Diffusional kurtosis imaging using a fast heuristic constrained linear least squares algorithm: a plugin for OsiriX

Diffusion Kurtosis Imaging (DKI) is a fairly new magnetic resonance imag-ing (MRI) technique that tackles the non-gaussian motion of water in biological tissues by taking into account the restrictions imposed by tissue microstructure, which are not considered in Diffusion Tensor Imaging (DTI), where the water diffusion is considered purely gaussian. As a result DKI provides more accurate information on biological structures and is able to detect important abnormalities which are not visible in standard DTI analysis. This work regards the development of a tool for DKI computation to be implemented as an OsiriX plugin. Thus, as OsiriX runs under Mac OS X, the pro-gram is written in Objective-C and also makes use of Apple’s Cocoa framework. The whole program is developed in the Xcode integrated development environ-ment (IDE). The plugin implements a fast heuristic constrained linear least squares al-gorithm (CLLS-H) for estimating the diffusion and kurtosis tensors, and offers the user the possibility to choose which maps are to be generated for not only standard DTI quantities such as Mean Diffusion (MD), Radial Diffusion (RD), Axial Diffusion (AD) and Fractional Anisotropy (FA), but also DKI metrics, Mean Kurtosis (MK), Radial Kurtosis (RK) and Axial Kurtosis (AK).The plugin was subjected to both a qualitative and a semi-quantitative analysis which yielded convincing results. A more accurate validation pro-cess is still being developed, after which, and with some few minor adjust-ments the plugin shall become a valid option for DKI computation

A new least-squares approach to differintegration modeling

Signal Processing, Vol. 86, nº 10

Optimization of multi-stage amplifiers in deep-submicron CMOS using a distributed/parallel genetic algorithm

IEEE International Symposium on Circuits and Systems, pp. 724 – 727, Seattle, EUA

Partial Least Square – Path Modeling: metodologia, software e aplicação

Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

Modelação estatística das co-infecções da SIDA em países da União Europeia

Dissertação apresentada para obtenção do Grau de Doutor em Matemática, especialidade de Estatística, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Determinantes da satisfação dos estudantes de primeiro ciclo de estudos na Universidade Nova de Lisboa

Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Desenvolvimento de métodos de espetroscopia NIR. Quantificação de grupos hidróxilo em polímeros

O objetivo deste estudo é o desenvolvimento e validação de métodos espectroscópicos (espectroscopia NIR) que possam vir a substituir os métodos químicos convencionais, para quantificação de grupos hidróxilo em resinas alquídicas. As resinas alquídicas estudadas neste trabalho são normalmente utilizadas em sistemas de revestimento de dois componentes, em que os seus grupos hidróxilo reagem com pré-polímeros de isocianato para formar revestimentos de alta dureza. Por este motivo e por questões processuais ligadas à estequiometria da reação existente na aplicação referida, é extremamente importante a quantificação destes grupos. O método mais comum de quantificação de grupos hidróxilo é conhecido como método de titulação. Este é um método demorado, pois cada medição implica um procedimento experimental de cerca de duas horas, para além de ser muito dispendioso, a nível económico. Foram estudadas as influências da temperatura, heterogeneidade e nível de enchimento da célula na recolha do espectro. As conclusões dos estudos mencionados levaram à fixação de um tempo ideal de permanência da célula dentro da câmara do espectrofotómetro antes da medição do espectro. Para além disto, conclui-se que para lotes standard, a heterogeneidade não é uma variável significativa. O nível da célula deve ser mantido constante. Os métodos desenvolvidos, baseados na norma de qualidade ISO 15063:2011, foram construídos a partir de algoritmos de Partial Least Squares Regression (PLS), utilizando um equipamento NIRVIS, Büchi©. Foram obtidos bons coeficientes de regressão linear para a Resina A (R2>0,9). Quanto aos restantes resultados, estes indicam a possibilidade de aplicação em resinas do mesmo tipo. Este método proporciona resultados 8 vezes mais rápidos e com custos em material que representam 1% do método standard.

