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Energy saving has become a key concern of metro systems to reduce operating costs and meet the requirements of sustainable development. Energy-efficient timetabling, an effective way to reduce traction energy consumption, has gotten much attention in recent decades. However, limited research about energy-efficient timetabling simultaneously considered realistic speed profiles and the influence of train loads, which change greatly in different sections and significantly affect energy consumption. Therefore, this paper proposes an energy-efficient timetabling approach to improve regenerative energy utilization based on varying train loads and realistic speed profiles for bidirectional metro lines. First, based on the operational and safety constraints, this paper constructs an integer energy-efficient timetabling model where dwell times and nonuniform headways are taken as decision variables. Besides, the turnaround process is also considered to ensure rolling stock circulation efficiency. Sectional passenger volumes are employed to determine the varying train loads. Energy consumption is calculated based on realistic speed profiles. Owing to the complexity of the model, an improved adaptive large neighborhood search (ALNS) algorithm is designed to solve this model according to its characteristics. Finally, numerical examples are conducted based on the practical data from Shanghai Metro Line 17. The results indicate that the proposed approach effectively solves the energy-efficient timetabling problem with varying train loads and realistic speed profiles for bi-directional metro lines. The approach is suitable for off peak hours and can reduce energy consumption effectively, and the reduction is up to 11.9% for the presented cases. The improved ALNS algorithm can find good solutions within reasonable times in different cases. Moreover, compared with the widely used genetic algorithm in the literature, the improved ALNS algorithm is more efficient in solving the proposed energy-efficient timetabling problem in different cases. [ABSTRACT FROM AUTHOR]

Human geographers are increasingly concerned with how 'futures' are imagined and rendered governable, yet mostly their methods lack the sensitivity to explore the functioning of complex relations between heterogeneous actors across places. The world's electric vehicle (EV) sector is booming, presaging a widely expected decarbonised future, associated with a restructuring of the automobile industry as anticipated by proactive players. This paper interrogates the spatiality and politics of the EV future‐making through disentangling the translocal practices involved in realising Tesla's Gigafactory in Shanghai (TGS) as assemblage. Informed by interviews with industrial insiders and opensource information in Chinese and English, the article finds that, first, TGS's imagined future embodies a multiplicity of interdependent but divergent expectations, the coherence of which underlies the formation and operation of the TGS assemblage by virtue of the concerted actions of its member‐actors. Second, such coherence is conditional as designed by TGS's central planners—namely, Tesla and Chinese government agencies at central and local levels—for their differentiated but overlapping interests. The TGS's imagined future is rendered actionable, enrolling other agents at certain moments, through anticipatory practices of regulatory changes, strategic arrangements interweaving land and financing, firm acquisition and intra‐firm reorganisation linking up places in and outside China, as well as the selection of key suppliers and technological use of critical raw materials. Concluding after a sketch on the TGS's 'possible futures' and broader implications, the paper contributes an assemblage‐informed approach to disentangle futuremaking practices and generates timely insights into the 'future‐oriented' restructuring of the automobile industry. [ABSTRACT FROM AUTHOR]

Buildings increase the urban surface roughness and reduce near‐surface wind speeds in the urban canopy due to the drag effect. Urban heat storage and other effects cause urban warming as well, which decreases the urban boundary layer stability and enhances the turbulence exchange between upper and lower layer. As upper momentum is transported downward, the wind speed of urban canopy increases. Quantitative descriptions of these mechanisms are still lacking currently. This paper presents high‐resolution numerical simulation results of a mega city, Shanghai, China from 2016 to 2020 using the building effect parameterization in WRF (WRF‐BEP) with urban morphological parameters. The dynamic and thermal effects of building morphology on urban canopy wind speed were separated and their quantitative expression functions were given. The results indicate that the influence of building morphology on urban canopy wind speed is mainly dynamic resulting in a wind speed attenuation of approximately 50% and nearly constant. The thermal effect of building morphology on urban canopy wind speed increases with the urban heat island intensity, and the thermal effect could increase urban canopy wind speed by about 30% under the condition of strong urban heat island. The relative contributions of the dynamic and thermal effects of building morphology to urban canopy wind speed change with the wind speed. As wind speed increases, the contribution of the thermal effect of building morphology to urban canopy wind speed gradually decreases. This paper provides a quantitative relationship between the urban canopy wind speed variation and urban morphology, as well as urban heat island intensity. Plain Language Summary: Urbanization changes the dynamic and thermal properties of urban and creates new dynamic and thermal processes in urban areas. Buildings increase the urban surface roughness and reduce urban canopy wind speed due to the drag effect. At the same time, urban warming causes the downward transportation of momentum, which increases the wind speed. Quantitative descriptions of these mechanisms are lacking currently. This study investigated the impact of building morphology on urban canopy wind speed using WRF‐BEP model with high‐resolution urban morphological parameters. The dynamic and thermal effects of building morphology on urban canopy wind speed were separated and their quantitative expression functions were given. Key Points: The dynamic and thermal effects of building morphology on urban canopy wind speed are separatedThe quantitative expression functions of the dynamic and thermal effects of building morphology on wind speed are givenThe relative contributions of the dynamic and thermal effects on urban canopy wind speed are investigated [ABSTRACT FROM AUTHOR]

This paper takes the establishment of the Green Financial Reform and Innovation Pilot Zone (GFPZ) in 2017 as a natural experiment, adopts the data of a-share industrial listed enterprises in Shanghai and Shenzhen from 2010 to 2020, and utilizes the difference-in-differences (DID) method to carry out empirical tests. The results show that (1) GFPZ policy significantly improves the environmental, social, and governance (ESG) performance of enterprises, and the positive effect is mainly realized by improving the external financing ability and green-technology innovation level of enterprises. (2) There is heterogeneity in the impact of GFPZ policy on the ESG performance of firms with different equity natures and internal control levels. (3) Green finance promotes active corporate social responsibility, and it can further improve environmental governance in the regions where it operates. This paper provides a useful supplement to the comprehensive understanding of green-finance policy effects and ESG impact factors, and it is of great significance in mitigating the negative environmental and social externalities caused by the excessive pursuit of economic benefits by enterprises. [ABSTRACT FROM AUTHOR]

Although there is extensive research demonstrating the significant loss and fragmentation of urban spaces caused by rapid urbanization, to date, no empirical research in Shanghai has investigated the spatiotemporal dynamics of urban open spaces using a comprehensive set of integrated geospatial techniques based on long-sequence time series. Based on the Google Earth Engine (GEE) platform and using the Random Forest (RF) classifier, multiple techniques, namely landscape metrics, trend analysis, open space ratio, transition matrix, Normalized Difference Vegetation Index (NDVI), and fractal dimension analysis, were applied to analyze the Landsat satellite data. Next, Geographic Detector (GeoDetector) methods were used to investigate the driving forces of such spatial variations. The results showed that (1) the RF classification algorithm, supported by the GEE, can accurately and quickly obtain a research object dataset, and that calculating the optimal spatial grain size for open space pattern was 70 m; (2) open spaces exhibited declining and contracting trends; and open spaces in the city experienced a decline from 91.83% in 1980 to 69.63% in 2020. Meanwhile, the degree of open spaces in each district increased to different extents, whilst connectivity markedly decreased. Furthermore, the open space of city center districts showed the lowest rate of decrease, with open space patterns fragmenting due to encroaching urbanization; (3) the contribution of socioeconomic factors to the spatial–temporal changes in open space continually has increased over the past 40 years, and were also higher than natural geographic factors to some extent. Apart from offering policy insights guiding the future spatial planning and development of the city, this paper has contributions from both methodological and empirical perspectives. Based on integrated remote sensing and geographic information science (GIS) techniques, this paper provides updated evidence and a clearer understanding of the spatiotemporal variations in urban spaces and their influencing mechanisms in Shanghai. [ABSTRACT FROM AUTHOR]

