Subjects: Nuclear Science and Technology >> Nuclear Materials and Techniques submitted time 2024-04-20
Abstract： After decades of research, the problems and behavior of the corrosion of reactor alloy materials are well known. However, some problems in corrosion of reactor materials have not been clarified, including the critical corrosion process of the reactor materials under operational conditions, the role of a single factor in the corrosion process, and the prediction of corrosion behaviors of new materials in extreme environments. The density functional theory, which is based on quantum mechanics, can accurately predict the motion process of atoms and the change in the relevant energy within a very short period. The density functional theory has become an important auxiliary method for investigating the corrosion process of reactor alloy materials in recent years and can help solve the above problems. In this paper, two parts are reviewed. The first part introduces the density functional theory and includes the theoretical basis, development process, and mainstream computing software. In the second part, the research status of the density functional theory in the corrosion of reactor alloy materials is reviewed, including the adsorption, separation, combination, and internal diffusion of the reactor alloy material surfaces in the environments of water-cooled reactor, liquid-metal-cooled reactor, and molten salt reactor.
Subjects: Other Disciplines >> Synthetic discipline submitted time 2023-03-28 Cooperative journals: 《中国科学院院刊》
Abstract： Numerous great discoveries have been made in the field of deep space exploration over the past 50 years, and they deepen our knowledge and synergetic comprehension greatly about the Earth, Planets, and the Solar system. The deep space exploration not only acts as impetus to drive the development of modern science and technology, but also fosters the planetary physics as a new interdiscipline. This study analyzes the background and current status for the discipline of planetary physics, and compares the progress made on the planetary physics of China with that of the other well-developed countries. The relationship of the Chinese planetary physics with the other traditional disciplines, like geophysics, space physics etc., as well as with the projects of deep space missions is elaborated. Based on the current status and developing trend of planetary study, this paper presents possible directions as well as instructive suggestions for the development of Chinese planetary physics in the near future.
Subjects: Psychology >> Social Psychology submitted time 2020-05-24
Abstract：人们普遍拥有“期待不朽、被人铭记”的传承动机，文章通过四个实验探讨了该动机如何通过未来自我连续性的影响作用于个体的金融冒险行为。实验1发现传承动机能够提升个体对未来自我的连续性感知。实验2在此基础上发现传承动机会弱化个体金融冒险行为(2a)，并且该效应被自我连续性感知中介(2b)。实验3进一步考察个体社会经济地位对上述中介效应的调节，结果发现上述中介效应只出现在社会经济地位相对较高(vs. 较低)的个体身上。
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Management Psychology submitted time 2019-09-24
Abstract： Idiosyncratic deals (simplified as “i-deals”) refer to personalized employment arrangements in order to meet both employees and their employers’ benefits. Drawing on self-determination theory (SDT), the current study investigated the relationship between i-deals and the two important employee work outcomes (i.e., proactive career behavior and creativity) by focusing on the mediating role of psychological needs satisfaction (i.e., competence need satisfaction, autonomy need satisfaction and relatedness need satisfaction) and the moderating role of workload. Three time points of data were collected from 230 supervisor-subordinate dyads in 40 work teams within Guangzhou and Shenzhen. At Time 1, subordinates reported i-deals and provided demographic information. At Time 2, subordinates responded to measures of workload, competence need satisfaction, autonomy need satisfaction, and relatedness need satisfaction. At Time 3, supervisors rated their subordinates’ creativity, and employees self-reported their own proactive career behavior. Results showed that: (1) i-deals was positively related to all three forms of employees’ psychological needs satisfaction (competence need satisfaction, autonomy need satisfaction, and relatedness need satisfaction); (2) i-deals was positively associated with both employee proactive career behavior and creativity; (3) competence need satisfaction mediated the relationship between i-deals and the two employee work outcomes (i.e., proactive career behavior and creativity), whereas the mediating effect of autonomy and relatedness need satisfaction was not significant; (4) workload strengthened the positive relationship between i-deals and employee competence / autonomy need satisfaction, as well as the indirect effect of i-deals on proactive career behavior and creativity via competence need satisfaction. The current study contributes to the literature in two aspects. First, drawing on SDT, we identified the mediating mechanism of psychological need satisfaction (competence need satisfaction in specific) in understanding the influence of i-deals on employee’s proactive career behavior and creativity. Second, in testing the moderating role of workload on the effects of i-deals and its outcomes, we clarified the boundary condition of the positive effects of i-deals. The theoretical contributions and practical implications of the results were discussed.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-03 Cooperative journals: 《计算机应用研究》
Abstract： Most recommendation systems based on the network structure suffer from lack of diversity, so that a recommendation system of big data based on multi-weight projection of bipartite network is proposed. Firstly, the basic information of datasets is abstracted, items-users lists are applied as an input to Levenshtein Distance algorithm to compute similarity of each property; then, the number of common neighbors of the nodes in the bipartite network, the degree of common neighbors of the nodes in the bipartite network and degree of each node in bipartite network are all computed, triple weights of each side of the bipartite network are computed; lastly, the enhanced bipartite projection technique is adopted to abstract the potential links of the bipartite network to realize the link prediction based on similarity. The experiments based on both of big dataset and small dataset are realized, the results show that the proposed algorithm outperforms different kinds of recommendation systems in terms of accuracy and coverage of recommendation, at the same time, it outperforms the other recommendation system based on network structure.
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