946 resultados para neuromuscular blocking agent
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Portugal é o país que mais transplantes hepáticos efectuou a nível mundial e o segundo com maior número de dadores por milhão de habitantes, com a região centro do país a liderar a doação de órgãos. Esta liderança na área da transplantação hepática contribui também para as elevadas taxas de sobrevivência destes doentes, suportada pela excelência técnica de uma equipa multidisciplinar diferenciada, complementada por recentes avanços terapêuticos. Portugal é, também a nível mundial, o país com maior número de casos de polineuropatia amiloidótica familiar (PAF), variante TTRmet30 (proteína transtirretina mutada) tipo português, diagnosticados, sendo em algumas regiões considerada como uma doença endémica. Apesar de novas terapêuticas em estudo (exemplo: Tafamidis), até à data o transplante hepático parece ser a única terapêutica com eficácia ao retardar ou mesmo na estabilização da evolução desta doença hereditária e degenerativa, progressiva e fatal no prazo de 10-15 anos após o início da sintomatologia.
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This paper describes the development and the implementation of a multi-agent system for integrated diagnosis of power transformers. The system is divided in layers which contain a number of agents performing different functions. The social ability and cooperation between the agents lead to the final diagnosis and to other relevant conclusions through integrating various monitoring technologies, diagnostic methods and data sources, such as the dissolved gas analysis.
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This paper presents MASCEM - Multi-Agent Simulator for Electricity Markets improvement towards an enlarged model for Seller Agents coalitions. The simulator has been improved, both regarding its user interface and internal structure. The OOA, used as development platform, version was updated and the multi-agent model was adjusted for implementing and testing several negotiations regarding Seller agents’ coalitions. Seller coalitions are a very important subject regarding the increased relevance of Distributed Generation under liberalised electricity markets.
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The increasing number of players that operate in power systems leads to a more complex management. In this paper a new multi-agent platform is proposed, which simulates the real operation of power system players. MASGriP – A Multi-Agent Smart Grid Simulation Platform is presented. Several consumer and producer agents are implemented and simulated, considering real characteristics and different goals and actuation strategies. Aggregator entities, such as Virtual Power Players and Curtailment Service Providers are also included. The integration of MASGriP agents in MASCEM (Multi-Agent System for Competitive Electricity Markets) simulator allows the simulation of technical and economical activities of several players. An energy resources management architecture used in microgrids is also explained.
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The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.
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Renewable based power generation has significantly increased over the last years. However, this process has evolved separately from electricity markets, leading to an inadequacy of the present market models to cope with huge quantities of renewable energy resources, and to take full advantage of the presently existing and the increasing envisaged renewable based and distributed energy resources. This paper proposes the modelling of electricity markets at several levels (continental, regional and micro), taking into account the specific characteristics of the players and resources involved in each level and ensuring that the proposed models accommodate adequate business models able to support the contribution of all the resources in the system, from the largest to the smaller ones. The proposed market models are integrated in MASCEM (Multi- Agent Simulator of Competitive Electricity Markets), using the multi agent approach advantages for overcoming the current inadequacy and significant limitations of the presently existing electricity market simulators to deal with the complex electricity market models that must be adopted.
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This paper presents a Multi-Agent Market simulator designed for analyzing 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. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agents reactions.
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Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.
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This paper presents a new methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using the multi-agent market simulator MASCEM, taking advantage of its ability to provide the means to model and simulate VPP (Virtual Power Producers). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. The new features include the development of particular individual facilitators to manage the communications amongst the members of each coalition independently from the rest of the simulation, and also the mechanisms for the classification of the agents that are candidates to join the coalition. In addition, a global study on the results of the Iberian Electricity Market is performed, to compare and analyze different approaches for defining consistent and adequate strategies to integrate into the agents of MASCEM. This, combined with the application of learning and prediction techniques provide the agents with the ability to learn and adapt themselves, by adjusting their actions to the continued evolving states of the world they are playing in.
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This paper presents a new architecture for the MASCEM, a multi-agent electricity market simulator. This is implemented in a Prolog which is integrated in the JAVA program by using the LPA Win-Prolog Intelligence Server (IS) provides a DLL interface between Win-Prolog and other applications. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets.
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The scheduling problem is considered in complexity theory as a NP-hard combinatorial optimization problem. Meta-heuristics proved to be very useful in the resolution of this class of problems. However, these techniques require parameter tuning which is a very hard task to perform. A Case-based Reasoning module is proposed in order to solve the parameter tuning problem in a Multi-Agent Scheduling System. A computational study is performed in order to evaluate the proposed CBR module performance.
