The study of voice behavior examines the inclination of staff and team members to speak up and contribute ideas to the team. In this article, we investigate how factors such as leader-member exchange (LMX), psychological safety and psychological empowerment influence such behavior. Our findings, which are based on a sample of 308 employees working for a state-owned telecommunications company on the Chinese mainland, indicate that ethical leadership promotes employees’ voice behavior through enhanced leader-member exchange, which also leads to greater feelings (...) of psychological safety and psychological empowerment. The theoretical and practical implications of these results are discussed. (shrink)

Using a sample of 32 work teams (32 work team leaders and their 321 followers) in Chinese cultural context, this study investigated the relationships between leaders’ and their followers’ psychological capital and the multilevel multiple mediation effects of social exchange and emotional contagion. Structural equation model and hierarchical linear model were applied to analyze the survey data. The results revealed that leaders’ psychological capital had a positive influence on their followers’ psychological capital. Leader-member exchange was the cross-level mediator between leaders’ (...) psychological capital and their followers’. The cross-level mediating effect of leaders’ positive emotions perceived by followers was not significant. The results of this study extended the social exchange theory and enriched researches on leadership. The implication was discussed in details. (shrink)

Drawing on the theory of planned behavior, we investigate the legitimacy of platform governance and whether consumers with greater ranges of risk propensity are more likely to purchase innovative products. This study develops a moderated mediation model involving risk propensity, cognitive legitimacy, purchase intention and perceived benefit. To examine our hypotheses, we conducted a survey of 315 consumers from Shanghai, China. The results reveal that risk propensity is positively related to consumers’ purchase intentions, in which cognitive legitimacy plays a mediating (...) role. Furthermore, the interaction suggests that perceived benefit moderates the relationship between risk propensity and cognitive legitimacy. (shrink)

Previous studies have noted that personality traits are important predictors of well-being, but how big five personality influences social well-being is still unknown. This study aims to examine the link between big five personality and five dimensions of social well-being in the Chinese cultural context and whether social support can play the mediating effect in the process. This study included 1,658 participants from different communities in China, and regression analyses were conducted. Results revealed that five personality traits were significantly related (...) to overall social well-being; extraversion was significantly related to social integration; agreeableness was positively related to all five dimensions of social well-being; conscientiousness was positively related to social actualization, social coherence, and social contribution; neuroticism was negatively related to social integration, social acceptance, social actualization, and social coherence; openness was positively related to social integration, social acceptance, social coherence, and social contribution. Social support plays mediating roles in the relationships between extraversion/agreeableness/conscientiousness/neuroticism/openness and social well-being, respectively. (shrink)

In this article, we investigate the resource-based mechanism underlying the relationship between political skill and salespersons’ work outcomes. Specifically, we propose that political skill influences salespersons’ sales performance and job satisfaction through organizational resources and salesperson–customer guanxi, which serve as their internal and external resources. To examine our model, we collected data from 203 salespersons working at a large financial services institution in China. The findings reveal that both access to resources and build-up of s–c guanxi mediate the effect of (...) political skill on salespersons’ work outcomes. Moreover, access to resources and build-up of s–c guanxi interact to predict salespersons’ sales performance and job satisfaction. Implications and future research directions are discussed. (shrink)

We review state‐of‐the‐art computational methods for constructing, from image data, generative statistical models of cellular and nuclear shapes and the arrangement of subcellular structures and proteins within them. These automated approaches allow consistent analysis of images of cells for the purposes of learning the range of possible phenotypes, discriminating between them, and informing further investigation. Such models can also provide realistic geometry and initial protein locations to simulations in order to better understand cellular and subcellular processes. To determine the structures (...) of cellular components and how proteins and other molecules are distributed among them, the generative modeling approach described here can be coupled with high throughput imaging technology to infer and represent subcellular organization from data with few a priori assumptions. We also discuss potential improvements to these methods and future directions for research. (shrink)

The aesthetic appreciation of animals in China is different from that in the West. In this paper, I identify these differences by tracing the various definitions of the word ‘animal’ in Chinese, an...

