The foremost aim of this research was to forecast the performance of three stock market indices using the multilayer perceptron, recurrent neural network, and autoregressive integrated moving average on historical data. Moreover, we compared the extrapolative abilities of a hybrid of ARIMA with MLP and RNN models, which are called ARIMA-MLP and ARIMA-RNN. Because of the complicated and noisy nature of financial data, we combine novel machine-learning techniques such as MLP and RNN with ARIMA model to predict the three stock (...) market data. The data used in this study are taken from the Pakistan Stock Exchange, National Stock Exchange India, and Sri Lanka Stock Exchange. In the case of Pakistan, the findings show that the ARIMA-MLP and ARIMA-RNN beat the individual ARIMA, MLP, and RNN models in terms of accuracy. Similarly, in the case of Sri Lanka and India, the hybrid models show more robustness in terms of forecasting than individual ARIMA, MLP, and RNN models based on root-mean-square error and mean absolute error. Apart from this, ARIMA-MLP outperformed the ARIMA-RNN in the case of Pakistan and India, while in the context of Sri Lanka, ARIMA-RNN beat the ARIMA-MLP in forecasting. Our findings reveal that the hybrid models can be regarded as a suitable option for financial time-series forecasting. (shrink)

This paper presents an active fault-tolerant control strategy for quadrotor helicopters to simultaneously accommodate sensor faults and external disturbances. Unlike most of the existing fault diagnosis and fault-tolerant control schemes for quadrotor helicopters, the proposed fault diagnosis scheme is able to estimate sensor faults while eliminating the effect of external disturbances. Moreover, the proposed fault-tolerant control scheme is capable to eliminate the adverse effect of external disturbances as well by designing a disturbance observer to effectively estimate the unknown external disturbances (...) and integrating with the designed integral sliding-mode controller. In this case, the continuous operation of the quadrotor helicopter is ensured while avoiding the unexpected control chattering. In addition, the stability of the closed-loop system is theoretically proved. Finally, the effectiveness and advantages of the proposed scheme are validated and demonstrated through comparative numerical simulations of the quadrotor helicopter under different faulty and uncertain scenarios. (shrink)

Executive functions are of vital importance in the process of active cognition, which is thought to be associated with the dorsolateral prefrontal cortex. As a valid brain stimulation technology, high-definition transcranial direct current stimulation has been used to optimize cognitive function in healthy adults. Substantial evidence indicates that short-term or single anodal tDCS sessions over the left DLPFC will enhance the performance of executive functions. However, the changes in performance and cortical activation of executive functions after modulation by repeated anodal (...) HD-tDCS is as yet unexplored. This study aims to examine changes in three core components of executive functions produced by nine HD-tDCS sessions, and to use functional near-infrared spectroscopy to bilaterally record DLPFC neural activity. A total of 43 participants were divided randomly into two study groups to complete nine interventions. Our results demonstrate that the enhancement of cognitive flexibility in the anodal group was significantly better than that in the sham group. Additionally, a Stroop effect-related decrease in oxygenated hemoglobin concentration in the DLPFC was observed in the anodal group but not the sham group. In conclusion, our study found that repeated anodal HD-tDCS sessions can significantly promote cognitive flexibility, one of the core components of executive function, and that alterations in DLPFC activation can enhance our understanding of the neuroplastic modifications modulated by HD-tDCS. (shrink)

Although the ethical aspects of transformational leadership have attracted considerable attention, very little is known about followers’ reactions to the moral and immoral conduct of transformational leaders. Against this background, this study examined whether and how transformational leadership interacts with moral and authoritarian leadership behaviors in predicting followers’ in-role and extra-role efforts. Building on attribution theory, we hypothesized that the positive and negative effects of these leadership behaviors would be particularly pronounced for highly transformational leaders given that this leadership style (...) elicits strong attention and sense-making efforts among followers. We tested our model in a sample of 228 individuals comprising 114 leader–follower dyads from a wide range of organizations and industries. In line with our hypotheses, results revealed that for highly transformational leaders, moral leadership behaviors related positively to employees’ in-role and extra-role efforts whereas authoritarian leadership behaviors related negatively to employees’ in-role and extra-role efforts. In contrast, moral and authoritarian leadership behaviors did not significantly affect followers’ reactions to leaders low in transformational leadership. Taken together, these findings suggest that transformational leadership, contrary to its largely positive perception in the literature, can be a rather mixed blessing. Implications for theory, future research, and managerial practice are discussed. (shrink)

