The satellite-based augmentation system(SBAS)provides differential and integrity augmentation services for life safety fields of aviation and navigation.However,the signal structure of SBAS is public,which incurs a ri...The satellite-based augmentation system(SBAS)provides differential and integrity augmentation services for life safety fields of aviation and navigation.However,the signal structure of SBAS is public,which incurs a risk of spoofing attacks.To improve the anti-spoofing capability of the SBAS,European Union and the United States conduct research on navigation message authentication,and promote the standardization of SBAS message authentication.For the development of Beidou satellite-based augmentation system(BDSBAS),this paper proposes navigation message authentication based on the Chinese commercial cryptographic standards.Firstly,this paper expounds the architecture and principles of the SBAS message authentication,and then carries out the design of timed efficient streaming losstolerant authentication scheme(TESLA)and elliptic curve digital signature algorithm(ECDSA)authentication schemes based on Chinese commercial cryptographic standards,message arrangement and the design of over-the-air rekeying(OTAR)message.Finally,this paper conducts a theoretical analysis of the time between authentications(TBA)and maximum authentication latency(MAL)for L5 TESLA-I and L5 ECDSA-Q,and further simulates the reception time of OTAR message,TBA and MAL from the aspects of OTAR message weight and demodulation error rate.The simulation results can provide theoretical supports for the standardization of BDSBAS message authentication.展开更多
The emergence of large language models(LLMs)has brought about revolutionary social value.However,concerns have arisen regarding the generation of deceptive content by LLMs and their potential for misuse.Consequently,a...The emergence of large language models(LLMs)has brought about revolutionary social value.However,concerns have arisen regarding the generation of deceptive content by LLMs and their potential for misuse.Consequently,a crucial research question arises:How can we differentiate between AI-generated and human-authored text?Existing detectors face some challenges,such as operating as black boxes,relying on supervised training,and being vulnerable to manipulation and misinformation.To tackle these challenges,we propose an innovative unsupervised white-box detection method that utilizes a“dual-driven verification mechanism”to achieve high-performance detection,even in the presence of obfuscated attacks in the text content.To be more specific,we initially employ the SpaceInfi strategy to enhance the difficulty of detecting the text content.Subsequently,we randomly select vulnerable spots from the text and perturb them using another pre-trained language model(e.g.,T5).Finally,we apply a dual-driven defense mechanism(D3M)that validates text content with perturbations,whether generated by a model or authored by a human,based on the dimensions of Information TransmissionQuality and Information TransmissionDensity.Through experimental validation,our proposed novelmethod demonstrates state-of-the-art(SOTA)performancewhen exposed to equivalent levels of perturbation intensity across multiple benchmarks,thereby showcasing the effectiveness of our strategies.展开更多
Neuromodulation techniques effectively intervene in cognitive function,holding considerable scientific and practical value in fields such as aerospace,medicine,life sciences,and brain research.These techniques utilize...Neuromodulation techniques effectively intervene in cognitive function,holding considerable scientific and practical value in fields such as aerospace,medicine,life sciences,and brain research.These techniques utilize electrical stimulation to directly or indirectly target specific brain regions,modulating neural activity and influencing broader brain networks,thereby regulating cognitive function.Regulating cognitive function involves an understanding of aspects such as perception,learning and memory,attention,spatial cognition,and physical function.To enhance the application of cognitive regulation in the general population,this paper reviews recent publications from the Web of Science to assess the advancements and challenges of invasive and non-invasive stimulation methods in modulating cognitive functions.This review covers various neuromodulation techniques for cognitive intervention,including deep brain stimulation,vagus nerve stimulation,and invasive methods using microelectrode arrays.The non-invasive techniques discussed include transcranial magnetic stimulation,transcranial direct current stimulation,transcranial alternating current stimulation,transcutaneous electrical acupoint stimulation,and time interference stimulation for activating deep targets.Invasive stimulation methods,which are ideal for studying the pathogenesis of neurological diseases,tend to cause greater trauma and have been less researched in the context of cognitive function regulation.Non-invasive methods,particularly newer transcranial stimulation techniques,are gentler and more appropriate for regulating cognitive functions in the general population.These include transcutaneous acupoint electrical stimulation using acupoints and time interference methods for activating deep targets.This paper also discusses current technical challenges and potential future breakthroughs in neuromodulation technology.It is recommended that neuromodulation techniques be combined with neural detection methods to better assess their effects and improve the accuracy of non-invasive neuromodulation.Additionally,researching closed-loop feedback neuromodulation methods is identified as a promising direction for future development.展开更多
In conventional higher-order topological insulators(HOTIs),the emergence of topological states can be explained by using the nonzero bulk polarization index.However,corner states emerge in HOTIs with incomplete bounda...In conventional higher-order topological insulators(HOTIs),the emergence of topological states can be explained by using the nonzero bulk polarization index.However,corner states emerge in HOTIs with incomplete boundary unit cells(i.e.,boundary defects)even though the bulk polarization is zero,which challenges the conventional understanding of HOTIs.Here,based on a Kekul´e-distorted honeycomb lattice with incomplete unit cells,we reveal that incomplete unit cells exhibit fractional charges through the analysis of Wannier centers by developing a compensation method and creating the concept of Wannier center domain(WCD)which is the smallest region that one Wannier center occupies.This method compensates for the missing parts of these boundary incomplete unit cells with additional WCDs to make them complete.The compensated WCDs automatically carry the corresponding charge,and this charge together with that of the incomplete unit cell constitutes the total charge of the complete unit cell after compensation.We conclude that the emergence of corner states is attributed to the filling anomaly,which is a fundamental mechanism.Our results refresh the understanding of HOTIs,especially those with structural discontinuities,and provide a novel design for topological states which have application value in producing optical functional devices.展开更多
