West Java in the western part of the Sunda Arc has a relatively high seismicity due to subduction activity and faults.In this study,double-difference tomography was used to obtain the 3D velocity tomograms of P and S ...West Java in the western part of the Sunda Arc has a relatively high seismicity due to subduction activity and faults.In this study,double-difference tomography was used to obtain the 3D velocity tomograms of P and S waves beneath the western part of Java.To infer the geometry of the structure beneath the study area,precise earthquake hypo・center determination was first performed before tomographic imaging.For this,earthquake waveform data were extracted from the regional Meteorological,Climatological,Geophysical Agency(BMKG)network of Indonesia from South Sumatra to Central Java.The P and S arrival times for about 1,000 events in the period April 2009 to July 2016 were selected,the key features being events of magnitude>3,azimuthal gap<210°and number of phases>8.A nonlinear method using the oct-tree sampling algorithm from the NonLinLoc program was employed to determine the earthquake hypocenters.The hypocenter locations were then relocated using double-difference tomography(tomoDD).A significant reduction of travel-time(root mean square basis)and a better clustering of earthquakes were achieved which correlated well with the geological structure in West Java.Double-difference tomography was found to give a clear velocity structure,especially beneath the volcanic arc area,i.e.,under Mt Anak Krakatau,Mt Salak and the mountains complex in the southern part of West Java.Low velocity anomalies for the P and S waves as well as the vp/vs ratio below the volcanoes indicated possible partial melting of the upper mantle which ascended from the subducted slab beneath the volcanic arc.展开更多
In this paper,we use the double difference location method based on waveform crosscorrelation algorithm for precise positioning of the Three Gorges Reservoir( TGR)earthquakes and analysis of seismic activity. First,we...In this paper,we use the double difference location method based on waveform crosscorrelation algorithm for precise positioning of the Three Gorges Reservoir( TGR)earthquakes and analysis of seismic activity. First,we use the bi-spectrum cross-correlation method to analyze the seismic waveform data of TGR encrypted networks from March,2009 to December,2010,and evaluate the quality of waveform cross-correlation analysis.Combined with the waveform cross-correlation of data obtained, we use the double difference method to relocate the earthquake position. The results show that location precision using bi-spectrum verified waveform cross-correlation data is higher than that by using other types of data,and the mean 2 sig-error in EW,NS and UD are 3.2 m,3.9 m and 6.2 m,respectively. For the relocation of the Three Gorges Reservoir earthquakes,the results show that the micro-earthquakes along the Shenlongxi river in the Badong reservoir area obviously show the characteristics of three linear zones with nearly east-west direction,which is in accordance with the small faults and carbonate strata line of the neotectonic period,revealing the reservoir water main along the underground rivers or caves permeated and induced seismic activity. The stronger earthquakes may have resulted from small earthquakes through the active layers.展开更多
We applied double-difference tomography to relocate seismic events and determine the lithospheric velocity structure beneath the New Britain Island arc and the South Bismarck Sea Basin,based on the local P wave arriva...We applied double-difference tomography to relocate seismic events and determine the lithospheric velocity structure beneath the New Britain Island arc and the South Bismarck Sea Basin,based on the local P wave arrival time dataset collected by the International Seismological Centre.Results of the seismic relocation and velocity inversion show that the subduction of Solomon Sea Plate along the New Britain Trench is spatially different above 150 km,and the subduction angle of the slab on the west side is higher than that on the east side.The relocated earthquakes also show that there are double seismic zones at the depths of about 30–90km beneath the New Britain Island Arc.The velocity structure shows that the dehydration of the subducting slab caused the low-velocity anomalies in mantle wedge above the slab,which are associated with the magmatic activities around the New Guinea-New Britain Island arc.Moreover,it shows that there is another low-velocity anomaly zone beneath the Bismarck mid-oceanic ridge with spatial variation.Beneath the west of the Bismarck mid-oceanic ridge,the low-velocity anomaly is weakly connected to the subducted Solomon Sea slab.Conversely,the low-velocity anomaly beneath the Manus Sea Basin is highly intertwined to the subducting slab and its mantle wedge,indicating that the subduction of the Solomon Sea Plate might be a key deep dynamic factor that drives the spreading of the Manus Sea Basin and the separation of the Bismarck Plate.展开更多
The locations of about 400 earthquakes in Yangjiang, Guangdong Province are determined using the double, difference earthquake location algorithm （DDA）. The seismicity pattern becomes concentrated from discrete grid...The locations of about 400 earthquakes in Yangjiang, Guangdong Province are determined using the double, difference earthquake location algorithm （DDA）. The seismicity pattern becomes concentrated from discrete grids. The rupture characteristics of the Yangjiang earthquake sequence show a conjugated distribution in NW and NE directions. The major distribution trends NE and dips NE with an angle of 30^o and a length of 30km,and the minor distribution trends NW and dips SE with an angle of 30^o and a length of 20km. The focal depth is 5km - 15km. The distribution of the Enping earthquake sequence,which is not far from Yangjiang,is NW-trending. The relationship between hypocenter distribution and geological structure is discussed.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
