Rural industrial development and ecological civilization transformation are crucial to China's comprehensive advancement of rural revitalization. However, many regions still face the issue of a conflict between ec...Rural industrial development and ecological civilization transformation are crucial to China's comprehensive advancement of rural revitalization. However, many regions still face the issue of a conflict between economic development and ecological protection. Symbiosis theory provides a new perspective for understanding the interactive relationship of rural industry and ecology(RIE). Jiangxi Province, one of China's first national pilot zones for ecological conservation, exemplifies rural areas' typical challenges in balancing industrial development and ecological protection, and has been selected as the study area. By integrating the characteristics of RIE with symbiosis theory, a comprehensive RIE assessment framework was constructed. The comprehensive model, spatial autocorrelation method, and symbiosis theory model were employed to address the spatio-temporal evolution characteristics of RIE, reveal the symbiotic relationship(SR) and the symbiosis types of RIE, and explore the path of symbiotic development between RIE. Results indicated that:(1) Since 2015, RIE has shown an upward trend, with regional differences in ecological development levels gradually shrinking. Significant spatial correlation and agglomeration characteristics exist, but a coordinated regional development pattern has not yet emerged.(2) Overall, the symbiosis degree(SD) between RIE showed a positive trend with narrowing gaps, the symbiosis coefficient(SC) of industry to ecology converged to 0.5 under a positive asymmetric mutualism(PAM) mode, suggesting that their relationship tended to be coordinated. Specifically, rural ecology grew increasingly influential on industry in most counties.(3) Rural areas were classified into different types led by industry-dominated PAM, and various optimization paths were proposed. Future efforts should promote the equalization of the interaction forces between RIE according to local conditions.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
Hepatocellular carcinoma(HCC)is a pressing global health problem and is the sixth most common cancer and the third leading cause of cancer mortality worldwide.Despite continuous advances in treatment modalities,the 5-...Hepatocellular carcinoma(HCC)is a pressing global health problem and is the sixth most common cancer and the third leading cause of cancer mortality worldwide.Despite continuous advances in treatment modalities,the 5-year survival rate is low with a high propensity for recurrence and metastasis1.This clinical challenge in treating HCC is largely attributed to the heterogeneity and intrinsic therapy resistance of cancer stem cells(CSCs),which are a subpopulation of cells with self-renewal capability and multidirectional differentiation potential to induce tumorigenicity2.The behavior and maintenance of CSCs are not autonomous but critically dependent on the complex bidirectional crosstalk between CSCs and the tumor immune microenvironment(TIME)1.In this review we first summarize the recent progress in characterizing CSCs and the interactions between CSCs and the TIME in HCC.Next,we discuss the emerging therapeutic strategies targeting CSC populations with the ongoing challenges.Finally,we give our perspectives on the future directions in HCC CSC research.展开更多
It is urgent and important to explore the dynamic evolution in comprehensive transportation green efficiency(CTGE)in the context of green development.We constructed a social development index that reflects the social ...It is urgent and important to explore the dynamic evolution in comprehensive transportation green efficiency(CTGE)in the context of green development.We constructed a social development index that reflects the social benefits of transportation services,and incorporated it into the comprehensive transportation efficiency evaluation framework as an expected output.Based on the panel data of 30 regions in China from 2003-2018,the CTGE in China was measured using the slacks-based measure-data envelopment analysis(SBM-DEA)model.Further,the dynamic evolution trends of CTGE were determined using the spatial Markov model and exploratory spatio-temporal data analysis(ESTDA)technique from a spatio-temporal perspective.The results showed that the CTGE shows a U-shaped change trend but with an overall low level and significant regional differences.The state transition of CTGE has a strong spatial dependence,and there exists the phenomenon of“club convergence”.Neighbourhood background has a significant impact on the CTGE transition types,and the spatial spillover effect is pronounced.The CTGE has an obvious positive correlation and spatial agglomeration characteristics.The geometric characteristics of the LISA time path show that the evolution process of local spatial structure and local spatial dependence of China’s CTGE is stable,but the integration of spatial evolution is weak.The spatio-temporal transition results of LISA indicate that the CTGE has obvious transfer inertness and has certain path-dependence and spatial locking characteristics,which will become the major difficulty in improving the CTGE.展开更多
