Search

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]

Tea plants are evergreen broad-leaved perennial shrubs, and their spectral characteristics are very similar to those of other evergreen vegetation, making it difficult to distinguish them. Currently, the most commonly used method of tea plantation extraction is machine learning, which classifies tea plantation through various feature combinations and algorithms. The disadvantage of these methods is that they require a large number of local training samples, making it challenging to produce an accurate model applicable to a large region. Furthermore, complex feature combinations and indicators may result in over-fitting, reducing the accuracy of the results. Therefore, it is necessary to develop a new algorithm suitable for tea plantation extraction in extensive regions. This paper uses Shihe District, Henan Province, China as a case in 2019, combined with Landsat-7/8 and Sentinel-2A/B images, and develops a new phenological-based algorithm to extract the tea plantation area. Firstly, we generated an evergreen vegetation map. Secondly, based on high-quality time series curves, the tea plant growth period was divided into seven parts to extract phenological indicators for classification. Finally, the tea plantation in the study area was extracted on a per-pixel basis. The overall accuracy of the algorithm is 87.59%, and the Kappa coefficient is 0.80. This study demonstrates the potential of the phenology-algorithms in extracting tea plantation areas and provides an advanced scheme and scientific basis for extracting tea plantation in other years, and also offers a reference for identifying tea plantation in other regions. Additionally, this paper generated a map of classified phenological indicators to provide guidance for monitoring tea plants growth. [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]

The dislocation between regional innovation and economic development directly influences the economic effect of regional innovation. However, no in-depth researches have been made on how to solve this problem. Using data from Henan Province, China, employing geographical detector technology, this paper focuses on testing whether the industry-university-research cooperation can contribute to coordinating the relation between regional innovation and economic development. It is shown that: 1) the industry-university-research cooperation in Henan Province is increasing gradually, and the network presents a core-edge structure, and the coupling degree between regional innovation and economic development is spatially unbalanced, which is similar to the spatial distribution of the intensity of industry-university-research cooperation; 2) as an important approach to effectively connect scientific researches with market demands, the industry-university-research cooperation can help form an interactive, interconnected, coupled and coordinated virtuous relation between regional innovation and economic development. Compared with the cooperation between organizations of the same type and the separate innovation of organizations, the improvement of the industry-university-research cooperation level can better coordinate the relation between regional innovation and economic development; 3) the cooperative innovation model between enterprises and universities can better promote the coupling between regional innovation and economic development, compared with many industry-university-research cooperation models. For underdeveloped areas lacking local knowledge base, industry-university-research cooperation should be considered as a long-term development strategy, especially using the knowledge sources of external universities and scientific research institutions to enhance innovation capability and achieve economic growth. [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]

The Huayuankou flood event (1938–1947) refers to the prolonged flooding caused by the artificial bursting of the Yellow River embankment at Huayuankou during the Sino-Japanese War (1937–1945). It recreated the historical scenes of frequent floods in the lower Yellow River region of China since the Ming and Qing Dynasties (1368–1911), with the counties along the Jialu River in the eastern plains of Henan especially becoming the disaster-stricken areas. The flood lasted for nearly nine years until the completion of embankment restoration work in 1947, causing long-term and extensive environmental impacts. This paper discusses this catastrophic historical flood event caused by human factors, the warfare strategies and hydraulic technology that acted as drives, and the location factors and historical context leading to the start of flooding in flood-prone areas of Henan. Based on spatial perspectives and the historical GIS approach, the paper compiles and integrates historical documents and maps with archival material and topographic maps from the 1930s and 1940s to present the extent of the flood, the associated disasters, and the persistent effects of official relief strategies and political situation in the wider context, examining how the Huayuankou flood was used as a military tactic, but with unpredictable disastrous consequences. [ABSTRACT FROM AUTHOR]

