Search

New energy vehicles (NEVs) are the main direction for the development of the global automobile industry. Evaluating and analyzing the competitiveness of new energy vehicle enterprises (NEVEs) is of great significance for promoting their development. In order to explore the current situation of NEVEs in Henan Province, this paper firstly constructs a competitiveness evaluation index system for NEVEs, comprising both quantitative and qualitative indexes. Then, a new definition of consistency, the consistency measure level, and corresponding improvement methods for interval multiplicative preference relations (IMPRs) are proposed. On this basis, fuzzy group decision-making models with IMPRs are constructed to deal with the ambiguity and uncertainty of the decision information, where consistency and consensus are both considered. In our case study, decision results are derived using Lingo 11.0 software. The results of this paper show that the degree of specialization has the greatest impact on the competitiveness of NEVEs, and some NEVEs are deficient in this regard. Related suggestions based on expert evaluation results are also provided. In addition, a comparison with other consistency improvement methods of IMPRs reveals that the methods proposed utilize the original information provided to decision-makers to the utmost degree. [ABSTRACT FROM AUTHOR]

Geological hazards in Xinxian County, Xinyang City, Henan Province, are characterized by their small scale, wide distribution, and significant influence from regional tectonics. This study focuses on collapses and landslide hazards within the area, selecting twelve evaluation factors: aspect, slope shape, normalized difference vegetation index (NDVI), topographic relief, distance from geological structure, slope, distance from roads, land use cover type, area of land change (2012–2022), average annual rainfall (2012–2022), and river network density. Utilizing data from historical disaster sites across the region, the information quantity method and hierarchical analysis method are employed to ascertain the information quantity and weight of each factor. Subsequently, a random forest model is applied to perform susceptibility zoning of geological hazards in Xinxian County and to examine the characteristics of these geological disasters. The results show that in the study area, the primary factors influencing the development of geohazards are the distance from roads, rock groups, and distance from geological structure areas. A comparison of the susceptibility results obtained through two methods, the analytic hierarchy process information quantity method and the random forests model, reveals that the former exhibits a higher accuracy. This model categorizes the geohazard susceptibility in the study area into four levels: low, medium, high, and very high. Notably, the areas of very high and high susceptibility together cover 559.17 km2, constituting 35.99% of the study area's total area, and encompass 57 disaster sites, which represent 72.15% of all disaster sites. Geological hazards in Xinxian County frequently manifest on steep canyon inclines, along the curved and concave banks of mountain rivers, within watershed regions, on gully inclines, atop steep cliffs, and on artificially created slopes, among other sites. Areas with very high and high vulnerability to these hazards are mainly concentrated near the county's geological formations. The gneiss formations are widely exposed in Xinxian County, and the gneisses' strength is significantly changed under weathering, which makes the properties of the different degrees of weathering of the rock and soil bodies play a decisive role in the stability of the slopes. This paper provides a basis for evaluating and preventing geologic hazards in the Dabie mountainous area of the South Henan Province, and the spatial planning of the national territory. [ABSTRACT FROM AUTHOR]

Extreme precipitation usually cause grievous losses&casualties, which varies greatly under different scenarios. This paper took Henan province as an example, it innovatively constructed three different extreme precipitation scenarios and built indicators system of social vulnerability from exposure, sensitivity and resilience based on MOVE framework. Social Vulnerability Indexs(SoVI) were then calculated by mathematical models under three different reoccurrence intervals. The results show that SoVI was low in the west and high in the north. High SoVI areas expanded to the middle and south as recurrence intervals increased. SoVI in each area of Henan province increased along with the recurrence intervals at different growth rates. The larger the recurrence interval was, the faster the SoVI increased. The results indicate SoVI is greatly affected by disaster levels, which need to be incorporated into social vulnerability. This study provides not only a new thought for social vulnerability assessment, but also a reference for the policymakers to formulate related risk management policies. [ABSTRACT FROM AUTHOR]

The South-to-North Water Diversion Project (SNWDP) is believed to drive the next phase of sustainable productivity growth, meeting growing water demand, so as to address increasing environmental sustainability challenges. The Middle Route of SNWDP is regarded as an extremely large long-distance inter-basin water diversion project, which has benefited Henan, Hebei, Tianjin and Beijing since 2014 with great sustainable changes to the cities, groundwater, ecological environment, industrial structure and social development of the beneficiary areas. Taking the number of industrial enterprises above designated size (IEDS) in the water-receiving areas as the research object, this paper takes the year of policy implementation 2014 as the basic time point, evaluating the change of the number of IEDS in the beneficiary areas of the Middle Route of SNWDP through difference-in-difference model. The results show that: (1) The Middle Route of SNWDP promotes the additional growth of the number of IEDS in the beneficiary areas. (2) When the Middle Route of SNWDP promotes the growth of the number of IEDS in beneficiary areas, there is no regional difference for regions with different development levels. (3) The reasons why the Middle Route of SNWDP contributes to the additional growth of the number of IEDS are composed of promoting mixed ownership reform of enterprises in beneficiary areas, increasing water supply and increasing population. However, the Middle Route of SNWDP has not had a significant impact on the traditional total factor productivity or the components of production factors, technology and capital. From the final outcome, the South-to-North Water Diversion Project has played a facilitating role in the sustainable development of large-scale enterprises in the water-receiving areas. [ABSTRACT FROM AUTHOR]

