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Background: Paper mulberry has been regarded as a potential protein resource for relieving the forage supply crisis, and ensiling has become the most important method for preserving it. An in-depth analysis of the fermentation characteristics of paper mulberry silage could provide a theoretical basis for producing high-quality silage. In this study, we aimed to investigate the dynamic fermentation quality and bacterial community of paper mulberry silages harvested from different regions in China. Results: The results showed an increased trend in ammonia nitrogen (NH3-N) concentration, despite a decrease in pH with prolonged ensiling days. Furthermore, fermentation patterns varied among paper mulberry silages from three regions. Paper mulberry from Zhuozhou, Hebei (HZ) showed the highest dry matter (DM) content and a slight decrease in pH during ensiling. While the lowest DM content was observed in Hechi, Guangxi (GH), which exhibited abnormal fermentation in the silage. In particular, silage from Lankao, Henan (HL) exhibited the best fermentation quality, with lower pH and NH3-N concentration, and higher lactic acid concentration than others (P < 0.05). The bacterial richness and evenness also declined with prolonged ensiling. Among all samples, Enterobacter was the most abundant in all silages, with a trend of increasing and then decreasing during the fermentation process. Pseudocitrobacter dominated in GH silage with abnormal fermentation. Although the bacteria community during ensiling varied widely among silages from different regions, Enterobacter cloacae and Lactobacillus plantarum were the main differential bacteria in silage quality of paper mulberry. Conclusion: Ensiling days and regions had significant effects on the fermentation patterns and bacterial community of paper mulberry silage which might be due to the differences in DM content. Notably, silage quality showed a close relationship with Enterobacter cloacae and Lactobacillus plantarum. Inhibiting the proliferation of Enterobacter and Pseudocitrobacter could be critical for improving the fermentation quality of paper mulberry silage. [ABSTRACT FROM AUTHOR]

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Purpose: This paper aims to promote urban–rural synergy in carbon reduction and achieve the dual carbon goal, reconstruct the low-carbon urban–rural spatial pattern and explore planning strategies for carbon mitigation in urban agglomerations. Design/methodology/approach: The authors propose the idea of land governance zoning based on low-carbon scenario simulation, using the Beijing–Tianjin–Hebei (BTH) urban agglomeration as the empirical research area. Specifically, the authors analyze its spatiotemporal evolution characteristics of carbon balance over the past two decades and simulate the land use pattern under the scenario of low-carbon emission in 2030. Furthermore, the authors create spatial zoning rules combined with land use transition characteristics to classify the urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone and put forward corresponding targeted governance principals. Findings: The study findings classify the BTH urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone, which account for 28.1%, 17.2%, 20.1% and 34.6% of the total area, respectively. The carbon sink restoration zone and carbon sink protection zone are mainly distributed in the northern and western parts and Bohai Rim region. The carbon transition agriculture zone and carbon control development zone are mainly distributed in the southeastern plain and Zhangjiakou. Research limitations/implications: The authors suggest restoring and rebuilding ecosystems mainly in the northwest and east parts to increase the number of carbon sinks and the stability of the ecosystem. Besides, measures should be taken to promote collaborative emission reduction work between cities and optimize industrial and energy structures within cities such as Beijing, Langfang, Tianjin and Baoding. Furthermore, the authors recommend promoting sustainable intensification of agriculture and carefully balance between both economic development and ecological protection in Zhangjiakou and plain area. Originality/value: The authors propose a zoning method based on the optimization of land use towards low-carbon development by combining "top-down" and "bottom-up" strategies and provide targeted governance suggestions for each region. This study provides policy implications to implement the regional low-carbon economic transition under the "double carbon" target in urban agglomerations in China. [ABSTRACT FROM AUTHOR]

Continuous enhancement of sustainable development capacity is one of the goals of building a well-off society. In order to understand the development of each region, it is necessary to make a comprehensive evaluation of their sustainable development capacity. This paper presents a study of the 11 regions of Hebei Province, China. Considering the influence of time on urban development, this paper comprehensively evaluates the sustainable development ability of each region in Hebei Province from three dimensions of society, economy and environment based on panel data. The evaluation results show that Shijiazhuang has the strongest sustainable development capacity. On this basis, the promoting factors and restricting factors of sustainable development in each region are found by using grey correlation analysis method. This study provides a reference for the future sustainable development of each district. [ABSTRACT FROM AUTHOR]

Reports that PanAsia Paper in Singapore has increased its ownership in the Hebei Project of Hebei PanAsia Long-Teng Paper Co. Ltd, that involves building a newsprint mill in Shijiazhuang, China.

Forest biomass estimation is undoubtedly one of the most pressing research subjects at present. Combining multi-source remote sensing information can give full play to the advantages of different remote sensing technologies, providing more comprehensive and rich information for aboveground biomass (AGB) estimation research. Based on Landsat 8, Sentinel-2A, and ALOS2 PALSAR data, this paper takes the artificial coniferous forests in the Saihanba Forest of Hebei Province as the object of study, fully explores and establishes remote sensing factors and information related to forest structure, gives full play to the advantages of spectral signals in detecting the horizontal structure and multi-dimensional synthetic aperture radar (SAR) data in detecting the vertical structure, and combines environmental factors to carry out multivariate synergistic methods of estimating the AGB. This paper uses three variable selection methods (Pearson correlation coefficient, random forest significance, and the least absolute shrinkage and selection operator (LASSO)) to establish the variable sets, combining them with three typical non-parametric models to estimate AGB, namely, random forest (RF), support vector regression (SVR), and artificial neural network (ANN), to analyze the effect of forest structure on biomass estimation, explore the suitable AGB of artificial coniferous forests estimation of machine learning models, and develop the method of quantifying saturation value of the combined variables. The results show that the horizontal structure is more capable of explaining the AGB compared to the vertical structure information, and that combining the multi-structure information can improve the model results and the saturation value to a great extent. In this study, different sets of variables can produce relatively superior results in different models. The variable set selected using LASSO gives the best results in the SVR model, with an R 2 values of 0.9998 and 0.8792 for the training and the test set, respectively, and the highest saturation value obtained is 185.73 t/ha, which is beyond the range of the measured data. The problem of saturation in biomass estimation in boreal medium- and high-density forests was overcome to a certain extent, and the AGB of the Saihanba area was better estimated. [ABSTRACT FROM AUTHOR]