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
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
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
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
In this study,we propose a constraint learning strategy based on interpretability analysis to improve the convergence and accuracy of the enriched physics-informed neural network(EPINN),which is applied to simulate tw...In this study,we propose a constraint learning strategy based on interpretability analysis to improve the convergence and accuracy of the enriched physics-informed neural network(EPINN),which is applied to simulate two-phase flow in heterogeneous porous media.Specifically,we first analyze the layerwise outputs of EPINN,and identify the distinct functions across layers,including dimensionality adjustment,pointwise construction of non-equilibrium potential,extraction of high-level features,and the establishment of long-range dependencies.Then,inspired by these distinct modules,we propose a novel constraint learning strategy based on regularization approaches,which improves neural network(NN)learning through layer-specific differentiated updates to enhance cross-timestep generalization.Since different neu ral network layers exhibit varying sensitivities to global generalization and local regression,we decrease the update frequency of layers more sensitive to local learning under this constraint learning strategy.In other words,the entire neural network is encouraged to extract more generalized features.The superior performance of the proposed learning strategy is validated through evaluations on numerical examples with varying computational complexities.Post hoc analysis reveals that gradie nt propagation exhibits more pronounced staged characte ristics,and the partial differential equation(PDE)residuals are more uniformly distributed under the constraint guidance.Interpretability analysis of the adaptive constraint process suggests that maintaining a stable information compression mode facilitates progressive convergence acceleration.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 power inversion(PI)algorithm lacks specific constraints on desired signals.Thus,the beampattern has fluctuation in all directions other than the jamming sources.This phenomenon will damage the reception of desired...The power inversion(PI)algorithm lacks specific constraints on desired signals.Thus,the beampattern has fluctuation in all directions other than the jamming sources.This phenomenon will damage the reception of desired signals.In high signal-to-noise ratio(SNR)application,the desired signal is inevitably suppressed by the PI algorithm,resulting in a deterioration to the out signal-to-interference-and-noise ratio(SINR).This paper proposes an improved PI algorithm based on derivative constraint.Firstly,the proposed method uses subspace projection to extract jamming-free data,the derivative constraint is imposed to the non-jamming data,and subsequently the Lagrange multiplier can be used to calculate the array weight vector.Simulation results demonstrate that,the proposed algorithm in this paper has a higher output SNR,flat gains in nonjamming directions,and applicability of high SINR than the PI algorithm,thus verifying the effectiveness of the algorithm.展开更多
Given the existence of real estate market bubbles and risks arising from high government debt,countries are faced with the challenge of preventing systemic risks.This study investigates the macroeconomic dynamics of t...Given the existence of real estate market bubbles and risks arising from high government debt,countries are faced with the challenge of preventing systemic risks.This study investigates the macroeconomic dynamics of the real estate market and local government debt risk from the perspective of liquidity constraints.We build a dynamic stochastic general equilibrium model with real estate and local government debt risk based on the New Keynesian-Dynamic Stochastic General Equilibrium Model(NK-DSGE)model to investigate the transmission path of local government debt risk under real estate regulation.In addition,we analyze the risk transmission between the real estate market and local government under different tax systems and investigate the shock to household welfare from a local government debt default.The results show monetary policy can effectively control the scale of local government debt to reduce default risk.An increase in property taxes that restrains housing demand can effectively regulate the real estate market.Although reducing taxes can increase macroeconomic output,reducing tax rates on consumption,capital,and labor weakens the liquidity of household assets.Further,lowering taxes increases local government default risk,which reduces household welfare and makes it more difficult for local governments to deleverage.Our findings provide important insights for countries seeking an effective real estate regulation mechanism to curb local government default risk.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
