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
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
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
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
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
In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing e...In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing ellipse detection algorithms often face issues such as high computational complexity,strong dependence on initial conditions,sensitivity to noise,and lack of robustness to occlusions.In this paper,we propose a fast and robust ellipse detection method to address these challenges.This method first utilizes edge gradient and curvature information to segment the curve into circular arcs.Next,based on the convexity of the arcs,it divides them into different quadrants of the ellipse,groups and fits the arcs according to multiple geometric constraints at a low computational cost.Finally,it reduces the parameter space for hierarchical clustering and then segments the complete ellipse into several sectors for verification.We compare our method across seven datasets,including five public image datasets and two from industrial camera scenes.Experimental results show that our method achieves a precision ranging from 67.1%to 98.9%,a recall ranging from 48.1%to 92.9%,and an F-measure ranging from 58.0%to 95.8%.The average execution time per image ranges from 25 ms to 192 ms,demonstrating both high accuracy and efficiency.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
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
Free cash flow and financing constraints can exert significant influences on the operational development of enterprises.Based on the pecking order theory and using data from A-share listed companies in China,this pape...Free cash flow and financing constraints can exert significant influences on the operational development of enterprises.Based on the pecking order theory and using data from A-share listed companies in China,this paper employs fixed-effects models and moderation effect models to examine the relationship and mechanisms between enterprises'free cash flow generation capacity and their financing constraints.The study found that:(1)Free cash flow can alleviate corporate financing constraints.(2)Corporate performance plays a positive moderating role in the impact of free cash flow on financing constraints.(3)The impact of free cash flow on financing constraints is weaker in state-owned enterprises compared to non-state-owned enterprises.The findings of this paper imply that free cash flow can have a significant impact on corporate financing activities.Therefore,enterprises should pay more attention to their cash flow indicators,signaling their operational stability and risk management capabilities to the outside world,thereby reducing the level of financing constraints faced by the enterprise.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
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
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
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
Digital financial inclusion provides financial services through digital platforms,aiming to improve the ability of MSMEs and low-income groups to access financial resources,thereby easing their financing constraints a...Digital financial inclusion provides financial services through digital platforms,aiming to improve the ability of MSMEs and low-income groups to access financial resources,thereby easing their financing constraints and promoting economic growth and inclusive development.As an innovative financial model,digital financial inclusion utilizes modern technological means to significantly improve the accessibility and convenience of financial services,especially in areas where traditional banking services are under-covered.Digital finance has promoted the popularization of financial services such as micro-credit,micro-savings,and micro-insurance,and helped improve the financing environment of low-income groups and small and micro enterprises.At the same time,digital financial inclusion promotes financial literacy education and digital inclusion construction,and enhances the acceptance and use of digital financial instruments by the general public,which is the key to achieving sustainable development of digital financial inclusion.Therefore,digital financial inclusion can better ease the financing constraints of small and medium-sized enterprises and promote economic development.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
Under the socialist market economic system of our country,the government,through the“invisible hand,”carries on macro regulation and control to improve the financing constraints that small and medium-sized enterpris...Under the socialist market economic system of our country,the government,through the“invisible hand,”carries on macro regulation and control to improve the financing constraints that small and medium-sized enterprises are facing.But because of the huge base number of small and medium-sized enterprises in our country,there are many kinds,and the problem of financing constraints is still puzzling the development of enterprises at present.With the continuous promotion of inclusive finance in our country,the problems plaguing SMEs in the last mile of financing are gradually improved.In this context,small and medium-sized enterprises in Hainan Free Trade Port are taken as the research object to study the role of digital inclusive finance on the financing constraints of SMEs.The research shows that,first of all,small and medium-sized enterprises in Hainan Free Trade Port generally have financing problems.The development of digital inclusive finance solves the“last kilometer”problem of traditional finance,enhances financial access ability,broadens the financial service group,provides convenience and diversified services for SMEs'financing,and provides inexhaustible impetus for the long-term healthy development of SMEs.Secondly,digital inclusive finance alleviates the financing difficulties faced by SMEs on the island by reducing financial costs and expanding the scale of credit.展开更多
