X. Wang

Based on social information processing theory, we provide a novel theoretical account of how and when leader humor influences subordinate boundary-spanning behavior. We develop a moderated mediation model explicating the mechanism of psychological safety and the boundary condition of subordinate interpersonal influence. Using multiwave data, we tested our research hypotheses with a sample of 452 members from 140 teams in a Chinese information technology company. Results showed that leader humor positively affects subordinate boundary-spanning behavior via increased psychological safety. Moreover, this mediated effect is stronger when subordinates have high interpersonal influence. These findings offer theoretical and practical insights into boundary-spanning activities and leader humor, which we discuss.

This study conceptualized digital competence in line with self-determined theory and investigated how it alongside help-seeking and learning agency collectively preserved university students’ psychological well-being by assisting them to manage cognitive load and academic burnout, as well as increasing their engagement in online learning during the coronavirus disease 2019 pandemic. Moreover, students’ socioeconomic status and demographic variables were examined. Partial least square modeling and cluster analysis were performed on the survey data collected from 695 students. The findings show that mental load and mental effort were positively related to academic burnout, which was significantly negatively associated with student engagement in online learning. Digital competence did not directly affect academic burnout, but indirectly via its counteracting effect on cognitive load. However, help-seeking and agency were not found to be significantly negatively related to cognitive load. Among the three SDT constructs, digital competence demonstrated the greatest positive influence on student engagement. In addition, female students from humanities and social sciences disciplines and lower-income families seemed to demonstrate the weakest digital competence, lowest learning agency, and least help-seeking behaviors. Consequently, they were more vulnerable to high cognitive load and academic burnout, leading to the lowest learning engagement. This study contributes to the ongoing arguments related to the psychological impact of the COVID-19 pandemic and informs the development of efficient interventions that preserve university students’ psychological well-being in online learning.

Background: Trait self-esteem reflects stable self-evaluation, and it affects social interaction patterns. However, whether and how trait self-esteem can be expressed through behaviors are controversial. Considering that facial expressions can effectively convey information related to personal traits, the present study investigated the three-dimensional facial movements related to self-esteem level and the sex differences therein. Methods: The sample comprised 238 participants. Their levels of trait self-esteem were evaluated by employing the Rosenberg Self-Esteem Scale. During self-introductions, their facial movements in 3D space were recorded by Microsoft Kinect. Two-way ANOVA was performed to analyze the effect of self-esteem and gender on 3D facial movements. Additionally, Logistic regression models were established to describe the relationship between 3D facial movements and self-esteem levels in both genders. Results: The results of two-way ANOVA revealed a main effect of trait self-esteem level for cheeks and lips’ movements. Meanwhile, there was a significant interaction between trait self-esteem and gender on the variability of lips’ movements. In addition, the combination of facial movements can effectively identify trait self-esteem in men and women, with 75.5 and 68% accuracy, respectively. Conclusion: The present results suggest that the 3D facial expressions of individuals with different trait self-esteem levels were different, and such difference is affected by gender. Our study explores a possible way in which trait self-esteem plays a role in social interaction and also provides the basis for automatic self-esteem recognition.

Education of Chinese cultural traditions has been endorsed by the central government in Mainland China in recent years. The article presents a study which examined how nationalism advocated in the policy text has been interpreted at the localized level by primary school teachers in Beijing. The study draws on discourse theories as the primary point of reference. The qualitative coding methods and textual analysis were employed to interpret the meanings of 52 interview transcripts of public primary school teachers. The findings reveal a discrepancy between the discourse on nationalism presented by the policy and the discourse used by the respondents. The former exhibited a strong nationalist aspiration. The latter made a discourse of cultural nationalism more explicit, which cherishes the intellectual and esthetic aspects of Chinese cultural heritage, and considers them important in cultivating students’ cultural taste and moral characters. Teachers’ lack of knowledge of the original policy text mi...

The growing Chinese middle class and their accumulation of wealth and economic capital have seen an increasing number of Chinese students pursuing their education in the West. Due to this growing number, motivations behind their decision to study abroad warrant scholarly treatment. This article discusses the motives of Chinese middle-class families and their children in seeking studying abroad. The paper reports on a recent study of 166 students on American campuses from 2017 to 2018. It uses Bourdieusian concepts of capital, habitus, and the idea of social mobility and social reproduction, to understand Chinese middle-class families’ strategic decisions around studying overseas in relation to employability, labour market competitiveness, and family support. Studying abroad, therefore, is construed by Chinese middle class families as a way of pursuing and preserving their social status and social mobility.

