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
Aiming at the mode mixture in local wave decomposition（LWD） caused by a noise signal, the original data is preprocessed using the lifting wavelet transformation to suppress abnormal interference of noise and improve...Aiming at the mode mixture in local wave decomposition（LWD） caused by a noise signal, the original data is preprocessed using the lifting wavelet transformation to suppress abnormal interference of noise and improve the quality of decomposition. It is employed to analyze the vibration signal of rotor rub-impact for extracting the weak impulsive feature. The signal is decomposed into intrinsic mode functions by LWD, then the high-frequency components are analyzed by Hilbert envelop demodulation. The period of the impulse response can be achieved, and the modulate fault feature of the vibration signal of a rotor system with rub-impact fault can be extracted exactly. Analysis results show that the proposed method is accurate and efficient, and is expected to be applied in engineering practice effectively.展开更多
In this paper,the adaptive lifting scheme (ALS) and local gradient maps (LGM) are proposed to isolate the transient feature components from the gearbox vibration signals. Based on entropy minimization rule,the ALS is ...In this paper,the adaptive lifting scheme (ALS) and local gradient maps (LGM) are proposed to isolate the transient feature components from the gearbox vibration signals. Based on entropy minimization rule,the ALS is employed to change properties of an initial wavelet and design adaptive wavelet. Then LGM is applied to characterize the transient feature components in detail signal of decomposition results using ALS. In the present studies, the orthogonal Daubechies 4 (Db 4) wavelet is used as the initial wavelet. The proposed method is applied to both simulated signals and vibration signals acquired from a gearbox for periodic impulses detection. The two conventional methods (cepstrum analysis and Hilbert envelope analysis) and the orthogonal Db4 wavelet are also used to analyze the same signals for comparison. The results demonstrate that the proposed method is more effective in extracting transient components from noisy signals.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
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
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
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
Inhomogeneous Calderon-Zygmund operator T maps each atom into an approximate molecule of weighted local Hardy space if and only if some approximate cancellation condition holds for T.An equivalent norm for weighted Le...Inhomogeneous Calderon-Zygmund operator T maps each atom into an approximate molecule of weighted local Hardy space if and only if some approximate cancellation condition holds for T.An equivalent norm for weighted Lebesgue space which has vanishing moments up to order s plays an important role,where s∈N.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
This work presents a method for the three-dimensional localization of individual shallow NV center in diamond,leveraging the near-field quenching effect of a gold tip.Our experimental setup involves the use of an atom...This work presents a method for the three-dimensional localization of individual shallow NV center in diamond,leveraging the near-field quenching effect of a gold tip.Our experimental setup involves the use of an atomic force microscope to precisely move the gold tip close to the NV center,while simultaneously employing a home-made confocal microscope to monitor the fluorescence of the NV center.This approach allows for lateral super-resolution,achieving a full width at half maximum(FWHM)of 38.0 nm and a location uncertainty of 0.7 nm.Additionally,we show the potential of this method for determining the depth of the NV centers.We also attempt to determine the depth of the NV centers in combination with finite-difference time-domain(FDTD)simulations.Compared to other depth determination methods,this approach allows for simultaneous lateral and longitudinal localization of individual NV centers,and holds promise for facilitating manipulation of the local environment surrounding the NV center.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
In order to contribute to a better understanding of the biodiversity of local chicken populations, this study focused on the description of the essential qualitative parameters in the phenotypic characterization of lo...In order to contribute to a better understanding of the biodiversity of local chicken populations, this study focused on the description of the essential qualitative parameters in the phenotypic characterization of local species. Conducted in 6 localities in the Far North Region of Cameroon (Doukoula, Yagoua, Guidiguis, Dziguilao, Maroua 3rd and Méri), a population of 240 local chickens, including 172 hens and 68 cocks were characterized in family farms. The choice of localities was made on the basis of their strong potential local chicken flocks in the region. To this end, each animal was the subject of a qualitative description based on the identification of the sex of the animal, the description of the colorations of the plumage and extremities, and the description of the types of format, plumage and crests. All observations were made with the naked eye and in daylight and then photographed. The main results show that the plumage colors are multiple and dominated by the White-Pied-Black (21.7%) and the Mille-fleur (20.8%);the wattles are dominated by the red (60%) and the pink (35.4%);the tarsi are dominated by the white (43.8%) and the black (32.08%);the white skin (92.5%) dominates over the pink skin (7.5%);the “Smooth-uniform” feather is dominant (97.08%), followed by the smooth-crested type (2.08%) and the fries type (0.82%);the medium size of the chickens is dominant (86.66%), followed by the dwarf size (9.58%) and the large size (3.75%). The results of this study demonstrate that there is a strong phenotypic diversity within the local chicken population. This diversity can serve as a basis for the development of selection, conservation and genetic potential improvement programs based on rational exploitation of the local chicken.展开更多