Tajikistan,a mountainous country and a vital water tower for Central Asia,is becoming increasingly vulnerable to snow drought under climate change,threatening its snow-and glacier-fed streamflow.Yet,the impacts of sno...Tajikistan,a mountainous country and a vital water tower for Central Asia,is becoming increasingly vulnerable to snow drought under climate change,threatening its snow-and glacier-fed streamflow.Yet,the impacts of snow drought on the regional hydrology remain insufficiently understood.In this study,we integrated multisource data,including the Fifth Generation European Centre for Medium-Range Weather Forecasts Atmospheric Reanalysis for Land Applications(ERA5-Land)data and hydrological station data,to systematically assess the snow drought patterns and their impacts on streamflow during 1950–2023.We identified snow drought events based on precipitation and snow fraction anomalies relative to climatological means and classified them into warm snow drought,dry snow drought,and warm&dry snow drought.The results revealed that snow drought was a recurrent phenomenon,occurring in 51.70%of the years during the study period,with warm&dry snow drought accounting for 21.90%of the total events.Both the frequency and severity exhibited pronounced spatial variability,largely governed by the elevation and snowfall fraction.Specifically,the frequency of warm snow drought was negatively correlated with the snowfall fraction,decreasing on average by 0.20 per unit increase in snowfall fraction,whereas the frequency of dry snow drought was positively correlated,increasing by 0.07 per unit increase.The streamflow analysis results demonstrated that snow drought typically reduced the warm-season discharge by 5.00%–18.00%in certain rivers,thereby exacerbating the water stress during the dry season.The results of this study advance our understanding by explicitly linking the types of snow drought to hydrological responses in Central Asia’s high mountains,providing a scientific basis for climate adaptation and sustainable water resource management in Tajikistan.展开更多
Human activities have significantly impacted the land surface temperature(LST),endangering human health;however,the relationship between these two factors has not been adequately quantified.This study comprehensively ...Human activities have significantly impacted the land surface temperature(LST),endangering human health;however,the relationship between these two factors has not been adequately quantified.This study comprehensively constructs a Human Activity Intensity(HAI)index and employs the Maximal Information Coefficient,four-quadrant model,and XGBoostSHAP model to investigate the spatiotemporal relationship and influencing factors of HAI-LST in the Yellow River Basin(YRB)from 2000 to 2020.The results indicated that from 2000 to 2020,as HAI and LST increased,the static HAI-LST relationship in the YRB showed a positive correlation that continued to strengthen.This dynamic relationship exhibited conflicting development,with the proportion of coordinated to conflicting regions shifting from 1:4 to 1:2,indicating a reduction in conflict intensity.Notably,only the degree of conflict in the source area decreased significantly,whereas it intensified in the upper and lower reaches.The key factors influencing the HAI-LST relationship include fractional vegetation cover,slope,precipitation,and evapotranspiration,along with region-specific factors such as PM_(2.5),biodiversity,and elevation.Based on these findings,region-specific ecological management strategies have been proposed to mitigate conflict-prone areas and alleviate thermal stress,thereby providing important guidance for promoting harmonious development between humans and nature.展开更多
A large-scale view of the magnetospheric cusp is expected to be obtained by the Soft X-ray Imager(SXI)onboard the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE).However,it is challenging to trace the three-d...A large-scale view of the magnetospheric cusp is expected to be obtained by the Soft X-ray Imager(SXI)onboard the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE).However,it is challenging to trace the three-dimensional cusp boundary from a two-dimensional X-ray image because the detected X-ray signals will be integrated along the line of sight.In this work,a global magnetohydrodynamic code was used to simulate the X-ray images and photon count images,assuming an interplanetary magnetic field with a pure Bz component.The assumption of an elliptic cusp boundary at a given altitude was used to trace the equatorward and poleward boundaries of the cusp from a simulated X-ray image.The average discrepancy was less than 0.1 RE.To reduce the influence of instrument effects and cosmic X-ray backgrounds,image denoising was considered before applying the method above to SXI photon count images.The cusp boundaries were reasonably reconstructed from the noisy X-ray image.展开更多
This article analyzed the importance of information monitoring and quick response on agricultural focuses and significant events, proposed the workflow and technical framework for information monitoring and quick resp...This article analyzed the importance of information monitoring and quick response on agricultural focuses and significant events, proposed the workflow and technical framework for information monitoring and quick response based on modern information technologies, and explained key technologies during implementation and the functional structure for prototype system of the technical support platform.展开更多
Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background...Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.展开更多
The acquisition of spatial-temporal information of frozen soil is fundamental for the study of frozen soil dynamics and its feedback to climate change in cold regions.With advancement of remote sensing and better unde...The acquisition of spatial-temporal information of frozen soil is fundamental for the study of frozen soil dynamics and its feedback to climate change in cold regions.With advancement of remote sensing and better understanding of frozen soil dynamics,discrimination of freeze and thaw status of surface soil based on passive microwave remote sensing and numerical simulation of frozen soil processes under water and heat transfer principles provides valuable means for regional and global frozen soil dynamic monitoring and systematic spatial-temporal responses to global change.However,as an important data source of frozen soil processes,remotely sensed information has not yet been fully utilized in the numerical simulation of frozen soil processes.Although great progress has been made in remote sensing and frozen soil physics,yet few frozen soil research has been done on the application of remotely sensed information in association with the numerical model for frozen soil process studies.In the present study,a distributed numerical model for frozen soil dynamic studies based on coupled water-heat transferring theory in association with remotely sensed frozen soil datasets was developed.In order to reduce the uncertainty of the simulation,the remotely sensed frozen soil information was used to monitor and modify relevant parameters in the process of model simulation.The remotely sensed information and numerically simulated spatial-temporal frozen soil processes were validated by in-situ field observations in cold regions near the town of Naqu on the East-Central Tibetan Plateau.The results suggest that the overall accuracy of the algorithm for discriminating freeze and thaw status of surface soil based on passive microwave remote sensing was more than 95%.These results provided an accurate initial freeze and thaw status of surface soil for coupling and calibrating the numerical model of this study.The numerically simulated frozen soil processes demonstrated good performance of the distributed numerical model based on the coupled water-heat transferring theory.The relatively larger uncertainties of the numerical model were found in alternating periods between freezing and thawing of surface soil.The average accuracy increased by about 5%after integrating remotely sensed information on the surface soil.The simulation accuracy was significantly improved,especially in transition periods between freezing and thawing of the surface soil.展开更多
