999 resultados para Strategic Behavior


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Bifunctional Pt-HMOR catalysts were prepared by incipient wetness impregnation of various desilicated MOR obtained by alkaline treatment using NaOH concentrations ranging from 0.1 to 0.5 M. The zeolite structural changes upon modification were investigated by several techniques including powder X-ray diffraction,Al-27 and Si-29 MAS-NMR spectroscopy, N-2 adsorption, pyridine adsorption followed by infrared spectroscopy and the catalytic model reaction of m-xylene transformation. For low alkaline concentration the zeolite acidity is preserved, along with a slight increase of the volume correspondent to the larger micropores due to the removal of extra-framework debris already existent at the parent zeolite. At higher NaOH concentrations there is a significant loss of crystalinity and acidity as well as the formation of mesoporosity. The characterization of the metal function shows similar patterns for Pt-HMOR and Pt-M/0.1 samples, with Pt particles located mainly inside the inner porosity. In contrast, large Pt particles become visible at the intercrystalline mesoporosity of MOR crystals developed during the desilication treatments at severe alkaline conditions. The catalytic results obtained for n-hexane hydroisomerization showed an improved selectivity for dibranched over monobranched isomers for Pt-M/0.1 sample, likely due to the preservation of the support acidity and the slight enlargement of the micropores. This work is a new example in which the mesoporous development does not improve the catalytic efficiency of the zeolites, whereas mild alkaline desilication might be considered as an effective solution to produce customized catalysts with enhanced performance for a given application. (C) 2014 Elsevier B.V. All rights reserved.

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ABSTRACT OBJECTIVE To describe the methodological characteristics of the studies selected and assess variables associated with sedentary behavior in Brazilian children and adolescents. METHODS For this systematic review, we searched four electronic databases: PubMed, Web of Knowledge, LILACS, SciELO. Also, electronic searches were applied in Google Scholar. A supplementary search was conducted in the references lists of the included articles and in non-indexed journals. We included observational studies with children and adolescents aged from three to 19 years developed in Brazil, presenting analyses of associations based on regression methods and published until September 30, 2014. RESULTS Of the 255 potential references retrieved by the searches, 49 met the inclusion criteria and composed the descriptive synthesis. In this set, we identified a great number of cross-sectional studies (n = 43; 88.0%) and high methodological variability on the types of sedentary behavior assessed, measurement tools and cut-off points used. The variables most often associated with sedentary behavior were “high levels of body weight” (in 15 out of 27 studies; 55.0%) and “lower level of physical activity” (in eight out of 16 studies; 50.0%). CONCLUSIONS The findings of this review raise the following demands to the Brazilian agenda of sedentary behavior research geared to children and adolescents: development of longitudinal studies, validation of measuring tools, establishment of risk cut-offs, measurement of sedentary behavior beyond screen time and use of objective measures in addition to questionnaires. In the articles available, the associations between sedentary behavior with “high levels of body weight” and “low levels of physical activity” were observed in different regions of Brazil.

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Basaltic rocks are the main component of the oceanic upper crust, thus of potential interest for water and geothermal resources, storage of CO2 and volcanic edifice stability. In this work, we investigated experimentally the mechanical behavior and the failure modes of a porous basalt, with an initial connected porosity of 18%. Results were acquired under triaxial compression experiments at confining pressure in the range of 25-200 MPa on water saturated samples. In addition, a purely hydrostatic test was also performed to reach the pore collapse critical pressure P*. During hydrostatic loading, our results show that the permeability is highly pressure dependent, which suggests that the permeability is mainly controlled by pre-existing cracks. When the sample is deformed at pressure higher than the pore collapse pressure P*, some very small dilatancy develops due to microcracking, and an increase in permeability is observed. Under triaxial loading, two modes of deformation can be highlighted. At low confining pressure (Pc < 50 MPa), the samples are brittle and shear localization occurs. For confining pressure > 50 MPa, the stress-strain curves are characterized by strain hardening and volumetric compaction. Stress drops are also observed, suggesting that compaction may be localized. The presence of compaction bands is confirmed by our microstructure analysis. In addition, the mechanical data allows us to plot the full yield surface for this porous basalt, which follows an elliptic cap as previously observed in high porosity sandstones and limestones.

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Journal of Business, Vol. 78 Issue 3, p1049-1072

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Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Gestão Estratégica das Relações Públicas.

