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
In this paper,the growth characteristic of meromorphic solutions for the following difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=0 with no dominating coefficient is studied.By imposing certain restriction o...In this paper,the growth characteristic of meromorphic solutions for the following difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=0 with no dominating coefficient is studied.By imposing certain restriction on the entire coefficients associated with Petrenko's deviation of the above equation,we obtain some results and partially address a question posed byⅠ.Laine and C.C.Yang.Furthermore,for the entire solutions f(z)of the difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=F(z),where Aj(z)(j=0,…,n),F(z)are entire functions,we discover a close relationship between the measure of common transcendental directions associated with classical difference operators of f(z)and Petrenko's deviations of the coefficients.展开更多
As a fundamental component in computer vision,edges can be categorized into four types based on discontinuities in reflectance,illumination,surface normal,or depth.While deep CNNs have significantly advanced generic e...As a fundamental component in computer vision,edges can be categorized into four types based on discontinuities in reflectance,illumination,surface normal,or depth.While deep CNNs have significantly advanced generic edge detection,real-time multi-class semantic edge detection under resource constraints remains challenging.To address this,we propose a lightweight framework based on PiDiNet that enables fine-grained semantic edge detection.Our model simultaneously predicts background and four edge categories from full-resolution inputs,balancing accuracy and efficiency.Key contributions include:a multi-channel output structure expanding binary edge prediction to five classes,supported by a deep supervision mechanism;a dynamic class-balancing strategy combining adaptive weighting with physical priors to handle extreme class imbalance;and maintained architectural efficiency enabling real-time inference.Extensive evaluations on BSDS-RIND show our approach achieves accuracy competitive with state-of-the-art methods while operating in real time.展开更多
In the era of the Internet of Things,distributed computing alleviates the problem of insufficient terminal computing power by integrating idle resources of heterogeneous devices.However,the imbalance between task exec...In the era of the Internet of Things,distributed computing alleviates the problem of insufficient terminal computing power by integrating idle resources of heterogeneous devices.However,the imbalance between task execution delay and node energy consumption,and the scheduling and adaptation challenges brought about by device heterogeneity,urgently need to be addressed.To tackle this problem,this paper constructs a multi-objective real-time task scheduling model that considers task real-time performance,execution delay,system energy consumption,and node interests.The model aims to minimize the delay upper bound and total energy consumption while maximizing system satisfaction.A real-time task scheduling algorithm based on bilateral matching game is proposed.By designing a bidirectional preference mechanism between tasks and computing nodes,combined with a multi-round stable matching strategy,accurate matching between tasks and nodes is achieved.Simulation results show that compared with the baseline scheme,the proposed algorithm significantly reduces the total execution cost,effectively balances the task execution delay and the energy consumption of compute nodes,and takes into account the interests of each network compute node.展开更多
An integrated real-time control methodology is introduced to mitigate process-induced challenges,namely temperature overshoot,uneven cure,and interfacial shear stress,during the autoclave curing of Carbon Fiber-Reinfo...An integrated real-time control methodology is introduced to mitigate process-induced challenges,namely temperature overshoot,uneven cure,and interfacial shear stress,during the autoclave curing of Carbon Fiber-Reinforced Polymer(CFRP)composites.First,a high-fidelity Finite Element(FE)model incorporating tool-part interaction is developed to reveal the curing process of the composites,wherein the interaction is characterized by friction interface modeling with experimentally measured cure-dependent friction coefficients.The accuracy of FE model is confirmed through experimental tests on a doubly curved T-stiffened composite panel.This validated model then generates a dataset of curing temperature profile and associated defect information,which is used to train a customized Long Short-Term Memory(LSTM)neural network.We culminate in a real-time control framework that actively optimizes the curing process by integrating LSTM-based state prediction with Q-learning-driven decision logic.The optimized thermal profile demonstrates a clear performance enhancement over the traditional multi-dwell approach,achieving marked reductions in temperature difference,Degree of Cure(DoC)difference and tool-part interface shear stress,which provides more insights for intelligent composite manufacturing.展开更多
