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Real-time train rescheduling for high-speed railway (HSR) is a pivotal technique in HSR transportation to efficiently recover train operation under disturbance scenarios. This paper aims to put forward an integrated resolving and rescheduling method considering network delay propagation. A tree-based conflict resolution mechanism is first established, with delicate considerations on the strategy's adaptability under different conflict scenarios. By inputting the scheduled arrival and departure time under different conflict resolution strategies, the timetable optimizing model aims to look for an optimal solution with minimal weighted train delay and average train adjustments under necessary technical and empirical constraints solved by a combined algorithm of Pareto optimality and Nash equilibrium, where the feasible solution space is narrowed in advance by a depth-first pruning algorithm. The performance of this coordinated train rescheduling approach is validated by a typical section disturbance in a regional HSR network administrated by the Shanghai Bureau. The results show that the proposed method can well utilizes timetable buffers and organizes train avoidance. The delay propagation characteristics are also simultaneously estimated based on the indicators of cumulative delay and instantaneous delay, which are established considering the spatio-temporal difference between the scheduled and planned timetables, in order to verify the coordination between resolution strategies and train running delays. [ABSTRACT FROM AUTHOR]

Previous studies on pedestrian crossing have mostly focused on pedestrian crossing decisions; while as an important behavioral aspect, the pedestrian crossing process, i.e., their motions during the entire crossing process, has been narrowly studied. Understanding how pedestrian moves across the street during their entire crossing process helps identify risky movements and reasons for such movements, which can further help in the implementation of effective countermeasures. Therefore, this paper proposed a new and easily applied approach for investigating and understanding the pattern of the pedestrian crossing process at crosswalks based on vision-based trajectory tracking technology and UAV (unmanned aerial vehicle) data. This study uses UAV for collecting video data which is timesaving and has a sufficient coverage area, compared to other methods. For trajectory extraction, the vision-based Deep-SORT-Yolov5 architecture is applied. An improved DBSCAN (density-based spatial clustering of applications with noise) algorithm is introduced for clustering and identification of patterns of pedestrian crossing processes based on their trajectories. This approach is tested via a case study involving six marked crosswalks in Shanghai, China. By using the proposed method, different crossing patterns are extracted and compared. The results show reasonable outputs of trajectory patterns, which reasonably explain the potential instincts of the pedestrians and affecting factors on the behavior of the pedestrian crossing process. Suggestions are made based on the results. This paper contributes to a more comprehensive safety analysis of pedestrian crossings by considering the pedestrian crossing process. The model, along with the UAV-based trajectory observation method, provides an easily-applied and low-cost way of traffic data collection for the purpose of pedestrian safety evaluation. [ABSTRACT FROM AUTHOR]

Under the background of the rapid development of digital economy, this paper empirically analyzes the impact of digital transformation on enterprise innovation and selects the panel data of China's Shanghai and Shenzhen A-share listed companies from 2013 to 2021 as the research objective is to study the impact of digital transformation on enterprise innovation from theoretical and empirical perspectives. First, we find that digital transformation accelerates enterprise innovation, a conclusion that has been validated through robustness testing. Second, digital transformation impacts enterprise innovation by enhancing productivity and information transparency. Third, financing constraints and financial redundancy play distinct regulatory roles in the process. Fourth, heterogeneity analysis finds that the role of digital transformation in promoting enterprise innovation has different effects in state-owned and non-state-owned enterprises, high-tech and non-high-tech enterprises, and enterprises with different life cycles. Finally, the functional analysis suggests that further investigation is needed to determine whether digital transformation can significantly promote the sustainable development of enterprises through innovation while also recognizing that this function may have a lag effect. Overall, this study contributes to a deeper understanding of digital transformation and innovation-driven practices and encourages more significant integration of the real and digital economies. [ABSTRACT FROM AUTHOR]

The key to solving the problem of redundant financial indicators in addressing financial warning issues is to reduce the dimensionality of the original financial indicators. This paper proposes a model based on the whale optimization algorithm with mixed strategy (IWOA) combined with support vector machine (SVM), namely, the IWOA-SVM early warning model, which simultaneously performs index optimization and dimensionality reduction, and financial risk early warning identification. This paper takes a total of 302 enterprises specially treated in Shanghai and Shenzhen stock exchanges and normal enterprises of the same specification as the research samples to design the model. The results show that the improved whale optimization algorithm has better optimization speed and accuracy and improves the search ability of the original algorithm for the optimal solution. Compared with other dimensionality reduction methods, the IWOA-SVM model has the lowest index dimension after dimensionality reduction and has more excellent recognition effect. The dimensionality reduction results have certain universality for different classifiers, which provides a new idea for the selection of indicators for financial early warning. [ABSTRACT FROM AUTHOR]

A supply chain's risk spillover effect will affect the customer's risk on the financing constraints of suppliers. This paper builds on the evaluation of customer risk by fuzzy mathematics, combines with the A-share listed companies in Shanghai and Shenzhen from 2007 to 2019 as a study sample, and empirically inspects the influence of customer risk on the level of corporate financing constraints. According to the study, it shows that the customer risk is currently at a moderate level, which will notably impair the supplier's external financing ability. This phenomenon is more remarkable when the monetary policy is tightened with fierce competition in the industry. This paper unveils the economic consequences of customer risk spillovers from a supply chain, enriches the study of the generation mechanism of corporate financing constraints, and provides investors and regulators with empirical evidence to appreciate corporate financing constraints. [ABSTRACT FROM AUTHOR]

As the cradle of scientific research institutions and the cultivation of innovative talents, high-level universities are of certain theoretical and practical significance to investigate the impact of high-level universities on the innovation of local enterprises under the realistic background of the revival of machine learning. This paper takes A-share listed enterprises in Shanghai and Shenzhen stock markets from 2013 to 2019 as samples, and empirically examines the relationship between high-level universities and local enterprise innovation from the perspective of "double first-class" universities. The study found that high-level universities have a significant role in promoting the innovation of local enterprises, and a series of robustness tests have also confirmed the conclusions of this paper. Mechanism analysis shows that high-level universities promote local enterprise innovation mainly by promoting human capital output and school-enterprise cooperation. Heterogeneity analysis shows that executive gender, government intervention, and differences in regional development levels have significant heterogeneity effects. This paper has obvious policy implications: China should guide high-level universities to cultivate high-quality talents, cultivate positive school-enterprise cooperation, promote the sharing of innovative resources, and promote the high-quality development of the real economy. [ABSTRACT FROM AUTHOR]

