Rice metallothionein-like protein (rgMT) shows characteristics of a three-section pattern composed of two highly conserved cysteine rich (CR) domains in the terminals and a spacer without cysteine (cys) residues in th...Rice metallothionein-like protein (rgMT) shows characteristics of a three-section pattern composed of two highly conserved cysteine rich (CR) domains in the terminals and a spacer without cysteine (cys) residues in the center of the molecule. In this paper, the two CR domains and the spacer region were modeled by the distance geometry and homology methods separately. For the CR domains, twenty random models were generated for each cys combination based on the constraint conditions of CXC (C represents cys, X represents any amino acid other than cys), and CXXC motifs and a metal-sulfur chelating cluster. Four models for the N-terminal and two for C-terminal CR domain containing metal chelating structures formed by different combinations of cys were selected from 900 possible conformations. The GOR method was used to predict the secondary structure of the spacer region and its model was built by the homology method. After three parts of the protein were modeled, they were connected to form a three-dimensional structure model of rgMT. The whole conformation showed that rgMT could form two independent metal-sulfur chelating structures connected by a spacer peptide, without a structural or energy barrier for them to form two independent metal-chelating clusters just as mammalian metallothionein (MT) proteins. As all plant metallothionein-like (MT-L) proteins have the same primary structural characteristic, two CR domains connected by a spacer region, and many have the same cys arrangement pattern as rgMT, the three-dimensional structure model of rgMT will provide an important reference for the structural study of other plant MT-L proteins.展开更多
A kind of improved contact frictional model on basis of traditional Coulomb Friction model is adopted.Corresponding contact element is also given.The contact algorithm on basis of augmented Lagrange method is introduc...A kind of improved contact frictional model on basis of traditional Coulomb Friction model is adopted.Corresponding contact element is also given.The contact algorithm on basis of augmented Lagrange method is introduced and successfully applied to complex contact friction problem.Test example and actual engineering case all show that the algorithm of the model is efficient and computation results agree well with general rules.展开更多
The equivalent source(ES)method in the spherical coordinate system has been widely applied to processing,reduction,field modeling,and geophysical and geological interpretation of satellite magnetic anomaly data.Howeve...The equivalent source(ES)method in the spherical coordinate system has been widely applied to processing,reduction,field modeling,and geophysical and geological interpretation of satellite magnetic anomaly data.However,the inversion for the ES model suffers from nonuniqueness and instability,which remain unresolved.To mitigate these issues,we introduce both the minimum and flattest models into the model objective function as an alternative regularization approach in the spherical ES method.We first present the methods,then analyze the accuracy of forward calculation and test the proposed ES method in this study by using synthetic data.The experimental results from simulation data indicate that our proposed regularization effectively suppresses the Backus effect and mitigates inversion instability in the low-latitude region.Finally,we apply the proposed method to magnetic anomaly data from China Seismo-Electromagnetic Satellite-1(CSES-1)and Macao Science Satellite-1(MSS-1)magnetic measurements over Africa by constructing an ES model of the large-scale lithospheric magnetic field.Compared with existing global lithospheric magnetic field models,our ES model demonstrates good consistency at high altitudes and predicts more stable fields at low altitudes.Furthermore,we derive the reduction to the pole(RTP)magnetic anomaly fields and the apparent susceptibility contrast distribution based on the ES model.The latter correlates well with the regional tectonic framework in Africa and surroundings.展开更多
Trend forecasting is an important aspect in fault diagnosis and work state supervision. The principle, where Grey theory is applied in fault forecasting, is that the forecast system is considered as a Grey system; the...Trend forecasting is an important aspect in fault diagnosis and work state supervision. The principle, where Grey theory is applied in fault forecasting, is that the forecast system is considered as a Grey system; the existing known information is used to infer the unknown information's character, state and development trend in a fault pattern, and to make possible forecasting and decisions for future development. It involves the whitenization of a Grey process. But the traditional equal time interval Grey GM (1,1) model requires equal interval data and needs to bring about accumulating addition generation and reversion calculations. Its calculation is very complex. However, the non equal interval Grey GM (1,1) model decreases the condition of the primitive data when establishing a model, but its requirement is still higher and the data were pre processed. The abrasion primitive data of plant could not always satisfy these modeling requirements. Therefore, it establishes a division method suited for general data modeling and estimating parameters of GM (1,1), the standard error coefficient that was applied to judge accuracy height of the model was put forward; further, the function transform to forecast plant abrasion trend and assess GM (1,1) parameter was established. These two models need not pre process the primitive data. It is not only suited for equal interval data modeling, but also for non equal interval data modeling. Its calculation is simple and convenient to use. The oil spectrum analysis acted as an example. The two GM (1,1) models put forward in this paper and the new information model and its comprehensive usage were investigated. The example shows that the two models are simple and practical, and worth expanding and applying in plant fault diagnosis.展开更多
