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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]

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]

The COVID-19 outbreak and the implementation of peak and carbon neutral policies have severely impacted oil price volatility and the industrial sector. Exploring the impact mechanisms between oil prices and industries is particularly important for accurate forecasting of crude oil prices. As one of the world's largest commodity consumers, China's crude oil market is more representative and susceptible to external factors than that of developed countries. In this paper, we propose an analytical forecasting framework based on the causal effects between Shanghai crude oil prices and various industries in China to improve the forecasting accuracy of crude oil prices. Information geometric causal inference (IGCI) is applied to detect causal relationships between 31 different industries in China and Shanghai crude oil prices in the three time periods before, during and after COVID-19, and industries with strong causal information effects on crude oil prices in the long run are screened out as additional features. An oil price forecasting model based on Gray Wolf Optimization and Extreme Learning Machine (GWO-ELM) is proposed. Considering the small amount of data for Shanghai crude oil, this paper proposes a cross-learning data approach to solve the problem. Experimental results show that the GWO-ELM model outperforms RF, LSTM, GRU, and migration learning-based Tr-LSTM and Tr-Adaboost models in the task of Shanghai crude oil futures price prediction, and find that industry characteristics with long-term causal effects on oil prices can improve the model prediction accuracy. Our proposed analytical prediction can capture the oil price trend more accurately through the information of the industry and solve the problem of insufficient training data for the model. The application of this framework is expected to provide new methods and ideas for data mining of crude oil and other futures prices. [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]

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]

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 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]

In order to solve the challenges brought by multi-source and cross-domain scenarios to online music education, this paper designs an online music education system based on advanced artificial intelligence technology, which can provide personalized learning course resource recommendations for music online learners. The system includes four layers, consisting of user interface layer, application module layer, function module layer and data storage layer. At the application module level, this paper proposes a music recommendation algorithm based on a personalized multimodal network model. The recommendation algorithm performs music information retrieval (MIR) based on the similarity judgment of the contour of music pitch and the overall change, and constructs a multimodal network model based on the user's preference for resources to achieve personalized music recommendation. This paper crawls more than one million music score data from a well-known music platform database in China to establish a dataset to evaluate the performance of this method. The comparison results with three existing works show that the method proposed in this paper has good performance and can provide users with suitable music recommendations. The artificial intelligence technology-driven online music education mechanism proposed in this paper has good prospects. [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]

In this paper, we first proposed a statistical test for the detrended multiple moving average cross-correlation coefficient DMMC (s). The DMMC (s) mainly was used to analyze the correlation between the dependent variable y and other n independent variables x i . We proved that DMMC (s) approximately obeys the chi-square distribution. We studied the statistical properties of the DMMC (s) between normally distributed random sequences and power-law ARFIMA long memory random sequences. Furthermore, we discussed the influence of the cross-correlation among the target variable and independent variables on DMMC (s). Finally, we further study the application of DMMC (s) to China's stock markets and China carbon emission trading markets to investigate multiple cross-correlation. The empirical results show that there is a strong multiple correlation between China's Shanghai, Shenzhen and Hong Kong stock markets, while the correlation between China's carbon markets is not significant. This paper provides new ideas and theoretical support for exploring the correlation between multiple variables, which has implications for investors and policymakers. [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]

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]

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]

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]

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]