Simultaneous Localization and Mapping(SLAM)is the foundation of autonomous navigation for unmanned systems.The existing SLAM solutions are mainly divided into the visual SLAM(vSLAM)equipped with camera and the lidar S...Simultaneous Localization and Mapping(SLAM)is the foundation of autonomous navigation for unmanned systems.The existing SLAM solutions are mainly divided into the visual SLAM(vSLAM)equipped with camera and the lidar SLAM equipped with lidar.However,pure visual SLAM have shortcomings such as low positioning accuracy,the paper proposes a visual-inertial information fusion SLAM based on Runge-Kutta improved pre-integration.First,the Inertial Measurement Unit(IMU)information between two adjacent keyframes is pre-integrated at the front-end to provide IMU constraints for visual-inertial information fusion.In particular,to improve the accuracy in pre-integration,the paper uses the RungeKutta algorithm instead of Euler integral to calculate the pre-integration value at the next moment.Then,the IMU pre-integration value is used as the initial value of the system state at the current frame time.We combine the visual reprojection error and imu pre-integration error to optimize the state variables such as speed and pose,and restore map points’three-dimensional coordinates.Finally,we set a sliding window to optimize map points’coordinates and state variables.The experimental part is divided into dataset experiment and complex indoor-environment experiment.The results show that compared with pure visual SLAM and the existing visual-inertial fusion SLAM,our method has higher positioning accuracy.展开更多
Experimental teaching plays a crucial role in the trainings of students＇ abilities to analyze and solve problems. Therefore, it is very necessary to continuously carry out experiment teaching reform, improve experime...Experimental teaching plays a crucial role in the trainings of students＇ abilities to analyze and solve problems. Therefore, it is very necessary to continuously carry out experiment teaching reform, improve experiment teaching methods and means, and comprehensively open laboratories so as to provide students with more opportunities of doing experiments. To improve the teaching effect of electronic information experimental courses, a network interactive virtual experimental platform is developed. This platform allows students to finish the construction of all kinds of circuit structures and test virtual instruments in a simulation environment, upload experimental data and also interactively communicate with teachers through the lnternet. The platform can be applied to the teaching activities of related electronic information experimental courses, and also can be used as an aid teaching method for theory teachers. Therefore, it possesses a very good interactivity, and makes up the disadvantages of the experimental teaching in hardware environment, so that a feasible solution is provided for the opening of laboratories.展开更多
The advent of the information era has resulted in exceptional advances in geographic science.The domain of geographic science has expanded from traditional physical and human geography to physical,human,and informatio...The advent of the information era has resulted in exceptional advances in geographic science.The domain of geographic science has expanded from traditional physical and human geography to physical,human,and information geography,resulting in the emergence of the field of information geography.Three subdisciplines have gradually formed,i.e.,geographic remote sensing science,geographic information science,and geographic data science.With a view towards preparing a description of the disciplinary structure of geographic science for the“Development Strategy of Discipline and Frontier Research in China(2021-2035)”,this article summarizes the history,definition,and disciplinary structure of information geography.The strategic layout of the discipline,along with the goals and key directions of priority development fields,are also highlighted.The insights into this new discipline provided in this paper will promote the development and application of remote sensing and geographic information within the framework of geographic science,advancing the synthesis of geographic research and the integrated development of geographic science.展开更多
The current study was conducted to probe farmers’ accessible agricultural information sources in rural areas of Pakistan. For this purpose a random sample of 160 households from four districts of the Punjab province ...The current study was conducted to probe farmers’ accessible agricultural information sources in rural areas of Pakistan. For this purpose a random sample of 160 households from four districts of the Punjab province of Pakistan was selected. Data were collected using validated and expert reviewed questionnaire with the help of interview method. The results revealed that majority of farmers (47.5%) ranked neighbor-friends-relatives as first source of information while 31.9% of farmers ranked this source as second and 33.7% farmers’ ranked it as third major source. With contrast to this very less farmers (10%) ranked agricultural extension staff as first information source. Keeping in view the study results, the performance of extension staff is not encouraging;therefore government should plan and launch a policy to foster performance of public agricultural extension system to fulfill the advanced technological needs of farmers to flourish sustainable agriculture and rural development.展开更多
Multi‐agent reinforcement learning relies on reward signals to guide the policy networks of individual agents.However,in high‐dimensional continuous spaces,the non‐stationary environment can provide outdated experi...Multi‐agent reinforcement learning relies on reward signals to guide the policy networks of individual agents.However,in high‐dimensional continuous spaces,the non‐stationary environment can provide outdated experiences that hinder convergence,resulting in ineffective training performance for multi‐agent systems.To tackle this issue,a novel reinforcement learning scheme,Mutual Information Oriented Deep Skill Chaining(MioDSC),is proposed that generates an optimised cooperative policy by incorporating intrinsic rewards based on mutual information to improve exploration efficiency.These rewards encourage agents to diversify their learning process by engaging in actions that increase the mutual information between their actions and the environment state.In addition,MioDSC can generate cooperative policies using the options framework,allowing agents to learn and reuse complex action sequences and accelerating the convergence speed of multi‐agent learning.MioDSC was evaluated in the multi‐agent particle environment and the StarCraft multi‐agent challenge at varying difficulty levels.The experimental results demonstrate that MioDSC outperforms state‐of‐the‐art methods and is robust across various multi‐agent system tasks with high stability.展开更多
