Self-serving leadership is a form of unethical leadership behavior that has destructive effect on its targets and the overall organization. Adopting a social cognition perspective, this study expands our knowledge of its adverse effect and the way to mitigate the effect. Integrating two sub-theories of social cognition, we propose a theoretical model wherein self-serving leadership hinders team creativity through psychological safety as well as knowledge hiding, with task interdependence acting as a contextual condition. Results from a sample of 107 R&D (...) teams revealed that self-serving leadership not only reduced team psychological safety, but also induced team knowledge hiding, both of which ultimately affected team creativity. The presence of high task interdependence buffered the destructive effect of self-serving leadership on team creativity via team psychological safety as well as the indirect effect via knowledge hiding. (shrink)

In the course of an immune response, antibodies undergo affinity maturation in order to increase their efficiency in neutralizing foreign invaders. Affinity maturation occurs by the introduction of multiple point mutations in the variable region gene that encodes the antigen binding site. This somatic hypermutation is restricted to immunoglobulin genes and occurs at very high rates. The precise molecular basis of this process remains obscure. However, recent studies using a variety of in vivo and in vitro systems have revealed important (...) regulatory regions, base motifs that are preferred targets of mutation and evidence that transcription may play an active role in hypermutation. BioEssays 20:227–234, 1998. © 1998 John Wiley & Sons, Inc. (shrink)

Recurrent neural network has been widely applied to many sequential tagging tasks such as natural language process and time series analysis, and it has been proved that RNN works well in those areas. In this paper, we propose using RNN with long short-term memory units for server load and performance prediction. Classical methods for performance prediction focus on building relation between performance and time domain, which makes a lot of unrealistic hypotheses. Our model is built based on events, which is (...) the root cause of server performance. We predict the performance of the servers using RNN-LSTM by analyzing the log of servers in data center which contains user’s access sequence. Previous work for workload prediction could not generate detailed simulated workload, which is useful in testing the working condition of servers. Our method provides a new way to reproduce user request sequence to solve this problem by using RNN-LSTM. Experiment result shows that our models get a good performance in generating load and predicting performance on the data set which has been logged in online service. We did experiments with nginx web server and mysql database server, and our methods can been easily applied to other servers in data center. (shrink)

Faced with increasing global environmental problems, organizational scholars and practitioners have increasingly considered how to promote employee pro-environmental behavior. This research seeks to expand our understanding of the facilitators of employee pro-environmental behavior from the perspective of leader expectations. Drawing on behavioral confirmation theory, we propose that leader pro-environmental expectations are expressed in active support for the environment, which subsequently facilitates employee pro-environmental behavior, thus rising to meet the leader's initial expectations. Furthermore, we argue that the above relationship becomes stronger (...) with the increase in employees' pro-environmental self-expectations. Based on data from 197 leader-employee dyads, the results of regression analysis showed that leader pro-environmental expectations are positively related to employee pro-environmental behavior via demonstrated leader support for the environment, and this indirect relationship is positively moderated by employee pro-environmental self-expectations. When an employee holds high pro-environmental expectations for himself or herself, a leader with high pro-environmental expectations will render support for the environment, which ultimately increases employee pro-environmental behavior. Our findings highlight the relevance of incorporating behavioral confirmation theory into the pro-environmental behavior literature and provide valuable insights for managers on how to effectively promote employee pro-environmental behavior. (shrink)

Through the analysis of facial feature extraction technology, this paper designs a lightweight convolutional neural network. The LW-CNN model adopts a separable convolution structure, which can propose more accurate features with fewer parameters and can extract 3D feature points of a human face. In order to enhance the accuracy of feature extraction, a face detection method based on the inverted triangle structure is used to detect the face frame of the images in the training set before the model extracts the (...) features. Aiming at the problem that the feature extraction algorithm based on the difference criterion cannot effectively extract the discriminative information, the Generalized Multiple Maximum Dispersion Difference Criterion and the corresponding feature extraction algorithm are proposed. The algorithm uses the difference criterion instead of the entropy criterion to avoid the “small sample” problem, and the use of QR decomposition can extract more effective discriminative features for facial recognition, while also reducing the computational complexity of feature extraction. Compared with traditional feature extraction methods, GMMSD avoids the problem of “small samples” and does not require preprocessing steps on the samples; it uses QR decomposition to extract features from the original samples and retains the distribution characteristics of the original samples. According to different change matrices, GMMSD can evolve into different feature extraction algorithms, which shows the generalized characteristics of GMMSD. Experiments show that GMMSD can effectively extract facial identification features and improve the accuracy of facial recognition. (shrink)