To revitalise established urban areas in the context of stock planning, the river surges in established urban areas play an irreplaceable role. In recent years, the water systems of rivers and surges in established urban areas of many international metropolises have undergone transformation and regeneration. The formerly hardened river banks have begun to be transformed into post-industrial places of integrated residence, leisure, and work, reshaping the ecological landscape and the functions of leisure activities of the rivers and urban spaces. By selecting typical representative cases for analysis and research, this paper determines the research angle and conducts a comparative study of waterfront open space in small and medium-sized cities and large cities from the perspectives of spatial layout, functional structure, ecological restoration, and artistic style, summarises the characteristics and current problems of waterfront open space in small and medium-sized cities at the present stage, and takes the problem as a guide, combining urban design, place theory and other theoretical studies as a guide. Planning and design strategy for waterfront open space in small and medium-sized cities is proposed. This paper selects representative waterfront open spaces and open waterfront spaces for field research. It uses the waterfront open space planning strategy proposed in the paper as a guide to provide a basis for waterfront open space planning and design and, at the same time, selects typical lots for optimal design to verify the implementation ability of the strategy. This paper digs into the rich historical, and geographical information contained in the sample villages in each area summarises the site selection characteristics of traditional villages in Hebei at the mesoscopic level between different areas and analyses the characteristics of the overall layout of villages dominated by natural factors such as mountains, hills and plains, and human factors such as ancient defile post roads, military defences, industries and temples. The spatial skeleton structure of the single-axis type, multi-axis type, organic network type, regular network type, and the fortress-wall enclosed village is extracted. The characteristics of its subtypes are summarised with sample cases. The elemental composition of village centres and boundaries is summarised. [ABSTRACT FROM AUTHOR]

In China, Hebei Province and Guangdong Province have many pollution-intensive industries; yet Hebei suffers more serious atmospheric or environmental pollution than Guangdong. To explain the phenomenon, this paper chooses the statistical data of 286 prefecture-level cities in the Chinese mainland from 2005 to 2018 and empirically tests the spatial effect and threshold characteristics of atmospheric self-purification capacity on environmental pollution by using the spatial autoregression model (SAR), spatial Durbin model (SDM), and panel threshold model. As evinced, the local atmospheric self-purification capacity has a significant inhibitory effect on environmental pollution, and the absolute value of the direct effect coefficient reaches 1.337. Simultaneously, atmospheric self-purification capacity has a threshold effect on environmental pollution. The threshold value of environmental regulation as a threshold variable is 11.6349. This means that when the level of environmental regulation proves higher than 11.6349, it attenuates the inhibitory effect of the atmospheric self-purification capacity on environmental pollution. As the heterogeneity research unveils, atmospheric self-purification capacities in various regions form a significant correlation with environmental pollution. This paper suggests that local governments should strengthen environmental regulation and construct an inter-regional joint prevention and control system for atmospheric-pollution governance to enhance the atmospheric self-purification capacity. [ABSTRACT FROM AUTHOR]

Owing to a long-term, extensive development model and inadequate industrial development planning, cases of atmospheric environment pollution frequently occur in Hebei province. By using such approaches as the Spatial Gini Coefficient, the Herfindahl–Hirschman Index and location entropy, this paper analyzes the spatial-distribution characteristics of atmospheric pollution-intensive industries such as the thermal power industry in Hebei province. As shown, atmospheric pollution-intensive industries, such as the thermal power industry in Hebei province, excessively cluster. As industrial agglomeration continuously intensifies, the spatial imbalance becomes increasingly prominent. Taking the number of days with excellent air quality as a benchmark, this paper divides prefecture-level cities of Hebei province into four types of industrial management and designs targeted strategies for the optimization of atmospheric pollution-intensive industries, such as the thermal power industry. In terms of policies, Type I and Type II cities are advised to strengthen the transfer of atmospheric pollution-intensive industries such as the thermal power industry, and Type III and Type IV cities are advised to improve capacities in atmospheric self-purification and green-technology innovation in a bid to help government departments to scientifically manage atmospheric pollution-intensive industries such as the thermal power industry. [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]

Photovoltaic power generation prediction constitutes a significant research area within the realm of power system artificial intelligence. Accurate prediction of future photovoltaic output is imperative for the optimal dispatchment and secure operation of the power grid. This study introduces a photovoltaic prediction model, termed ICEEMDAN-Bagging-XGBoost, aimed at enhancing the accuracy of photovoltaic power generation predictions. In this paper, the original photovoltaic power data initially undergo decomposition utilizing the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) algorithm, with each intrinsic mode function (IMF) derived from this decomposition subsequently reconstructed into high-frequency, medium-frequency, and low-frequency components. Targeting the high-frequency and medium-frequency components of photovoltaic power, a limiting gradient boosting tree (XGBoost) is employed as the foundational learner in the Bagging parallel ensemble learning method, with the incorporation of a sparrow search algorithm (SSA) to refine the hyperparameters of XGBoost, thereby facilitating more nuanced tracking of the changes in the photovoltaic power's high-frequency and medium-frequency components. Regarding the low-frequency components, XGBoost-Linear is utilized to enable rapid and precise prediction. In contrast with the conventional superposition reconstruction approach, this study employs XGBoost for the reconstruction of the prediction output's high-frequency, intermediate-frequency, and low-frequency components. Ultimately, the efficacy of the proposed methodology is substantiated by the empirical operation data from a photovoltaic power station in Hebei Province, China. Relative to integrated and traditional single models, this paper's model exhibits a markedly enhanced prediction accuracy, thereby offering greater applicational value in scenarios involving short-term photovoltaic power prediction. [ABSTRACT FROM AUTHOR]

As a politically and culturally important city cluster, the Beijing–Tianjin–Hebei (BTH) region is the most prominent area in China where the imbalance between the supply and demand of water resources restricts the sustainable and healthy development of the regional social economy. In the context of global warming, research into water demand prediction that takes climate change into consideration would be more in line with the strategic goal of the low-carbon sustainable development of future cities. At the same time, the prediction of agricultural water demands against a background of climate change is urgently needed, while industrial water consumption is weakly correlated with climate change, an investigation of the statistical relationship between the two is needed. Thus, in this paper, future climate data from the BTH region under the scenarios RCP2.6, RCP4.5 and RCP8.5 were generated using a statistical downscaling model, and then coupled with agricultural and industrial water demand prediction models to simulate and analyze the impact of climate change on the agricultural and industrial water demands, respectively. The results show that during the forecast period (2020–2035), the reference crop evapotranspiration (ET0) growth rates in the Beijing, Tianjin and Hebei areas under the RCP2.6 scenario are 1.438 mm·a−1, 1.393 mm·a−1 and 2.059 mm·a−1, respectively. Under the RCP4.5 scenario, they are 2.252 mm·a−1, 2.310 mm·a−1 and 2.827 mm·a−1, respectively. Under the RCP8.5 scenario, they are 3.123 mm·a−1, 2.310 mm·a−1 and 2.141 mm·a−1, respectively. Furthermore, under each climate scenario, the increase in evapotranspiration in the Hebei area is the largest, followed by that in the Tianjin area, and that in the Beijing area is the smallest. For water consumption per CNY 10,000 of industrial added value during the forecast period, under the three different climate scenarios, a downward trend is seen in the Beijing area, with rates of 0.158, 0.153 and 0.110, respectively, but in the Tianjin area, there is an upward trend, with an upward tendency in rates of 0.170, 0.087 and 0.071, and an upward trend in the Hebei area, with an upward tendency in rates of 0.254, 0.071 and 0.036, respectively. This study will help the BTH region to rationally allocate agricultural and industrial water against the background of future climate change, and strengthen the coordination and cooperation between the different regions to promote the healthy and sustainable development of the cities. [ABSTRACT FROM AUTHOR]