Exploring the spatio-temporal dynamics of poverty is important for research on sustainable poverty reduction in China. Based on the perspective of development geography, this paper proposes a panel vector autoregressi...Exploring the spatio-temporal dynamics of poverty is important for research on sustainable poverty reduction in China. Based on the perspective of development geography, this paper proposes a panel vector autoregressive(PVAR) model that combines the human development approach with the global indicator framework for Sustainable Development Goals(SDGs) to identify the poverty-causing and the poverty-reducing factors in China. The aim is to measure the multidimensional poverty index(MPI) of China’s provinces from 2007 to 2017, and use the exploratory spatio-temporal data analysis(ESTDA) method to reveal the characteristics of the spatio-temporal dynamics of multidimensional poverty. The results show the following:(1) The poverty-causing factors in China include the high social gross dependency ratio and crop-to-disaster ratio, and the poverty-reducing factors include the high per capita GDP, per capita social security expenditure, per capita public health expenditure, number of hospitals per 10,000 people, rate of participation in the new rural cooperative medical scheme, vegetation coverage, per capita education expenditure, number of universities, per capita research and development(R&D) expenditure, and funding per capita for cultural undertakings.(2) From 2007 to 2017, provincial income poverty(IP), health poverty(HP), cultural poverty(CP), and multidimensional poverty have been significantly reduced in China, and the overall national poverty has dropped by 5.67% annually. there is a differentiation in poverty along different dimensions in certain provinces.(3) During the study period, the local spatial pattern of multidimensional poverty between provinces showed strong spatial dynamics, and a trend of increase from the eastern to the central and western regions was noted. The MPI among provinces exhibited a strong spatial dependence over time to form a pattern of decrease from northwestern and northeastern China to the surrounding areas.(4) The spatio-temporal networks of multidimensional poverty in adjacent provinces were mainly negatively correlated, with only Shaanxi and Henan, Shaanxi and Ningxia, Qinghai and Gansu, Hubei and Anhui, Sichuan and Guizhou, and Hainan and Guangdong forming spatially strong cooperative poverty reduction relationships. These results have important reference value for the implementation of China’s poverty alleviation strategy.展开更多
Based on the adaptive analysis paradigm,this paper constructs an evaluation index system and an evaluation model of the level of industrial ecology of a restricted development zone from the perspective of the industri...Based on the adaptive analysis paradigm,this paper constructs an evaluation index system and an evaluation model of the level of industrial ecology of a restricted development zone from the perspective of the industrial system and of the environmental system,and studies the spatial-temporal differentiation characteristics and the driving factors of the level of industrial ecology of the restricted development zone of the Shandong Province,China,by using a variety of measurement methods.The results show that:1)In the temporal dimension,the level of industrial ecology of the research area increased from 2005 to 2017,while in the regional dimension,it was higher in the eastern coastal areas,followed by the northwestern area and the southwestern area;2)In the spatial dimension,from 2005 to 2017 the level of industrial ecology of the research area had a clear spatial dependence,and the regional spatial agglomeration of the restricted development zones with similar industrial ecology levels become increasingly evident;3)On the whole,the industrial ecology level in the study area had a clear spatial differentiation pattern,as it was higher in the north and in the east and lower in the south and in the west.Moreover,its evolution model changed from a‘three-core driven model’to a‘spatial scattered mosaic distribution model’,and then to a‘single-core driven model’;4)Industrial ecology was positively correlated with economic development,foreign investment,science and technology,and negatively correlated with the government role,while industrial structure and environmental regulation failed to pass the statistical significance test.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 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