Financial time series are nonlinear, volatile and chaotic. Inspired by quantum computing, this paper proposed a new model, called primary ensemble empirical mode decomposition combined with quantum neural network (PEEMD-QNN) in predicting the stock index. PEEMD-QNN takes the advantages of the PEEMD which retains the main component of modal component and QNN. To demonstrate that our PEEMD-QNN model is robust, we used the new model to predict six major stock index time series in China at a specific time. Detailed experiments are implemented for both of the proposed prediction models, in which empirical mode decomposition combined with QNN (EMD-QNN), QNN and BP neural network are compared. The results demonstrate that the proposed PEEMD-QNN model has higher accuracy than BP neural network, QNN model and EMD-QNN model in stock market prediction. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 shocked financial markets globally, including China's crude oil future market, which is the third-most traded crude oil futures after WTI and Brent. As China's first crude oil futures are accessible to foreign investors, the Shanghai crude oil futures (SC) have attracted significant interest since launch at the Shanghai International Energy Exchange. The impact of COVID-19 on the new crude oil futures is an important issue for investors and policy makers. Therefore, this paper studies the short-term influence of COVID-19 pandemic on SC via multifractal analysis. We compare the market efficiency of SC before and during the pandemic with the multifractal detrended fluctuation analysis and other commonly used random walk tests. Then, we generate shuffled and surrogate data to investigate the components of multifractal nature in SC. And we examine cross-correlations between SC returns and other financial assets returns as well as SC trading volume changes by the multifractal detrended cross-correlation analysis. The results show that market efficiency of SC and its cross-correlations with other assets increase significantly after the outbreak of COVID-19. Besides that, the sources of its multifractal nature have changed since the pandemic. The findings provide evidence for the short-term impacts of COVID-19 on SC. The results may have important implications for assets allocation, investment strategies and risk monitoring. [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]

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]

Providing a scientific basis and method to ensure the smooth functioning of the Chinese crude oil market would be hugely significant to China's future economic development and security. To this end, attempts have been made to both internationalize the Shanghai crude oil market and minimize financial risks. This paper selects three crude oil markets (INE, WTI and Brent) and five Chinese financial markets (the futures, bond, fund, stock and foreign exchange markets) as the research objects. The Diebold and Yilmaz spillover index model and the multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) method are used to study the volatility spillover effect and the asymmetric cross-correlation between crude oil markets and financial markets. When the volatility spillover effect and the asymmetric relationship that exists between the financial markets are examined, the volatility spillover of the oil market to the financial market is found to be significantly higher than that of the financial market to the oil market. In particular, the spillover effect was even more significant from late-2019 to early-2020. Analysis demonstrates an asymmetric cross-correlation between crude oil markets and the abovementioned five Chinese financial markets. In particular, the impact of the Chinese crude oil market on the stock market is greatest, especially with respect to the Brent and WTI crude oil markets. Except for the bond market, when the INE and Brent markets are increasing, the risk exposure to financial markets is more significant. Among financial markets, INE-Bond market asymmetry is stronger than WTI-bond market asymmetry, but weaker than that of the Brent-Bond market when there are large fluctuations. [ABSTRACT FROM AUTHOR]

In this paper, a SEIR epidemic model related to media coverage and exogenous reinfections is established to explore the transmission dynamics of COVID-19. The basic reproduction number is calculated using the next generation matrix method. First, the existence of equilibrium points is investigated, and different kinds of equilibrium points indicate that the disease may disappear, or exist that result in different quantity of susceptible individuals, pre-symptomatic infected individuals and symptomatic infected individuals. The stability of the equilibria is discussed by a geometric approach, and it is found that controlling reproduction number to be lower than 1 is not sufficient for eradication of COVID-19. Second, transcritical bifurcation is explored, and it is found that improving the ratio of exogenous reinfection may lead to backward bifurcation under poor medical conditions, which indicates that two endemic equilibrium points appear. Third, to investigate the influence of parameters on the basic reproduction, sensitivity analysis is done to choose relatively sensitive parameters, and the parameters for treatment and media coverage are selected. An optimal control model is established to balance the treatment and media awareness. By exploring the existence and the uniqueness of the optimal control solution, the optimal control strategies are given. Finally, we run numerical simulations to verify the theoretical analysis on actual data of China, and the data from the four different states of India is used for forecasting the situation of infected individuals in a short period. It is found by the simulation that the co-function of treatment and media coverage results in the reduced number of infectious individuals. [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]

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]

