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
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
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
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
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
Considering the nonlinear structure and spatial-temporal correlation of traffic network,and the influence of potential correlation between nodes of traffic network on the spatial features,this paper proposes a traffic...Considering the nonlinear structure and spatial-temporal correlation of traffic network,and the influence of potential correlation between nodes of traffic network on the spatial features,this paper proposes a traffic speed prediction model based on the combination of graph attention network with self-adaptive adjacency matrix(SAdpGAT)and bidirectional gated recurrent unit(BiGRU).First-ly,the model introduces graph attention network(GAT)to extract the spatial features of real road network and potential road network respectively in spatial dimension.Secondly,the spatial features are input into BiGRU to extract the time series features.Finally,the prediction results of the real road network and the potential road network are connected to generate the final prediction results of the model.The experimental results show that the prediction accuracy of the proposed model is im-proved obviously on METR-LA and PEMS-BAY datasets,which proves the advantages of the pro-posed spatial-temporal model in traffic speed prediction.展开更多
As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wet...As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wetland,the Xianghai Wetland,and the Danjiang Wetland in Jilin Province.The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space,and the intensification of land salinization.Zhenlai County and Da an City in the Nenjiang River Basin have sufficient surface water resources,with surface water as the drinking water source.Baicheng City and Tongyu County have scarce surface water resources,and both use groundwater as their domestic water source.The main polluted section in the basin is the Xianghai Reservoir,and the annual water quality evaluation is Class V.However,the water quality of the Tao er River,the main stream of the Nenjiang River,is significantly better than that of the Xianghai Reservoir.In order to better study the water environmental pollution situation in the Nenjiang River basin,monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality.This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development,agricultural pattern transformation,and the promotion of water ecological civilization construction.展开更多
We are intrigued by the issues of shock instability,with a particular emphasis on numerical schemes that address the carbuncle phenomenon by reducing dissipation rather than increasing it.For a specific class of plana...We are intrigued by the issues of shock instability,with a particular emphasis on numerical schemes that address the carbuncle phenomenon by reducing dissipation rather than increasing it.For a specific class of planar flow fields where the transverse direction exhibits vanishing but non-zero velocity components,such as a disturbed onedimensional(1D)steady shock wave,we conduct a formal asymptotic analysis for the Euler system and associated numerical methods.This analysis aims to illustrate the discrepancies among various low-dissipative numerical algorithms.Furthermore,a numerical stability analysis of steady shock is undertaken to identify the key factors underlying shock-stable algorithms.To verify the stability mechanism,a consistent,low-dissipation,and shock-stable HLLC-type Riemann solver is presented.展开更多
Mechanical snap-through instability of bi-stable structures may find many practical applications such as state switching and energy transforming.Although there exist diverse bi-stable structures capable of snap-throug...Mechanical snap-through instability of bi-stable structures may find many practical applications such as state switching and energy transforming.Although there exist diverse bi-stable structures capable of snap-through instability,it is still difficult for a structure with high slenderness to undergo the axial snap-through instability with a large stroke.Here,an elastic structure with high slenderness is simply constructed by a finite number of identical,conventional bi-stable units with relatively low slenderness in series connection.For realizing the axial snap-through instability with a large stroke,common scissors mechanisms are further introduced as rigid constraints to guarantee the synchronous snap-through instability of these bi-stable units.The global feature of the large-stroke snap-through instability realized here is robust and even insusceptible to the local out-of-synchronization of individual units.The present design provides a simple and feasible way to achieve the large-stroke snap-through instability of slender structures,which is expected to be particularly useful for state switching and energy transforming in narrow spaces.展开更多
