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Permafrost is a significant part of the cryosphere, which has gained increasing attention from scientists, policy-makers, and the general public due to global warming, environmental degradation, water shortages, and intense human activities. Although many permafrost research review articles have been published, these studies were predominantly limited to either one subject or one field, while systematic studies about permafrost based on bibliometric analysis methods remain limited. We aim to fill this gap by conducting a bibliometric analysis of 13,697 articles in the field of permafrost research from 1942 to 2021, collected from the Web of Science core collection database. The results indicate that permafrost research is a typically multi-author, multi-country, and multi-institution cooperative field, involved in many research fields. The cumulative number of publications has presented an exponential increase over the past 80 years, with an average annual growth rate of 10.40%. Since 2000, China has seen a rapid growth in the number of publications per year, surpassing the USA in 2016 and leading in the years since then. In addition, the authors from China have great contributions in publications, and there is good room for permafrost development in the future according to the authors' M-index ranking. After the analysis of authors' keywords, we found that, compared to the conventional methods, machine learning and interferometric synthetic aperture radar (InSAR) are new technological approaches introduced in recent years, and the Qinghai–Tibet Plateau has become a popular study area. The results presented here can help related researchers, scholars, and students in the field to better understand the past developments, current status, and future trends of permafrost research. Furthermore, this paper presents and expands the general process of the bibliometric method used in permafrost studies, which can provide researchers with new inspirations and improve discipline research approach. [ABSTRACT FROM AUTHOR]

Drylands are vast and face threats from climate change and human activities. Traditional reviews cannot capture interdisciplinary knowledge, but bibliometric analysis provides valuable insights. Our study conducted bibliometric research of scientific production on climate change and land degradation in drylands using remote sensing. We examined 1527 Scopus-indexed publications to identify geographic and thematic hotspots, extracting leading authors, journals, and institutions. China leads in publications, followed by the US, Germany, and Australia. The US has the highest citation count. Collaboration networks involve the US, China, and European countries. There has been an exponential increase in remote sensing of land degradation in drylands (RSLDD) publications since 2011. Key journals include "International Journal of Remote Sensing" and "Remote Sensing of Environment". The analysis highlights the growing interest in the field, driven by Australia, the US, and China. Key areas of study are vegetation dynamics and land use change. Future perspectives for this scientific field involve promoting collaboration and exploring emerging technologies for comprehensive land degradation and desertification research. [ABSTRACT FROM AUTHOR]

Transportation infrastructure is essential to regional innovation systems, and the high-speed railway (HSR) is reshaping China's regional innovation pattern. Previous research lacks an analysis of the impact of opening an HSR on urban traditional and green innovation. This paper uses urban panel data from 285 prefecture-level cities in China from 2003 to 2019 to study the impact and mechanism of opening an HSR on urban innovation from a comparative perspective. The results of a multi-period difference-in-difference (DID) model show that opening an HSR can promote both traditional and green urban innovation, especially impacting urban green innovation. A further analysis of the mechanism of action found that high-quality talent and communication infrastructures are two crucial mechanisms of transmission for the opening of an HSR to affect urban innovation. In addition, heterogeneity analysis showed that opening an HSR promotes traditional urban and green innovation for cities in general. However, for central cities, the opening of an HSR has no significant impact on green innovation and has little effect on promoting traditional innovation. The policy inspiration of this paper is that, in the face of an innovation gap and the inequality of regional innovation and development, the construction of HSRs should be promoted according to local conditions. Construction and layout resources should be shifted from central cities to general cities to narrow the regional innovation gap. In addition, it is necessary to pay attention to the roles of the flow of high-quality talent and communication infrastructure in promoting urban innovation and sustainable urban development. [ABSTRACT FROM AUTHOR]

Imported air pollution has a significant impact on urban air quality. Relevant studies have shown that many urban air pollution events are not resourced by local emissions but are imported by air pollution from surrounding areas transported across regions. The prevention and control of air pollution is very necessary. However, the existing supervision of urban air quality mostly relies on ground monitoring stations, which are extremely limited in time and space, and cannot satisfy continuous time-space air pollution research. Therefore, aiming at the problem of urban air pollution control, this paper used MERRA-2 reanalysis data and ground monitoring data to establish a "Time-Longitude-Latitude" three-dimensional pollution curve, and then a genetic algorithm was used to optimize its fitting. This study finally reconstructed the imported air pollution transmission route. This paper takes an air pollution event that occurred in Xuzhou City, China, on 12 January 2020, as an example. Through the analysis of aerosol optical depth (AOD), particulate matter (PM), wind speed, and other factors, we found the source, transmission route, and impact time of this pollution. We have verified the correctness and accuracy of the reconstructed contamination transport paths. It is proved that the method is universal and it can quickly and accurately restore the air pollution transmission route and identify the urban imported air pollution transmission entrance. This method will also provide strong data support for the division of responsibilities of environmental protection departments in various regions for severe air pollution transmission events and provide effective governance ideas for the prevention and control of imported air pollution in recipient cities. [ABSTRACT FROM AUTHOR]

Philosophies in the East and West have favored wisdom in their search for truths. The Chinese civilization has sought holistic wisdom in its long history of absorbing the Abrahamic faiths since the seventh century. This paper aims to investigate how the Abrahamic faiths have interacted with ancient Chinese culture. In particular, this paper will examine the earliest written records in Chinese of the Luminous Religion (or Jingjiao), the earliest Jews in Kaifeng, and the earliest Muslims in China. By analyzing their theology of creation with reference to the Holy Spirit and qi (wind/breath/pneuma), this paper attempts a constructive Chinese natural theology based on a sympathetic and critical assessment of Alister McGrath's natural theology but makes up for his spirit deficit. This paper argues that the holistic wisdom achieved in the early integration process of the Abrahamic faiths with the Chinese culture is closely intertwined with the Spirit and qi, which provides a fruitful ground to construct a Chinese natural theology. The contribution of this paper lies in its original research into the earliest written records of the three Abrahamic faiths in China from the perspective of the doctrine of creation and its relationship with the Spirit and qi. [ABSTRACT FROM AUTHOR]

China's sea surface area is vast, the need to monitor the area is too large, and the traditional human monitoring method consumes a lot of manpower. Additionally, the monitoring period is too long; the monitoring efficiency is too low; and long-term human monitoring can easily cause visual fatigue, as well as missed detection and error detection. At present, the detection of sea surface targets generally includes infrared, visible light and other different means, which can obtain the image information of sea surface targets in different ways. The infrared target detection of the sea surface can be processed in the spatial domain and frequency domain, respectively, but the image resolution is not high in general, and the detection effect is not good because it is easily affected by weather. In this paper, we propose a maritime target detection method based on embedded vision. Based on visible video images, this paper realizes the rapid detection and recognition of sea surface targets. Clouds and waves in ocean images are filtered by adding an image preprocessing module. Compared with the traditional two-frame difference method, this algorithm has better detection capability for sea surface targets. Experiments were carried out in different weather conditions to detect moving ships at sea. By comparing the number of detection boxes and the detection accuracy, the accuracy of this method reaches 90.2 percent. By designing a single camera location algorithm for the marine environment, the world coordinate location of the marine target is realized. On this basis, the communication function is added to realize the intelligent monitoring of the sea surface without human intervention. [ABSTRACT FROM AUTHOR]