Network topology is the basic for the development of traffic management and control. In a road network, bayonets with installation of surveillance facilities are key components to recognize traffic congestion from time to time. Therefore, identifying the essential bayonets in a road network becomes one of the most efficient ways to alleviate traffic congestion for traffic engineers and transport department. To do so, this paper aims to propose a novel sorting algorithm based on similarity measurements and traffic flow information to efficiently identify key bayonets in road networks. Our research results show that by analyzing the bayonet data in a fixed period of time in a medium-sized city of China, we have successfully identified the location of key bayonet points. Most of these key bayonet points are closed to residential areas and important traffic stations. The rank of these bayonet points can help the city managers better understand the topological characteristics of the road network as well as the propagation of congestion so as to make the traffic policies or control strategies for traffic congestion alleviation. [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 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]

The parameters of biological system may change under the influence of different states or state processes. The change of parameters can also affect the dynamic behaviors of epidemic disease. This paper presents a mean field stochastic susceptible-infected-vaccinated (SIV) epidemic model which parameters depend on the state process. The sufficient and necessary conditions of optimal control of the novel epidemic model are obtained by maximum principle. Finally, we perform representative numerical simulations to illustrate the theoretical results and further discuss the feasibility based on the hand, foot and mouth disease (HFMD) data in China. [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]

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]

Railway transportation, as an important lifeline during earthquake relief and post-disaster reconstruction, has an extremely significant role. The study of track irregularity caused by earthquakes is the basis for ensuring traffic safety after their occurrence. In this paper, a finite element model of a five-span simply supported high-speed railway beam bridge with the China Railway Track System (CRTS) II was established and an experimental verification was performed. Eighty arbitrarily selected seismic waves were extracted from the Pacific Earthquake Engineering Research Center (PEER) strong ground motion database and a nonlinear time-history analysis was performed on the finite element model. The frequency–domain distribution law of earthquake-induced track irregularities was studied. A stable target earthquake-induced track irregularity spectrum model was constructed, and its expression was fitted. According to the results, in the case of transverse earthquakes, the rails experienced noticeable alignment irregularity and cross-level irregularity, while the amplitude of the gauge and vertical irregularity were relatively small. The target irregularity spectrum has a higher amplitude in the low-frequency components. When peak ground acceleration (PGA) was low, earthquake-induced track irregularity was not obvious, but the deteriorating effects of earthquakes on track irregularities increased significantly with increasing PGA. [ABSTRACT FROM AUTHOR]

This paper investigates the presence and asymmetry of cross-correlations between agricultural futures markets in China and the US as well as the impact of price support policies and public emergencies (Sino–US trade conflict and COVID-19 pandemic) on the cross-correlations by the multifractal methods. The results show that the fluctuation characteristics and conduction directions of cross-correlations are asymmetric. The price fluctuations of soybean and corn futures in China are easier to be affected by the US soybean and corn futures. We find that the cross-correlations are multifractal under different price support policies and pubic emergencies. The price support policies with greater interventions on soybean and corn prices have aggravated the complexity of cross-correlations between the two futures markets in China and the US. The soybean and corn futures in China are hardly correlated to the US futures under the dual effect of the Sino–US trade conflict and the COVID-19 pandemic. The Sino–US trade conflict strengthens the complexity of cross-correlation for soybean futures and weakens it for corn futures, while the COVID-19 pandemic enhances the complexity of cross-correlations for soybean and corn futures. In addition, the fat-tailed probability distributions in different price support policy and public emergency periods have a dominant influence on the multifractality of cross-correlations. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 has resulted in an unprecedented attention and response to health surveillance in China, in which the Health Code has made outstanding contributions to digital social governance as well as epidemic control work. As China steps into the post-COVID-19 era, the Health Code will keep upgrading, optimizing and continue to play a role in regular epidemic prevention and control. This paper reviews the background, promoting reasons, significance and controversies of Health Code, so as to provide reference for the relative research and practical applications in the future. [ABSTRACT FROM AUTHOR]