Desenvolvimento de métodos de espetroscopia NIR. Quantificação de grupos hidróxilo em polímeros

O objetivo deste estudo é o desenvolvimento e validação de métodos espectroscópicos (espectroscopia NIR) que possam vir a substituir os métodos químicos convencionais, para quantificação de grupos hidróxilo em resinas alquídicas. As resinas alquídicas estudadas neste trabalho são normalmente utilizadas em sistemas de revestimento de dois componentes, em que os seus grupos hidróxilo reagem com pré-polímeros de isocianato para formar revestimentos de alta dureza. Por este motivo e por questões processuais ligadas à estequiometria da reação existente na aplicação referida, é extremamente importante a quantificação destes grupos. O método mais comum de quantificação de grupos hidróxilo é conhecido como método de titulação. Este é um método demorado, pois cada medição implica um procedimento experimental de cerca de duas horas, para além de ser muito dispendioso, a nível económico. Foram estudadas as influências da temperatura, heterogeneidade e nível de enchimento da célula na recolha do espectro. As conclusões dos estudos mencionados levaram à fixação de um tempo ideal de permanência da célula dentro da câmara do espectrofotómetro antes da medição do espectro. Para além disto, conclui-se que para lotes standard, a heterogeneidade não é uma variável significativa. O nível da célula deve ser mantido constante. Os métodos desenvolvidos, baseados na norma de qualidade ISO 15063:2011, foram construídos a partir de algoritmos de Partial Least Squares Regression (PLS), utilizando um equipamento NIRVIS, Büchi©. Foram obtidos bons coeficientes de regressão linear para a Resina A (R2>0,9). Quanto aos restantes resultados, estes indicam a possibilidade de aplicação em resinas do mesmo tipo. Este método proporciona resultados 8 vezes mais rápidos e com custos em material que representam 1% do método standard.

Development of process control strategies exploiting knowledge from systems biology: application to MDCK suspension cells

Madine Darby Canine Kidney (MDCK) cell lines have been extensively evaluated for their potential as host cells for influenza vaccine production. Recent studies allowed the cultivation of these cells in a fully defined medium and in suspension. However, reaching high cell densities in animal cell cultures still remains a challenge. To address this shortcoming, a combined methodology allied with knowledge from systems biology was reported to study the impact of the cell environment on the flux distribution. An optimization of the medium composition was proposed for both a batch and a continuous system in order to reach higher cell densities. To obtain insight into the metabolic activity of these cells, a detailed metabolic model previously developed by Wahl A. et. al was used. The experimental data of four cultivations of MDCK suspension cells, grown under different conditions and used in this work came from the Max Planck Institute, Magdeburg, Germany. Classical metabolic flux analysis (MFA) was used to estimate the intracellular flux distribution of each cultivation and then combined with partial least squares (PLS) method to establish a link between the estimated metabolic state and the cell environment. The validation of the MFA model was made and its consistency checked. The resulted PLS model explained almost 70% of the variance present in the flux distribution. The medium optimization for the continuous system and for the batch system resulted in higher biomass growth rates than the ones obtained experimentally, 0.034 h-1 and 0.030 h-1, respectively, thus reducing in almost 10 hours the duplication time. Additionally, the optimal medium obtained for the continuous system almost did not consider pyruvate. Overall the proposed methodology seems to be effective and both proposed medium optimizations seem to be promising to reach high cell densities.

