As China's high-speed railway technology advances,high-speed trains have emerged as a pivotal mode of transportation,instrumental in facilitating passenger and freight mobility while fostering robust regional eco-...As China's high-speed railway technology advances,high-speed trains have emerged as a pivotal mode of transportation,instrumental in facilitating passenger and freight mobility while fostering robust regional eco-nomic and trade interactions.Nonetheless,the safety of train operations remains a paramount concern,prompting extensive research into the dynamic behavior of critical components,which is essential to ensuring seamless and secure transportation services.This article commences by comprehensively reviewing the current landscape and evolutionary trajectory of dynamic model analysis for both traditional bearings and axle box bearings.Emphasis is placed on elucidating the profound influence of diverse bearing fault types on the system's kinematic state,alongside delving into the research methodologies employed in developing multi-physics field coupling models.Subsequently,it expounds on the content of investigations focusing on various wheel and track impairments,grounded in the dynamic modeling of the bearing vehicle coupling system.Concurrently,the intricate interplay between wheel-rail excitation and axle box bearing faults on the system's performance is elucidated.Concludingly,the article underscores the inadequacy of current multi-source fault diagnosis meth-odologies in tackling the intricacies of complex train operating environments,thereby highlighting its sig-nificance as a pressing and vital research agenda for the future.展开更多
Domain adaptation aims to reduce the distribution gap between the training data(source domain)and the target data.This enables effective predictions even for domains not seen during training.However,most conventional ...Domain adaptation aims to reduce the distribution gap between the training data(source domain)and the target data.This enables effective predictions even for domains not seen during training.However,most conventional domain adaptation methods assume a single source domain,making them less suitable for modern deep learning settings that rely on diverse and large-scale datasets.To address this limitation,recent research has focused on Multi-Source Domain Adaptation(MSDA),which aims to learn effectively from multiple source domains.In this paper,we propose Efficient Domain Transition for Multi-source(EDTM),a novel and efficient framework designed to tackle two major challenges in existing MSDA approaches:(1)integrating knowledge across different source domains and(2)aligning label distributions between source and target domains.EDTM leverages an ensemble-based classifier expert mechanism to enhance the contribution of source domains that are more similar to the target domain.To further stabilize the learning process and improve performance,we incorporate imitation learning into the training of the target model.In addition,Maximum Classifier Discrepancy(MCD)is employed to align class-wise label distributions between the source and target domains.Experiments were conducted using Digits-Five,one of the most representative benchmark datasets for MSDA.The results show that EDTM consistently outperforms existing methods in terms of average classification accuracy.Notably,EDTM achieved significantly higher performance on target domains such as Modified National Institute of Standards and Technolog with blended background images(MNIST-M)and Street View House Numbers(SVHN)datasets,demonstrating enhanced generalization compared to baseline approaches.Furthermore,an ablation study analyzing the contribution of each loss component validated the effectiveness of the framework,highlighting the importance of each module in achieving optimal performance.展开更多
The spatial offset of bridge has a significant impact on the safety,comfort,and durability of high-speed railway(HSR)operations,so it is crucial to rapidly and effectively detect the spatial offset of operational HSR ...The spatial offset of bridge has a significant impact on the safety,comfort,and durability of high-speed railway(HSR)operations,so it is crucial to rapidly and effectively detect the spatial offset of operational HSR bridges.Drive-by monitoring of bridge uneven settlement demonstrates significant potential due to its practicality,cost-effectiveness,and efficiency.However,existing drive-by methods for detecting bridge offset have limitations such as reliance on a single data source,low detection accuracy,and the inability to identify lateral deformations of bridges.This paper proposes a novel drive-by inspection method for spatial offset of HSR bridge based on multi-source data fusion of comprehensive inspection train.Firstly,dung beetle optimizer-variational mode decomposition was employed to achieve adaptive decomposition of non-stationary dynamic signals,and explore the hidden temporal relationships in the data.Subsequently,a long short-term memory neural network was developed to achieve feature fusion of multi-source signal and accurate prediction of spatial settlement of HSR bridge.A dataset of track irregularities and CRH380A high-speed train responses was generated using a 3D train-track-bridge interaction model,and the accuracy and effectiveness of the proposed hybrid deep learning model were numerically validated.Finally,the reliability of the proposed drive-by inspection method was further validated by analyzing the actual measurement data obtained from comprehensive inspection train.The research findings indicate that the proposed approach enables rapid and accurate detection of spatial offset in HSR bridge,ensuring the long-term operational safety of HSR bridges.展开更多
Objective:To evaluate the clinical efficacy of blood-letting cupping combined with manual lymphatic drainage in treating breast cancer-related lymphedema(BCRL)and explore its mechanism of action from both traditional ...Objective:To evaluate the clinical efficacy of blood-letting cupping combined with manual lymphatic drainage in treating breast cancer-related lymphedema(BCRL)and explore its mechanism of action from both traditional Chinese medicine and modern medical perspectives,providing a scientific basis and novel therapeutic approaches for clinical management of BCRL.Methods:Patients with BCRL admitted to the outpatient and inpatient departments of Hebei University Affiliated Hospital were enrolled.A prospective randomized controlled trial design was adopted,with eligible patients randomly assigned to a treatment group and a control group.The control group received manual lymphatic drainage alone,while the treatment group received manual lymphtic drainage combined with blood-letting cupping therapy.Posttreatment comparisons evaluated upper limb circumference reduction,edema severity grading,and upper limb functional scores.Vital signs and adverse reactions during treatment were recorded for both groups.Statistical software analyzed the data.Results:The treatment group demonstrated significantly greater reduction in upper limb circumference,improvement in edema severity,and higher upper limb function scores compared to the control group(P<0.05).Vital signs remained stable throughout treatment in both groups.No severe adverse reactions occurred in the treatment group;only isolated cases of mild skin itching were reported,which resolved after symptomatic management.Conclusion:The combination of bloodletting cupping and manual lymphatic drainage demonstrates reliable efficacy in treating BCRL,effectively alleviating edema symptoms and improving upper limb function with high safety.Its mechanism may relate to traditional Chinese medicine principles of“unblocking meridians,promoting blood circulation,and resolving stasis”and modern medical concepts of“enhancing local blood circulation,facilitating lymphatic drainage,and reducing inflammatory responses”.展开更多
Here we report on simultaneous lidar observations of sporadic Ni(Nis)layers and sporadic Na(Nas)layers in the atmosphere over Yanqing,Beijing(40.42°N,116.02°E)from April 2019 to October 2022.During 343 night...Here we report on simultaneous lidar observations of sporadic Ni(Nis)layers and sporadic Na(Nas)layers in the atmosphere over Yanqing,Beijing(40.42°N,116.02°E)from April 2019 to October 2022.During 343 nights of observation,68 Nis and 56 Nas were observed.The seasonal variation of Nis and Nas was also obtained,with the highest occurrence of Nis being in July(43%)and that of Nas being in June(61%).We found that the seasonal variation of Nis is similar to that of Nas and that both occur more frequently in summer than in winter.In addition,we found 23 events in which Nis and Nas occur simultaneously.The average peak altitude of Nas is approximately 1 km higher than that of Nis,and the peak density ratio of Nas to Nis is approximately 5,which is half the density ratio of the two main layers.Additionally,the strength factor for Nas is smaller than that for Nis.Through data analysis of sporadic E layers(Es),we found that Nis and Nas has a significant correlation with Es.The neutralization rates of Ni^(+)/Na^(+)were calculated according to the dissociative recombination reaction of Ni^(+)/Na^(+)and the WACCM-Ni(Whole Atmosphere Community Climate Model of Ni).The production rates of Ni and Na were estimated to be approximately 1:4.4,which is consistent with the density ratio of Nis to Nas.The results showed that the neutralization reaction of Ni+,Na+,and electrons in Es is the main reason for the formation of the Nis layer and the Nas layer.展开更多
