In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deploym...In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.展开更多
The flow field architecture of the proton exchange membrane fuel cell(PEMFC)cathode critically determines its performance.To enhance PEMFC operation through structural optimization,trapezoidal obstacles were implement...The flow field architecture of the proton exchange membrane fuel cell(PEMFC)cathode critically determines its performance.To enhance PEMFC operation through structural optimization,trapezoidal obstacles were implemented in the cathode flow channels.The height dependence of these obstacles was systematically investigated,revealing that a 0.7 mm obstacle height enhanced mass transfer from channels to the gas diffusion layer(GDL)compared to conventional triple-serpentine designs.This configuration achieved a 12.08%increase in limiting current density alongside improved water management.Subsequent studies on obstacle distribution density identified 75%density as optimal,delivering maximum net power density with 10.6%lower pressure drop than full-density arrangements.展开更多
Every day walking consists of frequent voluntary modifications in the gait pattern to negotiate obstacles.After spinal cord injury,stepping over an obstacle becomes challenging.Stepping over an obstacle requires senso...Every day walking consists of frequent voluntary modifications in the gait pattern to negotiate obstacles.After spinal cord injury,stepping over an obstacle becomes challenging.Stepping over an obstacle requires sensorimotor transformations in several structures of the brain,including the parietal cortex,premotor cortex,and motor cortex.Sensory information and planning are transformed into motor commands,which are sent from the motor cortex to spinal neuronal circuits to alter limb trajectory,coordinate the limbs,and maintain balance.After spinal cord injury,bidirectional communication between the brain and spinal cord is disrupted and animals,including humans,fail to voluntarily modify limb trajectory to step over an obstacle.Therefore,in this review,we discuss the neuromechanical control of stepping over an obstacle,why it fails after spinal cord injury,and how it recovers to a certain extent.展开更多
Autonomous trucks have the potential to enhance both safety and convenience in intelligent transportation.However,their maximum speed and ability to navigate a variety of driving conditions,particularly uneven roads,a...Autonomous trucks have the potential to enhance both safety and convenience in intelligent transportation.However,their maximum speed and ability to navigate a variety of driving conditions,particularly uneven roads,are limited by a high center of gravity,which increases the risk of rollover.Road bulges,sinkholes,and unexpected debris all present additional challenges for autonomous trucks’operational design,which current perception and decisionmaking algorithms often overlook.To mitigate rollover risks and improve adaptability to damaged roads,this paper presents a novel Road Obstacle-Involved Trajectory Planner(ROITP).The planner categorizes road obstacles using a learning-based algorithm.A discrete optimization algorithm selects a multi-objective optimal trajectory while taking into account constraints and objective functions derived from truck dynamics.Validation across various scenarios on a hardware-in-loop platform demonstrates that the proposed planner is effective and feasible for real-time implementation.展开更多
[Objectives]This study was conducted to comprehensively understand the changes in gene expression of plants under environmental stress during different growth and development stages.[Methods]The effects of continuous ...[Objectives]This study was conducted to comprehensively understand the changes in gene expression of plants under environmental stress during different growth and development stages.[Methods]The effects of continuous cropping on the roots and leaves of Polygonatum sibiricum were investigated using transcriptome sequencing.Normally-grown first crop P.sibiricum was used as the control group,while continuous cropping plants served as the treatment group.Transcriptomic differences in roots and leaves under different conditions were compared.[Results]The leaf materials of first crop and continuous cropping P.sibiricum(CCLZ vs FCLZ)showed 21916 differentially expressed genes(DEGs),while the root materials of first crop and continuous cropping P.sibiricum(CCRZ vs FCRZ)exhibited 12726 DEGs(the lowest DEG count)(12726).Among them,1896 DEGs were common.GO enrichment analysis revealed that DEGs were mainly enriched in metabolism,cell wall degradation,and pathogen defense.KEGG enrichment analysis indicated that DEGs in CCLZ vs FCLZ and CCRZ vs FCRZ primarily affected hormone signal transduction and pathogen interaction pathways.[Conclusions]This study preliminarily elucidate the regulatory mechanisms in the roots and leaves of continuous cropping P.sibiricum at the molecular level,providing reference for research on its adaptation to continuous cropping.展开更多
In recent years, the uncontrollable risks of urban production-living-ecological(PLE)space have increased sharply, making resilience enhancement essential for sustainable urban development. Based on the social-ecologic...In recent years, the uncontrollable risks of urban production-living-ecological(PLE)space have increased sharply, making resilience enhancement essential for sustainable urban development. Based on the social-ecological system(SES) theory, this study constructs an assessment framework for urban PLE space resilience by analyzing its inherent characteristics. The central urban area of Ganzhou city is taken as a case study to evaluate urban PLE space resilience and diagnose its obstacles. The results are as follows: The PLE space resilience in the central urban area of Ganzhou exhibits gradations and substantial spatial differentiation. The ecological space resilience in the study area was the highest, followed by that of production space, while living space resilience was the lowest. The primary factors influencing PLE space resilience are concentrated in the dimensions of robustness and adaptability. In particular, the robustness of the PLE space is relatively low. Based on these results, targeted spatial resilience governance strategies for the PLE space have been proposed. These strategies serve as theoretical and technical references for the study area. By adopting the PLE space perspective, this paper enriches resilience research and provide theoretical support for sustainable urban development.展开更多
