To improve the safety of construction workers and help workers remotely control humanoid robots in construc-tion,this study designs and implements a computer vision based virtual construction simulation system.For thi...To improve the safety of construction workers and help workers remotely control humanoid robots in construc-tion,this study designs and implements a computer vision based virtual construction simulation system.For this pur-pose,human skeleton motion data are collected using a Ki-nect depth camera,and the obtained data are optimized via abnormal data elimination,smoothing,and normalization.MediaPipe extracts three-dimensional hand motion coordi-nates for accurate human posture tracking.Blender is used to build a virtual worker and site model,and the virtual worker motion is controlled based on the quaternion inverse kinematics algorithm while limiting the joint angle to en-hance the authenticity of motion simulation.Experimental results show that the system frame rate is stable at 60 frame/s,end-to-end delay is less than 20 ms,and virtual task comple-tion time is close to the real scene,verifying its engineering applicability.The proposed system can drive virtual work-ers to perform tasks and provide technical support for con-struction safety training.展开更多
Electroacoustic Tomography(EAT)is an imaging technique that detects ultrasound waves induced by electrical pulses,offering a solution for real-time electroporation monitoring.This study presents EAT system using a dua...Electroacoustic Tomography(EAT)is an imaging technique that detects ultrasound waves induced by electrical pulses,offering a solution for real-time electroporation monitoring.This study presents EAT system using a dual-frequency ultrasound array.The broadband nature of electroacoustic signals requires ultrasound detector to cover both the high-frequency range(around 6MHz)signals generated by small targets and the low-frequency range(around 1MHz)signals generated by large targets.In our EAT system,we use the 6 MHz array to detect high-frequency signals from the electrodes,and the 1 MHz array for the electrical field.To test this,we conducted simulations using COMSOL Multiphysics^(®) and MATLAB's k-Wave toolbox,followed by experiments using a custom-built setup with a dual-frequency transducer and real-time data acquisition.The results demonstrated that the dual-frequency EAT system could accurately and simultaneously monitor the electroporation process,effectively showing both the treatment area and electrode placement with the application of 1 kV electric pulses with 100 ns duration.The axial resolution of the 6MHz array for EAT was 0.45 mm,significantly better than the 2mm resolution achieved with the 1MHz array.These findings validate the potential of dual-frequency EAT as a superior method for real-time electroporation monitoring.展开更多
Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing addit...Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing additive-induced defects,and alleviating residual stress and deformation,all of which are critical for enhancing the mechanical performance of the manufactured parts.Integrating interlayer friction stir processing(FSP)into WAAM significantly enhances the quality of deposited materials.However,numerical simulation research focusing on elucidating the associated thermomechanical coupling mechanisms remains insufficient.A comprehensive numerical model was developed to simulate the thermomechanical coupling behavior in friction stir-assisted WAAM.The influence of post-deposition FSP on the coupled thermomechanical response of the WAAM process was analyzed quantitatively.Moreover,the residual stress distribution and deformation behavior under both single-layer and multilayer deposition conditions were investigated.Thermal analysis of different deposition layers in WAAM and friction stir-assisted WAAM was conducted.Results show that subsequent layer deposition induces partial remelting of the previously solidified layer,whereas FSP does not cause such remelting.Furthermore,thermal stress and deformation analysis confirm that interlayer FSP effectively mitigates residual stresses and distortion in WAAM components,thereby improving their structural integrity and mechanical properties.展开更多
Vehicle-induced response separation is a crucial issue in structural health monitoring(SHM).This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements ...Vehicle-induced response separation is a crucial issue in structural health monitoring(SHM).This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements of monitoring data.To extend the separation target from a fixed dataset to a continuously updating data stream,a block-wise sliding framework is first developed.This framework is further optimized considering the characteristics of real-time data streams,and its advantage in computational efficiency is theoretically demonstrated.During the decomposition and reconstruction processes,information from neighboring data blocks is fully utilized to reduce algorithmic complexity.In addition,a delay-setting strategy is introduced for each processing window to mitigate boundary effects,thereby balancing accuracy and efficiency.Simulated signal experiments are conducted to determine the optimal delay configuration and to verify the algorithm’s superior performance,achieving a lower Root Mean Square Error(RMSE)and only 0.0249 times the average computational time compared with the original algorithm.Furthermore,strain signals from the Lieshi River Bridge are employed to validate the method.The proposed algorithm successfully separates the static trend from vehicle-induced responses in real time across different sampling frequencies,demonstrating its effectiveness and applicability in real-time bridge monitoring.展开更多
