A new scheme of super-resolution optical fluctuation imaging(SOFI)is proposed to broaden its application in the high-order cumulant reconstruction by optimizing blinking characteristics,eliminating noise in raw data a...A new scheme of super-resolution optical fluctuation imaging(SOFI)is proposed to broaden its application in the high-order cumulant reconstruction by optimizing blinking characteristics,eliminating noise in raw data and applying multi-resolution analysis in cumulant reconstruction.A motor-driven rotating mask optical modulation system is designed to adjust the excitation lightfield and allows for fast deployment.Active-modulated fluorescence fluctuation superresolution microscopy with multi-resolution analysis(AMF-MRA-SOFI)demonstrates enhanced resolution ability and reconstruction quality in experiments performed on sample of conventional dyes,achieving a resolution of 100 nm in the fourth order compared to conventional SOFI reconstruction.Furthermore,our approach combining expansion super-resolution achieved a resolution at-57 nm.展开更多
In this paper, we design high-order Runge-Kutta discontinuous Galerkin (RKDG) methods with multi-resolution weighted essentially non-oscillatory (multi-resolution WENO) limiters to compute compressible steady-state pr...In this paper, we design high-order Runge-Kutta discontinuous Galerkin (RKDG) methods with multi-resolution weighted essentially non-oscillatory (multi-resolution WENO) limiters to compute compressible steady-state problems on triangular meshes. A troubled cell indicator extended from structured meshes to unstructured meshes is constructed to identify triangular cells in which the application of the limiting procedures is required. In such troubled cells, the multi-resolution WENO limiting methods are used to the hierarchical L^(2) projection polynomial sequence of the DG solution. Through using the RKDG methods with multi-resolution WENO limiters, the optimal high-order accuracy can be gradually reduced to first-order in the triangular troubled cells, so that the shock wave oscillations can be well suppressed. In steady-state simulations on triangular meshes, the numerical residual converges to near machine zero. The proposed spatial reconstruction methods enhance the robustness of classical DG methods on triangular meshes. The good results of these RKDG methods with multi-resolution WENO limiters are verified by a series of two-dimensional steady-state problems.展开更多
In this study,a wavelet multi-resolution interpolation Galerkin method(WMIGM)is proposed to solve linear singularly perturbed boundary value problems.Unlike conventional wavelet schemes,the proposed algorithm can be r...In this study,a wavelet multi-resolution interpolation Galerkin method(WMIGM)is proposed to solve linear singularly perturbed boundary value problems.Unlike conventional wavelet schemes,the proposed algorithm can be readily extended to special node generation techniques,such as the Shishkin node.Such a wavelet method allows a high degree of local refinement of the nodal distribution to efficiently capture localized steep gradients.All the shape functions possess the Kronecker delta property,making the imposition of boundary conditions as easy as that in the finite element method.Four numerical examples are studied to demonstrate the validity and accuracy of the proposedwavelet method.The results showthat the use ofmodified Shishkin nodes can significantly reduce numerical oscillation near the boundary layer.Compared with many other methods,the proposed method possesses satisfactory accuracy and efficiency.The theoretical and numerical results demonstrate that the order of theε-uniform convergence of this wavelet method can reach 5.展开更多
The basic theory of YOLO series object detection algorithms is discussed, the dangerous driving behavior dataset is collected and produced, and then the YOLOv7 network is introduced in detail, the deep separable convo...The basic theory of YOLO series object detection algorithms is discussed, the dangerous driving behavior dataset is collected and produced, and then the YOLOv7 network is introduced in detail, the deep separable convolution and CA attention mechanism are introduced, the YOLOv7 bounding box loss function and clustering algorithm are optimized, and the DB-YOLOv7 network structure is constructed. In the first stage of the experiment, the PASCAL VOC public dataset was utilized for pre-training. A comparative analysis was conducted to assess the recognition accuracy and inference time before and after the proposed improvements. The experimental results demonstrated an increase of 1.4% in the average recognition accuracy, alongside a reduction in the inference time by 4 ms. Subsequently, a model for the recognition of dangerous driving behaviors was trained using a specialized dangerous driving behavior dataset. A series of experiments were performed to evaluate the efficacy of the DB-YOLOv7 algorithm in this context. The findings indicate a significant enhancement in detection performance, with a 4% improvement in accuracy compared to the baseline network. Furthermore, the model’s inference time was reduced by 20%, from 25 ms to 20 ms. These results substantiate the effectiveness of the DB-YOLOv7 recognition algorithm for detecting dangerous driving behaviors, providing comprehensive validation of its practical applicability.展开更多
Model predictive control(MPC)has been deemed as an attractive control method in motor drives by virtue of its simple structure,convenient multi-objective optimization,and satisfactory dynamic performance.However,the s...Model predictive control(MPC)has been deemed as an attractive control method in motor drives by virtue of its simple structure,convenient multi-objective optimization,and satisfactory dynamic performance.However,the strong reliance on mathematical models seriously restrains its practical application.Therefore,improving the robustness of MPC has attained significant attentions in the last two decades,followed by which,model-free predictive control(MFPC)comes into existence.This article aims to reveal the current state of MFPC strategies for motor drives and give the categorization from the perspective of implementation.Based on this review,the principles of the reported MFPC strategies are introduced in detail,as well as the challenges encountered in technology realization.In addition,some of typical and important concepts are experimentally validated via case studies to evaluate the performance and highlight their features.Finally,the future trends of MFPC are discussed based on the current state and reported developments.展开更多
