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In the twenty-first century, with the development of urbanization, large-scale mine wastelands in peri-urban areas have become increasingly closely related to the daily lives of urban and rural residents. Adopting a reuse method that meets the health needs of these residents, restoration, construction of mine wastelands in the suburbs of cities, and the formation of high-quality healthy environments and service supply are in line with the demands of healthy city construction and sustainable development. In addition, they have received increasing attention from all sectors of society. Based on the main criteria for constructing a healthy urban environment, this paper takes the comprehensive remediation and construction project of mine wastelands in the Taiyuan Xishan Ecological and Cultural Tourism Demonstration Area as a case study. It uses on-site surveys and an open-ended web-based questionnaire. It focuses on researching the perceived health needs of urban and rural residents in Taiyuan City, Shanxi Province, China concerning the main elements that determine health, such as the natural ecological environment, the construction of facilities and activities, and the local economic and industrial development. The results of 748 questionnaires that were completed by participants who effectively participated in the survey show that most participants preferred a comprehensive development model (86.6%) to reuse these areas. In addition, the specific needs of urban and rural residents for health safety, equity and quality, and healthy low-carbon industries should be considered. The differences in demand among groups of citizens due to different ages, living distances, levels of education, and occupations should be comprehensively considered. This paper demonstrates that a full understanding of the health needs of residents has great practical significance when improving the healthy environment and service supply level in mine wasteland restoration and construction and promoting the development of regional healthy city construction. Recently, the healthy environment and sustainable development of areas that host large-scale mine wastelands on the outskirts of cities have received increasing attention from all sectors of society. This paper suggests that during the reuse and construction of these areas, government management, development, and construction companies, planning and design organizations, and other departments that are involved in policy formulation and construction implementation should give full consideration to the perceived health needs of urban and rural residents in the host city, and to groups of residents of different ages, living distances, occupations, and educational levels, to form a high-quality and equitable health environment and services in the area. In addition, active public participation, on-site research, and interviews are essential for relevant departments to improve their understanding of resident health needs. [ABSTRACT FROM AUTHOR]

To solve the problem of the insufficient driving force and low adoption rate of conservation tillage adoption and to enhance the effect of industrial organization in influencing technology diffusion, this paper explored the relationship and the mechanism of perceived organizational support and inter-temporal choice in the adoption of conservation tillage by using micro-research data from 725 melon farmers in the Shaanxi and Shanxi provinces in China and by applying the experimental economics method to obtain the inter-temporal choices of the farmers. This paper also analyzed farmers' risk preferences' moderating effect on the relationship between inter-temporal choice and conservation tillage. Additionally, it examined the impact of perceived organizational support on the differentiation of different conservation tillage technologies. The study found that perceived organizational support significantly contributes to adopting zero tillage and minimum tillage, and water-saving irrigation. Perceived organizational support was not conducive to farmers' adoption of furrow and ridge tillage. The impact of perceived organizational support on technology adoption is heterogeneous, depending on the differences in the size of the family's cultivated land. The inter-temporal choice of farmers significantly impedes the adoption of conservation tillage. The increase in risk preference helps alleviate the hindering effect of inter-temporal choice on farmers' adoption of conservation tillage. Perceived organizational support can promote the adoption of conservation tillage by reducing farmers' inter-temporal choices. Inter-temporal choice is an essential mechanism by which perceived organizational support affects the adoption of conservation tillage. Compared with the existing studies, this paper incorporates the technology-attribute-induced inter-temporal choice of farmers into the impact analysis framework and considers the relationship between perceived organizational support, inter-temporal choice, and the adoption of conservation tillage and the mechanism of its action. The findings of the study provide a theoretical basis for the enrichment of incentive mechanisms for the adoption of conservation tillage, which is of great significance for the improvement of the tool for the integration of small farmers in developing countries into the industrial activities of the new agricultural business central bodies and for promoting the diffusion of conservation tillage in agriculture. [ABSTRACT FROM AUTHOR]

Accurate medium- and long-term runoff prediction models play crucial guiding roles in regional water resources planning and management. However, due to the significant variation in and limited amount of annual runoff sequence samples, it is difficult for the conventional machine learning models to capture its features, resulting in inadequate prediction accuracy. In response to the difficulties in leveraging the advantages of machine learning models and limited prediction accuracy in annual runoff forecasting, firstly, the variational mode decomposition (VMD) method is adopted to decompose the annual runoff series into multiple intrinsic mode function (IMF) components and residual sequences, and the spectral clustering (SC) algorithm is applied to classify and reconstruct each IMF. Secondly, an annual runoff prediction model based on the adaptive particle swarm optimization–long short-term memory network (APSO-LSTM) model is constructed. Finally, with the basis of the APSO-LSTM model, the decomposed and clustered IMFs are predicted separately, and the predicted results are integrated to obtain the ultimate annual runoff forecast results. By decomposing and clustering the annual runoff series, the non-stationarity and complexity of the series have been reduced effectively, and the endpoint effect of modal decomposition has been effectively suppressed. Ultimately, the expected improvement in the prediction accuracy of the annual runoff series based on machine learning models is achieved. Four hydrological stations along the upper reaches of the Fen River in Shanxi Province, China, are studied utilizing the method proposed in this paper, and the results are compared with those obtained from other methods. The results show that the method proposed in this article is significantly superior to other methods. Compared with the APSO-LSTM model and the APSO-LSTM model based on processed annual runoff sequences by single VMD or Wavelet Packet Decomposition (WPD), the method proposed in this paper reduces the RMSE by 40.95–80.28%, 25.26–57.04%, and 15.49–40.14%, and the MAE by 24.46–80.53%, 16.50–59.30%, and 16.58–41.80%, in annual runoff prediction, respectively. The research has important reference significance for annual runoff prediction and hydrological prediction in areas with data scarcity. [ABSTRACT FROM AUTHOR]

The food crisis has increased demand for agricultural resources due to various factors such as extreme weather, energy crises, and conflicts. A solar greenhouse enables counter-seasonal winter cultivation due to its thermal insulation, thus alleviating the food crisis. The root temperature is of critical importance, although the mechanism of soil thermal environment change remains uncertain. This paper presents a comprehensive study of the soil thermal environment of a solar greenhouse in Jinzhong City, Shanxi Province, employing a variety of analytical techniques, including theoretical, experimental, and numerical simulation, and deep learning modelling. The results of this study demonstrate the following: During the overwintering period, the thermal environment of the solar greenhouse floor was divided into a low-temperature zone, a constant-temperature zone, and a high-temperature zone; the distance between the low-temperature boundary and the southern foot was 2.6 m. The lowest temperature in the low-temperature zone was 11.06 °C and the highest was 19.05 °C. The floor in the low-temperature zone had to be heated; the lowest value of the constant-temperature zone was 18.29 °C, without heating. The minimum distance between the area of high temperature and the southern foot of the solar greenhouse was 8 m and the lowest temperature reading was 19.29 °C. The indoor soil temperature tended to stabilise at a depth of 45 cm, and the lowest temperature reading at a horizontal distance of 1400 mm from the south foot was 19.5 °C. The Fluent and LSTM models fitted well and the models can be used to help control soil temperature during overwintering in extreme climates. The research can provide theoretical and data support for the crop areas and the heating of pipelines in the solar greenhouse. [ABSTRACT FROM AUTHOR]

Carbon storage services play an important role in maintaining ecosystem stability. Land use/cover change (LUCC) is the main factor leading to changes in ecosystem carbon storage. Understanding the impact of LUCC on regional carbon storage changes is crucial for protecting regional ecosystems and promoting sustainable socio-economic development. This paper selects Shanxi province as the study area and explores the spatial and temporal evolution characteristics of carbon storage in Shanxi province based on the InVEST model and univariate spatial autocorrelation. The results show that the total carbon storage in Shanxi Province in 2000, 2010, and 2020 is 513.51 × 104 t C, 513.46 × 104 t C, and 509.29 × 104 t C, respectively. High carbon storage areas are distributed in forest and grassland land types, while low carbon storage areas are widely distributed in building land in urban metropolitan areas. Shanxi Province is mainly dominated by farmland, which has decreased by 3448.60 km2 in the past 20 years. Grassland has decreased by 1588.31 km2 and the area of building land has increased by 4205.73 km2. Due to the influence of carbon conversion among different land use types, the total carbon storage loss of Shanxi Province in the past 20 years was 4.21 × 104 t C. The transfer of farmland resulted in an increase in carbon stock of 14.46 × 104 t C. The transfer of grassland resulted in an increase of 17.15 × 104 t C, while the transfer of forest resulted in a decrease of 41.44 × 104 t C. The increase in land use types with low carbon density and the decrease in land use types with high carbon density led to the decrease in carbon storage in Shanxi Province. Furthermore, social factors were more likely to influence the carbon storage than natural factors, and the influence of social factors was often negative. On this basis, regional development countermeasures were proposed for the current situation of carbon storage in Shanxi Province and provide a scientific basis for Shanxi Province to achieve the carbon neutrality target. [ABSTRACT FROM AUTHOR]

The ability to predict gas emissions accurately is pivotal in managing gas control and ensuring safe mining operations. Existing internationally acknowledged gas control and prediction software does not cater to the specific conditions in Chinese coal mines. Hence, this paper introduces an object-oriented programming method to design a software tool for calculating the total gas emission quantity using the MATLAB application program designer runtime environment. The software incorporates an algorithm, data structure, framework, and module functions, all of which enable seamless integration and visualization of gas emission calculation software. This software tool mitigates the inefficiencies and inaccuracies associated with manual, different-source forecast methods. Based on the field data of the Hulonggou Coal Mine in Shanxi province, this technical software was used to predict the gas emission of the mine. The research results show that the predicted value of the technical software is close to the actual measured value. The differing estimates of the working face and coal mine output primarily account for the deviation between the tool's predicted gas emission value and the field-measured value. The underlying design logic of this technical software determines that it has good adaptability to mines with clear mining technology parameters and gas geological parameters. This study provides a valuable method for researchers and engineers seeking to improve gas emission calculation efficiency. [ABSTRACT FROM AUTHOR]

