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Featured Application: The LM-IEKF algorithm proposed in this paper can effectively estimate the state of charge of a lithium-ion battery, and it is suitable for the estimation of an electric vehicle. The error covariance matrix in the IKEF process is modified by the LM algorithm, and it can still maintain a good convergence speed and estimation accuracy in the face of severe current changes. With the application of lithium batteries more and more widely, in order to accurately estimate the state of charge (SoC) of the battery, this paper uses the iterated extended Kalman filter (IEKF) algorithm to estimate the SoC. The Levenberg–Marquardt (LM) method is used to optimize the error covariance matrix of IKEF. Based on the hybrid pulse power characteristics experiment, a second-order Thevenin model with variable parameters is established on the MATLAB platform. The experimental results show that the proposed model is effective under the constant current discharge condition, the Federal Urban Driving Schedule (FUDS) condition, and the Beijing dynamic stress test (BJDST) condition. The results show that the simulation error of the improved LM-IEKF algorithm is less than 2% under different working conditions, which is lower than that of the IKEF algorithm. The improved algorithm has a fast convergence speed to the true value, and it has a good estimation accuracy in the case of large changes in external input current. Additionally, the fluctuation of error is relatively stable, which proves the reliability of the algorithm. [ABSTRACT FROM AUTHOR]

In response to the international appeal of developing low-carbon economy and realizing carbon peaking and neutrality goals, China has been exploring the construction of the carbon emissions trading market for years. Without the guidance of advanced technology, there would not be a low-carbon economy in the first place. Based on panel data of 30 provinces and cities in China from 2005 to 2020, this paper takes Beijing—which is the first pilot city in China—as the only treated group and uses the Synthetic Control Method to study the impact of the pilot policy on low-carbon technology innovation. The results show that, firstly, the number of low-carbon technology patents in Beijing increases significantly after the implementation of the pilot policy, proving a positive influence on technology innovation. Secondly, the policy effect has a certain time lag and is sensitive to the shock from both domestic and foreign carbon market, but this effect is gradually stable over time. This paper confirms that technological innovation is the key means of promoting the development of the low-carbon economy and calls on various carbon trading markets to pay attention to the internal mechanism of promoting low-carbon technology innovation to stimulate the vitality of market entities. [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]

Accurate prediction of air quality is crucial for assessing the state of the atmospheric environment, especially considering the nonlinearity, volatility, and abrupt changes in air quality data. This paper introduces an air quality index (AQI) prediction model based on the Dung Beetle Algorithm (DBO) aimed at overcoming limitations in traditional prediction models, such as inadequate access to data features, challenges in parameter setting, and accuracy constraints. The proposed model optimizes the parameters of Variational Mode Decomposition (VMD) and integrates the Informer adaptive sequential prediction model with the Convolutional Neural Network-Long Short Term Memory (CNN-LSTM). Initially, the correlation coefficient method is utilized to identify key impact features from multivariate weather and meteorological data. Subsequently, penalty factors and the number of variational modes in the VMD are optimized using DBO. The optimized parameters are utilized to develop a variationally constrained model to decompose the air quality sequence. The data are categorized based on approximate entropy, and high-frequency data are fed into the Informer model, while low-frequency data are fed into the CNN-LSTM model. The predicted values of the subsystems are then combined and reconstructed to obtain the AQI prediction results. Evaluation using actual monitoring data from Beijing demonstrates that the proposed coupling prediction model of the air quality index in this paper is superior to other parameter optimization models. The Mean Absolute Error (MAE) decreases by 13.59%, the Root-Mean-Square Error (RMSE) decreases by 7.04%, and the R-square (R2) increases by 1.39%. This model surpasses 11 other models in terms of lower error rates and enhances prediction accuracy. Compared with the mainstream swarm intelligence optimization algorithm, DBO, as an optimization algorithm, demonstrates higher computational efficiency and is closer to the actual value. The proposed coupling model provides a new method for air quality index prediction. [ABSTRACT FROM AUTHOR]

In the knowledge economy era, innovation has become a key emphasis for urban competitions. This paper constructs a theoretical research framework that integrates the basic understandings, influencing factors and ensuing results of intercity innovative competition relations. On the basis of data from the general programs of the National Natural Science Foundation of China from 2005 to 2019, this paper constructs intercity innovative competition relations in China, analyses their spatial distribution and quantitative characteristics, and quantitatively investigates the impact of urban innovation capacity and multidimensional proximity (e.g., geographical proximity, institutional proximity and cognitive proximity) on intercity innovative competition relations through a negative binomial model. The study obtained the following findings: (1) In terms of the overall intercity innovative competition relations, the intensity of China's intercity innovative competition relations gradually increased from 2005 to 2019, with a spatial clustering towards cities with high administrative ranks (e.g., municipalities directly under the central government, sub-provincial cities and provincial capitals); Beijing is always at the centre of innovative competition relations, but its standing has slightly slipped in recent years. (2) From the perspective of disciplines, cities can become benchmarks in particular fields of innovative competitions by competing according to their disciplinary strengths; intercity innovative competition relations in China vary across various academic disciplines. (3) In terms of influencing factors, urban innovation capacity has significant positive effects on intercity innovative competition relations; geographical proximity, institutional proximity and cognitive proximity all have significant positive effects on innovative competition relations; and interactions occur between multidimensional proximities, including a complementary effect between geographical proximity and institutional proximity, a substitutive effect between cognitive proximity and geographical proximity, and a substitutive effect between cognitive proximity and institutional proximity. [ABSTRACT FROM AUTHOR]

This paper proposes a ResGA-Net algorithm for cloud top height (CTH) retrieval using FY-4A satellite data. The algorithm utilizes genetic algorithms for data selection and employs a residual module-based neural network for modeling. It takes the spectral channel data from the FY-4A satellite as input features and uses CTH extracted from ground-based millimeter-wave cloud radar reflectivity as the target. By combining the large observation scale of the FY-4A satellite and the high accuracy of ground-based cloud radar observations, the model can generate satellite CTH products with higher precision. To validate the effectiveness of the algorithm, experiments were conducted using data from the Beijing area spanning from January 2020 to January 2022. The experimental results show that the metrics of the proposed ResGA-Net outperform those of various contrastive algorithms, and compared to the original FY-4A CTH product, the RMSE and MAE have decreased by 37.89% and 34.77%, while the PCC and SRCC have increased by 11.17% and 9.47%, respectively, demonstrating the superiority of the proposed method presented in this paper. [ABSTRACT FROM AUTHOR]

Industrial heritage is regarded as an important stock of spatial resources in cities, which highlights its utilization value for urban regeneration in high-density urban areas. With the dramatic increase in the number of industrial heritage reuse projects, how to scientifically evaluate the satisfaction with their spatial reuse is a key part of the solution for the mutual balance between heritage preservation and urban renewal. This paper takes eight industrial heritage conversion and utilization projects in the high-density core area of Beijing's central city as examples; establishes an evaluation system for the satisfaction with the spatial reuse through six dimensions, namely, functional replacement, transportation accessibility, carrying capacity, public space, boundary form, and recognition of value; and uses the IPA method to evaluate the cases. This method is used to determine the degree of user satisfaction with the spatial reuse of industrial heritage in the core area of Beijing's central city and to summarize the advantages and problems of its reuse. The results of this study reveal a trend toward the "community-oriented" re-generation of industrial heritage in the core area of Beijing's central city, and this paper proposes recommendations for adaptive use to support high-quality urban regeneration work. [ABSTRACT FROM AUTHOR]

Against the backdrop of increasingly severe global climate change, the risk of rainstorm-induced waterlogging has become the primary threat to the safety of historic and cultural districts worldwide. This paper focuses on the historic and cultural districts of Beijing, China, and explores techniques and methods for identifying extreme rainstorm warnings in cultural heritage areas. Refined warning and forecasting have become important non-engineering measures to enhance these districts' waterlogging prevention control and emergency management capabilities. This paper constructs a rainstorm-induced waterlogging risk warning model tailored for Beijing's historical and cultural districts. This model system encompasses three sets of models: a building waterlogging early-warning model, a road waterlogging early-warning model, and a public evacuation early-warning model. During the construction of the model, the core concepts and determination methods of "1 h rainfall intensity water logging index" and "the waterlogging risk index in historical and cultural districts" were proposed. The construction and application of the three models take into full account the correlation between rainfall intensity and rainwater accumulation, while incorporating the characteristics of flood resilience in buildings, roads, and the society in districts. This allows for a precise grading of warning levels, leading to the formulation of corresponding warning response measures. Empirical tests have shown that the construction method proposed in this paper is reliable. The innovative results not only provide a new perspective and method for the early-warning of rainstorm-induced waterlogging, but also offer scientific support for emergency planning and response in historical and cultural districts. [ABSTRACT FROM AUTHOR]

