戈夫曼拟剧理论视角下球场观众暴力动力因素探析

戈夫曼作为符号互动论的代表人物之一,将戏剧语言引入社会学进行研究,提出了拟剧理论;尝试从戈夫曼拟剧理论视角分析球场观众暴力背后的推动力,将“常规程序的破坏”作为事件爆发的前提,具体情境作为事件爆发的起点,将不良互动、领导者等作为事件发生的动力因素,并提出相应的缓解措施应对球场观众暴力事件。     

基于科研机构的绩效考核系统设计

针对中国科学院绩效考核管理实际情况，本文提出了一种绩效考核信息化系统的设计方案。该系统首先根据组织战略目标构建绩效考核指标体系，然后借用信息化手段将此体系固化到信息系统中，并利用联机分析处理和数据挖掘技术为管理者提供有效的决策信息。实际应用结果表明该系统显著提升了绩效考核管理的效率。     

Memory access optimization for particle operations in computational fluid dynamics-discrete element method simulations

Computational Fluid Dynamics – Discrete Element Method is used to model gas-solid systems in several applications in energy, pharmaceutical and petrochemical industries. Computational performance bottlenecks often limit the problem sizes that can be simulated at industrial scale. The data structures used to store several millions of particles in such large-scale simulations have a large memory footprint that does not fit into the processor cache hierarchies on current high-performance-computing platforms, leading to reduced computational performance. This paper specifically addresses this aspect of memory access bottlenecks in industrial scale simulations. The use of space-filling curves to improve memory access patterns is described and their impact on computational performance is quantified in both shared and distributed memory parallelization paradigms. The Morton space filling curve applied to uniform grids and k-dimensional tree partitions are used to reorder the particle data-structure thus improving spatial and temporal locality in memory. The performance impact of these techniques when applied to two benchmark problems, namely the homogeneous-cooling-system and a fluidized-bed, are presented. These optimization techniques lead to approximately two-fold performance improvement in particle focused operations such as neighbor-list creation and data-exchange, with ∼ 1.5 times overall improvement in a fluidization simulation with 1.27 million particles.     

Recent studies on advance spectroscopic techniques for the identification of microorganisms: A review

The continuous development of resistance to antibiotic drugs by microorganisms causes high mortality and morbidity. Pathogens with distinct features and biochemical abilities make them destructive to human health. Therefore, early identification of the pathogen is of substantial importance for quick ailments and healthcare outcomes. Several phenotype methods are used for the identification and resistance determination but most of the conventional procedures are time-consuming, costly, and give qualitative results. Recently, great focus has been made on the utilization of advanced techniques for microbial identification. This review is focused on the research studies performed in the last five years for the identification of microorganisms particularly, bacteria using advanced spectroscopic techniques including mass spectrometry (MS), infrared (IR) spectroscopy, Raman spectroscopy (RS), and nuclear magnetic resonance (NMR) spectroscopy. Among all the techniques, MS techniques, particularly MALDI-TOF/MS have been widely utilized for microbial identification. A total of 44 bacteria i.e., 6 Staphylococcus spp., 3 Enterococcus spp., 6 Bacillus spp., 4 Streptococcus spp., 6 Salmonella spp., and one from each genus including Escherichia, Acinetobacter, Pseudomonas, Proteus, Clostridioides, Candida, Brucella, Burkholderia, Francisella, Yersinia, Moraxella, Vibrio, Shigella, Serratia, Citrobacter, and Haemophilus (spp.) were discussed in the review for their identification using the above-mentioned techniques. Among all the identified microorganisms, 21% of studies have been conducted for the identification of E. coli, 14% for S. aureus followed by 37% for other microorganisms.