X. Wang

Judges tend to discount the opinions of others even though advice is often helpful in improving their accuracy. The present research proposes that this phenomenon of advice discounting results from the judges’ confidence in their initial decision and little trust in advice. Furthermore, the degree of advice discounting may be predicted by the combined roles of confidence and trust. Three studies provide evidence for these hypotheses. Participants were very confident in their initial estimation and had little trust in the advice (study 1). The degree of advice discounting decreased when participants felt less confidence in performing difficult tasks compared with easy tasks (study 2) or when participants placed more trust in advice because the advice was from an expert rather than from a novice (study 3). In addition, confidence and trust predicted the degree of advice discounting across three studies. These findings shed new light on the mechanism underlying advice discounting and advice taking by indicating the combined roles of confidence and trust.

Recently, several studies have demonstrated that tetracyclines, the antibiotics most intensively used in livestock and that are also widely applied in biomedical research, interrupt mitochondrial proteostasis and physiology in animals ranging from round worms, fruit flies, and mice to human cell lines. Importantly, plant chloroplasts, like their mitochondria, are also under certain conditions vulnerable to these and other antibiotics that are leached into our environment. Together these endosymbiotic organelles are not only essential for cellular and organismal homeostasis stricto sensu, but also have an important role to play in the sustainability of our ecosystem as they maintain the delicate balance between autotrophs and heterotrophs, which fix and utilize energy, respectively. Therefore, stricter policies on antibiotic usage are absolutely required as their use in research confounds experimental outcomes, and their uncontrolled applications in medicine and agriculture pose a significant threat to a balanced ecosystem and the well‐being of these endosymbionts that are essential to sustain health.Also watch the Video Abstract.

Managerial myopia occurs when executives value short-term benefits to the extent that firm long-run development will be obstructed. Recent studies have shown that the locality effect plays an important role in managerial myopia—local United States chief executive officers who work near their home states are less likely to behave myopically because of more effective monitoring and greater reputation concern. In an emerging market, government policies play a more important role in the strategic planning enterprises. A local CEO may have better understanding of local government’s policies thus makes less short-term decisions. This article adds to this literature by testing whether local-province CEOs in China, i.e., the CEO’s native place or birthplace is in the same province as her company’s headquarters, are also far-sighted. Using data on 470 publicly listed non-state-owned Chinese firms from 2014 to 2018, supportive evidence has been found that non-local-province CEOs in China tend to cut R&D expenses for beating analyst forecasts, reversing earnings decline, or pursuing higher returns. This article also confirms social capital as one mechanism of Chinese local-province CEOs behaving less myopically. This investigation also adds to the literature by revealing a new mechanism that CEO locality in China has a positive and direct bearing on how governments support corporate innovation.

Knearest neighbor search is an important problem in location-based services and has been well studied on static road networks. However, in real world, road networks are often time-dependent; i.e., the time for traveling through a road always changes over time. Most existing methods forkNN query build various indexes maintaining the shortest distances for some pairs of vertices on static road networks. Unfortunately, these methods cannot be used for the time-dependent road networks because the shortest distances always change over time. To address the problem ofkNN query on time-dependent road networks, we propose a novel voronoi-based index in this paper. Furthermore, we propose a novel balanced tree, namedV-tree, which is a secondary level index on voronoi-based index to make our querying algorithm more efficient. Moreover, we propose an algorithm for preprocessing time-dependent road networks such that the waiting time is not necessary to be considered. We confirm the efficiency of our method through experiments on real-life datasets.

Emotion is fundamental to human experiences influencing our daily activities including cognition, communication, learning, and decision-making, but the effect of emotion on knowledge management in firms receives a little attention, especially in the field of knowledge hiding behaviors. Drawing on the cognitive appraisal theory of stress and coping as a unique theoretical lens to explicate how knowledge hiding behaviors happen, this study investigates the mediating effect of job stress in the relationship between emotional intelligence and knowledge hiding behaviors. We conducted a field study with 193 full-time employees in smart healthcare firms to test our hypotheses. Results supported the mediating effects of job stress in accounting for the relationship between EI and knowledge hiding behaviors. Our study is among the first to examine how emotional intelligence predicts knowledge hiding behaviors. This study contributes to the literature on knowledge management and emotional intelligence.