A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path...A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path-planning process into two layers is proposed by designing the velocityobstacle strategy for satisfying timeliness and effectiveness.The upper-level layer focuses on creating an efficient Dubins initial path considering the dynamic constraints of the fixed wing.Subsequently,the lower-level layer detects potential collisions and adjusts its flight paths to avoid collisions by using the threedimensional velocity obstacle method,which describes the maneuvering space of collision avoidance as the intersection space of half space.To further handle the dynamic and collisionavoidance constraints,a priority mechanism is designed to ensure that the adjusted path is still feasible for fixed-wing UAVs.Simulation experiments demonstrate the effectiveness of the proposed method.展开更多
Despite its immense potential,the application of digital twin technology in real industrial scenarios still faces numerous challenges.This study focuses on industrial assembly lines in sectors such as microelectronics...Despite its immense potential,the application of digital twin technology in real industrial scenarios still faces numerous challenges.This study focuses on industrial assembly lines in sectors such as microelectronics,pharmaceuticals,and food packaging,where precision and speed are paramount,applying digital twin technology to the robotic assembly process.The innovation of this research lies in the development of a digital twin architecture and system for Delta robots that is suitable for real industrial environments.Based on this system,a deep reinforcement learning algorithm for obstacle avoidance path planning in Delta robots has been developed,significantly enhancing learning efficiency through an improved intermediate reward mechanism.Experiments on communication and interaction between the digital twin system and the physical robot validate the effectiveness of this method.The system not only enhances the integration of digital twin technology,deep reinforcement learning and robotics,offering an efficient solution for path planning and target grasping inDelta robots,but also underscores the transformative potential of digital twin technology in intelligent manufacturing,with extensive applicability across diverse industrial domains.展开更多
Rural resilience,a core capability for addressing systemic risks and enabling sustainable development,is increasingly vital to promoting urban-rural integrated development and rural revitalization strategies.However,c...Rural resilience,a core capability for addressing systemic risks and enabling sustainable development,is increasingly vital to promoting urban-rural integrated development and rural revitalization strategies.However,current research lacks exploration of the collaborative mechanisms between rural economic resilience(RER)and rural social resilience(RSR)in ecologically vulnerable areas.Based on the practical context of rural sustainable development in such regions,this study investigates the interaction between RER and RSR from a resilience coordination perspective.In this paper,a rural resilience evaluation framework for collaborative development of economic and social resilience was established.By employing the coupling coordination degree model,obstacle degree model,and equilibrium entropy model,this paper examines the synergies,constraints,and potential of rural resilience subsystems in Jinchang City,Gansu Province,China,in 2020.The results reveal that:1)RER contributes to RSR by stabilizing the economy,enhancing community adaptability,and driving modernization.In turn,RSR strengthens RER by mitigating instability,building social capital,and fostering confidence—together forming a mutually reinforcing coupling mechanism.2)The rural economic and social resilience level in Jinchang City remains generally low with spatially clustered patterns,while the coupling coordination degree is at an intermediate level overall,with 62.59%of villages exhibiting unbalanced development between rural economic and social resilience.3)RER and RSR demonstrate synergistic degradation in ecologically vulnerable areas,where low-level rural economic and social resilience induce integrated systemic deterioration.4)Considering the unbalanced development of rural economic and social resilience in ecologically fragile areas,differentiated coordination pathways are proposed for three village typologies:RER-lagging villages,RSR-lagging villages,and villages where RER and RSR develop synchronously but lack effective coordination.These findings offer spatial governance strategies and practical guidance for enhancing rural resilience and advancing sustainable development in ecologically vulnerable regions.展开更多
Introduction: Vaccination faces several obstacles in the fight against COVID-19, yet it has been identified as one of the most effective means of preventing new epidemics of COVID-19. The aim was to contribute to impr...Introduction: Vaccination faces several obstacles in the fight against COVID-19, yet it has been identified as one of the most effective means of preventing new epidemics of COVID-19. The aim was to contribute to improving vaccination coverage against COVID-19 in the Kindu health zone. Method: We conducted a cross-sectional descriptive study with an analytical focus, using a questionnaire that enabled us to carry out a survey from October 03 to 30, 2022. Our target study population was residents of the Kindu health zone. A total of 420 subjects participated in our study, including 42 per site. Results: The study revealed a low proportion of vaccinated subjects (38.3%) and a high proportion of non-vaccinated subjects (61.70%). Non-belief in the efficacy of vaccines (p = 0.001), infodemia (p = 0.001) and respect for ethnic norms (p = 0.001) were identified as perceived barriers to vaccination. Fear of being branded with the “666” beast badge (p = 0.004) as the perceived severity. Respondents’ perceptions of mass vaccination against COVID-19 are mixed, and their opinions and expectations of COVID-19 vaccination in the town of Kindu are divided. Conclusion: In order to increase the proportion of people vaccinated against COVID-19, it is suggested here to increase the population’s ability to detect false information through a well-structured communication and health education program.展开更多
