This paper investigates the following mixed local and nonlocal elliptic problem fea-turing concave-convex nonlinearities and a discontinuous right-hand side:{L(u)=H(u−μ)|u|^(p−2)u+λ|u|^(q−2)u,x∈Ω,u≥0,x∈Ω,u=0,x...This paper investigates the following mixed local and nonlocal elliptic problem fea-turing concave-convex nonlinearities and a discontinuous right-hand side:{L(u)=H(u−μ)|u|^(p−2)u+λ|u|^(q−2)u,x∈Ω,u≥0,x∈Ω,u=0,x∈R^(N)\Ω,where Ω R^(N)(N>2)is a bounded domain,μ≥0 and λ>0 are real parameters,H denotes the Heaviside function(H(t)=0 for t<0,H(t)=1 for t>0),and the mixed local and nolocal operator is defined as L(u)=−Δu+(−Δ)^(s)u with(−Δ)^(s) being the restricted fractional Laplace(0<s<1).The exponents satisfy 1<q<2<p.By employing a novel non-smooth variational principle,we establish the existence of an M-solution for this problem and identify a range for the exponent p.展开更多
Existing Transformer-based image captioning models typically rely on the self-attention mechanism to capture long-range dependencies,which effectively extracts and leverages the global correlation of image features.Ho...Existing Transformer-based image captioning models typically rely on the self-attention mechanism to capture long-range dependencies,which effectively extracts and leverages the global correlation of image features.However,these models still face challenges in effectively capturing local associations.Moreover,since the encoder extracts global and local association features that focus on different semantic information,semantic noise may occur during the decoding stage.To address these issues,we propose the Local Relationship Enhanced Gated Transformer(LREGT).In the encoder part,we introduce the Local Relationship Enhanced Encoder(LREE),whose core component is the Local Relationship Enhanced Module(LREM).LREM consists of two novel designs:the Local Correlation Perception Module(LCPM)and the Local-Global Fusion Module(LGFM),which are beneficial for generating a comprehensive feature representation that integrates both global and local information.In the decoder part,we propose the Dual-level Multi-branch Gated Decoder(DMGD).It first creates multiple decoding branches to generate multi-perspective contextual feature representations.Subsequently,it employs the Dual-Level Gating Mechanism(DLGM)to model the multi-level relationships of these multi-perspective contextual features,enhancing their fine-grained semantics and intrinsic relationship representations.This ultimately leads to the generation of high-quality and semantically rich image captions.Experiments on the standard MSCOCO dataset demonstrate that LREGT achieves state-of-the-art performance,with a CIDEr score of 140.8 and BLEU-4 score of 41.3,significantly outperforming existing mainstream methods.These results highlight LREGT’s superiority in capturing complex visual relationships and resolving semantic noise during decoding.展开更多
Objective:To analyze the efficacy of whole-course local simultaneous integrated boost intensity-modulated radiotherapy(SIB-IMRT)on patients with locally advanced esophageal squamous cell carcinoma(ESCC).Methods:88 pat...Objective:To analyze the efficacy of whole-course local simultaneous integrated boost intensity-modulated radiotherapy(SIB-IMRT)on patients with locally advanced esophageal squamous cell carcinoma(ESCC).Methods:88 patients with ESCC admitted to the hospital between October 2022 and October 2024 were selected and randomly divided into two groups using a random number table.The experimental group received SIB-IMRT treatment,while the control group received conventional intensity-modulated radiotherapy(C-IMRT).The objective remission rate,immune function,tumor markers,and adverse reaction rate were compared between the two groups.Results:The objective remission rate in the experimental group was higher than that in the control group(P<0.05).Before treatment,there was no difference in immune function levels and tumor marker levels between the two groups(P>0.05).After treatment,the immune function levels in the experimental group were better than those in the control group,and the tumor marker levels were lower than those in the control group(P<0.05).The adverse reaction rate in the experimental group was lower than that in the control group(P<0.05).Conclusion:SIB-IMRT can improve the objective remission rate of patients with ESCC,protect their immune function,down-regulate tumor marker levels,and prevent side effects after treatment.展开更多
