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A high-precision mechanized seeding can greatly contribute to the vegetable production at present. In this study, a spotting glue-paper tape precision seeder was designed for the small seed vegetables, particularly combining the seed rope and printing seeding. Three components were also divided in the seeder, including the peristaltic pump glue, ratchet spotting glue, and seed metering device. Among them, the glue was a mixture of pregelatinized starch and water. Specifically, the glue volume and viscosity were the main factors affecting the number of adhered seeds. The glue point volume depended mainly on the rotation angle of the peristaltic pump during the movement. A pretest of seed adhesion was carried out to preliminarily determine the mass ratio of pregelatinized starch to water (less than 1:5), representing the glue viscosity. Furthermore, the frequency of pump and dispensing were analyzed to clarify the relationship between the peristaltic pump and ratchet speed, where the number of ratchet teeth was determined to be 4. As such, the matching was realized between the peristaltic pump and ratchet spotting glue. The ratchet profile was also designed, according to the spotting glue motion. A theoretical analysis was made on the movement of seeds in the seed guiding tube. It was found that the aggregation effect of seeds on the paper tape relied on the length and cross-sectional angle of the seed guiding tube, as well as the rotation speed of the socket wheel. The seed guiding tube was then optimized for the optimal structural parameters. A Box_Behnken test was also carried out, where the length and cross-sectional angle of the seed guiding tube, while the rotation speed of the socket wheel was taken as the test factors, whereas, the percentage of seeds in the effective area on the paper tape was taken as the test index. The results showed that the percentage of seeds in the effective area on the paper tape was 57.23%, when the length of the seed guiding tube was 56 mm, the section angle was 35°, and the rotation speed of the seed metering wheel was 30 r/min. An adhesion test was also performed on the Shanghai Qing 605 seeds with a diameter of 1.5-2.0 mm. The test factors were then selected as the roller angle of the peristaltic pump and the mass ratio of pregelatinized starch to water. An optimal combination of parameters was achieved, including the size of the glue point, and the mass ratio of pregelatinized starch to water. Once the roller rotation angle was 10° and the mass ratio of pre-gelatinized starch to water was 1:6, the single seed rate of glue point adhesion to seeds reached 97.4%. The adaptability test was also carried out on the whole machine on the working performance of different varieties of small seed vegetables. It was found that the single seed rates of Shanghai Qing 605 and Siji Chinese cabbage seeds were greater than 95% under the working speed of 0.5-1.5 m/s, whereas, the coefficient of variation of plant spacing was less than 10%, fully meeting the requirements of precision sowing indicators that specified in the standard NY/T1143-2006. Therefore, the single seed rate and the working efficiency of the improved seeder increased by 3.53%, and 50% than before. [ABSTRACT FROM AUTHOR]

This article presents a case study of how the Renminbi won the currency war in Shanghai between 1949 and 1950. This case study supports the proposition of chartalism and MMT that money is a creature of the state, and in two ways deepens our understanding of the role of the state in the sovereign currency system. First, taxation is not the only way to drive money. The Shanghai government also drove money by supplying goods. Second, the outcome of a currency war depends on many historical factors, and the government plays an important role by changing the conventions that shape people's monetary behavior. The Shanghai government adopted anti-inflation policies to transform the conventions of valuing commodities and metallic currencies over paper currencies. [ABSTRACT FROM AUTHOR]

Cultural translation: Horse racing, greyhound racing, and Jai Alai in modern Shanghai: Ning Jennifer Chang , Taipei: Institute of Modern History, Academia Sinica, 2019. Chang focuses on three cases of horse racing, greyhound racing, and jai alai in modern Shanghai society to demonstrate the multi-tiered process of cultural translation. Chang's book expands our knowledge of spectator sports in modern China by focusing on its societal dimension in contrast to the conventional political perspective. [Extracted from the article]

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]

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Compared with financial information, whether corporate social responsibility disclosure has impacts on debt financing cost has obviously become a heated topic in the academic. This paper selects A-share listed companies in Shanghai and Shenzhen stock markets of China from 2013 to 2017 as sample to study the impact of corporate social responsibility disclosure on debt financing cost, including bond financing cost and bank loan cost. In addition, this paper divides the sample into voluntary corporate social responsibility disclosure group and mandatory corporate social responsibility disclosure group and studies whether the effects of voluntary corporate social responsibility disclosure and mandatory corporate social responsibility disclosure on bond financing cost and bank loan cost are different. The empirical results are presented as follows: Firstly, enterprise disclosing high-quality corporate social responsibility report is more conducive to reducing the debt financing cost. Specifically, corporate social responsibility disclosure significantly lowers both the bond financing cost and bank loan cost. Moreover, the reduction impact of corporate social responsibility disclosure on bond financing cost is greater than that of bank loan cost. Secondly, enterprises voluntarily disclosing corporate social responsibility reports are more conducive to reducing the debt financing cost than that of enterprises mandatorily disclosing corporate social responsibility reports. Thirdly, non-state-owned enterprises are more conducive to reducing debt financing cost than that of state-owned enterprise. The enterprises with more market competition are more conducive to reducing the debt financing cost than the oligopolistic enterprises. Finally, this paper concludes and gives policy implications. This paper amplifies the literature regarding the economic consequences of corporate social responsibility disclosure and improves the understanding of the impact of corporate social responsibility disclosure on debt financing cost. [ABSTRACT FROM AUTHOR]

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]