As the autonomous vehicles technology gradually enters the public eye, understanding consumers' psychological motivations for accepting autonomous vehicles is critical for the development of autonomous vehicles and society. Previously, researchers have explored the determinants of fully autonomous vehicles but the relevant research is far from enough. Moreover, the relationship between anthropomorphism and users' behavior has been ignored to a large extent. Therefore, this study aim to fill the gap by using anthropomorphism and the unified theory of acceptance and use of technology to explore how system attributes and UTAUT attributes influence consumers' acceptance behavior. The data were collected via questionnaire survey conducted in Beijing, China, which can be a promising early adopter of AVs. Structural equation modeling was used to analyze the data. The results reveal that perceived anthropomorphism and perceived intelligence have a direct positive influence on the adoption of AVs; performance expectancy, effort expectancy, and facilitating conditions have an indirect positive influence on intention to adopt AVs. Also, this research contributes to the literature by enriching studies on psychological determinants of autonomous vehicles' adoption by taking an initial step to highlight anthropomorphism perceptions. This can provide managerial implications for policy-makers and businesses on how to effectively allocate resources to enhance autonomous vehicle adoption.

Background and ObjectiveThere is a paucity of research that has explored “False Alarm” mechanisms. In order to remedy this deficiency in knowledge, the present study used event-related potential technology to reveal the mechanisms underlying False Alarm in response to fear stimuli.MethodsThis study selected snakes as experimental materials and the “oddball paradigm” was used to simulate the conditions of False Alarm. The mechanism underlying False Alarm was revealed by comparing cognitive processing similarities and differences between real snakes and toy snakes.ResultsEvent-related potential findings demonstrated that there was no significant difference between N1 and P2 components induced by real and toy snakes in the early processing stage. Compared with toy snakes, real snakes induced smaller N2 amplitude, larger P3 amplitude, and a shorter P3 latency at the late processing stage. The results of brain topographic mapping analysis showed that the brain regions activated by a real or toy snake were basically the same within the time windows of 110–150 and 220–270 ms, respectively. In the time window of 300–360 and 400–500 ms, the degree of brain regions activation with a real snake was significantly greater than that induced by a toy snake.ConclusionFalse Alarm is caused by the brain’s inability to distinguish, in the early stage of cognitive processing, stimulus objects with similar appearances. When the brain is able to distinguish the differences between different stimulus objects in the late stage of cognitive processing, False Alarm disappears.

As of the end of October 2020, the cumulative number of confirmed cases of COVID-19 has exceeded 45 million and the cumulative number of deaths has exceeded 1.1 million all over the world. Faced with the fatal pandemic, countries around the world have taken various prevention and control measures. One of the important issues in epidemic prevention and control is the assessment of the prevention and control effectiveness. Changes in the time series of daily new confirmed cases can reflect the impact of policies in certain regions. In this paper, a smooth transition autoregressive model is applied to investigate the intrinsic changes during the epidemic in certain countries and regions. In order to quantitatively evaluate the influence of the epidemic control measures, the sequence is fitted to the STAR model; then, comparisons between the dates of transition points and those of releasing certain policies are applied. Our model well fits the data. Moreover, the nonlinear smooth function within the STAR model reveals that the implementation of prevention and control policies is effective in some regions with different speeds. However, the ineffectiveness is also revealed and the threat of a second wave had already emerged.

Detecting and correcting execution errors is crucial for safe and efficient goal-directed behavior. Despite intensive investigations on error processing, the cognitive foundations of this process remain unclear. Based on the presumed relation between executive attention and error processing, we implemented a seven-day EA intervention by adopting the Posner cueing paradigm to test the potential causal link from EA to error processing in healthy adults. The experimental group was trained on the Posner cueing paradigm, with a ratio of invalid cue trials to valid cue trials of 5:1 and a corresponding ratio of 1:1 in the active control group. We found that the EA intervention improved EA across intervention sessions. Critically, after the EA intervention, the HEA group showed that post-error accuracy was restored to the same level as the post-correct accuracy. However, post-error slowing and the flanker effect were not modulated by the EA intervention. Furthermore, we observed that the changes in the accuracy of VC trials positively predicted the changes in PEA and that the two groups were classified according to the changes in PEA with a 61.3% accuracy. Based on these results, we propose that EA causally drives error processing. And the capabilities of the “actively catch” more attention resources and the automatic mismatch processing developed after EA intervention is transferable to error processing, thereby directly resulting in the gains in post-error adjustments. Our work informs the potential cognitive mechanisms underlying this causal link.