The Regional Comprehensive Economic Partnership(RCEP)has created favorable conditions for building deeply integrated agricultural value chains(AVC)in Asia-Pacific.Based on the RCEP agreement,this study employed the gl...The Regional Comprehensive Economic Partnership(RCEP)has created favorable conditions for building deeply integrated agricultural value chains(AVC)in Asia-Pacific.Based on the RCEP agreement,this study employed the global trade analysis project(GTAP)model to evaluate the impact of RCEP on AVC of member countries in terms of time,tariff reduction,and reduction of non-tariff barriers(NTB).The results indicate that(1)the implementation of RCEP boosts the value-added to agricultural exports for most member countries,particularly in competitive industries;(2)the increase in domestic production and processing capacity,reflected in domestic value-added(DVA),is the primary factor driving the rise in the value-added of agricultural exports across various industries of member countries;(3)RCEP enhances the participation of most regional countries in AVC,with varying impacts on AVC positioning,thereby fostering regional AvC development;and(4)RCEP has a positive effect on AVC indicators both in the short and long term,with the effect becoming more pronounced over time.Additionally,reducing NTB enhances the positive effects of tariff reductions on AVC indicators.Based on the analyses,the following recommendations are proposed:(1)Leverage the development opportunities arising from RCEP implementation to enhance the agricultural DVA;(2)capitalize on cooperative opportunities created by RCEP to build cohesive regional AVC;and(3)prioritize the effective implementation of RCEP'shigh-qualityrules.展开更多
Yellow rust(Puccinia striiformis f.sp.Tritici,YR)and fusarium head blight(Fusarium graminearum,FHB)are the two main diseases affecting wheat in the main grain-producing areas of East China,which is common for the two ...Yellow rust(Puccinia striiformis f.sp.Tritici,YR)and fusarium head blight(Fusarium graminearum,FHB)are the two main diseases affecting wheat in the main grain-producing areas of East China,which is common for the two diseases to appear simultaneously in some main production areas.It is necessary to discriminate wheat YR and FHB at the regional scale to accurately locate the disease in space,conduct detailed disease severity monitoring,and scientific control.Four images on different dates were acquired from Sentinel-2,Landsat-8,and Gaofen-1 during the critical period of winter wheat,and 22 remote sensing features that characterize the wheat growth status were then calculated.Meanwhile,6 meteorological parameters that reflect the wheat phenological information were also obtained by combining the site meteorological data and spatial interpolation technology.Then,the principal components(PCs)of comprehensive remote sensing and meteorological features were extracted with principal component analysis(PCA).The PCs-based discrimination models were established to map YR and FHB damage using the random forest(RF)and backpropagation neural network(BPNN).The models’performance was verified based on the disease field truth data(57 plots during the filling period)and 5-fold cross-validation.The results revealed that the PCs obtained after PCA dimensionality reduction outperformed the initial features(IFs)from remote sensing and meteorology in discriminating between the two diseases.Compared to the IFs,the average area under the curve for both micro-average and macro-average ROC curves increased by 0.07 in the PCs-based RF models and increased by 0.16 and 0.13,respectively,in the PCs-based BPNN models.Notably,the PCs-based BPNN discrimination model emerged as the most effective,achieving an overall accuracy of 83.9%.Our proposed discrimination model for wheat YR and FHB,coupled with multi-source remote sensing images and meteorological data,overcomes the limitations of a single-sensor and single-phase remote sensing information in multiple stress discrimination in cloudy and rainy areas.It performs well in revealing the damage spatial distribution of the two diseases at a regional scale,providing a basis for detailed disease severity monitoring,and scientific prevention and control.展开更多
In this paper,a wideband true time delay line for X-band is designed to overcome the beam dispersion problem in a high-resolution spaceborne synthetic aperture radar phased array antenna system.The delay line loads th...In this paper,a wideband true time delay line for X-band is designed to overcome the beam dispersion problem in a high-resolution spaceborne synthetic aperture radar phased array antenna system.The delay line loads the electromagnetic bandgap structure on the upper surface of the substrate integrated waveguide.This is equivalent to including an additional inductance-capacitance for energy storage,which realizes the slow-wave effect.A microstrip line-SIW tapered transition structure is introduced to achieve a low loss and a large bandwidth.In the frequency band between 8-12 GHz,the measured results show that the delay multiplier of the delay line reaches 4 times,i.e.,delay line’s delay time is 4 times larger than 50Ωmicrostrip line with same length.Furthermore,the delay fluctuation,i.e.,the difference between the maximum and minimum delay as a percentage of the standard delay is only 2.5%,the insertion loss is less than-2.5 dB,and the return loss is less than-15 dB.Compared with the existing delay lines,the proposed delay line has the advantages of high delay efficiency,low delay error,wide bandwidth and low loss,which has good practical value and application prospects.展开更多
Dense-array ambient noise tomography is a powerful tool for achieving high-resolution subsurface imag-ing,significantly impacting geohazard prevention and control.Conventional dense-array studies,how-ever,require simu...Dense-array ambient noise tomography is a powerful tool for achieving high-resolution subsurface imag-ing,significantly impacting geohazard prevention and control.Conventional dense-array studies,how-ever,require simultaneous observations of numerous stations for extensive coverage.To conduct a comprehensive karst feature investigation with limited stations,we designed a new synchronous-asyn-chronous observation system that facilitates dense array observations.We conducted two rounds of asynchronous observations,each lasting approximately 24 h,in combination with synchronous backbone stations.We achieved wide-ranging coverage of the study area utilizing 197 nodal receivers,with an average station spacing of 7 m.The beamforming results revealed distinct variations in the noise source distributions between day and night.We estimated the source strength in the stationary phase zone and used a weighting scheme for stacking the cross-correlation functions(C ^(1) functions)to suppress the influ-ence of nonuniform noise source distributions.The weights were derived from the similarity coefficients between multicomponent C^(1)functions related to Rayleigh waves.We employed the cross-correlation of C ^(1) functions(C^(2)methods)to obtain the empirical Green’s functions between asynchronous stations.To eliminate artifacts in C ^(2) functions from higher-mode surface waves in C^(1)functions,we filtered the C^(1)functions on the basis of different particle motions linked to multimode Rayleigh waves.The dispersion measurements of Rayleigh waves obtained from both the C^(1)and C^(2)functions were utilized in surface wave tomography.The inverted three-dimensional(3D)shear-wave(S-wave)velocity model reveals two significant low-velocity zones at depths ranging from 40 to 60 m,which align well with the karst caves found in the drilling data.The method of short-term synchronous-asynchronous ambient noise tomography shows promise as a cost-effective and efficient approach for urban geohazard investigations.展开更多
基金supported by National Natural Science Foundation of China:Space-based occultation detection with ground-based GNSS atmospheric horizontal gradient model(41904033).
