Occupational skill level and hazardous exposures among working Victorians

This paper examines the patterning of exposures to occupational hazards in relation to occupational skill level as a proxy for pay rate, testing the general hypothesis that exposures to occupational hazards increase in prevalence with decreasing skill level. A population-based telephone survey was conducted on a random sample of working Victorians (N = 1,101). A set of 10 indicators of exposure to occupational hazards were analysed individually and as a summary scale in multivariate regression models. A significant increasing trend in hazardous working conditions from the highest to lowest occupational skill level was observed, with those in lower skill level jobs twice as likely to be exposed as those at the highest skill level. This overall trend was driven primarily by higher exposure in the middle skill level group (technicians and skilled trades) as well as the lowest (labourers and elementary clerical), the two main bluecollar groups. Findings provided partial support for the hypothesised relationship.

Experiences of racism, racial/ethnic attitudes, motivated fairness and mental health outcomes among primary and secondary school students

While studies investigating the health effects of racial discrimination for children and youth have examined a range of effect modifiers, to date, relationships between experiences of racial discrimination, student attitudes, and health outcomes remain unexplored. This study uniquely demonstrates the moderating effects of vicarious racism and motivated fairness on the association between direct experiences of racism and mental health outcomes, specifically depressive symptoms and loneliness, among primary and secondary school students. Across seven schools, 263 students (54.4% female), ranging from 8 to 17 years old (M = 11.2, SD = 2.2) reported attitudes about other racial/ethnic groups and experiences of racism. Students from minority ethnic groups (determined by country of birth) reported higher levels of loneliness and more racist experiences relative to the majority group students. Students from the majority racial/ethnic group reported higher levels of loneliness and depressive symptoms if they had more friends from different racial/ethnic groups, whereas the number of friends from different groups had no effect on minority students' loneliness or depressive symptoms. Direct experiences of racism were robustly related to higher loneliness and depressive symptoms in multivariate regression models. However, the association with depressive symptoms was reduced to marginal significance when students reported low motivated fairness. Elaborating on the negative health effects of racism in primary and secondary school students provides an impetus for future research and the development of appropriate interventions.

Among- and within-individual correlations between basal and maximal metabolic rates in birds

The aerobic capacity model proposes that endothermy is a by-product of selection favouring high maximal metabolic rates (MMR) and its mechanistic coupling with basal metabolic rate (BMR). Attempts to validate this model in birds are equivocal and restricted to phenotypic correlations (rP), thus failing to distinguish among- and within-individual correlations (rind and re). We examined 300 paired measurements of BMR and MMR from 60 house sparrows before and after two levels of experimental manipulation - testosterone implants and immune challenge. Overall, repeatability was significant in both BMR (R=0.25±0.06) and MMR (R=0.52±0.06). Only the testosterone treatment altered the rP between BMR and MMR, which resulted from contrasting effects on rind and re. While rind was high and significant (0.62±0.22) in sham-implanted birds, re was negative and marginally non-significant (-0.15±0.09) in testosterone-treated birds. Thus, the expected mechanistic link between BMR and MMR was apparent, but only in birds with low testosterone levels.

Clustering of diet, physical activity and sedentary behaviour among Australian children: cross-sectional and longitudinal associations with overweight and obesity

BACKGROUND/OBJECTIVES: Evidence suggests diet, physical activity (PA) and sedentary behaviour cluster together in children, but research supporting an association with overweight/obesity is equivocal. Furthermore, the stability of clusters over time is unknown. The aim of this study was to examine the clustering of diet, PA and sedentary behaviour in Australian children and cross-sectional and longitudinal associations with overweight/obesity. Stability of obesity-related clusters over 3-years was also examined. SUBJECTS/METHODS: Data were drawn from the baseline (T1: 2002/03) and follow-up waves (T2: 2005/06) of the Health Eating and Play Study. Parents of Australian children aged 5-6 (n=87) and 10-12 years (n=123) completed questionnaires. Children wore accelerometers and height and weight were measured. Obesity-related clusters were determined using K-medians cluster analysis. Multivariate regression models assessed cross-sectional and longitudinal associations between cluster membership, and BMI z-score and weight status. Kappa statistics assessed cluster stability over time. RESULTS: Three clusters, labelled 'most Healthy', 'Energy-dense (ED) consumers who watch TV' and 'high sedentary behaviour/low moderate-to-vigorous physical activity' were identified at baseline and at follow-up. No cross-sectional associations were found between cluster membership, and BMI z-score or weight status at baseline. Longitudinally, children in the 'ED consumers who watch TV' cluster had a higher odds of being overweight/obese at follow-up (OR=2.8; 95% CI: 1.1, 6.9; P<0.05). Tracking of cluster membership was fair to moderate in younger (K=0.24; P=0.0001) and older children (K=0.46; P<0.0001). CONCLUSIONS: This study identified an unhealthy cluster of TV viewing with ED food/drink consumption which predicted overweight/obesity in a small longitudinal sample of Australian children. Cluster stability was fair to moderate over three years and is a novel finding. Prospective research in larger samples is needed to examine how obesity-related clusters track over time and influence the development of overweight and obesity.International Journal of Obesity accepted article preview online, 24 April 2015. doi:10.1038/ijo.2015.66.

