Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,w...Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,we propose HUANNet(High-Resolution Unified Attention Network),a convolutional neural network designed to capture both local features and rich semantic information through a high-resolution representation learning framework,while optimizing computational distribution across parallel branches.HUANNet introduces three core modules:the High-Resolution Attention Module(HRAM),which enhances feature extraction by optimizing multiresolution feature fusion;the Unified Multi-Scale Attention Module(UMAM),which integrates spatial,channel,and convolutional kernel information through an attention mechanism applied across multiple levels of the network;and the Grid-Assisted Point Matching Module(GPMM),which stabilizes and improves point-to-point matching by leveraging grid-based mechanisms.Extensive experiments show that HUANNet achieves competitive results on the ShanghaiTech Part A/B crowd counting datasets and sets new state-of-the-art performance on dense object counting datasets such as CARPK and XRAY-IECCD,demonstrating the effectiveness and versatility of HUANNet.展开更多
With the continuous upgrading of traditional manufacturing industries and the rapid rise of emerging technology fields,the performance requirements for the permanent magnet synchronous motors(PMSMs)have become higher ...With the continuous upgrading of traditional manufacturing industries and the rapid rise of emerging technology fields,the performance requirements for the permanent magnet synchronous motors(PMSMs)have become higher and higher.The importance of fast and accurate electromagnetic thermal coupling analysis of such motors becomes more and more prominent.In view of this,the surfacemounted PMSM(SPMSM)equipped with unequally thick magnetic poles is taken as the main object and its electromagnetic thermal coupling analytical model(ETc AM)is investigated.First,the electromagnetic analytical model(EAM)is studied based on the modified subdomain method.It realizes the fast calculation of key electromagnetic characteristics.Subsequently,the 3D thermal analytical model(TAM)is developed by combining the EAM,the lumped parameter thermal network method(LPTNM),and the partial differential equation of heat flux.It realizes the fast calculation of key thermal characteristics in 3D space.Further,the information transfer channel between EAM and TAM is built with reference to the intrinsic connection between electromagnetic field and temperature field.Thereby,the novel ETcAM is proposed to realize the fast and accurate prediction of electromagnetic and temperature fields.Besides,ETcAM has a lot to commend it.One is that it well accounts for the complex structure,saturation,and heat exchange behavior.Second,it saves a lot of computer resources.It offers boundless possibilities for initial design,scheme evaluation,and optimization of motors.Finally,the validity,accuracy,and practicality of this study are verified by simulation and experiment.展开更多
Real-time and accurate drogue pose measurement during docking is basic and critical for Autonomous Aerial Refueling(AAR).Vision measurement is the best practicable technique,but its measurement accuracy and robustness...Real-time and accurate drogue pose measurement during docking is basic and critical for Autonomous Aerial Refueling(AAR).Vision measurement is the best practicable technique,but its measurement accuracy and robustness are easily affected by limited computing power of airborne equipment,complex aerial scenes and partial occlusion.To address the above challenges,we propose a novel drogue keypoint detection and pose measurement algorithm based on monocular vision,and realize real-time processing on airborne embedded devices.Firstly,a lightweight network is designed with structural re-parameterization to reduce computational cost and improve inference speed.And a sub-pixel level keypoints prediction head and loss functions are adopted to improve keypoint detection accuracy.Secondly,a closed-form solution of drogue pose is computed based on double spatial circles,followed by a nonlinear refinement based on Levenberg-Marquardt optimization.Both virtual simulation and physical simulation experiments have been used to test the proposed method.In the virtual simulation,the mean pixel error of the proposed method is 0.787 pixels,which is significantly superior to that of other methods.In the physical simulation,the mean relative measurement error is 0.788%,and the mean processing time is 13.65 ms on embedded devices.展开更多
The combination of flexible sensors and bionic innovative design has become an important direction for the development of intelligent sensing technology.To this end,this paper systematically describes the latest resea...The combination of flexible sensors and bionic innovative design has become an important direction for the development of intelligent sensing technology.To this end,this paper systematically describes the latest research progress of bionic sensors inspired by the synergistic mechanism of“stress concentration-high pass filtering-omnidirectional localization”of scorpion slit receptors.First,it presents breakthroughs such as ultra-high sensitivity through gradient-cracked structures,dynamic signal decoupling mediated by viscoelastic materials,and omnidirectional localization accuracy supported by curvilinear array layouts.Aiming at the cross-interference and integration redundancy problems faced by traditional multimodal sensing systems,this paper introduces a vertically stacked heterogeneous integration strategy.Through the synergistic design of bionic stretchable conductive film and strain-isolated communication interfaces,a flexible multimodal sensing system with pressure-temperature bimodal sensing,multiaxial stress decoupling,and spatial distribution tracking capability is successfully constructed.Relevant research further confirms that the bionic architecture shows significant advantages in medical monitoring,industrial equipment health management and lunar rover terrain sensing scenarios.It provides a new paradigm of cross-scale structure-function synergistic optimization for the development of adaptive intelligent sensing systems in extreme environments,and marks an important leap in the integration of bionic flexible electronics from single-device innovation to systematic technology.展开更多
