This study developed a comprehensive system to evaluate the intensity of cropland use and evolution of cropland use in the Huang-Huai-Hai Plain.Delphi-entropy methods were adopted to determine the weight of the index,...This study developed a comprehensive system to evaluate the intensity of cropland use and evolution of cropland use in the Huang-Huai-Hai Plain.Delphi-entropy methods were adopted to determine the weight of the index,and the Geo Detector model was established to explore the influencing factors.The results are summarized as follows:(1) The intensity of inputs,degree of utilization,and production increased continuously,but the intensity of continuous conditions experienced an overall decline followed by a rebound towards the end of the study period.The number of counties with high and moderately high intensity increased by 56.8% and 14.6%,respectively,from 1996 to 2011.The number of counties with moderately low and low intensity declined by 35.9 % and 11.9 %,respectively.Areas with significant increases in intensity were mainly distributed in northeast Hebei Province,northwest Shandong Province,and north Jiangsu Province.The intensity is high in northern Jiangsu and Anhui;the output effect remained above moderate intensity mainly near Beijing,Tianjin,Tangshan,and counties in the suburbs of Shijiazhuang.(2) Natural disasters,elevation,slope,and road networks were the main factors influencing the intensity of cropland use in this region,with influence values of 0.158,0.143,0.129,and 0.054,respectively.Areas with moderately high and high levels of intensity were distributed in low-lying areas.Uneven distribution of precipitation,seasonal drought,and flood disasters can directly affect the stability index of croplands and reduce the intensity of cropland use.Developed road networks are associated with moderately high intensity.Our results suggest recommendations such as promoting agricultural intensification and large-scale management,promoting the construction of road networks,improving early warning systems for drought and flood disasters,and promoting moderate and intensive use of arable land,and focusing on restoration and sustainable use of cropland.展开更多
Currently, the historical archive images of Landsat family sensors are probably the most effective data products for tracking global longitudinal changes since the 1970 s. However, the issue of the degree and extent o...Currently, the historical archive images of Landsat family sensors are probably the most effective data products for tracking global longitudinal changes since the 1970 s. However, the issue of the degree and extent of cloud coverage is always a challenge and varies distinctively worldwide. So far, acquisition probability（AP） analyses of cloud cover（CC） of Landsat observations have been conducted with different sensors at regional scale. To our knowledge, CC probability analysis for the newly-launched Landsat-8 Operational Land Imager（OLI） across China is not reported. In this paper, monthly, seasonal, and annual APs for Landsat OLI（44,228 in total） images over China acquired from April 2013 to October 2016 with various CC thresholds were analyzed. The results showed that： first, the cumulative average APs of all OLI data over China at the CC thresholds ≤30% was about 49.6% which illustrated the availability of OLI imagery across China. Second, the spatial patterns of 10%, 20%, and 30% CC thresholds of OLI observations, coincided well with the precipitation distributions separated by the respective 200 mm, 400 mm, and 800 mm isohyetal lines. Third, the APs of images with the 30% CC threshold are the highest in autumn and winter especially in October of 58.7%, while the corresponding lowest probability occurred in June of 41.0%. Finally, the spatial differences in APs of targeted images with ≤30% CC thresholds were quite significant. At regional scales, the arid and semi-arid areas, Inland River and Songliao River basins, and northwestern side of the Hu Huanyong population line had the larger probabilities of obtaining high-quality images. Our study suggested that OLI imagery satisfy the data requirements needed for land surface monitoring, although there existed obvious spatio-temporal differences in APs over China at the 30% CC threshold.展开更多
Deterioration of city air quality is the serious problem in the process of rapid urbanization and economic development in China. Taking 74 cities that have implemented the new Ambient Air Quality Standards （GB3095- 2...Deterioration of city air quality is the serious problem in the process of rapid urbanization and economic development in China. Taking 74 cities that have implemented the new Ambient Air Quality Standards （GB3095- 2012） since 2013 as examples, using statistical and ArcGIS spatial analysis method, the multi-scale temporal and spatial variations characteristics and the impact of social and economic factors on urban air quality variations, are analyzed in this paper. The main research conclusions are as follows：（1） Air quality in Chinese cities shows very significant seasonal variations, with higher air quality in summer and autumn, and lower air quality in spring and winter; （2） Seen from a daily pollution perspective, air pollution is very serious and will tend to be more serious in the future; （3） Seen from an hourly variation perspective, urban air quality is time coupled with social production and urban living; （4） The overall spatial pattern of urban air quality is high in the east and north and low in the west and south, but with an obvious trend towards regional integration. （5） Cities in different regions have different factors that cause air quality variations. In general, urbanization level and energy consumption per GDP are the common factors.展开更多
Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LM...Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LMRB's terrestrial water storage anomaly(TWSA)and its spatio-temporal dynamics during 2002–2020.Considering the effects of natural factors and human activities,the respective contributions of climate variability and human activities to terrestrial water storage change(TWSC)were separated.Results showed that:(1)LMRB's TWSA decreased by 0.3158 cm/a.(2)TWSA showed a gradual increase in distribution from southwest of MRB to middle LMRB and from northeast of LRB to middle LMRB.TWSA positively changed in Myanmar while slightly changed in Laos and China.It negatively changed in Vietnam,Thailand and Cambodia.(3)TWSA components decreased in a descending order of soil moisture,groundwater and precipitation.(4)Natural factors had a substantial and spatial differentiated influence on TWSA over the LMRB.(5)Climate variability contributed 79%of TWSC in the LMRB while human activities contributed 21%with an increasing impact after 2008.The TWSC of upstream basin countries was found to be controlled by climate variability while Vietnam and Cambodia's TWSC has been controlled by human activities since 2012.展开更多
