BACKGROUND:Hemiplegia,a prevalent stroke-related condition,is often studied for motor dysfunction;however,spasticity remains under-researched.Abnormal muscle tone significantly hinders hemiplegic patients’walking rec...BACKGROUND:Hemiplegia,a prevalent stroke-related condition,is often studied for motor dysfunction;however,spasticity remains under-researched.Abnormal muscle tone significantly hinders hemiplegic patients’walking recovery.OBJECTIVE:To determine whether early suspension-protected training with a personal assistant machine for stroke patients enhances walking ability and prevents muscle spasms.METHODS:Thirty-two early-stage stroke patients from Shenzhen University General Hospital and the China Rehabilitation Research Center were randomly assigned to the experimental group(n=16)and the control group(n=16).Both groups underwent 4 weeks of gait training under the suspension protection system for 30 minutes daily,5 days a week.The experimental group used the personal assistant machine during training.Three-dimensional gait analysis(using the Cortex motion capture system),Brunnstrom staging,Fugl-Meyer Assessment for lower limb motor function,Fugl-Meyer balance function,and the modified Ashworth Scale were evaluated within 1 week before the intervention and after 4 weeks of intervention.RESULTS AND CONCLUSION:After the 4-week intervention,all outcome measures showed significant changes in each group.The experimental group had a small but significant increase in the modified Ashworth Scale score(P<0.05,d=|0.15|),while the control group had a large significant increase(P<0.05,d=|1.48|).The experimental group demonstrated greater improvements in walking speed(16.5 to 38.44 cm/s,P<0.05,d=|4.01|),step frequency(46.44 to 64.94 steps/min,P<0.05,d=|2.32|),stride length(15.50 to 29.81 cm,P<0.05,d=|3.44|),and peak hip and knee flexion(d=|1.82|to|2.17|).After treatment,the experimental group showed significantly greater improvements than the control group in walking speed(38.44 vs.26.63 cm/s,P<0.05,d=|2.75|),stride length,peak hip and knee flexion(d=|1.31|to|1.45|),step frequency(64.94 vs.59.38 steps/min,P<0.05,d=|0.85|),and a reduced support phase(bilateral:24.31%vs.28.38%,P<0.05,d=|0.88|;non-paretic:66.19%vs.70.13%,P<0.05,d=|0.94|).For early hemiplegia,personal assistant machine-assisted gait training under the suspension protection system helps establish a correct gait pattern,prevents muscle spasms,and improves motor function.展开更多
In this paper,large deviations principle(LDP)and moderate deviations principle(MDP)of record numbers in random walks are studied under certain conditions.The results show that the rate functions of LDP and MDP are dif...In this paper,large deviations principle(LDP)and moderate deviations principle(MDP)of record numbers in random walks are studied under certain conditions.The results show that the rate functions of LDP and MDP are different from those of weak record numbers,which are interesting complements of the conclusions by Li and Yao[1].展开更多
The no-cloning theorem has sparked considerable interest in achieving high-fidelity approximate quantum cloning.Most of the previous studies mainly focused on the cloning of single particle states,and cloning schemes ...The no-cloning theorem has sparked considerable interest in achieving high-fidelity approximate quantum cloning.Most of the previous studies mainly focused on the cloning of single particle states,and cloning schemes used there are incapable of cloning quantum entangled states in multipartite systems.Few schemes were proposed for cloning multiparticle states,which consume more entanglement resources with loss of qubits,and the fidelity of the cloned state is relatively low.In this paper,cloning schemes for bipartite and tripartite entangled states based on photonic quantum walk and entanglement swapping are proposed.The results show that according to the proposed schemes,two high-fidelity(up to 0.75)cloned states can be obtained with less quantum resource consumption.Because of the simple cloning steps,few quantum resources and high fidelity,these schemes are both efficient and feasible.Moreover,this cloning machine eliminates the need for tracing out cloning machine,thereby minimizing resource waste.展开更多
[Objectives]To synthesize evidence on HIIT versus moderate-intensity continuous training(MICT)or routine rehabilitation in stroke survivors.[Methods]We systematically searched 8 databases(PubMed,EMBASE,CENTRAL,Web of ...[Objectives]To synthesize evidence on HIIT versus moderate-intensity continuous training(MICT)or routine rehabilitation in stroke survivors.[Methods]We systematically searched 8 databases(PubMed,EMBASE,CENTRAL,Web of Science,SPORTSDiscus,PsycINFO,SCOPUS,CINAHL)up to May 2025.Seventeen randomized controlled trials(RCTs;total n=1142)met inclusion criteria:adults with stroke,device-based HIIT(≥70%HRR/VO 2peak),and outcomes assessing VO 2peak,6-min walk distance(6MWD),or Berg Balance Scale(BBS).Methodological quality was evaluated using the PEDro scale.Pooled effect sizes(Hedges'g)were calculated via random-effects models,with heterogeneity quantified by I^(2).