Search

As the carrier of enterprise water resources management disclosure, water information disclosure is a means of expression of enterprises' environmental responsibility. First, a corporate water information disclosure quality evaluation index system and evaluation method are established, and with the help of the projection tracing method of accelerated genetic algorithm, 27 paper companies in China are selected as a sample and the disclosure quality level is analyzed empirically. Then, the analysis is carried out in terms of three changes in vertical trends, horizontal trends and changes in laws, regulations and policies, and the results show that Chinese paper and paper product enterprises have low quality of water information disclosure, weak disclosure content and low voluntary disclosure. Finally, feasible suggestions are made based on the evaluation of disclosure issues. [ABSTRACT FROM AUTHOR]

The continuous expansion of the construction scale of smart city has reconstructed the urban information pattern. How to maintain the stability of information security while giving full play to the role of information sharing is a practical problem that must be solved for the sustainable development of smart city. Based on the information ecology theory, this paper construct the smart city information security risk evaluation system from six aspects. Then, zGT2FSs is established based on type-2 fuzzy set theory and IAA method, which fully considers the internal and external uncertainty of expert decision-making. According to the calculation results, the key influencing factors of information security risk of smart city are analyzed to provide suggestions and guidance for the formulation of information security control in the process of smart city construction in China. [ABSTRACT FROM AUTHOR]

Durability is one of the technical bottlenecks restricting fuel cell electric vehicle development. As a result, significant time and resources have been invested in research related to this area worldwide. Current durability research mainly focuses on the single cell and stack levels, which is quite different from the usage scenarios of actual vehicles. There is almost no research on developing durability test cycles on the fuel cell system level. This paper proposes a universal model for developing a durability test cycle for fuel cell system based on the China automotive test cycle. Large-scale comparison tests of the fuel cell systems are conducted. After 1000 h test, the output performance degradation of three mass-produced fuel cell system is 14.49%, 9.59%, and 4.21%, respectively. The test results show that the durability test cycle proposed in this paper can effectively accelerate the durability test of the fuel cell system and evaluate the durability performance of the fuel cell system. Moreover, the methodology proposed in this paper could be used in any other test cycles such as NEDC (New European Driving Cycle), WLTC (Worldwide Harmonized Light Vehicles Test Procedure), etc. And it has comprehensive application value and are significant for reducing the cost of durability testing of fuel cell systems and promoting the industrialization of fuel cell electric vehicles. [ABSTRACT FROM AUTHOR]

Effective forecasting of energy consumption structure is vital for China to reach its "dual carbon" objective. However, little attention has been paid to existing studies on the holistic nature and internal properties of energy consumption structure. Therefore, this paper incorporates the theory of compositional data into the study of energy consumption structure, which not only takes into account the specificity of the internal features of the structure, but also digs deeper into the relative information. Meanwhile, based on the minimization theory of squares of the Aitchison distance in the compositional data, a combined model based on the three single models, namely the metabolism grey model (MGM), back-propagation neural network (BPNN) model, and autoregressive integrated moving average (ARIMA) model, is structured in this paper. The forecast results of the energy consumption structure in 2023–2040 indicate that the future energy consumption structure of China will evolve towards a more diversified pattern, but the proportion of natural gas and non-fossil energy has yet to meet the policy goals set by the government. This paper not only suggests that compositional data from joint prediction models have a high applicability value in the energy sector, but also has some theoretical significance for adapting and improving the energy consumption structure in China. [ABSTRACT FROM AUTHOR]

In the process of global urban development, there are urgent ecological security and environmental pollution problems, green development is the fundamental way for urban sustainable development, economic transformation and mitigation of ecological and environmental problems. Based on the panel data of 283 cities at prefecture level and above in China from 2003 to 2017, this paper analyzes spatial–temporal evolution characteristics of urban green development efficiency (UGDE) and the peer effects of UGDE between cities of different grades. It is found that during the study period, in terms of temporal evolution, the average UGDE in China increased from 0.47 in 2003 to 0.61 in 2017, with a cumulative growth rate of 29.79%, showing a rising trend in general. In terms of spatial evolution, the number of low-efficiency cities and medium-efficiency cities continued to decrease. The eastern region has always been the main distribution area of higher-efficiency cities and high-efficiency cities; in the central region, UGDE in most cities improved significantly; in the western region, UGDE has always lagged behind that in the eastern and central regions. In addition, the center of gravity of UGDE presented a trend of northwest migration in general, with a total displacement of 100.07 km, and UGDE showed a spatial dispersion trend. The empirical results indicate that the improvement of UGDE in large cities has a driving effect on that in neighboring medium cities and small cities through the positive peer effect, and the growth of UGDE in medium cities has a promoting effect on that in neighboring small cities through the positive peer effect; the increase of UGDE in medium cities has a positive peer effect on that in neighboring large cities, and the growth of UGDE in small cities has a positive peer effect on that in neighboring medium cities; UGDE promotes each other between large cities through the positive peer effect. [ABSTRACT FROM AUTHOR]

Industrial ecology (IE) is the process of constructing industrial-ecological systems (IES) with the realization of the mutual benefits for industrial system (IS) and ecological system (ES). Therefore, the IE level depends on the IES development and the relationship between IS and ES. This paper calculated the development index of ES and IS to account for IES development and adopted the grey Lotka–Volterra to analyze the relationship between IS and ES. Choosing the π-shaped curve area in the Yellow River basin of China as the study area, this paper analyzed its IE level and influence factors from 2005 to 2019. Findings include: (1) The development level of IES in the Area presented significant spatial differentiation and could be classified into three levels. (2) IS and ES remained in the stage of isolated development or mutual restriction. (3) IE was found to be positively correlated with scientific innovation, economic development, openness degree, pollution control, and industrial structure while negatively correlated with urbanization, resource consumption, and government influence. [ABSTRACT FROM AUTHOR]

Accurate prediction of sea level height is critically important for the government in assessing sea level risk in coastal areas. However, due to the nonlinear, time-varying and highly uncertain characteristics of sea level change data, sea level prediction is challenging. To improve the accuracy of sea level prediction, this paper uses a new swarm intelligence algorithm named the sparrow search algorithm (SSA), which can imitate the foraging behavior and antipredation behavior of sparrows, to determine optimal solutions. To avoid the algorithm falling into a local optimal situation, this paper integrates the sine–cosine algorithm and the Cauchy variation strategy into the SSA to obtain an algorithm named the SCSSA. The SCSSA is used to optimize the parameter values of the CNN-BiLSTM (convolutional neural network combined with bidirectional long short-term memory neural network) model; finally, a combined neural network model (named SCSSA-CNN-BiLSTM) is proposed. In this paper, the time series data of seven tidal stations located in coastal China are used for experimental analysis. First, the SCSSA-CNN-BiLSTM model is compared with the CNN-BiLSTM model to predict the time series data of SHANWEI Station. With respect to the training and test sets of data, the SCSSA-CNN-BiLSTM model outperforms the other models on all the evaluation metrics. In addition, the remaining six tide station datasets and five neural network models, including the SCSSA-CNN-BiLSTM model, are used to further study the performance of the proposed prediction model. Four evaluation indices including the root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and coefficient of determination (R2) are adopted. For six stations, the RMSE, MAE, MAPE and R2 of SCSSA-CNN-BiLSTM model are ranged from 20.9217 ~ 27.8427 mm, 9.4770 ~ 17.8603 mm, 0.1322% ~ 0.2482% and 0.9119 ~ 0.9759, respectively. The experimental analysis results show that the SCSSA-CNN-BiLSTM model makes effective predictions at all stations, and the prediction performance is better than that of the other models. Even though the combination of SCSSA algorithm may increase the complexity of the model, indeed the proposed model is a new prediction method with good accuracy and robustness for predicting sea level change. [ABSTRACT FROM AUTHOR]

The mining of open pit mines is widespread in China, and there are many cases of landslide accidents. Therefore, the problem of slope stability is highlighted. The stability of the slope is a factor that directly affects the mining efficiency and the safety of the entire mining process. According to the statistics, there is a 15 percent chance of finding landslide risk in China's large-scale mines. And due to the expansion of the mining scale of the enterprise, the problem of slope stability has become increasingly obvious, which has become a major subject in the study of open-pit mine engineering. In order to better predict the slope stability coefficient, this study takes a mine in China as a case to deeply discuss the accuracy of different algorithms in the stability calculation, and then uses a deep learning algorithm to study the stability under rainfall conditions. The change of the coefficient and the change of the stability coefficient before and after the slope treatment are experimentally studied with the displacement of the monitoring point. The result shows that the safety coefficient calculated by the algorithm in this paper is about 7% lower than that of the traditional algorithm. In the slope stability analysis before treatment, the safety factor calculated by the algorithm in this paper is 1.086, and the algorithm in this paper is closer to reality. In the stability analysis of the slope after treatment, the safety factor calculated by the algorithm in this paper is 1.227, and the stability factor meets the requirements of the specification. It also shows that the deep learning algorithm effectively improves the efficiency of the slope stability factor prediction and improves security during project development. [ABSTRACT FROM AUTHOR]

City reputation is a valuable asset for the local economy and firms in the contemporary society. However, the impact of city reputation on micro-level firms has been largely overlooked by the literature. This paper uses the National Civilized City (NCC) policy in China as a quasi-natural experiment to enhance city reputation. We employ the DID approach to investigate the relationship between city reputation and corporate risk-taking. The result shows that corporate risk-taking significantly increases following the NCC policy adoption. Moreover, information asymmetry can strengthen the positive impact of city reputation on corporate risk-taking. Channel tests show that city reputation improves financial condition and decreases default risk, leading to improved risk-taking tolerance. Overall, our paper indicates that city reputation is an important mechanism to improve corporate financial performance, providing empirical evidence for local governments to pursue the NCC title. [ABSTRACT FROM AUTHOR]

This paper examines the coupling coordination degree between digital economy and green technology innovation in 19 urban agglomerations across China from 2011 to 2020. Through the analysis of the coupling coordination degree model, spatial autocorrelation, multi-distance spatial clustering analysis, kernel density analysis and grey correlation model, this study uncovers the mechanism of coupling between digital economy and green technology in Chinese urban agglomerations. Data analysis revealed a significant increase in the coupling coordination between the digital economy and green technology innovation within urban agglomerations. However, there are noticeable spatial imbalances in this trend. Additionally, the multi-distance spatial distance analysis highlights a shift from a random distribution to a clustered distribution of spatial characteristics. The polarization features vary among each urban agglomeration and exhibit a significant positive spatial correlation. Factors such as economic sustainability, creative talent, policy support, digital impetus, and technological support will affect the coupling mechanism of green technology innovation and the digital economy in China's urban agglomerations. Policy recommendations are proposed to foster the development of the digital economy, promote coordinated growth within and beyond urban clusters, and ultimately build a digital ecological civilization that is both green and intelligent. [ABSTRACT FROM AUTHOR]

The application of industrial robots is considered a significant factor affecting environmental pollution. Selecting industrial wastewater discharge, industrial SO2 emissions and industrial soot emissions as the evaluation indicators of environmental pollution, this paper uses the panel data model and mediation effect model to empirically examine the impact of industrial robots on environmental pollution and its mechanisms. The conclusions are as follows: (1) Industrial robots can significantly reduce environmental pollution. (2) Industrial robots can reduce environmental pollution by improving the level of green technology innovation and optimizing the structure of employment skills. (3) With the increase in emissions of industrial wastewater, industrial SO2, and industrial dust, the impacts generated by industrial robots are exhibiting trends of a "W" shape, gradual intensification, and progressive weakening. (4) Regarding regional heterogeneity, industrial robots in the eastern region have the greatest negative impact on environmental pollution, followed by the central region, and the western region has the least negative impact on environmental pollution. Regarding time heterogeneity, the emission reduction effect of industrial robots after 2013 is greater than that before 2013. Based on the above conclusions, this paper suggests that the Chinese government and enterprises should increase investment in the robot industry. Using industrial robots to drive innovation in green technology and optimize employment skill structures, reducing environmental pollution. [ABSTRACT FROM AUTHOR]

This study uses a two-step approach to construct a multi-period double-difference model and introduces a quasi-natural experiment of the Broadband China pilot policy to investigate whether household financial market participation at the urban level is affected by the digital economy, which is significant for promoting Chinese households' shift from savings to investment and alleviating the long-standing problem of insufficient household financial market participation in China. In terms of direct impact, the digital economy increases the household financial market participation rate of urban residents by 3.26%, and increases the financial market participation rate of highly financially literate households by 2.14%; in terms of indirect impact, the development of the digital economy increases the total number of household smart Internet devices by 8.27%, and similarly increases the attention to household financial information by a significant 4.22%, which further positively influences the household financial market participation rate. This paper also evaluates the individual and regional differences of the digital economy on household financial market participation, and the estimated causal effect of the digital economy on household financial market participation is purer, which expands the scope of research on the digital economy and household financial market participation, and provides a certain reference basis and policy inspiration for the government to promote the construction of the digital economy. [ABSTRACT FROM AUTHOR]

The rise of China as a scientific research superpower has been frequently discussed in media and literature. However, past analyses are usually based on the geographical database and they ignore how the millions of emigrated Chinese students, who are now being considered the major research workforce in many countries, affect their academic outputs. Here we quantitatively analyze the contribution of Chinese scholars in physical science around the globe by their publications in a country's papers from 2010 to 2021 as well as their citations. Contrary to common perception, we find that increasing the number of Chinese scholars does not correlate with the net publication growth or decline in their host countries before the Chinese population exceeds a critical value. On the other hand, increasing Chinese authors in a paper improves its citations. The phenomena, though anomalous, are observed in many subfields of physics across the globe. Our analysis suggests that although Chinese scholars do not change the perceived publication capabilities of many countries but may have reshaped their research culture as well as workforce distributions. The results would be valuable for R&D, higher education, and immigration policymakers. [ABSTRACT FROM AUTHOR]

Improving total factor carbon emission efficiency (TCE) is the key to achieving carbon emission reduction targets while ensuring economic growth. In this paper, the global Malmquist index based on the SBM model is used to measure TCE of 283 cities in China from 2011 to 2019. On this basis, this paper uses the spatial econometric model and intermediary effect model to empirically analyze the impact of industrial co-agglomeration on TCE and its transmission mechanism. Furthermore, considering the differences in geographical location and resource endowment among regions, this paper analyzes the heterogeneous effect of industrial collaboration agglomeration on TCE in different regions and cities. The results show that: (1) Industrial co-agglomeration can improve TCE, and its main transmission channel is technological innovation. (2) Industrial co-agglomeration has a positive spatial spillover effect. Industrial co-agglomeration in one region can improve the TCE in the surrounding regions. (3) Industrial co-agglomeration of cities with different geographic locations and resource endowments has a heterogeneous effect on TCE. Regarding geographical heterogeneity, the industrial co-agglomeration in the eastern region has the greatest promoting effect on TCE, followed by the central region. However, the impact of industrial co-agglomeration in the western region on TCE is not significant. Regarding resource endowment heterogeneity, the industrial co-agglomeration in non-resource-based cities has a greater promoting effect on TCE than that in resource-based cities. [ABSTRACT FROM AUTHOR]

