As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limite...As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.展开更多
In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed p...In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed panel data from the Yellow River(YR)region from 2013 to 2021 and discovered notable spatial variances in the composite index and coupling coordination of the two systems.Specifically,the downstream region exhibited the highest coupling coordination,while the upstream region had the lowest.We identified that favorable factors such as economic development,innovation,industrial upgrading,and government intervention can bolster the coupling.Our findings provide a valuable framework for promoting DE and HQD in the YR region.展开更多
In this study,we performed a systematic analysis of the multiplicity dependence of hadron production at mid-rapidity(|y|<0.5),ranging from the light to the charm sector in proton-proton(pp)collisions at√s=13 TeV.T...In this study,we performed a systematic analysis of the multiplicity dependence of hadron production at mid-rapidity(|y|<0.5),ranging from the light to the charm sector in proton-proton(pp)collisions at√s=13 TeV.This study used a multi-phase transport(AMPT)model coupled with PYTHIA8 initial conditions.We investigated the baryon-to-meson and the strange-to-non-strange meson ratios varying with the charged particle density.By tuning the coalescence parameters,the AMPT model provides a reasonable description of the experimental data for the inclusive production of both light and charm hadrons,comparable to the string fragmentation model calculations with color reconnection effects.Additionally,we analyzed the relative production of hadrons by examining the self-normalized particle ratios as a function of the charged hadron density.Our findings suggest that parton evolution effects and the coalescence hadronization process in the AMPT model result in a strong flavor hierarchy in the multiplicity dependence of the baryon-to-meson ratio.Furthermore,our investigation of the p_(T) differential double ratio of the baryon-to-meson fraction between high-and low-multiplicity events revealed distinct modifications to the flavor associated baryon-to-meson ratio p_(T) shape in high-multiplicity events when comparing the coalescence hadronization model to the color reconnection model.These observations highlight the importance of understanding the hadronization process in high-energy pp collisions through comprehensive multiplicity-dependent multi-flavor analysis.展开更多
Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address ...Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.展开更多
OBJECTIVE:To observe the effect of different acupuncture frequencies on the abstinence rate which could be used as a reference for optimizing acupuncture cessation programs.METHODS:From July 2018 to June 2022,a total ...OBJECTIVE:To observe the effect of different acupuncture frequencies on the abstinence rate which could be used as a reference for optimizing acupuncture cessation programs.METHODS:From July 2018 to June 2022,a total of 220 smokers were recruited based on inclusion criteria and randomly divided into the high-frequency acupuncture group(HF group,n=110):5 times a week from the 1st to the 4th week,from weeks 5 to 8,three times a week and the low-frequency acupuncture group(LF group,n=110):3 times a week from the 1st to the 4th week,from weeks 5 to 8,twice a week,then treated for 8 weeks and followup at 1 month in Beijing.RESULTS:In total,162 subjects completed the whole study with a drop-out rate of 20.45%.The expiratory CO point abstinence rate was HF group 53/110(48.18%)vs LF group 41/110(37.27%)in Week 8(P=0.102)and HF group 46/110(41.82%)vs LF group 45/110(40.91%)in Week 12(P=0.891)and the HF acupuncture and LF acupuncture were nearly equal in the 8-week abstinence rate.In addition,both HF and LF acupuncture significantly reduced Fagerstr?m test for nicotine dependence scale(FTND)scores(P<0.05),Minnesota nicotine withdrawal scale(MNWS)scores(P<0.05),and Brief Questionnaire of Smoking Urges scale(QSU-Brief)scores(P<0.05),but HF acupuncture showed some superiority over LF acupuncture in relieving patients'smoking cravings(P<0.05).CONCLUSIONS:The study initially showed that both high-frequency acupuncture and low-frequency acupuncture treatment were safe and effective on smoking cessation for 8 weeks,but high-frequency acupuncture was advantageous in reducing smoking cravings.More accurate acupuncture frequency needs to be validated through larger clinical studies to optimize acupuncture smoking cessation programs.展开更多
Nanomaterials have garnered recognition for their notable surface effects and demonstration of superior mechanical properties.Previous studies on the surface effects of nanomaterials,employing the finite element metho...Nanomaterials have garnered recognition for their notable surface effects and demonstration of superior mechanical properties.Previous studies on the surface effects of nanomaterials,employing the finite element method,often relied on simplified twodimensional models due to theoretical complexities.Consequently,these simplified models inadequately represent the mechanical properties of nanomaterials and fail to capture the substantial impact of surface effects,particularly the curvature dependence of nanosurfaces.This study applies the principle of minimum energy and leverages the Steigmann-Ogden surface theory of nanomaterials to formulate a novel finite element surface element that comprehensively accounts for surface effects.We conducted an analysis of the stress distribution and deformation characteristics of four typical 2D and 3D nanomaterial models.The accuracy of the developed surface element and finite element calculation method was verified through comparison with established references.The resulting finite element model provides a robust and compelling scientific approach for accurately predicting the mechanical performance of nanomaterials.展开更多
