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The construction industry has long been regarded as a relatively conservative and less innovative sector. Adjusting corporate governance structure is an effective method to promote innovation in the construction industry, as it can internally address the reluctance to innovate within companies. While it is widely known that the chief executive officer (CEO) plays a crucial role in firm innovation, few studies have explored the effects of CEO duality on innovation from a corporate governance aspect, which serves as a pressing need for construction industry. This study investigates the influence of CEO duality and its important moderating variable, CEO overconfidence, on corporate innovation based on a sample of stock-listed China construction companies and their patent data from 2009 to 2022. Quantile regression is applied to deeply investigate the variation in the impact of CEO duality throughout different conditional quantiles of the construction innovation performance distribution. The results demonstrate a favorable correlation between CEO duality and corporate innovation performance, and the promotion effect of CEO duality is more significant for firms with lower innovation performance. Additionally, CEO overconfidence negatively moderates the impact of CEO duality on corporate innovation. These findings indicate that CEO duality plays a noteworthy role in promoting corporate innovation within the construction industry and more effective corporate governance mechanism is needed to control CEO overconfidence, which promotes the negative impact of CEO duality. The research provides a research framework for exploring the dynamic impact of corporate governance structures on firm performance in the future. The results of this study are of significant importance for both the theoretical understanding and practical implementation of corporate governance mechanisms in the construction industry. [ABSTRACT FROM AUTHOR]

Globally, the transportation industry has become one of the leading sectors in carbon emission, and all countries are committed to environmental protection and energy conservation while experiencing rapid development. Under China's "dual-carbon" goal, the carbon emission problem hinders the construction of China's green transportation system and affects the high-quality development of transportation, so it is of great significance to study the spatial pattern of carbon emission efficiency in the transportation industry and the factors affecting it. Firstly, this paper measures the carbon emission value of transportation in 30 provinces in China from 2010 to 2020 based on the IPCC method and measures the carbon emission efficiency through the super-efficiency slack-based measurement model. Secondly, spatial autocorrelation analysis was conducted to determine the spatial clustering characteristics of the efficiency values. Finally, two spatial Durbin models are constructed to measure the spatial spillover effects and analyze the short-term immediate effects of each influencing factor on the static model and the long-term effects of the dynamic model considering the time lag of the transportation carbon emission efficiency. The results of the study show that (1) the average value of efficiency in the central and eastern regions is basically higher than 0.5; in the western and northeastern regions, it is basically lower than 0.3.The overall efficiency of carbon emission in the region shows a fluctuating upward trend but with increasing regional differences. (2) The number of regions with positive spatial correlation increased from 21 to 25 during the study period, and the degree of provincial transportation carbon emission efficiency agglomeration increased. (3) Although urbanization and energy intensity have a large detrimental influence on transportation carbon emission efficiency, environmental regulation has a major favorable effects on it both long and short term. Population scale, opening level, and urbanization all have significant spatial spillover effects. Accordingly, relevant policy recommendations are put forward to provide theoretical guidance for promoting the realization of low-carbon transportation. [ABSTRACT FROM AUTHOR]

Human mobility survey data usually suffer from a lack of resources for validation. Epidemiological survey records, which are released to the public as a containment measure by local authorities, provide place visitation details validated by the authority. This study collected and analyzed the epidemiological survey reports published by local governments in the Chinese mainland, between January 2020 and November 2021. To reveal the mobility patterns during the COVID-19 pandemic across the urban-rural gradient in China's mainland, we derived key mobility indicators from the epidemiological survey data from rural to megacities. We then applied exploratory factor analysis to identify latent factors that affected people's mobility. We found that the pandemic poses varying impacts across the urban-rural gradient in the Chinese mainland, and the mobility patterns of middle and small cities are more influenced. Our results also showed that the pandemic did not enlarge gender gap in people's mobility, as gender was not a significant driving factor for explaining people's quantity of out-of-home activities as well as extent of life space, while age group and city levels were significant. Overall, we argue that the epidemiological survey data are valuable data sources for daily mobility modeling, especially for relevant studies to understand human mobility patterns during the pandemic. [ABSTRACT FROM AUTHOR]

The Tarim Basin, a significant region of coal-derived gas generation in China, has widely dispersed coal measure source rocks, especially in the Kuqa Depression. The typical coal measure strata from the Kuqa River and Kapushaliang River sections in the Kuqa Depression were systematically sampled. According to a conventional geochemical analysis (including materials and lithology), a total of 25 typical coal measure source rock samples were chosen for chromatography and chromatography–mass spectrometry examination. It was demonstrated that there were significant discrepancies in the coal source rock samples, particularly the coal rock from the Kuqa River section and the Kapushaliang River section. The specific performance of the Kuqa River section was characterized by a high Pr/Ph ratio (up to 9.29), a low gammacerane ratio, a low abundance of tricyclic terpane, and an "L"-type distribution of regular steranes, all of which are consistent with the properties of humic coal found in freshwater lakes that have undergone partial oxidation. The Kapushaliang River section, by contrast, exhibited a low Pr/Ph ratio (<1.0), a high gammacerane ratio, a concentration of tricyclic terpane comparable to that of hopane, and a distribution of regular steranes in a "V" shape, all of which indicate a strongly reduced saline water environment. Additionally, the degree of thermal evolution is not the key factor resulting in the above biomarker diversity within the CSRs, which was supported by the poor correlation between the maturity parameters (Ro%, Tmax °C), the sedimentary environment-related parameters (such as Pr/Ph and Ga/C31H), and the biogenic-related parameters (such as ∑tricyclic terpane/∑ hopane and ∑sterane/∑hopane). A comparative analysis suggested that transgression-related changes in the redox conditions and parent materials triggered the biomarker diversity within the CSRs, resulting in a large difference in the hydrocarbon-forming parent materials between the two abovementioned outcrop sections. These might provide some insight for hydrocarbon exploration from CSRs, which have been attracting increasing attention in China, with proven coal reserves are ranked first in the world. [ABSTRACT FROM AUTHOR]