Allogeneic hematopoietic cell transplantation(allo-HCT) remains a cornerstone therapy for severe hematologic malignancies, offering a potential cure when conventional therapies are ineffective. However, not all patien...Allogeneic hematopoietic cell transplantation(allo-HCT) remains a cornerstone therapy for severe hematologic malignancies, offering a potential cure when conventional therapies are ineffective. However, not all patients are suitable recipients of allo-HCT, particularly the elderly patients and those with high comorbidity burdens.Furthermore, patients who develop relapse or graft failure after initial transplantation encounter additional challenges when evaluated for a second transplant.展开更多
Objective To explore the impact of mergers and acquisitions(M&A)on the innovation performance of the companies from both a patent perspective and a financial perspective by taking the case of M&A Company J as ...Objective To explore the impact of mergers and acquisitions(M&A)on the innovation performance of the companies from both a patent perspective and a financial perspective by taking the case of M&A Company J as an example.Methods The literature research method,patent data analysis method,and financial data analysis method were used.Results:The M&A has a positive impact on the innovation performance of Company J,and the results from the patent perspective and the financial perspective are consistent.Results and Conclusion The literature research method,patent data analysis method,and financial data analysis method were used.The M&A has a positive impact on the innovation performance of Company J,and the results from the patent perspective and the financial perspective are consistent.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
Hardship The Double Take column looks at a single topic from an African and Chinese perspective.This month,we explore whether enduring hardship is still a necessary path to growth in a changing world.
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
Sodium-sulfur(Na-S)batteries are considered as a promising successor to the next-generation of high-capacity,low-cost and environmentally friendly sulfur-based battery systems.However,Na-S batteries still suffer from ...Sodium-sulfur(Na-S)batteries are considered as a promising successor to the next-generation of high-capacity,low-cost and environmentally friendly sulfur-based battery systems.However,Na-S batteries still suffer from the“shuttle effect”and sluggish ion transport kinetics due to the dissolution of sodium polysulfides and poor conductivity of sulfur.MXenes,as 2D transition metal carbides/nitrides,have exhibited excellent conductivity,diverse structure and tunable surface groups,particularly playing a crucial role in inhibiting polysulfide shuttle and sodium dendrite growth.In this review,achievements and advancements of MXene-based Na-S batteries are discussed,including applications of a sulfur cathode,separator,interlayer between separator and cathode,and sodium anode.In the end,perspectives and challenges on the future development of MXene-based materials in Na-S batteries are proposed.展开更多
Objective:This study aims to explore the experiences of social alienation among adolescents with depression,providing practical This study aims to explore the experiences of social alienation among adolescents with de...Objective:This study aims to explore the experiences of social alienation among adolescents with depression,providing practical This study aims to explore the experiences of social alienation among adolescents with depression,providing practical guidance for improving their interpersonal relationships and facilitating their reintegration into society.Methods:This qualitative research was conducted following the conventional content analysis method.20 adolescents with depression were employed to select from June to August 2024 for face-to-face semi-structured interviews.The collected data were analyzed using Colaizzi's seven-step method.Results:Three themes and eight sub-themes were analyzed and identified:individual level(feelings of helplessness and powerlessness,cognitive distortion,avoidance and withdrawal),family level(lack of family awareness,family conflict),social level(limitations of academic stress and social circle,lack and degradation of skills,generalization of virtual reality,social“stigma”).Conclusion:Adolescents with depression experience complex social alienation.Healthcare providers should enhance their self-awareness and social adaptation skills,improve family dynamics,and provide a comprehensive range of services and services to help them to cope with the challenges of depression.Healthcare providers should enhance their self-awareness and social adaptation skills,improve family dynamics,strengthen communication,bolster family support systems,and collaborate to develop comprehensive social networks and psychological services.This will create a supportive social atmosphere to help adolescents gradually alleviate their feelings of social alienation.展开更多