The pseudo-two-dimensional(P2D)model plays an important role in exploring physicochemical mechanisms,predicting the state of health,and improving the fast charge capability for Li-ion batteries(LIBs).However,the fast ...The pseudo-two-dimensional(P2D)model plays an important role in exploring physicochemical mechanisms,predicting the state of health,and improving the fast charge capability for Li-ion batteries(LIBs).However,the fast charge leads to the lithium concentration gradient in the solid and electrolyte phases and the non-uniform electrochemical reaction at the solid/electrolyte interface.In order to decouple charge transfer reactions in LIBs under dynamic conditions,understanding the spatio-temporal resolution of the P2D model is urgently required.Till now,the study of this aspect is still insufficient.This work studies the spatio-temporal resolution for dynamic/static electrochemical impedance spectroscopy(DEIS/SEIS)on multiple scales.In detail,DEIS and SEIS with spatio-temporal resolutions are used to decouple charge transfer reactions in LIBs based on the numerical solution of the P2D model in the frequency domain.The calculated results indicate that decoupling solid diffusion requires a high spatial resolution along the r-direction in particles,decoupling electrolyte diffusion and interfacial transfer reaction requires a high spatial resolution along the x-direction,and decoupling charge transfer reactions in LIBs at an extremely low state of charge(SOC)requires an extremely high temporal resolution along the t-direction.Finally,the optimal range of spatio-temporal resolutions for DEIS/SEIS is derived,and the method to decouple charge transfer reactions with spatio-temporal resolutions is developed.展开更多
This study proposes a novel forecasting framework that simultaneously captures the strong periodicity and irregular meteorological fluctuations inherent in solar radiation time series.Existing approaches typically def...This study proposes a novel forecasting framework that simultaneously captures the strong periodicity and irregular meteorological fluctuations inherent in solar radiation time series.Existing approaches typically define inter-regional correlations using either simple correlation coefficients or distance-based measures when applying spatio-temporal graph neural networks(STGNNs).However,such definitions are prone to generating spurious correlations due to the dominance of periodic structures.To address this limitation,we adopt the Elastic-Band Transform(EBT)to decompose solar radiation into periodic and amplitude-modulated components,which are then modeled independently with separate graph neural networks.The periodic component,characterized by strong nationwide correlations,is learned with a relatively simple architecture,whereas the amplitude-modulated component is modeled with more complex STGNNs that capture climatological similarities between regions.The predictions from the two components are subsequently recombined to yield final forecasts that integrate both periodic patterns and aperiodic variability.The proposed framework is validated with multiple STGNN architectures,and experimental results demonstrate improved predictive accuracy and interpretability compared to conventional methods.展开更多
AIM:To investigate the sex-specific correlation between systemic factors and retinal neurovascular alterations in individuals with type 1 diabetes mellitus(T1DM)who do not exhibit signs of diabetic retinopathy(DR).MET...AIM:To investigate the sex-specific correlation between systemic factors and retinal neurovascular alterations in individuals with type 1 diabetes mellitus(T1DM)who do not exhibit signs of diabetic retinopathy(DR).METHODS:A cohort participant without DR diagnosed with T1DM,underwent comprehensive ophthalmologic evaluation,optical coherence tomography angiography retinal structural and microvascular density analysis,and systemic parameter assessment.Multiple linear regression analysis was used to investigate the impact of systemic parameters on retinal alterations in distinct gender groups.RESULTS:A total of 182 individuals were included,consisting of 85 males(mean age 23.28±12.75y)and 97 females(mean age 22.98±13.68y).Males exhibited significantly greater thickness in both the internal retinal layer and the entire retina compared to females(P<0.01),whereas females had higher densities of deep retinal vessels and choroidal capillaries(P<0.05).Additionally,glycemic control was found to have a notable influence on retinal thickness in males(P<0.05),while insulin function had a more pronounced impact on retinal structure in females(P<0.01).Furthermore,a significant correlation was observed between thyroid function markers and retinal parameters in both male and female(P<0.05).CONCLUSION:Sex differences in alterations in retinal structure and microcirculation are observed in individuals with T1DM prior to the development of clinical DR,with a noted association between these changes and systemic parameters.展开更多
Residential energy-use behavior and energy-saving awareness play a crucial role in sustainable urban energy planning and building energy efficiency,particularly under the pressures of climate change.However,existing s...Residential energy-use behavior and energy-saving awareness play a crucial role in sustainable urban energy planning and building energy efficiency,particularly under the pressures of climate change.However,existing studies often lack comparative analysis of urban-rural differences and tend to focus excessively on behavior patterns while neglecting the dimension of energysaving awareness.With China’s urbanization rate reaching 66.16%,understanding such regional disparities has become increasingly important.To address these research gaps,this study conducts a large-scale survey on space cooling behaviors among residents in Beijing,a representative Chinese megacity.It should be noted that living standards in such megacities are generally higher than the national average,which may shape distinctive energy-use profiles.Analyzing 1573valid samples(1064 urban/442 rural)in 2024,this study employed K-Prototypes and K-Modes clustering to identify typical cooling behavior and energy-saving awareness pattems,followed by Kendall/Chi-square correlation tests and XGBoost importance analysis to determine key influencing factors,with subsequent urban-rural comparative analysis.Results indicate that urban residents are primarily heat-sensitive or heat-tolerant,with a secondary patten of mid-low temperature preference,and generally exhibit long cooling durations;rural behavior is dominated by heat-tolerant type,followed by heat-sensitive,mid-low temperature preference,and never-on types as secondary patterns;both urban and rural areas exhibit energy-savingawareness characterized by low consumption-lowwillingness,though urban areas show marginally higher motivation;energy-saving awareness correlates with cooling behavior in rural areas,but this relationship weakens significantly in urban contexts.展开更多
The Healthy China Initiative is a major health strategy being pursued by the country.To prevent and control different types of diseases as well as their complex variants,research on the spatio-temporal differentiation...The Healthy China Initiative is a major health strategy being pursued by the country.To prevent and control different types of diseases as well as their complex variants,research on the spatio-temporal differentiation among and mechanisms of influence of epidemic diseases is growing worldwide.This study analyzed monthly data on the incidence of influenza by using different methods,including Moran’s I,the hotspot analysis model,concentration analysis,and correlation analysis,to determine the characteristics of spatiotemporal differentiation in the incidence of influenza across prefecture-level cities in China from 2004 to 2017,and to examine its relationship with air pollution.According to the results,the overall incidence of influenza in China exhibited a trend of increase from 2004 to 2017,with small peaks in 2009 and 2014.More cases of influenza were recorded in the first and fourth quarters of each year.Regions with higher incidences of influenza were concentrated in northwestern and northern China,and in the coastal areas of southeastern China.Over time,the distribution of regions with a higher incidence of influenza has shifted from the west to the east of the country.A significant relationship was observed between the incidence of influenza and factors related to air pollution.The contents of five air pollutants(PM_(2.5),PM10,SO_(2),NO_(2),and CO)were significantly positively correlated with the incidence of influenza,with a decreasing order of contribution to it of SO_(2)>CO>NO_(2)>PM_(2.5)>PM_(10).The content of O_(3) in the air was negatively correlated with the incidence of influenza.The influence of air pollution-related factors on the incidence of influenza in different regions and seasons showed minor differences.The large-scale empirical results provided here can supply a scientific basis for governmental disease control authorities to formulate strategies for regional prevention and control.展开更多
