Search

Paper-cutting is one of the valuable intangible cultural heritages of China, with distinctive features such as "round as the autumn moon, sharp as the wheat mane, square as the green brick, missing as the serrated teeth, and thread as the beard," and is a widely spread folk art. The art of paper-cutting brings new inspiration to the design of structures, and by changing the topology of the raw material, the material/structure can undergo significant changes in physical properties, such as optical, thermal, acoustic, and mechanical aspects. The protection of intangible cultural heritage is a process of cultural self-awareness and a kind of cultural reflection and enlightenment. In the history of promoting socialist cultural development, the protection of "intangible heritage" paper-cutting is undoubtedly of great significance. The purpose of digital image repair is to restore the integrity of the broken image, and the process is to fill in the specified area of the digital image with information, requiring a natural transition between the filled area and the original area of the image and minimizing artificial traces, so that the image looks as if it has never been broken. In this paper, the paper-cutting pattern design method based on image restoration technology is investigated, starting from the preprocessing of paper-cutting images by acquiring the edges of the images and using the Criminisi image restoration algorithm with image broken edge reconstruction to realize the image broken edge reconstruction design of paper-cutting graphics. Therefore, the paper-cut graphics generated by the method in this paper are concise and coherent as a whole, which reduces the difficulty of paper-cut design while satisfying individual design requirements. [ABSTRACT FROM AUTHOR]

A scientific paper's citation represents its influence, which is the most intuitive indicator to access the quality of papers. This paper mainly adopts the social network analysis method, using the authors and the keywords of sports industry papers in China to constitute the networks of collaboration and knowledge, to explore effects of the degree centrality of authors and keywords and the structural hole of authors and keywords on the citation of papers in the collaboration and knowledge networks and draw the following conclusions: (1) as for collaboration networks, the degree centrality at the paper level is positively correlated with citations; (2) in the collaboration network, the positive correlation between the structural hole at the paper level and citations does not exist; (3) within knowledge networks, an inverted- U shape was found between degree centrality and paper's citation; and (4) within knowledge networks, a positive correlation is in existence between the structural hole of papers and their citation. This study synthesizes the already widely used collaboration network with the knowledge network constructed through keywords, distinguishes from the previous network features focusing at the author level, and explores research projects of Chinese Sports Industry from the paper level, providing a new perspective for the research of sports industry in China, complementing the methods and ideas of sports industry research, as well as providing a reference for the research in other disciplinary fields. [ABSTRACT FROM AUTHOR]

Folk paper-cut art is one of the bright pearls, with a wide range of shapes and a long history, that serves as a model for modern visual communication design in China and encourages designers to think creatively. Integrating emotional elements into a design not only can elicit an emotional response from the viewer but also can make works created using traditional rational thinking more vivid, energetic, and touching. The main focus of this research is on the path and method of incorporating folk paper-cut emotion into visual communication design. The research status of various feature extraction methods and image recognition methods at home and abroad is examined in depth in this paper. For the recognition of distorted images that are not transformed by mathematics, some effective methods are proposed. They are used to recognize artistic images of paper-cut patterns because they can extract effective features that are not affected by translation, rotation, scale change, or small deformation. Experiments have shown that they have a positive impact. The use of folk paper-cut art in visual communication design not only improves the quality of design work but also generates new ideas for the transmission and development of other traditional Chinese cultures. [ABSTRACT FROM AUTHOR]

Regional poverty is one of the most serious challenges facing the world today. Poverty, antipoverty, and poverty alleviation are the focus of the attention of scholars and the public. This paper takes China's counties as the research unit, selects the influencing factors of poverty from natural and socio-economic factors, establishes an evaluation index system, simulates the natural poverty index and socio-economic poverty eradication index of each county, and clarifies the distribution characteristics of spatial poverty using GIS spatial analysis and BP artificial neural network. The results indicate that natural factors are the main cause of poverty in Chinese counties, with 710 counties having a high natural poverty index, accounting for nearly 30% of the total number of counties in the country. The national county-level natural poverty index shows a clear strip distribution pattern along latitude and longitude, with a strip distribution from north to south and from west to east; socio-economic factors have played a certain role in poverty alleviation, with as many as 1521 counties with low socio-economic poverty alleviation indices, accounting for approximately 64% of the total number of counties in the country. The spatial distribution of the county-level socio-economic poverty alleviation index is relatively fragmented. Through spatial scanning statistics, a total of 44 county poverty pressure index risk clusters reached a statistical significance level, involving 243 counties and districts. In poverty reduction practice, the internal counties and districts of contiguous poverty-stricken areas should strengthen cooperation and exchange. In the process of poverty alleviation and development, targeted poverty alleviation and economic development should be carried out based on the poverty-dominant type and self-development ability of the county, in order to improve efficiency. Regions that are relatively prosperous and have taken the lead in poverty reduction should play a leading and exemplary role in strengthening the radiation power of regional central cities. The prominent feature of this study is the comprehensive utilization of multisource data and the use of new spatial analysis methods (flexible spatial scanning method is widely used in the field of infectious disease prevention and control research). By constructing a multidimensional poverty measurement system that includes natural and social factors, it distinguishes the differences between the factors that cause poverty and the factors that eliminate poverty in regional poverty. At the same time, the flexible spatial scanning detection method was used to detect the differentiation mechanism of poverty spatial patterns. [ABSTRACT FROM AUTHOR]

In the past few years, drones have been adopted as a novel delivery tool towards medical supplies, improving delivery service efficiency due to fast speed and neglection of geographical limitations. However, the flight endurance of a battery‐operated drone is limited for long‐distance medical supplies delivery operations. Recharging stations, as a kind of drone facility, allow multiple stops for drones to supplement the power to overcome the flight‐range limitations. This paper studies drone‐assisted long‐distance medical supplies delivery with recharging stations in rural communities by a mixed integer linear programming model. To illustrate the applicability of this model and explore the key factors influencing delivery efficiency of medical supplies, a case study from China is conducted. The results indicate that enhancements on the speed of a truck or a drone can yield considerable delivery cost reduction. In addition, drone‐recharging technology advances can improve delivery efficiency of medical supplies in rural communities. [ABSTRACT FROM AUTHOR]

This paper examines the dynamic linkages among economic policy uncertainty (EPU), the green bond market, the carbon market, and the macroeconomy using the time-varying parameter vector autoregressive (TVP-VAR) model with monthly data spanning from January 2016 to December 2021. Additionally, it assesses the robustness and accuracy of the empirical results through the Bayesian vector autoregressive (BVAR) model. The findings indicate that EPU negatively affects the green bond market in the short term but has a positive impact in the medium and long term. Conversely, EPU has a positive impact on the carbon market in the short term but a negative impact in the medium and long term. Furthermore, the green bond market negatively influences the carbon market in both the short and medium to long term. These results suggest that emerging markets, such as the green bond and carbon markets, are influenced by EPU. The adverse impact of the green bond market on the carbon market, however, contributes to expediting China's attainment of its low-carbon objectives. Appropriate economic policies can play a vital role in accelerating the transition to a low-carbon economy. The study also reveals that the US-China trade war has expedited the development of green capital markets in China, despite its impact on the green economic transition in the country. These findings provide insights for the government and investors to formulate suitable strategies for risk mitigation. [ABSTRACT FROM AUTHOR]

