Achieving continuous motions typically requires dynamic external stimuli for cyclic deformation,or crafted geometries with intricate modules to form a self-regulated feedback loop upon static stimulation.It is still a...Achieving continuous motions typically requires dynamic external stimuli for cyclic deformation,or crafted geometries with intricate modules to form a self-regulated feedback loop upon static stimulation.It is still a grand challenge to realize self-sustained motion in soft robots subject to unchanging environment,without complex geometry or a control module.In this work,we report soft robots based on an anisotropic cylindrical hydrogel showing self-regulated,continuous rolling motions under constant light irradiation.The robots are animated by mirror-symmetry-breaking induced by photothermal strain gradient.The self-sustained motion is attributed to the fast and reversible deformation of the gel and the autonomous refresh of the irradiated region during the rolling motion.The hydrogel robots can reach a rolling speed of 1.27 mm·s^(-1)on a horizonal surface and even climb a ramp of 18°at a speed of 0.57 mm·s^(-1)in an aqueous environment.Furthermore,the hydrogel robots can overcome an obstacle,with rolling direction controllable through irradiation angle of the light and local irradiation on selective regions.This work suggests a facile strategy to develop hydrogel robots and may provide unforeseen inspirations for the design of self-regulated soft robots by using other intelligent materials.展开更多
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
Currently, many studies have been made for years on dimensions of pneumatic nozzle, which influence the flow characteristic of blowing system. For the purpose of outputting the same blowing force, the supply pressure ...Currently, many studies have been made for years on dimensions of pneumatic nozzle, which influence the flow characteristic of blowing system. For the purpose of outputting the same blowing force, the supply pressure could be reduced by decreasing the ratio of length to diameter of nozzle. The friction between high speed air and pipe wall would be reduced if the nozzle is designed to be converging shape comparing with straight shape. But the volume flow and pressure, discussed in these studies, do not describe energy loss of the blowing system directly. Pneumatic power is an innovative principle to estimate pneumatic system’s energy consumption directly. Based on the above principle, a pulse blowing method is put forward for saving energy. A flow experiment is carried out, in which the high speed air flows from the pulse blowing system and continuous blowing system respectively to a plate with grease on top. Supply pressure and the volume of air used for removing the grease are measured to calculate energy consumption. From the experiment result, the pulse blowing system performs to conserve energy comparing with the continuous blowing system. The frequency and duty ratio of pulse flow influence the blowing characteristic. The pulse blowing system performs to be the most efficient at the specified frequency and duty ratio. Then a pneumatic self-oscillated method based on air operated valve is put forward to generate pulse flow. A simulation is made about dynamic modeling the air operated valve and calculating the motion of the valve core and output pressure. The simulation result verifies the system to be able to generate pulse flow, and predicts the key parameters of the frequency and duty ratio measured by experiment well. Finally, on the basis of simplifying and solution of the pulse blowing system’s mathematic model, the relationship between system’s frequency duty ratio and the dimensions of components is simply described with four algebraic equations. The system could be designed with specified frequency and duty ratio according to the four equations. This study provides theoretical basis for designing energy-saving air blowing system.展开更多
In this paper we investigate spatiotemporal pattern formation in excitable media with only a long-range link. Besides the trivial solutions of spiral patterns, we find the asymptotic self-sustained target waves in the...In this paper we investigate spatiotemporal pattern formation in excitable media with only a long-range link. Besides the trivial solutions of spiral patterns, we find the asymptotic self-sustained target waves in the autonomous tissues. The wave source supporting this kind of new pattern is the oscillatory one-dimensional Winfree-loop self- organized under the presence of a long-range link, which is explored by the dominant phase-advanced driving method. Based on this understanding we can effectively regulate the oscillations of excitable media by suitably arranging the long-range link, including construction of self-sustained target waves with controllable period and wave length, or manipulation of system states between different patterns.展开更多
We generalize a simple model for superlattices to include the effect of differential capacitance. It is shown that the model always has a stable steady-state solution （SSS） if all differential capacitances are posit...We generalize a simple model for superlattices to include the effect of differential capacitance. It is shown that the model always has a stable steady-state solution （SSS） if all differential capacitances are positive. On the other hand, when negative differential capacitance is included, the model can have no stable SSS and be in a self-sustained current oscillation behavior. Therefore, we find a possible minimum toy model with both negative differential resistance and negative differential capacitance which can include the phenomena of both self-sustained current oscillation and I-V oscillation of stable SSSs.展开更多
Oscillatory behaviors can be ubiquitously observed in various systems. Biological rhythms are significant in governing living activities of all units. The emergence of biological rhythms is the consequence of large nu...Oscillatory behaviors can be ubiquitously observed in various systems. Biological rhythms are significant in governing living activities of all units. The emergence of biological rhythms is the consequence of large numbers of units. In this paper we discuss several important examples of sustained oscillations in biological media, where the unit composed in the system does not possess the oscillation behavior. The dominant phase-advanced driving method is applied to study the skeletons and oscillatory organizing motifs in excitable networks and gene regulatory networks.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
