This paper begins with a discussion of the trust issues that agricultural supply chain finance faces.It then examines the constraints of using blockchain technology to enhance trust in agricultural supply chain financ...This paper begins with a discussion of the trust issues that agricultural supply chain finance faces.It then examines the constraints of using blockchain technology to enhance trust in agricultural supply chain finance in accordance with the technological and institutional logic of combining blockchain with supply chains.This study then proposes the creation of an agricultural“blockchain+supply chain”information service platform and a financing trust mechanism that can effectively ensure the authenticity of the initial information input on the blockchain,consistency between on-chain transaction data and off-chain physical transactions,the controllability of risks in the set up and execution of smart contracts,and the removal of information constraints,resource allocation constraints,and institutional constraints in the agricultural supply chain financing.This aims to improve the efficiency of financing in agricultural supply chains and contribute to the industrial development of rural areas and rural revitalization.展开更多
Traditional deconvolution methods based on single-channel inversion do not consider the spatial structural relation between channels,and hence,they yield high-resolution results with the existing transverse inconsiste...Traditional deconvolution methods based on single-channel inversion do not consider the spatial structural relation between channels,and hence,they yield high-resolution results with the existing transverse inconsistency or discontinuity.Therefore,in this study,the local dip angle was used to obtain the structural information and construct the spatial structurally constraint operator.This operator is then introduced into multichannel deconvolution as a regularization operator to improve the resolution and maintain the transverse continuity of seismic data.Model tests and actual seismic data processing have demonstrated the effectiveness and practicability of this method.展开更多
Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become...Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become a significant instrument for propelling the energy revolution and ensuring energy security.Under increasingly stringent carbon emission constraints,how to achieve multi-dimensional improvements in energy utilization efficiency,renewable energy accommodation levels,and system economics-through the intelligent coupling of diverse energy carriers such as electricity,heat,natural gas,and hydrogen,and the effective application of market-based instruments like carbon trading and demand response-constitutes a critical scientific and engineering challenge demanding urgent solutions.展开更多
As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods ge...As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.展开更多
Recent experiments have found that a liquid crystal elastomer(LCE)rod supported in the middle can rotate continuously under horizontal illumination due to the combined impacts of gravity and light-fueled lateral bend-...Recent experiments have found that a liquid crystal elastomer(LCE)rod supported in the middle can rotate continuously under horizontal illumination due to the combined impacts of gravity and light-fueled lateral bend-ing deformation.Similar to traditional gravity-driven systems,it is constrained by the direction of gravity and cannot be applied in microgravity environments.This study introduces a lateral constraint to a liquid crystal elastomer rod system,enabling self-rotation under lighting from any direction,including horizontal and vertical illumination.Through theoretical modeling,the results indicate that the system can steadily rotate under the combined impacts of lateral forces and vertical illumination.Factors like thermal energy flux,thermal conduc-tivity coefficient,the LCE rod length,contraction coefficient,and friction coefficient affect the angular velocity of the self-rotation.The numerical computations align closely with the experimental data.Our proposed steadily self-rotating system features a simple structure with constant self-rotation.It operates independently of gravity direction,making it an excellent choice for special environments,such as the microgravity conditions on the Moon.The lateral constraint strategy presented in this study offers a general approach to expanding the applica-tions of gravity-driven self-sustained motion,with promising potential,especially in microgravity settings,where its versatility under varying lighting conditions could yield valuable insights.展开更多
This study aimed to identify and compensate for the geometric errors of the double swiveling axes in a five-axis computer numerical control(CNC)machining center.Hence,a three-dimensional coordinate calculation algorit...This study aimed to identify and compensate for the geometric errors of the double swiveling axes in a five-axis computer numerical control(CNC)machining center.Hence,a three-dimensional coordinate calculation algorithm for a measured point with additional rotational rigid body motion constraints is proposed.The motion constraints of the rotational rigid body were analyzed,and a mathematical model of the measured point algorithm in the swiveling axes was established.The Levenberg-Marquard method was used to solve the nonlinear superstatically determined equations.The spatial coordinate error was used to separate the spatial deviation of the measured point.An identification model of the position-independent and position-dependent geometric errors was established.The three-dimensional coordinate-solving algorithm of the measured point in the swiveling axis and geometric error identification method based on the Monte Carlo method were analyzed numerically.Geometric error measurement and cutting experiments were performed on a VMC25100U five-axis machining center,which integrated two swiveling axes.Geometric errors of the A-and B-axes were identified and measured experimentally.The angular positioning errors before and after compensation were measured using a laser interferometer,which verified the effectiveness of the proposed algorithm.A cutting experiment of a round table part was performed.The shape and position accuracy of the processed part before and after compensation were detected using a coordinate measuring machine.It verified that the geometric error of the swiveling axis was effectively compensated by the algorithm proposed herein.展开更多
Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the nume...Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the numerical model outputs and historical observations,which can partly predict seasonal precipitation.However,solving a nonlinear problem through linear regression is significantly biased.This study implements a nonlinear optimization of an existing observational constrained correction model using a Light Gradient Boosting Machine(LightGBM)machine learning algorithm based on output from the Beijing National Climate Center Climate System Model(BCC-CSM)and station observations to improve the prediction of summer precipitation in China.The model was trained using a rolling approach,and LightGBM outperformed Linear Regression(LR),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost).Using parameter tuning to optimize the machine learning model and predict future summer precipitation using eight different predictors in BCC-CSM,the mean Anomaly Correlation Coefficient(ACC)score in the 2019–22 summer precipitation predictions was 0.17,and the mean Prediction Score(PS)reached 74.The PS score was improved by 7.87%and 6.63%compared with the BCC-CSM and the linear observational constraint approach,respectively.The observational constraint correction prediction strategy with LightGBM significantly and stably improved the prediction of summer precipitation in China compared to the previous linear observational constraint solution,providing a reference for flood control and drought relief during the flood season(summer)in China.展开更多
This study examines the moderating role of entrepreneurs’creative cognitive styles in the relationship between resource constraints and bricolage.Drawing on insights from cognitive psychology and entrepreneurial rese...This study examines the moderating role of entrepreneurs’creative cognitive styles in the relationship between resource constraints and bricolage.Drawing on insights from cognitive psychology and entrepreneurial research,we explore how divergent and convergent thinking influence the extent to which entrepreneurs engage in bricolage under resource limitations.Bricolage refers to the creative recombination of available resources to address challenges and seize opportunities,a process often adopted by firms facing financial or knowledge constraints.Yet,individual cognitive differences may determine how effectively entrepreneurs can employ bricolage as a strategic response to scarcity.We propose that divergent thinking—the capacity to generate multiple creative solutions and identify novel resource combinations—strengthens the positive association between resource constraints and bricolage.In contrast,convergent thinking,which emphasizes logical analysis and the pursuit of a single optimal solution,weakens this association.To test these propositions,we collected survey data from 183 entrepreneurs in the United States and employed moderated regression analyses to examine the interactions among cognitive styles,resource constraints,and bricolage behaviors.Our findings reveal that divergent thinking significantly enhances the effect of both financial and knowledge constraints on bricolage,enabling entrepreneurs to creatively leverage limited resources.Conversely,convergent thinking appears to diminish the likelihood of engaging in bricolage when resources are scarce.These results highlight the importance of individual cognitive styles in shaping strategic responses to resource scarcity and contribute to a more nuanced understanding of entrepreneurial bricolage.The study offers practical implications for firms operating in resource-constrained environments by suggesting that enhancing divergent thinking abilities may facilitate more effective resource recombination.Future research should investigate additional cognitive factors and employ longitudinal designs to capture the dynamic nature of entrepreneurial decision-making.These insights open new avenues for further innovative entrepreneurial practices.展开更多
Constraint satisfaction problems(CSPs)are a class of problems that are ubiquitous in science and engineering.They feature a collection of constraints specified over subsets of variables.A CSP can be solved either dire...Constraint satisfaction problems(CSPs)are a class of problems that are ubiquitous in science and engineering.They feature a collection of constraints specified over subsets of variables.A CSP can be solved either directly or by reducing it to other problems.This paper introduces the Julia ecosystem for solving and analyzing CSPs with a focus on the programming practices.We introduce some important CSPs and show how these problems are reduced to each other.We also show how to transform CSPs into tensor networks,how to optimize the tensor network contraction orders,and how to extract the solution space properties by contracting the tensor networks with generic element types.Examples are given,which include computing the entropy constant,analyzing the overlap gap property,and the reduction between CSPs.展开更多
Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system rob...Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system robustness and inaccurate position estimation.In this study,we propose a YGC-SLAM for indoor dynamic environments based on the ORB-SLAM2 framework combined with semantic and geometric constraints to improve the positioning accuracy and robustness of the system.Methods First,the recognition accuracy of YOLOv5 was improved by introducing the convolution block attention model and the improved EIOU loss function,whereby the prediction frame converges quickly for better detection.The improved YOLOv5 was then added to the tracking thread for dynamic target detection to eliminate dynamic points.Subsequently,multi-view geometric constraints were used for re-judging to further eliminate dynamic points while enabling more useful feature points to be retained and preventing the semantic approach from over-eliminating feature points,causing a failure of map building.The K-means clustering algorithm was used to accelerate this process and quickly calculate and determine the motion state of each cluster of pixel points.Finally,a strategy for drawing keyframes with de-redundancy was implemented to construct a clear 3D dense static point-cloud map.Results Through testing on TUM dataset and a real environment,the experimental results show that our algorithm reduces the absolute trajectory error by 98.22%and the relative trajectory error by 97.98%compared with the original ORBSLAM2,which is more accurate and has better real-time performance than similar algorithms,such as DynaSLAM and DS-SLAM.Conclusions The YGC-SLAM proposed in this study can effectively eliminate the adverse effects of dynamic objects,and the system can better complete positioning and map building tasks in complex environments.展开更多
Acoustic waves in the pseudo-triaxial experiment system experience refraction phenomena.The conventional assumption that acoustic waves propagate along a straight line in traditional methods can lead to significant er...Acoustic waves in the pseudo-triaxial experiment system experience refraction phenomena.The conventional assumption that acoustic waves propagate along a straight line in traditional methods can lead to significant errors in localization results.To the end,this paper presents a method for locating acoustic emission(AE)sources in pseudo-triaxial experiments using shortest paths and orthogonal constraints.The approach consists of three main steps:(1)establishing control equations for refraction paths from AE sources to sensor locations;(2)calculating refraction point locations using the shortest travel principle and orthogonal constraints;(3)determining source coordinates using Taylor's first-order expansion.The results from laboratory AE experiments demonstrate that the average localization accuracy of the new method is only 6.5 mm,which is 66%more precise than the accuracy(19.4 mm)of the traditional method.Furthermore,simulation results indicate that the new method is not affected by the refraction ratio of the media and maintains the highest positioning accuracy across various arrival and velocity errors.展开更多