This work proposes an online collaborative hunting strategy for multi-robot systems based on obstacle-avoiding Voronoi cells in a complex dynamic environment. This involves firstly designing the construction method us...This work proposes an online collaborative hunting strategy for multi-robot systems based on obstacle-avoiding Voronoi cells in a complex dynamic environment. This involves firstly designing the construction method using a support vector machine(SVM) based on the definition of buffered Voronoi cells(BVCs). Based on the safe collision-free region of the robots, the boundary weights between the robots and the obstacles are dynamically updated such that the robots are tangent to the buffered Voronoi safety areas without intersecting with the obstacles. Then, the robots are controlled to move within their own buffered Voronoi safety area to achieve collision-avoidance with other robots and obstacles. The next step involves proposing a hunting method that optimizes collaboration between the pursuers and evaders. Some hunting points are generated and distributed evenly around a circle. Next, the pursuers are assigned to match the optimal points based on the Hungarian algorithm.Then, a hunting controller is designed to improve the containment capability and minimize containment time based on collision risk. Finally, simulation results have demonstrated that the proposed cooperative hunting method is more competitive in terms of time and travel distance.展开更多
The importance of unmanned aerial vehicle(UAV)obstacle avoidance algorithms lies in their ability to ensure flight safety and collision avoidance,thereby protecting people and property.We propose UAD-YOLOv8,a lightwei...The importance of unmanned aerial vehicle(UAV)obstacle avoidance algorithms lies in their ability to ensure flight safety and collision avoidance,thereby protecting people and property.We propose UAD-YOLOv8,a lightweight YOLOv8-based obstacle detection algorithm optimized for UAV obstacle avoidance.The algorithm enhances the detection capability for small and irregular obstacles by removing the P5 feature layer and introducing deformable convolution v2(DCNv2)to optimize the cross stage partial bottleneck with 2 convolutions and fusion(C2f)module.Additionally,it reduces the model’s parameter count and computational load by constructing the unite ghost and depth-wise separable convolution(UGDConv)series of lightweight convolutions and a lightweight detection head.Based on this,we designed a visual obstacle avoidance algorithm that can improve the obstacle avoidance performance of UAVs in different environments.In particular,we propose an adaptive distance detection algorithm based on obstacle attributes to solve the ranging problem for multiple types and irregular obstacles to further enhance the UAV’s obstacle avoidance capability.To verify the effectiveness of the algorithm,the UAV obstacle detection(UAD)dataset was created.The experimental results show that UAD-YOLOv8 improves mAP50 by 3.4%and reduces GFLOPs by 34.5%compared to YOLOv8n while reducing the number of parameters by 77.4%and the model size by 73%.These improvements significantly enhance the UAV’s obstacle avoidance performance in complex environments,demonstrating its wide range of applications.展开更多
The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajecto...The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits.In addition,owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios,it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters.Therefore,an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed.First,numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset.Subsequently,a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory.Furthermore,a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function,and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed.Finally,the proposed strategy is verified based on real driving scenarios.The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the“emergency degree”of obstacle avoidance and the state of the vehicle.Moreover,this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories,effectively improving the adaptability and acceptability of trajectories in driving scenarios.展开更多
This paper investigates the path-following control problem with obstacle avoidance of autonomous surface vehicles in the presence of actuator faults,uncertainty and external disturbances.Autonomous surface vehicles in...This paper investigates the path-following control problem with obstacle avoidance of autonomous surface vehicles in the presence of actuator faults,uncertainty and external disturbances.Autonomous surface vehicles inevitably suffer from actuator faults in complex sea environments,which may cause existing obstacle avoidance strategies to fail.To reduce the influence of actuator faults,an improved artificial potential function is constructed by introducing the lower bound of actuator efficiency factors.The nonlinear state observer,which only depends on measurable position information of the autonomous surface vehicle,is used to address uncertainties and external disturbances.By using a backstepping technique and adaptive mechanism,a path-following control strategy with obstacle avoidance and fault tolerance is designed which can ensure that the tracking errors converge to a small neighborhood of zero.Compared with existing results,the proposed control strategy has the capability of obstacle avoidance and fault tolerance simultaneously.Finally,the comparison results through simulations are given to verify the effectiveness of the proposed method.展开更多
In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone ...In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account.展开更多