Driven by the goal of carbon neutrality,prefabricated buildings,as an important form of green construction,have become a key focus in the study of lifecycle carbon footprint management.Based on this,this paper starts ...Driven by the goal of carbon neutrality,prefabricated buildings,as an important form of green construction,have become a key focus in the study of lifecycle carbon footprint management.Based on this,this paper starts from the perspective of carbon footprint and combines the digital and visual advantages of BIM technology to construct a green evaluation system for prefabricated buildings.It explores the carbon emissions in each stage of the building and proposes corresponding improvement measures,aiming to provide necessary references for the low-carbon transformation of prefabricated buildings.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
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
Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing...Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing on 31 provincial-level regions in China,this study uses the Exploratory Spatio-temporal Data Analysis(ESTDA)and Panel Quantile Regression(PQR)model to analyze the spatio-temporal interaction characteristics and influencing factors of ACI in China from 2004 to 2023.The findings are as follows:(1)ACI showed an overall downward trend,and the spatial distribution pattern was characterized by“high in the western region and low along the southeastern coast”.Although the overall disparity tended to converge,some high-carbon-intensity regions exhibited extreme trends.ACI displayed clear spatial directionality,with the spatial center shifting steadily toward the northeast.(2)Regions in the northwest,northeast,and central-south parts exhibited strong local spatial structural dynamics,and the local spatial dependence of ACI in each region showed a nonlinear trend.Generally speaking,the spatial association pattern demonstrated a certain degree of inertia in spatial transfer,reflecting strong path dependence or spatial lock-in characteristics.(3)Optimization of industrial structure and improvement in agricultural mechanization will increase ACI,while economic development can effectively reduce it.The impact of urbanization on ACI exhibits a nonlinear pattern.The coordinated development of economic growth and urbanization significantly reduces ACI,with a stronger emission reduction observed in regions with low ACI.The optimization of industrial structure,when combined with urbanization and environmental regulation,contributes to significant emission reductions particularly in high-ACI areas.Similarly,the synergy between agricultural mechanization and urbanization effectively lowers emissions in low-ACI regions,though this effect diminishes in areas with higher ACI.展开更多
基金supported by the National Natural Science Foundation of China (No.42361050,42201232)Humanities and Social Sciences Research Project of Jiangxi Colleges and Universities (No.JC24211)+1 种基金Science and Technology Research Project of Jiangxi Provincial Department of Education (No.GJJ2200553)Jiangxi provincial Social Science Foundation of China (No.23JL11)。
文摘Rural industrial development and ecological civilization transformation are crucial to China's comprehensive advancement of rural revitalization. However, many regions still face the issue of a conflict between economic development and ecological protection. Symbiosis theory provides a new perspective for understanding the interactive relationship of rural industry and ecology(RIE). Jiangxi Province, one of China's first national pilot zones for ecological conservation, exemplifies rural areas' typical challenges in balancing industrial development and ecological protection, and has been selected as the study area. By integrating the characteristics of RIE with symbiosis theory, a comprehensive RIE assessment framework was constructed. The comprehensive model, spatial autocorrelation method, and symbiosis theory model were employed to address the spatio-temporal evolution characteristics of RIE, reveal the symbiotic relationship(SR) and the symbiosis types of RIE, and explore the path of symbiotic development between RIE. Results indicated that:(1) Since 2015, RIE has shown an upward trend, with regional differences in ecological development levels gradually shrinking. Significant spatial correlation and agglomeration characteristics exist, but a coordinated regional development pattern has not yet emerged.(2) Overall, the symbiosis degree(SD) between RIE showed a positive trend with narrowing gaps, the symbiosis coefficient(SC) of industry to ecology converged to 0.5 under a positive asymmetric mutualism(PAM) mode, suggesting that their relationship tended to be coordinated. Specifically, rural ecology grew increasingly influential on industry in most counties.(3) Rural areas were classified into different types led by industry-dominated PAM, and various optimization paths were proposed. Future efforts should promote the equalization of the interaction forces between RIE according to local conditions.
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 the Hong Kong Research Grants Council Theme-based Research Scheme(Grant No.T12-716/22-R)Innovation and Technology Commission grant for State Key Laboratory of Liver Research(Grant No.ITC PD/17-9)University Development Fund of The University of Hong Kong,and Loke Yew Endowed Professorship award.I.O.L.Ng is Loke Yew Professor in Pathology.
