Pre-meal tomato (Lycopersicon esculentum) intake can have anti-obesity effects in young women?

The effect of pre-meal tomato intake in the anthropometric indices and blood levels of triglycerides, cholesterol, glucose, and uric acid of a young women population (n=35, 19.6 ± 1.3 years) was evaluated. During 4 weeks, daily, participants ingested a raw ripe tomato (~90 g) before lunch. Their anthropometric and biochemical parameters were measured repeatedly during the follow-up time. At the end of the 4 weeks, significant reductions were observed on body weight (-1.09 ± 0.12 kg on average), % fat (-1.54 ± 0.52%), fasting blood glucose (-5.29 ± 0.80 mg/dl), triglycerides (-8.31 ± 1.34 mg/dl), cholesterol (-10.17 ± 1.21 mg/ dl), and uric acid (-0.16 ± 0.04 mg/dl) of the participants. The tomato pre-meal ingestion seemed to interfere positively in body weight, fat percentage, and blood levels of glucose, triglycerides, cholesterol, and uric acid of the young adult women that participated in this study.

Comércio bilateral Portugal - Brasil

Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do Grau de Mestre em Empreendedorismo e Internacionalização Orientadora: Professora Doutora Celsa Maria de Carvalho Machado

A Data Mining Framework for Electric Load Profiling

This paper consists in the characterization of medium voltage (MV) electric power consumers based on a data clustering approach. It is intended to identify typical load profiles by selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The best partition is selected using several cluster validity indices. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ behavior. The data-mining-based methodology presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partitions. To validate our approach, a case study with a real database of 1.022 MV consumers was used.

A Data-mining-based Methodology to support MV Electricity Customers' Characterization

This paper presents an electricity medium voltage (MV) customer characterization framework supportedby knowledge discovery in database (KDD). The main idea is to identify typical load profiles (TLP) of MVconsumers and to develop a rule set for the automatic classification of new consumers. To achieve ourgoal a methodology is proposed consisting of several steps: data pre-processing; application of severalclustering algorithms to segment the daily load profiles; selection of the best partition, corresponding tothe best consumers’ segmentation, based on the assessments of several clustering validity indices; andfinally, a classification model is built based on the resulting clusters. To validate the proposed framework,a case study which includes a real database of MV consumers is performed.

Load Profiling Tool to Support Smart Grid Operation Scenarios

This paper presents the characterization of high voltage (HV) electric power consumers based on a data clustering approach. The typical load profiles (TLP) are obtained selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The choice of the best partition is supported using several cluster validity indices. The proposed data-mining (DM) based methodology, that includes all steps presented in the process of knowledge discovery in databases (KDD), presents an automatic data treatment application in order to preprocess the initial database in an automatic way, allowing time saving and better accuracy during this phase. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ consumption behavior. To validate our approach, a case study with a real database of 185 HV consumers was used.

Power Law Behavior and Self-similarity in Modern Industrial Accidents

Advances in technology have produced more and more intricate industrial systems, such as nuclear power plants, chemical centers and petroleum platforms. Such complex plants exhibit multiple interactions among smaller units and human operators, rising potentially disastrous failure, which can propagate across subsystem boundaries. This paper analyzes industrial accident data-series in the perspective of statistical physics and dynamical systems. Global data is collected from the Emergency Events Database (EM-DAT) during the time period from year 1903 up to 2012. The statistical distributions of the number of fatalities caused by industrial accidents reveal Power Law (PL) behavior. We analyze the evolution of the PL parameters over time and observe a remarkable increment in the PL exponent during the last years. PL behavior allows prediction by extrapolation over a wide range of scales. In a complementary line of thought, we compare the data using appropriate indices and use different visualization techniques to correlate and to extract relationships among industrial accident events. This study contributes to better understand the complexity of modern industrial accidents and their ruling principles.

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.

Gait Selection for Quadruped Legged Robots

This paper studies periodic gaits of quadruped locomotion systems. The purpose is to determine the best set of gait and locomotion variables for different robot velocities based on the system dynamics during walking. In this perspective, several performance measures are formulated and a set of experiments reveals the influence of the gait and locomotion variables upon those proposed indices. The results show that the locomotion parameters (β, LS and HB) should be adapted to the walking velocity in order to optimize the robot performance. Furthermore, for the case of a quadruped robot, we concluded that the gait should be adapted to VF .

Analysis of Two Arms Working in Cooperation

This paper analyzes the performance of two cooperative robot manipulators. In order to capture the working performancewe formulated several performance indices that measure the manipulability, the effort reduction and the equilibrium between the two robots. In this perspective the proposed indices we determined the optimal values for the system parameters. Furthermore, it is studied the implementation of fractional-order algorithms in the position/force control of two cooperative robotic manipulators holding an object.

Gait Analysis of Natural and Artificial Walking Systems

This paper studies periodic gaits of multi-legged locomotion systems based on dynamic models. The purpose is to determine the system performance during walking and the best set of locomotion variables. For that objective the prescribed motion of the robot is completely characterized in terms of several locomotion variables such as gait, duty factor, body height, step length, stroke pitch, foot clearance, legs link lengths, foot-hip offset, body and legs mass and cycle time. In this perspective, we formulate three performance measures of the walking robot namely, the mean absolute energy, the mean power dispersion and the mean power lost in the joint actuators per walking distance. A set of model-based experiments reveals the influence of the locomotion variables in the proposed indices.