During geothermal resource exploitation,the potential deterioration of mechanical properties in high-temperature granite subjected to cooling poses a significant safety concern.To address this,the present study invest...During geothermal resource exploitation,the potential deterioration of mechanical properties in high-temperature granite subjected to cooling poses a significant safety concern.To address this,the present study investigates the coupled thermo-mechanical behavior of granite during heating and cooling through a combination of laboratory tests and finite difference method analysis.Initial investigations involve X-ray diffraction,thermal expansion test,thermogravimetric analysis,and uniaxial compression test.Results show the significant variations of granite properties under different thermal conditions,attributed to temperature gradients,water evaporation,and mineral phase transitions.Subsequently,a model considering temperature-dependent parameters and real-time cooling rates was employed to simulate linear heating and nonlinear cooling processes.Simulation results indicate that the thermal cracking predominantly occurs during the heating stage,with tensile failure as the primary mode.Additionally,a faster real-time cooling rate at higher temperatures intensifies the thermal cracking behavior in granite.This study effectively elucidates the thermomechanical coupling behavior of granite during heating and cooling processes,providing insights into the mechanisms of mechanical property changes with rising or decreasing temperatures.展开更多
The intelligent environmental sensing systems are quickly transforming the sparse and retrospective monitoring to dense and decision-oriented environmental intelligence.This review brings together the manner in which ...The intelligent environmental sensing systems are quickly transforming the sparse and retrospective monitoring to dense and decision-oriented environmental intelligence.This review brings together the manner in which integration of Internet of Things(IoT)sensing,edge computing,and real-time analytics facilitates timely detection,interpretation,and prediction of the environmental conditions across the applications,such as urban air quality,watershed and coastal surveillance,industrial safety,agriculture,and disaster response.We define end-to-end architectural patterns to organize devices,edge nodes,and cloud services to satisfy latency,reliability,bandwidth,and governance constraints with emphasis on event-time processing,adaptive offloading,and hierarchical aggregation.Then we look at sensing and infrastructure foundations,emphasizing the effects of sensor modality and power autonomy,connectivity,and the practices of calibration on the practicable analytics and eventual plausibility.It is on this basis that we examine real-time analytics pipelines and Artificial Intelligence(AI)techniques to preprocess,sensor combine,anomaly detect,and short-horizon forecast,with a focus on edge-deployable models,quantification of uncertainties,and query resistance to drift and domain shift.Lastly,we address the realities of deployment that condition operational success,such as lifecycle engineering,provenance-aware data management,security and privacy risks,ethical governance,and evaluation methodologies,which place end-to-end latency and field generalization as a priority.This review offers cohesion to algorithmic capabilities and systems engineering and governance to define an overall framework,show open areas of research directions,and provide practical recommendations on how to design trustworthy,scalable,and sustainable environmental monitoring systems.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
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
This paper presents an efficient and automated Overset Grid Assembly(OGA)method for the structured grid,and investigates high-order interpolation methods for inter-grid boundaries with the cell-centered finite differe...This paper presents an efficient and automated Overset Grid Assembly(OGA)method for the structured grid,and investigates high-order interpolation methods for inter-grid boundaries with the cell-centered finite difference method.Four enhancements are introduced:a hybrid holecutting approach integrates the efficiency of approximate hole-cutting and the accuracy and robustness of direct-cutting,effectively addressing challenges such as small gaps and thin cuts;an improved implicit hole boundary optimization method,incorporating quality comparison,can significantly reduce donor search workloads;an improved implicit interpolation cell cancellation algorithm minimizes overlap regions,particularly beneficial for high-order interpolation with large stencils;an algorithm for identifying and eliminating islands without using wall distances,effectively removes islands.The OGA results of a multi-element airfoil,a circular array of cylinders,multiple spheres,and a wing-pylon-store configuration indicate that the proposed method would be a suitable selection for multi-body problems,even in the presence of small gaps and thin geometries.Additionally,for high-order interpolation at inter-grid boundaries,this study presents an optimized interpolation method designed to minimize spectral property errors.Numerical results indicate that for periodic problems frequently crossing inter-grid boundaries,the optimized interpolation is more accurate than classical Lagrange interpolation and would be a suitable selection.展开更多