Numerical simulations are used to investigate the self-sustained oscillating flows past an open cavity. The two-dimensional incompressible Navier-Stokes equations are solved directly by using the finite difference met...Numerical simulations are used to investigate the self-sustained oscillating flows past an open cavity. The two-dimensional incompressible Navier-Stokes equations are solved directly by using the finite difference method for cavities with an upstream laminar boundary layer. A series of simulations are performed for a variety of cavity length-to-depth ratio. The results show the switching among some flow modes including non-oscillation mode, shear layer mode and wake mode. The variation of the Strouhal number is in favorable agreement with available experimental data. The results of flow fields in the cavity reveal the relationship between the cavity shear layer oscillation modes and recirculating vortices in the cavity.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
Seawater electrolysis for hydrogen production faces inherent challenges, including side reactions, corrosion, and scaling, stemming from the intricate composition of seawater. In response, researchers have turned to c...Seawater electrolysis for hydrogen production faces inherent challenges, including side reactions, corrosion, and scaling, stemming from the intricate composition of seawater. In response, researchers have turned to continuous water splitting using forward osmosis(FO)-driven seawater desalination. However, the necessity of a neutral electrolyte hampers this strategy due to the limited current density and scarcity of precious metals. Herein, this study applies alkali-durable FO membranes to enable self-sustaining seawater splitting, which can selectively withdraw water molecules, from seawater, via concentration gradient. The membranes demonstrates outstanding perm-selectivity of water/ions(~5830 mol mol^(-1)) during month-long alkaline resistance tests, preventing electrolyte leaching(>97% OHàretention) while maintaining ~95%water balance(V_(FO)= V_(electrolysis)) via preserved concentration gradient for consistent forward-osmosis influx of water molecules. With the consistent electrolyte environment protected by the polyamide FO membranes, the Ni Fe-Ar-P catalyst exhibits promising performance: a sustain current density of 360 m A cmà2maintained at the cell voltage of 2.10 V and 2.15 V for 360 h in the offshore seawater, preventing Cl/Br corrosion(98% rejection) and Mg/Ca passivation(99.6% rejection). This research marks a significant advancement towards efficient and durable seawater-based hydrogen production.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
基金supported by the National Natural Science Foundation of China(Nos.52325302 and 52173012)Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering(No.2022SZ-FR005)。
文摘Achieving continuous motions typically requires dynamic external stimuli for cyclic deformation,or crafted geometries with intricate modules to form a self-regulated feedback loop upon static stimulation.It is still a grand challenge to realize self-sustained motion in soft robots subject to unchanging environment,without complex geometry or a control module.In this work,we report soft robots based on an anisotropic cylindrical hydrogel showing self-regulated,continuous rolling motions under constant light irradiation.The robots are animated by mirror-symmetry-breaking induced by photothermal strain gradient.The self-sustained motion is attributed to the fast and reversible deformation of the gel and the autonomous refresh of the irradiated region during the rolling motion.The hydrogel robots can reach a rolling speed of 1.27 mm·s^(-1)on a horizonal surface and even climb a ramp of 18°at a speed of 0.57 mm·s^(-1)in an aqueous environment.Furthermore,the hydrogel robots can overcome an obstacle,with rolling direction controllable through irradiation angle of the light and local irradiation on selective regions.This work suggests a facile strategy to develop hydrogel robots and may provide unforeseen inspirations for the design of self-regulated soft robots by using other intelligent materials.
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.
文摘Currently, many studies have been made for years on dimensions of pneumatic nozzle, which influence the flow characteristic of blowing system. For the purpose of outputting the same blowing force, the supply pressure could be reduced by decreasing the ratio of length to diameter of nozzle. The friction between high speed air and pipe wall would be reduced if the nozzle is designed to be converging shape comparing with straight shape. But the volume flow and pressure, discussed in these studies, do not describe energy loss of the blowing system directly. Pneumatic power is an innovative principle to estimate pneumatic system’s energy consumption directly. Based on the above principle, a pulse blowing method is put forward for saving energy. A flow experiment is carried out, in which the high speed air flows from the pulse blowing system and continuous blowing system respectively to a plate with grease on top. Supply pressure and the volume of air used for removing the grease are measured to calculate energy consumption. From the experiment result, the pulse blowing system performs to conserve energy comparing with the continuous blowing system. The frequency and duty ratio of pulse flow influence the blowing characteristic. The pulse blowing system performs to be the most efficient at the specified frequency and duty ratio. Then a pneumatic self-oscillated method based on air operated valve is put forward to generate pulse flow. A simulation is made about dynamic modeling the air operated valve and calculating the motion of the valve core and output pressure. The simulation result verifies the system to be able to generate pulse flow, and predicts the key parameters of the frequency and duty ratio measured by experiment well. Finally, on the basis of simplifying and solution of the pulse blowing system’s mathematic model, the relationship between system’s frequency duty ratio and the dimensions of components is simply described with four algebraic equations. The system could be designed with specified frequency and duty ratio according to the four equations. This study provides theoretical basis for designing energy-saving air blowing system.
