Dear Editor,Linear and whorled nevoid hypermelanosis(LWNH)is a rare,sporadic pigmentary disorder characterized by hyperpigmented macules arranged in linear streaks and whorls along Blaschko's lines,typically appea...Dear Editor,Linear and whorled nevoid hypermelanosis(LWNH)is a rare,sporadic pigmentary disorder characterized by hyperpigmented macules arranged in linear streaks and whorls along Blaschko's lines,typically appearing within the first few weeks of life[1],and remains a challenge to treat.Here,we report a case of LWNH and review the relevant literature to help clinicians better understand this disease.展开更多
Integrated environmental management is important for sustainable development.Under China’s“Three Lines One Permit”(TLOP)policy,three types of management zones—priority protection,critical control,and general contr...Integrated environmental management is important for sustainable development.Under China’s“Three Lines One Permit”(TLOP)policy,three types of management zones—priority protection,critical control,and general control zones—are established based on the ecological red line,the lower-limit line for environmental quality,and the resource use line.Human activities are regulated through a permit system.Integrated and multifactorial protection of soil,plant,hydrological,and atmospheric elements is promoted at the regional level.A follow-up assessment contributes to the improvement of policy implementation and effectiveness.This study demonstrates the achievements of the TLOP policy in Sichuan Province.Results show that(1)276 protection zones have been established under the ecological red line,covering key ecosystems and protected areas to ensure environmental security.Under the lower-limit line,1,626 functional(priority,key,and general control)zones have been designated to regulate air,water,and soil quality,enhancing environmental capacity and pollution control.(2)Through the integration and merging of the three lines,1,128 integrated management zones have been established,including 375,625,and 128 priority protection,critical control,and general control zones,respectively.Each zone has its own list of environmental permits to regulate human activities according to different environmental protection and natural resource development regimes.(3)The design of the follow-up assessment index system was informed by regional primary functions and industrial structure.The index system for provinces and cities is structured around three primary indicators—implementation updating,application,and guarantees—and 15 secondary indicators.The system for critical control zones is structured around environmental access,management,and effectiveness and 14 secondary indicators.A stringent environmental zoning system has been established through the TLOP policy,thereby safeguarding environmental security,promoting harmonious existence between humans and nature,and supporting the vision of Beautiful China.展开更多
Traveling wave(TW)fault location technology has been widely used in transmission systems due to its high accuracy and simplicity.Recently,there has been growing interest in applying this technology to medium voltage(M...Traveling wave(TW)fault location technology has been widely used in transmission systems due to its high accuracy and simplicity.Recently,there has been growing interest in applying this technology to medium voltage(MV)distribution lines.However,current practices in its deployment,signal measurement,and threshold setting are usually from the application experiences in transmission lines,despite significant differences in fault-induced wave characteristics between transmission and distribution systems.To address these issues,this paper investigates the feasibility and applicability of TW fault technology in MV overhead distribution lines through characteristic analysis of fault-induced TWs.The propagation characteristics of aerial mode and zero mode TWs on overhead distribution lines are studied.Furthermore,it evaluates the influence of critical distri-bution network components including distribution transformers,multi-branch configurations,and busbar structures on wave propagation characteristics.Deployment strategies for traveling wave fault location(TWFL)devices is proposed to address the unique challenges of distribution networks,while the fault location method is also improved.Field test results demonstrate the effectiveness of the proposed methodology,showing improved fault detection accuracy and system reliability in distri-bution network applications.This research provides practical implementation suggestions for TWFL technology in distribution networks.展开更多
The atom-bond sum-connectivity(ABS)index,put forward by[J.Math.Chem.,2022,60(10):20812093],exhibits a strong link with the acentric factor of octane isomers.The experimental physico-chemical properties of octane isome...The atom-bond sum-connectivity(ABS)index,put forward by[J.Math.Chem.,2022,60(10):20812093],exhibits a strong link with the acentric factor of octane isomers.The experimental physico-chemical properties of octane isomers,such as boiling point,of formation are found to be better measured by the ABS index than by the Randi,atom-bond connectivity(ABC),and sum-connectivity(SC)indices.One important source of information for researching the molecular structure is the bounds for its topological indices.The extrema of the ABS index of the line,total,and Mycielski graphs are calculated in this work.Moreover,the pertinent extremal graphs were illustrated.展开更多
