Sequences of individual words make up media reports. And sequences of media reports constitute the power of the news media to influence corporate practices. In this paper, we focus on the micro-foundations of news reports to elaborate how an atmosphere of negative news reports following an initial exposure of corporate pollution activity can help stop such activity through their impact on corporate managers. We extend our understanding of the corporate governance effect of news media by considering two new aspects of (...) reports—one, the proportion of words in negative reports relative to the total number of words in all reports; and two, the geographical origin of news media. We suggest that the more negative the media coverage, and the more local this coverage, the greater the impact on corporations. Our study of news media reports from more than 600 newspaper sources on disciplining pollution activities of listed Chinese firms from 2004 to 2012 provides strong support for our hypotheses. These findings have valuable implications for the handling of pollution issues in transitional economies via the power of news words. (shrink)

For CVaR portfolio nonsmooth optimization problem, we propose an infeasible incremental bundle method on the basis of the improvement function and the main idea of incremental method for solving convex finite min-max problems. The presented algorithm only employs the information of the objective function and one component function of constraint functions to form the approximate model for improvement function. By introducing the aggregate technique, we keep the information of previous iterate points that may be deleted from bundle to overcome the (...) difficulty of numerical computation and storage. Our algorithm does not enforce the feasibility of iterate points and the monotonicity of objective function, and the global convergence of the algorithm is established under mild conditions. Compared with the available results, our method loosens the requirements of computing the whole constraint function, which makes the algorithm easier to implement. (shrink)

Transportation cyber-physical systems are constrained by spatiality and real-time because of their high level of heterogeneity. Therefore, applications like traffic control generally manage moving objects in a single-machine multithreaded manner, whereas suffering from frequent locking operations. To address this problem and improve the throughput of moving object databases, we propose a GPU-accelerated indexing method, based on a grid data structure, combined with quad-trees. We count object movements and decide whether a particular node should be split or be merged on the (...) GPU. In this case, bottlenecked nodes can be translated to quad-tree without interfering with the CPU. Hence, waiting time of other threads caused by locking operations raised by object data updating can be reduced. The method is simple while more adaptive to scenarios where the distribution of moving objects is skewed. It also avoids shortcomings of existing methods with performance bottleneck on the hot area or spending plenty of calculation resources on structure balancing. Experiments suggest that our method shows higher throughput and lower response time than the existing indexing methods. The advantage is even more significant under the skewed distribution of moving objects. (shrink)

Different countries have different education systems and their advantages and disadvantages. It is necessary to optimize their own higher education system and formulate policy plans to fully realize the optimization of the higher education system. For this reason, we propose to establish a continuous evaluation model of higher education health. This study mainly uses principal component analysis and entropy weight method to determine the evaluation model of higher education health status and makes autoregressive moving average model time series analysis based (...) on the higher education evaluation model, which is obtained by studying long-term trends. The future development of education realizes the evaluation of sustainability. For Vietnam, that needs to be adjusted, the evaluation indicators based on the health status of the higher education system in developing countries will be added, tested, and adjusted and combined with the ARMA model prediction to determine the time period for the policy to meet reasonable expectations, and targeted development policies are proposed. Finally, we test the sensitivity of the established model, evaluate and analyze the advantages and disadvantages of the model, And combine the full text analysis to get the final conclusion. (shrink)

The energy hole is a severe problem for underwater acoustic distributed networks in that it affects the normal operations of the network and shortens the network’s life span. To deal with this problem, a loop-free routing control technique is proposed in this paper. The classical shortest-path routing control method is used to generate multiple disjointed routing tables. The residual energy of the nodes and the changing information of the uplink/downlink matrix are added to the data frames for distribution. The source (...) node specifies the routing path to transmit the data frames based on the changing information, and the relay nodes route the data frames strictly according to the routing path designated by the source node. Besides, the energy consumption of the relay node is saved by replying to the pseudo-ACK frame. Simulation experiments are implemented in four typical scenarios, and the results reflect that the proposed technique could extend the network’s life span by approximately 10% when compared to other mature techniques. Besides, it has no other negative effects on the normal operations of the network. (shrink)

Ben shu jie shao le gong zi zhen, wei yuan, yan fu, kang you wei, tan si tong, liang qi chao, chen tian hua, zhang bing lin deng wan qing si xiang jia de zhe xue si xiang.

