Universities shoulder the important mission of talent cultivation,scientific research,social service,cultural heritage and innovation,and international exchange and cooperation.International exchange and cooperation h...Universities shoulder the important mission of talent cultivation,scientific research,social service,cultural heritage and innovation,and international exchange and cooperation.International exchange and cooperation have become the fifth major function of universities.Based on the background of the globalization era,undergraduate colleges and universities should pay more attention to the cultivation of students’intercultural communication and understanding ability while cultivating their professional skills,and take expanding students’international vision and enhancing the international competitiveness of China’s education as important tasks.Labor education is an important content of the national education system,which has the comprehensive nurturing value of cultivating morality,increasing intelligence,strengthening physical fitness,and cultivating beauty.Higher education institutions should further optimize the system of labor education,expand students’space and field of thinking in the process of labor education,and broaden students’international perspectives.展开更多
In response to the Beautiful China development strategy,in accordance with the"applicable,economical,green and beautiful"architectural policy of the new era,green buildings have been continuously optimized a...In response to the Beautiful China development strategy,in accordance with the"applicable,economical,green and beautiful"architectural policy of the new era,green buildings have been continuously optimized and popularized.Based on the life cycle theory,from the multi-dimensional perspectives of policy,building materials,construction,design,evaluation standards,operation,etc.,this paper studied the implementation path and development trend of green buildings.It discussed the main implementation paths and restrictive factors of green buildings,and provided solutions and development directions.It mainly elaborated the influencing factors and development direction of green buildings,in order to provide a documentary support for the development of green building industry,and provide a certain reference for the ecological civilization construction of beautiful China.展开更多
Financial quotient education has become an inevitable requirement of quality education in China,with vital practical significance.By investigating the current financial education situation for teenagers in Banan Distr...Financial quotient education has become an inevitable requirement of quality education in China,with vital practical significance.By investigating the current financial education situation for teenagers in Banan District,Chongqing,we find some problems such as parents'weak awareness of financial education,lack of financial education in schools,and lack of professional teachers.This paper proposes the"three-in-one"financial quotient education implementation path of family,school,and government,hoping to explore the construction of a youth financial quotient education system and provide a reference for various subjects to carry out financial quotient education for young people.Further,enrich the achievements of characteristic education and promote the development of quality education in primary and secondary schools.展开更多
Climate change is a common problem in human society.The Chinese government promises to peak carbon dioxide emissions by 2030 and strives to achieve carbon neutralization by 2060.The proposal of the goal of carbon peak...Climate change is a common problem in human society.The Chinese government promises to peak carbon dioxide emissions by 2030 and strives to achieve carbon neutralization by 2060.The proposal of the goal of carbon peak and carbon neutralization has led China into the era of climate economy and set off a green change with both opportunities and challenges.On the basis of expounding the objectives and specific connotation of China’s carbon peak and carbon neutralization,this paper systematically discusses the main implementation path and the prospect of China’s carbon peak and carbon neutralization.China’s path to realizing carbon neutralization includes four directions:(1)in terms of carbon dioxide emission control:energy transformation path,energy conservation,and emission reduction path;(2)for increasing carbon sink:carbon capture,utilization,and storage path,ecological governance,and land greening path;(3)in key technology development:zero-carbon utilization,coal new energy coupling,carbon capture utilization and storage(CCUS),energy storage technology and other key technology paths required to achieve carbon peak and carbon neutralization;(4)from the angle of policy development:Formulate legal guarantees for the government to promote the carbon trading market;Formulate carbon emission standards for enterprises and increase publicity and education for individuals and society.Based on practicing the goal and path of carbon peak and carbon neutralization,China will vigorously develop low carbon and circular economy and promote green and high-quality economic development;speed up to enter the era of fossil resources and promoting energy transformation;accelerate the integrated innovation of green and low-carbon technologies and promote carbon neutrality.展开更多
Information technology has assisted in the elevation of the development of human society,thereby accelerating the development process,altering the way of life of human beings,and also changing the way of thinking of h...Information technology has assisted in the elevation of the development of human society,thereby accelerating the development process,altering the way of life of human beings,and also changing the way of thinking of human beings.The effect on human society is beyond words.For college students who collectively represent a group of entrepreneurs in the society,the use of big data technology for innovation and entrepreneurship has become the current development trend.The application of big data technology has provided convenience for entrepreneurial activities carried out by college students.In view of this,this article explores the implementation path of innovation and entrepreneurship among college students in the context of big data.At first,the paper introduces the advantages of innovation and entrepreneurship to college students in the era of big data,and then analyzes its current situation.Finally,the paper discusses the implementation path of innovation and entrepreneurship which can be used by the college students as a reference to carry out innovation and entrepreneurship activities.展开更多
Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical ...Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.展开更多
As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path pla...As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards.For larger terminalmaps and complex environments,the grid method is employed to model AGVs’road networks.An improved bounded conflict-based search(IBCBS)algorithmtailored to ACT is proposed,leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range.Comparative experiments involving 60 AGVs indicate a reduction in computing time by 37.397%to 64.06%while maintaining the over cost within 1.019%.Numerical experiments validate the proposed algorithm’s efficacy in enhancing efficiency and ensuring solution quality.展开更多
Acupuncture enjoys a robust evidence base for dozens of clinical conditions and decades of research exploring its mechanisms of action. It has over 9,000 positive recommendations from official government and clinical ...Acupuncture enjoys a robust evidence base for dozens of clinical conditions and decades of research exploring its mechanisms of action. It has over 9,000 positive recommendations from official government and clinical guidelines. However, it still remains relatively inaccessible in the United States, Europe and elsewhere, especially compared to the strength of evidence-based recommendations for its use. Acupuncture would benefit from robust implementation strategies, utilizing insights and approaches from implementation science. The clinical use of Botox for migraine suffered from weaker evidence of effectiveness and greater evidence of harm, but using a streamlined and robust implementation strategy, Allergan was able to achieve widespread implementation from when it began its efforts around 2010. Such a systematic approach that identifies and overcomes barriers to implementation for acupuncture would benefit millions of people who currently are offered less effective and more invasive treatments, contrary to the recommendations of clinical guidelines.展开更多
This article investigates a multi-circular path-following formation control with reinforced transient profiles for nonholonomic vehicles connected by a digraph.A multi-circular formation controller endowed with the fe...This article investigates a multi-circular path-following formation control with reinforced transient profiles for nonholonomic vehicles connected by a digraph.A multi-circular formation controller endowed with the feature of spatial-temporal decoupling is devised for a group of vehicles guided by a virtual leader evolving along an implicit path,which allows for a circumnavigation on multiple circles with an anticipant angular spacing.In addition,notice that it typically imposes a stringent time constraint on time-sensitive enclosing scenarios,hence an improved prescribed performance control(IPPC)using novel tighter behavior boundaries is presented to enhance transient capabilities with an ensured appointed-time convergence free from any overshoots.The significant merits are that coordinated circumnavigation along different circles can be realized via executing geometric and dynamic assignments independently with modified transient profiles.Furthermore,all variables existing in the entire system are analyzed to be convergent.Simulation and experimental results are provided to validate the utility of suggested solution.展开更多
Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a gro...Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.展开更多
The contents of carbon(C),nitrogen(N),and phosphorus(P)in soil-microorganisms-plant significantly affect tea quality by altering the main quality components of tea,such as tea polyphenols,amino acids,and caffeine.Howev...The contents of carbon(C),nitrogen(N),and phosphorus(P)in soil-microorganisms-plant significantly affect tea quality by altering the main quality components of tea,such as tea polyphenols,amino acids,and caffeine.However,few studies have quantified the effects of these factors on the main quality components of tea.The study aimed to explore the interactions of C,N,and P in soil-microorganisms-plants and the effects of these factors on the main quality components of tea by using the path analysis method.The results indicated that(1)The contents of C,N,and P in soil,microorganisms,and tea plants were highly correlated and collinear,and showed significant correlations with the main quality components of tea.(2)Optimal regression equations were established to esti-mate tea polyphenol,amino acid,catechin,caffeine,and water extract content based on C,N,and P contents in soil,microorganisms,and tea plants(R^(2)=0.923,0.726,0.954,0.848,and 0.883,respectively).(3)Pathway analysis showed that microbial biomass phosphorus(MBP),root phosphorus,branch nitrogen,and microbial biomass carbon(MBC)were the largest direct impact factors on tea polyphenol,catechin,water extracts,amino acid,and caffeine content,respectively.Leaf carbon,root phosphorus,and leaf nitrogen were the largest indirect impact factors on tea polyphenol,catechin,and water extract content,respectively.Leaf carbon indirectly affected tea polyphenol content mainly by altering MBP content.Root phosphorus indirectly affected catechin content mainly by altering soil organic carbon content.Leaf nitrogen indirectly affected water extract content mainly by altering branch nitrogen content.The research results provide the scientific basis for reasonable fertilization in tea gardens and tea quality improvement.展开更多
In the domain of autonomous industrial manipulators,precise positioning and appropriate posture selection in path planning are pivotal for tasks involving obstacle avoidance,such as handling,heat sealing,and stacking....In the domain of autonomous industrial manipulators,precise positioning and appropriate posture selection in path planning are pivotal for tasks involving obstacle avoidance,such as handling,heat sealing,and stacking.While Multi-Degree-of-Freedom(MDOF)manipulators offer kinematic redundancy,aiding in the derivation of optimal inverse kinematic solutions to meet position and posture requisites,their path planning entails intricate multiobjective optimization,encompassing path,posture,and joint motion optimization.Achieving satisfactory results in practical scenarios remains challenging.In response,this study introduces a novel Reverse Path Planning(RPP)methodology tailored for industrial manipulators.The approach commences by conceptualizing the manipulator’s end-effector as an agent within a reinforcement learning(RL)framework,wherein the state space,action set,and reward function are precisely defined to expedite the search for an initial collision-free path.To enhance convergence speed,the Q-learning algorithm in RL is augmented with Dyna-Q.Additionally,we formulate the cylindrical bounding box of the manipulator based on its Denavit-Hartenberg(DH)parameters and propose a swift collision detection technique.Furthermore,the motion performance of the end-effector is refined through a bidirectional search,and joint weighting coefficients are introduced to mitigate motion in high-power joints.The efficacy of the proposed RPP methodology is rigorously examined through extensive simulations conducted on a six-degree-of-freedom(6-DOF)manipulator encountering two distinct obstacle configurations and target positions.Experimental results substantiate that the RPP method adeptly orchestrates the computation of the shortest collision-free path while adhering to specific posture constraints at the target point.Moreover,itminimizes both posture angle deviations and joint motion,showcasing its prowess in enhancing the operational performance of MDOF industrial manipulators.展开更多