The East China Sea section of the Chinese international submarine optical fiber cable generally starts from the Shanghai coast, crosses the East China Sea shelf and continental slope to the east, and intersects with the international optical fiber cable system in Okinawa Trough. In this paper, the regional tectonic, seismic, and other environmental conditions of the East China Sea section of the international submarine optical cable are briefly described based on the previous data. Additionally, the geological engineering conditions of the international optical cable routing in the East China Sea area will be analyzed based on the field investigation data such as multibeam, side-scan sonar, shallow stratigraphic profile, sediment sampling, and cone penetration test (CPT). It is found that the main geological factors in the East China Sea shelf area are submarine scouring, sandwave, shallow gas, and hard seabed; in the land slope area are steep slope, submarine valley, rock, landslide, and shallow gas (pockmark); and in the Okinawa Trough area are gully, sea mound/seamount, rock, shallow gas, fault, and hard strata outcrop. This paper briefly analyzes the impact of each geological disaster factor on the submarine cable project and proposes solutions for providing essential information and some scientific basis for designing, constructing, operating, and maintaining international submarine optical fiber cables in the East China Sea area. [ABSTRACT FROM AUTHOR]

With the development of 3D technology, based on the perspective of 3D video, this paper analyzes the principle of 3D video, establishes the perspective model of 3D video, and discusses the modeling process in detail. Then, from the perspective of 3D video, this paper studies the three-dimensional intervention model of public art in Beijing, Shanghai, Chongqing, and Tianjin. Through the combination of public art and rural culture, the countryside can obtain vitality through art and popularize and promote rural culture and image. In general, this paper provides some ideas and experience for the research of public art in rural culture from the perspective of 3D video. [ABSTRACT FROM AUTHOR]

Affected by the fluctuation of the market and economic environment during the epidemic period, the capital pressure of companies has increased sharply, which increases the possibility of risk transmission in the same industry and poses new challenges to the operation and financing of companies. From the perspective of preventive motivation of corporate cash holding, we creatively use the industry working capital shortfall as the explanatory variable to construct an Extended Cash Holding Model and a Cash Holding Value Regression Model. Taking the panel data of A-share listed companies in Shanghai and Shenzhen as samples, this paper uses the Classical Linear Regression Model and Fixed Effects Regression Model to study the relationship between industry working capital shortfall and cash holdings in the same industry, as well as the relationship between industry working capital shortfall and cash holding value. The empirical results show that industry working capital shortfall has an important impact on the cash holding level within the same industry, and the cash holding level is significantly and positively correlated with industry working capital shortfall. Moreover, this study also reveals that the industry working capital shortfall has a dual impact on cash holdings. Specifically, the higher the risk of industry working capital shortfall, the lower the value of company cash holdings. The conclusions of this paper not only extend the research on cash holding but also provide support and reference for companies to optimize the cash holding value. [ABSTRACT FROM AUTHOR]

Affected by the fluctuation of the market and economic environment during the epidemic period, the capital pressure of companies has increased sharply, which increases the possibility of risk transmission in the same industry and poses new challenges to the operation and financing of companies. From the perspective of preventive motivation of corporate cash holding, we creatively use the industry working capital shortfall as the explanatory variable to construct an Extended Cash Holding Model and a Cash Holding Value Regression Model. Taking the panel data of A-share listed companies in Shanghai and Shenzhen as samples, this paper uses the Classical Linear Regression Model and Fixed Effects Regression Model to study the relationship between industry working capital shortfall and cash holdings in the same industry, as well as the relationship between industry working capital shortfall and cash holding value. The empirical results show that industry working capital shortfall has an important impact on the cash holding level within the same industry, and the cash holding level is significantly and positively correlated with industry working capital shortfall. Moreover, this study also reveals that the industry working capital shortfall has a dual impact on cash holdings. Specifically, the higher the risk of industry working capital shortfall, the lower the value of company cash holdings. The conclusions of this paper not only extend the research on cash holding but also provide support and reference for companies to optimize the cash holding value. [ABSTRACT FROM AUTHOR]

Digital twins can facilitate high-fidelity representations of container terminals by applying various technologies and methods to better measure, understand, and improve operations. In this paper, a decision support system (DSS) based on digital twin and big data technologies is designed to demonstrate how real-time monitoring and an integrated decision support can be established. The DSS provides optimal operation plans and the benchmark for vessel delay early warnings through different resource allocation simulations at the planning level. It further enables real-time operational decision making through real-time monitoring and efficiency analyses using big data engines at the operational level. A case study is conducted for the ultralarge Yangshan Deepwater Automated Container Terminal Phase IV (ACT4) in Shanghai (China) and experimental results have revealed that the proposed digital twin-based DSS can help ACT4 operators to evaluate vessel service using optimized resource allocation plans and operations. [ABSTRACT FROM AUTHOR]

Through the construction of wavelet coherence analysis and frequency-domain spillover framework, this paper makes a comparative study of the volatility spillover effects of international economic policy uncertainty (EPU) on China's Shanghai and Hong Kong stock market from a time-frequency perspective. To fully reflect the international EPU, this paper selects China, the United States, Australia, and the United Kingdom and uses the monthly EPU index of these countries and regions. China chooses China's EPU index and Hong Kong's EPU index. At the same time, the 5-minute high-frequency volatility of the Shanghai Composite Index (SSEC) and the Hang Seng Index (HSI) is selected to represent the Shanghai and Hong Kong's stock market, respectively. It is found that there are obvious differences between the EPU and the dependence of the stock market in time domain and frequency domain, and the lead-lag relationship between them has time-varying characteristics. Static and dynamic spillover effects play a dominant role in the analysis of medium- and long-term spillover effects. In particular, the EPU and the risk spillover of the Hong Kong stock market are stronger than those of the Shanghai stock market, and the dynamic frequency-domain net risk spillover between them has frequency characteristics, and there are two-way and asymmetric risk spillovers. This provides a certain reference for policy makers to improve the safety management of financial markets and for market investors to optimize their portfolios. [ABSTRACT FROM AUTHOR]

Recently, electric vehicles (EVs) have received more and more attention, but the problem of the insufficient range is still the main reason that hinders electric vehicles to travel long distances. Under the premise of the battery capacity without technological innovation, the path planning method can ensure the safety and efficiency of electric vehicles in long-distance travel. This paper studies the actual freeway network to optimize the vehicle driving path and give the charging strategy based on the shortest travel time of a single vehicle. In this paper, a path and charging strategy planning model is proposed. In this model, the shortest travel time of a single vehicle is taken as the objective function, and the state of charging equipment in the actual road network and the safe electric quantity are considered as constraints. And the genetic algorithm is used to solve the model. Through case analysis, the rationality and optimization efficiency of the model proposed in this paper are verified. Finally, the sensitivity analysis of the three parameters of traffic volume, temperature, and travel speed is carried out with the Shanghai-Nanjing freeway network. The experimental results can get the nodes with the highest service pressure in the network, which can provide a theoretical basis for charging nodes' expansion in the freeway network in the future. [ABSTRACT FROM AUTHOR]