Semi-supervised clustering techniques attempt to improve clustering accuracy by utilizing a limited number of labeled data for guidance.This method effectively integrates prior knowledge using pre-labeled data.While s...Semi-supervised clustering techniques attempt to improve clustering accuracy by utilizing a limited number of labeled data for guidance.This method effectively integrates prior knowledge using pre-labeled data.While semi-supervised fuzzy clustering(SSFC)methods leverage limited labeled data to enhance accuracy,they remain highly susceptible to inappropriate or mislabeled prior knowledge,especially in noisy or overlapping datasets where cluster boundaries are ambiguous.To enhance the effectiveness of clustering algorithms,it is essential to leverage labeled data while ensuring the safety of the previous knowledge.Existing solutions,such as the Trusted Safe Semi-Supervised Fuzzy Clustering Method(TS3FCM),struggle with random centroid initialization,fixed neighbor radius formulas,and handling outliers or noise at cluster overlaps.A new framework called Active Safe Semi-Supervised Fuzzy Clustering with Pairwise Constraints Based on Cluster Boundary(AS3FCPC)is proposed in this paper to deal with these problems.It does this by combining pairwise constraints and active learning.AS3FCPC uses active learning to query only the most informative data instances close to the cluster boundaries.It also uses pairwise constraints to enforce the cluster structure,which makes the system more accurate and robust.Extensive test results on diverse datasets,including challenging noisy and overlapping scenarios,demonstrate that AS3FCPC consistently achieves superior performance compared to state-of-the-art methods like TS3FCM and other baselines,especially when the data is noisy and overlaps.This significant improvement underscores AS3FCPC’s potential for reliable and accurate semisupervised fuzzy clustering in complex,real-world applications,particularly by effectively managing mislabeled data and ambiguous cluster boundaries.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
The biased allocation of emission reduction target constraints quantifies emission reduction responsibilities and reflects differences in pollutant reductions both across and within cities.This approach represents a s...The biased allocation of emission reduction target constraints quantifies emission reduction responsibilities and reflects differences in pollutant reductions both across and within cities.This approach represents a systematic innovation aims to enhance China’s green competitiveness and facilitate its economic transformation through localized and precise policymaking.Using panel data from 275 Chinese cities spanning 2000-2022,this study applies the difference-in-differences method to estimate the impact of biased allocation of emission reduction target constraints on urban green competitiveness.The findings indicate that such constraints-whether based on chemical oxygen demand or sulfur dioxide targets-significantly improve urban green competitiveness,with both pollutant-specific constraints producing comparable effects.Furthermore,these constraints exhibit significant spatial spillover effects within a 200-km geographical radius.Heterogeneity analysis reveals stronger policy impacts in resource-based cities,eastern regions,and cities designated as key areas for pollution prevention and control.Mechanism analysis demonstrates that the constraints enhance green competitiveness primarily by fostering green technological innovation and optimizing industrial structures.These conclusions provide a practical foundation for addressing China’s enduring conflict between environmental protection and economic development.展开更多
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 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.
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 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 National Major Scientific Research Instrument Development Project of China(No.51927804)Science Fund for Shaanxi Provincial Department of Education's Youth Innovation Team Research Plan under Grant(No.23JP169).
文摘In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing ellipse detection algorithms often face issues such as high computational complexity,strong dependence on initial conditions,sensitivity to noise,and lack of robustness to occlusions.In this paper,we propose a fast and robust ellipse detection method to address these challenges.This method first utilizes edge gradient and curvature information to segment the curve into circular arcs.Next,based on the convexity of the arcs,it divides them into different quadrants of the ellipse,groups and fits the arcs according to multiple geometric constraints at a low computational cost.Finally,it reduces the parameter space for hierarchical clustering and then segments the complete ellipse into several sectors for verification.We compare our method across seven datasets,including five public image datasets and two from industrial camera scenes.Experimental results show that our method achieves a precision ranging from 67.1%to 98.9%,a recall ranging from 48.1%to 92.9%,and an F-measure ranging from 58.0%to 95.8%.The average execution time per image ranges from 25 ms to 192 ms,demonstrating both high accuracy and efficiency.
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Free cash flow and financing constraints can exert significant influences on the operational development of enterprises.Based on the pecking order theory and using data from A-share listed companies in China,this paper employs fixed-effects models and moderation effect models to examine the relationship and mechanisms between enterprises'free cash flow generation capacity and their financing constraints.The study found that:(1)Free cash flow can alleviate corporate financing constraints.(2)Corporate performance plays a positive moderating role in the impact of free cash flow on financing constraints.(3)The impact of free cash flow on financing constraints is weaker in state-owned enterprises compared to non-state-owned enterprises.The findings of this paper imply that free cash flow can have a significant impact on corporate financing activities.Therefore,enterprises should pay more attention to their cash flow indicators,signaling their operational stability and risk management capabilities to the outside world,thereby reducing the level of financing constraints faced by the enterprise.
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.
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.
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.