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

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

Folk art is a "living fossil" of hisory, whose existence and evolution reflect the way people live and think. It is a one-of-a-kind way of communicating the process of human development to the rest of the world. However, as China's economic development and cultural globalization accelerate, many folk arts are being severely harmed and lost. The emergence of virtual reality technology, which benefits from the advantages of virtual reality technology, has greatly strengthened the utilization and protection of folk art resources in recent years, with the rapid development of Internet technology. Virtual reality technology is a human-computer interaction experience technology that uses complex calculations to provide corresponding operational feedback to the senses of touch, hearing, vision, and balance. It is more reasonable and perfect to reconstruct and integrate the resource content and realize the digital utilization of folk art resources in this paper, which is based on the ALS collaborative filtering algorithm. This paper will make some necessary improvements to the original algorithm, which has met the requirements of virtual reality technology, through the comparison of algorithms. Finally, experiments show that the proposed algorithm's accuracy is 85 percent higher than the original algorithms, and the data retrieval processing interval is more reasonable. [ABSTRACT FROM AUTHOR]

With the increasing frequency of scientific cooperation, research on the impact of scientific cooperation on scholars' scientific performance has become a hot topic in academic research. This paper mainly uses quantitative research methods such as bibliometrics and social network analysis to analyze the correlation between degree centrality, L-index, and scientific performance of the Chinese author of Physical Education and Training Science and draws the following conclusions: (1) degree centrality is positively correlated with the number of papers, average citations per paper, and H-index and (2) L-index is positively correlated with the number of papers, average citations per paper, and H-index. Unlike previous studies on scientific collaboration networks and scholars' performance that focused on traditional network characteristics indicators, this study introduces a new network characteristics indicator, L-index, through which the degree of collaboration between authors and other important authors in the research field can be better assessed, which also provides a new direction for research related to research collaboration networks and scholars' performance; at the same time, it also provides a theoretical basis for subsequent research on the utility of scientific collaboration, a reference for the assessment of the research performance of scholars in other disciplines, and a theoretical reference for more scientific and comprehensive prediction of scholars' research performance in the future. [ABSTRACT FROM AUTHOR]

Given the phenomenon of "financing is difficult and expensive" for MSEs, this paper empirically investigated the influencing mechanism of the credit demand side characteristics on the financing constraints of MSEs based on the information conveyance perspective. The conclusions show that MSEs in China are severely suffering from financing constraints and 57.17% and 50.00% of MSEs with credit demand have not applied for loans from formal and informal financing channels, respectively. In terms of enterprise characteristics, MSEs have low asset size, short establishment history, weak profitability, and lack of tools such as fixed assets, complete financial management system, professional technicians, and private brands to convey risk information to financing institutions, which are key factors resulting in their financing constraints. In terms of owner characteristics, young owners lack financing experience and convey higher risk information to financing institutions; therefore, owners' age negatively influences the financing constraints of MSEs. These findings suggest that banks can use big data credit technology as a tool to obtain risk information about MSEs, and the government should implement diversified interventions to improve the information environment in financial markets. These findings provide empirical evidence for banks and governments to address the financing constraints of MSEs. [ABSTRACT FROM AUTHOR]

Under the condition of weakly cemented soft rock in Western China, the surrounding rock deformation of gob-side entry is obvious, especially under the influence of fault, and the problem of surrounding rock control becomes increasingly prominent. To solve this issue, this paper firstly studied and obtained the evolution law of the ground pressure appearance of the gob-side entry in the fault area, then put forward the concept of surrounding rock control in the fault area of the gob-side entry, put forward a targeted pressure relief + increase preload + passive reinforcement parallel to the roadway surrounding rock strengthening control scheme, and carried out field applications. The results show that the roof subsidence and mining side heave of the roadway in the fault area increase significantly, accompanied by the characteristics of broken cables, the length of the broken cable is 0.2 m–0.6 m, and the breaking process is divided into multiple breaks. The stress evolution of gob-side entry in fault area presents a stage characteristic of "rapid growth-stable." The surrounding rock control effect is improved under the bolt cable high pre-tightening support, and the roadway deformation is effectively controlled under the pressure relief + active + passive support, with a good application effect. [ABSTRACT FROM AUTHOR]

The magnitude of pretension force serves as an important indicator of the effectiveness of anchor bolt active support and is one of the significant factors influencing the stability of tunnel surrounding rock. Therefore, in practical engineering, it is crucial to establish the relationship between pretension torque and pretension force. However, current research in this field has some limitations. With a specific mine in western China as the engineering background, this paper first analyzed the influence factors of surrounding rock deformation and failure, established a mechanical model for pretension structure of anchor bolt support, and derived the quantitative relationship between pretension torque and pretension force based on hypothetical conditions. Finally, it proposed the loss effect of anchor bolt support and modified the pretightening loss coefficient for engineering application. The research results show that the actual pretightening force of anchor support is lower due to the influence of deep soft coal seam, which leads to failure of coal pillar under mining stress. The loss effect of surrounding rock on pretightening force was represented by a coefficient k, and the modified value of the coefficient was calculated as 0.19∼0.43. By applying the modified relationship between pretightening torque and pretightening force, it was found that the actual pretightening torque of 300 Nm applied to 11307 return air roadway effectively controlled surrounding rock deformation and failure, with coal pillar displacement less than 120 mm. [ABSTRACT FROM AUTHOR]

Hub economy is a kind of emerging economic form. Developing a hub economy is essential to strengthen domestic and foreign connectivity and build a powerful country in transportation. This paper designs a two-stage analysis framework for the evaluation and impact study of the input-output efficiency of the hub economy based on the super SBM model, Malmquist model, and Tobit model. In the first stage, the Super SBM and Malmquist models are used to measure the static and dynamic efficiency of the hub economy. In the second stage, the Tobit model is used to analyze the factors influencing the efficiency of the hub economy. Among them, the explained variable in the second stage is the measurement result of technical efficiency in the first stage. The empirical results of 30 provinces and cities in China from 2012 to 2021 show that (1) the technical efficiency (TE), pure technical efficiency (PTE), and scale efficiency (SE) of China's hub economy are 0.585, 0.740, and 0.820, respectively, which do not reach the effective state; (2) the technical efficiency change index (Effch), technical progress change index (Techch), and total factor productivity change index (Tfpch) of China's hub economy are 0.994, 0.945, and 0.939, respectively, indicating that the corresponding efficiencies show a downward trend; and (3) industrial structure, innovation, and technology are significantly and positively correlated with the efficiency of the hub economy; policy and enterprises are significantly negatively correlated with the efficiency of the hub economy; and education does not correlate with the efficiency of the hub economy. [ABSTRACT FROM AUTHOR]