Ben shu jie shao le gong zi zhen, wei yuan, yan fu, kang you wei, tan si tong, liang qi chao, chen tian hua, zhang bing lin deng wan qing si xiang jia de zhe xue si xiang.

Emotion recognition plays an important part in human-computer interaction. Currently, the main challenge in electroencephalogram -based emotion recognition is the non-stationarity of EEG signals, which causes performance of the trained model decreasing over time. In this paper, we propose a two-level domain adaptation neural network to construct a transfer model for EEG-based emotion recognition. Specifically, deep features from the topological graph, which preserve topological information from EEG signals, are extracted using a deep neural network. These features are then passed through (...) TDANN for two-level domain confusion. The first level uses the maximum mean discrepancy to reduce the distribution discrepancy of deep features between source domain and target domain, and the second uses the domain adversarial neural network to force the deep features closer to their corresponding class centers. We evaluated the domain-transfer performance of the model on both our self-built data set and the public data set SEED. In the cross-day transfer experiment, the ability to accurately discriminate joy from other emotions was high: sadness, anger, and fear on the self-built data set. The accuracy reached 74.93% on the SEED data set. In the cross-subject transfer experiment, the ability to accurately discriminate joy from other emotions was equally high: sadness, anger, and fear on the self-built data set. The average accuracy reached 87.9% on the SEED data set, which was higher than WGAN-DA. The experimental results demonstrate that the proposed TDANN can effectively handle the domain transfer problem in EEG-based emotion recognition. (shrink)

Low frequency oscillation is an important attribute of human brain activity, and the amplitude of low frequency fluctuation is an effective method to reflect the characteristics of low frequency oscillation, which has been widely used in the treatment of brain diseases and other fields. However, due to the low accuracy of the current analysis methods for low frequency signal extraction of ALFF, we propose the Fourier-based synchrosqueezing transform, which is often used in the field of signal processing to extract the (...) ALFF of the low frequency power spectrum of the whole-time dimension. The low frequency characteristics of the extracted signal are compared with those of FSST and fast Fourier transform through the resting-state data. It is clear that the signal extracted by FSST has more low frequency characteristics, which is significantly different from FFT. (shrink)

Conducting emotion analysis and generating users' feedback from social media platforms may help understand their emotional responses to video products, such as a documentary on the lockdown of Wuhan during COVID-19. The results of emotion analysis could be used to make further user recommendations for marketing purposes. In our study, we try to understand how users respond to a documentary through YouTube comments. We chose “The lockdown: One month in Wuhan” YouTube documentary, and applied emotion analysis as well as a (...) machine learning approach to the comments. We first cleaned the data and then introduced an emotion analysis based on the statistical characteristics and lexicon combination. After that, we applied the Latent Dirichlet Allocation topic modeling approach to further generate main topics with keywords from the comments and visualized the distribution by visualizing the topics. The result shows trust, joy, and anticipation are the most prominent emotions dominating the comments. The major three themes, which account for 70% of all comments, are discussing stories about fighting against the virus, medical workers being heroes, and medical workers being respected. Further discussion has been conducted on the changing of different sentiments over time for the ongoing health crisis. This study proves that emotion analysis and LDA topic modeling could be used to generate explanations of users' opinions and feelings about video products, which could support user recommendations in marketing. (shrink)

We examine the dynamics between enforcement actions and the responses from both the board of directors and supervisory boards amid China's governance reform. Rather than examining determinants of fraudulent activities, we investigate, after enforcement actions are imposed, whether the board of directors and supervisory boards react differently, and whether their different reactions play a role in preventing future occurrences of frauds. We find that both boards react to enforcement actions, but only the responses from the board of directors help us (...) curb future enforcements under certain circumstances. The supervisory board fails to play any role in preventing future enforcements, even though it is one of the two monitoring mechanisms in the listed companies. Policy implications are discussed. (shrink)

