In the field of infrared small target detection(ISTD),the ability to detect targets in dim environments is critical,as it improves the performance of target recognition in nighttime and harsh weather conditions.The bl...In the field of infrared small target detection(ISTD),the ability to detect targets in dim environments is critical,as it improves the performance of target recognition in nighttime and harsh weather conditions.The blurry contour,small size and sparse distribution of infrared small targets increase the difficulty of identifying such targets in cluttered backgrounds.Existing methodologies fall short of satisfying the requisites for the detection and categorisation of infrared small targets.To address these challenges and to enhance the precision of small object detection and classification,this paper introduces an innovative approach called location refinement and adjacent feature fusion YOLO(LA-YOLO),which enhances feature extraction by integrating a multi-head self-attention mechanism(MSA).We have improved the feature fusion method to merge adjacent features,to enhance information utilisation in the path aggregation network(PAN).Lastly,we introduce supervision on the target centre points in the detection network.Empirical results on publicly available datasets demonstrate that LA-YOLO achieves an impressive average precision(AP)of 92.46% on IST-A and a mean average precision(mAP)of 84.82%on FLIR.The results surpass those of contemporary state-of-the-art detectors,striking a balance between precision and speed.LA-YOLO emerges as a viable and efficacious solution for ISTD,making a substantial contribution to the progression of infrared imagery analysis.The code is available at https://github.com/liusjo/LA-YOLO.展开更多
When facing a sudden danger or aversive condition while engaged in on-going forward motion,animals transiently slow down and make a turn to escape.The neural mechanisms underlying stimulation-induced deceleration in a...When facing a sudden danger or aversive condition while engaged in on-going forward motion,animals transiently slow down and make a turn to escape.The neural mechanisms underlying stimulation-induced deceleration in avoidance behavior are largely unknown.Here, we report that in Drosophila larvae, light-induced deceleration was commanded by a continuous neural pathway that included prothoracicotropic hormone neurons, eclosion hormone neurons, and tyrosine decarboxylase 2 motor neurons(the PET pathway). Inhibiting neurons in the PET pathway led to defects in lightavoidance due to insufficient deceleration and head casting.On the other hand, activation of PET pathway neurons specifically caused immediate deceleration in larval locomotion. Our findings reveal a neural substrate for the emergent deceleration response and provide a new understanding of the relationship between behavioral modules in animal avoidance responses.展开更多
The precise movement speed regulation is a key factor to improve the control effect and efficiency of the cyborg rats.However,the current stimulation techniques cannot realize the graded control of the speed.In this s...The precise movement speed regulation is a key factor to improve the control effect and efficiency of the cyborg rats.However,the current stimulation techniques cannot realize the graded control of the speed.In this study,we achieved the multi-level speed regulation of cyborg rats in the large open field and treadmill by specifically targeting the Cuneiform Nucleus(CnF)of the Mesencephalic Locomotor Region(MLR).Detailed,we measured the influence of each stimulation parameter on the speed control process which included the real-time speed,accelerated speed,response time,and acceleration period.We concluded that the pulse period and the pulse width were the main determinants influencing the accelerated speed of cyborg rats.Whereas the amplitude of stimulation was found to affect the response time exhibited by the cyborg rats.Our study provides valuable insights into the regulation of rat locomotion speed and highlights the potential for utilizing this approach in various experimental settings.展开更多
Millimeter-scale animals such as Caenorhabditis elegans,Drosophila larvae,zebrafish,and bees serve as powerful model organisms in the fields of neurobiology and neuroethology.Various methods exist for recording large-...Millimeter-scale animals such as Caenorhabditis elegans,Drosophila larvae,zebrafish,and bees serve as powerful model organisms in the fields of neurobiology and neuroethology.Various methods exist for recording large-scale electrophysiological signals from these animals.Existing approaches often lack,however,real-time,uninterrupted investigations due to their rigid constructs,geometric constraints,and mechanical mismatch in integration with soft organisms.The recent research establishes the foundations for 3-dimensional flexible bioelectronic interfaces that incorporate microfabricated components and nanoelectronic function with adjustable mechanical properties and multidimensional variability,offering unique capabilities for chronic,stable interrogation and stimulation of millimeter-scale animals and miniature tissue constructs.This review summarizes the most advanced technologies for electrophysiological studies,based on methods of 3-dimensional flexible bioelectronics.A concluding section addresses the challenges of these devices in achieving freestanding,robust,and multifunctional biointerfaces.展开更多