The bioeconomy model provides an alternative view of global economic systems by putting sustainable practices combined with digital approaches at the forefront to tackle issues such as climate change. To address this new business trends, financial institutions began to set up the environmental, social, and governance (ESG) business units to evaluate their business strategies. This paper is aimed at examining the nonfinancial effect created by the digital transformation (DT) activities, highlighting the role of enterprise heterogeneity after the implementation of Environmental Protection Law (EPL) in China. We employ the panel data of A-share listed companies from 2010 to 2020, selecting DT and ESG indicators as the important representations of "Industry 5.0." Our empirical results demonstrate a positive impact of EPL on the ESG performance in sight of resource enterprises (REs), environmental enterprises (EEs), and polluting enterprises (PEs), but a negative impact of EPL on the DT indicators among those environmental related industries. Additional causal relationship regression reveals that enterprise DT has an intrinsic promoting effect on the ESG performance, emphasizing on the high risk of digitization process being the shock transmitters to enterprise nonfinancial indices. Notably, the connectedness of environmental policy illustrates dynamic patterns by parallel trend test and propensity score matching (PSM) DID regression. This paper is prone to benefit lawmakers, regulators, and firm executives responsible for analyzing and assessing enterprise digitization behavior by exploring the influence of macrolevel environmental policy. [ABSTRACT FROM AUTHOR]

International experiences have underscored the dual implications of financial openness. Given China's unique circumstances and its escalating level of financial openness, it is crucial to assess potential impacts on the country's bank systemic risk. This paper uses the quarterly data of 37 listed banks in China from 2010 to 2022 to explore the relationship between financial openness and systemic risk of the banking system, the mechanism of action, and the moderating effect of macroprudential policy on the two. The findings indicate an inverted "U"-shaped correlation between financial openness and bank systemic risk. On one side of this shape, financial openness primarily exacerbates funding mismatch, thereby increasing the systemic risk of banks. Conversely, on the other side, it primarily alleviates systemic risk by optimizing capital management. Moreover, with the help of macroprudential supervision, the inverted "U"-shaped relationship between financial openness and bank systemic risk leads to a lower level of systemic risk and, at the same time, promotes the early arrival of the inverted "U"-shaped inflection point between financial openness and bank systemic risk. Notably, the impact of financial openness on the systemic risk of joint-stock commercial banks, urban commercial banks, and rural commercial banks is more significant. The above research results provide a regulatory reference for effectively preventing and resolving systemic risk while achieving high-quality openness to the outside world. In deepening financial openness, the banking industry needs to pay attention to the funding mismatch and the efficiency of capital management and implement differential risk supervision and prevention mechanisms for banks with different ownership, which is conducive to the reduction of bank systematic risk. [ABSTRACT FROM AUTHOR]

Particle swarm optimization algorithms (PSOA) is a metaheuristic algorithm used to optimize computational problems using candidate solutions or particles based on selected quality measures. Despite the extensive research published, studies that critically examine its recent scientific developments and research impact are lacking. Therefore, the publication trends and research landscape on PSOA research were examined. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and bibliometric analysis techniques were applied to identify and analyze the published documents indexed in Scopus from 2001 to 2021. The published documents on PSOA increased from 8 to 1,717 (21,362.50%) due to the growing applications of PSOA in solving computational problems. "Conference papers" is the most common document type, whereas the most prolific researcher on PSOA is Andries P. Engelbrecht (South Africa). The most active affiliation (Ministry of Education) and funding organization (National Natural Science Foundation) are based in China. The research landscape on PSOA revealed high levels of publications, citations, and collaborations among the top authors, institutions, and countries worldwide. Keywords co-occurrence analysis revealed that "particle swarm optimization (PSO)" occurred more frequently than others. The findings of the study could provide researchers and policymakers with insights into the prospects and challenges of PSOA research relative to similar algorithms in the literature. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the activity, resistance, clonality of MIC distribution, and the correlation between virulence and resistance genes and biofilm formation of omadacycline (OMC) in clinics for Streptococcus agalactiae isolates from China. 162 isolates were collected retrospectively in China. The S. agalactiae were collected from the body's cervical secretions, wound secretions, ear swabs, secretions, semen, venous blood, cerebrospinal fluid, pee, etc. The MIC of OMC against S. agalactiae was determined by broth microdilution. The inhibition zone diameters of OMC and other common antibiotics were measured using filter paper. D-test was performed to determine the phenotype of cross resistance between erythromycin and clindamycin. In Multilocus sequence typing (MLST), some commonly-detected resistance genes and virulence gene of these S. agalactiae isolates were investigated using polymerase chain reaction (PCR). Biofilms were detected by crystal violet staining. Our data demonstrated the correalation of the biofilm formation and OMA antimicrobial susceptibility of S.agalactiae clinical isolates with the carrier of virulence gene scpB. Conclusively, OMC exhibits the robust antimcirobial activity against clinical S. agalactiae isolates from China compared with DOX or MIN, and the carrier of the virulence gene scpB might correlate with the biofilm formation in OMC-resistant S. agalactiae. [ABSTRACT FROM AUTHOR]

The digital economy has great potential to sustain China's high-quality economic growth and substantially strengthen urban innovation capacity. This paper developed a digital economy index using city-level data from China and measured the level of urban innovation with patents per capita. We used a spatial econometric model to explore the spatial implications of the digital economy on urban innovation, probed into the mechanism by which the digital economy affects urban innovation, and further measured the spatial spillover distance and threshold of the digital economy on urban innovation. The findings suggest that China's digital economy and urban innovation are characterized by spatial aggregation, and the spatial distribution varies from region to region. The digital economy, with strong spatial spillover effects on the innovation capacity of cities in China, may not only enhance the innovation capacity of one city but also drive a simultaneous growth of the innovation capacity in peripheral cities. The analysis of mechanisms indicates that the digital economy enhances local innovation capacity directly through promoting human resources and increasing science and technology spending and drives the improvement of the innovation capacity in peripheral cities through the spatial spillover of human resources and science and technology spending. The effects of the latter one outweigh those of the former one. The analysis of heterogeneity shows that the central, western, and northern regions, where the digital economy is relatively less developed, have the latecomer advantage, and the digital economy has more prominent effects on innovation capacity. Calculating the spillover distance and threshold demonstrates that the digital economy influences urban innovation within a spatial spillover range and threshold of approximately 500 kilometers. Within 500 kilometers, the positive spatial spillover effects prevail, while beyond 500 kilometers, the negative siphon effect prevails. Therefore, it is necessary to consider the differences in the impact and role of the digital economy on urban innovation from a spatial perspective. [ABSTRACT FROM AUTHOR]

