Multi-scale modeling of the mechanical behavior of polymer-based materials

Polymers have become the reference material for high reliability and performance applications. In this work, a multi-scale approach is proposed to investigate the mechanical properties of polymeric based material under strain. To achieve a better understanding of phenomena occurring at the smaller scales, a coupling of a Finite Element Method (FEM) and Molecular Dynamics (MD) modeling in an iterative procedure was employed, enabling the prediction of the macroscopic constitutive response. As the mechanical response can be related to the local microstructure, which in turn depends on the nano-scale structure, the previous described multi-scale method computes the stress-strain relationship at every analysis point of the macro-structure by detailed modeling of the underlying micro- and meso-scale deformation phenomena. The proposed multi-scale approach can enable prediction of properties at the macroscale while taking into consideration phenomena that occur at the mesoscale, thus offering an increased potential accuracy compared to traditional methods.

Predicting the mechanical behavior of amorphous polymeric materials under strain through multi-scale simulation

Polymeric materials have become the reference material for high reliability and performance applications. However, their performance in service conditions is difficult to predict, due in large part to their inherent complex morphology, which leads to non-linear and anisotropic behavior, highly dependent on the thermomechanical environment under which it is processed. In this work, a multiscale approach is proposed to investigate the mechanical properties of polymeric-based material under strain. To achieve a better understanding of phenomena occurring at the smaller scales, the coupling of a finite element method (FEM) and molecular dynamics (MD) modeling, in an iterative procedure, was employed, enabling the prediction of the macroscopic constitutive response. As the mechanical response can be related to the local microstructure, which in turn depends on the nano-scale structure, this multiscale approach computes the stress-strain relationship at every analysis point of the macro-structure by detailed modeling of the underlying micro- and meso-scale deformation phenomena. The proposed multiscale approach can enable prediction of properties at the macroscale while taking into consideration phenomena that occur at the mesoscale, thus offering an increased potential accuracy compared to traditional methods.

A JOINT EXPERIMENTAL ANALYSIS OF INVESTOR BEHAVIOR IN IPO PRICING METHODS

This article jointly examines the differences of laboratory versions of the Dutch clock open auction, a sealed-bid auction to represent book building, and a two-stage sealed bid auction to proxy for the “competitive IPO”, a recent innovation used in a few European equity initial public offerings. We investigate pricing, seller allocation, and buyer welfare allocation efficiency and conclude that the book building emulation seems to be as price efficient as the Dutch auction, even after investor learning, whereas the competitive IPO is not price efficient, regardless of learning. The competitive IPO is the most seller allocative efficient method because it maximizes offer proceeds. The Dutch auction emerges as the most buyer welfare allocative efficient method. Underwriters are probably seeking pricing efficiency rather than seller or buyer welfare allocative efficiency and their discretionary pricing and allocation must be important since book building is prominent worldwide.

Learning techniques for automatic email message tagging

A organização automática de mensagens de correio electrónico é um desafio actual na área da aprendizagem automática. O número excessivo de mensagens afecta cada vez mais utilizadores, especialmente os que usam o correio electrónico como ferramenta de comunicação e trabalho. Esta tese aborda o problema da organização automática de mensagens de correio electrónico propondo uma solução que tem como objectivo a etiquetagem automática de mensagens. A etiquetagem automática é feita com recurso às pastas de correio electrónico anteriormente criadas pelos utilizadores, tratando-as como etiquetas, e à sugestão de múltiplas etiquetas para cada mensagem (top-N). São estudadas várias técnicas de aprendizagem e os vários campos que compõe uma mensagem de correio electrónico são analisados de forma a determinar a sua adequação como elementos de classificação. O foco deste trabalho recai sobre os campos textuais (o assunto e o corpo das mensagens), estudando-se diferentes formas de representação, selecção de características e algoritmos de classificação. É ainda efectuada a avaliação dos campos de participantes através de algoritmos de classificação que os representam usando o modelo vectorial ou como um grafo. Os vários campos são combinados para classificação utilizando a técnica de combinação de classificadores Votação por Maioria. Os testes são efectuados com um subconjunto de mensagens de correio electrónico da Enron e um conjunto de dados privados disponibilizados pelo Institute for Systems and Technologies of Information, Control and Communication (INSTICC). Estes conjuntos são analisados de forma a perceber as características dos dados. A avaliação do sistema é realizada através da percentagem de acerto dos classificadores. Os resultados obtidos apresentam melhorias significativas em comparação com os trabalhos relacionados.

