890 resultados para the EFQM excellence model


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For the first time, we introduce a generalized form of the exponentiated generalized gamma distribution [Cordeiro et al. The exponentiated generalized gamma distribution with application to lifetime data, J. Statist. Comput. Simul. 81 (2011), pp. 827-842.] that is the baseline for the log-exponentiated generalized gamma regression model. The new distribution can accommodate increasing, decreasing, bathtub- and unimodal-shaped hazard functions. A second advantage is that it includes classical distributions reported in the lifetime literature as special cases. We obtain explicit expressions for the moments of the baseline distribution of the new regression model. The proposed model can be applied to censored data since it includes as sub-models several widely known regression models. It therefore can be used more effectively in the analysis of survival data. We obtain maximum likelihood estimates for the model parameters by considering censored data. We show that our extended regression model is very useful by means of two applications to real data.

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This article suggests a pricing model for commodities used to produce biofuel. The model is based on the concept that the deterministic component of the Wiener process is not constant and depends on time and exogenous variables. The model, which incorporates theory of storage, the convenience yield and the seasonality of harvests, was applied in the Brazilian sugar market. After predictions were made with the Kalman filter, the model produced results that were statistically more accurate than those returned by the two-factor model available in the literature.

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The aim of this study was to evaluate the resindentin bonds of two simplified etch-and-rinse adhesive after simulated cariogenic and inhibited cariogenic challenge in situ. Dental cavities (4 mm wide, 4 mm long, and 1.5 mm deep) were prepared in 60 bovine teeth with enamel margins. Restorations were bonded with either adhesive Adper Single Bond 2 (3MESPE) or Optibond Solo Plus (Kerr). Forty restorations were included in an intra-oral palatal appliance that was used for 10 adult volunteers while the remaining 20 dental blocks were not submitted to any cariogenic challenge [NC group] and tested immediately. For the simulated cariogenic challenge [C+DA], each volunteer dropped 20% sucrose solution onto all blocks four times a day during 14 days and distilled water twice a day. In the inhibited cariogenic challenge group [C + FA], the same procedure was done, but slurry of fluoride dentifrice (1.100 ppm) was applied instead of water. The restored bovine blocks were sectioned to obtain a slice for cross-sectional Vickers microhardness evaluation and resindentin bonded sticks (0.8 mm2) for resindentin microtensile evaluation. Data were evaluated by two-way ANOVA and Tukey's tests (a = 0.05). Statistically lower microhardness values and degradation of the resindentin bonds were only found in the C + DW group for both adhesives. The in situ model seems to be a suitable short-term methodology to investigate the degradation of the resindentin bonds under a more realistic condition. (c) 2012 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 100B: 14661471, 2012.

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The ferromagnetic Ising model without external field on an infinite Lorentzian triangulation sampled from the uniform distribution is considered. We prove uniqueness of the Gibbs measure in the high temperature region and coexistence of at least two Gibbs measures at low temperature. The proofs are based on the disagreement percolation method and on a variant of the Peierls contour method. The critical temperature is shown to be constant a.s.

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We use the star count model of Ortiz & Lépine to perform an unprecedented exploration of the most important Galactic parameters comparing the predicted counts with the Two Micron All Sky Survey observed star counts in the J, H, and KS bands for a grid of positions covering the whole sky. The comparison is made using a grid of lines of sight given by the HEALPix pixelization scheme. The resulting best-fit values for the parameters are: 2120 ± 200 pc for the radial scale length and 205 ± 40 pc for the scale height of the thin disk, with a central hole of 2070$_{-800}^{+2000}$ pc for the same disk, 3050 ± 500 pc for the radial scale length and 640 ± 70 pc for the scale height of the thick disk, 400 ± 100 pc for the central dimension of the spheroid, 0.0082 ± 0.0030 for the spheroid to disk density ratio, and 0.57 ± 0.05 for the oblate spheroid parameter.

