A sexual dimorphism exists in the incidence and prevalence of coronary artery disease--men are more commonly affected than are age-matched women. We explored the role of the Y chromosome in coronary artery disease in the context of this sexual inequity. We genotyped 11 markers of the male-specific region of the Y chromosome in 3233 biologically unrelated British men from three cohorts: the British Heart Foundation Family Heart Study (BHF-FHS), West of Scotland Coronary Prevention Study (WOSCOPS), and Cardiogenics Study. On the basis of this information, each Y chromosome was tracked back into one of 13 ancient lineages defined as haplogroups. We then examined associations between common Y chromosome haplogroups and the risk of coronary artery disease in cross-sectional BHF-FHS and prospective WOSCOPS. Finally, we undertook functional analysis of Y chromosome effects on monocyte and macrophage transcriptome in British men from the Cardiogenics Study. Of nine haplogroups identified, two (R1b1b2 and I) accounted for roughly 90% of the Y chromosome variants among British men. Carriers of haplogroup I had about a 50% higher age-adjusted risk of coronary artery disease than did men with other Y chromosome lineages in BHF-FHS (odds ratio 1·75, 95% CI 1·20-2·54, p=0·004), WOSCOPS (1·45, 1·08-1·95, p=0·012), and joint analysis of both populations (1·56, 1·24-1·97, p=0·0002). The association between haplogroup I and increased risk of coronary artery disease was independent of traditional cardiovascular and socioeconomic risk factors. Analysis of macrophage transcriptome in the Cardiogenics Study revealed that 19 molecular pathways showing strong differential expression between men with haplogroup I and other lineages of the Y chromosome were interconnected by common genes related to inflammation and immunity, and that some of them have a strong relevance to atherosclerosis. The human Y chromosome is associated with risk of coronary artery disease in men of European ancestry, possibly through interactions of immunity and inflammation. British Heart Foundation; UK National Institute for Health Research; LEW Carty Charitable Fund; National Health and Medical Research Council of Australia; European Union 6th Framework Programme; Wellcome Trust.

Financial status is thought to be an important determinant of psychological well-being. We investigate this relationship, and the effect of other factors, using a parametric mixed modelling approach for panel data, controlling the problem of unobservable heterogeneity. Two nationally representative surveys, the British Household Panel Survey (BHPS) and the Understanding Society Survey (USS), were used to construct a unified data set which measured psychological well-being and associated factors using the 12-item General Health Questionnaire (GHQ-12). The GHQ-12 score for the head of the household was used as the dependant variable and its relationship with multiple independent demographic and financial status variables was investigated. Following assessment of growth curve characteristics with linear, curvilinear and higher-order polynomial modelling; several variance-covariance structures were tested to assess the error covariance structure of the longitudinal data. The random intercept and random slope were allowed to vary across participants, and methods such as natural splines and B-splines were used to improve the fit of some variables. Our final model demonstrated the most important variables affecting self-reported psychological well-being, as determined by GHQ-12, were perception and expectation of future financial situation and problems meeting household expenditure. Gender, age, marital status, number of children at home, highest qualification and job status were also significantly implicated. Unlike previous studies however we did not find that size of income was significant. These results provide further strong evidence of the impact that financial concerns have on self-reported measures of psychological well-being.

The prediction of the drilling rate of penetration (ROP) is one of the key aspects of drilling optimization due to its significant role in reducing expensive drilling costs. Many variables could affect ROP, which can be classified into two general categories; controllable operational variables and uncontrollable or environmental variables. Minimizing the drilling cost can be achieved through optimizing the controllable drilling parameters. As a direct result, the drilling speed will be increased while maintaining safe practices. The primary purpose of this study is to address the simultaneous impact of controllable parameters such as weight on bit (WOB), revolutions per minute, and flow rate (FR) on the rate of penetration (ROP). Response surface methodology was applied to develop a mathematical relation between operational controllable drilling parameters and ROP. To accomplish this, actual field datasets from several wells drilled in Southern Iraq in different fields were used. The second purpose of this study was to identify all prospective optimal ranges of these controllable parameters to obtain superior drilling performance with an optimum ROP. The obtained results showed that the developed model offers a cost-effective tool for determining the maximum ROP as a function of controllable parameters with reasonable accuracy. In addition, the proposed model was used to estimate optimal combinations of controllable drilling parameters for various depths. The results have shown that FR has the most significant effect on ROP variation with a sum of squares values of 23.47. Applying high WOB does not permanently improve ROP but could result in reducing ROP for some cases. The developed mechanical specific energy model for polycrystalline diamond compact (PDC) bit with vertical and deviated wells can estimate combinations of controllable drilling parameters. The developed model can be successfully applied to predict and optimize the drilling rate when using PDC bits, hence reducing the drilling time and the associated drilling cost for future wells.

In this paper, a robust extreme ranked set sampling (RERSS) procedure for estimating the population mean is introduced. It is shown that the proposed method gives an unbiased estimator with smaller variance, provided the underlying distribution is symmetric. However, for asymmetric distributions a weighted mean is given, where the optimal weights are computed by using Shannon's entropy. The performance of the population mean estimator is discussed along with its properties. Monte Carlo simulations are used to demonstrate the performance of the RERSS estimator relative to the simple random sample (SRS), ranked set sampling (RSS) and extreme ranked set sampling (ERSS) estimators. The results indicate that the proposed estimator is more efficient than the estimators based on the traditional sampling methods.