The motivation for analyzing the impact of deep neural networks on enterprise performance is mainly due to the continuous deepening of enterprise information construction, shifting from traditional paper-based data acquisition methods to electronic data management. The data generated by the sales, production, logistics and other links of enterprises is also becoming increasingly large. How to scientifically and effectively process these massive amounts of data and extract valuable information has become an important issue that enterprises need to solve. The continuous and stable growth of China's economy has promoted the development and growth of enterprises, however, it has also made enterprises face a more complex competitive environment. The question of how to improve the performance of enterprises to enhance their competitiveness in the market has become a major issue to be addressed in the face of fierce competition and to ensure the long-term development of enterprises. In this paper, based on the research of firm performance evaluation, deep neural network is introduced to analyse the influence of ambidextrous innovation and social network on firm performance, and the theories of social network, ambidextrous innovation and deep neural network are sorted out and analysed, and a deep neural network-based firm performance evaluation model is established, and finally the sample data is obtained using crawler technology, and then the response values are analysed. Innovation and the improvement of the mean value of social networks are helpful to firm performance. [ABSTRACT FROM AUTHOR]

Old urban community renovation is an important task of urban renewal in China. In order to ensure the quality and efficiency of renovation work, the government requires a method to assess the priority for old urban community renovation. This paper proposes an evaluation model from a more comprehensive perspective. It establishes the evaluation index system with CIPP model. The method of Cloud-VIKOR is selected to construct the evaluation model. Finally, selects nine case communities to verify the evaluation model. The results show that the evaluation index system covers the whole process of renovation project and the evaluation indexes proposed in the existing research. The priority decision result of 9 case communities is basically consistent with the actual renovation sequence and does not change greatly due to the fluctuation of decision-making mechanism coefficient or the evaluation index weight. This evaluation model can help decision-makers diagnose and optimize the renovation project. [ABSTRACT FROM AUTHOR]

In this paper, the adoption of SO2 emission tax rates higher than the legal minimum standard is regarded as a noteworthy policy reform in China (quasi-natural experiment), and a spatial Difference-in-Differences (Spatial-DID) model is constructed to test the direct effects (local effects) and indirect effects (spatial spillover effects) of SO2 emission tax policy reform on PM2.5 concentrations in the atmosphere of 285 China's cities. The estimation and calculation results of the Spatial-DID model show that the SO2 emission tax policy reform can significantly reduce local PM2.5 concentration and significantly promote PM2.5 concentration in surrounding areas. The results of heterogeneity analysis show that the SO2 emission tax policy reform can produce a relatively more beneficial spatial spillover effect in eastern cities and higher administrative level cities, while the pollutants emission rights trading and the reform of NOx emission tax rates can produce beneficial spatial spillover effects when cooperating with the reform of SO2 emission tax rates. The results of the mediation effect analysis show that the higher SO2 emission tax rate can aggravate the surrounding PM2.5 pollution by promoting the aggregation level of industrial production factors and the industrial SO2 emission intensity in the surrounding areas, which can support the existence of the pollution heaven effect. [ABSTRACT FROM AUTHOR]

There are urgent ecological and environmental problems in the process of the utilization of urban construction land, promoting green utilization of construction land is conducive to urban sustainable development and high-quality economic development. Based on the panel data of 108 prefecture-level and above cities in the Yangtze River Economic Belt, China from 2003 to 2017, this paper uses the super-efficiency SBM model to measure the green efficiency of urban construction land (GEUCL), analyzes its spatial–temporal evolution characteristics, and constructs the spatial autoregressive model to study its spatial spillover effects from the perspective of urban hierarchy. It is found that, in terms of temporal variation, the average efficiency value shows a fluctuating upward trend during the study period, rising from 0.27 in 2003 to 0.39 in 2017, the cumulative growth rate is 44.44%, with an average annual growth rate of 3.14%. In terms of spatial distribution characteristics, during the study period, the number of medium-efficiency and high-efficiency cities increases significantly, while the number of low-efficiency cities decreases sharply; high-efficiency cities always present scattered distribution, while medium-efficiency cities change from scattered distribution to agglomeration distribution. In addition, GEUCL has significantly positive spatial spillover effects between neighboring cities of different grades and between neighboring cities of the same grade, among them, the increase of GEUCL in higher-grade cities has significantly positive spatial spillover effects on that in adjacent lower-grade cities; the increase of GEUCL in lower-grade cities has significantly positive spatial spillover effects on that in neighboring higher-grade cities; GEUCL has significantly positive spatial spillover effects between neighboring cities of the same grade. [ABSTRACT FROM AUTHOR]

Green innovation plays a crucial role in transforming economic models and achieving sustainable development in enterprises. As an important embodiment of artificial intelligence technology, how industrial robots can effectively promote the green transformation of enterprises has become an important issue. This paper examines the impact and mechanisms of industrial robot adoption on corporate green innovation, as well as its heterogeneous effects. Using data from Chinese listed companies from 2007 to 2019, we find that industrial robot adoption has a significant positive impact on corporate green innovation, enhancing both its quantity and quality. Furthermore, our mechanism study reveals that industrial robot adoption can promote corporate green innovation by improving productivity and environmental management capabilities. Additionally, we investigate the moderating effects of various factors and conclude that the positive impact of industrial robot adoption on green innovation is more pronounced among the state-owned enterprises, enterprises with the intense market competition, as well as enterprises located in regions with higher carbon emissions intensity. This paper contributes to enrich the research on industrial robots and corporate green innovation, and provides a reference to improve environmental management and achieve a low-carbon economy in emerging markets. [ABSTRACT FROM AUTHOR]

The health of young people is crucial for the future and development of a nation. It is the collective responsibility and imperative mission of society to ensure the holistic well-being, both physically and mentally, of young individuals. Therefore, it is essential to thoroughly comprehend the factors that influence their health in order to expedite the exploration of effective solutions. The objective of this study is to comprehend the mechanisms that underlie the correlation between physical exercise behavior and psychological resilience among teenagers, while also examining the mediating role played by social sensitivity and need to belong. So put forward the hypothesis: (1) physical exercise behavior can positively predict the psychological resilience. (2) Social sensitivity and need to belong plays a mediating role between physical exercise behavior and psychological resilience. (3) Social sensitivity and need to belong plays a chain mediating role between physical exercise behavior and psychological resilience. Using the cluster sampling method, a total of 1106 students (with an average age of 15.7 and a standard deviation of 0.598) who met the requirements were surveyed from Shandong Province in China. Standard scales were utilized to assess Physical Exercise Behavior, Psychological Resilience, Social Sensitivity, and Need to Belong. For data analysis, Pearson's correlation analysis and bias-corrected percentile Bootstrap method were sequentially conducted. (1) The present study did not find any significant methodological bias, and the observed correlations between physical exercise behavior, psychological resilience, social sensitivity, and need to belong were all statistically significant; (2) Based on the self-determination theory, this study elucidates the relationship between physical exercise behavior and psychological resilience among teenagers. The findings indicate that physical exercise behavior positively predicts the need to belong and psychological resilience, while negatively predicting social sensitivity. Similarly, social sensitivity negatively predicts the need to belong and psychological resilience. Moreover, the need to belong directly and positively predicts psychological resilience. Importantly, all hypotheses proposed in this paper were empirically supported. (3) The indirect effect of the path mediated by social sensitivity is 0.009, while the indirect effect of the path mediated by need to belong is 0.033. Additionally, the combined indirect effect of both social sensitivity and need to belong as mediating variables is 0.014. (4) The cumulative sum of all these indirect effects amounts to 0.056. Based on the self-determination theory, we propose a chain mediation model, specially, physical exercise behavior can significantly positively predict psychological resilience, among which, social sensitivity and need to belong play a significant mediating role between Physical exercise behavior and psychological resilience. In addition, the adoption of good physical exercise behavior can enhance the psychological resilience of adolescents by diminishing social sensitivity and augmenting the need to belong. [ABSTRACT FROM AUTHOR]

This paper develops a theoretical model of determinants influencing multimodal fake review generation using the theories of signaling, actor-network, motivation, and human–environment interaction hypothesis. Applying survey data from users of China's three leading E-commerce platforms (Taobao, Jingdong, and Pinduoduo), we adopt structural equation modeling, machine learning technique, and Bayesian complex networks analysis to perform factor identification, path analysis, feature factor importance ranking, regime division, and network centrality analysis of full sample, male sample, and female sample to reach the following conclusions: (1) platforms' multimodal recognition and governance capabilities exert significant negative moderating effects on merchants' information behavior, while it shows no apparent moderating effect on users' information behavior; users' emotional venting, perceived value, reward mechanisms, and subjective norms positively influence multimodal fake review generation through perceptual behavior control; (2) feature factors of multimodal fake review generation can be divided into four regimes, i.e., regime 1 includes reward mechanisms and perceived social costs, indicating they are key feature factors of multimodal fake review generation; merchant perception impact is positioned in regime 2, signifying its pivotal role in multimodal fake review generation; regime 3 includes multimodal recognition and governance capabilities, supporting/disparaging merchants, and emotional venting; whereas user perception impact is positioned in regime 4, indicating its weaker influence on multimodal fake review generation; (3) both in full sample, male sample, and female sample, reward mechanisms play a crucial role in multimodal fake review generation; perceived value, hiring review control agency, multimodal recognition and governance capabilities exhibit a high degree of correlation; however, results of network centrality analysis also exhibit heterogeneity between male and female samples, i.e., male sample has different trends in closeness centrality values and betweenness centrality values than female sample. This indicates that determinants influencing multimodal fake review generation are complex and interconnected. [ABSTRACT FROM AUTHOR]

Due to the increased frequency of extreme weather events and the implementation of the China's dual-carbon target, thermal power companies have been under pressure to construct green infrastructure and to actively pursue low-carbon transformation in response to stricter environmental regulations. This research thus selects 30 listed thermal power enterprises in China as study objects and assesses their green investment efficiency in the low-carbon transition process using three-stage DEA evaluation model with environmental regulation as an exogenous variable. Based on this, a benchmark regression model is used to corroborate the relationship between environmental regulation and green investment. Simultaneously, we carry out analysis to compare the correlation between thermal power firms' green investment efficiency and their focus on green investments. The results show in terms of total efficiency that environmental regulation significantly improves the total efficiency of 80% of thermal power enterprises compared to the absence of this exogenous variable. With the addition of environmental regulation, firms' total efficiency declines gradually in general from 2018 to 2022, with the mean value of efficiency falling by 0.068. In terms of stage-specific efficiency, the efficiency of the green investment stage of the majority of firms is between 0.3 and 0.6, which is much lower than that of the operational stage and the market performance stage. In terms of sub-indicator efficiency, both green investment efficiency and social donation efficiency among thermal power enterprises show obvious polarization, with 30% of them having an efficiency of 1 and 30% less than 0.1. In terms of green investment focus, thermal power unit renovation has a more obvious role in boosting the green investment efficiency of thermal power enterprises than do wind power and photovoltaic projects. Therefore, both governmental departments and thermal power enterprises need to take active measures in order to achieve green transformation from the perspective of green investment efficiency. Through the segmentation of important projects of green investment, this paper provides a reasonable investment direction reference for the sustainable transformation of China's thermal power industry. It also provides a rich and novel theoretical basis for the Chinese government to further improve the relevant environmental protection laws and regulations of thermal power industry. [ABSTRACT FROM AUTHOR]

The colloidal borescope, using colloidal particle motion, is used to monitor the flow velocities and directions of groundwater. It integrates advanced techniques such as microscopy, high-speed photography, and big data computing and enjoys high sensitivity at the micron level. However, In the same well, the groundwater flow velocity monitored by colloidal hole mirror is varies greatly from that obtained by conventional hydrogeological monitoring, such as pumping test. In order to solve this problem, the stability catcher and stratified packer are designed to control the interference of the vertical flow in drilling, and to monitor the flow velocity and direction of groundwater velocity at the target aquifer and target fracture. Five wells with different aquifers and different groundwater types were selected for monitoring in south-central China. The instantaneous velocity and direction are converted into east–west component and north–south component, the average velocity and direction is calculated according to the time of 10 min, and the particle trajectory diagram is established. Based on these results, it proposed a concept of cumulative flow velocity. Using curve-fitting equations, the limits of cumulative flow velocities as the monitoring time tends to infinity were then calculated as the actual flow velocities of the groundwater. The permeability coefficient of aquifer is calculated by using the fissure ratio of aquifer, hydraulic slope and flow velocity, and compared with the permeability coefficient obtained by pumping test. The results are as follows: (1) The variation coefficient of the instantaneous flow velocity measured at the same depth in the same well at different times is greater than that of the time average flow velocity and greater than that of the cumulative flow velocity. The variation coefficient of the actual velocity is the smallest, indicating that the risk of using the actual flow velocity is lower. (2) The variation coefficient of the flow rate monitored at different depths in the same well is mainly controlled by the properties of the aquifer. The more uniform water storage space in the aquifer, the smaller the variation coefficient. (3) The comparison between the permeability coefficient obtained by monitoring and the permeability coefficient obtained by pumping test shows that the flow of structural fissure water controlled by planar fissure is more surface flow, and the results are consistent. When the groundwater flow is controlled by pores and solution gaps, the flow channel is complicated, which is easy to produce turbulent flow, and the result consistency is poor. (4) According to different research accuracy requirements, different monitoring and calculation methods can be selected for different aquifers and groundwater types. Researches show that, the permeability coefficient calculated for the actual flow velocity in well DR01 is the same as that calculated for the pumping test. The aquifer characteristics reflected by the coefficient of variation of the actual flow velocity in the same aquifer are more realistic. The pumping test method obtains the comprehensive parameters of a certain aquifer, and this method can be used to monitor a certain fissure. In this paper, the new technology developed for monitoring, and the new algorithm established for data processing, can accurately obtain the flow velocity and direction of groundwater, using capsule hole mirror monitoring method. The key parameters of hydrogeology can be obtained by using one well, which can reduce the time and cost input and improve the work efficiency. [ABSTRACT FROM AUTHOR]

In order to quantitatively calculate the critical depth and critical load of mines affected by rock burst, and to achieve effective prevention and control of rock burst in coal mines, this paper proposes a mechanical model for predicting the occurrence of rock burst in coal mine roadways based on catastrophe theory. Additionally, a theoretical calculation formula for initiating rock burst is derived. The first step was to establish a mechanical analysis model, which directly correlated with the in-situ stress, physical and mechanical characteristics of the coal-rock mass, and engineering structural parameters. Following this, a mechanical instability criterion was derived for the key load-bearing circle within the surrounding rock of the roadway. In the final step, the critical depth and load for rock burst initiation were verified for 25 distinct coal mines in China that were prone to rock burst hazards. The research results demonstrate that the discrepancy between the theoretically calculated critical depth and the actual measured statistical values was less than 35%. In addition, the difference between the theoretically determined critical depth and the value calculated by Pan Yishan was less than 32%. Notably, the ratio of the theoretically calculated critical load to the uniaxial compressive strength of the coal-rock mass ranged from 0.38 to 1.93. This aligns with empirical data on rock burst occurrences, as set out in the engineering classification standards for rock masses. These research outcomes substantiated the practical utility of the proposed theory, thereby laying a robust theoretical groundwork for the quantitative control of rock burst. [ABSTRACT FROM AUTHOR]

