Set-nets are common alongshore fishing gear used in Haizhou Bay, which rely on flow to catch fish. The catch per unit effort(CPUE) of set-net is affected by spatial-temporal and environmental factors but no research h...Set-nets are common alongshore fishing gear used in Haizhou Bay, which rely on flow to catch fish. The catch per unit effort(CPUE) of set-net is affected by spatial-temporal and environmental factors but no research has been conducted on this subject. In this study, we used generalized additive models(GAMs) to explore the influence of spatial-temporal and environmental factors on CPUEs of species aggregated, small yellow croaker(Larimichthys polyactis), and octopus(Octopus variabilis) based on logbooks investigations conducted at 4 stations in an alongshore area of Haizhou Bay from 2011 to 2012. The results showed that all CPUEs exhibited significant spatial-temporal differences at various scales. Aggregated CPUE was high when the sea surface temperature(SST) was 15-18℃ and 20-23℃, which was mainly determined by life history traits of the octopus and small yellow croaker(optimal SSTs 14-17℃ and 19-24℃, respectively). Chlorophyll-a concentration had significant influences on the aggregated, small yellow croaker and octopus CPUEs at optimal ranges of 3.8-6.2 mg m^(-3), 4.2-4.8 mg m^(-3) and 4.5-5.5 mg m^(-3), respectively. Flow through the net had positive relationships with CPUEs. The approximate logarithmic trends in regression curves had a critical point of 2.5 Mm^3 d^(-1), which was the dividing point that differentiated whether the major factor affecting CPUEs was the flow velocity or the fishery resource. Our results from this study will help guide fishery production and improve catch rate of set-net fishing in Haizhou Bay.展开更多
Sunshine duration has an important impact on agriculture.In order to study the temporal and spatial variation of sunshine duration in China under the background of climate change,based on the observation data of 2089 ...Sunshine duration has an important impact on agriculture.In order to study the temporal and spatial variation of sunshine duration in China under the background of climate change,based on the observation data of 2089 national meteorological stations during 1961-2017,trend analysis,mutation analysis,partial correlation analysis,and Mann-Kendall mutation analysis were used to analyze the temporal and spatial variation characteristics of sunshine duration in different regions of China,and the influence of main climatic factors and human activities.The results showed that:the sunshine duration in China showed a significant decreasing trend with a rate of-45.8 h/10 a,and the sunshine duration in 7 regions of Northwestern China,Northern China,Northeastern China,Center China,Eastern China,Southern China,and Southwestern China also showed a significant decrease.The spatial distribution of sunshine duration in China was characterized by"less in the south and more in the north",and the sunshine duration in the northern region was significantly higher than those in the southern region.The sunshine duration in Tibet,Qinghai,Gansu and west Inner Mongolia was higher,while it was obviously lower in Sichuan Basin.Through M-K mutation test analysis,it was found that sunshine duration in the whole country decreased significantly,but there was no mutation station,while mutation occurred at 1989 in Southwestern China,1983 in Northwestern China,1985 in Northeastern China.Seasonally,there was the highest sunshine duration in summer,followed by spring,autumn,and winter;the decline rate was also the highest in summer,followed by autumn,winter,and spring.Sunshine duration had a highly negative correlation with total cloud amount,visibility,haze,and precipitation,while had a strongly positive correlation with wind speed,and had no significant correlation with fog.展开更多
This paper provides a systematic review of the histochemical localization,content characteristics,and influencing factors of saponins in Pseudostellaria heterophylla based on an extensive literature survey.It provides...This paper provides a systematic review of the histochemical localization,content characteristics,and influencing factors of saponins in Pseudostellaria heterophylla based on an extensive literature survey.It provides an in-depth analysis and summary of the effects of biological factors,environmental conditions,agronomic practices,processing methods,and continuous cropping obstacles on the synthesis of P.heterophylla saponins,as well as their underlying mechanisms.Based on identified gaps in the current literature,future research directions and prospects are proposed.The findings of this review offer valuable insights for advancing the understanding of the saponin biosynthesis mechanisms in P.heterophylla and for enhancing its quality.展开更多
Background:The trajectory of intrinsic capacity(IC)among the older population is characterized by its diversity and is predictive of adverse health outcomes such as disability,nursing home admission,decline in quality...Background:The trajectory of intrinsic capacity(IC)among the older population is characterized by its diversity and is predictive of adverse health outcomes such as disability,nursing home admission,decline in quality of life,and mortality.Gaining an understanding of the trajectory of IC and the factors that influence it is of paramount importance for fostering healthy aging.This research is focused on exploring the trajectory of IC among older adults in China and examining the factors that influence it.Methods:This observational longitudinal cohort study leveraged data from the China Health and Retirement Longitudinal Study(CHARLS),which was conducted in the years 2011,2013,and 2015.For the purpose of this analysis,a total of 2,233 participants who were aged 60 and over were included.A Growth Mixture Model(GMM)was utilized to define trajectory categories for IC.Influential factors were ascertained based on the health ecology model,and binary logistic regression analysis was utilized to investigate the factors linked with the different trajectory categories.Results:Two distinct trajectory classes of IC were identified:Class 1,the normal-stable group,encompassed 90.4%of the elderly population,while Class 2,the declining group,made up 9.6%.Advanced age and a history of stroke were found to be significantly associated with Class 2.High scores in activities of daily living(ADL),employment status,receiving primary or junior high school education,and residence in the East or Central regions of China were significantly linked with Class 1.Conclusion:The trajectory of IC among older Chinese adults is marked by its heterogeneity.Advanced age and a history of stroke are significant risk factors for a declining IC trajectory,while higher ADL scores,being employed,receiving primary or junior high school education,and residing in the East or Central regions of China are protective factors associated with a stable IC trajectory.Healthcare institutions must closely monitor IC levels and understand these trajectory patterns to implement personalized and targeted interventions promptly to maintain IC at a healthy level and advocate for healthy aging.展开更多
The discharge of micro-polluted water from sources such as agricultural runoff,urban stormwater,and treated effluents presents significant challenges to aquatic ecosystems.Constructed wetlands(CWs)have gained recog-ni...The discharge of micro-polluted water from sources such as agricultural runoff,urban stormwater,and treated effluents presents significant challenges to aquatic ecosystems.Constructed wetlands(CWs)have gained recog-nition as an eco-friendly solution for removing pollutants from various wastewater sources and are increasingly applied for micro-polluted water treatment.By reviewing 78 full-scale CW studies from Web of Science,it is summarized that the ranges of ammonium nitrogen(NH4+-N)concentrations in runoff,wastewater treatment plant effluent and polluted river were 0.1–6.6,0.3–12.3,and 0.2–41.1 mg/L,respectively.The ranges of ni-trate nitrogen concentrations were 0.2–14.2,0–5.7,and 0–2.6 mg/L,respectively.Removal efficiencies of CWs for micro-polluted water varied by CW types.The total nitrogen removal efficiencies for subsurface-flow CWs,free-water surface-flow CWs,and hybrid CWs ranged from 27.4%to 66.5%,16.8%to 89.8%,and 19.4%to 88.2%,respectively.The NH4+-N removal efficiencies ranged from 34.2%to 73.6%,38.4%to 89.4%and 13.5%to 94.2%,respectively.Additionally,other factors influencing contaminant removal efficiency such as hydraulic retention time,vegetation types,redox micro-environment and influent water quality were evaluated.Based on these findings,two strategies for improving the purification performance of CWs were proposed:the selection of incorporating electron donor substrates and the optimization of operation parameters.This paper serves as a synthesis of information to guide future research and full-scale CW applications in micro-polluted water treatment.展开更多