The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to u...The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.展开更多
Based on air temperature observation data from 32 meteorological stations, temperature changes in the middle Qinling Mountains from 1959 to 2016 were analysed with respect to the north-south, seasonal and altitude dif...Based on air temperature observation data from 32 meteorological stations, temperature changes in the middle Qinling Mountains from 1959 to 2016 were analysed with respect to the north-south, seasonal and altitude differences. Our research mainly showed the following results. The annual temperature(TA) rose approximately 0.26℃/10 a within the past 58 years. This warming trend was stronger on the northern slope than on the southern slope, and a warming trend reversal occurred in 1994 on the northern slope, which was three years earlier than on the southern slope. The temperature changes for the four seasons were not synchronized, and the trend in spring contributed the most to the TA trend, followed by winter, autumn, and summer. The temperature difference between summer and winter(TDSW) decreased significantly over the past 58 years. The temperature change in the middle Qinling Mountains was clearly dependent on altitude. With increases in altitude, the TA increased gradually and became stronger while the TDSW decreased gradually and became weaker. Differences in temperature change between the north and south were mainly observed in low-altitude areas. With increase in altitude, the differences gradually tended to disappear.展开更多
This study explores the impact of intergenerational differences on farmers' terrace abandonment in response to increasing intergenerational differentiation among rural households and the practical issue of terrace...This study explores the impact of intergenerational differences on farmers' terrace abandonment in response to increasing intergenerational differentiation among rural households and the practical issue of terrace abandonment. Logit and Tobit models are employed to conduct empirical analysis and it is found that terrace abandonment increases sequentially among the new, middle, and old generations, confirming that intergenerational differences significantly influence whether farmers abandon terraces and the terrace abandonment scale. Village characteristics and government subsidies significantly influence farmers' terrace abandonment. An increase in the number of migrant workers in the village increases terrace abandonment among new and middle generation farmers, whereas an increase in the distance from the village to the county significantly increases terrace abandonment among old generation farmers. An increase in the village's total population significantly reduces terrace abandonment among new generation farmers. An increase in government subsidies significantly reduces terrace abandonment among middle and old generation farmers. The impact of intergenerational differences on terrace abandonment is more pronounced in low-altitude areas. To reduce terrace abandonment, it is necessary to promote terrace transfer, develop characteristic agriculture, improve terrace farming subsidies, and propose targeted strategies for the different generations of farmers.展开更多
Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB ...Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering.Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive(ST-CAR)model.Results Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000in 2019.Spatial hotspots were found in northeastern Guangdong,particularly in Heyuan,Shanwei,and Shantou,while Shenzhen,Dongguan,and Foshan had the lowest rates in the Pearl River Delta.The STCAR model showed that the TB risk was lower with higher per capita Gross Domestic Product(GDP)[Relative Risk(RR),0.91;95%Confidence Interval(CI):0.86–0.98],more the ratio of licensed physicians and physician(RR,0.94;95%CI:0.90-0.98),and higher per capita public expenditure(RR,0.94;95%CI:0.90–0.97),with a marginal effect of population density(RR,0.86;95%CI:0.86–1.00).Conclusion The incidence of TB in Guangdong varies spatially and temporally.Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection.Strategies focusing on equitable health resource distribution and economic development are the key to TB control.展开更多
Background: For nursing students, gathering social information is essential for understanding healthcare and social issues and developing critical thinking and decision-making skills. However, the choice of informatio...Background: For nursing students, gathering social information is essential for understanding healthcare and social issues and developing critical thinking and decision-making skills. However, the choice of information sources varies by age and individual habits. With the widespread use of the internet, there are notable differences between younger and older generations in their reliance on the internet versus traditional media sources like newspapers and television. Given the wide age range and diverse backgrounds of nursing students, understanding generational differences in information-gathering methods is important for implementing effective education. Purpose: The purpose of this study is to identify how nursing students in different age groups obtain social information and to examine media usage trends by age group. Additionally, we aim to use the findings to provide insights into effective information dissemination methods in nursing education. Results: The results showed that nursing students in their teens to forties, regardless of gender, primarily relied on the internet as their main information source, with television playing a secondary role. In contrast, students in their fifties tended to obtain information more often from newspapers and television than from the internet. This highlights an age-related difference in preferred information sources, with older students showing a greater reliance on traditional media. Conclusions: This study demonstrates that nursing students use different information-gathering methods based on their age, suggesting a need to custo-mize information dissemination strategies in nursing education. Digital media may be more effective for younger students, while traditional media or printed materials might better serve older students. Educational institutions should consider these generational differences in media usage and adopt strategies that meet the diverse needs of their student populations.展开更多