Aiming at the current low degree of mechanization of pomegranate sprouting tiller pruning in China, all relying on manual pruning, this paper designs a PLC-based pomegranate sprouting tiller removal machine. This machine adopts the identification method of wireless map transmission, the sprouting tiller removal method of multi-cylinder cooperative operation, and the MCGS configuration to realize the interaction between the user and the system, which realizes the displacement and angle compensation of the end-effector under complex conditions to realize the all-around accurate removal of the pomegranate sprouting tiller. The performance test and finite element analysis showed that the device could remove up to 74.62% of sprouting tillers, and the damage rate was as low as 18%. This meets the requirements of pomegranate plantations for the removal of emergent tillers. [ABSTRACT FROM AUTHOR]

Stool characteristics are of great value to assess diseases, but patients knew little. E-learning applied in health popularization and patient education is booming. In China, WeChat applets has advantages of abundant users, convenient access and low cost, which may be a great media in patient education on stool. This preliminary study aims to develop and evaluate a stool card WeChat applet. We collected stools images during 2020 to 2022 in the Department of Gastroenterology and Hepatology in the Second Affiliated Hospital of Harbin Medical University, constructed a stool card applet named the Doctor Friend Primary Screening Stool Card (DFPSSC) and evaluated it. Eligible participants were divided into the applet, traditional paper media and control group. We implement a series of tests to evaluate the effectiveness. 20 clinicians and participants using the DFPSSC completed a questionnaire to evaluate the usability. We developed the DFPSSC for an E-learning approach. Of 108 volunteers, 97 completed the DFPSSC learning. No significant pretest differences were found among the three groups (P = 0.303). Applet group had significantly higher posttest scores than pretest scores in intervention (P < 0.001, d = 1.68) and simulation (P = 0.006) test, and it had higher scores than other two group (P < 0.001). 63% participants and 59% clinicians strongly agree or agree to the usability of DFSSC. This preliminary study verified that the DFPSSC can effectively improve participants' knowledge of feces, making it an effective clinical tool for patient education and the avoidance of treatment delay. [ABSTRACT FROM AUTHOR]

Sustainable development of agriculture is the basis for achieving social sustainable development. As the basic industry of national economy, green development of agriculture has become an important support for building an environment-friendly society. Agricultural fiscal expenditure is a direct channel for the government to support agriculture and promote agricultural transformation. It is important to analyze the impact of agricultural fiscal expenditure (AFE) on agricultural green total factor productivity (AGTFP) for sustainable agricultural development. Therefore, this paper employs the random effect model and spatial Durbin model to empirically analyze the direct effect and spatial spillover effect of AFE on AGTFP by using the agricultural panel data of 30 provinces in China from 2008 to 2020. Then, by taking the policy proposal as the time node, this paper also conducts a time heterogeneity analysis to measure the impact of policy enactment on AFE and AGTFP. The main conclusions are as follows: (1) AGTFP exists significant positive spatial spillover effect. The "radiation effect" of agricultural green development is significant. (2) AFE can significantly reduce the AGTFP in the local area, that is, 1% increase of AFE in the local area will reduce AGTFP by 0.037%. At present, agriculture is still yield-oriented. The improvement of AFE in the local area will lead to the expansion of local agricultural production and increase pollution emission. (3) AFE has a significant negative spatial spillover effect on AGTFP, that is, for every 1% increase in AFE, the AGTFP will decrease 0.123% in geographically similar areas, while the AGTFP will decrease by 0.116% in economically and geographically similar areas. It is obvious that AFE will promote the optimization of agricultural production conditions in the province, with the "demonstration effect" on the surrounding areas, the enthusiasm of production in the surrounding areas will increase, thus expanding the pollution emission. (4) According to the analysis of different periods, AFE has a negative impact on AGTFP mainly before the reform innovation is proposed in 2015. It indicates that reform policies have a significant impact on agricultural sustainability. [ABSTRACT FROM AUTHOR]

They have provided useful suggestions and corrections to an earlier draft of our paper." now reads:"This study was funded by the "National Natural Science Foundation of China" (Grant numbers: [72274029] and [71774027]) and "The Liaoning BaiQianWan Talents Program". The original article can be found online at https://doi.org/10.1038/s41598-023-40084-x. [Extracted from the article]

The paper presents a novel statistical approach for analyzing the daily coronavirus case and fatality statistics. The survival discretization method was used to generate a two-parameter discrete distribution. The resulting distribution is referred to as the "Discrete Marshall–Olkin Length Biased Exponential (DMOLBE) distribution". Because of the varied forms of its probability mass and failure rate functions, the DMOLBE distribution is adaptable. We calculated the mean and variance, skewness, kurtosis, dispersion index, hazard and survival functions, and second failure rate function for the suggested distribution. The DI index demonstrates that the proposed model can represent both over-dispersed and under-dispersed data sets. We estimated the parameters of the DMOLBE distribution. The behavior of ML estimates is checked via a comprehensive simulation study. The behavior of Bayesian estimates is checked by generating 10,000 iterations of Markov chain Monte Carlo techniques, plotting the trace, and checking the proposed distribution. From simulation studies, it was observed that the bias and mean square error decreased with an increase in sample size. To show the importance and flexibility of DMOLBE distribution using two data sets about deaths due to coronavirus in China and Pakistan are analyzed. The DMOLBE distribution provides a better fit than some important discrete models namely the discrete Burr-XII, discrete Bilal, discrete Burr-Hatke, discrete Rayleigh distribution, and Poisson distributions. We conclude that the new proposed distribution works well in analyzing these data sets. The data sets used in the paper was collected from 2020 year. [ABSTRACT FROM AUTHOR]

Large Scale Natural Draft Cooling Tower has become a hot topic in China because it is an important part of the nuclear power plant, and its environmental impacts include shading, solar energy loss, water deposition and salt deposition. In China, there is no built large-scale natural draft cooling tower of nuclear power plant. Therefore, model prediction becomes an effective way to solve this problem. This paper introduces the basic principles and structure of SACTI (Seasonal and Annual Cooling Tower Impact) model. SACTI is a cooling tower assessment model developed by Argonne National Laboratory, USA. A comparative case study between China's Pengze Nuclear Power Plant and the US Amos Power Plant is also presented. Calculations were carried out for the Pengze and Amos power plants, and the results showed that the maximum value of salt deposition at the Pengze plant was about 166.5 kg/(km2-month) at a distance of 800 m from the cooling tower. The maximum value of salt deposition at the Amos plant was about 92.85 kg/(km2-month) at a distance of 600 m from the cooling tower. Conclusions show that the research work can provide a useful solution in future work, the simulation results of the SACTI model have a potential mean in the absence of monitoring data. This research provides a way to generate simulation data through SACTI program in the design process of nuclear power plant cooling tower, and designers can use these data to determine how the cooling tower will affect the natural environment and manage within an appropriate range to reduce the impact on the environment. [ABSTRACT FROM AUTHOR]

Longwall top coal caving technology is one of the main methods of thick coal seam mining in China, and the classification evaluation of top coal cavability in longwall top coal caving working face is of great significance for improving coal recovery. However, the empirical or numerical simulation method currently used to evaluate the top coal cavability has high cost and low-efficiency problems. Therefore, in order to improve the evaluation efficiency and reduce evaluation the cost of top coal cavability, according to the characteristics of classification evaluation of top coal cavability, this paper improved and optimized the fuzzy neural network developed by Nauck and Kruse and establishes the fuzzy neural network prediction model for classification evaluation of top coal cavability. At the same time, in order to ensure that the optimized and improved fuzzy neural network has the ability of global approximation that a neural network should have, its global approximation is verified. Then use the data in the database of published papers from CNKI as sample data to train, verify and test the established fuzzy neural network model. After that, the tested model is applied to the classification evaluation of the top coal cavability in 61,107 longwall top coal caving working face in Liuwan Coal Mine. The final evaluation result is that the top coal cavability grade of the 61,107 longwall top coal caving working face in Liuwan Coal Mine is grade II, consistent with the engineering practice. [ABSTRACT FROM AUTHOR]

Climate change has become an unavoidable problem in achieving sustainable development. As one of the major industries worldwide, tourism can make a significant contribution to mitigating climate change. The main objective of the paper is to assess the development level of low-carbon tourism from multi-aspect, using the Yellow River Basin as an example. Firstly, this study quantified tourism carbon dioxide emissions and tourism economy, and analyzed their evolution characteristics. The interaction and coordination degree between tourism carbon dioxide emissions and tourism economy were then analyzed using the improved coupling coordination degree model. Finally, this study analyzed the change in total factor productivity of low-carbon tourism by calculating the Malmquist–Luenberger productivity index. The results showed that: (1) the tourism industry in the Yellow River Basin has the characteristics of the initial environmental Kuznets curve. (2) There was a strong interaction between tourism carbon dioxide emissions and tourism economy, which was manifested as mutual promotion. (3) The total factor productivity of low-carbon tourism was increasing. Based on the above results, it could be concluded that the development level of low-carbon tourism in the Yellow River Basin has been continuously improved from 2000 to 2019, but it is still in the early development stage with the continuous growth of carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

This transition from gathering to cultivation is a significant aspect of studying early agricultural practices. Fruit trees are an essential component of food resources and have played a vital role in both ancient and modern agricultural production systems. The jujube (Ziziphus jujuba Mill.), with its long history of cultivation in northern China, holds great importance in uncovering the diet of prehistoric humans and understanding the origins of Chinese agricultural civilization. This paper focuses on the domestication of jujube by analyzing the morphology of jujube stones found in three Neolithic sites in northern China's Qi River basin, Zhujia, Wangzhuang, and Dalaidian. The measurements of these jujube kernels are compared with those found in other areas of northern China, as well as modern jujube kernels that were collected. The measurements revealed that the length-to-diameter (L/D) ratio of sour jujube kernels ranged from 1.36 to 1.78, whereas the L/D ratio of cultivated jujube stones varied between 1.96 and 4.23. Furthermore, jujube stones obtained from Zhujia and Wangzhuang sites exhibit pointed ends and possess an elongated oval or narrow oval shape overall, which is indicative of clearly artificial domestication traits. Therefore, this study suggests that jujube was selected and cultivated as an important food supplement in the Qi River basin no later than around 6200 BP. [ABSTRACT FROM AUTHOR]

Currently, a standardized design and calculation specification for suction drum foundations has yet to exist in China. The engineering design currently depends mainly on the subjective understanding and engineering experience of the designers, which can be considered somewhat blind and subjective. In this paper, we utilize the offshore wind power project in Yangjiang City, Guangdong Province, as our case study. Building upon domestic and international research results, relevant investigations, design specifications, and engineering applications in related fields, we conduct a systematic study on the design calculation and construction control technology of the suction drum foundation. The document presents the design calculation and inspection of the suction drum foundation. Building on this foundation, we propose a sinking feasibility analysis method and a parameter value method for the suction drum foundation calculation. We also examine the suction drum foundation construction process, examining its control parameters, technology, and standards. Finally, based on the measured data from six four-barrel guided frame platform suction drum foundations that were successfully installed, the proposed design and control method are evaluated, and their effectiveness is verified. The results of this study can provide valuable references for the design and construction of similar suction drum foundation platforms. [ABSTRACT FROM AUTHOR]

Encryption chips are specialized integrated circuits that incorporate encryption algorithms for data encryption and decryption, ensuring data confidentiality and security. In China, the domestic SM4 algorithm is commonly utilized, as opposed to the international AES encryption algorithm. These widely implemented encryption standards have been proven to be difficult to crack through crypt analysis methods Currently, power consumption side-channel attacks are the most prevalent method. They involve capturing power consumption data during the encryption process and subsequently recovering the encryption key from this data. The two leading methods are Differential Power Analysis (DPA) and machine learning techniques. DPA does not necessitate prior knowledge but relies heavily on the number of power consumption curves. With only 50 power consumption data points, the accuracy is a mere 80%. Machine learning methods require prior knowledge, achieving an accuracy rate above 95% with only 30 power traces, albeit with training times typically exceeding 15 min. In this paper, a distributed energy analysis attack approach was presented based on Correlation Power Analysis (CPA). The power consumption data was divided into 16 subsets, with each subset corresponding to 8 bytes of the key. By training each subset separately, the 8-byte key's corresponding power consumption data is reduced to only 100 dimensions, resulting in a 76% decrease in cracking time and a 3% improvement in cracking accuracy rate.This article also trains a more complex 256 classification model to directly crack the final key, achieving a success rate of 28% in cracking 128-bit passwords with only 1 power trace [ABSTRACT FROM AUTHOR]

Shenfu Dongsheng coal field is a cross-century energy base which is developed and constructed in China. In recent years, some mines have successively entered to the coal seam of the second layer. Due to the reasons of early mining, many coal pillars are left in the coal seam of the first layer, resulting in the phenomenon of strong ore pressure in the mining range before and after the coal pillar in the lower coal seam and even causing the buckling accident. In order to solve such safety problems, this paper takes the 22,307 working face in Bulianta coal mine as the research object, adopts physical similarity simulation experiment and theoretical analysis to systematically study the overlying rock characteristics and abnormal ore pressure manifestation mechanism of shallow and close coal seam in different working stages. The results show that the roof overburden of the key layer in the lower group bends and sinks when the coal pillar is mined, resulting in the activation and instability of the "masonry beam" structure formed by the roof of the upper coal seam. When the coal pillar is discharged, the residual concentrated coal pillar and the room type coal pillar are unstable under the action of high supporting stress, resulting in shear failure of the inter-layer rock in the upper part of 22,307 working face, causing the strong dynamic pressure of the working face to appear and then leading to the buckling accident. The working resistance of the support in each stage is obtained by establishing the structure diagram of the overlying rock under each stage and the corresponding mechanical structure model. Finally, the working resistance required by the support in the mining stage under the goaf is 16,692.6 kN, the working resistance required by the support in the coal pillar stage is 19,692.6 kN, the working resistance required by the support in the mining stage under the concentrated coal pillar is 13,150.6 kN, and the working resistance required by the support in the coal pillar stage is 19,215.6 kN. [ABSTRACT FROM AUTHOR]

Underground coal mining leads to land subsidence, which, in turn, results in damage to buildings and infrastructure, disturbs the original ecological environment, and hinders the sustainable development of coal mining cities. A reasonable estimation of land subsidence, on the other hand, is the foundation for building protection, land reclamation, and ecological environment reconstruction. However, when we applied the existing land subsidence estimation theory to the deep mining areas of the Ordos coalfield in western China, there was a significant deviation between the estimations and the measurements. To explain such unusual case, we propose using the overburden's average GSI (Geological Strength Index) value instead of the compressive strength (UCS) of rock specimens for a better representation of the overburden's overall properties. By using on-site subsidence monitoring results and historical data, we provided evidence which supports that the overburden's average GSI value has a much greater impact on subsidence rates than the UCS. Subsequently, we investigated the relationship between three typical overburden's GSI values and the subsidence rates via a calibrated numerical model, revealing the variation patterns of maximum surface subsidence when the overburden's average GSI value is set at 30, 50, and 75, respectively. Finally, on the basis of the measured and simulated results, we discussed a non-conventional strip mining method for mining subsidence control in the deep mining areas of the Ordos coalfield in western China, and explained why it is possible and what are the significant advantages behind. The proposed methods, findings, and suggestions in this paper are therefore quite helpful for researchers and engineers who wish to estimate and control the mining-induced land subsidence, as well as for those who are particularly interested in the study of environment science related to land subsidence. [ABSTRACT FROM AUTHOR]