To investigate the influence of different longitudinal constraint systems on the longitudinal displacement at the girder ends of a three-tower suspension bridge,this study takes the Cangrong Xunjiang Bridge as an engi...To investigate the influence of different longitudinal constraint systems on the longitudinal displacement at the girder ends of a three-tower suspension bridge,this study takes the Cangrong Xunjiang Bridge as an engineering case for finite element analysis.This bridge employs an unprecedented tower-girder constraintmethod,with all vertical supports placed at the transition piers at both ends.This paper aims to study the characteristics of longitudinal displacement control at the girder ends under this novel structure,relying on finite element(FE)analysis.Initially,based on the Weigh In Motion(WIM)data,a random vehicle load model is generated and applied to the finite elementmodel.Several longitudinal constraint systems are proposed,and their effects on the structural response of the bridge are compared.The most reasonable system,balancing girder-end displacement and transitional pier stress,is selected.Subsequently,the study examines the impact of different viscous damper parameters on key structural response indicators,including cumulative longitudinal displacement at the girder ends,maximum longitudinal displacement at the girder ends,cumulative longitudinal displacement at the pier tops,maximum longitudinal displacement at the pier tops,longitudinal acceleration at the pier tops,and maximum bending moment at the pier bottoms.Finally,the coefficient of variation(CV)-TOPSIS method is used to optimize the viscous damper parameters for multiple objectives.The results show that adding viscous dampers at the side towers,in addition to the existing longitudinal limit bearings at the central tower,can most effectively reduce the response of structural indicators.The changes in these indicators are not entirely consistent with variations in damping coefficient and velocity exponent.The damper parameters significantly influence cumulative longitudinal displacement at the girder ends,cumulative longitudinal displacement at the pier tops,and maximum bending moments at the pier bottoms.The optimal damper parameters are found to be a damping coefficient of 5000 kN/(m/s)0.2 and a velocity exponent of 0.2.展开更多
This paper is concerned with the construction of two types of generalized Heisenberg supermagnet model with the constraint S^(3)=S,including the inhomogeneous Heisenberg supermagnet model in(1+1)dimensions and the(2+1...This paper is concerned with the construction of two types of generalized Heisenberg supermagnet model with the constraint S^(3)=S,including the inhomogeneous Heisenberg supermagnet model in(1+1)dimensions and the(2+1)-dimensional Heisenberg supermagnet model.Furthermore,by means of the gauge transformation,we investigate the gauge equivalent counterparts,which are the(1+1)-dimensional inhomogeneous nonlinear Schrodinger equation and the(2+1)-dimensional super nonlinear Schrodinger equation,respectively.展开更多
The rapid development of digital financial inclusion is profoundly changing the financing environment for small and medium-sized enterprises(SMEs).As an important driver of economic growth and innovation,SMEs account ...The rapid development of digital financial inclusion is profoundly changing the financing environment for small and medium-sized enterprises(SMEs).As an important driver of economic growth and innovation,SMEs account for a significant share of employment and GDP globally.However,the traditional bank credit model has long failed to effectively meet the financing needs of SMEs due to issues such as information asymmetry,high cost,and difficulty in risk assessment,resulting in serious financing constraints.Digital financial inclusion,through technological innovation and big data analysis,has significantly reduced credit costs,alleviated information asymmetry,and provided SMEs with more flexible and efficient financing channels.Research shows that digital financial inclusion can not only ease the financing constraints of SMEs,but also promote their innovation and growth,providing important support for building a more inclusive and sustainable financial ecosystem.展开更多
In air combat,one effective way to counter an incoming missile attacking an aircraft is to launch a defense missile compared with traditional passive defense strategies such as decoy and electronic countermeasures.To ...In air combat,one effective way to counter an incoming missile attacking an aircraft is to launch a defense missile compared with traditional passive defense strategies such as decoy and electronic countermeasures.To address this issue,this paper proposes a three-body cooperative active defense guidance law with overload constraints from the perspective of a small speed ratio.First,a cooperative guidance-oriented model for active defense is established and linearized to provide a foundation for the design of the guidance law.Then,the essential quantity known as Zero-Effort-Miss(ZEM)is analyzed during the engagement process.In order to minimize the influence of inaccurate estimates of remaining flight time in the ZEM,the concept of Zero-Effort-Velocity(ZEV)is introduced.Subsequently,utilizing the sliding mode control method,the guidance law is designed by selecting the ZEM and ZEV as sliding mode surfaces,combined with the fast power reaching law,and its finite-time stability is analyzed using the Lyapunov method.Furthermore,to quantitatively evaluate the performance of the proposed active defense guidance law,the interception rendezvous angle index is introduced.The proposed active defense guidance law considers integrating information from the incoming missile,aircraft,and defense missile with fewer simplifications and assumptions,and ensures that the aircraft is effectively protected with less overload required for the defense missile.Finally,simulation experiments demonstrate the effectiveness and adaptability of the proposed active defense guidance law.展开更多
Dear Editor,The distributed constraint optimization problems(DCOPs) [1]-[3]provide an efficient model for solving the cooperative problems of multi-agent systems, which has been successfully applied to model the real-...Dear Editor,The distributed constraint optimization problems(DCOPs) [1]-[3]provide an efficient model for solving the cooperative problems of multi-agent systems, which has been successfully applied to model the real-world problems like the distributed scheduling [4], sensor network management [5], [6], multi-robot coordination [7], and smart grid [8]. However, DCOPs were not well suited to solve the problems with continuous variables and constraint cost in functional form, such as the target tracking sensor orientation [9], the air and ground cooperative surveillance [10], and the sensor network coverage [11].展开更多
