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The optimization of the e-commerce logistics distribution path has always been an important research object in intelligent control. Based on the geographic information system (GIS) platform, this paper proposes an improved ant colony algorithm for the logistics distribution path optimization model based on the GIS platform. Firstly, ArcGIS software is used to solve the problem of complex networks and realize the selection and output of optional routes. Secondly, the basic ant colony algorithm is improved, and a dynamic path planning method combining global planning information and local planning is proposed. It mainly includes the improvement of the heuristic function and the improvement of the update method of pheromone. Finally, through simulation experiments and case validation experiments, it is concluded that the improved algorithm outperforms the traditional ant colony algorithm. In the case validation part, a local area of Beijing is selected to simulate a natural distribution environment, and the path optimization experiments are validated by building an actual road network model. The results show that the model can plan the optimal path for logistics distribution according to the road congestion. The data analysis shows that the route optimization model proposed in this paper can effectively reduce the distribution cost of enterprises, increase vehicle loading, and increase the profit and industry competitiveness of logistics enterprises. [ABSTRACT FROM AUTHOR]

This paper proposed an effective method, the overflow control strategy, for identifying and controlling the frequent overflow of signalized intersections based on the unmanned aerial vehicle (UAV) remote sensing and vehicle trajectory data that provide multi-dimensional vehicle dynamic data. This strategy can effectively control the overflow intersection and restore normal operation as soon as possible. The strategy was implemented as follows. First, UAV remote sensing was used to quickly find the overflow precursor at the intersection. Second, by using moving trajectory data, the second-flow model of the road section was constructed, and overflow identification indexes were established. Third, considering the traffic demand of controlled intersection and non-overflow phase from the global perspective, the queue length model of the non-overflow phase based on moving trajectory data was established and overflow identification indexes were taken as the objective function to design overflow control strategy set. Finally, according to the sampling rate requirement of moving trajectory data and the field traffic survey, the Changping District in Beijing, which meets the requirements, is selected as the case study for simulation and verification. Usually, when overflow occurs, total delay time and the average number of stop cycles at intersections are relatively high. However, by taking the proposed method, overflow at intersections was identified quickly, and a control strategy was implemented immediately, which alleviated the overflow and eventually eliminated it. The results show that the method proposed in this paper can accurately detect the occurrence of overflow, restrain and eliminate the overflow eventually. [ABSTRACT FROM AUTHOR]

The sustainable development goals (SDGs) reflect the pursuit of achieving spatial justice. Both SDG 1.4 and SDG 11.1 reflect a concern for urban services. Life service resources, which are the new concept proposed by the Chinese government, also call for sustainable development path. However, few studies have focused on the realization of spatial justice in life service resources. This paper proposes a two-level, four-step analysis framework composed of quantity, structure, pattern, and coupling coordination to perceive the spatial justice of life service resources. Based on remote sensing technology and geographic information science, this paper acquires and analyses multi-source data including population density, building outlines, point of interests, subway lines, etc. Furthermore, the case study in downtown Beijing found the following: (1) The total life service resources are extensive and varying in type; (2) regional differences are evident and low-level equilibrium and high-level priority development coexist; (3) life service resources are concentrated in contiguous and multi-centre clusters with a greater north–south than east–west difference; (4) the overall level of life service resources is low, specifically for "high in the centre and low in the periphery" and "high in the east and low in the west". Future management should consider narrowing the development gap and formulating industry development plans to improve spatial justice. Finally, the comparison between Beijing and London and more cities in the future needs to consider the urban development stage, population density, and other aspects. [ABSTRACT FROM AUTHOR]

Water is the source of life, and in recent years, with the progress in technology, water quality data have shown explosive growth; how to use the massive amounts of data for water quality prediction services has become a new opportunity and challenge. In this paper, we use the surface water quality data of an area in Beijing collected and compiled by Zhongguancun International Medical Laboratory Certification Co., Ltd. (Beijing, China). On this basis, we decompose the original water quality indicator data series into two series in terms of trend and fluctuation; for the characteristics of the decomposed series data, we use the traditional time series prediction method to model the trend term, introduce the deep learning method to interpret the fluctuation term, and fuse the final prediction results. Compared with other models, our proposed integrated Wavelet decomposition, Autoregressive Integrated Moving Average (ARIMA) and Gated Recurrent Unit (GRU) model, which is abbreviated as the W-ARIMA-GRU model, has better prediction accuracy, stability, and robustness for three conventional water quality indicators. At the same time, this paper uses the ensemble learning model LightGBM for the prediction of water quality evaluation level, and the accuracy and F1-score reached 97.5% and 97.8%, respectively, showing very strong performance. This paper establishes a set of effective water quality prediction frameworks that can be used for timely water quality prediction and to provide a theoretical model and scientific and reasonable analysis reference for the relevant departments for advanced control. [ABSTRACT FROM AUTHOR]

In China, the capitalization of education resources in housing prices has been widely discussed. However, insufficient attention is paid to it in rents. Thus, this paper mainly aims to identify the capitalization of school quality in rents. It estimates a hedonic treatment effects model by introducing the propensity score matching (PSM) method. The empirical analysis is based on 49,438 rental transaction data of 2016–2018 in Beijing, China. It finds that school quality can be significantly capitalized in rents across different school quality (ranked as 1st-class, 2nd-class, and popular-class), space, and time. Besides, quality school density (the number of quality schools) within neighborhoods can significantly moderate the nearest school's capitalization, promoting a 3.5% capitalization increase in outer municipal districts but a 3% decrease in inner districts. The popular-class schools can be capitalized into the rent of inner districts, probably because of other exogenous factors (e.g., housing prices, public transit). In addition, the equitable housing policy might show a potential risk in worsening social inequality between homeowners and renters in the municipal areas with high competition for 1st-class schools. In contrast, it may remedy such inequality in outer districts with less competition for quality schools. [ABSTRACT FROM AUTHOR]

This paper focuses on Chinese sources suggested for a narrative medicine (NM) program, called AfterWards. Dr Lauren Small established AfterWards in 2014 and has been coordinating it since out of the Pediatrics Department at Johns Hopkins Medicine. In early 2019, she started giving a series of lectures and workshops about AfterWards to Chinese medical educators and clinicians in Beijing and Shanghai. She created an AfterWards Facilitator's Guide based on Western-language sources for workshop participants. She also started to organize with Jiang Yuhong (Peking Union Medical College) a workshop for Chinese colleagues to be held at Johns Hopkins Medicine in October 2019. They invited the author to participate. The idea was hatched then to develop Chinese source materials following the AfterWards structure for an updated Facilitator's Guide that Dr Small had initially written. A typical one-hour AfterWards session consists of a specific five-part structure: a literary text or artwork, an associated theme, discussion topics, a writing exercise, and shared reflection. While the content of the program always changes from session to session, the basic structure remains the same. This paper summarizes the types of Chinese sources and their related narrative-medicine themes that were originally selected for inclusion in the updated AfterWards Facilitator's Guide intended for Chinese colleagues. These sources about coping with sick family members, aging, and illness ranged from the textual (classical Chinese poems on aging and diagnostic forms for training students) and visual (premodern Chinese paintings and murals of medical encounters) to the fictive (novels) and performative (contemporary Asian-American film in English and Chinese-language film and documentaries). [ABSTRACT FROM AUTHOR]

