Influence of Visual Attention on the Likelihood of Choice Through Regression Analysis

Eye tracking technology allows for a relatively direct and continuous measurement of unconcealed visual attention. In the consumer goods market today, it is important for companies to make their brand or product stand out within a vast competitive array. Even though it is highly unlikely that a product would be purchased without having been noticed (unseen is unsold), it is important to investigate if products that garner high attention are in fact purchased in the marketplace, and if a correlation between the two metrics exists. Through the utilization of real consumers in an immersive consumer retail experience laboratory, an eye tracking study on seasoned breading mix was conducted to test the correlation between attention and sales data. Data captured from 37 study participants were used to create a regression model by utilizing the Fit Y by X function in the statistical program JMP Pro 12. Statistical analysis indicated that including attention metrics in the prediction model significantly improves the ability to predict average sales. Demographics such as gender, age, relationship status, education, employment, shopping habits were also investigated in order to understand the trends of individual participants to find ideal consumers. Overall, eye tracking is a viable option to foreshadow sales and attention performance within this category

Learning to Fix Build Errors with Graph2Diff Neural Networks

Professional software developers spend a significant amount of time fixing builds, but this has received little attention as a problem in automatic program repair. We present a new deep learning architecture, called Graph2Diff, for automatically localizing and fixing build errors. We represent source code, build configuration files, and compiler diagnostic messages as a graph, and then use a Graph Neural Network model to predict a diff. A diff specifies how to modify the code’s abstract syntax tree, represented in the neural network as a sequence of tokens and of pointers to code locations. Our network is an instance of a more general abstraction which we call Graph2Tocopo, which is potentially useful in any development tool for predicting source code changes. We evaluate the model on a dataset of over 500k real build errors and their resolutions from professional developers. Compared to the approach of DeepDelta [23], our approach tackles the harder task of predicting a more precise diff but still achieves over double the accuracy

Pathogenesis of HIV-associated sensory neuropathy: evidence from in vivo and in vitro experimental models

HIV-associated sensory neuropathy (HIV-SN) is a frequent neurological complication of HIV infection and its treatment with some antiretroviral drugs. We review the pathogenesis of the viral- and drug-induced causes of the neuropathy, and its primary symptom, pain, based on evidence from in vivo and in vitro models of HIV-SN. Viral coat proteins mediate nerve fibre damage and hypernociception through direct and indirect mechanisms. Direct interactions between viral proteins and nerve fibres dominate axonal pathology, while somal pathology is dominated by indirect mechanisms that occur secondary to virus-mediated activation of glia and macrophage infiltration into the dorsal root ganglia. The treatment-induced neuropathy and resulting hypernociception arise primarily from drug-induced mitochondrial dysfunction, but the sequence of events initiated by the mitochondrial dysfunction that leads to the nerve fibre damage and dysfunction are still unclear. Overall, the models that have been developed to study the pathogenesis of HIV-SN, and hypernociception associated with the neuropathy, are reasonable models and have provided useful insights into the pathogenesis of HIV-SN. As new models are developed they may ultimately lead to identification of therapeutic targets for the prevention or treatment of this common neurological complication of HIV infection

Novel three-day, community-based, nonpharmacological group intervention for chronic musculoskeletal pain (COPERS): a randomised clinical trial

