Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frame...Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.展开更多
Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,...Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.展开更多
In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):104...In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].展开更多
The plastic deformation of semiconductors,a process critical to their mechanical and electronic properties,involves various mechanisms such as dislocation motion and phase transition.Here,we systematically examined th...The plastic deformation of semiconductors,a process critical to their mechanical and electronic properties,involves various mechanisms such as dislocation motion and phase transition.Here,we systematically examined the temperature-dependent Peierls stress for 30°and 90°partial dislocations in cadmium telluride(CdTe),using a combination of molecular statics and molecular dynamics simulations with a machine-learning force field,as well as density functional theory simulations.Our findings reveal that the 0 K Peierls stresses for these partial dislocations in CdTe are relatively low,ranging from 0.52 GPa to 1.46 GPa,due to its significant ionic bonding characteristics.Notably,in the CdTe system containing either a 30°Cd-core or 90°Te-core partial dislocation,a phase transition from the zinc-blende phase to theβ-Sn-like phase is favored over dislocation motion.This suggests a competitive relationship between these two mechanisms,driven by the bonding characteristics within the dislocation core and the relatively low phase transition stress of∼1.00 GPa.Furthermore,we observed a general trend wherein the Peierls stress for partial dislocations in CdTe exhibits a temperature dependence,which decreases with increasing temperature,becoming lower than the phase transition stress at elevated temperatures.Consequently,the dominant deformation mechanism in CdTe shifts from solid-state phase transition at low temperatures to dislocation motion at high temperatures.This investigation uncovers a compelling interplay between dislocation motion and phase transition in the plastic deformation of CdTe,offering profound insights into the mechanical behavior and electronic performance of CdTe and other II-VI semiconductors.展开更多
Internal learning-based video inpainting methods have shown promising results by exploiting the intrinsic properties of the video to fill in the missing region without external dataset supervision.However,existing int...Internal learning-based video inpainting methods have shown promising results by exploiting the intrinsic properties of the video to fill in the missing region without external dataset supervision.However,existing internal learning-based video inpainting methods would produce inconsistent structures or blurry textures due to the insufficient utilisation of motion priors within the video sequence.In this paper,the authors propose a new internal learning-based video inpainting model called appearance consistency and motion coherence network(ACMC-Net),which can not only learn the recurrence of appearance prior but can also capture motion coherence prior to improve the quality of the inpainting results.In ACMC-Net,a transformer-based appearance network is developed to capture global context information within the video frame for representing appearance consistency accurately.Additionally,a novel motion coherence learning scheme is proposed to learn the motion prior in a video sequence effectively.Finally,the learnt internal appearance consistency and motion coherence are implicitly propagated to the missing regions to achieve inpainting well.Extensive experiments conducted on the DAVIS dataset show that the proposed model obtains the superior performance in terms of quantitative measurements and produces more visually plausible results compared with the state-of-the-art methods.展开更多
This study employed a computational fluid dynamics model with an overset mesh technique to investigate the thrust and power of a floating offshore wind turbine(FOWT)under platform floating motion in the wind–rain fie...This study employed a computational fluid dynamics model with an overset mesh technique to investigate the thrust and power of a floating offshore wind turbine(FOWT)under platform floating motion in the wind–rain field.The impact of rainfall on aerodynamic performance was initially examined using a stationary turbine model in both wind and wind–rain conditions.Subsequently,the study compared the FOWT’s performance under various single degree-of-freedom(DOF)motions,including surge,pitch,heave,and yaw.Finally,the combined effects of wind–rain fields and platform motions involving two DOFs on the FOWT’s aerodynamics were analyzed and compared.The results demonstrate that rain negatively impacts the aerodynamic performance of both the stationary turbines and FOWTs.Pitch-dominated motions,whether involving single or multiple DOFs,caused significant fluctuations in the FOWT aerodynamics.The combination of surge and pitch motions created the most challenging operational environment for the FOWT in all tested scenarios.These findings highlighted the need for stronger construction materials and greater ultimate bearing capacity for FOWTs,as well as the importance of optimizing designs to mitigate excessive pitch and surge.展开更多