This paper aims to solve the resonance failure probability and develop an effective method to estimate the effects of variables and failure modes on failure probability of axially functionally graded material(FGM)pipe...This paper aims to solve the resonance failure probability and develop an effective method to estimate the effects of variables and failure modes on failure probability of axially functionally graded material(FGM)pipe conveying fluid.Correspondingly,the natural frequency of axially FGM pipes conveying fluid is calculated using the differential quadrature method(DQM).A variable sensitivity analysis(VSA)is introduced to measure the effect of each random variable,and a mode sensitivity analysis(MSA)is introduced to acquire the importance ranking of failure modes.Then,an active learning Kriging(ALK)method is established to calculate the resonance failure probability and sensitivity indices,which greatly improves the application of resonance reliability analysis for pipelines in engineering practice.Based on the resonance reliability analysis method,the effects of fluid velocity,volume fraction and fluid density of axially FGM pipe conveying fluid on resonance reliability are analyzed.The results demonstrate that the proposed method has great performance in the anti-resonance analysis of pipes conveying fluid.展开更多
This study introduces a comprehensive theoretical framework for accurately calculating the electronic band-structure of strained long-wavelength InAs/GaSb type-Ⅱsuperlattices.Utilizing an eight-band k·p Hamilto⁃...This study introduces a comprehensive theoretical framework for accurately calculating the electronic band-structure of strained long-wavelength InAs/GaSb type-Ⅱsuperlattices.Utilizing an eight-band k·p Hamilto⁃nian in conjunction with a scattering matrix method,the model effectively incorporates quantum confinement,strain effects,and interface states.This robust and numerically stable approach achieves exceptional agreement with experimental data,offering a reliable tool for analyzing and engineering the band structure of complex multi⁃layer systems.展开更多
Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie conditio...Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie condition.Hanging crossties usually yield unfavorable dynamic effects such as higher wheel loads,which negatively impact the serviceability and safety of railway operations.Hence,a better understanding of the mechanisms that cause hanging crossties and their effects on the ballast layer load-deformation characteristics is necessary.Since the ballast layer is a particulate medium,the discrete element method(DEM),which simulates ballast particle interactions individually,is ideal to explore the interparticle contact forces and ballast movements under dynamic wheel loading.Accurate representations of the dynamic loads from the train and track superstructure are needed for high-fidelity DEM modeling.This paper introduces an integrated modeling approach,which couples a single-crosstie DEM ballast model with a train–track–bridge(TTB)model using a proportional–integral–derivative control loop.The TTB–DEM model was validated with field measurements,and the coupled model calculates similar crosstie displacements as the TTB model.The TTB–DEM provided new insights into the ballast particle-scale behavior,which the TTB model alone cannot explore.The TTB–DEM coupling approach identified detrimental effects of hanging crossties on adjacent crossties,which were found to experience drastic vibrations and large ballast contact force concentrations.展开更多
Software systems are vulnerable to security breaches as they expand in complexity and functionality.The confidentiality,integrity,and availability of data are gravely threatened by flaws in a system’s design,implemen...Software systems are vulnerable to security breaches as they expand in complexity and functionality.The confidentiality,integrity,and availability of data are gravely threatened by flaws in a system’s design,implementation,or configuration.To guarantee the durability&robustness of the software,vulnerability identification and fixation have become crucial areas of focus for developers,cybersecurity experts and industries.This paper presents a thorough multi-phase mathematical model for efficient patch management and vulnerability detection.To uniquely model these processes,the model incorporated the notion of the learning phenomenon in describing vulnerability fixation using a logistic learning function.Furthermore,the authors have used numerical methods to approximate the solution of the proposed framework where an analytical solution is difficult to attain.The suggested systematic architecture has been demonstrated through statistical analysis using patch datasets,which offers a solid basis for the research conclusions.According to computational research,learning dynamics improves security response and results in more effective vulnerability management.The suggested model offers a systematic approach to proactive vulnerability mitigation and has important uses in risk assessment,software maintenance,and cybersecurity.This study helps create more robust software systems by increasing patch management effectiveness,which benefits developers,cybersecurity experts,and sectors looking to reduce security threats in a growing digital world.展开更多
In this paper,we propose a multiphysics finite element method for a nonlinear poroelasticity model with nonlinear stress-strain relation.Firstly,we reformulate the original problem into a new coupled fluid system-a ge...In this paper,we propose a multiphysics finite element method for a nonlinear poroelasticity model with nonlinear stress-strain relation.Firstly,we reformulate the original problem into a new coupled fluid system-a generalized nonlinear Stokes problem of displacement vector field related to pseudo pressure and a diffusion problem of other pseudo pressure fields.Secondly,a fully discrete multiphysics finite element method is performed to solve the reformulated system numerically.Thirdly,existence and uniqueness of the weak solution of the reformulated model and stability analysis and optimal convergence order for the multiphysics finite element method are proven theoretically.Lastly,numerical tests are given to verify the theoretical results.展开更多
The topology structure of the artificial neural network is an intelligent control model,which is used for the intelligent vehicle control system and household sweeping robot.When setting the intelligent control system...The topology structure of the artificial neural network is an intelligent control model,which is used for the intelligent vehicle control system and household sweeping robot.When setting the intelligent control system,the connection point of each network is regarded as a neuron in the nervous system,and each connection point has input and output functions.Only when the input of nodes reaches a certain threshold can the output function of nodes be stimulated.Using the networking mode of the artificial neural network model,the mobile node can output in multiple directions.If the input direction of a certain path is the same as that of other nodes,it can choose to avoid and choose another path.The weighted value of each path between nodes is different,which means that the influence of the front node on the current node varies.The control method based on the artificial neural network model can be applied to vehicle control,household sweeping robots,and other fields,and a relatively optimized scheme can be obtained from the aspect of time and energy consumption.展开更多