文摘Hepatocellular carcinoma(HCC)is a pressing global health problem and is the sixth most common cancer and the third leading cause of cancer mortality worldwide.Despite continuous advances in treatment modalities,the 5-year survival rate is low with a high propensity for recurrence and metastasis1.This clinical challenge in treating HCC is largely attributed to the heterogeneity and intrinsic therapy resistance of cancer stem cells(CSCs),which are a subpopulation of cells with self-renewal capability and multidirectional differentiation potential to induce tumorigenicity2.The behavior and maintenance of CSCs are not autonomous but critically dependent on the complex bidirectional crosstalk between CSCs and the tumor immune microenvironment(TIME)1.In this review we first summarize the recent progress in characterizing CSCs and the interactions between CSCs and the TIME in HCC.Next,we discuss the emerging therapeutic strategies targeting CSC populations with the ongoing challenges.Finally,we give our perspectives on the future directions in HCC CSC research.
基金National Key Research and Development Program of China(2019YFB1600400)National Natural Science Foundation of China(72174035)+2 种基金National Natural Science Foundation of China(71774018)Liaoning Revitalization Talents Program(XLYC2008030)Liaoning Provincial Natural Science Foundation Shipping Joint Foundation Program(2020-HYLH-20)。
文摘It is urgent and important to explore the dynamic evolution in comprehensive transportation green efficiency(CTGE)in the context of green development.We constructed a social development index that reflects the social benefits of transportation services,and incorporated it into the comprehensive transportation efficiency evaluation framework as an expected output.Based on the panel data of 30 regions in China from 2003-2018,the CTGE in China was measured using the slacks-based measure-data envelopment analysis(SBM-DEA)model.Further,the dynamic evolution trends of CTGE were determined using the spatial Markov model and exploratory spatio-temporal data analysis(ESTDA)technique from a spatio-temporal perspective.The results showed that the CTGE shows a U-shaped change trend but with an overall low level and significant regional differences.The state transition of CTGE has a strong spatial dependence,and there exists the phenomenon of“club convergence”.Neighbourhood background has a significant impact on the CTGE transition types,and the spatial spillover effect is pronounced.The CTGE has an obvious positive correlation and spatial agglomeration characteristics.The geometric characteristics of the LISA time path show that the evolution process of local spatial structure and local spatial dependence of China’s CTGE is stable,but the integration of spatial evolution is weak.The spatio-temporal transition results of LISA indicate that the CTGE has obvious transfer inertness and has certain path-dependence and spatial locking characteristics,which will become the major difficulty in improving the CTGE.
基金National Natural Science Foundation of China,No.71974070, No.41501593National Key R&D Project,No.2016YFA0602500Humanities and Social Sciences Foundation of Ministry of Education of China,No.19YJCZH068。
文摘Exploring the spatio-temporal dynamics of poverty is important for research on sustainable poverty reduction in China. Based on the perspective of development geography, this paper proposes a panel vector autoregressive(PVAR) model that combines the human development approach with the global indicator framework for Sustainable Development Goals(SDGs) to identify the poverty-causing and the poverty-reducing factors in China. The aim is to measure the multidimensional poverty index(MPI) of China’s provinces from 2007 to 2017, and use the exploratory spatio-temporal data analysis(ESTDA) method to reveal the characteristics of the spatio-temporal dynamics of multidimensional poverty. The results show the following:(1) The poverty-causing factors in China include the high social gross dependency ratio and crop-to-disaster ratio, and the poverty-reducing factors include the high per capita GDP, per capita social security expenditure, per capita public health expenditure, number of hospitals per 10,000 people, rate of participation in the new rural cooperative medical scheme, vegetation coverage, per capita education expenditure, number of universities, per capita research and development(R&D) expenditure, and funding per capita for cultural undertakings.(2) From 2007 to 2017, provincial income poverty(IP), health poverty(HP), cultural poverty(CP), and multidimensional poverty have been significantly reduced in China, and the overall national poverty has dropped by 5.67% annually. there is a differentiation in poverty along different dimensions in certain provinces.(3) During the study period, the local spatial pattern of multidimensional poverty between provinces showed strong spatial dynamics, and a trend of increase from the eastern to the central and western regions was noted. The MPI among provinces exhibited a strong spatial dependence over time to form a pattern of decrease from northwestern and northeastern China to the surrounding areas.(4) The spatio-temporal networks of multidimensional poverty in adjacent provinces were mainly negatively correlated, with only Shaanxi and Henan, Shaanxi and Ningxia, Qinghai and Gansu, Hubei and Anhui, Sichuan and Guizhou, and Hainan and Guangdong forming spatially strong cooperative poverty reduction relationships. These results have important reference value for the implementation of China’s poverty alleviation strategy.