An integrated hog futures price forecasting model based on whale optimization algorithm, LightGBM, and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise is proposed to overcome the limitations of a single machine learning model with low prediction accuracy and insufficient model stability. The simulation process begins with a grey correlation analysis of the hog futures price index system in order to identify influencing factors; after that, the WOA-LightGBM model is developed, and the WOA algorithm is used to optimize the LightGBM model parameters; and, finally, the residual sequence is decomposed and corrected by using the CEEMDAN method to build a combined WOA-LightGBM-CEEMDAN model. Furthermore, it is used for comparison experiments to check the validity of the model by using data from CSI 300 stock index futures. Based on all experimental results, the proposed combined model shows the highest prediction accuracy, surpassing the comparative model. The model proposed in this study is accurate enough to meet the forecasting accuracy requirements and provides an effective method for forecasting future prices.

The micro-level corporate social responsibility (CSR) literature has underscored the economic benefits of an organization's CSR investments, such as bolstering employees' organizational commitment and improving work performance. Yet, research on the potential influence of CSR in fostering socially oriented outcomes among employees has been rather scarce. This study aims to investigate the influence of CSR on employees' internal whistleblowing behaviors and the underlying mechanisms. A three-time-point survey was distributed across the service, manufacturing, construction, and financial insurance industries in Chinese enterprises. The findings reveal that both internal and external CSR positively impact employees' internal whistleblowing behaviors through the mediating role of moral courage, with internal CSR demonstrating a stronger effect. Organizational loyalty positively moderates the mediating role of moral courage in the relationship between internal CSR/external CSR and internal whistleblowing behaviors. Theoretically, this study presents a pioneering endeavor in establishing the link between CSR and employees' internal whistleblowing behaviors, underscoring the significant role that employees' perceptions of CSR play in enhancing societal well-being and ethical governance. Besides contributing to the micro-level CSR literature, this study also provides practical insights for organizations seeking to leverage CSR as a tool for promoting employees' ethical conduct.

Previous studies that explored the impact of task-related variables on translation performance focused on task complexity but reported inconsistent findings. This study shows that, to understand the effect of task complexity on translation process and its end product, performance in translation tasks of various complexity levels needs to be compared in a specific setting, in which more factors are considered besides task complexity—especially students’ translating self-efficacy belief. Data obtained from screen recording, subjective rating, semi-structured interview, and quality evaluation were triangulated to measure how task complexity influenced the translation performance of Chinese students with high and low TSEB. We found that the complex task led to significantly longer task duration, greater self-reported cognitive effort, lower accuracy, and poorer fluency than the simple one among students, irrespective of their TSEB level. Besides, the high-TSEB group outperformed the low-TSEB group in translation accuracy and fluency in both tasks. However, the interaction effect of task complexity and TSEB was not significant, due possibly to weak problem awareness among students. Our study has implications for effectively designing task complexity, getting the benefits of TSEB, and improving research on translation performance.

In the presence of heterogeneity between the randomized controlled trial (RCT) participants and the target population, evaluating the treatment effect solely based on the RCT often leads to biased quantification of the real-world treatment effect. To address the problem of lack of generalizability for the treatment effect estimated by the RCT sample, we leverage observational studies with large samples that are representative of the target population. This article concerns evaluating treatment effects on survival outcomes for a target population and considers a broad class of estimands that are functionals of treatment-specific survival functions, including differences in survival probability and restricted mean survival times. Motivated by two intuitive but distinct approaches, i.e., imputation based on survival outcome regression and weighting based on inverse probability of sampling, censoring, and treatment assignment, we propose a semiparametric estimator through the guidance of the efficient influence function. The proposed estimator is doubly robust in the sense that it is consistent for the target population estimands if either the survival model or the weighting model is correctly specified and is locally efficient when both are correct. In addition, as an alternative to parametric estimation, we employ the nonparametric method of sieves for flexible and robust estimation of the nuisance functions and show that the resulting estimator retains the root- n n consistency and efficiency, the so-called rate-double robustness. Simulation studies confirm the theoretical properties of the proposed estimator and show that it outperforms competitors. We apply the proposed method to estimate the effect of adjuvant chemotherapy on survival in patients with early-stage resected non-small cell lung cancer.

