863 resultados para Col·laborative agents
Resumo:
Background: There is ample evidence of important symptomatic efficacy of tumour necrosis factor alpha (TNFalpha) inhibition in ankylosing spondylitis (AS). Moreover, studies suggest that anti-TNF could be considered as the first disease controlling antirheumatic treatment (DC-ART) for AS. Objective: To determine precisely which patients with AS are most likely to benefit from anti-TNFalpha treatment because of the cost and possible long term side effects of such treatment. Methods: Assessment in Ankylosing Spondylitis (ASAS) members were asked to use a Delphi technique to name the characteristics of patients with AS for whom they would start DC-ART, in three different clinical presentations (isolated axial involvement, peripheral arthritis, enthesitis). Results: Among the 62 invited ASAS members, more than 50% actively participated in the four phases of definition according to the Delphi technique. For each of the three clinical presentations, a combination of five to six domains was proposed, with an evaluation instrument and a cut off point defining a minimum level of activity for each domain. Conclusion: This study provides a profile for a patient with AS for considering initiation of biological agents that reflects the opinion of the ASAS members, using a Delphi exercise. Further studies are required to assess their relevance and their consistency with clinical practice.
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Implementing multi-level governance has been a key priority in EU cohesion policy. This study assesses the perceived achievements and shortcomings in implementing European Social Fund by analyzing the deficits and weaknesses as well as the poor participation of local agents who are in direct contact with the beneficiaries in order to design and implement this fund, which is the main financial instrument of EU social policy.
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Protein-based polymers are present in a wide variety of organisms fulfilling structural and mechanical roles. Advances in protein engineering and recombinant DNA technology allow the design and production of recombinant protein-based polymers (rPBPs) with an absolute control of its composition. Although the application of recombinant proteins as biomaterials is still an emerging technology, the possibilities are limitless and far superior to natural or synthetic materials, as the complexity of the structural design can be fully customized. In this work, we report the electrospinning of two new genetically engineered silk-elastin-like proteins (SELPs) consisting of alternate silk- and elastin-like blocks. Electrospinning was performed with formic acid and aqueous solutions at different concentrations without addition of further agents. The size and morphology of the electrospun structures was characterized by scanning electron microscopy showing to be dependent of concentration and solvent used. Treatment with air saturated with methanol was employed to stabilize the structure and promote water insolubility through a time-dependent conversion of random coils into β-sheets (FTIR). The resultant methanol-treated electrospun mats were characterized for swelling degree (570-720%), water vapour transmission rate (1083 g/m2/day) and mechanical properties (modulus of elasticity of ~126 MPa). Furthermore, the methanol-treated SELP fiber mats showed no cytotoxicity and were able to support adhesion and proliferation of normal human skin fibroblasts. Adhesion was characterized by a filopodia-mediated mechanism. These results demonstrate that SELP fiber mats can provide promising solutions for the development of novel biomaterials suitable for tissue engineering applications.
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In vitro propagation has become an effective practice for large-scale production of strawberry plants. The objective of this study was to evaluate the hyperhydricity and the multiplication capacity of two strawberry varieties (Fragaria x ananassa Duch. 'Dover' and 'Burkley') propagated in vitro. Plants maintained in MS medium supplemented with 1.0 mg L-1 BA were individualized and transferred to the same medium solidified with Agar (6.5 g L-1) or Phytagel® (2.5 g L-1) and BA at different concentrations (0; 0.5; 1.0; 2.0 and 3.0 mg L-1). Biochemical and anatomical analyses were carried out, as well as the analysis of the morphological hyperhydricity characteristics. The analysis of data showed: a) the increase in cytokinin concentration increased hyperhydricity frequency in both varieties; b) at concentrations up to 2.0 mg L-1 BA, the replacement of Agar by Phytagel® induced a higher formation of hyperhydric shoots; and c) the addition of BA induced oxidative stress, which is characterized by increased antioxidant activity and lipid peroxidation, as well as alterations at the cellular level, such as malformation of stomata and epidermal cells. In conclusion, the culture medium containing 0.5 mg L-1 BA solidified with Agar provided lower hyperhydricity percentages in association with higher rates of shoot proliferation in strawberry.