The rapid expansion of metro networks, e.g., in many cities of China, continuously introduces the operation of new stations every year. Due to the lack of historical data and complicate variations of short-term passenger flow in the early stage of operation, it is difficult to accurately predict inbound and outbound passenger flows of new metro stations in the short term, which would be the database for train scheduling for new stations before operation, dynamic capacity optimization for new stations under operation, short-term prediction of cycle sharing demands near new stations, and so on. Traditional methods usually failed to exactly reflect the complicate rules or were unusable without the new station's historical data. In order to solve the above problems, this paper proposes a short-term inbound and outbound passenger flow prediction model for new metro stations at the early stage of operation by combining the K-means clustering algorithm, an improved spatiotemporal long short-term memory model (Sp-LSTM), and a real-time feedback error model (mean absolute error, MAE), where passenger flows' spatial-temporal characteristics and land-use relevance are considered. The application in Guangzhou Metro, China, where Line 21 is regarded as a new line, shows that the proposed K-Sp-LSTM model has the best prediction accuracy compared with traditional methods. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of cross-border investment of domestic venture firms (VCs) on the overseas listings of their domestic portfolio companies. Using a sample of 1,439 domestic VCs' first-round domestic investment events collected by Crunchbase and PEDATA, we find that the more cross-border investment experience domestic VCs have, the more likely their domestic portfolio companies are to go public outside China. The findings remain robust after using the instrumental variable method to eliminate endogeneity, the Heckman two-stage regression method to eliminate sample selection bias, and the exclusion of a portion of the sample for reregression. In addition, we further find that foreign VCs participating in follow-on financing play a mediating role in the relationship between the cross-border investments of domestic VCs and the overseas listings of their portfolio companies. This paper reveals the critical path for domestic VCs to go out and bring in foreign VCs to promote overseas listings of domestic firms. The findings of this paper are critical to the layout of domestic VCs' internationalization strategy and the sustainable development of domestic firms. [ABSTRACT FROM AUTHOR]

Ink element is one of the unique cultural symbols in China, which has profound cultural heritage and spiritual connotation. Animation is a form of art design, and it is a good way to convey and express information in an intuitive artistic image. The use of ink and wash elements for animation design has important value and significance in the start of Chinese culture. It can develop animation design, innovate animation creation forms, and can highlight Chinese style. In this article, we have studied the creation process, creation format, and creation method of using angular digital technology to make ink VR design. It combines art and technology and combines practical experience with wireless sensors. Based on HTML5 interactive technology, we have studied its advantages more deeply, better introduced the theme of ink element animation, solved the problem of realizing ink effect in 3D virtual environment, and better introduced ink animation in virtual reality environment. During the production process, students will learn how to simulate digital objects, render ink and wash effects, build a virtual environment in the later stage, and explore the knowledge, operation, and meaning of ink and wash elements and the animation design process. This paper studies the wireless sensor and HTML5 interactive technology and applies it to the design of ink and wash animation VR, aiming to promote its vigorous development and application. [ABSTRACT FROM AUTHOR]

In China, slope engineering occasionally faces landslides in rocky slopes containing muddy interlayers, primarily triggered by excavation activities. These incidents lead to considerable human casualties and substantial economic losses. However, existing studies predominantly concentrate on the excavation-induced impacts on the stability of rocky slopes characterized by single-layered soft and weak interlayers. Conversely, reports on how excavation influences the stability of bedding cataclastic rock mass high slope containing multimuddy interlayers remain notably absent in the literature. Moreover, unloading due to excavation can swiftly compromise the mechanical integrity and overall quality of the rock mass, consequently impacting the stability of slopes postexcavation. Therefore, this paper modeled the unstable slope excavated at a waste incineration power plant in Yuxi, Yunnan, using the finite element strength reduction method. This approach was employed to comprehensively simulate the entire process of artificial multilevel excavation in a bedding cataclastic rock mass high slope containing multimuddy interlayers. This study investigated the impact of multilevel artificial excavation on slope stability by thoroughly considering factors including alterations in slope morphology, unloading effects, and the degradation of geotechnical parameters. The research yielded the subsequent conclusions. Multimuddy interlayers were the key to the slope's instability. For slopes subjected to such multilevel excavation, efforts were made to minimize the exposure of muddy interlayers. Slopes above exposed muddy interlayers did not require additional support, while those below needed prioritized reinforcement. The likely instability mode of the actual slope was local destabilization leading to landslides. Furthermore, when using numerical simulation methods to study the impact of excavation disturbances on the stability of such slopes, it was necessary to consider the deterioration of geotechnical parameters to obtain results more reflective of actual conditions. These research findings provided valuable theoretical and empirical support for studies on similar excavated slopes. [ABSTRACT FROM AUTHOR]

Anemia is a global public health problem, especially common among children in developing countries, which affects their physical and mental health development. However, there is currently a lack of research on the relationship between anemia and academic performance. The objective of this study was to explore the association between anemia and academic performance, and the possible factors mediating this association among Chinese children. The data for this study came from the baseline survey of the Chinese Education Panel Survey Elementary School Cohort. The cohort was conducted from September 2018 to June 2019 in 160 elementary schools, covering 20 provinces and 40 counties/districts throughout China. Paper-based questionnaires were used, completed by 4th grade students, parents, head teachers, main teachers, and principals. The data used included questionnaire responses, physical measurements, and academic performance of 17,695 students. Based on students' hemoglobin levels and school altitude data, we grouped them into anemia and nonanemia categories using WHO criteria. The anemia group had 1,154 individuals, while the nonanemia group had 16,541 individuals. An ordinary least squares regression and mediation effect analysis were conducted. Our findings found the prevalence of anemia was 6.52% among Chinese Grade 4 students. Students without anemia had a higher average test score for three academic subjects than students with anemia (P < 0.001); their test scores for Chinese, Mathematics, and English were also higher (P < 0.05). Multivariate regression analysis showed a negative association between anemia and average test scores as well as individual test scores for the three subjects. Mediation analysis found that anemia affected academic performance directly (P < 0.05), and indirectly by decreasing the cognition score (P < 0.05). The indirect effect was 19.9% of the total effect. Findings highlighted anemia affected academic performance both directly and indirectly. Nutrition-related interventions should be implemented to prevent a decrease in academic performance among students with anemia. [ABSTRACT FROM AUTHOR]

In order to evaluate the effect of market-oriented environmental management measures on regional carbon emission intensity in the pilot areas better, this paper adopts a quasinatural experiment of energy-use rights trading (EURT) policy by using the difference-in-difference method from the perspective of cities in China from 2006 to 2019. The results show that the policy of EURT can significantly reduce regional carbon emission intensity, which varies in different regions and different scales of cities. The main goal of implementing the policy is to reduce regional carbon emission intensity by improving the energy consumption structure and promoting the improvement of industrial structure and green innovation. In addition, the spatial impact of the EURT pilot project is demonstrated by its ability to not only reduce local carbon emission intensity but also decrease carbon intensity in and around the designated areas. [ABSTRACT FROM AUTHOR]

