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Drawing on conservation of resources theory, this study aims to examine the relationship between temporal leadership (TL) and employees’ thriving at work (TW) by focusing on the positive mediating role of perception of work-goal progress (PWP), the negative mediating roles of job-based psychological ownership (JPO) and the moderating role of synchrony preference (SP).

We employed a dedicated data collection platform called Credamo for two waves of online questionnaires in China between March 2022 and April 2022. A total of 326 questionnaires were collected and analyzed to test the hypotheses.

(1) TL directly and positively affects TW. (2) TL indirectly and positively affects TW via PWP. (3) TL indirectly and negatively affects TW via JPO. (4) SP positively moderates the positive mediating effect of PWP on the relationship between TL and TW. (5) SP negatively moderates the negative mediating effect of JPO on the relationship between TL and TW.

Supervisors in organizations ought to discreetly practice TL and try to maximize the positive role of PWP and minimize the negative role of JPO.

The findings simultaneously discuss the effects of TL on TW from dark and bright perspectives. The influence of interaction between contextual and individual features on TW is also specified.

Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.

This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.

This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.

It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.

This study aims to better understand the relationship between peer feedback in the context of online collaborative note-taking and how comments impacted student performance and understanding.

This one sample investigation was of graduate students participating in an academic writing class working collaboratively online. Data was gathered on student feedback during note-taking activity to test for its effects on student performance and understanding.

The use of peer comments in online note-taking was found to impact student quiz scores and academic writing skills positively. However, no significance was found between comments and the completeness of their notes taken, suggesting its limits to promote deeper understanding.

The level and detail about the comments made and how accurately they recall the important details from the video lectures is not known. The average number of comments made weekly by each group was also low.

Designers and teachers using online collaborative activities could benefit by understanding the nature in which peer comments can enhance student learning, bearing in mind the need for explicit guidance in how to comment and at what level of knowledge their comments should target.

Online collaboration, peer editing and commenting is widely used by educators and the public. A better understanding of how these elements operate might improve the quality of knowledge artefacts such as academic writing and research notes.

Existing literature focuses mainly on peer feedback on writing or other artefacts; this paper seeks to find out more about the impact of comments in particular on collaborative note-taking.

Despite the increasingly growing empirical research on leader humor, the critical issue of how and when leader humor affects newcomer adjustment was largely overlooked. The purpose of this study is to examine the relationship between leader humor and newcomer adjustment. Based on social information processing theory, the authors identify newcomers' role breadth self-efficacy (RBSE) as the mediator and suggest that newcomers' cognitive flexibility moderates the effects.

Data were obtained from a 2-wave sample of 195 newcomers. The authors utilized the PROCESS procedure developed by Hayes to assess the hypothesized moderated mediation model.

The findings showed that leader humor could boost newcomers' RBSE which, in turn, was beneficial to newcomer adjustment. Besides, newcomers' cognitive flexibility plays a moderating role in the relationship between leader humor and newcomers' RBSE.

This study utilized a cross-sectional research design, making the design difficult to obtain causal conclusions. Moreover, the data were all based on self-reports from newcomers, which may raise a concern of common method bias.

This paper extends the literature on leader humor and newcomer adjustment by treating RBSE as the mediator and newcomers' cognitive flexibility as the moderator. This study is one of several empirical studies to test the link between leader humor and newcomer adjustment.

The purpose of this paper is to exploit the multiple-Toeplitz matrices reconstruction method combined with quadratic spatial smoothing processing to improve the direction-of-arrival (DOA) estimation performance of coherent signals at low signal-to-noise ratio (SNRs).

An improved multiple-Toeplitz matrices reconstruction method is proposed via quadratic spatial smoothing processing. Our proposed method takes advantage of the available information contained in the auto-covariance matrices of individual Toeplitz matrices and the cross-covariance matrices of different Toeplitz matrices, which results in a higher noise suppression ability.

Theoretical analysis and simulation results show that, compared with the existing Toeplitz matrix processing methods, the proposed method improves the DOA estimation performance in cases with a low SNR. Especially for the cases with a low SNR and small snapshot number as well as with closely spaced sources, the proposed method can achieve much better performance on estimation accuracy and resolution probability.

The study investigates the possibility of reusing pre-existing designs for the DOA estimation of the coherent signals. The proposed technique enables achieve good estimation performance at low SNRs.

The paper includes implications for the DOA problem at low SNRs in communication systems.

The proposed method proved to be useful for the DOA estimation at low SNR.

A wide urban–rural income gap exists in China despite the implementation of pro-rural policies. Additionally, with the proliferation of the internet and information technology, the promotion effect of e-commerce on the economy has become apparent. Accordingly, China has been actively encouraging rural households to participate in e-commerce activities. This study aims to examine the effect of e-commerce on the urban–rural income gap.

In the study, linear and panel threshold models were applied to provincial-level panel data from 2002 to 2018.

