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With the development of information technology, such as cloud computing and 5G technologies, the construction of smart cities has been an essential part of the city's long-term development strategy for the 14th five-year plans in China. After a few years of development, the research problem of the dynamic performance assessment of smart cities has been a hot and urgent issue. This paper constructed the dimensions of smart productivity, smart livability, smart governance, and eco-community based on the connotations of smart cities. Then, an indicator system including 35 indicators was built based on the four dimensions. To enlarge the overall differences of the final assessment values, we used the vertical and horizontal deviation maximization (VH-DM) method to measure the performances of 31 smart cities in China from the year 2014–2018. Two essential findings and driving indicators were identified from the assessment results. Firstly, the development among the smart cities was unbalanced and more than half of the smart cities (accounting for 64.52%) were below the average level. The local authorities considered the urban agglomeration strategies to alleviate the problem of unbalanced urban development. Secondly, some smart cities (such as Chongqing) with large scale of population and total resources showed a low level after the total resources were allocated to per capita, which provided a warning for the smart cities to pay more attention to individual development. The local authorities have proposed the high-quality development strategies to deal with such problems. [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]

The relationship between social factors and the formation of exported mug designs is blurred. This study addresses how they influence material design. Based on a quantitative typological analysis, this paper interprets the cultural relationships underlying the evolution of mug designs exported during the Ming and Qing dynasties. The study reveals: (1) the typology and handle styles of mugs can be categorized into six types, with a predominance of Cylindrical bodies and Ear-shaped handles. Notably, artistic emphasis is concentrated on Bulbous cup bodies and Tail outward curved handles; (2) the design of mugs in the eighteenth century exhibited diversity, morphological similarities, and feature continuity, evolving from representational (Ming Dynasty) to abstract and then to minimalistic styles (Qing Dynasty), particularly evident in the three-dimensional modeling of handles for ergonomic comfort (transitioning from a singular Outward curved form to Ear-shaped form, and then to Entwined branch form); (3) the body shape of mugs transformed from Arc-barrel bodies to Bulbous bodies (focusing on heat retention), and eventually to Cylindrical bodies (prioritizing heat retention, practicality, and cost-efficiency).; (4) the volume of mugs steadily increased from the early eighteenth century, generally classified into large volume (≥ 500 ml), medium volume (200-499 ml), and small volume (< 200 ml); (5) considering the extreme range of volume (11090 ml) and height (25 cm), it indicates that these two variables do not necessarily have a direct positive correlation; (6) the low center of gravity in handle design (average width of 3.4 cm against an average height of 9.9 cm for the body) reflects considerations for the distribution of liquid weight and operational convenience. The volume of sample-10 (11127 ml) notably exceeds the typical range for tea-drinking utensils, revealing the mechanism of wealth and status symbolism. Market demand orientation emerged as the primary driver for the evolution of export mug designs during the Ming and Qing Dynasties, with adjustments in the merchant system playing a secondary role. The transformation in mug design reflects the interplay of multiple factors, with the trend toward minimalist design being a response to market demands. [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]

With the continuous advancement of deep space exploration missions, the solar system boundary exploration mission is established as one of the China's most important deep space scientific exploration missions. The mission of the solar system boundary exploration has many challenges such as ultra-remote detection distance, ultra-long operation time, and ultra-long communication delay. Therefore, the problem of high-precision autonomous navigation needs to be solved urgently. This paper designs an autonomous intelligent navigation method based on X-ray pulsars in the cruise phase, which estimate the motion state of the probe in real time. The proposed navigation method employs the Q-learning Extended Kalman filter (QLEKF) to improve navigation accuracy during long periods of self-determining running. The QLEKF selects automatically the error covariance matrix parameter of the process noise and the measurement noise by the reward mechanism of reinforcement learning. Compared to the traditional EKF and AEKF, the QLEKF improves the estimation accuracy of position and velocity. Finally, the simulation result demonstrates the effectiveness and the superiority of the intelligent navigation algorithm based on QLEKF, which can satisfy the high-precision navigation requirements in the cruise phase of the solar system boundary exploration. [ABSTRACT FROM AUTHOR]

Organization's sustainability performance is influenced by its suppliers' sustainability performance. This relationship makes sustainable supplier development a strategic competitive option for a buyer or focal organization. When considering sustainable supplier development practices (SSDPs) adoption, organizations have to balance and consider their limited financial resources and operational constraints. It becomes necessary to both select the best SSDPs set and investment allocation among the selected SSDP set such that the organization can maximize overall sustainability performance level. In this paper, an integrated formal modeling methodology using DEMATEL, the NK model, and multi-objective linear programming model is used support this objective. The proposed methodology is evaluated in a practical sustainable supply chain field study of an equipment manufacturing company in China. Through case study, we found that the interdependency among SSDPs must be considered in SSDPs selection and investment allocation problem. Theoretical, managerial and methodology implications, conclusions, and directions for future research are also presented. [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]