基金Under the auspices of National Natural Science Foundation of China(No.41801105,41771138)National Natural Science Foundation of Shandong(No.ZR2018BD002)Social Science Planning Research Project of Shandong(No.18DJJJ14)。
文摘Based on the adaptive analysis paradigm,this paper constructs an evaluation index system and an evaluation model of the level of industrial ecology of a restricted development zone from the perspective of the industrial system and of the environmental system,and studies the spatial-temporal differentiation characteristics and the driving factors of the level of industrial ecology of the restricted development zone of the Shandong Province,China,by using a variety of measurement methods.The results show that:1)In the temporal dimension,the level of industrial ecology of the research area increased from 2005 to 2017,while in the regional dimension,it was higher in the eastern coastal areas,followed by the northwestern area and the southwestern area;2)In the spatial dimension,from 2005 to 2017 the level of industrial ecology of the research area had a clear spatial dependence,and the regional spatial agglomeration of the restricted development zones with similar industrial ecology levels become increasingly evident;3)On the whole,the industrial ecology level in the study area had a clear spatial differentiation pattern,as it was higher in the north and in the east and lower in the south and in the west.Moreover,its evolution model changed from a‘three-core driven model’to a‘spatial scattered mosaic distribution model’,and then to a‘single-core driven model’;4)Industrial ecology was positively correlated with economic development,foreign investment,science and technology,and negatively correlated with the government role,while industrial structure and environmental regulation failed to pass the statistical significance test.
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.
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supported by National Natural Science Foundation of China (No. 82370215).
文摘Allogeneic hematopoietic cell transplantation(allo-HCT) remains a cornerstone therapy for severe hematologic malignancies, offering a potential cure when conventional therapies are ineffective. However, not all patients are suitable recipients of allo-HCT, particularly the elderly patients and those with high comorbidity burdens.Furthermore, patients who develop relapse or graft failure after initial transplantation encounter additional challenges when evaluated for a second transplant.
文摘Objective To explore the impact of mergers and acquisitions(M&A)on the innovation performance of the companies from both a patent perspective and a financial perspective by taking the case of M&A Company J as an example.Methods The literature research method,patent data analysis method,and financial data analysis method were used.Results:The M&A has a positive impact on the innovation performance of Company J,and the results from the patent perspective and the financial perspective are consistent.Results and Conclusion The literature research method,patent data analysis method,and financial data analysis method were used.The M&A has a positive impact on the innovation performance of Company J,and the results from the patent perspective and the financial perspective are consistent.
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Hardship The Double Take column looks at a single topic from an African and Chinese perspective.This month,we explore whether enduring hardship is still a necessary path to growth in a changing world.
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 the National Natural Science Foundation of China(Nos.51972198 and 61633015)the Natural Science Foundation of Shandong Province(No.ZR2020JQ19)+1 种基金Taishan Scholars Program of Shandong Province(No.ts20190908)Shenzhen Fundamental Research Program(No.JCYJ20190807093405503).
