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Background: Extensive research has been conducted treating burnout as an independent variable and performance as a dependent variable to proffer possible solutions to burnout and job performance among academics. Despite this, the burnout crises persist and are exacerbated by the ongoing global proliferation of higher education. Acknowledging this, the current study explored whether performance may contribute to the emergence of burnout. Methods: The study's sample population comprised 689 academics from Jiangsu province, China. Key Performance Indicator (KPI) results served to measure performance. Psychological counselling and Burnout were calculated using mental health results garnered from the universities. Data was collected on respondents' demographic characteristics and work situations. The mean scores were 0.517 (SD = 0.5) for gender and 1.586 (SD = 1.103) for age. The relationship among performance, job burnout, and psychological counselling was analysed via a cross-sectional survey deploying grouped regression. Results: Academics' job performance was found to regulate their burnout (β = -0.058, P < 0.01). Higher performance of academics was significantly associated with lower job burnout and psychological counselling. Furthermore, psychological counselling significantly moderated job burnout (β = -0.012, P < 0.05) among academics without regulating their job performance. Conclusion: The paper supplements the discourse on job burnout and academic performance by suggesting a pre-counselling measure as a strategy to address the crises of burnout. The paper argued that the continued competence of employees should prevent burnout in Higher education and ensure better job performance. [ABSTRACT FROM AUTHOR]

This paper focuses on the cardinality constrained mean-variance portfolio optimization, in which only a small number of assets are invested. We first treat the covariance matrix of asset returns as a diagonal matrix with a special matrix processing technique. Using the dual theory, we formulate the lower bound problem of the original problem as a max-min optimization. For the inner minimization problem with the cardinality constraint, we obtain its analytical solution for the portfolio weights. Then, the lower bound problem turns out to be a simple concave optimization with respect to the Lagrangian multipliers. Thus, the interval split method and the supergradient method are developed to solve it. Based on the precise lower bound, the depth-first branch and bound method are designed to find the global optimal investment selection strategy. Compared with other lower bounds and the current popular mixed integer programming solvers, such as CPLEX and SCIP, the numerical experiments show that our method has a high searching efficiency. History: Accepted by Pascal Van Hentenryck, Area Editor for Computational Modeling: Methods & Analysis. Funding: This work was supported by the National Natural Science Foundation of China [Grants 12101317, 12271071, and 11991024], the Natural Science Foundation of Jiangsu Province [Grant BK20200819], the Team Project of Innovation Leading Talent in Chongqing [Grant CQYC20210309536], the Contract System Project of Chongqing Talent Plan [Grant cstc2022ycjh-bgzxm0147], and the Philosophy and Social Science Fund of Education Department of Jiangsu Province [Grant 2020SJA0168]. K.F.C. Yiu is supported in part by the Research Grants Council of Hong Hong [Grant PolyU 15223419], the Hong Kong Polytechnic University [Grants 4-ZZPT and 1-WZ0E], and the Research Centre for Quantitative Finance [Grant 1-CE03]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0344) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2022.0344). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/. [ABSTRACT FROM AUTHOR]

The site investigation is a key part of the design of tunnel construction projects, as it provides accurate geotechnical parameters. A systematic site investigation, which consists of mainly in situ tests and laboratory sample tests, was conducted for the Haimen-Taicang river-crossing tunnel project on Yangtze River. This paper aims to analyze and compare the piezocone penetration testing (CPTU) and dilatometer test (DMT) results of both onshore and under-river subsoils to provide insights into the interpretation of the in-situ tests. The accuracy of well-documented interpretation methods based on CPTU and DMT was discussed. Current empirical correlations between in-situ test results and unit weight, undrained shear strength and constrained modulus of the subsoils were checked, and their site adaptability was discussed in detail. A series of site-specific correlations were derived based on the analysis of the in-situ tests and the comparison between the in situ tests interpretation and the laboratory results. In order to reduce the errors between testing locations caused by soil variability and get the consistent understanding of soil behaviors, CPTU–DMT correlations were reviewed and improved based on local testing results. [ABSTRACT FROM AUTHOR]

This paper presents an optimized preparation process for external ointment using the Definitive Screening Design (DSD) method. The ointment is a Traditional Chinese Medicine (TCM) formula developed by Professor WYH, a renowned TCM practitioner in Jiangsu Province, China, known for its proven clinical efficacy. In this study, a stepwise regression model was employed to analyze the relationship between key process factors (such as mixing speed and time) and rheological parameters. Machine learning techniques, including Monte Carlo simulation, decision tree analysis, and Gaussian process, were used for parameter optimization. Through rigorous experimentation and verification, we have successfully identified the optimal preparation process for WYH ointment. The optimized parameters included drug ratio of 24.5%, mixing time of 8 min, mixing speed of 1175 rpm, petroleum dosage of 79 g, liquid paraffin dosage of 6.7 g. The final ointment formulation was prepared using method B. This research not only contributes to the optimization of the WYH ointment preparation process but also provides valuable insights and practical guidance for designing the preparation processes of other TCM ointments. This advanced DSD method enhances the screening approach for identifying the best preparation process, thereby improving the scientific rigor and quality of TCM ointment preparation processes. [ABSTRACT FROM AUTHOR]

Based on the data of urban residents' consumption in Jiangsu Province, this paper looks for the Statistical Yearbook of Jiangsu Province from Jiangsu Statistics Bureau, collects the required data of residents' consumption structure, and defines the components of residents' consumption structure in Jiangsu Province from eight aspects: clothing, food, housing, transportation and communication, medical care, culture, education, entertainment and other miscellaneous commodities. First, make a systematic theoretical explanation of these eight factors, so as to help us better understand how these eight factors are pieced together into a whole of residents' consumption structure. Then it analyzes the present situation of consumption structure. Secondly, based on the relevant theories of residents' consumption structure, in order to know the changes of the components of residents' consumption structure in Jiangsu Province over the years, this paper analyzes the relevant data of the collected structural factors by using factor analysis and ELES model, based on the data from 2009 to 2018. In the last part, according to the previous analysis results, the characteristics of urban residents' consumption structure in Jiangsu Province are summarized, and some suggestions and opinions are given. Finally, the future consumption structure is predicted according to the historical data, and some suggestions are given. [ABSTRACT FROM AUTHOR]

The growing impact of ecological theories and environmental preservation has resulted in a movement towards people-oriented design approaches for ecological landscape creation. However, certain university campuses continue to suffer hardships due to underutilized terrains and severe damage caused by large-scale earthworks. Given the new waves of campus growth, there is an urgent need to address these difficulties and consider the planning and design of natural biological landscapes on various campuses of Jiangsu province. A more scientific approach to maintaining ecological balance, protecting biodiversity, and increasing landscape variation on campuses may be taken by combining ecological environment conservation with university landscape design. Based on summarizing and analyzing previous research, this paper takes the Nanjing Communications Institute of Technology as a case study and expounds on the research status and significance of university campus landscape design in Jiangsu Province. Firstly, this study elaborates on the background, current status and future challenges of the concept of ecological environment protection, introduces the study objects, indicators and constituent elements of landscape design of the university campus, and conducts the ecological analysis. Secondly, this paper uses regression analysis to investigate the complex interactions between ecological features and the Ecological Balance Index (EBI) in university campus landscape design. Our suggested design reveals links between various design aspects and overall ecological-aesthetic attributes Inspired by the Principle of Landscape Diversity Design. In addition, we quantified landscape diversity and spatial optimization using the Shannon Diversity Index and Space Utilization Efficiency. Third, this research analyzes the space and visual forms of the landscape on the university campus and proposes a landscape design model for it using ecological environment protection. Third, it explores the expression methods of ecological environment protection and conducts the space division and index selection of landscape design. Finally, this paper discusses the landscape design approaches for university campuses to protect the ecological environment. In experimental work, the paper evaluates and compares several landscape design methodologies. Our proposed design exceeded previous approaches in terms of ecological balance (83%), aesthetic appeal (91%), and sustainability (93%). The proposed design is beneficial in protecting the environment and improving the overall quality of university campuses. These findings provide useful insights and references for future study in landscape design for university campuses in Jiangsu Province under the ecological environment preservation paradigm. [ABSTRACT FROM AUTHOR]