In China, table tennis has always been one of the most popular sports, with small field restrictions and it is simple and fun to play. But what is unknown is that with China's major table tennis events thriving, the psychological pressure of table tennis players' training is also increasing. However, the existing training methods obviously do not pay enough attention to psychological training, and there is no complete system for psychological training. Although the current dynamic heart rate measurement method can play a certain role in the detection, there is still the disadvantage of low detection accuracy. The heart rate is an important sign of life, and the monitoring of the heart rate of table tennis players should be strengthened, reflecting the functional state of the athletes' heart, and facilitating the more intuitive adjustment of the psychological training method of athletes. The heart rate measurement method based on face recognition contains a plate content that is rich. Through deep learning face recognition, the heart rate measurement method has high calculation efficiency, can effectively eliminate the influence of other external environmental factors, can use video recording, and can use face recognition and physiological parameters' quantification to monitor athletes' heart rate changes in real time; the visible artificial intelligence auxiliary diagnosis potential is huge. To this end, this paper aims to provide effective suggestions for the psychological training of table tennis players with deep learning as the technical support. In response to this, the aim of this paper was to design a deep learning-based face recognition heart rate measurement method that judges the psychological fluctuations of athletes through changes in heart rate. We conducted a questionnaire survey with the table tennis players of the Hunan team as the object of investigation, so as to understand the source of the psychological pressure of athletes and make reasonable suggestions. The experimental results of this paper show that the heart rate error of the video heart rate measurement algorithm is within 3% in the calm state and within 4% in the post-exercise state. This can effectively measure psychological fluctuations, and through investigation and research, it can provide an effective method for the psychological training of table tennis players. [ABSTRACT FROM AUTHOR]

Since the reform and opening up, the socioeconomic status of women in rural China has risen rapidly. However, unlike men, women have not been able to earn higher wages by "working in all directions". Based on the interview data of 2064 migrant workers, this paper explores the nonlinear interaction of individual characteristics and urban geographic factors with gender differences in migrant workers' wages with the help of random forest regression models. The results show the following: (1) migrant workers' wages show obvious gender differences in different dimensions, but in general, men's wages are higher than women's wages; (2) there are also gender differences in the influencing factors of migrant workers' wages. Work experience is more important for male migrant workers' wages, age is more important for female migrant workers' wages, and there is a variable effect of each factor on migrant workers' wages. This paper is of great help in understanding the travel trajectories of migrant workers and gender differences in wages and holds reference value for guiding migrant workers in choosing jobs and places and increasing their income. [ABSTRACT FROM AUTHOR]

With the rapid development of the Internet and digital technology, digital infrastructure has become an important part of urban infrastructure. Many cities are enacting smart policies to promote the development of digital technology infrastructure. However, what are their mechanisms? There is currently a shortage of literature on the subject. This paper tried to solve this problem and used China as an example. Using panel data from cities in China, this paper used the spatial multiple-period difference-in-difference (SDID) method to investigate the impact of smart city policy (SCP) on digital infrastructure. First, we found that SCP significantly promotes the construction of digital infrastructure, with strong positive spatial spillover effects. This result remained valid after a series of rigorous robustness tests. Second, we discovered that the indirect effects of policy implementation outweigh the direct effects. Furthermore, smart city development enhances local government investment in digital infrastructure, attracts more high-tech enterprises, and consequently drives improvements in urban digital infrastructure levels. Lastly, we observed that the effectiveness of smart city policies is stronger in cities with good fiscal conditions, strong economic development, and a thriving digital economy. This research will not only enrich research on smart cities but also provide policy recommendations for strengthening digital infrastructure. [ABSTRACT FROM AUTHOR]

With the deepening of modernization in China, the situation of air environmental pollution in China is very serious, and the environmental capacity is becoming less and less. Haze has gradually become one of the main sources of pollution in most cities in China. Volatile organic compounds (VOC) have the activity of participating in photochemical reactions and can participate in a variety of complex reactions in the atmosphere to promote the formation of haze and ozone. Through the experiment of daily ceramic flower paper baking, it can be concluded that the burning loss of flower paper accounts for more than 60% of the total quality of flower paper, and most of them are between 60% and 80%. Among them, the burning loss of PVB flower paper is about 80%, the water transfer paper is about 60%, and the low temperature flower paper is about 86%. In the experiment, the VOC proportion of low temperature flower paper, the PVB paper and water transfer paper accounted for 3.17%, 0.92% and 0.45%, respectively. Through the wax removal experiment of special ceramics molded by hot pressing, it is found that paraffin wax, beeswax and oleic acid are used as binders, and the amount of VOC emitted is also different when the dosage range is different; in addition, the burning loss is generally between 10% and 20% in the process of wax removal. The content of VOC in flue gas is about 0.42%, accounting for 0.046% of special ceramics. It provides an important basis for the calculation of VOC generated during the process of ceramic flower baking. [ABSTRACT FROM AUTHOR]

The precise and visual analysis of solid waste recycling in concrete construction engineering is critical for the development of ecological civilization and for the secure supply of resources. This research makes a bibliometric analysis of the solid waste application in concrete construction engineering from 2000 to 2021 based on the Web of Science. The global bibliometric status, current research focus and future directions were used to indicate the global development of solid waste recycling in concrete construction engineering. The most reused solid wastes and most solid waste productive regions were concluded with this bibliometric analysis. China is far ahead of other countries in solid waste recycling in all aspects and heavy metal is one of the most prominent solid waste themes in China. By analyzing the most studied solid waste, fly ash appears to be the most popular and is widely used; half of the top ten-cited papers are correlated with it. [ABSTRACT FROM AUTHOR]

The Qinghai-Tibetan Plateau (QTP), known as the "Third Pole of the Earth", contains fragile ecosystems and is sensitive to global environmental changes. With the intensification of climate change and human activities, the land cover of the QTP is changing significantly, which affects its function as an ecological security barrier. This paper searched 379 papers in the Web of Science core database, conducted a bibliometric analysis, and proposed potential future research directions to gain a macroscopic understanding of the impact of land use and cover change (LUCC) on the regional and global ecological environment of the QTP. The results are as follows. (1) The period from 1995 to 2022 witnessed an overall increase in the number of publications in this field with a high development potential. (2) Climate change, land use, China, impacts, conservation, and management were high-frequency keywords in the field; among these, climate change has received increasing research attention since 2018. (3) The field included three main research directions: the impact of LUCC on biodiversity, the impact of land degradation on ecosystems, and the impact of climate change and land use changes on ecosystem services. (4) The development and evolution of research hotspots were mainly focused on three aspects: the impact of cultivated land expansion and deforestation, the impact of land use management and conservation, and the impact of climate change and human activities on LUCC. (5) Future research should focus on improving the accuracy of land use and cover data on the QTP, assessing and preventing the ecological risks of LUCC, investigating the impacts of human activities on LUCC and the ecological environment, and exploring the interactions between climate change and human activities on the ecological environment. The findings of this paper will help researchers and stakeholders gain a rapid and comprehensive understanding of this research area and thus contribute to the sustainable development of the QTP. [ABSTRACT FROM AUTHOR]

With the massive use of lithium-ion batteries in electric vehicles and energy storage, the environmental and resource problems faced by used lithium-ion batteries are becoming more and more prominent. In order to better resource utilization and environmental protection, this paper employs bibliometric and data analysis methods to explore publications related to waste lithium-ion battery recycling from 1984 to 2021. The Web of Science core set from the SCIE online database was used for this article. These findings demonstrate a considerable increase trend in the number of publications published in the subject of recycling used lithium-ion batteries, with a natural-sciences-centric focus. Argonne National Lab, Chinese Academy of Sciences, and China Academic and Scientific Research Center are the top three institutions in terms of quantity of papers published. The affiliated journals corresponding to these three institutions also have high impact factors, which are 106.47, 44.85, and 58.69, respectively. In comparison to comparable institutes in other nations, the American Argonne National Laboratory supports 223 research articles in this area. China and the US make up the majority of the research's funding. The two key aspects of current lithium-ion battery recycling research are material structure research and environmentally friendly recycling. Nevertheless, high-capacity lithium-ion batteries, waste lithium-ion integrated structures, and gentle recycling of spent lithium-ion batteries will be the major aspects of study in the future. It is hoped that the above analysis can bring new ideas and methods to the field of waste lithium-ion battery recycling and provide a basis for the subsequent research and application of waste lithium-ion battery recycling. [ABSTRACT FROM AUTHOR]

