Muon capture by 3He nuclei followed by proton and deuteron production

The paper describes an experiment aimed at studying muon capture by ${}^{3}\mathrm{He}$ nuclei in pure ${}^{3}\mathrm{He}$ and $\mathrm{D}_2 + {}^{3}\mathrm{He}$ mixtures at various densities. Energy distributions of protons and deuterons produced via $\mu^-+{}^{3}\mathrm{He}\to p+n+n + \nu_{\mu }$ and $\mu^-+{}^{3} \mathrm{He} \to d+n + \nu_{\mu}$ are measured for the energy intervals $10 - 49$ MeV and $13 - 31$ MeV, respectively. Muon capture rates, $\lambda_\mathrm{cap}^p (\Delta E_p)$ and $\lambda_\mathrm{cap}^d (\Delta E_d)$ are obtained using two different analysis methods. The least--squares methods gives $\lambda_\mathrm{cap}^p = (36.7\pm 1.2) {s}^{- 1}$, $\lambda_\mathrm{cap}^d = (21.3 \pm 1.6) {s}^{- 1}$. The Bayes theorem gives $\lambda_\mathrm{cap}^p = (36.8 \pm 0.8) {s}^{- 1}$, $\lambda_\mathrm{cap}^d = (21.9 \pm 0.6) {s}^{- 1}$. The experimental differential capture rates, $d\lambda_\mathrm{cap}^p (E_p) / dE_p$ and $d\lambda_\mathrm{cap}^d (E_d) / dE_d$, are compared with theoretical calculations performed using the plane--wave impulse approximation (PWIA) with the realistic NN interaction Bonn B potential. Extrapolation to the full energy range yields total proton and deuteron capture rates in good agreement with former results.Comment: 17 pages, 13 figures, accepted for publication in PR

Self-persuasion as marketing technique: the role of consumers’ involvement

Purpose This paper aims to demonstrate that self-persuasion can be used as a marketing technique to increase consumers’ generosity and that the efficacy of this approach is dependent on consumers’ involvement with target behavior. Design/methodology/approach An experimental field-study was conducted to investigate the effects of self-persuasion versus direct persuasion attempts versus no persuasion attempts on consumers’ tipping behavior in a lunchroom. Additionally, in a lab experiment, the moderating role of involvement on self-persuasion versus direct persuasion was tested. Findings The results reveal that self-persuasion is more effective than direct persuasion attempts or no persuasive messages in increasing consumers’ generosity. This is moderated by consumers’ involvement with the target behavior. For consumers with high involvement, self-persuasion is more effective than direct persuasion, while no differences were found for consumers with moderate or low involvement. Practical implications The scope of self-persuasion is not limited to the inhibition of undesired behavior, but it also extends to the facilitation of desired behavior, which considerably broadens the scope of this technique. Self-persuasion might be used as a marketing technique to influence consumers’ purchase behavior. This might be particularly viable in situations in which consumers feel high involvement with products or behavior. Originality/value Recently, research in health psychology demonstrated that self-persuasion is a very effective way of inhibiting undesired, addictive behavior and being more successful than direct persuasion. Yet, insufficient knowledge is available about the efficacy of self-persuasion with regard to promoting other target behaviors. In particular, its potential as a marketing technique to influence consumers’ behavior and its boundary conditions are still understudied

Tenure, gender and household structure

Starting with a review of recent literature on gender and housing, this paper goes on to develop a new theory of household structure, in which concepts of gender and generation play a key role. The utility of this theory is then demonstrated in the analysis of data from a survey of households in the City of Salford

Genome-wide interaction study of a proxy for stress-sensitivity and its prediction of major depressive disorder

Individual response to stress is correlated with neuroticism and is an important predictor of both neuroticism and the onset of major depressive disorder (MDD). Identification of the genetics underpinning individual differences in response to negative events (stress-sensitivity) may improve our understanding of the molecular pathways involved, and its association with stress-related illnesses. We sought to generate a proxy for stress-sensitivity through modelling the interaction between SNP allele and MDD status on neuroticism score in order to identify genetic variants that contribute to the higher neuroticism seen in individuals with a lifetime diagnosis of depression compared to unaffected individuals. Meta-analysis of genome-wide interaction studies (GWIS) in UK Biobank (N = 23,092) and Generation Scotland: Scottish Family Health Study (N = 7,155) identified no genome-wide significance SNP interactions. However, gene-based tests identified a genome-wide significant gene, ZNF366, a negative regulator of glucocorticoid receptor function implicated in alcohol dependence (p = 1.48x10-7; Bonferroni-corrected significance threshold p < 2.79x10-6). Using summary statistics from the stress-sensitivity term of the GWIS, SNP heritability for stress-sensitivity was estimated at 5.0%. In models fitting polygenic risk scores of both MDD and neuroticism derived from independent GWAS, we show that polygenic risk scores derived from the UK Biobank stress-sensitivity GWIS significantly improved the prediction of MDD in Generation Scotland. This study may improve interpretation of larger genome-wide association studies of MDD and other stress-related illnesses, and the understanding of the etiological mechanisms underpinning stress-sensitivity

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder

This paper is dedicated to the memory of Psychiatric Genomics Consortium (PGC) founding member and Bipolar disorder working group co-chair Pamela Sklar. We thank the participants who donated their time, experiences and DNA to this research, and to the clinical and scientific teams that worked with them. We are deeply indebted to the investigators who comprise the PGC. The views expressed are those of the authors and not necessarily those of any funding or regulatory body. Analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org ) hosted by SURFsara, and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu).Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P<1x10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (GWS, p < 5x10-8) in the discovery GWAS were not GWS in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis 30 loci were GWS including 20 novel loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene-sets including regulation of insulin secretion and endocannabinoid signaling. BDI is strongly genetically correlated with schizophrenia, driven by psychosis, whereas BDII is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential new biological mechanisms for BD.This work was funded in part by the Brain and Behavior Research Foundation, Stanley Medical Research Institute, University of Michigan, Pritzker Neuropsychiatric Disorders Research Fund L.L.C., Marriot Foundation and the Mayo Clinic Center for Individualized Medicine, the NIMH Intramural Research Program; Canadian Institutes of Health Research; the UK Maudsley NHS Foundation Trust, NIHR, NRS, MRC, Wellcome Trust; European Research Council; German Ministry for Education and Research, German Research Foundation IZKF of Münster, Deutsche Forschungsgemeinschaft, ImmunoSensation, the Dr. Lisa-Oehler Foundation, University of Bonn; the Swiss National Science Foundation; French Foundation FondaMental and ANR; Spanish Ministerio de Economía, CIBERSAM, Industria y Competitividad, European Regional Development Fund (ERDF), Generalitat de Catalunya, EU Horizon 2020 Research and Innovation Programme; BBMRI-NL; South-East Norway Regional Health Authority and Mrs. Throne-Holst; Swedish Research Council, Stockholm County Council, Söderström Foundation; Lundbeck Foundation, Aarhus University; Australia NHMRC, NSW Ministry of Health, Janette M O'Neil and Betty C Lynch