This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in So...This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in Sonipat have undergone notable transformation,as open spaces and agricultural lands are increasingly converted into residential colonies,commercial hubs,and industrial zones.While such changes reflect economic development and urban growth,they also raise critical concerns about sustainability,especially in terms of food security,groundwater depletion,and environmental degradation.The study examines land use changes between 2000 and 2024 using remote sensing techniques and spatial analysis.It further incorporates secondary data and insights from community-level interactions to assess the socio-economic and ecological impacts of this transformation.The findings indicate rising land fragmentation,loss of agricultural livelihoods,pressure on civic infrastructure,and increasing pollution—factors that threaten long-term regional sustainability.The study underscores the urgent need to reconcile urban development with environmental and social sustainability.By offering a detailed case study of Sonipat,this research contributes to the broader discourse on India’s urbanisation pathways.It aims to provide policymakers,planners,and researchers with evidence-based recommendations to manage land transitions more responsibly,promoting urban growth models that ensure ecological integrity,equitable development,and long-term resilience.展开更多
As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limi...As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limits their ability to capture temporal differences between frames.Current methods also exhibit limited generalization capabilities,struggling to detect content generated by unknown forgery algorithms.Moreover,the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content(AIGC)present significant challenges for traditional detection frameworks,whichmust balance high detection accuracy with robust performance.To address these challenges,we propose a novel Deepfake detection framework that combines a two-stream convolutional network with a Vision Transformer(ViT)module to enhance spatio-temporal feature representation.The ViT model extracts spatial features from the forged video,while the 3D convolutional network captures temporal features.The 3D convolution enables cross-frame feature extraction,allowing the model to detect subtle facial changes between frames.The confidence scores from both the ViT and 3D convolution submodels are fused at the decision layer,enabling themodel to effectively handle unknown forgery techniques.Focusing on Deepfake videos and GAN-generated images,the proposed approach is evaluated on two widely used public face forgery datasets.Compared to existing state-of-theartmethods,it achieves higher detection accuracy and better generalization performance,offering a robust solution for deepfake detection in real-world scenarios.展开更多
Objective:Near vision loss(NVL)is one of the leading causes of visual impairment worldwide,exerting a profound impact on individual quality of life and socio-economic development.This study aims to analyze the burden ...Objective:Near vision loss(NVL)is one of the leading causes of visual impairment worldwide,exerting a profound impact on individual quality of life and socio-economic development.This study aims to analyze the burden of NVL in China by sex and age groups from 1990 to 2021 and to project trends over the next 15 years.Methods:Using data from the Global Burden of Disease(GBD)2021 database,we conducted descriptive analyses of NVL prevalence in China,calculated age-standardized prevalence rates(ASPR)and age-standardized disability-adjusted life years rates(ASDR)to compare burden differences between sexes and age groups,and applied an autoregressive integrated moving average(ARIMA)model to predict NVL trends for the next 15 years.The model selection was based on best-fit criteria to ensure reliable projections.Results:From 1990 to 2021,China’s ASPR of NVL rose from 10096.24/100000 to 15624.54/100000,and ASDR increased from 101.75/100000 to 158.75/100000.In 2021,ASPR(16551.70/100000)and ASDR(167.69/100000)were higher among females than males(14686.21/100000 and 149.76/100000,respectively).China ranked highest globally in both NVL cases and disability-adjusted life years(DALYs),with female burden significantly exceeding male burden.Projections indicated this trend and sex gap will persist until 2036.Compared with 1990,the prevalence cases and DALYs increased by 239.20%and 238.82%,respectively in 2021,with the highest burden among females and the 55−59 age group.The ARIMA model predicted continued increases in prevalence and DALYs by 2036,with females maintaining a higher burden than males.Conclusion:This study reveals a marked increase in the NVL burden in China and predicts continued growth in the coming years.Public health policies should prioritize NVL prevention and control,with special attention to women and middle-aged populations to mitigate long-term societal and health impacts.展开更多
Sandfly fever is a viral infectious disease transmitted by sand flies that is widely prevalent in tropical and subtropical regions.Previous studies on its infection mechanism,immune response and diagnosis and treatmen...Sandfly fever is a viral infectious disease transmitted by sand flies that is widely prevalent in tropical and subtropical regions.Previous studies on its infection mechanism,immune response and diagnosis and treatment methods were lack of systematic.This study applied spatio-temporal omics technology to comprehensively explain the dynamic changes of immunity in the incubation period,exacerbation period,peak period and recovery period of Sandfl y fever,and integrated with diff erent coping strategies.To provide new research ideas for its overall research.展开更多
基金Project of Ministry of Education Humanities and Social Sciences,No.16YJCZH082,No.16YJC630149
文摘This study developed a comprehensive system to evaluate the intensity of cropland use and evolution of cropland use in the Huang-Huai-Hai Plain.Delphi-entropy methods were adopted to determine the weight of the index,and the Geo Detector model was established to explore the influencing factors.The results are summarized as follows:(1) The intensity of inputs,degree of utilization,and production increased continuously,but the intensity of continuous conditions experienced an overall decline followed by a rebound towards the end of the study period.The number of counties with high and moderately high intensity increased by 56.8% and 14.6%,respectively,from 1996 to 2011.The number of counties with moderately low and low intensity declined by 35.9 % and 11.9 %,respectively.Areas with significant increases in intensity were mainly distributed in northeast Hebei Province,northwest Shandong Province,and north Jiangsu Province.The intensity is high in northern Jiangsu and Anhui;the output effect remained above moderate intensity mainly near Beijing,Tianjin,Tangshan,and counties in the suburbs of Shijiazhuang.(2) Natural disasters,elevation,slope,and road networks were the main factors influencing the intensity of cropland use in this region,with influence values of 0.158,0.143,0.129,and 0.054,respectively.Areas with moderately high and high levels of intensity were distributed in low-lying areas.Uneven distribution of precipitation,seasonal drought,and flood disasters can directly affect the stability index of croplands and reduce the intensity of cropland use.Developed road networks are associated with moderately high intensity.Our results suggest recommendations such as promoting agricultural intensification and large-scale management,promoting the construction of road networks,improving early warning systems for drought and flood disasters,and promoting moderate and intensive use of arable land,and focusing on restoration and sustainable use of cropland.