This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in China’s Yangtze River Delta region(YRD)from 2008 to 2020.Utilizing data fr...This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in China’s Yangtze River Delta region(YRD)from 2008 to 2020.Utilizing data from the Infrared Atmospheric Sounding Interfer-ometer(IASI),Generalized Additive Models(GAM),and the GEOS-Chem chemical transport model,we observed a significant increase of NH_(3)VCDs in the YRD between 2014 and 2020.The spatial distribution analysis revealed higher NH_(3)concentrations in the northern part of the YRD region,primarily due to lower precipitation,alkaline soil,and intensive agricul-tural activities.NH_(3)VCDs in the YRD region increased significantly(65.18%)from 2008 to 2020.The highest growth rate occurs in the summer,with an annual average growth rate of 7.2%during the period from 2014 to 2020.Agricultural emissions dominated NH_(3)VCDs during spring and summer,with high concentrations primarily located in the agricultural areas adjacent to densely populated urban zones.Regions within several large urban areas have been discovered to exhibit relatively stable variations in NH_(3)VCDs.The rise in NH_(3)VCDs within the YRD region was primarily driven by the reduction of acidic gases like SO_(2),as emphasized by GAM modeling and sensitivity tests using the GEOS-Chem model.The concentration changes of acidic gases contribute to over 80%of the interannual variations in NH_(3)VCDs.This emphasizes the crucial role of environmental policies targeting the reduction of these acidic gases.Effective emission control is urgent tomitigate environmental hazards and secondary particulate matter,especially in the northern YRD.展开更多
Permanent magnet synchronous motor based electro-mechanical actuation servo drives have widespread applications in the aviation field,such as unmanned aerial vehicle electric servos,electric cabin doors,and mechanical...Permanent magnet synchronous motor based electro-mechanical actuation servo drives have widespread applications in the aviation field,such as unmanned aerial vehicle electric servos,electric cabin doors,and mechanical arms.The performance of the servo drive,which encompasses the response to the torque,efficiency,control bandwidth and the steady-state positioning accuracy,significantly influences the performance of the aviation actuation.Consequently,enhancing the control bandwidth and refining the positioning accuracy of aviation electro-mechanical actuation servo drives have emerged as a focal point of research.This paper investigates the multi-source disturbances present in aviation electro-mechanical actuation servo systems and summarizes recent research on high-performance servo control methods based on active disturbance rejection control(ADRC).We present a comprehensive overview of the research status pertaining to servo control architecture,strategies for suppressing disturbances in the current loop,and ADRC-based strategies for the position loop.We delineate the research challenges and difficulties encountered by aviation electro-mechanical actuation servo drive control technology.展开更多
Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoti...Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoting high-quality development of new energy in China.This paper constructs an evaluation index system for the development of NEVs and the ecological environment.It uses game theory combining weighting model,particle swarm optimized projection tracking evaluation model,coupling coordination degree model,and machine learning algorithms to calculate and analyze the level of coupling coordination development of NEVs and the ecological environment in China from 2010 to 2021,and identifies the driving factors.The research results show that:(i)From 2010 to 2021,the development index of NEVs in China has steadily increased from 0.085 to 0.634,while the ecological environment level index significantly rose from 0.170 to 0.884,reflecting the continuous development of China in both NEVs and the ecological environment.(ii)From 2010 to 2012,the two systems—new energy vehicle(NEV)development and the ecological environment—were in a period of imbalance and decline.From 2013 to 2016,they underwent a transition period,and from 2017 to 2021,they entered a period of coordinated development showing a trend of benign and continuous improvement.By 2021,they reached a good level of coordination.(iii)Indicators such as the number of patents granted for NEVs,water consumption per unit of GDP,and energy consumption per unit of GDP are the main driving factors affecting the coupling coordination development of NEVs and the ecological environment in China.展开更多
Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and ev...Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.展开更多
The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ec...The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth.展开更多
Trajectory prediction is a critical task in autonomous driving systems.It enables vehicles to anticipate the future movements of surrounding traffic participants,which facilitates safe and human-like decision-making i...Trajectory prediction is a critical task in autonomous driving systems.It enables vehicles to anticipate the future movements of surrounding traffic participants,which facilitates safe and human-like decision-making in the planning and control layers.However,most existing approaches rely on end-to-end deep learning architectures that overlook the influence of driving style on trajectory prediction.These methods often lack explicit modeling of semantic driving behavior and effective interaction mechanisms,leading to potentially unrealistic predictions.To address these limitations,we propose the Driving Style Guided Trajectory Prediction framework(DSG-TP),which incorporates a probabilistic representation of driving style into trajectory prediction.Our approach enhances the model’s ability to interact with vehicle behavior characteristics in complex traffic scenarios,significantly improving prediction reliability in critical decision-making situations by incorporating the driving style recognition module.Experimental evaluations on the Argoverse 1 dataset demonstrate that our method outperforms existing approaches in both prediction accuracy and computational efficiency.Through extensive ablation studies,we further validate the contribution of each module to overall performance.Notably,in decision-sensitive scenarios,DSG-TP more accurately captures vehicle behavior patterns and generates trajectory predictions that align with different driving styles,providing crucial support for safe decision-making in autonomous driving systems.展开更多