With the maturity of big data technology, analyzing residents' travel habits and tracks has become an important research direction in the field of intelligent transportation study. In this paper, based on the subway and bus ride data, a subway-bus double-layer network model was established using complex network theory, taking the optimal traffic efficiency as the goal, the structure of intelligent bus network optimization method is proposed, and an empirical study is conducted on the Beijing bus network. In the empirical study, by adding or deleting bus station in the network, obtain an efficient network structure, the goal of optimal operation efficiency of the bus network was realized, and the theoretical and practical research on solving the problem of transportation line network planning with big data of traffic travel was enriched. [ABSTRACT FROM AUTHOR]

In the new era, the key measure to accelerate the construction of smart city, so as to promote the modernization of urban governance system and governance capacity, is to establish a good urban innovation ecosystem, and guide its continuous evolution to the direction of the highest efficiency and the best performance. Focusing on solving the practical problem of "how the urban innovation ecosystem evolves", this paper develops a NK algorithm using BP neural network and DEMATEL method. First, through literature research, constructing the urban innovation ecosystem including five subsystems of innovation talents, innovation subjects, innovation resources, innovation environment and innovation network. Then, taking Beijing as an example, the weights and the number of epistatic relationships of each subsystem in its innovation ecosystem are calculated by BP neural network and DEMATEL method, and the NK model is modified; on this basis, the fitness values corresponding to different states of the system are calculated using MATLAB software, and the optimal evolution path of Beijing innovation ecosystem is determined through the comparison of 100,000 simulation results. The results show that the optimal evolution path of Beijing's innovation ecosystem is to create a favorable environment and culture for innovation first; then increase the input of innovation resources; and then promote the development of innovation network assets; on this basis, cultivate, attract and retain innovative talents; and finally strengthen the construction of innovation subjects. [ABSTRACT FROM AUTHOR]

Accurate prediction is a fundamental and leading work of the emergency medicine reserve management. Given that the emergency medicine reserve demand is affected by various factors during the public health events and thus the observed data are composed of different but hard-to-distinguish components, the traditional demand forecasting method is not competent for this case. To bridge this gap, this paper proposes the EMD-ELMAN-ARIMA (ELA) model which first utilizes Empirical Mode Decomposition (EMD) to decompose the original series into various components. The Elman neural network and ARIMA models are employed to forecast the identified components and the final forecast values are generated by integrating the individual component predictions. For the purpose of validation, an empirical study is carried out based on the influenza data of Beijing from 2014 to 2018. The results clearly show the superiority of the proposed ELA algorithm over its two rivals including the ARIMA and ELMAN models. [ABSTRACT FROM AUTHOR]

To efficiently handle the projected growth in air traffic, operational concepts such as "corridors-in-the-sky" have been developed in future Air Traffic Management (ATM) plans. Corridors-in-the-sky are defined as reserved airspace where aircraft move in a common direction along parallel lanes on high flight levels. The on and off ramps play an important role in connecting this airspace structure to the jet route. This paper addresses the scheduling problem for flight sequences entering the corridors-in-the-sky via the on-ramp. To satisfy the requirements of various stakeholders, this paper proposes time-based and cost-based aircraft scheduling optimization models for the on-ramp of the corridors-in-the-sky. An improved Particle Swarm Optimization (PSO) algorithm is also developed to solve a case study of the air route B215 in the Beijing control area. Computational results indicate that the optimized models have advantages in reducing the delay time and cost for both single aircraft and flight sequences, compared with the First-come, First-served (FCFS) approach. [ABSTRACT FROM AUTHOR]

A reasonable assessment of urban ecological resilience (UER), as well as quantitative identification of critical thresholds of UER, is an important theoretical basis for the formulation of scientific urban development planning. The existing UER assessment methods ignore the dynamic relationship between protection factors and disturbance factors in urban systems and do not address the question of where UER starts to become unstable. Therefore, based on the "source-sink" landscape theory, we constructed a UER assessment model and a method to quantitatively identify the UER's critical distance belt (UER-CDB) using the transect gradient analysis. Additionally, we combined scenario simulation to analyze the change characteristics of UER and its critical distance belt in different urban development directions over past and future periods. The results show that: (1) Based on the "source-sink" theory and transect gradient method, the UER can be effectively assessed and the UER-CDB can be quantitatively identified. (2) The UER in Beijing shows a distribution pattern of high in the northwest and low in the southeast, and the High resilience area accounts for more than 40%. (3) The changes in UER-CDB in Beijing in different development directions have obvious variability, which is mainly influenced by topography and policy planning. (4) Compared with the natural development scenario (NDS), the ecological protection scenario (EPS) is more consistent with Beijing's future urban development plan and more conducive to achieving sustainable development. The methodology of this paper provides a fresh perspective for the study of urban ecological resilience and the critical threshold of ecosystems. [ABSTRACT FROM AUTHOR]

China is internationalizing its higher education sector - setting up several bilateral and multilateral partnerships between public and private institutions across the globe. However, as the "West" is disentangling itself from partnerships with Chinese institutions of higher education and the Confucius Institutes (CIs), African countries seem to be turning to Beijing. As a result, China overtook France to become the most preferred destination for African students. But, is higher education Beijing's new strategy to enhance its global status? What is the effect of the shift toward Chinese higher education on Africa's migration trends, and what is the agency of actors in Africa? Focusing on these questions, and premised on the concepts of student mobility, South-South Cooperation (SSC), and people-to-people exchange to explain the novelty and exceptionality of the partnerships, this paper explores the typology, nature, and processes involved in these partnerships and collaborations. [ABSTRACT FROM AUTHOR]

The Palace Museum in Beijing manages a wealth of tangible and intangible cultural heritage, including the world-famous Forbidden City and many ancient collections. For the past thirty years, informatization has gradually become an important method in the Palace Museum to protect, promote, and research their precious cultural heritages. Although museum service quality and user experience and satisfaction have received growing attention, the quality control of museum digital information services remains a less explored research area. The challenges faced by the Palace Museum include how to follow changes in the technological environment, user needs, and the large scale of digital resources and how to continuously and effectively control and improve the service quality of digital information. This research, based on total quality management (TQM) and LibQUAL as well as the relevant indicators of museum quality assessment in the literature review, uses the Digital Cultural Relics Library Platform of the Palace Museum as the research case and constructs a user-centered control model to measure and improve the service quality of cultural heritage digital information, and puts the model into practice. The paper proposes theoretical advances and has implications for future improvements in the quality control of cultural heritage digital information services. [ABSTRACT FROM AUTHOR]

