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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]

As one of the largest markets of electronic and electric equipment, China has not completely established the formal recycling system of WEEE compared with the developed countries. As a result, China is facing the huge challenge of resource waste and water/soil environmental pollution. In this paper, according to the current regulations on WEEE recycling and disposal issued by Chinese government, the business model of the Chinese WEEE recycling system was designed, and a bilevel programming-based model was proposed to help the disposal factories to establish the regional efficient and economical WEEE recycling network. This model addressed the optimization of bilateral benefits of disposal factories and the third-party recycling agencies/stations. An experiment based on a regional WEEE recycling business data was solved by the NSGA algorithm to validate the proposed model. With the result, the proposed model was compared with the related studies on Chinese WEEE recycling network planning. With the comparison and the analysis on the experiment result, it was found that the proposed model had considerably stable convergence and optimization performance, which proved that this model can be regarded as a useful tool to the planning of the Chinese regional WEEE recycling network. In the last part, the future improvement of the proposed model was also discussed. [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]

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]

Health education competency is essential for nurses to engage in clinical nursing practice. Nurses with a high level of health education competency have a promising future. However, at the present stage, health education of nurses suffers from insufficient effective communication skills, poor skillfulness, and lack of health education knowledge. The above problems seriously affect the improvement of nurses' health education level and restrict the development of health education in health industry. Therefore, it is very important to construct a health education competency model on how to improve health education. This paper, by taking nurses as the research object, constructed a health education competency model for nurses using the fuzzy comprehensive evaluation method and fuzzy cluster analysis method. In this paper, we first applied the fuzzy cluster analysis method to classify the relevant factors affecting nurses' health education competency. Then, we investigated 10 experts from four tertiary general hospitals in Heilongjiang Province of China and asked them to rate nurses' health education competency through the fuzzy comprehensive evaluation method. According to the results of this research, nurses' knowledge and experience, nurse-patient communication competency, and health education implementation competency are the key factors affecting nurses' health education competency. But the influence from overall quality is relatively minimal. Among the indicators of knowledge and experience, nurses' health education knowledge is the most important indicator because it can provide objective basis and expand ideas for the hospital health education management and nursing personnel training. [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]

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 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]

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 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]

Connotative development of higher education is of great significance in China. To promote this endeavor, this paper has established a connotative teaching system based on the Kano model and has applied it in the teaching of statistics. Guided by the fundamental demands of students, this system is built from the four perspectives, including students, third-party evaluation institutions, schools, and morality and law. It also takes the advantages of the Kano model, featuring the three dimensions of essential demand quality, expected demand quality, and charismatic demand quality. The paper also describes a two-year experiment to test the effect of the Kano-model-based connotative teaching system. It has collected more than 200 effective samples and compared the performance of students in private colleges. The results are as follows: the connotative teaching of statistics guided by the Kano model can meet the demands of students in private colleges and improve their comprehensive scores. This model shows remarkable performance and will promote the reform on connotative teaching. [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]

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]

With the rapid development of China's economy, power demand has been closely linked with economic development in order to analyze and predict the future power situation in China. Based on the historical data of China's electricity consumption, this paper analyzes the data characteristics of China's electricity consumption by using Eviews software. The long-term trend of power consumption sequence is eliminated by fitting the regression curve, and then the residual sequence is analyzed and identified according to the relevant theory of time series. Using the data of China's power demand from 2004 to 2019, the ARMA time series model is used to analyze China's future power situation finally according to the test statistics of the model. Finally, the exponential regression ARMA model is selected to predict China's electricity consumption. The index regression analysis method extracts the long-term characteristic information of the sequence, which is conducive to the stability processing and empirical analysis of long-term prediction. The result predicts China's power demand in 2020 more accurately, which can provide a reference for the future productivity layout of China's power. [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]

Lack of trust, lack of standards, and low efficiency are the three biggest problems in China's trade financing at present. With the development and application of new generation technologies such as big data, cloud computing, artificial intelligence, and blockchain technology, China is in the stage of financial technology 3.0 under the deep integration of finance and technology. In the field of financial technology, the most concerned is the application of blockchain technology in trade finance business. With the successive construction of various blockchain platforms and the acceleration of the internationalization process, the international trade credit risk behind it is also increasing. Among many financial services, trade finance is the most closely integrated field with blockchain technology. In this context, preventing the risks in the business process of international trade enterprises, so as to reduce the cost of financial transactions, improve the effectiveness of financial services, and better serve the real economy is not only the internal development needs of enterprises, but also the national financial strategy needs. In view of the above problems, this paper analyzes the risk factors faced by multinational trading enterprises in the transaction process through the transaction data of some multinational enterprises on mobile phones, and constructs a credit evaluation system of international trading enterprises based on blockchain, in order to enhance the trade risk resistance ability of international trading companies. [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]