Comprehending the spatiotemporal dynamics and driving factors of small and micro wetlands (SMWs) holds paramount significance in their conservation and sustainable development. This paper investigated the spatiotemporal evolution and driving mechanisms of SMWs in the Yellow River Basin, utilizing buffer zones, overlay analysis, and the Geodetector model based on Landsat satellite images and an open-surface water body dataset from 1990 to 2020. The results revealed that (1) from 1990 to 2020, SMWs in the Yellow River Basin exhibited an overall pattern of fluctuation reduction. The total area decreased by approximately 1.12 × 105 hm2, with the predominant decline occurring in the 0–1 hm2 and 1–3 hm2 size categories. In terms of spatial distribution, SMWs in Qinghai and Gansu decreased significantly, while the SMWs in Inner Mongolia, Henan, and Shandong gradually increased. (2) From 1990 to 2020, SMWs were mostly converted into grassland and cropland, with some transformed into impervious water surface and barren, and only a small percentage converted into other land types in the Yellow River basin. (3) The alterations in SMWs were influenced by factors, with their interplay exhibiting nonlinear or bilinear enhancement. Among these factors, annual precipitation, elevation, and potential evapotranspiration were the primary natural factors influencing the changes in the distribution of SMWs. On the other hand, land use cover type, gross domestic product (GDP), and road distance were the main anthropogenic factors. [ABSTRACT FROM AUTHOR]

Currently, there is a wealth of data and expert knowledge available on monitoring agro-meteorological disasters. However, there is still a lack of technical means to organically integrate and analyze heterogeneous data sources in a collaborative manner. This paper proposes a method for monitoring agro-meteorological disasters based on a spatio-temporal knowledge graph. It employs a semantic ontology framework to achieve the organic fusion of multi-source heterogeneous data, including remote sensing data, meteorological data, farmland data, crop information, etc. And it formalizes expert knowledge and computational models into knowledge inference rules, thereby enabling monitoring, early warning, and disaster analysis of agricultural crops within the observed area. The experimental area for this research is the wheat planting region in three counties in Henan Province. The method is tested using simulation monitoring, early warning, and impact calculation of the past two occurrences of dry hot wind disasters. The experimental results demonstrate that the proposed method can provide more specific and accurate warning information and post-disaster analysis results compared to raw records. The statistical results of NDVI decline also validate the correlation between the severity of wheat damage caused by dry hot winds and the intensity and duration of their occurrences. Regarding remote sensing data, this paper proposes a method that directly incorporates remote sensing data into spatio-temporal knowledge inference calculations. By integrating remote sensing data into the regular monitoring process, the advantages of remote sensing data granted by continuous observation are utilized. This approach represents a beneficial attempt to organically integrate remote sensing and meteorological data for monitoring, early warning, and evaluation analysis of agro-meteorological disasters. [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]

Volunteered geographic information (VGI) plays an increasingly crucial role in flash floods. However, topic classification and spatiotemporal analysis are complicated by the various expressions and lengths of social media textual data. This paper conducted applicability analysis on bidirectional encoder representation from transformers (BERT) and four traditional methods, TextRank, term frequency–inverse document frequency (TF-IDF), maximal marginal relevance (MMR), and linear discriminant analysis (LDA), and the results show that for user type, BERT performs best on the Government Affairs Microblog, whereas LDA-BERT performs best on the We Media Microblog. As for text length, TF-IDF-BERT works better for texts with a length of <70 and length >140 words, and LDA-BERT performs best with a text length of 70–140 words. For the spatiotemporal evolution pattern, the study suggests that in a Henan rainstorm, the textual topics follow the general pattern of "situation-tips-rescue". Moreover, this paper detected the hotspot of "Metro Line 5" related to a Henan rainstorm and discovered that the topical focus of the Henan rainstorm spatially shifts from Zhengzhou, first to Xinxiang, and then to Hebi, showing a remarkable tendency from south to north, which was the same as the report issued by the authorities. We integrated multi-methods to improve the overall topic classification accuracy of Sina microblogs, facilitating the spatiotemporal analysis of flooding. [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]

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]

• The matrix representation of grey possibility function is provided. • The solution method of possibility function's turning points is given. • The "maximum criterion" decision paradox is solved. • A variable stage self-correcting grey clustering model is proposed. • The meteorological drought grade of 17 stations in china henan province is evaluated. The grey clustering model based on the possibility function is frequently used in system evaluation, but the setting of the possibility function is frequently subjective, which results in the weak credibility of the clustering results. In addition, the "maximum criterion" decision paradox of the model has fuzzy boundaries, making the clustering process impossible to program. Based on this, the possibility function is represented as a matrix in the paper, and the possibility function is calculated by an optimization model to guarantee the objectivity of the clustering results. A variable stage self-correcting grey clustering model is built by using the kernel weight transformation as the primary tool, "entropy subtraction" as the signal of the decision paradox, and "entropy non-subtraction" as the model's termination signal. The model's Matlab source code is provided to reduce the complexity of the model. The illustration and comparative analysis demonstrate the model's logic and efficacy. Using the model for the evaluation of the meteorological drought grade in Henan Province can offer a fresh perspective for meteorological departments to make choices and assessments. [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]

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]

In the context of carbon neutrality, the phase-out of coal from the energy structure has resulted in numerous old coal mines that possess abundant underground space resources suitable for underground pumped hydroelectric energy storage (UPHES). Site selection and estimation of potential are critical to the planning and implementation of UPHES in old coal mines. This paper introduces a two-step site selection concept, including a screening assessment followed by a comprehensive assessment, to determine suitable locations for UPHES. The screening indicators in the screening assessment comprise geological features, mine water disasters, and minimum installed capacity, while the analytic hierarchy process (AHP) is applied in the comprehensive assessment. Additionally, coal mines in Henan Province are preliminarily screened through the screening assessment and the potential for UPHES is thoroughly investigated. The estimated volume of the drifts and shafts in old coal mines is approximately 1.35 × 107 m3, while in producing coal mines, it is around 2.96 × 107 m3. Furthermore, the corresponding annual potential for UPHES is 1468.9 GWh and 3226.3 GWh, respectively. By consuming surplus wind and solar power, UPHES is able to reduce 4.68 × 105 tonnes of carbon dioxide (CO2) emissions. The study provides preliminary guidance for policy-makers in developing UPHES in old coal mines. [ABSTRACT FROM AUTHOR]

