Gait coordination in lower limbs plays a critical role in maintaining stability of the human body during walking.For transfemoral amputees,the absence of limbs disrupts this coordination,reducing prosthesis control ac...Gait coordination in lower limbs plays a critical role in maintaining stability of the human body during walking.For transfemoral amputees,the absence of limbs disrupts this coordination,reducing prosthesis control accuracy.Hip-knee coordination mapping offers a feasible solution for lower-limb prosthesis control,involving the generation of a reference trajectory for the knee joint by leveraging information from the hip.However,current reference trajectories are usually derived from static models,which cannot generate reference trajectories robustly when dealing with perturbations.Therefore,this paper introduces a time-dependent model based on the Delayed Feedback Reservoir(DFR)for hip-knee coordination in lower-limb prosthetic control.Experimental results show that DFR outperforms classical gait planning approaches when facing perturbations,achieving a 20%lower Root Mean Square Error(RMSE)and reducing residuals by up to 18.14 degrees.This research contributes to understanding gait mapping approaches and emphasizes the potential of time-dependent models for robust and strong lower-limb prosthetic control.The discovery provides a novel way to enhance the perturbation adaptability of prosthetic control.展开更多
Selenium(Se)is a nutrient that is considered beneficial for plants,because its improvement in growth,yield and quality helps plants to mitigate stress.The objective of this research was to evaluate the application of ...Selenium(Se)is a nutrient that is considered beneficial for plants,because its improvement in growth,yield and quality helps plants to mitigate stress.The objective of this research was to evaluate the application of sodium selenite(Na2SeO3),nanoparticles(SeNPs)and microparticles(SeMPs)of Se in cucumber seedlings,via two experiments:one with seed priming and the other with foliar application of Sematerials.The doses used were:0,0.1,0.5,1.0,1.5 and 3.0 mg⋅L^(−1),for each form of Se and for each form of application.Treatment 0 consisted of the application of distilled water,which was used as a control.The results indicated that the SeMPs treatment at 3.0 mg⋅L^(−1)for seed priming had the greatest effect on stem diameter and leaf area.Foliar application of SeMPs at 1.5 mg⋅L^(−1)was the most effective at increasing the leaf area.In terms of fresh and dry biomass(aerial,root and total)for seed priming,all the treatments were superior to the control,and SeMPs at 1.5 and 3.0 mg⋅L^(−1)caused the greatest effects.With foliar application,fresh root biomass improved to a greater extent with the SeMPs treatment at 3.0 mg⋅L^(−1),and dry biomass(aerial,root and total)increased with the SeMPs at 1.0 and 3.0 mg⋅L^(−1).With respect to the photosynthetic pigments,proteins,phenols and minerals,the Se treatments,both for seed priming and foliar application,caused increases and decreases;however,reduced glutathione(GSH)increased with treatments in both forms of application.The Se concentration in the seedlings increased as the dose of Se material increased,and greater accumulation was achieved with foliar application of SeNPs and SeMPs.The results indicate that the use of Se materials is recommended,mainly the use of SeMPs,which improved the variables studied.This opens new opportunities for further studies with SeMPs,as little information is available on their application in agricultural crops.展开更多
The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced met...The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced metering infrastructure services.However,this digital transformation also exposes power system to evolving threats,ranging from cyber intrusions and electricity theft to device malfunctions,and the unpredictable nature of these anomalies,coupled with the scarcity of labeled fault data,makes realtime detection exceptionally challenging.To address these difficulties,a real-time decision support framework is presented for smart meter anomality detection that leverages rolling time windows and two self-supervised contrastive learning modules.The first module synthesizes diverse negative samples to overcome the lack of labeled anomalies,while the second captures intrinsic temporal patterns for enhanced contextual discrimination.The end-to-end framework continuously updates its model with rolling updated meter data to deliver timely identification of emerging abnormal behaviors in evolving grids.Extensive evaluations on eight publicly available smart meter datasets over seven diverse abnormal patterns testing demonstrate the effectiveness of the proposed full framework,achieving average recall and F1 score of more than 0.85.展开更多