In this study, a mesoscale Weather Research and Forecast (WRF) model coupled with an AgI (silver iodide) cold cloud catalytic module were used to explore the potential impact of the catalytic position and rate in the catalytic module based on a ground rain enhancement operation in the Qilian Mountains, on 16 August 2020. Results show that the simulated precipitation, liquid water content (LWC), and water vapor content (PWV) are in good agreement with the observations, demonstrating that the WRF model using the coupled AgI cloud-seeding scheme is well-applicable to the precipitation simulation of the Qilian Mountains. It is also observed that there are some differences in the catalytic effect of catalysis at different cloud temperatures. The precipitation enhancement effect is the most favorable in the fifth layer of 15 km, followed by that in the fourth layer of 12 km and the sixth layer of 18 km. Considering the flight cost and catalytic efficiency, the fourth layer is highly recommended for seeding. Furthermore, the AgI seeding rate also plays a crucial impact on ground precipitation. In the case of a seeding rate of about 1.2 g·s−1, the precipitation enhancement effect tends to be stable, and the percentage of the precipitation increase reaches up to 10.4%. While in the case of a seeding rate of about 1.5 g·s−1, the percentage of ground precipitation increase is 10%, which is 0.4% lower than that of 1.2 g·s−1. In summary, the introduction of a AgI catalyst with a seeding rate of 1.2 g·s−1 can significantly increase the ground precipitation at a height of 12 km and a temperature of −3 °C in the Qilian Mountains. [ABSTRACT FROM AUTHOR]

Seasonal low-oxygen in marine ranching in the northern Yellow Sea has been one of the major environmental problems in coastal waters in recent years. Nitrogen (N) and phosphorus (P) are important nutrients, which are susceptible to the concentration of dissolved oxygen (DO). This article studied the effects of low-oxygen on nutrients represented by N and P fractions in marine ranching in the northern Yellow Sea. The results showed that there were significant layer differences in temperature and salinity during the low-oxygen period. In the seawater, the nutrient distribution in the death disaster zone of sea cucumbers and the non-disaster zone was similar, and DO had a strong positive correlation with dissolved inorganic nitrogen (DIN). In the sediment, significant regional differences existed in nutrient concentration, and the concentration of total phosphorus (TP) decreased significantly with the increase in DO content. The results showed that the sources and sinks of nitrogen and phosphorus nutrients were inconsistent in this zone, and migration and transformation of the existing form of nitrogen with the seasonal changes in the water environment was a main factor for N distribution. This study extended the understanding of the effects of seasonal low-oxygen on N and P. [ABSTRACT FROM AUTHOR]

With the rapid development of communication technology and automation technology, sensors are becoming more and more intelligent. This study proposes an environmental accounting system model based on artificial intelligence blockchain and embedded sensors. A high-precision sensor system based on embedded technology is first built, which not only avoids the shortcomings of analog data transmission, but also has high performance and price advantages. At the same time, it can be easily combined into a simple sensor network, and array measurement can be realized through the development of blockchain technology. However, the current blockchain system has the disadvantage of storage limitation. The problem is particularly serious when a large amount of data needs to be stored in the blockchain, especially when the blockchain is combined with big data. As a comprehensive field of accounting, ecology, and environmental science, environmental accounting has made great contributions to sustainable development in the field of accounting. The theoretical research in the field of environmental accounting in China started late, and a unified environmental accounting system has not actually been established. Under the conditions of immature theoretical and policy basis, companies have almost no actual surveys on environmental accounting. The characteristics of blockchain technology, such as decentralization, transparency, and changes in information unavailability, can fully solve the problem that the current accounting information system cannot consolidate transaction information and the accounting process. The reliability assurance mechanism of the accounting information system based on blockchain technology can greatly ensure the reliability of the accounting information system, effectively suppress accounting fraud, and improve the transparency of information. [ABSTRACT FROM AUTHOR]

Aim: This study aimed to assess the overall status of burnout in nurses in China on a national scale and investigate the demographic characteristics related to burnout and the relationships between demographics, job satisfaction and burnout. Methods: This was a national cross‐sectional study conducted by the Chinese Nursing Association between July 2016 and July 2017. Data were collected using a structured, self‐administered questionnaire. Results: A total of 51 406 registered nurses in 311 Chinese cities completed the questionnaire. Fifty per cent of the participants suffered burnout, and 33.8% of nurses had high scores on emotional exhaustion, 66.6% had high scores on depersonalization and 93.5% had low scores on personal accomplishment; 16.2% reported a high level of job satisfaction, only 0.4% was satisfied with their jobs and 70.7% intended to leave their jobs. Marital status, educational level, income and years of working experience affected job burnout. Nurses with a high level of burnout were more likely to have a high degree of job dissatisfaction and intend to leave their jobs. Conclusion: We found a high prevalence of burnout among nurses in China. Nursing managers need to pay more attention to job burnout and its influencing factors. Interventions to reduce nurse burnout should be implemented. SUMMARY STATEMENT: What is already known about this topic? Burnout is a prolonged response to chronic job‐related stress and it has a negative effect on job satisfaction and quality of nursing care. What this paper adds? The prevalence of burnout among nurses working in China is high.Marital status, educational level, income and years of working experience affect job burnout.Nurses with a high level of burnout have high job dissatisfaction and intend to leave. The implications of this paper: Nursing supervisors and managers need to be more aware of the high prevalence of job burnout among nurses in China.Interventions should be undertaken to prevent or reduce nurse burnout. [ABSTRACT FROM AUTHOR]