Objective:To evaluate the global liter-ature output on the relationship between brain-derived neurotrophic factor(BDNF)and cognitive function in al-cohol dependence syndrome using bibliometric methods and explore the ...Objective:To evaluate the global liter-ature output on the relationship between brain-derived neurotrophic factor(BDNF)and cognitive function in al-cohol dependence syndrome using bibliometric methods and explore the status and trends in this field.Method:The literature on the application of BDNF in cognitive impairment caused by alcohol dependence syndrome published from 1995 to 2023 were retrieved from Web of Science,and the relevant information(publication characteristics,country and institution,author,number of publications,citation,journal and research field,corresponding author,key words,etc.)was recorded.The bibliometrix R package was used for quantitative and qualitative analysis of publication output and author contributions.Result:A total of 99 articles were included.The overall number of publications in this field has increased over time.The countries and institutions that contributed the most to the field were the United States and the Academy of Medical Sciences of Iranian universities,respectively.Most of the authors were from the United States,followed by Spain,China,and Iran.Ceccanti M,Fiore M were the most productive authors.Publications with Ceccanti M had the highest h-index.The most cited reference author is Haenninen H(227 citations),and the number one published journal is Alcohol.Most articles were published in 2020(n=12)and 2022(n=11),followed by 2019 and 2021(n=10).The corresponding author has the largest number of publications from the United States,and more publications from a single country tend to have more cooperation from other countries.BDNF and alcohol appeared more frequently in various keyword clouds.However,significant differences remained in the author keyword cloud,keyword plus word cloud,and paper topic word cloud.Conclusion:BDNF has great potential in the application of cognitive dysfunction caused by alcohol dependence syndrome.Bibliometric methods and data visualization techniques can help understand the current state of research progress and enable relevant scholars and practitioners to predict the development trends in this field.展开更多
The post-fledging period, extending from fledging to independence, is a crucial life stage characterized by high mortality due to fledglings' limited mobility and inexperience. During this stage, fledglings gradua...The post-fledging period, extending from fledging to independence, is a crucial life stage characterized by high mortality due to fledglings' limited mobility and inexperience. During this stage, fledglings gradually increase their mobility, leave their parents, disperse from their natal site, and respond to the challenges of new environments. Characterizing these post-fledging movements and space use is essential for understanding juvenile survival strategies and devising targeted conservation measures. The Crested Ibis (Nipponia nippon), an endangered species and a highly protected animals at the national level in China, has seen limited research on its post-fledging movements and space use. From 2015 to 2023, we utilized biologgers, combined with field surveys, to study the movement and space use characteristics of 37 fledglings in Hanzhong City, Shaanxi Province, China, over a two-month post-fledging period. We quantified changes in activity levels (based on overall dynamic body acceleration), independence timing, onset of post-fledging dispersal, habitat selection, and daily activity rhythms after independence. Our results revealed individuals began independent living 26.23 ± 2.34 days post-fledging and onset of dispersal at 25.58 ± 2.33 days, with a range area at the natal of 2.08 ± 0.56 km^(2). The initial 30 days post-fledging are characterized as an ontogenetic phase marked by a rapid increase in body activity level. Fledglings preferred paddy fields during the independent period rather than the forests they relied on before independence. Interestingly, the daily activity rhythm, particularly foraging behavior, peaked at noon—contrasting with the expected morning and evening activity peaks—likely as an adaptation to avoid periods of peak human activity. Additionally, drowning, collisions, and predation in paddy fields are noteworthy causes of fledgling mortality. Consequently, we recommend protecting a 2-km^(2) area around the nest site for at least two-month post-fledging, implementing safety measures around power lines and cesspools. Additionally, reducing human disturbances near foraging habitats and expanding space within paddy fields would help mitigate survival pressures on fledglings.展开更多
This paper investigates the spatial-temporal cooperative guidance problem for multiple flight vehicles without relying on time-to-go information.First,a two-stage cooperative guidance strategy,namely the cooperative g...This paper investigates the spatial-temporal cooperative guidance problem for multiple flight vehicles without relying on time-to-go information.First,a two-stage cooperative guidance strategy,namely the cooperative guidance and the Proportional Navigation Guidance(PNG)stage strategy,is developed to realize the spatial-temporal constraints in two dimensions.At the former stage,two controllers are designed and superimposed to satisfy both impact time consensus and impact angle constraints.Once the convergent conditions are satisfied,the flight vehicles will switch to the PNG stage to ensure zero miss distance.To further extend the results to three dimensions,a planar pursuit guidance stage is additionally imposed at the beginning of guidance.Due to the inde-pendence of time-to-go estimation,the proposed guidance strategy possesses great performance in satisfying complex spatial-temporal constraints even under flight speed variation.Finally,several numerical simulations are implemented to verify the effectiveness and advantages of the proposed results under different scenarios.展开更多
In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal ...In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal graph.Most GCNs define the graph topology by physical relations of the human joints.However,this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs,resulting in a low recognition rate for specific actions with implicit correlation between joint pairs.In addition,existing methods ignore the trend correlation between adjacent frames within an action and context clues,leading to erroneous action recognition with similar poses.Therefore,this study proposes a learnable GCN based on behavior dependence,which considers implicit joint correlation by constructing a dynamic learnable graph with extraction of specific behavior dependence of joint pairs.By using the weight relationship between the joint pairs,an adaptive model is constructed.It also designs a self-attention module to obtain their inter-frame topological relationship for exploring the context of actions.Combining the shared topology and the multi-head self-attention map,the module obtains the context-based clue topology to update the dynamic graph convolution,achieving accurate recognition of different actions with similar poses.Detailed experiments on public datasets demonstrate that the proposed method achieves better results and realizes higher quality representation of actions under various evaluation protocols compared to state-of-the-art methods.展开更多