Urban populations are increasingly exposed to extreme heat due to climate change and rapid urbanization,heightening health risks in cities worldwide.Accurate heat exposure assessment is essential for public health pla...Urban populations are increasingly exposed to extreme heat due to climate change and rapid urbanization,heightening health risks in cities worldwide.Accurate heat exposure assessment is essential for public health planning and risk reduction.Most existing approaches rely on a single threshold temperature(e.g.,35℃of daily max temperature),applied uniformly to the entire population.However,this one-size-fits-all assumption overlooks substantial differences in heat sensitivity across population subgroups.In this study,we address this limitation by quantifying subgroup-specific temperature-mortality relationships and using corresponding minimum mortality temperatures(MMTs)to assess heat exposure.Results show that the population-wide MMT was 27.5℃,but it varied greatly across population subgroups.The elderly population(≥65)had an MMT of 24.6℃,much lower than the 28.6℃observed in younger individuals(<65).Females also exhibited a lower MMT that males(25℃versus 28.2℃).However,educational attainment did not significantly affect MMT.Using a uniform MMT resulted in substantial underestimation of heat exposure,ranging from 25.3%in 1990 to 13.9%in 2020,reflecting demographic shifts over time.Spatially,nearly half of the city experienced underestimated heat risk,especially in central and northeastern regions where heat-vulnerable populations are concentrated.These findings underscore the need for more nuanced heat exposure assessments that account for demographic and spatial variability,paving the way for targeted public health interventions to protect the most vulnerable urban populations.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
AIM:To investigate the sex-specific correlation between systemic factors and retinal neurovascular alterations in individuals with type 1 diabetes mellitus(T1DM)who do not exhibit signs of diabetic retinopathy(DR).MET...AIM:To investigate the sex-specific correlation between systemic factors and retinal neurovascular alterations in individuals with type 1 diabetes mellitus(T1DM)who do not exhibit signs of diabetic retinopathy(DR).METHODS:A cohort participant without DR diagnosed with T1DM,underwent comprehensive ophthalmologic evaluation,optical coherence tomography angiography retinal structural and microvascular density analysis,and systemic parameter assessment.Multiple linear regression analysis was used to investigate the impact of systemic parameters on retinal alterations in distinct gender groups.RESULTS:A total of 182 individuals were included,consisting of 85 males(mean age 23.28±12.75y)and 97 females(mean age 22.98±13.68y).Males exhibited significantly greater thickness in both the internal retinal layer and the entire retina compared to females(P<0.01),whereas females had higher densities of deep retinal vessels and choroidal capillaries(P<0.05).Additionally,glycemic control was found to have a notable influence on retinal thickness in males(P<0.05),while insulin function had a more pronounced impact on retinal structure in females(P<0.01).Furthermore,a significant correlation was observed between thyroid function markers and retinal parameters in both male and female(P<0.05).CONCLUSION:Sex differences in alterations in retinal structure and microcirculation are observed in individuals with T1DM prior to the development of clinical DR,with a noted association between these changes and systemic parameters.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
China's requisition-compensation balance strategy has dramatically reshaped cropland spatial patterns,drawing multidisciplinary research attention.However,existing studies predominantly emphasize horizontal distri...China's requisition-compensation balance strategy has dramatically reshaped cropland spatial patterns,drawing multidisciplinary research attention.However,existing studies predominantly emphasize horizontal distribution,overlooking the significant influence of slope gradient on cropland spatial patterns.This paper proposes a slope location quotient(SLQ)index that reflects the relative advantage of cropland distribution and explores the slope grade difference of cropland spatial patterns in China at the county scale.The analysis adopts 30-m resolution digital elevation model with land cover data,taking 2672 counties with cropland ratio>1%as study units.The temporal scope covers 1990 and 2020,with slope gradients categorized into five grades:0°~2°,2°~6°,6°~15°,15°~25°,and 25°~90°.Results show that:1)The inverse correlation between cropland area and slope gradient remained stable throughout the study period,with the variation in cropland area frequency across slope grades being less than 1%.2)The spatial patterns of SLQ in 1990 and 2020 both transited stepwise with slope gradient,while≤2°and>6°slopes exhibited opposing patterns.3)The mean absolute variation of SLQ during 1990-2020 increased with slope gradient(R2=0.926,p<0.01).Particularly for slope grades>15°,the mean absolute variation reached 0.26(for 15°~25°)and 0.43(for 25°~90°),respectively,and displayed a distinct southward-increasing and northwarddecreasing pattern.This study offers novel slopegradient perspectives for analyzing cropland spatial patterns.To enhance cropland protection benefits,reversing the steep cropland SLQ surge in southern China is recommended.展开更多