Continuous cropping can bring economic benefits in a short time and meet the growing demand of agricultural products such as grain,but long-term continuous cropping will accelerate soil degradation,lead to the reducti...Continuous cropping can bring economic benefits in a short time and meet the growing demand of agricultural products such as grain,but long-term continuous cropping will accelerate soil degradation,lead to the reduction of crop yield and the increase of disease rate,and destroy the balance of soil microbial structure.Therefore,it is not conducive to the sustainable development of soil ecosystem.In this paper,the problems caused by continuous cropping,such as imbalance of soil microbial flora,decrease of biodiversity,accumulation of root exudates and their effects on soil fertility and crop growth,were summarized,and some measures were suggested to alleviate the obstacles of continuous cropping,such as reasonable rotation,adjustment of intercropping planting mode and application of biological fertilizers.Moreover,the paper also looked forward to the development trend of continuous cropping obstacle reduction techniques,including the integration and application of biological techniques,the promotion of green ecological techniques and the application of intelligent management system.This study provides theoretical basis and technical support for the research of continuous cropping obstacle reduction techniques and promote the healthy and sustainable development of modern agriculture.展开更多
A differential game guidance scheme with obstacle avoidance,based on the formulation of a combined linear quadratic and norm-bounded differential game,is designed for a three-player engagement scenario,which includes ...A differential game guidance scheme with obstacle avoidance,based on the formulation of a combined linear quadratic and norm-bounded differential game,is designed for a three-player engagement scenario,which includes a pursuer,an interceptor,and an evader.The confrontation between the players is divided into four phases(P1-P4)by introducing the switching time,and proposing different guidance strategies according to the phase where the static obstacle is located:the linear quadratic game method is employed to devise the guidance scheme for the energy optimization when the obstacle is located in the P1 and P3 stages;the norm-bounded differential game guidance strategy is presented to satisfy the acceleration constraint under the circumstance that the obstacle is located in the P2 and P4 phases.Furthermore,the radii of the static obstacle and the interceptor are taken as the design parameters to derive the combined guidance strategy through the dead-zone function,which guarantees that the pursuer avoids the static obstacle,and the interceptor,and attacks the evader.Finally,the nonlinear numerical simulations verify the performance of the game guidance strategy.展开更多
Obstacle detection and platoon control for mixed traffic flows,comprising human-driven vehicles(HDVs)and connected and autonomous vehicles(CAVs),face challenges from uncertain disturbances,such as sensor faults,inaccu...Obstacle detection and platoon control for mixed traffic flows,comprising human-driven vehicles(HDVs)and connected and autonomous vehicles(CAVs),face challenges from uncertain disturbances,such as sensor faults,inaccurate driver operations,and mismatched model errors.Furthermore,misleading sensing information or malicious attacks in vehicular wireless networks can jeopardize CAVs’perception and platoon safety.In this paper,we develop a two-dimensional robust control method for a mixed platoon,including a single leading CAV and multiple following HDVs that incorpo-rate robust information sensing and platoon control.To effectively detect and locate unknown obstacles ahead of the leading CAV,we propose a cooperative vehicle-infrastructure sensing scheme and integrate it with an adaptive model predictive control scheme for the leading CAV.This sensing scheme fuses information from multiple nodes while suppressing malicious data from attackers to enhance robustness and attack resilience in a distributed and adaptive manner.Additionally,we propose a distributed car-following control scheme with robustness to guarantee the following HDVs,considering uncertain disturbances.We also provide theoretical proof of the string stability under this control framework.Finally,extensive simulations are conducted to validate our approach.The simulation results demonstrate that our method can effectively filter out misleading sensing information from malicious attackers,significantly reduce the mean-square deviation in obstacle sensing,and approach the theoretical error lower bound.Moreover,the proposed control method successfully achieves obstacle avoidance for the mixed platoon while ensuring stability and robustness in the face of external attacks and uncertain disturbances.展开更多
Computer simulations are utilized to investigate the dynamic behavior of self-propelled particles(SPPs)within a complex obstacle environment.The findings reveal that SPPs exhibit three distinct aggregation states with...Computer simulations are utilized to investigate the dynamic behavior of self-propelled particles(SPPs)within a complex obstacle environment.The findings reveal that SPPs exhibit three distinct aggregation states within the obstacle,each contingent on specific conditions.A phase diagram outlining the aggregation states concerning self-propulsion conditions is presented.The results illustrate a transition of SPPs from a dispersion state to a transition state as persistence time increases within the obstacle.Conversely,as the driving strength increases,self-propelled particles shift towards a cluster state.A systematic exploration of the interplay between driving strength,persistence time,and matching degree on the dynamic behavior of self-propelled particles is conducted.Furthermore,an analysis is performed on the spatial distribution of SPPs along the y-axis,capture rate,maximum capture probability,and mean-square displacement.The insights gained from this research make valuable contributions to understanding the capture and collection of active particles.展开更多
At present,long-term continuous cropping in agricultural production has formed a relatively common development trend.With the increase of continuous cropping years,soil phenolic acids are also affected to varying degr...At present,long-term continuous cropping in agricultural production has formed a relatively common development trend.With the increase of continuous cropping years,soil phenolic acids are also affected to varying degrees.This paper summarized the effects of continuous cropping on soil phenolic acids and the research progress of continuous cropping obstacle reduction techniques,aiming at providing theoretical basis and technical support for the research of continuous cropping obstacle reduction techniques and promoting the healthy and sustainable development of modern agriculture.展开更多
文摘In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.