There are two main ways to achieve an active lifestyle, the first is to make an effort to exercise and second is to have the activity as part of your daily routine. The study's major purpose is to examine the influence of various kinds of physical engagements on density dispersion of participants in Shanghai, China, and even prototype check-in data from a Location-Based Social Network (LBSN) utilizing a mix of spatial, temporal, and visualization methodologies. This paper evaluates Weibo used for big data evaluation and its dependability in some types rather than physically collected proofs by investigating the relationship between time, class, place, frequency, and place of check-in built on geographic features and related consequences. Kernel density estimation has been used for geographical assessment. Physical activities and frequency allocation are formed as a result of hour-to-day consumption habits. Our observations are based on customer check-in activities in physical venues such as gyms, parks, and playing fields, the prevalence of check-ins, peak times for visiting fun parks, and gender disparities, and we applied relative difference formulation to reveal the gender difference in a much better way. The purpose of this research is to investigate the influence of physical activity and health-related standard of living on well-being in a selection of Shanghai inhabitants. [ABSTRACT FROM AUTHOR]

The challenges of financing have been troubling the development of Chinese enterprises, especially private enterprises. This paper aims to examine the antecedents and consequences of debt financing costs. Drawing on a sample of Chinese A-share listed companies in Shanghai and Shenzhen from 2009 to 2018, the study examined the relationship between corporate social responsibility disclosure, debt financing costs, and innovation capacity. This paper found that the quality of CSR disclosure is negatively related to the cost of debt financing and examined the situational differences in the impact of CSR disclosure quality under different property rights, different disclosure forms, and different forensic effects. Moreover, it is found that the negative effect of CSR disclosure quality on debt financing cost helps to induce the innovation capacity of enterprises. The findings of this paper have certain reference value for corporate improvement of social responsibility disclosure. [ABSTRACT FROM AUTHOR]

The paper constructs an economic growth model that contains human, physical capital, innovation, and energy factors and estimates the output elasticity of seven provinces and cities in East China in the period of 2004–2018. Having calculated the contribution rate of these different factors to economic growth, the paper finds that factors of production have a different elasticity that impacts the growth of different regions and industries and notes that energy and physical capital are the most significant factors for the growth of primary and secondary industries. This highlights that industrial growth has not freed from the path dependence of extensive input, and the authors cite Shanghai and Jiangsu as typical regions in this regard. The former's growth largely depends on physical capital and energy, and the latter's growth depends on the input of diverse elements including innovation. The latter is better suited to the needs of the "new normal" economic growth. The authors construct a simulation model of economic growth based on system dynamics, and system simulation results show that energy and material capital investment not only have the most significant effect on economic growth in East China but also provide clear evidence of extensive economic growth. The paper then demonstrates that increasing the optimal allocation of input factors and the rational flow between regions is conducive to improving output efficiency and provides the results of the Malmquist index calculation: on the whole, there is no obvious technological progress in East China. Shanghai, Jiangsu, and Zhejiang are, however, provincial-level regions of this part of the country which demonstrate significant technological progress in East China. In conclusion, the paper suggests that this region of China will be unable to maintain its current level of economic growth because of the combined influence of factor input constraints and insufficient technological progress. [ABSTRACT FROM AUTHOR]

Dockless sharing bikes play an increasingly significant role in transit transfer, especially for the first/last mile. However, it is not always accessible for users to find sharing bicycles. The objective of this paper is to assess the accessibility of dockless sharing bikes from a network perspective, which would provide a decision-making basis not only for potential bike users but also for urban planners, policymakers, and bicycle suppliers to optimize sharing-bike systems. Considering bicycle travel characteristics, a hierarchical clustering algorithm was applied to construct the dockless sharing-bike network. The social network analysis (SNA) method was adopted to assess the accessibility of the bike network. Then, a spatial interaction model was chosen to conduct a correlation analysis to compare the accessibility obtained from the SNA approach. The case study of Shanghai indicates a strong connection between the accessibility and the SNA indicators with the correlation coefficient of 0.779, which demonstrates the feasibility of the proposed method. This paper contributes to a deep understanding of dockless sharing-bike network accessibility since the SNA approach considers both the interaction barriers and the network structure of a bicycle network. The developed methodology requires fewer data and is easy to operate. Thus, it can serve as a tool to facilitate the smart management of sharing bikes for improving a sustainable transportation system. [ABSTRACT FROM AUTHOR]

Container shipping drives the development of international trade, yet previous studies have not fully appreciated the possible bidirectional causal relationship between container freight rates and international trade. In the context of the "twenty-first Century Maritime Silk Road," we use data on export container freight rates and import/export data from Shanghai to ASEAN-6 countries (Singapore, Vietnam, Thailand, Philippines, Malaysia, and Indonesia) from February 2017 to January 2020 and apply a panel VAR to explore the relationship between maritime transport costs and international trade in the container shipping market. We use the freight rate data are from the Southeast Asia Freight Index, which is used for the first time in an empirical study. The quality and reliability of the freight rate data allow this paper to better identify causal relationships. The results of the panel Granger causality test and the orthogonal impulse response function suggest a bidirectional causal relationship between freight rates and export trade; to further explain, an increase in export trade lowers export freight rates, but an increase in export freight rates hinders export trade, and a growth in import trade unidirectionally raises export freight rates. We believe that international trade may impact freight rates through economies of scale and trade imbalances. [ABSTRACT FROM AUTHOR]

Rapid urbanization and growth of population in megacities generate severe pressures on urban rail transit (URT) system. The quantity and frequency of disruptive events have increased significantly, which might have obvious adverse impacts. A large number of passengers are stranded at disrupted URT station when a disruptive event occurs. One essential solution for passenger evacuation is the bus bridging service. This paper is aimed at addressing the passenger evacuation problem caused by a disruptive event in the URT network, by proposing a bus bridging service model considering the passengers' space-time requirements. The model is proposed to minimize the waiting time of passengers and considers factors including bus service capacity limitations, bus stop parking capacity, and the maximum bridging time limit of a single bus. Buses are assumed to provide bridging service on either the local bus route or the direct bus route. The optimal routes and scheduling plans of bridging bus are designed. The model is applied to an example of a disruptive event in Shanghai URT line 9. The results of this example show that the proposed model is capable of reducing the waiting time of passengers and the number of buses used by 3.2% and 24.7%, compared with the traditional bus bridging service. Further analysis of the example shows that it is not a cost-effective solution to reserve a large number of buses for URT disruption. Decision-makers should comprehensively trade off between passengers' space-time demands and monetary costs of bus bridging service. [ABSTRACT FROM AUTHOR]