With the rapid development of wearable electronic skin technology, flexible strain sensors have shown great application prospects in the fields of human motion and physiological signal detection, medical diagnostics, ...With the rapid development of wearable electronic skin technology, flexible strain sensors have shown great application prospects in the fields of human motion and physiological signal detection, medical diagnostics, and human-computer interaction owing to their outstanding sensing performance. This paper reports a strain sensor with synergistic conductive network, consisting of stable carbon nanotube dispersion (CNT) layer and brittle MXene layer by dip-coating and electrostatic self-assembly method, and breathable three-dimensional (3D) flexible substrate of thermoplastic polyurethane (TPU) fibrous membrane prepared through electrospinning technology. The MXene/CNT@PDA-TPU (MC@p-TPU) flexible strain sensor had excellent air permeability, wide operating range (0–450 %), high sensitivity (Gauge Factor, GFmax = 8089.7), ultra-low detection limit (0.05 %), rapid response and recovery times (40 ms/60 ms), and excellent cycle stability and durability (10,000 cycles). Given its superior strain sensing capabilities, this sensor can be applied in physiological signals detection, human motion pattern recognition, and driving exoskeleton robots. In addition, MC@p-TPU fibrous membrane also exhibited excellent photothermal conversion performance and can be used as a wearable photo-heater, which has far-reaching application potential in the photothermal therapy of human joint diseases.展开更多
In this study,we present a unified sparsity-driven framework that significantly enhances motion deblurring performance by integrating two key components:a custom-designed dataset and a low-rank module(LRM).This framew...In this study,we present a unified sparsity-driven framework that significantly enhances motion deblurring performance by integrating two key components:a custom-designed dataset and a low-rank module(LRM).This framework leverages the inherent sparsity of per-pixel blur kernels to bolster both deblurring accuracy and model interpretability.Firstly,we propose an adaptive-basis decomposition-based deblurring(ADD)approach,which constructs a tailored training dataset to enhance the generalization capacity of the deblurring network.The ADD framework adaptively decomposes motion blur into sparse basis elements,effectively addressing the intricacies associated with non-uniform blurs.Secondly,an LRM is proposed to improve the interpretability of deblurring models as a plug-and-play module,primarily designed to identify and harness the intrinsic sparse features in sharp images.A series of ablation studies have been conducted to substantiate the synergistic advantages of combining the proposed ADD with the LRM for overall improvement in deblurring efficacy.Subsequently,we empirically demonstrate through rigorous experimentation that incorporating the LRM into an existing Uformer network leads to substantial enhancement in reconstruction performance.This integration yields a sparsity-guided low-rank network(SGLRN).Operating under the overarching principle of sparsity,SGLRN consistently outperforms state-of-the-art methods across multiple standard deblurring benchmarks.Comprehensive experimental results,assessed through quantitative metrics and qualitative visual evaluations,provide compelling evidence of its effectiveness.The overall deblurring results are available at Google Drive.展开更多
Piezoelectric actuators are widely utilized in positioning systems to realize nano-scale resolution. However, the backward motion always generates for some piezoelectric actuators, which reduces the working efficiency...Piezoelectric actuators are widely utilized in positioning systems to realize nano-scale resolution. However, the backward motion always generates for some piezoelectric actuators, which reduces the working efficiency. Bionic motions have already been employed in the field of piezoelectric actuators to realize better performance. By imitating the movement form of seals, seal type piezoelectric actuator is capable to realize large operating strokes easily. Nevertheless, the conventional seal type piezoelectric actuator has a complicated structure and control system, which limits further applications. Hence, an improved bionic piezoelectric actuator is proposed to realize a long motion stroke and eliminate backward movement with a simplified structure and control method in this study. The composition and motion principle of the designed actuator are discussed, and the performance is investigated with simulations and experiments. Results confirm that the presented actuator effectively realizes the linear movement that has a large working stroke stably without backward motion. The smallest stepping displacement ΔL is 0.2 μm under 1 Hz and 50 V. The largest motion speed is 900 μm/s with 900 Hz and 120 V. The largest vertical and horizontal load are 250 g and 12 g, respectively. This work shows that the improved bionic piezoelectric actuator is feasible for eliminating backward motion and has a great working ability.展开更多