Demand-side flexible load resources, such as Electric Vehicles (EVs) and Air Conditioners (ACs), offer significant potential for enhancing flexibility in the power system, thereby promoting the full integration of renewable energy. To this end, this paper proposes an optimal allocation method for demand-side flexible resources to enhance renewable energy consumption. Firstly, the adjustable flexibility of these resources is modeled based on the generalized energy storage model. Secondly, we generate random scenarios for wind, solar, and load, considering variable correlations based on non-parametric probability predictions of random variables combined with Copula function sampling. Next, we establish the optimal allocation model for demand-side flexible resources, considering the simulated operation of these random scenarios. Finally, we optimize the demand-side resource transformation plan year by year based on the growth trend forecast results of renewable energy installed capacity in Jiangsu Province from 2025 to 2031. [ABSTRACT FROM AUTHOR]

Leading with the principle of 'people-oriented urbanization,' the adaptation of rural migrants in urban China has attracted increasing concerns from policy-makers and scholars. Today, China has proceeded to a new stage of urbanization. Many rural migrants prefer moving to cities near their home villages rather than to large cities, reflecting the changes in migration patterns and expectations of rural migrants. Although migrant adaptation has been repeatedly investigated in academia, researchers tend to address the topic in one host setting, while migrant adaptation in diverse urban settings has rarely been compared. This paper seeks to fill this research gap via a survey conducted in two cities with different urban settings in Jiangsu. The rural migrant adaptation experiences in the two cities are systematically compared. Our statistical results show that economic structure and living costs, on the one hand, and local regulations and socio-cultural environments, on the other hand, determine rural migrant adaptation experiences in different urban settings. Despite abundant employment opportunities in more-developed cities, the high living costs, working pressure, and strict institutional schemes significantly hamper rural migrant adaptation. In less-developed cities, limited employment opportunities and conservative socio-cultural environments hinder rural migrants from adapting in host societies. Our findings suggest that the governments of different cities need to tailor strategies to assist rural migrants in adapting in urban communities. [ABSTRACT FROM AUTHOR]

In this paper, the numerical calculation model of salt cavern hydrogen storage was established based on the proposed salt cavern hydrogen storage in a bedded salt mine in Jiangsu Province of China. The effects of the minimum internal pressure, maximum internal pressure, average internal pressure and injection-production rate on the stability and tightness of the storage were explored respectively. The results revealed that: (1) The volume shrinkage rate and the plastic zone distribution of the surrounding rock decreased with the increase of the minimum internal pressure, and increased with the decrease of the maximum internal pressure. (2) When the depth of salt cavern is around 1700 m , its long-term stability cannot meet the requirements according to the traditional standard of 0.3–0.8 times of the vertical stress at the cavern roof. It is therefore suggested that the minimum internal pressure of the storage should be increased to 0.4 times of the vertical stress at the cavern roof. (3) The tightness evaluation indexes, including leak range, pore pressure distribution of hydrogen, and cumulative leakage of hydrogen in surrounding rock, all increased with the increase of average pressure and amplitude of internal pressure. (4) Under the same average internal pressure and injection-production frequency, the greater the injection-production rate (the amplitude of internal pressure), the smaller the cumulative leakage rate is. Therefore, increasing the injection-production rate is beneficial to the storability of the hydrogen storage. • Different internal pressures are set to study the stability and tightness of the salt cavern for hydrogen storage. • Raising the minimum internal pressure can enhance the stability of the salt cavern. • The amplitude of internal pressure is the key factor affecting the tightness of the salt cavern. • The selection of internal pressure for hydrogen storage should take into account the effects of multiple factors. [ABSTRACT FROM AUTHOR]

BACKGROUND: During an outbreak such as COVID-19, hospital staff needs to be in close contact with all types of patients visiting the hospital and the risk of cross-infection is extremely high. Payment and medication pickup is a mandatory part of a patient's hospital visit, with direct contact between healthcare workers and patients, and long waiting times in the hospital area, which can easily lead to the spread of disease infection. OBJECTIVE: This paper designed the prototype of a contactless smart medicine cabinet based on RFID technology and optimized the patient consultation and medication pickup process to address these problems. METHODS: We conducted a 50-day field observation of patients for consultation and medication pickup at the First Hospital in H city, Jiangsu Province, China, and randomly timed 1600 sets of data from Surgery (ophthalmology) and Internal patients, then we designed the prototype of a contactless smart medicine cabinet based on RFID technology, optimized the patient consultation and medication pickup process, comparing the traditional and intelligent models using AnyLogic. RESULTS: The results show that this contactless medicine cabinet was able to reduce the time taken by patients in consultation and medicine pickup by 18.74 minutes, increasing the overall efficiency of the consultation by 32.20%. The simulation revealed that this contactless intelligent medication pickup model was able to reduce the time taken by patients in consultation and medicine pickup, increasing the overall efficiency of the consultation, effectively reducing the frequency of contact between healthcare workers and patients, and reducing the risk of disease infection. CONCLUSION: The proposed technical model provides a new idea to solve the problems of long queues, low efficiency and high risk of infection for patients to consult and get medicine during epidemics. Especially within hospitals it has important theoretical and practical implications for epidemic prevention and control as well as future hospital management. [ABSTRACT FROM AUTHOR]

The one-child policy in China brought about a fast decline in fertility levels and an increasingly skewed sex ratio at birth in China. The deep-seated tradition of son preference has been regarded as the main cause. However, news and recent research have pointed out that having daughters appears more popular among young people in urban areas. The analysis reported in this paper was based on empirical evidence drawn from 47 in-depth interviews. Findings highlighted that regarding the preference of sex at birth, a relatively balanced composition is sought in most cases. Other than the absolute dominance of one son and one daughter together, a preference for having a son remains. Although having two daughters has gained greater popularity among young couples, this turns out to be a compromise to some extent. Daughter preference cannot be regarded as a major trend. In practice, a stronger preference for a certain sex increases the fertility rate as couples attempt to fulfil their preferences, whereas no preference signals the least likelihood to realise fertility intentions. In this sense, the desire to have two children with at least one son may help boost fertility. [ABSTRACT FROM AUTHOR]

In recent years, the convergence of the Internet of Things (IoT) and machine learning technologies has instigated advancements in IoT, and machine learning has revolutionized SMEs, reshaping their role in regional economic growth. These technologies provide SMEs with innovative tools, fostering connectivity within regional ecosystems. This transformation is crucial for China's economic realignment in its 'new normal' phase, with enterprises driving social and economic progress. This study proposed the XGBoost algorithm and IoT data enhance collaboration among SMEs in regional economies, fostering innovation and driving economic development. The role of IoT and machine learning in promoting sustainable regional economic prosperity. Technological innovation is essential for enterprise survival and growth in a competitive landscape. This paper examines the influence of environmental factors and geography on economic development across China's regions. It focuses on SME coupling and coordination, contributing to regional economic progress through performance evaluation. IoT integration provides SMEs with abundant real-time data, enabling deep insights into customer behavior, supply chains, and production. Simultaneously, the XGBoost algorithm efficiently processes and extracts actionable insights from this data. Data from 11 provinces in the Yangtze River economic belt highlights Jiangsu Province's leadership in regional innovation performance for 2015 and 2020. The empirical results, grounded in datasets amalgamating information from these provinces, attest to the potential of this IoT and XGBoost-driven approach. Boasting an impressive accuracy rate of 91.7%, surpassing alternative machine learning techniques like SVM, KNN, DT, RF, and LR, this research underscores the effectiveness of this integrated strategy in optimizing SME operations. Additionally, it computes the coupling coordination degree, innovation environment ranking, mean value, and numerical changes from 2010 to 2020, with an average innovation coupling coordination degree of 0.1624 across 30 Chinese provinces. [ABSTRACT FROM AUTHOR]