文摘The flow field architecture of the proton exchange membrane fuel cell(PEMFC)cathode critically determines its performance.To enhance PEMFC operation through structural optimization,trapezoidal obstacles were implemented in the cathode flow channels.The height dependence of these obstacles was systematically investigated,revealing that a 0.7 mm obstacle height enhanced mass transfer from channels to the gas diffusion layer(GDL)compared to conventional triple-serpentine designs.This configuration achieved a 12.08%increase in limiting current density alongside improved water management.Subsequent studies on obstacle distribution density identified 75%density as optimal,delivering maximum net power density with 10.6%lower pressure drop than full-density arrangements.
文摘Every day walking consists of frequent voluntary modifications in the gait pattern to negotiate obstacles.After spinal cord injury,stepping over an obstacle becomes challenging.Stepping over an obstacle requires sensorimotor transformations in several structures of the brain,including the parietal cortex,premotor cortex,and motor cortex.Sensory information and planning are transformed into motor commands,which are sent from the motor cortex to spinal neuronal circuits to alter limb trajectory,coordinate the limbs,and maintain balance.After spinal cord injury,bidirectional communication between the brain and spinal cord is disrupted and animals,including humans,fail to voluntarily modify limb trajectory to step over an obstacle.Therefore,in this review,we discuss the neuromechanical control of stepping over an obstacle,why it fails after spinal cord injury,and how it recovers to a certain extent.
基金Supported by National Natural Science Foundation of China (Grant Nos. 52072215, 52221005, 52272386)Beijing Municipal Natrual Science Foundation (Grant No. L243025)+2 种基金National Key R&D Program of China (Grant No. 2022YFB2503003)State Key Laboratory of Intelligent Green Vehicle and Mobilityfundamental Research Funds for the Central Universities
文摘Autonomous trucks have the potential to enhance both safety and convenience in intelligent transportation.However,their maximum speed and ability to navigate a variety of driving conditions,particularly uneven roads,are limited by a high center of gravity,which increases the risk of rollover.Road bulges,sinkholes,and unexpected debris all present additional challenges for autonomous trucks’operational design,which current perception and decisionmaking algorithms often overlook.To mitigate rollover risks and improve adaptability to damaged roads,this paper presents a novel Road Obstacle-Involved Trajectory Planner(ROITP).The planner categorizes road obstacles using a learning-based algorithm.A discrete optimization algorithm selects a multi-objective optimal trajectory while taking into account constraints and objective functions derived from truck dynamics.Validation across various scenarios on a hardware-in-loop platform demonstrates that the proposed planner is effective and feasible for real-time implementation.
基金Supported by Agricultural Science and Technology Innovation Fund of Hunan Province(XCNZ[2021]No.15)Loudi Science and Technology Innovation Program(LKF[2022]29)+1 种基金Applied Characteristic Discipline Construction Project of Hunan Province:Plant ProtectionPostgraduate Research and Innovation Project of Hunan University of Humanities,Science and Technology(ZSCX2022Y12).
文摘[Objectives]This study was conducted to comprehensively understand the changes in gene expression of plants under environmental stress during different growth and development stages.[Methods]The effects of continuous cropping on the roots and leaves of Polygonatum sibiricum were investigated using transcriptome sequencing.Normally-grown first crop P.sibiricum was used as the control group,while continuous cropping plants served as the treatment group.Transcriptomic differences in roots and leaves under different conditions were compared.[Results]The leaf materials of first crop and continuous cropping P.sibiricum(CCLZ vs FCLZ)showed 21916 differentially expressed genes(DEGs),while the root materials of first crop and continuous cropping P.sibiricum(CCRZ vs FCRZ)exhibited 12726 DEGs(the lowest DEG count)(12726).Among them,1896 DEGs were common.GO enrichment analysis revealed that DEGs were mainly enriched in metabolism,cell wall degradation,and pathogen defense.KEGG enrichment analysis indicated that DEGs in CCLZ vs FCLZ and CCRZ vs FCRZ primarily affected hormone signal transduction and pathogen interaction pathways.[Conclusions]This study preliminarily elucidate the regulatory mechanisms in the roots and leaves of continuous cropping P.sibiricum at the molecular level,providing reference for research on its adaptation to continuous cropping.
基金Social Science Foundation Project of Jiangxi Province,No.24GL61D。
文摘In recent years, the uncontrollable risks of urban production-living-ecological(PLE)space have increased sharply, making resilience enhancement essential for sustainable urban development. Based on the social-ecological system(SES) theory, this study constructs an assessment framework for urban PLE space resilience by analyzing its inherent characteristics. The central urban area of Ganzhou city is taken as a case study to evaluate urban PLE space resilience and diagnose its obstacles. The results are as follows: The PLE space resilience in the central urban area of Ganzhou exhibits gradations and substantial spatial differentiation. The ecological space resilience in the study area was the highest, followed by that of production space, while living space resilience was the lowest. The primary factors influencing PLE space resilience are concentrated in the dimensions of robustness and adaptability. In particular, the robustness of the PLE space is relatively low. Based on these results, targeted spatial resilience governance strategies for the PLE space have been proposed. These strategies serve as theoretical and technical references for the study area. By adopting the PLE space perspective, this paper enriches resilience research and provide theoretical support for sustainable urban development.
基金supported by the National Science Fund for Distinguished Young Scholars(52425211)BIT Research Fund Program for Young Scholars(XSQD-202201005).
