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This study aims to examine the effect of supervisor developmental feedback on employee silence behaviour by developing a moderated mediation model. The model focuses on the mediating role of role breadth self-efficacy and high activated positive affect underpinning the relationship between supervisor developmental feedback and employee silence behaviour, and the moderating role of interdependent self-construal.

The two-wave survey was conducted among 265 employees. Structural equation modelling was conducted to test the mediation and moderation mediation hypotheses.

Results indicated that high activated positive affect mediated the negative relationship between supervisor developmental feedback and employee silence behaviour. The authors also found that interdependent self-construal moderated the relationship between supervisor developmental feedback and role breadth self-efficacy, as well as the indirect effect of supervisor developmental feedback on employee silence behaviour via role breadth self-efficacy.

This empirical study provides preliminary evidence of the mediating role of breadth self-efficacy and high activated positive affect in the negative relationship between supervisor developmental feedback and employee silence behaviour. The moderated mediation results further show that the mediation of role breadth self-efficacy between supervisor developmental feedback is contingent on individual interdependent self-construal, such that the mediation effect is significant among individuals with high interdependent self-construal, but the mediation effect of high activated positive effect is independent of individual interdependent self-construal. The findings further extend boundary conditions (interdependent self-construal) that may constrain the effect of supervisor developmental feedback on role breadth self-efficacy and high activated positive affect. The research makes considerable contributions to the cognitive-affective personality system theory by specifying the cognitive and affective mechanisms between supervisor developmental feedback and employee silence behaviour, as well as the boundary conditions.

Previously, the effect of pore-forming agents on the properties of pore size and morphology was studied. In this paper, we determine the optimal combination of parameters by tensile strength and perform tribological tests with optimal combination of parameters.

In this paper, porous polyimide (PI) materials were fabricated using vacuum hot molding technology. The orthogonal experiment was designed to test the mechanical properties of porous PI materials with the process parameters and the content of pore-forming agent as the changing factors. The porous PI oil-bearing materials were obtained by vacuum immersion, and tribological test were carried out.

The results showed that porous PI oil-bearing materials are suitable for low-speed and low-load conditions. The actual value of the friction coefficient basically match with the theoretical value of the regression analysis, and the errors of the friction coefficient are within 10% and 3%, respectively, which proves that the method used in the study is feasible for the friction coefficient prediction.

In this paper, we have produced a new porous oil-bearing material with good tribological properties. This study can effectively predict the friction coefficient of PI porous material.

Innovations are imperative for organizational growth and sustainability. This study focuses on the employees' innovative behavior, a source of organizational innovations, which has received substantial attention from the researchers. Based on the psychological empowerment theory, the study exposes the effect of the various dimensions of public service motivation (PSM) on employees' innovative behavior (IB) in public sector institutions especially in the context of developing countries such as Pakistan. Moreover, the study also investigates the mediating role of psychological empowerment (PSE) between the dimensions of PSM and IB.

This study used the cross-sectional research design. By using random sampling, the adapted survey questionnaires were used to collect data from 346 faculty members of public sector universities located in provincial capitals of Pakistan. A partial least square–structural equation modeling (PLS-SEM) tool was used to assess the proposed hypotheses through SMART-PLS software.

Results revealed that attraction to policymaking (APM), compassion (COM), self-sacrifice (SS) have a significant impact on employees' PSE and their innovative behavior, while the relationship of commitment to the public interest (CPI) with PSE and IB was found insignificant. Moreover, PSE partially mediated the relationship between PSM dimensions and employees' IB.

There was a scarcity of research on IB especially in public sector institutions such as academia. This study theoretically contributed to the literature by providing a refined picture in assessing the proposed relationship of the constructs. This is also one of the original studies that examine the relationship between the dimensions of PSM and IB.

In the era of mobile internet, the social Q&A community has built a large-scale and complex knowledge label network through its internal knowledge units, and the scale and structure of the network have changed over time. By analysing the structural characteristics and evolution rules of knowledge label networks, the main purpose of this study is to understand the internal mechanisms of the replacement of old and new knowledge and the expansion of knowledge element boundaries, so as to explore the realization path of knowledge management in the new era from the perspective of complex networks.

