This paper aims to verify the effects of work–family conflict and work–family facilitation on employee innovation in the digital era. Based on resource conservation theory, this study regards the work–family relationship as a conditional resource. Employees who are in a state of lack of resources caused by work–family conflict will maintain existing resources by avoiding the consumption of further resources to perform innovation activities; employees who are in a state of sufficient resources are more willing to invest existing resources to (...) obtain more resources. In this study, 405 employees from enterprises in the Chinese provinces of Jiangsu, Anhui, Sichuan, and Guangdong, and in the municipality of Tianjin were selected as the research object. These enterprises are knowledge-based companies, and their employees frequently transfer knowledge at work. We collected questionnaires from the frontline employees of these companies. The results show that negative and positive emotions mediate the effect of work–family conflict and work–family facilitation on employee innovation. Moreover, work flexibility has a significant moderating effect on the mediating role of emotions between work–family facilitation and employee innovation behavior. In the digital era, when facing different work–family situations, employees need to pay attention to and dredge their negative emotions to avoid reducing their innovative behaviors due to self-abandonment; in parallel, they need to guide their positive emotions toward innovation, so as to promote their innovative consciousness and behavior. This paper expands the research perspective of employee innovation behavior. (shrink)

Background Caring behaviour is critical for nursing quality, and the clinical internship environment is a crucial setting for preparing nursing students for caring behaviours. Evidence about how to develop nursing students’ caring behaviour in the clinical environment is still emerging. However, the mechanism between the clinical internship environment and caring behaviour remains unclear, especially the mediating role of moral sensitivity and the moderating effect of self-efficacy. Research objective This study aimed to examine the mediating effect of moral sensitivity and the (...) moderating function of self-efficacy on the association between the clinical internship environment and caring behaviours. Research design A cross-sectional design used acceptable validity scales. The hypothesised moderated mediation model was tested in the SPSS PROCESS macro. Participants and research context This survey collected data from 504 nursing students in an internship at a teaching hospital in Changsha, China. Ethical considerations This study was pre-approved by the ethics committee of the medical school (No. E2022210). Informed consent was obtained from all students. Results The clinical internship environment ( B = 0.450, 95% CI = [0.371, 0.530]) and moral sensitivity ( B = 1.352, 95% CI = [1.090, 1.615]) had positive direct effects on nursing students' caring behaviours. Clinical internship environment also indirectly influenced students’ caring behaviours via moral sensitivity ( B = 0.161, 95% CI = [0.115, 0.206]). In addition, self-efficacy played a moderating role between the clinical internship environment and caring behaviours ( B = 0.019, 95% CI = [0.007, 0.031]), as well as the relationship between the clinical internship environment and moral sensitivity ( B = 0.006, 95% CI = [0.003, 0.010]). Conclusion Moral sensitivity mediates the effect of the clinical internship environment on caring behaviour, and self-efficacy strengthens both direct and indirect effects. This study emphasises the importance of self-efficacy in developing moral sensitivity and caring behaviours in nursing students. (shrink)

In order to improve the accuracy and reliability of wireless location in NLOS environment, a wireless location algorithm based on artificial neural network is proposed for NLOS positioning error caused by non-line-of-sight propagation, such as occlusion and signal reflection. The mapping relationship between TOA and TDOA measurement data and coordinates is established. The connection weights of neural network are estimated as the state variables of nonlinear dynamic system. The multilayer perceptron network is trained by the real-time neural network training algorithm (...) based on extended Kalman. Combined with the statistical characteristics of NLOS error, the state component NLOS bias estimation is modified to realize TDOA data reconstruction. Simulation and experimental data analysis show that the algorithm can effectively weaken the influence of NLOS error. The localization method does not depend on the specific NLOS error distribution, nor does it need LOS and NLOS recognition. It can significantly improve the mobile positioning accuracy. (shrink)

As a worldwide epidemic in the digital age, cyberbullying is a pertinent but understudied concern—especially from the perspective of language. Elucidating the linguistic features of cyberbullying is critical both to preventing it and to cultivating ethical and responsible digital citizens. In this study, a mixed-method approach integrating lexical feature analysis, sentiment polarity analysis, and semantic network analysis was adopted to develop a deeper understanding of cyberbullying language. Five cyberbullying cases on Chinese social media were analyzed to uncover explicit and implicit (...) linguistic features. Results indicated that cyberbullying comments had significantly different linguistic profiles than non-bullying comments and that explicit and implicit bullying were distinct. The content of cases further suggested that cyberbullying language varied in the use of words, types of cyberbullying, and sentiment polarity. These findings offer useful insight for designing automatic cyberbullying detection tools for Chinese social networking platforms. Implications also offer guidance for regulating cyberbullying and fostering ethical and responsible digital citizens. (shrink)