In China, in recent years it has become a prevailing trend to promote the spatial maturity and high-quality transformation of new towns, yet there are few quantitative methods to evaluate their urban morphological maturity. From the perspective of quantitative urban morphology, this paper integrates street view data and cutting-edge analytical techniques into classic urban morphological study and develops a quantitative index for evaluating urban morphological maturity that fits Chinese cities by adjusting the indicators in line with the unique characteristics of the built environment of Chinese cities. Focusing on five new towns, as well as a historic area, of Shanghai, the paper evaluates their urban morphological maturity with this quantitative index and verifies its validity by comparing the evaluation result with that of expert consensus. It then proposes some design guidelines that may provide robust support for the regeneration of these new towns. Given its reliance on the multi-source data of open access and ready availability, this index holds promise for evaluating the urban morphological maturity of other new towns, to provide support for urban form improvement from both holistic and detailed perspectives. [ABSTRACT FROM AUTHOR]

• A choice experiment was used to assess the preferences and willingness to pay for tangible and intangible industrial heritage. • The case study is the Baosteel steel factory, an industrial brownfield in Shanghai planned to be transformed into an arts and entertainment hub. • The results show that individuals tend to support selective rather than extensive preservation of physical attributes of the industrial sites. • Findings show there exist a demand for preserving and transmitting the intangible heritage of industrial culture along with adaptive reuse of the industrial sites. Industrial heritage has in recent years become an important component in land use and urban development policies. Yet, assessing the economic value associated with the preservation and reuse of industrial complexes remains an open question. In this paper, we apply a discrete choice experiment (DCE) method to assess the economic valuation of the Baosteel steel factory, an industrial brownfield in Shanghai planned to be transformed into an arts and entertainment hub. By eliciting the preferences of locals for the preservation and reuse of distinct attributes of the site, our findings suggest that the preservation of significant landmarks and the intangible component of the industrial site are the two most relevant attributes worth protection. Moreover, we add evidence on the relationship between respondents' economic preferences and their attitude toward the cultural value conveyed by industrial heritage by showing how distinct groups of respondents express different preferences for single attributes of the industrial heritage. The paper contributes to the heritage valuation literature by illustrating the implications and challenges of assessing the demand for industrial heritage rehabilitation projects. [ABSTRACT FROM AUTHOR]

The BL17B beamline at the Shanghai Synchrotron Radiation Facility was first designed as a versatile high‐throughput protein crystallography beamline and one of five beamlines affiliated to the National Facility for Protein Science in Shanghai. It was officially opened to users in July 2015. As a bending magnet beamline, BL17B has the advantages of high photon flux, brightness, energy resolution and continuous adjustable energy between 5 and 23 keV. The experimental station excels in crystal screening and structure determination, providing cost‐effective routine experimental services to numerous users. Given the interdisciplinary and green energy research demands, BL17B beamline has undergone optimization, expanded its range of experimental methods and enhanced sample environments for a more user‐friendly testing mode. These methods include single‐crystal X‐ray diffraction, powder crystal X‐ray diffraction, wide‐angle X‐ray scattering, grazing‐incidence wide‐angle X‐ray scattering (GIWAXS), and fully scattered atom pair distribution function analysis, covering structure detection from crystalline to amorphous states. This paper primarily presents the performance of the BL17B beamline and the application of the GIWAXS methodology at the beamline in the field of perovskite materials. [ABSTRACT FROM AUTHOR]

Based on 908 consumer questionnaire data from 15 urban areas in Shanghai, we use the binary logit model to empirically analyze the impact of traceability label trust on consumers' traceable pork purchase behavior and the moderating effect of food safety identification. After constructing the theoretical analysis framework, this paper verifies it from the two aspects of statistical analysis and econometric analysis and tests the robustness of the final results. The results show that: first, traceability label trust has a significant positive impact on consumers' traceability pork behavior. Second, food safety identification can significantly strengthen and promote this process. Third, consumers' purchasing behavior is significantly positively affected by traceable pork consumption scenarios and price labels, but the permanent elderly in the composition of family members significantly negative impact on it. Therefore, we put forward relevant policy suggestions, such as strengthening the knowledge popularization and publicity based on the advantageous commodity attributes of traceable pork, carrying out food safety knowledge popularization education, and enhancing consumers' risk perception and food safety identification ability. [ABSTRACT FROM AUTHOR]

Prior literature finds senior executives can influence auditor decision making. However, few studies have discussed the impact of employee's personal characteristics. Our research aims to fill the above research gaps by examining the impact of employee level education on audit costs. Taking A-share listed companies in Shanghai and Shenzhen from 2006 to 2021 as the research object, this paper examines the impact of employee education on audit fees. It is found that highly educated employees can effectively reduce the audit fees borne by the company, but the implementation of the Labor Protection Law weakens this inhibitory effect. In the case of low marketization level and weak Confucian culture intensity, employee education level has a more significant inhibitory effect on audit fees of listed companies. This study provides a basis for empirical research on the impact of employee attributes on auditor decision making, provides a new research perspective on the impact of labor protection law at the corporate micro level, and enriches the theoretical research on corporate governance rooted in traditional Chinese culture. We contribute to the practice that implications for evaluating the effectiveness of adopting labor protection. [ABSTRACT FROM AUTHOR]

In shield tunneling, the joint is one of the most vulnerable parts of the segmental lining. Opening of the joint reduces the overall stiffness of the ring, leading to structural damage and issues such as water leakage. Currently, the Winkler method is commonly used to calculate structural deformation, simplifying the interaction between segments and soil as radial and tangential Winkler springs. However, when introducing connection springs or reduction factors to simulate the joint stiffness of segments, the challenge lies in determining the reduction coefficient and the stiffness of the springs. Currently, the hyperstatic reflection method cannot simulate the discontinuity effect at the connection of the tunnel segments, while the state space method overlooks the nonlinear interaction between the tunnel and the soil. Therefore, this paper proposes a numerical simulation method considering the interaction between the tunnel and the soil, which is subjected to compression rather than tension, and the discontinuity of the joints between the segments. The model structure and external load are symmetrical, resulting in symmetrical calculation results. This method is based on the soft soil layers and shield tunnel structures of the Shanghai Metro, and the applicability of the model is verified through deformation calculations using three-dimensional laser scanning point clouds of sections from the Shanghai Metro Line 5. When the subgrade reaction coefficient is 5000 k N / m 3 , the model can effectively simulate the deformation of operational tunnels. By adjusting the bending stiffness of individual connection springs, we investigate the influence of bending stiffness reduction on the bending moment, radial displacement, and rotational displacement of the ring. The results indicate that a decrease in joint bending stiffness significantly affects the mechanical response of the ring, and the extent and degree of this influence are correlated with the joint position and the magnitude of joint bending stiffness. [ABSTRACT FROM AUTHOR]

