Although the dominant view in the literature suggests that work-related anxiety experienced by employees affects their behavior and performance, little research has focused on how and when leaders’ workplace anxiety affects their followers’ job performance. Drawing from Emotions as Social Information theory, we propose dual mechanisms of cognitive interference and emotional exhaustion to explain the relationship between leader workplace anxiety and subordinate job performance. Specifically, cognitive interference is the mechanism that best explains the link between leader workplace anxiety and follower (...) task performance, while emotional exhaustion is the mechanism that best explains the link between leader workplace anxiety and follower contextual performance. Additionally, we examine how follower epistemic motivation serves as a boundary condition for the effect of leader anxiety on follower performance outcomes. Results from a 2-wave study of 228 leader-follower dyads in a high-tech company mostly supported our theoretical model. We conclude the study with a discussion of the theoretical and practical implications of our findings. (shrink)

This paper argues for a new perspective on Locke's account of toleration by looking at a set of important but neglected arguments for toleration. Standard accounts which view Lockean toleration as justified solely on considerations of conscience fail to explain Locke's preferred form of toleration, the process by which he overcame his earlier objections to toleration, and the importance of considerations regarding the practicability of religious toleration. The paper argues that attention to Locke's political arguments provides a more complete account (...) of his toleration, which integrates his views on toleration with his wider political theory. These political arguments arise from, and are intimately related to this theory of consent and his epistemological views. The political arguments allow Locke to formulate a response to the then prevailing problematique of toleration exemplified by Samuel Parker's objections. These arguments not only establish toleration as a natural right, but also a necessary condition for maintaining legitimate political society. They also explain his intolerance of atheists and Catholics on grounds other than prejudice. (shrink)

Accumulating empirical evidence suggests that anger elicited in one situation can influence trust behaviors in another situation. However, the conditions under which anger influences trust are still unclear. The present study addresses this research gap and examines the ways in which anger influences trust. We hypothesized that the social distance to the trustee, and the trusting person’s gender would moderate the effect of anger on trust. To test this hypothesis, a study using a 2 (Anger vs. Control) × 2 (Low (...) vs. High social distance) × 2 (Men vs. Women) factorial design was conducted in Germany (N= 215) and in China (N= 310). Results reveal that in both countries men’s trust behavior was not influenced by the manipulations (i.e., anger and social distance). The pattern for women, however, differed by country. In Germany, women’s trust to a stranger (i.e., high social distance) was increased by anger; while in China, women’s trust to someone who they have communicated with (i.e., low social distance) was increased by anger. These results indicate that women’s trust levels seem to be more context-sensitive than men’s. (shrink)

The social network in the organizational learning process is a critical knowledge source to realize superior performance. The purpose of this study is to examine the relationship between relational memory, relational embeddedness, and absorptive capacity, and their impact on the relational performance of small and middle enterprises. This study empirically verifies the research framework from 223 Chinese internationalized SMEs. The results confirm previous studies that indicate positive correlations among relational embeddedness, relational memory, and absorptive capacity. The results also indicate that (...) relational embeddedness and relational memory have positive effects on relational performance. The findings show that relational memory plays a mediating role in the relationship between relational embeddedness, absorptive capacity, and relational performance. (shrink)

In Everettian quantum mechanics, justifications for the Born rule appeal to self-locating uncertainty or decision theory. Such justifications have focused exclusively on a pure-state Everettian multiverse, represented by a wave function. Recent works in quantum foundations suggest that it is viable to consider a mixed-state Everettian multiverse, represented by a (mixed-state) density matrix. Here, we develop the conceptual foundations for decoherence and branching in a mixed-state multiverse, and extend arguments for the Born rule to this setting. This extended framework provides (...) a unification of 'classical' and 'quantum' probabilities, and additional theoretical benefits, for the Everettian picture. (shrink)

