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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]

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]

The coordination and stability of the regional economy (RE) and ecological quality (EQ) are essential for the synergistic development of the Beijing–Tianjin–Hebei urban agglomeration (BTH). In this paper, based on remote sensing data and economic statistics data, this paper analysed the current situation and evolution of the RE and EQ in the BTH region. Based on the coupled coordination degree (CCD) model, this paper has developed an evaluative framework and quantifies the spatiotemporal coupled coordination of the RE and EQ in the BTH region from 2000 to 2020. The results show that: (1) in 2020, the GDP of the poverty-stricken counties (PSCs) around BTH accounted for 4.57% of the total BTH region, and the area of high-quality ecosystems, Net Primary Productivity (NPP), soil conservation, water conservation, and sand fixation accounted for more than 40% of the total BTH region; (2) the GDP growth of the PSCs accounted for 4.45% of the total growth in BTH, the reduced area of high-quality ecosystems accounted for 21.04%, and the increase in NPP, soil conservation, water conservation, and sand fixation accounted for more than 40% of the total growth in the BTH region; (3) the CCD of the RE and EQ in the BTH region showed a tendency to increase, but the gap between the regions gradually expanded, and the development type changed from a lagging RE to a lagging EQ, in which the coupled coordination grade of the PSCs was in a dissonance stage for a long time, and the level of economic development had to improve. Deepening the understanding of the spatiotemporal coupling relationship between the RE and EQ and adopting appropriate development policies is of great significance for achieving the coordinated and integrated development of the BTH region. [ABSTRACT FROM AUTHOR]

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]

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]

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]

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]

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]

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 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]

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]

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]

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]

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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]

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 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]

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]

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]

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]

Copyright of Big Data Research (2096-0271) is the property of Beijing Xintong Media 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.)

The presence of an urban active fault carries a geological hazard risk that threatens urban construction. Therefore, detecting such faults is crucial for mitigating potential risks and ensuring safe urban development. The grounded-wire source short-offset transient electromagnetic method (SOTEM) offers an opportunity to identify faults with high-conductivity. The results of a SOTEM survey conducted in Shunping, Hebei Province, were presented to detect buried faults and locate the industrial park. Data were analysed using the one-dimensional inversion method with SOTEMsoft software, which was denoised using the short-time sliding window adaptive singular value decomposition algorithm based on the wavelet threshold. Despite the challenges posed by urban features, particularly traffic, the survey results located the fault and hold significant potential to reveal its extent and depth. The study highlights the importance of avoiding fault sites during urban construction, even though the area is currently tectonically stable. This paper reveals an unusual opportunity to study the effectiveness of electromagnetic methods for detecting buried faults in cities and reveal geological structures covered by Quaternary formations. [ABSTRACT FROM AUTHOR]

Studying the internal relationship between urbanization process and cultivated land change can reveal the differential law of different urbanization processes and effectively protect cultivated land resources. Using the land-use change analysis method, this paper analyzed the quantity and quality change of cultivated land during the process of urbanization in the Bohai Rim region from 1990 to 2020 and explored its driving mechanism. The results show that the urbanization level in the Bohai Rim region increases by 31.06%, and 120 km2 farmland will be occupied for every 1% increase in urbanization level. The level of urbanization is higher in Beijing and Tianjin, medium in Liaoning and Shandong, and lower in Hebei. The area of cultivated land decreased year by year, and the decrease in dry land was the largest, followed by paddy land. Hebei, Shandong, and Liaoning have a high contribution rate to the reduction in cultivated land around the Bohai Sea. Population urbanization, spatial urbanization, and other factors have a significant impact on the study area, while economic urbanization and life urbanization show different laws. It is suggested that the development of urbanization can be promoted in a timely and appropriate manner, and the harmonious development of urbanization can be promoted by optimizing the layout of land use and avoiding excessive occupation of cultivated land at the expense of food security and ecological environment. [ABSTRACT FROM AUTHOR]

