X. Wang

This book captures the quintessence of the author’s 20-year career, presenting both unique perspectives and logical arguments. Guided by the Marxist concept of historical materialism, it reveals the function and effect of morality by analyzing and defining the moral domain. Further, it argues that economic development requires moral support by analyzing the inseparable logical connection between economics and morality. Moreover, it investigates moral capital and its route to achieving value multiplication in economic activities, and proposes a practice and evaluation index system for moral capital in enterprises. Combining philosophical analysis and the exploration of practical applications, the book also discusses a basic strategy to help enterprises enrich and manage their moral capital.

In 2015, the Chinese pharmacologist, Tu Youyou, was awarded the Nobel Prize for Physiology or Medicine for the discovery of artemisinin. Traditional Chinese medicine (TCM) was the source of inspiration for Tu's discovery and provides an opportunity for the world to know more about TCM as a source of medical knowledge and practice. In this article, the value of TCM is evaluated from an ethical perspective. The characteristics of ‘jian, bian, yan, lian’ are explored in the way they promote accessibility and economic efficiency for TCM. The article also examines how the increased use and prevalence of TCM reflects the scientific, cultural, and ethical values of TCM and their increasing attraction in meeting major challenges to medicine and health systems currently and in the future. The article discusses safety issues within TCM, which is a controversial area, and also comments on some shortcomings and challenges which pose difficulties for more widespread and greater uptake of TCM‐derived clinical or therapeutic interventions. The article concludes that TCM is generally safe if it is used according to TCM theory and where such applications are cognizant of the strengths and weaknesses of TCM. TCM has important bioethical values which may inform potential measures for meeting challenges facing global health care systems and the article argues that it can have an increasing role in improving human health.

Attentional biases have received considerable focus in research on cognitive biases and body dissatisfaction (BD). However, most work has focused on spatial allocation of attention. The current two experiments employed a rapid serial visual presentation (RSVP) task to investigate the temporal allocation of attention to body-related words among young females with high and low BD. Experiment 1 assessed the stimulus-driven attention of body-related stimuli. Participants identified a neutral second target (T2) as accurately as possible while ignoring the preceding neutral, fat-, or thin-related first target (T1). As expected, we observed spontaneous attentional blink effects elicited by fat- and thin-related T1s among participants with high BD, suggesting enhanced awareness of body-related stimuli even when this information does not have to be identified. Such effects did not emerge among participants without BD. Experimental 2 investigated the goal-directed attention of body-related stimuli, during which participants needed to identify both the T1 and neutral T2. Participants with BD showed reduced attentional blink effects after both fat- and thin-related T1, suggesting facilitated consolidation of body-related information in goal-directed attention among participants with BD. The findings may have important clinical implications for understanding how to decrease and even prevent body image dissatisfaction.

This study examined the cognitive mechanism underlying acute stress in creative cognition among individuals with high and low trait anxiety. Specifically, cognitive inhibition was assessed using the flanker task during acute stress. Fifty-two participants (26 high trait anxiety, 26 low trait anxiety) (mean age = 18.94 years) underwent stress induction via the Trier Social Stress Test (TSST). They all completed the Alternative Uses Test (AUT) and the Remote Associates Test (RAT) before and after the TSST. Biochemical markers (salivary cortisol and salivary alpha amylase) were recorded at regular intervals. The results showed that cognitive inhibition was influenced by trait anxiety and acute stress. Compared to before experiencing acute stress, there was a lack of cognitive inhibition in low trait anxious individuals and they performed better in AUT (fluency) after acute stress, whereas high trait anxious individuals showed a decreased interference effect and reduced performance in AUT (fluency, flexibility, and originality). In the RAT, there were shorter response times and increased accuracy after acute stress in both high and low trait anxiety groups. Thus, we suggest that cognitive control, which modulates changes in acute stress, influences creative cognition. These findings provide evidence that inhibition control mediates the effect of stress on the creativity of individuals with different trait anxiety.

Firms have been increasingly using social commerce platforms to engage with customers and support their brand value co-creation. While social commerce is now bringing a variety of benefits to business, it has also challenged marketing ethics surrounding online consumer privacy. Drawing on the trust-commitment theory, we develop a model that aims to create an ethical and trustworthy social commerce community for brand value co-creation by examining the impacts of online consumer privacy concerns and social interaction constructs on consumers’ psychological reactions. Using an empirical study, we find that: privacy risk, privacy control, and collaborative norms significantly influence consumers’ trust; consumer-peer interaction and collaborative norms are positively related to relationship commitment; and relationship commitment and trust positively affect consumers’ brand value co-creation in the context of social commerce. Theoretical and practical implications are discussed.

The aim of this research is to explore the process linking participative leadership to organizational identification. The study examines the relationship between participative leadership and internal CSR perceptions of employees and also investigates the role that pride in membership plays in the affiliation of CSR perceptions with organizational identification. By studying these relationships, the paper aspires to contemplate new presumed mediators in the association of participative leadership with organizational identification as well as determine a possible novel antecedent of employee CSR perceptions. Empirical evidence is provided from data that was collected through a survey distributed to employees working for small- and medium-sized enterprises in three countries in the Middle East and North Africa regions, particularly the United Arab Emirates, Lebanon, and Tunisia. Findings show that participative leadership leads to positive internal CSR perceptions of employees and that these CSR perceptions lead to pride in membership which, in turn, results in organizational identification. Implications of these findings are also discussed.

In the automatic detection of epileptic seizures, the monitoring of critically ill patients with time varying EEG signals is an essential procedure in intensive care units. There is an increasing interest in using EEG analysis to detect seizure, and in this study we aim to get a better understanding of how to visualize the information in the EEG time-frequency feature, and design and train a novel random forest algorithm for EEG decoding, especially for multiple-levels of illness. Here, we propose an automatic detection framework for epileptic seizure based on multiple time-frequency analysis approaches; it involves a novel random forest model combined with grid search optimization. The short-time Fourier transformation visualizes seizure features after normalization. The dimensionality of features is reduced through principal component analysis before feeding them into the classification model. The training parameters are optimized using grid search optimization to improve detection performance and diagnostic accuracy by in the recognition of three different levels epileptic of conditions (healthy subjects, seizure-free intervals, seizure activity). Our proposed model was used to classify 500 samples of raw EEG data, and multiple cross-validations were adopted to boost the modeling accuracy. Experimental results were evaluated by an accuracy, a confusion matrix, a receiver operating characteristic curve and an area under the curve. The evaluations indicated that our model achieved the more effective classification than some previous typical methods. Such a scheme for computer-assisted clinical diagnosis of seizures has a potential guiding significance, which not only relieves the suffering of patient with epilepsy to improve quality of life, but also helps neurologists reduce their workload.