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

Including context in a routing algorithm for the internet of things

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

Modelling a cable structure for a new wind energy production device

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Mecânica Especialização em Concepção e Produção

A lightweight distributed super peer election algorithm for unstructured dynamic P2P systems

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

New analytical methodologies for doping control – detection of anabolic androgenic steroids in human urine

Dissertation submitted to Faculdade de Ciências e Tecnologia - Universidade Nova de Lisboa in fulfilment of the requirements for the degree of Doctor of Philosophy (Biochemistry - Biotechnology)

Archaeological roman glasses: comparative characterisation by non-destructive analytical techniques

Dissertation presented in fulfilment of the requirements for the Master’s degree in Conservation and Restoration

Geodupa - a geography-driven partial membership algorithm

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

A study on reducing digital piracy: an analytical network process approach with benefits, opportunities, costs and risks analysis

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Target-specific multiphysics modeling for thermal medicine applications

Dissertation to obtain the degree of Doctor of Philosophy in Biomedical Engineering

Rastreio combinado do 1º trimestre e doenças autoimunes : Impacto das variaveis pré-analíticas na avaliação do risco

RESUMO: Contexto: As anomalias congénitas, com particular destaque para as neuploidias , afectam aproximadamente 2% dos recém-nascidos, constituindo causas frequentes de morbilidade e mortalidade. Actualmente, a avaliação do grau de risco para as aneuploidias mais prevalentes (T21, T13, T18) é efectuada através do “Rastreio Combinado do 1º Trimestre”, devendo as grávidas com risco acrescido ser sujeitas a exames invasivos (ex.biópsia das vilosidades coriónicas,amniocentese). Quanto mais qualidade existir num rastreio, menos falsos positivos existirão e menor o número de exames diagnósticos invasivos desnecessários. As doenças autoimunes são doenças inflamatórias crónicas em cuja fisiopatologia se encontram distúrbios da imunidade humoral e celular, dependentes de factores genéticos, hormonais,psicológicos e ambientais. Atingem mais o sexo feminino e durante a idade fértil,podendo influenciar o outcome da gravidez e a saúde neonatal causando significativa morbilidade e mortalidade. O lúpus eritematoso sistémico para além de potencialmente afectado pelas alterações imunoendócrinas fisiológicas da gravidez, associa-se frequentemente a problemas de fertilidade. Recentemente, foi sugerido que as anormalidades ocorridas durante a invasão precoce do sinciciotrofoblasto, resultando em deficiente diferenciação, deficiente maturação e diminuição na produção de hCG, poderão ser o mecanismo fisiopatológico primário para as perdas fetais no primeiro trimestre, nos doentes com SLE. A ocorrência de níveis elevados de hCG total e ß-hCG livre no rastreio para despiste de síndrome de Down do segundo e do primeiro trimestre foi assinalada em grávidas portadoras de lúpus, mas a escassez de estudos comprovativos e a pequena dimensão das amostras estudadas constituiu uma limitação significativa na fidedignidade dos resultados obtidos. Objectivos: O estudo teve como objectivos i. estabelecer valores normativos Portugueses e de distribuição para as MoM’s dos parâmetros séricos do primeiro trimestre, por semana de gestação:(PAPP-A e ß-hCG livre), ii. avaliar a influência que as doenças autoimunes têm sobre as MoM’s individuais dos parâmetros bioquímicos PAPP-A e/ou ß-hCG livre, utilizados no rastreio pré-natal combinado do 1º trimestre, e iii. saber se as doenças autoimunes podem condicionar um aumento da taxa de resultados falsos positivos, com consequente aumento do número de amniocenteses. Metodologia: Estudo longitudinal prospectivo, consistindo num rastreio pré-natal combinado de 1º trimestre para pesquisa de aneuploidias, em duas amostras provenientes do Reino Unido (n= 45,854) e de Portugal (n=3122). Foram avaliados parâmetros socio-demográficos, ecográficos, laboratoriais, e calculados os indicadores de desempenho do rastreio combinado. A execução analítica dos testes bioquímicos séricos (PAPP-A e ß-hCG livre) foi realizada no autoanalisador Brahms Kryptor e no autoanalizador 6000 Delfia Xpress. Compararam-se os grupos autoimune e não autoimune das amostras. Resultados: Relativamente às características populacionais, o grupo auto imune tinha valores significativamente superiores nas variáveis idade materna e idade gestacional. Comparando os grupos com e sem doença autoimune, constatou-se a existência de uma elevação das MoM’s da ß-hCG livre nas grávidas com doença autoimune, nomeadamente nos casos de lúpus eritematoso sistémico. Conclusões: os resultado obtidos reforçam a indicação do rastreio combinado do 1º trimestre certificado pela FMF nas grávidas com doenças autoimunes, nomeadamente para as doentes com LES; no entanto, devem ser calculados e introduzidos factores de correcção no algoritmo de risco, de modo a evitar a subida no número de resultados falso-positivos, e consequentemente a sobre- utilização de métodos invasivos.------------ ABSTRACT: Context: Congenital anomalies, with particular reference to aneuploidias, affect approximately 2% of newborns, and are frequent causes of morbidity and mortality. Currently, the risk evaluation for the most prevalent aneuploidias (T21, T13, T18) is carried out through the “combined first trimester screening”, and pregnant women with increased risk are subjected to invasive tests (e.g. villus biopsy done, amniocentesis). The more quality exists in a screening, less false positives exists and fewer unnecessary invasive diagnostic exams. Autoimmune diseases are chronic inflammatory diseases in whose pathophysiology are immune humoral and cellular disorders, dependent on genetic factors, hormonal, psychological and environmental factors. The disease is more prevalent among females, during the child-bearing age, and may influence the outcome of pregnancy and neonatal health causing significant morbidity and mortality. Lupus Erythematosus in addition to potentially affected by immunoendocrine physiological changes of pregnancy, is often associated with fertility problems. Recently, it has been suggested that the abnormalities that occurred during the early invasion of the syncytiotrophoblast, resulting in insufficient differentiation, deficient maturation and decrease in production of hCG may be the primary pathophysiological mechanism for fetal losses in the first quarter, in patients with SLE. The occurrence of elevated levels of total hCG and free ß-hCG in screening for Down’s syndrome of the second and first trimester was reported in pregnant women with lupus, but the paucity of supporting studies and the small size of the samples studied constituted a significant limitation on the trustworthiness of the results obtained. Objectives: this study aims to i. establish normative values for the serum parameters MoM’s (PAPP-A and free β-hCG) and it’s distribution, in the first trimester, by week of pregnancy; ii. assess the influence that the autoimmune diseases have on the MoM’s of individual biochemical PAPP-A and/or β-hCG, used in antenatal screening combined for the first trimester, and iii. whether the autoimmune diseases may make an increased rate of false positives, with consequent increase in the number of amniocenteses.Methodology: Prospective longitudinal study, consisting of a combined first trimester antenatal screening for aneuploidies lookup in two samples from the United Kingdom (n=45.854) and Portugal (n= 3.122). Socio-demographic, echographic and laboratory parameters were evaluated, and combined screening performance indicators were calculated. The analytical run of serum biochemical tests (PAPP-A and ß-hCG) was held at the Brahms Kryptor and in Delfia Xpress 6000. Comparisons between autoimmune group and non-autoimmune group were made. Results: Relating to population characteristics, the autoimmune group had significantly diferente values in the variables maternal age and gestational age. Comparing the groups with and without autoimmune disease, it was noted that there is an elevation of the MoM’s of free ß-hCG levels in pregnant women with autoimmune disease, particularly in cases of systemic lupus erythematosus. Conclusions: The results obtained reinforce the indication of FMF certified combined screening in pregnant women with autoimmune diseases, notably to the patients with SLE; However, correction factors should be calculated and entered in the risk algorithm, in order to avoid the rise in the number of false positive results, and consequently the over-use of invasive methods.