In advocating gender equality today, we should not only pay attention to women's social status but also call for the women's psychological identification of class equality. What dominates female class identification? To answer this question, based on the data of the Chinese General Social Survey in 2015, this study constructs a female class identity framework from five aspects: the mother's intergenerational influence, female personal characteristics, lifestyle, gender consciousness, and spouse status. In this study, the ordered logit model is used to (...) empirically analyze the impact of various factors on female class identification, and the results show the following: gender consciousness has a significant impact on female class identification. Lifestyle has a significant impact on the situation of having a spouse. Spouse status has a significant positive effect on female class identification. But the mother's intergenerational influence has no effect on female class identification. Therefore, this paper suggests that we should improve laws and regulations to protect women's normal rights, encourage women to establish an independent and self-improvement character, and enhance the class consciousness of women, especially rural women, in order to achieve the overall improvement of female class and psychological identification. (shrink)

View of future time orientation is a cognitive construct about future time. This view has its unique work of motivation and effect on academic performance. Previous studies have only explored the influence that future time orientation brings to the learning process at a single time, and most of them focus on cross-sectional studies. To further explore the cross-lagged relationship for freshmen between future time orientation and learning engagement during different periods, AMOS 23.0 was performed for cross-lagged analysis in this study (...) to explore the influence and effect among variables of different periods. This research was based on the theory of self-determination to discover the relationship between future time and learning involvement for freshmen in enrollment and the first summer vacation. In this research, there were 1,000 valid samples in the first stage and 840 valid samples in the second stage for the conduction of descriptive statistics, pair t-test, and cross-lagged analysis. The results show that: for learning engagement, freshmen at the end of the first year have a higher average score than at the beginning of the first year. View of students of future time orientation can affect their learning engagement of the future through self-determination of students. At last, we provide some suggestions as references for institutional research and future research. (shrink)

ABSTRACTWhile pedagogical content knowledge has been studied across a wide range of research areas, including science, language teaching and mathematics, there is limited research on the role...

Based on work-family border theory and work-home resource theory, this paper examines the impact of border keeper’s support on work-family enrichment and whether or how work-family boundary flexibility mediates the relationship between border keeper’s support and work-family enrichment. A sample of 504 preschool teachers in Guangdong province, China completed questionnaires. The research results show a two-way process of work-family enrichment for preschool teachers in China. Organizational support was directly and significantly correlated with work-to-family enrichment, and family support was significantly and (...) directly correlated with family-to-work enrichment. Organizational support had no significant positive predictive effect on work boundary flexibility which has a significant positive predictive effect on WFE. Family support had a significant positive predictive effect on family boundary flexibility which had a significant positive predictive effect on the FWE. In addition, the study found that family boundary flexibility mediates the relationships between family support and FWE whereas work boundary flexibility did not mediate the relationships between organizational support and WFE. The above research results are partly consistent with the existing research, and partly inconsistent, which is related to the profound influence of traditional culture in Chinese society and the current situation of preschool teachers in China. Such findings have important implications for improving the work-family enrichment of preschool teachers. (shrink)