Accurate cancer staging is the foundation of precision oncology and guides prognosis prediction and therapeutic decision-making. The conjoint TNM System by the American Joint Committee on Cancer (AJCC) and the Interna...Accurate cancer staging is the foundation of precision oncology and guides prognosis prediction and therapeutic decision-making. The conjoint TNM System by the American Joint Committee on Cancer (AJCC) and the International Union Against Cancer (UICC) has served as the global standard for tumor classification since inception.展开更多
The axial field hybrid permanent magnet memory machine(AFHPM-MM)employs a hybrid permanent magnet excitation combining NdFeB and AlNiCo,achieving high torque density and a wide flux adjustment range.A separated stator...The axial field hybrid permanent magnet memory machine(AFHPM-MM)employs a hybrid permanent magnet excitation combining NdFeB and AlNiCo,achieving high torque density and a wide flux adjustment range.A separated stator structure is adopted to enhance its antidemagnetization capability.To analyze the contributions of AlNiCo and NdFeB to the induced electromotive force(EMF)in the AFHPM-MM,a frozen permeability-based induced EMF calculation method is proposed.Theoretical analysis reveals that the conventional method exhibits substantial errors in calculating the AlNiCo-induced EMF,primarily attributed to its failure to adequately account for the dynamic magnetization characteristic discrepancies of AlNiCo under varying magnetization states.Through the analysis of magnetization variations in AlNiCo during the flux adjustment process under different magnetization states,an improved induced EMF calculation method is proposed.Comparative results indicate that,during the flux enhancement process,the average calculation error of the AlNiCo-induced EMF is reduced from 19.84%to 2.09%,whereas during the flux weakening process,the error is reduced from 3.87%to 1.67%.The proposed method achieves accurate induced EMF calculation for the AFHPM-MM.展开更多
Accurate kinematic calibration is the very foundation for robots'application in industry demanding high precision such as machining.Considering the complex error characteristic and severe ill-posed identification ...Accurate kinematic calibration is the very foundation for robots'application in industry demanding high precision such as machining.Considering the complex error characteristic and severe ill-posed identification issues of a 5-DoF parallel machining robot,this paper proposes an adaptive and weighted identification method to achieve high-precision kinematic calibration while maintaining reliable stability.First,a kinematic error propagation mechanism model considering the non-ideal constraints and the screw self-rotation is formulated by incorporating the intricate structure of multiple chains and a unique driven screw arrangement of the robot.To address the challenge of accurately identifying such a sophisticated error model,a novel adaptive and weighted identification method based on generalized cross validation(GCV)is proposed.Specifically,this approach innovatively introduces Gauss-Markov estimation into the GCV algorithm and utilizes prior physical information to construct both a weighted identification model and a weighted cross-validation function,thus eliminating the inaccuracy caused by significant differences in dimensional magnitudes of pose errors and achieving accurate identification with flexible numerical stability.Finally,the kinematic calibration experiment is conducted.The comparative experimental results demonstrate that the presented approach is effective and has enhanced accuracy performance over typical least squares methods,with maximum position and orientation errors reduced from 2.279 mm to 0.028 mm and from 0.206°to 0.017°,respectively.展开更多
Accurately modeling real network dynamics is a grand challenge in network science.The network dynamics arise from node interactions,which are shaped by network topology.Real networks tend to exhibit compact or highly ...Accurately modeling real network dynamics is a grand challenge in network science.The network dynamics arise from node interactions,which are shaped by network topology.Real networks tend to exhibit compact or highly optimized topologies.But the key problems arise:how to compress a network to best enhance its compactness,and what the compression limit of the network reflects?We abstract the topological compression of complex networks as a dynamic process of making them more compact and propose the local compression modulus that plays a key role in effective compression evolution of networks.Subsequently,we identify topological compressibility-a general property of complex networks that characterizes the extent to which a network can be compressed-and provide its approximate quantification.We anticipate that our findings and established theory will provide valuable insights into both dynamics and various applications of complex networks.展开更多
Dear Editor,This letter introduces an innovative event-triggered secondary control strategy for Microgrid(MG)to address challenges of low inertia and renewable energy integration.Utilizing semi-Markov switching topolo...Dear Editor,This letter introduces an innovative event-triggered secondary control strategy for Microgrid(MG)to address challenges of low inertia and renewable energy integration.Utilizing semi-Markov switching topologies,this method employs semi-Markov jump processes for accurate load forecasting,facilitating adaptive adjustments of distributed generators(DGs)in response to load changes.展开更多