As one of the most important examinations in China, the National College Entrance Examination (commonly known as the Gaokao, hereafter denoted Gaokao) has a long history and has attracted attention from the Chinese educational community, among others. This study focused on mathematics test items of the Gaokao from the perspective of mathematical culture and examined the national papers (drafted by the Ministry of Education of the People's Republic of China) of tests from 1978 to 2021 in order to investigate the content and time variation characteristics of mathematics test items reflecting mathematical culture since its restoration. A mathematical culture categorization conceptual framework was established based on previous studies and was applied to test item analysis. Mathematical culture in test items was classified using four categories: Historical Topics, Interdisciplinary Connections, Social Roles, and Aesthetics & Recreation. These were used for data coding and analysis. The results showed that mathematical culture in the mathematics test items of the Gaokao over a 44-year period, in terms of content categories, was diverse but uneven in distribution, with greater focus on demonstrating the social roles of mathematics and less on the historical development of mathematical knowledge. Moreover, the average number of items with mathematical culture during this period was small and fluctuated over time. The content of topics related to social context and technology also changed over time with the distinct characteristics of the times and changes in society. This study provides empirical evidence on how mathematical culture is integrated into test items and how they have changed over time. [ABSTRACT FROM AUTHOR]

With the continuous development of China's economy and society, people and the government have higher and higher requirements for food safety. Testing for food dopants and toxins can prevent the occurrence of various adverse health phenomena in the world's population. By deploying new and powerful sensors that enable rapid sensing processes, the food industry can help detect trace adulteration and toxic substances. At present, as a common food safety detection method, lateral flow immunochromatography (LFI) is widely used in food safety testing, environmental testing and clinical medical treatment because of its advantages of simplicity, speed, specificity and low cost, and plays a pivotal role in ensuring food safety. This paper mainly focuses on the application of lateral flow immunochromatography and new technologies combined with test strips in food safety detection, such as aptamers, surface-enhanced Raman spectroscopy, quantum dots, electrochemical test strip detection technology, biosensor test strip detection, etc. In addition, sensing principles such as fluorescence resonance energy transfer can also more effective. Different methods have different characteristics. The following is a review of the application of these technologies in food safety detection. [ABSTRACT FROM AUTHOR]

Through extensive data research and analysis, this paper comprehensively summarizes the status and key insights of global carbon dioxide capture and storage (CCS) development. It aims to gain a comprehensive understanding of the relevant policies, technologies, and security measures adopted by major countries in their CCS development processes. Furthermore, it explores the existing status and limitations of China's offshore development efforts, while providing valuable recommendations for enhancing China's offshore CCS initiatives, as well as serving as a reference for other nations worldwide. Offshore CCS plays a crucial role for China to achieve the development target of carbon peak and carbon neutrality, due to its energy structure and industrial distribution. While China possesses significant offshore CCS potential, achieving commercialization still requires substantial efforts. To facilitate the process and draw insights from successful experiences in other countries, this paper illustrates the characteristics and generalizes the experience of offshore CCS industry practices in America, Europe and Japan, respectively. Furthermore, it is recommended that a new round of investigation into offshore CCS potential be conducted, while promoting integrated collaboration between geological surveying and marine scientific research. Additionally, further research on industrial policies and green financial strategies should be undertaken. [ABSTRACT FROM AUTHOR]

Shallow-water deltas serve as a critical area for the exploration and development of terrestrial lacustrine oil and gas reservoirs. Current research on oil and gas exploration and development in China's terrestrial lacustrine basins primarily focuses on their delta front facies zones. Despite extensive discussions on the sedimentary characteristics of shallow-water deltas by predecessors, there is a lack of comprehensive analysis on the combined effects of dynamic factors such as climate change, lake level fluctuations, and sediment supply. This paper, through a detailed examination of 12 core samples and integrating data from 493 exploratory, appraisal, and development wells in the study area, establishes a stratigraphic correlation framework using well–seismic integration techniques. It identifies two main sedimentary facies types in the southern Da'anbei area of the Songliao Basin: shallow-water deltas and lake facies, which can be further subdivided into four sub-facies and nine microfacies. Two depositional models for the shallow-water deltas of the Southern Songliao Nenjiang Formation are established: a deeper water background with channel-river mouth bar sequences forming the delta front framework and a shallower water background with channel-sheet sand sequences forming the delta front framework. This paper also discusses the controlling effects of paleoclimate, sediment supply, and lake level changes on sedimentary evolution, providing a scientific basis for the exploration of lithologic oil and gas reservoirs in the Nenjiang Formation of the study area and the deployment of horizontal wells. [ABSTRACT FROM AUTHOR]

Time series dynamic prediction of surface deformation in mining areas can provide reference data for coal mine safety and production, which has important impacts. The combination of interferometric synthetic aperture radar (InSAR) technology and the probability integral method (PIM) is commonly used for predicting deformation. However, most surface subsidence prediction in mining areas is based on the static PIM parameters, failing to achieve the three-dimensional (3D) dynamic deformation prediction. This paper proposed a 3D deformation dynamic prediction model (InSAR-3D-CTPIM) between InSAR deformation observations and dynamic coordinate-time PIM (CTPIM) parameters, which can realize the prediction of east–west, north–south, and vertical series deformation caused by mining. The method has been validated by simulation experiments and real experiments in the mining area of Jiansheng Coal Mine in Baisha Reservoir, Henan Province, China. The results showed that the modeling accuracy was improved by 34.3% compared to the traditional multi-rate model, and the accuracy was improved by 28.5% compared to the vertical deformation obtained by the traditional static PIM method. The InSAR-3D-CTPIM model can be used to predict the evolutionary history of basin-wide surface deformation dynamics in coal mining areas, and provide a reference for the early warning and prediction of geological hazards in coal mining areas. [ABSTRACT FROM AUTHOR]

The development and utilization of unconventional water resources has become a strategy to alleviate the agricultural water crisis in many countries and regions. To understand the research progress, hot spots, and future trends in the field of unconventional water agricultural irrigation (UWAI), this paper systematically analyzes 6738 publications based on the core database of Web of Science 1990–2023 using the scientific bibliometric analysis software CiteSpace, VOSviewer, and Scimago Graphica. The results showed that the research on UWAI is always rapidly developing. Soil science, crop science, and bioengineering are the main disciplines involved. Most research on WUAI has occurred in China and the United States. Countries with higher levels of development tend to have more influence. Collaboration among authors is fragmented, and collaboration between authors and states needs to be strengthened. Through keyword analysis, the research hotspots are summarized as follows: (1) The effects of traditional and emerging pollutants brought by unconventional water irrigation on soil physicochemical properties, crop growth, and groundwater quality; (2) the health threats caused by pollutants entering the food chain and groundwater; (3) unconventional water utilization technologies, including rainwater harvesting agriculture, precision agriculture, and urban agriculture. Future research hotspots will focus on the mechanisms of pollutant solute transport and transformation in the water–soil–crop system under non-conventional water irrigation conditions and crop physiological responses. We suggest that the research on traditional and emerging pollutants in unconventional water should be strengthened in the future, and the risk control system of unconventional water irrigation should be improved. International cooperation should be strengthened, especially with poor countries in arid regions, to promote the formation of unified international standards and guidelines for non-conventional water irrigation in agriculture. [ABSTRACT FROM AUTHOR]

