Risky Recruitment: How Rape Myth Acceptance Among Potential New Sorority Members Is Related to Their Self-Efficacy to Prevent Sexual Assault and Perceptions of University Sexual Assault Reporting

This study examined how rape myth acceptance among potential new sorority members is related to their self-efficacy to prevent sexual assault and perceptions of how their university would handle a sexual assault report. Results indicate that the more these women reported acceptance with common rape myths, the less efficacious they felt to prevent sexual assault and the less likely they were to believe the university would handle a sexual assault report adequately. Universities must therefore consider how to dispel dangerous rape myths among this unique population to ensure sorority women feel comfortable intervening in and reporting sexual assault incidents

Sparse Superpixel Unmixing for Hyperspectral Image Analysis

Software was developed that automatically detects minerals that are present in each pixel of a hyperspectral image. An algorithm based on sparse spectral unmixing with Bayesian Positive Source Separation is used to produce mineral abundance maps from hyperspectral images. A superpixel segmentation strategy enables efficient unmixing in an interactive session. The algorithm computes statistically likely combinations of constituents based on a set of possible constituent minerals whose abundances are uncertain. A library of source spectra from laboratory experiments or previous remote observations is used. A superpixel segmentation strategy improves analysis time by orders of magnitude, permitting incorporation into an interactive user session (see figure). Mineralogical search strategies can be categorized as supervised or unsupervised. Supervised methods use a detection function, developed on previous data by hand or statistical techniques, to identify one or more specific target signals. Purely unsupervised results are not always physically meaningful, and may ignore subtle or localized mineralogy since they aim to minimize reconstruction error over the entire image. This algorithm offers advantages of both methods, providing meaningful physical interpretations and sensitivity to subtle or unexpected minerals

The Role of Hypermasculinity, Token Resistance, Rape Myth, and Assertive Sexual Consent Communication Among College Men

Purpose A greater understanding of how college men\u27s gendered beliefs and communication styles relate to their sexual consent attitudes and intentions is essential within the shifting context of negative to affirmative consent policies on college campuses. The results of this study can be used to help design more effective sexual consent interventions

Media exposure to mass violence events can fuel a cycle of distress.

The established link between trauma-related media exposure and distress may be cyclical: Distress can increase subsequent trauma-related media consumption that promotes increased distress to later events. We tested this hypothesis in a 3-year longitudinal study following the 2013 Boston Marathon bombings and the 2016 Orlando Pulse nightclub massacre using a national U.S. sample (N = 4165). Data were collected shortly after the bombings, 6 and 24 months post-bombings, and beginning 5 days after the Pulse nightclub massacre (approximately 1 year later; 36 months post-bombings). Bombing-related media exposure predicted posttraumatic stress symptoms (PTS) 6 months later; PTS predicted worry about future negative events 2 years after the bombings, which predicted increased media consumption and acute stress following the Pulse nightclub massacre 1 year later. Trauma-related media exposure perpetuates a cycle of high distress and media use

Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery

Many current and future NASA missions are capable of collecting enormous amounts of data, of which only a small portion can be transmitted to Earth. Communications are limited due to distance, visibility constraints, and competing mission downlinks. Long missions and high-resolution, multispectral imaging devices easily produce data exceeding the available bandwidth. To address this situation computationally efficient algorithms were developed for analyzing science imagery onboard the spacecraft. These algorithms autonomously cluster the data into classes of similar imagery, enabling selective downlink of representatives of each class, and a map classifying the terrain imaged rather than the full dataset, reducing the volume of the downlinked data. A range of approaches was examined, including k-means clustering using image features based on color, texture, temporal, and spatial arrangemen

Metric Learning to Enhance Hyperspectral Image Segmentation

Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an over-segmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis. In this innovation, a metric learning approach is presented to improve the performance of unsupervised hyperspectral image segmentation. The prototype demonstrations attempt a superpixel segmentation in which the image is conservatively over-segmented; that is, the single surface features may be split into multiple segments, but each individual segment, or superpixel, is ensured to have homogenous mineralogy