The shift from the conventional agri-food system to alternative practices is a challenging transition for agricultural producers, yet surprisingly under-studied. Little research has examined the social and cultural processes in rural communities that mobilize producers and construct and sustain producer-driven alternative food networks (AFNs). For AFNs to go beyond just offering "alternative foods" or "alternative networks" and to be constructed as "alternative economies", this transformation in the producer community is indispensable. This paper presents a case study of a rural cooperative in Shanxi, China. The discontent with both productivist agriculture and the social decay in communities motivated a group of women to engage in a decade-long process of social mobilization, cultural reconstruction, and learning by experimentation. Through this, they developed an alternative vision and successfully created a localized alternative socio-economic model, which I call "anti-productivism". It prioritizes ecological sustainability, self-reliance, reciprocity, and cultural values over output maximization, productivity growth, commodity exchange, and monetary gains. This case contrasts sharply with the urban-initiated, consumer-driven AFNs studied in the China literature, which mostly just offered alternative foods but brought little change to the producer community. It shows that the alternative economy must be embedded in an alternative community united by strong social bonds and shared cultural values. [ABSTRACT FROM AUTHOR]

Heritage buildings represent history and act as vessels of human civilisation. The significance of these architectural phenomena increases as society increases, which renders their preservation and ethical use increasingly crucial. Hence, preserving heritage buildings is necessary for societal benefit. The accuracy of three-dimensional (3D) point cloud models of heritage buildings is important to their digital conservation. Traditional mapping methods typically require more time and human resources. Furthermore, the outcome is subject to measurement omissions, errors, and other issues, which are contrary to the protection of the object measured. The complex elements of ancient Chinese architecture render it challenging for traditional measuring techniques to accurately capture spatial structural information. The 3D laser scanning technology is a novel technology to obtain 3D data rapidly. In this paper, the Great Achievement Palace of the Confucian Temple in Yuci District, Jinzhong City, Shanxi Province, was used as an example to examine the application of 3D laser scanning technology to acquire point cloud models of heritage buildings. Field data collection for architectural heritage using 3D laser scanning technology requires measuring station setting analysis to ensure effect accuracy while considering the elements of target location and quantity. For the 3D point cloud model of the Great Achievement Palace, error analysis and accuracy assessment were conducted on the quality elements of alignment accuracy between scanning stations, point cloud model reliability, point cloud data noise condition, and whether the point cloud data were stratified. The findings demonstrated that the improved method quickly and accurately acquired 3D point cloud model data and obtained realistic spatial data models of the heritage building. [ABSTRACT FROM AUTHOR]

Encouraging the use of conservation tillage technology is a highly effective approach to safeguarding soil health, improving the environment, and promoting sustainable agricultural development. With the mounting concerns surrounding climate change, developing conservation tillage methods that facilitate sustainable agricultural growth has become an imperative both in China and around the world. While it is widely recognized that adapting to climate change is crucial in agriculture, there is limited research on evaluating the risks, discovering resilience, measuring farmers' perceptions on climate change, and exploring how tillage technology can be adjusted in the context of small-scale farming in China to foster sustainable development. Using research data from smallholder farmers in the Shaanxi and Shanxi provinces of China, this paper aims to explore the impact of climate change perceptions on farmers' adoption of conservation tillage technologies based on an ordered Probit model. We found that farmers tend to refrain from embracing conservation tillage technology due to the presence of unclear and conflicting perceptions regarding climate change. Focus on short-term profitability and inadequate preparation hinder them from prioritizing adaptation. We recognized several measures that could help farmers adapt and thrive within the agricultural sector. Furthermore, we have validated the need for self-system moderation in promoting farmers' adoption of conservation tillage technology. By utilizing such tools and resources, farmers can comprehend the gravity of climate change's impact on agricultural productivity and, more importantly, channel their efforts towards fortifying resilience to extreme weather conditions and long-term climate risks, thus fortifying agricultural sustainability. [ABSTRACT FROM AUTHOR]

China stands out as a major contributor to anthropogenic methane (CH 4) emissions, with coal mine methane (CMM) playing a crucial role. To control and reduce CH 4 emissions, China has made a dedicated commitment and formulated an ambitious mitigation plan. To verify the progress made, the consistent acquisition of independent CH 4 emission data is required. This paper aims to implement a wind-assigned anomaly method for the precise determination of regional-scale CMM emissions within the coal-rich Shanxi province. We use the TROPOspheric Monitoring Instrument (TROPOMI) CH 4 observations from May 2018 to May 2023, coupled with ERA5 wind and a bottom-up inventory dataset based on the IPCC (Intergovernmental Panel on Climate Change) Tier 2 approach covering the Changzhi, Jincheng, and Yangquan regions of the Shanxi province. The derived emission strengths are 8.4 × 10 26 molec. s -1 (0.706 Tg yr -1 , ± 25 %), 1.4 × 10 27 molec. s -1 (1.176 Tg yr -1 , ± 20 %), and 4.9 × 10 26 molec. s -1 (0.412 Tg yr -1 , ± 21 %), respectively. Our results exhibit biases of - 18 %, 8 %, and 14 %, respectively, when compared to the IPCC Tier 2 bottom-up inventory. Larger discrepancies are found when comparing the estimates to the Copernicus Atmosphere Monitoring Service global anthropogenic emissions (CAMS-GLOB-ANT) and Emissions Database for Global Atmospheric Research (EDGARv7.0) inventories (64 %–176 %), suggesting that the two inventories may be overestimating CH 4 emissions from the studied coal mining regions. Our estimates provide a comprehensive characterization of the regions within the Shanxi province, contribute to the validation of emission inventories, and provide additional insights into CMM emission mitigation. [ABSTRACT FROM AUTHOR]

LuTan-1 (LT-1) satellite constellation is used to conduct surface deformation monitoring. Following the successful launch of two satellites, we began to use the independently developed LandSAR software for differential interferometric data processing and application at the beginning of 2022. In this paper, we tested the LandSAR software by assessing the DInSAR and stacking modules. We used 21 LT-1 single look complex (SLC) images from December 2022 to May 2023 to conduct DInSAR and stacking processing of Datong City, Shanxi Province. DInSAR revealed more subsidence funnels and larger relative deformation values compared to stacking. We tested the DInSAR technology with different parameter combination. Results show that multi-looking factor is the most important to detect the deformation details because of the phase gradient limitation of DInSAR. Compared multi-looking ratios of 2×2 and 4×4, the subsiding funnels that were detected decreased from 60 to 47. After deep testing and assessment, we found that the linear model used by stacking affects the result severely, meaning that most of the subsidence of coal mines were not linear. Stacking only found 32 subsidence funnels which were active coal mines during our observation time. The test result show that LandSAR was compatible for DInSAR and stacking. And it is useful to observe linear and nonlinear deformation in the coal mine regions. [ABSTRACT FROM AUTHOR]

Rainfall erosivity, which signifies the inherent susceptibility of soil erosion induced by precipitation, plays a fundamental role in formulating a comprehensive soil loss equation (RUSLE). It stands as a crucial determinant among the foundational factors considered in a comprehensive soil loss equation's establishment. Nonetheless, the prediction and quantification of future alterations in rainfall erosivity under the influence of global warming have been relatively limited. In this study, climate change was widely evaluated and 10 preferred global climate models in the Loess Plateau were selected by using the data sets of 27 models simulating climate change and the CN05.1 data set provided by the latest CMIP6. The monthly precipitation forecast data were obtained by using the delta downscaling method. Combined with trend analysis, significance test, and coefficient of variation, the annual rainfall erosivity during 1961–2100 under four SSP scenarios was analyzed and predicted. Among the 27 GCM models used in this paper, the most suitable climate models for simulating monthly precipitation in the Loess Plateau were CMCC-CM2-SR5, CMCC-ESM2, TaiESM1, EC-Earth3, EC-Earth-Veg-LR, INM-CM4-8, CAS-ESM2-0, EC-Earth-Veg, ACCESS-ESM1-5, and IPSL-CM6A-LR. In comparison to the base period (1961–1990), during the historical period (1961–2014), the average annual rainfall erosivity on the Loess Plateau amounted to 1259.64 MJ·mm·hm−2·h−1·a−1, showing an insignificant downward trend. In the northwest of Ningxia, Yulin City and Yanan City showed a significant upward trend. In the future period (2015–2100), the annual rainfall erosivity continues to constantly change and increase. The potential average increase in rainfall erosivity is about 13.48–25.86%. In terms of spatial distribution, most areas showed an increasing trend. Among these regions, the majority of encompassed areas within Shanxi Province, central Shaanxi, and Inner Mongolia increased greatly, which was not conducive to soil and water conservation and ecological environment construction. This study offers a scientific reference for the projected future erosivity characteristics of the Loess Plateau. [ABSTRACT FROM AUTHOR]

In this paper, anthracite in Shanxi region is taken as a research object, and the pore structure of coal under different freeze-thaw times is characterized and analyzed by scanning electron microscope and nitrogen adsorption experiment. The SEM experimental results show that the micron-scale cracks on the surface of anthracite gradually connect after freeze-thaw, and the secondary crack channels are formed around the pores and air holes, so that the pores also begin to connect. Further, the quantitative information of the picture was extracted, and it was found that the surface porosity and fractal dimension of the coal sample changed significantly after three freeze-thaw cycles, which increased by 163.3% and 15.9% respectively, and increased with the increase of freeze-thaw cycles. The results of low-temperature nitrogen adsorption experiments show that the coal samples after freeze-thaw are mainly crack, and the pore structure changes from simple to complex. In addition, the maximum nitrogen adsorption capacity, specific surface area and pore volume increased by 125.7%, 69.3% and 72.6%, respectively. With the increase of freeze-thaw times, the growth rates of maximum nitrogen adsorption capacity, specific surface area and pore volume are significantly different. The results of joint characterization show that the number of pores and cracks increases to different degrees after freezing and thawing. Comparing the increase in the degree of fracturing (163.3%) with the increase in the total pore volume (30.68%), we find that the degree of change of the crack after thawing is higher than that of the pore. In this paper, the damage effect of coal samples after freezing and thawing with liquid nitrogen is investigated from an experimental point of view, which accelerates the great leap of cyclic cryogenic fracturing technology from basic theory to technical practice. [ABSTRACT FROM AUTHOR]