This study examines why and when negative workplace gossip promotes self-serving behaviors by the employees being targeted. Using conservation of resources theory, we find that targets tend to increase their political acts as a result of ego depletion triggered by negative gossip. We also show that sensitivity to interpersonal mistreatment and moral disengagement moderate this process. Specifically, we demonstrate that targets with high levels of sensitivity to interpersonal mistreatment are more likely to experience ego depletion, and that targets with high (...) levels of moral disengagement will find it easier to persuade themselves to engage in political acts. We conducted a three-wave time-lagged survey of 265 employees in Guangdong, China, to test our hypotheses. The results support our theoretical model and indicate that COR theory can be used to explain the impacts of negative workplace gossip. Alongside our important and timely theoretical contributions, we provide new perspectives on how managers can avoid or mitigate these political acts. (shrink)

As an important corporate governance mechanism, directors’ and officers’ liability insurance is theoretically associated with corporate financialization because it directly affects incentive constraints and risk preference of enterprise managers. However, whether there is a causal relationship in fact has not been sufficiently empirically investigated. Using a sample of Chinese non-financial listed companies in Shanghai and Shenzhen A-shares from 2008 to 2020, this paper empirically analyzes how corporate subscription to directors’ and officers’ liability insurance affects corporate financialization and examines the mediating (...) role played by risk-taking, financing constraints, and audit quality. The study finds that corporate subscription to D&O insurance increases corporate financialization. In terms of the influential mechanism, subscription to D&O insurance promotes financialization by increasing risk-taking, alleviating financing constraints, and improving audit quality. In addition, the results in the heterogeneity analysis suggest that the promotion of financialization by subscribing to D&O insurance is more significant in state-owned enterprises, growth and decline stage enterprises, and non-dual-employment enterprises. (shrink)

In the recent years, gesture recognition based on the surface electromyography (sEMG) signals has been extensively studied. However, the accuracy and stability of gesture recognition through traditional machine learning algorithms are still insufficient to some actual application scenarios. To enhance this situation, this paper proposed a method combining feature selection and ensemble extreme learning machine (EELM) to improve the recognition performance based on sEMG signals. First, the input sEMG signals are preprocessed and 16 features are then extracted from each channel. (...) Next, features that mostly contribute to the gesture recognition are selected from the extracted features using the recursive feature elimination (RFE) algorithm. Then, several independent ELM base classifiers are established using the selected features. Finally, the recognition results are determined by integrating the results obtained by ELM base classifiers using the majority voting method. The Ninapro DB5 dataset containing 52 different hand movements captured from 10 able-bodied subjects was used to evaluate the performance of the proposed method. The results showed that the proposed method could perform the best (overall average accuracy 77.9%) compared with decision tree (DT), ELM, and random forest (RF) methods. (shrink)

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. (shrink)

Previous studies have shown that the motion intention recognition for lower limb prosthesis mainly focused on the identification of performed gait. However, the bionic prosthesis needs to know the next movement at the beginning of a new gait, especially in complex operation environments. In this paper, an upcoming locomotion prediction scheme via multilevel classifier fusion was proposed for the complex operation. At first, two motion states, including steady state and transient state, were defined. Steady-state recognition was backtracking of a completed (...) gait, which would be used as prior knowledge of motion prediction. In steady-state recognition, surface electromyographic and inertial sensors were fused to improve recognition accuracy; five typical locomotion modes were recognized by random forest classifier with over 97.8% accuracy. The transient state was defined as an observation period at the initial stage of upcoming movement, in which only the sEMG signal was recorded due to the limitation of sliding window length. LightGBM classifier was validated to outperform other methods in the accuracy and prediction time of transient-state recognition. Finally, a simplified HMM model based on prior knowledge and observation result was constructed to predict upcoming locomotion. The results indicated that the locomotion prediction was over 91% accuracy. The proposed scheme implements the locomotion prediction at the initial stage of each gait and provides critical information for the gait control of lower limb prosthesis. (shrink)