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Emergencies have a significant impact on the passenger flow of urban rail transit. It is of great practical significance to accurately predict the urban rail transit passenger flow and carry out research on its temporal and spatial distributions under emergency conditions. Urban rail transit operating units currently use video surveillance information mainly to process emergencies and rarely use computer vision technology to analyze passenger flow information collected. Accordingly, this paper proposes a passenger flow-based temporal and spatial distribution model for urban rail transit emergencies based on the CPT. First, this paper clarifies the categories and classification of urban rail transit emergencies, analyzes the factors affecting passenger route selection, and establishes a generalized travel cost model for passengers under emergencies. Second, this paper establishes a passenger route choice behavior model for urban rail transit based on the cumulative prospect theory. Finally, taking Beijing as an example, this paper analyzes passenger travel behavior under emergencies based on multiple logistic regression models and analyzes the impact of emergencies on rail transit travel behavior. The research results show that the cumulative prospect theory can better describe the route choice behavior of rail transit passengers under emergencies than the existing models, and this model is of great significance for handling urban rail transit emergencies. The model proposed in this paper can provide a theoretical basis for the government and relevant departments to formulate traffic management measures. [ABSTRACT FROM AUTHOR]

Online shopping has led to the rapid development of e-commerce, and at the same time, the pressure of offline distribution has increased abruptly. Therefore, a current development trend is to share end-to-end distribution against the background of the Internet. The main research content of this paper is the benefit distribution mechanism of shared end distribution. Based on an analysis of the current situation of interest distribution, this paper proposes factors that affect interest distribution from the perspectives of individuals and groups. The suitable income distribution mode of enterprise alliances is chosen from two dimensions—cooperation mode and coordination mechanism. Based on extant theory, this paper proposes a benefit distribution scheme-selection mechanism based on the modified Shapley value method and takes the terminal distribution in the Haidian District of Beijing as an example. The revised income distribution results better reflect the income-generating abilities of different enterprises within a cooperative organization and assign different benefit proportions to this cooperative organization based on different income-generating capacities to provide development incentives and, at the same time, better achieve income distribution. [ABSTRACT FROM AUTHOR]

Carsharing is regarded as a new mode of transportation that can meet the diversity of travel demands. Carsharing systems have different operating modes, and one-way systems are more widely used since cars can be dropped off at any station. However, their planning involves a series of joint decisions regarding the number, size, and location of stations, as well as the fleet size. This paper develops a data-driven mixed-integer linear programming (MILP) model for planning one-way carsharing systems that consider the spatial distribution of demand and the interacting decisions between stations. The characteristics of existing stations and their spatiotemporal correlations are an important part of the model. To solve the MILP model, the extension of the Benders decomposition algorithm is adopted. The practicality of the proposed approach is demonstrated in a case study in Beijing, China. The results show that the existing planning of carsharing could result in a serious waste of resources. In contrast, the proposed method can obtain effective results in a reasonable time. The location results corresponding to a different rate of satisfied demand show that increasing the parking spots to improve the interaction between stations can effectively reduce the cost of operations. It should be noted that this paper only considers the benefit of operators. Future works will be carried out to optimize the one-way carsharing system by considering the benefits of operators, as well as the benefits of users and society. In addition, the impact of COVID-19 will be taken into account in future modeling and case studies. [ABSTRACT FROM AUTHOR]

In order to forecast prices of arbitrary agricultural commodity in different wholesale markets in one city, this paper proposes a mixed model, which combines ARIMA model and PLS regression method based on time and space factors. This mixed model is able to obtain the forecasting results of weekly prices of agricultural commodities in different markets. Meanwhile, this paper sets up variables to measure the price changing trend based on the change of exogenous variables and prices, thus achieves the warning of daily price changes using neural networks. The model is tested with the data of several types of agricultural commodities and error analysis is made. The result shows that the mixed model is more accurate in forecasting agricultural commodity prices than each single model does, and has better accuracy in warning values. The mixed model, to some extent, forecasts the daily price changes of agricultural commodities. [ABSTRACT FROM AUTHOR]

Students’ college satisfaction is an important part of measuring the quality of college teaching. The admission of college entrance exam is the first step for college students to enter colleges and corresponding majors. Whether they affect students’ college satisfaction after enrollment is related to the formulation and adjustment of college admission strategies and training methods. This paper is based on data from students in colleges in Beijing enrolled in the fall of 2006 and 2008 and adopts propensity score matching to analyze the influence of the admitted characteristics of college entrance exams, such as whether they were accepted by their first choice. We also further explored the heterogeneity. The empirical results show that whether the student was admitted to the first-choice college has a significant positive impact on overall satisfaction and academic and nonacademic satisfaction, while whether the student was admitted to the firstchoice major has no significant impact on nonacademic satisfaction. In addition, making an independent major choice has a positive effect on the improvement of overall satisfaction and academic satisfaction, and the impact on overall satisfaction is even greater than that of being admitted to the first-choice major. The impact of the admission characteristics of college entrance examinations on the satisfaction of students in liberal arts and science and students of different types of colleges and universities presents different characteristics. [ABSTRACT FROM AUTHOR]

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

Intelligent connected vehicles (ICVs) have played an important role in improving the intelligence degree of transportation systems, and improving the trajectory prediction capability of ICVs is beneficial for traffic efficiency and safety. In this paper, a real-time trajectory prediction method based on vehicle-to-everything (V2X) communication is proposed for ICVs to improve the accuracy of their trajectory prediction. Firstly, this paper applies a Gaussian mixture probability hypothesis density (GM-PHD) model to construct the multidimension dataset of ICV states. Secondly, this paper adopts vehicular microscopic data with more dimensions, which is output by GM-PHD as the input of LSTM to ensure the consistency of the prediction results. Then, the signal light factor and Q-Learning algorithm were applied to improve the LSTM model, adding features in the spatial dimension to complement the temporal features used in the LSTM. When compared with the previous models, more consideration was given to the dynamic spatial environment. Finally, an intersection at Fushi Road in Shijingshan District, Beijing, was selected as the field test scenario. The final experimental results show that the GM-PHD model achieved an average error of 0.1181 m, which is a 44.05% reduction compared to the LiDAR-based model. Meanwhile, the error of the proposed model can reach 0.501 m. When compared to the social LSTM model, the prediction error was reduced by 29.43% under the average displacement error (ADE) metric. The proposed method can provide data support and an effective theoretical basis for decision systems to improve traffic safety. [ABSTRACT FROM AUTHOR]