Regional debris flow susceptibility assessment is an effective method to prevent debris flow hazards, and deep learning is emerging as a novel approach in this discipline with the development of computers. However, when debris flow samples are insufficient, there will be problems like overfitting or misclassification. To overcome these problems, this paper proposes a semi-supervised deep neural network model (LPA-DNN) combined with label propagation algorithm (LPA), which utilizes high confidence unlabeled samples as pseudo-samples reasonably in few-label scenarios. Xinzhou, Shanxi Province, was selected as the study area, and a dataset containing 292 debris flow samples and 10 types of impact factors was compiled based on watershed units. Using the dataset and pseudo-samples, the LPA-DNN model was built to get debris flow susceptibility map. Meanwhile, DNN and SVM were set up for comparison to demonstrate that the proposed LPA-DNN model has excellent performance and higher accuracy. LPA-DNN alleviates the problem of low accuracy that caused by samples lacking in deep learning to a certain extent, and obtains great classification results, which proves that it is quite potential in regional debris flow susceptibility assessment. [ABSTRACT FROM AUTHOR]

Introduction: Power industry is one of the largest sources of CO2 emissions in China. The Yellow River Basin plays a supportive role in guaranteeing the effective supply of electricity nationwide, with numerous power generation bases. Understanding the drivers and peak of CO2 emissions of power industry in the Yellow River Basin is vital for China to fulfill its commitment to reach carbon emissions peak by 2030. Methods: The Logarithmic Mean Divisia Index (LMDI) model was employed to explore the drivers to the change of CO2 emissions in power industries of three study areas, including Inner Mongolia Autonomous Regions, Shanxi Province, and Shandong Province in the Yellow River Basin. And Back Propagation (BP) neural network was combined with scenario analysis to empirically predict the trend of the amount of CO2 emitted by power industry (CEPI) from provincial perspective. Results: CEPI in Inner Mongolia under the scenarios of a low degree of CO2 emissions promotion with a medium degree of CO2 emissions inhibition (LM) and a low degree of CO2 emissions promotion with a high degree of CO2 emissions inhibition (LH) scenario can reach a peak as early as 2030, with the peak value of 628.32 and 638.12 million tonnes, respectively. Moreover, in Shanxi, only CEPI under a low degree of CO2 emissions promotion scenarios (LL, LM, LH) can achieve the peak in 2025 ahead of schedule, with amounts of 319.32, 308.07, and 292.45 million tonnes. Regarding Shandong, CEPI under scenarios of a low degree of CO2 emissions promotion with a high degree of CO2 emissions inhibition (LH) and a medium degree of CO2 emissions promotion with a high degree of CO2 emissions inhibition (MH) could achieve the earliest peak time in 2025, with a peak of 434.6 and 439.36 million tonnes, respectively. Discussion: The earliest peak time of CEPI in Shandong Province and Shanxi Province is 2025, but the peak of CEPI in Shanxi is smaller than that of Shandong. The peak time of CEPI in Inner Mongolia is relatively late, in 2030, and the peak is larger than that of the other two provinces. The per capita GDP is the most positive driving factor that contributes to the CEPI. Shandong has a strong economy, and its per capita GDP is much higher than Shanxi's. Therefore, even under the same peak time, the CEPI in Shandong is much higher than that of Shanxi. Inner Mongolia is extensive and sparsely populated, which makes its per capita GDP rank among the top in China. In addition, Inner Mongolia's coal-based power generation structure and high power generation also contribute to its late CO2 peak time and large CO2 peak. [ABSTRACT FROM AUTHOR]

• Ecological restoration is not just an environmental issue and it is a societal problem. This paper analyzes ecological restoration and its impact on society in coal resource-based areas, focusing on the Ruhr region in Germany and Liulin County in China. Through the analysis and comparison, the study not only reveals the unique ecology-social system and explain the reasons for dependence on coal, but the finding shows that industrial transformation is a key factor in determining ecological restoration of coal resource-based regions. • The industries abandoned by the Ruhr area were taken over by China. Shanxi Province is very similar to the Ruhr area in terms of ecological destruction and social development at that time. The Ruhr region has become one of the most polluted areas in the world due to its coal and steel industry. After nearly 40 years of arduous practice, ecological governance and economic transformation in the Ruhr area achieved initial success. • Shanxi Province in China is a hub for energy and heavy chemical industries, and it ranks first in coal production nationally.. The Liulin county is located in the west of Shanxi Province, it is a typical coal mining subsidence and is scattered with numerous villages affected by subsidence due to coal mining. Shanxi Province and the Liulin county is undergoing difficult industrial transformation. • The author of this work visited the Duisburg-Essen University for a year, located in the Ruhr area of Germany, and learned about the ER and transformation in the Ruhr. When the author returned to China, she conducted field research for a two-month survey in Liulin County. Therefore, the author collected a large amount of literature ,data sources and gained practical experiences in these two areas. The coal resource-based areas rely on coal resources and primary processing as their pillar industries, such as the old industrial areas in China and Germany. Long-term, large-scale coal mining has significantly damaged the ecological environment of mining areas. Environmental restoration refers to repairing, rehabilitating, or revitalizing ecosystems that have been degraded, damaged, or destroyed by human activities or natural disasters. In fact, ecological restoration is not just an environmental issue and it is a societal problem. Ecological restoration is closely linked to natural resources, the environment, the economy, society, and politics. These factors form a social ecological system and it is the basis for local stability and sustainable development in the coal resource-based areas. In this process, the relationship between government, enterprise, and local people is constantly being reshaped and defined, then it causes changes in the local social ecology and political ecology. The paper researches the Ruhr area in Germany and the Liulin County in China, the former is a world-famous old industrial and the latter is a typical coal mining subsidence district. By analyzing and comparing the ecological restoration and significant social changes in the Ruhr area and the Liulin County at different periods, the findings show the unique ecology— social system of the coal resource-based area, then enhances the effective measures for ecological restoration and sustainable development of the coal resource-based areas. [ABSTRACT FROM AUTHOR]

Increased CO2 emissions from urban energy consumption pose a significant challenge to regional carbon mitigation policies. In this paper, we integrated two nighttime light (NTL) data: the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (NPP) composite data to estimate the energy carbon emissions from 2000 to 2019. Then the spatiotemporal dynamics of carbon footprint and deficit in the Yellow River Basin were analyzed at the provincial, municipal, and county scales combined with NPP data. The study shows that (1) the total amount of energy consumption CO2 emissions in the Yellow River Basin had increased from 1332 Mt in 2000 to 6469 Mt in 2019, but the average annual growth rate slowed down after 2010 from 11.5 to 5.61%. (2) From 2000 to 2018, the provinces with the highest carbon footprint and carbon deficit were concentrated in Inner Mongolia and Shanxi. In 2018, Inner Mongolia's carbon footprint was 1366.91 × 104 km2, accounting for 22.8% of the total. Cities with high carbon footprint were mainly economic centers and energy-intensive areas of various provinces. High-carbon deficit counties were mainly distributed in the western region. In 2018, 954 counties exhibited carbon deficits. (3) The carbon footprint in the Yellow River Basin at the municipal and county scales have a significant spatial correlation. The H–H clusters of the carbon footprint on the municipal scale were distributed in the middle reaches of the Yellow River Basin. At the county scale, the L-L clusters were mainly in Sichuan and eastern Henan regions. Through the analysis of the spatial and temporal evolution of carbon footprint and carbon deficit in the Yellow River Basin, it is significant to measure the degree of comprehensive coordination of carbon sources and sinks in the basin, to grasp the differences in the level of regional carbon emissions, and to promote synergistic regional governance, assist in the formulation of more precise carbon emission reduction policies, and to promote green and high-quality development. [ABSTRACT FROM AUTHOR]

Economic transformation and development serve as effective strategies for resource-based regions to avoid the "resource curse." By optimizing industrial structure and enhancing energy efficiency through government macro-regulation, these regions can achieve sustainable and environment-friendly growth. The general equilibrium model is widely employed to assess the effectiveness of economic transformation and development. In this study, we constructed a provincial social accounting matrix based on macro data from Shanxi, China, to examine the impact of different environmental protection tax rates on the macro economy, industrial structure, and energy consumption. The findings reveal that the implementation of environmental protection tax has successfully optimized the industrial structure and improved energy utilization efficiency. However, it has also led to a slight decline in total output. Hence, it is imperative to establish a more balanced and reasonable environmental protection tax rate to further promote economic transformation and development in resource-based areas. Consequently, this paper puts forth policy recommendations aimed at achieving a harmonious balance between ecological preservation and economic progress in resource-based regions, ultimately enhancing the overall quality of economic development in such areas. • Economic transformation and development are effective ways for resource-based regions to avoid the "resource curse". • This paper is based on macro data from Shanxi, and constructs a provincial social accounting matrix to study the impact of different environmental protection tax rates on macroeconomic, industrial structure, and energy consumption. • Setting a reasonable environmental protection tax rate can promote the economic transformation and development of resource-based areas [ABSTRACT FROM AUTHOR]