Polytrauma with significant bone and volumetric muscle loss presents substantial clinical challenges.Although immune responses significantly influence fracture healing post-polytrauma,the cellular and molecular underp...Polytrauma with significant bone and volumetric muscle loss presents substantial clinical challenges.Although immune responses significantly influence fracture healing post-polytrauma,the cellular and molecular underpinnings of polytrauma-induced immune dysregulation require further investigation.While previous studies examined either injury site tissue or systemic tissue(peripheral blood),our study uniquely investigated both systemic and local immune cells at the same time to better understand polytrauma-induced immune dysregulation and associated impaired bone healing.Using single-cell RNA sequencing(scRNA-seq)in a rat polytrauma model,we analyzed blood,bone marrow,and the local defect soft tissue to identify potential cellular and molecular targets involved in immune dysregulation.We identified a trauma-associated immunosuppressive myeloid(TIM)cell population that drives systemic immune dysregulation,immunosuppression,and potentially impaired bone healing.We found CD1d as a global marker for TIM cells in polytrauma.展开更多
In recent years,local government debt reduction and risk prevention have been the subjects of common concern to all parties.China's local government debt has different reasons in different historical periods,and t...In recent years,local government debt reduction and risk prevention have been the subjects of common concern to all parties.China's local government debt has different reasons in different historical periods,and the main line running through this is the development orientation of local governments.It is undeniable that local government debt has played an indelible role in China's rapid economic growth.However,due to historical restrictions,flood irrigation inevitably brought sediment all over the ground.Therefore,this paper intends to rethink the causes of local government debt from the perspective of the dual role of regional government and the main body of meso economics.展开更多
Electron-electron interactions(EEIs),quantum interference,and the effects of disorder on transport properties are essential topics in condensed matter physics.A series of our characterization work demonstrates that th...Electron-electron interactions(EEIs),quantum interference,and the effects of disorder on transport properties are essential topics in condensed matter physics.A series of our characterization work demonstrates that the morphology of Bi_(2)Te_(3)/MnTe bilayer film mainly depends on the magnetic substrate's growth mode and thickness.We propose that the temperature-dependent quantum interference of the electron wave function caused by disorder drives the transition from weak antilocalization(WAL) to weak localization(WL).Due to spin regulation,WL under low fields originates from the ferromagnetism in MnTe.The quantum interference effect(QIE) model analysis gives the degree of impurity scattering of the electron wave function.The electron wave is scattered by impurities,which causes the Berry phase to change from π to 0,producing a complete WL behavior.The stacked structure provides tunable degrees of freedom,allowing for independent optimization of topological properties and magnetic order through preferential growth orientation of topological insulator(TI) and magnetic layers,respectively.展开更多
Urban investment bonds are another financing method designed by local governments in China to avoid the legal restrictions of urban economic construction, especially urban infrastructure construction under specific ec...Urban investment bonds are another financing method designed by local governments in China to avoid the legal restrictions of urban economic construction, especially urban infrastructure construction under specific economic environment. Although the issuance of urban investment bonds has eased the financing difficulties of local governments to a certain extent, the credit risk of urban investment bonds has gradually emerged due to the rapid increase in the number of urban investment companies and the expansion of the debt scale. In the borrowing process, not only the local government has expanded the land finance, but also the financial transparency has decreased, which will affect the regional economic development level, the urbanization process and the financial and credit status of the city investment companies themselves. Therefore, first of all, the local government should promote the improvement of the tax system, reduce the government's reliance on land finance, actively enhance the government's financial transparency, reduce the information asymmetry between bond issuers and market investors, and reduce the debt risk. Secondly, for the sake of stable growth of local economy, over-investment and development of cities should be avoided. Finally, standardize enterprises to increase credit guarantee, avoid false credit guarantee, and improve the system of public disclosure of corporate financial risk information and the role of third-party market capital in strictly guarding the market, providing a more reliable capital guarantee for the issuance and operation of China's bond market.展开更多