The utilization of Inlet Guide Vane (IGV) plays a key factor in affecting the instability evolution. Existing literature mainly focuses on the effect of IGV on instability inception that occurs in the rotor region. Ho...The utilization of Inlet Guide Vane (IGV) plays a key factor in affecting the instability evolution. Existing literature mainly focuses on the effect of IGV on instability inception that occurs in the rotor region. However, with the emergence of compressor instability starting from the stator region, the mechanism of various instability inceptions that occurs in different blade rows due to the change of IGV angles should be further examined. In this study, experiments were focused on three types of instability inceptions observed previously in a 1.5-stage axial flow compressor. To analyze the conversion of stall evolutions, the compressor rotating speed was set to 17 160 r/min, at which both the blade loading in the stator hub region and rotor tip region were close to the critical value before final compressor stall. Meanwhile, the dynamic test points with high-response were placed to monitor the pressures both at the stator trailing edges and rotor tips. The results indicate that the variation of reaction determines the region where initial instability occurs. Indeed, negative pre-rotation of the inlet guide vane leads to high-reaction, initiating stall disturbance from the rotor region. Positive pre-rotation results in low-reaction, initiating stall disturbance from the stator region. Furthermore, the type of instability evolution is affected by the radial loading distribution under different IGV angles. Specifically, a spike-type inception occurs at the rotor blade tip with a large angle of attack at the rotor inlet (−2°, −4° and −6°). Meanwhile, the critical total pressure ratio at the rotor tip is 1.40 near stall. As the angle of attack decreases, the stator blade loading reaches its critical boundary, with a value of approximately 1.35. At this moment, if the rotor tip maintains high blade loading similar to the stator hub, the partial surge occurs (0° and +2°);otherwise, the hub instability occurs (+4° and +6°).展开更多
Rotating Instability (RI) is a typical unsteady flow phenomenon in compressors and may cause severe aerodynamic noise and even potential nonsynchronous vibration. Most studies of RI are based on the uniform inflow, ig...Rotating Instability (RI) is a typical unsteady flow phenomenon in compressors and may cause severe aerodynamic noise and even potential nonsynchronous vibration. Most studies of RI are based on the uniform inflow, ignoring the influence of inlet distortions. This study investigates the mechanism of RI in a transonic rotor through full-annulus unsteady simulations, with a particular focus on the effects of boundary layer ingesting distortions. The results show that at the uniform inflow, the RI fluctuations with the broadband hump can be observed over a relatively wide mass flow rate range, and its origin can be attributed to the coupling effect between the tip leakage flow and shear layer instability. At the inlet distortions, the broadband hump only occurs with partial circumferential locations. This kind of flow phenomenon is defined as Partial Rotating Instability (PRI). The PRI only occurs in a narrower mass flow rate range in which the circumferential range of strong shear is sufficiently large and the self-induced unsteady effects are strong enough. Further, this study confirms that the averaged tip leakage flow axial momentum at the onset of RI or PRI is close, so it can be used as the parameter to determine whether RI or PRI occurs.展开更多
A hydrodynamic model is used to study Kelvin-Helmholtz(KH)instability of the interface between two particle-laden inviscid fluids moving with two different uniform mean velocities.Explicit eigen-equation is derived to...A hydrodynamic model is used to study Kelvin-Helmholtz(KH)instability of the interface between two particle-laden inviscid fluids moving with two different uniform mean velocities.Explicit eigen-equation is derived to study the effect of suspended particles on the growth rate of KH instability.For dusty gases with negligible volume fraction of heavy particles and small particle-to-fluid mass ratio,the real and imaginary parts of leading-order asymptotic expression derived by the present model for the growth rate are shown to be identical to the earlier results derived by the classical Saffman model established for dusty gases.Beyond the known results,explicit leading-order asymptotic expressions for the effect of suspended particles on the growth rate are derived for several typical cases of basic interest.It is shown that the suspended particles can decrease or increase the growth rate of KH instability depending on the Stokes numbers of the particles and whether the particles are heavier or lighter than the clean fluid.Compared to the mass density of the clean fluid,our results based on leading-order asymptotic solutions show that heavier particles and lighter particles have opposite effects on the growth rate of KH instability,while the effect of neutrally buoyant particles on the growth rate of KH instability is negligible.展开更多
