51 research outputs found

    Reward Reactivity and Dark Flow in Slot-Machine Gambling: “Light” and “Dark” Routes to Enjoyment

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    Background and aims: Slot machines are a very popular form of gambling. In this study, we look at two different routes to enjoying slots play. One route involves the degree to which players react to rewards. The other route involves what we call dark flow – a pleasurable, but maladaptive state where players become completely engrossed in slots play, providing an escape from the depressing thoughts that characterize their everyday lives. Methods: One hundred and twenty-nine high-frequency slots players were tested on slot-machine simulators set up in the lobby of a casino. We measured reward reactivity using post-reinforcement pauses (PRPs) and the force with which players pressed the spin button following different slot-machine outcomes. For each player, we calculated the slopes of PRPs and force as a function of credit gains. We also assessed players’ slots game enjoyment and their experience of dark flow, depression, and problem gambling. Results: Both the PRP and the force measures of reward reactivity were significantly correlated with players’ enjoyment of the slots session, but neither measure was correlated with either problem gambling or depression. Ratings of dark flow were strongly correlated with slots enjoyment (which accounted for far more positive affect variance than the reward reactivity measures) and were correlated with both problem gambling scores and depression. Discussion and conclusions: Our results suggest that of these two routes to enjoying slot-machine play, the dark flow route is especially problematic. We contend that the dark flow state may be enjoyable because it provides escape from the negative thoughts linked to depression

    Dicamba Retention in Commercial Sprayers Following Triple Rinse Cleanout Procedures, and Soybean Response to Contamination Concentrations

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    The commercial launch of dicamba‐tolerant (DT) crops has resulted in increased dicamba usage and a high number of dicamba off‐target movement complaints on sensitive soybeans (Glycine max L.). Dicamba is a synthetic auxin and low dosages as 0.028 g ae ha−1 can induce injury on sensitive soybean. Tank contamination has been identified as one of the sources for unintended sensitive crop exposure. The labels of new dicamba formulations require a triple rinse cleanout procedure following applications. Cleanout efficacy might vary based on the sprayer type and procedure followed. This study was performed to quantify dicamba retention in commercial sprayers and assess the risk for crop injury from remaining contaminants. The results indicate triple rinse with water was comparable to cleanout procedures utilizing ammonium, commercial tank cleaners, and glyphosate in rinses. Dicamba contaminants in final rinsates resulted in \u3c15% visual injury and no yield response when applied to sensitive soybeans at R1 stage. A survey of 25 agricultural sprayers demonstrated a cleanout efficacy of 99.996% by triple rinsing with water following applications of dicamba at 560 g ae ha−1, with concentrations of less than 1 ug mL−1 detected rinsates from the fourth rinse. A dose response experiment predicted dosages causing 5% visual injury and the yield losses were 0.1185 and 2.8525 g ae ha−1. However, symptomology was observed for all tested dosages, including the rate as low as 0.03 g ae ha−1. The results from this study suggest triple rinsing with sufficient amount of water (≥10% of tank volume) is adequate for the removal of dicamba residues from sprayers to avoid sensitive soybean damage. This study can provide producers with confidence in cleanout procedures following dicamba applications, and aid in minimizing risk for off‐target movement through tank contamination

    Employing machine learning for reliable miRNA target identification in plants

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    <p>Abstract</p> <p>Background</p> <p>miRNAs are ~21 nucleotide long small noncoding RNA molecules, formed endogenously in most of the eukaryotes, which mainly control their target genes post transcriptionally by interacting and silencing them. While a lot of tools has been developed for animal miRNA target system, plant miRNA target identification system has witnessed limited development. Most of them have been centered around exact complementarity match. Very few of them considered other factors like multiple target sites and role of flanking regions.</p> <p>Result</p> <p>In the present work, a Support Vector Regression (SVR) approach has been implemented for plant miRNA target identification, utilizing position specific dinucleotide density variation information around the target sites, to yield highly reliable result. It has been named as p-TAREF (plant-Target Refiner). Performance comparison for p-TAREF was done with other prediction tools for plants with utmost rigor and where p-TAREF was found better performing in several aspects. Further, p-TAREF was run over the experimentally validated miRNA targets from species like <it>Arabidopsis</it>, <it>Medicago</it>, Rice and Tomato, and detected them accurately, suggesting gross usability of p-TAREF for plant species. Using p-TAREF, target identification was done for the complete Rice transcriptome, supported by expression and degradome based data. miR156 was found as an important component of the Rice regulatory system, where control of genes associated with growth and transcription looked predominant. The entire methodology has been implemented in a multi-threaded parallel architecture in Java, to enable fast processing for web-server version as well as standalone version. This also makes it to run even on a simple desktop computer in concurrent mode. It also provides a facility to gather experimental support for predictions made, through on the spot expression data analysis, in its web-server version.</p> <p>Conclusion</p> <p>A machine learning multivariate feature tool has been implemented in parallel and locally installable form, for plant miRNA target identification. The performance was assessed and compared through comprehensive testing and benchmarking, suggesting a reliable performance and gross usability for transcriptome wide plant miRNA target identification.</p

    Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

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    Background: The EMPA KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. Methods: EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. Findings: Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5–2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62–0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16–1·59), representing a 50% (42–58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all &gt;0·1). Interpretation: In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. Funding: Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

    Social Acceptability in Ecosystem Management

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    Defining social acceptability in ecosystem management: a workshop proceedings.

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    This compendium of papers was developed in response to the assumption that implementing an ecological approach to forest management requires an understanding of socially acceptable forestry -- what it is and the implications of doing it. The papers in this collection bring to bear perspectives from a variety of social science disciplines and question whether the focus on social acceptability is an appropriate and useful one
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