In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):104...In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].展开更多
A multi-phase heterogeneous FeCoNi-based high-entropy alloy is developed to overcome the trade-off between strength and ductility.By alloying with a small amount of Cu and employing a rapid recrystalliza-tion process,...A multi-phase heterogeneous FeCoNi-based high-entropy alloy is developed to overcome the trade-off between strength and ductility.By alloying with a small amount of Cu and employing a rapid recrystalliza-tion process,it exhibits a good combination of yield strength(roughly 1300 MPa)and ductility(approach-ing 20%).Firstly,a multi-phase heterogeneous structure is tailored ranging from nano to micron.Cu is efficiently precipitated as nanoscale clusters(4.2 nm),high-density cuboidal L1_(2) particles(20-40 nm)and L2_(1) particles(500-800 nm)are found to be embedded in the matrix and a bimodal heterogeneous grain structure(1-40μm)is constructed.Secondly,the introduction of Cu effectively suppresses the pre-cipitation of coarse L21 phase at grain boundaries,reducing its volume fraction by 80%and replaced by smaller-scale continuous precipitations within the grains.Thirdly,the high mixing enthalpy gap of Cu and the matrix leads to the formation of local chemical fluctuation and the consequential rugged topog-raphy in the matrix,which result in retarded dislocation motion and promotes dislocation plugging and interlocking during strain,enhancing yield stress and work hardening rate.This study provides a valuable perspective to enhance strength and ductility via enlarged local chemical fluctuation-tailored multi-phase heterogeneous structures.展开更多
Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accu...Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.展开更多
The fast growth of mobile autonomous machines from traditional equipment to unmanned autonomous vehicles has fueled the demand for accurate and reliable localization solutions in diverse application domains.Ultra Wide...The fast growth of mobile autonomous machines from traditional equipment to unmanned autonomous vehicles has fueled the demand for accurate and reliable localization solutions in diverse application domains.Ultra Wide Band(UWB)technology has emerged as a promising candidate for addressing this need,offering high precision,immunity to multipath interference,and robust performance in challenging environments.In this comprehensive survey,we systematically explore UWB-based localization for mobile autonomous machines,spanning from fundamental principles to future trends.To the best of our knowledge,this review paper stands as the pioneer in systematically dissecting the algorithms of UWB-based localization for mobile autonomous machines,covering a spectrum from bottom-ranging schemes to advanced sensor fusion,error mitigation,and optimization techniques.By synthesizing existing knowledge,evaluating current methodologies,and highlighting future trends,this review aims to catalyze progress and innovation in the field,unlocking new opportunities for mobile autonomous machine applications across diverse industries and domains.Thus,it serves as a valuable resource for researchers,practitioners,and stakeholders interested in advancing the state-of-the-art UWB-based localization for mobile autonomous machines.展开更多
The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to indus...The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.展开更多
Neurons are highly polarized cells with axons reaching over a meter long in adult humans.To survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and m...Neurons are highly polarized cells with axons reaching over a meter long in adult humans.To survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and metabolic events,which need to be carried out at the right place,time,and intensity.Such mechanisms include axonal transport,local synthesis,and liquid-liquid phase separations.Alterations and malfunctions in these processes are correlated to neurodegenerative diseases such as amyotrophic lateral sclerosis(ALS).展开更多
Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)informati...Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)information.This paper proposes a security position verification technique based on Multilateration(MLAT)to detect false signals,ensuring UAV safety and reliable airspace operations.First,the proposed method estimates the current position of the UAV by calculating the Time Difference of Arrival(TDOA),Time Sum of Arrival(TSOA),and Angle of Arrival(AOA)information.Then,this estimated position is compared with the ADS-B message to eliminate false UAV signals.Furthermore,a localization model based on TDOA/TSOA/AOA is established by utilizing reliable reference sources for base station time synchronization.Additionally,an improved Chan-Taylor algorithm is developed,incorporating the Constrained Weighted Least Squares(CWLS)method to initialize UAV position calculations.Finally,a false signal detection method is proposed to distinguish between true and false positioning targets.Numerical simulation results indicate that,at a positioning error threshold of 150 m,the improved Chan-Taylor algorithm based on TDOA/TSOA/AOA achieves 100%accuracy coverage,significantly enhancing localization precision.And the proposed false signal detection method achieves a detection accuracy rate of at least 90%within a 50-meter error range.展开更多
Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environ...Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.展开更多
The local structure and thermophysical behavior of Mg-La liquid alloys were in-depth understood using deep potential molecular dynamic(DPMD) simulation driven via machine learning to promote the development of Mg-La a...The local structure and thermophysical behavior of Mg-La liquid alloys were in-depth understood using deep potential molecular dynamic(DPMD) simulation driven via machine learning to promote the development of Mg-La alloys. The robustness of the trained deep potential(DP) model was thoroughly evaluated through several aspects, including root-mean-square errors(RMSEs), energy and force data, and structural information comparison results;the results indicate the carefully trained DP model is reliable. The component and temperature dependence of the local structure in the Mg-La liquid alloy was analyzed. The effect of Mg content in the system on the first coordination shell of the atomic pairs is the same as that of temperature. The pre-peak demonstrated in the structure factor indicates the presence of a medium-range ordered structure in the Mg-La liquid alloy, which is particularly pronounced in the 80at% Mg system and disappears at elevated temperatures. The density, self-diffusion coefficient, and shear viscosity for the Mg-La liquid alloy were predicted via DPMD simulation, the evolution patterns with Mg content and temperature were subsequently discussed, and a database was established accordingly. Finally, the mixing enthalpy and elemental activity of the Mg-La liquid alloy at 1200 K were reliably evaluated,which provides new guidance for related studies.展开更多
We show that the torsion module Tor_(j)^(R)(R/a,H_(a)^(i)(X))is in a Serre subcategory for the bounded below R-complex X.In addition,we prove the isomorphism Tor_(s-t)^(R)(R/a,X)≅Tor_(s)^(R)(R/a,H_(a)^(t)(X))in some c...We show that the torsion module Tor_(j)^(R)(R/a,H_(a)^(i)(X))is in a Serre subcategory for the bounded below R-complex X.In addition,we prove the isomorphism Tor_(s-t)^(R)(R/a,X)≅Tor_(s)^(R)(R/a,H_(a)^(t)(X))in some case.As an application,the Betti number of a complex X in a prime ideal p can be computed by the Betti number of the local cohomology modules of X in p.展开更多
Finger Knuckle Print biometric plays a vital role in establishing security for real-time environments. The success of human authentication depends on high speed and accuracy. This paper proposed an integrated approach...Finger Knuckle Print biometric plays a vital role in establishing security for real-time environments. The success of human authentication depends on high speed and accuracy. This paper proposed an integrated approach of personal authentication using texture based Finger Knuckle Print (FKP) recognition in multiresolution domain. FKP images are rich in texture patterns. Recently, many texture patterns are proposed for biometric feature extraction. Hence, it is essential to review whether Local Binary Patterns or its variants perform well for FKP recognition. In this paper, Local Directional Pattern (LDP), Local Derivative Ternary Pattern (LDTP) and Local Texture Description Framework based Modified Local Directional Pattern (LTDF_MLDN) based feature extraction in multiresolution domain are experimented with Nearest Neighbor and Extreme Learning Machine (ELM) Classifier for FKP recognition. Experiments were conducted on PolYU database. The result shows that LDTP in Contourlet domain achieves a promising performance. It also proves that Soft classifier performs better than the hard classifier.展开更多
基金Supported by the National Natural Science Foundation of China(Grant No.12361026)the Discipline Con-struction Fund Project of Northwest Minzu University.