Regional land-use change is the leading cause of ecosystem carbon stock change; it is essential to investigate the response of LUCC to carbon stock to achieve the strategic goal of "double carbon" in a region. This paper proposes a residual network algorithm, the Residual Multi-module Fusion Network (R-MFNet), to address the problems of blurred feature boundary information, low classification accuracy, and high noise, which are often encountered in traditional classification methods. The network algorithm uses an R-ASPP module to expand the receptive field of the feature map to extract sufficient and multi-scale target features; it uses the attention mechanism to assign weights to the multi-scale information of each channel and space. It can fully preserve the remote sensing image features extracted by the convolutional layer through the residual connection. Using this classification network method, the classification of three Landsat-TM/OLI images of Zhengzhou City (the capital of Henan Province) from 2001 to 2020 was realized (the years that the three images were taken are 2001, 2009, and 2020). Compared with SVM, 2D-CNN, and deep residual networks (ResNet), the overall accuracy of the test dataset is increased by 10.07%, 3.96%, and 1.33%, respectively. The classification achieved using this method is closer to the real land surface, and its accuracy is higher than that of the finished product data obtained using the traditional classification method, providing high-precision land-use classification data for the subsequent carbon storage estimation research. Based on the land-use classification data and the carbon density data corrected by meteorological data (temperature and precipitation data), the InVEST model is used to analyze the land-use change and its impact on carbon storage in the region. The results showed that, from 2001 to 2020, the carbon stock in the study area showed a downward trend, with a total decrease of 1.48 × 10 7 t. Over the course of this 19-year period, the farmland area in Zhengzhou decreased by 1101.72 km 2 , and the built land area increased sharply by 936.16 km 2 . The area of land transfer accounted for 29.26% of the total area of Zhengzhou City from 2001 to 2009, and 31.20% from 2009 to 2020. The conversion of farmland to built land is the primary type of land transfer and the most important reason for decreasing carbon stock. The research results can provide support, in the form of scientific data, for land-use management decisions and carbon storage function protections in Zhengzhou and other cities around the world undergoing rapid urbanization. [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]

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]

Although vegetation index time series from optical images are widely used for crop mapping, it remains difficult to obtain sufficient time-series data because of satellite revisit time and weather in some areas. To address this situation, this paper considered Wen County, Henan Province, Central China as the research area and fused multi-source features such as backscatter coefficient, vegetation index, and time series based on Sentinel-1 and -2 data to identify crops. Through comparative experiments, this paper studied the feasibility of identifying crops with multi-temporal data and fused data. The results showed that the accuracy of multi-temporal Sentinel-2 data increased by 9.2% compared with single-temporal Sentinel-2 data, and the accuracy of multi-temporal fusion data improved by 17.1% and 2.9%, respectively, compared with multi-temporal Sentinel-1 and Sentinel-2 data. Multi-temporal data well-characterizes the phenological stages of crop growth, thereby improving the classification accuracy. The fusion of Sentinel-1 synthetic aperture radar data and Sentinel-2 optical data provide sufficient time-series data for crop identification. This research can provide a reference for crop recognition in precision agriculture. [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]

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]

Crop-type mapping is the foundation of grain security and digital agricultural management. Accuracy, efficiency and large-scale scene consistency are required to perform crop classification from remote sensing images. Many current remote-sensing crop extraction methods based on deep learning cannot account for adaptation effects in large-scale, complex scenes. Therefore, this study proposes a novel adaptive feature-fusion network for crop classification using single-temporal Sentinel-2 images. The selective patch module implemented in the network can adaptively integrate the features of different patch sizes to assess complex scenes better. TabNet was used simultaneously to extract spectral information from the center pixels of the patches. Multitask learning was used to supervise the extraction process to improve the weight of the spectral characteristics while mitigating the negative impact of a small sample size. In the network, superpixel optimization was applied to post-process the classification results to improve the crop edges. By conducting the crop classification of peanut, rice, and corn based on Sentinel-2 images in 2022 in Henan Province, China, the novel method proposed in this paper was more accurate, indicated by an F1 score of 96.53%, than other mainstream methods. This indicates our model's potential for application in crop classification in large scenes. [ABSTRACT FROM AUTHOR]

Social media has become an essential channel for the public to create and obtain information during emergencies. As the theme of public concern for emergencies changes over time, there is a lack of research on its dynamic evolution from its latent stage. This paper selects the Henan rainstorm event as a case study and extracts the theme characteristics by combining the life cycle theory and Latent Dirichlet Allocation (LDA) model. It integrates the Term Frequency–Inverse Document Frequency (TF-IDF) and Pointwise Mutual Information (PMI) algorithms as the theme-coding data source to build a dynamic theme propagation model for emergencies. Our research results showed that the theme coding effectively verified the assumption of latent development trends. The dynamic theme model could reveal the theme characteristics of different time series stages of emergencies, analyze the law of the theme evolution of the network's public opinion, and provide practical and theoretical insights for the emergency management of urban cities. [ABSTRACT FROM AUTHOR]