Life satisfaction and morbidity among postmenopausal women

OBJECTIVE: To investigate associations between morbidity and global life satisfaction in postmenopausal women taking into account type and number of diseases.

MATERIALS AND METHODS: A total of 11,084 women (age range 57-66 years) from a population-based cohort of Finnish women (OSTPRE Study) responded to a postal enquiry in 1999. Life satisfaction was measured with a 4-item scale. Self-reported diseases diagnosed by a physician and categorized according to ICD-10 main classes were used as a measure of morbidity. Enquiry data on health and lifestyle were used as covariates in the multivariate logistic models.

RESULTS: Morbidity was strongly associated with life dissatisfaction. Every additional disease increased the risk of life dissatisfaction by 21.1% (p < .001). The risk of dissatisfaction was strongest among women with mental disorders (OR = 5.26; 95%CI 3.84-7.20) and neurological disorders (OR = 3.62; 95%CI 2.60-5.02) compared to the healthy (each p < .001). Smoking, physical inactivity and marital status were also associated with life dissatisfaction (each p < .001) but their introduction to the multivariate model did not attenuate the pattern of associations.

CONCLUSIONS: Morbidity and life dissatisfaction have a disease-specific and dose-dependent relationship. Even if women with mental and neurological disorders have the highest risk for life dissatisfaction, monitoring life satisfaction among aging women regardless of disorders should be undertaken in order to intervene the joint adverse effects of poor health and poor well-being.

Modelando a volatilidade dos retornos de Petrobrás usando dados de alta frequência

O objetivo do presente trabalho é analisar as características empíricas de uma série de retornos de dados em alta freqüência para um dos ativos mais negociados na Bolsa de Valores de São Paulo. Estamos interessados em modelar a volatilidade condicional destes retornos, testando em particular a presença de memória longa, entre outros fenômenos que caracterizam este tipo de dados. Nossa investigação revela que além da memória longa, existe forte sazonalidade intradiária, mas não encontramos evidências de um fato estilizado de retornos de ações, o efeito alavancagem. Utilizamos modelos capazes de captar a memória longa na variância condicional dos retornos dessazonalizados, com resultados superiores a modelos tradicionais de memória curta, com implicações importantes para precificação de opções e de risco de mercado

Modelo de volatilidade estocástica com saltos aplicado a commodities agrícolas

Mensalmente são publicados relatórios pelo Departamento de Agricultura dos Estados Unidos (USDA) onde são divulgados dados de condições das safras, oferta e demanda globais, nível dos estoques, que servem como referência para todos os participantes do mercado de commodities agrícolas. Esse mercado apresenta uma volatilidade acentuada no período de divulgação dos relatórios. Um modelo de volatilidade estocástica com saltos é utilizado para a dinâmica de preços de milho e de soja. Não existe um modelo ‘ideal’ para tal fim, cada um dos existentes têm suas vantagens e desvantagens. O modelo escolhido foi o de Oztukel e Wilmott (1998), que é um modelo de volatilidade estocástica empírica, incrementado com saltos determinísticos. Empiricamente foi demonstrado que um modelo de volatilidade estocástica pode ser bem ajustado ao mercado de commodities, e o processo de jump-diffusion pode representar bem os saltos que o mercado apresenta durante a divulgação dos relatórios. As opções de commodities agrícolas que são negociadas em bolsa são do tipo americanas, então alguns métodos disponíveis poderiam ser utilizados para precificar opções seguindo a dinâmica do modelo proposto. Dado que o modelo escolhido é um modelo multi-fatores, então o método apropriado para a precificação é o proposto por Longstaff e Schwartz (2001) chamado de Monte Carlo por mínimos quadrados (LSM). As opções precificadas pelo modelo são utilizadas em uma estratégia de hedge de uma posição física de milho e de soja, e a eficiência dessa estratégia é comparada com estratégias utilizando-se instrumentos disponíveis no mercado.