BACKGROUND Lumbar interbody fusion(LIF)is the primary treatment for lumbar degenerative diseases.Elderly patients are prone to anxiety and depression after undergoing surgery,which affects their postoperative recovery...BACKGROUND Lumbar interbody fusion(LIF)is the primary treatment for lumbar degenerative diseases.Elderly patients are prone to anxiety and depression after undergoing surgery,which affects their postoperative recovery speed and quality of life.Effective prevention of anxiety and depression in elderly patients has become an urgent problem.AIM To investigate the trajectory of anxiety and depression levels in elderly patients after LIF,and the influencing factors.METHODS Random sampling was used to select 239 elderly patients who underwent LIF from January 2020 to December 2024 in Shenzhen Pingle Orthopedic Hospital.General information and surgery-related indices were recorded,and participants completed measures of psychological status,lumbar spine dysfunction,and quality of life.A latent class growth model was used to analyze the post-LIF trajectory of anxiety and depression levels,and unordered multi-categorical logistic regression was used to analyze the influencing factors.RESULTS Three trajectories of change in anxiety level were identified:Increasing anxiety(n=26,10.88%),decreasing anxiety(n=27,11.30%),and stable anxiety(n=186,77.82%).Likewise,three trajectories of change in depression level were identified:Increasing depression(n=30,12.55%),decreasing depression(n=26,10.88%),and stable depression(n=183,76.57%).Regression analysis showed that having no partner,female sex,elevated Oswestry dysfunction index(ODI)scores,and reduced 36-Item Short Form Health Survey scores all contributed to increased anxiety levels,whereas female sex,postoperative opioid use,and elevated ODI scores all contributed to increased depression levels.CONCLUSION During clinical observation,combining factors to predict anxiety and depression in post-LIF elderly patients enables timely intervention,quickens recovery,and enhances quality of life.展开更多
Tuberculosis(TB),one of the oldest infectious diseases caused by Mycobacterium tuberculosis,poses a considerable challenge to global public health.There are approximately 10 million new TB cases worldwide annually,and...Tuberculosis(TB),one of the oldest infectious diseases caused by Mycobacterium tuberculosis,poses a considerable challenge to global public health.There are approximately 10 million new TB cases worldwide annually,and TB claims the lives of nearly 3 million people each year,making it one of the leading causes of death from a single infectious disease[1].China ranks third globally in terms of TB burden,with approximately 733,000 TB cases reported in 2023[2].Based on the ecological model of health determinants developed by Whitehead and Dahlgren,health determinants can be classified into direct causes.展开更多
BACKGROUND Identifying factors that influence non-curative resection(NCR)is critical to optimize treatment strategies and improve patient outcomes in patients with early gastric cancer(EGC).AIM To investigate the fact...BACKGROUND Identifying factors that influence non-curative resection(NCR)is critical to optimize treatment strategies and improve patient outcomes in patients with early gastric cancer(EGC).AIM To investigate the factors influencing the NCR of EGC and to evaluate the predictive value of these factors.METHODS The clinical data of 173 patients with EGC admitted between July 2020 and July 2023 were retrospectively collected.According to radical resection criteria,the patients were further divided into curative resection group(n=143)and NCR group(n=30).Clinical information was collected,including surgical method,tumor diameter,tumor site,ulcer formation,depth of invasion,pathological type,and lymph node metastasis.Logistic regression analysis was used to explore the factors affecting non-curable resection.RESULTS Multivariate logistic regression analysis showed that ulcer formation[odds ratio(OR)=3.53;95%confidence interval(CI):1.55-8.01,P=0.003],pathological type(OR=3.73;95%CI:1.60-8.74,P=0.002),tumor diameter(OR=3.15;95%CI:1.40-7.05,P=0.005),tumor location(OR=3.50;95%CI:1.16-10.58,P=0.027),lymph node metastasis(OR=4.40;95%CI:1.83-10.57,P=0.001),and depth of penetration(OR=3.75;95%CI:1.60-8.74,P=0.002)were all risk factors for NCR in EGC patients.Predictive analysis showed varying area under the curve values for factors such as tumor diameter(0.636),tumor location(0.608),ulcer formation(0.652),infiltration depth(0.658),pathological type(0.656),and lymph node metastasis(0.674).CONCLUSION The results suggest that factors such as tumor diameter,tumor location,ulcer formation,depth of invasion,pathological type,and lymph node metastasis increase the risk of NCR in EGC patients.展开更多
[Objective]The construction of weirs changes the hydraulic characteristics of rivers and affects the structure of phytoplankton communities and the health of aquatic ecosystems in the river.This study aims to explore ...[Objective]The construction of weirs changes the hydraulic characteristics of rivers and affects the structure of phytoplankton communities and the health of aquatic ecosystems in the river.This study aims to explore the nonlinear response relationship between phytoplankton community structure and its driving factors in spring and autumn in Furong Creek under the construction of cascade weirs.[Methods]The structure of phytoplankton communities and related environmental factors were investigated in Furong Creek from 2023 to 2024.This study focused on the analysis of the changes of nutrient concentrations and biomass of phytoplankton in autumn and spring within the same dry season in Furong Creek.Redundancy analysis was used to identify the key factors influencing the structure of phytoplankton communities.The MIKE 11 model was employed to simulate the hydrodynamic changes in the river.Combined with total nitrogen and permanganate index,a GAM model of phytoplankton diversity index and hydrodynamic factors was developed,and the change of phytoplankton diversity after the optimized layout of the cascade weirs was fitted.[Results]The result showed that the annual average value of Shannon-Wiener diversity index of phytoplankton in Furong Creek was 2.79,which was in a state of mild pollution.A total of 239 species from 95 genera in 8 phyla were identified.Among the phytoplankton,Chlorophyta was the dominant group throughout the year in Furong Creek,followed by Bacillariophyta and Cyanophyta.The cell abundance of phytoplankton ranged from 3.11 to 20.64 mg/L and from 0.23 to 6.31 mg/L in spring and autumn,which indicated a clear seasonal succession of phytoplankton community structure.Compared with autumn,the relative abundance of Cyanophyta significantly decreased in spring across the whole river section,while Chrysophyta and Dinophyta showed significant increase at some monitoring sites,leading to water bloom phenomenon and a noticeable decline in the diversity of phytoplankton.The dominant species in the water bodies throughout the year were Cyclotella catenata,Chlorella vulgaris,Scenedesmus bijuga,Scenedesmus quadricauda,Chroomonas acuta,Cryptomonas ovata,and Cryptomonas erosa.Redundancy analysis(RDA)showed that hydrodynamic factors(v,h)and water environmental factors(TN,COD_(Mn))were the main influencing factors of phytoplankton community structure.[Conclusion]The result show that the nutrient concentration,phytoplankton biomass,and density in Furong Creek in spring are significantly higher than in autumn.The GAM model,constructed by combining hydrodynamic and environmental factors,can effectively reflect the nonlinear relationship between phytoplankton diversity index and its driving factors.In spring,with an increase in nutrient concentration,the habitat conditions of low flow speed and high water depths formed by overflow weirs will lead to a decrease in the Shannon-Wiener index of phytoplankton and an intensified risk of eutrophication.However,a reasonable layout scheme of cascade weirs will improve the diversity of phytoplankton and reduce the risk of eutrophication in the river.The findings of this study can help deepen the understanding of the ecological and environmental effects of cascade weir construction in the river.展开更多
The spatial-temporal distribution of charging loads for electric vehicles is influenced by multiple factors,Nowadays,the accuracy of the forecasts needs to be improved and the completeness of the modeling is relativel...The spatial-temporal distribution of charging loads for electric vehicles is influenced by multiple factors,Nowadays,the accuracy of the forecasts needs to be improved and the completeness of the modeling is relatively lacking.Therefore,this paper proposes a method for modeling the charging load of electric vehicles based on the influence of multiple factors.First,an in-depth analysis of the factors affecting the charging load of electric vehicles was conducted.Then,a model of electric vehicle electricity consumption per unit kilometer was constructed based on the influencing factors.Next,the electric vehicle,the charging station,the traffic network and the grid are modeled separately.In addition,a unified model of vehicle-station-road-network was constructed through the interaction and coupling of information between the models.Finally,the spatial-temporal distribution of electric vehicle charging loads was simulated using real data from a region.The study shows that the model is able to simulate the charging load of electric vehicles more accurately.Different traffic flows and areas have a significant impact on the charging load distribution.展开更多