Cognitive diversity is an important concept stemming from western management research in the 1990s. With the rapid development of science and technology, there is a growing interest in the composition of an academic research team, such as team diversity. However, there is no tool available for measuring team cognitive diversity for academic research teams. Based on Van der Vegt’s theoretical model of TCD, an Academic Research Team Cognitive Diversity Scale is developed and validated for an academic research team in our (...) research with two studies. In Study One, in-depth interviews and panel discussions were conducted to generate a preliminary questionnaire. In Study Two, the questionnaire was administered among academic research teams. Exploratory factor analysis revealed four factors regarding cognitive diversity: the way of thinking, knowledge and skills, the view of the world, and beliefs about what is right and wrong. The factor structure was further validated by confirmatory factor analysis. Moreover, correlation and regression analyses showed that academic research TCD was positively related to team creativity and performance. To sum up, our newly developed 15-item ATCDS is sufficiently reliable and valid to be used for understanding cognitive diversity among academic research teams. (shrink)

Manager stewardship behavior, defined as an ethical initiative whereby managers subjugate their personal interests to protect their organization’s long-term welfare, has been widely considered beneficial for organizations and subordinates. However, is manager stewardship behavior also viewed as good in the eyes of peers? This research examines peer reactions to manager stewardship behavior. Drawing on person perception theory, we expect that a peer may credit and support manager stewardship behavior or stigmatize and undermine it depending on his or her attributions (organizational (...) concern versus impression management). Study 1 (a vignette experiment: _n_ = 200) found that manager stewardship behavior is related to credit evaluation by a peer and subsequently increases peer support and decreases peer undermining when attributed to organizational concern motives; however, it is related to stigma evaluation by a peer and subsequently increases peer undermining and decreases peer support when attributed to impression management motives. Study 2 (_n_ = 221) replicated the results of Study 1 using a field survey design. These findings expand our understanding of the implications of stewardship behavior from a peer perspective and offer insight for managers into how to engage in stewardship behavior wisely. (shrink)

Background: Social, emotional, and behavioral problems in childhood are key predictors of persistent problem behaviors throughout the life courses of individuals. Early parental intervention training, as an important preventive measure, plays a critical role in improving the social, emotional, and behavioral development of children.Method: We conducted a systematic review and meta-analysis to analyze the intervention effects of the latest literature on Triple P, which is a multilevel system that provides treatment and prevention for children at risk of social, emotional, and (...) behavioral problems via parenting approaches to enhance the parenting knowledge, skills, and confidence of parents. Since the literature on Triple P from 1970 to 2012 has already been systematically reviewed, this study searched the literature from 2013 to 2020 from the Web of Science, EBSCO, ERIC, MEDLINE, CNKI, and Triple P Evidence-Base website using multiple search strategies. This study differs from the existing research by its inclusion criteria of studies that use experimental designs or quasi-experimental designs. A total of 37 studies were included in the final analysis, and STATA 16.0 was used for evaluation while RevMan 5.3 for risk of bias assessment.Results: The results show that Triple P can promote the social competence of children and prevent their emotional and behavioral problems to a certain extent. Simultaneously, the proximal effects on parents mainly included changing negative parenting styles, reducing parenting conflicts, and improving parenting efficacy and self-confidence. The distal effects on parents included reducing the psychological adjustment problems of parents, improving parent–child relationships, and reducing parent–child conflict. However, the meta-analysis results did not show a significant effect of Triple P on improving the marital relationship quality and satisfaction of parents. Components of the program intervention, including intervention level, service delivery format, service method, and program implementation setting, and the age of the children were crucial moderating factors on the outcomes of Triple P.Conclusion: This study systematically reviewed the latest Triple P intervention literature and found the significant effectiveness of Triple P on the SEB problems of children and parenting outcomes and the moderators of the effect size. (shrink)