The intricate relationship between origami and mechanism underscores the fertile ground for innovation,which is particularly evident in the construction theory of thick-panel origami.Despite its potential,thick panel ...The intricate relationship between origami and mechanism underscores the fertile ground for innovation,which is particularly evident in the construction theory of thick-panel origami.Despite its potential,thick panel origami remains relatively unexplored in the context of single-loop metamorphic mechanisms.Drawing inspiration from thickpanel origami,particularly Miura origami,this study proposes a pioneering single-loop 6R multiple metamorphic mechanism.Through rigorous mathematical modeling(including the construction and resolution of the D-H closed-loop equation)and leveraging advanced analytical tools such as the screw theory and Lie theory,this study meticulously elucidates the planar,spherical,and Bennett motion branches of the mechanism.Furthermore,it delineates all the three bifurcation points between the motion branches,thereby providing a comprehensive understanding of the kinematic behavior of the mechanism.A metamorphic network can be constructed by applying several single-loop mechanisms to a symmetrical layout.Owing to its metamorphic properties,this network can act as a structural backbone for deployable antennas,aerospace shelters,and morphing wing units,thereby enabling a single mechanism to achieve multiple folding configurations.This paper not only introduces innovative metamorphic mechanisms but also suggests a promising method for uncovering and designing metamorphic mechanisms by developing new mechanisms from thick-panel origami.展开更多
Small-scale magnetic soft robots are promising candidates for minimally invasive medical applications;however,they struggle to achieve efficient locomotion across various interfaces.In this study,we propose a magnetic...Small-scale magnetic soft robots are promising candidates for minimally invasive medical applications;however,they struggle to achieve efficient locomotion across various interfaces.In this study,we propose a magnetic soft robot that integrates two distinct bio-inspired locomotion modes for enhanced interface navigation.Inspired by water striders’superhydrophobic legs and the meniscus climbing behavior of Pyrrhalta nymphaeae larvae,we developed a rectangular sheet-based robot with hydrophobic surface treatment and novel control strategies.The proposed robot implements two locomotion modes:a bipedal peristaltic locomotion mode(BPLM)and a single-region contact-vibration locomotion mode(SCLM).The BPLM achieves stable movement at 20 mm/s through coordinated front-rear contact points,whereas the SCLM reaches an ultrafast speed of 52 mm/s by optimizing surface tension interactions.The proposed robot demonstrates precise trajectory control with minimal deviations and successfully navigates confined spaces while manipulating objects.Theoretical analysis and experimental validation demonstrate that the integration of triangular wave control signals and steady-state components enables smooth transitions between locomotion modes.This study presents a new paradigm for bio-inspired design of small-scale robots and demonstrates the potential for medical applications requiring precise navigation across multiple terrains.展开更多
Local precise drug delivery is conducive to improving therapeutic efficacy and minimizing off-target toxicity.Current local delivery approaches are focused mostly on superficial or postoperative tumor lesions,due to t...Local precise drug delivery is conducive to improving therapeutic efficacy and minimizing off-target toxicity.Current local delivery approaches are focused mostly on superficial or postoperative tumor lesions,due to the challenges posed by the inaccessibility of deep-seated tumors.Herein,we report a magnetic continuum soft robot capable of non-invasive and site-specific delivery of prodrug nanoassemblies-loaded hydrogel.The nanoassemblies are co-assembled from redox-responsive docetaxel prodrug and oxaliplatin prodrug,and subsequently embedded into a hydrogel matrix.The hydrogel precursor and crosslinker are synchronously delivered using the soft robot under magnetic guidance and in situ crosslinked at the gastric cancer lesions,forming a drug depot for sustained release and long-lasting treatment.As the hydrogel gradually degrades,the nanoassemblies are internalized by tumor cells.The redox response ability enables them to be selectively activatedwithin tumor cells to trigger the release of docetaxel and oxaliplatin,exerting a synergistic anti-tumor effect.We find that the combination effectively induces immunogenic cell death of gastric tumor,enhancing antitumor immune responses.This strategy offers an intelligent and controllable integration platform for precise drug delivery and combined chemo-immunotherapy.展开更多
