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The fossils of Hamipterus tianshanensis (Wang et al. in Curr Biol 24:1323–1330, 2014) and their eggs have important scientific significance because they can provide unique information about the reproduction, development, and evolution of pterosaurs. The fossils and the rock surrounding them have, however, been weathered, which including powdering and flaking, since they were relocated from Xinjiang to Beijing. The high content of soluble salts is a significant factor in fossil deterioration because the dissolution–recrystallization process can generate tremendous pressure and lead to decreased mechanical strength. This study evaluated the electrokinetic desalination performance for the fossils, and two types of poultices employed including paper pulp from Bioline® and CKS121 (cellulose: kaolin: sand = 1:2:1, w/w). Mercury intrusion porosimetry (MIP), scanning electron microscopy (SEM), ion chromatography (IC), and other methods were applied to evaluate the desalination effect. The surface salt content reduction by applied direct current (DC) was about 70%, and the inner salt content reduction was about 80%. The experimental results suggest that the electrokinetic method is a promising way to desalinate fossils. Nonetheless, cracks appeared in the surrounding rock crack after electrokinetic desalination, which can be explained by the montmorillonite swelling-induced stresses. Pre-consolidation, especially for electro-chemical method may solve the cracking problem for the clay-rich sandstone desalination. [ABSTRACT FROM AUTHOR]

Purpose: There is a wealth of value hidden in regional cultural heritage, but its preservation status is not optimistic. This study introduces a method that focuses on the inherent cultural value of regional cultural heritage to preserve it by value construction and release. Design/methodology/approach: Based on the great value of regional cultural heritage due to spatial adjacency and temporal continuity, this paper focuses on its inherent cultural value to explore the preservation path and chooses Shichahai cultural heritage digital resources for a case study. This paper draws lessons from the narrative method of ancient Chinese historiography, constructs a cultural space and tells cultural stories. A linked data organization model for digital resources is created to construct a conceptual cultural space. Then, the space is materialized by linked dataset creation. The authors tell cultural stories discovered from the space, which are presented by various user interfaces using visualization technologies. Findings: A cultural space promotes the development of a fine-grained description of regional cultural heritage and aids in relationship discovery to enhance the value construction ability. Additionally, storytelling via interactive user interfaces is helpful in the utilization and dissemination of knowledge extracted from a cultural space and enhances the value release of regional cultural heritage. In this way, a path with the inherent cultural value of regional cultural heritage as the core is established, and preservation is achieved. Originality/value: This study focuses on the inherent cultural value of regional cultural heritage and proposes a new path to preserve these resources. This approach will enrich research on the preservation of regional cultural heritage and contribute to the construction and release of its cultural value. [ABSTRACT FROM AUTHOR]

Transit as an alternative means of travel allows travelers to access a wide range of activities and services. In addition to focusing on how many job opportunities and other basic urban services such as parks and healthcare can be accessed by transit, more attention should be paid to how many transit services can be obtained and how easy it is to access them. It should be noted that accessibility by transit and accessibility to transit are not the same thing, and most existing studies tend to focus on the former while ignoring the measurement of the latter. However, accessibility to transit is an important concept that can provide a framework for understanding and explaining the availability of transit services. In the literature, transit is more often used as a tool for accessing activities and opportunities to analyze the basic services such as healthcare resources and job opportunities that can be accessed, which not only ignores the transit service provided by the means of transit as a supplying facility, but also ignores the diversity of facilities in the integrated public transportation system. With this in mind, this paper introduces the entropy index into the adjusted Gaussian two-step floating catchment area (2SFCA) method to measure accessibility to transit to capture how the overall accessibility changes when considering different transit facilities. From the spatial distribution of accessibility, the areas with high accessibility score are distributed in the six core administrative districts of Beijing, accounting for 99.3% of the grids with high accessibility scores. When considering facility diversity, 46.7% of the grids within the core administrative districts experience an increase in their accessibility rank, and there is an increase in the number of grids with high accessibility. The research results indicate that considering facility diversity enhances the accessibility level of grids, elucidates the diversity differences in each area, and provides valuable information for the location selection of transit facilities and urban planning. The applicability of the proposed method to Beijing illustrates that it can provide valuable insights for the measurement of accessibility, which can help planners obtain more effective evaluation results. [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]