In 1843, Hamilton (1805–1865) discovered the 4-dimensional division algebra H (ℝ) = ℝ ⊕ i ℝ ⊕ j ℝ ⊕ k ℝ over the field ℝ of real numbers. Hamilton's big discovery is the following beautiful multiplications for the basis { 1 , i , j , k } : i 2 = j 2 = k 2 = i j k = − 1. (⋆) H (ℝ) contains the field ℂ of complex numbers; therefore ℝ ⊂ ℂ ⊂ H (ℝ). Frobenius (1849–1917) showed the following outstanding theorem. Theorem (Frobenius). Up to isomorphism, the only finite-dimensional non-commutative division algebra over ℝ is H (ℝ). Starting from given any ring R and a free right R -module R ⊕ i R ⊕ j R ⊕ k R , the quaternion ring H (R) is canonically defined by the multiplications (⋆). For a commutative field F with 2 ≠ 0 , H (F) is a division ring or isomorphic to the ring of 2 × 2 matrices over F. This is a classical theorem. For nonzero a , b in the center of a ring R , the generalized quaternion ring H (R ; a , b) is defined. H (R ; − 1 , − 1) is H (R). In [I. Kikumasa, K. Koike and K. Oshiro, Complex rings and quaternion rings, East-West J. Math. 21 (2019) 1–19; I. Kikumasa, G. Lee and K. Oshiro, Complex Rings, Quaternion Rings and Octonion Rings (Lambert Academic Publishing, 2020); G. Lee and K. Oshiro, Quaternion rings and octonion rings, Front. Math. China 12(1) (2017) 143–155], quaternion rings and generalized quaternion rings over division rings or other rings are studied. Now, in this paper, from ring theoretic viewpoints, we study quaternion rings H (R) and generalized quaternion rings H (R ; a , b) over local rings R. From our results, we can clearly look over several classical results on H (F) and H (F ; a , b) over commutative fields  F. [ABSTRACT FROM AUTHOR]

This paper formulates a diffusive tuberculosis (TB) model with early and late latent infections, vaccination and treatment that may more properly describe the slow and fast dynamics of TB transmission. We develop a new concise approach to determine the combination coefficients in the Lyapunov function candidate for the model and its time derivative in the case that both are the linear combinations of several Volterra-type functions, which highly simplifies the computations in global dynamical analysis for the nonlinear high-dimensional model. Based on the TB case data reported in China, the parameter values of the model are estimated. We further predict the TB prevalence trend in China. Sensitivity analysis for the control reproduction number and endemic equilibrium is conducted to seek some effective interventions that can significantly reduce initial TB transmission and lower TB prevalence levels in China. In the end, numerical simulations show that the bigger diffusive rates pick up the speeds of convergence to the equilibria of the model. [ABSTRACT FROM AUTHOR]

The low-medium maturity shale oil in China has large resource potential. The occurrence state of such resource is mainly retained hydrocarbon and unconverted organic substance, making the in-situ conversion process a requisite technology. Meanwhile, the naturally fractured shale reservoir has multiple types of pore space, making the hydrothermal coupling process more complex. In this paper, a coupled thermal-reactive compositional flow model and numerical solution method is proposed. Specifically, the apparent permeability of fractured shale oil reservoir is derived based on fractal theory. Besides, the multistage parallel chemical kinetic reactions during in-situ conversion process and evolution of reservoir fluid composition and shale porosity are incorporated. Then the accuracy of the proposed model is tested through numerical cases. Finally, the impact of key operation parameters and fractal parameters on shale oil exploitation is analyzed, such as heating temperature, heating spacing, pore size fractal dimension, fracture length fractal dimension and tortuosity fractal dimension. The proposed model is capable of accurate and efficient prediction of the fractured low-medium maturity shale oil reservoir production. [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]

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]

