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In recent years, with the rapid development of the Internet industry, the publicity effect of paperbark walnuts has been substantially increased, and the consumption and demand of paperbark walnuts have been rising, and the output of paperbark walnuts in China has also increased year by year. This paper takes the panel data of the top three prefecture-level cities in each GDP ranking of five provinces in northwest China from 2012 to 2021 as the sample and combines the DEA model with Malmquist to evaluate and analyze the logistics efficiency of paper walnuts in northwest China. It is found that the overall logistics efficiency of paperback walnuts in Northwest China has been improved in recent years, but there are still areas that need to be improved, such as the factor distribution is not reasonable enough; the logistics efficiency of paperback walnuts in Northwest China from 2012 to 2021 is in a fluctuating state; the logistics efficiency of paperback walnuts in Shaanxi Province is better than the other provinces and is in the leading position; the improvement of technological progress has a key role in the total factor productivity improvement. As a result, this paper puts forward five specific suggestions based on the research results to help accelerate the improvement of paper walnut logistics efficiency in Northwest China. [ABSTRACT FROM AUTHOR]

China, situated in the circum-Pacific seismic belt, experiences frequent seismic activity and faces diverse geological conditions, making structural stability of paramount importance, especially under seismic conditions. The majority of current earthquake generation methods do not consider the nonstationary nature of earthquakes. This paper introduces a spectral representation-random function model for generating nonstationary earthquakes, effectively simulating stochastic seismic ground motion. Furthermore, traditional slope stability analysis methods are deterministic and incapable of providing probabilistic assessments of slope instability. Therefore, this paper proposes a unified framework for static and dynamic structural reliability analysis based on the direct probability integration method, quantifying the impact of stochastic seismic ground motion on the dynamic reliability of slope stability. Finally, the proposed methods are applied to an excavation slope in Nanjing, using sliding displacement and safety factors as evaluation criteria to study the reliability of the slope under the influence of stochastic seismic events. [ABSTRACT FROM AUTHOR]

The problems of operating range and costs are the two most critical bottlenecks restricting the extensive application of electric vehicles (EVs) in China and some other countries. There are also some prominent problems in China's EVs, which lead to poor competitiveness of EVs compared with traditional internal combustion engine vehicles. This paper analyzes the key mathematical factors restricting the development and popularization of EVs in China from the aspects of strategic policy, sales situation, and self-problems. For the best-selling family cars in China, select the representative models with the same body structure, and make statistics on various parameters most concerned by consumers, establish a database through data statistics and analysis software. Through summarizing France's standardization development strategy and relevant issues reflected by the development data of its EVs, this paper puts forward the hypothesis leading the development of EVs through standardization to enhance their competitiveness, gives the specific suggestions, and briefly analyzes the feasibility from the aspects of product situation. The research content of this paper provides a certain basis and ideas for the future research work. [ABSTRACT FROM AUTHOR]

Research Background and Content. Intellectual property and high-quality economic development are mutually reinforcing and restrictive, China is a large but not a strong intellectual property country, and China's high-quality economic development still has problems of inadequacy and imbalance. Based on the above research background, this paper mainly studies the relationship between the intellectual property system and the high-quality economic development system from the perspective of coupled and coordinated development. Research Objective. The objective is to measure the coupling and coordination degree between the intellectual property development system and the high-quality economic development system and to explore the spatiotemporal characteristics and differences in the coupling and coordination between the two systems. Research Method. Based on the data of 30 provinces (autonomous regions and municipalities) from 2013 to 2020, the methods used in this paper to analyse include entropy weight method, grey correlation analysis, coupling coordination degree model, and Dagum Gini coefficient. Research Results. The development of economic openness and innovation are more closely related to the development of intellectual property, and the protection, utilization, and creation of intellectual property are more closely related to high-quality economic development; the coupling coordination degree of the two systems shows the characteristics such as "high in the east and low in the west" and "coastal area is better than inland," and the development of intellectual property lags behind the high-quality economic development; the coupling and coordination degree of the two systems shows a slight growth trend in most provinces, but the overall differences shows an expanding trend, and differences between regions are the main sources of overall regional differences. Research Innovation. Research innovation is to study the two-way relationship between intellectual property and high-quality economic development and to measure the coupling and coordination degree between the development system of intellectual property and the high-quality economic development system, and its spatiotemporal characteristics, regional differences, and sources of differences are analyzed. Research Value. Research value is to provide decision reference for the two-way empowerment of intellectual property and high-quality economic development and regional coordinated development. [ABSTRACT FROM AUTHOR]

The new development pattern is a strategic choice to reshape China's new advantages in international cooperation and competition. It is based on China's current development stage, changes in the environment, and other factors. Located deep within China's interior, Xinjiang is a crucial region for the development of the western region and the Belt and Road Initiative. Its agricultural resources are exported to numerous foreign nations. In the context of the new development pattern, this paper first examines the foreign trade issues in Xinjiang. Second, this paper analyzes the current state of Sino-Kazakhstani trade, in particular the current state of trade in agricultural products. In addition, the growth potential of Xinjiang's agricultural international trade is analyzed utilizing the gravity model and fuzzy algorithm. Finally, countermeasures for the mode of development of Xinjiang's international trade are proposed. [ABSTRACT FROM AUTHOR]

Green credit is an important manifestation of commercial banks' environmental responsibility, but few studies have examined the impact of green credit policies on the financial performance of commercial banks. Based on the panel data of 62 commercial banks in China from 2013 to 2020, this paper investigates the changes in financial performance due to the implementation of green credit policies in 2016 using the difference-in-differences (DID) method and explores the mediating mechanism of green credit affecting commercial banks' profit. The sample was divided into a treatment and a control group. The treatment group disclosed total green credit data during the sample period, while the control group did not. The findings of this paper are as follows: (1) the implementation of the green credit policy increases the profits of commercial banks. (2) The green credit policy improves the profits of commercial banks by increasing their noninterest income and reducing their nonperforming loan ratios. (3) The green credit policy does not improve commercial banks' profit by reducing their cost-to-income ratios. (4) The implementation of the green credit policy significantly improves the profits of banks with low (vs. high) nonperforming loan ratios. (5) Compared to large national banks, regional urban and agricultural commercial banks' profits improve more significantly after executing the green credit policy. The research contribution of this paper provides a quantitative basis for Chinese commercial banks to improve their financial performance through the implementation of green credit in recent years and for the government to further improve green credit policies to motivate banks to implement green credit and achieve sustainable development. Then, we further discuss the implications for the prominent theoretical and managerial policies, study's limitations, and future research directions. [ABSTRACT FROM AUTHOR]