文摘This paper investigates the following mixed local and nonlocal elliptic problem fea-turing concave-convex nonlinearities and a discontinuous right-hand side:{L(u)=H(u−μ)|u|^(p−2)u+λ|u|^(q−2)u,x∈Ω,u≥0,x∈Ω,u=0,x∈R^(N)\Ω,where Ω R^(N)(N>2)is a bounded domain,μ≥0 and λ>0 are real parameters,H denotes the Heaviside function(H(t)=0 for t<0,H(t)=1 for t>0),and the mixed local and nolocal operator is defined as L(u)=−Δu+(−Δ)^(s)u with(−Δ)^(s) being the restricted fractional Laplace(0<s<1).The exponents satisfy 1<q<2<p.By employing a novel non-smooth variational principle,we establish the existence of an M-solution for this problem and identify a range for the exponent p.
基金supported by the Natural Science Foundation of China(62473105,62172118)Nature Science Key Foundation of Guangxi(2021GXNSFDA196002)+1 种基金in part by the Guangxi Key Laboratory of Image and Graphic Intelligent Processing under Grants(GIIP2302,GIIP2303,GIIP2304)Innovation Project of Guang Xi Graduate Education(2024YCXB09,2024YCXS039).
文摘Existing Transformer-based image captioning models typically rely on the self-attention mechanism to capture long-range dependencies,which effectively extracts and leverages the global correlation of image features.However,these models still face challenges in effectively capturing local associations.Moreover,since the encoder extracts global and local association features that focus on different semantic information,semantic noise may occur during the decoding stage.To address these issues,we propose the Local Relationship Enhanced Gated Transformer(LREGT).In the encoder part,we introduce the Local Relationship Enhanced Encoder(LREE),whose core component is the Local Relationship Enhanced Module(LREM).LREM consists of two novel designs:the Local Correlation Perception Module(LCPM)and the Local-Global Fusion Module(LGFM),which are beneficial for generating a comprehensive feature representation that integrates both global and local information.In the decoder part,we propose the Dual-level Multi-branch Gated Decoder(DMGD).It first creates multiple decoding branches to generate multi-perspective contextual feature representations.Subsequently,it employs the Dual-Level Gating Mechanism(DLGM)to model the multi-level relationships of these multi-perspective contextual features,enhancing their fine-grained semantics and intrinsic relationship representations.This ultimately leads to the generation of high-quality and semantically rich image captions.Experiments on the standard MSCOCO dataset demonstrate that LREGT achieves state-of-the-art performance,with a CIDEr score of 140.8 and BLEU-4 score of 41.3,significantly outperforming existing mainstream methods.These results highlight LREGT’s superiority in capturing complex visual relationships and resolving semantic noise during decoding.
文摘Objective:To analyze the efficacy of whole-course local simultaneous integrated boost intensity-modulated radiotherapy(SIB-IMRT)on patients with locally advanced esophageal squamous cell carcinoma(ESCC).Methods:88 patients with ESCC admitted to the hospital between October 2022 and October 2024 were selected and randomly divided into two groups using a random number table.The experimental group received SIB-IMRT treatment,while the control group received conventional intensity-modulated radiotherapy(C-IMRT).The objective remission rate,immune function,tumor markers,and adverse reaction rate were compared between the two groups.Results:The objective remission rate in the experimental group was higher than that in the control group(P<0.05).Before treatment,there was no difference in immune function levels and tumor marker levels between the two groups(P>0.05).After treatment,the immune function levels in the experimental group were better than those in the control group,and the tumor marker levels were lower than those in the control group(P<0.05).The adverse reaction rate in the experimental group was lower than that in the control group(P<0.05).Conclusion:SIB-IMRT can improve the objective remission rate of patients with ESCC,protect their immune function,down-regulate tumor marker levels,and prevent side effects after treatment.