[Results]HIIT significantly improved peak oxygen uptake(VO 2peak)versus controls(g=0.59,95%CI:0.44-0.75,p<0.001;I^(2)=16.29%).Low heterogeneity and symmetrical funnel plots supported robustness.HIIT also enhanced walking endurance(6MWD:g=0.32,95%CI:0.16-0.48,p<0.01;I^(2)=30%).In contrast,no significant benefit was observed for balance function(BBS:g=0.07,95%CI:-0.13-0.26,p=0.50;I^(2)=0%).[Conclusions]HIIT is a safe and highly effective intervention for enhancing aerobic capacity and walking function post-stroke.Its benefits are maximized at higher intensities and longer durations but do not extend to balance improvement.Integrating HIIT into stroke rehabilitation protocols is strongly recommended to promote functional independence.展开更多
Walking is the basic locomotion pattern for bipedal robots.The walking pattern is widely generated using the linear inverted pendulum model.The linear inverted pendulum motion of each support period can be designed as...Walking is the basic locomotion pattern for bipedal robots.The walking pattern is widely generated using the linear inverted pendulum model.The linear inverted pendulum motion of each support period can be designed as a walk primitive to be connected to form a walking trajectory.A novel method of integrating double support phase into the walk primitive was proposed in this article.The method describes the generation of walking patterns using walk primitives with double support,specifically for lateral plane including walking in place,walking for lateral,and walking initiation,and for sagittal plane including fixed step length walking,variable step length walking,and walking initiation.Compared to walk primitives without double support phase,those with double support phase reduce the maximum speed required by the robot and eliminate the need to adjust foothold for achieving continuous speed.The performance of the proposed method is validated by simulations and experiments on Neubot,a position-controlled biped robot.展开更多
Background The redirected walking(RDW)method for multi-user collaboration requires maintaining the relative position between users in a virtual environment(VE)and physical environment(PE).A chasing game in a VE is a t...Background The redirected walking(RDW)method for multi-user collaboration requires maintaining the relative position between users in a virtual environment(VE)and physical environment(PE).A chasing game in a VE is a typical virtual reality game that entails multi-user collaboration.When a user approaches and interacts with a target user in the VE,the user is expected to approach and interact with the target user in the corresponding PE as well.Existing methods of multi-user RDW mainly focus on obstacle avoidance,which does not account for the relative positional relationship between the users in both VE and PE.Methods To enhance the user experience and facilitate potential interaction,this paper presents a novel dynamic alignment algorithm for multi-user collaborative redirected walking(DA-RDW)in a shared PE where the target user and other users are moving.This algorithm adopts improved artificial potential fields,where the repulsive force is a function of the relative position and velocity of the user with respect to dynamic obstacles.For the best alignment,this algorithm sets the alignment-guidance force in several cases and then converts it into a constrained optimization problem to obtain the optimal direction.Moreover,this algorithm introduces a potential interaction object selection strategy for a dynamically uncertain environment to speed up the subsequent alignment.To balance obstacle avoidance and alignment,this algorithm uses the dynamic weightings of the virtual and physical distances between users and the target to determine the resultant force vector.Results The efficacy of the proposed method was evaluated using a series of simulations and live-user experiments.The experimental results demonstrate that our novel dynamic alignment method for multi-user collaborative redirected walking can reduce the distance error in both VE and PE to improve alignment with fewer collisions.展开更多
The successful application of perimeter control of urban traffic system strongly depends on the macroscopic fundamental diagram of the targeted region.Despite intensive studies on the partitioning of urban road networ...The successful application of perimeter control of urban traffic system strongly depends on the macroscopic fundamental diagram of the targeted region.Despite intensive studies on the partitioning of urban road networks,the dynamic partitioning of urban regions reflecting the propagation of congestion remains an open question.This paper proposes to partition the network into homogeneous sub-regions based on random walk algorithm.Starting from selected random walkers,the road network is partitioned from the early morning when congestion emerges.A modified Akaike information criterion is defined to find the optimal number of partitions.Region boundary adjustment algorithms are adopted to optimize the partitioning results to further ensure the correlation of partitions.The traffic data of Melbourne city are used to verify the effectiveness of the proposed partitioning method.展开更多