基金supported by the National Natural Science Foundation of China (Grant No. 11047146)the Science Foundation of the Education Bureau of Shaanxi Province of China (Grant No. 11JK0544)+1 种基金the Natural Science Foundation of Shaanxi Province of China (Grant No. 2010JQ1014)the Science Foundation of Baoji University of Arts and Sciences (Grant Nos. ZK1048 andZK1049)
文摘In this paper we investigate spatiotemporal pattern formation in excitable media with only a long-range link. Besides the trivial solutions of spiral patterns, we find the asymptotic self-sustained target waves in the autonomous tissues. The wave source supporting this kind of new pattern is the oscillatory one-dimensional Winfree-loop self- organized under the presence of a long-range link, which is explored by the dominant phase-advanced driving method. Based on this understanding we can effectively regulate the oscillations of excitable media by suitably arranging the long-range link, including construction of self-sustained target waves with controllable period and wave length, or manipulation of system states between different patterns.
基金The project supported by National Natural Science Foundation of China under Grant No. 10347101 and the Grant from Beijing Normal University
文摘We generalize a simple model for superlattices to include the effect of differential capacitance. It is shown that the model always has a stable steady-state solution （SSS） if all differential capacitances are positive. On the other hand, when negative differential capacitance is included, the model can have no stable SSS and be in a self-sustained current oscillation behavior. Therefore, we find a possible minimum toy model with both negative differential resistance and negative differential capacitance which can include the phenomena of both self-sustained current oscillation and I-V oscillation of stable SSSs.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11475022 and 11675001)the Scientific Research Funds of Huaqiao University,China(Grant No.15BS401)
文摘Oscillatory behaviors can be ubiquitously observed in various systems. Biological rhythms are significant in governing living activities of all units. The emergence of biological rhythms is the consequence of large numbers of units. In this paper we discuss several important examples of sustained oscillations in biological media, where the unit composed in the system does not possess the oscillation behavior. The dominant phase-advanced driving method is applied to study the skeletons and oscillatory organizing motifs in excitable networks and gene regulatory networks.
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].
文摘Numerical simulations are used to investigate the self-sustained oscillating flows past an open cavity. The two-dimensional incompressible Navier-Stokes equations are solved directly by using the finite difference method for cavities with an upstream laminar boundary layer. A series of simulations are performed for a variety of cavity length-to-depth ratio. The results show the switching among some flow modes including non-oscillation mode, shear layer mode and wake mode. The variation of the Strouhal number is in favorable agreement with available experimental data. The results of flow fields in the cavity reveal the relationship between the cavity shear layer oscillation modes and recirculating vortices in the cavity.
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funding provided by the National Key R&D Program of China (Grant No. 2021YFB3801301)National Natural Science Foundation of China (Grant Nos. 22075076, 22208097 and 22378119)Shanghai Pilot Program for Basic Research (22TQ1400100-4)。
文摘Seawater electrolysis for hydrogen production faces inherent challenges, including side reactions, corrosion, and scaling, stemming from the intricate composition of seawater. In response, researchers have turned to continuous water splitting using forward osmosis(FO)-driven seawater desalination. However, the necessity of a neutral electrolyte hampers this strategy due to the limited current density and scarcity of precious metals. Herein, this study applies alkali-durable FO membranes to enable self-sustaining seawater splitting, which can selectively withdraw water molecules, from seawater, via concentration gradient. The membranes demonstrates outstanding perm-selectivity of water/ions(~5830 mol mol^(-1)) during month-long alkaline resistance tests, preventing electrolyte leaching(>97% OHàretention) while maintaining ~95%water balance(V_(FO)= V_(electrolysis)) via preserved concentration gradient for consistent forward-osmosis influx of water molecules. With the consistent electrolyte environment protected by the polyamide FO membranes, the Ni Fe-Ar-P catalyst exhibits promising performance: a sustain current density of 360 m A cmà2maintained at the cell voltage of 2.10 V and 2.15 V for 360 h in the offshore seawater, preventing Cl/Br corrosion(98% rejection) and Mg/Ca passivation(99.6% rejection). This research marks a significant advancement towards efficient and durable seawater-based hydrogen production.
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.