Camera Pose Estimating from point and line correspondences is critical in various applications,including robotics,augmented reality,3D reconstruction,and autonomous navigation.Existing methods,such as the Perspective-...Camera Pose Estimating from point and line correspondences is critical in various applications,including robotics,augmented reality,3D reconstruction,and autonomous navigation.Existing methods,such as the Perspective-n-Point(PnP)and Perspective-n-Line(PnL)approaches,offer limited accuracy and robustness in environments with occlusions,noise,or sparse feature data.This paper presents a unified solution,Efficient and Accurate Pose Estimation from Point and Line Correspondences(EAPnPL),combining point-based and linebased constraints to improve pose estimation accuracy and computational efficiency,particularly in low-altitude UAV navigation and obstacle avoidance.The proposed method utilizes quaternion parameterization of the rotation matrix to overcome singularity issues and address challenges in traditional rotation matrix-based formulations.A hybrid optimization framework is developed to integrate both point and line constraints,providing a more robust and stable solution in complex scenarios.The method is evaluated using synthetic and realworld datasets,demonstrating significant improvements in performance over existing techniques.The results indicate that the EAPnPL method enhances accuracy and reduces computational complexity,making it suitable for real-time applications in autonomous UAV systems.This approach offers a promising solution to the limitations of existing camera pose estimation methods,with potential applications in low-altitude navigation,autonomous robotics,and 3D scene reconstruction.展开更多
Objective:To investigate the impact of precise nursing care based on dynamic nursing quality feedback model on the postoperative recovery of elderly patients undergoing radical resection for colon cancer,with a partic...Objective:To investigate the impact of precise nursing care based on dynamic nursing quality feedback model on the postoperative recovery of elderly patients undergoing radical resection for colon cancer,with a particular focus on its effects on psychological flexibility.Methods:Medical records of 124 elderly patients undergoing radical resection for colon cancer at The First Affiliated Hospital of Baotou Medical College between January 2021 and May 2024 were retrospectively analyzed in this study.Based on the received nursing interventions,the patients were divided into a control group(standard nursing care)and an observation group(precise nursing care based on a dynamic nursing quality feedback model).Results:The observation group exhibited significantly higher levels of hemoglobin,prealbumin,and albumin compared to the control group.Additionally,the observation group had lower scores in somatization,interpersonal sensitivity,depression,anxiety,obsessions-compulsions,hostility,phobic anxiety,psychoticism,and paranoid ideation.The observation group also demonstrated higher scores in active coping,self-efficacy,and the management of emotions,life,and symptoms.Improvements were also observed in nursing quality,perioperative intervention,satisfaction with rehabilitation guidance,and awareness of regular reexaminations,diet intervention,and complication prevention(all with P<0.05).Conclusion:Precise nursing based on a dynamic nursing quality feedback model can improve nutritional status and medical coping style,reduce psychological issues,and enhance self-management abilities in elderly patients following radical resection of colon cancer.Additionally,it increases nursing satisfaction and raises awareness regarding the importance of regular reexaminations and complication prevention.展开更多
Accurate Electric Load Forecasting(ELF)is crucial for optimizing production capacity,improving operational efficiency,and managing energy resources effectively.Moreover,precise ELF contributes to a smaller environment...Accurate Electric Load Forecasting(ELF)is crucial for optimizing production capacity,improving operational efficiency,and managing energy resources effectively.Moreover,precise ELF contributes to a smaller environmental footprint by reducing the risks of disruption,downtime,and waste.However,with increasingly complex energy consumption patterns driven by renewable energy integration and changing consumer behaviors,no single approach has emerged as universally effective.In response,this research presents a hybrid modeling framework that combines the strengths of Random Forest(RF)and Autoregressive Integrated Moving Average(ARIMA)models,enhanced with advanced feature selection—Minimum Redundancy Maximum Relevancy and Maximum Synergy(MRMRMS)method—to produce a sparse model.Additionally,the residual patterns are analyzed to enhance forecast accuracy.High-resolution weather data from Weather Underground and historical energy consumption data from PJM for Duke Energy Ohio and Kentucky(DEO&K)are used in this application.This methodology,termed SP-RF-ARIMA,is evaluated against existing approaches;it demonstrates more than 40%reduction in mean absolute error and root mean square error compared to the second-best method.展开更多
An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, clo...An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.展开更多
The Raman depolarization ratios of gaseous CO2 in the spectral range of 1240-1430 cm-I are determined with a sensitive photoacoustic Raman spectroscopy, and more accurate data compared to the literature results are pr...The Raman depolarization ratios of gaseous CO2 in the spectral range of 1240-1430 cm-I are determined with a sensitive photoacoustic Raman spectroscopy, and more accurate data compared to the literature results are presented. The precision of the obtained depolarization ratio is achieved by measuring and fitting the dependence of the PARS signal intensity on the cross angle between the polarizations of two incident laser beams.展开更多