Random walk algorithms are crucial for sampling and approximation problems in statistical physics and theoretical computer science.The mixing property is necessary for Markov chains to approach stationary distribution...Random walk algorithms are crucial for sampling and approximation problems in statistical physics and theoretical computer science.The mixing property is necessary for Markov chains to approach stationary distributions and is facilitated by walks.Quantum walks show promise for faster mixing times than classical methods but lack universal proof,especially in finite group settings.Here,we investigate the continuous-time quantum walks on Cayley graphs of the dihedral group D_(2n)for odd n,generated by the smallest inverse closed symmetric subset.We present a significant finding that,in contrast to the classical mixing time on these Cayley graphs,which typically takes at least orderΩ(n^(2)log(1/2∈)),the continuous-time quantum walk mixing time on D_(2n)is of order O(n(log n)^(5)log(1/∈)),achieving a quadratic improvement over the classical case.Our paper advances the general understanding of quantum walk mixing on Cayley graphs,highlighting the improved mixing time achieved by continuous-time quantum walks on D_(2n).This work has potential applications in algorithms for a class of sampling problems based on non-abelian groups.展开更多
Quantum algorithms have demonstrated provable speedups over classical counterparts,yet establishing a comprehensive theoretical framework to understand the quantum advantage remains a core challenge.In this work,we de...Quantum algorithms have demonstrated provable speedups over classical counterparts,yet establishing a comprehensive theoretical framework to understand the quantum advantage remains a core challenge.In this work,we decode the quantum search advantage by investigating the critical role of quantum state properties in random-walk-based algorithms.We propose three distinct variants of quantum random-walk search algorithms and derive exact analytical expressions for their success probabilities.These probabilities are fundamentally determined by specific initial state properties:the coherence fraction governs the first algorithm’s performance,while entanglement and coherence dominate the outcomes of the second and third algorithms,respectively.We show that increased coherence fraction enhances success probability,but greater entanglement and coherence reduce it in the latter two cases.These findings reveal fundamental insights into harnessing quantum properties for advantage and guide algorithm design.Our searches achieve Grover-like speedups and show significant potential for quantum-enhanced machine learning.展开更多
文摘BACKGROUND:Hemiplegia,a prevalent stroke-related condition,is often studied for motor dysfunction;however,spasticity remains under-researched.Abnormal muscle tone significantly hinders hemiplegic patients’walking recovery.OBJECTIVE:To determine whether early suspension-protected training with a personal assistant machine for stroke patients enhances walking ability and prevents muscle spasms.METHODS:Thirty-two early-stage stroke patients from Shenzhen University General Hospital and the China Rehabilitation Research Center were randomly assigned to the experimental group(n=16)and the control group(n=16).Both groups underwent 4 weeks of gait training under the suspension protection system for 30 minutes daily,5 days a week.The experimental group used the personal assistant machine during training.Three-dimensional gait analysis(using the Cortex motion capture system),Brunnstrom staging,Fugl-Meyer Assessment for lower limb motor function,Fugl-Meyer balance function,and the modified Ashworth Scale were evaluated within 1 week before the intervention and after 4 weeks of intervention.RESULTS AND CONCLUSION:After the 4-week intervention,all outcome measures showed significant changes in each group.The experimental group had a small but significant increase in the modified Ashworth Scale score(P<0.05,d=|0.15|),while the control group had a large significant increase(P<0.05,d=|1.48|).The experimental group demonstrated greater improvements in walking speed(16.5 to 38.44 cm/s,P<0.05,d=|4.01|),step frequency(46.44 to 64.94 steps/min,P<0.05,d=|2.32|),stride length(15.50 to 29.81 cm,P<0.05,d=|3.44|),and peak hip and knee flexion(d=|1.82|to|2.17|).After treatment,the experimental group showed significantly greater improvements than the control group in walking speed(38.44 vs.26.63 cm/s,P<0.05,d=|2.75|),stride length,peak hip and knee flexion(d=|1.31|to|1.45|),step frequency(64.94 vs.59.38 steps/min,P<0.05,d=|0.85|),and a reduced support phase(bilateral:24.31%vs.28.38%,P<0.05,d=|0.88|;non-paretic:66.19%vs.70.13%,P<0.05,d=|0.94|).For early hemiplegia,personal assistant machine-assisted gait training under the suspension protection system helps establish a correct gait pattern,prevents muscle spasms,and improves motor function.
