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Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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

This paper explores the intersection of spirituality and martial arts through an in-depth examination of Shaolin Kung Fu as practiced within the Shaolin Monastery in Henan Province, China. Conducting fieldwork from April 2018 to August 2020, the study employs theories of practice and embodiment to understand how religious teachings are interwoven into physical movements and martial practices. This phenomenological analysis of bodily movement integrates the physical body with the sense of self, highlighting the relationship between individual habitus and the agency of the moving body, referred to as the "lived body." It argues that Shaolin martial artists engage in a form of dynamic embodiment, where Chan Buddhist doctrines are embedded within the "lived body," influencing both movement and perception. This process allows practitioners to interpret and interact with their socio-cultural environment through a religious lens, highlighting the deep connection between spiritual beliefs and bodily actions. The paper presents a comprehensive approach, combining intensive participant observation, historical analysis, and a close look at both the communal and individual aspects of monastic life and learning. By examining narratives, daily routines, and pedagogical methods, the study reveals how the socio-cultural setting of the monastery fosters collective habitus and transforms the individual habitus of practitioners. It shows how this transformation contributes to the development of a spiritual dimension in their martial performance. By highlighting the link between the habitus, the lived body, and the dynamic embodiment, the paper extends the current discourse on embodiment, offering a novel perspective on the relationship between spirituality, culture, and physical practice in the context of Shaolin Kung Fu. [ABSTRACT FROM AUTHOR]

Promoting farmers' participation in rural industrial integration and driving farmers' agricultural production with cooperatives and agribusinesses are conducive to realizing cost saving, efficiency, and green production and guaranteeing food security and sustainable agricultural development. Based on the microsurvey data of 1039 grain farmers in Henan Province, China in 2022, this paper examined the impact of contractual choices of farmers' participation in rural industrial integration on agricultural green productivity while analyzing the mechanism of action by using OLS regression, a causal mediation analysis of instrumental variables, propensity score matching, and two-stage least squares (2SLS). The study found that: (1) farmers' participation in a contract, driven by cooperatives or agribusinesses to carry out agricultural production, is conducive to improving their agricultural green productivity, but the effect of each main body to drive farmers varies; (2) farmers' participation in a contract, through cooperatives or agribusinesses to obtain all kinds of agricultural production services—such as agricultural machinery services, agricultural supply services, and technical guidance services—improves the use of agricultural machinery, the standardization of chemical fertilizers, pesticides, and other agricultural materials' use, increases technical guidance, and improves agricultural green productivity. The findings of this paper suggest policy and practical implications for safeguarding food security and promoting sustainable agriculture, as well as enriching research on agricultural productivity. [ABSTRACT FROM AUTHOR]

The development and utilization of biomass energy based on the thermochemical conversion of crop biomass to produce hydrogen are of great significance for promoting China's ecological civilization construction, energy revolution, and low-carbon economic development. Henan province is one of the largest agricultural and pasturage provinces in China. Based on the analysis of the status and trends of Henan's biomass energy (BE) development, this paper summarizes the present status of the construction of ecological civilization (CEC) and the factors restricting its development. Challenges in developing biomass energy are analyzed systematically, and strategies and key technical directions for future biomass energy development are discussed. Finally, the paper presents countermeasures and suggestions for CEC based on the development of BE, which will vigorously promote the development and utilization of BE and the process of CEC. This research provides a reference for the further development of BE and CEC in the future. [ABSTRACT FROM AUTHOR]

Safety, progress, and investment risks are correlated during the construction period of large-scale water transfer projects. However, previous studies have only considered individual risk factors, overlooking the potential systemic risk posed to safety, progress, and investment, as well as any underlying common cause failures. Since traditional risk analysis methods are ill-suited to addressing common cause failure, this paper's objective was to establish a comprehensive evaluation index framework and to identify the basic events of common cause failure. To do that, we developed a risk analysis method that models common cause failure based on a Bayesian network for assessing that systemic risk. The Henan Section of the Yangtze-to-Huaihe River Water Diversion Project in China was then used as a case study. The results show that a variety of common cause failure events, such as epidemic disease, design alteration, lagged approval process, heavy rain in the flood season, renewal material and failing equipment, construction accidents, and external interference, can significantly impact the safety, progress, and investment systemic risk. Design alteration poses the greatest risk, with renewal material and failing equipment exerting the strongest influence among all common cause failure events. It is also possible to elucidate the predominant causal chains; specifically, the contributing influence of each basic failure event to the systemic risk can be clarified by adjusting their respective initial state. The failure of renewal material and failing equipment was found to significantly increase the safety risk. This study effectively simulated the complex causal relationships and uncertainties of pertinent risk factors, thereby enhancing our understanding of the systemic risk associated with safety, progress, and investment in large-scale water transfer projects. [ABSTRACT FROM AUTHOR]

This paper utilizes high-resolution ERA5 hourly data from 1980 to 2020 and long-term normalized difference vegetation index (NDVI) time series obtained from remote sensing and applies trend analysis, correlation analysis, lag analysis, and other methods to study the spatiotemporal characteristics of extreme rainfall at daily and hourly scales in the Huang-Huai-Hai Plain. The paper explores the NDVI's variability and its relationship with extreme hourly precipitation and analyzes the main factors affecting it. The study made the following observations: (1) The extreme daily precipitation in the Huang-Huai-Hai Plain shows a decreasing trend, with a 13.6 mm/yr reduction rate. In contrast, the proportion of extreme rainfall to total precipitation generally exceeds 20%, and the intensity of extreme rain has gradually increased. The spatial distribution pattern of extreme rainfall follows the distribution pattern of China's rain belts, with the terrain being an important influencing factor. The high-incidence areas for extreme rainfall are the Huaihe River region and the Shandong Peninsula. (2) The observed significant increase in hourly extreme precipitation events in the Shandong and Henan provinces of the Huang-Huai-Hai Plain has led to an increased risk of flooding, while the corresponding events in the northwest region of the Plain have exhibited a gradual weakening trend over time. (3) The extreme hourly precipitation in the Huang-Huai-Hai plain shows a frequent and scattered pattern, with decreasing intensity over time. Extreme precipitation mainly occurs in the first half of the night, especially between 19:00 and 21:00, with extreme hourly rainfall intensity fluctuating between 0.2 and 0.25 and the proportion of rainfall to total precipitation reaching as high as 10%. The spatial distribution of extreme hourly rainstorms during the peak period (19:00–21:00) exhibits a high rainfall volume, intensity, and frequency pattern in the eastern region, while the western part exhibits low rainfall volume, intensity, and frequency. (4) The incidence of extremely heavy rainfall in an hour has exhibited a more significant increase compared to extreme daily events in the Huang-Huai-Hai Plain, primarily in the form of backward-type precipitation. Hourly extreme precipitation events in the Huang-Huai-Hai Plain are affected by terrain and land use/cover change (LUCC), with the micro-topography of hilly areas leading to a concentrated distribution of precipitation and LUCC suppressing extreme precipitation events in arid climates. (5) At the ten-day scale, the spatial distribution of the NDVI shows a gradually increasing trend from northwest to southeast, with the highest NDVI value reaching up to 0.6 in the southern part of the study area. For extreme hourly precipitation, there is no significant change observed at the multi-year ten-day scale; while the NDVI in the northern and central parts of the Huang-Huai-Hai Plain shows a significant decreasing trend, in contrast, it presents a significant increasing trend in the southern region. (6) Finally, the correlation between NDVI at the ten-day scale and extreme hourly precipitation exhibits a decreasing pattern from north to south, with a correlation coefficient decreasing from 0.48 to 0.08. The lagged correlation analysis of extreme hourly rainfall and NDVI for one, two, and three ten-day periods shows that the lagged effect of extreme hourly precipitation on NDVI is negligible. Analyzing the correlation between extreme hourly rainfall and NDVI for different months, the impact of extreme hourly precipitation on NDVI is predominantly negative, except for June, which shows a positive correlation (0.35), passing the significance test. This study offers a scientific foundation for enhancing disaster warning accuracy and timeliness and strengthening the research on disaster reduction techniques. [ABSTRACT FROM AUTHOR]