Benthic habitat mapping is an emerging discipline in the international marine field in recent years,providing an effective tool for marine spatial planning,marine ecological management,and decision-making applications...Benthic habitat mapping is an emerging discipline in the international marine field in recent years,providing an effective tool for marine spatial planning,marine ecological management,and decision-making applications.Seabed sediment classification is one of the main contents of seabed habitat mapping.In response to the impact of remote sensing imaging quality and the limitations of acoustic measurement range,where a single data source does not fully reflect the substrate type,we proposed a high-precision seabed habitat sediment classification method that integrates data from multiple sources.Based on WorldView-2 multi-spectral remote sensing image data and multibeam bathymetry data,constructed a random forests(RF)classifier with optimal feature selection.A seabed sediment classification experiment integrating optical remote sensing and acoustic remote sensing data was carried out in the shallow water area of Wuzhizhou Island,Hainan,South China.Different seabed sediment types,such as sand,seagrass,and coral reefs were effectively identified,with an overall classification accuracy of 92%.Experimental results show that RF matrix optimized by fusing multi-source remote sensing data for feature selection were better than the classification results of simple combinations of data sources,which improved the accuracy of seabed sediment classification.Therefore,the method proposed in this paper can be effectively applied to high-precision seabed sediment classification and habitat mapping around islands and reefs.展开更多
Lithium metal batteries(LMBs)represent a promising solution for next-generation energy storage due to their high energy density,but the growth of lithium dendrites presents significant challenges to their performance ...Lithium metal batteries(LMBs)represent a promising solution for next-generation energy storage due to their high energy density,but the growth of lithium dendrites presents significant challenges to their performance and safety.This review provides a comprehensive overview of the mechanisms behind lithium dendrite formation and the role of in situ/operando observation and phase field simulation in understanding and mitigating this issue,The key driving factors of dendrite growth,such as lithium-ion flux heterogeneity,surface defects,and localized stress,are explored through advanced experimental techniques,which enable real-time visualization of dendrite nucleation and growth dynamics.Complementarily,phase field simulations provide insights into subsurface and temporal evolution of dendrites by modeling thermodynamic and kinetic processes,while machine learning techniques optimize simulation accuracy through data-driven parameter refinement.The integration of experimental observations with simulation models holds great potential in improving understanding and predictive capabilities.Despite ongoing progress,challenges remain in resolving technical limitations in observation techniques,improving computational efficiency,and fostering interdisciplinary collaboration.This review highlights the synergy between experimental and computational strategies in advancing the development of LMBs and calls for continued research to overcome existing hurdles and unlock the full potential of lithium metal anodes.展开更多
The spatial variability in the atmospheric CO_(2)and CH_(4)concentrations in urban land is affected by the source type,source distribution,and emission intensity in the cityscape.In this study,we analyzed vehicle-moun...The spatial variability in the atmospheric CO_(2)and CH_(4)concentrations in urban land is affected by the source type,source distribution,and emission intensity in the cityscape.In this study,we analyzed vehicle-mounted measurements of street-level CO_(2)and CH_(4)concentrations in Hangzhou—a large metropolitan area in the Yangtze River Delta in eastern China.The results revealed that CO_(2)and CH_(4)emission hotspots did not overlap geographically,with the former occurring as linear features at elevated road intersections and expressways and the latter occurring at waste treatment facilities(sewage treatment plants and landfills).The CH_(4):CO_(2)emission ratios(ppb ppm^(-1))were ranked in increasing order as follows:traffic(1.01±1.82;mean±1 SD);overall(3.46±2.71);sewage treatment(12.76±2.50);and landfill(36.50±10.15).Waste treatment was largely responsible for the increased overall emission ratio,supporting this source category as a major contributor to the CH_(4)budget in this city and suggesting a negligible role of domestic appliances(cookstoves and water heaters).A two-source mixing model calculation indicated that 99.9%of nonelectric vehicles in Hangzhou were gasoline-powered,revealing a recent shift in vehicle fuel composition from gasoline/natural gas to gasoline/electricity.The methodology established in this study is applicable to cities elsewhere.展开更多
Snow depth （SD） is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with ...Snow depth （SD） is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS （AMSR-E） and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System （IMS）. AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as ＂virtual＂ in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model （DEM） but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method.展开更多
On January 7,2025,an Ms6.8 earthquake struck Dingri County,XigazêCity,in the Xizang Autonomous Region.The epicenter,located near the Shenzha-Dingjie fault zone at the boundary between the Qinghai-Xizang Plateau a...On January 7,2025,an Ms6.8 earthquake struck Dingri County,XigazêCity,in the Xizang Autonomous Region.The epicenter,located near the Shenzha-Dingjie fault zone at the boundary between the Qinghai-Xizang Plateau and the Indian Plate,marked the largest earthquake in the region in recent years.The Shenzha-Dingjie fault zone,situated at the boundary between the Qinghai-Xizang Plateau and the Indian Plate,is a key tectonic feature in the India-Eurasia collision process,exhibiting both thrust and strike-slip faulting.This study analyzed the disaster characteristics induced by the earthquake using Differential Synthetic Aperture Radar Interferometry(DIn SAR)to process Sentinel-1 satellite data and derive pre-and post-earthquake surface deformation information.Additionally,high-resolution optical remote sensing data,UAV(unmanned aerial vehicle)imagery,and airborne Li DAR(light detection and ranging)data were employed to analyze the spatial distribution of the surface rupture zone,with field investigations validating the findings.Key results include:(1)Field verification confirmed that potential landslide hazard points identified via optical image interpretation did not exhibit secondary landslide activity;(2)D-In SAR revealed the co-seismic surface deformation pattern,providing detailed deformation information for the Dingri region;(3)Integration of Li DAR and optical imagery further refined and validated surface rupture characteristics identified by optical-In SAR,indicating a predominantly north-south rupture zone.Additionally,surface fracture features extending in a near east-west direction were observed on the southeast side of the epicenter,accompanied by some infrastructure damage;(4)Surface fracture was most severe in high-intensity seismic areas near the epicenter,with the maximum surface displacement approximately 28 km from the epicenter.The earthquake-induced surface deformation zone spanned approximately 6 km by 46 km,with deformation concentrated primarily on the western side of the Dingmucuo Fault,where maximum subsidence of 0.65 m was detected.On the eastern side,uplift was dominant,reaching a maximum of 0.75 m.This earthquake poses significant threats to local communities and infrastructure,underscoring the urgent need for continued monitoring in affected areas.The findings highlight the effectiveness of multi-source data fusion(space-air-ground based observation)in seismic disaster assessment,offering a methodological framework for rapid post-earthquake disaster response.providing a valuable scientific foundation for mitigating secondary disasters in the region.展开更多
