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Drawing on bargaining power and the inequality aversion perspective, this study aims to probe employees’ influence on addressing income inequality between top executives and nonexecutive employees. Meanwhile, it examines the moderating role of employee-related factors and plan attributes.

This study uses a staggered difference-in-differences design with a propensity scoring match approach and verification of the parallel trend assumption to test the hypotheses.

The results support the hypothesis that employee stock ownership plans (ESOPs) significantly reduce within-firm income inequality. The negative effect is amplified by both the presence of trade unions and the unemployment rate at the regional level, as well as the duration of the lock-in period and the scale of participants within the stock ownership plan.

This study has implications for income inequality research and ESOP design and provides theoretical support for policymakers and corporate governance.

This study contributes to the literature on income inequality by examining the implementation of ESOPs from the employee perspective. Furthermore, it extends the current literature by investigating the strengthening effects of regional factors and ESOP attributes on the relationship between ESOPs and income inequality. The conclusions provide new empirical evidence to promote the effective implementation of ESOPs by combining internal and external factors.

The impact of globalization and worldwide competition has become excruciatingly noticeable in China. The purpose of this study is to examine China’s transformation of state‐owned enterprises (SOEs) to competitive, capable organizations by identifying the dominant challenges and forces for change to State‐Owned Enterprises in China (SOE), the nature of SOE responses to those forces, and the degree of SOE success in making the necessary transformations to compete in a global business environment.

Owing to the importance of the efficiency of commercial banks, the aim of this paper is to find the relationship between capital regulation, monetary policy and the asymmetric effects of the commercial banks' efficiency.

First, the paper makes a static profit model of commercial banks with double constraints and then makes a proposition with numeric simulation.

In this paper, the author finds it unreasonable to calculate the commercial banks' cost and profit efficiency by SFA (DEA) directly, as there is no evidence that indicates the linearity relationship among them. Hence, more complicated solutions should be introduced.

The rate of non‐performing loans (NPL) is inversely proportional to the commercial banks' cost and profit efficiency and capital adequacy ratio (CAR) and statutory reserve ratio (SRR) show a nonlinear relationship between commercial banks' cost and profit efficiency. Hence, the paper defines the different influences of commercial banks' efficiency imposed by CAR and SRR as the asymmetric effects of commercial banks' efficiency.

The nonlinear relationship is found based on improved Kopecky and VanHoose, so excessive regulation has harmful effects on the commercial banks. The reasonable capital regulation and other prudential supervision measures should be emphasized.

First, the paper gets its proposition through the improved KV model, which displays a new perception on analyzing this problem. Second, the nonlinear relationship is discovered by this new model and the empirical results show the nonlinear relationship further.

Path planning is an important part of UAV mission planning. The main purpose of this paper is to overcome the shortcomings of the standard particle swarm optimization (PSO) such as easy to fall into the local optimum, so that the improved PSO applied to the UAV path planning can enable the UAV to plan a better quality path.

Firstly, the adaptation function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself. Secondly, the standard PSO is improved, and the improved particle swarm optimization with multi-strategy fusion (MFIPSO) is proposed. The method introduces class sigmoid inertia weight, adaptively adjusts the learning factors and at the same time incorporates K-means clustering ideas and introduces the Cauchy perturbation factor. Finally, MFIPSO is applied to UAV path planning.

Simulation experiments are conducted in simple and complex scenarios, respectively, and the quality of the path is measured by the fitness value and straight line rate, and the experimental results show that MFIPSO enables the UAV to plan a path with better quality.

Aiming at the standard PSO is prone to problems such as premature convergence, MFIPSO is proposed, which introduces class sigmoid inertia weight and adaptively adjusts the learning factor, balancing the global search ability and local convergence ability of the algorithm. The idea of K-means clustering algorithm is also incorporated to reduce the complexity of the algorithm while maintaining the diversity of particle swarm. In addition, the Cauchy perturbation is used to avoid the algorithm from falling into local optimum. Finally, the adaptability function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself, which improves the accuracy of the evaluation model.

The purpose of this paper is to synthesize SnO₂–ZnO hollow nanofibers, study their sensing properties and introduce an attractive candidate for formaldehyde detection in practice.

Pure and SnO₂–ZnO hollow nanofibers were synthesized by electrospinning method and characterized via X-ray diffraction, field-emission scanning electron microscopy and Fourier transform infrared spectroscopy. The formaldehyde-sensing properties were investigated.

The optimum performance was obtained at 260°C by the 14 at.% SnO₂–ZnO hollow nanofiber sensor. The sensor could detect formaldehyde down to 0.1 ppm with rapid response–recovery time (4-6 s and 7-9 s, respectively), high sensitivity, good selectivity and stability. The relationship between the sensor’s sensitivity and formaldehyde concentration suggests that the adsorbed oxygen species on the sensor’s surface is O2−. The prominent sensing properties are attributed to the one dimensional hollow nanofiber structures and the promoting effects of SnO₂.

The sensor fabricated from 14 at.% SnO₂–ZnO fibers exhibits excellent formaldehyde-sensing characteristics. It can be used for formaldehyde detection in practice.

The electrospinning method is a very simple and convenient method for fabricating hollow nanofibers and the sensing material is of low cost.

To the best of the authors’ knowledge, studies on formaldehyde sensing of SnO₂–ZnO hollow nanofibers have not been reported before.

The sudden outbreak of COVID-19 has become a major public health emergency of global concern. Studying the Internet public opinion dissemination mechanism of public health emergencies is of great significance for creating a legalized network environment, and it is also helpful for managers to make scientific decisions when encountering Internet public opinion crisis.