With the raising complexity of modern civil aircraft,both academy and industry have shown strong interests on MBSE(Model-Based System Engineering).However,following the application of MBSE,the duration of the design p...With the raising complexity of modern civil aircraft,both academy and industry have shown strong interests on MBSE(Model-Based System Engineering).However,following the application of MBSE,the duration of the design phase exceeded expectations.This paper conducted a survey to the relevant participants involved in the design,revealed that a lack of proper process management is a critical issue.The current MBSE methodology does not provide clear guidelines for monitoring,controlling,and managing processes,which are crucial for both efficiency and effectiveness.To address this,the present paper introduced an improved Process Model(PM)within the MBSE framework for civil aircraft design.This improved model incorporates three new Management Blocks(MB):Progress Management Block(PMB),Review Management Block(RMB),and Configuration Management Block(CMB),developed based on the Capability Maturity Model Integration(CMMI).These additions aim to streamline the design process and better align it with engineering practices.The upgraded MBSE method with the improved PM offers a more structured approach to manage complex aircraft design projects,and a case study is conducted to validate its potential to reduce timelines and enhance overall project outcomes.展开更多
WITHDRAWAL:Zhang,J.J.,Guo,Y.Q.,Qin,Z.Y.,Wei,C.T.,Hu,Q.H.,Vandeginste,V.,Miao,H.Y.,Yao,P.,and Zhang,P.F.,“Predicting Irreducible Water Saturation of Unconventional Reservoirs by Using NMR T2 Spectra:Methods of Morphol...WITHDRAWAL:Zhang,J.J.,Guo,Y.Q.,Qin,Z.Y.,Wei,C.T.,Hu,Q.H.,Vandeginste,V.,Miao,H.Y.,Yao,P.,and Zhang,P.F.,“Predicting Irreducible Water Saturation of Unconventional Reservoirs by Using NMR T2 Spectra:Methods of Morphological Division and Fractal Models”,Acta Geologica Sinica-English Edition(Accepted Article):https://doi.org/10.1111/1755-6724.15094.展开更多
With the increasing accuracy requirements of satellite magnetic detection missions,reducing low-frequency noise has become a key focus of satellite magnetic cleanliness technology.Traditional satellite magnetic simula...With the increasing accuracy requirements of satellite magnetic detection missions,reducing low-frequency noise has become a key focus of satellite magnetic cleanliness technology.Traditional satellite magnetic simulation methods have matured in static magnetic dipole simulations,but there is still significant room for optimization in the simulation and computation of low-frequency magnetic dipole models.This study employs the Gauss-Newton method and Fourier transform techniques for modeling and simulating low-frequency magnetic dipoles.Compared to the traditional particle swarm optimization(PSO)algorithm,this method achieves significant improvements,with errors reaching the order of10^(-13)%under noise-free conditions and maintaining an error level of less than 0.5%under 10%noise.Additionally,the use of Fourier transform and the Gauss-Newton method enables high-precision magnetic field frequency identification and rapid computation of the dipole position and magnetic moment,greatly enhancing the computational efficiency and accuracy of the model.展开更多
Accurate prediction of coal and gas outburst(CGO)hazards is paramount in gas disaster prevention and control.This paper endeavors to overcome the constraints posed by traditional prediction indexes when dealing with C...Accurate prediction of coal and gas outburst(CGO)hazards is paramount in gas disaster prevention and control.This paper endeavors to overcome the constraints posed by traditional prediction indexes when dealing with CGO incidents under low gas pressure conditions.In pursuit of this objective,we have studied and established a mechanical model of the working face under abnormal stress and the excitation energy conditions of CGO,and proposed a method for predicting the risk of CGO under abnormal stress.On site application verification shows that when a strong outburst hazard level prediction is issued,there is a high possibility of outburst disasters occurring.In one of the three locations where we predicted strong outburst hazards,a small outburst occurred,and the accuracy of the prediction was higher than the traditional drilling cuttings index S and drilling cuttings gas desorption index q.Finally,we discuss the mechanism of CGO under the action of stress anomalies.Based on the analysis of stress distribution changes and energy accumulation characteristics of coal under abnormal stress,this article believes that the increase in outburst risk caused by high stress abnormal gradient is mainly due to two reasons:(1)The high stress abnormal gradient leads to an increase in the plastic zone of the coal seam.After the working face advances,it indirectly leads to an increase in the gas expansion energy that can be released from the coal seam before reaching a new stress equilibrium.(2)Abnormal stress leads to increased peak stress of coal body in front of working face.When coal body in elastic area transforms to plastic area,its failure speed is accelerated,which induces accelerated gas desorption and aggravates the risk of outburst.展开更多
We propose a novel workflow for fast forward modeling of well logs in axially symmetric 2D models of the nearwellbore environment.The approach integrates the finite element method with deep residual neural networks to...We propose a novel workflow for fast forward modeling of well logs in axially symmetric 2D models of the nearwellbore environment.The approach integrates the finite element method with deep residual neural networks to achieve exceptional computational efficiency and accuracy.The workflow is demonstrated through the modeling of wireline electromagnetic propagation resistivity logs,where the measured responses exhibit a highly nonlinear relationship with formation properties.The motivation for this research is the need for advanced modeling al-gorithms that are fast enough for use in modern quantitative interpretation tools,where thousands of simulations may be required in iterative inversion processes.The proposed algorithm achieves a remarkable enhancement in performance,being up to 3000 times faster than the finite element method alone when utilizing a GPU.While still ensuring high accuracy,this makes it well-suited for practical applications when reliable payzone assessment is needed in complex environmental scenarios.Furthermore,the algorithm’s efficiency positions it as a promising tool for stochastic Bayesian inversion,facilitating reliable uncertainty quantification in subsurface property estimation.展开更多