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The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

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This study aims to understand the reality of social service organizations, the level of implementation of the strategic planning as well as the impact of its application on organizational effectiveness. At first, we will group organizations in clusters according to the level of strategic planning implementation and its degree of effectiveness. Secondly, we will analyse all the different groups. Given the growing number of social service organizations and the consequent complexity of their structures, it turns out the need for these organizations adopt formal management techniques. Strategic planning is a valuable strategic management tool and one of its main objectives is to make organizations more effective. Therefore, the research has been conducted in order to determine if strategic planning is implemented in social service organizations and which effects has its application on organizational effectiveness. The survey, applied to 220 social service organizations, allowed us to gather them into different clusters, showing that different levels of strategic planning determine distinct degrees of organizational efficiency. Finally, it should be noted that findings of this research may be essential to decision makers of these organizations, because it was shown that the adoption of strategic planning has a positive influence on organizational effectiveness of social service organizations.

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We study exotic patterns appearing in a network of coupled Chen oscillators. Namely, we consider a network of two rings coupled through a “buffer” cell, with Z3×Z5 symmetry group. Numerical simulations of the network reveal steady states, rotating waves in one ring and quasiperiodic behavior in the other, and chaotic states in the two rings, to name a few. The different patterns seem to arise through a sequence of Hopf bifurcations, period-doubling, and halving-period bifurcations. The network architecture seems to explain certain observed features, such as equilibria and the rotating waves, whereas the properties of the chaotic oscillator may explain others, such as the quasiperiodic and chaotic states. We use XPPAUT and MATLAB to compute numerically the relevant states.

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Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

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We introduce a simple model for a biaxial nematic liquid crystal. This consists of hard spheroids that can switch shape between prolate (rodlike) and oblate (platelike) subject to an energy penalty Δε. The spheroids are approximated as hard Gaussian overlap particles and are treated at the level of Onsager's second-virial description. We use both bifurcation analysis and a numerical minimization of the free energy to show that, for additive particle shapes, (i) there is no stable biaxial phase even for Δε=0 (although there is a metastable biaxial phase in the same density range as the stable uniaxial phase) and (ii) the isotropic-to-nematic transition is into either one of two degenerate uniaxial phases, rod rich or plate rich. We confirm that even a small amount of shape nonadditivity may stabilize the biaxial nematic phase.

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The behavior of T. cruzi strains from S. Felipe - BA (19 SF, 21 SF and 22 SF) classified as Type II Zymodeme 2, was investigated after passage through the authoctonous (P. megistus) and foreign vectors (T. infestans and R. prolixus). For each strain Swiss mice were infected: I - with blood forms (control); II - with metacyclic forms (MF) from P. megistus; III - with MF from T. infestans; IV - with MF from R. prolixus. Inocula: MF from the three species of triatomine, 60 to 120 days after feeding in infected mice, adjusted to 10 4. Biological behavior in mice (parasitemia, morphology, mortality, virulence and pathogenicity) after passage through triatomine was compared with data from the same strain in control mice. Isoenzymic electrophoresis (ASAT, ALAT, PGM, GPI) were also performed after culture into Warren medium. The three strains maintained the isoenzyme profiles (zymodeme 2), in the control groups and after passages through different species of triatomine. Biological characterization disclosed Type II strains patterns for all groups. An increased virulence was observed with the 22 SF strain isolated from P. megistus and T. infestans and higher levels of parasitemia and predominance of slender forms in mice inoculated with the 19 SF and 21 SF from these same species. Results indicate that the passage through the two species T. infestans and P. megistus had a positive influence on the virulence of the regional strains of S. Felipe, regardless of being autocthonous (P. megistus) or foreign to the area (T. infestans).

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Proceedings of the First International Conference on Coastal Conservation and Management in the Atlantic and Mediterranean, p. 91-98

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The deregulation of electricity markets has diversified the range of financial transaction modes between independent system operator (ISO), generation companies (GENCO) and load-serving entities (LSE) as the main interacting players of a day-ahead market (DAM). LSEs sell electricity to end-users and retail customers. The LSE that owns distributed generation (DG) or energy storage units can supply part of its serving loads when the nodal price of electricity rises. This opportunity stimulates them to have storage or generation facilities at the buses with higher locational marginal prices (LMP). The short-term advantage of this model is reducing the risk of financial losses for LSEs in DAMs and its long-term benefit for the LSEs and the whole system is market power mitigation by virtually increasing the price elasticity of demand. This model also enables the LSEs to manage the financial risks with a stochastic programming framework.

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Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which simulates the electricity markets environment. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated by being included in ALBidS and then compared with the application of an Artificial Neural Network, originating promising results. The proposed approach is tested and validated using real electricity markets data from MIBEL - Iberian market operator.

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The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players’ actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets’ players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets’ data, using MASCEM - a multi-agent electricity market simulator that simulates market players’ operation in the market.