Under the background of global urbanization, the continuous expansion and extensive utilization of urban and rural construction land has caused a large amount of arable land to be occupied, which seriously threatens national food security. This paper describes the spatio-temporal patterns of urban and rural construction land expansion and its occupation of arable land by using the urban and rural construction land expansion intensity, the urban and rural construction land expansion intensity difference index, and geo-detector model. It also explores the mechanisms through which the arable land was occupied. Results showed that construction land in both urban and rural areas expanded over the period 2009–2018 despite a large number of rural and urban migrants, and the major contributor to the rapid urbanization in China. This dual expansion could mainly be attributed to the tendency of these migrants to keep or even enlarge their rural construction land, which also resulted in a severer arable land loss than that caused by the expansion of urban construction land. Second, the rate of arable land occupied by urban and rural construction land in Henan province has been gradually slowing down, whereas the expansion of rural construction land is most dependent on arable land occupation. Third, according to the geo-detector model, the relationship between urbanization level and arable land occupied by urban and rural construction was the strongest, followed by the growth rate of fixed asset investment and the proportion of secondary and tertiary industries in GDP. [ABSTRACT FROM AUTHOR]

Henan Province is the birthplace of Chinese civilization and one of the earliest human settlements, which means that the area has an important national cultural heritage. Traditional villages are an important facet of this cultural heritage, and studying their spatiotemporal characteristics in different periods has important theoretical and practical significance for the sustainable development and protection of cultural heritage in the region. This paper takes the traditional villages of the Yellow River basin in Henan Province that were formed before 1919 as the research object. Information on the ancient river was obtained through a literature search as well as via field research, and the important tributaries of the Yellow River in different periods were mapped using ArcGIS 10.0 software. The nearest neighbor index, kernel density estimation, standard deviation ellipse and other methods were adopted to analyze the spatiotemporal characteristics of the traditional villages. The factors that influenced the evolution of traditional villages were explored in depth by combining changes in the course of the river and water conservancy projects. The results show that the formation of traditional villages along the Yellow River in Henan Province has experienced a historical track of growth, contraction, growth and prosperity and stability. The traditional villages along the Yellow River in Henan Province generally show a clustered pattern, forming a dense concentration of traditional villages in the middle reaches of the Yellow River. The center of gravity shows a migration trend from southeast to northwest. In terms of influencing factors, the spatiotemporal evolution of the relationship between villages and their distance to water is closely related to climatic fluctuations, changes in channel, water conservancy projects and social and cultural factors. This paper deepens our understanding of the relationship between traditional village evolution and watersheds by improving the consistency between village spatial distribution and historical geography and provides a useful theoretical reference for the sustainable development of China's traditional villages. [ABSTRACT FROM AUTHOR]

Under the background of the new normal economy, ecotourism maintains a good momentum of development. Therefore, it can be foreseen that industrial integration is an inevitable trend in the development of contemporary industries, and the integration of cultural industries and tourism industries will bring good effects to regional economic development. In order to fully study the impact of ecotourism and its applied technologies on regional economy and culture, this paper proposes research on the application of virtual reality technology in the coordination and interaction of regional economy and culture in the sustainable development of ecotourism. The approach of this paper is to study VR technology in digital tourism and then to evaluate the sustainability of ecotourism and economic culture. The role of these methods is to study the interaction process between the tourism industry, regional economy, and cultural industry. It explores the law of action between the three so as to achieve the purpose of system optimization. Taking Henan Province, China, as an example, this paper discusses the application of virtual reality technology in ecotourism and studies the impact of ecotourism on economy and culture. The experimental results show that the average value of ecotourism-economic-cultural coordination degree in Henan Province is 0.399, and it is urgent to apply virtual reality technology in ecotourism. [ABSTRACT FROM AUTHOR]

China is going to vigorously develop a new type of agricultural business that is characterized by large-scale planting, and its farmland transfer market is expected to shift from a "buyer's market" to a "seller's market". In the literature, the optimal scale of farmland management is mainly discussed from the perspective of farmland lessees. The development of a healthy farmland transfer market should also consider the needs of farmland lessors. In this paper, we construct a farmland transfer supply function from the perspective of farmers, based on the theory of land market pricing, and apply it to assess the price–volume relationship using surveyed farmland transfer data on wheat farmers in Henan Province, China. The major findings of the present study are as follows: (i) farmers can optimize the allocation of production factors through the farmland transfer market to maximize their profits, and (ii) the quantity of farmland transferred to the market is significantly positively correlated with the price of farmland transferred, demonstrating a power function relation. Currently, the average price of farmland transferred in China's main grain-producing areas exceeds CNY 800 per mu. There is a difference between the actual quantity of farmland transferred and the supply function estimated in this paper, indicating that the market is currently in a crucial period of vigorously promoting farmland transfer. We suggest that government departments follow the laws of farmland transfer, refer to the farmland transfer supply function, and implement policies that support and benefit grain production to provide rapid and consistent guidance to the farmland transfer market. [ABSTRACT FROM AUTHOR]

Eucommia ulmoides Oliver. (E. ulmoides) is a species of small tree native to China. It is a valuable medicinal herb that can be used to treat Alzheimer's disease, diabetes, hypertension, and other diseases. In addition, E. ulmoides is a source of rubber. It has both medicinal and ecological value. As ecological problems become increasingly prominent, accurate information on the cultivated area of E. ulmoides is important for understanding the carbon sequestration capacity and ecological suitability zoning of E. ulmoides. In previous tree mapping studies, no studies on the spectral characteristics of E. ulmoides and its remote sensing mapping have been seen. We use Ruyang County, Henan Province, China, as the study area. Firstly, using the 2021 Gao Fen-6 (GF-6) Wide Field of View (WFV) time series images covering the different growth stages of E. ulmoides based on the participation of red-edge bands, several band combination schemes were constructed. The optimal time window to identify E. ulmoides was selected by calculating the separability of E. ulmoides from other land cover types for different schemes. Secondly, a random forest algorithm based on several band combination schemes was investigated to map the E. ulmoides planting areas in Ruyang County. Thirdly, the annual NPP values of E. ulmoides were estimated using an improved Carnegie Ames Stanford Approach (CASA) to a light energy utilization model, which, in turn, was used to assess the carbon sequestration capacity. Finally, the ecologically suitable distribution zone of E. ulmoides under near current and future (2041–2060) climatic conditions was predicted using the MaxEnt model. The results showed that the participation of the red-edge band of the GF-6 data in the classification could effectively improve the recognition accuracy of E. ulmoides, making its overall accuracy reach 96.62%; the high NPP value of E. ulmoides was mainly concentrated in the south of Ruyang County, with a total annual carbon sequestration of 540.104835 t CM−2·a−1. The ecological suitability zone of E. ulmoides can be divided into four classes: unsuitable area, low suitable area, medium suitable area, and high suitable area. The method proposed in this paper applies to the real-time monitoring of E. ulmoides, highlighting its potential ecological value and providing theoretical reference and data support for the reasonable layout of E. ulmoides. [ABSTRACT FROM AUTHOR]

Straw, which is characterized by its low cost, large quantity, and rich supply of biomass energy, is often converted into energy that can be utilized in industrial production through pyrolysis technology. This paper examines the pyrolysis experiments of four kinds of straw (rice, wheat, peanut, and corn) from the Henan Province of China, conducted in an air environment with varying temperature-rise rates. Based on the experimental results, an analysis was conducted on the effect of the rate of temperature rise on the degree of straw pyrolysis and the pyrolysis characteristics of each type of straw. The activation energies of the pyrolysis reactions were calculated utilizing the Kissinger–Akahira–Sunose (KAS), Flynn–Wall–Ozawa (FWO), and Starink methods. It was concluded that the pyrolysis process of all four types of straw could roughly be classified into three stages: dehydration and drying stage, volatile release stage, and carbonization stage. Among the four types of straw evaluated, rice straw exhibited the most favorable combustion performance, while wheat straw demonstrated the best pyrolysis effect. Increasing the heating rate resulted in a pronounced thermal hysteresis effect during the straw's pyrolysis, as evidenced by the TG and DTG curves shifting toward higher temperatures. The reaction speed increased as the heating rate increased, and the amount of residual carbon displayed an upward trend. [ABSTRACT FROM AUTHOR]