The characteristics of nonmetallic inclusions formed during steel production have a significant influence on steel performance.In this paper,studies on inclusions using confocal scanning laser microscopy(CSLM)are revi...The characteristics of nonmetallic inclusions formed during steel production have a significant influence on steel performance.In this paper,studies on inclusions using confocal scanning laser microscopy(CSLM)are reviewed and summarized,particularly the col-lision of various inclusions,dissolution of inclusions in liquid slag,and reactions between inclusions and steel.Solid inclusions exhibited a high collision tendency,whereas pure liquid inclusions exhibited minimal collisions because of the small attraction force induced by their<90°contact angle with molten steel.The collision of complex inclusions in molten steel was not included in the scope of this study and should be evaluated in future studies.Higher CaO/Al_(2)O_(3)and CaO/SiO_(2)ratios in liquid slag promoted the dissolution of Al_(2)O_(3)-based in-clusions.The formation of solid phases in the slag should be prevented to improve dissolution of inclusions.To accurately simulate the dissolution of inclusions in liquid slag,in-situ observation of the dissolution of inclusions at the steel-slag interface is necessary.Using a combination of CSLM and scanning electron microscopy-energy dispersive spectroscopy,the composition and morphological evolution of the inclusions during their modification by the dissolved elements in steel were observed and analyzed.Although the in-situ observa-tion of MnS and TiN precipitations has been widely studied,the in-situ observation of the evolution of oxide inclusions in steel during so-lidification and heating processes has rarely been reported.The effects of temperature,heating and cooling rates,and inclusion character-istics on the formation of acicular ferrites(AFs)have been widely studied.At a cooling rate of 3-5 K/s,the order of AF growth rate in-duced by different inclusions,as reported in literature,is Ti-O<Ti-Ca-Zr-Al-O<Mg-O<Ti-Zr-Al-O<Mn-Ti-Al-O<Ti-Al-O<Zr-Ti-Al-O.Further comprehensive experiments are required to investigate the quantitative relationship between the formation of AFs and inclusions.展开更多
The high-temperature dissolution behavior of primary carbides in samples taken from GCr15 continuous-casting bloom was observed in-situ by confocal laser scanning microscopy.Equations were fitted to the dissolution ki...The high-temperature dissolution behavior of primary carbides in samples taken from GCr15 continuous-casting bloom was observed in-situ by confocal laser scanning microscopy.Equations were fitted to the dissolution kinetics of primary carbides during either heating or soaking.Dissolution of carbides proceeded in three stages(fast→slow→faster)as either temperature or holding time was increased.During the heating process and during the first and third stages of the soaking process,the original size of the carbides determined the steepness of the slope,but during the middle(“slow”)stage of the soaking process,the slope remained zero.The initial size of the carbides varied greatly,but their final dissolution temperature fell within the narrow range of 1210-1235℃,and the holding time remained within 50 min.Fractal analysis was used to study the morphological characteristics of small and medium-sized carbides during the dissolution process.According to changes in the fractal dimension before and after soaking,the carbides tended to evolve towards a more regular morphology.展开更多
The Macao satellites differ from their predecessors in their orbits:MSS-1(Macao Science Satellite-1)is in low inclination and the planned MSS-2 will be in highly elliptical orbits.This paper reviews the fundamental ad...The Macao satellites differ from their predecessors in their orbits:MSS-1(Macao Science Satellite-1)is in low inclination and the planned MSS-2 will be in highly elliptical orbits.This paper reviews the fundamental advantages and disadvantages of the different possible magnetic measurements:the component(declination,intensity,etc.)and location(satellite,ground,etc.).When planning a survey the choice of component is the"What?"question;the choice of location the"Where?"question.Results from potential theory inform the choice of measurement and data analysis.For example,knowing the vertical component of magnetic field provides a solution for the full magnetic field everywhere in the potential region.This is the familiar Neumann problem.In reality this ideal dataset is never available.In the past we were restricted to declination data only,then direction only,then total intensity only.There have also been large swathes of Earth's surface with no measurements at all(MSS-1 is restricted to latitudes below).These incomplete datasets throw up new questions for potential theory,questions that have some intriguing answers.When only declination is known uniqueness is provided by horizontal intensity measurements on a single line joining the dip-poles.When only directions are involved uniqueness is provided by a single intensity measurement,at least in principle.Paleomagnetic intensities can help.When only total intensity is known,as was largely the case in the early satellite era,uniqueness is provided by a precise location of the magnetic equator.Holes in the data distribution is a familiar problem in geophysical studies.All magnetic measurements sample,to a greater or lesser extent,the potential field everywhere.There is a trade-off between measurements close to the source,good for small targets and high resolution,and the broader sample of a distant measurement.The sampling of a measurement is given by the appropriate Green's function of the Laplacian,which determines both the resolution and scope of the measurement.For example,radial and horizontal measurements near the Earth's surface give a weighted average of the radial component over a patch of the core surface beneath the measurement site about in radius.The patch is smaller for shallower surfaces,for example from satellite to ground.Holes in the data distribution do not correspond to similar holes at the source surface;the price paid is in resolution of the source.I argue that,in the past,we have been too reluctant to take advantage of incomplete and apparently hopeless datasets.展开更多
Accurate estimation of understory terrain has significant scientific importance for maintaining ecosystem balance and biodiversity conservation.Addressing the issue of inadequate representation of spatial heterogeneit...Accurate estimation of understory terrain has significant scientific importance for maintaining ecosystem balance and biodiversity conservation.Addressing the issue of inadequate representation of spatial heterogeneity when traditional forest topographic inversion methods consider the entire forest as the inversion unit,this study pro⁃poses a differentiated modeling approach to forest types based on refined land cover classification.Taking Puerto Ri⁃co and Maryland as study areas,a multi-dimensional feature system is constructed by integrating multi-source re⁃mote sensing data:ICESat-2 spaceborne LiDAR is used to obtain benchmark values for understory terrain,topo⁃graphic factors such as slope and aspect are extracted based on SRTM data,and vegetation cover characteristics are analyzed using Landsat-8 multispectral imagery.This study incorporates forest type as a classification modeling con⁃dition and applies the random forest algorithm to build differentiated topographic inversion models.Experimental re⁃sults indicate that,compared to traditional whole-area modeling methods(RMSE=5.06 m),forest type-based classi⁃fication modeling significantly improves the accuracy of understory terrain estimation(RMSE=2.94 m),validating the effectiveness of spatial heterogeneity modeling.Further sensitivity analysis reveals that canopy structure parame⁃ters(with RMSE variation reaching 4.11 m)exert a stronger regulatory effect on estimation accuracy compared to forest cover,providing important theoretical support for optimizing remote sensing models of forest topography.展开更多