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

Accurate delineation of debris-flow-endangered areas (e.g., the maximum runout distance) is a necessary prerequisite for the debris-flow risk assessment and countermeasures design. Recently, machine-learning models have been proved to be an effective tool in predicting debris-flow parameters. However, existing machine-learning models are generally developed based on a very limited number of observation data, which may result in the predictive model overfitting or underfitting. How to develop a robust model for accurate forecasting of debris-flow-endangered areas still remains a difficult task. This paper proposes a hybrid method for predicting debris-flow hazard zone by integrating machine-learning algorithms and an empirical regression model. The proposed method takes the calculated maximum runout distance obtained from the empirical model as supplementary inputs to increase the amount of training data to construct hybrid machine-learning models. Three commonly used machine-learning models (i.e., multivariate adaptive regression splines (MARS), random forest (RF), and support vector machine (SVM)) are developed based on the training datasets of a specific debris basin. Then, these three machine-learning models are combined with an empirical relationship developed using the same training datasets to generate corresponding hybrid models. Finally, the performance metrics (i.e., coefficient of determination (R2), root-mean-square error (RMSE), and mean absolute error (MAE)) of the proposed hybrid models are comprehensively investigated and compared with the single predictive model (i.e., MARS, RF, SVM, and the empirical model) under fivefold cross-validation. The proposed method is illustrated using 134 channelized debris-flow events in Sichuan province, China. Results show that compared with the three individual machine-learning models, hybridization of machine-learning algorithms and the empirical model results in R2, RMSE, and MAE improved by 70.5%, 32.9%, and 41.1%, respectively. In contrast to the empirical model, the R2, RMSE, and MAE value of the proposed hybrid models are improved by 29.6%, 22.3%, and 32.5%, respectively. The proposed hybrid models generally perform better than the single machine-learning and the empirical model, providing a promising tool for accurate forecasting of a debris-flow-endangered area. [ABSTRACT FROM AUTHOR]

Due to the demand for safety and convenience in traveling, self-driving technology has developed very fast in the past decades. In this paper, a novel technology forecasting model is developed. The topic-based text mining and expert judgment approaches are combined to forecast the technology trends efficiently and accurately. To improve the reliability of the results, multidimensional information including scientific papers, patents, and industry data is considered. Then, the model is utilized to forecast the development trends of self-driving technology in China. Data ranging from 2002 to 2019 are adopted with proper data cleaning. Topic clustering for papers and patents is performed, and the hierarchical structures are constructed. On this basis, the results of technology's evolution based on papers and patents are compared and the development trends are obtained. With these results, it is speculated that technology on "Decision" will be the next hotspot in patents. The research results of this paper will provide reference and guidance for Chinese enterprises and government in decision-making on self-driving technology. [ABSTRACT FROM AUTHOR]

In the context of the rapid development of multimedia and information technology, machine translation plays an indispensable role in cross-border e-commerce between China and Japan. However, due to the complexity and diversity of natural languages, a single neural machine translation model tends to fall into local optimality, leading to poor accuracy. To solve this problem, this paper proposes a general multimodal machine translation model based on visual information. First, visual information and text information are used to generate a visual representation of perceptual text information. Then, the two modal information are encoded separately, and the proportion of visual information in the whole multimodal information is controlled by a gating network. Finally, experiments are conducted on the image description datasets MSCOCO, Flickr30k, and video dataset VATEX, respectively. The results show that the algorithm in this paper achieves the best performance on both the BLEU and METEOR evaluation metrics. [ABSTRACT FROM AUTHOR]

With the increasing frequency of scientific cooperation, research on the impact of scientific cooperation on scholars' scientific performance has become a hot topic in academic research. This paper mainly uses quantitative research methods such as bibliometrics and social network analysis to analyze the correlation between degree centrality, L-index, and scientific performance of the Chinese author of Physical Education and Training Science and draws the following conclusions: (1) degree centrality is positively correlated with the number of papers, average citations per paper, and H-index and (2) L-index is positively correlated with the number of papers, average citations per paper, and H-index. Unlike previous studies on scientific collaboration networks and scholars' performance that focused on traditional network characteristics indicators, this study introduces a new network characteristics indicator, L-index, through which the degree of collaboration between authors and other important authors in the research field can be better assessed, which also provides a new direction for research related to research collaboration networks and scholars' performance; at the same time, it also provides a theoretical basis for subsequent research on the utility of scientific collaboration, a reference for the assessment of the research performance of scholars in other disciplines, and a theoretical reference for more scientific and comprehensive prediction of scholars' research performance in the future. [ABSTRACT FROM AUTHOR]

As the fastest-growing crowdfunding model, equity crowdfunding (ECF) brings high returns and uncertainty. In this context, it is crucial to understand these crowdfunding projects' actual performance. Since ECF is currently in the early stage of integration, there are still a lot of risk issues, such as the uncertainty of equity structure, capital supervision, or project management. Therefore, this paper develops a new profitability indicator, "return on registered capital," to test its impact on the ECF project's actual return. This paper studies which factors affect the financial performance of ECF projects through the traditional statistical model and a deep neural network (DNN) model. There is evidence that return on registered capital affects the actual return of the project. At the same time, the company's operating time and the number of employees had an unexpected effect on project performance. In addition, the recognition accuracy of the DNN model in this study exceeds 97%, which affirms the applicability of the DNN model in the analysis of ECF success factors. This paper also uses tenfold cross-validation to prove that deep learning has certain advantages in this topic's accuracy and generalization error. This study explores whether company representatives' gender and knowledge level affect project performance. The results will be described in detail in the paper. [ABSTRACT FROM AUTHOR]

With the steady increase of air traffic column, an auxiliary decision tool is required to compensate the operation redundancy deficiency of more sectors of air traffic control. To solve the problem of nonconflict high-density departure and arrival traffic flow, this method is expected to rapidly establish and maintain safe separation with more flexible changing strategies for aircraft heading and speed. This paper proposes an improved reinforcement learning framework to achieve conflict detection and resolution. The proposed framework includes the first development of an air traffic flow model based on a multiagent Markov decision process. The goal reward function was then maximized by improved Monte-Carlo tree search combined with an upper confidence bound tree. Three simulation scenarios were designed for illustrating the improvements of the proposed algorithm, with the results indicating that the algorithm could establish and maintain safe separation between 20 agents in the simplified hexagon-shaped airspace of Huadong, China. Furthermore, the proposed method was demonstrated to reduce the number of conflicts between aircraft agents by up to 26.32% compared to previous research. [ABSTRACT FROM AUTHOR]