Achieving an efficient, modern, and sustainable energy transition towards carbon neutrality has attracted worldwide attentions. Composite statistical indices are increasingly recognized as valuable tools for policymakers, offering enhanced understanding of the present condition and anticipated direction of energy transition. In this research, we constructed a comprehensive index to track provincial energy transition in China. With this index, we monitored the energy transition progress of 30 provinces in China. The Provincial energy transition index (PETI) scores exhibited considerable heterogeneity across provinces and throughout different time periods, with eastern provinces having the highest scores, and some northwestern and large coal provinces, like Shanxi, having the lowest scores. These findings indicated that provincial energy transition policies should be tailored to the local energy status and economic structures. The paper delineated conclusions and policy implications derived from the study's extensive evaluation. Specifically, effective ways to further improve a region's sustainable energy transition path include advancing the use of clean energy, vigorously promoting power grid construction, and investing in new energy sectors. The implementation of these strategies is expected to reduce energy consumption and carbon intensity, thereby decreasing carbon emissions, then ultimately accelerating the realization of the dual carbon targets. • We present a provincial energy transition index to track regional energy transition process. • There was significant heterogeneity in PETI scores across different provinces. • There were disparities among the performances in the three dimensions of the PETI. • Energy transition policies ought to give precedence to regions that are lagging in their energy transition. [ABSTRACT FROM AUTHOR]

The excessive utilization of cesarean section (CS) has become a global concern, given the potential short-term and long-term detrimental effects for mothers and infants. Worldwide, the rate of CS continues to rise, but efforts to curtail unnecessary CS procedures have yielded limited success. By combining data from three resources, this study aims to estimate the effects of anti-corruption campaigns under the Xi administration on CS rates. We focus on Shanxi Province, a major coal-producing province in north-central China, with notoriety for the collusion between local politicians and business elites. Using the data from the China Corruption Investigation Dataset and data from publicly listed firms between 2013 and 2016, we found that anti-corruption campaigns significantly changed the social environment as firms' business entertainment spending experienced substantial reductions. Using discharge records from 137 public hospitals, we adopted an instrumental variable (IV) approach and found that the anti-corruption campaigns led to significant reductions in unnecessary CS rates. The reductions are bigger among patients with second or later deliveries. We also find that the anti-corruption campaigns changed behaviors of attending and resident physicians. Our results provide insights into strategies to reduce corrupt practices within the healthcare sector and implementing interventions to minimize the occurrence of CS among healthy women and newborns. [ABSTRACT FROM AUTHOR]

The realisation of the low-carbon transition of the energy system in resource-intensive regions, as embodied by Shanxi Province, depends on a thorough understanding of the factors impacting the power sector's carbon emissions and an accurate prediction of the peak trend. Because of this, the power industry's carbon emissions in Shanxi province are measured in this article from 1995 to 2020 using data from the Intergovernmental Panel on Climate Change (IPCC). To obtain a deeper understanding of the factors impacting carbon emissions in the power sector, factor decomposition is performed using the Logarithmic Mean Divisia Index (LMDI). Second, in order to precisely mine the relationship between variables and carbon emissions, the Sparrow Search Algorithm (SSA) aids in the optimisation of the Long Short-Term Memory (LSTM). In order to implement SSA-LSTM-based carbon peak prediction in the power industry, four development scenarios are finally built up. The findings indicate that: (1) There has been a fluctuating upward trend in Shanxi Province's total carbon emissions from the power industry between 1995 and 2020, with a cumulative growth of 372.10 percent. (2) The intensity of power consumption is the main factor restricting the rise of carbon emissions, contributing -65.19%, while the per capita secondary industry contribution factor, contributing 158.79%, is the main driver of the growth in emissions. (3) While the baseline scenario and the rapid development scenario fail to peak by 2030, the low carbon scenario and the green development scenario peak at 243,991,100 tonnes and 258,828,800 tonnes, respectively, in 2025 and 2028. (4) Based on the peak performance and the decomposition results, resource-intensive cities like Shanxi's power industry should concentrate on upgrading and strengthening the industrial structure, getting rid of obsolete production capacity, and encouraging the faster development of each factor in order to help the power sector reach peak carbon performance. [ABSTRACT FROM AUTHOR]

To investigate the contents of carbon, nitrogen, and phosphorus in tea plantation soils and their ecological stoichiometric characteristics, as well as their response to environmental factors in high-latitude regions of China, soil samples from 0 to 20 cm depth were collected from tea plantations at different altitudes and cultivation years in the main tea-producing areas of Shaanxi Province. These samples were used to determine the soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) contents and to calculate their stoichiometric ratios. The findings revealed the following: the average soil SOC and TN content in tea gardens were 13.15 and 1.30 g·kg−1, respectively, exceeding the national soil average. These values met the Class I tea garden fertility standards. However, the average soil TP content, at 0.45 g·kg−1, fell below the national soil average, meeting the Class II tea garden fertility standards. In tea gardens, the average ratios of carbon to nitrogen (C:N), carbon to phosphorus (C:P), and nitrogen to phosphorus (N:P) in the soil were 10.42, 30.98, and 3.32, respectively. These ratios were all lower than the national soil average, indicating relatively high phosphorus availability but nitrogen deficiency in tea garden soils. As altitude increased, there was a decline in soil SOC content, C N, and C P ratios, followed by a subsequent increase. No significant changes were seen in TN, TP, and N P ratio in the soil, but there was an increase in SOC content, TN content, and C P ratio during cultivation. The N-to-P ratio initially increased before decreasing, while the C-to-N ratio decreased before increasing. Soil TP content did not change significantly. The study recommends careful nitrogen fertilizer application in tea garden management to balance nitrogen and phosphorus. [ABSTRACT FROM AUTHOR]

Special attention was drawn to the heavy metals contained in coal, due to it will cause harm to the environment during coal processing and utilization. The sequential chemical extraction of Shanxi coal (SX coal) and Wulanchabu coal (WLCB coal) was carried out to investigate the distribution of arsenic (As) in coals. Two raw coals were pyrolyzed at 300–900 °C in horizontal tubular furnace to investigate release behavior of As during pyrolysis process. The results showed that As in SX coal mainly existed in aluminosilicate-bound state (40.25%) and disulfide-bound state (32.51%), followed by carbonate-bound state and organic-bound state. The As in WLCB coal mainly existed in aluminosilicate-bound state (62.50%), followed by disulfide-bound state (19.10%). The As contents of water-soluble, ion-exchange and residue states in the two coals were less than others. The modes of occurrence of As had great influence on its volatilization behavior. As in organic part was easy to volatilize at low temperature. Sulfide-bound state would escape with the decomposition of pyrite. Because SX coal contained higher organic state and sulfide-bound state, the volatilization rate of As was higher than WLCB coal at any temperature, and the difference was more obvious at low temperature. In addition, FactSage simulation value was basically consistent with the experimental value. [ABSTRACT FROM AUTHOR]

Seven pieces of gold foils for surface decoration of the lacquerware were excavated in the late Western Han Dynasty tomb in the area of the Jin Yang (晋阳) Ancient City site in Taiyuan (太原), Shanxi (山西), China. These gold foils portray images of the carriage, the leopard, the tigers, the ox, and the dancer with fluttering sleeves, etc., with black lines outlining the contours and red paint depicting vivid patterns. The study used Stereo Microscopes, Metallurgical Microscopy, Environmental Scanning Electron Microscopy coupled with Energy-Dispersive X-ray Spectroscopy (ESEM-EDS), and Laser Raman Spectroscopy (LRS) to analyse the thickness of the gold foils, the alloy composition, the composition of the paint and other surface attachments, and investigate the manufacturing process. As the results show, the thickness of the gold foils is about 26 μm. The composition is a gold-silver alloy with about 96% Au/(Au + Ag) (surface) and 98% Au/(Au + Ag) (cross-section). The metallurgical observation shows that the gold foils underwent heating and forging. The black lines on the front side are Chinese ink lines, with cracking and peeling phenomenon, and parallel polishing lines can be seen at the peeling places, while no polishing lines are observed on the back side. Some red paint made of cinnabar is above the black lines, and the binder is organic. Some lacquer residues are found on the back. According to the results of the study, the manufacturing process of the gold foils applied on the lacquerware is as follows: the gold foils are obtained by heating and forging, the front sides of the gold foils are polished, the shapes are carved out, and the gold foils are pasted on the lacquerware when the lacquerware's surface is not yet dry. The gold foils are painted with black Chinese ink and red cinnabar pigment. The study's results offer important references for understanding the manufacturing craft of the gold foils applied on the lacquerware in the late Western Han Dynasty of China and guide the conservation of the lacquerware decorated with painted gold foils. [ABSTRACT FROM AUTHOR]

Extreme drought and flood events, as well as their combined events, pose significant challenges to global sustainable socio-economic development and ecological health. However, the impact of dry–wet combination events (DWCEs) on vegetation vulnerability remains to be investigated. The Loess Plateau (LP) was selected as the study area to explore the response time of vegetation to precipitation index changes by optimal correlation coefficient; then, the impact of different DWCEs on vegetation vulnerability under moderate and severe scenarios was analyzed; finally, a vegetation loss probability model was constructed based on the copula function and Bayesian framework, to quantify the vegetation loss probability under DWCEs stress. The results indicate that: (1) normalized difference vegetation index (NDVI) shows an upward trend in spring, summer, and autumn, with the proportion of areas are 90.5%, 86.2%, and 95.4%, respectively, and show an insignificant trend in winter; (2) the response time of vegetation to precipitation index changes tends to be one or two seasons; (3) moderate scenarios have more influence than severe scenarios, dry-to-wet events (DWEs), wet-to-dry events (WDE) and continuous dry events (CDE) in spring-summer have a significant impact on summer vegetation of Ningxia and Shanxi, and WDE and CDE have a higher impact on autumn vegetation. (4) in terms of the probability of vegetation loss, DWE, and CDE cause higher losses to summer vegetation, while WDE and CDE cause higher losses to autumn vegetation. This study quantifies the impact of adjacent seasonal DWCE stress on future vegetation vulnerability. [ABSTRACT FROM AUTHOR]