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An out of equilibrium Ising model subjected to an irreversible dynamics is analyzed by means of a stochastic dynamics, on a effort that aims to understand the observed critical behavior as consequence of the intrinsic microscopic characteristics. The study focus on the kinetic phase transitions that take place by assuming a lattice model with inversion symmetry and under the influence of two competing Glauber dynamics, intended to describe the stationary states using the entropy production, which characterize the system behavior and clarifies its reversibility conditions. Thus, it is considered a square lattice formed by two sublattices interconnected, each one of which is in contact with a heat bath at different temperature from the other. Analytical and numerical treatments are faced, using mean-field approximations and Monte Carlo simulations. For the one dimensional model exact results for the entropy production were obtained, though in this case the phase transition that takes place in the two dimensional counterpart is not observed, fact which is in accordance with the behavior shared by lattice models presenting inversion symmetry. Results found for the stationary state show a critical behavior of the same class as the equilibrium Ising model with a phase transition of the second order, which is evidenced by a divergence with an exponent µ ¼ 0:003 of the entropy production derivative.

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In this work, we reported some results about the stochastic quantization of the spherical model. We started by reviewing some basic aspects of this method with emphasis in the connection between the Langevin equation and the supersymmetric quantum mechanics, aiming at the application of the corresponding connection to the spherical model. An intuitive idea is that when applied to the spherical model this gives rise to a supersymmetric version that is identified with one studied in Phys. Rev. E 85, 061109, (2012). Before investigating in detail this aspect, we studied the stochastic quantization of the mean spherical model that is simpler to implement than the one with the strict constraint. We also highlight some points concerning more traditional methods discussed in the literature like canonical and path integral quantization. To produce a supersymmetric version, grounded in the Nicolai map, we investigated the stochastic quantization of the strict spherical model. We showed in fact that the result of this process is an off-shell supersymmetric extension of the quantum spherical model (with the precise supersymmetric constraint structure). That analysis establishes a connection between the classical model and its supersymmetric quantum counterpart. The supersymmetric version in this way constructed is a more natural one and gives further support and motivations to investigate similar connections in other models of the literature.

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We use the star count model of Ortiz & L´epine to perform an unprecedented exploration of the most important Galactic parameters comparing the predicted counts with the Two Micron All Sky Survey observed star counts in the J, H, and KS bands for a grid of positions covering the whole sky. The comparison is made using a grid of lines of sight given by the HEALPix pixelization scheme. The resulting best-fit values for the parameters are: 2120 ± 200 pc for the radial scale length and 205 ± 40 pc for the scale height of the thin disk, with a central hole of 2070+2000 −800 pc for the same disk, 3050 ± 500 pc for the radial scale length and 640 ± 70 pc for the scale height of the thick disk, 400 ± 100 pc for the central dimension of the spheroid, 0.0082 ± 0.0030 for the spheroid to disk density ratio, and 0.57 ± 0.05 for the oblate spheroid parameter.

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[EN]Ensemble forecasting is a methodology to deal with uncertainties in the numerical wind prediction. In this work we propose to apply ensemble methods to the adaptive wind forecasting model presented in. The wind field forecasting is based on a mass-consistent model and a log-linear wind profile using as input data the resulting forecast wind from Harmonie, a Non-Hydrostatic Dynamic model used experimentally at AEMET with promising results. The mass-consistent model parameters are estimated by using genetic algorithms. The mesh is generated using the meccano method and adapted to the geometry…

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This thesis describes modelling tools and methods suited for complex systems (systems that typically are represented by a plurality of models). The basic idea is that all models representing the system should be linked by well-defined model operations in order to build a structured repository of information, a hierarchy of models. The port-Hamiltonian framework is a good candidate to solve this kind of problems as it supports the most important model operations natively. The thesis in particular addresses the problem of integrating distributed parameter systems in a model hierarchy, and shows two possible mechanisms to do that: a finite-element discretization in port-Hamiltonian form, and a structure-preserving model order reduction for discretized models obtainable from commercial finite-element packages.

