Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Cost-effectiveness analysis of universal childhood hepatitis A vaccination in Brazil: Regional analyses according to the endemic context

Objective: To To conduct a cost-effectiveness analysis of a universal childhood hepatitis A vaccination program in Brazil. Methods: An age and time-dependent dynamic model was developed to estimate the incidence of hepatitis A for 24 years. The analysis was run separately according to the pattern of regional endemicity, one for South + Southeast (low endemicity) and one for the North + Northeast + Midwest (intermediate endemicity). The decision analysis model compared universal childhood vaccination with current program of vaccinating high risk individuals. Epidemiologic and cost estimates were based on data from a nationwide seroprevalence survey of viral hepatitis, primary data collection, National Health Information Systems and literature. The analysis was conducted from both the health system and societal perspectives. Costs are expressed in 2008 Brazilian currency (Real). Results: A universal immunization program would have a significant impact on disease epidemiology in all regions, resulting in 64% reduction in the number of cases of icteric hepatitis, 59% reduction in deaths for the disease and a 62% decrease of life years lost, in a national perspective. With a vaccine price of R$16.89 (US$7.23) per dose, vaccination against hepatitis A was a cost-saving strategy in the low and intermediate endemicity regions and in Brazil as a whole from both health system and society perspective. Results were most sensitive to the frequency of icteric hepatitis, ambulatory care and vaccine costs. Conclusions: Universal childhood vaccination program against hepatitis A could be a cost-saving strategy in all regions of Brazil. These results are useful for the Brazilian government for vaccine related decisions and for monitoring population impact if the vaccine is included in the National Immunization Program. (C) 2012 Elsevier Ltd. All rights reserved.

Analysis of energy dissipation in stirred suspension polymerisation reactors using computational fluid dynamics

This work evaluates the spatial distribution of normalised rates of droplet breakage and droplet coalescence in liquidliquid dispersions maintained in agitated tanks at operation conditions normally used to perform suspension polymerisation reactions. Particularly, simulations are performed with multiphase computational fluid dynamics (CFD) models to represent the flow field in liquidliquid styrene suspension polymerisation reactors for the first time. CFD tools are used first to compute the spatial distribution of the turbulent energy dissipation rates (e) inside the reaction vessel; afterwards, normalised rates of droplet breakage and particle coalescence are computed as functions of e. Surprisingly, multiphase simulations showed that the rates of energy dissipation can be very high near the free vortex surfaces, which has been completely neglected in previous works. The obtained results indicate the existence of extremely large energy dissipation gradients inside the vessel, so that particle breakage occurs primarily in very small regions that surround the impeller and the free vortex surface, while particle coalescence takes place in the liquid bulk. As a consequence, particle breakage should be regarded as an independent source term or a boundary phenomenon. Based on the obtained results, it can be very difficult to justify the use of isotropic assumptions to formulate particle population balances in similar systems, even when multiple compartment models are used to describe the fluid dynamic behaviour of the agitated vessel. (C) 2011 Canadian Society for Chemical Engineering

Long-Term Prospective Study of the Influence of Estrone Levels on Events in Postmenopausal Women with or at High Risk for Coronary Artery Disease

Background. The link between endogenous estrogen, coronary artery disease (CAD), and death in postmenopausal women is uncertain. We analyzed the association between death and blood levels of estrone in postmenopausal women with known coronary artery disease (CAD) or with a high-risk factor score for CAD. Methods. 251 postmenopausal women age 50-90 years not on estrogen therapy. Fasting blood for estrone and heart disease risk factors were collected at baseline. Women were grouped according to their estrone levels (<15 and >= 15 pg/mL). Fatal events were recorded after 5.8 perpendicular to 1.4 years of followup. Results. The Kaplan-Meier survival curve showed a significant trend (P = 0.039) of greater all-cause mortality in women with low estrone levels (< 15 pg/mL). Cox multivariate regression analysis model adjusted for body mass index, diabetes, dyslipidemia, family history, and estrone showed estrone (OR = 0.45; P = 0.038) as the only independent variable for all-cause mortality. Multivariate regression model adjusted for age, body mass index, hypertension, diabetes, dyslipidemia, family history, and estrone showed that only age (OR = 1.06; P = 0.017) was an independent predictor of all-cause mortality. Conclusions. Postmenopausal women with known CAD or with a high-risk factor score for CAD and low estrone levels (< 15 pg/mL) had increased all-cause mortality.

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.

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.

A Bayesian analysis of the Conway-Maxwell-Poisson cure rate model

The purpose of this paper is to develop a Bayesian analysis for the right-censored survival data when immune or cured individuals may be present in the population from which the data is taken. In our approach the number of competing causes of the event of interest follows the Conway-Maxwell-Poisson distribution which generalizes the Poisson distribution. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the proposed model. Also, some discussions on the model selection and an illustration with a real data set are considered.