Due to its flexibility and complementarity, the multiUAVs system is well adapted to complex and cramped workspaces, with great application potential in the search and rescue(SAR) and indoor goods delivery fields. Howe...Due to its flexibility and complementarity, the multiUAVs system is well adapted to complex and cramped workspaces, with great application potential in the search and rescue(SAR) and indoor goods delivery fields. However, safe and effective path planning of multiple unmanned aerial vehicles(UAVs)in the cramped environment is always challenging: conflicts with each other are frequent because of high-density flight paths, collision probability increases because of space constraints, and the search space increases significantly, including time scale, 3D scale and model scale. Thus, this paper proposes a hierarchical collaborative planning framework with a conflict avoidance module at the high level and a path generation module at the low level. The enhanced conflict-base search(ECBS) in our framework is improved to handle the conflicts in the global path planning and avoid the occurrence of local deadlock. And both the collision and kinematic models of UAVs are considered to improve path smoothness and flight safety. Moreover, we specifically designed and published the cramped environment test set containing various unique obstacles to evaluating our framework performance thoroughly. Experiments are carried out relying on Rviz, with multiple flight missions: random, opposite, and staggered, which showed that the proposed method can generate smooth cooperative paths without conflict for at least 60 UAVs in a few minutes.The benchmark and source code are released in https://github.com/inin-xingtian/multi-UAVs-path-planner.展开更多
With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated...With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated from monitoring and long-distance transmission places a heavy burden on sensor nodes with the limited battery power.For this,we investigate an unmanned aerial vehicles assisted mobile wireless sensor network(UAV-assisted WSN)to prolong the network lifetime in this paper.Specifically,we use UAVs to assist the WSN in collecting data.In the current UAV-assisted WSN,the clustering and routing schemes are determined sequentially.However,such a separate consideration might not maximize the lifetime of the whole WSN due to the mutual coupling of clustering and routing.To efficiently prolong the lifetime of the WSN,we propose an integrated clustering and routing scheme that jointly optimizes the clustering and routing together.In the whole network space,it is intractable to efficiently obtain the optimal integrated clustering and routing scheme.Therefore,we propose the Monte-Las search strategy based on Monte Carlo and Las Vegas ideas,which can generate the chain matrix to guide the algorithm to find the solution faster.Unnecessary point-to-point collection leads to long collection paths,so a triangle optimization strategy is then proposed that finds a compromise path to shorten the collection path based on the geometric distribution and energy of sensor nodes.To avoid the coverage hole caused by the death of sensor nodes,the deployment of mobile sensor nodes and the preventive mechanism design are indispensable.An emergency data transmission mechanism is further proposed to reduce the latency of collecting the latency-sensitive data due to the absence of UAVs.Compared with the existing schemes,the proposed scheme can prolong the lifetime of the UAVassisted WSN at least by 360%,and shorten the collection path of UAVs by 56.24%.展开更多
Reducing casualties and property losses through effective evacuation route planning has been a key focus for researchers in recent years.As part of this effort,an enhanced sparrow search algorithm(MSSA)was proposed.Fi...Reducing casualties and property losses through effective evacuation route planning has been a key focus for researchers in recent years.As part of this effort,an enhanced sparrow search algorithm(MSSA)was proposed.Firstly,the Golden Sine algorithm and a nonlinear weight factor optimization strategy were added in the discoverer position update stage of the SSA algorithm.Secondly,the Cauchy-Gaussian perturbation was applied to the optimal position of the SSA algorithm to improve its ability to jump out of local optima.Finally,the local search mechanism based on the mountain climbing method was incorporated into the local search stage of the SSA algorithm,improving its local search ability.To evaluate the effectiveness of the proposed algorithm,the Whale Algorithm,Gray Wolf Algorithm,Improved Gray Wolf Algorithm,Sparrow Search Algorithm,and MSSA Algorithm were employed to solve various test functions.The accuracy and convergence speed of each algorithm were then compared and analyzed.The results indicate that the MSSA algorithm has superior solving ability and stability compared to other algorithms.To further validate the enhanced algorithm’s capabilities for path planning,evacuation experiments were conducted using different maps featuring various obstacle types.Additionally,a multi-exit evacuation scenario was constructed according to the actual building environment of a teaching building.Both the sparrow search algorithm and MSSA algorithm were employed in the simulation experiment for multiexit evacuation path planning.The findings demonstrate that the MSSA algorithm outperforms the comparison algorithm,showcasing its greater advantages and higher application potential.展开更多
Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm ...Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm is proposed for the urban rescue search or military search in outdoor environment.Due to flexible control of small UAVs, it can be considered that all UAVs fly at the same altitude, that is, they perform search tasks on a two-dimensional plane. Based on the agents’ motion characteristics and environmental information, a mathematical model of CCPP problem is established. The minimum time for UAVs to complete the CCPP is the objective function, and complete coverage constraint, no-fly constraint, collision avoidance constraint, and communication constraint are considered. Four motion strategies and two communication strategies are designed. Then a distributed CCPP algorithm is designed based on hybrid strategies. Simulation results compared with patternbased genetic algorithm(PBGA) and random search method show that the proposed method has stronger real-time performance and better scalability and can complete the complete CCPP task more efficiently and stably.展开更多
To address the shortcomings of single-step decision making in the existing deep reinforcement learning based unmanned aerial vehicle(UAV)real-time path planning problem,a real-time UAV path planning algorithm based on...To address the shortcomings of single-step decision making in the existing deep reinforcement learning based unmanned aerial vehicle(UAV)real-time path planning problem,a real-time UAV path planning algorithm based on long shortterm memory(RPP-LSTM)network is proposed,which combines the memory characteristics of recurrent neural network(RNN)and the deep reinforcement learning algorithm.LSTM networks are used in this algorithm as Q-value networks for the deep Q network(DQN)algorithm,which makes the decision of the Q-value network has some memory.Thanks to LSTM network,the Q-value network can use the previous environmental information and action information which effectively avoids the problem of single-step decision considering only the current environment.Besides,the algorithm proposes a hierarchical reward and punishment function for the specific problem of UAV real-time path planning,so that the UAV can more reasonably perform path planning.Simulation verification shows that compared with the traditional feed-forward neural network(FNN)based UAV autonomous path planning algorithm,the RPP-LSTM proposed in this paper can adapt to more complex environments and has significantly improved robustness and accuracy when performing UAV real-time path planning.展开更多
This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapi...This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapidly-exploring Random Trees*(Q-RRT*)algorithm.A cost inequality relationship between an ancestor and its descendants was derived,and the ancestors were filtered accordingly.Secondly,the underwater gravity-aided navigation path planning system was designed based on the DSFS algorithm,taking into account the fitness,safety,and asymptotic optimality of the routes,according to the gravity suitability distribution of the navigation space.Finally,experimental comparisons of the computing performance of the ChooseParent procedure,the Rewire procedure,and the combination of the two procedures for Q-RRT*and DSFS were conducted under the same planning environment and parameter conditions,respectively.The results showed that the computational efficiency of the DSFS algorithm was improved by about 1.2 times compared with the Q-RRT*algorithm while ensuring correct computational results.展开更多
Surrounding rocks at different locations are generally subjected to different stress paths during the process of deep hard rock excavation.In this study,to reveal the mechanical parameters of deep surrounding rock und...Surrounding rocks at different locations are generally subjected to different stress paths during the process of deep hard rock excavation.In this study,to reveal the mechanical parameters of deep surrounding rock under different stress paths,a new cyclic loading and unloading test method for controlled true triaxial loading and unloading and principal stress direction interchange was proposed,and the evolution of mechanical parameters of Shuangjiangkou granite under different stress paths was studied,including the deformation modulus,elastic deformation increment ratios,fracture degree,cohesion and internal friction angle.Additionally,stress path coefficient was defined to characterize different stress paths,and the functional relationships among the stress path coefficient,rock fracture degree difference coefficient,cohesion and internal friction angle were obtained.The results show that during the true triaxial cyclic loading and unloading process,the deformation modulus and cohesion gradually decrease,while the internal friction angle gradually increases with increasing equivalent crack strain.The stress path coefficient is exponentially related to the rock fracture degree difference coefficient.As the stress path coefficient increases,the degrees of cohesion weakening and internal friction angle strengthening decrease linearly.During cyclic loading and unloading under true triaxial principal stress direction interchange,the direction of crack development changes,and the deformation modulus increases,while the cohesion and internal friction angle decrease slightly,indicating that the principal stress direction interchange has a strengthening effect on the surrounding rocks.Finally,the influences of the principal stress interchange direction on the stabilities of deep engineering excavation projects are discussed.展开更多
基金Key Research Base of Humanities and Social Sciences of Sichuan Province-Sichuan International Education Development Research Center“Research on the Implementation Path of Labor Education in Private Undergraduate Colleges and Universities Under International Perspective”(SCGJ2023-12)。
文摘Universities shoulder the important mission of talent cultivation,scientific research,social service,cultural heritage and innovation,and international exchange and cooperation.International exchange and cooperation have become the fifth major function of universities.Based on the background of the globalization era,undergraduate colleges and universities should pay more attention to the cultivation of students’intercultural communication and understanding ability while cultivating their professional skills,and take expanding students’international vision and enhancing the international competitiveness of China’s education as important tasks.Labor education is an important content of the national education system,which has the comprehensive nurturing value of cultivating morality,increasing intelligence,strengthening physical fitness,and cultivating beauty.Higher education institutions should further optimize the system of labor education,expand students’space and field of thinking in the process of labor education,and broaden students’international perspectives.