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This paper describes a Multi-agent Scheduling System that assumes the existence of several Machines Agents (which are decision-making entities) distributed inside the Manufacturing System that interact and cooperate with other agents in order to obtain optimal or near-optimal global performances. Agents have to manage their internal behaviors and their relationships with other agents via cooperative negotiation in accordance with business policies defined by the user manager. Some Multi Agent Systems (MAS) organizational aspects are considered. An original Cooperation Mechanism for a Team-work based Architecture is proposed to address dynamic scheduling using Meta-Heuristics.
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Group decision making plays an important role in organizations, especially in the present-day economy that demands high-quality, yet quick decisions. Group decision-support systems (GDSSs) are interactive computer-based environments that support concerted, coordinated team efforts toward the completion of joint tasks. The need for collaborative work in organizations has led to the development of a set of general collaborative computer-supported technologies and specific GDSSs that support distributed groups (in time and space) in various domains. However, each person is unique and has different reactions to various arguments. Many times a disagreement arises because of the way we began arguing, not because of the content itself. Nevertheless, emotion, mood, and personality factors have not yet been addressed in GDSSs, despite how strongly they influence results. Our group’s previous work considered the roles that emotion and mood play in decision making. In this article, we reformulate these factors and include personality as well. Thus, this work incorporates personality, emotion, and mood in the negotiation process of an argumentbased group decision-making process. Our main goal in this work is to improve the negotiation process through argumentation using the affective characteristics of the involved participants. Each participant agent represents a group decision member. This representation lets us simulate people with different personalities. The discussion process between group members (agents) is made through the exchange of persuasive arguments. Although our multiagent architecture model4 includes two types of agents—the facilitator and the participant— this article focuses on the emotional, personality, and argumentation components of the participant agent.
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Tese de Doutoramento, Biologia (Biologia Celular e Molecular), 18 de Novembro de 2013, Universidade dos Açores.
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Introdução: A aplicação das técnicas de Contrair-Relaxar com Contracção do Antagonista (CRCA) e de Músculo Energia (TME) promovem um aumento da flexibilidade muscular, contudo poucos estudos comparam a eficácia de ambas. Apresentam aspectos comuns como a contracção prévia do músculo a alongar sendo esta máxima na CRCA e uma percentagem da máxima na TME. Contudo, alguma evidência sugere que não existe correspondência entre a força produzida e a desejada pelo que este aspecto da TME carece de explicação. Objectivos: Confirmar se a técnica CRCA e a TME são efectivas no alongamento muscular dos isquiotibiais a curto prazo, caso sejam determinar qual a mais efectiva. Pretende-se ainda avaliar se a percepção ao esforço durante a aplicação da TME corresponde à força efectivamente realizada. Métodos: Efectuou-se um estudo experimental com 45 voluntários distribuídos aleatoriamente pelos grupos CRCA, TME e Controlo. Avaliou-se a amplitude articular passiva de extensão do joelho antes e depois de aplicar as técnicas, utilizando um goniómetro. Nos participantes submetidos à TME avaliou-se a percepção ao esforço, solicitando uma contracção submáxima isométrica de 40% medida através do dinamómetro de mão. Resultados: Verificou-se um efeito das técnicas entre as avaliações (Teste ANOVA medidas repetidas factor tempo: p<0,001) e entre os grupos (tempo*grupo: p<0,001). Comparando os grupos dois a dois, verificaram-se diferenças entre o grupo CRCA e o grupo Controlo (Teste Post Hoc Games-Howell: p=0,001) e entre o grupo TME e o grupo Controlo (p=0,009), não existindo diferenças entre os grupos CRCA e TME (p=0,376). Os grupos CRCA e TME obtiveram um ganho de 10,7º e de 11,4º respectivamente, não havendo diferenças significativas entre os ganhos (Teste T-Student Independente: p=0,599). Existiram diferenças significativas entre os 40% CMVI produzida e desejada (Teste Wilcoxon: p=0,018). Conclusão: Ambas foram efectivas no aumento da flexibilidade muscular dos isquiotibiais a curto prazo. Os efeitos foram comparáveis, mas dada a menor complexidade e menor solicitação a TME foi considerada mais eficiente. A percepção ao esforço durante a aplicação da TME não correspondeu ao esforço desejado, existindo uma tendência para a produção de intensidades de contracções maiores.