Currently, the opportunistic method to estimate rainfall using commercial microwave links (CMLs) has been shown as an efficient way to complement traditional instruments in terms of spatial‐temporal resolution and coverage. In this paper, we collected data from 26 CMLs in Jiangyin City, Jiangsu Province, and conducted experiments on rainfall field reconstruction and nowcasting. First, the raw CML data were processed to invert the path‐averaged rainfall intensity. Second, the algorithms of inverse distance weighting (IDW) and ordinary kriging (OK) interpolation were employed to reconstruct the rainfall field. Then a 10‐min prediction of the rainfall field was achieved using a nowcasting model based on the long short‐term memory neural network and a setup window was introduced to improve the prediction performance of the first few minutes. The reconstruction results show that the average correlation coefficient (ACC) and the average root mean square error (ARMSE) between the IDW‐based results and daily cumulative rainfall from rain gauges (RGs) are 0.89 and 8.69 mm, respectively, while the ACC and ARMSE between the OK‐based results and RG data are 0.89 and 9.13 mm, respectively. The nowcasting results show that the ACC between the prediction results with a 5‐min setup window and the IDW‐retrieved rainfall fields can reach 0.91 at the first minute and gradually decrease to 0.20 within 10 min. Furthermore, the model has better nowcasting performance for stratiform precipitation and mixed precipitation compared to convective precipitation. Plain Language Summary: Accurate and real‐time rainfall monitoring and forecasting are of great significance for disaster prevention and control, agriculture, meteorological research, and related fields. However, traditional rainfall measurement methods are insufficient for meeting the demands of comprehensive precipitation observations because of poor spatial‐temporal resolution and limited coverage. Currently, measuring rainfall using additional microwave attenuation caused by raindrops has been shown as an efficient way to complement traditional instruments. Based on commercial microwave link (CML) rainfall measurement technology, this paper carries out rainfall field reconstruction and nowcasting experiments in Jiangyin City, China. The results show the CML network enables accurate rainfall field reconstruction and nowcasting. Key Points: Based on the commercial microwave link (CML) rainfall monitoring network in Jiangyin, China, accurate rainfall inversion by CMLs is achievedThe two‐dimensional rainfall fields are accurately reconstructed using the inverse distance weighting and ordinary kriging interpolation algorithmsA long short‐term memory‐based rainfall field nowcasting model is proposed to achieve 10‐min continuous predictions of rainfall fields [ABSTRACT FROM AUTHOR]

Industrial wastewater discharge has become the main cause of water pollution in China. However, the spatial interaction mechanism between industrial structure and water pollution is still unclear. Accordingly, we evaluated and analyzed spatiotemporal changes of the agglomeration pattern of pollution-intensive industrial enterprises and the evolution of the water environmental pollution pattern, as well as the correlation between them. The study results show that the polluting industrial enterprises were located mainly along the Yangtze River and Taihu Lake Basin in southern Jiangsu in 2013 and 2018. However, we observed a spatial trend of pollution transfer to northern Jiangsu. The industrial water pollution discharge presents the distribution pattern of facing rivers, seas, lakes and cities. Papermaking and paper products industry are the leading factors of COD and NH 3 –N pollution, with explanatory power of 0.3666 and 0.6201 respectively. The spatial positive coupling effect between the concentration degree of polluting enterprises and the intensity of water environment pollution discharge is 94.95% of the region. The spatial agglomeration of polluting industrial enterprises is an important cause of water environment pollution. They promote and couple each other, proving the existence of "Pollution haven" and "Porter hypothesis". [Display omitted] • The polluting industrial enterprises are located mainly along the Yangtze River and Taihu Lake Basin. • Papermaking and paper products industry are the leading factors of COD and NH 3 –N pollution. • The spatial agglomeration of polluting industrial enterprises is a significant cause of water environment pollution. • This study proves the existence of "Pollution haven" and "Porter hypothesis". • This study fills the gap in the spatial response mechanisms of different industrial structures and pollutants. [ABSTRACT FROM AUTHOR]

Interfacial zones straddling terrestrial and marine realms, colloquially known as mudflats, epitomize a dynamic nexus between these environments and are fundamental to the coastal ecosystem. The investigation of these regions is paramount for facilitating infrastructural developments including ports, wharfs, cross-sea bridges, and the strategic utilization of freshwater resources sequestered from mainland islands amid ongoing economic progress. Terrestrial realms conventionally employ electromagnetic techniques as efficacious modalities to delineate subterranean geological information, encompassing structural details and water-bearing strata. However, the peculiar topographic and geological nuances of mudflat regions pose substantial challenges for the efficacious application of electromagnetic methodologies. The present paper endeavors to address these challenges by suggesting innovative modifications to the existing instrumentation and evolving novel data acquisition techniques specifically tailored for electromagnetic exploration within mudflat environments. This paper delves into the electrical characteristics of water-bearing layers within mudflats, and ascertains details pertaining to the subterranean structure and the spatial distribution of fresh and saline water resources, through the holistic interpretation of a multitude of profiles. [ABSTRACT FROM AUTHOR]

The research explored the temp-spatial evolution characteristics for the spatial mismatch and vulnerability among the tourism-economy-ecosystem along the Yangtze River Economic Belt by using research methods including the spatial mismatch and vulnerability based on the panel data from 2004 to 2018. The results are as follows. (1) The overall mismatch along the Yangtze River Economic Belt presented a polarized development trend within which Shanghai, Jiangsu, and Zhejiang showed a typical positive mismatch and other provinces showed a negative mismatch; the overall spatial mismatch index tended to be more severe, the phenomenon of antagonism occurred more frequent and the situation of mismatch became more critical. (2) The overall vulnerability index along the Yangtze River Economic Belt presented a fluctuating trend and the healthy, risky, and severe development trends coexisted within the development process of each province’s vulnerability index. (3) The nine provinces and two cities could be decided into 3 typical categories of planned development regions by the comprehensive spatial mismatch and vulnerability index: Shanghai, Jiangsu, Zhejiang, and Hubei belonging to developing regions; Hunan, Chongqing, and Sichuan belonging to development and protection regions; Anhui, Jiangxi, Guizhou, and Yunnan belonging to protective regions. In the end, the paper puts forward specific suggestions on how to eliminate the spatial mismatch and vulnerability situation in the Yangtze River Economic Belt from both macro and micro perspectives, so as to provide theoretical reference for the high-quality sustainable development of the Yangtze River Economic Belt and other major river basins. The research explored the temp-spatial evolution characteristics for the spatial mismatch and vulnerability among the tourism-economy-ecosystem along the Yangtze River Economic Belt by using research methods including the spatial mismatch and vulnerability based on the panel data from 2004 to 2018. The results are as follows. (1) The overall mismatch along the Yangtze River Economic Belt presented a polarized development trend within which Shanghai, Jiangsu, and Zhejiang showed a typical positive mismatch and other provinces showed a negative mismatch; the overall spatial mismatch index tended to be more severe, the phenomenon of antagonism occurred more frequent and the situation of mismatch became more critical. (2) The overall vulnerability index along the Yangtze River Economic Belt presented a fluctuating trend and the healthy, risky, and severe development trends coexisted within the development process of each province’s vulnerability index. (3) The nine provinces and two cities could be decided into 3 typical categories of planned development regions by the comprehensive spatial mismatch and vulnerability index: Shanghai, Jiangsu, Zhejiang, and Hubei belonging to developing regions; Hunan, Chongqing, and Sichuan belonging to development and protection regions; Anhui, Jiangxi, Guizhou, and Yunnan belonging to protective regions. In the end, the paper puts forward specific suggestions on how to eliminate the spatial mismatch and vulnerability situation in the Yangtze River Economic Belt from both macro and micro perspectives, so as to provide theoretical reference for the high-quality sustainable development of the Yangtze River Economic Belt and other major river basins. [ABSTRACT FROM AUTHOR]