Using basic data from China's 30 provincial regions from 2005 to 2015, the slacks-based measure of super-efficiency in data envelopment analysis (super-efficiency SBM-DEA) is used to measure industrial green economic efficiency (IGEE). Moreover, the temporal change and spatial equilibrium of IGEE are analyzed, and the panel quantile regression model (PQRM) is used to empirically analyze the impacts of the degree of agglomeration of pollution-intensive industries (PIIs) and other influencing factors on IGEE. The results reveal the following. (1) The kernel density distribution curve of China's IGEE exhibits a double-peaked distribution, and the overall peak value of the curve changes relatively greatly, exhibiting obvious spatial inequality. (2) Based on their trajectories, the centers of gravity of IGEE are all distributed in the central region. The moving speed of the centers of gravity exhibits a trend of "accelerating–decreasing–quickly accelerating." Judging from the changes of the standard deviation ellipse (SDE), the spatial distribution pattern of China's IGEE generally presents a northeast–southwest pattern, and it has exhibited the trend of shifting to a north–south pattern in recent years. (3) The agglomeration level of PIIs has a significant positive effect on the development of China's IGEE at each quantile level, and the most significant impact on China's IGEE is at the 75th quantile level. This paper empirically analyzes the impact of the agglomeration level of PIIs on IGEE to aid in the greening of industrial economic efficiency and the sustainable development of the ecological environment in China and other developing countries. [ABSTRACT FROM AUTHOR]

The quality development of tourism is an important means of implementing China's quality development strategy, meeting people's aspirations for a better life and enhancing China's tourism competitiveness. On the basis of defining the concept of high-quality tourism development, this paper constructs an evaluation system for high-quality tourism development that includes five dimensions: tourism economic scale, tourism development speed, tourism supply quality, tourism industry structure and tourism industry efficiency. Using the entropy value method, multi-indicator comprehensive index method and health distance model, we measure the level of high-quality tourism development and its mismatch in 30 Chinese provinces (municipalities and regions) from 2010 to 2019, and analyze the factors affecting high-quality tourism development in China. The findings show that: (1) the overall level of quality development in China's tourism industry is not high, with a low degree of mismatch dominating, and a trend from mismatch to match. The high-quality development of the national tourism industry is mainly due to the high quality of tourism supply and the comprehensive benefits of tourism. The role of tourism industry structure in promoting high-quality tourism development in China has not yet been fully exploited. (2) The four major regions of China have seen high-quality tourism development, with the eastern region generally outperforming the central, western and northeastern regions. The gap between the four regions has narrowed, but the performance is unstable. It is difficult to change the pattern of quality tourism development in the four regions in the short term. (3) The ranking of each province in terms of the level of quality tourism development remains relatively stable, but the average level varies considerably. Spatial differentiation within the four regions is evident, most notably in the east. (4) Policymakers should focus their policies on optimizing the structure of the tourism industry, implementing differentiated development strategies and enhancing the capacity for coordinated regional development, with a focus on the quality of tourism supply and the overall benefits of tourism in the western region. [ABSTRACT FROM AUTHOR]

Environmental regulation would often limit production, causing conflicts between environmental protection and industrial development. The fundamental reason is the weak compatibility between environmental regulation goals and pig production goals. In order to improve the compatibility, this paper analysed how the herd structure adjusts the impact of environmental regulation on pig production based on the rational theory on small farmer. With the use of inter-provincial panel data from 2008 to 2020 in China, a dual moderation effect model is constructed for the empirical analysis. The results show that: (1) Strengthening environmental regulation would inhibit pig production. (2) Herb structure not only affects pig production directly, but also the nonlinear impact of environmental regulation on pig production, which would be used as a specific guideline to improve the compatibility. (3) Moderate adjustment on herb structure would help to weaken the inhibitory effect of environmental regulation on pig production and realize the sustainable development of the pig industry. [ABSTRACT FROM AUTHOR]

In recent years, the vigorous development of the wind power industry has become an important measure in the transformation of energy structure in China. However, the overall low technical efficiency of wind farms has severely hindered wind power industrial development. It is of great practical significance to evaluate the technical efficiency (TE) of wind power in China and analyze its main factors. Most of the existing literature on the assessment of the TE of wind power in China focuses only on large listed companies and applies the traditional data envelopment analysis (DEA) while ignoring its potential shortcomings for TE estimation. Based on panel data, this paper used stochastic frontier analysis (SFA) to construct an analytical model for assessing the TE and influencing factors of Chinese wind farms and compared the results with those from DEA to verify the robustness. The empirical results showed that the TE of Chinese wind farms was generally low. The age of a wind farm and its power consumption have a negative impact on its technical efficiency, while the utilization of power generation equipment has a positive impact on its technical efficiency. Enhancing the technological innovation capabilities of wind power companies, speeding up the construction of supporting infrastructure and solving structural problems of wind power supply and demand are important measures for the wind power industry to improve the overall TE and promote industrial development in China. [ABSTRACT FROM AUTHOR]