基金the Directorate General of Resources for Science Technologythe Higher Education of the Republic of Indonesia for granting a PMDSU scholarship to SR
文摘West Java in the western part of the Sunda Arc has a relatively high seismicity due to subduction activity and faults.In this study,double-difference tomography was used to obtain the 3D velocity tomograms of P and S waves beneath the western part of Java.To infer the geometry of the structure beneath the study area,precise earthquake hypo・center determination was first performed before tomographic imaging.For this,earthquake waveform data were extracted from the regional Meteorological,Climatological,Geophysical Agency(BMKG)network of Indonesia from South Sumatra to Central Java.The P and S arrival times for about 1,000 events in the period April 2009 to July 2016 were selected,the key features being events of magnitude>3,azimuthal gap<210°and number of phases>8.A nonlinear method using the oct-tree sampling algorithm from the NonLinLoc program was employed to determine the earthquake hypocenters.The hypocenter locations were then relocated using double-difference tomography(tomoDD).A significant reduction of travel-time(root mean square basis)and a better clustering of earthquakes were achieved which correlated well with the geological structure in West Java.Double-difference tomography was found to give a clear velocity structure,especially beneath the volcanic arc area,i.e.,under Mt Anak Krakatau,Mt Salak and the mountains complex in the southern part of West Java.Low velocity anomalies for the P and S waves as well as the vp/vs ratio below the volcanoes indicated possible partial melting of the upper mantle which ascended from the subducted slab beneath the volcanic arc.
基金funded by the National Science and Technology Pillar Program(2008BAC38B04)the Special Research Fund for Seismology(16A44ZX282)
文摘In this paper,we use the double difference location method based on waveform crosscorrelation algorithm for precise positioning of the Three Gorges Reservoir( TGR)earthquakes and analysis of seismic activity. First,we use the bi-spectrum cross-correlation method to analyze the seismic waveform data of TGR encrypted networks from March,2009 to December,2010,and evaluate the quality of waveform cross-correlation analysis.Combined with the waveform cross-correlation of data obtained, we use the double difference method to relocate the earthquake position. The results show that location precision using bi-spectrum verified waveform cross-correlation data is higher than that by using other types of data,and the mean 2 sig-error in EW,NS and UD are 3.2 m,3.9 m and 6.2 m,respectively. For the relocation of the Three Gorges Reservoir earthquakes,the results show that the micro-earthquakes along the Shenlongxi river in the Badong reservoir area obviously show the characteristics of three linear zones with nearly east-west direction,which is in accordance with the small faults and carbonate strata line of the neotectonic period,revealing the reservoir water main along the underground rivers or caves permeated and induced seismic activity. The stronger earthquakes may have resulted from small earthquakes through the active layers.
基金supported by the National Natural Science Foundation of China(Nos.41906048 and 91858215).
文摘We applied double-difference tomography to relocate seismic events and determine the lithospheric velocity structure beneath the New Britain Island arc and the South Bismarck Sea Basin,based on the local P wave arrival time dataset collected by the International Seismological Centre.Results of the seismic relocation and velocity inversion show that the subduction of Solomon Sea Plate along the New Britain Trench is spatially different above 150 km,and the subduction angle of the slab on the west side is higher than that on the east side.The relocated earthquakes also show that there are double seismic zones at the depths of about 30–90km beneath the New Britain Island Arc.The velocity structure shows that the dehydration of the subducting slab caused the low-velocity anomalies in mantle wedge above the slab,which are associated with the magmatic activities around the New Guinea-New Britain Island arc.Moreover,it shows that there is another low-velocity anomaly zone beneath the Bismarck mid-oceanic ridge with spatial variation.Beneath the west of the Bismarck mid-oceanic ridge,the low-velocity anomaly is weakly connected to the subducted Solomon Sea slab.Conversely,the low-velocity anomaly beneath the Manus Sea Basin is highly intertwined to the subducting slab and its mantle wedge,indicating that the subduction of the Solomon Sea Plate might be a key deep dynamic factor that drives the spreading of the Manus Sea Basin and the separation of the Bismarck Plate.
基金The research was sponsored by the Key Science and Technology R&D Program of Guangdong Province(Grant No. 2005B32601003)
文摘The locations of about 400 earthquakes in Yangjiang, Guangdong Province are determined using the double, difference earthquake location algorithm （DDA）. The seismicity pattern becomes concentrated from discrete grids. The rupture characteristics of the Yangjiang earthquake sequence show a conjugated distribution in NW and NE directions. The major distribution trends NE and dips NE with an angle of 30^o and a length of 30km,and the minor distribution trends NW and dips SE with an angle of 30^o and a length of 20km. The focal depth is 5km - 15km. The distribution of the Enping earthquake sequence,which is not far from Yangjiang,is NW-trending. The relationship between hypocenter distribution and geological structure is discussed.