The issue of regional soil and water loss caused by human activity is particularly severe in coastal regions. Since coastal reclamation areas are a valuable land reserve resource, it is of practical significance to understand the distribution characteristics of rainfall erosion and its impact on soil erosion for the prediction, evaluation, and management of regional soil and water resources. Rainfall erosivity should be updated and estimated from simplified indices. This paper analyzed the observed rainfall data of field runoff plots in Dongtai City, Jiangsu Province, between 2011 and 2017. According to the standard of erosive rainfall in coastal areas, reporting 10.8 mm of rainfall or 7.6 mm·h−1 of I30 (maximum 30 min rainfall intensity), the annual average erosive rainfall frequency in Dongtai City was 37.7 and the annual erosive rainfall was 1082.0 mm on average, which accounted for 51.6% and 90.6% of the total rainfall frequency and the total rainfall, respectively. Moreover, the annual average rainfall erosivity in the region from 2011 to 2017 was 7717.4 MJ·mm·hm−2·h−1. The annual distribution of rainfall erosivity was irregular, with an average monthly erosivity value of 4501.8 MJ·mm·hm−2·h−1. Since the accumulated rainfall erosivity of Dongtai City in the flood season (May to September) accounted for 88.1% of the total rainfall erosivity, it is essential to focus on preventing soil and water loss in the flood season. This paper established a rainfall-based model and a composite model and intensity appropriate for a single event and monthly rainfall erosivity in the region. Both models can be used to calculate the annual rainfall erosivity, but only the composite model based on rainfall amount and intensity is recommended for calculating single and monthly rainfall erosivity levels in Jiangsu coastal areas. The empirical formulas in Jiangsu coastal areas can be updated using more recent rainfall data and assess soil erosion risk accurately. [ABSTRACT FROM AUTHOR]

China has been fully implementing the policy of the cultural and tourism industrial integration since 2018. However, the value-added benefits of this policy are not prominent, and the relationship between industrial integration and the value added to the tourism value chain was seldom addressed by researchers. In the context of China's high-quality development, it is necessary to conduct the impact of the integration of cultural and tourism industries on the value added to tourism value chain. This paper proposed four theoretical hypotheses and the corresponding econometric models based on the panel data from 2013 to 2020 in China's Jiangsu Province. According to empirical results, the integration of cultural and tourism industries is spatially unbalanced, with notable imbalances between the south and the north. This paper identified a new connection between cultural and tourism integration and the tourism value chain. It is found that the integration of cultural and tourism industries can enhance the value added to tourism value chain either directly or indirectly through the information technology, with the direct effect being positively moderated by tourism agglomeration. Moreover, this paper may overturn how people generally think about the integration between cultural and tourism industries. It reveals a single-threshold effect that only when the integration of cultural and tourism industries reached a high level will it exert a positive effect. To be more specific, not all Chinese cities are suitable for implementing cultural and tourism integration, because the integration is likely to be ineffective in regions where the cultural industry is substantially less developed than the tourism industry. [ABSTRACT FROM AUTHOR]

Finding a means to extract water body information efficiently and accurately from high-resolution remote sensing images has been an important research direction in the field of water body extraction in recent years. However, shadows from buildings and other obstacles interfere with the accuracy of water body extraction. To address this problem, this paper proposes a neural network method incorporating an attention mechanism for water body extraction. This paper is based on the U-Net convolutional neural network and adds the squeeze-and-excitation module of SENet, an attention mechanism, to the downsampling process of the U-Net network. The module weights the feature maps so that the network focuses more on the features of the water body information and thus reduces attention to the shadow features from buildings and other features, thus improving the accuracy of image segmentation. The dropout and batch normalization layers are also added to improve the generalization ability and stability of the model. In this paper, a water extraction network SE-CU-Net model is presented to overcome the shadowing effect from buildings and other features. Using GF-2 images of Jiangsu province as the data source, the recognition results of this paper are compared with Dense-Net, Res-Net, Seg-Net, U-net, SVM, and RF. Through the comparison experiments, the model of this paper can not only better overcome the influence of shadows from buildings and other features, but it also has a stronger recognition ability and recognition effect. The average ASCR, Precision, mIoU, OA, F1-Score and kappa coefficients in the three tested areas reached 98.27%, 97.17%, 89.33%, 98.2%, 89.3% and 0.883, respectively, with significantly higher accuracy than the other six classical methods, verifying the effectiveness of the model in overcoming the influence of shadows from buildings and other features in water body extraction research. [ABSTRACT FROM AUTHOR]

Based on the survey data of 936 rural households in Jiangsu Province, China in 2020, this paper empirically tests the influence mechanism of internet use on the rural residents' consumption level by constructing the theoretical analysis framework of "internet use—consumption literacy—rural residents consumption level" and taking consumption literacy as the mediator variable. The results demonstrate that, with other conditions unchanged, internet use has significantly improved the consumption level of rural residents. The mediating effect of the consumption literacy accounts for 15.08% among the entire effect of internet use on the rural residents' consumption level. Therefore, when applying digital information technology to improve the consumption level of rural residents in future, we should not only continue to increase investment in the construction of communication infrastructure in rural areas, but also continuously improve the consumption literacy of rural residents through building a multi-level complementary consumption education system and expanding the ways of consumption education and training. [ABSTRACT FROM AUTHOR]

With the three-dimensional (3D) geological information system development, 3D geological cross-sections (GCs) have become the primary data for geological work and scientific research. Throughout past geological surveys or research works, a lot of two-dimensional (2D) geological cross-section maps have been accumulated, which struggle to meet the scientific research and application needs of 3D visual expression, 3D geological analysis, and many other aspects. Therefore, this paper proposes an automatic generation method for 3D GCs by increasing the dimensions based on a digital elevation model (DEM) and 2D geological cross-section maps. By matching corresponding nodes, generating topographic feature lines, constructing an affine transformation matrix, and inferring the elevation value of each geometric node on the GC, the 3D transformation of the 2D GCs is realized. In this study, fourteen 2D GCs within Nanjing City, Jiangsu Province, are transformed into 3D GCs using the proposed method. The transformed results and quantitative error show that: (1) the proposed method applies to both straight and bent GCs; (2) each transformed GC can fit seamlessly with the ground and maintain minimal geometric deformation, and the geometric shape is consistent with the original GC in non-mountains area. This paper corroborated the proposed method's effectiveness by comparing it with the other two 3D transformation strategies. In addition, the transformed GCs can be subjected to 3D geological modeling and digital Earth presentation, achieving positive effects in both 3D application and representation. [ABSTRACT FROM AUTHOR]

This paper investigates the formation of monastic networks in Tang Dynasty (618–907) China, focusing primarily on the Buddhist traditions of Tiantai, Chan and Vinaya, which have yet to be explored as a series of related regional movements. Central to this effort is a dataset that documents over 2000 interactions between some 700 actors that were extracted from stelae inscriptions, monastic biographical collections, historical accounts, letters, and poems. The network data show two clear patterns in the organization of regional Buddhist communities: (1) individual actors bridged cliques of monastics and officials; (2) both monastics and officials contributed to network activities. To illustrate these two patterns, this paper focuses on the ego-network of Fayun 法雲 (?–766), a prominent Vinaya leader based in Jiangsu region, as an example of the formation and evolution of regional Buddhist communities in southern China. Degree centrality indicates that Fayun was one of the central figures in the southern Buddhist landscape of the early eighth century. By tracing his heterogeneous ties with prominent state officials, local authorities, and monastics affiliated with the Tiantai, Chan, and Vinaya traditions, this study outlines general patterns in the formation and legitimization of regional Buddhist communities in Tang China. All three traditions are revealed as intersecting social formations that were sustained through shared ties with local and nationally prominent bureaucrats. [ABSTRACT FROM AUTHOR]

The development of China's manufacturing industry has received global attention. However, research on the distribution pattern, changes, and driving forces of the manufacturing industry has been limited by the accessibility of data. This study proposes a method for classifying based on natural language processing. A case study was conducted employing this method, hotspot detection and driving force analysis, wherein the driving forces industrial development during the "13th Five-Year plan" period in Jiangsu province were determined. The main conclusions of the empirical case study are as follows. 1) Through the acquisition of Amap's point-of-interest (POI, a special point location that commonly used in modern automotive navigation systems.) data, an industry type classification algorithm based on the natural language processing of POI names is proposed, with Jiangsu Province serving as an example. The empirical test shows that the accuracy was 95%, and the kappa coefficient was 0.872. 2) The seven types of manufacturing industries including the pulp and paper (PP) industry, metallurgical chemical (MC) industry, pharmaceutical manufacturing (PM) industry, machinery and electronics (ME) industry, wood furniture (WF) industry, textile clothing (TC) industry, and agricultural and food product processing (AF) industry are drawn through a 1 km× 1km projection grid. The evolution map of the spatial pattern and the density field hotspots are also drawn. 3) After analyzing the driving forces of the changes in the number of manufacturing industries mentioned above, we found that manufacturing base, distance from town, population, GDP per capita, distance from the railway station were the significant driving factors of changes in the manufacturing industries mentioned above. The results of this research can help guide the development of manufacturing industries, maximize the advantages of regional factors and conditions, and provide insight into how the spatial layout of the manufacturing industry could be optimized. [ABSTRACT FROM AUTHOR]

