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Rural revitalization strategies are an important task in China. Currently, it is in the transition from poverty alleviation to rural revitalization. This paper proposes an evaluation index of rural revitalization and development potential based on a summary of previous studies. Together with the TOPSIS method, the corresponding coefficients of each index layer and the weight coefficient of the criterion layer were analyzed. This shows that during the process, the work direction of rural revitalization varies based on different revitalization types. In this study, diagnostic tools are utilized to conduct a potential development analysis of rural human settlements by identifying the main influencing factors for rural revitalization. In addition, an index system for improving rural human settlement strategies is established. Overall, it helps in defining the interventions of reducing and managing the risk of rural vitalization and evaluating the potential ability of rural revitalization. It also suggests that Anhui Province should focus on carrying out the comprehensive revitalization of rural areas according to the different functional positions of the countryside. [ABSTRACT FROM AUTHOR]

Water system management is a worldwide challenge, especially in arid and semi-arid regions. Ecological water conveyance projects aim to raise the groundwater table, thereby saving natural vegetation and curbing ecological deterioration. Since 2000, these projects have been implemented in the arid zone of northwest China, with generally successful outcomes. Taking a portion of the lower reaches of the Tarim River as the study area, this paper analyzes in detail the ecohydrological effects which have occurred since the launching of artificial water conveyance 20 years ago. The results show that the groundwater table in the upper, middle and lower segments of the Tarim River's lower reaches has been raised on average 4.06, 4.83 and 5.13 m, respectively, while the area of surface water bodies connected to those sections has expanded from 49.00 km2 to 498.54 km2. At the same time, Taitema Lake, which is the terminal lake of the Tarim River, has been revived and now boasts a water area of 455.27 km2. Other findings indicate that the surface ecological response is extremely sensitive and that the area of natural vegetation has expanded to 1423 km2. Furthermore, the vegetation coverage, vegetation index (NDVI), and Net Primary Productivity (NPP) have increased by 132 km2, 0.07 and 7.6 g C m−2, respectively, and the Simpson dominance, McIntosh evenness, and Margalef richness indices have risen by 0.33, 0.35 and 0.49, respectively, in the monitored sample sites. As well, the carbon sink area has expanded from 1.54% to 7.8%. Given the increasing intensity of the occurrence of extreme hydrological events and successive dry years, similar ecological water conveyance projects should be considered elsewhere in China and in other parts of the world. The water conveyance scheme has generally proven successful and should be optimized to enhance the benefits of ecological water conveyance under water resource constraints. [ABSTRACT FROM AUTHOR]

Based on an analysis of the formation mechanism, stability state and development trend, this paper focuses on monitoring key indicators, such as surface deformation and rainfall, to realize the early warning of landslides and provide some guidance for landslide disaster prevention and avoidance in the alpine mountainous area of Nangqian, Qinghai Province. The landslide of the Baima Elin Monastery has the topographic and geomorphological conditions of landslide formation and has the basic characteristics indicating that it can be influenced by rainfall and climate, so a landslide warning should be comprehensive. At the same time, the landslide is currently in an unstable state, and the seasonal freeze–thaw cycle will cause it to become more unstable. Based on macroscopic signs, it is predicted that the deformation of the Baima Elin Monastery landslide will continue to intensify without abatement, the stability will be further reduced after winter, developing in an unfavorable direction, and engineering measures should be taken as soon as possible to manage the landslide. [ABSTRACT FROM AUTHOR]

It is of much importance to clarify the impact of technological innovation on carbon emission intensity for the low-carbon transformation of China's economy. This study, based on the panel data of 30 Chinese provinces and municipalities from 2010 to 2020, measures and analyzes the carbon emission intensity and the level of technological innovation, establishing a spatial econometric model to study the spatial spillover effect and a panel threshold model to analyze the nonlinear influence of technological innovation level on carbon emission intensity. The findings are as follows: First, the overall carbon emission intensity in China shows a decreasing trend from 2010 to 2020, with the average dropping from 3.09 in 2010 to 1.98 in 2020; Second, the spatial autocorrelation results reveal that the level of technological innovation and carbon emission intensity in China are obviously aggregated in the global spatial distribution pattern. Third, the regression results of the spatial econometric model show that the direct effect of technological innovation on carbon emission intensity is significantly negative at the level of 1%, that is, the improvement of the technological innovation in a certain area has a significant inhibitory effect on carbon emission intensity. Fourth, based on the level of economic development, there is a significant three-threshold effect of the level of technological innovation on carbon emission intensity in China, and the influence of the level of technological innovation on carbon emission intensity varies in the direction of existence and coefficient values within different threshold intervals. As economic development reaches the third interval, the technological innovation level has the most significant inhibition on carbon emission intensity. These findings enriches the research of the nonlinear relationship between technological innovation and carbon emission intensity, clarifies the spatial spillover effect and threshold effect between among them, and provides inspiration for better promote the low-carbon transformation of economy. [ABSTRACT FROM AUTHOR]

Smart city construction represents an advanced stage of China's urbanisation process and plays an important role in promoting green economic growth and sustainable development. Propensity score matching is combined with the difference-in-difference method to analyse the data of 221 prefecture-level cities in China from 2006 to 2020 to assess the impact of smart city construction on urban green development. We found that smart city construction can significantly contribute to urban green development; this contribution has long-term benefits. Further analysis shows that smart city construction promotes urban green development via industrial structure and green technology innovation and that smart city construction has a significant positive spatial spillover effect, i.e., it promotes urban green development locally while significantly contributing to urban green development in neighbouring regions. [ABSTRACT FROM AUTHOR]

To better implement the Strategy of Rural Revitalization, it is essential to characterize the rural settlements and understand their roles in the socio-environmental interactive system. This paper is hence aimed at achieving such a study using different spatial analysis such as kernel density and spatial autocorrelation (SA) and modeling approaches, e.g., simple and multiple linear regression analyses taking Jiangxi, a province in China as an example. Remote sensing, topographic and socioeconomic data were employed for this purpose. Through these analyses, it is found that the rural settlements in the study area appear to have a spatial distribution pattern of "dense north and sparse south" as an "F" type, and are quantitatively characterized as low elevations, flat terrain, high river and road densities, rich cultivated land resources and susceptible to the impact of urban radiation with a R2 of 0.520–0.748. Based on this understanding, a new inequality evaluation indicator of rural development, i.e., socio-environmental evaluation index (SEI), was developed. Areas with SEI lower than 0.40 should be given a priority to implement the revitalization strategy in the province. This index can also be extended to study of the imbalance of rural development in other regions and countries. [ABSTRACT FROM AUTHOR]