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

New urbanization in counties and the logistics industry are closely related and are essential in promoting regional economic and social development. There are specific challenges and obstacles to revealing the interaction mechanism and system state measurement between the two. This paper explains the two coupling mechanisms and constructs the evaluation index system. It proposes a new analysis method based on the coupling coordination degree model, the spatio-temporal evolution analysis, and the grey prediction model. The goal is to learn more about and fully realize the coordinated development mechanisms of the two. It then uses the Hebei province of China as an example to empirically analyze its systematic cross-sectional data from 2013 to 2022. Research findings: (1) In Hebei province, the new urbanization in counties and the logistics industry have a systematic coupling relationship. However, the logistics industry's comprehensive development level is relatively lagging. The two systems have been at a high-level coupling stage for the last decade and maintain a high coupling status. The coupling coordination has shown significant improvement. (2) Although the geographical distribution of the coupling and coordination degree of the new urbanization in counties and logistics industry system has short-term volatility, it is still stable in the long term and presents economic-related spatial characteristics. (3) Over the next five years, the coupling coordination of 11 cities in Hebei province will steadily grow. There will be greater harmonization between the two systems. (4) From the analysis results, the evaluation index system of the coupled system constructed is scientific and reasonable. The analysis method can not only measure the system's coupling degree, but it can also predict the development trend and analyze the spatial evolution. The technique has novelty and validity, which can be used as a reference for analyzing and making decisions about similar systems. [ABSTRACT FROM AUTHOR]

Sandy soil in the north of Hebei region of China is widely distributed, the temperature difference between day and night is large, the phenomenon of freezing and thawing is obvious, and the soil body before and after the freezing and thawing cycle of sandy soil slopes is affected by the changes. This paper takes the stability of a sandy soil anchorage interface under a freeze-thaw cycle as the research background and, based on the self-developed anchor-soil interface shear device, analyses the influence of changing sand rate, confining pressure, and the number of freeze-thaw cycles on the shear characteristics of an anchor-soil interface in anchorage specimens. The research findings indicate that, at 50–60% sand contents, the shear strength increases with a higher sand content and is positively correlated with confining pressure within a higher range. A higher sand content stabilises the anchoring body, but an excessively high sand content can lead to failure. Increasing the sand content, confining pressure, and freeze-thaw cycle number all result in a reduction in the shear displacement at the peak strength. After 11 freeze-thaw cycles, the shear strength of the anchoring body stabilises, with a reduction in strength of approximately 32%, and a higher sand content effectively reduces the reduction in strength. [ABSTRACT FROM AUTHOR]

Beijing, Tianjin and Hebei are located in the Bohai Rim region of Northeast Asia, China. It is the region with the largest economic scale and strongest economic vitality in northern China. Due to historical development and administrative division, the economic strength of Beijing and Tianjin is strong, while the economic strength of Hebei Province is weak. The economic development of the Beijing-Tianjin-Hebei region is severely uneven. The "Beijing-Tianjin-Hebei Coordinated Development Strategy" is proposed and elevated to a national strategy in this context, aiming to explore the path of coordinated economic development in the Beijing-Tianjin-Hebei region, promote economic cooperation, balance economic differences, and enhance the overall economic strength of the Beijing Tianjin Hebei region through national leadership. The economic collaborative development evaluation in the Beijing-Tianjin-Hebei region is a classical multiple attribute decision making (MADM) problems. Recently, the TODIM and Evaluation based on Distance from Average Solution (EDAS) method has been used to cope with MADM issues. The hesitant triangular fuzzy sets (HTFSs) are used as a tool for characterizing uncertain information during the economic collaborative development evaluation in the Beijing-Tianjin-Hebei region. In this paper, the hesitant triangular fuzzy TODIM-EDAS (HTF-TODIM-EDAS) method is built to solve the MADM under HTFSs. In the end, a numerical case study for economic collaborative development evaluation in the Beijing-Tianjin-Hebei region is given to validate the proposed method. The main contributions of this paper are summarized: (1) the HTF-TODIM-EDAS method is proposed under HTFSs. (2) The MADM method is designed based on the information entropy and HTF-TODIM-EDAS method under HTFSs. (3) A numerical case study for economic collaborative development evaluation in the Beijing-Tianjin-Hebei region is given to validate the proposed method. (4) A comparison between proposed method and existing methods is carried out to check its effectiveness. [ABSTRACT FROM AUTHOR]

In order to deal with severe problems such as environmental pollution and climate change, the Chinese government has proposed the goal of carbon neutrality in 2030 and carbon peak in 2060. Strategic emerging industries have become key areas of high-quality growth of green economy. In order to solve the practical problems of insufficient funds and financing constraints, this paper empirically measures the financing efficiency of strategic emerging industries. Based on the Super Slack-Based Measure model, this paper selects the data analysis of listed companies in Beijing, Tianjin and Hebei from 2011 to 2020. At the same time, this paper systematically combs the index system that affects financing efficiency based on grounded theory. Based on the binary relation and structural level of adjacent matrix and reachable matrix, the explanatory analysis is carried out. On this basis, a systematic GMM model is established to explore the significance of different factors influencing financing efficiency. The research shows that the strategic emerging industry is still in the initial stage, the financing efficiency is not high and the financing output is insufficient. The factors affecting financing efficiency can be divided into 6 dimensions, 20 indicators in total and 5 multipole hierarchical levels. Credit financing, equity financing, financing constraints, technological innovation and government support are the important factors affecting financing efficiency. [ABSTRACT FROM AUTHOR]

