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Purpose: This study provides a bibliometric analysis of bank efficiency and competition over the past years (from 1993 to 2022) to (1) discover the past and current state of knowledge on bank competition and efficiency, (2) identify leading and authoritative journals and scholars who made significant contributions to the distribution of knowledge and impact, (3) identify nations that made a significant contribution and impact to the literature and (4) identify the structure of collaboration that exists between scholars in the areas of bank competition and efficiency and key thematic areas. Design/methodology/approach: A total number of 868 documents made up of articles, reviews, book chapters, book and conference papers from the Scopus database were gathered. This study used a bibliometric analytic approach. Findings: The number of documents on bank competitiveness and efficiency has increased significantly, as have their total publications, citations and national output. Additionally, the most esteemed and prestigious academic journals of eminent academics who have had a significant impact on the dissemination of knowledge on bank efficiency and competition literature champion papers on banking efficiency and competition. In terms of citation performance and collaborative efforts, the United States tops the developed countries, led by China, which is also the most productive. Additionally, single-country publications predominate in the literature, with China ranking first among the top five countries with corresponding authors. While the Lerner index, H-statistic, concentration index and market power were used to measure bank competitive behaviour, the data envelopment analysis approach predominates efficiency estimation techniques that are linked to cost, profit or revenue, scale, technical and productivity indexes. Originality/value: This study is one of the first to offer bibliometric evidence of both bank competition and efficiency. It also offers proof of the distribution of knowledge and intellectual structure of the concepts and concerns in bank competition and efficiency. [ABSTRACT FROM AUTHOR]

It is an important way to realize rural revitalization and sustainable development to guide rural settlement transition (RST) in an appropriate way. This paper uses actor network theory (ANT) to construct a theoretical framework for the study of RST. Taking two typical villages with different transition paths in rural areas of North China Plain as examples, this paper reveals the mechanism of RST and makes a comparative analysis. The results show that: 1) after identifying problems and obligatory passage point, key actors recruit heterogeneous actors into the actor network by entrusting them with common interests, and realize RST under the system operation. 2) Rural settlements under different transition paths have similarities in the problems to be solved, collective actions and policy factors, but there are differences in the transition process, mechanism and effect. The actor network and mechanism of RST through the path of new rural community construction are more complex and the transition effect is more thorough. In contrast, the degree of RST of retention development path is limited if there is no resource and location advantage. 3) Based on the applicable conditions of different paths, this paper designs a logical framework of 'Situation-Structure-Behavior-Result' to scientifically guide the identification of RST paths under the background of rural revitalization. [ABSTRACT FROM AUTHOR]

To solve the problem where the prediction formula for vibration velocity by dynamic compaction cannot fully reflect the elevation amplification effect, the elevation amplification effect of vibration velocity by dynamic compaction was studied theoretically, and the factors that influence the elevation amplification effect of vibration velocity by dynamic compaction were systematically analyzed in this paper. The elevation amplification effect of a loess high slope under dynamic compaction is coformed by the refraction and reflection superposition effect of dynamic compaction vibration waves at the soil layer interface and the diffraction effect of dynamic compaction vibration waves. The propagation path of dynamic compaction vibration waves in soil was analyzed, and the elevation amplification effect was verified theoretically. The related physical quantities that affected the dynamic compaction vibration velocity of a loess high slope were analyzed based on the dimensional analysis method, and the calculation and improved calculation formulas that considered the elevation amplification effect of dynamic compaction vibration velocity were obtained. The multiple regression analysis of the calculation and improved calculation formula that considered the elevation amplification effect of the dynamic compaction vibration velocity was carried out using MATLAB with engineering examples. The results show that the relative error of the two formulas is small when the elevation difference is small; when the elevation difference is large, the calculation accuracy of the improved calculation formula that considered the elevation difference is higher, and it is more in line with the actual situation. Finally, according to the selected maximum allowable value of the slope particle velocity (e.g., 1.5, 2.0, and 2.5 cm/s), the allowable safe distance for dynamic compaction on a loess high slope is proposed area of northern Shaanxi Province, China. The results of this paper could provide a reliable basis for predicting vibration velocity by dynamic compaction in the Loess Plateau area of northern Shaanxi Province, China. They might have a reference value for dynamic compaction vibration control under similar terrain environments with large elevation differences and provide a safe guide for a dynamic compaction construction site in the Loess Plateau area of northern Shaanxi Province, China. [ABSTRACT FROM AUTHOR]

Considering China's 'isolated' digital ecosystem, this paper examines China's 'check-in' activities to understand how the wanghong economy is driving China's new rounds of urban development, with the purpose of supplementing existing research on digital economies from the Chinese context. Focusing on a representative case study area called Dongshankou in Guangzhou, which is regarded as one of the most popular wanghong places and an emerging commercial centre, I sought to enrich existing studies about digital economies and extend scholarship on platform urbanism from the cultural economy perspective. First, I argue that Chinese consumers' check-in activities function as the data accumulation process, structuring Dongshankou's digital capital through the assemblage of online posts and geotags. Therefore, Dongshankou's urban development challenges the conventional view of creativity as the key factor in the cultural economy for urban development, given that digital capital is now the key driver for urban development in the digital age. Second, the growth of wanghong stores in Dongshankou reveals how the wanghong economy is materialised into urban cultural objects. Emotional value – a crucial selling point that these wanghong stores aim to provide to facilitate consumers' check-in activities – illustrates how China's highly participatory digital ecosystem extracts users' emotions and bodily experiences into the process of capital accumulation, which structures the 'platform urbanism' through our daily lives. This paper broadens the horizon for an alternative theoretical agenda in platform urbanism: beyond focusing solely on platform algorithms, how digital platforms and emotions become inextricably linked in economic production should be further explored. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to explore the potential of implementing an action competence teaching model as a framework for achieving sustainable development goals (SDGs) in higher education. The paper seeks to draw insights from the students on the potential of this teaching model. Design/methodology/approach: The study adopted a quantitative research design in exploring the potential of an action competence teaching model. This study used self-report measures to obtain insights into the objective of the study. Findings: The action competence teaching model was seen as useful in equipping students with knowledge about a problem, confidence and willingness to act. However, some issues like the design of the projects, teamwork and instructional practices were identified and discussed. Originality/value: To the best of the authors' knowledge, this study is the first to implement an action competence teaching model to help draw insights from students on its potential. This paper documents certain aspects of action competence that require attention before being implemented in higher education. This information so far lacking in scientific literature contributes to ongoing discussions on SDGs while unveiling strengths and weaknesses to be considered. [ABSTRACT FROM AUTHOR]

How to effectively utilize renewable energy and improve the economic efficiency of microgrid system and its ability to consume renewable energy has become one of the main problems facing China at present. In response to this challenge, this paper establishes a multiobjective capacity optimization model with the minimum levelized cost of energy, the maximum proportion of renewable energy consumption, and the minimum comprehensive system cost. Based on this model, a new improved beluga whale optimization algorithm is proposed to solve the multiobjective optimization problem in the capacity allocation process of wind–solar–storage microgrid system with the goal of ensuring that the microgrid can meet the maximum load demand at different moments throughout the year. In this paper, opposition‐based learning, artificial bee colony, dynamic opposite, and beluga whale optimization are combined to improve the population diversity and convergence accuracy, thereby enhancing the optimization performance of the algorithm. Finally, after finding the optimal Pareto front solution, the Technique for Order Preference by Similarity to an Ideal Solution is used to help decision‐makers select the optimal solution. Using real load data and meteorological data, the results of this paper show that the multiobjective capacity allocation optimization method of grid‐connected scenic storage microgrid system based on the improved beluga whale optimization algorithm can improve the economics of the wind–solar–storage microgrid system and promote the photovoltaic consumption simultaneously, providing a solution for the realization of low‐carbon power and regional economic development. The best‐found levelized cost of energy for the wind–solar–storage microgrid system is 0.192 yuan/kWh. [ABSTRACT FROM AUTHOR]