Learning from demonstration is widely regarded as a promising paradigm for robots to acquire diverse skills.Other than the artificial learning from observation-action pairs for machines,humans can learn to imitate in ...Learning from demonstration is widely regarded as a promising paradigm for robots to acquire diverse skills.Other than the artificial learning from observation-action pairs for machines,humans can learn to imitate in a more versatile and effective manner:acquiring skills through mere“observation”.Video to Command task is widely perceived as a promising approach for task-based learning,which yet faces two key challenges:(1)High redundancy and low frame rate of fine-grained action sequences make it difficult to manipulate objects robustly and accurately.(2)Video to Command models often prioritize accuracy and richness of output commands over physical capabilities,leading to impractical or unsafe instructions for robots.This article presents a novel Video to Command framework that employs multiple data associations and physical constraints.First,we introduce an object-level appearancecontrasting multiple data association strategy to effectively associate manipulated objects in visually complex environments,capturing dynamic changes in video content.Then,we propose a multi-task Video to Command model that utilizes object-level video content changes to compile expert demonstrations into manipulation commands.Finally,a multi-task hybrid loss function is proposed to train a Video to Command model that adheres to the constraints of the physical world and manipulation tasks.Our method achieved over 10%on BLEU_N,METEOR,ROUGE_L,and CIDEr compared to the up-to-date methods.The dual-arm robot prototype was established to demonstrate the whole process of learning from an expert demonstration of multiple skills and then executing the tasks by a robot.展开更多
In the existing impact time control guidance (ITCG) laws for moving-targets, the effects of time-varying velocity caused by aerodynamics and gravity cannot be effectively con-sidered. Therefore, an ITCG with field-of-...In the existing impact time control guidance (ITCG) laws for moving-targets, the effects of time-varying velocity caused by aerodynamics and gravity cannot be effectively con-sidered. Therefore, an ITCG with field-of-view (FOV) constraints based on biased proportional navigation guidance (PNG) is developed in this paper. The remaining flight time (time-to-go) estimation method is derived considering aerodynamic force and gravity. The number of differential equations is reduced and the integration step is increased by changing the integral variable, which makes it possible to obtain time-to-go through integration. An impact time controller with FOV constraints is proposed by analyzing the influence of the biased term on time-to-go and FOV constraint. Then, numerical simulations are performed to verify the correctness and superiority of the method.展开更多
This paper investigates the secure communication between legitimate users in the presence of eavesdroppers, where the Intelligent Reflective Surface-Unmanned Aerial Vehicle (IRS-UAV) and Buffer-Aided (BA) relaying tec...This paper investigates the secure communication between legitimate users in the presence of eavesdroppers, where the Intelligent Reflective Surface-Unmanned Aerial Vehicle (IRS-UAV) and Buffer-Aided (BA) relaying techniques are utilized to enhance secrecy performance. By jointly optimizing the link selection strategy, the UAV position, and the reflection coefficient of the IRS, we aim to maximize the long-term average secrecy rate. Specifically, we propose a novel buffer in/out stabilization scheme based on the Lyapunov framework, which transforms the long-term average secrecy rate maximization problem into two per-slot drift-plus-penalty minimization problems with different link selection factors. The hybrid Particle Swarm Optimization-Artificial Fish Swarm Algorithm (PSO-AFSA) is adopted to optimize the UAV position, and the IRS reflection coefficient optimization problem is solved by iterative optimization in which auxiliary variables and standard convex optimization algorithms are introduced. Finally, the delay constraint is set to ensure the timeliness of information packets. Simulation results demonstrate that our proposed scheme outperforms the comparison schemes in terms of average secrecy rate. Specifically, the addition of BA improves the average secrecy rate by 1.37 bps/Hz, and the continued optimizations of IRS reflection coefficients and UAV positions improve the average secrecy rate by 2.46 bps/Hz and 3.75 bps/Hz, respectively.展开更多
As an important tool to achieve sustainable economic and environmental development,green finance can effectively alleviate the financing constraints of small and medium-sized enterprises(SMEs),especially in promoting ...As an important tool to achieve sustainable economic and environmental development,green finance can effectively alleviate the financing constraints of small and medium-sized enterprises(SMEs),especially in promoting green transformation plays a key role.SMEs play an important role in economic growth,innovation,and job creation,but due to a lack of collateral,imperfect credit history,and opaque financial information,they face great obstacles in the financing process,especially in the early capital investment required for green transformation.Green finance,through innovative financial instruments such as green credit and green bonds,provides new financing channels for SMEs,helping them reduce financing costs,optimize financing structure,and promote their green transformation and sustainable development.This paper analyzes the current situation and root causes of SMEs’financing dilemma from the perspective of green finance,and probes into the influence of green finance policies on financing behavior.展开更多
基金an initial outcome of the Research on the Trust Mechanism of Agricultural Supply Chain Financing in the Context of “Blockchain+Supply Chain” Integrated Governance (Project No:20AGL021)a key project under the National Social Science Fund of China (NSSFC)+3 种基金the Research on the Trust Mechanism of Online Bank Lending System Based on Online Social Capital of Long-tail Rural Households (Project No:19BGL155)a project under the NSSFCthe Research on the Cost Formation Mechanism of Data Factor Transactions and the Design of Transaction Mechanism (Project No:23CJY068)a youth project under the NSSFC
文摘This paper begins with a discussion of the trust issues that agricultural supply chain finance faces.It then examines the constraints of using blockchain technology to enhance trust in agricultural supply chain finance in accordance with the technological and institutional logic of combining blockchain with supply chains.This study then proposes the creation of an agricultural“blockchain+supply chain”information service platform and a financing trust mechanism that can effectively ensure the authenticity of the initial information input on the blockchain,consistency between on-chain transaction data and off-chain physical transactions,the controllability of risks in the set up and execution of smart contracts,and the removal of information constraints,resource allocation constraints,and institutional constraints in the agricultural supply chain financing.This aims to improve the efficiency of financing in agricultural supply chains and contribute to the industrial development of rural areas and rural revitalization.