At present, atmospheric aerosol pollution is a major issue in China. Himawari-8 (H8) aerosol products with high temporal resolutions are helpful for achieving real-time monitoring of subtle aerosol variation. However, the H8 aerosol optical depth (AOD) product has been updated three times since its launch, and evaluations of this dataset are scarce at present. To validate its accuracy, this study compared the H8 Level-2 (L2) minute AOD products of all versions with measurements obtained from eight typical sites in eastern China, a high aerosol region, in 2016. The AOD of H8 version 010 underestimated observed AOD by 37%-46% in this region. The overall underestimation of AOD in version 021 still exists (7%-15%). The absolute error of H8 AOD in version 010 symmetrically increased by 0.05 while increasing the observed AOD by 0.1, which was a span error for H8 AOD in version 010. Based on the absolute error linear regression equation, a span error correction was performed in the region. Compared with the AOD of version 021, the span error corrected AOD of version 010 has lower uncertainty (Root Mean Squared Error (RMSE): 0.13-0.39) and higher consistency (s: 0.80-1.2). The underestimation was also further improved (2%-4%). [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: Recently, the concept of financial technology (FinTech) has attracted extensive attention from international organisations and regulators, in particular, how to achieve a "win–win" situation between financial institutions' FinTech innovation and effective regulation has become a hot topic. This study purposes to explore the evolutionary game relationship between FinTech innovation and regulation by constructing both static and dynamic earmarking game models. Design/methodology/approach: A simulation experiment was conducted using primary data obtained from a commercial bank in China. Findings: The results of the theoretical analysis of evolutionary game models were consistent with the corresponding simulation results, proving the validity of the proposed evolutionary game models. It was also found that the dynamic earmarking game model was more stable and effective than the static earmarking game model in promoting FinTech innovation and regulation. Furthermore, when the regulators utilised a dynamic earmarking mechanism, the evolutionary path of financial institutions and regulators' behaviour strategies took the shape of a spiral and eventually converged to a central point, indicating the existence of an evolutionary stable strategy and Nash equilibrium. Finally, because the behaviour strategies of financial institutions were mainly influenced by the regulators' policies, the regulators were inspired to adjust the corresponding regulation policies on FinTech innovation. Originality/value: This study bridges the knowledge gap in the existing literature on financial innovation and regulation, in particular by establishing evolutionary game models from the perspective of financial earmarking policies. Also, the case study for simulation experiments can gain a more intuitive insight into FinTech innovation and financial earmarking policies. [ABSTRACT FROM AUTHOR]

A distinctive kind of organic carbon aerosol that could absorb ultraviolet-visible radiation is called brown carbon (BrC), which has an important positive influence on radiative budget and climate change. In this work, we reported the absorption properties and potential source of BrC based on a seven-wavelength aethalometer in the winter of 2018–2019 at an urban site of Sanmenxia in Fenwei Plain in central China. Specifically, the mean value of BrC absorption coefficient was 59.6 ± 36.0 Mm−1 at 370 nm and contributed 37.7% to total absorption, which made a significant impact on visibility and regional environment. Absorption coefficients of BrC showed double-peak pattern, and BrC had shown small fluctuations under haze days compared with clean days. As for the sources of BrC, BrC absorption coefficients expressed strong correlations with element carbon aerosols and primary organic carbon aerosols, indicating that most of BrC originated from primary emissions. The linear correlations between trace metal elements (K, As, Fe, Mn, Zn, and Pb) and BrC absorption coefficients further referred that the major sources of BrC were primary emissions, like coal burning, biomass burning, and vehicle emissions. The moderate relationship between BrC absorption coefficients and secondary organic aerosols suggested that secondary production of BrC also played an important role. The 120 hr backward air mass trajectories analysis and concentration-weighted trajectories analysis were also used to investigate potential sources of BrC in and around this area, which inferred most parts of BrC were derived from local emissions. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Suicide has become one of the most prominent concerns for public health and wellness; however, detecting suicide risk factors among individuals remains a big challenge. The aim of this study was to develop a machine learning algorithm that could effectively and accurately identify the probability of suicide attempts in medical college students.Methods: A total of 4,882 medical students were enrolled in this cross-sectional study. Self-report data on socio-demographic and clinical characteristics were collected online via website or through the widely used social media app, WeChat. 5-fold cross validation was used to build a random forest model with 37 suicide attempt predictors. Model performance was measured for sensitivity, specificity, area under the curve (AUC), and accuracy. All analyses were conducted in MATLAB.Results: The random forest model achieved good performance [area under the curve (AUC) = 0.9255] in predicting suicide attempts with an accuracy of 90.1% (SD = 0.67%), sensitivity of 73.51% (SD = 2.33%) and specificity of 91.68% (SD = 0.82%).Limitation: The participants are primarily females and medical students.Conclusions: This study demonstrates that the random forest model has the potential to predict suicide attempts among medical college students with high accuracy. Our findings suggest that application of the machine learning model may assist in improving the efficiency of suicide prevention. [ABSTRACT FROM AUTHOR]

Atmospheric aerosol plays critical roles in suppressing planetary boundary layer (PBL) and deteriorating air quality. However, comprehensive understanding on how aerosol optical properties (absorption and scattering) affect PBL remains lacking. Utilizing a large‐eddy simulation model incorporated with in situ observations, we demonstrate distinct impacts of absorption aerosol on PBL development when it is present below (stove effect and promotion) or above morning residual layer (dome effect and strong inhibition) and similar inhibition umbrella effects of scattering aerosol on PBL regardless of its vertical locations. There exists a transition height, above which absorption aerosol is more effective in suppressing PBL and below which scattering aerosol dominates the suppression. This height is highly related to the height of morning residual layer. Aerosol stove, dome, and umbrella effects enrich our knowledge on aerosol‐PBL interactions and the latter two can be interpreted as "double inhibitions" in promoting haze episodes in the North China Plain. Key Points: Aerosol stove, dome, and umbrella effects are summarized by lying absorption and scattering aerosol below or above morning residual layerThere exists a transition height, above which the absorption aerosol dominates the PBL inhibition, otherwise scattering aerosol dominatesAerosol dome and umbrella effects are interpreted as "double inhibitions" to explain the formation of haze events in NCP region, China [ABSTRACT FROM AUTHOR]

As a type of clean and renewable energy, the superiority of wind power has increasingly captured the world’s attention. Reliable and precise wind speed prediction is vital for wind power generation systems. Thus, a more effective and precise prediction model is essentially needed in the field of wind speed forecasting. Most previous forecasting models could adapt to various wind speed series data; however, these models ignored the importance of the data preprocessing and model parameter optimization. In view of its importance, a novel hybrid ensemble learning paradigm is proposed. In this model, the original wind speed data is firstly divided into a finite set of signal components by ensemble empirical mode decomposition, and then each signal is predicted by several artificial intelligence models with optimized parameters by using the fruit fly optimization algorithm and the final prediction values were obtained by reconstructing the refined series. To estimate the forecasting ability of the proposed model, 15 min wind speed data for wind farms in the coastal areas of China was performed to forecast as a case study. The empirical results show that the proposed hybrid model is superior to some existing traditional forecasting models regarding forecast performance. [ABSTRACT FROM AUTHOR]

