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The purpose of this paper is to retrieve and study the highly cited papers as well as the correlation between the citation frequency and the download frequency of the 20 traditional Chinese medicine journals in China, in order to provide the guidance for improving the influence and academic quality of these journals. Bibliometric analyses were conducted on 1103 papers of 20 traditional Chinese medicine journals from 2011 to 2020 by retrieving for the China Academic Journal Network Publishing Database (CAJD) in China National Knowledge Infrastructure (CNKI). SPSS 17.0 software was used to analyze the correlation between the citation frequency and the download frequency via conducting regression fitting and establishing the mathematical models. The results showed that the total citations of the 1103 papers were 93051 times and the average citations were 84.36 times per paper. The total downloads of the 1103 papers were 2058442 times, and the average downloads were 1866.22 times per paper. China Journal of Chinese Materia Medica ranked first according to the number of papers, total citations and total downloads. The citations of Journal of Chinese Medicinal Materials ranked first based on the number of citations per paper. One of Li's paper had been cited the most (983 times). There were 629 (57.03%) papers whose first author was from universities. The scopes of the first authors were distributed in 29 regions and 2 special administrative regions (Macao, Hong Kong) in China. The authors from Beijing published 283 (25.66%) papers, ranking number one. The number of papers supported by funds was 882 (79.96%). The research results of correlation showed that the citation frequency and the download frequency of the highly cited papers had a highly positive correlation from both journal and paper level for whether the sample data of journals was normally distributed or nonnormally distributed. The correlation coefficients of the 20 journals at journal level and that at paper level were 0.9765 and 0.6677, respectively. The correlation was better at journal level than that at paper level, while the optimal regression fitting was all cubic polynomial. Among the 1103 papers, there were 684 (62.01%) research papers and 419 (37.99%) review papers. The main citation period of the top 15 papers was from the 2nd year to the 6th year after publication, accounting for 78.39%. Papers on clinical therapeutics research, papers on the pharmacological effects and its mechanism of traditional Chinese medicine, and papers on traditional Chinese medicine and natural medicine were the main source of the highly cited papers of the traditional Chinese medicine journals. Editors of the journals should focus on the above-mentioned research areas to select manuscripts for exploiting the excellent sources extensively, while paying attention to review papers, focusing on national major or key projects, paying attention to network spreading, stabilizing authors with quality services, in order to improve the influence and the academic quality of journals. [ABSTRACT FROM AUTHOR]

Scholars from Mainland China have published 8541 papers in 79 Operations Research and Management Science (OR/MS) journals available on the ISI Web of Science (WOS). Data from 2001 to 2013 constitute the basis of the bibliometric method used in this paper for statistical analysis of status of OR/MS research in Mainland China, from the perspectives of number of papers, quality of papers, most productive institutions, co-author analysis, citations analysis and research topic analysis, etc. The results show that although the number of OR/MS papers by Mainland China scholars grew exponentially during this period, the quality of papers needs to be further improved. Besides, the competition among the institutions in Mainland China is very fierce. Furthermore, the co-author analysis shows that the depth of cooperation has increased steadily and yet the breadth of cooperation has much room for development. Moreover, from the perspective of citations, only a small number of papers by Mainland China scholars have influenced the international OR/MS field. In addition, analysis of research topics shows that Mainland China scholars have been studying the OR/MS problems from a variety of perspectives. Additionally, we also visualize the relationship of the keywords to describe the status of development of the OR/MS discipline in Mainland China, and conclude that the connection nodes will have greater potential in the future. [ABSTRACT FROM AUTHOR]

In stock trading, a common phenomenon is that the trends of stocks in the same industry are very similar. In contrast, the movements of stocks in different industries are often different. Therefore, applying the same model to all stock trading is inappropriate without distinguishing the industries in which the stocks belong. However, recommending an optimal industry stock trading model is very challenging based on performance evaluation indicators. First, the indicators of the trading model are diverse. Second, the ranking of multiple indicators is often inconsistent. In the paper, we model the problem to be solved as a multi-criteria decision-making process. Therefore, we first divide stock dataset into nine industries according to their main business. Then, we apply several machine learning algorithms as candidate models to generate trading signals. Second, we conduct daily trading backtesting based on the trading signals to obtain multiple performance evaluation indicators. Third, we propose an optimal recommendation algorithm for the industry stock trading model with TODIM. The experimental results in the US stock market and China's A-share market show that the proposed algorithm can get a better trading model out-of-sample industry stock. Moreover, we effectively evaluate the generalization ability of the algorithm based on the proposed metrics. Finally, the proposed long–short portfolios based on the algorithm have achieved returns exceeding the benchmark on most out-of-sample datasets. [ABSTRACT FROM AUTHOR]

Bridge influence lines (BILs) and bridge influence surfaces (BISs) are inherent static parameters of bridges which can be extracted from moving vehicle-induced bridge responses. Compared with dynamic parameters, these parameters are directly related to the stiffness and internal forces in each cross-section of a bridge therefore can be considered as an effective bridge metamodel. To accelerate the engineering practice of BIL- and BIS-based bridge evaluation, this paper first briefly reviews the current BIL and BIS field test and identification methods. Then, the bridge evaluation guidelines of China and the United States are introduced as the basis of the evaluation methods. Engineering application scenarios for bridge evaluation, including permit load verification, performance degradation checking, and load carrying capacity evaluation, are summarized, and a multiple-scenario bridge evaluation method is established. At the end of this paper, an evaluation example of a four-span continuous bridge is presented to illustrate the application procedure and verify the effectiveness of the proposed method. The outcomes of this paper provide a promising application method of field test BILs and BISs, which may help bridge engineers more effectively use these parameters in engineering practice. [ABSTRACT FROM AUTHOR]

Bibliometric rankings are quite common in the field of software engineering. For example, there are a series of ranking repeated every year which identify the top researchers and institutions at the international level in the field. There are also other studies to determine the most cited articles in software engineering journals, the most popular research topics in this area, or identify the top researchers and institutions in regional levels. However, there exists no existing bibliometric quantitative analysis of publications in the area of software engineering (SE), including relative and absolute growth in the number of all SE publications as well as an analysis among countries. This is the main goal and motivation of this article. Besides, this study intends to provide an overall quantitative trend of the software engineering papers, and compare that trend to research output in other areas of science. The bibliometric study reported in this paper is motivated by the fact that understanding the amount of geographical research contributions to the field of software engineering can help identify different countries' level of commitment to support research activities in this area over years. We analyze how the contribution levels of top-ranked countries have changed over the years and how SE compares to other disciplines of engineering and science. Among the most interesting findings of this study are: (1) Over 40 years, in total about 60% of the SE literature has been contributed by only 7% of all countries, (2) the SE research output of different countries does not necessarily correlate with their GDPs, (3) the share of contributions to the SE discipline by the American researchers has declined from 71.43% (in 1980) to 14.90% (in 2008), and (4) China is the country with the biggest share growth in the number of publications (from 0.82% of the entire SE publications in 1991 to 13.82% in 2009). [ABSTRACT FROM AUTHOR]