To investigate the energy relief effect of real-time drilling in preventing rockburst in high-stress rock,a series of high-stress real-time drilling uniaxial compression tests were conducted on red sandstone specimens...To investigate the energy relief effect of real-time drilling in preventing rockburst in high-stress rock,a series of high-stress real-time drilling uniaxial compression tests were conducted on red sandstone specimens using the SG4500 drilling rig.Results showed that the mechanical behavior(i.e.peak strength and rockburst intensity)of the rock was weakened under high-stress real-time drilling and exhibited a downward trend as the drilling diameter increased.The real-time drilling energy dissipation index(ERD)was proposed to characterize the energy relief during high-stress real-time drilling.The ERD exhibited a linear increase with the real-time drilling diameter.Furthermore,the elastic strain energy of post-drilling rock showed a linear relationship with the square of stress across different stress levels,which also applied to the peak elastic strain energy and the square of peak stress.This findingreveals the intrinsic link between the weakening effect of peak elastic strain energy and peak strength due to high-stress real-time drilling,confirmingthe consistency between energy relief and pressure relief effects.By establishing relationships among rockburst proneness,peak elastic strain energy,and peak strength,it was demonstrated that high-stress real-time drilling reduces rockburst proneness through energy dissipation.Specifically,both peak elastic strain energy and rockburst proneness decreased with larger drill bit diameters,consistent with reductions in peak strength,rockburst intensity,and fractal dimensions of high-stress real-time drilled rock.These results validate the energy relief mechanism of real-time drilling in mitigating rockburst risks.展开更多
The F_(1)-ATPase and V_(1)-ATPase are rotary biomotors.Alignment of their amino acid sequences,which originate from bovine heart mitochondria(1BMF)and Enterococcus hirae(3VR6),respectively,demonstrates that the segmen...The F_(1)-ATPase and V_(1)-ATPase are rotary biomotors.Alignment of their amino acid sequences,which originate from bovine heart mitochondria(1BMF)and Enterococcus hirae(3VR6),respectively,demonstrates that the segment forming the ATP catalytic pocket is highly conserved.Single-molecule experiments,however,have revealed subtle differences in efficiency between the F_(1) and V_(1) motors.Here,we perform both atomistic and coarse-grained molecular dynamics simulations to investigate the mechanochemical coupling and coordination in F_(1) and V_(1) ATPase.Our results show that the correlation between conformational changes in F_(1) is stronger than that in V_(1),indicating that the mechanochemical coupling in F_(1) is tighter than in V_(1).Moreover,the unidirectional rotation of F_(1) is more processive than that of V_(1),which accounts for the higher efficiency observed in F_(1) and explains the occasional backward steps detected in single-molecule experiments on V_(1).展开更多
An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of a...An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of adverse geological conditions in deep-buried tunnel construction.The installation techniques for microseismic sensors were optimized by mounting sensors at bolt ends which significantly improves signal-to-noise ratio(SNR)and anti-interference capability compared to conventional borehole placement.Subsequently,a 3D wave velocity evolution model that incorporates construction-induced disturbances was established,enabling the first visualization of spatiotemporal variations in surrounding rock wave velocity.It finds significant wave velocity reduction near the tunnel face,with roof and floor damage zones extending 40–50 m;wave velocities approaching undisturbed levels at 15 m ahead of the working face and on the laterally undisturbed side;pronounced spatial asymmetry in wave velocity distribution—values on the left side exceed those on the right,with a clear stress concentration or transition zone located 10–15 m;and systematically lower velocities behind the face than in front,indicating asymmetric rock damage development.These results provide essential theoretical support and practical guidance for optimizing dynamic construction strategies,enabling real-time adjustment of support parameters,and establishing safety early warning systems in deep-buried tunnel engineering.展开更多
The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-ti...The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-time scenarios.This review begins with a concise overview of traditional tight-binding(TB)models,including both(semi-)empirical and first-principles approaches,establishing the foundation for understanding MLTB developments.We then present a systematic classification of existing MLTB methodologies,grouped into two major categories:direct prediction of TB Hamiltonian elements and inference of empirical parameters.A comparative analysis with other ML-based electronic structure models is also provided,highlighting the advancement of MLTB approaches.Finally,we explore the emerging MLTB application ecosystem,highlighting how the integration of MLTB models with a diverse suite of post-processing tools from linear-scaling solvers to quantum transport frameworks and molecular dynamics interfaces is essential for tackling complex scientific problems across different domains.The continued advancement of this integrated paradigm promises to accelerate materials discovery and open new frontiers in the predictive simulation of complex quantum phenomena.展开更多