In this paper,we report the construction of two accurate mass databases and the development of a combination detection method that simultaneously screens for 733 pesticide and chemical contaminant multi-residues via h...In this paper,we report the construction of two accurate mass databases and the development of a combination detection method that simultaneously screens for 733 pesticide and chemical contaminant multi-residues via high-throughput liquid chromatography(LC)-and gas chromatography(GC)-quadru pole-time-of-flight mass spectrometry(Q-TOFMS).This work demonstrates that electronic mass spectral standards may replace chemical-source standard materials as references through one sample preparation and the combination of GC/LC-Q-TOFMS screening.This cutting-edge technique has also replaced multiresidue determination using targeted detection with non-targeted screening.The pesticide residue types,sensitivity,recovery,and reproducibility of this combination technique are evaluated in eight fruit and vegetable matrices.This technique shows three advantages:①In comparison with the discovery capability of a single technique,the combination technique shows an improvement of 51.1%(GC-QTOFMS)and 39.6%(LC-Q-TOFMS),respectively;②the combination technique can satisfy a screening limit lower than 10μg·kg^-1 and meet the requirements of“uniform standards,”although some of the pesticide residues could be optimized to further improve screening sensitivity;③over 488 pesticides with recoveries between 60%-120%and relative standard deviation(RSD)<20%at a spiked level of 10μg·kg^-1 were detected with the combination technique in eight different matrices.From 2012 to 2017,this combination technique was applied in an investigation to screen pesticide residues from 1384 sampling locations for 38138 batched samples covering 18 categories and 134 types of fruits and vegetables obtained from across the mainland of China.After statistical analysis,533 pesticides in 115891 determinations were detected,and the regularity of pesticides in the fruits and vegetables sold on the Chinese market was shown.展开更多
The Ordos basin is a stable craton whose late Paleozoic undergoes two sedimentary stages: from the middle- late Carboniferous offshore plain to the Permian continental river and lake delta. Sandstones in delta plain c...The Ordos basin is a stable craton whose late Paleozoic undergoes two sedimentary stages: from the middle- late Carboniferous offshore plain to the Permian continental river and lake delta. Sandstones in delta plain channels, delta-front river mouth bars and tidal channels are well developed. The sandstones are distributed on or between the genetic source rocks, forming good gas source conditions with widespread subtle lithologic gas pools of low porosity, low permeability, low pressure and low abundance. In recent years, a series of experiments has been done, aimed at overcoming difficulties in the exploration of lithologic gas pools. A set of exploration techniques, focusing on geological appraisal, seismic exploration, accurate logging evaluation and interpretation, well testing fracturing, has been developed to guide the exploration into the upper Paleozoic in the basin, leading to the discoveries of four large gas fields: Sulige, Yulin, Wushenqi and Mizhi.展开更多
An improved algebraic reconstruction technique（ART） combined with tunable diode laser absorption spectroscopy（TDLAS） is presented in this paper for determining two-dimensional（2D） distribution of H2O concentrati...An improved algebraic reconstruction technique（ART） combined with tunable diode laser absorption spectroscopy（TDLAS） is presented in this paper for determining two-dimensional（2D） distribution of H2O concentration and temperature in a simulated combustion flame.This work aims to simulate the reconstruction of spectroscopic measurements by a multi-view parallel-beam scanning geometry and analyze the effects of projection rays on reconstruction accuracy.It finally proves that reconstruction quality dramatically increases with the number of projection rays increasing until more than 180 for 20 × 20 grid,and after that point,the number of projection rays has little influence on reconstruction accuracy.It is clear that the temperature reconstruction results are more accurate than the water vapor concentration obtained by the traditional concentration calculation method.In the present study an innovative way to reduce the error of concentration reconstruction and improve the reconstruction quality greatly is also proposed,and the capability of this new method is evaluated by using appropriate assessment parameters.By using this new approach,not only the concentration reconstruction accuracy is greatly improved,but also a suitable parallel-beam arrangement is put forward for high reconstruction accuracy and simplicity of experimental validation.Finally,a bimodal structure of the combustion region is assumed to demonstrate the robustness and universality of the proposed method.Numerical investigation indicates that the proposed TDLAS tomographic algorithm is capable of detecting accurate temperature and concentration profiles.This feasible formula for reconstruction research is expected to resolve several key issues in practical combustion devices.展开更多
Accurate diagnosis of tumors needs much detailed information. However, available single imaging modality cannot provide complete or comprehensive data. Nanomedicine is the application of nanotechnology to medicine, an...Accurate diagnosis of tumors needs much detailed information. However, available single imaging modality cannot provide complete or comprehensive data. Nanomedicine is the application of nanotechnology to medicine, and multimodality imaging based on nanoparticles has been receiving extensive attention. This new hybrid imaging technology could provide complementary information from different imaging modalities using only a single injection of contrast agent. In this review, we introduce recent developments in multifunctional nanoparticles and their biomedical applications to multimodal imaging and theragnosis as nanomedicine. Most of the reviewed studies are based on the intrinsic properties of nanoparticles and their application in clinical imaging technology. The imaging techniques include positron emission tomography, single-photon emission computed tomography, computerized tomography, magnetic resonance imaging, optical imaging, and ultrasound imaging.展开更多
基金funded by the National Natural Science Foundation of China(62273213,62472262,62572287)Natural Science Foundation of Shandong Province(ZR2024MF144)+1 种基金Natural Science Foundation of Shandong Province for Innovation and Development Joint Funds(ZR2022LZH001)Taishan Scholarship Construction Engineering.