The urban underlying surface may affect the thunderstorm process. However, current research on this phenomenon is still in its infancy. This paper aimed to analyze the influence of the urban underlying surface on the evolution of thunderstorm organization through ground observation and numerical simulation. The results indicated that when the thunderstorm system with strong synoptic conditions passed through the built-up area of Beijing, it exhibited obvious bifurcation and detour. The dynamic field of near-surface cold pools could serve as diagnostic indicators for understanding how the urban underlying surface affects the thunderstorm process. The large-scale compact-rise clusters in the city center could alter the movement direction and path of the cold pool outflow, thereby influencing the thunderstorm organization process. In addition to the spatial configuration of the building complex, the city size might also be an important factor influencing the thunderstorm process. This study might provide a fundamental foundation and technical support for predicting and assessing urban thunderstorm disasters. [ABSTRACT FROM AUTHOR]

The phenomenon of algal bloom seriously affects the function of the aquatic ecosystems, damages the landscape of urban river and lakes, and threatens the safety of water use. The introduction of a multi-attribute decision-making method avoids the shortcomings of traditional algal bloom management that relies on manual experience. However, the weight-calculation part of this method still receives the artificial influence of human factors, which reduces the accuracy and scientific rigor of the decision. This paper presents a group decision-making method based on information self-learning which makes decision weights automatically clustered and assigned. A general framework of decision-making management is constructed for the algal bloom management process. In the decision-making process, an improved density-based clustering algorithm is used to automatically cluster and rank the decision data in the form of the three-parameter interval number, and ultimately obtain the optimal management method that meets the management objectives. Finally, the method was applied at the monitoring station of Sanjiadian Reservoir in Beijing, China. Based on the treatment objectives and water quality monitoring data of the station, relevant experts were invited to evaluate the management solutions, and the information self-organizing algorithm of this paper was used to automatically rank the decision-making methods, and finally obtain the most suitable management method for the station. Comparison with the water quality data and treatment inputs after the previous man-made selection of treatment options, and discussion among experts, show that the decision-making method is feasible and effective, and contributes to the sustainable treatment of algal blooms. [ABSTRACT FROM AUTHOR]

A solar heat pump based on the photovoltaic photothermal (PV/T) module is a new technology that can improve the photovoltaic efficiency and recovery of waste heat in photovoltaic conversion. The comprehensive efficiency of a system can thus be greatly improved. At present, there is little research on the simulation of a solar heat pump based on the Simulink 2018 software. In this paper, PV/T modules are modeled and simulated using the Simulink software based on the typical meteorological parameters in Beijing city during summer and winter conditions. Considering the system characteristics of a simultaneous operation, the models of all components such as the compressor, condenser, evaporator, expansion valve, and heat storage tanks contained in a system are established based on the system's working principle, energy conservation equations, and some empirical formulas and then simulated. As PV/T modules are the key influencing factor for system performance, the model and simulation process are introduced in detail in this paper. The results show that the surface temperature of PV/T modules under different operating conditions are all significantly lower than that of ordinary photovoltaic panels. The average temperature of PV/T modules is only 15.2 °C, which is 20.2 °C lower than that of ordinary panels under summer conditions, and the average temperature of PV/T modules is only 0.5 °C, 17.8 °C lower than that of ordinary panels under winter conditions. The average photoelectric efficiency can be improved by 15.4% and 8.9%. And, the temperature change amplitude of PV/T modules is lower, which weakens the temperature fluctuation of the modules. The photovoltaic efficiency is therefore further increased. As a result, the power generation and photovoltaic efficiency are both improved significantly. [ABSTRACT FROM AUTHOR]

Addressing inherent limitations in distinguishing metrics relying solely on Euclidean distance, especially within the context of geo-indistinguishability (Geo-I) as a protection mechanism for location-based service (LBS) privacy, this paper introduces an innovative and comprehensive metric. Our proposed metric not only incorporates geographical information but also integrates semantic, temporal, and query data, serving as a powerful tool to foster semantic diversity, ensure high servifice similarity, and promote spatial dispersion. We extensively evaluate our technique by constructing a comprehensive metric for Dongcheng District, Beijing, using road network data obtained through the OSMNX package and semantic and temporal information acquired through Gaode Map. This holistic approach proves highly effective in mitigating adversarial attacks based on background knowledge. Compared with existing methods, our proposed protection mechanism showcases a minimum 50% reduction in service quality and an increase of at least 0.3 times in adversarial attack error using a real-world dataset from Geolife. The simulation results underscore the efficacy of our protection mechanism in significantly enhancing user privacy compared to existing methodologies in the LBS location privacy-protection framework. This adjustment more fully reflects the authors' preference while maintaining clarity about the role of Geo-I as a protection mechanism within the broader framework of LBS location privacy protection. [ABSTRACT FROM AUTHOR]

By precisely controlling the distance between two train sets, virtual coupling (VC) enables flexible coupling and decoupling in urban rail transit. However, relying on train-to-train communication for obtaining the train distance can pose a safety risk in case of communication malfunctions. In this paper, a distance-estimation framework based on monocular vision is proposed. First, key structure features of the target train are extracted by an object-detection neural network, whose strategies include an additional detection head in the feature pyramid, labeling of object neighbor areas, and semantic filtering, which are utilized to improve the detection performance for small objects. Then, an optimization process based on multiple key structure features is implemented to estimate the distance between the two train sets in VC. For the validation and evaluation of the proposed framework, experiments were implemented on Beijing Subway Line 11. The results show that for train sets with distances between 20 m and 100 m, the proposed framework can achieve a distance estimation with an absolute error that is lower than 1 m and a relative error that is lower than 1.5%, which can be a reliable backup for communication-based VC operations. [ABSTRACT FROM AUTHOR]

Recent research has played a pivotal role in advancing our understanding of cloisonné enamel production in China during the 19th and 20th centuries. However, Christian workshops, whether operating under missionary subcontracting or owned by the Catholic Church, have yet to be accurately identified and contextualized. This article delves into three significant contexts. Firstly, it identifies and contextualizes the Christian connections and interactions of the Decheng private cloisonné workshop, involving the French Lazarist Bishop Alphonse Favier, in Beijing. Secondly, it identifies the cloisonné workshop stablished by the Lazarists in the Beitang complex in Beijing and elucidates the role it played. Finally, this paper presents new evidence concerning cloisonné Christian objects crafted by the Tushanwan Jesuit workshop in Shanghai. Some of the primary works of these three workshops are identified for the first time. Additionally, this paper shows that certain cloisonné crosses, some of them thought to be originally Japanese, including those referred to as Namban, were, in fact, crafted in Beijing during the 1920s. These preliminary results will contribute to placing Chinese Christian cloisonné within the history of Chinese Art and its interactions at a global level in the context of evangelization in China, the production of the so-called export art, and the processes of indigenization carried out by the Lazarists and the Jesuits. [ABSTRACT FROM AUTHOR]

Given the complex interplay between economic and cultural–historical factors, this paper explores scene perception and its mechanism in individual and collective cognition of historical commercial streets. Based on a perception model constructed from scene theory, the study utilizes user scene experience feedback from Beijing Road, a commercial pedestrian street in Guangzhou. It conducts a systematic assessment using hierarchical analysis (AHP) across three dimensions: authenticity, theatricality, and legitimacy. The findings reveal the following: (1) according to visitors, traditional cuisine, cultural and creative arts, and Lingnan's intangible cultural heritage received low ratings; (2) historical relics and traditional cuisine are dominant factors, highlighting public attention to cultural heritage, but the role of historical–cultural characteristics and festival activities is relatively marginalized; (3) cultural–historical relics and traditional cuisine are the leading factors that contribute to an authentic experience, while historical context and festival activities constitute secondary factors; (4) cultural landscapes and arts are central to theatrical experiences, with modern visual elements playing a lesser role; (5) diversified commercial formats and public services are the core factors influencing legitimacy experience, reflecting the role of market diversity and policy orientation in building consumer trust. The design of historical and cultural streets should prioritize the preferences of those experiencing them to promote cultural identity and historical continuity. Additionally, the synergy between commercial diversity and policy orientation should be strategically emphasized to form a business ecosystem supporting sustainable development. Future commercial street renewals should focus on the key role of visual narrative in shaping brand culture. This paper offers insights into the dynamic process of constructing scene experience from perspectives of spatial materialization and emotional empowerment to cultural identity, providing references for strategies in historical place renewal. [ABSTRACT FROM AUTHOR]