Vitrimers belong to a class of polymeric materials capable of bond exchange reactions,showing great promise for environmental protection and sustainable development.However,studies on the coupling mechanism between th...Vitrimers belong to a class of polymeric materials capable of bond exchange reactions,showing great promise for environmental protection and sustainable development.However,studies on the coupling mechanism between the bond exchange kinetics and segmental dynamics near the glass transition temperature(T_(g))remain scarce.Herein,we employed molecular dynamics simulations to investigate the dynamic heterogeneity of the segment motion and bond exchange in vitrimers.The simulation results revealed that the bond exchange energy barrier exerts a much stronger influence on the bond exchange kinetics than on the segmental dynamics.At lower temperatures,slower segmental relaxation further constraind the bond exchange rate.Additionally,increasing the bond exchange energy barrier markedly enhanced the dynamic heterogeneity of segment motion.A close correlation was observed between heterogeneity and bond exchange.This study elucidated the coupling mechanism between bond exchange and segmental dynamics at the molecular scale,thereby providing a theoretical basis for designing vitrimer materials with tunable dynamic properties.展开更多
Online examinations have become a dominant assessment mode,increasing concerns over academic integrity.To address the critical challenge of detecting cheating behaviours,this study proposes a hybrid deep learning appr...Online examinations have become a dominant assessment mode,increasing concerns over academic integrity.To address the critical challenge of detecting cheating behaviours,this study proposes a hybrid deep learning approach that combines visual detection and temporal behaviour classification.The methodology utilises object detection models—You Only Look Once(YOLOv12),Faster Region-based Convolutional Neural Network(RCNN),and Single Shot Detector(SSD)MobileNet—integrated with classification models such as Convolutional Neural Networks(CNN),Bidirectional Gated Recurrent Unit(Bi-GRU),and CNN-LSTM(Long Short-Term Memory).Two distinct datasets were used:the Online Exam Proctoring(EOP)dataset from Michigan State University and the School of Computer Science,Duy Tan Unievrsity(SCS-DTU)dataset collected in a controlled classroom setting.A diverse set of cheating behaviours,including book usage,unauthorised interaction,internet access,and mobile phone use,was categorised.Comprehensive experiments evaluated the models based on accuracy,precision,recall,training time,inference speed,and memory usage.We evaluate nine detector-classifier pairings under a unified budget and score them via a calibrated harmonic mean of detection and classification accuracies,enabling deployment-oriented selection under latency and memory constraints.Macro-Precision/Recall/F1 and Receiver Operating Characteristic-Area Under the Curve(ROC-AUC)are reported for the top configurations,revealing consistent advantages of object-centric pipelines for fine-grained cheating cues.The highest overall score is achieved by YOLOv12+CNN(97.15%accuracy),while SSD-MobileNet+CNN provides the best speed-efficiency trade-off for edge devices.This research provides valuable insights into selecting and deploying appropriate deep learning models for maintaining exam integrity under varying resource constraints.展开更多
In federated learning,backdoor attacks have become an important research topic with their wide application in processing sensitive datasets.Since federated learning detects or modifies local models through defense mec...In federated learning,backdoor attacks have become an important research topic with their wide application in processing sensitive datasets.Since federated learning detects or modifies local models through defense mechanisms during aggregation,it is difficult to conduct effective backdoor attacks.In addition,existing backdoor attack methods are faced with challenges,such as low backdoor accuracy,poor ability to evade anomaly detection,and unstable model training.To address these challenges,a method called adaptive simulation backdoor attack(ASBA)is proposed.Specifically,ASBA improves the stability of model training by manipulating the local training process and using an adaptive mechanism,the ability of the malicious model to evade anomaly detection by combing large simulation training and clipping,and the backdoor accuracy by introducing a stimulus model to amplify the impact of the backdoor in the global model.Extensive comparative experiments under five advanced defense scenarios show that ASBA can effectively evade anomaly detection and achieve high backdoor accuracy in the global model.Furthermore,it exhibits excellent stability and effectiveness after multiple rounds of attacks,outperforming state-of-the-art backdoor attack methods.展开更多
The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,th...The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.展开更多
UHMWPE fibers exhibit impressive modulus and strength,but they have not reached their theoretical limits.Researchers focus on molecular weight,orientation,and crystallinity of UHMWPE,yet their contributions to mechani...UHMWPE fibers exhibit impressive modulus and strength,but they have not reached their theoretical limits.Researchers focus on molecular weight,orientation,and crystallinity of UHMWPE,yet their contributions to mechanical properties are unclear.Molecular dynamics simulations are valuable but often limited by computational constraints.Our aim is to simulate higher molecular weights to better represent real UHMWPE fibers.We used Packmol and Polyply methodologies to construct PE systems,with Polyply reproducing more reasonable properties of UHMWPE fibers.Additionally,tensile simulations showed that orientation and crystallinity greatly impact Young's modulus more than molecular weight.Energy decomposition indicated that higher molecular weights lead to covalent bonds that can withstand more energy during stretching,thus increasing breaking strength.Combining simulations with machine learning,we found that orientation has the most significant impact on Young's modulus,contributing 60%,and molecular weight plays the most crucial role in determining the breaking strength,accounting for 65%.This study provides a theoretical basis and guidelines for enhancing UHMWPE's modulus and strength.展开更多
