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Through the study, we identified four effective paths to improve governance performance and also found the key direction for future research on digital twin urban implementation of public crisis governance, i.e. how to find a balance between the cost and the effectiveness of governance.

A total of 22 urban public emergencies were selected based on key influencing factors, and four action paths to improve the performance of public crisis governance in digital twin cities were obtained using a fuzzy set qualitative comparative analysis model.

This paper identified digital twin technologies in urban public crisis governance, analyzed the key factors of public crisis governance in the digital twin city and proposed a path of action to improve the performance of public crisis governance in digital twin cities.

This study focuses on the influencing factors of public crisis governance in digital twin cities and the action paths to promote improved governance performance.

Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

The purpose of this paper is to build a phase-type risk model with stochastic return on investment and random observation periods to characterize the ruin quantities under which the insurance company may take effective investment strategies to avoid bankruptcy.

By the Markov property and Ito’s formula, this paper derives the integro-differential equations in which the interclaim times follow a phase-type distribution. Using the sinc method, this paper obtains the approximate solutions of the expected discounted penalty function. The numerical examples are given to verify the robustness of the proposed sinc method.

This paper discloses the relationship between the investment strategy and initial surplus level. The insurance company with a high initial surplus level prefers high risk portfolios to earn more profit. Contrarily, the insurance company would invest low risk portfolios to avoid bankruptcy. In addition, this paper shows that a short observation period would bring higher ruin probability.

The risk model is distinct in that a phase-type risk model is constructed with stochastic return on investment and random observation periods. These considerations in the risk model are in sharp contrast to the setting in which the stochastic return on investment is observed continuously. In practice, the insurance company only can periodically observe the surplus level to check the balance of the book. This setting, therefore, is difficult to adopt. This paper develops a sinc method to solve the approximate solutions of the expected discounted penalty function.

This study holistically and systematically consolidates the available research on digital reading to reveal the research trends of the past 20 years. Moreover, it explores the thematic evolution, hotspots and developmental characteristics of digital reading. This study, therefore, has the potential to serve as a research guide to researchers and educators in relevant fields.

The authors applied a bibliometric approach using Derwent Data Analyzer and VOSviewer to retrieve 2,456 publications for 2003–2022 from the Web of Science (WoS) database.

The results revealed that most studies' participants were university students and the experimental methods and questionnaires were preferred in digital reading researches. Among the influential countries or regions, institutions, journals and authors, the United States of America, University of London, Electronic Library and Chen, respectively, accounted for the greatest number of publications. Moreover, the authors identified the developmental characteristics and research trends in the field of digital reading by analyzing the evolution of keywords from 2003–2017 to 2018–2022 and the most frequently cited papers by year. “E-books,” “reading comprehension” and “literacy” were the primary research topics. In addition, “attention,” “motivation,” “cognitive load,” “dyslexia,” “engagement,” “eye-tracking,” “eye movement,” “systematic analysis,” “meta-analysis,” “smartphone” and “mobile reading/learning” were potential new research hotspots.

This study provides valuable insights into the current status, research direction, thematic evolution and developmental characteristics in the field of digital reading. Therefore, it has implications for publishers, researchers, librarians, educators and teachers in the digital reading field.

Yi Jing is one of the most archaic works among the Chinese classics. Various schools of thought developed their philosophies from the philosophical perspectives in this book and its influence is wide ranging and far reaching. This paper attempts to show how leaders can approach the Yi Jing beneficially by identifying the principles, values and virtues in each of the 64 scenarios, deriving insights about change and leadership. It also aims to show how the Yi Jing compares with Western management literature.

This paper provides an analysis of Qian Gua of Yi Jing as an example of how leaders can draw insights from Yi Jing about change and leadership.

Qian Gua, which is the first scenario in the Yi Jing, offers us powerful insights about change and leadership by offering: a framework of understanding change and human enterprises, considering the aspects of beginning, process, benefit and sustainability; a framework to understand the leadership development process; and leadership principles of conscientious self‐cultivation, transformational leadership through virtues and riding the tides of change.

A change and leadership model inspired by the Yi Jing should interest business leaders both in the east and the west, and help Westerners gain success in doing business in China or collaborating with the Chinese on a joint venture.

This is the first paper to draw insights about change and leadership through an analysis of Qian Gua of Yi Jing.

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.

While the adverse health consequences of obesity are well-documented, the causal effect between obesity and economic outcomes, particularly individual income in the labor market, has yielded inconsistent findings. At the same time, China has the highest number of obese or overweight people around the world in recent years. However, limited research has examined the causal effect of obesity on Chinese rural residents’ income. To answer this question, our study aims to identify the causal impact of obesity on Chinese rural residents.

First, we conduct ordinary least squares, instrumental variable and Mendelian randomization methods to evaluate the impact of obesity on Chinese rural residents’ income. Then, we employ quantile regression and instrumental variable quantile regression to investigate the potential distributional impacts of obesity across various income segments. For the generality of our results, we also use 485,849 samples from the UK Biobank and the two-sample Mendelian randomization method to analyze.

Our one-sample Mendelian randomization analysis, based on a sample of 441 people collected from rural China in 2019 and 2021, revealed that obesity reduced residents’ annual income by 647.87 China Yuan. Results from the UK further support our findings. We also find that the adverse causal impact of obesity on income is significant in individuals within the above 50th percentile of the income distribution. Additionally, childhood obesity has a long-term adverse effect on income in adulthood.

These results contribute to a more nuanced understanding of the economic costs of obesity. Weight penalties may lead to a deviation from the efficiency that should be pursued in the labor market and widen income disparity.

We provide novel and robust instrumental variables and utilize the Mendelian randomization method to analyze the effect of obesity on Chinese rural residents.

This study aims to investigate the effects of irregular groove textures on the friction and wear performance of sliding contact surfaces. These textures possess multiple depths and asymmetrical features. To optimize the irregular groove texture structure of the sliding contact surface, an adaptive genetic algorithm was used for research and optimization purposes.

Using adaptive genetic algorithm as an optimization tool, numerical simulations were conducted on surface textures by establishing a dimensionless form of the Reynolds equation and setting appropriate boundary conditions. An adaptive genetic algorithm program in MATLAB was established. Genetic iterative methods were used to calculate the optimal texture structure. Genetic individuals were selected through fitness comparison. The depth of the groove texture is gradually adjusted through genetic crossover, mutation, and mutation operations. The optimal groove structure was ultimately obtained by comparing the bearing capacity and pressure of different generations of micro-convex bodies.

After about 100 generations of iteration, the distribution of grooved textures became relatively stable, and after about 320 generations, the depth and distribution of groove textures reached their optimal structure. At this stage, irregular texture structures can support more loads by forming oil films. Compared with regular textures, the friction coefficient of irregular textures decreased by nearly 47.01%, while the carrying capacity of lubricating oil films increased by 54.57%. The research results show that irregular texture structures have better lubrication characteristics and can effectively improve the friction performance of component surfaces.

Surface textures can enhance the friction and lubrication performance of metal surfaces, improving the mechanical performance and lifespan of components. However, surface texture processing is challenging, as it often requires multiple experimental comparisons to determine the optimal texture structure, resulting in high trial-and-error costs. By using an adaptive genetic algorithm as an optimization tool, the optimal surface groove structure can be obtained through simulation and modeling, effectively saving costs in the process.