Walking assistance can be realized by active and passive robotic walkers when their users walk on even roads.However,fast signal processing and real-time control are necessary for active robotic walkers when the users...Walking assistance can be realized by active and passive robotic walkers when their users walk on even roads.However,fast signal processing and real-time control are necessary for active robotic walkers when the users walk on slopes,while assistive forces cannot be provided by passive robotic walkers when the users walk uphill.A robotic walker with an active-passive hybrid actuator(APHA)was developed in this study.The APHA,which consists of a rotary magnetorheological(MR)brake and a DC motor,can provide mobility assistance to users walking both uphill and downhill via the cooperative operation of the MR brake and DC motor.The rotary MR brake was designed with a T-shaped configuration,and the system was optimized to minimize the brake volume.Prototypes of the APHA and robotic walker were constructed.A control algorithm for the robotic walker was developed based on the characteristics of the APHA and the structure of the robotic walker.The mechanical properties of the APHA were characterized,and experiments were conducted to evaluate the mobility assistance supplied by the robotic walker on different roads.The results show that the APHA can meet the requirements of the robotic walker,and suitable assistive forces can be provided by the robotic walker,which has a simple mechanical structure and control method.展开更多
Existing microprocessor-controlled passive prosthetic knees(PaPKs)and active prosthetic knees(AcPKs)cannot truly simulate the muscle activity characteristics of the active–passive hybrid action of the knee during the...Existing microprocessor-controlled passive prosthetic knees(PaPKs)and active prosthetic knees(AcPKs)cannot truly simulate the muscle activity characteristics of the active–passive hybrid action of the knee during the normal gait.Differences in EMG between normal and different prosthetic gait for different phases were never separately analyzed.In this study,a novel hybrid active–passive prosthetic knee(HAPK)is proposed and if and how muscle activity and kinematics changes in different prosthetic gait are analyzed.The hybrid hydraulic-motor actuator is adopted to fully integrate the advantages of hydraulic compliance damping and motor efficiency,and the hierarchical control strategy is adopted to realize the adaptive predictive control of the HAPK.The kinematic data and EMG data of normal gait and different prosthetic gait were compared by experiments,so as to analyze the changes in the muscle activity and spatio-temporal data per phase compared to normal walking and the adaptations of amputees when walking with a different kind of prosthesis(the mechanical prosthesis(MePK),the PaPK and the HAPK).The results show that changes in prosthetic gait mainly consisted of decreased self-selected walking speed,gait symmetry and maximum knee flexion,increased first double support phase duration,muscle activation in both opposed and prosthetic limb and inter-subject variability.The differences between controls and MePK,PaPK and HAPK decreases sequentially.These results indicate that the hybrid active–passive actuating mode can have positive effects on improving the approximation of healthy gait characteristics.展开更多
Reconfigurable Intelligent Surfaces(RIS)have emerged as a promising technology for improving the reliability of massive MIMO communication networks.However,conventional RIS suffer from poor Spectral Efficiency(SE)and ...Reconfigurable Intelligent Surfaces(RIS)have emerged as a promising technology for improving the reliability of massive MIMO communication networks.However,conventional RIS suffer from poor Spectral Efficiency(SE)and high energy consumption,leading to complex Hybrid Precoding(HP)designs.To address these issues,we propose a new low-complexity HP model,named Dynamic Hybrid Relay Reflecting RIS based Hybrid Precoding(DHRR-RIS-HP).Our approach combines active and passive elements to cancel out the downsides of both conventional designs.We first design a DHRR-RIS and optimize the pilot and Channel State Information(CSI)estimation using an adaptive threshold method and Adaptive Back Propagation Neural Network(ABPNN)algorithm,respectively,to reduce the Bit Error Rate(BER)and energy consumption.To optimize the data stream,we cluster them into private and public streams using Enhanced Fuzzy C-Means(EFCM)algorithm,and schedule them based on priority and emergency level.To maximize the sum rate and SE,we perform digital precoder optimization at the Base Station(BS)side using Deep Deterministic Policy Gradient(DDPG)algorithm and analog precoder optimization at the DHRR-RIS using Fire Hawk Optimization(FHO)algorithm.We implement our proposed work using MATLAB R2020a and compare it with existing works using several validation metrics.Our results show that our proposed work outperforms existing works in terms of SE,Weighted Sum Rate(WSR),and BER.展开更多