In order to ensure the safety of coal mine production, a mine water source identification model is proposed to improve the accuracy of mine water inrush source identification and effectively prevent water inrush accidents based on kernel principal component analysis (KPCA) and improved sparrow search algorithm (ISSA) optimized kernel extreme learning machine (KELM). Taking Zhaogezhuang mine as the research object, firstly, Na+, Ca2+, Mg2+, Cl-, SO2- 4 and HCO- 3 were selected as evaluation indexes, and their correlation was analyzed by SPSS27 software, with reducing the dimension of the original data by KPCA. Secondly, the Sine Chaotic Mapping, dynamic adaptive weights, and Cauchy Variation and Reverse Learning were introduced to improve the Sparrow Search Algorithm (SSA) to strengthen global search ability and stability. Meanwhile, the ISSA was used to optimize the kernel parameters and regularization coefficients in the KELM to establish a mine water inrush source discrimination model based on the KPCA-ISSA-KELM. Then, the mine water source data are input into the model for discrimination in compared with discrimination results of KPCA-SSA-KELM, KPCA-KELM, ISSA-KELM, SSA-KELM and KELM models. The results of the study show as follows: The discrimination results of the KPCA-ISSA-KELM model are in agreement with the actual results. Compared with the other models, the accuracy of the KPCA-ISSA-KELM model is improved by 8.33%, 12.5%, 4.17%, 21.83%, and 25%, respectively. Finally, when these models were applied to discriminate water sources in a coal mine in Shanxi, and the misjudgment rates of each model were 28.57%, 19.05%, 14.29%, 23.81%, 9.52% and 4.76%, respectively. From this, the KPCA-ISSA-KLEM model is the most accurate about discrimination and significantly better than other models in other evaluation indicators, verifying the universality and stability of the model. It can be effectively applied to the discrimination of inrush water sources in mines, providing important guarantees for mine safety production. [ABSTRACT FROM AUTHOR]

Forests are vital for terrestrial ecosystems, providing crucial functions like carbon sequestration and water conservation. In the Yellow River Basin, where 70% of forest coverage is concentrated in the middle reaches encompassing Sichuan, Shaanxi, and Shanxi provinces, there exists significant potential for coal production, with nine planned coal bases. This study centered on Jincheng City, Shanxi Province, a representative coal mining area in the Yellow River Basin, and combined the MSPA analysis method and MCR model to generate the five-period forest ecological network of Jincheng City from 1985 to 2022 under the background of coal mining and calculate the degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality; the correlation between the four centralities and carbon sequestration ability is further explored. Simultaneously, employing the RAND-ESU algorithm for motif identification within forest ecological networks, this study integrates the ecological policies of the research area with the specific conditions of the coal mining region to optimize the forest ecological network in Jincheng City. Findings reveal the following. (1) Forest ecological spatial networks: Forest ecological networks exhibit robust overall ecological connectivity in the study area, with potential ecological corridors spanning the region. However, certain areas with high ecological resistance hinder connectivity between key forest ecological nodes under the background of coal mining. (2) Correlation between topological indices and carbon sequestration ecological services: From 1985 to 2022, the carbon sequestration capacity of Jincheng City's forest source areas increased year by year, and significant positive correlations were observed between degree centrality, betweenness centrality, eigenvector centrality with carbon sequestration ecological services, indicating a strengthening trend over time. (3) Motif Recognition and Ecological Network Optimization: During the study, four types of motifs were identified in the forest ecological network of Jincheng City based on the number of nodes and their connections using the RAND-ESU network motif algorithm. These motifs are 3a, 4a, 4b, and 4d (where the number represents the number of nodes and the letter represents the connection type). Among these, motifs 3a and 4b play a crucial role. Based on these motifs and practical considerations, network optimization was performed on the existing ecological source areas to enhance the robustness of the forest ecological network. [ABSTRACT FROM AUTHOR]

Objective: To understand the epidemiological distribution characteristics of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) in Yangquan City, Shanxi Province, China, from 2006 to 2021, to explore the influencing factors leading to the re-emergence of the epidemic, and to provide a basis for the formulation of targeted control strategies. Methods: Case information spanning from 2006 to 2021 in Yangquan City was collected for a retrospective case-control study conducted from June to September 2022. A 1:3 matched ratio was employed. A questionnaire was utilized to gather data on basic information, demographic characteristics, awareness of MT-ZVL knowledge, residence, and dog breeding and living habits. The study employed a multifactorial conditional stepwise logistic regression model to analyze the influencing factors. Results: A total of 508 subjects was analyzed. Risk factors for MT-ZVL included the use of soil/stone/concrete as building materials (OR = 3.932), presence of nearby empty/stone stack houses (OR = 2.515), dog breeding (OR = 4.215), presence of stray dogs (OR = 2.767), and neighbor's dog breeding (OR = 1.953). Protective factors comprised knowledge of MT-ZVL (OR = 0.113) and using mosquito repellents (OR = 0.388). The findings indicate significant associations between environmental and behavioral factors and MT-ZVL incidence in Yangquan City, Shanxi Province, China, from 2006 to 2021. These results underscore the importance of public awareness campaigns and targeted interventions aimed at reducing exposure to risk factors and promoting protective measures to mitigate the re-emergence of MT-ZVL outbreaks. Conclusion: House building materials, presence of neighboring empty houses, breeding domestic dogs and distribution of stray dogs surrounding the home are risk factors for MT-ZVL. Awareness of MT-ZVL and implementation of preventive measures during outdoor activities in summer and autumn are protective and may reduce the risk of MT-ZVL. Author summary: In recent years, a rapid reemergence of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) has been seen in the extension region of the Loess Plateau that had previously achieved elimination in China. In this study, we investigate the epidemiological characteristics of MT-ZVL and identify the factors associated with the rapid rise in MT-ZVL epidemics using a case-control design. A questionnaire was used to collect basic information, demographic characteristics, awareness of MT-ZVL knowledge, residence, and dog breeding and living habits. A multifactorial conditional stepwise logistic regression model was used to analyze the influencing factors. The study revealed that there has been a rising trend in the MT-ZVL endemic areas. House building materials, presence of neighboring empty houses, breeding domestic dogs and distribution of stray dogs surrounding the home are risk factors for MT-ZVL. Awareness of MT-ZVL and implementation of preventive measures during outdoor activities in summer and autumn are protective and may reduce the risk of MT-ZVL. We believe that our study makes a significant contribution to the literature to develop strategy for control the ongoing local transmission of MT-ZVL in hill districts. By analyzing the epidemiological characteristics and influencing factors of MT-ZVL, this research provides a basis for further optimizing the targeted control strategies. [ABSTRACT FROM AUTHOR]

Background: As a chronic metabolic disease, diabetes poses a serious threat to human health and has become a major public health problem in China and worldwide. In 2020, 30% of Chinese people (aged ≥ 60 years) reported having diabetes mellitus. Moreover, individuals with diabetes living in rural areas face a significantly higher mortality risk compared to those in urban areas. In this study, we explored the inner experience of self-management behaviors in elderly patients with type 2 diabetes in rural areas to inform targeted interventions. Methods: A phenomenological research design was used to explore the inner experience of self-management in rural elderly diabetes. Ten elderly diabetic patients were sampled from December 2022 to March 2023 in rural areas of Yangcheng County, Jincheng City, ShanXi Province, China. The seven-step Colaizzi phenomenological was used to analyze the interview data and generate themes. Results: Four themes emerged: "Insufficient self-management cognition", "Negative self-management attitude", "Slack self-management behavior", and "No time for self-management". Conclusion: The level of self-management among elderly patients with type 2 diabetes in rural areas is low. Healthcare professionals should develop targeted interventions aimed at enhancing their cognitive levels, modifying their coping styles, and improving their self-management abilities to improve their quality of life. [ABSTRACT FROM AUTHOR]

The Baijiu industry is a significant contributor to both the food industry and the light industry. Its high tax characteristics effectively promote the sustainable development of the regional economy. First, the evaluation index system of scientific and technological innovation (STI) and high-quality development of Baijiu industry (HQDBI) were constructed. The entropy-improved CRITIC method was used to measure the weights. Second, the coordination relationship and evolution trend of STI and HQDBI were explored using the coupling coordination model and the Tapio decoupling model. Then, the transfer law and key influencing factors were further investigated using the Markov chain and grey correlation, respectively. The main contribution is the dynamic evolution of the coupling and decoupling relationships from the perspective of multiple Baijiu provinces, and deeply depicts the coordination relationship and evolutionary trends of STI and HQDBI. The results show that: the spatial distribution of the coupling coordination degree shows high values in the east-west and low values in the north-south characteristics. In 2021, a pattern of coordinated development in Baijiu provinces has emerged along the Yangtze River basin. The decoupling state is mainly strong decoupling, but it remains poor in Shanxi. The coordination process is unstable and difficult to achieve leapfrog development. Coordination, sustainability and innovation environment have a greater impact on the coordination of subsystems. [ABSTRACT FROM AUTHOR]