This review summarizes the clinical applications and mechanisms of action of motion-style acupuncture(MSAT)in rehabilitation medicine.Patients are required to perform active or passive movements while the acupuncture ...This review summarizes the clinical applications and mechanisms of action of motion-style acupuncture(MSAT)in rehabilitation medicine.Patients are required to perform active or passive movements while the acupuncture needles are inserted.Owing to its effectiveness,MSAT is progressively applied in clinical settings,including musculoskeletal and neurological diseases.Acupuncture and exercise generate syner-gistic effects through interactive mechanisms.From the perspective of the Traditional Chinese Medicine(TCM)theory,needling with movement can trigger the propagation of the needling sensation,thereby enhancing its efficacy in dredging meridians and regulating qi-blood circulation.In modern medicine,these mechanisms include neural inhibition,ischemia/reperfusion,and fascial stimulation propagation.Although the clinical applications and mechanism research of MSAT in rehabilitation medicine have ad-vanced,the mechanisms of MSAT in treating various diseases and the scope of applicable diseases war-rant deeper exploration.This will provide novel therapeutic strategies for clinical applications,thereby advancing the integration and application of TCM therapies with exercise-based interventions.展开更多
The study of capture mechanisms with high capture adaptability is the key to improving the efficiency of autonomous underwater vehicle(AUV)retrieval and release.This study aims to develop a capture mechanism for the l...The study of capture mechanisms with high capture adaptability is the key to improving the efficiency of autonomous underwater vehicle(AUV)retrieval and release.This study aims to develop a capture mechanism for the launch and recovery of AUV and elucidate its kinematic characteristics.Initially,based on the principles of deployment and retraction for AUV capture movements,a design scheme for a novel foldable and deployable capture mechanism is proposed.Subsequently,a detailed analysis of the Degrees of Freedom(DoFs)for enveloping and grasping movements is conducted according to screw theory.Additionally,the structural design of the actuation units for the capture mechanism is thoroughly discussed.Motion screw topology diagram is utilized to construct the kinematic model.On this basis,kinematic simulation verification of the capture mechanism is performed.The theoretical analysis revealed that the DoF for enveloping and grasping movements are 6 and 2,respectively.By appropriately configuring the actuation mechanism,enveloping and grasping movements can be achieved with a single actuation.The displacement and velocity curves of the capture mechanism were smooth,with no interference occurring.Vibration test results validate the reliability of the capture mechanism.The research work provides a valuable reference for the development of novel capture equipment for AUVs.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.72161034).
文摘Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.
基金supported by the Basic Science Research Program(2023R1A2C3004336,RS-202300243807)&Regional Leading Research Center(RS-202400405278)through the National Research Foundation of Korea(NRF)grant funded by the Korea Government(MSIT)。
文摘Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.
基金Supported by NSFC(Nos.11661025,12161024)Natural Science Foundation of Guangxi(Nos.2020GXNSFAA159118,2021GXNSFAA196045)+2 种基金Guangxi Science and Technology Project(No.Guike AD20297006)Training Program for 1000 Young and Middle-aged Cadre Teachers in Universities of GuangxiNational College Student's Innovation and Entrepreneurship Training Program(No.202110595049)。
文摘In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].
基金supported by the National Science Foundation(No.CMMI-2019459).
文摘The plastic deformation of semiconductors,a process critical to their mechanical and electronic properties,involves various mechanisms such as dislocation motion and phase transition.Here,we systematically examined the temperature-dependent Peierls stress for 30°and 90°partial dislocations in cadmium telluride(CdTe),using a combination of molecular statics and molecular dynamics simulations with a machine-learning force field,as well as density functional theory simulations.Our findings reveal that the 0 K Peierls stresses for these partial dislocations in CdTe are relatively low,ranging from 0.52 GPa to 1.46 GPa,due to its significant ionic bonding characteristics.Notably,in the CdTe system containing either a 30°Cd-core or 90°Te-core partial dislocation,a phase transition from the zinc-blende phase to theβ-Sn-like phase is favored over dislocation motion.This suggests a competitive relationship between these two mechanisms,driven by the bonding characteristics within the dislocation core and the relatively low phase transition stress of∼1.00 GPa.Furthermore,we observed a general trend wherein the Peierls stress for partial dislocations in CdTe exhibits a temperature dependence,which decreases with increasing temperature,becoming lower than the phase transition stress at elevated temperatures.Consequently,the dominant deformation mechanism in CdTe shifts from solid-state phase transition at low temperatures to dislocation motion at high temperatures.This investigation uncovers a compelling interplay between dislocation motion and phase transition in the plastic deformation of CdTe,offering profound insights into the mechanical behavior and electronic performance of CdTe and other II-VI semiconductors.