文摘The satellite-based augmentation system(SBAS)provides differential and integrity augmentation services for life safety fields of aviation and navigation.However,the signal structure of SBAS is public,which incurs a risk of spoofing attacks.To improve the anti-spoofing capability of the SBAS,European Union and the United States conduct research on navigation message authentication,and promote the standardization of SBAS message authentication.For the development of Beidou satellite-based augmentation system(BDSBAS),this paper proposes navigation message authentication based on the Chinese commercial cryptographic standards.Firstly,this paper expounds the architecture and principles of the SBAS message authentication,and then carries out the design of timed efficient streaming losstolerant authentication scheme(TESLA)and elliptic curve digital signature algorithm(ECDSA)authentication schemes based on Chinese commercial cryptographic standards,message arrangement and the design of over-the-air rekeying(OTAR)message.Finally,this paper conducts a theoretical analysis of the time between authentications(TBA)and maximum authentication latency(MAL)for L5 TESLA-I and L5 ECDSA-Q,and further simulates the reception time of OTAR message,TBA and MAL from the aspects of OTAR message weight and demodulation error rate.The simulation results can provide theoretical supports for the standardization of BDSBAS message authentication.
文摘The emergence of large language models(LLMs)has brought about revolutionary social value.However,concerns have arisen regarding the generation of deceptive content by LLMs and their potential for misuse.Consequently,a crucial research question arises:How can we differentiate between AI-generated and human-authored text?Existing detectors face some challenges,such as operating as black boxes,relying on supervised training,and being vulnerable to manipulation and misinformation.To tackle these challenges,we propose an innovative unsupervised white-box detection method that utilizes a“dual-driven verification mechanism”to achieve high-performance detection,even in the presence of obfuscated attacks in the text content.To be more specific,we initially employ the SpaceInfi strategy to enhance the difficulty of detecting the text content.Subsequently,we randomly select vulnerable spots from the text and perturb them using another pre-trained language model(e.g.,T5).Finally,we apply a dual-driven defense mechanism(D3M)that validates text content with perturbations,whether generated by a model or authored by a human,based on the dimensions of Information TransmissionQuality and Information TransmissionDensity.Through experimental validation,our proposed novelmethod demonstrates state-of-the-art(SOTA)performancewhen exposed to equivalent levels of perturbation intensity across multiple benchmarks,thereby showcasing the effectiveness of our strategies.
基金supported by STI 2030-Major Projects,No.2021ZD0201603(to JL)the Joint Foundation Program of the Chinese Academy of Sciences,No.8091A170201(to JL)+1 种基金the National Natural Science Foundation of China,Nos.T2293730(to XC),T2293731(to XC),T2293734(to XC),62471291(to YW),62121003(to XC),61960206012(to XC),62333020(to XC),and 62171434(to XC)the National Key Research and Development Program of China,Nos.2022YFC2402501(to XC),2022YFB3205602(to XC).
文摘Neuromodulation techniques effectively intervene in cognitive function,holding considerable scientific and practical value in fields such as aerospace,medicine,life sciences,and brain research.These techniques utilize electrical stimulation to directly or indirectly target specific brain regions,modulating neural activity and influencing broader brain networks,thereby regulating cognitive function.Regulating cognitive function involves an understanding of aspects such as perception,learning and memory,attention,spatial cognition,and physical function.To enhance the application of cognitive regulation in the general population,this paper reviews recent publications from the Web of Science to assess the advancements and challenges of invasive and non-invasive stimulation methods in modulating cognitive functions.This review covers various neuromodulation techniques for cognitive intervention,including deep brain stimulation,vagus nerve stimulation,and invasive methods using microelectrode arrays.The non-invasive techniques discussed include transcranial magnetic stimulation,transcranial direct current stimulation,transcranial alternating current stimulation,transcutaneous electrical acupoint stimulation,and time interference stimulation for activating deep targets.Invasive stimulation methods,which are ideal for studying the pathogenesis of neurological diseases,tend to cause greater trauma and have been less researched in the context of cognitive function regulation.Non-invasive methods,particularly newer transcranial stimulation techniques,are gentler and more appropriate for regulating cognitive functions in the general population.These include transcutaneous acupoint electrical stimulation using acupoints and time interference methods for activating deep targets.This paper also discusses current technical challenges and potential future breakthroughs in neuromodulation technology.It is recommended that neuromodulation techniques be combined with neural detection methods to better assess their effects and improve the accuracy of non-invasive neuromodulation.Additionally,researching closed-loop feedback neuromodulation methods is identified as a promising direction for future development.
基金supported by the Natural Science Basic Research Program of Shaanxi Province (Grant Nos.2024JC-JCQN-06 and2025JC-QYCX-006)the National Natural Science Foundation of China (Grant No.12474337)Chinese Academy of Sciences Project (Grant Nos.E4BA270100,E4Z127010F,E4Z6270100,and E53327020D)。
文摘In conventional higher-order topological insulators(HOTIs),the emergence of topological states can be explained by using the nonzero bulk polarization index.However,corner states emerge in HOTIs with incomplete boundary unit cells(i.e.,boundary defects)even though the bulk polarization is zero,which challenges the conventional understanding of HOTIs.Here,based on a Kekul´e-distorted honeycomb lattice with incomplete unit cells,we reveal that incomplete unit cells exhibit fractional charges through the analysis of Wannier centers by developing a compensation method and creating the concept of Wannier center domain(WCD)which is the smallest region that one Wannier center occupies.This method compensates for the missing parts of these boundary incomplete unit cells with additional WCDs to make them complete.The compensated WCDs automatically carry the corresponding charge,and this charge together with that of the incomplete unit cell constitutes the total charge of the complete unit cell after compensation.We conclude that the emergence of corner states is attributed to the filling anomaly,which is a fundamental mechanism.Our results refresh the understanding of HOTIs,especially those with structural discontinuities,and provide a novel design for topological states which have application value in producing optical functional devices.
基金supported by the National Key Research and Development Project of China(2025YFE0103300)the National Natural Science Foundation of China(W2412135)+2 种基金the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2024D01A143,2025D01B165)the China Postdoctoral Science Foundation(GZC20250226)the S&T Innovation and Development Project of Information Institution of Ministry of Emergency Management,China(2024506).