Whilst China's aid and development model has been traditionally understood as divergent from the dominant post‐1945 liberal development model, scholars are also increasingly exploring convergence between features of the two development models. Recently, scholars from a range of disciplines including development studies, development geography and international (business, environment and legal) studies have explored a process whereby China's Belt and Road Initiative and the United Nations Sustainable Development Goals converge ('BRI‐SDG integration'). This paper brings these multidisciplinary strands of scholarship together and places them in dialogue with social sciences convergence theory to understand how BRI‐SDG integration aligns with or challenges previous conceptualisations of Chinese‐dominant development convergence. The paper first demonstrates that BRI‐SDG integration proposes a novel and deliberate convergence process ‐ which the paper names 'complementary convergence'. However, BRI‐SDG integration also underscores the need for more multidirectional frameworks that reject Eurocentricity for evaluating the contemporary Chinese‐dominant relationship, and an enhanced focus on how China is influencing dominant development institutions. Finally, BRI‐SDG integration reiterates the methodological difficulties of delineating between 'development models' in an increasingly interrelated global governance of development. [ABSTRACT FROM AUTHOR]

China is currently focusing on the cooperative control of air pollution and CO2 emissions, as well as the mitigation of economic policy uncertainty (EPU). By using panel data from 282 cities spanning from 2003 to 2017 and a newly constructed city-level EPU index, a spatial Durbin, two-way fixed-effects model is employed, with the aim of estimating the impact of EPU on the synergistic emissions intensity (SEI) of air pollutants and CO2. Additionally, this paper investigates the potential channels through which EPU influences SEI. It also explores how pressures related to environmental protection and economic development affect the impact of EPU on SEI. The results indicate that a unit increase in EPU will result in a rise in the SEI of local cities, adjacent cities, and total cities by 930.9%, 69,162.7%, and 70,093.6%, respectively. Moreover, the channel analysis suggests that EPU exacerbates SEI by undermining the upgrading of the industrial structure, augmenting industrial structure distortion, and escalating labor market distortion. Furthermore, the effect of EPU on SEI may be lessened by an increase in environmental protection pressure, while an increase in economic development pressure may exert a positive influence. Finally, this paper concludes by recommending that policymakers should prioritize the maintenance and stability of economic policies, facilitate the advancement of the industrial structure, enhance the efficiency of labor resource allocation, and underscore the significance of managing urban air pollution and CO2 emissions. [ABSTRACT FROM AUTHOR]

A predictive model for the spatiotemporal distribution of electric vehicle (EV) charging load is proposed in this paper, considering multimodal travel behavior and microscopic traffic simulation. Firstly, the characteristic variables of travel time are fitted using advanced techniques such as Gaussian mixture distribution. Simultaneously, the user's multimodal travel behavior is delineated by introducing travel purpose transfer probabilities, thus establishing a comprehensive travel spatiotemporal model. Secondly, the improved Floyd algorithm is employed to select the optimal path, taking into account various factors including signal light status, vehicle speed, and the position of starting and ending sections. Moreover, the approach of multi-lane lane change following and the utilization of cellular automata theory are introduced. To establish a microscopic traffic simulation model, a real-time energy consumption model is integrated with the aforementioned techniques. Thirdly, the minimum regret value is leveraged in conjunction with various other factors, including driving purpose, charging station electricity price, parking cost, and more, to simulate the decision-making process of users regarding charging stations. Subsequently, an EV charging load predictive framework is proposed based on the approach driven by electricity prices and real-time interaction of coupled network information. Finally, this paper conducts large-scale simulations to analyze the spatiotemporal distribution characteristics of EV charging load using a regional transportation network in East China and a typical power distribution network as case studies, thereby validating the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Small-scale landslides that occur at unexpected locations and seasons can cause severe losses of life and property. Unusually, the Shidang landslide occurred prior to the rainy season in Jinkouhe County, Sichuan Province, China, resulting in 19 deaths and missing persons. In this paper, landslide characteristics and causes are revealed through a field investigation, laboratory experiments, and numerical calculations. The results show that the Shidang landslide was a small-scale landslide with a total volume of approximately 19500 m3, originating from hollow colluvial deposits. The geomorphological hollow above the landslide provided topographic conditions for the collection of subsurface runoff. Groundwater flow was transported downward along dolomite and accumulated in the area above shale, with a low conductivity. Groundwater table rise combined with the decrease in the soil strength led to landslide occurrence. Improper siting of residential areas and insufficient vigilance against post-rainfall landslides caused this tragedy. Considering the post-disaster lessons, it is strongly recommended that in the future, more attention should be given to the investigation of landslides triggered by groundwater, especially in determining landslide hydrological system boundaries. In mountainous areas where the developable space is limited, areas with hollow landforms are potentially at risk of geohazards. This paper could provide a reference for the prevention and management of similar landslides and new insights for updating landslide investigation systems and residential housing plans. [ABSTRACT FROM AUTHOR]

China has experienced rapid development in the digital economy. Using data from 30 provinces in China between 2011 and 2017, this paper constructs a two-way fixed effects model to study the effects and mechanisms of the digital economy development on social insurance funds revenue. An increase of one unit in digital economy development led to a 0.56% increase in basic endowment insurance funds revenue and a 0.33% increase in basic health insurance funds revenue. The digital economy increased the social insurance funds revenue by promoting employment and increasing income. Furthermore, the effects of digital economic development on social insurance funds revenue were heterogeneous for different levels of economic development and urbanization. The conclusions stood after robustness tests by changing the method of weighting the digital economy indicators and using instrumental variables. This paper confirmed the positive role of the development of the digital economy in increasing the revenue of social insurance funds from the perspective of quantitative research and explored the mechanisms in depth. In order to increase social insurance funds revenue, it is essential to accelerate the development of the digital economy, especially in regions with lower economic development and urbanization, and to address the needs of the technically unemployed and those engaged in flexible employment. [ABSTRACT FROM AUTHOR]

With the increasing importance of the stock market, it is of great practical significance to accurately describe the systemic risk of the stock market and conduct more accurate early warning research on it. However, the existing research on the systemic risk of the stock market lacks multi-dimensional factors, and there is still room for improvement in the forecasting model. Therefore, to further measure the systemic risk profile of the Chinese stock market, establish a risk early warning system suitable for the Chinese stock market, and improve the risk management awareness of investors and regulators. This paper proposes a combination model of EEMD-LSTM, which can describe the complex nonlinear interaction. Firstly, 35 stock market systemic risk indicators are selected from the perspectives of macroeconomic operation, market cross-contagion and the stock market itself to build a comprehensive indicator system that conforms to the reality of China. Furthermore, based on TEI@I complex system methodology, an EEMD-LSTM model is proposed. The EEMD method is adopted to decompose the composite index sequence into intrinsic mode function components (IMF) of different scales and one trend term. Then the LSTM algorithm is used to predicted and model the decomposed sub-sequences. Finally, the forecast result of the composite index is obtained through integration. The empirical results show that the stock market systemic risk index constructed in this paper can effectively identify important risk events within the sample period. In addition, compared with the benchmark model, the EEMD-LSTM model constructed in this paper shows a stronger early warning ability for systemic financial risks in the stock market. [ABSTRACT FROM AUTHOR]