Theoretical researchers of manager psychology have excellent potential to extend its research framework to more enterprise application areas, such as innovation, performance, and safety in production. Research in these areas has also been increasing in the past 10 years. Psychological capital is composed of four aspects: self-efficacy, hope, optimism, and tenacity. It plays an essential role in stimulating organizational growth and improving organizational performance. In safety management work, managers, as the core members of the organization, have a relationship between their (...) psychological capital and employees’ safety performance. Nevertheless, the closeness of the relationship between psychological capital and employee safety performance has not been fully demonstrated by academic circles. Based on positive psychology theory, this paper conducts a questionnaire survey of 157 managers and 314 employees related to safety work in manufacturing enterprises. From the new perspective of organizational emotional capability, this paper investigates the complex and extensive social-psychological role in organizations and combs, analyzes, and integrates relevant psychological research to construct the influence mechanism of managers’ psychological capital and employee safety performance. Finally, the three important issues found based on data analysis were: Managers’ psychological capital has a significant positive impact both on employee safety performance and organizational emotional capability; Organizational emotional capability has a significant positive impact on employee safety performance; organizational emotional capability plays a partial mediating role in the relationship between managers’ psychological capital and employee safety performance. (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)

Our prior research demonstrated that the right temporoparietal junction exerted a modulatory role in ingroup bias in emotional mimicry. In this study, two experiments were conducted to further explore whether the rTPJ is a neural region for emotional mimicry or for the modulation of emotional mimicry by group membership in a sham-controlled, double-blinded, between-subject design. Both experiments employed non-invasive transcranial direct current stimulation to temporarily change the cortical excitability over the rTPJ and facial electromyography to measure facial muscle activations as (...) an index of emotional mimicry. After the anodal or sham stimulation, participants in Experiment 1 passively viewed a series of happy clips, while participants in Experiment 2 viewed happy clips performed by ethnic ingroup and outgroup models. fEMG analyses revealed that participants in Experiment 1 showed the same degree of happy mimicry for both tDCS conditions and participants in Experiment 2 showed an ingroup bias in happy mimicry in the sham condition, which disappeared in the anodal condition. Taken together, the present study demonstrated that rTPJ plays a role in the modulation of emotional mimicry by group membership. (shrink)

ObjectiveTo investigate the instant impact of hemodialysis on the cerebral morphological measurements of patients with end-stage renal disease.Materials and methodsTwenty-five patients undergoing maintenance HD and twenty-eight age-, sex-, and education-matched healthy control were included. The HD group and HC group had 3D high-resolution structural magnetic resonance imaging scans twice and once, respectively. Both groups underwent neuropsychologic tests. The morphological measurements of structural MRI were measured using CAT12 and these measures were compared among three groups. The relationship between morphological measures and (...) clinical parameters and neuropsychological tests were investigated through multiple regression analysis.ResultsCompared to the HC group, the cortical thickness before HD significantly decreased in the bilateral temporal lobe and significantly decreased in the left superior temporal gyrus after HD. The cortical thickness significantly increased in the bilateral temporal lobe, frontal lobe and occipital lobe after HD compared to before HD. The sulcus depth in the bilateral insula, frontal lobe, and parietal lobe after HD significantly increased compared to before HD. No significant differences in sulcus depth between HD and HC were detected. After HD, the cortical thickness of the right parsopercularis was positively correlated with the number connection test-A. Cortical thickness in multiple regions were positively correlated with blood flow velocity and cortical thickness in the left parahippocampal gyrus was negatively correlated with ultrafiltration volume. Patients showed better performance in the digit symbol test and line tracing test after HD compared to before HD, but there were no significant differences in the comparison of neuropsychologic tests between patients and HC.ConclusionThe instant morphological changes were captured during a single hemodialysis in HD patients. There was an association between these instant changes in the brain and clinical parameters and neuropsychologic tests. This work implied the instant impact of a single hemodialysis impact on the brain in HD patients. (shrink)

