1,341 research outputs found

    The relationship between problem gambling, excessive gaming, psychological distress and spending on loot boxes in Aotearoa New Zealand, Australia, and the United States-A cross-national survey

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    Loot boxes are digital containers of randomised rewards available in many video games.Due to similarities between some loot boxes and traditional forms of gambling, concernsregarding the relationship between spending on loot boxes in video games and symptomsof problematic gambling have been expressed by policy makers and the general public. Wepresent the first investigation of these concerns in large cross-sectional cross-national samples from three countries (Aotearoa New Zealand, Australia, and the United States). A sample of 1,049 participants were recruited through Qualtrics’ Survey Targeting service from abroad cross-section of the population in Australia (n = 339), Aotearoa New Zealand (n =323), and the United States (n = 387). Participants answered a survey assessing problemgambling, problem gaming symptomology, and how much they spent on loot boxes permonth. On average, individuals with problem gambling issues spent approximately $13USD per month more on loot boxes than those with no such symptoms. Loot box spendingwas also associated with both positive and negative moods, albeit with small effect sizes.Analyses showed both interactions and correlations between problematic gambling andproblematic gaming symptoms, indicating both some commonality in the mechanismsunderlying, and independent contributions made by, these proposed diagnostic criteria.These results provide context for dialogues regarding how best to reduce the impacts of lootbox spending among those with problematic gambling symptoms

    An integrated gene annotation and transcriptional profiling approach towards the full gene content of the Drosophila genome

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    BACKGROUND: While the genome sequences for a variety of organisms are now available, the precise number of the genes encoded is still a matter of debate. For the human genome several stringent annotation approaches have resulted in the same number of potential genes, but a careful comparison revealed only limited overlap. This indicates that only the combination of different computational prediction methods and experimental evaluation of such in silico data will provide more complete genome annotations. In order to get a more complete gene content of the Drosophila melanogaster genome, we based our new D. melanogaster whole-transcriptome microarray, the Heidelberg FlyArray, on the combination of the Berkeley Drosophila Genome Project (BDGP) annotation and a novel ab initio gene prediction of lower stringency using the Fgenesh software. RESULTS: Here we provide evidence for the transcription of approximately 2,600 additional genes predicted by Fgenesh. Validation of the developmental profiling data by RT-PCR and in situ hybridization indicates a lower limit of 2,000 novel annotations, thus substantially raising the number of genes that make a fly. CONCLUSIONS: The successful design and application of this novel Drosophila microarray on the basis of our integrated in silico/wet biology approach confirms our expectation that in silico approaches alone will always tend to be incomplete. The identification of at least 2,000 novel genes highlights the importance of gathering experimental evidence to discover all genes within a genome. Moreover, as such an approach is independent of homology criteria, it will allow the discovery of novel genes unrelated to known protein families or those that have not been strictly conserved between species

    Inductively guided circuits for ultracold dressed atoms

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    Recent progress in optics, atomic physics and material science has paved the way to study quantum effects in ultracold atomic alkali gases confined to non-trivial geometries. Multiply connected traps for cold atoms can be prepared by combining inhomogeneous distributions of DC and radio-frequency electromagnetic fields with optical fields that require complex systems for frequency control and stabilization. Here we propose a flexible and robust scheme that creates closed quasi-one-dimensional guides for ultracold atoms through the ‘dressing’ of hyperfine sublevels of the atomic ground state, where the dressing field is spatially modulated by inductive effects over a micro-engineered conducting loop. Remarkably, for commonly used atomic species (for example, 7Li and 87Rb), the guide operation relies entirely on controlling static and low-frequency fields in the regimes of radio-frequency and microwave frequencies. This novel trapping scheme can be implemented with current technology for micro-fabrication and electronic control

    A close examination of double filtering with fold change and t test in microarray analysis

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    <p>Abstract</p> <p>Background</p> <p>Many researchers use the double filtering procedure with fold change and <it>t </it>test to identify differentially expressed genes, in the hope that the double filtering will provide extra confidence in the results. Due to its simplicity, the double filtering procedure has been popular with applied researchers despite the development of more sophisticated methods.</p> <p>Results</p> <p>This paper, for the first time to our knowledge, provides theoretical insight on the drawback of the double filtering procedure. We show that fold change assumes all genes to have a common variance while <it>t </it>statistic assumes gene-specific variances. The two statistics are based on contradicting assumptions. Under the assumption that gene variances arise from a mixture of a common variance and gene-specific variances, we develop the theoretically most powerful likelihood ratio test statistic. We further demonstrate that the posterior inference based on a Bayesian mixture model and the widely used significance analysis of microarrays (SAM) statistic are better approximations to the likelihood ratio test than the double filtering procedure.</p> <p>Conclusion</p> <p>We demonstrate through hypothesis testing theory, simulation studies and real data examples, that well constructed shrinkage testing methods, which can be united under the mixture gene variance assumption, can considerably outperform the double filtering procedure.</p
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