SAFEST: A Framework for Early Security Triggers in Public Spaces

International audiencePublic spaces such as airports, railway stations or stadiums bring together large numbers of people on a quite limited space to use a security-sensitive infrastructure. Electronic security systems may help to provide better and faster security, as well as safety for the general public. Application scenarios may include intrusion detection and monitoring of large crowds in order to provide guidance in case of unexpected events (e.g., a mass panic). However, current security systems used within the public infrastructure are typically expensive, non-trivial to deploy, difficult to operate and maintain, prone to malfunction due to individual component failures, and generally lack citizen privacy-friendliness. The advent of novel, large-scale distributed security systems based on wireless, lightweight sensors may enhance security and safety in public spaces. In this realm, SAFEST is a project aiming at analyzing the social context of area surveillance and developing a system that can fulfill this task, both in terms of technology as well as acceptance by the general public. The targeted system will operate in a distributed way, collect anonymized data, securely transfer this data to a central location for evaluation, and - if necessary - notify the operator or issue alerts directly to the general public. Work on the technical aspects of the system is accompanied by social studies investigating the individual perception of risk and the methods for reaching public acceptance of the technical solutions

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives

Genetic testing of children for adult-onset conditions: opinions of the British adult population and implications for clinical practice

This study set out to explore the attitudes of a representative sample of the British public towards genetic testing in children to predict disease in the future. We sought opinions about genetic testing for adult-onset conditions for which no prevention/treatment is available during childhood, and about genetic 'carrier' status to assess future reproductive risks. The study also examined participants' level of agreement with the reasons professional organisations give in favour of deferring such testing. Participants (n=2998) completed a specially designed questionnaire, distributed by email. Nearly half of the sample (47%) agreed that parents should be able to test their child for adult-onset conditions, even if there is no treatment or prevention at time of testing. This runs contrary to professional guidance about genetic testing in children. Testing for carrier status was supported by a larger proportion (60%). A child's future ability to decide for her/himself if and when to be tested was the least supported argument in favour of deferring testing.European Journal of Human Genetics advance online publication, 5 November 2014; doi:10.1038/ejhg.2014.221

Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI

In this work, we tackle the problem of Semi-Supervised Anomaly Segmentation (SAS) in Magnetic Resonance Images (MRI) of the brain, which is the task of automatically identifying pathologies in brain images. Our work challenges the effectiveness of current Machine Learning (ML) approaches in this application domain by showing that thresholding Fluid-attenuated inversion recovery (FLAIR) MR scans provides better anomaly segmentation maps than several different ML-based anomaly detection models. Specifically, our method achieves better Dice similarity coefficients and Precision-Recall curves than the competitors on various popular evaluation data sets for the segmentation of tumors and multiple sclerosis lesions.Comment: 10 pages, 4 figures, accepted to the MICCAI 2021 BrainLes Worksho

A Critical Analysis of the Carolina Leadership Academy’s CREED Program at the University of North Carolina-Chapel Hill

Student-athletes often know how to recognize leadership, but struggle to master techniques to best exemplify leadership characteristics. In 2003, sport psychologist Jeff Janssen partnered with the University of North Carolina at Chapel Hill (UNC) Athletics Department to create a learning environment fostering leadership within the unique special population of student-athletes. The creation of the Carolina Leadership Academy (CLA), comprised of a three-tiered formal leadership development curriculum, set UNC apart as a leader in higher education and intercollegiate athletics leadership development programs by helping student-athletes, administrators and coaches understand and foster leadership best practices. This formal leadership curriculum begins with the Carolina CREED program completed by all first year student-athletes at UNC. The intent of this mandatory foundational program is to introduce freshmen to the importance of personal leadership development. Quantitative and qualitative analysis were used to analyze research questions and examine the relationship between gender and student-athletes' perceived effectiveness of the CREED program curriculum components. A survey including twelve five-point Likert-scale and four open-ended questions was electronically transmitted to 211 student-athletes who completed the CREED program in the Spring 2008 semester. Other large universities look to UNC as a model for future leadership programming options. Therefore, these research findings from the Carolina CREED program curriculum will enable other intercollegiate athletic departments nationwide to improve student-athlete first-year leadership development programming