With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyz...With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyze the charging load characteristics of six battery electric vehicle categories in Hebei Province,leveraging multi-source probabilistic distribution data under typical operational scenarios.The findings reveal that electric vehicle charging loads are primarily concentrated during midday and nighttime periods,with significant load fluctuations exerting substantial pressure on the grid.In response,this paper proposes strategic interventions including optimized charging infrastructure planning,time-of-use electricity pricing mechanisms,and smart charging technologies to balance grid loads.The results provide a theoretical foundation for electric vehicle load forecasting,smart grid dispatching,and vehicle-grid integration,thereby enhancing grid operational efficiency and sustainability.展开更多
An in-depth understanding of the behaviours of solid propellants under low-velocity impact loads is crucial for enhancing their safety in applications such as aerospace propulsion.This study investigated the dynamic r...An in-depth understanding of the behaviours of solid propellants under low-velocity impact loads is crucial for enhancing their safety in applications such as aerospace propulsion.This study investigated the dynamic responses of single ammonium perchlorate(AP)/octogen(HMX)particles embedded in a hydroxyl-terminated polybutadiene(HTPB)binder under dynamic compression loading via real-time synchrotron-based X-ray phase contrast imaging and a modified split Hopkinson pressure bar(SHPB)system.The compression of the viscoelastic binder and subsequent dynamic fracturing of the AP/HMX particles were captured.During compression,transverse cracks developed within the AP particles,and their propagation led to particle fracturing,resulting in ductile fracturing.Unlike AP,HMX generated numerous short cracks within the internal and edge regions simultaneously,leading to fragmentation and brittle fracturing.Moreover,particle damage reduced the modulus of the sample,shifting its dynamic stress response from nonlinear elasticity to strain softening and further strain hardening as the binder exhibited plastic deformation.A compression simulation incorporating a real particle microscopic structure was established to study the mechanical response of the interface and particles.The simulation results agreed with the experimental observations.These results indicate that the shear stress at the HTPB-AP interface is greater than that at the HTPB-HMX interface,which is a factor influencing the differences in the mesoscale damage mechanisms of the particles.展开更多
In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In additi...In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In addition,methods for deploying multiple cameras for motion capture of users(e.g.,performers)are widely used in computer graphics.As the need to minimize and optimize the number of cameras grows to reduce costs,various technologies and research approaches focused on Optimal Camera Placement(OCP)are continually being proposed.However,as most existing studies assume homogeneous camera setups,there is a growing demand for studies on heterogeneous camera setups.For instance,technical demands keep emerging in scenarios with minimal camera configurations,especially regarding cost factors,the physical placement of cameras given the spatial structure,and image capture strategies for heterogeneous cameras,such as high-resolution RGB cameras and depth cameras.In this study,we propose a pre-visualization and simulation method for the optimal placement of heterogeneous cameras in XR environments,accounting for both the specifications of heterogeneous cameras(e.g.,field of view)and the physical configuration(e.g.,wall configuration)in real-world spaces.The proposed method performs a visibility analysis of cameras by considering each camera’s field-of-view volume,resolution,and unique characteristics,along with physicalspace constraints.This approach enables the optimal position and rotation of each camera to be recommended,along with the minimum number of cameras required.In the results of our study conducted in heterogeneous camera combinations,the proposed method achieved 81.7%~82.7%coverage of the target visual information using only 2~3 cameras.In contrast,single(or homogeneous)-typed cameras were required to use 11 cameras for 81.6%coverage.Accordingly,we found that camera deployment resources can be reduced with the proposed approaches.展开更多
基金The Eighth National “Ten Thousand Talents Plan for Top Young Talents” of Chinathe National Natural Science Foundation of China (No. 52478117, 52378120)。
文摘To improve the safety of construction workers and help workers remotely control humanoid robots in construc-tion,this study designs and implements a computer vision based virtual construction simulation system.For this pur-pose,human skeleton motion data are collected using a Ki-nect depth camera,and the obtained data are optimized via abnormal data elimination,smoothing,and normalization.MediaPipe extracts three-dimensional hand motion coordi-nates for accurate human posture tracking.Blender is used to build a virtual worker and site model,and the virtual worker motion is controlled based on the quaternion inverse kinematics algorithm while limiting the joint angle to en-hance the authenticity of motion simulation.Experimental results show that the system frame rate is stable at 60 frame/s,end-to-end delay is less than 20 ms,and virtual task comple-tion time is close to the real scene,verifying its engineering applicability.The proposed system can drive virtual work-ers to perform tasks and provide technical support for con-struction safety training.