This study aims to present a multiattribute decision-making (MADM) and clustering method to explore the ranking, classifications and evolution mechanisms of the research fronts in the Web of Science Essential Science Indicators (ESI) database. First, bibliometrics are used to reveal the characteristics of the 57 ESI research fronts with more than 40 ESI highly cited papers (ESI-HCPs) for each research front. Second, the eight representative indicators are discovered to get answers to the following two questions: (i) Who publishes the ESI-HCPs that form a research front? and (ii) Where citations to these ESI-HCPs come from on a research front? Next, we investigate the ranking and clusters among the 57 ESI research fronts using the MADM and k -means clustering method and uncover the evolution process of the research fronts in different clusters based on the representative indicators. We also compare the performances of different countries in these research fronts and find that the USA and China are the leading countries in most research fronts. However, the two countries behave differently with regard to the rankings, the classifications and the evolution. [ABSTRACT FROM AUTHOR]

The prevention and control of communicable diseases such as COVID-19 has been a worldwide problem, especially in terms of mining towards latent spreading paths. Although some communication models have been proposed from the perspective of spreading mechanism, it remains hard to describe spreading mechanism anytime. Because real-world communication scenarios of disease spreading are always dynamic, which cannot be described by time-invariant model parameters, to remedy such gap, this paper explores the utilization of big data analysis into this area, so as to replace mechanism-driven methods with big data-driven methods. In modern society with high digital level, the increasingly growing amount of data in various fields also provide much convenience for this purpose. Therefore, this paper proposes an intelligent knowledge discovery method for critical spreading paths based on epidemic big data. For the major roadmap, a directional acyclic graph of epidemic spread was constructed with each province and city in mainland China as nodes, all features of the same node are dimension-reduced, and a composite score is evaluated for each city per day by processing the features after principal component analysis. Then, the typical machine learning model named XGBoost carries out processing of feature importance ranking to discriminate latent candidate spreading paths. Finally, the shortest path algorithm is used as the basis to find the critical path of epidemic spreading between two nodes. Besides, some simulative experiments are implemented with use of realistic social network data. [ABSTRACT FROM AUTHOR]

After the carbon peaking and carbon neutrality goals were proposed, different institutions and scholars carried out research on China's medium- and long-term mitigation pathways. Through the literature review of China's research on carbon neutrality, this paper finds that the zero-carbon energy transition is the key to achieving carbon neutrality. The main driving factors of reducing energy-related carbon emissions include the cleanliness of primary and secondary energy supply systems, the electrification of energy consumption and the development of hydrogen energy, energy efficiency improvement, carbon capture and storage (CCS), and negative emissions. Furthermore, based on the literature, this paper conducts a quantitative comparative analysis, and selects key indicators for comparative analysis and summary from seven dimensions, including economic and social development, carbon emission pathways, primary energy consumption, final energy consumption, final hydrogen energy consumption, electricity demand and supply, and installed capacity and structure of power generation. Main conclusions are as follows: (i) In terms of carbon emission pathways, the institutions generally believed that China will peak carbon emissions around 2028 and achieve carbon neutrality between 2050 and 2060. Achieving net-zero or near-zero emissions first in the power sector is the key to carbon neutrality across the society; (ii) In terms of energy supply, it is a consensus to increase the proportion of clean energy and reduce carbon emissions from the source. The proportion of clean energy in primary energy will increase to more than 85%, and the proportion of clean energy power generation and installed capacity will reach more than 90%; (iii) In terms of energy use, electricity will become the core of final energy consumption in the future. The predicted electricity consumption across the society will range 14.3–18.4 PWh, and the predicted electrification rate will exceed 65%. [ABSTRACT FROM AUTHOR]

The water eutrophication restricts the development of economy and society in China, which attracts increasing attention. It also affects the health and ecological environment. The evaluation of water eutrophication is very complicated due to the dynamic variability of the water quality data. This paper adopts the hesitant fuzzy set (HFS) to depict the massive data of samples and uncertain preference information of experts, which reduces the complexity of calculation and avoids the loss of information. After that, we construct the projection index function based on the main factors of water eutrophication. The particle swarm optimization (PSO) algorithm is applied to determine the global optimal projection direction by optimizing the projection index function. Therefore, we construct an improved projection pursuit regression (PPR) model. Finally, the water eutrophication evaluation of several lakes in China is used to demonstrate the improved PPR model. Also, the comparative analysis and contribution rate analysis are conducted to validate its rationality and advantages. [ABSTRACT FROM AUTHOR]

Steel and composite walls with corrugated steel plates have found their wide application in China due to their excellent structural performance. Extensive research has been conducted over the past few decades to investigate their behavior and load-bearing capacity. This paper summarized numerous experimental and numerical studies on the corrugated steel plate shear walls (CSPSWs), double corrugated steel plate shear walls (DCSPSWs), and concrete-infilled double steel corrugated-plate walls (CDSCWs). First, the load-bearing mechanism and design methods of CSPSWs and DCSPSWs under monotonic and horizontal cyclic loads were elucidated. Subsequently, this paper elaborates the load-bearing capacity and corresponding design methods including the sectional strength capacity, the overall stability, and the wall panel stability of CDSCWs under axial compression, compressive-bending combination, and compressive-bending-shear combination. The proposed design methods of CSPSWs, DCSPSWs, and CDSCWs have successfully implemented in practical high-rise building structures and some of them have been adopted by the Chinese engineering construction standards T/CECS 290 and T/CECS 624. [ABSTRACT FROM AUTHOR]

Based on China's green energy development strategy, this paper constructs a basic model of recycling and a channel expansion model for the circular economy foundation of Zaozhuang, Shandong Province, China. Through numerical simulation, it is found that each member of the supply chain should control the rate of price adjustment, otherwise it will cause market disruption. The model is controlled based on a chaos control method. Then, based on the fuzzy comprehensive evaluation method, an early warning system for the circular economy of Zaozhuang City is constructed. It is found that the economic development of Zaozhuang is a serious warning, resources are moderate warning, and the environment is not in an alarm state. In addition to paying attention to energy conservation and emission reduction of enterprises, the government should pay attention to creating awareness of energy conservation and emission reduction in society, and strengthen the technological investment in reducing pollutant emissions. This paper provides a strategic reference for the circular economy model in Zaozhuang, Shandong, China. [ABSTRACT FROM AUTHOR]