In this study,we introduce the sequence space l^(μ)(p,Δ^(m)) with a fractional order μ.Furthermore,we give some topological properties of this space.Also we introduce α-,β-,andγ-duals of l^(μ)(p,Δ^(m)) and its...In this study,we introduce the sequence space l^(μ)(p,Δ^(m)) with a fractional order μ.Furthermore,we give some topological properties of this space.Also we introduce α-,β-,andγ-duals of l^(μ)(p,Δ^(m)) and its some matrix mappings.展开更多
Residential energy-use behavior and energy-saving awareness play a crucial role in sustainable urban energy planning and building energy efficiency,particularly under the pressures of climate change.However,existing s...Residential energy-use behavior and energy-saving awareness play a crucial role in sustainable urban energy planning and building energy efficiency,particularly under the pressures of climate change.However,existing studies often lack comparative analysis of urban-rural differences and tend to focus excessively on behavior patterns while neglecting the dimension of energysaving awareness.With China’s urbanization rate reaching 66.16%,understanding such regional disparities has become increasingly important.To address these research gaps,this study conducts a large-scale survey on space cooling behaviors among residents in Beijing,a representative Chinese megacity.It should be noted that living standards in such megacities are generally higher than the national average,which may shape distinctive energy-use profiles.Analyzing 1573valid samples(1064 urban/442 rural)in 2024,this study employed K-Prototypes and K-Modes clustering to identify typical cooling behavior and energy-saving awareness pattems,followed by Kendall/Chi-square correlation tests and XGBoost importance analysis to determine key influencing factors,with subsequent urban-rural comparative analysis.Results indicate that urban residents are primarily heat-sensitive or heat-tolerant,with a secondary patten of mid-low temperature preference,and generally exhibit long cooling durations;rural behavior is dominated by heat-tolerant type,followed by heat-sensitive,mid-low temperature preference,and never-on types as secondary patterns;both urban and rural areas exhibit energy-savingawareness characterized by low consumption-lowwillingness,though urban areas show marginally higher motivation;energy-saving awareness correlates with cooling behavior in rural areas,but this relationship weakens significantly in urban contexts.展开更多
In this study,a high-confining pressure and real-time large-displacement shearing-flow setup was developed.The test setup can be used to analyze the injection pressure conditions that increase the hydro-shearing perme...In this study,a high-confining pressure and real-time large-displacement shearing-flow setup was developed.The test setup can be used to analyze the injection pressure conditions that increase the hydro-shearing permeability and injection-induced seismicity during hot dry rock geothermal extraction.For optimizing injection strategies and improving engineering safety,real-time permeability,deformation,and energy release characteristics of fractured granite samples driven by injected water pressure under different critical sliding conditions were evaluated.The results indicated that:(1)A low injection water pressure induced intermittent small-deformation stick-slip behavior in fractures,and a high injection pressure primarily caused continuous high-speed large-deformation sliding in fractures.The optimal injection water pressure range was defined for enhancing hydraulic shear permeability and preventing large injection-induced earthquakes.(2)Under the same experimental conditions,fracture sliding was deemed as the major factor that enhanced the hydraulic shear-permeability enhancement and the maximum permeability increased by 36.54 and 41.59 times,respectively,in above two slip modes.(3)Based on the real-time transient evolution of water pressure during fracture sliding,the variation coefficients of slip rate,permeability,and water pressure were fitted,and the results were different from those measured under quasi-static conditions.(4)The maximum and minimum shear strength criteria for injection-induced fracture sliding were also determined(μ=0.6665 andμ=0.1645,respectively,μis friction coefficient).Using the 3D(three-dimensional)fracture surface scanning technology,the weakening effect of injection pressure on fracture surface damage characteristics was determined,which provided evidence for the geological markers of fault sliding mode and sliding nature transitions under the fluid influence.展开更多
This paper introduces a real-time high precision measurement of phase difference based on Field Programmable Gate Array（FPGA） technology,which has been successfully applied to laser grating interference measurement ...This paper introduces a real-time high precision measurement of phase difference based on Field Programmable Gate Array（FPGA） technology,which has been successfully applied to laser grating interference measurement and real-time feedback of plasma electron density in HL-2A tokamak.It can track the changes of electron density while setting the starting point of the density curve to zero.In a laboratory test,the measuring accuracy of phase difference is less than 0.1°,the time resolution is 80 ns,and the feedback delay is 180 μs.展开更多
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Supported by the National Natural Science Foundation of China(Grant No.11661043)and the ScienceTechnology Research Project of Jiangxi Provincial Department of Education(Grant No.GJJ2200320).
