTkAIiwsljTBPpnbv2IzW7XuiarXfZTubqE8wucqeI4/UxLF8sbLSwd/fFydJY502XSZkzpxNlmcwGCmNVmqSuX11OisaY0zQarRU5qs+wiWrLvEi8NFkR6MI+AZFo9nYc+g05ZIkGYLuk5v+r3Mv0GzMWdQaeArr9j8Gk6J52++h9uBTqBXH1RhwCvO23cetx6FoN+UiGgw9g6sPQqgTCVy8E4SW486j0YgzGLb0BtpOvohag+Kn57w6TrmAxTsfou7Q0xi25AaiiDgpXBGqC39ccAeZ1epQmV2nX5YkSqGHgILU3/+BgBCKfHth2pxV2L7nDDbvPIHla/bg15oNpEAoUbIc1m89hH2HrmDvwUvkLuPA8ZsYNW4OkRMTypPQWrxyJzZuO4ZN249hxdrdUlskhIBCM+YatRpi6aqdcmbNAqVBkzZYu+UQ1m85jC07T2LmvNVyzQULK6ibisA/IMD9xNXNA3807wB+869P91bo1aWF/Lhg/vxF5avGGo0GYWFh2Ll9A9gvR858LwcyRdHIxbHDBnbBxHGDiSD54uzpY/ij3k/o0q4RBvXthNbNa0sNQcUfqkry9A9VUoMTRMCMNGnTo3TZSti1cws6tW2APt1bY+vmNURSatMkKQ8eP76PCWMHYta00VJWhIQEYd7sSejRuSn+2rMdbFqaMnEo+COB/kRAL108g327t8lJ1snjh9CtYxN0bt8YXdo3wvPnT1CsRGlkI8LDX3rvRf2iX4/WuHPrOhr+0Ro6MpMXKvINbGiCNmxQV8qzNwb364hli2Yib/7C4Le8jDQxS/BWvjJPIQSEsLj3uTUh3j/u++T3b8T5aLLDhQvaGY1mGIgl0+nLn8IBdGUms5QQlgshBJko8IYjb/AWm0/stUInRjJpRZP2iMMVgTfSsp8QAmz6Ys2SmSLSJe3j/ATA39sx0Kwhju/nOv1qyjUajTTDNUoh4uzsQg8C6NrwcoDgAYZnT3Ed+zEAnJaP/HVlftMKEJTWiNhNCCEFWdz4PBP3TJESjmRGM1Fbml7rc1A3FYF3IGAyGVGHTE3tOvVG8hRe1E9NaNC4Nbr3GYaUXqllSn7dmAe36r/Vh4vrqwWoZrMJDg6OqPzzb/ipyq+kIXKSBKldxz5wdnVDaFgI8uQtBF4DVK9hS/DM30yyS2aq7j4IAXt7B2qXNmBsHZ1cYGdnhyZEUlu160FtZoaLixsqVvpZLjA2kRwQJDtsbW2lHCpaohSqVK0Jbk8bXvtDJSf3TCHf/OS36vicv7vjSXIkWfIUNJ5oZNyOXfqjWs16METrkSFTVvTsMwLlKvwE7jP5iNT0oOvCRUvKL23z1+B/qVEXvfqNApvcTF+9HKLx3aBHNJkWYx1/lZqgTfAnhJD+/KFO/kQJy3ohLH4y4DPu/i+yw/X+L+/jQyD6p3p8SF58X6p7PwRYqLN7v9jxY3E6dvF9337FguVD4r89JzUkqSHA/caGBsVfa9ZHnwGj0XfQeKnpSZsuoxxEuW8x+W7boRf4696szYnFiNOy+bVRk7ZyzYadnT2ZUpPh9/rNZF78YcIefYbLD9txGMePTasePwwBxs4jWXLUrtsEfQeOkaSiZu1G4LdAzUQ6nYns1CeSWplIDZMRNhn+Xq+ZjMcfDOzWa5g8b9uxN9xIm8dvXrWhNu3eexh69h350jFZ4fY2EynNmj0XWrbphn6Dx6FLjyFgc3osYeVj8W/KoFO3geg/ZDzVaSyRr45ITyZ8Hsg/7O6+tNgCT58+wdKFMzFp/BD5/wwnkWZz9vSxeOL9UE5IX78jXq+2dvUijBreB8OH9MDSRTPkJ0KEeNsI/HoO/9218t9lreasIqAioCKQeBDggQ0kdHndhbW1NZ0KSXRiayiEgEarlf5IYOMwhcysHCTzohMrMnXYkfaBNY/sx4681d//gUAshlbURuw4q1g/PteQyVGIV4Mnt0lCjuOySyiM/TiMHecthICtrZ1cu2UmiwT7xzoO5zLtiORy3xEifr+Jjfe1Hek28fjhPWxavxyH/t6N40cPyLdwT588irDQULrdV21AF/JZ4pdSZkwZjVvXr+DalQuYPX0cZkwZJeMLET8+p/mUTiU7nxJttSwVARUBFQEVgQ9GQE3weRAwk6mQSf7E6UuwYdtRbNx+DItX7gBrw0xkGn69VoUKl8D4yQuwasM+LF2zG998Ww5nTh/Do0f3EtQEvZ7+v7xWyc5/ie4Xmjdpdr/QmqvV/n8R4HVv/28eanoVARWBrwsBXq/Dr/+DtF5CSVizJYRAydLlUbjot2CzsB1pyjJlzi7fWDTo9QSIqtkhENTf50ZAQx2Yu6KttQaeHrbk7FTnkfQwSEH37OpkA42iwMnBCik87L+gfpD02suT2uu/cikob2dHK/Bbra5O1tQXVHz/K6zfli+3gYuTFYSCz7MJyNf/58+ZjDEj+shvql2+cOatdWGTH2t8hBCIioqSX9r39PSCRzJPSYDemvATBHwuCD/BralFfAgCxHVkdBtrLQk1e9XRIJ8iiTo3ZyI7GgFHBxrgktmrfSGJ9oMU1PbOjtbQaBS4Up/g66T6THy2+6Y2cHG0gULkQQroT7zjRdz8j1H5/4Hxx2F5TU73Tk3BX8vXaLRvrY1Op8OB/Ttx+tRRlCpbCcmSpYDZbHpr/E8RoJKdT4HyF1AGv5rPJgx+hT8wJApfs1Pv7d3tGxqhp1mYGRERRrUfJPFnITxSL/tCGPUJ9bl593PzX+HDbWD+DGsLuEz+R6ijJ87FgqVbsHDpVvQfPB6KRoMNa5dRvzAmuJhfCIHzZ09iyvhhyJW7AH7+pRY0Ws1nHwVVsvPZmyBxVCD2WTKbzNBHGxGtuiSLgcFgIss85LeP1H6QdJ8Fvd4Ig9FMM3KA+4TaF4yfRSboDWb5PH6ukcJoMED+rzIyabGWJ1XqtPDz85F+QihQyOQtBAXGVPD8uVMYMaSn/DwDf8ohdZr0sg/FBH+2g0p23gp90g3gfqs6IMligJgtRn4lWRzo/pPyvXMvIAj4IF1SxuJz37tsgM+wCw0NIQ1vODRkshJC4PGj+3jh64MUKVPD1tYegYF+8v+EhYQEk7xUcOP6FcycMgpGkwHdew3mCFwmAAAQAElEQVRDjlz5aNJkoJqz3YAOn/Gnkp3PCP7XULQQgjq5AOiHt2xCJBwohIAQFveWpAl6CyES9Fc9VQRUBFQEVAT+HQSMRgPmzZqILu0bY+7M8Zg+eSSGDeqK8IgwVK9RlzQ6AvyvOLp1aoLjR/6W64qWL5mNUyePEBGyw59b12HksF4YPrg7dv65ieJ/XrrxeUv/d9pEzeUzICCEIHNXNHx9fIjtP0RgQADZcHkB2isiIoQgVWcknj97Bp4hxK1mZGQknjzxxoMH90kl+oLYvzFu8FvP+TPkz58/Q3h4OIgpQd1UBD4UASEEdR2Le1taId4dzumEsMQRIv6Rw1T3/yMghAXXD8lJiLenEeLtYVyGEJZwIQRfJuiEELLvJBj4lXlqFC3yFywK/vcQmzaswI7tG5AqVToMGDweBQoVI9OmEW7uycCvl3skS0Hy3whnFxdkzZ6T5HMYzpw+igtnT+D82ZN49ODuZ8dNJTtfWQf9FLdjNBpx4vhR9O/fC61aNMYfjeuiXZvmmD1zmiQ1QlgEAi9wmzdnJpo1rY+F8+eQ3ZbJEHD1ymUMG9IfLZo1RPOmDdCudTOsX7eawt+u6hRC0MNlwJhRw9G8SQOsX7sKGo3mU9yuWsZXggCvLWCS7e39GPfv3UVQUGCCApi/EeL34oUk6dzXE7r9KCLrPqTO9/X1RVzn5/cC0dHRCSVJKn7/930KIWAiGePj8xyPHj2UA6cQ4r3yfUHtwW3H6WMTCCEQFhaGhw8f4vHjR+C2E+JVfkII2Q94wvaQJl+PHz9EVFRkbPJ4R78XfmTG8X3vyVm8xF/ahYD81ykz5q7GwuXbsHjFDoyfshDffPsd3QkFwoxSZSqS3yLkK1CEroDO3QZh2epdWL5mN1au3yfd6o1/o2nLTp8dM5XsULOpv/dHQAiB06dOYNCA3vj7rz34tlQZ1K/fmBh/aixftgi3b90ADypMRE4cO4rZs6bi/LkzuHnzBjF/SEJz8cI50ub4oW7dhmjUqCkCAgMweeJYPLx/n9JqEqwM57lt6yZZxpkzJ3Hnzi2pNk0wsuqpIvAaAtx/blHf7NenO9q0aoK2bZuhfdvm2LljWzwhLITAubNn0KNbR7Rt0xR3blM/U+KLSSEE9u7ZhVbNGxHZf+XaUL7du3agicCx10pXL98XASEEnnh7Y/SoYWjZvDHatGyCXj06U5ucJtkQvx3i5sn/ruPC+XPo3LE1BvTrCSZKQhBpMplw9MghdO/aniZkTWXbjxo5FM+ePpH5CUFEKDQUK5cvlWFt2zSjY1PMnD6FCJDysgiNRotr166iW9d26NOri6yjEOJl+Nd6whNW/pcoHh7J4ermBkWjITlumbTyPfNzxa+ZC2HBgq8Zq9cd+3P8z+letebnrIVa9heDAM+QWDA8e/YU06bPRdfuvdCocTOMGDUes+YuRrr0ln+sGBQUhKFD+iFFSi8UKlz05f0JIVC12q+YOHkG6tZvhDr1GqFGjVoICPDHnXu3odG82SU19ICxuWvUiCEoWKgIsmXP8TI/9eQLReATV5tn8107t8WePTtRvERJVK9eUxLwsWNGSEIjhEVYh4aEYNmShdixYyuOHD4If3+/BGuaLHlyZMmSHTly5JIud+68ciHnsWOHqS8nnCbBjFTPeAiEEvGYPn0SFsyfjZw5c6FsufI4e+Y0kYz2b9XwKERG2aw9bsxw7N69A8dJ68xySggBJrjDhw4gonIFVX/5lfLMjdWrl2HWrOngdAaDgSZQizF4UB8oGg3FqYHyFb4H/x8sc8x3YYQQpFWOpgnZGOz4cyuOHj2MYLkg19Jn4t3AV3hhNpvlJJWPX/LtvTmyfMl3o9b9P0WAhcPTJ964ePEcvitfCcWKl6BZMb+mbCaSokG+fPnh7u5OfkasXrUcN25cR4cOXZEyhVe8erEgsbKyAr/SGBLij7t378DBwUFqh9iEEDeyEJZ1P4sXzUdgUCA6de4GJ0fnuFHUcxWBdyLA/fbx48c0aJ5B2bLfoWevfujStStatmwHXzKVeHs/olm8oMFOoYHsEE6fOSH7N96ysdAv8U0pTJoyA2PHTZFu8JCREIpA+nQZkD9/QZnfW5Kr3m9BQAgBNi8eOvA3GjRsggmTpqNXn35o2bodHty/h907d5Cc0b6RmsZirFu7Ekw0KxBR0Wgsw5oQAiePHwNPlIaPGI/2HTphwMCh1AfKY9uWDeAJ28NHD7B+/WowqVq0ZCXF6YwePfqidZsOL8sRQsHWLZuxe9cOlCe5p7Oyehmmnnw5CFh6xZdTX7WmnxEBhWZQL1740szVX85mWcjErQ6vb+CB4Mb1a1i9cilq/14PZcp9B8Nr/zCO1zT8uX0LxtBMrHu3zmBTQtVqNZAtaw5wHnHylKdnTp8kQbMdnTp1R85cFMdkkP7qTkXgfRDgPunk5ITkninAg+bVK1dw9coNqeVJntwTXl6pIYRAMGkjF86fg2JFS6BkyVLvzNpoNMjF95FRkYjW6/EnzfjPnj6F8hV/QKrUad6ZVg1MGAEhLJqYiIgIlCpdFnq9geSBGXnzFoCjoxMOHzlIZCf+kCWEwM0b1zB3zkz8Uq0m4V/pZeZCCPAEydbODukzZKD2ioa9gxPy5isIX18f8PqeG9eukUn9BapVr4mw0GDcvXMb/qRlNsUIN5Z59+/dIbPWJFSq9CN++KlKjPnc/LIc9eTLQCB+z/ky6qzW8jMhIIRARGQEWMCzAEmoGmwu2LB+DaytbdCOtDpW1joI+lNodqTVaiCExY7u4+ODOyRYnng/AZMf1u48phm2hlTJsfkKIRAcHCS1ROnJPNagUSMQ35J5CDrRaDhnERtdPaoIJIgAkx2PZMkwcNBwGsgCwOYsXlh/+fIFtO/YFVmyZgWvrlw4f65cEFuLSLqjk3OCeb3uKYRAUGAAaRZW0YDsjCpVfoHOykqq/V+Pq16/GwEhhCQgWp0WTEKZUHIKR0dHsCY4gEyKRoORvV46Nl+tWrWMrs3o3KUnbGxsYTK9IiLOzs5EYkJx/NgRRISHw48ma0FBARQfCAwMBC9GZnK1bOliNGncAK1a/oFuXdrh2NFDRKw0iIyIxJo1K6Uc6tajDxwdHCl/k0yv7r4sBL4OsvNlYf7F1paFiAM97Ha2duC3ToSITzSYqNy8cQO8kDh9hoy4c/smDvz9N3x8nuHpM28cOXQQbEu3tbVF4z+aYtbsBVi1ZgPatO0ohctCstPHBYfzO3vmFPbt3YUsWbLh3JmzOHjgMORbEw8f4MjhwzDQDDtuGvVcRSAhBBRFg2+/LS0H0fPnz+LkyeMUTSGTqBMNpDa4cvUyxo8fhZ8qV5VrehRhEY2cTiFiTZHf+rt06QJ4Ef5PlX9Gjpy55ZtEb42sBrwDAZpMRYQTUQR4wTFHZKKq0WiIeGihj9bHe96FELh29QpphrejeYu2RFozy7TkDUWjoXMzipCWjjVt/ft2R4N6tVCvbg3MmzMD/FaeRqOQPApFCE2oIsLDqO1/QblyFWRb9urRiQhOMG7dukkmrI0kr1ogT948zInlZEujaOWR66i6LwMB5cuoplrLxICA2WyCJ6n92Rxw9PBBEhIhUGggEELIB99giIKP73MSTAoO7N+HNjFvp5w9c5pmVkfRpXMbIkC3oFEUSqeFVquDk5MLvitfAck8klPYbbBmiO/VZDLJPIODg6WAYZs8vynRq0cX3Ll7B/v27EL3rh0R4O8v43Ea1akIJIQAExdea1b7t6rw9XmOxcvWYPmqDXB1cUH37h2liXTGtEnUj4BChYrIAZRn/GzJuEfax+fPn8mBM6G8+TP6u3ZuR3BICFq2ai/zSCie6vc+CJhhZ+9AWJsQTqRHiFi5YoDeoKcweyKmVi8zMlMD8RugdmSmSpsmrZwMcbuxpvg6kSA2U+XMlRtTp89FvQZ/kKxxRLFiJfD9D1XAaVxd3cB9g8kQv2DRrkNHdOveC/UpLr+mfunieaxZvVzWJ3OWrDhLky1+NZ3zv3H9KnyeP6f2Fi/rk5hO1Lq8iYDyppfqoyKQMAJMQDxTpEDZsuVx4cI5jB41FBfOn8Pt27ew/+996NenJ6ytrTCTNDbzFy7D/IXLMW3GbJpdFcM333yL6TPnIm26dNhLmpr9f++Vr396P36MgwcPknnBHyyYrKytKc+zWLhgLqmYH6F0mXJYvGQV5i2w5DdpyjTS8mQlgfUTpk2fCVdXVxJGZqibisDbENCQ+XTP7h24SINXqzbtydRUFZVJgzN67CRERUUR2dkhzSfOzi5Su9OpY2sa5FZQvzJh+vSJ2L51c4KmCyb6vKCW39ri9RxZs2dPMN7b6qX6x0eAyYuHhweio6LB30LSarUUQcDX1wc8CcqcOTNdx/4EtY+ZZMRDBAcFYtiwgejcqQ3Wrl6BFy9e0PUAkjO7icwI5CLCM3DQCCxZvg59+w+RL0OkTp0WyT094ULyw6A3IJBMkXq9EUYygTmRCVNDmiF+U+vJk8dk/orA6JFDZf5MrnhNz6hRQ6QGO7Y26jHxI6CSncTfRomqhlZWNvKV8Z+rVgdrW1h706ZlE/SgGfKVK1eQKlUaFChYGMWKlyT3DQoXKQ53dw94pkgpz23JBHb82FH06dVV2sdbtmiMObOnIX/+gvi9bkMSNkYcOnQAUyePx21SIbPtvkjR4jKvYsW/QeHCRaXd3MsrFQoWLgKNFIiJCiK1MokQAb3BIGvFAyMTHJPRRINkEMykQUyR0gs9+/Qn8jwX/Wgw5AGxcpWqctZer/4fpHmsSCTGSIPbZvDC+siICBnGZOdvIvm8aL9q1V+hpQGSB2xZ0BexS1yVZOzYXO3o5IhtWzbCh7RwbC7/c/tWua7vJyKowUFBYDP5wQN/QUN4c1uNnzgdffsNRt/+Q/FTlV/g4uKKdu274JuS34L/Z9MTb29ERUVK8/fGDWvwN020OC83N3dkzJgZXO6OP7cjPDwcT588wWHSWjs5OSFrtuzo3LWX/ExG3/6W/H+pXhPORIZate6AcuUrQqqdExeMam3egoDyFn/VW0XgLQiYkTZtOgwcPByLSOPSvkNXIikNMHzEONLkLEOGjJmgp5mS0UizJHJMjpo0bSlfJSWts1RDt2jZhuKPJe1MFfCgMmr0REyZOhvpSOsjIPDjD5UxhmbdufPklUIuNi8+2to5omu3PqhR43cSYJYB7C0VVb1VBCQC3G8qVKhE/SsDJk4YixrVK+PXaj+iY4fWcHN3R8WKP4DJNn8gs1TpsihduhwyZc4GIQTy5ssv+7S/nx/GjhmGGVMnkabBl8ywCnjx/Ib1a5A9R04UKlIErAmQBaq7j0KASQfLjx9//Fmu0+M2qlWjClatXCrlR67cefHo8SPMmD4Zc+dMl22QN29+vGw30gJnzpwFOp0ORYoUk3Lq9KmTaPpHXfz268/U7j+hX98eyJw5Kxo2bkoE1kTa5DwoWrQYFi2cKlMfwgAAEABJREFUg+q/fI+6v1eXZTdr3gYpiQTnzJnrVf7UN7JmzQ7WOPGkK336DMR1VK3yRzX2Z0ikkp3PAPqXXiQLJXuyrZf8tjTqN2wMJi8//vQzkiVLLmdJce+PBQPHK17im5feHhTv+x8ro32HzmjbrhN+rPwz3JMle5k2a/YcqFK1mpyhcVkvE9KJtbUNKlT6HvkLFnwZn7zV33+IwJeeNZtf09HAtHnrLrRs1RYpPFPKr8HygLdg0QowqY7bz8xmE3Llzo269RrJ18g5vYurG2rXroffatclTaW77HtMoooVKwFeHMtagi8dp8RQf3t7e3To1BXDRo5H7tz5kDtPPowaMxFdu/eW5IRlDH8csOZvdeR13Dpzu+XMmUcSI24vbjdea1P2uwrS3J05Sxb06jMQU6fPAWugOdzNzY0mbiPRpVsvsLa4cOFiZG6fjxbUT7h94+bPahwmOw0bNQOb28w8e4sfQb1KxAioZCcRN05irho/6Hq9Xmpe+KjXR78hfGLrzzNedrHXLGR4kZ+e0ksXHQ02J8SGs5DhcC4j1i/2yH6cJm5+sWHqUUXgbQhwn/JKlRrde/bD9FnzMWPWAgwYMBRZsmQD96m46fi6cOGimDR5JmmD0oPTWltbg19Tb9KsFewdHGRfdyJzxshRE1Cx0o9SyxA3D/X84xBg2WBPE6n69Rth8tRZ8sOCtYhg2tjYyHZydXWlCVJn/FqjtmyDuKVwu7FGp3vPvjTxskyeUlGb9+jRDzPnLCSSMxctWrQhsupBeZlkUk7jmSIFOnfpgZnUJ8ZNmIqfaPLFJjIZIc6O47IGsGfv/mDTJ1/HCVZPEzkCKtlJ5A305VRPramKQOJGgAdSJsk8kPF6m+h3EHQZ12igQfGVmYJJjzGOHw92/OkD02sfzUzcKCT+2jGuPKGJrSm3GfvxNR+5Ddjx9evORFo5DuN4HMZHI7UPf6dHQJCJXR+vTWPjcBlaMn9xej5n/4Qch8fNP6E4ql/iREAlO4mzXdRaqQioCPxHCPAA+B9lrWabSBHgNjfjFXFNqJocJyF/1e/rQOCdZEd2Dd79i072NzU/Nv8mGiebg3dfR59W70JFQEVARUBFQEUgHgLvJDvpktuiaA5XFM6uuq8ZgyLZXJA/szM0ioBCTqfTwEp1SRYDrVYhhT+g1SiwtlL7QlJ+FrgPCAHoqE8kZRz+w3v/Rzmj1Qh6HgVsbbRwcrBS3ftg4GgFe1sdhBCI3ZTYk4SO5Qp6oPvvWdClVibVfc0Y1M6MllXTw1qngAc69YGyStICxc5WK0mvjbUmSeOgPgdWsKEBlidAttQnVDw+j1xgksNjtpuzNdKkdEKaFI6q+wcM0lJ4Cg87aGjChphNiTkmeDh6yR+zNt3H3K2q+6ox2HIfy3Y/QrTBhPAIAx4+C8XDp6pLqhj4+EXAYDQhIDgKD56o/SBR9IPP8Dxy2/sFRsBAcsHXP0LtC5+jDZ6G4EVAJEwmMwJCovD4eSi8fcJU9w8YPKZwH+qz/PHQWHLzTrJz43Eodp15jr1nfFX3FWOw56wvDl30g8FoJsJjRGBQFAKCIlWXRDEICYuWwjU8Qk99IIKc2heS4vMQSP0/PMwA/hcKIaHcF9R+8Mn7QWAUwsL5DTIgjNqC2+ST14H6wRdXZmAkQkJIjsX5FtI7yY5CujO2F2rIZqg6QSqxr9NpFct9IWajZidbJ1QnvjgM/rU2Q8ym9gX8a5h+aViC+r90AL60un9N9UXM9jXd06e4F7zGbl67jEH1Pz6wSs5IWoRYZ7J83+llqSZiY7Fh8kgqvLgvC1GwnG3IsJh8KMrL9HFPeFbCGgsuM65/7Dmn43C9wSw1G1x2bBgf+XVELofjvB7G4bGO8+d4CToqhOvPeXE+by8L4PR6UhsbyIzwenmcB9+Pnu7ZQI5xiC3/cxyFEFAUhUigloQhS0a8sSmKRsZ5I4DTajTgLywrlMcb4a95CCFkORxfCAF1UxFQEVARUBFQEXhfBJT3jfhvxVNIi+DlYYusaRyQhVzm1PbwcLYCD+w8mAsqyNXBCplTW8I5TupktmANEw/0FAwbawXpU9ojS1pLnIxe9nCy1UqywuGxzkCEIRWVlTeTM1K42cR6vzxyfg6ULkc6RxTP6QqOZ2+jBRMXjsRkgsOzU3iuDE5wd7IG15PD4joN3VMqqiPX9XWXleqYztMOWhqgHe10yEd1+Sa3K/jtJwcqi+vAefHRxkpBLiqnRC43FMjiAhcHHQxElDic68LYpEluhyLZXZE3oxOc7bUJ1ofjv9P9C4GKokii4vfCB/fv3UJoSAh0OquXpEcIIcmJn58PAvz94n3Ii9OCGO7jh/dx68ZVBAT4J0yIYNk0RIr4H/ndvXsDd27dQHh4GBSNxhKo7lUEVARUBFQEVAT+AYFPSnaYKHi522DQH9kxplVujG1NTh5zoXXVDHBztKIBUqDRD2kpLBc5S/g4ijfkjxzIT0SBtSPFc7hheLOcGNuSwimM8xnXJjfqlE8NayuFBlaAScqvpb0wrnUuKisXfi6ZAgoNwKCNSZWGTHPf5nHHmJaW8JEtLMfBVE72tI4yDwNpT6qW9JL1GE/5t6ueETqNJX/KRv6YhCRzsULHGplkPL6veI7q2Ld+Nlm30TFlDG+WC6Nb5cLIFjmRg8picsUkaETzWH8+8r3lQQm6Vy7DzkZDuKTDBKrHqOY5KX1uuq/ckjzJinzCnYmIyqULZ9C5fWM0b1wdrZrWpGM1zJoxFlGRkbImwUGBWLpoBpo3qo4lC6eDyQpiths3rqBf73Zo07wW2rasQ8ffsHHdcpjpLybKywOXdejgXnRq2xDtW9ZFmxa10KV9I5w8duglsXoZWT1REXgPBITgaYMlohDxz/lSCCH7lhCWoyXm2/dCCApkRwf1968gIMQrPIUQsj3elbEQ4mWwEK/OYz2FYD92eCMvISz+PC7wmRC8R5xNxKQR0k8IOrKTV+ruS0FAeUdFPyiIB2QrnSJfX+Zz7jivZ8D+PGinJMJjS9qZZ36ReOofheSuNqhRJhX++DEtNIqga2vSWugQGWXE/WfhYGLC3/vpUTcLWKPjSBoNDyedJDaPfSIQHK5HuhR2aFYlHaqVTAnWiDSrnJ4IVEZ4kkbHSmupF2I2KgLlCyRDt9+zSA1TRJQJVx8E48mLSGQljVKu9ER2aOB1cdTh2zxusCeiYU33ViCrM7JQOJO2mKwAQaYnMsP5BEbhEdXlRVAU+N4c7TQICtXjIfn5kl/ezM5wdbLC5XvBVFYIKzaQM70Tqpfyovy1KJTVBdlJC+QbEIXHvhGcLTKmtEOD79OA61GxcHLULkdxSRN17WEIAkOjwRqtFlUywNPVWpIzfKLt3OnjGNy/M+7euo5y5X9CnXrNkSNXXuz6cyNu3bqGe6TpGTaoG9avWQJf32fwe/GC7pdAovqZSFN1/eolGA0G1G3QAn8060BaOx3mz54I1vQopDGiaC9/en00Lp4/gxQpU6FZy86oUasxHj96QARqGiIiwiEENcDL2OqJisDbERDUt8LCQnHm1DFs3rACa1YuwNHDf8t+xP3x2NH92LVjM7lN0u2k/nyb+rgQb+9jQggEEbE/8PdOSrMZrMUU4u3x3147NYQREELAaDTg9s1r2Ll9IzauX47TJ48gPCwswWddCIHIiAhcPHeK2nQltm1eg2tXLso8YvPTR0fjyuXz2LZlDbZsXImLF06D5QqHG400xty7jd3U7quXz8eeXVvh/fgBB710IcEBOH50v5RnG9YuxSmqT6Qqe17i86WcfDTZoTELrIlp9UsG/EoD9vdFkqNttYxo92tGVCmRAk52WqILb8LAhId9wyKNWLr7EUatuInTNwJl3G9yu8HGSkMDt4UqnbwWgOFLb2D9gScIjTCATVG5iIjwgMkxAkP0mL7pHqZuuCtJkUIdvwTl4UoaIiZUhy/5wZuIA5cnyyUZxOk8iVxVIPLgSMThKRGu2VvuYcTSmxi94haW732EO0/CqA5ADiIfGYhw8CvZvI7GkeKzCUmjUEacKTk+8wuOxsIdDzBsyQ3M2/aASI4BeoMZa/Z7Y+ji67J+q/96jElrb2PU8puYvuEOEaNwSg1J7JgkMtlatPOhrMNMuicmcRyBMc6Qwh6Fs7kQKVBw5X4wxqy8JTHRk5kupYc1MpEZj+P+104IgTASOltJoLCmpnf/0WjboRcaNmmDbr2Gof+gcUidOi2CAgOQIVM29BkwBmnTZoDJbHxZNSEESpWpgJ79RuL3ek3x2++NUL5iFYSGhpCQeUjENr55SkemsZq1G6JrzyGoXrMeEaTmKFCoOJ54PyLTWXCCAvBlYeqJikAMAkIIRESEYe7M8Rg+pDvWERHfu3sbli2aSf3uAcLINDpuZH9MHDsIs6aNkW7mlFE00B5+Zx/jwXLf7q0YO7Ivxo3qh5uktVQ08ftwTBXUw3sgwHge2r8Hgwd0lhMgnjCNHNoTS0hLnFBynvCsW7MYg/p3wuoV87F8yWwMobR/790hzez8D4X/3LYOg/t1wtIF07GKCM2Q/l2wbdMaaldFtteoYb0wY+oorF21EONHcx8YLCdUikaDkJBgLJ4/HcMHd8eWTSuJLK3CyCE9sG71kjdkVUL1U/0SDwIfTXbMxB5cSfNR7duUaFo5HdrXyIgfiiZHJSI9zX9Oj++LeEIhAfO2W+X0gWHReECam4fPw8EEhr/SGTdJOGl2nvlH4tbjUIQTOeK8NGR+4iM7XufiFxyFO95h8AuKlgSFtTg+AZEYu/oWRhKRek6aEo770plBpMkaqZPZUGeHfOV6//kX4Hi3vUOxjgjKJdK+cN3LF0wOJjZX7gbjyj3WxpjBhIxNZHT7L7PkuvsH6/Gc6sr1MZKZh8OZjD2juvhQHU7fCMCZm4Fg4sTriJzsdDI9318E3ScTvrVU9o3HIbhPeEREWwiCnkxpOq1AMjKVMTYXbgfh4fMInKcjEyo2q3k4WxPWMrv/dCeEgM/zJ7hy5RyKf1MWhYuVBINoovu1tbVH3vxF4Ozihrx5C6Flm67IlacANBotJJOFZaMs4OrqDncPwpbCoqOiSBN0E1orHVIRUTISgbPEtOwVmo0nS+ZJ+bpCo9UhmIjUE++H8EieAg6OztTm1KCWqOpeReCtCCgaDTatXQ6e+Vf9pTamzlyOSdOXYMCwSUTIM0pNwLNn3vj+x2qYs3AjuQ2Yt2QzqlavQ7LJlGC+QggiSg/x57b1iI6KJq3OC0STJpInQAkmUD3/EQFfn+dEWhZAq9Fi6uyVmDRtCcmVwlhBJObO7RtQFM3LPIQQuHXjKtauWowiRb/FnEUbMWzUdNja2klyxETl8aP7WLNqEdJnyISZC9Zh7KQFUs7MnTWBNM7PpWwqWLgExk9ZhAVLt+LHKjVxmMzmJ48fknW4d+cmdu7YRBrsypg1fx1GjJ2FNDSB27RhOVijJ8RHD6Ev75n/A+AAABAASURBVEM9+TQIfHxLmQHqa9Aoghi0gmdkjlr9lzdpUiLJLKMh84+7PGo5PMZxXJAkoKRQyC+Fiw0KZnGJ0VoI0nZEIEr/SrA4EyFgs1KpvB7SBMSDO5eDmI0/ZZ7Gw44IiDsyeNmB68OmpHAiCr5EMqLoGBP15YHjONvrYGejpYESuPYgBEZiJuzPjutGY7ckRHkyOYHJxnHSMB2/5i8XCydztiJzkyON3xwTLzdOyw6gG0TMRh70kxfODlbo2yAbZnbOj061MpF5zRoh4QZsPfoMkVRPqoKMp1CCfBmdwZop9rtCxIvjWek0MjwwxCBLYNLExEChFrQhk6BQ4pQrY/77OyEUBAb4ISQoCBkzZiUM4pZhJjwtmCgaDRQSSkxokUC1mODs2LYBY0b0QYc29bBvz3b8WqMB0qbLSAOLMW6m8jyQCM7yxbMxfFBXGf/hg7uoWash7OzsX5YpI6o7FYEEEBBCSC3gooXTkTVHbtSo3Qhu7smo/zgiJZlHbe3sXqZycHRCMiLSyZKnRHLPlHLgfBn42olGUbBj+3oY9HpUrlpThgoA8kTdfTACgvC8d/cmHty/g2o16iNdepKTKbyIgFaHlZU1mZg2Q6O1yEFL5mZcvniW8I+Wberk7IJMWbKj7Hc/4i4Ro+tXL+Lm9ct4QQSqTv0W4ElT6jTpUb5SFdIkB+P82ZPInbcATcy6I0vWHDShckPpspVoEuUEfrGCJBoiIyOkRpDDnZycwWXY2ztKsWZm84aw1ETdJ34ElH+jioGheizZ9Qizt94DaycMpI3wdLNGDjI5dayZCZ1/y4QuNMA3+TEd7K01NEABbBJqUz0jhjXLIdfBPCOtyNq/vSW5EMLSg0rlc8fYNrlR5ZsU0BtM2HfGB5fuBBPjtlTb3UmHPg2yoCNplTycrHDvaTi2HHlGA6YZQgiIt9yctZUCCzcwyze4EorHC4ad7XWIJK2LDxG5py+iYCDTFK85ypPRCaxBekv2b/WOJFITHK4nkmOEkR4UDVWiZG53OFE5TGx4LVD2tI7ghdW87ojXK60hbY+BtB0UNSZffgTp1IyXZIPTks9//iNICY9IREdHwcbWlvClSnxgqUIIuncjCaBneEy2cdYKOTu74tHDe3j88D6RJEvbxmYrhICeynv25DGePfWGtY0NDVL2uHHtshRYQiTUerGp1aOKACCEwP17t+H7/Cm8vNLg9InDWL9mKfbv+xPepCWUpJy6soDANRogt29ZS7P7PZTmDskqE4QQeH1TNBqKewm7adb/Q+Vfabaf8fUo6vUHIiAg8OTJI+isrJAhY2aSt3qZQ7JkKWBtbYNHD+7L69gdyz2WIV6p0pK22A1mmqVqqF28SEOs1eng98IXL174wM7eHim9UpP2ziiTpk6djuSXHR48uANQ25pMRhozuJ2B56TdMxj08PT0Am9MjnLnKYilZO7csnE19ZsluHnjMrjNnV1dZZkcT3WJH4H4I8tH1pfNMD6kSVFoRPYNjKJOZeY+RKYXa3yTxx3FaUAvlssd+UmLw6YqUC+l8RtsOjp1I1Cajiatu4OjV/xjSIilIqzRuP4wFLtOPMfsLfexYMdDsGkLwhLOr2U/9InE4Uv+WLbnEcaR6eoqaWoU6sCWGG/uqWgiGwZpThJCIK2nbbxIBiJqNkSG+DV0KzIfMbmpUyE16lVMDSudIolW9rQOcCMTHt5zo2IQEqbH/O0PMGrFLUxefwdX74fAlohfxSLJkDmVPREAMzJ5OaBV1fTIRNePfCIwfeNd3H8aRmEA14uLc7DTgvPTaoiwKYIeUsRohswc/J86HhQcHBxJUNiSOesp1SOmIT6gVM7DxsYWv9ZqgEFkQhg+egZq/d4YJ44dwPq1S6lr8H28ypfju3skQ/PWXSn+ZAwdOQ3FSpTGutWLcfbUMSJHmg8oPTFFVevyqRAQQqGBz4eeFRMOH9iLhfOmYvOGFRg3qj/GjeyHu2Sq4MExc9bsePzgHlYsnYMxI/qib8/WUuvIhDxuXTm/sNAQTJs8grQFKeSaM61OGzeKev4xCNBjHxocBEHtFau15edfZ6WDhsgLr88x6A2vciZhHhwcCNbM6Ujzw3HZ8URMQ2awUGojdnb2DlA0FjnBstOWNMIaug6mskjgyPwURZHaPzZZpSRCnCdfIRgNRkmS6jdqBf7cxZgRfbCI+g5roH/5tS7i/isCmYm6S9QI/Ctkx8FWAy8PG6l9SZ/CTpICHpwv3ArCwIXXMGTRdQxZfB0T195GMJluBA3SvOB43rb74AXI8/+8jzNEelh7Q/39JWBHL/lhEKWfsuEOdhx/joCQ6HhkKCBYj0lrbmP0yptYTmTnBhEj7uw8XLLmhMkQPQ8yPz4aDCaw9iQgRE/kw/LQlM3vgfSedlR3M5EKs3wrirUtTDgUqqcQQr7pxffFedAl0iS3JZJkR88JlySzf+dOoUT8JlYA1f8uaZ/O3QrEvWdhsi5ajYCNlQZpKc9uv2eWb2gxCZy99b5c48OkkMkka5i4EDbrcX5M0qw0CvQUgdcrmUhTxOH/pTPRzMnDI7lcb3Pm9FFERkRCQ0JFURRotFpoyQlhaUEhBIQQlurQUQjx8lpDgoZJE2t0UnqlxjelvoOLqzvNpG9Br4+GRqO8zEsIIb/f4+jkRGpmV2TImEWuFxJU5iPSBkFA3VQE3okAdSHoDXoIIaSZYszEeZi9YD0aNWkHftPn6OG/wIPrlJkrsGD5NsyYuxoduw7AU+9HWLZoNp6SVlGIuB3NjN07N8s3dOo2bIF0GTJS3hZRqqG+rSiad9ZHDUwYAUZYCNqbTWATfWwsAfoTgELPvKKIWG+A4gpBEz6jEWaSTUJYwoSwHLVaDRShUF4UzsIblk0IDhfQkuxiHyEEFI2CxQum48K5U6j2a72XJvXQkGAc2L8LgYH+0vyVjcyg/DbWeppsUTKo25eDgPJvVJXNPc1/zoCBjbKjVrnUMsvbj8PwIigaTHjO3gzEWSIzNx+FwESDMnc1kBGGB2q9njq2SSZ5Y8draaIpnImTmeK/HoGJC+dhITHgvg/enGy1qF4qJdqRmSw1kQjulKypaUvX35KW6e6TMJy7HSS1Jfwq+ZCmOdGvYTZMapsXQ5rkwG/lUoHXzPCiaCZb9YadRl1yvedeQRBpaJK5WCNXeid6kCx3wmXGutd9+BmzJzLY6bfMmNguD5pVTivfWiuT1wMaenBZe+UfHI1fSqZE7FtV/KCXzeeB3vWygl+3Z3J1y5vIEWFXOLsLuv+eBQ0qpZWk0ts3EhwWW/5/eWQimSx5SpQmu/alC2fBb6DcunkV/KrmqeOH0atbC5w9c0zOePz9X8DX9zmZvKIRRXZvP1Inh4QQ5jQzO3JwH2lyDiLAj+KQPZ2/mcNrgbJkyQnW+lwiO/yShTPg4/MMPIPes3MLrlw6Lxcnez96CF48GE2mrazZckH8lzes5v1VIMD91tbWTt5LejKPMMFm0wav3fAgE8nzZ09JLhnh6OgEe9ICOLu44qcqNaXGhtdu+Pv5QggSlSRIFEWRGoAtG1aBz48d+RvDBnTDn2T6MtGAu27VEuz/a4ccYGWB6u69EeB2cnB0pkmnCSEhgRBCSBcRGS4XgLu6uUFDBEUI8TJPR4ofGhaKqOhIix+FhZDGxmgw0OTITbYnyxBeV8URWB7zN8AMNKlKljwFqAA5wVq+ZK4kOz9Wro6ff6kVM9kCDh/ai53bNqBzt4EYPHwyRo+fi3Llf8TyJbNxisyhWq0O6vZlIEBP8P9fUb3BDF7DUqZAMrCW5+HzCOw57YMovREajXjlaHDnDs0EJprSkFICeNVvwZuZdtGkgWGCE01x6PKNn5FMTZZwEz0YnOJVFO7MjvY6lCuQHNVLe8HVQQcuLx2Zq37+JgWYLIRFGbHx4BMcOP8CAaF6JHe1QlnS8GRP7yAJmolIhRWZsG4+DgVrnPyJtDEhuUgE6fLdkJckSadVXhXMZ3QvkoDpzTST5LqZ5O1xXTmPdCnsUbd8GvxYzBM21hrcJy3P2v1P8NQvUpq0OJ6e7p3JVOl87rJOpfO6g1+5333KB9cehNJsREGFwsmQijRpD56HY90Bb/iS6VAIKpzr8B87HamTWRhU+eU3HCbS0rVDY3Tr2BSD+3fCC18fuLt74vKlsxjSvzMG9O6AJ94PceHCafTt0QbzZ08GMUScP3cS/Cpnjy7NwG7l8nnyjYtqNeuS4NFLMrNk4Uw8uH9HDhq7iez069WW4rZAz27NceTQPlSvWR+58xaU4f/xLavZf+EIsMzhtTo6nTWuX70kTRKKRoPnz5/QeSicnV2I7JhgoAGSCQw7HmxfEFnntSJs9uDJWQAReH8i6IIIT/6ChfFt6YrwIaLEfTyIZv4Mk3+AL4ICAyh6fLnEYap7NwLcTilTpZZtcfXKBSKTGphJy8Pf3IkID0PBQt9QG+nhT+STCY0QAmnSZpAy5jFpeTXUpjyx4ja2IXKbNl0muJEJPDIiHNevXZIExmg04NrVCzRuGJEzV34iUZHYunE1FsyZjB9+qo5mLbvA3sFBVpTHkrt3bslFyQUKFYcQAh7JPFGk2Ldy6u3z/CnV8bUxQKZUd/8hAh+d9b/SUoGh0Vix9xHYLDVr832MX3MLp27QA/9atYQQ8q2taRvuYvbme3jyIgIK+cWNZiAiw0Rkwprb2H/uBXUmETdYnp8jTdGUdXcwf9uDl2YxGUA7zo6JyeJdD+T3aPibNHHdn2QO0ypCfuyP18Rw2NT1dzFv+31Mpjx53c/sLfcxae0dLNj+ANHEyDRM2CgNm8Z4bdBEqtvmw0/pgYkv0IQQ8CHiwXlNWX9HvhLPaSOjjVj112OMX31LlsP5svlt1Iqb2HXyOcIijdhy9BnGrrr1Rp0nkOnvzM0AXH8YInGdsPo2GGde48R1P0KmPrrtT/YzkwRISTbtth16Y+ioafijeQdUq1EXnbsPwsBhk0j4pAd/AJDJUO26f8hv7XShWVHtek1RksxVOq0WNWo1RCfyK/PdD/iuQmV07TlYfneHFxryjZQp9z169RuJrFlzyDcjWrXrjhatu6BEybI066qNfoPGokWrLrCxtSVhGL8NOL3qVATiImAijUuq1Olk/zlx/CDWrV6E3Ts2Y+rE4dJEWrBwcRzYt1Ou4WEt4v6/dmLapBE4eeIQChcpKV9VDg4OxKRxQ+T3WPgNnZZtusuZ/pCRUzF87ExJvpkk1WvYUg6aGurnceugnv8zAixbMmbMioyZs2HDmqXgD/ht27wWa1ctIrmSQX6f6/mzJ9QGo7Fk0QwoGg3y0ISHTeLzZk/C3l1bKe5i/LV3O0qVrgDW4mXPkQcsrxbPn4ZtpH3btH45OM+ChUoga45cpJ05gsULp1NeCjJkyopDB/Zg/dql8nMC3G/SpMlAWqZgbFizBKyB5ry5HEcnZ2TJmosmW4Z/vjE1RqJA4F8hO3rSwPANB7eZAAAQAElEQVTC4A2HnmDrsaekgQiR2pTX75C4gPw44IELL3CIBukQXr/zGpcxkVbl0t1gsGaI17VwmtfzeUKakH1nfcGvg7PW5rUs5ILd87eCwJobLivW7SdNDn8wkPNkFxJhIM1NAHYS4dhAmh6L9iQEF+8GYfdp0qQQwVA4YkwFFEWAv8XDYUzmmPzEBMkD14NNX7zQmsviNToKpSd+QCQvEocu+oHLWXfQG1x/rgvnwdogzvf1+nK9D13wI1IYKfPnRct/n/cF47z3jA/4+0MElwz7lDsWSvwKZuGiJVG12u+oWbsRyhJxYaEihJCv7DKJ4ZlSpR9+QaUfq5FZoAY4Pqdl9XFpMoXVqd9MfliwTLkf5NsPHCaEAK/L4fycnF3lbCpd+kwyj/qNW0miVLR4abCw4fhQNxWB90CANZLdeg2Vn0yYOW0s+vduh6dPHqFdpz7Il78obOzsceCvXRjYryP69GiNrZvW4JfqddGsVWfY2TnAaDDi1vUreHj/LplpjUS07UgD4PjS8SJYroa9vSN4sSyfq+7DEUjumQJNaQLl7OqOkcN6gRcF63RW6Nl3JBydXcAfM7198xq1nTdY3mYjMtOsZSc8efxItum82ROpPYugOU2OaCaENOkySm1NWGgohg7sSgR3GNKkTY/2nfvCjiZLjx/dh98LX/j5+soPTo4a3htjR/TF5HFDYSQtUOlyFVHl59+wfes6dGzXAH17tsHjRw/QoXM/ZM2ek+IYP/wmv7AUTOJZaxbr+PpdtyCEIGuOVmrS/ikuPuH28WSHepqBtDDBYQZJYNi0xIM6u09Y/3+tqE9VbyYnXJb5/6g5p/8/kv/rSYWgzsC5fmDFhFAgRExaTv8PTgjxQfH/ITs1OAkhYCLtTtp0GTB11gqs2bgfazftx2o6/lj5VygaBWXKVcKmHUewct0+LF21E1t2Hidt4wgi7inIrGKEi4srZi/cgInTl0hTBufHZJudPjqayPgv2H3gMooWLyVNLUkI2n/5VgUKFi6BeYs3YMPWw1i14W/MmLsKefIVlCSTNXRTZ61E/8HjCWcDaeZ0qFy1FlZv3o9la/Zg3eaDGDxiCjxTeBHXMUOjKDQRq4QV6/dgNeW1ZtMBjJ00X06oDERgq9eoh937L2D/0WvYc+AS9rI7eBkbtx+hvK3gSqSrY7cB1DeOY8HSLbJ/LFu7S07euA/8yzef6LKL1kfLz4LcunEVse7e3Vtk/otOsK6MCZPHC+dP4cypo/AmYmg0Jg5CqCRY4/fwVBSBp/6R4Les2Bz02Dcc4j3SqVFUBFQEVAQ+BwIsiLU6nZzZe5FZy9raWs7MmbCws7GxQ7r0GZGRzBmsOWQhzWm4rjw5cXJ2Ji2PPV++4XSkfXB3Twae/b4RqHp8EAKMOePplSoN2GkJW/bjTIQQcHRygo2NDV9KQsNtZ2tjSwQmMxHR5FAURfrLCLRjzbmVtQ2Y7Cb39KI20hKBNVEIwOZG1srZOzi+1NLxuZ29pZ05b1CZvK4rS9acsu/YUj+JrY/M5CvdCSHk/yhjjViv7i3Rp2dr9O7RSmrI7t+/DUWjeePODx3cg36k/RoxuLuM17NrC9KKraXn7POb+z6a7Ai6zchoE87eCgT/e4XwSEvnIW/1pyKgIqAikGgR4IGKX1WWA1mcWvI1h7Hj8zhB8pT92MmLBHZmsyoDE4Dlo7zMpCXmdmDH53Ez4Wt2r/txXHavh8l4MfmZqY3MdC79YnZ8nZCLCQYxJ/qZJUF6a/4vI39dJ/zq/bOnj6VJl9epsWvcpB34y+P8DMW9W8bQ9/kz+bIJr8lsT6Y+M8zYsGapfHlFEAmNG/9Tn3802eGKMuHRkIaHHZFA9lKdisDXh4B6RyoCKgIqAkkRATNIg6OVi/srVPoZ5StWxrdlK5J2zVkSwLiQCCFQtfrvaNG6K4qVKEWm4e9RtNi38It5e06h8LjxP/X5/0V2PnVl1fL+ewQEBBQBMIFVnUhyOCjU+Owg+4FIcvev9vn4bU7dATxGKbRTsYmPzafCw/I84rNtrM26d/cmbt24Il/7528Uva0yVlbWMJH2LCo6Ct6PH8rvo6VKk05+AsDEC1bflvAT+Ktk598D+YvOSasREHQHjg46ZE7norokikEWuu9UyR2g0yrwcLNDlvSual8gTJLiM5ElvQs8k9nJvuDlaU99QZULn7ofcBuk8LDD5yI81jY2cHRwxJwZ49C3V1t0aFMfM6aOgq/PMwih0IgR/xcSHISVy+ZhaP8u6NrxD9y5cwPf/1gNrq5upAn6vGbeN2sbv+7qVRJBgO2t8lZJbSmP6i7JI8DkN8mDkOQBUHvB5+wCLI4/VwvwmMDfPOrWexh69B2Bdh17I1fuAti6cQ02rlsORXmTPgjy488vuLp5IF26jLC2tsGJoweQGD7A+GZtP2fLqmV/NgSMRLr5wTIYTAgJi1ZdEsYgItJAqmgzoqINCA6NVvtCku0LekRGGagvANwnVLkQ/cmfhVB6/vh/I/JC388xODg6OiF/gaLy45qlylREoyZt5RuL/Fp5eHgohIhPIRxIC1S9Zj106T4I/MHNOvWagf/33KEDe5EQOfqU9xS/pp+yZLWsRIvA55pJJFpAkmjFmPwm0VtXb1siENMDYg7S6z/YqVm+AwEWxp8Zf9bwAFwRSMIihIC1jTU0Gi0RYRP0Bj2ZqCyVNJmMEEKANTy2tnbgjz7yRzkD/P0ACHzOTfmchatlf9kICCFk52fGLkTCHVkISxwh4ocLYfHXaDQyD7znJoSQ8YWInx/UTUVARUBFQEXgX0PAbDbh5PHD8t9v3L55Ffw/xzatXwFv70coWqw0mMxcvnAGM6eOxu1b1+T/NWTz1q4dm3Dr5jVcorBdOzbCYDQgR658+FzaqVhAlNgT9agi8L4ICCHAJCUyIoIegCs4cfwoHjy4L9k9Ex/EbHweFBSESxcv4OlT7xhfQAiB4OBgnD59Egf3/43bt2+CP+CGf+AvnJ/fixe4ePE8fH19IMQ/JIC6fT0IqHeiIqAi8CkR4M8RXb92EZMnDJWLk/v1bocd29ejQqUqqFy1JgwGA+7cvoGd2zeA37ziMeHBvduYPmmE/LDgwL4diCwdwm+1GyN/waLyC9ifsv6vl6WSndcRUa//EQGT0URsfw9++eUHVK/+ExrU/w0//1QefXp2kf80TwghiQjtMXbUMNSq+TOmTZkIk8kk8z518gQa1PsN9evWQLOm9VGrxs+YOX0yiPrL8IR2Qgj5cHXv1gG/16qGpYsWSMKVUFzVT0VARUBFQEXg/0OAJ5c1azfChKmL0b5TX3TrOQTTZq9Cu4594ObuQZNbE76rWBnT56xGseKlpMa9ZbsemDh9Kdp37ote/UZhxtzVaNKiA3gtj5nZ0/9Xpf8rtUp2/i/4kmbiw4cPoEf3Dnjh44O2bTti+Mhx+LFyVezZsxOXSYujKBrq+BocOLAPK1YuIS1OEFjDw33dZDLjwoVzcKeHZezYKRg7fjJSeqXC3DkzcffO7bcSGEUoWLtmBXbv+hOBAQEICgmShOr1FlCvVQTehYAQRJr1BiLlIdQnAxEVFfUyuhBCquJDQoJlnzXo9RQmyL37p9dHU36UhrSYfP7u2GroPyMgaGJkRnh4mMRVT+0gxNvbQQghNcMhISEICwuVGgQhXsWPjo5GRER4HBchJ05x68H9IDg4SJbHGgvgVXrQFhERIftLWFgY1c0yaSPvr/7H620yZ86BUmUqyA8LpkmbHlbW1kR0LLfu5OSCjJmywdbOXnrY2zsgc5bsKFW2EoqWKI3UadKD//WHDPzMO+Uzl68W/4UhEEIDwZrVK4iUaDF77mJ07Nwddeo0wAgiPAsXr0K27DnpjsxktnqCEcMGIW/e/ChStAT5WX6KIlC7dl1MmzEX1Wv8hmrVa6AyESU9DRiPHj2AorzZJdnv6tUrGD9uFH74sQqyZcuOl0+bJVt1ryLwjwgIIcBaxRHDBqJt66Zo0awRRo4YDG/vxxBC4AyZVQcP7INWLf5Ay+aNMXBAb5w/d5q6mmXx5RsFkPfff+/DoAF90LrlH2jRvBGmTBovB0UhxBvRVY9/RkAIQbLDG3NmT0PH9q1kWwyn9rpw/myCsoG1BVcuX8K40cPRplUTtGvTHNOmTsATalOWGzzJmjVjKjp3bBvj2qBLxzbYSxMzKysrSW7//msv+vftgRbNGlI7NsG4MSNw794dWV4wmdtXr1qOLp3bomnjemjftjmWLJpPpChE9pl/vqMvPYaZ+r9JEjxeasB4x78jS3hcP45jMhol6eTzuGGf8/zNkeVz1uaTla0W9DEIsPB49uwpLl08j9Jlv0OhwkXkDIlnThqNBvnyF4Crm5ucLa9euRT3799Du/ZdkDy5Z7ziYv+RH8+SvB974/Lli3BxcUH6DJnkDA1xNiEEwmk2tXjRXGgUDVq2ag9HR8c4MdRTFYF/RkBD/fPypYvo06sLzpw5hYKFiqBipR/kx86MBgOePX2Kzp3a4uCBv1GsWAnp/ty+FRMnjE5wfZhWq8W+fbtpkOyOu3fvoMQ3pfBd+YqwsbWlZ8L4zxVSYySIQGhoCGl5Z2D2zGlIkyYdChQsjANEKPsRGQkh4iHEKxIphMCTJ940CRqJnaTxLVy4KNKlS48Vy5dg+rRJMv+wsBDs3buL2vA5MmTMKP+RZ5p06eDs7EKDuBm3bt7AmFFD5brB78pXQq7cebBp4zrMnT2d0guSYXexedN6eHgkQ4WKPyAqMgpjiFgdIe029ymKpP6+EARUsvOFNFRiqCaTnRe+vggI8Ef2bDnkzCaWufPRFLMm5+qVy1i/fg2atWiN4iWKy1lBbP2FEFKdvHD+bLSmmVid2tWwn4RZi5btkCFDxnhxY9McP35Umsg6d+2JrNkygD9HHhumHlUE3gcBo9GE0aOGIZzMGcNGjEbnLt3RvHlrtG/fGenSZ8CN69fIXUXNWnWktrJ7z14oX6EiDYK34OvzXPb12HKEEGBT6uiRQ+Hi7IoRI8eifYfO4D7cqnV7uBHh5+chNr56fD8EhCByce8e9uzagRq/1cagIcPQtWsvNGnWktrmGvnvxOsE49zZMzh54ji69+iLLt16oUev/tRu3+PPbVtx88Z1ig8olG+Fit+j34CB6NN3IHr1GUjk9Fs5sbpx4xqeU/s2b9GGJmadqB27IE/efDh27DCRVgMyZ86KCZOmY+Cg4WjdrgPad+wiJ1tnz5ymPvEVDZ/v10RfdCy1tb7o5vu0lRdCIDIyEmzftrGxoZnRm+WzbXvtmpWws7VDkyYtKYIgB/CekkNuZsh8wmgWJ4SlC+7fvw+PHj0EEyoZJ2YXFBSIVaQlypkzD36pVpMEFNnLKT0oMwE6j4mnHlQE3oYA9ynvx49wYP9efFuqDDJmygw2T0RGRUHRaMDhLkRQuE9fv3YF/n4vcOfOXfCAxlpJy2JM7nSWElirXM7ggQAAEABJREFUw9rIS5fOo9L3P8ErVRoEBwWTSSQaWq2Guib3dktcdf/+CAghcPPmdSlfSpYsTe2ig1anRd58+WFvb4+jxw8RedG8ytBsJq3wBaRIkQK58+SFyWSGA2l98+YrgODQINy+exMaxRJdH61HeGgkERi9JD9CCPk+BJNVNrlcvHAe4WHhuHvnDh4+uI88efJDS21pR+WmTOkFnU4r5V1QcKBsZ+4XKqG1YPul7GO6wpdSXbWenxMBE2luXFxc5MzmMQ0eihJfqPMgwLOpPbv/RLLkyaVdfN2aVXj48L60gW8kbY+/vx9YgLRu2xHLVqzHlu170LFTN/n6+pxZ06RAEULIAUOn00mTw6GD++Hu7k7q5HXYsG4j+LVzHpQ2bNggBePnxEQtO/EjIITAvft3ZV+5RyanPr26y7UgXTu3w/p1q+T6i1y5cqNDpx6kJTiGNq2bonWLPxBCZLwj9U0vr1TUL1+RHb5jXufDg92pU8fRtXN7qaXs1aMzdu7YDjbrcpyv0P2ntySEgB8RTX7umUzwB+q4QEcHJ+isrBDg70+TnVcmQm6RF74+0sTkYO9AUcmHfm5u7uD1OCGBwVKOQJixgWQPr8Xq2b0TFs6fAzbHC0pRoFAhOYlasng+2rVpht49O0tTJGvohCBCRDLv+vWrWLpkISaMG4mJ40ZL8xqTXKPRQDmovy8FAZXsfCktlQjqycLdM0VK+fYUv5HFpIOFCquWmeiEBIfIxZkpUnjh2dMnWLxoHmllluPB/XtyxsYamhcvfKUAYoHGjm3n35T8lsiMB3gAMcR8jTP2jQijwQhPmrkxuVlKAmktaY18SO3M6y/Wrl4B/taPECy2EgFAahUSJQJCCLAWkfuvL5lhU6VKjTJlvwObp0aTaevwof1ycCxe4htoiWCfP3cG10jDY2NtK4k5p4t7Y0z6eb0Z+7FJN3PmzPimZClcuXIJbNri70BRJ+dg1X0gAqw5ZrxZpnDS2HMtaeAMekM8sgPSzUREREDRaCCUV0MZtyG/vckaaEcndzRq3By169RHwcKFERoaiqlTxmPq5PFSy+Pk5IwcOXNTcwkcO3YEN0izZGdnT5ocHRFcrgHw8P597CbT2p/bt+I+yTIzlevn5wsuwxJD3X8JCLzqIV9CbdU6flYEWMh7enqiYsUfwWr8bjSjPXb0MG7fugVe1Neo4W8wmgxYvmodVq/bgqUr1mHO/EUoXrwkypatgDnzFoMHmjVEUjZuWAte98CDz65dO/H8+TNkz5kL1tbW4MV//AbGnds3Ue67iti4aSdWrN4o85s5exayZc+BKlWrYeac2XBydiahRNO5z4qMWng8BBLhhUKDoRACtWvXQ/eefcGaxYFDRsJMM/cL58/Jt7TatGyC1GnSYsnydRg/aQbCwkIxsF8vXLt6WQ6Gr25LgPNj17RZK3Tp1gPt2nfBoMEjwYPhlUsXaRxW+yQ+YrO1tQUTHDYxCiEk7gbSoOgNBvnFXp4gxc3W1s5Oaux4khTrz292sqxycHAkLbQzqlevidZtOqBtu84YOXoCihYrITU9vj4+YPk1feoEfPttaWzauhuDh4ySWujevbogPDxcll/mu/KYNnM+1m3YjuEjx+P5s2cYNWIIovXRMjy23P/sqI7S/wq0Koz/CoxJJxOtVoc69RqiZs3fcfzEUdSpXR1Vq1RAty7tiLwEI2P6zFLAuLi4wuLcYe9gT36OcHZ2pUFCA7aPd+vaAeXLlUCl8iXla6YsgJo2aQE2AZw+dRIb1q3G3Xt3SMDZwNnFJSYvVzpPRn72cLB3JKKT7NMIm6TTvF/lnfLg6ebqJvsKrwGj0RSC7pRNozY2tnKGv2bNCvj4PEOfvoNo4CuFunXrY8Dg4dL8dZ7IEA+eQnAqUB8WcIkh2SEhIXStBQcl90wOrVYj/1cQZa/+PhAB1piwCSpaH4WnTx4jVrvj7+eH6KgopE2fnnIU5GJ/Ah7uHvDxfU6myGBqA4Wa1oyn3t7Upga4J0smrwURXcQkc3V1hxdp9lgjZCSiu3vXn1KrN4iIb5YsWVGXZNtvterizOlTuHTpgqyDtZU1nJ2c4Orqiu9/+FEuYL5166YkPUx4oW5fBAIq2fkiminxVJIHjuTJk2PQkBGYv2A5BgwaBv7WzsTJM7Fq7Uakz5gRPDDE1tjGxgZ16jTEb7Xr0qCggK87dOqKKVPnoEnTVuCZ8USaRU+dPgfuHslknJ8qV6UZ1Djkz19QCq3YvPhoTySnTduOqPJzdfkdB/ZTnYrAuxDg/pgpc1Y5yB0+fBC379xGcHAQdv65TR4z0yCnUSwDpZ+vjzR1BAUFIzgoEDzQ2ZP2wGg0yjVo/Lp5REQ4MmfJBtYcHNi/j8y098EDMq9Js7WzB79VKETM6Pquiqlh8RAwm8zImjW7nMhs376FyMRTPH/+HDt2bJNy4GfS5oaEBFE77MLxY0ehaDREPPKD/4XM3j27iPAE4c6dW+Dv5mSh9smfvwB4YfrVK5cRFBiICNLUXLhwlojMSeTKlYfIixtpok1gzdGzZ0/AJjReuB5OGj2dzkpO0O7euYOjRw6BTZ7hYWG4eeOazJNN6+4e7vFkHdQtUSOgkp1E3TyJs3I8eNja2qFU6bJo2Kgp+LXNKj9Xk+tuOCxurVntXKpMWfmqJ2IGAP5mxU+Vq6BVm/bkOhBxqRYvLZupqv7yqxRGr+fHZq5KlX5EwUKFVEETF2j1/K0IMEF3c3cnU1NnPHxwD906t0NrMllNmjQW35QsTf24nFykmi5dBgwbxh8cbIY2rZpgyuRxKFSoKAoXKSaJz/ixIzFr+hT4+vrKD1s2btIcJ44fQ8f2LSm/P7Bg/hxUJRJesGARqNuHI8DtlCFDRvCzf+jA3+AFxfwRvx3bt6J+/cbIlTsvnjx5ghnTJmHRwjngNTPcPuXKlSft8HRqs6bo0qkN+IOALJPcSetz8uRxdO/WAe3aNEe7ts3BC5SDg4LAC5AdHR1Rpsx3sqK9e3ZFh3Yt0aFtC2zdsglMrLJkyYIrly+ib5/u4PTtKax3r24IDAxE06YtYWfnIDVHMgN1l+gRSPxkJ9FDmDQryILJSLZ0JiOWc+NbH3yOwy4Wqdj4QgjpZaRZM/vJC9px3Nf9yPvlz2gyqkTnJRrqyfsgwH2qQcM/MHrsZCLKRZAxQ2b07NUfQ4ePAb9aXKRocSxcshK1ateTxDt1qjTo0LEbho8ah1Sp08DB0Ql16jYk14BMWC5Sq9C1W2/ScI5ETtIS5MyZW8bt2WeA/LBm3P78PvVT41gQsHdwQIuWbTFs5DjkzpNPEpyBg4ajQ6duYGnh7uaO32rVQY0atUkGGJEipRf69BuMTl16IE2atJK8jKE2rvLzL9Dr9ShatAQaNGyC9Okzyre2qlWviSnTZuPHyj/Lxc5liSiNnziNzFNVSKPkgMyZs6B334HoN2AoWLtTslQZdO7SU9aDP5j6008/g9NX+/U3Sm+wVFrdfxEIqGTni2gmtZIqAioC/y8CvN6MB8FhI8YSMRmLxn80Q7LYdR0CyE2agy5de2Ls+CkYMXqcHHS9vFJLEs8axabNW+H3ug3An05gMmNDJtq69Rpg5OjxGDxslFz87Ejagv+3nkk5PePKLx3UrFlbEtEhQ0eiarVfwSSIw5xdXMAatZ+qVCWyYyKozEhNZLRZs1ZEZCehF5HNkqVKQ6vjt6nMSO7pKcnOyNETMG7CVHD78leZeT0Q58eaZ36Bomfv/hg/aRqGjhiD2r/Xkx+GZILsQuXV/K0WhgwbLT8u2KNXP6ml1mq1VPbn+amlfhwCKtn5ONzUVCoCKgJfIAJ6mu3r9dFyIXxkZKQkMrG3wdpEfl2ZP3sQHa2XazjMZh5Q+eUqs0wTHR0dLw1f6ylPPnJas9kcm516/EgEGEPGMjo66g3MY8MY89jsmZRwW3K7cTo+xoZxfM7HGKOFjo0XG85Hjh8VFSnJE7cjO07HYXyMiooGv+3F5URFRdG5qtFhbL40906yw4+t6kjQUasmBRzoNtWfioCKwFeBQNK7CSYmb7trDmP3tnD2f1c4h7HjeKr7MhF4J9khza60k6pHJAkcoG4qAioCKgIqAioCXyEC7yQ7FQsnQ78G2dG7XjbVvRWDrITNl+86/JoR1jqFbN0KHB2t4KS6JIFBQu1sZ6eDIgRsrbVwdlL7QkIYJQ0/a9jaaKEoAtwnksY9J77+bkdtIISAh6sN0ns5I52Xk+r+AYP0qZzglcweGuUVxXl1hjc3B1stPF2tkczFSnVvxYDx+bJdcmpjd2cr0PMEXnJgNJihuqSLgcnI61TMMJnMMKh9Ick+CwaDSfYBM8zgPmFQ+8Ln6QtGs1xLodEo0FkpsKJJqer+GQetVqExTSB2U2JPEjruOe2DYUtvYNTym6r7ijEYuewmpm64i2i9CeERejx8EoIH8Zx6nZTweOYXAQMJWP+gSDzwVts+KbV9vHultn/hHwkmOc9fRKh94TPIxPvcBgERMNEs1C8gktogWJXN79EOjNtTnzAY5MTNwm7eSXZCIgx4Rp39eWAUVPc1YxAJ36BoeqAAI83mo4j0ROuNRH5UlxRxMBiMpOEzS0ERrTeo/SAJPws8WPDCXD5GJ2EcPue96w2kaSXljtoGHzYe6SXRIeAsXAfvJDsC9CdA+/dzFPWD4yJmSygtB73uz37/5F5PE/dapo25/7j+cc9lHNol5Efe8X7x4nC+7ChGXP/Efy5ku1G15Y/NWfLkPXdCiPeM+WY0Id4/rRACQog3M1F9VARUBFQEVARUBN6BwDvJzjvS/StBvCDWwVYDO2sNlNcGMSuyt3EY2yZjC9PF+NlTfE7Dx4Qcx4tNE3skLSC0GgEnOy1cHHRwsNEkOHBak02Uwzh/ISwDK9choXJi43DeXF8ne0ve9m/JO7YuX8NRCAGNRgP+/gT/ryCT0QglzmIw0KYIhcIN0tHly58QQmIfFRUJ/n8zBoNBXr+M8NqJEEJqGiLCwxAeHg6TyfTO+K8lVy9VBFQEVAQ+BwJqmYkIAeVz1IXJAS9+rlshDTr/lhmtqmZAplT2L6vCZOX7IsnRhcJ+LOopSQqTiZqlvdCpZma0pPitfsmAttUzok21V46v2f1QNDlsiLS8zJBOUiezRd0KadHt9yzoVS8rOtbIhPIFk1GI5cc2UVdHHZpXyYCOVAbn6+GkA5dbrWTKN8ri8Pa/ZoKXuw2ypHZAw+/ToEcdS94dyL9sfg9oFBqkLdl/VXuFSA3/I8U/t63HzKmjMX70QCyYOwUXz5+W9ymEgKJocO3qRcyZOR5/7d0OvT4alk0gKCgAO7ZvwKRxQzB2ZF8snDcFt25eeyuBefLkEdasXCjLGT+6H9asWgif50/fGt9SjrpXEXg7AkII6qOKdEIIvL4p1Mdj3ethsddCCJme4wnxZh5Qt/8LASHe3j4JZSyEgKA0r4cJYfHnsFgH8osbj4XMXOIAABAASURBVNsw1sX153MhEkjPAar7ohBQ/t/amuNkwISB7btxvBI85TSZidz8VNwTpfJ6gF9xL5nbTfY/JkKsgcmXxRnf5nVHAToy+SmVxx01y6bCt3QslM0FfF2+UDJUKPzK8fV3RGDyZ3YGp+Fy2LEmp8lPaVGrnBeK5XRFvkzOKE1kpPEPaS2EhCIJCNQolQqVqU5l8rujIuXt7GAF1uoUy+UGzjtuWXxevqAHUhGJ+qVkCvxKRKxwNlcUyuqCcgU80JoIWd5MTnL1foIgfKGeQgg8J6IxZkRfDB/cHfv2bMeVS2exZvUi9OjcjEjLVbCmZ9XyeejUtgGWLpqBk8cPEdnRyzs2m03YvXMLpk0cjls3ruLJk8dYuWwexo3qh9DQYAghZLzYXVRkJJYtnoUlC6fj2TNv3Lx+FTOnjMLiBdPB/yVZiPjxY9OpRxWBtyGg0WqpP0bD1/c5ggIDKZp42e+EEOB/BcAaRB+fZwgNCQEPgkIIivfqx3FYwxgY4Ad/vxcwGt+tnXyVMoEz1SseAkII6HQ6hIWFIsDfn55zk2yDeJFeu9CQltlI2mWWIdwucYP1ej0iSCsc1xlJm8xxhBCyvUNDQ8DtHUbH19tbHx39RnqWY5xedV8OAv8X2VGoo7ja68gkpCVNigYZUtgho5c9bMnMREF426ZVBAoSKWDtDmCGTqsgDxEQexstXVlSsWgRsPyl97RDtdIpwWaih88jMGntHUzfdA+T193F0cv+0gT2Iigas7fex7SNd7H16DNERBkpNeVlBtJ42iJ7Okf5HZntR5+j77wrWLb7Ea49DAGTKzPtclB4JdImcb25VIXqyOecz5Yjz7B8z2OZZsXex7j1OEySJF7/FBZpQKTehF0nfTBgwTWK8xB6gxmuTjrkTOsECKoAvp6NTU5/blmHA3/tRPXq9bBy/T6s2XQAcxasR/lKVQACjcnN6hULUOa7H5DSK40cWBCzMRpZs+bE4BFTsGjFNsyctwa/VPsd169eIk3QJbDQiokqD4pGg5LffocpM5Zj9sL1mD5nFfIXKo5TJw7DP8CXihMynrpTEXgfBPSkYdz150Z07dAETRv8gtbNfsOcGWNpUH1BfUkBD3asRezYpj6aNayKdq3qgIl7eHjoy+z5H9EePfy3JPetmtZEyya/YuzIfmBiLsT/JVKR1DchBPxe+GL65FFo16I2WjWtgUH9OuHG9ctQFE2C8LD8vnH9Cvr2bItBfTvC+/EDCGGRC0FBgZg2aYRsx3at6r487t6xGVZW1kR2A7CQtNIdKKx5o+poT8f1a5YgKipK5sFEdtL4IWjXsk5M2joUpw4OH9z3hqxKsHKqZ6JB4KOfTH5rJ3UyG8zqmh/Dm+fEgEbZMLZ1boxtlRuD/siB3BlooE/gNs3k50ZEIHtaR7AG5/rDUISEGyRRypbGQb4NRFFe/uxsNKjyTQpkIhLFhGbutvs4ftUfO048w7oDj3HpbjARJDMCQvTYduQpNh56gtM3AmEwckmWbGx0Gug0lltl8nLHOxzL9jzC+NW3YSSi42ivxY+k0XFy0Mr8gsIsWghOrTeY8PdZHyze+QCLdz3EdiJSrMHisKOX/XDzUSgW/PlAki+u17nbQWACxOHRJhMdBLmv4ycECyIfHDqwG3nyFUSrDj3g4OAIXreTKXM2dO4+EJkyZUOWrDkwYuwsdOjSDy7OrmANTCwCCuWRv2BRFP+mDEwmM1hQ2VEeWprJabW62GgvjzzDK1WmIrLlyAOejSmKAns7exI0WhJGCQu/l4m/rhP1bv4FBHx9nmPHtg000FmhfMWf4OzsQlrDmdiyaZWc4T+4f4c0j5uRLLknhVeRfW7mtDE0uP1FfU4DMz3TB//ahWGDuiGAtDplyv2Iit//AkdHZxhJuwOSRv9CNZNsFkw2F86fik0bliNr9lwoWao8rlw+h6EDuyGYzN9CxJenrEVev2YpBvbtgBPHDuDunRsIJy2OEILkg0BERBguXjiN6KhIZM6aHRkzZUWmzFnh5u4Blj23bl3DcUqXOVtO/PxLLbBsnz1jHC6cO0ntrUVYWAguXzwLjVaLzFks6TNQHs4s12jsSLIN9QXeuIUBfEzFiUtY6RTwx+hypndErvROeOYfBR35sRmpcvEU0JHGxkCkI65jWZDO0w6pPGxIA2LCSiId95+Fw9FOi2I53EhLE78ymVLbS3MW58HamFPXA6DVCPBaGmvKX6MImYD6Nrhs9udw6RmzY5IUGKqXV1W+8UT33zOjUhFPgJNSh82dwRlFyAQVRHE2HHiCsAgDYje6TZpRCOlobJZmsCxkgouIMmEnaXOYPNlYafATkaXmldOjyU/p4Oygw4Pn4Th7I+iN+8EXvAmh4MWL59KMVaBQcdjZEzkl1THfkpGOGo0WCpERr1RpkTNXPgghSHgw4eMYrxxrh9iEdfzofqxbvRh7d29F/oLFkJUEDufzKqblLCI8HJcunsGRQ3+RWWwWrlw5jzLffQ8XF1eYaPCxxFL3KgL/jICrqztatOmGAUMmoFO3gWhPhDylV2qcOXWMEpuRKnU6dOkxGH0HjiXyPgjNW3eBNWkAePDTanUIpAF36+Y18EzhhZHjZqNtx96UX1e0pDxtbO3kAEoZqb+PQEAIgQf37+EoPeeVfvgFffqPlvj+Xq8ZHty7jUMH90BDmt64WYeR2enxo3uoWbsRvqvwEwUJKXfoxPIzQ15zftzmfQaMRu/+o1CsRGmpcWYC07PvSHTrOQTNWnVG46btwPLmMWmH4pZVrUZd9B88Hpb0o5E3f2FV9uDL2pR/o7rhUUas+dsbfeZdxfZjzyAoUyY/KdxsUCKnG3g9Djtef8MEKRdpfXgx8OV7wTh1MxBX7wfTrMiM0vndwW9LMSGiLOTP0VYr39ZiDctNMh8x85YB77mj5wcPfMKxnkgMa3/YVFaU6tS2Wga5SNnV0QqVCieHh5MV1v79BNcfhUAIIXOPWxafO9vp8H0RTzCJ47pfvkdkhhBM4WaNat+mlGuK+L41RMACSdMUHv2KNMkMP8XuPyxDISITFBgg1zF4eqYkwR6fyPBMiYvn49tIiBACPBtbtXw++vdqi8kThsL3+VMUILJjY/PmYCGEgK/vM8yYPBIDerfDIpr1CaEgV+4C4PpweapTEXhfBGzt7JA9R244ObuQzDGSRsYJTFK0Wi31Z0j/bNlzw5aIC/dhFxc3WFlbQ0Phgp7rJ48f4iFpfypXqYnkyTzh5+cDg94g4whhkRvvWxc1XnwEhBC4d+8WoqOjSPNbFopGI7VtuXLnp4mVvSSkikYTL5GrmwdatO6K2nWbwM3VwxJmthzi7qMoz9CQEBpaBHQ6awghZDBraDJkzELtbS/b2M/XV/o7kabObH4l36JIM8TEChCwsrKCEJb0ULcvBgHl36hpIA3sbDqKPfKXeLU6gcLZXTCseQ4MaUKuaQ50rZ0FKd1tkD2tA3SkldGT1uf7wp5wc7SGkdQm7kQ4Cmd3leex9XoeEIUgMis52evQoFJque6GlDGxwe91NBrMpIV5jh6zLhMZe44Qyo/XFZXN7yE1MbkyOMInKEo6XrxsbWWBJQeZ2tyIDHF57IrmcEFOisv3d+yKHyJIu6NQp/d+EYGlux5hwfYHOHk1gDRWZuTL7Iz21TLSw6pIIfpeFU30kczQ6azonjSkKg6HoL8PrbKZgLSzs0f9Rq0weuI8DBo6EZmz5MDMaaOxZ9cmylsbL0uOnzx5SnTsOhBjJs5HV5qBaUmDNHp4b5oF3nljphcvsXqhIpAAAtyn2DFZvnP7Jh49vIv8BYuDHmUZm8P4hMMvXzoHf38/5MtXWJKjFy98EBIShL/2/YmmjaqhVZOa6NSuPvb/tROKIjiZ6j4WAWqAoEA/KQPc3JJJzQm3hZ2dA7Qkd4KDAmE0GOPlriHyY0caZkWQnE1gfaSgNlEUjdQg8xqsts1/x8K5U8BvhAohpGy+RGaqlcvmYsTgHpgxbRQKFy2JgoVLkOZHT31CgInuwjlT0LRhdfDanaWLZ1EfCIa6fRkIxNbSMqrHXn3kkc1GttbU2WggcyJzlMK5Erv29o3A/rMvsP/8Cxw49wKHLrwA/6+t7EQiuKhCWVzQoUZGfFfQA0x+2K9kbne5wJmS8yXYxLXzhA8RCyOK5nDFr6W8oKEOHBsuI/3Dzobqxt++ueUdiknrbsuFzEygNBqBPBmdpebIw9kKPX7PAn593I1IFz0H6FAzE8oQITKSqcSZyFbVkillSffI7HbxrqWzc7zwSCP2nvHBqr8fY+zqW7h0N0jGy5PJCbaSOH1IbWXSRLnjmS7PpHhWfPP6FSmMhBBSIAghoFDDCyHAW8yBT6VjXyF4DxkvfcbMKEJCpXLVWmjdvidcybzw194dNKuLluGcl0xIO2sbIsg586BIsW/BKu16jVoiMMAfp04ckWVTFPWnIvBBCCiKBs+eemPZ4pnIkCELSpetCAOZYmMzUagvX7tyEevXLMY335QFm1l5vQ6v/YiKigIPvPkLFCVz6g90HoSRQ3ri1s3r0Gg0sVmoxw9EQFD8qMgoIiBmwpEHEfKgn6JRoNVoiOgYpMzBe25MlBwcnPBztVqo9mtdqS2ysbXBwvlT5KJli8ncLN8K5c9jnD93isYhHZWtIYLrK2WLM2n2qvxSCz/9XIPSlwZrAGdPG4u5MyfI8PesihotESDwqkf9H5VxcdShSokURAySoVKR5NRhFPA6mesPQjF5/R1MXX8XUzbcxaJdD+Vr345EiO4/DceS3Y+waOdDebxyPwRsKsqWxgGpk9tSh7dUyEjan7/P+eLKvRAoNFjyYuU8GZ1A+khLhPfYF8rqihZVM+CHop7Imc5REi6NQo8WkbMzNwKx48Rz7D7lg31nfXHkkj8iiLxwtsev+OP+0zA6FfIVeH5dXk9aIl4U/fRFJPmDzG461CqbCj8VTyHzLpjVGclcrGWYX5AeBhOfUll8+MIdkx02X+XImRdHj/yNv/ftoNlPNFhosPDfvWMLzZLvE1lhgR9zz5Ln8Tk5aj/O49lTb/jL13WNlNZABCcS7G9LZiweLPwo7CoNNFGRkZS/Ho8fPaCZVJCMYzBEI5oGGzOpmO3tHb5wRNXqfw4EFCIyvPaMP5/w1PsRmDynSZseTGa4PoqiwZ3bN8CfVuDBrU6DFnBzc+cgCEprTWateg1bokOX/mhDRL1+o1ZgM8n5syfUAVCi9PE7WzuW/SaSwRGWTISAwWD5MKktmSC5PSwB77dnGfFL9Tpo06EX2nXqA14HVKTot9i3ZxtYS6chLXGF73/GoGGTMWrcLPzRvD14QfSi+dNhpvGBF57/WrO+TN++c1/07DsC+QoWlbKP0yvUH96vJmqsz42A8m9UwIpMUiXzuMuFv/xKOZunTlwLQEiEAWFRRoREGhAcrpeLir/J7UadCDh82Q+r/nosHb/Ovevkc7B5iNfy5E4mzhiQAAAQAElEQVTvBA2TEa4cjZFP/CKx9ehT8GJg1gyxhoW/ncM8gp4FUBRyvOcE8R2H83qcMvk8wB8BHPxHDtQqlwr82ju/Qr5i7yPM3fZAvrLOr60vIULGWh/q51Q3b1wkDY6rgw78PSBrnYJQuqdjVPcovUWdyhqjsgWSoU21DBjWLCdpqjIhdTJbeS/8CnwkESeuQ/xafblXDo5O+IVmSSzwhwzojD492mDcqP7o3K4RRg7tSQLkOZmXbsuPDM6eMR7e3g9x4/olzJo+Dtu3rIVBr8eSBdPRteMfmDdrImbRLGnKhGGIiAjDj1WqS2D+pHi9urXA5UtnERIciFGUb7+e7bBk/jRMGj8USxbNQGoanAoVKSEJkEyk7lQE3gMBIQQCyCw1ccwgHDm0Vy5KLVf+J2ho0OPkQggi1/cwalgvPHxwV5pPCxYuDiY5PPg5ODiBTSqRkRHQaBQpy1xc3aDT6eiZj+YsVPeRCDC+rmS+Ys0ZT4i0Wp3MidsrKioSadNnghAg3DU0oVJkWOxOCAERcyGEgBBCXglhObJ2nidU7h7JkSJlKkTSRMpIJEqhNnRycoZnilRIR/lXqFQVGTNlw6ULp2kiZrTkQ3nwhM7ESy3ck8PT04sIWDT00dTeFCYLUneJHoH4PeYjq8uvjl97EIJQGth9AqKw/ehz/HnsGVhTw12NHWtinO2tiCwY5XdqLtwOgom0NlykicxEvOCXyYdfUDS0WgFeq8N5PSMNipE62bFr/viTNDDsryEiZEPmISGE1CB5v4gCr5sxUTzOL65jr9M3AnDowgsEheoRqTfBLzgau0iTM3zZDUofBYPRRIKKHKlhmMw89YvCIzLBhRBB47LZDMZEh8tmEnf9USjoKeAf/IP12HPaB8/8I2U+bNLiRc5MnLYceULx8NVtRYuXwvDRM1C8RBlcu3Ief+3ZTs1rRvc+Q5E7T0F4P36IXTs2Ys/OzbB3cAQLql07NuDYkf2wsbXFN6W+g0Jtt4Ls5Pw1ZF4g2m/geFITl5MCxpEIFS/+dHB0hjOpkUuXrYQnj++T+nkqdv25ETlIszRgyEQpoEzUd746gNUb+s8QCA8PA3+xm98AbNayCyrQrJ4XzIeGBMNEwoI1jvxdliuXz1N/Hob8NIvnsLDQUNk3vVKlAZObwwf3gj96Fx4eitOnjiKc8s2duwCRH/N/VvevPWMTPcsZM2WBIz33/B2v4OBAhAQF4sDfO6U2t9L3VREaGoJDB/bi/LmTJH+ZbJol6YgID0c0kQ8zaXyZyERGREq42Nz9hCZckRHhYA3R7ZvXcPH8ablO0NnFFbdvXpXf9+K2jI6OkhO1Z08fI126TJJU8ecFeFE6a5lZq3z71jWp+UmRMjVSeqVGrDZQFqbuEjUC/xrZmf/nA3Seegkdp1zE9E13JKGQJCfm9hWFCIx/BLrNuITO0y/iwp0gICYChz0mctFj1hW0nngBq/Y9xrxt99Fs7DnMoSNrfOg5wOyt99B87HkwSWHiodMI7D/vi1bjz2HMypuIjGZdD+JtXIQ3EaaJ6+6g/eQL6DztIh0vYsLqW3jsE0EzBI5hScJnAUSI+s27itbjz+PR/9i7CsAqjib87b0XdyPB3d0LtDjFocWlOMXd3bW4u7tTnALF3d01kBB3f/LPbAgkEPiBAkHu8vZkd3Z2b3Zv9tuZvQulM7DyJQA2asVttJl4CVM23APXh2k5VyRZeNYffIZuM6+ix6xr6ErHnnTcecoL0eTyojGdyb67kCdfIYyfvADrtxzGuq2H5Af/qlavK2e4/FrnyvX/YNue09i07Sg2bT+GnfvOY/joaTSgGPBzyQqYvXAD1m05ROEg5i/ZJAcdVlSKooB95LMXrEfWbDmlwqnbsAWWrdn94gOGhzBhyiICVfmJl/67k6t6Q59XAo8f3cfe3VslcLlw7iT6dv8Tvbu1xMC+HfDg/i3cuH4Zhw7uhRACe3ZsRs/OzSm9FcaM6CPfCkyRIjXKla+KC+dPoQelDe7XCXt3bgG7SnLkykd98k0d9Hnv6Pvizq/+V6xcE6dOHEavLi0wiOR75NA/qEc6IEOmrHKd1dyZf5F1eLbUDSHBQVi0YBr69vwTh8itzl9BnjltDMaP6Q9/Xx+cO3OcrMgtMbh/J4wY0kN+j4eBTfOWnWgi5UDlHMGA3u0wsE97jBjcA6OpnRVFI8vj44mjB6idm2HIgM4yfThZs3W6GPzZrgeNHbFg6/tqgTfvRgghnwchXh3fpEoYIwTTMrwQCROS8Ipr89HFs6snLjNbQLwCo+BPYIHj6F75kCAY6SqarCdRZF2Jn5ei5Y8tLJHRejAvDnHnnChFRgyiCFzEEA+O48B8mJ/uhZWI414PXBcjEQaF6eATGC3da8SKOqvk+jo5YtjS81oZXGYE1c1As7/XMzD/cHLXeZK7zYcsW3yPhO2og7xO+X1csyz1ej34aGllBf7ejZZMznFxQghoFAUajSZBUCgOtBlp9sVpzs4ucHJyIRotDRKvgIui0UBLbgEilT8jtZ2pmTmSuSaHnZ0DyVUQvTqoSOGouw+SgIuLK1q16YYu3QfhpxKlUbR4KRQrUQZFfyoJtiSmI1dGp6790bZ9LxQq+rOkKfZzGbAry8zMAqZmZqhVr4l8K5AtjJmz5kCHrv0kT61WK5+JD6qQSpxAApaWVuDJTd9BY5GbJlQ5cuVFp24D0bRFBylbR0dnNGjcCr/XaSx1ALsPMxIIypWnAOrUb452HXvTZKo8WX/zSh2Sr0BRNPrjT6RLn1nqmmo162PQsIn4pXR56VIvV6EaWrbpiiw0sXJyTobfazeW39PhCRvrM34zi1+KSJM2A5xdKL3OHxgyfDKKkHWb0xNU/ju9iImJltZ5ttBziGYL2lvuNVbHC7J6hiCYgKher6NxVnkL9ZeN/uhaCMrpFxKNjYc9wC4hXwI6coB/j/qL96D5HCQ0BtNACXxs+e/Kx2n/lT++wY2BCAfSRB9ce87H4f0yGqmI2PB+9CqVKoE3JcADWp36zfBH83Zo0rz9y9CwyZ/gxfcpU6dFoyZt3kivVfcP8NoOA5mY7cm1WqnKb2jXqQ/+bNsdFci94uDoJPvnmyWqMR8iAdYHdnaOKP9rdSlbBqb8sUBrcm1zGh8rV6uNEuQKNxj0sCBwxPLntuQ25cXiTahta9ej9rKzhxNNqKrVrCdBUEcCsQ3/aC1BlJYmZ8yPv5Rdhfjxt3o6EmhtSMAod96CEiiBnPM8wapZqwG1dW906NIfDRq1RM7c+WmCpvmQ2/omaYUQeOr+GLOmjcXwQd1lGDawG8aPHgBezxYLbBLeGv+vw4XzpqBvjzZkEW2OGVNG4eGDuwDxQhJvBFk+rgYKVd4/OBrTN93Dkt2P4U1ghwf8j+Om5lIloEpAlUDSSkCId2mw19OEHPAUTeygxwMn1O2FBP7rge3uRigaDRIbUIXgtuDwrnISprMlWUuWNyEonizFr+eMTTehMVkkAloFtbUWnB9ILB3f7cbrnfbt3U7u3Uvk5r2N+/dvy3VNMVHRb9wzPwMb1i7BpvXLoVE0JCkF69Yska/5h4WGED3JnvZJ9VP+S8EMeMxMNDAzUeSCU6ibKgFVAqoEVAmoElAl8H1IgHCnqamp/KDr2s3/Yu2mA5i/ZAsyZc0u3Yiv32TpspUwY+4qTJuzCtPp+GvFmuBF3d5enokC19fzf87r/wR2PmfFVN5JIwGe9BgMse4iRupq+BFl8arvcX/4XH1A5fu19y3qB9wBXhzU9kqa9iJTE7VA0v5ioqPkG3EaDVu4NOThIxT0WpWEEMiTtxCyZc9NVjAFQgiAfqZm5mDARJmQlJuSlIWrZX89EtBQT6B+CUtzDZK7WFGwVoPLjykDJ3tzaKhD2FqbIUWyH1MGyX/Qto9/3ymSWcHezgxa6guO1CfUvvDlnwWWuYOdOQTpZyTFRoNCdHQ0pk4cjv6922Hi2IHyTUQwisGbW3RUFC5eOIM9O7ZiyoThOHXiEEqXqQhX1xSJWoLe5PD5YpJKhJ/vjlTOHyUBdklyRnMzLVydLb+ioNblS7eHgy2BHUXAxspU7Qc/+LPAgFejEXCwNVP7QhL1BTsbsyRbJuLs4ir/TQ8vBOfvTe3ZvRW9uraQH+SMXcPEo8aLIAQCA/2xbNFMjB7VB1s3rSKLjhnSZ8wCUBqSeFPBThI3wNdSvI5dV1SZmBgDgkKi1PADyyAsIoZmYUZERukQ+APLQX0OohAeqZN9ISw8RtUJSfAs8PPHbfDCm0ga+sv92G3JX5MePno6+LtncxdvxLCRU8FfEd+2ZS34e0NCiFcVoko6ODqja8/BmDlnNUaNm4W0aTNg2sQRuHDuFFmLNa9ok+DsuwE7SSC776pI6qfyfgwGA6Jj9Gr4gWXA35Rij7yOvzcVrfaFH/l54D7AuoGPP7Ickuze6fmL0elhpD+poL/wjrGM0WgAf2tHkC8tW47ccHVLIS047N4SQkBRFAgRC3p4bU669Jnk6/3lK1ZH/UatZN6rV86/pEESbUoSlasW+9VKQEB8tXVTK/YlJKC2/5eQ8rdRhtoXkradGEMI8VGt8EkqHh4WiuioSGi1JtIyw9/X8XruiRQpUsPS0lr+n7lLF88iJCSILIAGPH54H6EhwXIMMRJKDg4ORFR0FOztHKk+SXcfVDhUsMNSUMPHSYAeQiOhfrYGGaljv42JgWgSS+d8BrIeJJb2Nl5scTBQWR+S52281HhVAqoEVAmoEkhcAnq9DnNm/IV2repi5tTRmDR+KIYP7k7ERvCHOVkH79u7Dd06/oETxw9KCw7/A12mnz55NMaN6o8ZlC8NubKKFPuZwJCe8ibdTwU7SSf7b7pkXx9v7Ny2FRPGj8GgAb0xa+ZUnD9/FnoCL3E3pigaHDl8EGNHDcfuXTviouHv74dtf2/GsKED0Ld3V8yYPhk3rl99mf62EyEEdm7finGjh+HYkUPSfPo2WjVelUBiEhBCyH6jxDO9I94mhKB0DQUF77MJISQt88O3uH3FdRbURixXId7DIkA0TMshwS1RvBAKRCIhAd2Li1i6N8sTQoB5cxDizXR8h5ui0eLnUuWQIlVaXL50DnduX0Phor9g8LBJ4P8DpzfowECmTLkqSJUqPczNLcht1RJp0mXA1Svn5FeW+evXA4aMR+o06QnsGJJUSkqSlq4W/s1JQAgB9yePMXLEEPTs0RlnTp+Et9dzbNm0Hj26dsDdO7dIKWikyfPZM3cMHzYQ06dNxN7dOxBnxdm7ZxdmTp8CH29vhIWFYdmShRg2ZAACAgIgROKKRKPR4DoBosED+0hwdPDQAVnGNydAtcJJJgEeqCLCw3Hv3h3Zl/z9/KivKrI+QgjqTwrYRH/92hU8fvQQRoPhrf0RtHGfDA0JoUHgNvX72/J/LXEZlKT+/oMEWIZs9X3q/gR3SJ+EkIwZ+LyNJdNHRUbi3t07ePjgPqLJaCV0mwAAEABJREFUbcJxTB8ZEYHnnh7wePY0QXhG1zExMUzyMnCZnh7PZB/gc5lA/YJ5BQcF4dbNG9R37oLLEiJxPSXzfCc7vsMiDG6GT8LYiXMpzEOfAaNRsEjx2OeCzOz8v8P6DhyL7Dlygy09JctUxODhkyXt2Inz5P+Qy5W7wFchkdgn/auoilqJb0ECrCA2blyLvXt3oVOXHli0ZBVmzlmIxctWo2HjpuB/lMgfj9Lr9Zg2dYJUHFmyZoN0PdEN8gNUqGBhTJ4yE1Onz8bEyVNRt15DXLt+RVp3NDSbILIEP1Y2oaGhGD1yKCwsLMhfnFICpwRE6sXnlMA3z5uBya1bN/Bn6yZoVP93NPujHurVqYGNG9ZIJR1OIGjE8EGoU7s6/mhUB/Xq1kSfXl0RFBQYq9hfk4AiFBw9eljS/tGoNhoQz3ZtmkuQxP31NXL18j0lwHJ1f/IEvXp2QZ3fq6JRg1po1aIxTp88Dm7DN9gQ6Dh75jRaNW+E+vVqUjv8hh7dOskJmVarxb5/dqMBxdf6rTJq/V4FtSnwdUOKOxWPp4mJCY4fO4qGDX4na3N3PH8e+8VfvU6HXTu3o0njuhTqUH1+R/9+PeHl5ZVov3ijft96BMmXFx3bOzjB1tYeLFMGNXG3xX2d04VgzR4by9cORG9ja0dtppXPV2xK0u5VsJO08v+mShdCkBXHC/v37UXhIkXRvkNn2Ds4SPNl+vQZ0alzd2TKlJnuSUj31bo1q9CyVVvkINRPkbE/4pEtR07kzV9Q5jM3t4a1tbV8KLRaE6IxUkj444dr+9bN5Bc+gvYduyFt2nRE8CYdRao/VQJvSEAIgXCyIHZs3xrXrl1Fg0ZN0a1nX8TERGHKpPFkPbhJlplbWLNqBUqVLIPOXXsgderUWLlyKVatWPbGoMaD7pWrl9CiaQOEhoWiTduOqFKlupwATJw4FgzMhXil/N+okBrxVgkEBQdh8qRx2LFtC6pVr4kWLf8knfMc3clqHJiI5fcxWeBGDh+Iu2Sta926HWrWrIWjRw5i9KihNMgC6dJnQJWqNVC1Wk1Uq1YDlatWh6WVFe7dv0vtysOfoKMgq7I/WasH4s7tm3j8+KG03lACrl6+hFEjB8NIfz169cOvv1bGju1bMG/ODDnw40fZjEa6Uw50eI8f62zZAO9B+6VIlC9VkFrOty8BRvHe3s+l8ilUqCh4NiQ7Nd2agUz+OpoF8TXPipYuXoD8+QugfoPGrDOI4tWPX1m8eeMaDh8+iFWrlmLrlo0oUqQY8uTJBz1ZhF5RgvIKaZpeuXIJKa2aqFSpEnSv0UDdVAm8QwJCCHiSK+M2WXZ+/rkkunTtjrZt26Jho2ZgF8lzz+fInDkrNv+9B6PG/IUOnbqg/4AhpKuNYGsQ9+n47LmPHjywDyGhIejdZyDaE/2IUePwa8UquHD+LB49ehCfXD1/TwkIIfDg/j2cPXMKLVu1wcjRE6iteqBNu47w8fHG3j075aQojp0QAhfPnyN5P8TwEWPRrUcv9OzdDzUI8Jw8cQw3blxFQbIiDxg0DMNHjcXwkeNoQtYVLi4uMj5/gYLEyggd6a1FC+fBw8MDZcpWoDI0IGxDwYjT5KZnV9jgISPRomUr9O7bD6VKl8MecstznVgnEhP19w1IQAU730AjfS1VFEKQWT8IvM4mmUsyGAxvIn0eCNh0zDOn/gOHwdnZSQ4aQghSIooEL9FRURLgjBoxGGNHD8fDhw+kRYhnzHhtY7fZ1i2bEEk+eZ5ZmVuw9QfER4GiQN1UCfxfCTBYsbd3QKpUaciKc5sAyQVcvHAZu3dtg5tbcrLipIEVWRezZ88BXhsSGhKG27dvE1+BNGnSUV8TdB77E0LIwVEOdHSePl166HV6sOm+Mll3QoKD4enxTPb52Bzq/n0lIITAfbK4RJF+KF6iJPR6HekYIFeuPLC2scEpAh4azauHntv15s3rcKU2zJU7D+mIaJiZWSJv3vxgi9uDB/dk27EOiYmOgY74nTp5CjdvXEetWvXAfYJ5XLp4HuvWrETTZi1RrNjP1Havauzr6wN7B0fZT6Ki9bCxtpf1CQjwJ5D1gHSQ5hWxevZVS+BVz/ly1VRL+oYlwEpdS/7tsPBwUiQJb0SI2Bn0ujUrULhwUQlgfHx8wMqLAysIPVllzC0s0LR5K8yYvQBLlq5G+QoVsXLFEqxftwraeGt2FEWD27du4u+tG1GBzMfOTk7w9QmQC0EjIsLJ9ByUsALqlSqBRCTAA5ojge4JE6cjIiIC7du1QOMGtWiweoQBg4YjQ4ZMNGgpuHz5IkYMG4R2bVpgzOhh+Omn4vijSfMEHJmXVquFq6sbDcZ6aZ1k65APWR68nj8n11g0lRGeII968X4SEELAj8CFVquhSZKLlC/nZCDKeieQAAZbYTguLvj4eMHR0QmWllaxUYRL7R0dYWpiiqCAQAIusRMyIQRioqOldcjBwRGsc3S6GLLsBZPuWSp5tO/Q5YVrKjYPM0yWzA1P3d3J2nQabOHx9fOFP9UjKioSvDid2DKZGr4BCahg5xtopK+liqzonUix2NvZy8XEIFuvEKRdqIJCCOnWuk2ugofkRz9y5F/Ur1sTzZo0wMkTR3Ho4D7wotC7d2/LWXCKFCmRPVsOlPilFDp26go7O3v8S66BiMgIAlFCBhMTrXQj8AyNX1WvW7s6WrVoIuP+/nszWjZriAB/f0lLVVB/qgTeLgEavzJmzozkyVOA38Ly9feVlsZI6m8Go57AjoYsMh44eHA/Llw4IwcyTnv48N7LATOOuUajQaXK1eV6kIkTxqBurWpyMe2kiWOpLyoUNHGk6vGDJCDIOhMl5c0y5qxGo1G2jUbRIIbcTfp4n7bgtMiISHCaEAqTs0qChtpHCIFosuYwDScIIfDwwUP8s3c3uaHKSmsQx586eUK+Udq2fSe4JHOUZXM8FNZBCn4pWQoZMmRA//490KDub2hQ73esWL6Y6EDlaPFpNpXLl5DAix7yJYpSy/jWJWAwGJAiZSrky18Qhw8dIIvLZgQHB8kZz3NPT2wlC4ypqRk6d+6O+g3+QIWKlVGmXAVSLCloJpwcZcv9SmZgW/LL38ezZ89ophUjrT7e3t6kmKLhSJYbnjV7eT0nV8NZ6TLLnTsvuvfoi99+ry35lS5bFvbkkkiXNh3xKwdzshJ963JV6/95JaAoCg10D6Q1Jzw8DIvJmrhsxTqkTZseA/v3wqGD/yImJpr6UwX8vf0f7Nt/HFOnzYa7+xOMHzcKT5+6QwjxspJsncxEwGndhm3o1r03ChYqgt9q1ZHrTMzMzWFnZ5eA/mVG9eT/SMAo3YkGco+zq1wIIeXIbRNDVhgbaxuaKMW6sZmREEK6t8IjwsBWm9g4gF8N1xv0sLOndqC253hGJ0sWzwO/DMHrcszMzEhvRWLd2pXyDU8GRbt37QFPxkJCgmmCdoza/zGykWtzyvQ56NK1lzz/7bdaqFixCtitxhYlfstU8ld3X70EVLDz1TfR11NBVgj8kDds1ATOLskwdHA/9OjWEYMG9kbXzm0xbPBAUlZW6Ehgp0/fQejbbzABlT7Ili078uUvgG49ektAwzOj7l3bS1fBqBFDMGnCOCgaBb/VqiuV266d29C3dzdcIbcC++J5rU7vF/y6dOmOlAS4ipKLoXPXni8V1dcjJbUmX5sEeKZ/6NB++W2d5i1akwvjVwI2v2LIsNGIidFJYK2LiQEPgPb29jTDT4bqNWqhQIFC4MX2/uS6UGjQ5BD/3jJmzIROnXtg9NgJ6NylB548eQIHBwe5Big+3ac6/975sH5JliwZ2EXk7v6YLMVakEKAt5cXAZMIZM2WDbwJEQuC6ECTKDeyyD1DUHAguH0MNCFjkCqEQIoUKcDfSuL2v3HzOk3ONiF/gYLImTM3sRXS3RgWGipdWTOmTcSYUUNxYP9e8GL2WTMmk8XnBIErU0nP7Tt+whQ0b9kaZGxCKtJB6TNkhIHc8lwnNXz9ElDBztffRl9dDXktw7QZc1GrTn2EBAdLS41r8uSYOGkacufORwNIDFjpcFAUjVQWOXLkIiVhlMqjwq+VSBGlwrlzp8llcA5Zs2bDlKmzUbz4LzJfsmSuyJ49J5zI0sOzaOYTF7RacxQq/BOyZMlGPn3yTXx10lEr9DVKQIhYVefxzENaEQV1HY9n7tRXo2Fra4fz585g88Z1cmDlBfTnz5/B1auXCbw4woFct9HR0VizZgU2rF8tB95gsmjyYlq2OAQGBGDB/DnkItmJ0qXLU99O+TWK4KuvE4OdzPRcs7y3bFpPQNMLfj4+EqRERUWhevVaCAwMkO2wZ/dOKIoWufPkQ3BICLZt3SJdYPfu3ZXrcjJkyIS8eQuQjtCD1+Zs3rgebLGpXKUataejjLclC9ykKTPBFroFi1aCQ916jZA2bTqMHTcZ5StURgC1LVv22H0WSGWvXb0Kx44ewu+16sHKykrqtK9esGoFpQRiNYA8VXeqBN5PAoJmuQxeRo+ZiI1bdmLT1l2YO2+JdFmxGyo+F0tLS/Ts3Z9mvj0hhAKF8hYtVgKz5izAxs2Ul/LPmb8EJUuVobTYGRvPqufOXwpWfAx24vOzsbWVrwc3bd6KlJgufpJ6LiWg7l6XAC9q5e+jZM+eC7NmTkGNar+iWtVy6NmzM9KkSYty5cpLYNO1SzvUrP4ralBo0awh+EODjRo3Q1oa/Hx9vDBz2iQsWTQfgUE+ctZftVIZ/FajItFXwLgxw+Wi/Pbtu4BdWTxwv14P9frdEmCZpUuXHjVq/I5Tp06gZrUK8iOAO7ZvRTuSK7sOnz19iqXUBsuXLZL6okDBQihTuhzmzpmGGtSmTRvXwcOHD9CV3E78PR0ukT9SyDzSpc8oLXpcDsezLnJLngLp0meQIT0dnZ1cwP/gMjX1C1vSNefOngJ/hPD3Gr+iZvWK5NYcgZIly6Be/Uaq/mEhfkNB+Ybqqlb1K5IAW1p4ASeDEVYaPPPi89eryIqFB5sY8rnHpbHpl+lNTU3JVG1CZusoOdOKS9frdfI/5XIZcXFxR+YXQy4H5hkXpx5VCbxLAtxnUqZKhdXrtqBPv0HIl68AGKx3694HswmkZ86aXX5ocNqMeahUuSry5smPFi3bYNXazWj8RzNpbXRwdEZbGnBbt+kAe/tkZFHIjzbtOhGf3ChTpjzGjp+CZSs3wMU1maSHun2UBMzNzeVHGtniUr5CJZQt/ysmT52DDp26Sh3h6uaG5i3+pPb5k64NcCF3+pBhozBsxDhp8a1dtwHmzF2C8mQ9Zh3Bbc+TswYNm2DEyHGws7N/qzWGaQsX/QlNmrWU7na+zpo1Bxo0+INcaDlRmkDVhIkzqK0nw57clZz+UTepZkoSCShJUqpaaJJL4FNVgB94Dh/Dj/Nx+Ji8ah5VAh8iAb1eL91Lrf/sAP4AHYcOHbuB190wqOaFq7/XqouBg0dg+Khx6AdN430AABAASURBVNVnAIoWLQYhhBwcGZg3bdoSdWgw5QHZ1dUN3br1wcjR4zFoyEg502e3BvP6kHqptAklwPrAytoaNWrWAn/Ib8DAYaharbpcT8VptuRybEQA9NeKVQhU6mXbuLoll9/IGT5yLHr26o+fir34303EmvOw9a5r994oU7a8pKfot/4KFiosecWBouQpUqB9x67gj00OHjoCtevWh5392wHTWxmrCUkuARXsJHkTqBVQJaBK4EtIwGg0yAFS0WigaDRkGdDRtUEWbTQa6Vovz9kVy6CFg4x4sTPI/PHoDXowrRBC5mUeL0jVw3+QAMuRwSkEIESsbBFv43bhEBcVR88WZj6Pn8Y0HGeM13Yc97ZgpH4QPz9fc+B2BmLrwtdQt29OAsq7a6ymqhJQJaBKQJWAKgFVAqoEvm0JvBPsGEF/RpDpTw0E+L9jOXA7U0N/231Zrb0qAVUCqgQ+rwSSmLuqpT++Ad4JdtK7WeLnXE4ontNRDd+zDKiNC2V1gFYRUCiYmmqghh9XBiZahQz2gFajwEztCz/ss8Btr+W+QK4k7hOqTkganWCiEfQ8CliYa2FnYw5bGzM1/B8Z2FG6laUphBCI25S4k8SOZQu6oG+jzOjZIJMavmMZ9KJ76/BbepiaKGDlZmNlCls1/LAysLTQStBrbqaBrbXaFz7oWWB5WZvGyu1rP/8/zzjrAQsz7gsA94kPksP/4a3yev/nikEOj9lO9uZIm8IaaZKr4f/KgOSU3NlSTtjwYnsn2Dl5zR9z/36MBduffGDgPI8oz7cR5m9/hB85zKP7X/GPO6J1BkRE6vDMKxRP1fDDysDHPwI6vQEBwdF4+lztCx/0LLC8vpXwHs+4f2Ck7As+ARFqX3gPeX1QX3kfftSX/KgNDAYjAoOj4OEVBg9vNfxfGZCcvEmP6fWvHH/vBDvXH4Vg+ylP7Dr9oeE55fH6ZsLu0174ocMpL/x7wYeUmhFRMXr4BUbBLyBSDZ9bBl8p/+DQaLByDY+Ipr4QofaDr7SdvsQzGhoWAx4wQkJj4PsDy+FLyDrRMgjohFAb8JrRkHBuA/V5TFROr/VN7qvBIVHgNyhfGHbwTrCjkO2M3PbQKEIN37kMeK0OXmzU7OTrhBrEjykD0H0j3qb2B+BHlAF4i9cXfkQZJPU9cxPEBW6KpK7Pt1Q+WGBxwqPjO8EOpX+Wn55McrrXgp6ha7zSeGbJpnR2rcSQSZ3zxCWzYYqvOZ3pXsZTgp5odWS6is+OipJWi/i8iDQumzwaKAOXwzQ64sHXMiHejkholmMgXgY6vs4hHuGLU/4eA/NinjHkIuJ6vEjC62l8Py/T6ISvX8gIcUeOoyT547owb+bLIb4cJMEX2AkhoNFowN+gUJTEuxKnJ5YmhICieXdexNuEENBotbIsIQTUTZWAKgFVAqoEVAm8rwQSH6HeN/dH0Gk1AhlTWiNPelvkfhH4PLWzxUsgJoSAi70Z8mayR+l8zvgpuyPSuVlCIesKF2mqVZAltTX4DaLUySxlPoYe5qYKcmWwQ56MdrC10jKpTHO2NZVxZSQvJ6R3s4KpRpHpvOOhk2kKZ3VEmfwu+CmHI9wczTkpQTChcrOntUXBrA7IktoGCtUzAUG8CwYjvAivUDYH4umMYjkdkYzuieOZzNJci1zp7VCK6vRzHidkSG5F/AB5HyYKMpOM4uTDxzwZbJHW1ZKzShobSw3ySfm4oEQeZ6Ql+byjOjLfp9wJIaCLiYH7k0e4cf0KfLyfQ1YsfiF0s0/dH8Pby5PAXezH2GKTBSIiwnHv9k1cuXwenp5PYTDET4+lir8PCgzEjWuXcf3aRfj7+xG/+KnquSoBVQKqBFQJ/BgS+Li7VD4uW+K5eKDmkHgqwNaSlM7mGNwkK0a2zoGRrV4EOm9cIQ2EELA006DKT64Y1iI7RrbMjuHNKdBxNNF0qJkeyRzMYGWhQbOKaTCC4vlNIo4zktmkQqFkYLqe9TOBwZEZgYZKRV0xnHiNapUdQ4nXiJbZMKp1drStkQ6uxIvGY+TLbIfBzbJhZKtsGErH4S1zSN6FCajEWVP4mDOdjYzneg9qmhVpklnIe3r9fgVFFMhsT+URT+I1pGl2WYcRLbIihZM5UrpYoHvdTFQexVOd+B5HU53qlUkFrSJk3Xs2yEzpOV6G0a1zokXltGDAlZ6ATa/6nM73lI148z3lQI0SbngDcFBdPvUvOjoaRw79g57dWqJ7p6bo1/NPdGnfGFMmDkdISBDJxICn7o8wc/o4dG7bEKtXzEdUVOSLahhx9co5DOnfGQP6tMeQAZ3Qg3isXrmArGW6FzSvDnq9Hvv/2Y4+PVpj6IDO6N+rHXpTuYcP7pH95RWleqZK4P9LwGg0EFCOH17lEULIPqXX68h6q5PnQohXBK+dCSEkjZ76qF6nk6lCCHlUd/9BAiRDRdGAJ0AsWyGElPPbOAohaCKskP7QUx79G7RCxKZLfobYdCEEYjch83K/4P+lZaBxRIi4NLzchBCSr4EmZUYeNF6mqCffigSU/1JRbnMDdQ76gcGAOYELC7KucBynvc6b48xMNHC2N4WFqQbPfCJw83EwhRC4e4dLHqXzO6MlDepZyXLjFRCFI1d8ce9ZGBxtTVHz5+RoUSktdWojrjwIhoaAQSaygJTM64w0ZPXgwd7KXIPHz8Ph4RuJXwu7ok31dMic2go+gVE4Srxuu4dKXtWKu6FZpTQw1QppVXEi/qdvBlB5foiK1iNjCivUKZVSlsH1ZhDCVh8nO667QqDFDCVyO1GdE94lgz1bKxOqqxvYGhMYGoO9Z71w4U4g+FVOG0pLRWAnT0ZbBATH4NrDYETFGOBKlqS6pVMiPVl4GNDYEKAzMxF4SnJ55BGGBx6hdE8R9DAbkZpAFltyrj8MkQuLA4KjqT7maFw+NeysTUiZJ6zTp746e/ooJv81DP6+3qhTvxnadeqDn0uVx6ULp8nS8xB3bl3HuFH9cfL4QQQG+sPfz1fWm+vBisLjmTucXahtOvREh879YWvniDUEdh4/egANubaYLi7odTHwePoEefIWROfuA9GsVWcEBvhj/erFCAsNJQWkxJGqR1UC75TAiaP/Ur9Z8jKsW7UEp08epr5pkP0oODgQ/+z+G4sXTMeieVPleVBgAKWJN/gKIRAaGox9e7dhCdEvnDcFe3Ztof6eOP0bDNSIRCUghJAW44vnT2PtqoVYsnA6DuzbSZOo4Le3Q0gIjh7ah2WLZ2LF0rk4Q/pJp4sBFyCEQGRkhNRFK5fNxbJFs3DsyAEZJwSVpYvG1SsXqKxFmDvrL+obi3D39g3SoazJmQMIDGkQFRmJf6keWzevlvpMCBGbqO6/GQl89EjBgCaZg6m0XrQkcFKXgAFbO4aQZaQhD7ov3EivSyKuC4VF6rBs72OMWHYbo5ffxsYjz2BjqUX9sqmlC+rSvSCMXnEb41ffxfhVd3Dyuj8BCyO5kOwJiFjjwAVvPCNAY0bgqlReJzSiMlMSiAiL1OPAeR9pAalTKgWszLW4+SgEE9YRnzV3MWblbRy66CurVZLcP1nJHXX8mh9GrbiDiWvvYuqGexKAMAEDGzMCZUYylzBAY0sPW6ciowzywStK7i7718EF3aCDjQncyILDz8O1B0GYuvE+xq2+I8tm8PLUOwILdzzCiOW35D2eoPK5PFuSmQvJlMEVX3v6RWHcqrsYvPgmhi25hdUH3KUMbj4OwYS19zCW5DJl4z0cu+onAaAtASlrCy3VlirBDD5DCA0Nwfa/19P9A4NHTEG9hi1RsfJvaNO+J0aNn4106TIhOioKJX4uixFjZiBl6rQw0Gw6ripCKChVpiK69hyCchWqomz5KvilVAVEhIfhueczKErCLmliaoa69ZvjT+L/c8nyqFTld+TJVxjPn3sgLDwELOM43upRlcC7JMCAZBZZGxctmAYOC+dPoUHyHzmwRUVFYOK4IfhrzAAc3L8Lhw7swZgRfbBo/jSwyzV+RxNCICY6igD/CIwb2Y8G4x1k6dxHAL8f5s+eiHDqy0KId1VFTXuLBNiS88+evzF0YGesWj4P+/ZskzKeO3P8ixwJ5RoeFoYVS2djxJAe2Ll9I/7evAbDBnbFrh2bYGJigmhqp03rl2P44O7YuG4pxW8k2u5Yv2YxNamQrvFRw3phDQGrUycOY/7cSfhr7EA8oYlXnC56/Og+RlNfGDG0B9auXAgvr2dUl4T1oAj195VLIOHI8gGV5QHZjgZXtqo0rpAK7WqmR8EsDnIdDbuYapRILjuTkXjGBTp99SMG0TFGadWIJMtGNIV05J5xo8GeAcveM954QqCAF/c+JQvQ4Uu+ktbCTJGWDR+y+qw7+BQMurKmsUGFQi5kpVEkUDl90x+pCfgwEIkkK81BAjd33cPAZXgHRuMg8Qoii4sZAaX0Ka3IqhSBR55hMDfVIlc6W+JvSQoQcKdywyN0IPSAvBntJQgLDNFJS01wWAyyp7VGppSWMNC9IG6jZ4DL4cBRRbI7oj5ZbMzJonXtQTD43vh+9p71lvfHrxWGR+mZVNYvNFxHcpOXsCPwUyCrnSyHLVYMsjiF7+H2kxDw+qdMKagOqWygaAS8SSb+IdGgKjDZJw/88HsRyOCZT3ECM9my5yI5GSgYySKjRdp0GWBlbYO8+QujacuOSJkqDdWFasMdIF5tzM0tYGZmSnIzICgoENevXYKFhRXSpc9EoC1WFnHkQghYWFnBRKuldjASyHmGhw/uIFXqdLCzc5Blx9GqR1UC75JACFkASpatiM07TmDnvvPYfeAievYfCRNTU2mN3L51LUqVrYSV6/+hsFeC6mNH9uHZ08dQqB/G8daQ9fHatUs0sK5ESQLuy9bswqoN+1CgYDFpKWJLZBytevwwCXg9f0agZBlcXZNjw99HsHztbpSvWA2bN6zArRtXoSikT16wFELg1s0rcvJVuXptbNlxHHMXrUeatBmwctk8sgAH4PHD+9i6aTUKFS5O7X4ci5dvQ778RbBs8Sw5ubK0tEK9Bi2wct0/WL1hP9p26I2rl8/j8uVzYLDkT1bpyX8Nxb27N5AtRx6wO57HHFJsL2qhHr4VCXw02Il/g3q9EdfJHbNo52Owm8iEXENFaZC3JUuNnaUJ7AkUcbAhqwP3VcYGVnT+Z7W04LUqvI6mXAEXsHuHO3MEDf5egZEv+xP1afAgzm8daYgB8xVC4PhVf9x6HPqyKuxK+/vYc0RGG+BMrjKmjaG6PQ+IpIE1dsSlbAghQBFKFiDO6EhWGF4szGBtUoec6NMoM9XDHEEEZnYc92QSWJJrLHcGW/B93fcIw36yHPkERcu0X/K4SNAhL2jHj6JPUBTO3ApAMJVjS4ClScXUGNk6O2qQG86MABaRgevGICoTuesKZXXgKOmau/c0DFxHjrAjq1Gn3zNgSPNsGNs2J+qWSUl1UEjxAg3LpcakDrkwpFlWAmg2iCFwds/rAAAQAElEQVSwuOWohwRTQgjO/smDEAoCyS0VGhIkFYqB/NfxC+FrdlNxYP83H5FIVdjys23rOoymGVXPzs1x/OgBVP+tPoGj1GAe8XkKIRAQ4IelZKIeNqgb+nRrBU+Pp5Le3NxSBTvxhaWe/x8JGOm5U+QbfWZmZmDQrVCf5ueQ3RSgzsoAmvugLiYaQgiYkmVRqzVBwk2A1+hoNFrYWNtAURTEuU1MTEyhYWCeMIN69R4SEELgwf27EoTUqNUI9vaOchJUplwVmkTZ4t/9O6Ahmcdndf3qZWgUDarVqCejk7mmwC8lK+C5h7sEQnfu3AC7J+uQddjMzBx29g7SshwdHY3LF88ia47c0hXPZYF0VarU6ahMSz4l3QKYUZ7a9Zpg+uzVKEl8ZSHq7puUgPIpah1AVpL1B5+BLS3bCCAwwHAisMEAoXfDzOjzIvD6GQYWDHZMtAoypLBC9rQ2yEauJFcHc5hoqLdRhTidFRCdvvYTMlovCUCWGA3MzTQvaTiarSEcwVYP2WPpguPpEPuTmMcYlyTdQmyZCSCLiJd/FHzI8qMjgMRvdvHiZkc7U7jYm5MFx4oeKoHHzwmMECe2DDHffBltKd1MPhgULX/RZLH6+5gnlux6jMv3g8FrmjKnspbrh3jdDxMxMEvpYi7XJyUnl5enXyRW7nNHKLn3GEjxR/62HvXEP2QB8guOQUpnCzQiV13mVFaSX3B4DJ5Tfb0Dowjc6UnhCpTK5yxlyuVxGZ86kC5CDCmJGF2MnA1DtsZHlELNrAiFBh1TOLm4wM7OXs6m7t65BQ3NmhFvYxnzpVAUmNIA5eqWHDzjOnPqCFmFAiCE4OTPHtQCvg8J3Ll9HavJPbJx3TKcO30cMTEx8sYyZ8mBoj+VxJ5dm7F00QzMnDYWly+dwa/kok2RIjUYAElC2hkMejB9iZLlsP+fHVg8fzpmTR+Lc2ePo9yv1ZA8RSqiUn8fKgFBOuG551OYmpoiLVln9HqdZOHknIzizPHU/bG8jtvxZMrj2RO4pUgJBwdH0sFGKIqGrlORHtHCj6wy/n4+sLK0hqtbCuj1bDUWSJEyjQS6T548JBVmhK+vF7hfnDx2UFqQkhFt5qw5iV5HIMsaPxPISZUmHXQv6hNXvnr8tiTwScBOFFkV2PLCt+4fHA0DgQUNjUG2ZNHJRRaR7OlskINCxhTWkCCEBslQcg/N2/4I/efdwKBFN6RriMEGD27sqnK0NWF2Mhhpn8zejNxUgjqcEQEhMSD2qFbMFencLBCji3WHMe/fSyaHk60p/AkgGGjU5zhnAixkECIusT8Hspjw2ha+8iFwE0mWoHUE1sauvoNRy2+BgYaZiQa/5HGSi4zTJ7cEAxKmL1sgGfo1zoJsBNJ4nHWksnLQOdeR02MD1zEaO08+l+t0Fu18RPWJlm+aFc5iDzMTBckJ3HWvmwkMCP1IZsv3uuPGo2BoqKLPCfjwv2/gdT2ztj7A6v3uCCRAya6sNMms5EO96/RzuQ5o1PLb2EKgSEcyz5nOFmUI8PB9x9bj0+5ZudjY2JKisAS7s4T4uO5jSrPlytVqo1e/ERg2ahpa/tkFd2kGtokGIL1USPHrbZQzvD+atEXv/qMwcuxM/FqpJg1KW3Dm5BFoXgNH8XOq56oEXklAIGPmbIgIj8DunZsxd9YE9O35J5YunI7IyHA4ODlh6KjJcHZxlet01q9Zgjx5C6FW3T9gZm7+ig2dGciiae/ohP4Dx8I1eUosIXDEbxzmyVcItes1lZYBflaIVP19gARYn4aEBFMOAXYvxcrQSJMbUwpaREREyMXLRCB/nM5WGwtzC0o3lXoRNLZweykajVxAzvwsLC1f6gkuw9wi9jokJJBArBG7tm1E3x6tMbBvB5w9fQzFipeWLnluZ1kQ8Xx1Hhuj7r89CXzcaPXafdqQSyqdmxVonEZWcsuYmgi5vubc7QD0mH4FfWZfQ28Ko1bcBq91UYgwRmfAg2dhuPHibSxfcgs99g6X+ayIX+n8yeQaGUAguaM5Sud3gRm5gMLJ/fSQXEnp3CxRvURy8Hb4ki92nHhOoMcgv0XDIIXXrzAIMzfVgN+a4redQD3d3lqLsuQys6Mju8vuPAmBKwEpM7I0hUTo8dQ3Ak+8IsDWHgYe7MJiMGNjqZVrajTkorOmcwMBKbbOWJhpkCu9nQQyANcGcLQzQ8EsjlRfDfzovo5c8ZOLqTnVSDsGSK2rp0NesgpxHbcc8cChy75gAEdVlLzMCBARfpHgjp41cDxlpZmoHhKsmWsRRlYgtu6wPHhtE6ebUj4+fo5gICXPg4Er+dP5jSxeb6MoGqqbkMFAQIVpuGwhYuPinwsh+FIGrVYLrYkJrK1tkCtPAdja2ksApYuh2RzR8aJwSUg7IYSk1ZI7wcHRBbnzFJTKzcvLk0VDFOpPlcD/k4AR4yfNx45/zsi1G3MXbpBWRXan3r51DWFhoZg/axI8nrqjEllzChUpgZPHD2HOzAkIDgqU/TuuBCEEQkNCsJiA0sMHd1Gpym8oXORnnDl1FDOnjkHgW97gisuvHt8uAQ2BFKPRQHou5gXRK52hIZ2haF4NWQJCghi2uLC1TQgB3mL3IGsQgSSNFuxSN5C+5rT4wdTEDILGIrbQdejaX75kkSNXHmxYuwS80FlRXpUVP596/m1K4JO0pq2VFi0qp8Gw5tnxW8kUJAkh19KwNeKeZxhuPw2V4alvOIEISpY/ITuaIgQURUBD4XlAFNgawkCoWA4H+Y2Z3g0yyW/gFMnmQGDGKNfLPCPLR+WibrAl0BEcpsM/57zB7jMe+BnclMrnjBi9Qb51xZ2cv3kzqElW9KqfCSNa5UDJvE4SuLBFhBchNyyXEuPb5UTn39Kja+1M4FfcZX38osALkvNmsqNZA7Bq/1O0Hn8BbSZcRKepl3H5XhDYcpQltRWcyHrEVikOaV0t0LN+xlietTIQz4zSDaYj9MJrmrKlsUbhbPbyvhW6/3yZ7dGvYRYMbpodNYsnBy/u/qtdLvB3hTr+lgG85seOrFH8Kv4dkiV/T2h825zoUTczeE0PpzPgZPDGi6CJJT7HZqSbcyaTctkKVXH/3m2MHdEXp04cwrUrF7B391b07dVGuqMiIyPw4N4d3L19U76ZwoPFvTs34fHMXSoxfpV0764teEj++bsUz66AwAA/5MlXiGbRZjh/9gTm0SDD9GGhIeAFhkcP75evtV+7egEHD+wC32POXPl4Ivc5blXl+Z1KgAc+PbkjclDfqVu/hQQ5/n5+2LZlLbZuWYM/2/fAkJFT8NeUhahVtwkO7t+Bs2eO0fNvpD5HOos7Hsnmn91bwNafVn92xaBhkzBx6iI0btIGBw/sBlsc+VkhMvX3ARIg9SInPXqaNAUFBZB+VAAB0iGh8g1P1j0aAjxCCAghZJqdvQOCg4PIOheJuI3BJq+hcnRwhpWNDQHTYLmwGBDUjgDrmpiYaLglTwUhyOKXKSsB3N/xR7N26DtwHNJnzILtW9dJkEQEULf/IIGvKCv1pv9em2hyYzFgKZ7bUQKQuzQg7znrJQEFg4aXgToWW0xiyO2ko4FfT4AE1GfjasCdfctRD+w65YWA0GhpJWIrTIbklvAKiMQGcjVtPPQMvKiYv1PDZZ65GSAXR/Nr6DvIbcQWjgzJrcCLndcT7XaKY168ZqYcWXQyp7SCl380Nh7yIPePhwRfbFVyIesOf3un8k/JYEdWnzvuoVi8+xFiyALFHx9kV9MRsr74ksuJXV+PvSNwhCxKnO5Mlhw3B7O424B/UAzcKT0TlcU8CxNQ4zeudp16jn0EzNj6wiBHR/evaIB8mW1RPLcDiudyQBYCQnwP7Dar8bMbqhZzA/O/8SgEc/9+SJanSPiTG49BXYXCLmCaFM4W4De81v77FGxNY3m/rMwnPtGQdaUKuaDqN2xJIOc8eNHw4P6daEY7FhqNBuwbv3HtEsaN6otRw3rAkwDOlSvnMHJIDyxbPFPSuJOvfO7MvzC4b0cM6tcRO/5ej59LVUC13+pLBXPt8gX8TQOPl+czgPrM5UtnMXHsQAzs0wHDBnbB1Svn0fCPP5E9Z17wjA7qpkrg/0hATwNodHS0HEA1NNvnt2oe3L8DczNzsGv2zu3r1NUE8hcoAnMLC/DA+nPJ8hKchwQH0yBplF8C9/byoLhoPHp4j+gVCdAtLa1g7+CEchWqIYqAPoP7/1MdNTkRCRjJopMyVVqZws+4omhAgge/hRUWHoqiP/0iZc8udH9/X5K/QJq0GaWO4fZgyy9PtG5cvSTbNF2GzHBJ5oao6CjwJMnExESuw+FzA1mpebIUSkCJXV16AsCsS8zJJWZmZibrwDtBO0VRoNEosjwhRGwfojghOBXq9o1IQPkU9eQ1NPO2PcTYlXcwfOktjFx+W1o9XuetKAL8jZlBC29g+LJbePg8HBqKi6PjUy+y7iza+Rj9eC0P0Y1ecQf95t8A52HLCluLeAHv9E0PpGts0c5HiCKwxTx2n/ZC7znXMGzJTQmA2JW1kHj1f5F/NLnR+s27joELr2PNv08JUMXQYGkEA6IBRDOa6j9hzT0MXBBbv0MEZtiSMmTRTQym4EkWJS1VUiGp8fEggZ/ec66D+TId930ODDymbLgH5jmG6s/fyOHzBTseg+t/6ro/es65iq4zrqJbvNBlxhUs3/tELkoeQHUYu/IuRi2n+6c6j1p+C8ev+dGzbwR/l2fI4psYvvQ2Jq69h7j68SLxOFmwPD5PMIJdWS3bdMPM+WswYuwM9OgzAn9NXYCBwybCLXlKuXize++hGDJiCuYt3oTpc1ZjyKipaND4T2gIENWt3wzjJi9Aq7bdpel44tTFcv0O8xVCoGr1OpgyYzkYzFhZWaNL94EYOW4mmrbogK49h2LS9KVo0rwDTEkpGRkhf54bVbl+JxLgPseLT7u0a0TWmKX4Z8/fmDRuMLZuXoVc5BLNki0nchBwNtJgy9/VOfDPDvB3WhbNnwobaztkpJl/CA2KIwZ3x19jBiIoMFD2cR4cly+ehf17t0vL5owpo+Hg6AweZIVQB8IP6D6S1EjPcvqMmaVs165ahGWLZmLd6sVYvWI+MmXMhmI/l4XH0ycYP3oAZk8fJ3VJ7rwF4OjkghlTRmHb5jVYunAm+EOPpctURuq0GZAte26kIgC1YM5krFm1ECuXzsXfm1ejWPEyyJI1B7ZsWoX+vdth3Zol+Gf3NsyaNha3b16T3/9iNzuD4hPHDmLjmuXgt7cYGLH1bue2jWDrkxA0GMjaq7uvXQKfpKV47Qq7lg5c8MHxq35gUMBxid18FAET/ijercchiIo2JEYi3y56TEDo7K0AHL7sgyv3A+WaFx1ZQliHREbpcfNJMC5RfEBoDDiOA7txrj8KxpUHQRLIcFx0tB6PvcIRy8sXl8j19NQnUlqd4tQRrwO6/TQEBy/6YO8ZL1y8GwgGSvTsgRdSX3kYlN+q/QAAEABJREFUBLZWxb8n5s35rlLaNQr8OnvczbD1yicwWvI5eMkHJ2/4gV9Zj6S6cL7gcB34uz+3n4QifuDX6D39o2SZt+j+DlzwxtErPrhK98PWJ64Pl8EyfETyOXbVFwzwTt/yBwMsHVnLOP1zB1ZKPPtJmy4TihT9GSVLV0D27HloYLCVRdvY2iFbjrxyIMmZuwByUeB1NukzZJJgzcraBlmz5ZLfz+APC2bLkRvW1rZyFscMnJO5IkeuvHKGzdc8gOTNXwQVq/yOX0qVRwYyM3P5xIyT1aBK4J0S4P7KFsfgkGBMmzQc/G9Htm1di4oVaxBQH0auEztUq1kPbdr1xIXzp9CvZ1sMIWslf6m7Y9f+yJknv1wbFhIaHOsuIcXxa+XfwGnXr15E/z7tMKhvB/D/eOM4/s5U3LP6zoqpiW9IgC1qbTv0omc8G2bPGIeZ08YgmWtyDB4+CZaWljQ5NZBbK4wsNHrKKyRgadepD6KjYzB6ZB+sX7sYpcpWRJsOPaHXxSBV6nTo0KUfLMhaN23icPCbdnnyFkLXHoOhNTFF5iw5EUTgdcbkkfJf15w7exz1G7dG3YYtYNDrER4WJt/QGje6H06fPIIYsg6uIyDG4Iqt1hqNQvVQf9+CBD6+peiBjyTgwu4aT/9ICVw0GgGFLB88oOMdG6dzeAeJBDDMSyP5UWGvESvEgMNr0eA4IRLS81UcLz6+lixZcD4ui+9BCM4ho+WO016LkvG8i01LSM/xTM9lMc9YGo59FTg90fCCRAgBmVcRJAuB1zdKlum8ZkihC/q9TvLZr3kQYXMwBz6PX6CRZslvBuNLEiONBnpSJhz4/GXCixPm+eJUHvhaL03NBsI4r/jIRHX3Y0jgI++S+w5bbxYt34p1Ww5hxdq92LzjBAbSAJoyVRo5gJqRO6td575YT+kr1+3F2s0HwR8XZIANCNjZ2WPa7JUYN3EeHMl6w1bF1m27Y+2Wf8H0azb/i7WbDoBdvFqtFpDwiA7q74MkwLoge648ZA1egfVbD5NM/8XE6UuQPlMW6Elf8GcAxk9aIN/M1JM+UBSNtMIsXb0Dq9fvA7db34Fj5Pd04gouQu6vhcv/xhpqn7WbD2D4mOlwTZ6C+OlQmCZrcxauxeqNB7BszW5ZXkcCR9zeXBc7ewcMGz0NO/45myCs2fQvMpNliNeAxZXzPR5ZBmzdiowIx8tArlqOT+x+hRAkV71cJ8Xu3GgCh0K8OX4llvdzx3002OEB1otAzthVt+VaEg/fCFIJn7u6Kn9VAqoEVAl8uARYOVtYWNJMPy0yZs4KJ2cXmpgpUjEzN04HARS2ImaggTV1mnRkbbQmYE3WZwLmTGNv7whrG1sIIWA0GMB5eK0OWxpTp0kPtlhyHAemV8PHScBoMMLc3AIMRDmYExCNk6lQFAIy9mTlsZLyj4u3trYh92EmJEvmBq3WRKbFlc40lpZWSENuLdfkqeSbnBwXm24kXtaUlh6Zs2SXbkiFyohLF0KAXel21Pbxgy2BX4WAViyP73Uv4PHMHfy/4v4aM0i6cMePHogZk0fHflWc5PT6nbs/eYRl5Nrlf7UycmhP+e9T7t658TpZklx/NNihPoAYnRG8kPehZzjYtZIkd6AWqkogoQTUK1UCiUqABzC28nDg88SIjGSR5HQOxhcgJ46OrznEXfORryXtC/DDcWr47xKIk6uU7Qe0Q2L0XJs4fsZE2ikuLTZvLIjlPHGB043UL14Pcenf65HHeA8Pd+zesQnu7o8QEOiPgABf8Folg54mAa/duJHaaeumVXL9mqWlNUxNTbFl00rw2rdQcgELkbQWno8GO3H3KYSgmU7clXr8HiTAnfZ7uA/1HlQJqBJQJaBK4OMlYCRQwwu1Bw2bgDkL1mPOwg3yswzpMmSS7t/XOVes/BumzVwhXygZM2EeSpetjBtXL8s3GZVELEGv5/+c1/8Z7HzOyn1W3irzBBIQL64URcDMVKOGH1gGJloNTWAETLSK2g9+4H7AesBEI9S+kMR9gJ9DCCTdRhYbfhsxkCw7ERHhiImJThToCCHAL5ukTJ0G0UTDa3x44mxmYUFWHrMErsWkuBklKQpVy/z6JCAXZlO1+N9opEtpi7Rq+GFl4OZsCa1GgaOdOdKltPth5fCjPwPpUtnC2dECWgK9rtQn+PpHl8mXvn+WeTInC/AkFJ95S5S9APgDjfPnTMKY4X3Ar/yfPnUEep0+UfLw8DCcO3Ncur7mzZ6AC+dOomy5ykjmmiJRgJQok88UqYKdzyTYb40tgfcXVabeTWe8VwPkhOpHkwNebEa6e5qs0R5qAH5IGcibhhG8/WjPwddyvyz7F00gT7/kzi1FSlSoVBPJU6SSxe77ZzuGD+qO48f+JRCslXGvdgL8b1S2bFyFmVNHY9XyefIL5U4uyaBRkh5qJH0NXklKPUtCCegMRvk86Qixh4RGIVgNP6wMwiNiwN+KiorSIShE7Qs/8rMQEamD0QBEROhePA9qf/jS/SGc20Bq5y87QLALKl26TOjVdyRGjJ2J8ZPnY9ioqeBvnG3buga6mBgIwZAwrl5G+TZbj74jsGjFNsxdvAn8puKsqWNxniw8Wu3r4Cgu35c5qmDny8j5qy/lVZcVsgMLoR6F+HFlIDusgNoXfuA+IISQ7Q/eBOS5EEI9JoEMkEQbAx7+Vk4EuaeiCdykTZdRuqT4GzpR0VEv+wIgwJuG3N9OTi5IkSIN+J/jNmvRERqtBlevXODkJA0q2ElS8X/bhQshoNFowIhdeYuZUohYmtfThYiNf1deJLIJIWSZQgio29crAbVmqgRUCXzrEjDCx9sLfj5eYNCj1+nkv9Lwev4MDHr420Xe3p7yy9IBAX7Q6/W4dfMqPD3d5TofXszs6fkM/NVpBwdHEkbS6mwV7FATqL8Pk4AQQgKO6KhoQuyXcfDf/Xj44D6EEDLgxcYAhz/Ffv7cGbi7P3mZxvEhISE4duwI9uzagdu3bsJAbrQX2d564Hy+Pj44f/YMvL28XvJ7awY1QZWAKgFVAqoEPkoC/I+6169dgt7dW2HcqP4YPbw3JowbBP6wY83fGxJPgWOHD2D0iD5yITKDnUXzpqBvjzYYN7IfRgzpAb7mD24WKvoz6fjEFzUToy/yU8HOFxHz91WIjhD+7p3bUeqXwqhYoSQaN6yN0iWLolOHP8H/IVoIIYEIzwaGDu6HyhVLY+KEMRL5sySOHz+K36pXRMN6v+HP1k1RtXIZTKJ0puf0xIIQAlGRUWjfriWqVS2PBQtmS4tSYrRqnCqBxCTASvqNQP0qMVoG1opGk1jSG3FCCDC9RqPIfg91+88SEIJ0CFmLFQpCiP/Pj2iYloMQidNrqD0VRZNoGylCAacpbymP4zXvyP//K/jtUfD9Fi32C+wdnXDh7AlcI1cU/18x/pcpufMWkvrcLXlK5MqZD8npaG5hgdp1m8LJ0Rnnz5/EvTs3UaJkOYz+aw7Sps1AYMeQpEJQkrR0tfBvTgJGGHFg/z8YMKAXrG1sMGbcRMydvwTtOnTB/Xt3cOfObVIarDgU7Nj+N3bt2i4/t66L0UlTKFtw3J88RqHCRbBoyQrMX7QM+QsUxqqVS3GX8vIDhtc2IYTMu3TJfLCVyMREi+ioqNeo1EtVAm+XgBACBw/sw5KF87B4wVwZFs6fgyOHDyZQwkIIsho+x+qVy7Fg7kz4+fkmOjhySUIIeHg8w7atmzF50niMGzcKe3bvjP1noUyghg+WgBA0qYmKxDmy3i6YNwtTJv+F3WT9DQj0f2s7BAUF4hC17bSpEzFr5lQcJ4sx/z+nuMLDwkKlFXnmjCmYPnUCWaL3ISwsTPLj9ShXr1zCwoVzMXrUECxZNJ9cMTcS9AlvcuVs3bIRE/4ag0kTx2AXTfS4TCFEXBHf7bFI0V8wZcYyLFu3GyvW7cGocTPlf5I38qp1GguKlSiNsZPmIVeeAvIfp/J/pp9M9CvW7MHyNbswZOQU8CJl46vXfZNMVt8E2Eky6agFJ5CAEALBgUHYtGEtbKxtMGXaHLRo2QY1atZCr979MX3mfGTOkpWACfDo0UNpzSlcpCgKFCz8go8gICRQrVpNDBs+FpUqV0elSlVQpkw58OK35889Kf3NLimEwOVLFzFn9nQq63dkzpwV6qZK4EMkwMp28qSxEpRs2rQOWzZvwJZN63H27OkEA1sUgeh161Zj6NB+GDliCB7cuycHxdfL4pn+Y+rjfXt3w4QJo3HhwjncvH4Nf2/dhMDAgETzvM5DvX5TAgw+tmzeiM6d2khZnjxxFCOGDyT3yWiwRfn1HMHBQZg9axp69+5KIOcw/tmzE9wm66kNeT1gREQEli1ZiF7dO2Hfvj04ePAABvTrhcUEbrhPXL92BQMH9MG6NStx5vRJAlfj0a9vDzlp44mXn68vJk8ch9Ejh+DSxXMEwk5j+ND+mDt7ZqK66vX6fevX7JoyGAywsrSGmZm5bAO+jrsvliFfc+A4g0EPAwEhSysr8D/L5XU+cWmcnpThzZElKWujlv1VS0AIAQYkN25cwy+lyiBXrtyy87MSYsXCQMfW1pasLpHSUvPc0wOdOvUgs6ZTgvuysraGuYU5eGDxeOYhBxw7WzsJlPjhik8shEBYaCjNuObBwsIKf7bpCAtLy/gk6rkqgfeSQFBQMIoVK06WyKVYvHQ1lixbQ/2pw0t3qBAK7pF18m8CLMmTp0B0dBT0pLwTY84KfOyYEbh96wb69RuCmbPmY9qMuRg6bDScnJwJ8BsTy6bG/R8JeJLOWLN6OTJnyozFi1dh5ux5qFixCjZtXEsTngtyrWAcCyEErl+7io3r16Ju3YZYsGgpJk2djrTp0mPZ0kXw8fHGgwf3sGH9GpQkfbVo0QrMmDUP+QsWwvx5M/Hs6VPY2TmgSdMWmLdwKZYsXYnWrdvjyuWLOHXyGJWllf3hn727Ub/BH5g7byH+mjgVufPkJ6v1Fvj7+YFBL7789sVLZFDD4X0LZloO70v/JehUsPMlpPydlMEPNs90ggIDkSlTFpBGf3ln3LE5cMRlUhY7tm1Ft+69SbHklwMGG3xlIAUVER6OOTQba9ywFipXKk2uhH/RqXMPpEqVGjyIMI+4wDwPHzmEIxQGDB6GNGncqFhDXLJ6VCXwQRKwsLRCsmSuSOYaG2zIFYsXG/fvFcuWwNHREdVr1HoR++aBgf11sgjsJStClSrVUblqddjb28OWALtb8uQwMTV5M5Ma838lwPK/dfMGnrq7ow6Bl1Rp0sDVNSUqV64Gc3MLbCe3uEajjcfHiHPnzsDMzBS169SHnZ0TMmXMjnLlfsWD+/dw9eplXL1yGX7+fmjWvDWcnF1Ix6SR4CmG3Oonjh9D1mzZ0ahxU6RPnwkOji4oVuJncs9bE5Dxp3KMNJmLAf97BGcXF9g7uMDKygZ6vQ6KRiHLhSnpIhXUkqC+iZ8Kdr6JZvp6Khmji6DsevgAABAASURBVIGOHnaNVkMe2zfrxW9ZrVu7Cjyg1KvfCJGR0VIhGMhny7NkBi9CCDkwuLqlQM6ceeDikgw7dmylWdo1KIrmJVMhBHx9fbB+7UoULlwUZcuWR2RUzCt+VI+XxOqJKoH/IwHqTmSJuY5FC+aA+ygPlOEv1m7wIHro4H5wqFOnoey/b2MnhJBu2oiIcPCCZ+Y1c/oUbCXX2JPHj2B8jzcL38b7k8Z/Y8yEEGDLjpmZGVKnTgO2GPMtODg6EaAxgxdZfUB6hOM48CmvmUqRIpXUJ1K3KAKuBDiZR6B/AAIDAmBvZw9HJ6eXE6nkyVMSeDKHh4c7xekJzLBOiZ1A3b1zhyzT0UiXPj0VIZAxYxb88ktpzJw+GbNmTJXhzp3baNGiDWxsbKk6KtghQX0TPxXsfBPN9HVUkpWJnb29nPm4P35MwCRh9zExMcGd2zfBr6IzGFq9ajkWzJuNe3fvyEV/PMjwYj8LckM1pNnUhInTpEuhY+fuuEazsOXLFknlI4SAEAJarQkuXjiPE8ePwEB+4MVycelCeHp44NKFc+Tamg+2Egkhvg4BqbX4qiXw88+laHbuKK2Es2dORZtWTTBv7kyEk6XR2/s5Ro0cgly586BSlarQvADdQgjZF+PfGIMZHkQNBGp27tiGbX9vwvHjRzF4YB8MHTIAjx8/eiNP/Pzq+dskIOS/G4AAzElHsL7hYEKWMi3plvCICMTodPEyG8H/oNLc3ByseziBAZAFWYE0Gg1CQoIlP+alKK90lYWFBekuDYKCgziLDEzv7e2FDRtWkzs9m3yBgv8nlBsBp8ZNmktQM3zYANlf0qZNj0pkbTIYYgGSZKDuvnoJvOoBX31V1QomtQT44XYja0xKmkkdOfwv+Fs3PIPSarVS2YSEhCCCFBK7owL8/WkQ2Iw9u3fQDOoZHj68j927ttNMK1AOJGZm5uC8dnZ2KFCgAOztHYjfczIR6+Vt6vV6CCFIKQmkTJkajx89lPz27t0FfzJL3yUAxW6EqOhoqNt/ksAPk7n/gKGYt2AZhSWYS8f0GTKCF7Iy0F65Yilu3riBps1awtraRs72WTAx1L+4L/J5XDCSTVNPA51CVoSWrdpi9txFmL9gMXr06o9jRw/h3JlTcaTq8QMlwLqEwaQuJkY+/5ydAYyR5G1CekajeTVkGRE7IWIApI+3tsoAA7WQEWYMgkxNoIsmyw0BU+bFgQEU+eDBoIivFUWR6wf5baxHDx+gRas20t3F+u45WZNWr1wGCAWDh45CPbJWc3+ZNHGszCMEITOo27cggVc951uorVrHJJUAK4lkyZKhStWauH37Ftq1bYED+/dJv/jqVctQo1oFOUjs2nsIh46exYFDp7Bt536ULlNevoG1bde/SEfm4WVLF71YwOwJ9ydPsGXzZjx/7oG8+QtI8/K/B/ahf98e0hpUkWZQh4+dw7+HT0t+m//eTrPvvGjYqAk2/70LDg4OctaVpIJRC/8mJMAL43ldja2tPfLly4dGjZvJ2T0vSOXX0k3NTDF92mT53ahFi+aAB7uxY0dIQMSARwgBIQR4cLSytJLnrq5u5IZ1hZ29E8pV+BU8iPr5+al9kiTxoT8jWW9tbW1pwqN7+UabEALhYaHgt7ScXVygIYuNEEKy5r0dTZb4jaxImmRxJCcF+fmDwZIjub+srKzBr4nH/1QFT5aiY6LBVhtuy8jICIwfNxJbNm1Ek6YtUbPG77Ic5vfP3j04RBO7cX9NQbfufTBu/GTUrdcA7Lo8dPCAnOQxnRq+fgmoYOfrb6Ovo4YvasHKpnbd+vizbUdpienWtR1atWgM/s5IcvKFZ8mSlQBPNPnbY2TgAcPa2hrWNjbQ62J4LIC3z3NMnzoR9evVpIGlFnbu2Iqq1Wrijz+ay9nSnTu3yHV1FM+9PMEKjc3JccFgELAjH7yFhSV0eppj87TvRd3UgyqBt0kgKioSQYGB0LPFkHoVD4AXL5yDFblLUqdJi8pVqqNmzVpInTo1kpPrwt7OQbKyp77GA7CR+tmTJ4/BQUc8UhGdiYkpLl48hzAajLmf82JYHjxdaEIgBPdcyULdvacEjESXLn0GGEjWp06dgIGsNQxy+LV+djWWLlNO6ocnTx7B6/lz8IcAM2XOgqfuT3Dz5g0IIRAUFITz58/RJMgRWbJmhVuKFKQnYnDq9AmZHkGg6Cxb3qiwQoWKSlfXvLmzsIZc7s2at0bL1u2oFkDceiEPz6ewt7dHcrfkFBdD1iJTZMqUSVqlud2pSEmv7r5+Cahg5+tvo6+qhqz0+dXa7t17YxaZ70eN+gt9+w3G5CmzMH3mXKR87Y0qCwtz+SYEz6J5IODZc/MWbTCJ6Dt07IqOnbpj4uSZGD5yHJycnOSsuUqVGhg/YSpy585LCkaX4P6trW3RtVtv/FarDgwJ/PcJyNQLVQIvJcAA/eyZ0+jRtQPmzJqOZUsXYvjQQXJ2XrRYCRQu8hPatu9E/XCG7Jf8/ai65K7g/spvCVar/ptc+8Hfe/mLLAA+Xl7IlSsPihf/WX40c9qUiZgxfTLGjRmBnBSfv0Chl2WrJ+8vAaPBAP58RaFCRbBh3WpMnvgXZs+ciqWLFyBv3gIoVbocnj17inFjR2LWzClQNBoUKlQUKVKmwtTJ4+X6wCl03H9gL2rUqIW0adMjD+mQrFmySz7yo4LTJpIleQMqVapKYCgbDh/6F0sWz4cgVxav++F1hfwhw/kEgBgY58iRC7wukMtbu3oFFi2cj3Xr1pBVKAXVKT/pJ/3736BKmaQS+NRgJ0lvRi38y0iAAQ/7w/PmzU8urRoSeJT4uSTNgN50KWk0WuTNlx+88DOudux6+qlYcTIHNwRbieLy8oyOadKkTYsSP5eCDVmDuCyOiwuskPhDhVmyZEMcfVyaelQlkJgEuA/xgKhoNdi4YQ0WzJ+Ns2dPoV2Hzhg4aLi0AnA+IYSc/Qsh4OzsgvTpM8KG3CpGStRotTAajNJtwSDI1s4OY8ZNQmEabLdv24KN69cgV568GEngP1269OAyKZv6+0AJsNy79eiL4iV+xtYtG+SHBQsS+Bk1ZgIsyQqnUNsYyLJmbm5OnI0SsAwYOAwOjo5YumQBTp44hnr1G6Ndxy5ga1uq1GnQhyZjGTJmAr/Vue+fvahYuSp69h4AU1NTREVGwY2sNsmSueLokYNyXSGvM9y/fy+1oQFlylZA56698PjxY0wja/SyJQupvzhJdxbzZEBEFVF/34AElG+gjmoVv1IJsDIxkJ+dFTuf8zGxqnI8h7g0PucQd/16Xk4zEt+49NePRjJzc3g9Xr1WJZCYBLh/ZcyYGctXrse+f49j196DOHDwJFkkhyBFipRvZGH6KlVr4OSZy8hNAIa/AsuurMVLVmPGzAVwcnaW7rCMmTJjwZKV2Lv/KPYfPIFFi1dKUC+EeIOnGvH+EsiRIydmz10sZbr7n8OYOn0ugZqsErwwaJ2/YDmGDhtDVhUd2GpXtlwFrNuwndrhCHbtOYh+/YeQldiZwIoRDEyLFP0Jq9ZupvRj2L33kASkKVKmlG1Yq049/HvoJE6cuoijJ87LcOzkBezcfUC+Dcrt3qZtB+z55xB27DqAPfuOYOXqDfIjhe+ng97/vlXKzysBFex8Xvmq3FUJqBL4CiRgJPAcFRUlZ/O85otn5DEx0XJATKx6TG+MB6rlOYzg70zxOedhUMQLYdniwG8RMX+O4zQ1fLwEWIYsS7bisvUlOjpKAh3myLLnN6+4HfiaA7cl0/BiZL5+vV0lv8hIWFhYEDhS5JpC5sO0vDYnktJ4LU/8wHGcznQxMTESWNk7OMgXKHgdEZfJ6Wr4diSggp1vp63UmqoSUCXwHyXAgxcPfu/Dhmnj071+HZfG8Rzirj/mqOZ5UwIsUw5vpiQe8/9o/1964lxfxXK/+a88XnFTz760BFSw86UlrpanSkCVgCoBVQKqBFQJfFEJ/B+ww0vzVP/zF20RtTBVAm+VwJdPUJeffHmZfy0lxm97dRT4alrla6nI118Phi941XPfCXbKFkiGvg0zo2f9TGr4jmXQq0EmtK+RHmYmCrQUbKxNYauGH1YGlhZa8Fsv5mbaH1YGav83hY2VGSyoDyiKgIWFidoXkkgnWphpIISAk7050qSwUcN7yCBtShu4uVhCQ30XLzblxTHRg5W5Bs52pnCyNVPDNySDj2kvB1sTeqAAg4EXYRoRrVPDjyoDHbW9EUbo9dQHYijQ9Y8qix/7vg3QGQxyEbdOb1B1QlI8B/T88XNIjyM0GgUmWg20anhvGRBGRNz2TrCz77w3Rq+4g/Gr1fA9y2Acte/MzQ8QFWNAeIQOjz1C8ORZsBp+UBl4+YVLoBMQHEl9Qe0HP+qz8Jj6v59/JHQEer19I8DXP6oskuq+H3sEwycgAgajEb50VNvg/fQRy8nTO0zqMQAS77wT7ERGGRAYFo2gsBg1fM8yCI1BcLiOZnBk2aGHSk+zOJ0aSMnTzPYHlAP/k0t+60T2A53+h5XDD/8M6AzQk6VX9gWy8Ojo+oeXyZfWByRzPYFNtuyw1V2nV5/H9+qDLDfqs0YWnIQ6wDvBzguaT36g8VQOrK8f4xcUl8aINu78zXS6FbkI6VXK22ljB3J+cJnmVY7YM2bDaVweB76OTUm457xxIWHKj3klhCD3V2xITAJC/P80IURiWd+IE0LIst5IUCNUCagSUCXwXyWg5v+uJfDFwQ6NV7A018DWSgtby1fBwuxVVRhMmGgE7KxMkMzeHA42JrAwVcDIFrQJIWBNee2tTWFO8RQlfxQNG4pn3lrKz5HMi89t43jZmkpeHM/pHPhcqwgqxxTJHMzhRDQmWiEBGafHBUEnseWawMpCix95E0KQ39QE0VFR8h8h8se5NJqEMtFoNOAPcPEHv+LLSggBRSgIDw9DSEiQ/MgXX+Mtm6Io4MYIDQ1BaGgw9QMDgR6Kewu9Gq1KQJWAKgFVAqoE4kvgi44YbDlxtjND51oZMOCPrOjfJDYMoGPtkimhEOBgmlQuFmhWOS0GNMmCcW1yYnjL7OhWNxMKZ3Oggc4Ie2stWldNi2HNs6F5pbQw1SpkajciSyprDGqaFb0bZJbnbIJ1dTBDs0ppMJDKGNcmB0a0zIGuxKtIdgcweGFhuDqa4Y9fU2N4i+wYT+WNoPL+rJqOwI8Jj7FMIs25ro7mkvdQoutC92BNgOdtFiCZ6TvdMfgIDgrEutWLMHZkXwzu1xGTJwzFmVNHIYSQgb8oe/niWUwYMwA7/t4gQU+cOAIC/LBh3VIMG9gV/Xu3w5QJw3D9+iWZL44m/vHJkwdYMG+KLGdQ3w5YROeenk/fSh8/r3quSiCBBKh/cv/lIIRIkMQXQgjSQ4oMSHx7I5Z5cXgjQY34aAkIIWQbsFyFeLOd8NomhHgnvRCv0pHIJoR4mR+vbUKIl2lcHw5Qt29OAv8Z7MQf7MmpRB6y+DG3mhwDAAAQAElEQVQJ5UHuXwkgfs7jjEJZ7VEgsx3yZ7JDPgoZU1oRsDAiYwprDGmWDQ3KppTxKV3MkTW1NcoVdMHo1jlQrXhyREUb5GvSOdLZoGKRZJKOLTz1y6ZCwSz2cLU3Q0SUHhmSW2Fc25xoWC4VlWOLlASisqSyQnnixWWUL5QM7LL6JbcT6pVOicypreHmZEbl2aBWyRRoWSWtfBsBtPHjViyHI0rkckTu9Db4Ja8TCma2h558uJT8w/yEEPD0eIohA7pg/Oj+OE0A59nTx9i9fRO6dWqCG9cvIyI8HIvnT0fblnWweeMqXLl0FjpdtJSR0WjArh2bMGv6OPj6eEMXo8Pfm9di9PDeCAkOegPA8GfblyyYgbWrFkkLkJ+vLxbMnYx5sydQfzEQT24ZOqg/VQL/RwL8zzyjIyPh5eUJPz8f6j9G6m+vVCAPYvzvH3x9vGS6ECJB+uvsmV6v18HX1xt+vj5Ey/TidTL1+gMlIISQsgwOCiK5epOOiIFQXrXT6+y4HYxknvcn3RDg7weDwSDzx9IJAioasiKHwuu5BwID/cGbEIIPMrBVOSoqEt7ULwJoIsaRQsSmM9/IyAgEBwdTCJIhhPQUtzvTqeHbkcDbe9D/uQfqWzA1UZA9jQ3SuFrCjaweRbI6oGg2R6R0NodGE9tZXmfD+bgDhUXqseaAO8avuYOJa+9i02EPKNTBGpRPhQwpLOEfEo3V+59ixLJbWLzrMdy9I6jTCtQmEOJgY4o9Z7wRFKYDvx7PQKhsfhcUIKDDbxQdueoHv+AYNK+cBqmTWUhe6w4+w4iltzBv2yM8eh4uwVKTX9PAldxWPkHR2HfOG6OorDEr7lB6mKw235ulmZaUImBloUGp/M4E5iCtPKZkTfo5jyNM6GiU1D/GLiY6msDJGly5fA5/tuuFDX8fxroth7FszS40bdEBFpaWuHjhFI4d2Y/GTdsiXfpMUvkAcf1BIH+Bopg6czmWrNyOWfPXoH7jlnjm/hi3bl6lfqNB/I0tRJWr1cbCZVsxZ+EGzJy3Fj+XrIDrVy7B389X9on49F/NuVqRr0oCer0ea1cuRI8uzdClfWN0bF0fwwd3x6OHdyGEoGfcgMMH96Jvz7bo2rEJOrVtiBGU7v7kvkx//WYMBNpPHP0X/Yi+G9F3bFtf0j98cA+UAer28RJ48ug+Jo0bQu3UEJ2prQaSNffMySP0rCtvMGVgc+HcSZp8dUbnDo3QtcMfGD+qPx49vCfpGZisXjEP3To2RbtWddGxTQPMmjZWgighFDCQ2b5tPXp3bYXunZqiS7vGmD1jHPwIDHO6Px2nTBhO8Q3B/SYunDh28A1d9Ubl1IivSgJv9p73rJ6BUAsDnGHkShrQOAv6NcqCPg05ZJbHAmT1eBer6Bg9Tlzzx84TXth5ygsX7wYihZM52HoSozNgL4GZVfvdceSKHzYe8pDghuOd7EyRhSww1x4G4xilKYpAQbISNa6QWq7F8fCNxMGLPkjubIY8Ge3AeY5c8sMaAk4MgrYc9cD2488RTpYfN3Jf5Uxni+MEjub8/RDHqT53n4bKN5O47hFkQWJXGN9rppTWSOtqgUjKd+txCCKj9chH98guNyObrDjDdx6EEHIWe/LEQeTJW5DATXtYW9vIgSJtuoxo+WcXpEmTAZmz5MDAYRPQrFVH2NjaUvorOCiEQI6ceVGg0E9QNNz9BCkNLXjWbWFhidc3BjtFiv4seXIat7dGo4GZuZlcMwR1UyXwfyQghEBISDD27dmGjBmzoUGjVsiTvzCB9tVYs2ohWWf1uHblIkYN6y0tALXrNkWJn8thz+6tWLZ4NsLCwqgEQSH2pygKbl67jFFkjQwODkSt2n+gdNnK2LvnbyxbNANhocEQ4hV9bC51/z4SYHCyYtlcHDq4ByVLV0T13+qDLcmTxg+B3wvrWRwfIYScJM2bPRFP3R/ht98bUp4KOHXyMBbOmyLb1cfbExcvnEG27LnRoHEruLqmwKb1y7Fn11b5T2HPnTmORXOnwNrGBo2atkVe6hc7/l6PXds3gts5PDwMt25cQTLKV7psJcn/l9IVkDx5qgR6La5O6vHrlQCPNh9XOxq/TLUCDD7YBZU+uQWeeEdIS0f2tDaoXMQVbP1gsBEXdPwK3YvSzEw1KFvABfXKpkCdUsmRPS2BCTdLueA4lKw+l+8HkevDCF6oHEOuoltPQsBWG752ITdVdIwBmwi4ePhFyoXMKZzNqXMK7Dj5HE+9I5GCLE1My3muEjAKjdRJXoTRcO9ZGIJCY0ghAZyPwQzXpWvtjHJNTrbUNginOmw77inBEi9wzkfAycxEA+/AKGw/8RwBITGwtzYBu80gXtzUhx++qRz88Pv5esHH2wt58hUiK47FC6sN5FGj0VIbKHB2cUX6DFnkOVvxXr9JvU6Hm9ev4MC+XVi8YBr27NyMn4qXQpasOaWCep0+IiIc58+dwD80WPGs7NrViyj/a3XY2TvIcl+nV69VCcSXAPdBGxrMho2eio7dBuC32o3RvnMfWFhY4d6dm9JNcvjfveRWfY5Wbbqidr0maNO+B37+pRwunj8FdtMqNKmK42kgK9FpsjQ893yKZi07oVbdJvizbQ+ULFWBLJ7naQB+EkeqHj9AAkIIPHn8ACzbKtXroFXbbqjXoAXqNmyO58+fEQDaDQ3pmPgsr165gAf37qDln92IrgUaN2sHBiUnjx/E3Ts3kDptBvToPQwduw6Q6S1oQmZn70j65zKBFQMY7JiamaJtx96oUq0OtWdHZMqUDexq1+liqKhY5V6qbEW0atON0jvJkClLdlX3kHS+pd/Hg514d8nAYNled3SfdRXsjqI+i2wEeJI7WeCX3M4ondcFpfO5oHBWewmGGHBYmmkI5KRE19qZ0KlWRpmejFxKzJaBDK+5iQMR3N0YMDEoEULA1ERAQ8rnCbmjHniEI26LIGvLtQfBYDp7W1NJQ+5bhBHQiaNhnjoCT7oXwMvMVCGXlga/5HFClZ9cyRpkC45jyw9bcQQAR3Kb5cpgCwY9Z28G4MLdQLAFie+jVD5nsihpiOr7/wmhIIj86GE0c3UhQGN4h0WLB5jEJCKEAIOXVcvnY0CfdphPs7JwmjnnyVcYilZLCsiYIJsQQvrSp08aiUH9O2Lj+mWwsrZG1my53qBNkFG9UCUQTwIaGiRTpkpHAMcCGq0Gjx89pH4YBje3FNCamMDL2wNarQldp6RcgvqYDQoWLoFQsgj5+XpL9zUlQAgBnV4HHx8votciZao0ACkJE1MTlCpTCWyZeP7cQ+2b+PBNCIGHD+7CSEq7YKFiEEJIGWelSZClpRWuXjoHRaO8ZMw65u6d63BLnhKZMmcDXzMdW3H4LdCnTx7Bysoarm4ppRWHmglmZubQaDRggKMoWtJnAbC1c4CDo7PMz0AoXfrMcH/ykKx8YVQHyC2CLDxBgf4wUN20pKdeJshUdffpJPD5OL3qOf+hjECyklx/FEKzciNuPA5GFLl/BHHOl9kWw1pmw6BmWTG4aVZ0qZMR1hYa2akYbFwlYHLwoi8OX/LFrSehCAyNXcTKFiELsvzEaRge/vhaoc5voAE2LEIn180Uzu6AfBltiR/AAIdpqhRzJfCiIDRcJ+MUqgcDq5e3R8x4rRG/Ws5xwWExcjHzmgNPMXn9PfDxqU8EnMld1r1+JgJttmT9sZCBigcDsqo/uclX3Dl/cnK9ZU5lTWXx1fcdjEYDuY/MYWJqKhfqCcHq48Pu2UgIkRXSn+17YN6ijZg4dTHyFSiC2dPHYcfWdVIRxefI9KzMBg6biHkLN2LYqGmwtrbFqGG95MyNFVd8evVclUBiElBIETBoWTRvGsYM74MhBJxdkiVHXbIcmJqZIQ1ZAHgmf/zYv/Dy8iALw31yn7iTnjEgKjISUskQY+6PWgJFqVKnRUxMDI4e3i/B+FP3x3AnVwoDoehooida9feBEiB9EhQcCA2BCTsCIAYCFixvM3MLaCkuJITGGJ0+AdOgwAByldvBnGg4gemtbWxpUm2C0NAQajZS+HEDCYS05HCefPmLErkRLi5usp153U+Avy8Y5PgH+IIBVxiVp1E0MCOAtJomZ7zep3O7Rpg9Yzy8PJ9BiA/Xf1C3JJMAQYH/XjYDBwYxDDj42zcaXpxsAB49D8fmw57YepTCMU/sPuUtgYUQAqEEWFb8446/1tzBJAIZJ677wd0rgpQL5GLgXOltoVDtdARu+E2rvJmoQ5sqiNYZ8Mw3EvbWWtQvk5JotbjvEYYbDLaI9ufcTsiZzgZe/lEEviCBT450tmDAw+tvtFS3XGSl4UXOBqJ/5BkOjrtCwGvX6edYvvcJDlzwIfBilN8BSutmgWxprMHf3mFJlcjtiD8qpEamlFbU2QFrcy24ribEl9O/58CKxIlmQHZ2jmQGvkLy1ZMMxMugodmzEEKK4MVBngOC/mj/IlJDiitNugzIRyCnLLmjmjRvDzs7exw/egAx0dHU7ooMQgjwxsomc9YcyF+wKPnwG6B23SYEtgLBr7YLEUvDdGpQJfA2CQghwG/cPHx4Fx7PnlD/0tAAaoJ7d28hMjwcFSv9hvwFfsLyxbPkJw74bcN9e/+GEALcXwGBuI2B0y/ksiry0y9YvWI+BvXriKEDu2A7gXWekCmKJo5UPX6ABFjCMTHRYD0jBF/FZlZoINBoNDAY9DASAOJYDjRvkp+0EEJACPES0igakj9dM/A0vojlNuS1N5s3rJDrckr8UpYm5VEoWaYi3MjyM3XicNmG/FYoL4ZmiKQli5+DoxMaNW2DJi3ao1rNekhOVqRN65eDP4XB9eR6qOHbkADBif9eUXbz1C2VEtWLuaFacTcweOC1LfefhWHJnsdYsvuxfKNq81EPRLLVRwCyo8boERVjkIH78BPvcNx8FAxTrYJKRV3Bb0uVIRdYs4pp8WvhZITWFbne5g5ZgYrnckZ2cpVFEY+9Z7ykRYZ521uZoFzBZPALjiawFSbzlMnvTAAlDUrldSaeqVGD6sgAii1Lt4kXX7eplg5FszvKb/nkyWAnHx6dzogYqh8vdGZAd/KaP8avvouJ6+5h+qYH8PSLAluJchK4srHUvnis8N1uBmqkZGT2z5m7AE7QDHj3jk3Q63TUlkZpvt9ISoAHj1jQoyEZUvcirUF6B4IUlhAKgVk9nj59jAB/P5ITJZK1KDwsFAxyeEbGCoZfSb986Rz4TYkYUn7sxw8LDSV6AT25EELItcDlMugCBNRNlcD/k4Beryd3Rgr0HTgGo8bNwpgJc2BLFoA1Kxfg9q3rSJchE0aOm4luvYfi18q/oVGTNihXoRpMTEylK0TE62b8HLAlaPiY6ejRZxgqVvkd9Rq2RHUaDBmY2xBfIeJl+H+VU9NjJUDqwMLCUuoTfvaFIBlSiNHFgD9RwS4pLQGQWGLIJ9/CykqCWKYhaoBi+fMCvK7KxtoGCukcDU2uHj+8ChfjbAAAEABJREFUDwYylIwmNLlydHIBA6ccOfPIlyl4zU6ZcpVRv1FL5C/4k2xz1kcW5D4rRYDot9qNUad+M7n2h9NPHT8IH29PMBCDun0TEqDR6L/XU6MR8rXv3g0zS6sKr7k5fs0PYWS94bU2bI3hoNOTuYd7JHVqWSp1ZL6UgXZhkXqsJGuPb1C0tKQ0+TU1hjTPivplU8LR1hTeZK1ZtucJuLxfC7nA3EyD5wQ4Dl/yxfnbgeD1NJxWKJs9eOH0yn3uCA7TgcFYg3IpMbR5NjQmq4yTnRme+URiwc5H4HU+mcgNVbd0SvA3eUa1JgtCZjt6EIw4ecMfXJfsaa3lQuWNRzyw58xz7D79HFvJUnXkii/oFpDWzRKpXSzw3aMdajRWOLXqNoa9g5N83bNj2wY0I+qKZo2rYsKY/gR6AvDg/i0y9Y7FtIkj5FsS169dwtQJw7F5w0pSWjGYN3MCWjetiemTx2AKxY8fMwCRURGo/nt98GxpE82+OrdriIsXTpNPPRD86ilfz5s1AeNG9sOi+VORPmMWFCpaXM72oG6qBBKVQLxIelDZFWJJg5eNrR3y5C1EoKYmAshl4ePzXBLy+pvK1WrLt3bKlq+CZ0+fwJZok7kmp34JGtgEBIF2SUw7V9cUqML0jVqiavW6EjTZ2TsgZco0lKr+PlQC7BlwcnSR4IUXhWvIUsw61c/Xh+KikDZDZro0UjsopHcFaAdnp2TkUvJAcFAgXZJ1hyZP/PaWniZFTsncwJsHtSN/ZoDXA3XvNUy+CcrxHBRFg4yZsqHGb/Wp3Vvjp2KlwGsKc+bKBzNyb/KknBhT+8cOWpZWNqT7HEnvGGjiZaAkqgczUsNXLwHlU9QwiADFyev+uP4wGGwtWfvvM+w7x66ghNwV6he8lub8nUDw21ZBoTHUWV7RsEXowr0gjFlxB7tOe+HS3SDiF4KztwLJHeaBAQtv4MqDIFiYEcgh4HOZaFcfeAr/kBjp3tp4+BnO3AzAE3KHsXWI8w1adAO7Tj3HRckrGOcIFG0h0DJy+S25TogfsH/OeuNfcl1dfxiCW49DJc3yve6YtvEedGTduUlxvLbovkcoWXI0MCHLE+u8Y1f9qG4B4EXS7G6DeHUv3+sZgxEeKEb/NRv8Ci/Pcp8+eYQsWXNi1F9zkCtPQQSSH/3+vdtgl0HW7LmRjAaLR4/u4/Gje+Rbt5TmYKY/e+YY+G2XHDnzYsSYmShAbgQDmarTp88kX/3l1z0dHBxRn2bN1qRkjh7eh/v3b6NCxeoYMmIynGh2xuV/r7JW7+vTSEChh/Xxg3vYtmUt+Psr/A2VG9cv4fChvXBwcJZujMAAf/CbWd5ennhCfXX5ktk4dnS/XHScImVqcpdEYce2jdhN1kxewxMcHET0N+BF9I8fP8CKpXNw9PA/KPFLObi4un2aiv9gXFi3ZMycDWx14TcvH1M7PHV/iH92byWQKfBrxRoIJt2yk9rhCOkCRaMgZ+58CAsPxf6928Afg7x544ps1+w58yFnjrxyPQ6vB7x5/TJatO4i12YxXwZTDIgCA/xIL92Ht/dzPHxwB2tXL6LJ2m1UrlobGo2GAO9jXLl4Ft5ez+V3vc6fPY5L508TQMoKN3Jp6cli+IM10zd7u58E7LAFZ8OhZxi+7BaGL72FlfuewJ/cSOK1wV8Igef+keQKuoMJa+/imW8EofSERNzhGdDM2HQfw4gXf1SQw4Idj/DweTg0hJh4zc6MzfcxmIDMoUs+ILYy/rZ7qCx/+NKbBG4Y6UMCsBmbH1D8TTCfEZQ2b/sj3CUXG5fMyJ2BF68bkvWnexhJYfUBdwSG6nD7aShGEzCauvE+wiL04Dzc2lwP/t4O3++4VbfB7rC4NE7/3kN2Aig9+40Efxxw6qzlGEkm/fIvzP78DZ4xBIZmzF2NqbNWYNrslZgxdxWZgPvTDMkAXuswbNRUTJmxFJNnLMfwMTPAayC47YVQUIZm1UMpnUGPhmZ3VarXwbhJ84l2KeVZjt79RyMbgahPBXS+97ZS70/A399XfntlYJ8OGDqgC/jIA9hvtRuBB9gbNBgO6NMewwZ2xcC+HbF21SKy1tSTrgsTcp3wW1lLF87AutWLERoWIhfH9+vdTtIPIvoVS2ejUpXfyJ3VAqamZtTPYy0Bquw/RAJGpCCrWHVyBzI46U/yHUrtcZHARdPmHZA2XUb4+HhhzaoF2LZ5DRTSFTlz50fFyr+R1XgVuB3GjOgDdnk3JVeVtY0N+EOlp04epvYw4PDBPUTTgUJHGZjX5QtnMXpYbwwf1A2D+nUiMLuZ3JENUPyXMmS50eP6tYsYTTyHDuxMbd0FU/4aKq19rdp0h6LRfMjNqbRJLIH/BHbiP846vRF+wTEIDIuhjgUwAEEiG4OLqBgD2NXF54mQyLx6gxH8bZyA0GhERuvBFhjCOZKcB0XmwWt0XufB7jKO5/xMrFAmPg8lF1kAWZL4Q4Gcn6I5+WVgd5t/SDR8AqMQFqV/eQ9MG0n15fSXxPFOZD0onesXL/q7PzUaDFAUBRaW1rC1s4fWxBQMPlheQijQak1gQoPEq2BKcVrwxjTse+fXPR0cHSWdkczPnMaBZ1SmpqYQ4hV8NDM3h5NzMirLDpzOZTGtGlQJ/D8JGMhamCtPAYyZMFcuNi3+c1k0a9kRE6YuegFOTJE9Zx60bttdujGq1aiH4aOnoWff4XBJ5ioHPXZndes5FJ26DoCtrT0yZ86Odh37oCi5ParR4DxkxBT0GThWWjGNryul/1dBNf2lBNh19FvtxhgzcR5+r9UY3BZDRkxGnQbNSScbqT3c0LFLf2ml4XZ1IHd663bdwZOj0uWqoFGTtuDvKRUrURoxMTHgT1QMHj4JI8bNBH/klBcaN23ZAXzkdsyVtwBq12uKQoVLoFbdP8CTsKYt2ss3Prkd2a3VrecQlC1fFT8Rz849BmLY6OlykTOvC3pZ8e/1hHSwotFInct6Ny68z+0KIaTO53Hifeg/N43ysQXQOCeBAVtA+EN+DBIYQIiPZZhIPubFIZGkD45iPhzelZHTqX3Axzfp1JjEJWCUSijxtHfHsjLh8G6qV6lMy+FVjHqmSuD9JMCgOxdZAWr+3lAOdDXomJsAkOkLK4y9vSMqVq2FJjQQ1qnfFIWL/gxLSyvZt7nP8SLXX0pXkFZJ5mVn7yAtCvwvUurUa0ag55eX9O9XI5XqbRJguRcs9BNqUztw4Lc2GQRxO3Aag9VcefLLyRXzcHR0xs8lyxKQ/ZPAUV1kzpIDikbDSRIclSpTCfy23a+VfkP8YGVlDf4AasUqv6NZ6074jcBV/oJFaAJnJfPyjtv555Ll0bDJn9RvOhDoqQb+7IAQP8YoERMVhccP7+HmjasvwhWyat5EdHQUi+etgQEOr6O6cumcXFP1VsIvmPDRYEcIIb9CPG/bI/C6Gd+gd9/8F7wntShVAqoEVAm8IQG2BvK3dPifffKRr+OIeCDV62LkAnqdTietOXFpcUe9nuN18pLpmUdc0Ov1Ml7d/XcJsGxZnlK2ZJ3h8ziusWm6l0CH42Pj9C/aLiaRNB0kL27feIHzcdBTu8b1Cb3ewCxfhgTpsi46CYBfEnzHJ0IIAjhX0LdHG/To3Ax9urUC/w+xIf074/69O1DY4pHI/QshEBoSgqEDu6B963pYTi5elnEipF806qPBDtdSCAFeCMzfmBHix0C6fN9qUCWgSkCVgCoBVQLfuwQiIyMQFhaCP5q1Q89+I2To2LU/UqdO+1bQxwBx25Y1OH/upHx7jj8V8jV4dpXvvbHU+/swCRiJ3GAw0uxIDT+qHOIUEx9Zcf2ocvjR75vbnvsAqQQ5sH2kPFRd8h/0aWwbsFbmVkiCQEWzC7dosZLkwquC0mUrg92I1ja2sk+8XiN2X925dR1rVi1Epcq/I3v23BDi6zCEqGDn9db6Qa811CG5S1qYauDqYgm3ZFZq+EFl4GhnDo2iwNbGjPqCtdoPftB+4Er3bWdrBv4kiIO9OZK7qjrhi+tFFys40PMoknCkNpKLlj/LcPP6FQQFBoBQDgAeLfDGFhkRgS2bVsFoMKB1+x7yzcQ3iJIoIglFmER3rBabqARobJPx5mZauDpaquEHloEDDXAajYCNlQncnL5QX/iB5f21Pm9u1CZ21ibQaBQ4MPCl66+1rt9tvej5s7M2hUKTUamgv/DOwtJSfvdo5rQx6NGlORrVLY9Rw3vjuedTiLhB42WdBC6cP4XzZ09IoJPMxQ1f01vKnwTssKmTTZxk8Xp52+rJp5PAS/nyyadjm4ATfxSR20+n0yM4NEoNP7AMwiJiwM9zZKRO7Qc/cD9gPRBBfYD7QniE2hdYHkkRwqkNPqPqTzAOxL9gF1qGjFnQo+8IjBw7E4OGTUS58lVx6MBu8P8Yiw/AhBAIDQ3G31vWyO8hlSz9K6JjosE84kJ83klx/knAjqW5Bi72sebOpLiJ773MWPmaw8xEAwYkn+N+4x4mVmz8TaGvNMh/26HWzfBZ5aDXG2U/0xuMpLA+b1lqW37d8uU+wLpBp/+66/m99iP+Hp2eZB/7RH4Ozf9unlbWtsidpwDyFSgqvzNUv3ErpE2fEZcvnkF4eBjEC/+aRqMBr9U5engfwkJDsGLJHPCXq588vo8b1y5hyYJpCAsLhRDi3QV+xtT/DHbMTBS0rZ4OE9vnQp70duCH4zPWN0lZMxDgwA//l6qIQn2jenE3TOmUCzVLJIdOl/DVyE9fDwHx6ZmqHFUJqBJQJaBK4AMlILGB3H1gxk9EriEXpkKDkNFokOOCVquVnC0srWCiNUFc1QToj+j4X/g8JoDD/1Zlz67N8l94PHl0H/v37QCv55GZk2j3n8AOA5vMqazxcx4n2JJ/n79QTPebRLcSr9jPcGpuqiBXBkK5GexgbaH5JCW8j5XGSJ0oIkov5ftrEVckIwva1+IHVRQFgpC9ENTRXxxfF4wQnBYb4qcJERsnBB+Zj4if/NZzIQSEiA1vJVITVAmoElAloErgP0mAAc6RQ/uwfet6+b2dK5fPY9WK+eD/hchfqDazsMS5sycwbmQ/XLl8DgULFcPGbUexZedJbN19Cpu2H0P+gj/h1yq/Y/nq3XB0cpZuLSTRpvynco1AsVyOsLU0wY3HIfAOiJQDEVs+dGQKZ958rqdzPvI1W0Y4Le7I9nI+jz+AE1vINSR8QpkS5Kc4zs9Ai/PRuEcCjF0gzvFcjsEAsoAYpamf4zgwDy6L2El6jtOxeZD4cVz8wLxjaYW0VOmo/imcLNCtdkZ0rp0BGVNYyX88ymVxGof4dWFecWl8zvcmefIFBfIOSL4MDJmO81K0/L1+33qq452nYfJ/jaV1tUDujHaIrZskT5KdEEKW6+X1HGfPnMKB/f/g2tVLZKZ8ZdZkAgZDTHPyxDE8eHCfo2QwUAN5ejzD4UP/Ys+u7bh08TzCw8Jk2rt2Qgg8dX+CkyeO4tXSefMAABAASURBVOlTd9nX3kWvpqkSeJsEuG9qyPQuRGxfjqOLjdcisbQ4mvhHIYSk1dCMl/NC3T6ZBBSNRspWiIRtlGgBRMNtxkGIxOk5TaPRvlVvcPtxOtMJkZAHp7FVI7G0ROvzlUV+THV4aHR/8hDLFs/CiCE9MGpYL5w5eRQ1azVEpaq15UccPZ+548L50/D19YGGZGtiYirfwDI1NZNHe3tH2NnZw8TU9K1y/5i6fUwe5WMycR4esG2ttchLgy8P9rcI7LAFgtOszDX4ObcTGpVLhXplUqJgVgeYkrvLQJmyprZB1WJuyJTSCiUIKDUqnwrViieHq4M5ZWXxAqYaBQUy26Nu6RSSxy95ncmaopWLJpM7mqPKT24y/dfCrmhSIQ0yp7KCrZUW5Qu6oGHZlKhTKgWqFHNFZaIrmt0BVem8dH5nmJF1hsGFjaUWpfM5o9pPyeFoayLBDxUuMYQJlV00uyMaUN3/qJAaZfK7IL2bJYrmcEAKFwukcDaXlqwSuZzAbypUpDqUovoVp+umFdOgON0Tgxt7axOUo/qwDOqUTInc6W25CFmGK1lnKhd1Q9Nf09A9pkT2tLZg4COEQJFsDqhP98BllyuUDFYWWnj4RMCdAjMomdcJGibmiyQK/D9ntm7ZiGZ/1EO7Ns3RrWs7tGrRGH16dYUfdXohhOzYer0eE8ePQYd2rbB08QJqP0KhVOfjx46gQ/tW6N6tAwb074U2rZti+rRJlB7b/kTyxk8IgcjISPTv15PytsaGdavBA8wbhGqEKoH/IwEjKYHnzz1x5/YthIeHS2ohhPw/Ps+ePcX582dw984d6o8GKGS9lASJ7HjwCwkOwdWrlyVgDwwMlDwSIVWjPkACcTJ/SBOka1evgD9Kp1GUt3LQECjif2tw48Y13L59E9FRUQnaTdEo4P9jdefOLdy4fhUREREJ0oWIbXtvLy9cvnQe168RTXiE1GFCxOqyJ0+e4MzpU7h39478n1tCiLfW53tJUISCGr/Vl/9TrmuPwejVbyT+mrIALdp0hZ29A42bBpQs/SvFLUShIsXJwBBDt258GbhdOnUfiCbN20NDbUAJSfp7ew/6P9VihWFnaYp0BAR4tbiHXwR4KGN3T4ffMmBo82xoVjkN/qyWDiNaZsPvv6SQA32FwsnQo14mjGydg2iyo0WVtOheNyO61MoAK3MTOejXJpAzomV2tKmennikxeCmWdGuRjpoNQJ5CFx1rZMBwym9Z4NMEhiUL5gMHanMfo2zoEXVdGhXMz16N8iMvg0zE490ZJHJRGVkQo50NtCRpYQBVycqr3u9jARkrMDgBLQZyIJT8+fkVK9saEn1alIxFbpR3RqWT4UaJZLDjACbhakGv9G9dKb8GZNboePv6THgjywYRHVkgFKtuBvcCLj1apiF4rNS/dPI+oxtkxMMzmwJvHQlnj3rZ0KjCqnwZ/W0aFElNQEnU9T6JTlGk1xa0z00qZia8mdB/kz2CAiJhrd/FHUuowSFFmafb6EyieGdPyEEDh3cj2FD+iMgwB/DR4zF8hXr0aBRExw9ehA3b12Homik0meLz6pVS+Ht/Rz+/n5Uf8BAVp27d28jY4ZMWLZiHRYtXY30GTJg2bJFNPjcpIdCk2j5Go0GK5cvxoH9e+H1/DmCggIhEqVUI1UJvF0CCg2aN65fQ7Mm9VGpYmns/2e37HMMenr16IIKZUvg9xoVUbliKbT7sxkC/P0hxJs9jfvjvwf+QfWqZfFbtV8pTyVUqlASe3btfHvhX31K0leQ2+fxw0c0efoDv5YrgRrVKqBWzSo4cuSQ1Cmv11AIgePHjqImtVnVymVRtXI5ytsYjx49lO0mhMD1q1dRu1Y1atPSqFa1HBrW/00CGkWjkTShoaGY9NdYlC1dDL/VrIxqVcqhX7/uMs3fzx9DBvdD5V9Lok6tKsS/DAbSBC0wIECmv16f7+3a0soaGTNlRbESpVG4SAmkSp0O5mbmkMqcbtbG1g7p0meEBbm0GBNQ1MufEAIpU6ZBMtfkFPfmM0SRX/T30WCHa+lsZyIBQLTOgJBwHXjxbAmy6JQt4Ay/4Ggs3vkYfx/3hIlWQZWirnB1MHvpvnG0McW9Z6G4dDdIuptyZbBDBnIPpafAC3JJmth46BlW7H2C0AidtLDkJOuIngZLRk1sPfIPipbuM2c7UwJBtggKi8HS3Y9x8V4QDarAM7KG/H38OW65h4CtOcVzOsm6ZEtjDVuy7ngFROM2pSlkKeGGYppyZI3RkFQOX/bFrC0Pcfiiryzj8v0g6AgM8ar/y8T/n7Pe0pXFcmCrVWS0ATcehcDdKwJlC7gQSLGFT2AUFu54jIPEw0Qr0JhAE8snexobBFNdF+9+gmV7nuD6wxCYE5CqQUCL+gfO3AzA3L8f4cglPwSHx4CeKgQSPRnGYElAhy1KLAN84U0IAQYZ69atgrWNjQQ5terUo4fgJ/TqPQDbd+xH3jz56Tkw4Mnjxxg1cjB+KVUGJX4u9bKmiqKgSdOWmDB5BgoUKISCBQujbLlfubnh5eVJQEl5SRt3wnkuXbyA6dMno1btesiVKzeVwTOIOAr1qErg/SQQEhKCVauW0WD4AKEhweCBTgiBRw8e4NzZU2je4k9MmDgNpajfbtu2RYJwIRIqagY6D+7fQ9fO7QgoaTFk2GiMHTcJOp0OkyaOJVer6mJ9v9Z4k8qfJkUTJo7GxQtn0blLTwwZOpLcIabo1bMzPD09SRW+agshhLS0jBo5SMp++PAx6Ny5G1l3bmHEsIE0Bhjg6eGBEcMHIYD49uk7CH36DIS/nx/69e2OkOAgaS2eNWMKFi+ehyrVqmPChGkYMWocihf/ReqYJ08ewf3JY7Rs1RaTpsxC6dLlsWH9GvyzNxYkv3kH318Mj408SeXwLd+d8l8qb2dlIrNH64wEdvRy/C2c1UECCt/AaBqodQgMiYGeQIKDjQlSJ7OkDmiUee64h2LSuruYt+0hPPwiyaqjIVeVBplTWsOF3DxBoTr4EJgJJhDFQIJdUFlS2YAHfGYQTIM//xPSUStug4GImYkGQaExOHHNH3eJt54I7z0Lx76zXrj6IJgAlRHFczsiFbmishLYYQB29IqvrCM/PlwrDlxXhcCPo40JmSsN2H7iOfac9sbeM97yNVyuyw6KW7XPHTFkJeK6RBHQ2X7CE8OX3cSmwx7IktpagkBPuq9AqlNIBMmA6sMus5TOFhLwmRIAdLUzwwOPMOw65YUgAjUxMQZ6mAFbcsnpiPfaf5/i9pNQsnYJBNH9sgWKLWfWZB0ySmlz6V8uCCHwnBTO7Vu3ULpMeWTJlg1RZDJmtxYr+nTpM8DG1hYRkRFYuWIJggKD0Kljdzg6OCaopImJiVQyPj4+uHXzOnjdj6urG80gslBf0SegFUIgmJTSksXz4UD+39Z/tqdZhEUCGvXiy0rgWy2NQcqZ0yeov50kq07Vl7fBSjwdWRcXLl6Fnr37ExhvgY6dusnB7v69uzDSs/uSmE4YfD+hAZBdYeUrVELzVm3IVN8KRX4qhrCwUIQQiCIy9feBEhBCgOV94dxZaoOWsi2at/wTLVq2kWBlz+4db1h3zp8/i2fPnqFf/yFo2bot2rbvjGrVa+L0qROkW27g2rUruEvuq85de6JDx674s20H1KvfGOzOunL5Eh49vI9du7ajeo3fCbBOQMPGf6Bps1ZE0wg8yGfOkhVjx09G9x59UL9BIzAYdnZ2xv37dxOdmH3gLavkX1AC/wnsKC9yc6dgcGFOLh4e0Ln+mVNbSRdSvbIpCZkrchDXEIjgNA4evhFw946EN1k/ggnYUD+XIMnZ3hQMPpKRFahZxTTSnZSM4jgPu7EEIxK6eE5unUv3AuFPFqTHzyMQFqmTQGYIuc/YVcZF3X4SgvAoPRjsMFhgEMVWI3a9sSXqzK0A6tDEjH4KVSAsUk/A4zkBNx1ZiuzQltxhnWpnQKaUlgR0YsEcufsRRaCEA2RNgRCyPHEZPgTwosnKxWAFtGVPa4MOv6VHxcKuBH405IZTJLg5S+WakiWnajFXdK2TSa7b0VD5m454kBVLj2xk+WFXVndyd2VOZUWwxkgAiRjST9EI4iPo7Mv/FGpwXwIogeS+ypw5C1UgYT140KBIXLtyBdu3bUEbUiz5CxSguhs4WgYhBCIiwrF44Tx0aNsCrVs2wZkzp9CsRWukSZMWcTwkMe24b504fhTHjx1G1x69yeWVBgbjK35Eov5UCfxfCXDfjYyMxJLFC5AlS3aUJ5ASP5OlpSWB7UwwISAeERmFi2RJFEIgY8ZMEMqb/TxVqtRwcUmGY9Qvz9PgfPjgv+TePYD0ZNJ3dXOLz1o9f08JCCHALzLwxKlI0WIvJj4C2bLngBW5Uy5ePAdux5fsSBnfuX0TKZKnQLZs2REdHQMzMwvkzJVHTsKePHkkrTIaclcVKlxUpiuKBrnz5IW5uQUBnmu4RRM3nrBVqVIDPt4+uH79Ok2ugslip5HFcL9IkSIlNFotWY/0ZDW6iaCgIOoXmfG6rpIZ1N1XKwHlv9QsLDJ20GErBb+OzS6eyOhYNHL8ih+GLL6JwQtvosfMq+hO4cKdAOpEsYqDqahvy+LjrBTUdxFOgIMj2TozYtktDFl0E73mXEOnaVew9ZgHFBrsOf2FNwsKKSIncmNZkHuHAYiWmIaSNWj94Wf4m6wtWrKg3H8WhqfeERKa8JocN0dzPPQMw92nYdBQfubHgWu29Zgn+sy9hn/IkmOiUZCDAEvJvM4wIT6ShoiEECBjFYEQjgEBJroDuiFmpaME/hAUp+wjV9eA+TcwcMEN9Jh1FZ2nXcbBSz6YtP4exq2+g/tk1XGmuvNi7rRulmCw04Xuc9ep5zCQMLKQhahqseTQ0j3bkjVHoXINNMtk6xPz/9JBCEFALwrRMTEEYE0TLT4iPByryU2QLJkrWv3ZARqSG9dbURRoTbTgTVE0sCULkIOTExwcneT3F9auWUEm6XvUHrFKhuk4BAYGSH4FChZBHXKZgdCuEAoE8SAdBkF/TKcGVQLvkgAvJt64YS2u00z/jz+ay34Xn16j0eLC+XPo1b0T6tSqhmFDB5D7tSSak1WBAXd8Wr1ej0wE9qfNmEfu2keo/Xtl1K9bHU5OLhg5ejycnV2kToifRz3//xIQQiDA3xcajQJH0g0GUvIse0sCoiamZggKDIQuRveSEY8+fn4+crGsBdHIBAG6tgeD1sCAADAwsbWzJ3BjTsmkpGnv4EDeBwK1vj7e5OZ6SmX6oWfPzihcMDdKlyyCCuVKYM/unVQPjWzHEzTZ6t+3B+rVie0XpUqXQ6XK1Qj8vKoLsVV/X7kElP9SP7+QaLBFh4GAjaUJdDTQPyIQYaABOSO5o+ytTaTFxcHGFLzexkgDk6Dw9jKNeOoTgUhyC6VwNgcDgFByAZmRxShPRlv5RtfreQVFuJDby8pcC34b7Ba5sM7dDoDQ8yzZAAAQAElEQVSnbyT4dXEeaHmB75UHvDbICI0iJJC49jCEgJUO9HwRB1CnBqwsNNIalYpcTTtPe8E3KIoSQDSCBngD0RhhbqqgXAFnVCqcDOQ5Q/xNgMGAHmx1Yrnwa+K8viYiWge2VOXJYIcc6WxRv0xKeAdEYfMRz5eAiWXV6fcM8rX2fy/6EhgLp/IADQEdQYUwH65rJFmq2ColqCyK/qI/AykfB3JJ2drakJJ/Aq5P/ArwgHLz5g0cPnQA1tbWWL92JZYtWYL7D+6B34RYtXwJ/Hx9pRuqWYs/MW/+Umz5e7f0y7uTW2D+vJkkD+olxFgIQQrLFOfOnsapkyekslq6eCFWLltNrjQPXL1yCatXrkJkVGT8KqjnqgTekIBCQPsW9ctxY0agYsUqKFykCNEYKbz6UXdDaGgwnnk8g04XA2cXFwQGBII/m6AncPOKEtTvBaKjo8H93dUtBdxck8OZAA4Vgxs3rpNVIRLq9jESYLnqpH6Or98E6WyFAusfngS+4mykdoih9ngVQwoE3N5CCGpHPWKonYQQ8QhA9DTsUZye9FnUCzd8gfwFMWXaLIwZ8xdsbWwxsH9PeHt5Sdrg4GDZLyKJNlmyZHJt4YULZ2U5ULdvRgLU6h9XV+4+gcEx8KJBmxfN8mDOoGf/eR9cfxSC5E7m6FkvM8a2yYFeDTKhclFXAgecC3KjCbo8GmlPRgzagywYCq49CAavpWGA07JKWoxrm1O+ldSgbCrYWmoJAHAOSQ7JjS4DQ6MJIOnhaGuK/JltUaFQMuk+GtgkC9gNFEMg7NztQISEx8iMQaExuPowWJ7H7Yz0lGjogWIrTs8GmTGkWVbwgmrfoGhcI1oGYewu43vkjyjyK/VajRKbnepA2eW5jso6ctkX98ialCaZBfo2yozRrXOiO7mkKhRJhmTkkqtTKiWGt8iOdjXTgd8Au/M0VK5P+jmXE/gtLX67i9cV+ROYPHXdT4I8F7IAKfSA+pHMGWTSqSzvS+5Y2bi5JUeqVGlx5PC/ePLkCQESEwJkGnrwNXj+/Jlc9JkzV24aOEKw7e9N2Lt3J82enhE4eojd5Bv3D/AD8+Ggp0GEZ2B58uWHPc22/Px85cyN48PCwmRbm5iaIkfOXHjq/li6xvb9swv+/v5kBbojeUdGRkAI2RO+pCjUsr4RCQhBExAapNasXgFv7+ewJHfI9m1bcfDf/bJ/MZg+c/okuB/9VOxnzJ2/BEuXr5OLlAMD/cGLV5+6P6H+rch+JoSQx1MnjqFbl3bkEstKeZZi+sz5cHRwwqiRg6WFSAjxjUjoa6qmUU6SWDeEhoZIOQvBACia9EIMbAiEmLywDnOtBQSsbWwQHhaO6KhojgKRg63LetIt9g72lG5NuiiUgI9OpvOO3eic7uTsLAFrsmSu6NCpGxo2aiLd6b/Xrid1zK1bNyhdgzJly2PmrPlYRv2CLXdsMZo8cRzCQkOpPMEs1fANSED52DoKRcA/JAo3CdiYkrUjYwpLafV44h2OaRvvY/72h3L9y5Er/th82AP8lhS7uU5c85NvIB287AdG6VFkxdlNVpSle54QQAgFr39ZsvsJZm6+j7+PeuDwJT/sPuWFOVsfkqUlmlxPoVi5zx3byEUVEW2QQCBLKmv5ltK5WwEYtfwOVu1/ShYlA3htTr6MdvIWn/lGwNMvUp7zN2uePA+X53E7hZ6SMHKhzd/xCNuPe+II1W/twWeYtuk+zt4MkAuZZ299IMveedILO6lOz8gKtWq/O9Yfegbmjxf9/ioBtukkgwXEaw/dG7/Zte7fZ1i4/ZFcTL10z2McuOCDfy/4Yv7Ox1I29wjwLNj5SN7XUXIBbqCyJ629h2NX/eSC7ZQuFqAqgsEgyyyu3l/yyCZlF5rxVqpUlXzr96TJnwcOHiwWLZyDls0a0wBiwLSZczCHrDaz5izCpMlTUZBcUMWLl8SkqdOQnPzry5YsxOKFc/Ho4QPcvXMbmzduIGuNJ/LnLwATUxPwK738uicvXi5RoiTmL1yOWXMXYdachRj/11/IlCkzfv21MiZMmiAVINfrS8pBLevbkkAMuV158HRwdMTOHVsxccJYsEuL+83u3TuwZ9cOGkx10nrIH0BzcnKmAe5XubbDx9cbgeQ+EUJAURQZeE3JwYMHCNx7okXLP5GPrAKlSpdF/4FD8ezpU9y6dZOeAyPU7cMkwO3BLypERUbi8eNHUhcIIcCfmoiIiECOHLmIoZBtwG3B6jY5WdaePnNHUHCgjGegxG+CCkUgZarUsLWzA7/gwDzYEieEwONHDwkQhSFbthxgixz3j4CAAACC2k3AzMwMvMXRW1hYwNbWDo7kci9W/GdkyZoVz6hM5sv1YNpPGFRWn0kCysfy5Y7GX/s9ddMfvEYlV3o7sryYUGcBuWDCwIP17L8fYtrGe1hIA/rxa/7S+HHhTiAW7XoMBj1s0YnSGbDnjDeWUNxjr3BoqJOyi2fHyeeYu/0RphPomU1AhwFRVIwBj59HSLDEYIMXA/N6Fhc7M7C7x47cZQ42WqqHFqZa7riAT2CMLDcZubr4bTAdWV7uuIcRUIudCcS/fwO53xhczN32ENMJ5CwgwHbyht/LV8xvPgnBwh2PMHXDPWw77iHB1xoCVusJmDwnC1ccLz3xuUW0/MbWLKo781qy+7F8pdw/JAabCcTN2vJAlrGWwNIjAl6c5wiBHH7lnOkZKJ0k2XJ9M6SwAq/t0RuAE9f9JUiMK+tLH7VaE/zRtAVatm6Ls+dOo2XzhvK7FEMG9SUlYUEKJCfNcF3g4pIMLjRjcnJODnMLc5pRW8HJKTlMtKZwp5kyr4koWjg3iv+UD0uXzEfFSlWIZzuwe+AKuah2bt9K1pwnsCRfPCskFxdXyc/ZJQW05G+3sLKEo1NKKDQAfWkZqOV9OxLgAZT70MjRf+Hi5Ts4dPQsDh87Sy6L2bLv9Os/BAOHjJDWmDWrVhCAeU5WgihyXx2V7lMnJxc4E8CPjo7CokXzqK8uAA+8vGCWed8hsG4wxEjLwdUrl6mvW8De3v7bEdBXVFPWv1mzZafnPBnWr1sNj2ce0pW0Yf1qqRd+q1WXLC6+WEztsHXLJigaDRhoshV44/q1sl1uE9BkQMuL0PPlK4Ds2XNKt9SypQsRFBhEQOcRNm9ajxQpU6FAwUIEXLKBMA62bF4vLTWsm3YT+GXQyxZlXse1ZfNGWY8YAs2XLlwEv43qljwl3AhoGcgVBnX7JiSg/JdaammguXgnCNfJzWNhpiCFsxmBHSMUAiwmJgq5pQQ0fE7Ag0EJaNNoBMxepNEl9zMaAAVMKU4h1C3jBChOSZDfhHiANkWBpDWlayIj95UBpwkUPPGKQCpncp3Vz4waJdzIsqPDLrKqnL7pJ/nwWhkQ7PEJjMKlu4GI0SU+89Iq4mXZ7LLScoFULv9i70UB3wO7sLi6XG8OlI1JXgaFIjie7zt+Pq6ziUaRddKSLJiGaUGbCV3zfWoob2zZAnRKco216hw47y2BpMIFI2k2VvDW1tbo0aOv/K7OoiWrMXvuYmzcvBPLV62HW4oUiK8AeKDp2LEb/mzbkeSmwMzcDN169Cb6HZg6fS6mzZiHtetptj15hlzLo9FoULduIyxasgqFi/4EVjDx79TG1h5Dh44GLzLlr6LGT1PPVQm8TQImBJDNzc3BwcyMjxbU3yxhZWUlF9u7k5t0zOihaFC3BmrXqiq/oeNMgL31n+3IbZuaBll/rFqxhAbFDQghK0LV6tWRv0BhTJk8HrV/r0ahCqZM+QsVfq2En4qVgBDibVX5NPHfJRejlHWDBk3w6NEDuej7j0a1JRDt3WcgUhJA4XU0DEy2k4tcURTkzZuf2qsuNmxYQ21QGe3btSRgFCP1k1arRdbsOfDb77Vx9Ogh1PqtMlq1aATP5x7o0bMf7O0dkDlLVtSoWQv/7N2FmjUqoUWzhnj21B39BwyldEc5MRs3ZjgaNvgddWtVQ5/eXcB8e/TsA0WjyPEO6vZNSED5L7Xk55k/ereIrDIzNz8gV07kF3/I2RV2gFxCf625i1lbHmLetkfkAnuA8avvYi5Zltg1xWrnxqNgsso8BlttrtP5f7nvL5mXIdnpG/6YSZagNQeeEkgzkIy/ZA3eLIvBjJYGjzx586F6jd9Qp24D+eaKpaVVAqDDOVkx5KcZVF6i5WsGSzbkey9G5uBGjZuiQcMmlLcUDTrWLxVH2nTpULJUGVhb27yM47wcTE1N8VPxEshKJmiuB8epQZXA/5MA97u4YDDokTFTJgwbMRYFChWRVplqNX6XwLtR42YoV/5XAuR9wOt3eCDkfDww9uzZH1269oKDozOyZcsp0/v2G4zSpcuhQoXK8nssDMTd3JK/0W+hbu8lATMCpI3+aIbJU2ahPoGeOnUbYsKkGWjarCXpFj34tf6OnXqgTbuO8tV0fmurW8++UvaVq9RAq1btMHnqLPxSqrRsV2sra7Tr0BUTJk5H7Tr10PiP5sR7NqpUqynzs47p1Lk7xk+YhsqVq+KPJs0xfeY8/FarDqXrwO7JcX9NRb36jVGSXJX8ocNZ5J4vXaY8pevf655Uoq9DAv8J7PAtsCuKP3x36JKvdOswAOL4LxmiYgxgt9G+c97YSe4vXiTN62YiovUvgQEvGN59xgvHr/qT1edV/Jes58eUxfK9/ywMhy76wt07AorC0O1jOH3aPDwA8NoFDnq9XioW41u+f8PpHOJqYKSbisvHAw+fc1xcOoOY1+Pi0piO0zhfXJx6fKsE1IREJMB9yIWsNs2at0L69BkkMGELDw9sLVu1lR8UbEwDbq5ceeh5i529s2WoctXqKFO2PMzMzGjgNcjvQtWt1xDtO3aVg2/16r9JlxfzT6RYNeo9JMCys7S0xC+/lEYrcpW3aNUGxUv8AlOSOadZEXhhl3eRosVlG3Acu7krV66O9u27oNEfTZErdx7S+7F6ktPt7OykxY2ty02btZLuK61G87I2Tk7OqEbgp0OnbmjWvDWlF5bWGyawJiv2LyVLybp07tIdDWmCxu4tRfnPQyezV8MXlMAnaTEGODJ8wYq/XpQsn/s3hbhzOn2djB6CN6K++oiX95PYDX31tVcrqErg65QAD4RxNeNzBtmgZ4wHMr7mEJfOR77mwOcc+JwD0wshXg6+nKaGj5cAy9RAEychBIQQBEYNCZhxOoe4SD43Mv2LiaCRJlNxaXzka25bIQRAP75GvI2vuTxuR47maz5y4HMOQggCvhqqi1EGqNs3J4FPAna+ubtWK5xQAuqVKgFVAqoEVAmoEviOJfBOsGMghMyLzQ0GI81a1PDdykG2M68Oiu3pfKYG4EeVQWwveLX/UeXwo9839wCWAR858LkakkYvsPw5kKomyxLVgRpCPX+7HFhWUoHLk9jdO8FOejdLFMvpiKI5ZFCP36scsjuiQBZ7aMgMrFAwNdHATA0/rAy0WoWt/dBoFJiZlxYDJQAAEABJREFUqn3hR30WWA+YUB8gDw64T/yockjq+5ZtQE+khZkWdtZmanhPGVhbmEAIgbhNiTtJ7Fi1uBvGt82J0a1zqOE7lsGYP3Ogf+Ms4H+FwZ8MsLc1gxp+XBlYW5qAQa+luVbtBz/4s2DJ/5OPJkDcJ1Sd8LpO+DLXVtQGPGa7OFkgY1o7ZEhjq4b3kEHK5NbQEliPwzbvBDtHLvlh8ob7mL75gRq+YxlM2/QA/OFH/jhkeIQOT5+HqOEHloGPfwR0eiMCgiPh7qn2hR/5efAPjJR9wZf6hNoXvvyzwDL3C4yQy0j8g9Tn8X2fRZabl2849PpXi9vfCXauPgjC1qMe2HbcUw3ftQw8sPesF/h/iEXF6OEbEEUhUg0BP54MfOieg0KiSLkaEBYeQ30ggsKPJwdfksOnCt8qHx//SISExcgBIyg0Wu0HSdQngkNj5DqdUGoLnoh8q/3pS9c7MJj0GC9semHaeSfYEUKQORvyK75kyVSPAt+pDKidqa3xYot3+iJGPfwoEhB8o3LHJ2pQJaBK4GuSgKqbP6A1XtNj7wQ778OWrURs8o4L/D+e4oGplyw4Tk+mcbYeMC3TxSXyOcfFBX4LzBiXSEeZ12CU5lSmYXq6pBT1l9QSUBQFGo2WQHHiXYnTObxeTyEENBqNDIml47VNCAH+GjPnEUJ5LfV7uFTvQZWAKgFVAqoEPpcE/tOoodUIFMhsh5J5nfFLXicZCmW1h6uDGRQ2BcWrtbOdKQplc0CVn1xRtZgbCtO5jYUWluYaeV6S8nP4JY8T8mW0hwvR0/gmOdham0gaLoNpiudyRPY01uCFW5JA3X1RCQghwP+XysfbC5cunsGxI/tx8/oVhIWFAJQG2oQQCA8Pw5VL5/Dg/h3pFqFo+dPr9Xju+QwnTxzGoX/34NrViwgPC0NcXry2RUdF4eGDuzhyeJ8M9+/dQkx09GtU6qUqgY+RgPjwTNS3ZV+Nf8RH8Pnwkn+wHCxTDl/mtoXgsjgkXp4QAkKIxBPV2K9eAsrH1pC/OWNPIKRb3YzoVT8TetfPTMfM6NMwC3rQNYOeuG6RK70tOv6eAb0bZEb3OhnRnfL0ofNG5VMhc0pr9KibSebt9YJH30aZ0bNeZuTJYEeDpBG50tmgK+WLS+ey+jXOgi61MiK1i4X0Z37sfXxr+ZK8vvSwR0SEY+eOjRjUtwNGDO6Ov8YMwOD+neg4CH6+3tRmBgl+Jo0bjEH9OmLrplWIioqMrTqZ6c6fPY4RQ3pgyl/DMGvaGAwd0AXLFs+CLuZNAMP/GmLXjk0YNqgbZk0diynjh2JI/87Yu+dvVfHESlTdf4QEhBA0IdNQX9WR/ohvR4bc2NooRCyoJwIZF7czGgyU77VgfLUQMo5OPX6cBIQQZPHVShnrdToIRaFnXcG7tpftZdAnSiaEkO3NEy3+IjLibUIoVJ4GMTExVKYezAtEH0fC10IImc40QghKFnHJ6vEbkcC7e9A7boLVA7/W5WxnBnNTDe48DcXxq35QqCMUyGyPykVdYWqiwIEAUdNfU4OtMbZWWly6FyTpdOSH4m+72FCcvU3sq65nbwXg0t1AWJhpUJAsRC0qp4FGEdL6w3zMiN+FO4G45xEGLrd0fmcwYDLRitf1EdTt80jASO12/OgBzJ35FykGA7r1HIKR42aiXsPmeOb+WFpsrl4+jzEj+uD+vdvSuhMY4E/tY5QVMsKI4OAg5M1XGENGTsbg4ZORJm1GbN28WtKzm0oSvtixcoqICEPlqrUwYsx09Ow3UvL6mwBUCPER4qO78IsS1MOPJgGFBk+9Xod9e7ZhwZzJePzwHoR4NXhxHwwLC8XmDSuxdPFM+Ph4yXRF0eDenVtYvGA65s+eiAWzJ8mwcA4fJ+LJk4dQiPePJs9Peb9CCEST1fbEsX8xZ8Y4TBo/GNs2ryGdESDbILGyNOQODyWr8qb1K7Bi6Rw54RLiVXsqioZ4RmHX9g1YsnAGPD2evuQlhEBgoB92/L0ekycMw4wpo8lSfYAmXjGyKCEEvJ57YuPaZZgwdqAMf29Zg5CQ4Jc8JKG6SyoJvHe5/3mk4MErJEKHrcc8MWTxTew9w4oBSOlsIYHKz7mdkY/AD03osXqfO/rMuY7Bi25i4IIbWPGPO/h1Z+pPCAqLwfI97hi27CYOXPChIRFIncwSdgSE4u4mIlKPBTseY9Ty27jyIAjcnXOR9YfBURyNevy8EggNDSbFsAHm5pYYM2EuypSvgly5C6DBH39i2pyVyJI1B7g9a9driqmzliN16nQSFMXVSggFv1asiQ5d+iF7jjzImTs/ipUoRcolGuwWY8UUR8tH/qeLfzRth0ZN2yBj5qwoVKQEcuUpAF8fbwmkuCymU4MqgfeTQOzgNWpYb/Tq1gLr1y7Bo0f3IQRrE+YgJOju2/1Psj52J6vkanh7e8p0hSZe9+/dxPLFs7F4/jQsWjANiyksmDsZc2dNwK3rl6Eo/1mlciV+2KAnF/eObevRu3srrF29CEfJRT5iSE9MGjdEtkFigrl75yZ6dW6BkUN74O/Na+FL1mUh4toT4EnYwL4dMaBPe0pfTWDH/SUbBi1sMR42qCsO7tuJnQSI+vZojb07N8s1ggE0UZv01xCMHdUXZ08fwYVzJ6lf9MA8am9eQ/iSkXry1UvgkzyZJhqBdK6WKJXXGVnTWIMXED/0DENElB65M9pQJwUeeoZj+8nnIBAuLT4PKJ1BDdOylHj9j7ODKQEcKzjYmIK7akhEDMIj9JwcGyjSzESA+zGDJCPFxuj0NJjyGV2ov88qAVbkXp7P8PjRPfxcshzckqeQpl0uVEcmYGtrW5iamiFPvsJgsGNuYQlWXpwePxjI5B8SEoTgoAC5FufUicNwckmGzFmyE70uPqk8j9HFSNqgoEBcu3KeXGSXkC1Hbjg4OEkrjyRSd6oE3kMCEWQlXLZkJp48foAavzcAaRMIIV7mDPD3BYMXRaNB8RJlZZoQsWqSXarlK9bAnoMXcejEbRw6fgu7D1xC9d8aIJlrctnvDWT5fMlMPfkgCQgh4PH0MbZuXIX8BYqSbC9i/dZDaEwTnX17t+Hi+TM0fmgS8OQJEgNN1jU/FS8NIYQMcUSsY+bPnYhAatcK1Hax8UIehBDE8yRZcvajbcc+2HXgPJas2oHceQth2ZLZ4DWHD+/fwaULpym9N7buOo0FS7eidNlKOHp4HxgIsU6UzNTdVy+B2Kf4P1bTylyDWiVTyK/w5stkJ9+a8vCNhEIzIRc7M8nd0zcCUdGGlx1RQ2kcZCLtHAngtKmWDgObZMVPORwQGBqDrUc9ERmtR2zXBEzJXVU8lxPqlk6J7GltyGUG3H4ShqgYA3FQf59bAkIoCAzylybc1GnSE8jUJyjSSCDGyCY8imWQI8/jGo/i4n5RkZHYumk1RgztKdf6XDx/ChUr/wZXtxTE87W2JIXEAxDPpIcP6i7z+Pv74ddKNWFmbq6CnTihqsf3koBWayL72qjxs1D+12pv5DG3sECd+s0wfMw05M1f+I10DYEgS0srWFlbw9rGllwmXrh+7RLKlq+KlKnSvNl/3+CgRrxLAg8e3CWZ+qBKtTpwdHSGtbUNfilVgeRtgyOH9r4BdqysrNCgUSvp4s5LIEXyjjf3NTUzR81ajaQVmidoMv3FTlEUXL50DrZ29rJPaDQmSJ48FQoX/RkeHu64d/cWmIbJ+chsdeT+5Imdja0dTExMVP3DwvlGwicBOzq9Ee7eEbj6IBjP/SMJlCgoXyiZBCRCvBjtXhzeJhdOdnU0Q+aUVuC1OfeeheJfcmfFZed8/L9BGpRLhdqlUsDJ1hTXH4Vgw+FniNYZEZ+OadXw6SUghAAvGNSTqZmV/seWoGgUUiopkSlzdmTLnhtWNjY4uH83bly/Ao1Wm5CtETAha1FqAleZyUWWNVtOWYddOzfRzMrvpTJKmEm9UiWQuAR4gMqdpyDSps0I7sevUcGCrJEFCv4ENwm8E4L5OFoG8RwUGiyPH/0XvHasXIVqNPAxBXVYPqjhgyUghAIvr+fQEohIRc+7jiy6LE1HZ2eyGJsSAHlKMuaYV6wtraxRsHAxuCRzI4/Cm+1lbm5BVqIiSJ4i1RtAlNvQ18cLTs4uEvAYDHpoNBqkSJEaWo0WnmTFTp8hMwoWKo51qxdj2qQRmDV1DB48uIP6BLAY9DKPV7VRz75mCSifonJhkXpsOuKB4UtvYeiS2/ANjoYbAZc8Ge3gExT7Fk4KZwuYaBXqrLElsrk3Whc7i2egw3lGLLuN9QefSYK8ZCHKmtqaOqi8lDsdgapbT0Kx+7Q3/lpzDwMX3sC9p6HSwiMJ1N1nlYCRLDc8o7G0tJQLkVk5fUyBJiamKF+pBrr1GoKRY2eiW8+h8PbyxNpVC8FgSgjuEXGcjbCjmVfdhi3QvfdQjJ+0QM68jx76BzzQ8IATR6keVQm8rwSMLyyQidFzGofE0uLiuO+Hhgbjnz1b5bqzrDlyka56c7CNo1eP/18C/NiHBgcSoRGWZGGjE/CAYaIxobHDBFER4S/d5jLtxY7bigPiq40XaXzgppbpfPEyCMkrLDQU5mYWNIbEDoVCCLIY0zUB2VBytTOI6tx9IJycXLBkwXT5FmqJn8uiElmiDYbY8eslS/Xkq5aA8ilqR/0C1hZaONiYgF1a5KHiPooYAjPXHoYQ4jYiraslGpRLiWT2ZmCXFb9tVadkSphoCAABpCiMCAiJJtD0DDcfh0rr0O+/pKBOLuRiZSJBWKQOMzffx5T197DnzHOEhsdA4cI4UQ2fXQL8cCdzcUOqVOlw8vhBufBPCAEhBLWfATxL4tfShRDULgooBbGNR9cUJ4SgayP4bQt2ZUVFRYFnbzyTsibrTkR4GPRkNYqJiUFYWCj1IQMFI5iWv7UTFRkFIQRSp00PcwsrhIWExLLHF97U4n54CSiKggP/7MTTp4/Bg5+1lc0PL5NPIQATM1P5zEdHR71gR7qFnnIDIRZO02hfs/y+oPrwg1FacdjSFx0TTWUaXrIwkoWHwRFb+Tw8nmDW9HGIJNd7+059UblqLezbux1/jRuEiMgIqY9eZlRPvmoJKP+ldjTuQNAfvw1VrZgr+Ps63etmlKDHJzAK1x8G48Q1P9x6HAKtBmDwMqhZVvT/I4v85k6NEm7QagV1tNhaaDWCAE8Mzt8OgI6sOLkz2iJPBnsaSF+ZLjVU49hAJXMFYrOq+y8gAVYAjjTDKfdrNTx75o7Rw3tj1/ZN8o2JNSsXyO/f3Ll1XZr1L104I99c4IXIfn7eOH/2pPSBM5DZuX0DWXEW4fKFs0RzCtv/XovAQH8UKlwCbPVhIDV14nA8fvQAoSHBWLl8HrZvXYcbVy+CX0ndu2srzcbM5VtZpAe/wJ2rRagSeCUBhYAOryNbvWIe2M1RgNwoikIK7hWJevYREiA8Aztbe/AEyN/flyZMsTINIx3A4CcZucJ/CGcAABAASURBVKo0ikLxCoQQH1FCwiwacllZWdsgOCiQJmBRkqeegI6fn4+cdLm5pcTRw/tJR51Ah8590a5Tb/TqOxJVq9fB3l1bKP4kjV8mCZmqV1+tBJSPrRn3NX4jKjhMJ60w2dLYoEQuJzjZmeLS3WAs2PEIt91D4RsYLf+j9qkbgbKoHGltwIuYTcildeSyH6FjvQQzBoOROhikFeji3UAwWOLv9+TNbEfpoEDpBL7JWCT5fAO777KKilaLSjS7afVnF7i7P8L4MQPkhwVXESBJnioNUqdJh2sESsaN6oeRw3riqftj8FeWRw3rRWbgadCSPz6crDYMjgb2aYeBfdvj3/27SIHURZUadagPxMhXfw8f3AseUJie3wCbPWM8+vZqg+GDu4O/ptyyTVdkyZaT+oXqOvguO9pnvCmFBkwt9WONogEEwEeNRgshBHjT0CD45rXmZTogCHQfBL/y/FPx0mTpTEuY2wh1+28SMJKbPFWaDNKldOXSOWi0GkAY5QLwUHI3FS9RTrqenj19IhcxC/Gqvbg9Fbqmn8ynoTYU4rV0RQMhBDQaBUzPLZY2XUZ4ez/H3bs3YWZmjsiICFy9fA72Do7ImDkbPGhSZ0Ju90xZsst1Q/zWKJ/zF+RD5Xe+YsuAun31EvhosMMdyz84Gm0nXUS9oWdQb9gZ1KXQdPR5DFhwXX4rh18r5w51+X4Qhi+9iSaU1n3mVXSdfgV/TriIlfuf4BKltR5/ET1nX8VT33BoFIGrj0LQdcYVNBtzHhsOPcXJ6/5oM/ESOk65CM8Xb3l99ZL9XitI0y9bWzs0adEBazf/i5Xr9mLmvLVYtWEfho2cAmcXV/CCwdkL1mI1xe359yJ27D1D6f+g3+BxUtnwq6Sr1v+DMRPnY/ykhVizaT969RsFGxtbSldQv2ELijsgX+VlU3LfQWOwfM0uDB89HdPnrsGK9XvQ8I/W0JBCM1J9vldRq/f16SWgJzfp2dPHsXrFAjCg5sHtyOF/sGHdUhr0PGkwjZbxq5bPx+VLZ6VlkS2J27asBX+ThftccHCgtDRqaDCuVKUWeOB8aZ7+9FX+YTjys5w+QyZkyZ4LSxfNwpzp47Fi8RwsWzQTWbPmwE8lSslPBvSjSQ9/94bbIpJcSfxyw6pl83Dl8nnw5yl279iCbVvWgddUsSWZ1/Zxe584+q9sT55crV21GEEBASj6U0lYWlhiwpiBWL9mMWZPHysnXzV/bwg7OwdkypQN/N2emVPH4MihfdhO/WAN9R0bW3vkzF2AJme6H6Z9/vuNJi2HjwY7XG0GMsFk2fEj0ONPIYBCUHgMdGSlYdDCNBz4nOP8gqNwhcDNVXJv+YdEE4IX1FmMeB4QSZacaJqlMzVgpPx+wTF46hOBsAgdosic85JGHdxihZSEe1ZKPGhYWlohTdr0yJ4jt1zAx3EGg4FmQGZwcHSGk3Oyl4FBkC0pCK62gKB0J+TNX4gATUE4OrrASLM6TuPAb1i4EGhiZcbXGpp1uyVPiUJFiiMbWXOsrWyp3+g5SQ2qBD5IAuwiOX/2BDauX4Zbt64hXYbMuHH9Mv7evAZsMYiOisbJ44dkejDN3JOnTI0zp49i5/aNCCRXqxAKfLw9YWJqiroNWiBDxsykt8jk/EG1UInfJgH+dlb7Tn1QtkJV/LPnb+wgl3fBwsUxZMQUaEgPmJiaIl26TEiTJiPpDCAiPBzHjx3ABmpPBqP8+YpTJw9h144NEsxER0dRe/6LLZtWwf3pI6Qg6/OF86foeiUCA/zAb3h27j4QyVxTYCUBpquXL6Bpy46o36il1DElfikLrg+71SaMHYTFC6cTbXIMHjEJadJlkDRvu5fvJV4IASEShnfdmxAJaYUQ7yL/Ymn/CexwLRXioJA15mWgG0vs1jhOoTSmY/DD55yfA8dx4PO4oFAGjhNCQFCkQke+plP195VIwEjAk8FNHMiJq1ZcPKe9HpjGSDsZr9dLZcHnFPXyF5c/LiLumsvhYIwHjOJo1KMqgfeRALsqmrRoj1nz1yYI02avkGvALK2s0LFLvwRpTDt2wlz5SjKDpVSp04P/1UnHzn1pwOXe/D4lqzTvIwGj0YjMWXJgyPBJmDZ7JabOWo7+Q8YjbfqMBCr1SJYsOVmBR6J1u+6kO3Swd3BAlx6D32gv/rq7W4pU4AlZu459MIusz9yO8QN/F0kIAf5I4IQpCzFlxjJMmbkMLVt3gbWNHbWtgY62aNi4NaZS/OQZSzFt1gqMmTAHxUuUAb85+j739C3TsG7ml0UY+McFXkfJ8YndF+tnTo+j5WN4WBhZMJL+OSGokliV1ThVAqoEVAl8nxLgAdDe3hHxA7sstGQ5EEKAF63GT+Nz/vCcosSqS36Dh19FNif3x/cpoaS9KwY85hYWYGsuLxI2N7cg4BE7WHIbcFtYWlrKSgqytPGHB7mN4ge2IjOtEAJsKbazd0jQ3vbU/opGE8uXaKzJhZ4qTTrwCxhaExPiHVse10XRaGDv4IQ0aTMgeYrUsLKyic1HVN/7j780PnXCcAzo3U6G/r3agv99x6OH98Dyff3++QOxI4f1krScp1/PNmAXYGBQIIRgs8XrOb7cdezT++XKU0tSJaBKQJXAJ5DAx7PgASyxEMcxsTSOi0vnI19z4HM1fHoJsGzjh/glxMXHxcVdv35833Sme1teTuPw/9KZ5nsLQgj5/TN2E4aHhUIoQgaNRoAnBond7727t3Du9DHo9DGSlvNotBokBowSy/8545TPyVzl/W1KgB/sb7Pmaq3/qwTkfFbu/isnNb8qAVUC/10CSfwwUvFmZFkbNGIy5i7cgDkU/pq6+IVb8c21agajgdIyYeLUJZJ27qKN6D1gNNgal9Tjigp2/ntv/C44CBF7G4zazc20MDfTfBdBvY8Pa0f+ZpapqUaanE1MOK/aF37YPmSugYmJIl8kMZV9gfuDGr5sf9DClNoAAkm2MUgJDvRHgL8f+OOu/No9xyVWIa6mTqcjWl8EBwaA/4+Y0UCgyEioKbEMXzBOBTtfUNhfc1EaNlFSBa0sTJA+lS3SpbJTww8qAzdnKzJTK3CyM6e+oPaDH/VZSE/938XRAlqtAjdnS6RPrfaFL90XWObJnCzB+pnU85f/EXrRRUfjrzED0aNzcwwZ0EW+ms8LkROrjKJo4P7kIQb17YieXVpg3Kj+4DfcEqP90nEq2JESV3cvgTedGAxGGNXw48qA+gBefCaPZ3BqX/iBn4cXE3JSBz/u80A3n6TPALUB/ZJkkOI31qrUqIv8BYogRarU4AXIA/u0l4BHq+WF3AmrlSNnXlQj+lx58oP/j+KenZswoG97+aFYjUaTkPgLX6lg5wsL/GstTs8PNFVOpzMiJDQawWr4YWUQHqEDdQdERuoQFBL9w8pBfQaiERGlA09+IiJj1H6QRDoxnJ5DnnSQev5yPyqJy0yVOh26dB+EgcMnY9S4WRg9frZ8I23Pjk2IiY6CEGT6Idq4X978hdFv0DgMIvrxkxagd/8xCAkKxMljh4g2aeFG0pYeJyH1+FVJgPuvGkAP548bwBvpMbUf4IfuB9QFELepfQFJ1heQRJsQAnq9DtFRkXTUyw8p8r/MCAsPQUxMDMlDgVAoiBc9hY78LaqoyAgoGg0yZs4KewdHhIQE0h0YKSTdT0m6otWSVQmoElAloErgG5aAWvXvWALszX7u+Qz8v8P4NvV6Pa5duQCPp0+QLn1mWFpbwdPDHYf275L/UsNA5mD3Rw8RFBgARSiIiAjHhXMnKc0HGTJlZRZJGlSwk6Ti/3YLF0LAxMSUgsnLkJhPluNMTEzAx7i7FUKA/b0cHxcUmh3Epb/rqNFoZXnx+b2LXk1TJaBKQJWAKoEPl4DBoMOi+VPR6o/q8iOBfbq3lv+ImXU2/6sUg96IgwR0hgzsgtMnDiMyMhzDBnVB25a1MbBvB3Tv1AQzpowBr/f5qVgpaRn68Fp8uhwq2Pl0svyhOHl6emDtmhUY0K8X2rZuhjGjhuH40SPQ6V79zyoGMHt27UDPHp2wYf2al/Lx8fbGmtUr0KlDazRvUh8jhg3ExfPnXqa/64TL7Nm9E/bs3gnm/y5aNe0rkcBXUA1efxATo5Omdza/xw8GfjX2RR2FYLO9nhR3BCIjIhA/7QVJgoMQQtJER0eDy0iQqF58lASEEOQeEYgmN0lkZKSUrxDinbyEeHs7CBGbxrwiI97kR8nUL6LJEhFBx5h3lsOvUnPf+RHamieW1WrURZFiJREQ4EfyCUf1mvUxfvICZMqcjfq7Hlmz50I1iuP/Mcb/aqVB41bS6uPl7QkzMwu07dALg4ZNlK6spJaZCnbe2bXVxNclIITAgwf3MHzoAAwe2AePHz+EolFw9Mgh9OjeEffu3IaiaKDRaPDwwX0MHz4ISxcvwMF/9xOyN9ADYsT+fXuwfOlCUmgKrG3tsHnzBgwe3FeaO5W3WHiY38UL5zCS+C1bshDHjx2WZbxeP/ValcDrEuA+dfvWDUwYPwoT/xr9MkyaMBYzp0/GBQLarIhj6W5i4fw5BMAHYeiQ/tiwbjXCQkOpr4rX2cr+5+vrg/XrVmHalAkIDQ2hvq+8QadGvL8EhBAkx1Ds3rUdf40diZEjBmHF8sXgyRW3z+uchBBS5l5ez0nPzMeCebPg4+OdoL2ePHks03hSNYz0FuujZ8+eynwRBGgPHthPfWMMBvbvhSmTxuH06ZOkq15N2kAbl+3t7YU5s6dj7uwZ8PPzTVAGkXyXv7z5i2DQ0AmYNH0pJk9fgh59hiFrtlxSj7ObK3/Bn9C730hkyZoTMAIVKtXEqPGz5P8Zmzh1EVq17YpkrsklfVILSEnqCqjlf1sSiI6Kwvq1q3Ds2BH07T8Y02bMxbi/pmLW3EXo2KkbrMiPy72eZ7oTaTCJjIxAjhy5Xt4kDxlFfyqOCZOmY8zYiRg5ejzq1m2I+/fu4PbNG3IAeUn84oQVjb+fn7QeOTu7IE3atJTCnOig/lQJ/B8JCCFoZhqAs2dO48zpU/J4/txZ7N2zE/PmzsTlSxfkwHft2lV079oeq1YuRWBgIMLDw3D27GkEhQS/UYIQApcvnkfvHp0J+A/EooVzERIc/EMMgG8I4xNGRJF+Wb1qGfr36wme3Hh6eGD2rGkk4wHS6iJEwudep4vB4YMH0Kl9a4wZPRwbN66Fr4/Py3ZgUDJpwhjMmjlVTqYCAvwxd850TCLdpNPpZNuPGjmYJk9HJKBavWo5Bg3ojWvXrryhixYvmospk8djyeL58CHrtBAJ6/IJxfDVsGLLJmEYWFhYwtTMXFrZOO71CvJkgeM4jfW1lZU1NFqtBI1xaZyelEEFO0kp/W+sbO7Ez728cOjQvyhS5Cc0adoSdnYO4H/Klzp1GjRt3oqASDo5cLAlZ9vfm9GiRRtC/dlf3SkpiAwZMyFnrtzyPwrb2drA3NyclJMCE3qYEnswOO5v4nVfaLARAAAQAElEQVTy5HF07NwdKVOmAngaQXv1p0rg/0lAr9ejxM8lsW3nPgr7KezD9l37UbXab6TELZA5SzY5kI4aMRj+NBhOmTYbi5asxPyFy/HXhGlwc3VLMDMVQiAiPBydO7eDh8czFCtWQqbzoAB8/wMgPtsm4PHsGTZtXIfChYpi67Y9WLJsJerUbUBu6x04d+6M1C3xi/f08MSkSeNhZ2+PsuV+JTe6jjRDbEuwvnpI1uXTp06gQaMmWLNuPebNXyzp9uzZAW+y1CRPngJ9+g3Bpq27sGXrDvTo1Q/37t7GmVMnX4IdjUZLoOgi5s2ZidSp01JbG2Bgs0b8iqjnCSTAOjtBxFdw8e2Bna9AaD9qFYQQNKN5LmdOBQoWgZaQe3zQwYMKy8bd3V3OdIsX/wX1GjQi5RCrfDiNA8+orl65LE3VM2dMxfr1q/FLyTIokL+AnAkwTVwQQuAuucZWkim7UaOmKFu2HHQ0eMWlq0dVAu8jAZ5xGgx6cGBF/OD+PSxeNA+5cudFoUKFcfvWLfx74B/UqFEL+fIXRAhZc9jFoTXRQkMu2fhlcH4TU1OMHDUe6zduR+GixSCECnLiy+hjzhUS4a1b10m/eKPm73Wg0ZoQuDFB6dLlYGdnj13k2tK81haOjo4YNfovLFi0HJkzZ0lQLLeTEIJ4aBAVGYnAgFD4+fuTC8oPLi6uNMmyQMaMmVGlanUJeqOidciWLQdsbGylVQ+0CUFWQX9fcnONlmmNGjd90R8S6jQiVX9fuQRUsPOVN9DXVD2hKDQIhEhF4ODg8AaI4boykNm9ezueP/dE/4FDYWNrTdFGORhoNIo8sitsz+4dmDZ1AubPmw0fMgmnTJkSkWTCJuIEv8ioSGzetB4mpqbo3K0nSP+BdCKEUEDVSUCrXqgSeJcEePDjwKB8y+aN5Nryw280qNqSVYAHWc4bHByESRPHYfiwQWAgfuP6VQJIBk5KEDQ06JYqXVZaFJhfgkT14qMkwPqF9YapqRlSpUoF1iXMyMHBERzn5enxhs7hRbF58uaT1uXXJ0Hc1gxmypQtTzpkA0aOGIy/xo2SLvM2bTrAkfjqCQBzOUzLZd24cQ06vQ5sfeZrbtudO7fj+vUr6NN3ENzIEhRHy+lfQ1Dr8H4SUN6PTKVSJUASINOtmZmZBB68GJNiEvyEEHB/8gQb1q1Bbpox29nZkWK5JxcchoaE4MnjR4iJjoa5hQUa/9Ec7C5YuGgFuRNqSuvO+rWrXsyaYtlqyHx8k5TP9m1bwFYiIymmBw8eIyIyAoFBAcTv8RvKLzanulclkLgEFELIT6iP7tixFdlz5EKZMuXB4NnX11v2JXa/3rl9C97krl04fxaGDu5PffguhGCqhDx5IFQHvoQy+W9XAqEhoQCJ2tzcAmCHFOkctq5x4LepdDE6ik/4MxgMsu0oW8IEunJ0ckL9Bn/A1tYWCxfMkeuxXJK5kiW5NASZkuLaj8Eru9DWr1uNnDnzoFDhomAQ5O5O+mz9GlSuUh3lK1SUwJfzCK6kDFSI+vsmJKCCnW+imb6OSrJScXJyhj3NhNkNpZCyiKuZEIJmV+a4f/+OfFuLB5MqlUqjzu/VcOTwQfzzzy78XrMSbt64DlMCTG7Jk5PZOSsKF/kJrf9sCztbexw+dADsOuABiZUPu8nu3r6Ne/fuYPnyRahcsTQa1P0d169dxaYNa1GndnX4+vqC6ePqoR5VCbxLAtyHT508hkcPH6Bp05bgfshxvAaD+1H/gcOwfOVarFq7Hr36DMSVK5dw8eJ5cPq7+H79ad9CDY0wNTWB0WCUr52DdIqstZFgD4EeUxNTsE6Qce+58/L0xNQpf8Hbxwujx05E2/adceHCWQzo14MmYSFUhJD6IyY6BgMH9ITHs6ekj9ojeYqU4H6xfesm+Pn6oGmzVuA+EAdwY48GqNu3IwEV7Hw7bZXkNeWHPyWZlwsWLCLfgFi7eiXY7B8WFkZK4hmWLl0ifd8jRo7FwEHD0aNnP3Tq3A1Zs2ZH9uw50aVrD7gSyOE1OPzqZxRZeXi29vTpU+kacyMTsSm5qzw9nuEkDUiBgf7g9RBjx0+RJmTm175DJ7lAmevQmXjb2NiA65XkwlEr8E1IIDAwQL6FxaC9Xv1G4G+mcMUd7Bz4AC25pww82EbrUahQEfkBy5DgYFAnkwOjEELSxe34MmFMXIp6/FAJsMXEntzj/IaVr483NIoiZR4UFCjX3DAAUTSxcUL8f6nzhGn/gb3gN/CmTpuDNm07YQCB2U6dusu3Sf/9dz80Wi38/PwweFAfHD9+lPRVD1T4tRKYuxEGHDt+BFw+pzeoV1O+1eXn54vePTtj3ZpVEIIpP/ROVfqkkICSFIWqZX67ErC0tCIXVDNkzpoVI4YPQtfO7WiW1BMdOrTClInjYW1tg6bNW6IdzaDadeiCVq3bImOmTGQazo0WrciCY2ePVSuWoHPHPzGK8o8YOlC+Bsr5atepT4Ixgq1CvXt2wZXLlwgoZcOfbdq/5Ne8Bc3G3ZKDF5E2b9kK5ubmlEf9fSoJfM98FBo8r169An7VvFbterAjCyUPsHzP/EYWH4/T4MbgnT8ed/LEMTnrdyOATqOatEqyZZLdG0IIJidXhx76F24UAx0N5GqVCerugyXAbfE/9q4CsKqbC3957/XVHSju7i7DJj9jA4bbGIyx4e7u7u7uMtxdhru7Fy911/fef07KKy0UHaOU5ra5luQk90tu8uWc3LxMmbJKAnL48D+k3YkAf4p+4vgxGgyFgL+2Ys3v1SuXwV9ZCRFdBhyPcWf8OdGYc/L39fWFIA10KhpIGQxRUnOUJm06OlqCJy37+vhgxrRJ4C9HW7RoJz+oMBgMlDYvLqhBnbq/olHjP+XXp0x+M2fOQgRYD/6aNA0N/Dg95RIHAorsJI5y+qJyWbhwUYwYNR7NW7aFk5MzIiLCUYTujRk3Sa6pEx4WIUfMctQstPKz35KlSsNgMFIjo0elKtVQpEgJOYnZ47kHypb/DrzuDpu0jDSqzpo1O36s8DNSEqnhjoXlmJ1WZ4WKFStT/GIIDzd8UbiozHy5CAghiK8IbN64FlZEkHn+BXdqnGMjkZRcuXOjXPnvwfPDBvbvhQH9emLypLHIl78gihQtAV9fH/Tv1wMjhw+Cl6cnYAJ4cbqhg/tj355dCA4JxtTJ48lkMga86CbLVe7DEGDSkjVbNkksVq9ajn69u2PIoH6YN28mvvmmDLUjZfHo4QOMoDLgjxu0Wi14LuDSxQswqH9f8MKmnqQRmjNrBpXdOLD5iTXKlqQtHjSwD6ZOmSAnn/OaSLxeV4kS32D//j1YsXwxeHL0o0cPqXwHo1+f7nQcBCORnpq16pGGuof8JL1z197guTusTW7yZ3OUKVsenOcPe0oVOqEQUGQnoZBPxOlyw5CDTFNdu/XCtBlzMXvuEgwZNlqSFp2FRZwns7a2Ju1OSzk6EiK6wylSpBgGDRmOufOXkuO4o1CSyJAQ0f7f//AjBg8bhUw0ijJ3SGahrAHq1LUHatSsQ+RJkR0zLknr+OFPK4QAj+KfPn2Kij9XkWs/MclhSdxhcb2aOn0uyn/7A7Zu3UjaxY34X4WfMHb8FDKbppEkncM4u7jC0spSdnIH/9mHjUSennt6IFOmzDhwYC/M67ewXOU+HAFX12To1XsAfqpUhcphE7Zt24gKVA5jqBzYxM2/y8RkNUUKNyk8LCwMrI1bs24V/AP85SflPCdr186tCPD3x7ff/YABg4ZLUjRl4ljMnzsLyZKlwPQZ85AxUyYiNFFgrQ8TmCNH/sHevbuwb99uHD54gCyXRrA2UAgNBDkNaYicnJyRPXtOsIZbCCHzoHaJAwFN4simyuWXhgB3EOHh4aTViSDSEUValnBqOF4nHxzOrJUxPwN3MhzXfB0eRnFpdG2+ZoLD/hzOfM98ZHkREaQ5ioo031JHhcA7EeC65ODoiMVLV6P/gKHUWdnEicP+bm5umD5zHo6fuIjjJy9h8tRZsiNk7SKvvTJ/4XK5YrgLER5QP7d42RpcunIHp85cofAXcfb8dezecwSlSpWJI1tdvD8CXA5pyMw0YeJ0nKAyOHz0HEaOnkAEJbkkHzxvZ/bcxejbbwi4XJKnSEEDpqW4cPEWlcNlKocLOHfxJnbsOoQMGTNBCAFeXmDX3sM4evIijp+6hOUr16Jw0WJS+1yzVn3s++cETp6+LMuPy/DchRt07ziZqywkqTXnntse1gj+vXaz/DSd82r2U8cvHwFFdr78Mvpqc8iNB7v/6gGVXIXAqwjw6JzrHLtX/bjzYmdrZ0eaHAvZGfI1h+PwQkT/oCSf870oItxmIm8+8j2zP4dR7sMRYMwZT9agsRaHSc2rmPL6OCyZ77M/h4/tYpcD+7NMXhvM1taWBmcG6Tg+z+/hsLHjms/ZX7mvBwFFdr6eslRPohBQCLwDAe4c3xFEjubjCxffvXfJUv4fjwDjze7jJcSNyYTnU8qLK11dfekIKLKDL72IVP4UAgoBhYBCQCGgEPg3CLyV7FjoBGwsdeS0yll+xRhYaWGt10JwTeIdqeuFEBBCOSGSKAZUF+jRITRJ9PmFem4hBED/7OQp7YQQEEI5IT4PBgQ2eBO0E0KAJ0yzKfY/dfTOJ3b5Wn4Gwgtg5CC3t5Kd8gWToVOdLGhXS7mvGYP2NTOjaeUM0FtooNNqYG9roVwSxsDaSgchBCz1OjgkYRzUe2BBgyAdqN8A1wmFh8Vnbxf5/bMmhQO9kHBxskS6VHZIm1K5d2JAOLkls4GWKy+iN030If69LWkzXB0s4GKv3FeNgYMeTnYW/D6Bl0SPjDJCuaSLQZTBCBP9GQ0mRKi6kKTfBcOLrySjqC680iYkaVw+JxayDEyQHbdOp4GFcu+FgVYrqE8TMG9vJTubjjxFl+mX0XPWFeW+Ygx6zLyMIUtuICzCiKCQSNx5GEDOX7mHSQ+D2/TMT54HI4pIjpdfCO48SHoY3CEMlPPHbSp7D69QREYa8dQzWF4rXPzxOTHgMnjmFQKj0QQPn1Dcdv+86X/OZ/2UaTFuj54FIYoGbu9FdkwQNL6Ti4WqIyFm+mrdS/ZLj0ilTvuv92FVhX5L2Qr2k287wcTnJtrRv7z1MUcVh4BMxO/Ti6yr8n8BRELVZ0qe303ZIydUHhJbuoRZ9MsnT/BWzU50kLfvZVtIIJiP8YU2+/HR7M/nrzqzn/n4qj9fy5fOHOAdRyLDYEfZe0dI5f2xCAghIIQGQoh4RQgh3uH35rhxBUbLEW9JK254daUQUAgoBBQCCoFoBDTRh4/bM/mw0mvgYKuDnTVPaoxfDvtxGP7ih0NoNKDwWhmP79tTXAsLgShiJrHXQTDL5jDs7Ky1oL4TBgrHct7kOF/s52xnARdyFmS742vlPh0CgkiHhYVerqAcHBQII6kLdTqLOAlotTpSgUfKMLE9NFQB+HdtQkJCEBjgY/ZxRQAAEABJREFUR2GioNFoYweJc85+XO6cTmBgAIxGI4WnShQnlLpQCCgEFAIKAYVA/Ah8dI/BpMSWyEeXutkwrk1+jG6VB9VKp4LBYIpJie1l/yuSHKNa5sF4CtPt12ywtdIhXyZHDP4zN8a2zodx5EaTf9+GOVH/+7TgT92ZzFjqNWhdPbOMJ8O1yYdRLfKgXc3MyJ7W7o0KHiY6TJJqlkuDie3ySZc/i+M7CVJMptXJOxHQarUI8PfFgrlT0L1TU7RuXg8D+rTHkUN7JQkRQoCJ0NnTR9GrawusWj4P4RHhMXJ9fLywaP50tG/ZAM2b1MSgvu1x8fwpCBF/dbx//zYmjBmEln/VRaumtTFx7CA8fvgAQogYmepEIfAxCGiIeL8tnhAi/npG9zkuu7fFV34fj4AQAu+LrxDRYd8UXog3+wsRXcZCvDzilU0I8qO6Ei1fvOKrLhMDAvH3Lu+Rc1auONpYoGReZ2RKaS0JSD0iKxlS2khiwV/1JHPQSwKTI50dMlKYojmdYG+jg5uzJTKntkGmVDZwJK1QChdLFM/lhBa/ZMQIIjS5M9hL0pMzvZ2Ml5L8WfuTIaUtqhCh6lQnK7Kksn0tl0yzUpDs7r9mx5+V0iNtcms4kmbHxkr7Wlh14+MQEELg7p2b6NuzDebNmgA/Px84ODjixvXLGNSvI65dvQhfH29MnTgcPbq0wOGDu3Hn1nUYoqJ/y8pkMmLvrq3YvGElXFyTIVOW7Dh54jBGDOkJHx/P1xq38PAwrF65EMeO7EfmLNng6poC69csw8zpo8HLwAMCalMIfCgCQgiqu76yLoeEBMcTXUgN4sMH9/Dw4X3SPkbXXw5oMBjg5fkM169dkvXej94B8CiLPZX7JAgEBwfh3t3buHHtMry9nsuyeJPgsLAQPHC/g8sXz1KcmwgNjVue4WFheOh+D5cvncXtW9cQRNphsyxuQ549fQz3+3di3AP3uwglrbMQ0W0Ll7fHsye4fuWibN+8vDzemh+zbHX8shD4aLIT32Mkd9ITaXEG1xHq01AkhzPSEOFgEsLhmSDx0XwdRVqgyevuYtKaO9h+4jmCQqPABKdmudTgT6G5/eA4p677YeSym9h09Cm4+qVNYY0cRITYn+WZnZECZ01ji0LZHPHMOwwxWiZzguaA6vjRCHDDsXHdSvnSt2zbHdNnr8Sk6UsxcdpiNGnaHnZ2Drhx4zJu376O35u0QroMmV80DFxynKxA4SIlMGTEFIwcNxuDhk1C9Zq/4cmTB7h98xqRnbjElE1hP1eqgXGTF2LQ8CkYMnwySn5THteo4fHz9aHwZrksWzmFwLsRYAJ95NA+DCZyPrh/Z1y9cgFCxK1HrL08cewf9O7WCiMG98DTp49kmMjICCLrWzCobycMHdAV/Xu3w6ihvSTx4TjvTl2FeBcCTHDGjuiLPt1bYWDfDuQ6Yv+e7fSuv95dPSMSMmPqGPSicupN4Xt1bYlZ08fC19dblpcvaZFZA923VxsM6d8Fvbu3xuQJQ6m9eSTlMdEZP3oAenZtHuP69WqLK5fPQavTISI8HNu3rJXlPLh/JwwZ0AUD+3TA0cP7oCUN97ue5b/2V/LfH4HXa8/7x40xJYWEG/DcN5w6NRPK5U8GOzJVWVtq8X3h5FThAA+fcHCYV0WbiK1cvO2PA+e9MHfrfRy66AOtRhDhsUcqFyspn8Ow7ONXfXDkkrccQFEQWOhez7qGPO48CcaYlbewcv9jhEcaX01SXf8LBIQQ8PT0wOmTh1CICEutOo1gY2tHZSyQOk161Kr7Ox3TIVfuAujRexiq12wAWxsyOVI5m5MVQiBz1hzInbcg9Ho9uMGIjIqATquDvb0jlW/cMtPpdMiTrxAyZsoKCwsdQGXMP9xnbWMLvaWlWaw6KgTeC4EIMqf+vWIBmUUHkDbgHh7QiJ7nggkhYuJrNBo893iC6ZNH4g6R9rt3biAsNER2jjevX8X8OZNgbW2DDl36o36Dprh58yqWLZ4ltT9CvJQTI1CdvDcCfqQlW7poJi6cO4VGTVqieesuhGsEJo0bTGVCg91Y+Aoh6N4TeJBmhtuarj2HIF36TFi7ajEO/bMb3HYw6fHyeoZqNRqA/UuUKifJ6r49W6g90SMkhDVIt1C0WGk0bdEJf/zVjgZpbZAhYxYYSYPnTvVj2eLZsKF2rGO3AfirWQfSCPpgwZzJCAsLlW3fez+cCpigCGg+RepBIVG46h6EiCgT0qWwQhbSrqRzi9a+hEcYceVeAIJJaxNfWhrqvKjOSq3O3jPPweYvntDs4mABbjY05Jk9nR2ZpTKgVdXMoEsEUHoPn4fKsLEXd2LNDhOjw0SKvP0jJFmKL0117+MQ0Gi08PH2hBe5vHkLw0KvJ3JiksKYlGo0GiofIc1aKdxS0bmGyiDaXwZ6sTNQI3L50jls37oOk8cPxab1K1GmfAXkyJWXtHGGF6FeHkJDQ3Hy+CFs3rgKI2kUff7sSfxcuSYcHZ1hNMYlRy9jqTOFwOsIREVGyTrTirSS7Tv3fT0A36GGZ/3a5dKEUq3Gr9RpWtBdAY1WSxrF8/QOeOEP0mIWK1EalavWQZmyP5C5di+8yLzB7wC+uC1xZEgIQaakuzh7+hhq0ECqOml8v/uhEurWb4KgoADs3rmZyoIGPC8eh9uc3HkKYMjIaahDYcp9WxH1GzaFk5MLldNFcFlkzJwdvfuPQc06DVGsRBnUqN2QzOfJ5Zw/9mdROhpEFS5aEpWq1EbFn2vgfz9WRvIUKcF9kbf3c9LqPSSyVB9ly1VA6XI/0GAuH54/fybNYUJQZWEhyn3xCGg+VQ4v3fGHb2AkeGnr4jldUDqvK2xIu/PcLxyXiewI8fZKwd7hEdTRmUCdJKDTRIfn+/ky2eOPn9MjZwY7ufDd5qPPcPluALKltZOTonliNLsi2Z2oc+X40XGhtk+KgBBCNjqhIcFwdHKOITrxJSKVOfEUgxBCjoh2bF0nR8581BKJYs1QSHAwlX3cSEII+Pp4YsWyOZhF6uqTxw7C2dmVGjRnGvGFvxY+vryoewoBMwLWNjZo9EcrIil1YTRSe2P2eHEUQuDi+TPYQsT6r5adkK9AEZheEGohBHiiPWskra2twXXcwkJPWoCsVBcj4e3lqerjCxw/5iCEkJo2LWlzc+fJLzEVQiBdhkywIk3ajeuXXsNXp7OAXg66eNBjkmanKEOUbCOYrGgoPueFtTCswbtIGiOeDyQ1N7JcTTBGGfD40UPcvHGVSMxThIaGcRRwASdL7oa0aTNgzd+Lpen+9MkjuHzxHAoXLQXXZCnAaUQHVvsvHQHNp8gg1ycPMmNdJAKi0wqUzueCcgVcodNqcPq6L7wDIqiSvj0lrnepXK0pnCANkRFBYdENETcotx4F4/BFb0S8MEtxd2giWlM2nys61smK9rWyyOMv36SiCkrpEGGivfr/xAjwSMrKygZ6C0v5NZYQXBIflgjLsKaOokGj5hg1fg6NyqbTaOl7rFw2V2puNJq4VZLD8yirQ+d+GDl+LvoOGodUqdNKjdC1K5fk6O3DcqBCvwmBpHBfCEF1RhuvBhG0BQUFynrIndxvv7eQ7RG3NeQF1iLy/bDwMOzZtRkPH9zF9WsXcYvMWAbqYIMCgziYch+LAJVNgL+fNG07kNbWZDIS3zDB0tJaanSYrEQRMXlVvIk7CbppII3x8aMHYDKaULR4aRiiomT5Xb54FtMmjZDzbXg+T6Ys2VD++4pEpiIoLR0EaezW/L0Qvbu3RG8552cMnj55SPVEI4lsvd+a4sb1y+jRuSlGD+sDB0cn/EnmLEqS+hvV2UgcEsEubs/ykRkW1OdFGoz457wXmOnyV1DpU9ggLNIANinxp+RvEs1r60SS+SulqxUqFk9BlRPwC4qET0Ak0RmuSyYykQVi6vq7uHI/EPxZedn8ruA0jl31xfxtD7Bg+wM6umPnqecyDqdH9T0mSb5mF3NDnXwUAtzYu7gmh7OLK9gMxY2LEFT4JE0IQQ2ShWwg6PKt/1qtDimJsOTIlQ9sQ69VpzH4i67TJ44gIiJCytBSAyREtGy93ooanSxSffzt9z/LUXkIaZeukClMVpi3pqY8FQKvIhB/B8VE+/y5k9KM0vD3lmBTLMB1UIDro4lGZDy5vmy5/2HtqkXo1vEvDOjdHgf376SOMxJ6Sz3U9vEIMNJRBmr3ibzwuVmSRiMIf43sW6hHQHwbl8/BA7uwY9s6fF+hEnKRZojbq+iwAnwuqCytrK3AX2adPX1cerFGuWefEWTqGo1Wbboje848pNX7G8uXzIEQAiYiXBFEbjm+ta0t9S8meDx7gls3rkh/KUTtEgUCn4Ts8JNSfcSNB4G49zSEKgGku/EgCDcfBkFDlQbxbEIIVCicHE0rZcCA33OiYDZHRBlMOHfTD0+8QiFexOGRFWuHNh5+Ku+kd7NGgSyOuO4egOV7HmLF3kd0fITjV73hYKNDOSJD+TM7QKuhDpg0TXkzOaBELhdJlOg9kjLU7sMR4BffLWVq5M1fWM5R2LhumRSi0WjkRD+eWHj96kVoiczoyA7ODRCoFAX564i88LWBRl+PHroj0N8PWo1GEht/fx9p2nIi85TeQi8nQZ87c0LeiyTy89D9Lp2HQUtyubHz9fUiUhQu7eqC5ENtCoFPgADXL57cqtXo4Ofrjc0bVuLC+ZNgsy1PeHW/dxtuKdOiW69h8kvCpi070vlQVKvZAFZWVmQ6caHOEWr7SAS4bba2sQMPmENjJv8KSSQjIyNha2sHNlu9Kl5HZi/W3vCXdalSp8dvv7eAjY2tDGYioQULF0PPviMxZuI8jBwzC6yZ4WUzfH28pcwChYqjWPEyKF3+f+AvTPPmK4wD+3YgijRD584cx5wZ4/BTpRqYM3+9lOFKA77Rw/tIsxfXGZmQ2n3xCPwrskNcRb7cVJ8ghIBnQDhO3/CV91iTcuSSN4LJHEVe0UDQgMpE3NhIaheOY0FEpE3NzPjtx3TImMoG/qTR2X/OE+sPPUEoaYU4EkXh/g0aEnL+tj8RqiAiLVoUyu4EGysdqL+McSQaudLbY2CTnGhEMlkLZKXXou53adCtXlakTW4jXySWq9zHIWBNJij+Citn7nwYM6KfXBSwZ9cWaNygMpYsmI7IqEga9VzF+FEDMGpob/CaFRfPn8ZIOl+5dB74C4fF86ehaePq0n/4oO4YO6ofrMgmX712AyofIzauW4HO7Rrj0oUzCAwKwLDB3dG6WT2MG9UfA/p0AJOqQkVLokixUjDGM+/i455MxUoqCAhBFJkdhHxkIQSEEAD9s+N1WhbMmyJNpTwpNiDQXy6MeezIAfBm5+CA4iXLofIvdSXxZ5NHpszZwSYuE2kCOIxyH44A9w3JU7iBBzj3792ClgY3XCzPnjxCWFgYcuTMR32LEZFEfJiIcAom6kjO0cCINWzJk7uhR5/hUgvMfuyMpI3jsAYyM3GBbVwAABAASURBVEaSS58hC7JkzQmv5x4IDeWBORe6CUIIyD868qDMQq+ntExg2azRqVP/D9ja2SNP3kKoWachQsNCIAd2Oi0no1wiQOCjyQ6TD14XZ/txD+w76yU/L+dJxfvOemLjkafYQFqYI5d9YKHT4Kl3GPae8cT2E88QHGoAfx6+9dgzbDryVIZd+88TLN75AOP+voOp6+7imW84jdyNOHDBi+J4gOcCCQIzMCQSfx94jG2U5tX7AXTHRO7lvxCC4oZh09Fn2Hz0qZTPabDbdfo5fAPJREJhXsZQZx+KADcuufIUkGrfZq06y8l7OmqUSpf9Af2HTqAGKS+kKhpG6PQ6VPjpFxQvVQYWegsYjFGk6rdElep1weG9vT3h5++Lb7/7Gf0GjQOPqJi88OTEqjV+Bc/NcSLbff3f/kL2HLnx5PEDmKjx4k/cu/UcAtYEcWP2oc+gwiddBLj+ej5/htu3rst5GQbSNHJnygtl8mJz3XoNxYSpi6WbPGM5GjZuCReXZOhK93+qXAPe3s9x8fwpsJbnxvVL0txxjkxfFStVB5tiVX38F3WLiEvmLDnApGXbpjVgbc21KxexdfNqWFlZ44f/VZZfwvHSAWyuYlJyn7RtUycNh4fHUyIhjcDle/HCaTmPikkOE5J1q5fgyuXzePLogVwf59qV88ieKy+1Hy44f/akNEO6378j52Dt2LqeSMwllC79PXQWFrB3cERwUBDOnD4GNl9xelcpT3rSQKdMlZYGb8Z/8cAq6udE4KPJDnOGwJAozNt2H4uIqDz0DIFWI6QZa/bm+5i39T48/cLB4dw9QrBwxwM5r4YJkvl6+sZ7mEFu/jZ3rP3nMU5c8wFrgjQUKTTCgNVEbNj/2BUfVtqQBkfg0EUvTNtwF+sOPkFYRNyKRtHwyDMUMzfdA8s2O5axZNdD+LzHROnPCX5iTitL1hz448+26N57BHr1G4W27XuhZKny0OkskC17brRu1wvdeg6LcV17DpWfh3JjxKSG1cW9+48i0jQKrdv3lF83sApPCA2KlyxL8XsgTdoM0Gi1KFf+R3Ts0h99BoxBz34j0aRpO/BI2qRG0Ym5CiVI3iPCw8GdZZcOTbBowQwEBgZgIWkae3VrKTvE9OkzI2v2XNJlo6ObWypZpzOQRsCZSM9D9/uYOGYwunT4E906NQV3pN9+/xMq/VIbTJwS5KG+kkRNRHbSpEmP2vUbg1et7tGluZw0zJODW7buRu1BeviSeXHn9g34Z/9OCKEhU9JlSVj4a6sVS+eCf56GFw4cObQXmNQGBwdjLZGdvj1aoyuV+VjSDltZ2YAnGNvZOYAnmE8YO0j+7A3PwVowZ5LU1tX5tQk1RyaULvM9ctPgbs6M8ejYppGUwWlXr/Ub8hcsSmUe9b7oq3AJjIDm36bPk4sjo4zEqF9K4uvIKFPMDarDZN4w0og/+h5fs5nLYDBRZSFHZi36B2tvmLCYI7J/RKSRTBXR8fg+x+V7URSXr1917M/xYjsOy+m9lPJqLHX9oQhwwyTIhmhpZQlrGxtodTqqA9EICyGog9DFcRYWFtAScTGno6PwrBaOtsPrZMNi9tNotOBRlfmaK4aFXg87ewe5mBv7c/pQm0LgAxHQUz2qWqM++g4cg1HjZ2P+0k0YOW6WJN3ZsucGL1jJplZ2kZERKPFNOQo3R3a0rCnIkSsPOnUbKOeFtGrbA1NI+9OuY2/wPA5VJz+wMOIJzu3CL9XqYta8NYTzAPDCjZOmL0Nl0gYbyGSdMlUaWVYdOvenviMKJUp9i3lLNmLOovUYNHwSuckYPGwyeAHBZMlSoGjxUhg3aQHJGoRfGzQl/0mYOH0JSpf9XpZ1lWr1MGLMLPBiguzGTl6IAaShzpAxeuX3jJmzYciIqRg5djbqNfgLzVt1xaTpS+UAjdu0r7/MhWy3uVzMThurHccrmxDig8LjM27/mux8xryqpBQCCgGFwL9CgAl6hoxZUKRoqTiuUOEScHR0iiHsnAh3ZMmSuaFQ4eIxE17ZnMIj+mo166NCxarIki0HdKTN5LAc5187JQCCNDbpiWx8X6EyeFHBdOkzQrzARW9pBV5RPQP5M+bOzi4oWKhEnLLkuXx58xWSJnNBsjj+dz/8jOp1fpPa52REgjgui+SJzHnyF0KVanVQuWpt0uoUkgMqsz+HcXByRpFiJVGt5q9klq8K/mJLR4M19vvaXXBwoPw68SBp0lijxY7nrgUFBUIIc6m8RMHb6znYn8NFux04f/YEeODwMlTCnCmykzC4q1QVAgqBBELAYDBQ4xv5motvvg3fY42OufPjo8EQRVoBdpGkXTDEIUgJ9EhfXbIGKqMoORE5GuOYByTVPa+fw/58j8uDtXGRFDa2i11mHJbD8D12XKYclx3HZ3l8nx2f8z32MzueJ8h+0TIoP1FRSaLMhRDyR5xHD++LcWMGYsqEYZg8fghmzxgLnj8pxOtk5+jh/Rg6kLRf44bI8JPouGLZPAQFxk+OzBh/jqMiO58DZZWGQuDTIqCkKQQUAgqB/xwBngvF2p0Wrbti0DAyE5KJsEefEUifIXO8hC8w0B92dvbgif4y/PAp4Lg80ftVEvmfZ/6VBBTZeQUQdQnwOhfKmZIsDjR4lq8BH1U9SLr1wGgyUocmqwIdkzIOCfvsJvl5TnQ5fPa9CdBoteDJ+ry+Wu68BZE9Rx6wOTc+8kLB5RxO/mKXzY08uTtjpqxk6tV99qy/mqAiO68i8jVdf8CzaAVA/7Cy1MHN1QYpk9kql0QxcHG0glajgYOdnuqAHTlVF5Lm+2AHRwc9tNQ4OFOdSJncVtWFz90mEOZO9lYQCdVTU6fAZsATRw/iwN4duH71kvypILxh01AvEhgQID/nP3JwL+7dvYWQkJA3hP68tzWfNzmV2peKgNBQrabMWek1SEFkRzmbJIuDk4Ol7ODsbfVwS5Z0cUjq7wCXvSMRXp1WA64TPAhK6ph87udnzJ3s9dAIQa3z5//nz/PTpcuIrVvWYPqUUejepRmGD+mJ+3dvQ0MDoldzxAtrstZn5bJ54E/6u7T/Q65A7e/nCyES5hnMeWSyYz5XxySMgPnT/MgoIwKDwhGgXJLFICQ0EkajCaHhUQgIVHUhKb8LoWFRsi5wnUjKOCTks4dQGcRnMvqvuytOM0vWHOjVbySGj56JQcMno1r1+vLrrLWrF8dLXkp+Ux5DR03H8DEz5EKx/IOsG9Yuw8kTh2gAlbCmLEV2/usak0jk8/wMziqZ6RFFhEc5Y5LFgdeoYts7Ex4mv6ouJOG6QKSX2wauE0mnHnxZ5W0eiHL7/LmdpZUV0pJmhz/fz54jN6rW/FUu6Hr18gUEBwcR4YlLIXgtNF4WgOPkK1AU1Ws3hJOLKzg8EnLuEQEXN6d0Q/0rBBQCCgGFgEJAIaAQ4Pk6hihDNKmhEVBwUCD4N8WcicBY6i0RGRmBAH8/GhhGSrD4E32j0ShNXEajAfyDz+FhYUiWPIX0T8idIjsJiX4iT5tttux4RU0+CvG6TVYIQRVfSy9LXD8Or9FoSbWpJX/Na/54w6YhO7GG4gkRV94bgqvbCoH/DAElWCHwNSPAZGXvri1YtmQWjh7ai38O7MSi+dPkz3CU+/ZHuWjjqZOHMXp4b/Bvj0VERGD1yoXyJ1SOHzmAXds3YunCmbCw0KNwkVLyi76ExEuTkImrtBMnAkII8N+zp8/oBdiLdWtX4fSpE3LWvYbIiPmptFotnj55jN07t+H69avm22Dm//DhA2zatB7Lly7CsaOHERIcDCFETJj4Tlj23Tt3sIvk3b93953h45Oh7iVtBIQQ8jNYnc5CkuxX0eA6xn5are696pcQZnnvF/7V9NR1/AgIIcA/QaPTEa6x2hS8ZeOy01KbI8TLdkQIAb4XnxPiZTiOy2mxE+LlfcTazGGEiN8/VtCv4lQIDZmqArF54yqMHNYLY0f2w41rl9GwcQv878dfSJsTBV9vb9y6eQ2s8WGMPZ49xpJFMzBscHdMnTQC4eFhaN+5L7KRCYy1RAkJjCI7CYl+Ik2bVZfLly/GD9+VQoP6tdCmVVNUr1oRf/xeH889n0NQ4ySEQJQhCv369cQfjetj5rQp4N8b4kfeu2cXatWohDYtm6BH906oV6caBg/qB4Mh7g+7clizE0KQ+jQUbVr/iT//+BWLF8+nRkxn9v6CjyprXwoC3JGFkUr98qULOHXyKDw9PSXx4fwJIaDX6/H06ROcPHkMd+7chKDGXog3d2zc+XEDfuP6NRrZXiKVfiTVSS2LU+5fIMC4CiFw5/YtnD9/FkEBgW/FVQgBC70e/v7+Mk54eHh06nSfP3t+4O6O+/fu4f79uI7bMSEEOD1v6rRP0YDt6rUrYFOMEHHLXWdhgcDAQOrYb4LrEJLAJoRAjdoNsWj5NkyZuQIz563BwmVb5O/C2djaSk3Nj5WqYdGK7ShV+ltZRh269MfiFTswafoSLFy+GTPm/U3EqHLMe5aQsGkSMnGVdmJEwIQd27Zg9MihyJgxI+bOW4JNW/eg34Ch8PP3pUblDvgzSW5A1q9djX17dsLS0hJRRHxMEFKr4+fniypVqmPLtn3YsHkHvv32e9LyrMM1GjVoaUT9OipCvlgzZ0zB9WvXwCMIJk70Lr4eVN1RCMSDANfHg//sQ73aVdGk8a9o3eovVK38A2ZOnwxWv/v7+aFD+5aoUe0n/En+1av+hGZ/NcTjxw8hRNyOzyz+AnXETNQbNqiNxo3q4ZdKP2D/vj2yrprDqOOHI3CJyOgfhGf9OlXRtElD1K39CzZtXCdJSXzSAojkrF65XA642rVtTqTmrgyrpXLbu3sHGjaoJWXUIznsatNA65dK/8PhQ4ekNnr6tImoVf1n8KCt4a+10Kljayr3R1IGpxcUFITNG9ahJsVrTQO0WzdvUJ1IOl2ntbUNMmTMjNRp0oFJH3+lxbiw01F7bWVlFYOHEAIODo7InCUHXF1TEIZaavNNHDTBXdIpsQSH+u0ZSBy+Ar6+vli79m+4JnPF5KmzUaVqDRQvXhLNW7bF/AXLkTt3XtnY3751E+PGjsC33/0PxUt8E/N43OlUr14LffoNQpGixVCUXKlvyoAiwYdGV0LzeseioXunTp7A3NnTUafur8iRIxcF/zJeoJgHUydfLAJCCPhRve3ZvTMCAvzRpVsvjBg5jsh6FsybO5MI9BU8e/YUd2/fRoMGv6P/wGEoQXV244a1WLxw/mt1TaPR4vGjR+jYvhUCSV6HTl3Ro1dfBIcEY+zo4Xjgfp8a/9fr8RcL0BeUMW9vL0ydPB63b99Eh07d0LvvANjZ22PQgD54RKZvjSZul8UkdfKksZg2dQJCQ0LgRwOpyIgI+URGkwl58hZA6zYd0K59Z3Jd0LJVe6RJm07WA2dnZ+zbuxvz585CiZKlMXLUOPz2W2Mc+ucAli5eAE6Lf9NpxrRJsi0LpfKV8iMjqHxLVYQWAAAQAElEQVRlEklmxwSH3fs+ME9V+JDw7yv334SLW3P+jSQV96tHgF/+Z0+fkir3BsqV/57Ye1ZS3UeA1b4moxFpqRGxtbWTo6XFi+aDZ+G3btNRMv3Y4Fjo9WBVs+fz57h44QIOHTyAlKnSIEfO3DGmLnN4IYRswObNnUEji7T486/m4M8hzf7qqBB4FwJCCHAnev/+XeQvUAg1atZB5SpV8U2ZstIk4efvh0yZMmPKtDlo3bYj6v/aEG3adpBibxFpl2YLkiFvvNgdPnyQNJFX0fiPpmhAHWTder+hQ8duuH3nFi5ePP8ilDp8CAJCCGpbbuLc2TNo0KAxYdtMllWj35uAf2V769bNUqsbWyZrjFOnTosRoyeg4k+Vor1IDp9wZ5s5SxbUo/JsSDIaNmqCH/5XEfwFdJky5ZA/f16cOH4UTs4usry//6ECGjdpigKFCmHrlo1S48dmyhQp3DB0+FjUqFEXkuUoHovPsH3yJBTZ+eSQfr0CNVqN7DR4NJU5c5bXHpQbFyEEzp87i23bNqFj5+7InTc3qTENMWGFEAgODsaEcaNQq2Yl1KxeCefOnaFRVyekSp2awr4+b+efA/vkPIruPfoiVarkNNJ+PUxMAupEIfAKAlwvU6ZKhUyZs+LokYM4fPAgdXLHsWjBXKpzaZAta3boydSaJm1aOZqPHpVGC7G2tgbP5aFKJ28IISTBv37tCnW8GhQtVkLeNxpNKFKkmCT+T548puBK8yiB+YCdhrC9f++O5BOFihQFEw1AIEuWbLCxscHly+dl+SDW5uqaDH82bYHy5ctBb2kVyyf6lMveSAMxdlwix44ewh0ipDVq1YWtrSUCAwPoaAtHJ3tKzwgHewdkyZwNT58+RmBAAJgI/dGkGX743/ewsraSRClastonNgQU2UlsJZaQ+SW1MDdABqOBmqD4hzf+NEpetnQhMmTIhKrVaiI8NAwm6gi40TEYIsFHCwsdspMpquQ3ZVG23HewJzX1rJlTcZ5GdFqtNuYJhRDw8HiGlSuWoHTpchS2vByJszxuvKKiwmPCqhOFwJsQ4DrHv8Q8bfpcWFnZoHmzRqhVozJCQkMxgExWaUgjyWHYCSHA5pA1q1dS52lJndyPsLCwiCPaEBUFXx9vMAlydHKSdZp7QSZMdnZ28stC41sm28cRpi5eIiA0YC2bRqOFo4Mj4WokZwKTDC4DnqgcFRn1MjyfkeNyIz5DbRJdvOU/LDQE27dtQYaMmVCmbHnSLgukTZcO9+/dxfat26SZjLVy7u73EGUwyEEZVQdSBJloEIZ3yofavmgEFNn5oovny8ocNyrOLi5klnLAPWoghIhLePR6C/CXKUcO/0OjpCjMmTUNU6dMwo0b12hUdhHTp06UcyOsrW1Qp259DCfV8Kw5C9C1e288fvQQixfOpXgGCCGk0+kscO7safB8nZDgEEyeOBYzps3A48ePwF9OzJg2DSFkpxdCfFlAqdx8cQgwSX/+/Bls7WyRmTQFmbNkZX6Cs1S/eB6aENF1iMPt2LEVmzetQ+XKVfFjxZ+po4urSTRR98emW35Ifif4yE4IAQ112OwPwXoEqO0DEWD8jSYjIfwyohACQqMB35XYvvR67zMtDaJYg8xf2v3vfz/BxcUVnE7lKtVQmDRyEyeMQcvmTdC3d3ecPnUSlCIsSVMUu3zfOzEV8ItEQJGdL7JYvsxMsTYlVcrUSE9amwP79+DundtydMsNCTv3B+4ICw9D8RKlwOr/CxfO4erVS2Btj7eXJ65cuSxHzbKjEIIe0kSjZr2ccGxP6uMAUhtzGgZDFI2qgmCi4RrfZ3mRURFyLgR/sRUSEgzP5x64RqYEKYskqX+FwJsQ0Gq1uHD+HLp2boe0adNj8pRZmDFzvpzjwZNP9+7ZCa53Op0Op0+ekKQ6T978GDR4BGkdHfBqh8eaB3sHBzJnRSIwMBBCcF2ONm+FhgbDztYOHOZN+VH340fARBSHNWP83vMcHSGExDYiPFxizdoeC9IKxx/7LXdJDrcT8+bOgpOTM8qV/xZc1lyuObLnwpChozB67CS0adcJPXr3Q4mS38DZ2RkOjg5vEaq8EhsCiuwkthJLwPxy45AseXLwaMjd/T6a/dUIrO4/fuwIJpHWpXqVH6lRCsf8RUuwYtUGLFuxDnPnLUDJUqXx/fcV5Hmq1GkwbcpETKGR1P1793Hn9i0sW7KItDUPUaRYcVha6rF1yya0a9Mc/Alq+W+/J1nrpSyWN3PWDEmOfqlaAzPnzIADdTqcrwSERSX9hSOg1WpwmLSNvIZOg98aIk/evMiWPQc6dekGaxsbXL92lZ7ABPf799G3T3dJwLkDZPMWech/IYTsILWkIWDzVdo0acEd6J07N+m+Vrp7d+5QWAGu43Si/j8UATKTp0yZEqFkXmTTEuMshMDTp08RRvdy581HxBPgxQa1VA5m8UIIIpdCEiMBQCMgr+lU/jOxOXvmNHbt3IpixUtKE7r0oJ1Wp0W69BmIAH1H7VpVZM+WA140MCtevBSsrKwoPZOUqyGhQlB3KQAhBPgaaktUCFDpJar8qswmMAIajQa169RHp849EBoWir69u4HXLVkwbxYKFCyCvHkKIDLCKM1RBrJ7G0062Ds4knOAwaiRkzp5zs/CRfNQudJ3qPbLj9i3fzca/PY7Gv3+J9nRw8ETPHktCz9fH/m0LMfsjLCEo6MTbGzsKA09PummhH2VCBipE3VzS0kdlAaHDx3E/ft3yZz6BHt370IomUHTZ8gIXtG7yR+/yrpXq3Z9WbfPnT0jtYfc+YZRXZ8yeTyZYichhLQ3pcqUBX95uGLZEpw7dxZnzpzCyBGDkTVrNhQsVFh2iF8lmP/hQ7F2LWfOPODyWLFyKRh/HvDwHEC93hI1qteGp+dzGixNwIrli2V5crvAZu0b12+QnyfCIyLg7u6Oe3fvSjIqhKAyDsYqkqfRalGFzFY8R5AHSEIIsPn8Amn9njx+jMuXLoLNWffu3UHtur9K+Tz3ileBv3HjJjw8nsovtB64P8AdIrbmRQn/Q0iU6E+IgOYTylKikgAC3EjY2dmhRcs2WLh4JaZOn4sJk2Zg/sLlmDx1JlKkTCVHQ2YorK2t0axZKzRu0kw2HhYWejSl63nzl2PU6IkYSW7O3MXo138oERgbCqOVE5snTZmJAtRp8OjZLIuP9vaO6N6jH+rWawCeKMr3lFMIvA0BQ5RBahaZxGzbugktmv6Bpn82Ak+K/6FCRfL7Hy5cOC/NsoJG8MuWLUSHdi3RsX1LIvPd6f4t8NwwXtiOTV7+fn4oUKAQunbrTX63ZdgO7VoQmTeiVZuOSJMmXZx34G15U35xEUhNGjMe9Pj5+sqFHzu2b4UHZB7v0bMfUqZKDV8fH+zasRX8haZGowWXxaTxY9CiWWPwopHBQUEYNWII+vTqRoT2KVgLxPGPHz8C1tawlplJFacqhJCEqlePzjI+L0jIpJWXy+C1v7jtCQwKwNQpE9GiaWNs37ZZapgmjB2JHt06gkmPhgZ/LEu5Lx8BRXY+vIySfAwmPNyI8OJ+3373g5z7wJP8eOIx29tjA6Sl0VSu3HnI9JQz5jaTJR79Vq5SFZUqV5UTBM3Lj3Og1GTq4k96bW3tXus0WCWdv2BBZMqc+TU/jqucQuBVBLi+uiZLhqHDRoMXwmzWvA2aNGmOiZNnoG+/IXKRuVJkal209G/Mmr0Ig4eOwsDBIzBwyEh0695HmjkcHBwxbNgY9B8wFK6uyWGh04PXfJo6Yy66dOlJcgZjxqz5ckKzRqt9NQvq+j0R0Ov1qFa9FqbPnI/uhH3nLj3kHKsaterIeVVMeHjRx06kWTYYouSCgw1/b4KevQfK8pw9bwmGUDm3bd+ZyikZjER0kyVLjmHDx2L4iLGwpYEa1wfODpMeJjXdevQBy2BCNWXabNIwN5HmTQ5nY2OLXxs0IvkDMHb8NMyZvxRDho8GL6vBJjeWwbKU+/IRUGTnyy+jLzaHBjZTGY2yEeJzbhziyyw3COzMfhzOaDRIsmIyRZu8TGRqiO3/IfLM8dRRIfAmBLh+OTg6yjkb1WrUog61Jnjiu6urq6yH3CGWLl0W35QuA15wzuyKlygJJjpM2nlOWZ58+WFhYQEj1VsLvR758xdEJSLt331fAbwejBzpx6rLb8qPuh8/AlxOlpaWyJkzF36qVAU//VwF2XPklJizn5WVFQoWKoKs2bLLcmNylC9/AbksxTdcft9Q+ZUtT2VbUn4kweXEZu9y5b9D5ixZZZzYKfPXpeW//V5qiiv8+BMNynKB06eAMhiXdZ68+aT80mWofryQX7LkN3GIkwycZHeJ48EV2Ukc5aRyqRBQCHwiBLjTNH2ELI4XX7Q33Y8vrLr3YQh8KmzfJof92H1YzlToxIaAIjuJrcRUfhUCCgGFQCJEQGVZIZCQCLyV7BhJHcsLgRqMJij3dWNgpDJOyIqo0lYIKAQUAgqBNyPA2kjqkqWFTR3xThzAgMWC861kJ5WLJfJlskeejA7KfcUY5KVny5HOHlqqDYKcTqeBhXJJFgOtVkAA0FKF0FtoPjMOKr0v6d3TagS4MnCd+JLylVTyotNqoKUyEFQIlnotbG0tYGuj3DsxIJysrHSEmoB5o67NfPr6sWrpVBjbOh9Gtsij3NeMQcs86PN7dvDLZKHTwsHeUrkkjIGttQU01MBaWWpVPUjC9YDbAWtrnexsuU7wtXKft210dLCEDXfa1GencLVG1vROyJLeUbl3YJCV/NOltAMP3PFi07w4xns4fNkH0zbcxaxN95R7BwazyT+xOi7fJTsfIjLSiNCwKDzxCCYX9EW7Jx4qf/8VBl5+YYgi+7V/YLiqA0m8nvn6hyMqyghvqhOPkzgW/9X79ja5jLkPlQFPM/Cj4+NnQeqdfI96yLg99wmFwfDSlvVWsnPtfiC2HnuG7Sc8lHsHBtvIP9G64x7Ye9YTkVQxwiMN8PEPk40bN3DKJT0sAoLCwY1rcEgkvHxDVV2gjj4pvgdevmEICo6U8zUDgiLgTddJEYcEfWbCPDA4Qs5PCaL30dtPvY/vVR6EGw/WjKaXP+L7VrITr7onUd1UmVUIKAQUAgoBhYBCIKkj8N+SHUHwmh2d8j/PIufjq05QOHYvlU7mEAJ8H4Ku2dGBZbwWjv3YkT//cxg+KvdfISAghIglXLxyDXkthMDrm5B+gIlGLCZ5LoR4PdiLO0IIGSb6Mjo8IKA2hYBCQCGgEPgABJJw0P+E7FDfhGxp7VC5ZEpUKRXtfiyWAgWyOMDOWic7ODPmep0GpfO6oEbZ1Pjlm1RI7qAnf+4GAf4CoEw+F5KRily0nApF3ZA7oz2s9VoZzsFWhwpFU5B/dJifS7ihRG4XpHCylP7mdNTx0yEghCA7fgRu37yOA3u3Y/PGv3HsyH54enpACCET0mi08PH2woF9O3Dl0jmynRrkfd5FRITj5o2ridOlwgAAEABJREFU2L5lHTasXYbDB/fAx8crJi6Hie2CgoJw/uxJbNqwChvXr8TZ08cQGhocO4g6Vwj8NwhwfWb330hXUt+JQHR78s5g7xvgXWXJ/uzikSfEJ85LPGmoW/8dAppPJZo1KeZVKJnAfF84Of6qnAHNKmeUrmXVTOhSLxua0j1Xh2giwvMCUrlaofFPGfBnpQzS77tCyWEkYSzLxlKLplUykssgZbCsltUyomu9rKhaOiU0lPusqe1kvGYkl/2b/5IRHWplQbtamZEplQ04jU/1jEoOJCEJCQ7CquXz0btHK4wa3hszpozCsEFdMbhfRzx9+ohIphFnTh3BILoeMaQHtm9dhwgiOKCNdDk4engfhvTvhHmzJmL5ktkYPrg7Zk0fQ2EipHwKFvMfGRmJdasXYzCFX754FubPmURyOxHpWfFa2JhI6kQh8A4EhBA0mOIBkwnxbVqtVvobDVFgp+HGJlZAIYT053YKX9+WoE8khIBOFz0o5p+V4bIQ4u1Eg8uHw8VXHkJo3imPf+uPZRijuLwN4HO82LRaHYTgAV4ktW0mcDovvNQhESGg+bd5JV6CyCgjVSYBayInkVHRjYedlQ62dB1OfvvOesLTPwJuLlb4oUhylCvgSpUJMBhBWhoHZExpA0sLjYxfPJcznO2itTsaqmD2NjpYaDW4ci8Au894IjTciPRuNqj7bRokc7SENWl4OIwQAnvI/8r9IDjZ6VCStDt1yqehdARV0H/7lCq+GQGT0Yh9e7Zj3uxJcHF2xZQZy7F89S506TEYIcHBeO7xFCePH0b/3u3h6+NDjQQQFBhAZRBdL3i+WFRkJH6uXAvzlm7CjHlrUKhIKezathE3r1+CRqs1JyWPRqOB6pYFWrbpjvlLN2P85EVwpnS3bV4DPz9fki9kOLVTCLwvAhoiLkaqx5s3rsLYEX1x6+bVOPWI/e/dvYXZ08aiV7eW6NW1JbZSfdNoo+sm+0dFRmA9aSXHjeqP+/duv2/SKtw7EBBCgAc4/+zbhVFDe6Fvj9ZYsWweAvz9wLjHF53JRwgNwBYvmI5pk0bINkiI6HZBCCG1wFs3rcGQgV0woFd7OVAKCwuNKXMhBGmpr2HaxBHo0aUFpdkG+3Zvlelx+3Px/ClMHDsYXdo3wahhvah9OwQT1Z/48qLufbkI/Cuyw0QnTXJrtK+VFeNb58P4NvnR87fskoyYXjyzp284xq++jbGrbiEoNEouUJY6mbU86rQC3xVMBtbkeBEZ4lWaWRvD5IdlvxAB/kLowHkvjF5+E4t2uCMi0ggbMoe5sskL0Smx7Nlb7mPwwms4ftWXKjKQkTQ7tlZaChEdxixPHT8eAf8AP+zasQFuKVNjyIipyJk7P5xdkqFCxaqYOH0JcubKB/7BxdbtemLC1EVIlTo9uGMxp6jRCPyPwjZs0gpORFqSJ0+B3HnyQ9D9oKBACPozh+WjpaUVGjRqjp+r1ISdnQPSpcuITFmyS2IVGfG6Jghq+3wIJMKUeOR/++Y1DOzbkbSLXbBj+3o8fvQAQoiYp2Gy3r1TU6xdsxSB/v7SxHpw/y7AaALHv371EnWIbcGdMXeKHs8ex4kfI0idfDACkUQi16xaiAF92+H8uZNEXJ5h5tTRGDG0pyRBrwo0GAw4c/IounT4E5PHD8W+vdvg6+sdUx4hIcFYMHcyxozsKwdTDx/cI4LbD7OmjoW5XTp4YBc6tG6IbVvXIjgkAM+fP8UBKm8u61tUV0YN6439e7bCi8z0e3ZtQR8iYOcobxqN9tXsqOsvGIGPJjtMRpztLdC5ThbUKJsKqZNZwYaIRXnS2hTL6SQbBfnc1IjoqCODka5MkPfDI4zg79+zprFFrox28Caiw5+4+wdFwppkFMzmSGToZeOjJVKU0tWStED2yJzKFtxhBocaEBASFVOpOTSTJ/YzUqNEqSGM06F02Y+vlft3CPDLzZqbBw/uotQ33yIFEZ6oqEhZplGk/nVwcIJeb4lcuQugSrW6sLG1JRPAy7k65tRNpN7x9fbCk8cPcO7sSTJr7UfatBmRJVsuqhevh+c0ON1Hj+7jyOG9uHrlAvIVKAJHZ2eZtlmuOioE3oUAj+i3bFqNkJAg1Kj9GwT9aaiNMsfz9fHGqhXzobOwwMRpizFl1nJMm7USPfuNlIOmYNIgbNywEjxA+7lyTVB0IHoHtf07BIQQePTQHVs2/o2ixUpj7uINmDxjKerUb4yDREjOnDpKJiRdnER8fbyIlC5BylRp8E2Z76gkqERJDgcSGg1u3biKPTs3o0rVupi7aBMmTV+KH36sgk0bV8L9/h14Pn8mTenJU6TElJnLMWXGClnenbsNlG0Lt2kNGjXDjHmrSbO8Be079UUEmeT379lGeVFkh3FOLO6jyQ6/7EVyOCFfZgf4BEaAF6UbRZqXZbsf4c7jEAghJAbOdhb4rUI6/Fk5gyRDEWTmuvcsGJFkwyqTzxW8au8jz1DsO+eJ249CoNdpkCu9PRxtLahxkSJgZaFFpZIp0ff3HKhUyg0RZBrbfdoDHj5hiE4FsCKSVL1MarSulgmFsjnJuNfcAxES/pIQRUtT+49FQAgBPxo1BQb4I226DHhVlWuMpdplQmNi0ikQJzkhBLjDWbl8Hnp3b4WBfTrg+rVLqFipOpIndwPHix1BCCFHVKye7k0mhdHD+yAsNFRqkiyJWJmYdceOoM4VAm9BwMJCj1+q10XfAWNRolR5GdIk96BBlIY62/u4QfWxfoO/kCdvQQihgTWRdhcXV6qbJlhaWqJm7YboPWA0Chct9SKmOnwKBIQQYPOhH5mnf6xYTWqM7R0cUar0d7C1tcORQ3uIYGjiJGVn74Dfm7RB9z7DkS17nmi/FwUqhMCNG5fBBPXnKrVgY2MrTeClSn8LHkBdvnQWd+7coEHXQ/xKhCZb9twQQsDWzo60zs5SVqrUafBT5ZpInSY99TFWyJo9F/m5IoQ0RhRUhlG7xIFA3JrzAXnmgs6Zzh4ajcADj1AcveKDq/cDsXLfI1y44w/xQlYyRz0aEtkpkt0JGoq0/6wnDl/0hou9HsVyOcNIHWIQaWkcbSwQGBYlY2VIaY10KaxJRnStNRF10VtokDa5DXjS8nMyjbFZK5zMWTIC7eyI7DSskBYVS6SAnY0OZ2/6Yd2hJyTDnBMKpP7/FQJCCCovIzkqFzoncN8oT3KQeKBncsIdTv4CRfG/H39BmXL/I22eNZYumoULpBrmiYmxhXJ4O2rQSn5TXoYvVqIM2e995URlHx9PCM1HV+HYyajzJIIA16/MWXIghVsqIi+k9o3z3IJG+k/h7+cjO91hA7thYN8OmD97Ep49fUxtnQZcd7NmywnXZMmpVaL3AGr7dAgQ/mQqsiCtWuq06WEgbTEjzOZuxt3D4xl4kB07PSsra2TPkRtOjs5UHq+WJxDg5wdH0ji7uLjAyIMxapNSpkwDK0trKtNHpN25K4nPHTJXDenXSQ6+Fs2fBh9vT1neeNHIcTtEdgkyebrD0+MpcpH53kh9F9SWaBD4Vz2FrZWOKhjAc224EnLFFFSZ2JkRCCBT0/YTz7FwxwP0mn1F/vxEaIQBbMJKS6YvrUagZB5nDG+eB2wC43iOpA3Km8kRQpAwuhEWbsQK0hiNXHYTIWEGpCci9F2hZMTyyfPFP5us9p/zwqp9jzF86Q2MoLDe/uEk40UAdfjXCBjJ/OTk5AI7O3s8dL9H8qLLh07kvxB8zU5evnHHjRmTnCZN26FXv1Ho3GMwDIYorF21hBqeKCozIZ1ZAKdX6Zc6+Kt5RwwaNhmN/mglP2c/emg/tJp/VYXNSahjEkKAOy528T1yEJmpWBOwZdPfUivAZpWF86ZgAGkggwIDweRaxpVsPj4J6t7HIiAEEBIURCTUBAu9PloM4azTaolk6hARHg4mQNEeL/dcHuxe3ok+MxG5CSENjAVp44R42U4wcRLU74QEByOEytubTOob1q3ArdvX4e5+F3NmjMOgfp1letGSACE08PX1wab1K5A+QxawGZ/bLKgt0SDwsgZ8aJaJ2TzxjjYjpXa1Qs50dkjpbIlyBZIhWxo7SYJAmwdpYaZtuIOlux/i1A1f8NdaetLSFMrmDEu9Fv7BkTh30x+XSBt08poPnniFSlNWPjKPMZliQVyRA0OjwF917T/vBSEEvsnjSulZyalAlAyCiFTN2HgX87a6g7VHvoGRMhz7KfdpEODGIznZtjNkyIyjR/bh1s2r0BDZYGc0GKRK2J9GxXzNTggNBCUthICGzvkelyU3QOFhYYiKjAITKB5lW1vbIJxs4TxaCg8Pk5NCDUYDjNxgUYPEdnJWPWup4UuZKg301ICxDKhNIfAJEeD6yZrEzt0HYc6iDZgxdzUaNGyOy5fO4dLFM2DN0CdMTol6BQELS70kO5ERES98hGwDjKRF0ZMfv/8vPN55EEIQSdJL0sLxzRG4XeFytrGhforaF2dnV/QhsyTPEZoxdxWq1vgVJ48fxO1b18DpcbsVFBiA6ZNH4c7tG9LkxZonlmGW+V8clcxPi4DmY8UR18HJ674ICI6Cm4slmv6SEX0aZUeLqhmRP4uDrLAsmzs7PhKRhpZ3dCOZgx4509uBJxSfueGPUStuYszKW6SNuYVNR0hVSRU7B5GnDG42MBCz5x6T+lQpk4lMIBGblJRmeSJWMZWY5HI6VL+hoXTony+V+4QI8MvNKuUKP1cjNa8XqXzbY+niWdi2eS2mTBqGvj3a4O6dm/D18caxIwdw+J/d4NGQh8cTHDq4hzqM84iMjMDKZfMwdfJwHKcwR/7Zg5VL54LjlCxdXnYm+/dux9CBXXDn1nXwJ6fTJo3E4vnTcfrEUezasQk8CrMhG36+AkVknfiEj6hEJWkETLC1tYcQAsmTp6T2SQdrGxtkzpKd2i4NgoICiLS/aGigtk+NALcvjo5O1EZEwtv7OZhocBqBRDTCSavj5paa2nYtOY0sI/Z7mxNCwMbWBv7+vggJCZJxOA1vr+eIIDLF83BsSUut1+vh4pocFjoL2BABypw1BzRaLfxo4CaEkEtnzJ4xFju2rkO9Bn/hhwpVIDQaqC1xIfDRJcbE5ebDQMzZcp+0M1FIl9wauTM6wGgw4e7TEBiJpDAhiiLmzMcYWOjCxcESKZz18tY/5z3hFxQJ1twEh0Xh7C1/PPMJh4OtDhlSWYO/2iJRMBgBmebjIFx1D4SG2AxPkObKS9yI/EmwlKh2/yUCGo0GP1eqiXYd+yAwIAATxwyS8xo2rl2BQkVKIGu2XPKT0YF926NvrzbgTz1PnzyCfnQ+c+oo6PWWYC3O1o1/o2PbRujUrjGOHt6Per/9hSpV65AZK1JOGLxw7rRsZDhsFJm45s2eiDYt6qFvz9Z4+uQR2nXojWzZc1P9MPyXj6tkf4UIcCdqYWFB7YkWECBSoyWSbQEhBFxdqdOzsMTVKxfAk5FZm/nwIZtsTUiWzIWGBoUAABAASURBVA08uIoTH0LGZ3lCCHz+7etJkdvyDBmyUrlocP7sCURjCly+cIbaAn+U/64iEaEIPH70AN6ezyGEkC6mPISGrkFlqZOOkUmXPjOVmRFnTx0Fz+8xUn90/uxJajeikL9QUfmhRRCZJ69duQi9pRUNnoxwv3dbxkmbLhPCQsPkfMI1qxah4R8t0PjPNnB0dISFTkdpCU5CuUSCgObf5nP7CQ+0Gn8eHadcQsfJl9Bu0kUcveKN+dvc0XT0OfSff40q1ksiQvUTt4mwdJtxBb8PP4MT13ypckdXGi0RmPvPQtBl+mU0GXlWannak7zWEy7gn/OeAAULDTdgDGmC/iT/kctv4RyRo2ZjzqHT1Evgic5Q23+OgJ5MSNVqNcCy1buweuM/WLR8G/7e8A+69xoOXmOn5DffYvGK7di0/QS27z2HbXvOYuO24xgyYgqEEKj7axOsWLsPsxask6aCVev3o3W7HtRAWUBDZKpu/SZYvno3ChQqBitra7lg4ap1+zF9zt9S7tJVO1ClWl2ycL6sV//5Q6sEvgoEeImEgwd2Y+a0MdixbQNCQ0KwY/tGzJszCY8euSNTlmwoXLQkliyYjhlTx5DpYiTWrV6K0mUryOUOQoKDsX/PdsycPh67d22W2p6tW9Zi9swJ8PX1gRrxf3w1YbKTPmMmFCpaCqtXLcbo4X0xg0xHK5fPR/GS5WgwVZIGT/dpwNMGY0f1A5McLo9thD+X1SkiNFwGa/5eguVL5kjNTN58hZEnbyHMmTUBkycMxeTxQ0g7vAG/VKuHNGnSg5e7yJ23gCz/WdPGkv8w7N65CZWr1Ea69Jlw9swxrF65QKbFdWXKxGEYM6IfZkwZDdYQcXv18U+sYn5OBP412RFEQLz8w3Hprj8u3fOHD2lpqBeS5q0HHiHwDYh87Xkio4x44h2Kx56hr2lkuMI/9wsDx+V5OB50/tgrFKERpNphSSZITZI7yfYOCJefobMcD98wYuXkyWGU+08R4DLiEa+DoxMyZc6OXNRYpHBLCf5agf2srKzk1y4pU6WF2aVKnU5+Ssr+Gq0WyVO4STKTv2BRCptSkiC82Ozs7SleGkl+OLye1Mxp0qVH4WKlkDN3fjg5u8iR14vg6vAeCKgg0QjwyP7JY3dcvniGtIgRKFPuB0SEh+I6aXL8fX2lZuePv9qi/PcVcfL4Idy8cQW8nk6rdt2oPuooTiR4nalrl89KjU6pb8ojmMxb1y6fIy1AMER0Mmr/kQg4Obngr+YdUL1mA9y+eQ1Xr14gs1FldO05RBIOK2pbClCbkTtvQdnes1nc/f4dXLpwijRvyVGU2ghvr2dyOQsmQm4pU6FF666kFfoJF8+fwQP3u6hRqyH+bNZeynNzS0XpdQSXI/++n7v7HVSv9RuateoC7tusbWxRvFQ5lCr9LWmU3PHowT3SPLvjMdUhXkJDCFXirxa1EIIGrVrwxu8bH4VIeJz+NdnhB9HQg2g0gh6Q3Itnolvymo+IZ9OQB8eJxwtmPwoSfU4nL8TK4HQpZXM4vsFyzOd8rdznQYArspEnERsMknwwMeGU+Rjjx/4xzkxYTTI8T2qWjlTLHIfjsuNzjs/H2Ncy7Iu0+L5yCoEPRYCJczXqSPsPnYgBZjdkIvoMHCs/YTZQ/cqZKx94gvLg4ZNlmGYtO5O5I6Oss6xprFP/D/QfMkH6xcggWSncUsswH5onFf4lAvzOZ8iYBa3b98DAYZOkY7KSJm16ia1rshRoSuXB2l8uK16H5/cmrak8XpZnfyrPzj0GIUWKlDJOrjz50anbQAwieVxuv//ZGiyH2xghBAoWLibJFJf3QCrXP/5qBx68sT+v7s6Tl2PXF5bfrfcw8ECO8/Ay91/XmRACPJdy+9Z1WLViPv5esQCrSMu2Yd1yeHt7EhmM3StHP7sQAlGRkXIZkRWkXZsxZSRWLpuL5x5PKfwnoRvRCX3EPmFT/4gMqyj/JQJKtkLg60dAr7eErY2dnIxqw0dbPreFRhs9GmUErKyskSy5G5xI06CzsJBaBL4vhIClpdXLuBz/hVMmDUbo0zguI9bgMv4W+ugvtFiyEIKwtwWb0s3XXFa2sgy5HO0gz61tITQaDiIdz79ycU0GR0dn0tC9LE/pCSHnEXJ5O0h/XUx5a7U6So9kvihjri9m+UmhvO/euYHZ08di/Kj+GEemw/Gj+2PG5JF48ugB4nt+gyEKa/5ejM7t/sB0Ijr79+7ArOnjcOb0MbDZMRrvhNm/rA0Jk75KVSGgEFAIKAQUAgqBLxABA2k6QWRw5rw12P3PZew6cBFrNh1CnnyFEO2HONv5c6ewculcFC5aCpt3nMTKtXuxbvNhlC1fgcJHxQn7uS8+iux87kyq9D4DArGmO7Eq+TOkqJL4AhHgasBfP36BWVNZ+uwIcG347ImqBOMgwGXALs7Nz3ohhACbC1nT5pqMtJ0urvFqdQATTh47KLVubTr0gguZHC30eiRL4SYXov3s/corsCmy81mrzZebGNVnmTmtRgMrSx2s9FrlkiAG1vTMluSEELDQUR1QdSHpvgdU9hY6DXg+pN6C2wWqD1Q3VNvwGg7/XR2hMtBbaEHKFSTUxpPAN29YhaWLZmLHtvV4/MgdQojXsmMwGHHv7k3YkEnxyqWzmDtrAlaQluf8mRMJrtXhzCqywygoB51WQBAO9jYWyJreEVkzOCmXRDFIk8KW6oMGyV2skS2JYqDqv5Mse7dkNtAR0UlFdULVBafP3iYy5imT2UKrEYiHX1CL/d/+W1nbSPKyacNKzJw2Wn72371TU9y5fTOOdkcIgYiIcPCaRfyl4/DB3bFm1UI5b6dT29/lorJare6/zew7pGve4a+8kwgCvDAjPyovBhlpMEG5pIsBDdC4KshlIVQ9+IT1IBG+VwZuGMiuaaSjqgsJUxe4DF6xyMj387/esdkpX/7CWLZqJ/YdvoYd+y6gU9cBePr4EWl5ZhD5YgImYrJhNBqpzTAif8GiWLR8O7bvPY9Z89YieYqUWLpwFoVLiKegZF/8K7LzAoikfjBQQ8xVMSrKiKDgcAQql2QxCAmNBJPesIgoBASpupCU34Ww8CiqC0BIaFSSfR8StPzp/QulMmDiQZzzs3dTQgj5o6xCo4GtrT1++LEyMmXJhkcP7yM0JDgO4bGwsAB/9ZYsmRvSZ8hEeTUhU+ZscnHGp08eICHyT5mI+VdkJwYKdRKDALMe5Xi+XUK4hE/TXBFUHUj4skjoMuC6wHkwH/lcuc9XLxj3BHRMsjh5rUYD/nScfyIoODgIzk4usLSyQlh4mFxDJ4JMWBYWerlcA/9EEK/Dw+QnODgQgYH+cHNLzWIS1Cmyk6Dwq8QVAgoBhYBCQCHw5SHAn5YvnDsVY0f0lb9fyD+TMn70ADwmrc7/KlaDTqfH/j3b0KFNI5zgr7D0lihSrDSePnmMaZNG4OiRA5gzYwIuXjiDqjXqQ2hemrwS4mkV2UkI1D9FmgksQwgBttEGBwfD398fvHT661kS4N8iCgoKQnh4eBxvQ1QUAgIC4Ofni9DQkDh+b7uIjIxEUFAg+Pi2cMpPIfBWBKj+CiGkGv5t4YQQb/QWQrwz/hsjK493IiDEh+MrhIhXrhBClpUQ0cf4AgnxZj9zeCGE+fSrP2pIm+Po6ISjRw9gQJ/2GD6kO3x9vdGmYx98X6GSbINNRhO0Gi04LANStvz/UKteIyI4p9G3RxucOX0UfzXrgB9/rg5eAZ/DJJTTJFTCKt3EiwCrNm/duokZ0yejd88u6NCuBQb2743NG9cjIhap0RCT37BuDbp37YDVf68gm61JPvTDB+6YNWsaOndsg7atmqF/3174Z/9e6fe2Hae7YP4cdO/SAdu3boY21oq3b4un/BQCsREQQiCc1O8+Pj6kYg+Q9VJAxA4iG28zUWdSH9tTCCFD85cnTPTZXwgRO4g6/xcICCEghED0QMoPhiiDvH6bSO5s31RePDAKCQlBSEjwCxcCgyEqRpwQQnbc/COigYGBVB9ivGJOWL7BYKCBVpAc5MV4fMUnQmjwC2lkps9ehQlTl2DyjKWYPH0Zatf5ndpe/rLKJH9DbuykBShavDQNbCPh4OCIZi27YMrM5Zg4dRGmzlopfynexsaWcI1u//8ryN4lV5GddyGk/OMgIITAjevXMKBfT0yZNF76ZcqcBffu3cXgQX1w/fpVehG00t28cR2jRg7G2jUrceL4UWokTLLC7ydis2vHNmTJkhW58+SlkcMhDBs6AB7PnoEbFSn0lZ1Op8Oxo4cxbuxwrFv3N86ePf3GsK9EVZcKgRgEuEM8euQQhg7qTyS9OXp264RVK5chKDgQQkR3skyiHz9+hPHjRmHs6GHgcyGElCGEAJOkuXNnoUf3jujWpR1mTp+C5x4eMr4MpHYfjYAQQhLQFcuWoFePzujauR0mTRyDhw8fyDblVcFCCHn/8aOHVF4jMWHcSDx7+jSmLJi8LF40D/36dKOBWVfp+vTqigP794HnlIC2c2fPYMSwQXLw1bN7J2xcvwYREREAFbkQQsrntmnypLGyPjx69ABCkCe+9s0EvV6PVKnTIk/eAsiRMy+SJU8BnqwMRBMXJjGpUqeBpaWVbNt5QGplZQX+fTP+sVb201m8+vMcCYObJmGSVakmVgTCSHOzYsUSnDt3GmPGTsLkqbMweMhILFy0AkOHjUHy5G6y0odTuGHDBshGoWChIjGPy03Ezz9XxrwFy9C33yD07tsPDX5rhIfUWF27elk2LDGBX5wwAfLy9MSgAb2RIX1GZMmajXyiXzY6Uf8KgfdGgDuqwQP7Yu/enTS6N+LkyePo06sLNm5YCybUTIb27d2Fhr/WxmTqZHcSKff29pL1mBMJIbPtpAljMHrUUHg89yBNQQgmTx6LEcMHEZk3xoTjsMp9OALcbsydMwP9+/WgAdQdqS1YuGCOJD2RkRGv4RtFZu1dO7ejft3qVF5jsWvXDviQqUUIIcPy5Ngtmzdg/749cm2YWzev4/atG/AP8JODpSuXL5LmuT04jLOLK27fvolePTuDB2MWOguqIwapdW5QvwYNtEaC64OX18v68OFPmLhiMHkxGo2ybpuPeEF0+EnM/nzka3Z8bg7LR77m+wntFNlJ6BJIROkLIeDx9AmOHTmMcuW+Q5VqNWTuWb1rY2uLSlWqIU2atJLsbNu6CQcP7EfL1u2RKVMWGU7uSEYKt5Q0QkiOKFILh4dFIjAgEFaWluDlyI1kA5bhYu2iSI3No2/WHrXv0BVuKdxi+apThcD7I8BzEDp26Y6Nm3dhw6atmDpjLlxdk2P3ru0kRMCHiM3yZYtRoGAhVK1WE0YTERjy4X8m3TdvXsee3TvQsOEf2LhpFxYtWY76vzaUneWd27dkB8phlftwBIQQeOB+H9u2bMaPP1bC1m37sGDRcvzVrCVOnDiKwwf/eQ3f50Q4ly9dhOIlSqHyL9UuxtxqAAAQAElEQVSp7aHyErHSNoHumdCiZVvsPXAUO/ccwvadB1Gn9q+IjIrEDiKzPr4+mDJ9DmbOmoMZsxaANdUrVixGVFQUmOguXboQuXLnQd26DaQsyibUlvgQUGQn8ZVZguVYo9HiuedzeHl5UmdQGBqhkS8/Z4jZu4Hs4GSogvv9+1iyaD5++N+P1GEQIXplgQVWER8jUwI3UmNGD8fmTetR4cefkTdffhpJRbG4GCeEwNWrl7B69XL8Rh1M6bJkGyaSFBNAnSgEPgABF2dXVKr0C9yIcAcHhyF1qjTyPDKS651Jzjno0rUXxoybhKxZc8SRrNVqqS5eRnBIMKpQxxpFnaVWq0eZ0uVhSWT9xIljUpsQJ5K6eG8EhBBgMunj440qVatDq9NCo9GhTJnycHR0xO49O6Gje7EF8gCpe6++GD12IpVX9thecc7DwsNefEgRBoPREENi+cuhtGnSIVeunAgJCUdaGqzlzZMP58+dpesQWR86de6BCZOmE+HJSzKJPdFe/Sc+BDSJL8sqxwmFgBACPCmTv55ycnKmbLz+4keSWnkLqY15XkO3Hn1hb28nlZ48WZkbKiE0YNXz0aOHsWLFUqxduwoeHs/A/qEhIXSMWyVDQ0OxdvVK2Nnao3Wb9tTYCVA2IDS87gPoXEBtCoH3RcBEtdFAZNlIqnkN1SHWJLiTNiF/gYIkQsDSygo5c+WGnZ0dEW8D3Xv5L4QGvj4+VKft4eziDJbBvslJ02htYwM2kfG1ch+HgBBCtgU8TyR16jRSs8KSnJycYKm3xPNnzwjzuG2OtbU1EZU8sCXNsoEGWxw+tuPQXE7r161B+7Yt0bdPd6yjNocnPwtB5W1pJbU3Tx4/gaDyZW0z14FwIkcBfn6Q8kmrY29vT/WBCXFs6eo8MSGgSUyZVXlNaARMsKFGnSeg+fv7vZYZc+exZvUKFClWnBooPW7fug3+VDwgwJ80PncRSXZ37hjatOuElX9vwLYd+/Frg0bUAK3G/HmzoNVogRf8RUsj6csXz4NNYuW+/Q4hoSFkd78PJkB+pHq+7/6AGj8jEm5TKSdWBIQQRLqjsGDBHDg4OuDnn6vEdGbcOb6ijJSPyfcDg4JgSR2kRkP1lO4KIcCdM9fbwIAAuqP+Px4BGkwFBcroTDj4hDXGWp0FDXIsEBoWRu1HJN+O47hcOFycm3TB9+xs7VC+/PfInj2nnHR85NBBdOnUBtOmjKcQAmXKlkMAtU0d2rXEsCH90bZ1U6xatYzqghFGIsYs403ySYD6T0QIaBJRXlVWExgBfuldkyWHq2synD1zChFEXIQQECLaQYAIzT1JbvaRyvm3X2ui2V+/4/ixI/jnn/1o8sdvuHXzBjVcOjBhsqPRUtq0aVH/19+QgkbH58+fJSITQmJIEACtVodHjx+T+tkPf69cjt/q10KrFn/ixvXr2LJ5I5r/+bscabOWh4Krf4XAeyEghACv+DpmzHAcOnQADRs2kSYKrt9vE6DRCFhbWSOcOl0DaYfMYfncZDISaXI031LHj0LABCsikoxlWFiolCCEgIm0cFw2VtZW4EnD0uM9d07OzujZqz8WL12Jpcv/xqIlq1CkSHGsWL5UfrX1vwo/oW//IXAk7dGOHZslmcqWLQcsySxpb2f/nqmoYIkBAUV2PkMpfS1JGGm4mzp1ahQv+Y38DHzenJlg1b23lxeuXrlMo6WJsLDUY/DQkejVZwA6dOqO1m3bIXuOnFLV3LZdByRPnoKI0mlcvnwJISHB4E9Dr1+/JglS2rTpoaf4d+/cxrZtm+Hp6YHixUti5OiJ6NajNzp27o6WrVohTZo0KFK0OMluC1syN4Dy9bVgrJ7jv0VAiGjtwawZUzFr+mQ0avQHGv7+B1g7EztlCiYvBe9pJwTt6NzewR4BgQEIJC2ORqOhO8Dz58+oLocic6as8lrtPg4Bfo35i6hIMoXzp/z8dRxo6OPn6ysXLU2XPgM0Wg2EEOQ0iL3RLboU5ADBf9E3wJvBaKD44QgPj0CmLFnk3EAfH285sGJNdb36v2HFqg3Ys+8Y+OvSdOnSI1v2HLCzt6OmhQ1hwEtxLD32NdSWSBCIW2MSSaZVNhMIAWqNrK1taCT8B/IXKAT+BLdFs8Zo2fwPtGn1FxYvWgBXF1fwVyx16/0GbkRq1qyH9NRIZc2SDTVr1QV3FuvX/Y12bZqibaumFK8pxo4ZAV6/oX79hmSWMmHXzm0YMrAvrly6iEyZM6NW7Xowy6teow5ckyVDzpy5UL1GbTkCM1G+oDaFwHsgEEZameVLF2EGEZ36ZD5t3qItaRmtqSMMjxPbaDTJiazc1Zk1C0bSMGTOnBU6rRYH9u+RHSF/in6YTCM8H60omW5VXYwD4wddmEg7loXaCdaq/HNgL2nfIqhcwnD48D9ygUH+QosXB2St8vVrV4mAiBj5RiovI5EavmEkOUYqKyEEmJR6Pn9O7YoRGiKnD93dwYOrDBkzSk0c14fw8HDZjrD/QdJAs/zKlauRBtqCxUlnZPmGaJO5PKdrIV6mLwOp3fsikCDhFNlJENgTd6J58ubDpCkz0affYOTJkx8pU6UmglMLS5etlosERkREks3bIJ2W7O3ffvsDypb/jhocUKNihUa//4UaNevSaNoSPAGwHhGj2XMWIW/+/LIDyUdEqm7dX5GRRmH8+SebCczOQm+DqlVroVSpMqRyjm58EjeaKvefE4Fbt27I1bt5zhl3gv379ZSEm+dx8CKYPB9szuwZ6NShtSTdXp6eROrHYfiQAXj27CkKFiwkif60qRPRoV1LdOnUFitXLEZ1IuGZMmehOq7q5MeWp4kGLbyGVkl6t5cvW0Tl8ie6dW6H2bOm4YcffkSJEqVw//5dDOjfCyOHD4KWzNxMZnhRx07t22D3rh3gxf/Gjx2FYVRePt7ecr5fvTrV5AKFg2kA1arFHzh54ij+aNKctMzJsWP7ZnRs3xJDB/eX5ckLDrIZq0atOrIsg4ODMHfOTHQi+Zs2riNt83NMnjgOg/r3xpPHjySB+tjnVfE+LwKK7HxevL+K1LhRYnNU02YtMXHydEyfMQ89e/cjc1UOIitxH9HKygqNmzTFr781ihmJZc2WDV279cKsOQsxc/ZCitsfWbNlp7gmGaZsufLo1Xcg0qZJJwlTbIn81UXbdp3kp6lMgGL7qXOFwLsQ4DkhefPmRzEyjz59+hgPH9zHo4fu0hwbFh5G9S2SOtQ7OH/hrPzqKn/+gnhGZqor1y6DiZBrsuToP2AoahC5uXTpPO6730PL1h3IxNpNJs3vhjxRu49CwNHRSbYNjf9sjps3b5AW5ioa/NYYQ0eMIWIhYGdnT1rd3ChcpAi1F0a5Vs69e7dx7sIZODg4gMv2KZHSa1RerAUqWqwEChQqhFMnj2Hnjq2kWXbA2HFT8FujP2iwZECyZCnk2kpbt2yQ8wnrkXZ59LjJSJkylSQ7PNhigsXy9VZ6IroF8dzLA1wfgoNDZHv1UQ+qIn12BBTZ+eyQfx0JcqMerQKOkOp+Po+PfHC4iIgIRJK2x/zkRlIxs+qYr/mc4/KRr9nxb+G8eo/vs2N54RHhYLs+XyunEPgQBJhU8yTVDZt2YuuO/dJt23kA6zfuRAHSKNrZOWD4iHHYuesgNm3ZjfWbdmAH+S9bvhY8l4M7v8xZsmL0uEnYvGUP1m3Yjk6du8OROmmumx+SFxX2dQRMZIJKnSYtBg0ajs1b92Ldxh2kQR5EpCS5JB9ubikxavREtOvQlYipAS5kNh89dvJr5bWUyitN2rRgTdH48dOwkcpq87Y9WL5yPWrVqQ9LvV6SpZKlSmPxsjUyLfbvP3CoLGcTaZk4d1yuw4aPkfK5vNdTfrbvOIC/V2+iAVo2mQcOp9yXj4AiO19+GX3xOTQ3DB+a0Y+N96HpqPBfNQIf/HBc797kWNjb/NifiTk7Wzs78PwSJvkch/2U+/cIMJaMrxVphdnMzed8zyxZaIT5VB7ZLz7HnvI+TFJL5+TkLDUxscuL/fk3spxdXGRZclrsOK7ZcZj4nNlfHRMHAorsJI5yUrlUCCgEvjAEuAP8wrKksvMGBLis2L3Bm7Q8June5K/uJ34E3kp2qPipAiT+h1RP8HYEZDm/PUji91VPoBBQCCgEFAJJFoG3kh29hQa2VlpYWyr3NWNgI8tYA7NyWAgBIZQTIqliEN0eCjqwyUAIoepDksWAKwGo/NmpeiDE58cALzYNme/48/joo4A6vgMDKitAwLxpzCfxHSsWS4EBf+RE30Y5kopLos+ZE53qZIGlXgMLIrgO9no4KpdkMbCxtoCGGgorK12SxUDV/+g2wNpSJ+sC1wmFSTQmnxMHBzs9bOg95PfR1dkKGdM6IGMa5d6JAeGUys0WOq2AeXsr2eGK7mJvCWfq+JTTf9U4ONrqJQfmjxAMRl5QTbmkioORyp8bCK4LfJ5UcVDPTQZuE9cEgKuEwuPzt4lGegnpH1wMWo0GbG3hAenncxo5AE5s6UmcdHHpTdwrxN3WHHiMluPOoe2kC8p9zRhMPI/ec64gNMKIgOAI3Lznp1wSxuCRRxAiowx47h2CG3d9VV1IonXhxl0/PH0ejMhIAx4/C6S6oNqFz9028vv3hMrAaDDBw0u9j++LP9dd98eBiHqx6jUzm7eSHWbzUbQzENDKEav/WnEwArHqBNcL8JcLyvHINmk6rgSq/JNm2ccpd6oIrFWQ2gXaxfGLda3u/1d1BbItpmKQR4Xzh+HMuJndW8mOoFBkusfHOopO//SqkKDYMugm/Zti5IL8qUhJVUcPQvvYYWOfcxizi33/1XMSTv8m6WL7meOSB2LfT/LnBIgsAjp+6L8QgrAUb4wmhHijvxDRfkKIN8aP7SGEeKOs2OHUuUJAIaAQUAgoBGIj8FayEzvgx5xbWWpgb6ODPpbtjPor2FhpYEf3tRpBtmATBAm3t7FAMkc9nOwtEH2fbsb6Z0ZrpdfC3tYCttY6OWkOb9gsdELKt7e2iAnB8dmOx/GtKV+cjxhPdfLBCGjIfmyhtyQ1oQFhoaEyvk73Em++odPpYDBEkRo8ki9jHMdlP15FOTg4iMIYoNVqY/xfPdFotNBQerxcPy8Bz/58zUflEhMCKq8KAYWAQiBhEND8F8maSKilhQbd62fD9M6FULt8GlgQ4SGtJxyI5HSpR/c7FkSJ3C5I7mSJ9rWyYHqnAljWtxjmdiuMng2yI1saW5IS/c/xnOz06NsoJ2Z2LohxrfOhZG7naEVNdJA4++I5nWWY6Z0LoEw+VzLRmIhg6dC6embM7lIQratlho2lLk4cdfFhCDx8cBczp4xC13aN0bJpbfTp3go7tq2TxIUlMZHZt3srunb4CyuWzEZ4eBjflu7Jk4eYNX0c2rX8FS3+rIU+PVrhyOF90u/VHZPUq1cuYOTQ3mjdrC5a/lWbznvi5o2rEIJp8qsx1LVC4P0QEEK8tQ4JY7r/MgAAEABJREFU8WZ/IV76CSHeL0EV6r0REEJEl435+JaYQrwIS2GEeHlOl/JfCEFHdpAyhYg+R6xNCEF+kI72eHUTQtAtQf7sII9QW6JC4KPJDhMQ/lKDHXdI5qfmGft8TwiBdCmskZy0Ncmd9NCSFofDMOlJ6WyF1Mms4GinQ9Hszvi5hBtYaxMUGgVnOwuUK+iKmuVSx2iEmDzlzWSPfFkc4OZsiaxEhErkcoaONDgsM46jwJ7+4WTfBFK5WqH2t2mQgghV4ayO+K5gcjiSZsgrIAIRkcY40dTF+yNw8/oVDBvcA6tXLYS1rR2yZ8+DgAB/TJs0ArdvXcOzp48xdeIwjB89ACePH8SdOzeJBEXJBExGE04eO4jTJw4hR468KFK0FK5fuYSJYwfh+fOnEBoNZMAXO/5drT27NuGh+10ZNlv23Ni3exvmz5mEiPBw1ei8wEkd3h8BIQSo4uDRQ3ecO3MC/n6+iL0JQRpnoxF3bt/AhXOnEBISTN4Uh/b8byS/p08f4fTJIzhB9fvhg3tUvw3spdwnQID7E8/nz3D29AkcP3IA9+7cRlQUa4dflkFMMtQR+fn64ML5Uzh4YBfOnz0BXx+vGG8+8ff3xeWLZ6Q/l9lzj6d8O8Zx+XKbdvjgHpyiMvXy9Ijx4xMhBEJDQ2iAdQXHDu/HkUP78ZAGe0LEkx+OoNwXicBHkR3iE7Cz1uKHoslRtXQqZEltS+TCBGsyM/1QODkqFncjjY2eTFTRlcFIHVyMo8g8M0eiQefP/cKx9ZgHxq+6jclr7sA/KBIaqkQZ3WxgT1og/vTOirRE+TM7grVFkVEmkgvkJ/LCxIXquhQVs6Mk7z0NwdHLPoiMMiJTShtULpkSPxZzgzWZzx55hmH/WU9EkF9MHHXy3giwhmbjhhXUAN1Exy4DMWDIBPToOxyDh09G24694ezsCnciJoGBAWjZtgfSZ8gMk5E7AioYToUOxUqURZ+BY9Gp2wAZp3K1Onj+7CnJvEWkWIvYG5u7fqlaD/2HTkCb9j3RoXNfFCtRWjY8/v5+1GeRwNgR1LlC4C0ICCHI7BqCXdvWozdpI8eM7Ivr1y5RPTI3hQIBVK9Wr1yAvj1aY/KEYXj86AGZUaPrGbdHJ48dwpD+XTB0YFeMHtYbA/q0xyHqaDVkan1L0srrPRG4eOE0hg7oiiEDOmMslc+APu2wddOamDIwixFC4NEjd0wYMxAD+3TA8EHdqSw6YNK4IfDy8qAyFfB87oHpk0dhUL9OdH8wBvcnmaP64wG1UVxePEhbsmA6+vduhylU1ixj3Oj+RGbuU3oaKcPL6zlmTx+Lfr3aYtyYARg3qh8mjx8GI5Fec17U8ctHQPNRWSSSYmdtgQY/pEOLqhlRvUxqWOq0SEFal1bVM6FhhXTIlMqWRJuosoBMRlo5F8eJtDZsxtJqopPVagVOXffFjI13ceyqDw5f9gZrXSgi5FdgRJL43NXBAjky2MkFgvad84Q3aWZSuVqhABEe1iRxmNguggjR7tPP8cw3HNaWWtT5Lg2K53aWJGrb8Wdwfx4i8wW1fRAC3Dg893iGc6ePo1jxMqhYuRqsrKypUdDCxTU5/vfjL0jhlgqFChVDn/6j8e33P4F/KDE2IRVCIFXqtMiYKSssraxIO2eB4OAgaKn+OLm4wmSKq3HTarXImDkrUlMcSytLKjdB4YNhb+8AK2urD8q/CqwQYLI+b/YkjBnRF0FBAfAgLWRYWCjVq2hsAgP8MI40kvPnTIY/nXuStjEyIiLak/ZepHFYOH8KgoOCMHz0DPQfPJHaFS2mTxkJ1iDwO0LB1P9HIuDr443F86fh/v3b6DtwDAaPmAZHJ2dJVJ4+eUTlFN13mMV7kRaGy699536YOnslChYugW1b1mDfnm3Q6Szg7+eDqMhItKdB0qTpy1Ctxq84fvQf7Nq5kdomK7A2Z83fi1H22x8xYcpi/N6kLc5S+7Z+zVJq1zRkfg/HyqVzsXL5fFSoWBXjJs3HmInz8Wuj5pQXYc6GOiYCBOLWnPfMMPVX8PANw93HIWDzU7Z0dkjurIe9rQ4u9nrwFhZuoI4LNFIXKJPfFcOb5cbY1nnRr3EOpCfzFocRtGOyEmUwybCFiLxkcLMhxmwCa2cCQ6KoIRHIRJqj1MmsERAchW2kBbr1gDpHjcC3BZORfBLyyj954bFXKDYdjlZXWuk1kijdfBSEnaeeg9OF2j4YASEEqYg94evnjRy58lLZaKjcTFKOiRgNO77QW1pJIkOlimhfvvvSGQwGnD51FH+vWIgxw/vSqG01vv3+ZzJr5Y7XHMAdy74927F86Twa7XXFpYtn8XOV2nB0dKa6YnwpWJ0pBN6BANc9Jub9Bo9Hp64DXqufUVQ3mYiPm7QANWo2hNxeNBhanQ7XrlyA+7071Cm2RIHCxVGoaAlUqVYXT4k0Xb5wVnaQMo7afTACQgjcv3cbN65fRv0GTVG67A/IX6AwatdtDJAfExQtDYrwYuP2Jl+BIhg+ZgZ+qFAZOXPlQ41aDZAiRSrcv3uLykIgS7ac6DdoLL774WdwuX73v5+RPHkK+Hp7k78Wly6cgRsN0Oo3+BNpM2TCjz/9goI0WNu3dxvYhP70yUNJjqpUrYM27XshU+YcYFN60WLfvMjFF3RQWXkrApq3+r7F00Balz1nn1NnY4Krg15qcvJncpAx2BTlExgpz3lH/aAkRTb8G0xk6tKSRofvxzhqTLKmtUWTShnAfg+eh2EvmZpYu6OjsHlJLpus3EkjwySGj6xOzpXBnkxodnICcows8wn1st7+EYiKtYCMpy9ds/mKXhxzMHV8fwSE0CA4JJjMAKGws7PHaz1FLFFc5rEuY06FEOCR8ukTRyTJOXnyEAT96fWWRKR88OrIWAghR+AHD+zEts1ryORwEba2tjBERZEdnUfkIka2OlEIvAsB1kTWqf8HdWrVZB16NbyzszMRmVYoVrIMoqJeanQ4nEZowJPrmfRkypJDzhkzkSkjPXWS9nYOuHHjCgdT7iMREITvw4f3oNFokT1nHkk2mNCkTpMOXG