Background: Fertility intentions, as a direct driver of fertility behavior, play an important role in the implementation of national fertility policy and population development. This study explored the influencing factors of college teachers' second child fertility intentions in Jinan, China on the basis of TPB. Methodology/Principal findings: Based on the theory of planned behavior, this paper employs basic characteristics analysis, difference analysis, and factor analysis related to the fertility intentions of the participants. Analysis found participants between 31 and 40 years old had the highest second child fertility intentions, and participants with a college-age first child had the lowest second child fertility intentions. Attitude and subjective norms had a positive impact on second child fertility intentions, and policy awareness had a positive impact on attitude, which indirectly affected second child fertility intentions. Subjective norms had the greatest influence on second child fertility intentions, followed by attitude, and policy awareness had the least influence on second child fertility intentions. Significance/Future research: The findings of this paper can enrich the theoretical research on fertility intentions, and also provide more optimal practical references for the formulation and propagation of China's fertility policy as well as the improvement of the division of family roles in China. Future research can further explore the impact of fertility policy on the fertility intentions of other groups. [ABSTRACT FROM AUTHOR]

This paper employs a unique data set to analyze the trading behavior of wealthy individual investors across Mainland China and their impact on Chinese stock markets' tail risk. Results show that the wealthy individual investors' trading behavior can explain Chinese stock markets' tail risk, and the daily investment portfolios based on the network density of wealthy individual investors have significant excess returns. This paper also investigates the determinants of wealthy individual investors' trading behavior with the social network method and the spatial econometric model, and reveals that wealthy individuals benefit from the spillover effect of their trading behavior through the investor networks. The results of this paper not only reveal micro evidence for the formation mechanism of asset prices, but also provide insight into the behavior of wealthy individual investors. [ABSTRACT FROM AUTHOR]

Green finance (GF) is recognized as a key driver of sustainable development. While existing studies have extensively discussed the relationship between GF and the Sustainable Development Goals (SDGs), few have explored the coupling coordination relationship between GF and SDGs. In this paper, we use data from thirty Chinese provinces (municipalities and autonomous regions) from 2008–2021 to examine the degree of coupling coordination development (CCD) between GF and the SDGs systems using the CCD model. We find that most SDGs and their sub-goals exhibit a significant upward trend, except for SDG8, 14–16. GF presents a fluctuating upward trend, with a significant decline in 2010 and 2019. The CCDs between GF and SDGs and their sub-goals generally show an M-shaped upward trend in most regions, with most of them experiencing a synchronous decline in 2011–2012 and 2019. In the analysis of regional heterogeneity, the eastern region performs better in SDG8–9, the central region performs better in SDG3, 14–15, while the western region performs better in SDG7. This paper provides empirical evidence for a further in-depth understanding of the relationship between GF and SDGs, which can contribute to advancing GF development and the SDG process. [ABSTRACT FROM AUTHOR]

The electric power sector is the primary contributor to carbon emissions in China. Considering the context of dual carbon goals, this paper examines carbon emissions within China's electricity sector. The research utilizes the LMDI approach for methodological rigor. The results show that the cumulative contribution of economies scale, power consumption factors and energy structure are 114.91%, 85.17% and 0.94%, which contribute to the increase of carbon emissions, the cumulative contribution of power generation efficiency and ratio of power dissipation to generation factor are -19.15% and -0.01%, which promotes the carbon reduction. The decomposition analysis highlights the significant influence of economic scale on carbon emissions in the electricity industry, among the seven factors investigated. Meanwhile, STIRPAT model, Logistic model and GM(1,1) model are used to predict carbon emissions, the average relative error between actual carbon emissions and the predicted values are 0.23%, 8.72% and 7.05%, which indicates that STIRPAT model is more suitable for medium- to long-term predictions. Based on these findings, the paper proposes practical suggestions to reduce carbon emissions and achieve the dual carbon goals of the power industry. [ABSTRACT FROM AUTHOR]

China eliminated rural poverty under current poverty standards in 2020. However, compared with rural poverty, urban poverty in China has been somewhat neglected. This paper aims to discover the changes and determinants of multidimensional urban poverty in Shandong Province, a representative province in Eastern China. Using a nationally representative panel dataset, the China Family Panel Studies, and the Dual Cutoff method, this study creates a multidimensional poverty index with four dimensions and 11 indicators to measure urban poverty in Shandong Province. This paper discovers that while the incidence of multidimensional urban poverty in Shandong Province decreased from 47.62% in 2010 to 36.45% in 2018, the intensity of multidimensional poverty only decreased from 41.27% to 37.25%, which indicates the inadequacy of urban anti-poverty efforts in Shandong Province. This paper also uses logistic regression to identify the determinants of multidimensional urban poverty. The findings suggest that income, health, drinking water, and durable goods are the main determinants of multidimensional urban poverty in Shandong Province. Based on these findings, this study provides targeted recommendations for future urban anti-poverty policies in Shandong Province. [ABSTRACT FROM AUTHOR]

Digital rural construction is a key strategic direction to promote China's rural revitalization and alleviate global climate problems. In order to put forward feasible suggestions for the subsequent development and ensure the smooth development of digital village construction, how to reflect the development level of the digital village through scientific and reasonable comprehensive evaluation has become an urgent problem to be solved. This paper establishes a comprehensive evaluation index system through the Delphi method and principal component analysis method, then assigns weights to the evaluation indicators based on the improved CRITIC-G1 method, and then grades the development level of digital villages according to the extension matter element method. Finally, taking Jiangxi Province in China as an example, the overall development level of digital villages in Jiangxi Province is evaluated from the provincial level according to the proposed method. And put forward the corresponding countermeasures and suggestions. Results: Firstly, the development level of digital villages in Jiangxi Province is good, and there is a trend of excellent development level. Secondly, from different aspects of digital rural development, the digitalization of infrastructure, services, economy, and green production in Jiangxi Province is at a good level, and the digitalization of life has reached an excellent level. Thirdly, from the perspective of development trends, the digitization of infrastructure has a progressive trend towards an excellent level of development, while the digitization of services, economy and green production has signs of development regression. According to the analysis results, the relevant countermeasures and suggestions are put forward from four aspects: talent, capital, governance system and development planning. Other regions can evaluate the development level of the digital village according to the evaluation model proposed in this paper so as to analyze the existing problems and put forward targeted solutions to promote the construction of the digital village. [ABSTRACT FROM AUTHOR]

The global digital wave has flourished in recent years, and the digital technology revolution has emerged. Digitalization plays an undeniable role in promoting modern economic and social development in multiple aspects such as economy, society, innovation, public services and sustainable development, China's digitalization application is also developing rapidly. In order to better measure the current situation of China's digitalization development level, this paper constructs a comprehensive evaluation index system of digitalization development from four dimensions of talents in the digital field, digital infrastructure construction, digitalization innovation ability and international competitiveness, and tests the index system. The entropy method is used to measure the level of digitalization development between China and the United States, the United Kingdom, France and other major developed countries in the world, and the coefficient of variation method, kernel density estimation and Dagum Gini coefficient method are used to analyze the temporal and spatial characteristics and regional differences of digitalization development level of seven countries. This paper makes a comparative analysis between China and major developed countries from the historical perspective of the evolution of the techno-economic paradigm. With a view to summarizing and exploring from it and drawing on the advanced experiences accumulated by the developed countries over a long period of time, so as to provide China with useful insights and bases for further enhancing its digitalization development level. [ABSTRACT FROM AUTHOR]