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The present dissertation focuses on burnout and work engagement among teachers, with especial focus on the Job-Demands Resources Model: Chapter 1 focuses on teacher burnout. It aims to investigate the role of efficacy beliefs using negatively worded inefficacy items instead of positive ones and to establish whether depersonalization and cynism can be considered two different dimensions of the teacher burnout syndrome. Chapter 2 investigates the factorial validity of the instruments used to measure work engagement (i.e. Utrecht Work Engagement Scale, UWES-17 and UWES-9). Moreover, because the current study is partly longitudinal in nature, also the stability across time of engagement can be investigated. Finally, based on cluster-analyses, two groups that differ in levels of engagement are compared as far as their job- and personal resources (i.e. possibilities for personal development, work-life balance, and self-efficacy), positive organizational attitudes and behaviours (i.e., job satisfaction and organizational citizenship behaviour) and perceived health are concerned. Chapter 3 tests the JD-R model in a longitudinal way, by integrating also the role of personal resources (i.e. self-efficacy). This chapter seeks answers to questions on what are the most important job demands, job and personal resources contributing to discriminate burned-out teachers from non-burned-out teachers, as well as engaged teachers from non-engaged teachers. Chapter 4 uses a diary study to extend knowledge about the dynamic nature of the JD-R model by considering between- and within-person variations with regard to both motivational and health impairment processes.

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In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

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This abstract presents the biomechanical model that is used in the European ContraCancrum project, aiming at simulating tumor evolution in the brain and lung. The construction of the finite element model as well as a simulation of tumor growth are shown. The construction of the mesh is fully automatic and is therefore compatible with a clinical application. This biomechanical model will be later combined to a cellular level simulator also developed in the project.

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A triple cell co-culture model was recently established by the authors, consisting of either A549 or 16HBE14o- epithelial cells, human blood monocyte-derived macrophages and dendritic cells, which offers the possibility to study the interaction of xenobiotics with those cells. The 16HBE14o- containing co-culture model mimics the airway epithelial barrier, whereas the A549 co-cultures mimic the alveolar type II-like epithelial barrier. The goal of the present work was to establish a new triple cell co-culture model composed of primary alveolar type I-like cells isolated from human lung biopsies (hAEpC) representing a more realistic alveolar epithelial barrier wall, since type I epithelial cells cover >93% of the alveolar surface. Monocultures of A549 and 16HBE14o- were morphologically and functionally compared with the hAEpC using laser scanning microscopy, as well as transmission electron microscopy, and by determining the epithelial integrity. The triple cell co-cultures were characterized using the same methods. It could be shown that the epithelial integrity of hAEpC (mean ± SD, 1180 ± 188 Ω cm(2)) was higher than in A549 (172 ± 59 Ω cm(2)) but similar to 16HBE14o- cells (1469 ± 156 Ω cm(2)). The triple cell co-culture model with hAEpC (1113 ± 30 Ω cm(2)) showed the highest integrity compared to the ones with A549 (93 ± 14 Ω cm(2)) and 16HBE14o- (558 ± 267 Ω cm(2)). The tight junction protein zonula occludens-1 in hAEpC and 16HBE14o- were more regularly expressed but not in A549. The epithelial alveolar model with hAEpC combined with two immune cells (i.e. macrophages and dendritic cells) will offer a novel and more realistic cell co-culture system to study possible cell interactions of inhaled xenobiotics and their toxic potential on the human alveolar type I epithelial wall.

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Osteoarticular allograft transplantation is a popular treatment method in wide surgical resections with large defects. For this reason hospitals are building bone data banks. Performing the optimal allograft selection on bone banks is crucial to the surgical outcome and patient recovery. However, current approaches are very time consuming hindering an efficient selection. We present an automatic method based on registration of femur bones to overcome this limitation. We introduce a new regularization term for the log-domain demons algorithm. This term replaces the standard Gaussian smoothing with a femur specific polyaffine model. The polyaffine femur model is constructed with two affine (femoral head and condyles) and one rigid (shaft) transformation. Our main contribution in this paper is to show that the demons algorithm can be improved in specific cases with an appropriate model. We are not trying to find the most optimal polyaffine model of the femur, but the simplest model with a minimal number of parameters. There is no need to optimize for different number of regions, boundaries and choice of weights, since this fine tuning will be done automatically by a final demons relaxation step with Gaussian smoothing. The newly developed synthesis approach provides a clear anatomically motivated modeling contribution through the specific three component transformation model, and clearly shows a performance improvement (in terms of anatomical meaningful correspondences) on 146 CT images of femurs compared to a standard multiresolution demons. In addition, this simple model improves the robustness of the demons while preserving its accuracy. The ground truth are manual measurements performed by medical experts.