This paper uses distributed crawlers to capture 419,349 samples from the Zhihu platform. Each sample contains 33 characteristic dimensions, and the natural year is used as the sliding window to divide the whole. In this study, the global knowledge label network and 11 local knowledge label networks are first constructed. Then, the degree distribution analysis and central node exploration of the knowledge label network are carried out using the complex network method. Finally, the average shortest path and average clustering coefficient of the network are analysed by the time series method, and the ARIMA model is used to predict the evolution of the correlation coefficient.

The research results show that the dissimilation degree of the degree distribution of the knowledge label network has gradually decreased from 2011 to 2021, and the attention of users in the knowledge community has shown a trend of distraction and diversification over time. With the expansion of the scale of the knowledge label network and the transformation to an information network, the network sparsity is becoming more and more obvious, and the knowledge granularity of the Q&A community is being refined and diversified. The prediction of the correlation coefficient of the knowledge label network by the ARIMA model shows that the connection between the labels is lacking diversity and the opinion strengthening phenomenon tends to strengthen, which is more likely to form the “echo chamber effect”, resulting in mutual isolation and even opposition between different circles. The Q&A community is about to enter a mature stage, and the corresponding status of each label has been finalized. The future development trend of label networks will be reflected in the substitution between labels, and the specific structure will not change significantly.

The Q&A community model is the trend in Web 2.0 community development. This study proves the effectiveness of complex networks and time series prediction methods in knowledge label network mining in the Q&A community.

The purpose of this study is to improve the dispersion of nanoserpentine modified with OA, KH550 and KH550/oleic acid in lubricating oil. The main aims are to analyze the influence of the dispersion and stability of nanoserpentine modified by different modifiers on the friction properties of lubricating oil.

The nanoserpentine particles obtained by ball-milling were modified by silane coupling agent KH550, OA and KH550/OA, respectively. The dispersity and stability of nanoserpentine in base lubricating oil were characterized by the absorbance value method, centrifuge precipitation rate method and static observation method. The MMU-5G screen display friction and wear tester was used to evaluate the tribological properties of C45E4/C45E4 friction pairs in corresponding lubricating oils. The surface morphology of the friction pairs was observed by scanning electron microscopy and energy dispersive spectroscopy.

The results showed that the dispersity and stability of nanoserpentine particles in lubricating oil were best modified by OA, followed by the KH550/OA and finally, the KH550. Nanoserpentine particles modified with oleic acid showed optimum tribological properties as lubricant additives.

This study can improve the dispersion stability of nanoserpentine particles in lubricating oil, increasing the antiwear and antifriction performance of lubricating oil, which has great significance in economic and military aspects.

The effect of SBF artificial body fluid on microstructure and morphology characteristics of AZ91D alloy was investigated using OM, SEM and XRD. The effect of corrosion on mechanical properties also was researched.

The results show that the corrosion weight loss rate initially increased, then clearly decreased, and finally remained steady. Pits began to appear when the sample was placed in a corrosive environment for five days and pitting gradually increased with longer exposure time.

The pits, which made the grain boundaries indistinct, first appeared near the grain boundary area and then gradually increased in area.

The main mode of corrosion is pitting and the primary corrosion product, MgOH2, could be observed after five days of corrosion.

The online Question and Answer community is full of a large number of science and technology topics, the discussion and dissemination of which play an important role in promoting the popularization of new technologies and cultivating public enthusiasm for science. However, the spread of false information and rumors weakens the community's positive effect, making the community more difficult for people to obtain useful information on such topics. Research on the influencing factors and governance of the spread of false information on science and technology topics has become the key to the spread of popular science.

Therefore, this paper uses the Elaboration Likelihood Model as the theoretical framework to examine the role of the factors influencing the spread of false information on science and technology topics in Zhihu community on the information persuasion and the impact on public behavior attitude from the core path and the edge path. This paper compiles a crawler program to capture 12,893 response information under the “Metaverse” topic in Zhihu community as an empirical sample and uses text mining and conducts visual correlation analysis to explore the key factors affecting the persuasive transmission path of information on science and technology topics.

The research finds that the content specialization, content consistency and content coherence of science and technology topics affect personal judgment from the aspect of information content through the core path and have a positive correlation with information persuasion; the number of comments, the length of the text and the publishing authors' influence from the edge image characteristics through the edge path are positively correlated with the information persuasion. Then, from the perspective of topic platform, government and topic participants, this paper puts forward a general plan to improve the information persuasion of science and technology topics so as to deal with false information.