We study the Rayleigh-Taylor instability(RTI)of electrostatic plane wave perturbations in compressible relativistic magnetoplasma fluids with thermal ions under gravity in three different cases of when(ⅰ)electrons ar...We study the Rayleigh-Taylor instability(RTI)of electrostatic plane wave perturbations in compressible relativistic magnetoplasma fluids with thermal ions under gravity in three different cases of when(ⅰ)electrons are in isothermal equilibrium,i.e.,classical or nondegenerate,(ⅱ)electrons are fully degenerate(with Te=0),and(ⅲ)electrons are partially degenerate or have finite temperature degeneracy(with Te≠0).While in the cases of(ⅰ)and(ⅲ),we focus on the regimes where the particle's thermal energy is more or less than the rest mass energy,i.e.,βe≡kBTe/mec2<1or>1,the case(ⅱ)considers from weakly to ultra-relativistic degenerate regimes.A general expression of the growth rate of instability is obtained and analyzed in the three different cases relevant to laboratory and astrophysical plasmas,which generalize and advance the previous theory on RTI.展开更多
A way to enhance the growth of stimulated Raman instability in laser-plasma interactions was investigated.This relies on the application of density modulation of a co-propagating electron beam in plasmas.In the stimul...A way to enhance the growth of stimulated Raman instability in laser-plasma interactions was investigated.This relies on the application of density modulation of a co-propagating electron beam in plasmas.In the stimulated Raman scattering process,an electromagnetic pump wave decays into a low-frequency wave and a scattered electromagnetic sideband wave.In this process,the pump wave produces an oscillatory velocity associated with the plasma electrons and the beam electrons.These oscillatory velocities combine with the existing low-frequency mode,producing ponderomotive force that drives high-frequency sideband waves.The sidebands couple to the pump wave,driving the beam-mode.A modulation of the electron beam density enhances the growth rate of the instability.The theoretical calculations show about 40%enhancements in growth of Raman instability at resonance(where the electron beam density modulation parameter approaches to unity)for the plasma density of the order of 10^(18)cm^(-3).展开更多
In order to calculate the multipoles in real materials with considerable intersite Coulomb interaction V,we develop a self-consistent program which starts from the frst-principles calculations to solve the tight-bindi...In order to calculate the multipoles in real materials with considerable intersite Coulomb interaction V,we develop a self-consistent program which starts from the frst-principles calculations to solve the tight-binding Hamiltonian including onsite Coulomb repulsion U,V,and spin-orbital couplingλ.The program is applied to Ba_(2)MgReO_(6)to fgure out the mechanism of structural instability and magnetic ordering.A comprehensive quadrupole phase diagram versus U and V withλ=0.28 eV is calculated.Our results demonstrate that the easy-plane anisotropy and the intersite Coulomb repulsion V must be considered to remove the orbital frustration.The increase of V to>20 meV would arrange quadrupole Q_(x^(2)-y^(2))antiparallelly,accompanied by small parallel Q_(3z)^(2)-r^(2),and stabilize Ba_(2)MgReO_(6)into the body-centered tetragonal structure.Such antiparallel Q_(x^(2)-y^(2))provides a new mechanism for the Dzyaloshinskii-Moriya interaction and gives rise to the canted antiferromagnetic(CAF)state along the[110]axis.Moreover,sizable octupoles such as O_(21)^(31),O_(21)^(33),O_(21)^(34)and O_(21)^(36)are discovered for the frst time in the CAF state.Our study not only provides a comprehensive understanding of the experimental results in Ba_(2)MgReO_(6),but also serves as a general and useful tool for the study of multipole physics in 5d compounds.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(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 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.
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.