Taking 138 key rural tourism villages in Beijing for example,this paper applied GIS analysis to analyze the spatial distribution characteristics of these villages,selected the influence factors of the villages conside...Taking 138 key rural tourism villages in Beijing for example,this paper applied GIS analysis to analyze the spatial distribution characteristics of these villages,selected the influence factors of the villages considering the classification characteristics,so as to explore the impact of different influence factors on its spatial distribution.The results showed(i)Key rural tourism villages in Beijing manifested an aggregated distribution on the whole,they were unevenly distributed and mostly located in the fringe area of northern mountainous areas and plains,such as Huairou District and Miyun District.Such a“multi-center distribution”pattern was significantly influenced by terrains and natural resources.(ii)Depending on local natural and cultural resources,tourism resources,development characteristics and functional differences,key rural tourism villages in Beijing could be devided into natural scenery type,scenic area-dependent type and agriculture experiencing type.(iii)Key factors influencing the distribution of these villages included mean temperature,annual precipitation,quantity of scenic area,road network density,agricultural land and so on,and the interaction of dual factors exerted more significant impact on single factors.展开更多
Green innovation is an important driving force for high-quality development and an important guarantee for the revitalization of the old industrial base in Northeast China.However,research on green innovation is still...Green innovation is an important driving force for high-quality development and an important guarantee for the revitalization of the old industrial base in Northeast China.However,research on green innovation is still insufficient.Using the super-efficiency epsilon-based measure Malmquist model,kernel density estimation,and spatial econometric model,this study investigated the spatiotemporal evolution characteristics and influencing factors of green innovation efficiency(GIE)in Northeast China from 2005 to 2020.The results reveal that:1)The GIE in Northeast China has obvious phased characteristics,where 2005-2011 was a period of fluctuating decline while 2012-2020 was a period of fluctuating increase,reflecting the severe resource and environmental constraints faced by the green innovation process.2)The GIE in the Northeast China has a significant spatial dependence,which has not formed a relatively stable spatial club feature.The process for improving the GIE in the Northeast China in the future is still arduous and far off.3)The interweaving and mutual influence of nonequilibrium factors have led to the diversity and complexity of the spatiotemporal pattern evolution of GIE.Overall,the level of economic development and industrial structure has a positive effect,while foreign investment and industrial agglomeration have a negative effect.The direct effects of government regulation,resource endowment,science and technology,environmental regulation,and urbanization are not significant.The research conclusion of this article can provide important reference for the revitalization of Northeast China.展开更多
The aviation industry has become one of the top ten greenhouse gas emission industries in the world. China’s aviation carbon emissions continue to increase, but the analysis of its influencing factors at the provinci...The aviation industry has become one of the top ten greenhouse gas emission industries in the world. China’s aviation carbon emissions continue to increase, but the analysis of its influencing factors at the provincial level is still incomplete. This paper firstly uses Stochastic Impacts by Regression on Population, Affluence and Technology model(STIRPAT) model to analyze the time series evolution of China’s aviation carbon emissions from 2000 to 2019. Secondly, it uses the Logarithmic Mean Divisia Index(LDMI) model to analyze the influencing characteristics and degree of four factors on China’s aviation carbon emissions, which are air transportation revenue, aviation route structure, air transportation intensity and aviation energy intensity. Thirdly, it determines the various factors’ influencing direction and evolution trend of 31 provinces’ aviation carbon emissions in China(not including Hong Kong, Macao, Taiwan of China due to incomplete data). Finally, it derives the decoupling effort model and analyzes the decoupling relationship and decoupling effort degree between air carbon emissions and air transportation revenue in different provinces. The study found that from 2000 to2019, China’s total aviation carbon emissions continued to grow, while the growth rate of aviation carbon emissions showed a fluctuating downward trend. Air transportation revenue and aviation route structure promote the growth of total aviation carbon emissions, and air transportation intensity and aviation energy intensity have a restraining effect on the growth of total aviation carbon emissions. The scope of negative driving effect of air transportation revenue and air transportation intensity on total aviation carbon emissions in various provinces has increased. While the scope of positive driving influence of aviation route structure on total aviation carbon emissions of various provinces has increased, aviation energy intensity mainly has negative driving influence on total aviation carbon emissions of each province. Overall, the emission reduction trend in the areas to the west and north of the Qinling-Huaihe River Line is obvious. The decoupling mode between air carbon emissions and air transportation revenue in 31 provinces is mainly expansion negative decoupling.The air transportation intensity effect shows strong decoupling efforts in most provinces, the decoupling effort of aviation route structure effect and aviation energy intensity effect is not prominent.展开更多
The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital...The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital financial inclusion relies on information technology to overcome spatial limitations. In this case, the research question is whether it adheres to the spatial laws governing conventional financial activities. This study uses exploratory spatial data analysis and a geographical detector to elucidate the spatiotemporal characteristics and factors influencing digital financial inclusion at the county level in China(Data don’t include that of Hong Kong, Macao and Taiwan of China) from 2014 to 2020. The research findings indicate: first, China’s county-level digital financial inclusion is generally increasing and exhibits significant spatial autocorrelation. Second, population density, level of traditional financial development, government regulation, and education level are key determinants of China’s county-level digital financial inclusion. Third,policies should be differentiated by region to narrow the spatial gap in digital financial inclusion. The results provide a reference for other developing countries on using digital technology to develop financial inclusion.展开更多
Playing an important role in global warming and plant growth,relative humidity(RH)has profound impacts on production and living,and can be used as an integrated indicator for evaluating the wet-dry conditions in the a...Playing an important role in global warming and plant growth,relative humidity(RH)has profound impacts on production and living,and can be used as an integrated indicator for evaluating the wet-dry conditions in the arid and semi-arid area.However,information on the spatial-temporal variation and the influencing factors of RH in these regions is still limited.This study attempted to use daily meteorological data during 1966–2017 to reveal the spatial-temporal characteristics of RH in the arid region of Northwest China through rotated empirical orthogonal function and statistical analysis method,and the path analysis was used to clarify the impact of temperature(T),precipitation(P),actual evapotranspiration(ETa),wind speed(W)and sunshine duration(S)on RH.The results demonstrated that climatic conditions in North Xinjiang(NXJ)was more humid than those in Hexi Corridor(HXC)and South Xinjiang(SXJ).RH had a less significant downtrend in NXJ than that in HXC,but an increasingly rising trend was observed in SXJ during the last five decades,implying that HXC and NXJ were under the process of droughts,while SXJ was getting wetter.There was a turning point for the trend of RH in Xinjiang,which occurred in 2000.Path analysis indicated that RH was negatively correlated to T,ETa,W and S,but it increased with increase of P.S,T and W had the greatest direct effects on RH in HXC,NXJ and SXJ,respectively.ETa was the factor which had the greatest indirect effect on RH in HXC and NXJ,while T was the dominant factor in SXJ.展开更多
Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization...Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture(hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector(OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that:(1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km^(2). In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak.(2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced.(3) The results of OPGD detection in 2015 show that the influence of each factor is slope(0.2371) > traffic accessibility(0.2098) > population(0.1403) > regional GDP(0.1325) > elevation(0.0987) > poverty alleviation(0). The results of OPGD detection in 2020 show that the influence of each factor is slope(0.2339) > traffic accessibility(0.2198) > population(0.1432) > regional GDP(0.1219) > poverty alleviation(0.0992) > elevation(0.093). Natural geographical factors(slope and elevation) are the basic factors affecting the spatial distribution of rural settlements, and rural settlements are widely distributed in the river valley plain and the second half mountain area. Socioeconomic factors(traffic accessibility, population, and regional GDP) have a greater impact on the spatial distribution of rural settlements, which is an important factor affecting the spatial distribution of rural settlements. Policy factors such as poverty alleviation relocation have an indispensable impact on the spatial distribution of rural settlements. The research results can provide decisionmaking basis for the spatial arrangement of rural settlements in Liangshan Prefecture, and optimize the implementation of rural revitalization policies.展开更多
Green development is an important issue of sustainable development in China.Due to the relatively backward economy and the fragile ecological environment,restricted development zones need to embrace green development....Green development is an important issue of sustainable development in China.Due to the relatively backward economy and the fragile ecological environment,restricted development zones need to embrace green development.Taking 38 counties in Jilin Province as the empirical research objects,and based on cross-sectional data for each county in 2005,2010,and 2015,we accurately depicted the spatiotemporal evolutionary characteristics of green development efficiency(GDE)in restricted development zones of Jilin Province using the slacks-based measure-data envelope analysis(SBM-DEA)model.Moreover,the factors that influence GDE were further analyzed using the Tobit model.We found that:first,GDE showed a V-shaped trend in restricted development zones of Jilin Province.The differences in GDE in the eastern,central,and western Jilin Province increased gradually.Second,76%of counties in the restricted development zones had high or higher efficiencies.The resource-based cities were the main areas with low or lower GDE.Third,the economic development level was the core factor affecting GDE.Urbanization level had a significant negative effect on GDE in the restricted development zones.The effect of technological innovation level on GDE fluctuated,and we found that a‘backward mechanism’of technological innovation was beginning to form.Industrial structure and environmental governance had no significant effects on GDE.展开更多
The middle class in metropolitan Chinese cities has become an important social group. With the rapid development of urbanization and constant advancement of suburbanization, the middle class has increasingly come to i...The middle class in metropolitan Chinese cities has become an important social group. With the rapid development of urbanization and constant advancement of suburbanization, the middle class has increasingly come to influence city traffic. Research into middle-class commuting activities thus has practical significance for improving traffic congestion and reducing the commuting burden in metropolitan cities. Based on a dataset formed by 816 completed surveys, this paper analyzes the commuting mode, time and distance of middle-class residents in Guangzhou City using the descriptive statistical method. The results indicate that private cars are the main commuting mode, followed by public transport. Meanwhile, middle-class residents mainly undertake medium-short time and medium-short distance commuting. The study subsequently uses multilevel logistic regression and multiple linear regression models to analyze the factors that influence commuting mode choice, time and distance. The gender, age, number of family cars, housing source and jobs-housing balance are the most important factors influencing commuting mode choice; housing, population density, jobs-housing balance and commuting mode significantly affect commuting time; and transport accessibility, jobs-housing balance and commuting mode are the notable factors affecting commuting distance. Finally, this paper analyzes what is affecting the commuting activities of middle-class residents and determines the differences in commuting activity characteristics and influence factors between middle-class and ordinary residents. Policy suggestions to improve urban planning and urban management are also proposed.展开更多
Eco-efficiency is an invaluable indicator for the measurement of the relationship between production activities and environmental depletion.This study measures the tourism eco-efficiency of 30 provinces in China from ...Eco-efficiency is an invaluable indicator for the measurement of the relationship between production activities and environmental depletion.This study measures the tourism eco-efficiency of 30 provinces in China from 2005 to 2020 based on the super-efficiency SBM model,and explores its spatial-temporal evolution characteristics using the kernel density function,standard deviation ellipse,and center of gravity model.Then,the influencing factors of the tourism eco-efficiency in China are analyzed by Tobit regression model.The results show that the tourism eco-efficiency of China is generally fluctuating upwards,but has not yet reached the maximum production possibility frontier.The kernel density curve shows a unimodal-bimodal-unimodal pattern,while the inter-provincial differences have been decreasing and becoming more balanced.The center of gravity of tourism eco-efficiency is located at the junction of Henan and Hubei province and generally moves to the south(slightly to the southwest).Meanwhile,it is revealed that the level of economic development and the tourism eco-efficiency has a significant inverted U-shaped relationship.The level of economic openness,traffic conditions,and tourism eco-efficiency is positively correlated.The environmental regulations and industrial structure have a negative but limited impact on tourism eco-efficiency.Finally,recommendations and suggestions for policy formulation to promote quality and sustainable development of the tourism industry are put forward,such as increasing investment in ecological protection and governance in tourism development,improving capacity-building in allocating green and low-carbon technologies and resources,strengthening tourism infrastructure construction,and enhancing environmental governance systems and mechanisms.展开更多
In order to determine the regulations of the development of taxi supply under entry regulations in Chinese cities, an improved neural network model is applied to find the particular years when the government artificia...In order to determine the regulations of the development of taxi supply under entry regulations in Chinese cities, an improved neural network model is applied to find the particular years when the government artificially puts new taxis into the market, and then extract the political influence from the taxi supply. The model is also utilized to study the relationships between the adjusted taxi supply and non-policy factors. A case study of Nanjing city is conducted. The results show that 2001 and 2007 are the particular years that the Nanjing government artificially put new taxis into its taxi market, which is in accordance with the five-year plan of China and the local development plans. The results also show that the improved neural network model has a good performance in expositing the evolution of adjusted taxi supply related to non-policy factors.展开更多
基金funded through the Special Fund for Agro-Scientific Research in the Public Interestthe Special Public Welfare Industry (agriculture) Research-Research and Demonstration of Fisheries Fishing Technology and Fishing Gear (No. 201203018)the National Natural Science Foundation of China (No. 31402350)
文摘Set-nets are common alongshore fishing gear used in Haizhou Bay, which rely on flow to catch fish. The catch per unit effort(CPUE) of set-net is affected by spatial-temporal and environmental factors but no research has been conducted on this subject. In this study, we used generalized additive models(GAMs) to explore the influence of spatial-temporal and environmental factors on CPUEs of species aggregated, small yellow croaker(Larimichthys polyactis), and octopus(Octopus variabilis) based on logbooks investigations conducted at 4 stations in an alongshore area of Haizhou Bay from 2011 to 2012. The results showed that all CPUEs exhibited significant spatial-temporal differences at various scales. Aggregated CPUE was high when the sea surface temperature(SST) was 15-18℃ and 20-23℃, which was mainly determined by life history traits of the octopus and small yellow croaker(optimal SSTs 14-17℃ and 19-24℃, respectively). Chlorophyll-a concentration had significant influences on the aggregated, small yellow croaker and octopus CPUEs at optimal ranges of 3.8-6.2 mg m^(-3), 4.2-4.8 mg m^(-3) and 4.5-5.5 mg m^(-3), respectively. Flow through the net had positive relationships with CPUEs. The approximate logarithmic trends in regression curves had a critical point of 2.5 Mm^3 d^(-1), which was the dividing point that differentiated whether the major factor affecting CPUEs was the flow velocity or the fishery resource. Our results from this study will help guide fishery production and improve catch rate of set-net fishing in Haizhou Bay.