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]

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]

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]

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]

China's regional economic competition is intensifying; in particular, the cluster development of air transport, high-end manufacturing, and modern service industries is closely related to the construction of regional airports. Local governments have listed aviation hubs as the hardcore advantage of high-quality growth in the new era, but it may also lead to excessive convergence and preferential system competition. Based on the "GDP competition" of local governments in China, this paper uses panel data of 78 airports in mainland China from 2001 to 2018 and tries to explore the causes of airport preferential policies. The Synthetic Control Method is used to study the influence of preferential policies on airport passenger and cargo flow, and then the Spatial Durbin Model is used to verify the spatial spillover effect of aviation hubs, which may be magnified by the preferential policies. This paper finds that the impact of preferential policies on airports in central and western China is mainly reflected in the increase of cargo throughput, and there is a spatial siphon effect on cargo throughput between airports. The implementation of the preferential policy enhances this spatial siphon effect, which in turn leads to more fierce competition. The research results show that the preferential policies, issued in central and western aviation economy, have shown a trend of evolving in the direction of vicious competition. Before the airport preferential system produces more negative effects, it should be corrected in time, and each aviation economic zone in the central and western regions should be scientifically coordinated and reasonably planned. [ABSTRACT FROM AUTHOR]

With the acceleration of popularization of higher education in China and the intensification of employment difficulties for college graduates, the employment field has gradually widened, the number of entrepreneurs has gradually increased, and the regional differences are obvious. The employment difficulty of college graduates has aroused wide-spread concern in the society. Therefore, the convolution neural network (CNN) is used to establish a prediction and evaluation model for the employment development trend of college graduates in this paper. The feasibility and practicability are proved by a case, which is of great significance for the government and colleges to provide decision-making support and suggestions to solve the problem of difficult employment. [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]

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]

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]

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]

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]

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, 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]

This paper uses Python programming to improve the existing price index method and calculate the integration level of the forest products market in China. Based on the model, the influencing factors of domestic forest product market integration were examined empirically. The results show that the integration degree of the forest product market in recent years lags behind the average level in China. In this paper, the improvement of the existing price index method can calculate the level of market integration more quickly and accurately, and this improvement has obvious advantages in the case of a large amount of data. In terms of development, the overall pattern shows an increasing trend, and the eastern, central, and western provinces are gradually converging, although the differences between provinces continue to expand. In terms of influencing factors, the coefficient of the local government's emphasis on forestry, the prosperity of international trade in forest products, and highway density were significantly positive factors, while the number of foreign investors and the railway density had no significant effects. In this paper, the optimization of the measurement method of market integration makes it easier for scholars to obtain the data on the level of market integration and promote in-depth research in the field of market integration. [ABSTRACT FROM AUTHOR]

Through the analysis of the risk transmission mechanism of chemical substances in toys, this paper identifies risk sources, transmission carriers, key nodes, and risk recipients, and draws a risk transmission path diagram. Taking the risk factors in the supply chain system as the research subject, this paper constructs a risk index system for chemical substances' limit in toys, and calculates the probability of risk and the degree of influence by the fuzzy evaluation method. Based on the Bayesian network model, this paper analyzes the causality of risk transmission effects. Through the comprehensive use of fuzzy evaluation and Bayesian network methods, a relatively complete chemical substance risk transmission path assessment system has been established using China's Guangdong toy companies as the data store to provide a feasible basis for responding to the risk control measures of toxic and hazardous chemical substances in toys. [ABSTRACT FROM AUTHOR]

In this paper, we propose a computable method to evaluate the aesthetic value of fusion images of folk martial arts and dance based on human visual and aesthetic habits, extract features and use them as evaluation indexes from three aspects: technical features, perceptual features, and social features, establish an aesthetic evaluation model by fusing each index, and determine the influence factors of each index by using online research. The aesthetic evaluation of fusion images of folk martial arts and dance is carried out automatically. The results of the experimental tests on the evaluation dataset of the aesthetic quality of fusion images of folk martial arts and dance at the Communication University of China show that the accuracy of the proposed deep learning algorithm-based method for analyzing the aesthetic index of fusion of folk martial arts and dance can reach 98.08% with certain validity, and the evaluation results of each index are clear and intuitive, which can play a guiding role in improving the aesthetic quality of fusion of folk martial arts and dance from various angles. It can be used as a guide to improving the aesthetics of the fusion of folk martial arts and dance from various perspectives. By integrating the model into the mobile application, it is possible to evaluate and score the aesthetics of multiple portrait photos uploaded by users and select photos to be kept or deleted based on the scoring results, thus simplifying user operations. [ABSTRACT FROM AUTHOR]