基金National Natural Science Foundation of China,No.41430861National Key Research and Development Program of China,No.2016YFC0503500Opening Fund of Key Laboratory of Poyang Lake Wetland and Watershed Research,Ministry of Education,Jiangxi Normal University,No.PK2016004
文摘Currently, the historical archive images of Landsat family sensors are probably the most effective data products for tracking global longitudinal changes since the 1970 s. However, the issue of the degree and extent of cloud coverage is always a challenge and varies distinctively worldwide. So far, acquisition probability（AP） analyses of cloud cover（CC） of Landsat observations have been conducted with different sensors at regional scale. To our knowledge, CC probability analysis for the newly-launched Landsat-8 Operational Land Imager（OLI） across China is not reported. In this paper, monthly, seasonal, and annual APs for Landsat OLI（44,228 in total） images over China acquired from April 2013 to October 2016 with various CC thresholds were analyzed. The results showed that： first, the cumulative average APs of all OLI data over China at the CC thresholds ≤30% was about 49.6% which illustrated the availability of OLI imagery across China. Second, the spatial patterns of 10%, 20%, and 30% CC thresholds of OLI observations, coincided well with the precipitation distributions separated by the respective 200 mm, 400 mm, and 800 mm isohyetal lines. Third, the APs of images with the 30% CC threshold are the highest in autumn and winter especially in October of 58.7%, while the corresponding lowest probability occurred in June of 41.0%. Finally, the spatial differences in APs of targeted images with ≤30% CC thresholds were quite significant. At regional scales, the arid and semi-arid areas, Inland River and Songliao River basins, and northwestern side of the Hu Huanyong population line had the larger probabilities of obtaining high-quality images. Our study suggested that OLI imagery satisfy the data requirements needed for land surface monitoring, although there existed obvious spatio-temporal differences in APs over China at the 30% CC threshold.
基金National Natural Sciences Foundation of China(A Study on the resource-environment base for the Modern Man-Land Relationship in China,No.8122015)
文摘Deterioration of city air quality is the serious problem in the process of rapid urbanization and economic development in China. Taking 74 cities that have implemented the new Ambient Air Quality Standards （GB3095- 2012） since 2013 as examples, using statistical and ArcGIS spatial analysis method, the multi-scale temporal and spatial variations characteristics and the impact of social and economic factors on urban air quality variations, are analyzed in this paper. The main research conclusions are as follows：（1） Air quality in Chinese cities shows very significant seasonal variations, with higher air quality in summer and autumn, and lower air quality in spring and winter; （2） Seen from a daily pollution perspective, air pollution is very serious and will tend to be more serious in the future; （3） Seen from an hourly variation perspective, urban air quality is time coupled with social production and urban living; （4） The overall spatial pattern of urban air quality is high in the east and north and low in the west and south, but with an obvious trend towards regional integration. （5） Cities in different regions have different factors that cause air quality variations. In general, urbanization level and energy consumption per GDP are the common factors.
基金National Natural Science Foundation of China,No.42161006Yunnan Fundamental Research Projects No.202201AT070094,No.202301BF070001-004+1 种基金Special Project for High-level Talents of Yunnan Province for Young Top Talents,No.C6213001159European Research Council(ERC)Starting-Grant STORIES,No.101040939。
文摘Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LMRB's terrestrial water storage anomaly(TWSA)and its spatio-temporal dynamics during 2002–2020.Considering the effects of natural factors and human activities,the respective contributions of climate variability and human activities to terrestrial water storage change(TWSC)were separated.Results showed that:(1)LMRB's TWSA decreased by 0.3158 cm/a.(2)TWSA showed a gradual increase in distribution from southwest of MRB to middle LMRB and from northeast of LRB to middle LMRB.TWSA positively changed in Myanmar while slightly changed in Laos and China.It negatively changed in Vietnam,Thailand and Cambodia.(3)TWSA components decreased in a descending order of soil moisture,groundwater and precipitation.(4)Natural factors had a substantial and spatial differentiated influence on TWSA over the LMRB.(5)Climate variability contributed 79%of TWSC in the LMRB while human activities contributed 21%with an increasing impact after 2008.The TWSC of upstream basin countries was found to be controlled by climate variability while Vietnam and Cambodia's TWSC has been controlled by human activities since 2012.