How the macro-external environment, i.e., the uncertainty of economic policies, affects the peer effect of corporate investment and whether the ability of managers, as the main decision of corporate investment, affects the peer effect of enterprise investment is worthy of further study. This paper uses Baker's economic policy uncertainty index to obtain China's economic policy uncertainty index and uses the DEA-Tobit two-stage model to measure the ability of managers, combined with the relevant data of China's A-share listed companies from 2010 to 2020, to study the impact of economic policy uncertainty and managers' ability on corporate investment peer effect. We found that China's economic policy uncertainty increases the information acquisition cost of micro-firms and deepens the degree of information asymmetry, and firms are strongly motivated to learn or even imitate the investment decisions of enterprises in the same industry, thus intensifying the peer effect of investment. For enterprises of different nature, the economic policy uncertainty has a more significant impact on the investment peer effect of non-state-owned enterprises than state-owned enterprises. Compared with large enterprises, the impact of economic policy uncertainty on the investment cohort effect of small enterprises is more significant. Then, through group regression according to the median of managerial ability, we found that the investment peer effect is more obvious in enterprises with low management ability and the effect of economic policy uncertainty on investment peer effect is more significant in the sample with low management ability. Based on the empirical research conclusions, this paper puts forward the following suggestions: improve the corporate governance mechanism and the management ability of managers. In issuing economic policies, the government should be cautious and stable to reduce the uncertainty of economic policies. [ABSTRACT FROM AUTHOR]

In the context of the continuous promotion of China's big data development strategy, this paper quantitively analyses China's existing national-level big data policies from the perspective of policy instruments and coword networks, discusses the rationality of existing policies, explores ways to improve policies, and provides a reference for the innovation of China's big data policies. This paper carries out a quantitative textual analysis of China's national big data policy from the perspective of policy instruments using word frequency analysis to obtain a keyword coword matrix and visualization analysis tools to obtain a coword network. This paper further studies the network node characteristics and structure using social network analysis methods, including degree centrality, clustering analysis, and multidimensional scale analysis, to identify the policy structure and characteristics. Improving big data policy requires improvements in policy instruments on the supply side, resolving existing policy gaps, and strengthening coordination with other policies. [ABSTRACT FROM AUTHOR]

In the farming era, the ancestors of Miao moved to a mountainous area in Qiandongnan to avoid wars. When they started their settlement construction, people gave priority to how to deal appropriately with the great survival pressure they were facing. This paper uses the methods GIS spatial analysis, morphological index, and spatial syntax to explain the spatial characteristics of Miao traditional settlements from the perspective of both regional scale and individual settlement and explores the adaptation mechanism. The results show that (1) spatial distribution of settlements shows a tendency of agglomeration and significant spatial heterogeneity; the maximum kernel density is in the Leikaitai area, which is featured by an inclined "T" shape; (2) settlements are concentrated in areas mainly around Qingshui River and Duliu River, with an elevation of 500–1000 m, terrain relief of 10–20 m, and the slope of 5–15°; (3) the external boundary of settlement is mainly finger-shaped and buildings showed a large concentration of small distribution; and (4) settlements have generally formed an overall landscape pattern of "mountain-water-field-forest-building," with the space center appearing inside the settlements and the road connecting the outside of the settlement. This paper summarizes the intrinsic relationship among settlements' spatial characteristics, the natural environment, and the social and economic environment and concludes the internal morphological evolution of the settlement which has shifted from survival adaptability to active search for development. The results of this research can provide a valuable reference for traditional settlement protection, utilization, and sustainable development. [ABSTRACT FROM AUTHOR]

Breast cancer is a cancer disease that seriously threatens women's health and occupies the first place in female cancer mortality. At present, the incidence rate of breast cancer in China is the first in the world and is on the rise. In view of the serious harm of breast cancer to life and health, researchers and institutions are making unremitting efforts to find a perfect diagnosis and treatment plan. With the improvement of computer performance and machine learning levels, intelligent algorithms have been able to replace human behavior and judgment in some fields. The traditional breast cancer diagnosis process requires medical experts to observe patient data repeatedly. In this case, the algorithm technology is used to quickly feedback a high probability reference result to doctors, which is particularly important to increase the diagnosis efficiency and reduce the burden of doctors. In order to improve the accuracy of existing breast cancer recognition methods, this paper proposes and implements a scheme based on a whale optimization algorithm to iteratively adjust the key parameters of the support vector machine to improve the accuracy of breast cancer recognition. In order to verify the performance of the WOA-SVM algorithm, this paper uses the Wisconsin breast cancer data in the UCI database for performance verification experiments. Experiments show that the WOA-SVM model has higher recognition accuracy than the traditional breast cancer recognition model. [ABSTRACT FROM AUTHOR]

Data warehouse technology has been created because of China's technological advancement and the increasing requirements of the educational sector. Physical assessments are treated as tests by many students. Institutions spend plenty of time every year through physical tests, yet the results are rarely shared with students. Teachers are impeded by the size and complexity of physical test data, finding it challenging to support experiments or judge individual students' development. Students have trouble following up and delivering test-based feedback after instruction. In recent years, various researchers have offered insightful advice on how to build multidimensional database structures for such trouble. However, quality requirements alone are not adequate to guarantee quality in reality. So, this paper presents a novel Hypertuned wide polynet convolutional neural network (HWPCNN) framework in the data warehouse technology to attain the greatest performance in physical education quality management. In this paper, we first apply HWPCNNs for physical education quality management to analyze the accuracy and recall of the model. It is no secret that HWPCNN is now one of the most widely used deep learning techniques. When it comes to managing the quality of physical education, the HWPCNN's local perception feature in the data warehouse technology allows it to achieve the best possible results. To validate the model's performance, it is compared to other models and then improved further to increase its accuracy. The physical education resources are gathered as a raw dataset for this inquiry. The raw dataset is cleaned using the Z-score approach to get it ready for further data processing. Then, a sparse matrix approach is employed to build a data cube, while the proposed method is used to index multidimensional databases. To demonstrate that our work is of the best quality in managing physical education, performance metrics of the suggested method are also evaluated and compared with other traditional methods. [ABSTRACT FROM AUTHOR]

Along with the accelerating urbanization process in China, the problem of urban infrastructure layout has become increasingly prominent. The high density of buildings and the extremely unreasonable distribution of infrastructure make the development face great resistance. This paper reveals the problems in the layout of garden infrastructure by studying and analyzing the theoretical foundations of federal learning and distributed learning and provides an in-depth analysis and elaboration of the problem. The paper uses the shape index and landscape index of green infrastructure (green space, arable land, and water bodies), the average width of roads, road network density, and weighted buildings to conduct a comparative study through the differences in ventilation speed and temperature at different layout garden scales. According to the problems existing in the garden layout in the experimental results, corresponding improvement measures are targeted, and the infrastructure layout of the garden is combined with ecology to make the layout within the garden more suitable. [ABSTRACT FROM AUTHOR]