In the rapidly changing multimodal transportation market, not only the obligation in providing train services but also the responsibility in helping other transportation modes to meet emergencies are instrumental for maximizing the generalized benefit of railway companies, leading to an increased utilization. This paper proposes an optimization framework, which includes multiple dispatching measures of arranging residual seats, modifying stopping plans, and inserting additional trains, to design a rescheduling operation plan on a high-speed rail corridor to meet the passenger demand of unexpected large passenger flow (ULPF), which is generated from the disruption of other transportation modes. Considering the revenues of shifting passengers and the costs of the three dispatching measures as two objectives, we formulate a linear integer programming (LIP) model by employing a time-space network to obtain an optimization rescheduling operation plan. Several experiments based on the Beijing-Shanghai high-speed railway corridor are conducted to evaluate the effectiveness and efficiency of the proposed model. The experimental results demonstrate that the proposed model can be used to obtain a reasonable rescheduling operation plan for serving the passengers from ULPF within an acceptable calculation timeframe. [ABSTRACT FROM AUTHOR]

In the context of digital economy, the international trade mode has undergone profound changes, so digital transformation has become the key to the sustainable development of foreign trade enterprises. In this paper, by collecting the data of 27 foreign trade enterprises listed in Shanghai and Shenzhen A shares from 2010 to 2020 and adopting the method of full text identification of enterprise comprehensive financial reports to quantify the intensity of enterprise digital transformation, the influence of digital transformation of foreign trade enterprises on the main business performance and the effect of two mediating variables of internal control and innovation ability of enterprises were studied. The result shows that the digital transformation of foreign trade enterprises has a significant role in promoting their main business performance. From the mechanism of action, digital transformation promotes the overall improvement of the main business performance of enterprises by improving the internal management of enterprises and enhancing the mediating role of enterprise innovation ability. Finally, from the perspectives of government and enterprises, some suggestions were put forward for foreign trade enterprises to choose the development path of digital transformation. [ABSTRACT FROM AUTHOR]

This paper selects the relevant data of Shanghai and Shenzhen NG listed companies from 2016 to 2020 as the research object. By drawing on relevant research results at home and abroad, the variable KZ is used to measure the degree of corporate financing constraints, and the variable Tobin Q is used to measure corporate performance. The test draws the following conclusions: financing constraints are conducive to improving corporate performance. The reason is that the higher the degree of corporate financing constraints is, the more cautious the managers are in the use of funds, and the company managers can formulate more scientific management strategies, so as to improve corporate performance. Through further research, it is found that, with the expansion of the scale of the enterprise, the degree of financing constraints has less negative impact on the performance of the enterprise. Performance has a positive impact. According to the above conclusions, the government should improve the financial market system, build a multilevel capital market, and fundamentally ease the financing constraints of enterprises, to develop and improve self-management. [ABSTRACT FROM AUTHOR]

According to the proposal of Kyoto protocol, carbon dioxide emission rights are traded as a commodity, and carbon emission trading market emerges as the times require. As the world's largest carbon emitter, China has established eight pilot markets for carbon emission trading. Selecting the closing price of eight carbon trading markets from the establishment to June 23, 2020, this paper analyzes the daily, weekly, and monthly return series data, using the first-order autoregressive process to adjust the daily income series to eliminate the weak trading market effect and then comprehensively uses the traditional variance ratio test and multiple variance ratio test to analyze the weak-form market efficiency of the eight carbon trading markets. The empirical results show that most of the carbon trading markets are non-weak-form market efficiency, and only Tianjin, Shanghai, and Hubei markets are weak-form market efficiency under the daily trading data. However, with the increase of carbon holding period, the weak-form market efficiency continues to strengthen. It shows that liquidity, quantity, and information transparency are important factors that affect the market efficiency. [ABSTRACT FROM AUTHOR]

The current development plans for logistics of city clusters often pursue investment speed, while overlooking the economic benefits of logistics within city clusters. To prevent the waste of logistics resources, it is meaningful to study the meaning of the logistics radiation ability of city clusters and determine their logistics radiation range. Taking Ningbo Metropolitan Area as an example, this paper tries to measure logistics radiation range and improve logistics radiation ability of city clusters. The analytic hierarchy process (AHP) was adopted to quantify the logistics influencing factors. Besides, an improved breakpoint model was established based on the breakpoint theory, the logistics radiation range model, and the integrated logistics field theory. Drawing on the statistics in 2017, the improved model was applied to empirically measure the variation of integrated logistics quality of eight cities and determine the logistics radiation ranges of Ningbo Metropolitan Area relative to Shanghai Metropolitan Area and Hangzhou Metropolitan Area. Finally, several countermeasures were developed to improve the logistics radiation ability of Ningbo Metropolitan Area: the positioning of metropolitan areas, the model of logistics development, the development of industries closely associated with logistics, and the cultivation of strategic locational advantages. The research provides a good reference for the government of Ningbo to develop advantageous logistics fields around advantages and turn the city into an economic center. [ABSTRACT FROM AUTHOR]

Promoting the innovative development of cities in the metropolitan area holds great significance for China's implementation of the "innovation-driven development" strategy. According to symbiosis theory, this paper constructed a city-based Lotka-Volterra symbiosis model and innovation-level index system. We used the Shanghai metropolitan area as a sample for empirical analysis to explore the evolution of the comprehensive development level of urban innovation under different symbiotic relationships. The research results showed that under a reciprocal relationship, the innovative development of core city and node cities was higher than the actual level; under a mutual inhibition symbiosis or parasitic symbiotic relationship, the innovative development of core city and node cities was lower than the actual level; and under an independent symbiotic relationship, the innovative development of the core city was higher than the actual level, while that of the node cities was lower than the actual level. [ABSTRACT FROM AUTHOR]

This paper developed a mixed multinomial probit (MMNP) model with alternative error specification and random coefficients (for both generic variables and personal attributes) to accommodate flexible covariance structure and taste variation. The MMNP model can be efficiently estimated with analytic approximations of multivariate normal cumulative distribution functions, which avoid defects of simulation-based integration in the mixed multinomial logit (MMNL) model. The integral dimension of the MMNL model increases as random coefficients increase, but it only depends on the number of available alternatives in the MMNP model. Simulation experiments and empirical analysis of Shanghai commuters' mode choice behavior were undertaken to examine the performance of MMNP models. Both simulation results and empirical results show that MMNP models can well accommodate flexible covariance structures and taste variation reflected through random coefficients being associated with both generic and personal variables. Empirical results indicate that the MMNP model performs better than traditional discrete choice models, such as the multinomial logit, the cross-nested logit, MMNL, and multinomial probit models. Random coefficients of "in-vehicle time of car" and "number of companions" indicate taste heterogeneity and the identifiability of random coefficients associated with both generic and personal attributes. Pairwise positive correlations between car/taxi, bus/metro, and bus/bus and metro are to be expected. However, the positive correlation between the car and metro modes may be unique to the Chinese city, Shanghai, because of the developed metro system. Unequal error variances reflect heterogeneities in unspecified factors in commute modes' utilities. The MMNP model will offer an alternative efficient way to accommodate taste heterogeneity and flexible error covariance structure in discrete choice models. Compared with the MMNL model, the MMNP model can accommodate more random coefficients without increasing computational complexity. [ABSTRACT FROM AUTHOR]

