976 resultados para financial regulation
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Dissertação para obtenção do Grau de Mestre em Biotecnologia
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics
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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics
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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics
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Dissertation presented to obtain the Ph.D degree in Plant Physiology
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A thesis submitted for the Degree of Master in Medical microbiology
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The analysis of molecular regulators involved in controlling the maintenance and function of plant meristems has been the subject of many studies. Some master regulators of these processes have been identified in Arabidopsis benefiting from the array of tools available for genetic and molecular analysis in this model plant. However, aspects such as secondary growth that are more extensively observed in woody plants, have been less studied. Secondary growth is responsible for the enlargement of the plant stems and roots and results from the activity of the lateral (secondary) meristems, vascular cambium and cork cambium (phellogen), which produce two important renewable natural resources, wood and cork, respectively.(...)
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Functional regeneration of organs upon injury is a key process for animals survival. Contrary to humans, some vertebrates are remarkably competent in regenerating after acute organ or appendage lesions. This advantageous skill allows overcoming limitations in repair even in adult stages, when tissues are fully developed, via a process of epimorphic regeneration. One such organism is the zebrafish, which can regenerate several organs, namely its heart, retina, spinal cord and fins. (...)
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AraL from Bacillus subtilis is a member of the ubiquitous haloalkanoate dehalogenase, HAD, superfamily. The araL gene has been cloned, over-expressed in Escherichia coli and its product purified to homogeneity. The enzyme displays phosphatase activity, which is optimal at neutral pH (7.0) and 65 °C. Substrate screening and kinetic analysis showed AraL to have low specificity and catalytic activity towards several sugar phosphates, which are metabolic intermediates of the glycolytic and pentose phosphate pathways. Based on substrate specificity and gene context within the arabinose metabolic operon, a putative physiological role of AraL in detoxification of accidental accumulation of phosphorylated metabolites has been proposed. The ability of AraL to catabolise several related secondary metabolites requires regulation at the genetic level. Here, by site- directed mutagenesis, we show that AraL production is regulated by a structure in the translation initiation region of the mRNA, which most probably blocks access to the ribosome-binding site, preventing protein synthesis. Members of HAD subfamily IIA and IIB are characterised by a broad-range and overlapping specificity that anticipated the need for regulation at the genetic level. In this study we provide evidence for the existence of a genetic regulatory mechanism controlling AraL production.
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The goal of this thesis is the study of a tool that can help analysts in finding sequential patterns. This tool will have a focus on financial markets. A study will be made on how new and relevant knowledge can be mined from real life information, potentially giving investors, market analysts, and economists new basis to make informed decisions. The Ramex Forum algorithm will be used as a basis for the tool, due to its ability to find sequential patterns in financial data. So that it further adapts to the needs of the thesis, a study of relevant improvements to the algorithm will be made. Another important aspect of this algorithm is the way that it displays the patterns found, even with good results it is difficult to find relevant patterns among all the studied samples without a proper result visualization component. As such, different combinations of parameterizations and ways to visualize data will be evaluated and their influence in the analysis of those patterns will be discussed. In order to properly evaluate the utility of this tool, case studies will be performed as a final test. Real information will be used to produce results and those will be evaluated in regards to their accuracy, interest, and relevance.
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This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.