BL19U1, an energy‐tunable protein complex crystallography beamline at the Shanghai Synchrotron Radiation Facility, has emerged as one of the most productive MX beamlines since opening to the public in July 2015. As of October 2023, it has contributed to over 2000 protein structures deposited in the Protein Data Bank (PDB), resulting in the publication of more than 1000 scientific papers. In response to increasing interest in structure‐based drug design utilizing X‐ray crystallography for fragment library screening, enhancements have been implemented in both hardware and data collection systems on the beamline to optimize efficiency. Hardware upgrades include the transition from MD2 to MD2S for the diffractometer, alongside the installation of a humidity controller featuring a rapid nozzle exchanger. This allows users to opt for either low‐temperature or room‐temperature data collection modes. The control system has been upgraded from Blu‐Ice to MXCuBE3, which supports website‐mode data collection, providing enhanced compatibility and easy expansion with new features. An automated data processing pipeline has also been developed to offer users real‐time feedback on data quality. [ABSTRACT FROM AUTHOR]

Crises constitute ideal opportunities for authoritarian leaders to promote certain narratives, shaping reality in their favor and crafting their own preferred storylines about current events. In other words: they serve authoritarian leaders on a silver platter the opportunity to instrumentalize these unforeseen circumstances to gain domestic political legitimacy by promoting strategic narratives. The COVID-19 pandemic was no exception in this regard. Ever since its onset in early 2020, the Chinese Communist Party (CCP) was among the most active actors worldwide seeking to capitalize on the global crisis for legitimation purposes. Whether applying narratives of governance supremacy, portraying the People's Republic of China as a "global savior," or promoting emotionally appealing nationalistic narratives, the regime used the pandemic as a window of opportunity to rebrand its international role and enhance its domestic legitimacy. When observing the CCP's communication style over the course of 24 pandemic months (2020–2022), however, major shifts become apparent regarding the main narratives crafted in communication with national audiences. Based on this, the paper focuses on the role of such narratives for legitimation claims. Using exemplary media articles collected between the outbreak of the pandemic in China in late 2019 until the harsh Shanghai lockdown in spring 2022, it thus traces the narratives employed by Chinese state elites and explores how they are intertwined with nationalism and broader power claims. [ABSTRACT FROM AUTHOR]

To improve the anti-interference ability of maglev trains, a dynamic model of the high-speed maglev train with a nonlinear suspension controller for the guideway system is proposed in this paper. Based on the nonlinear characteristics of the magnetic suspension system, a nonlinear decoupling controller is designed using the feedback linearization theory. Then, a high-speed maglev train model is refined with a guideway coupling system, consisting of a maglev train simulated as a multi-body dynamics model with 537 degrees of freedom and a spatial finite element model of the guideway. Taking the Shanghai high-speed maglev train as an example, the correctness of the computational model is verified by comparing the modeling results with field measurement data, and the control effectiveness of the nonlinear controllers and the traditional PD controllers is compared considering different train speeds and disturbance forces. The results show that the suspension gap under the decoupling control is smaller than that under the PD control during the train operations. Under the same disturbance force, the decoupling control exhibits better control performance than the PD control. The variation amplitudes of the magnetic pole gaps are generally linearly related to the disturbance force. [ABSTRACT FROM AUTHOR]

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]

To explore the relationship between air pollution and total factor productivity and new pathways, This paper examines the impact of air pollution on total factor productivity of A-share listed companies in Shanghai and Shenzhen between 2015 and 2019. It investigates this relationship by considering two pathways: investor sentiment and government attention. The findings indicate that air pollution suppresses total factor productivity of firms. However, air pollution stimulates investor sentiment, which in turn increases R&D investment and total factor productivity, reducing to some extent the dampening effect of air pollution on total factor productivity. There exists a notable positive correlation between air quality and government attention, acting as a mediating variable. This implies that air pollution has the potential to capture the attention of governmental entities, leading to the implementation of appropriate measures aimed at managing and mitigating the occurrence of air pollution caused by industrial enterprises.And the relevant governments should formulate a series of policies to meet the different needs of different enterprises. These two approaches have varying impacts depending on the type of enterprises, thus governments should develop laws to cater to the various demands of different types of enterprises. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) pandemic disrupted public health and economies worldwide. In this paper, we investigate an optimal control problem to simultaneously minimize the epidemic size and control costs associated with intervention strategies based on official data. Considering people with undetected infections, we establish a control system of COVID-19 with time-varying parameters. To estimate these parameters, a parameter identification scheme is adopted and a mixed algorithm is constructed. Moreover, we present an optimal control problem with two objectives that involve the newly increased number of infected individuals and the control costs. A numerical scheme is conducted, simulating the epidemic data pertaining to Shanghai during the period of 2022, caused by the Omicron variant. Coefficient combinations of the objectives are obtained, and the optimal control measures for different infection peaks are indicated. The numerical results suggest that the identification variables obtained by using the constructed mixed algorithm to solve the parameter identification problem are feasible. Optimal control measures for different epidemic peaks can serve as references for decision-makers. [ABSTRACT FROM AUTHOR]

The undulator is a key luminous component of the Shanghai high repetition rate x-ray free electron laser and extreme light facility, and the motion control system is an important part of the undulator. The main task of the motion control system is to complete the high precision adjustment of the gap and taper between the upper magnetic pole girder and lower magnetic pole girder, so as to adjust the wavelength of the radiation light. According to the development requirements of the motion control system for the U26 undulator, which is a conventional permanent magnet, this paper proposes a new motion control system with double position feedback closed-loop control, including programmable logic controller (PLC) closed-loop control based on position feedback by a linear absolute encoder (LAE) and driver closed-loop control based on position feedback by a rotary absolute encoder (RAE) of a servo motor. Multiple motion tests of the U26 undulator have shown that the repeatability accuracy of the gap is ±50 nm and the gap drive can reach 0.1 µm step size, the error of which is about ±20 nm according to the feedback of the LAE. The conclusion can be drawn that the motion step size and repeatability accuracy of the motion control system for the U26 undulator are improved by one order of magnitude on the basis of meeting all technical requirements. At the same time, motor torque protection, motor temperature protection, and redundant position protection with RAE can further improve the reliability and safety of the motion control system for the U26 undulator. [ABSTRACT FROM AUTHOR]