The creep characteristics of sliding zones strongly influence slope deformation and long-term stability, as well as the occurrence of landslide catastrophes. In this paper, large-scale triaxial creep tests were performed on the strongly weathered argillaceous sandstone sliding zone of the Huaipa landslide in the Henan Province, China, to study its creep characteristics and long-term strength in natural and saturated states. Three-dimensional numerical simulations were conducted to analyze the deformation creep law and catastrophic evolution mechanism of the slope after excavation and rainfall. The results show that the sliding zone underwent appreciable creep deformation prior to failure, and that the progression of specimen damage with an increasing stress level followed decay creep → steady creep → accelerated creep. The stress level played a decisive role in the creep deformation, with higher stress levels resulting in higher instantaneous displacement, creep displacement, and longer times required to reach steady creep. The stress level also determined the specimen's creep stage. When the stress level was low, the adjustment of the specimen's internal structure was dominated by air space compression and particle movement, whereas particle fragmentation mostly occurred at high stress levels. The long-term rock strength was approximately 62–66% of the instantaneous strength, the internal friction angle decreased by approximately 8° relative to the instantaneous strength, and the cohesion decreased by approximately 30%. The slope foot unloaded and deformed owing to the excavation of a bauxite mine at its front edge, after which the slope deformed via creep. The landslide disaster occurred when the deformation was significantly accelerated and the slope started to slide as a whole once the sliding zone became water saturated owing to continuous rainfall. The simulation results indicate that the landslide can be divided into a front edge bulging zone, central sliding zone, and trailing edge tension zone, which provides valuable insight on the creep deformation evolution process and the disaster mechanism of the landslide under the action of front edge excavation and rainfall. [ABSTRACT FROM AUTHOR]

Introduction: The impact of farm machinery outsourcing services (FMOS) on grain production has been extensively studied in the literature. However, whether FMOS would adjust cropping structures and ensure food security is little known. To address this research gap, we analyzed the impact of FMOS on the cropping structure adjustment and grain production of farmers. Methods: We estimate the impact of FMOS on grain production by using data collected from a survey of 3,863 wheat farmers in China. We employ the Extended Regression Model (ERM) to address selectivity bias. Results and discussion: The empirical results show that FMOS can adjust the cropping structure and increase the proportion of household food cultivation. Among all segments of FMOS, fertilizer application services drive the increase in grain acreage more significantly. We also find that large-scale households prefer to self-purchase farm machinery rather than FMOS, leading to an insignificant impact of FMOS on cropping structure. Therefore, in the process of promoting the development of FMOS, we should focus on the coordinated development of various types of FMOS, strengthen the popularization and application of fertilization services, and formulate a differentiated subsidy policy for heterogeneous farmers in terms of scale to better play the role of agricultural machinery in promoting grain production. [ABSTRACT FROM AUTHOR]

Estimating carbon emissions and assessing their contribution are critical steps toward China's objective of reaching a "carbon peak" in 2030 and "carbon neutrality" in 2060. This paper selects relevant statistical data on carbon emissions from 2000 to 2018, combines the emission coefficient method and the Logarithmic Mean Divisia Index model (LMDI) to calculate carbon emissions, and analyses the driving force of carbon emission growth using Henan Province as a case study. Based on the partial least squares regression analysis model (PLS), the contributions of inter-provincial factors of carbon emission are analyzed. Finally, a county-level downscaling estimation model of carbon emission is further formulated to analyze the temporal and spatial distribution of carbon emissions and their evolution. The research results show that: 1) The effect of energy intensity is responsible for 82 percent of the increase in carbon emissions, whereas the effect of industrial structure is responsible for -8 percent of the increase in carbon emissions. 2) The proportion of secondary industry and energy intensity, which are 1.64 and 0.82, respectively, have the most evident explanatory effect on total carbon emissions; 3). Carbon emissions vary widely among counties, with high emissions in the central and northern regions and low emissions in the southern. However, their carbon emissions have constantly decreased over time. 4) The number of high-emission counties, their carbon emissions, and the degree of their discrepancies are gradually reduced. The findings serve as a foundation for relevant agencies to gain a macro-level understanding of the industrial landscape and to investigate the feasibility of carbon emission reduction programs. [ABSTRACT FROM AUTHOR]

Analyzing the working conditions of a dam using safety monitoring indices (SMIs) is a relatively intuitive and effective method for dam safety evaluation. Therefore, a reasonable and accurate method for determining the SMIs of a dam is of vital importance for dam safety assessment. However, the current methods for determining the SMIs of dams, especially roller-compacted concrete (RCC) dams, have many shortcomings, such as ignoring the construction process of the dam, the coupling effect among multiple physical fields, etc. In this paper, a novel SMI determination method considering the seepage–stress coupling effects was proposed for RCC dams with the assistance of a constructed seepage and stress coupling model so as to address the deficiency of existing RCC dams in determining SMIs. The coupled mathematical model was developed in COMSOL Multiphysics to establish a finite element analysis model of an RCC gravity dam in Henan Province, China. Moreover, the seepage anisotropy of the RCC construction layers was also considered in the model. Finally, the seepage, stress, and deformation characteristics of the RCC dam were analyzed based on the model, and the seepage and deformation SMIs of the dam were determined and compared with traditional methods. The results show that seepage, stress, and displacement fields are distributed similarly for both coupled and uncoupled models. However, in contrast to the uncoupled model, the hydraulic head contour distribution is more dispersed in the coupled model. Additionally, the stress and displacement simulated by the coupled model increase at different rates, with a more pronounced stress concentration near the dam heel. Comparing the seepage and stress SMIs of RCC dam obtained from different methods, it was found that the indices of dam seepage discharge and crest displacement that are calculated by considering the seepage–stress coupling effect and anisotropic characteristics of RCC construction layers are 34.78% and 31.98% lower than results obtained by ignoring these two effects, respectively. Therefore, it is crucial to consider the seepage–stress coupling effect and the anisotropic characteristics of RCC when determining the SMIs for RCC dams. [ABSTRACT FROM AUTHOR]

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, the survival and development of traditional villages in China have been serious challenges. Rural tourism is regarded as an important way to solve rural problems, and the combination of rural culture and tourism has become a new power point for rural development. Therefore, it is necessary to explore the spatial distribution structure between traditional villages and rural tourism. In this paper, rural tourism was represented by the rural tourism characteristic village (RTCV), and Henan Province, China, was taken as a study area to analyze the distribution pattern and spatial correlation of rural tourism and traditional village (TV) and discuss the relationship between the spatial correlation and regional natural environment and socioeconomic factors. The results show that the coupling of the spatial correlation between RTCVs and TVs in Henan was clear. They could be divided into 5 regions based on geographical factors. In addition, the research summarized 4 typical spatial structures between TVs and RTCVs in Henan based on the regional symbiosis theory, and the spatial pattern formation mechanism of TVs and RTCVs was discussed based on three driving mechanisms. The spatial structure of the two can provide reference value for other developing countries and regions to achieve sustainable rural development. [ABSTRACT FROM AUTHOR]