Predictive analytical and numerical modeling for orthogonal cutting

In this thesis, a predictive analytical and numerical modeling approach for the orthogonal cutting process is proposed to calculate temperature distributions and subsequently, forces and stress distributions. The models proposed include a constitutive model for the material being cut based on the work of Weber, a model for the shear plane based on Merchants model, a model describing the contribution of friction based on Zorev’s approach, a model for the effect of wear on the tool based on the work of Waldorf, and a thermal model based on the works of Komanduri and Hou, with a fraction heat partition for a non-uniform distribution of the heat in the interfaces, but extended to encompass a set of contributions to the global temperature rise of chip, tool and work piece. The models proposed in this work, try to avoid from experimental based values or expressions, and simplifying assumptions or suppositions, as much as possible. On a thermo-physical point of view, the results were affected not only by the mechanical or cutting parameters chosen, but also by their coupling effects, instead of the simplifying way of modeling which is to contemplate only the direct effect of the variation of a parameter. The implementation of these models was performed using the MATLAB environment. Since it was possible to find in the literature all the parameters for AISI 1045 and AISI O2, these materials were used to run the simulations in order to avoid arbitrary assumption.

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

The use of analytical hierarchy process in spatial decision support system for land use management

Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

Automated quantitative analysis of MCC-IMS spectra

Ion Mobility Spectrometry coupled with Multi Capillary Columns (MCC -IMS) is a fast analytical technique working at atmospheric pressure with high sensitivity and selectivity making it suitable for the analysis of complex biological matrices. MCC-IMS analysis generates its information through a 3D spectrum with peaks, corresponding to each of the substances detected, providing quantitative and qualitative information. Sometimes peaks of different substances overlap, making the quantification of substances present in the biological matrices a difficult process. In the present work we use peaks of isoprene and acetone as a model for this problem. These two volatile organic compounds (VOCs) that when detected by MCC-IMS produce two overlapping peaks. In this work it’s proposed an algorithm to identify and quantify these two peaks. This algorithm uses image processing techniques to treat the spectra and to detect the position of the peaks, and then fits the data to a custom model in order to separate the peaks. Once the peaks are separated it calculates the contribution of each peak to the data.