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

Background: Public health emergencies are characterized by uncertainty, rapid transmission, a large number of cases, a high rate of critical illness, and a high case fatality rate. The intensive care unit (ICU) is the "last line of defense" for saving lives. And ICU resources play a critical role in the treatment of critical illness and combating public health emergencies. Objective: This study estimates the demand for ICU healthcare resources based on an accurate prediction of the surge in the number of critically ill patients in the short term. The aim is to provide hospitals with a basis for scientific decision-making, to improve rescue efficiency, and to avoid excessive costs due to overly large resource reserves. Methods: A demand forecasting method for ICU healthcare resources is proposed based on the number of current confirmed cases. The number of current confirmed cases is estimated using a bilateral long-short-term memory and genetic algorithm support vector regression (BILSTM-GASVR) combined prediction model. Based on this, this paper constructs demand forecasting models for ICU healthcare workers and healthcare material resources to more accurately understand the patterns of changes in the demand for ICU healthcare resources and more precisely meet the treatment needs of critically ill patients. Results: Data on the number of COVID-19-infected cases in Shanghai between January 20, 2020, and September 24, 2022, is used to perform a numerical example analysis. Compared to individual prediction models (GASVR, LSTM, BILSTM and Informer), the combined prediction model BILSTM-GASVR produced results that are closer to the real values. The demand forecasting results for ICU healthcare resources showed that the first (ICU human resources) and third (medical equipment resources) categories did not require replenishment during the early stages but experienced a lag in replenishment when shortages occurred during the peak period. The second category (drug resources) is consumed rapidly in the early stages and required earlier replenishment, but replenishment is timelier compared to the first and third categories. However, replenishment is needed throughout the course of the epidemic. Conclusion: The first category of resources (human resources) requires long-term planning and the deployment of emergency expansion measures. The second category of resources (drugs) is suitable for the combination of dynamic physical reserves in healthcare institutions with the production capacity reserves of corporations. The third category of resources (medical equipment) is more dependent on the physical reserves in healthcare institutions, but care must be taken to strike a balance between normalcy and emergencies. [ABSTRACT FROM AUTHOR]

The energy factor is the foundation of economic and social development, and it is also an important prerequisite for the effective operation of the elderly care industry. Based on the perspective of energy factor input, this paper constructs the DPSR mechanism model of the energy-elderly care industry system. Taking Shanghai as an example, through its 2010–2019 15 index data such as energy factors and industrial economy, the Entropy-TOPSIS method is comprehensively used to evaluate the energy-elderly care industry system. Finally, the following conclusions are drawn: (1) The energy factor has an important impact on the operation of the elderly care industry through its effect on the driving force module, the pressure module and the state module; (2) The elderly care industry has an important impact on the energy factor through the conduction of the response module; (3) The evaluation results of the Shanghai energy-elderly care industry system showed a continuous improvement trend from 2010 to 2019. [ABSTRACT FROM AUTHOR]

The analysis of the multi-scale evaluation of port city's international trade goal is conducive to the sustainable development of port city's international trade. In order to make a more in-depth study on the realization ability of port city's international trade sustainable development goal, this paper proposes a new multi-scale evaluation method of port city's international trade goal. This method selects the evaluation indexes, uses the improved normalization method to process the indexes, uses the combination of AHP and factor analysis method to form the subjective and objective combination weighting method, brings the processed indexes into the least square optimization combination evaluation model, calculates the index weight, and uses the fuzzy evaluation method to carry out multi-scale index evaluation on the international trade of port cities to realize its multi-scale evaluation and analysis. The results show that the standardized index of Shanghai's foreign trade dependence is 0.0056, indicating its independence in international trade. In the comprehensive evaluation, the evaluation values of Shanghai, Tianjin, and Guangzhou are 92.56, 87.89, and 88.45, respectively, which are very close to the actual results, which shows that the accuracy of the evaluation method is high, and provides a theoretical basis for the sustainable development of international trade in port cities. [ABSTRACT FROM AUTHOR]

Using data from the 2015 China Household Financial Survey (CHFS) this paper examines the effect of culture on the gender gap in financial literacy. We exploit geographical differences in culture in China, comparing outcomes between rural and urban areas and between areas in the east and west (Shanghai and Chongqing). Using the Blinder‐Oaxaca decomposition we show that, nationally, the gender gap in financial literacy is entirely the product of differences in the way men and women acquire financial literacy. It is a result consistent with cultural effects. When considering just women in Shanghai and Chongqing we observe a raw financial literacy differential of 13% (favoring Shanghai). This gap is also the product of differences in the way financial literacy is acquired. It provides additional evidence as to the importance of culture when it comes to understanding financial literacy. [ABSTRACT FROM AUTHOR]

This paper addresses doctor-patient communication about C-sections (CSs) in Shanghai, China. Specifically, we examine the information discrepancies between obstetricians' and patients' perceptions of CS and the important factors affecting shared decision-making. We conducted semi-structured individual interviews with 12 postnatal women who experienced CS and with 12 obstetricians. We identified barriers to patient-doctor communication and shared decision-making: obstetricians' lack of time in outpatient prenatal visits to explain the implications of CSs, family members' knowledge and opinions on CSs, and information from media and social networks. The lack of communication between the expectant women and the obstetricians was driving the women's distrust in the latter. The lack of obstetricians' time to communicate with the pregnant woman led to low trust in the medical staff and overutilization of CS, whereas a lack of financial resources led to underutilization of CS. The obstetricians suggested providing expectant women with more education programs and midwifery support. [ABSTRACT FROM AUTHOR]

Single and multi-vehicle (SMV) crashes remain a significant issue, causing serious safety and economic concerns, and therefore deserve more attention. Using crash data in the Beijing-Shanghai and Changchun-Shenzhen freeways over the five years (2015–2019), this paper explored the transferability and heterogeneity for crash type (single-vehicle versus multi-vehicle crashes) and spatiotemporal stability of determinants affecting the injury severity. The random parameters logit approach with heterogeneity in means and variances was used to model three possible crash injury severity outcomes (measured by the most severely injured individual in the crash) of no injury, minor injury, and severe injury and identify the determinants in terms of driver, vehicle, roadway, environment, temporal, spatial, traffic, and crash characteristics. Remarkable differences were observed in the SMV crashes, and the contributing factors also reported considerable temporal and (or) spatial instabilities. The insights of this study should be valuable to help freeway designers and decision-makers understand the contributing mechanism of the factors and develop the proper management strategies and enforcement countermeasures. [ABSTRACT FROM AUTHOR]

During the winter of 2019, the global outbreak of COVID-19 prompted extensive research on urban air pollution under lockdown measures. However, these studies predominantly focused on winter conditions, thereby limiting investigations into changes in urban air pollutants during other seasons that were also subject to lockdown restrictions. Shanghai, China, has undergone two COVID-19 lockdown periods in two seasons: winter 2019 and spring 2022. The seasonal variations and human activities were represented by meteorological factors and nighttime light brightness in this paper, respectively. The reduction in human-related emissions during the two lockdown periods was estimated based on the targets outlined in China's Air Pollution Prevention and Control Action Plan. The results showed significant reductions in NO2 and PM particles during the two lockdown periods, both accompanied by a notable increase in O3 concentration. In comparison to the winter lockdown, there was an approximate 40% decrease in the NO2 and PM2.5 concentrations in the spring, while the O3 concentration exhibited an increase of 48.81%. Furthermore, due to shifting wind patterns during the two lockdowns from winter to spring, the high-pollution core areas shifted 20–25 km southeastward in the spring. The PM particles and NO2 concentrations exhibited a considerable impact from human activities, whereas the O3 concentration was affected mostly by seasonal change and interactions among air pollutants. Compared to the corresponding non-lockdown condition, the concentration of CO decreased during the winter lockdown; however, it increased during the spring lockdown. The different change in CO concentration during the two lockdown periods was found to have a lower effect on the O3 concentration than that caused by changes in meteorological factors and nitrogen oxide (NO, NO2) concentrations. In summary, the impact of COVID-19 lockdown periods on urban air pollutants was more pronounced in spring compared to winter, and the interactions among air pollutants also underwent alterations. [ABSTRACT FROM AUTHOR]