The data of new urban investment bonds in cities from 2011 to 2021 to represent the growth of local government debt is used in this article. This paper studies the relationship between the increase of local government debt and the underinvestment of A-share listed enterprises, which are nonfinancial companies in China. The research finds that the increase in local government debt will crowd out the debt financing of enterprises and then significantly the degree of underinvestment of enterprises, which is represented non-state-owned enterprises, enterprises with high financing constraints, and enterprises with nonlocal debt invested in the industry. As for listed enterprises with relatively low fixed assets, the increase in local debt will further lead to the degree of underinvestment. The above conclusions remain unchanged after a series of robustness tests in this paper. Further research shows that the increase in local government debt will weaken the stimulus effect of loose monetary policy and thus affect the underinvestment of enterprises. This paper expands the research on the factors affecting the underinvestment of enterprises and deepens the research on the consequences of the influence of local government debt on the economic activities of microsubjects. [ABSTRACT FROM AUTHOR]

This paper adopts the method of the random matrix to conduct an in-depth study and analysis of the management of macroeconomic multivariate statistics and regionalization, and to design its management strategy based on a random matrix. A combination of theoretical and applied research, combined with the experience of other cities, is used to study regional economic management using literature analysis, comparative analysis, and deductive induction by summarizing the results achieved in community management, studying its experience, exploring the significance of community management in ETDZs for social development, analyzing the current obstacles and contradictions affecting community management in Suqian ETDZ, and proposing relevant countermeasures for the problems arising therein to enrich the relevant theories and thus promote the level of community management in ETDZs to a higher level. Macroeconomic uncertainty refers to the changes that cannot be accurately observed, analyzed, and foreseen, i.e., the deviation of the expected value of the economy from the actual value. Not all macroeconomic fluctuations belong to the category of macroeconomic uncertainty, only unpredictable economic fluctuations are uncertain. It can be seen from the above that there is a corresponding relationship between the financial income correlation matrix and the random correlation matrix, and both are affected by the same random factors. The importance of uncertainty for macroeconomic policy making is undeniable, and its quantification is a key step. In this paper, we propose an econometric model to eliminate expectations and compare the advantages and disadvantages of different measurement models; we measure a system of fourteen macroeconomic indicators to reflect macroeconomic uncertainty and provide quantitative measurement results for the correct understanding of macroeconomic uncertainty and economic policy making. Factor analysis is used to analyze these six comprehensive aspects to obtain the six-dimensional comprehensive scores of each province and city, and the scores are normalized and visualized. Based on a certain understanding of the economic equilibrium structure of each province and city in China, and a certain control of the overall development of each region itself at this stage, the future economic development trend is studied. [ABSTRACT FROM AUTHOR]

Based on the data of population mortality in China since 1994, this paper studies the changing trend of sex differences of mortality by proposing and implementing some novel approaches. First of all, this paper proposes a new method using the Poisson common factor (PCF) model to forecast the mortality jointly by both sexes. The study finds that the PCF model effectively captures the common trend of mortality between two sexes and uses additional factors to reflect differences of between two sexes, which can reduce the errors caused by low quality or large fluctuation of the mortality in China. Meanwhile, the forecasting values of mortality based on the PCF model can abide by the human biological law well, and the sex ratio of mortality converges to a fixed constant in the long run without increasing too much statistical error. Second, this paper improves the parameter estimation method of PCF model, and the innovative two-step method is used to estimate the model, which can make the maximum likelihood estimator converge more easily. Finally, as an application of the novel methods which are proposing in this study, we measure the longevity risk of pension by using the PCF model and find that the PCF model can make up the underestimation of longevity risk from traditional models and provide more scientific information to the sponsor of pension plan. [ABSTRACT FROM AUTHOR]

As a product of digital technology, financial shared services can be deeply integrated into enterprise operation and management, which is significant to accelerate the financial transformation of real enterprises and achieve high-quality development. Based on this, this paper examines whether and how financial shared services empower the real economy, using data from listed companies in China from 2008 to 2017 as a sample. The research results show that financial shared services can significantly improve enterprise value and thus empower the real economy, and the optimization of operational efficiency is an important path for financial shared services to empower the real economy. Further research finds that the empowering effect of financial shared services on the real economy mainly exists in enterprises with many subsidiaries, large scale, and high labor intensity. This paper not only bridges the gap between financial shared services and micro-enterprise related research but also provides references and lessons for how to implement financial shared services in the real economy. [ABSTRACT FROM AUTHOR]

Actively responding to population aging has become the new national condition of China's aging society in the new era. To do a good job of actively coping with aging in the new era, it is necessary to take multiple measures and work together on the basis of clarifying the major realities and problems faced by China's aging society. From the perspective of big data technology, this paper systematically studies the concerns of China's aging through the method of artificial intelligence. In addition, with two typical aging indicators, three coupled intelligent algorithms are introduced in this paper. The prediction results show that the multi-dimensional support vector machine optimized by the immune algorithm shows good advantages compared with the other two algorithms. The multi-dimensional support vector machine optimized by the immune algorithm, one of the big data, has a good prediction effect on the performance indicators of China's aging, which indirectly illustrates the applicability of big data analysis to the concerns of China's aging. [ABSTRACT FROM AUTHOR]

Digital literacy has been increasingly important among workers in the labour market, and it also has been viewed as a micro reflection of the growing of China's digital economy. Internet use is an integral part of workers' digital literacy, which has a significant influence on entrepreneurial decision-making. This paper aims to explore the direct impact of Internet use on entrepreneurship, analyzing the mechanism and group differences of Internet use. It has a practical meaning to China's policies of promoting employment. Based on the data of China Labour Dynamics Survey (CLDS), the paper uses Probit model and 2SLS regression analysis to examine the direct impact of Internet use on entrepreneurship, and to analyze its mechanism by adopting the mediation effect model. The study indicates that Internet use has significantly increased the probability of starting a business, the impact has been stronger on the new generation, rural residents and the groups with work experience. Further analysis shows that Internet use not only increases venture capital, social capital and income, but also helps to shape individual workers' learning ability, which has an indirect effect on promoting entrepreneurship. The above results show the way of promoting workers' willingness of entrepreneurship, which are expanding Internet access, promoting policies of improving workers' Internet skills, focusing on cultivating comprehensive cognitive abilities including risk awareness and learning abilities. [ABSTRACT FROM AUTHOR]

As an important factor in the creation and growth of new enterprises, social entrepreneurship and new enterprise performance have attracted more and more attention from scholars in recent years. This research analyzes the network relationship of new companies on the basis of existing entrepreneurial network research. This paper proposes social entrepreneurial capabilities and new company performance based on the SOM neural network algorithm to solve these problems and then establishes entrepreneurial networks, organizational learning, and new business performance models. The method of this paper is to study the SOM neural network algorithm and then establish the entrepreneurial ability and enterprise performance evaluation system. The function of these methods is to put forward the meaning and research of venture capital. It also defines the meaning and research of innovation capabilities based on innovation theory, ensuring the scientific nature of the evaluation indicators, evaluation standards, and evaluation processes of innovative enterprises. In this survey, this paper conducted a field survey in Shanxi Province, China, and analyzed the internal impact of the network of social entrepreneurship and new companies on corporate performance. The survey results show that the value of the correlation β between entrepreneurial orientation and entrepreneurial environment dynamics is 0.167 (P < 0.05). This shows that improving the entrepreneurial environment and enhancing social entrepreneurial capabilities have a positive impact on corporate performance. [ABSTRACT FROM AUTHOR]