In this paper, a multisensor data acquisition system based on FPGA is designed to provide an overview of the current development of the company based on the theoretical knowledge of enterprise development strategy. Through a comprehensive investigation of the company's internal environment, the advantages and disadvantages of the company at this stage are clarified, and the opportunities and threats to the company's development are analyzed in the context of the external macroenvironment and industry development. The coupling coordination degree from 2011 to 2025 was measured using the coupling coordination degree model based on the original data and the prediction results, and the results showed that from 2011 to 2025, the coupling coordination degree of Hebei Province showed a continuous growth and experienced the transition from low coordination, basic coordination, to medium coordination in the coupling coordination stage, aiming at the most innovative fields, mastering the most advanced technologies, cooperating with industry giants, innovating, and building digital ecology, creating, and forming core competitiveness based on core independent products and platform-based solutions, and further promoting transformation and upgrading and high-quality development. In this paper, the data acquisition system is tested by building an experimental platform. The main purpose is to test the stability and accuracy of each module of the data acquisition system. After each module test of the system meets the design requirements, the parallel mechanism attitude transformation test experiment is completed, including the moving platform moving test experiment and the moving platform rotation test experiment. The experimental results show that the designed data acquisition system has stable program and reliable function. [ABSTRACT FROM AUTHOR]

Although urban expansion statistics have been widely carried out, large-scale and rapid monitoring is still worth doing in order to improve the efficiency of statistics, as well as make up for the omissions and deficiencies of construction expansion statistics with multi-year intervals. This paper presents a study of urban expansion in the Beijing–Tianjin–Hebei plain based on ALOS Global Digital Surface Model "ALOS World 3D-30 m" (AW3D30 DSM), Shuttle Radar Topography Mission (SRTM) DSM, and Landsat 7 ETM+ images. Through the evaluation of errors and the elimination of non-building changes, a relatively objective result is derived. The neighborhood block statistics of the construction height expansion reveal that from 2000 to 2009, the largest centralized construction expansion mainly occurred between the Second Ring Road and the Fifth Ring Road of Beijing, followed by Yizhuang, Shunyi, Tianjin Central City, and Langfang. Zonal statistics also show a significant imbalance in the expansion of construction in the counties of the Beijing–Tianjin–Hebei plain. For example, Chaoyang, Dongcheng, Xicheng, Xuanwu, Chongwen, Nankai, Heping, and Hexi have a larger construction expansion; however, other counties present a relatively slow rate of building expansion. Furthermore, the correlation coefficient between the statistical average building height expansion per unit area (ABHE, by our method) and the actual average completed building floor space per unit area (ACBFS) derived from the Beijing Statistical Yearbook (BSY) is 0.9436, which proves that this method is feasible. With the continuous improvement of DSM data quality in the future, the method proposed in this paper can provide rapid and large-scale statistics to study more urban construction expansion in the world. [ABSTRACT FROM AUTHOR]

Air quality index (AQI) is an essential measure of air pollution evaluation, which describes the air pollution degree and its impact on health, so the accurate prediction of AQI is significant. This paper presents an AQI prediction model based on Convolution Neural Networks (CNN) and Improved Long Short-Term Memory (ILSTM), named CNN-ILSTM. ILSTM deletes the output gate in LSTM and improves its input gate and forget gate, and introduces a Conversion Information Module (CIM) to prevent supersaturation in the learning process. ILSTM realizes efficient learning of historical data, improves prediction accuracy, and reduces the training time. CNN extracts the eigenvalues of input data effectively. This paper uses air quality data from 00:00 on January 1, 2017, to 23:00 on June 30, 2021, in Shijiazhuang City, Hebei Province, China, as experimental data sets, and compares this model with eight prediction models: SVR, RFR, MLP, LSTM, GRU, ILSTM, CNN-LSTM, and CNN-GRU to prove the validity and accuracy of CNN-ILSTM prediction model. The experimental results show the MAE of CNN-ILSTM is 8.4134, MSE is 202.1923, R2 is 0.9601, and the training time is 85.3 s. In this experiment, the performance of this model performs better than other models. [ABSTRACT FROM AUTHOR]