The carbonate rock formations have obvious dual media characteristics, fracture development and good physical conditions, which are the main seepage channels and storage spaces for gas after the reconstruction of underground gas storage. The carbonate strata of the Ordovician system are important natural gas reservoirs in the eastern area of Sulige Gas Field in the Ordos Basin, and the identification and characterization of their fractures are of great significance for the modeling of fractures in the later stage and the improvement of the operation scheme of the gas storage. At present, there is little research on fractures, which restricts exploration and development. Therefore, taking the 39–61 gas storage reservoir in the eastern area of Sulige Gas Field in the Ordos Basin as the research object, this paper identifies and studies the characteristics of the fractures by core, microscopic, conventional logging curves, and imaging logging identification. The results show that the fracture length ranges from 5 to 15 cm and the width ranges from 0.1 to 3 mm. The fracture angles are mostly between 75° and 90° and the main direction is NW–SE. In conventional logging curves, porosity logging has a good response to fractures, while resistivity logging has a general response to fractures; In layers with more developed fractures, natural gamma values are mostly higher than 40API, rock volume density is less than 2.8 g/cm3, neutron porosity is greater than 12.5%, and acoustic time difference is greater than 160 μ s/m. This study is of great significance for improving the identification of carbonate fractures, enriching the relevant theories, and providing guidance for the construction of carbonate gas storage. [ABSTRACT FROM AUTHOR]

Wetland vegetation classification using deep learning algorithm and unmanned aerial vehicle (UAV) images have attracted increased attentions. However, there exist several challenges in mapping karst wetland vegetation due to its fragmentation, intersection, and high heterogeneity of vegetation patches. This study proposed a novel approach to classify karst vegetation in Huixian National Wetland Park, the largest karst wetland in China by fusing single-class SegNet classification using the maximum probability algorithm. A new optimized post-classification algorithm was developed to eliminate the stitching traces caused by SegNet model prediction. This paper evaluated the effect of multi-class and fusion of multiple single-class SegNet models with different EPOCH values on mapping karst vegetation using UAV images. Finally, this paper carried out a comparison of classification accuracies between object-based Random Forest (RF) and fusion of single-class SegNet models. The specific conclusions of this paper include the followings: (1) fusion of four single-class SegNet models produced better classification for karst wetland vegetation than multi-class SegNet model, and achieved the highest overall accuracy of 87.34%; (2) the optimized post-classification algorithm improved classification accuracy of SegNet model by eliminating splicing traces; (3) classification performance of single-class SegNet model outperformed multi-class SegNet model, and improved classification accuracy (F1-Score) ranging from 10 to 25%; (4) Fusion of single-class SegNet models and object-based RF classifier both produced good classifications for karst wetland vegetation, and achieved over 87% overall accuracy. [ABSTRACT FROM AUTHOR]

With the gradual increase of international willingness to reach the carbon peak and carbon neutrality, this paper decomposes the influencing factors of China's carbon emission changes from 2008 to 2019 using the Logarithmic Mean Divisia Index model (LMDI), and analyzes the contribution amount and rate of each influencing factor. The results found that: for the whole country, the cumulative growth of carbon emissions during the study period is about 416,484.47 (104 tons), among which the economic growth effect plays a major role in promoting, with a cumulative contribution rate of 284.16%; The increase in regulation intensity and the optimization of industrial structure, however, suppress carbon emissions well, with a cumulative contribution rate of about – 199.21% and − 64.75%, respectively, during the study period. For economic regions, the cumulative influence direction of each driver is the same as that of the whole country, while the population size effect in the northeast economic region and the regulation input effect in the eastern coastal economic region act in the opposite direction from other economic regions, and the carbon emission reduction direction of the energy intensity effect varies from one economic region to another. Accordingly, this paper proposes policy recommendations to enhance regulatory intensity, optimize industrial and energy consumption structure, implement localized emission reduction strategies, and promote synergistic emission reduction in economic zones. [ABSTRACT FROM AUTHOR]

In this paper, production system (PS) of shale oil is optimized according to production data and indoor experiments, including core and fluid tests. Results showed that: ① Pressure drop rate at wellhead is a reasonable reference for the determination of post-fracture shut-in duration (PFSID). When pressure at a wellhead of horizontal well is relatively stable and the pressure drop less than 0.1 MPa per day for three consecutive days, PFSID ends; ② Flowback intensity of fracturing fluid affects the effectiveness of proppant underground, thus flowback intensity can be determined by the critical flow rate and safety factor of each proppant; ③ Flowback intensity should be varied during different development stages, which could be divided into four according to production gas and oil ratio(GOR) of a shale oil horizontal well: low, medium–high, high and high-low production GOR. During the stage of low production GOR, ratio of flow pressure and saturation pressure should be maintained greater than 1.0, and the initial daily liquid productivity for a hundred-meter oil-bearing lateral length in a horizontal well is 2.4 ~ 2.9 m3/d; and during the medium–high production GOR, high production GOR and high-low production GOR stages, the responding initial daily liquid productivity should be maintained between 0.8 ~ 1.0 or less than 0.8 respectively. [ABSTRACT FROM AUTHOR]

Agglomeration of the industry significantly impacts economic performance and environmental sustainability. In line with its strategic context of striving to achieve carbon reduction targets, China is making efforts to optimize the producer services landscape to reduce carbon emissions. Understanding the spatial correlation between industrial agglomeration and carbon emissions is particularly crucial against this background. Based on POI and remote sensing data of China's Yangtze River Economic Belt (YREB), the paper adopts the mean nearest neighbor analysis, kernel density analysis, and standard deviation ellipse to portray the agglomeration of producer services. Then uses Moran's I to present the spatial distribution characteristics of carbon emissions. Accordingly, the spatial heterogeneity of producer services agglomeration and carbon emissions is showed using the Geographic detector so as to provide strong support for industrial structure optimization and sustainable development. Here are some of the conclusions drawn from the study: (1) Producer services are a significant state of agglomeration in the provincial capitals and some central cities, with similar agglomeration patterns. (2) Carbon emissions exhibits significant spatial aggregation characteristics, with the spatial distribution pattern of "High west–Low east". (3) Wholesale and retail services industry is the primary risk factor that causes spatial differentiation of carbon emission intensity, "leasing and business services industry-wholesale and retail services industry" is the key interaction factor of the spatial differentiation. (4) Carbon emissions shows a downward trend followed by an upward trend as producer services agglomeration increases. [ABSTRACT FROM AUTHOR]

Based on the counted power system emission factors of North China Power Grid, a community carbon emissions sample database is constructed. The support vector regression (SVR) model is trained to forecast the power carbon emissions, which is optimized by genetic algorithm (GA). A community carbon emission warning system is designed according the results. The dynamic emission coefficient curve of the power system is obtained by fitting the annual carbon emission coefficients. The time series SVR carbon emission prediction model is constructed, while the GA is improved to optimize its parameters. Taking Beijing Caochang Community as an example, a carbon emission sample database is generated based on the electricity consumption and emission coefficient curve to train and test the SVR model. The results show that the GA–SVR model fits well with the training set and the testing set, and the prediction accuracy of the testing set reaches 86%. In view of the training model in this paper, the carbon emission trend of community electricity consumption in the next month is predicted. The carbon emission warning system of the community is designed, and the specific strategy of community carbon emission reduction is proposed. [ABSTRACT FROM AUTHOR]

High temperature impacts the performance of marathon athletes, and hypothermia harms athletes. Twenty-one runners died, and eight were injured in the China Baiyin marathon on May 22, 2021. It's a typical human life test. The energy equations are combined with the maximum energy supply of Chinese male athletes to study this accident. We analyze the human body's route slope, travel speed, and heat dissipation under low temperatures in this marathon. The study shows that the large slope and long-distance of CP2 to CP3 section and the low temperature during the competition are the main reasons for the accident. The method of quantifying the slope and temperature and calculating the percentage of athletes' physical consumption proposed in this paper can evaluate the route design of field marathons. We suggest that the physical energy consumption ratio of 90%, i.e. 315 cal/min/kg, should be taken as the maximum energy supply for Chinese male marathon runners. Dangerous risk zones for wind speed and temperature on dangerous path sections are also formulated for athletes to make their assessments. This paper's theories and methods can effectively help design the marathon route and determine the race time. [ABSTRACT FROM AUTHOR]

This paper presents a predictive analysis of the Chinese economy in the post-epidemic era. Five major public health emergencies historically similar to the COVID-19 epidemic are used as the control group, and a fuzzy mathematical model is applied to forecast and analyze China's economy after the COVID-19 epidemic. The forecast results show that China's overall economy will have recovered to the pre-epidemic level in about 1 year, with the fastest recovery in individual economic indicators, followed by government final consumption and imports, then CPI, fiscal revenue, exports and money supply, and the slowest recovery in employment. Finally, a combination of all the parties makes policies and recommendations for China's economic and social development in the post-epidemic era. [ABSTRACT FROM AUTHOR]

20-inch Large area photomultiplier tube based on microchannel plate (MCP-PMT) is newly developed in China. It is widely used in high energy detection experiments such as Jiangmen Underground Neutrino Observatory (JUNO), China JinPing underground Laboratory (CJPL) and Large High Altitude Air Shower Observatory (LHAASO). To overcome the poor time performance of the existing MCP-PMT, a new design of large area MCP-PMT is proposed in this paper. Three-dimensional models are developed in CST Studio Suite to validate its feasibility. Effects of the size and bias voltage of the focusing electrodes and MCP configuration on the collection efficiency (CE) and time performance are studied in detail using the finite integral technique and Monte Carlo method. Based on the simulation results, the optimized operating and geometry parameters are chosen. Results show that the mean ratio of photoelectrons landing on the MCP active area is 97.5%. The acceptance fraction of the impinging photoelectrons is close to 100% due to the emission of multiple secondary electrons when hitting the MCP top surface. The mean transit time spread (TTS) of the photoelectrons from the photocathode is 1.48 ns. [ABSTRACT FROM AUTHOR]

Nowadays environmental issues have been of great concern to the world, among which the problem of global warming caused by greenhouse gas emissions is particularly prominent. All countries in the Kyoto Protocol and the Paris Agreement have committed to control greenhouse gas emissions, and China, as the largest carbon emitter, has assumed a heavier burden. China has been striving to develop low-carbon technologies such as hydrogen, nuclear, wind, and solar energy, but the most attention should be paid to CCUS, which many scholars have high expectations that CCUS can help China reduce emissions to some extent. Therefore, this paper presents a prediction that CCUS can reduce 3.8% of carbon emissions for China in 2040 when CCUS emission reductions increase at a rate of 30%. The power and chemical industries could reduce carbon emissions by 2.3% and 17.3%, respectively. [ABSTRACT FROM AUTHOR]

Bats are a crucial component within ecosystems, providing valuable ecosystem services such as pollination and pest control. In practical conservation efforts, the classification and identification of bats are essential in order to develop effective conservation management programs for bats and their habitats. Traditionally, the identification of bats has been a manual and time-consuming process. With the development of artificial intelligence technology, the accuracy and speed of identification work of such fine-grained images as bats identification can be greatly improved. Bats identification relies on the fine features of their beaks and faces, so mining the fine-grained information in images is crucial to improve the accuracy of bats identification. This paper presents a deep learning-based model designed for the rapid and precise identification of common horseshoe bats (Chiroptera: Rhinolophidae: Rhinolophus) from Southern China. The model was developed by utilizing a comprehensive dataset of 883 high-resolution images of seven distinct Rhinolophus species which were collected during surveys conducted between 2010 and 2022. An improved EfficientNet model with an attention mechanism module is architected to mine the fine-grained appearance of these Rhinolophus. The performance of the model beat other classical models, including SqueezeNet, AlexNet, VGG16_BN, ShuffleNetV2, GoogleNet, ResNet50 and EfficientNet_B0, according to the predicting precision, recall, accuracy, F1-score. Our model achieved the highest identification accuracy of 94.22% and an F1-score of 0.948 with low computational complexity. Heat maps obtained with Grad-CAM show that our model meets the identification criteria of the morphology of Rhinolophus. Our study highlights the potential of artificial intelligence technology for the identification of small mammals, and facilitating fast species identification in the future. [ABSTRACT FROM AUTHOR]

As an important part of urban public open space, pocket parks have become an important activity place for the elderly in the context of the aging society in China. With the pocket parks in Nanjing, Jiangsu province, China as research object, this paper set six landscape features to be studied, namely, Height of trees, Green color richness, Stratification of green landscapes, Green space ratio, Leisure facilities, and Water landscape. The elderly respondents with different demographic characteristics, such as age, gender, education level and residential type, were subjected to the picture stimulation experiment whose results were then statistically analyzed. The results indicate that gender and residential type exert certain influence on the elderly's visual impact assessment of pocket park landscape. To be specific, the male elderly prefer the pocket park landscape with 3-6 m high trees, medium green space ratio, and more leisure facilities; the female elderly are in greater favor of pocket park landscapes with 0-3 m high trees, five or more colors, three or more layers; the elderly who live with their families prefer pocket park landscapes with medium green space ratio and more leisure facilities; to the elderly who live alone, pocket park landscapes with trees which are 0–3 m high, five or more colors, and medium leisure facilities are more attractive. This study can provide valuable reference for pocket park design in China. [ABSTRACT FROM AUTHOR]

The Yellow River Basin is a key ecological barrier and commercial zone in China, as well as an essential source of energy, chemicals, raw materials, and fundamental industrial foundation, the achievement of its carbon peaking is of great significance for China's high-quality development. Based on this, we decomposed the influencing factors of carbon dioxide emissions in the Yellow River Basin using the LMDI method and predicted the carbon peaking in the Yellow River Basin under different scenarios using the STIRPAT model. The results show that (1) the energy intensity effect, economic activity effect and population effect play a positive role in promoting carbon emissions during 2005–2020. The largest effect on carbon emissions is the population size effect, with a contribution rate of 65.6%. (2) The STIRPAT model predicts that the peak of scenarios "M–L", "M–M" and "M–H" will occur in 2030 at the earliest. The "M–H" scenario is the best model for controlling carbon emissions while economic and social development in the Yellow River Basin. The results of this paper can provide a theoretical basis for the development of a reasonable carbon peak attainment path in the Yellow River Basin and help policy makers to develop a corresponding high-quality development path. [ABSTRACT FROM AUTHOR]