Eficiência e razão de hedge: uma análise dos mercados futuro brasileiros de boi, café, etanol, milho e soja

This research aims to investigate the Hedge Efficiency and Optimal Hedge Ratio for the future market of cattle, coffee, ethanol, corn and soybean. This paper uses the Optimal Hedge Ratio and Hedge Effectiveness through multivariate GARCH models with error correction, attempting to the possible phenomenon of Optimal Hedge Ratio differential during the crop and intercrop period. The Optimal Hedge Ratio must be bigger in the intercrop period due to the uncertainty related to a possible supply shock (LAZZARINI, 2010). Among the future contracts studied in this research, the coffee, ethanol and soybean contracts were not object of this phenomenon investigation, yet. Furthermore, the corn and ethanol contracts were not object of researches which deal with Dynamic Hedging Strategy. This paper distinguishes itself for including the GARCH model with error correction, which it was never considered when the possible Optimal Hedge Ratio differential during the crop and intercrop period were investigated. The commodities quotation were used as future price in the market future of BM&FBOVESPA and as spot market, the CEPEA index, in the period from May 2010 to June 2013 to cattle, coffee, ethanol and corn, and to August 2012 to soybean, with daily frequency. Similar results were achieved for all the commodities. There is a long term relationship among the spot market and future market, bicausality and the spot market and future market of cattle, coffee, ethanol and corn, and unicausality of the future price of soybean on spot price. The Optimal Hedge Ratio was estimated from three different strategies: linear regression by MQO, BEKK-GARCH diagonal model, and BEKK-GARCH diagonal with intercrop dummy. The MQO regression model, pointed out the Hedge inefficiency, taking into consideration that the Optimal Hedge presented was too low. The second model represents the strategy of dynamic hedge, which collected time variations in the Optimal Hedge. The last Hedge strategy did not detect Optimal Hedge Ratio differential between the crop and intercrop period, therefore, unlikely what they expected, the investor do not need increase his/her investment in the future market during the intercrop

Genetic associations between carcass traits measured by real-time ultrasound and scrotal circumference and growth traits in Nelore cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Associações genéticas entre pesos e características reprodutivas em rebanhos da raça Nelore

Dados de 14.918 animais da raça Nelore nascidos entre 1991 e 2000, provenientes de rebanhos localizados nas regiões Sul e Sudeste do País, foram utilizados para estimar componentes de co-variância, herdabilidade e correlações genéticas de peso ao desmame (PD), peso a 1 ano de idade (PA), peso ao sobreano (PS), peso ao primeiro parto (PPP), idade ao primeiro parto (IPP) e dias para o primeiro parto (DP). As estimativas dos componentes de co-variância e dos parâmetros genéticos foram obtidas pelo método de máxima verossimilhança restrita, em análises multivariadas. As herdabilidades estimadas para PD, PA, PS, PPP, IPP e DP foram de 0,26; 0,30; 0,34; 0,35; 0,14 e 0,07, respectivamente. Correlações genéticas negativas foram estimadas entre pesos medidos em diferentes idades e IPP, as quais variaram de -0,31 a -0,16. do mesmo modo, as estimativas de correlação genética entre PD × DP (-0,09); PA × DP (-0,13); PS × DP (-0,17) e PPP × DP (-0,16) foram negativas, embora de menor magnitude. As correlações genéticas estimadas entre as características de crescimento e a IPP foram favoráveis. Assim, a seleção para aumento de peso deve promover redução da IPP. A alta correlação genética estimada entre IPP e DP (0,73) indica que o uso de DP na seleção de bovinos de corte pode promover resposta correlacionada favorável na idade ao primeiro parto.

Determinação do teor de diclofenaco sódico em comprimidos por espectroscopia no infravermelho próximo NIR com calibração multivariada PLS

This work is combined with the potential of the technique of near infrared spectroscopy - NIR and chemometrics order to determine the content of diclofenac tablets, without destruction of the sample, to which was used as the reference method, ultraviolet spectroscopy, which is one of the official methods. In the construction of multivariate calibration models has been studied several types of pre-processing of NIR spectral data, such as scatter correction, first derivative. The regression method used in the construction of calibration models is the PLS (partial least squares) using NIR spectroscopic data of a set of 90 tablets were divided into two sets (calibration and prediction). 54 were used in the calibration samples and the prediction was used 36, since the calibration method used was crossvalidation method (full cross-validation) that eliminates the need for a validation set. The evaluation of the models was done by observing the values of correlation coefficient R 2 and RMSEC mean square error (calibration error) and RMSEP (forecast error). As the forecast values estimated for the remaining 36 samples, which the results were consistent with the values obtained by UV spectroscopy

Espectroscopia no infravermelho próximo e métodos de calibração multivariada aplicados à determinação simultânea de parâmetros bioquímicos em plasma sanguíneo

In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma

Thermophysical properties of mango pulp (Mangifera indica L. cv. Tommy Atkins)

The density, heat capacity and thermal conductivity of mango pulp (Mangifera indica L. cv. Tommy Atkins) were determined at moisture contents of between 0.9 and 0.52 kg kg(-1) (w.b.) and temperatures of between 20 and 80 degrees C. The experimental data were satisfactorily fitted (explained variation values >99.1%) as functions of the moisture content and temperature by using multivariate linear models. In the range of conditions considered, the moisture content exhibits a greater influence on the studied properties than temperature. (C) 2009 Elsevier Ltd. All rights reserved.

Microscopic origin of non-Gaussian distributions of financial returns

In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.