18 resultados para oral pharmacological agents

em Instituto Politécnico do Porto, Portugal


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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.

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A emergência de multiresistência apresentada por microrganismos é um dos grandes desafios que enfrentam actualmente os profissionais de Saúde e a população em geral. Os factores que contribuem para o desenvolvimento de resistência a antibióticos na comunidade podem ser categorizados como comportamentais ou ambientais/políticas. O objectivo deste trabalho foi caracterizar a situação actual na visão dos Pais de alunos do pré-escolar e 1º ciclo. De modo a avaliar as necessidades de intervenção e as actividades a serem desenvolvidas, um instrumento para estudar os hábitos e comportamentos adoptados na utilização de antibióticos, foi adaptado, validado e aplicado numa amostra piloto.

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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.

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This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.

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The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using cooperative negotiation. Scheduling resolution requires the intervention of highly skilled human problem-solvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing (AC) evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference.

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Marine cyanobacteria have been considered a rich source of secondary metabolites with potential biotechnological applications, namely in the pharmacological field. Chemically diverse compounds were found to induce cytoxicity, anti-inflammatory and antibacterial activities. The potential of marine cyanobacteria as anticancer agents has however been the most explored and, besides cytotoxicity in tumor cell lines, several compounds have emerged as templates for the development of new anticancer drugs. The mechanisms implicated in the cytotoxicity of marine cyanobacteria compounds in tumor cell lines are still largely overlooked but several studies point to an implication in apoptosis. This association has been related to several apoptotic indicators such as cell cycle arrest, mitochondrial dysfunctions and oxidative damage, alterations in caspase cascade, alterations in specific proteins levels and alterations in the membrane sodium dynamics. In the present paper a compilation of the described marine cyanobacterial compounds with potential anticancer properties is presented and a review on the implication of apoptosis as the mechanism of cell death is discussed.

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The nitrogen heterocyclic organic compounds 1,4 dioxide pyrazine and quinoxaline derivatives have been widely studied due to their potential use as synthetic drugs. The thermochemical study of three N,N´-dioxides: 2,3,5-trimethylpyrazine-1,4-dioxide, tetramethylpyrazine-1,4-dioxide and 6-chloro-2,3-dimethilquinoxaline 1,4-dioxide has been recently developed in order to establish relationships among the energetical, structural and reactivity properties [4,5]. Several studies have reported their pharmacological activity, particularly as antimicrobial agents [1,2,3]. It has also been established a relation between energetical and structural properties and biological activity, once these compounds present N – oxide bonds, increasing their oxidative capacity. The present work reports the study of antimicrobial activity for those compounds against the bacteria Geobacillus stearothermophylus, Staphylococcus aureus, Streptococcus agalactiae, Escherichia coli and also against the yeasts Saccharomyces cerevisiae PYCC 4072, Candida albicans PYCC3436T, Candida tropicalis PYCC, Issatchenka Orientalis PYCC. The determination of the minimal inhibitory concentration (MIC), points to an antimicrobial activity and the preliminary results indicate that these compounds may be potential candidates as antimicrobial drugs with clinical, agriculture or food industries applications.

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Com o crescimento das Tecnologias de Informação e Comunicação os métodos de ensino também foram evoluindo, verificando-se assim mudanças bastante significativas na forma como se adquire o conhecimento. O aparecimento do ensino à distância aliado aos meios digitais, que estão cada vez mais disponíveis e acessíveis, tanto a alunos como a professores, são um excelente complemento à actividade lectiva. Exemplo disso é mesmo o caso do e-learning que veio revolucionar todo o processo de aquisição de conhecimento, deixando para segundo plano pormenores como o local ou a hora de aquisição do conhecimento. Entre muitos tipos de recursos disponíveis, os OA’s (Objecto de Aprendizagem) têm uma utilização cada vez mais frequente. No levantamento do estado da arte e no estudo dos recursos educativos utilizados actualmente na Medicina Dentária, foi assinalado a utilização recorrente dos OA’s, que basicamente são pequenos pedaços de informação que podem ser reutilizados ou referenciados tecnologicamente. Seguidamente, iniciou-se a realização de um OA que pudesse servir de apoio ao ensino da Medicina Dentária, focando-se concretamente na higiene oral para as crianças entre os 7 e 12 anos. Finalmente, procedeu-se à sua validação conclui-se que no futuro será possível a sua reutilização em diferentes contextos de ensino e aprendizagem na área.

