Spatial and temporal evolution of family-farming land use in the Tapajós region of the Brazilian Amazon

Pressures on the Brazilian Amazon forest have been accentuated by agricultural activities practiced by families encouraged to settle in this region in the 1970s by the colonization program of the government. The aims of this study were to analyze the temporal and spatial evolution of land cover and land use (LCLU) in the lower Tapajós region, in the state of Pará. We contrast 11 watersheds that are generally representative of the colonization dynamics in the region. For this purpose, Landsat satellite images from three different years, 1986, 2001, and 2009, were analyzed with Geographic Information Systems. Individual images were subject to an unsupervised classification using the Maximum Likelihood Classification algorithm available on GRASS. The classes retained for the representation of LCLU in this study were: (1) slightly altered old-growth forest, (2) succession forest, (3) crop land and pasture, and (4) bare soil. The analysis and observation of general trends in eleven watersheds shows that LCLU is changing very rapidly. The average deforestation of old-growth forest in all the watersheds was estimated at more than 30% for the period of 1986 to 2009. The local-scale analysis of watersheds reveals the complexity of LCLU, notably in relation to large changes in the temporal and spatial evolution of watersheds. Proximity to the sprawling city of Itaituba is related to the highest rate of deforestation in two watersheds. The opening of roads such as the Transamazonian highway is associated to the second highest rate of deforestation in three watersheds.

Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.

Variação temporal do efluxo de CO2do solo em sistemas agroflorestais com palma de óleo na Amazônia Oriental

RESUMOA dinâmica do efluxo de dióxido de carbono (CO2) do solo e seus fatores controladores em sistemas agroflorestais da Amazônia são pouco compreendidas. O objetivo deste estudo foi avaliar a variação temporal do efluxo de CO2 do solo em sistemas agroflorestais onde a palma de óleo é a cultura principal e sua relação com fatores bióticos (carbono microbiano do solo, carbono total do solo, respiração microbiana do solo, raízes finas do solo, indivíduos componentes dos sistemas agroflorestais (SAFs) ) e abióticos (umidade e temperatura do solo). As medições foram realizadas nos períodos menos chuvoso (dezembro de 2010) e chuvoso (maio de 2011). O efluxo de CO2do solo foi mais alto no período chuvoso, provavelmente, devido à maior atividade microbiana nesse período influenciada por fatores climáticos aliados a fatores bióticos. O efluxo de CO2do solo se correlacionou positivamente com umidade do solo e carbono da biomassa microbiana e negativamente com temperatura do solo e quociente metabólico, porém as correlações foram fracas. O efluxo de CO2do solo foi sensível ao tipo de sistema agroflorestal e a sazonalidade da precipitação.

Exploring the role of O-Mannosylation in the modulation of E-Cadherin function in Gastric Cancer cell line models

Dissertação de mestrado em Bioquímica Aplicada – Biomedicina

Tendência temporal da esquizofrenia: um estudo realizado no âmbito hospitalar

OBJETIVO: Verificar as variações quanto a sexo, idade, número e tempo de internação em pacientes com esquizofrenia. MÉTODOS: O estudo foi realizado no Hospital Doutor João Machado, referência estadual psiquiátrica, situado em Natal/RN - Brasil, no período de 1999 a 2005. O número de casos, o tempo de internação, a idade e o sexo foram coletados. Esses dados foram analisados pela estatística descritiva e Teste de Mann-Whitney com nível de significância de 5%. RESULTADOS: Durante esse tempo, 12.732 pessoas foram internadas. Os portadores de esquizofrenia corresponderam a 35,35% (4.501). A permanência no hospital foi de 44,33 ± 36,9 dias, diferente daquela observada nos não-portadores de esquizofrenia, 29,5 ± 61,6 dias (p < 0,0001). A idade média foi de 38,7 ± 13,5 anos, sendo a maioria dos pacientes do sexo masculino (65,78%). Em 1999, de cada 100 internados, 39,8 eram portadores de esquizofrênia; em 2005 essa proporção reduziu-se para 30,1. A esquizofrenia paranóide foi a mais freqüente, ocorrendo em 1.829 (40%) dos pacientes durante o período. CONCLUSÕES: O estudo aponta uma tendência à redução no número de doentes internados com esquizofrenia, bem como uma diminuição no tempo de internação.