China is facing a serious land resource mismatch problem, which will profoundly affect the acceleration of economic growth and technological innovation. Reform of the industrial land allocation system can solve the mismatch of land resources, and that also has an important impact on the promotion of economic and technological development. This paper selects the data of Chinese A-share listed companies in Shanghai and Shenzhen from 2007 to 2020 as the research sample, constructs a double machine learning model, and empirically investigates the impact of a new industrial land use policy on firms' green innovation behavior. The study shows that: (1) the new industrial land use policy significantly promotes firms' substantive and strategic green technological innovation, and the effect on substantive green technological innovation is greater than that on strategic green technological innovation. (2) The enhancement of R&D investment sustainability and the "talent pool" effect are important mechanisms through which the new industrial land use policy influences firms' substantive and strategic green technological innovation. Meanwhile, the new industrial land use policy is conducive to firms' green coinnovation. (3) There is heterogeneity in the effect of the new industrial land use policy, which can significantly promote green technological innovation of firms in the eastern region, while it does not play a significant role in the green innovation behavior of firms in the central and western regions. The above research results enrich the research in the field of industrial land and innovation, help to understand more comprehensively the mechanism of new industrial land affecting firms' green technological innovation, and provide policy insights for strengthening the application of industrial land allocation reform in firms' green innovation. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the impact of digital finance on the breakthrough innovation of enterprises with a sample of A-share listed companies in Shanghai and Shenzhen from 2011 to 2022. It is found that digital finance can promote corporate breakthrough innovation, and presents certain structural heterogeneity characteristics. The mechanism test shows that digital finance has the dual attributes of a financing platform and a social platform, which can promote breakthrough innovation by alleviating corporate financing constraints and expanding corporate social networks. Heterogeneity analysis reveals that the role of digital finance in promoting breakthrough innovation is characterized by regional heterogeneity, with digital finance playing a greater role in promoting breakthrough innovation in provinces with a low level of development of the banking sector, provinces with a high level of development of the capital market sector, and the central region. In addition, the degree of firms' external financing dependence and the degree of product market competition can strengthen the positive effect of digital finance on firms' breakthrough innovation. This paper enriches the related research on the impact of digital finance on enterprise innovation, and provides theoretical basis and policy insights on how digital finance can better assist the innovation-driven development strategy. [ABSTRACT FROM AUTHOR]

Purpose: In this paper, the authors take the central environmental protection inspection (CEPI) as an exogenous shock to study the reaction of the stock market in China. Using the event study method, the authors check how the first round of the first batch of CEPI supervision affects the cumulative abnormal return (CAR) of the listed firms on the Shenzhen or Shanghai stock exchange. This paper aims to discuss the aforementioned objective. Design/methodology/approach: In this paper, the authors take the first round of the first batch of CEPI supervision as a clean exogenous shock to study its effects on the capital market. The authors collect daily trading data from the China stock market and accounting research (CSMAR) database, with the sample containing 1,950 Chinese firms listed on either the Shenzhen or Shanghai stock exchanges. And detailed information on CEPI supervision is obtained from the official website of the Ministry of Ecology and Environment of the People's Republic of China. The event study method is adopted to analyze the reaction of the stock market under CEPI supervision. Specifically, the authors constructed the cumulative abnormal return of each firm around the event day of CEPI. To capture the deterrent effects of CEPI supervision, the authors examine the situation of polluting and non-polluting firms in the supervised provinces, adjacent provinces and provinces that are not supervised or close to the supervised provinces, respectively. Findings: This paper throws light on the following: (1) the polluting firms in the supervised provinces were negatively impacted by CEPI within 20 trading days of the event day, and its effects spread to the polluting firms in the neighboring provinces; (2) CEPI had a favorable impact on the non-polluting businesses in the provinces that are neither supervised nor close to the supervised provinces. The authors contend that it is because the investment is being forced out of the polluting sector and into the non-polluting sector, which is more pronounced in the provinces not directly or indirectly targeted by CEPI; (3) by comparison, the "looking back monitoring of the first round" has had no discernible detrimental impact on the firms' CAR, indicating an important role of psychology anticipation of investors in the stock market performance; (4) although not physically located in the supervised provinces, the downstream enterprises of the polluting firms suffer significantly from CEPI shock; (5) the effectiveness of CEPI supervision in the supervised provinces depends on the level of local environmental regulation and the ownership structure of the company. Private firms in the provinces with stronger environmental regulations suffer more from the CEPI shock; (6) the multivariate analysis shows that while enterprises with high ROE and financial leverage may be at risk of CAR loss, older, larger firms are less likely to experience CEPI shock; (7) the study of persistent effect reveals that the strike of CEPI supervision can last for at least 10 months after the event day and deterrent effect can be spread within the whole polluting industry. Research limitations/implications: In this paper, the authors only concentrate on the market reaction within 20 trading days after the event day. An analysis of long-term effects should be valuable to get a deeper knowledge of the capital market reaction to the CEPI policy. In addition, the paper only focuses on the first round of the first batch of CEPI. Since CEPI has been built as a constant regulation of local environmental performance, further study may need to track both the reaction of listed firms and investment behavior in the capital market. Practical implications: Policy implications of the paper are as follows: First, for the policymakers, it is important to construct a constant environmental regulation system instead of a campaign movement. Second, for investors, as environmental issues are receiving increasing attention from both the government and the public, investment decisions should take into account firms' environmental performance, which can help reduce the risk from environmental regulations. Third, the firms in the polluting industry should take more action to reduce pollutant releases and adopt green technology, which is essential for sustainable development under environmental protection. Originality/value: This paper contributes to the existing literature in the following aspects. First, the authors provide new evidence on the effects of environmental regulations as a shock to the stock market, which has been wildly concentrated in the literature about environmental policies evaluation and capital market reaction. Second, the authors supplement the literature on green finance and sustainability transformation, which has got increasing attention in recent years. Theoretically, by guiding investment and affecting the stock market performance, environmental regulations are considered to be an efficient way to stimulate polluting firms to transform into green development. The results of the paper support this intuition by showing that the CAR of the non-polluting firms in non-supervised provinces in fact benefit from the CEPI supervision. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of Internet infrastructure construction on enterprise transformation and upgrading and the underlying mechanisms using a progressive double difference model based on a quasi-natural experiment of the Chinese government's "broadband China" policy by matching A-share listed companies and city panel data from 2008–2019 in Shanghai and Shenzhen. The conclusions show that the "broadband China" policy can significantly promote the transformation and upgrading of enterprises in pilot cities. However, its effect shows a diminishing marginal contribution, and the policy is more effective for traditional manufacturing industries during the implementation period. Enhancing human capital and reducing internal transaction costs are two important channels for Internet infrastructure construction to help enterprises transform and upgrade. Combined with the life cycle theory, we find that the "broadband China" policy has the most significant impact on changing and upgrading enterprises in the growth and maturity stages, especially those in the manufacturing industry, but not those in the maturity and decline stages of the service industry. Finally, a series of robustness tests using Monte Carlo simulation, entropy balance method, and instrumental variables method, excluding other factors, show that the findings are still robust. [ABSTRACT FROM AUTHOR]

