Contemporaneidades na governança do Programa Bolsa Família : uma análise à luz do Índice de Gestão Descentralizada-Municipal (IGD-M)

O presente trabalho tem como intuito analisar o modelo de gestão do Programa Bolsa Família (PBF) com foco em um dos seus principais instrumentos de gerenciamento: o Índice de Gestão Descentralizada-Municipal (IGD-M). Dado que a gestão do PBF está concentrada na relação direta entre União e municípios, houve a necessidade do estabelecimento, por parte da primeira, de um índice que ao mesmo tempo gerenciasse e fiscalizasse o programa. Nessa perspectiva, argumenta-se que o IGD-M reflete características contemporâneas de reforma na gestão pública. Destarte, foi realizada uma análise através de pesquisa bibliográfica e documental, de cunho qualitativo, para se demonstrar aspectos da atual gestão pública advindas dessas reformas. Os resultados obtidos demonstram que o IGD-M contribui para: i) maior descentralização da gestão para os municípios; ii) o desenvolvimento da intersetorialidade – que é a maior cooperação entre os atores envolvidos no processo de descentralização; iii) as condicionalidades (que remetem aos debates entre universalização e focalização), ensejando regras para os grupos de beneficiários; iv) a transparência pública, que condiz com a maior publicidade da gestão do programa; e v) o controle social, para tentar diminuir a pobreza e extrema pobreza do país, com maior grau de accountability. Com a criação do IGD-M pelo Ministério do Desenvolvimento Social e Combate à Fome (MDS), pôde-se estabelecer uma gestão mais transparente do PBF, uma vez que o índice remete a diferentes características da gestão pública contemporânea, dentre elas o estabelecimento de um incentivo fiscal para os municípios que cumprirem as regras estabelecidas pelo IGD-M.

Investigação numérica do desempenho de um sensor de fibra ótica de índice de refração, baseado em SPR e utilizando COMSOL multiphysics

Esta tese é dedicada aos sensores de fibra ótica especificamente aos sensores baseados no fenómeno de ressonância de plasmão de superfície, SPR (Surface Plasmon Resonance), gerados em fibras óticas com configuração do tipo “D”, para aplicação em sensores refratométricos. Numa primeira parte desta dissertação são descritos os aspetos teóricos fundamentais para a compreensão dos fenómenos de ressonância de plasmões de superfície e a sua utilização em sistemas sensores. Estes fenómenos ocorrem na superfície de interface entre metais e outros meios materiais, sendo capazes de afetar as propriedades em reflexão e transmissão de uma onda eletromagnética incidente (feixe luminoso), de uma forma que é fortemente dependente dos meios na proximidade do metal. Assim, a medição das propriedades do feixe luminoso, como por exemplo o comprimento de onda de ressonância com SPR, permite monitorizar esses meios. Numa segunda fase foi implementada a simulação destes modelos, em COMSOL Multiphysics, que permitia não só a obtenção dos espetros de transmissão dos fenómenos de ressonância de plasmões de superfície, mas também a obtenção das distribuições do campo elétrico e magnético em função das dimensões do sensor. O COMSOL permitiu também a obtenção das curvas do deslocamento do comprimento de onda ressonante, perante variações do índice de refração exterior, da espessura do metal, da espessura da bainha e da espessura de outro elemento de elevado índice de refração. A fase seguinte foi verificar que os resultados dos métodos teóricos para os diferentes parâmetros de estudo eram semelhantes aos resultados obtidos no COMSOL. Conclui-se que com este programa é possível criar novos sensores em fibra ótica, baseados em SPR, para melhorar e otimizar os parâmetros de ressonância e sensibilidade do sensor. A última fase do trabalho baseou-se na modelização de uma fibra cuja configuração seja tal que possa criar um pequeno efeito de antena e fazer com que parte da luz seja guiada para o exterior da fibra e possa interatuar com o meio externo para melhor sensibilidade.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Estado nutricional e efeito da vitamina A na resposta imune frente à infecção por Leishmania Infantum

Nutritional status is an important determinant to the response against Leishmania infection, although few studies have characterized the molecular basis for the association found between malnutrition and the disease. Vitamin A supplementation has long been used in developing countries to prevent mortality by diarrheal and respiratory diseases, but there are no studies on the role of vitamin A in Leishmania infection, although we and others have found vitamin A deficiency in visceral Leishmaniasis (VL). Regulatory T cells are induced in vitro by vitamin A metabolites and are considered important cells implicated T CD4+ cell suppression in human VL. This work aimed to examine the correlation of nutritional status and the effect of vitamin A in the response against Leishmania infantum infection. A total of 179 children were studied: 31 had active VL, 33 VL history, 44 were DTH+ and 71 were DTH- and had negative antibody to Leishmania (DTH-/Ac-). Peripheral blood monuclear cells were isolated in a subgroup of 10 active VL and 16 DTH-/Ac- children and cultivated for 20h under 5 different conditions: 1) Medium, 2) Soluble promastigote L. infantum antigens (SLA), 3) All-trans retinoic acid (ATRA), 4) SLA + ATRA and 5) Concanavalin A. T CD4+CD25highFoxp3+, T CD4+CD25-Foxp3- and CD14+ monocytes were stained and studied by flow cytometry for IL-10, TGF-β and IL-17 production. Nutritional status was compromised in VL children, which presented lower BMI/Age and retinol concentrations when compared to healthy controls. We found a negative correlation between nutritional status (measured by BMI/Age and serum retinol) and anti-Leishmania antibodies and acute phase proteins. There was no correlation between nutritional status and parasite load. ATRA presented a dual effect in Treg cells and monocytes: In healthy children (DTH-/Ac-), it induced a regulatory response, increasing IL-10 and TGF-β production; in VL children it modulated the immune response, preventing increased IL-10 production after SLA stimulation. Furthermore, we found a positive correlation between BMI/Age and IL-17 production and negative correlation between serum retinol and IL-10 and TGF-β production in T CD4+CD25highFoxp3+ cells after SLA stimulus. Our results show a potential dual role of vitamin A in the immune system: improvement of regulatory profile during homeostasis and down modulation of IL-10 in Treg cells and monocytes during symptomatic VL. Therefore, the use of vitamin A concomitant to VL therapy might improve recovery from disease status in Leishmania infantum infection

Otimização de vazão de poços injetores em projeto de injeção de água utilizando simulação por linhas de fluxo

Until the early 90s, the simulation of fluid flow in oil reservoir basically used the numerical technique of finite differences. Since then, there was a big development in simulation technology based on streamlines, so that nowadays it is being used in several cases and it can represent the physical mechanisms that influence the fluid flow, such as compressibility, capillarity and gravitational segregation. Streamline-based flow simulation is a tool that can help enough in waterflood project management, because it provides important information not available through traditional simulation of finite differences and shows, in a direct way, the influence between injector well and producer well. This work presents the application of a methodology published in literature for optimizing water injection projects in modeling of a Brazilian Potiguar Basin reservoir that has a large number of wells. This methodology considers changes of injection well rates over time, based on information available through streamline simulation. This methodology reduces injection rates in wells of lower efficiency and increases injection rates in more efficient wells. In the proposed model, the methodology was effective. The optimized alternatives presented higher oil recovery associated with a lower water injection volume. This shows better efficiency and, consequently, reduction in costs. Considering the wide use of the water injection in oil fields, the positive outcome of the modeling is important, because it shows a case study of increasing of oil recovery achieved simply through better distribution of water injection rates