文摘In this paper,the growth characteristic of meromorphic solutions for the following difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=0 with no dominating coefficient is studied.By imposing certain restriction on the entire coefficients associated with Petrenko's deviation of the above equation,we obtain some results and partially address a question posed byⅠ.Laine and C.C.Yang.Furthermore,for the entire solutions f(z)of the difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=F(z),where Aj(z)(j=0,…,n),F(z)are entire functions,we discover a close relationship between the measure of common transcendental directions associated with classical difference operators of f(z)and Petrenko's deviations of the coefficients.
基金supported by the National Natural Science Foundation of China 62402171.
文摘As a fundamental component in computer vision,edges can be categorized into four types based on discontinuities in reflectance,illumination,surface normal,or depth.While deep CNNs have significantly advanced generic edge detection,real-time multi-class semantic edge detection under resource constraints remains challenging.To address this,we propose a lightweight framework based on PiDiNet that enables fine-grained semantic edge detection.Our model simultaneously predicts background and four edge categories from full-resolution inputs,balancing accuracy and efficiency.Key contributions include:a multi-channel output structure expanding binary edge prediction to five classes,supported by a deep supervision mechanism;a dynamic class-balancing strategy combining adaptive weighting with physical priors to handle extreme class imbalance;and maintained architectural efficiency enabling real-time inference.Extensive evaluations on BSDS-RIND show our approach achieves accuracy competitive with state-of-the-art methods while operating in real time.
基金Supported by the National Program on Key Basic Research Project(2020YFA0713600)the National Natural Science Foundation of China(62272214)。
文摘In the era of the Internet of Things,distributed computing alleviates the problem of insufficient terminal computing power by integrating idle resources of heterogeneous devices.However,the imbalance between task execution delay and node energy consumption,and the scheduling and adaptation challenges brought about by device heterogeneity,urgently need to be addressed.To tackle this problem,this paper constructs a multi-objective real-time task scheduling model that considers task real-time performance,execution delay,system energy consumption,and node interests.The model aims to minimize the delay upper bound and total energy consumption while maximizing system satisfaction.A real-time task scheduling algorithm based on bilateral matching game is proposed.By designing a bidirectional preference mechanism between tasks and computing nodes,combined with a multi-round stable matching strategy,accurate matching between tasks and nodes is achieved.Simulation results show that compared with the baseline scheme,the proposed algorithm significantly reduces the total execution cost,effectively balances the task execution delay and the energy consumption of compute nodes,and takes into account the interests of each network compute node.
基金provided by the National Key Research and Development Program of China(No.2021YFB3401700)the National Natural Science Foundation of China(Nos.12302189 and 12220101002)the Shaanxi Provincial Key Science and Technology Innovation Team,China(No.2023-CX-TD-14)。
文摘An integrated real-time control methodology is introduced to mitigate process-induced challenges,namely temperature overshoot,uneven cure,and interfacial shear stress,during the autoclave curing of Carbon Fiber-Reinforced Polymer(CFRP)composites.First,a high-fidelity Finite Element(FE)model incorporating tool-part interaction is developed to reveal the curing process of the composites,wherein the interaction is characterized by friction interface modeling with experimentally measured cure-dependent friction coefficients.The accuracy of FE model is confirmed through experimental tests on a doubly curved T-stiffened composite panel.This validated model then generates a dataset of curing temperature profile and associated defect information,which is used to train a customized Long Short-Term Memory(LSTM)neural network.We culminate in a real-time control framework that actively optimizes the curing process by integrating LSTM-based state prediction with Q-learning-driven decision logic.The optimized thermal profile demonstrates a clear performance enhancement over the traditional multi-dwell approach,achieving marked reductions in temperature difference,Degree of Cure(DoC)difference and tool-part interface shear stress,which provides more insights for intelligent composite manufacturing.