Objective:To explore the application value of a new empowerment teaching method based on Kirkpatrick’s evaluation model in teaching Chinese medicine nursing in otorhinolaryngology.Methods:60 nurses who practiced in t...Objective:To explore the application value of a new empowerment teaching method based on Kirkpatrick’s evaluation model in teaching Chinese medicine nursing in otorhinolaryngology.Methods:60 nurses who practiced in the otolaryngology department of our hospital from June 2022 to October 2024 were included in the study and equally divided into two groups using a convenient sampling method.30 nurses who chose traditional Chinese medicine skill teaching management were included in the control group,and 30 nurses who chose the new empowerment teaching method based on Kirkpatrick’s evaluation model were included in the observation group.Relevant indicators such as clinical teaching environment perception,theoretical knowledge scores of Chinese medicine nursing,and excellent rate of practical operation assessment were compared.Results:The nurses in the observation group had higher scores for clinical teaching environment perception than the control group(P<0.05).However,the midterm and final exam scores for theoretical knowledge of Chinese medicine nursing were higher in the observation group than in the control group(P<0.05).Compared with the control group,the observation group had a higher excellent rate of practical operation assessment(93.33%>73.33%)and a higher Chinese medicine nursing ability score[(215.69±19.73)points>(184.87±15.66)points](P<0.05).Conclusion:Applying the new empowerment teaching method based on Kirkpatrick’s evaluation model to Chinese medicine nursing teaching in otolaryngology can help nurses understand the theoretical knowledge of Chinese medicine nursing and optimize the clinical teaching environment,thereby promoting their practical skills and Chinese medicine nursing abilities.展开更多
Effective and efficient SAR image segmentation has a significant role in coastal zone interpretation. In this paper, a coastal zone segmentation model is proposed based on Potts model. By introducing edge self-adaptio...Effective and efficient SAR image segmentation has a significant role in coastal zone interpretation. In this paper, a coastal zone segmentation model is proposed based on Potts model. By introducing edge self-adaption parameter and modifying noisy data term, the proposed variational model provides a good solution for the coastal zone SAR image with common characteristics of inherent speckle noise and complicated geometrical details. However, the proposed model is difficult to solve due to to its nonlinear, non-convex and non-smooth characteristics. Followed by curve evolution theory and operator splitting method, the minimization problem is reformulated as a constrained minimization problem. A fast alternating minimization iterative scheme is designed to implement coastal zone segmentation. Finally, various two-stage and multiphase experimental results illustrate the advantage of the proposed segmentation model, and indicate the high computation efficiency of designed numerical approximation algorithm.展开更多
In this study,a powerful thermo-hydro-mechanical(THM)coupling solution scheme for saturated poroelastic media involving brittle fracturing is developed.Under the local thermal non-equilibrium(LTNE)assumption,this sche...In this study,a powerful thermo-hydro-mechanical(THM)coupling solution scheme for saturated poroelastic media involving brittle fracturing is developed.Under the local thermal non-equilibrium(LTNE)assumption,this scheme seamlessly combines the material point method(MPM)for accurately tracking solid-phase deformation and heat transport,and the Eulerian finite element method(FEM)for effectively capturing fluid flow and heat advection-diffusion behavior.The proposed approach circumvents the substantial challenges posed by large nonlinear equation systems with the monolithic solution scheme.The staggered solution process strategically separates each physical field through explicit or implicit integration.The characteristic-based method is used to stabilize advection-dominated heat flows for efficient numerical implementation.Furthermore,a fractional step approach is employed to decompose fluid velocity and pressure,thereby suppressing pore pressure oscillation on the linear background grid.The fracturing initiation and propagation are simulated by a rate-dependent phase field model.Through a series of quasi-static and transient simulations,the exceptional performance and promising potential of the proposed model in addressing THM fracturing problems in poro-elastic media is demonstrated.展开更多
During fully mechanized caving mining of thick coal seams,a large amount of strain energy accumulates in the roof,especially when the roof is thick and hard,making it difficultfor the roof to collapse naturally.When t...During fully mechanized caving mining of thick coal seams,a large amount of strain energy accumulates in the roof,especially when the roof is thick and hard,making it difficultfor the roof to collapse naturally.When the roof eventually collapses,the accumulated energy is released instantaneously,exerting a strong impact on the roadway.To address this issue,we proposed the synergistic control method of directional comprehensive pressure relief and energy-absorbing support(PREA)for roadways with hard roofs.In this study,we developed a three-dimensional physical model test apparatus for roof cutting and pressure relief.The 122108 ventilation roadway at the Caojiatan Coal Mine,which has a thick and hard roof,was taken as the engineering example.We analyzed the evolution patterns of stress and displacement in both the stope and the roadway surrounding rocks under different schemes.The PREA reinforcement mechanism for the roadway was investigated through comparative model tests between the new and original methods.The results showed that,compared to the original method,the new method reduced surrounding rock stress by up to 60.4%,and the roadway convergence decreased by up to 52.1%.Based on these results,we proposed corresponding engineering recommendations,which can guide fieldreinforcement design and application.The results demonstrate that the PREA method effectively reduces stress and ensures the safety and stability of the roadway.展开更多