文摘A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path-planning process into two layers is proposed by designing the velocityobstacle strategy for satisfying timeliness and effectiveness.The upper-level layer focuses on creating an efficient Dubins initial path considering the dynamic constraints of the fixed wing.Subsequently,the lower-level layer detects potential collisions and adjusts its flight paths to avoid collisions by using the threedimensional velocity obstacle method,which describes the maneuvering space of collision avoidance as the intersection space of half space.To further handle the dynamic and collisionavoidance constraints,a priority mechanism is designed to ensure that the adjusted path is still feasible for fixed-wing UAVs.Simulation experiments demonstrate the effectiveness of the proposed method.
基金supported in part by the National Natural Science Foundation of China under Grants 62303098 and 62173073in part by China Postdoctoral Science Foundation under Grant 2022M720679+1 种基金in part by the Central University Basic Research Fund of China under Grant N2304021in part by the Liaoning Provincial Science and Technology Plan Project-Technology Innovation Guidance of the Science and Technology Department under Grant 2023JH1/10400011.
文摘Despite its immense potential,the application of digital twin technology in real industrial scenarios still faces numerous challenges.This study focuses on industrial assembly lines in sectors such as microelectronics,pharmaceuticals,and food packaging,where precision and speed are paramount,applying digital twin technology to the robotic assembly process.The innovation of this research lies in the development of a digital twin architecture and system for Delta robots that is suitable for real industrial environments.Based on this system,a deep reinforcement learning algorithm for obstacle avoidance path planning in Delta robots has been developed,significantly enhancing learning efficiency through an improved intermediate reward mechanism.Experiments on communication and interaction between the digital twin system and the physical robot validate the effectiveness of this method.The system not only enhances the integration of digital twin technology,deep reinforcement learning and robotics,offering an efficient solution for path planning and target grasping inDelta robots,but also underscores the transformative potential of digital twin technology in intelligent manufacturing,with extensive applicability across diverse industrial domains.
基金Under the auspices of National Natural Science Foundation of China(No.42271222)Natural Science Foundation of Gansu Province(No.22JR5RA130)。
文摘Rural resilience,a core capability for addressing systemic risks and enabling sustainable development,is increasingly vital to promoting urban-rural integrated development and rural revitalization strategies.However,current research lacks exploration of the collaborative mechanisms between rural economic resilience(RER)and rural social resilience(RSR)in ecologically vulnerable areas.Based on the practical context of rural sustainable development in such regions,this study investigates the interaction between RER and RSR from a resilience coordination perspective.In this paper,a rural resilience evaluation framework for collaborative development of economic and social resilience was established.By employing the coupling coordination degree model,obstacle degree model,and equilibrium entropy model,this paper examines the synergies,constraints,and potential of rural resilience subsystems in Jinchang City,Gansu Province,China,in 2020.The results reveal that:1)RER contributes to RSR by stabilizing the economy,enhancing community adaptability,and driving modernization.In turn,RSR strengthens RER by mitigating instability,building social capital,and fostering confidence—together forming a mutually reinforcing coupling mechanism.2)The rural economic and social resilience level in Jinchang City remains generally low with spatially clustered patterns,while the coupling coordination degree is at an intermediate level overall,with 62.59%of villages exhibiting unbalanced development between rural economic and social resilience.3)RER and RSR demonstrate synergistic degradation in ecologically vulnerable areas,where low-level rural economic and social resilience induce integrated systemic deterioration.4)Considering the unbalanced development of rural economic and social resilience in ecologically fragile areas,differentiated coordination pathways are proposed for three village typologies:RER-lagging villages,RSR-lagging villages,and villages where RER and RSR develop synchronously but lack effective coordination.These findings offer spatial governance strategies and practical guidance for enhancing rural resilience and advancing sustainable development in ecologically vulnerable regions.
文摘Introduction: Vaccination faces several obstacles in the fight against COVID-19, yet it has been identified as one of the most effective means of preventing new epidemics of COVID-19. The aim was to contribute to improving vaccination coverage against COVID-19 in the Kindu health zone. Method: We conducted a cross-sectional descriptive study with an analytical focus, using a questionnaire that enabled us to carry out a survey from October 03 to 30, 2022. Our target study population was residents of the Kindu health zone. A total of 420 subjects participated in our study, including 42 per site. Results: The study revealed a low proportion of vaccinated subjects (38.3%) and a high proportion of non-vaccinated subjects (61.70%). Non-belief in the efficacy of vaccines (p = 0.001), infodemia (p = 0.001) and respect for ethnic norms (p = 0.001) were identified as perceived barriers to vaccination. Fear of being branded with the “666” beast badge (p = 0.004) as the perceived severity. Respondents’ perceptions of mass vaccination against COVID-19 are mixed, and their opinions and expectations of COVID-19 vaccination in the town of Kindu are divided. Conclusion: In order to increase the proportion of people vaccinated against COVID-19, it is suggested here to increase the population’s ability to detect false information through a well-structured communication and health education program.