BACKGROUND Return to work(RTW)and resumption of driving(ROD)are critical factors that influence postoperative quality of life in patients undergoing total hip arthroplasty(THA).However,few studies have focused on the ...BACKGROUND Return to work(RTW)and resumption of driving(ROD)are critical factors that influence postoperative quality of life in patients undergoing total hip arthroplasty(THA).However,few studies have focused on the minimally invasive(MIS)approach and its effect on these outcomes.AIM To investigate RTW and ROD's timelines and influencing factors following anterior MIS-THA.METHODS A retrospective analysis was conducted on 124 patients who underwent anterior MIS-THA.Data on the demographics,occupational physical demands,and RTW/ROD timelines were also collected.Clinical outcomes were measured using standardised scoring systems.Statistical analyses were performed to evaluate the differences between the groups based on employment status and physical workload.RESULTS Among employed patients,the RTW rate was 94.7%,with an average return time of five weeks.The average ROD time was 3.5 weeks across all patients.Despite similar postoperative clinical scores,RTW time was significantly influenced by occupations'physical workload,with heavier physical demands associated with delayed RTW.CONCLUSION Anterior MIS-THA facilitates early RTW and ROD,particularly in occupations with lower physical demands.These findings highlight the importance of considering occupational and physical workload in postoperative care planning to optimize recovery outcomes.展开更多
From AI-powered chatbots capable of deep reasoning to humanoid robots equipped with intelligent“brains”for complex services,technological advancements continue to astonish us at an unprecedented pace.The rapid devel...From AI-powered chatbots capable of deep reasoning to humanoid robots equipped with intelligent“brains”for complex services,technological advancements continue to astonish us at an unprecedented pace.The rapid development of artificial intelligence(AI)is reshaping industries,enhancing productivity,and offering new possibilities for an intelligent life.展开更多
As one of the three key drivers of economic growth,export has been playing an important and positive role in the Chinese economy.According to the National Bureau of Statistics and World Bank,China’s gross domestic pr...As one of the three key drivers of economic growth,export has been playing an important and positive role in the Chinese economy.According to the National Bureau of Statistics and World Bank,China’s gross domestic product(GDP)in 2004 was US$1.96 trillion,with a total export of US$593.4 billion,accounting for 30.3 percent of GDP.Across the following 20 years,the share of export in GDP gradually declined to 24.47 percent in 2014 and 18.87 percent in 2024.But a look at China’s share of the global export market shows a continuing upward trend,and China’s position as the largest trading nation in goods has also become more secure.展开更多
Sine-wave drive and square-wave drive are two common motor control strategies.This study constructs a mathematical model capable of predicting the distribution of electromagnetic force waves in synchronous reluctance ...Sine-wave drive and square-wave drive are two common motor control strategies.This study constructs a mathematical model capable of predicting the distribution of electromagnetic force waves in synchronous reluctance motors(SynRMs)under these two drive methods,and comparatively analyzes the vibration phenomena induced by electromagnetic forces under different drive methods.It aims to provide an effective tool for predicting the distribution of electromagnetic force waves in SynRMs,while exploring the influence of drive modes on their vibration characteristics.The study focuses on a 4-pole,36-slot 5.5 kW SynRM.Based on the magnetomotive force(MMF)-permeance method,incorporating the special rotor structure and the characteristics of current harmonics under square-wave drive,an air-gap flux distribution function is established.Meanwhile,Maxwell’s stress tensor method is adopted to analyze how the air-gap flux density relates to electromagnetic excitation force waves.Subsequently,this analysis is applied to forecast the spatiotemporal distribution features of radial electromagnetic force waves.Finite element simulations are conducted to compute the modal and vibration responses of the SynRM,followed by a comparative analysis of the vibration characteristics under the two drive methods.Additionally,a 6-pole,36-slot SynRM is used for additional comparative verification.Ultimately,the effectiveness of the simulation results is verified through experiments.展开更多
Amid ongoing global environmental change and the critical pursuit of sustainable development,human-environment systems are exhibiting increasingly complex dynamic evolutions and spatial relationships,underscoring an u...Amid ongoing global environmental change and the critical pursuit of sustainable development,human-environment systems are exhibiting increasingly complex dynamic evolutions and spatial relationships,underscoring an urgent need for innovative research frameworks.Integrated geography synthesizes physical geography,human geography,and geographic information science,providing key frameworks for understanding complex human-environment systems.This editorial proposes an emerging research framework for integrated geography—“Composite driving-System evolution-Coupling mechanism-Synergistic regulation(CSCS)”—based on key issues such as climate change,biodiversity loss,resource scarcity,and social-ecological interactions,which have been highlighted in both recent critical literature on human-environment systems and UN assessment reports.The framework starts with diverse composite driving forces,extends to the evolution of human-environment system structures,processes,and functions that these drivers induce,explores couplings within human-environment systems,and calls for regulation aimed at sustainable development in synergies.Major research frontiers include understanding the cascading“evolution-coupling”effects of shocks;measuring system resilience,thresholds,and safe and just operating space boundaries;clarifying linkage mechanisms across scales;and achieving synergistic outcomes for multi-objective sustainability.This framework will help promote the interdisciplinary integration and development of integrated geography,and provide geographical solutions for the global sustainable development agenda.展开更多