Full-field transmission X-ray microscopy (TXM) in conjunction with X-ray absorption near edge structure (XANES) spectroscopy provides two-dimensional (2D) or three-dimensional (3D) morphological and chemical-specific information within samples at the tens of nanometer scale. This technique has a broad range of applications in materials sciences and battery research. Despite its extensive applicability, 2D XANES imaging is subject to the disadvantage of information overlap when the sample thickness is uneven. 3D XANES imaging combines 3D TXM with XANES to obtain 3D distribution information on chemical states. A 3D XANES imaging method has been established at the Shanghai Synchrotron Radiation Facility (SSRF) and has been used to characterize the structure and chemical state of commercial LiNixCoyMnzO2 (NCM, x + y + z = 1) battery powder materials. The imaging results provide a visual representation of the 3D chemical state information of the particles with depth resolution, allowing for the direct observation of 3D nickel oxidation. This paper will describe in detail the data acquisition, data processing, quantification and visualization analysis of 3D XANES imaging. [ABSTRACT FROM AUTHOR]

The Omicron pandemic broke out in Shanghai in March 2022, and some infected people spread to some cities in the Yangtze River Delta (YRD) region. To achieve the dynamic zero-COVID target as soon as possible, Shanghai and nine cities that were heavily affected by Shanghai implemented the lockdown measures. This paper aims to quantify the impact of the lockdown on air quality and human health. A difference-in-difference (DID) model was first used to measure the impact of the lockdown on air quality in these ten cities. Based on the results of the DID model, we estimated the PM2.5-related health and economic benefits using the concentration–response function and the value of statistical life method. Results showed that the lockdown has reduced the concentrations of PM2.5, PM10, SO2, NO2, and CO by 9.87 μg/m3, 17.31 μg/m3, 0.75 μg/m3, 9.03 μg/m3, and 0.07 mg/m3, respectively. The number of avoided premature deaths due to PM2.5 reduction was estimated to be 35,342. The resulting economic benefits totaled 18.86 billion US dollars. We investigated the reasons for the air quality improvement in these ten cities and found the "3 + 11" policy has had a great impact on air quality. Compared with the first COVID-19 lockdown in early 2020, the effect of the lockdown in 2022 was smaller. These findings demonstrated that reductions in anthropogenic emissions would achieve substantial air quality improvement and health benefits. This paper re-emphasized continuous efforts to improve air quality are essential to protect public health. [ABSTRACT FROM AUTHOR]

Purpose: Innovation is the most important quality of enterprise management. It is an important and controversial issue whether the heterosexual leadership structure of the chairman and chief executive officer (CEO) makes the work "easy" or "very tired" in enterprise innovation. This study investigates the specific impact of the heterosexual leadership structure on enterprise innovation investment, and further explores influence mechanism between them from two perspectives. Specifically, from the perspective of enterprise leaders including the chairman and CEO, this paper analyzes the impact of surname sharing, intergenerational differences and top management team (TMT) external social network between the heterosexual leadership structure and enterprise innovation investment. And from the perspective of enterprise itself, this study explores the impact of ownership and organizational slack between the heterosexual leadership structure and enterprise innovation investment. Design/methodology/approach: By using ordinary least squares regression (OLS), this study mainly takes the unbalanced panel data of A-share listed companies from 2008 to 2019 in Shanghai and Shenzhen as the research sample to empirically analyze the relationship and influence mechanism between the heterosexual leadership structure and enterprise innovation investment. Findings: The results show that the heterosexual leadership structure of the chairman and CEO has a negative impact on enterprise innovation investment. Surname sharing and ownership positively moderate the negative impact of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment. Intergenerational differences and TMT external social network negatively moderate the relationship between the heterosexual leadership structure of the chairman and CEO and enterprise innovation investment. In addition, the moderating effects of intergenerational differences and TMT external social network on the relationship between the heterosexual leadership structure and enterprise innovation investment both depend on organizational slack. When organizational slack is lower and intergenerational differences are higher, the negative impact of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment will be the strongest. And when organizational slack is lower and TMT external social network is higher, the negative impact of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment will be the strongest. Originality/value: By exploring the influence and the boundary mechanism of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment, the "heterosexual difference effect" is verified in this paper, that is, when men and women work together, work is very tired. This not only enriches the existing research of enterprise innovation investment, but also provides practical guidance for effectively improving enterprise innovation investment from a new perspective. In addition, it broadens the moderating mechanism of the impact of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment, which is conducive to reasonable response to improve enterprise innovation investment. [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]

The construction of deep foundation pits in subway stations can affect the settlement of existing buildings adjacent to the pits to varying degrees. In this paper, the Long Short-Term Memory neural network prediction model of building settlement caused by deep foundation pit construction was established using the monitoring data of building settlement around a deep foundation pit project in a metro station in Shanghai, and appropriate hyperparameters including batch size and training set ratio were determined. The accuracy of settlement prediction for single-point and multi-point monitoring of buildings was analyzed. Meanwhile, the effects of construction parameters, engineering geological parameters, and spatial parameters on the accuracy of building settlement prediction were investigated. The results show that the batch size and training set proportion can be taken as 16 and 60%, respectively, when using the Long Short-Term Memory neural network prediction model. The proposed Long Short-Term Memory network model can stably predict the settlement of buildings adjacent to deep foundation pits. The accuracy of settlement prediction at a single point of a building (80%) is lower than the accuracy of coordinated prediction at multiple points (88%). More accurate settlement prediction is achieved with the total reverse construction method. The more detailed the consideration of working conditions, geological parameters, and spatial parameters, the better. The evaluation metrics of the prediction model, RMSE, MAE, and R2, were 0.57 mm, 0.65 mm, and 0.91, respectively. The results of this paper have some practical reference value for analyzing the settlement of buildings caused by foundation pit works. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to identify the medical risk of applying big data technology and to build a medical big data risk (MBDR) control process and manage medical big data risk (MBDR) from a systematic perspective. In this process, we firstly used systematic literature reviews (SLRs) method to systematically search 322 papers in web of science with the topics of "medical risk" and "big data risk" to build a dimensional system of medical big data risk (MBDR) from the theoretical level. Based on a case study of a hospital in Shanghai, we explored the formation mechanism and interaction effect of medical big data risk (MBDR) by using Bayesian belief networks (BBNs) method, and built a systematic risk control process. This paper finally finds that: the dimensional system of medical big data risk (MBDR) includes 24 subdimensions and 5 major categories of dimensions, which helps to explore the medical application of big data technology from a risk perspective. In addition, the medical big data risk (MBDR) control process constructed in this paper includes: risk prediction, reverse reasoning, risk control, and risk prevention in 4 aspects, which is important for hospitals to actually carry out medical big data risk (MBDR) control. [ABSTRACT FROM AUTHOR]