China's financial market also faces some outstanding problems, namely, obvious structural imbalance in the size of the financial market, on the one hand, the absolute dominance of the size of the indirect financing market, mainly the bank lending market and on the other hand, the imbalance in the size of the direct financing market and the indirect financing market. At the same time, there is also a structural imbalance of the financial market among regions in China. How to verify the objective existence of such structural imbalance in different regions and measure the difference in the level of financial market development among regions is the focus of this paper. This paper constructs a financial market development level indicator system from three dimensions, equity market, bond market, and lending market, and measures the financial market development level by using inter-provincial panel data from 2001 to 2020 through neural network algorithm, time series model, and support vector machine algorithm, and analyzes the regional heterogeneity of financial market development on this basis. The results show that the overall market level of the financial industry in the eastern coastal region of China is the highest, but the intra-regional differences are also the most obvious; the overall market level of the financial industry in the northeastern region of China is the lowest, and the differences with the eastern region rise significantly; the market level of the financial industry at the provincial level in the central and eastern regions shows an all-time decreasing trend, while the western and northeastern regions of China show a convergence, then divergence, and then convergence trend. Therefore, differentiated financial policies should be implemented according to the stage of regional development in order to enhance the financial development level of each economic region and gradually narrow the regional financial development gap. [ABSTRACT FROM AUTHOR]

With the deepening of economic globalization, the communication between countries is getting closer and closer. The common topic of communication between people of different cultures and environments is English. Since the country has established English as a subject, the importance of English has become one of the main factors for the all-round development of students. In recent years, higher vocational education in China has once again developed towards high quality, all-round diversification, and innovation. According to the continuous reform and innovation and independent innovation, college English has been proved to be an important part of higher vocational education and an important measure to promote the development trend of higher vocational education all over the country. With the progress of science and technology and the development of economy, the level of education in China is still improving. People have put forward stronger teaching standards and regulations for English, a course with strong adaptability and practicality. Part of Chinese translation in college English shows its comprehensive ability and high-level thinking ability. In order to integrate this trend, this paper proposes the formulation and use of college English translation teaching model. The experiment proves that the accuracy of the traditional fuzzy evaluation method in the comment module design of college English translation teaching mode is low, only 82% at most. In order to solve this problem, BP optimization algorithm is introduced. The precision and reliability of BP optimization algorithm are improved. Because of the learning effect of the college English translation teaching mode based on the fuzzy evaluation BP optimization algorithm proposed in the certification paper, the certification is carried out according to the questionnaire and the final evaluation method. The students' satisfaction and favoritism at the assessment level and the final results of their classmates have proved the proposed college English translation teaching model. The article has excellent learning effect. [ABSTRACT FROM AUTHOR]

The paper measures the income distribution effects and welfare effects of VAT itself based on Chip2013 household income and expenditure microdata using the Gini coefficient, Suits index, and Theil index from the perspective of annual income and lifetime income, respectively, and the effective VAT rate. Taking provinces as the basic research unit, we use the first-right method, LISA time path, and Spatiotemporal leap to evaluate China's well-being level from 2010 to 2020 and analyze its Spatiotemporal dynamic characteristics. At present, most countries adopt a tax rate model with 1∼3 bands. The current VAT rate structure is "13% + 9% + 6%," which is in line with the international development trend. In the data preprocessing module, the HTTP(S) responses of non-IoT devices are first filtered out and then the text that may contain device information is extracted from the remaining HTTP(S) responses by integrating multidimensional features, and finally, the irrelevant strings in the text are filtered out. At the end of the paper, simulation experiments are designed to verify the function and performance of the identification information extraction system for this heritage connected device, and the results verify that the model identification method in this paper can achieve better identification results compared with existing methods. The results verify that the model recognition method in this paper can achieve better recognition results compared with existing methods. [ABSTRACT FROM AUTHOR]

Digitizing ethnic villages through VR technology is helpful for putting limited resources into the most urgent protection projects at this stage. In this paper, Basha village in western Hunan of China is selected as the carrier, and VR technology is used to simulate its virtual village scene. In this paper, ArcGIS is used to show the distribution of villages, through SketchUp software, 3D modeling of the buildings in the village is carried out, which is imported into Lumion platform and optimized, and finally the VR scene of Basha village is established. Through professional analysis tools, accurate reduction scale, and rational analysis and decision-making, it can not only open up a new situation for the protection of national history and culture, but also better promote the construction and renewal of new countryside. [ABSTRACT FROM AUTHOR]

As an important means of communication, sports public opinion has been paid more and more attention by the country. This article will focus on the emergency events of sports events as the main object and research and analysis of the communication function and law in the public opinion of sports events and analyzes the characteristics of public opinion communication. This paper holds that the media play the "should be" roles in different periods, such as network public opinion monitoring and early warning, public opinion information processing and interpretation, consensus builder highlighting the mainstream, and introspection of public opinion events, and there is a media role cycle in the secondary public opinion period. Spreading law of public opinion in sports events in China: trigger-conduction-outbreak mechanism. At present, the diversified interactive mode of sports events in China makes the communication environment of public opinion in sports events more and more three-dimensional and multidimensional, and it is also convenient for us to make better use of the current regulation means of public opinion in sports events. Sports network public opinion can easily go to "post-truth." In order to strengthen the monitoring of sports public opinion and improve the ability to respond to network public opinion, using interdisciplinary thinking, this paper proposes a network public opinion guidance strategy for sports events. The experiment is aimed at the disadvantage that the trend of sports public opinion analysis and tracking is not clear. The optimization method is proposed, and the accuracy is improved by 87.5%. [ABSTRACT FROM AUTHOR]

With the rapid development of high-speed rail in China, addressing the issue of safety assurance during the operation of the train is very important. A very important part of a train's power supply system is the pantograph and catenary system, which consists of a pantograph and a catenary. Failure of the pantograph-catenary system can cause significant damage to the normal operation of the train. The dynamic performance of the pantograph-catheter system must be detected in real time during the operation of the train. This paper is based on the study and analysis of pantograph-catheter dynamic performance parameters and developed a system for real-time detection of pantograph-catheter dynamic performance parameters based on a car visual system. The results are as follows: based on this detection method, the visual error is low and the accuracy is high. The machine-based directional height detection module developed in this paper has a good detection effect and high test accuracy; the arcing detection module designed in this paper can effectively detect the arcing and store the arcing pictures and can display the duration of single arcing and the arcing rate of the section in real-time. The practical application effect is good. The results show that the focal length of the camera lens is 16 mm, and the error of the machine vision system is low. The system designed in this paper may make a great contribution to the operation condition monitoring and fault diagnosis of the pantograph-catenary system of a high-speed train in the future. [ABSTRACT FROM AUTHOR]