In this paper we examine how English and Mandarin speakers think about time, and we test how the patterns of thinking in the two groups relate to patterns in linguistic and cultural experience. In Mandarin, vertical spatial metaphors are used more frequently to talk about time than they are in English; English relies primarily on horizontal terms. We present results from two tasks comparing English and Mandarin speakers’ temporal reasoning. The tasks measure how people spatialize time in three-dimensional space, including (...) the sagittal (front/back), transverse (left/right), and vertical (up/down) axes. Results of Experiment 1 show that people automatically create spatial representations in the course of temporal reasoning, and these implicit spatializations differ in accordance with patterns in language, even in a non-linguistic task. Both groups showed evidence of a left-to-right representation of time, in accordance with writing direction, but only Mandarin speakers showed a vertical top-to-bottom pattern for time (congruent with vertical spatiotemporal metaphors in Mandarin). Results of Experiment 2 confirm and extend these findings, showing that bilinguals’ representations of time depend on both long-term and proximal aspects of language experience. Participants who were more proficient in Mandarin were more likely to arrange time vertically (an effect of previous language experience). Further, bilinguals were more likely to arrange time vertically when they were tested in Mandarin than when they were tested in English (an effect of immediate linguistic context). (shrink)

Understanding personality effects and their role in influencing relationship quality, varied according to gender and relationship duration, could help us better understand close relationships. Participants were Chinese dating dyads and were asked to complete both the Big Five Inventory and Perceived Relationship Quality Component scales. Males and those who had a long-term relationship perceived better relationship quality; individuals who scored higher on agreeableness, conscientiousness, openness, and emotional stability enjoyed better relationship quality; gender and/or relationship duration moderated the actor effect of (...) extraversion and the partner effects of conscientiousness, emotional stability, and openness on relationship quality. Regarding the profile similarity, those couples who were more dissimilar in their profile personality had better relationship quality, especially when they were in a relatively long-term relationship. Meanwhile, with an increase in profile similarity, the males’ perceived relationship quality decreased. (shrink)

Background: The work engagement of police officers pertains to social stability and security, as well as to the orderly operation of the political-economic environment. Although there are many studies on work engagement at present, few studies focus on the influencing factors of police officers’ work engagement. According to the job demands-resources model and the conservation of resources theory, organizational job resources (e.g., perceived organizational support) and personal resources (e.g., regulatory emotional self-efficacy) are important factors influencing work engagement. We assume a (...) moderated mediation model in which job satisfaction plays a mediating role in the relationship between perceived organizational support and work engagement, regulatory emotional self-efficacy moderates not only the relationship between perceived organizational support and job satisfaction but also the relationship between job satisfaction and work engagement. Objective and Method: This study explores the drivers of work engagement through perceived organizational support and regulatory emotional self-efficacy among Chinese police officers using a convenient sampling method to administer a questionnaire to 744 Chinese police officers. A mediated model is proposed to investigate the mediating role of job satisfaction and the regulating role of regulatory emotional self-efficacy. Results: Job satisfaction mediated a positive relationship between organizational support and work engagement, and the perceived organizational support-job satisfaction and the job satisfaction-work engagement relationships were positively moderated by regulatory emotional self-efficacy, such that these relationships were stronger at higher levels of regulatory emotional self-efficacy. These findings, have a practical significance for Chinese police officers’ work engagement advancement. (shrink)

Objective: Based on how the identity of doctoral students is recognized and understood in the context of Chinese culture, we developed a doctoral identity scale using both qualitative and quantitative analyses.Methods: The initial project of the Scale was formed through qualitative analyses and expert consultation. Nine hundred and ninety-one doctoral students were officially tested, and 982 valid questionnaires were obtained. They were randomly divided into two parts, and 491 of which were assessed for item Response Theory and exploratory factor analysis (...) and 491 of which were assessed for confirmatory factor analysis. The Subjective Well-Being Scale, the Rosenberg Self-Esteem Scale, and the Psychological Sense of School Membership Scale were used to test its the criterion-related validity. One hundred and forty-one students were selected for retesting after 8 weeks.Results: The doctoral student identity questionnaire consisted of two factors identity exploration and identity commitment, explaining 57% of the total variance. The results of CFA showed that the two-factor model fitted the data well. The two dimensions of the Doctoral Student Identity Scale were significantly and positively correlated with the two dimensions of the SWB scale, the latent factor of the RSE scale, and the latent factor of the PSSM scale. Composite reliability values for exploration and commitment were 0.79 and 0.83 respectively, and the values of McDonald’s omega for exploration and commitment were 0.81 and 0.85 respectively. The test-retest reliability of the total questionnaire was 0.842.Conclusion: The Doctoral Student Identity Scale was developed with good reliability and validity, and can be used as a reliable tool for measuring the doctoral student identity. In addition, the questionnaire will provide corresponding ideas and methods for studying the identity issues of specific groups. (shrink)