This study explores the transformation of Buddhist culture in the Jiangnan region (present-day southern Jiangsu and northern Zhejiang), driven by wartime disruptions during the transition from the Yuan Dynasty to the Ming. The Yuan Dynasty witnessed the flourishing of Buddhism, and in Jiangnan, the thriving Zen tradition carried on the legacy of the Southern Song Dynasty. Buddhism found many adherents among the affluent gentry class in Jiangnan, fostering a culture of generous charity that sustained and expanded Buddhism in the region. However, the conflicts toward the end of the Yuan Dynasty inflicted considerable damage on the temples, causing monks to flee. Temples, recognizable landmarks during conflicts, were susceptible to military occupation. Visiting Goryeo monks Muhak Jacho and Naong Hyegeun, and Japanese monks Mumon Gensen and Ginan, were forced to abandon their travels and return to their respective homelands, disrupting the once-thriving Buddhist exchange between Jiangnan and broader East Asia. The chaotic environment also fostered alliances between influential monks and regional powers, providing refuge for monks and an opportunity for both sides to forge beneficial connections. Anti-Yuan factions strategically protected revered monks, leveraging their influence to attract literati and intellectuals, who shared common ethical and spiritual values. This dynamic showcased the mutual benefits derived from such collaboration. Through an exploration of the interplay between politics, social forces, and Buddhism, this paper examines the impact of wartime turmoil on the development of Buddhism in the Jiangnan region. [ABSTRACT FROM AUTHOR]

This cross-sectional study looks into how students' perceived teacher support is linked to achievement emotions in mathematics via academic control and value. The data was gathered from 602 secondary students (13-16-year-olds) in 16 mathematics classrooms from three public schools in Jiangsu province, China. Participants were asked to respond to the paper-pencil questionnaire assessing students' perceived teacher support, cognitive appraisals, and achievement emotions in mathematics. Findings showed that cognitive appraisals played complete mediation roles in teacher support and achievement emotions. Intrinsic value and mathematics self-concept were shown to serve a positive role in teacher support and achievement emotions, whereas extrinsic value was found to play a negative one. Besides, teacher support showed the greatest indirect effect on achievement emotions through mathematics self-concept. Lastly, findings indicated the great relevance of teacher support to students' anger, boredom, enjoyment and relaxation in mathematics classrooms. [ABSTRACT FROM AUTHOR]

A variety of power electronic equipment in AC/DC distribution networks causes oscillations with unknown origin. A self‐sustained low‐frequency oscillation appeared recently in a practical AC/DC distribution network in Tongli, Jiangsu Province, China. In this paper, the accident is introduced, and the oscillation phenomenon has been successfully reproduced by theoretical modelling. Based on the small signal model, the oscillation is well analysed and an additional controller is designed to suppress this low‐frequency oscillation. The reason of the oscillation is related to the power and control parameters of buck converter; the system is critically stable within the linear system stability theory, namely, the leading eigenvalues of the small‐signal system are on the imaginary axis. Meanwhile, a novel inhomogeneity phenomenon for oscillation amplitudes on different voltage‐level DC buses, which are not proportional to their steady‐state voltages, is found. This paper provides a new case study of self‐sustained oscillations coming from a practical AC/DC distribution network and is of great significance for our understanding of oscillations in electric power engineering. [ABSTRACT FROM AUTHOR]

With rural decline becoming a global issue, the implementation of rural revitalization strategy has been turning into general starting points for many countries, especially in contemporary China. In this paper, we proposed a systematic analysis framework and a new evaluation index system for the implementation effectiveness of rural revitalization at the county scale. In addition, empirical research was conducted based on Jiangsu Province. The results indicated that the average value of the comprehensive index of implementation effects of rural revitalization in Jiangsu was 1.8198, and nearly 60% counties in the province were below this average. Also, the obvious disequilibrium and spatial differentiation laws were observed which presenting a stepwise advance from south to north, with the inland superior to the coastal. The five‐dimensional coordination status of rural revitalization in Jiangsu was relatively high, with the majority of counties reached at barely balanced state. A total of 21 counties were identified as problematic regions in Jiangsu through comprehensive overlay analysis. They were mainly located in northern Jiangsu, and could be divided into seven specific types. The proposed evaluation framework and indicator system might make up for the lack of effective reference systems and scientific quantitative indicators in the current county‐scale rural revitalization strategy practices. Moreover, the idea of identifying problem areas and the classification mode of rural revitalization goal levels proposed in this paper are also of great reference for other regions. [ABSTRACT FROM AUTHOR]

As a pavement maintenance technology, hot in-place recycling (HIR) can realize full utilization of reclaimed asphalt pavement (RAP), significantly saving non-renewable resources and project costs. However, due to variability of material properties, recycled mixtures gradation, and temperature control in construction, HIR-maintained pavement usually suffers from segregation, affecting performance and service life. To control construction quality and prolong service life, a segregation evaluation system of HIR-maintained pavement is proposed. This evaluation system, including calculation of segregation indexes, determination of segregation zones, and discrimination of segregation types, is established based on digital image processing (DIP) and surface texture distribution characteristics. In addition, it is verified by a case study of qualified HIR projects in Jiangsu Province in China. According to the empirical acceptance requirements of maintenance projects, discriminative zones for segregation types are established at 95% confidence level. Fluctuation curves of segregation indexes and image tests of four segregation types identified by segregation zones show that segregation indexes are well correlated with texture distribution characteristics and segregation degree, confirming the effectiveness and accuracy of the segregation evaluation system. Therefore, the segregation evaluation system of HIR-maintained projects proposed in this paper can realize real-time monitoring, rapid diagnosis, evaluation, and treatment decision-making of recycled pavement segregation degree. [ABSTRACT FROM AUTHOR]

In this paper, a tide forecasting tool called T_TIDE based on the classical harmonic analysis is introduced. The measured tide data are harmonically analyzed and tide forecasting was made by using the T_TIDE and the characteristics of tides at L俟si Tide Station (LSI Station) and Lianyungang Tide Station (LYG station) along Jiangsu coast are studied. The results show that the accuracy of T_TIDE in tidal prediction of Jiangsu coastal tides is highly satisfactory, which can provide tidal forecasting service and theoretical support for selection of the window period for coastal construction. M2 is the main tidal constituent at both LSI station and LYG station. The type of tides at both stations is all semi-diurnal. At LSI station, the amplitude of M2 presents an upward trend from 1998 to 2012 while at LYG station, the amplitude of M2 gradually decreased between 1995 and 2001 and increased between 2001 and 2012. Whereas, the phase-lag shows a significant downward trend at both LSI station and LYG station. Sea level changes at the two stations are also studied and the statistical results illustrate that the sea levels at LSI station and LYG station present an increasing trend and a decreasing trend, respectively. [ABSTRACT FROM AUTHOR]

To ensure the safety and stability of the shield tunnel construction process, the ground settlement induced by the shield construction needs to be effectively predicted. In this paper, a prediction method combining empirical mode decomposition (EMD), chaotic adaptive sparrow search algorithm (CASSA), and extreme learning machine (ELM) is proposed. First, the EMD is used to decompose the settlement sequence into trend vectors and fluctuation vectors to fully extract the effective information of the sequence; Second, the sparrow search algorithm is improved by introducing Cubic chaotic mapping to initialize the population and adaptive factor to optimize the searcher's position formula, and the chaotic adaptive sparrow search algorithm is proposed; Finally, the CASSA-ELM prediction model is constructed by using CASSA to find the optimal values of weights and thresholds in the extreme learning machine. The fluctuation components and trend components decomposed by EMD are predicted one by one, and the prediction results are superimposed and reconstructed to obtain the predicted final settlement. Taking a shield interval in Jiangsu, China as an example, the meta-heuristic algorithm-optimized ELM model improves the prediction accuracy by 10.70% compared with the traditional ELM model. The combined EMD-CASSA-ELM prediction model can greatly improve the accuracy and speed of surface settlement prediction, and provide a new means for safety monitoring in shield tunnel construction. Intelligent prediction methods can predict surface subsidence more automatically and quickly, becoming a new development trend. [ABSTRACT FROM AUTHOR]