Ongoing environmental issues and degradation provoke the implementation of relevant incentives to overcome them without restrictions of economic growth. Considering the Chinese sustainable development policy, each province should provide the effective ecological regulations that consider the dynamic changes of the economic and ecological indicators of the province's development. In this case, the paper aims to analyze the relationship between economic growth and environmental quality. The object of the investigation is the Henan provinces of China from 1994 to 2020. The study applied a vector autoregression model between the one-way and two-way relationship analysis, Granger causality test, cointegration test, and impulse response function. The findings confirm that GDP growth causes exhaust gas production and that SO2 will also influence wastewater. The results of the co-consolidation analysis showed that if the production of industrial solid waste gas and SO2 volume increased by 1% each, GDP per capita would increase by 0.22% and 0.35%, respectively. The findings of the variance decomposition of the GDP per capita in the first phase are all due to their perturbation term. The other influencing factors have no influence. Over time, GDP per capita is less and less affected and significantly enhanced by wastewater, exhaust gas, and SO2. [ABSTRACT FROM AUTHOR]

Annual monitoring of the spatial distribution of cultivated land is important for maintaining the ecological environment, achieving a status quo of land resource management, and guaranteeing agricultural production. With the gradual development of remote sensing technology, it has become a common practice to obtain cultivated land boundary information on a large scale with the help of satellite Earth observation images. Traditional land use classification methods are affected by multiple types of land cover, which leads to a decrease in the accuracy of cultivated land mapping. In contrast, although the current advanced methods (such as deep learning) can obtain more accurate cultivated land mapping results than traditional methods, such methods often require the use of a massive amount of training samples, large computing power, and highly complex model tuning processes, increasing the cost of mapping and requiring the involvement of more professionals. This has hindered the promotion of related methods in mapping institutions. This paper proposes a method based on time series vector features (MTVF), which uses vector thinking to establish the features. The advantage of this method is that the introduction of vector features enlarges the differences between the different land cover types, which overcomes the loss of mapping accuracy caused by the influences of the spectra of different ground objects and ensures the calculation efficiency. Moreover, the MTVF uses a traditional method (random forest) as the classification core, which makes the MTVF less demanding than advanced methods in terms of the number of training samples. Sentinel-2 satellite images were used to carry out cultivated land mapping for 2020 in northern Henan Province, China. The results show that the MTVF has the potential to accurately identify cultivated land. Furthermore, the overall accuracy, producer accuracy, and user accuracy of the overall study area and four sub-study areas were all greater than 90%. In addition, the cultivated land mapping accuracy of the MTVF is significantly better than that of the maximum likelihood, support vector machine, and artificial neural network methods. [ABSTRACT FROM AUTHOR]

Stroke is the first leading cause of mortality in China with annual 2 million deaths. According to the National Health Commission of the People's Republic of China, the annual in-hospital costs for the stroke patients in China reach ¥20.71 billion. Moreover, multivariate stepwise linear regression is a prevalent big data analysis tool employing the statistical significance to determine the explanatory variables. In light of this fact, this paper aims to analyze the pertinent influence factors of diagnosis related groups- (DRGs-) based stroke patients on the in-hospital costs in Jiaozuo city of Henan province, China, to provide the theoretical guidance for medical payment and medical resource allocation in Jiaozuo city of Henan province, China. All medical data records of 3,590 stroke patients were from the First Affiliated Hospital of Henan Polytechnic University between 1 January 2019 and 31 December 2019, which is a Class A tertiary comprehensive hospital in Jiaozuo city. By using the classical statistical and multivariate linear regression analysis of big data related algorithms, this study is conducted to investigate the influence factors of the stroke patients on in-hospital costs, such as age, gender, length of stay (LoS), and outcomes. The essential findings of this paper are shown as follows: (1) age, LoS, and outcomes have significant effects on the in-hospital costs of stroke patients; (2) gender is not a statistically significant influence factor on the in-hospital costs of the stroke patients; (3) DRGs classification of the stroke patients manifests not only a reduced mean LoS but also a peculiar shape of the distribution of LoS. [ABSTRACT FROM AUTHOR]

The accuracy of the drainage radius plays a vital role in the gas drainage effect, and the establishment of the drainage model and numerical calculation of the model has an essential value for the accurate determination of the drainage radius. Based on the elastoplastic constitutive model of mining coal and rock mass, effective stress equation, gas content equation, gas flow continuity, and control equation established by predecessors, the gas-solid coupling model of coal-rock deformation and pressure-relief gas flow in protective layer mining was established in this paper. The numerical simulation prototype was based on the mining engineering practice of a short-distance and underprotective steep seam mining in a mine in western Henan of China. COMSOL Multiphysics coupling software was used to numerically calculate the coupling model, and the influence radius of different mining pressure-relief area and different drainage time was obtained. The results show that under the same geological conditions and mining conditions, the impact range of drilling in the pressure-relief area of the protected layer is larger than that of the nonrelief area. As the working face of the protection layer advances, the pressure-relief area of the protected layer gradually increases, the influence range of the drainage borehole increases, the drainage borehole has undergone a process of initial stress-stress concentration-stress reduction-stress recovery successively, and the strike drainage radius is larger than the inclined. [ABSTRACT FROM AUTHOR]

Industrial water consumption is a major component of the total regional water consumption. Accurate and scientific prediction of industrial water consumption is an essential guide to the rational use of natural resources. In this paper, we proposed a combined model of CEEMD (collective empirical modal decomposition) and ARIMA (autoregressive integrated moving average) for forecasting industrial water consumption to establish an accurate and efficient forecasting model, because of the poor generalization ability of most current industrial water consumption forecasting models. The influencing factors of industrial water consumption are complex, and the data are non-stationary. "Decomposition-prediction-reconstruction" is one of the significant methods for forecasting time series data, and the data decomposition has a suppressive influence on the modal mixing problem in the EMD decomposition procedure. Based on the smoothing ability of CEEMD for non-smooth signals and the better adaptation of the autoregressive moving average prediction model (ARIMA), a combined CEEMD-ARIMA model was established for industrial water consumption forecasting. This study was conducted for industrial water consumption in Henan Province in central China. The results suggest the combined CEEMD-ARIMA model has a favorable forecasting effect, with an average relative percentage error of 1.96%, and mean square error (MSE) of 0.35, a Nash efficiency coefficient (NSE) of 0.95, a prediction pass rate of 100%, and a better prediction accuracy than the ARIMA model and the combined EEMD-ARIMA model. It provides an effective prediction method for the prediction of industrial water consumption and has good application prospects. [ABSTRACT FROM AUTHOR]

The Shangfanggou Mo–Fe deposit is a typical and giant porphyry–skarn deposit located in the East Qinling–Dabie molybdenum (Mo) polymetallic metallogenic belt in the southern margin of the North China Block. In this paper, three-dimensional (3D) multi-parameter geological modeling and microanalysis are used to discuss the mineralization and oxidation transformation process of molybdenite during the supergene stage. Meanwhile, from macro to micro, the temporal–spatial–genetic correlation and exploration constraints are also established by 3D geological modeling of industrial Mo orebodies and Mo oxide orebodies. SEM-EDS and EPMA-aided analyses indicate the oxidation products of molybdenite are dominated by tungsten–powellite at the supergene stage. Thus, a series of oxidation processes from molybdenite to tungsten–powellite are obtained after the precipitation of molybdenite; eventually, a special genetic model of the Shangfanggou high oxidation rate Mo deposit is formed. Oxygen fugacity reduction and an acid environment play an important part in the precipitation of molybdenite: (1) During the oxidation process, molybdenite is first oxidized to a MoO2·SO4 complex ion and then reacts with a carbonate solution to precipitate powethite, in which W and Mo elements can be substituted by complete isomorphism, forming a unique secondary oxide orebody dominated by tungsten–powellite. (2) Under hydrothermal action, Mo4+ can be oxidized to jordisite in the strong acid reduction environment at low temperature and room temperature during the hydrothermal mineralization stage. Ilsemannite is the oxidation product, which can be further oxidized to molybdite. [ABSTRACT FROM AUTHOR]