As human–robot interaction(HRI)technology advances,dexterous robotic hands are playing a dual role—serving both as tools for manipulation and as channels for non-verbal communication.While much of the existing resea...As human–robot interaction(HRI)technology advances,dexterous robotic hands are playing a dual role—serving both as tools for manipulation and as channels for non-verbal communication.While much of the existing research emphasizes improving grasping and structural dexterity,the semantic dimension of gestures and its impact on user experience has been relatively overlooked.Studies from HRI and cognitive psychology consistently show that the naturalness and cognitive empathy of gestures significantly influence user trust,satisfaction,and engagement.This shift reflects a broader transition from mechanically driven designs toward cognitively empathic interactions—robots’ability to infer human affect,intent,and social context to generate appropriate nonverbal responses.In this paper,we argue that large language models(LLMs)enable a paradigm shift in gesture control—from rule-based execution to semantic-driven,context-aware generation.By leveraging LLMs and visual-language models,robots can interpret environmental and social cues,dynamically map emotions,and generate gestures aligned with human communication norms.We conducted a comprehensive review of research in dexterous hand mechanics,gesture semantics,and user experience evaluation,integrating insights from linguistics and cognitive science.Furthermore,we propose a closed-loop framework—"perception–cognition–generation–assessment"—to guide gesture design through iterative,multimodal feedback.This framework lays the conceptual foundation for building universal,adaptive,and emotionally intelligent gesture systems in future human–robot interaction.展开更多
Parallel mechanisms(PMs)are known for their precision,stiffness,and load‐carrying capacity.However,the rigidity of their end‐effectors limits adaptability in tasks involving multi‐point interaction or the manipulat...Parallel mechanisms(PMs)are known for their precision,stiffness,and load‐carrying capacity.However,the rigidity of their end‐effectors limits adaptability in tasks involving multi‐point interaction or the manipulation of irregular objects.To resolve this challenge,parallel mechanisms with configurable platforms(PMCPs)have been developed,utilizing configurable kinematic chains to replace rigid end‐effectors,allowing for adjustments in shape and contact points.This paper comprehensively explores the characteristics of PMCPs,emphasizing the analysis of motion pattern,design methodology,kinematic performance,and a wide range of applications.PMCPs are categorized into groups based on specific criteria,followed by methodologies for analyzing mobility,reconfiguration,workspace,and singularity.Additionally,significant applications spanning several robotic fields are enumerated to highlight the potential of PMCPs.Furthermore,despite PMCPs providing considerable advantages in task adaptability,challenges remain in systematic type synthesis,motion description,and kinematic and dynamic complexity.This paper consolidates advancements in PMCPs to guide researchers toward next‐generation parallel robotic systems.展开更多
Dynamic dimension assessments of tumor tissues have broad relevance in clinical diagnosis and treatments of patients.Current technologies for such purpose include quasi-static measurements that lack microscale resolut...Dynamic dimension assessments of tumor tissues have broad relevance in clinical diagnosis and treatments of patients.Current technologies for such purpose include quasi-static measurements that lack microscale resolution and sensing sites,with limited capabilities for time-dependent,three-dimensional profiling of tumors particularly at early growth stage.Here,we report the conformal Hall-sensor-based systems for continuous monitoring of tumor morphological features such as growth rates and volumes.Such platforms incorporate ultrathin crystalline-silicon nanomembranes(200 nm thick)as basis for displacement sensing via magnetic flux detection,in an array design that yields spatiotemporal information of tumor geometries at high sensitivity.Evaluation involves real-time measurements on a living mouse model with tumor tissues at various pathological conditions,where the integration with deep learning algorithms can further enable the system for large-scale tumor profile reconstruction across tissue surfaces.These microsystems provide the potential for monitoring of tumor progression and treatment guidance in patients.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.12372065,12372022,and 11932015)Shanghai Pilot Program for Basic Research—Fudan University(Grant No.21TQ1400100-22TQ009).