To effectively promote the efficient dissemination of sci-tech journals and improve the influence of sci-tech journals, a precise push method of sci-tech journals based on knowledge graph reasoning is proposed, using knowledge graph to build network to realize push reasoning of scientific and Technological Journals. Based on the one-way author relationship network diagram and the two-way keyword network diagram, the PageRank algorithm is used to calculate the weight of network vertices, quantitatively and accurately identify the research direction of push customers and predict customers, and realize the accurate push management of content, so as to obtain the basis for the construction of network diagram. Based on the previous article in the Journal of the information society of science and technology of China, this paper constructs a knowledge reasoning diagram, mines 52 co-author cases and 60 related papers as experimental data, and verifies the progressiveness method through customer value. According to the network diagram, the progressiveness of this method is verified. The experimental results show that the knowledge map network reasoning method proposed in this paper has high accuracy in identifying the push objects of scientific and technological journals and accurately predicting the research direction. The matching degree between the number of customers and the pushed content. Using knowledge map network can ensure the timeliness and accuracy of pushing scientific and technological journals. [ABSTRACT FROM AUTHOR]

This paper aims to determine the dynamic influence of provincial tourism development on carbon emissions and ecological efficiency in China. For this purpose, the paper first develops a new index to evaluate the ecological efficiency and then utilises the SYS-GMM method by using the provincial data during 2004–2017. Besides, we explore the heterogeneous, asymmetric, and mediating impact effect in the tourism–carbon–ecological efficiency nexus. The following findings are highlighted: (1) An inverted U-shaped nexus exists between tourism development and carbon emissions, which confirms the existence of the tourism–environment Kuznets curve; (2) tourism development can promote ecological efficiency, and this positive impact of tourism on the economy is enhanced by the tourism infrastructure; (3) the impact of tourism development on carbon emissions is heterogeneous and asymmetric, while its influence on ecological efficiency is consistent; and (4) investment effect is the significant mediator. This paper puts forward several policy suggestions based on the conclusion. [ABSTRACT FROM AUTHOR]

This paper constructs an artificial stock market, especially the description of Chinese stocks to form a benchmark model of this paper. Then, we examine the relationships between price limit changes and market quality in the Chinese stock market. We set up five boards in the model and adopt the current price limits of the A-share market. In terms of experimental design, this paper adjusts the price limit to explore the path of the reform of the price limit. We also cancel the price limit to explore the necessity of price limits in China's A-share market. After simulations, the experimental results of this paper show that relaxing the price limit will improve market quality. When we adjust the price limit from 10% to 20%, market volatility increases slightly, market liquidity increases and market pricing efficiency improves. When we cancel the price limit, market volatility increases significantly, market liquidity increases and market pricing efficiency decreases significantly. Our study shows that it is necessary to implement the price limit policy in the Chinese market, and a moderate relaxation of the price range will improve the quality of the market. [ABSTRACT FROM AUTHOR]

Now, China has made it clear that it will strive to have CO2 emissions peak before 2030 and achieve carbon neutrality before 2060 (the "dual carbon" goals), based on the logic that carbon peaking is a prerequisite for carbon neutrality. The year 2021 is the first year of China's 14th Five-Year Plan period. As the main battlefields to achieve the "dual carbon" goals, cities are also required to build on their pathways towards such goals under new conditions. Based on the progress China has made with pilot cities for low-carbon development and the discussion on 60 cities by category, this paper identifies the commonalities and differences between Chinese cities' pathways towards carbon peaking, and concludes that Chinese cities need to peak their carbon emissions in an organized and step-wise way on the basis of classification and according to their own development level and emission characteristics. In light of the above conclusion, this paper provides feasible suggestions for Chinese cities' carbon peaking. [ABSTRACT FROM AUTHOR]

China's railway network is wide, and some of them cross the seismic zone, and the ratio of high-speed railway (HSR) bridges is high. Therefore, the safety of trains on the bridge may be endangered in the event of an earthquake. Because the response of track–bridge system is sensitive to the randomness of bridge structural parameters during the earthquake, while the train wheelset is directly in contact with the track system, the running safety of train (RST) may be also sensitive to the randomness of structural parameters. In this paper, the model of train–bridge coupled system (TBCS) under earthquake was established, and the accuracy of the model was verified by test results. To efficiently calculate the safety performance of trains considering the randomness of structural parameters, the point estimation method (PEM) was used in this paper, and the applicability of PEM was proved by comparing with the calculation results of Monte Carlo simulation (MCS). Then, PEM was used to discuss the running safety performance of trains under different ground motion (GM) intensities, different train speeds, and different pier heights. Finally, based on the maximum probability, the GM intensity threshold of a bridge based on running safety is determined. [ABSTRACT FROM AUTHOR]

Earthquake hazards may cause a significant loss to urban hospital network system (UHNS), including hospitals and medical transportation networks. As such, systematic seismic resilience assessment of such systems is of paramount importance to reduce loss and optimize casualty care during earthquakes. For that purpose, this paper proposes a novel method for assessing the seismic resilience of UHNS that considers the logical dependencies or coupling among the system's components, such as the casualty sources, the hospitals and the medical transportation networks. A resilience index is defined as the ratio between the average "shortest" time for a casualty to receive medical treatment before and after an earthquake. The time consists of both transportation time to a hospital and queuing time at the hospital. To obtain the shortest time, a real-time simulation model is proposed that considers the casualty sources, the changes in road traffic, the updates of Origin-Destination (OD) matrix for transportation time, the modifications of waiting time in hospital, the path reselection by casualty, and the changes in functionalities of bridges, hospitals and roads. The functionalities are obtained by analyzing fragility models, calculating residual functionality and estimating functionality recovery times. To calculate the fragilities of bridges and hospitals, a refined nonlinear finite element (FE) analysis is performed based on a general FE software, OpenSees, and the damages are obtained for various structural and nonstructural components, e.g. column, stairs and CT scanner of hospitals, as well as piers, bearings and abutments of bridges. The proposed method is demonstrated in a seismic resilience assessment of a realistic UHNS in Xiamen city of China and provides valuable references to assessments of seismic resilience of UHNS. [ABSTRACT FROM AUTHOR]

