177 research outputs found

    Half of Women in New Hampshire Have Experienced Sexual Harassment at Work

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    In this brief, authors Kristin Smith, Sharyn Potter, and Jane Stapleton discuss the results of a 2018 Granite State Poll survey conducted by the University of New Hampshire on workplace sexual harassment in New Hampshire. They report that over half of women and nearly one-quarter of men in New Hampshire have been victims of sexual harassment at their workplaces during their lifetimes. Women are more likely to state they suffered work-related consequences (for example, financial loss, being fired or demoted) than men, but similar shares reported quitting their jobs as a result of the harassment. Sexual harassment is problematic for the workplace, as it reduces worker morale and job satisfaction, diminishes productivity, and increases absenteeism and worker withdrawal. The authors suggest that employers would do well to invest in prevention, such as bystander intervention training, and encourage victims’ use of supports to mitigate the negative effects of workplace sexual harassment

    Data Analysis with the Morse-Smale Complex: The msr Package for R

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    In many areas, scientists deal with increasingly high-dimensional data sets. An important aspect for these scientists is to gain a qualitative understanding of the process or system from which the data is gathered. Often, both input variables and an outcome are observed and the data can be characterized as a sample from a high-dimensional scalar function. This work presents the R package msr for exploratory data analysis of multivariate scalar functions based on the Morse-Smale complex. The Morse-Smale complex provides a topologically meaningful decomposition of the domain. The msr package implements a discrete approximation of the Morse-Smale complex for data sets. In previous work this approximation has been exploited for visualization and partition-based regression, which are both supported in the msr package. The visualization combines the Morse-Smale complex with dimension-reduction techniques for a visual summary representation that serves as a guide for interactive exploration of the high-dimensional function. In a similar fashion, the regression employs a combination of linear models based on the Morse-Smale decomposition of the domain. This regression approach yields topologically accurate estimates and facilitates interpretation of general trends and statistical comparisons between partitions. In this manner, the msr package supports high-dimensional data understanding and exploration through the Morse-Smale complex

    Visual summary statistics

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    technical reportTraditionally, statistical summaries of categorical data often have been visualized using graphical plots of central moments (e.g., mean and standard deviation), or cumulants (e.g., median and quartiles) by box plots. In this work we reexamine the box plot and its relatives and develop a new hybrid summary plot that combines moment, cumulant, and density information. In view of the important role of plots in decision making, our work focuses on incorporating additional descriptive parameters while simultaneously improving the comprehensibility of the summary plots using advanced visual techniques. In many complex situations providing a comprehensive view of the data requires additional summary characteristics, therefore, we submit that these additional parameters, like higher-order central moments can be valuable elements of multi-dimensional summary displays

    3D Line textures and the visualization of confidence in Architecture

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    technical reportThis work introduces a technique for interactive walkthroughs of non-photorealistically rendered (NPR) scenes using 3D line primitives to define architectural features of the model, as well as indicate textural qualities. Line primitives are not typically used in this manner in favor of texture mapping techniques which can encapsulate a great deal of information in a single texture map, and take advantage of GPU optimizations for accelerated rendering. However, texture mapped images may not maintain the visual quality or aesthetic appeal that is possible when using 3D lines to simulate NPR scenes such as hand-drawn illustrations or architectural renderings. In addition, line textures can be modi ed interactively, for instance changing the sketchy quality of the lines, and can be exported as vectors to allow the automatic generation of illustrations and further modi cation in vector-based graphics programs. The technique introduced here extracts feature edges from a model, and using these edges, generates a reduced set of line textures which indicate material properties while maintaining interactive frame rates. A clipping algorithm is presented to enable 3D lines to reside only in the interior of the 3D model without exposing the underlying triangulated mesh. The resulting system produces interactive illustrations with high visual quality that are free from animation artifacts

    Uncertainty visualization in forward and inverse cardiac models

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    pre-printQuantification and visualization of uncertainty in cardiac forward and inverse problems with complex geometries is subject to various challenges. Specific to visualization is the observation that occlusion and clutter obscure important regions of interest, making visual assessment difficult. In order to overcome these limitations in uncertainty visualization, we have developed and implemented a collection of novel approaches. To highlight the utility of these techniques, we evaluated the uncertainty associated with two examples of modeling myocardial activity. In one case we studied cardiac potentials during the repolarization phase as a function of variability in tissue conductivities of the ischemic heart (forward case). In a second case, we evaluated uncertainty in reconstructed activation times on the epicardium resulting from variation in the control parameter of Tikhonov regularization (inverse case). To overcome difficulties associated with uncertainty visualization, we implemented linked-view windows and interactive animation to the two respective cases. Through dimensionality reduction and superimposed mean and standard deviation measures over time, we were able to display key features in large ensembles of data and highlight regions of interest where larger uncertainties exist

    No reduction in C-reactive protein following a 12-month randomized controlled trial of exercise in men and women.

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    Low-grade systemic inflammation is suggested to play a role in the development of several chronic diseases including cancer. Higher levels of physical activity and lower adiposity have been associated with reduced levels of markers of systemic inflammation, such as C-reactive protein (CRP); however, reductions in CRP have not been observed consistently in randomized controlled trials of exercise. Purpose: To examine the effect of a 12-month aerobic exercise intervention on CRP levels in men and women. Methods: 102 men and 100 women, sedentary and aged 40-75 years, mean BMI of 29.9 and 28.7 kg/m2, respectively, were randomly assigned to a 12-month moderate-to-vigorous aerobic exercise intervention (6 d/wk, 60 min/d, 60-85% maximum heart rate) or control group. Fasting blood samples were collected at baseline and at 12-months. CRP levels were measured by high-sensitivity latex-enhanced nephelometry. Results: At baseline, CRP was 1.16 mg/L and 2.11 for men and women, respectively, and CRP was correlated with percent body fat (r=0.48, p ≤0.001), BMI (r=0.37, p ≤0.001) and aerobic fitness (r=-0.49, p ≤0.001). No intervention effects were observed for CRP in men or women, or when stratified by baseline BMI (< 30 kg/m2 vs. ≥ 30 kg/m2) , baseline CRP (< 3 mg/L vs. ≥ 3 mg/L) or change in body weight, body composition or aerobic fitness. Conclusion: A 12 month moderate-to-vigorous aerobic exercise intervention did not affect CRP levels in previously sedentary men or women with average-risk CRP values at baseline

    The FaceBase Consortium: A comprehensive program to facilitate craniofacial research

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    The FaceBase Consortium consists of ten interlinked research and technology projects whose goal is to generate craniofacial research data and technology for use by the research community through a central data management and integrated bioinformatics hub. Funded by the National Institute of Dental and Craniofacial Research (NIDCR) and currently focused on studying the development of the middle region of the face, the Consortium will produce comprehensive datasets of global gene expression patterns, regulatory elements and sequencing; will generate anatomical and molecular atlases; will provide human normative facial data and other phenotypes; conduct follow up studies of a completed genome-wide association study; generate independent data on the genetics of craniofacial development, build repositories of animal models and of human samples and data for community access and analysis; and will develop software tools and animal models for analyzing and functionally testing and integrating these data. The FaceBase website (http://www.facebase.org) will serve as a web home for these efforts, providing interactive tools for exploring these datasets, together with discussion forums and other services to support and foster collaboration within the craniofacial research community
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