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The travel efficiency of public transportation is a key indicator for judging whether the quality of public transportation has developed compared with other modes of transportation, especially private vehicles. The quality of public transportation is also an important reference factor for residents' choices. With the rapid urban expansion and improvement in motorized travel levels, reducing the time difference between private vehicles and public transportation is the key to improving the attractiveness of public transportation. The relative spatiotemporal efficiency is based on the time difference between private vehicles and public transportation, considering the number of passengers. Recently, scholars have shown great interest in relative travel efficiency. However, relevant studies have shown poor real-time performance because of the unavailability of large datasets, which cannot dynamically reflect the characteristics of relative travel efficiency. The spread of big data and internet maps enables us to perform systematic efficiency evaluations. The internet map incorporates various travel-related information such as travel route, time, and cost under different travel modes based on real-time road conditions and provides access to the extracted embedded travel information. This study proposes a framework for evaluating the spatiotemporal efficiency of different travel modes based on real-time road conditions in Shenzhen. First, travel time data were obtained using an internet map during the morning, afternoon, and evening rush hours. The passenger flow volume was computed using smart card data. We then constructed an evaluation index model of spatiotemporal efficiency based on the relative time efficiency and weighted passenger flow volume. Finally, the results highlighted the following: 1) the relative time efficiency of public transportation was higher during the evening rush hours than in the morning. The main reason was the increase in private vehicle travel time during the evening rush hours, reflecting the complexity of urban road conditions during the evening; 2) the spatiotemporal efficiency index of central public transport stations fluctuated greatly during the three periods, which was closely related to the dynamics of traffic volume caused by the high concentration of workplaces; 3) the spatiotemporal efficiency index of public transportation stations exhibited spatial aggregation characteristics in the three periods, highlighting the different clustering characteristics in the central and outer areas; 4) the spatiotemporal efficiency index of subway stations was generally higher than that of bus stations, reflecting the importance of subway systems in urban transportation networks. Evaluating the relative travel efficiency of urban public transport contributes to analyzing the development status of public transportation, supporting decisions to achieve high-quality development of public transport, and providing travel information for the government and residents.

On the basis of fully understanding the scientific connotation of coordinated development of urban agglomeration in the Guangdong-Hong Kong-Macao Greater Bay Area, the evaluation index system of coordinated development is constructed from four dimensions: industrial coordinative innovation, environmental coordinative governance, service coordinative sharing and institutional coordinative arrangement. The theory and method of space of flows, big data, network analysis and interlocking network model are comprehensively used to quantitatively analyze the interurban relationship, liquidity, connectivity and boundary effect. The research shows that: 1) Interurban capital flow is concentrated between Guangzhou and Shenzhen, and interurban knowledge flow is concentrated among Hong Kong, Guangzhou and Shenzhen. Macao, Zhuhai, Zhongshan and Jiangmen have higher level of collaborative environmental governance, while Shenzhen-Dongguan-Huizhou and Guangzhou-Foshan have lower level of collaborative environmental governance. The interurban service coordination sharing level of infrastructure such as transportation, communications, logistics and banking is higher among cities of Guangzhou-Shenzhen, Guangzhou-Foshan and Shenzhen-Dongguan. And Hong Kong and Macao have institutional advantages in cross-border regional coordination. 2) Guangzhou and Shenzhen, Guangzhou and Foshan, Shenzhen and Dongguan, and Hong Kong and Shenzhen have the best level of coordinated development in the Guangdong-Hong Kong-Macao Greater Bay Area. At the same time, Guangzhou and Dongguan, Shenzhen and Foshan show a linkage trend. Although the de-boundary trend is obvious and the interurban liquidity is enhanced, the coordinated development level of the Guangdong-Hong Kong-Macao Greater Bay Area is generally not high. 3) The collaborative capacity of Guangzhou and Shenzhen is the strongest, and there is still much room for improvement in the collaborative capacity of the two international cities, Hong Kong and Macao. It is of great practical value to deeply understand the typical characteristics and potential trends of the coordinated development of urban agglomeration in the Guangdong-Hong Kong-Macao Greater Bay Area for the construction of international first-class bay area and world-class urban agglomeration.