At present, China is in a period of rapid urbanization, and the concept of green structure is getting more and more attention. Green structures can solve asset utilization and ecological problems brought about by rapid urbanization. Therefore, green structure has become the only way for the development of China's construction industry. This paper aims to study the feasibility analysis of new green building technology measures. The related concepts of green building, the analytic hierarchy process, and the meaning of life cycle cost are proposed. The main assessment bottom lines include engineering, environmental, social, and economic bottom lines. From the application examples of green building technology in the starting area of Guangzhou International Financial City, it can be seen that, based on the green building technology proposed in this paper, it is necessary to sort out specific technologies and practices suitable for the actual application of the project in a specific project. Then, the applicability and incremental cost of each technology can be analyzed, and finally, a green building technology system suitable for specific project applications is formed. The experimental results show that compared with residential buildings, the increase of public buildings is 338 million yuan, and the increase of nonassigned parts is about 9.84 million yuan. [ABSTRACT FROM AUTHOR]

In recent years, my country's economic development has entered a new stage, and economic development has entered a new height. Gross Domestic Product (GDP) is the most important and commonly used measure to evaluate social and economic development. It can comprehensively reflect the operating conditions of the economy. At the 2014 APEC summit, Xi Jinping focused on the characteristics of the new normal of China's economy. The economic growth has undergone major changes, and the economic structure has become more and more complete and has been continuously optimized. Therefore, the driving force of innovation plays an important role in the future social and economic development. The high-tech demonstration zone is the main hub of my country's economic innovation and scientific and technological progress, and the development of the high-tech demonstration zone is particularly important in the development of the innovative economy. By predicting the economic growth, the development structure can be adjusted in time, and the coordinated allocation of resources can be achieved, which is conducive to the stable and rapid development of the economy. Therefore, it is very necessary to predict my country's economic growth. At present, more and more scholars have invested more energy in the establishment of economic forecasting models. Previously, the prediction effect of traditional models was not satisfactory. At present, the field of target camera machine learning has been transferred. The application of the powerful nonlinear fitting ability of the machine learning model can improve the prediction effect. Based on this, this paper studies the use of artificial neural network with improved BP algorithm to predict social and economic development, and analyzes social and economic development trends and changing laws. The results show that the forecasting model constructed in this paper has a good forecasting effect, and the research results can provide a theoretical basis for scientifically formulating macro-control policies. [ABSTRACT FROM AUTHOR]

In recent years, the tourism industry has grown rapidly around the world as an emerging force, especially in China, which has become the world's leading tourism country in recent years, and its tourism revenue also occupies a good weight in the country's total income. The number of tourists every year shows a very high growth rate, which not only improves the tourism economy but also brings great pressure to the management of various tourist attractions. In this context, many tourist attractions are actively developing innovative applications of new technologies, hoping to effectively improve their management efficiency. In these experiments, the speech big data analysis technology has achieved remarkable achievements, so it is necessary to combine the speech big data analysis technology with the demand analysis of the tourism industry. The purpose of this paper is to study the effective model of tourism consumer demand prediction using big data analysis. In the process of completing this paper, we consulted a large number of research results of big data analysis technology, tourism-related books, and demand prediction models in HowNet, VIP, and other network databases as well as campus libraries, summarized the related concepts of tourism, and used big data analysis technology to predict the demand of tourism consumers. Understand the needs of tourism consumers on major tourism websites, and extract the indicators that will affect the forecast results of consumer demand, establish a demand forecast model based on the indicators, and analyze its forecast effects through comparative analysis to understand its advantages and disadvantages, in order to establish a tourism demand forecast models providing actionable advice. Through the practical application case of the demand forecasting model, this paper puts forward the development strategy of tourism. The experimental results show that the mean square error of the neural network model is less than 2.5, which is more suitable for predicting the number of tourists, indicating that different models are suitable for predicting different indicators. The main contribution of this research lies in the modeling and analysis of regional tourism characteristics and tourists' willingness, so as to achieve accurate prediction of tourists in scenic spots and formulate targeted plans. [ABSTRACT FROM AUTHOR]

The rapid development of tourism in China has also caused a lot of energy consumption and serious environmental problems. In the context of sustainable development, low-carbon tourism has become the consensus of management departments, relevant industries, and academia. In environmental-related fields, DEA is considered as an excellent efficiency analysis tool because of its powerful optimization ability. The final variable of DEA method is weight. In order to avoid the influence of human factors with predetermined weights in tourism analysis, this paper studies the evaluation of tourism ecological efficiency based on DEA model. China's overall tourism ecological efficiency showed a fluctuating upward trend, rising from 0.853 in 2018 to 0.906 in 2021. The national average efficiency over the past four years is 0.855, which is at a low level, indicating that the construction of tourism ecology is still in its infancy, and there is still much room for improvement in the future. As the tourism industry system involves many aspects, such as natural ecology, humanities, economy, and so on, it is an extremely complex system. The research on the ecological efficiency of tourism cannot simply rely on the knowledge system and thinking of a single discipline. Therefore, combined with the relevant theories and knowledge of tourism, management, industrial economics, regional economics, industrial ecology, and other disciplines, this paper makes a systematic study on the problems and countermeasures of Qiaozhai. [ABSTRACT FROM AUTHOR]

With breakthroughs in big data, communication networks, artificial intelligence, and other next-generation information technologies, intelligent production methods and digital lifestyles have risen rapidly. Digital economy has become a significant force in promoting regional low-carbon development as a new economic form in the important period of the intersection of digitalization and "carbon peaking and carbon neutrality goals." This paper empirically explores the moderating role and threshold role of human capital in digital economy and regional carbon productivity by systematically measuring digital economy indicators. Research shows that China's digital economy development index is rising annually. However, the development of digital economy varies significantly between different regions. The results of moderating effect showed that human capital accumulation could dramatically strengthen the role of digital economy in promoting regional carbon productivity. The results of the threshold effect showed that human capital plays an important threshold role in the relationship between digital economy and regional carbon productivity. This paper provides a practical reference for exploring power sources, policy design, and path selection of low-carbon development. [ABSTRACT FROM AUTHOR]

As a key means to elevate low-carbon energy transformation in China, multi-energy microgrid accelerates the construction of new power systems. In order to scientifically evaluate the benefits of multi-energy microgrids, we proposed a benefit evaluation index system from the dimensions of economy, reliability, low carbonization, and intelligence. Considering the relationship between the evaluation indicators, this paper innovatively proposed a multi-energy microgrid benefit evaluation model based on AHP-VWT-MEEM. In addition, this paper selected different multi-energy microgrid demonstration projects in the China Southern Power Grid Company Limited's region for example analysis. In the example analysis, through the comparison of the comprehensive benefits of the three projects, the comprehensive benefit of the project 3 is the best. On this basis, from the specific configuration plan of Project 3, it can be concluded that the configuration of larger capacity thermal storage can realize the "thermal decoupling" of cogeneration, thereby improving the flexible adjustment capability of the demonstration area, promoting the consumption of renewable energy, and obtaining more considerable comprehensive benefits. At the same time, it is pointed out that the comprehensive benefit evaluation result can be improved by appropriately reducing the investment cost of project 3. [ABSTRACT FROM AUTHOR]