基金supported by the National Natural Science Foundation of China(Nos.22479092 and 22078190)。
文摘The pseudo-two-dimensional(P2D)model plays an important role in exploring physicochemical mechanisms,predicting the state of health,and improving the fast charge capability for Li-ion batteries(LIBs).However,the fast charge leads to the lithium concentration gradient in the solid and electrolyte phases and the non-uniform electrochemical reaction at the solid/electrolyte interface.In order to decouple charge transfer reactions in LIBs under dynamic conditions,understanding the spatio-temporal resolution of the P2D model is urgently required.Till now,the study of this aspect is still insufficient.This work studies the spatio-temporal resolution for dynamic/static electrochemical impedance spectroscopy(DEIS/SEIS)on multiple scales.In detail,DEIS and SEIS with spatio-temporal resolutions are used to decouple charge transfer reactions in LIBs based on the numerical solution of the P2D model in the frequency domain.The calculated results indicate that decoupling solid diffusion requires a high spatial resolution along the r-direction in particles,decoupling electrolyte diffusion and interfacial transfer reaction requires a high spatial resolution along the x-direction,and decoupling charge transfer reactions in LIBs at an extremely low state of charge(SOC)requires an extremely high temporal resolution along the t-direction.Finally,the optimal range of spatio-temporal resolutions for DEIS/SEIS is derived,and the method to decouple charge transfer reactions with spatio-temporal resolutions is developed.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(RS-2023-00249743).
文摘This study proposes a novel forecasting framework that simultaneously captures the strong periodicity and irregular meteorological fluctuations inherent in solar radiation time series.Existing approaches typically define inter-regional correlations using either simple correlation coefficients or distance-based measures when applying spatio-temporal graph neural networks(STGNNs).However,such definitions are prone to generating spurious correlations due to the dominance of periodic structures.To address this limitation,we adopt the Elastic-Band Transform(EBT)to decompose solar radiation into periodic and amplitude-modulated components,which are then modeled independently with separate graph neural networks.The periodic component,characterized by strong nationwide correlations,is learned with a relatively simple architecture,whereas the amplitude-modulated component is modeled with more complex STGNNs that capture climatological similarities between regions.The predictions from the two components are subsequently recombined to yield final forecasts that integrate both periodic patterns and aperiodic variability.The proposed framework is validated with multiple STGNN architectures,and experimental results demonstrate improved predictive accuracy and interpretability compared to conventional methods.
基金Supported by Natural Science Foundation of Hunan Province(No.2023JJ70017No.2025JJ50627)Peak Climbing Project of Optometry Hospital Affiliated to Wenzhou Medical University。
文摘AIM:To investigate the sex-specific correlation between systemic factors and retinal neurovascular alterations in individuals with type 1 diabetes mellitus(T1DM)who do not exhibit signs of diabetic retinopathy(DR).METHODS:A cohort participant without DR diagnosed with T1DM,underwent comprehensive ophthalmologic evaluation,optical coherence tomography angiography retinal structural and microvascular density analysis,and systemic parameter assessment.Multiple linear regression analysis was used to investigate the impact of systemic parameters on retinal alterations in distinct gender groups.RESULTS:A total of 182 individuals were included,consisting of 85 males(mean age 23.28±12.75y)and 97 females(mean age 22.98±13.68y).Males exhibited significantly greater thickness in both the internal retinal layer and the entire retina compared to females(P<0.01),whereas females had higher densities of deep retinal vessels and choroidal capillaries(P<0.05).Additionally,glycemic control was found to have a notable influence on retinal thickness in males(P<0.05),while insulin function had a more pronounced impact on retinal structure in females(P<0.01).Furthermore,a significant correlation was observed between thyroid function markers and retinal parameters in both male and female(P<0.05).CONCLUSION:Sex differences in alterations in retinal structure and microcirculation are observed in individuals with T1DM prior to the development of clinical DR,with a noted association between these changes and systemic parameters.
文摘Residential energy-use behavior and energy-saving awareness play a crucial role in sustainable urban energy planning and building energy efficiency,particularly under the pressures of climate change.However,existing studies often lack comparative analysis of urban-rural differences and tend to focus excessively on behavior patterns while neglecting the dimension of energysaving awareness.With China’s urbanization rate reaching 66.16%,understanding such regional disparities has become increasingly important.To address these research gaps,this study conducts a large-scale survey on space cooling behaviors among residents in Beijing,a representative Chinese megacity.It should be noted that living standards in such megacities are generally higher than the national average,which may shape distinctive energy-use profiles.Analyzing 1573valid samples(1064 urban/442 rural)in 2024,this study employed K-Prototypes and K-Modes clustering to identify typical cooling behavior and energy-saving awareness pattems,followed by Kendall/Chi-square correlation tests and XGBoost importance analysis to determine key influencing factors,with subsequent urban-rural comparative analysis.Results indicate that urban residents are primarily heat-sensitive or heat-tolerant,with a secondary patten of mid-low temperature preference,and generally exhibit long cooling durations;rural behavior is dominated by heat-tolerant type,followed by heat-sensitive,mid-low temperature preference,and never-on types as secondary patterns;both urban and rural areas exhibit energy-savingawareness characterized by low consumption-lowwillingness,though urban areas show marginally higher motivation;energy-saving awareness correlates with cooling behavior in rural areas,but this relationship weakens significantly in urban contexts.