This work explored the mediating effects of affective commitment on transformational leadership and job performance and job insecurity on transformational leadership and affective commitment. Meanwhile, the inter-relationships between the four verified the mediating effect of affective commitment, including job insecurity. The results were as follows: transformational leadership and job performance were positively related. Transformational leadership was proportional to an emotional commitment. The affective commitment had a positive impact on job performance. Transformational leadership indirectly positively affected job performance through the intermediary (...) effect of affective commitment. Transformational leadership regulated affective commitment through job insecurity. The more job security employees have, the higher the impact of transformational leadership on affective commitment; the lower the contrary. (shrink)

People often judge trustworthiness based on others’ faces (e.g., facial expression and facial gender). However, it is unclear whether social context plays a moderating role in forming trustworthiness judgments. Based on the emotions as social information (EASI) model, differing contexts may impact the effect of facial expression; however, there is no evidence demonstrating that differing contexts will or will not influence the effect of facial gender. In this study, we used two experiments to examine how facial expression and facial gender (...) affect facial trustworthiness judgments and whether the effects on facial trustworthiness judgments are consistent in cooperative and competitive settings. Twenty-seven undergraduates (14 female; Mage = 21.81 years, SD = 2.66) participated in experiment 1. The results showed significant main effects of facial expression and facial gender as well as the interaction between them. To examine the social context effect, 28 undergraduates (18 female; Mage = 20.93 years, SD = 2.94) participated in experiment 2. The results showed the main effects of facial expression, facial gender, and social context. Moreover, there was a significant interaction between facial gender and facial expression and a marginally significant interaction between social context and facial expression. These results suggest that in the process of judging facial trustworthiness, individuals’ judgments are affected by both facial expression and facial gender. Furthermore, the effect of facial gender on facial trustworthiness judgments presents cross-situational stability, and the role of facial expression is influenced by the settings. These findings support and expand the EASI model. (shrink)

Extant literature suggests that firms may gain legitimacy through imitation. But little known is about whom foreign multinational enterprises (MNEs) will imitate, given that they have multiple social referents: home-country peers and host-country industry competitors. Drawing upon category theory, we develop a dynamic imitation model and explicate how MNEs’ categorization process is affected by social activism, which causes the shift from self-categorization to categorical imperative. We investigate this model in the context of MNE philanthropy and propose that the social movement (...) may delegitimize MNEs’ original self-category and change their imitation target. Using a hand-collected dataset of MNEs’ philanthropic donation for the 2008 Sichuan Earthquake in China, we find that MNEs imitate their home-country peers first but shift to host-country industry competitors after an online social movement. This is because the online social movement delegitimizes MNEs as a category and suggests host-country industry peers as the new model for comparison. Further, we find that liability of foreignness impedes whereas firm reputation facilitates an MNE’s adaptation after the online social movement. Our paper contributes to the literatures on MNEs’ imitation behavior and CSR in emerging market. We also contribute to category theory by integrating self-categorization and categorical imperative and highlighting the role of social movements. (shrink)

In the 1920s Heyting attempted at axiomatizing constructive geometry. Recently, von Plato used different concepts to axiomatize it. He used 14 axioms to formulate constructive apartness geometry, seven of which have occurrences of negation. In this paper we show with the help of ANDP, a theorem prover based on natural deduction, that four new axioms without negation, shorter and more intuitive, can replace seven of von Plato's 14 ones. Thus we obtained a near negation-free new system consisting of 11 axioms.

本书讲述了中国传统道德文化治国之道, 强调了传统文化对国家发展的重要性.内容包括: 故国之思, 核心之道, 庙堂之器, 大道之行及复兴之焰五个部分.