The production connection is a crucial component of the Inter City Association. An urban network based on the enterprise perspective better reflects the structural characteristics of regional cities. Based on data gathered from the headquarters and branches of the listed manufacturing enterprises in 2020, this paper analyzes the county-level administrative units in the Beijing-Tianjin-Hebei region of China. Using the subordinate connection model and the social network analysis method, this paper examines the spatial structural characteristics and factors of urban networks in the Beijing-Tianjin-Hebei region. The results suggest that resource allocation in the Beijing-Tianjin-Hebei region is unbalanced, with a significant difference in urban radiation and agglomeration capacity. As the administrative centers, Beijing, Tianjin, and Shijiazhuang show a strong ability to allocate resources within the network. The overall network density in the region was shown to be relatively low, with the main links being of low or medium level. The urban network is defined by the network connection led by Beijing and Tianjin with Beijing-Tianjin-Tangshan and Beijing-Baoding-Shijiazhuang as the main axis. These cities exhibit a "dense southeast and sparse northwest" pattern. From a hierarchical perspective, high-level network connections are based mainly on spatial proximity. Analyzing the agglomerative subgroups, the study found that the inner and outer connections of the core subgroups were relatively high. Semi-marginal subgroups generally accepted the radiation of core subgroups, while marginal subgroups had little connection with other subgroups in the region. The results of the QAP analysis show that the administrative relationship, spatial distance, city size difference, economic development level difference, industrial structure difference, and labor cost difference have a significant influence on the urban network of the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

Agricultural ecological efficiency is an important tool with which to measure the coordination of the sustainable development of agricultural economies and ecological environments. In this paper, a super-efficiency slacks-based measures model was used to measure the agricultural ecological efficiency in Hebei Province. The characteristics of spatial and temporal evolution patterns were explored using a spatial Markov transfer matrix. The results showed that (i) based on measurements, the agricultural ecological efficiency in Hebei Province showed regional differences in four regions (eastern, northern, central and southern Hebei) and 141 counties; (ii) from the perspective of evolutionary characteristics of agricultural ecological efficiency, the overall development of in Hebei Province was good, with more concentrated spatial distribution and more obvious direction, while the type of transfer of agricultural ecological efficiency in Hebei Province showed strong stability that was significantly affected by geographical neighborhood conditions and the club convergence phenomenon; (iii) from the perspective of the long-term evolutionary trend of agricultural ecological efficiency, the areas adjacent to counties with low efficiency had limited potential for improvement, and the areas adjacent to counties with high grade had great potential. However, it was difficult to achieve large-scale improvement in agricultural ecological efficiency in Hebei Province, whether the impact of geospatial backgrounds was considered or not. [ABSTRACT FROM AUTHOR]

As climate change intensifies, drought has become a major global engineering and environmental challenge. In critical areas such as agricultural production, accurate drought monitoring is vital for the sustainable development of regional agriculture. Currently, despite extensive use of traditional meteorological stations and remote sensing methods, these approaches have proven to be inadequate in capturing the full extent of drought information and adequately reflecting spatial characteristics. Therefore, to improve the accuracy of drought forecasts and achieve predictions across extensive areas, this paper employs deep learning models, specifically introducing an attention-weighted long short-term memory network model (AW-LSTM), constructs a composite drought monitoring index (CDMI) and validates the model. Results show that: (1) The AW-LSTM model significantly outperforms traditional long short-term memory (LSTM), support vector machine (SVM) and artificial neural network (ANN) models in drought monitoring, offering not only better applicability in meteorological and agricultural drought monitoring but also the ability to accurately predict drought events one month in advance compared to machine learning models, providing a new method for precise and comprehensive regional drought assessment. (2) The Huang-Huai-Hai Plain has shown significant regional variations in drought conditions across different years and months, with the drought situation gradually worsening in the northern part of Hebei Province, Beijing, Tianjin, the southern part of Huai North and the central part of Henan Province from 2001 to 2022, while drought conditions in the northern part of Huai North, southern Shandong Province, western Henan Province and southwestern Hebei Province have been alleviated. (3) During the sowing (June) and harvesting (September) periods for summer maize, the likelihood of drought occurrences is higher, necessitating flexible adjustments to agricultural production strategies to adapt to varying drought conditions. [ABSTRACT FROM AUTHOR]

The Great Wall Villages (GWVs) are linked to the Great Wall in history, culture, and ecology. The cultural landscape resilience of Great Wall Villages (CLRGWVs) is distinctly significant. However, it is influenced by urbanization, pollution, and a lack of awareness of cultural landscape protection. Therefore, conservation and development practices still lack scientific strategies and guidance. This study proposes a new assessment system to quantify CLRGWVs, an analysis of the main influencing factors of resilience, and optimization paths to maintain sustainable development. Based on the socio-ecological system, this research designed the assessment with three criteria, eleven factors, and thirty-three indexes from the perspective of CLRGWVs. Furthermore, a demonstration test was constructed in Ningyuanbao Village, Dushikou Village, and Longmensuo Village in Chicheng County, Hebei Province, China. The results showed that there is some disparity between the three GWVs, with the resilience score of Dushikou Village being the highest in terms of resistance and learning. In contrast, Ningyuanbao Village's resilience score is the lowest since resistance, recovery, and learning capacity are lower than in Dushikou and Longmensuo. Some influencing factors were found to be highly related to adaptive capacity. Lastly, some low-resilience aspects were identified as critical improvement targets for which corresponding optimization strategies should be proposed. This could be applied to streamline resilience optimization paths according to local conditions. This paper provides new ideas and directions for dealing with the sustainable development of villages and the conservation of cultural landscapes. It will also help villages deal with the relationship between socio-economic development and the conservation of cultural landscapes. [ABSTRACT FROM AUTHOR]

The Beijing-Tianjin-Hebei integration plan rose to the status of a national-level strategy in 2014. This paper provides a deep analysis of the Beijing-Tianjin-Hebei area's inter-city commuter big data. This research analyzed the overview of spatial structure, polycentric structure, hierarchical structure and clustering characteristics of the BTH based on network analysis methods. It reveals that the inter-city commuter network exhibits clear polycentric characteristics, with Beijing acting as the central hub. The degree of network correlation between cities in Tianjin and Hebei is notably low, indicating that the flow of people primarily revolves around Beijing, while interactions between other cities remain limited. Therefore, it is necessary to further decentralize Beijing's non-capital core functions. The level of connectedness among the areas surrounding the Bohai Rim is not very high, and it has not developed the coastal advantage. The cooperation could be strengthed among the cities within Bohai Rim. The polycentric structure has initially taken shape, but it exhibits obvious polarization characteristics. It is necessary to strengthen the interaction of talents between cities to form secondary central units in BTH. [ABSTRACT FROM AUTHOR]

Traditional settlements are vital carriers of Chinese history and culture, reflecting the direct and original needs of generations. However, the modernization of settlements will inevitably disrupt the spontaneous growth patterns inherent in traditional settlements. The degree of disorder of the settlement is not only the embodiment of its form, but also the concrete manifestation of its construction intention. We use the degree of disorder in settlements to assess the construction intentions of the settlements, the results allow us to assess whether new planning aligns with the original construction logic, thereby assessing the extent of interference by modernization in traditional villages. This can provide guidance and assistance for settlement conservation and future planning. By using the Delaunay triangulation network, street polar histogram and direction entropy, and comprehensibility of settlements, this paper quantitatively analyzes the degree of disorder in the three levels of architecture, street and local environment of the settlement. Liangjia Village, the example in this research, is divided into three areas—two new and one old. degree of disorders in architecture, streets, and local environment are calculated and compared with the overall settlement. The study finds that the construction logic for buildings and streets remains stable throughout development. However, notable differences exist in environmental construction principles between new and old sections. The analysis suggests that traditional settlements, guided by inherent principles, maintain stability under external influences, serving as a benchmark for future planning and modernization decisions. [ABSTRACT FROM AUTHOR]