China is in the transition period of urbanization, and the imbalance of land use generated during the original rapid development of megacities still exists, resulting in the preservation of a large number of urban villages in the peripheral areas of cities. Unlike formal housing, these villages are heavily influenced by the confrontation and interweaving between top-down policies of local governments and bottom-up spontaneous construction by local villagers, resulting in a diverse and complex status quo. At the same time, self-built housing in urban villages has become a gathering place for a large number of low-income migrants due to its relatively low rental prices. In terms of the research of urban villages on the current situation of housing, the real needs of users and housing performance are mostly subjective judgments and conclusions. Therefore, the entry point of this paper is the leased space and the leasers, taking Laojuntang Village in Chaoyang District of Beijing as the research object and analyzing its current problems and the real needs of users. This paper adopts an integrated approach of fuzzy Kano model evaluation and building performance simulation. After analyzing the data and discussing the influencing factors, this paper identifies the specific problems and user needs that exist in leased spaces in Laojuntang Village: (1) The architectural performance of leased space is a Must-be Quality, which is the bottom-line requirement and must be improved. (2) The quality of the basic facilities and equipment of the leased space is mostly a One-dimensional Quality, Attractive Quality, and the degree of importance is lower than that of the building performance. (3) The external activity facilities of the leased space are mostly undifferentiated needs, for which the local users are not particularly prominent. (4) The scale and plot ratio of local housing is relatively high, and users are dissatisfied and complaining, which falls under the category of Reverse Quality. [ABSTRACT FROM AUTHOR]

Short-term origin–destination (termed as OD) prediction is crucial to improve the operation of urban rail transit (termed as URT). The latest research results show that deep learning can effectively improve the performance of short-term OD prediction and meet the real-time requirements. However, many advanced neural network design ideas have not been fully applied in the field of short-term OD prediction in URT. In this paper, a novel parallel interactive attention network (termed as PIANet) for short-term OD prediction in URT is proposed to further improve the short-term OD prediction accuracy. In the proposed PIANet, a novel omnidirectional attention module (termed as OAM) is proposed to improve the representational power of the network by calculating the feature weights in the channel–spatial dimension. Moreover, a simple yet effective feature interaction is proposed to improve the feature utilization. Based on the two real-world datasets from the Beijing subway, the comparative experiments demonstrate that the proposed PIANet outperforms the state-of-the-art deep learning methods for short-term OD prediction in URT, and the ablation studies demonstrate that the proposed OAMs and feature interaction play an important role in improving the short-term OD prediction accuracy. [ABSTRACT FROM AUTHOR]

The bogie frame, as one of the most critical load-bearing structures of the Electric Multiple Unit (EMU), is responsible for bearing and transmitting various loads from the car body, wheelsets, and its own installation components. With the increasing operating speed of high-speed EMUs, especially when the design and operational speeds exceed 400 km/h, the applicability of current international standards is uncertain. The load spectrum serves as the foundation for structural reliability design and fatigue evaluation. In this paper, the measured loads of the bogie frame of a CR400AF high-speed train on the Beijing–Shanghai high-speed railway are obtained, and the time-domain characteristic of the measured loads is analyzed under different operating conditions. Then, through the Weibull distribution of three parameters, the Weibull parameters at the 450 km/h speed level are fitted, and the maximum load and cumulative frequency under the speed level are derived. Finally, the load spectrum of the bogie frame at the 450 km/h speed level is established, which provides a more realistic load condition for accurately evaluating the fatigue strength of bogie frames at higher speed levels. [ABSTRACT FROM AUTHOR]

Community green spaces (CGSs) constitute a crucial element of urban land use, playing a pivotal role in maintaining the stability of urban ecosystems and enhancing the overall quality of the urban environment. Through the post-occupancy evaluation (POE) of green spaces, we can gain insights into residents' actual needs and usage habits, providing scientific evidence for the planning, design, and management of green spaces. This ensures that CGSs better meet residents' needs and improve their quality of life. The POE of CGSs relies heavily on high-precision data support. However, the current POE system for CGSs faces challenges, such as limited data collection methods, incomplete indicator systems, and excessive manual involvement. To address these limitations in data collection, this study proposes a comprehensive, dynamically monitored, objective, and sustainable POE system for CGSs. This system incorporates a multi-dimensional perception system that integrates the Internet of Things (IoT) and sensors to collect data from various sources. It establishes an evaluation framework from the perspectives of policy guidance and usage needs for CGSs, utilizing neural network systems and artificial intelligence techniques to compute the evaluation results. Using the Jiayuan Sanli Community in Beijing as a case study, this paper demonstrates the feasibility of the proposed system. A comparison between the POE results obtained using the multi-dimensional perception technique and those obtained manually reveals an 87% improvement in the accuracy of the evaluation results based on the multi-dimensional perception system. This system bridges the gap between planning perspectives and user experiences, contributing significantly to future urban land planning and land policy formulation. [ABSTRACT FROM AUTHOR]

Rapid urbanization has made mountain development an important means to alleviate the shortages of construction land on plains, which has significantly affected regional ecosystem services. In-depth research on the impact of urbanization on ecosystem services under altitude gradients is of great significance to clarify the relationship between the two. Based on data from 2000, 2010 and 2020, the urbanization level and ecosystem services of the study area were evaluated. The spatial correlation of ecosystem services was analyzed by Moran's I. A spatial Durbin model (SDM) was selected to fit the regression. The results show that (1) from 2000 to 2020, the ecosystem services in the study area displayed obvious regional characteristics and aggregation characteristics; (2) in plain areas, the indirect effects of economic, population and land urbanization have a greater negative impact, and compared with shallow mountain areas, deep mountain areas are more negatively affected by economic urbanization and land urbanization; and (3) the significant difference in regression results reflects the rationality of using the spatial Durbin model, as in this paper, and proves the scientific nature of regional coordinated development. The research results provide a reference for the future coordinated development of regional economies and environments. [ABSTRACT FROM AUTHOR]

Analyzing the spatio-temporal relationship between socio-economics and land-use structure at the micro-scale is crucial for effective spatial governance in large cities. This paper focuses on Beijing, utilizing long time-series remote sensing images and multi-source data spanning 30 years. We employ spatio-temporal clustering based on kilometer grid cells and a community-scale multi-factor aggregation method to categorize the linkages and spatio-temporal matching of population, GDP, land development, and ecological protection at the community level in a problem-oriented approach. Results indicate significant changes in Beijing's population, GDP, and land use, with a 11.53% increase in land development intensity. We identify significant temporal and spatial disparities between population–GDP dynamics, population–land development trends, and GDP–land development patterns, underscoring the multifaceted challenges inherent in urban governance. Areas characterized by lagging population concentration, sluggish economic growth, rampant land development, and ecological fragility collectively encapsulate notable portions of Beijing's expansive urban terrain. Mismatches pose governance risks, with medium to high-risk communities comprising 18.08% of community units and high-risk types representing 4.27% in Beijing. These discrepancies pose formidable governance risks, with communities ranging from moderate to high-risk categories, necessitating tailored interventions to address their unique challenges. This systematic exploration of comprehensive governance issues within mega-cities promises to furnish decision-makers with invaluable insights, facilitating nuanced and strategic urban governance approaches tailored to the intricacies of urban dynamics and challenges. [ABSTRACT FROM AUTHOR]

China's policies about reducing carbon emissions mainly focus on saving energy and reducing pollutant emissions. However, the carbon emissions of the logistics industry remain high. Thus, logistics companies should not only reduce distribution costs, but also consider the impact of carbon emissions when planning distribution routes. This paper studies the supermarket delivery distribution route planning problem considering carbon emissions. Aiming at the lowest economic operating cost composed of fixed cost, driving cost, and carbon emission cost, we propose a grey wolf optimized genetic algorithm to generate delivery route plans, where the social rank and hunting behavior of the grey wolf optimization algorithm are integrated into the selection operation of the genetic algorithm. Finally, a real case of a large third-party logistics enterprise in Beijing is studied. The case study results verify the effectiveness and applicability of the model and algorithm. [ABSTRACT FROM AUTHOR]