基金supported by the National Natural Science Foundation of China (62273007,61973023)Project of Cultivation for Young Top-motch Talents of Beijing Municipal Institutions (BPHR202203032)。
文摘This work proposes an online collaborative hunting strategy for multi-robot systems based on obstacle-avoiding Voronoi cells in a complex dynamic environment. This involves firstly designing the construction method using a support vector machine(SVM) based on the definition of buffered Voronoi cells(BVCs). Based on the safe collision-free region of the robots, the boundary weights between the robots and the obstacles are dynamically updated such that the robots are tangent to the buffered Voronoi safety areas without intersecting with the obstacles. Then, the robots are controlled to move within their own buffered Voronoi safety area to achieve collision-avoidance with other robots and obstacles. The next step involves proposing a hunting method that optimizes collaboration between the pursuers and evaders. Some hunting points are generated and distributed evenly around a circle. Next, the pursuers are assigned to match the optimal points based on the Hungarian algorithm.Then, a hunting controller is designed to improve the containment capability and minimize containment time based on collision risk. Finally, simulation results have demonstrated that the proposed cooperative hunting method is more competitive in terms of time and travel distance.
基金supported by Xinjiang Uygur Autonomous Region Metrology and Testing Institute Project(Grant No.XJRIMT2022-5)Tianshan Talent Training Project-Xinjiang Science and Technology Innovation Team Program(2023TSYCTD0012).
文摘The importance of unmanned aerial vehicle(UAV)obstacle avoidance algorithms lies in their ability to ensure flight safety and collision avoidance,thereby protecting people and property.We propose UAD-YOLOv8,a lightweight YOLOv8-based obstacle detection algorithm optimized for UAV obstacle avoidance.The algorithm enhances the detection capability for small and irregular obstacles by removing the P5 feature layer and introducing deformable convolution v2(DCNv2)to optimize the cross stage partial bottleneck with 2 convolutions and fusion(C2f)module.Additionally,it reduces the model’s parameter count and computational load by constructing the unite ghost and depth-wise separable convolution(UGDConv)series of lightweight convolutions and a lightweight detection head.Based on this,we designed a visual obstacle avoidance algorithm that can improve the obstacle avoidance performance of UAVs in different environments.In particular,we propose an adaptive distance detection algorithm based on obstacle attributes to solve the ranging problem for multiple types and irregular obstacles to further enhance the UAV’s obstacle avoidance capability.To verify the effectiveness of the algorithm,the UAV obstacle detection(UAD)dataset was created.The experimental results show that UAD-YOLOv8 improves mAP50 by 3.4%and reduces GFLOPs by 34.5%compared to YOLOv8n while reducing the number of parameters by 77.4%and the model size by 73%.These improvements significantly enhance the UAV’s obstacle avoidance performance in complex environments,demonstrating its wide range of applications.
基金supported by the National Natural Science Foundation of China(51875302)。
文摘The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits.In addition,owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios,it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters.Therefore,an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed.First,numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset.Subsequently,a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory.Furthermore,a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function,and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed.Finally,the proposed strategy is verified based on real driving scenarios.The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the“emergency degree”of obstacle avoidance and the state of the vehicle.Moreover,this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories,effectively improving the adaptability and acceptability of trajectories in driving scenarios.
基金the National Natural Science Foundation of China(51939001,52171292,51979020,61976033)Dalian Outstanding Young Talents Program(2022RJ05)+1 种基金the Topnotch Young Talents Program of China(36261402)the Liaoning Revitalization Talents Program(XLYC20-07188)。
文摘This paper investigates the path-following control problem with obstacle avoidance of autonomous surface vehicles in the presence of actuator faults,uncertainty and external disturbances.Autonomous surface vehicles inevitably suffer from actuator faults in complex sea environments,which may cause existing obstacle avoidance strategies to fail.To reduce the influence of actuator faults,an improved artificial potential function is constructed by introducing the lower bound of actuator efficiency factors.The nonlinear state observer,which only depends on measurable position information of the autonomous surface vehicle,is used to address uncertainties and external disturbances.By using a backstepping technique and adaptive mechanism,a path-following control strategy with obstacle avoidance and fault tolerance is designed which can ensure that the tracking errors converge to a small neighborhood of zero.Compared with existing results,the proposed control strategy has the capability of obstacle avoidance and fault tolerance simultaneously.Finally,the comparison results through simulations are given to verify the effectiveness of the proposed method.
基金This work was supported by the Postdoctoral Fund of FDCT,Macao(Grant No.0003/2021/APD).Any opinions,findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the sponsor.
文摘In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account.
基金Supported by Key Project of Yunnan Provincial Science and Technology Plan(202202AE090015)Scientific Research Fund of Yunnan Education Department(2024Y742+3 种基金2023Y0863)National Natural Science Foundation of China(42067009)2023 Undergraduate Innovation and Entrepreneurship Training Program of Yunnan Education Department(S202311393044S202311393061).