This study extends regulatory capture theory to investigate how and to what extent a firm’s political and nonpolitical ties jointly influence corporate regulatory participation. In the context of regulatory standards setting, although firms with political ties are better able to promote firm standards into industry regulations, it remains unclear whether the coexistence of firms’ nonpolitical ties (i.e., university ties and interlocked firms in our study) is more or less likely to reduce the effect of political ties. Although corporate leaders with political and nonpolitical ties may provide complementary resources, they may follow different mechanisms to drive firm actions. We, thus, argue that nonpolitical ties likely reduce the effect of political ties on regulatory standards setting. Using a sample of public manufacturing firms in China, we find evidence that supports our predictions. Our study contributes to the regulatory capture literature by redirecting attention to the dynamics of political versus nonpolitical ties.

Most previous empirical studies just addressed the influence of geographical proximity on interactive learning regarding the collaboration between knowledge-intensive business service and manufacturing industries. Drawing upon the social cognitive and knowledge-based perspective, this study bridged the research gaps by investigating the joint effects of geographical proximity and two representative non-geographic-proximities in fostering manufacturing firms’ innovation performance. In terms of the empirical analysis, we applied a research sample that involves the data of various manufacturing industries in 260 cities of China from 2003 to 2014 to test the corresponding hypotheses. Additionally, the Spatial Durbin Model was adopted and the research findings showed that: the geographic and social proximity significantly promote the knowledge transfer from KIBS to manufacturing firms, which further improves the innovation performance of the latter. However, the effect of cognitive proximity presents insignificant; the interactive effect of geographic and social proximity was positively associated with the innovation collaboration between KIBS and manufacturing firms; although the individual effect of cognitive proximity was insignificant, when it interacted with geographic or social proximity, the joint effects were proved to promote the innovation performance of manufacturing firms. This study extends our understanding pertaining to the influencing mechanism of proximity for KIBS and the innovation process. The findings proved that geographic and social proximity are two imperative facilitators of knowledge-creating collaboration, highlighting their indispensable role in moderating and mediating the knowledge transfer of KIBS as well as the innovation performance of manufacturing firms. Notably, cognitive proximity is contingent upon geographic and social proximity on its positive effects on the innovation performance for KIBS and their clients’ collaboration.

Background: With the outbreak of the coronavirus disease 2019 epidemic in China, the general public but also medical staff were confronted with psychological challenges, suffering from the highly infectious and unknown characteristics of COVID-19. In this study, we surveyed psychological symptoms including anxiety, depression, and sleep disorders in medical staff.Method: A questionnaire star/WeChat link-based survey assessing the Generalized Anxiety Disorder 7-item scale, Patient Health Questionnaire-9 depression, the Insomnia Severity Index, Social Support scales in addition to lifestyle, and income level was conducted and included 8,288 medical staff from 24 provinces in China. Pearson Chi-square and Mann-Whitney U-tests were used to evaluate single risk factors and significant differences in psychological symptoms before and during the outbreak of COVID-19. Binary logistic regression analyses were conducted for the risk factors of anxiety, depression, and sleep disorder symptoms.Results: Medical staff had a high incidence of psychological symptoms, which was more prominent during the COVID-19 epidemic. Comparatively, females, nurses, first-line department, never exercised, and low income were risk factors for psychological symptoms. Social support including objective support, subjective support, support utility, and regular sports over 3 times per week were protective and manageable elements that could protect from and manage the psychological symptoms of medical staff.Conclusion: The susceptibility of psychological symptoms among medical staff should be of concern to policymakers and the public in the long-term, and the aggravation of mental health problems of medical staff could be eased by providing adequate social support during and after the COVID-19 outbreak.

