968 resultados para external hazard index


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Densities ([rho]) and viscosities ([eta]) of binary mixtures containing the Protic Ionic Liquid (PIL), pyrrolidinium octanoate with five molecular solvents: water, methanol, ethanol, n-butanol, and acetonitrile are determined at the atmospheric pressure as a function of the temperature and within the whole composition range. The refractive index of all mixtures (nD) is measured at 298.15†K. The excess molar volumes VE and deviation from additivity rules of viscosities [eta]E and refractive index [Delta][phi]n, of pyrrolidinium octanoate solutions were then deduced from the experimental results as well as apparent molar volumes V[phi]i, partial molar volumes and thermal expansion coefficients [alpha]p. The excess molar volumes VE are negative over the entire mole fraction range for mixture with water, acetonitrile, and methanol indicating strong hydrogen-bonding interaction for the entire mole fraction. In the case of longest carbon chain alcohols (such as ethanol and n-butanol)†+†pyrrolidinium octanoate solutions, the VE variation as a function of the composition describes an S shape. The deviation from additivity rules of viscosities is negative over the entire composition range for the acetonitrile, methanol, ethanol, and butanol, and becomes less negative with increasing temperature. Whereas, [eta]E of the {[Pyrr][C7CO2]†+†water} binary mixtures is positive in the whole mole fraction range and decreases with increasing temperature. the excess Gibbs free energies of activation of viscous flow ([Delta]G*E) for these systems were calculated. The deviation from additivity rules of refractive index [Delta][phi]n are positive over the whole composition range and approach a maximum of 0.25 in PIL mole fraction for all systems. The magnitude of deviation for [Delta][phi]n describes the following order: water†>†methanol†>†acetonitrile†>†ethanol. Results have been discussed in terms of molecular interactions and molecular structures in these binary mixtures.

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Objectives. We investigated whether exposure to negative aspects of close relationships was associated with subsequent increase in body mass index (BMI) and waist circumference.
Methods. Data came from a prospective cohort study (Whitehall II) of 9425 civil servants aged 35 to 55 years at baseline (phase 1: 1985-1988). We assessed negative aspects of close relationships with the Close Persons Questionnaire (range 0-12) at phases 1 and 2 (1989-1990). We measured BMI and waist circumference at phases 3 (1991-1994) and 5 (1997-1999). Covariates at phase 1 included gender, age, marital status, ethnicity, BMI, employment grade, smoking, physical activity, fruit and vegetable consumption, and common mental disorder.
Results. After adjustment for sociodemographic characteristics and health behaviors, participants with higher exposure to negative aspects of close relationships had a higher likelihood of a 10% or greater increase in BMI and waist circumference (odds ratios per 1-unit increase 1.08 [95% confidence interval (CI)=1.02, 1.14; P=.007] and 1.09 [CI=1.04, 1.14; P <= .001], respectively) as well as a transition from the overweight (25 <= BMI <30) to the obese (BMI >= 30) category.
Conclusions. Adverse social relationships may contribute to weight gain.

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A scheme employing an external axial magnetic field is proposed to diagnose the intrinsic divergence of laser-generated fast electron beams, and this is studied numerically with hybrid simulations. The maximum beam radius of fast electrons increases with the initial divergence and decreases with the amplitude of the axial magnetic field. It is indicated that the intrinsic divergence of fast electrons can be inferred from measurements of the beam radius at different depth under the axial field. The proposed scheme here may be useful for future fast ignition experiments and in other applications of laser-generated fast electron beams. (C) 2011 American Institute of Physics. [doi:10.1063/1.3630925]

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Objective: The proportion of overweight and obese people has grown rapidly, and obesity has now been widely recognized as an important public health problem. At the came time, stress has increased in working life. The 2 problems could be connected if work stress promotes unhealthy eating habits and sedentary behavior and thereby contributes to weight gain. This study explored the association between work stress and body mass index (BMI; kg/m(2)). Methods: We used cross-sectional questionnaire data obtained from 45,810 female and male employees participating in the ongoing Finnish Public Sector Cohort Study. We constructed individual-level scores, as well as occupational- and organizational-level aggregated scores for work stress, as indicated by the demand/control model and the effort-reward imbalance model. Linear regression analyses were stratified by sex and socioeconomic status (SES) and adjusted for age, marital status, job contract, smoking, alcohol consumption, physical activity, and negative affectivity. Results: The results with the aggregated scores showed that lower job control, higher job strain, and higher effort-reward imbalance were associated with a higher BMI. In men, lower job demands were also associated with a higher BMI. These associations were not accounted for by SES, although an additional adjustment for SES attenuated the associations. The results obtained with the individual-level scores were in the same direction, but the relationships were weaker than those obtained with the aggregated scores. Conclusions: This study shows a weak association between work stress and BMI.

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The aim of our study was to investigate whether intakes of total fat and fat subtypes were associated with esophageal adenocarcinoma (EAC), esophageal squamous cell carcinoma (ESCC), gastric cardia or gastric noncardia adenocarcinoma. From 1995–1996, dietary intake data was reported by 494,978 participants of the NIH-AARP cohort. The 630 EAC, 215 ESCC, 454 gastric cardia and 501 gastric noncardia adenocarcinomas accrued to the cohort. Cox proportional hazards regression was used to examine the association between the dietary fat intakes, whilst adjusting for potential confounders. Although apparent associations were observed in energy-adjusted models, multivariate adjustment attenuated results to null [e.g., EAC energy adjusted hazard ratio (HR) and 95% confidence interval (95% CI) 1.66 (1.27–2.18) p for trend <0.01; EAC multivariate adjusted HR (95% CI) 1.17 (0.84–1.64) p for trend 5 0.58]. Similar patterns were also observed for fat subtypes [e.g., EAC saturated fat, energy adjusted HR (95% CI) 1.79 (1.37–2.33) p for trend <0.01; EAC saturated fat, multivariate adjusted HR (95% CI) 1.27 (0.91–1.78) p for trend 5 0.28]. However, in multivariate models an inverse association for polyunsaturated fat (continuous) was seen for EAC in subjects with a body mass index (BMI) in the normal range (18.5–<25 kg/m2) [HR (95% CI) 0.76 (0.63–0.92)], that was not present in overweight subjects [HR (95% CI) 1.04 (0.96–1.14)], or in unstratified analysis [HR (95% CI) 0.97 (0.90–1.05)]. p for interaction 5 0.02. Overall, we found null associations between the dietary fat intakes with esophageal or gastric cancer risk; although a protective effect of polyunsaturated fat intake was seen for EAC in subjects with a normal BMI.