The level of difficulty of mathematical test items is a critical aspect for evaluating test quality and educational outcomes. Accurately predicting item difficulty during test creation is thus significantly important for producing effective test papers. This study used more than ten years of content and score data from China's Henan Provincial College Entrance Examination in Mathematics as an evaluation criterion for test difficulty, and all data were obtained from the Henan Provincial Department of Education. Based on the framework established by the National Center for Education Statistics (NCES) for test item assessment methodology, this paper proposes a new framework containing eight features considering the uniqueness of mathematics. Next, this paper proposes an XGBoost-based SHAP model for analyzing the difficulty of mathematics tests. By coupling the XGBoost method with the SHAP method, the model not only evaluates the difficulty of mathematics tests but also analyzes the contribution of specific features to item difficulty, thereby increasing transparency and mitigating the "black box" nature of machine learning models. The model has a high prediction accuracy of 0.99 for the training set and 0.806 for the test set. With the model, we found that parameter-level features and reasoning-level features are significant factors influencing the difficulty of subjective items in the exam. In addition, we divided senior secondary mathematics knowledge into nine units based on Chinese curriculum standards and found significant differences in the distribution of the eight features across these different knowledge units, which can help teachers place different emphasis on different units during the teaching process. In summary, our proposed approach significantly improves the accuracy of item difficulty prediction, which is crucial for intelligent educational applications such as knowledge tracking, automatic test item generation, and intelligent paper generation. These results provide tools that are better aligned with and responsive to students' learning needs, thus effectively informing educational practice. [ABSTRACT FROM AUTHOR]

In the context of China's new power system, various regions have implemented policies mandating the integration of new energy sources with energy storage, while also introducing subsidies to alleviate project cost pressures. Currently, there is a lack of subsidy analysis for photovoltaic energy storage integration projects. In order to systematically assess the economic viability of photovoltaic energy storage integration projects after considering energy storage subsidies, this paper reviews relevant policies in the Chinese photovoltaic energy storage market. It analyzes the cost and revenue composition of photovoltaic energy storage integration projects, and constructs a system dynamics model for the levelized cost of electricity (LCOE) of such projects. Taking a specific photovoltaic energy storage project as an example, this paper measures the levelized cost of electricity and the investment return rate under different energy storage scenarios. Combining energy storage allocation ratios and internal rate of return indicators, this paper analyzes the net present value of photovoltaic energy storage integration projects under different subsidy standards. The results indicate that, while the current energy storage subsidy policies positively stimulate photovoltaic energy storage integration projects, they exhibit a limited capacity to cover energy storage investment costs, thereby failing to incentivize capital market participation in the construction of such projects. Rational allocation of energy storage capacity and optimization of corresponding subsidy policies are crucial prerequisites for enhancing the economic viability and widespread adoption of photovoltaic energy storage integration projects. This study not only aids in investment decision making for photovoltaic power stations but also contributes to the formulation of energy storage subsidy policies. [ABSTRACT FROM AUTHOR]

This paper explores the development of a smart Structural Health Monitoring (SHM) platform tailored for long-span bridge monitoring, using the Forth Road Bridge (FRB) as a case study. It discusses the selection of smart sensors available for real-time monitoring, the formulation of an effective data strategy encompassing the collection, processing, management, analysis, and visualization of monitoring data sets to support decision-making, and the establishment of a cost-effective and intelligent sensor network aligned with the objectives set through comprehensive communication with asset owners. Due to the high data rates and dense sensor installations, conventional processing techniques are inadequate for fulfilling monitoring functionalities and ensuring security. Cloud-computing emerges as a widely adopted solution for processing and storing vast monitoring data sets. Drawing from the authors' experience in implementing long-span bridge monitoring systems in the UK and China, this paper compares the advantages and limitations of employing cloud- computing for long-span bridge monitoring. Furthermore, it explores strategies for developing a robust data strategy and leveraging artificial intelligence (AI) and digital twin (DT) technologies to extract relevant information or patterns regarding asset health conditions. This information is then visualized through the interaction between physical and virtual worlds, facilitating timely and informed decision-making in managing critical road transport infrastructure. [ABSTRACT FROM AUTHOR]

The "Three Rural Issues", encompass challenges related to agriculture, farmer, and rural area, which hold significant importance in driving comprehensive rural revitalization efforts in China. Farmer entrepreneurship, as a crucial means to enhance productivity, create job opportunities, and increase residents' income, has gradually become a key driving force in promoting rural revitalization in the new stage of development in China. With the rapid development of rural e-commerce, farmer entrepreneurship has encountered new opportunities. This study utilizes the 2020 China Family Panel Studies (CFPS) data and employs a structural equation model (SEM) to analyze the direct impact of rural e-commerce participation on farmer entrepreneurial behavior, considering factors such as human capital, social capital, and network infrastructure. This study further explores the indirect effects and mechanisms of e-commerce participation as a mediating variable and analyzes the impact and mechanisms on agricultural entrepreneurship behavior. The findings are as follows: (1) E-commerce participation significantly promotes farmer entrepreneurial behavior; (2) E-commerce participation as a mediating variable has a positive indirect effect on the relationship between social trust, network infrastructure, human capital, and farmer entrepreneurial behavior; (3) E-commerce participation has a significant positive influence on farmer entrepreneurship in the agricultural sector, and farmers with higher levels of network infrastructure and human capital have a higher probability of choosing agricultural entrepreneurship under the influence of e-commerce participation. Finally, this study provides policy recommendations in terms of infrastructure construction, entrepreneurial policy environment, and education level, aiming to optimize the situation of farmer entrepreneurship and contribute to the comprehensive promotion of rural revitalization.Overall, the research in this paper effectively combines theory and empirical evidence to outline the direct and indirect impact mechanisms of rural e-commerce participation on farmers' entrepreneurial behavior and agriculture-related entrepreneurial behavior and to test the effects of their impacts. First, most of the existing literature deals with farmers in individual sample areas, while the sample selected in this paper is farmers in the whole country, which is relatively more generalizable; second, most of the previous studies explore the level of e-commerce in the inter-provincial or county areas, while this paper expands the empirical study of rural e-commerce on the entrepreneurial behavior of farmers and the micro-period of agricultural entrepreneurial behavior, and focuses on the impacts of the e-commerce activities of farmers on their entrepreneurial behavior. [ABSTRACT FROM AUTHOR]

The development of urbanization has brought new challenges to the ecological environment, and the promotion of green technology innovation and development is widely recognized as an essential method to achieve cities' economic benefits and environmental protection. This paper examines whether the new urbanization pilot policies (NUP) increase green technology innovation (GTI) from both theoretical and empirical perspectives. This paper examines the impact of new urbanization on GTI by analyzing data from 285 cities in China between 2010 and 2021, using the multi-period DID model with the implementation of NUP as an exogenous policy shock. The study results indicate that NUP significantly affects GTI, and the conclusion still holds after the parallel trend test, placebo test, and other robustness tests. Heterogeneity analysis shows that the NUP significantly enhances GTI in low environmental pollution, non-resource-based, Medium-sized, and Central Region cities. The test of moderating effect shows that NUP has a "linkage effect" with the government's environmental attention, financial investment in innovation, and regional talent pooling. The findings of this paper provide empirical evidence and decision-making reference for promoting NUP and sustainable development of cities. [ABSTRACT FROM AUTHOR]