Compared with the research results of water microplastics, soil microplastics have been of concern for a shorter time, and the research started later. As a whole, they are still in the initial stage of development, and the problems of arable land and food security caused by them have attracted close attention from scholars around the world, but have not been effectively solved. To reveal the research status, development and change process and future trend, this paper is based on the data in the Web of Science (WOS) databases from 2016 to November 2021, with the help of Citespace software. The number of articles published, source countries and degree of cooperation, research institutions and teams, keyword clustering and change trend are sorted out. The results showed that: (1) the research results of soil microplastics has experienced a slow-rapid growth stage. In terms of the number of articles published, China occupies the first place in the world, with 55 articles. In terms of the number of publications, Free Univ Berlin ranks first, followed by the Chinese Academy of Sciences, Berlin Brandenburg Inst Adv Biodivers Res, and Wageningen Univ&Res. (2) In terms of content, environmental pollution and exposure, the function and health of soil-associated media, the common shape characteristics of microplastics and their influencing factors, and the combined pollution caused by microplastics are all covered, and can be divided into eight main categories: soil, ingestion, heavy meals, fiber, marine environment, microplastic, metals, and plants. (3) The migration behavior and ecotoxicological effects of microplastics in soil media are still the focus of attention at present. (4) In the future, "regression process and mechanism", "detection method and evaluation standard", "risk assessment model", "removal technology and control means" are undoubtedly worthy of attention. [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]

Travel has become the most popular way to relieve stress at present. Choosing suitable travel cities and scenic spots among the many alternatives and planning travel routes are the two most troublesome problems for people. For the first question, this paper uses the multi-criteria decision-making method—best-worst method (BWM) to build a priority model of core scenic spots to help people filter out the cities and core scenic spots with the highest travel value from a large number of tourist attractions. For the second question, this paper uses the genetic algorithm to plan the travel route of core scenic spots, so as to reduce the cost of tourists in the travel process and improve the travel happiness as much as possible. Subsequently, a case about the selection of core scenic spots and travel route planning in Hubei Province of China was presented. Among them, 6 cities (i.e. 24 core scenic spots) with the highest travel priority were selected by the score of BWM. Then, the genetic algorithm was programmed by MATLAB to obtain the optimal travel routes of these 24 core scenic spots, with a total distance of 1355.72 km. This paper will promote the practical application of BWM and genetic algorithm. Highlights: Best-worst method (BWM) is applied to filter out the cities and core scenic spots with leading travel values. Genetic algorithm is utilized to plan the travel route of core scenic spots. Case study on Hubei Province of China is conducted to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

High-speed rail (HSR) has been highly valued as an accelerator of green economic growth. However, the difficulty in financing caused by the high investment demand and long construction cycle of high-speed rail is an ongoing dilemma facing the high-speed rail industry. Using data from Chinese cities from 2003 to 2018, this paper explores whether fiscal policy is conducive to solving financing problems for high-speed railway construction. At the same time, this paper investigates the economic and environmental benefits of high-speed rail construction investment for urban development. We find that fiscal policy helps reduce the financing cost of high-speed railway construction projects and attracts social capital, spurring investment in high-speed rail construction. When economic policy uncertainty rises, companies will choose more secure, "safe" investments to avoid potential risks, such as government-led high-speed rail construction projects, which has led to their further expansion. Regarding its economic effect, high-speed rail construction investment directly promotes urban productivity, investment scale, and industrial structure upgrades. Over the long term, investment in HSR construction helps curb urban pollutant emissions, thus contributing to urban eco-efficiency. [ABSTRACT FROM AUTHOR]

Focuses on the use of fetal-cell injections for patients with spinal cord injuries and amyotrophic lateral sclerosis in Beijing, China. Historical background of the unconventional treatment for neurological disease; Assessment of the effectiveness of the technique of injecting fetal cells into patients; Claims of Hongyun Huang who developed the treatment concerning the efficacy of the technique in improving the quality of life for people with spinal injuries.

Why would an emerging market economy without Western democratic institutions provide and promote social welfare to its citizens? This paper explores the driving forces behind the rapid yet unequal expansion of social welfare in China, a phenomenon notable since the late 1990s. Rather than adhering to the conventional state-centered approach that views welfare expansion as a strategy for one-party regimes to seek legitimacy, this study offers an alternate perspective that emphasizes the 'demand' side, particularly the role of business. Through a systematic analysis of all 336 Chinese municipalities from 2001 to 2012, the study demonstrates how big businesses act as 'vanguard,' pushing local governments to enhance social welfare provision. It suggests that big businesses, in the absence of institutionalized democratic institutions, serve as 'functional equivalents,' channeling societal demands to the government. This paper also finds that firms' influence on social policy in non-democracies is more capability based instead of institutional based; large domestic and multinational corporations are more capable in lobbying the government. [ABSTRACT FROM AUTHOR]

