A Second Look at Single Photon Production in S+Au Collisions at 200 A⋅\cdotGeV and Implications for Quark Hadron Phase Transition

We reanalyze the production of single photons in S+Au collisions at CERN SPS to investigate: i) the consequences of using a much richer equation of state for hadrons than the one used in an earlier study by us; and, ii) to see if the recent estimates of photon production in quark-matter (at two loop level) by Aurenche et al. are consistent with the upper limit of the photon production measured by the WA80 experiment. We find that the measured upper limit is consistent with a quark hadron phase transition. The measured upper limit is also consistent with a scenario where no phase transition takes place, but where the hadronic matter reaches a density of several hadrons per unit volume; which is rather unphysical.Comment: 10 pages, including 3 figures; Submitted to Euro. Phys. Jour.

Predicting Multi-actor collaborations using Hypergraphs

Social networks are now ubiquitous and most of them contain interactions involving multiple actors (groups) like author collaborations, teams or emails in an organizations, etc. Hypergraphs are natural structures to effectively capture multi-actor interactions which conventional dyadic graphs fail to capture. In this work the problem of predicting collaborations is addressed while modeling the collaboration network as a hypergraph network. The problem of predicting future multi-actor collaboration is mapped to hyperedge prediction problem. Given that the higher order edge prediction is an inherently hard problem, in this work we restrict to the task of predicting edges (collaborations) that have already been observed in past. In this work, we propose a novel use of hyperincidence temporal tensors to capture time varying hypergraphs and provides a tensor decomposition based prediction algorithm. We quantitatively compare the performance of the hypergraphs based approach with the conventional dyadic graph based approach. Our hypothesis that hypergraphs preserve the information that simple graphs destroy is corroborated by experiments using author collaboration network from the DBLP dataset. Our results demonstrate the strength of hypergraph based approach to predict higher order collaborations (size>4) which is very difficult using dyadic graph based approach. Moreover, while predicting collaborations of size>2 hypergraphs in most cases provide better results with an average increase of approx. 45% in F-Score for different sizes = {3,4,5,6,7}

Study on the knowledge of school girls regarding menstrual and reproductive health and their perceptions about family life education program

Background: The doctors of The Obstetric and Gynecological Society of Bhopal and the department of Obstetrics and Gynecology, Gandhi Medical College, Bhopal have been imparting Family Life Education to school girls and aganwadis as part of their school health program. This project was designed to evaluate the effect of school health programs and to gain an insight into the perceptions of the school girls regarding menstruation, hygiene, nutrition, marriage and the program.Methods: The study was conducted in five schools in which 537 girls participated. A questionnaire was provided to the school girls to know their knowledge and perception regarding menstruation, reproduction, nutrition and their views on the quality and usefulness of the Family life skills sessions.Results: The study showed that most of the girls gained information about menstruation from their mothers. Menstruation is still considered as something shameful and young girls face many restrictions. Knowledge regarding menstruation, reproduction, contraception and diet is still lacking among the school girls. Family life skill sessions address these issues very effectively. Most of the girls enjoyed the sessions and were ready for more.Conclusions: The Family Life sessions provide age appropriate, uniform skilled advice on nutrition, prevention of anemia, hygiene (menstrual), problems of growing years, career counseling, safe sex, contraception, teenage pregnancy and exclusive breastfeeding. Imparting family life skills to school girls provides a welcome platform for them to interact with doctors and counsellors, increasing their knowledge on health issues like menstruation, hygiene and nutrition

Technology Commercialization: Indian University Perspective

Technology transfer is the complete, enabling disclosure of advancement in Science and technology, sufficient for its unfettered use and improvement. Universities and institutions of high end research and learning are the focus of such knowledge economy. University- industry partnerships in the field of Science and technology are complex and develop through a large number of mechanisms. The protection and the licensing mechanism of Intellectual property rights at such institutions are the focus of attention of the policy makers at all levels, including the Parliament, wherein a bill has been passed recently, PFIP Bill,2010, which emulates the technology commercialization at US University through Bayh Dole Act. A detailed commercialization process has been evaluated and the success of such technology transfer analysis and commercialization has been reviewed with reference to controlling parameters and revenue being generate