Study Population
The colonies of Cx. quinquefasciatus (Cidade Nova-Ananindeua/Pará) were maintained in conditioned insectary, with temperature of 28ºC ± 1ºC, humidity of 80% ± 10% and light/dark cycles of 12/12 hours, according to Vogels et al. [19] protocol.
The egg rafts were created in basins containing 700 mL of distilled water and supplemented with crushed and sterilized fish food, with 12/12 light and dark photoperiod, average temperature of 28ºC ± 1ºC. As the pupae evolved, they were transferred to a transparent polypropylene container (Firstlab®) containing 50 mL of distilled water, then they were placed in entomological cages with 30 cm3 of dimensions. The winged forms were maintained with cotton wool soaked in 10% sugar solution ad libitum, according to the protocol established by SILVA et al. [47].
Viral Strain
The BEAN854747 strain of WNV was originally isolated from a sample of the Central Nervous System (CNS) of an adult male horse from the city of Pedra Grande, state of Espírito Santo, Brazil. The isolation of the strain was carried out by the Evandro Chagas Institute (IEC), Ananindeua/Pará. The virus was isolated using the Viral Isolation technique on C6/36 cells and the Indirect Immunofluorescence technique, which demonstrated approximately 75% of positive cells for Flavivirus and WNV antibodies. Already in horse brain sample, the strain was identified by RT-qPCR [12].
Viral Stock Preparation
The viral stocks were prepared in Vero cells from African green monkey kidney (Chlorocebus aethiops) (ATCC® CCL-81 ™), in which 150µL of virus was inoculated in a polystyrene cell culture flask (Sarstedt®) with a capacity of 21 mL to 55 mL, then the bottle was incubated at a 37ºC in an incubator oven at 5% CO2 for one hour for adsorption, shaking the flask every 15 minutes. After adsorption, 25mL of maintenance culture medium 199 (GIBCO) containing 2% fetal bovine serum, penicillin (100 UI/mL) and streptomycin (100 µg/mL) are added. Infected cells are maintained in an incubator oven and monitored daily with an inverted microscope (ZEISS) to assess the occurrence of cytopathic effects for a period of five to six days. After the identification of the cytopathic effects in 90% of the monolayer, the flask is shaken to release the monolayer from the wall, 10% of fetal bovine serum is added and 2mL of the culture supernatant was aliquoted in tubes for cryogenic freezing KMA (Mylabor®), keeping them in a freezer -70ºC until the moment of use [48,49].
The viral stock of WNV was titrated, obtaining 1.4x108 PFU/mL of titer.
Mosquitoes Infection
After the emergence of adulthood, approximately 106 females with five to seven days of life were separated and deprived of sugar for 24 hours before feeding an infected blood meal. The oral infection was carried out with the assist of an artificial glass feeder, in which the blood supply area for mosquitoes is surrounded by a bovine liver peritoneum membrane acquired from a fridge. The artificial feeder was filled with 2 mL of defibrinated goose blood acquired from the IEC vivarium and 2 mL of the WNV stocks. The blood was constantly kept at 37ºC in a water bath (Digital Bath NI 1255-25L) (Fig. 3A). The females were exposed to the infected blood meal for 60 minutes. The mosquito control group was composed of uninfected females belonging to the same generation used in the infection, according to the protocols defined by Salazar et al. [50], Serrão [51], Goenaga et al. [52] and Vogels et al. [19].
After the period of exposure to the infectious blood meal, a total of 46 engorged females were obtained, which were separated and transferred to an entomological cage. Forty-eight hours after the infective blood feeding, a transparent polypropylene container (Firstlab®) containing 15 mL of distilled water and organic matter was deposited inside the cages for oviposition, remaining inside the cage for a period of up to seven days after infective feeding, as proposed by Pesko & Mores [34].
Mosquito processing
The segmentation of mosquitoes and the saliva extraction were performed after the 7th, 14th and 21st day of post-infection (pi) with legs and wings, body and saliva being separated individually. The segmentation of the body, legs and wings was performed according to the technique described by Consoli & Oliveira [53] in which the infected females were cooled to inactivity in an ice bath, then deposited from the belly upwards on a sterilized microscope slide (Kolplast ®) being removed first, with the aid of entomological forceps, the wings and legs. Then, the saliva extraction procedure was performed according to the adapted technique described by Castro et al. [54] and Nuñez et al. [55], in which the female's proboscis was inserted into a 10µL polypropylene micropipette tip (Axygen®) containing 5µL of fetal bovine serum (GIBCO) and waiting for 30 minutes for salivation (Fig. 3B). After, the medium containing the saliva was transferred to epperdorf tubes (Sarstedt®) containing 45µL of Leibowitz L-15 medium (GIBCO), then the saliva was immediately stored in a freezer at -70ºC.
After the saliva extraction, the body, legs and wings was transferred to epperdorf tubes (Sarstedt®) and 1000µL of Dulbecco's Phosphate-Buffered Saline (DPBS) (Life technologies, Carlsbad, CA, USA) containing 2% penicillin and streptomycin, 1% of fungizone and 5% of fetal bovine serum was added, as well as a 3mm stainless steel bead to perform the maceration procedure in TissueLyser II (Qiagen, Hilden, Germany), at a speed of 25 turns (Hz) for one minute, followed by the storage of the samples in a freezer -70ºC for a minimum period of 24 hours, according to Vazeille et al. [56] protocol.
Viral Isolation
The attempts of viral isolation in cell culture were carried out according to the Gubler et al. [57] protocol. After the process of maceration and incubation of the samples in a freezer -70ºC, the eppendorfs were centrifuged (Hettich® model Mikro 220R) at a speed of 10.000 rotations per minute (rpm) for 10 minutes at a temperature of 4ºC, then 100µL of the macerate supernatant was collected and inoculated into the monolayer of Aedes albopictus C6/36 cell culture (ATCC: CRL-1660 ) grown in tubes 16 x 125mm for cell culture (TPP®), after inoculation the tubes were maintained in an incubator at a 28◦C for one hour for adsorption and homogenized every 15 minutes. Then, based on Beaty et al. [49] protocol, 1.5 mL of Leibowitz L-15 maintenance medium (GIBCO) prepared with 2.95% tryptose phosphate, non-essential amino acids, penicillin, streptomycin and 2% fetal bovine serum was added to monolayer.
The inoculated C6/36 cells were stored in an oven (NAPCO) with 5% CO2 at 28ºC (± 2ºC) and evaluated daily under an inverted optical microscope (OLYMPUS model CK-2) for seven days to check the occurrence of a cytopathic effect. Positive and negative controls were also used to provide greater reliability to the test.
Indirect Immunofluorescence Test (IFI)
The Indirect Immunofluorescence Test (IF) was performed according to the Gubler et al. [57] protocol. 25µL of the inoculated sample was added in C6/36 cell culture in each hole of the immunofluorescence assay slide, waiting 10 minutes, then, remove the sample excess from the slide and fixed with acetone for 10 minutes at -20ºC, followed by acetone (propanone) PA for 10 minutes at -20ºC. After that, the slides were immersed in bovine albumin solution (3% and 1% concentrations) and in PBS (pH 7.4) for 10 minutes at 25ºC and 25µL of the polyclonal antibody, with West Nile hyperimmune ascitic fluid (in house), was added and the slides were packaged in a humid chamber in an oven (NAPCO) for 30 minutes at 37ºC. Subsequently, the sample was washed in phosphate-buffered saline solution (PBS) pH 7.4 for 10 minutes, then the slides were briefly washed with distilled water and 50 µL of the conjugated anti-mouse antibody (Cappel) diluted was added at 1:900 to each slide orifice, the conjugated anti-mouse was marked with fluorochrome allowing the visualization of positive samples and Evans Blues (0.5%) was used as a dye. Then, the slides were conditioned again in a humid chamber in the oven for 30 minutes at 37ºC and 5% CO2, repeating the washing in PBS for 10 minutes, finishing the preparation of the samples with 50µL of buffered glycerin (pH 8.2) in each slide orifice and fixed the coverslip for observation under a fluorescence microscope (Olympus BX51, UPlanFL N 20X / 0.5 lens and WB and U-25nd filters).
Cells inoculated with samples of head, body and saliva from uninfected mosquitoes were used as negative controls.
The images of the samples were acquired in 200X magnification in the fluorescence microscope with Canon PowerShot G6 camera (Canon, Tokyo, Japan).
Viral Titration
Viral titration was performed on the saliva, body, legs and wings samples, as well as the viral stocks used in the infection process.
Viral titration was carried out according to Dulbecco & Vogt [58] protocol, in which a 96-well cell culture plate (Kasvi®) divided in half to allow a 10-fold serial dilution of the samples (10-1 to 10-6) in PBS diluent with 0.75% bovine, penicillin (100 IU/mL), streptomycin (100 µg/mL) and 2 % fetal bovine serum. 180µL of maintenance culture medium 199 (GIBCO) was added to the plate, then 20µL of the “-1” dilution was added to the orifice identified as “-1” and the mixture was homogenized and 20µL was aspirated from "-1" and transfers to the next hole identified by "-2", repeating the procedure until the last dilution of "-6".
After the sample dilution process, in a six-well cell culture plate (Kasvi®) containing monolayer of cultured Vero cells (Cercopithecus aethiops) (ATCC® CCL-81 ™), each hole was identified from “-1” to “- 6” according to the dilution performed. Then, the culture medium 199 (GIBCO) used to grow VERO cells was replaced and 100µL of the diluted viral sample was added to each well according to the identification. Then, the plate was incubated in an oven (NAPCO) at 37ºC and 5% CO2 for one hour, in which, every 15 minutes the plate was homogenized to increase viral adsorption.
After viral adsorption 3 mL of carboxymethylcellulose (CMC, 3% in 199 medium) supplemented with 5% fetal bovine serum, penicillin (100UI/mL) and streptomycin (100µg/mL) were added to each orifice, followed by incubation of the plate in an oven at 37ºC for five days. After that period, the cells were fixed with 3 mL of 10% formaldehyde in water and the plate was incubated in the oven for four to seven hours or overnight. Subsequently, the plate was washed until the product is completely removed and 3 mL of 0.1% Violet Crystal dye were added, waiting at room temperature for a period of 24 hours.
Viral titration was determined by multiplying the number of plaques obtained from a given dilution, by the dilution factor (Eq. 1), with the result being expressed in Plaque Forming Units per Milliliter (PFU/mL), according to the mathematical calculation established by Guerra [59].
![](data:image/png;base64,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)
Calculation of Infection, Dissemination and Transmission Rates
Viral infection in mosquitoes starts from the mesentery, spreading through the hemolymph to other regions of the animal's body and ends with its multiplication in the salivary glands and ovaries [60]. Thus, the studies of vector competence use the calculations of infection, dissemination and transmission rates as parameters of the different phases of the viral multiplication in the mosquito’s organism [19].
Thereby, the infection rate (Eq. 2) is calculated from the number of mosquitoes with the infected body among the engorged females, whereas the dissemination rate (Eq. 3) is calculated based on the number of mosquitoes with the infected head, wings and legs among mosquitoes previously identified with infected body and the transmission rate (Eq. 4) is calculated according to the number of mosquitoes with the infected saliva among those positive for infection and dissemination [61].