With the proposal of the carbon neutrality target, China's attention to carbon emissions has been further enhanced. Effective prediction of future carbon emissions is important for the formulation of carbon neutralization target and action plans in the region. Many factors affecting carbon emissions, cause their development trends may be nonlinear. To forecast the carbon emissions of coal and natural gas in the industrial sector more accurately, a new MGM(1,m,N|γ) model considering nonlinear characteristics is proposed in this paper. The new model introduces power function γ as nonlinear parameter, and the γ value is solved by nonlinear constraint function. We further deduce the simulation and prediction formula and then apply the improved model to the carbon emission forecast. The comparisons show that the nonlinear parameters can modify the trend of sequences and improve the prediction accuracy, which verifies the validity of the model. Finally, according to the influencing factors and forecast results, this paper analyzes the causes of high carbon emissions and puts forward reasonable suggestions for China's carbon governance. [ABSTRACT FROM AUTHOR]

Academic interest in corporate venturing (CV) has grown considerably over the past decade, given its importance to corporate transformation and improvement. Prior research emphasized the effect of the external market environment on CV, neglecting the role of nonmarket arenas in supplying resources and opportunities to incumbent firms as a potentially vital antecedent to CV activities. This paper brings attention to the important but ignored role of corporate philanthropy, which has been employed by private firms to build their political legitimacy and garner the resources and opportunities needed in their external corporate venturing (ECV) activities. Drawing on institutional theory, in particular the notion of political legitimacy, this paper first tests the relationship between corporate philanthropy and ECV. It then unveils the varying moderating roles of three types of political connections (i.e., exploiting entrepreneurs' prior governmental working experience, being political council members and affiliating with the All-China Federation of Industry and Commerce) that influence the proposed relationship. Research findings from 1,574 entrepreneurial private firms in China support our theoretical predictions. This paper advances the CV literature by introducing a nonmarket strategy explanation to the antecedent of ECV and specifying the simultaneous effect of corporate philanthropy and political connections on ECV. [ABSTRACT FROM AUTHOR]

Located in Dunhuang, northwest China, the Mogao Grottoes are a cultural treasure of China and the world. However, after more than 2000 years of weathering and destruction, many murals faded and were damaged. This treasure of human art is in danger. Mural inpainting through deep learning can permanently preserve mural information. Therefore, a digital restoration method combining the Deformable Convolution (DCN), ECANet, ResNet and Cycle Generative Adversarial Network (CycleGAN) is proposed. We name it DC-CycleGAN. Compared with other image digital inpainting methods, the proposed DC-CycleGAN based mural image color inpainting method has better inpainting effects and higher model performance. Compared with the current repair network, the Frechet Inception Distance (FID) value and the two-image structural similarity metric (SSIM) value are increased by 52.61% and 7.08%, respectively. Image color inpainting of Dunhuang murals can not only protect and inherit Chinese culture, but also promote academic research and development in related fields. [ABSTRACT FROM AUTHOR]

This paper investigates optimal decisions for private banking development in China under two innovative organizational structures—the big retail mode (BRM) and the independent development mode (IDM). Under the BRM, the retail and private banking divisions form a cooperative relationship wherein the former transfers high-net-worth customers to the latter. In addition, retail banking receives a share of private banking revenues. We investigate the optimal revenue-sharing ratio between the two divisions and the optimal effort by private banking to serve transferred customers within the cooperative relationship. The analytical results show that as the private banking division becomes more developed, the optimal revenue-sharing ratio decreases, and the private banking division's optimal effort to serve transferred customers decreases because it puts more effort into acquiring new customers. Under the IDM, the two divisions form a competitive relationship since they compete to acquire customers independently. We investigate customer acquisition efforts in this interdivisional competition. Optimal customer acquisition efforts by both divisions increase in potential assets and rates of return. This paper contributes to the literature by (1) analyzing financial innovation by private banks from an organizational perspective; (2) providing an economic analysis for private banking development in China. [ABSTRACT FROM AUTHOR]

Although green technology innovation is an important means to balance the environment and economy, few studies have analyzed the employment effects of green technology innovation in developing countries. Therefore, this paper employs the panel data of 286 prefecture-level cities in China from 2006 to 2017 to empirically test the impact of various green technology innovations on urban employment. Meanwhile, from the perspectives of air quality and industrial structure optimization, the influencing mechanism of green technology innovation on employment is deeply analyzed. The results reveal that all kinds of green technology innovation can significantly increase the employment level of the city, and the promotion effect is strongest in the 2nd year after the patent application. According to the results of heterogeneity analysis, key cities of environmental protection and non-resource cities are more likely to generate positive employment effects through green technology innovation. Finally, the mediation effect test model confirms that green technology innovation can promote employment by improving air quality and causing industrial structure optimization. [ABSTRACT FROM AUTHOR]

