988 resultados para D-Symmetric Operators


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The Tevatron has measured a discrepancy relative to the standard model prediction in the forward-backward asymmetry in top quark pair production. This asymmetry grows with the rapidity difference of the two top quarks. It also increases with the invariant mass of the t (t) over bar pair, reaching, for high invariant masses, 3.4 standard deviations above the next-to-leading order prediction for the charge asymmetry of QCD. However, perfect agreement between experiment and the standard model was found in both total and differential cross section of top quark pair production. As this result could be a sign of new physics we have parametrized this new physics in terms of a complete set of dimension six operators involving the top quark. We have then used a Markov chain Monte Carlo approach in order to find the best set of parameters that fits the data, using all available data regarding top quark pair production at the Tevatron. We have found that just a very small number of operators are able to fit the data better than the standard model.

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Glucose 2-oxidase (pyranose oxidase, pyranose: oxygen-2-oxidoreductase, EC 1.1.3.10) from Coriolus versicolor catalyses the oxidation of D-glucose at carbon 2 in the presence of molecular O(2) producing D-glucosone (2-keto-glucose and D-arabino-2-hexosulose) and H(2)O(2). It was used to convert D-glucose into D-glucosone at moderate pressures (i.e. up to 150 bar) with compressed air in a modified commercial batch reactor. Several parameters affecting biocatalysis at moderate pressures were investigated as follows: pressure, [enzyme], [glucose], pH, temperature, nature of fluid and the presence of catalase. Glucose 2-oxidase was purified by immobilized metal affinity chromatography on epoxy-activated Sepharose 6B-IDA-Cu(II) column at pH 6.0. The rate of bioconversion of D-glucose increased with the pressure since an increase in the pressure with compressed air resulted in higher rates of conversion. On the other hand, the presence of catalase increased the rate of reaction which strongly suggests that H(2)O(2) acted as inhibitor for this reaction. The rate of bioconversion of D-glucose by glucose 2-oxidase in the presence of either nitrogen or supercritical CO(2) at 110 bar was very low compared with the use of compressed air at the same pressure. The optimum temperature (55 degrees C) and pH (5.0) of D-glucose bioconversion as well as kinetic parameters for this enzyme were determined under moderate pressure. The activation energy (E(a)) was 32.08 kJmol(-1) and kinetic parameters (V(max), K(m), K(cat) and K(cat)/K(m)) for this bioconversion were 8.8 Umg(-1) protein, 2.95 mM, 30.81 s(-1) and 10,444.06 s(-1)M(-1), respectively. The biomass of C. versicolor as well as the cell-free extract containing glucose 2-oxidase activity were also useful for bioconversion of D-glucose at moderate pressures. The enzyme was apparently stable at moderate pressures since such pressures did not affect significantly the enzyme activity.

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The immobilized glucose 2-oxidase (pyranose oxidase, pyranose:oxygen-2-oxidoreductase, EC 1.1.3.10) from Coriolus versicolor was used to convert D-glucose into D-glucosone at moderate pressures, up to 150 bar, with compressed air in a modified commercial batch reactor. Several parameters affecting biocatalysis at moderate pressures were investigated as follows: pressure, different forms of immobilized biocatalysts, glucose concentration, pH, temperature and the presence of catalase. Glucose 2-oxidase (GOX2) was purified by immobilized metal affinity chromatography on epoxy-activated Sepharose 6B-IDA-Cu(II) column at pH 6.0. Purified enzyme and catalase were immobilized into a polyethersulfone (PES) membrane in the presence of glutaraldehyde and gelatin. Enhancement of the bioconversion of D-glucose was done by the pressure since an increase in the pressure with compressed air increases the conversion rates. The optimum temperature and pH for bioconversion of D-glucose were found to be 62 degrees C and pH 6.0, respectively and the activation energy (E(a)) was 28.01 kJ mol(-1). The apparent kinetic constants (V(max)' K(m)', K(cat)' and K(cat)/K(m)') for this bioconversion were 2.27 U mg(-1) protein, 11.15 mM, 8.33 s(-1) and 747.38 s(-1) M(-1), respectively. The immobilized biomass of C. versicolor as well as crude extract containing GOX2 activity were also useful for bioconversion of D-glucose at 65 bar with a yield of 69.9 +/- 3.8% and 91.3 +/- 1.2%, respectively. The immobilized enzyme was apparently stable for several months without any significant loss of enzyme activity. On the other hand, this immobilized enzyme was also stable at moderate pressures, since such pressures did not affect significantly the enzyme activity. (C) 2010 Elsevier Ltd. All rights reserved.

