Impact of today's media on university student's body image in Pakistan: a conservative, developing country's perspective

<p>Abstract</p> <p>Background</p> <p>Living in a world greatly controlled by mass media makes it impossible to escape its pervading influence. As media in Pakistan has been free in the true sense of the word for only a few years, its impact on individuals is yet to be assessed. Our study aims to be the first to look at the effect media has on the body image of university students in a conservative, developing country like Pakistan. Also, we introduced the novel concept of body image dissatisfaction as being both negative and positive.</p> <p>Methods</p> <p>A cross-sectional study was conducted among 7 private universities over a period of two weeks in the city of Karachi, Pakistan's largest and most populous city. Convenience sampling was used to select both male and female undergraduate students aged between 18 and 25 and a sample size of 783 was calculated.</p> <p>Results</p> <p>Of the 784 final respondents, 376 (48%) were males and 408 (52%) females. The mean age of males was 20.77 (+/- 1.85) years and females was 20.38 (+/- 1.63) years. Out of these, 358 (45.6%) respondents had a positive BID (body image dissatisfaction) score while 426 (54.4%) had a negative BID score. Of the respondents who had positive BID scores, 93 (24.7%) were male and 265 (65.0%) were female. Of the respondents with a negative BID score, 283 (75.3%) were male and 143 (35.0%) were female. The results for BID vs. media exposure were similar in both high and low peer pressure groups. Low media exposure meant positive BID scores and vice versa in both groups (p < 0.0001) showing a statistically significant association between high media exposure and negative body image dissatisfaction. Finally, we looked at the association between gender and image dissatisfaction. Again a statistically significant association was found between positive body image dissatisfaction and female gender and negative body image dissatisfaction and male gender (p < 0.0001).</p> <p>Conclusions</p> <p>Our study confirmed the tendency of the media to have an overall negative effect on individuals' body image. A striking feature of our study, however, was the finding that negative body image dissatisfaction was found to be more prevalent in males as compared to females. Likewise, positive BID scores were more prevalent amongst females.</p

Understanding size effects and forming limits in the micro-stamping of industrial stainless steel foils

This study investigates the effect of grain size and composition on the material properties and forming limits of commercially supplied stainless steel foil for bipolar plate manufacture via tensile, stretch forming and micro-stamping trials. It is shown that in commercially supplied stainless steel the grain size can vary significantly and that &lsquo;size effects&rsquo; can be influenced by prior steel processing and composition effects. While the forming limits in micro-stamping appear to be directly linked to the plane strain forming limits of the individual stainless steel alloys, there was a clear effect of the tensile anisotropy. In contrast to previous studies, forming severity and the likelihood of material failure did not increase with a decreasing channel profile radius. This was related to inaccuracies of the forming tool profile shape

Predicting Chronic Heart Failure Using Diagnoses Graphs

Part 5: MAKE AALInternational audiencePredicting the onset of heart disease is of obvious importance as doctors try to improve the general health of their patients. If it were possible to identify high-risk patients before their heart failure diagnosis, doctors could use that information to implement preventative measures to keep a heart failure diagnosis from becoming a reality. Integration of Electronic Medical Records (EMRs) into clinical practice has enabled the use of computational techniques for personalized healthcare at scale. The larger goal of such modeling is to pivot from reactive medicine to preventative care and early detection of adverse conditions. In this paper, we present a trajectory-based disease progression model to detect chronic heart failure. We validate our work on a database of Medicare records of 1.1 million elderly US patients. Our supervised approach allows us to assign likelihood of chronic heart failure for an unseen patient’s disease history and identify key disease progression trajectories that intensify or diminish said likelihood. This information will be a tremendous help as patients and doctors try to understand what are the most dangerous diagnoses for those who are susceptible to heart failure. Using our model, we demonstrate some of the most common disease trajectories that eventually result in the development of heart failure