The purpose of this paper is to retrieve and study the highly cited papers as well as the correlation between the citation frequency and the download frequency of the 20 traditional Chinese medicine journals in China, in order to provide the guidance for improving the influence and academic quality of these journals. Bibliometric analyses were conducted on 1103 papers of 20 traditional Chinese medicine journals from 2011 to 2020 by retrieving for the China Academic Journal Network Publishing Database (CAJD) in China National Knowledge Infrastructure (CNKI). SPSS 17.0 software was used to analyze the correlation between the citation frequency and the download frequency via conducting regression fitting and establishing the mathematical models. The results showed that the total citations of the 1103 papers were 93051 times and the average citations were 84.36 times per paper. The total downloads of the 1103 papers were 2058442 times, and the average downloads were 1866.22 times per paper. China Journal of Chinese Materia Medica ranked first according to the number of papers, total citations and total downloads. The citations of Journal of Chinese Medicinal Materials ranked first based on the number of citations per paper. One of Li's paper had been cited the most (983 times). There were 629 (57.03%) papers whose first author was from universities. The scopes of the first authors were distributed in 29 regions and 2 special administrative regions (Macao, Hong Kong) in China. The authors from Beijing published 283 (25.66%) papers, ranking number one. The number of papers supported by funds was 882 (79.96%). The research results of correlation showed that the citation frequency and the download frequency of the highly cited papers had a highly positive correlation from both journal and paper level for whether the sample data of journals was normally distributed or nonnormally distributed. The correlation coefficients of the 20 journals at journal level and that at paper level were 0.9765 and 0.6677, respectively. The correlation was better at journal level than that at paper level, while the optimal regression fitting was all cubic polynomial. Among the 1103 papers, there were 684 (62.01%) research papers and 419 (37.99%) review papers. The main citation period of the top 15 papers was from the 2nd year to the 6th year after publication, accounting for 78.39%. Papers on clinical therapeutics research, papers on the pharmacological effects and its mechanism of traditional Chinese medicine, and papers on traditional Chinese medicine and natural medicine were the main source of the highly cited papers of the traditional Chinese medicine journals. Editors of the journals should focus on the above-mentioned research areas to select manuscripts for exploiting the excellent sources extensively, while paying attention to review papers, focusing on national major or key projects, paying attention to network spreading, stabilizing authors with quality services, in order to improve the influence and the academic quality of journals. [ABSTRACT FROM AUTHOR]

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]

The layout, scale and spatial form of urban employment centers are important guidelines for the rational layout of public service facilities such as urban transportation, medical care, and education. In this paper, we use Internet cell phone positioning data to identify the workplace and residence of users in the Beijing city area and obtain commuting data of the employed to measure the employment center system in Beijing. Firstly, the employment density distribution is generated using the data of the working places of the employed persons, and the employment centers are identified based on the employment density of Beijing. Then, we use the business registration data of employment centers to measure the industrial diversity within the employment centers by using the ecological Shannon Wiener Diversity Index, and combine the commuting links between employment centers and places of residence to measure the energy level of each employment center, analyze the hinterland and sphere of influence of each center, and finally using the industrial diversity index of employment centers and the average commuting time of employed persons, combined with the K-Means clustering algorithm, to classify the employment centers in Beijing. The employment center identification and classification method based on big data constructed in this study can help solve the limitations of the previous employment center system research in terms of center identification and commuting linkage measurement due to large spatial units and lack of commuting data to a certain extent. The study can provide reference for the regular understanding and technical analysis of employment centers and provide help for the employment multi-center system in Beijing in terms of quantifying the employment spatial structure, guiding the construction of multi-center system, and adjusting the land use rules. [ABSTRACT FROM AUTHOR]

LED ground display system, as an important outdoor display system in the opening and closing ceremonies of the 24th Beijing Winter Olympic and Paralympic Games, has brought spectacular and gorgeous artistic presentation to the world. Compared with the traditional outdoor display system, this display system has many innovations in display product design, control system design and field implementation. This paper gives detail introduction to the ground display system, especially about the innovative product design, high reliability design, color correction and on site implementation of the semicircular display area on both sides. It provides a successful design case for world class large‐scale outdoor display system. [ABSTRACT FROM AUTHOR]

Optimizing resource efficiency and mitigating climate change have become consensuses of human society. However, there is still a gap in assessing the carbon emission efficiency (CEE) and identifying the influence of various factors, especially in rapid urbanizing regions. In this paper, we built a stochastic frontier analysis model to assess CEE and conducted a case study in the Beijing–Tianjin–Hebei Urban Agglomeration (BTHUA), a typical area of collaborative development in China. A comprehensive influencing factor index was constructed to analyze and identify the key influencing factors of CEE. The results revealed that the average CEE among the 13 cities increased in volatility from 2000 to 2019. The average CEE in Langfang was lowest, while that in Tangshan was highest. The input-related factors had a negative effect on CEE, including carbon emissions per capita, employment per ten thousand people, total assets per capita, and energy intensity. GDP per capita, the urbanization level, and the proportion of the tertiary sector's GDP had positive impacts on CEE. Future policy formulation should focus on the transition from labor- and material-intensive industries to knowledge- and technology-intensive industries. All the results can contribute to achieving high-quality development and dual-carbon target of rapid-urbanizing areas. [ABSTRACT FROM AUTHOR]

Copyright of Acta Scientiarum Naturalium Universitatis Pekinensis is the property of Editorial Office of Acta Scientiarum Naturalium Universitatis Pekinensis 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.)

