The on-road experiences and awareness of sleepiness in a sample of Australian highway drivers: A roadside driver sleepiness study

Objective Driver sleepiness contributes substantially to road crash incidents. Simulator and on-road studies clearly reveal an impairing effect from sleepiness on driving ability. However, the degree to which drivers appreciate the dangerousness of driving while sleepy is somewhat unclear. This study sought to determine drivers’ on-road experiences of sleepiness, their prior sleep habits, and personal awareness of the signs of sleepiness. Methods Participants were a random selection of 92 drivers travelling on a major highway in the state of Queensland, Australia, who were stopped by police as part of routine drink driving operations. Participants completed a brief questionnaire that included demographic information, sleepy driving experiences (signs of sleepiness and on-road experiences of sleepiness), and prior sleep habits. A modified version of the Karolinska Sleepiness Scale (KSS) was used to assess subjective sleepiness in the 15 minutes prior to being stopped by police. Results Participants rating of subjective sleepiness were quite low, with 90% reporting being alert to extremely alert on the KSS. Participants were reasonably aware of the signs of sleepiness, with many signs of sleepiness associated with on-road experiences of sleepiness. Additionally, the number of hours spent driving was positively correlated with the drivers’ level of sleep debt. Conclusions The results suggest the participants had moderate experience of driving while sleepy and many were aware of the signs of sleepiness. The relationship between driving long distances and increased sleep debt is a concern for road safety – increased education regarding the dangers of sleepy driving seems warranted.

Genetic analyses in a sample of individuals with high or low BMD shows association with multiple Wnt pathway genes

INTRODUCTION Although the high heritability of BMD variation has long been established, few genes have been conclusively shown to affect the variation of BMD in the general population. Extreme truncate selection has been proposed as a more powerful alternative to unselected cohort designs in quantitative trait association studies. We sought to test these theoretical predictions in studies of the bone densitometry measures BMD, BMC, and femoral neck area, by investigating their association with members of the Wnt pathway, some of which have previously been shown to be associated with BMD in much larger cohorts, in a moderate-sized extreme truncate selected cohort (absolute value BMD Z-scores = 1.5-4.0; n = 344). MATERIALS AND METHODS Ninety-six tag-single nucleotide polymorphism (SNPs) lying in 13 Wnt signaling pathway genes were selected to tag common genetic variation (minor allele frequency [MAF] > 5% with an r(2) > 0.8) within 5 kb of all exons of 13 Wnt signaling pathway genes. The genes studied included LRP1, LRP5, LRP6, Wnt3a, Wnt7b, Wnt10b, SFRP1, SFRP2, DKK1, DKK2, FZD7, WISP3, and SOST. Three hundred forty-four cases with either high or low BMD were genotyped by Illumina Goldengate microarray SNP genotyping methods. Association was tested either by Cochrane-Armitage test for dichotomous variables or by linear regression for quantitative traits. RESULTS Strong association was shown with LRP5, polymorphisms of which have previously been shown to influence total hip BMD (minimum p = 0.0006). In addition, polymorphisms of the Wnt antagonist, SFRP1, were significantly associated with BMD and BMC (minimum p = 0.00042). Previously reported associations of LRP1, LRP6, and SOST with BMD were confirmed. Two other Wnt pathway genes, Wnt3a and DKK2, also showed nominal association with BMD. CONCLUSIONS This study shows that polymorphisms of multiple members of the Wnt pathway are associated with BMD variation. Furthermore, this study shows in a practical trial that study designs involving extreme truncate selection and moderate sample sizes can robustly identify genes of relevant effect sizes involved in BMD variation in the general population. This has implications for the design of future genome-wide studies of quantitative bone phenotypes relevant to osteoporosis.

Model selection with misspecified spatial covariance structure

Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.

Modeling strategies in longitudinal data analysis: Covariate, variance function and correlation structure selection

A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.

Sexual selection in a tropical fruit fly : role of a plant derived chemical in mate choice

The specific mechanisms by which selective pressures affect individuals are often difficult to resolve. In tephritid fruit flies, males respond strongly and positively to certain plant derived chemicals. Sexual selection by female choice has been hypothesized as the mechanism driving this behaviour in certain species, as females preferentially mate with males that have fed on these chemicals. This hypothesis is, to date, based on studies of only very few species and its generality is largely untested. We tested the hypothesis on different spatial scales (small cage and seminatural field-cage) using the monophagous fruit fly, Bactrocera cacuminata. This species is known to respond to methyl eugenol (ME), a chemical found in many plant species and one upon which previous studies have focused. Contrary to expectation, no obvious female choice was apparent in selecting ME-fed males over unfed males as measured by the number of matings achieved over time, copulation duration, or time of copulation initiation. However, the number of matings achieved by ME-fed males was significantly greater than unfed males 16 and 32 days after exposure to ME in small cages (but not in a field-cage). This delayed advantage suggests that ME may not influence the pheromone system of B. cacuminata but may have other consequences, acting on some other fitness consequence (e.g., enhancement of physiology or survival) of male exposure to these chemicals. We discuss the ecological and evolutionary implications of our findings to explore alternate hypotheses to explain the patterns of response of dacine fruit flies to specific plant-derived chemicals.

Raman spectroscopic study of vivianites of different origins

Raman spectroscopy has been used to study a selection of vivianites from different origins. A band is identified at around 3480 cm-1 whose intensity is sample dependent. The band is attributed to the stretching vibration of Fe3+ OH units which are formed through the autooxidation of the vivianite minerals either by self-oxidation or by photocatalytic oxidation according to the reaction: (Fe2+)3(PO4)2·8H2O + 1/2O2 (Fe2+)3– x(Fe3+)x(PO4)2(OH)x·(8–x)H2O in which some of the water of crystallization is converted to hydroxyl anions. Complexity of the OH stretching region through the overlap of broad bands is reflected in the water HOH deformation modes at 1660 cm–1. Using the infrared bands at 3281, 3105 and 3025 cm–1, hydrogen bond distances of 2.734(5), 2.675(2) and 2.655(2) Å are calculated. Vivianites are characterised by an intense band at 950 cm–1 assigned to the PO4 symmetric stretching vibration. Low Raman intensity bands are observed at ~1077, ~1050, 1015 and ~ 985 cm–1 assigned to the phosphate PO4 antisymmetric stretching vibrations. Multiple antisymmetric stretching vibrations are due to the reduced tetrahedral symmetry. This loss of degeneracy is also reflected in the bending modes. Two bands are observed at ~ 423 and ~ 456 cm–1 assigned to the2bending modes. For the vivianites four bands are observed at ~ 584, ~ 571, ~ 545 and ~ 525 cm–1 assigned to the 4modes of vivianite.