Wind power curve (WPC) is an important index of wind turbines, and it plays an important role in wind power prediction and condition monitoring of wind turbines. Motivated by model parameter estimation of logistic function in WPC modelling, aimed at the problem of selecting initial value of model parameter estimation and local optimum result, based on the combination of genetic algorithm and least square estimation method, a genetic least square estimation (GLSE) method of parameter estimation is proposed, and the global optimum estimation result can be obtained. Six evaluation indices including the root mean square error, the coefficient of determination R2, the mean absolute error, the mean absolute percentage error, the improved Akaike information criterion and the Bayesian information criterion are used to select the optimal power curve model in the different candidate models, and avoid the model's over-fitting. Finally, to predict the annual energy production and output power of wind turbines, a two-component Weibull mixture distribution wind speed model and five-parameter logistic function power curve model are applied in a wind farm of Jiangsu Province, China. The results show that the GLSE approach proposed in this paper is feasible and effective in WPC modelling and wind power prediction, which can improve the accuracy of model parameter estimation, and five-parameter logistic function can be preferred compared with high-order polynomial and four-parameter logistic function when the fitting accuracy is close. [ABSTRACT FROM AUTHOR]

Based on the CH-3 and WH-110A unmanned aerial vehicle (UAV) platforms, we independently developed aeromagnetic systems for fixed-wing UAVs (FUAV) and modified unmanned helicopters (MUH), respectively. These systems overcome key technological challenges in system integration, aeromagnetic compensation, and electromagnetic (EM) compatibility. We conducted a 1:100,000 aeromagnetic test using both systems in a tidal flat area in Jiangsu province, China. Both systems successfully completed 240 line km measurement lines and collected high-quality data with magnetic compensation accuracies of 0.01428 nT and 0.04690 nT, respectively. The dynamic noise was below 0.14 nT, accounting for 95.72% and 100% of the measurements. These results indicate that both systems offer high measurement accuracy, efficiency, low cost, convenience, and flexibility. We compared the two aeromagnetic systems based on their system parameters, integration modes, magnetic compensation methods and effects, and practical applications. By comprehensively analyzing their characteristics and application fields, we provide guidance for UAV-based aeromagnetic surveys in mineral exploration, basic geological survey and other related fields. And the FUAV and MUH aeromagnetic systems presented in this paper serve as a valuable reference for future research in this area. [ABSTRACT FROM AUTHOR]

There are often planned (for example, regular maintenance) and unplanned (for example, pipe bursts) interruptions in a water distribution network (WDN). Therefore, part of the isolation valves must be closed to isolate the part (segment) of the network that contains one or more pipes. Isolation of the target pipe segment with minimum possible disruption has been a problem to be solved. A large number of studies have been conducted to optimize the design of isolation valve placement in new WDNs, but less attention has been given to reducing the isolation zone and improving the reliability of old WDNs by adding optimally placed isolation valves. Therefore, this paper proposes a multiobjective optimization model for adding optimally located isolation valves to old WDNs, which considers the dual objectives of economy and reliability. The installation or removal of isolation valves can cause the original segments to split or merge, so this paper proposes the use of the segment-valve (SV) graph local update (SVLU) algorithm instead of the seed-filling algorithm to construct the SV graph. The optimization model was applied to the valve layout modification of part of the WDN in Changshu, Jiangsu Province, China, and the results showed that the model can solve the optimization solution quickly (15.358 s). Moreover, the use of the SVLU algorithm improved the efficiency of the solved model by 26.71%. [ABSTRACT FROM AUTHOR]

The achievement of the carbon peaking and carbon neutrality targets requires the adjustment of the energy structure, in which the dual-carbon progress of the power industry will directly affect the realization process of the goal. In such terms, an accurate demand forecast is imperative for the government and enterprises' decision makers to develop an optimal strategy for electric energy planning work in advance. According to the data of the whole social electricity consumption in Jiangsu Province of China from 2015 to 2019, this paper uses the improved particle swarm optimization algorithm to calculate the fractional-order r of the FGM (1, 1) model and establishes a metabolic FGM (1, 1) model to predict the whole social electricity consumption in Jiangsu Province of China from 2020 to 2023. The results show that in the next few years the whole social electricity consumption in Jiangsu Province will show a growth trend, but the growth rate will slow down generally. It can be seen that the prediction accuracy of the metabolic FGM (1, 1) model is higher than that of the GM (1, 1) and FGM (1, 1) models. In addition, the paper analyzes the reasons for the changes in the whole society electricity consumption in Jiangsu Province of China and provides support for government decision making. [ABSTRACT FROM AUTHOR]

[Display omitted] • We constructed an industrial waste metabolism input-output model. • We considered the industrial wastewater, industrial waste gas and industrial solid waste. • We accounted for both direct and indirect industrial waste discharge. • The dominant sectors and ecological utility relationships of systems are identified. • The results support the formulation of waste management plans in Jiangsu Province. The enormous discharge of industrial waste seriously hinders the sustainable development of cities. However, most studies only involve a single or limited category of industrial pollutants, ignoring the environmental pressure caused by multiple resources and environmental factors. This paper combines input-output analysis and ecological network analysis to construct an industrial waste metabolic input–output (IWMIO) model, which explores the industrial waste discharge and discharge relationships among different sectors in Jiangsu Province from the three aspects of industrial wastewater, industrial waste gas, and industrial solid waste. The results show that the indirect discharge of industrial waste is greater than the direct discharge in the industrial waste metabolism system. TI (Tertiary industry), CI (Chemical industry), SPM (Smelting and pressing of metals), and PSEH (Production and supply of electricity and heat) dominate the industrial waste metabolism system. In addition, MWC (Mining and washing of coal), MNMP (Manufacture of non-metallic mineral products), SPM (Smelting and pressing of metals) have more mutualism and competition relationships with other sectors, so the control of industrial waste discharge in these sectors contributes to achieving emission reduction targets. Based on the research results, this paper proposes corresponding policy recommendations such as considering both direct and indirect emissions of sectors when formulating waste reduction policies and developing pertinent industrial waste reduction programs based on the characteristics of the identified sectors. The results of this paper are helpful to identify the dependence and influence relationships of various sectors in the industrial waste metabolism system, promote industrial waste discharge control, and provide theoretical support for the adjustment of industrial structure and the formulation of related policies in Jiangsu Province. [ABSTRACT FROM AUTHOR]

Due to the strategic emerging industrial cluster includes different types of subjects, their interaction will affect the industrial economy and innovation capacity. According lo the data of strategic emerging enterprises, this paper constructs the economic 2-mode network and innovative 2-mode network composed of the strategic emerging industries and regions, respectively, according to the main business income and the number of effective patents of enterprises. Using the centrality of social network analysis to measure the structural characteristics of the 2-mode network, this paper analyzes the development status and evolution trend of strategic emerging industrial clusters. Then the three-dimensional grey correlation model is used to evaluate the innovation ability of each region with strategic emerging industrial clusters. Finally, an empirical study is carried out with Jiangsu province's strategic emerging industrial cluster as a typical case. The results show that: (1)The new generation of informational technology, biological industry, and high-end equipment manufacturing industry all have high centrality in the network, and they are located in an important position in the network. It shows that these three industries have strong economic effects and innovation ability and have a strong ability to control inter-enterprise and inter-regional informational transfer, while the digital creative industry has low centrality and is still in its initial stage located at the edge of the network. (2) The network centrality of Nanjing and Suzhou has always ranked first and second, indicating that these two regions have the highest influence on the network. The strategic emerging industrial clusters of Nanjing and Suzhou are relatively well-developed, and the innovation and economy have formed a positive interaction effect in these industrial clusters. (3) The innovation ability Of strategic emerging industrial clusters in Suzhou, Wuxi, and Nanjing is relatively strong, while the innovation ability of strategic emerging industrial clusters iii Taizhou and Yancheng is relatively weak. There is a great difference between southern Jiangsui and northern Jiangsu. [ABSTRACT FROM AUTHOR]