Compared with the small data set of the traditional questionnaire survey, the research based on community empirical big data is more reliable. The model takes into account the attitude and behavior of users and is more suitable for the research on the transmission path of scientific and technological information in the internet era. This research provides a direction for analyzing the text characteristics and development trends of information in the field of science and technology and is conducive to promoting the optimization of the network information environment and building a good ecology, with the spread of rumors about science and technology topics curbed and the governance of false information strengthened.

Quantitative analysis of existing literature is conducted to compare the textual features of ethics education in science and technology under the broad theme of ethics in science and technology. On this basis, the authors reveal the research hotspots and topic evolution in this field, and propose development suggestions in conjunction with the 5W theory.

In this paper, the authors visualize the graph and quantify the indicators in four aspects: time series, institutional collaboration, author co-authorship, and research hotspots.

Compared to ethics of science and technology, the research results in the field of ethics of science and technology education are limited. There is still room for improvement in the low density of cooperation between authors and institutions. The research themes are focused on theoretical discussions and countermeasure research. At present, the reform of ethics of science and technology is still in its infancy and has not yet formed a perfect system for education and personnel training. It is necessary for research on the ethical theory of technology to provide theoretical support.

In the context of sustainable development strategies, it is beneficial to explore the path of pedagogical optimization of ethics of science and technology in this study. This includes the maintenance of a good research environment and the realization of a healthy development in the field of science and technology.

Nowadays, the breakout of the COVID-19 pandemic has caused an important change in teaching models. The emotional experience of this change has an important impact on online teaching. This paper aims to explore its time evolution characteristics and provide reference for the development of online teaching in the post epidemic era.

The article firstly crawls the online teaching-related comment text data on Zhihu platform and performs emotional calculation to obtain a one-dimensional time series of daily average emotional values. Then, by using non-linear time-series analysis, this paper reconstructs the daily average emotion value time series in high-dimensional phase space, calculates the maximum Lyapunov exponent and correlation dimension and finally, explores the feature patterns through recurrence plot and recurrence quantification analysis.

It was found that the sequence has typical non-linear chaotic characteristics; its correlation dimension indicates that it contains obvious fractal characteristics; the public emotional evolution shows a cyclical rise and fall. By text mining and temporal evolution analysis, this paper explores the evolution law over chronically of the daily average emotion value time series, provides feasible strategies to improve students' online learning experience and quality and continuously optimizes this new teaching model in the era of pandemic.

Based on social knowledge sharing platform of Q&A, this paper models and analyzes users interaction data under online teaching-related topics. This paper explores the evolution law over a long time period of the daily average emotion value time series using text mining and temporal evolution analysis. It then offers workable solutions to enhance the quality and experience of students' online learning, and it continuously improves this new teaching model in the age of pandemics.

In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an important issue for the further development of higher education, thus leading to extensive and in-depth research by many scholars. The study summarizes the characteristics and patterns of dual-innovation education at different stages of development, hoping to provide a systematic model for the development of dual-innovation education in China and make up for the shortcomings.

This paper uses Citespace software to visualize and analyze the relevant literature in CNKI and Web of Science databases from a bibliometric perspective, focusing on quantitative analysis in terms of article trends, topic clustering, keyword co-linear networks and topic time evolution, etc., to summarize and sort out the development of innovation and entrepreneurship education research at home and abroad.

The study found that the external characteristics of the literature published in the field of bi-innovation education in China and abroad are slightly different, mainly in that foreign publishers are more closely connected and have formed a more stable ecosystem. In terms of research hotspots, China is still in a critical period of reforming its curriculum and teaching model, and research on the integration of specialization and creative education is in full swing, while foreign countries focus more on the cultivation of students' entrepreneurial awareness and the enhancement of individual effectiveness. In terms of cutting-edge analysis, the main research directions in China are “creative education”, “new engineering”, “integration of industry and education” and “rural revitalization”.

Innovation and entrepreneurship education in China is still in its infancy, and most of the studies lack an overall overview and comparison of foreign studies. Based on the econometric analysis of domestic and foreign literature, this paper proposes a path for domestic innovation and entrepreneurship education reform that can make China's future education reform more effective.