Integrated ocean management (IOM) aligns with the United Nations' Sustainable Development Goals (SDGs) and serves as a crucial strategy for promoting the enduring health of marine ecosystems and the sustainable utilization of marine resources. An analysis of the evolution of China's integrated ocean management policy (IOMP) is crucial for providing valuable guidance in achieving sustainable growth in marine management and the marine economy for both China and other coastal nations worldwide. This paper studies the evolution characteristics, challenges, and prospects of IOMP in China since 1978 using content analysis. The findings indicate that the evolution of IOMP can be categorized into four stages: the germination period (1978–1998), the construction period (1999–2009), the systematization period (2010–2017), and the strategization period (2018–present), based on the state of international marine management. The IOMP has transitioned over time from its initial emphasis on resource development during the germination period to a strategization period that prioritizes the full development of all parts of the system. However, the ultimate goal has consistently been to achieve harmonious coexistence between people and the sea. China's IOMP has experienced a progressive development; nevertheless, it continues to encounter obstacles such as the pressing requirement to revise sea-related policies and the absence of policy alignment. The objective of this paper is to explore the evolution, challenges, and prospects of China's IOMP to better improve the land–sea coordination policy, strengthen international judicial cooperation. and provide effective policy reference for other maritime countries. [ABSTRACT FROM AUTHOR]

Sustainable agricultural development is a fundamental requirement and a crucial goal of modern agriculture. It is also a significant means of enabling farmers to increase their incomes. This paper analyses the evolutionary characteristics, regional differences and spatial convergence of the level of sustainable agricultural development using kernel density estimation, Dagum's Gini coefficient and the spatial convergence model based on panel data from 30 provinces in China from 2012 to 2021.The results show that: (1) At the level of development, the level of sustainable agricultural development at the national level and in the three major regions has shown an upward trend with fluctuations, with the average level of development in the eastern and central parts of the country higher than the national average, and in the western part of the country lower than the national average; however, the growth rate in the western part of the country is the highest among the three major regions. (2) In terms of evolutionary characteristics, the level of sustainable agricultural development in the country and the three major regions is characterised by spatial agglomeration, with varying degrees of polarisation. (3) In terms of regional differences, the Gini coefficients for the country as a whole, within the three major regions and between regions, generally show a downward trend, with interregional differences remaining the main source of overall differences. (4) In terms of spatial convergence, there is σ-convergence and β-convergence in the level of sustainable agricultural development across the country and the three major regions, and there is a positive spatial spillover effect. The conditional β convergence results show that the eastern region has the fastest rate of convergence. The above findings provide a scientific basis for the formulation of policies related to sustainable agricultural development in China. [ABSTRACT FROM AUTHOR]

The PIESAT-01 constellation is the world's first multi-baseline distributed synthetic aperture radar (SAR) constellation with a "Cartwheel" formation. The "Cartwheel" formation is a unique formation in which four satellites fly in companion orbits, ensuring that at any given moment, the main satellite remains at the center, with three auxiliary satellites orbiting around it. Due to this unique configuration of the PIESAT-01 constellation, four images of the same region and six pairs of baselines can be obtained with each shot. So far, there has been no imaging and interference research based on four-satellite constellation measured data, and there is an urgent need to explore algorithms for the "Cartwheel" configuration imaging and digital surface model (DSM) production. This paper introduces an improved bistatic SAR imaging algorithm under the four-satellites interferometric mode, which solves the problem of multi-orbit nonparallelism in imaging while ensuring imaging coherence and focusing ability. Subsequently, it presents an interferometric processing method for the six pairs of baselines, weighted fusion based on elevation ambiguity from different baselines, to obtain a high-precision DSM. Finally, this paper selects the Dingxi region of China and other regions with diverse terrains for imaging and DSM production and compares the DSM results with ICESat-2 global geolocated photon data and TanDEM DSM data. The results indicate that the accuracy of PIESAT-01 DSM meets the standards of China's 1:50,000 scale and HRTI-3, demonstrating a high level of precision. Moreover, PIESAT-01 data alleviate the reliance on simulated data for research on multi-baseline imaging and multi-baseline phase unwrapping algorithms and can provide more effective and realistic measured data. [ABSTRACT FROM AUTHOR]

This study provides a comprehensive analysis of global patent trends in battery recycling, focusing on secondary batteries and related technologies across Korea, China, and the United States. The methodology involved collecting data from various patent databases, followed by quantitative analysis to identify technology trends and guide future development. The research employed statistical tools to analyze patent activities, including the frequency and scope of patent filings, and comparative analysis to highlight differences between countries. This study reveals distinct emphases on technologies such as lithium-ion and waste battery recycling, highlighting notable differences in patent activities among key companies and countries. China's large number of patents in battery manufacturing processes contrasts with the USA's focus on electrochemical cell construction and storage systems, while Korea shows significant activity in waste battery technology. The novelty of this paper lies in its detailed comparative analysis of patent trends across these three major economies, providing insights into the technological focuses and priorities of each country. The study also identifies key challenges, such as the need for consistent innovation and broader geographic coverage in Korea, enhancing patent influence and international presence in China, and ensuring high patent quality and fostering innovation in lagging sectors in the United States. Addressing these challenges through enhanced collaboration, increased R&D investments, and supportive policies is crucial for strengthening the global position and driving further innovation in the battery recycling sector. [ABSTRACT FROM AUTHOR]

This article explores the concept of "immigrant consumption behavior (ICB)" in the context of its holistic surroundings. The study investigated the current dynamics and scientometrics of the research field regarding immigrant consumption behaviors. Using an integrative approach employing bibliometric and content analysis, it scrutinized a collection of 224 studies from the Web of Science and Scopus databases to detect the field evolution, disciplinary distribution thematic map, and emerging trends in the ICB literature, as well as to forecast research directions. The results showed that ICB is a multi- and inter-disciplinary research area that experienced three phases of growth between 1989 and 2023: initiation (1989–2006), development (2007–2012), and consolidation (2013–now). The thematic analysis revealed five current trends, i.e., (1) the immigrant consumption behavior domain, (2) the demographic sub-groups of immigrants and related consuming products, (3) country-, region-, and cultural-focused studies, (4) the effects of culture and the acculturation process, and (5) the impact of urbanization. Each theme contains a number of sub-themes. Based on the current thematic evolution and keyword burst analysis, this paper suggests a number of critical research directions, comprising (1) observatory studies including remittances, China, ethnic minorities, lifestyle, inequality, urbanization, and food consumption; (2) context-based studies focused on socioeconomic, cultural, legal, and environmental factors; (3) studies based on compensatory and compromissory consumption behavior; (4) studies focused on sustainable and green consumption behaviors; and (5) studies regarding the behavior of specific demographic co-ethnic communities. The results have great implications for developing interventions and programs that can support immigrant populations in making appropriate consumption patterns and adapting to new cultural environments. The paper pushes forward the ICB investigation from individual empirical studies to synthesis-based research, which (1) provides an ample overview of the ICB literature, (2) identifies research priorities, emerging trends, and gaps, (3) proposes new research avenues for investigation, and (4) outlines expected contributions. The research contributes to a variety of disciplines through the provision of new knowledge, since ICB studies are multidisciplinary in nature. It also has numerous implications for policymakers and practitioners. [ABSTRACT FROM AUTHOR]