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA0YAAAEwCAIAAAAcova6AAAABGdBTUEAALGPC/xhBQAAAAlwSFlzAAAOwwAADsMBx2+oZAAAY/BJREFUeF7tvX+IVmX+/6/fZeHNsmmj+8duuNI6Chu2KKYVrQYG6mRLtGQ7WkvEW0mdQth3pamFu6xa/qgFqcbxrWy0lWMaReSUuuRiJqmjOGQYpIO4voUFx8mED/tf30f388y1l+e+7zP3/J6jzwd4vH5fr+u6zpzrec65rnMP/e6774YYY4wxxpg88/8l/xtjjDHGmNxiSWeMMcYYk3ss6Ywxxhhjco8lnTHGGGNM7rGkM8YYY4zJPZZ0xhhjjDG5x5LOGGOMMSb3WNIZY4wxxuQeSzpjjDHGmNxjSWeMMcYYk3ss6Ywxxhhjco8lnTHGGGNM7vnBH//4x8RpjDGDgJaWljfeeOOzzz772c9+VlVVlYReTVNT03vvvXfy5Mlf/OIXP/rRj5LQPqOtre2DDz6gonL29CmNjY3nzp0bN25c4i+C3vjXv/41evToxJ/JwYMHP/roo8mTJyf+yqhkUPoIOv9vf/tbOYNpDp1TYduzya7ImMHP0O+++y5xGmOuP9avXy/H8OHDFy5cKLdobW3dtWtX4hky5K677po6dWri6TOw5/jx45MmTdqyZcuZM2d27949e/bsJK6Dmpqa2267DUd9fT3H5ubmMWPGFGL6BATTkiVLMObTTz/thx4oZujQodXV1adPn078ESitZcuW7dmzZ926dUuXLk1CM6H3SE9zKu+0Sgalj1i5ciWj3N7eXjxV0fYXXnhhx44dlbc9g4yKjMkNnL7GmOsWpsPwWGL79u1JaAEmb2IRE1VVVStWrEDQJBF9BlWEi9LFixepnaO8AQJnzZol94kTJzZv3ix3n0KlGNYPPVASJBQkngKxJeo0LEz8ndHVTqtkUCqkex24ePHiYEAKLOlS27PJqMiYXOC1dMZc1yxduvTo0aO1tbW4582bd/DgQYXDmDFjiF29ejVT3Zo1a/rhAdVHH32UuIYMGTlyJLVzTPwd7Ny5M3ENGTJhwoTUk8VrktkFEk/h/eArr7ySeLpOVzutkkGpBE6tQ4cOJZ6ucPPNNyeuIrpnSTkyKjImF1jSGWOGTJo0Sc/q7r///paWFgWKUaNGDR8+PPH0MceOHUtc5Wlubk5c1ysvv/zyN998k3j6nkoGpRL+8Ic/JC5jTN/g7RHGmCGfffbZ+PHj58yZs2vXLjTTgw8+GPYcnDt37p///Oevf/1reUXYnTBixIiuLpYvmffgwYONjY379u1rb2+n6pLL8ElA3r///e+4//3vf5MmWFWyzHhPg/J+9913Wkevxf6069Zbb1VioWSU/OMf//inP/1pElroH+r97//+73gZfslKQYVcvnz566+//sEPfpBqhVpKgYA9dG/wglq0fv163ME8rP3HP/4hN1GrVq3CQQ8oASX89a9/nTFjBnlVeGhmSVpbW995553wtj14tTkAARd2nGQMinJ98sknNDO1byNEBTMoma6jHHrjwoULcTgDRF/REEoOpxzEUVRB55ebqv70pz+p7er24rZn1AIlK4rHSJ1MyhCY3b3GDCB+SmeMSVi4cOHixYuRdI888kgSVAQT9pQpUzZt2oQbQVNdXb1y5UpFdUpP8paDKbmmpubDDz/EvWHDBqQJ0zNujoTPmzfvq6++mjt37uuvv/7iiy9OmzaNiRlVtGDBgp07dxJLVKGY78vBtpdeegk3cmTixIkkU1Qx5SoFCqEuHDTzvvvuQ8EoPGbLli3Lli0Lb5CPHz+OF/PkhbNnzxKCwqCiuro6jFGZdKASlISUq1evpnCaGexJQaOwdtGiRSkvqpEWMSi4cSi2HCib2tpazMNO2hinZ0BnzpypKMzAJAJPnTqF6lWCgGr84osvSEyyO+64I7SOKGSimvzcc8/FPVMOSmA06bRQqWC4KerAgQO4KQo3xisKMirSGKWqJjB+72/MoIMbDmPMdc66AnLPmjWLK8OKFSvk/fTTT+Pl5ygApvPE8913WoSX2ldRjk7zqurEUwYShO0RgAYN5l28eLGqqgqlKC8lqyFazn/ixAm82BAW6cfVbd68GXeIopC4FqqIY8tVSoJQINDAkCVGi/opJPEXqsOwxFPYDxH3OYljY1JeVUrImTNn8KrwOEEKokiQeDq8YRToLryx2an01EJ71aWgnlF2jnGUMtLtuGVk3CiaHGpRrDpE/Rk6By8pYwNSEBWK4kg3EiJ7ZGrYCxKKCh2VUZFi40EBvMprzODET+mMMVfx1ltvMXWtXbs2fp4hmpqampubH3300cQ/ZAjJOD733HPyZtCTvOVoa2urr68/e/bs+gLbtm0bMWIEk+7BwiaPUaNGcbz33nu1iH7ChAkccYd9Hvfccw9HPRyaM2cOguOWW27BrezlyKj0pptuIkHoNxqokBTYgJKgEIpSyMyZM+mcUO8bb7yBPXJXCG3RR0koXFqqS4SnlXSXHOVQezmq+fQDgeFBF+Wot4H+RE6p21NwMtBjhw4dUiHaNkGHcNy1a1d7e/vTTz9dSPh9cyT9M3j88cc1phz/8pe/4Hj//fc5YiRFhZ6kqNWrV+PYuHEjx+yK8D777LPxoLS0tBDYp5/LMaaHWNIZY66CeWvr1q1VVVXz5s1jGktCC5w8eZLjsGHD5AVmOD26SPzl6Unecpw6dSpxdcDsjpIoKaTKoXejtHrp0qX79u0bO3Zs9n7SjEpp0fbt2+vq6qZMmYKwwwtJoqvRnlM0B0eEHb1dXV399ttv40ViopnKZRxwUrslbr75Ztr+2GOP4WYo402jGVtrdTLEUAjgeO+99zjGze/S7hxpO20fkamM7PcRBWbMmMFRIr7TijgfGBQ1DRoaGpYsWSK3MYMTSzpjTBom4/379+OYPn36+fPnFRj49ttvE1eBeMrslJ7kLcfDDz/M7BuTRHQFdBU67P3339+7dy9qDGGXRJShXKVz5879+uuvH3roIYQdhaQ0cYAenjVr1pYtW3Aj7ObPn48urK+vR23gpXAlG5zQrqTNHdx+++2K0kO7mHI9AEnmDrr6YLJCwqNQ6Or5tnr1anQq5wPjwonRbx9YNqZ7WNIZY0qA5ti+fXt7e3u82Fwb/bQtIMCUWcmbvp7kLYfek6YeqhW/L66EJ554QpN3p4/HMipl4gc98EPYEfLCCy8U4kvw2GOPUWNDQwMyiEolaFasWHHs2LF++ARgt7ntttv27NmTEmq7Cr8yUl1dTT/EEqrcK2ztIaXt8goVcuONN3LMEILZqPbf/va3HDWU+/bt+z6igGLvKbxwr6QiBDqN4k+AcdFLW2MGM5Z0xpjSMJ+tW7cOVZf4O2a4+vr6MBHiaG5uDuvhmpqamP/iST3Qad5ugHhCEe7YsYNK0VKEoCEOHDiguTz1RDCbb775hpbKcoo6ffq03MVtyaj0woULWqelZDNnzsz4gJw6ZPny5XomR/ba2lqKDW/6ylFVVSWrygkmKDkElZPRdVpsN336dG2qpSL6Qbr88ccfpw9rampCtyCDtJbuhhtu4Hj58mWF33HHHbRi0aJFqDqZikPvPbXactmyZaEJyqUySxI/Gnz++efpVeljrZPjBAtFoRqpd/78+bgrrIgm0Ki9e/fqpa0xg5pkm4Qx5rrkTOFXv5jnAAfeJKKDxdHuTjhx4gRTJolXFMCh3YVCU3vYyZgiIy9ZqEgXJZRNXGOAxOGRHtmV9+LFi5Oj31nHTYgSK5wjbtoVyidvaDVeyqR2vLgJwUsCVUQWSiO7UqqojEopR15KIy+5Uj/klYJkVJR4ChtdyZJ4CqTMVqBW8VMLIdQoU8lIaaQnsJA8aaayBAhUWygk7gS8FJXqtHKDQpQChfpEhPTAWGu7q1BFlKw+IUohgoxKBmoC2akRt9pLM+PSAmo+R3Um5cfJsI1aVJRGJI6tsCJCiE08xgxi/LP9ZoDhlv2VV17ZsWMHbq65f/7zn7u63qVTuO2eOXMmjsOHD/d64XmHztELLzFnzhw94gq0tbWdOnUqfhVIyL59+86dOzd8+PAZM2bE6VtaWj7//POM35sql5fTIPVrUUuLlsQ1NjaSMfEU3uTO7din2dTUdPLkSUIoU0McJyb89ttvTzUz9t511100UFnkVkNIRmmpojIqpTO/+uorfbS2uHOKIf2VK1f0HEtQZrxgKzU66hP6kEDKx5JUv6XaVTya66OP7RV3wvnz5+OWjho1qtygYBjjSDORO7H9IJPibhFqi7pXIeFkuPXWW1PL1Oj/PXv20EaM1H6UjJfRGiyMKS4HgqnFJkElFY0dO3bv3r3ZQ3ktoT4p/gMsRmNdSUrTT0jZGdNVkhPoapK4iuF+nVvkM2fOhMceHJO43oPyqQX0KKXv4F5f/ZCiqvDsJ36YYYzJBXpUmXiuA7hMpdrLZY2Lpy5ltbW1qUeYek7c15dWUyGWdKb7SCrxd86x+BVPJaB1whsNqTquDvL2BK47iavfoRV6fQMhZPPmzXrH1O25YQBbZMx1CMoGKcM9JxclVEsSeq1Dq1NXYLxcuDjKAVzKUh1CLnrJqm4wYElnekT4g0/8XYHrAnm5bib+XqL4qtTPqF2Q+AtglQJxJEEVM+AtMuZ6Q/dg3fuDzSknCj+vEt+c03ZuJkMIDr1L4R5eIQGS+bZzMOAdr2bASC3T6RXa2tp6soOy75g7d64mCX1nv3IGbYuMuYbZv38/d5uonLB08ppnwYIFyLJ4yeAXX3zx6quvhhAcWvSMtjt49W7rJ598kihtgjYDiCWduaZ4/vnnudwknkFG+BxrlxjMLTLmWmXChAlLly5N7fy4hmlsbGxubn7ggQcSf4E1a9akdpOg6sIb2JipU6dyy+pf1xhwLOlML9Pa2trQ0DB27Nj169e3tbWtXLlyRAEcSYrCtruhQ4cuW7YMN0fcEG77KKGuro4sBFJO8Z0fV58pU6YoF46QoKamRj8TuWfPHsWqTI4UiLeQ6j+QkSxKqV9wSiIKEBtyUYJq5NjSrY+g0hVYhUMfOI2h8GCG+i2JKN8iyO4lepvw4q4zxphi9Pag8ttOfXA7ZubMmdx8du/yaHqN5AWsMd0itZbu4sWL6zq+dLWi8HEvjqCQ1KoUUhKYWkt3ovC1qs2bN+MOSzfijIsXLw4LlpWYBOHrX1rHFq88Iy9ZCIQkqACB5FVGKlJDwvYFwms7djlQArHYqTTF60hSlFxLp8aCLA8oseoNWyviPiluEXTaS9q24tUtxphO4crD5QISfyZcW1KXI6FLHFf7xG8GAks60yOkclJ/4fxVExjvgUJtEJJSGLoExPIFuF4UCxrki4pSObEqUl1BzZQUQEAgJJ6CYsMbayDKlwwKgeEyFydTGhRV4i+FbIDgjdWhAgOKCi0qtr9ki7J7CbCQBKg9eTMgozGmcpK/nGsIXUC4Yif+8ihlyQsgd5hEFV97TX/iF6+m9xle+GGfhx56KKzDGDVqFMeMH0cSTU1NqJA50a9367Of7e3thw8fxvHcc89x3Ym/BbpmzRrO464uYV61ahXHGdEv/GDqM888gyPsRQjGx4WPLfya+5UrV+TNpvCmdOi0adN27NghgVVsJ+IMKXbTTTcl/grotJdAK4Gun4+jGmO6jXaqpZbNlWT16tVcykouMRw/fjxHLS8xA4UlnRlEnDx5kiMqR2JIhKi2tjakTCXXnWwop7m5GUeqqDvvvJMjVbSW/zXJLoHWvHjxIooNt36aXeExSNJLly4RRaXr16/v9Pc9IbuX5Kicwq2dMaZSkr+c64+GhgaO/q2IwYwlnRl0hLeHMVxH9HM9PadcOeHW88KFC3L0HFTjBx98gKO+vj61/SKAmJs7d+7MmTOHDx/OTXAS2hnleimJNsaY3qOlpWXr1q1vvfVW4jeDEks6M+gIbw9T6O3knj172traFNI9wlvOcpuzin/ksSdQmlaZzJs3L+xXDaDzqgucPn164cKFekNdCeV6yRhjehculcuWLfv44497/pLE9CmWdGYQMXr0aI6rVq1KiTYuKEifMWPG6CVm/FvjIv7wR6dQDhIKx+eff64Qofets0p9damHoNW0DeL+++9P6ci6ujqMWbNmTeKvgOxeSjzGGFMZd911F0fuKuVNwYVlwYIFb731Vrae+/bbbzn2xfXTVI4lnRlEzJgxA9HW3NxcU1MTvqmG48EHH9RWhmeffZbj8uXLw+MuZA2qSConBVEp/RTQ+03KiVXRkSNHOPbRTzW8+uqrSLf29nYujqFSzCPk0qVLIeT8+fNyQGybUIs67SV5kbm9tSjQGHMNo4/MnSn1SXMuOFxYtm7dmtJzXHVTFygt5L3tttvkNQNDsgbHmK7DJUCPuzjiVuDFwq/vExh/skRvHhEixcnib52APi+SIv6wiHIBDu4IKTN8TA5OFH6mEFYUvoqnkrXxHuK99/pYHYXIJNJQVPxRJSpN5aI0tTfj20ukCZ8sCV/LE8E2KqJw1YubEMxYV/junawCqlD2ki3K7iVQsfEQGGNMOXTViq+QgJcrCRc9rjwxBBZfW3Tt4kKa+M1AYElnusn3IqKIIJ4CxSFoF0g8EUm5hetIUEVondQ1Ak1DdkkWrjW4k4gOkD6K0uWJC1ChpIQ4PRooCERqjBVYKhfeYpuTpBEl2xXbH2SiIAojJRNDS3HQulifpVoksntJWVKa0hhjSqJLU3zZ4Z5Tl9mSFF9buEBB4jEDxFD+JUNkjDHXOi0tLQ0NDY2NjZcuXUqCrmlaW1s3btzI8eOPP06CSkGfbNiwgVmcWXnTpk2zZ89OIvqG620UcsGUKVMY/e6tx2VAJ06ciM7r6zPHZOO1dMaYgST8vm05knS9xJUrV/bu3dve3p74r2lQcrt27dLPBGeAutq/f//p06f1YEYf4u5TrqtRyAtbt27dsWMH4izxdwVOodraWuu5AceSzhgzkNx4443hrTEOQsLLcRTG5MmTi7/8UpKVK1cmrkymTp2qnwC5HhgzZszSpUtTqwiKWb58+aRJk3CQ/mgBhfcd19Uo5IUJEyZs3759wYIFib9iUIGcM6+++mriNwOHJZ0xZiB54IEHyn0IEIXxl7/8JfFk0tbW1umzKFMS5mM/LTNi7ty5Tz31VIV3R4Lzx5+sGzxY0hljBpLs3+dF7ZUTfDFPPPGEdUn3qPAHi811An+Pv/vd7yr80ufBgwc///xz67nBgyWdMSYfNDU1TZkyZejQoSNGjKirqwtf3SNwx44dOOK1d8xJJAuJiz/yl0FDQ8PYsWPJyxG3Apm9KIfScKtwSK0lJ1wZY0KacvaHkjFSKwv1ucGWlhbm10IZ/yG8ryR7iMURSgPKUYFEUWBG20kwbdo0HMuWLVNihZfsAewJPUCgytcTHaLUNEqILenSKJSsFEIhFB6ab/qOCRMmVPjTgtxuLVy4MPGYwYDWrBhjzICTWksXs3nz5qqqKq2644gb9G0/0HIxuUFfk9E3X+Qmu6IglTjFihUrFi9efLGAPrWlLztQqT55Q4GEBG+wQRUFC3HH33TIsD8UpZLJtXv3bmonQW1trSzRB2vCNybISLK4tFAXiSkNSINbTaDJii2G7Ko68Xe9B/CSDK8+P4mpKkcdUuEolKtUHaKOUvmF5MaYEvjPwxgzWCiWF4IZPSUImOkJYe6Xt1gfoHIST+E7TXGZGZJOFaEq5MWBN6glZQyxsgGb5aXGWDlJhMldof0SLkLyJRSOMMIbWkFG2ig34CZWGkjiKRgJKcNSpPo8uwdShStvbAkiL9RV+ShkVEoWylQ4hB4zxhTjF6/GmMHOvn37OI4fP15emDt3LnKh3JaINWvW6GfW9C4vCa0AVfSTn/xkaAEceCU4AmHZ0KhRo+QQI0aMiH8lE0WSuCq2f8yYMYlryJDhw4dzDD8Ql6qrsbFx7dq1MhJwE3ju3DmOW7ZsQS3Fa5tuv/32xFUBXeoBIVMFUXv27JG78lHIqHTOnDk46K6Wwsc1XnvtNY7GmJJY0hljBjuXL19OXBHZSmX9+vV33HEHGffu3ZsEVYAqSm54IxSbzaZNm1AwWgTW2tq6Y8cOPTyDbtiPiEGZvfTSS1qatm3bNiQg+kax7e3t8RMvofVPKfnVVXrSA8VUOAoZlSJzm5ubkcsTJ06sqamp8Is2xlyfWNIZY/LBl19+mbg6QOUkrqupq6vbsmXL4cOHUTnxo69O0QOneIE/VPg9/dmzZ8+cOXPr1q1Dhw6dPHlybW3tmjVrkrgCldsvEG1IN4qiwJ07d+7fvz+0hYxnz56VOxDszN6FkE1PeiBF5aOQXSl5X3vtNaTqjTfeOG3aNKs6Y8phSWeMGezo6dSGDRvkFUeOHHn22WcTz9XU19ejhLrxYYU777yTI2osqCIcX3zxhdzZNDQ0VFdXHz169Lvvvrt06VKs57pqP1Dvgw8+iB6iKAqk2AkTJiRxQ4agHWljrLSo/ZZbbsFBw5ubm/Washv0pAdSVD4KGZWuX79egQg72ksPHzp0qJDEGFMEFwtjjBkMaKsjOiCslA/oJSYJiAIccTLFbt68GceZwq9awfbt23fv3q2oWbNmafcAWbTKTTsxi5ENpCGj1uZToKJwxxm1gyG8AKUKKuUoCIeQN8N+jio5/il07TwgXKWRntLUBMAG6iIBMohwYilfUcqI/dpawVHtpfBgTAzZVU7iz+wBLCEq9IA2eYS8NER1KX1hECodhXKVyq1kalroBGNMCks6Y8zAo9k6hrk8iesACSUdgFBAAUgPCaZ8oiQg8HLETUr0gQQTsZIFhbITiqsQhKuiICZAWQQJJG4EbhLIBmUMYEaws5z9Silik5BKcS0iJKA6EhBCaUHPCToTy4miOuQUhVCdFF6KQpH/IRReSQ9A4imQGkG8XR0FHMWVEhg6gVj6UOHGmGKG8k9/LcYYY7pNXV3dwoUL49ejra2tqJknn3yykh/ASNHS0tLQ0JDa4NnU1LRp06aPP/448RtjTITX0hljTE9pbGxMLXeDMWPGVFdXa4lbV3nwwQd/85vfJJ4OfvnLX95zzz2JxxhjrsZP6YwxpqesXLly7dq1tbW1jz766LBhwwj59ttv33jjjQceeGBu5o/YlqS1tVVvTl944YXwNbsvv/zyvffee+utt7qx7cMYcz1gSWeMMb1AY2Pj66+/rg/tVlVVoeSefvrp7I93ZICq27hx4969e88UvjOHwnvqqae6oQ6NMdcPlnTGGGOMMbnHa+mMMcYYY3KPJZ0xxhhjTO6xpDPGGGOMyT2WdMYYY4wxuceSzhhjjDEm91jSGWOMMcbkHks6Y4wxxpjcY0lnjDHGGJN7LOmMMcYYY3KPJZ0xxhhjTO6xpDPGGGOMyT2WdMYYY4wxuceSzhhjjDEm91jSGWOMMcbkHks6Y4wxxpjcY0lnjDHGGJN7LOmMMcYYY3KPJZ0xxhhjTO6xpDPGGGOMyT2WdMYYY4wxuceSzhhjjDEm91jSGWOMMcbkHks6Y4wxxpjcY0lnjDHGGJN7LOmMMcYYY3KPJZ0xxhhjTO6xpDPGGGOMyT2WdMYYY4wxuceSzhhjjDEm91jSGWOMMcbkHks6Y4wxxpjcY0lnjDHGGJN7LOmMMcYYY3KPJZ0xxhhjTO6xpDPGGGOMyT2WdMYYY4wxuceSzhhjjDEm91jSGWOMMcbkHks6Y4wxxpjcY0lnjDHGGJN7LOmMMcYYY3KPJZ0xxhhjTO6xpDPGGGOMyT2WdMYYY4wxuceSzhhjjDEm91jSGWOMMcbkHks6Y4wxxpjcY0lnjDHGGJN7LOmMMcYYY3KPJZ0xxhhjTO6xpDPGGGOMyT2WdMYYY4wxuceSzhhjjDEm91jSGWOMMcbkHks6Y4wxxpjcY0lnjDHGGJN7LOmMMcYYY3KPJZ0xxhhjTO6xpDPGGGOMyT2WdMYYY4wxuceSzhhjjDEm91jSGWOMMcbkHks6Y4wxxpjcY0lnjDHGGJN7fvDHP/4xcRpjTCmampree++9kydP/uIXv/jRj36UhEa0tbV98MEHJPvnP/956623JqF9SUtLyz/+8Y/+qSsFjf3b3/72wx/+8Kc//WkSdDWtra3vvPPO5MmTE38mnZZWjk4Hpe+ggXv27CnX+Rj2r3/9a/To0Ym/Dzh48OC5c+d6vQra9b//+7+//OUv+7k/e4XGxkbMrqqqSvxX0w+DYgYDfkpnzCCCSWV9B1yFk9AOmMmSuAIkTiL6kpqams8+++zy5cvLly8fN25ccaWEkIYp9uzZs/PmzZsyZUoS0Teggerq6iZOnPj6668nQf3LqVOnFi1a1NDQkPivhvDq6moSJP7OyC6tHJ0OSh9BRXQ+DSzZ+ehsDLvvvvsOHTqUBPU2/AlQxbRp0/qiil27di1btmzfvn2JPycg5saOHcuf3oULF5KgiH4YFDOI+M4YM2g4c+bMihUrmDL52+SG+8SJE0lEgU8//ZRYwkmwbt06EicRfQa1zJo1S26M2bx5s9wxJCCZ3LsLyN2n0D/BsP6HfigemsRV6JAuXVqLS8umkkGphNjmLsHpV67zKZO2h/OhL+C076MqLl68SLEcE39+2L59O31SbkD7YVDMIMFP6YwZRIwZM2bNmjWHDx9m1mxvb58+fXpbW1sSN2TI1KlTiZ07d+6mTZuWLl1K4iSiz9i5c2fiGjJkwoQJCxcuTDwdYN6ePXsSz5AhswsknmsX+oHeSDyFR0c9eQSSKq1TOh2UClm9enXi6iJjx45NXANB3532I0eO5M+KY+LPD6NGjUpc5vrGks6YQQeTCrPm5MmTUXU1NTWxqoObb7552LBhiaePaW5uTlxlOHXqVOK6jvnDH/6QuPqFTgelEpqammItboy5BvD2CGMGI2+++ebatWv/3//7f/v27bty5cp9992XRAwZ8tlnn/385z+PVzqj+cLuhJ/97GddWtxdLm9jYyOBf//733H/+9//ptJf//rXigqsX7/+008/RWH84Ac/uHDhQtgbUa7M1o59AyT429/+9sknnxCrBd0kfu+997777rtUu5Ts5MmTI0aMiJd+/+lPf0L1/v73v0/85SsNhVD4oUOHihf1q6U0EMiI0AletQiz//d//xdvMI8EWmxO4f/93//NGKkHlICxO3PmDJdWVX3s2LHsHQyhNHnDzg/VG3oVMgaFcO2WSHUUUOAbb7xB4ri36TpKwKq4EA0QfXX58uVx48YpUIQo2njgwAFC4s4PnDt37q9//euMGTMo8+DBgxicGlMI9vz4xz+ON4VkDDfErdi0aZOqSOLKwPlJekHi2CurZCFe9YxOIfpEVcde9XzowIC6XWWK0HUqnOH75ptvMjZzBBtSfZ76Yyl5FoVB/6//+q+3336bU7FkLfGgJEHlRwFCVIAqtN1H5yReTh6OqZPEDDh+SmfM4OXVV1/lSlpfX89slAQVwZTAhVWz7HPPPYebGUJRndKTvOVgPqipqfniiy+Yourq6u644w6mAcIbGhpoy6JFi0jwyCOPMBUtW7aMEGL1KnnLli3Tpk0LGwVIhj379+/HvWHDhurqaqxVVDHlKuVIIcTifuyxx+bNm1dIfhVkefHFFzHm+PHjCtm5cyfe+P0mOoM0OFRRWGx+6tQpxEchSRqlpJk0GUcSejWp0pi8w84PBqK2thYbsHnlypVKXxJyUciHH36Im46iS5np4yjagpsm0IcaX2mmQpL/oBrpjbNnz2JSbDNR5MVaYu+///4jR44kEeWhIatXr9aYBnuAtgR7aGk4sSk8Y7gpbfr06bJN2qISSExdQEaFpAYasFADjZGcNmGTQfB+9dVXdAUjQl6droV83/ftlClTlixZgjtUpCigmZxvOPjjytjMQbvoTxypPqdbwh8LgcVnUVw7sSXldQblRgFCV4O6C9sURZ9gFeFoRMzmb1bhZhDBzYoxZrAxa9YsLXa+ePGiHgyEbQfr1q0L66DPnDlDbFggT2LmQhJXsnOikrx4s3chFK+8ppBgnmIXL14sLw6827dvl5eq8SIjVKNaGqojnFi5SZCqBW9sWLlKyRKSqYFyp6BvyRIMU3UrVqyQF3Cnyg/GpLxAjXFp5MUbsqcozo43bo4UjNwCb9x2Whqyqw9DM4mKU5KRWLllpNygk4Hs8lIgsWqCLAzNOXHiRMqAGCUmNoxpnJhC4oyyQSkzhhsHtoUdJDpt4h7LQJ2vKgAD8MY7eLAh1erQ8/JSghLoJImtikvWuR3yxm4MLmmtejJEqQS5QZ1T7iwilhMjWK7eC7EpCI8ryhgFpQyVqrtCRlIGN8bHhZhBgp/SGTOoGTly5P79+5nSuBHnlj0J7WDbtm3t7e1z5syRl8Ra875x40aFZNCTvOXgPp654dChQ9z3gx5O1NfXK/bmm2/mOHfuXHnHjx/PcdKkSVrwjgG333776dOnC5FDli9frskbsh8LZVQ6evRo8qrfKL/cd09mz56NDHrppZfkxR68lNDWsYpx7969U6dOlbtCQjPvvfdeOSpn7NixobqHHnpIjpJgIXaePXtWbWdMR4wYQW8cPHiwtbWVKD0rEoiSN998M/FcjTJyVDl6MKPueuWVV+iN0JwJEyZIZWZwzz33hDGVYhDqYVUBCty1axfHjOF+8cUXqT3sIAlnbCXMnz+fI+2SlxOMY3i8xImBnRgpb0kYPiVI7fv55JNPOIa9Gr/5zW/kEPTY22+/LffChQvvuusuuWNoEU1W/zBY4flfTMmzCLP37Nnz1FNPBcsfffRROSohYxT0txM2W8yYMUMOQWN37typPwqMf+655xRuBg+WdMYMdrh6vvbaa8ivBx98MIgMcezYMY7xnKSrcMnpIUVP8pbj5MmTiasDbush8VQAckQOWs3kzZSDvtGr4XJkVMqMuHjx4okTJ+JA5WTIsmeeeaa5uVkv+zg+/vjjdLg+UdbY2Mj0WUg16CjenoLltP2mm27SC8R4L2RhO3Lp/cg6GQKIbwqRHNyxY0dqi2u2BsogtbED5UctkjvlhpuxYCB0MyC6VDsqpLa2NqhzhAs1ood0kjc0NDz99NOFhF1GncPthLz//Oc/OdLt8r777rvcBtAWWkTV5U481N6VK1dqamr0mK1CtK8lHtku7ZfKGAXJ5Y8++qgQM+T8+fMcw/q8P//5z3T+uHHj6urq6MCu3uSYfsCSzpgcgCLhhh65E6+nCcQ6r6vTbU/ylmPp1XTpsUqgpbC4Csfhw4dRtArMIKmsg1DpmjVr6LcRI0ZMmzaN3ktp4gDpq6qq9GSFIyXMmjVLzyFef/311OOKwcbDDz+sVgeSiI5ZOUDzy0l29EeSuQM90+pdEBBJ6R1IBnV1uCvnySeflDqn7ZcvX54/fz4DvXHjRnVFeMzWVfiTRAn9/ve/X1lg+fLl27dvD6WhUE+fPq3VhLRLSxiLQRv94Q9/4DQ7evQoPZOE9j3lRgH7P/3007Vr12IYYpR7SO6IwpNCrg8ff/zxBx98QL9VV1fTaoWbwYMlnTH5gBt6Lq/cYWudvtAUEn/vXpKlkumhJ3nLob2Zqd9C0DudrjJ9+vSZM2cy2XQqNDMq1VM3WopKOHHixJ49e8oZQy1MXfX19cy+zMeEPPbYY2hB5rbbbrutt8Rur3PLLbdwfOWVV+QVEhCapFPvmml+kB0xtJHO0RvqgPoKAVTJfohKmDx5MhJHp5lAHKjwcsN9ww03cIw3NHSVqVOnoj+QTdu2bfvd734XBvr555/X9oJu88knn7z55pvDC+zfvz9IH9CJRwjCjnZxFik8hjMWM7Zu3drVx11Ux/HLL7+Ut6tkjAJ89NFH3D3qT2DTpk2xvFajsBZhRxqUX+qEMQOOJZ0xuYHL66xZs9rb2xP/kCF6bcR0FS7QTMPMwVpCBNxqg9wpOs3bDe644w5K0C9cqVgcmoHgcsfGw0qgmeElrOYSssfzUCCj0kOHDoUHJMxSTO0ZNoQO0RM+5mOKZdLN7hBpDhUrO0vy7bffJq5uUbLhgEDhlNixY4fehRGCDQcOHEC3AVEINaJCt5w7d66Qb8iNN97IkXBygZZqoav0JpFwcmmZFzcSjEX8SIbYsOSxEoLxDz30kJ40SwpQ74oVK/QEtNxwM2pIEBoYXnGqtLANk8Sc4aGKkqxevZrC0YVSKvo48969e8u9hs4gnD90Jp0wbNiwuwqkPvb7hz/8IZj0wAMPxH+zARX1f//3fxxJLNmKI2QsRmcRPcaZuXz5cjowDk89kS1HxigQglD7+c9/Pn78eBr1y1/+spAjgTuHoOGU/sqVK/KawUKyTcIYMzj4tPCrX/xtMpOtK9ood/HiRcLjrW3bt2/n+o5YITGzL+6wNxCy/8wz8hKlGR2wB6/CY8hFXhKQEbesogS8yggUGxIrvLa2lpSg8pWXOUatBrLgVSzl46B23CFlWHhEFrzZleIlPQ7KoTSlLwdpSJl4CtsMyZt4CsRmhz5R1YzL7t27ySKvmkkawhVb3Iep0uJOUNMwJlWa0iuBCtQpoUDAHTZCpqLIG6K0F0HdqxBKUzIRrCWLKuWIPdSrMmWh0oiMMQ2JGRqFAMnC+aaMxcNNFGl0mpGXEPg+85AhNIFYRZGrUExpaAKlYV7iL+wjVvYAlaoooooHjhCddcEqbYBNgRnqYdyURqshZElBmSEXhZNSbtpLenLhLXcWcSQBqAoglhrjzbyC7MpL4mBGuVFgjPAmER1QrBJgG7EaBQKz+9wMCEP5l4yb6TO4DZo5cyaOw4cPD9o3ONzpLlu2jMtct39fqHL6s67ccfDqX5daGq2LEtwo33DDDfHrM06wffv2cdM/evRo7p7jc0zPNjKeRpTL29jYGJ7oALHxeyWRev7Hbb1eIbW1tVEm2W+99dZQdZyYlBzjZs6ZMyd+JYp3+PDhhGAYbhpLQ7799ltswOBUSnVFyUr1vEcVFXdOMaS/5ZZbQhrqunLlih7tiHh0Qp/IJDU/1czz58+Hbizuw1Rpt99+e6ppsTdVGsQF0j8nT54s2UYNZdwtgnB1b9xenQzM1nGrIZRPjWTE1PgMFKlTN2V/GClO4D179jC+mBoKYfhIXDzcIVaDq05uaGgIZivlSy+9dPToUSUuCcni5qcGGuITvnjgRo0aFTeNv0pMev7553/zm9+E3TkYv2PHjmeeeYbLGqURohKKOzOgHlOvUuC2bdvU/ErOojBYZMF75MiR0F0xqUEJ15OSowB1dXUPP/xwnGXnzp0IOFpEH+JVe4tPp2uSeFCSoPKsXLnyd7/7Xbmx7iek7EwlcGuS9FoRumVBo6RuWwWBJIBwizwIUetSd659RL/VxaAUxicNY6Hb3ySdMSa36Dli4ukvJk+eXHy155LSP5fQPmJFmefxXC0T1/XEicK39+JZmxA9rAVOgNQMQsrFixeX7MB+w5KuazBmYUTDw2oCd+/eHdRDeLhtBB01gH0iPc24hIs+IXpPAd378xvYFhljAvw5M48Wq6s+hetG8dVDs0OsAPIFfUij6MzE3wFXy+vw7peLfOopDJ2gN91c/PUuG4IMEKQPL8cHBEu6LsO4aiwTfwT3Z4pi1JMgU1i3MbACiNoZlNR9PFZpsLoxGQx4i4wxYkCmT2Zu3cMz6+MIpCb43KF7XYRL0p7Cb1QUr8+75mF8GdnUqZXS63q4U6yAOQcIH6gzwTtee5OFCxdKPaxdu/Zg+b1v1xUtLS31HT8eMKgIy/ji5T6VMGhbZMx1SMkFZH3NyMIX2pi2n3nmmXsKcOUnZIDXUfUYfcTxtddeU6OWLFly9OjR62HNXIqXX3750qVL8anV1tbGtB4vvnzyySc5kkzeAOcAUnjBggWJv3+xpOtl9B1LHPptpesc/gwG6szulO5dfAdzi4wx/QnXEO4MlxbIu5gLjBkzBimjRl2HYg5aW1tRb6lbBcRcaoeEPhxT8qfYfvvb3zY3N2uLTD9jSdfLMPB6o7en4zdn4ODBg3V1dUOHDpVXrC/89A2BHImNT6CWlha8REFNTQ3u+JkfqiLkHTFiRLw3iqiGhgb9Cg1ejiQgWfgwVVNT05QpUwghjbYviVRGhXBGUjvgVSwZMUZFBYhSmYAjFEvz77jjDv34zLJly5QAd3FdAUJCUcWtrtCeCgl2hq+mBbraIoF5IVfo8ABRjEU4JYwxxgxC9N7m7rvvlrckXN5XrVrFXF9S9d55550c33//fXn7leQFrKmYjLV0QitnQUtK8YZlW0oA6wrf9dEqLpJNnjx5VsdKr4uFTyhpqRZuvclVUQohMQXiAJXMkShKU7GErFixggIJJ0RPDXFjCXkJIYoQwmVAnBFHoZ7v1wWSmBCVo6KUBrfSAIGEaM0B5ShBsBaUIBRbsi5Qu0BLEChBacJqhgrtKYlsCD0sQidQdRJUQIkrb5HABsxTf2pJJd5QMuGEQK53wxljzDWPJpr4mh/DVZ3ZgXkBUnNHjC74GQn6CEu6LsNIa7QSfxEhQTzrKyTxFPREvIWCLEFwKHt8KhAVTi+kQyxNSCbFFhJIcMR6QgWSLNYTEjRBMEGxUtG3NMkYVnpKmhAiL6j2xFOqkOIQKA7UslxJIqFFpnFgJfaURNWp3+gWytEfbVxUoBstohvJlRqyVBoqpf/jNOUgozHG5ILksnUNoXaVu1br2i5KziBC80iYl/sNv3gdMOrr61s6flxl6tSpqff0zz//fOIq/NakHG1tbeQKXhg5cqR+Wvujjz5SiHjooYfCQk59/bW9vT3+ru89hd/xDJ+vLMmwYcM4Un5YJiIj4x+34U5F8qgn0K61a9dSTtwJVKotRRs3blRIJfZksGfPnqFDh/7kJz+57777yILA+vrrr4tXwHSjRS+99NLcuXPjlbPq3p07d8oLs2fPpv/jNMYYYwYVYbVPuWv1xx9/fKbjZ12YR6ZPn15y5Y/m5fiLzf2DJV3vE35o767CJ/JLsmTJEs6GiRMn1tXVSdiFX0dGgSEpkG5jx45tbGzkdEEuSJadOnWK47x587RgS6BUCDx27Nj3mfudowVw0AraEv+ifOUcPnyYY/GfEH8tHPfu3StvD9FTOj2z5G9y+PDhJf9ou9Gi5uZmxisZjwLLli1TuBJ0Cd1sGWPM4Ce5bF1PjBkzZunSpfv375eq27dvXxIxCLCk632++OILOW655RY5ipk9ezaqApGBFEDY1dTUxAvnkRSbN2++dOkS6m3cuHENDQ1JRIGSXwni1iGJ7ne4rZkyZQoi5u67714c/XRg5YRf1Ekxfvx4jnq72lsgjvXmNIjpYrrRonJfIkyijTHGXENMmDDh2WefxZH9squfsaTrZfRuFEdtbW32WzaUPjrs08Iquj179kyePDl+frtw4cKvv/5a4mPRokXx5tDPPvsscQ0CEEbTpk3705/+RFvmzp1bvHu0EkaPHs3xyJEj8qaI1y70CtxgMTrlnpl3r0W99SjRGGNMLtCLuO7Nen2EJV0v8/LLL6MVcCxfvlwhJVm5cqUcU6dORTosXryYXNo7ffDgQX01A0UYnu7q9d9NN93EEcmYeryELin+IEg/gBkYg/E9/HyRlh3QA6l26RW21qX1Lq+++mp1dTU11tTUxKquey2iqJJfIQqjbIwxZvCjNU5Q+QenZsyYkbgiNK1kLL7qIyzpepOGhoa1a9fi2L59e/G6+5hjx47FH117+OGHE1eBTZs2Ja7C010pHhgzZsysWbP0eEnL7AhEhaBL+v/Ugc8//5xjfOqfPXs2cXWc0zGYWhwItEvvN7UELXDgwAHk7Pz58xN/74Fcfvfdd3EgxeKdKN1r0eOPP4573rx5CGvl5VhXVxffvXFuQMnmG2OMGSRoe9yFCxfkzeCVV15h5tIuvRRaSJ2x+KqvSJb8mMq42NnP9iNBite6aUl+nIXEpNQ3RFQmXu2aVmJCznR8tQ5v+BwGgaQsFPYfOKsUSwkyg+wKgVA7DoWEVnBUpVCcUTIr/voO9n9fUMd6vuAlFxbyl6BiyUJe2b+58JE2bCZBKLy4LqrQHxIZVZ0yxp3ZqT0lwQyykAYbZFJAVQBVUwLFdrtFMj6GkGI7yasQY4wxgxBd4VPXagUyc2mu4drOjIA3XORjmCmUOPH3I5Z0XYAp/PtpuRRM+czuSLTiAZZ8CVAIgSSOw/EGtYHwQg1IhQCO1Lmlk0nCLo4N0i1ASKp2vCWTJa4OKC1xdYDZxUWRTJ9kw6smAF6sQsQUjPqPyuSIu2RdglhqUcMphDaGQkCJA+XsSZFKI5K4ApKJAUK62iIFQmz8ihUr4ihgTAmntMRvjDFm8MFVmss4U0PiL8D1P9y3cyXXdJ/EFUEUyTIS9B2WdMaYawSuxRLW3DkkQaVAbaO5JdzR5fGdQx/Bnb3u4hJ//0IDaSw9k/ivhljdIib+zsgurRzceeqGh2PGM/W+gLOCBpbsfM4EGZZ9wlRIRkUmX+j6kHi6Dn/s6L/E0794LZ0xpq9Yv3598qW+MsQrSnvOlStXjh8/rpvsDJ544onRo0dfunSJifzIkSPvvPNOEtE3aAHljh075O1/brjhhsRVCjpt79692tRVCdmllaShoWH//v2nT59maJgpV61alUT0Pa2trbt27dJXCIo5derUuXPnOj1hKiG7IpMv/ud//mfEiBGct4m/K3Am8Me+devWxN/PJNLOGGN6m3Xr1sXLBrjghGcYFwvrByp82LN79+4Kn6NQILVkJD5RWNfYK09lukTc9gGHzo97HsP6dC7oxlO9kpT7+mOn0MBync+Z0IvnQ0ZFJl9woaju+B32LpH9Trav8VM6Y0xfMXr06Phn6GJGjhwZfjGlU+I94D1Em5qvc7Zt25a4+p6WlpbKHwFm0NbxyU9j+oEJEya8++673EV06TMFdXV1DzzwwNy5cxN/v2NJZ4zpKzq9tC1dujRxlaehoUG/etcrXL58OXFdr6CxUl8L6lOuXLmSuHrGE0880SvS0JgKQdW9+uqr3P/o01Sdsn79eu5gB1DPgSWdMWbgQWdwKdQCOxxhjd3KlSsXLVqEY9q0aWHtXVNT09ixY0Ni8hbSdgJ5SS81o9LCB7pRjSqQY1hAQy0Uro9RYwaxI0aM0AelOSo9N+VKDCTDSyAQm/31b5VJgSSeMmVKvKaQjAqnaspJQiMIL1TyPWSMvbhJoJYCRVERLaIK2UOjJk6ciIN+UILvS+xAVUPxd7NFqrTYyyjIEo6EKz1euhqHqpN5gIXkIoS66IeQHqg6RAXzCNFiRMJBgUy08TkTz7sUyFhQAlGxPRlQr9KTMU4fF4UZqZ4pV5G6QoRWhMB4uM1gRh/8L/nluWJImf092v4geQFrjDF9DBeckiuNtL5Nq+7OnDmjjwWEfZGp5XFa/KTEctdGHzjsdC1dcYIVK1YsLnwNUcv7iN1e+BqRCscYEmAMVBWgBCBWicNiQZpWXfhoImASUbRLUYA3bjvFptqrVTtUHVbwkIDw71NfDeWr6tBFShkvNcNC0uCgKMUSoii1K3gBwxRC7cTG9qRIlRa8tJfaySuvqhbF1WE2VcRtDOkpJESRJc4oI+UG0oSdqhwZF7yKon8oROWEvip54oHMIw1QF4XgJa9iyU4IUThCUaGfCSlXUXFiQUh8VhjTu1jSGWP6iTDhpWDWjGUZEyQpwwytqV2TNyAI4nmRAuMyU4mLSSVQXUzA8uLAG6qm5DC7g/IGIaXEBMpLytAKCYXYDLzBTpRTXKxahALATWlxlAKLkdlxLJom7gfcoVEyJtiZ8gKJCQnpMQ9vbHxMydJi4ULvxZYUV0eC0IdAe0lAi9SoEIWXRoWSZaTcQNvjSnETi+W4qQt3aA6kOidG5qEsE39HRTKDWsircIHxxGIb7uyKCE/VS13xeW5Mr+MXr8aYgaSlpYUJctKkSYm/8ANxzHwElnw/NXv2bK5cEyZMaGxsrKmp6eEyu3379nH8yU9+ojdiOPBKW4iRI0cmrg6GDRsmh6I++eQTeY8ePYpJra2tK1euvP/++xVYkvfff7+5uVk1wn333Ueg3hvOmTOH2sPb5HI7SPQbelSnN30ckRp0hXJRFAmKLc8mpB81apQclRP/9l3Jl8UBDTdNTho/dKh+OunChQv6kevw88o04dKlS2vWrJE3BW1fu3ZtUsTQofolxnPnznHcsmULQipufvhNxXKMHz8+cQ0ZsmTJEo4nT57kSC2pvM888wxHmZpdEeEvvPACg6Lf7Ia33377ySeflNuYvsCSzhgzkJRcPh8rvGK0lu7AgQPrin5EpKtot4RucGMU2yW0rGrmzJm/+tWv3nzzzSS0FN9880388EZ8/PHHRKFjkDgjRoyYOHEigjVj0dXDDz/c3t4ubbFt27YdO3ZUVVVpIeDGjRvLbTQecDTcnxY9Agw/l14htD1+8ie02yZW5N0gSHYo3pARi79OK2IUkNrSiOjsvXv3drWZxnQJSzpjzMBz/PjxxBVR8qu2jY2N991337vvvvvaa6/1fDGyHi/FK+uBKhJXxaDnUGCXLl06ffr03LlzY1lQzI033kiyxNNBqBRVR9OQCySbNm1aOVWHOJg8efKGDRuoGmGq53b19fUtLS2YMfDLtMugMT1//ry8gv4PzQzPtES5sUC/nj17NvF0EBLr4WVPGD16tBxHjhyRIyY8ley0otWrVzOUSG10Nu4k1Ji+wZLOGDOQIE2qq6t37NgR6yoU3qxZs0rqktdff53pvLcky5133smxtrY2zM04vvjiC7kr59SpU83NzdOnT0/8mZCMab4u2i2LDtPzwvWFPao4kGgIFHrm0KFDhSQleOqppyjnkUceuffee/HOnz+fI4U/8MADhfjBCAPH8NF2vSMWyB1OAz1wXbVqVRgL0uhdajEzZ85Ev8aCD9l0yy234EDpMhZx+V2CDsfCGTNm4EYlt7e3x7V8+eWXxM6ZMwd3JRWh7xnE5cuXUwjuJNSYPiJ5YG2MMX2JFt0DKiQJ6kD7A5ggFbV582ZmzbABIuweoARAfuFdV9hzumLFCuZLEpNGeRUbr3aPudixFzVOQMmEUA6lUWwwQ8vbCQ/r35Uy5NVGXdKTILixJBhJgVplr9hQFEdSKj01kiy8h5UBartW7lOaokqChfE7XNzUkng6oATKwSR5qV1VYxvVBWNCh9NAvETJmyJVmkYnLlwjopYC5cQJQCWQhv4kFpvVSxDGgnANbigHL1HYhoMBwlpKUMkkJiPhSql+I69e73LETQi1FJ97SowN4dxTSsUSSC0QisIdRkR5O61IXVSuP43pRSzpjDF9DlNaTKxCBNOhhAUwSQd5AUzqpCdcczZRmjg1DRMYZlklEyWrSOI60EwMTLcqMyWnAnhThZMl8RQgizQHxiALJAVIhvHFRZGYcFQIaQihvbEAChVhUpCP5aDS0AqgH1LSIbYz9IlMlXmKEnHtENIHUqXFXihuaeLqINiGytFw08agkARpQrfEwkjjHsZaIaQhJYE6NwJUHcqnLkylt+OOiqHA0OrUuQfYoFqAMoPaExVWhIVxW4zpI4byTyerMcYYY3qXpqamDz/8sPKfvzOm23gtnTHGGNNXbNq0adBuQDbXGJZ0xhhjTG/S2to6tPCbZmPHjh0zZsyg3YBsrjEs6YwxxpjeZPjw4VpjV1tb61eupt/wWjpjjDHGmNzjp3TGGGOMMbnHks4YY4wxJvdY0hljjDHG5B5LOmOMMcaY3GNJZ4wxxhiTeyzpjDHGGGNyjyWdMcYYY0zusaQzxhhjjMk9lnTGGGOMMbnHks4YY4wxJvdY0hljjDHG5B5LOmOMMcaY3GNJZ4wxxhiTeyzpjDHGGGNyjyWdMcYYY0zusaQzxhhjjMk9lnTGGGOMMbnHks4YY4wxJvdY0hljjDHG5B5LOmOMMcaY3GNJZ4wxxhiTeyzpjDHGGGNyjyWdMcYYY0zusaQzxhhjjMk9lnTGGGOMMbnHks4YY4wxJvdY0hljjDHG5B5LOmOMMcaY3GNJZ4wxxhiTeyzpjDHGGGNyjyWdMcYYY0zusaQzxhhjjMk9lnTGGGOMMbnHks4YY4wxJvdY0hljjDHG5B5LOmOMMcaY3GNJZ4wxxhiTeyzpjDHGGGNyjyWdMcYYY0zusaQzxhhjjMk9lnTGGGOMMbnHks4YY4wxJvdY0hljjDHG5B5LOmOMMcaY3GNJZ4wxxhiTeyzpjDHGGGNyjyWdMcYYY0zusaQzxhhjjMk9lnTGGGOMMbnHks4YY4wxJvdY0hljjDHG5B5LOmOMMcaY3GNJZ4wxxhiTeyzpjDHGGGNyjyWdMcYYY0zusaQzxhhjjMk9lnTGGGOMMbnnB3/84x8TpzHGdIuWlpY33njjs88++9nPflZVVZWEXk1TU9N777138uTJX/ziFz/60Y+S0D6jtbX1nXfemTx5cuLvXxobG8+dOzdu3LjEXwS98a9//Wv06NGJP5ODBw9+9NFHXW1LJYPSR7S1tf3tb3/rxc5PjabK/+EPf/jTn/5UIcYYGPrdd98lTmNMHli/fr0cw4cPX7hwodyCmW/Xrl2JZ8iQu+66a+rUqYmnz8Ce48ePT5o0acuWLWfOnNm9e/fs2bOTuA5qampuu+02HPX19Rybm5vHjBlTiOkTGhoaFi1ahGOgrm9Dhw6trq4+ffp04o9AaS1btmzPnj3r1q1bunRpEpoJvUd6+rbyTqtkUPqIlStXMsrt7e291fnFo4nGnTZt2uLFi1977TWFGGO+hz8SY0yOQAqExxXbt29PQgsweROLmKiqqlqxYsWnn36aRPQZVBEuIxcvXqR2jvIGCJw1a5bcJ06c2Lx5s9x9CjUGw/ofJBQkngLxWKjT6JbE3xld7bRKBqUSOJ0g8XQFxFbvdn7xaNIhdEviMcYUGLBLnjGmJ9TW1jLJQbFuQ+eh5xJPH0NFqbm2GARokHT9xsBKuhQoKsYr8XRd0nWVSgalErCw+OyqBDL2bucPqtE0ZtDi7RHG5JJJkybpWd3999/f0tKiQDFq1Kjhw4cnnj7m2LFjias8zc3Niet65eWXX/7mm28ST99TyaB0Smtr64svvph4jDF5wNsjjMkln3322fjx4+fMmbNr1y4004MPPhj2HJw7d+6f//znr3/9a3lF2J0wYsSIri6WL5n34MGDjY2N+/bta29vp+qSy/BJQN6///3vuP/973+TJlhVssy2trYPPviA0ghRXu47tYdAi/1p16233qrEQsko+cc//nG8WP7NN988c+ZM6vpWslJQIZcvX/76669/8IMfpFqhllIFYA/dG7ygFq1fvx53MA9r//GPf8hN1KpVq3DQA0pACX/9619nzJhBXhUemlmS1OaA4NUuAQRc2HGSMShht0Sqo0AFfvLJJ3FvP/roo4T/13/915dffhkK0QDRVzSEwHDKQRxFTzLo5SYXma3qDh06FAY0hBcPUPFoUpH2l8SjE/qfEBIQotHJKNmYawk/pTMmxyxcuHDx4sVIukceeSQJKoKJecqUKZs2bcKNoKmurl65cqWiOqUnecvB/FpTU/Phhx/i3rBhA9KE2Rc3R8LnzZv31VdfzZ079/XXX3/xxRenTZvGnI0qWrBgwc6dO4klqlDM9+Vg20svvYSb2XrixIkkU1Qx5SoFCqEuHDTzvvvuu3DhgsJjtmzZsmzZMgyQ9/jx43jjh1hnz54lBClDRXV1dRijMulAJSgJKVevXk3hNDPYk4JGYa32B8ReVBctYlBw41BsORg1zMNR3FFEzZw5E8tpAmZgEoGnTp0aOXKkEgRU4xdffEFikt1xxx2hdUSNGzdOTX7uuecyHu+RhZSkx/3YY48xoApXCfv378fNAHGmMe6KSiEzGCnkoEJSoyOwgWHCUXnJxuQe7pOMMbljXQG5tdIorJ/79NNPQxSgAOKFXFqEl9pXUY5O81ayyIkE8Vo6NGgw7+LFi1VVVcyy8lKyGqLl/CdOnMCLDWFFV1zd5s2bcYcoColrSRlWrlIta1M40MCSq8fIQjIKSfyF6jAs8RT2Q8R9TuLYmJRXlRKizQcqPE6QItUWecMoaOVcbHYqPSnjwhWrqomiK9TbIUrbDmhOqliaHLxqgjpE/Rk6By8pYwNiKDYYo5Ry69SSG9twx/2ZapFqDwmUPh4dSg7nbXbJxlxL+CmdMbnnrbfeQl6sXbu2sbExCeqgqampubn50UcfTfxDhpCM43PPPSdvBj3JW462trb6+vqzZ8+uL7Bt27YRI0Yw0erByahRozjee++9ekQ0YcIEjrjDp1juuecejno4NGfOHObmW265BXf2c5eMSm+66SYShH6jgQpJgQ0oBgqhKIXMnDmTzgn1vvHGG9gjd4XQFn2UhMIlWbpEeFpJd8lRDj3IVNtBgfrYDUNJOeGBHP2JUFa3p+BkoMcOHTqkQvSETJ+koaj29vann366kPD75khFlWT06NFHjhzRUzpS6sEeLF++XBodSCBHhdCNGp3w1BCTHnjgAbl7UrIx+cKSzpjcw9S4devWqqqqefPmabIMnDx5kuOwYcPkBeY/9J8eV2TTk7zlOHXqVOLq4PHHH0dJlBRS5dC7UVq9dOnSffv2jR079pVXXlFUSTIqpUXbt2+vq6ubMmUKwg4vJImuRp8ARA5yRNjpOd/bb7+NFyWBRiyXccBBeiauAkhJ2n7XXXfhZihvvvlmhQNiLvWlw4BOhhgKARzvvfcex7j5GbtzUJDIr4kTJ+JAEAexTtVoYsQio3ngwAEFVo4E5caNG+XFpCB5e1iyMTnCks6YawHmLa0Wmj59+vnz5xUY+PbbbxNXgfBUphJ6krccDz/8MGosJonoCugqdNj777+/d+9e1BgTdhJRhnKVMvd//fXXDz30EMKOQlKaOEAPz5o1a8uWLbgRdvPnz0cX6skQXgpXssEJMi5pcwdBQ589e1aOQLkegCRzB119MCnWrFmDlEQET5s2raamRg8+teINx+HDh7vxAWEEJaOj4eBkeOyxx5KIHpdsTI6wpDPmGgHNsX379vb2dq1wF9rAqG0BASbRSt709SRvOfSeNPVQrfh9cSU88cQTKAM9WkuCypBRKQoA9MAPYUfICy+8UIgvAUKBGhsaGpBBVCpBs2LFimPHjvXDr3R0m8mTJ6NEpZwETdYryOrqavohjir3Cls7SWm7vEJvb2+88UaOGUIwRuXTe6irEydO7NmzR4VwKzJz5kxGodv3DFoPQGkvvfRSeEQHPS/ZmLxgSWfMtQMz2bp161B1ib8QwrRdX18fZlwczc3NYT1cU1MTEjCe1AOd5u0GTKsowh07dlApwoIQ5vgDBw5IlqWeCGbzzTff0FJZTlGnT5+Wu7gtGZVeuHAhvK0jGXN/xgfk1CHLly/XMzmy19bWUmz8TKgkVVVVsqqcYIKSQ1A5GV330EMPoURramo0jvQAMnTGjBm4H3/8cfqQqNAtq1ev5t4At16eqljC77jjDlqxaNEiVJ1MxaE0Wm25bNmy0ITLly9zVJkpDh06FBQ8FdGfSowZGKlw9ZK2DyukElDVjDJm0N4kqEDPSzYmNyTbJIwxOYH5Cd3G/Ao48CYRHSyOdnfCiRMnmDhJzEQOOMJmSdAjt3hjY0xGXrJQkS4jKJu4xgCJwyM9sivvxYsXJ0c/6I6bECVWOEfctCuUT97QaryUSe14cROClwSqiCyUhvf7bAXD1LRylWrvJF5KIy+lpX7IKwXJqCjxFDa6kiXxFEiZrUBtF6AWQqhRppKR0kgfrMVRPJoEqtUUEneCmpbqNEJKDkoIBLJrT6uIoxjrEIWDEBJTsqwiRFULMiolqAlkp0bcai/NjCsSJCBKtpGALCpcfYIXBw3BTV2yP/SPmgyhA0lZKDWBKAI1soGMko25xvDP9vcV3KFyx4/j8OHDPX/gz230kSNHPvjgg8H8fsf0D5xaelcl5syZo0dcgba2tlOnTsWnCiH79u07d+7c8OHDZ8yYEadvaWn5/PPPyy2Kh3J5Dx48GD4MJpYWLYlrbGwkY+IpvMkNb8SamppOnjxJCGXqDyROTPjtt9+eambsveuuu2igssithpCM0tZH311TrNzFldKZX331lb6OW9w5xZD+ypUreo4lKDP+RfzU6KhP6EMCKZ/mp/ot1a7i0YzbUtwJ58+fjztt1KhR5QaF/tmzZ0/JNsqkuFuEwmOTwslw6623xq2GUD7ptR+l5MVKz8lkZFyjuohRUHX06rfffquzJTWaHEMbKSGcUYJTIhWSUbK5zuHc2LZtW3yGZ7By5crf/e538d/+IGQgJR0yhUtA4ikPN14lLw2DnJxKuqFDhyauq+FOfcqUKU8//XQlp74xxhgzmOEmZNmyZW+99VbJCRq1x7RL1McffxxCnn/++bvvvnsw3w8M5Fo69Ny6devCQ3I9kJ8VvdTYXvgMphLnDqTP6QI913PAWXXp0qV+kLZ0Oxpa7vBu4sSJE7Sivr4eYcefgWK7RENDg+7OjTHGmIGFiezBBx8sp+fg5ZdfTn39h5R//vOfX3rppbAYdBAykJIO9Za9Cwkt/OyzzyYe018gHLX6JDBhwgQ0ZXV1dXt7O38GSWhX2LBhQ+IyxhhjBo62tjYmstWrV5eTH01NTfWFz2inIP3WrVuLP/85eBhISXdP4UPw2WjlhBkMPPPMMxzPdHzov3IaGhrIlXiMMcaYgePll1++dOlSufenra2tS5YsKfcJwwmF71MuWLAg8Q8yBlLSFS+mLmZqgcRjBpTx48cnrq7A3czy5csTjzHGGDNwoNjWrl2bsR6urq5u06ZN+nHCkvz2t79tbm4enK9f8/Fdura2NrqvpoAWLQ4dOjRsg2poaJgyZQohgKOpqUnhwOARO3bsWBKTceXKlSMK4EhSFEB2MMAqgcJxhwdRoV7clExRSqPnriEjZcbbsoASODOISvwFKEGmkp6MuJOITBtohSxPPR6jRVQhk4gN39wSFba9cj766CM5brjhBjmECpcZgOXqHKC906dPby98Jm3atGnEqieBXBgWjE/1HsYTGPePMcYY00O0Z/zuu++WNwUz0ZgxY1K7uVPceeedHN9//315Bxda/z4YKN4eEdi8ebO+vUTs4gK4q6uriVIufZ3ozJkzBOL9tONLVMRqg8WKwmerOIJCwgeNSBY+U6QsoQTcWlWmevUtJVlCRSdOnMBNgbIHwhetKDwEKgS07UAlY6o+3aSoDBs4yhtChL4RRS36qhNdhBf0IagK214OtVr2CFlIIFFJUAeEhHrVRrykVyyotNh4Yuk6jMcB6iuOSXShAwkBFWuMMcb0HM3g8XwUIJBYpiS5SVY834nC7DREKQcV+ZB0ELSCFAwzvRzSGYUk36NCYi2CjiEkjBNILqCo5FXJ8dhgQxjvUG/QFqRUpZQccqneWJQAIZB4CmkwI/F0lCN3tg1QrIooSqI2gKojTRzYadvLoerUjfQzudTkuChBtxAej1qxqcUhdFScRV2RSkNzOpWegozGGGOySa6Y1zfqitREBoQwwYWJnsmIZPE8FVM8YQ0S8vHiNXD77bfru2gTJkyQAwXDMBQiSzO88JM1Dz30UNjbonfkqZ/9ef755xNX4ZccE1cH1Bs+MEg5eHHce++9oUxt44jfe5YkfgFP3rlXv87PtiGmqamJovScL7Bw4ULOMxRYqKLCtpdj2bJlQ4cOpYfnzZtHkxFYR48eDUWJG264gUpvu+22xF8BbW1t9fX1cQNDl4Z3u0BzUv1jjDHGdJuweCk1kcETTzzx1FNPVfglYU1Yqc96DwZyJumKQWQAjpaWlrq6uhdffFHhlTN16lREISJj7NixiCEEB0qiL/ZkzJkzB/WDPKqpqdGCv7Cnpqs2fPbZZxyl2GL0ceMDBw7I20P0lE4PII8cOaLfPk+BsL506dKaNWtw0yjM7vTz0fqyPP3w/cq7DpTr2LFjhSRdQ3cnxhhjMkiumKaIhoaGEYUF7ok/t+Re0gG6e8qUKcuWLbv77ru1KqurIAo3b96MNEFnjBs3jtFNInoV1M/XX3+9YsUK5Mt9992Heou3O3TJhnLSZ9KkSRw7fVjYJZYuXTpr1qz29vYFCxagNZPQq9E+jA8//PDRRx/Va9ZOKflLmuE73cYYY0z/sHz58vr6+uQBQ4Fp06YRzmQtr5INfnIv6erq6uj6P/3pT6gBJHbxg6sKWbhwIXpLT6QWLVqU2oDZW4wcOXLNmjVnCj/szRHLY1VXuQ166Xz8+HF5U1Tywb8u8dZbb1VXVzc3Nz/yyCNJUAeIPPT0hg0b3n333ddeey17o1CMHjQaY4wxA8vtt98+62q0oKuqqkpeJRv85FvStbS0oKyRR5UriWIQVXoNit5aunTp/v37GcVuvMDtFCSannIhyFA/2qnwyiuvcOyqDdqAvXfvXnkDZ8+e5djr32fGKhQbDm5Z0NAKFLt27ULqrV69usIlCHDTTTdxZODCt04EndNHStoYY4wJy5lS77I+LuIvf/kL4Ug9eZUsoKl8EP4UQr4l3eeff84xHhtpGlHuLWExmzZtSlyFjRda+dgXbNu2LXEVfu4scRXokg3krS78PFdKAyHyuJ/oi4WAmKQdtUixsP0CUJ8cz507Jy99Hrq9ZP8jXlG0GInx06dP18JBwpF3NTU14S+EQJoWV2SMMcb0ED1+u3Dhgrzdo7nw868l15cPMMkipoHmTMcn5aqiz4XE6HscxJIyCer4ggaEL8ZpEyhF6c2mtiUrQZKn42MfoSjtVSZB7NXOAFC9FBj2PAdTQxrQ21LCg3kqB0JzlIajipJXu6CzbSA91hKC5QoBio0DSUOT4/6ppO0lCZYjvEKrhboXcMhyFQh0FJBFleLAnjgX4SRQo6hdxseE9BCKLXkyGGOMMd1Ak4vmzQw0DzKRJf4I5q9yUQPOoJB0dM33s/fVJHEFkqAOgtaB8Mk06SFpBaQVUiBIk0BxCEURiNqQSgMcYbAVEiAxJJ4OipNRYKpF5CIZR8KDlKFSUhbq+f7sKWdDqsb4NKKxknGEkwXBFBRYcUuLQ2RViiQuIq4xyEShKOrFjRkyYPfu3YoKxjAWahoJFALExsan/sA0jtSV+I0xxpgew+TCpBM/QSiJZsx4+gto0VSFn03tZ/wBCGO6BlcE1DAyNCjykqBZkbDSrFwX+uFxI2KaG5uS16B+QJe5cn1C86XgE39nkJ7EJe86MuDGQDcPHEtuqe47aDg9X9JgThidCYm/Z2RU1CUqPI17CGdFH1Wh0yncN+YFDKbby50M/TMopod/j1xmB+3jhmvhIybmOmf9+vXaZ16OeFtxz7ly5crx48d1q5fBE088MXr06EuXLnF1PnLkyDvvvJNE9A1akrhjxw55+59hw4YlrlLQaXv37tWv/VZC6neEK6GhoWH//v2nT59maLher1q1KonoezjB3n777XJfZPzqq6+OHTtWedszyK6oS1R4GveExsbG119/vY+qYIgTV67Ytm3bli1byp0M/TAoBv7nf/5nxIgR3ftaWWtrK5fZrVu3Jv7BRiLtjMkt3NfG7205q8OTKr3erfCRxu7duyu8OaZAaslIfKKwyrP/b7Xjtg84eiCReDrWVySePoA5vsKBziZeHtAlaF05A3TCJJ4ek1FRl5BVfXqWUnhfV5E7sk+GfhgUA1oOhHpO/BVTW1s7OF+5Cj+lM7ln9OjRCxcuTDxXM3LkyPATHZ0SbzruIdqLfZ0T7+/ua1paWnrlMVhb4dfqEo8x5hplwoQJ7777LvdvJb/MUI66uroHHnhgMP/IhCWdyT2d/oEtXbo0cZWnoaGhV95nicuXLyeu6xU01rJlyxJP33PlypXE1TOeeOKJXpGGxphBDqru1Vdf5c6zwt9bWr9+/eD/5XFLOnMdgc7gD1IL7HCENXYrV65