Dynamics of the deconfinement transition of quarks and gluons in a finite volume

We employ finite elements methods for the approximation of solutions of the Ginzburg-Landau equations describing the deconfinement transition in quantum chromodynamics. These methods seem appropriate for situations where the deconfining transition occurs over a finite volume as in relativistic heavy ion collisions. where in addition expansion of the system and flow of matter are important. Simulation results employing finite elements are presented for a Ginzburg-Landau equation based on a model free energy describing the deconfining transition in pure gauge SU(2) theory. Results for finite and infinite system are compared. (C) 2009 Elsevier B.V. All rights reserved.

Predicting body and carcass characteristics of 2 broiler chicken strains using support vector regression and neural network models

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.

Connection between the affine and conformal affine Toda models and their Hirota solution

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.

Robust linear mixed models with normal/independent distributions and Bayesian MCMC implementation

Linear mixed effects models have been widely used in analysis of data where responses are clustered around some random effects, so it is not reasonable to assume independence between observations in the same cluster. In most biological applications, it is assumed that the distributions of the random effects and of the residuals are Gaussian. This makes inferences vulnerable to the presence of outliers. Here, linear mixed effects models with normal/independent residual distributions for robust inferences are described. Specific distributions examined include univariate and multivariate versions of the Student-t, the slash and the contaminated normal. A Bayesian framework is adopted and Markov chain Monte Carlo is used to carry out the posterior analysis. The procedures are illustrated using birth weight data on rats in a texicological experiment. Results from the Gaussian and robust models are contrasted, and it is shown how the implementation can be used for outlier detection. The thick-tailed distributions provide an appealing robust alternative to the Gaussian process in linear mixed models, and they are easily implemented using data augmentation and MCMC techniques.

Influence of microthreads and platform switching on stress distribution in bone using angled abutments

Purpose: To evaluate the stress distribution in peri-implant bone by simulating the effect of an implant with microthreads and platform switching on angled abutments through tridimensional finite element analysis. The postulated hypothesis was that the presence of microthreads and platform switching would reduce the stress concentration in the cortical bone. Methods: Four mathematical models of a central incisor supported by an implant (5.0mm×13mm) were created in which the type of thread surface in the neck portion (microthreaded or smooth) and the diameter of the angled abutment connection (5.0 and 4.1mm) were varied. These models included the RM (regular platform and microthreads), the RS (regular platform and smooth neck surface), the SM (platform switching and microthreads), and the SS (platform switching and smooth neck). The analysis was performed using ANSYS Workbench 10.0 (Swanson Analysis System). An oblique load (100N) was applied to the palatine surface of the central incisor. The bone/implant interface was considered to be perfectly integrated. Values for the maximum (σmax) and minimum (σmin) principal stress, the equivalent von Mises stress (σvM), and the maximum principal elastic strain (e{open}max) for cortical and trabecular bone were obtained. Results: For the cortical bone, the highest σmax (MPa) were observed for the RM (55.1), the RS (51.0), the SM (49.5), and the SS (44.8) models. The highest σvM (MPa) were found for the RM (45.4), the SM (42.1), the RS (38.7), and the SS models (37). The highest values for σmin were found for the RM, SM, RS and SS models. For the trabecular bone, the highest σmax values (MPa) were observed in the RS model (6.55), followed by the RM (6.37), SS (5.6), and SM (5.2) models. Conclusion: The hypothesis that the presence of microthreads and a switching platform would reduce the stress concentration in the cortical bone was partially rejected, mainly because the microthreads increased the stress concentration in cortical bone. Only platform switching reduced the stress in cortical bone. © 2012 Japan Prosthodontic Society.

Principal components and factor analytic models for birth to mature weights in Nellore cattle

A total of 61,528 weight records from 22,246 Nellore animals born between 1984 and 2002 were used to compare different multiple-trait analysis methods for birth to mature weights. The following models were used: standard multivarite model (MV), five reduced-rank models fitting the first 1, 2, 3, 4 and 5 genetic principal components, and five models using factor analysis with 1, 2, 3, 4 and 5 factors. Direct additive genetic random effects and residual effects were included in all models. In addition, maternal genetic and maternal permanent environmental effects were included as random effects for birth and weaning weight. The models included contemporary group as fixed effect and age of animal at recording (except for birth weight) and age of dam at calving as linear and quadratic effects (for birth weight and weaning weight). The maternal genetic, maternal permanent environmental and residual (co)variance matrices were assumed to be full rank. According to model selection criteria, the model fitting the three first principal components (PC3) provided the best fit, without the need for factor analysis models. Similar estimates of phenotypic, direct additive and maternal genetic, maternal permanent environmental and residual (co)variances were obtained with models MV and PC3. Direct heritability ranged from 0.21 (birth weight) to 0.45 (weight at 6 years of age). The genetic and phenotypic correlations obtained with model PC3 were slightly higher than those estimated with model MV. In general, the reduced-rank model substantially decreased the number of parameters in the analyses without reducing the goodness-of-fit. © 2013 Elsevier B.V.