Natural hybridization frequently occurs in plants and can facilitate gene flow between species, possibly resulting in species refusion. However, various reproductive barriers block the formation of hybrids and maintai...Natural hybridization frequently occurs in plants and can facilitate gene flow between species, possibly resulting in species refusion. However, various reproductive barriers block the formation of hybrids and maintain species integrity. Here, we conducted a field survey to examine natural hybridization and reproductive isolation （RI） between sympatric populations of Primula secundiflora and P. poissonii using ten nuclear simple sequence repeat （SSR） loci. Although introgressive hybridization occurred, species boundaries between P. secundiflora and P. poissonii were maintained through nearly complete reproductive isolation. These interfertite species provide an excellent model for studying the RI mechanisms and evolutionary forces that maintain species boundaries.展开更多
Benefiting from the growth of the bandwidth,Terahertz(THz)communication can support the new application with explosive requirements of the ultra-high-speed rates for future 6G wireless systems.In order to compensate f...Benefiting from the growth of the bandwidth,Terahertz(THz)communication can support the new application with explosive requirements of the ultra-high-speed rates for future 6G wireless systems.In order to compensate for the path loss of high frequency,massive Multiple-Input Multiple-Output(MIMO)can be utilized for high array gains by beamforming.However,the existing THz communication with massive MIMO has remarkably high energy consumption because a large number of analog phase shifters should be used to realize the analog beamforming.To solve this problem,a Reconfigurable Intelligent Surface(RIS)based hybrid precoding architecture for THz communication is developed in this paper,where the energy-hungry phased array is replaced by the energy-efficient RIS to realize the analog beamforming of the hybrid precoding.Then,based on the proposed RIS-based architecture,a sum-rate maximization problem for hybrid precoding is investigated.Since the phase shifts implemented by RIS in practice are often discrete,this sum-rate maximization problem with a non-convex constraint is challenging.Next,the sum-rate maximization problem is reformulated as a parallel Deep Neural Network(DNN)based classification problem,which can be solved by the proposed low-complexity Deep Learning based Multiple Discrete Classification(DL-MDC)hybrid precoding scheme.Finally,we provide numerous simulation results to show that the proposed DL-MDC scheme works well both in the theoretical Saleh-Valenzuela channel model and practical 3GPP channel model.Compared with existing iterative search algorithms,the proposed DL-MDC scheme significantly reduces the runtime with a negligible performance loss.展开更多
基金Supported by National Natural Science Foundation of China(Grant No.U1813222)Hebei Provincial Natural Science Foundation of China(Grant No.E2018202316).
文摘Walking assistance can be realized by active and passive robotic walkers when their users walk on even roads.However,fast signal processing and real-time control are necessary for active robotic walkers when the users walk on slopes,while assistive forces cannot be provided by passive robotic walkers when the users walk uphill.A robotic walker with an active-passive hybrid actuator(APHA)was developed in this study.The APHA,which consists of a rotary magnetorheological(MR)brake and a DC motor,can provide mobility assistance to users walking both uphill and downhill via the cooperative operation of the MR brake and DC motor.The rotary MR brake was designed with a T-shaped configuration,and the system was optimized to minimize the brake volume.Prototypes of the APHA and robotic walker were constructed.A control algorithm for the robotic walker was developed based on the characteristics of the APHA and the structure of the robotic walker.The mechanical properties of the APHA were characterized,and experiments were conducted to evaluate the mobility assistance supplied by the robotic walker on different roads.The results show that the APHA can meet the requirements of the robotic walker,and suitable assistive forces can be provided by the robotic walker,which has a simple mechanical structure and control method.
基金supported in part by the National Natural Science Foundation of China under Grant 62073224the National Key Research and Development Program of China under Grant 2018YFB1307303the program of China Scholarships Council under Grant 202108310200.