Objective: Unsafe medication practices and medication errors are a major cause of harm in healthcare systems around the world. This study aimed to explore the factors that influence the risk of medication and provide medication risk evaluation model for adults in Shanxi province, China. Methods: The data was obtained from the provincial questionnaire from May to December 2022, relying on the random distribution of questionnaires and online questionnaires by four hospitals in Shanxi Province. Multiple linear regression analysis was used to explore the factors affecting the KAP score of residents. Univariate and multivariate logistic regression was used to determine the independent risk factors, and the nomogram was verified by receiver operating characteristic curve, calibration and decision curve analysis. Results: A total of 3,388 questionnaires were collected, including 3,272 valid questionnaires. The average scores of drugs KAP were 63.2 ± 23.04, 33.05 ± 9.60, 23.67 ± 6.75 and 33.16 ± 10.87, respectively. On the evaluation criteria of the questionnaire, knowledge was scored "fair", attitude and practice were scored "good". Sex, monthly income, place of residence, insurance status, education level, and employment were regarded as independent risk factors for medication and a nomogram was established by them. Conclusion: Males, low-income, and low-educated people are important factors affecting the risk of medication. The application of the model can help residents understand the risk of their own medication behavior and reduce the harm of medication. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the characteristics of the combined application of organic fertilizer and inorganic fertilizer using different tillage methods to delay the senescence of maize leaves. The yield and activities of GDH, CAT, APX, GR, and GSH enzymes in maize leaves were measured at different growth stages by using two tillage methods, three organic and inorganic combined applications (P1, P2, and P3), and four control treatments. (1) During the growth period, the R + S and R treatments were P1 treatments, with the highest enzyme activities noted for GDH, CAT, APX, GR, and GSH, which were 36.79–103.22% higher than those of CK. (2) The average yield of all R + S treatments was higher than that of R treatments, and the average yield of P1 treatment was the highest under R + S, which was 13,663.79 kg hm−2, which was 6.39%, 7.90%, and 14.67% higher than that of P2, P3, and CK, respectively, which was lower than that of R. The yield of P1 treatment was 2.53% higher. (3) There was a significant positive correlation between APX activity, CAT activity, GR activity, GDH activity, GSH activity, grain number per ear, ear length, and 100-grain weight of maize leaves at the grain filling stage, and a significant negative correlation between bald tip length and yield. The treatment details had the strongest enzyme activity and the highest yield when using the rotary tillage + subsoiling (R + S) P1 method, which was the most suitable tillage method and the best fertilizer ratio combination, which could be demonstrated and popularized in a large area in the dry farming area of spring maize in Shanxi Province. [ABSTRACT FROM AUTHOR]

Satellite-based detection of methane (CH4) point sources is crucial in identifying and mitigating anthropogenic emissions of CH4 , a potent greenhouse gas. Previous studies have indicated the presence of CH4 point source emissions from coal mines in Shanxi, China, which is an important source region with large CH4 emissions, but a comprehensive survey has remained elusive. This study aims to conduct a survey of CH4 point sources over Shanxi's coal mines based on observations of the Advanced Hyperspectral Imager (AHSI) on board the Gaofen-5B satellite (GF-5B/AHSI) between 2021 and 2023. The spectral shift in centre wavelength and change in full width at half-maximum (FWHM) from the nominal design values are estimated for all spectral channels, which are used as inputs for retrieving the enhancement of the column-averaged dry-air mole fraction of CH4 (ΔXCH4) using a matched-filter-based algorithm. Our results show that the spectral calibration on GF-5B/AHSI reduced estimation biases of the emission flux rate by up to 5.0 %. We applied the flood-fill algorithm to automatically extract emission plumes from ΔXCH4 maps. We adopted the integrated mass enhancement (IME) model to estimate the emission flux rate values from each CH4 point source. Consequently, we detected CH4 point sources in 32 coal mines with 93 plume events in Shanxi province. The estimated emission flux rate ranges from 761.78 ± 185.00 to 12 729.12 ± 4658.13 kgh-1. Our results show that wind speed is the dominant source of uncertainty contributing about 84.84 % to the total uncertainty in emission flux rate estimation. Interestingly, we found a number of false positive detections due to solar panels that are widely spread in Shanxi. This study also evaluates the accuracy of wind fields in ECMWF ERA5 reanalysis by comparing them with a ground-based meteorological station. We found a large discrepancy, especially in wind direction, suggesting that incorporating local meteorological measurements into the study CH4 point source are important to achieve high accuracy. The study demonstrates that GF-5B/AHSI possesses capabilities for monitoring large CH4 point sources over complex surface characteristics in Shanxi. [ABSTRACT FROM AUTHOR]

Strong soil erosion and increasing human activities have made Loess Plateau areas ecologically fragile regions. Constructing the ecological security pattern (ESP) is imperative to maintain their ecosystem functions and sustainable development. However, it is still challenging to establish the ESP in such an unstable and scattered ecological environment. In this study, we take Shanxi Province, which suffers severe ecological problems in Loess Plateau areas, as an example to construct the ESP in a pattern of "source-resistance-corridor". The proposed methods include the following steps: (1) potential ecological sources are selected with important ecosystem functions based on contributions of soil and water conservation, habitat quality, and carbon storage; (2) ecological sources are determined by considering core areas at the landscape scale based on morphological spatial pattern analysis (MSPA) along with stability based on dynamic assessment on previous sources; (3) the comprehensive resistance surface is constructed by multiple resistance factors and remotely sensed nighttime light data; (4) ecological corridors are simulated and extracted based on circuit theory. As a result, the proposed ESP in our study area mainly includes 13,592 km2 of ecological sources, 8519.64 km of ecological corridors, and 277 ecological nodes. Meanwhile, an ecological framework of "two axes, three belts, and three zones" was proposed based on the optimization and reorganization of ecological components within the ESP. Our research lays a methodological and practical foundation for regional ESP construction and sustainable development in Loess Plateau areas. [ABSTRACT FROM AUTHOR]

The simulated digestion and fermentation characteristics in vitro of exopolysaccharide (EPS) of Levilactobacillus brevis M‐10 were studied to evaluate its postbiotic properties. The simulated digestion results showed that EPS could not be degraded in saliva but could be very slightly degraded in gastric juice and could be degraded in intestinal juice. The results of simulated fermentation demonstrated that EPS could lower the intestine pH and be utilized by gut microbes to produce short‐chain fatty acids such as propionic acid and butyric acid. Meanwhile, EPS significantly raised the diversity of human gut microbiota, and the relative abundances of Phascolarctobacterium were significantly increased, whereas Fusobacterium and Morganella significantly decreased. In conclusion, EPS from L. brevis M‐10 was a good postbiotic as inulin. This was the first report about EPS as the postbiotic of L. brevis M‐10 screened from broomcorn millet sour porridge in northwestern Shanxi Province, China. [ABSTRACT FROM AUTHOR]

There is a huge reservation of loess in the Shanxi mining area in China, which has great potential for preparing supplementary cementitious materials. Loess was modified via mechanical and thermal activation, and the pozzolanic activity was evaluated using an Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES). Moreover, the workability of grouting materials prepared using modified loess was assessed. The experimental results revealed that the number of ultrafine particles gradually increased with the grinding time, enhancing the grouting performance. The coordination number of Al decreased upon the breakage of the Al–O–Si bond post-calcination at 400 °C, 550 °C, 700 °C, and 850 °C. Moreover, the breaking of the Si–O covalent bond produced Si-phases, and the pozzolanic activity of loess increased. Furthermore, the modified loess was hydrated with different cement proportions. With increasing grinding time, the overall setting time increased until the longest time of 14.5 h and the fluidity of the slurry decreased until the lowest fluidity of 9.7 cm. However, the fluidity and setting time decreased with increasing calcination temperature. The lowest values were 12.03 cm and 10.05 h. With the increase in pozzolanic activity, more ettringite was produced via hydration, which enhanced the mechanical properties. The maximum strength of the hydrated loess after grinding for 20 min reached 16.5 MPa. The strength of the hydrated loess calcined at 850 °C reached 21 MPa. These experimental findings provide theoretical support for the practical application of loess in grouting. [ABSTRACT FROM AUTHOR]

This study systematically investigates the impact of pre-stretching amount (PSA) on the acceleration, motion status, and screening efficiency of the Flip-flow screen plate (FFSP). Initially, a nonlinear spring-multi-body model of the FFSP is established. Subsequently, the acceleration signals at the midpoint of the FFSP under various PSAs are measured and analyzed. The nonlinear stiffness coefficient of FFSP along the vertical direction is then determined and it is found that simplifying the nonlinear spring-multi-body system to a nonlinear spring-tri-body system under the experimental conditions can maintain the calculation error of FFSP's acceleration within 30%. Phase and Poincaré mapping diagrams of the FFSP under different PSAs are subsequently created to illustrate the impact of PSA on the motion status of the FFSP. Finally, screening experiments are performed to study the optimal PSA for a kind of bituminous coal from Shanxi province. [ABSTRACT FROM AUTHOR]

This paper examines how perceived social equity (distributional equity, procedural equity, and recognitional equity) affects acceptance of protected areas by local communities. We also consider the consequences of these perceptions on the behaviour of local people in relation to biodiversity conservation. Despite increasing importance being given to social issues in protected area management, there is limited evidence about the effect of perceived equity on local support for conservation initiatives. Questionnaires (mostly face-to-face interviews) were undertaken with 426 households living in and around the Giant Panda National Park, which lies across the Sichuan, Shanxi and Gansu provinces of China. Structural equation modelling revealed that local residents with positive perceptions of procedural and distributional equity were more willing to support conservation and engage in conservation behaviours. Surprisingly, perceived recognitional equity had no effect on acceptance and negatively impacted conservation behaviour. This highlights that, although it is essential to promote recognitional equity, the complexities around this must be considered further. The context (e.g. age, education, village of residence) moderates the relationships between procedural equity, distributional equity and local acceptance. We suggest that, in order to achieve better park-people relationships, in addition to addressing equity concerns, it is also necessary to implement supplementary measures, such as community co-management and benefit sharing with host communities. • Procedural and distributional equity facilitate acceptance of protected areas. • Recognitional equity has an intricate relationship with local support. • Perceived justice tends to be non-linear in relation to local support. • The location of communities influences local pro-conservation behaviours. • There is a need for a better understanding of the equity-acceptance relationship. [ABSTRACT FROM AUTHOR]