The two-part tariff (TPT) policy is implemented as an important initiative to accelerate the marketization of the pumped storage industry and promote its high-quality development. However, it is not clear exactly how the TPT policy affects the productivity of the pumped storage industry. Using the EBM-GML method and the DID model, this paper measures the total factor productivity of the pumped storage industry and explores the impact of the Two-Part Tariff (TPT) policy on its total factor productivity. Based on the samples of 16 provinces in China from 2004 to 2020, we find the following: (1) At present, the total factor productivity of China's pumped storage industry is still at a low level. (2) TPT policy can promote the improvement of total factor productivity, which was strongly supported by the robustness test. Innovation incentive is one of the main mechanisms. (3) The impact of TPT policy on total factor productivity has obvious regional heterogeneity. By geographic location, the TPT policy has little effect on the pumped storage industry's TFP in the eastern region, but it exerts a significant positive role in the central region. By energy affluence, TPT policy effect is stronger in provinces with low energy dependence. By environmental governance, the role of this policy is more obvious in provinces with low environmental regulation but developed green financial market. Finally, some corresponding policy implications have been put forward. [ABSTRACT FROM AUTHOR]

The "Grotto-Heavens and Blissful Lands" (dongtian and fudi, 洞天福地) is a unique concept of sacred space in China and even in East Asia, combining beautiful natural scenery, rich historical heritage, and diverse cultural heritage. This paper tries to explain Mount Jingfu's (jingfu shan, 靜福山) aesthetic representations. The results show that the landscape's physical environment projects the spatio-temporal system and the concept of the universe in Daoist aesthetic ideals. With the spatial evolution of divine immortals' abodes from imagination to reality, people's yearning for divine cave palaces is transformed into their connection with and their expression of the palaces in exploring space interests and aesthetic trends that are then integrated into the secular life of thousands of households through living religious rituals. Preserved by local religious believers, the ritual activities incorporated geographic, familial, and divine interactions, and characterised essential social aesthetics. By exploring a typical case of Lingnan Region (lingnan, 嶺南, an old term for South China), this paper aims to elucidate the significance of the Grotto-Heavens and Blissful Lands as living heritage in contemporary society across multiple dimensions, and to provide a theoretical basis for the protection of its system. [ABSTRACT FROM AUTHOR]

Research on introductory psychology textbooks used in higher education abounds around the world. Although most studies focus on textbooks designed for students majoring in psychology, this paper looks into textbooks used for a compulsory undergraduate course on mental health and well-being in mainland China. Like in many other countries, Chinese students face mental and well-being issues and this course aims to support all undergraduate students in dealing with their own psychology rather than specialising in the subject. Based on an in-depth discourse analysis of two widely used textbooks published in Chinese for this course, the authors examine how the textbooks construct the university experiences of Chinese students. At the same time, the paper also delves into the ways different kinds of Chinese students are portrayed and the types of changes that they are said to experience at university. The foci of invisibility and selectivity from the field of textbook analysis help highlight generalising, stereotyping, and recourse to biases in the textbooks. Recommendations as to how such textbooks could be used to boost university students' mental health and well-being, while taking into account their diversity, are proposed at the end of the paper. [ABSTRACT FROM AUTHOR]

A predictive model for the spatiotemporal distribution of electric vehicle (EV) charging load is proposed in this paper, considering multimodal travel behavior and microscopic traffic simulation. Firstly, the characteristic variables of travel time are fitted using advanced techniques such as Gaussian mixture distribution. Simultaneously, the user's multimodal travel behavior is delineated by introducing travel purpose transfer probabilities, thus establishing a comprehensive travel spatiotemporal model. Secondly, the improved Floyd algorithm is employed to select the optimal path, taking into account various factors including signal light status, vehicle speed, and the position of starting and ending sections. Moreover, the approach of multi-lane lane change following and the utilization of cellular automata theory are introduced. To establish a microscopic traffic simulation model, a real-time energy consumption model is integrated with the aforementioned techniques. Thirdly, the minimum regret value is leveraged in conjunction with various other factors, including driving purpose, charging station electricity price, parking cost, and more, to simulate the decision-making process of users regarding charging stations. Subsequently, an EV charging load predictive framework is proposed based on the approach driven by electricity prices and real-time interaction of coupled network information. Finally, this paper conducts large-scale simulations to analyze the spatiotemporal distribution characteristics of EV charging load using a regional transportation network in East China and a typical power distribution network as case studies, thereby validating the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

At present, agricultural non-point source pollution has become the main source of water pollution, which mainly comes from the excessive use of agricultural chemicals such as pesticides and fertilizers. The TRS is another land system reform in China after the household contract responsibility system, which relaxes the management rights of rural land and clarifies the ownership of land. Using this land reform in China as a case study, this paper constructs panel data for 30 provinces in China to explore the impact of land tenure intensification on agricultural non-point source pollution, using the difference-in-difference (DID) model to identify the causal relationship between the two. The results show that the coefficient of the TRS policy variable is −4.056 at the 1% significance level, indicating that this round of land reform has suppressed agricultural non-point source pollution. The provinces that have implemented TRS have seen an average annual reduction of 405,600 tons in Agnps emissions compared to those that have not implemented TRS, and the scale operation of agriculture and the size of the agricultural economy act as two paths. Moreover, heterogeneity analysis shows that the policy effect of the provinces in non-major food-producing areas is smaller than that of the provinces in major food-producing areas, and the path to realization is also different. Therefore, we should continue to encourage large-scale agricultural operations, cultivate new agricultural business entities, and strengthen the inhibitory effect of TRS on agricultural non-point source pollution. [ABSTRACT FROM AUTHOR]

The objective of this research is to explore the impact mechanism of agricultural digital transformation in alleviating the mismatch of agricultural land resources and provide an effective path for the formation of new quality agricultural productivity. Using the balance panel data of 29 provinces in China from 2011 to 2022, this paper analyzed the mitigation effect and mechanism of agricultural digitalization on agricultural land resource misallocation from the perspectives of land scale management and agricultural socialization services. The results indicate that agricultural digitalization can alleviate the misallocation of agricultural land resources, promote the large-scale management of agricultural land, and improve the level of agricultural socialization services, all significant ways to reduce the mismatch of agricultural land resources. The heterogeneity test showed that the mitigation effect of agricultural digitalization on the agricultural land resource mismatch in eastern and central China and major grain-producing areas was better than that in western China and non-major grain-producing areas. Hence, we ought to strengthen the construction of agricultural digital infrastructures and play into the role of agricultural land scale management and agricultural socialization services in slowing down the mismatch of agricultural land resources. [ABSTRACT FROM AUTHOR]

Traditional potato grading in China relies mostly on manual sorting, which is labor-intensive, time-consuming, costly, and inefficient. To enhance the operational performance of potato-grading devices, this paper focuses on optimizing the slide rail structure, which is the key component of a self-developed first-generation potato-grading device. A five-factor, three-level orthogonal experiment was designed, with the experimental factors being the height of the horizontal slide rail, angle of the first-stage inclined slide, angle of the second-stage inclined rail, chain horizontal movement speed, and conveyor belt speed. The indoor experiments were conducted using grading accuracy and grading efficiency as the experimental indicators. On the basis of the analysis of the orthogonal experiment results, two relatively optimal solutions were obtained, and validation experiments were conducted. The validation results show that when the height of the horizontal slide rail was 185 mm, the angle of the first-stage inclined rail was 4°, the angle of the second-stage inclined rail was 2.5°, the horizontal movement speed of the chain was 700 mm/s, and the movement speed of the conveyor belt was 275.60 mm/s, the performance of the movable rotating plate (MRP)-type grading device for potatoes reached its optimum. At this point, the grading accuracy was 94.88%, and the grading efficiency was 13.9477 t/h. Compared with the first-generation grading device, the optimized grading device achieved an improvement of 3.84% in grading accuracy and 12.94% in grading efficiency. The research methodology provided in this paper serves as a reference for the performance optimization of potato-grading devices. [ABSTRACT FROM AUTHOR]