Arid area is very sensitive to global warming and are extremely vulnerable to climate change. Moreover, the water resources system in the arid area is fragile and will undergo tremendous changes with climate change. Therefore, the interaction of climate and hydrology in arid area has an important impact on the formation of regional microclimate and hydrological changes. Daihai Lake is a typical closed inland lake in arid area of China, and a key area for ecological protection in North China. In this paper, WRF-Hydro model is used to simulate the climate hydrological coupling situation of Daihai Basin from 1980 to 2020, and the coupling results are verified and calibrated by meteorological statistics, runoff calculation and remote sensing analysis. Based on the synopsis of climate and hydrology in the past 40 years, the causes and future trends of the hydrological elements in Daihai Basin are analyzed. Through the analysis, it is found that the interannual variation of precipitation in Daihai Basin is sharp, with 401.75 mm as the average from 1980 to 1994; and drastic fluctuations from 1995 to 2011, with a difference of nearly 400 mm between the interannual maximum and minimum; From 2012 to 2020, the fluctuation is small. Although the interannual variation of evaporation fluctuated, it showed an upward trend with a slope of 8.855 mm/year. The annual average temperature showed an obvious upward trend with a slope of 0.040 °C/year. From 1980 to 2020, the inflow of Daihai Lake shows a downward trend; Since 2013, the runoff into the lake has tended to be flat. Climate change and human activities are the decisive factors leading to the change of water quantity in Daihai, among which human activities play a greater role. Cultivated land irrigation and industrial water use are highly correlated with the lake discharge, and these two factors have a great influence on the lake discharge. If the current agricultural and industrial water consumption does not increase, Daihai still has a lifespan of nearly 120 years. If human activities do not change and any protective measures are not taken in time, under the background of global climate change, the flow of the Daihai Lake into the lake will be reduced to zero in 2025, and the Daihai Lake will completely dry up in 2031–2033. The study of climate hydrological coupling of long time series in Daihai Basin can not only make up for the lack of runoff data, but also provide the basis for water resources management, disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study to assess the behaviour of coal samples under tensile loadings to better understand the failure mechanisms and the interactions with the coal characteristics. A set of Brazilian splitting tests were carried out using disk specimens obtained from Tashan Coal Mine in China. The digital speckle correlation method and acoustic emission (AE) were used to capture the deformation localisation and AE characteristics of each specimen during the loading process. The precursor characteristics of AE and the failure mechanism are discussed. It was found that the entire loading process mainly consists of compaction, elastic and post-peak dropping stage without an obvious yielding stage. Two kinds of deformation localisation were observed: central symmetry and axis symmetry. The corresponding AE evolution patterns have different phases, including gradual rise, step rise, transient rise and steady rise. During the subcritical failure stage, AE counts demonstrate a "rapidly increasing + flatten" intermittent feature. The results provide a reference for a better understanding of the damage process of the brittle coal material and its application in ground control design. [ABSTRACT FROM AUTHOR]

At present, more patients suffer from multiple chronic diseases. However, the hospital's existing chronic disease management is carried out according to the department. This means that a patient needs to go to more than one department for a chronic disease treatment. Therefore, this study proposes 6 dimensions (organizational management, medical service support, medical service, community alliance, self-management support, management information system) and 36 questions, to help evaluate the current chronic disease management system in China's large third-class hospitals. In this study, 143 survey samples from doctors and nurses were collected. A principal component analysis was used to extract three key elements of chronic disease management service delivery system (service management organization, management information system, medical core service). Then, multiple regression was used to establish the relationship model between the overall performance of the system and the main elements. Three key service nodes of the system (medical specialist support, patient tracking management and personalized intervention) were determined according to the weight of the regression model. The regression coefficients of the above three main elements show a similar impact on the overall performance of the system, but the key service nodes under each major element have relative differences, including medical specialist support, patient tracking management and personalized intervention. Finally, to establish a chronic disease management system with multiple departmental continuous care for chronic diseases, it is necessary to improve the chronic disease management system from three aspects of medical specialty support, patient tracking management and personalized intervention. This paper proposes corresponding improvement strategies. [ABSTRACT FROM AUTHOR]

The development of industry has brought about the pollution of the atmospheric environment. Pollution is harmful to people's health. Realizing the real-time monitoring of atmospheric environmental quality parameters can improve the above-mentioned effects. China's existing environmental monitoring systems focus on the accuracy of the system hardware itself for assessment, lack of data analysis and forecasting and early warning, and cannot provide managers and ordinary people with decision-making and activity guidance. This paper develops an IPV6-based high-spatial–temporal precision air pollutant monitoring and early warning platform. The feasibility of the system is verified through networking tests, operation tests, and early warning tests. Through actual data analysis and comparison, it is concluded that the monitoring system has field feasibility, and the atmospheric environment monitoring for the target observation area has achieved the desired observation function. This system integrates GIS technology and B/S architecture to analyze changes in the regional environment to provide support for regional environmental air quality management. The forecast and early warning module constructed by combining the weight method of the influence of different input factors on the environmental quality index and minute-level observations can provide technical support for the government to improve the level of supervision. [ABSTRACT FROM AUTHOR]

Titanium alloy has become a promising candidate material for oil country tubular goods (OCTGs) in harsh service environments owing to its high specific strength, low density, low elastic modulus, excellent toughness, excellent anti-fatigue and corrosion resistance. However, because the high-quality natural gas resources in China are mainly concentrated deep underground, titanium alloy tubing and casing will bear great external pressure loads underground, so the collapse strength of titanium alloy tubing and casing is very important for the safety of the string in the well. In this paper, a new collapse strength calculation model, the strength collapse criterion model (SCM), was proposed for titanium alloy tubing and casing. 35 different specifications of titanium alloy tubing and casing were selected for the full-scale collapse tests to verify the reliability of the established SCM model. Furthermore, the effect of different key parameters (such as strength, ovality, eccentricity and residual stress) on collapse strength of titanium alloy pipes were investigated systematically and compared with the same specifications of steel pipes. The strength collapse criterion model and analysis results can provide a technical reference for the design and use of titanium alloy OCTGs in the petroleum and natural gas industries. [ABSTRACT FROM AUTHOR]

China suffers from frequent large-scale earthquakes, posing a significant challenge to the development and integrity of its rural water supply system (RWSS). The earthquake resilience of water supply systems is understood to be a function of multifaceted factors, which are time- and space-dependent. Measuring the seismic-resilience of RWSS in China remains a challenge. This paper proposes a multi-stage comprehensive evaluation framework, focusing on the relationship between multi-dimensional factors and the seismic- resilience of RWSS in rural areas, across three stages: before, during and after earthquake events. This study comprises four steps: (1) Development of a multi-stage evaluation conceptual framework; (2) identification of seismic-resilience factors; (3) verification of the relationships between factors and stages; and (4) formation of the final evaluation framework. The relationship between multi-dimensional factors is confirmed by a method of triangulation through the quantitative analysis of PLS-SEM combined with the qualitative literature analysis, highlighting the causal approach of the resilience of RWSSs, so as to better understand the resilience state of each stage of disaster. Understanding these factors and their influence on the seismic capacity of RWSS will enable local authorities to recognize the existing advantages and disadvantages of these factors, so as to carry out better resilience practice in all stages of disasters. [ABSTRACT FROM AUTHOR]