基金the National Natural Science Foundation of China(No.61461027,61762059)the Provincial Science and Technology Program supported the Key Project of Natural Science Foundation of Gansu Province(No.22JR5RA226)。
文摘Considering the nonlinear structure and spatial-temporal correlation of traffic network,and the influence of potential correlation between nodes of traffic network on the spatial features,this paper proposes a traffic speed prediction model based on the combination of graph attention network with self-adaptive adjacency matrix(SAdpGAT)and bidirectional gated recurrent unit(BiGRU).First-ly,the model introduces graph attention network(GAT)to extract the spatial features of real road network and potential road network respectively in spatial dimension.Secondly,the spatial features are input into BiGRU to extract the time series features.Finally,the prediction results of the real road network and the potential road network are connected to generate the final prediction results of the model.The experimental results show that the prediction accuracy of the proposed model is im-proved obviously on METR-LA and PEMS-BAY datasets,which proves the advantages of the pro-posed spatial-temporal model in traffic speed prediction.
文摘As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wetland,the Xianghai Wetland,and the Danjiang Wetland in Jilin Province.The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space,and the intensification of land salinization.Zhenlai County and Da an City in the Nenjiang River Basin have sufficient surface water resources,with surface water as the drinking water source.Baicheng City and Tongyu County have scarce surface water resources,and both use groundwater as their domestic water source.The main polluted section in the basin is the Xianghai Reservoir,and the annual water quality evaluation is Class V.However,the water quality of the Tao er River,the main stream of the Nenjiang River,is significantly better than that of the Xianghai Reservoir.In order to better study the water environmental pollution situation in the Nenjiang River basin,monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality.This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development,agricultural pattern transformation,and the promotion of water ecological civilization construction.
基金Project supported by the National Natural Science Foundation of China(Nos.12471367 and12361076)the Research Program of Science and Technology at Universities of Inner Mongolia Autonomous Region(Nos.NJZY19186,NJZY22036,and NJZY23003)。
文摘We are intrigued by the issues of shock instability,with a particular emphasis on numerical schemes that address the carbuncle phenomenon by reducing dissipation rather than increasing it.For a specific class of planar flow fields where the transverse direction exhibits vanishing but non-zero velocity components,such as a disturbed onedimensional(1D)steady shock wave,we conduct a formal asymptotic analysis for the Euler system and associated numerical methods.This analysis aims to illustrate the discrepancies among various low-dissipative numerical algorithms.Furthermore,a numerical stability analysis of steady shock is undertaken to identify the key factors underlying shock-stable algorithms.To verify the stability mechanism,a consistent,low-dissipation,and shock-stable HLLC-type Riemann solver is presented.
基金supported by the National Natural Science Foundation of China(Grant Nos.11972027,12472093,and 11772272)the New Interdisciplinary Cultivation Fund of Southwest Jiaotong University(Grant No.2682022JX001)+1 种基金the Frontier Science and Technology Cultivation Project of Southwest Jiaotong University(Grant No.2682022KJ048)the Laboratory of Flexible Electronics Technology at Tsinghua University.
文摘Mechanical snap-through instability of bi-stable structures may find many practical applications such as state switching and energy transforming.Although there exist diverse bi-stable structures capable of snap-through instability,it is still difficult for a structure with high slenderness to undergo the axial snap-through instability with a large stroke.Here,an elastic structure with high slenderness is simply constructed by a finite number of identical,conventional bi-stable units with relatively low slenderness in series connection.For realizing the axial snap-through instability with a large stroke,common scissors mechanisms are further introduced as rigid constraints to guarantee the synchronous snap-through instability of these bi-stable units.The global feature of the large-stroke snap-through instability realized here is robust and even insusceptible to the local out-of-synchronization of individual units.The present design provides a simple and feasible way to achieve the large-stroke snap-through instability of slender structures,which is expected to be particularly useful for state switching and energy transforming in narrow spaces.