• Water resources system has multi-link characteristics. • The resilience evaluation index system of water resources system is constructed. • The resilience of regional water resources system is evaluated. • The temporal and spatial evolution characteristics of resilience are analyzed. As environmental and human changes combine, water shortage and ecological fragility are becoming increasingly serious issues in the basin. The national "14th Five-Year Plan" proposes to build resilient basins to enhance disaster resilience. On the basis of clarifying the multi-link characteristics of water resources system resilience under the influence of meteorology-hydrology-ecology-society-economy, this paper reveals the interrelationship and chain reaction among the factors affecting the resilience of water resources system by clarifying the multi-link characteristics of water resources system resilience. Based on the interconnections among meteorology-hydrology-engineering-economic society-ecology in regional water resources systems, this study constructs a resilience evaluation index for the water resources system. The index considers different objectives, dimensions, and scales to provide a comprehensive assessment of the system's resilience. Based on the multi-dimensional relationship of the evaluation index system, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method based on entropy weight method is employed to depict the resilience level of the water resources system at varying spatial and temporal scales. By focusing on Shanxi Province as the research subject, a multi-link evaluation framework for assessing the resilience of the water resources system is established, and a quantitative approach to evaluate its resilience is investigated. The results show that the level of water resources resilience in Shanxi Province has improved from 2017 to 2021, and there are certain spatial and temporal differences. In 2021, only Lvliang City and Yangquan City have low resilience level, and the resilience level of other cities has been improved. Among them, Taiyuan City has the highest resilience level of 0.56, which belongs to the high resilience level. The research results can improve the cognitive level of multi-link evolution mechanism of resilience to a certain extent, and provide scientific basis for multi-dimensional targeted regulation of water resources system resilience. [ABSTRACT FROM AUTHOR]

Bromus japonicus is a common monocot weed that occurs in major winter wheat fields in the Huang–Huai–Hai region of China. Pyroxsulam is a highly efficient and safe acetolactate synthase (ALS)-inhibiting herbicide that is widely used to control common weeds in wheat fields. However, B. japonicus populations in China have evolved resistance to pyroxsulam by different mutations in the ALS gene. To understand the resistance distribution, target-site resistance mechanisms, and cross-resistance patterns, 208 B. japonicus populations were collected from eight provinces. In the resistant population screening experiment, 59 populations from six provinces showed different resistance levels to pyroxsulam compared with the susceptible population, of which 17 B. japonicus populations with moderate or high levels of resistance to pyroxsulam were mainly from the Hebei (4), Shandong (4) and Shanxi (9) Provinces. Some resistant populations were selected to investigate the target site-resistance mechanism to the ALS-inhibiting herbicide pyroxsulam. Three pairs of primers were designed to amplify the ALS sequence, which was assembled into the complete ALS sequence with a length of 1932 bp. DNA sequencing of ALS revealed that four different ALS mutations (Pro-197-Ser, Pro-197-Thr, Pro-197-Phe and Asp-376-Glu) were found in 17 moderately or highly resistant populations. Subsequently, five resistant populations, QM21-41 with Pro-197-Ser, QM20-8 with Pro-197-Thr and Pro-197-Phe, and QM21-72, QM21-76 and QM21-79 with Asp-376-Glu mutations in ALS genes, were selected to characterize their cross-resistance patterns to ALS inhibitors. The QM21-41, QM20-8, QM21-72, QM21-76 and QM21-79 populations showed broad-spectrum cross-resistance to pyroxsulam, mesosulfuron–methyl and flucarbazone–sodium. This study is the first to report evolving cross-resistance to ALS-inhibiting herbicides due to Pro-197-Phe mutations in B. japonicus. [ABSTRACT FROM AUTHOR]

Based on the 'three highs and one low' geological conditions of high gas pressure, high gas content, high ground stress, and low permeability in deep coal seams, this study proposes a dual method of hydraulic fracturing of key layers of overlying rock layers combined with pre-extraction of gas via large-diameter caving boreholes. The aim is to unload and dissipate the coal seam by fracturing the overlying key strata, allowing the stress and energy from the excavation working face to be transmitted and transferred to the deep coal seam. Additionally, large-diameter drilling effectively increases the effective drainage radius of the coal seam, resulting in a shorter extraction time. To validate this approach, a fracturing model and a gas extraction model were established for the key layers of the overlying rock layer using the engineering background of the 15,111 excavation working face of a mine in Shanxi. FLAC3D software v.6.0 was utilized to simulate the stress and energy changes of the coal seam before and after fracturing of the key layers, while COMSOL software v.6.0 was used to analyze the gas migration conditions, permeability, and effective drainage radius changes before and after drilling and caving drilling. The findings, combined with the engineering test results, conclude that key strata fracturing combined with large-diameter caving can effectively increase the permeability of coal seams and improve gas extraction. This study serves as a theoretical basis for guiding the design of gas drainage technology under the effects of coal seam pressure relief and permeability enhancement. [ABSTRACT FROM AUTHOR]

Background: The attrition of nursing staff significantly contributes to the shortage of healthcare professionals. This study entailed an examination of the propensity of nurses to sustain employment within Grade-A tertiary general hospitals and the various influencing factors. Methods: A total of 2,457 nurses from three grade-A tertiary general hospitals were surveyed. The survey instruments included a general information questionnaire, a scale measuring their willingness to continue working, and a Chinese version of the Magnet Hospital Factor scale. Results: The scores of the willingness to continue working scale and the Magnet Hospital Factor scale were 21.53 ± 4.52 and 145.46 ± 25.82, respectively. There were statistically significant differences in the scores of willingness of nurses to continue working across various factors, including the department, age, marital status, family location, length of service as nurses, professional title, position, and employment type, upon comparison (P < 0.001). The correlation analysis showed that there was a positive correlation between the willingness of nurses to continue working and the magnet hospital factors, with a correlation coefficient of 0.523 (P < 0.01). Regression analysis showed that department, length of service as nurses, professional title, position, average monthly income, number of night shifts, medical care relationship, educational support, and nursing manager support among the magnet hospital factors were important predictors of willingness to continue working (P < 0.001). Conclusion: The willingness of nurses to continue working in grade-A tertiary general hospitals in Shanxi Province was determined to be at an upper-middle level. The magnet status of grade-A tertiary general hospitals needs to be improved, and there are many factors that influenced willingness of nurses to continue working. To cultivate a more favorable environment and bolster nurse recruitment and retention, all healthcare institutions should strive to establish a magnet nursing environment, thereby fostering the robust development of the nursing team. [ABSTRACT FROM AUTHOR]

Stand spatial structure plays a key role in forest management, and in particular the random structural unit, comprising random tree and its neighbors, largely determines forest stability and its productivity. However, how the spatial structure of the random structural unit affects productivity remains unclear. The study focused on four larch forest types from Hebei and Shanxi provinces, China: 35‐year‐old larch (Larix principis‐rupprechtii) plantations (35LP), 39‐year‐old mixed larch–birch (Betula platyphylla) forests (39LB), 58‐year‐old natural larch forests (58LN), and 73‐year‐old mixed larch–birch–spruce (Picea asperata) forests (73LBS). The forest spatial structure index (FSSI) was employed to comprehensively evaluate the stand spatial structure. Additionally, the uniform angle index was used to discern whether the stand structure units were uniform, random, or clumped. A regression model was used to elucidate the effects of species mingling, diameter dominance, and crowding on the productivity of random trees. Results showed that the FSSI varied among the stand types, ranking as 35LP < 58LN < 39LB < 73LBS. The values of distribution frequency and the percentages of basal area increment (BAI) for random trees were above 0.5% and 40% in most stand types, respectively. The diameter dominance of random structural units in four stand types showed a significant negative correlation with the BAI of random trees, whereas the mingling and crowding of random structural units in the 73LBS displayed a significant positive correlation with BAI of random trees. Thus, increasing the size of random trees, as well as mingling and crowding in random structural units, can facilitate the formation of a rational stand spatial structure, thereby enhancing the productivity of larch forests. [ABSTRACT FROM AUTHOR]

Owing to the increasing challenges associated with coal mine exploration and development, extremely precise surveys with high-resolution images are required to support production. Conventional inversion methods cannot provide sufficiently precise images of the complex lithologies in coal measure strata. Accordingly, this study performed research in Qiyuan mining area, Shanxi Province, China, and predicted the complex lithology on the basis of facies control using waveform indication inversion and waveform indication simulation. Horizontal changes in seismic waveforms were used to reflect lithologic assemblage characteristics for facies-controlled constraints, and the vertical mapping the connection between seismic waveform and logging curves was shown. Moreover, high-resolution inversions of wave impedance and natural gamma parameters were conducted. Combined with lithologic shielding and accurate time–depth conversion, the inversions enabled the precise characterization of the lithological assemblage distribution in the study area. Our results showed that waveform indication inversion could distinguish between coal seams and limestone, whereas waveform indication simulation based on natural gamma could effectively distinguish between sandstone and mudstone. Furthermore, the horizontal resolution was improved and the vertical resolution extended to a thickness of 2–3 m. In addition, the inversion results were highly consistent with drilling results, with an error <0.1 m. Therefore, waveform indication inversion and simulation could be applied to coal mines for safe and efficient production. [ABSTRACT FROM AUTHOR]

Environmental context: Carbonaceous components in PM2.5 have a negative effect on the environment, human health and climate. We explored the pollution characteristic, potential sources and interaction of carbonous aerosols in two adjacent areas in Shanxi, China. The concentration levels of organic carbon and elemental carbon were of a moderate level of all those measured between 2009 and 2020. Vehicle exhaust and coal combustion were the two main sources, and Yuci may be affected by the regional transport of Taiyuan in winter. Rationale: Carbonaceous aerosols seriously affect people's health and have a strong scattering effect on visible light. Pollution cuased by carbonaceous components in Taiyuan is serious. Numerous universities in Taiyuan have been moving to Yuci college town since 2013, and the amount of organic pollutants has increased gradually with the growing population. It is necessary to study the characteristics and relationship of carbonaceous aerosols in these two adjacent areas. Methodology: PM2.5 samples were collected in Taiyuan and Yuci college town in 2017 and 2018, and eight carbonaceous components were analysed using a Sunset Laboratory analyser. Pollution characteristic, potential sources and interaction of carbonous aerosols in the two adjacent areas were investigated. Results: The average organic carbon (OC) and elemental carbon (EC) concentrations were 12.6 and 6.8 µg m−3 in Taiyuan and 11.7 and 6.9 µg m−3 in Yuci. The OC and EC concentrations in Taiyuan can be approximately divided into three levels between 2009 and 2020, and the OC and EC levels in Taiyuan studied here (2017 and 2018) were in the middle level. The OC and EC concentrations were higher when the temperature was lower. Discussion: The OC concentration in December was the highest among three winter periods, which may be caused by secondary organic carbon formation related to the lower temperature and an inversion layer. Four source categories were identified using positive matrix factorisation, namely secondary source (25.0%), dust source (16.6%), vehicle exhaust (27.0%) and coal combustion (31.4%). In Taiyuan and Yuci, the trajectory clusters were mainly from north-west and west in winter, whereas the air masses not only originated from north-west, but also north and south in autumn. Yuci may be affected by Taiyuan's regional transport in winter. The results clarify the characteristics of carbon aerosols in the two adjacent areas, and provide fundamental data for the prevention and control of regional air pollutants. Environmental context. Carbonaceous components in PM2.5 have a negative effect on the environment, human health and climate. We explored the pollution characteristic, potential sources and interaction of carbonous aerosols in two adjacent areas in Shanxi, China. The concentration levels of organic carbon and elemental carbon were of a moderate level of all those measured between 2009 and 2020. Vehicle exhaust and coal combustion were the two main sources, and Yuci may be affected by the regional transport of Taiyuan in winter. [ABSTRACT FROM AUTHOR]