文摘Gait coordination in lower limbs plays a critical role in maintaining stability of the human body during walking.For transfemoral amputees,the absence of limbs disrupts this coordination,reducing prosthesis control accuracy.Hip-knee coordination mapping offers a feasible solution for lower-limb prosthesis control,involving the generation of a reference trajectory for the knee joint by leveraging information from the hip.However,current reference trajectories are usually derived from static models,which cannot generate reference trajectories robustly when dealing with perturbations.Therefore,this paper introduces a time-dependent model based on the Delayed Feedback Reservoir(DFR)for hip-knee coordination in lower-limb prosthetic control.Experimental results show that DFR outperforms classical gait planning approaches when facing perturbations,achieving a 20%lower Root Mean Square Error(RMSE)and reducing residuals by up to 18.14 degrees.This research contributes to understanding gait mapping approaches and emphasizes the potential of time-dependent models for robust and strong lower-limb prosthetic control.The discovery provides a novel way to enhance the perturbation adaptability of prosthetic control.
文摘Selenium(Se)is a nutrient that is considered beneficial for plants,because its improvement in growth,yield and quality helps plants to mitigate stress.The objective of this research was to evaluate the application of sodium selenite(Na2SeO3),nanoparticles(SeNPs)and microparticles(SeMPs)of Se in cucumber seedlings,via two experiments:one with seed priming and the other with foliar application of Sematerials.The doses used were:0,0.1,0.5,1.0,1.5 and 3.0 mg⋅L^(−1),for each form of Se and for each form of application.Treatment 0 consisted of the application of distilled water,which was used as a control.The results indicated that the SeMPs treatment at 3.0 mg⋅L^(−1)for seed priming had the greatest effect on stem diameter and leaf area.Foliar application of SeMPs at 1.5 mg⋅L^(−1)was the most effective at increasing the leaf area.In terms of fresh and dry biomass(aerial,root and total)for seed priming,all the treatments were superior to the control,and SeMPs at 1.5 and 3.0 mg⋅L^(−1)caused the greatest effects.With foliar application,fresh root biomass improved to a greater extent with the SeMPs treatment at 3.0 mg⋅L^(−1),and dry biomass(aerial,root and total)increased with the SeMPs at 1.0 and 3.0 mg⋅L^(−1).With respect to the photosynthetic pigments,proteins,phenols and minerals,the Se treatments,both for seed priming and foliar application,caused increases and decreases;however,reduced glutathione(GSH)increased with treatments in both forms of application.The Se concentration in the seedlings increased as the dose of Se material increased,and greater accumulation was achieved with foliar application of SeNPs and SeMPs.The results indicate that the use of Se materials is recommended,mainly the use of SeMPs,which improved the variables studied.This opens new opportunities for further studies with SeMPs,as little information is available on their application in agricultural crops.
文摘The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced metering infrastructure services.However,this digital transformation also exposes power system to evolving threats,ranging from cyber intrusions and electricity theft to device malfunctions,and the unpredictable nature of these anomalies,coupled with the scarcity of labeled fault data,makes realtime detection exceptionally challenging.To address these difficulties,a real-time decision support framework is presented for smart meter anomality detection that leverages rolling time windows and two self-supervised contrastive learning modules.The first module synthesizes diverse negative samples to overcome the lack of labeled anomalies,while the second captures intrinsic temporal patterns for enhanced contextual discrimination.The end-to-end framework continuously updates its model with rolling updated meter data to deliver timely identification of emerging abnormal behaviors in evolving grids.Extensive evaluations on eight publicly available smart meter datasets over seven diverse abnormal patterns testing demonstrate the effectiveness of the proposed full framework,achieving average recall and F1 score of more than 0.85.
基金Supported by National Natural Science Foundation of China(Grant Nos.52192634,52305015,52335003)Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515011268)Science and Technology Innovation Committee of Shenzhen(Grant Nos.GXWD20231129102029003,KQTD20210811090146075).
