Aspectos evolucionários das unidades de produção camponesas do território Manaus e entorno

Nesta tese, aborda-se os processos de mudança e diversificação dos sistemas produtivos camponeses localizados em uma parte do Território Manaus e Entorno. O objetivo da pesquisa é a compreensão dos processos de mudança econômica e tecnológica em curso nestes sistemas produtivos. A abordagem do tema é realizada através de uma estrutura analítica multidisciplinar envolvendo conceito da teoria econômica evolucionária, da teoria do desenvolvimento endógeno, da antropologia econômica e da teoria do investimento camponês. Os resultados encontrados revelam que os sistemas produtivos estudados são diversificados em relação aos territórios onde ocorrem. Essa diversificação decorre do modo como os produtores camponeses adaptam seus sistemas produtivos alterando as rotinas de trabalho que os constituem em função das injunções provenientes do ambiente institucional complexo e da dinâmica dos ecossistemas. Tais adaptações são orientadas pelas características socioculturais inerentes às famílias camponesas e motivadas pela busca da eficiência reprodutiva. Ao final, os dados da pesquisa de campo são processados através da Análise Fatorial, revelando diferenciações de trajetórias de sistemas produtivos semelhantes em territórios distintos, bem como agrupamentos que posicionam os produtores camponeses entre situações de integração ao mercado e subsistência subsidiada por benefícios sociais e previdenciários. Esses resultados evidenciam a complexidade da socioeconomia camponesa e suas diversas estratégias de inovação adaptativa.

Inversão de dados sísmicos de reflexão a partir da curva do tempo de trânsito

A presente Dissertação de Mestrado tem como objetivo o estudo do problema de inversão sísmica baseada em refletores planos para arranjo fonte-comum (FC) e ponto-médiocomum (PMC). O modelo direto é descrito por camadas homogêneas, isotrópicas com interfaces plano-horizontais. O problema é relacionado ao empilhamento NMO baseado na otimização da função semblance, para seções PMC corrigidas de sobretempo normal (NMO). O estudo foi baseado em dois princípios. O primeiro princípio adotado foi de combinar dois grupos de métodos de inversão: um Método Global e um Método Local. O segundo princípio adotado foi o de cascata, segundo a teoria Wichert-Herglotz-Bateman, que estabelece que para conhecer uma camada inferior tem-se que conhecer primeiro a camada superior (dissecação). A aplicação do estudo é voltada à simulação sísmica de Bacia Sedimentar do Solimões e de Bacia Marinha para se obter uma distribuição local 1D de velocidades e espessuras para a subsuperfície em horizontes alvo. Sendo assim, limitamos a inversão entre 4 e 11 refletores, uma vez que na prática a indústria limita uma interpretação realizada apenas em número equivalente de 3 a 4 refletores principais. Ressalta-se que este modelo é aplicável como condição inicial ao imageamento de seções sísmicas em regiões geologicamente complexas com variação horizontal suave de velocidades. Os dados sintéticos foram gerados a partir dos modelos relacionados a informações geológicas, o que corresponde a uma forte informação a priori no modelo de inversão. Para a construção dos modelos relacionados aos projetos da Rede Risco Exploratório (FINEP) e de formação de recursos humanos da ANP em andamento, analisamos os seguintes assuntos relevantes: (1) Geologia de bacias sedimentares terrestre dos Solimões e ma rinha (estratigráfica, estrutural, tectônica e petrolífera); (2) Física da resolução vertical e horizontal; e (3) Discretização temporal-espacial no cubo de multi-cobertura. O processo de inversão é dependente do efeito da discretização tempo-espacial do campo de ondas, dos parâmetros físicos do levantamento sísmico, e da posterior reamostragem no cubo de cobertura múltipla. O modelo direto empregado corresponde ao caso do operador do empilhamento NMO (1D), considerando uma topografia de observação plana. O critério básico tomado como referência para a inversão e o ajuste de curvas é a norma 2 (quadrática). A inversão usando o presente modelo simples é computacionalmente atrativa por ser rápida, e conveniente por permitir que vários outros recursos possam ser incluídos com interpretação física lógica; por exemplo, a Zona de Fresnel Projetada (ZFP), cálculo direto da divergência esférica, inversão Dix, inversão linear por reparametrização, informações a priori, regularização. A ZFP mostra ser um conceito út il para estabelecer a abertura da janela espacial da inversão na seção tempo-distância, e representa a influência dos dados na resolução horizontal. A estimativa da ZFP indica uma abertura mínima com base num modelo adotado, e atualizável. A divergência esférica é uma função suave, e tem base física para ser usada na definição da matriz ponderação dos dados em métodos de inversão tomográfica. A necessidade de robustez na inversão pode ser analisada em seções sísmicas (FC, PMC) submetida a filtragens (freqüências de cantos: 5;15;75;85; banda-passante trapezoidal), onde se pode identificar, comparar e interpretar as informações contidas. A partir das seções, concluímos que os dados são contaminados com pontos isolados, o que propõe métodos na classe dos considerados robustos, tendo-se como referência a norma 2 (quadrados- mínimos) de ajuste de curvas. Os algoritmos foram desenvolvidos na linguagem de programação FORTRAN 90/95, usando o programa MATLAB para apresentação de resultados, e o sistema CWP/SU para modelagem sísmica sintética, marcação de eventos e apresentação de resultados.

