Xue Wang

This study examines the impact of mandatory Corporate Social Responsibility reporting on firms’ financial reporting quality using a quasi-natural experiment in China that mandates a subset of firms to report their CSR activities starting in 2008. We find that mandatory CSR disclosure firms constrain earnings management after the policy. The result is robust to a battery of sensitivity tests and more prominent for firms with lower analyst coverage. Further analyses reveal that upward earnings management by mandatory disclosure firms is more likely to be caught after the policy. The findings suggest that mandatory CSR disclosure mitigates information asymmetry by improving financial reporting quality.

Anxiety is one of the most important affective factors affecting college students' foreign language learning. Especially in the Internet age, new teaching ideas and methods bring new load and anxiety to students' psychology. Taking students who attend a college English online course learning as the research object, this paper analyzes the general situation and professional skills of the students' psychological anxiety under the network environment by using the method of investigation and data analysis. It conceives six methods to reduce the students' psychological anxiety according to the reason analysis and summarizes the more effective ways with data mining of another questionnaire. It points out that teachers can advocate the mode of group learning and peer cooperation, strengthen the timeliness and diversity of tests, increase the richness of extracurricular activities, and increase teachers' and students' quality of online teaching and learning to reduce the anxiety of students' foreign language learning in an online teaching environment.

In recent years, the distributed architecture has been widely adopted by security companies with the rapid expansion of their business. A distributed system is comprised of many computing nodes of different components which are connected by high-speed communication networks. With the increasing functionality and complexity of the systems, failures of nodes are inevitable which may result in considerable loss. In order to identify anomalies of the possible failures and enable DevOps engineers to operate in advance, this paper proposes a two-layer prediction architecture based on the monitoring sequences of nodes status. Generally speaking, in the first layer, we make use of EXPoSE anomaly detection technique to derive anomaly scores in constant time which are then used as input data for ensemble learning in the second layer. Experiments are conducted on the data provided by one of the largest security companies, and the results demonstrate the predictability of the proposed approach.

Based on the power basis theory, this study examined the relationship between high-level talents’ perceived overqualification and withdrawal behavior and the mediating role of sense of power. We also analyze the boundary effects of protected values and being trusted. The hypotheses of this study were tested through questionnaires gathered across three phases over 3 months from 371 high-level talents from 6 enterprises, 5 governments, and 13 universities in China. Hierarchical regression analyses and bootstrapping appraisals showed that: POQ has a positive relationship with withdrawal behavior; sense of power mediates the relationship between overqualification and withdrawal behavior, with high POQ resulting in low perceived power, which then reinforces withdrawal behavior; the negative relationship between POQ and sense of power is stronger for high-level talents with high protected value ; the negative relationship between sense of power and withdrawal behavior is stronger for high-level talents with highly being trusted ; moderated-mediation analyses reveal that the mediating effects of sense of power are stronger for employees with high protected values or being trusted. At the end of this study, the theoretical and practical implications are discussed.