文摘Continuous cropping can bring economic benefits in a short time and meet the growing demand of agricultural products such as grain,but long-term continuous cropping will accelerate soil degradation,lead to the reduction of crop yield and the increase of disease rate,and destroy the balance of soil microbial structure.Therefore,it is not conducive to the sustainable development of soil ecosystem.In this paper,the problems caused by continuous cropping,such as imbalance of soil microbial flora,decrease of biodiversity,accumulation of root exudates and their effects on soil fertility and crop growth,were summarized,and some measures were suggested to alleviate the obstacles of continuous cropping,such as reasonable rotation,adjustment of intercropping planting mode and application of biological fertilizers.Moreover,the paper also looked forward to the development trend of continuous cropping obstacle reduction techniques,including the integration and application of biological techniques,the promotion of green ecological techniques and the application of intelligent management system.This study provides theoretical basis and technical support for the research of continuous cropping obstacle reduction techniques and promote the healthy and sustainable development of modern agriculture.
基金supported by National Natural Science Foundation(NNSF)of China under(Grant No.62273119)。
文摘A differential game guidance scheme with obstacle avoidance,based on the formulation of a combined linear quadratic and norm-bounded differential game,is designed for a three-player engagement scenario,which includes a pursuer,an interceptor,and an evader.The confrontation between the players is divided into four phases(P1-P4)by introducing the switching time,and proposing different guidance strategies according to the phase where the static obstacle is located:the linear quadratic game method is employed to devise the guidance scheme for the energy optimization when the obstacle is located in the P1 and P3 stages;the norm-bounded differential game guidance strategy is presented to satisfy the acceleration constraint under the circumstance that the obstacle is located in the P2 and P4 phases.Furthermore,the radii of the static obstacle and the interceptor are taken as the design parameters to derive the combined guidance strategy through the dead-zone function,which guarantees that the pursuer avoids the static obstacle,and the interceptor,and attacks the evader.Finally,the nonlinear numerical simulations verify the performance of the game guidance strategy.
基金supported by the National Key Research and the Development Program of China(2022YFC3803700)the National Natural Science Foundation of China(52202391 and U20A20155).
文摘Obstacle detection and platoon control for mixed traffic flows,comprising human-driven vehicles(HDVs)and connected and autonomous vehicles(CAVs),face challenges from uncertain disturbances,such as sensor faults,inaccurate driver operations,and mismatched model errors.Furthermore,misleading sensing information or malicious attacks in vehicular wireless networks can jeopardize CAVs’perception and platoon safety.In this paper,we develop a two-dimensional robust control method for a mixed platoon,including a single leading CAV and multiple following HDVs that incorpo-rate robust information sensing and platoon control.To effectively detect and locate unknown obstacles ahead of the leading CAV,we propose a cooperative vehicle-infrastructure sensing scheme and integrate it with an adaptive model predictive control scheme for the leading CAV.This sensing scheme fuses information from multiple nodes while suppressing malicious data from attackers to enhance robustness and attack resilience in a distributed and adaptive manner.Additionally,we propose a distributed car-following control scheme with robustness to guarantee the following HDVs,considering uncertain disturbances.We also provide theoretical proof of the string stability under this control framework.Finally,extensive simulations are conducted to validate our approach.The simulation results demonstrate that our method can effectively filter out misleading sensing information from malicious attackers,significantly reduce the mean-square deviation in obstacle sensing,and approach the theoretical error lower bound.Moreover,the proposed control method successfully achieves obstacle avoidance for the mixed platoon while ensuring stability and robustness in the face of external attacks and uncertain disturbances.
基金Project supported by the Natural Science Foundation of Shanxi Province,China(Grant Nos.202303021212148 and 202103021223245)。
文摘Computer simulations are utilized to investigate the dynamic behavior of self-propelled particles(SPPs)within a complex obstacle environment.The findings reveal that SPPs exhibit three distinct aggregation states within the obstacle,each contingent on specific conditions.A phase diagram outlining the aggregation states concerning self-propulsion conditions is presented.The results illustrate a transition of SPPs from a dispersion state to a transition state as persistence time increases within the obstacle.Conversely,as the driving strength increases,self-propelled particles shift towards a cluster state.A systematic exploration of the interplay between driving strength,persistence time,and matching degree on the dynamic behavior of self-propelled particles is conducted.Furthermore,an analysis is performed on the spatial distribution of SPPs along the y-axis,capture rate,maximum capture probability,and mean-square displacement.The insights gained from this research make valuable contributions to understanding the capture and collection of active particles.
基金Supported by Scientific Research Fund of Yunnan Education Department(2024Y742,2023Y0863)National Natural Science Foundation of China(42067009)+1 种基金College Students'Innovative Training Plan Program of Yunnan Education Department in 2023(S202311393044,S202311393061)Key Project of Science and Technology Program of Yunnan Province(202202AE090015).
文摘At present,long-term continuous cropping in agricultural production has formed a relatively common development trend.With the increase of continuous cropping years,soil phenolic acids are also affected to varying degrees.This paper summarized the effects of continuous cropping on soil phenolic acids and the research progress of continuous cropping obstacle reduction techniques,aiming at providing theoretical basis and technical support for the research of continuous cropping obstacle reduction techniques and promoting the healthy and sustainable development of modern agriculture.