文摘In response to the Beautiful China development strategy,in accordance with the"applicable,economical,green and beautiful"architectural policy of the new era,green buildings have been continuously optimized and popularized.Based on the life cycle theory,from the multi-dimensional perspectives of policy,building materials,construction,design,evaluation standards,operation,etc.,this paper studied the implementation path and development trend of green buildings.It discussed the main implementation paths and restrictive factors of green buildings,and provided solutions and development directions.It mainly elaborated the influencing factors and development direction of green buildings,in order to provide a documentary support for the development of green building industry,and provide a certain reference for the ecological civilization construction of beautiful China.
文摘Financial quotient education has become an inevitable requirement of quality education in China,with vital practical significance.By investigating the current financial education situation for teenagers in Banan District,Chongqing,we find some problems such as parents'weak awareness of financial education,lack of financial education in schools,and lack of professional teachers.This paper proposes the"three-in-one"financial quotient education implementation path of family,school,and government,hoping to explore the construction of a youth financial quotient education system and provide a reference for various subjects to carry out financial quotient education for young people.Further,enrich the achievements of characteristic education and promote the development of quality education in primary and secondary schools.
基金This study was supported by the project of China Geological Survey(DD20211413,Comprehensive Evaluation of Ecological Protection and Utilization of Natural Resources).
文摘Climate change is a common problem in human society.The Chinese government promises to peak carbon dioxide emissions by 2030 and strives to achieve carbon neutralization by 2060.The proposal of the goal of carbon peak and carbon neutralization has led China into the era of climate economy and set off a green change with both opportunities and challenges.On the basis of expounding the objectives and specific connotation of China’s carbon peak and carbon neutralization,this paper systematically discusses the main implementation path and the prospect of China’s carbon peak and carbon neutralization.China’s path to realizing carbon neutralization includes four directions:(1)in terms of carbon dioxide emission control:energy transformation path,energy conservation,and emission reduction path;(2)for increasing carbon sink:carbon capture,utilization,and storage path,ecological governance,and land greening path;(3)in key technology development:zero-carbon utilization,coal new energy coupling,carbon capture utilization and storage(CCUS),energy storage technology and other key technology paths required to achieve carbon peak and carbon neutralization;(4)from the angle of policy development:Formulate legal guarantees for the government to promote the carbon trading market;Formulate carbon emission standards for enterprises and increase publicity and education for individuals and society.Based on practicing the goal and path of carbon peak and carbon neutralization,China will vigorously develop low carbon and circular economy and promote green and high-quality economic development;speed up to enter the era of fossil resources and promoting energy transformation;accelerate the integrated innovation of green and low-carbon technologies and promote carbon neutrality.
文摘Information technology has assisted in the elevation of the development of human society,thereby accelerating the development process,altering the way of life of human beings,and also changing the way of thinking of human beings.The effect on human society is beyond words.For college students who collectively represent a group of entrepreneurs in the society,the use of big data technology for innovation and entrepreneurship has become the current development trend.The application of big data technology has provided convenience for entrepreneurial activities carried out by college students.In view of this,this article explores the implementation path of innovation and entrepreneurship among college students in the context of big data.At first,the paper introduces the advantages of innovation and entrepreneurship to college students in the era of big data,and then analyzes its current situation.Finally,the paper discusses the implementation path of innovation and entrepreneurship which can be used by the college students as a reference to carry out innovation and entrepreneurship activities.
文摘Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.
基金supported by National Natural Science Foundation of China(No.62073212)Shanghai Science and Technology Commission(No.23ZR1426600).
文摘As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards.For larger terminalmaps and complex environments,the grid method is employed to model AGVs’road networks.An improved bounded conflict-based search(IBCBS)algorithmtailored to ACT is proposed,leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range.Comparative experiments involving 60 AGVs indicate a reduction in computing time by 37.397%to 64.06%while maintaining the over cost within 1.019%.Numerical experiments validate the proposed algorithm’s efficacy in enhancing efficiency and ensuring solution quality.