As the carrier of human economic activities, the change of territorial space affects the level of regional carbon balance. Therefore, with regional carbon balance as the goal, this paper proposed a framework from the perspective of production-living-ecological space and took Henan Province of China as a study area for empirical research. First, the study area established an accounting inventory that considers nature, society, and economic activities to calculate carbon sequestration/emission. Then, the spatiotemporal pattern of carbon balance was analyzed by ArcGIS from 1995 to 2015. Later, the CA-MCE-Markov model was used to simulate the production-living-ecological space pattern in 2035, and carbon balance in three future scenarios was predicted. The study showed that from 1995 to 2015, the living space gradually expanded, and the aggregation rose while the production space decreased. Carbon sequestration (CS) was less than carbon emission (CE) and presented an unbalanced state of negative income in 1995, while CS exceeded CE and showed a positive income imbalance in 2015. In 2035, living space has the highest carbon emission capacity under natural change scenario (NC), while ecological space has the highest carbon sequestration capacity under ecological protection scenario (EP), and production space has the highest carbon sequestration capacity under food security scenario (FS). The results are crucial for understanding the carbon balance changes in territorial space and supporting regional carbon balance goals in the future. [ABSTRACT FROM AUTHOR]

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]

In this paper, an empirical analysis is proposed by employing a regression-based convergence test, which was first introduced by Phillips and Sul. Unlike most related studies, this approach allows examining for evidence of club convergence and enables to endogenously identify groups of counties that converge to different equilibria. The results obtained in this paper support the existence of convergence clubs, indicating that 108 counties of Henan Province in China form four separate groups within which income per capita dispersion is decreasing over time. Moreover, results from an ordered logit model suggest that differences in initial income, physical capital, government intervention, geographical agglomeration, and topography factor among these counties have played vital roles in determining club membership. The most important conclusion of this paper is that the structural characteristics and infrastructure level do not contribute to determining club membership, and neighbors' effect is also not a decisive factor. Particularly, counties which belong to Central Henan Urban Agglomeration are more likely to fall into a club with a higher mean income per capita. The findings in this paper may have significant policy implications for developing regions. [ABSTRACT FROM AUTHOR]

As China's economy progresses towards high-quality development, the construction of science and technology think tanks, with talent construction as the key, has become an important supporting force and occupies a unique position in the national innovation system. In recent years, with the rapid expansion of the number of think tank talents, how to evaluate and manage think tank talents has become a key factor in the development of think tank influence and competitiveness. Based on the experience of talent team construction at home and abroad, Taking the typical science and technology innovation think tanks of Henan Province as an example, this paper analyzes the current situation and status quo of science and technology innovation think tank talents, and finds problems in the talents, Summarize the factors that affect the talent construction and development of science and technology innovation think tanks, From the perspective of six dimensions of competency model, four first-level indicators of talent quantity, talent quality, talent ability and talent contribution of science and technology innovation think tank and 16 subordinate second-level indicators are constructed for talent evaluation of think tank. Ahp is adopted to set questionnaires and collect data with Likert5-level scale, and yaahp software is used to verify the weight verification evaluation effect. Invite experts in the field to score the evaluation indicators. The research results show that the talent evaluation index of science and technology innovation think tank based on competency model pays more attention to the standardization, integration and systematization of the talent evaluation of the think tank, and the system is scientific and reasonable. It can provide reference and reference for promoting the construction, evaluation and development management of scientific and technological innovation think tanks. [ABSTRACT FROM AUTHOR]

The information released by the public on various social media platforms can assist experts in decision-making, thus improving the reliability of the decision-making results and increasing their likelihood of gaining public support. However, the determination of how to fully integrate public opinions with expert opinions and in what aspects to realize the integration is a research topic worthy of attention. Based on this, this paper proposes a multi-subject weighted information fusion method that fully considers public opinion. First, the Bayesian subject model is used to obtain the attribute set of public opinion, and the sentiment analysis technique is used to calculate the reference attribute weights. Second, public opinion is utilized to improve the traditional best–worst method to determine the subjective attribute weights of experts at a faster rate. Third, expert weights are determined using "knowledge" and attribute weights are defined at the aggregate level. Fourth, the cluster weights are determined according to the proximity of the clustered opinions to the public opinions, and the clustered opinions are then summarized to get the overall decision-making information, thus scientifically realizing the synergistic decision-making between the public and experts. Finally, the case of a rainstorm emergency in Henan Province, China, is used to analyze and determine the best plan that matches with the actual situation, and the results are then compared with the findings of existing research to illustrate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

