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The unilateral axle counting sensor is an important railway signal device that detects a train. For efficient and stable detection, the amplitude of induced electromotive force and its changes must be big enough. Therefore, the purpose of this study is to find a way to design and optimize the sensor structure quickly and accurately.

With the help of extensive electromagnetic field calculations, the study puts forward a modified model based on the finite element method, establishes an independent air domain around the sensor, wheel and the railway and adopts a unique grid division method. It offers a design optimization method of the induction coil angles and its spatial location with respect to the excitation coil by using the combination weighting algorithm.

The modified modeling method can greatly reduce the number of finite element mesh and the operation time, and the method can also be applied to other areas. The combination weighting algorithm can optimize the structure of the sensor quickly and accurately.

This study provides a way to design and optimize the structure of the sensor and a theoretical basis for the development. The results can improve and expand the technology of the axle counting sensor.

Ball bearings in gas turbine have played a critical role in supporting heavy radial loads but with higher failure rates and repair costs. Therefore, the purpose of this study is to introduce and study a method for their failure analysis with an actual industrial example to guarantee operation reliability and safety.

Spectrometric oil analysis was used as an early abnormal wear indicator, based on which emergent in-use oil replacement was carried out to reduce the wear rate. However, with wear deterioration, further wear failure investigation was conducted by LaserNet Fines and ferrography to detect the imminent wear failure. Finally, with the assistance of elemental analysis of the typical wear particles, the root cause and worn components were determined by scanning electronic microscope and energy-dispersive X-ray spectroscopy.

The results have shown that an extraneous source led to wear failure, which later caused overheat between the outer bearing ring and ball. It is in accordance with visual inspection of the disassembled engine.

This method has specified the occasion under which the suitable measurement can be taken. It can achieve the rapid wear condition assessment allowing for root cause and worn parts identification. In addition, wear rate reduction by change of oil can be efficient for most of the time to avoid premature disassemble, especially with the possibility of contamination. It has provided experience to address similar industry-level practical wear failure analysis problems.

This empirical study of one of China's biggest take-out platforms during coronavirus disease 2019 (COVID-19) explores the legal rights and protections for gig workers' availability time.

The study uses a quantitative survey and interviews of take-out platform riders, investigating the intrinsic features of working time and availability time. Labour law professionals and scholars are interviewed to verify the findings.

The availability time of take-out platform riders is difficult to define under the current legal working-time framework. There is a need for a specific method to define availability time, considering the multiple factors in gig-take-out-sector work. One option is to apply working-time regulations to availability time but to use a proportionality test to preserve flexibility whilst the platform offers protection to the riders during that time.

Pandemic-related travel restrictions limited the authors' study to one take-out platform in Beijing. Future studies should cover a wider geographical area and multiple take-out platforms.

The study uniquely evaluates the availability time of take-out platform riders to determine appropriate public policy and theoretical implications. It proposes a proportionality test regulating riders' availability. In particular, the workers being “at leisure” during availability time could mitigate the platform's liability for full remuneration or moderate the ceiling of working hours. The occupational health and safety of riders must be fully protected, as they are still “at the platform's disposal” at that time.

The construction of geographical indications agri-food (GIAF) brands play an important role in rural revitalization in China, this study aims to explore how to jointly promote brand building among multiple parties.

A tripartite game model of the producers, sales operating enterprises, and local governments is constructed to analyze the strategy choice of the parties in the complex system behavior evolution stability, and the simulation analysis of the influence factors of brand construction of GIAF and verify the game result.

(1) Increased government subsidies and supervision costs are beneficial to accelerating variety improvement and quality improvement of agri-food, but it is not conducive to the government, Therefore, it is necessary to ensure that the subsidy and supervision cost is kept within a reasonable range; (2) The dividend distributed to producers by sales operating enterprises play an important role in encouraging producers to improve the quality safety of agri-food, but it must be kept within a reasonable range to avoid discouraging the enthusiasm of sales operating enterprises; (3) Cost reduction, and revenue improvement are also effective ways to cooperate with all parties in brand co-construction.

This study does not consider consumers or logistics companies in the evolutionary game model.

This study proposes innovative policies and suggestions for improvement of the brand co-construction of all parties.

Based on the “Rural Revitalization” initiative, this study enriches research methods about brand value and provides a new perspective for brand value co-construction, and theoretical guidance, and empirical basis for formulating innovation policies and recommendations.