基金supported by the basic and forward-looking project(No.2023YQX302)。
文摘Traditional deconvolution methods based on single-channel inversion do not consider the spatial structural relation between channels,and hence,they yield high-resolution results with the existing transverse inconsistency or discontinuity.Therefore,in this study,the local dip angle was used to obtain the structural information and construct the spatial structurally constraint operator.This operator is then introduced into multichannel deconvolution as a regularization operator to improve the resolution and maintain the transverse continuity of seismic data.Model tests and actual seismic data processing have demonstrated the effectiveness and practicability of this method.
文摘Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become a significant instrument for propelling the energy revolution and ensuring energy security.Under increasingly stringent carbon emission constraints,how to achieve multi-dimensional improvements in energy utilization efficiency,renewable energy accommodation levels,and system economics-through the intelligent coupling of diverse energy carriers such as electricity,heat,natural gas,and hydrogen,and the effective application of market-based instruments like carbon trading and demand response-constitutes a critical scientific and engineering challenge demanding urgent solutions.
基金National Natural Science Foundation of China(Nos.42301473,42271424,42171397)Chinese Postdoctoral Innovation Talents Support Program(No.BX20230299)+2 种基金China Postdoctoral Science Foundation(No.2023M742884)Natural Science Foundation of Sichuan Province(Nos.24NSFSC2264,2025ZNSFSC0322)Key Research and Development Project of Sichuan Province(No.24ZDYF0633).
文摘As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.
基金supported by the University Natural Science Research Project of Anhui Province(Grant Nos.2022AH040042 and 2022AH020029)the National Natural Science Foundation of China(Grant No.12172001)+1 种基金Anhui Provincial Natural Science Foundation(Grant No.2208085Y01)the Housing and Urban-Rural Development Science and Technology Project of Anhui Province(Grant No.2022-YF069).
文摘Recent experiments have found that a liquid crystal elastomer(LCE)rod supported in the middle can rotate continuously under horizontal illumination due to the combined impacts of gravity and light-fueled lateral bend-ing deformation.Similar to traditional gravity-driven systems,it is constrained by the direction of gravity and cannot be applied in microgravity environments.This study introduces a lateral constraint to a liquid crystal elastomer rod system,enabling self-rotation under lighting from any direction,including horizontal and vertical illumination.Through theoretical modeling,the results indicate that the system can steadily rotate under the combined impacts of lateral forces and vertical illumination.Factors like thermal energy flux,thermal conduc-tivity coefficient,the LCE rod length,contraction coefficient,and friction coefficient affect the angular velocity of the self-rotation.The numerical computations align closely with the experimental data.Our proposed steadily self-rotating system features a simple structure with constant self-rotation.It operates independently of gravity direction,making it an excellent choice for special environments,such as the microgravity conditions on the Moon.The lateral constraint strategy presented in this study offers a general approach to expanding the applica-tions of gravity-driven self-sustained motion,with promising potential,especially in microgravity settings,where its versatility under varying lighting conditions could yield valuable insights.
基金Supported by Shanxi Provincial Natural Science Foundation(Grant No.2021JM010)The Youth Innovation Team of Shaanxi Universities.
文摘This study aimed to identify and compensate for the geometric errors of the double swiveling axes in a five-axis computer numerical control(CNC)machining center.Hence,a three-dimensional coordinate calculation algorithm for a measured point with additional rotational rigid body motion constraints is proposed.The motion constraints of the rotational rigid body were analyzed,and a mathematical model of the measured point algorithm in the swiveling axes was established.The Levenberg-Marquard method was used to solve the nonlinear superstatically determined equations.The spatial coordinate error was used to separate the spatial deviation of the measured point.An identification model of the position-independent and position-dependent geometric errors was established.The three-dimensional coordinate-solving algorithm of the measured point in the swiveling axis and geometric error identification method based on the Monte Carlo method were analyzed numerically.Geometric error measurement and cutting experiments were performed on a VMC25100U five-axis machining center,which integrated two swiveling axes.Geometric errors of the A-and B-axes were identified and measured experimentally.The angular positioning errors before and after compensation were measured using a laser interferometer,which verified the effectiveness of the proposed algorithm.A cutting experiment of a round table part was performed.The shape and position accuracy of the processed part before and after compensation were detected using a coordinate measuring machine.It verified that the geometric error of the swiveling axis was effectively compensated by the algorithm proposed herein.