Comparison of factor-analytic and reduced rank models for test-day milk yield in Gyr dairy cattle (Bos indicus)

We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields. © FUNPEC-RP.

Positioning and number of nutritional levels in dose-response trials to estimate the optimal-level and the adjustment of the models

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

Growth in weight and of some tissues in the bullfrog: fitting nonlinear models during the fattening phase

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

Application of the finite element method in Dentistry

The finite element method (FEM) involves a series of computational procedures to calculate the stress in each element, which performs a model solution. Such a structural analysis allows the determination of stress resulting from external force, pressure, thermal change, and other factors. This method is extremely useful for indicating mechanical aspects of biomaterials and human tissues that can hardly be measured in vivo. The results obtained can then be studied using visualization software within the FEM environment to view a variety of parameters, and to fully identify implications of the analysis. Objective: An overview to show application of FEM in dentistry was undertaken. Literature review: This paper shows the basic concept, advances, advantages, limitations and applications of finite element method (FEM) in dentistry. Conclusion: It is extremely important to verify what the purpose of the study is in order to correctly apply FEM.

Application of hte finite element method in Dentistry

Introduction: The finite element method (FEM) involves a series of computational procedures to calculate the stress in each element, which performs a model solution. Such a structural analysis allows the determination of stress resulting from external force, pressure, thermal change, and other factors. This method is extremely useful for indicating mechanical aspects of biomaterials and human tissues that can hardly be measured in vivo. The results obtained can then be studied using visualization software within the FEM environment to view a variety of parameters, and to fully identify implications of the analysis. Objective: An overview to show application of FEM in dentistry was undertaken. Literature review: This paper shows the basic concept, advances, advantages, limitations and applications of finite element method (FEM) in dentistry. Conclusion: It is extremely important to verify what the purpose of the study is in order to correctly apply FEM.

Evaluation of roof slope and exposure with different roofing materials in reduced models of animal production facilities in spring and summer

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

Using occupancy models to investigate space partitioning between two sympatric large predators, the jaguar and puma in central Brazil

Coexistence of sympatric species is mediated by resource partitioning. Pumas occur sympatrically with jaguars throughout most of the jaguar's range but few studies have investigated space partitioning between both species. Here, camera trapping and occupancy models accounting for imperfect detection were employed in a Bayesian framework to investigate space partitioning between the jaguar and puma in Emas National Park (ENP), central Brazil. Jaguars were estimated to occupy 54.1% and pumas 39.3% of the sample sites. Jaguar occupancy was negatively correlated with distance to water and positively correlated with the amount of dense habitat surrounding the camera trap. Puma occupancy only showed a weak negative correlation with distance to water and with jaguar presence. Both species were less often present at the same site than expected under independent distributions. Jaguars had a significantly higher detection probability at cameras on roads than at off-road locations. For pumas, detection was similar on and off-road. Results indicate that both differences in habitat use and active avoidance shape space partitioning between jaguars and pumas in ENP. Considering its size, the jaguar is likely the competitively dominant of the two species. Owing to its habitat preferences, suitable jaguar habitat outside the park is probably sparse. Consequently, the jaguar population is likely largely confined to the park, while the puma population is known to extend into ENP's surroundings. (C) 2011 Deutsche Gesellschaft fur Saugetierkunde. Published by Elsevier GmbH. All rights reserved.

Use of recent geoid models to estimate mean dynamic topography and geostrophic currents in South Atlantic and Brazil Malvinas confluence

The use of geoid models to estimate the Mean Dynamic Topography was stimulated with the launching of the GRACE satellite system, since its models present unprecedented precision and space-time resolution. In the present study, besides the DNSC08 mean sea level model, the following geoid models were used with the objective of computing the MDTs: EGM96, EIGEN-5C and EGM2008. In the method adopted, geostrophic currents for the South Atlantic were computed based on the MDTs. In this study it was found that the degree and order of the geoid models affect the determination of TDM and currents directly. The presence of noise in the MDT requires the use of efficient filtering techniques, such as the filter based on Singular Spectrum Analysis, which presents significant advantages in relation to conventional filters. Geostrophic currents resulting from geoid models were compared with the HYCOM hydrodynamic numerical model. In conclusion, results show that MDTs and respective geostrophic currents calculated with EIGEN-5C and EGM2008 models are similar to the results of the numerical model, especially regarding the main large scale features such as boundary currents and the retroflection at the Brazil-Malvinas Confluence.