Adaptive optics(AO)has significantly advanced high-resolution solar observations by mitigating atmospheric turbulence.However,traditional post-focal AO systems suffer from external configurations that introduce excess...Adaptive optics(AO)has significantly advanced high-resolution solar observations by mitigating atmospheric turbulence.However,traditional post-focal AO systems suffer from external configurations that introduce excessive optical surfaces,reduced light throughput,and instrumental polarization.To address these limitations,we propose an embedded solar adaptive optics telescope(ESAOT)that intrinsically incorporates the solar AO(SAO)subsystem within the telescope's optical train,featuring a co-designed correction chain with a single Hartmann-Shack full-wavefront sensor(HS f-WFS)and a deformable secondary mirror(DSM).The HS f-WFS uses temporal-spatial hybrid sampling technique to simultane-ously resolve tip-tilt and high-order aberrations,while the DSM performs real-time compensation through adaptive modal optimization.This unified architecture achieves symmetrical polarization suppression and high system throughput by min-imizing optical surfaces.A 600 mm ESAOT prototype incorporating a 12×12 micro-lens array HS f-WFS and 61-actuator piezoelectric DSM has been developed and successfully conducted on-sky photospheric observations.Validations in-cluding turbulence simulations,optical bench testing,and practical observations at the Lijiang observatory collectively confirm the system's capability to maintain aboutλ/10 wavefront error during active region tracking.This architectural breakthrough of the ESAOT addresses long-standing SAO integration challenges in solar astronomy and provides scala-bility analyses confirming direct applicability to the existing and future large solar observation facilities.展开更多
To elucidate the fracturing mechanism of deep hard rock under complex disturbance environments,this study investigates the dynamic failure behavior of pre-damaged granite subjected to multi-source dynamic disturbances...To elucidate the fracturing mechanism of deep hard rock under complex disturbance environments,this study investigates the dynamic failure behavior of pre-damaged granite subjected to multi-source dynamic disturbances.Blasting vibration monitoring was conducted in a deep-buried drill-and-blast tunnel to characterize in-situ dynamic loading conditions.Subsequently,true triaxial compression tests incorporating multi-source disturbances were performed using a self-developed wide-low-frequency true triaxial system to simulate disturbance accumulation and damage evolution in granite.The results demonstrate that combined dynamic disturbances and unloading damage significantly accelerate strength degradation and trigger shear-slip failure along preferentially oriented blast-induced fractures,with strength reductions up to 16.7%.Layered failure was observed on the free surface of pre-damaged granite under biaxial loading,indicating a disturbance-induced fracture localization mechanism.Time-stress-fracture-energy coupling fields were constructed to reveal the spatiotemporal characteristics of fracture evolution.Critical precursor frequency bands(105-150,185-225,and 300-325 kHz)were identified,which serve as diagnostic signatures of impending failure.A dynamic instability mechanism driven by multi-source disturbance superposition and pre-damage evolution was established.Furthermore,a grouting-based wave-absorption control strategy was proposed to mitigate deep dynamic disasters by attenuating disturbance amplitude and reducing excitation frequency.展开更多
Micro-nano Earth Observation Satellite(MEOS)constellation has the advantages of low construction cost,short revisit cycle,and high functional density,which is considered a promising solution for serving rapidly growin...Micro-nano Earth Observation Satellite(MEOS)constellation has the advantages of low construction cost,short revisit cycle,and high functional density,which is considered a promising solution for serving rapidly growing observation demands.The observation Scheduling Problem in the MEOS constellation(MEOSSP)is a challenging issue due to the large number of satellites and tasks,as well as complex observation constraints.To address the large-scale and complicated MEOSSP,we develop a Two-Stage Scheduling Algorithm based on the Pointer Network with Attention mechanism(TSSA-PNA).In TSSA-PNA,the MEOS observation scheduling is decomposed into a task allocation stage and a single-MEOS scheduling stage.In the task allocation stage,an adaptive task allocation algorithm with four problem-specific allocation operators is proposed to reallocate the unscheduled tasks to new MEOSs.Regarding the single-MEOS scheduling stage,we design a pointer network based on the encoder-decoder architecture to learn the optimal singleMEOS scheduling solution and introduce the attention mechanism into the encoder to improve the learning efficiency.The Pointer Network with Attention mechanism(PNA)can generate the single-MEOS scheduling solution quickly in an end-to-end manner.These two decomposed stages are performed iteratively to search for the solution with high profit.A greedy local search algorithm is developed to improve the profits further.The performance of the PNA and TSSA-PNA on singleMEOS and multi-MEOS scheduling problems are evaluated in the experiments.The experimental results demonstrate that PNA can obtain the approximate solution for the single-MEOS scheduling problem in a short time.Besides,the TSSA-PNA can achieve higher observation profits than the existing scheduling algorithms within the acceptable computational time for the large-scale MEOS scheduling problem.展开更多
Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.P...Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.展开更多
The SiO_(2) inverse opal photonic crystals(PC)with a three-dimensional macroporous structure were fabricated by the sacrificial template method,followed by infiltration of a pyrene derivative,1-(pyren-8-yl)but-3-en-1-...The SiO_(2) inverse opal photonic crystals(PC)with a three-dimensional macroporous structure were fabricated by the sacrificial template method,followed by infiltration of a pyrene derivative,1-(pyren-8-yl)but-3-en-1-amine(PEA),to achieve a formaldehyde(FA)-sensitive and fluorescence-enhanced sensing film.Utilizing the specific Aza-Cope rearrangement reaction of allylamine of PEA and FA to generate a strong fluorescent product emitted at approximately 480 nm,we chose a PC whose blue band edge of stopband overlapped with the fluorescence emission wavelength.In virtue of the fluorescence enhancement property derived from slow photon effect of PC,FA was detected highly selectively and sensitively.The limit of detection(LoD)was calculated to be 1.38 nmol/L.Furthermore,the fast detection of FA(within 1 min)is realized due to the interconnected three-dimensional macroporous structure of the inverse opal PC and its high specific surface area.The prepared sensing film can be used for the detection of FA in air,aquatic products and living cells.The very close FA content in indoor air to the result from FA detector,the recovery rate of 101.5%for detecting FA in aquatic products and fast fluorescence imaging in 2 min for living cells demonstrate the reliability and accuracy of our method in practical applications.展开更多
Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on co...Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.展开更多
基金Supported by the National Natural Science Foundation of China(Grant Nos.12393783,12302067,12172235,52072249)Joint Funds of the National Natural Science Foundation of China(Grant No.U24A2003)+3 种基金College Education Scientific Research Project of Hebei Province(Grant No.JZX2024006)Central Guiding Local Scientific and Technological Development Funding Project(Grant No.246Z2206G)the Key Research Project of China State Railway Group Co.,Ltd.(Grant No.N2024T009)S&T Program of Hebei(Grant No.21567622H).
文摘As China's high-speed railway technology advances,high-speed trains have emerged as a pivotal mode of transportation,instrumental in facilitating passenger and freight mobility while fostering robust regional eco-nomic and trade interactions.Nonetheless,the safety of train operations remains a paramount concern,prompting extensive research into the dynamic behavior of critical components,which is essential to ensuring seamless and secure transportation services.This article commences by comprehensively reviewing the current landscape and evolutionary trajectory of dynamic model analysis for both traditional bearings and axle box bearings.Emphasis is placed on elucidating the profound influence of diverse bearing fault types on the system's kinematic state,alongside delving into the research methodologies employed in developing multi-physics field coupling models.Subsequently,it expounds on the content of investigations focusing on various wheel and track impairments,grounded in the dynamic modeling of the bearing vehicle coupling system.Concurrently,the intricate interplay between wheel-rail excitation and axle box bearing faults on the system's performance is elucidated.Concludingly,the article underscores the inadequacy of current multi-source fault diagnosis meth-odologies in tackling the intricacies of complex train operating environments,thereby highlighting its sig-nificance as a pressing and vital research agenda for the future.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.RS-2024-00406320)the Institute of Information&Communica-tions Technology Planning&Evaluation(IITP)-Innovative Human Resource Development for Local Intellectualization Program Grant funded by the Korea government(MSIT)(IITP-2026-RS-2023-00259678).