Ultraviolet radiation (UV) has strong chemical and biological effects on human health and ecosystems, and it plays an important role in the atmospheric environment by affecting photochemical processes, etc. Clouds and aerosols are the main factors affecting UV radiation and analyzing the quantitative impact of them on UV radiation is of great significance. Using the observation data of UV radiation in Beijing from 2005 to 2020, as well as the data of aerosol optical depth (AOD), single scattering albedo (SSA), and other related parameters, this paper simulated the surface UV radiation in two scenarios of cloudless without aerosol and cloudless with aerosol based on the TUV (Tropospheric Ultraviolet-Visible model), and quantitatively evaluated the attenuation of UV radiation by aerosol and cloud in the Beijing area. The results show that UV radiation is more sensitive to changes in AOD. Fixing the SSA value to 0.9, when the AOD increases from 0.2 to 1.0, the UV radiation decreases from 21.16 W/m2 to 12.64 W/m2 at 12:00; when AOD is maintained at 0.64, the SSA increases from 0.7 to 0.95, and the UV radiation increases from 14.55 W/m2 to 19.91 W/m2. The average annual attenuation rates of ultraviolet radiation by aerosols and clouds from 2005 to 2020 are 30.64% and 40.22%, respectively; the monthly averaged attenuation rates are 30.48% and 42.04%, respectively; and the daily averaged attenuation rates are 31.02% and 50.45%, respectively. [ABSTRACT FROM AUTHOR]

To predict and explore the return period wind speed distribution in Beijing urban area, based on the short-term measured wind speed record, the measured independent storm peak samples are extracted and the Monte–Carlo numerical simulation method is used to randomly generate pseudo-independent storm peak samples with the same distribution as the independent storm peak samples. In addition, the appropriate threshold is used to select and extract the over-threshold independent storm peak samples from the measured samples. And, then, the return period wind speed of the whole wind direction is predicted. Further, the traditional Cook method is used to predict and analyze the return period wind speed of each wind direction according to the measured wind speed data. The results show that the return period wind speed prediction results of the whole wind direction corresponding to the simulated pseudo samples and the measured over-threshold samples are basically close to each other, and the maximum relative deviation is less than 7%. The mean relative deviation of the return period wind speed prediction results is about 10.6% between each wind direction and the whole wind direction, and the mean relative deviation is about 9.4% between the RPWS prediction result of each wind direction and the design value of the code. In addition, the return period wind speed prediction values of the west by southwest, northwest and north by northeast wind directions exceed the design value of the code, while the predicted values of the other wind directions are within the envelope range of the design value of the code. Finally, the research content of this paper can provide some reference for the wind resistance design analysis of building structures in Beijing area. [ABSTRACT FROM AUTHOR]

The profound impacts of severe air pollution on human health, ecological balance, and economic stability are undeniable. Precise air quality forecasting stands as a crucial necessity, enabling governmental bodies and vulnerable communities to proactively take essential measures to reduce exposure to detrimental pollutants. Previous research has primarily focused on predicting air quality using only time-series data. However, the importance of remote-sensing image data has received limited attention. This paper proposes a new multi-modal deep-learning model, Res-GCN, which integrates high spatial resolution remote-sensing images and time-series air quality data from multiple stations to forecast future air quality. Res-GCN employs two deep-learning networks, one utilizing the residual network to extract hidden visual information from remote-sensing images, and another using a dynamic spatio-temporal graph convolution network to capture spatio-temporal information from time-series data. By extracting features from two different modalities, improved predictive performance can be achieved. To demonstrate the effectiveness of the proposed model, experiments were conducted on two real-world datasets. The results show that the Res-GCN model effectively extracts multi-modal features, significantly enhancing the accuracy of multi-step predictions. Compared to the best-performing baseline model, the multi-step prediction's mean absolute error, root mean square error, and mean absolute percentage error increased by approximately 6%, 7%, and 7%, respectively. [ABSTRACT FROM AUTHOR]

Taking the high and large space of the University of Science and Technology Beijing Gymnasium as this research object, this paper analyzes the influence of different window positions, window-to-wall ratio (WWR), solar heat gain coefficient (SHGC), heat transfer coefficient (K), and visible light transmittance (VT) on the total indoor energy consumption in winter and summer and obtains the relationship between the daylight factor and VT formed when the window is opened per unit area. Through energy consumption simulation, the variation law and calculation formula for indoor total energy consumption are obtained. The results show that the SHGC and K of the exterior window have a significant influence on the total energy consumption. By using the energy consumption simulation of different types of exterior windows, it is concluded that the SHGC of the south-facing window is negatively correlated with the variation of air conditioning energy consumption per unit area Δe1,w, while the others are positively correlated. Moreover, the SHGC and K of the skylight have the most significant influence on the Δe1,w. The total energy consumption decreases and then increases with the increase in the window area, and there is a lowest point, so the right side of the lowest point is less than or equal to 105% of the lowest total energy consumption as a reasonable window area zone. Finally, a progressive optimization method for weighing daylighting and energy consumption in university gymnasiums in Beijing is proposed. [ABSTRACT FROM AUTHOR]

Optimizing travel routes in urban transportation networks is essential for enhancing traffic efficiency in major cities. This study focuses on optimizing the combined subway and taxi travel routes from Beijing Union University to Beijing South Railway Station, a critical route for students and staff in Beijing. To address this, we propose three genetic algorithms: the Standard Genetic Algorithm (SGA), the Multipoint Crossover and Elitist Selection Genetic Algorithm (MPEGA), and the Improved Dynamic Crossover and Mutation Rate Genetic Algorithm (IDCMGA). Experimental results indicate that MPEGA reduces the mean travel cost by 15.21%, the variance by 81.72%, and the standard deviation by 57.25% compared to SGA. Additionally, IDCMGA reduces the average by 1.76%, the variance by 63.16%, and the standard deviation by 39.30% compared to MPEGA. The improved IDCMGA algorithm demonstrates significant advantages over the other two algorithms in terms of global optimization capability, convergence speed, and stability, and is more adept at adapting to new traffic conditions to identify the optimal route. Optimizing this route not only reduces commuting time and costs but also alleviates traffic congestion, thereby enhancing the overall efficiency of the urban transportation system. [ABSTRACT FROM AUTHOR]

Based on the mean sea level pressure field and 10-meter wind field across eastern China, weather patterns were classified using principal component analysis in the T-model (T-PCA), and four weather conditions were identified. Weather conditions and meteorological factors affecting the winter PM2.5 concentration in the Beijing–Tianjin–Hebei (BTH) region and the Yangtze River Delta (YRD) were also analyzed. The results showed that there were significant differences in the PM2.5 distribution between BTH and the YRD under different weather conditions. The intensity and path of cold air played important roles in regulating the PM2.5 concentration distribution in eastern China. For the BTH region, under type 2 and type 4 conditions, the weather was stable, and heavy pollution frequently occurred; however, under type 1 and type 3 conditions, cold air was active, and the air quality improved. For the YRD, both type 1 and type 4 conditions lead to high PM2.5 concentrations in this region. Type 1 cold air flows southward along the northwestern path and is beneficial for transporting pollutants from BTH to the YRD, causing a high probability of PM2.5 pollution. Conversely, the southward movement of type 3 cold air along the eastern path was beneficial for pollutant diffusion in the YRD. [ABSTRACT FROM AUTHOR]