基金jointly supported by the National Natural Science Foundation of China(Grant Nos.42122034,42075043,42330609)the Second Tibetan Plateau Scientific Expedition and Research program(2019QZKK0103)+2 种基金Key Talent Project in Gansu and Central Guidance Fund for Local Science and Technology Development Projects in Gansu(No.24ZYQA031)the Youth Innovation Promotion Association of Chinese Academy of Sciences(2021427)West Light Foundation of the Chinese Academy of Sciences(xbzg-zdsys-202215)。
文摘Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the numerical model outputs and historical observations,which can partly predict seasonal precipitation.However,solving a nonlinear problem through linear regression is significantly biased.This study implements a nonlinear optimization of an existing observational constrained correction model using a Light Gradient Boosting Machine(LightGBM)machine learning algorithm based on output from the Beijing National Climate Center Climate System Model(BCC-CSM)and station observations to improve the prediction of summer precipitation in China.The model was trained using a rolling approach,and LightGBM outperformed Linear Regression(LR),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost).Using parameter tuning to optimize the machine learning model and predict future summer precipitation using eight different predictors in BCC-CSM,the mean Anomaly Correlation Coefficient(ACC)score in the 2019–22 summer precipitation predictions was 0.17,and the mean Prediction Score(PS)reached 74.The PS score was improved by 7.87%and 6.63%compared with the BCC-CSM and the linear observational constraint approach,respectively.The observational constraint correction prediction strategy with LightGBM significantly and stably improved the prediction of summer precipitation in China compared to the previous linear observational constraint solution,providing a reference for flood control and drought relief during the flood season(summer)in China.
文摘This study examines the moderating role of entrepreneurs’creative cognitive styles in the relationship between resource constraints and bricolage.Drawing on insights from cognitive psychology and entrepreneurial research,we explore how divergent and convergent thinking influence the extent to which entrepreneurs engage in bricolage under resource limitations.Bricolage refers to the creative recombination of available resources to address challenges and seize opportunities,a process often adopted by firms facing financial or knowledge constraints.Yet,individual cognitive differences may determine how effectively entrepreneurs can employ bricolage as a strategic response to scarcity.We propose that divergent thinking—the capacity to generate multiple creative solutions and identify novel resource combinations—strengthens the positive association between resource constraints and bricolage.In contrast,convergent thinking,which emphasizes logical analysis and the pursuit of a single optimal solution,weakens this association.To test these propositions,we collected survey data from 183 entrepreneurs in the United States and employed moderated regression analyses to examine the interactions among cognitive styles,resource constraints,and bricolage behaviors.Our findings reveal that divergent thinking significantly enhances the effect of both financial and knowledge constraints on bricolage,enabling entrepreneurs to creatively leverage limited resources.Conversely,convergent thinking appears to diminish the likelihood of engaging in bricolage when resources are scarce.These results highlight the importance of individual cognitive styles in shaping strategic responses to resource scarcity and contribute to a more nuanced understanding of entrepreneurial bricolage.The study offers practical implications for firms operating in resource-constrained environments by suggesting that enhancing divergent thinking abilities may facilitate more effective resource recombination.Future research should investigate additional cognitive factors and employ longitudinal designs to capture the dynamic nature of entrepreneurial decision-making.These insights open new avenues for further innovative entrepreneurial practices.
基金funded by the National Key R&D Program of China(Grant No.2024YFE0102500)the National Natural Science Foundation of China(Grant No.12404568)+1 种基金the Guangzhou Municipal Science and Technology Project(Grant No.2023A03J00904)the Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area,China and the Undergraduate Research Project from HKUST(Guangzhou).
文摘Constraint satisfaction problems(CSPs)are a class of problems that are ubiquitous in science and engineering.They feature a collection of constraints specified over subsets of variables.A CSP can be solved either directly or by reducing it to other problems.This paper introduces the Julia ecosystem for solving and analyzing CSPs with a focus on the programming practices.We introduce some important CSPs and show how these problems are reduced to each other.We also show how to transform CSPs into tensor networks,how to optimize the tensor network contraction orders,and how to extract the solution space properties by contracting the tensor networks with generic element types.Examples are given,which include computing the entropy constant,analyzing the overlap gap property,and the reduction between CSPs.
基金Supported by Jiangsu Key R&D Program(BE2021622)Jiangsu Postgraduate Practice and Innovation Program(SJCX23_0395).
文摘Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system robustness and inaccurate position estimation.In this study,we propose a YGC-SLAM for indoor dynamic environments based on the ORB-SLAM2 framework combined with semantic and geometric constraints to improve the positioning accuracy and robustness of the system.Methods First,the recognition accuracy of YOLOv5 was improved by introducing the convolution block attention model and the improved EIOU loss function,whereby the prediction frame converges quickly for better detection.The improved YOLOv5 was then added to the tracking thread for dynamic target detection to eliminate dynamic points.Subsequently,multi-view geometric constraints were used for re-judging to further eliminate dynamic points while enabling more useful feature points to be retained and preventing the semantic approach from over-eliminating feature points,causing a failure of map building.The K-means clustering algorithm was used to accelerate this process and quickly calculate and determine the motion state of each cluster of pixel points.Finally,a strategy for drawing keyframes with de-redundancy was implemented to construct a clear 3D dense static point-cloud map.Results Through testing on TUM dataset and a real environment,the experimental results show that our algorithm reduces the absolute trajectory error by 98.22%and the relative trajectory error by 97.98%compared with the original ORBSLAM2,which is more accurate and has better real-time performance than similar algorithms,such as DynaSLAM and DS-SLAM.Conclusions The YGC-SLAM proposed in this study can effectively eliminate the adverse effects of dynamic objects,and the system can better complete positioning and map building tasks in complex environments.
基金the financial support provided by the National Key Research and Development Program for Young Scientists(Grant No.2021YFC2900400)the National Natural Science Foundation of China(Grant No.52304123)the China Postdoctoral Science Foundation(Grant No.2023M730412).