We investigated whether and how emotional facial expressions affect sustained attention in face tracking. In a multiple-identity and object tracking paradigm, participants tracked multiple target faces that continuously moved around together with several distractor faces, and subsequently reported where each target face had moved to. The emotional expression of the target and distractor faces was manipulated. Tracking performance was better when the target faces were angry rather than neutral, whereas angry distractor faces did not affect tracking. The effect persisted when (...) the angry faces were presented upside-down and when surface features of the faces were irrelevant to the ongoing task. There was only suggestive and weak evidence for a facilitatory effect of happy targets and a distraction effect of happy distractors in comparison to neutral faces. The results show that angry expressions on the target faces can facilitate sustained attention on the targets via increased vigilance, yet this effect likely depends on both emotional information and visual features of the angry faces. (shrink)

Link prediction is a key tool for studying the structure and evolution mechanism of complex networks. Recommending new friend relationships through accurate link prediction is one of the important factors in the evolution, development, and popularization of social networks. At present, scholars have proposed many link prediction algorithms based on the similarity of local information and random walks. These algorithms help identify actual missing and false links in various networks. However, the prediction results significantly differ in networks with various structures, (...) and the prediction accuracy is low. This study proposes a method for improving the accuracy of link prediction. Before link prediction, k-shell decomposition method is used to layer the network, and the nodes that are in 1-shell and the nodes that are not linked to the high-shell in the 2-shell are deleted. The experiments on four real network datasets verify the effectiveness of the proposed method. (shrink)

Virtual reality provides an immersive 360-degree viewing experience and has been widely used in many areas. However, the transmission of panoramic video usually places a large demand on bandwidth; thus, it is difficult to ensure a reliable quality of experience under a limited bandwidth. In this paper, we propose a field-of-view prediction methodology based on limited FoV feedback that can fuse the heat map and FoV information to generate a user view. The former is obtained through saliency detection, while the (...) latter is extracted from some user perspectives randomly, and it contains the FoV information of all users. Then, we design a QoE-driven panoramic video streaming system with a client/server architecture, in which the server performs rate adaptation based on the bandwidth and the predicted FoV. We then formulate it as a nonlinear integer programming problem and propose an optimal algorithm that combines the Karush–Kuhn–Tucker conditions with the branch-and-bound method to solve this problem. Finally, we evaluate our system in a simulation environment, and the results show that the system performs better than the baseline. (shrink)

Following the outbreak of COVID-19, farmer-assisted live streaming has become a hot topic in China. In this manuscript, we explore the ways in which broadcaster and platform characteristics jointly influence consumers’ purchase intention. To examine our hypotheses, we distributed questionnaires to 261 Chinese consumers who viewed farmer-assisted live streaming. Correlational analyses, regression analyses, and confirmatory factor analyses were conducted to examine our hypotheses. The results show that broadcasters’ expertise is positively related to consumer trust and that platform reputation moderates this (...) relationship. In addition, consumer trust mediates the positive relationship between broadcasters’ expertise and consumer purchase intention. Furthermore, the theoretical and practical implications of these findings are discussed. (shrink)

BackgroundThe death of a loved one can trigger a range of responses, including painful thoughts and emotions, as well as positive changes, such as post-traumatic growth. To understand more about the relationship between these outcomes this study explored the co-occurrence of depression, anxiety and PTG among a group of bereaved Chinese adults.MethodsData were collected from 194 participants, who had lost a first-degree relative. Latent class analysis was used to analyze the data to identify subgroups of participants with shared symptom profiles.ResultsThree (...) classes were identified: a Growth class, a Depression/Anxiety/Growth class and a Depression/Anxiety class. Marital status, social support, close relationship with the deceased and witnessing the suffering of the deceased were identified as differential predictors of class membership.ConclusionThe findings contribute to our understanding of the potentially wide ranging impacts of bereavement and highlight the important role of stressor characteristics and support and in influencing impairment and positive outcomes. (shrink)

In recent years government publicity was extensively used to convey environmental issues; therefore, it is important to explore the role of green government publicity influencing people’s pro-environmental behaviors. This study is to uncover the impact of China’s green government publicity on people’s willingness to use green packaging. This research collected data from Guangzhou of China, we used convenient sampling and online questionnaire survey to gather data, and there were 584 effective samples. Using the statistical software Amos17.0, the results reveal that (...) green government publicity has a significant effect on environmental concerns and moral obligation. Environmental concerns and moral obligation both have positive effects on PEBs. In addition, Environmental concerns and moral obligation all have mediating effects in the relationship between green government publicity and people’s PEBs. (shrink)