Post-stroke depression is a serious complication of stroke that significantly restricts rehabilitation. The use of immersive virtual reality for stroke survivors is promising. Herein, we investigated the effects of a novel immersive virtual reality training system on PSD and explored induced effective connectivity alterations in emotional networks using multivariate Granger causality analysis. Forty-four patients with PSD were equally allocated into an immersive-virtual reality group and a control group. In addition to their usual rehabilitation treatments, the participants in the immersive-virtual reality (...) group participated in an immersive-virtual reality rehabilitation program, while the patients in the control group received 2D virtual reality rehabilitation training. The Hamilton Depression Rating Scale, modified Barthel Index, and resting-state functional magnetic resonance imaging data were collected before and after a 4-week intervention. rsfMRI data were analyzed using multivariate GCA. We found that the immersive virtual reality training was more effective in improving depression in patients with PSD but had no statistically significant improvement in MBI scores compared to the control group. The GCA showed that the following causal connectivities were strengthened after immersive virtual reality training: from the amygdala, insula, middle temporal gyrus, and caudate nucleus to the dorsolateral prefrontal cortex; from the insula to the medial prefrontal cortex; and from the thalamus to the posterior superior temporal sulcus. These causal connectivities were weakened after treatment in the control group. Our results indicated the neurotherapeutic use of immersive virtual reality rehabilitation as an effective non-pharmacological intervention for PSD; the alteration of causal connectivity in emotional networks might constitute the neural mechanisms underlying immersive-virtual reality rehabilitation in PSD. (shrink)

While an increasing number of organizations have introduced artificial intelligence as an important facilitating tool for learning online, the application of artificial intelligence in e-learning has become a hot topic for research in recent years. Over the past few decades, the importance of online learning has also been a concern in many fields, such as technological education, STEAM, AR/VR apps, online learning, amongst others. To effectively explore research trends in this area, the current state of online learning should be understood. (...) Systematic bibliometric analysis can address this problem by providing information on publishing trends and their relevance in various topics. In this study, the literary application of artificial intelligence combined with online learning from 2010 to 2021 was analyzed. In total, 64 articles were collected to analyze the most productive countries, universities, authors, journals and publications in the field of artificial intelligence combined with online learning using VOSviewer through WOS data collection. In addition, the mapping of co-citation and co-occurrence was explored by analyzing a knowledge map. The main objective of this study is to provide an overview of the trends and pathways in artificial intelligence and online learning to help researchers understand global trends and future research directions. (shrink)

We examine enforcement action in China’s emerging markets by focusing on the agents that impose this action and the role played by supervisory boards. Using newly available databases, we find that supervisory boards play an active role when Chinese listed companies face enforcement action. Listed firms with larger supervisory boards are more likely to have more severe sanctions imposed upon them by the China Security Regulatory Commission, and listed companies that face more severe enforcement actions have more supervisory board meetings. (...) Our findings are of interest, as supervisory boards in China are generally perceived to be dysfunctional. This study contributes to the existing literature in three ways. First, we shed light on the effects of supervisory boards whose role in a fraud setting has not yet been examined. Second, the study has important policy implications for governance reform. Finally, our analyses provide the most up-to-date picture of fraud and governance issues in China’s ever-growing markets. (shrink)

This research examines business and psychology students’ attitude toward unethical behavior (measured at Time 1) and their propensity to engage in unethical behavior (measured at Time 1 and at Time 2, 4 weeks later) using a 15-item Unethical Behavior measure with five Factors: Abuse Resources, Not Whistle Blowing, Theft, Corruption, and Deception. Results suggested that male students had stronger unethical attitudes and had higher propensity to engage in unethical behavior than female students. Attitude at Time 1 predicted Propensity at Time (...) 1 accurately for all five factors (concurrent validity): If students consider it to be unethical, then, they are less likely to engage in that unethical behavior. Attitude at Time 1 predicted only Factor Abuse Resources for Propensity at Time 2. Propensity at Time 1 was significantly related to Propensity at Time 2. Attitude at Time 1, Propensity at Time 1, and Propensity at Time 2 had achieved configural and metric measurement invariance across major (business vs. psychology). Thus, researchers may have confidence in using these measures in future research. (shrink)

Does greater CEO power come with more responsibility? Previous scholarly work in this field entails divergent results on this question. Based on the upper echelons theory and CEO power literature, this study aimed to explore the mechanisms underlying how different sources of CEO power, including structural, ownership, expert, and prestige power, affect firms’ corporate social responsibility (CSR) practices and whether such relationships are moderated by firm visibility. Using a panel dataset comprising 6604 yearly observations of Chinese publicly traded firms from (...) 2009 to 2019, we found that structural power is negatively related to CSR practices and that expert power is positively related to CSR practices, whereas ownership power and prestige power have no direct relationship with CSR practices. Our results show that firm visibility weakens the negative relationship between structural power and CSR practices and strengthens the relationship between expert power and CSR practices, respectively. Overall, this study reconciles the mixed results of previous studies on the impact of CEO power on CSR and integrates the effect of firm visibility as a contextual factor. This article concludes with practical recommendations on how to manage CSR engagement. (shrink)