Factors affecting nutrition behavior among middle-class adolescents in urban area of Northern region of Brazil

INTRODUCTION: Brazil has been called a nation in nutrition transitional because of recent increases in the prevalence of obesity and related chronic diseases. With overweight conditions already prevalent among middle-income populations, there exists a need to identify factors that influence nutrition behavior within this group. OBJECTIVE: To address this subject, a research study was implemented among middle-class adolescents attending a large private secondary school in Manaus, Amazonas, Brazil. The study determined the availability and accessibility of snack foods as well as subjects’ attitudes and preferences towards, and the influence of family and friends on healthy (high-nutrient density) snack choices. METHODS: The 4-stage process included: (a) a nutrition expert focus group discussion that reported local nutrition problems in general and factors related to adolescent nutrition, (b) an adolescent pilot survey (n=63) that solicited information about snacking preferences and habits as well as resources for nutrition information and snack money; (c) a survey of various area food market sources to determine the availability and accessibility of high nutrient density snacks; and (d) a follow-up adolescent survey (n=55) that measured snack food preferences and perceptions about their cost and availability. RESULTS: Results included the finding that, although affordable high nutrient density snacks were available, preferences for low nutrient density snacks prevailed. The adolescents were reportedly more likely to be influenced by and obtain nutrition information from family members than friends. CONCLUSION: From study results it is apparent that a focus on food availability will not automatically result in proper nutritional practices among adolescents. This fact and the parental influence detected are evidence of a need to involve adolescents and their parents in nutrition education campaigns to improve adolescent snack food choices.

Influence of HIV positive status on sexual behavior among males

OBJECTIVE: To compare HIV seronegative (HIV-) and HIV seropositive (HIV+) males in terms of sexual behavior with female and male partners of different types. METHOD: Cross-sectional study. From August 1994 to February 1995, a sample of 236 respondents (150 HIV- and 86 HIV+) recruited from public health centers in the State of S. Paulo (Brazil), answered a questionnaire, including questions on demographic aspects, HIV and AIDS related knowledge, sexual orientation, use of alcohol and other drugs, sexual behavior with regular and casual female and male partners, and perceived risk of HIV infection. Sexual behavior with regular and casual female and male partners within the previous three months, was investigated. RESULTS: A lower proportion of HIV+ engaged in sexual contact with regular female partners (p < .01) and in vaginal intercourse with this type of partner (p < .01). A lower proportion of HIV+ engaged in overall sexual activity (p < .001) and reported lower frequency of penetrative sexual practices (p < .05). A high level of condom use with female and male partners was identified with no significant differences being found between the two serostatus groups. Some risky sexual behavior was identified, however, especially with regular partners, suggesting that some men were continuing to practice unsafe sex. CONCLUSIONS: The high level of condom use identified suggests that safer sex advice has been taken up. Condom use was not universal, however, and some men continue to place themselves at risk, especially with regular partners. Prevention programs should strive not only to encourage HIV- to practice safer sex, but also to encourage HIV+ to do so in order to prevent further transmission of the virus.

Enhancing reflexivity and technology in translation learning: case study on the use of ePortfolio as a training environment

In this paper we describe a casestudy of an experiment on how reflexivity and technology can enhance learning, by using ePorfolios as a training environment to develop translation skills. Translation is today a multiskilled job and translators need to assure their clients a good performance and quality, both in language and in technology domains. In order to accomplish it, for the translator all the tasks and processes he develops appear as crucial, being pretranslation and posttranslation processes equally important as the translation itself, namely as far as autonomy, reflexive and critical skills are concerned. Finally, the need and relevance for collaborative tasks and networks amongst virtual translation communities, led us to the decision of implementing ePortfolios as a tool to develop the requested skills and extend the use of Internet in translation, namely in terminology management phases, for the completion of each task, by helping students in the management of the projects deadlines, improving their knowledge on the construction and management of translation resources and deepening their awareness about the concepts related to the development and usability of ePorfolios.

Knowledge sharing and learning processes: case study of portuguese technological schools and higher education institutions

Paper to be presented at the ESREA Conference Learning to Change? The Role of Identity and Learning Careers in Adult Education, 7-8 December, 2006, Université Catholique Louvain, Louvain–la-Neuve, Belgium

A influência do contexto familiar no aparecimento de dor espinal em crianças do concelho da Maia