This paper uses the spatial panel data model of 272 cities in China from 2000 to 2010 to explore the relationship between ecological infrastructure and tourism development to determine the influencing degree of ecological infrastructure on tourism development. It is found that the expansion of ecological infrastructure has promoted tourism development, with different regional performances. For subsamples with different environmental governance capacities, the expansion of ecological infrastructure generates greater and more tourism growth only for cities with the best ecological infrastructure (BEI cities). In exploring the potential mechanism, BEI cities have the strongest environmental governance effect, followed by cities with good ecological infrastructure (GEI cities) and cities with normal ecological infrastructure (NEI cities), while negative environmental governance effect exists in cities with poor ecological infrastructure (PEI cities). Environmental governance capacity is critical for promoting tourism growth. On spatial correlation, NEI and PEI cities compete for tourism development, but promote each other in BEI and GEI cities, while both ecological infrastructure and environmental governance capacity have a neighbor–companion relationship. The contributions of this paper are: (1) Cities with different types have heterogeneous characteristics. (2) The mechanism linking ecological infrastructure and tourism development is environmental governance effect, with different effects in different types of cities. (3) Spatial interaction among cities is fully considered. [ABSTRACT FROM AUTHOR]

The COVID-19 has impacted the social economy of various provinces in China to varying degrees. How to quickly restore the social economy has become the most concerned issue of the Party, the country and all sectors of society. This paper combines the entropy weight method and TOPSIS method-technique for order performance by similarity to ideal solution, taking the financial policy transmission mechanism as the theoretical basis, and selects the data of 29 provinces in China to obtain the contribution of finance in the socio-economic resilience under the pandemic situation. The empirical analysis results show that the weights of financial policy, pandemic situation and financial basis are different. It can be clearly seen from the weight data that the financial basis is crucial to the socio-economic resilience. Although the COVID-19 pandemic will cause huge losses to the whole society and will also seriously hinder the socio-economic recovery, the effective implementation of financial policies and the good trend of the pandemic situation have a significant promoting effect on the socio-economic recovery. [ABSTRACT FROM AUTHOR]

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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]

Severe disturbances in a power network can cause the system frequency to exceed the safe operating range. As the last defensive line for system emergency control, under frequency load shedding (UFLS) is an important method for preventing a wide range of frequency excursions. This paper proposes a hierarchical UFLS scheme of "centralized real-time decision-making and decentralized real-time control" for inter-connected systems. The centralized decision-layer of the scheme takes into account the importance of the load based on the equivalent transformation of kinetic energy (KE) and potential energy (PE) in the transient energy function (TEF), while the load PE is used to determine the load shedding amount (LSA) allocation in different loads after faults in real-time. At the same time, the influence of inertia loss is considered in the calculation of unbalanced power, and the decentralized control center is used to implement the one-stage UFLS process to compensate for the unbalanced power. Simulations are carried out on the modified New England 10-generator 39-bus system and 197-bus system in China to verify the performance of the proposed scheme. The results show that, compared with other LSA allocation indicators, the proposed allocation indicators can achieve better fnadir and td. At the same time, compared with other multi-stage UFLS schemes, the proposed scheme can obtain the maximum fnadir with a smaller LSA in scenarios with high renewable energy sources (RES) penetration. [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]

To ameliorate the efficiency of urban green innovation is the key to realizing green economic transition. This paper constructs a Super-NSBM model with green patents as the intermediate output, uses this model to assess and decompose the green innovation efficiency of 284 Chinese cities, and finally analyzes the spatiotemporal characteristics and influential factors. The research result showed the gap of urban green innovation total efficiency among various regions in China is narrowing, while the spatial differentiation of decomposition efficiency is deepening. This means that a spatial collaborative innovation division pattern of "Eastern Region R&D + Southwest and Northeast Region Transformation" has gradually formed. In the meantime, this paper also found that the spillover effects of the urban green innovation total efficiency and phased efficiency all can form a significant demonstration effect on the surrounding areas. Finally, financial agglomeration, industrial structure, knowledge sharing, economic activity, higher education, opening, and environmental regulations may affect urban green innovation total efficiency and phased efficiency, and this effect has regional heterogeneity. [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]

The quality assurance of higher education in China is an issue of vital international interest. To improve the international reputation of the nation's universities, steps must be taken to ensure a sustained focus on the quality assurance within its ranks. This paper is primarily focused on the quality assurance models operational in Chinese universities, the Big data challenges and the legal framework backing them. The paper also discusses the implementation of the models, the extent to which they meet international standards, and how they adhere to prevailing laws. The degree of success in attaining and maintaining quality and evaluation of quality improvement opportunities are also discussed. Some of the solutions recommended in this study are the participation of more teachers and students in quality management, more emphasis of Higher Education Institution (HEI) quality assurance on self-regulation and a learning-oriented approach and conducting sessions to collect anonymous feedback from students to reward staff with best practices. Some of the Quality Assurance practices/models adopted in Chinese Universities are the Ministry of Education (MOE) reviews; the Academic Degree Committee oversight; Higher Education Evaluation Center (HEEC) overview, University self-evaluation according to HEEC Indicators, and the Webometric Ranking Model. [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]