The routine maintenance and rehabilitation of road pavement is vital to keep up with the service level and bearing capacity. However, the current problem is that, with the continuous increase of the scale of maintenance data, the traditional decision-making cannot satisfy the requirements in terms of accuracy and efficiency. The objectives of this paper were to improve the accuracy and efficiency of the maintenance decisions, overcome the decision error caused by insufficient human experience, and develop the mapping process for decision plans. This paper presented a decision-making method for asphalt pavement maintenance using improved weight random forest algorithm (IWRF) based on the correlation analysis (CA) and the analytic hierarchy process (AHP). Firstly, appropriate features were selected through CA of road detection data, and then decision trees were constructed based on Bootstrapping. Finally, qualified decision trees were chosen and weighted by AHP to form a random forest. To examine the feasibility, the algorithm was applied in a maintenance decision of the 80 km highway in Jiangsu province. The results showed that IWRF had a decision-making accuracy of up to 90%. Comparing with the traditional random forest algorithm, the IWRF algorithm had a 4.35% higher accuracy and saved 75% computation time. [ABSTRACT FROM AUTHOR]

Under the sustainability goals, how to promote the integration of port resources and reduce the ecological risks is important for the water transportation industry. Port cities in Jiangsu Province, a major coastal area in China, face a huge risk of resource waste. This paper aims to take Jiangsu as an example, understand the evolution of the spatial structure and the evolution of the water transportation industry, and explore the factors affecting development from the perspective of low-carbon development. Based on ArcGIS and multi-source data, methods such as Standard Deviation Ellipse (SDE) were used to understand the evolution, and the factors influencing the evolution at different stages were explored based on the green total factors such as industrial pollutions. It shows that the scale of the water transportation is expanding, but the industrial upgrading is not realized and has multiple agglomeration cores. The evolution was initially more affected by non-interventional factors such as geographical environment, while later the influence weakened significantly. The disordered development of water transportation industry has been worsening the current inefficient industrial structure and environmental risks. Further integration of industrial structure is needed, and strong administrative means are needed to help tap the unrealized spatial potential of resource integration. [ABSTRACT FROM AUTHOR]

Social and organizational innovations are one of the most effective ways to gain social collaboration for effective, rapid, and coordinated interventions. An analysis of the relationship among organizational performance (OP), social innovations (SI) and organizational innovation (OI) in social organizations (SOs) is little discussed in the literature and much less with main component analysis. This paper is an effort to provide some empirical evidences about social and organizational innovations that social organizations in China have implemented to address the social issues of the society. A survey of Chinese SO's is conducted during beginning two months of 2022 in provinces of Jiangsu, Guangdong and Zhejiang to attain the statistics and assessing the insights of the executives of the SOs participating in this study with respect to organizational performance, social and organizational innovations. The technique used to select the sample is a non-probabilistic sampling and multiple linear regression model is applied to determine the partial impact of organizational innovations and social innovations on the organizational performance. The grouping of the variables is carried out through main components analysis. The empirical findings of the study highlight that Chinese SOs are innovative because they adopt management strategies to address the social issues associated with their institutional mission. There are four groups of derived components from organizational and social innovations based on the empirical evidence: SO's innovative activities to modify the environment; inside innovative measures to enhance SO's performance; innovative activities of SO's to enhance their relationships with outside actors; innovative measures to improve the management of SOs related to their mission and institutional projects. The findings of this study offer an efficient solution to government and policy makers for involving SOs in terms of planning of social development in China. The social and organizational innovations are very necessary to overcome the social issues so government should encourage the establishment and sustainability of social organizations. [ABSTRACT FROM AUTHOR]

• A novel discrete multivariable grey prediction model considering the spatial proximity effect is proposed. • The complete spatial distance index is designed to quantify the intensity of the spatial proximity effect. • The spatial proximity effect term is constructed and incorporated into the grey prediction framework. • The proposed method extends the application field of the grey forecasting technology. • The novel forecasting method significantly outperforms a range of benchmark models. The temporal and spatial characteristics of the collected data typically play an essential role in time series forecasting. However, traditional grey models pay more attention to temporal information, meanwhile disregarding the presence of spatial features critical to producing accurate forecasts. Moreover, the grey theory has few attempts to overcome this problem. Given this situation, this paper proposes a novel multivariable grey prediction model considering the spatial proximity effect for time series forecasting. More specifically, the complete spatial distance index is defined initially based on the geographical and economic distance to quantify the intensity of the spatial proximity impact. On this basis, the spatial proximity effect term is constructed and incorporated into the conventional discrete multivariable grey model, establishing the novel model. Subsequently, the particle swarm optimization algorithm determines the optimal weight coefficient in the developed index. For illustration and verification purposes, the proposed model performs experiments predicting Jiangsu's economic outputs compared to five prevalent benchmarks. Furthermore, three statistical metrics, the Diebold-Mariano test, the Monte Carlo experiments, and the probability density analysis are employed to validate the model's efficacy and robustness. Empirical results demonstrate that the proposed method outperforms all five competitors with strong robustness and broad generalization. Therefore, this new model is used for forecasting Jiangsu's future economic outputs from 2021 to 2025. [ABSTRACT FROM AUTHOR]

Employee silence can degrade the working environment and decrease employees' motivation and commitment to an organization. As a result, it not only affects employees but also reduces the productivity of the organization. However, few studies have investigated the influencing mechanisms of employee silence empirically. This paper studies how illegitimate tasks affect employee silence based on artificial intelligence and fuzzy algorithms. We surveyed 325 employees in several medium-sized enterprises in Jiangsu and Anhui, China. According to the findings, emotional exhaustion partially mediates the relationship between illegitimate tasks and employees' silence behaviors, and leadership humor can moderate the positive effect of illegitimate tasks on emotional exhaustion. Therefore, situating the mechanisms underlying employees' silence behaviors in the context of artificial intelligence and fuzzy algorithm research helps researchers understand the relationship between illegitimate tasks and employees' silence behaviors, thus improving related research on silence behaviors. [ABSTRACT FROM AUTHOR]

[Display omitted] • A model for multi-objective optimization operation of multiple water sources under uncertainties was proposed. • Uncertainties in inflow and water demand forecasts can be considered simultaneously, and the correlation between uncertainties can be considered quantitatively. • The impact of inflow-water demand forecast uncertainties and their correlations on water resource operations are explored for water resources managers. Uncertainties in inflow and water demand forecasts bring risks to water resources management. Therefore, the research on multi-objective optimization operation of multiple water sources under uncertainties holds critical research significance and application value. This paper proposes a model for the multi-objective optimization operation of multiple water sources that can consider the inflow and water demand forecast dual uncertainties. In handling uncertainties, this paper adopts a scenario generation method based on joint distribution-Monte Carlo (JDMC), which allows for a quantitative consideration of the correlation between uncertainties. Moreover, the variable weight method and LINGO 20.0 are employed for solving multi-objective optimization issues to obtain stable Pareto frontiers. The proposed model is applied to the water receiving area inside Jiangsu Province of the South-to-North Water Transfer East Route Project (SNWTERP) in China. The main findings are as follows: 1) The impact of the inflow and water demand forecast uncertainties on the operation results is synergistic rather than antagonistic. Considering only a single uncertainty may result in water receiving area facing more severe water shortages or purchasing spot water at high prices. 2) There is a strong spatial correlation between uncertainties. If we ignore or only qualitatively consider the correlation between uncertainties, the impact of uncertainties on operation results will be underestimated or overestimated. 3) The Pareto frontiers are convex functions, indicating that decision-makers should choose a solution in the middle part. [ABSTRACT FROM AUTHOR]

In this paper, a computational fluid dynamics (CFD) simulation based on FLUENT software was performed to analyze the flow and heat transfer of the accident pipeline network in the water hammer burst accident of a thermal power plant in Jiangsu Province, China. Furthermore, the CFD simulation is also performed on the modified pipeline network to verify the effect of pipe network modification. The simulation results from the original accident pipeline show that in the accident pipeline, the steam velocity can reach up to 50 m/s due to the aggregation of liquid water. And when the high-velocity steam strikes the pipe elbow, it will lead to a sharp pressure change and cause the burst accident finally. Then it can be concluded that in the modified pipeline network, the distribution of temperature, pressure, and velocity at the pipe burst place is more uniform and reasonable. In addition, the simulation is also used to analyze the variable working conditions, which ensures that the new design of the pipe network can be used in more complex conditions. The paper is expected to guide the design of other similar pipelines and ensure the safe production and operation of thermal power plants. [ABSTRACT FROM AUTHOR]