Innovation is the driving force behind enterprise development. Improving the quality of the internal control of enterprises and increasing the intensity of R&D investment are important ways to enhance the level of scientific and technological innovation. Based on the data of Shanghai and Shenzhen A-share listed companies from 2010 to 2019, in this paper, we empirically examine the correlation between the quality of internal control and the intensity of R&D investment by using the level of corporate cash holdings as an intermediary variable. We find that high internal control quality can improve cash-holding level and that improving cash-holding level will increase R&D investment intensity. That is, cash-holding level has a mediating effect between internal control quality and R&D investment intensity, while internal control quality can have a direct or indirect positive effect on R&D investment. Accordingly, this study has important theoretical significance and practical value for enterprises that seek to promote R&D innovation and improve their internal control. [ABSTRACT FROM AUTHOR]

With the development of Internet technology, multisource big data can collect and analyze information so as to provide people with a good vision. In the process of governance, local governments will have problems of incomplete information. With the development of big data, multisource and big data will have advanced nature. Therefore, based on multisource big data, this paper analyzes the multisource big data algorithm in detail and establishes a local government governance model based on multisource big data. Then, the proposed model is applied to the local government governance process of Beijing, Shanghai, Chongqing, and Tianjin, and the local governance situation of each city is compared and analyzed so as to provide some reference for the optimization of the local government governance path. The experimental results show that the local governance model based on multisource big data can optimize the local government governance path and point out the direction for the local government governance path. [ABSTRACT FROM AUTHOR]

With the improvement of environmental policies and industry requirements for enterprise production and management, small- and medium-sized enterprises in environment-related industries were also changing. It was known from the existing research that the investment allocation of assets of small- and medium-sized enterprises was closely related to risk and return, and the leverage ratio of enterprises affected the risk-taking level of enterprises. In the process of sustainable development, enterprises will inevitably bear certain risks, but excessive risk-taking will bring all kinds of uncertainty and bankruptcy risk to the expected income and future cash flow of enterprises. Therefore, taking small- and medium-sized enterprises in environment-related industries as an example, this paper put forward relevant assumptions by analyzing the interaction between the existing enterprise financial asset allocation, risk-taking level and leverage ratio. In order to facilitate empirical analysis, A-share listed companies in environment-related industries in Shanghai and Shenzhen stock exchanges, small- and medium-sized board and GEM listed companies in Shenzhen stock exchange from 2007 to 2019 were selected as research samples. These data came from the information open platform for small- and medium-sized enterprises in environment-related industries, the research reports of third-party consulting companies and CSMAR and Wind databases. The empirical results showed that the allocation of financial assets had a significant impact on the level of risk-taking, and there was a U-shaped relationship between them when other conditions remained unchanged. At the same time, the financial asset allocation of small- and medium-sized enterprises in Chinese environment-related industries had a significant impact on the enterprise leverage ratio. Under other conditions unchanged, there was a U-shaped relationship between the two. In addition, leverage played an intermediary role in the relationship between financial asset allocation and risk-taking level. In addition to directly affecting the allocation of financial assets, it can also indirectly affect the risk-taking level of enterprises through leverage ratio. [ABSTRACT FROM AUTHOR]

The deep mining of passengers' travel data can identify competitive segments and gain insights into passengers' characteristics and differentiated demands. This can not only effectively support precise marketing strategy adjustment of railway transport but also improve its competitiveness in the passenger transportation market. In this paper, hidden railway travel behaviour is introduced and integrated with railway travel behaviour to create a complete passenger travel chain, based on existing distance-based competitive segment recognition methods. The loyalty index values of passengers are calculated using this travel chain to identify competitive segments. Furthermore, passenger classification and grouping currently ignore social relationships as well as personal travel characteristics. Therefore, a novel passenger grouping method is proposed; it integrates individuals' travel characteristics and social relations. Individual travel labels are created for travellers based on their travel data. Social relation topologies, such as ticketing relation, the relation of travelling together, and benefit relation via point redemption, can be extracted using these labels. Social relation traits can be retrieved using graph attention networks and multigraph fusion. Finally, travellers are categorised based on their individual travel characteristics. As an example, and a case study, the grouping of Guangzhou–Shanghai passengers in 2020 is taken which shows that the suggested method has the potential to improve both the precision and the feasibility of grouping railway passengers. As a result, new ideas for passenger grouping in railway marketing might be offered. [ABSTRACT FROM AUTHOR]

Travel has become a way of life for more and more people. The rapid development of technologies such as the Internet and 5G brings convenience to life, so recording one's travel through social media has become the main way of sharing. Based on the classification of UGC pictures by computer program, this paper studies the perception of tourist destination image by inbound tourists from different regions so as to find the factors that potentially affect tourists' decision-making. This study collects a large number of UGC pictures and classifies them according to computer programs. It conducts UGC data picture research through two different aspects of cognitive image and emotional image and finally analyzes the specific image perception of Shanghai tourism. The research results show that, in the analysis of specific inbound tourists' perception of tourist destination image, in the eyes of Western inbound tourists, Shanghai is a very modern cultural city with very distinctive architectural features; inbound tourists from East Asia are more and more interested in the cultural landscape and natural scenery of Shanghai. In the eyes of inbound tourists from East Asia, Shanghai is a city full of vitality. Among them, the Huangpu River is the place that receives the most tourists. 21.5% of inbound tourists will visit, and 13.7% of inbound tourists choose to visit Lujiazui. [ABSTRACT FROM AUTHOR]

To solve the difficult problems in the field of unconventional oil and gas extraction and hard rock excavation in urban underground spaces, this paper proposes a rock-breaking technique with high-temperature and high-pressure water under thermally driven conditions and establishes a coupled thermal-fluid-solid model with COMSOL Multiphysics (COMSOL Co., Ltd. Shanghai, China). Different simulation groups are established by controlling variables to explore the effects of the surrounding rock load, heat source power, and Biot coefficient on the damage evolution during thermally driven rock breaking. To make the results relevant to practical engineering, the damage evolution results under the maximum normal stress criterion, maximum normal strain criterion, and Coulomb-Navier damage criterion are considered, and a comparative analysis is performed. The results of this study show that an increase in unilateral load and heat source power accelerates the damage evolution rate, while an increase in bilateral load and Biot coefficient has the opposite effect. The damage evolution rate controlled by the maximum normal stress criterion is the fastest under general conditions. Finally, the advantages in rock breaking provided by the established method are verified by a comparison of results from the proposed model and a conventional hydraulic fracturing model. [ABSTRACT FROM AUTHOR]