Recent advances in knowledge graphs show great promise to link various data together to provide a semantic network. Place is an important part in the big picture of the knowledge graph since it serves as a powerful glue to link any data to its georeference. A key technical challenge in constructing knowledge graphs with location nodes as geographical references is the matching of place entities. Traditional methods typically rely on rule-based matching or machine-learning techniques to determine if two place names refer to the same location. However, these approaches are often limited in the feature selection of places for matching criteria, resulting in imbalanced consideration of spatial and semantic features. Deep feature-based methods such as deep learning methods show great promise for improved place data conflation. This paper introduces a Semantic-Spatial Aware Representation Learning Model (SSARLM) for Place Matching. SSARLM liberates the tedious manual feature extraction step inherent in traditional methods, enabling an end-to-end place entity matching pipeline. Furthermore, we introduce an embedding fusion module designed for the unified encoding of semantic and spatial information. In the experiment, we evaluate the approach to named places from Guangzhou and Shanghai cities in GeoNames, OpenStreetMap (OSM), and Baidu Map. The SSARLM is compared with several classical and commonly used binary classification machine learning models, and the state-of-the-art large language model, GPT-4. The results demonstrate the benefit of pre-trained models in data conflation of named places. [ABSTRACT FROM AUTHOR]

Building change detection (BCD) plays a vital role in city planning and development, ensuring the timely detection of urban changes near metro lines. Synthetic Aperture Radar (SAR) has the advantage of providing continuous image time series with all-weather and all-time capabilities for earth observation compared with optical remote sensors. Deep learning algorithms have extensively been applied for BCD to realize the automatic detection of building changes. However, existing deep learning-based BCD methods with SAR images suffer limited accuracy due to the speckle noise effect and insufficient feature extraction. In this paper, an attention-guided dual-branch fusion network (ADF-Net) is proposed for urban BCD to address this limitation. Specifically, high-resolution SAR images collected by TerraSAR-X have been utilized to detect building changes near metro line 8 in Shanghai with the ADF-Net model. In particular, a dual-branch structure is employed in ADF-Net to extract heterogeneous features from radiometrically calibrated TerraSAR-X images and log ratio images (i.e., difference images (DIs) in dB scale). In addition, the attention-guided cross-layer addition (ACLA) blocks are used to precisely locate the features of changed areas with the transformer-based attention mechanism, and the global attention mechanism with the residual unit (GAM-RU) blocks is introduced to enhance the representation learning capabilities and solve the problems of gradient fading. The effectiveness of ADF-Net is verified using evaluation metrics. The results demonstrate that ADF-Net generates better building change maps than other methods, including U-Net, FC-EF, SNUNet-CD, A2Net, DMINet, USFFCNet, EATDer, and DRPNet. As a result, some building area changes near metro line 8 in Shanghai have been accurately detected by ADF-Net. Furthermore, the prediction results are consistent with the changes derived from high-resolution optical remote sensing images. [ABSTRACT FROM AUTHOR]

This study was designed based on a cross-sectional investigation conducted Shanghai, China. Demographic characteristics, diaper utilization, Activities of Daily Living (ADL) and emotion were collected by Unified Needs Assessment Form for Elderly Care Questionnaire. Cognition function was assessed by Mini-mental State Examination (MMSE) scale. Multivariate logistic regression was used for statistical analysis. The diaper utilization rate was 31.2%. Female, higher level of education, poorer ADL and cognition, more severe incontinence and financial dependence on others were facilitating factors for diaper usage (P < 0.05). The possibility of using diaper differed according to the intimacy of caregivers. Among incontinent individuals with relatively good ADL and cognition level, diaper utilization can significantly decrease the risk of going out only once a month (OR: 2.63 vs 4.05), and going out less than once a month (OR: 5.32 vs 6.53). Incontinence people who going out at least once a week had a lower risk of some negative emotion. Significantly, diaper utilization further decreased this risk. In conclusion, for incontinence elderly people with relatively independent ability, proper use of diaper may improve the frequency of outdoor activity and emotion. Nevertheless, diaper utilization should be decided based on elderly people's own will. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to investigate the impact of performance feedback (performance expectation surplus, performance expectation deficit) on corporate ESG performance, and this paper also to investigate the role of environmental strategy as a mechanism in the impact of enterprises' performance feedback on corporate ESG performance. Design/Methodology/Approach: The study used data from 3679 companies listed on the Shanghai and Shenzhen stock exchanges for the period 2009–2021 and also measured the intensity of corporate environmental strategies through analysis. Finally, we used a fixed effects model to test the research hypothesis. Findings: This study shows that enterprise performance feedback positively affects corporate ESG performance and that environmental strategy plays a significant mechanistic role in enterprise performance feedback and corporate ESG performance. Overall, performance expectation surplus negatively affects ESG performance, performance expectation deficit positively affects ESG performance, and the mechanism of environmental strategy plays a significant role in performance expectation deficit and ESG performance. Practical implications: The results of this study can help enterprises establish a scientific environmental management system, strengthen the supervision of enterprise environmental management, and have certain reference significance for enterprises to speed up the implementation of environmental protection measures. Originality/Value: This study adds to the literature by describing corporate ESG performance using performance feedback theory and explaining the inherent role of enterprise performance feedback in corporate ESG performance utilizing environmental strategies. [ABSTRACT FROM AUTHOR]

Currently, countries worldwide are embracing digital strategies, enabling enterprises to utilize digital technology, digital supply chains, blockchain, and additional digital measures to increase their competitiveness. This paper analyzed the correlation between the digital transformation of manufacturing export enterprises and their business and export performance, focusing on China's manufacturing export enterprises through empirical analysis. The study investigated the influence of digital transformation on enterprise performance. Using the Resource Based View theory and Trade theory, hypotheses were proposed and regression models were developed to analyze a sample of 1007 enterprises listed on the Shanghai and Shenzhen Stock markets from 2012 to 2019. The study conducted regression analysis, intermediate effect test, robustness test, stage lag, and heterogeneity analysis. The study found that (1) Manufacturing export enterprises listed in the stock market implemented digital transformation, leading to a significant positive impact on their overall performance. (2) Digital transformation led to cost reduction, improved R&D intensity, and enhanced human resources, among other benefits for enterprise performance. (3) According to the fractal analysis, non-state-owned enterprises exhibited more favorable effects on enterprise performance, and the digital transformation of manufacturing export companies in developed regions had a more significant impact on their performance. Finally, the study's empirical results yielded pertinent proposals for digital transformation. [ABSTRACT FROM AUTHOR]

In this paper we study planned and unplanned adjustment processes in master-planned communities and new towns by a first wave of residents, in which changes in lifestyles play a central role. How can unplanned transitions be stimulated and play a role in making a new town more attractive, sustainable, adjustable, and flexible in use? We apply this to the case of Anting New Town in Shanghai. We focus on both personal and collective adjustments and appropriation in housing, commercial, as well as public space. We explore methods of doing visual research by observation, in line with methods by Venturi and Boudon. By adding economic and socio-cultural drivers and institutional frameworks, which allow these alterations to happen, conclusions are made about the possible sustainability, adjustability, and flexibility of these planned structures. We analyze adjustments from different perspectives on the themes of urbanity and identity: (1) architectural-morphological, (2) functional-economical, and (3) socio-cultural. Following different approaches to studying the planned and unplanned city, we explain how the urbanity and identity of Anting have changed in various ways. Appropriation of building structures and urban spaces is a key element in this process of change. It is the outcome of a wider process of economic and socio-cultural change. [ABSTRACT FROM AUTHOR]