Dithionite-citrate-bicarbonate (DCB) treatment is a classical method for removing iron oxides from soil. The DCB-induced dissolution effects on iron oxides are controversial. In this paper, samples from a typical loess-paleosol sequence in the Chinese Loess Plateau (CLP) and from other aeolian dust deposits in southern China were collected, and changes in the grain size composition and magnetic properties of the samples after DCB treatment were analyzed. The results show that the dissolution of iron oxides in loess-paleosol samples from the CLP is highly grain size dependent. In addition to completely dissolving nanometer-sized pedogenic iron oxides (< 0.2 μm), the standard DCB procedure can also dissolve submicron- and micron-sized aeolian iron oxides (0.2–6 μm). For these aeolian iron oxides, the submicron-sized (0.2–1 μm) iron oxides are sufficiently dissolved, and the solubility of the micron-sized (1–6 μm) iron oxides decreases with increasing particle size. The dissolution of > 6 μm aeolian iron oxides is negligible. DCB can neither separate pedogenic iron oxides from aeolian iron oxides nor selectively dissolve magnetite or maghemite. Although the total amount of dissolved iron oxides in the profiles from southern China is higher than that in the LC profile from northern China, the submicron- and micron-sized aeolian iron oxides in the latter are more easily dissolved. [ABSTRACT FROM AUTHOR]

As the demand for health grows, the increase in medical waste generation is gradually outstripping the load. In this paper, we propose a deep learning approach for identification and classification of medical waste. Deep learning is currently the most popular technique in image classification, but its need for large amounts of data limits its usage. In this scenario, we propose a deep learning-based classification method, in which ResNeXt is a suitable deep neural network for practical implementation, followed by transfer learning methods to improve classification results. We pay special attention to the problem of medical waste classification, which needs to be solved urgently in the current environmental protection context. We applied the technique to 3480 images and succeeded in correctly identifying 8 kinds of medical waste with an accuracy of 97.2%; the average F1-score of five-fold cross-validation was 97.2%. This study provided a deep learning-based method for automatic detection and classification of 8 kinds of medical waste with high accuracy and average precision. We believe that the power of artificial intelligence could be harnessed in products that would facilitate medical waste classification and could become widely available throughout China. [ABSTRACT FROM AUTHOR]

Soil microbial community were usually reconsidered as a sensitive indicator in soil quality and soil environment change of paddy field. However, the effects of different tillage and crop residue incorporation managements on soil bacterial community under the double-cropping rice cropping system were still need to further investigated. Therefore, the impacts of different tillage and crop residue incorporation managements on soil bacterial community under the double-cropping rice cropping system in southern of China were studied by using phospholipid fatty acids (PLFAs) profile method in the present paper. The experiment included four different tillage treatments: rotary tillage without crop residue input as a control (RTO), no-tillage with crop residue retention (NT), rotary tillage with crop residue incorporation (RT), and conventional tillage with crop residue incorporation (CT). Compared with RTO treatment, grain yield of rice with NT, RT and CT treatments increased by 1.21%, 3.13% and 6.40%, respectively. This results showed that soil aC15:0, C16:0, iC17:0, C19:0c9, 10 fatty acids with CT and RT treatments were higher than that of RTO treatment, while soil C16:1ω6c and C18:1ω9t fatty acids with NT treatment were higher than that of RTO treatment, respectively. Soil G+ and G− bacteria PLFAs contents with CT treatment were higher than that of NT, RT and RTO treatments, while the value of soil G+/G− bacteria PLFAs with NT treatment were higher than that of CT, RT and RTO treatments. This results indicated that Richness and McIntosh indices with CT treatment were significantly higher than that of RTO treatment. Principal component analysis (PCA) results showed that the first and second principal components (PC1 and PC2) were explained 93.2% of total variance with all tillage treatments. Except C12:0, C14:0 2OH and C18:2ω6, all unsaturated and cyclopropyl PLFAs contents were belong to PC1. PC1 and PC2 were explained 88.4% of total variance with all tillage treatments. There had significantly positive correlation between soil Richness, Shannon indices and soil PLFAs, G+ bacteria, G− bacteria, fungi contents. As a result, it were benefit practices for increasing soil bacterial community structure in the double-cropping rice field of southern China by combined application of rotary, conventional tillage with crop residue incorporation managements. [ABSTRACT FROM AUTHOR]

Deep coal seam mining often leads to water resource loss due to bedrock water entering the workings of the mine and is discharged adjacent to the mining area. Using the geological conditions of the Maiduoshan coal mine, this paper applied a physical simulation experiment. The specified rock above the coal seam was hydraulically fractured in advance to form a postmining grouted fracture network, followed by grouting to construct a flexible isolation layer that blocked the infiltration of groundwater from the aquifer into the water-conducting fracture zone. Stress sensors, flow sensors and strata displacement monitoring technology were deployed inside the experimental material to study the spatial distribution characteristics and evolution law of the water-conducting fracture zone in the overlying rocks. Analysis of the water-conducting fracture zone development law, stress variation, overburden evolution characteristics, fracturing and grouting sequence of the flexible isolation layer and the effect of postmining grouting on the water barrier was conducted. These experiments verified the feasibility of fracture and grouting of the flexible isolation layer. These research results will provide practical guidance for the transition from the current safe and efficient mining methods to safe and green mining methods of deep coal mining in the western mining areas of China. [ABSTRACT FROM AUTHOR]

Isatis indigotica planting is the backbone of the medicinal industry in Hexi Oasis, Gansu. In order to solve the problems insufficient water resources and excessive application of nitrogen fertilizer in this area, this paper explored the irrigation and nitrogen levels that can meet the multiple goals of Isatis indigotica. The two-factor split-plot field experiment (2018‒2019) was conducted in Minle County, Gansu Province, China, which contains 9 treatments. There were three levels of irrigation water: W1(low), W2(medium), and W3(high). The soil moisture contents were 60–70%, 70–80%, and 80–90% of the field water-holding capacity, respectively. The nitrogen application rate was classified into three levels, N1(low), N2(medium) and N3(high), which were 150, 200 and 250 kg N/ha, respectively. The standard local irrigation water amount and nitrogen application rate corresponded to W3N3. The results showed that the yield of Isatis indigotica increased first and then decreased with the increase of irrigation amount and nitrogen application rate, the yield of W2N2 is 12.2–17.1% higher than that of W1N1, the yield of W3N3 was 12.1–17.5% lower than that of W2N2. Saving water and reducing nitrogen can improve the quality of Isatis indigotica, compared with W3N3, the indigo, indirubin, (R,S)-epigoitrin and polysaccharides of W2N2 increased by 4.5–5.9%, 2.7–3.1%, 5.2–6.0%, and 1.8–2.1%, respectively. With the increase of nitrogen application rate, the water use efficiency (WUE) first increased and then decreased, as the irrigation volume increases, WUE decreases. Compared with W3N3, the WUE of W2N2 increased by 24.3–27.2%. With the increase of water input, the nitrogen fertilizer use efficiency (NUE) first increased and then decreased, as the nitrogen application rate increases, NUE decreases. Compared with W3N3, the NUE of W2W2 increased by 31.8–34.5%. Therefore, W2N2 can improve quality and increase water and nitrogen utilization efficiency on the basis of ensuring yield. [ABSTRACT FROM AUTHOR]