文摘Acupuncture enjoys a robust evidence base for dozens of clinical conditions and decades of research exploring its mechanisms of action. It has over 9,000 positive recommendations from official government and clinical guidelines. However, it still remains relatively inaccessible in the United States, Europe and elsewhere, especially compared to the strength of evidence-based recommendations for its use. Acupuncture would benefit from robust implementation strategies, utilizing insights and approaches from implementation science. The clinical use of Botox for migraine suffered from weaker evidence of effectiveness and greater evidence of harm, but using a streamlined and robust implementation strategy, Allergan was able to achieve widespread implementation from when it began its efforts around 2010. Such a systematic approach that identifies and overcomes barriers to implementation for acupuncture would benefit millions of people who currently are offered less effective and more invasive treatments, contrary to the recommendations of clinical guidelines.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.62173312 and 61803348in part by the National Major Scientific Instruments Development Project under Grant No.61927807+3 种基金in part by the Program for the Innovative Talents of Higher Education Institutions of ShanxiShanxi Province Science Foundation for Excellent Youthsin part by the Shanxi"1331 Project"Key Subjects Construction(1331KSC)in part by Graduate Innovation Project of Shanxi Province under Grant No.2021Y617。
文摘This article investigates a multi-circular path-following formation control with reinforced transient profiles for nonholonomic vehicles connected by a digraph.A multi-circular formation controller endowed with the feature of spatial-temporal decoupling is devised for a group of vehicles guided by a virtual leader evolving along an implicit path,which allows for a circumnavigation on multiple circles with an anticipant angular spacing.In addition,notice that it typically imposes a stringent time constraint on time-sensitive enclosing scenarios,hence an improved prescribed performance control(IPPC)using novel tighter behavior boundaries is presented to enhance transient capabilities with an ensured appointed-time convergence free from any overshoots.The significant merits are that coordinated circumnavigation along different circles can be realized via executing geometric and dynamic assignments independently with modified transient profiles.Furthermore,all variables existing in the entire system are analyzed to be convergent.Simulation and experimental results are provided to validate the utility of suggested solution.
文摘Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.
基金This work was supported by Guizhou Provincial Basic Research Program(Natural Science),Grant Number Qiankehejichu-ZK[2021]YB133Guizhou Provincial Scientific and Technological Program,Grant Number Qiankehehoubuzhu[2020]3001National Natural Science Foundation of China-Guizhou Provincial People’s Government Karst Science Research Centre(U1612442).
文摘The contents of carbon(C),nitrogen(N),and phosphorus(P)in soil-microorganisms-plant significantly affect tea quality by altering the main quality components of tea,such as tea polyphenols,amino acids,and caffeine.However,few studies have quantified the effects of these factors on the main quality components of tea.The study aimed to explore the interactions of C,N,and P in soil-microorganisms-plants and the effects of these factors on the main quality components of tea by using the path analysis method.The results indicated that(1)The contents of C,N,and P in soil,microorganisms,and tea plants were highly correlated and collinear,and showed significant correlations with the main quality components of tea.(2)Optimal regression equations were established to esti-mate tea polyphenol,amino acid,catechin,caffeine,and water extract content based on C,N,and P contents in soil,microorganisms,and tea plants(R^(2)=0.923,0.726,0.954,0.848,and 0.883,respectively).(3)Pathway analysis showed that microbial biomass phosphorus(MBP),root phosphorus,branch nitrogen,and microbial biomass carbon(MBC)were the largest direct impact factors on tea polyphenol,catechin,water extracts,amino acid,and caffeine content,respectively.Leaf carbon,root phosphorus,and leaf nitrogen were the largest indirect impact factors on tea polyphenol,catechin,and water extract content,respectively.Leaf carbon indirectly affected tea polyphenol content mainly by altering MBP content.Root phosphorus indirectly affected catechin content mainly by altering soil organic carbon content.Leaf nitrogen indirectly affected water extract content mainly by altering branch nitrogen content.The research results provide the scientific basis for reasonable fertilization in tea gardens and tea quality improvement.
基金supported by the National Natural Science Foundation of China under Grant No.62001199Fujian Province Nature Science Foundation under Grant No.2023J01925.
文摘In the domain of autonomous industrial manipulators,precise positioning and appropriate posture selection in path planning are pivotal for tasks involving obstacle avoidance,such as handling,heat sealing,and stacking.While Multi-Degree-of-Freedom(MDOF)manipulators offer kinematic redundancy,aiding in the derivation of optimal inverse kinematic solutions to meet position and posture requisites,their path planning entails intricate multiobjective optimization,encompassing path,posture,and joint motion optimization.Achieving satisfactory results in practical scenarios remains challenging.In response,this study introduces a novel Reverse Path Planning(RPP)methodology tailored for industrial manipulators.The approach commences by conceptualizing the manipulator’s end-effector as an agent within a reinforcement learning(RL)framework,wherein the state space,action set,and reward function are precisely defined to expedite the search for an initial collision-free path.To enhance convergence speed,the Q-learning algorithm in RL is augmented with Dyna-Q.Additionally,we formulate the cylindrical bounding box of the manipulator based on its Denavit-Hartenberg(DH)parameters and propose a swift collision detection technique.Furthermore,the motion performance of the end-effector is refined through a bidirectional search,and joint weighting coefficients are introduced to mitigate motion in high-power joints.The efficacy of the proposed RPP methodology is rigorously examined through extensive simulations conducted on a six-degree-of-freedom(6-DOF)manipulator encountering two distinct obstacle configurations and target positions.Experimental results substantiate that the RPP method adeptly orchestrates the computation of the shortest collision-free path while adhering to specific posture constraints at the target point.Moreover,itminimizes both posture angle deviations and joint motion,showcasing its prowess in enhancing the operational performance of MDOF industrial manipulators.