Forest fires pose a significant threat to human life and property,so the utilization of unmanned aircraft systems provides new ways for forest firefighting.Given the constrained load capacities of these aircraft,aeria...Forest fires pose a significant threat to human life and property,so the utilization of unmanned aircraft systems provides new ways for forest firefighting.Given the constrained load capacities of these aircraft,aerial refueling becomes crucial to extend their operational time and range.In order to address the complexities of firefighting missions involving multi-receiver and multi-tanker deployed from various airports,first,a fuel consumption calculation model for aerial refueling scheduling is established based on the receiver path.Then,two distinct methods,including an integrated one and a decomposed one,are designed to address the challenges of establishing refueling airspace and allocating tasks for tankers.Both methods aim to optimize total fuel consumption of the receivers and tankers within the aerial refueling scheduling framework.The optimization problem is established as nonlinear optimization models along with restrictions.The integrated method seamlessly combines refueling rendezvous point scheduling and tanker task allocation into unified process.It has a complete solution space and excels in optimizing total fuel consumption.The decomposed method,through the separation of rendezvous point scheduling and task allocation,achieves a reduced computational complexity.However,this comes at the cost of sacrificing optimality by excluding specific feasible solutions.Finally,numerical simulations are carried out to verify the feasibility and effectiveness of the proposed methods.These simulations yield insights crucial for the practical engineering application of both the integrated and decomposed methods in real-world scenarios.This comprehensive approach aims to enhance the efficiency of forest firefighting operations,mitigating the risks posed by forest fires to human life and property.展开更多
In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.A...In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.展开更多
The spatial and temporal variation of green economic efficiency and its driving factors are of great significance for the construction of high-efficiency and low-consumption green development model and sustainable soc...The spatial and temporal variation of green economic efficiency and its driving factors are of great significance for the construction of high-efficiency and low-consumption green development model and sustainable socio-economic development.The research focused on the Yangtze River Economic Belt(YREB)and employed the miniumum distance to strong efficient frontier DEA(MinDs)model to measure the green economic efficiency of the municipalities in the region between 2008 and 2020.Then,the spatial autocorrelation model was used to analyze the evolution characteristics of its spatial pattern.Finally,Geodetector was applied to reveal the drivers and their interactions on green economic efficiency.It is found that:1)the overall green economic efficiency of the YREB from 2008 to 2020 shows a W-shaped fluctuating upward trend,green economic efficiency is greater in the downstream and smallest in the upstream;2)the spatial distribution of green economic efficiency shows clustering characteristics,with multi-core clustering based on‘city clusters-central cities'becoming more obvious over time;the High-High agglomeration type is mainly clustered in Jiangsu and Zheji-ang,while the Low-Low agglomeration type is clustered in the western Sichuan Plateau area and southwestern Yunnan;3)from input-output factors,whether it is the YREB as a whole or the upper,middle and lower reaches regions,the economic development level,labor input,and capital investment are the leading factors in the spatial-temporal evolution of green economic efficiency,with the com-prehensive influence of economic development level and pollution index being the most important interactive driving factor;4)from so-cio-economic factors,information technology drivers such as government intervention,transportation accessibility,information infra-structure,and Internet penetration are always high impact influencers and dominant interaction factors for green economic efficiency in the YREB and the three major regions in the upper,middle and lower reaches.Accordingly,the article puts forward relevant policy re-commendations in terms of formulating differentiated green transformation strategies,strengthening network leadership and informa-tion technology construction and coordinating multi-factor integrated development,which could provide useful reference for promoting synergistic green economic efficiency in the YREB.展开更多
To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to...To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to measure the resilience of each city from 2003 to 2020.The spatial-temporal evolution characteristics were analyzed using Kernel density estimation,standard deviation ellipse,and spatial Markov chain analysis,and the spatial Tobit model was introduced to discover the influencing factors.The results indicate the following:①Urban resilience in the Chengdu-Chongqing Economic Circle displays an upward trend,with the center of gravity moving to the southwest,and the polarization phenomenon intensifying.②The urban resilience level in a region has certain spatial and geographical dependence,while the probability of urban resilience transfer differs in adjacent cities with different resilience levels.③Urban centrality,economic scale,openness level,and financial development promote urban resilience,whereas government scale significantly inhibits it.Finally,this paper proposes countermeasures and suggestions to improve the urban resilience of the Chengdu-Chongqing Economic Circle.展开更多
The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries an...The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other fields.Furthermore,it is important to construct a digital twin system.However,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted accuracy.In this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)layer.Specifically,we fuse the spatial-temporal graph based on the interrelationship of spatial graphs.Simultaneously,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding methods.Subsequently,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)module.The module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like data.AFSTGCN dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted accuracy.Experiments on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models.展开更多