基金support of the National Natural Science Foundation of China(No.52322603)the Science Center for Gas Turbine Project of China(Nos.P2022-B-II-004-001 and P2023-B-II-001-001)+1 种基金the Fundamental Research Funds for the Central Universities,Chinathe Beijing Nova Program of China(Nos.20220484074 and 20230484479).
文摘The utilization of Inlet Guide Vane (IGV) plays a key factor in affecting the instability evolution. Existing literature mainly focuses on the effect of IGV on instability inception that occurs in the rotor region. However, with the emergence of compressor instability starting from the stator region, the mechanism of various instability inceptions that occurs in different blade rows due to the change of IGV angles should be further examined. In this study, experiments were focused on three types of instability inceptions observed previously in a 1.5-stage axial flow compressor. To analyze the conversion of stall evolutions, the compressor rotating speed was set to 17 160 r/min, at which both the blade loading in the stator hub region and rotor tip region were close to the critical value before final compressor stall. Meanwhile, the dynamic test points with high-response were placed to monitor the pressures both at the stator trailing edges and rotor tips. The results indicate that the variation of reaction determines the region where initial instability occurs. Indeed, negative pre-rotation of the inlet guide vane leads to high-reaction, initiating stall disturbance from the rotor region. Positive pre-rotation results in low-reaction, initiating stall disturbance from the stator region. Furthermore, the type of instability evolution is affected by the radial loading distribution under different IGV angles. Specifically, a spike-type inception occurs at the rotor blade tip with a large angle of attack at the rotor inlet (−2°, −4° and −6°). Meanwhile, the critical total pressure ratio at the rotor tip is 1.40 near stall. As the angle of attack decreases, the stator blade loading reaches its critical boundary, with a value of approximately 1.35. At this moment, if the rotor tip maintains high blade loading similar to the stator hub, the partial surge occurs (0° and +2°);otherwise, the hub instability occurs (+4° and +6°).
基金supports of the National Natural Science Foundation of China(Nos.52076129,92360308,52376027)the Shanghai Municipal Education Commission of China(No.2023-02-4)+1 种基金the Fundamental Research Funds for the Central Universities of Chinathe United Innovation Center(UIC)of Aerothermal Technologies for Turbomachinery of China.
文摘Rotating Instability (RI) is a typical unsteady flow phenomenon in compressors and may cause severe aerodynamic noise and even potential nonsynchronous vibration. Most studies of RI are based on the uniform inflow, ignoring the influence of inlet distortions. This study investigates the mechanism of RI in a transonic rotor through full-annulus unsteady simulations, with a particular focus on the effects of boundary layer ingesting distortions. The results show that at the uniform inflow, the RI fluctuations with the broadband hump can be observed over a relatively wide mass flow rate range, and its origin can be attributed to the coupling effect between the tip leakage flow and shear layer instability. At the inlet distortions, the broadband hump only occurs with partial circumferential locations. This kind of flow phenomenon is defined as Partial Rotating Instability (PRI). The PRI only occurs in a narrower mass flow rate range in which the circumferential range of strong shear is sufficiently large and the self-induced unsteady effects are strong enough. Further, this study confirms that the averaged tip leakage flow axial momentum at the onset of RI or PRI is close, so it can be used as the parameter to determine whether RI or PRI occurs.
文摘A hydrodynamic model is used to study Kelvin-Helmholtz(KH)instability of the interface between two particle-laden inviscid fluids moving with two different uniform mean velocities.Explicit eigen-equation is derived to study the effect of suspended particles on the growth rate of KH instability.For dusty gases with negligible volume fraction of heavy particles and small particle-to-fluid mass ratio,the real and imaginary parts of leading-order asymptotic expression derived by the present model for the growth rate are shown to be identical to the earlier results derived by the classical Saffman model established for dusty gases.Beyond the known results,explicit leading-order asymptotic expressions for the effect of suspended particles on the growth rate are derived for several typical cases of basic interest.It is shown that the suspended particles can decrease or increase the growth rate of KH instability depending on the Stokes numbers of the particles and whether the particles are heavier or lighter than the clean fluid.Compared to the mass density of the clean fluid,our results based on leading-order asymptotic solutions show that heavier particles and lighter particles have opposite effects on the growth rate of KH instability,while the effect of neutrally buoyant particles on the growth rate of KH instability is negligible.