With the construction of a new-type power system under the China "double carbon" target and the increasing diversification of the energy demand on the user side, the short-term load forecasting of the power system is facing new challenges. To fully exploit the massive information contained in data, based on the graph convolutional network (GCN) and long short-term memory network (LSTM), this paper presents a new short-term load forecasting method for power systems considering multiple factors. The Spearman rank correlation coefficient was used to analyse the correlation between load and meteorological factors, and a model including meteorology, dates, and regions was established. Secondly, GCN and LSTM are jointly used to extract the spatial and temporal characteristics of massive data, respectively, and finally achieve short-term power load prediction. Historical electrical load data from 2020 to 2022 public data of a real industrial park in southern China were selected to verify the validity of the proposed method from the aspects of forecasting accuracy, feature dimension, and training time. [ABSTRACT FROM AUTHOR]

With the rapid development of the real estate industry in China, urban air quality is inevitably affected. By using data of Chinese cities located in the Yangtze River Delta from 2009 to 2018, this paper is aim at examining the casual impact of house prices on air quality. By considering the endogenous problems, in this study, first, the birth rate of the previous six years and the area of state-owned land supply per capita in the previous year are taken as instrumental variables of house price. Second, the two-stage least squares method is used to assess the causal impact of house price on air quality. The findings of this study show that there is no significant relationship between urban house prices and air quality, and these results are obtained without considering the endogenous problem. While, after considering the endogenous problem, urban house prices showed a significant negative effect on overall air quality, especially for low administrative level cities. The increase in house prices has hindered the improvement of air quality mainly through the blind-scale expansion of real estate development investments and the inhibitory effect of innovation. [ABSTRACT FROM AUTHOR]

In this paper, a vehicle-bridge coupling dynamic model is established considering the vertical wheel-rail tight contact and the lateral simplified wheel-rail creeping. Through the site test and the numerical calculation, the dynamic deflections and the stresses of the U-shaped girder in the Nanjing S6 Urban Rail Transit in China are obtained, and the effectiveness of the established numerical model is verified. By changing the vehicle types and speeds, the dynamic amplification coefficients (DAFs) of the vertical deflections and the biaxial stresses at the girder bottom including the key points at the plate and section intersections are calculated. The research shows that the distribution of the lateral stresses is more complex than that of the deflection and the longitudinal stresses. Based on the calculation results considering various vehicle types, it is suggested that the DAFs of the vertical deflections and the longitudinal stresses are taken as 1.30, and the DAF of the lateral stresses remains at 1.40 as stipulated by the code. The research of this paper is to provide a reference for the structural design and size optimization of the U-shaped girders for urban rail transit. [ABSTRACT FROM AUTHOR]

Since the reform and development, after decades of changes in the times, China's basic education reform has been promoted several times, and the degree of information technology in the campus will become one of the important factors for parents to choose this school or not. From digital projectors since 2003 to multimedia-assisted English teaching nowadays, it is evident that online English teaching has become an important part of today's English online resources, but most of the English online resources nowadays are developed by professional research institutions, which leads to a situation where online English curriculum resources are not closely connected to the actual English teaching mode, and more importantly, there is a lack of online English course resources and they are outdated. In the new curriculum reform requirements, the development and utilization of English online resources are clearly pointed out, which shows the importance of developing and utilizing English online course resources and the need to develop in the direction of innovation and modernity, and the need to consider combining the development and utilization of English online course resources with modern technological progress, not only at the theoretical level but also at the practical level. English is a comprehensive and practical language that needs to be used and reinforced by users in order for them to be able to communicate and express their thoughts in English. In this paper, we adopt a fuzzy neural network approach and a gradient descent algorithm to address the shortcomings of current English online course resource development and utilization, and adopt an averaging process for weight updates, and then realize the control of the number of fuzzy rules by adding pooling operations. The experimental results show that this paper can effectively develop English online resources. [ABSTRACT FROM AUTHOR]

In recent years, China's economy has been developing rapidly, and people's life and quality of life have been improving; more importantly, people's habits and living habits have also developed from the previous "unhygienic" and "not very careful" to the current "Healthier, more hygienic, greener and more sophisticated" direction. In the process of this development, due to the rapid development of the economy and the industrialization of cities, the incidence of heart disease is also increasing year by year. According to relevant studies, China's urbanization process has been unprecedented, the number of urbanized people in China has exploded in recent years, and the ratio of urban to rural population has increased from about 20 percent to about 75 percent today. The effects of the population and the urbanization of urban architecture are affecting people's physical and mental health, both consciously and unconsciously, causing both positive and negative physical and mental effects on the psychological and physical levels. In this paper, the concept of deep learning is fully utilized to train the CNN neural network model and apply it to the ECG abnormality recognition and prediction examination. In order to fully validate the application and significance of deep learning in ECG abnormality identification and prediction, the whole project was completed through subjective and objective experiments. The experimental results show that, from the subjective aspect, the ECG examination has been accepted by most people for different age groups, and the analysis results of the ECG examination with the deep learning model in this paper are more satisfactory; from the objective aspect, the CNN-ECG abnormality recognition prediction network model trained in this paper has high. The accuracy of the model for ECG abnormality recognition prediction can reach 86% when the learning rate is set to 0.0001 and the batch size is set to 120, and the model can reduce the burden of medical personnel to a certain extent. [ABSTRACT FROM AUTHOR]

China's renewable energy products have an important place in international trade, and the conclusion of the RCEP agreement can create favourable external conditions for China's renewable energy product exports. This paper measures the export potential of China's renewable energy products to other RCEP countries through a trade gravity model. The results show that (1) the GDP of the importing and exporting countries, the energy consumption of the importing countries, and the particulate emissions damage significantly enhance China's renewable energy product exports; (2) among the RCEP countries, China has a greater potential to export renewable energy products to five countries in 2020, which are mainly located in East and Southeast Asia; and (3) from a dynamic perspective, China's renewable energy trade potential is increasing, while in the Oceania region it is weakening, while trade links to Southeast Asian countries are developing in a more mature direction. Based on the above research, this paper puts forward corresponding policy recommendations. [ABSTRACT FROM AUTHOR]

Accurate risk assessment of international scientific and technological (S&T) cooperation is significant to international cooperation. In this paper, 5 risk dimensions with respect to the political, economic, social, cultural as well as technological of the regional comprehensive economic partnership countries (RCEP) are selected to establish a proper S&T cooperation index system for risk assessment. To calculate the weight of each index, a cross-entropy combination weighting method is proposed based on the combination weighting method of game theory. Furthermore, the standard cloud model is constructed by using the golden ratio, and the risk of S&T cooperation among the RCEP countries is analyzed by the cloud model. The results show that the combination weighting method proposed in this paper is effective, and its calculation is simpler than that of the game theory combination weighting method. Besides, compared with political, social, cultural, and technological indicators, economic indicators have a greater impact on S&T cooperation risk. Furthermore, it is also obtained from the results that the risk of S&T cooperation with China and the Philippines is at a lower to low level and medium to higher level, respectively, and the risk of S&T cooperation with other countries is all at a lower to medium level. [ABSTRACT FROM AUTHOR]