Geração e otimização de trajetórias de um manipulador robótico utilizando algoritmos genéticos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliação da variabilidade genética em uma população base de Eucalyptus camaldulensis Dehnh para fins de conservação e melhoramento genético

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Jet and underlying event properties as a function of charged-particle multiplicity in proton-proton collisions at root s=7 TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Performance evaluation of multi-stage filtration with use of granular activated carbon and synthetic non-woven fabrics

The multi stage filtration (MSF) is an alternative that permits to enlarge the spectrum of application of the slow sand filtration as for the effluent quality and run duration. In this research the use of MSF technology associated to a granular activated carbon (GAC) column as polishing mechanism of the final effluent was evaluated; in the slow sand filters GAC was used as an intermediate layer and non-woven synthetic fabrics were utilized as a first layer of the filter media. Five different tests were conducted, where the systems subjected to the treatment were: water from the Ipe Lake (Ilha Solteira, Sao Paulo, Brazil); water from the lake with water from a recreational fish pond; water from the lake with a phytoplankton and cyanobacteria overload simulation, with and without the use of the pre-filters as a stage of the treatment. The synthetic fabrics and GAC use resulted in the best turbidity removal and an efficient apparent and true color removal; in spite that the polishing columns reported similar results for those parameters. The utilization of GAC as an intermediate layer contributed to a better organic matter removal and the fabrics improved chlorophyll-a removal. The pre-filtration columns made an efficient algae and cyanobacteria removal, a function that was completed by the filters and reached >98% efficiency. The synthetic non-woven fabrics and GAC inclusion in MSF operation improved performance of this technology with ease of application and operation.

Diastolic function and functional capacity after a single session of continuous positive airway pressure in patients with compensated heart failure

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A Spatial and Temporal Prediction Model of Corn Grain Yield as a Function of Soil Attributes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estimates of genetic parameters for total milk yield over multiple ages in Brazilian Murrah buffaloes using different models

The objective of this study was to estimate variance components and genetic parameters for accumulated 305-day milk yield (MY305) over multiple ages, from 24 to 120 months of age, applying random regression (RRM), repeatability (REP) and multi-trait (MT) models. A total of 4472 lactation records from 1882 buffaloes of the Murrah breed were utilized. The contemporary group (herd-year-calving season) and number of milkings (two levels) were considered as fixed effects in all models. For REP and RRM, additive genetic, permanent environmental and residual effects were included as random effects. MT considered the same random effects as did REP and RRM with the exception of permanent environmental effect. Residual variances were modeled by a step function with 1, 4, and 6 classes. The heritabilities estimated with RRM increased with age, ranging from 0.19 to 0.34, and were slightly higher than that obtained with the REP model. For the MT model, heritability estimates ranged from 0.20 (37 months of age) to 0.32 (94 months of age). The genetic correlation estimates for MY305 obtained by RRM (L23.res4) and MT models were very similar, and varied from 0.77 to 0.99 and from 0.77 to 0.99, respectively. The rank correlation between breeding values for MY305 at different ages predicted by REP, MT, and RRM were high. It seems that a linear and quadratic Legendre polynomial to model the additive genetic and animal permanent environmental effects, respectively, may be sufficient to explain more parsimoniously the changes in MY305 genetic variation with age.