基金National Natural Science Foundation of China,Grant/Award Number:52104120Hunan Provincial Key Laboratory of Key Technology on Hydropower Development,Grant/Award Number:PKLHD202303。
文摘During geothermal resource exploitation,the potential deterioration of mechanical properties in high-temperature granite subjected to cooling poses a significant safety concern.To address this,the present study investigates the coupled thermo-mechanical behavior of granite during heating and cooling through a combination of laboratory tests and finite difference method analysis.Initial investigations involve X-ray diffraction,thermal expansion test,thermogravimetric analysis,and uniaxial compression test.Results show the significant variations of granite properties under different thermal conditions,attributed to temperature gradients,water evaporation,and mineral phase transitions.Subsequently,a model considering temperature-dependent parameters and real-time cooling rates was employed to simulate linear heating and nonlinear cooling processes.Simulation results indicate that the thermal cracking predominantly occurs during the heating stage,with tensile failure as the primary mode.Additionally,a faster real-time cooling rate at higher temperatures intensifies the thermal cracking behavior in granite.This study effectively elucidates the thermomechanical coupling behavior of granite during heating and cooling processes,providing insights into the mechanisms of mechanical property changes with rising or decreasing temperatures.
基金supported by Jiangxi Polytechnic Institute Key Research Topics in Educational Reform 2025-JGJG-07.
文摘The intelligent environmental sensing systems are quickly transforming the sparse and retrospective monitoring to dense and decision-oriented environmental intelligence.This review brings together the manner in which integration of Internet of Things(IoT)sensing,edge computing,and real-time analytics facilitates timely detection,interpretation,and prediction of the environmental conditions across the applications,such as urban air quality,watershed and coastal surveillance,industrial safety,agriculture,and disaster response.We define end-to-end architectural patterns to organize devices,edge nodes,and cloud services to satisfy latency,reliability,bandwidth,and governance constraints with emphasis on event-time processing,adaptive offloading,and hierarchical aggregation.Then we look at sensing and infrastructure foundations,emphasizing the effects of sensor modality and power autonomy,connectivity,and the practices of calibration on the practicable analytics and eventual plausibility.It is on this basis that we examine real-time analytics pipelines and Artificial Intelligence(AI)techniques to preprocess,sensor combine,anomaly detect,and short-horizon forecast,with a focus on edge-deployable models,quantification of uncertainties,and query resistance to drift and domain shift.Lastly,we address the realities of deployment that condition operational success,such as lifecycle engineering,provenance-aware data management,security and privacy risks,ethical governance,and evaluation methodologies,which place end-to-end latency and field generalization as a priority.This review offers cohesion to algorithmic capabilities and systems engineering and governance to define an overall framework,show open areas of research directions,and provide practical recommendations on how to design trustworthy,scalable,and sustainable environmental monitoring systems.
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 Foundation of State Key Laboratory of Aerodynamics of China(No.SKLA-2024-KFKT-1-008)the National Natural Science Foundation of China(No.91952203)。
文摘This paper presents an efficient and automated Overset Grid Assembly(OGA)method for the structured grid,and investigates high-order interpolation methods for inter-grid boundaries with the cell-centered finite difference method.Four enhancements are introduced:a hybrid holecutting approach integrates the efficiency of approximate hole-cutting and the accuracy and robustness of direct-cutting,effectively addressing challenges such as small gaps and thin cuts;an improved implicit hole boundary optimization method,incorporating quality comparison,can significantly reduce donor search workloads;an improved implicit interpolation cell cancellation algorithm minimizes overlap regions,particularly beneficial for high-order interpolation with large stencils;an algorithm for identifying and eliminating islands without using wall distances,effectively removes islands.The OGA results of a multi-element airfoil,a circular array of cylinders,multiple spheres,and a wing-pylon-store configuration indicate that the proposed method would be a suitable selection for multi-body problems,even in the presence of small gaps and thin geometries.Additionally,for high-order interpolation at inter-grid boundaries,this study presents an optimized interpolation method designed to minimize spectral property errors.Numerical results indicate that for periodic problems frequently crossing inter-grid boundaries,the optimized interpolation is more accurate than classical Lagrange interpolation and would be a suitable selection.
基金supported by the National Natural Science Foundation of China(Grant No.42225104)CAS Project for Young Scientists in Basic Research(Grant No.YSBR-086).