This paper explores the characteristics and influencing factors of the spatial distribution of 889 national intangible cultural heritage sites in the Yellow River basin of China based on ArcGIS spatial analysis and Geodetector. The results show that the distribution of national intangible cultural heritage sites in the Yellow River basin is significantly different among provinces, and most of them are distributed in the central and western regions. From east to west, the density of intangible heritage in the Yellow River basin presents a triangular "one area and three points" pattern. All kinds of intangible cultural heritage in the Yellow River basin generally show the characteristic of aggregated distribution.Traditional skills, traditional medicine, traditional theatre, traditional music, and folklore have high levels of agglomeration, and traditional dance, Quyi, folk literature, and traditional fine arts have lower levels. The levels of traditional sports, entertainment and acrobatics have the lowest agglomeration. Among social and humanistic factors, highway density is the most influential indicator for the spatial distribution of national intangible cultural heritage in the Yellow River basin. GDP, population density and the urbanization level also have a great impact on the spatial distribution of national intangible cultural heritage in the Yellow River basin. Among geographical environmental factors, the river system and topography have a certain effect on the spatial distribution of national intangible cultural heritage in the Yellow River basin. Based on these facts, this paper finally discusses the specific path to protect and develop intangible cultural heritage in the Yellow River basin in the context of the newerato promote its creative protection and innovative development. [ABSTRACT FROM AUTHOR]

Performance degradation with intraspeaker variability is a hot topic in speaker recognition. Accuracy dropping over time has become a common and accepted phenomenon in the field of speaker recognition. In China, many people travel between their birthplace and workplaces. Different cultural atmospheres and customs have an effect on the pronunciation of speech. The ongoing work focuses on time-varying and region-changed factors that are caused by population migration. This paper introduces a time-varying and region-changed speech database (TRSD) collected from 55 university students over 3 years. In total, it contains 3795 utterances. To study the impact of the time-varying and region-changed factors on speaker identification and explore hidden factors that may lead to performance degradation, there are also many experimental studies for the database. In the experiments, the changes in characteristic parameters (pitch, intensity, formant and spectrogram) are analyzed and grouped by gender and birthplace. The Gaussian mixture model-universal background model, deep neural network model, i-vector/PLDA and x-vector/PLDA are evaluated on TRSD to provide a reference performance. For the time-varying and region-changed factors, this paper also provided three kinds of corresponding solutions: speaker model adaption, cepstral mean normalization and mel-frequency cepstrum coefficient normalization. [ABSTRACT FROM AUTHOR]

As an ecological barrier to ensure the high-quality development of China's economy, the Yangtze River Economic Belt has attracted more and more attention from academic circles on how to promote the green development of the Yangtze River Economic Belt. This paper uses the SBM directional distance function and the Malmquist–Luenberger index to measure the green total factor productivity of 110 cities in the Yangtze River Economic Belt from 2006 to 2018, and then based on the panel threshold model to empirically explore the intensity of environmental regulations that induce trade openness and promote green total factor productivity. Studies have shown that: Firstly, trade openness has significantly inhibited the increase in green total factor productivity, but environmental regulations can play a positive regulatory role, that is increasing the intensity of environmental regulation can alleviate the adverse effects of trade openness, and it is mainly to improve the adverse effects by promoting the progress of green technology. Secondly, the results of the panel threshold model show that environmental regulations have a nonlinear regulatory effect on trade openness and green total factor productivity. When the intensity of environmental regulations crosses the second threshold, trade openness has a significant positive effect on the impact of green total factor productivity. Finally, the heterogeneity results show that in order to reverse the adverse impact of trade openness on green total factor productivity, the upper, middle and lower reaches of the Yangtze River Economic Belt should formulate relatively strict environmental regulations. [ABSTRACT FROM AUTHOR]

The article reports on the requirements of Chinese universities for the doctors of philosophy degree (PhD) candidates to publish papers in high-impact journals before acquiring their degree.

The article outlines the research of Jake Bailey in disproving the pre-historic microfossils discovered in 1998 in South China as fossils of Algae. Two researchers influenced his work. Samantha Joye presented evidence of reductive cell division in giant sulfur bacteria from the Gulf of Mexico. Heide Schulz researched in biochemical activities in giant sulfur bacteria in the formation of phosphorite. In his paper, Jake Bailey declares the microfossils as fossilized giant sulfur bacteria.