This study examined the factors that affect the attitude and behavioral intentions toward electronic sports (eSports) among students of higher education institutions based on the technology acceptance model (TAM). The conditional impact of preventive regulatory focus was analyzed in various aspects developed on the regulatory focus theory. These aspects comprised of perceived usefulness, perceived ease of use, and perceived risk on the attitude toward eSports. Accordingly, data were collected from 293 students of higher education institutions in China's Henan Province, presenting a 54.56% response rate. The PLS-SEM analysis was subsequently implemented to confirm the proposed hypotheses. The empirical findings confirmed the significant positive impact of perceived usefulness and perceived ease of use on the attitude toward eSports. However, perceived risk negatively affected the attitude toward eSports. Meanwhile, the findings on the moderating hypotheses found a negligible impact on preventive regulatory focus. This impact was found explicitly on the perceived usefulness-perceived ease of use link with attitude toward eSports. However, the preventive regulatory focus negatively moderated the perceived risk attitude toward eSports. Finally, the implication and limitations were illustrated at the end of the paper. [ABSTRACT FROM AUTHOR]

Drought forecasts could effectively reduce the risk of drought. Data-driven models are suitable forecast tools because of theirminimal information requirements. Themotivation for this study is that because most data-driven models, such as autoregressive integrated moving average (ARIMA) models, can capture linear relationships but cannot capture nonlinear relationships they are insufficient for long-term prediction. The hybrid ARIMA-support vector regression (SVR) model proposed in this paper is based on the advantages of a linear model and a nonlinear model. The multiscale standard precipitation indices (SPI: SPI1, SPI3, SPI6, and SPI12) were forecast and compared using the ARIMA model and the hybrid ARIMA-SVR model. The performance of all models was compared using measures of persistence, such as the coefficient of determination, root-mean-square error, mean absolute error, Nash-Sutcliffe coefficient, and kriging interpolation method in the ArcGIS software. The results show that the prediction accuracies of the multiscale SPI of the combined ARIMA-SVR model and the single ARIMA model were related to the time scale of the index, and they gradually increase with an increase in time scale. The predicted value decreases with increase in lead time. Comparing the measured data with the predicted data from the model shows that the combined ARIMA-SVR model had higher prediction accuracy than the single ARIMA model and that the predicted results 1-2 months ahead show reasonably good agreement with the actual data. [ABSTRACT FROM AUTHOR]

China's natural gas market is focusing on price reform and aims to reconstruct vertically integrated industrial chains in the future. Based on the mixed complementarity problem model of gas markets with nodes in Henan Province, China, as an example, this paper applies numerical modeling to simulate the effects of social welfare and equilibrium prices on nodes in two scenarios: pipeline integration and pipeline separation. The findings reveal the following: (1) Pipeline separation yields greater overall social welfare than pipeline integration, with the welfare shifting from gas producers to consumption markets. (2) Pipeline separation lowers the equilibrium consumption prices by driving competition among gas supply sources. (3) Pipeline separation will increase the contribution of natural gas to primary energy. [ABSTRACT FROM AUTHOR]

Extraordinary floods are linked with heavy rainstorm systems. Among various systems, their synoptic features can be quite different. The understanding of extreme rainstorms by their causative processes may assist in flood frequency analysis and support the evaluation of any changes in flood occurrence and magnitudes. This paper aims to identify the most dominant meteorological factors for extreme rainstorms, using the ERA5 hourly reanalysis dataset in Henan, central China as a case study. Past 72 h extreme precipitation events are investigated, and six potential factors are considered in this study, including precipitable water (PW), the average temperature (Tavg) of and the temperature difference (Tdiff) between the value at 850 hPa and 500 hPa, relative humidity (RH), convective available potential energy (CAPE), and vertical wind velocity (Wind). The drivers of each event and the dominant factor at a given location are identified using the proposed metrics based on the cumulative distribution function (CDF). In Henan, central China, Wind and PW are dominant factors in summer, while CAPE and Wind are highly related factors in winter. For Zhengzhou city particularly, Wind is the key driver for summer extreme rainstorms, while CAPE plays a key role in winter extreme precipitation events. It indicates that the strong transport of water vapor in summer and atmospheric instability in winter should receive more attention from the managers and planners of water resources. On the contrary, temperature-related factors have the least contribution to the occurrence of extreme events in the study area. The analysis of dominant factors can provide insights for further flood estimations and forecasts. [ABSTRACT FROM AUTHOR]

This paper explored the transmission mechanism of the public sense of gain (PSG) and YB conservation and development, suggested to take the PSG as a better regulation and guidance for the sound development of the Yellow River Basin. Based on the data of CSS2019, this paper tried to exam the PSG at the opening stage of Chinese major strategy on YB Conservation and Development. An evaluation index system including 5 factor dimensions and 25 indices was constructed, and the normal distribution was used to fitting the survey data, after that, the dominance matrix method was applied to make decision based on PROMETHEE?. The empirical analysis results indicated that the PSG of the middle and upper reaches of the Yellow River was lower than the overall level of China, while that of Henan and Shandong in the lower Yellow River were both higher than its national average; and the public generally had a higher sense of gain on government public service and social civilization, however, the PSG on individual self-fulfillments of Henan and Shandong and that on economic situations of the middle and upper reaches of the Yellow River were both at a lower level. [ABSTRACT FROM AUTHOR]

Skywave refers to the electromagnetic wave reflected or refracted from the ionosphere and propagated in the form of a guided wave between the ionosphere and the Earth's surface. Since the skywave can propagate over large distances, it has been widely used in long-distance communication. This paper explores and demonstrates the feasibility of skywave for deep resource and energy exploration at depths of up to 10 km. Theoretical and technical advancements were accomplished in furthering skywave applications. A new solution method based on Green's function has been developed to study skywave propagation in a fully coupled lithosphere-air-ionosphere full space model. For the first time, the model allows one to study skywave distribution characteristics in the lithosphere containing inhomogeneity such as ore deposits or oil and gas reservoirs. This model also lays a foundation for skywave data processing and interpretation. On a parallel line, we have developed a multi-channel, broadband, low-noise, portable data acquisition system suitable for receiving skywave signals. Using the skywave field excited by a high-power fixed source located in central China, actual field surveys have been carried out in some areas in China including the Biyang depression of Henan Province. The initial results appear encouraging—the interpreted resistivity models prove to be consistent with those of seismic exploration and known geological information, and the exploration cost is only ∼1/4 to 1/10 that of seismic surveys. These initial successful applications of the skywave theory lay a solid foundation for further verification of the new method. [ABSTRACT FROM AUTHOR]

The teacher–learner relationship is not just a simple action and reaction on both sides of the relationship but a complete exchange that takes shape in the context of the factors that affect it. To understand the factors affecting this relationship, the present study investigated the predictability of Chinese English as a Foreign Language (EFL) students' willingness to communicate (WTC) through teachers' immediacy and teacher–student rapport. To conduct the study, 858 EFL students from Xinyang Normal University in Henan province of China were invited to participate in the study. To collect the required data, the researcher employed the Willingness to Communicate Questionnaire, Verbal and Nonverbal Immediacy Questionnaire, and Professor–Student Rapport Scale. Pearson product–moment correlation coefficient and structural equation modeling (SEM) were used to analyze the data. Results revealed that there was a strong positive relationship between teacher immediacy and teacher–student rapport and learners' willingness to communicate. The findings also demonstrated that teachers' immediacy and teacher–student rapport were positive predictors of learners' willingness to communicate. The paper argues that teachers need to enhance their interpersonal relations with their students to make them willing to communicate in their classes. [ABSTRACT FROM AUTHOR]