文摘Acoustic waves in the pseudo-triaxial experiment system experience refraction phenomena.The conventional assumption that acoustic waves propagate along a straight line in traditional methods can lead to significant errors in localization results.To the end,this paper presents a method for locating acoustic emission(AE)sources in pseudo-triaxial experiments using shortest paths and orthogonal constraints.The approach consists of three main steps:(1)establishing control equations for refraction paths from AE sources to sensor locations;(2)calculating refraction point locations using the shortest travel principle and orthogonal constraints;(3)determining source coordinates using Taylor's first-order expansion.The results from laboratory AE experiments demonstrate that the average localization accuracy of the new method is only 6.5 mm,which is 66%more precise than the accuracy(19.4 mm)of the traditional method.Furthermore,simulation results indicate that the new method is not affected by the refraction ratio of the media and maintains the highest positioning accuracy across various arrival and velocity errors.
基金supported by the National Key Research and Development Program of China(No.2022YFB3706704)the Academician Special Science Research Project of CCCC(No.YSZX-03-2022-01-B).
文摘To investigate the influence of different longitudinal constraint systems on the longitudinal displacement at the girder ends of a three-tower suspension bridge,this study takes the Cangrong Xunjiang Bridge as an engineering case for finite element analysis.This bridge employs an unprecedented tower-girder constraintmethod,with all vertical supports placed at the transition piers at both ends.This paper aims to study the characteristics of longitudinal displacement control at the girder ends under this novel structure,relying on finite element(FE)analysis.Initially,based on the Weigh In Motion(WIM)data,a random vehicle load model is generated and applied to the finite elementmodel.Several longitudinal constraint systems are proposed,and their effects on the structural response of the bridge are compared.The most reasonable system,balancing girder-end displacement and transitional pier stress,is selected.Subsequently,the study examines the impact of different viscous damper parameters on key structural response indicators,including cumulative longitudinal displacement at the girder ends,maximum longitudinal displacement at the girder ends,cumulative longitudinal displacement at the pier tops,maximum longitudinal displacement at the pier tops,longitudinal acceleration at the pier tops,and maximum bending moment at the pier bottoms.Finally,the coefficient of variation(CV)-TOPSIS method is used to optimize the viscous damper parameters for multiple objectives.The results show that adding viscous dampers at the side towers,in addition to the existing longitudinal limit bearings at the central tower,can most effectively reduce the response of structural indicators.The changes in these indicators are not entirely consistent with variations in damping coefficient and velocity exponent.The damper parameters significantly influence cumulative longitudinal displacement at the girder ends,cumulative longitudinal displacement at the pier tops,and maximum bending moments at the pier bottoms.The optimal damper parameters are found to be a damping coefficient of 5000 kN/(m/s)0.2 and a velocity exponent of 0.2.
基金supported by the National Natural Science Foundation of China(Grant Nos.12461048 and 12061051)Natural Science Foundation of Inner Mongolia Autonomous Region(Grant No.2023MS01003)+2 种基金the Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region(Grant No.NJYT23096)the financial support from the Program of China Scholarships Council(Grant No.202306810054)for one year's study at the University of Leedsthe support of Professor Ke Wu and Professor Weizhong Zhao at Capital Normal University,China。
文摘This paper is concerned with the construction of two types of generalized Heisenberg supermagnet model with the constraint S^(3)=S,including the inhomogeneous Heisenberg supermagnet model in(1+1)dimensions and the(2+1)-dimensional Heisenberg supermagnet model.Furthermore,by means of the gauge transformation,we investigate the gauge equivalent counterparts,which are the(1+1)-dimensional inhomogeneous nonlinear Schrodinger equation and the(2+1)-dimensional super nonlinear Schrodinger equation,respectively.
文摘The rapid development of digital financial inclusion is profoundly changing the financing environment for small and medium-sized enterprises(SMEs).As an important driver of economic growth and innovation,SMEs account for a significant share of employment and GDP globally.However,the traditional bank credit model has long failed to effectively meet the financing needs of SMEs due to issues such as information asymmetry,high cost,and difficulty in risk assessment,resulting in serious financing constraints.Digital financial inclusion,through technological innovation and big data analysis,has significantly reduced credit costs,alleviated information asymmetry,and provided SMEs with more flexible and efficient financing channels.Research shows that digital financial inclusion can not only ease the financing constraints of SMEs,but also promote their innovation and growth,providing important support for building a more inclusive and sustainable financial ecosystem.
基金support provided by the National Natural Science Foundation of China(No.62173274)the National Key R&D Program of China(No.2019YFA0405300)+3 种基金the Natural Science Foundation of Hunan Province of China(No.2021JJ10045)Shanghai Aerospace Science and Technology Innovation Fund,China(No.SAST2020-004)Postdoctoral Fellowship Program of CPSF(No.GZB20240989)the Open Research Subject of State Key Laboratory of Intelligent Game,China(No.ZBKF-24-01).
文摘In air combat,one effective way to counter an incoming missile attacking an aircraft is to launch a defense missile compared with traditional passive defense strategies such as decoy and electronic countermeasures.To address this issue,this paper proposes a three-body cooperative active defense guidance law with overload constraints from the perspective of a small speed ratio.First,a cooperative guidance-oriented model for active defense is established and linearized to provide a foundation for the design of the guidance law.Then,the essential quantity known as Zero-Effort-Miss(ZEM)is analyzed during the engagement process.In order to minimize the influence of inaccurate estimates of remaining flight time in the ZEM,the concept of Zero-Effort-Velocity(ZEV)is introduced.Subsequently,utilizing the sliding mode control method,the guidance law is designed by selecting the ZEM and ZEV as sliding mode surfaces,combined with the fast power reaching law,and its finite-time stability is analyzed using the Lyapunov method.Furthermore,to quantitatively evaluate the performance of the proposed active defense guidance law,the interception rendezvous angle index is introduced.The proposed active defense guidance law considers integrating information from the incoming missile,aircraft,and defense missile with fewer simplifications and assumptions,and ensures that the aircraft is effectively protected with less overload required for the defense missile.Finally,simulation experiments demonstrate the effectiveness and adaptability of the proposed active defense guidance law.