基金partly supported by Program for the National Natural Science Foundation of China (62373052, U1913203, 61903034)Youth Talent Promotion Project of China Association for Science and TechnologyBeijing Institute of Technology Research Fund Program for Young Scholars。
文摘Due to its flexibility and complementarity, the multiUAVs system is well adapted to complex and cramped workspaces, with great application potential in the search and rescue(SAR) and indoor goods delivery fields. However, safe and effective path planning of multiple unmanned aerial vehicles(UAVs)in the cramped environment is always challenging: conflicts with each other are frequent because of high-density flight paths, collision probability increases because of space constraints, and the search space increases significantly, including time scale, 3D scale and model scale. Thus, this paper proposes a hierarchical collaborative planning framework with a conflict avoidance module at the high level and a path generation module at the low level. The enhanced conflict-base search(ECBS) in our framework is improved to handle the conflicts in the global path planning and avoid the occurrence of local deadlock. And both the collision and kinematic models of UAVs are considered to improve path smoothness and flight safety. Moreover, we specifically designed and published the cramped environment test set containing various unique obstacles to evaluating our framework performance thoroughly. Experiments are carried out relying on Rviz, with multiple flight missions: random, opposite, and staggered, which showed that the proposed method can generate smooth cooperative paths without conflict for at least 60 UAVs in a few minutes.The benchmark and source code are released in https://github.com/inin-xingtian/multi-UAVs-path-planner.
基金supported in part by National Natural Science Foundation of China under Grants 62122069, 62071431, 62072490 and 62301490in part by Science and Technology Development Fund of Macao SAR, China under Grant 0158/2022/A+2 种基金in part by the Guangdong Basic and Applied Basic Research Foundation (2022A1515011287)in part by MYRG202000107-IOTSCin part by FDCT SKL-IOTSC (UM)-2021-2023
文摘With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated from monitoring and long-distance transmission places a heavy burden on sensor nodes with the limited battery power.For this,we investigate an unmanned aerial vehicles assisted mobile wireless sensor network(UAV-assisted WSN)to prolong the network lifetime in this paper.Specifically,we use UAVs to assist the WSN in collecting data.In the current UAV-assisted WSN,the clustering and routing schemes are determined sequentially.However,such a separate consideration might not maximize the lifetime of the whole WSN due to the mutual coupling of clustering and routing.To efficiently prolong the lifetime of the WSN,we propose an integrated clustering and routing scheme that jointly optimizes the clustering and routing together.In the whole network space,it is intractable to efficiently obtain the optimal integrated clustering and routing scheme.Therefore,we propose the Monte-Las search strategy based on Monte Carlo and Las Vegas ideas,which can generate the chain matrix to guide the algorithm to find the solution faster.Unnecessary point-to-point collection leads to long collection paths,so a triangle optimization strategy is then proposed that finds a compromise path to shorten the collection path based on the geometric distribution and energy of sensor nodes.To avoid the coverage hole caused by the death of sensor nodes,the deployment of mobile sensor nodes and the preventive mechanism design are indispensable.An emergency data transmission mechanism is further proposed to reduce the latency of collecting the latency-sensitive data due to the absence of UAVs.Compared with the existing schemes,the proposed scheme can prolong the lifetime of the UAVassisted WSN at least by 360%,and shorten the collection path of UAVs by 56.24%.
基金supported by National Natural Science Foundation of China(71904006)Henan Province Key R&D Special Project(231111322200)+1 种基金the Science and Technology Research Plan of Henan Province(232102320043,232102320232,232102320046)the Natural Science Foundation of Henan(232300420317,232300420314).
文摘Reducing casualties and property losses through effective evacuation route planning has been a key focus for researchers in recent years.As part of this effort,an enhanced sparrow search algorithm(MSSA)was proposed.Firstly,the Golden Sine algorithm and a nonlinear weight factor optimization strategy were added in the discoverer position update stage of the SSA algorithm.Secondly,the Cauchy-Gaussian perturbation was applied to the optimal position of the SSA algorithm to improve its ability to jump out of local optima.Finally,the local search mechanism based on the mountain climbing method was incorporated into the local search stage of the SSA algorithm,improving its local search ability.To evaluate the effectiveness of the proposed algorithm,the Whale Algorithm,Gray Wolf Algorithm,Improved Gray Wolf Algorithm,Sparrow Search Algorithm,and MSSA Algorithm were employed to solve various test functions.The accuracy and convergence speed of each algorithm were then compared and analyzed.The results indicate that the MSSA algorithm has superior solving ability and stability compared to other algorithms.To further validate the enhanced algorithm’s capabilities for path planning,evacuation experiments were conducted using different maps featuring various obstacle types.Additionally,a multi-exit evacuation scenario was constructed according to the actual building environment of a teaching building.Both the sparrow search algorithm and MSSA algorithm were employed in the simulation experiment for multiexit evacuation path planning.The findings demonstrate that the MSSA algorithm outperforms the comparison algorithm,showcasing its greater advantages and higher application potential.