Cascade Control of a Hexapod Robot

6th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines, Catania, Italy, 17-19 September

Quasi-periodic Gaits in Multi-legged Robots

5th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines

Energy analysis of Multi-legged Locomotion Systems

4th International Conference on Climbing and Walking Robots - From Biology to Industrial Applications

Fractional Dynamics in Forest Fires

Every year forest fires consume large areas, being a major concern in many countries like Australia, United States and Mediterranean Basin European Countries (e.g., Portugal, Spain, Italy and Greece). Understanding patterns of such events, in terms of size and spatiotemporal distributions, may help to take measures beforehand in view of possible hazards and decide strategies of fire prevention, detection and suppression. Traditional statistical tools have been used to study forest fires. Nevertheless, those tools might not be able to capture the main features of fires complex dynamics and to model fire behaviour [1]. Forest fires size-frequency distributions unveil long range correlations and long memory characteristics, which are typical of fractional order systems [2]. Those complex correlations are characterized by self-similarity and absence of characteristic length-scale, meaning that forest fires exhibit power-law (PL) behaviour. Forest fires have also been proved to exhibit time-clustering phenomena, with timescales of the order of few days [3]. In this paper, we study forest fires in the perspective of dynamical systems and fractional calculus (FC). Public domain forest fires catalogues, containing data of events occurred in Portugal, in the period 1980 up to 2011, are considered. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses. The frequency spectra of such signals are determined using Fourier transforms, and approximated through PL trendlines. The PL parameters are then used to unveil the fractional-order dynamics characteristics of the data. To complement the analysis, correlation indices are used to compare and find possible relationships among the data. It is shown that the used approach can be useful to expose hidden patterns not captured by traditional tools.

Melhoria e automação de linhas de montagem

Hoje em dia, e com os avanços tecnológicos a surgirem de forma constante, existem novas áreas que têm de ser consideradas com um foco importante por parte de todas as organizações, sendo uma delas a robótica industrial. Motivada em aumentar o seu output, as condições de trabalho para os seus colaboradores, bem como todas as condições de organização da logística interna, a Grohe Portugal, mais especificamente o departamento da montagem, achou relevante fazer um estudo de métodos e tempos, calculando os ganhos potenciais de aumento de output com introdução de robótica nas linhas dos cartuchos. Os objetivos principais seriam então, fazer uma restruturação de todo o layout dessas linhas, tendo como foco automatizar alguma(s) operação(ões), conseguindo assim uma melhoria significativa do output dessas linhas com o menor payback possível. Posto isto, esta dissertação pretende apresentar o trabalho desenvolvido junto da Grohe Portugal, que teve como objetivo fazer os estudos e a automatização de linhas de montagem de cartuchos, bem como melhorar algumas linhas de montagem tendo em conta fatores ergonómicos. Relativamente à automatização da linha dos cartuchos, foi importante estudar todos os seguintes aspetos:  utilização de unidades robóticas;  ergonomia;  ganhos de produtividade;  automatizar ou semi-automatizar operações;  simplificar processos de montagem;  simplificar setups;  solicitar orçamentos;  elaborar caderno de encargos. Para a realização deste projeto, o trabalho desenvolvido foi decomposto em várias etapas, entre as quais se destacam:  análise e estudo dos métodos e sequências de montagem;  levantamento de todos os componentes e operações de montagem até à obtenção do cartucho final;  estudo de tempos de todas essas operações de montagem;  caraterização de um novo layout para as linhas com a introdução de unidades robóticas, tanto quanto possível, mais adequadas;  elaboração de caderno de encargos para ser enviado a empresas, para estas poderem apresentar uma orçamentação, bem como indicar as unidades robóticas mais adequadas para as tarefas pretendidas;  automatização da linha dos cartuchos. Relativamente ao projeto de novas linhas de montagem tendo em conta fatores ergonómicos, de forma a melhorar os sistemas de abastecimento e as condições de trabalho por parte dos operadores, foram postos em prática diferentes passos, nomeadamente:  identificação de todos os processos de montagem realizados pelos operadores na linha a melhorar;  estudo e definição da disposição dos componentes na nova linha, bem como a sua forma de abastecimento;  projeto da nova linha de montagem em 3D com recurso ao software SolidWorks;  realização prática da linha, acompanhando e ajudando a equipa da ferramentaria. O balanço final do trabalho foi bastante positivo, tanto na automatização das linhas de montagem dos cartuchos, em que todo o seu estudo foi alcançado com sucesso, como no melhoramento ergonómico das linhas de montagem, tendo-se alcançado melhorias em alguns índices de qualidade, tempos de abastecimento, organização das linhas, e nas condições de iluminação, resultando essas melhorias numa avaliação positiva por parte dos colaboradores que nelas trabalham todos os dias.