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Digital financial inclusion provides financial services through digital platforms,aiming to improve the ability of MSMEs and low-income groups to access financial resources,thereby easing their financing constraints and promoting economic growth and inclusive development.As an innovative financial model,digital financial inclusion utilizes modern technological means to significantly improve the accessibility and convenience of financial services,especially in areas where traditional banking services are under-covered.Digital finance has promoted the popularization of financial services such as micro-credit,micro-savings,and micro-insurance,and helped improve the financing environment of low-income groups and small and micro enterprises.At the same time,digital financial inclusion promotes financial literacy education and digital inclusion construction,and enhances the acceptance and use of digital financial instruments by the general public,which is the key to achieving sustainable development of digital financial inclusion.Therefore,digital financial inclusion can better ease the financing constraints of small and medium-sized enterprises and promote economic development.
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.
文摘Under the socialist market economic system of our country,the government,through the“invisible hand,”carries on macro regulation and control to improve the financing constraints that small and medium-sized enterprises are facing.But because of the huge base number of small and medium-sized enterprises in our country,there are many kinds,and the problem of financing constraints is still puzzling the development of enterprises at present.With the continuous promotion of inclusive finance in our country,the problems plaguing SMEs in the last mile of financing are gradually improved.In this context,small and medium-sized enterprises in Hainan Free Trade Port are taken as the research object to study the role of digital inclusive finance on the financing constraints of SMEs.The research shows that,first of all,small and medium-sized enterprises in Hainan Free Trade Port generally have financing problems.The development of digital inclusive finance solves the“last kilometer”problem of traditional finance,enhances financial access ability,broadens the financial service group,provides convenience and diversified services for SMEs'financing,and provides inexhaustible impetus for the long-term healthy development of SMEs.Secondly,digital inclusive finance alleviates the financing difficulties faced by SMEs on the island by reducing financial costs and expanding the scale of credit.
文摘Semi-supervised clustering techniques attempt to improve clustering accuracy by utilizing a limited number of labeled data for guidance.This method effectively integrates prior knowledge using pre-labeled data.While semi-supervised fuzzy clustering(SSFC)methods leverage limited labeled data to enhance accuracy,they remain highly susceptible to inappropriate or mislabeled prior knowledge,especially in noisy or overlapping datasets where cluster boundaries are ambiguous.To enhance the effectiveness of clustering algorithms,it is essential to leverage labeled data while ensuring the safety of the previous knowledge.Existing solutions,such as the Trusted Safe Semi-Supervised Fuzzy Clustering Method(TS3FCM),struggle with random centroid initialization,fixed neighbor radius formulas,and handling outliers or noise at cluster overlaps.A new framework called Active Safe Semi-Supervised Fuzzy Clustering with Pairwise Constraints Based on Cluster Boundary(AS3FCPC)is proposed in this paper to deal with these problems.It does this by combining pairwise constraints and active learning.AS3FCPC uses active learning to query only the most informative data instances close to the cluster boundaries.It also uses pairwise constraints to enforce the cluster structure,which makes the system more accurate and robust.Extensive test results on diverse datasets,including challenging noisy and overlapping scenarios,demonstrate that AS3FCPC consistently achieves superior performance compared to state-of-the-art methods like TS3FCM and other baselines,especially when the data is noisy and overlaps.This significant improvement underscores AS3FCPC’s potential for reliable and accurate semisupervised fuzzy clustering in complex,real-world applications,particularly by effectively managing mislabeled data and ambiguous cluster boundaries.
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The funding was provided by National Office for Philosophy and Social Science.The authors express their gratitude to the research project titled“Study on Synergistic Governance and Optimization Path of Urban Environment under the Constraint of Biased Emission Reduction Target”[Grant No.23BGL222]this research is also supported by the Hubei Market Entity Vitality Research Center,a Key Research Institute of Humanities and Social Sciences in Hubei Universities[Grant No.00120721].
文摘The biased allocation of emission reduction target constraints quantifies emission reduction responsibilities and reflects differences in pollutant reductions both across and within cities.This approach represents a systematic innovation aims to enhance China’s green competitiveness and facilitate its economic transformation through localized and precise policymaking.Using panel data from 275 Chinese cities spanning 2000-2022,this study applies the difference-in-differences method to estimate the impact of biased allocation of emission reduction target constraints on urban green competitiveness.The findings indicate that such constraints-whether based on chemical oxygen demand or sulfur dioxide targets-significantly improve urban green competitiveness,with both pollutant-specific constraints producing comparable effects.Furthermore,these constraints exhibit significant spatial spillover effects within a 200-km geographical radius.Heterogeneity analysis reveals stronger policy impacts in resource-based cities,eastern regions,and cities designated as key areas for pollution prevention and control.Mechanism analysis demonstrates that the constraints enhance green competitiveness primarily by fostering green technological innovation and optimizing industrial structures.These conclusions provide a practical foundation for addressing China’s enduring conflict between environmental protection and economic development.