Pellet is widely used in blast furnace ironmaking. Pellet quality affects the effect of ironmaking, the existing control system of grating-rotary kiln mainly adopts manual control mode, and the quality of pellet production largely depends on the experience, fatigue, and sense of responsibility of the site operators. The use of the Internet of things technology in the integration and improvement of enterprise information level, to achieve fine, intelligent production management, at the same time, is conducive to promoting steel enterprises to (...) reduce costs and increase efficiency, energy conservation and emission reduction, transformation and upgrading, and taking a new road to industrialization. According to the working principle and technological characteristics of the grate-rotary kiln at all stages, this paper designs the management system of firing pellets based on convolutional neural network and IoT technology, so as to realize automatic recognition of image data obtained by the perceptual layer and make an intelligent analysis of it. The system can classify the working conditions of the current equipment, so as to judge whether the production process parameters of the grate-rotary kiln are up to the standard, thus achieving the goal of controlling the quality of the finished pellet. (shrink)

The existing risk assessment and control methods of enterprise risk financing have a large error in mobile data, which leads to inaccurate risk assessment results and low-risk optimization control efficiency. In order to improve the accuracy of risk financing risk assessment for small and medium-sized enterprises and risk control optimization efficiency, this article proposes risk assessment and risk control algorithms for SMEs in the era of big data. Through verifying the information of the loan application and supplementing the data during (...) the loan period, invoke the existing enterprise financing risk database, establish the SME venture financing risk assessment model; build the risk evaluation index system according to the characteristics of the enterprise production organization, process characteristics, and the development of the socioeconomic and technical environment; apply the GA–PSO algorithm to the design of the SME risk financing risk control scheme, and complete the SME risk financing risk assessment and risk control. The experimental results show that the risk optimization control efficiency of the control algorithm reaches more than 70%, and the risk assessment accuracy of SMEs reaches over 95%, and the runtime less than 80 ms, with good convergence performance of risk assessment and control, strong risk optimization control ability, and accurate evaluation effect. (shrink)

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

The large scale, time varying, and diversification of physically coupled networked infrastructures such as power grid and transportation system lead to the complexity of their controller design, implementation, and expansion. For tackling these challenges, we suggest an online distributed reinforcement learning control algorithm with the one-layer neural network for each subsystem or called agents to adapt the variation of the networked infrastructures. Each controller includes a critic network and action network for approximating strategy utility function and desired control law, respectively. (...) For avoiding a large number of trials and improving the stability, the training of action network introduces supervised learning mechanisms into reduction of long-term cost. The stability of the control system with learning algorithm is analyzed; the upper bound of the tracking error and neural network weights are also estimated. The effectiveness of our proposed controller is illustrated in the simulation; the results indicate the stability under communication delay and disturbances as well. (shrink)

The brain-computer interface based on functional near-infrared spectroscopy has received more and more attention due to its vast application potential in emotion recognition. However, the relatively insufficient investigation of the feature extraction algorithms limits its use in practice. In this article, to improve the performance of fNIRS-based BCI, we proposed a method named R-CSP-E, which introduces EEG signals when computing fNIRS signals’ features based on transfer learning and ensemble learning theory. In detail, we used the Independent Component Analysis algorithm for (...) the correspondence between the sources of the two signals. We then introduced the EEG signals when computing the spatial filter based on a modified Common Spatial Pattern algorithm. Experimental results on public datasets show that the proposed method in this paper outperforms traditional methods without transfer. In general, the mean classification accuracy can be increased by up to 5%. To our knowledge, it is an innovation that we tried to apply transfer learning between EEG and fNIRS. Our study’s findings not only prove the potential of the transfer learning algorithm in cross-model brain-computer interface, but also offer a new and innovative perspective to research the hybrid brain-computer interface. (shrink)