Loess presents very unique collapsible behaviour due to its special under-compactness, weak cementation and porousness. Many environmental issues and geological hazards including subgrade subsidences, slope collapses or failures, building cracking and so on are directly caused by the collapsible deformation of loess. Such collapsible behaviour may also severe accidents due to sinkholes, underground caves or loess gullies. Moreover, with the increasing demand of construction and development in the loess areas, an in-depth research towards effective evaluation of loess collapsibility is urged. Currently no studies have made attempts to explore a rather complete and representative area of Loess Plateau. This paper thus provides a novel approach on spatial modelling over Jin-Shan Loess Plateau as an extension to experimental studies. The in-lab experiment results have shown that shown that the porosity ratio and collapsibility follow a Gaussian distribution and a Gamma distribution respectively for both sampling areas: Yan'an and Lv Liang. This establishes the prior intuition towards spatial modelling which provides insights of potential influential factors on loess collapsibility and further sets a potential direction of the loess studies by considering an extra dimension of spatial correlation. Such modelling allows robust predictions taken into account of longitudinal information as well as structural parameters and basic physical properties. Water contents, dry densities, pressure levels and elevations of samples are determined to be statistically significant factors which affect the loess collapsibility. All regions in Lv Liang area are at risk of high collapsibility with average around 0.03, out of which roughly a third of them are predicted to be at high risk. Clear spatial patterns of higher expected collapsibility in the southwest comparing to the northeast are shown adjusting for influential covariates. On reference guidelines for potential policy makings, county-level regions with the highest expected loess collapsibility are also identified. [ABSTRACT FROM AUTHOR]

In this paper, a generalized partially functional linear regression model is proposed and the asymptotic property of the proposed estimated coefficients in the model is established. Extensive simulation experiment results are consistent with the theoretical result. Finally, two application examples of the model are given. One is sleep quality study where we studied the effects of heart rate, percentage of sleep time on total sleep in bed, wake after sleep onset and number of wakening during the night on sleep quality in 22 healthy people. The other one is mortality rate where we studied the effects of air quality index, temperature, relative humidity, GDP per capita and the number of beds per thousand people on the mortality rate across 80 major cities in China. [ABSTRACT FROM AUTHOR]

To scientifically and reasonably evaluate air quality with a large amount of monitored data, this paper proposes a new evaluation method called ideal grey close function cluster correlation analysis (IGCFCCA). Taking the air quality in Ningxia Province, China, as an example, according to China's air quality standard, SO2, NO2, PM10, PM2.5 and O3 are selected as evaluation indexes to perform the evaluation. The results show that the air quality in this region in 2018 can be divided into three classifications, among which the relatively poor air quality in March, April and May is the first classification, the better air quality in August and September is the third classification, and the air quality in other months falls under the second classification. Correlation analysis is used to qualitatively determine that these three classifications correspond to first-level air quality in China's air quality standard, and the correlation degree, which is the distance between the three classifications and the first-level air quality, is quantitatively determined. Specifically, the correlation degrees of the first-classification, second-classification and third-classification of air quality are 0.674, 0.697 and 0.71, respectively. The research results indicate potential directions and objectives for air quality management to achieve scientific management. [ABSTRACT FROM AUTHOR]

It is of great significance to carefully evaluate the actual impact of macro-policy formulation on promoting micro-enterprise innovation and implementing innovation-driven strategies. This study utilizes data from Chinese listed companies between 2012 and 2019 and takes the implementation of urban agglomeration policies as a natural experiment. By employing the multi-period differential method, the driving mechanism of urban agglomeration policies on enterprise innovation is investigated. The results show that: (1) Urban agglomeration policies effectively promote the enhancement of regional enterprises' innovation capability. (2) Urban agglomeration policies reduce enterprise transaction costs through integration effects, mitigate the influence of geographical distance through spillover effects, and stimulate enterprise innovation. (3) Urban agglomeration policies have a regulatory effect on the siphon and spillover mechanism formed by the central city, thereby driving the innovation and development of peripheral micro-enterprises. (4) Further research from the perspectives of enterprises, industries, and locations reveals that the macro, medium, and micro effects of urban agglomeration policies differ, leading to heterogeneity in enterprise innovation responses. Therefore, it is necessary to continue promoting policy planning for urban agglomerations, enhance the coordination of urban policies within urban agglomerations, adjust the influence of the self-mechanism of urban agglomerations, and foster the formation of a multi-center innovation structure and network within urban agglomerations. [ABSTRACT FROM AUTHOR]

China's Green Space System Planning (GSSP) research has gradually expanded from central urban areas to municipal and provincial scales in recent years. Besides, the research on the role of green space in the water environment has also attracted much attention. However, the study of green corridors usually ignored hydrological data, which widespread absence especially in the large area scale. And the scale of green corridor construction mainly focused on central urban areas. This paper took China's Fujian province as an example. Based on the DEM elevation data, the article identified blue corridors without hydrological data. In addition, the green corridors were determined based on the land use data. According to the green corridors and blue corridors protection, we identified the ecological networks and nodes by the network analysis method. The results showed that the blue corridors identified by DEM data were consistent with the hydrological status quo. The regional status of the identified ecological networks and nodes were basically in line with their characteristics, proving the value of the planning methods. Finally, based on the identification results, suggestions for Fujian's ecological networks and nodes are put forward. [ABSTRACT FROM AUTHOR]