In recent years, the development of China's megacities has entered the stage of stock renewal. Research and practice concerning old city renewal in cities with a long history, represented by Beijing, has also become a hot spot for researchers and designers in the fields of urban planning, architecture and landscape architecture. As one of the main spatial components of the old city, Beijing's traditional quadrangles are closely related to the spatial perception and emotional experience of citizens and tourists due to their near-human scale characteristics. However, current research focuses more on the evaluation of the historical value of the quadrangles in the early stage of renovation and the specific design and construction methods in the process of renovation, and few studies pay attention to the characteristics of the built environment that promote the emotional experience of users after renovation is completed. Under these circumstances, the study focuses on the emotional attachment between people and the spatial composition and built environment characteristics of the renovated traditional Beijing quadrangles; the avant garde small-scale quadrangle renovation type, which has a wider coverage, more types of user, and pays more attention to people's emotional experience in the renovated space, was selected as the research object. Four typical quadrangle cases were selected for in-depth discussion. Based on the theory of emotional attachment from a multidisciplinary perspective, this study constructed a series of scales that can measure the degree and dimension of emotional attachment between people and the built environment, coupled with local observation and interviews, to obtain multi-dimensional data reflecting attachment, and used SPSS to conduct correlation analysis and exploratory factor analysis to quantitatively explore the effects of different built environment characteristics on attachment. The results show that: (1) As for the material characteristics, the organic integration of traditional and modern materials, structures and colors can effectively enhance people's positive emotional experience and promote the establishment of emotional attachment. The combination of these characteristics and the process of people's three-dimensional spatial experience can further enhance the degree of attachment. In addition, the consistency of materials and technologies, the organic integration of the old and the new, and the carrying capacity of the renovation method for traditional history and culture are the basis for promoting this kind of emotional attachment, which needs to be further explored and considered. (2) As for the non-material characteristics, the diverse, variable, recognizable, unique, and digital spatial function settings that respond to changes in people's need and current developments can significantly promote the establishment of emotional attachment between people and the environment. This further emphasizes the importance of positioning the space in the early stage of the renovation and the operation of the space in the later stage. (3) The results further support the validity and rationality of the series of scales constructed in this study in quantitatively measuring the attachment characteristics between people and the built environment. As a result, the study provides a reference for emotion-oriented design means, research logic and quantitative evaluation methods in the practice and research of urban renovation and renewal in the future. [ABSTRACT FROM AUTHOR]

Studying urban heat islands holds significance for the sustainable development of cities. This comprehensive study analyzed the temporal characteristics of a Surface Urban Heat Island and Canopy Layer Heat Island by employing Moderate-Resolution Imaging Spectroradiometer image data spanning from 2003 to 2020 over Beijing, China. Leveraging the Gaussian capacity model, the geometrical characteristics of the Surface Urban Heat Island and Canopy Layer Heat Island, such as intensity, center, direction, and range, were examined among three different timescales of day, month, and year. Results indicate that the intensities of the Surface Urban Heat Island and Canopy Layer Heat Island tend to have bigger seasonal variations during winter nights and summer daytime. In addition, at night the centers of Surface Urban Heat Island and Canopy Layer Heat Island are mainly concentrated in the range of 116.3°~116.4° E in longitude and 39.90°~39.95° N in latitude, while during the daytime they are more scattered, mainly in the range of 116.2°~116.5° E in longitude and 39.7°~40.0° N in latitude. In the hot season, the center of the heat island moves east to north, while in the cold season it moves west to south. Monthly average ellipse areas of Surface Urban Heat Island and Canopy Layer Heat Island vary more during the day than that at night, the maximum daytime differences were 2662 km2 and 2293 km2, while the maximum nighttime differences were 484 km2 and 265 km2. Overall, the average area is increasing, with the heat island center moving eastward and deflecting towards the northeast-southwest direction. The expansion of urban areas will continue to influence the movement and extent of heat islands. The study offers insights to inform strategies for mitigating urban heat islands. [ABSTRACT FROM AUTHOR]

This study was conducted in response to the Beijing–Tianjin–Hebei mega heavy rainfall event at the end of July 2023, and the severely affected and representative Jiangou village in Beijing was selected as the study area. A variety of methods were used to synthesize and analyze the situation and propose an adaptive response to heavy rainfall and flooding in the village. Based on multi-source remote sensing (RS) data, a comprehensive topographic and hydrological characterization was carried out, and the precipitation before and after the disaster was analyzed; the flood inundation area was extracted using the improved normalized water body index (MNDWI) and OTSU thresholding methods, and the changes of water bodies during the flooding period were quantitatively analyzed; and an improved convolutional-neural-network-based building identification and extraction model was constructed to extract the research distribution of buildings in the area. The sponge city construction (SPCC) method was improved to obtain a method that can mitigate flood risk and adapt to villages by constructing small artificial lakes and local topographic buffers to improve the water storage and drainage capacity of villages. The study shows that these methods are innovative in flood hazard analysis and mitigation but still need further improvement in data accuracy, simulation depth, and system evaluation. [ABSTRACT FROM AUTHOR]

Understanding human movement patterns is crucial for comprehending how a city functions. It is also important for city planners and policymakers to create more efficient plans and policies for urban areas. Traditionally, human movement patterns were analyzed using origin–destination surveys, travel diaries, and other methods. Now, these patterns can be identified from various geospatial big data sources, such as mobile phone data, floating car data, and location-based social media (LBSM) data. These extensive datasets primarily identify individual or collective human movement patterns. However, the impact of spatial scale on the analysis of human movement patterns from these large geospatial data sources has not been sufficiently studied. Changes in spatial scale can significantly affect the results when calculating human movement patterns from these data. In this study, we utilized Weibo datasets for three different cities in China including Beijing, Guangzhou, and Shanghai. We aimed to identify the effect of different spatial scales on individual human movement patterns as calculated from LBSM data. For our analysis, we employed two indicators as follows: an external activity space indicator, the radius of gyration (ROG), and an internal activity space indicator, entropy. These indicators were chosen based on previous studies demonstrating their efficiency in analyzing sparse datasets like LBSM data. Additionally, we used two different ranges of spatial scales—10–100 m and 100–3000 m—to illustrate changes in individual activity space at both fine and coarse spatial scales. Our results indicate that although the ROG values show an overall increasing trend and the entropy values show an overall decreasing trend with the increase in spatial scale size, different local factors influence the ROG and entropy values at both finer and coarser scales. These findings will help to comprehend the dynamics of human movement across different scales. Such insights are invaluable for enhancing overall urban mobility and optimizing transportation systems. [ABSTRACT FROM AUTHOR]

The coordination and balance between agricultural development (AD) and agricultural carbon emissions (ACE) is one of the most important ways to boost the high-quality development of agriculture in the Beijing-Tianjin-Hebei region. Taking 13 prefecture-level cities in the Beijing-Tianjin-Hebei region as the research object, this study uses the comprehensive evaluation method and Tapio decoupling model to analyze the decoupling effect between the AD level and the Agricultural Carbon emissions intensity (ACEI) from 2000 to 2020, based on the assessment of AD status and the calculation of Agricultural Carbon emissions quantities (ACEQ) and ACEI. It found that: (1) From 2000 to 2020, the AD in the Beijing-Tianjin-Hebei region generally showcased a gradual increase trend, and demonstrated a basic feature that AD in the northern areas was higher than that in the southern ones. (2) From 2000 to 2020, the ACEQ in the Beijing-Tianjin-Hebei region showed a trend of first increasing and then decreasing, with a spatial distribution feature that the ACEQ in the southern cities was higher than that in the northern ones. Regarding the source of ACE, the livestock and poultry farming took the highest proportion. ACEI was decreasing year by year, higher in the southern areas than in the northern ones. (3) The main types of decoupling in the Beijing-Tianjin-Hebei region were strong decoupling, recession decoupling, strong negative decoupling, weak negative decoupling, recession coupling, and expansion negative coupling. The decoupling relationship between AD and ACEI were in dynamic change, but the change trend of the decoupling relationship was optimistic. The results of this study deliver certain deployable practice value for improving the sustainability of regional agricultural green development and ecological environmental protection. [ABSTRACT FROM AUTHOR]

There is a consensus toward quantitative environmental design in the information age, but the content and specific practices of its quantification have yet to be systematically studied. To enhance residents' subjective well-being through environmental design, this study includes 847 valid questionnaires across four types of communities and identifies different types of resident groups using correspondence analysis. Then, this study compares the differences in the built environment and subjective well-being using one-way ANOVA and analyzes their impact via regression analysis. The results indicate that residents in old communities have the highest subjective well-being (3.93/5) and built environment assessments, and residents in policy housing communities have the lowest subjective well-being (3.37/5) and built environment assessments. A resident's subjective well-being is more influenced by two types of built environment factors: architecture and landscape and the human–land relationship. Age, education level, public place usage, and the community's overall evaluation also significantly affect residents' subjective well-being. In the information age, quantitative design is the inevitable direction of future design. Through quantitative research, targeted design strategies can be proposed to serve community residents better in their communities and provide references for communities in other developing countries. [ABSTRACT FROM AUTHOR]