The two-dimensional grating serves as a critical component in plane grating interferometers for achieving high-precision multidimensional displacement measurements.The calibration of grating groove density and orthogo...The two-dimensional grating serves as a critical component in plane grating interferometers for achieving high-precision multidimensional displacement measurements.The calibration of grating groove density and orthogonality error of grating grooves not only improves the positioning accuracy of grating interferometers but also provides essential feedback for optimizing two-dimensional grating fabrication.This study proposes a method for simultaneous calibration of these parameters using orthogonal heterodyne laser interferometry.A two-dimensional grating interferometer is built with the grating to be measured,and a biaxial laser interferometer provides a displacement reference for it.The phase mapping relationship between grating interference and laser interference is established.The interference phase information obtained by any two displacements can simultaneously solve the above three parameters and obtain the grating installation error.The feasibility of the proposed method is verified by using a 1200 gr/mm two-dimensional grating.The standard deviation of the grating groove density in the X and Y directions is 0.012 gr/mm and 0.014 gr/mm,respectively.The standard deviation of the orthogonality error of grating grooves is 0.004°,and the standard deviation of the installation error is 0.002°.Compared with the atomic force microscope method,the consistency of the grating groove density in the X and Y directions is better than 0.03 gr/mm and 0.06 gr/mm,and the orthogonality error of grating grooves is better than 0.008°.The experimental results show that the proposed method can be simply and efficiently applied to the calibration of the grating line parameters of the two-dimensional grating.展开更多
With the continuous development of artificial intelligence and computer vision technology,numerous deep learning-based lane line detection methods have emerged.DeepLabv3+,as a classic semantic segmentation model,has f...With the continuous development of artificial intelligence and computer vision technology,numerous deep learning-based lane line detection methods have emerged.DeepLabv3+,as a classic semantic segmentation model,has found widespread application in the field of lane line detection.However,the accuracy of lane line segmentation is often compromised by factors such as changes in lighting conditions,occlusions,and wear and tear on the lane lines.Additionally,DeepLabv3+suffers from high memory consumption and challenges in deployment on embedded platforms.To address these issues,this paper proposes a lane line detection method for complex road scenes based on DeepLabv3+and MobileNetV4(MNv4).First,the lightweight MNv4 is adopted as the backbone network,and the standard convolutions in ASPP are replaced with depthwise separable convolutions.Second,a polarization attention mechanism is introduced after the ASPP module to enhance the model’s generalization capability.Finally,the Simple Linear Iterative Clustering(SLIC)superpixel segmentation algorithmis employed to preserve lane line edge information.MNv4-DeepLabv3+was tested on the TuSimple and CULane datasets.On the TuSimple dataset,theMean Intersection over Union(MIoU)and Mean Pixel Accuracy(mPA)improved by 1.01%and 7.49%,respectively.On the CULane dataset,MIoU andmPA increased by 3.33%and 7.74%,respectively.Thenumber of parameters decreased from 54.84 to 3.19 M.Experimental results demonstrate that MNv4-DeepLabv3+significantly optimizes model parameter count and enhances segmentation accuracy.展开更多
Intelligent inspection of transmission lines enables efficient automated fault detection by integrating artificial intelligence,robotics,and other related technologies.It plays a key role in ensuring power grid safety...Intelligent inspection of transmission lines enables efficient automated fault detection by integrating artificial intelligence,robotics,and other related technologies.It plays a key role in ensuring power grid safety,reducing operation and maintenance costs,driving the digital transformation of the power industry,and facilitating the achievement of the dual-carbon goals.This review focuses on vision-based power line inspection,with deep learning as the core perspective to systematically analyze the latest research advancements in this field.Firstly,at the technical foundation level,it elaborates on deep learning algorithms for intelligent transmission line inspection based on image perception,covering object detection algorithms,semantic segmentation algorithms,and other relevant methodologies.Secondly,in application practice,it summarizes deep learning-based intelligent inspection applications across six dimensions—including detection of power insulators and their defects,transmission tower detection,power line feature extraction,metal fitting and defect detection,thermal fault diagnosis of power components,and safety hazard detection in power scenarios,and further lists relevant public datasets.Finally,in response to current challenges,it identifies five key future research directions,such as the deep integration of multiple learning paradigms,multi-modal data fusion,collaborative application of large and small models,cloud-edge-end collaborative integration,and multi-agent cluster control.This paper reviews and analyzes numerous deep learning-based intelligent detectionmethods for aerial images,comprehensively explores the application of deep learning in Unmanned Aerial Vehicle(UAV)inspection scenarios,and thus provides valuable theoretical and practical references for scholars engaged in smart grid automated inspection research.展开更多
Owing to its large aperture and advanced receivers,research plans for the Qitai 110 m radio telescope(QTT)include a variety of spectral line scientific studies.Sequential construction of receiver systems and multidisc...Owing to its large aperture and advanced receivers,research plans for the Qitai 110 m radio telescope(QTT)include a variety of spectral line scientific studies.Sequential construction of receiver systems and multidisciplinary planning require overcoming serious challenges to spectral line digital backend development,notably to digitize,process,and transmit considerable quantities of observational data,to minimize time-to-science with an easily scalable architecture,and to provide robust,high-quality data.As a proof-of-concept for the QTT backend,here we implement a baseband spectral line digital backend with a SNAP+GPU architecture.The SNAP-based digital frontend comprises two digitization links(1000 MHz,8-bit),two parallel quad-channel preprocessing modules,a quantization module,and a finite-state packaging module,generating a 100-MHz bandwidth digital link from the original analog signal through high-speed Ethernet transmission.The GPU node receives preprocessed baseband packets,constructs a ring buffer for lossless unpacking and distributing,with real-time data reception and caching,and conducts real-time spectral analysis(frequency resolution:3.051 kHz)of the 100 MHz baseband data.We evaluated system performance experimentally using spectral line observations with the Nanshan 26-m radio telescope(NSRT).For the QTT,the SNAP digital frontend will be seamlessly migrated to a radio frequency system-on-chip(RFSoC)architecture,resulting in five-and tenfold increases in instantaneous bandwidth and data throughput,respectively.The low-coupling digital frontend and GPU node can be easily extended to multiple nodes.展开更多
Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in oper...Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in operator workloads and significantly increase the complexity of scheduling.To address this challenge,this study investigates the Aircraft Pulsating Assembly Line Scheduling Problem(APALSP)under skilled operator allocation,with the objective of minimizing assembly completion time.A mathematical model considering skilled operator allocation is developed,and a Q-Learning improved Particle Swarm Optimization algorithm(QLPSO)is proposed.In the algorithm design,a reverse scheduling strategy is adopted to effectively manage large-scale precedence constraints.Moreover,a reverse sequence encoding method is introduced to generate operation sequences,while a time decoding mechanism is employed to determine completion times.The problem is further reformulated as a Markov Decision Process(MDP)with explicitly defined state and action spaces.Within QLPSO,the Q-learning mechanism adaptively adjusts inertia weights and learning factors,thereby achieving a balance between exploration capability and convergence performance.To validate the effectiveness of the proposed approach,extensive computational experiments are conducted on benchmark instances of different scales,including small,medium,large,and ultra-large cases.The results demonstrate that QLPSO consistently delivers stable and high-quality solutions across all scenarios.In ultra-large-scale instances,it improves the best solution by 25.2%compared with the Genetic Algorithm(GA)and enhances the average solution by 16.9%over the Q-learning algorithm,showing clear advantages over the comparative methods.These findings not only confirm the effectiveness of the proposed algorithm but also provide valuable theoretical references and practical guidance for the intelligent scheduling optimization of aircraft pulsating assembly lines.展开更多
Thinopyrum ponticum(2n=10×=70),a wild relative of common wheat(Triticum aestivum L.),is considered an invaluable genetic resource for wheat improvement due to its abundance of genes conferring resistance to bioti...Thinopyrum ponticum(2n=10×=70),a wild relative of common wheat(Triticum aestivum L.),is considered an invaluable genetic resource for wheat improvement due to its abundance of genes conferring resistance to biotic and abiotic stresses.This study focused on the CH97 line,derived from the BC1F7 progeny of a cross between wheat cv.7182 and Th.ponticum.Cytological evidence showed that CH97 has 42 chromosomes,forming 21 bivalents at meiotic metaphase I,with the bivalents subsequently separating and moving to opposite poles during meiotic anaphase I.Through a combination of fluorescence in situ hybridization(FISH),genomic in situ hybridization(GISH),multicolor GISH(mc-GISH),and liquid array analysis,it was determined that CH97 comprises 40 wheat chromosomes and two alien chromosomes from the Ee genome of Th.ponticum,featuring the absence of a pair of 5D chromosomes and variations in 1B,6B,and 7B chromosomes.These findings confirm that CH97 is a stable wheat-Th.ponticum 5E(5D)alien disomic substitution line.Inoculation experiments revealed that CH97 exhibits high resistance to wheat powdery mildew and stripe rust throughout the growth period,in contrast to the highly susceptible common wheat parent 7182.Compared to 7182,CH97 displayed improvements in thousand-kernel weight and kernel length.Additionally,utilizing specific-locus amplified fragment sequencing(SLAF-seq)technology,chromosome 5E-specific molecular markers were developed and validated,achieving a 33.3% success rate,facilitating marker-assisted selection for disease resistance in wheat.Overall,the CH97 substitution line,with its resistance to diseases and improved agronomic traits,represents valuable new germplasm for wheat chromosome engineering and breeding.展开更多
Grinding technology is widely applied in the manufacturing and mechanical processing sectors.Different from conventional three-dimensional rough surface friction models,ground metals exhibit a striated surface morphol...Grinding technology is widely applied in the manufacturing and mechanical processing sectors.Different from conventional three-dimensional rough surface friction models,ground metals exhibit a striated surface morphology,which can be simplified as a two-dimensional plane strain friction issue.Due to surface morphology diversity and loading condition complexity,numerical modeling and experimental approaches have difficulty achieving rapid prediction of line-contact surface friction behavior.Therefore,this study innovatively proposes a hybrid physics-data-driven model integrating finite element analysis(FEA)with machine learning(ML),enabling efficient and accurate prediction of line-contact friction behavior on two-dimensional rough surfaces.An extensive friction behavior database was generated through finite element simulations.Based on this dataset,the random forest(RF)algorithm was used to achieve high-precision prediction of the friction coefficient.Furthermore,a comprehensive analysis was performed on the effects of surface roughness,normal load,yield strength,and local friction coefficient on friction behavior.The RF model exhibits excellent performance in predicting friction coefficients and also accurately identifies the most influential features governing friction behavior.Residual analysis further verifies our model’s reliability,as the RF predictions agree with the FEA results,demonstrating remarkable adaptability and accuracy.Feature importance analysis results reveal that the local friction coefficient and normal load are the main factors influencing friction behavior,but the surface roughness and yield strength exhibit a relatively minor influence.The study innovatively identifies the coupling effects of key parameters through contour maps.Namely,the influence of local friction coefficient decreases with increasing normal load but becomes significantly more pronounced with elevated material yield strength.By integrating ML,our proposed model maintains the high accuracy of FEA while capturing the complexity of interfacial responses through data-driven approaches.Our study advances traditional tribological research from“experience-driven”to“data-intelligence-driven,”thus providing novel insights for understanding and predicting complex friction behaviors,as well as for optimizing frictional design in engineering applications.展开更多