The farmers' deep participation in the classification of domestic waste plays a crucial role in reducing the amount of waste out of the village from the source, lowering the cost of waste treatment, and realizing the sustainable development of rural waste resocialization, reduction, and harmlessness. This paper aims to identify the key factors and logical structure that influence the farmers' behavior in classifying domestic waste and provide recommendations for improving it. Based on the Participants' Intellectual Decision (PID) Model, we constructed a theoretical analysis framework for farmers' decision-making on domestic waste classification, and the PID model was further extended by combining with the practice of rural domestic waste management in China and proposing the research hypothesis that factors, such as community attributes, rules of operation, the status of the participants, and the situation of external actions, have a significant impact on the farmers' behavior in classifying domestic waste. Empirical analyses were carried out with the help of the ordered logistic model and the DEMATEL-ISM using 939 research data of farmers in Jiangsu and Gansu provinces of China. The results show the following: (1) classification of domestic waste by farmers in the sample area was predominantly unclassified (34.40%) and two-classified (40.58%); (2) 17 factors, including regional disparity, Party affiliation, organizational support perception, environmental emotions, conscious governance attitudes, trust in village cadres, social reference norms, and expected outcomes, have a significant impact on the farmers' behavior in classifying domestic waste; (3) trust in village cadres, organizational support perception, and environmental emotion are superficial direct factors; incentive measures, fee level, waste transport situation, difficulty perception, self-consciousness perception, social reference norms, and expected outcomes are middle indirect factors; whether or not it is a demonstration village, Party membership and regional disparity are deep root factors affecting farmers to classify their domestic waste. [ABSTRACT FROM AUTHOR]

In response to the intensification of urbanization, characterized by increasingly dense land use, the proliferation of high-rise residences has emerged as a predominant housing solution, particularly evident in developed cities like those in China. With a primary aim of enhancing the residential living environment within high-rise structures, this study advocates for a comprehensive whole life cycle perspective. By employing digital technology and conducting experiments centered on a representative case study, this paper focuses on optimizing the functional layout of public activity spaces within high-rise residential projects. Specifically, this article aims to address challenges such as the inadequate configuration and articulation of various public spaces, along with the underutilization of peripheral activity areas. Central to the optimization efforts is the utilization of the Kruskal algorithm, which enables the analysis of flow lines and functions, ultimately leading to the derivation of optimal solutions. Through a detailed analysis of our case study, this paper provides actionable insights into enhancing the feasibility and effectiveness of public spaces within high-rise residential projects. Recognizing the pivotal role of public space layout in shaping residents' living experiences, the importance of addressing this issue early in the design phase was emphasized. By integrating scientifically driven digital technology solutions, smart, inclusive, and convenient communities that cater to the diverse needs of their inhabitants are aspired to be created. [ABSTRACT FROM AUTHOR]

As a project construction organization model, whole-process engineering consulting (WPEC) is currently being promoted in China's engineering consulting industry. However, various factors create numerous obstacles that hinder this model's effective promotion and application. One essential task is to deeply analyze the transmission mechanism of the influencing factors in the promotion and application of WPEC, and explore effective pathways for promoting and applying this model. This paper systematically organizes and summarizes 10 primary influencing factors and 38 secondary influencing factors for promoting WPEC. Using the complex network analysis method, a network of influencing factors for promoting WPEC, a network structure, and motif analyses are conducted. The results show that the influencing factors have a complex transmission mechanism, and complex network analysis can reveal the laws of their construction and their causes. This paper provides a systematic basis and theoretical support for the effective formulation of policies related to the promotion and application of WPEC. [ABSTRACT FROM AUTHOR]

Featured Application: This study is aimed at the detection of sulfur dioxide concentration in the real environment. Due to the vast territory of China and the large temperature difference span between the north and the south, the current sulfur dioxide detection devices find it difficult to meet the requirements of portability, low-cost delivery, and temperature adaptability. A reliable real-time monitoring device and detection algorithm for sulfur dioxide concentration using PMT are proposed. Air is the environmental foundation for human life and production, and its composition changes are closely related to human activities. Sulfur dioxide (SO2) is one of the main atmospheric pollutants, mainly derived from the combustion of fossil fuels. But SO2 is a trace gas in the atmosphere, and its concentration may be less than one part per billion (ppb). This paper is based on the principle of photoluminescence and uses a photomultiplier tube (PMT) as a photoelectric converter to develop a device for real-time detection of SO2 concentration in the atmosphere. This paper focuses on the impact of noise interference on weak electrical signals and uses wavelet transform to denoise the signals. At the same time, considering that the photoelectric system is susceptible to temperature changes, a multi parameter fitting model is constructed, and a BP neural network is used to further process the signal, separating the real data from the original data. Finally, a high-precision and wide-range trace level sulfur dioxide concentration detection device and algorithm were obtained. [ABSTRACT FROM AUTHOR]

Scientific and technological innovation and ecological progress are important forces for China's high-quality development. Nevertheless, the current body of research seldom explores the mutual dependence and evolutionary patterns of the two regional systems when considering both historical and future perspectives. This paper aims to enhance the current theoretical research framework by focusing on the coastal region of China. It analyzes and predicts the co-evolution and space–time distribution process of two systems by constructing a coupled model and a gray prediction model. The results show the following: (1) the coupling and coordinated development level of the two coastal systems has basically reached the stage of good coupling and coordinated development, and the level has increased, but the gap has gradually increased, and Jiangsu and Guangdong have reached the leading level; (2) the spatial distribution in coastal areas is uneven, showing a convex spatial pattern of "high in the middle and low at both ends"; (3) during the forecast period, the overall coupling and coordination level of the two systems will continue to improve, but individual cities still cannot jump out of the development state of slow development processes. With the aim of fostering the harmonious growth of both systems at both regional and national levels, this paper proposes practical recommendations concerning the establishment of a sustainable interaction mechanism, the evolution of the industrial structure towards ecological sustainability, and the economic contribution to scientific and technological innovation. Furthermore, this article serves as a valuable reference for advancing the sustainable development of other nations. [ABSTRACT FROM AUTHOR]

The establishment of government investment funds serves as a crucial measure for governments at all levels to leverage their certification role and financial resources in attracting social capital to support enterprise development. This paper empirically examines the guiding certification effect and governance supervision effect of government investment funds on enterprise value enhancement, utilising panel data from listed companies and government investment fund investment event data spanning the period from 2011 to 2021. The research findings reveal that government investment funds significantly enhance the value of recipient enterprises. By leveraging their guidance and certification effects and governance supervision effects, these funds alleviate financing constraints, actively participate in corporate governance, and ultimately enhance corporate value. The impact of government investment funds is negatively moderated by the age and size of the enterprise, indicating that the "invest in early-stage and small businesses" investment strategy yields better results in promoting value enhancement. Furthermore, heterogeneity analysis demonstrates that government investment funds have a more pronounced impact on the value of non-heavily polluting industries, enterprises located in the eastern and southern regions of China, and non-state-owned enterprises. This article expands the research scope of government investment funds at the micro level, providing empirical evidence and theoretical support for optimising government investment funding policies and fostering the development of a modern capital market with distinctive Chinese characteristics. [ABSTRACT FROM AUTHOR]

Urban villages represent informal residential areas emerging since China's rapid urbanization process. Scientific map generalization of urban villages with scientific maps aids readers in discerning their distribution and making informed decisions concerning them. However, there is still a scarcity of research on the automatic extraction and generalization of urban villages from vector data, which needs to be studied to further improve the expression of maps. To address this problem, this paper presents a methodology for the extraction and generalization of urban villages from Digital Line Graphics. Firstly, a heuristic approach is employed to analyze the atypical morphological characteristics of urban villages. Then, indices based on computational geometry and the modified Hausdorff distance are utilized to quantify these traits. Lastly, an automatic generalization principle for urban villages is offered. The approach was tested in experimental blocks and proved to be effective. It offers a novel method for the automatic extraction and cartography of urban villages. [ABSTRACT FROM AUTHOR]