In the built heritage studies, the intricate web of social and selective processes that define heritage is evident. These processes are, in many cases, intertwined with the notion of scale, examplified through the production of heritage sites at the local, national, and transnational scales. While heritage and geography scholars have articulated the role played by scale in heritage-making and argue against a rigid, fixed, and hierarchical understanding of scale, they highlight the constant reproduction of scale. There is, so far, limited explanation of how the perception of scale gets reproduced and how crucial actors manipulate scalar power and resources for heritage making and the reproduction of scale. To fill this gap, this paper delves into mainland China's heritage-making, using the southern Anhui historical villages as an example. Based on intensive 5-month field research, this paper has three findings: 1) The nomination process for a World Heritage Site is notably influenced by politics and selectivity; 2) Diverse stakeholders are pivotal in shaping heritage narratives; 3) Individual contributions to heritage creation directly interact with, and subsequently reshape, 'scale', an entity that is simultaneously discursive and tangible. By integrating the notion of 'scale' into heritage discussions, we illuminate two concurrent processes: creating hierarchies through rule assimilation by interpreting the UNESCO standard internally and evolving socio-spatial dynamics via the manifestation of individual agency with resource manipulation, scale jumping, and reproduction of scale. This approach aligns with the material orientation in human geography and repositions 'scale'. Here, it's not just an epistemological framework but also a tangible force that steers individual perceptions and actions and yields measurable material impacts. [ABSTRACT FROM AUTHOR]

The study of morphological characteristics and growth information in fish scales is a crucial component of modern fishery biological research, while it has been less studied in fossil materials. This paper presents a detailed morphological description and growth analysis of a fossil ctenoid scale obtained from the Upper Cretaceous Campanian lacustrine deposits in northeastern China. The morphological features of this fossil scale are well-preserved and consistent with the structures found in ctenoid scales of extant fish species and display prominent ring ornamentation radiating outward from the central focus, with grooves intersecting the rings. A comparative analysis of the morphological characteristics between the fossil ctenoid scale and those well-studied extant fish Mugilidae allows us to explore the applicability of modern fishery biological research methods to the field of fossil scales. The scale length, scale width, the vertical distance from the focus to the apex of the scale, and the total number of radii have been measured. The age of the fish that possessed this ctenoid scale has been estimated by carefully counting the annuli, suggesting an age equal to or more than seven years. The distribution of growth rings on the scale potentially reflects the warm paleoclimatic condition and fish-friendly paleoenvironment prevalent during that period. This paper, moreover, serves as a notable application of fishery biological methods in the examination of fossil materials. [ABSTRACT FROM AUTHOR]

In the rural areas of Northwest China, the utilization of clean and renewable energy is deemed a crucial measure for reducing building energy consumption and environmental pollutant emissions. This paper focuses on constructing a simulation platform for a solar-assisted air source heat pump heating system. A rural residential building in Yongshou County, Shaanxi Province, serves as an illustrative example. A novel flexible temperature control method with a feedback controller in sub-area and period is proposed in this paper, alongside the selection of three distinct objective functions aimed at optimizing the heating system. The simulation results indicate an average temperature of 17.0 °C throughout the heating cycle, with a peak temperature of 18.7 °C. Moreover, the solar fraction is measured at 25.11%, underscoring the significance of collector area and heat storage tank volume as primary factors in system design. The results also demonstrate that across various optimization objectives, the life cycle cost optimization scheme yields greater economic benefits, while the target building unit heating cost optimization scheme boasts the shortest static payback period and lowest unit heating cost. Conversely, the solar fraction optimization scheme stands out for its superior environmental benefits. These findings offer valuable insights for the design of heating systems tailored to diverse objectives. [ABSTRACT FROM AUTHOR]

While new infrastructure, as a technological extension of traditional infrastructure, has important digital economy attributes, mismatched investment in new infrastructure can still be environmentally damaging. To this end, this paper explores the potential impact of the matching relationship between the new infrastructure investment (NII) and the upgrading of industrial structure (UIS) on environmental pollution from the perspective of coupling and coordination between the two. Through a series of quantitative empirical and robustness tests on China's relevant data from 2011 to 2019, this paper concludes that the coupling coordination level (NUC) of NII and UIS has an inhibitory effect on major environmental pollutants; in terms of mediating effect, NUC can reduce the emission of major environmental pollutants by improving energy consumption structure (ECS) and green innovation level (GII); in terms of nonlinear change characteristics, there is a threshold effect of NUC on the emission of industrial sewage and industrial dust; in terms of spatial properties, NII, NUC, PM2.5 and industrial sewage have positive spatial spillover effects. This study provides theoretical and empirical evidence that can support the government's decision to implement differentiated new infrastructure investment decisions based on environmental protection, and it also provides a certain level of reference for developing countries to make more environmentally friendly new infrastructure investment decisions. [ABSTRACT FROM AUTHOR]

Based on the perspective of flight technology and flight safety, the unsaturated clayey foundation soil of a high plateau airport in the mountainous area of southwest China is taken as the research object, and the calculation method of the composite modulus of CFG pile composite foundation with the soil between the piles as the unsaturated soil is established according to the relevant characteristics of unsaturated soil, and the calculation method of the composite foundation's settlement is carried out on the basis of this method. At the same time, Plaxis finite element analysis software is used to model the actual project and numerically analyze the settlement characteristics of the composite foundation. Finally, the calculation results of the two methods are compared and studied with the actual settlement monitoring values on site. The study shows that: 1) the theoretical analysis method is able to consider the effects of pile length, pile modulus, and matrix suction in unsaturated soil of rigid piles on the composite modulus, which is more in line with the reality than the conventional composite modulus method that does not consider the unsaturated nature of the soil between the piles; 2) the resultant values computed by the theoretical and numerical analysis methods recommended in this paper are both smaller than those measured at the site but the difference is within the range of 10%, so that in the actual plateau of the High Plains airports can choose the two analysis methods recommended in this paper to conduct related research. [ABSTRACT FROM AUTHOR]

Existing studies have shown that environmental tax reform (ETR) in China has a significant effect on green innovation (GI), but there is no in-depth study on the heterogeneous effects of different types of green innovation. Using the data of listed companies in China's high-pollution manufacturing industry from 2012 to 2020, this paper adopts the difference in differences (DID) method to study the differentiation effect of ETR's signal effect and resource crowding-out effect on different green innovation. The empirical results indicate that ETR may significantly improve green product innovation through signaling effect, while reducing green process innovation through resource crowding-out effect. Further moderating effect studies show that enterprises with high institutional corporation social responsibility (ICSR) strengthens the positive effect of ETR on green product innovation. However, enterprises with high technical corporation social responsibility (TCSR) enhances the negative impact of ETR on green process innovation. This paper offers valuable implications for government green governance and enterprises' green transformation. [ABSTRACT FROM AUTHOR]

The behaviors of local governments can affect the enforcement of environmental regulations. Environmental regulation can influence the behaviour of energy-intensive enterprises. This paper examines the relationship between local government competition, environmental regulation and the investment efficiency of high energy consuming firms using a basic panel regression and moderating effects model based on data from 2011-2020 for high energy consuming firms in China. The paper found that local government competition and environmental regulation can promote increased investment efficiency in energy-intensive firms in the short term. However, environmental regulation is not beneficial to investment efficiency in the long run. Local government competition plays a positive moderating role in the impact of environmental regulation on the investment efficiency of high energy consuming firms. There is a threshold effect on the role of local government competition. When the level of government competition exceeds 2.097, it has a negative impact on the investment efficiency. We further test for heterogeneity and we find that this promotion effect is also more obvious in areas with high environmental taxes and low marketability. Finally, we provide constructive suggestions for the development of government and the improvement of the investment efficiency of high energyconsuming firms. [ABSTRACT FROM AUTHOR]