As a type of coronavirus, COVID-19 has quickly spread around the majority of countries worldwide, and seriously threatens human health and security. This paper aims to depict cumulative numbers of COVID-19 infections in China using the growth model chosen by cross validation. The residual plot does not look like a null plot, so we can not find a distribution function for the disturbance term that is close enough to the true frequency. Therefore, the disturbance term can not be characterized as random variables, and stochastic regression analysis is invalid in this case. To better describe this pandemic automatically, this paper first employs uncertain growth models with the help of uncertain hypothesis tests to detect and modify outliers in data. The forecast value and confidence interval for the cumulative number of COVID-19 infections in China are provided. [ABSTRACT FROM AUTHOR]

Background: Because cities prioritize economic development and face ecological space and resource constraints, the development of rural areas, which have untapped potential, should receive increased attention. Consequently, rural ecological landscapes should be constructed through the control of land use types and quality to fully ensure the sustainable development of urban and rural ecosystems. The digital twin is a philosophy and a methodology that connects the digital and physical realms, facilitating realistic and dynamic mapping simulations of the real world. This capability offers valuable insights for digital decision-making, maintenance, and optimization of rural ecological landscapes. Given the digital transformation of rural ecological landscape control, this paper proposes a rural intelligent control approach based on the digital twin concept and new technology. Methods: Five components of the rural ecological landscape digital twin framework are selected to collectively facilitate the monitoring and analysis of rural conditions, formulate strategic solutions, implement management and control behaviors, and enhance participant interaction. The method includes three steps: mapping and fusing information, constructing and managing a database, and constructing a digital platform. Data mining and spatial fusion are performed through targeted mapping methods, and Oracle and ArcGIS SDE are utilized for database construction and fused data management. The twin platform is generated via HTML, desktop application development and geographic information system development technologies using a distributed system as the core. Results: Based on multiple case studies, our platform efficiently gathers system information on rural ecological landscapes using a twin model. Through evaluation and analysis, it determines landscape governance zones, adjusting them based on land use conditions. The platform refines control schemes with feedback from diverse users, ensuring effective control in various scenarios. Its key advantages include high development efficiency, flexible access, and smooth cross-platform integration. Although implemented in rural China, the proposed digital twin framework is applicable to any rural area requiring ecological landscape digital control. Conclusions: The value of the platform lies in its powerful information processing capability, overcoming the limitations of time and space and enabling the presentation and integration of fictional scenes Thus, the platform provides a reference for the digital transformation of rural ecological landscape control. [ABSTRACT FROM AUTHOR]

Accelerating efforts for the Sustainable Development Goals requires understanding their synergies and trade-offs at the national and sub-national levels, which will help identify the key hurdles and opportunities to prioritize them in an indivisible manner for a country. Here, we present the importance of the 17 goals through synergy and trade-off networks. Our results reveal that 19 provinces show the highest trade-offs in SDG13 (Combating Climate Change) or SDG5 (Gender Equality) consistent with the national level, with other 12 provinces varying. 24 provinces show the highest synergies in SDG1 (No Poverty) or SDG6 (Clean Water and Sanitation) consistent with the national level, with the remaining 7 provinces varying. These common but differentiated SDG priorities reflect that to ensure a coordinated national response, China should pay more attention to the provincial situation, so that provincial governments can formulate more targeted policies in line with their own priorities towards accelerating sustainable development. The paper reveals areas of common and differentiated SDG priority at the national and subnational levels in China considering synergy and trade-off. The findings suggest that provincial governments should formulate more targeted policy aligning with national priority to achieve SDGs. [ABSTRACT FROM AUTHOR]

This study introduces a comprehensive framework grounded in recurrence analysis, a tool of nonlinear dynamics, to detect potential early warning signals (EWS) for imminent phase transitions in financial systems, with the primary goal of anticipating severe financial crashes. We first conduct a simulation experiment to demonstrate that the indicators based on multiplex recurrence networks (MRNs), namely the average mutual information and the average edge overlap, can indicate state transitions in complex systems. Subsequently, we consider the constituent stocks of the China's and the U.S. stock markets as empirical subjects, and establish MRNs based on multidimensional returns to monitor the nonlinear dynamics of market through the corresponding the indicators and topological structures. Empirical findings indicate that the primary indicators of MRNs offer valuable insights into significant financial events or periods of extreme instability. Notably, average mutual information demonstrates promise as an effective EWS for forecasting forthcoming financial crashes. An in-depth discussion and elucidation of the theoretical underpinnings for employing indicators of MRNs as EWS, the differences in indicator effectiveness, and the possible reasons for variations in the performance of the EWS across the two markets are provided. This paper contributes to the ongoing discourse on early warning extreme market volatility, emphasizing the applicability of recurrence analysis in predicting financial crashes. [ABSTRACT FROM AUTHOR]

The existing literature primarily examined the impact of unexpected events on the stock market at a single scale, posing the challenge of a lack of multiscale analysis. This paper investigates the impact of COVID-19 on stock markets (China, the U.S., and Hong Kong) from a multiscale perspective using an improved ensemble empirical mode decomposition (EEMD)-based event analysis method. First, the stock price series is decomposed into several independent intrinsic mode functions (IMFs) and a residue. Second, a novel composition method is proposed to reconstruct the IMFs into three components: high-frequency, low-frequency, and long-term trend. We find that the composition of low-frequency and long-term trend components is dominant, which is used to estimate the strength of COVID-19 impact on the stock markets. In addition, the outbreak of COVID-19 significantly increased the intensity of short-term fluctuations in stock prices. Finally, the high-frequency component is analyzed to capture the volatility spillover effects among the three stock markets by the BEKK(Baba-Engle-Kraft-Kroner)-GARCH model. The results show that before the outbreak, there are two-way volatility spillovers between any two of the three markets. After the outbreak, there is no spillover effect between China and Hong Kong, and Hong Kong has no spillover effect on the U.S. However, volatility in the U.S. market still has a significant spillover effect on the other two markets, implying that a mature market can absorb new information more quickly. [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]

