Xin Dong

© 2015 Macmillan Publishers Limited. All rights reserved.One of the primary goals of nuclear physics is to understand the force between nucleons, which is a necessary step for understanding the structure of nuclei and how nuclei interact with each other. Rutherford discovered the atomic nucleus in 1911, and the large body of knowledge about the nuclear force that has since been acquired was derived from studies made on nucleons or nuclei. Although antinuclei up to antihelium-4 have been discovered and their masses measured, little is known directly about the nuclear force between antinucleons. Here, we study antiproton pair correlations among data collected by the STAR experiment at the Relativistic Heavy Ion Collider, where gold ions are collided with a centre-of-mass energy of 200 gigaelectronvolts per nucleon pair. Antiprotons are abundantly produced in such collisions, thus making it feasible to study details of the antiproton-antiproton interaction. By applying a technique similar to Hanbury Brown and Twiss intensity interferometry, we show that the force between two antiprotons is attractive. In addition, we report two key parameters that characterize the corresponding strong interaction: the scattering length and the effective range of the interaction. Our measured parameters are consistent within errors with the corresponding values for proton-proton interactions. Our results provide direct information on the interaction between two antiprotons, one of the simplest systems of antinucleons, and so are fundamental to understanding the structure of more-complex antinuclei and their properties.

Smart grids are rolling out internationally, with the United States nearing completion of a significant USD4-plus-billion federal program funded under the American Recovery and Reinvestment Act. The emergence of smart grids is widespread across developed countries. Multiple approaches to analyzing the benefits of smart grids have emerged. The goals of this white paper are to review these approaches and analyze examples of each to highlight their differences, advantages, and disadvantages. This work was conducted under the auspices of a joint U.S.-China research effort, the Climate Change Working Group Implementation Plan, Smart Grid. We present comparative benefits assessments of smart grid demonstrations in the U.S. and China along with a BA of a pilot project in Europe. In the U.S., we assess projects at two sites: the University of California, Irvine campus, which consists of two distinct demonstrations: Southern California Edison’s Irvine Smart Grid Demonstration Project and the UCI campus itself; and the Navy Yard area in Philadelphia, which has been repurposed as a mixed commercial-industrial, and possibly residential, development. In China, we cover several smart-grid aspects of the Sino-Singapore Tianjin Eco-city and the Shenzhen Bay Technology and Ecology City. In Europe, we look at a BA of a pilot smart grid project in the Malagrotta area west of Rome, Italy, contributed by the Joint Research Centre of the European Commission. The Irvine sub-project BAs use the U.S. Department of Energy Smart Grid Computational Tool, which is built on methods developed by the Electric Power Research Institute. The TEC sub-project BAs apply Smart Grid Multi-Criteria Analysis developed by the State Grid Corporation of China based on the analytic hierarchy process with fuzzy logic. The B-TEC and TNY sub-project BAs are evaluated using new approaches developed by those project teams. JRC has adopted an approach similar to EPRI’s but tailored to the Malagrotta distribution grid.

The purpose of this study was to examine the role of personality traits on academic performance. Furthermore, this study also aims at exploring the effects of virtual experience (mediator) and emotional intelligence (moderator) between personality traits and academic performance of the students. The findings imply that personality traits are the strong predictors of better academic performance. However, several personality traits do not have a positive impact on the academic performance. The study further suggests that students who have emotional abilities and virtual experience are more likely to perform well in their academics. The population of this research consists of students in various colleges and universities in developing regions. Thus, the sample consists of bachelor's and master's students. Existing scales are adopted with minor changes to make it more suitable and understandable within the study context. A total of 319 questionnaires were distributed. Among these 365 questionnaires, 234 questionnaires were received and further used for the purpose of data analysis. This shows an encouraging response from the targeted sample. Education and productivity of the students are influenced by their personality as well as their emotional intelligence abilities. The findings imply that being extrovert is a strong predictor of student achievement and should be prioritized in intervention strategies. This personality feature is responsible for performance in addition to virtual learning experience. Despite its low overall relative value, agreeableness is a significant driver of student achievement. Along with ability and aptitude assessments, personality evaluations might be utilized as a secondary screening tool to identify adolescents at risk of underperformance and academic performance failure. Therefore, learning emotional skills would be beneficial to cope the modern challenges of the competitive educational environment. Virtual experience and being emotionally sound can help students to learn quickly and to be more adaptive into the new world of digitalization. The conclusions of the current study have significant consequences for educators and policymakers. They must accept that boosting emotional intelligence levels through teaching or training is a significant objective of contemporary education. The emotional intelligence abilities of the students related to culture may be shown in a variety of ways, from expectations toward students to interpersonal interactions with students, and from teaching techniques to evaluation methods.