基金supported by the National Nature Science Foundation of China(62272078)
文摘Dear Editor,The distributed constraint optimization problems(DCOPs) [1]-[3]provide an efficient model for solving the cooperative problems of multi-agent systems, which has been successfully applied to model the real-world problems like the distributed scheduling [4], sensor network management [5], [6], multi-robot coordination [7], and smart grid [8]. However, DCOPs were not well suited to solve the problems with continuous variables and constraint cost in functional form, such as the target tracking sensor orientation [9], the air and ground cooperative surveillance [10], and the sensor network coverage [11].
基金Supported by Zhejiang Provincial Key Research and Development Program(Grant No.2021C04015)。
文摘Learning from demonstration is widely regarded as a promising paradigm for robots to acquire diverse skills.Other than the artificial learning from observation-action pairs for machines,humans can learn to imitate in a more versatile and effective manner:acquiring skills through mere“observation”.Video to Command task is widely perceived as a promising approach for task-based learning,which yet faces two key challenges:(1)High redundancy and low frame rate of fine-grained action sequences make it difficult to manipulate objects robustly and accurately.(2)Video to Command models often prioritize accuracy and richness of output commands over physical capabilities,leading to impractical or unsafe instructions for robots.This article presents a novel Video to Command framework that employs multiple data associations and physical constraints.First,we introduce an object-level appearancecontrasting multiple data association strategy to effectively associate manipulated objects in visually complex environments,capturing dynamic changes in video content.Then,we propose a multi-task Video to Command model that utilizes object-level video content changes to compile expert demonstrations into manipulation commands.Finally,a multi-task hybrid loss function is proposed to train a Video to Command model that adheres to the constraints of the physical world and manipulation tasks.Our method achieved over 10%on BLEU_N,METEOR,ROUGE_L,and CIDEr compared to the up-to-date methods.The dual-arm robot prototype was established to demonstrate the whole process of learning from an expert demonstration of multiple skills and then executing the tasks by a robot.
基金supported by the National Natural Science Foundation of China(U21B2028).
文摘In the existing impact time control guidance (ITCG) laws for moving-targets, the effects of time-varying velocity caused by aerodynamics and gravity cannot be effectively con-sidered. Therefore, an ITCG with field-of-view (FOV) constraints based on biased proportional navigation guidance (PNG) is developed in this paper. The remaining flight time (time-to-go) estimation method is derived considering aerodynamic force and gravity. The number of differential equations is reduced and the integration step is increased by changing the integral variable, which makes it possible to obtain time-to-go through integration. An impact time controller with FOV constraints is proposed by analyzing the influence of the biased term on time-to-go and FOV constraint. Then, numerical simulations are performed to verify the correctness and superiority of the method.
基金co-supported by the National Natural Science Foundation of China(Nos.62271399,61901015,GNA22001 and GAA20024)the Zhejiang Provincial Natural Science Foundation of China(No.LQ24F010003).
文摘This paper investigates the secure communication between legitimate users in the presence of eavesdroppers, where the Intelligent Reflective Surface-Unmanned Aerial Vehicle (IRS-UAV) and Buffer-Aided (BA) relaying techniques are utilized to enhance secrecy performance. By jointly optimizing the link selection strategy, the UAV position, and the reflection coefficient of the IRS, we aim to maximize the long-term average secrecy rate. Specifically, we propose a novel buffer in/out stabilization scheme based on the Lyapunov framework, which transforms the long-term average secrecy rate maximization problem into two per-slot drift-plus-penalty minimization problems with different link selection factors. The hybrid Particle Swarm Optimization-Artificial Fish Swarm Algorithm (PSO-AFSA) is adopted to optimize the UAV position, and the IRS reflection coefficient optimization problem is solved by iterative optimization in which auxiliary variables and standard convex optimization algorithms are introduced. Finally, the delay constraint is set to ensure the timeliness of information packets. Simulation results demonstrate that our proposed scheme outperforms the comparison schemes in terms of average secrecy rate. Specifically, the addition of BA improves the average secrecy rate by 1.37 bps/Hz, and the continued optimizations of IRS reflection coefficients and UAV positions improve the average secrecy rate by 2.46 bps/Hz and 3.75 bps/Hz, respectively.
文摘As an important tool to achieve sustainable economic and environmental development,green finance can effectively alleviate the financing constraints of small and medium-sized enterprises(SMEs),especially in promoting green transformation plays a key role.SMEs play an important role in economic growth,innovation,and job creation,but due to a lack of collateral,imperfect credit history,and opaque financial information,they face great obstacles in the financing process,especially in the early capital investment required for green transformation.Green finance,through innovative financial instruments such as green credit and green bonds,provides new financing channels for SMEs,helping them reduce financing costs,optimize financing structure,and promote their green transformation and sustainable development.This paper analyzes the current situation and root causes of SMEs’financing dilemma from the perspective of green finance,and probes into the influence of green finance policies on financing behavior.