The purpose of this study was to examine the moderating effects of goal orientations and self-efficacy between competitive cognitive anxiety and motor performance under conditions featuring different levels of ego-threat. Eighty-one collegiate-level basketball players completed Sport Competitive Anxiety Test, Ego Orientation in Sport Questionnaire, and General Self-Efficacy Scale prior to the experiment. Athletes participated in two sessions of free-throw tasks. After the first session, which was under a control condition, participants performed in a free-throw competitive session while being provided opponents’ (...) scores that induced different levels of competitive cognitive anxiety. Performance is defined as the accuracy in two free-throw sessions. A hierarchical multiple regression showed that high level of task-orientation and low level of ego-orientation can buffer the impairment of competitive cognitive anxiety on motor performance. The relationship between competitive cognitive anxiety and motor performance did not vary with self-efficacy. An a repeated-measured analysis of covariance after cluster analysis revealed that a high-task/low-ego profile benefited athletes the most regarding the impairment of competitive cognitive anxiety. Together, ego- and task-orientations and “goal profile” moderate the relationship between competitive cognitive anxiety and motor performance; however, self-efficacy may not serve as a moderator variable in between. (shrink)

Although previous research has highlighted the positive effect of leaders’ voluntary workplace green behavior, limited research attention has been given to empirically testing how and when such behavior produces trickle-down effects. Taking a role model perspective and drawing on social identity theory, this research aims to fill this gap by proposing and testing the mechanism and boundary conditions of the influencing processes whereby leaders’ VWGB can trickle down to employees’ pro-environmental behaviors. By theorizing a moderated mediation model, the current research (...) empirically examines the hypotheses by conducting a hierarchical regression analysis. We employed a survey questionnaire research design to collect two waves of multisource data. The data used in the analysis are from survey responses of 313 subordinate-supervisor dyads at two different time points. The results show that leaders’ VWGB can have a trickle-down influence on employees’ task-related pro-environmental behavior and proactive pro-environmental behaviors through their green self-identity and that this trickle-down effect is greater among employees with higher green climate perceptions. Our results reveal the intervening mechanism and boundary condition of leaders’ VWGB by conducting a systematic examination of how this effect trickles down. (shrink)

ObjectivesWuhan is the city where coronavirus disease was first reported and developed into a pandemic. However, the impact of the prolonged COVID-19 pandemic on medical staff burnout remains limited. We aimed to identify the prevalence and major determinants of burnout among medical staff 1 year after the beginning of the COVID-19 pandemic in Wuhan, China.Materials and MethodsA total of 1,602 medical staff from three hospitals in Wuhan, China, were included from November 1–28, 2021. Chi-square tests were conducted to compare the (...) prevalence of burnout across groups based on sociodemographic and professional characteristics. A multivariate analysis was performed using a forward stepwise logistic regression model.ResultsApproximately 37.39% of the medical staff experienced burnout 1 year after COVID-19 pandemic. Emotional exhaustion was the most common symptom of burnout, with 1,422 participants reporting a severe EE. Burnout was associated with insufficient social support and “neutral” or “dissatisfied” patient-physician relationships. Respondents who participated in the care of COVID-19 patients had a higher risk of burnout symptoms than those who did not participate. In particular, mental resilience was negatively associated with burnout among the medical staff.ConclusionNearly two-fifths of the participants had symptoms of burnout, with reduced personal accomplishment being the predominant symptom 1 year after COVID-19. Healthcare organizations should regularly measure and monitor burnout among the medical staff. In addition, creating positive work environments and improving the mental resilience of medical staff may be effective ways to reduce burnout. (shrink)