Coping with the outbreak of Coronavirus disease 2019 (COVID-19), many countries have implemented public-health measures and movement restrictions to prevent the spread of the virus. However, the strict mobility control also brought about production stagnation and market disruption, resulting in a severe worldwide economic crisis. Quantifying the economic stagnation and predicting post-pandemic recovery are imperative issues. Besides, it is significant to examine how the impact of COVID-19 on economic activities varied with industries. As a reflection of enterprises' production output, high-frequency electricity-consumption data is an intuitive and effective tool for evaluating the economic impact of COVID-19 on different industries. In this paper, we quantify and compare economic impacts on the electricity consumption of different industries in eastern China. In order to address this problem, we conduct causal analysis using a difference-in-difference (DID) estimation model to analyze the effects of multi-phase public-health measures. Our model employs the electricity-consumption data ranging from 2019 to 2020 of 96 counties in the Eastern China region, which covers three main economic sectors and their 53 sub-sectors. The results indicate that electricity demand of all industries (other than information transfer industry) rebounded after the initial shock, and is back to pre-pandemic trends after easing the control measures at the end of May 2020. Emergency response, the combination of all countermeasures to COVID-19 in a certain period, affected all industries, and the higher level of emergency response with stricter movement control resulted in a greater decrease in electricity consumption and production. The pandemic outbreak has a negative-lag effect on industries, and there is greater resilience in industries that are less dependent on human mobility for economic production and activities. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Terrestrial vegetation growth activity plays pivotal roles on regional development, which has attracted wide attention especially in water resources shortage areas. The paper investigated the spatiotemporal change characteristics of vegetation growth activity using satellite-based Vegetation Health Indices (VHIs) including smoothed Normalized Difference Vegetation Index (SMN), smoothed Brightness Temperature (SMT), Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and VHI, based on 7-day composite temporal resolution and 16 km spatial resolution gridded data, and also estimated the drought conditions for the period of 1982–2016 in Jing-Jin-Ji region of China. The Niño 3.4 was used as a substitution of El Niño Southern Oscillation (ENSO) to reveal vegetation sensitivity to ENSO using correlation and wavelet analysis. Results indicated that monthly SMN has increased throughout the year especially during growing season, starts at approximate April and ends at about October. The correlation analysis between SMN and SMT, SMN and precipitation indicated that the vegetation growth was affected by joint effects of temperature and precipitation. The VCI during growing season was positive trends dominated and vice versa for TCI. The relationships between VHIs and drought make it possible to identify and quantify drought intensity, duration and affected area using different ranges of VHIs. Generally, the intensity and affected area of drought had mainly decreased, but the trends varied for different drought intensities, regions and time periods. Large-scale global climate anomalies such as Niño 3.4 exerted obvious impacts on the VHIs. The Niño 3.4 was mainly negatively correlated to VCI and positively correlated to TCI, and the spatial distributions of areas with positive (negative) correlation coefficients were mainly opposite. The linear relationships between Niño 3.4 and VHIs were in accordance with results of nonlinear relationships revealed using wavelet analysis. The results are of great importance to assess the vegetation growth activity, to monitor and quantify drought using satellite-based VHIs in Jing-Jin-Ji region. [ABSTRACT FROM AUTHOR]

This paper develops a new grey prediction model with quadratic polynomial term. Analytical expressions of the time response function and the restored values of the new model are derived by using grey model technique and mathematical tools. With observations of the confirmed cases, the death cases and the recovered cases from COVID-19 in China at the early stage, the proposed forecasting model is developed. The computational results demonstrate that the new model has higher precision than the other existing prediction models, which show the grey model has high accuracy in the forecasting of COVID-19. [ABSTRACT FROM AUTHOR]

Due to the COVID-19 pandemic originating in China in December 2019, apart from the grave concerns on the exponentially increasing casualties, the affected countries are called to deal with severe repercussions in all aspects of everyday life, from economic recession to national and international movement restrictions. Several regions managed to handle the pandemic more successfully than others in terms of life loss, while ongoing heated debates as to the right course of action for battling COVID-19 have divided the academic community as well as public opinion. To this direction, in this paper, an autoregressive COVID-19 prediction model with heterogeneous explanatory variables for Greece is proposed, taking past COVID-19 data, non-pharmaceutical interventions (NPIs), and Google query data as independent variables, from the day of the first confirmed case—February 26th—to the day before the announcement for the quarantine measures' softening—April 24th. The analysis indicates that the early measures taken by the Greek officials positively affected the flattening of the epidemic curve, with Greece having recorded significantly decreased COVID-19 casualties per million population and managing to stay on the low side of the deaths over cases spectrum. In specific, the prediction model identifies the 7-day lag that is needed in order for the measures' results to actually show, i.e., the optimal time-intervention framework for managing the disease's spread, while our analysis also indicates an appropriate point during the disease spread where restrictive measures should be applied. Present results have significant implications for effective policy making and in the designing of the NPIs, as the second wave of COVID-19 is expected in fall 2020, and such multidisciplinary analyses are crucial in order to understand the evolution of the Daily Deaths to Daily Cases ratio along with its determinants as soon as possible, for the assessment of the respective domestic health authorities' policy interventions as well as for the timely health resources allocation. [ABSTRACT FROM AUTHOR]

This paper presents the assessment of water resource security in the Guizhou karst area, China. A mean impact value and back-propagation (MIV-BP) neural network was used to understand the influencing factors. Thirty-one indices involving five aspects, the water quality subsystem, water quantity subsystem, engineering water shortage subsystem, water resource vulnerability subsystem, and water resource carrying capacity subsystem, were selected to establish an evaluation index of water resource security. In addition, a genetic algorithm and back-propagation (GA-BP) neural network was constructed to assess the water resource security of Guizhou Province from 2001 to 2015. The results show that water resource security in Guizhou was at a moderate warning level from 2001 to 2006 and a critical safety level from 2007 to 2015, except in 2011 when a moderate warning level was reached. For protection and management of water resources in a karst area, the modes of development and utilization of water resources must be thoroughly understood, along with the impact of engineering water shortage. These results are a meaningful contribution to regional ecological restoration and socio-economic development and can promote better practices for future planning. [ABSTRACT FROM AUTHOR]

In this paper, we analyzed the spatial and temporal causality and graph-based centrality relationship between air pollutants and PM2.5 concentrations in China from 2013 to 2017. NO2, SO2, CO and O3 were considered the main components of pollution that affected the health of people; thus, various joint regression models were built to reveal the causal direction from these individual pollutants to PM2.5 concentrations. In this causal centrality analysis, Beijing was the most important area in the Jing-Jin-Ji region because of its developed economy and large population. Pollutants in Beijing and peripheral cities were studied. The results showed that NO2 pollutants play a vital role in the PM2.5 concentrations in Beijing and its surrounding areas. An obvious causality direction and betweenness centrality were observed in the northern cities compared with others, demonstrating the fact that the more developed cities were most seriously polluted. Superior performance with causal centrality characteristics in the recognition of PM2.5 concentrations has been achieved. [ABSTRACT FROM AUTHOR]