基金Under the auspices of Key Program of National Natural Science Foundation of China(No.41630749)Program of the National Social Science Fund of China(No.17BJL051)Fundamental Research Funds for the Central Universities(No.1709103,2412020FZ001)。
文摘The Healthy China Initiative is a major health strategy being pursued by the country.To prevent and control different types of diseases as well as their complex variants,research on the spatio-temporal differentiation among and mechanisms of influence of epidemic diseases is growing worldwide.This study analyzed monthly data on the incidence of influenza by using different methods,including Moran’s I,the hotspot analysis model,concentration analysis,and correlation analysis,to determine the characteristics of spatiotemporal differentiation in the incidence of influenza across prefecture-level cities in China from 2004 to 2017,and to examine its relationship with air pollution.According to the results,the overall incidence of influenza in China exhibited a trend of increase from 2004 to 2017,with small peaks in 2009 and 2014.More cases of influenza were recorded in the first and fourth quarters of each year.Regions with higher incidences of influenza were concentrated in northwestern and northern China,and in the coastal areas of southeastern China.Over time,the distribution of regions with a higher incidence of influenza has shifted from the west to the east of the country.A significant relationship was observed between the incidence of influenza and factors related to air pollution.The contents of five air pollutants(PM_(2.5),PM10,SO_(2),NO_(2),and CO)were significantly positively correlated with the incidence of influenza,with a decreasing order of contribution to it of SO_(2)>CO>NO_(2)>PM_(2.5)>PM_(10).The content of O_(3) in the air was negatively correlated with the incidence of influenza.The influence of air pollution-related factors on the incidence of influenza in different regions and seasons showed minor differences.The large-scale empirical results provided here can supply a scientific basis for governmental disease control authorities to formulate strategies for regional prevention and control.
文摘The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.
基金National Forestry Public Welfare Industry Scientific Research Project of China,No.201304309。
文摘Based on air temperature observation data from 32 meteorological stations, temperature changes in the middle Qinling Mountains from 1959 to 2016 were analysed with respect to the north-south, seasonal and altitude differences. Our research mainly showed the following results. The annual temperature(TA) rose approximately 0.26℃/10 a within the past 58 years. This warming trend was stronger on the northern slope than on the southern slope, and a warming trend reversal occurred in 1994 on the northern slope, which was three years earlier than on the southern slope. The temperature changes for the four seasons were not synchronized, and the trend in spring contributed the most to the TA trend, followed by winter, autumn, and summer. The temperature difference between summer and winter(TDSW) decreased significantly over the past 58 years. The temperature change in the middle Qinling Mountains was clearly dependent on altitude. With increases in altitude, the TA increased gradually and became stronger while the TDSW decreased gradually and became weaker. Differences in temperature change between the north and south were mainly observed in low-altitude areas. With increase in altitude, the differences gradually tended to disappear.
基金Key Program of National Natural Science Foundation of China,No.41930757National Natural Science Foundation of China,No.42371285。
文摘This study explores the impact of intergenerational differences on farmers' terrace abandonment in response to increasing intergenerational differentiation among rural households and the practical issue of terrace abandonment. Logit and Tobit models are employed to conduct empirical analysis and it is found that terrace abandonment increases sequentially among the new, middle, and old generations, confirming that intergenerational differences significantly influence whether farmers abandon terraces and the terrace abandonment scale. Village characteristics and government subsidies significantly influence farmers' terrace abandonment. An increase in the number of migrant workers in the village increases terrace abandonment among new and middle generation farmers, whereas an increase in the distance from the village to the county significantly increases terrace abandonment among old generation farmers. An increase in the village's total population significantly reduces terrace abandonment among new generation farmers. An increase in government subsidies significantly reduces terrace abandonment among middle and old generation farmers. The impact of intergenerational differences on terrace abandonment is more pronounced in low-altitude areas. To reduce terrace abandonment, it is necessary to promote terrace transfer, develop characteristic agriculture, improve terrace farming subsidies, and propose targeted strategies for the different generations of farmers.
基金supported by the Guangdong Provincial Clinical Research Center for Tuberculosis(No.2020B1111170014)。
文摘Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering.Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive(ST-CAR)model.Results Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000in 2019.Spatial hotspots were found in northeastern Guangdong,particularly in Heyuan,Shanwei,and Shantou,while Shenzhen,Dongguan,and Foshan had the lowest rates in the Pearl River Delta.The STCAR model showed that the TB risk was lower with higher per capita Gross Domestic Product(GDP)[Relative Risk(RR),0.91;95%Confidence Interval(CI):0.86–0.98],more the ratio of licensed physicians and physician(RR,0.94;95%CI:0.90-0.98),and higher per capita public expenditure(RR,0.94;95%CI:0.90–0.97),with a marginal effect of population density(RR,0.86;95%CI:0.86–1.00).Conclusion The incidence of TB in Guangdong varies spatially and temporally.Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection.Strategies focusing on equitable health resource distribution and economic development are the key to TB control.
文摘Background: For nursing students, gathering social information is essential for understanding healthcare and social issues and developing critical thinking and decision-making skills. However, the choice of information sources varies by age and individual habits. With the widespread use of the internet, there are notable differences between younger and older generations in their reliance on the internet versus traditional media sources like newspapers and television. Given the wide age range and diverse backgrounds of nursing students, understanding generational differences in information-gathering methods is important for implementing effective education. Purpose: The purpose of this study is to identify how nursing students in different age groups obtain social information and to examine media usage trends by age group. Additionally, we aim to use the findings to provide insights into effective information dissemination methods in nursing education. Results: The results showed that nursing students in their teens to forties, regardless of gender, primarily relied on the internet as their main information source, with television playing a secondary role. In contrast, students in their fifties tended to obtain information more often from newspapers and television than from the internet. This highlights an age-related difference in preferred information sources, with older students showing a greater reliance on traditional media. Conclusions: This study demonstrates that nursing students use different information-gathering methods based on their age, suggesting a need to custo-mize information dissemination strategies in nursing education. Digital media may be more effective for younger students, while traditional media or printed materials might better serve older students. Educational institutions should consider these generational differences in media usage and adopt strategies that meet the diverse needs of their student populations.