In recent years, the development of intelligent iteration technology and the use of big data processing technology have set off an upsurge, and the analysis and application of artificial intelligence algorithms have been paid more and more attention. In order to face the challenges of Arab migration and international trade, this paper constructs the basic structure of the Arab migration action imitation model. In this paper, a simulated servo clustering algorithm based on big data and intelligent iteration is used. Then, through the analysis of pseudo servo clustering algorithm, an optimization model is established, and a big data analysis system is formed. This paper focuses on the wide application of big data statistics to solve the construction of Arab immigration and entrepreneurship data system. This paper studies and applies the big data statistics and intelligent iterative algorithm of Arab immigration behavior, focuses on the annual ladder degree of Arab immigrants, and constructs a pseudo servo cluster system based on Intelligent iterative algorithm. Finally, the simulation experiment verifies whether the clustering model can accurately retrieve the behavior of Arab immigrants in China. The era of big data provides good development opportunities for Arab immigrants and international trade, but it also faces severe challenges. The study provides a reference for strengthening the analysis of international trade, and puts forward perfect countermeasures in combination with the actual situation, so as to improve the efficiency of international trade management and promote the better implementation of international trade. [ABSTRACT FROM AUTHOR]

With breakthroughs in big data, communication networks, artificial intelligence, and other next-generation information technologies, intelligent production methods and digital lifestyles have risen rapidly. Digital economy has become a significant force in promoting regional low-carbon development as a new economic form in the important period of the intersection of digitalization and "carbon peaking and carbon neutrality goals." This paper empirically explores the moderating role and threshold role of human capital in digital economy and regional carbon productivity by systematically measuring digital economy indicators. Research shows that China's digital economy development index is rising annually. However, the development of digital economy varies significantly between different regions. The results of moderating effect showed that human capital accumulation could dramatically strengthen the role of digital economy in promoting regional carbon productivity. The results of the threshold effect showed that human capital plays an important threshold role in the relationship between digital economy and regional carbon productivity. This paper provides a practical reference for exploring power sources, policy design, and path selection of low-carbon development. [ABSTRACT FROM AUTHOR]

This paper explores the general decision mechanism of stock price synchronicity through in-depth research on the two main viewpoints of information efficiency view and irrational behaviour view. On this basis, we explore the effect of China's economic policy uncertainty gradually on the synchronisation of stock prices and provide a reasonable explanation for it. Based on the China Economic Policy Uncertainty Index developed by Baker et al., this paper takes China's A-share listed firms from 2010 to 2019 as the primary sample and tests the effect of China's economic policy uncertainty on the synchronicity of stock prices by constructing a comprehensive mediation effect test procedure. The fundamental effect and its internal mechanism of action have been supplemented and verified from investor sentiment. Strengthening the research on economic policy uncertainty and stock price synchronisation may deeply explore the internal mechanism of the listed firms' stock price changes, help in improving the information production function and information transmission function of the securities market, help in improving the resource allocation capacity of the entire capital market, and then promote the long-term healthy development of China's capital market. The main findings of this paper are as follows: (1) in China's stock market, which is driven by noise, the increase of economic policy uncertainty will significantly reduce the synchronisation of stock prices; (2) increased uncertainty about China's economic policy will fuel the investor sentiment and reduce stock price synchronicity, with investor sentiment playing an intermediary role. [ABSTRACT FROM AUTHOR]

This paper firstly reviews the achievements and existing problems of China's government in the supervision of medical service price in public hospitals in recent years. On this basis, patient's interests, the interests of the public hospital, medical staff perspective, analysis of the three main psychological cognitive differences' influence on medical diagnosis strategy, and the utility of public hospital medical service price regulation are analyzed, and accordingly perfect China's public hospital medical service price regulation suggestions are put forward. In this paper, taking a medical institution as an example, combined with the psychological cognitive differences of multi-interest theme, and through research, it is shown that the causes of influencing the unreasonable admission behavior of patients in medical institutions are as follows: first, the characteristics of vulnerable groups of patients affect the unreasonable admission behavior, mainly children and the elderly. Second, the health risk avoidance psychology drives patients to be hospitalized unreasonably, especially those with chronic diseases or those who pay attention to their own health. Third, the influence of convenience degree on unreasonable admission is relatively small. Fourth, doctor's advice has an important influence on unreasonable admission behavior. Fifth, the medical insurance system affects the unreasonable admission behavior of patients to a certain extent. [ABSTRACT FROM AUTHOR]

Buffer operators can effectively weaken the impact disturbance of the system and restore the original appearance of the system. However, the buffer strength of the existing buffer operator is fixed, and the buffer strength cannot be adjusted. So the buffer effect for the system impact disturbance is not flexible enough, and the accuracy of the prediction model established is not high. In order to solve this problem, this paper proposes weakened buffer operators with time-varying parameters, analyzes the properties of the newly constructed buffer operator, and proves the superiority of the new buffer operators theoretically. Finally, the new buffer operators proposed in this paper are applied to the prediction of the number of employees in China's air transport industry and the unsafe events in China's civil aviation. The results show that the proposed buffer operators are better than the existing buffer operators, which further verify the validity and practicability of the proposed buffer operators. [ABSTRACT FROM AUTHOR]

The digitalization of the automobile industry must depend on the information technology industry. The coupling development of the two creates conditions for the realization of industry 4.0 and intelligent manufacturing. The purpose of this paper is to make an empirical study on the possibility of coupling and the coupling degree, correlation degree, and innovation ability of China's automobile industry and information technology industry. This paper takes the intelligent manufacturing of the automobile industry as the research object. According to the current situation of China's automobile industry, this paper uses data to analyze and predict the development level of China's automobile industry and the gap with the foreign automobile industry. Firstly, it summarizes and analyzes the development of China's automobile industry and information technology industry. Then, the gray correlation analysis method is used to explore the factors affecting the innovation of China's automobile industry. It is found that the relationship between capital investment and innovation is the most significant in "industrial innovation investment." Finally, the coupling development model of the automobile industry and information technology industry is established, and the coupling degree of the two is analyzed by using the analytic hierarchy process and the Delphi method. The research of this paper mainly focuses on the automobile industry. Under the wave of internet, other industries such as the commerce and service industry also have a strong coupling relationship with the information technology industry, which will provide a new research direction for the follow-up research of experts and scholars. [ABSTRACT FROM AUTHOR]