Bivariate network meta-analysis for surrogate endpoint evaluation

Surrogate endpoints are very important in regulatory decision-making in healthcare, in particular if they can be measured early compared to the long-term final clinical outcome and act as good predictors of clinical benefit. Bivariate meta-analysis methods can be used to evaluate surrogate endpoints and to predict the treatment effect on the final outcome from the treatment effect measured on a surrogate endpoint. However, candidate surrogate endpoints are often imperfect, and the level of association between the treatment effects on the surrogate and final outcomes may vary between treatments. This imposes a limitation on the pairwise methods which do not differentiate between the treatments. We develop bivariate network meta-analysis (bvNMA) methods which combine data on treatment effects on the surrogate and final outcomes, from trials investigating heterogeneous treatment contrasts. The bvNMA methods estimate the effects on both outcomes for all treatment contrasts individually in a single analysis. At the same time, they allow us to model the surrogacy patterns across multiple trials (different populations) within a treatment contrast and across treatment contrasts, thus enabling predictions of the treatment effect on the final outcome for a new study in a new population or investigating a new treatment. Modelling assumptions about the between-studies heterogeneity and the network consistency, and their impact on predictions, are investigated using simulated data and an illustrative example in advanced colorectal cancer. When the strength of the surrogate relationships varies across treatment contrasts, bvNMA has the advantage of identifying treatments for which surrogacy holds, thus leading to better predictions

Stress, Burnout, Compassion Fatigue, and Mental Health in Hospice Workers in Minnesota

Background: Working in hospice care is a highly challenging yet rewarding profession. However, the challenges of working with dying patients and their families can overwhelm even the most highly dedicated professional, leading to burnout, compassion fatigue, anxiety, and depression. Objective: The aim of this study was to better understand how stress affects the mental health of hospice workers in terms of burnout and compassion fatigue and how they cope with these issues. Methods: Data for this study are from Compassion Fatigue and You, a cross-sectional survey of hospice staff from across Minnesota. We surveyed 547 hospice workers throughout Minnesota to better understand the overall mental health of staff, including levels of stress, burnout, and compassion fatigue, and how they cope with these issues. The study was conducted in 2008 and 2009 through a private, not-for-profit research institute affiliated with a large Midwestern health plan. Results: Hospice staff reported high levels of stress, with a small but significant proportion reporting moderate-to-severe symptoms of depression, anxiety, compassion fatigue, and burnout. Staff reported managing their stress through physical activity and social support, and they suggested that more opportunities to connect with coworkers and to exercise could help decrease staff burnout. Conclusions: Poor mental health places staff at risk for burnout and likely contributes to staff leaving hospice care; this is a critical issue as the profession attempts to attract new staff to meet the expanding demands for hospice care

Climate Change Challenges for Land Conservation: Rethinking Conservation Easements, Strategies, and Tools

Climate change has significant consequences for land conservation. Government agencies and nonprofit land trusts heavily rely on perpetual conservation easements. However, climate change and other dynamic landscape changes raise questions about the effectiveness and adaptability of permanent conservation instruments like conservation easements. Building upon a study of 269 conservation easements and interviews with seventy conservation-easement professionals in six different states, we examine the adaptability of conservation easements to climate change. We outline four potential approaches to enhance conservation outcomes under climate change: (1) shift land-acquisition priorities to account for potential climate-change impacts; (2) consider conservation tools other than perpetual conservation easements; (3) ensure that the terms of conservation easements permit the holder to adapt to climate change successfully; and (4) provide for more active stewardship of conservation lands. There is still a good deal of uncertainty as to the legal fate of a conservation easement that no longer meets its original purposes. Many state laws provide that conservation easements can be modified or terminated in the same manner as traditional easements. Yet, conservation easements are in many ways unlike other easements. The beneficiary is usually the public, not merely a neighboring landowner, and the holder is always a non-profit conservation organization or a government agency. Thus, there is a case to be made for adaptive protection. An overly narrow focus on perpetual property rights could actually thwart efforts to meet adaptation needs over the long term. We call for careful attention to ensuring conservation outcomes in dynamic landscapes over time