In order to obtain continuous stratum information during TBM tunneling, using TBM tunneling parameters, stratum recognition is carried out through the K-nearest neighbor model, and the model is improved by the entropy weight method to improve the stratum recognition rate. By analyzing the correlation between TBM tunneling characteristic parameters and stratum, the tunneling characteristic parameter vector which is most sensitive to the stratum is obtained by sensitivity analysis, and the stratum recognition model based on the K-nearest neighbor algorithm is established. (...) Aiming at the problem that the model has a large error in complex formation recognition, a formation recognition model based on the entropy weight K-nearest neighbor algorithm is established, and the wrong data of the K-nearest neighbor model is recalculated. The recognition rate of the stratum in the new model is increased from 90.95% to 98.55%. The results show that the K-nearest neighbor model has a better recognition effect for the interval with single stratum distribution, and the recognition rate of entropy weight K-nearest neighbor model for complex stratum is significantly improved, which provides an effective method to obtain stratum information by using tunneling characteristic parameters. (shrink)

IntroductionNew nurses struggled with time management, which was a prominent theme in safety care for patients. However, the transition training of time management for new nurses was complicated and ignored by clinical managers. The purpose of this study was to understand the level of new nurses’ TMD from a nationwide perspective and detect the influencing factors of the TMD.Materials and methodsA cross-sectional study design with a stratified sampling method was sampled in China. Six hundred and seventy new nurses within the (...) first year of employment were recruited. New nurses’ time management disposition, job stressors, self-efficacy, clinical communication competence, and safety behavior were measured by corresponding scales.ResultsNew nurses showed the best sense of time’s value, followed by the sense of time efficacy and time monitoring view for time management disposition. The related factors of time management disposition were communication skills, safety behavior, job stressors, and being without a preceptor. New nurses’ time management disposition was at a moderate level and they performed worse in time allocation. The highest education, with or without a preceptor, the experience of part-time jobs, and class cadre were significantly influencing the time management disposition of new nurses.ConclusionNursing managers should pay attention to new nurses’ time management disposition. Reducing the job stressors, improving communication ability, and safe behavior were important measures to improve the time management disposition. (shrink)

There are two contending models regarding the processing of negation: the fusion model and the schema-plus-tag model. Most previous studies have centered on negation in languages such as English and Mandarin, where negators are positioned before predicates. Mongolian, quite uniquely, is a language whose negators are post-verbal, making them natural replicas of the schema-plus-tag model. The present study aims to investigate the representation process of Mongolian contradictory negative sentences to shed light on the debate between the models, meanwhile verifying the (...) post-verbal effect of negators. A series of experiments using the sentence–picture verification paradigm supports the fusion model: Mongolian contradictory negative sentences were processed by representing the actual conditions rather than the negated state of affairs at 250 ISI, and despite the fact that a post-verbal effect of negators was measured at 250 ISI when Mongolian and Mandarin negative sentences were compared, Mongolian–Mandarin bilinguals adopted the same representational strategy for contradictory negation in both languages. (shrink)

To probe the motivational roles of hedonic gratification and social gratification in giving “Like” feedback on social media, we developed a set of novel pictures to simulate WeChat Moments. We subsequently examined how the personality trait of extraversion and stimulus content characteristics influenced “Liking” behavior. A 2 × 3 × 2 -mixed experimental design was applied to data obtained from 56 WeChat Moments users. These participants included 28 individuals with the highest extraversion scale scores, and 28 individuals with the lowest (...) extraversion scale scores, according to the NEO Five-Factor Inventory. Briefly, participants observed pictures on an interface similar to that of WeChat Moments and were given the option to “Like” each picture. “Like” rates and response time were then compared across groups and conditions by applying a mixed-design analysis of variance. Pearson's correlation coefficients were calculated to explore relationships between the “Like” rates under each condition and the scores for each personality trait. Compared with the neutral pictures, the positive and negative pictures were “Liked” more and less frequently, respectively. Compared with the poster-unrelated pictures, the personally related pictures were “Liked” more frequently. In the extrovert group, the frequency of “Likes” given to unrelated negative content positively associated with neuroticism and negatively associated with conscientiousness. No correlations were observed in the introvert group. Compared with not giving “Like” feedback, participants gave “Likes” to positive and negative pictures more quickly and slowly, respectively.These results support the hypothesis that hedonic gratification and social gratification motivate “Like” feedback for positive content and personally related content, respectively. “Liking” behavior was not affected by extraversion, but was related to neuroticism and conscientiousness. Content-related differences in time intervals for giving “Like” feedback in this study suggest that people do not hesitate to give “Like” feedback to positive content on WeChat Moments, yet linger in deciding to give “Like” feedback to negative content. (shrink)