Abnormal driving behavior includes driving distraction,fatigue,road anger,phone use,and an exceptionally happy mood.Detecting abnormal driving behavior in advance can avoid traffic accidents and reduce the risk of tra...Abnormal driving behavior includes driving distraction,fatigue,road anger,phone use,and an exceptionally happy mood.Detecting abnormal driving behavior in advance can avoid traffic accidents and reduce the risk of traffic conflicts.Traditional methods of detecting abnormal driving behavior include using wearable devices to monitor blood pressure,pulse,heart rate,blood oxygen,and other vital signs,and using eye trackers to monitor eye activity(such as eye closure,blinking frequency,etc.)to estimate whether the driver is excited,anxious,or distracted.Traditional monitoring methods can detect abnormal driving behavior to a certain extent,but they will affect the driver’s normal driving state,thereby introducing additional driving risks.This research uses the combined method of support vector machine and dlib algorithm to extract 68 facial feature points from the human face,and uses an SVM model as a strong classifier to classify different abnormal driving statuses.The combined method reaches high accuracy in detecting road anger and fatigue status and can be used in an intelligent vehicle cabin to improve the driving safety level.展开更多
Stimulated Raman scattering(SRS)under a new ignition path that combines the advantages of direct-drive(DD)and indirect-drive(ID)schemes is investigated experimentally at the Shenguang-100 kJ facility.The results show ...Stimulated Raman scattering(SRS)under a new ignition path that combines the advantages of direct-drive(DD)and indirect-drive(ID)schemes is investigated experimentally at the Shenguang-100 kJ facility.The results show that collective SRS in the plasma produced by ablating a polyimide film is detected for the ID beams,but is suppressed by adding a toe before the main pulse of the ID beams.The toe also strongly influences SRS of both the ID and DD beams excited in the plasma generated in the hohlraum.When a toe is used,the SRS spectra of the DD beams show that SRS tends to be excited in lower plasma density,which will result in a lower risk of super-hot electrons.Measurements of hot electrons support this conclusion.This research will help us produce a better pulse design for this new ignition path.展开更多
This paper introduces autonomous driving image perception technology,including deep learning models(such as CNN and RNN)and their applications,analyzing the limitations of traditional algorithms.It elaborates on the s...This paper introduces autonomous driving image perception technology,including deep learning models(such as CNN and RNN)and their applications,analyzing the limitations of traditional algorithms.It elaborates on the shortcomings of Faster R-CNN and YOLO series models,proposes various improvement techniques such as data fusion,attention mechanisms,and model compression,and introduces relevant datasets,evaluation metrics,and testing frameworks to demonstrate the advantages of the improved models.展开更多
This study analyzes the spatiotemporal patterns and driving factors of forest fires in Liangshan Prefecture based on fire data from 2016 to 2024 using statistical methods.The results indicate:1)From 2016 to 2024,fores...This study analyzes the spatiotemporal patterns and driving factors of forest fires in Liangshan Prefecture based on fire data from 2016 to 2024 using statistical methods.The results indicate:1)From 2016 to 2024,forest fires in Liangshan Prefecture occurred predominantly between January and May(140 incidents),accounting for 97.90%of the total.March recorded the highest number of fires(48 incidents),representing 33.57%.Within a 24-hour period,113 fires occurred between 12:00 PM and 9:00 PM,constituting 79.02%of all incidents.2)Spatially,Mianning County recorded the highest number of forest fires(28 incidents,19.58%),followed by Xichang,Muli,and Yanyuan with 22,23,and 20 incidents,respectively.Human activities,particularly agricultural burning,outdoor smoking,and other causes,were the dominant factors,collectively accounting for 41%of incidents.3)Forest fires predominantly occurred at elevations between 1500 and 3000 meters(132 fires,92.31%),on slopes with gradients of 5-25 degrees(81 fires,56.65%),on west-facing aspects(northwest,west,southwest)(72 fires,53.14%),in areas with NDVI values between 0.51 and 0.8(79 incidents,55.24%),within 500-2000 m residential buffer zones(151 incidents,98.60%),and within 500 m road buffer zones(103 incidents,72.03%).4)Among meteorological factors,the 20-day average temperature(0.3041),80-day maximum temperature(0.3487),20-day minimum temperature(0.2594),20-day minimum relative humidity(−0.3132),70-day maximum wind speed(0.1885),and 70-day peak wind speed(0.1965)showed the strongest correlations with forest fire burned area.Burned area also exhibited a positive correlation with the Meteorological Drought Index(MCI)on the day of the fire(0.1990).This study confirms the lagged and persistent effects of meteorological factors on forest fire occurrence,providing key scientific evidence for constructing regional fire prediction models that integrate multi-scale meteorological indicators.展开更多
基金supported by the National Natural Science Foundation of China(62175034,62175036,32271510)the National Key R&D Program of China(2021YFF0502900)+2 种基金the Science and Technology Research Program of Shanghai(Grant No.19DZ2282100)the Shanghai Key Laboratory of Metasurfaces for Light Manipulation(23dz2260100)the Shanghai Engineering Technology Research Center of Hair Medicine(19DZ2250500).