文摘Existing microprocessor-controlled passive prosthetic knees(PaPKs)and active prosthetic knees(AcPKs)cannot truly simulate the muscle activity characteristics of the active–passive hybrid action of the knee during the normal gait.Differences in EMG between normal and different prosthetic gait for different phases were never separately analyzed.In this study,a novel hybrid active–passive prosthetic knee(HAPK)is proposed and if and how muscle activity and kinematics changes in different prosthetic gait are analyzed.The hybrid hydraulic-motor actuator is adopted to fully integrate the advantages of hydraulic compliance damping and motor efficiency,and the hierarchical control strategy is adopted to realize the adaptive predictive control of the HAPK.The kinematic data and EMG data of normal gait and different prosthetic gait were compared by experiments,so as to analyze the changes in the muscle activity and spatio-temporal data per phase compared to normal walking and the adaptations of amputees when walking with a different kind of prosthesis(the mechanical prosthesis(MePK),the PaPK and the HAPK).The results show that changes in prosthetic gait mainly consisted of decreased self-selected walking speed,gait symmetry and maximum knee flexion,increased first double support phase duration,muscle activation in both opposed and prosthetic limb and inter-subject variability.The differences between controls and MePK,PaPK and HAPK decreases sequentially.These results indicate that the hybrid active–passive actuating mode can have positive effects on improving the approximation of healthy gait characteristics.
文摘Reconfigurable Intelligent Surfaces(RIS)have emerged as a promising technology for improving the reliability of massive MIMO communication networks.However,conventional RIS suffer from poor Spectral Efficiency(SE)and high energy consumption,leading to complex Hybrid Precoding(HP)designs.To address these issues,we propose a new low-complexity HP model,named Dynamic Hybrid Relay Reflecting RIS based Hybrid Precoding(DHRR-RIS-HP).Our approach combines active and passive elements to cancel out the downsides of both conventional designs.We first design a DHRR-RIS and optimize the pilot and Channel State Information(CSI)estimation using an adaptive threshold method and Adaptive Back Propagation Neural Network(ABPNN)algorithm,respectively,to reduce the Bit Error Rate(BER)and energy consumption.To optimize the data stream,we cluster them into private and public streams using Enhanced Fuzzy C-Means(EFCM)algorithm,and schedule them based on priority and emergency level.To maximize the sum rate and SE,we perform digital precoder optimization at the Base Station(BS)side using Deep Deterministic Policy Gradient(DDPG)algorithm and analog precoder optimization at the DHRR-RIS using Fire Hawk Optimization(FHO)algorithm.We implement our proposed work using MATLAB R2020a and compare it with existing works using several validation metrics.Our results show that our proposed work outperforms existing works in terms of SE,Weighted Sum Rate(WSR),and BER.
基金supported by the National Natural Science Foundation of China(31500194 and U1202261)
文摘Natural hybridization frequently occurs in plants and can facilitate gene flow between species, possibly resulting in species refusion. However, various reproductive barriers block the formation of hybrids and maintain species integrity. Here, we conducted a field survey to examine natural hybridization and reproductive isolation （RI） between sympatric populations of Primula secundiflora and P. poissonii using ten nuclear simple sequence repeat （SSR） loci. Although introgressive hybridization occurred, species boundaries between P. secundiflora and P. poissonii were maintained through nearly complete reproductive isolation. These interfertite species provide an excellent model for studying the RI mechanisms and evolutionary forces that maintain species boundaries.
基金supported in part by the National Key Research and Development Program of China(No.2020YFB1807201)the National Natural Science Foundation of China(No.62031019).
文摘Benefiting from the growth of the bandwidth,Terahertz(THz)communication can support the new application with explosive requirements of the ultra-high-speed rates for future 6G wireless systems.In order to compensate for the path loss of high frequency,massive Multiple-Input Multiple-Output(MIMO)can be utilized for high array gains by beamforming.However,the existing THz communication with massive MIMO has remarkably high energy consumption because a large number of analog phase shifters should be used to realize the analog beamforming.To solve this problem,a Reconfigurable Intelligent Surface(RIS)based hybrid precoding architecture for THz communication is developed in this paper,where the energy-hungry phased array is replaced by the energy-efficient RIS to realize the analog beamforming of the hybrid precoding.Then,based on the proposed RIS-based architecture,a sum-rate maximization problem for hybrid precoding is investigated.Since the phase shifts implemented by RIS in practice are often discrete,this sum-rate maximization problem with a non-convex constraint is challenging.Next,the sum-rate maximization problem is reformulated as a parallel Deep Neural Network(DNN)based classification problem,which can be solved by the proposed low-complexity Deep Learning based Multiple Discrete Classification(DL-MDC)hybrid precoding scheme.Finally,we provide numerous simulation results to show that the proposed DL-MDC scheme works well both in the theoretical Saleh-Valenzuela channel model and practical 3GPP channel model.Compared with existing iterative search algorithms,the proposed DL-MDC scheme significantly reduces the runtime with a negligible performance loss.
