889 resultados para Adaptive educational hypermedia systems
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Underground systems of Asteraceac species from the Brazilian Cerrado. The aim or this study was to describe the underground systems structure, the origin of the shoot buds, and to identify the storage reserve of seven Asteraceae species in order to understand the adaptive strategies of these species in burned Cerrado areas and their higher frequency in the floristic Surveys for herbaceous and undershrub layers of this biome. The subterranean systems types-diffuse underground system, rhizophore, tuberous roots, and xylopodium-varied among the studied species, but all of them have high shoot bud-forming potential. Fructans of the inulin type were detected as storage substances. The presence of these characteristics on the underground systems Could explain the frequency of these species in the floristic surveys from the Brazilian Cerrado, in which Fire and seasonal drought are frequent. It is possible that the belowground bud banks in the Cerrado biome are as important as demonstrated in North American prairies where fire is also frequent. However, in the Cerrado, as demonstrated here, there are types of underground systems other than rhizomes that are usually described in the prairie. Understanding the anatomical features of these plants is one of the steps to appropriate conservation management of these species in the Cerrado.
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The Apical Membrane Antigen-1 (AMA-1) is a well-characterized and functionally important merozoite protein and is currently considered a major candidate antigen for a malaria vaccine. Previously, we showed that AMA-1 has an influence on cellular immune responses of malaria-naive subjects, resulting in an alternative activation of monocyte-derived dendritic cells and induction of a pro-inflammatory response by stimulated PBMCs. Although there is evidence, from human and animal malaria model systems that cell-mediated immunity may contribute to both protection and pathogenesis, the knowledge on cellular immune responses in vivax malaria and the factors that may regulate this immunity are poorly understood. In the current work, we describe the maturation of monocyte-derived dendritic cells of P. vivax naturally infected individuals and the effect of P. vivax vaccine candidate Pv-AMA-1 on the immune responses of the same donors. We show that malaria-infected subjects present modulation of DC maturation, demonstrated by a significant decrease in expression of antigen-presenting molecules (CD1a, HLA-ABC and HLA-DR), accessory molecules (CD40, CD80 and CD86) and Fc gamma RI (CD64) receptor (P <= 0.05). Furthermore, Pv-AMA-1 elicits an upregulation of CD1a and HLA-DR molecules on the surface of monocyte-derived dendritic cells (P=0.0356 and P=0.0196, respectively), and it is presented by AMA-1-stimulated DCs. A significant pro-inflammatory response elicited by Pv-AMA-1-pulsed PBMCs is also demonstrated, as determined by significant production of TNF-alpha, IL-12p40 and IFN-gamma (P <= 0.05). Our results suggest that Pv-AMA-1 may partially revert DC down-modulation observed in infected subjects, and exert an important role in the initiation of pro-inflammatory immunity that might contribute substantially to protection. (c) 2009 Elsevier Ltd. All rights reserved.
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Immunological systems have been an abundant inspiration to contemporary computer scientists. Problem solving strategies, stemming from known immune system phenomena, have been successfully applied to chall enging problems of modem computing. Simulation systems and mathematical modeling are also beginning use to answer more complex immunological questions as immune memory process and duration of vaccines, where the regulation mechanisms are not still known sufficiently (Lundegaard, Lund, Kesmir, Brunak, Nielsen, 2007). In this article we studied in machina a approach to simulate the process of antigenic mutation and its implications for the process of memory. Our results have suggested that the durability of the immune memory is affected by the process of antigenic mutation.and by populations of soluble antibodies in the blood. The results also strongly suggest that the decrease of the production of antibodies favors the global maintenance of immune memory.
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Coastal wetlands are dynamic and include the freshwater-intertidal interface. In many parts of the world such wetlands are under pressure from increasing human populations and from predicted sea-level rise. Their complexity and the limited knowledge of processes operating in these systems combine to make them a management challenge.Adaptive management is advocated for complex ecosystem management (Hackney 2000; Meretsky et al. 2000; Thom 2000;National Research Council 2003).Adaptive management identifies management aims,makes an inventory/environmental assessment,plans management actions, implements these, assesses outcomes, and provides feedback to iterate the process (Holling 1978;Walters and Holling 1990). This allows for a dynamic management system that is responsive to change. In the area of wetland management recent adaptive approaches are exemplified by Natuhara et al. (2004) for wild bird management, Bunch and Dudycha (2004) for a river system, Thom (2000) for restoration, and Quinn and Hanna (2003) for seasonal wetlands in California. There are many wetland habitats for which we currently have only rudimentary knowledge (Hackney 2000), emphasizing the need for good information as a prerequisite for effective management. The management framework must also provide a way to incorporate the best available science into management decisions and to use management outcomes as opportunities to improve scientific understanding and provide feedback to the decision system. Figure 9.1 shows a model developed by Anorov (2004) based on the process-response model of Maltby et al. (1994) that forms a framework for the science that underlies an adaptive management system in the wetland context.