Surface solar radiation, as a primary energy source, plays a pivotal role in governing land–atmosphere interactions, thereby influencing radiative, hydrological, and land surface dynamics. Ground-based instrumentation and satellite-based observations represent two fundamental methodologies for acquiring solar radiation information. While ground-based measurements are often limited in availability, high-temporal- and spatial-resolution, gridded satellite-retrieved solar radiation products have been extensively utilized in solar radiation-related studies, despite their inherent uncertainties in accuracy. In this study, we conducted an evaluation of the accuracy of two high-resolution satellite products, namely Himawari-8 (H8) and Moderate Resolution Imaging Spectroradiometer (MODIS), utilizing data from a newly established solar radiation observation system at the Beijing Normal University (BNU) station in Beijing since 2017. The newly acquired measurements facilitated the generation of a firsthand solar radiation dataset comprising three components: Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI), and Diffuse Horizontal Irradiance (DHI). Rigorous quality control procedures were applied to the raw minute-level observation data, including tests for missing data, the determination of possible physical limits, the identification of solar tracker malfunctions, and comparison tests (GHI should be equivalent to the sum of DHI and the vertical component of the DNI). Subsequently, accurate minute-level solar radiation observations were obtained spanning from 1 January 2020 to 22 March 2022. The evaluation of H8 and MODIS satellite products against ground-based GHI observations revealed strong correlations with R-squared (R2) values of 0.89 and 0.81, respectively. However, both satellite products exhibited a tendency to overestimate solar radiation, with H8 overestimating by approximately 21.05% and MODIS products by 7.11%. Additionally, solar zenith angles emerged as a factor influencing the accuracy of satellite products. This dataset serves as crucial support for investigations of surface solar radiation variation mechanisms, future energy utilization prospects, environmental conservation efforts, and related studies in urban areas such as Beijing. [ABSTRACT FROM AUTHOR]

The accurate assessment of tree volume is crucial for developing forest management plans, and this can be achieved using tree volume models. In this study, data on individual trees were collected and calculated, including the diameter at breast height (D), ground diameter (DG), tree height (H), and tree volume (V). A total of 400 Populus × tomentosa Carrière, 400 Populus tomentosa Carr, and 400 Populus × canadensis Moench trees were sampled. Two compatible volume model systems were established using corresponding methods. The models consisted of the following five types: V-DH, V-D, V-DG, H-D, and DG-D. In our calculations, before the horizontal line was the dependent variable, and behind the horizontal line was the independent variable. Variations in preferences for the H-D models were observed among the tree species, with the logistic function proving the most suitable for Populus × tomentosa Carrière, Chapman–Richard function for Populus tomentosa Carr, and power function for Populus × canadensis Moench. Among the three volume models, the V-DH model exhibited a superior performance, with its R2 values ranging from 0.965 to 0.984 and mean estimated error (MPE) values ranging from 1.26% to 1.78%. Following this was the V-D model, with R2 values between 0.9359 and 0.9704 and MPE values between 1.71% and 2.46%. The V-DG model ranked third, with R2 values ranging from 0.8746 to 0.9501 and MPE values ranging from 2.33% to 3.16%. In the H-D model, the R2 and MPE values ranged from 0.4998 to 0.7851 and from 1.31% to 1.45%, respectively. For the DG-D model, the R2 values ranged from 0.9563 to 0.9868 and the MPE values ranged from 0.47% to 0.68%. Comparing both compatible methods, the nonlinear seemingly uncorrelated regression (NSUR) was more effective. The three volume models demonstrated high levels of accuracy and compatibility, providing a reliable scientific foundation for forest management and the formulation of harvesting plans in Beijing, with significant practical implications. [ABSTRACT FROM AUTHOR]

With the advancement of urbanization, land resources are becoming increasingly strained, particularly for urban greening purposes. In this context, a large number of newly cultivated lands dominated by construction waste and backfill soil are emerging in cities. Assessing the soil quality of these newly cultivated lands and achieving their rational utilization accurately and quantitatively has become an urgent issue. In this study, soil samples of five land use types, namely newly cultivated land (NCL, control), adjacent cropland (CL), arbor–shrub mixed forest (ASF), arbor forest (AF), and shrubland (SL) were selected around Beijing, China. ASF, AF, and SL are also newly cultivated lands composed of construction waste and backfill before greening. Based on principal component analysis (PCA), a total data set (TDS) and a minimum data set (MDS) were used to construct the soil quality index (SQI) model. Soil quality indicators covering the physical and chemical characteristics of the soil and their relationships with land use types were studied with the Partial Least Squares Path Model (PLS-PM). The results were summarized as follows: (1) The soil quality index under different land use types in the Beijing plain area were in the order of arbor–shrub mixed forest (ASF) > arbor forest (AF) > shrubland (SL) > cropland (CL) > newly cultivated land (NCL). (2) Soil organic carbon (SOC), soil water content (SWC), maximum water-holding capacity (MWHC), capillary water-holding capacity (CWHC), Pb, and Cd were identified as the MDS. The MDS of the soil quality assessment model showed a linear relationship with the TDS (y = 0.946x + 0.050, R2 = 0.51). (3) Land use types have an indirect impact on soil quality by changing the content of Pb. The chemical indicators' coefficient (0.602) contributed more to the SQI than did the physical indicators' (0.259) and heavy metal elements' (−0.234). In general, afforestation and agricultural production could improve the newly cultivated lands' soil quality, but afforestation is much better than agricultural production. These results will help to evaluate the SQI in the Beijing plain area objectively and accurately, and they have significant implications for soil restoration and management. [ABSTRACT FROM AUTHOR]

This study evaluated the effects of N6-benzyladenine (BAP) seed preconditioning and seedling-derived explants on in vitro plant regeneration potential in soybeans (Glycine max [L.] Merrill.). The findings showed that seed preconditioning with 2.55 mg/L BAP prior to germination significantly influenced seedling establishment and the development of shoots, shoot elongation, and rooting on MS media supplemented with BAP and TDZ, compared to the negative (MS-NC) and positive (MS-NP) controls. The results also showed significant differences based on the genotypes, with Dundee recording 91.0% germination over a minimum of 5 days, compared to 74.2% with Peking, followed by 87.5% and 80.0% overall shoot induction frequency in these genotypes, respectively. Regenerated shoots were successfully elongated on MS medium supplemented with 0.5 mg/L BAP plus 0.6 mg/L GA3 and rooted on hormone-free medium, for 3‒4 weeks, and then hardened in the acclimatization growth room under elevated light levels. Overall, this study revealed that BAP preconditioning of seeds enhances the frequency of bud initiation and shoot proliferation, mostly in whole-seedling and cotyledonary node explants subcultured on MS-E and MS-A media supplemented with BAP in combination with TDZ. [ABSTRACT FROM AUTHOR]

Exploring urban spatial structures through spatial coupling analysis methods is an important method to provide theoretical support for the construction of sustainable urban structures. In order to make up for the neglect of POI species differences in previous studies, information entropy was introduced to calculate POI confusion, and a comprehensive POI index was constructed by combining kernel density and the entropy weight method; impervious surface coverage was extracted based on land cover data. The spatial distribution of the Beijing–Tianjin–Hebei urban agglomeration and some typical cities was analyzed by coupling two types of data using the dual-factor mapping method. The research indicates the following: (1). The spatial distribution of the two sets of data in the Beijing–Tianjin–Hebei region is highly consistent, indicating a state of high spatial coupling; Beijing has the highest proportion of coupling in the same region at the city level (73.39%). (2). The areas with different coupling of the two types of data are mainly distributed in the urban fringe areas transitioning from the city center to the suburbs, as well as in large-scale areas with single functionality such as airports, scenic spots, and ports. This study shows that analysis combining the POI comprehensive index and impervious surface coverage can effectively characterize urban spatial structure characteristics, providing a new perspective for the study of the spatial structure of the Beijing–Tianjin–Hebei urban agglomeration. It is of great significance for a deeper understanding of the laws of urban agglomeration spatial structures and guiding the coordinated development of the Beijing–Tianjin–Hebei urban agglomeration. [ABSTRACT FROM AUTHOR]