基金supported by the National Natural Science Foundation of China (61903036, 61822304)Shanghai Municipal Science and Technology Major Project (2021SHZDZX0100)。
文摘Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm is proposed for the urban rescue search or military search in outdoor environment.Due to flexible control of small UAVs, it can be considered that all UAVs fly at the same altitude, that is, they perform search tasks on a two-dimensional plane. Based on the agents’ motion characteristics and environmental information, a mathematical model of CCPP problem is established. The minimum time for UAVs to complete the CCPP is the objective function, and complete coverage constraint, no-fly constraint, collision avoidance constraint, and communication constraint are considered. Four motion strategies and two communication strategies are designed. Then a distributed CCPP algorithm is designed based on hybrid strategies. Simulation results compared with patternbased genetic algorithm(PBGA) and random search method show that the proposed method has stronger real-time performance and better scalability and can complete the complete CCPP task more efficiently and stably.
基金supported by the Natural Science Basic Research Prog ram of Shaanxi(2022JQ-593)。
文摘To address the shortcomings of single-step decision making in the existing deep reinforcement learning based unmanned aerial vehicle(UAV)real-time path planning problem,a real-time UAV path planning algorithm based on long shortterm memory(RPP-LSTM)network is proposed,which combines the memory characteristics of recurrent neural network(RNN)and the deep reinforcement learning algorithm.LSTM networks are used in this algorithm as Q-value networks for the deep Q network(DQN)algorithm,which makes the decision of the Q-value network has some memory.Thanks to LSTM network,the Q-value network can use the previous environmental information and action information which effectively avoids the problem of single-step decision considering only the current environment.Besides,the algorithm proposes a hierarchical reward and punishment function for the specific problem of UAV real-time path planning,so that the UAV can more reasonably perform path planning.Simulation verification shows that compared with the traditional feed-forward neural network(FNN)based UAV autonomous path planning algorithm,the RPP-LSTM proposed in this paper can adapt to more complex environments and has significantly improved robustness and accuracy when performing UAV real-time path planning.
基金the National Natural Science Foundation of China(Grant No.42274119)the Liaoning Revitalization Talents Program(Grant No.XLYC2002082)+1 种基金National Key Research and Development Plan Key Special Projects of Science and Technology Military Civil Integration(Grant No.2022YFF1400500)the Key Project of Science and Technology Commission of the Central Military Commission.
文摘This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapidly-exploring Random Trees*(Q-RRT*)algorithm.A cost inequality relationship between an ancestor and its descendants was derived,and the ancestors were filtered accordingly.Secondly,the underwater gravity-aided navigation path planning system was designed based on the DSFS algorithm,taking into account the fitness,safety,and asymptotic optimality of the routes,according to the gravity suitability distribution of the navigation space.Finally,experimental comparisons of the computing performance of the ChooseParent procedure,the Rewire procedure,and the combination of the two procedures for Q-RRT*and DSFS were conducted under the same planning environment and parameter conditions,respectively.The results showed that the computational efficiency of the DSFS algorithm was improved by about 1.2 times compared with the Q-RRT*algorithm while ensuring correct computational results.
基金the financial support from the National Natural Science Foundation of China(Grant Nos.51839003 and 42207221).
文摘Surrounding rocks at different locations are generally subjected to different stress paths during the process of deep hard rock excavation.In this study,to reveal the mechanical parameters of deep surrounding rock under different stress paths,a new cyclic loading and unloading test method for controlled true triaxial loading and unloading and principal stress direction interchange was proposed,and the evolution of mechanical parameters of Shuangjiangkou granite under different stress paths was studied,including the deformation modulus,elastic deformation increment ratios,fracture degree,cohesion and internal friction angle.Additionally,stress path coefficient was defined to characterize different stress paths,and the functional relationships among the stress path coefficient,rock fracture degree difference coefficient,cohesion and internal friction angle were obtained.The results show that during the true triaxial cyclic loading and unloading process,the deformation modulus and cohesion gradually decrease,while the internal friction angle gradually increases with increasing equivalent crack strain.The stress path coefficient is exponentially related to the rock fracture degree difference coefficient.As the stress path coefficient increases,the degrees of cohesion weakening and internal friction angle strengthening decrease linearly.During cyclic loading and unloading under true triaxial principal stress direction interchange,the direction of crack development changes,and the deformation modulus increases,while the cohesion and internal friction angle decrease slightly,indicating that the principal stress direction interchange has a strengthening effect on the surrounding rocks.Finally,the influences of the principal stress interchange direction on the stabilities of deep engineering excavation projects are discussed.