With the quality of urbanization getting more attention, city-industry integration has increasingly become a hot topic in academia. This paper is based on the traditional quantitative research of city integration, introducing the measuring model of ternary coupling coordination degree of city-industry integration in Shanghai and highlighting the ecological environment has become an important factor in the process of integration. Through the entropy method and coupling coordination model to measure the integration of Shanghai, a reasonable conclusion was reached within data analyses. [ABSTRACT FROM AUTHOR]

In order to meet the demand of more refined urban weather forecast, it is of great practical significance to improve and optimize the single-layer urban canopy model (SLUCM) suitable for the megacity of Shanghai. In this paper, based on the offline SLUCM model driven by a whole-year surface flux observation data in the Shanghai central business district, a series of parameter sensitivity tests are carried out by using the one at a time (OAT) method, the relative importance and a set of optimized parameters of the SLUCM suitable for high-density urban area are established, and the improvement of simulation is evaluated. The results show that SLUCM well reproduces the seasonal mean diurnal patterns of the net all-wave radiation flux ( Q ∗) and sensible heat flux (QH) but underestimates their magnitudes. Both Q ∗ and QH are linearly sensitive to the albedo, and most sensitive to the roof albedo, the second to the wall albedo, but relatively insensitive to the road albedo. The sensitivity of Q ∗ and QH to emissivity is not as strong as that of albedo, and the variation trend is also linear. Similar to albedo, Q ∗ and QH are most sensitive to roof emissivity. The effect of thermal parameters (heat capacity and conductivity) on fluxes is logarithmic. The sensitivity of surface fluxes to geometric parameters has no specific variation pattern. After parameter optimization, RMSE of Q ∗ decreases by about 3.4–18.7 Wm−2 in four seasons. RMSE of the longwave radiation (L↑) decreases by about 1.2–7.87 Wm−2. RMSE of QH decreases by about 2–5 Wm−2. This study provides guidance for future development of the urban canopy model parameterizations and urban climate risk response. [ABSTRACT FROM AUTHOR]

In this paper, based on the existing research, the rural talent supply situation is analyzed. Rural talent relative to the existing rural labor force has a higher human capital of the labor force. We also discuss the part of moving workers who can be considered as talents. Financial dimension is mostly through literature collection and statistical data finding and computational calculation, according to the results of communicate indicators, to reflect its performance level. The performance analysis of organizational management dimension and institutional development dimension mainly focuses on qualitative analysis and comparative analysis, and then we summarize and evaluate the performance status of Shanghai basic endowment insurance system for urban and rural residents. Therefore, all countries in the world are constantly exploring and trying to improve the performance management model of their social security institutions. Through the evaluation and analysis of the above four dimensions, it can be found that the overall performance level of urban and rural residential insurance in Shanghai is relatively high, but there are still some problems in the operation process. [ABSTRACT FROM AUTHOR]

Promoting the innovative development of cities in the metropolitan area holds great significance for China's implementation of the "innovation-driven development" strategy. According to symbiosis theory, this paper constructed a city-based Lotka-Volterra symbiosis model and innovation-level index system. We used the Shanghai metropolitan area as a sample for empirical analysis to explore the evolution of the comprehensive development level of urban innovation under different symbiotic relationships. The research results showed that under a reciprocal relationship, the innovative development of core city and node cities was higher than the actual level; under a mutual inhibition symbiosis or parasitic symbiotic relationship, the innovative development of core city and node cities was lower than the actual level; and under an independent symbiotic relationship, the innovative development of the core city was higher than the actual level, while that of the node cities was lower than the actual level. [ABSTRACT FROM AUTHOR]

In order to meet the demand of more refined urban weather forecast, it is of great practical significance to improve and optimize the single-layer urban canopy model (SLUCM) suitable for the megacity of Shanghai. In this paper, based on the offline SLUCM model driven by a whole-year surface flux observation data in the Shanghai central business district, a series of parameter sensitivity tests are carried out by using the one at a time (OAT) method, the relative importance and a set of optimized parameters of the SLUCM suitable for high-density urban area are established, and the improvement of simulation is evaluated. The results show that SLUCM well reproduces the seasonal mean diurnal patterns of the net all-wave radiation flux ( Q ∗) and sensible heat flux (QH) but underestimates their magnitudes. Both Q ∗ and QH are linearly sensitive to the albedo, and most sensitive to the roof albedo, the second to the wall albedo, but relatively insensitive to the road albedo. The sensitivity of Q ∗ and QH to emissivity is not as strong as that of albedo, and the variation trend is also linear. Similar to albedo, Q ∗ and QH are most sensitive to roof emissivity. The effect of thermal parameters (heat capacity and conductivity) on fluxes is logarithmic. The sensitivity of surface fluxes to geometric parameters has no specific variation pattern. After parameter optimization, RMSE of Q ∗ decreases by about 3.4–18.7 Wm−2 in four seasons. RMSE of the longwave radiation (L↑) decreases by about 1.2–7.87 Wm−2. RMSE of QH decreases by about 2–5 Wm−2. This study provides guidance for future development of the urban canopy model parameterizations and urban climate risk response. [ABSTRACT FROM AUTHOR]

As for whether the customer risk leads to the inefficient investment of suppliers, 776 suppliers and customers of Shanghai and Shenzhen A-shares from 2007 to 2017 are chosen as the supply chain data of listed companies, the relationship between customer risk and supplier enterprise investment efficiency is studied by manual sorting, and the moderating effect of the nature of supply chain relationship on customer risk and enterprise investment efficiency is taken into account. According to the research, the customer risk will reduce the investment efficiency of supplier enterprises, which is manifested as underinvestment. Based on further research, the relationship is more significant in supplier enterprises with a higher customer concentration and state-owned enterprises that are customers and suppliers. The research of this paper enriches the relevant literature on investment efficiency and the relationship between customer and supplier, provides a new perspective for studying investment efficiency and the empirical evidence for risk prevention behavior among enterprises, and has important practical significance for supplier enterprises to choose core customers and manage customer relations. [ABSTRACT FROM AUTHOR]