Pedestrian vitality in commercial streets is influenced by various factors, among which the spatial form of the street and the resulting thermal environment have a significant impact. This study, from the perspective of thermal comfort, combines thermal comfort simulation with pedestrian simulation to establish an optimization model based on pedestrian vitality. The model aims to analyze and quantify the impact of street spatial form on thermal comfort and pedestrian vitality, providing a comprehensive evaluation of optimization schemes for commercial street spaces. Firstly, the study identifies the levels of spatial design parameters for commercial streets and generates optimized design scenarios for commercial street spaces. Using the simulation platforms Rhino 7 Grasshopper and MATLAB R2023a, a pedestrian simulation model guided by thermal comfort is constructed and validated against empirical data. Next, the influence of commercial street spatial design parameters on store visitations is assessed, identifying the most critical design parameters. Finally, design strategies for commercial streets are proposed based on vitality-oriented layouts. The results indicate that the spatial form of the street significantly affects store visitations, with the street width-to-height ratio being the most influential factor, followed by street orientation and interface form. NW-SE-oriented streets show a 47.2% higher Total Store Visitations (TSV) value compared to E-W-oriented streets, while E-W streets exhibit a Differential Store Visitation (DSV) value 4.47 times that of NW-SE streets. Streets with a W/H ratio of 0.25 have a 54.9% higher Total Store Visitations value than those with a W/H ratio of 0.9, and streets with a W/H ratio of 0.65 exhibit a Differential Store Visitations value 1.21 times that of streets with a W/H ratio of 0.25. Considering overall street vitality, the study recommends NW-SE- and NE-SW-oriented streets, with a width-to-height ratio between 0.25 and 0.4. The study also proposes strategies for the modification and expansion of streets in different orientations, providing the scientific basis and optimization recommendations for the planning and renovation of commercial streets in cold regions during summer. [ABSTRACT FROM AUTHOR]

Ambient particulate matter (PM) pollution is a leading environmental health threat worldwide. PM with an aerodynamic diameter ≤ 1.0 μm, also known as PM1, has been implicated in the morbidity and mortality of several cardiorespiratory and cerebrovascular diseases. However, previous studies have mostly focused on analyzing fine PM (PM2.5) associated with disease metrics, such as emergency department visits and mortality, rather than ultrafine PM, including PM1. This study aimed to evaluate the association between short-term PM1 exposure and hospital admissions (HAs) for all-cause diseases, chronic obstructive pulmonary disease (COPD), and respiratory infections (RIs), as well as the associated expenditures, using Beijing as a case study. Here, based on air pollution and hospital admission data in Beijing from 2015 to 2017, we performed a time-series analysis and meta-analysis. It was found that a 10 μg/m3 increase in the PM1 concentration significantly increased all-cause disease HAs by 0.07% (95% Confidence Interval (CI): [0, 0.14%]) in Beijing between 2015 and 2017, while the COPD and RI-related HAs were not significantly associated with short-term PM1 exposure. Meanwhile, we estimated the attributable number of HAs and hospital expenditures related to all-cause diseases. This study revealed that an average of 6644 (95% CI: [351, 12,917]) cases of HAs were attributable to ambient PM1, which was estimated to be associated with a 106 million CNY increase in hospital expenditure annually (95% CI: [5.6, 207]), accounting for 0.32% (95% CI: [0.02, 0.62%]) of the annual total expenses. The findings reported here highlight the underlying impact of ambient PM pollution on health risks and economic burden to society and indicate the need for further policy actions on public health. [ABSTRACT FROM AUTHOR]

Ischemic stroke (IS), chronic obstructive pulmonary disease (COPD) and diabetes mellitus (DM) account for a large burden of premature deaths. However, few studies have investigated the associations between fine particular matter (PM2.5) components and mortality of IS, COPD and DM. We aimed to examine these associations in Beijing, China. Data on daily mortality, air pollutants and meteorological factors from 2008 to 2011 in Beijing were collected. Daily concentrations of five PM2.5 components, namely, sulfate ion (SO42−), ammonium ion (NH4+), nitrate ion (NO3−), organic matter (OM) and black carbon (BC), were obtained from the Tracking Air Pollution (TAP) database in China. The association between PM2.5 components and daily deaths was explored using a quasi-Poisson regression with the distributed lag nonlinear model (DLNM). The average daily concentrations of SO42−, NH4+, NO3−, OM and BC were 11.24, 8.37, 12.00, 17.34 and 3.32 μg/m3, respectively. After adjusting for temperature, relative humidity, pressure, particulate matter less than 10 μm in aerodynamic diameter (PM10), nitrogen dioxide (NO2) and sulfur dioxide (SO2), an IQR increase in OM at lag day 2 and lag day 6 was associated with an increased DM mortality risk (RR 1.038; 95% CI: 1.005–1.071) and COPD mortality risk (RR 1.013; 95% CI: 1.001–1.026). An IQR increase in BC at lag day 0 and lag day 6 was associated with increased COPD mortality risk (RR 1.228; 95% CI: 1.017–1.48, RR 1.059; 95% CI: 1.001–1.121). Cumulative exposure to SO42− and NH4+ was associated with an increased mortality risk for IS, with the highest effect found for lag of 0–7 days (RR 1.085; 95% CI: 1.010–1.167, RR 1.083; 95% CI: 1.003–1.169). These effects varied by sex and age group. This study demonstrated associations of short-term exposure to PM2.5 components with increased risk of IS, COPD and DM mortality in the general population. Our study also highlighted susceptible subgroups. [ABSTRACT FROM AUTHOR]

Simple Summary: The shadow of prion protein (Sho) encoded by the shadow of prion protein gene (SPRN) has been implicated in prion disease biology. Here, we identified the SPRN gene sequence and characterized its genetic polymorphisms in ducks. As a result, the duck and chicken Sho amino acid sequences shared 100% identity. Notably, we found an abundance of single nucleotide polymorphisms in the open reading frame of duck SPRN gene, which is comparable to those in prion disease-susceptible species. To date, there has been no evidence of prion disease in ducks to our knowledge. Given that our previous study on the duck prion protein gene suggested several characteristics of potential prion disease susceptibility, this study supports the need for additional experiments to examine the risk of developing prion diseases in ducks. Prion diseases are fatal neurodegenerative disorders characterized by an accumulation of misfolded prion protein (PrPSc) in brain tissues. The shadow of prion protein (Sho) encoded by the shadow of prion protein gene (SPRN) is involved in prion disease progress. The interaction between Sho and PrP accelerates the PrPSc conversion rate while the SPRN gene polymorphisms have been associated with prion disease susceptibility in several species. Until now, the SPRN gene has not been investigated in ducks. We identified the duck SPRN gene sequence and investigated the genetic polymorphisms of 184 Pekin ducks. We compared the duck SPRN nucleotide sequence and the duck Sho protein amino acid sequence with those of several other species. Finally, we predicted the duck Sho protein structure and the effects of non-synonymous single nucleotide polymorphisms (SNPs) using computational programs. We were the first to report the Pekin duck SPRN gene sequence. The duck Sho protein sequence showed 100% identity compared with the chicken Sho protein sequence. We found 27 novel SNPs in the duck SPRN gene. Four amino acid substitutions were predicted to affect the hydrogen bond distribution in the duck Sho protein structure. Although MutPred2 and SNPs&GO predicted that all non-synonymous polymorphisms were neutral or benign, SIFT predicted that four variants, A22T, G49D, A68T, and M105I, were deleterious. To the best of our knowledge, this is the first report about the genetic and structural characteristics of the duck SPRN gene. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence technology, deep reinforcement learning (DRL) has become a major approach to the design of intelligent vehicle-to-everything (V2X) routing protocols for vehicular ad hoc networks (VANETs). However, if the V2X routing protocol does not consider both real-time traffic conditions and historical vehicle trajectory information, the source vehicle may not transfer its packet to the correct relay vehicles and, finally, to the destination. Thus, this kind of routing protocol fails to guarantee successful packet delivery. Using the greater network flexibility and scalability of the software-defined network (SDN) architecture, this study designs a two-phase integrated DQN and RF Packet Routing Framework (IDRF) that combines the deep Q-learning network (DQN) and random forest (RF) approaches. First, the IDRF offline phase corrects the vehicle's historical trajectory information using the vehicle trajectory continuity algorithm and trains the DQN model. Then, the IDRF real-time phase judges whether vehicles can meet each other and makes a real-time routing decision to select the most appropriate relay vehicle after adding real-time vehicles to the VANET. In this way, the IDRF can obtain the packet transfer path with the shortest end-to-end delay. Compared to two DQN-based approaches, i.e., TDRL-RP and VRDRT, and traditional VANET routing algorithms, the IDRF exhibits significant performance improvements for both sparse and congested periods during intensive simulations of the historical GPS trajectories of 10,357 taxis within Beijing city. Performance improvements in the average packet delivery ratio, end-to-end delay, and overhead ratio of the IDRF over TDRL-RP and VRDRT under different numbers of pairs and transmission ranges are at least 3.56%, 12.73%, and 5.14% and 6.06%, 11.84%, and 7.08%, respectively. [ABSTRACT FROM AUTHOR]