文摘Domain adaptation aims to reduce the distribution gap between the training data(source domain)and the target data.This enables effective predictions even for domains not seen during training.However,most conventional domain adaptation methods assume a single source domain,making them less suitable for modern deep learning settings that rely on diverse and large-scale datasets.To address this limitation,recent research has focused on Multi-Source Domain Adaptation(MSDA),which aims to learn effectively from multiple source domains.In this paper,we propose Efficient Domain Transition for Multi-source(EDTM),a novel and efficient framework designed to tackle two major challenges in existing MSDA approaches:(1)integrating knowledge across different source domains and(2)aligning label distributions between source and target domains.EDTM leverages an ensemble-based classifier expert mechanism to enhance the contribution of source domains that are more similar to the target domain.To further stabilize the learning process and improve performance,we incorporate imitation learning into the training of the target model.In addition,Maximum Classifier Discrepancy(MCD)is employed to align class-wise label distributions between the source and target domains.Experiments were conducted using Digits-Five,one of the most representative benchmark datasets for MSDA.The results show that EDTM consistently outperforms existing methods in terms of average classification accuracy.Notably,EDTM achieved significantly higher performance on target domains such as Modified National Institute of Standards and Technolog with blended background images(MNIST-M)and Street View House Numbers(SVHN)datasets,demonstrating enhanced generalization compared to baseline approaches.Furthermore,an ablation study analyzing the contribution of each loss component validated the effectiveness of the framework,highlighting the importance of each module in achieving optimal performance.
基金sponsored by the National Natural Science Foundation of China(Grant No.52178100).
文摘The spatial offset of bridge has a significant impact on the safety,comfort,and durability of high-speed railway(HSR)operations,so it is crucial to rapidly and effectively detect the spatial offset of operational HSR bridges.Drive-by monitoring of bridge uneven settlement demonstrates significant potential due to its practicality,cost-effectiveness,and efficiency.However,existing drive-by methods for detecting bridge offset have limitations such as reliance on a single data source,low detection accuracy,and the inability to identify lateral deformations of bridges.This paper proposes a novel drive-by inspection method for spatial offset of HSR bridge based on multi-source data fusion of comprehensive inspection train.Firstly,dung beetle optimizer-variational mode decomposition was employed to achieve adaptive decomposition of non-stationary dynamic signals,and explore the hidden temporal relationships in the data.Subsequently,a long short-term memory neural network was developed to achieve feature fusion of multi-source signal and accurate prediction of spatial settlement of HSR bridge.A dataset of track irregularities and CRH380A high-speed train responses was generated using a 3D train-track-bridge interaction model,and the accuracy and effectiveness of the proposed hybrid deep learning model were numerically validated.Finally,the reliability of the proposed drive-by inspection method was further validated by analyzing the actual measurement data obtained from comprehensive inspection train.The research findings indicate that the proposed approach enables rapid and accurate detection of spatial offset in HSR bridge,ensuring the long-term operational safety of HSR bridges.
文摘Objective:To evaluate the clinical efficacy of blood-letting cupping combined with manual lymphatic drainage in treating breast cancer-related lymphedema(BCRL)and explore its mechanism of action from both traditional Chinese medicine and modern medical perspectives,providing a scientific basis and novel therapeutic approaches for clinical management of BCRL.Methods:Patients with BCRL admitted to the outpatient and inpatient departments of Hebei University Affiliated Hospital were enrolled.A prospective randomized controlled trial design was adopted,with eligible patients randomly assigned to a treatment group and a control group.The control group received manual lymphatic drainage alone,while the treatment group received manual lymphtic drainage combined with blood-letting cupping therapy.Posttreatment comparisons evaluated upper limb circumference reduction,edema severity grading,and upper limb functional scores.Vital signs and adverse reactions during treatment were recorded for both groups.Statistical software analyzed the data.Results:The treatment group demonstrated significantly greater reduction in upper limb circumference,improvement in edema severity,and higher upper limb function scores compared to the control group(P<0.05).Vital signs remained stable throughout treatment in both groups.No severe adverse reactions occurred in the treatment group;only isolated cases of mild skin itching were reported,which resolved after symptomatic management.Conclusion:The combination of bloodletting cupping and manual lymphatic drainage demonstrates reliable efficacy in treating BCRL,effectively alleviating edema symptoms and improving upper limb function with high safety.Its mechanism may relate to traditional Chinese medicine principles of“unblocking meridians,promoting blood circulation,and resolving stasis”and modern medical concepts of“enhancing local blood circulation,facilitating lymphatic drainage,and reducing inflammatory responses”.
基金supported by the Specialized Research Fund for State Key Laboratories,Chinese Meridian Project,the Specialized Research Fund for the State Key Laboratory of Solar Activity and Space Weather,postgraduate Education Reform and Quality Improvement Project of Henan Province(Grant No.YJS2024JD32)Natural Science Foundation Project of Henan Province(Grant No.242300420253)National Natural Science Foundation of China for Young Scientists(Grant No.42504156)funding.
文摘Here we report on simultaneous lidar observations of sporadic Ni(Nis)layers and sporadic Na(Nas)layers in the atmosphere over Yanqing,Beijing(40.42°N,116.02°E)from April 2019 to October 2022.During 343 nights of observation,68 Nis and 56 Nas were observed.The seasonal variation of Nis and Nas was also obtained,with the highest occurrence of Nis being in July(43%)and that of Nas being in June(61%).We found that the seasonal variation of Nis is similar to that of Nas and that both occur more frequently in summer than in winter.In addition,we found 23 events in which Nis and Nas occur simultaneously.The average peak altitude of Nas is approximately 1 km higher than that of Nis,and the peak density ratio of Nas to Nis is approximately 5,which is half the density ratio of the two main layers.Additionally,the strength factor for Nas is smaller than that for Nis.Through data analysis of sporadic E layers(Es),we found that Nis and Nas has a significant correlation with Es.The neutralization rates of Ni^(+)/Na^(+)were calculated according to the dissociative recombination reaction of Ni^(+)/Na^(+)and the WACCM-Ni(Whole Atmosphere Community Climate Model of Ni).The production rates of Ni and Na were estimated to be approximately 1:4.4,which is consistent with the density ratio of Nis to Nas.The results showed that the neutralization reaction of Ni+,Na+,and electrons in Es is the main reason for the formation of the Nis layer and the Nas layer.
