A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.

THE LOG-BURR XII REGRESSION MODEL FOR GROUPED SURVIVAL DATA

The log-Burr XII regression model for grouped survival data is evaluated in the presence of many ties. The methodology for grouped survival data is based on life tables, where the times are grouped in k intervals, and we fit discrete lifetime regression models to the data. The model parameters are estimated by maximum likelihood and jackknife methods. To detect influential observations in the proposed model, diagnostic measures based on case deletion, so-called global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to these measures, the total local influence and influential estimates are also used. We conduct Monte Carlo simulation studies to assess the finite sample behavior of the maximum likelihood estimators of the proposed model for grouped survival. A real data set is analyzed using a regression model for grouped data.

Qualitative SEM/EDS analysis of microleakage and apical gap formation of adhesive root-filling materials

Objective: The aim of this study was to compare the correspondence between gap formation and apical microleakage in root canals filled with epoxy resin-based (AH Plus) combined or not with resinous primer or with a dimethacrylate-based root canal sealer (Epiphany). Material and Methods: Thirty-nine lower single-rooted human premolars were filled by the lateral condensation technique (LC) and immersed in a 50-wt% aqueous silver nitrate solution at 37 degrees C (24 h). After longitudinal sectioning, epoxy resin replicas were made from the tooth specimens. Both the replicas and the specimens were prepared for scanning electron microscopy (SEM). The gaps were observed in the replicas. Apical microleakage was detected in the specimens by SEM/energy dispersive spectroscopy (SEM/EDS). The data were analyzed statistically using an Ordinal Logistic Regression model and Analysis of Correspondence (alpha=0.05). Results: Epiphany presented more regions containing gaps between dentin and sealer (p<0.05). There was correspondence between the presence of gaps and microleakage (p<0.05). Microleakage was similar among the root-filling materials (p>0.05). Conclusions: The resinous primer did not improve the sealing ability of AH Plus sealer and the presence of gaps had an effect on apical microleakage for all materials.

A Poisson mixed model with nonnormal random effect distribution

In this paper, we propose a random intercept Poisson model in which the random effect is assumed to follow a generalized log-gamma (GLG) distribution. This random effect accommodates (or captures) the overdispersion in the counts and induces within-cluster correlation. We derive the first two moments for the marginal distribution as well as the intraclass correlation. Even though numerical integration methods are, in general, required for deriving the marginal models, we obtain the multivariate negative binomial model from a particular parameter setting of the hierarchical model. An iterative process is derived for obtaining the maximum likelihood estimates for the parameters in the multivariate negative binomial model. Residual analysis is proposed and two applications with real data are given for illustration. (C) 2011 Elsevier B.V. All rights reserved.

A note on the use of the generalized odds ratio in meta-analysis of association studies involving bi- and tri-allelic polymorphisms

Abstract Background The generalized odds ratio (GOR) was recently suggested as a genetic model-free measure for association studies. However, its properties were not extensively investigated. We used Monte Carlo simulations to investigate type-I error rates, power and bias in both effect size and between-study variance estimates of meta-analyses using the GOR as a summary effect, and compared these results to those obtained by usual approaches of model specification. We further applied the GOR in a real meta-analysis of three genome-wide association studies in Alzheimer's disease. Findings For bi-allelic polymorphisms, the GOR performs virtually identical to a standard multiplicative model of analysis (e.g. per-allele odds ratio) for variants acting multiplicatively, but augments slightly the power to detect variants with a dominant mode of action, while reducing the probability to detect recessive variants. Although there were differences among the GOR and usual approaches in terms of bias and type-I error rates, both simulation- and real data-based results provided little indication that these differences will be substantial in practice for meta-analyses involving bi-allelic polymorphisms. However, the use of the GOR may be slightly more powerful for the synthesis of data from tri-allelic variants, particularly when susceptibility alleles are less common in the populations (≤10%). This gain in power may depend on knowledge of the direction of the effects. Conclusions For the synthesis of data from bi-allelic variants, the GOR may be regarded as a multiplicative-like model of analysis. The use of the GOR may be slightly more powerful in the tri-allelic case, particularly when susceptibility alleles are less common in the populations.

Tragedy on grade crossing: driver failure or systemic fragility?