63b16jAVbc912r1UFLzkAk1Ujm8qCgQIRHhBOhSUl9kxFCUHsTFQkf0hh5PHss59uwJihr9lzkb6A0wqGzsJBpmqgsraxtkDJVGniT6SooMBBMdrjMc+cphLNnjuHYkf1gMhYSEiRlf+SjqmgJgMBHkx2qQ7hFmpJHnmHguTWFsjmiNGlwmAS5e4TCh0xNHIavz9/yx8TVdzB6xS3M3HQfHj5hMY/KnWIaVys0rpge2dLaSe3N+kNPcM09QHamLDsfkR3W1iQjUtW6RiYUzekEQX9sFiuag84pISY/hhcaIpbJn7BXKuUmvwIjXib75cLZHVE4uxNVcmJCMTlQJ++LgIlMTNbUGFjqreDn7wfxEbXHRIVjSear2vUbY9DwyWBTwE+Va2Dn9g1Yv3YZhBBxssPhXZMlR4s2XTFkxFQMHj4FOXPmxfzZE3H5khpJxwFLXbwTASEEdKShefN8CwEtdZ4mbjTw6mYi81WgJPpMzqN9BZFve3CH6fvKxNho/y9u/8VmiIoGAX5+YLLj4OhEWmMjOZPUElsQIQkm8hFFg5xXH4DbCEDAaDCQWWovuHyLlSgDJkBCCJw9dRwjh/REn56tsXjBdOTMlR/lyldARGQE0qbLgCePHmDLpr9x7+5NnDh2UM4HZFk8KZnnBYbSAG/Z4hkY1LcjRg3tJedyLV4wg/oRI9SWeBD4iO4q+uE0VIm8SHNy8W4AWPvCE4B5onIoma+OXfFBCB2526K+Tc7D4XDnbwfgyr0ABIYapBBuTxxstPjj5wwokYtNEibM23ofm48+BcvhCca50jsgXQob8ObmYoXyBZIhSyo7UPJ8C2WJYNlba6V2KVs6W/DaPuxROq8r8mR0kPnYedIDj56Hyvk7tb9NLb/44nxxOOXeHwFuVFxdksPZxRUXz52EIcpA5cClDHm0sNBDo9XiXZuWwjg7uyJN2vTU8ORDlap14UgmqYvnTyMsLAwajQYcRsqhgma5yZOnlOELFSmBnyrXBDdkbFKghGUwtVMIvC8CXI/fFjbaP/4BkYE0xSYaOrGTMqj6a7RaqoZC3pX31O6jETCQdobxN5GWxSxECA00WjKZm2/Ec9TptNi1cxO2b12Lij9XR3Yys5sJrZ29PdxIW+NG5i07OzvwF1v79+2Qg+kKP/6CXLnzY+bUMfijQRX079VWmio5CUvSNvMcLz4vVfo7jJ+yEKMnzkPGzNmxdOEMknOSiJUFeyuXCBD4aLLDz8balJsPg+RXTzwvRqMRuHo/COdu+ZG3idzLf/IiFSRAfReofQBvHP/nkilRvqArdW4Cj0lLZGutQ73v0+LX/6VDmmTWYG2MLZGZi3cCMGD+NfSdew395l3FPjJzGUiT40YEqHQ+V3Stlw0T2uZDtW9SyYnS/FWYFZnMHpCWadnuRzh+xZc6SBOyp7NDydwu4HxwHpR7fwS48UiRMjUKFymFU2SGWrpoJnx9faSZ6dHD+5g9fRw1FBelwPCwUPCIyEidAxOTsNAQRNJIis9vXLuCh+73wCOnkOAg3Lt3C8HBgUiXPqOcNPiQZP1DjVFQUABYzuWL5/Dc4ym44eGR1t07N6nORSJDhiwQ9CcTVLtPi4CS9hoCQmhgY2eH0JBQGMwaBho1hZBJI4pMJcmTub0WR914fwQIStiSedxEGuQQ0qYIIQByEWSWigiPgIODY7zkQkCAPwkfNaw38hcoiroN/gQTFdBmIqH5ChRBt55DMGr8HDm5OE26jFgyfzq8vZ8jQ+ZsGDxyKiZMW4z+gydg1Lg5KP/dT3JStJ2DA/R6PeXJQZo9M1HYHGReq1CxKoQQcL9/m/qtf9WFUg7V/+dC4F+VlI4YzJ0nwQgOM8j8PvIMxcId7nQdJSsDa26kB415JI2OvpCqSTMVyuhmSyRISB9el6dZ5QxoViUDmlfJiCJkomKzE6+Jw19tHbrkDdYa8XHfWS+ERRqltqZQVickd9LDxlKHZI6WKJzNCZlT2yKKyNDmo8/kZGX+isvDN1yG4YUGne30Mk21+zAErMgEVaN2Qzmngb9q6dyuMY2G2oOPO7evp3IHbl6/jAljB2L08L548OCenATI5yuWzCXVr0mqjLt1+gujh/bGcFIvz5w2Bm5EoqpUrwcjNXR7dm7GkIFdcePaZYSFhmLurAno0bk5xo7oB/7kd+P65XLyYoHCxWAg1fWHPYEKndQREEKAB2ZCaCAACCEgNBoAArwJISDYj44x1+TPZJ81kiEhgfLTZTatsD9PhuV6mpM0BNy58j3lPgYBk5wszKaqO3euQ0vmRkFiHj64R+1ACPLkKwQjaX4YayY/5EXXRhw/egCjhvdG5izZ0anbAKQjMsPxAAEmpTzRODIyEnxMnSY90qfPBD8/H4STFpm7JhfSVpcu+z1+rlITqVKnxeNH7nNbTX0AABAASURBVCharDQsLS3h6OhCaRjw8MF9CKoTXL5hYSHgdsqaTPrEpaC2xIEAv+EfnVMNkR1Pv3CEENnhQt9KxOL6w0Bo6T6boNYfeoplux++WPOG6A3VwCAyYW0+6oFF2x/gunsg9p/3xNwt7tItoHvztz3A/K0PMHeru5wTtOPkc/D9I5e9YaEVsNAJ6C00ck7P4p0PsHLvIxwmErSB0lpAcVneE69QrDv4BHO23MeRS14yP/eeBmPO1vtYuovyQ2a2qFhq0o8GIAlG5Jc9a/ac6NpjMLr0GIySpcqBRzzVav0m18LJmi0nrKgRyJAxK3Lmzoc//mqLmnUbkbkqL1KmSkMjJQtUq1kf1Ykw2Ts6wsnJBXXr/4G+A8YgR868MFG5FCpckuK1I01PJtjTaO73Jq1R/vuKFNcS6TJkQrOWndGxcz8a6UXb9ZNgMahH/kgEuP4+ffoIVy5dgLv7HRoQRUlCfu3KRYSGBoMJDXeuly+dw7NnT6iDDAdrEm/dvArWLPIXP2xS/XvFfFwgsysvUrdt81qkz5gZefIWpPjUzn1k3pJ6NC6bTGQickuZCutXLwOvZ3TuzElsXLtcalf4iypPz+eYN2cS1vy9EFqtDrepXGZMHQUfby9pvmJN8/FjB3Hp4hmwtu3C+VOYR4Ol06eOEEG9h927NuHSpTPInacgnMiUzkSVFz7l44lj/2DmtNGk8fFEpaq1IYQAT45OQwRp7d+LcIFM92dOHcOOrevABCl/QR5sRSX1Yks0z6/5tzmNiDIiKJQL3ASfwCjqrKIlRpFWZdcpDywlsnPmpp/8Yoq4DsIiDNh12kOSIP68/MIdP6zc9/A1t4rusdbo7/2PsOafx3j4PDRaMO1ZTkBIFNbS/WV7Hsr1ebadIJl7H+IqEahLdwPA99cdfExaJgNVWsj0D13wxuJdD7DjpAcCKT6JUv8fiQCPkKrW+BXNW3dF24698Vuj5shDDYhGo0X6DJnxa8OmaNKs3UvXvD0qVqoObtCyZM0J/tSzQ5cB6NClH4VthuxEdMiTykogf8Gi+LVRM6RwSwWNRgOep9P4zzbo3GMQ2nboSWSpAVKlSUfBVcfykcWXZKPxaH7h3Kn46/eq4HkagQH+mDFlFNo0q4vzZ09Kc+qUCUPxV6OqslPzfP4MI4f0QNf2f5Lp9S6yEpmv16Apbt64hlZ/1UHn9n8gIMAP7Tr2gZ29A9VJY5LF9t8+OLcNPI+v4e8t4ePjhfatfpM/KcNmbh5cpXBLjQA/X5w4+g+YdAgh5CrXV69ckGUwefxQdGzdCJ3b/o5+vdrJL+eMNArftWMTOtG9RvV/whgydTk5OqNVu25EoOxw8cJp9O3ZBg3rVqT0GuLcuVNyoFW02DdElqLkBOba9RqDP4lv2bQOOrRuCDbZt+/cB2nTZoAhCWiWhRCyXRbi5fFdZS3E+4d9l6xP5a/514KoMjHZCY0wQqcFgYLXt/juiOibAvQXCxghXl5Hh3jzXgghPaP3IEnRTp4AEMLsA7m9cinvqd3HIcANk4lMThxbCEGNvEk6vmZnonphIjtmHEf3YvzoXEMaQCYzMixds1+0IxIT65r9+T6HFUIj0zHf4/vKKQTeFwE9mSYaNm6OyTOXYsa8v7Fg2RbMmLMKE6YuQv4CRWBjYydX/p48YylmLViL+Us3Y9rslRg2erok2EIIVKtRD7MXrsXA4ZMxetwcTJ6+FIWLliKtjiI671sObwrH7/gPP1bG7PnrMHzMTHIzMH3O3yj33Y9ELKKQOm069CEtcKduA+X1N2W+x/wlm2Q5TZ29AtLNWoHho2cgJZnGi1C5TJ65HCPGzEL3XkMxcfoSTJi2FAULl5CLDX77/U8ybLdewzCSynLmvDWoVqsBdBZ6mUWdzgJVqtWlurAO/QaOx4ixMzFj7mr8UOEXGkAbZJiveWcwRMGfCKa3t6fUePHR18dbYv+m52aTobeXJx4/fgAv0sSxhu1NYT/n/X9NdsKJ5Kw58BgzN9zDZdKoUP/1OfOv0lIIKAQUAu+NAHemGcjEWqToN+COUDoaxRcqUlJqZtg0kjVbLhShe9KvaCl5ni9/YVhZWUuirdFqkSVLDlT4sQpKl/sfUpB59r0zoAK+FYHoQYyQZkEmIuW/qwj+PNwcSa+3RG4yF2YgsyGHdXJ2AZddTFm9KK+8+YvA0tIKPBcrXboMYDlVqtVDiVLl4eqaLIaYspmcP1OvQoSmbPn/gcOCtxeDLU5DS+WdPUce/FS5Osp9+6P8KtT0YqDHQT/GJYY4Qgip0Ro9og96dWmBXl3J0ZF/xoMX1uR36dXn4A9J5s+ehJ5dmqN3t5bo072l/Nw/0N8fQsRVPrwa97++/tdkJ4pG7yeu+WLL8Wd44h2W4A/0XwOm5CsEFAKJGwEDmR549PmqM8kOziRHra/68aTZaH9IwsPX0S5Sru+SuBH58nJvII0CawQYYwOVlzmHXAYG8jO8uMfXr5YVX3Nc9qPCovI0kEkqko5RUpvD87LM8vg8Og3yi+IwpK2R9cAcIrq8DZQmh2NneJH2yxBf7xlrci5dOIM8+QrKVe7LkyasdJkf5NdqEt/Yj24Cdu3YiI3rV4C/gGv0R2tkzpoTf69YgNOnj4BJY+zgn/v8X5MdzjCbI7Sk0klg4sZZUU4hoBBQCHwlCKjHUAgkMAJEYHSk2apUtS5++725nJvJH5y4JktBPJI8Y2XPCCNu3rgCNh/+2bw9+BP9KtXqwMraGu7371LIRK7ZoSdQ/18DAi/qYfTBBD4qhySHA2JvNHqh/ySHgar3iC5zYW4HRPQ1oI7A58XgRRkgATee5O3j7QlPTw+E8BeLbzDhcS1JlSotnj19jCMH9yEwwA8njx1EcFAg5Aco/J1/Aj7HJ9HsJGD+VdKfCAEN1QRBsiwttXBLZoMUyiUaDD5lWXHZuzhaQavRwMFWT3XBNkni8CkxTayy3JLZwsFeD61WwMnREm7JVbvwucuSy8DRQQ9B7bNkWfi8m1ark/ObJo0bhB6dm6F/r3ZYs3IhggIDIISIkxkhBCr9Uge85Mi40f3Rs2sL/L1yAWrWboTCRUqSGZFMhHFifN4LhvDzpqhS+yIR0FBF5YxZ6nVI5mSN5M7KJVUMHO300GgE7GwsVD1I4u+BPdUFJjtcJ5Lq+5DQz+1gZwkNtc9xqQW31v+tM5H4TFmyoX3nfmTCaomfq9SSxGfe7EnYsmkN4puDY2VlBRtbO0lsvDyfyZ//4VXvw0JDSFrC/iuyk7D4f8bU354U//QGV+6oSAP8AyOUS8IYBIdGSXt8aHgU/JIwDkn+PQiKQCjVBW4buE4keTwS4F3g9y8kNFK+j6/Mm357g/4pfClBF5dk+KFCZVQiolO77u/o0Lkv3FKmwaF/diE0JCSOdifKEIUli2bgwrlT6NlnOGbOW4u69f/E7h0bsXzJbBpAaT9Frj5ahiI7Hw3d1xWR6rV8ID7yFwoGoxHKJU0MjEaTtK7z0cC/babqQtJ8F6jseb4GNwyyLqh68NnrgZEwp9dRvo9cDgnhhBAxpMaatDY21jakuaEB0YtccR6F0IAX4Dx5/DC+/a4i/vdjVTgTUWr4R0vkzlcQe3dtpdCmhMh+TJqvkZ0YH3WiEHgPBIRGA41WCyFEvKGFENBQGCHi+gsRfZ9VoULE9cNbNiFEvPKgNoWAQkAhoBD4ZAjwp+XXr13CxfOn4e31HM+fP8PBA7vw8OF9FChQDLwA553bN8A/pfHo0X3oLfSw1Ovx9Olj8HVQUCDc799GgJ9f9IKcnyxnHydIkZ2Pwy3Jx2ICw45XyLx/7w4CAwKkDVeIl8RFCIHwiAg8e/oUAYEBMZhxPAOpPB8+fIBbN2/A18fnjWQpJhKdCCEQSrbfp0+fICQ4mO6of4WAQkAh8J8ikGSFM9k59M9uDO7XCb27t0Kfbq2waN5U5M5TAFVr/irn71w4fwrz50zG9auXkDxFSvn7ZPz5OU9k7t2tBYYP7oHIyAjwzwex1SAhwVRkJyHRT6RpM1m5fesWOrRriTq1fkHtmlVQv241zJszU6o3zY9lQUx/wdzZ0m/W9ClkdzZKUnPnzm306NZRxq1H8Ro3qoctmzdIP3PcV49CCKnRGTNqOH6rXxMrli+GTqeD2hQCH4uAEELWISFEjAghou9x3YrtXtVA8rWFhcVr8WMEqZN/hYAQ0eXAGAvxsnzeJFQICv+G8uD2KnZZ8rkQL2UKIeRAjdN61Q8vtqRY3oxbtRq/omW7nihV+jt8+7+f0avvSPQdODZmFeniJcqiR58RKFiomESq9q9NMGTkVFSuWpfuFUfD31vIn1opVfpbIkfqaywJktolDgSEEDh//ixaNGuMbVs3IUeOnPjxx0qwtLLC2DHDcfbMadlwaLU6Oj+FqVPH48bN63B3v0eV3URkyIC9e3biyuVL+KVKNdSpUx+epCIdMqgfnjx+LAlNfEgIocGe3TsxZ/Z0XLt2heTdhxAvG6z44qh7CoH4EBBCgGcPeDx7hpMnjsHX1zcmmI+3N86cPhXjztL52TOncOnieYSEhMhwoaGhuHzpErZv24Jjx46Qit8LpoQetsqcfS07E/z8fHHy5HHs378HDx7cB69cLET877vBYMAzKsuDB/bjyJFDeO7hQW2NUYJhiDLg/r17OEftkrlc+dzz+XNwZ87aC07r9KkTsjxPnTyJAH9/Gde8CwkJxoXz57Bj22ZZXzi82e9rP6ZMlQY/VaqOpi06oXGTNij3XUU4ObvIx2bs0qXPiAo/VUUy0urw3B1rK2vwT7GwJqdpy86kAWoA/vkVxlpGSsCdJgHTVkknQgRCgkOwasVSeHl5YszYyZgxcz5Gj52A+QtX0HESMf50siPx8/fFyJGDkcw1GfLlK0BPyg2VkA1MpUq/YO78peg/aBh69u6LevV+A3+eeOvWDfAICq9s/KI8IpPXyOEDUax4CWTMlJmIjuaVUOpSIfB+CPgRudm4bg2a/tUQHdu3oo7sjKyXXM8O/rMPnTq0QscXrgMdWzT7g8I2wtWrl6me+mPUiMFo0+ovDOjfC21a/omuXdrh+vWrJEP7fhlQod6IAHegJ44fQ5tWTdG1UxsM7NcLLZs1waqVS+mdfz1aREQ4Nq5fg7+aNEC/vt3Ru0dntG3TFMeJhGppwOXj643hwwaiRfMm6NyxtSxXLtPdu3dAr9fjrtQyd0K3Lu0xcvggtG7VBIMH9YWHxzMqTw0NwB5hIJVzuzbN0L9fT7Sm8u7VvTMeuCeNwRYTGDZDxXZcRnixSf+ICJiM0eSS/aKiIsHlwsdIKh8moy+CJ+hB9RgJCn/iSpw7g2ceT+Xopmy5b1GlanXwBOWIiEg4OTmhMmlqUqdOA0NUFDZtWIfjR4+gdZuOyJghU5wHTZsuPdJnyEijLxONlsOpYfGApaUlUrqlpHvRL405ghCCXpwILF++CI8fP0Lbtp2QPHkK8uaZMYKOAAAORklEQVSxOR0S17/KbQIjEB4WhoUL5mDa1Amw0FnAx8cbYXSPs8UNdbHiJdGn/xD07TdYuq7deoHrNMdLniwFAgOiR/1Nm7fCxElTUb1mHRw7ehjr160Gm0FYjnIfj4CXpydmz5om24S+/YZg8NARcEuZEuNIa3z37h1JQMzShRByzt/0aZOQKlVqjBw1Dl2796Iy9cGkiWMREhxEGqEIOWG2ZMlSGDRkBPoNGIJ+VL5lypRDZGQkAgMDkI7aox69+mPs+En44X8/YvOmdTh16rg0UfqTlkdvYYm27Ttj/MQp+KHCT9i1azs2b94g/c15UccvHwFFdr78Mvpicshkx9PzOby9vaS2hrUw3EFwBvnIDhC4R2rjZUsWonr1Wqj4cyVE30fMFh4ejm1bNmHMqKFo1aIJNm5YjV8b/I5sOXIhvlHA5UsXKMxaNG/RDoWLFniNEMUIVicKgXcgwHUxA5Fv1koyYYkdnP1Sp0mH/1GH978KFfFjxZ+RPXtO+BPB+f6HCsiSNaskPr37DkSD335HiZKl6diQtJlp4U51nkeyQojYItX5ByAghMBNMnlfuHAOvzX8HT9XqYoy5b5HA2obeEC1aWNcgsGWw1MnT1B75C0HVaW+KYuffqqCKjToYpPVhYvnodMCQgjkzJUbFX+qhApEVrgs06XPINua/AUKkXa5Pyr8+BMKFyku42pII+T74qOJ7GSmZw10bTK3l/qmPOrWbYBUqVPjxrWrJFd1n0hEmyqtL7GwvtA8CSEQHBQEnrvg4ODwGonhbLP6csO6vylMMDp37RUz+uEugKJTAyGkpub4iaNYv2ENzp87Q2EsaBQWDH+y0wvBIVlStGN7+YrlS8kclhxN/mwGmKjKKqVONDhq/8EIWFlbo1adevimTBmqi1SXXpNgkvWaiQ8FwIH9e/Hs6RPUqFVPdo4arZbMH5aI3gS9DyEICw2Fi6ur1OzIeNGeav+BCPBgyv3BPVjodMibJz9YQ8ytQbr06eWPSd68eY2LJJZUE+7evY0MGTNKEsoDJZ2FBTJnyUptikaWGzcnXCbu7vdJA3cUd27dQlBgYIwMTpNNMSGhIUSafEhrsxP8+XTGjJnloIoHdGzuYhns+HNqNuWnTJNG1pMYQerki0cgvrf9i8+0ymDCIMCNgp2dHWxsbODx3COOSplzxA3HPVI1b9m8kUbEuUjDcweHDx0Ea4PYBs52dG4sbG1t0alzD6xbvxVr1m1FbRo1rVixRJoXWAbLYqelRu/ihfPYs3s7cuXOg0uk4Tly5CiNtP3w6NFDnDh2lNTUURxUOYXAeyPAnSIvlvi2CEIIsMlq48Y1YNNWzpy5ZecXE4f8+ZwnKfOE5TJlvwXL5XvKfTwCAf4Bsl2xs7eTeDPBsLS0ApsIg4OCyfT08n1nzQ6bmWxsbKG31MtE+Z6trR247WBSoyVTpRuZxw/+sx+dO7VB48b10bZNc5w4flSmw/J37tiG7l06oHGjuliyaB6+/e5/yJ+/YJy2RQiByIgI7N61g+5H4vvvKlD+DDJNtfvvEfgUKWg+hRAlI2kgwA1DCjc3OWfm1MnjCA0JoRGUTjYaWhrxajRaMKkJCQnCuXOn0adXNwwZ1BcXiaScOnVCTvx79PAheKTk7OKClClTS/VyjVp1kCKFGy5ePC+1PixHo9FASzKfE6kKJtv7gf170LtnFznZ0P3+PRw8uB/Dhg5AII3ShODxX9IoA/WUnwcB/gSZicy9e3fxHXV+zs7OcRLWkamDO76VRNK//b4CypSNngMSJ5C6+EAEBHiiK6/abORlg82x6f0WQrzQ6gjzXXltNBrB7RKTHLOHEAL8x9cuLm7o0q0XJk+dKef0NGrUBNevXcGY0cPBAy9uZ1xcXZCZTJSFChVBtmzZpbb5yOGDsl1jGSB5GqEBD+I2bVyHGjXroEDBgorcSnASz06RncRTVgmeU25YUqVMg7LlvsPRI4cwZtQw8Ofi/KnmlSuX0LVre3BDtXrtFqz4ez3mLliCqdPnoHixEtQZlJfnadKmwxHS9lwiuzxPEAwLDQN/xutHJiyeKMgTla9du4zlyxbD49lTfP/Dj9i6Yz8WL1tN8pZi0uQZyJY9J376uQomTZmJN5nTEhwslYFEiwB3gD4+3pg3dyZSpkgl6y4Tb/MD8Tl3hvzVFk+2b9O2I5ycnM3e6vixCBBjsSXNMRMeMxERQoAnh7NWxdHRiTQ8ujjS7e3tadAVjIjwcABgXgIeHPGn6g5OTjSwsgRr5Xg+TrHipfAHmcJ5EjJ/au7l5QUu62++KYvOXXpg0JCRGD5ynLw3c+YUSWaEEGCis2/vbvTs0Ql58+VH85btSLttC7UlLgQU2Ulc5ZXgubW0skSD3xqj1DdlsGDBHFSvVhH16lSVCwfu3bWdtD7JkSlzFjJj5ZQuS9bscKRGx9XFFVmyZCdNkBbr1v2Nhg3q4Pff6qDhb7UxcsRg8NcUv//RVKqIef2ewQP74Py5s+ARdbZsOaQsniyaJUsW2JEZLLlrcrLNZ5HanwQHRWUgUSEgBI37pXuRbXkuXlyAOkwhCTmvr/Pt9z9QPcsKJvp4sfH93r26wMraWnaO2Ugb8MJLHf4FAiaTUc69CQ+PwI3r1+jd1kmtjbv7PbCpsGDhIpKA8AcOPFCiYkNaGjzxfBwPj6dEUrTg+7wqu1anRYYMGSl8tOaHsyWEkOUYZTAQWbEh4mQBQ5QBRroWEBRfI7/MSpkylfyii/NjIg3T0SMH5fIC/AXpgEHDkD59eqgt8SGgSXxZVjlOSARMNPrKmi0bxk+YhmEjxqBixcrgLxqat2iDpcvXIFfuvERYomSjwh2EhV6PChV+lhoawARLK2vwVzAcPmWq1LKxat68NabPnC9VyCQepUuXQ9t2ncBfUPAIjeWYnaWVDWrWqofSZcsjymBMSChU2okQAa5HvLbK0SOHcO3aVdk5csfKczgCAgJkh8fr8KxcuRSOpElgkwVrcvhRhRC4TybU0aOGgjvgX3/9HT6kHdi7e6ecyMwdshCCgyr3EQiwVjhHztw0KMoKxn/P7h3458A+LF28AC40WOKvrNisPXXKeCxZPF+SoSJFi0vSMnf2DJw6eQxbN2/Eli0bUaZMeeTLlx/nzp6S8Y8fPyoHT8uXLsJBkvnD/yqQ6Tw5du3ahlkzp+LIoX+k/6qVy3Dt+lWUK/8ddDoL+XXY0CH94eX1HLWo3Xny+JGct3Pk8D/yIwwhVHl/RFEnSBRFdhIE9sSdKHcYvPYFa3j6DxyGocNGg9e/YaLz6qvPXzbUql0Pv1SrASEEBD16NtLUtGzdDiNGjpcj47btOyNHzlySIAkhULxkKbQhssPrm3BaFCXm39raBo0a/ynJE4/IYjzUiULgPRBgc8jKFUvBiwYuW7JAag4WL5qHnt07kzbhKnVwOrni99Url/FL1ZrgOm2ug2zyePTwgfwCSKfTYc3q5ejerSN69eoCNnFwR8xh3iMbKsgbEGANLw+GDKRt6dqlvZynFxAYiD59B5PWOAWYkB46eAC8UjuLyJuvAJo2a42z506jfdsWYCLK63p16NiNytICXt5eWEoEp0vHNmjXphkRmykoXKQY2rbrAktLK/BgatOmdehGJvh2bZth4cK5crDV5M/mLJ5I7X0wwbXQ64lgzZM/c8NlPXRwfzx98gQarVaGU7svHwFFdr78Mvoic8gaHu4EiJtASw0/j8r4Or7MmkijE/s+h+P4FnoLOSrja3YxYUykAyIVD4eJuffaCQV67d6nvKFkfY0I6C0twUR7xar12LB5Fw4cOomNdFy8dBXy5S8gNT25STu5cvVGsMmCSY25HnIHzCt4r9+4E/v2H8Pfa7dg9bot8otC/qowTZq04DBfI26f65kY7x8rVgKXz4KFyzFz9kIsXLwCvF4XtxFstuJV24cMHSWJCn8d+mfTFuAymTxlNhYsXonJ02YjT9580r9s2W+xeOnfmDJtDkaNmYhVazZjzLjJL7TGBlT8qTKWLFuD6bMWYNSoiVizditGj51EWuYcsizLkgZ5955DOHDwpIy7et1WrFu/DXMXLAebtQxRUZ8LGpXOv0RAkZ1/CaCKrhBQCCQeBIQQcHZ2IfNpenLpwASFO1CeOG9FJlYmNjY2NsiaNRt48itfx3461gaw9oHDc7zYjjvq2GHV+cchwNoxNlvlJTMUE1CnWJO/GeNURCr5a06WzuXD99zc3FC0RAkiKdnBS1vwffY3+xUpWgyly5RDhgwZYW1tLTV67K8lzUyyZMnBX2J9U6asXLOH/Wm4xd5yXlZqSs9cT2R5p0tP9SaNHKjJQGqXKBBQZOdfFpOKrhBQCCQ+BLgzfNXFfgrWIsS+jn3+ajzzdeww6vzfIcCYchmwe00SaX1fvSfDk+mLj/H6GY1SUxOfP4fndNjF58/34nMcT7nEg4AiO4mnrFROFQIKAYWAQkAh8CUj8MXm7a1kh9ms0WiCckkAg3hGS19srVUZUwgoBBQCSRABbqaVIyOj6d3u1erxVrLj5mKJXBnskTO9cl81BhnskDWtLTRUG4QAdDoNLJRLshhotUJ+NafVUD2wIKfqQtKtCxoBrgxcJz5pm6Dq1HvVKW6LtVQGVArQW2hha21BTqec9TswsNHBylJHVVfAvGnMJ/Eda3+bGrO6FMTUjvmV+4oxmNaxAEY0yw1rvRZ6cs6OVlAu6WJgb6sn4itgQw2Ki6oLSfpdsLWxAHe2XCdUm/D52wR+/+yoDIQQSJncBjkyOyN7JuXehUEOwihDGns5cMeLTfPiGO9BMC8ikIWgM+UgxNeNQ7yVQN1UCCQcAiplhYBCQCHwSRB4K9n5JCkoIQoBhYBCQCGgEFAIKAQSEIH/AwAA//82lX+pAAAABklEQVQDAFrHo3/DoofqAAAAAElFTkSuQmCC\" style=\"width: 356px; height: 425.205px;\" width=\"356\" height=\"425.205\"\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePeptide activation of the APC resensitizes resistant cells to drug treatment and reduces the expression of markers of drug resistance\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe next asked whether APC impairment is linked to cancer progression (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e) and whether APC activation via peptides C13-3 and C43-4 in aggressive cancer cells resensitized them to chemotherapy. Here, we used an MTT assay to show that the MCF7\u003csup\u003eRes\u003c/sup\u003e cells are indeed MDR, as the MCF7\u003csup\u003eRes\u003c/sup\u003e cells selected against TAM are less sensitive to DOX than the MCF7\u003csup\u003eSens\u003c/sup\u003e cells are (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The difference did not reach significance, but trends were consistently observed. We next treated MCF7\u003csup\u003eSens\u003c/sup\u003e and MCF7\u003csup\u003eRes\u003c/sup\u003e cells expressing pcDNA, C13-3 or C43-4 with 1 \u0026micro;M DOX for 48 hours and assessed cell viability via an MTT assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Survival was normalized to that of the pcDNA control, which revealed that, compared with MCF7\u003csup\u003eSens\u003c/sup\u003e cells, MCF7\u003csup\u003eRes\u003c/sup\u003e cells are more sensitive to DOX when the peptides are expressed. As above, the difference did not reach significance, but trends were consistently observed. We next assessed the viability of MDA-MB-231 cells expressing the constructs via the trypan blue dye exclusion method (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). We observed that the peptides alone reduced the viability of MDA-MB-231 cells, with the reduction in C43-4-expressing cells reaching significance. The MDA-MB-231 cells expressing the constructs were then treated with 1 \u0026micro;M DOX for 48 hours. C43-4, but not C13-3, significantly increased the killing of these cells by DOX (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). MDA-MB-231 cells were next subjected to DOX dose titration in 96-well plates, and survival was measured via an MTT assay. This experiment revealed that 231 cells were more sensitive to most of the DOX doses tested when they expressed C13-3 or C43-4, with C43-4 having the greatest effect (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). We previously reported that the killing of MDR cells coincided with a reduction in MDR protein markers, such as MDR-1 and BCRP (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e). We show here that C43-3, but not C13-3, modestly reduced both MDR-1 and BCRP protein levels in MDA-MB-231 cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF-\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH; uncropped blots are shown in \u003cb\u003eSupplemental Fig.\u0026nbsp;1C\u003c/b\u003e). The consistent decreases observed did not reach significance. These observations indicate that peptide-induced activation of the APC that reduces APC substrate levels resensitizes MDR cells to DOX.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eThe C13-3 and C43-4 peptides are expressed in 231\u003c/h2\u003e\u003cp\u003eTo determine where the peptides were expressed in cells, we used immunofluorescence microscopy to visualize the localization of the HA-tagged peptides. Antibodies against HA did not signal in pcDNA3.1 control cells but did signal in C13-3- and C43-4-expressing cells. In MDA-MB-231 cells, both peptides predominantly localized to perinuclear structures, with some nuclear punctate staining (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Notably, these constructs did not contain the NLS that was part of the original yeast construct, as preliminary studies using MDA-MB-231 cells revealed that constructs lacking the NLS were more active at reducing APC substrate levels (data not shown). Nevertheless, nuclear staining, where the APC is localized (\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e), was observed, and this appeared sufficient to promote APC activity. We next assessed peptide mRNA expression as a measure of gene expression. mRNA was extracted from MDA-MB-231 cells, converted to cDNA and used in PCRs with primers designed to amplify the thioredoxin backbone from which the peptide is expressed. As a control, plasmid DNA was used as a template in the PCRs. Primers against the EFEMP2 gene were also used as loading controls. Our observations revealed that the peptides were indeed expressed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eThe peptides inhibited MDA-MB-231 cell migration\u003c/h2\u003e\u003cp\u003eTo investigate whether activation of the APC interferes with cell migration, we performed wound healing assays with metastatic MDA-MB-231 cells expressing C13-3, C43-4 or pcDNA3.1. For this assay, a scratch was made in a lawn of confluent cells. The plate was left to incubate, and over a period of 24 hours, MDA-MB-231 cells with stably integrated pcDNA3.1 migrated into the gap and filled the void (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, top panels; a representative experiment is shown from 3 biological replicates). The cells stably transfected with C13-3 or C43-4 were also allowed to migrate back into the wound over a 24-hour period. Our results revealed that while MDA-MB-231 cells stably transfected with pcDNA3.1 almost fully migrated into the void space (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, top panel), cells expressing C43-4 were almost entirely devoid of migratory activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, bottom panel), whereas C13-3 clearly slowed cell migration (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, middle panel). The quantification of cell migration in the presence or absence of 0.5 \u0026micro;M DOX suggested that the peptides work additively with DOX (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). This effect was observed with a variety of different DOX doses (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Finally, to gain further evidence that APC activation inhibits cell migration, we performed experiments in the presence of 10 or 20 \u0026micro;M M2-1, an indirect APC activator (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). We observed that M2I-1 alone inhibited MDA-MB-231 cell migration and worked additively with the peptides (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Taken together, these observations indicate that the peptides potentially act in a pathway that differs from those impacted by DOX and M2I-1.\u003c/p\u003e\u003cp\u003e\u003cb\u003eC13-3 and C43-4 increase the mitotic index of cells, inducing mitotic catastrophe, DNA damage and apoptosis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOne hypothesis to explain how APC activation could be anti-proliferative for cancer cells is that APC activation pushes aggressive cancer cells with high loads of chromosome instability (CIN) into premature mitosis, which may be unsustainable, leading to death (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). We previously tested this hypothesis on MCF7\u003csup\u003eRes\u003c/sup\u003e cells arrested in mitosis in the presence or absence of M2I-1 and then released into the cell cycle in fresh media (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). We observed that cells progressed more rapidly through mitosis when treated with M2I-1, which correlated with cell death. To test whether the peptides induced mitotic errors, we counted the number of mitotic and abnormal cells in populations of DAPI-stained MDA-MB-231 cells. We observed that the peptides slightly increased the number of mitotic cells from approximately 3% in control cells to 4% in peptide-expressing cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). We also observed that there was a greater number of mitotic catastrophe events in cells expressing the peptides (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), which consisted of a variety of aberrant cells, including tridirectional anaphases and micronuclei formation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). We predict that the killing of cells that enter mitosis might be due to increased chromosomal damage resulting from dysregulated mitosis. To assess this possibility, we prepared lysates from pcDNA3.1-, C13-3- and C43-4-expressing cells and measured the level of gH2AX, a measure of DNA damage (\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e). The results indicated that gH2AX is elevated in C43-4-expressing cells in particular (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, top panel; quantitated in lower panel; the uncropped blot is shown in \u003cb\u003eSupplemental Fig.\u0026nbsp;1D\u003c/b\u003e), suggesting that there is more DNA damage in these cells. To test this hypothesis, we examined markers of apoptosis in these cells. We observed that the level of PARP cleavage (cPARP), a sign of commitment to apoptosis (\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e), was elevated in peptide-expressing cells treated with DOX (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, top panel quantitated in the lower panel; the uncropped blot is shown in \u003cb\u003eSupplemental Fig.