文摘Urban populations are increasingly exposed to extreme heat due to climate change and rapid urbanization,heightening health risks in cities worldwide.Accurate heat exposure assessment is essential for public health planning and risk reduction.Most existing approaches rely on a single threshold temperature(e.g.,35℃of daily max temperature),applied uniformly to the entire population.However,this one-size-fits-all assumption overlooks substantial differences in heat sensitivity across population subgroups.In this study,we address this limitation by quantifying subgroup-specific temperature-mortality relationships and using corresponding minimum mortality temperatures(MMTs)to assess heat exposure.Results show that the population-wide MMT was 27.5℃,but it varied greatly across population subgroups.The elderly population(≥65)had an MMT of 24.6℃,much lower than the 28.6℃observed in younger individuals(<65).Females also exhibited a lower MMT that males(25℃versus 28.2℃).However,educational attainment did not significantly affect MMT.Using a uniform MMT resulted in substantial underestimation of heat exposure,ranging from 25.3%in 1990 to 13.9%in 2020,reflecting demographic shifts over time.Spatially,nearly half of the city experienced underestimated heat risk,especially in central and northeastern regions where heat-vulnerable populations are concentrated.These findings underscore the need for more nuanced heat exposure assessments that account for demographic and spatial variability,paving the way for targeted public health interventions to protect the most vulnerable urban populations.
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Supported by Natural Science Foundation of Hunan Province(No.2023JJ70017No.2025JJ50627)Peak Climbing Project of Optometry Hospital Affiliated to Wenzhou Medical University。
文摘AIM:To investigate the sex-specific correlation between systemic factors and retinal neurovascular alterations in individuals with type 1 diabetes mellitus(T1DM)who do not exhibit signs of diabetic retinopathy(DR).METHODS:A cohort participant without DR diagnosed with T1DM,underwent comprehensive ophthalmologic evaluation,optical coherence tomography angiography retinal structural and microvascular density analysis,and systemic parameter assessment.Multiple linear regression analysis was used to investigate the impact of systemic parameters on retinal alterations in distinct gender groups.RESULTS:A total of 182 individuals were included,consisting of 85 males(mean age 23.28±12.75y)and 97 females(mean age 22.98±13.68y).Males exhibited significantly greater thickness in both the internal retinal layer and the entire retina compared to females(P<0.01),whereas females had higher densities of deep retinal vessels and choroidal capillaries(P<0.05).Additionally,glycemic control was found to have a notable influence on retinal thickness in males(P<0.05),while insulin function had a more pronounced impact on retinal structure in females(P<0.01).Furthermore,a significant correlation was observed between thyroid function markers and retinal parameters in both male and female(P<0.05).CONCLUSION:Sex differences in alterations in retinal structure and microcirculation are observed in individuals with T1DM prior to the development of clinical DR,with a noted association between these changes and systemic parameters.
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.
基金supported by the project of the National Natural Science Foundation of China entitled“Distribution and change characteristics of construction land on slope gradient in mountainous cities of southern China”(No.41961039)。
文摘China's requisition-compensation balance strategy has dramatically reshaped cropland spatial patterns,drawing multidisciplinary research attention.However,existing studies predominantly emphasize horizontal distribution,overlooking the significant influence of slope gradient on cropland spatial patterns.This paper proposes a slope location quotient(SLQ)index that reflects the relative advantage of cropland distribution and explores the slope grade difference of cropland spatial patterns in China at the county scale.The analysis adopts 30-m resolution digital elevation model with land cover data,taking 2672 counties with cropland ratio>1%as study units.The temporal scope covers 1990 and 2020,with slope gradients categorized into five grades:0°~2°,2°~6°,6°~15°,15°~25°,and 25°~90°.Results show that:1)The inverse correlation between cropland area and slope gradient remained stable throughout the study period,with the variation in cropland area frequency across slope grades being less than 1%.2)The spatial patterns of SLQ in 1990 and 2020 both transited stepwise with slope gradient,while≤2°and>6°slopes exhibited opposing patterns.3)The mean absolute variation of SLQ during 1990-2020 increased with slope gradient(R2=0.926,p<0.01).Particularly for slope grades>15°,the mean absolute variation reached 0.26(for 15°~25°)and 0.43(for 25°~90°),respectively,and displayed a distinct southward-increasing and northwarddecreasing pattern.This study offers novel slopegradient perspectives for analyzing cropland spatial patterns.To enhance cropland protection benefits,reversing the steep cropland SLQ surge in southern China is recommended.