Population agglomeration and haze pollution are two major problems that urban development will inevitably face in the future. Population agglomeration has a spatial impact on smog pollution through scale and intensive effects. This paper uses panel data from 236 prefecture-level cities in China from 2001 to 2012 to verify the impact of urban population agglomeration on haze pollution and its mechanism based on a spatial lag model. The research shows that: (1) China's urban haze pollution has a significant positive spatial spillover effect, and presents a spatial distribution state of high-high and low-low agglomeration. (2) There is a significant "N-type" nonlinear relationship between urban population agglomeration and haze pollution. (3) At present, the scale effect of urban population agglomeration in China is greater than the intensification effect, and the scale effect as well as intensification effect have opposite effects on haze pollution. This shows that urban layout should be scientifically planned, urban population should be reasonably controlled, production efficiency should be improved, and green development should be promoted to deal with haze pollution. (4) The spillover effect of urban population agglomeration on haze pollution is significantly greater than the direct effect, indicating that local haze pollution is more likely to be affected by spatially related regions, indicating that strengthening regional coordination and cooperation and joint prevention and control are necessary to control haze pollution. [ABSTRACT FROM AUTHOR]

Due to increased global carbon dioxide emissions, the greenhouse effect is being aggravated, which has attracted wide attention. China is committed to promoting the low-carbon development of all industries. This paper analyzed the influencing factors of carbon emissions in the Chinese logistics industry, so as to identify the key factors that influence carbon emissions. Based on the carbon emission data of China's logistics industry in 2000–2019, this paper applied the carbon emission coefficients issued by the Intergovernmental Panel on Climate Change. For the first time, the Generalized Divisia Index Method was used to analyze the degree of influence of the factors on carbon emissions. This method considered more variables and their relationships. The results showed that (1) the carbon emissions of the logistics industry were increased by 3.22 times from 2000 to 2018, and showed negative growth for the first time in 2019; (2) the added value of the logistics industry is the most important factor in increasing carbon emissions (with a contribution ratio of 65.45%), energy consumption and practical population size are the main factors in carbon emissions. The promotion of this industry is subjected to decreased per capita carbon emissions, which have a large impact on total carbon emissions; (3) the intensity of carbon output is the most important factor in the reduction of carbon emissions (with a contribution ratio of −29.1%), where the energy carbon intensity and per capita added value are the main influencing factors with regard to the reduction of carbon emissions, while energy intensity has a negative inhibitory effect on carbon emissions, and (4) the influencing factors have negative effects on the cumulative inhibition of carbon emissions in the logistics industry, to an extent that is far less than the integral promotion of carbon emissions. Finally, according to the research conclusions of this paper, it is feasible to make recommendations for the carbon reduction of the logistics industry. [ABSTRACT FROM AUTHOR]

• Monetary resettlement compensation influences the house purchase intention greatly. • Compensation flows back from rural to urban areas through house purchase behavior. • The existing policy has hindered two-way flow between urban- rural resources. • A new strategy to achieve two-way flow between urban-rural resources was proposed. The reasonable two-way flow of resources between urban and rural areas underlies the processes of urban-rural transformation and rural revitalization in China. The monetary resettlement compensation policy has been formulated to promote this two-way flow through market-oriented measures. This study extends the Theory of Planned Behavior by enhancing the variable of monetary resettlement compensation factor to analyze the behavioral tendencies of house purchase intention of relocated households in Zhejiang Province, China. An empirical analysis through PLS-SEM was conducted on the results obtained from 271 survey responses, and eight hypotheses were verified using SmartPLS 3. The results demonstrate that the monetary resettlement compensation policy may facilitate relocated households' purchase of houses in urban areas, which is indicative of compensation flowing back from the rural to urban areas through the house purchase behavior. Furthermore, a study on the possible gap between relocated households' purchase intention and their actual purchase behavior shows that the intention is aligned with actual action. The monetary resettlement compensation policy has thus failed and even hindered the achievement of a reasonable two-way flow of resources between urban and rural areas. [ABSTRACT FROM AUTHOR]

• Mobile social media use intention in emergencies among China's Gen Y is studied. • Social media dependency is related to gratifications sought during emergencies. • Gratifications influence use intention except for information sharing. • Task-technology fit influences use intention. • Communication and task-technology fit are the most important antecedents. Mobile social media have great potential for emergency management with their penetration into the daily life of humans. Drawing on theories of gratifications, task-technology fit, and media dependency, we develop an integrative research model to understand Gen Yers' mobile social media use intention in emergencies. Based on survey data from 424 Gen Y users in China, we conduct a structural equation modeling analysis and an artificial neural network analysis to validate the model. On one hand, social media dependency has a significant and positive effect on gratifications users seek during emergencies. Each gratification positively influences use intention except for information sharing. In order of the effects on use intention, communication is the most important, followed by solitary play and information seeking. On the other hand, both perceived mobility and task features positively influence perceived task-technology fit, which in turn exerts a significant effect on mobile social media use intention. The findings provide a fine-grained understanding of the relative importance of key predictors of mobile social media use intention in emergencies. Moreover, these findings, however limited to China's Gen Y, suggest a role of solitary play and raise possible concern regarding an absence of information sharing. [ABSTRACT FROM AUTHOR]

• Explore how environmental regulation impacts the urban land use of eco-efficiency. • An inverted U-shaped relationship between environmental regulation and urban land use eco-efficiency. • The mediation model is used to analyze the mediation effect. • The mediated chain model is used to analyze the conduction pathway. • Environmental regulation improves urban land eco-efficiency mainly through mediating effects. Due to high pollution and low eco-efficiency of urban land use, the sustainable development of urban economy and ecology is restricted. Environmental regulation (EnR) is essential for the government to guide the eco-efficient use of land resources, solve environmental problems, and promote ecological civilization construction. Utilizing a dataset comprising 266 cities in China from 2011 to 2021, this paper studies the intermediary effect of green technology innovation (GTI) and industrial structure optimization (ISO) in EnR affecting urban land use eco-efficiency (ULUEE). The results show that: (1) The EnR significantly promotes the improvement of ULUE, reaching 0.354; (2) EnR also promotes GTI and ISO to 0.653 and 0.189, respectively; (3) From the results of mediating effect, GTI and ISO are mediating variables that affect the level of ULUEE. GTI also affects ULUEE through ISO. From the perspective of the path coefficient of the chain mediating effect, the influence coefficient of path① (EnR → GTI → ULUEE) is 0.107, path② (EnR → ISO → ULUEE) is 0.111, and path③ (EnR → GTI → ISO → ULUEE)) is 0.043; (4) There is an inverted U-shaped relationship between the effects of EnR on ULUEE; (5) In the heterogeneity analysis, the effect of EnR on ULUEE is more evident, but the impact is less pronounced in eastern cities and large cities of scale. [ABSTRACT FROM AUTHOR]