To predict the future condition of a bridge, statistical models for the time-in-condition rating (TICR) can estimate the time that a bridge stays in a given condition and then predict the future condition of the bridge. However, existing research typically uses the probability density functions as the likelihood function when the TICR is estimated by Bayesian updating, in which the change in the condition rating (CR) between two consecutive inspections is assumed to occur at the later inspection, which ignores the uncertainty of the time of the condition change. This assumption will introduce an error, which is particularly significant when the two consecutive inspections are separated over a long time. In addition, a large amount of existing bridge inspection data in China has not been fully recorded; for instance, a lot of bridge inspection data only contains the CR of the bridge from the last inspection. Current research that is based on the TICR has difficulty using this incomplete data. To solve these difficulties, this paper proposes a probability-based likelihood function for the Bayesian updating of the TICR models, which could estimate the distribution of the TICR more accurately using fully recorded or single data. The accuracy of the proposed method is verified with numerical examples, and the results from different methods are discussed. Then, the effect of using complete and single data are examined. The proposed method is applied to the CR of the superstructures of reinforced concrete bridges in Beijing that uses the real inspection data, and the future deterioration risk is evaluated using the updated TICR models. [ABSTRACT FROM AUTHOR]

The underground hub of Xinghuo Station of M3 Line of Beijing Metro is an integral part of the underground comprehensive hub of Xinghuo Station of high-speed railway, and it is constructed by open-excavation method. Due to the different requirements of the main structure function inside the foundation pit of the hub, the foundation pit adopts the three-level layout. One side of the foundation pit is adjacent to the existing high-speed railway Xinghuo station, and the other side is adjacent to the urban road, the foundation pit is affected by four layers of groundwater. In order to solve the difficulties encountered in the design of the multi-stage foundation pit support structure of the underground hub of the Xinghuo Station on the metro line M3, this paper carries out the research of the foundation pit composite support structure system. Firstly, the spatial layout characteristics, surrounding environment and groundwater occurrence characteristics of the hub foundation pit are analyzed, and the problems of the conventional support structure system are discussed. Based on the concept of graded support and graded water stop, the combined foundation pit support structure system is developed. The paper presents in detail the layout, structural parameters and step sequence of multi-stage foundation pit excavation and support structure system at all stages, then establishes the three-dimensional numerical calculation model of multi-stage foundation pit excavation and support, analyzes the pit bottom uplift and the deformation of the retaining structure, and finally discusses the deformation characteristics of the combined retaining structure of the foundation pit based on the measured results of the deformation of the retaining structure at all stages. The results of numerical simulation and on-site monitoring show that the uplift of pit bottom and the deformation of supporting structure meet the requirements of control values. [ABSTRACT FROM AUTHOR]

Cities serve as both political and economic hubs. Sustainable development has long been acknowledged as crucial to the well-being of the environment, people, and society. In order to improve the current state of spatial affairs and attain long-term resilience, humanity is looking for reliable and sustainable urban planning approaches. Urban agriculture has received a lot of attention in recent years as an enduring and pervasive kind of landscape. Although the contribution of urban agriculture has been well documented in many studies on economic, social and ecological aspects, there has been little discussion of its practical value as a tool for spatial development. Additionally, the potential of urban agriculture as a landscape approach remains underdeveloped. In summary, current research and practice lacks a scientific framework for considering urban agriculture as a landscape approach to intervene in urban spaces. To this end, this paper explores the potential of urban agriculture as a landscape approach in sustainable urban planning and design through qualitative case study. Taking Songzhuang in Beijing as an example, we discuss and summarise the operational value and potential of urban agriculture from a design perspective. The findings suggest that landscape-based urbanism that includes urban agriculture can harmonise social, economic, environmental and ecological elements. Finally, in order to provide a generalised approach, this paper proposes a scientific framework for articulating a landscape approach to urban agriculture to guide future research and practice. [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]

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]

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

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]

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]

Beijing is a typical energy-imported city, and the study of energy consumption factors in Beijing is important for the sustainable development of Beijing. There are many influencing factors of energy consumption in Beijing, and the influence degree of each factor differs in different development periods. By constructing the IPAT model of energy consumption change in Beijing, this paper breaks down the factors that cause the change in energy consumption in Beijing into population, affluence, and technological progress. The results show that Beijing is a highly energy-consuming city and the change in energy consumption in Beijing is the superposition of multiple effects. The energy consumption change caused by population growth in Beijing continues to increase through data from 2006 to 2020, but begins to show a downward trend, with a maximum change in energy consumption of 19.8 million tons of standard coal. The largest change in energy consumption is caused by per capita GDP growth, which reached 50.3 million tons of standard coal in 2018–2019, and the effect caused by affluence is greater than the impact of population changes. Technological advances always reduce energy consumption and are increasingly effective. To reduce energy consumption and improve environmental quality, the following two things need to be done: first, to continuously control the population of Beijing, and second, to enhance the development and introduction of innovative technologies for energy conservation. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to apply the bibliometric analysis to summarize acupuncture therapy for stroke, demonstrated and evaluated the trends, major research hotspots and frontier areas. Materials and Methods: Articles on acupuncture for stroke were selected from the Web of Science Core Collection (WoSCC) from the inception of the database up until 2023. CiteSpace software was performed to conduct the collaborative analysis of networks of countries, institutions, authors and cited authors, journals and cited journals, cited references, keywords clustering and burstiness analysis. Results: A total of 1141 articles were retrieved. China was the most productive country (851) and had the greatest centrality (0.43). Beijing Univ Chinese Med (86) contributed to the most publications. Chen LD (31) and Tao J (31) were the most prolific authors, of which all from Fujian Univ Tradit Chinese Med. Wu P (124) from Canadian College of Naturopathic Medicine, Canada, was the most cited author. Evidence-based Complementary and Alternative Medicine (89) was the most productive journal, while Stroke (744) was first cited journals. Stimulation, recovery, ischemic stroke, electroacupuncture, rehabilitation were the most high-frequency keywords. Future research in this area will pay more attention to the evaluation of the effectiveness of acupuncture therapeutics in treating stroke, conducting the clinical research on cognitive ability, quality of life and partial function of stroke patients, and basic research related to mechanisms. Conclusion: The publications on acupuncture in stroke have shown major development, but the international cooperation for academic exchange among researchers and institutions remained to be strengthened to promote interdisciplinary and academic innovation. Furthermore, except for the molecular mechanism of acupuncture in treating functional rehabilitation of stroke, exploring the more high-quality clinical studies may become a key point based on the evidence-based medicine. [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]