In this paper,we study systems of conservation laws in one space dimension.We prove that for classical solutions in Sobolev spaces H^(s),with s>3/2,the data-to-solution map is not uniformly continuous.Our results a...In this paper,we study systems of conservation laws in one space dimension.We prove that for classical solutions in Sobolev spaces H^(s),with s>3/2,the data-to-solution map is not uniformly continuous.Our results apply to all nonlinear scalar conservation laws and to nonlinear hyperbolic systems of two equations.展开更多
The recent discovery of field emission devices based on one-dimensional nanostructures has attracted much interest in emerging applications on next-generation flat panel displays,molecule-based sensors,and so forth.To...The recent discovery of field emission devices based on one-dimensional nanostructures has attracted much interest in emerging applications on next-generation flat panel displays,molecule-based sensors,and so forth.To achieve a comprehensive understanding of surface potentials at the nano-emitters during the tunneling process,in this study we systematically investigated the image potentials of single-walled boron nitride nanotubes with different edges,diameters and lengths in the frame of a composite first-principles calculation.The image potentials of zigzag single-walled boron nitride nanotubes are found to be dependent on the non-equivalent sides.Only the image potentials of isolated armchair single-walled boron nitride nanotube can be well fitted with the image potential of an ideal metal sphere of a size comparable to the tube diameter.On the contrary,the image potentials of zigzag and grounded armchair single-walled boron nitride nanotubes exhibit a strong length-dependence characteristic and are significantly different from that of an ideal metal sphere,which originates from the significant axial symmetry breaking of induced charge at the tip for the long tube.The correlation between the testing electron and electronic structure of single-walled boron nitride nanotube has also been discussed.展开更多
Firm entry plays an important role in the industrial transformation of mature resource-based cities.This study describes the industrial evolution of resource-based cities at the firm level and uses kernel density esti...Firm entry plays an important role in the industrial transformation of mature resource-based cities.This study describes the industrial evolution of resource-based cities at the firm level and uses kernel density estimation and econometric models to study the spatiotemporal characteristics and determinants of new firm entry from 2011 to 2019 in four mature resource-based cities.The results are summarized as follows:(1)New resource-based firm entry tends to be natural resource-oriented and path-dependent.The new non-resource-based firms show a high concentration in central urban areas,and the industry types are mainly wholesale and retail of resource products,cultural tourism,and equipment manufacturing.(2)Heterogeneous incumbent firms affect firm entry differently.Affected by competition and agglomeration effects,resource-based and non-resource-based incumbent firms have negative and positive impacts on new resource-based firm entry,respectively.Resourcebased incumbent firm agglomeration positively influences new non-resource-based firm entry.(3)Besides incumbent firms,firm entry can also be affected by multidimensional factors,such as factor costs,economic environment,and institutional environment.Research on new firm entry can better reveal the path dependence and path creation process of the industrial development of resource-based cities from a micro-perspective.展开更多
Highly evolved granite is an important sign of the mature continent crust and closely associated with deposits of rare metals.In this work,the authors undertake systematically zircon U-Pb ages and whole rock elemental...Highly evolved granite is an important sign of the mature continent crust and closely associated with deposits of rare metals.In this work,the authors undertake systematically zircon U-Pb ages and whole rock elemental data for highly evolved granitic intrusions from the Great Xing’an Range(GXR),NE China,to elucidate their discriminant criteria,spatial-temporal distribution,differentiation and geodynamic mecha-nism.Geochemical data of these highly evolved granites suggest that high w(SiO_(2))(>70%)and differentiation index(DI>88)could be quantified indicators,while strong Eu depletion,high TE_(1,3),lowΣREE and low Zr/Hf,Nb/Ta,K/Rb could only be qualitative indicators.Zircon U-Pb ages suggest that the highly evolved gran-ites in the GXR were mainly formed in Late Mesozoic,which can be divided into two major stages:Late Ju-rassic-early Early Cretaceous(162-136 Ma,peak at 138 Ma),and late Early Cretaceous(136-106 Ma,peak at 126 Ma).The highly evolved granites are mainly distributed in the central-southern GXR,and display a weakly trend of getting younger from northwest to southeast,meanwhile indicating the metallogenic potential of rare metals within the central GXR.The spatial-temporal distribution,combined with regional geological data,indicates the highly evolved Mesozoic granites in the GXR were emplaced in an extensional environ-ment,of which the Late Jurassic-early Early Cretaceous extension was related to the closure of the Mongol-Okhotsk Ocean and roll-back of the Paleo-Pacific Plate,while the late Early Cretaceous extension was mainly related to the roll-back of the Paleo-Pacific Plate.展开更多
基金supported by the National Natural Science Foundation of China(Nos.U19A2044,42105132,42030609,41975037,and 42105133)the National Key Research and Development Program of China(No.2022YFC3703502)+1 种基金the Plan for Anhui Major Provincial Science&Technology Project(No.202203a07020003)Hefei Ecological Environment Bureau Project(No.2020BFFFD01804).
文摘As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.
基金supported by the National Office for Philosophy and Social Sciences(grant reference 22&ZD067).
文摘In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed panel data from the Yellow River(YR)region from 2013 to 2021 and discovered notable spatial variances in the composite index and coupling coordination of the two systems.Specifically,the downstream region exhibited the highest coupling coordination,while the upstream region had the lowest.We identified that favorable factors such as economic development,innovation,industrial upgrading,and government intervention can bolster the coupling.Our findings provide a valuable framework for promoting DE and HQD in the YR region.