With the rise of the strategy of Coordinated Development for the Beijing-Tianjin-Hebei Region, it is necessary to evaluate the trade-offs/synergies of the survival environment and human well-being in Hebei, the capital region of China. However, existing methods cannot analyze and express trade-offs/synergies of two or more variables simultaneously. Therefore, this paper proposes a new framework to express the trade-offs/synergies among land-use intensity, ecosystem services, and human well-being. In this paper, we first identified the land-use intensity change and land-use transformation and evaluated ecosystem services and human well-being in Hebei from 2000–2015 under the Millennium Ecosystem Assessment framework. Then, the trade-offs/synergies of the three indicators were determined by GIS-based methods and MATLAB. The results show that land-use intensity and human well-being mainly present a synergistic relationship, while ecosystem services and land-use intensity mainly present a trade-off relationship, and ecosystem services and human well-being also present a trade-off relationship in Hebei during 2000–2015. In addition, some regional solutions to achieve sustainable development were proposed: region 1 needs to adjust land-use structure, region 2 needs to protect the ecological environment to improve the supply of ecosystem services, and region 3 needs to commit to improving the regional comprehensive human well-being. This study not only proposes a new framework for analyzing trade-offs/synergies of land use intensity, ecosystem services, and human well-being, but it also provides regional solutions for Hebei to achieve sustainable development. [ABSTRACT FROM AUTHOR]

In order to determine the key content of preventive maintenance of the cement concrete pavement in military airports in the seasonal frozen area, the relationship among pavement diseases is analyzed in this paper, and the degree of impact of each disease on pavement damage is quantified. Based on the survey data of 36 sample airports in 12 provinces, such as Hebei, Shandong, and Liaoning, a questionnaire covering many disease variables affecting pavement damage was designed. The exploratory factor analysis method and structural equation model (SEM) were used to analyze the interaction among joint disease, surface disease, vertical disease, repair disease, and fracture disease. And the influence degree of each disease on pavement damage was quantified as well. The research results show that the questionnaire has good reliability and validity and is suitable for confirmatory factor analysis. The SEM fits well with the observed data and meets the adaptation standard. Joint disease, surface disease, and vertical disease all have significant positive direct impact on pavement damage. Moreover, joint disease and surface disease can also indirectly affect pavement damage. The effects of surface disease (0.327), vertical disease (0.283), and joint disease (0.219) on pavement damage decrease in turn. Surface diseases have the greatest impact on pavement damage, which are the critical diseases to accelerate the pavement damage. By strengthening the prevention and control of surface diseases and delaying the conversion process of other diseases to surface diseases, the service life of the pavement can be greatly improved, and the maintenance cost can be reduced. [ABSTRACT FROM AUTHOR]

With the development of global economy, the evaluation of industrial clusters has become an important method to scientifically analyze the advantages and disadvantages of industrial development. The current research model uses the traditional evaluation method, which leads to the problem of unsatisfactory evaluation results and low effect. This paper proposes an evaluation model based on the BP neural network combined with the LM algorithm, which has the advantages of fast convergence speed and strong application ability. The comprehensive evaluation model of industrial clusters is put forward from the comprehensive application of the scale, benefit, and 27 related evaluation indexes of industrial clusters. This paper takes Beijing, Tianjin, and Hebei industrial clusters for BP-LM evaluation and analysis, which fully illustrates the advantages of this method. The evaluation results show that the evaluation target value and the average error of the overall parity have obvious advantages compared with those of other models, which provides application guidance for local economic development and policy formulation. [ABSTRACT FROM AUTHOR]