The couple between the power network and the transportation network (TN) is deepening gradually with the increasing penetration rate of electric vehicles (EV), which also poses a great challenge to the traditional voltage control scheme. In this paper, we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV. In the first stage, the action of on-load tap changer and capacitor banks, etc., are determined by optimal power f low calculation, and the node electricity price is also determined based on dynamic time-of-use tariff mechanism. In the second stage, multiple operating scenarios of multiple types of EVs such as cabs, private cars and buses are considered, and the scheduling results of each EV are solved by building an optimization model based on constraints such as queuing theory, Floyd-Warshall algorithm and traffic flow information. In the third stage, the output power of photovoltaic and energy storage systems is fine-tuned in the normal control mode. The charging power of EVs is also regulated in the emergency control mode to reduce the voltage deviation, and the amount of regulation is calculated based on the fair voltage control mode of EVs. Finally, we test the modified IEEE 33-bus distribution system coupled with the 24-bus Beijing TN. The simulation results show that the proposed scheme can mitigate voltage violations well. [ABSTRACT FROM AUTHOR]

This paper conceptualises digital displacement as both a way through which the digital, dynamic and fragile spatialities of contentious politics can be examined and as a geographic critique of censorship. Digital displacement, understood here as the act of removing users from the digital places and spaces they wish to remain in and use, often through the act of deletion, is conceptualised through the digital displacement of two contentious political groups that attempted to contest the forced eviction of migrants from Beijing in 2017; hashtag focused #BeijingSurgery# and instant messaging group using BeijingTogether. Explored through participant observation, interviews and playful digital exploration, this paper examines the spatialities that made multiple digital displacements possible and the activist spatialities that emerged during and post‐displacement. In exploring this, I develop a flexible vocabulary around digital place, space, scale, territory and mobility to analyse the practices of digital displacement, to understand the socio‐spatial positionality of activists involved in digitally centred contentious politics and to contextualise their territorial positionality within Chinese digital territory and global digital territories. Through the examination of #BeijingSurgery# and BeijingTogether, the article highlights: the importance of digital territorial positionality for both activists and the digital places and spaces used for contentious politics; that within systems of digital spatial governance, deletion and displacement can be effective strategies of repressive governance with wide‐ranging displacement effects; and that while digital displacement is not necessarily the ending point of contentious politics, the re‐production of activist spatialities is more difficult when the authority being protested against governs the digital territory used for protest. This paper conceptualises digital displacement as: a way through which the digital, dynamic and fragile spatialities of contentious politics can be examined; a way to understand China's digital territorialization project; and as a geographic critique of censorship. Digital displacement is conceptualised through the ethnographic research conducted in Beijing and examines efforts to contest the forced eviction of migrants from Beijing in 2017. [ABSTRACT FROM AUTHOR]

Traffic congestion occurs when there is a mismatch between the demand for road use and the available capacity. The volume-delay function (VDF) can quantify the relationship between travel time and the volume of traffic on a particular link, and also provide insight into the state of a traffic system, such as whether it is congested or uncongested. In this paper, we present a VDF model that is based on the fundamental diagram and has two main components: (1) an improved VDF with fewer parameters that can handle both congested and uncongested traffic conditions, based on a fundamental diagram, and (2) a model-based VDF practical calibration framework for practical traffic applications that can determine key parameters for a link in a corridor. Our experiments using corridors in Los Angeles and Beijing demonstrate that our proposed analytical methods effectively calculate road impedance under congested conditions. The results indicate that the proposed model is superior to other existing models in terms of the root mean squared error (RMSE) and mean absolute error (MAE). In addition, our calibrated results indicate that the travel time index (TTI) in Los Angeles is 2.12, in Beijing is 1.74. The model proposed in this paper provides a useful calibration tool for enhancing model performance and improving the accuracy of travel time and speed estimates in traffic assignment. [ABSTRACT FROM AUTHOR]