基金Supported by the National Natural Science Foundation of China(Nos.42376185,41876111)the Shandong Provincial Natural Science Foundation(No.ZR2023MD073)。
文摘Benthic habitat mapping is an emerging discipline in the international marine field in recent years,providing an effective tool for marine spatial planning,marine ecological management,and decision-making applications.Seabed sediment classification is one of the main contents of seabed habitat mapping.In response to the impact of remote sensing imaging quality and the limitations of acoustic measurement range,where a single data source does not fully reflect the substrate type,we proposed a high-precision seabed habitat sediment classification method that integrates data from multiple sources.Based on WorldView-2 multi-spectral remote sensing image data and multibeam bathymetry data,constructed a random forests(RF)classifier with optimal feature selection.A seabed sediment classification experiment integrating optical remote sensing and acoustic remote sensing data was carried out in the shallow water area of Wuzhizhou Island,Hainan,South China.Different seabed sediment types,such as sand,seagrass,and coral reefs were effectively identified,with an overall classification accuracy of 92%.Experimental results show that RF matrix optimized by fusing multi-source remote sensing data for feature selection were better than the classification results of simple combinations of data sources,which improved the accuracy of seabed sediment classification.Therefore,the method proposed in this paper can be effectively applied to high-precision seabed sediment classification and habitat mapping around islands and reefs.
基金the financial support of the National Natural Science Foundation of China(Nos.12172206 and 11972218)。
文摘Lithium metal batteries(LMBs)represent a promising solution for next-generation energy storage due to their high energy density,but the growth of lithium dendrites presents significant challenges to their performance and safety.This review provides a comprehensive overview of the mechanisms behind lithium dendrite formation and the role of in situ/operando observation and phase field simulation in understanding and mitigating this issue,The key driving factors of dendrite growth,such as lithium-ion flux heterogeneity,surface defects,and localized stress,are explored through advanced experimental techniques,which enable real-time visualization of dendrite nucleation and growth dynamics.Complementarily,phase field simulations provide insights into subsurface and temporal evolution of dendrites by modeling thermodynamic and kinetic processes,while machine learning techniques optimize simulation accuracy through data-driven parameter refinement.The integration of experimental observations with simulation models holds great potential in improving understanding and predictive capabilities.Despite ongoing progress,challenges remain in resolving technical limitations in observation techniques,improving computational efficiency,and fostering interdisciplinary collaboration.This review highlights the synergy between experimental and computational strategies in advancing the development of LMBs and calls for continued research to overcome existing hurdles and unlock the full potential of lithium metal anodes.
基金supported by the National Natural Science Foundation of China(Grant Nos.U24A20590,42021004)the Joint funds of the Zhejiang Provincial NaturalScienceFoundationofChina(GrantNo.LZJMZ23D050002)+2 种基金the 333 Project of Jiangsu Province(Grant No.BRA2022023)the Natural Science Foundation of Jiangsu Province for Distinguished Young Scholars(Grant No.BK20220055)the Key Laboratory of Ecosystem Carbon Source and Sink,China Meteorological Administration(Grant No.ECSS-CMA202302)。
文摘The spatial variability in the atmospheric CO_(2)and CH_(4)concentrations in urban land is affected by the source type,source distribution,and emission intensity in the cityscape.In this study,we analyzed vehicle-mounted measurements of street-level CO_(2)and CH_(4)concentrations in Hangzhou—a large metropolitan area in the Yangtze River Delta in eastern China.The results revealed that CO_(2)and CH_(4)emission hotspots did not overlap geographically,with the former occurring as linear features at elevated road intersections and expressways and the latter occurring at waste treatment facilities(sewage treatment plants and landfills).The CH_(4):CO_(2)emission ratios(ppb ppm^(-1))were ranked in increasing order as follows:traffic(1.01±1.82;mean±1 SD);overall(3.46±2.71);sewage treatment(12.76±2.50);and landfill(36.50±10.15).Waste treatment was largely responsible for the increased overall emission ratio,supporting this source category as a major contributor to the CH_(4)budget in this city and suggesting a negligible role of domestic appliances(cookstoves and water heaters).A two-source mixing model calculation indicated that 99.9%of nonelectric vehicles in Hangzhou were gasoline-powered,revealing a recent shift in vehicle fuel composition from gasoline/natural gas to gasoline/electricity.The methodology established in this study is applicable to cities elsewhere.
基金Meteorological Research in the Public Interest,No.GYHY201106014Beijing Nova Program,No.2010B037China Special Fund for the National High Technology Research and Development Program of China(863 Program),No.412230
文摘Snow depth （SD） is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS （AMSR-E） and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System （IMS）. AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as ＂virtual＂ in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model （DEM） but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method.
基金supported by the National Natural Science Foundation of China(No.42477170)the Major Project of the National Natural Science Foundation of China(No.42090054)+1 种基金the Research Fund Program of Hubei Key Laboratory of Resources and Eco-Environment Geology(No.HBREGKFJJ-202411)Innovative Group Project of Natural Science Foundation of Hubei Province(No.2024AFA015)。
文摘On January 7,2025,an Ms6.8 earthquake struck Dingri County,XigazêCity,in the Xizang Autonomous Region.The epicenter,located near the Shenzha-Dingjie fault zone at the boundary between the Qinghai-Xizang Plateau and the Indian Plate,marked the largest earthquake in the region in recent years.The Shenzha-Dingjie fault zone,situated at the boundary between the Qinghai-Xizang Plateau and the Indian Plate,is a key tectonic feature in the India-Eurasia collision process,exhibiting both thrust and strike-slip faulting.This study analyzed the disaster characteristics induced by the earthquake using Differential Synthetic Aperture Radar Interferometry(DIn SAR)to process Sentinel-1 satellite data and derive pre-and post-earthquake surface deformation information.Additionally,high-resolution optical remote sensing data,UAV(unmanned aerial vehicle)imagery,and airborne Li DAR(light detection and ranging)data were employed to analyze the spatial distribution of the surface rupture zone,with field investigations validating the findings.Key results include:(1)Field verification confirmed that potential landslide hazard points identified via optical image interpretation did not exhibit secondary landslide activity;(2)D-In SAR revealed the co-seismic surface deformation pattern,providing detailed deformation information for the Dingri region;(3)Integration of Li DAR and optical imagery further refined and validated surface rupture characteristics identified by optical-In SAR,indicating a predominantly north-south rupture zone.Additionally,surface fracture features extending in a near east-west direction were observed on the southeast side of the epicenter,accompanied by some infrastructure damage;(4)Surface fracture was most severe in high-intensity seismic areas near the epicenter,with the maximum surface displacement approximately 28 km from the epicenter.The earthquake-induced surface deformation zone spanned approximately 6 km by 46 km,with deformation concentrated primarily on the western side of the Dingmucuo Fault,where maximum subsidence of 0.65 m was detected.On the eastern side,uplift was dominant,reaching a maximum of 0.75 m.This earthquake poses significant threats to local communities and infrastructure,underscoring the urgent need for continued monitoring in affected areas.The findings highlight the effectiveness of multi-source data fusion(space-air-ground based observation)in seismic disaster assessment,offering a methodological framework for rapid post-earthquake disaster response.providing a valuable scientific foundation for mitigating secondary disasters in the region.