文摘Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,we propose HUANNet(High-Resolution Unified Attention Network),a convolutional neural network designed to capture both local features and rich semantic information through a high-resolution representation learning framework,while optimizing computational distribution across parallel branches.HUANNet introduces three core modules:the High-Resolution Attention Module(HRAM),which enhances feature extraction by optimizing multiresolution feature fusion;the Unified Multi-Scale Attention Module(UMAM),which integrates spatial,channel,and convolutional kernel information through an attention mechanism applied across multiple levels of the network;and the Grid-Assisted Point Matching Module(GPMM),which stabilizes and improves point-to-point matching by leveraging grid-based mechanisms.Extensive experiments show that HUANNet achieves competitive results on the ShanghaiTech Part A/B crowd counting datasets and sets new state-of-the-art performance on dense object counting datasets such as CARPK and XRAY-IECCD,demonstrating the effectiveness and versatility of HUANNet.
基金supported by the Project of National Natural Science Foundation of China under Grant 52077122。
文摘With the continuous upgrading of traditional manufacturing industries and the rapid rise of emerging technology fields,the performance requirements for the permanent magnet synchronous motors(PMSMs)have become higher and higher.The importance of fast and accurate electromagnetic thermal coupling analysis of such motors becomes more and more prominent.In view of this,the surfacemounted PMSM(SPMSM)equipped with unequally thick magnetic poles is taken as the main object and its electromagnetic thermal coupling analytical model(ETc AM)is investigated.First,the electromagnetic analytical model(EAM)is studied based on the modified subdomain method.It realizes the fast calculation of key electromagnetic characteristics.Subsequently,the 3D thermal analytical model(TAM)is developed by combining the EAM,the lumped parameter thermal network method(LPTNM),and the partial differential equation of heat flux.It realizes the fast calculation of key thermal characteristics in 3D space.Further,the information transfer channel between EAM and TAM is built with reference to the intrinsic connection between electromagnetic field and temperature field.Thereby,the novel ETcAM is proposed to realize the fast and accurate prediction of electromagnetic and temperature fields.Besides,ETcAM has a lot to commend it.One is that it well accounts for the complex structure,saturation,and heat exchange behavior.Second,it saves a lot of computer resources.It offers boundless possibilities for initial design,scheme evaluation,and optimization of motors.Finally,the validity,accuracy,and practicality of this study are verified by simulation and experiment.
基金supported by the National Science Fund for Distinguished Young Scholars,China(No.51625501)Aeronautical Science Foundation of China(No.20240046051002)National Natural Science Foundation of China(No.52005028).
文摘Real-time and accurate drogue pose measurement during docking is basic and critical for Autonomous Aerial Refueling(AAR).Vision measurement is the best practicable technique,but its measurement accuracy and robustness are easily affected by limited computing power of airborne equipment,complex aerial scenes and partial occlusion.To address the above challenges,we propose a novel drogue keypoint detection and pose measurement algorithm based on monocular vision,and realize real-time processing on airborne embedded devices.Firstly,a lightweight network is designed with structural re-parameterization to reduce computational cost and improve inference speed.And a sub-pixel level keypoints prediction head and loss functions are adopted to improve keypoint detection accuracy.Secondly,a closed-form solution of drogue pose is computed based on double spatial circles,followed by a nonlinear refinement based on Levenberg-Marquardt optimization.Both virtual simulation and physical simulation experiments have been used to test the proposed method.In the virtual simulation,the mean pixel error of the proposed method is 0.787 pixels,which is significantly superior to that of other methods.In the physical simulation,the mean relative measurement error is 0.788%,and the mean processing time is 13.65 ms on embedded devices.
基金funded by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(No.52021003)“Fundamental Research Funds for the Central Universities”.
文摘The combination of flexible sensors and bionic innovative design has become an important direction for the development of intelligent sensing technology.To this end,this paper systematically describes the latest research progress of bionic sensors inspired by the synergistic mechanism of“stress concentration-high pass filtering-omnidirectional localization”of scorpion slit receptors.First,it presents breakthroughs such as ultra-high sensitivity through gradient-cracked structures,dynamic signal decoupling mediated by viscoelastic materials,and omnidirectional localization accuracy supported by curvilinear array layouts.Aiming at the cross-interference and integration redundancy problems faced by traditional multimodal sensing systems,this paper introduces a vertically stacked heterogeneous integration strategy.Through the synergistic design of bionic stretchable conductive film and strain-isolated communication interfaces,a flexible multimodal sensing system with pressure-temperature bimodal sensing,multiaxial stress decoupling,and spatial distribution tracking capability is successfully constructed.Relevant research further confirms that the bionic architecture shows significant advantages in medical monitoring,industrial equipment health management and lunar rover terrain sensing scenarios.It provides a new paradigm of cross-scale structure-function synergistic optimization for the development of adaptive intelligent sensing systems in extreme environments,and marks an important leap in the integration of bionic flexible electronics from single-device innovation to systematic technology.