Toll-gates are crucial points of management and key congestion bottleneck for the freeway. In order to avoid traffic deterioration and alleviate traffic congestion in advance, it is necessary to predict and evaluate the congestion in toll-gates scattering in large-scale region of freeway network. In this paper, traffic volume and operational delay time are selected from various traffic indicators to evaluate congestion considering the particular characteristics of the traffic flow within the toll-gate area. The congestion prediction method is designed including two modules: a deep learning (DL) prediction and a fuzzy evaluation. We propose a modified deep learning method based on graph convolutional network (GCN) structure in the fusion of dilated causal mechanism and optimize the method for spatial feature extraction by constructing a new adjacency matrix. This new AI network could process spatiotemporal information of traffic volume and operational delay time, that extracted from large-scaled toll-gates spontaneously, and predict key indicators in 15/30/60 min future time. The evaluation module is proposed based on these predicted results. Then, fuzzy C-means algorithm (FCM) is further modified by determining coupling weight for these two key indicators to detect congestion state. Original traffic data are obtained from the current 186 toll-gates served on the freeway network in Shaanxi Province, China. Experimental tests are carried out based on historical data of four months after preprogressing. The comparative tests show the proposed CPT-DF (congestion prediction on toll-gates using deep learning and fuzzy evaluation) outperforms the current-used other models by 6-15%. The successful prediction could extend to the real-time prediction and early warning of traffic congestion in the toll system to improve the intelligent level of traffic emergency management and guidance on the key road of disasters to some extent. [ABSTRACT FROM AUTHOR]

Automatic heavy-haul train (HHT) operation technology has recently received considerable attention in the field of rail transportation. In this paper, a discrete-time-based mathematical formulation is proposed to address the speed profile optimization problem in order to ensure the safe, efficient, and economical operation of heavy-haul trains (HHTs). Due to the presence of long and steep downgrades (LSDs) on some heavy-haul lines, the brake forces of the HHT are typically jointly determined by air braking and electric braking. The time characteristics of the air braking, such as the command delay and the change process caused by the air pressure, are taken into account, and then formulas are presented to calculate the air brake force. In addition, the influence of the neutral section on the control of the electric braking is considered via space-based constraints. The resulting problem is a nonlinear optimal control problem. To achieve linearization, auxiliary 0-1 binary variables and the big-M approach are introduced to transform the nonlinear constraints regarding slope, curve, neutral section, air brake force, and air-filled time into linear constraints. Moreover, piecewise affine (PWA) functions are used to approximate the basic resistance of the HHT. Finally, a mixed integer linear programming (MILP) model is developed, which can be solved by CPLEX. The experiments are carried out using data from a heavy-haul railway line in China, and the results show that the proposed approach is effective and flexible. [ABSTRACT FROM AUTHOR]

Foundation settlement prediction is significant to the reuse and management of the reclaimed land from the sea by dykes where composite stratum of many strata with different physical and mechanical properties is encountered. Toward the foundation settlement analysis of reclaimed land in the Yellow Sea composite stratum in eastern China, a weighted-combination model is proposed in this paper combining the hyperbolic model, exponential curve model, and Asaoka model. First, the weight coefficient of the weighted-combination model is calculated by the reciprocal square method of average absolute error (MAE). Second, the settlement prediction results of different models are evaluated by the absolute error, MAE, root-mean-square error, and mean absolute percentage error. Finally, the settlement mechanism of reclaimed foundations in a composite stratum is analyzed from the point of view of the multistratum coupling, and the adaptability of different models to the settlement prediction of reclaimed foundations in a composite stratum is discussed. The results show that the predicted settlement duration curves of the weighted-combined model are in good agreement with the measured settlement duration curves, and the prediction performance is better than that of the hyperbolic model, exponential curve model, and Asaoka model. The MAE of the weighted-combination model is 75.7% lower than that of the exponential curve model, 90.2% lower than that of the hyperbolic model, and 70% lower than that of the Asaoka model. This model provides a new way to predict the settlement of reclaimed foundations in a similar composite stratum. [ABSTRACT FROM AUTHOR]

Large temperature differences exist between the winter and summer seasons in different regions of China. Such temperature differences, caused by seasonal changes, may affect the life cycles of piles. Under natural conditions, such as long-term operation under the ambient environment and loads, piles and the surrounding soil undergo peel damage. To study such peel damage between the pile and soil at different temperatures, we installed concrete test piles in soil and subjected them to different temperatures. A crack with a width of 2 cm, depth of 10 cm, and damage range of 90° was applied at the side of the piles. Furthermore, a horizontal impact load was applied near the top of the pile and a piezoelectric ceramic sensor was used to obtain the stress wave response signals. The experimental results reveal that with a decrease in the soil temperature, the amplitude and fluctuation range of the signals received by the piezoelectric sensor decreased. According to the experimental results, in the group with the greatest influence of temperature, keeping other conditions unchanged and setting different crack depths, the horizontal impact load can also be introduced to observe the frequency change. It can be observed that the larger the crack depth, the smaller the frequency. Finally, ABAQUS was used for simulations, whose results were found to be consistent with those of the experiments. This paper describes a method for determining the safety of soil and piles with peel damage at different temperatures, and it also provides a validation of the necessity of holding the rest constant. [ABSTRACT FROM AUTHOR]

Aims. To understand what domains of acculturation are experienced by Chinese immigrants with cardiovascular disease (CVD) in Australia and how these domains of acculturation influence their CVD self‐care behaviours. Design. A qualitative descriptive design. Methods. Individual phone interviews were conducted among Chinese immigrants with CVD in Sydney, recruited from Chinese Community associations and social media. Inductive and deductive thematic analysis was employed, guided by the Middle‐Range Theory of Self‐Care of Chronic Illness and the conceptual model of acculturation. Results. Twenty participants, mean age 69.9 years, were interviewed. The domains of acculturation in relation to CVD self‐care behaviours encompassed cultural practices, cultural values, healthcare system navigation, and new living environment. Retaining their Chinese culture and integrating into Australian culture regarding dietary practices, social networks, traditional values and family relationships served as both enablers and barriers of self‐care maintenance through factors such as heart‐healthy diets, physical activity, stress management and medication adherence. Many participants denied encountering difficulties to utilize primary care services, but language barriers deterred them from accessing acute services and heart‐health information from mainstream sources. Some preserved beliefs and practices in Traditional Chinese Medicine may complicate their self‐care maintenance (medication adherence) and self‐care management (responding to acute angina episodes). Conclusion. The influence of acculturation on CVD self‐care behaviours among Chinese immigrants is multifaceted and individualized. Clinicians and community health workers should assess patients' acculturation experiences to enable culturally sensitive practices. The lack of culturally and linguistically appropriate heart health information in the community should be addressed urgently to mitigate the cardiac health disparity. Collaboration with Chinese community associations offers an opportunity for co‐design and dissemination of information about Australian healthcare systems and heart health education to upskill CVD self‐care practices and mitigate the health inequities experienced by Chinese immigrants. [ABSTRACT FROM AUTHOR]

