Soleus activity in post-stroke subjects: movement sequence from standing to sitting

O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

Spatio-temporal alignment of pedobarographic image sequences

O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

Comparative analysis of the ground reaction forces, during the support phase, in a group of pregnant women on their 3rd trimester of pregnancy and in a group of not pregnant women

PURPOSE: To analyze and compare the Ground Reaction Forces (GRF), during the stance phase of walking in pregnant women in the 3rd trimester of pregnancy, and non pregnant women. METHODS: 20 women, 10 pregnant and 10 non pregnant, voluntarily took part in this study. GRF were measured (1000 Hz) using a force platform (BERTEC 4060-15), an amplifier (BERTEC AM 6300) and an analogical-digital converter of 16 Bits (Biopac). RESULTS: The study showed that there were significant differences among the two groups concerning absolute values of time of the stance phase. In what concerns to the normalized values the most significant differences were verified in the maximums values of vertical force (Fz3, Fz1) and in the impulse of the antero-posterior force (Fy2), taxes of growth of the vertical force, and in the period of time for the antero-posterior force (Fy) be null. CONCLUSIONS: It is easier for the pregnant to continue forward movement (push-off phase). O smaller growth rates in what concerns to the maximum of the vertical force (Fz1) for the pregnant, can be associated with a slower speed of gait, as an adaptation strategy to maintain the balance, to compensate the alterations in the position of her center of gravity due to the load increase. The data related to the antero-posterior component of the force (Fy), shows that there is a significant difference between the pregnant woman’s left foot and right foot, which accuses a different functional behavior in each one of the feet, during the propulsion phase (TS).

João Romano Torres e Cia: hermenêutica social de uma editora

Em 29 de Outubro de 1885 era publicado o primeiro número d’O Recreio, Publicação Semanal, Litteraria e Charadistica, criado e dirigido por Ignacio Moreira. No número 26, de 9 de Agosto de 1886, na primeira página, sob o título “Expediente”, dá-se conta aos leitores e aos colaboradores que “d’este numero em deante toda a correspondencia deve ser dirigida a João Romano Torres, rua Nova de S. Mamede, aos Caldas, 26, 3.º - Lisboa” (p. 201). Para João Romano Torres, que acabara de adquirir a publicação, trata-se de um acto refundacional, que significará para o editor o início de um percurso editorial através do qual se dará origem a uma editora cuja actividade chegará ao último quartel do século seguinte, estabelecendo um catálogo que a tornou reconhecível e reconhecida no espaço do livro em Portugal. Desta editora se falará aqui apenas de um período situado entre o ano de 1885 e o fim da primeira década de 1900. ABSTRACT - On the 29th October 1885, the first issue of O Recreio, Publicação Semanal, Litteraria e Charadística (proposed English translation: The Playground, Weekly, Literary and Charades Publication) was published, created and headed by Ignacio Moreira. On the 26th issue, issued on the 9th August 1886, in the front page, under the headline “Dispatch”, it is imparted with readers and collaborators that “from this issue forward, all correspondence should be addressed to João Romano Torres, Nova de S. Mamede street, at Caldas, 26, 3rd - Lisbon” (p. 201). For João Romano Torres, who had just acquired the publication, this was a re-foundational act, which will represent for this publisher the beginning of a publishing trajectory through which a new publishing house will emerge, whose activity will reach the final quarter of the next century, establishing a catalogue which made it recognizable and recognized in the book field in Portugal. This publishing house will be addressed here regarding only the period spanning from the year 1885 to the end of the first decade of the 1900s.

A decision-support system based on particle swarm optimization for multiperiod hedging in electricity markets

This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.

