Short Communication: In vitro evaluation of the abrasiveness of acidic dentifrices.

AIM: This in vitro study evaluated the abrasiveness of acidic fluoride (F) dentifrices with different F concentrations on bovine enamel. METHODS: Enamel blocks (4.0 x 4.0 mm2, n=120) were selected according to their surface microhardness and divided into 12 groups. Slurries of dentifrices were used containing 0 (placebo), 275, 412, 550 and 1,100 ppm F (pH 4.5 or 7.0), as well as testing two commercial dentifrices (Crest, positive control, 1,100 ppm F and Colgate Baby, 500 ppm F). Enamel blocks were partially protected with an adhesive tape (control area) and then brushed by an automated toothbrushing machine (16,000 strokes). During this process, 0.4 ml of the slurries were injected every 2 mins on the enamel blocks. After toothbrushing, enamel wear was determined by profilometry. STATISTICS: Results were analyzed by ANOVA and Tukey's test (p<0.05). RESULTS: The mean values for pH in the suspensions during treatment were 6.93, 4.32, 7.56 and 8.19 for neutral experimental dentifrices, acidic experimental dentifrices, Crest and Colgate baby, respectively. The abrasiveness of the acidic dentifrices was similar (p<0.05) to the neutral ones, whereas commercial dentifrices yielded lower abrasion (p<0.05). CONCLUSION: It was concluded that a reduction of the pH of dentifrices does not increase their abrasiveness.

Multi-trait and random regression mature weight heritability and breeding value estimates in Nelore cattle

Mature weight breeding values were estimated using a multi-trait animal model (MM) and a random regression animal model (RRM). Data consisted of 82 064 weight records from 8 145 animals, recorded from birth to eight years of age. Weights at standard ages were considered in the MM. All models included contemporary groups as fixed effects, and age of dam (linear and quadratic effects) and animal age as covariates. In the RRM, mean trends were modelled through a cubic regression on orthogonal polynomials of animal age and genetic maternal and direct and maternal permanent environmental effects were also included as random. Legendre polynomials of orders 4, 3, 6 and 3 were used for animal and maternal genetic and permanent environmental effects, respectively, considering five classes of residual variances. Mature weight (five years) direct heritability estimates were 0.35 (MM) and 0.38 (RRM). Rank correlation between sires' breeding values estimated by MM and RRM was 0.82. However, selecting the top 2% (12) or 10% (62) of the young sires based on the MM predicted breeding values, respectively 71% and 80% of the same sires would be selected if RRM estimates were used instead. The RRM modelled the changes in the (co)variances with age adequately and larger breeding value accuracies can be expected using this model. © South African Society for Animal Science.

Upconversion ultraviolet random lasing in Nd 3+ doped fluoroindate glass powder

An upconversion random laser (RL) operating in the ultraviolet is reported for Nd 3+ doped fluoroindate glass powder pumped at 575 nm. The RL is obtained by the resonant excitation of the Nd 3+ state 2G 7/2 followed by energy transfer among two excited ions such that one ion in the pair decays to a lower energy state and the other is promoted to state 4D 7/2 from where it decays emitting light at 381 nm. The RL threshold of 30 kW/cm 2 was determined by monitoring the photoluminescence intensity as a function of the pump laser intensity. The RL pulses have time duration of 29 ns that is 50 times smaller than the decay time of the upconversion signal when the sample is pumped with intensities below the RL laser threshold. © 2011 Optical Society of America.

As características dos alunos são determinantes para o adoecimento de professores - um estudo comparativo sobre a incidência de Burnout em professores do ensino regular e especial

The practice of teaching is permeated by adverse working conditions, low wages, inadequacy of material and teaching resources, overcrowded classrooms, tension in relationships with the students, excessive work load, lack of safety in the school environment, insignificant participation in institutional planning and in institutional politics. The objective of the present study was to compare burnout among three groups of teachers who work in elementary grades: a) 20 teachers who teach in regular school classrooms without the inclusion of students with special educational needs - RSI Group; b) 20 teachers who teach in the regular classroom with special needs students - RCI Group; c) 20 teachers who teach in resource classrooms (SR Group). The instruments used for data collection were the Maslach Burnout Inventory -MBI. The data was analyzed by SPSS version 13.0 and Kruskal-Wallis test for comparison of the three groups. The results were organized in the form of figures and tables. In general, the results demonstrated that the groups presented relative similarity. The teachers from the SR Group obtained the best results in the evaluation of the three burnout scales when compared to the RSI Group and RCI Group, that is, there was a prevalence of answers in the lower levels of emotional exhaustion, high level of low personal accomplishment and low level for depersonalization. It is hoped that these results contribute to a better understanding of burnout in teachers from regular classrooms with or without students with educational special needs and/or to indicate new directions for investigation.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.

Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data. © FUNPEC-RP.

Regular and switching platform: Bone stress analysis with varying implant diameter

The aim of this study was to evaluate stress distribution of the peri-implant bone by simulating the biomechanical influence of implants with different diameters of regular or platform switched connections by means of 3-dimensional finite element analysis. Five mathematical models of an implant-supported central incisor were created by varying the diameter (5.5 and 4.5 mm, internal hexagon) and abutment platform (regular and platform switched). For the cortical bone, the highest stress values (rmax and rvm) were observed in situation R1, followed by situations S1, R2, S3, and S2. For the trabecular bone, the highest stress values (rmax) were observed in situation S3, followed by situations R1, S1, R2, and S2. The influence of platform switching was more evident for cortical bone than for trabecular bone and was mainly seen in large platform diameter reduction.

Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach

Background: Meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal's life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality.Results: The set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism.Conclusions: These results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle. © 2013 Mokry et al.; licensee BioMed Central Ltd.

Genetic evaluation using multi-trait and random regression models in Simmental beef cattle

The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil. ©FUNPEC-RP.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

OPF-MRF: Optimum-path forest and Markov random fields for contextual-based image classification

Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.

Influência da prática regular de atividade física sobre sintomas depressivos em idosos institucionalizados

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A influência da prática de atividade física regular na qualidade de vida e na composição corporal de portadores de osteoartrite

Pós-graduação em Alimentos e Nutrição - FCFAR

Consumo regular de suco de laranja vermelha em portadores de hepatite C crônica

Pós-graduação em Alimentos e Nutrição - FCFAR