In order to achieve the targets specified in the Action Plan for Air Pollution Prevention and Control (APAPPC), a limited coal banning area (10,000 km2) was designated in the heavily polluted Beijing-Tianjin-Hebei region (BTH) for the first time in 2017. PM 2.5 and elements were sampled by the network of BTH to evaluate the effectiveness of this policy. This study found that the fine days with PM 2.5 < 75 μg m−3 accounted for 74.3% in the autumn and winter of 2017, which was significantly higher than that in 2016 (43%). The heavily polluted days (PM 2.5 > 150 μg m−3) also decreased from 32.2% in 2016 to 4.9% in 2017. Arsenic (As) is an important tracer in coal consumption, which can be used to reflect the influence of the establishment of coal banning areas on north China. The cluster analysis of air mass forward trajectory identified that the number of polluted trajectories with PM 2.5 and As in 2017 decreased by 47.6% and 49.7%, respectively. Under the implementation of the coal banning policy, the weighted concentration of PM 2.5 and As decreased by 94.2 μg m−3 and 5.1 ng m−3 in the coal banning area, 60.9 μg m−3 and 3.4 ng m−3 in the no coal banning area in BTH, respectively. The influence of weighted concentration of PM 2.5 and As in coal banning area on North China were 1.6–49.2 μg m−3 and 0.15–2.8 ng m−3, respectively, which was 38.8% and 29.7% lower than 2016. In coal banning area, BTH and other parts of North China, the reduction of the weight concentration of PM 2.5 in 2017 accounted for 41.4%, 26.8% and 31.8% of the total reduction, respectively, so was the As in 39%, 26.3% and 34.6%, indicating that setting up a coal banning area scientifically in limited areas can produce remarkable regional benefit. [Display omitted] • Coal banning area brought remarkable environmental benefit to the whole north China. • Fine days in the autumn and winter of BTH increased from 43% in 2016 to 74% in 2017. • Impact of PM 2.5 in coal banning area (BTH) reduced by 94.2 (60.9) μg m−3 in 2017. • The impact of coal banning area on PM 2.5 in North China decreased by 48.3% in 2017. [ABSTRACT FROM AUTHOR]

The particulate matter (PM) pollution has been significantly improved by carrying out various valid emission control strategies since 2013 in China. Meanwhile the variation trend of nitrous acid (HONO) is worthy to investigate due to its vital role in the atmospheric oxidation process. In this study, field observation in the winter is conducted to investigate the concentration of HONO in an urban area of Beijing. In the winter of 2019, the mean HONO concentration is 1.38 ppbV during the whole winter. Photo-enhanced NO 2 heterogeneous reactions on the ground and aerosol surfaces were found as the possible daytime sources of HONO. Compared to O 3 , photolysis of HONO dominates the primary OH sources during the winter time. To understand the HONO pollution patterns by years variation, multi-year data is summarized and finds that primary pollutants including CO and NO decreased, but secondary pollutants i.e., HONO (mostly generated via secondary process) increased. Our study highlights the requirement to mitigate secondary pollution by control HONO concentration. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: Wind energy has been well recognized as a renewable resource in electricity generation, which is environmentally friendly, socially beneficial and economically competitive. For proper and efficient evaluation of wind energy, a hybrid Seasonal Auto-Regression Integrated Moving Average and Least Square Support Vector Machine (SARIMA–LSSVM) model is significantly developed to predict the mean monthly wind speed in Hexi Corridor. The design concept of combining the Seasonal Auto-Regression Integrated Moving Average (SARIMA) method with the Least Square Support Vector Machine (LSSVM) algorithm shows more powerful forecasting capacity for monthly wind speed prediction at wind parks, when compared with the single Auto-Regression Integrated Moving Average (ARIMA), SARIMA, LSSVM models and the hybrid Auto-Regression Integrated Moving Average and Support Vector Machine (ARIMA–SVM) model. To verify the developed approach, the monthly data from January 2001 to December 2006 in Mazong Mountain and Jiuquan are used for model construction and model testing. The simulation and hypothesis test results show that the developed method is simple and quite efficient. [Copyright &y& Elsevier]

In 2017, a coal banning area of approximately 10,000 square kilometers was established in the Beijing-Tianjin-Hebei (BTH) region of China for the first time. This study compared the change of elemental concentrations during the autumn and winter of 2016 and 2017, and analyzed the environmental and health benefits of the coal banning policy. Result showed that compared to 2016, the reduction rate of atmospheric particulate matter with an aerodynamic diameter no larger than 2.5 μm (PM 2.5) in 2017 was as high as 63.5% (p < 0.01), and that of the total elements in PM 2.5 was up to 43% (p < 0.01). Coal consumption, transportation, industry, soil dust, and fuel consumption were the main sources of these elements in BTH. Coal consumption and industry accounted for 5.8–26.2% and 6.5–31.3%, respectively, of the total elements. After the coal banning area was established, the elements from coal consumption were reduced by 13.5–60.3% (the background station was reduced by 19.6%, p < 0.05), and those from industrial sources were reduced by 11–80.1%. The results of the health risk assessment showed that the carcinogenic risk of the coal consumption and industrial sources had been reduced by 30.7–48.3% in 2017. The policy of the coal banning is very effective in controlling the air pollution in urban agglomeration in developing countries and has resulted in great health and environmental benefits. Image 1 • Coal Banning Area is the most efficient pollution control measure in BTH in 2017. • The measure cut down the bulk coal consumption by 10.2% in the 10,000 km2 region. • The measure has resulted in the high benefits of environment and health in BTH. • PM 2.5 and total elements declined drastically by 63.5% and 43% in 2017. • The carcinogenic risk index of hazardous elements decreased by 36.3% in BTH. [ABSTRACT FROM AUTHOR]