The peak particle velocity (PPV) is an important indicator for predicting blasting excavation disturbances. However, the PPV distribution in the deep underground space is significantly different from that on the outdoor ground. Therefore, it is difficult to predict the underground PPV by Sadovsky's vibration formula. The PPV sidewall distribution characteristics were studied during site blasting in an underground cavern in the Taohuazui mine in China, and a similar numerical model was used to verify the site test data. We derived a PPV prediction formula for the underground cavern sidewall surrounding rock using a mechanical analysis model of a simply supported plate and beam in combination with dimensional analysis. The model considered derived boundary constraints, comparison with site measured data, the value predicted by Sadovsky's vibration formula, and numerical simulation results. The results showed that the PPV distribution on the middle 1/3 section of the underground cavern sidewall showed a "platform" or "bulge" different from the curve from Sadovsky's vibration formula. The PPV amplification coefficient in this section was distributed in a drum shape. The PPV prediction formula for the middle section of the sidewall derived in this paper was highly consistent with the data measured on-site and the numerical simulation results. The mechanical analysis model with a simply supported plate and beam included an underground cavern sidewall length–height ratio of 5 and effectively supplemented the PPV prediction formula for the middle section of the traditional underground cavern sidewall. [ABSTRACT FROM AUTHOR]

The spread of COVID-19 is closely related to the structure of human social networks. Based on 237 cases, by using epidemiological retrospective statistics, data visualization, and social network analysis methods, this paper summarized characteristics of patients with COVID-19 in Shaanxi, China, and analyzed these patients' dynamic contact network structure. The study found that there are many clustered infections through strong ties, about one-third of cases are caused by relatives' infection. In early stages of the epidemic, imported cases were the most, and in the later stages, local infection cases were the most. The infected people were mostly middle-aged men. Symptoms of imported cases occurred on average of 3 days after they arrived, and medical measures were taken 5 days later on average. All cases showed symptoms in less than 2 days on average and were then taken to medical treatment. The contact network can be divided into multiple disconnected components. The largest component has 12 patients. The average degree centrality in the network is 0.987, average betweenness degree is 0, average closeness degree is 0.452, and average PageRank index is 0.0042. The number of contacts of patients is unevenly distributed in the network. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Coral reef islands provide precious living space and valuable ecological services for human beings, and its sustainability cannot be ignored under the pressure of human activities. Carrying capacity (CC) assessment has gradually become an important means to measure sustainability of islands. However, there is little comprehensive evaluation of the carrying capacity of coral reef islands, and traditional evaluation methods are difficult to express the social-ecological characteristics of coral reef islands. The present paper proposes a comprehensive assessment model for coral reef island carrying capacity (CORE-CC) which comprises dimensions of resources supply, environmental assimilative, ecosystem services, and socio-economic supporting. According to the characteristics of the coral reef islands, the core factors and indicators of each dimension are selected and the corresponding assessment index system of "pressure-support" is constructed. The assessment involves (1) identification of carrying dimensions and core factors, (2) pressure/support measurement and (3) assessment of carrying state. A case study is conducted in Zhaoshu Island of China, demonstrating the applicability of CORE-CC model and serving as a reference for adaptive management. [ABSTRACT FROM AUTHOR]

In December 2019, corona virus disease 2019 (COVID-19) has broken out in China. Understanding the distribution of disease at the national level contributes to the formulation of public health policies. There are several studies that investigating the influencing factors on distribution of COVID-19 in China. However, more influencing factors need to be considered to improve our understanding about the current epidemic. Moreover, in the absence of effective medicine or vaccine, the Chinese government introduced a series of non-pharmaceutical interventions (NPIs). However, assessing and predicting the effectiveness of these interventions requires further study. In this paper, we used statistical techniques, correlation analysis and GIS mapping expression method to analyze the spatial and temporal distribution characteristics and the influencing factors of the COVID-19 in mainland China. The results showed that the spread of outbreaks in China's non-Hubei provinces can be divided into five stages. Stage I is the initial phase of the COVID-19 outbreak; in stage II the new peak of the epidemic was observed; in stage III the outbreak was contained and new cases decreased; there was a rebound in stage IV, and stage V led to level off. Moreover, the cumulative confirmed cases were mainly concentrated in the southeastern part of China, and the epidemic in the cities with large population flows from Wuhan was more serious. In addition, statistically significant correlations were found between the prevalence of the epidemic and the temperature, rainfall and relative humidity. To evaluate the NPIs, we simulated the prevalence of the COVID-19 based on an improved SIR model and under different prevention intensity. It was found that our simulation results were compatible with the observed values and the parameter of the time function in the improved SIR model for China is a = − 0.0058. The findings and methods of this study can be effective for predicting and managing the epidemics and can be used as an aid for decision makers to control the current and future epidemics. [ABSTRACT FROM AUTHOR]

This paper describes a recent landslide event, which occurred at Liucheng village in Tianquan County, Sichuan Province, China, on July 15, 2018. The Laochang landslide described in this research is an outstanding and valuable reference for understanding the characteristics of such kind of landslides that are geologically similar to the landslide. The deformation characteristics of the landslide are investigated based on field investigations, drilled boreholes, and exploratory trenches. The 225 residents of 64 households living on the flat platform were threatened by the landslide. Therefore, to guarantee the safety of human life and property becomes the primary emergency task. The anti-sliding piles were taken to stabilize the landslide and mitigate impacts caused by the landslide. Based on the analysis of the monitoring data, the effectiveness of anti-sliding piles is evaluated. The results indicate that the anti-sliding piles are effective in increasing the stability of the landslide, and this work can provide a reference for similar slope engineering projects. [ABSTRACT FROM AUTHOR]

The current outbreak of coronavirus disease 2019 (COVID-19) has become a global crisis due to its quick and wide spread over the world. A good understanding of the dynamic of the disease would greatly enhance the control and prevention of COVID19. However, to the best of our knowledge, the unique features of the outbreak have limited the applications of all existing dynamic models. In this paper, a novel stochastic model was proposed aiming to account for the unique transmission dynamics of COVID-19 and capture the effects of intervention measures implemented in Mainland China. We found that: (1) instead of aberration, there was a remarkable amount of asymptomatic virus carriers, (2) a virus carrier with symptoms was approximately twice more likely to pass the disease to others than that of an asymptomatic virus carrier, (3) the transmission rate reduced significantly since the implementation of control measures in Mainland China, and (4) it was expected that the epidemic outbreak would be contained by early March in the selected provinces and cities in China. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Supply chain management with uncertainty in consumer perception of product greenness under an eco-label policy." The original article can be found online at the provided link. The correction addresses an incomplete Acknowledgements section in the original version of the article. The corrected version now includes additional funding support from the National Natural Science Foundation of China. The original article has been corrected by the authors, Jingzhe Gao and Haixiao Wei. [Extracted from the article]