Urban last-mile express delivery in China encounters several challenges. This paper presents the establishment of a sharing logistics center aimed at enhancing the overall efficiency of urban last-mile express delivery while optimizing the utilization of essential resources. The successful implementation of shared delivery within sharing logistics center necessitates the creation of a robust collaborative mechanism. Recognizing that cooperative benefit allocation is dynamically influenced by factors such as resource input, operational efficiency, risk management, and other cost-related considerations, this study introduces a multi-weight H-Shapley value method for benefit allocation. By conducting empirical analyses of urban last-mile express delivery in Beijing within a sharing logistics service framework, our findings reveal that the revised benefit allocation model better aligns with the interests of participating entities and positively correlates with their contributions. Analyzing the impact of delivery volume and express operational costs changes, it is found that when the delivery volume and express operational costs of the sharing logistics center change, the benefits of participating enterprises move in the same direction. The benefit allocation model established in this study enriches the existing body of research in the field of shared delivery and offers valuable insights for benefit allocation issues that necessitate consideration of the dynamic effects of multiple parameter variations. [ABSTRACT FROM AUTHOR]

The vegetable sector is a vital pillar of society and an indispensable part of the national economic structure. As a significant segment of the agricultural market, accurately forecasting vegetable prices holds significant importance. Vegetable market pricing is subject to a myriad of complex influences, resulting in nonlinear patterns that conventional time series methodologies often struggle to decode. In this paper, we exploit the average daily price data of six distinct types of vegetables sourced from seven key wholesale markets in Beijing, spanning from 2009 to 2023. Upon training an LSTM model, we discovered that it exhibited exceptional performance on the test dataset. Demonstrating robust predictive performance across various vegetable categories, the LSTM model shows commendable generalization abilities. Moreover, LSTM model has a higher accuracy compared to several machine learning methods, including CNN-based time series forecasting approaches. With R2 score of 0.958 and MAE of 0.143, our LSTM model registers an enhancement of over 5% in forecast accuracy relative to conventional machine learning counterparts. Therefore, by predicting vegetable prices for the upcoming week, we envision this LSTM model application in real-world settings to aid growers, consumers, and policymakers in facilitating informed decision-making. The insights derived from this forecasting research could augment market transparency and optimize supply chain management. Furthermore, it contributes to the market stability and the balance of supply and demand, offering a valuable reference for the sustainable development of the vegetable industry. [ABSTRACT FROM AUTHOR]

Free-floating bike sharing (FFBS) attracts increasing research focusing on usage patterns, determining factors, and integrated transportation. However, existing researchers tend to overlook the variation in usage characteristics over various time ranges, particularly the usage pattern at night. This paper is conducted to fill the gap through a series of analysis approaches on FFSB in Beijing. The characteristics of the usage pattern, including time-varying usage and traveling distance distributions, are initially illustrated. Subsequently, the spatial patterns of FFBS are visualized and thoroughly analyzed in different time ranges and origin-destination (O-D) flows. A statistical model evaluating the environmental effects of FFBS trips revealed the source of FFBS usage. In addition to focusing on the nighttime, the usage patterns varying day and night are compared through the analysis. The findings explain the usage pattern variation and the unique pattern at night, providing valuable insight for improving the management of the FFBS system. [ABSTRACT FROM AUTHOR]

The General Assembly of the United Nations adopted on 7 December 2022 the 'United Nations Convention on the International Effects of Judicial Sales of Ships' known as the ' Beijing Convention on the Judicial Sales of Ships '. The European Union as Regional Economic Integration Organization signed the Convention in New York on 14th March 2024. In recent years the need to have an instrument that establish generally accepted rules on foreign judicial sales of ships and its international recognition has become essential, as there was no domestic or international law on this specific subject. National barriers of a procedural nature between the States left room for legal uncertainty on the amount of sale proceeds that could be achieved for a ship at a judicial sale. In this paper is emphasised how the need for a close harmonisation between the applicable laws has brought to the adoption of the Convention on international recognition of foreign judicial sales of ships in a way which provides clarity and resolves the issues identified to date. This paper includes a comparative overview of selected national frameworks and international instruments on the judicial sale of ships. [ABSTRACT FROM AUTHOR]

Urban energy issues have attracted global attentions due to the key role in controlling climate change. As one of the world's largest metropolises, Beijing has been focusing on improving urban energy performances to achieve green transition and sustainable development during the past decades, for which purpose the measurement and decomposition of energy performance is of vital importance. In this paper, exergy is introduced as one of the indicators under the frame of index decomposition analysis. An hierarchical framework is constructed to reveal the contributions from different level of urban energy system to overall energy performance. Beijing's energy and exergy consumption and intensity are then analyzed and compared from the city and sector level during 2008–2017. Results suggest that Beijing's city and sector-level energy performance has been improving during the last 10 years and technical improvements contribute significantly from both energy and exergy perspectives. Meanwhile, changes from Beijing's industrial structure and energy supply structure display neutral contributions, which probably indicate the underestimation of structural contribution is caused under the IDA framework. [ABSTRACT FROM AUTHOR]