基金Shenzhen Science and Technology Programme,Grant/Award Number:JCYJ202308071208000012023 Shenzhen sustainable supporting funds for colleges and universities,Grant/Award Number:20231121165240001Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology,Grant/Award Number:2024B1212010006。
文摘Internal learning-based video inpainting methods have shown promising results by exploiting the intrinsic properties of the video to fill in the missing region without external dataset supervision.However,existing internal learning-based video inpainting methods would produce inconsistent structures or blurry textures due to the insufficient utilisation of motion priors within the video sequence.In this paper,the authors propose a new internal learning-based video inpainting model called appearance consistency and motion coherence network(ACMC-Net),which can not only learn the recurrence of appearance prior but can also capture motion coherence prior to improve the quality of the inpainting results.In ACMC-Net,a transformer-based appearance network is developed to capture global context information within the video frame for representing appearance consistency accurately.Additionally,a novel motion coherence learning scheme is proposed to learn the motion prior in a video sequence effectively.Finally,the learnt internal appearance consistency and motion coherence are implicitly propagated to the missing regions to achieve inpainting well.Extensive experiments conducted on the DAVIS dataset show that the proposed model obtains the superior performance in terms of quantitative measurements and produces more visually plausible results compared with the state-of-the-art methods.
基金Supported by the National Natural Science Foundation of China(51679080 and 51379073)the Fundamental Research Funds for the Central Universities(B230205020).
文摘This study employed a computational fluid dynamics model with an overset mesh technique to investigate the thrust and power of a floating offshore wind turbine(FOWT)under platform floating motion in the wind–rain field.The impact of rainfall on aerodynamic performance was initially examined using a stationary turbine model in both wind and wind–rain conditions.Subsequently,the study compared the FOWT’s performance under various single degree-of-freedom(DOF)motions,including surge,pitch,heave,and yaw.Finally,the combined effects of wind–rain fields and platform motions involving two DOFs on the FOWT’s aerodynamics were analyzed and compared.The results demonstrate that rain negatively impacts the aerodynamic performance of both the stationary turbines and FOWTs.Pitch-dominated motions,whether involving single or multiple DOFs,caused significant fluctuations in the FOWT aerodynamics.The combination of surge and pitch motions created the most challenging operational environment for the FOWT in all tested scenarios.These findings highlighted the need for stronger construction materials and greater ultimate bearing capacity for FOWTs,as well as the importance of optimizing designs to mitigate excessive pitch and surge.
基金supported by the National Natural Science Foundation of China(Nos.52373093 and 12072325)the Outstanding Youth Fund of Henan Province(No.242300421062)+1 种基金National Key R&D Program of China(No.2019YFA0706802)the 111 project(No.D18023).
文摘With the rapid development of wearable electronic skin technology, flexible strain sensors have shown great application prospects in the fields of human motion and physiological signal detection, medical diagnostics, and human-computer interaction owing to their outstanding sensing performance. This paper reports a strain sensor with synergistic conductive network, consisting of stable carbon nanotube dispersion (CNT) layer and brittle MXene layer by dip-coating and electrostatic self-assembly method, and breathable three-dimensional (3D) flexible substrate of thermoplastic polyurethane (TPU) fibrous membrane prepared through electrospinning technology. The MXene/CNT@PDA-TPU (MC@p-TPU) flexible strain sensor had excellent air permeability, wide operating range (0–450 %), high sensitivity (Gauge Factor, GFmax = 8089.7), ultra-low detection limit (0.05 %), rapid response and recovery times (40 ms/60 ms), and excellent cycle stability and durability (10,000 cycles). Given its superior strain sensing capabilities, this sensor can be applied in physiological signals detection, human motion pattern recognition, and driving exoskeleton robots. In addition, MC@p-TPU fibrous membrane also exhibited excellent photothermal conversion performance and can be used as a wearable photo-heater, which has far-reaching application potential in the photothermal therapy of human joint diseases.
基金supported by the National Natural Science Foundation of China(No.62206143)the Key Research and Development and Promotion Special Project in Henan Province(Nos.222102210141 and 232102211015)。
文摘In this study,we present a unified sparsity-driven framework that significantly enhances motion deblurring performance by integrating two key components:a custom-designed dataset and a low-rank module(LRM).This framework leverages the inherent sparsity of per-pixel blur kernels to bolster both deblurring accuracy and model interpretability.Firstly,we propose an adaptive-basis decomposition-based deblurring(ADD)approach,which constructs a tailored training dataset to enhance the generalization capacity of the deblurring network.The ADD framework adaptively decomposes motion blur into sparse basis elements,effectively addressing the intricacies associated with non-uniform blurs.Secondly,an LRM is proposed to improve the interpretability of deblurring models as a plug-and-play module,primarily designed to identify and harness the intrinsic sparse features in sharp images.A series of ablation studies have been conducted to substantiate the synergistic advantages of combining the proposed ADD with the LRM for overall improvement in deblurring efficacy.Subsequently,we empirically demonstrate through rigorous experimentation that incorporating the LRM into an existing Uformer network leads to substantial enhancement in reconstruction performance.This integration yields a sparsity-guided low-rank network(SGLRN).Operating under the overarching principle of sparsity,SGLRN consistently outperforms state-of-the-art methods across multiple standard deblurring benchmarks.Comprehensive experimental results,assessed through quantitative metrics and qualitative visual evaluations,provide compelling evidence of its effectiveness.The overall deblurring results are available at Google Drive.