An integrated energy system (IES) plays a key role in transforming energy consumption patterns and solving serious environmental and economic problems. However, the abundant optional schemes and the complex coupling relationship among each piece of equipment make the optimization of an IES very complicated, and most of the current literature focuses on optimization of a specific system. In this work, a simulation-based two-step decoupling method is proposed to simplify the optimization of an IES. The generalized IES is split into four subsystems, and a two-layer optimization method is applied for optimization of the capacity of each piece of equipment. The proposed method enables fast comparison among abundant optional configurations of an IES, and it is applied to a hospital in Beijing, China. The optimized coupling system includes the gas-fired trigeneration system, the GSHP, and the electric chiller. Compared with the traditional distributed systems, the emission reduction rate of CO2 and NOX for the coupling system reaches 153.8% and 314.5%, respectively. Moreover, the primary energy consumption of the coupling system is 82.67% less than that of the traditional distributed energy system, while the annual cost is almost at the same level. [ABSTRACT FROM AUTHOR]

As the capital of China and a densely populated major city, the characteristics of Beijing's near-surface wind field change significantly with the increase in the density of underlying urban structures. The high randomness of natural wind makes it extremely difficult to develop a universally applicable wind-resistant load design code based on topographic factors and architectural features. This article takes the wind speeds recorded at 15 different height levels within the urban area by the 325 m meteorological tower in Beijing from 1991 to 2020 as the research subject. It quantifies the wind speed trends at different heights and introduces time-varying functions to establish a non-stationary wind speed model based on the optimal model. Additionally, it compares the basic wind speeds and wind pressure height variation coefficients obtained from measurements with the standards. The results show that, during the past 30 years of urbanization, the near-surface wind speed in the Beijing area has shown a decreasing trend. The model incorporating time-varying functions exhibited the best fit and demonstrated good predictive capabilities, with its calculated basic wind speeds being relatively high. The wind pressure height variation coefficient values in Beijing are between Class C and Class D terrains, being closer to Class C at lower altitudes. The conclusion reveals that urbanization has a significant impact on wind speeds, primarily concentrated at lower height levels, and that the basic wind speeds calculated based on standards underestimate the actual conditions when this impact is not considered. Although the average wind speed's wind profile index across the entire time series is mostly greater than the fixed value of 0.3 given by Class D, this represents an overestimated wind profile index for maximum wind speeds. [ABSTRACT FROM AUTHOR]

To address current ecological issues and a lack of historical preservation in Beijing's waterfront, it has become necessary to establish an urban design project that optimizes these aspects. This study focuses on "Beijing's Waterfront Overall Urban Design," a project that integrates government requirements with Beijing's waterfront urban design characteristics and problems to establish an urban layer system from two dimensions: historical and ecological. It explores how the urban layer system can be applied to Beijing's overall waterfront urban design, from investigation to evaluation, analysis, visualization, and strategy development. First, an urban layer system for Beijing's waterfront was established from a historical perspective, based on urban setting and construction stages and space utilization, referring to the literature and field surveys. The evolution of urban layers of waterbodies, the water–city relationship, and water functions was systematically analyzed. Second, an urban layer system was established for the ecological dimension of Beijing's waterfront based on a literature review, expert interviews, and analytic hierarchy process methods. It included four urban layers: waterbody, greening, shoreline, and ecological function. The quality of the ecological urban design of 54 waterfront reaches in Beijing was evaluated using questionnaires and field surveys. Third, a series of urban layer maps was generated using the mapping method. Finally, urban design strategies were developed based on the combined historical and ecological characteristics and problems of Beijing's waterfront. The results of this study and the concept of an urban layer system for waterfront urban design can benefit waterfront urban design projects and future studies. [ABSTRACT FROM AUTHOR]

Considering the essential expansion of agricultural production, current research primarily focuses on static factors, such as the distribution of fine-grained arable land, omitting an in-depth analysis of its developmental dynamics and key drivers. Addressing this knowledge gap is crucial for enhancing the scalability of agricultural production. This research utilizes landscape ecology techniques, correlation analysis, random forest algorithms, and structural equation modeling to explore spatial pattern trends of arable land in the Beijing–Tianjin–Hebei region. Its objective is to clarify how the expansion of agricultural production scale affects food production through changes in arable land patterns and to determine the impact of socio-economic factors on these configurations. The results show that: (1) the landscape pattern of arable land is transitioning to a more fragmented arrangement with complex contours, (2) grain yield per unit area correlates positively with the landscape pattern index in Beijing, negatively in Hebei, and exhibits no significant correlation in Tianjin, and (3) land ownership plays a crucial role in land fragmentation, alterations in land morphology, and influences other socio-economic variables. Analyzing the spatial pattern of arable land in conjunction with socio-economic factors is essential for developing holistic land management approaches, improving resource efficiency, minimizing external inputs, and mitigating food security challenges. [ABSTRACT FROM AUTHOR]

Most studies on Chinese dormitories are carried out in summer, while few focus on a transition season or winter. This study evaluated the air quality of a student dormitory in a university in the Beijing area by using a questionnaire survey and on-site measurements. The CO2 concentration was used as an indoor air quality evaluation index to characterize the freshness of the air, and different window opening conditions in the dormitory were simulated, with corresponding improvement plans proposed. The results of this study revealed that the air quality and thermal comfort of the student dormitories during a transition season and winter fell short of expectations. According to the survey, students who opened their windows frequently had a better subjective perception of the air quality. However, due to the large temperature difference between day and night, more than 80% of the students felt too cold when opening the windows. For daytime conditions, the area of unilateral ventilation window opening should not be less than 0.39 m2, the area of bilateral ventilation window opening should not be less than 0.13 m2, and the time taken to close the windows and doors should not exceed the maximum ventilation interval. Empirical equations were fitted for nighttime conditions based on the CO2 concentration, number of people in the room, and window opening area, resulting in a reasonable window opening area of 0.349 m2~0.457 m2. In sum, this study assessed the air quality status within typical university dormitories across varying seasons, gaining a clear understanding of how different ventilation strategies and occupant densities influence air freshness and thermal comfort. Based on these insights, a practical and optimized window area recommendation was formulated to enhance the indoor environmental quality in these dormitories. [ABSTRACT FROM AUTHOR]

Beijing, China's capital city, has experienced decades of severe land subsidence due to the long-term overexploitation of groundwater. The implementation of the South-to-North Water Diversion Project (SNWDP) and artificial ecological restoration have significantly changed Beijing's hydro-ecological and geological environment in recent years, leading to a widespread rise in groundwater levels. However, whether the related land subsidence has slowed down or reversed under these measures has not yet been effectively monitored and quantitatively analyzed in terms of time and space. Accordingly, in this study, we proposed using an improved time-series deformation method, which combines persistent scatterers and distributed scatterers, to process Sentinel-1 images from 2015 to 2022 in the Beijing Plain region. We performed a geospatial analysis to gain a better understanding of how the new hydrological conditions changed the pattern of deformation on the Beijing Plain. The results indicated that our combined PS and DS method provided more measurements both in total quantity and spatial density than conventional PSI methods. The land subsidence in the Beijing Plain area has been effectively alleviated from a subsidence region of approximately 1377 km2 in 2015 to only approximately 78 km2 in 2022. Ecological restoration areas in the northeastern part of the Plain have even rebounded over this period, at a maximum of approximately 40 mm in 2022. The overall pattern of ground deformation (subsidence and uplift) is negatively correlated with changes in the groundwater table (decline and rise). Local deformation is controlled by the thickness of the compressible layer and an active fault. The year 2015, when anthropogenic water transfers were eliminated and ecological measures to recharge groundwater were implemented, was the crucial turning point of the change in the deformation trend in the subsidence history of Beijing. Our findings carry significance, not only for China, but also for other areas where large-scale groundwater extractions are causing severe ground subsidence or rebound. [ABSTRACT FROM AUTHOR]