文摘Tajikistan,a mountainous country and a vital water tower for Central Asia,is becoming increasingly vulnerable to snow drought under climate change,threatening its snow-and glacier-fed streamflow.Yet,the impacts of snow drought on the regional hydrology remain insufficiently understood.In this study,we integrated multisource data,including the Fifth Generation European Centre for Medium-Range Weather Forecasts Atmospheric Reanalysis for Land Applications(ERA5-Land)data and hydrological station data,to systematically assess the snow drought patterns and their impacts on streamflow during 1950–2023.We identified snow drought events based on precipitation and snow fraction anomalies relative to climatological means and classified them into warm snow drought,dry snow drought,and warm&dry snow drought.The results revealed that snow drought was a recurrent phenomenon,occurring in 51.70%of the years during the study period,with warm&dry snow drought accounting for 21.90%of the total events.Both the frequency and severity exhibited pronounced spatial variability,largely governed by the elevation and snowfall fraction.Specifically,the frequency of warm snow drought was negatively correlated with the snowfall fraction,decreasing on average by 0.20 per unit increase in snowfall fraction,whereas the frequency of dry snow drought was positively correlated,increasing by 0.07 per unit increase.The streamflow analysis results demonstrated that snow drought typically reduced the warm-season discharge by 5.00%–18.00%in certain rivers,thereby exacerbating the water stress during the dry season.The results of this study advance our understanding by explicitly linking the types of snow drought to hydrological responses in Central Asia’s high mountains,providing a scientific basis for climate adaptation and sustainable water resource management in Tajikistan.
基金Shanxi Province Graduate Research Practice Innovation Project,No.2023KY465Project on the Reform of Graduate Education and Teaching in Shanxi Province,No.2021YJJG146+1 种基金Research Project of Shanxi Provincial Cultural Relics Bureau,No.22-8-14-1400-119National Key R&D Program of China,No.2021YFB3901300。
文摘Human activities have significantly impacted the land surface temperature(LST),endangering human health;however,the relationship between these two factors has not been adequately quantified.This study comprehensively constructs a Human Activity Intensity(HAI)index and employs the Maximal Information Coefficient,four-quadrant model,and XGBoostSHAP model to investigate the spatiotemporal relationship and influencing factors of HAI-LST in the Yellow River Basin(YRB)from 2000 to 2020.The results indicated that from 2000 to 2020,as HAI and LST increased,the static HAI-LST relationship in the YRB showed a positive correlation that continued to strengthen.This dynamic relationship exhibited conflicting development,with the proportion of coordinated to conflicting regions shifting from 1:4 to 1:2,indicating a reduction in conflict intensity.Notably,only the degree of conflict in the source area decreased significantly,whereas it intensified in the upper and lower reaches.The key factors influencing the HAI-LST relationship include fractional vegetation cover,slope,precipitation,and evapotranspiration,along with region-specific factors such as PM_(2.5),biodiversity,and elevation.Based on these findings,region-specific ecological management strategies have been proposed to mitigate conflict-prone areas and alleviate thermal stress,thereby providing important guidance for promoting harmonious development between humans and nature.
基金funded by the National Natural Science Foundation of China(NNSFC)under Grant Numbers 42322408,42188101,and 42441809Additional support was provided by the Climbing Program of the National Space Science Center(NSSC,Grant No.E4PD3005)as well as the Specialized Research Fund for State Key Laboratories of China.
文摘A large-scale view of the magnetospheric cusp is expected to be obtained by the Soft X-ray Imager(SXI)onboard the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE).However,it is challenging to trace the three-dimensional cusp boundary from a two-dimensional X-ray image because the detected X-ray signals will be integrated along the line of sight.In this work,a global magnetohydrodynamic code was used to simulate the X-ray images and photon count images,assuming an interplanetary magnetic field with a pure Bz component.The assumption of an elliptic cusp boundary at a given altitude was used to trace the equatorward and poleward boundaries of the cusp from a simulated X-ray image.The average discrepancy was less than 0.1 RE.To reduce the influence of instrument effects and cosmic X-ray backgrounds,image denoising was considered before applying the method above to SXI photon count images.The cusp boundaries were reasonably reconstructed from the noisy X-ray image.
文摘This article analyzed the importance of information monitoring and quick response on agricultural focuses and significant events, proposed the workflow and technical framework for information monitoring and quick response based on modern information technologies, and explained key technologies during implementation and the functional structure for prototype system of the technical support platform.
基金The Science and Technoloav Innovation Program of the Chinese Academy of Agricultural Sciences(CAAS-ASTIP-2020-A11-02)is appreciated for supporting this study.
文摘Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.
基金This work was supported by the National Key R&D Program of(Grant No.2016YFA0602302).
文摘The acquisition of spatial-temporal information of frozen soil is fundamental for the study of frozen soil dynamics and its feedback to climate change in cold regions.With advancement of remote sensing and better understanding of frozen soil dynamics,discrimination of freeze and thaw status of surface soil based on passive microwave remote sensing and numerical simulation of frozen soil processes under water and heat transfer principles provides valuable means for regional and global frozen soil dynamic monitoring and systematic spatial-temporal responses to global change.However,as an important data source of frozen soil processes,remotely sensed information has not yet been fully utilized in the numerical simulation of frozen soil processes.Although great progress has been made in remote sensing and frozen soil physics,yet few frozen soil research has been done on the application of remotely sensed information in association with the numerical model for frozen soil process studies.In the present study,a distributed numerical model for frozen soil dynamic studies based on coupled water-heat transferring theory in association with remotely sensed frozen soil datasets was developed.In order to reduce the uncertainty of the simulation,the remotely sensed frozen soil information was used to monitor and modify relevant parameters in the process of model simulation.The remotely sensed information and numerically simulated spatial-temporal frozen soil processes were validated by in-situ field observations in cold regions near the town of Naqu on the East-Central Tibetan Plateau.The results suggest that the overall accuracy of the algorithm for discriminating freeze and thaw status of surface soil based on passive microwave remote sensing was more than 95%.These results provided an accurate initial freeze and thaw status of surface soil for coupling and calibrating the numerical model of this study.The numerically simulated frozen soil processes demonstrated good performance of the distributed numerical model based on the coupled water-heat transferring theory.The relatively larger uncertainties of the numerical model were found in alternating periods between freezing and thawing of surface soil.The average accuracy increased by about 5%after integrating remotely sensed information on the surface soil.The simulation accuracy was significantly improved,especially in transition periods between freezing and thawing of the surface soil.