ctGgRjmnTpoW1d01NTWPHjg2JUx9GLgd5SS81o9L07UDuBallxIgRhEyZMiVUrR/GrampUQJiSaMP8nGUAfHnnUmGl0AgNvVhwhTlKg2FEEXVJS9ShBcq+R4yxl7cJFBLARu4JlJR+I07GjVx4kQc9IMSfF9iB3ipF8p9dxDzUNgYHLouePX9QsrkSLjS49Wv96g6mQcYQy5CqAvzQnqg6hAVzCNEixEJBwXStPicia/+8elE+UloJmGIU31S7swU5SpSiAhZEn9XfsIonOqpVpTrQBwZJyGlhVxvv/12EpoJFak0YPhiL6hpGndQegyg/ELuq7wYgwNSZxfhamOM0oTmYzaoumLCuaeU5FI4hTA6OiHVLZRGYsWKUDvHcr/6Uw7soTry0qh4FCB0dQw2EBWspUYcqTEyQt/2168xdQopUYGJZ9CSvIA15lqBs7rkejKtb9OquzNnzuhrLGFfZGoJi9YAKbHctdHn/Tpd71KcgOpSVeO4ePGiCidkxYoVGANVBSgBiF1c+NnisFiQplUXvpIImEQU7VIU4I3bXrJSvJRJXhWCu2R3KYosoYsoCm+81AwLSYMDG5Q4NFntIoG8oLV0hGzfvp3Y2J4UBKouZQ9ebKZ28sqrqkVxdZhNFSo/lZ5CQhRZ4owyUm4gTdh+yJFxwasomoyXMukokqk5sQExqoV6BRnlVWz2mZlRUXFiwE6dIYm/PMEqHOTSCIZ1QhkdmHESauOz2qIew6sOzEaJqVFeSqYK8uJQCJBAFZFYDVd48NKQkmeXWiozOOIO40iaOIoq5E6BGUTpIkAWsuNVuAqkRnqSTgOiQvlAv4Vi1ZOgqGJiUyFjFFQv6XHLJLyhyXhDFCXIba55LOnMtQbXtZIahWucrsiCKx0pw5W3+EqKN0xUFBiXmUpcTCoB0wxXVblBhccTZByrvKSRlzkDb7gikzK0Qtf02Ay8wc6MSkkT9AQES1Koi+JYZqa4H3CHGTfVZNkWzAYSExLSa+6PjY9JZZc3tpmBiy0pro4EoQ+BriABLVKjQhReGhVKlpFyA22PK8VNLJbjJmXcvZJlsQEx6pxwOkkfEKLeyD4zsysqbjhuKapOkVVxV8RFletAuUuehGpX3GNSIYrtFHo7VAGpvDjiklMjJW+5syt13mJ8yEuaVMaS1uo8CR2rrpMbcMdjpIbIrfLjnoxrL0YlBxsyRiFVTqq7cMcjG4bVXNv4xau5LmhpaeG6NmnSpMRf+KVdrokElnzPMnv2bP48JkyY0NjYWFNT08Nldu+//35zc7Nei8B9991HYPwKb+TIkYmrg/BNEEV98skn8h49ehST9KLz/vvvV2BJMipdsmTJ2rVr1xdemOItt4OELmJyojq96+HIBENX6KUSeUlQbHk2If2oUaPkqJzhw4cnriFDxo4dm7hKoeGmyUnjhw7VD/hcuHBh165dOMKvQtOES5curVmzRt4UtJ2OSooYOhQ3gefOnaPt9MNDDz2kZFDJG5mQhk7QrH/q1KnsM7PTiqZOnUriF198UUMJO3funDNnjtyVEM406pUDMjqQY7mTcN++fe3t7ffee2/iHzJk/PjxiasCnn76aY4aILh8+TLnm34FG95+++358+fLXY5yZ9eIESNOnz6deApyOXEVOhCdxN+4XqTOnTu35A8q6jxZuHChXvIWrxON/xBuvvnmxFUwm2P8K+TxWGeTPQo0imMY95///OdyCOTv73//e/3xYnwl64nNNYAlnbkuKLl8PvvaqhU2Bw4c4AZXzwC6zTfffBM/JBDFPwVdCVqvM3PmzF/96ldvvvlmElqKjEqZYLibRyYyt1FamBWKefjhh5mkNctu27Ztx44dVVVV+p7Txo0by200HnA03MWPW7r688e0vfjxBrNjD38gEoI8zT4zK6kIoYmdDAdupvApU6Z0VWcXk92B5U7C8FvP3QPlwRmLPMVNFUi6Z555hlOO8xNQVLHo7BKbNm0iu85biqJMPXAV/FEgmhFA/L3TgUloEQgslN/q1at/85vf6FlaJVBd4uo62aOAAubvl3Gnr+CNN95Am4YznLsUbtWee+65cePGcfNGAoWbaxtLOnMdUXJhcsmv2nJl5+b43Xff5bLY8yWxN954Y/yQQGRMHuXgusykwuREaXPnzs3+um92pVz6mcmYLY4ePcpMUO6KTzJiN2zYQAKmWObUxYsX19fXM71hRs97po/QmJ4/f15eweQansiGte2i3FigX8+ePZt4OgiJe76v+aabbpIj+8zMrigeFKZwPevqIRkd2OlJ+O233yaurrNkyRLkKT3M/cP8+fP1uBHVwk3Fk08+qTTdgHsYBOjWrVuHDh3K+VxbWxs/l0UBI9O//vrrxx9/fN68eSV3EtC306dP/+1vf8tfTfzIrUK6p6iyT2PGHcnL3+9PChCSuktkdBgjrmCo5EceeSQJNdc0lnTmugBpwh2t7viToMI8OmvWrJK65PXXX2c67y3JwmRw5swZ7UQTzBDdEASnTp1qbm6mtMSfSUalYWMj3UKfMIlSskKKeeqppyiHKUEv1PTyi8IfeOCBQvxghIFj+Gg7TU6CCsqA9uqB66pVq8IsS5pyj5fQAUilWPA1NDTcUgA3Xde9qRo++eQTLGFWzj4zK6xIMo5BQa90+1FWTEYHZpyEt956K8c33nhD3m6AWqI3XnrpJXqAhugNNUOwc+dOqk4SdR1GjWJRP9999x1iNNZzyCPpewk7qguLHGL27NnDn8mdd96Z+Cvmtttu4xjeJneJjFHAQSAiVY0CztL46Wz4G0fYoep6uHTE5AadDcZcG2hZNKBCkqAOdhf2BzDnKWrz5s1cLsOKdcVyQacE0NLjdYWdgCtWrGA+IDFplFexYa10iosd2wBDAkKoV7VTJgUyYYcoSqb8sEAbG+K8Wg5PRhIEN5YEIylN66AVG4rKqBQHtagteoVU3F0xWBjyAm5qSTwdpMymdlWNbVQRjAkdTkq8RMmbgtYRSwPl1egEL6VpRNRSUCtCAlAJpMEwYrFZvQQylRII1+CGcvAShW046BOspQSVTGIyEq6UqpFi1XWqjqJCLTFKTF4qAsqh2NDnah39oxBqJzZ0VIUVyfLUSzqdIWRJ/FeTGjKdP2Ggy3WgkmlkSaMqqF2xJJNXLZVVpMEwvBq10LSS6MQIDcGBN9UEikqdTtlnF1ZRL0dBOKg/KZ8oGU8IFtLeQqarUIFqCHkpRFapXbjjs0h9oiYQSPmgfqYK5aWQkv2gvGFQyo0C4CXq+/YUoKsJUaWgQqgdKBPzFG6ubSzpzLUDV7EYLnNJRAdc73TpBy5z8SWVCx/pCefKiJcoLoJ4CeQqTCBXVc0rSiZKVpHEdRCu7JrICaFqvMWJ8aYK11U7QBbNkZohMAwHySituKhylQLu0A84lDgDKo3T0A8YlngKxGaHKJkq8xQlSJBqptIH4lYTm+qE4pYmrg6CAUx+aiZDmdIEpAndoqldaNyJCukJIQ0pCdS5EWAIwklCMiWISwvQA9QoY0jGoISxELSi3JkJlVQkyxNPB6QnsDgciFJ1UNzJSlOuAzWymJE6CYniSCwhJKCZlEDeoC0Ip0AaqHJKQjJKSzwFyEJg4inwvYkdpE4AGpJqGunVOZCEFsAYilXPy2COGJ+qS8gq0lAIWWgXbhKnai82hrx0UTiFCJGFqRNSFFsO5UYBkwhXVAw2EFtobtLe1ElurmGG8k+jbowxJqesXLnyV7/61dxSX42eMmXK0aNHE89A09raihIqt3ixj6irq1u4cGG8jkJmPPnkkz15nzuw0IeXL1+Otyi1tbXpV/i8v/W6xWvpjDEm3zCX79ixo6SeY+JfsGBB4hkEbNy4cfny5YmnX6AHULSxnoMxY8ZUV1drqWIeQZLOmzcv9bWakSNHjh49+q677kr85vrDks4YY3IJYmVo4Refxo0bt3r16iQ0Yv369cOGDRsk35pBhWBP6mlZP/DFF180Nzejd5uamg4WwIH3V7/6VbyfIF989dVXHGtqajgH1ChYuXLlgQMH8vvc0fQcv3g1xphc0lL4ssaIESPQcyUf0RmB7nn99de167Oqqoq+evrpp3tla/AAgoZ75ZVX9u7d297ejre2tjbX75FNr2BJZ4wxxhiTe/zi1RhjjDEm91jSGWOMMcbkHks6Y4wxxpjcY0lnjDHGGJN7LOmMMcYYY3KPJZ0xxhhjTO6xpDPGGGOMyT2WdMYYY4wxuceSzhhjjDEm91jSGWOMMcbkHks6Y4wxxpjcY0lnjDHGGJN7LOmMMcYYY3KPJZ0xxhhjTO6xpDPGGGOMyT2WdMYYY4wxuceSzhhjjDEm91jSGWOMMcbkHks6Y4wxxpjcY0lnjDHGGJNzhgz5/wFnqA4HNWZdEQAAAABJRU5ErkJggg==)
Statistical Analysis
The analysis of the infection, dissemination and transmission rates were expressed in percentages and analyzed by the Chi-square test of Trend (α = 0.05) aiming to evaluate the growth tendency or decrease of the rates. The viral titers of bodies, heads and saliva were analyzed using the Kruskal-Wallis Test (KW) and Dunn's Test for multiple comparisons (α=0.05), aiming to determine the differences in the titers according to the day of post infection. Statistical tests were applied using the BioEstat 5.3 program (Instituto Mamirauá / Pará).