Disposal of landfill leachate is a critical environmental challenge due to its high pollution content. Effective treatment technologies are essential to mitigate the adverse impacts on groundwater and surrounding ecosystems. This paper employs bibliometric analysis and utilizes CiteSpace software to conduct a visual analysis of the knowledge graph of 959 research articles on "Disposal of Landfill Leachate" from the Web of Science core database for the period 1996-2022. The results indicate that the publication quantity has undergone three stages: the sprouting stage, the stable development stage, and the rapid development stage. In terms of international collaboration, China and the USA play an absolute core role. The journals Waste Management, Journal of Hazardous Materials, and Water Research are ranked among the top 3 publications in the field of landfill leachate treatment. The keyword co-occurrence clustering analysis revealed 7 clusters, including groundwater quality, heavy metals, hydrogeophysics, municipal solid, hydraulic conductivity, geochemical barriers and waste disposal, representing the primary research topics. This paper provides a comprehensive analysis of the research progress and development trends in the field of disposal of landfill leachate. It contributes to a better understanding of the key research areas and offers potential prospects for future investigations to researchers. [ABSTRACT FROM AUTHOR]

Researches on the Porter hypothesis have paid more attention to the effect of the external constraint force of environmental regulation on green total factor productivity (GTFP), while ignoring the effect of internal force of market competition on GTFP. Using the panel data of Chinese manufacturing industries, this paper measures China's GTFP with the global frontier MML index which is based on the EBM model. The paper then studies the effect of environmental regulation and market competition on GTFP. The combined effect of environmental regulation and market competition on enhancing GTFP is further investigated. The results are as follows: 1) The GTFP of the manufacturing industry has progressed during the study period and the progress of green technology plays a crucial role in promoting GTFP improvement. 2) The environmental regulation and market competition both have an obvious nonlinear effect of U-type on GTFP. Relying solely on the external constraint force of environmental regulation or the internal force of market competition does not promote the improvement of GTFP quickly. 3) As for the combined effect, improving market competition is beneficial to the positive effect of environmental regulation on GTFP. Market competition and environmental regulation show a significant combined positive effect, accelerating the arrival of environmental regulation inflection point. Thus the rapid improvement of GTFP requires the combined effect to be effectively exerted. However, only when the level of environmental regulation is strong or the level of market competition is high can a combined positive effect appear. The conclusion provides China with a meaningful reference for better implementing the policy of environmental regulation and market-oriented reforms to promote green economic transformation. [ABSTRACT FROM AUTHOR]

Domestic and international risk shocks have greatly increased the demand for systemic risk management in China. This paper estimates China's multi-layer financial network based on multiple financial relationships among banks, assets, and firms, using China's banking system data in 2021. An improved PageRank algorithm is proposed to identify systemically important banks and other economic sectors, and a stress test is conducted. This study finds that China's multi-layer financial network is sparse, and the distribution of transactions across financial markets is uneven. Regulatory authorities should support economic recovery and adjust the money supply, while banks should differentiate competition and manage risks better. Based on the PageRank index, this paper assesses the systemic importance of large commercial banks from the perspective of network structure, emphasizing the role of banks' transaction behavior and market participation. Different industries and asset classes are also assessed, suggesting that increased attention should be paid to industry risks and regulatory oversight of bank investments. Finally, stress tests confirm that the improved PageRank algorithm is applicable within the multi-layer financial network, reinforcing the need for prudential supervision of the banking system and revealing that the degree of transaction concentration will affect the systemic importance of financial institutions. [ABSTRACT FROM AUTHOR]

Simple Summary: In the sorting process of Chinese softshell turtles, it is necessary to classify them based on their weight and accurately identify their plastron and carapace. This process requires heavy manual labor and complex mechanical processing methods. To improve processing efficiency and reduce costs, this article introduces machine vision technology, and a new image processing method is proposed. This method can estimate the weight of Chinese softshell turtles and accurately locate the positions of their plastron and carapace. The automation level of aquaculture can be greatly enhanced, and hardware costs can be reduced through software optimization through this approach. With the rapid development of the turtle breeding industry in China, the demand for automated turtle sorting is increasing. The automatic sorting of Chinese softshell turtles mainly consists of three parts: visual recognition, weight prediction, and individual sorting. This paper focuses on two aspects, i.e., visual recognition and weight prediction, and a novel method for the object detection and weight prediction of Chinese softshell turtles is proposed. In the individual sorting process, computer vision technology is used to estimate the weight of Chinese softshell turtles and classify them by weight. For the visual recognition of the body parts of Chinese softshell turtles, a color space model is proposed in this paper to separate the turtles from the background effectively. By applying multiple linear regression analysis for modeling, the relationship between the weight and morphological parameters of Chinese softshell turtles is obtained, which can be used to estimate the weight of turtles well. An improved deep learning object detection network is used to extract the features of the plastron and carapace of the Chinese softshell turtles, achieving excellent detection results. The mAP of the improved network reached 96.23%, which can meet the requirements for the accurate identification of the body parts of Chinese softshell turtles. [ABSTRACT FROM AUTHOR]

The increasing global warming trend has resulted in the mass loss of most glaciers. The Urumqi Vally, located in the dry and cold zone of China, and its widely dispersed glaciers are significant to the regional ecological environment, oasis economic development, and industrial and agricultural production. This is representative of glaciers in Middle Asia and represents one of the world's longest observed time series of glaciers, beginning in 1959. The Urumqi Headwater Glacier No. 1 (UHG-1) has a dominant presence in the World Glacier Monitoring Service (WGMS). This paper supplies a comprehensive analysis of past studies and future modeling of glacier changes in the Urumqi Valley. It has received insufficient attention in the past, and the mass balance of UHG-1 was used to verify that the geodetic results and the OGGM model simulation results are convincing. The main conclusions are: The area of 48.68 ± 4.59 km2 delineated by 150 glaciers in 1958 decreased to 21.61 ± 0.27 km2 delineated by 108 glaciers in 2022, with a reduction of 0.47 ± 0.04 km2·a−1 (0.96% a−1 in 1958–2022). The glacier mass balance by geodesy is −0.69 ± 0.11 m w.e.a−1 in 2000–2022, which is just deviating from the measured result (−0.66 m w.e.a−1), but the geodetic result in this paper can be enough to reflect the glacier changes (−0.65 ± 0.11 m w.e.a−1) of the URB in 2000–2022. The future loss rate of area and volume will undergo a rapid and then decelerating process, with the fastest and slowest inflection points occurring around 2035 and 2070, respectively. High temperatures and large precipitation in summer accelerate glacier loss, and the corresponding lag period of glacier change to climate is about 2–3 years. [ABSTRACT FROM AUTHOR]

Urbanization and the release of carbon emission are two significant features of contemporary economic and social progress in China. However, there are few studies that consider how urbanization policy goals affect carbon emission. This paper aims to study the nonlinear effects of urbanization policy goals on carbon emission in 13 cities of the Beijing-Tianjin-Hebei region. In this paper, a multi-dimensional spatial disturbance grey model is proposed. Based on matrix perturbation theory, this paper explores the spatial perturbation bounds of the novel model and verifies that the spatial property of the model is consistent with the viewpoint of the First Law of Geography. Then, the novel model is used to predict the urban carbon emission under different urbanization policy goal scenarios. The results showed that the novel model has spatial regional correlation in spatial region prediction. With the development of urbanization level, carbon emissions show a downward trend in more than 50% of cities from 2022 to 2025. In addition, the improvement of urbanization policy goals will promote the carbon peak time of most cities. The carbon emission intensity will exhibit an inverted U-shaped trend distribution in space. The research results are conducive to providing scientific guidance for the formulation of new-type urbanization policies and helping to achieve the dual carbon goals. • A multi-dimensional spatial disturbance grey model is proposed. • The novel grey model is consistent with the viewpoint of the First Law of Geography. • The spatial distribution of carbon intensity showed an inverted U-shaped pattern. [ABSTRACT FROM AUTHOR]