文摘Sodium-sulfur(Na-S)batteries are considered as a promising successor to the next-generation of high-capacity,low-cost and environmentally friendly sulfur-based battery systems.However,Na-S batteries still suffer from the“shuttle effect”and sluggish ion transport kinetics due to the dissolution of sodium polysulfides and poor conductivity of sulfur.MXenes,as 2D transition metal carbides/nitrides,have exhibited excellent conductivity,diverse structure and tunable surface groups,particularly playing a crucial role in inhibiting polysulfide shuttle and sodium dendrite growth.In this review,achievements and advancements of MXene-based Na-S batteries are discussed,including applications of a sulfur cathode,separator,interlayer between separator and cathode,and sodium anode.In the end,perspectives and challenges on the future development of MXene-based materials in Na-S batteries are proposed.
基金2024 Annual project of National Social Science Foundation“Research on Problem Identification and Governance Countermeasures of Minor Mental Health Network Support”(Project No.:24BXW044).
文摘Objective:This study aims to explore the experiences of social alienation among adolescents with depression,providing practical This study aims to explore the experiences of social alienation among adolescents with depression,providing practical guidance for improving their interpersonal relationships and facilitating their reintegration into society.Methods:This qualitative research was conducted following the conventional content analysis method.20 adolescents with depression were employed to select from June to August 2024 for face-to-face semi-structured interviews.The collected data were analyzed using Colaizzi's seven-step method.Results:Three themes and eight sub-themes were analyzed and identified:individual level(feelings of helplessness and powerlessness,cognitive distortion,avoidance and withdrawal),family level(lack of family awareness,family conflict),social level(limitations of academic stress and social circle,lack and degradation of skills,generalization of virtual reality,social“stigma”).Conclusion:Adolescents with depression experience complex social alienation.Healthcare providers should enhance their self-awareness and social adaptation skills,improve family dynamics,and provide a comprehensive range of services and services to help them to cope with the challenges of depression.Healthcare providers should enhance their self-awareness and social adaptation skills,improve family dynamics,strengthen communication,bolster family support systems,and collaborate to develop comprehensive social networks and psychological services.This will create a supportive social atmosphere to help adolescents gradually alleviate their feelings of social alienation.
文摘Driven by the goal of carbon neutrality,prefabricated buildings,as an important form of green construction,have become a key focus in the study of lifecycle carbon footprint management.Based on this,this paper starts from the perspective of carbon footprint and combines the digital and visual advantages of BIM technology to construct a green evaluation system for prefabricated buildings.It explores the carbon emissions in each stage of the building and proposes corresponding improvement measures,aiming to provide necessary references for the low-carbon transformation of prefabricated buildings.
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.
基金National Natural Science Foundation of China,No.42230106,No.42171250State Key Laboratory of Earth Surface Processes and Resource Ecology,No.2022-ZD-04。
文摘Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing on 31 provincial-level regions in China,this study uses the Exploratory Spatio-temporal Data Analysis(ESTDA)and Panel Quantile Regression(PQR)model to analyze the spatio-temporal interaction characteristics and influencing factors of ACI in China from 2004 to 2023.The findings are as follows:(1)ACI showed an overall downward trend,and the spatial distribution pattern was characterized by“high in the western region and low along the southeastern coast”.Although the overall disparity tended to converge,some high-carbon-intensity regions exhibited extreme trends.ACI displayed clear spatial directionality,with the spatial center shifting steadily toward the northeast.(2)Regions in the northwest,northeast,and central-south parts exhibited strong local spatial structural dynamics,and the local spatial dependence of ACI in each region showed a nonlinear trend.Generally speaking,the spatial association pattern demonstrated a certain degree of inertia in spatial transfer,reflecting strong path dependence or spatial lock-in characteristics.(3)Optimization of industrial structure and improvement in agricultural mechanization will increase ACI,while economic development can effectively reduce it.The impact of urbanization on ACI exhibits a nonlinear pattern.The coordinated development of economic growth and urbanization significantly reduces ACI,with a stronger emission reduction observed in regions with low ACI.The optimization of industrial structure,when combined with urbanization and environmental regulation,contributes to significant emission reductions particularly in high-ACI areas.Similarly,the synergy between agricultural mechanization and urbanization effectively lowers emissions in low-ACI regions,though this effect diminishes in areas with higher ACI.
