Epistasis and genotype-by-environment interaction of grain protein content in durum wheat

Parental, F1 , F 2 , BC 1 and BC 2 generations of four crosses involving four cultivars of durum wheat (Triticum durum Desf.) were evaluated at two sites in Tunisia. A three-parameter model was found inadequate for all cases except crosses Chili x Cocorit 71 at site Sidi Thabet and Inrat 69 x Karim at both sites. In most cases a digenic epistatic model was sufficient to explain variation in generation means. Dominance effects (h) and additive x additive epistasis (i) (when significant) were more important than additive (d) effects and other epistatic components. Considering the genotype-by-environment interaction, the non-interactive model (m, d, h, e) was found adequate. Additive variance was higher than environmental variance in three crosses at both sites. The estimated values of narrow-sense heritability were dependent upon the cross and the sites and were 0%-85%. The results indicate that appropriate choice of environment and selection in later generations would increase grain protein content in durum wheat

Association between solar insolation and a history of suicide attempts in bipolar I disorder

In many international studies, rates of completed suicide and suicide attempts have a seasonal pattern that peaks in spring or summer. This exploratory study investigated the association between solar insolation and a history of suicide attempt in patients with bipolar I disorder. Solar insolation is the amount of electromagnetic energy from the Sun striking a surface area on Earth. Data were collected previously from 5536 patients with bipolar I disorder at 50 collection sites in 32 countries at a wide range of latitudes in both hemispheres. Suicide related data were available for 3365 patients from 310 onset locations in 51 countries. 1047 (31.1%) had a history of suicide attempt. There was a significant inverse association between a history of suicide attempt and the ratio of mean winter solar insolation/mean summer solar insolation. This ratio is smallest near the poles where the winter insolation is very small compared to the summer insolation. This ratio is largest near the equator where there is relatively little variation in the insolation over the year. Other variables in the model that were positively associated with suicide attempt were being female, a history of alcohol or substance abuse, and being in a younger birth cohort. Living in a country with a state-sponsored religion decreased the association. (All estimated coefficients p <0.01). In summary, living in locations with large changes in solar insolation between winter and summer may be associated with increased suicide attempts in patients with bipolar disorder. Further investigation of the impacts of solar insolation on the course of bipolar disorder is needed.Peer reviewe

Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions

YesAlthough many modelling and prediction frameworks for corporate bankruptcy and distress have been proposed, the relative performance evaluation of prediction models is criticised due to the assessment exercise using a single measure of one criterion at a time, which leads to reporting conflicting results. Mousavi et al. (Int Rev Financ Anal 42:64–75, 2015) proposed an orientation-free super-efficiency DEA-based framework to overcome this methodological issue. However, within a super-efficiency DEA framework, the reference benchmark changes from one prediction model evaluation to another, which in some contexts might be viewed as “unfair” benchmarking. In this paper, we overcome this issue by proposing a slacks-based context-dependent DEA (SBM-CDEA) framework to evaluate competing distress prediction models. In addition, we propose a hybrid crossbenchmarking- cross-efficiency framework as an alternative methodology for ranking DMUs that are heterogeneous. Furthermore, using data on UK firms listed on London Stock Exchange, we perform a comprehensive comparative analysis of the most popular corporate distress prediction models; namely, statistical models, under both mono criterion and multiple criteria frameworks considering several performance measures. Also, we propose new statistical models using macroeconomic indicators as drivers of distress