Based on the analysis of the process of spreading the Internet public opinion in major epidemics, a dynamic model of the Internet public opinion spread system was constructed to study the interactive relationship among the public opinion events, network media, netizens and government and the spread of epidemic public opinion. The Shuanghuanglian event in COVID-19 in China was taken as a typical example to make simulation analysis.

Research results show three points: (1) the government credibility plays a decisive role in the spread of Internet public opinion; (2) it is the best time to intervene when Internet public opinion occurred at first time; (3) the management and control of social media are the key to public opinion governance. Besides, specific countermeasures are proposed to assist control of Internet public opinion dissemination.

The epidemic Internet public opinion risk evolution system is a complex nonlinear social system. The system dynamics model is used to carry out research to facilitate the analysis of the Internet public opinion propagation mechanism and explore the interrelationship of various factors.

The overall objective of the study was to track, over a two‐year period, the reported incidences of corporate governance transgressions at five strategic South African state‐owned enterprises (SOEs).

Transgressions for each SOE were documented against the Organisation for Economic Co‐operation and Development's framework of best practice in governance for SOEs by reviewing annual reports and newspaper article citations over a two‐year period.

While political intervention in the operational running of each SOE is apparent, government appears not to have fulfilled its oversight role of ensuring the sound governance of SOEs according to best practices. While the SOEs appear to comply with external governance demands, compliance to internal, self‐regulated governance appears to be lacking.

The use of annual reports and media reports to document governance practices are open to subjectivity. The broader extrapolation of findings based on five SOEs must be undertaken with caution.

The present study alerts government to potential areas of corporate governance practices at South African SOEs that warrant attention. As South Africa has recently joined the BRICS bloc of developing countries, the findings from the present study could afford a starting point for future comparative study among this group of countries, which appears to evidence similar challenges with regard to governance within their SOEs.

The present study begins to elevate the debate on corporate governance at South African SOEs from public rhetoric to a deeper understanding of the nature of the major problems that warrant attention. Although limited in scope, the study contributes to the scarce academic literature on public sector corporate governance in Africa in general, and in the South African SOE sector in particular.

It is a challenge to print a model with the size that is larger than the working volume of a three-dimensional (3D) printer. The purpose of this paper is to present a feasible approach to divide a large model into small printing parts to fit the volume of a printer and then assemble these parts into the final model.

The proposed approach is based on the skeletonization and the minima rule. The skeleton of a printing model is first extracted using the mesh contraction and the principal component analysis. The 3D model is then partitioned preliminarily into many smaller parts using the space sweep method and the minima rule. The preliminary partition is finally optimized using the greedy algorithm.

The skeleton of a 3D model can effectively represent a simplified version of the geometry of the 3D model. Using a model’s skeleton to partition the model is an efficient way. As it is generally desirable to have segmentations at concave creases and seams, the cutting position should be located in the concave region. The proposed approach can partition large models effectively to well retain the integrity of meaningful parts.

The proposed approach is new in the rapid prototyping field using the model skeletonization and the minima rule. Based on the authors’ knowledge, there is no method that concerns the integrity of meaningful parts for partitioning. The proposed method can achieve satisfactory results by the integrity of meaningful parts and assemblability for most 3D models.

The purpose of this study is to numerically examine the heat transfer and transport of space charges in the solid insulating materials [low density polyethylene (LDPE), flame retardant type 4 (FR4), Polytetrafluoroethylene (PTFE)] using the transmission line modeling (TLM) method. Besides, a comprehensive study is performed on the mutual influences of heat transfer and space charges transport within the solid dielectric bulk.

The obtained governing equations including continuity and circuit equations are coupled with heat transfer equations, and they are solved via fourth-order Runge–Kutta method.

The electric potential and field, current density and temperature distribution are calculated. It is shown that compared with FR4 and PTFE, the temperature increment rate in LDPE is much lower. Moreover, the heat transfer in the solid insulating materials bulk increases the homo-charges density and temperature in the vicinity of electrodes. Hence, the reduction in electric field is reflected in the potential deformations in the proximity of electrodes. Furthermore, where the electric field is maximized, the temperature is minimized.

This study is restricted to two-dimensional problems.

Interestingly, because of the lower temperature in LDPE, the current density and their increment rates in LDPE are much lower than that in FR4 and PTFE dielectric materials.

To solve the problem that the traditional received signal strength indicator real-time location method does not test the attenuation characteristics of the electromagnetic wave transmission in the location area, which cannot guarantee the accuracy of the location, resulting in a large location error.

At present, the compressed sensing (CS) reconstruction algorithm can be roughly divided into the following two categories (Zhouzhou and Fubao, 2014; Lagunas et al., 2016): one is the greedy iterative algorithm proposed for combinatorial optimization problems, which includes matching pursuit algorithm (MP), positive cross matching tracking algorithm (OMP), greedy matching tracking algorithm, segmented orthogonal matching tracking algorithm (StOMP) and so on. The second kind is the convex optimization algorithm, which also called the optimization approximation method. The common method is the basic tracking algorithm, which uses the norm instead of the norm to solve the optimization problem. In this paper, based on the piecewise orthogonal MP algorithm, the improved StOMP reconstruction algorithm is obtained.

In this paper, the MP algorithm (OMP), the StOMP and the improved StOMP algorithm are used as simulation reconstruction algorithms to achieve the comparison of location performance. It can be seen that the estimated position of the target is very close to the original position of the target. It is concluded that the CS grid-based target stepwise location method in underground tunnel can accurately locate the target in such specific region.

In this paper, the offline fingerprint database in offline phase of location method is established and the measurement of the electromagnetic noise distribution in different localization areas is considered. Furthermore, the offline phase shares the work of the location process, which greatly reduces the algorithm complexity of the online phase location process and the power consumption of the reference node, meanwhile is easy to implement under the same conditions, as well as conforms to the location environment.