This paper examines disabled people's digital political engagement in China, which is a largely overlooked issue. Current studies about disability politics often focus on manifest political behaviours in western democratic societies, while the literature on technologies and China lacks the examination of everyday politics of specific identity groups, such as disabled people. This paper attempts to fill the gaps with a broader framework of political engagement. Based on long-term ethnographic observation and in-depth interviews, the paper presents a variety of political activities in China's cyberspace, including everyday presence, campaigning for policy changes, networking for disability constituencies, and organised online activism. These suggest both latent and manifest forms of political engagement, which are equally 'worthy' in understanding disability politics in China. The forms also interact with each other to build Chinese disability politics in the digital world. New information and communication technologies, such as the internet, have changed the ways we engage in politics. However, how the technologies have been used by Chinese disabled people for politics is a missing topic. The paper uses a broader framework to examine disabled people's online political engagement. The findings suggest a variety of activities that have explicit or implicit relations to disability politics. The study found Chinese disabled people use the internet to document their everyday life, and, to interact with others and create disability groups. These activities suggest no obvious political targets. The study also found actions with clear political purposes, for example personal or group activities to aim to change discriminative policies. The paper argues all these forms of engagement are meaningful. They interact with each other and contribute to the building of disability politics in China. [ABSTRACT FROM AUTHOR]

This paper provides an overview of the trade in artists' materials in Canton between 1750 and 1842. Through an investigation of China's foreign trade archives and records, this study gives a picture of international trade in artists' materials, particularly pigments, during this period in Canton. Furthermore, it reveals a close trade in Western modern pigments between the West and China. The results of this research may be helpful to conservators and conservation scientists conducting treatments or technical studies on Chinese export paintings of this period. [ABSTRACT FROM AUTHOR]

Background: Although existing studies have shown that both repetitive transcranial magnetic stimulation (rTMS) and music therapy have advantages in the treatment of non‐fluent aphasia, the efficacy of the combination of these two methods remains to be investigated. Aims: To investigate the clinical efficacy of low‐frequency rTMS combined with music therapy on language function and depression in patients with non‐fluent aphasia after stroke. Methods & Procedures: A single‐blind parallel randomised controlled trial was conducted. Sixty patients (mean duration = 93.78 days) with non‐fluent aphasia after stroke were randomly divided into a traditional therapy group (n = 20), a music therapy group (n = 20) and a combined therapy group (n = 20, 1 Hz). The language function and depression were evaluated before and 3 weeks after treatment with the Chinese version of the Western Aphasia Battery scale, Boston Diagnostic Aphasia Examination scale and Stroke Aphasic Depression Questionnaire Hospital Version scale. Outcomes & Results: The combined therapy group was significantly better in all outcomes than the traditional therapy group and was significantly better in depression than the music therapy group. The music therapy group was significantly better in repetition and depression than the traditional therapy group. Language improvement was positively correlated with depression improvement. For adverse events, only two patients in the combined therapy group showed slight dizziness during rTMS treatment and their symptoms improved after rest. Conclusions & Implications: Our preliminary randomised controlled study indicates that low‐frequency rTMS combined with music therapy is feasible and safe in improving language function and depression in non‐fluent aphasia patients after stroke. WHAT THIS PAPER ADDS: What is already known on this subject: Repetitive transcranial magnetic stimulation (rTMS) and music therapy respectively have advantages in the treatment of non‐fluent aphasia after stroke, but whether the combination of the two methods is more effective is still unknown. What this paper adds to the existing knowledge: This is one of the first randomised control trials to investigate whether the clinical efficacy of low‐frequency rTMS combined music therapy for non‐fluent aphasia is better. The findings show that low‐frequency rTMS combined music therapy is superior to traditional therapy in spontaneous speech, auditory comprehension, repetition, naming, aphasia quotient, functional language level and depression, and superior to music therapy in depression, while music therapy is superior to traditional therapy in repetition and depression. What are the potential or actual clinical implications of this work?: Low‐frequency rTMS combined music therapy may be a better method for treatment of non‐fluent aphasia. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate the role of the high speed railway (HSR) project, one of the largest transportation infrastructure projects in the world, in poverty alleviation in China. This study combines county-level data from the China County Statistical Yearbooks with HSR data from the China Railway Yearbooks. The method of difference-in-differences is applied to examine the HSR connection effect on government expenditure in poverty alleviation across Chinese poverty counties over the period of 2010-2018. The results show that the HSR connection has a significantly positive impact on reducing government expenditure in poverty alleviation. Our results, which are based on alternative measurement of poverty alleviation and possible bias arising from endogeneity issue, are robust. This paper highlights that HSR can help achieve accessibility of rural area and poverty alleviation simultaneously. An understanding of the effect is critical for policymakers to promote intra-regional development, balancing efficiency and regional equality. [ABSTRACT FROM AUTHOR]

More and more Chinese enterprises have participated in the Belt and Road initiative (BRI) since its launch in 2013. However, have they all actually benefited? Which companies otherwise have benefited most from the plan? To answer these questions, this paper analyzes the impact of the BRI on Chinese enterprises. Among several findings, it reveals that the performance of companies remained low even though the initiative policy initially stimulated performance, the performance of enterprises depends on the geographical location of enterprises and that the returns of China's outward foreign direct investment in various industries became more volatile with only the mining industry enjoying better returns. Thus, the paper shows that the BRI offers Chinese enterprises opportunities but also brings challenges for companies to optimize the allocation of their resources and improve the performance of their investments. [ABSTRACT FROM AUTHOR]

Income inequality had been one of the important manifestations of social inequality, which can affect the health level by affecting savings, health care and living standards. Existing researches about the relationship between income inequality and health ignored the comprehensive characteristic of health concept, and did not consider the intrinsic relationship between health and income inequality. This paper attempts to re-shed light on the relationship. Firstly, this paper constructs a new health level evaluation system from three aspects: health basis, health environment and behavior, and health security. By means of the combination evaluation method, the health levels can be obtained. Then, considering the interaction between health and income inequality, a simultaneous equation group model is constructed to empirically test the relationship between income inequality and health levels in China. The results reveal that health level is negatively correlated with income inequality. Reducing income inequality plays an important role in improving health levels in China. [ABSTRACT FROM AUTHOR]

Digitalization and greening are key themes in global development, the manufacturing industry, as a major sector of energy consumption and carbon emissions, is in urgent need of transformation to realize energy conservation and emission reduction, digital transformation provides an opportunity for its green development. However, whether digital transformation can restrain the carbon emission intensity (CEI) of enterprises is still controversial. Based on the data of China's A‐share manufacturing listed companies from 2013 to 2020, this paper uses fixed effect model and intermediary effect model to explore the relationship between digital transformation and enterprise CEI and the influence path. the results show that: (1) Digital transformation has significantly reduced the CEI of manufacturing enterprises. (2) Mechanism analysis indicates that green technological innovation and resource allocation efficiency play a chain mediating role in this relationship. (3) Heterogeneity analysis shows that the carbon emission reduction effect of digital transformation is more significant when enterprises belong to an energy‐intensive manufacturing industry or face strong environmental regulations and industry competition. The analysis of this paper not only deepens enterprises' understanding of digital transformation and green development but also provides a policy basis for China to advocate the coordinated development of the digital economy and green economy. [ABSTRACT FROM AUTHOR]