In recent years, more and more attention has been paid to the construction of rural tourism, and tourists' demand for rural tourism public services has become stronger and stronger. Through the objective and fair evaluation of rural tourism public service performance, on the one hand, it is helpful to improve the overall satisfaction of tourists to rural tourism. On the other hand, it can also ensure the efficiency of public service financial investment and expenditure. Firstly, on the basis of theoretical summary and hierarchical analysis, this paper constructs the performance evaluation index system of rural tourism public service from five aspects of infrastructure services, public transport services, public information services, security services, and public environmental services. Then taking China as an example, the performance of rural tourism public service is evaluated by analytic hierarchy process. The results show that the construction of hard environment such as public transport services, security services, and infrastructure services is a key factor in the construction of rural tourism public services. Finally, according to the evaluation results obtained in this paper, some suggestions are put forward for the development of rural tourism and the improvement of public service quality in the future. [ABSTRACT FROM AUTHOR]

This paper makes a comprehensive description of the innovation ecosystem from three perspectives, the concept refinement of the innovation ecosystem, factor symbiosis, and system efficiency, since the traditional definition of innovation ecosystem is not sufficient to fully describe the innovation ecosystem. With grounded theory for reference, the concept of innovation ecosystem is reconstructed, and it is discovered that the conceptual model of innovation ecosystem is composed of main categories and subcategories. The main category is the innovation population and innovation habitat category in the innovation ecosystem, and the subcategory is the input and output activities of the innovation subjects in the innovation ecosystem. The concept refinement of the innovation ecosystem based on the Chinese scenario reflects the characteristics of the innovation ecosystem in a specific context. It has been found that, under the Chinese scenario, there is an asymmetric symbiotic relationship between populations and habitats in the innovation ecosystem. The input-output total factor productivity of the entire innovation ecosystem is in a state of decline, and this decline in total factor productivity is mainly due to the decline in technological change. China's innovation ecosystem is an asymmetric symbiosis system that relies on factor inputs. Due to insufficient technological innovation, the total factor productivity of the innovation ecosystem has declined. [ABSTRACT FROM AUTHOR]

Under the background of the new normal economy, ecotourism maintains a good momentum of development. Therefore, it can be foreseen that industrial integration is an inevitable trend in the development of contemporary industries, and the integration of cultural industries and tourism industries will bring good effects to regional economic development. In order to fully study the impact of ecotourism and its applied technologies on regional economy and culture, this paper proposes research on the application of virtual reality technology in the coordination and interaction of regional economy and culture in the sustainable development of ecotourism. The approach of this paper is to study VR technology in digital tourism and then to evaluate the sustainability of ecotourism and economic culture. The role of these methods is to study the interaction process between the tourism industry, regional economy, and cultural industry. It explores the law of action between the three so as to achieve the purpose of system optimization. Taking Henan Province, China, as an example, this paper discusses the application of virtual reality technology in ecotourism and studies the impact of ecotourism on economy and culture. The experimental results show that the average value of ecotourism-economic-cultural coordination degree in Henan Province is 0.399, and it is urgent to apply virtual reality technology in ecotourism. [ABSTRACT FROM AUTHOR]

In the Internet era, traditional performance management has failed to satisfy the modern enterprise development; therefore, enterprises must achieve timely innovation and improvement of performance management. The application of performance management in state-owned firms promotes employee motivation and skill development, as well as the development of innovative thinking. Performance effect, therefore, on the role of management in the state-owned enterprise development is bigger, especially because of the influence of traditional human resources performance management mode. The further development of state-owned enterprise resource management work affected the operation and management of state-owned enterprises. Therefore, state-owned enterprises must further optimize the path of performance management, to achieve its fine development. In view of this, this paper deeply analyzes the problems existing in the current performance management of state-owned enterprises and puts forward optimization methods for the problems, aiming at providing help for the optimization of the performance management of state-owned enterprises. In essence, a value network is a value symbiosis system between firms that involves resource sharing, value cocreation, risk sharing, and benefit win-win situations. The formation and development of value network not only extremely change the industrial structure and mode of production, but also have an important impact on enterprise innovation mechanism. Enterprise innovation under the value network system has become the focus of academic and business circles. With the rapid development of machine learning and internet of things (IOT) technologies, as well as China's urbanization, China's agriculture is embracing new development opportunities. Using artificial intelligence (AI) technology to effectively mine agricultural big data and realize effective control and management of intelligent agriculture has become a research hotspot and difficulty. Based on recurrent neural network (RNN) and IOT technology, this paper proposes an enterprise network innovation performance management path optimization system. [ABSTRACT FROM AUTHOR]