基金supported by the National Key R&D Program(No.2023YFB3709900)the National Nature Science Foundation of China(No.U22A20171)+2 种基金China Baowu Low Carbon Metallurgy Innovation Foundation(No.BWLCF202315)the High Steel Center(HSC)at North China University of TechnologyUniversity of Science and Technology Beijing,China.
文摘The characteristics of nonmetallic inclusions formed during steel production have a significant influence on steel performance.In this paper,studies on inclusions using confocal scanning laser microscopy(CSLM)are reviewed and summarized,particularly the col-lision of various inclusions,dissolution of inclusions in liquid slag,and reactions between inclusions and steel.Solid inclusions exhibited a high collision tendency,whereas pure liquid inclusions exhibited minimal collisions because of the small attraction force induced by their<90°contact angle with molten steel.The collision of complex inclusions in molten steel was not included in the scope of this study and should be evaluated in future studies.Higher CaO/Al_(2)O_(3)and CaO/SiO_(2)ratios in liquid slag promoted the dissolution of Al_(2)O_(3)-based in-clusions.The formation of solid phases in the slag should be prevented to improve dissolution of inclusions.To accurately simulate the dissolution of inclusions in liquid slag,in-situ observation of the dissolution of inclusions at the steel-slag interface is necessary.Using a combination of CSLM and scanning electron microscopy-energy dispersive spectroscopy,the composition and morphological evolution of the inclusions during their modification by the dissolved elements in steel were observed and analyzed.Although the in-situ observa-tion of MnS and TiN precipitations has been widely studied,the in-situ observation of the evolution of oxide inclusions in steel during so-lidification and heating processes has rarely been reported.The effects of temperature,heating and cooling rates,and inclusion character-istics on the formation of acicular ferrites(AFs)have been widely studied.At a cooling rate of 3-5 K/s,the order of AF growth rate in-duced by different inclusions,as reported in literature,is Ti-O<Ti-Ca-Zr-Al-O<Mg-O<Ti-Zr-Al-O<Mn-Ti-Al-O<Ti-Al-O<Zr-Ti-Al-O.Further comprehensive experiments are required to investigate the quantitative relationship between the formation of AFs and inclusions.
基金supported by Independent Research Project of State Key Laboratory of Advanced Special Steel,Shanghai Key Laboratory of Advanced Ferrometallurgy,Shanghai University(SKLASS-2023-Z13)the Science and Technology Commission of Shanghai Municipality(No.19DZ2270200)+1 种基金A portion of the work was performed at US National High Magnetic Field Laboratory,which is supported by the National Science Foundation(Cooperative Agreement No.DMR-1157490 and DMR-1644779)the State of Florida.Thanks also to Mary Tyler for editing.
文摘The high-temperature dissolution behavior of primary carbides in samples taken from GCr15 continuous-casting bloom was observed in-situ by confocal laser scanning microscopy.Equations were fitted to the dissolution kinetics of primary carbides during either heating or soaking.Dissolution of carbides proceeded in three stages(fast→slow→faster)as either temperature or holding time was increased.During the heating process and during the first and third stages of the soaking process,the original size of the carbides determined the steepness of the slope,but during the middle(“slow”)stage of the soaking process,the slope remained zero.The initial size of the carbides varied greatly,but their final dissolution temperature fell within the narrow range of 1210-1235℃,and the holding time remained within 50 min.Fractal analysis was used to study the morphological characteristics of small and medium-sized carbides during the dissolution process.According to changes in the fractal dimension before and after soaking,the carbides tended to evolve towards a more regular morphology.
文摘The Macao satellites differ from their predecessors in their orbits:MSS-1(Macao Science Satellite-1)is in low inclination and the planned MSS-2 will be in highly elliptical orbits.This paper reviews the fundamental advantages and disadvantages of the different possible magnetic measurements:the component(declination,intensity,etc.)and location(satellite,ground,etc.).When planning a survey the choice of component is the"What?"question;the choice of location the"Where?"question.Results from potential theory inform the choice of measurement and data analysis.For example,knowing the vertical component of magnetic field provides a solution for the full magnetic field everywhere in the potential region.This is the familiar Neumann problem.In reality this ideal dataset is never available.In the past we were restricted to declination data only,then direction only,then total intensity only.There have also been large swathes of Earth's surface with no measurements at all(MSS-1 is restricted to latitudes below).These incomplete datasets throw up new questions for potential theory,questions that have some intriguing answers.When only declination is known uniqueness is provided by horizontal intensity measurements on a single line joining the dip-poles.When only directions are involved uniqueness is provided by a single intensity measurement,at least in principle.Paleomagnetic intensities can help.When only total intensity is known,as was largely the case in the early satellite era,uniqueness is provided by a precise location of the magnetic equator.Holes in the data distribution is a familiar problem in geophysical studies.All magnetic measurements sample,to a greater or lesser extent,the potential field everywhere.There is a trade-off between measurements close to the source,good for small targets and high resolution,and the broader sample of a distant measurement.The sampling of a measurement is given by the appropriate Green's function of the Laplacian,which determines both the resolution and scope of the measurement.For example,radial and horizontal measurements near the Earth's surface give a weighted average of the radial component over a patch of the core surface beneath the measurement site about in radius.The patch is smaller for shallower surfaces,for example from satellite to ground.Holes in the data distribution do not correspond to similar holes at the source surface;the price paid is in resolution of the source.I argue that,in the past,we have been too reluctant to take advantage of incomplete and apparently hopeless datasets.
基金Supported by the National Natural Science Foundation of China(42401488,42071351)the National Key Research and Development Program of China(2020YFA0608501,2017YFB0504204)+4 种基金the Liaoning Revitalization Talents Program(XLYC1802027)the Talent Recruited Program of the Chinese Academy of Science(Y938091)the Project Supported Discipline Innovation Team of the Liaoning Technical University(LNTU20TD-23)the Liaoning Province Doctoral Research Initiation Fund Program(2023-BS-202)the Basic Research Projects of Liaoning Department of Education(JYTQN2023202)。
文摘Accurate estimation of understory terrain has significant scientific importance for maintaining ecosystem balance and biodiversity conservation.Addressing the issue of inadequate representation of spatial heterogeneity when traditional forest topographic inversion methods consider the entire forest as the inversion unit,this study pro⁃poses a differentiated modeling approach to forest types based on refined land cover classification.Taking Puerto Ri⁃co and Maryland as study areas,a multi-dimensional feature system is constructed by integrating multi-source re⁃mote sensing data:ICESat-2 spaceborne LiDAR is used to obtain benchmark values for understory terrain,topo⁃graphic factors such as slope and aspect are extracted based on SRTM data,and vegetation cover characteristics are analyzed using Landsat-8 multispectral imagery.This study incorporates forest type as a classification modeling con⁃dition and applies the random forest algorithm to build differentiated topographic inversion models.Experimental re⁃sults indicate that,compared to traditional whole-area modeling methods(RMSE=5.06 m),forest type-based classi⁃fication modeling significantly improves the accuracy of understory terrain estimation(RMSE=2.94 m),validating the effectiveness of spatial heterogeneity modeling.Further sensitivity analysis reveals that canopy structure parame⁃ters(with RMSE variation reaching 4.11 m)exert a stronger regulatory effect on estimation accuracy compared to forest cover,providing important theoretical support for optimizing remote sensing models of forest topography.