Production of polyhydroxyalkanoates from oil-containing substrates

Different oil-containing substrates, namely, used cooking oil (UCO), fatty acids-byproduct from biodiesel production (FAB) and olive oil deodorizer distillate (OODD) were tested as inexpensive carbon sources for the production of polyhydroxyalkanoates (PHA) using twelve bacterial strains, in batch experiments. The OODD and FAB were exploited for the first time as alternative substrates for PHA production. Among the tested bacterial strains, Cupriavidus necator and Pseudomonas resinovorans exhibited the most promising results, producing poly-3-hydroxybutyrate, P(3HB), form UCO and OODD and mcl-PHA mainly composed of 3-hydroxyoctanoate (3HO) and 3-hydroxydecanoate (3HD) monomers from OODD, respectively. Afterwards, these bacterial strains were cultivated in bioreactor. C. necator were cultivated in bioreactor using UCO as carbon source. Different feeding strategies were tested for the bioreactor cultivation of C. necator, namely, batch, exponential feeding and DO-stat mode. The highest overall PHA productivity (12.6±0.78 g L-1 day-1) was obtained using DO-stat mode. Apparently, the different feeding regimes had no impact on polymer thermal properties. However, differences in polymer‟s molecular mass distribution were observed. C. necator was also tested in batch and fed-batch modes using a different type of oil-containing substrate, extracted from spent coffee grounds (SCG) by super critical carbon dioxide (sc-CO2). Under fed-batch mode (DO-stat), the overall PHA productivity were 4.7 g L-1 day-1 with a storage yield of 0.77 g g-1. Results showed that SCG can be a bioresource for production of PHA with interesting properties. Furthermore, P. resinovorans was cultivated using OODD as substrate in bioreactor under fed-batch mode (pulse feeding regime). The polymer was highly amorphous, as shown by its low crystallinity of 6±0.2%, with low melting and glass transition temperatures of 36±1.2 and -16±0.8 ºC, respectively. Due to its sticky behavior at room temperature, adhesiveness and mechanical properties were also studied. Its shear bond strength for wood (67±9.4 kPa) and glass (65±7.3 kPa) suggests it may be used for the development of biobased glues. Bioreactor operation and monitoring with oil-containing substrates is very challenging, since this substrate is water immiscible. Thus, near-infrared spectroscopy (NIR) was implemented for online monitoring of the C. necator cultivation with UCO, using a transflectance probe. Partial least squares (PLS) regression was applied to relate NIR spectra with biomass, UCO and PHA concentrations in the broth. The NIR predictions were compared with values obtained by offline reference methods. Prediction errors to these parameters were 1.18 g L-1, 2.37 g L-1 and 1.58 g L-1 for biomass, UCO and PHA, respectively, which indicates the suitability of the NIR spectroscopy method for online monitoring and as a method to assist bioreactor control. UCO and OODD are low cost substrates with potential to be used in PHA batch and fed-batch production. The use of NIR in this bioprocess also opened an opportunity for optimization and control of PHA production process.

Proposta de um modelo de medição e análise da satisfação de clientes em empresas de software : caso prático do ambiente business-to-business

Os estudos da satisfação e lealdade do cliente em ambiente Business-to-Business têm emergido devido ao interesse práctico e académico. Recorreu-se a um caso práctico de uma empresa de software internacional, ESRI, a operar em Portugal com modelo de negócio B2B e comportamento de compra extensivo. Desenvolveu-se um modelo estrutural com 11 variáveis latentes: lealdade; satisfação; imagem; atmosfera; cooperação; adaptação; processos; tecnologia; orientação ao cliente; competências; colaboradores e comunicação. Foram analisadas 304 respostas ao questionário de satisfação e de seguida aplicou-se o modelo a seis grupos de clientes segmentados de acordo com a contribuição do cliente para as receitas e o comportamento no processo de decisão de compra. Recorreu-se a modelos SEM (Structural Equation Modelling) com estimação dos parâmetros através da metodologia PLS (partial Least Squares). Os resultados mostram nos seis segmentos, que os valores da empresa, a cooperação através da competência dos colaboradores e da orientação ao cliente e a tecnologia são factores mais importantes para a satisfação e lealdade dos clientes.

Time-domain optimization of amplifiers based on distributed genetic algorithms

Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering

Extremum estimators and stochastic optimization methods

Submitted in partial fulfillment for the Requirements for the Degree of PhD in Mathematics, in the Speciality of Statistics in the Faculdade de Ciências e Tecnologia

Brownian motion with drift threshold model

In this thesis we implement estimating procedures in order to estimate threshold parameters for the continuous time threshold models driven by stochastic di®erential equations. The ¯rst procedure is based on the EM (expectation-maximization) algorithm applied to the threshold model built from the Brownian motion with drift process. The second procedure mimics one of the fundamental ideas in the estimation of the thresholds in time series context, that is, conditional least squares estimation. We implement this procedure not only for the threshold model built from the Brownian motion with drift process but also for more generic models as the ones built from the geometric Brownian motion or the Ornstein-Uhlenbeck process. Both procedures are implemented for simu- lated data and the least squares estimation procedure is also implemented for real data of daily prices from a set of international funds. The ¯rst fund is the PF-European Sus- tainable Equities-R fund from the Pictet Funds company and the second is the Parvest Europe Dynamic Growth fund from the BNP Paribas company. The data for both funds are daily prices from the year 2004. The last fund to be considered is the Converging Europe Bond fund from the Schroder company and the data are daily prices from the year 2005.