基金supported by the National Institute of Health(R37CA240806,U01CA288351,and R50CA283816)support from UCI Chao Family Comprehensive Cancer Center(P30CA062203).
文摘Electroacoustic Tomography(EAT)is an imaging technique that detects ultrasound waves induced by electrical pulses,offering a solution for real-time electroporation monitoring.This study presents EAT system using a dual-frequency ultrasound array.The broadband nature of electroacoustic signals requires ultrasound detector to cover both the high-frequency range(around 6MHz)signals generated by small targets and the low-frequency range(around 1MHz)signals generated by large targets.In our EAT system,we use the 6 MHz array to detect high-frequency signals from the electrodes,and the 1 MHz array for the electrical field.To test this,we conducted simulations using COMSOL Multiphysics^(®) and MATLAB's k-Wave toolbox,followed by experiments using a custom-built setup with a dual-frequency transducer and real-time data acquisition.The results demonstrated that the dual-frequency EAT system could accurately and simultaneously monitor the electroporation process,effectively showing both the treatment area and electrode placement with the application of 1 kV electric pulses with 100 ns duration.The axial resolution of the 6MHz array for EAT was 0.45 mm,significantly better than the 2mm resolution achieved with the 1MHz array.These findings validate the potential of dual-frequency EAT as a superior method for real-time electroporation monitoring.
基金National Key Research and Development Program of China(2022YFB4600902)Shandong Provincial Science Foundation for Outstanding Young Scholars(ZR2024YQ020)。
文摘Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing additive-induced defects,and alleviating residual stress and deformation,all of which are critical for enhancing the mechanical performance of the manufactured parts.Integrating interlayer friction stir processing(FSP)into WAAM significantly enhances the quality of deposited materials.However,numerical simulation research focusing on elucidating the associated thermomechanical coupling mechanisms remains insufficient.A comprehensive numerical model was developed to simulate the thermomechanical coupling behavior in friction stir-assisted WAAM.The influence of post-deposition FSP on the coupled thermomechanical response of the WAAM process was analyzed quantitatively.Moreover,the residual stress distribution and deformation behavior under both single-layer and multilayer deposition conditions were investigated.Thermal analysis of different deposition layers in WAAM and friction stir-assisted WAAM was conducted.Results show that subsequent layer deposition induces partial remelting of the previously solidified layer,whereas FSP does not cause such remelting.Furthermore,thermal stress and deformation analysis confirm that interlayer FSP effectively mitigates residual stresses and distortion in WAAM components,thereby improving their structural integrity and mechanical properties.
基金the support of the Major Science and Technology Project of Yunnan Province,China(Grant No.202502AD080007)the National Natural Science Foundation of China(Grant No.52378288)。
文摘Vehicle-induced response separation is a crucial issue in structural health monitoring(SHM).This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements of monitoring data.To extend the separation target from a fixed dataset to a continuously updating data stream,a block-wise sliding framework is first developed.This framework is further optimized considering the characteristics of real-time data streams,and its advantage in computational efficiency is theoretically demonstrated.During the decomposition and reconstruction processes,information from neighboring data blocks is fully utilized to reduce algorithmic complexity.In addition,a delay-setting strategy is introduced for each processing window to mitigate boundary effects,thereby balancing accuracy and efficiency.Simulated signal experiments are conducted to determine the optimal delay configuration and to verify the algorithm’s superior performance,achieving a lower Root Mean Square Error(RMSE)and only 0.0249 times the average computational time compared with the original algorithm.Furthermore,strain signals from the Lieshi River Bridge are employed to validate the method.The proposed algorithm successfully separates the static trend from vehicle-induced responses in real time across different sampling frequencies,demonstrating its effectiveness and applicability in real-time bridge monitoring.
基金supported by the National Natural Science Foundation of China(Grant No.42077244)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX24_0434).