Objective. Intrahepatic cholestasis of pregnancy (ICP) significantly impacts the maternal and fetal safety. Research on the role of clinical pharmacists in guiding drug therapy for this condition remains limited. This study aimed to evaluate the effectiveness of graded pharmaceutical care for women with intrahepatic cholestasis of pregnancy and to provide a theoretical foundation for clinical pharmacist services. Study Design. This study comprises a pre‐and‐post analysis of women with intrahepatic cholestasis of pregnancy (ICP) treated between December 2019 and June 2023 at a tertiary hospital in Jiangsu province. Each group consisted of 102 participants. The control group received standard treatment, while the guardianship group received graded pharmacological care provided by a clinical pharmacist. The effectiveness of pharmacological monitoring by clinical pharmacists was assessed by comparing and analyzing clinical outcome indicators, quality management indicators, safety indicators, and economic factors. Results. The guardianship group exhibited a noteworthy 12.8% reduction in combined adverse pregnancy outcome and more effective management of total prenatal bile acids compared to the control group (16.05 µmol/L vs. 22.85 µmol/L, P < 0.05). The guardianship group displayed superior rationalization of therapeutic drugs and medication duration (P < 0.05). The cost‐benefit analysis revealed a favorable economic impact concerning medication costs but did not indicate economic significance regarding total inpatient costs. Conclusion. The implementation of a graded pharmaceutical care model by a clinical pharmacist holds the potential to enhance outcomes for women experiencing intrahepatic cholestasis during pregnancy, mitigate adverse pregnancy results, optimize the rational utilization of therapeutic medications, and yield positive economic results. [ABSTRACT FROM AUTHOR]

This study examined the associations between community social capital and self‐reported oral health among older adults in urban China, as well as the moderating effect of household income and the mediating role of depressive symptoms in these associations. Data were obtained from a community survey conducted in 2020 in Tianjin and Shijiazhuang City, China; the final analytical sample comprised 776 adults aged 60 years and above. To test the proposed moderation and mediation models, the data were analysed using binary logistic regression models and a path analysis, respectively. The findings showed that cognitive social capital and social participation (i.e., an indicator of structural social capital) were significantly associated with self‐reported oral health. Additionally, the results revealed that while income significantly moderated the association between cognitive social capital and self‐reported oral health, depressive symptoms significantly mediated it. The findings not only highlight the crucial role of community social capital in promoting oral health in later life among low‐income older adults but also provide important evidence for a psychosocial pathway between social capital and oral health. Given the impacts of income and depressive symptoms on the relationship between community social capital and oral health among older adults, future social policies and interventions to support oral health should target financially vulnerable older adults with poor psychological well‐being. [ABSTRACT FROM AUTHOR]

Tourist resorts play a crucial role in providing people with diverse and high-quality leisure and vacation options. The development of tourist resorts is integral to the high-quality growth of the national tourism industry. This study utilizes a combination of the nearest neighbour index, kernel density analysis, and geographic concentration index to examine the spatial and temporal distribution of 758 national and provincial tourist resorts in China. The analysis reveals several key findings: (1) the years 1992 and 2015 were pivotal for the development of China's tourist resorts, with significant government attention and steady growth in the number of national tourism resorts from 2015 to 2023. (2) The distribution of China's tourist resorts shows an overall uneven distribution at a national level but a more balanced distribution locally. The southeast region exhibits a high and even distribution density, while the northwest region has a lower density and quantity of resorts. (3) Some specific areas have emerged such as the junction of Anhui, Hubei, and Jiangxi provinces as the first core gathering areas and the junction of Shanxi, Jiangsu, and Zhejiang provinces as the secondary core areas. These core areas have gradually weakened and spread to other regions, leading to changes in the distribution patterns of tourist resorts. (4) The distribution of China's tourist resorts is influenced by various factors, including economic development, resource endowment, source market, and government support. Government support is a key factor in accelerating the development of tourism resorts. These findings shed light on the complex dynamics shaping the distribution of tourist resorts in China. [ABSTRACT FROM AUTHOR]

From the emergence of the concept of the Internet of Things to today, China has always been very concerned about the development of the Internet of Things technology. The research and application of Internet of Things technology has become an important measure for the country to promote supply-side reform. The Internet of Things technology is the core innovation content of the country and an important measure to realize the smart city. This paper analyzes the cutting-edge research results in the field of Internet of Things abroad. This paper focuses on the application of IoT technology in English terminology research. This paper specifically analyzes the feature extraction methods of Internet of Things terms and studies the application content of Internet of Things technology in English-Chinese translation. We specifically conduct translation research on the content in "The Internet of Things: Enabling Technologies, Platforms, and Use Cases," focusing on the translation of scientific and technological terms. As a kind of technical English terminology, IoT English terminology has the characteristics of strong professionalism and rigorous semantics. This article specifically translates the original part of the practice report and classifies the terms that appear in it, including IoT English terms for which canonical translations have been made and IoT English terms that do not have standardized translations. The research will further carry out the investigation and analysis work. The research is to identify the terms that have standardized translation, especially the detailed research of the terms of the industry field. This paper selects standard translations and summarizes the translation methods of terms from three aspects: abbreviations, compound words, and semi-technical words. The research results provide guidance for terminology translation. This article translates terms that do not yet have a canonical translation. Based on terminology characteristics and existing terminology translation methods, this paper proposes a variety of translation methods such as literal translation, decomposing and combining, and non-translation. The study described in detail with examples. The research results of this paper are expected to provide some reference for translators engaged in the translation of scientific and technological documents. [ABSTRACT FROM AUTHOR]

Facing the dual background of risk society and the fourth scientific and technological revolution, digital emergency management (DEM) research has attracted wide attention worldwide. Based on the comparative analysis of data from Web of Science (WOS) and China National Knowledge Infrastructure (CNKI) databases, the research draws the knowledge map by CiteSpace, in order to analyse the spatiotemporal distribution, hotspots, and trends of DEM research. The following are the results: (1) DEM research shows a spiral growth, with a significant increase in the number of papers. Existing highly cited references are mainly carried out from the perspective of management or technology. (2) The complex countries' cooperation network has been formed from the USA, China, and other countries; the complexity of the institutions' cooperation network must be strengthened, and the density of the authors' cooperation network is low; DEM research has significant interdisciplinary attributes. (3) The hotspots of DEM research can be divided into three categories: means, processes, and objects, but the research emphases between international and China are different. (4) The evolution of DEM research can be divided into three stages between international and China: embryonic, development, and deepening stages, and research contents in each stage show some differences. (5) The trends of DEM research between international and China are different. The former are information technology, artificial intelligence, and machine learning, whereas the latter are emergency decision making, scenario analysis, and public health. [ABSTRACT FROM AUTHOR]

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