基金supported by The Key Science and Technology Plan Project of Jinhua City,China:2023-3-084,2023-2-011Zhejiang Provincial"Revealing the list and taking command"Project of China KYH06Y22349Open Fund Project of Key Laboratory of CNC Equipment reliability,Ministry of Education JLU-cncr-202407.
文摘Piezoelectric actuators are widely utilized in positioning systems to realize nano-scale resolution. However, the backward motion always generates for some piezoelectric actuators, which reduces the working efficiency. Bionic motions have already been employed in the field of piezoelectric actuators to realize better performance. By imitating the movement form of seals, seal type piezoelectric actuator is capable to realize large operating strokes easily. Nevertheless, the conventional seal type piezoelectric actuator has a complicated structure and control system, which limits further applications. Hence, an improved bionic piezoelectric actuator is proposed to realize a long motion stroke and eliminate backward movement with a simplified structure and control method in this study. The composition and motion principle of the designed actuator are discussed, and the performance is investigated with simulations and experiments. Results confirm that the presented actuator effectively realizes the linear movement that has a large working stroke stably without backward motion. The smallest stepping displacement ΔL is 0.2 μm under 1 Hz and 50 V. The largest motion speed is 900 μm/s with 900 Hz and 120 V. The largest vertical and horizontal load are 250 g and 12 g, respectively. This work shows that the improved bionic piezoelectric actuator is feasible for eliminating backward motion and has a great working ability.
基金Supported by Winter Sports Management Center of General Administration of Sport of China:0773-2441GNOEFWGK4888。
文摘This review summarizes the clinical applications and mechanisms of action of motion-style acupuncture(MSAT)in rehabilitation medicine.Patients are required to perform active or passive movements while the acupuncture needles are inserted.Owing to its effectiveness,MSAT is progressively applied in clinical settings,including musculoskeletal and neurological diseases.Acupuncture and exercise generate syner-gistic effects through interactive mechanisms.From the perspective of the Traditional Chinese Medicine(TCM)theory,needling with movement can trigger the propagation of the needling sensation,thereby enhancing its efficacy in dredging meridians and regulating qi-blood circulation.In modern medicine,these mechanisms include neural inhibition,ischemia/reperfusion,and fascial stimulation propagation.Although the clinical applications and mechanism research of MSAT in rehabilitation medicine have ad-vanced,the mechanisms of MSAT in treating various diseases and the scope of applicable diseases war-rant deeper exploration.This will provide novel therapeutic strategies for clinical applications,thereby advancing the integration and application of TCM therapies with exercise-based interventions.
基金Supported by Jiangsu Provincial Natural Science Foundation(Grant No.BK20220649)Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Grant No.23KJB460010)+2 种基金Provincial Key Laboratory of High-end Deepsea Machinery Equipment(Grant Nos.SYH2024003 and SYH2025001)the Jiangsu Provincial Key R&D Project(Grant No.BE2022062)Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.SJCX25_2526).
文摘The study of capture mechanisms with high capture adaptability is the key to improving the efficiency of autonomous underwater vehicle(AUV)retrieval and release.This study aims to develop a capture mechanism for the launch and recovery of AUV and elucidate its kinematic characteristics.Initially,based on the principles of deployment and retraction for AUV capture movements,a design scheme for a novel foldable and deployable capture mechanism is proposed.Subsequently,a detailed analysis of the Degrees of Freedom(DoFs)for enveloping and grasping movements is conducted according to screw theory.Additionally,the structural design of the actuation units for the capture mechanism is thoroughly discussed.Motion screw topology diagram is utilized to construct the kinematic model.On this basis,kinematic simulation verification of the capture mechanism is performed.The theoretical analysis revealed that the DoF for enveloping and grasping movements are 6 and 2,respectively.By appropriately configuring the actuation mechanism,enveloping and grasping movements can be achieved with a single actuation.The displacement and velocity curves of the capture mechanism were smooth,with no interference occurring.Vibration test results validate the reliability of the capture mechanism.The research work provides a valuable reference for the development of novel capture equipment for AUVs.