Understanding the behavior of consumers and especially the purchase-related behavior has been a focus of research for the past decades. Thus, researchers and practitioners are curious to know how purchase patterns are different under different conditions such as product category, price, feeling, and so on. The primary focus of this study was to examine how the price of the products influences the purchase behavior of consumers across hedonic and utilitarian categories under regulatory focus theory. The secondary insight was to examine (...) how mood can moderate this impact. We conducted three experimental studies to examine these research questions regarding the preference of consumers of hedonic products when the price is low and at different mood conditions in this purchase process. The results confirmed our hypothesis that product category has a significant impact on purchase choice of products and mood can mediate this impact. In the last section, we discussed the theoretical contribution, strategic insights for product designers and marketers, and possible future research directions. (shrink)

Registration of a series of the two-dimensional electron microscope images of the brain tissue into volumetric form is an important technique that can be used for neuronal circuit reconstruction. However, complex appearance changes of neuronal morphology in adjacent sections bring difficulty in finding correct correspondences, making serial section neural image registration challenging. To solve this problem, we consider whether there are such stable "markers" in the neural images to alleviate registration difficulty. In this paper, we employ the spherical deformation model (...) to simulate the local neuron structure and analyze the relationship between registration accuracy and neuronal structure shapes in two adjacent sections. The relevant analysis proves that regular circular structures in the section images are instrumental in seeking robust corresponding relationships. Then, we design a new serial section image registration framework driven by this neuronal morphological model, fully utilizing the characteristics of the anatomical structure of nerve tissue and obtaining more reasonable corresponding relationships. Specifically, we leverage a deep membrane segmentation network and neural morphological physical selection model to select the stable rounded regions in neural images. Then, we combine feature extraction and global optimization of correspondence position to obtain the deformation field of multiple images. Experiments on real and synthetic serial EM section neural image datasets have demonstrated that our proposed method could achieve more reasonable and reliable registration results, outperforming the state-of-the-art approaches in qualitative and quantitative analysis. (shrink)

Several recent studies have found that when the other’s gain is greater, even subjects’ reward may seem like a loss and lead to a negative experience. These studies indicate the complexity of reward evaluation in the context of social comparison. The satisfaction rating of reward outcome not only depends on objective social comparison but also on subjective evaluation. However, less is known about the neural time course of subjective evaluation. Therefore, we employed a 2 × 2 within-subjects factorial design, in (...) which we manipulated the reward distribution for the subjects. Electroencephalography responses were recorded, while two subjects concurrently but independently performed a simple dot-estimation task that entailed monetary rewards. Behavioral results showed that the subjects were more satisfied with the advantageous distribution, regardless of upward or downward comparison. The analysis of event-related potentials revealed that disadvantageous distribution elicited a larger P2 than advantageous distribution, and this effect was not modulated by comparison direction. In contrast, the late positive potential showed an effect of comparison direction independent of subjective evaluation. The data suggest that subjective evaluation acts upon the early stage of reward processing and manifests in the P2 component, whereas social comparison plays a role in the later appraisal process. (shrink)