The red line of Permanent Basic Farmland is the most important part in the "three-line" demarcation of China's national territorial development plan. The scientific and reasonable delineation of the red line is a major strategic measure being taken by China to improve its ability to safeguard the practical interests of farmers and guarantee national food security. The delineation of Permanent Basic Farmland zoning (DPBFZ) is essentially a multi-objective optimization problem. However, the traditional method of demarcation does not take into account the synergistic development goals of conservation of cultivated land utilization, ecological conservation, or urban expansion. Therefore, this research introduces the idea of artificial immune optimization and proposes a multi-objective model of DPBFZ red line delineation based on a clone selection algorithm. This research proposes an objective functional system consisting of these three sub-objectives: optimal quality of cropland, spatially concentrated distribution, and stability of cropland. It also takes into consideration constraints such as the red line of ecological protection, topography, and space for major development projects. The mathematical formal expressions for the objectives and constraints are given in the paper, and a multi-objective optimal decision model with multiple constraints for the DPBFZ problem is constructed based on the clone selection algorithm. An antibody coding scheme was designed according to the spatial pattern of DPBFZ zoning. In addition, the antibody-antigen affinity function, the clone mechanism, and mutation strategy were constructed and improved to solve the DPBFZ problem with a spatial optimization feature. Finally, Tongxu County in Henan province was selected as the study area, and a controlled experiment was set up according to different target preferences. The results show that the model proposed in this paper is operational in the work of delineating DPBFZ. It not only avoids the adverse effects of subjective factors in the delineation process but also provides multiple scenarios DPBFZ layouts for decision makers by adjusting the weighting of the objective function. [ABSTRACT FROM AUTHOR]

This paper summarizes the arguments within the scientific discussion on the investigation of human resource management of willingness and ability of long-term care insurance. The main purpose of the research is to investigate human resource management of willingness and ability of long-term care insurance considering the innovative international experience and the case of Henan province in China. Systematization literary sources and approaches for solving how the person could be motivated to use long-term care insurance indicate that this goal could be reached by issuing questionnaires. The relevance of the decision of this scientific problem is that the demand for long-term care insurance, domestic and foreign scholars mainly use questionnaire survey to conduct quantitative and qualitative research. Investigation of the proposed topic in the paper is carried out in the following logical sequence: the method of expert analysis allowed forming the survey of long-term care insurance. The research's theoretical and methodological basics are general scientific and special methods of certain economic phenomena and processes' cognition. The dialectical method was used to synthesize theoretical and methodological foundations of human resource management of willingness and ability of long-term care insurance foreign countries and China and formulate conclusions. Methodological tools of the research methods were respondents from January 20, 2020, until the end of March 31, 2020. The paper presents the results of the empirical analysis that the proportion of those willing to participate in the long-term care insurance system with an income of «less than 2,000 yuan» is 65.4%; the proportion of those willing to participate in the long-term care insurance system with an income of «2000-4000 yuan» is 69.0%, and the proportion of those willing to participate in the long-term care insurance system with an income of «4000-6000 yuan» is 74.1%. The regression analysis as the statistical method was used to determine whether and to what extent dependent and independent variables are significant. The research empirically confirms and theoretically proves that the factors of the insurance awareness model and the regression of Q24 «are you willing to participate in the long-term care insurance system» are not significant, indicating that the insurance awareness factor is not an influential factor for the old-age care insurance demand. Therefore, the original hypothesis was denied, and the insurance consciousness model factors became not significantly related to the willingness of demand for long-term care insurance. The research results could be useful for those who have a deal with responsible staff, but for this reason, some indicators could influence his behavior. Summing up the results of the held scientific research it could be done the following recommendations. First of all, strengthening publicity and standardize management of long-term care insurance system. Secondly, that should be accelerated the development of the nursing industry with aging, chronic diseases, and other increasingly serious, China's medical resources are very scarce, especially in the nursing industry. Thirdly, it would be progressive if China absorbed the foreign long-term care insurance experience. Fourthly, it should be improved the design of long-term care insurance and increased the types of insurance products. [ABSTRACT FROM AUTHOR]

Encouraging farmers to adopt green prevention and control techniques (GCTs) is conducive to ensuring the quality and safety of agricultural products, the ecological environment and agricultural production in China. To explore the factors influencing vegetable farmers' adoption of GCTs, this study utilized the "information-motivation-behavior" intervention (IMB) model and ordered logistic model to empirically study the adoption behavior of 653 vegetable farmers in Henan Province, China. Estimation results indicated that the IMB model significantly predicted farmers' adoption of GCTs: 1) From the perspective of adoption decisions, 88.82% of the farmers have adopted GCTs, but the degree of adoption is low. 2) the farmers' adoption of GCTs IMB model specifies that higher levels of GCTs information, motivation, and behavioral skills should result in a greater likelihood of engaging in GCTs adoption behavior. 3) Motivation and behavioral skills are activated through information. 4) Finally, motivation can indirectly affect farmers' GCTs adoption behavior through behavioral skills. The results of this study support the need for the government to promote the use of GCTs for vegetable pest control, as well as advance integrated prevention and control in the agricultural industry. [ABSTRACT FROM AUTHOR]

The construction industry of China is characterized by its huge consumption and carbon emissions, thereby making this industry one of the most important areas that require energy conservation efforts. Identifying those factors that affect carbon emissions in the construction industry carries great significance in reducing building carbon emissions, promoting low-carbon cities, and achieving China’s emission reduction goals. This paper firstly reviews the literature on those factors that affect the carbon emissions in the construction industries of developed countries. Second, by using Henan Province as an example, those factors that influence carbon emissions are measured by using the classical STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model. Third, some measures for reducing carbon emissions in the construction industry are developed. Those factors that influence the carbon emissions of buildings are multi-dimensional and diversified. Resident population, urbanization rate, building carbon emission intensity, per capita GDP (Gross Domestic Product), and per capita added value of the tertiary industry all have significant effects on the carbon emissions of buildings in Henan Province. Some policy suggestions can be derived from the findings of this work, such as encouraging building energy conservation, improving the energy efficiency of the construction industry, adjusting the use of building materials, and improving the extant policies for building emission reduction. The results also provide a theoretical basis for identifying those factors that affect the carbon emissions in the construction industry and for formulating and implementing strategies for the low-carbon development of this industry. [ABSTRACT FROM AUTHOR]

Effectively treating industrial SO 2 emissions depends on the synergy of different factors from the industrial SO 2 generation source to the end of treatment. Applying a whole process treatment perspective, this paper decomposes industrial SO 2 emissions into six specific driving factors in three whole process treatment dimensions (i.e. source prevention, process control, and end-of-pipe treatment), and economic scale. A temporal index decomposition analysis (Temporal-IDA), attribution analysis (AA), and spatial index decomposition analysis (Spatial-IDA) methods are then applied to quantify each dimension's treatment effect and its spatial differences. The empirical study across 30 regions in China using data from 2005 to 2015 shows that: (1) The end-of-pipe treatment is the dominant dimension for decreasing industrial SO 2 emissions, followed by process control. The contribution of source prevention to reduce industrial SO 2 emissions has begun to appear, however, there remains room for further improvement; (2) End-of-pipe treatment strength and energy intensity are key factors in reducing industrial SO 2 emissions; Inner Mongolia, Henan, and Shandong are the main contributors; (3) The treatment emphasis are different among regions; as such, there are different treatment effects across the three dimensions of the whole process treatment. Regions can be classified into four categories: the Leading type , Process-dependent type , End-dependent type, and Lagging type. Based on the empirical results, this paper identifies the policy implications of promoting whole process treatment on China's industrial SO 2 emissions. • We study China's industrial SO 2 emissions from a whole process treatment perspective. • Both temporal and spatial index decomposition analysis methods are used. • End-of-pipe treatment and process control majorly reduce industrial SO 2 emissions. • Industrial SO 2 emissions whole process treatment performances vary among regions. [ABSTRACT FROM AUTHOR]