The energy content of ground motion records obtained during the 2019 M6.4, M7.1 Ridgecrest, California earthquakes which occurred closely in space is analyzed in this paper. Wavelet transform as a powerful tool, that is used to evaluate the energy content characteristics including cumulative energy profiles and the total energy for different components of records, was obtained at three stations named China Lake Christmas Canyon, China Lake and Tower 2. Due to the fact that the energy-based parameters could be well correlated with damage distribution, this path has been taken into consideration in this research work with the light of the powerful wavelet tool. For this purpose, the discrete wavelet transform is efficiently used for multi-resolution decomposition of acceleration time history of ground motions and a new framework is presented to estimate the energy level of earthquake sequences. Finally, the pseudo-period corresponding to each corresponding level is introduced and the distribution of energy vs. the pseudo-period is discussed. The results of this paper provide a platform to compare the energy levels of different earthquake sequences in different periods. Analysis showed that wide-band energy distribution could be identified at China Lake Christmas Canyon and Tower 2 stations. [ABSTRACT FROM AUTHOR]

As we enter the digital era, the digital economy provides an opportunity for China's manufacturing industry to achieve 'smart manufacturing' and provides important support for China to move from a 'big manufacturing country' to a 'strong manufacturing country'. This paper constructs an indicator system for the level of digital economy development in Chinese cities by determining the connotation of China's digital economy based on the characteristics of its digital economy development. Based on the application of entropy value method to measure the level of digital economy development of cities, we empirically investigate the impact of the level of digital economy development of cities on the innovation efficiency of manufacturing industry using mixed panel data of listed Chinese A-share manufacturing companies and cities from 2011 to 2019. The empirical study finds that the level of urban digital economy development is conducive to improving the overall innovation efficiency, innovation quality efficiency and innovation quantity efficiency of enterprises, and overall, the digital economy has a significant contribution to the innovation efficiency of manufacturing industry. There is regional, firm size and industry heterogeneity in the impact of urban digital economy development level on manufacturing innovation efficiency, and this heterogeneity is further manifested in the types of manufacturing innovation efficiency. For example, the urban digital economy enhances the innovation efficiency of small-scale firms mainly through the quantity of innovation rather than the quality of innovation. [ABSTRACT FROM AUTHOR]

Hydrogen energy has an advantage over conventional fossil energy because of its clean and low-carbon features, while its stability gives it an advantage over renewable energy sources such as hydropower, photovoltaic (PV) power, and wind power. Using hydrogen as a fuel can achieve zero carbon emissions or even net zero emissions at the end of energy conversion. Moreover, with hydrogen as the carrier, an energy system of multi-energy complementarity will be established by coupling multiple energy systems such as power grids, gas grids and heat networks, which can realize the comprehensive utilization of renewable energy sources in an efficient, stable, and flexible manner. Based on the "dual carbon" goals, this paper targets sectors with high carbon emissions represented by electric power, steel and transportation, analyzes the feasible path of using hydrogen energy to promote deep carbon reduction, and points out the obstacles faced by hydrogen energy development in various sectors. On account of the current development and expected prospects, this paper proposes that the current focus of hydrogen energy industry is to coordinate the development of industrial sectors and regions, build a pattern that can facilitate the industry's systematic and concerted development, address key technical challenges (such as green hydrogen production or hydrogen storage and transportation via pipeline), improve industrial standards, and promote the industry's development in a balanced, coordinated and orderly way. [ABSTRACT FROM AUTHOR]

China's automotive industry has been dedicated to a series of carbon-reduction efforts and has strived for comprehensive green and low-carbon transformation in order to achieve carbon peaking and carbon neutrality goals. On the basis of automobiles' whole life-cycle (WLC) carbon emission accounting, this paper calculates life-cycle carbon emissions per vehicle, proposes green and low-carbon development path for China's automotive industry, quantifies and analyzes implicated carbon-reduction potential, and puts forth suggestions for high-quality green and low-carbon development of China's automotive industry. The first is to establish a sound standard and data management system; the second is to promote research, development and application of low-carbon materials and low-carbon technologies; the third is to accelerate the pace of fostering a new consumption model in the automotive industry. The research results can further support national policy-making regarding carbon emissions, promote corporations' research, development and application of low-carbon technologies, encourage green and low-carbon consumption, and lead the automotive industry to achieve WLC neutrality. [ABSTRACT FROM AUTHOR]

With the improvement of our country's economic level and quality of life, the numbers and scales of highway networks and motor vehicles are constantly expanding, which makes the current road traffic burden more and more serious. As an important means of traffic automation management, license plate recognition (LPR) technology plays an important role in traffic surveillance and control. However, the recognition rate and accuracy of the traditional license plate recognition methods still need to be improved. In the case of poor surrounding environment, it is prone to localization failure, vehicle license plate recognition errors or unrecognizable phenomena. Wavelet transform, as another landmark signal processing method after Fourier transform, has been widely used in the field of image processing. In China, the number of horizontal lines is usually larger than that of vertical lines. If the two vertical boundaries of the license plate can be detected successfully, the four angles of the license plate can be determined efficiently to complete the license plate positioning. In view of the advantages of wavelet transform technology and the characteristics of vehicle license plate, in this paper, a vehicle license plate recognition algorithm based on wavelet transform and vertical edge matching is proposed. The edge of the license plate is detected by wavelet transform technology, and then the license plate is located by vertical edge matching technology. After the location is realized, the characters are segmented by vertical projection method and the characters are recognized by improved BP neural network algorithm. The experimental results show that the proposed vehicle license plate recognition algorithm based on wavelet transform and vertical edge matching performs well in algorithm performance, which provides a good reference for the development of vehicle license plate recognition system. [ABSTRACT FROM AUTHOR]

Based on the data of the Growth Enterprise Market (GEM)-listed companies in the Shenzhen Stock Exchange of China, this paper researched the influence mechanism of political connections on enterprise innovation intention. This paper is based on the theory of reciprocal exchange of social capital. The research found that the entrepreneur's political connections are detrimental to the improvement of enterprise innovation intention, and the differentiation strategy has a mediation effect between them. Moreover, the market competition intensity of enterprise production adjusts the influence of the differentiation strategy on enterprise innovation intention, and it can alleviate the negative influence of the political connection on the innovation intention through the differentiation strategy. Although the country's innovation-driven strategy will provide more innovative resources for enterprises, securing the survival and development of an enterprise is becoming increasingly narrower by relying solely on establishing connections with the government. [ABSTRACT FROM AUTHOR]