文摘To investigate the energy relief effect of real-time drilling in preventing rockburst in high-stress rock,a series of high-stress real-time drilling uniaxial compression tests were conducted on red sandstone specimens using the SG4500 drilling rig.Results showed that the mechanical behavior(i.e.peak strength and rockburst intensity)of the rock was weakened under high-stress real-time drilling and exhibited a downward trend as the drilling diameter increased.The real-time drilling energy dissipation index(ERD)was proposed to characterize the energy relief during high-stress real-time drilling.The ERD exhibited a linear increase with the real-time drilling diameter.Furthermore,the elastic strain energy of post-drilling rock showed a linear relationship with the square of stress across different stress levels,which also applied to the peak elastic strain energy and the square of peak stress.This findingreveals the intrinsic link between the weakening effect of peak elastic strain energy and peak strength due to high-stress real-time drilling,confirmingthe consistency between energy relief and pressure relief effects.By establishing relationships among rockburst proneness,peak elastic strain energy,and peak strength,it was demonstrated that high-stress real-time drilling reduces rockburst proneness through energy dissipation.Specifically,both peak elastic strain energy and rockburst proneness decreased with larger drill bit diameters,consistent with reductions in peak strength,rockburst intensity,and fractal dimensions of high-stress real-time drilled rock.These results validate the energy relief mechanism of real-time drilling in mitigating rockburst risks.
基金supported by the National Natural Science Foundation of China(Grant Nos.22193032 and 32401033)the Research Fund of Wenzhou Institute,Chinese Academy of Sciences(Grant Nos.WIUCASQD2020009,WIUCASQD2023005,XSZD2024004,2021HZSY0061,and WIUCASICTP2022)。
文摘The F_(1)-ATPase and V_(1)-ATPase are rotary biomotors.Alignment of their amino acid sequences,which originate from bovine heart mitochondria(1BMF)and Enterococcus hirae(3VR6),respectively,demonstrates that the segment forming the ATP catalytic pocket is highly conserved.Single-molecule experiments,however,have revealed subtle differences in efficiency between the F_(1) and V_(1) motors.Here,we perform both atomistic and coarse-grained molecular dynamics simulations to investigate the mechanochemical coupling and coordination in F_(1) and V_(1) ATPase.Our results show that the correlation between conformational changes in F_(1) is stronger than that in V_(1),indicating that the mechanochemical coupling in F_(1) is tighter than in V_(1).Moreover,the unidirectional rotation of F_(1) is more processive than that of V_(1),which accounts for the higher efficiency observed in F_(1) and explains the occasional backward steps detected in single-molecule experiments on V_(1).
基金support of the National Natural Science Foundation of China(No.52274176)the Guangdong Province Key Areas R&D Program(No.2022B0101070001)+5 种基金Chongqing Elite Innovation and Entrepreneurship Leading talent Project(No.CQYC20220302517)the Chongqing Natural Science Foundation Innovation and Development Joint Fund(No.CSTB2022NSCQ-LZX0079)the National Key Research and Development Program Young Scientists Project(No.2022YFC2905700)the Chongqing Municipal Education Commission“Shuangcheng Economic Circle Construction in Chengdu-Chongqing Area”Science and Technology Innovation Project(No.KJCX2020031)the Fundamental Research Funds for the Central Universities(No.2024CDJGF-009)the Key Project for Technological Innovation and Application Development in Chongqing(No.CSTB2025TIAD-KPX0029).
文摘An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of adverse geological conditions in deep-buried tunnel construction.The installation techniques for microseismic sensors were optimized by mounting sensors at bolt ends which significantly improves signal-to-noise ratio(SNR)and anti-interference capability compared to conventional borehole placement.Subsequently,a 3D wave velocity evolution model that incorporates construction-induced disturbances was established,enabling the first visualization of spatiotemporal variations in surrounding rock wave velocity.It finds significant wave velocity reduction near the tunnel face,with roof and floor damage zones extending 40–50 m;wave velocities approaching undisturbed levels at 15 m ahead of the working face and on the laterally undisturbed side;pronounced spatial asymmetry in wave velocity distribution—values on the left side exceed those on the right,with a clear stress concentration or transition zone located 10–15 m;and systematically lower velocities behind the face than in front,indicating asymmetric rock damage development.These results provide essential theoretical support and practical guidance for optimizing dynamic construction strategies,enabling real-time adjustment of support parameters,and establishing safety early warning systems in deep-buried tunnel engineering.
