Visual search for normal color and dichromatic observers using a unique distracter color

It is well known that color coding facilitates search and iden- tification in real-life tasks. The aim of this work was to compare reac- tion times for normal color and dichromatic observers in a visual search experiment. A unique distracter color was used to avoid abnormal color vision vulnerability to background complexity. Reaction times for nor- mal color observers and dichromats were estimated for 2◦ central vision at 48 directions around a white point in CIE L∗a∗b∗ color space for systematic examination on the mechanisms of dichromatic color percep- tion. The results show that mean search times for dichromats were twice larger compared to the normal color observers and for all directions. The difference between the copunctual confusion lines and the confusion direction measure experimentally was 5.5◦ for protanopes and 7.5◦ for deuteranopes.

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)

Multithreading RTOS processor design

Tese de Doutoramento Plano Doutoral em Engenharia Eletrónica e de Computadores.

Algorithms and computational tools for metabolic flux analysis

PhD thesis in Biomedical Engineering

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.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

FISHji: new ImageJ macros for the quantification of fluorescence in epifluorescence images

Fluorescence in situ hybridization (FISH) is based on the use of fluorescent staining dyes, however, the signal intensity of the images obtained by microscopy is seldom quantified with accuracy by the researcher. The development of innovative digital image processing programs and tools has been trying to overcome this problem, however, the determination of fluorescent intensity in microscopy images still has issues due to the lack of precision in the results and the complexity of existing software. This work presents FISHji, a set of new ImageJ methods for automated quantification of fluorescence in images obtained by epifluorescence microscopy. To validate the methods, results obtained by FISHji were compared with results obtained by flow cytometry. The mean correlation between FISHji and flow cytometry was high and significant, showing that the imaging methods are able to accurately assess the signal intensity of fluorescence images. FISHji are available for non-commercial use at http://paginas.fe.up.pt/nazevedo/.

New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking

During must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of most-correlated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains.

Tradução e validação para o português do Medication Regimen Complexity Index

FUNDAMENTO: A complexidade da farmacoterapia consiste de múltiplas características do regime prescrito, incluindo o número de diferentes medicações no esquema, o número de unidades de dosagem por dose, o número total de doses por dia e os cuidados na administração dos medicamentos. O Medication Regimen Complexity Index (MRCI) é um instrumento específico, validado e utilizado para medir a complexidade da farmacoterapia, desenvolvido originalmente em língua inglesa. OBJETIVO: Tradução transcultural e validação desse instrumento para o português do Brasil. MÉTODOS: Foi desenvolvido um estudo transversal envolvendo 95 pacientes com diabete do tipo 2 utilizando múltiplas medicações. O processo de validação teve início pela tradução, retrotradução e pré-teste do instrumento, gerando uma versão adaptada chamada Índice de Complexidade da Farmacoterapia (ICFT). Em seguida foram analisados parâmetros psicométricos, incluindo validade convergente, validade divergente, confiabilidade entre avaliadores e teste-reteste. RESULTADOS: A complexidade da farmacoterapia medida pelo ICFT obteve média de 15,7 pontos (desvio padrão = 8,36). O ICFT mostrou correlação significativa com o número de medicamentos em uso (r = 0,86; p < 0,001) e a idade dos pacientes (r = 0,28; p = 0,005). A confiabilidade entre avaliadores obteve correlação intraclasse igual a 0,99 (p < 0,001) e a confiabilidade teste-reteste obteve correlação de 0,997 (p < 0,001). CONCLUSÃO: Os resultados demonstraram que o ICFT apresenta bom desempenho de validade e confiabilidade, podendo ser utilizado como ferramenta útil na prática clínica e em pesquisas envolvendo análise da complexidade da terapia.

Estrategias estadístico-computacionales avanzadas para análisis de expresión de proteínas/genes en cáncer. Advanced statistical and computational strategies for protein/gene expression analysis in cancer.

El objetivo de este proyecto, enmarcado en el área de metodología de análisis en bioingeniería-biotecnología aplicadas al estudio del cancer, es el análisis y caracterización a través modelos estadísticos con efectos mixtos y técnicas de aprendizaje automático, de perfiles de expresión de proteínas y genes de las vías metabolicas asociadas a progresión tumoral. Dicho estudio se llevará a cabo mediante la utilización de tecnologías de alto rendimiento. Las mismas permiten evaluar miles de genes/proteínas en forma simultánea, generando así una gran cantidad de datos de expresión. Se hipotetiza que para un análisis e interpretación de la información subyacente, caracterizada por su abundancia y complejidad, podría realizarse mediante técnicas estadístico-computacionales eficientes en el contexto de modelos mixtos y técnias de aprendizaje automático. Para que el análisis sea efectivo es necesario contemplar los efectos ocasionados por los diferentes factores experimentales ajenos al fenómeno biológico bajo estudio. Estos efectos pueden enmascarar la información subycente y así perder informacion relavante en el contexto de progresión tumoral. La identificación de estos efectos permitirá obtener, eficientemente, los perfiles de expresión molecular que podrían permitir el desarrollo de métodos de diagnóstico basados en ellos. Con este trabajo se espera poner a disposición de investigadores de nuestro medio, herramientas y procedimientos de análisis que maximicen la eficiencia en el uso de los recursos asignados a la masiva captura de datos genómicos/proteómicos que permitan extraer información biológica relevante pertinente al análisis, clasificación o predicción de cáncer, el diseño de tratamientos y terapias específicos y el mejoramiento de los métodos de detección como así tambien aportar al entendimieto de la progresión tumoral mediante análisis computacional intensivo.

Flame simulation in rotary kilns using computational fluid dynamics

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2011

Variations and application conditions of the data type "Image" : the foundation of computational visualistics

Visualistics, computer science, picture syntax, picture semantics, picture pragmatics, interactive pictures

Analysis of complex microwave structures using suitable computational electromagnetic techniques

Complex Microwave Structures Wake Field Computatation PETRA III Generalized Multipole Technique Antenna Antennen Wakefelder Berechnung

Forearm surface EMG signals recognition and muscoloskeletal system dynamics identification using intelligent computational methods

Biosignals processing, Biological Nonlinear and time-varying systems identification, Electomyograph signals recognition, Pattern classification, Fuzzy logic and neural networks methods