BackgroundSmartphone addiction has become a social problem that affects peoples’ quality of life and is frequently reported to be correlated with alexithymia, avoidant or anxious attachment styles, and subjective well-being. This study aimed to investigate the relationship between SA and alexithymia, attachment style, and subjective well-being.MethodsA meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The following electronic databases were searched: PubMed, Web of Science, Embase, PsycINFO, PsycArticles, China National Knowledge Infrastructure, WANFANG DATA, and Chongqing (...) VIP Information Co., Ltd.. Stata 16.0 was used to analyze the overall effect and test the moderating effect.ResultsOne hundred and ten studies were included, involving a total of 96,680 participants. SA had a significantly high positive correlation with alexithymia, attachment anxiety, and negative emotions, and a low positive correlation with attachment avoidance. In addition, there was a high negative correlation between SA and subjective well-being and a low negative correlation between SA, life satisfaction, and positive emotions. A moderation analysis revealed that age significantly moderated the relationship between SA and positive emotions. The tools for measuring SA significantly moderated the relationship between SA, alexithymia, attachment anxiety, and subjective well-being. Meanwhile, subjective well-being measurement tools significantly moderated the relationships between SA, subjective well-being, and negative emotions.ConclusionSA was closely related to alexithymia, attachment style, and subjective well-being. In the future, longitudinal research can be conducted to better investigate the dynamic changes in the relationship between them.Systematic review registration[www.crd.york.ac.uk/PROSPERO/], identifier [CRD42022334798]. (shrink)

本书紧扣《论语》的文本,分析了《论语》中孔子的思想观念,力图呈现孔子的思想特质。.

In higher education, student learning satisfaction is a significant predictor of learning that indicates the commitment students have to their learning and future academic achievement. The study combines the social cognitive career theory and the stimulus-organism-response model to explore the psychological cognition and attitudes derived from students during their learning, discusses the pattern of student learning satisfaction enhancement from the aspect of process, and further understands the relationships among social support systems, interaction relationships, self-efficacy, generic skills, and learning satisfaction. In (...) this study, 800 valid copies of questionnaires were collected from 12 universities through purposive sampling, and the structural model was analyzed by partial least squares structural equation modeling. The results showed that the relationships among all the constructs were positive and showed a significant effect; furthermore, the research results showed that self-efficacy and student generic skills had a significantly indirect effect in the model—specifically, a mediating effect. Finally, corresponding theoretical and practical implications were put forward based on the research results. (shrink)

Presently, the State Grid Corporation of China has accumulated a large amount of maintenance records for power primary equipment. Unfortunately, most of these records are unstructured data which lead to difficultly analyze and utilize them. The emergence of natural language processing technology and deep learning methods provide a solution for unstructured text data. This paper proposes a progressive multitype feature fusion model to recognize Chinese named entity of unstructured maintenance records for power primary equipment. Firstly, the textual characteristics and word (...) separation difficulties of maintenance records are analyzed, then 7 main entity categories of power technical terms from unstructured maintenance records are chosen, and 3452 maintenance records are labeled by these categories, which is so called EPE-MR training dataset. Secondly, the standard test reports, standard maintenance, and fault analysis reports for three types of power primary equipment are employed as corpus to train character embedding in order to obtain certain words representation ability of maintenance records. After that, progressive multilevel radicals feature extraction module is designed to get detailed and fine semantic information in a hierarchical manner. Further, radicals feature representation and character embedding are concatenated and sent to BiLSTM module to extract contextual information in order to improve Chinese entity recognition ability. Moreover, CRF is introduced to handle the dependencies among prediction labels and to output the optimal prediction sequence, which can easily obtain structured data of maintenance records. Finally, comparative experiments on public MSRA dataset, China People’s Daily corpus, and EPE-MR dataset are implemented, respectively, which show the effectiveness of the proposed method. (shrink)

Longitudinal diagnostic classification models (DCMs) with hierarchical attributes can characterize learning trajectories in terms of the transition between attribute profiles for formative assessment. A longitudinal DCM for hierarchical attributes was proposed by imposing model constraints on the transition DCM. To facilitate the applications of longitudinal DCMs, this paper explored the critical topic of the Q-matrix design with a simulation study. The results suggest that including the transpose of the R-matrix in the Q-matrix improved the classification accuracy; ten-item tests measuring three (...) linear attributes across three time points provided satisfactory classification accuracy for low-stakes assessment. Educational implications and future directions were discussed. (shrink)