Finite element analysis of bonded model Class I 'restorations' after shrinkage

Objectives. The C-Factor has been used widely to rationalize the changes in shrinkage stress occurring at the tooth/resin-composite interfaces. Experimentally, such stresses have been measured in a uniaxial direction between opposed parallel walls. The situation of adjoining cavity walls has been neglected. The aim was to investigate the hypothesis that: within stylized model rectangular cavities of constant volume and wall thickness, the interfacial shrinkage-stress at the adjoining cavity walls increases steadily as the C-Factor increases. Methods. Eight 3D-FEM restored Class I 'rectangular cavity' models were created by MSC.PATRAN/MSC.Marc, r2-2005 and subjected to 1% of shrinkage, while maintaining constant both the volume (20 mm(3)) and the wall thickness (2 mm), but varying the C-Factor (1.9-13.5). An adhesive contact between the composite and the teeth was incorporated. Polymerization shrinkage was simulated by analogy with thermal contraction. Principal stresses and strains were calculated. Peak values of maximum principal (MP) and maximum shear (MS) stresses from the different walls were displayed graphically as a function of C-Factor. The stress-peak association with C-Factor was evaluated by the Pearson correlation between the stress peak and the C-Factor. Results. The hypothesis was rejected: there was no clear increase of stress-peaks with C-Factor. The stress-peaks particularly expressed as MP and MS varied only slightly with increasing C-Factor. Lower stress-peaks were present at the pulpal floor in comparison to the stress at the axial walls. In general, MP and MS were similar when the axial wall dimensions were similar. The Pearson coefficient only expressed associations for the maximum principal stress at the ZX wall and the Z axis. Significance. Increase of the C-Factor did not lead to increase of the calculated stress-peaks in model rectangular Class I cavity walls. (C) 2011 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

Why Are Women With Cervical Cancer Not Being Diagnosed in Preinvasive Phase? An Analysis of Risk Factors Using a Hierarchical Model

Objective: To assess the risk factors for delayed diagnosis of uterine cervical lesions. Materials and Methods: This is a case-control study that recruited 178 women at 2 Brazilian hospitals. The cases (n = 74) were composed of women with a late diagnosis of a lesion in the uterine cervix (invasive carcinoma in any stage). The controls (n = 104) were composed of women with cervical lesions diagnosed early on (low-or high-grade intraepithelial lesions). The analysis was performed by means of logistic regression model using a hierarchical model. The socioeconomic and demographic variables were included at level I (distal). Level II (intermediate) included the personal and family antecedents and knowledge about the Papanicolaou test and human papillomavirus. Level III (proximal) encompassed the variables relating to individuals' care for their own health, gynecologic symptoms, and variables relating to access to the health care system. Results: The risk factors for late diagnosis of uterine cervical lesions were age older than 40 years (odds ratio [OR] = 10.4; 95% confidence interval [CI], 2.3-48.4), not knowing the difference between the Papanicolaou test and gynecological pelvic examinations (OR, = 2.5; 95% CI, 1.3-4.9), not thinking that the Papanicolaou test was important (odds ratio [OR], 4.2; 95% CI, 1.3-13.4), and abnormal vaginal bleeding (OR, 15.0; 95% CI, 6.5-35.0). Previous treatment for sexually transmissible disease was a protective factor (OR, 0.3; 95% CI, 0.1-0.8) for delayed diagnosis. Conclusions: Deficiencies in cervical cancer prevention programs in developing countries are not simply a matter of better provision and coverage of Papanicolaou tests. The misconception about the Papanicolaou test is a serious educational problem, as demonstrated by the present study.

Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)

Abstract Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.

The 3C cooperation model applied to the classical requirement analysis

Aspects related to the users' cooperative work are not considered in the traditional approach of software engineering, since the user is viewed independently of his/her workplace environment or group, with the individual model generalized to the study of collective behavior of all users. This work proposes a process for software requirements to address issues involving cooperative work in information systems that provide distributed coordination in the users' actions and the communication among them occurs indirectly through the data entered while using the software. To achieve this goal, this research uses ergonomics, the 3C cooperation model, awareness and software engineering concepts. Action-research is used as a research methodology applied in three cycles during the development of a corporate workflow system in a technological research company. This article discusses the third cycle, which corresponds to the process that deals with the refinement of the cooperative work requirements with the software in actual use in the workplace, where the inclusion of a computer system changes the users' workplace, from the face to face interaction to the interaction mediated by the software. The results showed that the highest degree of users' awareness about their activities and other system users contribute to a decrease in their errors and in the inappropriate use of the system.