54 resultados para grade and tonnage models
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Searches are reported for Higgs bosons in the context of either the standard model extended to include a fourth generation of fermions (SM4) with masses of up to 600 GeV or fermiophobic models. For the former, results from three decay modes (ττ, WW, and ZZ) are combined, whilst for the latter the diphoton decay is exploited. The analysed proton-proton collision data correspond to integrated luminosities of up to 5.1 fb-1 at 7 TeV and up to 5.3 fb-1 at 8 TeV. The observed results exclude the SM4 Higgs boson in the mass range 110-600 GeV at 99% confidence level (CL), and in the mass range 110-560 GeV at 99.9% CL. A fermiophobic Higgs boson is excluded in the mass range 110-147 GeV at 95% CL, and in the range 110-133 GeV at 99% CL. The recently observed boson with a mass near 125 GeV is not consistent with either an SM4 or a fermiophobic Higgs boson. © 2013 CERN.
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The strut-and-tie models are widely used in certain types of structural elements in reinforced concrete and in regions with complexity of the stress state, called regions D, where the distribution of deformations in the cross section is not linear. This paper introduces a numerical technique to determine the strut-and-tie models using a variant of the classical Evolutionary Structural Optimization, which is called Smooth Evolutionary Structural Optimization. The basic idea of this technique is to identify the numerical flow of stresses generated in the structure, setting out in more technical and rational members of strut-and-tie, and to quantify their value for future structural design. This paper presents an index performance based on the evolutionary topology optimization method for automatically generating optimal strut-and-tie models in reinforced concrete structures with stress constraints. In the proposed approach, the element with the lowest Von Mises stress is calculated for element removal, while a performance index is used to monitor the evolutionary optimization process. Thus, a comparative analysis of the strut-and-tie models for beams is proposed with the presentation of examples from the literature that demonstrates the efficiency of this formulation. © 2013 Elsevier Ltd.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Adjusting autoregressive and mixed models to growth data fits discontinuous functions, which makes it difficult to determine critical points. In this study we propose a new approach to determine the critical stability point of cattle growth using a first-order autoregressive model and a mixed model with random asymptote, using the deterministic portion of the models. Three functions were compared: logistic, Gompertz, and Richards. The Richards autoregressive model yielded the best fit, but the critical growth values were adjusted very early, and for this purpose the Gompertz model was more appropriate.
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The Constant Flux: Constant Sedimentation (CF:CS) and Constant Rate of Supply (CRS) of unsupported/excess Pb-210 models have been applied to a Pb-210 data set providing of eighteen sediments profiles sampled at four riverine systems occurring in Brazil, South America: Corumbatai River basin (S1=Site 1, Sao Paulo State), Atibaia River basin (S2=Site 2, Sao Paulo State), Ribeirao dos Bagres basin (S3=Site 3, Sao Paulo State) and Amazon River mouth. (S4=Site 4, Amapa State). These sites were chosen for a comparative evaluation of the performance of the CF:CS and CRS models due to their pronounced differences on the geographical location, geological context, soil composition, biodiversity, climate, rainfall, and water flow regime, among other variable aspects. However, all sediments cores exhibited a common denominator consisting on a database built from the use of the same techniques for acquiring the sediments major chemical composition (SiO2, Al2O3, Na2O, K2O, CaO, MgO, Fe2O3, MnO, P2O5, TiO2 and LOI-Loss on Ignition) and unsupported/excess 210Pb activity data. In terms of sedimentation rates, the performance of the CRS model was better than that of the CF:CS model as it yielded values more compatible with those expected from field evidences. Under the chronological point of view, the CRS model always provided ages within the permitted range of the Pb-210-method in the studied sites, whereas the CF:CS model predicted some values above 150 years. The SiO2 content decreased in accordance with the LOI increase in all cores analyzed and such inverse relationship was also tracked in the SiO2-LOI curves of historical trends. The SiO2-LOI concentration fluctuations in sites S1 and S3 also coincided with some Cu and Cr inputs in the drainage systems. (C) 2014 Elsevier Ltd. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The adoption of ERPs systems by small and middle-sized companies may not be possible due to their cost. At the same time, when adapting ERP to the company's particular needs, the user keeps depending on the system's sellers due to the lack of access and knowledge of the respective code. Free and open-source software may promote advantages to the enterprises, however, for its adoption it is necessary the development of techniques and tools in order to facilitate its deployment and code maintenance. This article emphasizes the importance of defining modeling architectures and reference models for the development and maintenance of open-source ERPs, in special the ERP5 project.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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As a new modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In this study, the SVR models had been introduced and developed to predict body and carcass-related characteristics of 2 strains of broiler chicken. To evaluate the prediction ability of SVR models, we compared their performance with that of neural network (NN) models. Evaluation of the prediction accuracy of models was based on the R-2, MS error, and bias. The variables of interest as model output were BW, empty BW, carcass, breast, drumstick, thigh, and wing weight in 2 strains of Ross and Cobb chickens based on intake dietary nutrients, including ME (kcal/bird per week), CP, TSAA, and Lys, all as grams per bird per week. A data set composed of 64 measurements taken from each strain were used for this analysis, where 44 data lines were used for model training, whereas the remaining 20 lines were used to test the created models. The results of this study revealed that it is possible to satisfactorily estimate the BW and carcass parts of the broiler chickens via their dietary nutrient intake. Through statistical criteria used to evaluate the performance of the SVR and NN models, the overall results demonstrate that the discussed models can be effective for accurate prediction of the body and carcass-related characteristics investigated here. However, the SVR method achieved better accuracy and generalization than the NN method. This indicates that the new data mining technique (SVR model) can be used as an alternative modeling tool for NN models. However, further reevaluation of this algorithm in the future is suggested.
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It is shown that the affine Toda models (AT) constitute a gauge fixed version of the conformal affine Toda model (CAT). This result enables one to map every solution of the AT models into an infinite number of solutions of the corresponding CAT models, each one associated to a point of the orbit of the conformal group. The Hirota τ-functions are introduced and soliton solutions for the AT and CAT models associated to SL̂ (r+1) and SP̂ (r) are constructed.