In 2010, an accident occurred in Americana-SP, Brazil, involving two trains and one bus on a Grade Crossing, when 10 people died and 17 were injured including workers. This paper aims to analyze the accident using the Model of Analysis and Prevention of Work Accidents (MAPA). The method provides observation of work, interviews and analysis of documents to understand precedents of the event in the following stages: to understand the usual work from the involved people, the changes occurred in the system, the operation of barriers, managerial and organizational aspects. By the end, measures are suggested to avoid new occurrences. The accident took place at night in a site with insufficient lighting. The working conditions of bus drivers, train operators and watchmen are inadequate. There were only symbolic barriers (visual and acoustic signals) triggered manually by watchman upon train operator radio communication. The fragility of the barrier system associated to poor lighting and short time to trigger the signaling seem to play a critical role in the event. Contrary to the official report which resulted in guilt of the bus driver, the conclusion of the paper emphasizes the fragility of the safety system and the need of level crossing reproject.

Quantitative MRI of Vastus Medialis, Vastus Lateralis and Gluteus Medius Muscle Workload after Squat Exercise: Comparison Between Squatting with Hip Adduction and Hip Abduction

The aim of the present study was to evaluate the use MRI to quantify the workload of gluteus medius (GM), vastus medialis (VM) and vastus lateralis (VL) muscles in different types of squat exercises. Fourteen female volunteers were evaluated, average age of 22 +/- 2 years, sedentary, without clinical symptoms, and without history of previous lower limb injuries. Quantitative MRI was used to analyze VM, VL and GM muscles before and after squat exercise, squat associated with isometric hip adduction and squat associated with isometric hip abduction. Multi echo images were acquired to calculate the transversal relaxation times (T2) before and after exercise. Mixed Effects Model statistical analysis was used to compare images before and after the exercise (Delta T2) to normalize the variability between subjects. Imaging post processing was performed in Matlab software. GM muscle was the least active during the squat associated with isometric hip adduction and VM the least active during the squat associated with isometric hip abduction, while VL was the most active during squat associated with isometric hip adduction. Our data suggests that isometric hip adduction during the squat does not increase the workload of VM, but decreases the GM muscle workload. Squat associated with isometric hip abduction does not increase VL workload.

Electrooxidation of Ethanol on Pt and PtRu Surfaces Investigated by ATR Surface-Enhanced Infrared Absorption Spectroscopy

Herein, it was investigated for the first time the electro-oxidation of ethanol on Pt and PtRu electrodeposits in acidic media by using in situ surface enhanced infrared absorption spectroscopy with attenuated total reflection (ATR-SEIRAS). The experimental setup circumvents the weak absorbance signals related to adsorbed species, usually observed for rough, electrodeposited surfaces, and allows a full description of the CO coverage with the potential for both catalysts. The dynamics of adsorption-oxidation of CO was accessed by ATR-SEIRAS experiments (involving four ethanol concentrations) and correlated with expressions derived from a simple kinetic model. Kinetic analysis suggests that the growing of the CO adsorbed layer is nor influenced by the presence of Ru neither by the concentration of ethanol. The results suggest that the C-C scission is not related to the presence of Ru and probably happens at Pt sites.

Flow Visualization with Quantified Spatial and Temporal Errors Using Edge Maps

Robust analysis of vector fields has been established as an important tool for deriving insights from the complex systems these fields model. Traditional analysis and visualization techniques rely primarily on computing streamlines through numerical integration. The inherent numerical errors of such approaches are usually ignored, leading to inconsistencies that cause unreliable visualizations and can ultimately prevent in-depth analysis. We propose a new representation for vector fields on surfaces that replaces numerical integration through triangles with maps from the triangle boundaries to themselves. This representation, called edge maps, permits a concise description of flow behaviors and is equivalent to computing all possible streamlines at a user defined error threshold. Independent of this error streamlines computed using edge maps are guaranteed to be consistent up to floating point precision, enabling the stable extraction of features such as the topological skeleton. Furthermore, our representation explicitly stores spatial and temporal errors which we use to produce more informative visualizations. This work describes the construction of edge maps, the error quantification, and a refinement procedure to adhere to a user defined error bound. Finally, we introduce new visualizations using the additional information provided by edge maps to indicate the uncertainty involved in computing streamlines and topological structures.

Circuit board accident - organizational dimension hidden by prescribed safety

This study analyzes an accident in which two maintenance workers suffered severe burns while replacing a circuit breaker panel in a steel mill, following model of analysis and prevention of accidents (MAPA) developed with the objective of enlarging the perimeter of interventions and contributing to deconstruction of blame attribution practices. The study was based on materials produced by a health service team in an in-depth analysis of the accident. The analysis shows that decisions related to system modernization were taken without considering their implications in maintenance scheduling and creating conflicts of priorities and of interests between production and safety; and also reveals that the lack of a systemic perspective in safety management was its principal failure. To explain the accident as merely non-fulfillment of idealized formal safety rules feeds practices of blame attribution supported by alibi norms and inhibits possible prevention. In contrast, accident analyses undertaken in worker health surveillance services show potential to reveal origins of these events incubated in the history of the system ignored in practices guided by the traditional paradigm.