As the aging population, including frail older people, continues to grow in Mainland China, quality of life and end-of-life care for frail older people has attracted much attention. Advance care planning is an effective way to improve end-of-life care for people with advanced diseases, and it is widely used in developed countries; however, it is a new concept in Mainland China. The effects of advance care planning and its acceptability in Mainland China are uncertain because of its culture-sensitive characteristics. The (...) objective of this article is to discuss the serious social issue of caring for frail older people and illustrate the possibility of implementing advance care planning in nursing homes in Mainland China through a review of relevant literature, which will focus on legislation, healthcare system engagement, public engagement, and cultural issues. Recommendations to promote and implement advance care planning include choosing nursing homes as a proper setting, establishing an ethical climate, and enhancing public awareness. (shrink)

Facial expressions of emotion play an important role in human social interactions. However, posed expressions of emotion are not always the same as genuine feelings. Recent research has found that facial expressions are increasingly used as a tool for understanding social interactions instead of personal emotions. Therefore, the credibility assessment of facial expressions, namely, the discrimination of genuine (spontaneous) expressions from posed (deliberate/volitional/deceptive) ones, is a crucial yet challenging task in facial expression understanding. With recent advances in computer vision and (...) machine learning techniques, rapid progress has been made in recent years for automatic detection of genuine and posed facial expressions. This paper presents a general review of the relevant research, including several spontaneous vs. posed (SVP) facial expression databases and various computer vision based detection methods. In addition, a variety of factors that will influence the performance of SVP detection methods are discussed along with open issues and technical challenges in this nascent field. (shrink)

This article proposes an alternative approach in sustainability assessment. The conceptual framework was developed by modifying Ken Wilber's All Quadrants, All Levels (AQAL) approach, and focuses on the inter-relatedness/inter-connection of various perspectives inherent to the concept of sustainability. To look at how our framework can facilitate the practice of sustainability assessment, we apply the framework to examine the relationships between social systems and the environmental changes in the Ili River basin across the period 1900?2008. This approach enables us to investigate (...) the environmental problems of the Ili River basin in a four-quadrant framework, and combine the empirics of quadrants obtained from traditional disciplinary methodologies. The four-quadrant framework adopted in this study illustrates the interlocking relationships among various perspectives of environmental issues in the Ili River basin, namely, physical perspective, personal perspective, cultural perspective, and social perspective. In particular, the protruding development (evolution) of the lower right dimension is the fundamental cause of the environmental degradation and its related social problems in the Ili River basin. Compared to other established approaches in literature that emphasize on the tradeoffs of various perspectives of sustainability, our findings indicate the potential contributions of four-quadrant framework to sustainability assessment through its focus on the inter-relatedness/inter-connection of different perspectives. (shrink)

Selective retrieval of task-relevant information often facilitates memory retention of that information. However, it is still unclear if selective retrieval of task-relevant information can alter memory for task-irrelevant information, and the role of emotional arousal in it. In two experiments, we used emotional and neutral faces as stimuli, and participants were asked to memorise the name (who is this person?) and location (where does he/she come from?) associated with each face in initial study. Then, half of the studied faces were (...) presented as cues, and participants were asked to retrieve the corresponding names (Experiment 1) or locations (Experiment 2). Finally, all the faces were presented and participants were asked to retrieve both the corresponding names and locations. The results of the final test showed that retrieval practice not only enhanced memory of task-relevant information but also enhanced memory of task-irrelevant information. More importantly, negative emotion amplified the retrieval practice effect overall, with a larger retrieval-induced benefit for the negative than neutral condition. These findings demonstrated an emotional arousal amplification effect on retrieval-induced enhancement effects, suggesting that the advantage of the retrieved memory representations can be amplified by emotional arousal even without explicit goals in a task setting. (shrink)