基金supported by the National Natural Science Foundation of China(Nos.12205259 and 12147101)the Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)with No.G1323523064.
文摘In this study,we performed a systematic analysis of the multiplicity dependence of hadron production at mid-rapidity(|y|<0.5),ranging from the light to the charm sector in proton-proton(pp)collisions at√s=13 TeV.This study used a multi-phase transport(AMPT)model coupled with PYTHIA8 initial conditions.We investigated the baryon-to-meson and the strange-to-non-strange meson ratios varying with the charged particle density.By tuning the coalescence parameters,the AMPT model provides a reasonable description of the experimental data for the inclusive production of both light and charm hadrons,comparable to the string fragmentation model calculations with color reconnection effects.Additionally,we analyzed the relative production of hadrons by examining the self-normalized particle ratios as a function of the charged hadron density.Our findings suggest that parton evolution effects and the coalescence hadronization process in the AMPT model result in a strong flavor hierarchy in the multiplicity dependence of the baryon-to-meson ratio.Furthermore,our investigation of the p_(T) differential double ratio of the baryon-to-meson fraction between high-and low-multiplicity events revealed distinct modifications to the flavor associated baryon-to-meson ratio p_(T) shape in high-multiplicity events when comparing the coalescence hadronization model to the color reconnection model.These observations highlight the importance of understanding the hadronization process in high-energy pp collisions through comprehensive multiplicity-dependent multi-flavor analysis.
基金supported by the National Natural Science Foundation of China(Grant Nos.62472149,62376089,62202147)Hubei Provincial Science and Technology Plan Project(2023BCB04100).
文摘Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.
基金the Fund of Science and Technology Innovation Project of Chinese Academy of Chinese Medical Sciences Project:Self-service Acupuncture Smoking Cessation Research and Development(No.CI2021A03506)Fund of Capital Health Development Special Research Project:Research on Development and Clinical Applicalion of Wrist Acupuncture Smoking Cessation Instrument(No.2022-1-4281)。
文摘OBJECTIVE:To observe the effect of different acupuncture frequencies on the abstinence rate which could be used as a reference for optimizing acupuncture cessation programs.METHODS:From July 2018 to June 2022,a total of 220 smokers were recruited based on inclusion criteria and randomly divided into the high-frequency acupuncture group(HF group,n=110):5 times a week from the 1st to the 4th week,from weeks 5 to 8,three times a week and the low-frequency acupuncture group(LF group,n=110):3 times a week from the 1st to the 4th week,from weeks 5 to 8,twice a week,then treated for 8 weeks and followup at 1 month in Beijing.RESULTS:In total,162 subjects completed the whole study with a drop-out rate of 20.45%.The expiratory CO point abstinence rate was HF group 53/110(48.18%)vs LF group 41/110(37.27%)in Week 8(P=0.102)and HF group 46/110(41.82%)vs LF group 45/110(40.91%)in Week 12(P=0.891)and the HF acupuncture and LF acupuncture were nearly equal in the 8-week abstinence rate.In addition,both HF and LF acupuncture significantly reduced Fagerstr?m test for nicotine dependence scale(FTND)scores(P<0.05),Minnesota nicotine withdrawal scale(MNWS)scores(P<0.05),and Brief Questionnaire of Smoking Urges scale(QSU-Brief)scores(P<0.05),but HF acupuncture showed some superiority over LF acupuncture in relieving patients'smoking cravings(P<0.05).CONCLUSIONS:The study initially showed that both high-frequency acupuncture and low-frequency acupuncture treatment were safe and effective on smoking cessation for 8 weeks,but high-frequency acupuncture was advantageous in reducing smoking cravings.More accurate acupuncture frequency needs to be validated through larger clinical studies to optimize acupuncture smoking cessation programs.
基金supported by the Jiangsu Funding Program for Excellent Postdoctoral Talent (Grant No.2023ZB397)the Project funded by China Postdoctoral Science Foundation (Grant No.2023M732986).
文摘Nanomaterials have garnered recognition for their notable surface effects and demonstration of superior mechanical properties.Previous studies on the surface effects of nanomaterials,employing the finite element method,often relied on simplified twodimensional models due to theoretical complexities.Consequently,these simplified models inadequately represent the mechanical properties of nanomaterials and fail to capture the substantial impact of surface effects,particularly the curvature dependence of nanosurfaces.This study applies the principle of minimum energy and leverages the Steigmann-Ogden surface theory of nanomaterials to formulate a novel finite element surface element that comprehensively accounts for surface effects.We conducted an analysis of the stress distribution and deformation characteristics of four typical 2D and 3D nanomaterial models.The accuracy of the developed surface element and finite element calculation method was verified through comparison with established references.The resulting finite element model provides a robust and compelling scientific approach for accurately predicting the mechanical performance of nanomaterials.
基金supported by grants from the Scientific Research Fund project of Education Department of Yunnan Province(2024J0314)Joint Special Project on Basic Research of Yunnan Provincial Department of Science and Technology and Kunming Medical University(202501AY070001-206).