The electrostatic suspension control system (ESCS) is the core component of the inertial sensor in space gravitational wave detection. To adapt to the changes in orbit environment and satellite platform vibration, the test mass stable is kept in the center of the electrode cage, the ESCS requires high-precision parameters calibration and high-stability verification of the control system. This paper studied the ESCS method, an adaptive controller with variable preload was proposed, and the stability conditions of the control system are given to provide a theoretical basis for the design of the controller. The structure and working principle of the system were also introduced. The electrostatic control system model was derived, and the performance of adaptive preload controller was analyzed. Finally, a simulation was conducted under different disturbance conditions. The results show that the control method proposed in this paper can achieve stable control in difference disturbance, and the preload voltage will change with the conditions. Compared with the traditional fixed preload method, we can see that our method has significantly improved the stability margin and the control quality during the process of dynamic response. This paper provides a solid foundation for the future exploration of space gravitational waves in China and clears the optimization direction for the next step. [ABSTRACT FROM AUTHOR]

Community is directly responsible for implementing the policy measures against public emergencies such as extreme weather, earthquake, flash flood and pandemic diseases. Summarizing the experience at the urban community level can help promote the global emergency management. This paper, from the perspective of COVID-19 prevention and control, selects three communities with different features to explore an effective response system for public emergency management at the urban community level. It demonstrates that based on a centralized leadership, the multi-level governance (MLG) network combined with information technology has mobilized their participation in combating COVID-19 and ensured the effective and timely response to the public emergencies, which blocked the spread of epidemic to the greatest extent, proving worthy of being promoted as one of the Chinese approaches and Chinese wisdom. [ABSTRACT FROM AUTHOR]

Most conventional air pollutants and carbon dioxide (CO2) are simultaneously emitted from the same sources, providing a sound theoretical basis for the synergistic governance of these emissions. At present, China faces severe challenges in protecting the eco-environment, such as reducing conventional pollutants, improving environmental quality, and peaking CO2 emissions. Internationally, the control of greenhouse gas (GHG) emissions has been incorporated into the comprehensive environmental management system in major developed economies such as the United States (US) and the European Union (EU), where, based on GHG emissions monitoring and statistical data, decision-making support is provided for the national governments in the form of policy evaluation, thus forming a management mode that enables overall planning, coordination, and unified regulatory at the national level and participation of multiple departments under the national government. The synergistic control of conventional air pollutants and GHGs is becoming an important measure to strengthen the environmental management and achieve low-carbon development. This paper summarizes the synergistic effects of reducing air pollution and carbon emissions from the aspects of synergistic policies, strategic planning, and institutional systems, and conducts an analysis based on existing synergistic practices. [ABSTRACT FROM AUTHOR]

For the Belt and Road Initiative, "extensive consultation, joint contribution and shared benefits" is the basic principle, and the competitiveness heterogeneity is an important condition for cooperation. Based on the complex network theory, this paper constructs a complex network model of global value chain (GVC) division of labor system by using the Multi-Regional Input-Output (MRIO) table and reveals the variation trend of competitiveness of industrial sectors and economies on the GVC network by the National Competitive Advantage Index (NCAI). The results verify the effectiveness of BRI and help countries along the BRI route to explore their comparative advantages and cooperation prospects with other countries. The research also provides a direction and reference for China to better implement the Initiative. [ABSTRACT FROM AUTHOR]

This paper investigates the fluctuation characteristics and asymmetry of cross-correlations between economic policy uncertainty (EPU) and agricultural futures prices in China and the US by using the multifractal detrended cross-correlation analysis (MF-X-DFA) and multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA). We find that the multifractal cross-correlations exist between EPU and agricultural futures prices, and the cross-correlations are anti-persistent and asymmetric. The anti-persistent cross-correlations in China are all stronger than those in the US. The multifractal degree of cross-correlation between EPU and soybean futures price is lower in China than in the US, while the multifractal degree of cross-correlation between EPU and soybean meal, soybean oil or corn futures price is higher in China than in the US. Moreover, China's soybean futures price is more susceptible to the upward and downward trends in China's EPU, while the US soybean meal, soybean oil, and corn futures prices are more susceptible to them in the US EPU. [ABSTRACT FROM AUTHOR]