基金Supported by the National Key R&D Plan(2017YFD0300201,2020YFE 0201900).
文摘Sunshine duration has an important impact on agriculture.In order to study the temporal and spatial variation of sunshine duration in China under the background of climate change,based on the observation data of 2089 national meteorological stations during 1961-2017,trend analysis,mutation analysis,partial correlation analysis,and Mann-Kendall mutation analysis were used to analyze the temporal and spatial variation characteristics of sunshine duration in different regions of China,and the influence of main climatic factors and human activities.The results showed that:the sunshine duration in China showed a significant decreasing trend with a rate of-45.8 h/10 a,and the sunshine duration in 7 regions of Northwestern China,Northern China,Northeastern China,Center China,Eastern China,Southern China,and Southwestern China also showed a significant decrease.The spatial distribution of sunshine duration in China was characterized by"less in the south and more in the north",and the sunshine duration in the northern region was significantly higher than those in the southern region.The sunshine duration in Tibet,Qinghai,Gansu and west Inner Mongolia was higher,while it was obviously lower in Sichuan Basin.Through M-K mutation test analysis,it was found that sunshine duration in the whole country decreased significantly,but there was no mutation station,while mutation occurred at 1989 in Southwestern China,1983 in Northwestern China,1985 in Northeastern China.Seasonally,there was the highest sunshine duration in summer,followed by spring,autumn,and winter;the decline rate was also the highest in summer,followed by autumn,winter,and spring.Sunshine duration had a highly negative correlation with total cloud amount,visibility,haze,and precipitation,while had a strongly positive correlation with wind speed,and had no significant correlation with fog.
基金Supported by Open Fund Project of the Engineering Technology Research Center of Characteristic Medicinal Plants of Fujian(PP202003).
文摘This paper provides a systematic review of the histochemical localization,content characteristics,and influencing factors of saponins in Pseudostellaria heterophylla based on an extensive literature survey.It provides an in-depth analysis and summary of the effects of biological factors,environmental conditions,agronomic practices,processing methods,and continuous cropping obstacles on the synthesis of P.heterophylla saponins,as well as their underlying mechanisms.Based on identified gaps in the current literature,future research directions and prospects are proposed.The findings of this review offer valuable insights for advancing the understanding of the saponin biosynthesis mechanisms in P.heterophylla and for enhancing its quality.
基金China Health and Retirement Longitudinal Study(CHARLS)the 2022-2023 Nursing Research Project of Chinese Medical Association Publishing House(Grant No.CMAPH-NRD2022024)。
文摘Background:The trajectory of intrinsic capacity(IC)among the older population is characterized by its diversity and is predictive of adverse health outcomes such as disability,nursing home admission,decline in quality of life,and mortality.Gaining an understanding of the trajectory of IC and the factors that influence it is of paramount importance for fostering healthy aging.This research is focused on exploring the trajectory of IC among older adults in China and examining the factors that influence it.Methods:This observational longitudinal cohort study leveraged data from the China Health and Retirement Longitudinal Study(CHARLS),which was conducted in the years 2011,2013,and 2015.For the purpose of this analysis,a total of 2,233 participants who were aged 60 and over were included.A Growth Mixture Model(GMM)was utilized to define trajectory categories for IC.Influential factors were ascertained based on the health ecology model,and binary logistic regression analysis was utilized to investigate the factors linked with the different trajectory categories.Results:Two distinct trajectory classes of IC were identified:Class 1,the normal-stable group,encompassed 90.4%of the elderly population,while Class 2,the declining group,made up 9.6%.Advanced age and a history of stroke were found to be significantly associated with Class 2.High scores in activities of daily living(ADL),employment status,receiving primary or junior high school education,and residence in the East or Central regions of China were significantly linked with Class 1.Conclusion:The trajectory of IC among older Chinese adults is marked by its heterogeneity.Advanced age and a history of stroke are significant risk factors for a declining IC trajectory,while higher ADL scores,being employed,receiving primary or junior high school education,and residing in the East or Central regions of China are protective factors associated with a stable IC trajectory.Healthcare institutions must closely monitor IC levels and understand these trajectory patterns to implement personalized and targeted interventions promptly to maintain IC at a healthy level and advocate for healthy aging.
基金supported by the Natural Science Foundation of China(No.52470105)the Young Taishan Scholars Program of Shandong Province(No.358202103017).
文摘The discharge of micro-polluted water from sources such as agricultural runoff,urban stormwater,and treated effluents presents significant challenges to aquatic ecosystems.Constructed wetlands(CWs)have gained recog-nition as an eco-friendly solution for removing pollutants from various wastewater sources and are increasingly applied for micro-polluted water treatment.By reviewing 78 full-scale CW studies from Web of Science,it is summarized that the ranges of ammonium nitrogen(NH4+-N)concentrations in runoff,wastewater treatment plant effluent and polluted river were 0.1–6.6,0.3–12.3,and 0.2–41.1 mg/L,respectively.The ranges of ni-trate nitrogen concentrations were 0.2–14.2,0–5.7,and 0–2.6 mg/L,respectively.Removal efficiencies of CWs for micro-polluted water varied by CW types.The total nitrogen removal efficiencies for subsurface-flow CWs,free-water surface-flow CWs,and hybrid CWs ranged from 27.4%to 66.5%,16.8%to 89.8%,and 19.4%to 88.2%,respectively.The NH4+-N removal efficiencies ranged from 34.2%to 73.6%,38.4%to 89.4%and 13.5%to 94.2%,respectively.Additionally,other factors influencing contaminant removal efficiency such as hydraulic retention time,vegetation types,redox micro-environment and influent water quality were evaluated.Based on these findings,two strategies for improving the purification performance of CWs were proposed:the selection of incorporating electron donor substrates and the optimization of operation parameters.This paper serves as a synthesis of information to guide future research and full-scale CW applications in micro-polluted water treatment.