With the development of the Semantic Web,the number of ontologies grows exponentially and the semantic relationships between ontologies become more and more complex,understanding the true semantics of specific terms o...With the development of the Semantic Web,the number of ontologies grows exponentially and the semantic relationships between ontologies become more and more complex,understanding the true semantics of specific terms or concepts in an ontology is crucial for the matching task.At present,the main challenges facing ontology matching tasks based on representation learning methods are how to improve the embedding quality of ontology knowledge and how to integrate multiple features of ontology efficiently.Therefore,we propose an Ontology Matching Method Based on the Gated Graph Attention Model(OM-GGAT).Firstly,the semantic knowledge related to concepts in the ontology is encoded into vectors using the OWL2Vec^(*)method,and the relevant path information from the root node to the concept is embedded to understand better the true meaning of the concept itself and the relationship between concepts.Secondly,the ontology is transformed into the corresponding graph structure according to the semantic relation.Then,when extracting the features of the ontology graph nodes,different attention weights are assigned to each adjacent node of the central concept with the help of the attention mechanism idea.Finally,gated networks are designed to further fuse semantic and structural embedding representations efficiently.To verify the effectiveness of the proposed method,comparative experiments on matching tasks were carried out on public datasets.The results show that the OM-GGAT model can effectively improve the efficiency of ontology matching.展开更多
文摘Rice metallothionein-like protein (rgMT) shows characteristics of a three-section pattern composed of two highly conserved cysteine rich (CR) domains in the terminals and a spacer without cysteine (cys) residues in the center of the molecule. In this paper, the two CR domains and the spacer region were modeled by the distance geometry and homology methods separately. For the CR domains, twenty random models were generated for each cys combination based on the constraint conditions of CXC (C represents cys, X represents any amino acid other than cys), and CXXC motifs and a metal-sulfur chelating cluster. Four models for the N-terminal and two for C-terminal CR domain containing metal chelating structures formed by different combinations of cys were selected from 900 possible conformations. The GOR method was used to predict the secondary structure of the spacer region and its model was built by the homology method. After three parts of the protein were modeled, they were connected to form a three-dimensional structure model of rgMT. The whole conformation showed that rgMT could form two independent metal-sulfur chelating structures connected by a spacer peptide, without a structural or energy barrier for them to form two independent metal-chelating clusters just as mammalian metallothionein (MT) proteins. As all plant metallothionein-like (MT-L) proteins have the same primary structural characteristic, two CR domains connected by a spacer region, and many have the same cys arrangement pattern as rgMT, the three-dimensional structure model of rgMT will provide an important reference for the structural study of other plant MT-L proteins.
文摘A kind of improved contact frictional model on basis of traditional Coulomb Friction model is adopted.Corresponding contact element is also given.The contact algorithm on basis of augmented Lagrange method is introduced and successfully applied to complex contact friction problem.Test example and actual engineering case all show that the algorithm of the model is efficient and computation results agree well with general rules.
基金supported by the National Natural Science Foundation of China(Grant Nos.42250103 and 42174090)the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(Grant No.GLAB2023ZR02)the MOST Special Fund from the State Key Laboratory of Geological Processes and Mineral Resources(Grant No.MSFGPMR2022-4).
文摘The equivalent source(ES)method in the spherical coordinate system has been widely applied to processing,reduction,field modeling,and geophysical and geological interpretation of satellite magnetic anomaly data.However,the inversion for the ES model suffers from nonuniqueness and instability,which remain unresolved.To mitigate these issues,we introduce both the minimum and flattest models into the model objective function as an alternative regularization approach in the spherical ES method.We first present the methods,then analyze the accuracy of forward calculation and test the proposed ES method in this study by using synthetic data.The experimental results from simulation data indicate that our proposed regularization effectively suppresses the Backus effect and mitigates inversion instability in the low-latitude region.Finally,we apply the proposed method to magnetic anomaly data from China Seismo-Electromagnetic Satellite-1(CSES-1)and Macao Science Satellite-1(MSS-1)magnetic measurements over Africa by constructing an ES model of the large-scale lithospheric magnetic field.Compared with existing global lithospheric magnetic field models,our ES model demonstrates good consistency at high altitudes and predicts more stable fields at low altitudes.Furthermore,we derive the reduction to the pole(RTP)magnetic anomaly fields and the apparent susceptibility contrast distribution based on the ES model.The latter correlates well with the regional tectonic framework in Africa and surroundings.
文摘Trend forecasting is an important aspect in fault diagnosis and work state supervision. The principle, where Grey theory is applied in fault forecasting, is that the forecast system is considered as a Grey system; the existing known information is used to infer the unknown information's character, state and development trend in a fault pattern, and to make possible forecasting and decisions for future development. It involves the whitenization of a Grey process. But the traditional equal time interval Grey GM (1,1) model requires equal interval data and needs to bring about accumulating addition generation and reversion calculations. Its calculation is very complex. However, the non equal interval Grey GM (1,1) model decreases the condition of the primitive data when establishing a model, but its requirement is still higher and the data were pre processed. The abrasion primitive data of plant could not always satisfy these modeling requirements. Therefore, it establishes a division method suited for general data modeling and estimating parameters of GM (1,1), the standard error coefficient that was applied to judge accuracy height of the model was put forward; further, the function transform to forecast plant abrasion trend and assess GM (1,1) parameter was established. These two models need not pre process the primitive data. It is not only suited for equal interval data modeling, but also for non equal interval data modeling. Its calculation is simple and convenient to use. The oil spectrum analysis acted as an example. The two GM (1,1) models put forward in this paper and the new information model and its comprehensive usage were investigated. The example shows that the two models are simple and practical, and worth expanding and applying in plant fault diagnosis.
基金The funding was provided by Laboratory Fund (Grant No.SYJJ200320).