This paper studies when and under what conditions the actions undertaken by the power plants involved in China's emission trading scheme (ETS) pilot became cost effective. Based on unique plant-level panel data and the difference-in-differences strategy, we identify that an insignificant initial reduction in cost efficiency occurred at the announcement stage for power plants in the pilot provinces; however, the cost efficiency of the pilot plants increased significantly following formal policy implementation. Additionally, the by-stage treatment effects differed across the pilot provinces due to localized market and non-market variations. Localized conditions of higher marketization, stricter policy enforcement, and lower carbon dependence enhanced this positive effect. The synthetic control results confirmed this variation in the policy effects. The carbon trading pilots resulted in improved efficiency in power plants in Shanghai, Guangdong, and Tianjin during the period 2013--2017, with an associated total cost saving of approximately 29.75 million RMB. To enhance the efficacy of the ETS policy, our findings suggest that the design of the policy should consider localized external factors. [ABSTRACT FROM AUTHOR]

During rapid urbanization, microclimate environment deterioration through events such as haze pollution and heat waves has continuously occurred in cities, which greatly affects the living environment, production activities, and health of urban residents. Therefore, it is particularly necessary to explore methods for controlling and optimizing the urban microclimate environment. In this paper, based on the mechanism of the effect of urban spatial structure at street-level on the distribution of atmospheric particulate matter, an indicator system that can be employed to comprehensively describe and quantify urban morphological structure at street-level was constructed from eight aspects: the spatial morphology of street-valleys, intensity of land use and development, geometric structure of buildings, inhomogeneity of buildings, roughness of the underlying surface, distribution of ecological landscapes, 3D architectural landscape morphology, and ventilation potential. Furthermore, using satellite remote sensing images and vector thematic maps of Shanghai, indicator factors were quantified by applying GIS technique. The intrinsic mechanism of the influence of the urban morphology on the diffusion and transport of atmospheric particulate matter was comprehensively analyzed by combining statistical methods and data mining algorithm, and eight key dominant factors were identified that can be considered to improve the urban ventilation conditions and help control urban air pollution, namely, the land use intensity, urban canopy resistance, vegetation cover, spatial congestion rate, comprehensive porosity, height-to-gross floor area ratio, building density, and average building volume ratio. As such, according to the quantitative analysis results for various combinations of the dominant factors, a spatial optimization strategy at street-level that can help improve the urban air quality was proposed in terms of identifying the pathways through which urban spatial elements affect the distribution of particulate matter, i.e., controlling the source–flow diversion–flow convergence process. [ABSTRACT FROM AUTHOR]

As the aging population continues to grow, the increasing number of disabled elderly individuals poses ongoing challenges to society in terms of healthcare and medical burdens. Grading disability is of significant importance for improving medical services and allocating social resources. Traditional grading methods using a single assessment scale tend to be subjective and cannot comprehensively and accurately reflect the real situation. This paper presents the NES (Needs assessment of Elderly care in Shanghai) scale, based on 33 quantified scoring items from basic surveys, to enhance the objectivity and accuracy of disability grading. Correlation analysis of observed items using the C4.5 decision tree algorithm is conducted, followed by an analysis and evaluation of the scale's performance. The data used in this study are derived from 266 questionnaires collected from eight regions in Shanghai and categorized into three classes: physiological (JKOM/BADL), psychological (BDI/SDS/SAS), and cognitive (CDR). The analysis results show that the NES scale exhibits better robustness in physiological assessment compared to the BADL and JKOM scales. In psychological assessment, the NES scale performs similarly to the SDS and SAS scales. In cognitive assessment, the NES scale's grading level is slightly higher than that of the CDR scale, demonstrating good comprehensive disability assessment capabilities. [ABSTRACT FROM AUTHOR]

This paper aims at discussing the recent evolutions experienced by housing in Contemporary China through the study of the living habits of wealthy families in the fringes of Shanghai and Chongqing. The copycat phenomenon widespread across Chinese cities is one example, on the one hand, of the transformations of social uses of the house which gains a dimension of visibility; and, on the other hand, of an object that so far has been studied only through Western-centred conceptions of visuality and materiality. This research offers a different perspective, one of the inhabitants of neighbourhoods with exotic atmospheres. The analysis of the discourse of the residents as well as their daily practices of space appropriation and home decoration reveals that the house plays a new role in social interactions. As a social mean of representing the status of its occupants, the outside part of the building, its surroundings and some of the interior are assigned a visual dimension destined to the outside viewers and guests of the family, transforming the relationships between the public and private spheres which duality do not match the one of what is visible and what is invisible. Contrariwise to general views about the Western style neighbourhoods, what is offered to the view does not convey a process of westernisation or acculturation of the daily life, but expresses the will for a liberation from certain social constraints experienced in the former place of residency. The Chinese contemporary home is then, among this wealthier part of the population where domestic space is a valuable resource, the place of production of a new urbanity where different forms of sociality and representations coexist. [ABSTRACT FROM AUTHOR]

Based on mobile positioning big data, this study analyzes the quantity of visitation changes of leisure tourism facilities under the impact of COVID-19, which is a direct way to evaluate the impact of COVID-19 on the leisure tourism industry. The quantity of visitation to the four types of leisure facilities (scenic spots, shopping services, sports services, science and cultural education services) in the three Chinese cities (Beijing, Shanghai, and Qingdao) decreased by 63.06% and 44.74% respectively on the Tomb Sweeping Day and the Labor Day in 2020 compared with 2019. The biggest decreasing was in science and cultural education services, followed by scenic spots and sports services, and finally shopping services. The curve of hourly visitations to leisure facilities in 2020 shows a smooth feature, indicating that the public has reduced the risk of pandemic through peak shifting leisure. The analysis of influencing factors shows that the influence of the floor area on visitation is different in different phases. From Tomb Sweeping Day to Labour Day in 2020, the influence of area on leisure behaviour changes from negative to positive. This paper provides a technical framework for assessing the impact of crisis event, and expands the protection motivation theory. [ABSTRACT FROM AUTHOR]

This study focuses on investigating the shear behavior of the Shanghai clay-concrete interface under cyclic loading using a large-scale multifunctional shear apparatus. Considering that soil-structure interfaces are typically found in shallow soil layers or even above the ground surface, the interface zone is unsaturated in its natural state, the shear experiments were therefore conducted on the tested soil with different water contents. The corresponding matric suction of the tested soil under different water content and initial dry densities was determined by the filter paper method. The experimental findings indicate a substantial influence of matric suction on the interfacial strength, revealing a pronounced non-linear relationship. The interface exhibits the highest shear strength during the initial shear, which gradually decreases with an increasing number of shear cycles. This reduction can be attributed to the weakening of the bonding effect at the interface caused by cyclic shear. On the other hand, the matric suction decreases with water content increases, leading to a decrease in interface shear strength. Additionally, the vertical cumulative displacement of the soil increases with higher water content. • Cyclic shear experiments were conducted on the interface between unsaturated Shanghai clay and concrete. • The interface strength exhibits a non-linear relationship with the matric suction. • The contribution of matric suction to the interface strength is significantly influenced by the number of shear cycles. [ABSTRACT FROM AUTHOR]