基金Supported by the Scientific Research Projects of the Health System in Pingshan District,No.2023122.
文摘BACKGROUND Lumbar interbody fusion(LIF)is the primary treatment for lumbar degenerative diseases.Elderly patients are prone to anxiety and depression after undergoing surgery,which affects their postoperative recovery speed and quality of life.Effective prevention of anxiety and depression in elderly patients has become an urgent problem.AIM To investigate the trajectory of anxiety and depression levels in elderly patients after LIF,and the influencing factors.METHODS Random sampling was used to select 239 elderly patients who underwent LIF from January 2020 to December 2024 in Shenzhen Pingle Orthopedic Hospital.General information and surgery-related indices were recorded,and participants completed measures of psychological status,lumbar spine dysfunction,and quality of life.A latent class growth model was used to analyze the post-LIF trajectory of anxiety and depression levels,and unordered multi-categorical logistic regression was used to analyze the influencing factors.RESULTS Three trajectories of change in anxiety level were identified:Increasing anxiety(n=26,10.88%),decreasing anxiety(n=27,11.30%),and stable anxiety(n=186,77.82%).Likewise,three trajectories of change in depression level were identified:Increasing depression(n=30,12.55%),decreasing depression(n=26,10.88%),and stable depression(n=183,76.57%).Regression analysis showed that having no partner,female sex,elevated Oswestry dysfunction index(ODI)scores,and reduced 36-Item Short Form Health Survey scores all contributed to increased anxiety levels,whereas female sex,postoperative opioid use,and elevated ODI scores all contributed to increased depression levels.CONCLUSION During clinical observation,combining factors to predict anxiety and depression in post-LIF elderly patients enables timely intervention,quickens recovery,and enhances quality of life.
基金supported by the National Natural Science Foundation of China(82574173,82003516)Jiangsu Provincial Natural Science Foundation(BK20251958)+2 种基金Jiangsu Provincial Medical Key Discipline(ZDXK202250)Top Talent Awards Project Fund(RDF-TP-0023,RDF-TP-0030)Postgraduate Research Fund(PGRS2112022)at Xi'an Jiaotong-Liverpool University.
文摘Tuberculosis(TB),one of the oldest infectious diseases caused by Mycobacterium tuberculosis,poses a considerable challenge to global public health.There are approximately 10 million new TB cases worldwide annually,and TB claims the lives of nearly 3 million people each year,making it one of the leading causes of death from a single infectious disease[1].China ranks third globally in terms of TB burden,with approximately 733,000 TB cases reported in 2023[2].Based on the ecological model of health determinants developed by Whitehead and Dahlgren,health determinants can be classified into direct causes.
文摘BACKGROUND Identifying factors that influence non-curative resection(NCR)is critical to optimize treatment strategies and improve patient outcomes in patients with early gastric cancer(EGC).AIM To investigate the factors influencing the NCR of EGC and to evaluate the predictive value of these factors.METHODS The clinical data of 173 patients with EGC admitted between July 2020 and July 2023 were retrospectively collected.According to radical resection criteria,the patients were further divided into curative resection group(n=143)and NCR group(n=30).Clinical information was collected,including surgical method,tumor diameter,tumor site,ulcer formation,depth of invasion,pathological type,and lymph node metastasis.Logistic regression analysis was used to explore the factors affecting non-curable resection.RESULTS Multivariate logistic regression analysis showed that ulcer formation[odds ratio(OR)=3.53;95%confidence interval(CI):1.55-8.01,P=0.003],pathological type(OR=3.73;95%CI:1.60-8.74,P=0.002),tumor diameter(OR=3.15;95%CI:1.40-7.05,P=0.005),tumor location(OR=3.50;95%CI:1.16-10.58,P=0.027),lymph node metastasis(OR=4.40;95%CI:1.83-10.57,P=0.001),and depth of penetration(OR=3.75;95%CI:1.60-8.74,P=0.002)were all risk factors for NCR in EGC patients.Predictive analysis showed varying area under the curve values for factors such as tumor diameter(0.636),tumor location(0.608),ulcer formation(0.652),infiltration depth(0.658),pathological type(0.656),and lymph node metastasis(0.674).CONCLUSION The results suggest that factors such as tumor diameter,tumor location,ulcer formation,depth of invasion,pathological type,and lymph node metastasis increase the risk of NCR in EGC patients.
文摘[Objective]The construction of weirs changes the hydraulic characteristics of rivers and affects the structure of phytoplankton communities and the health of aquatic ecosystems in the river.This study aims to explore the nonlinear response relationship between phytoplankton community structure and its driving factors in spring and autumn in Furong Creek under the construction of cascade weirs.[Methods]The structure of phytoplankton communities and related environmental factors were investigated in Furong Creek from 2023 to 2024.This study focused on the analysis of the changes of nutrient concentrations and biomass of phytoplankton in autumn and spring within the same dry season in Furong Creek.Redundancy analysis was used to identify the key factors influencing the structure of phytoplankton communities.The MIKE 11 model was employed to simulate the hydrodynamic changes in the river.Combined with total nitrogen and permanganate index,a GAM model of phytoplankton diversity index and hydrodynamic factors was developed,and the change of phytoplankton diversity after the optimized layout of the cascade weirs was fitted.[Results]The result showed that the annual average value of Shannon-Wiener diversity index of phytoplankton in Furong Creek was 2.79,which was in a state of mild pollution.A total of 239 species from 95 genera in 8 phyla were identified.Among the phytoplankton,Chlorophyta was the dominant group throughout the year in Furong Creek,followed by Bacillariophyta and Cyanophyta.The cell abundance of phytoplankton ranged from 3.11 to 20.64 mg/L and from 0.23 to 6.31 mg/L in spring and autumn,which indicated a clear seasonal succession of phytoplankton community structure.Compared with autumn,the relative abundance of Cyanophyta significantly decreased in spring across the whole river section,while Chrysophyta and Dinophyta showed significant increase at some monitoring sites,leading to water bloom phenomenon and a noticeable decline in the diversity of phytoplankton.The dominant species in the water bodies throughout the year were Cyclotella catenata,Chlorella vulgaris,Scenedesmus bijuga,Scenedesmus quadricauda,Chroomonas acuta,Cryptomonas ovata,and Cryptomonas erosa.Redundancy analysis(RDA)showed that hydrodynamic factors(v,h)and water environmental factors(TN,COD_(Mn))were the main influencing factors of phytoplankton community structure.[Conclusion]The result show that the nutrient concentration,phytoplankton biomass,and density in Furong Creek in spring are significantly higher than in autumn.The GAM model,constructed by combining hydrodynamic and environmental factors,can effectively reflect the nonlinear relationship between phytoplankton diversity index and its driving factors.In spring,with an increase in nutrient concentration,the habitat conditions of low flow speed and high water depths formed by overflow weirs will lead to a decrease in the Shannon-Wiener index of phytoplankton and an intensified risk of eutrophication.However,a reasonable layout scheme of cascade weirs will improve the diversity of phytoplankton and reduce the risk of eutrophication in the river.The findings of this study can help deepen the understanding of the ecological and environmental effects of cascade weir construction in the river.