文摘This paper aims to solve the resonance failure probability and develop an effective method to estimate the effects of variables and failure modes on failure probability of axially functionally graded material(FGM)pipe conveying fluid.Correspondingly,the natural frequency of axially FGM pipes conveying fluid is calculated using the differential quadrature method(DQM).A variable sensitivity analysis(VSA)is introduced to measure the effect of each random variable,and a mode sensitivity analysis(MSA)is introduced to acquire the importance ranking of failure modes.Then,an active learning Kriging(ALK)method is established to calculate the resonance failure probability and sensitivity indices,which greatly improves the application of resonance reliability analysis for pipelines in engineering practice.Based on the resonance reliability analysis method,the effects of fluid velocity,volume fraction and fluid density of axially FGM pipe conveying fluid on resonance reliability are analyzed.The results demonstrate that the proposed method has great performance in the anti-resonance analysis of pipes conveying fluid.
文摘This study introduces a comprehensive theoretical framework for accurately calculating the electronic band-structure of strained long-wavelength InAs/GaSb type-Ⅱsuperlattices.Utilizing an eight-band k·p Hamilto⁃nian in conjunction with a scattering matrix method,the model effectively incorporates quantum confinement,strain effects,and interface states.This robust and numerically stable approach achieves exceptional agreement with experimental data,offering a reliable tool for analyzing and engineering the band structure of complex multi⁃layer systems.
基金a U.S. Federal Railroad Administration (FRA)BAA project,titled “Mitigation of Differential Movement at Railway Transitions for High-Speed Passenger Rail and Joint Passenger/Freight Corridors”the financial support provided by the China Scholarship Council (CSC),which funded Zhongyi Liu’s and Wenjing Li’s time and research efforts for this study
文摘Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie condition.Hanging crossties usually yield unfavorable dynamic effects such as higher wheel loads,which negatively impact the serviceability and safety of railway operations.Hence,a better understanding of the mechanisms that cause hanging crossties and their effects on the ballast layer load-deformation characteristics is necessary.Since the ballast layer is a particulate medium,the discrete element method(DEM),which simulates ballast particle interactions individually,is ideal to explore the interparticle contact forces and ballast movements under dynamic wheel loading.Accurate representations of the dynamic loads from the train and track superstructure are needed for high-fidelity DEM modeling.This paper introduces an integrated modeling approach,which couples a single-crosstie DEM ballast model with a train–track–bridge(TTB)model using a proportional–integral–derivative control loop.The TTB–DEM model was validated with field measurements,and the coupled model calculates similar crosstie displacements as the TTB model.The TTB–DEM provided new insights into the ballast particle-scale behavior,which the TTB model alone cannot explore.The TTB–DEM coupling approach identified detrimental effects of hanging crossties on adjacent crossties,which were found to experience drastic vibrations and large ballast contact force concentrations.
基金supported by grants received by the first author and third author from the Institute of Eminence,Delhi University,Delhi,India,as part of the Faculty Research Program via Ref.No./IoE/2024-25/12/FRP.
文摘Software systems are vulnerable to security breaches as they expand in complexity and functionality.The confidentiality,integrity,and availability of data are gravely threatened by flaws in a system’s design,implementation,or configuration.To guarantee the durability&robustness of the software,vulnerability identification and fixation have become crucial areas of focus for developers,cybersecurity experts and industries.This paper presents a thorough multi-phase mathematical model for efficient patch management and vulnerability detection.To uniquely model these processes,the model incorporated the notion of the learning phenomenon in describing vulnerability fixation using a logistic learning function.Furthermore,the authors have used numerical methods to approximate the solution of the proposed framework where an analytical solution is difficult to attain.The suggested systematic architecture has been demonstrated through statistical analysis using patch datasets,which offers a solid basis for the research conclusions.According to computational research,learning dynamics improves security response and results in more effective vulnerability management.The suggested model offers a systematic approach to proactive vulnerability mitigation and has important uses in risk assessment,software maintenance,and cybersecurity.This study helps create more robust software systems by increasing patch management effectiveness,which benefits developers,cybersecurity experts,and sectors looking to reduce security threats in a growing digital world.
基金Supported by the National Natural Science Foundation of China(Grant Nos.12371393,11971150 and 11801143)Natural Science Foundation of Henan Province(Grant No.242300421047).
文摘In this paper,we propose a multiphysics finite element method for a nonlinear poroelasticity model with nonlinear stress-strain relation.Firstly,we reformulate the original problem into a new coupled fluid system-a generalized nonlinear Stokes problem of displacement vector field related to pseudo pressure and a diffusion problem of other pseudo pressure fields.Secondly,a fully discrete multiphysics finite element method is performed to solve the reformulated system numerically.Thirdly,existence and uniqueness of the weak solution of the reformulated model and stability analysis and optimal convergence order for the multiphysics finite element method are proven theoretically.Lastly,numerical tests are given to verify the theoretical results.
文摘The topology structure of the artificial neural network is an intelligent control model,which is used for the intelligent vehicle control system and household sweeping robot.When setting the intelligent control system,the connection point of each network is regarded as a neuron in the nervous system,and each connection point has input and output functions.Only when the input of nodes reaches a certain threshold can the output function of nodes be stimulated.Using the networking mode of the artificial neural network model,the mobile node can output in multiple directions.If the input direction of a certain path is the same as that of other nodes,it can choose to avoid and choose another path.The weighted value of each path between nodes is different,which means that the influence of the front node on the current node varies.The control method based on the artificial neural network model can be applied to vehicle control,household sweeping robots,and other fields,and a relatively optimized scheme can be obtained from the aspect of time and energy consumption.