Previous scientific research on reservoirs of the Deng IV Member in the Gaoshiti-Moxi area, the main production area of the Anyue gas field with reserves of tens of billions of cubic metres, has focused on karst palaeogeomorphology reconstruction, the facies distribution on platform margins, and their effects on creating favourable reservoirs. However, the quality of microbial carbonate reservoirs is also closely related to their original depositional environments on both inner and marginal platforms. Therefore, this paper attempts to reveal favourable microbial carbonate reservoir characteristics and the sedimentary effects on their distribution and prediction based predominantly on a synthetic analysis of the sequence stratigraphy and depositional facies. The results show that favourable reservoirs of the Deng IV Member are classified into three types according to their reservoir spaces: fracture-cavity, pore-cavity and pore reservoirs. Secondary dissolution pores and cavities are primary reservoir spaces developed mainly in nonskeletal grain dolomites with sparry cements, thrombolites, and stromatolites. The physical properties of the fracture-cavity and pore-cavity types of reservoirs are better than those of pore reservoirs and have porosities between 1 and 5% and permeabilities between 0.01 × 10–3 and 1 × 10–3 μm2. Vertically, favourable reservoirs are developed mainly in parasequence set 6 (PSS6) and PSS7 and are laterally distributed in well zone MX9-MX19-MX1 for the fracture-cavity type, MX105-MX110-GS20 for the pore-cavity type and MX17-MX107-MX41-MX102-GS102 for the pore type. Moreover, depositional effects on reservoirs in terms of depositional sequences, seismic facies, microfacies and microfacies associations indicate that to some extent, the fracture-cavity type of reservoir is constrained by the top boundaries of PSS7, PSS2, parasequence 17 (PS17) and PS14; the pore-cavity type of reservoir is constrained by the top boundaries of PSS7, PSS4, PS18 and PS12; and the pore type of reservoir is constrained by the top boundaries of PSS7, PSS6, PSS3, PSS2, PS18, PS17, PS14, and PS12. Seismic facies associated with shoals and mound-flat complexes are related to the facies distributions of pore cavities and pore reservoirs. MA1, MA3, MA7, and MA8 are predominant microfacies associations of favourable reservoirs of the Deng IV Member in the Gaoshiti-Moxi area. The above results are significant for further petroleum exploration and exploitation of ultradeep microbial carbonate reservoirs in this area. [ABSTRACT FROM AUTHOR]

Based on the literature on the factors influencing port competitiveness, this paper evaluates the competitiveness of Chinese ports along the Belt and Road based on Porter's diamond model. The evaluation system includes four primary indicators, including port infrastructure, port operation scale, port hinterland economic level and port development potential, and 13 secondary indicators. Then, based on the entropy-TOPSIS method, an evaluation model of port competitiveness is constructed. Finally, 15 seaports along China's "Belt and Road" are used to evaluate competitiveness, and a comprehensive ranking of port competitiveness is obtained. The advantages and shortcomings of each port are pointed out according to the evaluation results to provide a reference for the long-term development of the competitiveness of ports along the "Belt and Road" in China. [ABSTRACT FROM AUTHOR]

Despite being a clean and renewable energy source, photovoltaic (PV) power generation faces severe challenges in operation due to its strong intermittency and volatility compared to the traditional fossil fuel power generation. Accurate predictions are therefore crucial for PV's grid connections and the system security. The existing methods often rely heavily on weather forecasts, the accuracy of which is hard to be guaranteed. This paper proposes a novel GBDT-BiLSTM day-ahead PV forecasting model, which leverages the Teacher Forcing mechanism to combine the strong time-series processing capabilities of BiLSTM with an enhanced GBDT model. Given the uncertainty and volatility inherent in solar energy and weather conditions, the gradient boosting method is employed to update the weak learner, while a decision tree is incorporated to update the strong learner. Additionally, to explore the correlation between photovoltaic power output and historical time-series data, the adaptive gradient descent-based Adam algorithm is utilized to train the bidirectional LSTM model, enhancing the accuracy and stability of mid- to long-term time-series predictions. A prediction experiment, conducting with the real data from a PV power station in Sichuan Province, China, was compared with other methods to verify the model's effectiveness and robustness. [ABSTRACT FROM AUTHOR]

Public sports venues serve as a crucial material medium for human athletic activities. Research on their spatial distribution holds profound implications for optimizing spatial layout and promoting human sports endeavors. This paper takes interest points of sports venues in China as research samples, employing GIS spatial analysis tools, mathematical statistics, and Geo-detector as research methods. It systematically investigates the spatial distribution characteristics and causes of sports venues in China, aiming to provide insights and references for the optimization of spatial arrangement, sustainable development, and relevant policy formulation of sports venues in the country. The results indicate that: (1) In terms of overall distribution characteristics, sports venues in China present a multi-centric agglomeration in geographical space. (2) From a regional distribution perspective, the spatial layout of these venues reveals a pattern of "more in the south, less in the north," "dense in the southeast, sparse in the northwest," and a coastal strip distribution. (3) Regarding spatial correlation, the hot and cold spot partitions of sports venues largely align with the "Hu-Line", with their spatial distribution tending towards a positively correlated pattern of high–high clustering and low–low clustering. (4) There is evident heterogeneity in factors affecting sports venues' spatial distribution. The distribution results from the interactive coupling of multiple factors, where the interaction between any two factors offers stronger explanatory power for the spatial layout of the venues. [ABSTRACT FROM AUTHOR]

China's economic growth has reached a new plateau. It is no longer appropriate to use the old economic growth model, which relied on labor, land resources, mineral resources, and other economic considerations. Under the background of artificial intelligence, high-quality economic development is an inevitable trend. A new financial paradigm called "digital finance" integrates financial services with information technologies. Digital financial technology is thought to be a crucial foundation for fostering high-quality and sustainable economic and social development since it may offer more economic entities reduced cost of capital and more realistic financial service skills than in traditional financial models. In the era of artificial intelligence, how to reasonably release the momentum of digital finance for China's sustained economic growth has become a hot topic of discussion at this stage. This paper studies the impact of digital finance on the economic efficiency of the energy industry in the context of artificial intelligence. Relevant metrics were also calculated. The findings revealed that: The benchmark regression result of digital finance on the efficiency of the green economy was 0.4685 before adding the main restrictions; the benchmark regression result of digital finance on the efficiency of the green economy was 0.2243 after adding the main constraints. As a result, data finance had a favorable impact on the effectiveness of the green economy. [ABSTRACT FROM AUTHOR]

Patients narratives are being recorded increasingly frequently and spontaneously in short user produced content (UGC) films, which may have an impact on the vlogger's health as well as the public's comprehension of the relevant health concerns. This paper addressed three research questions regarding the population characteristics of UGC video publishers, the narrative theme of the videos, and the emotional orientation of the commenters. This study aimed to deepen our understanding of COVID-19 patients' narrative intentions and emotional needs through the theoretical frameworks of theory of planned behavior (TPB) and negative dominance theory (NDT). We collected 335 videos from 28 COVID-19 patients and 572,052 comments as samples on Douyin platform, the largest short-video website in China. Using Latent Semantic Analysis, we analyzed the descriptive information of the video blogs, the narrative textual information of the videos, and the emotional orientation of the comments. Our findings revealled seven categories of narrative themes, with 52.1% of video comments exhibiting a positive emotional orientation. Within a framework integrating TPB and NDT theories, we analyzed the behavioral intentions of vloggers and viewers during COVID-19 epidemic, and interpreted the persistent posting of videos and the active posting of comments as positive actions that counteracted the multiple effects of negative messages. This study contributes to the understanding of individual narratives in macro-risk communication, both theoretically and empirically, and offers policy recommendations in relevant fields. [ABSTRACT FROM AUTHOR]

China's construction industry has assumed an important role in China's urbanization process, improving China's urban landscape and the level of national production and living facilities, but the productivity of the construction industry in some regions of China is still at a relatively low level. Taking the construction industry in Guangxi province in southwest China as an example, this paper analyzes the relevant indexes affecting the total factor productivity level of the regional construction industry and composes the statistical relationships among the indexes using dynamic measurement methods, and obtains that: (1) The number of employees, enterprises, labor productivity and construction profit have positive influence on the total factor productivity of Guangxi construction industry, but the improvement of regional construction gross product does not drive the improvement of technical equipment rate; (2) There is a dynamic equilibrium relationship between input and output indicators of total factor productivity of Guangxi construction industry, and the positive driving effect of output indicators on input indicators is not obvious; the influence of input indicators on output indicators is greater, and the positive influence is more. Accordingly, this paper also puts forward corresponding suggestions to promote the technical production level of Guangxi's construction industry. [ABSTRACT FROM AUTHOR]

A better understanding of various patterns in the coronavirus disease 2019 (COVID-19) spread in different parts of the world is crucial to its prevention and control. Motivated by the previously developed Global Epidemic and Mobility (GLEaM) model, this paper proposes a new stochastic dynamic model to depict the evolution of COVID-19. The model allows spatial and temporal heterogeneity of transmission parameters and involves transportation between regions. Based on the proposed model, this paper also designs a two-step procedure for parameter inference, which utilizes the correlation between regions through a prior distribution that imposes graph Laplacian regularization on transmission parameters. Experiments on simulated data and real-world data in China and Europe indicate that the proposed model achieves higher accuracy in predicting the newly confirmed cases than baseline models. [ABSTRACT FROM AUTHOR]

The widespread use of the Internet of Things (Iot) makes it possible to connect everything but having enough IP addresses is a fundamental requirement of this paradigm. All previous environmental monitoring systems in China are based on IPv4. In combination with the characteristics and requirements of China's atmospheric environment monitoring system, this paper develops a monitoring system based on IPv6 technology. Users can directly access the monitoring equipment through the IPv6 website to view data and configure operations. This paper first introduces the design and implementation of the software and hardware of the system, then introduces the simplification of IPv6 protocol, the transplantation of IPv6 protocol on ARM and the design and implementation of embedded Web server system. The experimental results show that the developed atmospheric environment monitoring system can realize continuous data acquisition based on IPv6 and provide data-driven support for environmental protection management and decision-making. [ABSTRACT FROM AUTHOR]

Many developing countries are facing the difficulty of choosing between economic growth and energy conservation and emission reduction (ECER). China has strengthened the implementation of ECER by setting environmental accountability as the development goal of local governments, hoping to have better governance effects. To evaluate the actual intervention effect of this approach, this paper constructs panel data covering 46 countries from 1995 to 2014 and uses the difference-in-differences (DID) method and the composite control method to quantitatively analyse the policy effect. The results show that China can effectively curb energy consumption and carbon emission intensity per unit of GDP by adding ECER targets to the government's five-year plan, which has significant effects on ECER. Furthermore, we use an intermediary mechanism to test and identify low-carbon alternatives and an ECER promotion mechanism for technological advancement. The conclusion shows that economic development is compatible with low carbon and energy consumption. Combined with China's long-term goals for ECER, it can be considered that on the road to achieving carbon peaking and carbon neutrality in the future, the economy and tertiary industry should be rationally developed, the degree of urbanization should receive more attention, and the proportion of thermal power generation should be reduced. [ABSTRACT FROM AUTHOR]

Mega-urban agglomerations in developing countries have been main parts of economic development. But at the same time, they have become the most prominent and sensitive areas of resource and environment problems. It is important to clarify the mechanism and driving factors of green growth in mega-urban agglomerations. Based on the panel data of 28 major cities in China's Pan-Pearl River Delta urban agglomeration from 2006 to 2015, this paper evaluates the level of green development of urban agglomeration by green total factor productivity index (GTFP) based on Global Malmquist DEA model, and decomposes GTFP into technological progress, pure technical efficiency change, scale efficiency change and technological scale change. On this basis, this paper constructs a panel econometric model to analyze the influencing factors of GTFP and its decomposition factors. The results show that GTFP of Pan-Pearl River Delta urban agglomeration is growing, and the scale effect caused by technological progress is the main driving factor. Green development in the Pearl River Delta urban agglomeration takes into account efficiency and regional fairness, which causes differences in GTFP growth patterns of sub-urban agglomerations within mega-urban agglomerations. The technological progress and technical efficiency improvement are becoming the main driving force of GTFP growth in relatively backward areas. Furthermore, according to the influencing factors of GTFP and its decomposition factors, mega-urban agglomeration should eliminate internal administrative barriers to build an integrated market. It should also increase the proportion of technology industries in core cities, and give full play to the role of technology spillover effect on surrounding cities. In addition, improving the efficiency of resource and energy utilization is also helpful to promote the transformation of urban agglomeration development from factor-driven to efficiency-driven and innovation-driven. Our research results have implications for the coordinated development of economy and environment in developing countries. [ABSTRACT FROM AUTHOR]

Forestry plays an essential role in reducing CO2 emissions and promoting green and sustainable development. This paper estimates the CO2 emissions of 30 provinces in China from 2008 to 2017, and uses Global DEA-Malmquist to measure the total factor productivity of the forestry industry and its decomposition index. On this basis, by constructing a spatial econometric model, this paper aims to empirically study the impact of forestry industry's total factor productivity and its decomposition index on CO2 emissions, and further analyze its direct, indirect and total effects. The study finds that the impact of forestry industry's total factor productivity on CO2 emissions shows an "inverted U-shaped" curve and the inflection point is 0.9395. The spatial spillover effect of CO2 emissions is significantly negative. The increase of CO2 emissions in adjacent areas will provide a "negative case" for the region, so that the region can better address its own energy conservation and emission reduction goals. TFP of forestry industry also has positive spatial spillover effect. However, considering the particularity of forestry industry, this effect is not very significant. For other factors, such as foreign direct investment, urbanization level, industrial structure and technology market turnover will also significantly affect regional CO2 emissions. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) is an infectious disease that threatens human safety. Mainland China is an area with a high incidence of tuberculosis, and the task of tuberculosis prevention and treatment is arduous. This paper aims to study the impact of seven influencing factors and spatial–temporal distribution of the relative risk (RR) of tuberculosis in mainland China using the spatial–temporal distribution model and INLA algorithm. The relative risks and confidence intervals (CI) corresponding to average relative humidity, monthly average precipitation, monthly average sunshine duration and monthly per capita GDP were 1.018 (95% CI 1.001–1.034), 1.014 (95% CI 1.006–1.023), 1.026 (95% CI 1.014–1.039) and 1.025 (95% CI 1.011–1.040). The relative risk for average temperature and pressure were 0.956 (95% CI 0.942–0.969) and 0.767 (95% CI 0.664–0.875). Spatially, the two provinces with the highest relative risks are Xinjiang and Guizhou, and the remaining provinces with higher relative risks were mostly concentrated in the Northwest and South China regions. Temporally, the relative risk decreased year by year from 2013 to 2015. It was higher from February to May each year and was most significant in March. It decreased from June to December. Average relative humidity, monthly average precipitation, monthly average sunshine duration and monthly per capita GDP had positive effects on the relative risk of tuberculosis. The average temperature and pressure had negative effects. The average wind speed had no significant effect. Mainland China should adapt measures to local conditions and develop tuberculosis prevention and control strategies based on the characteristics of different regions and time. [ABSTRACT FROM AUTHOR]

A recent surge of patent applications among public hospitals in China has aroused significant research interest. A country's healthcare innovation capacity can be measured by its number of patents. This paper explores the link between the number of patents and ten independent variables. Multicollinearity was carefully detected and removed by using the variable selection method and LASSO regression, respectively. The Poisson model and the negative binomial model were proposed to analyze the patent data. Three goodness of fit tests, the Pearson test, the deviance test, and the DHARMa non-parametric dispersion test, were conducted to investigate if the model has a good fit. After discovering four clusters by conducting agglomerative hierarchical clustering, these two models were replaced by the negative binomial mixed model. The likelihood ratio test was used to determine which model is more appropriate and the results reveal that the negative binomial mixed model outperforms both the Poisson model and the negative binomial model. Three variables, number of health technicians per 10,000 people, financial expenditure on science and technology as well as number of patent applications per 10,000 health personnel, have a significantly positive relationship with the number of patents in Chinese tertiary public hospitals. [ABSTRACT FROM AUTHOR]