Accurate and rapid defect identification based on pulsed eddy current testing plays an important role in the structural integrity and health monitoring of in-service equipment in the renewable energy system. However, in conventional data-driven defect identification methods, the signal feature extraction is time consuming and requires expert experience. To avoid the difficulty of manual feature extraction and overcome the shortcomings of the classic deep convolutional network, such as large memory and high computational cost, an intelligent defect recognition pipeline based on (...) the general Warblet transform method and optimized two-dimensional DCNN is proposed. The GWT method is used to convert the one-dimensional PECT signal to a 2D grayscale image used as the input of 2D DCNN. A compound method is proposed to optimize the baseline VGG16, a well-known DCNN, from four aspects including reducing the input size, adding batch normalization layer after every convolutional layer and fully connection layer, simplifying the FCs, and removing unimportant filters in Convs so as to reduce memory and computational costs while improving accuracy. Through a pulsed eddy current testing experiment considering interference factors including liftoff and noise, the following conclusion can be obtained. The time-frequency representation obtained by the GWT method not only has excellent ability in terms of the transient component analysis but also is less affected by the reduction of image size; the proposed optimized DCNN can accurately identify defect types without manual feature extraction. And compared to the baseline VGG16, the accuracy obtained by the optimized DCNN is improved by 7%, to about 99.58%, and the memory and computational cost are reduced by 98%. Moreover, compared with other well-known DCNNs, such as GoogLeNet, Inception V3, ResNet50, and AlexNet, the optimized network has significant advantages in terms of accuracy and computational cost, too. (shrink)

The complexity of the Hedgehog (Hh) signaling cascade has increased over the course of evolution; however, it does not suffice to accommodate the dynamic yet robust requirements of differential Hh signaling activity needed for embryonic development and adult homeostatic maintenance. One solution to solve this dilemma is to apply multiple forms of post‐translational modifications (PTMs) to the core Hh signaling components, modulating their abundance, localization, and signaling activity. This review summarizes various forms of protein modifications utilized to regulate Hh signaling, (...) with a special emphasis on crosstalk between different forms of PTMs and their feedback regulation by Hh signaling. (shrink)

Risky driving behavior is a major cause of traffic conflicts, which can develop into road traffic accidents, making the timely and accurate identification of such behavior essential to road safety. A platform was therefore established for analyzing the driving behavior of 20 professional drivers in field tests, in which overclose car following and lane departure were used as typical risky driving behaviors. Characterization parameters for identification were screened and used to determine threshold values and an appropriate time window for identification. (...) A neural network-Bayesian filter identification model was established and data samples were selected to identify risky driving behavior and evaluate the identification efficiency of the model. The results obtained indicated a successful identification rate of 83.6% when the neural network model was solely used to identify risky driving behavior, but this could be increased to 92.46% once corrected by the Bayesian filter. This has important theoretical and practical significance in relation to evaluating the efficiency of existing driver assist systems, as well as the development of future intelligent driving systems. (shrink)

Previous studies only considered the impact of personal or environmental factors on intensive smartphone use separately, while largely ignoring the impact of person-environment fit on it. Drawing on the P-E fit theory, we proposed that perceived overqualification, an indicator of person-job misfit, positively affects intensive smartphone use via job boredom, and affective commitment moderates this indirect effect. We examined our hypotheses using four-wave time-lag data of 450 workers from 62 teams. The results revealed that POQ raised job boredom of an (...) individual and thus increased their intensive smartphone use. In addition, when the affective commitment was high, the indirect effect from POQ to intensive smartphone use via job boredom was weaker. The implications, limitations, and future directions of this research were discussed. (shrink)

Decision-making competence refers to the ability to make better decisions, as defined by decision-making principles posited by models of rational choice. The adult decision-making competence (A-DMC) scale is a relatively mature evaluation tool used for decision-making competence. However, the A-DMC is yet far from other mature psychological evaluation tools, and especially the structure of A-DMC remains unclear. In the current study, we estimated a regularized partial correlation network of decision-making competence in a Chinese sample consisting of 339 adults who were (...) evaluated by the A-DMC, and then the centrality indicators were calculated. The results revealed that all nodes of the decision-making competence networks are positively associated, except for the association of resistance to framing (RF) and resistance to sunk costs (SC). The strongest edge was between RF and applying decision rules (DR; regularized partial correlation = 0.37). The centrality indicators of RF and applying DR were highest, revealing that these two variables may play important roles in the decision-making competence network. Our study conceptualizes the decision-making competence from network perspectives, so as to provide some insights for future researches. (shrink)

GRAS is a recently discovered family of plant-specific proteins that play important regulatory roles in diverse aspects of plant development. Several of the motifs present in the GRAS proteins suggest that they function as transcription factors, although homology-searching programs have revealed no significant similarity to any non-plant proteins. Here we propose that the GRAS proteins are related to the Signal Transducers and Activators of Transcription (STAT) family of proteins. STATs are known in many non-plant species, and act as intracellular intermediaries (...) between extracellular ligands and the transcription and activation of genes. Our hypothesis is that the GRAS proteins perform this function in plants, with mechanisms similar to those of the animal STATs. If true, this hypothesis has important implications for the evolution of phosphotyrosine based signal transduction systems in eukaryotic organisms. BioEssays 22:573–577, 2000. © 2000 John Wiley & Sons, Inc. (shrink)