With the troubles of core losses and all-state confined to certain limitations which are the innate traits of permanent magnet synchronous motors, this article develops a command filtered adaptive backstepping approach to follow the track of PMSM’s desired rotor position. To begin with, the RBF neural network technique is utilized to get close to the uncharted nonlinear terms which existed in PMSM’s mathematical model. Meanwhile, an advanced adaptive command filter control methodology is constructed to avoid the computing explosion during the process of backstepping design. Furthermore, to make sure that all the state variables are confined into certain ranges, we employed the barrier Lyapunov function at every step of the controllers construction. In addition, an error compensating mechanism is proposed to neutralize filtering errors and only one adaptive law is required. At last, simulation results bear out the superiority of the aforementioned control scheme.

This study takes a holistic view of flow and anti-flow experiences as interactive subsystems in blended English as a foreign language learning and examines the dynamic complex construct in the field of instructed second language acquisition. We first rephrased the 22-item Classroom Flow Questionnaire to better reflect the context of blended EFL learning. The modified CFQ was then administered to 661 first language Chinese EFL learners. A final 14-item Foreign Language Flow Scale was developed based on results from a series of reliability and validity tests. Both exploratory and confirmatory factor analysis results have demonstrated that foreign language learning flow is a three-dimensional construct involving Enjoyment, Boredom, and Anxiety, thus conceptualizing and validating flow as a continuum with both positive and negative ends. Moreover, participants reported that they experienced the lowest degree of enjoyment, while with respect to the negative flow, they almost experienced similar degree of boredom and anxiety. The present study contributes to the development of the conceptual framework for flow in ISLA as well as constructive pedagogical implications for L2 researchers and educators. Suggestions for future research are also provided.

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

Classic of Changes is a Chinese cultural classic born more than 3000 years ago. Its profound philosophical thoughts and the use of divination have brought Classic of Changes to a strong oriental mysticism. The view of the heaven and man of yin and yang and the five elements states of Classic of Changes are completely different from the Western elemental theory of ancient Greece. The latter gave birth to classical and modern scientific theories, and the yin and yang and the eight trigrams symbol has become synonymous with oriental mysticism. In fact, the cosmology of the Holism of Classic of Changes is a precious scientific heritage of mankind. The axiomatization of the symbolic formal system of Classic of Changes aims to unveil the veil of oriental mysticism and provide oriental wisdom for the development of modern science. Transforming the symbolic system of Classic of Changes into a formal axiom system is the crystallization of the fusion of wisdom between the East and the West. The axiomatization of the symbolic formal system of Classic of Changes shows that the oriental and the western scientific tradition harmony but not sameness and there is no conflict. Classic of Changes can also be interpreted by the axiomatic system like Euclid’s Elements. The main contribution of this paper is that the author skillfully uses mathematical language to formulate the system of Classic of Changes, reconstructs the ideological system of Classic of Changes with the axiomatic method and realizes the scientificalization of Chinese classical natural philosophy. The formal axiom system of Classic of Changes may give us such a revelation: the gap between the oriental and western scientific traditions is mainly in the axiomatization, but the lack of oriental scientific tradition may be the bottleneck of the development of modern science.

In this paper, I discussed the possibility to argue for a human right to internet access in Confucian society. I argued firstly that Confucianism could properly accommodate the concept of human rights, even though it does not have an explicit term for it. Secondly, Confucian concept of min xin, as a similar concept of democracy with differences, is used in Confucianism as a normative concept to lay the foundation of the state and legitimatize the governance. Last but not least, I argued that the roles that min xin are supposed to play in reality are never fully carried out due to the specific hierarchical information structure of Confucian society. I proposed that with internet, the concept of min xin would have to be able to play its roles properly. As such, the arguments that disregard internet access by referting to the protection of the Confucian values might not stand.

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.

Nonlinear time series denoising is the prerequisite for extracting effective information from observation sequence. An effective chaotic signal denoising method not only has a good signal-to-noise ratio enhancement performance, but also can remain as a good unpredictable denoised signal. However, the inherent characteristics of chaos, such as extreme sensitivity to initial values and broadband spectrum, pose challenges for noise reduction of polluted chaotic signals. To address these issues, an adaptive smoothing multiscale morphological filtering is proposed to reconstruct chaotic signals. In the process of noise reduction for contaminated chaotic signals, firstly, a multiscale morphological filter is constructed adaptively according to the multiscale permutation entropy of morphological filter residuals, and the contaminated signals are filtered. Secondly, the weight coefficients of scale structural element are calculated by the residual sum of squares operation, and the chaotic signals are reconstructed. Finally, the resampled filter signals are smoothed by cubic B-spline interpolation operation. In the experiment, the Lorenz signal with white Gaussian noise, the measured sunspot, and the chaotic vibration signal are reconstructed by four comparison methods. The test results show that the proposed ASMMF method has obvious advantages in noise suppression and topological trajectory restoration.