Soft crawling robots have been widely studied and applied because of their excellent environmental adaptability and flexible movement.However,most existing soft crawling robots typically exhibit a single-motion mode a...Soft crawling robots have been widely studied and applied because of their excellent environmental adaptability and flexible movement.However,most existing soft crawling robots typically exhibit a single-motion mode and lack diverse capabilities.Inspired by Drosophila larvae,this paper proposes a compact soft crawling robot(weight,13 g;length,165 mm;diameter,35 mm)with multimodal locomotion(forward,turning,rolling,and twisting).Each robot module uses 4 sets of high-power-density shape memory alloy actuators,endowing it with 4 degrees of motion freedom.We analyze the mechanical characteristics of the robot modules through experiments and simulation analysis.The plug-and-play modules can be quickly assembled to meet different motion and task requirements.The soft crawling robot can be remotely operated with an external controller,showcasing multimodal motion on various material surfaces.In a narrow maze,the robot demonstrates agile movement and effective maneuvering around obstacles.In addition,leveraging the inherent bistable characteristics of the robot modules,we used the robot modules as anchoring units and installed a microcamera on the robot's head for pipeline detection.The robot completed the inspection in horizontal,vertical,curved,and branched pipelines,adjusted the camera view,and twisted a valve in the pipeline for the first time.Our research highlights the robot's superior locomotion and application capabilities,providing an innovative strategy for the development of lightweight,compact,and multifunctional soft crawling robots.展开更多
The deformability and high degree of freedom of mollusks bring challenges in mathematical modeling and synthesis of motions.Traditional analytical and statistical models are limited by either rigid skeleton assumption...The deformability and high degree of freedom of mollusks bring challenges in mathematical modeling and synthesis of motions.Traditional analytical and statistical models are limited by either rigid skeleton assumptions or model capacity,and have difficulty in generating realistic and multi-pattern mollusk motions.In this work,we present a large-scale dynamic pose dataset of Drosophila larvae and propose a motion synthesis model named Path2Pose to generate a pose sequence given the initial poses and the subsequent guiding path.The Path2Pose model is further used to synthesize long pose sequences of various motion patterns through a recursive generation method.Evaluation analysis results demonstrate that our novel model synthesizes highly realistic mollusk motions and achieves state-of-the-art performance.Our work proves high performance of deep neural networks for mollusk motion synthesis and the feasibility of long pose sequence synthesis based on the customized body shape and guiding path.展开更多
基金supported by Guangdong Basic and Applied Basic Research Foundation(No.2025A1515011617,2022A1515110570)Fundamental Research Funds for the Provincial Universities of Zhejiang(No.GK259909299001-006)+2 种基金Innovation Teams of Youth Innovation in Science and Technology of High Education Institutions of Shandong Province(No.2021KJ088)Anhui Provincial Joint Construction Key Laboratory of Intelligent Education Equipment and Technology(No.IEET202401)Aeronautical Science Foundation of China(No.2022Z0710T5001).
文摘In the field of infrared small target detection(ISTD),the ability to detect targets in dim environments is critical,as it improves the performance of target recognition in nighttime and harsh weather conditions.The blurry contour,small size and sparse distribution of infrared small targets increase the difficulty of identifying such targets in cluttered backgrounds.Existing methodologies fall short of satisfying the requisites for the detection and categorisation of infrared small targets.To address these challenges and to enhance the precision of small object detection and classification,this paper introduces an innovative approach called location refinement and adjacent feature fusion YOLO(LA-YOLO),which enhances feature extraction by integrating a multi-head self-attention mechanism(MSA).We have improved the feature fusion method to merge adjacent features,to enhance information utilisation in the path aggregation network(PAN).Lastly,we introduce supervision on the target centre points in the detection network.Empirical results on publicly available datasets demonstrate that LA-YOLO achieves an impressive average precision(AP)of 92.46% on IST-A and a mean average precision(mAP)of 84.82%on FLIR.The results surpass those of contemporary state-of-the-art detectors,striking a balance between precision and speed.LA-YOLO emerges as a viable and efficacious solution for ISTD,making a substantial contribution to the progression of infrared imagery analysis.The code is available at https://github.com/liusjo/LA-YOLO.
基金supported by grants from the National Basic Research Development Program of China (973 Program, 2013CB945603)the National Natural Science Foundation of China (31070944, 31271147, 31471063, 31671074, and 61572433)+1 种基金the Natural Science Foundation of Zhejiang Province, China (LR13C090001 and LZ14F020002)the Fundamental Research Funds for the Central Universities, China (2017FZA7003)
文摘When facing a sudden danger or aversive condition while engaged in on-going forward motion,animals transiently slow down and make a turn to escape.The neural mechanisms underlying stimulation-induced deceleration in avoidance behavior are largely unknown.Here, we report that in Drosophila larvae, light-induced deceleration was commanded by a continuous neural pathway that included prothoracicotropic hormone neurons, eclosion hormone neurons, and tyrosine decarboxylase 2 motor neurons(the PET pathway). Inhibiting neurons in the PET pathway led to defects in lightavoidance due to insufficient deceleration and head casting.On the other hand, activation of PET pathway neurons specifically caused immediate deceleration in larval locomotion. Our findings reveal a neural substrate for the emergent deceleration response and provide a new understanding of the relationship between behavioral modules in animal avoidance responses.