On November 26th,Zhengzhou Textile Machinery Co.,Ltd.(hereinafter referred to as"ZFJ")signed an order for a high-speed intelligent wide-width wetmethod spunlace production line with Hubei Lijie New Material ...On November 26th,Zhengzhou Textile Machinery Co.,Ltd.(hereinafter referred to as"ZFJ")signed an order for a high-speed intelligent wide-width wetmethod spunlace production line with Hubei Lijie New Material Technology Co.,Ltd.(hereinafter referred to as"Hubei Lijie").This cooperation marks a further consolidation of ZFJ's leading position in the nonwoven fabric equipment market in Hubei Province and lays a solid foundation for deeper cooperation between the two companies in the future.展开更多
Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone t...Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.展开更多
To address the issue of inconsistent image quality and data scarcity in bolt defect detection for transmission lines,this paper proposes an improved sparse region-based convolutional neural network(RCNN) based detecti...To address the issue of inconsistent image quality and data scarcity in bolt defect detection for transmission lines,this paper proposes an improved sparse region-based convolutional neural network(RCNN) based detection framework integrating image quality evaluation and text-to-image data augmentation.First,a HyperNetwork-based image quality assessment module is introduced to filter low-quality inspection images in terms of clarity and structural integrity,resulting in a high-quality training dataset.Second,a text-to-image diffusion model is utilized for sample augmentation.By designing text prompts that describe various bolt defect types under diverse lighting and viewing conditions,the model automatically generates realistic synthetic samples.The generated images are further filtered using a combination of quality and perceptual similarity metrics to ensure consistency with the real data distribution.Building upon the sparse RCNN baseline,a dynamic label assignment mechanism and a random decision path detection head are incorporated to enhance bounding box matching and prediction accuracy.Experimental results demonstrate that the proposed method significantly improves detection accuracy(mAP@0.5) over the original sparse RCNN while maintaining low computational cost,enabling more efficient and intelligent inspection of transmission line components.展开更多
Microstrip transmission lines connecting to the millimeter wave radar chip and antenna significantly affect the radiation efficiency and bandwidth of the antenna.Here,a wideband non-uniform wavy microstrip line for co...Microstrip transmission lines connecting to the millimeter wave radar chip and antenna significantly affect the radiation efficiency and bandwidth of the antenna.Here,a wideband non-uniform wavy microstrip line for complex impedance in automotive radar frequency range is proposed.Unlike the gradient transmission line,the wavy structure is composed of periodically semi-circular segments.By adjusting the radius of the semi-circular,the surface current is varied and concentrated on the semi-circular segments,allowing a wider tunability range of the resonant frequency.The results reveal that the bandwidth of the loaded wavy transmission line antenna improves to 9.37 GHz,which is 5.81 GHz wider than that of the loaded gradient line.The gain and the half power beam width of the loaded antenna are about 14.69 dB and 9.58°,respectively.The proposed non-uniform microstrip line scheme may open up a route for realizing wideband millimeter-wave automotive radar applications.展开更多
We report the fabrication of an 8-meter-long thin-flm lithium niobate optical true delay line using the photolithography-assisted chemomechanical etching technique,showing a low transmission loss of 0.036 dB/cm in the...We report the fabrication of an 8-meter-long thin-flm lithium niobate optical true delay line using the photolithography-assisted chemomechanical etching technique,showing a low transmission loss of 0.036 dB/cm in the conventional telecom band.展开更多
Sea lines of communication(SLOCs)security has long been a strategic concern for major powers.Following the establishment of the People’s Republic of China,the country’s focus was on the traditional security aspects ...Sea lines of communication(SLOCs)security has long been a strategic concern for major powers.Following the establishment of the People’s Republic of China,the country’s focus was on the traditional security aspects of its SLOCs.Since the reform and opening-up era-and especially after the end of the Cold War-China has shifted its emphasis toward economic security.China’s SLOCs security bears on multiple dimensions of a holistic approach to national security,encompassing economic security,the safety of its citizens.展开更多
We present a compact optical delay line(ODL)with wide-range continuous tunability on thin-film lithium niobate platform.The proposed device integrates an unbalanced Mach-Zehnder interferometer(MZI)architecture with du...We present a compact optical delay line(ODL)with wide-range continuous tunability on thin-film lithium niobate platform.The proposed device integrates an unbalanced Mach-Zehnder interferometer(MZI)architecture with dual tunable couplers,where each coupler comprises two 2×2 multimode interferometers and a MZI phase-tuning section.Experimental results demonstrate continuous delay tuning from 0 to 293 ps through synchronized control of coupling coefficients,corresponding to a 4 cm path difference between interferometer arms.The measured delay range exhibits excellent agreement with theoretical predictions derived from ODL waveguide parameters.This result addresses critical challenges in integrated photonic systems that require precise temporal control,particularly for applications in optical communications and quantum information processing,where a wide tuning range is paramount.展开更多
文摘Dear Editor,Linear and whorled nevoid hypermelanosis(LWNH)is a rare,sporadic pigmentary disorder characterized by hyperpigmented macules arranged in linear streaks and whorls along Blaschko's lines,typically appearing within the first few weeks of life[1],and remains a challenge to treat.Here,we report a case of LWNH and review the relevant literature to help clinicians better understand this disease.