Exploring a prevalent yet under-researched phenomenon in organizations, we examine the effect of multi-source negative gossip (i.e., gossip from coworkers and supervisors) on targets’ strategic behavioral responses. Drawing on appraisal theory of emotion, we propose that negative gossip from coworkers and supervisors interactively affect targets’ anger and shame. These discrete emotions, in turn, lead to distinct strategic behavioral responses of gossip targets: social undermining and exemplification, respectively. In Study 1, we tested our hypotheses with a three-wave, time-lagged survey among 500 (...) Chinese employees; in Study 2, we conducted a scenario experiment with 479 international employees. Supporting our theorizing, negative gossip from coworkers was associated with stronger feelings of anger when negative gossip from supervisors was lower (vs. higher), which led to social undermining of coworkers. Negative gossip from coworkers was associated with stronger feelings of shame when negative gossip from supervisors was higher (vs. lower), which led to exemplification of socially desirable behavior. Overall, investigating the phenomenon of multi-source gossip within organizations, we document emotional and behavioral responses of targets to multi-source negative gossip and discuss their theoretical and practical implications, as well as future avenues for research. (shrink)

ABSTRACT Public discourse under authoritarian rule is not monolithic. Yet how popular rhetoric engages with the hegemonic rhetoric in the same discursive space remains understudied. This article examines the rhetoric of a standup comedy show in China, streamed online and widely popular among Chinese millennials, to understand how alternative views on social issues can coexist with the hegemonic rhetoric. Using critical discourse analysis, it argues that some standup comedy performances transgress the hegemonic rhetoric of 'positive energy' without outright subversion. Comedians (...) use subversive affirmation, self-deprecation, ambiguity, absurd fantasy, and irony to present alternative viewpoints on social issues of broad interest, such as the neoliberal work culture and gender norms. The subtle yet powerful transgressions introduce previously marginal views into the public discourse, diminishing the aura of wide acceptance and authority assumed by the hegemonic rhetoric. The standup comedy performances thus open up new discursive pathways towards non-state-sanctioned views on important social issues. (shrink)

This project uses machine learning and computer vision techniques and a novel interactive visualization tool to provide street-level characterization of urban spaces such as safety and maintenance in urban neighborhoods. This is achieved by collecting and annotating street-view images, extracting objective metrics through computer vision techniques, and using crowdsourcing to statistically model the perception of subjective metrics such as safety and maintenance. For modeling human perception and scaling it up with a predictive algorithm, we evaluate perception predictions across two points (...) in time separated by economic changes in the urban core of Raleigh, North Carolina, in the aftermath of the 2008 Great Recession. We hypothesize specific socioeconomic processes can be substantially reflected in the built environment of cities and, thus, render themselves visible at the street level. This paper describes the process of incorporating subjective visual ratings across two datasets of temporally separated street-view images, an algorithm, and a visualization tool. This work serves as a case study for utilizing AI and visualization techniques in a richer characterization of urban spaces that includes both objective metrics such as income (that operates at a broader scale) and subjective metrics such as perception of individuals (that operates at a narrower scale at specific locations). We outline an interdisciplinary methodology to test this hypothesis in streetscape data from Raleigh, NC, from 2008 to 2020. We describe the results of training algorithms that utilized image features with crowdsourced human perception ratings. We provide a comparison of the results with income data. The analysis and interpretation of this comparison provide insight into the challenges and opportunities for using AI technology in characterizing changes in urban environments. One challenge is the ability of human domain experts to interpret the output of algorithms through manipulation and to integrate these results into their workflow. This is addressed with a novel interface designed for interactive analysis and visualization. We conclude with a discussion of some of the benefits and limitations of integrating AI models in the human expert’s decision-making process in the presence of both subjective and objective metrics. (shrink)

Judging similarities among objects, events, and experiences is one of the most basic cognitive abilities, allowing us to make predictions and generalizations. The main assumption in similarity judgment is that people selectively attend to salient features of stimuli and judge their similarities on the basis of the common and distinct features of the stimuli. However, it is unclear how people select features from stimuli and how they weigh features. Here, we present a computational method that helps address these questions. Our (...) procedure combines image-processing techniques with a machine-learning algorithm and assesses feature weights that can account for both similarity and categorization judgment data. Our analysis suggests that a small number of local features are particularly important to explain our behavioral data. (shrink)