The physical parameterizations have important influence on model performance in precipitation simulation and prediction; however, previous investigations are seldom conducted at very high resolution over Hebei Province, which is often influenced by extreme events such as droughts and floods. In this paper, the influence of parameterization schemes and analysis nudging on precipitation simulation is investigated using the WRF (weather research and forecasting) model with many sensitivity experiments at the cumulus "gray-zone" resolution (5 km). The model performance of different sensitivity simulations is determined by a comparison with the local high-quality observational data. The results indicate that the WRF model generally reproduces the distribution of precipitation well, and the model tends to underestimate precipitation compared with the station observations. The sensitivity simulation with the Tiedtke cumulus parameterization scheme combined with the Thompson microphysics scheme shows the best model performance, with the highest temporal correlation coefficient (0.45) and lowest root mean square error (0.34 mm/day). At the same time, analysis nudging, which incorporates observational information into simulation, can improve the model performance in precipitation simulation. Further analysis indicates that the negative bias in precipitation may be associated with the negative bias in relative humidity, which in turn is associated with the positive bias in temperature and wind speed. This study highlights the role of parameterization schemes and analysis nudging in precipitation simulation and provides a valuable reference for further investigations on precipitation forecasting applications. [ABSTRACT FROM AUTHOR]

Simple Summary: Enteric viruses act as etiological agents for a series of health disturbances that pose a threat to commercial chickens worldwide. The affected chickens exhibit stunted growth, low feed conversion, etc. On a global scale, research on enteric virus diversity has been performed in countries such as India, South Korea and Brazil, yet at present, there have been no conclusive reports of avian enteric viruses in China. In the present study, the virus species, infection types, clinical symptoms, and relationships among the virus species were studied in 145 positive enteric virus samples. Additionally, the evolutionary relationship and recombination of the viruses were also further studied. The results of this study can be used to define the distribution and infection type of enteric viruses in poultry, and to analyze the classification of and evolutionary relationship between certain viruses. Enteric viruses, as a potential pathogen, have been found to be vital causes of economic losses in poultry industry worldwide. The enteric viruses widely studied to date mainly include avian nephritis virus (ANV), avian reovirus (ARe), chicken astrovirus (CAstV), chicken parvovirus (ChPV), fowl adenovirus group I (FAdV-1), infectious bronchitis virus (IBV), and avian rotavirus (ARoV). This paper aimed to identify single and multiple infections of the seven enteric viruses using the data obtained from positive 145 enteric virus samples in poultry flocks from different areas in Hebei Province, throughout the period from 2019 to 2021. Next, the correlation between bird age and clinical signs was investigated using PCR and RT-PCR techniques. Furthermore, the whole genomes of seven parvovirus strains and open reading frame 2 (ORF2) of six CAstV strains and eight ANV strains were sequenced for phylogenetic analysis and recombination analysis, to characterize the viruses and evaluate species correlation and geographic patterns. A total of 11 profiles of virus combinations were detected; 191 viruses were detected in 145 samples; 106 single infections were reported in 73.1% of the samples; and multiple infections were detected in the remaining 26.9%. For viruses, 69% of ChPV was correlated with single infection, while ANV (61.4%) and CAstV (56.1%) were correlated with multiple infections. However, IBV and ARe were not detected in any of the samples. Recombination events were reported in parvovirus, and all CAstV sequences investigated in this paper were included within genotype Bii. The eight ANV strains pertained to different subtypes with significant differences. The above results revealed for the first time the complexity of enteric viruses over the past several years, thus contributing to disease prevention and control in the future. [ABSTRACT FROM AUTHOR]

Restoration and protection of ancient towns is an essential approach and a material carrier of inheriting cultural context, realizing economic transformation, revitalizing the tertiary industry, building a strong county and making a better life for peoples. This paper took Ancient Luanzhou Town in Luanzhou City, Tangshan of Hebei for example, used Photoshop to compare different elements of the town in pictures taken from Baidu Street View in 2014 and 2016, and calculated weights and scores of different elements using yaahp software. Based on this, the paper analyzed the space development tendency of Ancient Luanzhou Town, evaluated the changes of its space quality, and proposed suggestions for the improvement of space quality. [ABSTRACT FROM AUTHOR]

To effectively analyze the safety risk of chemical enterprises and ensure the safety of production and management of enterprises, the contradiction problems in the process of index selection and risk early warning model in practical application are addressed. In this paper, extension engineering is introduced into the safety-security field of chemical enterprises to extract hidden useful information from the production environment and outdoor environment data and provide decision support for the managers of chemical enterprises. First, based on data preprocessing and extension analysis, the safety-security data of chemical enterprises that meet the quality requirements and can be efficiently mined are searched. Then, the outdoor environment is combined in the paper to conduct the mining of these data in two aspects: (1) comprehensive analysis and evaluation of data quality; (2) key factors affecting factory safety mining, realizing the safety-security evaluation of intelligent factories in chemical enterprises. Based on the proposed chemical factory safety extension prerisk model, the risk assessment of the safety status of a chemical enterprise in Hebei Province is carried out. The research results of this paper provide a theoretical basis for the safety production analysis of such chemical enterprises and put forward practical suggestions for preventing possible accidents in the production process. [ABSTRACT FROM AUTHOR]

There is a centralization of the core content in the text information of the new crown epidemic notification. This paper proposes a joint learning text information extraction method: TBR-NER (topic-based recognition named entity recognition) based on topic recognition and named entity recognition to predict the labeled risk areas and epidemic trajectory information in text information. Transfer learning and data augmentation are used to solve the problem of data scarcity caused by the initial local outbreak of the epidemic, and mutual understanding is achieved by topic self-labeling without introducing additional labeled data. Taking the epidemic cases in Hebei and Jilin provinces as examples, the reliability and effectiveness of the method are verified by five types of topic recognition and 15 types of entity information extraction. The experimental results show that, compared with the four existing NER methods, this method can achieve optimality faster through the mutual learning of each task at the early stage of training. The optimal accuracy in the independent test set can be improved by more than 20%, and the minimum loss value is significantly reduced. This also proves that the joint learning algorithm (TBR-NER) mentioned in this paper performs better in such tasks. The TBR-NER model has specific sociality and applicability and can help in epidemic prediction, prevention, and control. [ABSTRACT FROM AUTHOR]