基金the National Key R&D Program of China(2020YFB1313501)Zhejiang Provincial Natural Science Foundation(LZ24F020003)+2 种基金National Natural Science Foundation of China(T2293723)the Key R&D program of Zhejiang Province(2021C03003)the Fundamental Research Funds for the Central Universities(No.226-2022-00051).
文摘The precise movement speed regulation is a key factor to improve the control effect and efficiency of the cyborg rats.However,the current stimulation techniques cannot realize the graded control of the speed.In this study,we achieved the multi-level speed regulation of cyborg rats in the large open field and treadmill by specifically targeting the Cuneiform Nucleus(CnF)of the Mesencephalic Locomotor Region(MLR).Detailed,we measured the influence of each stimulation parameter on the speed control process which included the real-time speed,accelerated speed,response time,and acceleration period.We concluded that the pulse period and the pulse width were the main determinants influencing the accelerated speed of cyborg rats.Whereas the amplitude of stimulation was found to affect the response time exhibited by the cyborg rats.Our study provides valuable insights into the regulation of rat locomotion speed and highlights the potential for utilizing this approach in various experimental settings.
基金N.Z.acknowledges the support from“STI 2030-Major Projects 2021ZD0200405”and National Natural Science Foundation of China(T2293723 and 61972347)K.N.acknowledges the support from start-up funding for the ZJU100 professorship from Zhejiang UniversityJ.A.R.acknowledges funding from the Querrey Simpson Institute for Bioelectronics.
文摘Millimeter-scale animals such as Caenorhabditis elegans,Drosophila larvae,zebrafish,and bees serve as powerful model organisms in the fields of neurobiology and neuroethology.Various methods exist for recording large-scale electrophysiological signals from these animals.Existing approaches often lack,however,real-time,uninterrupted investigations due to their rigid constructs,geometric constraints,and mechanical mismatch in integration with soft organisms.The recent research establishes the foundations for 3-dimensional flexible bioelectronic interfaces that incorporate microfabricated components and nanoelectronic function with adjustable mechanical properties and multidimensional variability,offering unique capabilities for chronic,stable interrogation and stimulation of millimeter-scale animals and miniature tissue constructs.This review summarizes the most advanced technologies for electrophysiological studies,based on methods of 3-dimensional flexible bioelectronics.A concluding section addresses the challenges of these devices in achieving freestanding,robust,and multifunctional biointerfaces.
基金supported by the Zhejiang Provincial Natural Science Foundation of China(LD22E-050007)National Natural Science Foundation of China(T2293724 and 62303407)the Key R&D Program of Zhejiang(2022C01022).
文摘Soft crawling robots have been widely studied and applied because of their excellent environmental adaptability and flexible movement.However,most existing soft crawling robots typically exhibit a single-motion mode and lack diverse capabilities.Inspired by Drosophila larvae,this paper proposes a compact soft crawling robot(weight,13 g;length,165 mm;diameter,35 mm)with multimodal locomotion(forward,turning,rolling,and twisting).Each robot module uses 4 sets of high-power-density shape memory alloy actuators,endowing it with 4 degrees of motion freedom.We analyze the mechanical characteristics of the robot modules through experiments and simulation analysis.The plug-and-play modules can be quickly assembled to meet different motion and task requirements.The soft crawling robot can be remotely operated with an external controller,showcasing multimodal motion on various material surfaces.In a narrow maze,the robot demonstrates agile movement and effective maneuvering around obstacles.In addition,leveraging the inherent bistable characteristics of the robot modules,we used the robot modules as anchoring units and installed a microcamera on the robot's head for pipeline detection.The robot completed the inspection in horizontal,vertical,curved,and branched pipelines,adjusted the camera view,and twisted a valve in the pipeline for the first time.Our research highlights the robot's superior locomotion and application capabilities,providing an innovative strategy for the development of lightweight,compact,and multifunctional soft crawling robots.
基金supported by the Zhejiang Lab,China(No.2020KB0AC02)the Zhejiang Provincial Key R&D Program,China(Nos.2022C01022,2022C01119,and 2021C03003)+2 种基金the National Natural Science Foundation of China(Nos.T2293723 and 61972347)the Zhejiang Provincial Natural Science Foundation,China(No.LR19F020005)the Fundamental Research Funds for the Central Universities,China(No.226-2022-00051)。
文摘The deformability and high degree of freedom of mollusks bring challenges in mathematical modeling and synthesis of motions.Traditional analytical and statistical models are limited by either rigid skeleton assumptions or model capacity,and have difficulty in generating realistic and multi-pattern mollusk motions.In this work,we present a large-scale dynamic pose dataset of Drosophila larvae and propose a motion synthesis model named Path2Pose to generate a pose sequence given the initial poses and the subsequent guiding path.The Path2Pose model is further used to synthesize long pose sequences of various motion patterns through a recursive generation method.Evaluation analysis results demonstrate that our novel model synthesizes highly realistic mollusk motions and achieves state-of-the-art performance.Our work proves high performance of deep neural networks for mollusk motion synthesis and the feasibility of long pose sequence synthesis based on the customized body shape and guiding path.
