Experimental and numerical evaluation of composite repairs on wood beams damaged by cross-graining

An experimental and Finite Element study was performed on the bending behaviour of wood beams of the Pinus Pinaster species repaired with adhesively-bonded carbon–epoxy patches, after sustaining damage by cross-grain failure. This damage is characterized by crack growth at a small angle to the beams longitudinal axis, due to misalignment between the wood fibres and the beam axis. Cross-grain failure can occur in large-scale in a wood member when trees that have grown spirally or with a pronounced taper are cut for lumber. Three patch lengths were tested. The simulations include the possibility of cohesive fracture of the adhesive layer, failure within the wood beam in two propagation planes and patch interlaminar failure, by the use of cohesive zone modelling. The respective cohesive properties were estimated either by an inverse method or from the literature. The comparison with the tests allowed the validation of the proposed methodology, opening a good perspective for the reduction of costs in the design stages of these repairs due to extensive experimentation.

Estratégia multi-temporal para produção automática de cartografia de ocupação do solo com imagens AWiFS

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

Comportamentos e percepções dos clientes dos operadores de rede móvel

Relatório de Projecto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Natural populations of saccharomyces kudriavzevii in Portugal are associated with oak bark and are sympatric with s. cerevisiae and s. paradoxus

Applied Environmental Microbiology, Vol. 74, nº7

Biogeography, host specificity, and molecular phylogeny of the basidiomycetous yeast phaffia rhodozyma and its sexual form, xanthophyllomyces dendrorhous

Applied and Environmental Microbiology, Vol. 73, No.4

Remediação de solos contaminados por compostos farmacêuticos

O recente surgimento de nanopartículas de ferro valente-zero (nFZV), um material com elevada capacidade de remediação de solos por via de reacções de oxidação/redução pode ser uma opção viável para a remoção de fármacos do solo. A sua aplicação já é uma realidade em alguns tipos de solos contaminados por compostos específicos e, com este trabalho, procura-se estudar a sua capacidade de remediação de solos contaminados por compostos farmacêuticos, recorrendo-se a uma tecnologia “verde” de síntese destas nanopartículas. Esta tecnologia é bastante recente, ainda não aplicada no campo de trabalho, que se baseia no uso de folhas de certas árvores para produzir extratos naturais que reduzem o ferro (III) a ferro zero valente, formando nFZV. Desta forma procedeu-se, à escala laboratorial, ao estudo da eficiência das nFZV na degradação de um fármaco – paracetamol – e comparou-se com a eficiência demonstrada por oxidantes, muito utilizados hoje em dia em casos de remediação in situ como o permanganato de potássio, o peróxido de hidrogénio, o persulfato de sódio e o reagente de Fenton. O estudo foi efectuado em dois meios diferentes: solução aquosa e solo arenoso. De forma muito sucinta, o estudo baseou-se na introdução dos oxidantes/nFZV em soluções/solos contaminados com paracetamol e consequente monitorização do processo de remediação através de cromatografia líquida de alta eficiência. Nos ensaios com soluções aquosas contaminadas com paracetamol, o permanganato de potássio e o reagente de Fenton revelaram capacidade para degradar o paracetamol, atingindo mesmo um grau de degradação de 100%. O persulfato de sódio também demonstrou uma capacidade de degradação do paracetamol, chegando a atingir 99% de degradação, mas apenas recorrendo ao uso de um volume de oxidante elevado quando comparado com os outros dois oxidantes já referidos. Por outro lado, o peróxido de hidrogénio não demonstrou qualquer capacidade de degradação do paracetamol, pelo que o seu uso não passou desta fase. Verificou-se também que o uso de ferro granulado para o tratamento de água contaminada com paracetamol revelou resultados diferentes dos observados no uso de nFZV, obtendo-se eficiências de 87%. Existiram dificuldades analíticas na quantificação do paracetamol, especificamente relacionadas com o uso do extracto de folhas de amoreira, cuja composição continha substâncias que causaram dificuldades acentuadas na análise dos cromatogramas. Por fim, um pequeno teste de combinação do reagente de Fenton com os fenómenos de biodegradação resultantes dos microrganismos presentes em folhas do extracto de chá preto demonstrou que este pode ser uma área que pode e deve ser mais estudada. Desta forma, a utilização das nFZV para o tratamento de água contaminada com paracetamol não permitiu a retirada de conclusões seguras sobre a capacidade que as nFZV produzidas com extractos de folhas de amoreira e de chá preto têm de degradação do paracetamol. Nos testes de remediação de solos contaminados os resultados demonstraram que, mais uma vez, tanto o permanganato de potássio como o reagente de Fenton se revelam como os melhores oxidantes para a degradação do paracetamol, obtendo-se a degradação total do paracetamol. Por outro lado, voltou a ser necessário uma elevada quantidade de persulfato de sódio quando comparada com os dois anteriores, para que ocorra a degradação desta mesma quantidade de paracetamol, demonstrando mais uma vez que, apesar de não ideal, o persulfato demonstra capacidade de degradação do paracetamol.