基金supported by the National Natural Science Foundation of China(grant numbers 42171085)and the National Key R&D Program of China(Grant No.2024YFF1307801,2024YFF1307804).
文摘Integrated environmental management is important for sustainable development.Under China’s“Three Lines One Permit”(TLOP)policy,three types of management zones—priority protection,critical control,and general control zones—are established based on the ecological red line,the lower-limit line for environmental quality,and the resource use line.Human activities are regulated through a permit system.Integrated and multifactorial protection of soil,plant,hydrological,and atmospheric elements is promoted at the regional level.A follow-up assessment contributes to the improvement of policy implementation and effectiveness.This study demonstrates the achievements of the TLOP policy in Sichuan Province.Results show that(1)276 protection zones have been established under the ecological red line,covering key ecosystems and protected areas to ensure environmental security.Under the lower-limit line,1,626 functional(priority,key,and general control)zones have been designated to regulate air,water,and soil quality,enhancing environmental capacity and pollution control.(2)Through the integration and merging of the three lines,1,128 integrated management zones have been established,including 375,625,and 128 priority protection,critical control,and general control zones,respectively.Each zone has its own list of environmental permits to regulate human activities according to different environmental protection and natural resource development regimes.(3)The design of the follow-up assessment index system was informed by regional primary functions and industrial structure.The index system for provinces and cities is structured around three primary indicators—implementation updating,application,and guarantees—and 15 secondary indicators.The system for critical control zones is structured around environmental access,management,and effectiveness and 14 secondary indicators.A stringent environmental zoning system has been established through the TLOP policy,thereby safeguarding environmental security,promoting harmonious existence between humans and nature,and supporting the vision of Beautiful China.
基金supported by the National Natural Sci-ence Foundation of China(No.52107109).
文摘Traveling wave(TW)fault location technology has been widely used in transmission systems due to its high accuracy and simplicity.Recently,there has been growing interest in applying this technology to medium voltage(MV)distribution lines.However,current practices in its deployment,signal measurement,and threshold setting are usually from the application experiences in transmission lines,despite significant differences in fault-induced wave characteristics between transmission and distribution systems.To address these issues,this paper investigates the feasibility and applicability of TW fault technology in MV overhead distribution lines through characteristic analysis of fault-induced TWs.The propagation characteristics of aerial mode and zero mode TWs on overhead distribution lines are studied.Furthermore,it evaluates the influence of critical distri-bution network components including distribution transformers,multi-branch configurations,and busbar structures on wave propagation characteristics.Deployment strategies for traveling wave fault location(TWFL)devices is proposed to address the unique challenges of distribution networks,while the fault location method is also improved.Field test results demonstrate the effectiveness of the proposed methodology,showing improved fault detection accuracy and system reliability in distri-bution network applications.This research provides practical implementation suggestions for TWFL technology in distribution networks.
基金Supported by Ningbo NSF(No.2021J234)Zhejiang Provincial Philosophy and Social Sciences Planning Project(No.24NDJC057YB)。
文摘The atom-bond sum-connectivity(ABS)index,put forward by[J.Math.Chem.,2022,60(10):20812093],exhibits a strong link with the acentric factor of octane isomers.The experimental physico-chemical properties of octane isomers,such as boiling point,of formation are found to be better measured by the ABS index than by the Randi,atom-bond connectivity(ABC),and sum-connectivity(SC)indices.One important source of information for researching the molecular structure is the bounds for its topological indices.The extrema of the ABS index of the line,total,and Mycielski graphs are calculated in this work.Moreover,the pertinent extremal graphs were illustrated.
文摘The two-dimensional grating serves as a critical component in plane grating interferometers for achieving high-precision multidimensional displacement measurements.The calibration of grating groove density and orthogonality error of grating grooves not only improves the positioning accuracy of grating interferometers but also provides essential feedback for optimizing two-dimensional grating fabrication.This study proposes a method for simultaneous calibration of these parameters using orthogonal heterodyne laser interferometry.A two-dimensional grating interferometer is built with the grating to be measured,and a biaxial laser interferometer provides a displacement reference for it.The phase mapping relationship between grating interference and laser interference is established.The interference phase information obtained by any two displacements can simultaneously solve the above three parameters and obtain the grating installation error.The feasibility of the proposed method is verified by using a 1200 gr/mm two-dimensional grating.The standard deviation of the grating groove density in the X and Y directions is 0.012 gr/mm and 0.014 gr/mm,respectively.The standard deviation of the orthogonality error of grating grooves is 0.004°,and the standard deviation of the installation error is 0.002°.Compared with the atomic force microscope method,the consistency of the grating groove density in the X and Y directions is better than 0.03 gr/mm and 0.06 gr/mm,and the orthogonality error of grating grooves is better than 0.008°.The experimental results show that the proposed method can be simply and efficiently applied to the calibration of the grating line parameters of the two-dimensional grating.