In order to reveal the relationship between new urbanization and carbon emission to provide reference opinions for the construction of low-carbon urbanization, an evaluation system between new urbanization and carbon emission was constructed. Then their matching degree relationship was analyzed by coupling coordination degree model based on the data from 2012 to 2021 in Anhui Province, and their development trend from 2023 to 2032 was predicted by gray prediction model. The results show that: (1) New urbanization and carbon emission have the co-trend effect, and the consistency of core impact factors is relatively significant. Among them, the level of new urbanization increases from 0.058 in 2012 to 0.699 in 2021 and carbon emission development increases from 0.023 in 2012 to 0.165 in 2021, which both showing an upward trend. Meanwhile, social urbanization and population carbon emission are the core influencing factors. (2) The coupling coordination degree between new urbanization and carbon emission is low, but the synergy trend is optimistic and there is a large room for improvement. Among them, the coupling coordination coefficient of the coupling system rises from 0.136 in 2012 to 1.412 in 2021 (antagonistic phase), and then reaches 0.820 by 2032 (highly coordinated phase) by forecast. It shows that their current development is unbalanced, but the development trend is good, and there is a chance for improvement. This paper deepens the understanding of the logical correlation between new urbanization and carbon emission, and the following views are formed: (1) Low-carbon development is still the mainstream of new urbanization; (2) The coordination development of new urbanization and carbon emission reduction should be strengthened. [ABSTRACT FROM AUTHOR]

China's flower industry is developing rapidly, and the size of the retail market is increasing year by year. Studying the factors influencing residents' flower purchasing behavior and understanding their flower needs can help promote the sustainable development of the flower industry. Based on customer satisfaction theory, this paper uses 838 consumer research questionnaires from 15 districts in Shanghai to analyze the influence of customer satisfaction on residents' flower purchasing behavior by conducting a binary logit model and to investigate the moderating effect of flower purchasing purpose on the influence of satisfaction. The results show that price satisfaction and satisfaction with promotional methods have a significant negative effect on flower purchasing behavior, service satisfaction has a significant positive effect on purchasing behavior, and different customer purchase purposes lead to different intensities of the effect of satisfaction on purchasing behavior. According to the conclusion of the study, three countermeasures are proposed: to popularize the knowledge of flower culture, guide the concept of flower consumption, and promote the transformation of flower consumption to daily consumption; to conduct regular research on consumers by flower merchants to clarify consumers' needs and improve their satisfaction; to clarify consumers' purchase intention, increase the investment in the research and development and cultivation of flower products, and improve the supply level of flowers. [ABSTRACT FROM AUTHOR]

Carbon sequestration in farmland ecosystems is an important link in the world carbon cycle and plays an important role in regional carbon reduction. Guangdong, a major industrial and economic province in China, was used as the study area, and the period 2001–2020 was taken as the study period. The carbon emissions, sequestration, and footprint of farmland ecosystems in Guangdong were estimated using carbon emission factors for agricultural inputs that are closer to the actual situation in China. The study showed that: (1) Carbon average emissions from farmland in Guangdong during the study period was 3.7624 million t a−1, with a balanced overall trend of change, and that nitrogen fertilize applications was the main factor contributing to carbon emissions. (2) The carbon sink capacity of Guangdong farmland ecosystems showed an overall decreasing trend of 10.32%, with an average annual carbon sink of 19.0363 million t a−1. Paddy and sugar cane cultivations were the main factor of carbon sink in farmland. (3) The average annual carbon footprint of Guangdong's farmland ecosystems was 531,100 ha a−1, which was in a carbon surplus. Carbon surplus and footprint showed a decreasing trend year by year. The paper results provide a theoretical basis for the formulation of carbon emission reduction policies and industrial restructuring in Guangdong and provinces with the same industrial structure. [ABSTRACT FROM AUTHOR]

As an important embodiment of a country's economic strength and national health, pharmaceutical manufacturing industry has made rapid development in China in recent years. But at the same time, the pharmaceutical manufacturing industry is facing many environmental problems, such as large pollution emissions, complex pollution components, controlling difficulties and so on. This paper measures the total factor productivity of pharmaceutical manufacturing industry (HTFP) by using data envelopment analysis with unexpected output, which is more accurate and effective than the traditional model. It also studies the effect of environmental regulation on the total factor productivity of pharmaceutical manufacturing industry (HTFP) by establishing panel data regression model and spatial econometric model based on 30 provinces in China from 2004 to 2019, which enriches the research results in the field of cleaning in pharmaceutical manufacturing industry. The conclusions are as follows: (1) Environmental regulation and total factor productivity of pharmaceutical manufacturing industry have significant spatial autocorrelation, showing "high-high" or "low-low" spatial aggregation characteristics; (2) Environmental regulation has a significant promoting effect on improving pharmaceutical manufacturing total factor productivity in local and surrounding areas, and there are differences in the impact of eastern, central and western regions; (3) Green technology, production technology and industrial structure play an important role in the impact of environmental regulation on pharmaceutical manufacturing total factor productivity, which provides theoretical guidance and policy recommendations for improving the level of total factor productivity of pharmaceutical manufacturing industry in the environmental aspect. [ABSTRACT FROM AUTHOR]

Under the background of the new development concept, compared with the absolute impacts, the relative impacts of climate change on agricultural growth deserve more attention. Based on the data from China for years 1991 and 2018, this paper uses historical fluctuations in temperature within cities to identify the heterogeneous effects on aggregate agricultural outcomes during farming and fallow periods. The results show that: first, as temperature rises reduce the economic growth rate of each agricultural sector, and the areas that are relatively vulnerable (i.e., areas where disposable income of farm households is below the sample mean) are more significantly affected by the negative impact of temperature rise; second, the impact of temperature rise on agricultural economic growth is mainly concentrated in the farming period, while the marginal damage of temperature rise is on a decreasing trend; third, the heterogeneous impact of temperature rise on agricultural economic growth during the agricultural fallow period is also not negligible. At the same time, its impact on agricultural economy is still in the primary stage, that is, its marginal damage tends to increase with the increase in temperature fluctuation. These results inform identifying the climate's role in agricultural development and provide a theoretical and operational perspective for further optimizing the adaptive policy systems. With wide coverage of adaptive technology, we should pay more attention to the even distribution of technological dividends and continuously improve the coping ability of vulnerable groups. [ABSTRACT FROM AUTHOR]

In people's daily life, egg is one of the main animal protein foods, which will produce different emissions on its breeding procedure. Therefore, in order to promote the development of China's layer industry, it is necessary to reduce pollutant emissions by improving efficiency. This paper uses Minimum distance to weak efficient frontier-Metafrontier Malmquist Luenberger (MinDW-MML) index model, by considering environmental factors and scale heterogeneity, to explore the evolution characteristics of laying hens breeding green total factor productivity (LHG) in China based on the data of 24 major laying provinces (municipalities) from 2004 to 2018. The results show that: (1) From 2004 to 2018, medium-scale LHG in China is the highest, the small-scale is the second, and the large-scale is the lowest. In the light of regional distribution, the western region is the highest, followed by the central region, and the eastern region is the lowest. (2) From 2004 to 2018, the overall China's LHG showed a positive growth, and the decomposition indicators were characterized by decreased efficiency and technological progress. In general, the layer industry is vulnerable and easily affected by external factors. (3) Results from common frontiers and group frontiers exist some differences. The LHG under the common frontier is lower than the LHG under the group frontier. Finally, according to the above empirical results, this paper puts forward policy suggestions to improve LHG and environmental protection suggestions for laying hens. [ABSTRACT FROM AUTHOR]

The contradiction between the exploitation of coal resources and the protection of the ecological environment in western China is becoming increasingly prominent. Reasonable ecological environment evaluation is the premise for alleviating this contradiction. First, this paper evaluates the eco-environment of Ibei coalfield by combining the genetic projection pursuit model and geographic information system (GIS) and using remote sensing image data and other statistical data of this area. The powerful spatial analysis function of GIS and the advantages of the genetic projection pursuit model in weight calculation have been fully used to improve the reliability of the evaluation results. Furthermore, spatial autocorrelation is used to analyze the spatial characteristics of ecological environment quality in the mining area and plan the specific governance scope. The geographic detector is used to determine the driving factors of the eco-environment of the mining area. The results show that Ibei Coalfield presents a spatially heterogeneous eco-environment pattern. The high-intensity mining area (previously mined area of Ili No.4 Coal Mine) has the worst ecological environment quality, followed by the coal reserve area of Ili No.4 Coal Mine and the planned survey area of Ili No.5 Coal Mine. The eco-environment quality (EEQ) of the study area is affected by both human and natural factors. Mining intensity and surface subsidence are the main human factors affecting the ecological environment in the study area. The main natural factors affecting the ecological environment in the study area are annual average precipitation, elevation, annual average evaporation, NDVI and land use type. Meanwhile, the interaction effect of any two indicators is greater than that of a single indicator. It is also indicated that the eco-environment of the mining area is nonlinearly correlated to impact indicators. The spatial autocorrelation analysis shows three areas that should be treated strategically that are the management area, close attention area and protective area. Corresponding management measures are put forward for different regions. This paper can provide scientific references for mining area eco-environmental protection, which is significant for the sustainability of coal mine projects. [ABSTRACT FROM AUTHOR]

Digital transformation and green innovation are powerful initiatives to achieve carbon peaking, carbon neutrality targets and high-quality economic development. Using a sample of high energy-consuming listed enterprises from 2012 to 2021, a double fixed-effect model is constructed to verify the effect of green innovation on the carbon emission reduction performance of high energy-consuming enterprises, and digital transformation is used as a moderating variable to analyze the inner mechanism of green innovation affecting the carbon emission reduction performance of high energy-consuming enterprises under the effect of digital transformation. The empirical results show that green innovation can significantly improve the carbon emission reduction performance of energy-consuming enterprises, while digital transformation positively moderates the effect of green innovation on the carbon emission reduction performance of energy-consuming enterprises. When considering the industry heterogeneity, the moderation effect of digital transformation is significant in the chemical raw materials and chemical products manufacturing industry and the electricity and heat production and supply industry, but the petroleum processing and coking and nuclear fuel processing industry, the non-metallic mineral products industry, the ferrous metal smelting and rolling processing industry and the non-ferrous metal smelting and rolling processing industry are not yet significantly affected by green innovation and digital transformation. The findings of the study provide empirical evidence to promote the improvement of carbon emission reduction performance of energy-intensive enterprises in China and to achieve the "double carbon" target. [ABSTRACT FROM AUTHOR]

In recent years, the survival and development of traditional villages in China have been serious challenges. Rural tourism is regarded as an important way to solve rural problems, and the combination of rural culture and tourism has become a new power point for rural development. Therefore, it is necessary to explore the spatial distribution structure between traditional villages and rural tourism. In this paper, rural tourism was represented by the rural tourism characteristic village (RTCV), and Henan Province, China, was taken as a study area to analyze the distribution pattern and spatial correlation of rural tourism and traditional village (TV) and discuss the relationship between the spatial correlation and regional natural environment and socioeconomic factors. The results show that the coupling of the spatial correlation between RTCVs and TVs in Henan was clear. They could be divided into 5 regions based on geographical factors. In addition, the research summarized 4 typical spatial structures between TVs and RTCVs in Henan based on the regional symbiosis theory, and the spatial pattern formation mechanism of TVs and RTCVs was discussed based on three driving mechanisms. The spatial structure of the two can provide reference value for other developing countries and regions to achieve sustainable rural development. [ABSTRACT FROM AUTHOR]

Recently, well-being of older people measure (WOOP) was developed and validated in a Dutch population. Although WOOP was developed targeting the older people, it has the potential for use in a wider population. In this study, we aimed to examine the relationship between WOOP and EQ-5D-5L and compared their psychometric properties in a sample of patients, carers and healthy general public covering a wider age group. We conducted a cross-sectional study in Guizhou Province, China between July and August 2022. Data was collected using paper and pencil. We analysed and reported the acceptability, item response distribution, the Spearman correlation coefficients of all items, the Exploratory Factor Analysis (EFA) of all items, the known-group validity and the convergent validity of EQ-5D-5L utility and WOOP utility. A total of 322 participants completed the survey with 105 patients, 101 carers and 116 healthy general public. 9% of participants had at least one missing response. Three items of WOOP did not have any level 5 responses and EQ-5D-5L had more level 1 responses. The correlations were low between EQ-5D-5L and WOOP items and the three-factor EFA showed these two instruments had only one shared factor and the other two factors were only related to WOOP items. Younger people had lower missing response rate and a different response distribution for three items. WOOP measures a broader construct beyond health while EQ-5D-5L is a more sensitive instrument when health is considered alone. There is a potential of using WOOP in a wider population. [ABSTRACT FROM AUTHOR]

In the study of protected areas, the "Fences & fines" approach is increasingly becoming acknowledged as obsolete and ineffectual, and there is mounting evidence suggesting that the "Community-based conservation" approach is acquiring consideration. It is significant to identify which protection model or factors perform a definitive part in China. Taking the East Dongting Lake National Nature Reserve in China as a survey site, this paper utilizes semi-structured interviews and random questionnaires surveyed 431 households to investigate the relationship between "community-based conservation" approaches such aslegal system, ecological compensation, environmental education, community participation, concessions, livelihoods, job provision, intrinsic motivation and pro-environmental behavior. The regression results declare that intrinsic motivation (β = 0.390) and legal system (β = 0.212) are the most effective factors impacting on pro-environmental behavior; concessions has a negative conflict on preservation;but other "community-based conservation" approaches had insignificant positive impacts on pro-environmental behavior. Further mediating effects analysis indicated that intrinsic motivation (B = 0.3899, t = 11.9694, p < 0.01) mediates between legal system and pro-environmental behavior of community residents, legal system promotes pro-environmental behavior by promoting intrinsic motivation, which is more effective than legal system promoting pro-environmental behavior directly. This demonstrates that "Fence and fine approach" still is an effective management tool which can shape community residents' positive attitude towards conservation and pro-environmental behavior especially protected areas with large communities. And appropriate "community-based conservation" approaches can mitigate conflicts between special groups with the combination of these two approaches, the management of protected areas can be successful. This supplies a valuable real-world case for the current debate on conservation and improved human livelihoods. [ABSTRACT FROM AUTHOR]

COVID-19 is a continuing threat to global public health security. For elderly people, timely and effective vaccination reduces infection rates in this group and safeguards their health. This paper adopted an offline Discrete Choice Experiment (DCE) to research the preference for COVID-19 vaccination amongst Chinese adults aged 50 years and above. Through multinomial logistic regression analysis, our DCE leverages five attributes—the risk of adverse reactions, protective duration, injection doses, injection period, and effectiveness—each of which is split into three to four levels. The risk of adverse reaction and the protective duration were demonstrated to be determinants of vaccination preference. Moreover, it was found that socio demographic factors like region, self-health assessment and the number of vaccinated household members can strengthen or weaken the effects of vaccine attributes. In conclusion, the preferences of the elderly population should be considered when developing COVID-19 vaccination programs for this population in China. Accordingly, the results may provide useful information for policymakers to develop tailored, effectively vaccination strategies. [ABSTRACT FROM AUTHOR]