Punning is an important means of creating humorous effects by intentionally exploiting semantic ambiguity. Previous psycholinguistic research on puns has mainly focused on the process of meaning retrieval in homograph puns, while it is still not entirely clear how readers dynamically utilize contextual information to understand homophone puns. In the current investigation, 68 native Chinese participants were recruited to read three types of experimental sentences while their eye movements were recorded: the homophone-pun sentences where the less salient homophone was visually presented, the homophone-salient sentences where the salient homophone was used, and the homophone-error sentences where the critical context noun in the homophone puns was replaced with an unrelated word. Humor rating results of the homophone puns and the homophone-salient sentences demonstrated that the less salient homophones rather than the salient ones elicited much larger humor responses when presented visually in the same potential pun context. In addition, the reverse fixation pattern in the homophone area and the spill-over region also suggested that meanings of the salient homophones were more recoverable even when not presented visually. Statistical analyses of the homophone puns and the homophone-error sentences showed that the semantic relatedness between the critical context noun and the less salient homophone could significantly predict the humor rating scores of Chinese readers. Taken together, less salient homophones need to receive more contextual support to balance out the advantages of salient homophones before generating a humorous pun interpretation.

The unprecedented outbreak of the novel coronavirus has led to a great shift toward online retailing and accelerated the need for contactless delivery. This study investigates how technological and health belief factors influence consumer acceptance of autonomous delivery robots. Anchored in four behavioral theories [i.e., technology acceptance model, health belief model, perceived value theory and trust theory], a synthesized model is developed. A total of 500 valid responses were collected through an online questionnaire in Singapore, and structural equation modeling was conducted to examine the responses. The results revealed that perceived ease of use, perceived usefulness, perceived susceptibility, perceived severity, self-efficacy and cues to action have a positive and significant influence on consumers’ perceptions of the value of ADRs. The total effect analysis also showed that perceived VAL strongly affects consumer acceptance of ADRs. Academically, this study introduces both technological and health belief factors to explain consumer acceptance of ADRs. It also provides recommendations for policymakers and autonomous delivery robot developers on policy formulation, public communication, product design and infrastructure development.

BackgroundUsing an effective method for evaluating Institutional Review Board (IRB) performance is essential for ensuring an IRB’s effectiveness, efficiency, and compliance with applicable human research standards and organizational policies. Currently, no empirical research has yet been published in China evaluating IRB performance measures by the use of a standardized tool. This study was therefore conducted to develop a Chinese version of the IRB Researcher Assessment Tool (IRB-RAT), assess the psychometric properties of the Chinese version (IRB-RAT-CV), and validate the tool for use in China.MethodsIn this cultural adaptation, cross-sectional validation study, the IRB-RAT-CV was developed through a back-translation process and then distributed to 587 IRB staff members and researchers in medical institutions and schools in Hunan Province that review biomedical and social-behavioral research. Data from the 470 valid questionnaires collected from participants was used to evaluate the reliability, content validity, and construct validity of the IRB-RAT-CV.ResultsParticipants’ ratings of their ideal and actual IRB as measured by the IRB-RAT-CV achieved Cronbach's alpha 0.989 and 0.992, Spearman-Brown coefficient 0.964 and 0.968, and item-total correlation values ranging from 0.631 to 0.886 and 0.743 to 0.910, respectively.ConclusionThe IRB-RAT-CV is a linguistically and culturally applicable tool for assessing the quality of IRBs in China.

As a traditional clothing symbol that is unique to the Chinese nation, the dragon symbol combines the distinctive features of the Chinese nation, reflecting the depth of mental changes and the historical context of Chinese culture. The image of the dragon has formed a kind of dragon pattern as a certain set of ideas about the culture that encoded all its changes. Therefore, in national clothing the dragon image has been one of the most favorite patterns for thousands of years. With the interweaving of world cultures and the deepening of the concept of clothing design, the dragon pattern will incorporate fresh elements of Western culture while maintaining the essence of traditional Chinese culture, and show a new design image through the utilization of various innovative ideas and design methods. The following methods were used for the study: literature review, field research, analysis of design cases, analysis of fashion trends. Using these methods, the specifics of using dragon designs in the fashion industry in different seasons and years are analyzed, and the trend of their evolution in the field of high fashion is studied. In the article we analyzed modern trends of clothing design and gave their characteristics. The results of the study showed that even in modern youth fashion this national symbol is actively used, which indicates that the patterns and images of the dragon have real applicability and wide prospects of application in modern fashion design. Modern clothing design provides a rich cultural heritage for modern clothing to retain the characteristics of civilization on the basis of continuous innovation. The use of dragon motifs in modern clothing not only meets the aesthetic concepts of modern people, but also adds vitality to clothing design.