文摘With the continuous development of artificial intelligence and computer vision technology,numerous deep learning-based lane line detection methods have emerged.DeepLabv3+,as a classic semantic segmentation model,has found widespread application in the field of lane line detection.However,the accuracy of lane line segmentation is often compromised by factors such as changes in lighting conditions,occlusions,and wear and tear on the lane lines.Additionally,DeepLabv3+suffers from high memory consumption and challenges in deployment on embedded platforms.To address these issues,this paper proposes a lane line detection method for complex road scenes based on DeepLabv3+and MobileNetV4(MNv4).First,the lightweight MNv4 is adopted as the backbone network,and the standard convolutions in ASPP are replaced with depthwise separable convolutions.Second,a polarization attention mechanism is introduced after the ASPP module to enhance the model’s generalization capability.Finally,the Simple Linear Iterative Clustering(SLIC)superpixel segmentation algorithmis employed to preserve lane line edge information.MNv4-DeepLabv3+was tested on the TuSimple and CULane datasets.On the TuSimple dataset,theMean Intersection over Union(MIoU)and Mean Pixel Accuracy(mPA)improved by 1.01%and 7.49%,respectively.On the CULane dataset,MIoU andmPA increased by 3.33%and 7.74%,respectively.Thenumber of parameters decreased from 54.84 to 3.19 M.Experimental results demonstrate that MNv4-DeepLabv3+significantly optimizes model parameter count and enhances segmentation accuracy.
基金financially supported by theNatural Research Project of College in Anhui Province under grant 2024AH051365,2025AHGXZK30826Research Platform of New Energy and Energy-Saving Technology Research Center under grant KYJG002.
文摘Intelligent inspection of transmission lines enables efficient automated fault detection by integrating artificial intelligence,robotics,and other related technologies.It plays a key role in ensuring power grid safety,reducing operation and maintenance costs,driving the digital transformation of the power industry,and facilitating the achievement of the dual-carbon goals.This review focuses on vision-based power line inspection,with deep learning as the core perspective to systematically analyze the latest research advancements in this field.Firstly,at the technical foundation level,it elaborates on deep learning algorithms for intelligent transmission line inspection based on image perception,covering object detection algorithms,semantic segmentation algorithms,and other relevant methodologies.Secondly,in application practice,it summarizes deep learning-based intelligent inspection applications across six dimensions—including detection of power insulators and their defects,transmission tower detection,power line feature extraction,metal fitting and defect detection,thermal fault diagnosis of power components,and safety hazard detection in power scenarios,and further lists relevant public datasets.Finally,in response to current challenges,it identifies five key future research directions,such as the deep integration of multiple learning paradigms,multi-modal data fusion,collaborative application of large and small models,cloud-edge-end collaborative integration,and multi-agent cluster control.This paper reviews and analyzes numerous deep learning-based intelligent detectionmethods for aerial images,comprehensively explores the application of deep learning in Unmanned Aerial Vehicle(UAV)inspection scenarios,and thus provides valuable theoretical and practical references for scholars engaged in smart grid automated inspection research.
基金supported by the “Light in China’s Western Region” program (2022-XBQNXZ012)by the National Natural Science Foundation of China(12073067)
文摘Owing to its large aperture and advanced receivers,research plans for the Qitai 110 m radio telescope(QTT)include a variety of spectral line scientific studies.Sequential construction of receiver systems and multidisciplinary planning require overcoming serious challenges to spectral line digital backend development,notably to digitize,process,and transmit considerable quantities of observational data,to minimize time-to-science with an easily scalable architecture,and to provide robust,high-quality data.As a proof-of-concept for the QTT backend,here we implement a baseband spectral line digital backend with a SNAP+GPU architecture.The SNAP-based digital frontend comprises two digitization links(1000 MHz,8-bit),two parallel quad-channel preprocessing modules,a quantization module,and a finite-state packaging module,generating a 100-MHz bandwidth digital link from the original analog signal through high-speed Ethernet transmission.The GPU node receives preprocessed baseband packets,constructs a ring buffer for lossless unpacking and distributing,with real-time data reception and caching,and conducts real-time spectral analysis(frequency resolution:3.051 kHz)of the 100 MHz baseband data.We evaluated system performance experimentally using spectral line observations with the Nanshan 26-m radio telescope(NSRT).For the QTT,the SNAP digital frontend will be seamlessly migrated to a radio frequency system-on-chip(RFSoC)architecture,resulting in five-and tenfold increases in instantaneous bandwidth and data throughput,respectively.The low-coupling digital frontend and GPU node can be easily extended to multiple nodes.
基金supported by the National Natural Science Foundation of China(Grant No.52475543)Natural Science Foundation of Henan(Grant No.252300421101)+1 种基金Henan Province University Science and Technology Innovation Talent Support Plan(Grant No.24HASTIT048)Science and Technology Innovation Team Project of Zhengzhou University of Light Industry(Grant No.23XNKJTD0101).