基金supported by the Sanming Project of Medicine in Shenzhen (SZSM202211017)。
文摘Accurate cancer staging is the foundation of precision oncology and guides prognosis prediction and therapeutic decision-making. The conjoint TNM System by the American Joint Committee on Cancer (AJCC) and the International Union Against Cancer (UICC) has served as the global standard for tumor classification since inception.
基金The National Natural Science Foundation of China(No.52107039)the Fujian Provincial Natural Science Foundation for Youth(No.2021J05133)the Key Project of the National Natural Science Foundation of China(No.51937002)。
文摘The axial field hybrid permanent magnet memory machine(AFHPM-MM)employs a hybrid permanent magnet excitation combining NdFeB and AlNiCo,achieving high torque density and a wide flux adjustment range.A separated stator structure is adopted to enhance its antidemagnetization capability.To analyze the contributions of AlNiCo and NdFeB to the induced electromotive force(EMF)in the AFHPM-MM,a frozen permeability-based induced EMF calculation method is proposed.Theoretical analysis reveals that the conventional method exhibits substantial errors in calculating the AlNiCo-induced EMF,primarily attributed to its failure to adequately account for the dynamic magnetization characteristic discrepancies of AlNiCo under varying magnetization states.Through the analysis of magnetization variations in AlNiCo during the flux adjustment process under different magnetization states,an improved induced EMF calculation method is proposed.Comparative results indicate that,during the flux enhancement process,the average calculation error of the AlNiCo-induced EMF is reduced from 19.84%to 2.09%,whereas during the flux weakening process,the error is reduced from 3.87%to 1.67%.The proposed method achieves accurate induced EMF calculation for the AFHPM-MM.
基金Supported by National Key R&D Program of China(Grant No.2022YFB3404101)National Natural Science Foundation of China(Grant Nos.52375018,92148301)。
文摘Accurate kinematic calibration is the very foundation for robots'application in industry demanding high precision such as machining.Considering the complex error characteristic and severe ill-posed identification issues of a 5-DoF parallel machining robot,this paper proposes an adaptive and weighted identification method to achieve high-precision kinematic calibration while maintaining reliable stability.First,a kinematic error propagation mechanism model considering the non-ideal constraints and the screw self-rotation is formulated by incorporating the intricate structure of multiple chains and a unique driven screw arrangement of the robot.To address the challenge of accurately identifying such a sophisticated error model,a novel adaptive and weighted identification method based on generalized cross validation(GCV)is proposed.Specifically,this approach innovatively introduces Gauss-Markov estimation into the GCV algorithm and utilizes prior physical information to construct both a weighted identification model and a weighted cross-validation function,thus eliminating the inaccuracy caused by significant differences in dimensional magnitudes of pose errors and achieving accurate identification with flexible numerical stability.Finally,the kinematic calibration experiment is conducted.The comparative experimental results demonstrate that the presented approach is effective and has enhanced accuracy performance over typical least squares methods,with maximum position and orientation errors reduced from 2.279 mm to 0.028 mm and from 0.206°to 0.017°,respectively.
基金supported inpart by the National Natural Science Foundation of China(Grant No. 12371088)the Innovative Research Group Project of Natural Science Foundation of Hunan Provinceof China (Grant No. 2024JJ1008)in part by the Australian Research Council (ARC) through the Discovery Projects scheme (Grant No. DP220100580)。
文摘Accurately modeling real network dynamics is a grand challenge in network science.The network dynamics arise from node interactions,which are shaped by network topology.Real networks tend to exhibit compact or highly optimized topologies.But the key problems arise:how to compress a network to best enhance its compactness,and what the compression limit of the network reflects?We abstract the topological compression of complex networks as a dynamic process of making them more compact and propose the local compression modulus that plays a key role in effective compression evolution of networks.Subsequently,we identify topological compressibility-a general property of complex networks that characterizes the extent to which a network can be compressed-and provide its approximate quantification.We anticipate that our findings and established theory will provide valuable insights into both dynamics and various applications of complex networks.
基金supported by the Shandong Provincial Natural Science Foundation(ZR2023QF092)the National Natural Science Foundation of China(62373224).
文摘Dear Editor,This letter introduces an innovative event-triggered secondary control strategy for Microgrid(MG)to address challenges of low inertia and renewable energy integration.Utilizing semi-Markov switching topologies,this method employs semi-Markov jump processes for accurate load forecasting,facilitating adaptive adjustments of distributed generators(DGs)in response to load changes.