Introduction: Leaf area index (LAI) is a critical physiological and biochemical parameter that profoundly affects vegetation growth. Accurately estimating the LAI for winter wheat during jointing stage is particularly important for monitoring wheat growth status and optimizing variable fertilization decisions. Recently, unmanned aerial vehicle (UAV) data and machine/depth learning methods are widely used in crop growth parameter estimation. In traditional methods, vegetation indices (VI) and texture are usually to estimate LAI. Plant Height (PH) unlike them, contains information about the vertical structure of plants, which should be consider. Methods: Taking Xixingdian Township, Cangzhou City, Hebei Province, China as the research area in this paper, and four machine learning algorithms, namely, support vector machine(SVM), back propagation neural network (BPNN), random forest (RF), extreme gradient boosting (XGBoost), and two deep learning algorithms, namely, convolutional neural network (CNN) and long short-term memory neural network (LSTM), were applied to estimate LAI of winter wheat at jointing stage by integrating the spectral and texture features as well as the plant height information from UAV multispectral images. Initially, Digital Surface Model (DSM) and Digital Orthophoto Map (DOM) were generated. Subsequently, the PH, VI and texture features were extracted, and the texture indices (TI) was further constructed. The measured LAI on the ground were collected for the same period and calculated its Pearson correlation coefficient with PH, VI and TI to pick the feature variables with high correlation. The VI, TI, PH and fusion were considered as the independent features, and the sample set partitioning based on joint x-y distance (SPXY) method was used to divide the calibration set and validation set of samples. Results: The ability of different inputs and algorithms to estimate winter wheat LAI were evaluated. The results showed that (1) The addition of PH as a feature variable significantly improved the accuracy of the LAI estimation, indicating that wheat plant height played a vital role as a supplementary parameter for LAI inversion modeling based on traditional indices; (2) The combination of texture features, including normalized difference texture indices (NDTI), difference texture indices (DTI), and ratio texture indices (RTI), substantially improved the correlation between texture features and LAI; Furthermore, multi-feature combinations of VI, TI, and PH exhibited superior capability in estimating LAI for winter wheat; (3) Six regression algorithms have achieved high accuracy in estimating LAI, among which the XGBoost algorithm estimated winter wheat LAI with the highest overall accuracy and best results, achieving the highest R² (R² = 0.88), the lowest RMSE (RMSE=0.69), and an RPD greater than 2 (RPD=2.54) Discussion: This study provided compelling evidence that utilizing XGBoost and integrating spectral, texture, and plant height information extracted from UAV data can accurately monitor LAI during the jointing stage of winter wheat. The research results will provide a new perspective for accurate monitoring of crop parameters through remote sensing. [ABSTRACT FROM AUTHOR]

A PDE‐constrained model predictive control (MPC) algorithm for open‐channel systems based on the Saint‐Vevant(S‐V) equations is investigated in this paper. The S‐V equations, which precisely model the dynamics of open‐channel systems, are quasi‐linear hyperbolic partial differential equations (PDEs) without analytical solutions. Directly applying the S‐V equations to an MPC controller design becomes sophisticated. In this work, the calculus of variation is used to obtain the adjoint equations and the adjoint analysis method is utilized to deduce the gradients of the MPC optimization problem. Particularly, the physical constraints involving both the state and control variables are also considered. A gradient‐based optimization algorithm in combination with the numerical computation of Preissmann implicit scheme is proposed to solve the constrained MPC optimization problem. The control performances of the developed PDE‐constrained MPC algorithm with respect to the controlled water levels and gate openings are compared with those of the MPC controller designed for the linearized model. All the simulation tests are carried out on an aqueduct reach in Yehe Irrigation District in Hebei Province, China. The results show that the proposed PDE‐constrained MPC algorithm is a promising method in dealing with the constraints in terms of hyperbolic PDEs, control variables and state variables simultaneously. [ABSTRACT FROM AUTHOR]

Based on county-level panel data from 2014 to 2017 in Jing-Jin-Ji region, this paper employs SDEM model to analyze the impact and heterogeneity of digital inclusive finance on poverty alleviation. The results show that, first, digital inclusive finance exerts significant poverty alleviation effect, and this effect focuses on local region, having no apparent spillover effects on neighborhood counties. Second, the poverty alleviation effects of digital inclusive finance are heterogeneous, the effects of index of Coverage and Usage, and basic, upgraded and supported digital finance service are different in Jing-Jin-Ji, Hebei and Poverty Area Samples. Third, digital inclusive finance exerts bigger poverty alleviation effect on the less developed region and poverty region, showing the effect of Corner Overtaking. [ABSTRACT FROM AUTHOR]

This article uses 43 Sentinel-1A image datasets covering Beijing to obtain time series surface deformation information in the study area from January 2022 to October 2023. It analyzes the causes of land subsidence by integrating precipitation and urban construction. The main research results are as follows: (1) Three distinct subsidence areas are identified in the eastern part of Chaoyang District in Beijing (Subsidence Area A), the northwestern part of Tongzhou District in Beijing (Subsidence Area B), and Yanjiao Town in Hebei Province (Subsidence Area B), which is adjacent to Beijing. Subsidence Areas A and B exhibit a dispersed pattern, with maximum land subsidence rates exceeding −30 mm/year. In contrast, Subsidence Areas C displays a funnel-shaped subsidence, where the majority of areas experience land subsidence rates exceeding −25 mm/year, with a maximum rate reaching −45 mm/year. (2) Precipitation has a significant impact on surface deformation in the study area, and there is a strong correlation between precipitation and land subsidence, with correlation values of 0.77, 0.77, and 0.74, respectively. (3) Urban construction has a certain impact on land subsidence, but the degree of impact varies in different regions. [ABSTRACT FROM AUTHOR]

Due to the influences of the storage environment, water content change, particle settlement, natural loss, and other factors, the distribution density of wheat and the volume of grain pile in the storage process are gradually changed so that the single weight calculation method cannot objectively evaluate the storage quantity of wheat and also causes difficulties to the regular inspection of the quantity of wheat stock. To meet the practical needs of wheat inventory monitoring, a wheat inventory monitoring method based on inventory measurement and the support vector machine regression (SVR) prediction model is proposed. By collecting the working papers for the physical inspection of wheat in grain warehouses in Shanxi province, Hebei province, Henan province, Jiangsu province, and other places, the storage time, storage weight, storage moisture content, measured moisture content, measured volume weight, measured net volume, and measured weight for inspection were selected as training samples for the SVR prediction model, and kernel function selection and parameter optimization were carried out. We developed an optimal prediction model for the amount of wheat in the grain depots. In the actual grain store measurement process, the net volume of wheat in the current grain store was obtained by a laser volumetric measuring apparatus, the actual bulk density of wheat was sampled, and the actual moisture content of wheat was measured by sampling. The three samples, their storage time, their storage moisture content, and their storage weight were fed into the trained SVR prediction model as new samples, and the predicted weight of the wheat in the current grain store was obtained from the output. The error rate calculation procedure was introduced to achieve an anomalous judgment error rate for grain depots. The experimental results showed that the SVR prediction model based on the linear kernel function had a very low mean squared error and high determination coefficient, and the average prediction accuracy of the grain stock error rate reached 93.2 percent, which can meet the requirements of wheat quantity monitoring in grain warehouses. [ABSTRACT FROM AUTHOR]