In this article, a comprehensive analysis is conducted on the influencing factors of carbon emissions in the transportation sector during the evolution of electrification in Beijing. We also considered the impact of indirect carbon emissions caused by carbon emissions from public and private cars and electricity consumption on overall carbon emissions. Based on the LMDI decomposition theory, nine influencing factors are separated, including development level, energy intensity, vehicle structure, number of private cars, and private transportation energy consumption. The analysis results show that, from 2010 to 2021, the carbon emissions from transportation in Beijing increased from 922.98 x 104t to 1490.6 x 104t. The private road carbon emission accounts for about 77.97%, and has become a decisive factor affecting road carbon emissions. In the public domain the contribution values of the development level and energy intensity are 25.20% and -38.71%, respectively. And they are the two most critical factors affecting carbon emissions on public road carbon emissions. In the private domain, the contribution values of the number of private cars, energy consumption of private transportation, and vehicle structure are 60.17%, 47.86%, and -12.99%, respectively. They are the three key factors affecting the private road carbon emissions. There is a significant difference in the proportion of indirect carbon emissions from electricity in the public and private domain. Indirect carbon emissions from electricity account for about 13.6% of road carbon emissions in the public sector, and about 0.9% in the private sector. The results in this paper provide useful references for decisionmaking in the adjustment of transportation energy structure and the promotion of electrified transportation in Beijing and other cities. [ABSTRACT FROM AUTHOR]

Debris flow is a prevalent geological disaster in Beijing, particularly in the Mentougou District, situated in the mountainous southwestern region of Beijing City. The past irrational exploitation of minerals has led to a substantial accumulation of slag, providing abundant loose materials for the formation of debris flow in the study area. Different from the traditional method of using hazard and vulnerability to carry out debris flow risk assessment, this paper proposes a debris flow risk assessment method based on (a) the possibility of debris flow occurrence, (b) the value of the disaster-affected object, and (c) the destructiveness of the debris flow. The possibility of 41 gully debris flows occurring was determined through theoretical calculations. Using the SFLOW model, the runout of the potential debris flow was simulated. On this basis, an investigation of the value of the disaster-affected objects was carried out. At the same time, according to the simulated movement information of debris flow, its destructiveness was determined. According to the results of the occurrence possibility of the debris flow, its destructiveness, and the value of the disaster-affected object, the risk levels of 41 potential debris flow gullies in the Mentougou District were obtained. The research results can guide the warning systems for debris flows in the Mentougou District of Beijing. [ABSTRACT FROM AUTHOR]

As urban development accelerates and natural disasters occur more frequently, the urgency of developing effective emergency shelter planning strategies intensifies. The shelter location selection method under the traditional multi-criteria decision-making framework suffers from issues such as strong subjectivity and insufficient data support. Artificial intelligence offers a robust data-driven approach for site selection; however, many methods neglect the spatial relationships of site selection targets within geographical space. This paper introduces an emergency shelter site selection model that combines a variational graph autoencoder (VGAE) with a random forest (RF), namely VGAE-RF. In the constructed urban spatial topological graph, based on network geographic information, this model captures both the latent features of geographic unit coupling and integrates explicit and latent features to forecast the likelihood of emergency shelters in the construction area. This study takes Beijing, China, as the experimental area and evaluates the reliability of different model methods using a confusion matrix, Receiver Operating Characteristic (ROC) curve, and Imbalance Index of spatial distribution as evaluation indicators. The experimental results indicate that the proposed VGAE-RF model method, which considers spatial semantic associations, displays the best reliability. [ABSTRACT FROM AUTHOR]

Copyright of Agricultural Outlook (1673-3908) is the property of Institute of Agricultural Information, Chinese Academy of Agricultural Sciences 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.)

In the context of global carbon emission reduction, solar photovoltaic (PV) technology is experiencing rapid development. Using high-resolution remote sensing images to accurately obtain PV information over a large region, including location and size, has the advantages of high statistical efficiency and timely data update for the PV energy management. Due to the intra-class diversity of PV panels and the intricate variability in their deployment environments, existing semantic segmentation methods often have problems such as under-segmentation and mis-segmentation. To alleviate these problems, this paper proposes an improved DeepLabv3+ semantic segmentation network to more accurately extract PV panels from high-resolution remote sensing images. With the aim of alleviating under-segmentation, a multi-level context aggregation module is developed. This module can enhance the model's ability to learn the characteristics of PV panels and their surrounding environment by aggregating rich contextual information from multi-scale and semantic levels. To alleviate the problem of mis-segmentation, a hybrid attention module is introduced. This module sequentially and adaptively adjusts the weight distribution in both the channel and spatial dimensions, thus enabling the model to focus more on the feature information and spatial positions of PV objects. Experiments conducted on a self-constructed Beijing PV segmentation dataset show that the method in this paper has advantages of completeness and accuracy in extracting PV panels compared to the baseline model and current mainstream semantic segmentation network. In addition, the results of experiments on extracting PV panels in real region show that our model also has good stability and generalization capability. [ABSTRACT FROM AUTHOR]