Distributed Virtual Reality (DVR) is a combination of network and virtual reality technology, it could facilitate to construct a uniformly shared Distributed Virtual Environment (DVE) by using network to connect geographically distributed multiplayers. This paper concentrates on the theoretical research and practical development about Multiplayer Virtual Intelligent System (MVIS), and the main contribution could be summarized as two points. (1) Based on the DVR technology, this paper presented some theoretical research on MVIS, including the classification of virtual entities, communication pattern of entities, and the behavioral consistency research. Furthermore, a Multiplayer Earliest Deadline First (MEDF) program was proposed in order to guarantee the consistency of entities. (2) A prototype algorithm experiment system, called Multiplayer Graph-algorithm Intelligent System (MGIS), was designed. MGIS not onlyefficiently solves many problems in traditional computer algorithm teaching, such as high-abstraction, difficulty to understand, and lack of interaction mechanism; but also extends the application of DVR to cultural tourism, because MGIS is developed on the 3D scene of Lushan Mountain, which is one of the notable tourist attractions in China, and was included in the UNESCO World Heritage list in 1996. What i's more, MGIS illustrates the ability of expression, applicability and generality of the theoretical research about MVIS. [ABSTRACT FROM AUTHOR]

Crowdsourcing recommendation is necessary to surmount information overload and assist workers to identify tasks of interest efficiently. However, existing studies mainly concentrate on investigating workers' qualifications or requirements, neglecting their fuzzy expectations and psychological behavior. Besides, workers can only passively accept the results and do not have any right to change them even if they are not satisfactory. As workers will pay different attention to task aspects, we regard the crowdsourcing recommendation as a multi-criteria decision-making (MCDM) problem. In this paper, we propose an MCDM-based method for automated and interactive crowdsourcing task recommendations while comprehensively considering workers' fuzzy expectations and psychological behavior. Given a large volume of available tasks on a crowdsourcing platform, the requirement of massive human efforts in traditional MCDM is not applicable in such situation. Therefore, we formulate a set of quantitative task evaluation criteria for automated task assessments based on the attributes that have the most impact on workers' participation behavior. Further, to capture workers' fuzziness in expectations, an intuitionistic fuzzy 2-tuple linguistic (IF2L) term is introduced, which are further leveraged as reference points to evaluate their "gains" and "losses" based on the prospect theory. Finally, the D-S evidence theory is adopted to gather workers' uncertain prospect values. A case of ZBJ.COM, a popular crowdsourcing platform in China, shows that the proposed method is efficient and effective in recommending suitable and personalized tasks to workers. [ABSTRACT FROM AUTHOR]

Steel sheeting is usually provided at the upper flange of purlin in steel roof with screw connections. The resulting diaphragm effect provided by the sheeting enhances the buckling resistance of the purlin. However, this diaphragm effect will be reduced due to any abnormality in the screw connection caused by wind-induced fatigue particularly from typhoon. This would reduce the buckling resistance of the purlin with sheeting (the purlin-sheeting system), and it would affect subsequent condition evaluation during their service life. This problem is addressed in this paper with a framework of time-dependent reliability evaluation of the buckling limit state of the purlin-sheeting system. The buckling resistance reduction due to the degradation of the diaphragm effect from typhoon is taken into account in the resistance model. The randomness of wind intensity and landfall occurrence of typhoon during the service life of purlin are also accounted for in the wind load effect model. The time-dependent reliability of the purlin at different positions of a roof is studied. Then the variation of reliability of the system due to the effect of climatic changes in the design service life is discussed. The proposed strategy is then applied to the evaluation of a purlin-sheeting system in eleven cities in China with typhoon occurrences with some useful results for future studies in the provisions of the design code. [ABSTRACT FROM AUTHOR]

With the ongoing development and deployment of medium-low speed maglev vehicles in China, it has become common to increase operational speeds from 100 km/h up to 140 km/h or even 160 km/h, necessitating further studies and simulation models to understand the implications of these changes. This paper analyzes medium-speed maglev vehicle-track-girder coupling dynamic performance at a speed of 160 km/h. First, a field dynamics experiment is carried out on the Changsha Maglev Express with a running speed of 80–140 km/h. Then we introduce the distributed coupling simulation platform for maglev transportation system (MTS-DCSP) and the vehicle-track-girder coupling model, taking into account the complex vehicle structure, the guideway structure, and the Proportion Integral Differential (PID) levitation control system. Together, this platform and model can conduct a simulation of the complete process at scale and at all degrees of freedom to obtain accurate results. Our analysis of the results gives an accurate portrayal of the coupling dynamics properties and validates the coupling model. The results from the field experiments together with the coupling simulation demonstrate that the medium-speed maglev train can operate safely and stably within the range of 140–160 km/h. While at 140 km/h, however, the Sperling ride quality index (RQI) is about 2.5, which is within the Excellent grade range, at a speed of 160 km/h, the Sperling ride quality index can increase to as high as 2.74, which is a grade of Good. Therefore, it is necessary to optimize the parameters of the secondary suspension system to improve the ride comfort of the maglev vehicle at 160 km/h. [ABSTRACT FROM AUTHOR]

Power and influence are important concepts in world politics. In this process, every country tries to maximize its interests and influence over other countries. The present world order, soft power, plays an important role in influencing others' policy-making processes in one's favor to establish a world order. This paper aims to give an overview of Chinese soft power and find out whether Chinese soft power is creating a debt trap or becoming a shared interest for both Bangladesh and China. Based on secondary sources, the paper has found that although Chinese soft power, especially its growing investment in Bangladesh, is a part of establishing its influence, it is a shared interest rather than a debt trap. Different infrastructure development projects are opportunities for Bangladesh, as that will open the door to economic development if Bangladesh can effectively utilize them, although China's investment can put Bangladesh's economy under pressure. However, economic and political instability, fragile institutions, growing corruption, leadership crisis, etc. are more harmful to its economy and can lead to an economic crisis. [ABSTRACT FROM AUTHOR]

Although recognised as useful, ambidextrous innovation also presents unique managerial challenges particularly when exploration and exploitation are pursued simultaneously. The paper aims to explore the forming mechanisms of firm's ambidextrous innovation capabilities using the main approaches in strategic management. The authors theoretically examine the direct effects of the digital economy (DE) on ambidextrous innovation capabilities and the mediating effect of knowledge acquisition (KA) and use the stepwise regression method to conduct an empirical analysis of 178 high-tech companies listed in China's A-share market from 2013 to 2019. The empirical results show that DE has significantly promoted the ambidextrous innovation capabilities of firms, and also has a significant positive impact on the balance effect between exploratory innovation and exploitative innovation; DE has a significant positive impact on both external knowledge acquisition (EKA) and internal knowledge creation; KA has a significantly positive effect on exploratory innovation, exploitative innovation and their balance effect, and the effect of KA on exploratory innovation is greater than that on exploitative innovation. Furthermore, KA plays a significantly mediating role in the relationship between DE and exploratory innovation/exploitative innovation. The findings of our study provide insights for knowledge management research and have important guiding significance for promoting ambidextrous innovation capabilities of firms in DE. [ABSTRACT FROM AUTHOR]

The article presents information on editorial board meeting of International Journal of Structural, Stability and Dynamics (IJSSD) in Majestic Harbor Plaza Hong Kong Hotel on 17 December 2009 in Hong Kong, China. Topics include the enhancement of impact factor and best paper award. The symposium featured several editorial board members of IJSSD including S. L. Chan, X. L. Zhao and D. A. Nethercot.