A dor espinal em crianças e jovens constitui um problema cujas dimensões e prevalência tem vindo aumentar nas últimas décadas. Esta problemática parece ser tanto mais significativa se for tido em consideração que os episódios de dor espinal na idade escolar se perpetuam e estão relacionados com os que acontecem na idade adulta. Desta forma, os investigadores alertam para a necessidade de identificar potenciais factores de risco para o desenvolvimento de dor espinal em crianças e jovens de idade escolar. Assim, o presente estudo pretende identificar qual a importância assumida pelo contexto familiar na presença de queixas dolorosas espinais nas crianças em idade escolar do concelho da Maia. A amostra é constituída pelos pais de 1017 crianças do 1º ciclo do Ensino Básico do Concelho da Maia que foram avaliadas relativamente à postura, numa fase anterior do estudo. Desta população constituiu amostra 636 pais que concordaram participar no estudo, tendo obtido resposta de 226, obtendo uma percentagem de adesão de 35,5%. Para a obtenção dos dados qualitativos foi utilizado um método de amostragem estratégica de forma a seleccionar dez pais representativos de todas as categorias possíveis (pais com e sem dor e filhos com e sem dor). Esta amostra foi seleccionada tendo em conta os dados obtidos no questionário Parental Pain e Questionário de Bournemouth, sendo, posteriormente aplicado uma entrevista não estruturada. Os principais resultados obtidos permitiram concluir que o contexto tem uma influência determinante na criança com dor. De acordo com os dados extraídos das entrevistas, os comportamentos de manifestação de dor por parte das crianças podem ser um reflexo de comportamentos apreendidos através da observação do comportamento dos adultos e, consequentemente mimetizados, opinião esta igualmente expressa por alguns dos pais. Mas nem sempre os pais apontam a mimetização como causa para a dor referida pelos filhos, referindo igualmente o transporte da mochila, as posturas assumidas no dia-a-dia, o mobiliário escolar e as actividades de lazer realizadas pelas crianças.

Learning business strategies for competitive electronic marketplaces

This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

Intelligent decision making in electricity markets: simulated annealing Q-Learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

Cost dependent strategy for electricity markets bidding based on adaptive reinforcement learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.

Seller, buyer and VPP agents behavior on a simulated electricity market

Competitive electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is an electricity market simulator able to model market players and simulate their operation in the market. As market players are complex entities, having their characteristics and objectives, making their decisions and interacting with other players, a multi-agent architecture is used and proved to be adequate. MASCEM players have learning capabilities and different risk preferences. They are able to refine their strategies according to their past experience (both real and simulated) and considering other agents’ behavior. Agents’ behavior is also subject to its risk preferences.

Case-based reasoning for self-optimizing behavior

In this paper we present a Self-Optimizing module, inspired on Autonomic Computing, acquiring a scheduling system with the ability to automatically select a Meta-heuristic to use in the optimization process, so as its parameterization. Case-based Reasoning was used so the system may be able of learning from the acquired experience, in the resolution of similar problems. From the obtained results we conclude about the benefit of its use.

Sistema de recomendação para plataformas de e-learning

O aumento do número de recursos digitais disponíveis dificulta a tarefa de pesquisa dos recursos mais relevantes, no sentido de se obter o que é mais relevante. Assim sendo, um novo tipo de ferramentas, capaz de recomendar os recursos mais apropriados às necessidades do utilizador, torna-se cada vez mais necessário. O objetivo deste trabalho de I&D é o de implementar um módulo de recomendação inteligente para plataformas de e-learning. As recomendações baseiam-se, por um lado, no perfil do utilizador durante o processo de formação e, por outro lado, nos pedidos efetuados pelo utilizador, através de pesquisas [Tavares, Faria e Martins, 2012]. O e-learning 3.0 é um projeto QREN desenvolvido por um conjunto de organizações e tem com objetivo principal implementar uma plataforma de e-learning. Este trabalho encontra-se inserido no projeto e-learning 3.0 e consiste no desenvolvimento de um módulo de recomendação inteligente (MRI). O MRI utiliza diferentes técnicas de recomendação já aplicadas noutros sistemas de recomendação. Estas técnicas são utilizadas para criar um sistema de recomendação híbrido direcionado para a plataforma de e-learning. Para representar a informação relevante, sobre cada utilizador, foi construído um modelo de utilizador. Toda a informação necessária para efetuar a recomendação será representada no modelo do utilizador, sendo este modelo atualizado sempre que necessário. Os dados existentes no modelo de utilizador serão utilizados para personalizar as recomendações produzidas. As recomendações estão divididas em dois tipos, a formal e a não formal. Na recomendação formal o objetivo é fazer sugestões relacionadas a um curso específico. Na recomendação não-formal, o objetivo é fazer sugestões mais abrangentes onde as recomendações não estão associadas a nenhum curso. O sistema proposto é capaz de sugerir recursos de aprendizagem, com base no perfil do utilizador, através da combinação de técnicas de similaridade de palavras, um algoritmo de clustering e técnicas de filtragem [Tavares, Faria e Martins, 2012].