Based on the data of A-share listed companies in China from 2016 to 2020, this study empirically analyzes the relationship among corporate social responsibility, debt financing cost and enterprise innovation by constructing a regulated mediation effect model. The results show that enterprises perform social responsibility actively can enhance the level of enterprise innovation. Besides, debt financing cost plays a part of the intermediary role between corporate social responsibility and enterprise innovation. It is found that market competition degree positively regulates the relationship between corporate social responsibility and enterprise innovation, and market competition degree strengthens the part of the intermediary effect of debt financing cost. The conclusions not only help to reveal the impact mechanism of corporate social responsibility on enterprise innovation, but also provide empirical evidence for promoting enterprises to actively assume social responsibility, improve the level of innovation, and provide empirical evidence for the government to formulate corresponding policies according to the degree of competition in different markets. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

The generation, formation, and development of debris flow are closely related to the vertical climate, vegetation, soil, lithology and topography of the mountain area. Taking in the upper reaches of Min River (the Upper Min River) as the study area, combined with GIS and RS technology, the Geo-detector (GEO) method was used to quantitatively analyze the respective influence of 9 factors on debris flow occurrence. We identify from a list of 5 variables that explain 53.92%% of the total variance. Maximum daily rainfall and slope are recognized as the primary driver (39.56%) of the spatiotemporal variability of debris flow activity. Interaction detector indicates that the interaction between the vertical differentiation factors of the mountainous areas in the study area is nonlinear enhancement. Risk detector shows that the debris flow accumulation area and propagation area in the Upper Min River are mainly distributed in the arid valleys of subtropical and warm temperate zones. The study results of this paper will enrich the scientific basis of prevention and reduction of debris flow hazards. [ABSTRACT FROM AUTHOR]

The rapid urbanization in China has been associated with a growing hunger for energy consumption and steadily-increasing CO2 emissions. In this paper, an integrated system dynamics model composed of four sub-models is developed to simulate the urbanization and energy consumption in China from 1998 to 2050. Three scenarios are provided: accelerated economic development, emission reduction constraint, and low-carbon oriented. The result reveals that rapid economic growth and sufficient energy supply will foster China's urbanization in all three scenarios. Under the low carbon transition scenario, China's urbanization rate is expected to reach 76.41% in 2050, both reducing carbon emissions and promoting eco-friendly development. All three scenarios witness a dramatic growth of residential energy consumption and a steady increase of industrial energy consumption. China still has a long way to achieve the low-carbon transition goal. China should promote renewable resources and energy, pursue a low-carbon lifestyle, and reduce energy intensity over the next few decades. [ABSTRACT FROM AUTHOR]

Stool characteristics are of great value to assess diseases, but patients knew little. E-learning applied in health popularization and patient education is booming. In China, WeChat applets has advantages of abundant users, convenient access and low cost, which may be a great media in patient education on stool. This preliminary study aims to develop and evaluate a stool card WeChat applet. We collected stools images during 2020 to 2022 in the Department of Gastroenterology and Hepatology in the Second Affiliated Hospital of Harbin Medical University, constructed a stool card applet named the Doctor Friend Primary Screening Stool Card (DFPSSC) and evaluated it. Eligible participants were divided into the applet, traditional paper media and control group. We implement a series of tests to evaluate the effectiveness. 20 clinicians and participants using the DFPSSC completed a questionnaire to evaluate the usability. We developed the DFPSSC for an E-learning approach. Of 108 volunteers, 97 completed the DFPSSC learning. No significant pretest differences were found among the three groups (P = 0.303). Applet group had significantly higher posttest scores than pretest scores in intervention (P < 0.001, d = 1.68) and simulation (P = 0.006) test, and it had higher scores than other two group (P < 0.001). 63% participants and 59% clinicians strongly agree or agree to the usability of DFSSC. This preliminary study verified that the DFPSSC can effectively improve participants' knowledge of feces, making it an effective clinical tool for patient education and the avoidance of treatment delay. [ABSTRACT FROM AUTHOR]

In recent years, ozone (O3) pollution in China has shown a worsening trend. Due to the vast territory of China, O3 pollution is a widespread and complex problem. It is vital to understand the current spatiotemporal distribution of O3 pollution in China. In this study, we collected hourly data on O3 concentrations in 338 cities from January 1, 2016, to February 28, 2019, to analyze O3 pollution in China from a spatiotemporal perspective. The spatial analysis showed that the O3 concentrations exceeded the limit in seven geographical regions of China to some extent, with more serious pollution in North, East, and Central China. The O3 concentrations in the eastern areas were usually higher than those in the western areas. The temporal analysis showed seasonal variations in O3 concentration, with the highest O3 concentration in the summer and the lowest in the winter. The weekend effect, which occurs in other countries (such as the USA), was found only in some cities in China. We also found that the highest O3 concentration usually occurred in the afternoon and the lowest was in the early morning. The comprehensive analysis in this paper could improve our understanding of the severity of O3 pollution in China. [ABSTRACT FROM AUTHOR]

The coincidence of flood flows in a mainstream and its tributaries may lead to catastrophic floods. In this paper, we investigated the flood coincidence risk under nonstationary conditions arising from climate changes. The coincidence probabilities considering flood occurrence dates and flood magnitudes were calculated using nonstationary multivariate models and compared with those from stationary models. In addition, the "most likely" design based on copula theory was used to provide the most likely flood coincidence scenarios. The Huai River and Hong River were selected as case studies. The results show that the highest probabilities of flood coincidence occur in mid-July. The marginal distributions for the flood magnitudes of the two rivers are nonstationary, and time-varying copulas provide a better fit than stationary copulas for the dependence structure of the flood magnitudes. Considering the annual coincidence probabilities for given flood magnitudes and the "most likely" design, the stationary model may underestimate the risk of flood coincidence in wet years or overestimate this risk in dry years. Therefore, it is necessary to use nonstationary models in climate change scenarios. [ABSTRACT FROM AUTHOR]

The construction of information infrastructure as well as the transformation and upgrading of the industrial structure are among the major challenges for the Chinese economy. Therefore, it is of great significance to explore how information infrastructure affects the upgrading of industrial structure. Based on the panel data of 31 provinces in China from 2013 to 2020, mediating effect model and non-parametric percentile bootstrap method are used to carry out empirical research, by creating an information infrastructure construction level and industrial structure upgrading indicators. The results show that, in addition to the direct effect of information infrastructure on industrial structure upgrading, information infrastructure can also work indirectly through three paths: (1) information infrastructure acts on industrial structure upgrading by enhancing urbanization level; (2) information infrastructure affects industrial structure upgrading by boosting technological innovation; (3) information infrastructure first enhances urbanization level, then acts on technological innovation, and finally promotes industrial structure upgrading. In addition, the intermediary effect of technological innovation is stronger than urbanization. In general, this study acknowledges that urbanization and technological innovation are partial mediators in the process of information infrastructure affecting industrial structure upgrading, notwithstanding other potential impact pathways being studied further. [ABSTRACT FROM AUTHOR]