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This paper presents a simulator for electric vehicles in the context of smart grids and distribution networks. It aims to support network operator´s planning and operations but can be used by other entities for related studies. The paper describes the parameters supported by the current version of the Electric Vehicle Scenario Simulator (EVeSSi) tool and its current algorithm. EVeSSi enables the definition of electric vehicles scenarios on distribution networks using a built-in movement engine. The scenarios created with EVeSSi can be used by external tools (e.g., power flow) for specific analysis, for instance grid impacts. Two scenarios are briefly presented for illustration of the simulator capabilities.

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This paper deals with the application of an intelligent tutoring approach to delivery training in diagnosis procedures of a Power System. In particular, the mechanisms implemented by the training tool to support the trainees are detailed. This tool is part of an architecture conceived to integrate Power Systems tools in a Power System Control Centre, based on an Ambient Intelligent paradigm. The present work is integrated in the CITOPSY project which main goal is to achieve a better integration between operators and control room applications, considering the needs of people, customizing requirements and forecasting behaviors.

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This paper describes an architecture conceived to integrate Power Sys-tems tools in a Power System Control Centre, based on an Ambient Intelligent (AmI) paradigm. This architecture is an instantiation of the generic architecture proposed in [1] for developing systems that interact with AmI environments. This architecture has been proposed as a consequence of a methodology for the inclu-sion of Artificial Intelligence in AmI environments (ISyRAmI - Intelligent Sys-tems Research for Ambient Intelligence). The architecture presented in the paper will be able to integrate two applications in the control room of a power system transmission network. The first is SPARSE expert system, used to get diagnosis of incidents and to support power restoration. The second application is an Intelligent Tutoring System (ITS) incorporating two training tools. The first tutoring tool is used to train operators to get the diagnosis of incidents. The second one is another tutoring tool used to train operators to perform restoration procedures.

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The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults like blackouts. In this paper, we present an Intelligent Tutoring approach for training Portuguese Control Center operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, having into account context awareness and the unobtrusive integration in the working environment. Several Artificial Intelligence techniques were criteriously used and combined together to obtain an effective Intelligent Tutoring environment, namely Multiagent Systems, Neural Networks, Constraint-based Modeling, Intelligent Planning, Knowledge Representation, Expert Systems, User Modeling, and Intelligent User Interfaces.

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Cyber-Physical Systems and Ambient Intelligence are two of the most important and emerging paradigms of our days. The introduction of renewable sources gave origin to a completely different dimension of the distribution generation problem. On the other hand, Electricity Markets introduced a different dimension in the complexity, the economic dimension. Our goal is to study how to proceed with the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances.

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The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, taking into account context awareness and the unobtrusive integration in the working environment.

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Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

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Em Portugal, no ano de 2009, existiam 983 mil indivíduos com Diabetes mellitus (DM), dos quais 90% DM tipo 2 (DM2). Um dos principais factores de risco para o desenvolvimento da DM2 é a obesidade. A DM2 está, desta forma, associada a um estilo de vida sedentário, quer pela diminuição do metabolismo da glicose, quer pela sua associação à obesidade devido ao aumento dos níveis de glicose como consequência da sobrealimentação. Outros factores como a lipotoxicidade e o stress oxidativo também têm sido considerados como responsáveis pela disfunção das células-beta pancreáticas. O gene da enzima conversora da angiotensina (ECA) é altamente polimórfico, sendo associado como factor predisponente para diferentes patologias como a DM. O polimorfismo melhor descrito até à actualidade é o de Inserção/Delecção (I/D), consistindo na inserção de um fragmento Alu de 287bp no intrão 16 do gene DCP1. A actividade pró-inflamatória e pró-oxidativa desta enzima sobre o pâncreas, bem como a sua actuação nos processos de fibrose, podem em parte auxiliar na compreensão do processo que origina esta patologia. O polimorfismo I/D torna-se assim um óptimo candidato para a detecção de indivíduos susceptíveis.Este estudo tem como objectivo analisar a distribuição do polimorfismo I/D, bem como a sua possível relação com a incidência de DM e com os níveis de glicose.

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A metodologia de projeto constitui a temática central de seis dos textos incluídos neste número do CIED. Tratando-se de contributos diversos, é possível encontrar algumas linhas de organização a partir da sua abordagem:

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)