The green economy is essential in supporting sustainable economic development and relies on talents and technologies. From the perspective of traditional economic theory, this study explores the impact of high-speed rail and innovation on the green economy from the perspectives of talent and technology. Using the data of 281 prefecture-level cities in China from 2008 to 2018, this study constructs empirical models to discuss the driving factors of the green economy. Empirical results show that high-speed rail and innovation can promote (...) the development of a green economy, and the opening of high-speed rail can strengthen the positive association between innovation and a green economy. The accessibility of high-speed rail improves the flow of talent between different cities and greatly stimulates the positive impact of innovation on green economic activities. In the further test, this study explores the impact of high-speed rail and innovation on the green economy from different dimensions, including government policy, economic strength, and administrative level. During China’s 12th Five-Year Plan, high-speed rail and innovation had a positive impact on the green economy, but the impact of innovation can still be significant after this period. Moreover, the opening of high-speed rail may motivate the migration of talents from developed cities to developing ones, while developed cities can rely on technological advantages to support green economic activities. Furthermore, low-administrative level cities will rely on attracting more talents to promote a green economy due to technological disadvantages. Innovation can play a critical role in enhancing the green economy of cities with high administrative levels. Talents and technology are both important to green economic activities, and the construction of high-speed rail changes the impact of technology on the green economy through the flow of talent. Our findings can explain why the opening of high-speed rail can promote the development of a green economy and effectively help governments achieve the goal of sustainable development. (shrink)

This paper examines the effect of financial shared service centers (FSSCs) on corporate misconduct. Using a sample of Chinese public companies with hand-collected FSSC data, we find that the adoption of FSSCs is negatively associated with the likelihood and frequency of corporate misconduct. The results hold to a battery of robustness tests. Moreover, we show that the negative association between FSSCs and corporate misconduct is more pronounced in firms that have no management equity ownership, disclose internal control weaknesses, and have (...) more subsidiaries. Additional analyses indicate that FSSCs can help mitigate both disclosure-related and nondisclosure-related misconduct. (shrink)

In Indian logic, Nigrahasthāna (fault) generally refers to the occasion of defeat in debates. The fundamental theme of Vādanyāya is to discuss the issue of fault in debates. Based on the standpoint of Buddhist logic, Dharmakīrti in Vādanyāya, starting from the argumentative structure and rules of Buddhism, creatively developed the theory of fault in his debate logic, which can also be seen as a revision of the theory of fault in the Nyāya school. Delving into the logic and culture of (...) the Nyāya school, he critically analyzed and accepted various types of faults in the Nyāyan list of faults. Dharmakīrti’s thoughts about fault can be explored from four aspects: first, establishing the logical rationality of debate; second, innovating the classification criteria of faults; third, criticizing the theory of fault in the Nyāya school; and fourth, accepting the reasonable types of faults in the Nyāya school. (shrink)

We report one production and one comprehension experiment investigating the effect of animacy in relative clause attachment in Chinese. Experiment 1 involved a fill-in-the-blank task that manipulated the order of an animate noun phrase in a complex NP construction. The results showed that while low attachment responses exceeded high attachment responses overall (cf. Shen, 2006), a tendency exists to attach a relative clause to an animate NP in Chinese (cf. Desmet et al., 2002). Experiment 2 used a rating task to (...) examine the interplay between animacy and structural information by manipulating the order of the animate NP as well as the relative clause type (i.e., subject vs. object relative clauses). The results showed that the animate NP modification tendency found in Experiment 1 was limited to subject-relative clauses and that no animacy-related effect was found with object-relative clauses. These results are incompatible with purely structural parsing strategies such as Late Closure (Frazier, 1987) and the Predicate Proximity Principle (Gibson et al., 1996). Instead, the current results suggest that attachment ambiguity resolution in Chinese relative clauses is sensitive to animacy as well as structural information. (shrink)

