Custo histórico versus justo valor

Oriêntador: Mestre Carlos Pedro

Análise de um veículo todo o terreno do tipo KARTCROSS

O presente trabalho descreve a análise feita a um veículo de todo o terreno. O kartcross/buggy em estudo é usado em provas do tipo Baja, sendo estas provas longas e com traçados sinuosos. O veículo, já construído, foi testado através de softwares, a nível estrutural e ciclístico, pretendendo-se assim efetuar engenharia inversa sobre o mesmo. No decorrer da sua utilização normal o kartcross/buggy sofre vários tipos de solicitações, como sejam aceleração, travagem e força centrípta em curva. Portanto, o veículo deve ser capaz de suportar estes esforços e ter uma boa habilidade. Além dos testes em uso corrente foi analisada também a rigidez torsional do quadro do veículo e do veículo completo, podendo-se assim melhorar estes valores. A nível ciclístico foram analisados os parâmetros das suspensões como o camber, convergência/divergência, caster, entre outros. Da análise destes parâmetros e possível fazerem-se melhorias de forma a que o veículo tenha um melhor desempenho. Para validar os testes computacionais efetuados foi reproduzido experimentalmente o teste da rigidez torsional. No final, compararam-se os valores numéricos com os experimentais e aferir se o modelo se encontra bem representado.

Integer and Fractional Order Entropy Analysis of Earthquake Data-series

This paper studies the statistical distributions of worldwide earthquakes from year 1963 up to year 2012. A Cartesian grid, dividing Earth into geographic regions, is considered. Entropy and the Jensen–Shannon divergence are used to analyze and compare real-world data. Hierarchical clustering and multi-dimensional scaling techniques are adopted for data visualization. Entropy-based indices have the advantage of leading to a single parameter expressing the relationships between the seismic data. Classical and generalized (fractional) entropy and Jensen–Shannon divergence are tested. The generalized measures lead to a clear identification of patterns embedded in the data and contribute to better understand earthquake distributions.

Entropy Analysis of Industrial Accident Data Series

Complex industrial plants exhibit multiple interactions among smaller parts and with human operators. Failure in one part can propagate across subsystem boundaries causing a serious disaster. This paper analyzes the industrial accident data series in the perspective of dynamical systems. First, we process real world data and show that the statistics of the number of fatalities reveal features that are well described by power law (PL) distributions. For early years, the data reveal double PL behavior, while, for more recent time periods, a single PL fits better into the experimental data. Second, we analyze the entropy of the data series statistics over time. Third, we use the Kullback–Leibler divergence to compare the empirical data and multidimensional scaling (MDS) techniques for data analysis and visualization. Entropy-based analysis is adopted to assess complexity, having the advantage of yielding a single parameter to express relationships between the data. The classical and the generalized (fractional) entropy and Kullback–Leibler divergence are used. The generalized measures allow a clear identification of patterns embedded in the data.

Fractional State Space Analysis of Economy Systems

This paper examines modern economic growth according to the multidimensional scaling (MDS) method and state space portrait (SSP) analysis. Electing GDP per capita as the main indicator for economic growth and prosperity, the long-run perspective from 1870 to 2010 identifies the main similarities among 34 world partners’ modern economic growth and exemplifies the historical waving mechanics of the largest world economy, the USA. MDS reveals two main clusters among the European countries and their old offshore territories, and SSP identifies the Great Depression as a mild challenge to the American global performance, when compared to the Second World War and the 2008 crisis.

Aerobic Exercise Does Not Predict Brain Derived Neurotrophic Factor And Cortisol Alterations in Depressed Patients

The pathophysiology of depression is related to neurobiological changes that occur in the monoamine system, hypothalamic-pituitary-adrenal axis, neurogenesis system and the neuroimmune system. In recent years, there has been a growing interest in the research of the effects of exercise on brain function, with a special focus on its effects on brainderived neurotrophic factor (BDNF), cortisol and other biomarkers. Thus, the aim of this study is to present a review investigating the acute and chronic effects of aerobic exercise on BDNF and cortisol levels in individuals with depression. It was not possible to establish an interaction between aerobic exercise and concentration of BDNF and cortisol, which may actually be the result of the divergence of methods, such as type of exercises, duration of the sessions, and prescribed intensity and frequency of sessions.