A clear understanding of the spatial and temporal distribution characteristics of water resources is essential for the optimal allocation and sustainable utilization of water resources. In this paper, the spatial and temporal distribution characteristics of water resources in Henan Province were studied based on GIS, combining the Mann-Kendall (M-K) nonparametric test and rescaled range (R/S) analysis. In addition, SPSS software was used to analyze the influence of climate and land use type on water resources. The results indicated that (1) the hot spots of water resources were concentrated in the southwest, while the low values were concentrated in the northeast, and the distribution of water resources decreased from southwest to northeast. (2) In the past 21 years, spatiotemporal mutations in the water resource sequence occurred between 2010 and 2014. The Z-values of the M-K trend test were all less than 0, the H-values of groundwater resources (GWRs) were mostly greater than 0.5, and the h-values of surface water resources (SWRs) and total water resources (TWRs) were less than 0.5, showing an overall declining trend. However, this trend may change in the future. (3) From the correlation analysis, climate change had a greater impact on water resources than land use changes did. [ABSTRACT FROM AUTHOR]

UAV (unmanned aerial vehicle) remote sensing provides the feasibility of high-throughput phenotype nondestructive acquisition at the field scale. However, accurate remote sensing of crop physicochemical parameters from UAV optical measurements still needs to be further studied. For this purpose, we put forward a crop phenotype inversion framework based on the optimal estimation (OE) theory in this paper, originating from UAV low-altitude hyperspectral/multispectral data. The newly developed unified linearized vector radiative transfer model (UNL-VRTM), combined with the classical PROSAIL model, is used as the forward model, and the forward model was verified by the wheat canopy reflectance data, collected using the FieldSpec Handheld in Qi County, Henan Province. To test the self-consistency of the OE-based framework, we conducted forward simulations for the UAV multispectral sensors (DJI P4 Multispectral) with different observation geometries and aerosol loadings, and a total of 801 sets of validation data were obtained. In addition, parameter sensitivity analysis and information content analysis were performed to determine the contribution of crop parameters to the UAV measurements. Results showed that: (1) the forward model has a strong coupling between vegetation canopy and atmosphere environment, and the modeling process is reasonable. (2) The OE-based inversion framework can make full use of the available radiometric spectral information and had good convergence and self-consistency. (3) The UAV multispectral observations can support the synchronous retrieval of LAI (leaf area index) and Cab (chlorophyll a and b content) based on the proposed algorithm. The proposed inversion framework is expected to be a new way for phenotypic parameter extraction of crops in field environments and had some potential and feasibility for UAV remote sensing. [ABSTRACT FROM AUTHOR]

Flood hazards resulting from short-term severe precipitation have caused serious social and economic losses and have posed extraordinary threats to the safety of lives and property. Vulnerability, which reflects the degree of the adverse impact of flooding on a city, the sensitivity of the environment, and the extent to which rescues are possible during flooding, is one of the significant factors of the disaster risk assessment. Because of this, this paper proposes an Environmental Vulnerability Analysis Model (EVAM), based on comprehensively evaluating multi-source remote sensing data. The EVAM includes a two-stage, short-term flood vulnerability assessment. In the first stage, the flood's areal extension and land-use classification are extracted, based on the U-NET++ network, using multi-source satellite remote sensing images. The results from the first stage are used in the second stage of vulnerability assessment. In the second stage, combining multi-source data with associated feature extraction results establishes the Exposure–Sensitivity–Adaptive capacity framework. The short-term flood vulnerability index is leveraged through the analytic hierarchy process (AHP) and the entropy method is calculated for an environmental vulnerability evaluation. This novel proposed framework for short-term flood vulnerability evaluation is demonstrated for the Henan Province. The experimental results show that the proportion of vulnerable cities in the Henan Province ranging from high to low is 22.22%, 22.22%, 38.89%, and 16.67%, respectively. The relevant conclusions can provide a scientific basis for regional flood control and risk management as well as corresponding data support for post-disaster reconstruction in disaster regions. [ABSTRACT FROM AUTHOR]