文摘A new scheme of super-resolution optical fluctuation imaging(SOFI)is proposed to broaden its application in the high-order cumulant reconstruction by optimizing blinking characteristics,eliminating noise in raw data and applying multi-resolution analysis in cumulant reconstruction.A motor-driven rotating mask optical modulation system is designed to adjust the excitation lightfield and allows for fast deployment.Active-modulated fluorescence fluctuation superresolution microscopy with multi-resolution analysis(AMF-MRA-SOFI)demonstrates enhanced resolution ability and reconstruction quality in experiments performed on sample of conventional dyes,achieving a resolution of 100 nm in the fourth order compared to conventional SOFI reconstruction.Furthermore,our approach combining expansion super-resolution achieved a resolution at-57 nm.
基金supported by the NSFC Grant No.11872210 and Grant No.MCMS-I-0120G01Chi-Wang Shu:Research is supported by the AFOSR Grant FA9550-20-1-0055 and the NSF Grant DMS-2010107Jianxian Qiu:Research is supported by the NSFC Grant No.12071392.
文摘In this paper, we design high-order Runge-Kutta discontinuous Galerkin (RKDG) methods with multi-resolution weighted essentially non-oscillatory (multi-resolution WENO) limiters to compute compressible steady-state problems on triangular meshes. A troubled cell indicator extended from structured meshes to unstructured meshes is constructed to identify triangular cells in which the application of the limiting procedures is required. In such troubled cells, the multi-resolution WENO limiting methods are used to the hierarchical L^(2) projection polynomial sequence of the DG solution. Through using the RKDG methods with multi-resolution WENO limiters, the optimal high-order accuracy can be gradually reduced to first-order in the triangular troubled cells, so that the shock wave oscillations can be well suppressed. In steady-state simulations on triangular meshes, the numerical residual converges to near machine zero. The proposed spatial reconstruction methods enhance the robustness of classical DG methods on triangular meshes. The good results of these RKDG methods with multi-resolution WENO limiters are verified by a series of two-dimensional steady-state problems.
基金supported by the National Natural Science Foundation of China (No.12172154)the 111 Project (No.B14044)+1 种基金the Natural Science Foundation of Gansu Province (No.23JRRA1035)the Natural Science Foundation of Anhui University of Finance and Economics (No.ACKYC20043).
文摘In this study,a wavelet multi-resolution interpolation Galerkin method(WMIGM)is proposed to solve linear singularly perturbed boundary value problems.Unlike conventional wavelet schemes,the proposed algorithm can be readily extended to special node generation techniques,such as the Shishkin node.Such a wavelet method allows a high degree of local refinement of the nodal distribution to efficiently capture localized steep gradients.All the shape functions possess the Kronecker delta property,making the imposition of boundary conditions as easy as that in the finite element method.Four numerical examples are studied to demonstrate the validity and accuracy of the proposedwavelet method.The results showthat the use ofmodified Shishkin nodes can significantly reduce numerical oscillation near the boundary layer.Compared with many other methods,the proposed method possesses satisfactory accuracy and efficiency.The theoretical and numerical results demonstrate that the order of theε-uniform convergence of this wavelet method can reach 5.
文摘The basic theory of YOLO series object detection algorithms is discussed, the dangerous driving behavior dataset is collected and produced, and then the YOLOv7 network is introduced in detail, the deep separable convolution and CA attention mechanism are introduced, the YOLOv7 bounding box loss function and clustering algorithm are optimized, and the DB-YOLOv7 network structure is constructed. In the first stage of the experiment, the PASCAL VOC public dataset was utilized for pre-training. A comparative analysis was conducted to assess the recognition accuracy and inference time before and after the proposed improvements. The experimental results demonstrated an increase of 1.4% in the average recognition accuracy, alongside a reduction in the inference time by 4 ms. Subsequently, a model for the recognition of dangerous driving behaviors was trained using a specialized dangerous driving behavior dataset. A series of experiments were performed to evaluate the efficacy of the DB-YOLOv7 algorithm in this context. The findings indicate a significant enhancement in detection performance, with a 4% improvement in accuracy compared to the baseline network. Furthermore, the model’s inference time was reduced by 20%, from 25 ms to 20 ms. These results substantiate the effectiveness of the DB-YOLOv7 recognition algorithm for detecting dangerous driving behaviors, providing comprehensive validation of its practical applicability.