China's photovoltaic poverty alleviation power stations (PPAPS) properly combine poverty alleviation and renewable power generation while also meeting rural energy demands. The fundamental problem is how to optimize the benefits of PPAPS during its limited lifetime. Using the post-operation of photovoltaic poverty alleviation power plants as a starting point, this paper proposes a model combining real option theory and cooperative game to determine the ideal contract period of service committed by the government to the operation and maintenance (O&M) company, thus providing a reference for both parties. The model's validity and applicability are verified by incorporating a PPAPS from Henan Province in China as an example; ultimately, the factors influencing the O&M contract period are ranked using the Sobol global sensitivity analysis. The results show that when the solar industry's environment is positive, the government is more inclined to sign long-term contracts with O&M companies. In contrast, the more the government invests in the facilities, the more likely both parties will sign short-term contracts. Furthermore, the O&M company's capital investment in the power station has a direct impact on the contract period. Finally, corresponding policy recommendations are proposed for future O&M contracts. [ABSTRACT FROM AUTHOR]

Understanding households' attitudes and willingness to pay (WTP) for clean heating can provide a scientific basis for decision-makers to assess the potential to develop clean heating, choose heating methods, and formulate subsidy standards in the region. In this paper, the double-bounded dichotomous contingent valuation method—modified by the spike model—was used to better estimate the actual WTP of households through a sample survey of 456 households in rural areas of Yongcheng City, China, in 2021. The factors influencing attitudes and WTP were examined to reveal mechanisms of accepting clean heating. The results showed that 94.96% of households were willing to pay for clean heating. The annual WTP was 1071 yuan per household, more than eight times the current heating cost. Factors that affect clean heating attitudes do not necessarily affect the WTP. Specifically, gender, length of time spent living at home, and family income had significant influences on WTP, whereas the educational level, adaptive perceptions in relation to environmental perceptions, and the recognition variables for gender equality in energy consumption had a significant impact on attitudes. It is worth noting that elderly people and females were identified as vulnerable groups in the implementation of clean heating. [ABSTRACT FROM AUTHOR]

Developing agricultural mechanization services has been an important approach to pushing smallholder farmers engaging modern agricultural production in China. However, whether smallholder farmers prefer adopting agricultural mechanization services is still under-analysed. In this paper, we use data covering 3,440 wheat farmers collected from Henan province in China to investigate the links between farm size and the adoption of agricultural mechanization services. The results indicate that an inverted U-shaped relationship between farm size and the adoption of agricultural mechanization services exists. We also find that small farms can input more family labour, and large farms tend to invest in self-owned machinery assets. Our analysis implies that the development of agricultural mechanization services is not inevitable to attract farmers with alternative elements, and smallholder farmers may not be the major groups involved in the market of social services in agriculture in the future. [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]

The mechanical parameter inversion model is an essential part of ensuring dam health; it provides a parametric basis for assessing the safe operational behavior of dams using numerical simulation techniques. Due to the complicated nonlinear mapping relationship between the roller compacted concrete (RCC) dam's mechanical parameters and various environmental quantities, as well as conventional statistical models, machine learning methods, and neural networks fail to consider the inputs of fuzzy uncertainty factors. Therefore, the accuracy, efficiency, and stability of inversion models are usually affected by their modeling methods. In this paper, a novel hybrid model for mechanical parameter inversion of an RCC dam is proposed, which uses a radial basis function neural network (RBFNN) to establish the nonlinear mapping relationship between the dam mechanical parameters and the environmental quantities, and the modified particle swarm optimization (PSO) algorithm is used to find the optimal parameters of the model. The modified PSO algorithm makes the inertia weight ω dynamically adjust with the number of iterations to improve the randomness and diversity of the particle population, and population crossover and mutation are introduced to improve the global search ability and convergence speed of the algorithm. The proposed hybrid model is verified and comparatively analyzed by four typical mathematical test functions, and the results show that the proposed model exhibits good performance in parameter inversion accuracy, convergence speed, stability and robustness. Finally, the model is applied to the mechanical parameter inversion analysis of an RCC gravity dam in Henan Province in China. The results show that the proposed model is feasible and reasonable for practical engineering applications, and the relative error between the results obtained by inputting the inverted parameters into the numerical model and monitoring data was within 10%. The methodology derived from this study can provide technical support and a reference for the mechanical parameter inversion analysis of similar dam projects. [ABSTRACT FROM AUTHOR]