BACKGROUND: Perlite is a vitreous rock formed by rapid cooling of volcanic eruptive acidic lava. It is a very important non-metallic mineral, because of its brittleness, light weight, rapid expansion on heating, and other excellent characteristics, and is widely used in construction, water treatment, agriculture and other fields. However, according to the International Database for Certified Reference Materials ( COMAR), there is no reference material for perlite composition analysis at home and abroad. So, in order to meet the research needs of perlite, it is necessary to develop one. OBJECTIVES: To develop a reference material for composition analysis of perlite. The reference material can basically cover the chemical composition needed by the market. METHODS: Perlite samples were collected from Shangcheng County, Henan Province. The collected samples were dried and picked out, the bulk ore was crushed and ground in a ball mill for 40h, then the samples were coarse crushed and discharged, and the debris was removed by 1mm sieve. The samples were dried at 105℃ for 24h, dehydrated and inactivated. After drying, the samples were crushed in a grinder containing high -alumina ceramic balls, and the grinding time was determined by the time required to meet the particle size requirements of the first class standard substance. The processed samples were stored temporarily in polyethylene plastic vats under constant temperature and clean conditions, then sub-packed at 70g per bottle for test. Random samples were taken for homogeneity and stability tests. Through nine collaborative laboratories, more targeted valuation methods such as the gravimetric method, volumetric method, inductively coupled plasma - mass spectrometry, and inductively coupled plasma-optical emission spectrometry were used to ensure the accuracy of the perlite valued components. RESULTS: Fifteen items of 60 components were tested for uniformity and stability, including Ag, As, B, Ba, Be, Bi, Cd, Co, Cr, Cs, Cu, Ga, Hf, Hg, In, Li, Mo, Nb, Ni, Pb, Rb, Sb, Sc, Sn, Sr, Ta, Th, U, V, W, Zn, Zr, SiO2, Al2O3, TFe2O3, FeO, MgO, CaO, Na2O, K2O, MnO, TiO2, P2O5, LOI, TC, and rare earth elements. The RSD of most of the components was less than 3%, and the F value of the variance test was less than the critical value [F0. 05 (29,60) = 1. 65], indicating that the homogeneity of the reference material was good. During the stability inspection period, there was no significant difference in the content of the 60 components, indicating that the reference material was stable. The data were processed in accordance with General and Statistical Principles for Characterization of Reference Materials and outlier tests were performed using the Grubbs and Dixon methods. According to statistics, there were 2500 original data of perlite reference material, and 68 outliers were eliminated, with an elimination rate of 2. 7%. The standard value and uncertainty of the certified reference material for perlite composition analysis were determined by statistical processing of the constant value test data. The normal distribution of the mean data set was tested by the method of Shapiro-wilk, and the test results were all normal distribution. The final values were 63 components, covering major, trace, and all rare earth elements. The contents of three major components MgO, CaO and TFe2O3 were all less than 1%, which formed a gradient with the existing silicate reference material content. CONCLUSIONS: The certified reference material for perlite composition analysis developed in this paper has met the requirements of Technical Norm of Primary Reference Material ( JJF1006—94 ) by processing, crushing, homogeneity and stability test of the candidate. The test for uniformity and stability adopts the same detection technology as the fixed value method, and the selected fixed value technology is suitable and accurate, which ensures the accuracy of the fixed value data. The development of perlite composition analysis standard material has enriched the series of China geological mineral composition analysis standard material, and its chemical composition is numerous, it provides important technical support for instrument calibration, analysis method verification, quality control and quantity traceability of modern analytical technology. [ABSTRACT FROM AUTHOR]

Although there is a consensus on religious revival in China, it must be noted that popular religion and institutional religions such as Buddhism and Daoism adopt different strategies to survive the state's regulations. Many temples that used to facilitate the worship of local deities have to establish some form of intangible cultural heritage or emphasize the deity's history and folklore to de-religionize. During this process, a temple may earn its lawful place to survive, but risks its communality in the village. Based on studies of rural and urban temples in Henan and Shandong provinces, in this paper, I attempt to understand people's religiosity and how they conduct the human–deity exchange under social transformation. Popular religion is characterized by the pursuit of efficacy and its embeddedness in rural life. The traditional binary exchange with deities could be used to maintain a relationship with deities as well as offer urgent solutions, while three-party chains of exchange not only constitute a religious gift economy but also offer a religious agent to seek answers. I argue that temples are marginalized and excluded from village life, so people need to find new means by which to continue their religious practices beyond what the state sponsors, and this has led to the flowing of sacred places. [ABSTRACT FROM AUTHOR]

Near-zero carbon emission power (NZCEP) plants, consisting of gas-fired units; wind turbines; power-to-gas (P2G); and carbon capture, utilization and storage (CCUS) systems, have recently received a lot of attention due to their enormous benefits in reducing carbon emissions and increasing the consumption of renewable energy. However, a complex environment of interest and a combination of risks makes their development very slow. This paper establishes a risk analysis framework for NZCEP considering multi-stakeholder participation. Firstly, a synthetic risk factor system was constructed based on stakeholders' interests. Subsequently, interval type II trapezoidal fuzzy numbers were used and final weights were calculated from both subjective and objective aspects. Finally, we applied an acronym in Portuguese of the interactive and multi-criteria decision-making (TODIM) method to site selection to achieve a balance of interests of all stakeholders. In addition, a case study was conducted. The case result demonstrates that Zhengzhou in Henan Province is the best choice for a NZCEP power plant. A further finding is that government plays an important role in the development of NZCEP plants, with site selection results being the most sensitive to changes in the government's risk appetite. Moreover, human resources are an important factor in the siting of an NZCEP plant. [ABSTRACT FROM AUTHOR]

Clarifying the influencing factors of energy consumption in underground production processes of coal mine is the premise and foundation for the coal mining industry to control the energy consumption and intensity to achieve the goal of carbon peak and carbon neutrality. This paper aims to investigate and compare the differences in energy consumption and carbon emissions between a mining‐separating‐backfilling integrated coal mine (MSBICM) and a traditional coal mine and explore the effects of the main production links underground on carbon emission intensity in coal mines. Hence, taking an MSBICM in Henan province as an example, this study constructed an energy consumption and carbon emission model of the mine using system dynamics (SD) method. Based on this model, the energy consumption of the main production logistics system and auxiliary production system in MSBICM was simulated and analyzed. In addition, this study made a comparative analysis of the energy consumption of the different production links in the two types of coal mines. The results showed that: (1) the comprehensive mechanized coal mining with solid filling system and ventilation system were the subsystems with the highest and lowest energy consumption in MSBICM respectively. (2) The influence rates of raw coal mining, gangue filling, coal‐gangue separating, and material transportation on carbon emission intensity in coal mine were 1.09%, 1.34%, 1.09%, and 5.13%, respectively. (3) Under the same production and filling targets, energy consumption of underground transportation systems in MSBICM was found to be 336.66 tons of standard coal less than that in traditional coal mine. This study has helped clarify the complex relationships among the factors that influence energy consumption in coal mines and provided a reference for implementing dual control of energy consumption to promote low‐carbon mining of coal resources. [ABSTRACT FROM AUTHOR]