Obesity Preserves Myocardial Function During Blockade of the Glycolytic Pathway

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A new probabilistic canopy dynamics model (SLCD) that is suitable for evergreen and deciduous forest ecosystems

There are strong uncertainties regarding LAI dynamics in forest ecosystems in response to climate change. While empirical growth & yield models (G&YMs) provide good estimations of tree growth at the stand level on a yearly to decennial scale, process-based models (PBMs) use LAI dynamics as a key variable for enabling the accurate prediction of tree growth over short time scales. Bridging the gap between PBMs and G&YMs could improve the prediction of forest growth and, therefore, carbon, water and nutrient fluxes by combining modeling approaches at the stand level.Our study aimed to estimate monthly changes of leaf area in response to climate variations from sparse measurements of foliage area and biomass. A leaf population probabilistic model (SLCD) was designed to simulate foliage renewal. The leaf population was distributed in monthly cohorts, and the total population size was limited depending on forest age and productivity. Foliage dynamics were driven by a foliation function and the probabilities ruling leaf aging or fall. Their formulation depends on the forest environment.The model was applied to three tree species growing under contrasting climates and soil types. In tropical Brazilian evergreen broadleaf eucalypt plantations, the phenology was described using 8 parameters. A multi-objective evolutionary algorithm method (MOEA) was used to fit the model parameters on litterfall and LAI data over an entire stand rotation. Field measurements from a second eucalypt stand were used to validate the model. Seasonal LAI changes were accurately rendered for both sites (R-2 = 0.898 adjustment, R-2 = 0.698 validation). Litterfall production was correctly simulated (R-2 = 0.562, R-2 = 0.4018 validation) and may be improved by using additional validation data in future work. In two French temperate deciduous forests (beech and oak), we adapted phenological sub-modules of the CASTANEA model to simulate canopy dynamics, and SLCD was validated using LAI measurements. The phenological patterns were simulated with good accuracy in the two cases studied. However, IA/max was not accurately simulated in the beech forest, and further improvement is required.Our probabilistic approach is expected to contribute to improving predictions of LAI dynamics. The model formalism is general and suitable to broadleaf forests for a large range of ecological conditions. (C) 2014 Elsevier B.V. All rights reserved.

Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

Double-objective economic statistical design of the VP T-2 control chart: Wald's identity approach

Research has shown that applying the T-2 control chart by using a variable parameters (VP) scheme yields rapid detection of out-of-control states. In this paper, the problem of economic statistical design of the VP T-2 control chart is considered as a double-objective minimization problem with the statistical objective being the adjusted average time to signal and the economic objective being expected cost per hour. We then find the Pareto-optimal designs in which the two objectives are met simultaneously by using a multi-objective genetic algorithm. Through an illustrative example, we show that relatively large benefits can be achieved by applying the VP scheme when compared with usual schemes, and in addition, the multi-objective approach provides the user with designs that are flexible and adaptive.

Áreas prioritárias para conservação e restauração da paisagem utilizando multi-caminhos e informações de avifauna

Habitat loss and fragmentation of landscapes endanger the planet’s biodiversity. Strategies for identify priority areas for conservation and restoration of biodiversity rich areas becomes essential for the planning of the management of these landscape become successful. This study aims to propose a novel, transparent and replicable method for choosing priority areas for restoration, and includes the following steps: (a) identification of regional biodiversity hotspots for conservation; (b) identification of priority areas for restoration with the greatest potential to increase the connectivity of the fragments already existing; (c) estimate the potential richness of understory birds before and after restoration, analyzing the gain of species for the future scenario. In order to identify the corridors to be restored in a future scenario we considered the approach of multiple corridors, which aimed to connect the main fragments within the region through analysis of multi-paths. Already existing regression models were applied to estimate the richness of the landscape considering three models: a) species richness as a function of patch area of the fragment selected as hotspots; b) richness as a function of areas connected by structural corridors and c) connected area for species which are able to access nearby fragments within 20m. The gain of species for future scenario which consider the potential restoration of selected areas was estimated. Based on our results we observed that species that use corridors showed the highest increment of species richness of understory birds. As a result it had to restore corridors to model species with the ability to use forest corridors was the highest gain potential species richness of understory birds. The methods proposed method in this study appears provide new ways to ensures a better cost / benefit relationship for restoration projects by increasing the chances of better reach high levels of...

Influências multi-escala da paisagem e limiar da fragmentação em morcegos no cerrado

Pós-graduação em Ciências Biológicas (Zoologia) - IBRC