Although the clarification of property rights for agricultural land has the potential to enhance agricultural production efficiency and support its sustainable growth, this goal may not always be met in reality. As a result, the emphasis of this study is on the elements that affect agricultural output. It also examines how the stability of land rights affects agricultural production efficiency and, most importantly, how the heterogeneity of farmers' perspectives affects this process. Through the empirical test using the data of farmers in Henan Province, the largest wheat area in China, the results show that: (1) The farmland confirmation policy significantly promotes the improvement of the pure technical efficiency of agricultural production, a series of robustness tests, and the treatment of endogenous problems, which also confirmed the robustness of the results. (2) In the allocation of factors, agricultural investment and credit acquisition have been proved to be important influencing mechanisms, while labor and land transfer have not played a mechanistic role. (3) Heterogeneity analysis shows that the self-service of farmers choosing to purchase agricultural machinery is more efficient than purchasing outsourcing services; The agricultural production of farmer households without hired workers has a significant technical efficiency, but the impact on farmer households with hired workers is not significant; for farmer households with agricultural insurance purchase behavior, purchase willingness, and planting and breeding advantages, the farmland ownership confirmation policy can play a more important role in promoting the pure technical efficiency of agricultural production; The promotion effect of the farmland right confirmation policy on the pure technical efficiency of agricultural output is strongest when there is a smaller level of farmers operating on a part-time basis and when more farmers prioritize profit maximization as the production goal. Corresponding policy recommendations are made at the conclusion of the study in light of the conclusions mentioned. [ABSTRACT FROM AUTHOR]

[Ag6]4+ clusters are extremely rare in nature (only found in Ag-rich tetrahedrite group minerals). Due to their remarkable structures and some promising applications, a few synthesis phases that contain octahedral [Ag6]4+ clusters have been reported. However, the kinds of natural conditions that promote the formation of subvalent hexasilver clusters in tetrahedrite group minerals are still unclear. Kenorozhdestvenskayaite-(Fe), ideally Ag6(Ag4Fe2)Sb4S12□ is a new tetrahedrite group mineral containing a natural [Ag6]4+ cluster, found in the Yindongpo gold deposit, Weishancheng ore field, Henan Province, China. This new species occurs at the edges of galena crystals as anhedral grains of 2 to 20 μm in size and is associated with pyrargyrite, pyrrhotite, and siderite. Kenorozhdestvenskayaite-(Fe) is black in color with metallic luster. It is brittle with conchoidal fracture and has a calculated density of 5.329 g/cm3. The empirical formula calculated on the basis of cation = 16 apfu is M(2)Ag6M(1)(Ag2.41Cu1.20Fe1.84Zn0.71)Σ6.16X(3)(Sb3.82As0.01)Σ3.83S(1)S11.60S(2)□. It is cubic, with space group I 4 3m, a = 10.7119(6) Å, V = 1229.1(2) Å3, and Z = 2. Since kenorozhdestvenskayaite-(Fe) is a new tetrahedrite group mineral containing a natural [Ag6]4+ cluster, its structure is comparable to the synthetic ternary phosphide (Ag6M4P12) M 6 ′ . The presence of the unusual mineral assemblages, i.e., pyrrhotite and pyrargyrite, as well as the other keno-end-member tetrahedrites, indicates a low-fS2 state for the mineralization stage, probably a result of the fluid boiling process in an open system that likely contributed to the formation of S-deficient tetrahedrites. [ABSTRACT FROM AUTHOR]

Background: Major depressive disorder (MDD) pathogenesis may involve metalloids in a significant way. The aim of our study was to identify potential links between MDD and metalloid elements [boron (B), germanium (Ge), arsenic (As), antimony (Sb)]. Methods: A total of 72 MDD cases and 75 healthy controls (HCs) were recruited from Zhumadian Second People's Hospital in Henan Province, China. The levels of four metallic elements (B, Ge, As, and Sb) in the serum and urine were measured using inductively coupled plasma mass spectrometry (ICP-MS). Results: In comparison to the HCs, the B, As, and Sb levels were considerably lower in the MDD group (p < 0.05) in the serum; the MDD group had significantly higher (p < 0.05) and significantly lower (p < 0.001) B and Sb levels in the urine. After adjusting for potential confounders, serum B (OR = 0.120; 95% CI, 0.048, 0.300; p < 0.001) and Sb (OR = 0.133; 95% CI, 0.055, 0.322; p < 0.001) showed a negative correlation with MDD. Urine B had a negative correlation (OR = 0.393; 95% CI, 0.193, 0.801; p = 0.01) with MDD, while urine Sb had a positive correlation (OR = 3.335; 95% CI, 1.654, 6.726; p = 0.001) with MDD. Conclusion: Our current research offers insightful hints for future investigation into the function of metalloids in connection to MDD processes. [ABSTRACT FROM AUTHOR]

In the context of ecological civilization construction in China, interregional ancient trees are important natural and cultural resources, and it is vital that they are effectively protected and utilized according to their spatial distribution and regional conditions in order to provide a balance between local economic development and the ecological environment. This article analyzes the spatial heterogeneity of 26,842 ancient trees and explores the underlying natural and human factors by using geoinformatics–based techniques (i.e., the nearest neighbor index, kernel density, spatial autocorrelation, and the geographically weighted regression model) in Henan Province, Central China. The research findings conclude that: (1) The interregional ancient trees show positive spatial autocorrelation, and the aggregation effect in Western Henan is the most significant. (2) The growing environment and elevation exert a more obvious influence on the spatial pattern of interregional ancient trees. (3) The main influencing factors per region are different, for example, historical culture in Western Henan, water source and elevation in Southern Henan, and the growing environment in Eastern Henan, while ancient trees in Northern Henan have a weak relationship with each factor. This research facilitates political strategy making for sustainable development and the protection of interregional ancient trees. [ABSTRACT FROM AUTHOR]

The transport and dispersion (T&D) of catalyst particles seeded by weather modification aircraft is crucial for assessing their weather modification effects. This study investigates the capabilities of the Chinese geostationary weather satellite FY-4A for identifying the physical response of cloud seeding with AgI-based catalysts and continuously monitoring its evolution for a weather event that occurred on 15 December 2019 in Henan Province, China. Satellite measurements are also used to verify an operational catalyst T&D algorithm. The results show that FY-4A exhibits a remarkable capability of identifying the cloud-seeding tracks and continuously tracing their evolution for a period of over 3 h. About 60 min after the cloud seeding, the cloud crystallization track became clear in the FY-4A tri-channel composite cloud image and lasted for about 218 min. During this time period, the cloud track moved with the cloud system about 153 km downstream (northeast of the operation area). An operational catalyst T&D model was run to simulate the cloud track, and the outputs were extensively compared with the satellite observations. It was found that the forecast cloud track closely agreed with the satellite observations in terms of the track widths, morphology, and movement. Finally, the FY-4A measurements show that there were significant differences in the microphysical properties across the cloud track. The effective cloud radius inside the cloud track was up to 15 μm larger than that of the surrounding clouds; the cloud optical thickness was about 30 μm smaller; and the cloud-top heights inside the cloud track were up to 1 km lower. These features indicate that the cloud-seeding catalysts led to the development of ice-phase processes within the supercooled cloud, with the formation of large ice particles and some precipitation sedimentation. [ABSTRACT FROM AUTHOR]

Minimum volume of straw should be retained in collecting wheat straw in order to obtain sustainable agricultural biomass energy and measure the energy utilization potential of wheat straw when considering ecological balance. Based on relevant literature, this paper calculates the minimum, medium, and maximum volume of wheat straw retention in various types of soil and designs three different scenarios of minimum, medium, and maximum wheat straw retention. Taking Henan province in China as a case, this paper calculates the potential of wheat straw for energy utilization using linear regression method and scenario analysis, with consideration of influencing factors such as the harvest coefficient and combustion ratio of wheat straw. The results show that the energy utilization potential of wheat straw in Henan province in 2020, 2030, 2050 are 13.77, 16.48, 22.54 million tons of coal equivalent (TCEs), respectively, in the minimum retention scenario, assuming that wheat straw is not directly used for combustion. Excessive straw left in the field causes resource waste and produces CH4 and other greenhouse gases. This paper finds that energy potential of wheat straw for energy utilization is limited when ecological balance is considered, however, it is beneficial to the sustainable development of crop biomass energy. [ABSTRACT FROM AUTHOR]