With the rapid development of technologies such as cloud computing and big data, various levels of government departments in the country have successively introduced digital subsidy policies to promote enterprises' digital transformation. However, the effectiveness of these policies and their ability to truly achieve policy objectives have become pressing concerns across society. Against this backdrop, this paper employs a moderated mediation effects model to empirically analyze the incentive effects of financial subsidies on the digital transformation of A-share listed manufacturing companies in the Shanghai and Shenzhen stock markets from 2013 to 2022. The research findings indicate a significant promotion effect of financial subsidies on the digital transformation of manufacturing enterprises, especially demonstrating a notable incentive impact on the digital transformation of large enterprises, non-asset-intensive enterprises, technology-intensive enterprises, and non-labor-intensive enterprises. However, the incentive effect on the digital transformation of small and medium-sized enterprises (SMEs), asset-intensive enterprises, non-technology-intensive enterprises, and labor-intensive enterprises is not significant. Notably, the expansion of financial subsidies positively influences the augmentation of R&D investment within manufacturing enterprises, subsequently providing indirect encouragement for their digital transformation. Additionally, the incorporation of the degree of marketization implies its potential to moderate both the direct and indirect impacts of financial subsidies on enterprise digital transformation. This study enriches the research on the mechanism of the role of financial subsidies in digital transformation and provides empirical evidence on how market participation influences the effects of financial subsidies, thereby assisting policymakers in comprehensively understanding the impact of financial subsidy policies on different types of enterprises. [ABSTRACT FROM AUTHOR]

This research paper gleans insights from significant historical cases to unravel the essence of a 'creative milieu.' Our study scrutinizes the factors that shaped artists' settlement patterns in Shanghai during the Republican era (1912–1948) by constructing both global and local spatial regression models across three pivotal years, thus unveiling seven distinct variable categories. We argue that paramount among these attributes are individual art intermediaries, art schools, and art organizations. Furthermore, our inquiry acknowledges the diverse and idiosyncratic characteristics inherent to artistic communities and delineates between attributes of particular relevance to the Chinese context and those adaptable within a Western paradigm. [ABSTRACT FROM AUTHOR]

The majority of modal disparity studies focus on accessibility to jobs and to non-work activities with little attention paid to actual commuting behavior. How modal differences in commuting behavior change when set against the minimum and maximum commutes possible within a fixed urban structure is much less known. In commuting efficiency studies, the mode of commuting flows has not been intersected with socio-economic characteristics. Using the 2015 1 % National Population Sample Survey (NPSS) in Shanghai, we apply the excess commuting framework to fill this research gap by measuring the modal disparity between public transport and cars, in commuting efficiency by education level of workers. Results show that public transport users are less efficient commuters than car users, indicating great capacity exists for optimizing public transportation. However, the modal disparity decreases with increasing educational attainment, because car commuting efficiency is decreasing at a faster rate than for public transport. Based on these findings, urban transportation policy should focus on improving jobs-housing balance of public transport, and building a friendly green travel environment to rectify car-oriented bias in urban spatial structure and narrow the difference between public transport users and car users, especially for the poorly-educated. • This paper is the result of an international collaboration between three authors who have worked extensively on topics related to commuting. • The paper examines aspects of the demographics and transportation interactions in Shanghai. • A very notable finding is the overwhelming mode share in public transport for the least educated workers. • The paper shows the importance of heterogeneity of socioeconomic characteristics in estimating excess commuting. [ABSTRACT FROM AUTHOR]

To achieve carbon neutrality quickly and deal with urban greenhouse effect, it is necessary to study the energy consumption of urban buildings. Energy consumption prediction is an important step in planning and managing energy use in buildings. At present, few studies have comprehensively considered the relationship between geometric features, functional types, location and energy use of buildings in urban built-up areas. In this paper, a spatial data-driven framework is introduced for the analysis and assessment of building energy consumption. The framework is grounded in the building centroid and is combined with single photon radar and point of interest data through the utilization of the nearest neighbor classification algorithm. Two megacities, Beijing and Shanghai, are taken as examples to illustrate the method and to generate the regional building energy use database. The results show that: a) building physical feature (geometric form, functional type) have a significant impact on energy consumption, and energy consumption is correlated with the economic level of the region; b) Energy use in urban built-up areas has obvious spatial agglomeration characteristics, and the siphon effect is obvious in region with high energy consumption. The contribution of the framework is to provide insights into the feasibility of employing multiple spatial data fusion for the analysis of energy consumption within urban built-up areas. This can be employed to address energy planning concerns and help promote sustainable environmental practices in urban areas worldwide. • This paper attempts to provide a feasible framework for analyzing urban building energy use by utilizing real-time urban semantic perception information and building features. • The proposed framework have comprehensively considered the relationship between geometric features, functional types, location and energy use of buildings. • The proposed methodology can obtain regional energy consumption stocks and produce spatial distribution results, thus improving the interpretability of the data. • The results show that energy use in urban built-up areas has obvious spatial agglomeration characteristics, and the siphoning effect is obvious in regions with high energy consumption. [ABSTRACT FROM AUTHOR]

• The definition of water sustainability is further expanded. • A water sustainability assessment model regarding quantity-quality-benefit is innovatively built. • The impact of coupled coordination relationships between the three subsystems is considered. • Water sustainability is evaluated from the single and three-dimensional perspective simultaneously. • Three-dimensional water sustainability assessment is more objective and scientific. An integrated water sustainability assessment is conducive to realizing the optimal allocation and efficient water utilization, and alleviating the water crisis. Existing research mainly appraises water quantity and water quality as unidimensional or in combination, without considering the water benefit, and few studies have assessed the regional water sustainability based on an integrated evaluation multidimensionally. Therefore, this paper innovatively introduces water benefit to construct a three-dimensional quantity-quality-benefit model (QQBM) to evaluate water sustainability in line with the water footprint (WF) theory and water resources balance sheet (WRBS). The impact of the coupled coordination relationship among water quantity, water quality, and water benefit on the water sustainability evaluation is further analyzed by introducing the coupled coordination degree model (CCDM). This paper takes the Yangtze River Economic Belt (YREB) as an example and makes a spatio-temporal analysis of the water sustainability in its 11 provincial capitals during 2010-2021 from a single dimension and a three-dimensional perspective, respectively. The results found that: (1) From a single dimension, the water sustainability in the 11 provincial capitals in the YREB during 2010-2021 is at a medium level, with better water benefit sustainability, moderate water quantity sustainability, and horrendous water quality sustainability. Among them, the water sustainability is the best in Guiyang and Hangzhou, while the worst in Shanghai. (2) From a three-dimensional perspective, the water sustainability in the 11 provincial capitals from 2010 to 2021 is horrific. Among them, the water sustainability is the best in Kunming, Changsha, Nanjing and Shanghai, while the worst in Wuhan and Hefei. (3) The degree of coupling coordination between water quantity, water quality and water benefit significantly influence the water sustainability in the 11 provincial capitals of the YREB. The three-dimensional assessment model QQBM constructed in this study is more comprehensive and objective than the single perspective assessment. The findings in this paper can help other regions to conduct similar water sustainability assessments and inform policy recommendations. [ABSTRACT FROM AUTHOR]