文摘Objective:To evaluate the global liter-ature output on the relationship between brain-derived neurotrophic factor(BDNF)and cognitive function in al-cohol dependence syndrome using bibliometric methods and explore the status and trends in this field.Method:The literature on the application of BDNF in cognitive impairment caused by alcohol dependence syndrome published from 1995 to 2023 were retrieved from Web of Science,and the relevant information(publication characteristics,country and institution,author,number of publications,citation,journal and research field,corresponding author,key words,etc.)was recorded.The bibliometrix R package was used for quantitative and qualitative analysis of publication output and author contributions.Result:A total of 99 articles were included.The overall number of publications in this field has increased over time.The countries and institutions that contributed the most to the field were the United States and the Academy of Medical Sciences of Iranian universities,respectively.Most of the authors were from the United States,followed by Spain,China,and Iran.Ceccanti M,Fiore M were the most productive authors.Publications with Ceccanti M had the highest h-index.The most cited reference author is Haenninen H(227 citations),and the number one published journal is Alcohol.Most articles were published in 2020(n=12)and 2022(n=11),followed by 2019 and 2021(n=10).The corresponding author has the largest number of publications from the United States,and more publications from a single country tend to have more cooperation from other countries.BDNF and alcohol appeared more frequently in various keyword clouds.However,significant differences remained in the author keyword cloud,keyword plus word cloud,and paper topic word cloud.Conclusion:BDNF has great potential in the application of cognitive dysfunction caused by alcohol dependence syndrome.Bibliometric methods and data visualization techniques can help understand the current state of research progress and enable relevant scholars and practitioners to predict the development trends in this field.
基金funded by the National Natural Science Foundation of China(No.32270554,32400400).
文摘The post-fledging period, extending from fledging to independence, is a crucial life stage characterized by high mortality due to fledglings' limited mobility and inexperience. During this stage, fledglings gradually increase their mobility, leave their parents, disperse from their natal site, and respond to the challenges of new environments. Characterizing these post-fledging movements and space use is essential for understanding juvenile survival strategies and devising targeted conservation measures. The Crested Ibis (Nipponia nippon), an endangered species and a highly protected animals at the national level in China, has seen limited research on its post-fledging movements and space use. From 2015 to 2023, we utilized biologgers, combined with field surveys, to study the movement and space use characteristics of 37 fledglings in Hanzhong City, Shaanxi Province, China, over a two-month post-fledging period. We quantified changes in activity levels (based on overall dynamic body acceleration), independence timing, onset of post-fledging dispersal, habitat selection, and daily activity rhythms after independence. Our results revealed individuals began independent living 26.23 ± 2.34 days post-fledging and onset of dispersal at 25.58 ± 2.33 days, with a range area at the natal of 2.08 ± 0.56 km^(2). The initial 30 days post-fledging are characterized as an ontogenetic phase marked by a rapid increase in body activity level. Fledglings preferred paddy fields during the independent period rather than the forests they relied on before independence. Interestingly, the daily activity rhythm, particularly foraging behavior, peaked at noon—contrasting with the expected morning and evening activity peaks—likely as an adaptation to avoid periods of peak human activity. Additionally, drowning, collisions, and predation in paddy fields are noteworthy causes of fledgling mortality. Consequently, we recommend protecting a 2-km^(2) area around the nest site for at least two-month post-fledging, implementing safety measures around power lines and cesspools. Additionally, reducing human disturbances near foraging habitats and expanding space within paddy fields would help mitigate survival pressures on fledglings.
基金the National Science Fund for Distinguished Young Scholars of China (No.62025301)the National Natural Science Foundation of China (Nos.62273043 and 62373055)+1 种基金the China National Postdoctoral Program for Innovative Talents (No.BX20230461)the China Postdoctoral Science Foundation (No.2023M740249)。
文摘This paper investigates the spatial-temporal cooperative guidance problem for multiple flight vehicles without relying on time-to-go information.First,a two-stage cooperative guidance strategy,namely the cooperative guidance and the Proportional Navigation Guidance(PNG)stage strategy,is developed to realize the spatial-temporal constraints in two dimensions.At the former stage,two controllers are designed and superimposed to satisfy both impact time consensus and impact angle constraints.Once the convergent conditions are satisfied,the flight vehicles will switch to the PNG stage to ensure zero miss distance.To further extend the results to three dimensions,a planar pursuit guidance stage is additionally imposed at the beginning of guidance.Due to the inde-pendence of time-to-go estimation,the proposed guidance strategy possesses great performance in satisfying complex spatial-temporal constraints even under flight speed variation.Finally,several numerical simulations are implemented to verify the effectiveness and advantages of the proposed results under different scenarios.
基金supported in part by the 2023 Key Supported Project of the 14th Five Year Plan for Education and Science in Hunan Province with No.ND230795.
文摘In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal graph.Most GCNs define the graph topology by physical relations of the human joints.However,this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs,resulting in a low recognition rate for specific actions with implicit correlation between joint pairs.In addition,existing methods ignore the trend correlation between adjacent frames within an action and context clues,leading to erroneous action recognition with similar poses.Therefore,this study proposes a learnable GCN based on behavior dependence,which considers implicit joint correlation by constructing a dynamic learnable graph with extraction of specific behavior dependence of joint pairs.By using the weight relationship between the joint pairs,an adaptive model is constructed.It also designs a self-attention module to obtain their inter-frame topological relationship for exploring the context of actions.Combining the shared topology and the multi-head self-attention map,the module obtains the context-based clue topology to update the dynamic graph convolution,achieving accurate recognition of different actions with similar poses.Detailed experiments on public datasets demonstrate that the proposed method achieves better results and realizes higher quality representation of actions under various evaluation protocols compared to state-of-the-art methods.