基金support from the National Science Foundation of China(NSFC)(Grants No.12293031 and No.61905252)the National Science Foundation for Distinguished Young Scholars(Grant No.12022308)the National Key R&D Program of China(Grants No.2021YFC2202200 and No.2021YFC2202204).
文摘Adaptive optics(AO)has significantly advanced high-resolution solar observations by mitigating atmospheric turbulence.However,traditional post-focal AO systems suffer from external configurations that introduce excessive optical surfaces,reduced light throughput,and instrumental polarization.To address these limitations,we propose an embedded solar adaptive optics telescope(ESAOT)that intrinsically incorporates the solar AO(SAO)subsystem within the telescope's optical train,featuring a co-designed correction chain with a single Hartmann-Shack full-wavefront sensor(HS f-WFS)and a deformable secondary mirror(DSM).The HS f-WFS uses temporal-spatial hybrid sampling technique to simultane-ously resolve tip-tilt and high-order aberrations,while the DSM performs real-time compensation through adaptive modal optimization.This unified architecture achieves symmetrical polarization suppression and high system throughput by min-imizing optical surfaces.A 600 mm ESAOT prototype incorporating a 12×12 micro-lens array HS f-WFS and 61-actuator piezoelectric DSM has been developed and successfully conducted on-sky photospheric observations.Validations in-cluding turbulence simulations,optical bench testing,and practical observations at the Lijiang observatory collectively confirm the system's capability to maintain aboutλ/10 wavefront error during active region tracking.This architectural breakthrough of the ESAOT addresses long-standing SAO integration challenges in solar astronomy and provides scala-bility analyses confirming direct applicability to the existing and future large solar observation facilities.
基金supported by the National Key R&D Program of China(No.2023YFB2603602)the National Natural Science Foundation of China(Nos.52222810 and 52178383).
文摘To elucidate the fracturing mechanism of deep hard rock under complex disturbance environments,this study investigates the dynamic failure behavior of pre-damaged granite subjected to multi-source dynamic disturbances.Blasting vibration monitoring was conducted in a deep-buried drill-and-blast tunnel to characterize in-situ dynamic loading conditions.Subsequently,true triaxial compression tests incorporating multi-source disturbances were performed using a self-developed wide-low-frequency true triaxial system to simulate disturbance accumulation and damage evolution in granite.The results demonstrate that combined dynamic disturbances and unloading damage significantly accelerate strength degradation and trigger shear-slip failure along preferentially oriented blast-induced fractures,with strength reductions up to 16.7%.Layered failure was observed on the free surface of pre-damaged granite under biaxial loading,indicating a disturbance-induced fracture localization mechanism.Time-stress-fracture-energy coupling fields were constructed to reveal the spatiotemporal characteristics of fracture evolution.Critical precursor frequency bands(105-150,185-225,and 300-325 kHz)were identified,which serve as diagnostic signatures of impending failure.A dynamic instability mechanism driven by multi-source disturbance superposition and pre-damage evolution was established.Furthermore,a grouting-based wave-absorption control strategy was proposed to mitigate deep dynamic disasters by attenuating disturbance amplitude and reducing excitation frequency.
基金supported by the National Natural Science Foundation of China(No.62101587)the National Funded Postdoctoral Researcher Program of China(No.GZC20233578)。
文摘Micro-nano Earth Observation Satellite(MEOS)constellation has the advantages of low construction cost,short revisit cycle,and high functional density,which is considered a promising solution for serving rapidly growing observation demands.The observation Scheduling Problem in the MEOS constellation(MEOSSP)is a challenging issue due to the large number of satellites and tasks,as well as complex observation constraints.To address the large-scale and complicated MEOSSP,we develop a Two-Stage Scheduling Algorithm based on the Pointer Network with Attention mechanism(TSSA-PNA).In TSSA-PNA,the MEOS observation scheduling is decomposed into a task allocation stage and a single-MEOS scheduling stage.In the task allocation stage,an adaptive task allocation algorithm with four problem-specific allocation operators is proposed to reallocate the unscheduled tasks to new MEOSs.Regarding the single-MEOS scheduling stage,we design a pointer network based on the encoder-decoder architecture to learn the optimal singleMEOS scheduling solution and introduce the attention mechanism into the encoder to improve the learning efficiency.The Pointer Network with Attention mechanism(PNA)can generate the single-MEOS scheduling solution quickly in an end-to-end manner.These two decomposed stages are performed iteratively to search for the solution with high profit.A greedy local search algorithm is developed to improve the profits further.The performance of the PNA and TSSA-PNA on singleMEOS and multi-MEOS scheduling problems are evaluated in the experiments.The experimental results demonstrate that PNA can obtain the approximate solution for the single-MEOS scheduling problem in a short time.Besides,the TSSA-PNA can achieve higher observation profits than the existing scheduling algorithms within the acceptable computational time for the large-scale MEOS scheduling problem.
基金supported by Natural Science Foundation of China(Nos.62303126,62362008,author Z.Z,https://www.nsfc.gov.cn/,accessed on 20 December 2024)Major Scientific and Technological Special Project of Guizhou Province([2024]014)+2 种基金Guizhou Provincial Science and Technology Projects(No.ZK[2022]General149) ,author Z.Z,https://kjt.guizhou.gov.cn/,accessed on 20 December 2024)The Open Project of the Key Laboratory of Computing Power Network and Information Security,Ministry of Education under Grant 2023ZD037,author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024)Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(No.ICT2024B25),author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024).
文摘Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.
基金supported by the National Natural Science Foundation of China(21663032 and 22061041)the Open Sharing Platform for Scientific and Technological Resources of Shaanxi Province(2021PT-004)the National Innovation and Entrepreneurship Training Program for College Students of China(S202110719044)。
文摘The SiO_(2) inverse opal photonic crystals(PC)with a three-dimensional macroporous structure were fabricated by the sacrificial template method,followed by infiltration of a pyrene derivative,1-(pyren-8-yl)but-3-en-1-amine(PEA),to achieve a formaldehyde(FA)-sensitive and fluorescence-enhanced sensing film.Utilizing the specific Aza-Cope rearrangement reaction of allylamine of PEA and FA to generate a strong fluorescent product emitted at approximately 480 nm,we chose a PC whose blue band edge of stopband overlapped with the fluorescence emission wavelength.In virtue of the fluorescence enhancement property derived from slow photon effect of PC,FA was detected highly selectively and sensitively.The limit of detection(LoD)was calculated to be 1.38 nmol/L.Furthermore,the fast detection of FA(within 1 min)is realized due to the interconnected three-dimensional macroporous structure of the inverse opal PC and its high specific surface area.The prepared sensing film can be used for the detection of FA in air,aquatic products and living cells.The very close FA content in indoor air to the result from FA detector,the recovery rate of 101.5%for detecting FA in aquatic products and fast fluorescence imaging in 2 min for living cells demonstrate the reliability and accuracy of our method in practical applications.
基金supported by the Sichuan Science and Technology Program(Nos.2024JDRC0100 and 2023YFQ0091)the National Natural Science Foundation of China(Nos.U21A20167 and 52475138)the Scientific Research Foundation of the State Key Laboratory of Rail Transit Vehicle System(No.2024RVL-T08).
文摘Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.