Malaria is a potentially lethal disease caused by parasites of the Plasmodium genus, transmitted to humans through the bite of infected female mosquitoes, primarily Anopheles. To control this disease, various strategi...Malaria is a potentially lethal disease caused by parasites of the Plasmodium genus, transmitted to humans through the bite of infected female mosquitoes, primarily Anopheles. To control this disease, various strategies are implemented, including biological control, which targets the vectors of the parasite. This approach uses biological agents such as entomopathogenic fungi, including Metarhizium pingshaense, a fungus capable of causing lethal infections in mosquitoes. The production of Metarhizium pingshaense is still limited in Burkina Faso, and local cultivation of this fungus could help fill this gap. A study was conducted to identify optimal local substrates that promote its growth. Indeed, after gathering information on the dietary habits of populations in Bobo-Dioulasso and Bama, three potential substrates were selected: rice, cornmeal dough (MFL), and beans. These substrates were inoculated with two strains of Metarhizium pingshaense (S10 and S26) to assess their ability to support fungal growth and their effectiveness. Experimental results showed that MFL and bean substrates favored optimal growth of Metarhizium pingshaense, with growths of 1.91 cm and 2.13 cm after 8 days, compared to 1.83 cm on a standard media (PDA). In terms of virulence, S26 strain caused 60% mosquito mortality on both the bean and PDA media, while S10 strain induced mortalities of 50% for bean and 62% for PDA.展开更多
Development of robust electrocatalyst for oxygen reduction reaction(ORR)in a seawater electrolyte is the key to realize seawater electrolyte-based zinc-air batteries(SZABs).Herein,constructing a local electric field c...Development of robust electrocatalyst for oxygen reduction reaction(ORR)in a seawater electrolyte is the key to realize seawater electrolyte-based zinc-air batteries(SZABs).Herein,constructing a local electric field coupled with chloride ions(Cl-)fixation strategy in dual single-atom catalysts(DSACs)was proposed,and the resultant catalyst delivered considerable ORR performance in a seawater electrolyte,with a high half-wave potential(E_(1/2))of 0.868 V and a good maximum power density(Pmax)of 182 mW·cm^(−2)in the assembled SZABs,much higher than those of the Pt/C catalyst(E_(1/2):0.846 V;Pmax:150 mW·cm^(−2)).The in-situ characterization and theoretical calculations revealed that the Fe sites have a higher Cl^(−)adsorption affinity than the Co sites,and preferentially adsorbs Cl^(−)in a seawater electrolyte during the ORR process,and thus constructs a low-concentration Cl^(−)local microenvironment through the common-ion exclusion effect,which prevents Cl^(−)adsorption and corrosion in the Co active centers,achieving impressive catalytic stability.In addition,the directional charge movement between Fe and Co atomic pairs establishes a local electric field,optimizing the adsorption energy of Co sites for oxygen-containing intermediates,and further improving the ORR activity.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
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 National Natural Science Foundation of China under Grant No. 50805014
文摘Aiming at the mode mixture in local wave decomposition（LWD） caused by a noise signal, the original data is preprocessed using the lifting wavelet transformation to suppress abnormal interference of noise and improve the quality of decomposition. It is employed to analyze the vibration signal of rotor rub-impact for extracting the weak impulsive feature. The signal is decomposed into intrinsic mode functions by LWD, then the high-frequency components are analyzed by Hilbert envelop demodulation. The period of the impulse response can be achieved, and the modulate fault feature of the vibration signal of a rotor system with rub-impact fault can be extracted exactly. Analysis results show that the proposed method is accurate and efficient, and is expected to be applied in engineering practice effectively.
基金Higher School Specialized Research Fund for the Doctoral Program Funding Issue(No.2011021120032)Fundamental Research Funds for the Central Universities(No.2012jdhz23)
文摘In this paper,the adaptive lifting scheme (ALS) and local gradient maps (LGM) are proposed to isolate the transient feature components from the gearbox vibration signals. Based on entropy minimization rule,the ALS is employed to change properties of an initial wavelet and design adaptive wavelet. Then LGM is applied to characterize the transient feature components in detail signal of decomposition results using ALS. In the present studies, the orthogonal Daubechies 4 (Db 4) wavelet is used as the initial wavelet. The proposed method is applied to both simulated signals and vibration signals acquired from a gearbox for periodic impulses detection. The two conventional methods (cepstrum analysis and Hilbert envelope analysis) and the orthogonal Db4 wavelet are also used to analyze the same signals for comparison. The results demonstrate that the proposed method is more effective in extracting transient components from noisy signals.
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].
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.
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.
文摘Inhomogeneous Calderon-Zygmund operator T maps each atom into an approximate molecule of weighted local Hardy space if and only if some approximate cancellation condition holds for T.An equivalent norm for weighted Lebesgue space which has vanishing moments up to order s plays an important role,where s∈N.
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.