Electricity Markets Simulation: MASCEM Contributions to the Challenging Reality

Electricity Markets are not only a new reality but an evolving one as the involved players and rules change at a relatively high rate. Multi-agent simulation combined with Artificial Intelligence techniques may result in sophisticated tools very helpful under this context. Some simulation tools have already been developed, some of them very interesting. However, at the present state it is important to go a step forward in Electricity Markets simulators as this is crucial for facing changes in Power Systems. This paper explains the context and needs of electricity market simulation, describing the most important characteristics of available simulators. We present our work concerning MASCEM simulator, presenting its features as well as the improvements being made to accomplish the change and challenging reality of Electricity Markets.

MASCEM: electricity markets simulation with strategic agents

Electricity markets are complex environments, involving numerous entities trying to obtain the best advantages and profits while limited by power-network characteristics and constraints.1 The restructuring and consequent deregulation of electricity markets introduced a new economic dimension to the power industry. Some observers have criticized the restructuring process, however, because it has failed to improve market efficiency and has complicated the assurance of reliability and fairness of operations. To study and understand this type of market, we developed the Multiagent Simulator of Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short- and mediumterm simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.

A long-term swarm intelligence hedging tool applied to electricity markets

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.

Research on evaluation system of emergency disposal plan for power plant incidents

This paper starts with the analysis of the unusual inherence mechanism, from two aspects: accumulating and human error. We put forward twelve factors affected the decision of the emergency treatment plan in practice and summarized the evaluation index system combining with literature data. Then we screened out eighteen representative indicators by used the FDM expert questionnaire in the first phase. Hereafter, we calculated the weight of evaluation index and sorted them by the FAHP expert questionnaire, and came up with the frame of the evaluation rule by combined with the experience. In the end, the evaluation principles are concluded.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

The darmstadt challenge (the turing test revisited)

Significant work has been done in the areas of Pervcomp/Ubicomp Smart Environments with advances on making proactive systems, but those advances have not made these type of systems accurately proactive. On the other hand a great deal is needed to make systems more sensible/sensitive and trustable (both in terms of reliability and privacy). We put forward the thesis that a more integral and social-aware sort of intelligence is needed to effectively interact, decide and act on behalf of people’s interest and that a way to test how effective systems are achieving these desirable behaviour is needed as a consequence. We support our thesis by providing examples on how to measure effectiveness in variety of different environments.

O grau de autonomia dos técnicos de cardiopneumologia

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Qualidade e Tecnologias da Saúde.

A inclusão de alunos com problemáticas graves: revisão de dissertações e projetos de investigação realizados no âmbito do Mestrado em Educação Especial da ESELx.

Este artigo pretende passar em revista de um conjunto de trabalhos, Dissertações e Projetos de Intervenção, realizados no âmbito do Mestrado em Educação Especial da Escola Superior de Educação de Lisboa, relacionados com a inclusão de alunos com problemáticas graves. O nosso propósito foi dar conta da investigação que se tem produzido no âmbito do curso, focando a emergência de temáticas relacionadas com a inclusão, de estudos iniciais de carácter descritivo e exploratório (ex: descrição de contextos e práticas educativas, percepções dos docentes sobre a inclusão) a, mais recentemente, estudos com objectivos mais precisos (ex: estudos sobre as interacções entre pares, a utilização de tecnologias de apoio à comunicação e aprendizagem) e projectos de intervenção (ex: inclusão de alunos com problemas graves em actividades com alunos com desenvolvimento típico, formação de Assistentes Operacionais). A nossa revisão foca-se também na evolução das metodologias adotadas (progressivo recurso a fontes diversificadas de informação e a dados de observação direta). Estes trabalhos, finalizados entre 2010 e 2012, são aqui revistos organizados em função de linhas de investigação. Nas notas finais apresentam-se sugestões de possíveis estudos futuros.

A importância do relacionamento bancário no financiamento das PME

Dissertação de Mestrado em Finanças Empresariais

Planeamento espacial marinho das áreas marinhas protegidas: o caso de estudo da ára protegida de gestão de recursos: Caloura - ilhéu de Vila Franca do Campo

Tese de Doutoramento, Ciências do Mar (Ecologia Marinha), 26 de Novembro de 2013, Universidade dos Açores.