Screening pentachlorophenol degradation ability by environmental fungal strains belonging to the phyla Ascomycota and Zygomycota

Pentachlorophenol (PCP) bioremediation by the fungal strains amongst the cork- colonising community has not yet been analysed. In this paper, the co- and direct metabolism of PCP by each of the 17 fungal species selected from this community were studied. Using hierarchical data analysis, the isolates were ranked by their PCP bioremediation potential. Fifteen isolates were able to degrade PCP under co-metabolic conditions, and surprisingly Chrysonilia sitophila, Trichoderma longibrachiatum, Mucor plumbeus, Penicillium janczewskii and P. glandicola were able to directly metabolise PCP, leading to its complete depletion from media. PCP degradation intermediates are preliminarily discussed. Data emphasise the signiWcance of these fungi to have an interesting potential to be used in PCP bioremediation processes.

Estimação de Modelos de Adopção e Difusão de Tecnologias de Informação e Comunicação em Portugal

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Exploraty Multivariate Statistical Methods Applied to Pharmaceutical Industry CRM Data

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Exploratory geospatial data analysis using self-organizing maps

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

Information flow analysis using data-dependent logical propositions

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

New visualization model for large scale biosignals analysis

Benefits of long-term monitoring have drawn considerable attention in healthcare. Since the acquired data provides an important source of information to clinicians and researchers, the choice for long-term monitoring studies has become frequent. However, long-term monitoring can result in massive datasets, which makes the analysis of the acquired biosignals a challenge. In this case, visualization, which is a key point in signal analysis, presents several limitations and the annotations handling in which some machine learning algorithms depend on, turn out to be a complex task. In order to overcome these problems a novel web-based application for biosignals visualization and annotation in a fast and user friendly way was developed. This was possible through the study and implementation of a visualization model. The main process of this model, the visualization process, comprised the constitution of the domain problem, the abstraction design, the development of a multilevel visualization and the study and choice of the visualization techniques that better communicate the information carried by the data. In a second process, the visual encoding variables were the study target. Finally, the improved interaction exploration techniques were implemented where the annotation handling stands out. Three case studies are presented and discussed and a usability study supports the reliability of the implemented work.