• This paper studies a vehicle deployment and dispatch problem. • A two-stage model is proposed to consider the uncertainties. • A variable neighborhood search method is designed to solve the model. • Managerial implications are derived on the basis of sensitivity analyses. To manage traffic emergencies, cities require multiple types of traffic rescue vehicles, which need to be dispatched from various rescue stations dispersed throughout the city. A reasonable way of deploying the rescue vehicles must be determined given that the times and locations at which the traffic emergencies occur are uncertain. In this paper, we propose a two-stage stochastic programming approach to deploying multiple types of emergency vehicles in response to traffic accidents in the context of uncertainty. The first stage of the proposed model concerns decisions on the quantities of the different types of vehicles to be stocked at each rescue station. In the second stage, when the locations and accident rescue demands are realized in each scenario, the decision-making involves dispatch of the emergency vehicles to the traffic accidents. To solve the proposed model, we suggest a variable neighborhood search method. Using the road network of Jiading District, Shanghai, as an example, we perform numerical experiments to investigate the efficiency of the proposed method and the model validity. Some managerial implications are also outlined in the sensitivity analysis. [ABSTRACT FROM AUTHOR]

An anomalous trajectory detection method based on ship trajectory clustering and prediction is proposed. The method consists of two modules, namely, trajectory clustering based on improved DBSCAN and Trajectory prediction by ProbSparse Attention-based Transformer. we propose the concept of ship behavior similarity for the first time in this paper, by decomposing the velocity according to the ship's heading to get 'velocity coordinates' to replace latitude and longitude coordinates, on the basis of which the ship behavior trajectories are clustered and the core trajectories are extracted. By comparing the behavioral similarity between the predicted trajectory and the core trajectory with the preset threshold, it is judged whether the abnormal trajectory or the ship has abnormal operation. AF-DP is used in this method for compression of trajectory data, and Fast-DTW is used to calculate the behavioral similarity between trajectories. Notably, this is the first application of ProbSparse Attention-based Transformer in the maritime domain. The proposed method is applicable to inland river traffic near Wusongkou, Shanghai. The final experimental results show that the method we proposed can effectively identify the abnormal behaviors in the trajectory, and can provide technical support for the analysis of ship track data and the risk management of maritime transport in this region. • In this paper, we reduce the algorithmic complexity of Transformer using ProbSparse Attention. • A new trajectory representation is proposed for the detection of anomalous trajectories. • Ship behavioral trajectories were clustered using improved DBSCAN. [ABSTRACT FROM AUTHOR]

In the context of prominent energy crisis, photovoltaic power (PV) generation has received increasing attention, then accurate PV generation forecasting is crucial for ensuring the smooth operation of power stations. However, existing research is insufficient in comprehensively analyzing the impact of PV generation volatility. To fill the gaps and enhance the prediction accuracy, this paper proposes a new hybrid forecasting method. We first introduce the Locally Weighted Scatterplot Smoothing (LOWESS) method to process the data and enhance the data stability, and use Pearson correlation coefficient (PCC) and Random Forests (RF) for feature selection to improve the quality of input data. Then we use Attention mechanism and Convolutional Neural Network (CNN) layer to optimize Bi-directional Gate Recurrent Unit (BiGRU) model and form a new hybrid model. Finally, based on the Bagging algorithm, we use ensemble learning to further optimize the hybrid BiGRU model to enhance the depth and performance. The proposed method is validated through case analysis results from two different locations, Xuhui District in Shanghai, China and the DKASC area in Alice Springs, Australia. The results demonstrate that, compared with other models, the developed method exhibits exceptional prediction performance and effectively enhances the accuracy of PV generation forecasting. Keywords : photovoltaic power generation; Locally Weighted Scatterplot Smoothing; feature selection; ensemble learning; Bi-directional Gate Recurrent Unit. • LOWESS smoothing technology is used to reduce the variability of PV generation data. • Pearson correlation coefficient and Random Forest are used to for extract feature. • Attention mechanism and CNN layer are used to optimize BiGRU model. • Two BiGRU layers are stacked to improve the depth and prediction performance. • Ensemble learning is introduced to further optimize the hybrid BiGRU model. [ABSTRACT FROM AUTHOR]

Previous experimental tests on clays have confirmed the non-coincidence of principal strain increments with principal stress axes even though the stress rate is colinear with the current stress. To simulate the non-coaxial behavior of saturated clay subjected to monotonic proportional or non-proportional loading with constant principal stress rate directions, an anisotropic hypoplastic model is presented in this paper. The model is proposed by incorporating an improved anisotropic asymptotic state boundary surface (ASBS) and a non-coaxial asymptotic strain rate direction into the original explicit-ASBS hypoplastic model. The non-coaxial flow results from a non-coaxial stress rate defined by a Gram-Schmidt orthogonalization process based on a reference stress tensor. The capability of the proposed model is demonstrated by simulating the test data performed in hollow cylindrical apparatus (HCA) on Wenzhou clay and Shanghai clay with different drainage conditions and initial consolidation states. In addition, a series of numerical stress probing tests have been conducted to gain further insights into the properties of the proposed model. [ABSTRACT FROM AUTHOR]

The advancement of low-cost, non-manually labeled big data technologies for fault detection in wind turbines is crucial to guarantee their safe and efficient operation. In this context, Normal Behavior Modelling (NBM) is a prevalent approach. However, existing NBM methods for wind turbine fault detection inadequately utilize complex spatial–temporal correlations within the Supervisory Control and Data Acquisition (SCADA) during the normal behavior prediction stage. To cope with this limitation, this paper propose a hierarchical spatial-temporal autocorrelation graph neural network method for online wind turbine pitch system fault detection. This approach integrates a dynamic graph network with an adaptive structure for spatial correlation learning and a transformer model with autocorrelation attention to identify periodic time-distance correlations. Furthermore, a hierarchical neural network, specifically designed for wind turbine physical structure, enhances local information extraction through seven latent graph neural networks and a probsparse attention mechanism. The proposed method demonstrates significant effectiveness in real-world applications, as evidenced by data from a Shanghai wind farm. [ABSTRACT FROM AUTHOR]

Colour is an important factor in the expression of recognizability and cultural identity of regional cultural and creative design. At present, the colour recognition of regional characteristic and the colour association of regional culture mainly rely on the designer's subjective perception. To obtain the target colour resources with reference for regional cultural and design need, this study proposes a scientific method of colour extraction and strong colour association matching of Shanghai style Chinese paintings by machine learning, and applies the related results to the colour design of cultural and creative products. Firstly, using the SLIC superpixel algorithm and Mean shift algorithm to realize the overall dimensionality reduction of the image features and the colour aggregation gradually, so as to extract the characteristic colours of Shanghai style Chinese paintings; Secondly, we introduce a data mining algorithm (Apriori) to mine out the association rules from multiple characteristics colours and filter out strongly associated colour combinations; Finally, we apply the colour combinations and colour tones to the colour design of the creative products. In order to verify the scientificity of the colour extraction and colour matching method proposed in this paper, we selected another painter's paintings in the same school as the algorithm experimental validation sample, similar results were obtained. In addition, we measured user satisfaction using the degree of awakening to Shanghai style culture and the propensity to make consumer decisions as the evaluation dimensions, which proves that the method of this study is effective. [ABSTRACT FROM AUTHOR]