Clarifying the constituent elements of agricultural land quality, carrying out multi-dimensional quality evaluation of agricultural land, and implementing precise land consolidation and utilization zoning all have important guiding significance for achieving efficient utilization of agricultural land in China. This work analyzed the multi-dimensional evaluation framework of agricultural land based on its comprehensive quality elements and the production, ecological, and health functions. This paper constructed a multi-dimensional agricultural land "production–ecology–health" quality evaluation index system and evaluation criteria, and carried out a multi-dimensional quality evaluation of agricultural land in Huanghua City, Hebei Province, China. The spatial superposition of each dimension′s evaluation results, combined with the logical relationship between agricultural land use and each dimension′s quality, realized the renovation and utilization zoning of agricultural land. The results are as follows: (1) The production, ecological, and health qualities of agricultural land in Huanghua City were below the average and there is spatial variability, whose proportions of grade III and below were 63.12, 66.23, and 69.32%, respectively. In addition, low score areas are mainly located in the south and northwest of the study area. (2) The obstacle factors to quality in different dimensions were different: The obstacle factors to production quality were matter content, soil pH, irrigation guarantee rate, and alkaline hydrolysis nitrogen; groundwater salinity and depth, soil pH, and chemical fertilizers consumption for ecological quality; and groundwater salinity and depth and soil pH for health quality. (3) Agricultural land in Huanghua city is divided into five types of remediation, including 30,277.34 hm2 for high efficiency utilization area, 10,576.54 hm2 for production quality cultivation area, 34,387.86 hm2 for health quality cultivation area, and 56,311.22 hm2 for comprehensive consolidation and restoration area; special remediation measures are proposed for different types of zones. The work improves the multi-objective quality evaluation index system for agricultural land and implements differentiated land remediation strategies by identifying obstacle factors through zoning. It provides methodological ideas to improve the efficiency of land remediation and utilization. [ABSTRACT FROM AUTHOR]

By taking 31 provinces (municipalities/autonomous regions) in Mainland China as the object of research, and using the data on urban population and built-up area of each region from 2005 to 2019, this paper measures the dispersion coefficient of population urbanization and land urbanization in each region through models and visually expresses the level and type of imbalance between them to reveal the temporal and spatial characteristics of imbalance. The results of the research show that since China's state-owned land was sold through bidding, auction, and listing, the overall urbanization of the population and land development have become unbalanced. There is obvious regional and category difference in imbalance between population urbanization and land urbanization. The degree of imbalance increases from the central, eastern, northeastern to western regions. The remaining 29 regions are generally lagging in population urbanization except for Beijing and Hebei province. This imbalance is mainly caused by China's dual household registration system, dual land system and the asymmetrical tax distribution system between financial rights and administrative rights. [ABSTRACT FROM AUTHOR]

Since 2020, COVID-19 has repeatedly arisen around the world, which has had a significant impact on the global economy and culture. The prediction of the COVID-19 epidemic will help to deal with the current epidemic and similar risks that may arise in the future. So, this paper proposes a hybrid prediction model based on particle swarm optimization variational mode decomposition (PSO-VMD), Long Short-Term Memory Network (LSTM) and AdaBoost algorithm. To address the issue of determining the optimal number of modes K and the penalty factor (α) in the variational mode decomposition (VMD), an adaptive value for particle swarm optimization (PSO) is proposed. Specifically, the weighted average sample entropy of the relevant coefficients is utilized to determine the adaptive value. First, the epidemic data are decomposed into multiple modal components, known as intrinsic mode functions (IMFs), using PSO-VMD. These components, along with policy-based factors, are integrated to form a multivariate forecast dataset. Next, each IMF is predicted using AdaBoost-LSTM. Finally, the prediction results of all the IMF components are reconstructed to obtain the final prediction result. Our proposed method is validated by the cumulative confirmed data of Hubei and Hebei provinces. Specifically, in the case of cumulative confirmation data, the coefficient of determination ( R 2 ) of the mixed model is increased compared to the control model, and the average mean absolute error (MAE) and root mean square error (RMSE) decreased. The experimental results demonstrate that the VMD–AdaBoost–LSTM model achieves the highest prediction accuracy, thereby offering a new approach to COVID-19 epidemic prediction. [ABSTRACT FROM AUTHOR]