基金supported by the National Natural Science Foundation of China(Grant No.11671145)the Science and Technology Commission of Shanghai Municipality(Grant No.18dz2271000).
文摘In this paper,large deviations principle(LDP)and moderate deviations principle(MDP)of record numbers in random walks are studied under certain conditions.The results show that the rate functions of LDP and MDP are different from those of weak record numbers,which are interesting complements of the conclusions by Li and Yao[1].
文摘The no-cloning theorem has sparked considerable interest in achieving high-fidelity approximate quantum cloning.Most of the previous studies mainly focused on the cloning of single particle states,and cloning schemes used there are incapable of cloning quantum entangled states in multipartite systems.Few schemes were proposed for cloning multiparticle states,which consume more entanglement resources with loss of qubits,and the fidelity of the cloned state is relatively low.In this paper,cloning schemes for bipartite and tripartite entangled states based on photonic quantum walk and entanglement swapping are proposed.The results show that according to the proposed schemes,two high-fidelity(up to 0.75)cloned states can be obtained with less quantum resource consumption.Because of the simple cloning steps,few quantum resources and high fidelity,these schemes are both efficient and feasible.Moreover,this cloning machine eliminates the need for tracing out cloning machine,thereby minimizing resource waste.
文摘[Objectives]To synthesize evidence on HIIT versus moderate-intensity continuous training(MICT)or routine rehabilitation in stroke survivors.[Methods]We systematically searched 8 databases(PubMed,EMBASE,CENTRAL,Web of Science,SPORTSDiscus,PsycINFO,SCOPUS,CINAHL)up to May 2025.Seventeen randomized controlled trials(RCTs;total n=1142)met inclusion criteria:adults with stroke,device-based HIIT(≥70%HRR/VO 2peak),and outcomes assessing VO 2peak,6-min walk distance(6MWD),or Berg Balance Scale(BBS).Methodological quality was evaluated using the PEDro scale.Pooled effect sizes(Hedges'g)were calculated via random-effects models,with heterogeneity quantified by I^(2).[Results]HIIT significantly improved peak oxygen uptake(VO 2peak)versus controls(g=0.59,95%CI:0.44-0.75,p<0.001;I^(2)=16.29%).Low heterogeneity and symmetrical funnel plots supported robustness.HIIT also enhanced walking endurance(6MWD:g=0.32,95%CI:0.16-0.48,p<0.01;I^(2)=30%).In contrast,no significant benefit was observed for balance function(BBS:g=0.07,95%CI:-0.13-0.26,p=0.50;I^(2)=0%).[Conclusions]HIIT is a safe and highly effective intervention for enhancing aerobic capacity and walking function post-stroke.Its benefits are maximized at higher intensities and longer durations but do not extend to balance improvement.Integrating HIIT into stroke rehabilitation protocols is strongly recommended to promote functional independence.
基金supported in part by the National Key R&D Program under Grant 2018YFB1304504.
文摘Walking is the basic locomotion pattern for bipedal robots.The walking pattern is widely generated using the linear inverted pendulum model.The linear inverted pendulum motion of each support period can be designed as a walk primitive to be connected to form a walking trajectory.A novel method of integrating double support phase into the walk primitive was proposed in this article.The method describes the generation of walking patterns using walk primitives with double support,specifically for lateral plane including walking in place,walking for lateral,and walking initiation,and for sagittal plane including fixed step length walking,variable step length walking,and walking initiation.Compared to walk primitives without double support phase,those with double support phase reduce the maximum speed required by the robot and eliminate the need to adjust foothold for achieving continuous speed.The performance of the proposed method is validated by simulations and experiments on Neubot,a position-controlled biped robot.
基金Supported by STI 2030 Major Projects of China(2021ZD0200400).