基金supported by the National Natural Science Foundation of China(No.62073267)。
文摘With the raising complexity of modern civil aircraft,both academy and industry have shown strong interests on MBSE(Model-Based System Engineering).However,following the application of MBSE,the duration of the design phase exceeded expectations.This paper conducted a survey to the relevant participants involved in the design,revealed that a lack of proper process management is a critical issue.The current MBSE methodology does not provide clear guidelines for monitoring,controlling,and managing processes,which are crucial for both efficiency and effectiveness.To address this,the present paper introduced an improved Process Model(PM)within the MBSE framework for civil aircraft design.This improved model incorporates three new Management Blocks(MB):Progress Management Block(PMB),Review Management Block(RMB),and Configuration Management Block(CMB),developed based on the Capability Maturity Model Integration(CMMI).These additions aim to streamline the design process and better align it with engineering practices.The upgraded MBSE method with the improved PM offers a more structured approach to manage complex aircraft design projects,and a case study is conducted to validate its potential to reduce timelines and enhance overall project outcomes.
文摘WITHDRAWAL:Zhang,J.J.,Guo,Y.Q.,Qin,Z.Y.,Wei,C.T.,Hu,Q.H.,Vandeginste,V.,Miao,H.Y.,Yao,P.,and Zhang,P.F.,“Predicting Irreducible Water Saturation of Unconventional Reservoirs by Using NMR T2 Spectra:Methods of Morphological Division and Fractal Models”,Acta Geologica Sinica-English Edition(Accepted Article):https://doi.org/10.1111/1755-6724.15094.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFC2206003)。
文摘With the increasing accuracy requirements of satellite magnetic detection missions,reducing low-frequency noise has become a key focus of satellite magnetic cleanliness technology.Traditional satellite magnetic simulation methods have matured in static magnetic dipole simulations,but there is still significant room for optimization in the simulation and computation of low-frequency magnetic dipole models.This study employs the Gauss-Newton method and Fourier transform techniques for modeling and simulating low-frequency magnetic dipoles.Compared to the traditional particle swarm optimization(PSO)algorithm,this method achieves significant improvements,with errors reaching the order of10^(-13)%under noise-free conditions and maintaining an error level of less than 0.5%under 10%noise.Additionally,the use of Fourier transform and the Gauss-Newton method enables high-precision magnetic field frequency identification and rapid computation of the dipole position and magnetic moment,greatly enhancing the computational efficiency and accuracy of the model.
基金supported by the National Natural Science Foundation of China(52174162)the Fundamental Research Funds for the Central Universities(FRF-TP-20-002A3).
文摘Accurate prediction of coal and gas outburst(CGO)hazards is paramount in gas disaster prevention and control.This paper endeavors to overcome the constraints posed by traditional prediction indexes when dealing with CGO incidents under low gas pressure conditions.In pursuit of this objective,we have studied and established a mechanical model of the working face under abnormal stress and the excitation energy conditions of CGO,and proposed a method for predicting the risk of CGO under abnormal stress.On site application verification shows that when a strong outburst hazard level prediction is issued,there is a high possibility of outburst disasters occurring.In one of the three locations where we predicted strong outburst hazards,a small outburst occurred,and the accuracy of the prediction was higher than the traditional drilling cuttings index S and drilling cuttings gas desorption index q.Finally,we discuss the mechanism of CGO under the action of stress anomalies.Based on the analysis of stress distribution changes and energy accumulation characteristics of coal under abnormal stress,this article believes that the increase in outburst risk caused by high stress abnormal gradient is mainly due to two reasons:(1)The high stress abnormal gradient leads to an increase in the plastic zone of the coal seam.After the working face advances,it indirectly leads to an increase in the gas expansion energy that can be released from the coal seam before reaching a new stress equilibrium.(2)Abnormal stress leads to increased peak stress of coal body in front of working face.When coal body in elastic area transforms to plastic area,its failure speed is accelerated,which induces accelerated gas desorption and aggravates the risk of outburst.
基金financially supported by the Russian federal research project No.FWZZ-2022-0026“Innovative aspects of electro-dynamics in problems of exploration and oilfield geophysics”.
文摘We propose a novel workflow for fast forward modeling of well logs in axially symmetric 2D models of the nearwellbore environment.The approach integrates the finite element method with deep residual neural networks to achieve exceptional computational efficiency and accuracy.The workflow is demonstrated through the modeling of wireline electromagnetic propagation resistivity logs,where the measured responses exhibit a highly nonlinear relationship with formation properties.The motivation for this research is the need for advanced modeling al-gorithms that are fast enough for use in modern quantitative interpretation tools,where thousands of simulations may be required in iterative inversion processes.The proposed algorithm achieves a remarkable enhancement in performance,being up to 3000 times faster than the finite element method alone when utilizing a GPU.While still ensuring high accuracy,this makes it well-suited for practical applications when reliable payzone assessment is needed in complex environmental scenarios.Furthermore,the algorithm’s efficiency positions it as a promising tool for stochastic Bayesian inversion,facilitating reliable uncertainty quantification in subsurface property estimation.
文摘Objective:To explore the application value of a new empowerment teaching method based on Kirkpatrick’s evaluation model in teaching Chinese medicine nursing in otorhinolaryngology.Methods:60 nurses who practiced in the otolaryngology department of our hospital from June 2022 to October 2024 were included in the study and equally divided into two groups using a convenient sampling method.30 nurses who chose traditional Chinese medicine skill teaching management were included in the control group,and 30 nurses who chose the new empowerment teaching method based on Kirkpatrick’s evaluation model were included in the observation group.Relevant indicators such as clinical teaching environment perception,theoretical knowledge scores of Chinese medicine nursing,and excellent rate of practical operation assessment were compared.Results:The nurses in the observation group had higher scores for clinical teaching environment perception than the control group(P<0.05).However,the midterm and final exam scores for theoretical knowledge of Chinese medicine nursing were higher in the observation group than in the control group(P<0.05).Compared with the control group,the observation group had a higher excellent rate of practical operation assessment(93.33%>73.33%)and a higher Chinese medicine nursing ability score[(215.69±19.73)points>(184.87±15.66)points](P<0.05).Conclusion:Applying the new empowerment teaching method based on Kirkpatrick’s evaluation model to Chinese medicine nursing teaching in otolaryngology can help nurses understand the theoretical knowledge of Chinese medicine nursing and optimize the clinical teaching environment,thereby promoting their practical skills and Chinese medicine nursing abilities.