In this paper, three new species of the tribe Anthocoptini from China are described and illustrated. They are Aculops grewiaesp. nov. infesting Grewia biloba G.Don. (Malvaceae), Aculops koelreuteriaesp. nov. infesting Koelreuteria paniculata Laxm. (Sapindaceae) and Tegolophus pogonatherisp. nov. infesting Pogonatherum crinitum (Thunb.) Kunth (Poaceae). All of them are vagrants on lower leaf surface and cause no apparent symptom to their host plants. [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]

In compensation events in some parts of China, funds for water and ecological compensation are usually allocated using the factor allocation method, which often fails to satisfy all stakeholders and affects the overall efficiency of ecological compensation Managers need to rethink the effectiveness of the fund allocation method in order to reduce stakeholder complaints and maintain the stability of the ecological protection system. In addition, the dynamic adjustment of the weights in the funding allocation process is an important means of satisfying stakeholders in real time. This paper is based on the entropy weight method (EWM), which has an objective weighting process, introduces fuzzy cognitive map (FCM) theory, integrates objective entropy weights with the state values in FCM, and uses the advantages of the objective assignment of EWM to compensate for the subjective nature of the initial assignment of FCM. At the same time the correlation weights of FCM provide a feedback mechanism for EWM allocation, which makes EWM dynamically adjustable and enhances the practicality of EWM allocation, resulting in an EWM-FCM integration method. The feedback function of the method was used to calculate the case of water ecological compensation funds allocated for the Yellow River (Henan section) in China, and a variety of options for the allocation ratio of water ecological compensation funds were calculated. Stakeholders could choose the appropriate option according to the agreement, which improved the efficiency and satisfaction of the allocation. [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]

The crop water relationship quantification is conducive to decision-making for regional food safety and resource conservation. However, irrigation water and crop water footprint (CWF) was observed separately in previous studies, which leads to incomplete evaluation of water resource occupation in agricultural system. The crop water resource use (WRU), combining WF and irrigation water accounting, in 31 provinces of China from 1999 to 2018 was estimated in current paper. The driving forces of WRU were analyzed using the logarithmic mean divisia index (LMDI) model, based on its spatial and temporal patterns demonstration. The results showed that national WRU increased from 1051.6 Gm3 in 1999 to 1676.4 Gm3 in 2018, with an average annual growth rate of 2.48%. The provinces with high WRU were mainly distributed in North China and Northeast China. Hebei, Shandong, and Henan jointly contributed 28.9% of the national WRU. In addition, economic level was the largest contributor to promote the growth of WRU, and water use intensity was the most important contributor to inhibit the growth of WRU. Economic level, resource endowment, and population size had a promoting effect on WRU in Northeast, Northwest, North China, and Southeast provinces, while water use intensity, irrigation technique, and urbanization degree showed inhibitory effect in Northeast, Northwest, and Southwest provinces. It is meaningful to combine water footprint and irrigation water use for agricultural water management and conservation. The arid North China Plain should adopt water-saving irrigation and rainwater recycling technologies to control WRU, and the Northeast granary should reduce WRU by strengthening water pollution prevention and improving water resources scheduling to ensure food security and sustainable use of water resources. [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]