China's Shanxi Province accounts for 12 % of global coal output and therefore is responsible for a very large fraction of the total global methane (CH 4) emissions, as well as being a large source of uncertainty due to the lack of in situ and field measurements. This work introduces the first comprehensive attempt to compute the coal mine methane (CMM) emissions throughout Shanxi, using a mixture of bottom-up and top-down approaches. First, public and private data from 636 individual coal mines in Shanxi Province were analyzed following the IPCC Tier 2 approach, using three to five sets of observed emission factors and rank information based on methods issued by the National Coal Mine Safety Administration and the National Energy Administration, to compile a range of bottom-up CMM on a mine-by-mine basis. An eddy covariance tower is set up near the output flue of a well-characterized high-rank coal mine in Changzhi and used to produce an average observed CH 4 flux over two 2-month-long periods (Winter 2021 and Autumn 2022). The observed half-hourly CH 4 flux variability is found to be roughly stable over the entire observed time and is subsequently used to produce a set of scaling factors (ratio correction) to update the preliminary bottom-up coal mine methane emissions to account for both bias and high-frequency temporal variability. The resulting emissions dataset has been compared against commonly used global CMM datasets including EDGAR and GFEI v2, and there are three unique scientific conclusions. First, their total CH 4 emissions over Shanxi lie between this work's 50th percentile and 70th percentile range, meaning they are slightly high. Second, both datasets have a very large amount of emissions which occur where there are no coal mines and no CH 4 -emitting industry, indicating that there are significant spatial disparities, with the overlapped portion of CMM emissions where mines exist consistently close to the 30th percentile of this work's emissions, meaning they underestimate CMM in general on a mine-by-mine basis. Third, some of the mines have average emissions values which are more than the 90th percentile of the computed mine-by-mine emissions, while many are far below the 10th percentile, showing that there is a significant issue with the sampling not capturing the observed temporal variability. It is hoped that this mine-by-mine and high-frequency approximation of CMM emissions can both improve top-down observation campaigns and provide quantitative support and identification of mitigation opportunities. [ABSTRACT FROM AUTHOR]

The possible influence of global climate changes on agricultural production is becoming increasingly significant, necessitating greater attention to improving agricultural production in response to temperature rises and precipitation variability. As one of the main winter wheat-producing areas in China, the temporal and spatial distribution characteristics of precipitation, accumulated temperature, and actual yield and climatic yield of winter wheat during the growing period in Shanxi Province were analysed in detail. With the utilisation of daily meteorological data collected from 12 meteorological stations in Shanxi Province in 1964–2018, our study analysed the change in winter wheat yield with climate change using GIS combined with wavelet analysis. The results show the following: (1) Accumulated temperature and precipitation are the two most important limiting factors among the main physical factors that impact yield. Based on the analysis of the ArcGIS geographical detector, the correlation between the actual yield of winter wheat and the precipitation during the growth period was the highest, reaching 0.469, and the meteorological yield and accumulated temperature during this period also reached its peak value of 0.376. (2) The regions with more suitable precipitation and accumulated temperature during the growth period of winter wheat in the study area had relatively high actual winter wheat yields. Overall, the average actual yield of the entire region showed a significant increasing trend over time, with an upward trend of 47.827 kg ha−1 yr−1. (3) The variation coefficient of winter wheat climatic yield was relatively stable in 2008–2018. In particular, there were many years of continuous reduction in winter wheat yields prior to 2006. Thereafter, the impact of climate change on winter wheat yields became smaller. This study expands our understanding of the complex interactions between climate variables and crop yield but also provides practical recommendations for enhancing agricultural practices in this region [ABSTRACT FROM AUTHOR]

Simple Summary: Caprine arthritis encephalitis is an infectious disease caused by the caprine arthritis encephalitis virus (CAEV). This virus can impair the quality of goat's milk, lamb, and other goat products. Most goats are latently infected with this virus and become long-term carriers, so the development of a rapid and accurate diagnostic method is necessary. Therefore, we constructed a TaqMan real-time quantitative polymerase chain reaction (RT-qPCR) assay and used it to detect CAEV in sheep in eastern China. We found that the prevalence of CAEV infection in sheep in eastern China was 0.77%. This method yields positive results when testing positive references and negative results when testing negative controls or other viruses. The consistency of these results was confirmed through repeating the experiment multiple times. It demonstrated excellent sensitivity, specificity, and reproducibility and holds great promise for its potential application in clinical and field samples in the future. Caprine arthritis encephalitis is an infectious disease caused by the caprine arthritis encephalitis virus that infects goats, sheep, and other small ruminants. An outbreak of CAEV could be extremely harmful to the goat farming industry and could cause severe economic losses. We designed specific primers and probes for the gag gene and established a TaqMan real-time quantitative polymerase chain reaction assay. This method's correlation coefficient (R2) was >0.999, and the sensitivity of the assay to the plasmid-carried partial gag gene was approximately 10 copies/µL, 1000 times higher than that of conventional PCR. No specific fluorescence was detected for other sheep viruses. Using this method, we tested 776 asymptomatic sheep blood samples and 4 neurodegenerative sheep brain samples from six farms in eastern China, and the positivity rate was 0.77% (6/780). The gag gene was partially sequenced in the three positive samples and compared with the sequences from other representative strains in GenBank. The results revealed that all three strains belonged to the B1 subtype and were most closely related to the strains from Shanxi and Gansu, previously isolated in China, with their homology ranging from 97.7% to 98.9%. These results suggest that the designed RT-qPCR assay can be used to detect subclinical CAEV in sheep and that the virus is still present in eastern China. [ABSTRACT FROM AUTHOR]

Loess landslide is one of the most harmful and serious geological hazards in the Loess Plateau of China. Early identification of potential loess landslide is an urgent need for its prevention. Traditional methods, e.g. support vector machines and decision trees, often suffer complicated data pre-processing, multitudinous causative factors, or low accuracy. This study aims to develop a high-performance loess landslide early identification model based on convolutional neural networks (CNNs). A case study was carried out in northwest Lvliang, China, where loess landslide is a major concern. Two hundred and six loess landslide cases were interpreted by comparing remote sensing images of two time phases, and were randomly divided into a training set (80%; 165) and a validation set (20%; 41). Four algorithms were developed, including a CNN structure with skip connection using data with (S–C) or without (S–N) slope crest and plain CNN structure using data with (P–C) or without (P–N) slope crest. The results show that the S–C structure is the most suitable for early identification of potential loess landslides because it achieved the highest overall accuracy (OA = 0.902) and largest area under the receiver operating characteristic curve (AUC = 0.932) on the validation set. [ABSTRACT FROM AUTHOR]

Introduction: The etiology and clinical presentation of vulvar carcinomas, especially vulvar lesions, are not fully understood. Because the vulva and cervix are anatomically connected, human papillomavirus (HPV) is the main cause of cervical lesions. Thus, this study explored the potential characteristics and effects of specific HPV infection types across vulvar lesions and concurrent cervical lesions. Methods: This retrospective, cross-sectional study analyzed patients with cervical HPV or cytological results and concurrent vulvar biopsy who were seen in our hospital colposcopy clinic in Shanxi Province, China, between 2013 and 2023. Data on age, menopause status, vulvar manifestations, and cytology and HPV infection testing results were collected. Attributable fractions and multinominal logistic models were used to evaluate HPV genotyping and clinical characteristics across vulvar lesions. Results: Among the 1,027 participants, 83 (8.1%) had vulvar intraepithelial neoplasia (VIN) of high grade or worse (VIN2+), and 127 (12.4%) had nonneoplastic epithelial disorders of the vulva (NNEDV). A total of 175 patients had either VIN2+ or cervical intraepithelial neoplasia (CIN) lesions of grade 2 or worse (CIN2+). The most common HPV genotypes for VIN2+ or concurrent VIN2+/CIN2+ were HPV16, HPV52, and HPV58, although attributable fractions differed among lesions. Patients with normal cytological or histopathological result were more likely to have NNEDV detected, while abnormal cervical diagnosis was associated with higher detection of VIN2+. Multinominal logistic modeling showed that age and HPV16 infection were risk factors for VIN2+ or concurrent VIN2+/CIN2+; however, only vulvar presentation with depigmentation was a risk factor for NNEDV. Among patients with low-grade CIN1/VIN1, compared with those who were HPV16 negative, those who were HPV16 positive were at 6.63-fold higher risk of VIN2+/CIN2+ [95% confidence interval (CI): 3.32, 13.21]. Vulvar depigmentation was also associated with increased risk of NNEDV (odds ratio: 9.98; 95% CI: 3.02, 33.04). Conclusions: Chinese women may be at specific, high risk for HPV infection types associated with VIN or CIN. The use of cervical cell HPV detection along with vulvar presentation during cervical cancer screening may also contribute to vulvar lesion detection. [ABSTRACT FROM AUTHOR]