With the impact of foreign exchange markets, risks in financial markets are becoming more complex and diversified, which underlines the importance of risk management in financial supervision. In this paper, China's non-ferrous metal futures market is selected as the research object, and Shanghai Futures Exchange's Industrial Metal Commodity Index (IMCI) data are used to measure risk using the conditional autoregressive value at risk (CAViaR) model. The US dollar index (USDX) is incorporated into the CAViaR model to study its impact on the risk. Through empirical analysis, we arrive at the following conclusions: First, the asymmetric slope CAViaR model (AS-CAViaR) is more suitable for measuring the risk in China's non-ferrous metal futures market. Second, the risk is positively impacted by the lagged risk. Moreover, the impacts of positive and negative returns on the risk are asymmetric, with a negative return having a greater impact. Third, the positive and negative shock of USDX has significant and different impacts on the risk. These impacts can be caused by global capital flows. In addition, the impact of the vector of explanatory variables on the IMCI at different quantile levels is discussed based on the CAViaR-USDX model, which reflects the comprehensive advantages of the quantile regression method and the model's applicability. The above conclusions verify the impact of USDX on China's non-ferrous metal futures market and provide a theoretical basis and direction for risk monitoring. [ABSTRACT FROM AUTHOR]

In seismically active regions, high-filled embankment slopes on liquefiable soils tend to damage after strong earthquakes. Therefore, post-seismic damages should be estimated as soon as possible to mitigate potential losses. Fragility function is an efficient tool for assessing the seismic vulnerability conditions of structures, which links the probability of exceeding different limit states to seismic intensity. An embankment slope on liquefiable soils at Yading Airport in China was selected as the study object, and a series of numerical analyses of the embankment-foundation system utilizing the finite element method were conducted. Advanced dynamic constitutive models considering liquefaction and hysteresis characteristics were also adopted to simulate the nonlinear stress–strain behavior of soils under cyclic loadings. The post-seismic stability of embankment slopes was assessed using the strength reduction method (SRM) based on the stress–strain analysis. On this basis, the permanent ground deformation (PGD) at the ground-free field conditions was selected as the intensity measure (IM), while the factor of safety (FoS) of the slopes was selected as the damage measure (DM). Then, a procedure was presented for deriving seismic fragility functions with different damage states in light of incremental dynamic analysis (IDA). This paper aims to investigate the effects of different embankment typologies, such as the thickness of liquefiable soils and slope inclination, on the post-seismic vulnerability of embankment slopes. The fragility curves constructed in this study may soon be helpful for predicting the post-seismic damage of similar high-filled embankment slopes on liquefiable soils, which enables efficient traffic control and rapid disaster response. [ABSTRACT FROM AUTHOR]

This paper is based on a qualitative study of the influence of the British Colonial government on the construction and development of British India from perspectives of Chinese scholars. It is based on the survey of the papers with the keywords "British India" or "Colonial India" from 2000 to 2020 in China National Knowledge Infrastructure (CNKI), the most authoritative retrieval platform in China. After the analysis and summary of the research on British India by Chinese scholars, this paper suggests a possible research field for Chinese scholars. The study of British India in Chinese academics can go further with the findings of new historical materials. In the future, a breakthrough in this field will be possible with an emphasized study on relevant historical materials and native language. [ABSTRACT FROM AUTHOR]

This paper explores the direct and indirect relationship between climate policy uncertainty and excessive corporate debt, and focuses on the moderating effect of financing constraints. We use the climate policy uncertainty index to represent climate policy uncertainty, and use the Kaplan and Zingales (KZ) index to represent financing constraints. Our study employs data from Chinese non-financial listed companies for the period 2007–2020. The results show that climate policy uncertainty not only directly curbs excessive debt, but also indirectly reduces excessive debt by increasing financing constraints. This direct weakening effect is more pronounced in non-state-owned enterprises, high-tech enterprises, and high-carbon enterprises. Moreover, the financing constraints channel is more effective in state-owned enterprises, high-tech enterprises, and high-carbon enterprises. Furthermore, due to the actual situation in China, the direct weakening effect of climate policy uncertainty is very obvious in the central region, while the indirect effect through the financing constraints channel is most obvious in the western region. These empirical findings will help policymakers, managers, and financial institutions to reconsider financing risk under climate policy uncertainty. [ABSTRACT FROM AUTHOR]

By adopting the consumption-based accounting (CBA) method of carbon emissions based on national carbon intensity (NCI), using the International Trade Centre (ITC) database, the Emissions Database for Global Atmospheric Research (EDGAR), and the World Bank database, and taking 13 countries and regions including the European Union (EU) countries and the United States (US) as research samples, this paper conducts an accounting of the embodied carbon in trade between China and other major economies in the world, clarifies the responsibilities China has taken for foreign consumption-based carbon emissions, and analyzes the various driving factors of China's embodied carbon in exports. The findings are as follows: (i) Most of the developed economies have higher consumption-based emissions than production-based emissions, which is contrary to most of the developing economies, with developing countries bearing responsibilities for 15–20% of the consumption-based carbon emissions for developed countries; (ii) the carbon emissions of countries and regions are closely related to the embodied carbon in trade, with a correlation coefficient of 0.96. (iii) China has taken responsibility for a large amount of carbon emissions from foreign consumer demand, most of which are from the US, the EU, ASEAN, and Japan, respectively accounting for 3.8%, 3.5%, 2.3%, and 1.2% of China's production-based carbon emissions in 2019; (iv) technique effect is the main driving factor for China's embodied carbon in trade, while the specific driving factors vary by industry. Based on the above analysis, it is suggested that China should: (i) consider the trade factor in its efforts to achieve carbon peaking and carbon neutrality; (ii) adopt differentiated measures to reduce trade-related emissions for specific industries; (iii) fully consider China's demand for carbon peaking and carbon neutrality in international negotiations; (iv) give more support to the research on and measurement of consumption-based carbon emissions. [ABSTRACT FROM AUTHOR]

