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This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

In recent years, a great number of top conferences and workshops on artificial intelligence (AI) were held in China, showing Chinese AI plays an important role in the world. Meanwhile, Chinese government announced an ambitious scheme, “New Generation Artificial Intelligence Development Plan,” for the country to become a world leader in AI technologies by 2030. The AI research in China has covered various aspects, ranging from chips to algorithms. This chapter attempts to give an overview of the recent advances of AI research and development in China, as well as some perspectives on the future development of AI in China.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

This research aims to improve the performance of rail fastener defect inspection method for multi railways, to effectively ensure the safety of railway operation.

Firstly, a fastener region location method based on online learning strategy was proposed, which can locate fastener regions according to the prior knowledge of track image and template matching method. Online learning strategy is used to update the template library dynamically, so that the method not only can locate fastener regions in the track images of multi railways, but also can automatically collect and annotate fastener samples. Secondly, a fastener defect recognition method based on deep convolutional neural network was proposed. The structure of recognition network was designed according to the smaller size and the relatively single content of the fastener region. The data augmentation method based on the sample random sorting strategy is adopted to reduce the impact of the imbalance of sample size on recognition performance.

Test verification of the proposed method is conducted based on the rail fastener datasets of multi railways. Specifically, fastener location module has achieved an average detection rate of 99.36%, and fastener defect recognition module has achieved an average precision of 96.82%.

The proposed method can accurately locate fastener regions and identify fastener defect in the track images of different railways, which has high reliability and strong adaptability to multi railways.

The purpose of this paper is to investigate the effect of water content of assembly solution on the adsorption behavior and corrosion protection performance of 1–tetradecylphosphonic acid [TDPA, CH3(CH2)13P(O)(OH)2] films on aluminum alloy surface in NaCl solution.

Self-assembled monolayers (SAMs) of TDPA were prepared on the 2024 aluminum alloy surface in TDPA containing ethanol-water solutions with different water contents. The adsorption behavior of the SAMs on the alloy surface and their corrosion protection properties in a 3.5 per cent NaCl solution were characterized by potentiodynamic polarization scan, Fourier-transformed infrared spectroscopy (FTIR) and atomic force microscopy (AFM).

The FTIR results demonstrated that the TDPA molecules were successfully adsorbed on the 2024 aluminum alloy surface, and the density of the SAMs increased with the increasing water content in the assembly solution. The electrochemical studies and corrosion morphologies observed by AFM showed that the optimal condition is 2 h of assembling in solution B or solution C. The corrosion inhibition efficiency values follow the order solution B ≈ solution C > solution A at the first 2 h assembly and solution B > solution C > solution A while the assembly time exceeded 2 h. The dependence of corrosion inhibition performance of the SAM on the water content and on the assembly time is related to the balancing of competition between TDPA adsorption and dissolution of the alloy oxidation film.

It illustrates potential application prospects of TDPA for surface treatment of aluminum alloy. Via the comparison with our previous work, this paper provides useful information regarding the difference of corrosion inhibition properties of organic phosphonic acid for aluminum alloy between in neutral and in acid solution.

This paper aims to solve the lubrication failures in the turning arm bearing of RV reducer, give some help in perfecting the bearing structure design and provide theoretical basis for the reducer’s performance improvement.

The paper establishes a mixed lubrication analysis model to study performance parameters. According to the discretization of parameters and iteration of equations, numerical simulation and theoretical analysis are achieved in computational process.

Considering influences of contact load, real rough surface and realistic geometry of RV reducer turning arm roller bearing, the mixed lubrication analysis model is established to study the ratio of oil film thickness, pressure distribution and maximum von Mises stress in different speeds, temperatures and fillets. The results of mixed lubrication show that reasonable round corner modification, increase in temperature and speed, decrease of surface roughness and lubricant types can improve the lubrication performance.

The mixed lubrication analysis model is established to study the influences of contact load, real rough surface and realistic geometry of RV reducer turning arm roller bearing. Different speed, temperature, lubricant and fillet modification are also considered in the research to analyze oil film thickness, pressure distribution and maximum von Mises stress. These studies can optimize structural design of bearing and direct engineer operations.

The purpose of this study is to investigate the tribological performance of helical gear pairs with consideration of the properties of non-Newtonian lubricant and the real three-dimensional (3D) topography of tooth flanks.

Based on the mixed elastohydrodynamic lubrication (EHL) theory for infinite line contact, this paper proposes a complete model for involute helical gear pairs considering the real 3D topography of tooth flanks and the properties of non-Newtonian lubricant. Film thickness, contact load and contact area ratios at the mid-point of contact line are studied for each angular displacement of pinion. Both the total friction coefficient and surface flash temperature are calculated after obtaining the values of pressure and subsurface stress. Then, the influences of input parameters including rotational speed and power are investigated.

During the meshing process, contact load ratio and area ratio of the two rough surface cases first increase and then decrease; the maximum flash temperature rise (MFTR) on the gear is lower than that on the pinion first, but later the situation converses. For cylindrical gears, on the plane of action, there is a point or a line where the instantaneous friction reduces to a minimum value in a sudden, as the sliding–rolling ratio becomes zero. When rotational speed increases, film thickness becomes larger, and meanwhile, contact load ratio, coefficient of friction and MFTR gradually reduce.

A comprehensive analysis is conducted and a computer program is developed for meshing geometry, kinematics, tooth contact, mixed EHL characteristics, friction, FTR and subsurface stress of involute helical gear pairs. Besides, a numerical simulation model is developed, which can be used to analyze mixed lubrication with 3D machined roughness under a wide range of operating conditions.

Since 2014, “sport for all” has been promoted as a new national strategy in China, which injects powerful dynamism and vitality for its development in numerous aspects. However, there has been very little feedback on sport service provision in community, and the satisfaction level of community participants is largely unmeasured. To promote physical and mental health of residents and form a stronger foundation of sport culture, more attention should be directed to community sports. The purpose of this paper is to examine the impact of community-sport service provisions on participants’ satisfaction and, in turn, on their sport participation behavior.

Community-sport program participants in China (n=576) responded to a survey measuring the proposed concepts.

Structural equation modeling analyses revealed that community-sport services in the areas of sport facility, grassroots sport organizations and sport activity programs had strong influences on participant satisfaction and, in turn, their desire for participation, which highlighted the demand for high-quality sport service provision by community.

The study contributed to the literature by proposing two clear dimensions (core sport service and peripheral sport service) for the measurement of public sport service provision in community sports. A second theoretical contribution of the study relates to the clarification of the relationship between the two dimensions of community-sport service provision (both core and peripheral services) and community participants’ satisfaction levels.