文摘Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in operator workloads and significantly increase the complexity of scheduling.To address this challenge,this study investigates the Aircraft Pulsating Assembly Line Scheduling Problem(APALSP)under skilled operator allocation,with the objective of minimizing assembly completion time.A mathematical model considering skilled operator allocation is developed,and a Q-Learning improved Particle Swarm Optimization algorithm(QLPSO)is proposed.In the algorithm design,a reverse scheduling strategy is adopted to effectively manage large-scale precedence constraints.Moreover,a reverse sequence encoding method is introduced to generate operation sequences,while a time decoding mechanism is employed to determine completion times.The problem is further reformulated as a Markov Decision Process(MDP)with explicitly defined state and action spaces.Within QLPSO,the Q-learning mechanism adaptively adjusts inertia weights and learning factors,thereby achieving a balance between exploration capability and convergence performance.To validate the effectiveness of the proposed approach,extensive computational experiments are conducted on benchmark instances of different scales,including small,medium,large,and ultra-large cases.The results demonstrate that QLPSO consistently delivers stable and high-quality solutions across all scenarios.In ultra-large-scale instances,it improves the best solution by 25.2%compared with the Genetic Algorithm(GA)and enhances the average solution by 16.9%over the Q-learning algorithm,showing clear advantages over the comparative methods.These findings not only confirm the effectiveness of the proposed algorithm but also provide valuable theoretical references and practical guidance for the intelligent scheduling optimization of aircraft pulsating assembly lines.
基金funded by the Key R&D Program of Yangling Seed Industry Innovation,China(Ylzy-xm-02)the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(2021QNRC001)。
文摘Thinopyrum ponticum(2n=10×=70),a wild relative of common wheat(Triticum aestivum L.),is considered an invaluable genetic resource for wheat improvement due to its abundance of genes conferring resistance to biotic and abiotic stresses.This study focused on the CH97 line,derived from the BC1F7 progeny of a cross between wheat cv.7182 and Th.ponticum.Cytological evidence showed that CH97 has 42 chromosomes,forming 21 bivalents at meiotic metaphase I,with the bivalents subsequently separating and moving to opposite poles during meiotic anaphase I.Through a combination of fluorescence in situ hybridization(FISH),genomic in situ hybridization(GISH),multicolor GISH(mc-GISH),and liquid array analysis,it was determined that CH97 comprises 40 wheat chromosomes and two alien chromosomes from the Ee genome of Th.ponticum,featuring the absence of a pair of 5D chromosomes and variations in 1B,6B,and 7B chromosomes.These findings confirm that CH97 is a stable wheat-Th.ponticum 5E(5D)alien disomic substitution line.Inoculation experiments revealed that CH97 exhibits high resistance to wheat powdery mildew and stripe rust throughout the growth period,in contrast to the highly susceptible common wheat parent 7182.Compared to 7182,CH97 displayed improvements in thousand-kernel weight and kernel length.Additionally,utilizing specific-locus amplified fragment sequencing(SLAF-seq)technology,chromosome 5E-specific molecular markers were developed and validated,achieving a 33.3% success rate,facilitating marker-assisted selection for disease resistance in wheat.Overall,the CH97 substitution line,with its resistance to diseases and improved agronomic traits,represents valuable new germplasm for wheat chromosome engineering and breeding.
基金support from the National Natural Science Foundation of China(Grant Nos.12302097 and 12202007)the Postdoctoral Science Foundation of China for Innovative Talents(BX20220008).
文摘Grinding technology is widely applied in the manufacturing and mechanical processing sectors.Different from conventional three-dimensional rough surface friction models,ground metals exhibit a striated surface morphology,which can be simplified as a two-dimensional plane strain friction issue.Due to surface morphology diversity and loading condition complexity,numerical modeling and experimental approaches have difficulty achieving rapid prediction of line-contact surface friction behavior.Therefore,this study innovatively proposes a hybrid physics-data-driven model integrating finite element analysis(FEA)with machine learning(ML),enabling efficient and accurate prediction of line-contact friction behavior on two-dimensional rough surfaces.An extensive friction behavior database was generated through finite element simulations.Based on this dataset,the random forest(RF)algorithm was used to achieve high-precision prediction of the friction coefficient.Furthermore,a comprehensive analysis was performed on the effects of surface roughness,normal load,yield strength,and local friction coefficient on friction behavior.The RF model exhibits excellent performance in predicting friction coefficients and also accurately identifies the most influential features governing friction behavior.Residual analysis further verifies our model’s reliability,as the RF predictions agree with the FEA results,demonstrating remarkable adaptability and accuracy.Feature importance analysis results reveal that the local friction coefficient and normal load are the main factors influencing friction behavior,but the surface roughness and yield strength exhibit a relatively minor influence.The study innovatively identifies the coupling effects of key parameters through contour maps.Namely,the influence of local friction coefficient decreases with increasing normal load but becomes significantly more pronounced with elevated material yield strength.By integrating ML,our proposed model maintains the high accuracy of FEA while capturing the complexity of interfacial responses through data-driven approaches.Our study advances traditional tribological research from“experience-driven”to“data-intelligence-driven,”thus providing novel insights for understanding and predicting complex friction behaviors,as well as for optimizing frictional design in engineering applications.