Digital transformation plays a crucial role in improving the quality development of companies in this era of digital economy with ever-changing technologies. This paper empirically investigates the impact of corporate digital transformation on total factor productivity and the mechanism of action, using A-share listed companies in Shanghai and Shenzhen from 2011–2021 as the research sample, and found that the digital transformation of companies significantly improves total factor productivity, with the plausibility of the findings being verified by a series of robustness tests. Based on the heterogeneity study, it is found that such effect is stronger for private companies, non-high-tech companies, and companies with a high degree of industry competition. The mechanism test indicates that digital transformation facilitates total factor productivity through four ways: strengthening company technological innovation, reducing operational costs, increasing resource allocation efficiency, and improving human capital structure. The findings of this paper support a better understanding of the micro effects of digital transformation and provide empirical evidence for policy formulation and adjustment. [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]

To explore the influencing factors of school climate, this paper used TALIS 2018 principal survey data and applied linear regression to examine the influence of three elements on school climate: external school environment and structure, principal personal characteristics, and principal leadership. According to the research targeting 198 principals from Shanghai secondary schools, all three aspects can influence the formation and development of school climate, with each influencing factor acting on different dimensions of school climate. These different paths are the mechanisms that influence the school climate in the education system. In addition, principal leadership plays a more important role than the other aspects in determining school climate. To create a school climate that is better suited to the development of all involved in the school, this paper offers suggestions on how to better select principals and improve their leadership skills. [ABSTRACT FROM AUTHOR]

Purpose: This paper examines firm-level accountability and performance implications under a state-dominated institutional environment, China, for firms engaged in the space economy. Extant studies on the rapidly evolving civil space economy predominantly focus on developed Western economies at national or sector levels, frequently ignoring alternative institutional contexts. Additionally, limited attention has been given to firm-level empirical evidence and analysis, including corporate social responsibility (CSR) practice-R&D quality relationships in the space economy. The paper addresses each of these areas. Design/methodology/approach: This paper utilises multiple regression, propensity score matching and split sampling methods applied to a proprietary dataset of Shanghai and Shenzhen Stock Exchange-listed A-share firms. Results are robust to endogeneity issues, alternative measurement of dependent variables and sampling. Findings: China's space firms demonstrate superior CSR performance to their counterparts in other sectors, supporting CSR's role in maintaining legitimacy. Their CSR practices also positively contribute to firm patent quality. The link is more pronounced among firms facing higher economic policy uncertainty and for state-owned enterprises (SOEs). The latter is due to SOEs' government support, advantages in financing and attracting and retaining a high-quality workforce. Originality/value: This paper adds to discussion on major space power's, by examining China's state-dominated civil space sector. It also addresses a lack of empirical firm-level evidence on space firm behaviour by examining the impact of firm-level CSR practices on R&D quality outcomes, areas in which there is a limited literature. [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]

Enterprise Digital Intelligence Transformation is based on the Digital Conversion of information and process service upgrading, further touching the enterprise's core business, with the goal of building a new business model of Digital Intelligence Transformation at a higher level. Based on dynamic capability theory, this paper conducts an in-depth study on the mechanism of enterprise Digital Intelligence Transformation and firm performance. This paper selects manufacturing companies listed in China's Shanghai and Shenzhen A-shares from 2013 to 2022 as the research sample, and analyzes and tests the sample data using empirical research methods in order to explore the actual impact of Digital Intelligence Transformation on firm performance, including the specific pathways of action and moderating effects. This study helps enterprises to positively face the megatrend of Digital Intelligence Transformation and upgrading and the challenges it brings, and to grasp the new opportunities in the digital era. This study finds that enterprises carry out digital empowerment transformation and development strategies, and implement information Digital Conversion, service upgrading, and Digital Intelligence Transformation to promote firm performance to different degrees. Enterprise innovation resilience has a mechanism effect between information digitalization conversion enterprise performance and process service upgrading enterprise performance. The higher the environmental uncertainty, the greater the positive contribution of information digitalization to firm performance. Digital Conversion is the base and service upgrading is the process. The current sample enterprises have limited years of data collection, and most of them have only carried out the strategic implementation of Digital Conversion or servitization, and have not reached the high-level stage of digital and intellectual transformation. Therefore, it is found that enterprise innovation resilience has not yet shown a significant role mechanism effect between digital–intelligent transformation and enterprise performance at present. And environmental uncertainty has not yet shown a significant moderating effect in the stage of Servitization Upgrading and digital–intelligent transformation. The marginal contributions of this paper are mainly reflected in the following: (1) This study introduces the dynamic capability theory to explore the role of Digital Intelligence Transformation (Digital Conversion + service upgrading) on enterprise performance. (2) This paper investigates the role of Digital Intelligence Transformation in influencing the performance of enterprises from the Digital Conversion and service upgrading phases, and enriches the relevant role and regulatory mechanisms. (3) This study provides new ideas and strategic suggestions on Digital Intelligence Transformation for enterprises with different factor intensities, at different stages of development, and in different regions. [ABSTRACT FROM AUTHOR]