Desenvolvimento de Ontologia para Apoio ao Diagnóstico de Distúrbios do Humor

Mestrado em Computação e Instrumentação Médica

Soil sampling design and sampling techniques for soil properties monitoring – common difficulties related to forest soils

Mathematical models and statistical analysis are key instruments in soil science scientific research as they can describe and/or predict the current state of a soil system. These tools allow us to explore the behavior of soil related processes and properties as well as to generate new hypotheses for future experimentation. A good model and analysis of soil properties variations, that permit us to extract suitable conclusions and estimating spatially correlated variables at unsampled locations, is clearly dependent on the amount and quality of data and of the robustness techniques and estimators. On the other hand, the quality of data is obviously dependent from a competent data collection procedure and from a capable laboratory analytical work. Following the standard soil sampling protocols available, soil samples should be collected according to key points such as a convenient spatial scale, landscape homogeneity (or non-homogeneity), land color, soil texture, land slope, land solar exposition. Obtaining good quality data from forest soils is predictably expensive as it is labor intensive and demands many manpower and equipment both in field work and in laboratory analysis. Also, the sampling collection scheme that should be used on a data collection procedure in forest field is not simple to design as the sampling strategies chosen are strongly dependent on soil taxonomy. In fact, a sampling grid will not be able to be followed if rocks at the predicted collecting depth are found, or no soil at all is found, or large trees bar the soil collection. Considering this, a proficient design of a soil data sampling campaign in forest field is not always a simple process and sometimes represents a truly huge challenge. In this work, we present some difficulties that have occurred during two experiments on forest soil that were conducted in order to study the spatial variation of some soil physical-chemical properties. Two different sampling protocols were considered for monitoring two types of forest soils located in NW Portugal: umbric regosol and lithosol. Two different equipments for sampling collection were also used: a manual auger and a shovel. Both scenarios were analyzed and the results achieved have allowed us to consider that monitoring forest soil in order to do some mathematical and statistical investigations needs a sampling procedure to data collection compatible to established protocols but a pre-defined grid assumption often fail when the variability of the soil property is not uniform in space. In this case, sampling grid should be conveniently adapted from one part of the landscape to another and this fact should be taken into consideration of a mathematical procedure.

Management Driven Hybrid Multicast Framework for Content Aware Networks

The need for better adaptation of networks to transported flows has led to research on new approaches such as content aware networks and network aware applications. In parallel, recent developments of multimedia and content oriented services and applications such as IPTV, video streaming, video on demand, and Internet TV reinforced interest in multicast technologies. IP multicast has not been widely deployed due to interdomain and QoS support problems; therefore, alternative solutions have been investigated. This article proposes a management driven hybrid multicast solution that is multi-domain and media oriented, and combines overlay multicast, IP multicast, and P2P. The architecture is developed in a content aware network and network aware application environment, based on light network virtualization. The multicast trees can be seen as parallel virtual content aware networks, spanning a single or multiple IP domains, customized to the type of content to be transported while fulfilling the quality of service requirements of the service provider.

Electrical ageing studies of polymeric insulation for power cables (estudo do envelhecimento eléctrico do isolante polimérico de cabos eléctricos

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Física - Física Aplicada pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

The ecology of Triatoma sordida in natural environments in two different regions of the state of Minas Gerais, Brazil

A study was undertaken about T. sordida in the natural environment in two different regions of the state of Minas Gerais: Itapagipe (Triângulo), an area of cerrado modified by the formation of fields of pasture and agriculture, and Mato Verde (north) an area of transition between caatinga and cerrado with profound deforestation in the last years due to the expansion of cotton cultivation. In both regions the principal ecotopes identified were hollow trees and the bark of live or dead trees, where the occurrence of a food source is not frequent. In this environment, the triatomines utilize various food sources; opposums appear to represent an important source of infection. In the north of Minas, a greater concentration of reservoirs and vectors was observed than in the Triángulo which could explain the higher level of infection of the triatomines in the north. Close attention to the process of domiciliation of T. sordida in the north of Minas is recommended where an extensive intervention by man in the natural environment has occurred and where a rise in the population of triatomines in the peridomestic environment has been observed in recent years.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Prognostic modelling of breast cancer patients: a benchmark of predictive models with external validation

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores – Sistemas Digitais e Percepcionais pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Análise de Desempenho e Recomendação para Soluções IVR

Mestrado em Engenharia Informática, Área de Especialização em Tecnologias do Conhecimento e da Decisão

Using data mining techniques to support breast cancer diagnosis

More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.