In the modern risk society, the general sense of collaborative governance is facing a profound crisis—poor governance efficiency due to the lack of authority. The paper introduces a case from China and finds a new mechanism in COVID-19 prevention and control which is called joint governance. Instead of the relatively equal status among multiple actors, joint governance is characterized by a dominant power forming alliances with other stakeholders. The political advantages that Beijing enjoys make it work. Our study suggests that joint governance is a new perspective of collaborative governance which brings politics back to administrative domains. [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]

Objective Our objective was to investigate the basic information of the personnel and facilities of nuclear medicine in Beijing. Methods This survey was performed by the Beijing Quality Control Center in 2018. The investigation included personnel, equipment, and clinical applications, and data were then compared with previous surveys. The paper questionnaires were used for the survey, which required information about the personnel, devices, and clinical applications. Results About 38 nuclear medicine departments in Beijing were involved in the survey. The number of nuclear medicine staff was 531 in 2018, showing an increase of 58.7% over the past decade. Positron emission tomography/computed tomography (PET/CT), single-photon emission computed tomography (SPECT), and single-photon emission computed tomography/computed tomography (SPECT/CT) represented the main nuclear medicine facilities, and the total number of surveyed departments was 18, 24, and 34, respectively. The quality control results showed significant improvement from the 2005 levels. The total number of scintigraphy procedures was estimated at 199,607 (153,185 SPECT and 46,422 PET/CT). The estimated annual number of scintigraphy images was 8.9 per 1,000 population for SPECT and 2.7 per 1,000 population for PET/CT during 2018. The most frequent radioiodine-targeted therapy was 131 I-targeted therapy for hyperthyroidism in 2018. Conclusion Nuclear medicine has experienced rapid growth in the past 10 years in Beijing, either in personnel, equipment, and scintigraphy. Future efforts will focus on the use of new isotopes in the diagnosis, implementing quality strategy, and enhancing training. [ABSTRACT FROM AUTHOR]

During the Beijing 2022 Winter Olympics, Eileen Gu attracted considerable attention and sparked numerous discussions on Chinese social media. Using the method of textual analysis, this paper examines the various responses of Chinese women, particularly Chinese feminists, to Eileen's achievements on Chinese social media, framing these responses within recent studies of neoliberalism's undoing of feminism as well as long-standing debates about the relationship between feminism and nationalism. This paper argues that discussions about Eileen on Chinese social media not only illustrate how neoliberalism is absorbed, reworked, and resisted in its transnational circulation but also demonstrate how nationalist narratives can be strategically used by Chinese feminists to validate their feminist positions. It further enriches existing scholarship on neoliberalism with a transnational perspective, reaffirms the importance of contextualizing the relationship between Third World feminism and nationalism, and highlights the significance of uncovering indigenous feminist resources in Third World countries. [ABSTRACT FROM AUTHOR]

Accurate forecasting of PM2.5 concentrations serves as a critical tool for mitigating air pollution. This study introduces a novel hybrid prediction model, termed MIC-CEEMDAN-CNN-BiGRU, for short-term forecasting of PM2.5 concentrations using a 24-hour historical data window. Utilizing the Maximal Information Coefficient (MIC) for feature selection, the model integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Convolutional Neural Network (CNN), and Bidirectional Recurrent Gated Neural Network (BiGRU) to optimize predictive accuracy. We used 2016 PM2.5 monitoring data from Beijing, China as the empirical basis of this study and compared the model with several deep learning frameworks. RNN, LSTM, GRU, and other hybrid models based on GRU, respectively. The experimental results show that the prediction results of the hybrid model proposed in this question are more accurate than those of other models, and the R2 of the hybrid model proposed in this paper improves the R2 by nearly 5 percentage points compared with that of the single model; reduces the MAE by nearly 5 percentage points; and reduces the RMSE by nearly 11 percentage points. The results show that the hybrid prediction model proposed in this study is more accurate than other models in predicting PM2.5. [ABSTRACT FROM AUTHOR]

For most ultralong bus lines, low punctuality rates and vehicle bunching are two main challenges. One potential strategy to solve these two problems is to split an ultralong line into two or three shorter lines according to historical passenger flow patterns as well as other presetting objectives and constraints. Thus, in this paper, a multiobjective optimization model is first established in consideration of both passenger flow distribution and coline metro networks. Then, the optimal truncated stop is determined by estimating the model results generated by enumerating each potential bus stop derived from related metro stops. The nondominated sorting genetic algorithm II (NSGA-II) is applied to solve the model efficiently. A case study conducted on a real bus line associated with metro networks in Beijing, China, demonstrates the efficiency of the optimization strategy adoption in terms of operating cost and passenger travel time, even with a slight increase in passenger cost. Besides, the multivehicle type is also referred in the experiments to verify economic efficiency to reduce operational costs. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Resources & Ecology is the property of Journal of Resources & Ecology 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.)