基金supported in part by the National Natural Science Foundation of China under Grant 52077002。
文摘Model predictive control(MPC)has been deemed as an attractive control method in motor drives by virtue of its simple structure,convenient multi-objective optimization,and satisfactory dynamic performance.However,the strong reliance on mathematical models seriously restrains its practical application.Therefore,improving the robustness of MPC has attained significant attentions in the last two decades,followed by which,model-free predictive control(MFPC)comes into existence.This article aims to reveal the current state of MFPC strategies for motor drives and give the categorization from the perspective of implementation.Based on this review,the principles of the reported MFPC strategies are introduced in detail,as well as the challenges encountered in technology realization.In addition,some of typical and important concepts are experimentally validated via case studies to evaluate the performance and highlight their features.Finally,the future trends of MFPC are discussed based on the current state and reported developments.
基金supported by the Joint Funds of the National Natural Science Foundation of China(No.U21A2027)the New Cornerstone Science Foundation through the XPLORER PRIZE(2023-1033).
文摘This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in China’s Yangtze River Delta region(YRD)from 2008 to 2020.Utilizing data from the Infrared Atmospheric Sounding Interfer-ometer(IASI),Generalized Additive Models(GAM),and the GEOS-Chem chemical transport model,we observed a significant increase of NH_(3)VCDs in the YRD between 2014 and 2020.The spatial distribution analysis revealed higher NH_(3)concentrations in the northern part of the YRD region,primarily due to lower precipitation,alkaline soil,and intensive agricul-tural activities.NH_(3)VCDs in the YRD region increased significantly(65.18%)from 2008 to 2020.The highest growth rate occurs in the summer,with an annual average growth rate of 7.2%during the period from 2014 to 2020.Agricultural emissions dominated NH_(3)VCDs during spring and summer,with high concentrations primarily located in the agricultural areas adjacent to densely populated urban zones.Regions within several large urban areas have been discovered to exhibit relatively stable variations in NH_(3)VCDs.The rise in NH_(3)VCDs within the YRD region was primarily driven by the reduction of acidic gases like SO_(2),as emphasized by GAM modeling and sensitivity tests using the GEOS-Chem model.The concentration changes of acidic gases contribute to over 80%of the interannual variations in NH_(3)VCDs.This emphasizes the crucial role of environmental policies targeting the reduction of these acidic gases.Effective emission control is urgent tomitigate environmental hazards and secondary particulate matter,especially in the northern YRD.
基金supported by the National Natural Science Foundation of China(Nos.52177059 and 52407064).
文摘Permanent magnet synchronous motor based electro-mechanical actuation servo drives have widespread applications in the aviation field,such as unmanned aerial vehicle electric servos,electric cabin doors,and mechanical arms.The performance of the servo drive,which encompasses the response to the torque,efficiency,control bandwidth and the steady-state positioning accuracy,significantly influences the performance of the aviation actuation.Consequently,enhancing the control bandwidth and refining the positioning accuracy of aviation electro-mechanical actuation servo drives have emerged as a focal point of research.This paper investigates the multi-source disturbances present in aviation electro-mechanical actuation servo systems and summarizes recent research on high-performance servo control methods based on active disturbance rejection control(ADRC).We present a comprehensive overview of the research status pertaining to servo control architecture,strategies for suppressing disturbances in the current loop,and ADRC-based strategies for the position loop.We delineate the research challenges and difficulties encountered by aviation electro-mechanical actuation servo drive control technology.
基金Supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_0102)the China Scholarship Council Program(202406190114)。
文摘Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoting high-quality development of new energy in China.This paper constructs an evaluation index system for the development of NEVs and the ecological environment.It uses game theory combining weighting model,particle swarm optimized projection tracking evaluation model,coupling coordination degree model,and machine learning algorithms to calculate and analyze the level of coupling coordination development of NEVs and the ecological environment in China from 2010 to 2021,and identifies the driving factors.The research results show that:(i)From 2010 to 2021,the development index of NEVs in China has steadily increased from 0.085 to 0.634,while the ecological environment level index significantly rose from 0.170 to 0.884,reflecting the continuous development of China in both NEVs and the ecological environment.(ii)From 2010 to 2012,the two systems—new energy vehicle(NEV)development and the ecological environment—were in a period of imbalance and decline.From 2013 to 2016,they underwent a transition period,and from 2017 to 2021,they entered a period of coordinated development showing a trend of benign and continuous improvement.By 2021,they reached a good level of coordination.(iii)Indicators such as the number of patents granted for NEVs,water consumption per unit of GDP,and energy consumption per unit of GDP are the main driving factors affecting the coupling coordination development of NEVs and the ecological environment in China.
基金Supported by the National Natural Science Foundation of China (11161027)。
文摘Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.
基金funded by the Central University D Project(HFW230600022)National Natural Science Foundation of China(71973021)+1 种基金National Natural Science Foundation Youth Funding Project(72003022)Heilongjiang Province University Think Tank Open Topic(ZKKF2022173).
文摘The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grant No.52267003.
