A Research on the Causes of Chinese College Students’ Overall Physique Decline and Physique Promotion Strategies

At present,Chinese colleges and universities are facing the reality of the overall physical decline of college students,and the quality of college physical education has been questioned by all parties.In order to improve the quality of college physical education and strengthen the physique of college students,this paper first studies the causes of the decline of College Students'overall physique.The study found that,in addition to historical and social factors,many practical factors of college physical education,including teaching content,teaching organization form,teachers’quality,teaching evaluation mechanism and hardware facilities construction,have great influences on the improvement of college students’overall physique.Based on the causes of the decline of college students’overall physique,this paper puts forward feasible promotion strategies from the aspects of physical education curriculum,extracurricular sports activities,and physique monitoring.

A comprehensive multi‐hazard risk assessment model for an urban agglomeration with multiple factors

To assist the Department of Emergency Management in understanding the overall risk characteristics and situation of an urban agglomeration for a reasonable risk prevention and control strategy,this study developed a comprehensive multi-hazard risk assessment model for an urban agglomeration with multiple factors.The proposed model includes disaster probability and disaster loss sub-models.The model evaluated four types of disaster risk in urban agglomerations:natural disasters,accidental disasters,public health incidents,and social security incidents.In addition,a variety of factors were integrated into the model,including the socioeconomic foundation of urban agglomerations,the oligopoly effect of core cities,historical disaster losses,the effect of disaster chains,the ability of disaster prevention and mitigation,and intercity coordinated rescue capabilities.Finally,the risk assessment model was applied to the Beijing-Tianjin-Hebei urban agglomeration.The assessment results were compared to the distribution of the new coronavirus pneumonia epidemic in the target urban agglomeration.The results showed that after analyzing the risk characteristics and evaluating the risk levels,the model not only showed the comprehensive risk levels and distribution of urban agglomerations but also revealed the high-risk areas and the key points of risk prevention and control.More importantly,the results obtained through the model can facilitate the strategic planning of disaster prevention and mitigation for urban agglomerations.

Developing the Science Product Algorithm Testbed for Chinese Next-Generation Geostationary Meteorological Satellites：Fengyun-4 Series

Fengyun-4A（FY-4A）, the first of the Chinese next-generation geostationary meteorological satellites, launched in2016, offers several advances over the FY-2： more spectral bands, faster imaging, and infrared hyperspectral measurements. To support the major objective of developing the prototypes of FY-4 science algorithms, two science product algorithm testbeds for imagers and sounders have been developed by the scientists in the FY-4 Algorithm Working Group（AWG）. Both testbeds, written in FORTRAN and C programming languages for Linux or UNIX systems, have been tested successfully by using Intel/g compilers. Some important FY-4 science products, including cloud mask, cloud properties, and temperature profiles, have been retrieved successfully through using a proxy imager, Himawari-8/Advanced Himawari Imager（AHI）, and sounder data, obtained from the Atmospheric Infra Red Sounder, thus demonstrating their robustness. In addition, in early 2016, the FY-4 AWG was developed based on the imager testbed—a near real-time processing system for Himawari-8/AHI data for use by Chinese weather forecasters.Consequently, robust and flexible science product algorithm testbeds have provided essential and productive tools for popularizing FY-4 data and developing substantial improvements in FY-4 products.