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The suitable use of array antennas in cellular systems results in improvement in the signal-to-interference ratio (StR), This property is the basis for introducing smart or adaptive antenna systems. in general, the SIR depends on the array configuration and is a function of the direction of the desired user and interferers. Here, the SIR performance for linear and circular arrays is analysed and compared.
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Joining efforts of academic and corporate teams, we developed an integration architecture - MULTIS - that enables corporate e-learning managers to use a Learning Management System (LMS) for management of educational activities in virtual worlds. This architecture was then implemented for the Formare LMS. In this paper we present this architecture and concretizations of its implementation for the Second Life Grid/OpenSimulator virtual world platforms. Current systems are focused on activities managed by individual trainers, rather than groups of trainers and large numbers of trainees: they focus on providing the LMS with information about educational activities taking place in a virtual world and/or being able to access within the virtual world some of the information stored in the LMS, and disregard the streamlining of activity setup and data collection in multi-trainer contexts, among other administrative issues. This architecture aims to overcome the limitations of existing systems for organizational management of corporate e-learning activities.
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Despite a massive expansion of education in Portugal, since the 1970’s, educational attainment of the adult population in the country remains low. The numbers of working-age people in some form of continuing education are among the lowest, according to the OECD and EU-27 statistics. Technological Schools(TS), initially created in the 1990’s, under the umbrella of the Ministry of Economy in partnership with industry and industrial associations, aimed to prepare qualified staff for industries and services in the country, particularly in the engineering sector, through the provision of post secondary non-university programmes of studies, the CET (Technological Specialization Courses). Successful CET students are awarded a DET(Diploma of Technological Specialization), which corresponds to Vocational Qualification level IV of the EU, according to the latest alteration (2005) of the Education Systems Act (introduced in 1986). In this, CET’s are also clearly defined as one of the routes for access to Higher Education (HE), in Portugal. The PRILHE (Promoting Reflective and Independent Learning in Higher Education) multinational project, funded by the European Socrates Grundtvig Programme, aimed to identify the learning processes which enable adult students in higher education to become autonomous reflective learners and search best practices to support these learning processes. During this research, both quantitative and qualitative methods were used to determine how students organise their studies and develop their learning skills. The Portuguese partner in the project’ consortium used a two case studies approach, one with students of Higher Education Institutions and other with students of TS. This paper only applies to students of TS, as these have a predominant bias towards engineering. Results show that student motivation and professional teaching support contribute equally to the development of an autonomous and reflective approach to learning in adult students; this is essential for success in a knowledge economy, where lifelong learning is the key to continuous employment.
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This paper presents a project consisting on the development of an Intelligent Tutoring System, for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students. One of the major goals of this project is to devise a teaching model based on Intelligent Tutoring techniques, considering not only academic knowledge but also other types of more empirical knowledge, able to achieve successfully the training of electrical installation design.
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The study of electricity markets operation has been gaining an increasing importance in last years, as result of the new challenges that the electricity markets restructuring produced. This restructuring increased the competitiveness of the market, but with it its complexity. The growing complexity and unpredictability of the market’s evolution consequently increases the decision making difficulty. Therefore, the intervenient entities are forced to rethink their behaviour and market strategies. Currently, lots of information concerning electricity markets is available. These data, concerning innumerous regards of electricity markets operation, is accessible free of charge, and it is essential for understanding and suitably modelling electricity markets. This paper proposes a tool which is able to handle, store and dynamically update data. The development of the proposed tool is expected to be of great importance to improve the comprehension of electricity markets and the interactions among the involved entities.
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Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal.
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With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.
Resumo:
The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players’ models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition.