Rapidly-exploring Random Tree(RRT)and its variants have become foundational in path-planning research,yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees l...Rapidly-exploring Random Tree(RRT)and its variants have become foundational in path-planning research,yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees lead to slow convergence and force an unfavorable trade-off between path quality and traversal safety.To address these challenges,we introduce HS-APF-RRT*,a novel algorithm that fuses layered sampling,an enhanced Artificial Potential Field(APF),and a dynamic neighborhood-expansion mechanism.First,the workspace is hierarchically partitioned into macro,meso,and micro sampling layers,progressively biasing random samples toward safer,lower-energy regions.Second,we augment the traditional APF by incorporating a slope-dependent repulsive term,enabling stronger avoidance of steep obstacles.Third,a dynamic expansion strategy adaptively switches between 8 and 16 connected neighborhoods based on local obstacle density,striking an effective balance between search efficiency and collision-avoidance precision.In simulated off-road scenarios,HS-APF-RRT*is benchmarked against RRT*,GoalBiased RRT*,and APF-RRT*,and demonstrates significantly faster convergence,lower path-energy consumption,and enhanced safety margins.展开更多
OBJECTIVE:Sub-optimal health status(SHS),in which a person's mind and body exists in a low-quality state of being between disease and health,has become a public health problem that cannot be ignored in China.SHS m...OBJECTIVE:Sub-optimal health status(SHS),in which a person's mind and body exists in a low-quality state of being between disease and health,has become a public health problem that cannot be ignored in China.SHS measurement presents a challenge to the academic fields.We developed and evaluated a questionnaire from the perspective of traditional Chinese medicine(TCM) that embodies the features of TCM syndrome diagnosis for measuring SHS in China.METHODS:The construction of the theoretical framework of the questionnaire was based on a literature review,an expert questionnaire survey and group interviews.The subscales and questionnaire items were screened through a pilot study using statistical means and qualitative analysis.Reliability tests that were used included test-retest reliability,Cronbach's α coefficient,split-half reliability;validity tests included content validity,criterion validity,discrimination validity and construct validity.RESULTS:The final questionnaire,the SHSQ-50,included 50 five-class quantifiable items that encompassed nine subscales:liver stagnation syndrome,liver-Qi deficiency syndrome,spleen-Qi deficiency syndrome,liver-fire syndrome,heart-fire syndrome,stomach-fire syndrome,heart-Qi deficiency syndrome,lung-Qi deficiency syndrome and dampness syndrome.Questionnaires were completed by 268 of the 288 SHS subjects(93.0%) and by 86 of the 94 healthy subjects(91.5%).The Cronbach α coefficients,split-half coefficients and stability coefficients ranged from 0.70 to 0.95,0.67 to 0.87 and 0.88 to 0.98,respectively,for the overall scores and subscales.The Wilcoxon rank test showed statistically significant differences in the subscales and overall scores between the SHS group and the healthy group(P<0.01).Twelve factors with an eigenvalue greater than one were extracted by factor analysis and merged into nine factors,for which the cumulative contribution rate was 63.63%.The nine factors were corresponded to the overall structure of the questionnaire.CONCLUSION:The SHSQ-50 is a reliable and valid instrument for measuring TCM syndrome diagnosis of SHS in China.展开更多
OBJECTIVE:To investigate biological indicators of sub-optimal health status and provide means of objective assessment of sub-optimal health status.METHODS:We set the unified standards for diagnosing a SHS.We tested va...OBJECTIVE:To investigate biological indicators of sub-optimal health status and provide means of objective assessment of sub-optimal health status.METHODS:We set the unified standards for diagnosing a SHS.We tested various laboratory indicators in 407 cases that we selected randomly from2807 subjects and collected 15 mL of fasting venous blood from each case.We measured serum immunoglobulin A(IgA)and immunoglobulin G(IgG)concentrations,serum beta endorphins(β-EP),cortisol(C),testosterone(T),plasma adrenocorticotropic hormone(ACTH)and serum T lymphocyte subsets CD3+and CD4+.RESULTS:Mean serum testosterone concentrations and their ratio to cortisol(C)concentrations weresignificantly higher in the healthy group than in those with sub-optimal health status(P<0.01).Mean serum CD3+concentrations were significantly higher in those with sub-optimal health status than in the healthy group(P<0.05).CONCLUSION:Decreased serum testosterone/cortisol ratio may be an objective indication of sub-optimal health status.Changes in neuroendocrine and immunological indicators may explain some of the symptoms,including malaise and poor work performance,attributable to persistent or relapsing fatigue in subjects with sub-optimal health status.展开更多
Joint sub-optimization of cooperative relays in Multiple-Input and Multiple-Output (MIMO) multiple relays aided communication system is discussed in this paper. Because the instantaneous channel state information of a...Joint sub-optimization of cooperative relays in Multiple-Input and Multiple-Output (MIMO) multiple relays aided communication system is discussed in this paper. Because the instantaneous channel state information of all source-relay channels and all relay-user channels is difficult to get at each relay node, an unjoined solution is designed according to the channel state information of that relay only. Then a multi-user loading algorithm is proposed to utilize the space diversity through multi-relay transmission. The simulation results show that with the newly proposed multi-user loading algorithm, the unjoined solution can achieve better system performance comparing with joint one in low SNR. However, the complexity of the former is much lower, for only partial CSI is needed.展开更多
Trochoidal milling is known for its advantages in machining difficult-to-machine materials as it facilitates chip removal and tool cooling.However,the conventional trochoidal tool path presents challenges such as lowe...Trochoidal milling is known for its advantages in machining difficult-to-machine materials as it facilitates chip removal and tool cooling.However,the conventional trochoidal tool path presents challenges such as lower machining efficiency and longer machining time due to its time-varying cutter-workpiece engagement angle and a high percentage of non-cutting tool paths.To address these issues,this paper introduces a parameter-variant trochoidal-like(PVTR)tool path planning method for chatter-free and high-efficiency milling.This method ensures a constant engagement angle for each tool path period by adjusting the trochoidal radius and step.Initially,the nonlinear equation for the PVTR toolpath is established.Then,a segmented recurrence method is proposed to plan tool paths based on the desired engagement angle.The impact of trochoidal tool path parameters on the engagement angle is analyzed and coupled this information with the milling stability model based on spindle speed and engagement angle to determine the desired engagement angle throughout the machining process.Finally,several experimental tests are carried out using the bull-nose end mill to validate the feasibility and effectiveness of the proposed method.展开更多
The global demand for effective skin injury treatments has prompted the exploration of tissue engineering solutions.While three-dimensional(3D)bioprinting has shown promise,challenges persist with respect to achieving...The global demand for effective skin injury treatments has prompted the exploration of tissue engineering solutions.While three-dimensional(3D)bioprinting has shown promise,challenges persist with respect to achieving timely and compatible solutions to treat diverse skin injuries.In situ bioprinting has emerged as a key new technology,since it reduces risks during the implantation of printed scaffolds and demonstrates superior therapeutic effects.However,maintaining printing fidelity during in situ bioprinting remains a critical challenge,particularly with respect to model layering and path planning.This study proposes a novel optimization-based conformal path planning strategy for in situ bioprinting-based repair of complex skin injuries.This strategy employs constrained optimization to identify optimal waypoints on a point cloud-approximated curved surface,thereby ensuring a high degree of similarity between predesigned planar and surface-mapped 3D paths.Furthermore,this method is applicable for skin wound treatments,since it generates 3D-equidistant zigzag curves along surface tangents and enables multi-layer conformal path planning to facilitate the treatment of volumetric injuries.Furthermore,the proposed algorithm was found to be a feasible and effective treatment in a murine back injury model as well as in other complex models,thereby showcasing its potential to guide in situ bioprinting,enhance bioprinting fidelity,and facilitate improvement of clinical outcomes.展开更多
With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths ha...With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths have become an important direction of intelligent teaching reform.The traditional“one-size-fits-all”teaching model has gradually failed to meet the individualized learning needs of students.However,through the advantages of data analysis and real-time feedback,AI technology can provide tailor-made teaching content and learning paths based on students’learning progress,interests,and abilities.This study explores the innovation of the personalized learning path model based on AI technology,and analyzes the potential and challenges of this model in improving teaching effectiveness,promoting the all-round development of students,and optimizing the interaction between teachers and students.Through case analysis and empirical research,this paper summarizes the implementation methods of the AI-driven personalized learning path,the innovation of teaching models,and their application prospects in educational reform.Meanwhile,the research also discussed the ethical issues of AI technology in education,data privacy protection,and its impact on the teacher-student relationship,and proposed corresponding solutions.展开更多
To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The...To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The inspection robot utilizes multiple sensors to monitor key parameters of the fans,such as vibration,noise,and bearing temperature,and upload the data to the monitoring center.The robot’s inspection path employs the improved A^(*)algorithm,incorporating obstacle penalty terms,path reconstruction,and smoothing optimization techniques,thereby achieving optimal path planning for the inspection robot in complex environments.Simulation results demonstrate that the improved A^(*)algorithm significantly outperforms the traditional A^(*)algorithm in terms of total path distance,smoothness,and detour rate,effectively improving the execution efficiency of inspection tasks.展开更多
In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms...In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms to solve the problem of multi-UAV path planning.The Dung Beetle Optimization(DBO)algorithm has been widely applied due to its diverse search patterns in the above algorithms.However,the update strategies for the rolling and thieving dung beetles of the DBO algorithm are overly simplistic,potentially leading to an inability to fully explore the search space and a tendency to converge to local optima,thereby not guaranteeing the discovery of the optimal path.To address these issues,we propose an improved DBO algorithm guided by the Landmark Operator(LODBO).Specifically,we first use tent mapping to update the population strategy,which enables the algorithm to generate initial solutions with enhanced diversity within the search space.Second,we expand the search range of the rolling ball dung beetle by using the landmark factor.Finally,by using the adaptive factor that changes with the number of iterations.,we improve the global search ability of the stealing dung beetle,making it more likely to escape from local optima.To verify the effectiveness of the proposed method,extensive simulation experiments are conducted,and the result shows that the LODBO algorithm can obtain the optimal path using the shortest time compared with the Genetic Algorithm(GA),the Gray Wolf Optimizer(GWO),the Whale Optimization Algorithm(WOA)and the original DBO algorithm in the disaster search and rescue task set.展开更多
Unmanned aerial vehicles(UAVs)are widely used in situations with uncertain and risky areas lacking network coverage.In natural disasters,timely delivery of first aid supplies is crucial.Current UAVs face risks such as...Unmanned aerial vehicles(UAVs)are widely used in situations with uncertain and risky areas lacking network coverage.In natural disasters,timely delivery of first aid supplies is crucial.Current UAVs face risks such as crashing into birds or unexpected structures.Airdrop systems with parachutes risk dispersing payloads away from target locations.The objective here is to use multiple UAVs to distribute payloads cooperatively to assigned locations.The civil defense department must balance coverage,accurate landing,and flight safety while considering battery power and capability.Deep Q-network(DQN)models are commonly used in multi-UAV path planning to effectively represent the surroundings and action spaces.Earlier strategies focused on advanced DQNs for UAV path planning in different configurations,but rarely addressed non-cooperative scenarios and disaster environments.This paper introduces a new DQN framework to tackle challenges in disaster environments.It considers unforeseen structures and birds that could cause UAV crashes and assumes urgent landing zones and winch-based airdrop systems for precise delivery and return.A new DQN model is developed,which incorporates the battery life,safe flying distance between UAVs,and remaining delivery points to encode surrounding hazards into the state space and Q-networks.Additionally,a unique reward system is created to improve UAV action sequences for better delivery coverage and safe landings.The experimental results demonstrate that multi-UAV first aid delivery in disaster environments can achieve advanced performance.展开更多
This study investigates the mechanical response of an underground cavern subjected to cyclic high gas pressure,aiming to establish a theoretical foundation for the design of lined rock caverns(LRCs)for energy storage ...This study investigates the mechanical response of an underground cavern subjected to cyclic high gas pressure,aiming to establish a theoretical foundation for the design of lined rock caverns(LRCs)for energy storage with high internal pressure,e.g.compressed air energy storage(CAES)underground caverns or hydrogen storage caverns.Initially,the stress paths of the surrounding rock during the excavation,pressurization,and depressurization processes are delineated.Analytical expressions for the stress and deformation of the surrounding rock are derived based on the MohreCoulomb criterion.These expressions are then employed to evaluate the displacement of cavern walls under varying qualities of surrounding rock,the contact pressure between the steel lining and the surrounding rock subject to different gas storage pressures,the load-bearing ratio of the surrounding rock,and the impact of lining thickness on the critical gas pressure.Furthermore,the deformation paths of the surrounding rock are evaluated,along with the effects of tunnel depth and diameter on residual deformation of the surrounding rock,and the critical minimum gas pressure at which the surrounding rock and the lining do not detach.The results indicate that residual deformation of the surrounding rock occurs after depressurization under higher internal pressure for higher-quality rock masses,leading to detachment between the surrounding rock and the steel lining.The findings indicate that thicker linings correspond to higher critical minimum gas pressures.However,for lower-quality surrounding rock,thicker linings correspond to lower critical minimum gas pressures.These findings will provide invaluable insights for the design of LRCs for underground energy storage caverns.展开更多
Small modular reactor(SMR)belongs to the research forefront of nuclear reactor technology.Nowadays,advancement of intelligent control technologies paves a new way to the design and build of unmanned SMR.The autonomous...Small modular reactor(SMR)belongs to the research forefront of nuclear reactor technology.Nowadays,advancement of intelligent control technologies paves a new way to the design and build of unmanned SMR.The autonomous control process of SMR can be divided into three stages,say,state diagnosis,autonomous decision-making and coordinated control.In this paper,the autonomous state recognition and task planning of unmanned SMR are investigated.An operating condition recognition method based on the knowledge base of SMR operation is proposed by using the artificial neural network(ANN)technology,which constructs a basis for the state judgment of intelligent reactor control path planning.An improved reinforcement learning path planning algorithm is utilized to implement the path transfer decision-makingThis algorithm performs condition transitions with minimal cost under specified modes.In summary,the full range control path intelligent decision-planning technology of SMR is realized,thus provides some theoretical basis for the design and build of unmanned SMR in the future.展开更多
The operating environment of the diesel engine air path system is complex and may be affected by external random disturbances.Potentially leading to faults.This paper addresses the fault-tolerant control problem of th...The operating environment of the diesel engine air path system is complex and may be affected by external random disturbances.Potentially leading to faults.This paper addresses the fault-tolerant control problem of the diesel engine air path system,assuming that the system may simultaneously be affected by actuator faults and external random disturbances,a disturbance observer-based sliding mode controller is designed.Through the linear matrix inequality technique for solving observer and controller gains,optimal gain matrices can be obtained,eliminating the manual adjustment process of controller parameters and reducing the chattering phenomenon of the sliding mode surface.Finally,the effectiveness of the proposed method is verified through simulation analysis.展开更多
In 2012, Ponraj et al. defined a concept of k-product cordial labeling as follows: Let f be a map from V(G)to { 0,1,⋯,k−1 }where k is an integer, 1≤k≤| V(G) |. For each edge uvassign the label f(u)f(v)(modk). f is c...In 2012, Ponraj et al. defined a concept of k-product cordial labeling as follows: Let f be a map from V(G)to { 0,1,⋯,k−1 }where k is an integer, 1≤k≤| V(G) |. For each edge uvassign the label f(u)f(v)(modk). f is called a k-product cordial labeling if | vf(i)−vf(j) |≤1, and | ef(i)−ef(j) |≤1, i,j∈{ 0,1,⋯,k−1 }, where vf(x)and ef(x)denote the number of vertices and edges respectively labeled with x (x=0,1,⋯,k−1). Motivated by this concept, we further studied and established that several families of graphs admit k-product cordial labeling. In this paper, we show that the path graphs Pnadmit k-product cordial labeling.展开更多
This paper, an addendum to “Dialectical Thermodynamics’ solution to the conceptual imbroglio that is the reversible path”, this journal, 10, 775-799, was written in response to the requests of several readers to pr...This paper, an addendum to “Dialectical Thermodynamics’ solution to the conceptual imbroglio that is the reversible path”, this journal, 10, 775-799, was written in response to the requests of several readers to provide further evidence of the said “imbroglio”. The evidence here presented relates to the incompatibility existing between the total-entropy and the Gibbs energy prescriptions for the reversible path. The previously published proof of the negentropic nature of the transformation of heat into work is here included to validate out conclusions about the Gibbs energy perspective.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
An efficient algorithm for path planning is crucial for guiding autonomous surface vehicles(ASVs)through designated waypoints.However,current evaluations of ASV path planning mainly focus on comparing total path lengt...An efficient algorithm for path planning is crucial for guiding autonomous surface vehicles(ASVs)through designated waypoints.However,current evaluations of ASV path planning mainly focus on comparing total path lengths,using temporal models to estimate travel time,idealized integration of global and local motion planners,and omission of external environmental disturbances.These rudimentary criteria cannot adequately capture real-world operations.To address these shortcomings,this study introduces a simulation framework for evaluating navigation modules designed for ASVs.The proposed framework is implemented on a prototype ASV using the Robot Operating System(ROS)and the Gazebo simulation platform.The implementation processes replicated satellite images with the extended Kalman filter technique to acquire localized location data.Cost minimization for global trajectories is achieved through the application of Dijkstra and A*algorithms,while local obstacle avoidance is managed by the dynamic window approach algorithm.The results demonstrate the distinctions and intricacies of the metrics provided by the proposed simulation framework compared with the rudimentary criteria commonly utilized in conventional path planning works.展开更多
Airborne area-array whisk-broom imaging systems typically adopt constant-speed scanning schemes.For large-inertia scanning systems,constant-speed scanning requires substantial time to complete the reversal motion,redu...Airborne area-array whisk-broom imaging systems typically adopt constant-speed scanning schemes.For large-inertia scanning systems,constant-speed scanning requires substantial time to complete the reversal motion,reducing the system's adaptability to high-speed reversal scanning and decreasing scanning efficiency.This study proposes a novel sinusoidal variable-speed roll scanning strategy,which reduces abrupt changes in speed and acceleration,minimizing time loss during reversals.Based on the forward image motion compensation strategy in the pitch direction,we establish a line-of-sight(LOS)position calculation model with vertical flight path correction(VFPC),ensuring that the central LOS of the scanned image remains stable on the same horizontal line,facilitating accurate image stitching in whisk-broom imaging.Through theoretical analysis and simulation experiments,the proposed method improves the scanning efficiency by approximately 18.6%at a 90o whiskbroom imaging angle under the same speed height ratio conditions.The new VFPC method enables wide-field,high-resolution imaging,achieving single-line LOS horizontal stability with an accuracy of better than O.4 mrad.The research is of great significance to promote the further development of airborne area-array whisk-broom imaging technology toward wider fields of view,higher speed height ratios,and greater scanning efficiency.展开更多
Against the backdrop of digital transformation,the agricultural digital economy is showing promising development trends,yet it also faces numerous challenges that hinder its high-quality growth.To align with the requi...Against the backdrop of digital transformation,the agricultural digital economy is showing promising development trends,yet it also faces numerous challenges that hinder its high-quality growth.To align with the requirements of agricultural digital transformation in the new era,it is necessary to accelerate the construction of digital infrastructure,create a favorable industrial environment,enhance the overall quality of the workforce,and implement a comprehensive approach to elevate the development level of the agricultural digital economy,thereby driving the high-quality development of modern agriculture.This article focuses on the development of the agricultural digital economy,summarizes relevant policies and practical pathways,and aims to provide references for related theories and practices.展开更多
基金supported in part by 14th Five Year National Key R&D Program Project(Project Number:2023YFB3211001)the National Natural Science Foundation of China(62273339,U24A201397).
文摘Rapidly-exploring Random Tree(RRT)and its variants have become foundational in path-planning research,yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees lead to slow convergence and force an unfavorable trade-off between path quality and traversal safety.To address these challenges,we introduce HS-APF-RRT*,a novel algorithm that fuses layered sampling,an enhanced Artificial Potential Field(APF),and a dynamic neighborhood-expansion mechanism.First,the workspace is hierarchically partitioned into macro,meso,and micro sampling layers,progressively biasing random samples toward safer,lower-energy regions.Second,we augment the traditional APF by incorporating a slope-dependent repulsive term,enabling stronger avoidance of steep obstacles.Third,a dynamic expansion strategy adaptively switches between 8 and 16 connected neighborhoods based on local obstacle density,striking an effective balance between search efficiency and collision-avoidance precision.In simulated off-road scenarios,HS-APF-RRT*is benchmarked against RRT*,GoalBiased RRT*,and APF-RRT*,and demonstrates significantly faster convergence,lower path-energy consumption,and enhanced safety margins.
基金Supported by China National Funds for Distinguished Young Scientists(30825046)the National High Technology Research and Development Grant(863 program, 2008AA02Z406)the Program for Innovative Research Team at Beijing University of Chinese Medicine (2011CXTD-07)
文摘OBJECTIVE:Sub-optimal health status(SHS),in which a person's mind and body exists in a low-quality state of being between disease and health,has become a public health problem that cannot be ignored in China.SHS measurement presents a challenge to the academic fields.We developed and evaluated a questionnaire from the perspective of traditional Chinese medicine(TCM) that embodies the features of TCM syndrome diagnosis for measuring SHS in China.METHODS:The construction of the theoretical framework of the questionnaire was based on a literature review,an expert questionnaire survey and group interviews.The subscales and questionnaire items were screened through a pilot study using statistical means and qualitative analysis.Reliability tests that were used included test-retest reliability,Cronbach's α coefficient,split-half reliability;validity tests included content validity,criterion validity,discrimination validity and construct validity.RESULTS:The final questionnaire,the SHSQ-50,included 50 five-class quantifiable items that encompassed nine subscales:liver stagnation syndrome,liver-Qi deficiency syndrome,spleen-Qi deficiency syndrome,liver-fire syndrome,heart-fire syndrome,stomach-fire syndrome,heart-Qi deficiency syndrome,lung-Qi deficiency syndrome and dampness syndrome.Questionnaires were completed by 268 of the 288 SHS subjects(93.0%) and by 86 of the 94 healthy subjects(91.5%).The Cronbach α coefficients,split-half coefficients and stability coefficients ranged from 0.70 to 0.95,0.67 to 0.87 and 0.88 to 0.98,respectively,for the overall scores and subscales.The Wilcoxon rank test showed statistically significant differences in the subscales and overall scores between the SHS group and the healthy group(P<0.01).Twelve factors with an eigenvalue greater than one were extracted by factor analysis and merged into nine factors,for which the cumulative contribution rate was 63.63%.The nine factors were corresponded to the overall structure of the questionnaire.CONCLUSION:The SHSQ-50 is a reliable and valid instrument for measuring TCM syndrome diagnosis of SHS in China.
基金Supported by China National Funds for Distinguished Young Scientists(No.30825046)Hi-Tech Research and Development Program of China(863 Program),No.2008AA02Z406Program for Innovative Research Team in Beijing University of Chinese Medicine(No.2011CXTD-07)
文摘OBJECTIVE:To investigate biological indicators of sub-optimal health status and provide means of objective assessment of sub-optimal health status.METHODS:We set the unified standards for diagnosing a SHS.We tested various laboratory indicators in 407 cases that we selected randomly from2807 subjects and collected 15 mL of fasting venous blood from each case.We measured serum immunoglobulin A(IgA)and immunoglobulin G(IgG)concentrations,serum beta endorphins(β-EP),cortisol(C),testosterone(T),plasma adrenocorticotropic hormone(ACTH)and serum T lymphocyte subsets CD3+and CD4+.RESULTS:Mean serum testosterone concentrations and their ratio to cortisol(C)concentrations weresignificantly higher in the healthy group than in those with sub-optimal health status(P<0.01).Mean serum CD3+concentrations were significantly higher in those with sub-optimal health status than in the healthy group(P<0.05).CONCLUSION:Decreased serum testosterone/cortisol ratio may be an objective indication of sub-optimal health status.Changes in neuroendocrine and immunological indicators may explain some of the symptoms,including malaise and poor work performance,attributable to persistent or relapsing fatigue in subjects with sub-optimal health status.
基金Supported by National Basic Research Program of China (2007CB310603)National Natural Science Foundation of China (No.60672093)National High Technology Project of China (2007AA01Z262)
文摘Joint sub-optimization of cooperative relays in Multiple-Input and Multiple-Output (MIMO) multiple relays aided communication system is discussed in this paper. Because the instantaneous channel state information of all source-relay channels and all relay-user channels is difficult to get at each relay node, an unjoined solution is designed according to the channel state information of that relay only. Then a multi-user loading algorithm is proposed to utilize the space diversity through multi-relay transmission. The simulation results show that with the newly proposed multi-user loading algorithm, the unjoined solution can achieve better system performance comparing with joint one in low SNR. However, the complexity of the former is much lower, for only partial CSI is needed.
基金supported by the National Natural Science Foundation of China(Grant Nos.U22A20202 and 52275477).
文摘Trochoidal milling is known for its advantages in machining difficult-to-machine materials as it facilitates chip removal and tool cooling.However,the conventional trochoidal tool path presents challenges such as lower machining efficiency and longer machining time due to its time-varying cutter-workpiece engagement angle and a high percentage of non-cutting tool paths.To address these issues,this paper introduces a parameter-variant trochoidal-like(PVTR)tool path planning method for chatter-free and high-efficiency milling.This method ensures a constant engagement angle for each tool path period by adjusting the trochoidal radius and step.Initially,the nonlinear equation for the PVTR toolpath is established.Then,a segmented recurrence method is proposed to plan tool paths based on the desired engagement angle.The impact of trochoidal tool path parameters on the engagement angle is analyzed and coupled this information with the milling stability model based on spindle speed and engagement angle to determine the desired engagement angle throughout the machining process.Finally,several experimental tests are carried out using the bull-nose end mill to validate the feasibility and effectiveness of the proposed method.
基金supported in part by the National Natural Science Foundation of China(Nos.52205532 and 624B2077)the National Key Research and Development Program of China(No.2023YFB4302003).
文摘The global demand for effective skin injury treatments has prompted the exploration of tissue engineering solutions.While three-dimensional(3D)bioprinting has shown promise,challenges persist with respect to achieving timely and compatible solutions to treat diverse skin injuries.In situ bioprinting has emerged as a key new technology,since it reduces risks during the implantation of printed scaffolds and demonstrates superior therapeutic effects.However,maintaining printing fidelity during in situ bioprinting remains a critical challenge,particularly with respect to model layering and path planning.This study proposes a novel optimization-based conformal path planning strategy for in situ bioprinting-based repair of complex skin injuries.This strategy employs constrained optimization to identify optimal waypoints on a point cloud-approximated curved surface,thereby ensuring a high degree of similarity between predesigned planar and surface-mapped 3D paths.Furthermore,this method is applicable for skin wound treatments,since it generates 3D-equidistant zigzag curves along surface tangents and enables multi-layer conformal path planning to facilitate the treatment of volumetric injuries.Furthermore,the proposed algorithm was found to be a feasible and effective treatment in a murine back injury model as well as in other complex models,thereby showcasing its potential to guide in situ bioprinting,enhance bioprinting fidelity,and facilitate improvement of clinical outcomes.
基金The 2024 Guangdong University of Science and Technology Teaching,Science and Innovation Project(GKJXXZ2024028)。
文摘With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths have become an important direction of intelligent teaching reform.The traditional“one-size-fits-all”teaching model has gradually failed to meet the individualized learning needs of students.However,through the advantages of data analysis and real-time feedback,AI technology can provide tailor-made teaching content and learning paths based on students’learning progress,interests,and abilities.This study explores the innovation of the personalized learning path model based on AI technology,and analyzes the potential and challenges of this model in improving teaching effectiveness,promoting the all-round development of students,and optimizing the interaction between teachers and students.Through case analysis and empirical research,this paper summarizes the implementation methods of the AI-driven personalized learning path,the innovation of teaching models,and their application prospects in educational reform.Meanwhile,the research also discussed the ethical issues of AI technology in education,data privacy protection,and its impact on the teacher-student relationship,and proposed corresponding solutions.
文摘To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The inspection robot utilizes multiple sensors to monitor key parameters of the fans,such as vibration,noise,and bearing temperature,and upload the data to the monitoring center.The robot’s inspection path employs the improved A^(*)algorithm,incorporating obstacle penalty terms,path reconstruction,and smoothing optimization techniques,thereby achieving optimal path planning for the inspection robot in complex environments.Simulation results demonstrate that the improved A^(*)algorithm significantly outperforms the traditional A^(*)algorithm in terms of total path distance,smoothness,and detour rate,effectively improving the execution efficiency of inspection tasks.
基金supported by the National Natural Science Foundation of China(No.62373027).
文摘In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms to solve the problem of multi-UAV path planning.The Dung Beetle Optimization(DBO)algorithm has been widely applied due to its diverse search patterns in the above algorithms.However,the update strategies for the rolling and thieving dung beetles of the DBO algorithm are overly simplistic,potentially leading to an inability to fully explore the search space and a tendency to converge to local optima,thereby not guaranteeing the discovery of the optimal path.To address these issues,we propose an improved DBO algorithm guided by the Landmark Operator(LODBO).Specifically,we first use tent mapping to update the population strategy,which enables the algorithm to generate initial solutions with enhanced diversity within the search space.Second,we expand the search range of the rolling ball dung beetle by using the landmark factor.Finally,by using the adaptive factor that changes with the number of iterations.,we improve the global search ability of the stealing dung beetle,making it more likely to escape from local optima.To verify the effectiveness of the proposed method,extensive simulation experiments are conducted,and the result shows that the LODBO algorithm can obtain the optimal path using the shortest time compared with the Genetic Algorithm(GA),the Gray Wolf Optimizer(GWO),the Whale Optimization Algorithm(WOA)and the original DBO algorithm in the disaster search and rescue task set.
基金supported by the Committee of Science of the Ministry of Education and Science of the Republic of Kazakhstan under Grant No.249015/0224.
文摘Unmanned aerial vehicles(UAVs)are widely used in situations with uncertain and risky areas lacking network coverage.In natural disasters,timely delivery of first aid supplies is crucial.Current UAVs face risks such as crashing into birds or unexpected structures.Airdrop systems with parachutes risk dispersing payloads away from target locations.The objective here is to use multiple UAVs to distribute payloads cooperatively to assigned locations.The civil defense department must balance coverage,accurate landing,and flight safety while considering battery power and capability.Deep Q-network(DQN)models are commonly used in multi-UAV path planning to effectively represent the surroundings and action spaces.Earlier strategies focused on advanced DQNs for UAV path planning in different configurations,but rarely addressed non-cooperative scenarios and disaster environments.This paper introduces a new DQN framework to tackle challenges in disaster environments.It considers unforeseen structures and birds that could cause UAV crashes and assumes urgent landing zones and winch-based airdrop systems for precise delivery and return.A new DQN model is developed,which incorporates the battery life,safe flying distance between UAVs,and remaining delivery points to encode surrounding hazards into the state space and Q-networks.Additionally,a unique reward system is created to improve UAV action sequences for better delivery coverage and safe landings.The experimental results demonstrate that multi-UAV first aid delivery in disaster environments can achieve advanced performance.
基金supported by the State Key Laboratory of Disaster Reduction in Civil Engineering(Grant No.SLDRCE23-02)Ningbo PublicWelfare Fund Project(Grant No.2023S100)the National Key Research and Development Program of China(Grant No.2024YFE0105800).
文摘This study investigates the mechanical response of an underground cavern subjected to cyclic high gas pressure,aiming to establish a theoretical foundation for the design of lined rock caverns(LRCs)for energy storage with high internal pressure,e.g.compressed air energy storage(CAES)underground caverns or hydrogen storage caverns.Initially,the stress paths of the surrounding rock during the excavation,pressurization,and depressurization processes are delineated.Analytical expressions for the stress and deformation of the surrounding rock are derived based on the MohreCoulomb criterion.These expressions are then employed to evaluate the displacement of cavern walls under varying qualities of surrounding rock,the contact pressure between the steel lining and the surrounding rock subject to different gas storage pressures,the load-bearing ratio of the surrounding rock,and the impact of lining thickness on the critical gas pressure.Furthermore,the deformation paths of the surrounding rock are evaluated,along with the effects of tunnel depth and diameter on residual deformation of the surrounding rock,and the critical minimum gas pressure at which the surrounding rock and the lining do not detach.The results indicate that residual deformation of the surrounding rock occurs after depressurization under higher internal pressure for higher-quality rock masses,leading to detachment between the surrounding rock and the steel lining.The findings indicate that thicker linings correspond to higher critical minimum gas pressures.However,for lower-quality surrounding rock,thicker linings correspond to lower critical minimum gas pressures.These findings will provide invaluable insights for the design of LRCs for underground energy storage caverns.
文摘Small modular reactor(SMR)belongs to the research forefront of nuclear reactor technology.Nowadays,advancement of intelligent control technologies paves a new way to the design and build of unmanned SMR.The autonomous control process of SMR can be divided into three stages,say,state diagnosis,autonomous decision-making and coordinated control.In this paper,the autonomous state recognition and task planning of unmanned SMR are investigated.An operating condition recognition method based on the knowledge base of SMR operation is proposed by using the artificial neural network(ANN)technology,which constructs a basis for the state judgment of intelligent reactor control path planning.An improved reinforcement learning path planning algorithm is utilized to implement the path transfer decision-makingThis algorithm performs condition transitions with minimal cost under specified modes.In summary,the full range control path intelligent decision-planning technology of SMR is realized,thus provides some theoretical basis for the design and build of unmanned SMR in the future.
基金Supported by the National Key R&D Program of China(2021YFB2011300)the National Natural Science Foundation of China(52275044,52205299)+1 种基金the Zhejiang Provincial Natural Science Foundation of China(Z23E050032)the China Postdoctoral Science Foundation(2022M710304).
文摘The operating environment of the diesel engine air path system is complex and may be affected by external random disturbances.Potentially leading to faults.This paper addresses the fault-tolerant control problem of the diesel engine air path system,assuming that the system may simultaneously be affected by actuator faults and external random disturbances,a disturbance observer-based sliding mode controller is designed.Through the linear matrix inequality technique for solving observer and controller gains,optimal gain matrices can be obtained,eliminating the manual adjustment process of controller parameters and reducing the chattering phenomenon of the sliding mode surface.Finally,the effectiveness of the proposed method is verified through simulation analysis.
文摘In 2012, Ponraj et al. defined a concept of k-product cordial labeling as follows: Let f be a map from V(G)to { 0,1,⋯,k−1 }where k is an integer, 1≤k≤| V(G) |. For each edge uvassign the label f(u)f(v)(modk). f is called a k-product cordial labeling if | vf(i)−vf(j) |≤1, and | ef(i)−ef(j) |≤1, i,j∈{ 0,1,⋯,k−1 }, where vf(x)and ef(x)denote the number of vertices and edges respectively labeled with x (x=0,1,⋯,k−1). Motivated by this concept, we further studied and established that several families of graphs admit k-product cordial labeling. In this paper, we show that the path graphs Pnadmit k-product cordial labeling.
文摘This paper, an addendum to “Dialectical Thermodynamics’ solution to the conceptual imbroglio that is the reversible path”, this journal, 10, 775-799, was written in response to the requests of several readers to provide further evidence of the said “imbroglio”. The evidence here presented relates to the incompatibility existing between the total-entropy and the Gibbs energy prescriptions for the reversible path. The previously published proof of the negentropic nature of the transformation of heat into work is here included to validate out conclusions about the Gibbs energy perspective.
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 by the funding from RMIT Internal Research Grant R1.
文摘An efficient algorithm for path planning is crucial for guiding autonomous surface vehicles(ASVs)through designated waypoints.However,current evaluations of ASV path planning mainly focus on comparing total path lengths,using temporal models to estimate travel time,idealized integration of global and local motion planners,and omission of external environmental disturbances.These rudimentary criteria cannot adequately capture real-world operations.To address these shortcomings,this study introduces a simulation framework for evaluating navigation modules designed for ASVs.The proposed framework is implemented on a prototype ASV using the Robot Operating System(ROS)and the Gazebo simulation platform.The implementation processes replicated satellite images with the extended Kalman filter technique to acquire localized location data.Cost minimization for global trajectories is achieved through the application of Dijkstra and A*algorithms,while local obstacle avoidance is managed by the dynamic window approach algorithm.The results demonstrate the distinctions and intricacies of the metrics provided by the proposed simulation framework compared with the rudimentary criteria commonly utilized in conventional path planning works.
基金Supported by the National Key Research and Development Program(2023YFC3107602)。
文摘Airborne area-array whisk-broom imaging systems typically adopt constant-speed scanning schemes.For large-inertia scanning systems,constant-speed scanning requires substantial time to complete the reversal motion,reducing the system's adaptability to high-speed reversal scanning and decreasing scanning efficiency.This study proposes a novel sinusoidal variable-speed roll scanning strategy,which reduces abrupt changes in speed and acceleration,minimizing time loss during reversals.Based on the forward image motion compensation strategy in the pitch direction,we establish a line-of-sight(LOS)position calculation model with vertical flight path correction(VFPC),ensuring that the central LOS of the scanned image remains stable on the same horizontal line,facilitating accurate image stitching in whisk-broom imaging.Through theoretical analysis and simulation experiments,the proposed method improves the scanning efficiency by approximately 18.6%at a 90o whiskbroom imaging angle under the same speed height ratio conditions.The new VFPC method enables wide-field,high-resolution imaging,achieving single-line LOS horizontal stability with an accuracy of better than O.4 mrad.The research is of great significance to promote the further development of airborne area-array whisk-broom imaging technology toward wider fields of view,higher speed height ratios,and greater scanning efficiency.
文摘Against the backdrop of digital transformation,the agricultural digital economy is showing promising development trends,yet it also faces numerous challenges that hinder its high-quality growth.To align with the requirements of agricultural digital transformation in the new era,it is necessary to accelerate the construction of digital infrastructure,create a favorable industrial environment,enhance the overall quality of the workforce,and implement a comprehensive approach to elevate the development level of the agricultural digital economy,thereby driving the high-quality development of modern agriculture.This article focuses on the development of the agricultural digital economy,summarizes relevant policies and practical pathways,and aims to provide references for related theories and practices.