基金funded by the Jiangsu Province Postgraduate Scientific Research and Practice Innovation Program(SJCX240449)projectthe Nanjing University of Information Science and Technology Talent Startup Fund(2022r078).
文摘Camera Pose Estimating from point and line correspondences is critical in various applications,including robotics,augmented reality,3D reconstruction,and autonomous navigation.Existing methods,such as the Perspective-n-Point(PnP)and Perspective-n-Line(PnL)approaches,offer limited accuracy and robustness in environments with occlusions,noise,or sparse feature data.This paper presents a unified solution,Efficient and Accurate Pose Estimation from Point and Line Correspondences(EAPnPL),combining point-based and linebased constraints to improve pose estimation accuracy and computational efficiency,particularly in low-altitude UAV navigation and obstacle avoidance.The proposed method utilizes quaternion parameterization of the rotation matrix to overcome singularity issues and address challenges in traditional rotation matrix-based formulations.A hybrid optimization framework is developed to integrate both point and line constraints,providing a more robust and stable solution in complex scenarios.The method is evaluated using synthetic and realworld datasets,demonstrating significant improvements in performance over existing techniques.The results indicate that the EAPnPL method enhances accuracy and reduces computational complexity,making it suitable for real-time applications in autonomous UAV systems.This approach offers a promising solution to the limitations of existing camera pose estimation methods,with potential applications in low-altitude navigation,autonomous robotics,and 3D scene reconstruction.
文摘Objective:To investigate the impact of precise nursing care based on dynamic nursing quality feedback model on the postoperative recovery of elderly patients undergoing radical resection for colon cancer,with a particular focus on its effects on psychological flexibility.Methods:Medical records of 124 elderly patients undergoing radical resection for colon cancer at The First Affiliated Hospital of Baotou Medical College between January 2021 and May 2024 were retrospectively analyzed in this study.Based on the received nursing interventions,the patients were divided into a control group(standard nursing care)and an observation group(precise nursing care based on a dynamic nursing quality feedback model).Results:The observation group exhibited significantly higher levels of hemoglobin,prealbumin,and albumin compared to the control group.Additionally,the observation group had lower scores in somatization,interpersonal sensitivity,depression,anxiety,obsessions-compulsions,hostility,phobic anxiety,psychoticism,and paranoid ideation.The observation group also demonstrated higher scores in active coping,self-efficacy,and the management of emotions,life,and symptoms.Improvements were also observed in nursing quality,perioperative intervention,satisfaction with rehabilitation guidance,and awareness of regular reexaminations,diet intervention,and complication prevention(all with P<0.05).Conclusion:Precise nursing based on a dynamic nursing quality feedback model can improve nutritional status and medical coping style,reduce psychological issues,and enhance self-management abilities in elderly patients following radical resection of colon cancer.Additionally,it increases nursing satisfaction and raises awareness regarding the importance of regular reexaminations and complication prevention.
基金supported by the Startup Grant(PG18929)awarded to F.Shokoohi.
文摘Accurate Electric Load Forecasting(ELF)is crucial for optimizing production capacity,improving operational efficiency,and managing energy resources effectively.Moreover,precise ELF contributes to a smaller environmental footprint by reducing the risks of disruption,downtime,and waste.However,with increasingly complex energy consumption patterns driven by renewable energy integration and changing consumer behaviors,no single approach has emerged as universally effective.In response,this research presents a hybrid modeling framework that combines the strengths of Random Forest(RF)and Autoregressive Integrated Moving Average(ARIMA)models,enhanced with advanced feature selection—Minimum Redundancy Maximum Relevancy and Maximum Synergy(MRMRMS)method—to produce a sparse model.Additionally,the residual patterns are analyzed to enhance forecast accuracy.High-resolution weather data from Weather Underground and historical energy consumption data from PJM for Duke Energy Ohio and Kentucky(DEO&K)are used in this application.This methodology,termed SP-RF-ARIMA,is evaluated against existing approaches;it demonstrates more than 40%reduction in mean absolute error and root mean square error compared to the second-best method.
基金Project(51274250)supported by the National Natural Science Foundation of ChinaProject(2012BAK09B02-05)supported by the National Key Technology R&D Program during the 12th Five-year Plan of China
文摘An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.
基金This work was supported by the National Natural Sci- ence Foundation of China （No.20903002, No.21273211, No.9112T042, and No.21373194） and the Anhui Provin- cial Natural Science Foundation （No.1408085MA18）, and the National Key Basic Research Special Founda- tion （No.2013CB834602 and No.2010CB923300）.
文摘The Raman depolarization ratios of gaseous CO2 in the spectral range of 1240-1430 cm-I are determined with a sensitive photoacoustic Raman spectroscopy, and more accurate data compared to the literature results are presented. The precision of the obtained depolarization ratio is achieved by measuring and fitting the dependence of the PARS signal intensity on the cross angle between the polarizations of two incident laser beams.