China, the world's largest developing country, faces a severe water shortage. As the government has set a goal of limiting water use to 7000 × 108 m3 by 2035, how to control the increase in water use will be a thorny issue for China. Unbalanced and uncoordinated regional socio-economic development is an important feature of China. Research on the interaction between provincial water use will help to optimize the rational allocation of water resources and control of water use. In this paper, SNA (social network analysis) method is first used to explore the characteristics of social network relationship between inter-provincial water use, construct a two-stage model of SNA–LMDI, and decompose the driving factors of inter-provincial water use evolution. We found the following points. (1) From 2000 to 2018, the spatial correlation network structure of water use is tending to be stable, and the stability and risk resistance of the whole network are enhanced. (2) From different angles to quantify the centricity analysis, can be found that eastern provinces located right in the heart of water network, obviously larger impact on water resources utilization in other provinces, Shanghai and Beijing is located in the former two, and central and western provinces in the edge position. (3) The national water use spatial correlation network can be divided into four blocks, net beneficial block, bidirectional spillover block, brokers block, and net spillover block. (4) Technological progress and industrial structure adjustment were the primary and secondary factors inhibiting the increase of total water use, while income increase was the main factor promoting the increase of total water use, population scale expansion had a weak role in promoting the increase of total water use. Some policy implications are put forward related to our research conclusions. [ABSTRACT FROM AUTHOR]

In response to the intensification of urbanization, characterized by increasingly dense land use, the proliferation of high-rise residences has emerged as a predominant housing solution, particularly evident in developed cities like those in China. With a primary aim of enhancing the residential living environment within high-rise structures, this study advocates for a comprehensive whole life cycle perspective. By employing digital technology and conducting experiments centered on a representative case study, this paper focuses on optimizing the functional layout of public activity spaces within high-rise residential projects. Specifically, this article aims to address challenges such as the inadequate configuration and articulation of various public spaces, along with the underutilization of peripheral activity areas. Central to the optimization efforts is the utilization of the Kruskal algorithm, which enables the analysis of flow lines and functions, ultimately leading to the derivation of optimal solutions. Through a detailed analysis of our case study, this paper provides actionable insights into enhancing the feasibility and effectiveness of public spaces within high-rise residential projects. Recognizing the pivotal role of public space layout in shaping residents' living experiences, the importance of addressing this issue early in the design phase was emphasized. By integrating scientifically driven digital technology solutions, smart, inclusive, and convenient communities that cater to the diverse needs of their inhabitants are aspired to be created. [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 importance and urgency of domestic solid waste (DSW) source segregation in universities is self-evident. Although many universities have carried out waste management, however, a comprehensive summary for successful implementation work of DSW segregation is lacking. This study summarizes the mechanism of DSW segregation in Chinese university based on questionnaire survey, on-site inquiry and sampling analysis in a comprehensive university in Shanghai. Questionnaire survey show that it is critical for encouraging students to participate in waste segregation to build convenient segregation facilities and humanized segregation reward and punishment method. The strengthened publicity and education due to the advantages in environmental discipline, easy-operating waste dumping site/facility as well as personalized solutions for different functional areas (teaching building) were considerably important strategies for implementing efficient waste segregation. The recyclables that were collected by intelligent recycling device and mobile recycling enterprise were dominated by paper, and the amounts increased dramatically during the graduation season. Therefore, the university correspondingly increased the collection frequencies of waste and the number of segregation guiders in the period to decrease the potential risk of fire safety. The study could provide a valuable reference for efficient implementation of waste segregation on university/college in China. [ABSTRACT FROM AUTHOR]

Smart city construction is crucial for regional economic development, and the micro-level impact of such construction on business operations cannot be ignored. Based on the panel data of Shanghai and Shenzhen A-share listed companies from 2008 to 2020, this paper investigates the relationship between smart city construction and firm performance and its mechanism of action. The study findings show that (1) smart city construction significantly improves enterprise performance; (2) the improvements are significant across all industries and regions; and (3) the impact of smart city construction on small and medium-sized enterprises (SMEs) and nonstate enterprises is more significant than that on large enterprises and state-owned enterprises. These findings provide a theoretical framework and fresh perspectives for encouraging coordinated regional development and new urbanization construction. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak and the implementation of peak and carbon neutral policies have severely impacted oil price volatility and the industrial sector. Exploring the impact mechanisms between oil prices and industries is particularly important for accurate forecasting of crude oil prices. As one of the world's largest commodity consumers, China's crude oil market is more representative and susceptible to external factors than that of developed countries. In this paper, we propose an analytical forecasting framework based on the causal effects between Shanghai crude oil prices and various industries in China to improve the forecasting accuracy of crude oil prices. Information geometric causal inference (IGCI) is applied to detect causal relationships between 31 different industries in China and Shanghai crude oil prices in the three time periods before, during and after COVID-19, and industries with strong causal information effects on crude oil prices in the long run are screened out as additional features. An oil price forecasting model based on Gray Wolf Optimization and Extreme Learning Machine (GWO-ELM) is proposed. Considering the small amount of data for Shanghai crude oil, this paper proposes a cross-learning data approach to solve the problem. Experimental results show that the GWO-ELM model outperforms RF, LSTM, GRU, and migration learning-based Tr-LSTM and Tr-Adaboost models in the task of Shanghai crude oil futures price prediction, and find that industry characteristics with long-term causal effects on oil prices can improve the model prediction accuracy. Our proposed analytical prediction can capture the oil price trend more accurately through the information of the industry and solve the problem of insufficient training data for the model. The application of this framework is expected to provide new methods and ideas for data mining of crude oil and other futures prices. [ABSTRACT FROM AUTHOR]

With the development of the digital city, data and data analysis have become more and more important. The database is the foundation of data analysis. In this paper, the software system of the urban land planning database of Shanghai in China is developed based on MySQL. The conceptual model of the urban land planning database is proposed, and the entities, attributes and connections of this model are discussed. Then the E-R conceptual model is transformed into a logical structure, which is supported by the relational database management system (DBMS). Based on the conceptual and logical structures, by using SpringBoot as the back-end framework and using MySQL and Java API as the development tools, a platform with data management, information sharing, map assistance and other functions is established. The functional modules in this platform are designed. The results of JMeter test show that the DBMS can add, store and retrieve information data stably, and it has the advantages of fast response and low error rate. The software system of the urban land planning database developed in this paper can improve the efficiency of storing and managing land data, eliminating redundant data and sharing data. [ABSTRACT FROM AUTHOR]