基金supported by the Advanced Materials-National Science and Technology Major Project(Grant No.2025ZD0618401)the National Natural Science Foundation of China(Grant No.12504285)+1 种基金the Natural Science Foundation of Jiangsu Province(Grant No.BK20250472)NFSG grant from BITS-Pilani,Dubai campus。
文摘The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-time scenarios.This review begins with a concise overview of traditional tight-binding(TB)models,including both(semi-)empirical and first-principles approaches,establishing the foundation for understanding MLTB developments.We then present a systematic classification of existing MLTB methodologies,grouped into two major categories:direct prediction of TB Hamiltonian elements and inference of empirical parameters.A comparative analysis with other ML-based electronic structure models is also provided,highlighting the advancement of MLTB approaches.Finally,we explore the emerging MLTB application ecosystem,highlighting how the integration of MLTB models with a diverse suite of post-processing tools from linear-scaling solvers to quantum transport frameworks and molecular dynamics interfaces is essential for tackling complex scientific problems across different domains.The continued advancement of this integrated paradigm promises to accelerate materials discovery and open new frontiers in the predictive simulation of complex quantum phenomena.
基金financially supported by the National Natural Science Foundation of China(Nos.52173020 and 52573023)。
文摘Vitrimers belong to a class of polymeric materials capable of bond exchange reactions,showing great promise for environmental protection and sustainable development.However,studies on the coupling mechanism between the bond exchange kinetics and segmental dynamics near the glass transition temperature(T_(g))remain scarce.Herein,we employed molecular dynamics simulations to investigate the dynamic heterogeneity of the segment motion and bond exchange in vitrimers.The simulation results revealed that the bond exchange energy barrier exerts a much stronger influence on the bond exchange kinetics than on the segmental dynamics.At lower temperatures,slower segmental relaxation further constraind the bond exchange rate.Additionally,increasing the bond exchange energy barrier markedly enhanced the dynamic heterogeneity of segment motion.A close correlation was observed between heterogeneity and bond exchange.This study elucidated the coupling mechanism between bond exchange and segmental dynamics at the molecular scale,thereby providing a theoretical basis for designing vitrimer materials with tunable dynamic properties.
文摘Online examinations have become a dominant assessment mode,increasing concerns over academic integrity.To address the critical challenge of detecting cheating behaviours,this study proposes a hybrid deep learning approach that combines visual detection and temporal behaviour classification.The methodology utilises object detection models—You Only Look Once(YOLOv12),Faster Region-based Convolutional Neural Network(RCNN),and Single Shot Detector(SSD)MobileNet—integrated with classification models such as Convolutional Neural Networks(CNN),Bidirectional Gated Recurrent Unit(Bi-GRU),and CNN-LSTM(Long Short-Term Memory).Two distinct datasets were used:the Online Exam Proctoring(EOP)dataset from Michigan State University and the School of Computer Science,Duy Tan Unievrsity(SCS-DTU)dataset collected in a controlled classroom setting.A diverse set of cheating behaviours,including book usage,unauthorised interaction,internet access,and mobile phone use,was categorised.Comprehensive experiments evaluated the models based on accuracy,precision,recall,training time,inference speed,and memory usage.We evaluate nine detector-classifier pairings under a unified budget and score them via a calibrated harmonic mean of detection and classification accuracies,enabling deployment-oriented selection under latency and memory constraints.Macro-Precision/Recall/F1 and Receiver Operating Characteristic-Area Under the Curve(ROC-AUC)are reported for the top configurations,revealing consistent advantages of object-centric pipelines for fine-grained cheating cues.The highest overall score is achieved by YOLOv12+CNN(97.15%accuracy),while SSD-MobileNet+CNN provides the best speed-efficiency trade-off for edge devices.This research provides valuable insights into selecting and deploying appropriate deep learning models for maintaining exam integrity under varying resource constraints.
文摘In federated learning,backdoor attacks have become an important research topic with their wide application in processing sensitive datasets.Since federated learning detects or modifies local models through defense mechanisms during aggregation,it is difficult to conduct effective backdoor attacks.In addition,existing backdoor attack methods are faced with challenges,such as low backdoor accuracy,poor ability to evade anomaly detection,and unstable model training.To address these challenges,a method called adaptive simulation backdoor attack(ASBA)is proposed.Specifically,ASBA improves the stability of model training by manipulating the local training process and using an adaptive mechanism,the ability of the malicious model to evade anomaly detection by combing large simulation training and clipping,and the backdoor accuracy by introducing a stimulus model to amplify the impact of the backdoor in the global model.Extensive comparative experiments under five advanced defense scenarios show that ASBA can effectively evade anomaly detection and achieve high backdoor accuracy in the global model.Furthermore,it exhibits excellent stability and effectiveness after multiple rounds of attacks,outperforming state-of-the-art backdoor attack methods.
基金supported by the National Natural Science Foundation of China(Grant No.62403486)。
文摘The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.