The results of the linear model show that e-commerce contributes to narrowing the urban–rural income gap. Moreover, the panel threshold model results show that the narrowing effect exists in regions where the e-commerce intensity is at a medium-to-high level and urbanization is at a relatively low level; otherwise, e-commerce has no effect. In addition, in regions with a relatively high level of public expenditure and education, the income-gap-narrowing effect of e-commerce is more than double.

The urban–rural income gap can be reduced by promoting e-commerce and reducing the urban–rural divide in e-commerce use.

To determine how varying levels of e-commerce development affect the urban–rural income gap across regions, the study proposes four key causes of the digital divide in e-commerce: e-commerce intensity, public expenditure level, urbanization level and education level and applies the variables as threshold variables to examine the non-linear effect of e-commerce on the income gap.

This study aims to use the ego depletion theory to examine the impact of hindrance stressors on knowledge sharing behaviors by investigating the mediating role of ego depletion and the moderating role of self-enhancing humor.

Data were obtained from a two-wave sample of 226 dyads, including employees in the manufacturing industry and their direct supervisors. The hypotheses were tested by hierarchical regression analyzes and Hayes’ PROCESS macro.

The results demonstrated that employees’ self-enhancing humor style could alleviate the impact of hindrance stressors on employees’ ego depletion state and buffer the negative indirect effect of hindrance stressors on employees’ knowledge-sharing behaviors.

Although the authors collected mediator and dependent variables from different sources, this study used a cross-sectional research design, making it difficult to draw causal conclusions. Besides, hindrance stressors, ego depletion and self-enhancing humor style were all reported by employees.

Through the study, the authors highlight the important role of the self-control view in explaining proactive behavior in the workplace and a great awareness of the unforeseeable consequences of ego depletion for employees.

This paper aims to investigate the effect of solder composition and roughness on early wetting behavior and interfacial reaction under atmospheric conditions.

High-speed photography is used to observe the early wetting and spreading process of the solder on the substrate in real time. The morphology of intermetallic compounds (IMCs) was observed by scanning electron microscopy, and the composition of IMCs micro bumps was determined by energy dispersive spectroscopy.

With a roughness range of 0.320–0.539 µm, the solder is distributed in an elliptical trilinear pattern along the grinding direction. With a roughness range of 0.029–0.031 µm, the solder spreads in the direction of grinding and perpendicular, forming a perfect circle (except in the case of Sn63Pb37 solder). The effect of three types of solder on early wettability is Sn63Pb37 > Sn96.5Ag3Cu0.5 > Sn. The wetting behavior is consistent with the Rn∼t model. The rapid spreading stage (Stage I) is controlled by the interfacial reaction with n1 values between 2.4 and 4. The slow spreading stage (stage II) is controlled by diffusion with n2 values between 4 and 6.7. The size of Cu6Sn5 formed on a rough substrate is greater than that produced on a smooth substrate.

Investigating the effect of solder composition and roughness on early wettability. This will provide a powerful guide in the field of soft brazing.

The purpose of this paper is to analyze the factors influencing the behaviors of government officials during the implementation of open government data (OGD). By identifying and understanding the key factors that determine government officials' adoption of OGD in China, this study can create a valuable reference for other countries and their decision-making regarding government implementation of OGD.

This research collected data by in-depth interviews with government officials in Chinese OGD departments. Through these interviews, the authors consulted 15 administrators from departments that are responsible for the information tasks in Beijing and other cities on their opinions about OGD. The authors also interviewed senior executives from information technology (IT) companies, as well as open data policy scholars from big data alliance and research institutions.

This paper provides insights about how to promote government officials in OGD implementation, including (1) strengthen social supervision for the environment, through developing and publishing OGD technology roadmaps, then attracting the public to actively participate in the implementing of OGD; (2) establish an OGD assessment mechanism for government officials, with bonus motivations, position promotion incentives, as well as spiritual incentives via regional or sector rankings; (3) alleviate the risks of officials' OGD decisions in actual practice, using the institution construction of OGD to guide its direction and strengthen security protection.

This paper fulfils an identified need to study how government officials' behavior can be motivated on OGD implementation.

In the era of big data, data have become an essential factor of production. In the context of open government data (OGD), encouraging the commercial development of OGD is significant for promoting mass innovation and entrepreneurship. This study aims to explore the configurational impact of data supply, external environment and entrepreneurial foundation on data-driven entrepreneurship.

This research used a fuzzy set qualitative comparative analysis (fsQCA). Fourteen start-ups using OGD were taken as a case sample.

This study produces two paths to achieving high entrepreneurial performance, one is a financing-enhanced entrepreneurial path and the other is a data-driven entrepreneurial path. Besides, four conditions are necessary for high performance of OGD-based entrepreneurship: good data quality, mature legal environment, favorable market environment and abundant big data entrepreneurial talents.

The findings have important practical implications for formulating policies related to promoting the application of government open data and innovation and entrepreneurship in terms of strengthening top-level design, improving the legal environment, developing the data market and cultivating entrepreneurial talents.

Although many studies have been conducted on OGD, studies on the paths to successful entrepreneurship based on OGD are limited. In this study, this issue is investigated from a configurational perspective by using the fsQCA technique.