Introduction: The purpose of this paper is to empirically test the impact of CEO's financial background on industrial AI transformation of manufacturing enterprises based on upper echelons theory and imprinting theory. Methods: The paper preliminarily takes listed manufacturing companies in Shanghai and Shenzhen stock markets that are affiliated to enterprise groups from 2014 to 2020 as samples, and manually collects and collates datas of CEO's financial background and industrial AI transformation. The research hypotheses are tested by stata 15.0 software*. Results: It is found that CEO's financial background significantly inhibits the industrial AI transformation of manufacturing enterprises, and when the CEO works part-time in the parent company, it will strengthen the negative impact of CEO's financial background on industrial AI transformation. Further research shows that enterprise financialization plays a partial intermediary role between CEO's financial background and industrial AI transformation; Compared with private enterprise groups, the inhibiting effect of CEO financial background on industrial AI transformation is stronger in state-owned enterprise groups; CEOs with non-banking financial background have a stronger inhibitory effect on industrial AI transformation. Discussion: Firstly, based on the process of making business decisions, it verifies and clarifies the action mechanism of CEO's financial background on industrial AI transformation through internal driving mechanism, which expands the research horizon of industrial AI transformation, and further applies the Imprinting Theory in biology to the research of business decision-making, which forms a beneficial complement to the relevant research on economic consequences of CEO's financial background. Secondly, different from the research of single independent company, this paper focuses on the special situation of parent-subsidiary corporate governance, and explores the mechanism of action, deepening the research on the synergy of enterprise groups. Finally, this paper further explores the influence of CEO's financial background on industrial AI transformation, which is conducive to a deeper understanding of the heterogeneity of managers except manpower and capital factors in the industrial AI transformation practice of manufacturing enterprises, and provides a new idea and a more comprehensive analysis perspective for industrial AI transformation. [ABSTRACT FROM AUTHOR]

For large-scale 3D building reconstruction, there have been several approaches to utilizing multi-view satellite imagery to produce a digital surface model (DSM) for height information and extracting building footprints for contour information. However, limited by satellite resolutions and viewing angles, the corresponding DSM and building footprints are sometimes of a low accuracy, thus generating low-accuracy building models. Though some recent studies have added GIS data to refine the contour of the building footprints, the registration errors between the GIS data and satellite images are not considered. Since OpenStreetMap (OSM) provides a high level of precision and complete building polygons in most cities worldwide, this paper proposes an automatic single building reconstruction method that utilizes a DSM from high-resolution satellite stereos, as well as building footprints from OSM. The core algorithm accurately registers the building polygons from OSM with the rasterized height information from the DSM. To achieve this goal, this paper proposes a two-step "coarse-to-fine registration" algorithm, with both steps being formulated into the optimization of energy functions. The coarse registration is optimized by separately moving the OSM polygons at fixed steps with the constraints of a boundary gradient, an interior elevation mean, and variance. Given the initial solution of the coarse registration, the fine registration is optimized by a genetic algorithm to compute the accurate translations and rotations between the DSM and OSM. Experiments performed in the Beijing/Shanghai region show that the proposed method can significantly improve the IoU (intersection over union) of the registration results by 69.8%/26.2%, the precision by 41.0%/15.5%, the recall by 41.0%/16.0%, and the F1-score by 42.7%/15.8%. For the registration, the method can reduce the translation errors by 4.656 m/2.815 m, as well as the rotation errors by 0.538°/0.228°, which indicates its great potential in smart 3D applications. [ABSTRACT FROM AUTHOR]

Based on the sample of major asset restructuring transactions of Shanghai and Shenzhen A-share listed companies from 2009 to 2018, this paper uses Logit model to examine the impact of auditors ' cooperation experience with independent financial advisors on the reliability of performance commitments, and to examine the moderating effect of management overconfidence on the relationship between the two. The results show that the cooperation experience between auditors and independent financial advisors is significantly positively correlated with the reliability of performance commitment, and the closer the cooperation experience is, the easier the performance commitment will be realized, this has played a financial intermediary team effect. Further analysis shows that in the context of management overconfidence, the positive relationship between financial intermediaries ' cooperation experience and the reliability of performance commitment is stronger. The research results enrich the research on the influencing factors of M & A performance commitment and the economic consequences of financial intermediaries ' cooperation, and help the transaction subjects to rationally view performance commitment and regulators to improve policies and regulations. [ABSTRACT FROM AUTHOR]