基金financial support of the National Key Technology Research and Development Program(2012BAD29B01)the Key Basic Research Program(2015FY111200)of the Ministry of Science and Technology,China.
文摘In this paper,we report the construction of two accurate mass databases and the development of a combination detection method that simultaneously screens for 733 pesticide and chemical contaminant multi-residues via high-throughput liquid chromatography(LC)-and gas chromatography(GC)-quadru pole-time-of-flight mass spectrometry(Q-TOFMS).This work demonstrates that electronic mass spectral standards may replace chemical-source standard materials as references through one sample preparation and the combination of GC/LC-Q-TOFMS screening.This cutting-edge technique has also replaced multiresidue determination using targeted detection with non-targeted screening.The pesticide residue types,sensitivity,recovery,and reproducibility of this combination technique are evaluated in eight fruit and vegetable matrices.This technique shows three advantages:①In comparison with the discovery capability of a single technique,the combination technique shows an improvement of 51.1%(GC-QTOFMS)and 39.6%(LC-Q-TOFMS),respectively;②the combination technique can satisfy a screening limit lower than 10μg·kg^-1 and meet the requirements of“uniform standards,”although some of the pesticide residues could be optimized to further improve screening sensitivity;③over 488 pesticides with recoveries between 60%-120%and relative standard deviation(RSD)<20%at a spiked level of 10μg·kg^-1 were detected with the combination technique in eight different matrices.From 2012 to 2017,this combination technique was applied in an investigation to screen pesticide residues from 1384 sampling locations for 38138 batched samples covering 18 categories and 134 types of fruits and vegetables obtained from across the mainland of China.After statistical analysis,533 pesticides in 115891 determinations were detected,and the regularity of pesticides in the fruits and vegetables sold on the Chinese market was shown.
文摘The Ordos basin is a stable craton whose late Paleozoic undergoes two sedimentary stages: from the middle- late Carboniferous offshore plain to the Permian continental river and lake delta. Sandstones in delta plain channels, delta-front river mouth bars and tidal channels are well developed. The sandstones are distributed on or between the genetic source rocks, forming good gas source conditions with widespread subtle lithologic gas pools of low porosity, low permeability, low pressure and low abundance. In recent years, a series of experiments has been done, aimed at overcoming difficulties in the exploration of lithologic gas pools. A set of exploration techniques, focusing on geological appraisal, seismic exploration, accurate logging evaluation and interpretation, well testing fracturing, has been developed to guide the exploration into the upper Paleozoic in the basin, leading to the discoveries of four large gas fields: Sulige, Yulin, Wushenqi and Mizhi.
基金Project supported by the Young Scientists Fund of the National Natural Science Foundation of China(Grant No.61205151)the National Key Scientific Instrument and Equipment Development Project of China(Grant No.2014YQ060537)the National Basic Research Program,China(Grant No.2013CB632803)
文摘An improved algebraic reconstruction technique（ART） combined with tunable diode laser absorption spectroscopy（TDLAS） is presented in this paper for determining two-dimensional（2D） distribution of H2O concentration and temperature in a simulated combustion flame.This work aims to simulate the reconstruction of spectroscopic measurements by a multi-view parallel-beam scanning geometry and analyze the effects of projection rays on reconstruction accuracy.It finally proves that reconstruction quality dramatically increases with the number of projection rays increasing until more than 180 for 20 × 20 grid,and after that point,the number of projection rays has little influence on reconstruction accuracy.It is clear that the temperature reconstruction results are more accurate than the water vapor concentration obtained by the traditional concentration calculation method.In the present study an innovative way to reduce the error of concentration reconstruction and improve the reconstruction quality greatly is also proposed,and the capability of this new method is evaluated by using appropriate assessment parameters.By using this new approach,not only the concentration reconstruction accuracy is greatly improved,but also a suitable parallel-beam arrangement is put forward for high reconstruction accuracy and simplicity of experimental validation.Finally,a bimodal structure of the combustion region is assumed to demonstrate the robustness and universality of the proposed method.Numerical investigation indicates that the proposed TDLAS tomographic algorithm is capable of detecting accurate temperature and concentration profiles.This feasible formula for reconstruction research is expected to resolve several key issues in practical combustion devices.
文摘Accurate diagnosis of tumors needs much detailed information. However, available single imaging modality cannot provide complete or comprehensive data. Nanomedicine is the application of nanotechnology to medicine, and multimodality imaging based on nanoparticles has been receiving extensive attention. This new hybrid imaging technology could provide complementary information from different imaging modalities using only a single injection of contrast agent. In this review, we introduce recent developments in multifunctional nanoparticles and their biomedical applications to multimodal imaging and theragnosis as nanomedicine. Most of the reviewed studies are based on the intrinsic properties of nanoparticles and their application in clinical imaging technology. The imaging techniques include positron emission tomography, single-photon emission computed tomography, computerized tomography, magnetic resonance imaging, optical imaging, and ultrasound imaging.