基金supported by the China Postdoctoral Science Foundation under Grant 2019M653870XBNational Natural Science Foundation of Shanxi Province under Grants No.2020GY-003 and 2021GY-036+1 种基金National Natural Science Foundation of China under Grants 62001340Fundamental Research Funds for the Central Universities,China,XJS211306 and JC2007
文摘Simultaneous Localization and Mapping(SLAM)is the foundation of autonomous navigation for unmanned systems.The existing SLAM solutions are mainly divided into the visual SLAM(vSLAM)equipped with camera and the lidar SLAM equipped with lidar.However,pure visual SLAM have shortcomings such as low positioning accuracy,the paper proposes a visual-inertial information fusion SLAM based on Runge-Kutta improved pre-integration.First,the Inertial Measurement Unit(IMU)information between two adjacent keyframes is pre-integrated at the front-end to provide IMU constraints for visual-inertial information fusion.In particular,to improve the accuracy in pre-integration,the paper uses the RungeKutta algorithm instead of Euler integral to calculate the pre-integration value at the next moment.Then,the IMU pre-integration value is used as the initial value of the system state at the current frame time.We combine the visual reprojection error and imu pre-integration error to optimize the state variables such as speed and pose,and restore map points’three-dimensional coordinates.Finally,we set a sliding window to optimize map points’coordinates and state variables.The experimental part is divided into dataset experiment and complex indoor-environment experiment.The results show that compared with pure visual SLAM and the existing visual-inertial fusion SLAM,our method has higher positioning accuracy.
文摘Experimental teaching plays a crucial role in the trainings of students＇ abilities to analyze and solve problems. Therefore, it is very necessary to continuously carry out experiment teaching reform, improve experiment teaching methods and means, and comprehensively open laboratories so as to provide students with more opportunities of doing experiments. To improve the teaching effect of electronic information experimental courses, a network interactive virtual experimental platform is developed. This platform allows students to finish the construction of all kinds of circuit structures and test virtual instruments in a simulation environment, upload experimental data and also interactively communicate with teachers through the lnternet. The platform can be applied to the teaching activities of related electronic information experimental courses, and also can be used as an aid teaching method for theory teachers. Therefore, it possesses a very good interactivity, and makes up the disadvantages of the experimental teaching in hardware environment, so that a feasible solution is provided for the opening of laboratories.
基金National Natural Science Foundation of China,No.41988101。
文摘The advent of the information era has resulted in exceptional advances in geographic science.The domain of geographic science has expanded from traditional physical and human geography to physical,human,and information geography,resulting in the emergence of the field of information geography.Three subdisciplines have gradually formed,i.e.,geographic remote sensing science,geographic information science,and geographic data science.With a view towards preparing a description of the disciplinary structure of geographic science for the“Development Strategy of Discipline and Frontier Research in China(2021-2035)”,this article summarizes the history,definition,and disciplinary structure of information geography.The strategic layout of the discipline,along with the goals and key directions of priority development fields,are also highlighted.The insights into this new discipline provided in this paper will promote the development and application of remote sensing and geographic information within the framework of geographic science,advancing the synthesis of geographic research and the integrated development of geographic science.
文摘The current study was conducted to probe farmers’ accessible agricultural information sources in rural areas of Pakistan. For this purpose a random sample of 160 households from four districts of the Punjab province of Pakistan was selected. Data were collected using validated and expert reviewed questionnaire with the help of interview method. The results revealed that majority of farmers (47.5%) ranked neighbor-friends-relatives as first source of information while 31.9% of farmers ranked this source as second and 33.7% farmers’ ranked it as third major source. With contrast to this very less farmers (10%) ranked agricultural extension staff as first information source. Keeping in view the study results, the performance of extension staff is not encouraging;therefore government should plan and launch a policy to foster performance of public agricultural extension system to fulfill the advanced technological needs of farmers to flourish sustainable agriculture and rural development.
基金National Natural Science Foundation of China,Grant/Award Number:61872171The Belt and Road Special Foundation of the State Key Laboratory of Hydrology‐Water Resources and Hydraulic Engineering,Grant/Award Number:2021490811。
文摘Multi‐agent reinforcement learning relies on reward signals to guide the policy networks of individual agents.However,in high‐dimensional continuous spaces,the non‐stationary environment can provide outdated experiences that hinder convergence,resulting in ineffective training performance for multi‐agent systems.To tackle this issue,a novel reinforcement learning scheme,Mutual Information Oriented Deep Skill Chaining(MioDSC),is proposed that generates an optimised cooperative policy by incorporating intrinsic rewards based on mutual information to improve exploration efficiency.These rewards encourage agents to diversify their learning process by engaging in actions that increase the mutual information between their actions and the environment state.In addition,MioDSC can generate cooperative policies using the options framework,allowing agents to learn and reuse complex action sequences and accelerating the convergence speed of multi‐agent learning.MioDSC was evaluated in the multi‐agent particle environment and the StarCraft multi‐agent challenge at varying difficulty levels.The experimental results demonstrate that MioDSC outperforms state‐of‐the‐art methods and is robust across various multi‐agent system tasks with high stability.
基金supported by the Major Subject of the National Social Science Foundation of China(21&ZD093)the Basic Research Funds of Chinese Academy of Agricultural Sciences(16100520240017)+1 种基金the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences(CAASCSAERD-202402,10-IAED-04-2024)the earmarked fund for China Agriculture Research System(CARS-08).