THE UBV(RI)(C) COLORS OF THE SUN

Photometric data in the UBV(RI)(C) system have been acquired for 80 solar analog stars for which we have previously derived highly precise atmospheric parameters T-eff, log g, and [Fe/H] using high-resolution, high signal-to-noise ratio spectra. UBV and (RI)(C) data for 46 and 76 of these stars, respectively, are published for the first time. Combining our data with those from the literature, colors in the UBV(RI) C system, with similar or equal to 0.01 mag precision, are now available for 112 solar analogs. Multiple linear regression is used to derive the solar colors from these photometric data and the spectroscopically derived T-eff, log g, and [Fe/H] values. To minimize the impact of systematic errors in the model-dependent atmospheric parameters, we use only the data for the 10 stars that most closely resemble our Sun, i.e., the solar twins, and derive the following solar colors: (B - V)(circle dot) = 0.653 +/- 0.005, (U - B)(circle dot) = 0.166 +/- 0.022, (V - R)(circle dot) = 0.352 +/- 0.007, and (V - I)(circle dot) = 0.702 +/- 0.010. These colors are consistent, within the 1 sigma errors, with those derived using the entire sample of 112 solar analogs. We also derive the solar colors using the relation between spectral-line-depth ratios and observed stellar colors, i.e., with a completely model-independent approach, and without restricting the analysis to solar twins. We find (B - V)(circle dot) = 0.653 +/- 0.003, (U - B)(circle dot) = 0.158 +/- 0.009, (V - R)(circle dot) = 0.356 +/- 0.003, and (V - I)(circle dot) = 0.701 +/- 0.003, in excellent agreement with the model-dependent analysis.

Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle

A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits.

Likelihood-based inference for power distributions

This paper considers likelihood-based inference for the family of power distributions. Widely applicable results are presented which can be used to conduct inference for all three parameters of the general location-scale extension of the family. More specific results are given for the special case of the power normal model. The analysis of a large data set, formed from density measurements for a certain type of pollen, illustrates the application of the family and the results for likelihood-based inference. Throughout, comparisons are made with analogous results for the direct parametrisation of the skew-normal distribution.

Electrooxidation of ethanol on Pt and PtRu surfaces investigated by ATR surface-enhanced infrared absorption spectroscopy

Herein, it was investigated for the first time the electro-oxidation of ethanol on Pt and PtRu electrodeposits in acidic media by using in situ surface enhanced infrared absorption spectroscopy with attenuated total reflection (ATR-SEIRAS). The experimental setup circumvents the weak absorbance signals related to adsorbed species, usually observed for rough, electrodeposited surfaces, and allows a full description of the CO coverage with the potential for both catalysts. The dynamics of adsorption-oxidation of CO was accessed by ATR-SEIRAS experiments (involving four ethanol concentrations) and correlated with expressions derived from a simple kinetic model. Kinetic analysis suggests that the growing of the CO adsorbed layer is nor influenced by the presence of Ru neither by the concentration of ethanol. The results suggest that the C-C scission is not related to the presence of Ru and probably happens at Pt sites.

Fuzzy linguistic model for bioelectrical impedance vector analysis

Backgrounds Ea aims: The boundaries between the categories of body composition provided by vectorial analysis of bioimpedance are not well defined. In this paper, fuzzy sets theory was used for modeling such uncertainty. Methods: An Italian database with 179 cases 18-70 years was divided randomly into developing (n = 20) and testing samples (n = 159). From the 159 registries of the testing sample, 99 contributed with unequivocal diagnosis. Resistance/height and reactance/height were the input variables in the model. Output variables were the seven categories of body composition of vectorial analysis. For each case the linguistic model estimated the membership degree of each impedance category. To compare such results to the previously established diagnoses Kappa statistics was used. This demanded singling out one among the output set of seven categories of membership degrees. This procedure (defuzzification rule) established that the category with the highest membership degree should be the most likely category for the case. Results: The fuzzy model showed a good fit to the development sample. Excellent agreement was achieved between the defuzzified impedance diagnoses and the clinical diagnoses in the testing sample (Kappa = 0.85, p < 0.001). Conclusions: fuzzy linguistic model was found in good agreement with clinical diagnoses. If the whole model output is considered, information on to which extent each BIVA category is present does better advise clinical practice with an enlarged nosological framework and diverse therapeutic strategies. (C) 2012 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.