The goal of carbon peak and carbon neutralization puts forward higher requirements for the energy and electricity industry development in China. Jing-jin-ji region (short for Beijing, Tianjin and Hebei Provinces) as an important economic growth pole in China, its electric power industry realizing low-carbon transformation can play a good exemplary role nationwide. To clarify the key factors affecting carbon dioxide emission from electric power industry and analyze the relationship between emission and regional economic growth, the paper established decoupling effort model based on LMDI two phases decomposition model and Tapio decoupling index. Firstly, we collected the data of Jing-jin-ji region from 2000 to 2017 and conducted factors decomposition. The results show that: among the ten key factors affecting electric power industry CO2 emission, power generation and consumption ratio, fossil energy consumption coefficient and industrial structure have the most significant effect on CO2 emission reduction, with contribution rates of − 23.27, − 16.50 and − 11.91%, respectively. Per capita GDP and total population are the main positive driving factors, with contribution rates of 132.20% and 23.38%, respectively. Then from the perspective of decoupling relationship, the electric power industry in Jing-jin-ji region has entered a weak decoupling state since the Eleventh Five Year Plan with the decoupling index declined from 0.85 in 2004 to 0.38 in 2017. Excluding the influence of economic development, there are six driving factors to realize the weak decoupling, including (1) Power generation and consumption ratio effect, (2) Industrial structure effect, (3) Industrial power consumption intensity effect, (4) Fossil energy consumption coefficient, (5) Thermal power proportion effect and (6) Fossil energy power generation structure effect, in which the decoupling degree decreases in turn. The total population effect, transmission and distribution loss effect and resident power consumption intensity effect have not achieved decoupling status. At last, based on the model calculation results, we put forward suggestions to promote the low-carbon development of power industry in Jing-jin-ji region, for example, accelerate industrial structure upgrading and the adjustment of power generation structure; Strengthen electricity demand side management; Promote the construction of ultra-high voltage and smart grid as a whole. [ABSTRACT FROM AUTHOR]

Energy security has become the focus of common attention of all countries in the world. It is an effective way to promote the transformation of energy consumption structure from fossil energy consumption to renewable energy consumption at present. Based on the current development status of China, this paper mainly studies the spatial evolution process of the traditional energy and the renewable energy industry in Hebei province from the perspective of space and time, and analyzes the influencing factors in this process. The results are as follows: (1) Moran's I of the traditional energy industry increased from 0.254515 in 2005 to 0.289301 in 2021. Moran's I of the renewable energy industry increased from 0.31409 in 2005 to 0.426467 in 2021. This indicates the energy transition in Hebei is progressing. It is worth noting that the wind and solar energy industries are both higher than the national average; (2) the spatial diffusion effect of the energy industry in Hebei province becomes more and more significant with the transformation of regional energy industry, forming a spatial distribution trend of southwest to northeast axial diffusion; (3) from 2005 to 2018, the number of green productivity factors affecting the development of both traditional and renewable energy industries increased from 2 to 6. The transformation process of the energy industry in Hebei province is influenced by different factors in different temporal stages. [ABSTRACT FROM AUTHOR]

Featured Application: This work was supported by the National Nature Science Foundation of China (No. 52075468; No. 52005428); General project of Natural Science Foundation of Hebei Province (No. E2020203052; No. 2021203099); Youth Fund Project of a scientific research project of Hebei University (No. QN202013). Magnetic liquid double suspension bearing (MLDSB) is composed of an electromagnetic system and hydrostatic system and its bearing capacity and stiffness can be greatly improved. It is very suitable for occasions of medium speed, heavy load, and starting frequently. Due to the gyroscopic effect and interference between the supporting system, the space state of the rotor can be affected and the operation stability of the MLDSB can be reduced greatly. Therefore, the coupling features of the multi-degree of freedom (multi-DOF) system are analyzed and a decoupling controller is designed and verified in the paper. Firstly, the paper introduces the structural characteristics, stress forms, and control regulation mechanism. Then, the mathematical transfer function of the multi-DOF supporting system is established and the coupling principle is revealed. The state feedback decoupling controller is designed by means of a state feedback decoupling, and its decoupling effect is analyzed by the Simulink module. Finally, the single-DOF decoupling system is independently controlled by the use of the root locus method. The coupling characteristics between channel x and channel y are tested experimentally, and the decoupling controller is added and its effect tested. The results show that the state feedback decoupling controller can effectively reduce the coupling degree in the multi-DOF system and convert the multi-DOF coupling problem into a single-DOF independent control problem. The coupling effect of channel x and channel y is reduced by using the decoupling controller, with the subsequent displacement characteristic of the rotor increased, and then the operation stability of the MLDSB is improved greatly. This paper can enrich the support system of the MLDSB and provide a theoretical reference for stability control. [ABSTRACT FROM AUTHOR]