This paper uses the data of China's A-share listed companies in Shanghai and Shenzhen stock markets from 2003 to 2014 and takes the pilot emission trading policy in 2007 for a quasinatural experiment to explore the role of the pilot emission trading policy in promoting enterprises' green technology innovation. The empirical research shows a Porter effect in the emission trading system in China. Specifically, first, the emission trading policy can significantly promote enterprises' green technology innovation in pilot areas. In addition, the incentive effect of emission trading policy on green technology innovation is significantly different due to the types of green patents. Second, the incentive effect of emission trading policy on enterprises' green technology innovation is different due to the nature and scale of enterprises. The incentive effect is greater in state-owned enterprises than in non-state-owned enterprises, and it is greater in large-scale enterprises than in small-scale enterprises. Finally, the incentive effect of emission trading policy on enterprises' green technology innovation has heterogeneity of regions. It has the greatest incentive effect in eastern region, followed by western region and then central region. [ABSTRACT FROM AUTHOR]

Sustained and stable external financing, affected by the financial environment, is a necessary condition to support the green technological innovation of enterprises. This paper focuses on the impact of bettering the financial environment of digital finance on enterprise green technological innovation, as well as the mediating role of financing costs and financial flexibility in this process. Using China's data on manufacturing enterprises listed in Shanghai and Shenzhen from 2011 to 2018, the hypotheses are tested. The result suggests the following: (a) digital finance effectively promotes enterprises to carry out green technological innovation, specifically, the coverage and depth of digital finance can promote enterprises' green technological innovation, but the degree of digitization has no significant impact; (b) digital finance improves the financial environment by making up the shortage of traditional financial system through reducing financing problems such as "financing difficulty," "matching difficulty," and "supervision difficulty," which make effective contributions to enterprise green technological innovation; (c) financing costs negatively mediate the relationship between digital finance and enterprise green technological innovation, while financial flexibility positively mediates the relationship. Overall, our findings shed light on the role digital finance plays in shaping corporate environmental behavior—and ultimately innovation in sustainability—in financing constraint setting. [ABSTRACT FROM AUTHOR]

Aiming at the problems of crowd distribution, scale feature, and crowd feature extraction difficulties in exhibition centers, this paper proposes a crowd density estimation method using deep learning for passenger flow detection systems in exhibition centers. Firstly, based on the pixel difference symbol feature, the difference amplitude feature and gray feature of the central pixel are extracted to form the CLBP feature to obtain more crowd group description information. Secondly, use the LR activation function to add nonlinear factors to the convolution neural network (CNN) and use dense blocks derived from crowd density estimation to train the LR-CNN crowd density estimation model. Finally, experimental results show that the mean absolute error (MAE) and mean square error (MSE) of the proposed method in the UCF_CC_50 dataset are 325.6 and 369.4, respectively. Besides, MAE and MSE in part_A of the Shanghai Tech dataset are 213.5 and 247.1, respectively, and they in part_B are 85.3 and 99.7, respectively. The proposed method effectively improves the accuracy of crowd density estimation in exhibition centers. [ABSTRACT FROM AUTHOR]

Based on social exchange theory, signal transmission theory and enterprise life cycle theory, this paper empirically analyzes the impact of CSR performance on enterprise innovation investment by taking the A-shares listed private enterprises in Shanghai and Shenzhen stock markets from 2009 to 2019 as research samples. At the same time, we pay attention to the moderating effect of executive compensation incentive, explore the dynamics of the influence mechanism in different life stages. The results show that: there is a significant positive correlation between CSR performance and enterprise innovation investment, that is, CSR behavior is conducive to the improvement of enterprise innovation investment intensity; Executive compensation incentive has a negative moderating effect on this relationship. The higher the incentive level of executive compensation, the weaker the positive impact of CSR performance on innovation investment. Further research shows that CSR performance affects innovation investment through the exchange of government resources and the promotion of market position, but the effects are different during the enterprise life cycle. Relevant conclusions enrich the theory and practice of CSR performance and enterprise innovation investment from the dynamic perspective, provide a theoretical basis for private enterprises to develop a reasonable and effective executive compensation incentive system. [ABSTRACT FROM AUTHOR]

Crowding in urban rail transit is an inevitable issue for most of the high-density cities across the world, especially during peak time. For commuters who have considerably fixed destination arrival times, departure time choice is an important tool to adjust their trips. The ignorance of crowding impact on commuters' departure time choice in urban rail transit may cause errors in forecasting dynamic passenger flow during peak time in urban rail transit. The paper develops a mixed logit model to identify how crowding impacts the departure time choice of commuters and their taste variation. Arrival time value was firstly measured in a submodel by applying the reference point approach and then integrated to the main model. Considering the characteristics of human perception, we divided crowding into five grades with distinct circumstances. All parameter distributions were assumed based on their empirical distributions revealed through resampling. The data from Shanghai Metro used for estimation were collected by a specifically designed survey, which combines revealed preference questions and stated preference experiments to investigate the willingness and extent of changing departure time choice of passengers who experienced various grades and duration of crowding in the most crowded part. The result shows that an asymmetric valuation model with preferred arrival time as the only reference point best captured commuters' responses to arrival time. The departure time choice model clearly identified that only crowding ranging from Grades 3 to 5 had an impact on commuters' departure time choice. The parameters of crowding costs can be assumed to follow transformed lognormal distributions. It is found that the higher the grade of crowding is, the bigger the impact each unit of crowding cost has on commuters' departure time choice, while commuters' tastes get more concentrated when crowded situation upgrades. The model in this paper can help policymakers better understand the interaction between commuters' departure time choice and crowding alleviation. [ABSTRACT FROM AUTHOR]

The metro system plays a very important role in the urban multimodal transportation system, yet it is susceptible to accidents. A well-designed metro system needs to provide alternative routes to travellers both in the disruptive events and the normal operating conditions for providing rerouting opportunities and balancing crowded lines. This paper provides a new dimension of assessing metro network performance—travellers' route redundancy (or route diversity), which is defined as the number of behaviourally effective routes between each origin-destination (O-D) pair in the network. The route redundancy of metro network is evaluated by statistical indicators of the distribution of the O-D-level number of effective routes. Compared with the existing connectivity and accessibility measures of topology network performance, route redundancy is also based on the topology network, but it takes the travellers' route choice into consideration. Specifically, the effective routes between each O-D pair would provide disaggregated information from the travellers' perspective. Case studies in four metropolises in the world, i.e., Shanghai, Beijing, London, and Tokyo, are conducted to examine the predisaster preparedness of the four metro networks explicitly from the perspective of route redundancy. The results indicate that the London metro network has the best route redundancy performance in terms of the statistical indicators of the distribution of the O-D level number of effective routes. Furthermore, the results of route redundancy are compared with typical measures of topology network performance in terms of measuring connectivity and accessibility of metro networks. Their differences are attributed to the fact that the route redundancy measure considers the travellers' O-D-level route choice beyond the pure network topology and the shortest path considerations of the existing measures. The route redundancy proposed in this paper could assist in evaluating the predisaster preparedness of current or planning metro networks from O-D level to network level. [ABSTRACT FROM AUTHOR]