Nowadays, sustainability-related issues have attracted growing attention due to fossil fuel depletion and environmental concerns. Considering many cities have gradually replaced taxis with electric vehicles (EVs), to reduce greenhouse gas emissions and traditional energy consumption, this paper studies the optimization strategy of battery swapping for electric taxis (ETs), and it is not only to ease congestion in the battery swapping station (BSS) but also for electric taxis to address their range anxiety and maximize their benefits. Firstly, based on the road network, the Dijkstra algorithm is adopted to provide the optimal path for ETs to BSSs with the minimum energy consumption. Then, this paper proposes the optimization objective function with minimum cost, which contains the battery service cost based on the battery's state of charge, waiting cost caused by waiting for swapping battery in BSSs and the carbon emission reduction benefit generated during ETs driving to BSSs, and uses a mixed-integer linear programming (MILP) algorithm to solve this function. Finally, taking the Leisure Park of Laoshan City in Beijing as an example, the numerical simulation is carried out and the proposed battery swapping strategy is efficient to alleviate the congestion of BSSs and maximize the total benefit of ETs, and the cost based on the proposed strategy is 14.21% less than that of disorderly swapping. [ABSTRACT FROM AUTHOR]

This paper examines the effects of interventions to reduce air pollution during two international events on air quality in Beijing and its neighbor cities. Air quality data were gathered from China's Ministry of Environmental Protection, meteorological data from the China Meteorological Administration and economic data from the China Statistical Yearbook. The paper uses fixed-effect panel data models to empirically evaluate air quality improvement in Beijing and other affected cities before, during, and after the 2008 Olympic Games and the 2014 Asia-Pacific Economic Cooperation summit. Results show substantial improvement in air quality in Beijing and neighboring cities during the two events. However, some of the air quality improvement achieved reverted within a year after the games and within a week after the summit. Furthermore, the improvement achieved during the summit completely reverted and air quality deteriorated severely five days after the summit. It is also found that air quality in China, at least in the cities included in this study, gradually improved over the past 15 years or so. The findings suggest that sustainable interventions and incentive-based programs to reduce emissions from industry production and traffic are the key to maintaining the air pollution reduction achieved during the events. [ABSTRACT FROM AUTHOR]

Air quality plays a vital role in people's health, and air quality forecasting can assist in decision making for government planning and sustainable development. In contrast, it is challenging to multi-step forecast accurately due to its complex and nonlinear caused by both temporal and spatial dimensions. Deep models, with their ability to model strong nonlinearities, have become the primary methods for air quality forecasting. However, because of the lack of mechanism-based analysis, uninterpretability forecasting makes decisions risky, especially when the government makes decisions. This paper proposes an interpretable variational Bayesian deep learning model with information self-screening for PM2.5 forecasting. Firstly, based on factors related to PM2.5 concentration, e.g., temperature, humidity, wind speed, spatial distribution, etc., an interpretable multivariate data screening structure for PM2.5 forecasting was established to catch as much helpful information as possible. Secondly, the self-screening layer was implanted in the deep learning network to optimize the selection of input variables. Further, following implantation of the screening layer, a variational Bayesian gated recurrent unit (GRU) network was constructed to overcome the complex distribution of PM2.5 and achieve accurate multi-step forecasting. The high accuracy of the proposed method is verified by PM2.5 data in Beijing, China, which provides an effective way, with multiple factors for PM2.5 forecasting determined using deep learning technology. [ABSTRACT FROM AUTHOR]

This paper constructs a matching index model to research the matching degree of embodied carbon trade and value-added trade among eight regions and 31 provinces in China in 2012 and 2015. The study finds that (1) At the regional level, a mismatch is shown between embodied carbon trade and value-added trade among regions, for example, in 2015, the northwest region has output embodied carbon to the north coast, while input the value-added trades from the north coast. (2) At the provincial level, a mismatch is displayed between embodied carbon transaction and value-added trade, for example, Beijing had a net shift of embodied carbon from Xinjiang in 2015, but Xinjiang had a net transfer of added value from Beijing. Therefore, the Chinese government needs to establish an ecological compensation mechanism to improve the mismatch between embodied carbon trade and value-added trade among Chinese regions (provinces). [ABSTRACT FROM AUTHOR]

Background: Classic locational principles predict a picture of urban intensity decaying from the city center to the periphery under ideal assumptions. However, various exogenous factors can influence the real-world urban intensity and often deviate from the theoretical pattern. The specific mechanisms are worthy of exploration and are of potential theoretical and practical significance. Methods: In this paper, we consider two city districts with typical urban locations, namely, Changping and Chaoyang in Beijing, and construct mechanistic models of the status quo urban intensity (floor area ratio, FAR) utilizing multisource spatiotemporal big data. We further compare these models with the "theoretically ideal" FAR patterns as would be predicted by applied locational theories. Results: We find that the status quo FAR distribution generally conforms to the theoretical predictions but still exhibits regional deviations that can be explained by historical inertia and influence from particular policies. Conclusion: We conclude this paper with discussions on the findings' methodological and practical implications for urban planning institutions, especially in a transition economy context. [ABSTRACT FROM AUTHOR]

At present, in the field of geotechnical engineering and agricultural production, with increasingly serious pollution an environmentally friendly and efficient means is urgently needed to improve the soil mass. This paper mainly studied the microbial induced calcium carbonate precipitation (MICP) technology and the combined effect of MICP technology and lignin on the improvement of silt in the Beijing area. Through unconfined compressive strength and dynamic triaxial test methods, samples improved by microorganisms were studied to obtain the optimal values of cement concentration and lignin under these two test schemes. The results show that after the incubation time of Sporosarcina pasteurii reached 24 h, the OD600 value was 1.7–2.0 and the activity value (U) was 930–1000 mM ms/min. In the unconfined static pressure strength test, after MICP treatment the optimal concentration of cementitious solution for constant temperature and humidity samples and constant-temperature immersion samples was 1.25 mol/L. The compressive strength of the constant temperature and humidity sample was 1.73 MPa, and the compressive strength of the constant-temperature immersion sample was 3.62 Mpa. At the concentration of 1.25 mol/L of cement solution, MICP technology combined with lignin could improve the constant temperature and humidity silt sample. The optimal addition ratio of lignin was 4%, and its compressive strength was 1.9 MPa. The optimal lignin addition ratio of the sample soaked at a constant temperature was 3%, and the compressive strength was 4.84 MPa. In the dynamic triaxial multi-stage cyclic load test, the optimal concentration of cementation solution for the constant temperature and humidity sample after MICP treatment was 1.0 mol/L, and the failure was mainly inclined cracks. However, in the condition of joint improvement of MICP and lignin, the sample mainly had a drum-shaped deformation, the optimal lignin addition ratio was 4%, and the maximum axial load that the sample could bear was 306.08 N. When the axial dynamic load reached 300 N, the strain accumulation of the 4% group was only 2.3 mm. In this paper, lignin, an ecofriendly material, was introduced on the basis of MICP technology. According to the failure shape and relevant results of the sample, the addition of lignin was beneficial for the improvement of the compressive strength of the sample. [ABSTRACT FROM AUTHOR]