文摘Background The redirected walking(RDW)method for multi-user collaboration requires maintaining the relative position between users in a virtual environment(VE)and physical environment(PE).A chasing game in a VE is a typical virtual reality game that entails multi-user collaboration.When a user approaches and interacts with a target user in the VE,the user is expected to approach and interact with the target user in the corresponding PE as well.Existing methods of multi-user RDW mainly focus on obstacle avoidance,which does not account for the relative positional relationship between the users in both VE and PE.Methods To enhance the user experience and facilitate potential interaction,this paper presents a novel dynamic alignment algorithm for multi-user collaborative redirected walking(DA-RDW)in a shared PE where the target user and other users are moving.This algorithm adopts improved artificial potential fields,where the repulsive force is a function of the relative position and velocity of the user with respect to dynamic obstacles.For the best alignment,this algorithm sets the alignment-guidance force in several cases and then converts it into a constrained optimization problem to obtain the optimal direction.Moreover,this algorithm introduces a potential interaction object selection strategy for a dynamically uncertain environment to speed up the subsequent alignment.To balance obstacle avoidance and alignment,this algorithm uses the dynamic weightings of the virtual and physical distances between users and the target to determine the resultant force vector.Results The efficacy of the proposed method was evaluated using a series of simulations and live-user experiments.The experimental results demonstrate that our novel dynamic alignment method for multi-user collaborative redirected walking can reduce the distance error in both VE and PE to improve alignment with fewer collisions.
基金Project supported by the National Natural Science Foundation of China(Grant No.12072340)the Chinese Scholarship Council and the Australia Research Council through a linkage project fund。
文摘The successful application of perimeter control of urban traffic system strongly depends on the macroscopic fundamental diagram of the targeted region.Despite intensive studies on the partitioning of urban road networks,the dynamic partitioning of urban regions reflecting the propagation of congestion remains an open question.This paper proposes to partition the network into homogeneous sub-regions based on random walk algorithm.Starting from selected random walkers,the road network is partitioned from the early morning when congestion emerges.A modified Akaike information criterion is defined to find the optimal number of partitions.Region boundary adjustment algorithms are adopted to optimize the partitioning results to further ensure the correlation of partitions.The traffic data of Melbourne city are used to verify the effectiveness of the proposed partitioning method.
基金supported by the Key-Area Research and Development Program of Guang-Dong Province(Grant No.2018B030326001)the National Natural Science Foundation of China(U1801661)Shenzhen Science and Technology Program(KQTD20200820113010023)。
文摘Random walk algorithms are crucial for sampling and approximation problems in statistical physics and theoretical computer science.The mixing property is necessary for Markov chains to approach stationary distributions and is facilitated by walks.Quantum walks show promise for faster mixing times than classical methods but lack universal proof,especially in finite group settings.Here,we investigate the continuous-time quantum walks on Cayley graphs of the dihedral group D_(2n)for odd n,generated by the smallest inverse closed symmetric subset.We present a significant finding that,in contrast to the classical mixing time on these Cayley graphs,which typically takes at least orderΩ(n^(2)log(1/2∈)),the continuous-time quantum walk mixing time on D_(2n)is of order O(n(log n)^(5)log(1/∈)),achieving a quadratic improvement over the classical case.Our paper advances the general understanding of quantum walk mixing on Cayley graphs,highlighting the improved mixing time achieved by continuous-time quantum walks on D_(2n).This work has potential applications in algorithms for a class of sampling problems based on non-abelian groups.
基金supported by the Fundamental Research Funds for the Central Universities,the National Natural Science Foundation of China(Grant Nos.12371132,12075159,12171044,12071179,and 12405006)the specific research fund of the Innovation Platform for Academicians of Hainan Province.
文摘Quantum algorithms have demonstrated provable speedups over classical counterparts,yet establishing a comprehensive theoretical framework to understand the quantum advantage remains a core challenge.In this work,we decode the quantum search advantage by investigating the critical role of quantum state properties in random-walk-based algorithms.We propose three distinct variants of quantum random-walk search algorithms and derive exact analytical expressions for their success probabilities.These probabilities are fundamentally determined by specific initial state properties:the coherence fraction governs the first algorithm’s performance,while entanglement and coherence dominate the outcomes of the second and third algorithms,respectively.We show that increased coherence fraction enhances success probability,but greater entanglement and coherence reduce it in the latter two cases.These findings reveal fundamental insights into harnessing quantum properties for advantage and guide algorithm design.Our searches achieve Grover-like speedups and show significant potential for quantum-enhanced machine learning.