Since China's reform and opening up in 1978, the acceleration of industrialization and urbanization in China had led to dramatic changes in the pattern of urban-rural land use. In this paper, we focused on the rural industrialized areas in central China (Xinxiang County and Changyuan City of Henan Province). We used the average nearest neighbor index, spatial statistical analysis, and a structural equation model to analyze the spatiotemporal evolution and influencing factors of urban-rural construction land based on multi-source spatial data and survey data. The results showed that: 1) from 1975 to 2019, the spatial distribution of urban-rural construction land in rural industrialized areas had evolved from homogeneous distribution to local agglomeration. In terms of comparative analysis of cases, the spatial distribution of urban-rural construction land in Changyuan City had shown a trend from diffusion to agglomeration, and Xinxiang County had overall shown a spatial change from homogenization to agglomeration and then to regional integration development. 2) The hot spots with increased urban-rural construction land significantly expanded, and they had a high degree of spatial overlap with industrial development. Among them, Xinxiang County was concentrated in central and marginal areas, and Changyuan was mainly concentrated in central urban areas. 3) From the evolution of spatial proximity of urban-rural construction land, rural industrialized areas generally decline, showing the characteristics of internal differentiation in the rate of change. 4) Industrial development, social economy, the policy environment, and urban development played a positive role in promoting the expansion of urban-rural construction land in rural industrialized areas. To promote the optimal use of regional land and the integrated development of urban-rural areas, we should combine the advantages of regional endowment, formulate development strategies according to local conditions, and adjust the way that land is used in a timely manner. [ABSTRACT FROM AUTHOR]

This paper represents the first study on the Xinzhai Culture pottery from Huadizui site, China using X‐ray diffraction (XRD), X‐ray fluorescence spectrometry (XRF), and petrographic. Huadizui pottery is considered to be produced locally, and the raw materials for making pottery come from the Xiaoqinling‐Xiong'er Mountain and Songshan Mountain chain. There are at least two or three clay sources or workshops in the Huadizui site, which is evidenced by petrographic characteristics and the chemical composition of samples. All of the investigated samples were mainly related to quartz and feldspar pellets. The corresponding relationship between the characteristics of the matrix and pottery categories reflects potters pursuing the function of vessels at that time. The range of firing temperature of almost all vessels is between 750 and 950°C. [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]

• The center of gravity of China's EPC is located in Luoyang City, Henan Province. • During the study period, China's EPC in general exhibits an east-high and west-low trend. • During the period 2000–2019, there are significant regional differences in the strength of the spatial linkage of EPC in China. • In 2000–2019, the decoupling status of EPC in china is of two types of decoupling: weak decoupling and expansive coupling. Exploring the evolution of spatial and temporal patterns of electricity power consumption in China is of great significance and value for the promotion of Carbon Peaking and Carbon Neutrality Strategy and the scientific allocation of electricity resources. Therefore, this paper takes China as an example and innovatively applies nighttime light data from a combination of two remote sensing satellites. And using spatial analysis methods to analyze the evolution of spatial and temporal patterns of electricity power consumption over a longer study time series. Meanwhile, this paper also uses the Tapio decoupling model to study the decoupling effect of electricity power consumption and economic growth in China. The results of the study show that, during the period 2000–2019, China's electricity power consumption was in an unbalanced state, with the eastern coastal region dominating. It also formed a gradient distribution from the coastal area to the inland area. In terms of spatial connection, it shows an unbalanced distribution pattern of "low in the west and high in the east". In addition, the spatial linkage of electricity power consumption among provinces is more than 93 % of weak linkage, and gradually increases to 97 %, indicating that the spatial linkage of electricity power consumption among regions is gradually weakening. The decoupling state of electricity power consumption in China is characterized by two types of decoupling: Weak decoupling and Expansive coupling. The decoupling status has experienced a significant change from 84 % of provinces being Expansive coupling to 100 % of provinces being Weak decoupling. [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]

Atmospheric mercury is a crucial pollutant that must be well‐controlled to avoid damaging public health. It is thus necessary to understand from multiple perspectives the roles played by different industrial sectors, as well as their geographical distribution. Existing studies have overlooked the transmission sectors in the economic supply chains of the embodied atmospheric mercury emission network. In this paper, we offer a betweenness‐based account (BBA) for Chinese regions and industrial sectors in transmitting embodied atmospheric mercury emissions and in doing so have identified the transmitting hubs. Our results show that the Henan province acts as the transmission hub of the embodied atmospheric mercury emission network in China. The metallurgy, chemical, and construction industries generally play important roles in the transmission of embodied atmospheric mercury emissions across China. Henan's metallurgy sector, the third highest of all, is more closely linked with inter‐provincial sectors than the top two transmission sectors (the metallurgy industry of Jiangsu and the chemical industry of Shandong). This study can help policy makers improve mercury control measures by focusing on transmission processes for effective and comprehensive atmospheric mercury emission control. [ABSTRACT FROM AUTHOR]