文摘On November 26th,Zhengzhou Textile Machinery Co.,Ltd.(hereinafter referred to as"ZFJ")signed an order for a high-speed intelligent wide-width wetmethod spunlace production line with Hubei Lijie New Material Technology Co.,Ltd.(hereinafter referred to as"Hubei Lijie").This cooperation marks a further consolidation of ZFJ's leading position in the nonwoven fabric equipment market in Hubei Province and lays a solid foundation for deeper cooperation between the two companies in the future.
文摘Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.
基金Supported by the Science and Technology Project from State Grid Corporation of China (No.5700-202490330A-2-1-ZX)。
文摘To address the issue of inconsistent image quality and data scarcity in bolt defect detection for transmission lines,this paper proposes an improved sparse region-based convolutional neural network(RCNN) based detection framework integrating image quality evaluation and text-to-image data augmentation.First,a HyperNetwork-based image quality assessment module is introduced to filter low-quality inspection images in terms of clarity and structural integrity,resulting in a high-quality training dataset.Second,a text-to-image diffusion model is utilized for sample augmentation.By designing text prompts that describe various bolt defect types under diverse lighting and viewing conditions,the model automatically generates realistic synthetic samples.The generated images are further filtered using a combination of quality and perceptual similarity metrics to ensure consistency with the real data distribution.Building upon the sparse RCNN baseline,a dynamic label assignment mechanism and a random decision path detection head are incorporated to enhance bounding box matching and prediction accuracy.Experimental results demonstrate that the proposed method significantly improves detection accuracy(mAP@0.5) over the original sparse RCNN while maintaining low computational cost,enabling more efficient and intelligent inspection of transmission line components.
基金Supported by the National Natural Science Foundation of China( 61974104)。
文摘Microstrip transmission lines connecting to the millimeter wave radar chip and antenna significantly affect the radiation efficiency and bandwidth of the antenna.Here,a wideband non-uniform wavy microstrip line for complex impedance in automotive radar frequency range is proposed.Unlike the gradient transmission line,the wavy structure is composed of periodically semi-circular segments.By adjusting the radius of the semi-circular,the surface current is varied and concentrated on the semi-circular segments,allowing a wider tunability range of the resonant frequency.The results reveal that the bandwidth of the loaded wavy transmission line antenna improves to 9.37 GHz,which is 5.81 GHz wider than that of the loaded gradient line.The gain and the half power beam width of the loaded antenna are about 14.69 dB and 9.58°,respectively.The proposed non-uniform microstrip line scheme may open up a route for realizing wideband millimeter-wave automotive radar applications.
基金supported by the National Natural Science Foundation of China(Grant Nos.12192251,12334014,92480001,12134001,12304418,12274130,12274133,12474378,and 12404378)the National Key R&D Program of China(Grant Nos.2022YFA1404600 and 2022YFA1205100)+2 种基金Shanghai Municipal Science and Technology Major Project(Grant No.2019SHZDZX01)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0301403)the Engineering Research Center for Nanophotonics&Advanced Instrument,Ministry of Education,East China Normal University(Grant No.2023nmc005)。
文摘We report the fabrication of an 8-meter-long thin-flm lithium niobate optical true delay line using the photolithography-assisted chemomechanical etching technique,showing a low transmission loss of 0.036 dB/cm in the conventional telecom band.
文摘Sea lines of communication(SLOCs)security has long been a strategic concern for major powers.Following the establishment of the People’s Republic of China,the country’s focus was on the traditional security aspects of its SLOCs.Since the reform and opening-up era-and especially after the end of the Cold War-China has shifted its emphasis toward economic security.China’s SLOCs security bears on multiple dimensions of a holistic approach to national security,encompassing economic security,the safety of its citizens.
基金supported by the National Natural Science Foundation of China(Grant Nos.12192251,12334014,12404378,92480001,12134001,12174113,12174107,12474325,12404379,and 12474378)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0301403)+1 种基金Shanghai Municipal Science and Technology Major Project(Grant No.2019SHZDZX01)Fundamental Research Funds for the Central Universities,the Engineering Research Center for Nanophotonics&Advanced Instrument,Ministry of Education,East China Normal University(Grant No.2023nmc005).
文摘We present a compact optical delay line(ODL)with wide-range continuous tunability on thin-film lithium niobate platform.The proposed device integrates an unbalanced Mach-Zehnder interferometer(MZI)architecture with dual tunable couplers,where each coupler comprises two 2×2 multimode interferometers and a MZI phase-tuning section.Experimental results demonstrate continuous delay tuning from 0 to 293 ps through synchronized control of coupling coefficients,corresponding to a 4 cm path difference between interferometer arms.The measured delay range exhibits excellent agreement with theoretical predictions derived from ODL waveguide parameters.This result addresses critical challenges in integrated photonic systems that require precise temporal control,particularly for applications in optical communications and quantum information processing,where a wide tuning range is paramount.