Guqin is the Chinese oldest musical instrument and intangible cultural heritage. The Tang Dynasty was the most prosperous in Chinese history, with a flourishing culture. One of the Guqin manufactured by Master Lei Wei, a notable Guqin maker in the Tang Dynasty, was recognized as a reference standard instrument and is kept in the Palace Museum in Beijing. Stradivari, a well-known Italian violin maker, has created and improved violins that no one else can surpass. Triangulation laser and CT/CBCT Scanner-Based 3D modelling data-driven analysis of the ancient musical instrument Guqin from the Tang Dynasty has been compared with the Italy Stradivari violin in a historical review perspective in this paper. After delving into the wood, spatial structure, and other aspects of the Stradivari violin, it has been discovered that the wood, paint, and inner cavity design used by the two masters during their respective heydays are strikingly similar, revealing their shared experience in creating ancient musical instruments in their countries. The bass bar of a Stradivari violin is meant to be transplanted into a Chinese Guqin prototype and get the conclusion that the timbre of the Guqin can be improved according to MATLAB spectrum analysis. This is the first time the two masters from Eastern and Western comparison analysis after the millennium. [ABSTRACT FROM AUTHOR]

Day by day pollution in cities is increasing due to urbanization. One of the biggest challenges posed by the rapid migration of inhabitants into cities is increased air pollution. Sustainable Development Goal 11 indicates that 99 percent of the world's urban population breathes polluted air. In such a trend of urbanization, predicting the concentrations of pollutants in advance is very important. Predictions of pollutants would help city administrations to take timely measures for ensuring Sustainable Development Goal 11. In data engineering, imputation and the removal of outliers are very important steps prior to forecasting the concentration of air pollutants. For pollution and meteorological data, missing values and outliers are critical problems that need to be addressed. This paper proposes a novel method called multiple iterative imputation using autoencoder-based long short-term memory (MIA-LSTM) which uses iterative imputation using an extra tree regressor as an estimator for the missing values in multivariate data followed by an LSTM autoencoder for the detection and removal of outliers present in the dataset. The preprocessed data were given to a multivariate LSTM for forecasting PM2.5 concentration. This paper also presents the effect of removing outliers and missing values from the dataset as well as the effect of imputing missing values in the process of forecasting the concentrations of air pollutants. The proposed method provides better results for forecasting with a root mean square error (RMSE) value of 9.8883. The obtained results were compared with the traditional gated recurrent unit (GRU), 1D convolutional neural network (CNN), and long short-term memory (LSTM) approaches for a dataset of the Aotizhonhxin area of Beijing in China. Similar results were observed for another two locations in China and one location in India. The results obtained show that imputation and outlier/anomaly removal improve the accuracy of air pollution forecasting. [ABSTRACT FROM AUTHOR]

This paper examines the relationship between property return and seller behavior and aims to test the disposition effect in China's real estate market. Using transaction data in Beijing, we find that loss properties have a lower sell propensity relative to gain properties, confirming the existence of the disposition effect. We also find that the disposition effect is more pronounced in samples with shorter holding periods. Sellers with financial constraints and popular projects are more likely to show the disposition effect. Furthermore, we find that sellers exhibit loss aversion; specifically, sellers with loss properties are likely to set a higher listing price, which provides indirect evidence for the disposition effect. [ABSTRACT FROM AUTHOR]

This paper aims to examine the contents of professional architectural books on worker residential areas in the Soviet Union, analyzing proposals based on the Northeast China's experience during the First Five‐Year Plan. Despite sharing a common source for residential design, differences in regional and situational conditions result in diversity between China and the Soviet Union. By considering the plan for worker residential areas in Beijing and analyzing the case of the planned Beijing No. 2 textile factory in 1953, it can be concluded that China had already developed original residential planning ideas and methods during that period. [ABSTRACT FROM AUTHOR]

Provides information on predictions extracted from a keynote address given by the author, at the closing session of the 10th World Conference on Tobacco or Health, in Beijing, China during August 24-28, 1997. INSET: The conference response to the proposed U.S. tobacco settlement.

The article presents a sensitivity study on aerosol retrieval algorithm of Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL). It focuses on aerosol mixtures composed of fine mode pollution particles combined with coarse mode desert dust. It examines the PARASOL aerosol products during the period 2005-2009 by comparing it with aerosol optical depth (AOD) derived by Aerosol Robotic Network in Beijing, China and Kanpur, India.

Zhang, J.; Zhang, Y.; Sun, S.-J.; Zhang, W.-W., and Zhang, S.-H., 2019. Analysis of the effect of low impact development on urban runoff control based on the SWMM model. In: Yu, T.-s. (ed.), Environmental Sustainability: Water Resources Integrated Management and the Development of Coastal Environments. Journal of Coastal Research, Special Issue No. 96, pp. 62-67. Coconut Creek (Florida), ISSN 0749-0208. In order to solve the problems of frequent urban flood disasters and the continuous deterioration of the water environment in the process of urbanization, the urban storm flood management method centered on Low Impact Development (LID) has become a new concept in urban construction. Taking one residential area in Beijing as the research object, and on the basis of the Storm Water Management Model (SWMM), this paper simulates and analyzes the effect of LID measures on runoff control under different rainfall conditions, and deduces the functional relationship between the LID scale and runoff reduction. The results show that the runoff reduction rate decreases with the increase in rainfall level, and LID measures have the most obvious effect on runoff quantity reduction while having a small effect on the peak time delay. The research methods and results of this paper can provide a reference for sponge city construction, flood control and drainage management. [ABSTRACT FROM AUTHOR]

In China, with the rapid development of economy and the advancement of urbanization, the deterioration of urban ecological environment is obvious. In order to obtain the quantitative state of urban ecological security, this paper contributes an integrated and coupled emergy ecological footprint framework and Beijing city was selected to verify methodology effect in this paper. The results demonstrate that: (1) from 2010 to 2019, the change range of EEFB is from 6.37 to 9.29%; meanwhile, EEFI is from 7.95 to 17.72%; EEFE is from 36.36 to 63.71%; EEFP is from 18.45% to 41.65%. Comparing the proportions of four subparts, the energy resource products (EEFE) and emissions (EEFP) are the main factors, far more significant than biological resources (EEFB) and industrial products (EEFI). (2) Compared to all ECCS data, there is a definite growing trend in Beijing city, from 2.68E + 4 hm2/cap in 2010 to 4.72E+4 hm2/cap in 2019, approximately 42.22% growth range. (3) Four sustainable indicators analysis: The changes of EEFT, EBI, and EEF are from 3.1, 2.46, and 1.02 in 2010 to 0.688, 9.29 and 1.14 in 2019, respectively. For EDI, total proportions of fossil land and built-up land are 85.25% to 90.43% of the entire EEF in Beijing city. These results reflect that Beijing city is suffering from a substantial ecological challenge due to remarkable ecological deficit, awfully high emergy ecological footprint intensity, and low cooperation level between ecological system and economic system. To identify key improvement factors, Pearson correlation analysis was conducted in this paper and revealed the most positive and negative elements, which are the unbalanced industrial structure and a large proportion heavy and polluting industries in Beijing city. Finally, based on the pivotal influencing factors, corresponding strategies and measures are proposed to improve and optimize the ecological security in Beijing city. [ABSTRACT FROM AUTHOR]