Aiming at the traditional ecological footprint model, the improved ecological footprint of the carbon footprint effectively makes up for the singularity of the ecological footprint's consideration of carbon emissions, and plays an important role in promoting high-quality development and ecological sustainability. This paper selects 2015, 2018 and 2020 as important time points for the study, corrects the ecological footprint parameter factors based on net primary productivity (NPP), measures the ecological footprint after the improvement of the carbon footprint, studies the spatial and temporal variation in the ecological footprint at the 100-m grid scale with the support of IPCC greenhouse gas inventory analysis, and analyzes the current ecological conservation status of the Yellow River Delta. Additionally, in the context of a low carbon economy, the decoupling index of carbon emissions and GDP is extended to the evaluation and analysis of high-quality development. The study showed that (1) the ecological footprint of the Yellow River Delta has increased year by year, from 0.721 hm2·person− 1 to 0.758 hm2·person− 1, an average annual increase of 2.9%; the ecological carrying capacity has decreased from 0.40 hm2·person− 1 to 0.31 hm2·person− 1, an overall decrease of 28.59%. (2) The overall ecological deficit of the Yellow River Delta grid is lightly overloaded, with most of the ecological surplus occurring in the northern and eastern parts of the study area and a few moderate and heavy overloads in the center of the core area where there is a lot of built-up land and the area is small and easy to gather. (3) Based on the low-carbon economy analysis, 2015, 2017 and 2020 reach absolute decoupling and are in the ideal scenario. However, in the rest of the years, carbon emissions and economic development are still in a large contradiction, and decoupling has fluctuated and varied greatly in the last six years. The effective combination of ecological footprint and low carbon economy analysis provides an important theoretical basis for improving ecological conservation and achieving high-quality development. [ABSTRACT FROM AUTHOR]

On August 20, 2019, at 2 a.m., a disastrous debris flow occurred in Chediguan gully in Yinxing town, China. The debris flow destroyed the drainage groove and the bridge at the exit of the gully. In addition, the debris flow temporarily blocked the Minjiang River during the flood peak, flooding the Taipingyi hydropower station 200 m upstream and leaving two plant workers missing. To further understand the activity of the debris flow after the Wenchuan earthquake, the characteristics of this debris flow event were studied. Eleven years after the Wenchuan earthquake, a disastrous debris flow still occurred in the Chediguan catchment, causing more severe losses than those of earlier debris flows. In this paper, the formation mechanism and dynamic characteristics of this debris flow event are analysed based on a drone survey, high-definition remote sensing interpretations and other means. The catastrophic debris flow event indicates that debris flows in the Wenchuan earthquake area are still active. A large amount of dredging work in the main gully could effectively reduce the debris flow risk in the gully. In addition, it is also important to repair or rebuild damaged mitigation measures and to establish a real-time monitoring and early warning system for the high-risk gully. [ABSTRACT FROM AUTHOR]

"Alteration" geologically refers to chemical composition and/or structural changes of minerals under the influences of hydrothermal fluids, surface water, seawater, or other environmental conditions. In this paper, we use the word "alteration" to refer to chemical component and structural changes in jade artifacts caused by human activity and natural weathering, which is different from the term in geology. "Mercury alteration", a kind of black alteration related to Hg, is unique among the several types of alteration that occur in Chinese ancient jades. Mercury alteration often appears on ancient jade artifacts unearthed from high-grade tombs of the pre-Qin period (before 221 B.C.). Therefore, ancient jades with mercury alteration have attracted substantial attention from Chinese archaeologists. This paper reports the use of materials analytic techniques to study such ancient jade fragments. The studied jade samples date to the middle and late periods of the Spring and Autumn Period (~500 B.C.) and were unearthed from Lizhou'ao Tomb in Jiangxi Province, China. Structural analyses revealed the internal microstructure of the ancient jade fragments and the microdistribution of the mercury alteration. The jade fragments exhibit typical characteristics of round holes and structural hierarchy, which imply that the jades were heated before burial. The black alteration on these jade samples was found to be rich in Hg. The results of this study will be widely useful in the study of ancient jade artifacts and jade culture in Chinese archeology. [ABSTRACT FROM AUTHOR]

This paper examines how spatial distance affects network topology on empirical data concerning the Global Container Shipping Network (GCSN). The GCSN decomposes into 32 multiplex layers, defined at several spatial levels, by successively removing connections of smaller distances. This multilayer decomposition approach allows studying the topological properties of each layer as a function of distance. The analysis provides insights into the hierarchical structure and (importing and exporting) trade functionality of the GCSN, hub connectivity, several topological aspects, and the distinct role of China in the network's structure. It also shows that bidirectional links decrease with distance, highlighting the importance of asymmetric functionality in carriers' operations. It further configures six novel clusters of ports concerning their spatial coverage. Finally, it reveals three levels of geographical scale in the structure of GCSN (where the network topology significantly changes): the neighborhood (local connectivity); the scale of international connectivity (mesoscale or middle connectivity); and the intercontinental market (large scale connectivity). The overall approach provides a methodological framework for analyzing network topology as a function of distance, highlights the spatial dimension in complex and multilayer networks, and provides insights into the spatial structure of the GCSN, which is the most important market of the global maritime economy. [ABSTRACT FROM AUTHOR]

Based on the digital elevation data, snow depth and snow cover remote sensing data, this paper divides six snow evolution areas and geographical partitions, extracts the geographical partitions of each evolution area and obtains the geographical characteristics of the evolution area for analysis. The results show that: (1) From 2003 to 2017, the average snow area decreased at a rate of − 0.004, and the average snow depth increased at a rate of 0.03. (2) The snow in the middle altitude hill with shady gentle slope area is the most obvious in the seasonal evolution, and the percentage of this region in the seasonal snow evolution area is 5.46%, the snow depth in the middle altitude hill with sunny and gentle slopes area increased and decreased significantly in the past 15 years, and the percentage of this region in the SD significant changes evolution area was 6.32%. The snow in the low relief middle altitude mountain with shady and moderate slope area not only shows obvious seasonal evolution, but also increases and decreases significantly in snow depth. And the percentage of this region in the seasonal snow significant evolution area is 5.82%. (3) The geographical partitions with the largest area in all evolution areas is the middle altitude hill with sunny and gentle slopes area (4.75%). (4) The geographical partition with the largest variation of snow depth in Tianshan region is the low relief middle altitude mountain with shady and moderate slope area (12.02 cm). (5) The snow accumulation and melting are obvious in the range of 1000–3500 m above altitude, different geomorphology types lead to obvious differences in snow characteristics. The snow melting is most obvious in the gentle slope area of the low topographic relief geomorphology types, and the snow accumulation is most obvious in the steep slope area of the middle relief geomorphology types. [ABSTRACT FROM AUTHOR]

Since the western region of China, which is typical of extraordinary resource endowments, has gradually emerged as the major mining zone in China, the mining of thick coal seams and roadways with coal-rock composite roof have become more and more common in this region. However, it is extremely difficult to realize safe and effective maintenance and control of such roadways due to the differences in natural endowments of coal-rock masses. With the roadway with coal-rock composite roof of Hulusu Coal Mine in western China as the engineering background, experiment research on large-scale similarity model was conducted through comprehensive measures such as the pneumatic loading system, the surrounding rock stress monitoring system, the roadway deformation monitoring system, the bolt load monitoring system, and the displacement field monitoring system in this paper. According to the results of the experiment, the control effects of the three support systems on the roadway with coal-rock composite roof were significantly different. When the single support of short anchor bolts was applied, the comparatively low initial anchor-hold failed to constrain the initial micro deformation of the roof. Consequently, wide-range fractures of the roof were triggered at a loading pressure of 0.8 MPa. In the meanwhile, the deep surrounding rocks witnessed a downward inflection point in stress, accompanied by the possibility of the collapse of the thin-layer anchorage zone at any time. As for the support combining both short anchor bolts and long anchor cables, though a reinforced effect on the bolt anchorage zone could be achieved with the help of the cables, the active reinforcement capacity of the bolt was limited. The bolt anchorage zone was the first to be damaged at a loading pressure of 0.9 MPa, which would subsequently affect the effective bearing capacity of the deep surrounding rocks. In the application of the single support of high-strength long anchor bolts, the long bolts with high pre-tightening force were able to lock multiple groups of coal-rock strata to form a thick-layer anchorage bearing structure capable of withstanding a load as high as 1.0 MPa. The crash and collapse of the coal wall eventually caused the subsidence of the roof. Based on the intense dynamic load experiment and the feedbacks of engineering application outcomes in the field, it was concluded that the high-pretension thick-layer (HPTL) anchoring technology can effectively constrain the deformation of roadways with coal-rock composite roof with favorable application outcomes. [ABSTRACT FROM AUTHOR]

As the main means to dovetail the domestic system with international rules, institutional openness is the key to deepening participation in the global economic governance system, breaking through energy and carbon emission constraints, and achieving green and sustainable economic development. Taking 284 prefecture-level cities in China from 2006 to 2019 as the research sample, this paper uses the establishment of Pilot Free Trade Zones as a quasi-natural experiment to systematically identify and test the actual impact of institutional openness on urban carbon emissions in China through the asymptotic difference in difference method, instrumental variables method, spatial econometric model, and mediating effects model. Meanwhile, technological progress is used as the entry point to analyze the intrinsic mechanism of action by adopting digital transformation oriented to efficiency improvement and green innovation capability oriented to R&D innovation as the differentiated perspective. It is found that institutional openness significantly suppresses urban CO2 emissions, and there is a certain heterogeneity and spatial spillover effect of this effect. Further study finds that institutional openness achieves carbon emission reduction through technological progress. The study aims to find new institutional innovation and development paths for low carbon development. [ABSTRACT FROM AUTHOR]

Stroke is the leading cause of death in China (Zhou et al. in The Lancet, 2019). A dataset from Shanxi Province is analyzed to predict the risk of patients at four states (low/medium/high/attack) and to estimate transition probabilities between various states via a SHAP DeepExplainer. To handle the issues related to an imbalanced sample set, the quadratic interactive deep model (QIDeep) was first proposed by flexible selection and appending of quadratic interactive features. The experimental results showed that the QIDeep model with 3 interactive features achieved the state-of-the-art accuracy 83.33%(95% CI (83.14%; 83.52%)). Blood pressure, physical inactivity, smoking, weight, and total cholesterol are the top five most important features. For the sake of high recall in the attack state, stroke occurrence prediction is considered an auxiliary objective in multi-objective learning. The prediction accuracy was improved, while the recall of the attack state was increased by 17.79% (to 82.06%) compared to QIDeep (from 71.49%) with the same features. The prediction model and analysis tool in this paper provided not only a prediction method but also an attribution explanation of the risk states and transition direction of each patient, a valuable tool for doctors to analyze and diagnose the disease. [ABSTRACT FROM AUTHOR]

The correlation characteristics between anomalous changes in summer precipitation on the Qinghai–Tibet Plateau (QTP) and the high-impact areas of global sea-surface temperature (SST) are mainly studied in this paper. The results show that the interdecadal change of the regional "warming-wetting" in China is especially prominent in the northern part of the main body of the QTP, which is therefore identified as the high-value area of precipitation variability. Investigations have revealed that the high-value areas of summer precipitation variability in the northern QTP are significantly correlated with four high-value areas of SST variability, namely the western North Pacific, the western Central Pacific, the Southwest Pacific, and the central Indian Ocean. In these four high-impact areas, a synchronous tendency is found in the SST increase and sea-surface specific humidity. Through the tracking analysis of the correlated vectors of the water vapor source for the warming-wetting of the QTP, it further confirms that the four high-value areas of SST variability in the Indo-Pacific Ocean are the major impact sources of water vapor transport for the warming-wetting of the QTP. Moreover, the comparison of the characteristics of various interdecadal global water vapor transport circulations show that from 1991 to 2020, the trans-equatorial water vapor transport from the Southern Hemisphere witnessed a notable increase, which furthermore suggests that the interdecadal change of SST increase in the Southwest Pacific and central Indian Ocean is the key reason for the warming-wetting of the QTP. In addition, a comprehensive image of high-impact marine water vapor sources for modulating the warming-wetting tendency in the QTP is proposed. [ABSTRACT FROM AUTHOR]

The emergence of SARS-CoV-2 in China in December 2019 has posed a major challenge to health systems in all countries around the world. One of the most relevant epidemiological measures to consider during the course of a pandemic is the proportion of cases that eventually die from the disease (case fatality ratio, CFR). Monitoring the evolution of this indicator is of paramount importance because it allows for the assessment of both variations in the lethality of the virus and the effectiveness of the control measures implemented by health authorities. One of the problems with estimating the CFR in practice is that the available data only show daily or weekly counts of new cases and deaths; there is no information on when each deceased patient was infected and therefore it is not possible to know exactly how many cases there were at the time the patient became infected. Various approaches have been proposed for calculating the CFR by correcting for the time lag between infection and death. In this paper, we present a novel methodology to perform a non-parametric estimation of the evolution of the CFR by initially identifying an optimal time lag between infections and deaths. The goodness of this procedure is assessed by means of a simulation study and the method is applied to the estimation of the CFR in Spain in the period from July 2020 to March 2022. [ABSTRACT FROM AUTHOR]

Perceived government corruption is an important indicator of depressive symptoms. Recent studies have explored the relationship between perceived government corruption and depressive symptoms in a cross-cultural context, but the underlying mechanisms need further research. This paper examines the impact of perceived government corruption on depressive symptoms in China and the moderating role of social status. Based on the 2018 wave of China Family Panel Studies (CFPS2018), 14,116 respondents aged between 16 and 96 were selected. The results revealed: (1) Perceived government corruption was significantly positively correlated with depressive symptoms. (2) Social class had an inhibitory effect in moderating the relationship between perceived government corruption and depressive symptoms. (3) The moderating effect was only significant for respondents who received education between junior high school and a bachelor's degree. The findings provide policy implications for developing countries and transitional societies like China. To build a more psychologically healthy society, we need to strengthen anti-corruption, stimulate social mobility, and improve people's sense of gain in the future [ABSTRACT FROM AUTHOR]

The novel coronavirus pneumonia (COVID-19) outbreak that emerged in late 2019 has posed a severe threat to human health and social and economic development, and thus has become a major public health crisis affecting the world. The spread of COVID-19 in population and regions is a typical geographical process, which is worth discussing from the geographical perspective. This paper focuses on Shandong province, which has a high incidence, though the first Chinese confirmed case was reported from Hubei province. Based on the data of reported confirmed cases and the detailed information of cases collected manually, we used text analysis, mathematical statistics and spatial analysis to reveal the demographic characteristics of confirmed cases and the spatio-temporal evolution process of the epidemic, and to explore the comprehensive mechanism of epidemic evolution and prevention and control. The results show that: (1) the incidence rate of COVID-19 in Shandong is 0.76/100,000. The majority of confirmed cases are old and middle-aged people who are infected by the intra-province diffusion, followed by young and middle-aged people who are infected outside the province. (2) Up to February 5, the number of daily confirmed cases shows a trend of "rapid increase before slowing down", among which, the changes of age and gender are closely related to population migration, epidemic characteristics and intervention measures. (3) Affected by the regional economy and population, the spatial distribution of the confirmed cases is obviously unbalanced, with the cluster pattern of "high–low" and "low–high". (4) The evolution of the migration pattern, affected by the geographical location of Wuhan and Chinese traditional culture, is dominated by "cross-provincial" and "intra-provincial" direct flow, and generally shows the trend of "southwest → northeast". Finally, combined with the targeted countermeasures of "source-flow-sink", the comprehensive mechanism of COVID-19 epidemic evolution and prevention and control in Shandong is revealed. External and internal prevention and control measures are also figured out. [ABSTRACT FROM AUTHOR]