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]

Commerce, as both an environmental and a social factor, is essential to the study of the causes of urban crimes. This paper aims to comprehensively propose research hypotheses based on these two types of commercial factors and optimise statistical tools with which to analyse commerce's impact on the level of theft in Beijing. Combining criminal verdicts, census data, points of interest, and information on nighttime lighting, this paper first applies a hierarchical regression model to verify the effectiveness of using commercial environmental and social factors to explain theft statistics and then constructs a structural equation model to analyse the joint influence of multiple commercial factors on those statistics. This paper finds that Beijing's commerce does not significantly promote theft, verifies the effectiveness of two types of commercial variables and the corresponding Western theories in explaining commerce's impact on theft in Beijing, and provides empirical data for the study of the causes of theft in a non-Western context. [ABSTRACT FROM AUTHOR]

This paper argues that in housing transaction with asymmetric information, sellers may signal their private information with special design of listing prices. We build a cheap-talk signalling model in which sellers strategically choose round number listing prices to signal their weakness, i.e. they are willing to accept lower prices in order to sell their houses more quickly. Using housing market transaction data in Beijing, we find that round number listings sell 0.13% lower and 0.086 months sooner than precise ones. We also show that these results are unlikely to be driven by housing unobserved attributes or round number self-attractiveness. In addition, we find that as the roundness of listing price increases, the signalling effects become more pronounced. Our results present empirical evidence that signalling helps improve negotiation efficiency under asymmetric information. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Soil & Water Conservation (1009-2242) is the property of Institute of Soil & Water Conservation 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.)

In recent years, the conflict between human activities and the natural environment has led to global warming and the emergence of extreme weather events, prompting reflection on the climate adaptability of buildings. Historical and cultural districts often reflect the design and construction strategies of their era, which were shaped by the prevailing social environments and natural conditions, so they typically embody construction techniques tailored to address local climatic characteristics. Consequently, in this paper, we focus on 33 historic and cultural districts within Beijing's old city, along with seven proposed historic and cultural districts, to retrieve land surface temperatures (LST) using Landsat remote sensing data and radiative transfer equations. A spatiotemporal analysis was conducted to investigate the variations in LST distribution across different historic and cultural districts and to characterize the internal temperature features within the historic and cultural districts of Beijing's old city. Research indicates the following: (1) The Dashilan area boasts the highest average LST, while the Huangcheng area records the lowest. (2) Over the past six years, most historic and cultural districts have experienced a decline in LST. Notably, the most significant reductions in average LST have been observed in the areas west of Xinjiekou, Dongsi South, and from the 3rd to the 8th Street in Dongsi. (3) Within the historic and cultural districts, hot spots of LST are primarily concentrated in the residential areas with one-story traditional houses, while cold spots are predominantly found around water, cultural relics, and modern architectural structures. [ABSTRACT FROM AUTHOR]

With the acceleration of urban development, the annual production of urban construction waste has been increasing yearly, which brings considerable challenges for urban supervision and management, and how to quickly and accurately identify construction waste is of great practical significance. In this paper, we propose a remote sensing image dust cover net construction waste recognition algorithm based on the improved U-network model to realize construction waste target recognition. The algorithm first prepares a dust cover net construction waste identification dataset using Google high-resolution remote sensing imagery as the database. Second, VGG16 is adopted as the backbone network of the U-Net model to improve the feature expression ability of the model. Finally, the Convolution Block Attention Module (CBAM) is embedded into the U-Net network to construct the CBAM-U-Net model to enhance the information extraction accuracy of high-resolution remote sensing images. With the remote sensing image encompassing Daxing District in Beijing as an example, the results show that the proposed algorithm can automatically and efficiently recognize the dust cover net construction waste with 95.51% recognition accuracy and 95.08% Mlou, which puts forward a new idea for the supervision of construction waste. [ABSTRACT FROM AUTHOR]

Traffic forecasting is a crucial task of an Intelligent Transportation System (ITS), which remains very challenging as it is affected by the complexity and depth of the road network. Although the decision‐makers focus on the accuracy of the top‐level roads, the forecasts on the lower levels also improve the overall performance of ITS. In such a situation, a hierarchical forecasting strategy is more appropriate as well as a more accurate prediction methods to reach an efficient forecast. In this paper, we present a deep learning (DL) approach for hierarchical forecasting of traffic flow by exploring the hierarchical structure of the road network. The proposed approach is considered an improved variation on the top‐down strategy for the reconciliation process. We propose a model based on two deep neural network components to generate a coherent forecast for the total number of road segments. We use N‐BEATS, a pure deep learning forecasting method, at the highest levels for traffic time series, then disaggregate these downwards to get coherent forecasts for each series of the hierarchy using a combination of CNN and LSTM. Experiments were carried out using Beijing road traffic dataset to demonstrate the effectiveness of the approach. [ABSTRACT FROM AUTHOR]