In van der Waals materials, the electronic property, including the bandgap as well as the charge carrier mobility and lifetime, significantly changes as its thickness shrinks to the monolayer limit. While such characteristic brings additional freedom and convenience in regard to device design and fabrication, it also raises uncertainty in terms of the semiconductor device functionality due to the competing roles of those factors in tuning the charge carrier transport. In this work, we perform scanning photocurrent microscopy experiments on different sets of MoS2 homojunctions under zero bias voltage and show the reverse photocurrent distribution among them. Specifically, in the combination of 1L–3L MoS2, the band offset is large and thus dominates the photocarrier separation. In the combination of 3L–7L MoS2, by contrast, the effect of band offset is negligible, and the mismatch in minority carrier diffusion length takes charge of the photoresponse. The authors hope that the findings presented here offer a perspective on the current transport and thus functionality realization in layered materials. [ABSTRACT FROM AUTHOR]

Due to continuous urban sprawl, large-scale bus network design has become a major challenge in urban transport planning. The continuous increase in urban population and scale makes the factors considered in the urban route network design increasingly complex. Contemporary public transportation network design problems are based more on efficiency goals such as the accessibility and comfort of the transportation network, which increases the difficulty of analyzing the problem. Bus network design is not only an NP-hard (nondeterministic polynomial) problem but also a multivariable and multiobjective problem. This paper focuses on the bivariate and multiobjective bus network design problem of route generation and station selection. This paper proposes an algorithm called the Pseudo Force Field. By combining the idea of Particle Swarm Optimization (PSO) and the properties of the force field, a feasible route generation scheme is provided for the design of the bus network. The algorithm does not need to determine the end station and has a high degree of completion of the demand. This solves the problem of the selection of terminal stations in large-scale road network design. On this basis, the article combines Genetic Algorithm (GA) and Pareto frontier to provide a new route optimization algorithm and proves the effectiveness of the algorithm. The model has achieved theoretical results in the design of the bus route network in the megacity of Shenzhen, China., Author(s): Yiming Chen [1]; Yanhong Gu (corresponding author) [1]; Zhengdong Huang [2]; Tianhong Zhao [2]; Liangyuan Guo [1] 1. Introduction Public transportation is one of the important ways to achieve [...]

In order to make gob-side filling body of gob-side entry retaining adapt to the roof movement, the properties of concrete material is modified by adding polymer and steel fiber to achieve the purpose of “yield-support”. The test of modified concrete was carried out to test the uniaxial compressive strength under different ratios, and the best ratio of each component was determined. The stress of filling body and displacement of upper and lower plate are simulated by FLAC3D numerical simulation method to analyze yielding performance. The results show that the ethylene vinyl acetate copolymer（ＥＶＡ） improves the plastic deformation ability of the concrete material, and steel fiber has a good effect on the ductility of concrete. When the dosage of polymer is 15%, the yielding property is 6.10%. The results of numerical simulation show that the modified concrete of gob-side filling material can sink with roof and release the pressure of the roof movement under the condition of its own strength, and finally achieve the purpose of coordination and yield. In addition, the best width of filling body beside gob-side retaining entry is 1.2 m.

With the advent of mass customisation, solving the assembly sequence planning (ASP) problem not only involves a non-convex optimisation problem that is hard to solve but also requires a high-speed response to the changes of assembly resources. This paper proposes a deep reinforcement learning (DRL) approach for the ASP problem, aiming at promoting the response speed by exploiting the reusability and expandability of past decision-making experiences. First, the connector-based ASP problem is described in a matrix manner, and its objective function is set to minimise assembly cost under the precedence constraints. Secondly, an instance generation algorithm is developed for policy training, and a mask algorithm is adopted to screen out impracticable assembly operations in each decision-making step. Then, the Monte Carlo sampling method is used to evaluate the ASP policy. The policy is learned from an actor–criticbased DRL algorithm, which contains two networks, policy network and evaluation network. Next, the network structures are introduced and they are trained by a mini-batch algorithm. Finally, four cases are studied to validate this method, and the results are discussed. It is demonstrated that the proposed method can solve the ASP problem accurately and efficiently in the environment with dynamic resource changes. [ABSTRACT FROM AUTHOR]

Fast urbanization brings great challenges to sustainable development goals, such as excessive exploitation and population explosion. Classical cellular automata (CA) have been widely used to independently simulate the change of spatial features, i.e. land use, population, economic production, etc. However, most CA models rely on historical data as static driving factors to simulate future scenarios while ignoring the inter-wined influences among multiple features in the development process. To address this issue, this study proposes a spatial cooperative simulation (SCS) approach to simulate the land use, population, and economy changes. The SCS approach starts with a separate CA model to obtain the initial scenes of each feature. Then, the simulation results of each other two features are used as dynamically updated driving factors, rather than the static historical data, to capture the inter-wined influence of multiple features during the development process. This step is iteratively performed until the changes of each feature converge and the final simulation results will be reported. The simulation experiment in Greater Bay Area demonstrates that the SCS approach can well capture the simultaneous development process and outperforms baseline approaches. The SCS approach is capable of forecasting future development scenarios and facilitates spatial planning and infrastructure synergies. [ABSTRACT FROM AUTHOR]