基金This work was supported by the National Natural Science Foundation of China(Nos.61833013,61473012 and 62103335)Key Research Program of Jiangxi Province in China(No.20192BBEL50005).
文摘Forest fires pose a significant threat to human life and property,so the utilization of unmanned aircraft systems provides new ways for forest firefighting.Given the constrained load capacities of these aircraft,aerial refueling becomes crucial to extend their operational time and range.In order to address the complexities of firefighting missions involving multi-receiver and multi-tanker deployed from various airports,first,a fuel consumption calculation model for aerial refueling scheduling is established based on the receiver path.Then,two distinct methods,including an integrated one and a decomposed one,are designed to address the challenges of establishing refueling airspace and allocating tasks for tankers.Both methods aim to optimize total fuel consumption of the receivers and tankers within the aerial refueling scheduling framework.The optimization problem is established as nonlinear optimization models along with restrictions.The integrated method seamlessly combines refueling rendezvous point scheduling and tanker task allocation into unified process.It has a complete solution space and excels in optimizing total fuel consumption.The decomposed method,through the separation of rendezvous point scheduling and task allocation,achieves a reduced computational complexity.However,this comes at the cost of sacrificing optimality by excluding specific feasible solutions.Finally,numerical simulations are carried out to verify the feasibility and effectiveness of the proposed methods.These simulations yield insights crucial for the practical engineering application of both the integrated and decomposed methods in real-world scenarios.This comprehensive approach aims to enhance the efficiency of forest firefighting operations,mitigating the risks posed by forest fires to human life and property.
基金This work is partly supported by the National Key Research and Development Program of China(Grant No.2020YFB1805403)the National Natural Science Foundation of China(Grant No.62032002)the 111 Project(Grant No.B21049).
文摘In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.
基金Under the auspices of the National Natural Science Foundation of China(No.71974070)‘CUG Scholar'Scientific Research Funds at China University of Geosciences(Wuhan)(No.2022005)。
文摘The spatial and temporal variation of green economic efficiency and its driving factors are of great significance for the construction of high-efficiency and low-consumption green development model and sustainable socio-economic development.The research focused on the Yangtze River Economic Belt(YREB)and employed the miniumum distance to strong efficient frontier DEA(MinDs)model to measure the green economic efficiency of the municipalities in the region between 2008 and 2020.Then,the spatial autocorrelation model was used to analyze the evolution characteristics of its spatial pattern.Finally,Geodetector was applied to reveal the drivers and their interactions on green economic efficiency.It is found that:1)the overall green economic efficiency of the YREB from 2008 to 2020 shows a W-shaped fluctuating upward trend,green economic efficiency is greater in the downstream and smallest in the upstream;2)the spatial distribution of green economic efficiency shows clustering characteristics,with multi-core clustering based on‘city clusters-central cities'becoming more obvious over time;the High-High agglomeration type is mainly clustered in Jiangsu and Zheji-ang,while the Low-Low agglomeration type is clustered in the western Sichuan Plateau area and southwestern Yunnan;3)from input-output factors,whether it is the YREB as a whole or the upper,middle and lower reaches regions,the economic development level,labor input,and capital investment are the leading factors in the spatial-temporal evolution of green economic efficiency,with the com-prehensive influence of economic development level and pollution index being the most important interactive driving factor;4)from so-cio-economic factors,information technology drivers such as government intervention,transportation accessibility,information infra-structure,and Internet penetration are always high impact influencers and dominant interaction factors for green economic efficiency in the YREB and the three major regions in the upper,middle and lower reaches.Accordingly,the article puts forward relevant policy re-commendations in terms of formulating differentiated green transformation strategies,strengthening network leadership and informa-tion technology construction and coordinating multi-factor integrated development,which could provide useful reference for promoting synergistic green economic efficiency in the YREB.
基金supported by the Graduate Research and Innovation Project of Chongqing Normal University[Grant No.YKC23035],comprehensive evaluation,and driving factors of urban resilience in the Chengdu-Chongqing Economic Circle.
文摘To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to measure the resilience of each city from 2003 to 2020.The spatial-temporal evolution characteristics were analyzed using Kernel density estimation,standard deviation ellipse,and spatial Markov chain analysis,and the spatial Tobit model was introduced to discover the influencing factors.The results indicate the following:①Urban resilience in the Chengdu-Chongqing Economic Circle displays an upward trend,with the center of gravity moving to the southwest,and the polarization phenomenon intensifying.②The urban resilience level in a region has certain spatial and geographical dependence,while the probability of urban resilience transfer differs in adjacent cities with different resilience levels.③Urban centrality,economic scale,openness level,and financial development promote urban resilience,whereas government scale significantly inhibits it.Finally,this paper proposes countermeasures and suggestions to improve the urban resilience of the Chengdu-Chongqing Economic Circle.
基金supported by the China Scholarship Council and the CERNET Innovation Project under grant No.20170111.