The building sector is the second-largest energy consumer in China. With the proposal to reach a carbon peak by 2030 and achieve carbon neutrality by 2060, China attaches more importance to the energy conservation and emission reduction of the residential sector. To study the connection between socioeconomic factors and residential energy consumption (REC), this paper collects the data of 13 prefecture-level cities in Jiangsu Province, China, from 2001 to 2019 to explore the REC impact factors by the STIRPAT model. The factors for modeling are identified from relevant studies and weighted by the independent weight coefficient method (IWCM). The regression result shows that the average number of persons per household, per capita housing construction area, urbanization rate, and cooling degree days have a significant positive impact on REC, while a negative correlation is found between per capita housing construction area, residential water consumption, and residential liquefied petroleum gas (LPG) consumption. Strategies of energy conservation and emission reduction in residential building sector are explored based on the demonstration of the future REC pattern evolution and the changes in its impact factors. [ABSTRACT FROM AUTHOR]

Background: This paper seeks to assess the sustainability of the reformed maternity insurance system and the extent to which China's current maternity insurance system can support different levels of fertility incentives in the future. Our findings will serve as a reference for countries in a similar demographic predicament and those about to face it. Methods: This study used a combination of qualitative and quantitative methods. In the qualitative assessment, we used a grounded theory model to generalize the factors influencing the sustainability of maternity insurance funds. For the quantitative analysis, we used a novel and comprehensive system dynamics model to visualize the status of the combined operation of maternity and health insurance. Data are mainly derived from the historical data of the Statistical Yearbook of Jiangsu Province and the National Bureau of Statistics of China. Results: In the short term, fertility incentive payments can be set to motivate people to have children. It is therefore recommended that when the scope of the fertility incentive policy is limited to two children, and an average amount above RMB 10 000 could be set, it would be prudent to set the amount at a level not exceeding RMB 10 000 when the scope of the fertility incentive policy is for all newborns. In the long term, a system of incentives for childbirth should be built from education policy, house price regulation, tax relief and childcare services. Conclusion: Our research not only highlights the significance of improving the resilience of maternity insurance by combining maternity insurance and health insurance funds, but also suggests a way to economically incentivize beneficiaries to have children so as to mitigate the decline in China's birth rate and cope with the crisis of an ageing population. [ABSTRACT FROM AUTHOR]

Urban agglomerations are becoming an increasingly important factor in advancing regional development and reshaping a new pattern of regional competition. However, few studies are focused on the impact of expanding urban agglomerations on reducing carbon emissions and its possible mechanism. Based on 285 city-level panel data from 2006 to 2017, this paper uses a staggered Difference-in-Differences (DID) model to explore the reduction effect and its possible mechanism of sustainable regional development policy, characterized by urban agglomeration expansion policy in the Yangtze River Delta, on carbon emissions with policy shocks in 2010 and 2013. The results are as follows: (1) The urban agglomeration expansion policy shows a significant marginal contribution to the reduction of carbon emissions, especially for the later joined (new) cities, and the reduction effect is particularly significant in the first and third years after the expansion, indicating that there are significant short-term and long-term reduction effects of the expansion policy. (2) The heterogeneities of reduction effect among three provinces are significant. Zhejiang Province enjoys the largest proportion carbon emission reduction effect, followed by Anhui and Jiangsu provinces. To be specific, urban agglomeration expansion in Zhejiang Province reduced carbon emissions and carbon emissions intensity in the overall, incumbent cities and new cities, while it only increased the total carbon emissions of the incumbent cities in Jiangsu province. (3) The heterogeneities of reduction effect brought by 2010 and 2013 are also significant. The urban agglomeration expansion policy in 2010 reduced carbon emissions on the whole cities and the incumbent cities with later joined cities excluded, while it had a significant reduction effect on the total, incumbent cities, and the new cities in 2013. (4) There are two possible mechanisms of this reduction effect. One is the strengthening of economic ties and enhanced environmental synergy between governments, called the market integration mechanism, which only has a significant effect on carbon emission reduction in the incumbent cities. Another is through the upgrade of the structure of regional industries, which has a significant effect in both the incumbent and new cities. These findings suggest that when formulating urban agglomerations polices, governments must take into account the carbon emissions effect, and advance the upgrading of industrial structure in the urban agglomeration. [ABSTRACT FROM AUTHOR]

More and more dynamic reactive power devices (DRPDs) have been put into operation to improve voltage stability in AC/DC hybrid power system. In order to make full use of these devices, this paper presented an optimization technology for multiple DRPDs’ coordinate operation in the receiving-end of AC/DC hybrid power system. DRPDs’ steady-state reactive instructions are treated as optimization variables in the proposed model, while the objective is minimizing the successive times of HVDC’s commutation failure under a number of grounding faults. Power flow constraints and electromechanical transient process are considered simultaneously. Based on the characteristics of the model, commutation failure of HVDC under each grounding fault could be obtained by employing time-domain simulation method. Furthermore, particle swarm optimization (PSO) is used to get DRPDs’ optimal reactive instruction in steady-state. The simulation is done by considering Jiangsu power grid in eastern China, including synchronous condenser, STATCOM, and UPFC. The results show that the proposed model and algorithm are corrective and effective. [ABSTRACT FROM AUTHOR]

The acquisition of high-quality asphalt pavement inspection data is a key factor for road maintenance and management throughout the pavement's life cycle. This paper establishes a data cleaning framework that is based on data mining and deep learning to eliminate abnormal data points and interpolate missing points to improve the accuracy of the original road inspection dataset. The first process in the proposed framework is to analyse the influential factors that are used to evaluate data quality and calculate the abnormality of the data through the confidence interval used in Gaussian fitting. Then, a deep artificial neural network is established to learn the mapping between the inspection data and data abnormality. The abnormal points are removed according to their abnormality level. Next, a second deep artificial neural network predicts the missing point values. Finally, by defining the overall cleanliness index of the dataset as the optimisation target, the steps are repeated until the cleanliness threshold is met. In this study, the proposed framework was applied to rut depth data cleaning for a highway maintenance project in Jiangsu Province, China. The cleanliness of the rut depth data increased by 6–95.75% after one cleaning cycle. [ABSTRACT FROM AUTHOR]

Road networks are the skeletal elements of topographic maps at different scales, and road selection is a prerequisite for implementing continuous multiscale spatial representations of road networks. The mesh-based approach is a common, advanced and powerful method for road selection in dense road areas in which small meshes are removed and road segments with the least importance in each mesh are eliminated. However, small meshes in a map can be classified into two types: aggregated small meshes and isolated small meshes. The number of the former is small, and that of the latter is large. Existing methods are generally applicable for the latter, and some or even most spatial characteristics will be lost when they are applied to the former; as a result, the road selection quality will be affected. Therefore, as a supplement to the mesh-based selection method, this paper proposed an automatic generalization method of dense road network areas (areas formed by aggregated small meshes) considering spatial structural features as constraints. First, the aggregated areas of small meshes were identified based on the number of adjoining small meshes, and the boundaries of aggregated areas are extracted and used as hard constraints during mesh elimination. Second, the starting meshes were redefined by simultaneously considering the edge features and mesh density of small meshes, and an ordinal elimination algorithm was proposed to eliminate the meshes in the stroke connection direction. Third, road selection was implemented by identifying the starting meshes and sequentially processing the related mesh pairs. This iterative process continued until all mesh densities of the newly formed meshes are beyond the threshold or the problem becomes a simple elimination problem involving two adjoining small meshes or one isolated small mesh. Finally, a 1:10,000 standard topographic road map for Jiangsu Province, China, was used for validation. The experimental results showed that in the aggregated areas with two small meshes, 31% of the areas obtained the same selection results by using the mesh-based method and the proposed method, and the remaining 69% obtained a more compact result with the proposed method. Moreover, for all aggregated areas with more than two small meshes, the spatial distribution structure of small meshes was preserved better by the proposed method. [ABSTRACT FROM AUTHOR]

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