Corporate social responsibility (hereinafter referred to as "CSR") sometimes does not directly affect enterprise performance but through some mediator variable. Corporate reputation and brand value have chain-mediating effects in the influence mechanism of CSR on enterprise performance. Theoretically, this paper broadens the scope of study on CSR and enterprise performance, deeply explores the internal mechanism between them, and opens the "black box" in the process of transforming CSR into enterprise performance. Practically, it can encourage Chinese enterprises to actively undertake CSR, strengthen reputation management, enhance brand value, and finally promote the sustainable development of enterprises. A-share listed companies (listed companies in the Chinese A stock market) in Shanghai and Shenzhen stock exchanges from 2008 to 2020 in "China's 500 Most Valuable Brands List" by World Brand Lab are studied in this paper. The results of the empirical study based on relevant data show a significant positive relationship between CSR and enterprise performance. It investigates the mediating chain effects of corporate reputation and brand value in the influence of CSR on enterprise performance. Listed companies must disclose the annual CSR report. CSR reports as an effective supplement to corporate financial information, which provides an important communication channel for the enterprise and stakeholders. Stakeholders can timely understand their rights and interests through the CSR information and have a more comprehensive and deeper understanding of enterprises. In turn, the enterprise can also win a good reputation, establish a good brand image, and get sustainable development. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to empirically analyze the impact of chief executive officer (CEO) turnover on strategic change and explore the mediating role of organizational slack between them, as well as the moderating role and joint moderating role of top management team (TMT) external social network, ownership nature and industry type. Design/methodology/approach: Based on the upper echelons theory, resource allocation theory and structuration theory, this paper takes the unbalanced panel data of A-share listed companies in Shanghai and Shenzhen Stock Exchanges of China from 2001 to 2018 as the research sample, uses ordinary least squares (OLS) regression method and fixed effect model to study the relationship between CEO turnover and strategic change, and focuses on the mediating mechanism and moderating mechanism between them. Findings: The authors find that CEO turnover is positively related to strategic change. When a CEO turns over, a new CEO will initiate strategic change. Precipitation organizational slack plays a mediating role between CEO turnover and strategic change. Non-precipitation organizational slack has no mediating effect between CEO turnover and strategic change, which is embodied as "suppressing effects." When the non-precipitation organizational slack variable is controlled, the impact of CEO turnover on strategic change will be enhanced. TMT external social network, ownership nature and industry type all negatively moderate the relationship between CEO turnover and strategic change. TMT external social network and ownership nature have a joint moderating effect between CEO turnover and strategic change. When TMT external social network is small, CEO turnover has a positive effect on strategic change in both state-owned enterprises and non-state-owned enterprises, but the promotion effect is stronger in non-state-owned enterprises. When TMT external social network is large, the positive effect of CEO turnover on strategic change in state-owned enterprises is from strong to weak, but in the non-state-owned enterprises is from weak to strong. TMT external social network and industry type have a joint moderating effect between CEO turnover and strategic change. When TMT external social network is small, CEO turnover has a positive impact on strategic change in high-tech enterprises and non-high-tech enterprises, but the promotion effect is stronger in non-high-tech enterprises. When TMT external social network is large, the positive impact of CEO turnover on strategic change in high-tech enterprises is from strong to weak, but in the non-high-tech enterprises is from weak to strong. Originality/value: On the basis of previous studies, this paper further expands the research scope of the mechanism of CEO turnover on strategic change, echoing the research arguments of relevant scholars. At the same time, the research results reveal the mechanism of organizational slack, TMT external social network, ownership nature and industry type in the relationship between CEO turnover and strategic change, and further deepen the application of upper echelons theory, resources allocation theory and structuration theory in China. In addition, the research conclusions of this paper also provide reference value for Chinese enterprises in carrying out strategic change, promoting enterprise transformation and improving the level of corporate governance, and help to enhance the understanding and attention of Chinese enterprises to CEO turnover, organizational slack, TMT external social network, strategic change and corporate governance under the background of high-quality economic development. [ABSTRACT FROM AUTHOR]

The city development is closely related to the performance of the transportation network system. Bridges and roads are important parts of the transportation system, and are also inseparable components of the transportation network. However, the effect of the correlation between bridges and roads on the network system has not been studies thoroughly in the literature. Therefore, it is necessary to analyse the vulnerability of the road network when both bridges and roads are involved. In this paper, the urban road network is modeled into the form of network connection and node, based on the analysis of the related research results of road network vulnerability in the literature. Taking the urban roads at all levels as the connection and the transportation hubs (including bridges) as the nodes, the paper puts forward the corresponding measurement indexes and calculation methods, and establishes the importance and correlation analysis model of roads and bridges in the urban road network. At last, the model is applied to the road network which is 5 × 3 km2 besides Yangpu Bridge of Shanghai for verification, the importance and correlation of specific roads and bridges in the analyzed urban road network are calculated, which provides a certain basis for dealing with various emergencies leading to the decline of urban road network vulnerability. In this paper, the importance analysis of urban road network is extended to the bridge correlation analysis, so that the proposed model of the vulnerability assessment of the urban road network system is more suitable for the increasingly demand of road and bridge construction in China, and provides a certain basis for dealing with the decline of road network vulnerability caused by various emergencies. [ABSTRACT FROM AUTHOR]

While development zones are the main locations of the urban industrial economy and sources of energy consumption, studies on the interactive relationship between mixed land use and CO2 emissions in these zones have not attracted much attention. In this paper, the development zone is selected as the research object, and a honeycomb grid with a side length of 50 meters is used as the unit to measure multiple dimensions of mixed land use. The efficiency and intensity of CO2 emissions are estimated for these units, and the coupling model is used to analyse the interactive relationship between these two factors. The results show that (1) the mixed land use degree of different types of development zones differs; the bonded zone has the highest degree, while the economic and technological development zone and the high-tech development zone have higher degrees than the industrial development zones. (2) The CO2 emissions capacities of economic and technological development zones and high-tech development zones are better than those of industrial development zones and bonded areas. (3) There is a strong interaction between the mixing degree of land use and the intensity of CO2 emissions; the relationship between the two may be diverse and complex in different development zones. (4) The coordinated development level between mixed land use and CO2 emissions in economic and technological development zones and bonded areas is better than that in high-tech development zones, which in turn is better than that in industrial development zones. Based on existing measurements of mixed land use, the index of land use intensity is introduced in this paper and the land use classification in development zones is refined to supplement the land use compatibility matrix. The results of this study have implications for the development zone to enhance mixed land use and low-carbon development. [ABSTRACT FROM AUTHOR]

The common production functions include the Leontief production function, the Cobb-Douglas (C-D) production function, the constant elasticity of substitution (CES) production function, the variable elasticity of substitution (VES) production function and so on. With different elasticity of substitution of factor, the production functions have different ranges of applications. In the production functions, the C-D production function is used the most widely because of its simple form, while the CES production function and the VES production function have limitations in applications due to their complicated forms. However, the C-D production function has the elasticity of substitution of factors of 1, and the CES production function has the elasticity of substitution of factors which is not 1 but a constant, so the two production functions both have limitations in applications. The VES production function with the variable elasticity of substitution is more practical in some application cases. This paper studies the applications of the VES production function model and gives a method of calculating the contribution rates of economic growth factors scientifically. As for the parameter estimation of the model, this paper gives an improved Sine Cosine Algorithm (SCA) to enhance the convergence rate and precision. Finally, the paper makes an empirical analysis on the contribution rates of economic growth factors of Shanghai City, China, using the method proposed. [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]