In the past decade, the number of cars in China has significantly raised, but the traffic jam spree problem has brought great inconvenience to people's travel. Accurate and efficient traffic flow prediction, as the core of Intelligent Traffic System (ITS), can effectively solve the problems of traffic travel and management. The existing short-term traffic flow prediction researches mainly use the shallow model method, so they cannot fully reflect the traffic flow characteristics. Therefore, this paper proposed a short-term traffic flow prediction method based on one-dimensional convolution neural network and long short-term memory (1DCNN-LSTM). The spatial information in traffic data is obtained by 1DCNN, and then the time information in traffic data is obtained by LSTM. After that, the space-time features of the traffic flow are used as regression predictions, which are input into the Fully-Connected Layer. In the end, the corresponding prediction results of the current input are calculated. In the past, most of the researches are based on survey data or virtual data, lacking authenticity. In this paper, real data will be used for research. The data are provided by OpenITS open data platform. Finally, the proposed method is compared with other road forecasting models. The results show that the structure of 1DCNN-LSTM can further improve the prediction accuracy. [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]

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]

The greenhouse gas emissions from China's transport sector, which account for a large proportion of China's total greenhouse gas emissions, are still increasing rapidly. Therefore, low-carbon transformation is urgently needed in China's transport sector. This paper provides an overview of the situation and features of greenhouse gas emissions from China's transport sector, and proposes carbon-neutral development paths for the transport sector based on current national policies, goals and previous research. China needs to work on many aspects, including transport restructuring, alternative fuel technologies and energy efficiency improvement, to achieve near-zero emission goals by 2060. Under the carbon neutrality goal, China's transport sector should strive to reach the carbon peaking goal by 2030, and limit carbon emissions within 100 million tons by 2060. [ABSTRACT FROM AUTHOR]

The coal-based energy industry plays a huge role in supporting the development of a national economy. As China pledges to achieve carbon peaking and carbon neutrality goals, how to keep a balance between carbon emission reduction and coal consumption has become a serious problem and daunting challenge facing the industrial chain of coal-based energy for a long time. The prospects for the coal mining industry are increasingly limited under carbon constraints. Faced with serious challenges in its positioning and technological development, the coal-fired power industry is suffering the consequences of negative environmental externalities. Therefore, the low-carbon transformation of China's coal-based energy industry is necessary and urgent. This paper conducts an in-depth analysis of the development status of China's coal-based energy industry under the carbon peaking and carbon neutrality goals and the obstacles in the transformation and upgrade of the coal-based energy industry, and comes up with response strategies. The future coal-based energy industry should make full use of emerging low-carbon clean technologies such as carbon capture, utilization, and storage to achieve low-carbon transformation, and upgrade of the entire industrial chain, following the current development trends. [ABSTRACT FROM AUTHOR]

This paper presents a multi-timescale receding horizon framework for the load forecast of large power customers. The future load pattern of individual users could be very difficult to predict because of its chronological and high volatile properties. Also, the sampling of nonaggregated load data may suffer from severe information missing issues. To address these challenges, we first develop an online singular value thresholding (SVT) algorithm, which utilizes the approximate low-rank property of load data matrices to efficiently recover the missing information. Then, a combinatorial deep learning method is developed, which applies the multi-layer perception (MLP) neural network and the long short-term memory (LSTM) neural network with gated recurrent unit (GRU) to deal with the short-term and ultra-short-term load forecast, respectively. Specifically, an early stopping strategy is designed and implemented to avoid the over-fitting of model training. Moreover, the receding time window is imposed to dynamically update the data recovery and load forecast outcomes, which supports the online computing on a Spark platform. Numerical experiments on real-world load data from North China confirms the effectiveness of the proposed methodology, which can support more complex applications in embedded systems and cyber physical systems. [ABSTRACT FROM AUTHOR]