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Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.

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Mestrado em Ensino de Inglês e de Francês ou Espanhol no Ensino Básico

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This paper reports the development of a B2B platform for the personalization of the publicity transmitted during the program intervals. The platform as a whole must ensure that the intervals are filled with ads compatible with the profile, context and expressed interests of the viewers. The platform acts as an electronic marketplace for advertising agencies (content producer companies) and multimedia content providers (content distribution companies). The companies, once registered at the platform, are represented by agents who negotiate automatically the price of the interval timeslots according to the specified price range and adaptation behaviour. The candidate ads for a given viewer interval are selected through a matching mechanism between ad, viewer and the current context (program being watched) profiles. The overall architecture of the platform consists of a multiagent system organized into three layers consisting of: (i) interface agents that interact with companies; (ii) enterprise agents that model the companies, and (iii) delegate agents that negotiate a specific ad or interval. The negotiation follows a variant of the Iterated Contract Net Interaction Protocol (ICNIP) and is based on the price/s offered by the advertising agencies to occupy the viewer’s interval.

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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 (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

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The ready biodegradability of four chelating agents, N,N -(S,S)-bis[1-carboxy-2-(imidazol-4-yl)ethyl]ethylenediamine (BCIEE), N - ethylenedi-L-cysteine (EC), N,N -bis (4-imidazolymethyl)ethylenediamine (EMI) and 2,6-pyridine dicarboxylic acid (PDA), was tested according to the OECD guideline for testing of chemicals. PDA proved to be a readily biodegradable substance. However, none of the other three compounds were degraded during the 28 days of the test. Chemical simulations were performed for the four compounds in order to understand their ability to complex with some metal ions (Ca, Cd, Co, Cu, Fe, Mg, Mn, Ni, Pb, Zn) and discuss possible applications of these chelating agents. Two different conditions were simulated: (i) in the presence of the chelating agent and one metal ion, and (ii) in the simultaneous presence of the chelating agent and all metal ions with an excess of Ca. For those compounds that were revealed not to be readily biodegradable (BCIEE, EC and EMI), applications were evaluated where this property was not fundamental or even not required. Chemical simulations pointed out that possible applications for these chelating agents are: food fortification, food process, fertilizers, biocides, soil remediation and treatment of metal poisoning. Additionally, chemical simulations also predicted that PDA is an efficient chelating agent for Ca incrustations removal, detergents and for pulp metal ions removal process.

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O presente relatório foi elaborado no âmbito do estágio de Prática Educativa I, II e III, do curso de 2.º ciclo do Mestrado em Ensino do Inglês e Francês ou Espanhol no Ensino Básico, da Escola Superior de Educação. Ao longo deste relatório reflicto sobre as minhas práticas, incidindo em dois aspectos basilares para a realização deste trabalho: o modo como se processam as estratégias que concorrem para que seja possível promover a interacção oral dos alunos em sala de aula, e consequente desenvolvimento da sua competência comunicativa em língua estrangeira; e a forma como planifiquei actividades assentes em recursos diversificados, nomeadamente, jogos, histórias, flashcards, vídeo, roleplay, canções e debate. De forma a documentar as minhas reflexões, faço uma análise a algumas planificações de aulas em que utilizei os recursos mencionados, incluindo algumas imagens ilustrativas desses momentos. Concluo o relatório tecendo algumas considerações finais sobre o percurso que tracei na qualidade de aluna deste mestrado e de futura professora, reflectindo sobre alguns aspectos que considero relevantes na construção da profissionalidade docente.