Resumo:
In the city of Rio de Janeiro, the management agencies of environmental conservation units of the park type have been attempting to meet five primary objectives set by the National System for Conservation Units (NSCU), using participatory management guidelines for these units. Two of these objectives relate to the development of recreation activities that involve contact with nature and ecological tourism. This article presents the analyses and conclusions regarding the implementation of collaborative strategies with businesses to achieve such objectives; it is part of a series of research studies having a broader scope. Case studies were conducted in eight parks by means of dozens of interviews with managers and other interested social actors, as well as by documentary research and direct observation. The results suggest that the ecotourism objective is still far from being reached, and that the collaborative strategies used are not sufficient to compensate for the organizational, material and human limitations that encumber these agencies. It was also concluded for the sample that there lacks a strategic vision on the part of the three branches of government involved in the management of these parks in the sense of viewing ecotourism in the city's conservation units as a powerful means to foster local sustainable development.
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In this text, we intend to explore the possibilities of sound manipulation in a context of augmented reality (AR) through the use of robots. We use the random behaviour of robots in a limited space for the real-time modulation of two sound characteristics: amplitude and frequency. We add the possibility of interaction with these robots, providing the user the opportunity to manipulate the physical interface by placing markers in the action space, which alter the behaviour of the robots and, consequently, the audible result produced. We intend to demonstrate through the agents, programming of random processes and direct manipulation of this application, that it is possible to generate empathy in interaction and obtain specific audible results, which would be difficult to otherwise reproduce due to the infinite loops that the interaction promotes.
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With this article we intend to contribute to the understanding of what can make Online Collaborative Teams (OCT) effective. This is done by identifying what can be considered best practices for individual team members, for leaders of OCT, and for the organizations that the teams are a part of. Best practices in these categories were identified from the existing literature related to online teams and collaborative work literature.
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This paper describes a multi-agent based simulation (MABS) framework to construct an artificial electric power market populated with learning agents. The artificial market, named TEMMAS (The Electricity Market Multi-Agent Simulator), explores the integration of two design constructs: (i) the specification of the environmental physical market properties and (ii) the specification of the decision-making (deliberative) and reactive agents. TEMMAS is materialized in an experimental setup involving distinct power generator companies that operate in the market and search for the trading strategies that best exploit their generating units' resources. The experimental results show a coherent market behavior that emerges from the overall simulated environment.
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Since collaborative networked organisations are usually formed by independent and heterogeneous entities, it is natural that each member holds his own set of values, and that conflicts among partners might emerge because of some misalignment of values. In contrast, it is often stated in literature that the alignment between the value systems of members involved in collaborative processes is a prerequisite for successful co-working. As a result, the issue of core value alignment in collaborative networks started to attract attention. However, methods to analyse such alignment are lacking mainly because the concept of 'alignment' in this context is still ill defined and shows a multifaceted nature. As a contribution to the area, this article introduces an approach based on causal models and graph theory for the analysis of core value alignment in collaborative networks. The potential application of the approach is then discussed in the virtual organisations' breeding environment context.
Resumo:
Collaborative networks are typically formed by heterogeneous and autonomous entities, and thus it is natural that each member has its own set of core-values. Since these values somehow drive the behaviour of the involved entities, the ability to quickly identify partners with compatible or common core-values represents an important element for the success of collaborative networks. However, tools to assess or measure the level of alignment of core-values are lacking. Since the concept of 'alignment' in this context is still ill-defined and shows a multifaceted nature, three perspectives are discussed. The first one uses a causal maps approach in order to capture, structure, and represent the influence relationships among core-values. This representation provides the basis to measure the alignment in terms of the structural similarity and influence among value systems. The second perspective considers the compatibility and incompatibility among core-values in order to define the alignment level. Under this perspective we propose a fuzzy inference system to estimate the alignment level, since this approach allows dealing with variables that are vaguely defined, and whose inter-relationships are difficult to define. Another advantage provided by this method is the possibility to incorporate expert human judgment in the definition of the alignment level. The last perspective uses a belief Bayesian network method, and was selected in order to assess the alignment level based on members' past behaviour. An example of application is presented where the details of each method are discussed.
Resumo:
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.
Resumo:
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.
Resumo:
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.