Estruturadores do discurso na aula de português em Moçambique

O nosso estudo debruça-se sobre o uso de estruturadores do discurso na interacção verbal, em contexto pedagógico. As nossas referências teóricas estão vinculadas à Análise do Discurso, quer à escola francesa (com origem na Linguística), quer à escola anglo-saxónica (com origem na Antropologia). Em relação à área da Linguística, buscámos os pressupostos da Pragmática, Sociolinguística e Psicolinguística; relativamente à Antropologia, seguimos as abordagens etnográficas, etnometodológicas e interaccionistas. Nesta pesquisa participaram 15 professores e 778 alunos de cinco escolas do ensino secundário/equiparado da cidade da Beira e da região de Maputo (Moçambique), que integravam, nomeadamente, as turmas do 1.º e 2.º ano do ramo comercial e 9.ª e 10.ª classe do ensino secundário geral. Observámos 40 aulas, das quais foram transcritas e analisadas 10 aulas. A transcrição e a anotação foram realizadas com o auxílio do programa Transcriber. Usámos métodos qualitativos e quantitativos e, predominantemente, procedimentos descritivos. Identificámos 4700 marcadores discursivos distribuídos nas seguintes subcategorias: marcadores discursivos directivos, marcadores discursivos de confirmação, marcadores discursivos de natureza fáctica e de concordância e as interjeições como marcadores discursivos. Os resultados da nossa pesquisa permitiram-nos concluir que os marcadores discursivos e as disfluências desempenham funções ligadas à estruturação textual-interactiva. Estes fenómenos linguísticos, ao estruturarem o discurso de professores e alunos, contribuem para a produção/compreensão de sentido das frases.

Mining biomedical information from scientific literature

The rapid evolution and proliferation of a world-wide computerized network, the Internet, resulted in an overwhelming and constantly growing amount of publicly available data and information, a fact that was also verified in biomedicine. However, the lack of structure of textual data inhibits its direct processing by computational solutions. Information extraction is the task of text mining that intends to automatically collect information from unstructured text data sources. The goal of the work described in this thesis was to build innovative solutions for biomedical information extraction from scientific literature, through the development of simple software artifacts for developers and biocurators, delivering more accurate, usable and faster results. We started by tackling named entity recognition - a crucial initial task - with the development of Gimli, a machine-learning-based solution that follows an incremental approach to optimize extracted linguistic characteristics for each concept type. Afterwards, Totum was built to harmonize concept names provided by heterogeneous systems, delivering a robust solution with improved performance results. Such approach takes advantage of heterogenous corpora to deliver cross-corpus harmonization that is not constrained to specific characteristics. Since previous solutions do not provide links to knowledge bases, Neji was built to streamline the development of complex and custom solutions for biomedical concept name recognition and normalization. This was achieved through a modular and flexible framework focused on speed and performance, integrating a large amount of processing modules optimized for the biomedical domain. To offer on-demand heterogenous biomedical concept identification, we developed BeCAS, a web application, service and widget. We also tackled relation mining by developing TrigNER, a machine-learning-based solution for biomedical event trigger recognition, which applies an automatic algorithm to obtain the best linguistic features and model parameters for each event type. Finally, in order to assist biocurators, Egas was developed to support rapid, interactive and real-time collaborative curation of biomedical documents, through manual and automatic in-line annotation of concepts and relations. Overall, the research work presented in this thesis contributed to a more accurate update of current biomedical knowledge bases, towards improved hypothesis generation and knowledge discovery.

Pathways of oxidative degradation of wine

The production of color/flavor compounds in wine is the result of different interrelated mechanism reactions. Among these, the oxidation phenomenon and the Maillard reaction stands out with particular relevance due to their large impact on the sensory quality of wines and consequently on the product shelflife. The aim of this thesis is to achieve a global vision of wine degradation mechanisms. The identification of mediators’ reactions involved in oxidative browning and aromatic degradation will be attempted based on different detectors. Two approaches are implemented in this work: a “non-target” approach by which relevant analytical tools will be used to merge the information of cyclic voltammetry and Diode-Array (DAD) detectors, allowing a broader overview of the system and the note of interesting compounds, and a “target” approach by which the identification and quantification of the different compounds related to the wine degradation process will be performed using different detectors (HPLC-UV/Vis, LC-MS, GC-MS, and FID). Two different patterns of degradation will be used in this study: wines generated by O2 and temperature perturbations, and synthetic solutions with relevant wine constituents for mechanisms validation. Results clearly demonstrate a “convolution” of chemical mechanisms. The presence of oxygen combined with temperature had a synergistic effect on the formation of several key odorant compounds.The results of this work could be translated to the wine-making and wine-storage environment from the modelling of the analysed compounds.