文摘This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in Sonipat have undergone notable transformation,as open spaces and agricultural lands are increasingly converted into residential colonies,commercial hubs,and industrial zones.While such changes reflect economic development and urban growth,they also raise critical concerns about sustainability,especially in terms of food security,groundwater depletion,and environmental degradation.The study examines land use changes between 2000 and 2024 using remote sensing techniques and spatial analysis.It further incorporates secondary data and insights from community-level interactions to assess the socio-economic and ecological impacts of this transformation.The findings indicate rising land fragmentation,loss of agricultural livelihoods,pressure on civic infrastructure,and increasing pollution—factors that threaten long-term regional sustainability.The study underscores the urgent need to reconcile urban development with environmental and social sustainability.By offering a detailed case study of Sonipat,this research contributes to the broader discourse on India’s urbanisation pathways.It aims to provide policymakers,planners,and researchers with evidence-based recommendations to manage land transitions more responsibly,promoting urban growth models that ensure ecological integrity,equitable development,and long-term resilience.
基金supported by National Natural Science Foundation of China(Nos.62477026,62177029,61807020)Humanities and Social Sciences Research Program of the Ministry of Education of China(No.23YJAZH047)the Startup Foundation for Introducing Talent of Nanjing University of Posts and Communications under Grant NY222034.
文摘As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limits their ability to capture temporal differences between frames.Current methods also exhibit limited generalization capabilities,struggling to detect content generated by unknown forgery algorithms.Moreover,the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content(AIGC)present significant challenges for traditional detection frameworks,whichmust balance high detection accuracy with robust performance.To address these challenges,we propose a novel Deepfake detection framework that combines a two-stream convolutional network with a Vision Transformer(ViT)module to enhance spatio-temporal feature representation.The ViT model extracts spatial features from the forged video,while the 3D convolutional network captures temporal features.The 3D convolution enables cross-frame feature extraction,allowing the model to detect subtle facial changes between frames.The confidence scores from both the ViT and 3D convolution submodels are fused at the decision layer,enabling themodel to effectively handle unknown forgery techniques.Focusing on Deepfake videos and GAN-generated images,the proposed approach is evaluated on two widely used public face forgery datasets.Compared to existing state-of-theartmethods,it achieves higher detection accuracy and better generalization performance,offering a robust solution for deepfake detection in real-world scenarios.
基金supported by the Natural Science Foundation of Hunan Province(2023JJ30817)Hunan Provincial Natural Science Foundation-Hengyang City Joint Fund Project(2025JJ70129)+1 种基金Changsha Natural Science Foundation(kq2403057)China。
文摘Objective:Near vision loss(NVL)is one of the leading causes of visual impairment worldwide,exerting a profound impact on individual quality of life and socio-economic development.This study aims to analyze the burden of NVL in China by sex and age groups from 1990 to 2021 and to project trends over the next 15 years.Methods:Using data from the Global Burden of Disease(GBD)2021 database,we conducted descriptive analyses of NVL prevalence in China,calculated age-standardized prevalence rates(ASPR)and age-standardized disability-adjusted life years rates(ASDR)to compare burden differences between sexes and age groups,and applied an autoregressive integrated moving average(ARIMA)model to predict NVL trends for the next 15 years.The model selection was based on best-fit criteria to ensure reliable projections.Results:From 1990 to 2021,China’s ASPR of NVL rose from 10096.24/100000 to 15624.54/100000,and ASDR increased from 101.75/100000 to 158.75/100000.In 2021,ASPR(16551.70/100000)and ASDR(167.69/100000)were higher among females than males(14686.21/100000 and 149.76/100000,respectively).China ranked highest globally in both NVL cases and disability-adjusted life years(DALYs),with female burden significantly exceeding male burden.Projections indicated this trend and sex gap will persist until 2036.Compared with 1990,the prevalence cases and DALYs increased by 239.20%and 238.82%,respectively in 2021,with the highest burden among females and the 55−59 age group.The ARIMA model predicted continued increases in prevalence and DALYs by 2036,with females maintaining a higher burden than males.Conclusion:This study reveals a marked increase in the NVL burden in China and predicts continued growth in the coming years.Public health policies should prioritize NVL prevention and control,with special attention to women and middle-aged populations to mitigate long-term societal and health impacts.
基金College Students Innovation and Entrepreneurship Training Program(X202511049398)College Students Innovation and Entrepreneurship Training Program(X202511049201)+1 种基金College Students Innovation and Entrepreneurship Training Program(X202511258005S)University-Level Research Funding Program of Hainan Science and Technology Vocational University(HKKY2024-87)。
文摘Sandfly fever is a viral infectious disease transmitted by sand flies that is widely prevalent in tropical and subtropical regions.Previous studies on its infection mechanism,immune response and diagnosis and treatment methods were lack of systematic.This study applied spatio-temporal omics technology to comprehensively explain the dynamic changes of immunity in the incubation period,exacerbation period,peak period and recovery period of Sandfl y fever,and integrated with diff erent coping strategies.To provide new research ideas for its overall research.