In the context of large-scale wind power access to the power system, it is urgent to explore new probabilistic supply–demand analysis methods. This paper proposes a wind power stochastic and extreme scenario generation method considering wind power–temperature correlations and carries out probabilistic supply–demand balance analysis based on it. Firstly, the influence of temperature on wind power output is analyzed via Pearson coefficient to obtain the correlation between wind power and temperature. Secondly, based on the historical wind power curve, a large number of wind power output scenarios are randomly generated while fully preserving its characteristics, and probabilistic supply–demand analysis is carried out. Thirdly, for the extreme case of continuous multi-day extreme heat without wind, extreme scenarios are selected from the generated scenarios for supply–demand balance analysis. Finally, a practical example in a province in central-eastern China is used to verify the effectiveness of the proposed method. The results indicate that the scenario generation method can effectively capture the historical wind power characteristics and can be better applied to the diversified supply and demand balance analysis to obtain more accurate analysis results. [ABSTRACT FROM AUTHOR]

In the context of China's new power system, various regions have implemented policies mandating the integration of new energy sources with energy storage, while also introducing subsidies to alleviate project cost pressures. Currently, there is a lack of subsidy analysis for photovoltaic energy storage integration projects. In order to systematically assess the economic viability of photovoltaic energy storage integration projects after considering energy storage subsidies, this paper reviews relevant policies in the Chinese photovoltaic energy storage market. It analyzes the cost and revenue composition of photovoltaic energy storage integration projects, and constructs a system dynamics model for the levelized cost of electricity (LCOE) of such projects. Taking a specific photovoltaic energy storage project as an example, this paper measures the levelized cost of electricity and the investment return rate under different energy storage scenarios. Combining energy storage allocation ratios and internal rate of return indicators, this paper analyzes the net present value of photovoltaic energy storage integration projects under different subsidy standards. The results indicate that, while the current energy storage subsidy policies positively stimulate photovoltaic energy storage integration projects, they exhibit a limited capacity to cover energy storage investment costs, thereby failing to incentivize capital market participation in the construction of such projects. Rational allocation of energy storage capacity and optimization of corresponding subsidy policies are crucial prerequisites for enhancing the economic viability and widespread adoption of photovoltaic energy storage integration projects. This study not only aids in investment decision making for photovoltaic power stations but also contributes to the formulation of energy storage subsidy policies. [ABSTRACT FROM AUTHOR]

This paper explores the development of a smart Structural Health Monitoring (SHM) platform tailored for long-span bridge monitoring, using the Forth Road Bridge (FRB) as a case study. It discusses the selection of smart sensors available for real-time monitoring, the formulation of an effective data strategy encompassing the collection, processing, management, analysis, and visualization of monitoring data sets to support decision-making, and the establishment of a cost-effective and intelligent sensor network aligned with the objectives set through comprehensive communication with asset owners. Due to the high data rates and dense sensor installations, conventional processing techniques are inadequate for fulfilling monitoring functionalities and ensuring security. Cloud-computing emerges as a widely adopted solution for processing and storing vast monitoring data sets. Drawing from the authors' experience in implementing long-span bridge monitoring systems in the UK and China, this paper compares the advantages and limitations of employing cloud- computing for long-span bridge monitoring. Furthermore, it explores strategies for developing a robust data strategy and leveraging artificial intelligence (AI) and digital twin (DT) technologies to extract relevant information or patterns regarding asset health conditions. This information is then visualized through the interaction between physical and virtual worlds, facilitating timely and informed decision-making in managing critical road transport infrastructure. [ABSTRACT FROM AUTHOR]

With the rapid development of artificial intelligence in recent years, intelligent evaluation of college students' growth by means of the monitoring data from training processes is becoming a promising technique in the field intelligent education. Current studies, however, tend to utilize course grades, which are objective, to predict students' grade-point averages (GPAs), but usually neglect subjective factors like psychological resilience. To solve this problem, this paper takes mechanical engineering as the research object, and proposes a new machine-learning-driven GPA prediction approach to evaluate the academic performance of engineering students by incorporating psychological evaluation data into basic course scores. Specifically, this paper adopts SCL-90 psychological assessment data collected in the freshman year, including key mental health indicators such as somatization, depression, hostility, and interpersonal sensitivity indicators, as well as professional basic course scores, including mechanical principles, mechanical design, advanced mathematics, and engineering drawing. Four representative machine learning algorithms, Support Vector Machine (SVM), CNN-CBAM, Extreme Gradient Boosting (XGBoost) and Classification and Regression Tree (CART) that include deep and shallow models, respectively, are then employed to build a classification model for GPA prediction. This paper designs a validation experiment by tracking 229 students from the 2020 class from the School of Mechanical and Electrical Engineering of Henan University of Science and Technology, China. The students' academic performance in senior grades is divided into five classes to use as the prediction labels. It is verified that psychological data and course data can be effectively integrated into GPA prediction for college students, with an accuracy rate of 83.64%. Meanwhile, this paper also reveals that anxiety indicators in the psychological assessment data have the greatest impact on college students' academic performance, followed by interpersonal sensitivity. The experimental results also show that, for predicting junior year GPAs, psychological factors play more important role than they do in predicting sophomore GPAs. Suggestions are therefore given: the current practice in existing undergraduate teaching, i.e., only conducting psychological assessments in the initial freshman year, should be updated by introducing follow-up psychological assessments in each academic year. [ABSTRACT FROM AUTHOR]

The Solow residual method, traditionally pivotal for calculating total factor productivity (TFP), is typically not applied to green TFP calculations due to its exclusion of undesired outputs. Diverging from traditional approaches and other frontier methodologies such as Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA), this paper integrates undesired outputs and three types of spatial spillover effects into the conventional Solow framework, thereby creating a new spatiotemporal econometric Solow residual method (STE-SRM). Utilizing this novel method, the study computes the industrial green TFPs for 280 Chinese cities from 2003 to 2019, recalculates these TFPs using DEA-SBM and Bayesian SFA for the same cities and periods, and assesses the accuracy of the STE-SRM-derived TFPs through comparative analysis. Additionally, the paper explores the statistical properties of China's urban industrial green TFPs as derived from the STE-SRM, employing Dagum's Gini coefficient and spatial convergence analyses. The findings first indicate that by incorporating undesired outputs and spatial spillover into the Solow residual method, green TFPs are computable in alignment with the traditional Solow logic, although the allocation of per capita inputs and undesired outputs hinges on selecting the optimal empirical production function. Second, China's urban industrial green TFPs, calculated using the STE-SRM with the spatial Durbin model with mixed effects as the optimal model, show that cities like Huangshan, Fangchenggang, and Sanya have notably higher TFPs, whereas Jincheng, Datong, and Taiyuan display lower TFPs. Third, comparisons of China's urban industrial green TFP calculations reveal that those derived from the STE-SRM demonstrate broader but more concentrated results, while Bayesian SFA results are narrower and less concentrated, and DEA-SBM findings sit between these extremes. Fourth, the study highlights significant spatial heterogeneity in China's urban industrial green TFPs across different regions—eastern, central, western, and northeast China—with evident sigma convergence across the urban landscape, though absolute beta convergence is significant only in a limited subset of cities and time periods. [ABSTRACT FROM AUTHOR]