Many countries have launched the carbon emission trading scheme (ETS), attempting to limit carbon emissions through total amount control, and thus accelerating the improvement of emission reduction technology. However, the role of the ETS in emission reduction technical change (ERTC) is still controversial. To clarify the role of the ETS in ERTC, this paper firstly proposes an endogenous growth equilibrium model to theoretically analyze how the ETS induces ERTC, and extracts the corresponding influencing factors. Then, the emission reduction technology is further decomposed into the source, process and end-of-pipe emission reduction technologies by the whole process decomposition method. Last, taking China's carbon pilot market as a sample, we use the time-varying difference-in-difference method to empirically estimate the impacts of the ETS on ERTC. Results show that: (1) the ETS is conducive to ERTC, but whether the effect is significant is depends on the technology accumulation in the early stage, research efforts, success probability of technology research, and carbon trading effect; (2) China's ETS significantly improved the process emission reduction technology, but has no obvious effects on the source and end-of-pipe emission reduction technology. (3) China's ETS has heterogeneous impacts on technical change concerning different regions. Accordingly, three suggestions are provided, including laying out new technologies for energy conservation and emission reduction, expanding the industry coverage of the ETS, and correcting the distortion of carbon trading price. [ABSTRACT FROM AUTHOR]

In the past decades, resource shortage and environmental degradation due to rapid economic development have become a severe challenge while limiting China's regional sustainable and coordinated development. This paper provides a case study of Jiangsu Province in China employing the coupling coordination model and geo-detector model to seek solutions for realizing the region coordinated development from the interaction of technological innovation (TI ), industrial upgrading (IU ) and eco-environment (EE ). This study reaches the following conclusions. (1) The coupling coordination degree (D ) of TI - IU - EE system (TIIUEES) in Jiangsu Province was general in the stage of mild unbalance. (2) The D value exhibited a positive evolutionary trend in time series. However, the backwardness of EE constrained the regional coordination development, which led to the slow and small growth with fluctuation. (3) Spatially, the D value generally conformed to a gradient distribution from south to north, which was caused by regional internal extremely unbalanced development. (4) Economic benefits had a decisive effect on the coordinated development in TIIUEES, and the interaction of two factors could gain an "enhanced, bilinear" or even "enhanced, nonlinear" result. This study contributes to exploring the driving determinants of D value in TIIUEES based on the description of the temporal and spatial features and providing a credible reference for future research and decision-makers. [ABSTRACT FROM AUTHOR]

The prevention and treatment of leprosy is a public health and social issue of global concern. China has become the first country in the world to put forward a proposal on the elimination of the harm caused by leprosy. This paper briefly introduces the status of the spread of leprosy in China, and systematically reviews the evolution of policies and measures at different stages of the disease in China, from the serious epidemic of leprosy to the control of the infection, to the basic elimination, and to the elimination of the hazards. On this basis, five main lessons learned from the control and elimination of leprosy in China were also summarized. These provide the basis for promoting the complete global elimination of leprosy and preventing its re-transmission, thereby benefiting all those who still suffer from the scourge of leprosy. [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]

The conventional technique for positioning seafloor geophones in ocean bottom seismic exploration encounters several challenges, including the significant impact of outliers on positioning results, underutilization of high-precision observations, and low efficiency in real-time data processing. These issues inevitably affect the quality of seismic exploration outcomes. To address these challenges and enhance the accuracy of geophone positioning, this paper proposes a rigorous real-time acoustic positioning method for geophones based on sequential adjustment and Baarda's outlier detection approach. The proposed method comprises three key steps: grouping the original acoustic observations, constructing the intra-group acoustic positioning model, and synthesizing the positioning results across the different groups. The validity and practicality of this approach are confirmed through a simulation experiment as well as the field experiment conducted in the Bohai Sea, China. The results demonstrate that the proposed method effectively eliminates outliers in the original observations and maximizes the utilization of high-quality observations. Compared to traditional acoustic positioning methods, it significantly reduces positioning errors from meters to decimeters, and in some cases can achieve centimeter-level precision. When the sound velocity profile in the operating sea area is measured, the method can attain the posterior standard deviation at the millimeter level and positioning errors within 10 cm. When the sound velocity profile is unknown, the method can achieve the posterior standard deviation at centimeter-level and positioning errors of approximately 20 cm. [ABSTRACT FROM AUTHOR]