With the development of network technology, many online educational resource platforms have emerged, and the number of resources on these platforms is increasing dramatically. Compared with the traditional resources, the interactive educational resources have hidden interactive information and dynamic content. Only when the users perform interactive operations correctly can they acquire the knowledge conveyed by the resources, which makes it a challenge to help the users understand the general content of resources and find the resources that they are interested in. (...) Therefore, in this paper, we propose a method for generating picture previews of IERs. Firstly, we analyze the file that stores interactive resource information, obtain the interactive elements’ information, extract the dependencies, and generate an operation sequence. Secondly, we execute the operation sequence using an automated software tool to mimic the interaction process between the user and the resource and save the screenshots in the process to generate a picture preview of an IER. We apply this method to a dynamic geometry platform, NetPad, and conduct experiments. Experimental results demonstrate that the method can effectively extract interactive semantic information and simulate the interactive process, and the generated picture previews are of great help to the users to understand the content of IERs. (shrink)

BackgroundMild cognitive impairment is a common neurological disorder. Moxibustion has been shown to be effective in treating MCI, but its therapeutic mechanisms still remain unclear. This study mainly aimed to investigate the modulation effect of moxibustion treatment for patients with MCI by functional magnetic resonance imaging.MethodsA total of 47 patients with MCI and 30 healthy controls participated in resting-state fMRI imaging scans. Patients with MCI were randomly divided into true moxibustion group and sham moxibustion group. The degree centrality approach was (...) applied to distinguish altered brain functions. Correlation analysis was then performed to examine the relationships between the neuroimaging findings and clinical symptoms.ResultsCompared with HCs, patients with MCI mainly showed decreased DC in the left middle frontal cortex and bilateral middle cingulate cortex. After moxibustion treatment, the SHAM group had no significant DC findings, while TRUE group mainly showed significant increased DC in the bilateral MFC and MCC, as well as decreased DC in the left middle occipital cortex. Repeated measures analysis of variance showed significant interactions between the two groups of patients with MCI. In addition, the higher Mini-Mental State Examination score was significantly positively correlated with increased DC in the right MFC and left MCC after moxibustion treatment.ConclusionOur findings demonstrate that the potential value of moxibustion treatment on MCI, which adds new insights into the popular view that moxibustion treatment may slow cognitive decline in patients with MCI. (shrink)

Cardiovascular disease is a major complication of type 2 diabetes mellitus. In addition to traditional risk factors, psychological determinants play an important role in CVD risk. This study applied Deep Neural Network to develop a CVD risk prediction model and explored the bio-psycho-social contributors to the CVD risk among patients with T2DM. From 2017 to 2020, 834 patients with T2DM were recruited from the Department of Endocrinology, Affiliated Hospital of Harbin Medical University, China. In this cross-sectional study, the patients' bio-psycho-social (...) information was collected through clinical examinations and questionnaires. The dataset was randomly split into a 75% train set and a 25% test set. DNN was implemented at the best performance on the train set and applied on the test set. The receiver operating characteristic curve analysis was used to evaluate the model performance. Of participants, 272 were diagnosed with CVD. The developed ensemble model for CVD risk achieved an area under curve score of 0.91, accuracy of 87.50%, sensitivity of 88.06%, and specificity of 87.23%. Among patients with T2DM, the top five predictors in the CVD risk model were body mass index, anxiety, depression, total cholesterol, and systolic blood pressure. In summary, machine learning models can provide an automated identification mechanism for patients at CVD risk. Integrated treatment measures should be taken in health management, including clinical care, mental health improvement, and health behavior promotion. (shrink)

One of the central issues in cognitive science is the nature of human representations. We argue that symbolic representations are essential for capturing human cognitive capabilities. We start by examining some common misconceptions found in discussions of representations and models. Next we examine evidence that symbolic representations are essential for capturing human cognitive capabilities, drawing on the analogy literature. Then we examine fundamental limitations of feature vectors and other distributed representations that, despite their recent successes on various practical problems, suggest (...) that they are insufficient to capture many aspects of human cognition. After that, we describe the implications for cognitive architecture of our view that analogy is central, and we speculate on roles for hybrid approaches. We close with an analogy that might help bridge the gap. (shrink)