基金supported by the China Postdoctoral Science Foundation under Grant No.2015M571993the Shandong Provincial Natural Science Foundation,China under Grant No.ZR2017MD004+1 种基金the National Natural Science Foundation of China under Grant No.61602269Qingdao Postdoctoral Application Research Funded Project
文摘Effective and efficient SAR image segmentation has a significant role in coastal zone interpretation. In this paper, a coastal zone segmentation model is proposed based on Potts model. By introducing edge self-adaption parameter and modifying noisy data term, the proposed variational model provides a good solution for the coastal zone SAR image with common characteristics of inherent speckle noise and complicated geometrical details. However, the proposed model is difficult to solve due to to its nonlinear, non-convex and non-smooth characteristics. Followed by curve evolution theory and operator splitting method, the minimization problem is reformulated as a constrained minimization problem. A fast alternating minimization iterative scheme is designed to implement coastal zone segmentation. Finally, various two-stage and multiphase experimental results illustrate the advantage of the proposed segmentation model, and indicate the high computation efficiency of designed numerical approximation algorithm.
基金supported by National Natural Science Foundation of China(Grant No.42377149)the Research Grants Council of Hong Kong(General Research Fund Project No.17202423).
文摘In this study,a powerful thermo-hydro-mechanical(THM)coupling solution scheme for saturated poroelastic media involving brittle fracturing is developed.Under the local thermal non-equilibrium(LTNE)assumption,this scheme seamlessly combines the material point method(MPM)for accurately tracking solid-phase deformation and heat transport,and the Eulerian finite element method(FEM)for effectively capturing fluid flow and heat advection-diffusion behavior.The proposed approach circumvents the substantial challenges posed by large nonlinear equation systems with the monolithic solution scheme.The staggered solution process strategically separates each physical field through explicit or implicit integration.The characteristic-based method is used to stabilize advection-dominated heat flows for efficient numerical implementation.Furthermore,a fractional step approach is employed to decompose fluid velocity and pressure,thereby suppressing pore pressure oscillation on the linear background grid.The fracturing initiation and propagation are simulated by a rate-dependent phase field model.Through a series of quasi-static and transient simulations,the exceptional performance and promising potential of the proposed model in addressing THM fracturing problems in poro-elastic media is demonstrated.
基金supported by the National Natural Science Foundation of China(Grant Nos.U24A2088 and 42277174)the Fundamental Research Funds for the Central Universities,China(Grant No.2024JCCXSB01).
文摘During fully mechanized caving mining of thick coal seams,a large amount of strain energy accumulates in the roof,especially when the roof is thick and hard,making it difficultfor the roof to collapse naturally.When the roof eventually collapses,the accumulated energy is released instantaneously,exerting a strong impact on the roadway.To address this issue,we proposed the synergistic control method of directional comprehensive pressure relief and energy-absorbing support(PREA)for roadways with hard roofs.In this study,we developed a three-dimensional physical model test apparatus for roof cutting and pressure relief.The 122108 ventilation roadway at the Caojiatan Coal Mine,which has a thick and hard roof,was taken as the engineering example.We analyzed the evolution patterns of stress and displacement in both the stope and the roadway surrounding rocks under different schemes.The PREA reinforcement mechanism for the roadway was investigated through comparative model tests between the new and original methods.The results showed that,compared to the original method,the new method reduced surrounding rock stress by up to 60.4%,and the roadway convergence decreased by up to 52.1%.Based on these results,we proposed corresponding engineering recommendations,which can guide fieldreinforcement design and application.The results demonstrate that the PREA method effectively reduces stress and ensures the safety and stability of the roadway.
基金supported by the National Natural Science Foundation of China(grant numbers 62267005 and 42365008)the Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing.
文摘With the development of the Semantic Web,the number of ontologies grows exponentially and the semantic relationships between ontologies become more and more complex,understanding the true semantics of specific terms or concepts in an ontology is crucial for the matching task.At present,the main challenges facing ontology matching tasks based on representation learning methods are how to improve the embedding quality of ontology knowledge and how to integrate multiple features of ontology efficiently.Therefore,we propose an Ontology Matching Method Based on the Gated Graph Attention Model(OM-GGAT).Firstly,the semantic knowledge related to concepts in the ontology is encoded into vectors using the OWL2Vec^(*)method,and the relevant path information from the root node to the concept is embedded to understand better the true meaning of the concept itself and the relationship between concepts.Secondly,the ontology is transformed into the corresponding graph structure according to the semantic relation.Then,when extracting the features of the ontology graph nodes,different attention weights are assigned to each adjacent node of the central concept with the help of the attention mechanism idea.Finally,gated networks are designed to further fuse semantic and structural embedding representations efficiently.To verify the effectiveness of the proposed method,comparative experiments on matching tasks were carried out on public datasets.The results show that the OM-GGAT model can effectively improve the efficiency of ontology matching.