a wide-range winter frontal fog that happened over Circum-Bohai-Sea (CBS) on December 17–192,016 was observed using satellite cloud image inversion, surface, ocean buoy, and radiosonde data. The evolution of fog processes was investigated with numerical simulations using the Weather Research and Forecasting (WRF) Model together with the FNL (Final) reanalysis data. The results show that the WRF model can reproduce the features of the heavy fog generation and development. The observed results show following characteristics: (1) Before fog appearance, the southwest low-level jet (LLJ) of which the wind speed was over 16 m/s at 925 hPa developed. The LLJ carrying warm and wet air provided a stable inversion layer about 1200 m thick and continuous vapor transport to the CBS area, which is favorable for the formation of heavy fog. With the weak northwestern cold air moving towards the CBS area, a typical frontal fog process was triggered; (2) the weak cold air did not destroy the structure of low-level thermal inversion, and the heavy fog maintained. With the weak front moving towards the east, the foggy coverage continually extended over the sea surface, finally covering the Bohai Sea and the North Yellow Sea. A water-vapor sensitivity test suggests that with the LLJ continually conveying water vapor to the area, the accumulative effect of an increase in water vapor content took place in the low-level atmosphere, which changed the temperature and humidity structure of the boundary layer. The liquid water content, coverage area, and thickness of fog changed drastically. • A large number of ocean and coastal observation data were used to analyze the causes of fog around Bohai Sea, which is the only inland sea in China. • The air parcel backward trajectory tracking by HYSPLIT model and water vapor sensitivity experiment based on WRF model have been done to illuminate the water vapor source and its influence to the fog case. • The sensitivity experiment shows that the reduction of the continual transport of water vapor altered the vertical structures of temperature and humidity in the low atmosphere, thus finally changed the liquid water content, coverage area, and thickness of fog. [ABSTRACT FROM AUTHOR]

Land abandonment is considered an effective strategy for ecological restoration on a global scale. However, few studies have focused on how environmental heterogeneity associated with the age of land abandonment affects the assembly and potential functions of the soil microbial community. In the present study, we investigated the community assembly of soil bacteria and fungi as well as the stability of soil networks and their potential functions in the chronosequence of abandoned apple orchards. We elucidated that the Shannon diversity of bacteria and the richness of fungi increased as land abandonment progressed. In addition, land abandonment destabilized the microbial network stability but increased network complexity. Soil available nitrogen, total carbon, and moisture are the potentially important factors in shaping the soil microbial assembly. Importantly, we showed that the microbial community diversity and functional diversity presented a synchronization effect in response to the different stages of land abandonment. Furthermore, specific bacterial taxa related to carbon fixation, dissimilatory nitrate reduction, and organic phosphorus mineralization were significantly enriched during the early abandonment stage. Collectively, these results indicate that land abandonment significantly transformed soil microbiome assembly and functional adaptation during the restoration process. These findings provide valuable insights into the influence of ecological restoration on soil microbiome and ecosystem functions in arable areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Objective: To explore the frequency and effect of extreme temperature on the non-accidental death rate in Hulunbuir, a Chinese ice city., Methods: From 2014 to 2018, mortality data of residents residing in Hulunbuir City were collected. The lag and cumulative effects of extreme temperature conditions on non-accidental death and respiratory and circulatory diseases were analyzed by distributed lag non-linear models (DLNM)., Results: The risk of death was the highest during high-temperature conditions, the RR value was 1.111 (95% CI 1.031 ~ 1.198). The effect was severe and acute. The risk of death during extreme low-temperature conditions peaked on the fifth day, (RR 1.057; 95% CI 1.012 ~ 1.112), then decreased and was maintained for 12 days. The cumulative RR value was 1.289 (95% CI 1.045 ~ 1.589). Heat significantly influenced the incidence of non-accidental death in both men (RR 1.187; 95% CI 1.059-1.331) and women (RR 1.252; 95% CI 1.085-1.445)., Conclusions: Regardless of the temperature effect, the risk of death in the elderly group (≥ 65 years) was significantly higher than that of the young group (0-64 years). High-temperature and low-temperature conditions can contribute to the increased number of deaths in Hulunbei. While high-temperature has an acute effect, low-temperature has a lagging effect. Elderly and women, as well as people with circulatory diseases, are more sensitive to extreme temperatures., (© 2023. The Author(s).)

Atmospheric trace metals are a key component of particulate matter and significantly influence the atmospheric process and human health. The dissolved fraction of trace metals represents their bioavailability and exhibits high chemical activity. However, the optimum measurement method for detecting the soluble fraction of trace metals is still undetermined. The impact of variations in pollution on the soluble fraction is largely unrevealed. Therefore, in this work, a one-month field observation was conducted in Central China and different extraction solvents were used to determine the proper measurement method for the soluble fraction of trace metals and investigate the variation pattern under different pollution conditions. The findings show that solvents with acidity near that of aerosol water can better reflect the actual soluble fraction of trace metals in fine particulate matter. The soluble fraction of trace metals tends to increase with pollution level increased, demonstrating unexpectedly high health risks and chemical activity under heavy haze conditions. Our results indicate that remediation and trace metal pollution control are urgently needed., Competing Interests: Declaration of competing interest Weigang Wang reports financial support was provided by National Natural Science Foundation of China. Maofa Ge reports financial support was provided by Beijing National Laboratory for Molecular Sciences., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Although many industrial heritage sites have been repurposed into attractive landscapes, the contamination and health risks from polycyclic aromatic hydrocarbons (PAHs) on industrial legacy surfaces remain unexplored. We collected 441wiping surface samples from 95 buildings and facilities at Beijing coking plant in China and found that the concentrations of 16 US EPA priority PAHs (∑ 16 PAHs) ranged from ND-982.16 and ND-4262.20 mg/m 2 on the surfaces of buildings and facilities, respectively. The main source of PAHs was the coking process, and spatial distribution of PAHs was consistent with ∑ 16 PAHs in the soil. The carcinogenic risks of BaP, DBA, BbF, BaA, Ind of the facilities remained as industrial heritage relics, and those of Bap, DBA and BbF in the buildings with commercial uses exceeded the acceptable level (10 -6 ). The hazard quotient of 9 PAHs was below the acceptable level (1.0). The remedial goals for BaP and DBA (0.11 mg/m 2 ) and BbF, BaA and Ind (1.14 mg/m 2 ) at the facility heritage relics were derived. Similarly, the RGs for the buildings with commercial uses of BaP, DBA and BbF were 0.16, 0.16, and 1.64 mg/m 2 , respectively. Overall, we determined that carcinogenic PAHs on the surfaces of industrial legacy should be regulated for regeneration., (Copyright © 2022 Elsevier B.V. All rights reserved.)