文摘The intricate relationship between origami and mechanism underscores the fertile ground for innovation,which is particularly evident in the construction theory of thick-panel origami.Despite its potential,thick panel origami remains relatively unexplored in the context of single-loop metamorphic mechanisms.Drawing inspiration from thickpanel origami,particularly Miura origami,this study proposes a pioneering single-loop 6R multiple metamorphic mechanism.Through rigorous mathematical modeling(including the construction and resolution of the D-H closed-loop equation)and leveraging advanced analytical tools such as the screw theory and Lie theory,this study meticulously elucidates the planar,spherical,and Bennett motion branches of the mechanism.Furthermore,it delineates all the three bifurcation points between the motion branches,thereby providing a comprehensive understanding of the kinematic behavior of the mechanism.A metamorphic network can be constructed by applying several single-loop mechanisms to a symmetrical layout.Owing to its metamorphic properties,this network can act as a structural backbone for deployable antennas,aerospace shelters,and morphing wing units,thereby enabling a single mechanism to achieve multiple folding configurations.This paper not only introduces innovative metamorphic mechanisms but also suggests a promising method for uncovering and designing metamorphic mechanisms by developing new mechanisms from thick-panel origami.
基金supported by the Shenzhen Science and Technology Program(Nos.JCYJ20210324132810026,KQTD20210811090146075,and GXWD20220811164014001)the National Natural Science Foundation of China(Nos.52375175,52005128,62473277,and 52475075)+4 种基金the National Key Research and Development Program of China(No.2022YFC3802302)Guangdong Basic and Applied Basic Research Foundation(No.2024A1515240015)Jiangsu Provincial Outstanding Youth Program(No.BK20230072)Suzhou Industrial Foresight and Key Core Technology Project(No.SYC2022044)a grant from Open Foundation of the State Key Laboratory of Fluid Power and Mechatronic Systems,and grants from Jiangsu Qinglan Project and Jiangsu 333 High-level Talents.
文摘Small-scale magnetic soft robots are promising candidates for minimally invasive medical applications;however,they struggle to achieve efficient locomotion across various interfaces.In this study,we propose a magnetic soft robot that integrates two distinct bio-inspired locomotion modes for enhanced interface navigation.Inspired by water striders’superhydrophobic legs and the meniscus climbing behavior of Pyrrhalta nymphaeae larvae,we developed a rectangular sheet-based robot with hydrophobic surface treatment and novel control strategies.The proposed robot implements two locomotion modes:a bipedal peristaltic locomotion mode(BPLM)and a single-region contact-vibration locomotion mode(SCLM).The BPLM achieves stable movement at 20 mm/s through coordinated front-rear contact points,whereas the SCLM reaches an ultrafast speed of 52 mm/s by optimizing surface tension interactions.The proposed robot demonstrates precise trajectory control with minimal deviations and successfully navigates confined spaces while manipulating objects.Theoretical analysis and experimental validation demonstrate that the integration of triangular wave control signals and steady-state components enables smooth transitions between locomotion modes.This study presents a new paradigm for bio-inspired design of small-scale robots and demonstrates the potential for medical applications requiring precise navigation across multiple terrains.
基金supported by National Natural Science Foundation of China(No.82161138029)Liaoning Revitalization Talents Program(No.XLYC2402040)the Project of China-Japan Joint International Laboratory of Advanced Drug Delivery System Research and Translation of Liaoning Province(No.2024JH2/102100007).
文摘Local precise drug delivery is conducive to improving therapeutic efficacy and minimizing off-target toxicity.Current local delivery approaches are focused mostly on superficial or postoperative tumor lesions,due to the challenges posed by the inaccessibility of deep-seated tumors.Herein,we report a magnetic continuum soft robot capable of non-invasive and site-specific delivery of prodrug nanoassemblies-loaded hydrogel.The nanoassemblies are co-assembled from redox-responsive docetaxel prodrug and oxaliplatin prodrug,and subsequently embedded into a hydrogel matrix.The hydrogel precursor and crosslinker are synchronously delivered using the soft robot under magnetic guidance and in situ crosslinked at the gastric cancer lesions,forming a drug depot for sustained release and long-lasting treatment.As the hydrogel gradually degrades,the nanoassemblies are internalized by tumor cells.The redox response ability enables them to be selectively activatedwithin tumor cells to trigger the release of docetaxel and oxaliplatin,exerting a synergistic anti-tumor effect.We find that the combination effectively induces immunogenic cell death of gastric tumor,enhancing antitumor immune responses.This strategy offers an intelligent and controllable integration platform for precise drug delivery and combined chemo-immunotherapy.