Background Chronic musculoskeletal pain is the leading cause of disability worldwide. The effectiveness of pharmacological treatments for chronic pain is often limited, and there is growing concern about the adverse effects of these treatments, including opioid dependence. Nonpharmacological approaches to chronic pain may be an attractive alternative or adjunctive treatment. We describe the effectiveness of a novel, theoretically based group pain management support intervention for chronic musculoskeletal pain. Methods and Findings We conducted a multi-centre, pragmatic, randomised, controlled effectiveness and cost-effectiveness (cost–utility) trial across 27 general practices and community musculoskeletal services in the UK. We recruited 703 adults with musculoskeletal pain of at least 3 mo duration between August 1, 2011, and July 31, 2012, and randomised participants 1.33:1 to intervention (403) or control (300). Intervention participants were offered a participative group intervention (COPERS) delivered over three alternate days with a follow-up session at 2 wk. The intervention introduced cognitive behavioural approaches and was designed to promote self-efficacy to manage chronic pain. Controls received usual care and a relaxation CD. The primary outcome was pain-related disability at 12 mo (Chronic Pain Grade [CPG] disability subscale); secondary outcomes included the CPG disability subscale at 6 mo and the following measured at 6 and 12 mo: anxiety and depression (Hospital Anxiety and Depression Scale [HADS]), pain acceptance (Chronic Pain Acceptance Questionnaire), social integration (Health Education Impact Questionnaire social integration and support subscale), pain-related self-efficacy (Pain Self-Efficacy Questionnaire), pain intensity (CPG pain intensity subscale), the census global health question (2011 census for England and Wales), health utility (EQ-5D-3L), and health care resource use. Analyses followed the intention-to-treat principle, accounted for clustering by course in the intervention arm, and used multiple imputation for missing or incomplete primary outcome data. The mean age of participants was 59.9 y, with 81% white, 67% female, 23% employed, 85% with pain for at least 3 y, and 23% on strong opioids. Symptoms of depression and anxiety were common (baseline mean HADS scores 7.4 [standard deviation 4.1] and 9.2 [4.6], respectively). Overall, 282 (70%) intervention participants met the predefined intervention adherence criterion. Primary outcome data were obtained from 88% of participants. There was no significant difference between groups in pain-related disability at 6 or 12 mo (12 mo: difference −1.0, intervention versus control, 95% CI −4.9 to 3.0), pain intensity, or the census global health question. Anxiety, depression, pain-related self-efficacy, pain acceptance, and social integration were better in the intervention group at 6 mo; at 12 mo, these differences remained statistically significant only for depression (−0.7, 95% CI −1.2 to −0.2) and social integration (0.8, 95% CI 0.4 to 1.2). Intervention participants received more analgesics than the controls across the 12 mo. The total cost of the course per person was £145 (US$214). The cost–utility analysis showed there to be a small benefit in terms of quality-adjusted life years (QALYs) (0.0325, 95$277], 95% CI −£125 [−US$184] to £501 [US$738]), resulting in an incremental cost-effectiveness ratio of £5,786 (US$8,521) per QALY. Limitations include the fact that the intervention was relatively brief and did not include any physical activity components. Conclusions While the COPERS intervention was brief, safe, and inexpensive, with a low attrition rate, it was not effective for reducing pain-related disability over 12 mo (primary outcome). For secondary outcomes, we found sustained benefits on depression and social integration at 6 and 12 mo, but there was no effect on anxiety, pain-related self-efficacy, pain acceptance, pain intensity, or the census global health question at 12 mo. There was some evidence that the intervention may be cost-effective based on a modest difference in QALYs between groups. Trial registration ISRCTN Registry 2442673

Evolutionary patterns in sound production across fishes

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Magnetic resonance imaging as a biomarker in diabetic and HIV-associated peripheral neuropathy: A systematic review-based narrative

Background: Peripheral neuropathy can be caused by diabetes mellitus and HIV infection, and often leaves patients with treatment-resistant neuropathic pain. To better treat this condition, we need greater understanding of the pathogenesis, as well as objective biomarkers to predict treatment response. Magnetic resonance imaging (MRI) has a firm place as a biomarker for diseases of the central nervous system (CNS), but until recently has had little role for disease of the peripheral nervous system. Objectives: To review the current state-of-the-art of peripheral nerve MRI in diabetic and HIV symmetrical polyneuropathy. We used systematic literature search methods to identify all studies currently published, using this as a basis for a narrative review to discuss major findings in the literature. We also assessed risk of bias, as well as technical aspects of MRI and statistical analysis. Methods: Protocol was pre-registered on NIHR PROSPERO database. MEDLINE, Web of Science and EMBASE databases were searched from 1946 to 15th August 2020 for all studies investigating either diabetic or HIV neuropathy and MRI, focusing exclusively on studies investigating symmetrical polyneuropathy. The NIH quality assessment tool for observational and cross-sectional cohort studies was used for risk of bias assessment. Results: The search resulted in 18 papers eligible for review, 18 for diabetic neuropathy and 0 for HIV neuropathy. Risk of bias assessment demonstrated that studies generally lacked explicit sample size justifications, and some may be underpowered. Whilst most studies made efforts to balance groups for confounding variables (age, gender, BMI, disease duration), there was lack of consistency between studies. Overall, the literature provides convincing evidence that DPN is associated with larger nerve cross sectional area, T2-weighted hyperintense and hypointense lesions, evidence of nerve oedema on Dixon imaging, decreased fractional anisotropy and increased apparent diffusion coefficient compared with controls. Analysis to date is largely restricted to the sciatic nerve or its branches. Conclusions: There is emerging evidence that various structural MR metrics may be useful as biomarkers in diabetic polyneuropathy, and technique to other forms of peripheral neuropathy, including HIV neuropathy, would be of value