This paper aims to examine the effect of innovation-driven polices on innovation efficiency of sport firms listed on the new Third Board in China.

Firm innovation efficiency, including comprehensive innovation efficiency, pure technical efficiency and scale innovation efficiency were calculated by using data envelopment analysis (DEA) models. The input variables and output variable in the DEA model were selected through correlation analysis. The effects of several innovation-driven policies on the innovation efficiency of sport firms were analyzed by a series of multiple regression analyses.

Regarding the innovation efficiency evaluation of sport firms, total research and development (R&D) investment and total R&D staff are two suitable input variables, and total profit, sales revenue and new effective patent are three suitable output variables. Income tax relief for high-tech enterprise has a positive effect on comprehensive innovation efficiency and pure technical efficiency, and governmental subsidies have a negative effect on comprehensive innovation efficiency and pure technical efficiency. However, pretax deduction of R&D expenses does not have a significant effect on comprehensive innovation efficiency, pure technical efficiency and scale innovation efficiency, and income tax relief for high-tech enterprise and pretax deduction of R&D expenses also have no effect on scale innovation efficiency. For a large-scale sport firm, the negative effect of “governmental subsidies” and the positive effect of “income tax relief for high-tech enterprise” on its pure technical efficiency are more significant. For a sport firm with more R&D staff, governmental subsides and “income tax relief for high-tech enterprise” have more positive effect on its innovation efficiency.

The study findings could potentially provide practical guidance to both managers and government-industry policymakers in the sports industry.

Firstly, this paper focused on Chinese sport firms from a rising industry in a developing country (China). The related conclusions are conducive to the governmental management of new industries and the innovation management of new enterprises. Second, this paper analyzed the effect of three special innovation-driven policies on three types of innovation efficiency and explored enterprise innovation development in more detail. Third, this paper not only discusses the effect of innovation-driven policies on innovation efficiency, but also the heterogeneity of their effects.

The purpose of this paper is to propose a novel mathematical model to present the three-dimensional tolerance of a discrete surface and to carry out an approach to analyze the tolerance of an assembly with a discrete surface structure. A discrete surface is a special structure of a large surface base with several discrete elements mounted on it, one, which is widely used in complex electromechanical products.

The geometric features of discrete surfaces are separated and characterized by small displacement torsors according to the spatial relationship of discrete elements. The torsor cluster model is established to characterize the integral feature variation of a discrete surface by integrating the torsor model. The influence and accumulation of the assembly tolerance of a discrete surface are determined by statistical tolerance analysis based on the unified Jacobian-Torsor method.

The effectiveness and superiority of the proposed model in comprehensive tolerance characterization of discrete surfaces are successfully demonstrated by a case study of a phased array antenna. The tolerance is evidently and intuitively computed and expressed based on the torsor cluster model.

The tolerance analysis method proposed requires much time and high computing performance for the calculation of the statistical simulation.

The torsor cluster model achieves the three-dimensional tolerance representation of the discrete surface. The tolerance analysis method based on this model predicts the accumulation of the tolerance of components before their physical assembly.

This paper proposes the torsor cluster as a novel mathematical model to interpret the tolerance of a discrete surface.

This study aims to assess the level of development of the digital economy by constructing a comprehensive measurement system. It explores regional differences within China’s digital economy, highlighting the varying degrees of digital infrastructure, industrialization, governance and innovation capabilities across provinces.

A multidimensional analytical framework including digital infrastructure, industrialization, digitization, governance and innovation was developed. Entropy methods were used to calculate the weights of each dimension. The coupled coordination degree model and the Tobit model with random effects panel are applied to analyze the current situation, discrepancies and influencing factors.

This study reveals significant regional differences in the development of China’s digital economy, characterized by a pattern of “strong in the east, weak in the west; high in the south, low in the north.” This geographical imbalance exacerbates the “polarization effect” and the “siphon effect,” where resources and growth tend to concentrate in already developed areas, further intensifying regional inequalities. The development of the digital economy is driven by principles of innovation, coordination and sharing, which facilitate the creation and dissemination of new technologies and collaboration across different sectors. However, this progress is also constrained by considerations of environmental sustainability (green) and economic openness.

This paper contributes to the body of knowledge by providing a novel multidimensional measurement system for the level of digital economy development. The unique application of the coupled coordination degree model and Tobit model to analyze regional differences and influencing factors provides insights into the dynamics of China’s digital economy.