This paper summarizes the new progress in building China's national carbon market since 2020, and analyzes the connotation of China's carbon peaking and carbon neutrality goals ("dual carbon" goals) and its significance to socio-economic development in China. Through case analysis, this paper expounds the role of China's recent carbon trading activities in promoting the transition toward green and low-carbon socio-economic development. On that basis, this paper conceives a top-level design for building the national carbon market that serves the "dual carbon" goals: building and improving the national carbon market that fundamentally serves as an emission reduction tool, developing the institutions and systems of the national carbon market with a focus on emission cap, creating a multilevel and diversified carbon trading scheme centered on the national carbon market, exploring a mechanism that takes carbon emission reduction as the core and promotes the synergistic effect of the carbon market with other environmental rights trading markets, and pursuing the healthy and orderly development of carbon finance that aims to serve carbon emission reduction. [ABSTRACT FROM AUTHOR]

Intelligent forecasting of economic indexes has been an important demand for sustainable management of smart cities. Existing methods for this purpose were mostly established upon the basis of economic mechanism. Econometric models are the most general technical means in this area. However, in era of digital economy, increasing amount of big data has brought great change to traditional production. It is becoming more difficult for conventional technological forecasting methods to deal with multi-dimensional economic indexes. To deal with such challenge, this paper introduces the artificial intelligence algorithms to implement automatic information processing, and proposes a deep neural network-based intelligent forecasting method for multi-dimensional economic indexes in smart cities. Specifically, a deep neural network with three-layer structure is developed as the backbone methodology. For empirical analysis, the real-world data from "Chengdu–Chongqing Economic Circle" in China from 2012 to 2022 are selected as the main simulation scenario. Four major indexes are selected as the main research object: gross product (GDP), per capita GDP, GDP growth rate and the proportion of tertiary industry in GDP. The experimental results show that the proposal can well deal with such forecasting problem from a data-driven perspective, with a proper forecasting effect on historical data. [ABSTRACT FROM AUTHOR]

The new generation of China Railway Track System III (CRTS III) ballastless track structure has been found vulnerable under high-level earthquakes. However, the seismic characteristics and the damage mechanism had not been well studied. In this paper, a 4-span high-speed railway (HSR) simply supported bridge-track system model is established to investigate the seismic response and damage mechanism of the bridge-CRTS III slab ballastless track system under transverse earthquakes by nonlinear history analysis. In accordance with the results, the piers have a good seismic performance under high-level earthquake (0.57 g). The non-uniform vibration of unequal-height piers results millimeter-level inconsistent displacements between the girders. The fixed bearing is vulnerable under the earthquakes with PGA of 0.3 g and 0.57 g, indicating that the seismic design of fixed bearing should be optimized to enhance the seismic resistance under high-intensity earthquake. After the damage of fixed bearing, the friction is not enough to pull the girders to vibrate together with piers which leads the sliding of girders. The sliding of girder exacerbates the non-uniform displacements of girders and roadbed. The non-uniform vibration and residual slips of girders lead deformation of the rail, especially forming turning angles at the girder joints which may impact the safety of train operation. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the capabilities of the inexpensive theodolite created by the authors, compared with modern commercial instruments, equipped with a Leica TPS1203 robotic total station with built-in GoPro Hero6 camera image sensors. This theodolite was tested in the laboratory where simulated dynamic displacements were determined. The results of the experimental tests showed that the displacement errors and differences between the simulated displacements of the test machine and those detected by the theodolite were in the range of Δ = − 0. 1 5 mm to +0.13 mm depending on the simulated amplitude. The theodolite was further used in the field for static and dynamic tests of the Wanzhou Railway Bridge, China. Determination of the dynamic motions of the bridge and the results of calculating the natural frequencies from the measurement data are presented. During loading tests of the bridge, the frequencies were also determined by accelerometers and these data were used as a reference to assess the accuracy of the theodolite and its suitability for dynamic tests. An original algorithm was developed in the MATLAB software environment to process the recorded videos, i.e. image processing to determine displacements and natural frequencies. It is demonstrated that the position of the theodolite at a distance of 28.5 m from the bridge provides the correspondence of one pixel of 0.333 mm, which provides a high level of accuracy when determining the dynamic vertical displacements of a moving target. It is established that the proposed theodolite will cost less than 5 000 euros. The results obtained are relevant for use in civil engineering for monitoring the amplitude vibrations of structures. [ABSTRACT FROM AUTHOR]

This paper discusses the understanding of traditional Chinese medicine, Uyghur medicine, Tibetan medicine and Mongolian medicine on bronchial asthma, and discusses the causes and pathogenesis, syndrome differentiation, treatment principles and treatment drugs, respectively. It compares the similarities and differences of different ethnic groups' traditional medicines on bronchial asthma treatment, so as to help each ethnic group learn from each other and further improve their understanding of asthma. [ABSTRACT FROM AUTHOR]

After Anwar Ibrahim assumed office in November 2022, Malaysia's China policy, including its stance towards the Belt and Road Initiative (BRI), was again thrust into the limelight. This paper analyses Malaysia's responses towards BRI since 2013 and argues that the "shift" is not to abandon its cooperation or adjust its overall foreign policy with China, but to cater for two sets of domestic considerations – the need for development and inter-elite competition, and eventual regime legitimation. [ABSTRACT FROM AUTHOR]

As the climate change risks' effects on social development increase, how to deal with these challenges has become extremely urgent, and it is necessary for companies to adapt to the changing circumstances. This paper estimates the impact of climate policy uncertainty on corporate innovation using unbalanced panel data with 2,449 listed companies from 2009 to 2020. The findings show a significant positive correlation between climate policy uncertainty and corporate innovation investment. Specially, two possible mechanisms are explored. Government environmental regulations force companies to produce cleanly. Optimistic market expectations encourage firms to shift to a green development model. Further, the renewable energy industry and state-owned enterprises' powers of innovation are more robust. Jointly, our findings offer the government a clear direction for policy making by identifying the effects of climate policy uncertainty on corporate innovation. [ABSTRACT FROM AUTHOR]

For China Railway Track System (CRTS) I twin-block slab tracks, the interface between the sleeper and track slab is susceptible to damage under the coupled effect of long-term train load and external environment factors. In order to analyze the damage behavior and identify the type of debonding at the interface, this paper established a three-dimensional finite element model and introduced the cohesion zone model and concrete damaged plasticity model to simulate the interface damage and the inner-layer damage of the track slab, respectively. The interface debonding induced by the temperature effect was analyzed, and the debonding types were identified based on the obtained vertical vibration responses of the sleeper surface under the train load. The results reveal that the damage mainly occurs on the bottom and lateral sides at the interface under the temperature load. The track model can be refined further to obtain higher analysis accuracy with acceptable calculation time using the sequential loading method. The 26 damage features derived from the time domain, frequency domain, and time–frequency domain are in good representativeness in reflecting the damage information hidden in the vibration signals. Among them, the peak values (maximum vertical acceleration of the sleeper) are 55.0, 56.7, 60.3, and 61.6 m/s2 for no debonding, debonding on the lateral side, debonding at the bottom, and debonding on the longitudinal side of the interface under train load, respectively. Moreover, the identification accuracy of the debonding type can reach 93.75% combining the particle swarm algorithm and support vector machine. It indicates that the proposed identification method is effective and reliable to provide theoretical guidance for developing scientific maintenance and repair strategies for twin-block slab tracks. [ABSTRACT FROM AUTHOR]