Ecological environment assessment, which forms the basis for the survival and development of human society, is a crucial measure for the sustainable development of society and economy. However, current quantitative assessment models such as EI, EQI, RSEI et al. are insufficient to meet the requirements of dynamic research in large areas, long time series and dense time intervals. Therefore, in this paper, we constructed the comprehensive ecological environment quality index model SCEQI that can meet these needs by applying the remote sensing big data as the data source. The SCEQI aggregated the ecological indices NDVI, NDBSI, Lst and Wet by full-sequence dynamic dimensionless, automated principal component analysis and multi-temporal average method. In order to verify the spatial and temporal accuracy of the model, we took Henan Province as an example to compare the result of SCEQI with that of EI, EQI, RSEI and proved that SCEQI performed better in both time and space. Also, we verified the superiority of time, space, and precision of SCEQI with profiles, samples, and cluster analysis. [ABSTRACT FROM AUTHOR]

At present, there is a huge gap between supply and demand of old-age services in rural areas of China. Developing rural mutual old-age services is of great significance to remedy the gap. Based on the survey data of 1200 rural residents in Hubei and Henan provinces, this paper adopts binary logistic regression model to analyze the influence of special trust and general trust on rural residents' willingness to participate in mutual care for the aged. The results show that both special trust and general trust have an impact on rural residents' willingness to participate in mutual support for the elderly, but the effect of special trust on rural residents' willingness to participate in mutual support for the elderly is not significant. General trust has a significant promoting effect on rural residents' willingness to participate in mutual care for the aged. Chinese rural residents' trust in village cadres has a significant promoting effect on their willingness to participate in mutual assistance for the aged. The trust of ordinary friends significantly inhibited their willingness to participate. The educational level, living style, and economic status of Chinese rural residents have a positive impact on their willingness to participate in mutual care for the aged. Age, marital status, health status, and intergenerational relationship are inversely correlated with willingness to participate. [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]

Numerical weather prediction (NWP) has become an important method of predicting extreme weather events, but orography is one of the key factors affecting the performance of NWPs. In this paper, based on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) elevation data, a method for constructing a global orographic dataset suitable for NWP spectral models is investigated. The Yin-He global spectrum model (YHGSM) is used to simulate the early and peak periods of the extreme rainfall event on 20 July 2021 in Henan Province, China, and the heavy rain in Beijing in order to verify the effectiveness and superiority of the proposed orographic construction method. It is demonstrated that in a few cases the direct two-dimensional filter can sometimes simulate more intense rainfall, but in general, the bidirectional one-dimensional filter is better than the direct two-dimensional filter in orographic processing, and the bidirectional one-dimensional filter can filter out more of the small-scale orographic information. The effect of the higher orographic resolution before conversion to spectral space is not very obvious, but it is demonstrated that the simulation results are better for the heavy-rainfall level. In conclusion, in most cases, the simulations conducted using the new global orographic dataset based on ASTER data are better than those obtained using the model's original orography, especially for torrential and extreme rainfall. These conclusions provide a reference for future predictions of and research on extreme rainfall events. [ABSTRACT FROM AUTHOR]

Accurate urban boundary data can directly reflect the expansion of urban space, help us accurately grasp the scale and form of urban space, and play a vital role in urban land development and policy-making. However, the lack of reliable multiscale and high-precision urban boundary data products and relevant training datasets has become one of the major factors hindering their application. The purpose of this study is to combine Sentinel-2 remote-sensing images and supplementary geographic data to generate a reliable high-precision urban boundary dataset for Henan Province (called HNUB2018). First, this study puts forward a clear definition of "urban boundary". Using this concept as its basis, it proposes a set of operable urban boundary delimitation rules and technical processes. Then, based on Sentinel-2 remote-sensing images and supplementary geographic data, the urban boundaries of Henan Province are delimited by a visual interpretation method. Finally, the applicability of the dataset is verified by using a classical semantic segmentation deep learning model. The results show that (1) HNUB2018 has clear and rich detailed features as well as a detailed spatial structure of urban boundaries. The overall accuracy of HNUB2018 is 92.82% and the kappa coefficient reaches 0.8553, which is better than GUB (Henan) in overall accuracy. (2) HNUB2018 is well suited for deep learning, with excellent reliability and scientific validity. The research results of this paper can provide data support for studies of urban sprawl monitoring and territorial spatial planning, and will support the development of reliable datasets for fields such as intelligent mapping of urban boundaries, showing prospects and possibilities for wide application in urban research. [ABSTRACT FROM AUTHOR]

In July 2021, an extreme precipitation event occurred in Henan, China, causing tremendous damage and deaths; so, it is very important to study the observation technology of extreme precipitation. Surface rain gauge precipitation observations have high accuracy but low resolution and coverage. Satellite remote sensing has high spatial resolution and wide coverage, but has large precipitation accuracy and distribution errors. Therefore, how to merge the above two kinds of precipitation observations effectively to obtain heavy precipitation products with more accurate geographic distributions has become an important but difficult scientific problem. In this paper, a new information fusion method for improving the position accuracy of satellite precipitation estimations is used based on the idea of registration and warping in image processing. The key point is constructing a loss function that includes a term for measuring two information field differences and a term for a warping field constraint. By minimizing the loss function, the purpose of position error correction of quantitative precipitation estimation from FY-4A and Integrated Multisatellite Retrievals of GPM are achieved, respectively, using observations from surface rain gauge stations. The errors of different satellite precipitation products relative to ground stations are compared and analyzed before and after position correction, using the '720' extreme precipitation in Henan, China, as an example. The experimental results show that the final run has the best performance and FY-4A has the worse performance. After position corrections, the precipitation products of the three satellites are improved, among which FY-4A has the largest improvement, IMERG final run has the smallest improvement, and IMERG late run has the best performance and the smallest error. Their mean absolute errors are reduced by 23%, 14%, and 16%, respectively, and their correlation coefficients with rain gauge stations are improved by 63%, 9%, and 16%, respectively. The error decomposition model is used to examine the contributions of each error component to the total error. The results show that the new method improves the precipitation products of GPM primarily in terms of hit bias. However, it does not significantly reduce the hit bias of precipitation products of FY-4A while it reduces the total error by reducing the number of false alarms. [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]