基金support from the University Grants Commission(UGC),Government of India,for a Senior Research Fellowship(SRF)with Ref.No.1161/(CSIR-UGC NET DEC.2018)and 16-6(DEC.2018)/2019(NET/CSIR)。
文摘We study the Rayleigh-Taylor instability(RTI)of electrostatic plane wave perturbations in compressible relativistic magnetoplasma fluids with thermal ions under gravity in three different cases of when(ⅰ)electrons are in isothermal equilibrium,i.e.,classical or nondegenerate,(ⅱ)electrons are fully degenerate(with Te=0),and(ⅲ)electrons are partially degenerate or have finite temperature degeneracy(with Te≠0).While in the cases of(ⅰ)and(ⅲ),we focus on the regimes where the particle's thermal energy is more or less than the rest mass energy,i.e.,βe≡kBTe/mec2<1or>1,the case(ⅱ)considers from weakly to ultra-relativistic degenerate regimes.A general expression of the growth rate of instability is obtained and analyzed in the three different cases relevant to laboratory and astrophysical plasmas,which generalize and advance the previous theory on RTI.
基金financially supported by the Science and Engineering Research Board,Government of India(Grant No.CRG/2022/001989)。
文摘A way to enhance the growth of stimulated Raman instability in laser-plasma interactions was investigated.This relies on the application of density modulation of a co-propagating electron beam in plasmas.In the stimulated Raman scattering process,an electromagnetic pump wave decays into a low-frequency wave and a scattered electromagnetic sideband wave.In this process,the pump wave produces an oscillatory velocity associated with the plasma electrons and the beam electrons.These oscillatory velocities combine with the existing low-frequency mode,producing ponderomotive force that drives high-frequency sideband waves.The sidebands couple to the pump wave,driving the beam-mode.A modulation of the electron beam density enhances the growth rate of the instability.The theoretical calculations show about 40%enhancements in growth of Raman instability at resonance(where the electron beam density modulation parameter approaches to unity)for the plasma density of the order of 10^(18)cm^(-3).
基金was supported by the National Key Research and Development Program of China(Grant Nos.2024YFA1611200 and 2018YFA0307000)the National Natural Science Foundation of China(Grant Nos.12274154 and 12404182)。
文摘In order to calculate the multipoles in real materials with considerable intersite Coulomb interaction V,we develop a self-consistent program which starts from the frst-principles calculations to solve the tight-binding Hamiltonian including onsite Coulomb repulsion U,V,and spin-orbital couplingλ.The program is applied to Ba_(2)MgReO_(6)to fgure out the mechanism of structural instability and magnetic ordering.A comprehensive quadrupole phase diagram versus U and V withλ=0.28 eV is calculated.Our results demonstrate that the easy-plane anisotropy and the intersite Coulomb repulsion V must be considered to remove the orbital frustration.The increase of V to>20 meV would arrange quadrupole Q_(x^(2)-y^(2))antiparallelly,accompanied by small parallel Q_(3z)^(2)-r^(2),and stabilize Ba_(2)MgReO_(6)into the body-centered tetragonal structure.Such antiparallel Q_(x^(2)-y^(2))provides a new mechanism for the Dzyaloshinskii-Moriya interaction and gives rise to the canted antiferromagnetic(CAF)state along the[110]axis.Moreover,sizable octupoles such as O_(21)^(31),O_(21)^(33),O_(21)^(34)and O_(21)^(36)are discovered for the frst time in the CAF state.Our study not only provides a comprehensive understanding of the experimental results in Ba_(2)MgReO_(6),but also serves as a general and useful tool for the study of multipole physics in 5d compounds.