基金the National Key Research and Development Program of China(No.2021YFB2501602)the National Natural Science Foundation of China(No.52077208)。
文摘The spatial-temporal distribution of charging loads for electric vehicles is influenced by multiple factors,Nowadays,the accuracy of the forecasts needs to be improved and the completeness of the modeling is relatively lacking.Therefore,this paper proposes a method for modeling the charging load of electric vehicles based on the influence of multiple factors.First,an in-depth analysis of the factors affecting the charging load of electric vehicles was conducted.Then,a model of electric vehicle electricity consumption per unit kilometer was constructed based on the influencing factors.Next,the electric vehicle,the charging station,the traffic network and the grid are modeled separately.In addition,a unified model of vehicle-station-road-network was constructed through the interaction and coupling of information between the models.Finally,the spatial-temporal distribution of electric vehicle charging loads was simulated using real data from a region.The study shows that the model is able to simulate the charging load of electric vehicles more accurately.Different traffic flows and areas have a significant impact on the charging load distribution.
文摘Taking 138 key rural tourism villages in Beijing for example,this paper applied GIS analysis to analyze the spatial distribution characteristics of these villages,selected the influence factors of the villages considering the classification characteristics,so as to explore the impact of different influence factors on its spatial distribution.The results showed(i)Key rural tourism villages in Beijing manifested an aggregated distribution on the whole,they were unevenly distributed and mostly located in the fringe area of northern mountainous areas and plains,such as Huairou District and Miyun District.Such a“multi-center distribution”pattern was significantly influenced by terrains and natural resources.(ii)Depending on local natural and cultural resources,tourism resources,development characteristics and functional differences,key rural tourism villages in Beijing could be devided into natural scenery type,scenic area-dependent type and agriculture experiencing type.(iii)Key factors influencing the distribution of these villages included mean temperature,annual precipitation,quantity of scenic area,road network density,agricultural land and so on,and the interaction of dual factors exerted more significant impact on single factors.
基金Under the auspices of the National Natural Science Foundation of China(No.42571228,42401212)National Natural Science Foundation of Shandong(No.ZR2024MD022)。
文摘Green innovation is an important driving force for high-quality development and an important guarantee for the revitalization of the old industrial base in Northeast China.However,research on green innovation is still insufficient.Using the super-efficiency epsilon-based measure Malmquist model,kernel density estimation,and spatial econometric model,this study investigated the spatiotemporal evolution characteristics and influencing factors of green innovation efficiency(GIE)in Northeast China from 2005 to 2020.The results reveal that:1)The GIE in Northeast China has obvious phased characteristics,where 2005-2011 was a period of fluctuating decline while 2012-2020 was a period of fluctuating increase,reflecting the severe resource and environmental constraints faced by the green innovation process.2)The GIE in the Northeast China has a significant spatial dependence,which has not formed a relatively stable spatial club feature.The process for improving the GIE in the Northeast China in the future is still arduous and far off.3)The interweaving and mutual influence of nonequilibrium factors have led to the diversity and complexity of the spatiotemporal pattern evolution of GIE.Overall,the level of economic development and industrial structure has a positive effect,while foreign investment and industrial agglomeration have a negative effect.The direct effects of government regulation,resource endowment,science and technology,environmental regulation,and urbanization are not significant.The research conclusion of this article can provide important reference for the revitalization of Northeast China.
基金Under the auspices of the National Natural Science Foundation of China(No.42071266)the Third Batch of Hebei Youth Top Talent ProjectNatural Science Foundation of Hebei Province(No.D2021205003)。
文摘The aviation industry has become one of the top ten greenhouse gas emission industries in the world. China’s aviation carbon emissions continue to increase, but the analysis of its influencing factors at the provincial level is still incomplete. This paper firstly uses Stochastic Impacts by Regression on Population, Affluence and Technology model(STIRPAT) model to analyze the time series evolution of China’s aviation carbon emissions from 2000 to 2019. Secondly, it uses the Logarithmic Mean Divisia Index(LDMI) model to analyze the influencing characteristics and degree of four factors on China’s aviation carbon emissions, which are air transportation revenue, aviation route structure, air transportation intensity and aviation energy intensity. Thirdly, it determines the various factors’ influencing direction and evolution trend of 31 provinces’ aviation carbon emissions in China(not including Hong Kong, Macao, Taiwan of China due to incomplete data). Finally, it derives the decoupling effort model and analyzes the decoupling relationship and decoupling effort degree between air carbon emissions and air transportation revenue in different provinces. The study found that from 2000 to2019, China’s total aviation carbon emissions continued to grow, while the growth rate of aviation carbon emissions showed a fluctuating downward trend. Air transportation revenue and aviation route structure promote the growth of total aviation carbon emissions, and air transportation intensity and aviation energy intensity have a restraining effect on the growth of total aviation carbon emissions. The scope of negative driving effect of air transportation revenue and air transportation intensity on total aviation carbon emissions in various provinces has increased. While the scope of positive driving influence of aviation route structure on total aviation carbon emissions of various provinces has increased, aviation energy intensity mainly has negative driving influence on total aviation carbon emissions of each province. Overall, the emission reduction trend in the areas to the west and north of the Qinling-Huaihe River Line is obvious. The decoupling mode between air carbon emissions and air transportation revenue in 31 provinces is mainly expansion negative decoupling.The air transportation intensity effect shows strong decoupling efforts in most provinces, the decoupling effort of aviation route structure effect and aviation energy intensity effect is not prominent.
基金Under the auspices of National Natural Science Foundation of China (No.42171188)Natural Science Foundation of Guangdong Province (No.2022A1515010992)。
文摘The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital financial inclusion relies on information technology to overcome spatial limitations. In this case, the research question is whether it adheres to the spatial laws governing conventional financial activities. This study uses exploratory spatial data analysis and a geographical detector to elucidate the spatiotemporal characteristics and factors influencing digital financial inclusion at the county level in China(Data don’t include that of Hong Kong, Macao and Taiwan of China) from 2014 to 2020. The research findings indicate: first, China’s county-level digital financial inclusion is generally increasing and exhibits significant spatial autocorrelation. Second, population density, level of traditional financial development, government regulation, and education level are key determinants of China’s county-level digital financial inclusion. Third,policies should be differentiated by region to narrow the spatial gap in digital financial inclusion. The results provide a reference for other developing countries on using digital technology to develop financial inclusion.
基金This study was supported by the National Natural Science Foundation of China(U1703241)the Key International Cooperation Project of Chinese Academy of Sciences(121311KYSB20160005)the Open Project of Xinjiang Uygur Autonomous Region Key Laboratory of China(2017D04010).