文摘Polytrauma with significant bone and volumetric muscle loss presents substantial clinical challenges.Although immune responses significantly influence fracture healing post-polytrauma,the cellular and molecular underpinnings of polytrauma-induced immune dysregulation require further investigation.While previous studies examined either injury site tissue or systemic tissue(peripheral blood),our study uniquely investigated both systemic and local immune cells at the same time to better understand polytrauma-induced immune dysregulation and associated impaired bone healing.Using single-cell RNA sequencing(scRNA-seq)in a rat polytrauma model,we analyzed blood,bone marrow,and the local defect soft tissue to identify potential cellular and molecular targets involved in immune dysregulation.We identified a trauma-associated immunosuppressive myeloid(TIM)cell population that drives systemic immune dysregulation,immunosuppression,and potentially impaired bone healing.We found CD1d as a global marker for TIM cells in polytrauma.
文摘In recent years,local government debt reduction and risk prevention have been the subjects of common concern to all parties.China's local government debt has different reasons in different historical periods,and the main line running through this is the development orientation of local governments.It is undeniable that local government debt has played an indelible role in China's rapid economic growth.However,due to historical restrictions,flood irrigation inevitably brought sediment all over the ground.Therefore,this paper intends to rethink the causes of local government debt from the perspective of the dual role of regional government and the main body of meso economics.
基金financially supported by the National Natural Science Foundation of China (Nos.52371204, 52201233,and 52031014)
文摘Electron-electron interactions(EEIs),quantum interference,and the effects of disorder on transport properties are essential topics in condensed matter physics.A series of our characterization work demonstrates that the morphology of Bi_(2)Te_(3)/MnTe bilayer film mainly depends on the magnetic substrate's growth mode and thickness.We propose that the temperature-dependent quantum interference of the electron wave function caused by disorder drives the transition from weak antilocalization(WAL) to weak localization(WL).Due to spin regulation,WL under low fields originates from the ferromagnetism in MnTe.The quantum interference effect(QIE) model analysis gives the degree of impurity scattering of the electron wave function.The electron wave is scattered by impurities,which causes the Berry phase to change from π to 0,producing a complete WL behavior.The stacked structure provides tunable degrees of freedom,allowing for independent optimization of topological properties and magnetic order through preferential growth orientation of topological insulator(TI) and magnetic layers,respectively.
文摘Urban investment bonds are another financing method designed by local governments in China to avoid the legal restrictions of urban economic construction, especially urban infrastructure construction under specific economic environment. Although the issuance of urban investment bonds has eased the financing difficulties of local governments to a certain extent, the credit risk of urban investment bonds has gradually emerged due to the rapid increase in the number of urban investment companies and the expansion of the debt scale. In the borrowing process, not only the local government has expanded the land finance, but also the financial transparency has decreased, which will affect the regional economic development level, the urbanization process and the financial and credit status of the city investment companies themselves. Therefore, first of all, the local government should promote the improvement of the tax system, reduce the government's reliance on land finance, actively enhance the government's financial transparency, reduce the information asymmetry between bond issuers and market investors, and reduce the debt risk. Secondly, for the sake of stable growth of local economy, over-investment and development of cities should be avoided. Finally, standardize enterprises to increase credit guarantee, avoid false credit guarantee, and improve the system of public disclosure of corporate financial risk information and the role of third-party market capital in strictly guarding the market, providing a more reliable capital guarantee for the issuance and operation of China's bond market.
基金Supported by NSFC(Nos.11661025,12161024)Natural Science Foundation of Guangxi(Nos.2020GXNSFAA159118,2021GXNSFAA196045)+2 种基金Guangxi Science and Technology Project(No.Guike AD20297006)Training Program for 1000 Young and Middle-aged Cadre Teachers in Universities of GuangxiNational College Student's Innovation and Entrepreneurship Training Program(No.202110595049)。
文摘In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].
基金financial support from the National Natural Science Foundation of China(Nos.52104306,52274301,52334009)the Aeronautical Science Foundation of China(No.2023Z0530S6005)+3 种基金the National Key Research and Development Program of China(No.2023YFB3712401)the Science and Technology Commission of Shanghai Municipality(No.21DZ1208900)the Academician Workstation of Kunming University of Science and Technology(2024),the Ningbo Yongjiang Talent-Introduction Programme(No.2022A-023-C)the Zhejiang Phenomenological Materials Technology Co.,Ltd.,China.