• Investigate a novel TrFBWM to yield the TrF criteria weights. • Develop the TrFZSG to rank the alternatives. • Propose a TrF-BWM-ZSG by fusinging the BWM and ZSG. This paper investigates a hybrid emergency decision-making (EDM) method called TrF-BWM-ZSG by combining the BWM (best-worst method) and ZSG (zero-sum game) in trapezoidal fuzzy (TrF) environment. Firstly, this paper defines the entropy and similarity for trapezoidal fuzzy numbers (TrFNs). Based on the entropy and similarity measures, a bi-objective programming model is constructed to distribute the weights for experts. Then, based on the multiplicative consistent trapezoidal fuzzy reference comparisons (TrFRCs), a novel TrFBWM is investigated to yield the TrF criteria weights. This novel TrFBWM highlights two innovations: (i) A crisp goal programming weight-determining model is constructed by using the multiplicative consistent TrFRCs; (ii) A reasonable consistency ratio is defined, in which the consistency index is determined according to the consistent transitivity of TrFRCs. Afterwards, the TrFZSG is developed to achieve the alternatives' ranking order by extending the classical ZSG into TrF environment. Lastly, the availability of the TrF-BWM-ZSG is corroborated through a real EDM case of Henan rainstorm disaster. The advantages of the TrF-BWM-ZSG are manifested by several valuable comparisons. Some desirable results derived by the TrF-BWM-ZSG are received: (i) The optimal alternative selected by the proposed TrF-BWM-ZSG suits the actual rescue situation; (ii) The proposed TrF-BWM-ZSG owns high generality since TrFN can reduce to crisp number, interval and triangular fuzzy number; (iii) The developed novel TrFBWM is helpful to preserve more inherent information of TrFNs. [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]

In order to carry out a quantitative analysis of the teaching effect of college English courses based on multivariate matrix evaluation model, this paper takes as research objects 87-year 2020-enrolled undergraduate students from a university in Zhengzhou City, Henan Province, central China. On the basis of summarizing and analyzing previous research works, this study expounded the research status and significance of quantitative analysis of the teaching effect of college English courses, elaborated the development background, current status, and future challenges of multivariate matrix evaluation model, introduced the data source and the subjects, contents, and means of teaching effect quantification in this research, analyzed the feedback and guiding function of the teaching effect quantification result of college English courses, discussed the motivation and diagnosis function of the teaching effect quantification result of college English courses, conducted analyses of factors affecting the teaching effect quantification of college English courses, constructed the quantitative dimension of teaching effect of college English courses based on the multivariate matrix evaluation model, and finally designed the quantification system of teaching effect of college English courses based on the multivariate matrix evaluation model. The research results show that the quantitative analysis process of the teaching effect of college English courses has the characteristics of complex structure and many hierarchies, and there are also mutual influences and functions between its subsystems. In order to ensure the rationality and effectiveness of comprehensive quantification, the index system construction of the multivariate matrix evaluation model follows scientific, systematic, and focused principles. The teaching effect quantification process combines four influencing factors of perspective, content, mode, and method with the quantification standard, and constructs a hierarchical quantification structure with target layer, restriction factor layer, and restriction sub-factor layer. The tools it uses usually include observations, interviews, self-evaluation, mutual evaluation, student files, reading notes, project presentations, etc. Teachers adjust teaching goals and plans in time by observing the quantification results of students at all levels, which will help improve students' enthusiasm for learning and give full play to students' autonomy and initiative in English courses. [ABSTRACT FROM AUTHOR]

The reciprocating action of the external environment gradually reduces the mechanical properties and water stability of original heritage buildings, resulting in the gradual loss of their cultural value. In this paper, the adobe for the construction of raw soil and cultural relics in western Henan is taken as the research object. The local plain soil is used as the raw material, and the adobe samples are prepared with modified materials such as quicklime and sodium methyl silicate, in order to improve its mechanical properties and water stability. The degree of correlation between the compressive strength, capillary water absorption, pH value, particle size distribution, and the electrical conductivity of modified raw adobe, as well as the modification mechanism of the microstructure, was studied. The results show that the addition of quicklime and sodium methyl silicate can enhance the compressive strength and water resistance of the modified raw adobe, and the optimum dosage is 1.5% sodium methyl silicate; with the increase of the curing age, the compressive strength of the single-mixed quicklime sample, the single mixed sodium methyl silicate samples, and the composite sample were increased by 1.94 times, 12.6 times and 2.61 times, respectively, compared with the plain soil samples, and with the increase of compressive strength, the pH, conductivity and capillary water absorption of the samples decreased continuously. It is evident from the particle gradation test and SEM images that the internal pores of the samples in the modified group become smaller, and the particle structure of the sample doped with sodium methyl silicate is the densest. The results of the study provide support for the restoration of the soil and cultural-relic buildings. [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]

