Variação terminolágica em textos de especialidade : o caso de VIH/Sida

Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Terminologia e Gestão de Informação de Especialidade

Domesticated domesticated! Some comments on the translation into English of José Carlos Somoza's La Caverna de las ideas

In order to cater for an extended readership, crime fiction, like most popular genres, is based on the repetition of a formula allowing for the reader's immediate identification. This first domestication is followed, at the time of its translation, by a second process, which wipes out those characteristics of the source text that may come into conflict with the dominant values of the target culture. An analysis of the textual and paratextual strategies used in the English translation of José Carlos Somoza's La caverna de las ideas (2000) shows the efforts to make the novel more easily marketable in the English-speaking world through the elimination of most of the obstacles to easy readability.

Corre mãe! Corre!: trabalho de projecto

Trabalho de Projeto submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro - especialização em Teatro do Movimento.

TV Recommendation and Personalization Systems: Integrating Broadcast and Video On-demand Services

he expansion of Digital Television and the convergence between conventional broadcasting and television over IP contributed to the gradual increase of the number of available channels and on demand video content. Moreover, the dissemination of the use of mobile devices like laptops, smartphones and tablets on everyday activities resulted in a shift of the traditional television viewing paradigm from the couch to everywhere, anytime from any device. Although this new scenario enables a great improvement in viewing experiences, it also brings new challenges given the overload of information that the viewer faces. Recommendation systems stand out as a possible solution to help a watcher on the selection of the content that best fits his/her preferences. This paper describes a web based system that helps the user navigating on broadcasted and online television content by implementing recommendations based on collaborative and content based filtering. The algorithms developed estimate the similarity between items and users and predict the rating that a user would assign to a particular item (television program, movie, etc.). To enable interoperability between different systems, programs characteristics (title, genre, actors, etc.) are stored according to the TV-Anytime standard. The set of recommendations produced are presented through a Web Application that allows the user to interact with the system based on the obtained recommendations.

Multidimensional scaling visualization of earthquake phenomena

Earthquakes are associated with negative events, such as large number of casualties, destruction of buildings and infrastructures, or emergence of tsunamis. In this paper, we apply the Multidimensional Scaling (MDS) analysis to earthquake data. MDS is a set of techniques that produce spatial or geometric representations of complex objects, such that, objects perceived to be similar/distinct in some sense are placed nearby/distant on the MDS maps. The interpretation of the charts is based on the resulting clusters since MDS produces a different locus for each similarity measure. In this study, over three million seismic occurrences, covering the period from January 1, 1904 up to March 14, 2012 are analyzed. The events, characterized by their magnitude and spatiotemporal distributions, are divided into groups, either according to the Flinn–Engdahl seismic regions of Earth or using a rectangular grid based in latitude and longitude coordinates. Space-time and Space-frequency correlation indices are proposed to quantify the similarities among events. MDS has the advantage of avoiding sensitivity to the non-uniform spatial distribution of seismic data, resulting from poorly instrumented areas, and is well suited for accessing dynamics of complex systems. MDS maps are proven as an intuitive and useful visual representation of the complex relationships that are present among seismic events, which may not be perceived on traditional geographic maps. Therefore, MDS constitutes a valid alternative to classic visualization tools, for understanding the global behavior of earthquakes.

O texto técnico na sua diversidade em ambiente de empresa

Relatório de Estágio apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Tradução.

Hemolymphatic components in vectors of Trypanosoma cruzi: study in several species of the subfamily Triatominae (Hemiptera: Reduviidae)

The members of the subfamily Triatominae (Hemiptera : Reduviidae) comprise a great number of species of medical importance in the transmission of the T. cruzi (American trypanosomiasis). The aim of this study was to contribute to the knowledge about the chemical composition in proteins, lipids, lipoproteins, and carbohydrates of vectors of Chagas' disease corresponding to twelve members of the subfamily Triatominae. This study was carried out in ninphs of the fifth instar and adult males of the species: T. delpontei, T. dimidiata, T. guasayana, T. infestans, T. mazzotti, T. pallidipennis, T. patagonica, T. platensis, T. rubrovaria, T. sordida of the Triatoma genus, and D. maximus and P. megistus of the Dipatalogaster and Panstrongylus genera respectively. The results show on one hand, qualitative differences in the protein composition, and on the other hand, similarity in the lipoprotein profiles. Lipids, proteins, and carbohydrates did not show significant differences between species or/and stages.