文摘A multi-phase heterogeneous FeCoNi-based high-entropy alloy is developed to overcome the trade-off between strength and ductility.By alloying with a small amount of Cu and employing a rapid recrystalliza-tion process,it exhibits a good combination of yield strength(roughly 1300 MPa)and ductility(approach-ing 20%).Firstly,a multi-phase heterogeneous structure is tailored ranging from nano to micron.Cu is efficiently precipitated as nanoscale clusters(4.2 nm),high-density cuboidal L1_(2) particles(20-40 nm)and L2_(1) particles(500-800 nm)are found to be embedded in the matrix and a bimodal heterogeneous grain structure(1-40μm)is constructed.Secondly,the introduction of Cu effectively suppresses the pre-cipitation of coarse L21 phase at grain boundaries,reducing its volume fraction by 80%and replaced by smaller-scale continuous precipitations within the grains.Thirdly,the high mixing enthalpy gap of Cu and the matrix leads to the formation of local chemical fluctuation and the consequential rugged topog-raphy in the matrix,which result in retarded dislocation motion and promotes dislocation plugging and interlocking during strain,enhancing yield stress and work hardening rate.This study provides a valuable perspective to enhance strength and ductility via enlarged local chemical fluctuation-tailored multi-phase heterogeneous structures.
基金funded by the Youth Fund of the National Natural Science Foundation of China(Grant No.42261070).
文摘Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.
文摘The fast growth of mobile autonomous machines from traditional equipment to unmanned autonomous vehicles has fueled the demand for accurate and reliable localization solutions in diverse application domains.Ultra Wide Band(UWB)technology has emerged as a promising candidate for addressing this need,offering high precision,immunity to multipath interference,and robust performance in challenging environments.In this comprehensive survey,we systematically explore UWB-based localization for mobile autonomous machines,spanning from fundamental principles to future trends.To the best of our knowledge,this review paper stands as the pioneer in systematically dissecting the algorithms of UWB-based localization for mobile autonomous machines,covering a spectrum from bottom-ranging schemes to advanced sensor fusion,error mitigation,and optimization techniques.By synthesizing existing knowledge,evaluating current methodologies,and highlighting future trends,this review aims to catalyze progress and innovation in the field,unlocking new opportunities for mobile autonomous machine applications across diverse industries and domains.Thus,it serves as a valuable resource for researchers,practitioners,and stakeholders interested in advancing the state-of-the-art UWB-based localization for mobile autonomous machines.
文摘The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.
文摘Neurons are highly polarized cells with axons reaching over a meter long in adult humans.To survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and metabolic events,which need to be carried out at the right place,time,and intensity.Such mechanisms include axonal transport,local synthesis,and liquid-liquid phase separations.Alterations and malfunctions in these processes are correlated to neurodegenerative diseases such as amyotrophic lateral sclerosis(ALS).
基金supported by the National Natural Science Foundation of China(Nos.U2441250,62301380,and 62231027)Natural Science Basic Research Program of Shaanxi,China(2024JC-JCQN-63)+3 种基金the Key Research and Development Program of Shaanxi,China(No.2023-YBGY-249)the Guangxi Key Research and Development Program,China(No.2022AB46002)the China Postdoctoral Science Foundation(No.2022M722504 and 2024T170696)the Innovation Capability Support Program of Shaanxi,China(No.2024RS-CXTD-01).