The development of connected and autonomous vehicle (CAV) technology has received increasing attention in recent years. Although car-following behavior in mixed traffic with CAVs and human-driven vehicles (HDVs) is a core component of microscopic traffic simulation, intelligent traffic systems, etc., the current study of car-following behavior in mixed traffic has some limitations. Furthermore, actual data do not support its applicability to the Chinese traffic environment. To address this gap, this paper designs and organizes a car-following experiment in mixed traffic in Beijing, extracts the trajectory data of CAVs and HDVs based on video recognition, and reconstructs the extracted trajectory data using the Lagrangian theory and Kalman filter theory to ensure the accuracy of the data. Based on this data set, this paper develops an extended car-following model. The model considers the cooperation between drivers by reformulating the prospect theory (PT). The root mean square percentage error (RMSPE) is selected to calibrate and validate the parameters of the proposed model, and the results show that there is significant heterogeneity between CAVs and HDVs in mixed traffic, and the proposed model captures this heterogeneity well. The model presented in this paper provides theoretical support for microscopic traffic simulation in mixed traffic. [ABSTRACT FROM AUTHOR]

In the process of development, global economies are prioritizing environmental protection and firms are also recognizing the importance of minimizing environmental impact during production along with maximization of profits through green investments. It is vivid that green investments are vital for environmental preservation. So this paper contributes to literature by investigating the role of internal and external factors affecting the decision making of Chinese firms regarding adoption of green investments and impact of green investments on environmental, social, and economic performance of firms. The data is collected from directors/senior managers of the firms. We received 463 valid responses from listed companies with Shenzhen, Beijing, and Shanghai Stock Exchange. The "structural equation modeling" with "maximum likelihood estimation" is employed for empirical analysis. The empirical findings reveal that adaptation to climate change and its mitigation is the most important driver of green investment. Moreover, green investment positively contributes to enhancing the social, economic, and environmental performances of Chinese firms. Based on the findings of the study, green investment should be adopted as a corporate strategy by firms for profit maximization, competitive advantage, and improvement in social well-being without compromising the environment. Policy makers can promote green investment by offering policy instruments such as tax incentives, guaranteed credits, grants, and investor education. Training courses may be offered to raise environmental awareness among firms and the general public. [ABSTRACT FROM AUTHOR]

As the demand for private vehicles rises, there has been a gradual increase in the number of motor vehicles on the roads, leading to a growing concern about addressing traffic safety. Currently, China's approach to assessing driver capabilities remains rooted in traditional, non-intelligent, and standardized evaluation methods based on examination subjects. The traditional model often falls short in providing constructive feedback on a driver's real-world vehicle handling abilities, as many of the examination subjects can be practiced in advance to achieve a mere passing result, which, undoubtedly, increases the likelihood of underqualified drivers on the road. To address the issues of the current examination-oriented driver evaluation system in China, we propose a road performance assessment model (RPAM) that assesses drivers comprehensively by evaluating their road environment perception and vehicle operation abilities based on an in-vehicle and out-vehicle perception system. The model leverages patterns of the driver's head posture, along with real-time information on the vehicle's behavior and the road conditions, to quantify various performance metrics related to reasonable operation processes. These metrics are then integrated to generate a holistic assessment of the driving capabilities. This paper ultimately conducted tests of the RPAM on one actual examination route in Beijing. Two drivers were randomly selected for the examination. The model successfully computed the overall ability scores for each driver, validating the effectiveness. [ABSTRACT FROM AUTHOR]

Geological hazards often occur in mountainous areas and are sudden and hidden, so it is important to identify and assess geological hazards. In this paper, the western mountainous area of Beijing was selected as the study area. We conducted research on landslides, collapses, and unstable slopes in the study area. The surface deformation of the study area was monitored by multi-temporal interferometric synthetic aperture radar (MT-InSAR), using a combination of multi-looking point selection and permanent scatterer (PS) point selection methods. Random forest (RF), support vector machine (SVM), convolutional neural network (CNN), and recurrent neural network (RNN) models were selected for the assessment of geological hazard susceptibility. Sixteen geological hazard-influencing factors were collected, and their information values were calculated using their features. Multicollinearity analysis with the relief-F method was used to calculate the correlation and importance of the factors for factor selection. The results show that the deformation rate along the line-of-sight (LOS) direction is between −44 mm/year and 28 mm/year. A total of 60 geological hazards were identified by combining surface deformation with optical imagery and other data, including 7 collapses, 25 unstable slopes, and 28 landslides. Forty-eight of the identified geological hazards are not recorded in the Beijing geological hazards list. The most effective model in the study area was RF. The percentage of geological hazard susceptibility zoning in the study area is as follows: very low susceptibility 27.40%, low susceptibility 28.06%, moderate susceptibility 21.19%, high susceptibility 13.80%, very high susceptibility 9.57%. [ABSTRACT FROM AUTHOR]

• To solve the forecasting problems of time-lead and nonlinearity in a system, a novel grey multivariable model is proposed. • To reduce the morbidity of the model, the solution of the proposed model is deduced through a derivation method. • The grey prediction evolution algorithm is employed to find the optimal value of parameters. • The validity of the new model was verified by three examples and applied to house price forecasting. Time lags or leads and non-linearity of complex systems are critical to address in accurate scientific prediction. However, few studies have focused on time-lead and nonlinear models with limited information. Therefore, this paper aims to develop a novel grey multivariate model with time-lead operator τ and nonlinear factor r from the perspective of this problem. Next, the solution of the proposed model is deduced through a derivation method to reduce the morbidity of the model. Then, the parameter identification of the model is given on the basis of the least-squares method. The grey prediction evolution algorithm is employed to find the optimal value of parameters τ and r to meet the minimum errors. Finally, house prices of Wuhan, Beijing and Shanghai in China are performed to verify the validity and reliability of the new model. The results demonstrate the model we proposed has satisfactory prediction precision, demonstrating that time-lead and nonlinear factor in the model is reasonable. At the end of the paper, the house prices of these three cities from 2022 to 2028 are also predicted. The average annual growth rate in the three regions is 2.49%, 3.57% and 2.97%, respectively. These results are useful to policy analysis regarding house price correlations. They provide insights for market investors and policy makers. [ABSTRACT FROM AUTHOR]