China issued the unified national soil screening levels (NSSLs) in 2018 to assist the regulation of contaminated sites, but the applicability of NSSLs was not thoroughly evaluated. Datasets from the National Qinghai-Tibet Plateau Scientific Data Center indicated great variability of soil organic matter (0.8-173 g/kg), soil water content (0.05-0.6), soil porosity (0.4-0.6), and soil bulk density (1.11-1.59 kg/m 3 ). We analyzed the effects of soil properties on the derivation of SSLs by using Monte Carlo simulations. The soil factors mainly affected the inhalation exposure pathway of volatile organic compounds (VOCs). They had an effect of more than two orders of magnitude on SSLs for most selected VOCs, particularly with the parameters 0.35 > Henry's law constant > 0.1 and carbon-water distribution coefficient of >100. We compared NSSLs with the recommended SSLs assuming fifth percentile by using Monte Carlo simulations. In general, NSSLs were not sufficient to identify contaminated sites that require additional investigation in the south, central, and northwest regions but were too conservative in screening sites out that required no further action in the east and northeast regions. Our framework and findings may contribute to more scientific and effective soil quality management in other large countries.

Background: A high tendency of intention to leave has been noted for nurses in China. The nursing profession is currently unstable., Methods: A sample of 51406 nurses from 311 hospitals in China who completed the self-administered questionnaire online was recruited via the China Nursing Association by email and phone using a simple random sampling method. The recruitment occurred between July 2016 and July 2017., Results: The majority of the nurses had working experience ≤20 years and had to work on night shifts. A high percentage of nurses (71.8%) had insomnia, followed by 37.0% who developed varicose veins and 40.9% who experienced musculoskeletal-related disorders. The proportions of the nurses who developed gastrointestinal and urinary system diseases were 56.0% and 18.2%, respectively. Nearly half of the nurses did not have a clear goal for their future career development and intended to leave. Nurses with long working hours each week were positively associated with the development of occupational diseases. The prevalence of occupational diseases was independently associated with career development., Conclusions: A high prevalence of occupational diseases was noted among nurses in China. The data indicated that 50% of the nurses were vague regarding their career planning. The data suggest that managers need to pay more attention and to prevent this problem. Appropriate interventions should also be provided.

Objective: To assess the occupational injuries and psychological support received by nurses and to investigate the relationship between the two., Method: This was a nation-wide cross-sectional study of nurses working across 1858 hospitals in China. Data were collected using an online structured, self-administered questionnaire between 2016 and 2017., Results: Nearly half of respondents had experienced aggressive behavior from patients or their attendants; 13.4% respondents had experienced aggressive behavior on more than three occasions. 78.96% respondents had experienced needle-stick injuries and 51.22% had experienced psychological trauma. 20.5% respondents believed that hospitals do not pay any attention to occupational safety. 86.1% respondents expressed the need for little or moderate psychological support. Nurses who had experienced aggressive behavior expressed a greater need for psychological support. Nurses working at hospitals that adequately addressed the occupational safety issues expressed the lowest need for psychological support., Conclusion: We found a high prevalence of psychological stress and occupational injuries among nurses. Nursing managers need to address this issue and implement interventions to prevent and reduce injuries.

What Is Known and Objective: Acarbose can efficiently block glucose absorption in the intestine as an alpha-glucosidase inhibitor. It is currently manufactured in several oral dosage forms, with the most common types being tablets and chewable tablets. The acarbose tablet (Glucobay ® , 50 mg, Bayer) package insert gives instructions for either directly swallowing or chewing then swallowing. This study compared the pharmacodynamic effects of a single formulation of acarbose tablets under these two different administration routes., Methods: This randomized, crossover study enrolled 24 healthy subjects who were instructed to chew (C group) or swallow (S group) the acarbose tablet. Glucose levels were monitored in subjects for up to 4 h following administration of 75 g of sucrose to establish a baseline firstly, after which subjects in the C and S groups were administered 50- or 100- mg of acarbose along with 75 g of sucrose. Then, subjects entered a 1-week washout period before being crossed over to the alternate dosing route., Results and Discussion: Compared with the S group, the C group had a lower maximum concentration of serum glucose (C max ) and areas under the concentration-time curve (AUC 0-2 , AUC 0-1.5 ). In addition, the maximum reduction in serum glucose (ΔC max ) and the reduction in the AUC (AUEC 0-1.5 ) were both increased in the S group. This occurred at both the 50 mg and 100 mg dosages. These results indicate that fluctuations in blood glucose were lower following chewing of the acarbose tablet. Both administration routes exhibited similar safety and tolerance profiles., What Is New and Conclusion: In summary, chewing acarbose tablets appears to induce a superior glycaemic-controlling effect compared with swallowing them directly, at least with a single dose. It will be important to inform both clinicians and patients about these differences between the two administrations so that informed clinical decisions can be made, as numerous patients with diabetes are inclined to directly swallow acarbose tablets for convenience., (© 2021 John Wiley & Sons Ltd.)