Lightning has a certain degree of potential threat to the safe operation of overhead transmission lines. In order to make targeted lightning protection arrangements and reduce the impact of lightning on overhead transmission lines, it is necessary to conduct lightning risk assessments on overhead transmission lines. This paper proposes a lightning failure risk assessment method for overhead transmission lines based on a modified Dempster–Shafer theory. First, analyze the historical lightning failure data of the line, determine the lightning failure impact factors, and use confidence to express the relationship between the lightning failure and the impact factor; then, use entropy weight theory and gray relational theory to calculate the value of mass function, and modify it on this basis; finally, use Dempster–Shafer theory to determine the trust degree and fit this with the calculated lightning trip rate to produce the risk assessment. This paper analyzes the lightning failure data of overhead transmission lines in some areas of Hebei Province. The results show that, compared with the evaluation method of the Dempster–Shafer theory, the accuracy of the evaluation is improved to a certain extent after correcting the mass function value. It can be seen that this method can integrate and comprehensively consider different data and can provide a reference for preventing damage to transmission lines by lightning strike weather. [ABSTRACT FROM AUTHOR]

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

Micro-credit for poverty alleviation is an important financial measure of targeted poverty reduction and rural revitalization in China. This paper employs the OLS model and Logit model to empirically test the effect of micro-credit for poverty alleviation on the income level and stability of income growth of farmers based on the field survey data of 458 registered poverty-stricken farmer households in Fuping County and Quyang County of Hebei Province. The results suggest that micro-credit for poverty alleviation can increase farmers' income, stabilize the growth of their income, and exert significant short-term and long-term effects on income growth and poverty alleviation. The specialized farmer cooperatives, the scale of production and operation, the proportion of family labor force, and the education level of the head of the farmer's household exert a significantly positive effect on the farmers' income and the stable growth of their income. There is a significant interaction between micro-credit for poverty alleviation and specialized farmer cooperatives. The physical conditions of family members exert a negative effect on the stable growth of their income, and other financing channels have no significant effect. [ABSTRACT FROM AUTHOR]

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

The suitability evaluation of urban human settlements is an important foundation to promote the sustainable development of urban human settlements. This paper took 11 prefecture-level cities in Hebei Province as the research area, and selected 18 indicators from four aspects of ecological environment quality, socio-economic status, living conditions, infrastructure and public services to construct an evaluation index system for the suitability evaluation of the human settlement environment in Hebei Province. The fuzzy clustering analysis method was used to divide the suitability of the human settlement environment in Hebei Province in 2017. The results showed that there are obvious regional differences of human settlement environment suitability in Hebei Province, the findings provide experience for the sustainable development of human settlement environment in Hebei Province. [ABSTRACT FROM AUTHOR]

With the accelerating urbanization process in China, the extensive economic growth model with high energy consumption and high pollution aggravates atmospheric environmental pollution and restricts the sustainable development of the social economy. The Beijing–Tianjin–Hebei region has the most severe haze pollution and the most acute contradiction between resources, environment and economic development. Based on the physical coupling theory, this paper constructs a coupling coordination degree model of the economy, environment and high haze pollution industries, such as the thermal power industry. Through literature analysis and expert investigation of the economic, industrial and environmental data of the Beijing–Tianjin–Hebei region from 2006 to 2018, the coordinated development of the economy, environment and high haze pollution industries, such as the thermal power industry, in the above region, was dynamically monitored. The monitoring results show that the development level of the Beijing, Tianjin and Hebei region is significantly different, and the three subregions have not entered the stage of coordinated development. Moreover, since 2015, they have been in a bottleneck period of development and have not achieved a higher level of progress. The three subregions have different advantages and restraining factors. For example, the backward level of Hebei's economy and high haze pollution industries, such as the thermal power industry, restrict the coordinated development of the region as a whole. Only by accelerating the high-quality development of the Hebei economy can we break through the bottleneck of the development of Beijing, Tianjin and Hebei. [ABSTRACT FROM AUTHOR]

Previous studies have demonstrated that grain loss in the harvest process accounts for a large loss in all aspects of the grain supply chain. This research extensively discusses the impact of farmland management scale on grain loss in the harvest process based on survey data on farmers' productivity in the Shandong and Hebei provinces of China. The findings revealed that the scale of farmland operation directly influenced the grain loss during harvest and that this effect is greatly reduced as the farmland operation scale increases. This study also constructed an intermediary model, investigated the influence mechanisms, and added agricultural capital as a variable in the harvest link. It was discovered that the scale of agricultural land management has an indirect effect on grain loss in the harvest link via the input of agricultural capital in the harvest link. The increase in agricultural capital investment in the harvest link considerably reduced this effect. In order to decrease grain losses during the harvest process, this paper suggests expanding the size of agricultural enterprises, developing new agricultural corporate organizations, and further playing the role of the rural land market. [ABSTRACT FROM AUTHOR]

This paper based on the theory of space syntax took Luochengtou Village in Handan City, Hebei Province for example, tried to figure out a proper way for the renewal of urban villages, and change the current dilemma of "one-size-fits-all" and "removing all" in most cases, and put forward that local conditions and regional characteristics must be considered to propose the renewal strategies more suitable for the targeted objects. Based on the space syntax Depthmap software and field investigation, the paper analyzed the accessibility, intelligibility and throughput of public spaces in Luochengtou Village, and put forward 3 optimization strategies in view of the problems such as insufficient public spaces, poor accessibility and intelligibility of roads, and poor activity of spaces, specifically, increasing public activity spaces, sorting out public space network, and creating active space nodes, so as to optimize public environment of the village, enhance villagers' sense of belonging, sense of safety and sense of identity. [ABSTRACT FROM AUTHOR]

The development of Xiongan New Area in Hebei Province, China, as a significant national choice, has considerable strategic significance for the integrated growth of Beijing, Tianjin, and Hebei. This paper proposes a cloud model for the suitability evaluation of the construction of Xiongan New Area based on entropy weight analysis, taking into account the geological conditions, groundwater environment, environmental geological problems, and other factors of the suitability of image city development. According to the research, the suitability evaluation findings for the project building employing the cloud model are in strong accord with those of the traditional model and have some application potential. The evaluation's findings indicate that the project construction in Xiongan New Area is acceptable, with suitable and relatively suitable sites making up 81.4% of the total area and excellent circumstances for project development, construction, and usage. This study offers helpful direction for Xiongan New Area's urban land-space design and serves as a useful point of comparison for studies looking at the viability of other deep Quaternary Plain region engineering buildings. [ABSTRACT FROM AUTHOR]