Currently, the entire world is fighting against the Corona Virus (COVID-19). As of now, more than thirty lacs of people all over the world were died due to the COVID-19 till April 2021. A recent study conducted by China suggests that Chest CT and X-ray images can be used as a preliminary test for COVID detection. This paper propose a transfer learning-based mathematical COVID detection model, which integrates a pre-trained model with the Random Forest Tree (RFT) classifier. As the available COVID dataset is noisy and imbalanced so Principal Component Analysis (PCA) and Generative Adversarial Networks (GANs) is used to extract most prominent features and balance the dataset respectively. The Bayesian Cross-Entropy Loss function is used to penalize the false detection differently according to the class sensitivity (i.e., COVID patient should not be classified as Normal or Pneumonia class). Due to the small dataset, a pre-trained model like VGGNet-19, ResNet50 and Inception_ResNet_V2 were chosen to extract features and then trained them over the RFT for the classification task. The experiment results showed that ResNet50 gives the maximum accuracy of 99.51%, 98.21%, and 97.2% for training, validation, and testing phases, respectively, and none of the COVID Chest X-ray images were classified as Normal or Pneumonia classes. [ABSTRACT FROM AUTHOR]

The variation principle widely used in structural dynamics analysis allows us to transform the differential equation of the boundary value problem into a functional with extreme value. In recent years, it has been applied to the band-gap analysis of periodic structures. However, for periodic beam-plate composite structures with periodic and ordinary boundaries, it is relatively difficult for the traditional energy methods, such as the Rayleigh–Ritz method, to construct the displacement functions that satisfy boundary conditions. Hence, a hybrid solution is proposed in this paper to account for various boundary conditions of the periodic beam-plate composite structure. Specifically, the displacement functions constructed by the plane wave series can automatically satisfy the periodic boundary conditions. With the ordinary boundaries modeled by artificial springs, the spectral functions conforming to arbitrary boundary conditions are used to represent the displacement functions. The proposed solution is used to solve the band-gap problems of CRTS-III and CRTS-II slab ballastless tracks in China, and the accuracy of the solution is verified by comparing the calculated results with numerical simulations. In addition, through band-gap formation mechanism analysis, the frequency range of propagating flexural waves in each track component is accurately evaluated, which provides a theoretical basis for refined structural vibration reduction in the future. The solution proposed in this paper is flexible and convenient, which can be extended to a more complex band-gap analysis of periodic structures. [ABSTRACT FROM AUTHOR]

Few studies have considered the information in the frequency domain to detect the structural breaks in financial markets. This paper provides a mixed model that integrates BEMD, AFD and Chow test to study the fluctuation characteristics of the soybean futures price. Due to the application of AFD, the mixed model can detect the structural breaks of the price fluctuation through obtaining the high-resolution information in the frequency domain. According to our results, in general, the soybean futures price in China is mainly determined by IMF11, followed by IMF9, IMF8 and IMF7, and there exist many structural breaks of different IMFs. Interestingly, national macro-controls have opposite effects at IMF8 and IMF11. The results show the effectiveness of the proposed mixed model for detecting structural breaks of financial markets in frequency-domain by revealing the impact of external events on the soybean futures price at multi-scales. [ABSTRACT FROM AUTHOR]

China's declaration to the international community to peak CO2 emissions before 2030 and achieve carbon neutrality before 2060 is of great significance in advancing the objectives of the Paris Agreement, and has a positive and far-reaching impact on China's high-quality development. This paper expounds on responsibilities and ambitions in tackling climate change, analyzes the high-quality development opportunities brought about by CO2 emissions peak and carbon neutrality, and discusses the net zero carbon emissions transformation in the new era of ecological civilization. This paper is of the view that development towards net zero carbon emissions provides a new impetus for building a Beautiful China, and promoting ecological civilization and green development. The essence of carbon neutrality should be correctly understood so that the world will work together to improve climate resilience. China should also deepen the understanding of the principles and methodologies of climate change economics. [ABSTRACT FROM AUTHOR]

China accounts for more than 22% of the total energy consumption worldwide. Building energy consumption, among which consumption in public buildings was about 40% took the second place. With the problems of high energy waste, error rate and complexity of the control systems available, an indoor intelligent lighting system based on occupants' location is proposed in this paper to improve the energy efficiency of the current lighting systems indoors. The transmission model of electromagnetic wave in free space is optimized in both aspects of reference signal strength and attenuation coefficient radiation in complex environment dynamically based on which occupants' positions are obtained. The smart lighting system will turn on or off corresponding lights adaptively to provide a more energy efficient platform. Experimental results show that the proposed system is able to improve the energy efficiency of indoor lighting by at least 15%, with a lower error rate below 2% compared with the existing lighting systems based on voice control. [ABSTRACT FROM AUTHOR]

In the operation of railway vehicles, the quality of bogies directly affects the operation quality and driving safety. Wheel set is one of the most important components in bogie, so the maintenance of wheel set is very important. For a long time, the detection of train wheel sets in China is still in the stage of manual measurement with backward technology and low efficiency. A new automatic detection method of wheel flange tread based on fuzzy neural network image processing technology is proposed in this paper. This method can accurately detect the defects of wheel flange tread. It collects the original image of the tested wheel set through the digital camera, inputs it into the computer, through certain calculation and processing, and compares it with the model established based on fuzzy neural network, so as to detect the defects of wheel flange and tread. First, the research status of wheel tread defect detection is summarized. Second, the basic principles of digital image technology are studied, the image processing models are confirmed, and the image processing method based on fuzzy neural network is established. Finally, eight wheel set treads are selected to carry out defect detection, and the analysis results show that the proposed method can obtain the better inspection precision. [ABSTRACT FROM AUTHOR]

This paper explores the non-technological innovation system for building low-carbon cities in China. It establishes a comprehensive evaluation index system and grading standards for low-carbon cities, concerning both technological innovation and non-technological innovation factors. Defining non-technological innovation factors as independent variables, GDP per capita as the main control variable, and low-carbon development and carbon productivity as dependent variables, this paper examines the contribution of non-technological innovation to the building of low-carbon cities. The result shows that non-technological innovation manifested a significant trajectory of progress. It demonstrates that the continuous improvement to non-technological innovation system should effectively promote the further development of low-carbon cities. [ABSTRACT FROM AUTHOR]