As one of the core systems of a city, urban rail transit plays a pivotal role in ensuring the safe, rational, and efficient operation of the city. Therefore, it is of great significance to ensure the safe operation of urban rail transit network to improve the operation efficiency and economic level of the city. The prerequisite to ensure the safety of urban rail transit network is whether the risk situation of urban rail transit network can be reasonably and accurately evaluated. In order to evaluate the risk level of urban rail transit network reasonably and accurately, firstly, with full consideration of the characteristics of urban rail transit, the risk evaluation system of urban rail transit network was established in this paper based on the three levels of regional economy, social resources, and rail transit. Secondly, based on the entropy-TOPSIS-coupling coordination model, the single-factor influence and multifactor coupling influence in the index system are calculated and analyzed, respectively; thus the coupling coordination degree of urban rail transit system is obtained, so as to quantitatively evaluate and analyze the risk situation in urban rail transit network. Finally, based on the actual data of Shanghai from 2000 to 2016, the case simulation and analysis are carried out. The results show that the two indicators of regional economy and social resources are more likely to affect the safety state of urban rail transit. At the same time, the safety factor of urban rail transit coupling system is increasing year by year and gradually develops from disorder to order. This is more in line with current urban rail transit condition, demonstrating the rationality and accuracy of the entropy-TOPSIS-coupling coordination model proposed in this study. [ABSTRACT FROM AUTHOR]

Fintech relies on emerging technologies such as artificial intelligence and big data to bring a new business model to the financial system; can this new change promote corporate technological innovation? To explore this question, this paper examines the possible impact mechanism of Fintech on enterprise technological innovation based on the examination of the impact of Fintech on enterprise technological innovation through a panel fixed effects model, using A-share listed enterprises in Shanghai and Shenzhen markets in China from 2011–2019, and further explores whether there is heterogeneity in this impact among enterprises with different traits. The results show that Fintech development can significantly promote firm technological innovation and that Fintech can influence firm technological innovation through two mechanisms: alleviating firm financing constraints and providing market opportunities for firms to enhance their profitability. In addition, the driving effect of Fintech on technological innovation is more pronounced in new firms, state-owned enterprises, and nonborrowed and listed firms. Based on the conclusion, it is proposed that the government should enhance certain policy support for Fintech guided by emerging technologies such as artificial intelligence, help Fintech empower the real economy, and at the same time promote the deep integration of Fintech and real enterprises, especially to strengthen the identification of Fintech for new enterprises and encourage state-owned enterprises to implement employee stock ownership system, as well as sound market construction to reduce barriers to listing of high-quality enterprises, so as to improve innovation policy effectiveness and provide a reference for the mitigation of enterprise innovation problems in the new situation. [ABSTRACT FROM AUTHOR]

The current article paper is aimed at assessing and comparing the seasonal check-in behavior of individuals in Shanghai, China, using location-based social network (LBSN) data and a variety of spatiotemporal analytic techniques. The article demonstrates the uses of location-based social network's data by analyzing the trends in check-ins throughout a three-year term for health purpose. We obtained the geolocation data from Sina Weibo, one of the biggest renowned Chinese microblogs (Weibo). The composed data is converted to geographic information system (GIS) type and assessed using temporal statistical analysis and spatial statistical analysis using kernel density estimation (KDE) assessment. We have applied various algorithms and trained machine learning models and finally satisfied with sequential model results because the accuracy we got was leading amongst others. The location cataloguing is accomplished via the use of facts about the characteristics of physical places. The findings demonstrate that visitors' spatial operations are more intense than residents' spatial operations, notably in downtown. However, locals also visited outlying regions, and tourists' temporal behaviors vary significantly while citizens' movements exhibit a more steady stable behavior. These findings may be used in destination management, metro planning, and the creation of digital cities. [ABSTRACT FROM AUTHOR]

Calibrating the microsimulation model is essential to enhance its ability to capture reality. The paper proposes a Bayesian neural network (BNN)-based method to calibrate parameters of microscopic traffic simulators, which reduces repeated running of simulations in the calibration and thus significantly improves the calibration efficiency. We use BNN with probability distributions on the weights to quickly predict the simulation results according to the inputs of the parameters to be calibrated. Based on the BNN model with the best performance, heuristic algorithms (HAs) are performed to seek the optimal values of the parameters to be calibrated with the minimum difference between the predicted results of BNN and the field-measured values. Three HAs are considered, including genetic algorithm (GA), evolutionary strategy (ES), and bat algorithm (BA). A TransModeler case of highway links in Shanghai, China, indicates the validity of the proposed calibration method in terms of error and efficiency. The results demonstrate that the BNN model is able to accurately predict the simulation and adequately capture the uncertainty of the simulation. We also find that the BNN-BA model produces the best calibration efficiency, while the BNN-ES model offers the best performance in calibration accuracy. [ABSTRACT FROM AUTHOR]

This paper investigates the cross-correlations between the foreign flows in A-share market and the uncertainties of market, economy, and policy in home markets, namely, the VIX index and the US EPU index. By employing the cross-correlation statistics and MF-DCCA method, we find the existence of the cross-correlations between the foreign flows and the VIX index, the foreign flows, and the US EPU index from qualitative and quantitative perspectives, respectively. For the cross-correlation between the foreign flows and VIX, small fluctuations are persistent, while large fluctuations are antipersistent. In contrast, the cross-correlation between the foreign flows and US EPU is antipersistent and steady. These results are robust by dividing the foreign flows into two parts in Shenzhen and Shanghai stock exchanges, respectively, and by shortening the periods to after the implementation of Shenzhen-Hong Kong Stock Connect. [ABSTRACT FROM AUTHOR]

Since the end of 2019, the outbreak of COVID-19 has severely affected port production and operation. There is little research on the systematic impact assessment. This study took Shanghai Port as an example and evaluated the impact under different scenarios through establishing a System Dynamics model. It is found that the epidemic mainly has a greater impact on passenger transport, but less on cargo transport. The ports with the function of transportation in highway, railway, and waterway were the key nodes in the international logistics network. More attention should be paid to the impact assessment of COVID-19 on ports' production and operation. It is necessary to strengthen the port's collection and distribution capabilities, improve port production efficiency, and further strengthen port modernization. This research method proposed in this paper can provide a reference for the impact assessment of similar events, and the empirical results can provide a reference for handling the epidemic shock for the port and shipping departments. [ABSTRACT FROM AUTHOR]