Under the new development model, the digital economy has become a new engine to promote the green development of the economy and realize the goal of "double carbon". Based on the panel data of 30 provinces in China from 2010 to 2020, this paper empirically investigates the impact of the development of the digital economy on energy and carbon emissions using a series of econometric models such as baseline regression, a mechanism test, and the spatial Durbin model, etc. Common prosperity plays an intermediary role between digital economy development and carbon emissions; digital economic development optimizes resource allocation, effectively solves the problem of uneven resource distribution, and reduces energy and carbon emissions while achieving common prosperity. In addition, green innovation, industrial structure, urbanization level, R&D intensity, and the degree of marketization also have different degrees of influence on energy and carbon emissions. Therefore, the government should accelerate the construction of new digital infrastructure and implement the digital economy development strategy according to local conditions, so as to promote the digital economy to produce a more significant carbon emission reduction effect. [ABSTRACT FROM AUTHOR]

This paper examines the construction and maintenance of Chinese Han Buddhist temples in modern China against the backdrop of societal transformation. Initially, it analyzes the profound impact of social changes since the mid-19th century on Buddhist monasteries, including political turmoil, economic development, and urbanization. Furthermore, the paper explores how temples were reconstructed and revitalized within this historical context, highlighting the monastic community's unwavering commitment to protecting the Dharma and ensuring its enduring presence. Additionally, this paper also explores the role of charismatic monks in enhancing the sanctity of temples and the influence of Buddhist institutional frameworks on the dynamics of state and society. The study employs a multifaceted analysis to understand the complex interplay between temple construction, economic development, and the cultural heritage of Buddhism in China. [ABSTRACT FROM AUTHOR]

In the current context of carbon neutrality, afforestation is an effective means of absorbing carbon dioxide. Stock can be used not only as an economic value index of forest wood resources but also as an important index of biomass and carbon storage estimation in forest emission reduction project evaluation. In this paper, we propose a data-driven machine learning framework and method for predicting plantation stock based on airborne LiDAR + satellite remote sensing, and carried out experimental verification at the site of the National Forest emission reduction project in Southern China. We used step-up regression and random forest (RF) to screen LiDAR and Landsat 8 OLI multispectral indicators suitable for the prediction of plantation stock, and constructed a plantation stock model based on machine learning (support vector machine regression, RF regression). Our method is compared with traditional statistical methods (stepwise regression and partial least squares regression). Through the verification of 57 plantation field survey data, the accuracy of the stand estimation model constructed using the RF method is generally better (ΔR2 = 0.01~0.27, ΔRMSE = 1.88~13.77 m3·hm−2, ΔMAE = 1.17~13.57 m3·hm−2). The model evaluation accuracy based on machine learning is higher than that of the traditional statistical method, and the fitting R2 is greater than 0.91, while the fitting R2 of the traditional statistical method is 0.85. The best fitting models were all support vector regression models. The combination of UAV point clouds and satellite multi-spectral images has the best modeling effect, followed by LiDAR point clouds and Landsat 8. At present, this method is only applicable to artificial forests; further verification is needed for natural forests. In the future, the density and quality of higher clouds could be increased. The validity and accuracy of the method were further verified. This paper provides a method for predicting the accumulation of typical Chinese plantations at the forest farm scale based on the "airborne LiDAR + satellite remote sensing" data-driven machine learning modeling, which has potential application value for the current carbon neutrality goal of the southern plantation forest emission reduction project. [ABSTRACT FROM AUTHOR]

The realization of the value of ecological products has led to an economic means for reducing carbon emissions in China. Tea is one of the most important cash crops and one of the most popular beverages in the world. Due to the complex the tea industrial chain, it is considered to be an industry with high carbon emissions. Ecological tea products with low-carbon attributes can be considered a linkage of ecology, economy, and society. Based on this, this paper presents research on low-carbon ecological tea (LCT). Herein, we construct the formational logic of low-carbon ecological products, explore the connotations of LCT, and form a conceptual pathway for realizing LCT to contribute to climate change mitigation and adaptation. This paper starts from the upstream, midstream, and downstream of the industrial chain; it establishes three value realization pathways that keep, as a priority, the promotion of ecological industrialization, focus on restoration to improve the ecology of the industrial chain, and innovate technology to expand the industrial chain. The pathways are a set of low-emission production solutions that use techniques to enhance carbon sequestration in soil, reduce the use of fertilizers and pesticides, and help shift to clean energy from low-emission sources in the stages of plantation, processing, and distribution. In the process of realizing LCT, the government plays an important role, and its support and guidance are needed. Based on stakeholder theory, this paper builds an implementation mechanism that focuses on the micro perspective (users, organizations), integrates the mesoscopic perspective (industry), and relies on the macro perspective (government). [ABSTRACT FROM AUTHOR]

This paper examines the relationship between income inequality and consumption, utilizing panel data from rural China over a span of four years to validate the application of relative income theory in the domain of food consumption. Food consumption represents a significant portion of expenditures for the low-income demographic and is of vital importance to China's food security and agricultural development. To ascertain the impact of income inequality on food consumption, this paper employs a bi-directional fixed-effects model, a mediation effect model, and machine learning causal analysis methods. Utilizing four years of rural resident survey data from the China Health and Nutrition Survey database, the study empirically tests the effect of income inequality on various types of food consumption, the channels through which it operates, and the heterogeneity among different income groups and educational backgrounds. The findings indicate that (1) income inequality within rural communities positively influences food consumption, and this conclusion remains robust under endogeneity treatment and robustness checks, positively affecting the transformation of food consumption and healthy intake; (2) income inequality among rural residents promotes food consumption through two mediating channels: the "demonstration effect" and the "ratchet effect;" (3) the impact of income inequality on food consumption exhibits heterogeneity among rural residents of different income levels and educational backgrounds. [ABSTRACT FROM AUTHOR]

Income increase is an important way to achieve comprehensive human development and to escape from poverty, and the growing aging problem in rural China poses a challenge to farm household income increase. In order to gain a deeper understanding of the impact of China's rural old-age burden on farm household income, this paper empirically examines the impact and mechanism of household old-age burden on farm household income based on the data from the 2023 micro-farm field survey of China's Henan Province, utilizing linear regression modeling and mediation effect modeling, filling the research gaps in the related fields. The results of the study found that, firstly, family old-age burden has a significant impact on the income of farm households, and that the heavier the family old-age burden, the lower the total income of farm households. Secondly, from the results of the heterogeneity of the impact, the poorer the health condition, the greater the negative impact of family old-age burden on farm household income. Old-age burden has a greater impact on high-income farm households than on low-income farm households, and old-age burden has a significant impact on the income of part-time farm households, while the impact is not significant on purely farm and non-farm households. Thirdly, the heavier the household old-age burden, the more unfavorable it is to the non-farm employment of farm households, thus affecting the income capacity of farm households. Finally, corresponding countermeasures and recommendations are put forward in three areas, namely, the continuous improvement of the social old-age security system, the realization of the function of the social old-age mechanism as an old-age pocket for key special groups, and the improvement of the social flexible employment mechanism. [ABSTRACT FROM AUTHOR]

The rock mass deformation modulus is one of the most important design parameters in a range of rock engineering applications. Its value is usually obtained directly through in situ testing or estimated indirectly on the basis of a rock mass quality classification system. Because in situ testing is generally costly, time-consuming, and presents operational difficulties, it cannot be carried out extensively, and many researchers have concentrated on developing indirect procedures to obtain information on the modulus of deformation, such as the RMR method, Q method, and GSI method. The purpose of this paper is to present a new system for estimating the rock mass deformation modulus called the BQ method, which is based on the BQ (basic quality) system. In this paper, the BQ system is first briefly reviewed, and then more than 60 in situ measurements from three large hydropower stations in China are used to develop a new relationship between BQ and the deformation modulus, based on a power function relationship. The paper also derives correlations based on the existing estimation formula and the relationship between BQ and other classification schemes, resulting in several recommended formulas for estimating the deformation modulus of a rock mass using the BQ method. [ABSTRACT FROM AUTHOR]