基金financially supported by the National Natural Science Foundation of China(Nos.52303298 and 52233002)。
文摘UHMWPE fibers exhibit impressive modulus and strength,but they have not reached their theoretical limits.Researchers focus on molecular weight,orientation,and crystallinity of UHMWPE,yet their contributions to mechanical properties are unclear.Molecular dynamics simulations are valuable but often limited by computational constraints.Our aim is to simulate higher molecular weights to better represent real UHMWPE fibers.We used Packmol and Polyply methodologies to construct PE systems,with Polyply reproducing more reasonable properties of UHMWPE fibers.Additionally,tensile simulations showed that orientation and crystallinity greatly impact Young's modulus more than molecular weight.Energy decomposition indicated that higher molecular weights lead to covalent bonds that can withstand more energy during stretching,thus increasing breaking strength.Combining simulations with machine learning,we found that orientation has the most significant impact on Young's modulus,contributing 60%,and molecular weight plays the most crucial role in determining the breaking strength,accounting for 65%.This study provides a theoretical basis and guidelines for enhancing UHMWPE's modulus and strength.
基金funded by Humanities and Social Sciences of Ministry of Education Planning Fund of China,grant number 21YJA790009National Natural Science Foundation of China,grant number 72140001.
文摘With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyze the charging load characteristics of six battery electric vehicle categories in Hebei Province,leveraging multi-source probabilistic distribution data under typical operational scenarios.The findings reveal that electric vehicle charging loads are primarily concentrated during midday and nighttime periods,with significant load fluctuations exerting substantial pressure on the grid.In response,this paper proposes strategic interventions including optimized charging infrastructure planning,time-of-use electricity pricing mechanisms,and smart charging technologies to balance grid loads.The results provide a theoretical foundation for electric vehicle load forecasting,smart grid dispatching,and vehicle-grid integration,thereby enhancing grid operational efficiency and sustainability.
基金supported by the National Natural Science Foundation of China(U2341288 and 12302492)。
文摘An in-depth understanding of the behaviours of solid propellants under low-velocity impact loads is crucial for enhancing their safety in applications such as aerospace propulsion.This study investigated the dynamic responses of single ammonium perchlorate(AP)/octogen(HMX)particles embedded in a hydroxyl-terminated polybutadiene(HTPB)binder under dynamic compression loading via real-time synchrotron-based X-ray phase contrast imaging and a modified split Hopkinson pressure bar(SHPB)system.The compression of the viscoelastic binder and subsequent dynamic fracturing of the AP/HMX particles were captured.During compression,transverse cracks developed within the AP particles,and their propagation led to particle fracturing,resulting in ductile fracturing.Unlike AP,HMX generated numerous short cracks within the internal and edge regions simultaneously,leading to fragmentation and brittle fracturing.Moreover,particle damage reduced the modulus of the sample,shifting its dynamic stress response from nonlinear elasticity to strain softening and further strain hardening as the binder exhibited plastic deformation.A compression simulation incorporating a real particle microscopic structure was established to study the mechanical response of the interface and particles.The simulation results agreed with the experimental observations.These results indicate that the shear stress at the HTPB-AP interface is greater than that at the HTPB-HMX interface,which is a factor influencing the differences in the mesoscale damage mechanisms of the particles.
基金supported by the 2024 Research Fund of University of Ulsan.
文摘In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In addition,methods for deploying multiple cameras for motion capture of users(e.g.,performers)are widely used in computer graphics.As the need to minimize and optimize the number of cameras grows to reduce costs,various technologies and research approaches focused on Optimal Camera Placement(OCP)are continually being proposed.However,as most existing studies assume homogeneous camera setups,there is a growing demand for studies on heterogeneous camera setups.For instance,technical demands keep emerging in scenarios with minimal camera configurations,especially regarding cost factors,the physical placement of cameras given the spatial structure,and image capture strategies for heterogeneous cameras,such as high-resolution RGB cameras and depth cameras.In this study,we propose a pre-visualization and simulation method for the optimal placement of heterogeneous cameras in XR environments,accounting for both the specifications of heterogeneous cameras(e.g.,field of view)and the physical configuration(e.g.,wall configuration)in real-world spaces.The proposed method performs a visibility analysis of cameras by considering each camera’s field-of-view volume,resolution,and unique characteristics,along with physicalspace constraints.This approach enables the optimal position and rotation of each camera to be recommended,along with the minimum number of cameras required.In the results of our study conducted in heterogeneous camera combinations,the proposed method achieved 81.7%~82.7%coverage of the target visual information using only 2~3 cameras.In contrast,single(or homogeneous)-typed cameras were required to use 11 cameras for 81.6%coverage.Accordingly,we found that camera deployment resources can be reduced with the proposed approaches.