After years of development, today's society is a prosperous era of the knowledge economy. Different from the previous period of development by consuming natural resources, people have realized that talents with technology and knowledge have become an important factor in promoting the development of social production. That is to say, the improvement of population quality has not only an impact on its own development but also an important impact on the comprehensive strength and competitiveness of its location. Population quality is the stipulation of the population in terms of quality, also known as population quality. It includes ideological quality, cultural quality, physical quality, and so on. Data fusion is a technology for the comprehensive analysis and processing of information from multiple sources. Therefore, this paper comprehensively considers the influence of ideological and moral quality and population structure. Under the algorithm of fusion data, the impact of population quality on residents' income is explored. This paper uses the analytic hierarchy process to weight each indicator and calculate the comprehensive score. This paper ranks the quality of population and economic development of each province, city, and autonomous region in China according to their high scores. The results of the experiments in this paper indicate a relevant analysis with the income distribution of the nation's residents, and the correlation is −0.9493. There exists a negative relation between the overall quality of Chinese residents and the income gap. [ABSTRACT FROM AUTHOR]

This paper presents an in-depth study and analysis of the impact of foreign trade on cement products and the ecological environment in China through Granger causality analysis. Based on the theoretical basis of foreign trade, ecological environment, and the relationship between them, a general equilibrium model is used to empirically analyze the "three effects" of foreign trade in Chinese cement products on the ecological environment, and the effects of import and export trade on ecological environment and the net effects are calculated, respectively. Then, based on the data of domestic and foreign cement product production and trade, the purpose, scope, and environmental impact factors of the ecological impact of foreign trade of Chinese cement products were determined by the life cycle assessment method, and the inventory analysis was carried out in phases based on the six aspects of nonrenewable resource depletion, global warming, photochemical ozone generation, acidification, eutrophication, and human health damage. The results were characterized and standardized, and the hierarchical analysis method was used to weight the evaluation of each environmental impact type, and finally, the resource consumption coefficient and environmental impact load index values and corresponding ratios were determined based on the green product evaluation method. This paper establishes an index system for the ecological and environmental impacts of foreign trade of cement products, which is a guide for the ecological and environmental impacts of foreign trade of other products in China. The results of the study on the ecological and environmental impacts of foreign trade of Chinese cement products also have important practical significance for the formulation of regulations and standards related to the cement industry, the adjustment of the import and export structure of cement products, and the improvement of production equipment and processes. [ABSTRACT FROM AUTHOR]

As China's economic level and industrial volume continue to develop and expand, the traditional methods of business management and resource scheduling demonstrate significant limitations and misalignments with China's daily economic activities. Traditional industrial and commercial management resource scheduling is highly reliant on manual labor. When confronted with the requirements of large-scale project management, the pure manual mode cannot track the real-time progress of the project flexibly, effectively, and in a timely manner, resulting in the inability to complete the corresponding resource-scheduling work efficiently, which will affect the overall operation progress of the project. Deep neural networks have a high-application potential for solving extremely complex and highly nonlinear optimization problems. Artificial intelligence and deep learning research have advanced at a rapid pace over the past few decades, thanks to the efforts of numerous researchers. Combined with GPU technology, the deep learning framework can provide an extremely complex optimization problem with a practical and feasible optimization scheme and corresponding solution path in a very short amount of time. Therefore, this paper explores the potential application of deep learning technology to industrial and commercial resource-scheduling management. By analyzing the benefits of deep learning technology and the bottleneck issues of existing industrial and commercial resource scheduling, a real-time optimized industrial and commercial resource-scheduling model based on deep learning technology is developed. The model is evaluated using the respective data set. The test results demonstrate that the resource-scheduling model proposed in this paper has strong real-time and high-operation efficiency and can assist engineers in completing the corresponding resource-scheduling tasks. [ABSTRACT FROM AUTHOR]

With breakthroughs in big data, communication networks, artificial intelligence, and other next-generation information technologies, intelligent production methods and digital lifestyles have risen rapidly. Digital economy has become a significant force in promoting regional low-carbon development as a new economic form in the important period of the intersection of digitalization and "carbon peaking and carbon neutrality goals." This paper empirically explores the moderating role and threshold role of human capital in digital economy and regional carbon productivity by systematically measuring digital economy indicators. Research shows that China's digital economy development index is rising annually. However, the development of digital economy varies significantly between different regions. The results of moderating effect showed that human capital accumulation could dramatically strengthen the role of digital economy in promoting regional carbon productivity. The results of the threshold effect showed that human capital plays an important threshold role in the relationship between digital economy and regional carbon productivity. This paper provides a practical reference for exploring power sources, policy design, and path selection of low-carbon development. [ABSTRACT FROM AUTHOR]

The new infrastructure is becoming the key support and important material guarantee for a new round of scientific and industrial changes in China. In recent years, the further upgrading of the scale and structure of resident consumption has faced resistance from both the supply and demand sides. By enhancing the consuming environment, enhancing transaction efficiency, and lowering spatial barriers, among other benefits, new infrastructure could encourage improvements in resident consumption level and the optimization of consumption structure. This research empirically investigates the consumption implications of new infrastructure under two standards using panel data from 30 Chinese provinces from 2003 to 2020. The findings demonstrate that new infrastructure significantly affects the expansion and upgrading of consumption. Its influence is quite heterogeneous. Additionally, it is discovered during the mechanism of influence test that improving the industrial structure might have a considerable impact on the consumption effect of new infrastructure. In the context of China's economic transition to high quality, this paper aims to quicken the upgrading of industrial structure and optimize the layout of new infrastructure investment in order to increase consumer returns from infrastructure and support consumption upgrading. [ABSTRACT FROM AUTHOR]

Landslides occur in most countries. As one of the most serious geological hazards, landslides affect infrastructure construction. Thus, it is vital to prepare reliable landslide susceptibility evaluation maps to avoid landslide-prone areas for various construction projects. In recent years, supervised machine learning algorithms have been widely used in landslide susceptibility evaluation, but many flaws remain in the selection of nonlandslide point samples for comparative analysis. It is significant to improve the authenticity of sample data and reduce the impact of noise. China's Funing County was used as a case study in this paper, which first identified 122 landslide incidents based on historical data, fieldwork, and remote sensing images to create a landslide inventory in the research area. In addition, 12 causal factors of landslides were determined, including elevation, slope, aspect, plan curvature, profile curvature, distance to roads, distance to rivers, distance to faults, rainfall, normalized difference vegetation index (NDVI), lithology, and land cover. K-means clustering was used to purify the factor data factors before data-driven certainty factor (CF) and frequency ratio (FR) models, and machine learning models, random forest (RF) and artificial neural network (ANN), were used for a comparative study on landslide susceptibility evaluation in Funing County. The results show that the selection method of nonlandslide sample data will affect the accuracy of different evaluation models. The purified sample data improved the prediction accuracy of the four models, with significant prediction accuracy improvements observed in the ANN model. The purification of nonlandslide sample data by K-means method is of great significance for the drawing of landslide sensitivity map. [ABSTRACT FROM AUTHOR]