The Solow residual method, traditionally pivotal for calculating total factor productivity (TFP), is typically not applied to green TFP calculations due to its exclusion of undesired outputs. Diverging from traditional approaches and other frontier methodologies such as Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA), this paper integrates undesired outputs and three types of spatial spillover effects into the conventional Solow framework, thereby creating a new spatiotemporal econometric Solow residual method (STE-SRM). Utilizing this novel method, the study computes the industrial green TFPs for 280 Chinese cities from 2003 to 2019, recalculates these TFPs using DEA-SBM and Bayesian SFA for the same cities and periods, and assesses the accuracy of the STE-SRM-derived TFPs through comparative analysis. Additionally, the paper explores the statistical properties of China's urban industrial green TFPs as derived from the STE-SRM, employing Dagum's Gini coefficient and spatial convergence analyses. The findings first indicate that by incorporating undesired outputs and spatial spillover into the Solow residual method, green TFPs are computable in alignment with the traditional Solow logic, although the allocation of per capita inputs and undesired outputs hinges on selecting the optimal empirical production function. Second, China's urban industrial green TFPs, calculated using the STE-SRM with the spatial Durbin model with mixed effects as the optimal model, show that cities like Huangshan, Fangchenggang, and Sanya have notably higher TFPs, whereas Jincheng, Datong, and Taiyuan display lower TFPs. Third, comparisons of China's urban industrial green TFP calculations reveal that those derived from the STE-SRM demonstrate broader but more concentrated results, while Bayesian SFA results are narrower and less concentrated, and DEA-SBM findings sit between these extremes. Fourth, the study highlights significant spatial heterogeneity in China's urban industrial green TFPs across different regions—eastern, central, western, and northeast China—with evident sigma convergence across the urban landscape, though absolute beta convergence is significant only in a limited subset of cities and time periods. [ABSTRACT FROM AUTHOR]

This paper examines the construction and maintenance of Chinese Han Buddhist temples in modern China against the backdrop of societal transformation. Initially, it analyzes the profound impact of social changes since the mid-19th century on Buddhist monasteries, including political turmoil, economic development, and urbanization. Furthermore, the paper explores how temples were reconstructed and revitalized within this historical context, highlighting the monastic community's unwavering commitment to protecting the Dharma and ensuring its enduring presence. Additionally, this paper also explores the role of charismatic monks in enhancing the sanctity of temples and the influence of Buddhist institutional frameworks on the dynamics of state and society. The study employs a multifaceted analysis to understand the complex interplay between temple construction, economic development, and the cultural heritage of Buddhism in China. [ABSTRACT FROM AUTHOR]

The no-pillar longwall mining method (NPLM) by roof cutting technology (RCT) is an innovative longwall mining method proposed in China. Its essential technology is the employment of RCT to replace the chain pillar to safeguard the roadway. In this paper, a novel physical model test method is designed to investigate the protective mechanism of RCT for roadways in greater detail. Furthermore, the physical model test of RCT is conducted in consideration of the effect of broken roof rock bulking. Combined with numerical simulation, the results indicate that RCT can increase the degree of gangue bulking in goaf, hence providing effective support to the overlying strata and maintaining their integrity. Moreover, RCT can significantly reduce the abutment stress of the roadway roof and solid coal side, thereby ensuring the stability of roadway surrounding rock. This paper proposes three protection mechanisms of RCT for roadway based on the findings of the conducted research: I. Reducing the dimensions of roadway roof; II. Utilizing bulking gangue to support the overlying strata; III. Eliminating the cavities in the goaf adjacent to the roadway. The in situ application provides evidence that RCT is effective in controlling roadway deformation. This paper can serve as a reference for no-pillar mining and analogous geotechnical engineering physical model tests. Highlights: A novel two-dimensional physical model test method is developed that can achieve bulking after failure. Three protection mechanisms of roof cutting technology for the gob-side roadway are elucidated. The effect of roof cutting technology on the bulking of broken roof rock is analyzed by experiment. In conjunction with the in-situ application, the key to no-pillar longwall mining by roof cutting technology is proposed. [ABSTRACT FROM AUTHOR]

Due to budget and sensor technology constraints, a single sensor cannot simultaneously provide observational images with both a high spatial and temporal resolution. To solve the above problem, the spatiotemporal fusion (STF) method was proposed and proved to be an indispensable tool for monitoring land surface dynamics. There are relatively few systematic reviews of the STF method. Bibliometrics is a valuable method for analyzing the scientific literature, but it has not yet been applied to the comprehensive analysis of the STF method. Therefore, in this paper, we use bibliometrics and scientific mapping to analyze the 2967 citation data from the Web of Science from 1991 to 2023 in a metrological manner, covering the themes of STF, data fusion, multi-temporal analysis, and spatial analysis. The results of the literature analysis reveal that the number of articles displays a slow to rapid increase during the study period, but decreases significantly in 2023. Research institutions in China (1059 papers) and the United States (432 papers) are the top two contributors in the field. The keywords "Sentinel", "deep learning" (DL), and "LSTM" (Long Short-Term Memory) appeared most frequently in the past three years. In the future, remote sensing spatiotemporal fusion research can address more of the limitations of heterogeneous landscapes and climatic conditions to improve fused images' accuracy. [ABSTRACT FROM AUTHOR]

With China's rapid industrialization and urbanization in the process of socio-economic development, the extensive use of energy has resulted in a large amount of CO2 emissions, which puts great pressure on China's carbon emission reduction task. Through multivariate socio-economic data, this paper proposes an extraction and screening method of multivariate variables based on land-use types, and the downscaled spatial decomposition of carbon emissions at different scales was carried out by using the spatial lag model (SLM). This paper makes up for the shortcomings of previous studies, such as an insufficient modeling scale, simple modeling variables, limited spatio-temporal span of spatial decomposition, and no consideration of geographical correlation. Based on the results of the spatial decomposition of carbon emissions, this paper explores the spatial and temporal dynamics of carbon emissions at different scales. The results showed that SLM is capable of downscaling the spatialization of carbon emissions with high precision, and the continuity of the decomposition results at the provincial scale is stronger, while the differences of the decomposition results at the municipal scale are more obvious within the municipal units. In terms of the spatial and temporal dynamics of CO2 emissions, carbon emissions at both scales showed a significant positive correlation. The dominant spatial correlation types are "Low–Low" at the provincial level, and "Low–Low" and "High–High" at the municipal level. The smaller spatial scope is more helpful to show the geographic dependence and geographic differences of China's carbon emissions. The findings of this paper will help deepen the understanding of the spatial and temporal changes of carbon emissions in China. They will provide a scientific basis for the formulation of feasible carbon emission reduction policies. [ABSTRACT FROM AUTHOR]

Many regions or countries seek to transition to a low-carbon economy, but there is ambiguity about how carbon emissions change with economic growth. This paper captures characteristics of carbon emissions in China using the Tapio Method. To detect driving factors of carbon emissions in economic growth, we adopt the Log-Mean Divisia Index decomposition method. The results of the paper are as follows: (1) Economic growth in most regions of China has outpaced the growth rate of carbon emissions, showing the characteristics of decoupling. (2) Metropolitan cities have a greater impact on the level of decoupling in neighboring provinces and municipalities. (3) The decoupling of carbon emissions from economic growth is caused by declining energy intensity in China. (4) The energy mix and industrial structure have little impact on the growth rate of carbon emissions. In addition, some policy implications are summarized according to the findings of this paper. [ABSTRACT FROM AUTHOR]