While the benefits of land-use mix have been widely analyzed with regard to transportation, public health, and economic development, relatively little attention has been paid to empirically investigating the impact of land-use mix on technological innovation at the intra-urban level. Drawing upon a database of geo-coded patents that are used to reflect the capacity of technological innovation, this paper takes Shanghai as a case study and analyzes how the intra-urban distribution of technological innovation has been associated with land-use mix at the 1 km × 1 km grid cell level. Empirical results, which are robust when the grids are divided at the 2 km × 2 km level, show that the degree of land-use mix is positively associated with the number of patents for a given grid, suggesting that grids with a higher level of land-use mix are likely to have more patents, ceteris paribus. Moreover, the results demonstrate an inverted U-curve relationship between land-use mix and technological innovation, indicating that a too much higher level of land-use mix could lead to a smaller number of patents for a certain grid. In addition, the empirical results suggest the existence of spatial dependence in the effect of land-use mix on technological innovation. [ABSTRACT FROM AUTHOR]

In recent years, the rapid growth of vehicles has imposed a significant burden on urban road resources. To alleviate urban traffic congestion in intelligent transportation systems (ITS), real-time and accurate traffic flow prediction has emerged as an effective approach. However, selecting relevant parameters from traffic flow information and adjusting hyperparameters in intelligent algorithms to achieve high prediction accuracy is a time-consuming process, posing practical challenges in dynamically changing traffic conditions. To address these challenges, this paper introduces a novel prediction architecture called Multiple Variables Heuristic Selection Long Short-Term Memory (MVHS-LSTM). The key innovation lies in its ability to select informative parameters, eliminating unnecessary factors to reduce computational costs while achieving a balance between prediction performance and computing efficiency. The MVHS-LSTM model employs the Ordinary Least Squares (OLS) method to intelligently reduce factors and optimize cost efficiency. Additionally, it dynamically selects hyperparameters through a heuristic iteration process involving epoch, learning rate, and window length, ensuring adaptability and improved accuracy. Extensive simulations were conducted using real traffic flow data from Shanghai to evaluate the enhanced performance of MVHS-LSTM. The prediction results were compared with those of the ARIMA, SVM, and PSO-LSTM models, demonstrating the innovative capabilities and advantages of the proposed model. [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]

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]

This paper aims to solve the decision-making problem of value chain reconstruction of Chinese port enterprises under the background of the Free Trade Zone policy. Based on value chain theory and system dynamics method, this paper constructs a simulation model that can simulate the value-added change process of port enterprises under different combination input conditions. Furthermore, it conducts simulation case studies. The research indicates that the Free Trade Zone policy has a significant promoting effect on the restructuring of port enterprise value chains and the transformation and upgrading of enterprises. Moreover, considering the impact of the Free Trade Zone policy and limited resources, the overall benefits to port enterprises from combined investments are superior to those from single-factor investments. According to the value chain theory, the business segments of a port are decomposed into ancillary value activities, basic value activities, and external value activities. The investments in these three types of value activities play roles, respectively, in enhancing the operational efficiency of port enterprises, expanding the business scope of port enterprises, and strengthening the core competitiveness of port enterprises. From the overall perspective of the system, Shanghai Port can obtain the maximum operating profit when the endogenous factor input rate is 13%, the basic factor input rate is 4%, and the exogenous factor input rate is 13%. The findings of this research provide a decision-making reference for Chinese port enterprises to realize value reconstruction, transformation, and upgrading in the context of the Free Trade Zone policy. [ABSTRACT FROM AUTHOR]

Water resources are a fundamental natural and strategic economic resource and are closely related to high-quality economic and societal development. This paper uses the pilot implementation of the water resource tax reform to explore the impact of that reform on the green innovation and total factor productivity of enterprises. The study sample includes data for high water-consuming A-share listed enterprises in Shenzhen and Shanghai, China, from 2007 to 2021; the double-difference method was used for the analysis. Study findings indicate that replacing water resource fees with taxes significantly improves the green innovation level and total factor productivity of enterprises. Green innovation has a significant partial mediating effect between the water resource tax reform and total factor productivity. The water resource tax reform promotes green innovation in enterprises, enhancing total factor productivity. When considering different types of enterprise property rights, the economic effect of the water resource tax reform is more pronounced in non-state-owned enterprises, compared to state-owned enterprises. This paper provides empirical evidence for expanding the pilot scope of the water resource tax reform. [ABSTRACT FROM AUTHOR]

With a large number of new energy vehicles being put into use, it is the general trend for traditional fuel vehicles to withdraw from the market in an orderly manner. Determining the optimal ratio between them in this process is of great significance to the low-carbon sustainable development of cities. Therefore, considering the constraints of urban automobile development planning and air pollution prevention and control policies, a multi-objective model to minimize pollutants and costs is constructed in this paper. Through model calculation and sensitivity analysis of dynamic impact relationship of different types of vehicles, it is determined that when new energy vehicles account for around 36% in Beijing, 57% in Shanghai and 46% in Guangzhou, the pollutant emissions can be minimized without causing a significant increase in social costs. Additionally, compared with 2030, Beijing, Shanghai and Guangzhou can achieve emission reductions of 320,000 tons, 200,000 tons and 250,000 tons, respectively, in 2050 if they implement the policy of banning the sale and delisting of fuel vehicles, which could provide suggestions for the guidance of the low-carbon development plan of the automobile industry. [ABSTRACT FROM AUTHOR]

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Green technological innovation is crucial for the manufacturing industry's green transformation and sustainable development. This study examines the impact of executive overconfidence on corporate green innovation, focusing on the internal drivers of corporate innovation and using a sample of Shanghai and Shenzhen A-share listed manufacturing companies from 2013 to 2020. We further examine the mediating role of digital transformation and the moderating role of external attention. The findings indicate that executive overconfidence promotes corporate green technological innovation. Overconfident executives enhance green innovation by accelerating digital transformation. Moreover, external attention from analysts and media positively moderates the relationship between executive overconfidence and corporate green innovation. Heterogeneity analysis reveals that the positive impact of executive overconfidence on green innovation is more significant in non-state-owned enterprises, high-tech firms, and enterprises with lower pollution levels. [ABSTRACT FROM AUTHOR]