With the sharply increased development of variable renewable energy resources (VRERs) in recent years, the hydro-wind-photovoltaic (PV) hybrid system (HWPHS) has the prospective to enhance the grid integration of VRERs. Nevertheless, the intense variation associated with wind and PV generation causes uncertainties in the long-term operation of the HWPHS. To overcome this drawback, this paper develops a novel method to derive adaptive operating rules for a cascade HWPHS. First, a scenario-generating method coupling Kernel density estimation with the copula function is proposed to characterize the wind and PV forecast errors. Second, based on the power generation scenarios, an optimal scheduling model for the cascade HWPHS considering transmission section constraints is proposed to simulate the hydro-wind-PV complementary operation; finally, the long-term operating rules for the cascade HWPHS are extracted by grey relational analysis and BP neural network. As a case study, the HWPHS of the Wu River basin in China is chosen. Results demonstrate that the proposed model can effectively utilize the flexibility of cascade hydropower stations, improve transmission section utilization efficiency, and promote clean energy absorption. [ABSTRACT FROM AUTHOR]

The carbon emission reduction potential of photothermal utilization of solar energy is outstanding, but the breakthrough of technology is closely related to the management of innovation and research in higher educational institutions. What factors affect such relationship is discussed in this paper. Based on the photothermal technology project data released by the National Natural Science Foundation of China (NSFC) and China education yearbook, this paper analyzes the variable relationship between the output of solar thermal technology innovation and industrial demand. Specifically, the negative binomial regression was constructed based on the technological project approval data. The results show that the input of scientific research resources has a key influence on the development of solar thermal technology, the establishment of technological projects or the subsequent patent application derived from technological projects. The results also show that the demand for photothermal technology and green innovation complement each other. [ABSTRACT FROM AUTHOR]

The rapid development of digital economy puts forward theoretical and practical requirements for the construction of legal model of big data transaction management (BDTM). The new problems of ambiguous data ownership, privacy leakage, chaotic digital transaction order, and low nationalization in the context of big data transactions have largely restricted the role of China's big data transaction market and related laws and regulations and are not conducive to promoting the scientific and standardized development of China's digital economy. In this paper, we firstly analyze the connotation, importance, and necessity of the construction of legal model of big data transaction in the era of digital economy from the basic connotation of legal model. Then, we analyze the need to adhere to the principles of systematization, security, and openness in the construction of legal model of big data transaction management and focus on four methods of contract law, market behavior, replication behavior, and dispute resolution in the construction of legal model of big data transaction management. Finally, we summarized the conclusions of this paper. The conclusions of this paper are important for promoting the transformation of digital resources into effective data elements and advancing the scientific and standardized development of China's digital economy. [ABSTRACT FROM AUTHOR]

In recent years, China has been paying more and more attention to the development of the sports industry, and many sports are no longer seen as a mere sport, but can be developed into an industry and play an important role in the development of the economy. This paper examines the application of multi-source big data mining techniques in the analysis of basketball economic management. Firstly, through multi-source big data mining technology, we collect various factors that influence the development of basketball economic industrialization, use Hash Tree-based Apriori algorithm to mine various influencing factors for basketball economic industrialization, and analyze the correlation between each influencing factor. The association rule mining results are then used to analyze the relationship between the key influencing factors and the industrialization of the basketball economy. This paper examines various aspects of the Chinese basketball league market, including the management system, market operations, and talent flow, and compares them with the foreign basketball industry models, in order to analyze the operation of China's basketball industrialization and develop corresponding countermeasures to improve basketball economic management based on the results of the study. [ABSTRACT FROM AUTHOR]

In recent years, the Chinese capital market has suffered several violent shocks, and the characteristics of systemic risk contagion across industries and markets have become increasingly important. It brings great potential danger to the stability of financial markets. Therefore, exploring the risk spillover among the real sectors has gradually attracted the attention of scholars. This paper examines the cross-industrial tail risk spillover network in the Chinese financial market. The characteristics and the dynamic contribution of each industry in the tail risk transmission chains are explored. We use the ∆CoES-ENGDFM-LVDN model based on monthly data from 2006 to 2020 to measure the tail risk of 28 industries in China and form a cross-industrial tail risk spillover network. The results show that different industries have different levels of spillover and importance in the network. Tail risk mainly spills over from the nonfinancial sector to the financial sector. The nonbank financial industry is the main recipient of tail risk spillover and is becoming progressively more important in the risk network. In addition, with the promotion of industrial structure, emerging industries such as communications, computers, and health care have begun to play more important roles in the tail risk spillover network in China. This paper not only enriches the research in the areas of tail risk spillover and systemic risk, but also has implications for regulators to maintain financial stability and prevent financial risks. [ABSTRACT FROM AUTHOR]

Dunhuang frescoes are one of China's precious historical and cultural heritages, but this treasure trove of human art has become very fragile due to natural weathering damage and the threat of major natural disasters. Therefore, the preservation of Dunhuang murals has become an urgent task. Digital fresco conservation and restoration work can preserve fresco information permanently, and can use computers to virtually repair frescoes, assist in fresco conservation, assist in fresco copying, virtually evolve the fresco disease process, and virtually display fresco realism. Digital fresco conservation and restoration provides sufficient scientific basis and testing environment for the physical conservation and restoration process of frescoes, and minimizes the danger of conservation work. This paper presents a new approach to digital conservation and virtual restoration of frescoes. Based on research by Dunhuang artists on the mural restoration process, research on pigment composition, knowledge accumulated by the artists' experience, and some of the better-preserved murals, digital image processing, computer graphics, artificial intelligence, and other technologies are synthesized to achieve the virtual restoration of murals. Aiming at the current situation of Dunhuang mural restoration, combined with the actual painting process, this paper puts forward a set of computer-aided mural restoration solution based on intelligent generation of line graph. It can be well applied to the actual restoration work. It is a new attempt of computer-aided restoration of ancient paintings. [ABSTRACT FROM AUTHOR]

In recent years, the environmental conditions in China have continued to deteriorate, and the pressure of environmental pollution and ecological deterioration has also increased. To strengthen environmental protection work, we must not only pay attention to the natural causes of environmental pollution but also find the social causes of its occurrence. Only in this way can environmental protection and social construction promote each other and develop together. The relationship between the public's environmental protection awareness (including environmental protection knowledge and environmental awareness) and environmental behavior is a research problem with important theoretical and practical significance. Based on the perspective of planned behavior theory, this paper derives the following research hypothesis: the more the public's knowledge of environmental protection, the deeper their understanding of the importance of environmental issues, which will directly promote the public's adoption of environmental behavior. The richer the environmental behavior, the more likely it will affect the environmental cognition that includes the two dimensions of subjective psychological will and the perception of environmental pollution, and then the environmental behavior. The state of the public's environmental cognition will also directly affect the environmental behavior. This paper analyzes China's CGSS2013 data, and the results show that there is a correlation between environmental protection awareness and environmental behavior. In addition, environmental protection awareness has a greater impact on private environmental behavior than on public environmental behavior. [ABSTRACT FROM AUTHOR]