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.
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 Key R&D Program of China(No.2023YFB4104200)the National Natural Science Foundation of China(Nos.52474067,52441411,52325402,52034010,and12131014)+2 种基金the Natural Science Foundation of Shandong Province,China(No.ZR2024ME005)Fundamental Research Funds for the Central Universities(Nos.25CX02025A and 21CX06031A)the Youth Innovation and Technology Support Program for Higher Education Institutions of Shandong Province,China(No.2022KJ070)。
文摘In this study,we propose a constraint learning strategy based on interpretability analysis to improve the convergence and accuracy of the enriched physics-informed neural network(EPINN),which is applied to simulate two-phase flow in heterogeneous porous media.Specifically,we first analyze the layerwise outputs of EPINN,and identify the distinct functions across layers,including dimensionality adjustment,pointwise construction of non-equilibrium potential,extraction of high-level features,and the establishment of long-range dependencies.Then,inspired by these distinct modules,we propose a novel constraint learning strategy based on regularization approaches,which improves neural network(NN)learning through layer-specific differentiated updates to enhance cross-timestep generalization.Since different neu ral network layers exhibit varying sensitivities to global generalization and local regression,we decrease the update frequency of layers more sensitive to local learning under this constraint learning strategy.In other words,the entire neural network is encouraged to extract more generalized features.The superior performance of the proposed learning strategy is validated through evaluations on numerical examples with varying computational complexities.Post hoc analysis reveals that gradie nt propagation exhibits more pronounced staged characte ristics,and the partial differential equation(PDE)residuals are more uniformly distributed under the constraint guidance.Interpretability analysis of the adaptive constraint process suggests that maintaining a stable information compression mode facilitates progressive convergence acceleration.
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.
基金supported by the National Natural Science Foundation of China(62071144).
文摘The power inversion(PI)algorithm lacks specific constraints on desired signals.Thus,the beampattern has fluctuation in all directions other than the jamming sources.This phenomenon will damage the reception of desired signals.In high signal-to-noise ratio(SNR)application,the desired signal is inevitably suppressed by the PI algorithm,resulting in a deterioration to the out signal-to-interference-and-noise ratio(SINR).This paper proposes an improved PI algorithm based on derivative constraint.Firstly,the proposed method uses subspace projection to extract jamming-free data,the derivative constraint is imposed to the non-jamming data,and subsequently the Lagrange multiplier can be used to calculate the array weight vector.Simulation results demonstrate that,the proposed algorithm in this paper has a higher output SNR,flat gains in nonjamming directions,and applicability of high SINR than the PI algorithm,thus verifying the effectiveness of the algorithm.
基金supported by the National Natural Science Foundation of China(Nos.72271135,72141304,71901130)National Social Science Fund of China(22&ZD117)+3 种基金Laboratory of Computation and Analytics of Complex Management Systems(Tianjin University)Special Funds for Taishan Scholars(tsqn202211120)2024 Qingdao Finance Society Key Project2024 Qingdao Social Science Planning Project.
文摘Given the existence of real estate market bubbles and risks arising from high government debt,countries are faced with the challenge of preventing systemic risks.This study investigates the macroeconomic dynamics of the real estate market and local government debt risk from the perspective of liquidity constraints.We build a dynamic stochastic general equilibrium model with real estate and local government debt risk based on the New Keynesian-Dynamic Stochastic General Equilibrium Model(NK-DSGE)model to investigate the transmission path of local government debt risk under real estate regulation.In addition,we analyze the risk transmission between the real estate market and local government under different tax systems and investigate the shock to household welfare from a local government debt default.The results show monetary policy can effectively control the scale of local government debt to reduce default risk.An increase in property taxes that restrains housing demand can effectively regulate the real estate market.Although reducing taxes can increase macroeconomic output,reducing tax rates on consumption,capital,and labor weakens the liquidity of household assets.Further,lowering taxes increases local government default risk,which reduces household welfare and makes it more difficult for local governments to deleverage.Our findings provide important insights for countries seeking an effective real estate regulation mechanism to curb local government default risk.
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.