Soil moisture (SM) plays an important role in regulating terrestrial–atmospheric water circulation and energy balance. Most of the existing studies have explored the dynamic patterns of SM based on experimental methods. However, the analysis of large-scale regions and long-term SM sequences was limited. Alternatively, satellite remote sensing data is a potential source for SM analysis for large-scale basins. Therefore, the SM data from the European Space Agency (ESA) Climate Change Initiative (CCI) from 2000 to 2015 is used in this paper to analyze the SM spatial-temporal changes in the Yellow River Basin (YRB). Further, the Normalized Difference Vegetation Index (NDVI) and meteorological data are used to explore the relationships between SM and NDVI, precipitation, air temperature, and wind speed, respectively. The results showed that the overall trend of SM in the YRB was decreasing from southeast to northwest during the past 16 years. The upper reaches of the YRB had shown a humid trend, with a value of 0.00047 m3·m−3·year−1, mainly due to the increase in precipitation; there was an obvious drought trend in the middle reaches of the YRB, especially in Shanxi Province and Henan Province, with a value of −0.00030 m3·m−3·year−1, which may be owed to vegetation greening increasing the soil evaporation. Overall, it is determined that the main factors influencing SM changes were NDVI and precipitation, followed by air temperature and wind speed. This study can provide a scientific basis for the spatial-temporal distribution characteristics and attributions of SM in the YRB over a long time series. [ABSTRACT FROM AUTHOR]

The quality of cultivated land determines the production capacity of cultivated land and the level of regional development, and also directly affects the food security and ecological safety of the country. This paper starts from the perspective of spatial pattern of cultivated land quality and uses spatial autocorrelation analysis to study the spatial aggregation characteristics and differences of cultivated land quality in Henan Province at the county level scale, and also uses bivariate spatial autocorrelation to analyze the influence of neighboring influences on the quality of cultivated land in the target area. The spatial autoregressive model was used to further analyze the driving factors affecting the quality of cultivated land, and the influence of cultivated land area index was coupled in the process of rating analysis, which was finally used as a basis to propose more precise measures for the protection of cultivated land zoning. The results show that: (1) The quality of cultivated land in Henan Province has a strong spatial correlation (global Moran's I≈0.710) and shows an obvious aggregation pattern in spatial distribution; positive correlation types (high-high and low-low) are concentrated in north-central and western mountainous areas of Henan Province, respectively; negative correlation types are discrete. The negative correlation types are distributed in a discrete manner. (2) The bivariate spatial autocorrelation results show that Slope (Moran's I≈-0.505), Irrigation guarantee rate (IGR, 0.354), Urbanization rate (-0.255), Total agricultural machinery power (TAMP, 0.331) and Pesticide use (0.214) are the main influencing factors. (3) According to the absolute values of the regression coefficients, it can be seen that the magnitude of the influence of different factors on the quality of cultivated land is: Slope (0.089) >IGR (0.025) > Urbanization rate (0.002) > TAMP (0.001) > Pesticide use (1.96e-006). (4) Based on the spatial pattern presented by the spatial autocorrelation results, we proposed corresponding protection zoning measures to provide more scientific reference decisions and technical support for the implementation of refined cultivated land management in Henan Province. [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]

• A new rigid-flexible composite recyclable supporting structure is proposed. • Numerical calculation and full-scale test are developed for the new supporting system. • Mutual validation of full-scale test and finite element result is carried out. • The full-scale test shows that the new supporting system is stable. The underground ecological granary has the advantages of low temperature, heat insulation, safety, and mechanization operation of moving grain in and out of the granary. It is the most suitable environmentally friendly warehouse for long-term grain storage at present. Traditional underground granary supporting structures mostly use cement materials and present disadvantages including long periods of construction, difficulties in repairing cracks and leakages, and difficulties in demolition. Based on a steel skeleton supporting structure and flexible waterproof polymers, this paper proposed a new rigid-flexible composite recyclable supporting structure for underground storage granaries. Through the use of ABAQUS software, this paper established a three-dimensional finite element numerical model for excavation of the new supporting structure; analyzed stresses and deformations of the steel pile, middle beam, and steel plate and ground settlement at different excavation steps; and checked the stability of the new supporting structure. Additionally, considering a certain ecological storage granary in Zhongmou County of Henan Province, this paper developed a full-scale test for the new supporting structure. By monitoring the stresses of the supporting structure and ground settlement during excavation, it was concluded that the field monitoring results basically matched the results from numerical simulation. The new supporting structure has the advantages of good stability, quick construction, recyclable usage, low cost, and broad application prospects. [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]

Based on the MEPDG method, the operation process of MEPDG was analyzed and the MEPDG correction method applied to the remaining life prediction of airport pavement was obtained. According to the theory of structural reliability, the performance function of airport pavement was obtained based on the limit state equation represented by flexural stress. Considering the characteristics of airport cement concrete pavement design, the calculation formula of the number of allowable load actions was obtained based on reliability by NCHRP126 fatigue equation without considering the temperature stress when the flexural fatigue strength of pavement plate cement concrete was less than 1.25 times of the design strength. Based on the actual situation of local civil airport runways in Henan Province, the proposed MEPDG correction method was used to analyze the flexural stress of the actual operating airport runway pavement at 95% reliability level based on the mechanical numerical model of airport runway, and the number of allowable load actions of three aircraft models was obtained. Given the impact of pass-to-coverage ratio P/C, the cumulative damage factor CDF of the major aircraft models was calculated; the annual average growth rate of different aircraft models in the airport pavement evaluation stage was obtained based on the trend extension method. According to the predicted average annual cumulative damage, the remaining life of pavement was predicted. Compared with the actual conditions of the airport, the remaining life predicted in this paper was consistent with the actual life, which verifies the effect of the prediction of the remaining life of airport runway considering the impact of reliability and damage accumulation. [ABSTRACT FROM AUTHOR]