IP geolocation is an important basis of location-based network services, while error estimation is an important basis for judging the reliability of results. Most of the existing IP geolocation algorithms cannot estimate the geolocation error. A few can achieve error estimation through high-precision delay measurement, but their performance is also affected by the common delay inflation in the actual network. A new IP target location estimation method is proposed in this manuscript to achieve geolocation with reliable error estimation of IP targets in actual network. Firstly, after the landmark set divided into training set and verification set for path detection, the metropolitan area network (MAN) topology is extracted through train path set. Secondly, the governed landmarks are searched level by level through the MAN, and the minimum covering circles are calculated through the geographical distribution of the landmarks to infer the routers' area center. Then, geolocation errors are counted after simulated geolocation through the verification path set, and the minimum mean square error radius of the error mean and the minimum covering circle radius is calculated as the router area radius. Finally, the path to the IP target is measured and compared with the MAN to get the location estimation result. The experimental results based on 12 cities in China show that compared with the existing typical algorithms, the proposed method not only improves the error estimation accuracy, but also has finer geolocation granularity and lower median error. [ABSTRACT FROM AUTHOR]

Land-use change is widely considered to be a major factor affecting soil carbon (C) sequestration (ΔCs). This paper studied changes to soil C stocks (Cs) following the conversion of farmland to forest, shrub and grassland across the key area for implementing China's "Grain for Green" — the Loess Plateau. The results are based on a synthesis of 44 recent publications (including 424 observations at 70 sites) which has allowed us to further refine our understanding of the mechanisms driving the increase in Cs following farmland conversion. This synthesis suggests that the ΔCs potential of the Loess Plateau could reach 0.59 Tg yr-1 based on an estimated annual average ΔCs rate of 0.29 Mg ha-1 yr-1. In the region's different rainfall zones both the main contributing factors and Cs dynamics varied. Across the entire Loess Plateau, Cs showed first an increasing (<5 yr) then a decreasing (6-10 yr) tendency only to increase (>10 yr) yet again. In addition, the ΔCs rates depended primarily on restoration age. This synthesis demonstrates that both the initial s Cs and the average annual temperature have a significant effect on ΔCs while the effect of land-use conversion type, rainfall zone, and average annual precipitation were minimal. [ABSTRACT FROM AUTHOR]

Previous studies suggested odor stimulation may influence feeding of premature neonates. Therefore, this systematic review and meta-analysis of randomized controlled trials was conducted to assess the effect of human milk odor stimulation on feeding of premature infants. All randomized controlled trials related to human milk odor stimulation on feeding in premature infants published in PubMed, Cochrane, Library, Medline, Embase, Web of science databases and Chinese biomedical literature databases, China National Knowledge Infrastructure, China Science and Technology Journal Database (VIP) and Wanfang Chinese databases were searched, and The Cochrane Handbook 5.1.0 was used to evaluate the quality and authenticity of the literature. Relevant information of the included studies was extracted and summarized, and the evaluation indexes were analyzed using ReviewManager5.3. The retrieval time was from the establishment of the database to July 28, 2022.12 articles were assessed for eligibility, and six randomized controlled studies were eventually included in the meta-analysis (PRISMA). A total of 6 randomized controlled studies with 763 patients were finally included in the study, and the quality evaluation of literatures were all grade B. Human milk odor stimulation reduced the transition time to oral feeding in premature infants [SMD = − 0.48, 95% CI (− 0.69, − 0.27), Z = 4.54, P < 0.00001] and shortened the duration of parenteral nutrition [MD = − 1.01, 95% CI (− 1.70, − 0.32), Z = 2.88, P = 0.004]. However, it did not change the length of hospitalization for premature infants [MD = − 0.03, 95% CI (− 0.41, 0.35), Z = 0.17, P = 0.86]. The implementation of human milk odor stimulation can reduce the transition time to oral feeding and the duration of parenteral nutrition in premature infants, but further studies are needed to determine whether it can reduce the length of hospital stay in premature infants. More high-quality, large-sample studies are needed to investigate the effect of human milk odor stimulation on the feeding process and other outcomes in premature infants. [ABSTRACT FROM AUTHOR]

To reflect both fuzziness and hesitation in the evaluation of interactivity between attributes in the identification process of 2-order additive fuzzy measure, this work uses the hesitant fuzzy linguistic term set (HFLTS) to describe and depict the interactivity between attributes. Firstly, the interactivity between attributes is defined by the supermodular game theory. According to this definition, a linguistic term set is established to characterize the interactivity between attributes. Under the linguistic term set, the experts employ linguistic expressions generated by context-free grammar to qualitatively describe the interactivity between attributes. Secondly, through the conversion function, the linguistic expressions are transformed into the hesitant fuzzy linguistic term sets (HFLTSs). The individual evaluation results of all experts were further aggregated with the defined hesitant fuzzy linguistic weighted power average operator (HFLWPA). Thirdly, based on the standard Euclidean distance formula of the hesitant fuzzy linguistic elements (HFLEs), the hesitant fuzzy linguistic interaction degree (HFLID) between attributes is defined and calculated by constructing a piecewise function. As a result, a 2-order additive fuzzy measure identification method based on HFLID is proposed. Based on the proposed method, using the Choquet fuzzy integral as nonlinear integration operator, a multi-attribute decision making (MADM) process is then presented. Taking the credit assessment of the big data listed companies in China as an application example, the analysis results of application example prove the feasibility and effectiveness of the proposed method. This work successfully reflects both the fuzziness and hesitation in evaluating the interactivity between attributes in the identification process of 2-order additive fuzzy measure, enriches the theoretical framework of 2-order additive fuzzy measure, and expands the applicability and methodology of 2-order additive fuzzy measure in multi-attribute decision making. [ABSTRACT FROM AUTHOR]

To promote the application of automated vehicles in large airports, in this study, we present an integrated optimization method for scheduling Unmanned follow-me cars. The scheduling process is divided into three phases: Dispatch, Guidance, and Recycle. For the Dispatch phase, we establish a vehicle assignment model, to allocate the vehicle resource equitably. For the Guidance phase, we offer an quantitative way, to measure the spacing between Unmanned follow-me car and aircraft. To optimize the efficiency of airport operation in the three phases and ensure safety, the collaborative planning model, and the conflict prediction model are established. An improved grey wolf optimization algorithm is adopted to enhance the convergence speed and generalization performance. A case study at Ezhou Huahu Airport in China demonstrates the effectiveness of the methods. The results show that the model of collaborative planning can make the balance of path selection, Unmanned follow-me car's working time, and departure sequence. The convergence speed of the improved algorithm has been increased by 18.75%. The inequity index of vehicle assignment is only 0.015731, and the spatiotemporal distribution of conflicts is influenced by the airport's surface layout. [ABSTRACT FROM AUTHOR]