Abstract: Poststroke pneumonia (PSP) is a common complication of stroke and an important cause of death following stroke. However, the treatment of PSP remains inadequate due to severe impairment to the respiratory system by PSP. Thus, it is crucial to focus on preventing PSP to improve the prognosis of patients with stroke.This prospective single-center Cohort study aimed to investigate the risk factors for pulmonary infection following an ischemic stroke and identify whether PSP significantly influences the prognosis of patients after stroke.Altogether, 451 patients who were treated for acute ischemic stroke in the First Affiliated Hospital of Chongqing Medical University in China between April 2017 and April 2018 were enrolled. Clinical data from the patients from admission to 3 months after discharge were collected. PSP was the primary outcome and poor prognosis or death at 3 months following discharge was the secondary outcome observed in this study. We performed logistic regression analyses to identify the risk factors for PSP and test an association between pneumonia and poor prognosis or death after stroke.Our findings revealed the following risk factors for PSP: atrial fibrillation odds ratio (OR) = 2.884, 95% confidence intervals (CI) = 1.316-6.322), being bedridden (OR = 2.797, 95%CI = 1.322-5.921), subject to an invasive procedure (OR = 12.838, 95%CI = 6.296-26.178), massive cerebral infarction (OR = 3.994, 95%CI = 1.496-10.666), and dysphagia (OR = 2.441, 95%CI = 1.114-5.351). Pneumonia was a risk factor for poor prognosis (OR = 2.967, 95%CI = 1.273-6.915) and death (OR = 5.493, 95%CI = 1.825-16.53) after stroke.Hence, since pneumonia increases the risk of poor prognosis and death following acute ischemic stroke, preventing, and managing the risk factors for PSP may improve the prognosis and reduce the mortality after stroke., Competing Interests: The authors have no funding and conflicts of interests to disclose., (Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc.)

The non-stationarity, nonlinearity and complexity of the PM 2.5 series have caused difficulties in PM 2.5 prediction. To improve prediction accuracy, many forecasting methods have been developed. However, these methods usually do not consider the importance of data preprocessing and have limitations only using a single forecasting model. Therefore, this paper proposed a new hybrid decomposition-ensemble learning paradigm based on variation mode decomposition (VMD) and improved whale-optimization algorithm (IWOA) to address complex nonlinear environmental data. First, the VMD is employed to decompose the PM 2.5 sequences into a set of variational modes (VMs) with different frequencies. Then, an ensemble method based on four individual forecasting approaches is applied to forecast all the VMs. With regard to ensemble weight coefficients, the IWOA is applied to optimize the weight coefficients, and the final forecasting results were obtained by reconstructing the refined sequences. To verify and validate the proposed learning paradigm, four daily PM 2.5 datasets collected from the Jing-Jin-Ji area of China are chosen as the test cases to conduct the empirical research. The experimental results indicated that the proposed learning paradigm has the best results in all cases and metrics., Competing Interests: The authors declare no conflict of interest.

Background: COVID-19 first appeared in China in December 2019, with a high rate of infectivity and morbidity, which brought tremendous psychological pressure to healthcare workers., Purpose: To understand the psychological health status of healthcare workers during the COVID-19 outbreak and decline, and to provide a theoretical reference for the future establishment of a psychological crisis intervention system., Methods: Healthcare workers were recruited using convenience sampling and snowball sampling methods, and the electronic version of the SCL-90 scale and a sociodemographic questionnaire were administered. In the pretest, a total of 5018 responses were collected; after six weeks, random sampling was performed. The SCL-90 and measures of other epidemic-related problems were administered, with 1570 responses received; then, the final data analysis was performed., Results: After six weeks, the post-test GSI score; SCL-90 total score; and PST, PSDI, O-C, I-S, DEP, ANX, PHOB, PAR, PSY, and HOS scores were significantly lower than the corresponding pretest scores (p < 0.05). The results by occupational category showed that the scores of nursing staff decreased significantly for 12 indexes and that the scores of the doctors and other hospital staff also significantly decreased. There was a significant difference between the pretest (50.78 ± 28.18) and post-test (45.00 ± 28.49) scores for the degree of worry about the epidemic. Healthcare workers believed that the top three aspects of life affected by the epidemic were economic problems (816 people), interpersonal communication problems (731 people), and mental health (728 people)., Conclusion: Over the course of the epidemic, the item scores generally declined significantly. Therefore, during an outbreak period, attention should be paid to psychological crisis interventions for healthcare workers; problems caused by psychological pressure, and even other psychological conditions, can be significantly alleviated to reduce the probability of subsequent health problems., Competing Interests: The authors have no competing interests to declare., (Copyright: © 2020 The Author(s).)

Due to the complexity of Crohn's disease (CD), it is difficult to predict disease course with a single stratification factor or biomarker. A logistic regression (LR) model has been proposed by Guizzetti et al to stratify patients with CD-related surgical risk, which could help decision-making on disease treatment. However, there are no reports on relevant studies on Chinese population. The aim of the study is to present and validate a novel surgical predictive model to facilitate therapeutic decision-making for Chinese CD patients. Data was extracted from retrospective full-mode electronic medical records, which contained 239 CD patients and 1524 instances. Two sub-datasets were generated according to different attribute selection strategies, both of which were split into training and testing sets randomly. The imbalanced data in the training sets was addressed by synthetic minority over-sampling technique (SMOTE) algorithm before model development. Seven predictive models were employed using 5 popular machine learning algorithms: random forest (RF), LR, support vector machine (SVM), decision tree (DT) and artificial neural networks (ANN). The performance of each model was evaluated by accuracy, precision, F1-score, true negative (TN) rate, and the area under the receiver operating characteristic curve (AuROC). The result revealed that RF outperformed all other baseline models on both sub-datasets. The 10 leading risk factors for CD-related surgery returned from RF for attribute ranking were changes of radiology, presence of a fistula, presence of an abscess, no infliximab use, enteroscopy findings, C-reactive protein, abdominal pain, white blood cells, erythrocyte sedimentation rate and platelet count. The proposed machine learning model can accurately predict the risk of surgical intervention in Chinese CD patients, which could be used to tailor and modify the treatment strategies for CD patients in clinical practice.

As E-government continues to develop with ever-increasing speed, the requirement to enhance traditional government systems and affairs with electronic methods that are more effective and efficient is becoming critical. As a new product of information technology, E-tendering is becoming an inevitable reality owing to its efficiency, fairness, transparency, and accountability. Thus, developing and promoting government E-tendering (GeT) is imperative. This paper presents a hybrid approach combining genetic algorithm (GA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to enable GeT to search for the optimal tenderer efficiently and fairly under circumstances where the attributes of the tenderers are expressed as fuzzy number intuitionistic fuzzy sets (FNIFSs). GA is applied to obtain the optimal weights of evaluation criteria of tenderers automatically. TOPSIS is employed to search for the optimal tenderer. A prototype system is built and validated with an illustrative example from GeT to verify the feasibility and availability of the proposed approach.