基金supported by the National Natural Science Foundation of China(62173114)Guangdong Basic and Applied Basic Research Foundation(2024A1515011228)+2 种基金Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics(2023B1212010005)the Shenzhen Science and Technology Program(KJZD20240903100501002 and GXWD20231129174132001)the Program of Shenzhen Pea-cock Innovation Team(KQTD20210811090146075).
文摘As human–robot interaction(HRI)technology advances,dexterous robotic hands are playing a dual role—serving both as tools for manipulation and as channels for non-verbal communication.While much of the existing research emphasizes improving grasping and structural dexterity,the semantic dimension of gestures and its impact on user experience has been relatively overlooked.Studies from HRI and cognitive psychology consistently show that the naturalness and cognitive empathy of gestures significantly influence user trust,satisfaction,and engagement.This shift reflects a broader transition from mechanically driven designs toward cognitively empathic interactions—robots’ability to infer human affect,intent,and social context to generate appropriate nonverbal responses.In this paper,we argue that large language models(LLMs)enable a paradigm shift in gesture control—from rule-based execution to semantic-driven,context-aware generation.By leveraging LLMs and visual-language models,robots can interpret environmental and social cues,dynamically map emotions,and generate gestures aligned with human communication norms.We conducted a comprehensive review of research in dexterous hand mechanics,gesture semantics,and user experience evaluation,integrating insights from linguistics and cognitive science.Furthermore,we propose a closed-loop framework—"perception–cognition–generation–assessment"—to guide gesture design through iterative,multimodal feedback.This framework lays the conceptual foundation for building universal,adaptive,and emotionally intelligent gesture systems in future human–robot interaction.
基金founded by the National Nature Science Foundation of China(Grant 52305012)the Research Institute for Artificial Intelligence of Things(RIAIoT),Research Institute for Intelligent Wearable Systems(RI‐IWEAR),Research Institute for Advanced Manufacturing(RIAM),and Research Centre of Textiles for Future Fashion(RCTFF)at the Hong Kong Polytechnic University.
文摘Parallel mechanisms(PMs)are known for their precision,stiffness,and load‐carrying capacity.However,the rigidity of their end‐effectors limits adaptability in tasks involving multi‐point interaction or the manipulation of irregular objects.To resolve this challenge,parallel mechanisms with configurable platforms(PMCPs)have been developed,utilizing configurable kinematic chains to replace rigid end‐effectors,allowing for adjustments in shape and contact points.This paper comprehensively explores the characteristics of PMCPs,emphasizing the analysis of motion pattern,design methodology,kinematic performance,and a wide range of applications.PMCPs are categorized into groups based on specific criteria,followed by methodologies for analyzing mobility,reconfiguration,workspace,and singularity.Additionally,significant applications spanning several robotic fields are enumerated to highlight the potential of PMCPs.Furthermore,despite PMCPs providing considerable advantages in task adaptability,challenges remain in systematic type synthesis,motion description,and kinematic and dynamic complexity.This paper consolidates advancements in PMCPs to guide researchers toward next‐generation parallel robotic systems.
文摘Dynamic dimension assessments of tumor tissues have broad relevance in clinical diagnosis and treatments of patients.Current technologies for such purpose include quasi-static measurements that lack microscale resolution and sensing sites,with limited capabilities for time-dependent,three-dimensional profiling of tumors particularly at early growth stage.Here,we report the conformal Hall-sensor-based systems for continuous monitoring of tumor morphological features such as growth rates and volumes.Such platforms incorporate ultrathin crystalline-silicon nanomembranes(200 nm thick)as basis for displacement sensing via magnetic flux detection,in an array design that yields spatiotemporal information of tumor geometries at high sensitivity.Evaluation involves real-time measurements on a living mouse model with tumor tissues at various pathological conditions,where the integration with deep learning algorithms can further enable the system for large-scale tumor profile reconstruction across tissue surfaces.These microsystems provide the potential for monitoring of tumor progression and treatment guidance in patients.