On similarities in infrared spectra of complex drugs

A chromatographic separation of active ingredients of Combivir, Epivir, Kaletra, Norvir, Prezista, Retrovir, Trivizir, Valcyte, and Viramune is performed on thin layer chromatography. The spectra of these nine drugs were recorded using the Fourier transform infrared spectroscopy. This information is then analyzed by means of the cosine correlation. The comparison of the infrared spectra in the perspective of the adopted similarity measure is possible to visualize with present day computer tools, and the emerging clusters provide additional information about the similarities of the investigated set of complex drugs.

Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.

Schistosoma mansoni: evaluation of the activity of oxamniquine on schistosomules, at 24 hours after infection

Mice transcutaneously infected with about 400 cercariae were submitted to treatment with oxamniquine (400 mg/kg), 24 hours after infection. The recovery of schistosomules, at 4, 24, 48 and 72 hours and 35 days after treatment, showed the activity of the drug on the parasites, thus practically preventing their migration from the skin to the lungs. Worm recovery performed in the lungs (96 hours after treatment) showed recovery means of 0.6 worms/mouse in the treated group and 53.8 in the control group (untreated). The perfusion of the portal system carried out at 35 days after treatment clearly showed the elimination of all the parasites in the treated group, whereas a recovery mean of 144.7 worms/mouse was detected in the control group (untreated). These findings confirm the efficacy of oxamniquine at the skin phase of infection, and also show similarity with the immunization method that uses irradiated cercariae. The practical application of these findings in the medical clinic is discussed too

A MAP approach to evidence accumulation clustering

The Evidence Accumulation Clustering (EAC) paradigm is a clustering ensemble method which derives a consensus partition from a collection of base clusterings obtained using different algorithms. It collects from the partitions in the ensemble a set of pairwise observations about the co-occurrence of objects in a same cluster and it uses these co-occurrence statistics to derive a similarity matrix, referred to as co-association matrix. The Probabilistic Evidence Accumulation for Clustering Ensembles (PEACE) algorithm is a principled approach for the extraction of a consensus clustering from the observations encoded in the co-association matrix based on a probabilistic model for the co-association matrix parameterized by the unknown assignments of objects to clusters. In this paper we extend the PEACE algorithm by deriving a consensus solution according to a MAP approach with Dirichlet priors defined for the unknown probabilistic cluster assignments. In particular, we study the positive regularization effect of Dirichlet priors on the final consensus solution with both synthetic and real benchmark data.

Text classification using compression-based dissimilarity measures

Arguably, the most difficult task in text classification is to choose an appropriate set of features that allows machine learning algorithms to provide accurate classification. Most state-of-the-art techniques for this task involve careful feature engineering and a pre-processing stage, which may be too expensive in the emerging context of massive collections of electronic texts. In this paper, we propose efficient methods for text classification based on information-theoretic dissimilarity measures, which are used to define dissimilarity-based representations. These methods dispense with any feature design or engineering, by mapping texts into a feature space using universal dissimilarity measures; in this space, classical classifiers (e.g. nearest neighbor or support vector machines) can then be used. The reported experimental evaluation of the proposed methods, on sentiment polarity analysis and authorship attribution problems, reveals that it approximates, sometimes even outperforms previous state-of-the-art techniques, despite being much simpler, in the sense that they do not require any text pre-processing or feature engineering.

Application de connaissances terminologiques dans le cadre de l'enseignement du Français langue etrangère I et II

Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Terminologia

Escrever para aprender estudo do meio

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Didáticas Integradas em Língua Portuguesa, Matemática, Ciências Naturais e Sociais

Possibilidade e rentabilidade da utilização do gás de xisto em Portugal

Mestrado em Engenharia Mecânica- Energia