文摘The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other fields.Furthermore,it is important to construct a digital twin system.However,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted accuracy.In this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)layer.Specifically,we fuse the spatial-temporal graph based on the interrelationship of spatial graphs.Simultaneously,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding methods.Subsequently,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)module.The module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like data.AFSTGCN dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted accuracy.Experiments on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models.
文摘In this paper,we study systems of conservation laws in one space dimension.We prove that for classical solutions in Sobolev spaces H^(s),with s>3/2,the data-to-solution map is not uniformly continuous.Our results apply to all nonlinear scalar conservation laws and to nonlinear hyperbolic systems of two equations.
基金the financial support from the National Natural Science Foundation of China(Grant Nos.12004083 and 51972069)the Science and Technology Projects in Guangzhou(Grant Nos.202102020350 and 202102010470)+7 种基金the National Key R&D Program of China(Grant No.2016YFB0200800)the Opening Project of Joint Laboratory for Planetary Science and Supercomputing(Grant No.CSYYGS-QT-2024-14)the Key-Area Research and Development Program of Guangdong Province(Grant No.2019B030330001)the College Students Innovation and Entrepreneurship Training Program of Guangdong Province(Grant No.S202311078133)Key Discipline of Materials Science and Engineering,Bureau of Education of Guangzhou(Grant No.202255464)the National Supercomputer Center in Guangzhouthe National Supercomputing Center in Chengduthe Network Center of Guangzhou University。
文摘The recent discovery of field emission devices based on one-dimensional nanostructures has attracted much interest in emerging applications on next-generation flat panel displays,molecule-based sensors,and so forth.To achieve a comprehensive understanding of surface potentials at the nano-emitters during the tunneling process,in this study we systematically investigated the image potentials of single-walled boron nitride nanotubes with different edges,diameters and lengths in the frame of a composite first-principles calculation.The image potentials of zigzag single-walled boron nitride nanotubes are found to be dependent on the non-equivalent sides.Only the image potentials of isolated armchair single-walled boron nitride nanotube can be well fitted with the image potential of an ideal metal sphere of a size comparable to the tube diameter.On the contrary,the image potentials of zigzag and grounded armchair single-walled boron nitride nanotubes exhibit a strong length-dependence characteristic and are significantly different from that of an ideal metal sphere,which originates from the significant axial symmetry breaking of induced charge at the tip for the long tube.The correlation between the testing electron and electronic structure of single-walled boron nitride nanotube has also been discussed.
基金National Natural Science Foundation of China,No.72050001。
文摘Firm entry plays an important role in the industrial transformation of mature resource-based cities.This study describes the industrial evolution of resource-based cities at the firm level and uses kernel density estimation and econometric models to study the spatiotemporal characteristics and determinants of new firm entry from 2011 to 2019 in four mature resource-based cities.The results are summarized as follows:(1)New resource-based firm entry tends to be natural resource-oriented and path-dependent.The new non-resource-based firms show a high concentration in central urban areas,and the industry types are mainly wholesale and retail of resource products,cultural tourism,and equipment manufacturing.(2)Heterogeneous incumbent firms affect firm entry differently.Affected by competition and agglomeration effects,resource-based and non-resource-based incumbent firms have negative and positive impacts on new resource-based firm entry,respectively.Resourcebased incumbent firm agglomeration positively influences new non-resource-based firm entry.(3)Besides incumbent firms,firm entry can also be affected by multidimensional factors,such as factor costs,economic environment,and institutional environment.Research on new firm entry can better reveal the path dependence and path creation process of the industrial development of resource-based cities from a micro-perspective.
基金Supported by projects of the National Natural Science Foundation of China(Nos.92062216,41888101).
文摘Highly evolved granite is an important sign of the mature continent crust and closely associated with deposits of rare metals.In this work,the authors undertake systematically zircon U-Pb ages and whole rock elemental data for highly evolved granitic intrusions from the Great Xing’an Range(GXR),NE China,to elucidate their discriminant criteria,spatial-temporal distribution,differentiation and geodynamic mecha-nism.Geochemical data of these highly evolved granites suggest that high w(SiO_(2))(>70%)and differentiation index(DI>88)could be quantified indicators,while strong Eu depletion,high TE_(1,3),lowΣREE and low Zr/Hf,Nb/Ta,K/Rb could only be qualitative indicators.Zircon U-Pb ages suggest that the highly evolved gran-ites in the GXR were mainly formed in Late Mesozoic,which can be divided into two major stages:Late Ju-rassic-early Early Cretaceous(162-136 Ma,peak at 138 Ma),and late Early Cretaceous(136-106 Ma,peak at 126 Ma).The highly evolved granites are mainly distributed in the central-southern GXR,and display a weakly trend of getting younger from northwest to southeast,meanwhile indicating the metallogenic potential of rare metals within the central GXR.The spatial-temporal distribution,combined with regional geological data,indicates the highly evolved Mesozoic granites in the GXR were emplaced in an extensional environ-ment,of which the Late Jurassic-early Early Cretaceous extension was related to the closure of the Mongol-Okhotsk Ocean and roll-back of the Paleo-Pacific Plate,while the late Early Cretaceous extension was mainly related to the roll-back of the Paleo-Pacific Plate.
