Heritability analysis of surface-based cortical thickness estimation on a large twin cohort

The aim of this paper is to assess the heritability of cerebral cortex, based on measurements of grey matter (GM) thickness derived from structural MR images (sMRI). With data acquired from a large twin cohort (328 subjects), an automated method was used to estimate the cortical thickness, and EM-ICP surface registration algorithm was used to establish the correspondence of cortex across the population. An ACE model was then employed to compute the heritability of cortical thickness. Heritable cortical thickness measures various cortical regions, especially in frontal and parietal lobes, such as bilateral postcentral gyri, superior occipital gyri, superior parietal gyri, precuneus, the orbital part of the right frontal gyrus, right medial superior frontal gyrus, right middle occipital gyrus, right paracentral lobule, left precentral gyrus, and left dorsolateral superior frontal gyrus.

Performance estimation of streaming applications for hierarchical MPSoCs

Parallel programming and effective partitioning of applications for embedded many-core architectures requires optimization algorithms. However, these algorithms have to quickly evaluate thousands of different partitions. We present a fast performance estimator embedded in a parallelizing compiler for streaming applications. The estimator combines a single execution-based simulation and an analytic approach. Experimental results demonstrate that the estimator has a mean error of 2.6% and computes its estimation 2848 times faster compared to a cycle accurate simulator.

Bayesian estimation of small effects in exercise and sports science

The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a ‘magnitude-based inference’ approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements.

Does gender moderate the relationship between polydrug use and sexual risk-taking among Australian secondary school students under 16 years of age?

Introduction and Aims This study examines the association of alcohol and polydrug use with risky sexual behaviour in adolescents under 16 years of age and if this association differs by gender. Design and Methods The sample consisted of 5412 secondary school students under 16 years of age from Victoria, Australia. Participants completed an anonymous and confidential survey during class time. The key measures were having had sex before legal age of consent (16 years), unprotected sex before 16 (no condom) and latent-class derived alcohol and polydrug use variables based on alcohol, tobacco, cannabis, inhalants and other illegal drug use in the past month. Results There were 7.52% and 2.55% of adolescents who reported having sex and having unprotected sex before 16 years of age, respectively. After adjusting for antisocial behaviours, peers' drug use and family and school risk factors, girls were less likely to have unprotected sex (odds ratio = 0.31, P = 0.003). However, the interaction of being female and polydrug use (odds ratio = 4.52, P = 0.004) was significant, indicating that girls who engaged in polydrug use were at higher risk of having unprotected sex. For boys, the effect of polydrug use was non-significant (odds ratio = 1.44, P = 0.310). Discussion and Conclusions For girls, polydrug use was significantly associated with unprotected sex after adjusting for a range of risk factors, and this relationship was non-significant for boys. Future prevention programs for adolescent risky sexual behaviour and polydrug use might benefit from a tailored approach to gender differences.

ACE Research Vignette 051: How and Why is Small Business Managers’ Age Related To Business Growth?

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international entrepreneurship researchers. This vignette, written by Professor Hannes Zacher, Professor Michael M. Gielnik and Dr Antje Schmitt, reports findings on relationships between small business managers’ age, their focus on opportunities, and business growth (sales and number of employees) over five years.

How small business managers’ age and focus on opportunities affect business growth: A mediated moderation growth model

Research on business growth has been criticized for methodological weaknesses. We present a mediated moderation growth model as a new methodological approach. We hypothesized that small business managers' age negatively affects business growth through focus on opportunities. We sampled 201 small business managers and obtained firm performance data over 5 years, resulting in 836 observations. Growth modeling showed systematic differences in firm performance trajectories. These differences could be explained by modeling focus on opportunities as a mediator of the relationship between small business managers' age and business growth. The study illustrates how mediation models can be tested using growth modeling.