基金supported by the National Natural Science Foundation of China(T2325023,92265204,12104447)the National Key R&D Program of China(2023YFF0718400)+1 种基金the Innovation Program for Quantum Science and Technology(2021ZD0302200)the Fundamental Research Funds for the Central Universities。
文摘This work presents a method for the three-dimensional localization of individual shallow NV center in diamond,leveraging the near-field quenching effect of a gold tip.Our experimental setup involves the use of an atomic force microscope to precisely move the gold tip close to the NV center,while simultaneously employing a home-made confocal microscope to monitor the fluorescence of the NV center.This approach allows for lateral super-resolution,achieving a full width at half maximum(FWHM)of 38.0 nm and a location uncertainty of 0.7 nm.Additionally,we show the potential of this method for determining the depth of the NV centers.We also attempt to determine the depth of the NV centers in combination with finite-difference time-domain(FDTD)simulations.Compared to other depth determination methods,this approach allows for simultaneous lateral and longitudinal localization of individual NV centers,and holds promise for facilitating manipulation of the local environment surrounding the NV center.
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.
文摘In order to contribute to a better understanding of the biodiversity of local chicken populations, this study focused on the description of the essential qualitative parameters in the phenotypic characterization of local species. Conducted in 6 localities in the Far North Region of Cameroon (Doukoula, Yagoua, Guidiguis, Dziguilao, Maroua 3rd and Méri), a population of 240 local chickens, including 172 hens and 68 cocks were characterized in family farms. The choice of localities was made on the basis of their strong potential local chicken flocks in the region. To this end, each animal was the subject of a qualitative description based on the identification of the sex of the animal, the description of the colorations of the plumage and extremities, and the description of the types of format, plumage and crests. All observations were made with the naked eye and in daylight and then photographed. The main results show that the plumage colors are multiple and dominated by the White-Pied-Black (21.7%) and the Mille-fleur (20.8%);the wattles are dominated by the red (60%) and the pink (35.4%);the tarsi are dominated by the white (43.8%) and the black (32.08%);the white skin (92.5%) dominates over the pink skin (7.5%);the “Smooth-uniform” feather is dominant (97.08%), followed by the smooth-crested type (2.08%) and the fries type (0.82%);the medium size of the chickens is dominant (86.66%), followed by the dwarf size (9.58%) and the large size (3.75%). The results of this study demonstrate that there is a strong phenotypic diversity within the local chicken population. This diversity can serve as a basis for the development of selection, conservation and genetic potential improvement programs based on rational exploitation of the local chicken.
文摘Malaria is a potentially lethal disease caused by parasites of the Plasmodium genus, transmitted to humans through the bite of infected female mosquitoes, primarily Anopheles. To control this disease, various strategies are implemented, including biological control, which targets the vectors of the parasite. This approach uses biological agents such as entomopathogenic fungi, including Metarhizium pingshaense, a fungus capable of causing lethal infections in mosquitoes. The production of Metarhizium pingshaense is still limited in Burkina Faso, and local cultivation of this fungus could help fill this gap. A study was conducted to identify optimal local substrates that promote its growth. Indeed, after gathering information on the dietary habits of populations in Bobo-Dioulasso and Bama, three potential substrates were selected: rice, cornmeal dough (MFL), and beans. These substrates were inoculated with two strains of Metarhizium pingshaense (S10 and S26) to assess their ability to support fungal growth and their effectiveness. Experimental results showed that MFL and bean substrates favored optimal growth of Metarhizium pingshaense, with growths of 1.91 cm and 2.13 cm after 8 days, compared to 1.83 cm on a standard media (PDA). In terms of virulence, S26 strain caused 60% mosquito mortality on both the bean and PDA media, while S10 strain induced mortalities of 50% for bean and 62% for PDA.
基金supported by the National Natural Science Foundation of China(52164028,52274297)the Start-up Research Foundation of Hainan University(KYQD(ZR)20008,KYQD(ZR)21125,KYQD(ZR)23169))+1 种基金Collaborative Innovation Center of Marine Science and Technology of Hainan University(XTCX2022HYC14)Innovative Research Project for Postgraduate Students in Hainan Province(Qhyb2024-95).
文摘Development of robust electrocatalyst for oxygen reduction reaction(ORR)in a seawater electrolyte is the key to realize seawater electrolyte-based zinc-air batteries(SZABs).Herein,constructing a local electric field coupled with chloride ions(Cl-)fixation strategy in dual single-atom catalysts(DSACs)was proposed,and the resultant catalyst delivered considerable ORR performance in a seawater electrolyte,with a high half-wave potential(E_(1/2))of 0.868 V and a good maximum power density(Pmax)of 182 mW·cm^(−2)in the assembled SZABs,much higher than those of the Pt/C catalyst(E_(1/2):0.846 V;Pmax:150 mW·cm^(−2)).The in-situ characterization and theoretical calculations revealed that the Fe sites have a higher Cl^(−)adsorption affinity than the Co sites,and preferentially adsorbs Cl^(−)in a seawater electrolyte during the ORR process,and thus constructs a low-concentration Cl^(−)local microenvironment through the common-ion exclusion effect,which prevents Cl^(−)adsorption and corrosion in the Co active centers,achieving impressive catalytic stability.In addition,the directional charge movement between Fe and Co atomic pairs establishes a local electric field,optimizing the adsorption energy of Co sites for oxygen-containing intermediates,and further improving the ORR activity.
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.