文摘Trajectory prediction is a critical task in autonomous driving systems.It enables vehicles to anticipate the future movements of surrounding traffic participants,which facilitates safe and human-like decision-making in the planning and control layers.However,most existing approaches rely on end-to-end deep learning architectures that overlook the influence of driving style on trajectory prediction.These methods often lack explicit modeling of semantic driving behavior and effective interaction mechanisms,leading to potentially unrealistic predictions.To address these limitations,we propose the Driving Style Guided Trajectory Prediction framework(DSG-TP),which incorporates a probabilistic representation of driving style into trajectory prediction.Our approach enhances the model’s ability to interact with vehicle behavior characteristics in complex traffic scenarios,significantly improving prediction reliability in critical decision-making situations by incorporating the driving style recognition module.Experimental evaluations on the Argoverse 1 dataset demonstrate that our method outperforms existing approaches in both prediction accuracy and computational efficiency.Through extensive ablation studies,we further validate the contribution of each module to overall performance.Notably,in decision-sensitive scenarios,DSG-TP more accurately captures vehicle behavior patterns and generates trajectory predictions that align with different driving styles,providing crucial support for safe decision-making in autonomous driving systems.
基金approved by the Institutional Ethics Committee of Shizuoka Red Cross Hospital(No.2023-36,approval date:January 12,2024).
文摘BACKGROUND Return to work(RTW)and resumption of driving(ROD)are critical factors that influence postoperative quality of life in patients undergoing total hip arthroplasty(THA).However,few studies have focused on the minimally invasive(MIS)approach and its effect on these outcomes.AIM To investigate RTW and ROD's timelines and influencing factors following anterior MIS-THA.METHODS A retrospective analysis was conducted on 124 patients who underwent anterior MIS-THA.Data on the demographics,occupational physical demands,and RTW/ROD timelines were also collected.Clinical outcomes were measured using standardised scoring systems.Statistical analyses were performed to evaluate the differences between the groups based on employment status and physical workload.RESULTS Among employed patients,the RTW rate was 94.7%,with an average return time of five weeks.The average ROD time was 3.5 weeks across all patients.Despite similar postoperative clinical scores,RTW time was significantly influenced by occupations'physical workload,with heavier physical demands associated with delayed RTW.CONCLUSION Anterior MIS-THA facilitates early RTW and ROD,particularly in occupations with lower physical demands.These findings highlight the importance of considering occupational and physical workload in postoperative care planning to optimize recovery outcomes.
文摘From AI-powered chatbots capable of deep reasoning to humanoid robots equipped with intelligent“brains”for complex services,technological advancements continue to astonish us at an unprecedented pace.The rapid development of artificial intelligence(AI)is reshaping industries,enhancing productivity,and offering new possibilities for an intelligent life.
文摘As one of the three key drivers of economic growth,export has been playing an important and positive role in the Chinese economy.According to the National Bureau of Statistics and World Bank,China’s gross domestic product(GDP)in 2004 was US$1.96 trillion,with a total export of US$593.4 billion,accounting for 30.3 percent of GDP.Across the following 20 years,the share of export in GDP gradually declined to 24.47 percent in 2014 and 18.87 percent in 2024.But a look at China’s share of the global export market shows a continuing upward trend,and China’s position as the largest trading nation in goods has also become more secure.
基金supported by the Science and Technology Project of State Grid Corporation of China Headquarters under Grant 5500-202416156A-1-1-ZN.
文摘Sine-wave drive and square-wave drive are two common motor control strategies.This study constructs a mathematical model capable of predicting the distribution of electromagnetic force waves in synchronous reluctance motors(SynRMs)under these two drive methods,and comparatively analyzes the vibration phenomena induced by electromagnetic forces under different drive methods.It aims to provide an effective tool for predicting the distribution of electromagnetic force waves in SynRMs,while exploring the influence of drive modes on their vibration characteristics.The study focuses on a 4-pole,36-slot 5.5 kW SynRM.Based on the magnetomotive force(MMF)-permeance method,incorporating the special rotor structure and the characteristics of current harmonics under square-wave drive,an air-gap flux distribution function is established.Meanwhile,Maxwell’s stress tensor method is adopted to analyze how the air-gap flux density relates to electromagnetic excitation force waves.Subsequently,this analysis is applied to forecast the spatiotemporal distribution features of radial electromagnetic force waves.Finite element simulations are conducted to compute the modal and vibration responses of the SynRM,followed by a comparative analysis of the vibration characteristics under the two drive methods.Additionally,a 6-pole,36-slot SynRM is used for additional comparative verification.Ultimately,the effectiveness of the simulation results is verified through experiments.
基金supported by the National Natural Science Foundation of China(Grants No.W2412144,42271292)the 111 project,and the Fundamental Research Funds for the Central Universities of China.
文摘Amid ongoing global environmental change and the critical pursuit of sustainable development,human-environment systems are exhibiting increasingly complex dynamic evolutions and spatial relationships,underscoring an urgent need for innovative research frameworks.Integrated geography synthesizes physical geography,human geography,and geographic information science,providing key frameworks for understanding complex human-environment systems.This editorial proposes an emerging research framework for integrated geography—“Composite driving-System evolution-Coupling mechanism-Synergistic regulation(CSCS)”—based on key issues such as climate change,biodiversity loss,resource scarcity,and social-ecological interactions,which have been highlighted in both recent critical literature on human-environment systems and UN assessment reports.The framework starts with diverse composite driving forces,extends to the evolution of human-environment system structures,processes,and functions that these drivers induce,explores couplings within human-environment systems,and calls for regulation aimed at sustainable development in synergies.Major research frontiers include understanding the cascading“evolution-coupling”effects of shocks;measuring system resilience,thresholds,and safe and just operating space boundaries;clarifying linkage mechanisms across scales;and achieving synergistic outcomes for multi-objective sustainability.This framework will help promote the interdisciplinary integration and development of integrated geography,and provide geographical solutions for the global sustainable development agenda.