Evaluating biomaterial-and microfluidic-based 3D tumor models

Cancer is a major cause of morbidity and mortality worldwide, with a disease burden estimated to increase in the coming decades. Disease heterogeneity and limited information on cancer biology and disease mechanisms are aspects that 2D cell cultures fail to address. We review the current "state-of-the-art" in 3D Tissue Engineering (TE) models developed for and used in cancer research. Scaffold-based TE models and microfluidics, are assessed for their potential to fill the gap between 2D models and clinical application. Recent advances in combining the principles of 3D TE models and microfluidics are discussed, with a special focus on biomaterials and the most promising chip-based 3D models.

Pervasive patient timeline

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

High-aspect-ratio tridimensional electrode arrays for neural applications

Tese de Doutoramento em Engenharia Biomédica.

Single line for assembly just-in-sequence multiple models

Programa Doutoral em Líderes para as Indústrias Tecnológicas

A bio-inspired computational model for motion detection

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Uso do procedimento de bissecção temporal na avaliação de idosos com doença de Alzheimer: uma revisão sistemática

OBJETIVO: Realizar revisão sistemática de artigos que utilizaram o método de bissecção, para avaliar a percepção de tempo em idosos com doença de Alzheimer e analisar seus parâmetros. MÉTODO: As buscas dos artigos foram conduzidas no período de março a maio de 2011, nas seguintes bases de dados: Web of Science, Science Direct on Line, Biological Abstracts, PsychoInfo e Medline. As palavras-chave e operadores booleanos foram: "interval timing" ou "perception of time" ou "time discrimination" ou "reproduction of time" e "Alzheimer's disease". Também foram realizadas buscas manuais nas referências dos artigos selecionados. RESULTADOS: Quatro artigos contemplavam todos os critérios de inclusão, nos quais foram encontradas grandes variações nos parâmetros utilizados no método. CONCLUSÃO: Pacientes com doença de Alzheimer apresentam prejuízos nas tarefas de bissecção de tempo, que podem ser explicados pelo declínio gradual nas habilidades que são utilizadas no teste de percepção de tempo. Há grandes variações nos intervalos de tempo utilizados. Neste contexto, há necessidade de mais estudos, controlados e randomizados, para investigar potenciais efeitos das variações nos intervalos de tempo do método de bissecção. Os resultados de tais estudos poderão contribuir para o estabelecimento de parâmetros mais adequados e fidedignos.

Metabolic engineering with multi-objective optimization of kinetic models

Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.

Development of computational and experimental methods for biomass composition and evaluation of its impact in genome-scale models prediction

The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.

Predicting SO2 pollution incidents by means of additive models with optimum variable selection

The aim of this paper is to predict time series of SO2 concentrations emitted by coal-fired power stations in order to estimate in advance emission episodes and analyze the influence of some meteorological variables in the prediction. An emission episode is said to occur when the series of bi-hourly means of SO2 is greater than a specific level. For coal-fired power stations it is essential to predict emission epi- sodes sufficiently in advance so appropriate preventive measures can be taken. We proposed a meth- odology to predict SO2 emission episodes based on using an additive model and an algorithm for variable selection. The methodology was applied to the estimation of SO2 emissions registered in sampling lo- cations near a coal-fired power station located in Northern Spain. The results obtained indicate a good performance of the model considering only two terms of the time series and that the inclusion of the meteorological variables in the model is not significant.

Investigations on relational control of time perception

Tese de Doutoramento em Psicologia Básica