Specific to the NCSs where sensor signals can be processed centrally, a collaborative design scheme of dynamic game scheduling and advanced control theory was proposed in the present study. Firstly, by using the Jordan standard state space equation of the research object, the three elements of state noncooperative game were built, and the existence and uniqueness of Nash equilibrium solution were verified. In addition, the iterative equation of the scheduling matrix was derived by complying with the designed utility function. Secondly, (...) refer to the number of restricted states the order of sliding mode was determined. And based on it, the corresponding sliding surface was designed. Subsequently, the quadratic optimization theory was adopted to regulate the control value following the implementation of the scheduling strategy to ensure that the control quality was further enhanced in the limited network service. Lastly, a TrueTime simulation example is established to verify the effectiveness of the proposed scheme. (shrink)

The coronavirus disease 2019 pandemic caused by severe acute respiratory syndrome coronavirus 2 is challenging the dental community to an unprecedented degree. Knowledge of the increased risk of infection in dental settings has been disseminated to the public and guidelines have been formulated to assist dental attendance decision-making. However, dental attendance behaviors incompatible with treatment need is not uncommon in clinical settings. Important gaps remain in the knowledge about how psychological factors are affecting dental attendance behaviors during the COVID-19 epidemic. (...) In this cross-sectional study, a questionnaire survey was performed during February and March 2020. A total of 342 and 294 dental patients who attended and avoided dental visits, respectively, were included. The participants were classified into four groups based on dental attendance behavior and emergent/urgent dental treatment need. Bivariate analysis was performed to investigate factors associated with dental attendance. Multivariable logistic regression based on principal component scores was performed to identify major psychological constructs associated with unnecessary dental avoidance and attendance. Among all the factors explored, inability to wear masks during dental treatment was most closely associated with the overall pattern of dental attendance among participants. Multivariable regression suggested that unnecessary dental avoidance was associated with perceived risk of infection in general and in dental settings, perceived impact of COVID-19 and dental problems on general health, and personal traits such as trust and anxiety. Unnecessary dental attendance was associated with optimism toward the epidemic and trust. Multidisciplinary efforts involving dental and medical professionals as well as psychologists are warranted to promote more widespread adoption, among the general public, of dental attendance behaviors compatible with dental treatment need during the COVID-19 epidemic. (shrink)

This comprehensive account of the history of Chinese lexicography is the first book on the subject to be published in English. It traces the development of Chinese lexicography over three millennia, from the Zhou Dynasty to the Qing Dynasty. Revealing how the emergence of lexicographical culture in ancient China was linked to the teaching of ancient characters, it describes the subsequent development of primers, thesauruses, and dictionaries of all major types, including those of dialects and technical terms. These works originated (...) and appeared in ancient China, predating their western counterparts by hundreds of years: and in one form or another most of them remain in use today. (shrink)

This study aims to reveal the impact of proactive personality on career success and the sequential mediation effect of organizational citizenship behavior and task performance on the relationship. Utilizing meta-analytic structural equation modeling technology sampling 101,131 employees from multiple organizations and industries, which deeply decreased sampling error, the results indicated slightly different findings of proactive personality and three types of career success. Specifically, in relation to salary, OCB and task performance independently transmit the effects of proactive personality to subjective career (...) success, but they sequentially mediate this link as well. In regard to subjective career success and promotion, OCB mediates the relationship between proactive personality and promotion. OCB and task performance sequentially mediate these links. We discussed findings cautiously and purpose future research directions. (shrink)

Due to the COVID-19 pandemic, most employees face increasing career-related stress, particularly those who work in multinational corporations, because the international travel constraints prevent them from going back to their families. Hence, it is imperative to investigate the critical impact of employees’ occupational burnout on career-related outcomes. In response, this research explores the moderating effect of OB on the relationships between career competencies and career sustainability. To achieve a more comprehensive understanding of relevant issues, we adopted a mixed-method research design (...) that includes both qualitative and quantitative analyses. Findings indicate that all the three dimensions of CCs were positively related to CS; moreover, OB negatively moderated the individual relationships of CC and BC with CS. The main contribution of this study is to enrich the existing career literature by addressing the critical moderating role of OB in the links of CC and BC individually with CS. Practical implications are also discussed in this study. (shrink)