During the "Parade Blue" period in 2015, Beijing and its surrounding areas implemented mandatory temporary source control strategies, which provided experimental conditions for studying the effects of source emission control measures on the sources of atmospheric PM2.5. Analyzing the source contribution rate of the main particulate matters via the source analysis method of the receptor model is an important method for studying the atmospheric pollution. Previous studies on the "Parade Blue" period only discussed the change in PM2.5 concentration during the source control period and the source non-control period, but did not select appropriate emission sources and acceptor components to analyze the contribution ratio of each emission source to fine particulate matter pollution. In this paper, based on the receptor component spectrum and emission source component spectrum, the chemical mass balance receptor model was used for source analysis. The results showed that outdoor PM2.5 concentration was 26.31 μg/m3 in the source control period, which was less than the 40.08 μg/m3 in the source non-control period. In the source control period, motor vehicle emissions, industrial combustion and urban fugitive dust contributed significantly to the fine particulate pollution, accounting for 76–81%, 8–9% and 11–16%, respectively. In the source non-control period, the contributions of motor vehicle emissions and industrial combustion accounted for 57–59% and 41–43%, respectively, significantly higher than that of urban fugitive dust, which accounted for less than 2%. The correlation between the contribution rate of emission sources and the source control strategy was studied and analyzed during the "Parade Blue" period, and the effectiveness of the source control strategy was proved. [ABSTRACT FROM AUTHOR]

With the continuous development of the Automatic Train Operation (ATO) system in high-speed railways, automatic driving is progressively supplanting manual operations, ushering in a new era of predictability and reliability for high-speed railway transport. Concurrently, the advent of the ATO system provides a notable impact on real-time rescheduling during disruptions, as it equips dispatchers with precise insights into train operation statuses. This paper is dedicated to a thorough analysis of how the transition to automatic driving in train operations influences the real-time rescheduling model. Based on the distinctive impact of the ATO system on real-time rescheduling, we have proposed a mixed-integer linear programming model that combines train re-timing, reordering, and the minimization of passenger delays. To validate the effectiveness of our model, we present several experiments conducted using data from the Beijing–Shanghai high-speed railway line. The results unequivocally demonstrate that our ATO-based model significantly mitigates train delay time, demonstrating its practical value in optimizing high-speed railway operations. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is one of the most important parameters of the interface between the earth surface and the atmosphere, and it plays a significant role in many research fields, such as agriculture, climate, hydrology, and the environment. However, the thermal infrared band of remote sensors is easily affected by clouds and aerosols, leading to many data gaps in LST products, which restricts the subsequent application of these products. In this paper, Beijing, China, is selected as the study area, and the LST data retrieved from Fengyun 4A (FY-4A) Advanced Geosynchronous Radiation Imager (AGRI) are reconstructed based on the two-point machine learning method. Firstly, the two-point machine learning model is built to reconstruct the theoretical clear-sky LST from simulated and actual images, and the accuracy of the reconstruction results is evaluated compared with the random forest algorithm and the inverse distance weighted method. Secondly, the actual LST under the influence of clouds is reconstructed by using the ERA5 reanalysis LST data as the auxiliary data, and the reconstruction accuracy is then evaluated by the field measurement LST data. The experimental results show that (1) the prediction accuracy of the two-point machine learning method is higher than that of the random forest method in both simulated data and actual data experiments; (2) the R2 of reconstructed LST under theoretical clear-sky conditions is 0.6860 and the root mean square error (RMSE) is 2.9 K, while the R2 of the reconstructed accuracy of actual LST under clouds is 0.7275 and the RMSE is 2.6 K, i.e., the RMSE decreases by 10.34%; (3) the two-point machine method combined with the auxiliary ERA5 LST data can well reconstruct LST under cloudy conditions and present a reasonable LST distribution. [ABSTRACT FROM AUTHOR]

Based on the resonance fluorescence scattering mechanism, a narrowband sodium (Na) lidar can measure temperature and wind in the mesosphere and lower thermosphere (MLT) region. By using a narrowband spectral filter, background light noise during the day can be suppressed, allowing for continuous observations. To obtain full-diurnal-cycle temperature and wind measurement results, a complex and precise retrieval process is required, along with necessary corrections to minimize measurement errors. This paper introduces the design of a data acquisition unit for three frequencies in three directions of the Na lidar system in the Chinese Meridian Project (Phase II) and investigates the calibration and retrieval methods for obtaining diurnal temperature and horizontal wind in the MLT region, using a Na Doppler lidar with Faraday anomalous dispersion optical filter (FADOF). Furthermore, these methods are applied to observations conducted by a Na lidar in Beijing, China. The wind and temperature results over full diurnal cycles obtained from the all-solid-state Na Doppler lidar are reported for the first time and compared with temperature measurements from satellite, as well as wind observations from a meteor radar. The comparison demonstrates a reasonable agreement between the results, indicating the rationality of the lidar-retrieved results and the feasibility and effectiveness of the data correction and retrieval method. [ABSTRACT FROM AUTHOR]

Since the 18th National Congress of Chinese Communist Party, ecological civilization construction has been incorporated into Five-sphere Integrated Plan, that is, to promote coordinated progress in the economic, political, cultural, social, and eco-environmental fields. The Chinese government has proposed the goal of "carbon peak" and "carbon neutrality". Low-carbon transportation becomes the mainstream. To achieve carbon peak and carbon neutrality in public transport, this paper takes Beijing's public transport sector as a case study, using system dynamics model with relevant policies and the current situation. It calculates and predicts carbon emissions under electric vehicle substitution scenario, clean energy generation, and carbon capture, utilization and storage scenario for the period of 2020–2060. The following main conclusions are obtained: Direct carbon emissions have peaked and started to decline based on the current measures, while indirect carbon emissions have peaked and started to decline under the suggested intervention. The direct carbon emissions peaked at 2.58005 × 106 tons in 2014. The indirect carbon emissions peaked at 1.59027 × 106 in 2025. They all achieved carbon neutrality under the suggested intervention. Electric vehicle substitution and carbon capture, clean energy generation, utilization and storage are the main factors of carbon emission reduction. The outcomes of this study can provide essential information for policy-makers to advance Beijing's future low-carbon development in public transport. The electric vehicle substitution, clean energy generation and carbon capture, utilization and storage provide a new perspective to research carbon emissions in the transport sector. [ABSTRACT FROM AUTHOR]