Historical progress is a core belief of the Enlightenment and modernity, also a spiritual catalyst of human emancipation in the past centuries. However, due to the naive understanding of scholars and its misuse by political power, the idea of progress has fallen from a realistic political belief in the pursuit of liberty and democracy to a metaphysical faith and a one-sided ideology. Instead of abandoning the concept itself, this paper will provide a new version for progress. In this version, supported theoretically with ideas from a Marxian critique of the paradox of progress in capitalist society and a Habermasian reconstruction of social evolution and progress, progress shall not be understood as an intrinsic trend of history itself, but a “historical-practical project” of humanity. The intent of rewriting progress is to transcend the dilemma between progressivism and catastrophism while at the same time preserving its positive meaning.

ObjectiveThere is little literature on the validity of kurtosis-adjusted noise energy metrics in human studies. Therefore, this study aimed to validate the application of cumulative noise exposure adjusted by kurtosis in evaluating occupational hearing loss associated with non-Gaussian noise among manufacturing workers.MethodsA cross-sectional survey was conducted on 1,558 manufacturing workers exposed to noise from five industries to collect noise exposure and hearing loss data. Both CNE and kurtosis-adjusted CNE were collapsed into 2-dB∙year bins, and the mean noise-induced permanent threshold shifts at 3, 4, and 6 kHz in each bin were calculated. The contributions of CNE and CNE′ to noise-induced hearing loss were compared using the multiple linear regression. The degree of overlap of two linear regression equations was used to evaluate the validity of the CNE′ using a stratified analysis based on age and sex.ResultsMultiple linear regression models showed that after kurtosis adjustment, the standardized regression coefficient of CNE increased from 0.230 to 0.255, and R2 increased from 0.147 to 0.153. The linear relationship between NIPTS346 and CNE′ or CNE showed that the regression line of non-Gaussian noise was closer to that of Gaussian noise when using CNE′ than using CNE. The mean difference in NIPTS346 between the equations of non-Gaussian noise and Gaussian noise was significantly reduced from 4.32 to 1.63 dB HL after kurtosis adjustment. Through a stratified analysis, these significant decreases were observed in male and female workers, and workers aged ≥30 years old.ConclusionAs a noise exposure metric combining noise energy and temporal characteristics, the kurtosis-adjusted-CNE metric was more effective than CNE alone in assessing occupational hearing loss among manufacturing workers in non-Gaussian noise environment. However, more studies are needed to verify the validity of the kurtosis-adjusted-CNE metric.

The direction and specificity of endolysosomal membrane trafficking is tightly regulated by various cytosolic and membrane‐bound factors, including soluble NSF attachment protein receptors (SNAREs), Rab GTPases, and phosphoinositides. Another trafficking regulatory factor is juxta‐organellar Ca2+, which is hypothesized to be released from the lumen of endolysosomes and to be present at higher concentrations near fusion/fission sites. The recent identification and characterization of several Ca2+ channel proteins from endolysosomal membranes has provided a unique opportunity to examine the roles of Ca2+ and Ca2+ channels in the membrane trafficking of endolysosomes. SNAREs, Rab GTPases, and phosphoinositides have been reported to regulate plasma membrane ion channels, thereby suggesting that these trafficking regulators may also modulate endolysosomal dynamics by controlling Ca2+ flux across endolysosomal membranes. In this paper, we discuss the roles of phosphoinositides, Ca2+, and potential interactions between endolysosomal Ca2+ channels and phosphoinositides in endolysosomal dynamics.

ObjectiveBasic combat training is a kind of necessary high-intensity training to help each military recruit convert into a qualified soldier. In China, both the physical fatigue and passive psychological state have been observed in new recruits during BCT. However, after same-intensity training, the degree of fatigue and passive mood vary among recruits. Therefore, this study aimed to explore the effect of BCT on mood state of recruits with different physical fitness levels from a perspective of fatigue.Materials and methodsBefore and after BCT, the degree of fatigue and mood state of participants were evaluated via the Borg Rating of Perceived Exertion Scale and Profile of Mood States Questionnaire immediately after 20 push-ups as RPE and POMS scores [total mood disturbance, passive mood and positive mood ]. The participants were divided into two groups according to the RPE score measured after BCT: group 1: RPE score after BCT < 13 and group 2: RPE score after BCT ≥ 13.ResultA total of 564 recruits were included. After BCT, in group 1, TMD and passive mood Ttension, Tfatigue, Tdepression, Tconfusion declined significantly, but positive mood both increased significantly ; while in group 2, only Tanger and Testeem increased significantly.ConclusionBCT could alleviate passive mood and add to positive mood for recruits with better physical fitness, while had no ameliorative effects on or even deteriorate most of the passive mood for recruits with worse physical fitness.

