Mould and yeast identification in archival settings: preliminary results on the use of traditional methods and molecular biology options in Portuguese archives

This project was developed to fully assess the indoor air quality in archives and libraries from a fungal flora point of view. It uses classical methodologies such as traditional culture media – for the viable fungi – and modern molecular biology protocols, especially relevant to assess the non-viable fraction of the biological contaminants. Denaturing high-performance liquid chromatography (DHPLC) has emerged as an alternative to denaturing gradient gel electrophoresis (DGGE) and has already been applied to the study of a few bacterial communities. We propose the application of DHPLC to the study of fungal colonization on paper-based archive materials. This technology allows for the identification of each component of a mixture of fungi based on their genetic variation. In a highly complex mixture of microbial DNA this method can be used simply to study the population dynamics, and it also allows for sample fraction collection, which can, in many cases, be immediately sequenced, circumventing the need for cloning. Some examples of the methodological application are shown. Also applied is fragment length analysis for the study of mixed Candida samples. Both of these methods can later be applied in various fields, such as clinical and sand sample analysis. So far, the environmental analyses have been extremely useful to determine potentially pathogenic/toxinogenic fungi such as Stachybotrys sp., Aspergillus niger, Aspergillus fumigatus, and Fusarium sp. This work will hopefully lead to more accurate evaluation of environmental conditions for both human health and the preservation of documents.

Coletores de distribuição e sua otimização hidráulica, aplicados a uma instalação de produção de água arrefecida em sistemas de AVAC ( Fórum Picoas)

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Complementarity of conventional and molecular methods in the assessment of fungal contamination caused by Aspergillus fumigatus complex in one Portuguese composting plant

The handling of waste and compost that occurs frequently in composting plants (compost turning, shredding, and screening) has been shown to be responsible for the release of dust and air borne microorganisms and their compounds in the air. Thermophilic fungi, such as A. fumigatus, have been reported and this kind of contamination in composting facilities has been associated with increased respiratory symptoms among compost workers. This study intended to characterize fungal contamination in a totally indoor composting plant located in Portugal. Besides conventional methods, molecular biology was also applied to overcome eventual limitations.

Unveiling the Biometric Potential of Finger-Based ECG Signals

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.

Vertex component analysis: a fast algorithm to unmix hyperspectral data

Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.

Parallel implementation of vertex component analysis for hyperspectral endmember extraction

International Conference with Peer Review 2012 IEEE International Conference in Geoscience and Remote Sensing Symposium (IGARSS), 22-27 July 2012, Munich, Germany

Robótica móvel: sistema de condução autónoma

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo Automação e Electrónica Industrial

Dosimetria e análise de incertezas em braquiterapia ginecológica

Mestrado em Radiações Aplicadas às tecnologias da Saúde

Implementação em hardware reconfigurável de método de separação de dados hiperespetrais

Relatório do Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Optimising protocol of acquisition and post-processing procedures in the assessment of coronary artery disease by computed tomography

Coronary artery disease (CAD) is currently one of the most prevalent diseases in the world population and calcium deposits in coronary arteries are one direct risk factor. These can be assessed by the calcium score (CS) application, available via a computed tomography (CT) scan, which gives an accurate indication of the development of the disease. However, the ionising radiation applied to patients is high. This study aimed to optimise the protocol acquisition in order to reduce the radiation dose and explain the flow of procedures to quantify CAD. The main differences in the clinical results, when automated or semiautomated post-processing is used, will be shown, and the epidemiology, imaging, risk factors and prognosis of the disease described. The software steps and the values that allow the risk of developingCADto be predicted will be presented. A64-row multidetector CT scan with dual source and two phantoms (pig hearts) were used to demonstrate the advantages and disadvantages of the Agatston method. The tube energy was balanced. Two measurements were obtained in each of the three experimental protocols (64, 128, 256 mAs). Considerable changes appeared between the values of CS relating to the protocol variation. The predefined standard protocol provided the lowest dose of radiation (0.43 mGy). This study found that the variation in the radiation dose between protocols, taking into consideration the dose control systems attached to the CT equipment and image quality, was not sufficient to justify changing the default protocol provided by the manufacturer.

Teacher placement report: investigation: action research project investigating methods for promoting creativity in double bass students attending a portuguese music school

The investigation which employed the action research method (qualitative analysis)was divided into four fases. In phases 1-3 the participants were six double bass students at Nossa Senhora do Cabo Music School. Pilot exercises in creativity were followed by broader and more ambitious projects. In phase 4 the techniques were tested and amplified during a summer course for twelve double bass students at Santa Cecilia College.

Simulation model for driving dynamics, energy use and power supply

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

ECG Biometrics: A Template Selection Approach

Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.

Phex: a computational tool for plate heat exchanges design problems

This paper presents a computational tool (PHEx) developed in Excel VBA for solving sizing and rating design problems involving Chevron type plate heat exchangers (PHE) with 1-pass-1-pass configuration. The rating methodology procedure used in the program is outlined, and a case study is presented with the purpose to show how the program can be used to develop sensitivity analysis to several dimensional parameters of PHE and to observe their effect on transferred heat and pressure drop.

Global localization with non-quantized local image features

In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.