With the decarbonization of the transportation sector and the diversification of travel demand, the development of shared electric vehicles has become crucial. Based on survey data of travel mode and destination of shared electric vehicles in Beijing, this paper aims to explore the formation and distribution mechanisms of the demand for shared electric vehicles. First of all, a multi-index and multi-cause (MIMIC) model was established to quantify the psychological latent variables that cannot be directly observed and to analyze the mechanisms between individual socio-demographic attributes and latent variables. Secondly, these psychological latent variables were added to mixed logit (ML) models as explanatory variables to form hybrid choice models to explore the travel mode choice behavior and travel destination choice behavior, respectively, when using shared electric vehicles for leisure travel. The results show that potential users of shared electric vehicles are characterized by higher education, employees of enterprises, no car availability and high driving years, and most of them travel for the purpose of connecting to transport hubs. Latent variables such as individual carbon trading, subjective norms, risks and behavioral intentions all affect the demand for shared electric vehicles; in-car time, out-of-car time, travel cost and the number of subway stations have negative impacts on the demand, while mall properties and the number of parking lots have positive impacts on the demand. Furthermore, the use of shared electric vehicles is highly correlated with the use of cars and subways, and part of the travel demand could be transferred to shared electric vehicles by taking certain measures. [ABSTRACT FROM AUTHOR]

Suburban railways in megacities exert a pivotal role in propelling urbanization and shaping urban agglomeration. However, previous study endeavors have overlooked the transformations occurring in urban expansion along suburban railways, with a particular dearth of attention on the spatio-temporal evolution of landscape ecology and urban function. Therefore, this study employs the megacity of Beijing as an example. It utilizes remote sensing and point-of-interest (POI) data spanning from 2008 to 2022 to construct an indicator system from two essential dimensions: urban form and function. We explored the spatio-temporal characteristics of alterations in urban expansion within the gradient buffer zone adjacent to the suburban railway network in Beijing. The results showed that: (1) The rates of urban expansion were highest in 2008–2013 and lowest in 2013–2018; moreover, suburban railways had the greatest impact on the built-up area within 2–4 km along the route, and the impact gradually decreased beyond 4 km. (2) The direction of urban expansion shifted northward in the direction of latitude and eastward in the direction of longitude from 2008 to 2022, with the shift in latitude being more distinct. (3) The number of urban functions gradually increased from 2008 to 2018, but the number of medical services suddenly increased and the number of other urban functions decreased from 2018 to 2022; in addition, urban functions other than scenic spots were mainly distributed in the main urban areas, with very few clusters distributed near stations. (4) The landscape shape index became more irregular and fragmented from the center along the route to the edge of the buffer zone from 2008 to 2013, and the degree of fragmentation was highest in the 2–4 km buffer zone. In summary, this paper analyzes the spatio-temporal characteristics of urban expansion along suburban railways through four indexes, namely expansion rate, expansion direction, urban function, and landscape shape, and the results of this study are of great significance to the development and planning of suburban railways in megacities. [ABSTRACT FROM AUTHOR]

Based on the provincial statistical data of the Beijing-Tianjin-Hebei region this paper uses the health distance model and obstacle degree model to explore the spatiotemporal mismatch of the development of the Beijing-Tianjin-Hebei regional innovation chain and analyzes the obstacle factor affecting the healthy development of Beijing-Tianjin-Hebei innovation chain. The results show that: (1) In terms of timing characteristics, the overall mismatch of the innovation chain in the Beijing-Tianjin-Hebei region shows a downward trend, and the absolute and relative difference of regional mismatch both show a "V" shaped development trend, which first decreases and then increases. (2) In terms of spatial characteristics, the mismatch of the innovation chain in the Beijing-Tianjin-Hebei region develops from unbalanced to balanced and then unbalanced, and the spatial pattern evolves from low in the middle and high around to high in the southeast and low around. (3) In terms of the obstacle factors, scientific research and development institutions, the number of college students, and the number of innovation platforms at or above the provincial and ministerial level are the obstacle factors to the more frequent occurrence. Plain Language Summary: preface This study aims to examine the spatio-temporal differentiation of the regional innovation chain in the Beijing-Tianjin-Hebei region of China. It investigates the mismatch between different components of the innovation chain and analyzes the factors that hinder its healthy development. The research utilizes the entropy method, health distance model, and obstacle degree model to calculate and analyze the innovation chain mismatch. Arc GIS geometric method is employed to divide the mismatch into different levels. Data from 2015 to 2019 is used to assess the evolution of the innovation chain mismatch over time and across different regions. The study reveals that the innovation chain mismatch in the Beijing-Tianjin-Hebei region has shown a declining trend during the study period. The overall mismatch has weakened, indicating significant progress in the coordinated development of the region. Beijing has played a leading role, while Tianjin and Hebei Province have also witnessed improvements, although to a lesser extent. The development difference among the three regions has been reduced, but significant disparities still exist. The findings highlight the importance of regional collaboration in promoting innovation chain development. The study provides insights for policymakers and stakeholders to enhance the coordination and integration of innovation activities in the Beijing-Tianjin-Hebei region. It emphasizes the need for further efforts to reduce development disparities and enhance the efficiency of innovation development. It is important to note that this study focuses specifically on the Beijing-Tianjin-Hebei region, and the findings may not be directly applicable to other regions or countries. The analysis is based on available data and selected models, which may have certain limitations and assumptions. Further research is needed to explore additional factors and dynamics influencing the innovation chain in the region. [ABSTRACT FROM AUTHOR]

How to promote and improve the level of urban innovation cooperation is a major issue in China's current high-quality economic development. Thus, enhancing innovation ability is essential to achieving high-quality economic growth under the "new normal". Based on the data of Chinese invention patents from 1985 to 2017, this paper analyzes the characteristics of China's urban innovation cooperation network and the different roles of proximity by using social network analysis and exploratory spatial data analysis methods. The analysis results show that: (1) On the whole, the development of China's urban innovation cooperation network is characterized by stages (initial development stage, rapid development stage, and gradual decline stage); The urban innovation cooperation network has strong connectivity and centripetal concentration but its imbalance needs to be further improved; The degree of urban participation has gradually increased, consolidating the stability of the network structure. (2) The centrality of urban innovation cooperation network has obvious characteristics of administrative center orientation, coastal areas orientation, and 'strong east and weak west'; Beijing is the center and bridge of the network, and the network flattening characteristics are obvious; A hierarchical 'core-edge' structure is gradually formed for the urban innovation cooperation network, and the pyramid structure with Beijing standing at the top is being consolidated. (3) The geographical proximity presents a significant global spatial positive correlation, while the network proximity and pure network proximity have a more significant global spatial negative correlation; The local spatial autocorrelation of China's urban innovation cooperation system based on network proximity is more obvious and identifiable than that based on the geographical proximity, which better reflects the new development model of "relationship economy". [ABSTRACT FROM AUTHOR]