\u0026nbsp;1D\u003c/b\u003e). Consistent with these findings, caspase 3 and 8 activity was also elevated in peptide-expressing cells (caspase 3 activity is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE; caspase 8 activity is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). These observations provide evidence that the peptides induce premature entry into mitosis, causing increased DNA damage and apoptosis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eC43-4, but not C13-3, inhibits the growth of MDA-MB-231 cells in a mouse xenograft model\u003c/h2\u003e\u003cp\u003eTo test whether the C13-3 and C43-4 peptides impact cancer growth \u003cem\u003ein vivo\u003c/em\u003e, we subcutaneously injected MDA-MB-231 cells stably expressing pcDNA3.1, C13-3 or C43-4 into the mammary fat pads of female NOD \u003cem\u003eSCID\u003c/em\u003e gamma (NSG) mice. Untransfected cells were injected as a control. Measurements of tumors via calipers began once tumor growth was obvious at 4 weeks post injection and continued weekly. We observed that C43-4-expressing tumors were smaller (455.3 mm\u003csup\u003e3\u003c/sup\u003e final volume) than pcDNA3.1-expressing tumors (834.5 mm\u003csup\u003e3\u003c/sup\u003e), C13-3-expressing tumors (959.5 mm\u003csup\u003e3\u003c/sup\u003e) and untransfected control tumors (996.5 mm\u003csup\u003e3\u003c/sup\u003e), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA and quantitated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe next asked whether the peptides could resensitize cells to DOX treatment \u003cem\u003ein vivo\u003c/em\u003e, as observed \u003cem\u003ein vitro\u003c/em\u003e (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, D, E). The recommended cumulative DOX dose for tumor-bearing mice is 20 mg/kg (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e). However, to determine the lowest dose of DOX that reduced MDA-MB-231 tumor growth in untransfected cells, DOX was injected 6 weeks after cell injection at cumulative doses of 5, 7.5 and 10 mg/kg. The control groups received intraperitoneal injections of PBS. Intraperitoneal DOX injections were performed every 2 days for 20 days at 1/10 the concentration to achieve the desired cumulative dose. As shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD, all three doses reduced tumor growth to the same extent, with no significant differences observed. Therefore, we combined peptide expression with a 5 mg/kg cumulative dose of DOX. MDA-MB-231 cells stably expressing pcDNA3.1, C13-3 or C43-4 were injected into the mammary fat pads of female mice as described above. Four weeks postinjection, tumor measurements began, with DOX dosing beginning at 6 weeks postinjection, with injections every 2 days for 20 days to reach a cumulative dose of 5 mg/kg. We observed that the 5 mg/kg dose partially reduced the growth of pcDNA3.1 and C13-3 tumors after 8 weeks, with no differences between the control and C13-3 groups (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). C43-4 reduced the growth of MDA-MB-231 cells, as observed above, and the addition of DOX significantly reduced their growth. These results indicate that while C13-3 impacts cancer cell growth \u003cem\u003ein vitro\u003c/em\u003e, it does not influence the growth of the same cells \u003cem\u003ein vivo\u003c/em\u003e. However, the C43-4 peptide continued to synergize with DOX \u003cem\u003ein vivo\u003c/em\u003e as it did \u003cem\u003ein vitro\u003c/em\u003e.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cb\u003eAPC activation reduced MDA-MB-231 cell growth\u003c/b\u003e \u003cb\u003ein vivo\u003c/b\u003e, \u003cb\u003ewhereas APC inhibition increased growth\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe next asked whether the C43-4-mediated reduction in tumor growth in our mouse xenograft model was dependent on the APC. As observed with the wound healing assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), chemical activation of the APC with M2I-1 reduced wound healing, with the combination of M2I-1 and C43-4 reducing it further. These findings suggested that M2I-1 and C43-4 activated the APC via separate mechanisms. Here, the mice were injected with MDA-MB-231 cells expressing pcDNA3.1 or C43-4 as described above (C13-3-expressing cells were not used in this experiment since C13-3 did not impact tumor growth \u003cem\u003ein vivo\u003c/em\u003e). At 6 weeks postinjection, a single intraperitoneal injection of 5, 10 or 25 mg/kg M2I-1 was given. Tumor measurement was performed daily following the M2I-1 dose for 8 days. The control pcDNA3.1-expressing tumor volume following the 25 mg/kg dose was 194.9 mm\u003csup\u003e3\u003c/sup\u003e on day 8, whereas the tumor volume was 341.3 mm\u003csup\u003e3\u003c/sup\u003e in untreated control tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC), indicating that M2I-1 did indeed slow tumor growth, similar to that of C43-4. In mice growing C43-4-expressing cells, the average tumor volume of untreated mice was 268.2 mm\u003csup\u003e3\u003c/sup\u003e after 8 days, whereas the average tumor volume was 136.8 mm\u003csup\u003e3\u003c/sup\u003e 8 days after receiving a dose of 25 mg/kg M2I-1 (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). As observed with the wound healing assay, C43-4 and M2I-1 combined to slow tumor growth even more than either alone did, providing further evidence that M2I-1 and C43-4 use different mechanisms to activate the APC.\u003c/p\u003e\u003cp\u003eFinally, to further validate that APC activation reduces tumor growth, we asked whether APC inhibition would increase tumor growth. Mice growing pcDNA3.1- and C43-4-expressing cells received intraperitoneal injections of cumulative doses of 1 and 10 mg/kg APCIN weekly starting at 6 weeks post cell injection. The mice were injected with 1/10 the APCIN dose every 2 days for 20 days. We observed that the control mice that received 1 mg/kg APCIN had a final average tumor volume of 1061.0 mm\u003csup\u003e3\u003c/sup\u003e after 8 weeks, and those that received 10 mg/kg APCIN had a final average tumor volume of 1167.0 mm\u003csup\u003e3\u003c/sup\u003e, which was greater than that of the tumors derived from the untreated mice, which was 937.1 mm\u003csup\u003e3\u003c/sup\u003e. While both volumes were larger than those of the untreated tumors, ANOVA revealed that the differences were not significant. The results obtained with C43-4-expressing MDA-MB-231 cells from mice were quite different. C43-4-expressing tumors remained smaller when treated with 1 or 10 mg/kg APCIN, with tumor volumes of 326.2 mm\u003csup\u003e3\u003c/sup\u003e and 346.7 mm\u003csup\u003e3\u003c/sup\u003e, respectively, compared to the untreated tumor volume of 305.0 mm\u003csup\u003e3\u003c/sup\u003e (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). The differences were not significant, but the differences in growth between empty vector- and C43-4-expressing tumors were significant.\u003c/p\u003e\u003cp\u003eTaken together, our results strongly support the hypothesis that APC activation plays a role in stalling tumor growth both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e. We identified a small peptide discovered via a 2-hybrid screen using the yeast APC subunit Apc10 as bait that resensitizes MDR breast cancer cells to drug treatment in both \u003cem\u003ein vitro\u003c/em\u003e cell culture and \u003cem\u003ein vivo\u003c/em\u003e mouse models.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eAs the mean lifespan of humans increases, so does the incidence of cancer. Cancer treatment has improved over the years, with many patients now experiencing extensive periods of remission. However, in many cases, the cancer recurs later in life, with the only recourse being more toxic therapy or palliative care (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). We previously reported that the activation of the APC via the small chemical SAC inhibitor Mad2 inhibitor-1 (M2I-1), a chemical that disrupts the binding of CDC20 to the SAC (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), prematurely activates the APC to resensitize MDR cancer cells to therapy (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). The notion that APC activation improves cancer outcomes is gaining traction, as we and others have shown that APC activation, predominantly that of APC\u003csup\u003eCDH1\u003c/sup\u003e, promotes cancer cell killing (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan additionalcitationids=\"CR65 CR66\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). For example, Rev7, a CDH1 inhibitor, results in a poor prognosis for many cancers when it is overexpressed, with better outcomes when it is decreased and when it is combined with platinum-based therapies (\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e). REV7 is a dual-function protein that is required for translesion synthesis DNA repair but also behaves similarly to proteins composing the Spindle Assembly Checkpoint (SAC) (\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e). REV7 overexpression results in slowed mitotic progression, impaired APC function, elevated APC substrate levels, and increased mitotic slippage upon nocodazole treatment in triple-negative breast cancer cells. REV7 is an APC substrate that is stabilized in TNBC cells ( 99). Several other reports also support that inhibition of the SAC activates the APC, which can resensitize TNBC to therapy (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSAC inhibitors are currently in clinical trials for cancer treatment (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e). In fact, key SAC components (such as MPS1, an APC substrate) that are overexpressed in aggressive cancer cells are being targeted (\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e). However, the SAC is involved in many processes that regulate chromosome segregation in both mitotic and meiotic cells (\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e, \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e). For example, a BioGRID search for proteins associated with the SAC component MPS1 revealed a network composed of 637 interactors (nodes) and 10,117 edges (unpublished). Therefore, the inhibition of the SAC may have several side effects. In this report, we describe the discovery of novel yeast lifespan-enhancing peptides, which were discovered via a yeast 2-hybrid screen where the APC subunit Apc10 was used as bait that possessed conserved function in MDR breast cancer cells by resensitizing them to therapy \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eWe arrived at these conclusions by first cloning 7 of the small peptides recovered in the yeast 2-hybrid screen into the pcDNA3.1 vector and stably expressing them in human MDA-MB-231 and matched MCF7\u003csup\u003eSens\u003c/sup\u003e and MCF7\u003csup\u003eRes\u003c/sup\u003e breast cancer cells. The selected peptides rescued the short replicative lifespan (RLS; 105, 106) of the \u003cem\u003eapc5\u003c/em\u003e\u003csup\u003e\u003cem\u003ets\u003c/em\u003e\u003c/sup\u003e mutant yeast (Harris et al., unpublished). In human cells, as a measure of direct APC activation, we asked whether the peptides could reduce the asynchronous levels of APC substrates, as reduced substrate levels suggest that the APC increases the turnover of its substrates. Figures\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-D shows that peptides C13-3 and C43-4 consistently reduced the protein levels of the substrates tested. These findings indicate that these peptides have conserved activity and are therefore the focus of this study. To assess APC activation when C13-3 and C43-4 were applied to MDA-MB-231 cells, we determined the levels of APC1 phosphorylated at Ser355, a marker of APC activation (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e), in peptide-treated cells. Western blotting with APC1\u003csup\u003eS355ph\u003c/sup\u003e antibodies revealed that the level of phosphorylated APC1 was elevated in peptide-treated cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE), suggesting that C13-3 and C43-4 indeed activate the APC. Finally, to test whether the peptides increased the direct E3 activity of the APC, we performed \u003cem\u003ein vitro\u003c/em\u003e Ub assays using APC purified from stably transfected MCF7\u003csup\u003eSens\u003c/sup\u003e and MCF7\u003csup\u003eRes\u003c/sup\u003e cells. The results show that APC E3 activity is reduced in MCF7\u003csup\u003eRes\u003c/sup\u003e cells and that the peptides can increase E3 activity in MCF7\u003csup\u003eRes\u003c/sup\u003e cells, with C43-4 being the most potent (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH). Taken together, our data strongly support the hypothesis that the peptides indeed activate the APC, particularly in MCF7\u003csup\u003eRes\u003c/sup\u003e cells.\u003c/p\u003e\u003cp\u003ePrevious work from our group using the APC chemical activator M2I-1 revealed that APC activation in human and canine MDR cells resulted in the killing of these cells (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). We showed here that using the C43-4 peptide to activate the APC in MCF7\u003csup\u003eRes\u003c/sup\u003e and MDA-MB-231 breast cancer cells also resulted in slowed cell proliferation when it was combined with 1 \u0026micro;M DOX but that C13-3 was not as effective, particularly in MDA-MB-231 cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB-E). Since neither C13-3 nor C43-4 slowed the proliferation of MCF7\u003csup\u003eSens\u003c/sup\u003e cells in the presence of 1 \u0026micro;M DOX, this suggested that C43-4 may specifically impact cells with greater DNA damage, which is often observed in aggressive MDR cancer cells. We also observed a trend toward a reduction in the MDR markers BCRP and MDR-1 when C43-4 was used (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF-H). This finding is consistent with the finding that C43-4 renders MDR cells sensitive to drug treatment.\u003c/p\u003e\u003cp\u003eThe C43-4 peptide, in particular, appears to have APC-activating ability and to resensitize MDR cells to DOX. This finding is consistent with studies showing that the APC\u003csup\u003eCDH1\u003c/sup\u003e complex has anticancer activity (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e). The APC\u003csup\u003eCDH1\u003c/sup\u003e complex works in both replicating and differentiated cells (\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e, \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e). Our preliminary data in yeast revealed that C43-4 increased the lifespan of wild-type stationary phase cells and the short lifespan of dividing APC mutant cells. Interestingly, C13-3 only extended the lifespan of dividing APC mutants but not the lifespan of stationary-phase wild-type cells. M2I-1, which specifically releases CDC20 from the SAC to prematurely activate the APC, increases the lifespan of only dividing yeast cells but not that of cells in the stationary phase (Harris et al., unpublished). Therefore, C43-4 appears to possess the unique ability to activate the APC\u003csup\u003eCDH1\u003c/sup\u003e complex to preserve genomic stability and defend against cancer progression.\u003c/p\u003e\u003cp\u003eWe tested whether C13-3 and C43-4 were able to reverse additional cancer cell phenotypes. We show here that the peptides inhibited the mobility of aggressive and metastatic MDA-MB-231 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The peptides worked additively with DOX, which also inhibited cell mobility. Interestingly, the SAC inhibitor/APC activator M2I-1 also inhibited cell mobility, and the peptides worked additively with it. These findings indicate that inhibiting the SAC, thereby releasing CDC20 prematurely to activate the APC, works differently from how the peptides work. Consistent with peptides exhibiting anticancer potential, both C13-3 and C43-4 induced mitotic progression and mitotic catastrophe (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). In our previously published work, we showed that activation of the APC via M2I-1 increased the passage rate through mitosis, increased the degradation of mitotic APC substrates, and increased the killing of resistant cells by DOX (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e). This finding is consistent with a model in which aggressive and MDR cancer cells progress slowly through mitosis to provide time to repair enough DNA damage to avoid mitotic catastrophe, whereas pushing MDR cells rapidly through mitosis may block the ability to repair enough damage, leading to elevated levels of mitotic catastrophe (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). Consistent with the peptides inducing mitotic catastrophe, we also observed that the peptides increased DNA damage, as indicated by elevated levels of gH2AX, and induced apoptosis, as indicated by increased PARP cleavage and increased caspase 3 and 8 activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF).\u003c/p\u003e\u003cp\u003eNotably, C13-3 and C43-4 appear to have evolutionarily conserved functions from yeast to humans in \u003cem\u003ein vitro\u003c/em\u003e cell culture. Not all the peptides cloned into the human pcDNA expression vector were able to consistently reduce APC substrate levels in human breast cancer cells. To further test the conserved nature of the peptides, we injected MDA-MB-231 cells stably expressing pcDNA or pcDNA vectors expressing C13-3 or C43-4 into the mammary fat pads of female NOD \u003cem\u003eSCID\u003c/em\u003e gamma (NSG) mice. As shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB, C43-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e slowed the growth of MDA-MB-231 cells in mice, whereas C13-3-expressing cells consistently grew at the same rate as the empty vector and untransfected controls. DOX slowed the growth of MDA-MB-231 cells in mice and decreased growth further when it was combined with C43-4, but not with C13-3. M2I-1 also slowed the growth of MDA-MB-231 cells in mice and worked additively with C43-4 (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC-\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). This provides further evidence that M2I-1 and C43-4 work independently of one another to activate the APC. Finally, we showed that, compared with M2I-1 and C43-4, the inhibition of APC had the opposite effect on tumor growth in mice. Strikingly, our results revealed that APCIN not only accelerated tumor growth in a dose-dependent manner, but was reversed by C43-4. These findings provide very strong evidence supporting the role of APC activity in suppressing the growth of MDR cancer cells both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e. This finding also suggests that C43-4 may work in a CDC20-independent manner since APCIN is thought to bind to CDC20 to disrupt the interaction between CDC20 and its substrates. It is also possible that C43-4 may inhibit the interaction between CDC20 and APCIN. Further investigations are ongoing to test this idea.\u003c/p\u003e\u003cp\u003eIn conclusion, we aimed to test whether the peptides we discovered in a yeast 2-hybrid screen in which the yeast Apc10 subunit was used as bait had conserved functions in human cells. Two of the peptides exhibited conserved APC-activating functions in \u003cem\u003ein vitro\u003c/em\u003e cell culture experiments, and one of the peptides continued to have activity in an \u003cem\u003ein vivo\u003c/em\u003e mouse xenograft model. These results support the use of the C43-4 peptide to search for small chemicals that directly bind the APC to potentially activate the cell protective APC\u003csup\u003eCDH1\u003c/sup\u003e complex and increase cell health. These results also support the use of yeast to screen for peptides and chemicals that can be used as longevity and anticancer therapeutics in human cells.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eETHICAL APPROVAL AND CONSENT TO PARTICIPATE\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eThe authors declare that they have no potential conflicts of interest.\u003c/p\u003e\u003ch2\u003eCONSENT FOR PUBLICATION\u003c/h2\u003e\u003cp\u003eAll authors consent to publication.\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCOMPETING INTERESTS\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFUNDING\u003c/h2\u003e\u003cp\u003eThis work was supported by grants to T.A.A.H. and T.G.A. from the Canadian Foundation for Innovation (CFI) and the Canadian Breast Cancer Foundation (CBCF). T.A.A.H. was awarded a Natural Sciences and Engineering Research Council (NSERC) of Canada Discovery grant to investigate APC activating peptides. G.M. was supported by an NSERC MSc award and S.V. was supported by an NSERC summer-student award.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eC.V. contributed Figures 1 (except E), 2E-H, and 5, and helped edit the final draft. G.M. contributed Figures 3, 4, 6 and 7. S.V. contributed Figure 1E. M.L. contributed Figures 2A-D. G.F.D. trained and supervised the mouse work by G.M. T.G.A. cowrote the grants for this work, helped design experiments, supervised C.V. and S.V., and edited the final drafts of the paper. T.A.A.H. wrote the grants supporting this work, planned and designed the experiments, wrote and edited the manuscript, and supervised G.M., M.L. and G.F.D.\u003c/p\u003e\u003ch2\u003eACKNOWLEDGEMENTS\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eNo datasets were generated or analyzed during the current study. Data are however available from the authors upon reasonable request. Please contact Troy Harkness at [email protected] if you have a request for data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMubarik, S., et al. Evaluation of lifestyle risk factor differences in global patterns of breast cancer mortality and DALYs during 1990-2017 using hierarchical age-period-cohort analysis. \u003cem\u003eEnviron. Sci Pollut. Res. Int\u003c/em\u003e. \u003cstrong\u003e28\u003c/strong\u003e, 49864-49876 (2021).\u003c/li\u003e\n\u003cli\u003eAhmad, A. 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APC/C-Cdh1: from cell cycle to cellular differentiation and genomic integrity. \u003cem\u003eCell Cycle\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 3904-12 (2010).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7309461/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7309461/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe primary care of cancer patients involves improving their outcomes, resulting in longer remission periods and, in some cases, cures. However, many cancers eventually return to a state that is too resistant to therapy. Once cancers become multidrug resistant (MDR) and aggressive, palliative care or more toxic therapies are the remaining options for this growing population of cancer survivors. New approaches to resensitize MDR malignancies to nontoxic therapies are critically important to improve patient outcomes. Previously, we reported that activation of the Anaphase Promoting Complex (APC) resensitized recurrent MDR malignancies \u003cem\u003ein vitro\u003c/em\u003e, independent of cancer type, chemotherapy exposure, or species. Specifically, the indirect APC chemical activator, M2I-1, resensitized MDR canine lymphoma cells and human breast cancer cells to first-line therapy. In this study, we applied small peptides that were discovered via a yeast 2-hybrid screen for peptides that interact with the Apc10 APC subunit as direct activators of the APC. The tested peptides indeed increased APC activity, as indicated by reduced APC protein substrate levels, increased (activating) phosphorylation of APC1\u003csup\u003eS355\u003c/sup\u003e, and increased E3 ligase activity, as determined via \u003cem\u003ein vitro\u003c/em\u003e ubiquitination assays. One peptide significantly restored chemosensitivity to the MDA-MB-231 breast cancer cell line \u003cem\u003ein vitro\u003c/em\u003e and in an \u003cem\u003ein vivo\u003c/em\u003e mouse model. The peptides induced mitotic catastrophe, increased DNA damage, and activated apoptotic pathways. Taken together, our results demonstrate that direct activation of the APC via a small APC-activating peptide has anticancer effects both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e in MDR breast cancer cells, suggesting the potential for targeted treatment to improve patient outcomes.\u003c/p\u003e","manuscriptTitle":"Restoration of chemosensitivity to drug resistant breast cancer cells through peptide activation of Anaphase Promoting Complex","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-25 11:40:57","doi":"10.21203/rs.3.rs-7309461/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"033c83b0-2e7e-4713-b47b-4b553ab47b9a","owner":[],"postedDate":"September 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55143002,"name":"Biological sciences/Cancer"},{"id":55143003,"name":"Biological sciences/Drug discovery"},{"id":55143004,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2026-02-09T17:53:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-25 11:40:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7309461","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7309461","identity":"rs-7309461","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}