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

A protocol for the systematic review and meta-analysis of thigmotactic behaviour in the open field test in rodent models associated with persistent pain

OBJECTIVE: Thigmotaxis is an innate predator avoidance behaviour of rodents and is enhanced when animals are under stress. It is characterised by the preference of a rodent to seek shelter, rather than expose itself to the aversive open area. The behaviour has been proposed to be a measurable construct that can address the impact of pain on rodent behaviour. This systematic review will assess whether thigmotaxis can be influenced by experimental persistent pain and attenuated by pharmacological interventions in rodents. SEARCH STRATEGY: We will conduct search on three electronic databases to identify studies in which thigmotaxis was used as an outcome measure contextualised to a rodent model associated with persistent pain. All studies published until the date of the search will be considered. SCREENING AND ANNOTATION: Two independent reviewers will screen studies based on the order of (1) titles and abstracts, and (2) full texts. DATA MANAGEMENT AND REPORTING: For meta-analysis, we will extract thigmotactic behavioural data and calculate effect sizes. Effect sizes will be combined using a random-effects model. We will assess heterogeneity and identify sources of heterogeneity. A risk-of-bias assessment will be conducted to evaluate study quality. Publication bias will be assessed using funnel plots, Egger’s regression and trim-and-fill analysis. We will also extract stimulus-evoked limb withdrawal data to assess its correlation with thigmotaxis in the same animals. The evidence obtained will provide a comprehensive understanding of the strengths and limitations of using thigmotactic outcome measure in animal pain research so that future experimental designs can be optimised. We will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines and disseminate the review findings through publication and conference presentation

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

A multiple scales approach to crack front waves

Perturbation of a propagating crack with a straight edge is solved using the method of matched asymptotic expansions (MAE). This provides a simplified analysis in which the inner and outer solutions are governed by distinct mechanics. The inner solution contains the explicit perturbation and is governed by a quasi-static equation. The outer solution determines the radiation of energy away from the tip, and requires solving dynamic equations in the unperturbed configuration. The outer and inner expansions are matched via the small parameter L/l defined by the disparate length scales: the crack perturbation length L and the outer length scale l associated with the loading. The method is first illustrated for a scalar crack model and then applied to the elastodynamic mode I problem. The dispersion relation for crack front waves is found by requiring that the energy release rate is unaltered under perturbation. The wave speed is calculated as a function of the nondimensional parameter kl where k is the crack front wavenumber, and dispersive properties of the crack front wave speed are described for the first time. The example problems considered here demonstrate that the potential of using MAE for moving boundary value problems with multiple scales.Comment: 25 pages, 5 figure

Resolving Gas Dynamics in the Circumnuclear Region of a Disk Galaxy in a Cosmological Simulation

Using a hydrodynamic adaptive mesh refinement code, we simulate the growth and evolution of a galaxy, which could potentially host a supermassive black hole, within a cosmological volume. Reaching a dynamical range in excess of 10 million, the simulation follows the evolution of the gas structure from super-galactic scales all the way down to the outer edge of the accretion disk. Here, we focus on global instabilities in the self-gravitating, cold, turbulence-supported, molecular gas disk at the center of the model galaxy, which provide a natural mechanism for angular momentum transport down to sub-pc scales. The gas density profile follows a power-law scaling as r^-8/3, consistent with an analytic description of turbulence in a quasi-stationary circumnuclear disk. We analyze the properties of the disk which contribute to the instabilities, and investigate the significance of instability for the galaxy's evolution and the growth of a supermassive black hole at the center.Comment: 16 pages (includes appendix), submitted to ApJ. Figures here are at low resolution; for higher resolution version, download http://casa.colorado.edu/~levinerd/ms.pd

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

Eleven neurology-related proteins measured in serum are positively correlated to the severity of diabetic neuropathy

About 20% of patients with diabetes suffer from chronic pain with neuropathic characteristics. We investigated the multivariate associations between 92 neurology-related proteins measured in serum from 190 patients with painful and painless diabetic neuropathy. Participants were recruited from the Pain in Neuropathy Study, an observational cross-sectional multicentre study in which participants underwent deep phenotyping. In the exploration cohort, two groups were defined by hierarchical cluster analyses of protein data. The proportion of painless vs painful neuropathy did not differ between the two groups, but one group had a significantly higher grade of neuropathy as measured by the Toronto Clinical Scoring System (TCSS). This finding was replicated in the replication cohort. Analyzing both groups together, we found that a group of 11 inter-correlated proteins (TNFRSF12A, SCARB2, N2DL-2, SKR3, EFNA4, LAYN, CLM-1, CD38, UNC5C, GFR-alpha-1, and JAM-B) were positively associated with TCSS values. Notably, EFNA4 and UNC5C are known to be part of axon guidance pathways. To conclude, although cluster analysis of 92 neurology-related proteins did not distinguish painful from painless diabetic neuropathy, we identified 11 proteins which positively correlated to neuropathy severity and warrant further investigation as potential biomarkers