文摘Playing an important role in global warming and plant growth,relative humidity(RH)has profound impacts on production and living,and can be used as an integrated indicator for evaluating the wet-dry conditions in the arid and semi-arid area.However,information on the spatial-temporal variation and the influencing factors of RH in these regions is still limited.This study attempted to use daily meteorological data during 1966–2017 to reveal the spatial-temporal characteristics of RH in the arid region of Northwest China through rotated empirical orthogonal function and statistical analysis method,and the path analysis was used to clarify the impact of temperature(T),precipitation(P),actual evapotranspiration(ETa),wind speed(W)and sunshine duration(S)on RH.The results demonstrated that climatic conditions in North Xinjiang(NXJ)was more humid than those in Hexi Corridor(HXC)and South Xinjiang(SXJ).RH had a less significant downtrend in NXJ than that in HXC,but an increasingly rising trend was observed in SXJ during the last five decades,implying that HXC and NXJ were under the process of droughts,while SXJ was getting wetter.There was a turning point for the trend of RH in Xinjiang,which occurred in 2000.Path analysis indicated that RH was negatively correlated to T,ETa,W and S,but it increased with increase of P.S,T and W had the greatest direct effects on RH in HXC,NXJ and SXJ,respectively.ETa was the factor which had the greatest indirect effect on RH in HXC and NXJ,while T was the dominant factor in SXJ.
基金funded by the National Natural Science Foundation of China (Grant Nos. 41971015)Doctoral research program of China West Normal University (Grant Nos.19E067)。
文摘Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture(hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector(OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that:(1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km^(2). In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak.(2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced.(3) The results of OPGD detection in 2015 show that the influence of each factor is slope(0.2371) > traffic accessibility(0.2098) > population(0.1403) > regional GDP(0.1325) > elevation(0.0987) > poverty alleviation(0). The results of OPGD detection in 2020 show that the influence of each factor is slope(0.2339) > traffic accessibility(0.2198) > population(0.1432) > regional GDP(0.1219) > poverty alleviation(0.0992) > elevation(0.093). Natural geographical factors(slope and elevation) are the basic factors affecting the spatial distribution of rural settlements, and rural settlements are widely distributed in the river valley plain and the second half mountain area. Socioeconomic factors(traffic accessibility, population, and regional GDP) have a greater impact on the spatial distribution of rural settlements, which is an important factor affecting the spatial distribution of rural settlements. Policy factors such as poverty alleviation relocation have an indispensable impact on the spatial distribution of rural settlements. The research results can provide decisionmaking basis for the spatial arrangement of rural settlements in Liangshan Prefecture, and optimize the implementation of rural revitalization policies.
基金Under the auspices of National Natural Science Foundation of China(No.41771138,41801105)。
文摘Green development is an important issue of sustainable development in China.Due to the relatively backward economy and the fragile ecological environment,restricted development zones need to embrace green development.Taking 38 counties in Jilin Province as the empirical research objects,and based on cross-sectional data for each county in 2005,2010,and 2015,we accurately depicted the spatiotemporal evolutionary characteristics of green development efficiency(GDE)in restricted development zones of Jilin Province using the slacks-based measure-data envelope analysis(SBM-DEA)model.Moreover,the factors that influence GDE were further analyzed using the Tobit model.We found that:first,GDE showed a V-shaped trend in restricted development zones of Jilin Province.The differences in GDE in the eastern,central,and western Jilin Province increased gradually.Second,76%of counties in the restricted development zones had high or higher efficiencies.The resource-based cities were the main areas with low or lower GDE.Third,the economic development level was the core factor affecting GDE.Urbanization level had a significant negative effect on GDE in the restricted development zones.The effect of technological innovation level on GDE fluctuated,and we found that a‘backward mechanism’of technological innovation was beginning to form.Industrial structure and environmental governance had no significant effects on GDE.
基金Under the auspices of National Natural Science Foundation of China(No.41271182)
文摘The middle class in metropolitan Chinese cities has become an important social group. With the rapid development of urbanization and constant advancement of suburbanization, the middle class has increasingly come to influence city traffic. Research into middle-class commuting activities thus has practical significance for improving traffic congestion and reducing the commuting burden in metropolitan cities. Based on a dataset formed by 816 completed surveys, this paper analyzes the commuting mode, time and distance of middle-class residents in Guangzhou City using the descriptive statistical method. The results indicate that private cars are the main commuting mode, followed by public transport. Meanwhile, middle-class residents mainly undertake medium-short time and medium-short distance commuting. The study subsequently uses multilevel logistic regression and multiple linear regression models to analyze the factors that influence commuting mode choice, time and distance. The gender, age, number of family cars, housing source and jobs-housing balance are the most important factors influencing commuting mode choice; housing, population density, jobs-housing balance and commuting mode significantly affect commuting time; and transport accessibility, jobs-housing balance and commuting mode are the notable factors affecting commuting distance. Finally, this paper analyzes what is affecting the commuting activities of middle-class residents and determines the differences in commuting activity characteristics and influence factors between middle-class and ordinary residents. Policy suggestions to improve urban planning and urban management are also proposed.
文摘Eco-efficiency is an invaluable indicator for the measurement of the relationship between production activities and environmental depletion.This study measures the tourism eco-efficiency of 30 provinces in China from 2005 to 2020 based on the super-efficiency SBM model,and explores its spatial-temporal evolution characteristics using the kernel density function,standard deviation ellipse,and center of gravity model.Then,the influencing factors of the tourism eco-efficiency in China are analyzed by Tobit regression model.The results show that the tourism eco-efficiency of China is generally fluctuating upwards,but has not yet reached the maximum production possibility frontier.The kernel density curve shows a unimodal-bimodal-unimodal pattern,while the inter-provincial differences have been decreasing and becoming more balanced.The center of gravity of tourism eco-efficiency is located at the junction of Henan and Hubei province and generally moves to the south(slightly to the southwest).Meanwhile,it is revealed that the level of economic development and the tourism eco-efficiency has a significant inverted U-shaped relationship.The level of economic openness,traffic conditions,and tourism eco-efficiency is positively correlated.The environmental regulations and industrial structure have a negative but limited impact on tourism eco-efficiency.Finally,recommendations and suggestions for policy formulation to promote quality and sustainable development of the tourism industry are put forward,such as increasing investment in ecological protection and governance in tourism development,improving capacity-building in allocating green and low-carbon technologies and resources,strengthening tourism infrastructure construction,and enhancing environmental governance systems and mechanisms.
基金The National Basic Research Program of China(973 Program)(No.2012CB725400)
文摘In order to determine the regulations of the development of taxi supply under entry regulations in Chinese cities, an improved neural network model is applied to find the particular years when the government artificially puts new taxis into the market, and then extract the political influence from the taxi supply. The model is also utilized to study the relationships between the adjusted taxi supply and non-policy factors. A case study of Nanjing city is conducted. The results show that 2001 and 2007 are the particular years that the Nanjing government artificially put new taxis into its taxi market, which is in accordance with the five-year plan of China and the local development plans. The results also show that the improved neural network model has a good performance in expositing the evolution of adjusted taxi supply related to non-policy factors.