Using ArcGIS to analyze satellite derived PM2.5 estimates, this paper obtains the average concentration and maximum concentration of fine particulate matter (PM2.5) in China's 31 provinces from 2002 to 2015. We adopt fixed effects model and spatial Durbin model to investigate the association between PM2.5 and perinatal mortality rates. The results indicate that PM2.5 has a significantly positive association with perinatal mortality rates. A 1% increase of log-transformed average concentration and maximum concentrations of PM2.5 is associated with 1.76‰ and 2.31‰ increase of perinatal mortality rates, respectively. In spatial econometrics analysis, we find PM2.5 has significant spatial autocorrelation characteristics. The concentrations of log-transformed average and maximum PM2.5 increase 1% is associated with a 2.49% increase in a 2.49‰ and 2.19‰ increase of perinatal mortality rates, respectively. The potential mechanism is that air pollution has an impact on infant weight to impact perinatal mortality rates. [ABSTRACT FROM AUTHOR]

The Yellow River basin spans nine provinces and autonomous regions and plays an important role in China's economic and social development and ecological security. However few studies have integrated the concept of carbon neutrality into research to evaluate the carbon-neutral development level. This paper calculates the comprehensive evaluation value of the provincial carbon-neutral capacities comprehensive evaluation index in the Yellow River basin through the driving-force-pressure-state-impact-response (DFPSIR) index system and the global entropy method based on provinces data between 2008 to 2019. The final results indicated that from 2008 to 2019, the carbon-neutral capacities of the provinces in the Yellow River basin were in a state of rapid development and had achieved a grade leap. However, seven provinces had carbon-neutral capacity levels at the Grade III standard in 2019, thereby leaving scope for substantial improvement. Through the above research, we identified the changes in the trend and driving mechanisms of the carbon-neutral capacity of the Yellow River basin and provide a theoretical reference value for a comprehensive realization of carbon neutrality in China in 2060. [ABSTRACT FROM AUTHOR]

Chinese fir (Cunninghamia lanceolata) is one of southern China's most important native tree species, which has experienced noticeable climate-induced changes. Published papers (1978–2020) on tree growth of Chinese fir forests in China were collected and critically reviewed. After that, a comprehensive growth data set was developed from 482 sites, which are distributed between 102.19° and 130.07°E in longitude, between 21.87° and 37.24°N in latitude and between 5 and 2260 m in altitude. The dataset consists of 2265 entries, including mean DBH (cm), mean H (m), volume (m3), biomass (dry weight) (kg) (stem (over bark) biomass, branches biomass, leaves biomass, bark biomass, aboveground biomass, roots biomass, total trees biomass) and related information, i.e. geographical location (Country, province, study site, longitude, latitude, altitude, slope, and aspect), climate (mean annual precipitation-MAP and mean annual temperature-MAT), stand description (origin, age, canopy density and stand density), and sample regime (plot size, number and investigation year). Our results showed that (1) the best prediction of height was obtained using nonlinear composite model Height = 1.3 + 34.23 ∗ (1 - e - 0.01025 ∗ DBH 1.347 ) , (R2 = 0.8715, p < 0.05), (2) the equation Volume = DBH2/(387.8 + 19,190/Height) (R2 = 0.9833, p < 0.05) was observed to be the most suitable model for volume estimation. Meanwhile, when the measurements of the variables are difficult to carry out, the volume model Volume = 0.03957 − 0.01215*DBH + 0.00118*DBH2 (R2 = 0.9573, p < 0.05) is determined from DBH only has a practical advantage, (3) the regression equations of component biomass against DBH explained more significant than 86% variability in almost all biomass data of woody tissues, which were ranked as total trees (97.25%) > aboveground (96.55%) > stems (with bark) (96.17%) > barks (88.95%) > roots (86.71%), and explained greater than 64% variability in branch biomass. The foliage biomass equation was the poorest among biomass components (R2 = 0.6122). The estimation equations derived in this study are particularly suitable for the Chinese fir forests in China. This dataset can provide a theoretical basis for predicting and assessing the potential of carbon sequestration and afforestation activities of Chinese fir forests on a national scale. [ABSTRACT FROM AUTHOR]

The observation of electromechanical coupling might be used as an important tool to detect pre-seismic changes associated with the preparation of earthquakes. This paper attempts to study the electromechanical coupling process before the large earthquakes by using the load/unload response ratio (LURR) approach in which the geo-electric data and Benioff strain of small earthquakes were adopted as the data input. The variation of Coulomb failure stress induced by earth tides on the fault surface of the mainshock is applied to differentiate the loading and unloading stages. Using this technique, we test the geo-electric data recorded at the Hotan observatory near the epicenter of 2020 Yutian Ms 6.4 earthquake. Results show that the LURR time sequence fluctuated around 1.0 for many years and reached significant high peaks at the beginning of 2020. More importantly, this evolution correlates well with the LURR time series calculated by using the Benioff strain of small earthquakes within the circular region of 300 km radius centered at the epicenter. The underlying physics of the changes should be caused by the fluid infiltration derived from pre-seismic rock dilatancy. The corresponding volume variations in the crust could be found in the geophysical observation time series in the same neighborhoods. [ABSTRACT FROM AUTHOR]

To quantitatively evaluate the impact of domestic aviation control measures on the spread of COVID-19 in China. The number of international flights from March to September 2019 simulated the number of flights from March to September 2020 without implementing aviation control measures. In addition, the proportion of asymptomatic persons and the delay in case reporting were adjusted to estimate the prevalence of each country during the same period and calculate the estimated imported cases. The estimated imported cases were assigned each day with weight, and the estimated daily reported cases were obtained based on the actual daily number of domestic cases in China. Effective Reproduction Number ( R t ) was calculated based on delayed distribution, Basic Reproductive Number ( R 0 ) distribution, and generation time distribution were reported in previous studies. Gaussian Process was used to estimate the effect of time-varying on R t , and the estimated R t was compared with the actual R t . The estimated imported cases increased significantly compared with the actual number of imported cases. The estimated imported cases were mainly concentrated in North America and Europe from March to April and gradually increased in many East Asian countries from May to September. The difference between predicted R t and actual R t was statistically significant. The estimated imported cases and the estimated R t have increased compared to the actual situation. This paper quantitatively proves that Chinese aviation control measures significantly suppress the COVID-19 epidemic, which is conducive to promoting and applying this measure. [ABSTRACT FROM AUTHOR]

The continuing decline in the birth rate has led to a series of problems, such as the disproportion of population structure and severe aging population, which have restricted the country's economic development. To have a deeper understanding of the geographical differences and influencing factors of the birth rate, this paper collects and organizes the birth population data of 31 provinces in mainland China from 2011 to 2019. The national region is divided into seven natural geographical regions to obtain the spatial hierarchy, and a hierarchical Bayesian Spatio-temporal model is established. The INLA algorithm estimates the model parameters. The results show significant spatial and temporal differences in birth rates in mainland China, which are reflected mainly in the combination of spatial, temporal, and Spatio-temporal interaction effects. In the spatial dimension, the northeast is low, the northwest and southwest are high, and the birth rate has an upward trend from east to west. These trends are caused by unbalanced economic development, different fertility attitudes and differences in fertility security, reflecting regional differences in spatial effects. From 2011 to 2019, China's birth rate showed an overall downward trend in the time dimension. However, all regions except the northeast saw a significant but temporary increase in birth rates in 2016 and 2017, reflecting the temporal effect difference in birth rates. [ABSTRACT FROM AUTHOR]

In recent years, with the advance of Artificial Intelligence, automatic music composition has been demonstrated. However, there are many music genres and music instruments. For a same piece of music, different music instruments would produce different effects. Invented some 2500 years ago, Guzheng is one of the oldest music instruments in China and the world. It has distinct timbres and patterns that cannot be duplicated by other music instruments. Therefore, it is interesting to see whether AI can compose Guzheng music or alike. In this paper we present a method that can automatically compose and play Guzheng music. First, we collect a number of existing Guzheng music pieces and convert them into Music Instrument Digital Interface format. Second, we use these data to train a Long Short-Term Memory (LSTM) network and use the trained network to generate new Guzheng music pieces. Next, we use the Reinforcement Learning to optimize the LSTM network by adding special Guzheng playing techniques. Comparing to the existing AI methods, such as LSTM and Generative Adversary Network, our new method is more effective in capturing the characteristics of Guzheng music. According to the evaluations from skilled Guzheng players and general audiences, our Guzheng music is very close to the real Guzheng music. The presented method can also be used to automatically compose the music of other Chinese music instruments. [ABSTRACT FROM AUTHOR]

The uncertainty of LNG import risks will have a significant impact on China's energy security. This paper establishes a multi-agent game model based on the current LNG transportation network and global LNG supply and demand pattern, evaluates the LNG import risks faced by China under the global governance model, and simulates and predicts the optimal LNG import strategy of China in 2030. The research results show that between 2007 and 2020, China's LNG import risks increased rapidly compared with political risks and national risks. From the perspective of risk identification, the comprehensive risk of China's imports from Southeast Asia and Australia is lower. However, due to the increasing demand gap for LNG, the Middle East, and Africa are still necessary supply sources. It is estimated that by 2030, the future LNG market will be oversupplied, and the United States is expected to become the world's top LNG supplier. China will reduce its dependence on Africa and the Middle East, and import a large amount of natural gas from the United States, Australia, Qatar, and Russia to reduce supply risks. From the perspective of import market competition, the new analysis model proposed in this article provides an effective tool for exploring the optimal strategy for LNG import. [ABSTRACT FROM AUTHOR]

This paper estimates the causal effect of only-child status on educational performance among junior high school students from only-child and two-child families in China. It uses the dataset of the China Education Panel Survey 2013–14. The results show that the only children's educational outcomes are significantly low than students from two-child families. Only children's willpower and extraversion are weaker than children's from two-child families. The scale economies effect is strong and the resource dilution effect is weak when sibling size is small. [ABSTRACT FROM AUTHOR]

The reservoir water level fluctuation zone (WLFZ) is a new and fragile ecosystem that is gaining attention with the construction of large and medium-sized hydropower plants. Compared to the natural riparian zone, it has a greater drop in water level, longer inundation time, more intense impact from alternating wet and dry conditions, and a wider impact on ecological security. The Jinsha River basin is located in the upper reaches of the Yangtze River in China, and several world-class large-scale hydropower projects with dam heights over 100 m have been built, forming a large area of reservoir WLFZ, however, due to the short time since their construction, there are few related studies. In this paper, fixed sample plots were set up in the typical WLFZs of each large reservoir in the Jinsha River basin. In response to the problem of the precipitous terrain and poor accessibility of the Jinsha River basin, a combination of small UAV surveys and field research in July 2020 was used to draw vegetation cover maps and extract topographic data for each site, and quantitatively analyse the community composition, dominant species types, area, coverage, spatial distribution patterns and environmental factors of tolerant vegetation using spatial superposition analysis, neural network models, landscape pattern indices and typical correlation analysis. The results showed that the original drought-tolerant vegetation in the arid river valley WLFZ has evolved into amphibious herbaceous vegetation, with trees and shrubs disappearing and species composition tending to be simpler. 44 species of plants, mainly in the Asteraceae and Gramineae families, were extant, 61% of which were also reported in the Three Gorges Reservoir WLFZ. The water level variation showed convergence in the natural screening process of suitable species in the WLFZ. Moreover, even in the dry valley WLFZs, flood stress showed a more significant filtering effect on vegetation species than drought stress. The vegetation in the WLFZ showed an obvious band-like aggregated distribution along the water level elevation gradient, and the vegetation coverage along the flooding gradient is as follows: upper part of the WLFZ >> middle part > lower part, and mainly concentrated in the gentle area with slope less than 35°. Flooding stress, drought stress and soil substrate deficiency were the main limiting factors for vegetation recovery in the WLFZ. The vegetation restoration of the WLFZ should be adapted to local conditions, and the dominant role of native species should be emphasized. At the early stage of the restoration of the WLFZ, native species should be selected for artificial planting to accelerate the formation of vegetation cover, and gradually advance downwards along the gradient of water level elevation, while for areas of the WLFZ with slopes greater than 35° and large topographic relief, biological engineering measures should be used to help plant establishment, and after a certain stable cover has been formed, natural restoration should be the main focus. [ABSTRACT FROM AUTHOR]

China's food security has always been a high priority issue on the political agenda with rapid urbanization affecting agricultural land, and it is challenged by several factors, such as human activities, social politics and policy. Shandong is an important grain-producing province and the second most populous province in China. In this paper, the spatiotemporal characteristics of grain yield and their potential influencing factors were explored at the county level in Shandong by using panel data over a 19-year period. The location Gini coefficient (L-Gini) and exploratory spatial data analysis (ESDA) were used to study the spatial agglomeration characteristics of grain yield, and spatial regression methods (SRMs) were used to analyse the influencing factors. The results indicated that grain yield increased from 38.3 million metric tons to 53.2 million metric tons in 2000–2018, with a growth rate of approximately 28.0%. The increase in grain yield in Shandong was due to the driving effect of radiation from high-yield counties to surrounding moderate-yield counties. This revealed an upward trend of spatial polarization in Shandong's grain yield. In 2000–2018, the L-Gini and global Moran's I increased from 0.330 to 0.479 and from 0.369 to 0.528, respectively. The number of counties in high-high (HH) and low-low (LL) agglomeration areas increased, and the spatial polarization effect was significant. SRMs analysis showed that irrigation investment and non-grain attention have significant positive and negative effects on grain production, respectively. The spatial relationship between grain yield and its influencing factors was explored to provide a reference for formulating scientific and rational agricultural policies. [ABSTRACT FROM AUTHOR]

The development of barbed-spring locks in ancient China has a history of more than 2000 years. With the development of the design and manufacturing techniques in ancient China, the safety of locks has gotten better and better. Since the seventeenth century, the puzzle lock, with a complicated structure and a high difficulty in opening, was gradually developed and used. The puzzle lock needs specific steps to be opened. Based on the difficulty of the opening process, traditional Chinese puzzle locks can be partition into two sorts, namely, general puzzle locks and complex puzzle locks. As the structure of the puzzle lock will change during the opening process, the puzzle lock belongs to the reconfigurable mechanism. In this paper, a method of topology matrix is provided to analyze the structure of the complex puzzle lock during systematical operation. Firstly, the characteristics and types of general puzzle locks are explained, and then the topology matrix representation is introduced. Finally, four complex puzzle locks are taken as examples, to illustrate the opening process. There are various types of complex puzzle locks, and the mechanism designs are quite ingenious and interesting, which shows the extraordinary technique and ingenuity of the ancient craftsmen. [ABSTRACT FROM AUTHOR]