836 resultados para Framework Model


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Tuberculosis (TB) resurged in the late 1980s and now kills approximately 3 million people a year. The reemergence of tuberculosis as a public health threat has created a need to develop new anti-mycobacterial agents. The shikimate pathway is an attractive target for herbicides and anti-microbial agents development because it is essential in algae, higher plants, bacteria, and fungi, but absent from mammals. Homologs to enzymes in the shikimate pathway have been identified in the genome sequence of Mycobacterium tuberculosis. Among them, the shikimate kinase I encoding gene (aroK) was proposed to be present by sequence homology. Accordingly, to pave the way for structural and functional efforts towards anti-mycobacterial agents development, here we describe the molecular modeling of M. tuberculosis shikimate kinase that should provide a structural framework on which the design of specific inhibitors may be based. © 2002 Elsevier Science (USA). All rights reserved.

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The paper addresses the issue of apportioning of the cost of transmission losses to generators and demands in a multimarket framework. Line flows are unbundled using equivalent bilateral exchanges on a DC-network model and allocated to generators and demands. Losses are then calculated based on unbundled flows and straightforwardly apportioned to generators and demands. The proposed technique is particularly useful in a multimarket framework, where all markets have a common grid operator with complete knowledge of all network data, as is the case of the Brazilian electric-energy system. The methodology proposed is illustrated using the IEEE Reliability Test System and compared numerically with an alternative technique. Appropriate conclusions are drawn. © The Institution of Engineering and Technology 2006.

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The chaotic low energy region (chaotic sea) of the Fermi-Ulam accelerator model is discussed within a scaling framework near the integrable to non-integrable transition. Scaling results for the average quantities (velocity, roughness, energy etc.) of the simplified version of the model are reviewed and it is shown that, for small oscillation amplitude of the moving wall, they can be described by scaling functions with the same characteristic exponents. New numerical results for the complete model are presented. The chaotic sea is also characterized by its Lyapunov exponents.

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One of the most important characteristics of intelligent activity is the ability to change behaviour according to many forms of feedback. Through learning an agent can interact with its environment to improve its performance over time. However, most of the techniques known that involves learning are time expensive, i.e., once the agent is supposed to learn over time by experimentation, the task has to be executed many times. Hence, high fidelity simulators can save a lot of time. In this context, this paper describes the framework designed to allow a team of real RoboNova-I humanoids robots to be simulated under USARSim environment. Details about the complete process of modeling and programming the robot are given, as well as the learning methodology proposed to improve robot's performance. Due to the use of a high fidelity model, the learning algorithms can be widely explored in simulation before adapted to real robots. © 2008 Springer-Verlag Berlin Heidelberg.

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Purpose: The aim of this work is to address the issue of environmental training in organizations, presenting a theoretical review on the subject and proposing a model that highlights the importance of this type of training for organizations. Design/methodology/approach: The paper presents a thorough, updated literature review, discusses typology and the best practices of environmental training, and presents a framework integrating environmental training and organizational results. Findings: A careful consideration allows identifying a significant theoretical gap related to the lack of theoretical references, best practices, and an alignment between environmental training and organizational results. To overcome this gap, a model was proposed that helps to manage the environmental training process in organizations. Research limitations/implications: The paper needs to be complemented with empirical research on the topic. Originality/value: Environmental training is considered to be an essential element for organizations seeking to mitigate their environmental impacts. ISO 14001 states that environmental management is a duty of certified organizations. However, there have been few published articles that suggest models and insights to improve the environmental training in organizations. © Emerald Group Publishing Limited.

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We present a nonperturbative quantization of the two-dimensional massless gauged Thirring model by using the path-integral approach. First, we will study the constraint structure of model via the Dirac's formalism and by using the Faddeev-Senjanovic method we calculate the vacuum-vacuum transition amplitude in a Rξ-gauge, then we compute the Green's functions in a nonperturbative framework. © 2010 American Institute of Physics.

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The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.

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Includes bibliography

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Questions: We assess gap size and shape distributions, two important descriptors of the forest disturbance regime, by asking: which statistical model best describes gap size distribution; can simple geometric forms adequately describe gap shape; does gap size or shape vary with forest type, gap age or the method used for gap delimitation; and how similar are the studied forests and other tropical and temperate forests? Location: Southeastern Atlantic Forest, Brazil. Methods: Analysing over 150 gaps in two distinct forest types (seasonal and rain forests), a model selection framework was used to select appropriate probability distributions and functions to describe gap size and gap shape. The first was described using univariate probability distributions, whereas the latter was assessed based on the gap area-perimeter relationship. Comparisons of gap size and shape between sites, as well as size and age classes were then made based on the likelihood of models having different assumptions for the values of their parameters. Results: The log-normal distribution was the best descriptor of gap size distribution, independently of the forest type or gap delimitation method. Because gaps became more irregular as they increased in size, all geometric forms (triangle, rectangle and ellipse) were poor descriptors of gap shape. Only when small and large gaps (> 100 or 400m2 depending on the delimitation method) were treated separately did the rectangle and isosceles triangle become accurate predictors of gap shape. Ellipsoidal shapes were poor descriptors. At both sites, gaps were at least 50% longer than they were wide, a finding with important implications for gap microclimate (e.g. light entrance regime) and, consequently, for gap regeneration. Conclusions: In addition to more appropriate descriptions of gap size and shape, the model selection framework used here efficiently provided a means by which to compare the patterns of two different types of forest. With this framework we were able to recommend the log-normal parameters μ and σ for future comparisons of gap size distribution, and to propose possible mechanisms related to random rates of gap expansion and closure. We also showed that gap shape varied highly and that no single geometric form was able to predict the shape of all gaps, the ellipse in particular should no longer be used as a standard gap shape. © 2012 International Association for Vegetation Science.

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Includes bibliography.

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The mechanisms underpinning fatigue and exhaustion, and the specific sources of exercise-endurance intensity regulation and (in)tolerance have been investigated for over a century. Although several scientific theories are currently available, over the past five years a new framework called Psychobiological model has been proposed. This model gives greater attention to perceptual and motivational factors than its antecedents, and their respective influence on the conscious process of decision-making and behavioral regulation. In this review we present experimental evidences and summarize the key points of the Psychobiological model to explain intensity regulation and (in)tolerance in endurance exercise. Still, we discuss how the Psychobiological model explains training-induced adaptations related to improvements in performance, experimental manipulations, its predictions, and propose future directions for this investigative area. The Psychobiological model may give a new perspective to the results already published in the literature, helping scientists to better guide their research problems, as well as to analyze and interpret new findings more accurately.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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An optimal control framework to support the management and control of resources in a wide range of problems arising in agriculture is discussed. Lessons extracted from past research on the weed control problem and a survey of a vast body of pertinent literature led to the specification of key requirements to be met by a suitable optimization framework. The proposed layered control structure—including planning, coordination, and execution layers—relies on a set of nested optimization processes of which an “infinite horizon” Model Predictive Control scheme plays a key role in planning and coordination. Some challenges and recent results on the Pontryagin Maximum Principle for infinite horizon optimal control are also discussed.