A significant corridor under the "Belt and Road Initiative" is announced by the government of China for numerous transport and energy projects. China focuses greatly on the sustainability of these projects, in accordance with Green Investment Principles. For this, environmental, social, governance, and technological considerations are taken into account. This paper offers a novel assessment of the impact of green sustainability under BRI and the current emission scenario in Pakistan. The question that needs to be addressed here is whether the projects under Belt and Road Initiative are as environment friendly as they claim. In the first phase of this study, we review theories establishing evidence based on existing literature to determine the influence of Belt and Road on economic development. In the next phase, we use Environment Kuznets Curve and apply estimates from Johansson's Cointegration Test to quantify the present environmental scenario of Pakistan and probable environmental risk portrayed by the China-Pakistan Economic Corridor (CPEC). This paper helps in determining the relationship between carbon emission and three major variables including energy consumption, economic growth, and foreign direct investment (FDI). Cointegration analysis is applied on time series data comprising of a 40 years' period from 1979 to 2019. The paper finds that (i) the belt and road corridors could substantially improve trade, foreign investment, and living conditions for citizens in participating countries; (ii) moreover, this study confirms the presence of one cointegrated equation suggesting the presence of a long term relationship between the CO2 and independent variables and a short run association running from EnC to CO2. The study also proposes a Green BRI Model which formulates a body that devises environmental performance standards, reviews procedures, and ensures that they get implemented on all CPEC projects. The Belt and Road Initiative increases emissions among participating countries. China and corridor economies need to adopt strict policy reforms that increase transparency, expand trade, improve debt sustainability, and mitigate environmental, social, and corruption risks. [ABSTRACT FROM AUTHOR]

To study the adaptation of the current automobile design load of highway bridges in China in case of separation of passenger cars and trucks, a statistical method is proposed in this paper to study the load data of special lanes for trucks. Four typical truck-based lanes were selected as the study object, from which information of continuous truck fleet was selected as the study of truck-specific lane load flow samples, and technical parameters of truck vehicles were determined. Finally, the load flow was introduced into simply supported bridges and continuous bridges of different spans, and the load effect at the control section was calculated and compared with the effect of the design load at the control section according to the current code. The results show that under the operation mode of "passenger car and truck separation," when the truck fleet passes through the simple support beam, the load effect at the control section generally does not exceed the effect of the vehicle load calculated according to the code design load. When the truck fleet passes through the continuous beam, the midspan bending moment of the continuous beam side span and the midspan bending moment of the middle span do not exceed the effect of the vehicle load calculated according to the code design load. However, the bending moment effect of the continuous beam support section exceeds the effect of the vehicle load calculated according to the design load of the code. To ensure the safety and durability of the bridge structure, the proposed lane load standard value is increased by 1.1 times and rounded up from the current Highway Bridge and Culvert Design Code. [ABSTRACT FROM AUTHOR]

The development of underground space is fast because of the lack of space. To build shafts in underwater tunnels, the vertical tunneling method (VTM) was invented in 1974 in China, which can act as a freshwater intake or sewage outlet. During the operation of the VTM, the jacking force is one of the essential factors that draw attention. This paper conducts a numerical study of the jacking force and its influencing factors during the vertical tunneling process. First, based on the finite element software ABAQUS, a numerical model of the vertical tunneling process is established according to the VTM project in Beihai, China. Second, in accordance with the Latin hypercube sampling method and the multivariate significance analysis, the mechanical parameters are determined or back-analyzed. Then, the calculated jacking force of the numerical model is compared with the measured jacking force. It turns out that the changing trend of the jacking force in the numerical model and the measured jacking force is relatively consistent. Finally, the influencing factors of the jacking force, such as elastic modulus and the angle of internal friction, are analyzed based on the numerical model. The results show that the elastic modulus and the angle of internal friction of soil are the main influencing factors of the jacking force. The secondary factors are Poisson's ratio, static earth pressure coefficient, unit weight, and cohesion. [ABSTRACT FROM AUTHOR]

As a large developing country, China's outward foreign direct investment (OFDI) and its relationship to trade have always been subjects of extensive scrutiny in academic circles. With the continuous advancement of the "Belt and Road" initiative (BRI), the pace of overseas expansion by Chinese firms has accelerated. This paper theoretically constructs a firm heterogeneity model of China's OFDI and bilateral trade, and conducts research based on panel data of China's OFDI in countries along the BRI from 2003 to 2019. The results show that China's OFDI can substantially enhance the potential for bilateral trade, and this conclusion remains robust after overcoming endogeneity and economic fluctuations. In a heterogeneity test, China's OFDI in countries along the "Land Silk Road" is shown to have a greater effect on trade potential than in countries along the "Maritime Silk Road." In the controlled test, China's OFDI to BRI countries has a greater role in upgrading trade potential than investment in other trading powerhouses. China's OFDI can promote the economic development of host countries along the BRI by strengthening the potential for bilateral trade. The results of this study are not only conducive to the "going global" of Chinese enterprises but also of practical significance for host countries to achieve high-quality economic development. [ABSTRACT FROM AUTHOR]