In the paper, Henan Province with prevalent straw burning was taken as the study case. Aimed at remote sensing recognition of the straw burning fire points in a large-scale area with complex terrain and climate conditions, an optimized recognition strategy of straw burning was proposed based on the MOD021KM data. In our new recognition strategy, the threshold determination method was optimised by systematic statistical analysis of spectral features. Then the non-straw burning fire points were eliminated by extracting the agricultural land from MCD12Q1 image. Thus, the true straw-burning fire points were determined. The results showed that the recognition accuracy of straw burning fire points was effectively improved by optimized threshold determination method. [ABSTRACT FROM AUTHOR]

As a developing country with insufficient water resources, China's water environment management and performance evaluation have important research value. The three provinces (Henan, Hubei, and Hunan) in central China with typical significance in geographical location and water resources governance were selected as research objects in this paper. Based on the principal component analysis (PCA) method and the pressure-state-response (PSR) model, a comprehensive evaluation system for the water environment in those three provinces during 2011–2017 was established in this paper. The evaluation results show that: (1) The water environment management and performance evaluation of the three provinces in central China were generally poor in 2011–2012, but the overall trend was rising; (2) in 2013–2014, the situation was improved compared to the previous two years, but needed further enhancement; (3) in 2015–2017, the water environment management and performance of the three provinces showed significant improvement. Among them, the Hubei Province had the highest water environment evaluation value (1.692), and the Henan Province had the most significant progress (from 0.043 to 1.671). The contributions of this paper are: (1) The comprehensive evaluation model based on PCA and the PSR model was constructed to analyze the sustainable development of water environment in central China; (2) the performance evaluation system for water environment management, which could comprehensively evaluate the performance of water environment treatment and effectively reveal the correlation between various indicators, was established. The principal factors in water environment management can be obtained by this evaluation system. Based on the analysis of the reasons underlying the above changes, the corresponding policy recommendations for improving water environment management and performance in central China were suggested in order to provide a reference for further improvement of water environment management in developing countries. [ABSTRACT FROM AUTHOR]

• The extent of flooding in China is greater than in any other country. • Nearly 66% of China's landmass is submerged by flooding. • Financial toll of flooding accounts for approximately 1.42% of the annual GDP. • Various forms of climatic change contribute to flooding. The extent of flooding in China is more significant than in any other country. Our research reveals that approximately 66 % of China's landmass is submerged by flooding, affecting about 50 % of the population. Furthermore, the financial toll of flooding now accounts for approximately 1.42 % of the annual gross domestic product (GDP), which is almost 40 times higher than the corresponding figure for the United States. We have observed that Zhengzhou city in Henan province, which faced a devastating flood in 2021, received a significant amount of rainfall, specifically a total of 552.5 mm within a 24-hour period. The floods in Henan province in 2021 caused considerable damage, including impacting nearly 15 million people, resulting in almost 400 deaths, damaging over 10,000 square kilometers of agricultural land, causing almost $19 billion in economic losses, and leading to the collapse of over 35,000 households and damage to various properties. In a similar manner, the significant flooding that occurred in southern China in 2020 impacted approximately 7.1 million individuals across eight provinces and resulted in 54 fatalities, the collapse of 6,700 houses, and incurred a direct economic loss of US$3.33 billion. We found that rainstorms have significantly increased to 10 % in the last 60 years in China. In this paper, we delved into exploring the existing published articles, reports, and government and authoritative legal texts to analyze the causes and impacts of flooding in China's flood-prone regions and potential mitigation strategies to reduce the repercussions of distressing flood events. We believe this study will help policymakers by providing new insights while formulating policy to reduce the loss caused by high-level flooding. [ABSTRACT FROM AUTHOR]

Theoretically, agricultural insurance influences farmers' use of pesticides by changing the expected income of agricultural production. Full-cost insurance, with high guarantee and high compensation characteristics, may significantly affect farmers' pesticide use. First, this paper constructs a production function to characterize and compare the marginal incomes of insured and uninsured farmers under risk uncertainty and analyses how insured farmers can increase marginal income by increasing or reducing factor inputs. Considering scale differentiation, it discusses pesticide use strategies different types of farmers may adopt to maximize household utility. Second, using survey data of the pilot counties of full-cost insurance for wheat in Henan Province, China, the simultaneous equation model is used for empirical testing. The results reveal the following: (i) Farmers' insurance participation and pesticide application behaviour are not mutually independent. (ii) For the whole sample, full-cost insurance for wheat has a significant pesticide reduction effect. (iii) However, considering scale differentiation, pesticide application decreases significantly among insured ordinary farmers but does not change significantly among insured large-scale farmers. Third, policy measures are proposed to activate the green development function of agricultural insurance. • Construct a production function and a utility function to conduct mechanism analysis. • Estimate simultaneous equation model based on pilot area household level dataset. • Analyse the effect of full-cost insurance on pesticide input behavior. • Find full-cost insurance significantly reduces the pesticide use of ordinary farmers. • But insignificant effect on the pesticide use of large-scale farmers. [ABSTRACT FROM AUTHOR]

Monitoring of spatio-temporal changes in crop phenology is an important part of the remote sensing of agricultural ecosystems. In this study, the segment turning point method was utilised to determine several phenological dates of winter wheat in northern Henan from 2003 to 2018. The spatio-temporal variation characteristics of these main phenological dates were analyzed, and the effects of temperature and precipitation on phenological changes were investigated. The results showed that: (1) The segment turning point method had strong space-time adaptability, and the RMSE of extracted phenoloical dates of multi-stations in a single year or single station in multi-years was less than 10d. (2) Roughly bounded by 114°E, the trefoil stage, tillering stage, overwintering stage and rising stage of winter wheat in the west were earlier than those in the east of northern Henan in 2018. (3) From 2003 to 2018, the interannual change rates of the trefoil date, tillering date, overwintering date, rising date, booting date, and milky date of winter wheat were 6.92 d/10a, 4.36 d/10a, 0.74 d/10a, -0.1 d/10a, -3.97 d/10a and -2.91 d/10a, indicating the trend of delaying pre-winter phenology and advancing post-winter phenology. (4) The delay of pre-winter phenology and the advance of post-winter phenology of winter wheat were significantly related to the increase in growing season temperature. The results of the study should provide a basis for further understanding of the effects of climate change on winter wheat phenology and to provide a reference for remote sensing monitoring of winter wheat phenology. [ABSTRACT FROM AUTHOR]

In the lining of water conveyance tunnels, the expansion joint is susceptible to leakage issues, significantly impacting the long-term safety of tunnel operations. Polyurea is a type of protective coating commonly used on concrete surfaces, offering multiple advantages such as resistance to seepage, erosion, and wear. Polyurea coatings are applied by spraying them onto the surfaces of concrete linings in water conveyance tunnels to seal the expansion joint. These coatings endure prolonged exposure to environmental elements such as water flow erosion, internal and external water pressure, and temperature variations. However, the mechanism of polyurea coating's long-term leakage prevention failure in tunnel operations remains unclear. This study is a field investigation to assess the anti-seepage performance of polyurea coating in a water conveyance tunnel project located in Henan Province, China. The testing apparatus can replicate the anti-seepage conditions experienced in water conveyance tunnels. An indoor accelerated aging test plan was formulated to investigate the degradation regular pattern of the cohesive strength between polyurea coating and concrete substrates. This study specifically examines the combined impacts of temperature, water flow, and water pressure on the performance of cohesive strength. The cohesive strength serves as the metric for predicting the service lifetime based on laboratory aging test data. This analysis aims to evaluate the polyurea coating's cohesive strength on the tunnel lining surface after five years of operation. [ABSTRACT FROM AUTHOR]