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Reasonably allocating the micro factor investment in the industry and trying to improve the energy efficiency are very important for the green development of industrial economy in Hebei Province, so as to the achievement of its double carbon target. This paper takes industrial energy consumption, assets and labor in Hebei Province as micro-input elements. Based on the panel data of 34 industrial industries in Hebei Province from 2005 to 2016, we identify the correlation of micro-input factors in different industries and conduct Granger causality test. The study shows that: (1) About half of the industry's combined energy consumption is correlated with the number of employees and assets; About two-thirds of the industry's asset workers are relevant; (2) There is a two-way causal relationship between the total energy consumption and assets of most industries and the annual average number of employees. (3) The rational allocation of capital, labor and energy consumption depends on the deepening reform of the factor market. The high energy consumption industry should actively improve and innovate the energy technology in this process to realize the coordinated promotion of energy saving and carbon reduction, and thus to promote the healthy and sustainable development of the industry steadily. [ABSTRACT FROM AUTHOR]

In order to promote the sustainable development of the hydrogen energy industry in Hebei Province, this paper investigates the coordinated industrial coupling and spatio-temporal evolution of the "resource conditions-project layout-user demand (R-P-D)" chain within the hydrogen energy industry in Hebei Province. First, a fitness model for the hydrogen energy industry is formulated based on the "(R-P-D)" chain perspective, and a comprehensive evaluation is performed using the AHP entropy weighting method.Subsequently, coupling coordination model of resource condition-project layout (R–P), resource condition-user demand (R-D), project layout-user demand (P-D), and R-P-D chain are constructed. The coupling coordination degree data of the system are then linked with the spatial unit for spatiotemporal evolution and analysis using ArcGIS software. The findings indicate that cities with high levels of economic development, advanced industrialization, abundant renewable energy resources, and well-developed clean energy industries tend to exhibit more harmonious development in the hydrogen energy industry. • Construct the "R-P-D″ chain within the hydrogen energy industry. • ArcGIS are used to carry out the spatiotemporal evolution of each system. • Provides a theoretical basis for the design and planning of hydrogen energy industry. [ABSTRACT FROM AUTHOR]

Aim Design Methods Results Conclusions To investigate symptom clusters and sentinel symptoms in breast cancer survivors based on self‐reported outcomes, explore the impact of sentinel symptoms on patients' quality of life and psychological distress, provide a basis for implementing accurate symptom management.A cross‐sectional survey.The study was conducted from September 2021 to December 2022. We recruited 281 patients who were re‐examined in an outpatient department of a tertiary hospital in Hebei Province. The European Organization for the Research and Treatment of Cancer (EORTC) Quality‐of‐Life Questionnaire ‐ Core30 (QLQ‐C30), the EORTC Quality‐of‐Life Questionnaire Breast Cancer ‐ 23 (QLQ‐BR23), the Hospital Anxiety and Depression Scale (HADS) were used to conduct the survey. Symptom clusters were explored using principal component analysis, sentinel symptoms were explored using the Apriori algorithm. Correlation analysis was used to explore the relationship between sentinel symptoms and quality of life, correlation with psychological distress. This paper adhered to the STROBE guidelines.Breast cancer survivors have a wide range of self‐reported symptoms in the form of four symptom clusters: a fatigue symptom cluster, a gastrointestinal symptom cluster, a sickness symptom cluster and a surgical trauma‐related symptom cluster. Three sentinel symptoms were explored: pain, alopecia and limited function of the upper limbs. Except for sexual function, all of the sentinel symptoms were negatively correlated with patients' quality of life and positively correlated with psychological distress (p < .05).Breast cancer survivors have a variety of symptoms in the form of four symptom clusters. Pain, alopecia and limited function of the upper limbs are the sentinel symptoms, which affect patients' quality of life and psychological distress. [ABSTRACT FROM AUTHOR]

Shallow geothermal heat has the characteristics of wide distribution and huge reserves. However, for northern rural buildings, the heating load in winter is much greater than the cooling load in summer, and thermal imbalance of the soil is prone to occur. This paper takes rural residences in southern Hebei as an example and designs a solar-assisted shallow geothermal energy system. Compared with the original shallow ground-source heat pump system, the indoor and outdoor temperature differences of the target building were first analyzed. Second, the changes in the soil temperature field and the differences in the supply and return water temperature were monitored. Finally, the initial investment and operating costs of the assisted system are analyzed. The results show that the average ground temperature field increases significantly in winter. Through the alternate operation of solar energy and ground-source heat pumps, heat extraction from the ground is reduced, and the imbalance cycle of heat extraction in winter and heat removal in summer is shortened. It alleviates the imbalance of the cold and heat loads for soil throughout the year. The inlet and outlet water temperature and heat exchange efficiency of the buried pipes have been significantly improved. The energy efficiency ratio of the system using the assisted system has increased from 3.40 in 2020 to 4.17, an increase of 0.77. The optimal ratio of the solar- assisted shallow geothermal energy system is a 12.80 m2 solar heat-collection area and one buried hole. The winter heating operating cost of the solar-assisted shallow geothermal energy system is 18.86 CNY/m2. It can save 37% of the annual operating costs of heating, cooling, and hot water compared to a single ground-source heat pump system and 40%–45% compared to traditional heating and cooling modes. [ABSTRACT FROM AUTHOR]

With the deepening implementation of the energy revolution and the advent of the era in which renewable energy will be grid parity, China's offshore wind power projects have gradually taking steps to shape a large-scale development. This paper reviews the relevant policies for offshore wind power, adopting the levelized cost of electricity (LCOE) model to conduct an economic evaluation of offshore wind power projects in six typical provinces in China. Among the six provinces studied in this paper, Hebei Province has the highest LCOE value of 0.87 yuan/kWh, and Fujian Province has the lowest LCOE value of 0.71 yuan/kWh; the LCOE results of offshore wind power projects in Hebei and Guangdong provinces are higher than the policy guidance price by 8.75% and 6.25% respectively; the LCOE value of the offshore wind power projects in the other four provinces are lower than the guidance price, and the average profit is considerable; the expected annual utilization hours and unit cost have varied impact on the LCOE value in different provinces. The results show that with the upcoming offshore wind power on-grid price bidding era, China's offshore wind power grid parity era is just around the corner. Finally, this paper puts forward relevant policy suggestions, hoping to provide practical guidance for the promotion of offshore wind power technology in China. [ABSTRACT FROM AUTHOR]