文摘Abnormal driving behavior includes driving distraction,fatigue,road anger,phone use,and an exceptionally happy mood.Detecting abnormal driving behavior in advance can avoid traffic accidents and reduce the risk of traffic conflicts.Traditional methods of detecting abnormal driving behavior include using wearable devices to monitor blood pressure,pulse,heart rate,blood oxygen,and other vital signs,and using eye trackers to monitor eye activity(such as eye closure,blinking frequency,etc.)to estimate whether the driver is excited,anxious,or distracted.Traditional monitoring methods can detect abnormal driving behavior to a certain extent,but they will affect the driver’s normal driving state,thereby introducing additional driving risks.This research uses the combined method of support vector machine and dlib algorithm to extract 68 facial feature points from the human face,and uses an SVM model as a strong classifier to classify different abnormal driving statuses.The combined method reaches high accuracy in detecting road anger and fatigue status and can be used in an intelligent vehicle cabin to improve the driving safety level.
基金supported by the National Natural Science Foundation of China(Grant Nos.12205274,12275251,12105270,12205272,12305262,and 12035002)the National Key Laboratory of Plasma Physics(Grant No.JCKYS2024212803)+2 种基金the Fund of the National Key Laboratory of Plasma Physics(Grant No.6142A04230103)the National Key R&D Program of China(Grant No.2023YFA1608400)the National Security Academic Fund(Grant No.U2430207).
文摘Stimulated Raman scattering(SRS)under a new ignition path that combines the advantages of direct-drive(DD)and indirect-drive(ID)schemes is investigated experimentally at the Shenguang-100 kJ facility.The results show that collective SRS in the plasma produced by ablating a polyimide film is detected for the ID beams,but is suppressed by adding a toe before the main pulse of the ID beams.The toe also strongly influences SRS of both the ID and DD beams excited in the plasma generated in the hohlraum.When a toe is used,the SRS spectra of the DD beams show that SRS tends to be excited in lower plasma density,which will result in a lower risk of super-hot electrons.Measurements of hot electrons support this conclusion.This research will help us produce a better pulse design for this new ignition path.
文摘This paper introduces autonomous driving image perception technology,including deep learning models(such as CNN and RNN)and their applications,analyzing the limitations of traditional algorithms.It elaborates on the shortcomings of Faster R-CNN and YOLO series models,proposes various improvement techniques such as data fusion,attention mechanisms,and model compression,and introduces relevant datasets,evaluation metrics,and testing frameworks to demonstrate the advantages of the improved models.
基金supported by the 2024 Science and Technology Plan Project of Sichuan Province[grant number 2024YFTX0016]the Undergraduate Innovation and Entrepreneurship Training Program[grant number S202510621001].
文摘This study analyzes the spatiotemporal patterns and driving factors of forest fires in Liangshan Prefecture based on fire data from 2016 to 2024 using statistical methods.The results indicate:1)From 2016 to 2024,forest fires in Liangshan Prefecture occurred predominantly between January and May(140 incidents),accounting for 97.90%of the total.March recorded the highest number of fires(48 incidents),representing 33.57%.Within a 24-hour period,113 fires occurred between 12:00 PM and 9:00 PM,constituting 79.02%of all incidents.2)Spatially,Mianning County recorded the highest number of forest fires(28 incidents,19.58%),followed by Xichang,Muli,and Yanyuan with 22,23,and 20 incidents,respectively.Human activities,particularly agricultural burning,outdoor smoking,and other causes,were the dominant factors,collectively accounting for 41%of incidents.3)Forest fires predominantly occurred at elevations between 1500 and 3000 meters(132 fires,92.31%),on slopes with gradients of 5-25 degrees(81 fires,56.65%),on west-facing aspects(northwest,west,southwest)(72 fires,53.14%),in areas with NDVI values between 0.51 and 0.8(79 incidents,55.24%),within 500-2000 m residential buffer zones(151 incidents,98.60%),and within 500 m road buffer zones(103 incidents,72.03%).4)Among meteorological factors,the 20-day average temperature(0.3041),80-day maximum temperature(0.3487),20-day minimum temperature(0.2594),20-day minimum relative humidity(−0.3132),70-day maximum wind speed(0.1885),and 70-day peak wind speed(0.1965)showed the strongest correlations with forest fire burned area.Burned area also exhibited a positive correlation with the Meteorological Drought Index(MCI)on the day of the fire(0.1990).This study confirms the lagged and persistent effects of meteorological factors on forest fire occurrence,providing key scientific evidence for constructing regional fire prediction models that integrate multi-scale meteorological indicators.