Linear regression and its variants have been widely used for classification problems. However, they usually predefine a strict binary label matrix which has no freedom to fit the samples. In addition, they cannot deal with complex real-world applications such as the case of face recognition where samples may not be linearly separable owing to varying poses, expressions, and illumination conditions. Therefore, in this paper, we propose the kernel negative ε dragging linear regression method for robust classification on noised and nonlinear data. First, a technique called negative ε dragging is introduced for relaxing class labels and is integrated into the LR model for classification to properly treat the class margin of conventional linear regressions for obtaining robust result. Then, the data is implicitly mapped into a high dimensional kernel space by using the nonlinear mapping determined by a kernel function to make the data more linearly separable. Finally, our obtained KNDLR method is able to partially alleviate the problem of overfitting and can perform classification well for noised and deformable data. Experimental results show that the KNDLR classification algorithm obtains greater generalization performance and leads to better robust classification decision.

Responding to serious environmental problems, requires urgent and fundamental shifts in our day-to-day lifestyles. This paper employs a qualitative, cross-cultural approach to explore people’s subjective self-reflections on their experiences of pro-environmental behavioral spillover in three countries; Brazil, China, and Denmark. Behavioral spillover is an appealing yet elusive phenomenon, but offers a potential way of encouraging wider, voluntary lifestyle shifts beyond the scope of single behavior change interventions. Behavioral spillover theory proposes that engaging in one pro-environmental action can catalyze the performance of others. To date, evidence for the phenomenon has been mixed, and the causal processes governing relationships between behaviors appear complex, inconsistent and only partly understood. This paper addresses a gap in the literature by investigating accounts of behavioral spillover in three diverse cultural settings using qualitative semi-structured interviews. The analysis shows that while around half of participants overall who were questioned recalled spillover effects, the other half had not consciously experienced spillover. There were few significant differences across cultures, though some forms of spillover effects were reported more in some cultures than others. More environmentally-engaged participants across all three countries were significantly more likely to experience spillover than those who were less engaged. Accounts of within-domain spillovers were most commonly reported, mainly comprising waste, resource conservation and consumption-related actions. Accounts of between-domain spillover were very rare. Recollection of contextual and interpersonal spillover effects also emerged from the interviews. Our findings suggest that more conscious behavioral spillover pathways may be limited to those with pre-existing environmental values. Behavioral spillover may comprise multiple pathways incorporating conscious and unconscious processes. We conclude that targeting behavioral catalysts that generate more socially diffuse spillover effects could offer more potential than conventional spillover involving a single individual.

Using U.S. listed firms during the period from 1971 to 2010, this paper investigates the effect of religion on corporate cost behavior. We find that religion mitigates cost stickiness induced by agency or behavioral biases of managers. This result holds for several robustness tests that address endogeneity concerns. The mitigating effect of religion on cost stickiness is through the channel of reducing top managers’ overconfidence and optimistic bias regarding future demand change and promoting managers’ adherence to fiduciary responsibilities and consideration of shareholder benefits. Further evidence shows that the reduction in cost stickiness caused by religion increases firm value. Overall, our findings suggest that religion reduces the wedge between a firm’s actual and optimal resource commitments, which helps to improve firm value and resource allocation efficiency.

Using U.S. listed firms during the period from 1971 to 2010, this paper investigates the effect of religion on corporate cost behavior. We find that religion mitigates cost stickiness induced by agency or behavioral biases of managers. This result holds for several robustness tests that address endogeneity concerns. The mitigating effect of religion on cost stickiness is through the channel of reducing top managers’ overconfidence and optimistic bias regarding future demand change and promoting managers’ adherence to fiduciary responsibilities and consideration of shareholder benefits. Further evidence shows that the reduction in cost stickiness caused by religion increases firm value. Overall, our findings suggest that religion reduces the wedge between a firm’s actual and optimal resource commitments, which helps to improve firm value and resource allocation efficiency.

A nonlinear coupled wing model subject to unknown external disturbances is proposed in this paper. Since the model is modeled by partial differential equations, the traditional control design scheme based on the ordinary differential equation model is not applicable, and the control law design becomes very complex. In this paper, a new antidisturbance boundary control scheme based on a finite time convergent disturbance observer is proposed. The control laws are designed based on the new disturbance observers to make the external disturbance errors converge to zero in a finite time and ensure the uniformly bounded stability of the controlled system. Finally, the effectiveness of the controllers and the finite-time convergence of disturbance errors are verified by the simulation and comparison.