文摘In this study,we introduce the sequence space l^(μ)(p,Δ^(m)) with a fractional order μ.Furthermore,we give some topological properties of this space.Also we introduce α-,β-,andγ-duals of l^(μ)(p,Δ^(m)) and its some matrix mappings.
文摘Residential energy-use behavior and energy-saving awareness play a crucial role in sustainable urban energy planning and building energy efficiency,particularly under the pressures of climate change.However,existing studies often lack comparative analysis of urban-rural differences and tend to focus excessively on behavior patterns while neglecting the dimension of energysaving awareness.With China’s urbanization rate reaching 66.16%,understanding such regional disparities has become increasingly important.To address these research gaps,this study conducts a large-scale survey on space cooling behaviors among residents in Beijing,a representative Chinese megacity.It should be noted that living standards in such megacities are generally higher than the national average,which may shape distinctive energy-use profiles.Analyzing 1573valid samples(1064 urban/442 rural)in 2024,this study employed K-Prototypes and K-Modes clustering to identify typical cooling behavior and energy-saving awareness pattems,followed by Kendall/Chi-square correlation tests and XGBoost importance analysis to determine key influencing factors,with subsequent urban-rural comparative analysis.Results indicate that urban residents are primarily heat-sensitive or heat-tolerant,with a secondary patten of mid-low temperature preference,and generally exhibit long cooling durations;rural behavior is dominated by heat-tolerant type,followed by heat-sensitive,mid-low temperature preference,and never-on types as secondary patterns;both urban and rural areas exhibit energy-savingawareness characterized by low consumption-lowwillingness,though urban areas show marginally higher motivation;energy-saving awareness correlates with cooling behavior in rural areas,but this relationship weakens significantly in urban contexts.
基金supported by the National Natural Science Foundation of China (Grant No.52122405)Science and Technology Major Project of Shanxi Province,China (Grant No.202101060301024)Science and Technology Major Project of Xizang Autonomous Region,China (Grant No.XZ202201ZD0004G0204).
文摘In this study,a high-confining pressure and real-time large-displacement shearing-flow setup was developed.The test setup can be used to analyze the injection pressure conditions that increase the hydro-shearing permeability and injection-induced seismicity during hot dry rock geothermal extraction.For optimizing injection strategies and improving engineering safety,real-time permeability,deformation,and energy release characteristics of fractured granite samples driven by injected water pressure under different critical sliding conditions were evaluated.The results indicated that:(1)A low injection water pressure induced intermittent small-deformation stick-slip behavior in fractures,and a high injection pressure primarily caused continuous high-speed large-deformation sliding in fractures.The optimal injection water pressure range was defined for enhancing hydraulic shear permeability and preventing large injection-induced earthquakes.(2)Under the same experimental conditions,fracture sliding was deemed as the major factor that enhanced the hydraulic shear-permeability enhancement and the maximum permeability increased by 36.54 and 41.59 times,respectively,in above two slip modes.(3)Based on the real-time transient evolution of water pressure during fracture sliding,the variation coefficients of slip rate,permeability,and water pressure were fitted,and the results were different from those measured under quasi-static conditions.(4)The maximum and minimum shear strength criteria for injection-induced fracture sliding were also determined(μ=0.6665 andμ=0.1645,respectively,μis friction coefficient).Using the 3D(three-dimensional)fracture surface scanning technology,the weakening effect of injection pressure on fracture surface damage characteristics was determined,which provided evidence for the geological markers of fault sliding mode and sliding nature transitions under the fluid influence.
基金supported by National Natural Science Foundation of China(Nos.11375195,11075048)the National Magnetic Confinement Fusion Science Program of China(No.2013GB104003)
文摘This paper introduces a real-time high precision measurement of phase difference based on Field Programmable Gate Array（FPGA） technology,which has been successfully applied to laser grating interference measurement and real-time feedback of plasma electron density in HL-2A tokamak.It can track the changes of electron density while setting the starting point of the density curve to zero.In a laboratory test,the measuring accuracy of phase difference is less than 0.1°,the time resolution is 80 ns,and the feedback delay is 180 μs.
