The relationship between environmental context and attentional engagement in podcast listening experiences.

Introduction: Previous research has shown that podcasts are most frequently consumed using mobile listening devices across a wide variety of environmental, situational, and social contexts. To date, no studies have investigated how an individual's environmental context might influence their attentional engagement in podcast listening experiences. Improving understanding of the contexts in which episodes of listening take place, and how they might affect listener engagement, could be highly valuable to researchers and producers working in the fields of object-based and personalized media.

Older Adults' Casino Gambling Behavior and Their Attitudes Toward New Casino Development.

Research on new casinos typically focuses upon their impact on the community, rather than on specific at-risk groups. This research study explores the impact of the opening of a new casino on attitudes of older adult casino patrons, especially those at particular risk of having gambling problems. Results demonstrate that over 80% of older adult casino patrons would not change their attitudes toward gambling or expect to increase their gambling as a result of the opening of a new casino.

Scoping Review of Interventions Supporting Mothers with Mental Illness: Key Outcomes and Challenges.

Despite the fact that more than 60 % of women experiencing mental distress also care for dependent children, little is known about the efficacy of interventions supporting parents with mental illness. A scoping review of the literature published between 1997 and 2014 was conducted to obtain an overview of empirically evaluated interventions and to typify their outcomes. Our review identified 19 publications reporting on 9 interventions.

Re-contacting participants for inclusion in the database of Genotypes and Phenotypes (dbGaP): Findings from three case-control studies of lung cancer.

Background: Since January 2008, the National Institutes of Health (NIH) has required that all investigators who receive NIH support submit de-identified high-throughput genomic data to the database of Genotypes and Phenotypes (dbGaP). The purpose of this study was to explore the feasibility of re-consenting participants from three inactive studies, conducted from 2000 through 2009, to submit their data to dbGaP.

Methods: Participants were those enrolled in one of three prior population-based case-control studies of lung cancer who had given a DNA sample.

Investigation of biochemical diversity in a soybean lineage representing 35 years of breeding.

This paper reports an assessment of seed biochemical and metabolite variability and diversity in a series of nine soybean varieties; all lines share the same genetic lineage but represent ∼35 years of breeding (launch years 1972-2008) and differing yield potentials. These varieties, including six conventional and three glyphosate-tolerant lines, were grown concurrently at two replicated field sites in the United States during the 2011 growing season, and seeds were harvested at maturity. A compositional assessment included measurement of proximates, amino acids, fatty acids, tocopherols, isoflavones, saccharides, organic acids, and selected phytohormones.

Principal variance component analysis of crop composition data: a case study on herbicide-tolerant cotton.

Compositional studies on genetically modified (GM) and non-GM crops have consistently demonstrated that their respective levels of key nutrients and antinutrients are remarkably similar and that other factors such as germplasm and environment contribute more to compositional variability than transgenic breeding. We propose that graphical and statistical approaches that can provide meaningful evaluations of the relative impact of different factors to compositional variability may offer advantages over traditional frequentist testing. A case study on the novel application of principal variance component analysis (PVCA) in a compositional assessment of herbicide-tolerant GM cotton is presented.

Bayesian statistical approaches to compositional analyses of transgenic crops 2. Application and validation of informative prior distributions.

Bayesian approaches to evaluation of crop composition data allow simpler interpretations than traditional statistical significance tests. An important advantage of Bayesian approaches is that they allow formal incorporation of previously generated data through prior distributions in the analysis steps. This manuscript describes key steps to ensure meaningful and transparent selection and application of informative prior distributions.

Assessing compositional variability through graphical analysis and Bayesian statistical approaches: case studies on transgenic crops.

New transgenic (GM) crops are subjected to extensive safety assessments that include compositional comparisons with conventional counterparts as a cornerstone of the process. The influence of germplasm, location, environment, and agronomic treatments on compositional variability is, however, often obscured in these pair-wise comparisons. Furthermore, classical statistical significance testing can often provide an incomplete and over-simplified summary of highly responsive variables such as crop composition.

Introduction to Bayesian statistical approaches to compositional analyses of transgenic crops 1. Model validation and setting the stage.

Statistical comparisons of compositional data generated on genetically modified (GM) crops and their near-isogenic conventional (non-GM) counterparts typically rely on classical significance testing. This manuscript presents an introduction to Bayesian methods for compositional analysis along with recommendations for model validation. The approach is illustrated using protein and fat data from two herbicide tolerant GM soybeans (MON87708 and MON87708×MON89788) and a conventional comparator grown in the US in 2008 and 2009.