文摘The Regional Comprehensive Economic Partnership(RCEP)has created favorable conditions for building deeply integrated agricultural value chains(AVC)in Asia-Pacific.Based on the RCEP agreement,this study employed the global trade analysis project(GTAP)model to evaluate the impact of RCEP on AVC of member countries in terms of time,tariff reduction,and reduction of non-tariff barriers(NTB).The results indicate that(1)the implementation of RCEP boosts the value-added to agricultural exports for most member countries,particularly in competitive industries;(2)the increase in domestic production and processing capacity,reflected in domestic value-added(DVA),is the primary factor driving the rise in the value-added of agricultural exports across various industries of member countries;(3)RCEP enhances the participation of most regional countries in AVC,with varying impacts on AVC positioning,thereby fostering regional AvC development;and(4)RCEP has a positive effect on AVC indicators both in the short and long term,with the effect becoming more pronounced over time.Additionally,reducing NTB enhances the positive effects of tariff reductions on AVC indicators.Based on the analyses,the following recommendations are proposed:(1)Leverage the development opportunities arising from RCEP implementation to enhance the agricultural DVA;(2)capitalize on cooperative opportunities created by RCEP to build cohesive regional AVC;and(3)prioritize the effective implementation of RCEP'shigh-qualityrules.
基金supported by National Key R&D Program of China(2022YFD2000100)National Natural Science Foundation of China(42401400)Zhejiang Provincial Key Research and Development Program(2023C02018).
文摘Yellow rust(Puccinia striiformis f.sp.Tritici,YR)and fusarium head blight(Fusarium graminearum,FHB)are the two main diseases affecting wheat in the main grain-producing areas of East China,which is common for the two diseases to appear simultaneously in some main production areas.It is necessary to discriminate wheat YR and FHB at the regional scale to accurately locate the disease in space,conduct detailed disease severity monitoring,and scientific control.Four images on different dates were acquired from Sentinel-2,Landsat-8,and Gaofen-1 during the critical period of winter wheat,and 22 remote sensing features that characterize the wheat growth status were then calculated.Meanwhile,6 meteorological parameters that reflect the wheat phenological information were also obtained by combining the site meteorological data and spatial interpolation technology.Then,the principal components(PCs)of comprehensive remote sensing and meteorological features were extracted with principal component analysis(PCA).The PCs-based discrimination models were established to map YR and FHB damage using the random forest(RF)and backpropagation neural network(BPNN).The models’performance was verified based on the disease field truth data(57 plots during the filling period)and 5-fold cross-validation.The results revealed that the PCs obtained after PCA dimensionality reduction outperformed the initial features(IFs)from remote sensing and meteorology in discriminating between the two diseases.Compared to the IFs,the average area under the curve for both micro-average and macro-average ROC curves increased by 0.07 in the PCs-based RF models and increased by 0.16 and 0.13,respectively,in the PCs-based BPNN models.Notably,the PCs-based BPNN discrimination model emerged as the most effective,achieving an overall accuracy of 83.9%.Our proposed discrimination model for wheat YR and FHB,coupled with multi-source remote sensing images and meteorological data,overcomes the limitations of a single-sensor and single-phase remote sensing information in multiple stress discrimination in cloudy and rainy areas.It performs well in revealing the damage spatial distribution of the two diseases at a regional scale,providing a basis for detailed disease severity monitoring,and scientific prevention and control.
基金Supported by the National Natural Science Foundation of China(61971401)。
文摘In this paper,a wideband true time delay line for X-band is designed to overcome the beam dispersion problem in a high-resolution spaceborne synthetic aperture radar phased array antenna system.The delay line loads the electromagnetic bandgap structure on the upper surface of the substrate integrated waveguide.This is equivalent to including an additional inductance-capacitance for energy storage,which realizes the slow-wave effect.A microstrip line-SIW tapered transition structure is introduced to achieve a low loss and a large bandwidth.In the frequency band between 8-12 GHz,the measured results show that the delay multiplier of the delay line reaches 4 times,i.e.,delay line’s delay time is 4 times larger than 50Ωmicrostrip line with same length.Furthermore,the delay fluctuation,i.e.,the difference between the maximum and minimum delay as a percentage of the standard delay is only 2.5%,the insertion loss is less than-2.5 dB,and the return loss is less than-15 dB.Compared with the existing delay lines,the proposed delay line has the advantages of high delay efficiency,low delay error,wide bandwidth and low loss,which has good practical value and application prospects.
基金supported by the National Natural Science Foundation of China(41830103)the Project of Nanjing Center of China Geological Survey(DD20190281).
文摘Dense-array ambient noise tomography is a powerful tool for achieving high-resolution subsurface imag-ing,significantly impacting geohazard prevention and control.Conventional dense-array studies,how-ever,require simultaneous observations of numerous stations for extensive coverage.To conduct a comprehensive karst feature investigation with limited stations,we designed a new synchronous-asyn-chronous observation system that facilitates dense array observations.We conducted two rounds of asynchronous observations,each lasting approximately 24 h,in combination with synchronous backbone stations.We achieved wide-ranging coverage of the study area utilizing 197 nodal receivers,with an average station spacing of 7 m.The beamforming results revealed distinct variations in the noise source distributions between day and night.We estimated the source strength in the stationary phase zone and used a weighting scheme for stacking the cross-correlation functions(C ^(1) functions)to suppress the influ-ence of nonuniform noise source distributions.The weights were derived from the similarity coefficients between multicomponent C^(1)functions related to Rayleigh waves.We employed the cross-correlation of C ^(1) functions(C^(2)methods)to obtain the empirical Green’s functions between asynchronous stations.To eliminate artifacts in C ^(2) functions from higher-mode surface waves in C^(1)functions,we filtered the C^(1)functions on the basis of different particle motions linked to multimode Rayleigh waves.The dispersion measurements of Rayleigh waves obtained from both the C^(1)and C^(2)functions were utilized in surface wave tomography.The inverted three-dimensional(3D)shear-wave(S-wave)velocity model reveals two significant low-velocity zones at depths ranging from 40 to 60 m,which align well with the karst caves found in the drilling data.The method of short-term synchronous-asynchronous ambient noise tomography shows promise as a cost-effective and efficient approach for urban geohazard investigations.