文摘Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)information.This paper proposes a security position verification technique based on Multilateration(MLAT)to detect false signals,ensuring UAV safety and reliable airspace operations.First,the proposed method estimates the current position of the UAV by calculating the Time Difference of Arrival(TDOA),Time Sum of Arrival(TSOA),and Angle of Arrival(AOA)information.Then,this estimated position is compared with the ADS-B message to eliminate false UAV signals.Furthermore,a localization model based on TDOA/TSOA/AOA is established by utilizing reliable reference sources for base station time synchronization.Additionally,an improved Chan-Taylor algorithm is developed,incorporating the Constrained Weighted Least Squares(CWLS)method to initialize UAV position calculations.Finally,a false signal detection method is proposed to distinguish between true and false positioning targets.Numerical simulation results indicate that,at a positioning error threshold of 150 m,the improved Chan-Taylor algorithm based on TDOA/TSOA/AOA achieves 100%accuracy coverage,significantly enhancing localization precision.And the proposed false signal detection method achieves a detection accuracy rate of at least 90%within a 50-meter error range.
基金supported by the project“GEF9874:Strengthening Coordinated Approaches to Reduce Invasive Alien Species(lAS)Threats to Globally Significant Agrobiodiversity and Agroecosystems in China”funding from the Excellent Talent Training Funding Project in Dongcheng District,Beijing,with project number 2024-dchrcpyzz-9.
文摘Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.
基金financially supported by the National Key R &D Program of China (No.2022YFB3709300)。
文摘The local structure and thermophysical behavior of Mg-La liquid alloys were in-depth understood using deep potential molecular dynamic(DPMD) simulation driven via machine learning to promote the development of Mg-La alloys. The robustness of the trained deep potential(DP) model was thoroughly evaluated through several aspects, including root-mean-square errors(RMSEs), energy and force data, and structural information comparison results;the results indicate the carefully trained DP model is reliable. The component and temperature dependence of the local structure in the Mg-La liquid alloy was analyzed. The effect of Mg content in the system on the first coordination shell of the atomic pairs is the same as that of temperature. The pre-peak demonstrated in the structure factor indicates the presence of a medium-range ordered structure in the Mg-La liquid alloy, which is particularly pronounced in the 80at% Mg system and disappears at elevated temperatures. The density, self-diffusion coefficient, and shear viscosity for the Mg-La liquid alloy were predicted via DPMD simulation, the evolution patterns with Mg content and temperature were subsequently discussed, and a database was established accordingly. Finally, the mixing enthalpy and elemental activity of the Mg-La liquid alloy at 1200 K were reliably evaluated,which provides new guidance for related studies.
基金Natural Science Foundation of Gansu Province(23JRRA866)Higher Education Innovation Fund of Gansu Provincial Department of Education(2025A-132)+1 种基金University-level Scientific Research and Innovation Project of Gansu University of Political Science and Law(GZF2024XQN16)Youth Foundation of Lanzhou Jiaotong University(2023023)。
文摘We show that the torsion module Tor_(j)^(R)(R/a,H_(a)^(i)(X))is in a Serre subcategory for the bounded below R-complex X.In addition,we prove the isomorphism Tor_(s-t)^(R)(R/a,X)≅Tor_(s)^(R)(R/a,H_(a)^(t)(X))in some case.As an application,the Betti number of a complex X in a prime ideal p can be computed by the Betti number of the local cohomology modules of X in p.
文摘Finger Knuckle Print biometric plays a vital role in establishing security for real-time environments. The success of human authentication depends on high speed and accuracy. This paper proposed an integrated approach of personal authentication using texture based Finger Knuckle Print (FKP) recognition in multiresolution domain. FKP images are rich in texture patterns. Recently, many texture patterns are proposed for biometric feature extraction. Hence, it is essential to review whether Local Binary Patterns or its variants perform well for FKP recognition. In this paper, Local Directional Pattern (LDP), Local Derivative Ternary Pattern (LDTP) and Local Texture Description Framework based Modified Local Directional Pattern (LTDF_MLDN) based feature extraction in multiresolution domain are experimented with Nearest Neighbor and Extreme Learning Machine (ELM) Classifier for FKP recognition. Experiments were conducted on PolYU database. The result shows that LDTP in Contourlet domain achieves a promising performance. It also proves that Soft classifier performs better than the hard classifier.
