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Subgroup Analysis of a Single-Index Threshold Penalty Quantile Regression Model Based on Variable Selection 认领 引用 被引量：1
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作者 QI Hui XUE Yaxin 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2025年第2期169-183,共15页
In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This... In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper. 展开更多
关键词 longitudinal data subgroup analysis threshold model quantile regression variable selection
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Using mixed kernel support vector machine to improve the predictive accuracy of genome selection 认领 引用 被引量：2
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作者 Jinbu Wang Wencheng Zong +6 位作者 Liangyu Shi Mianyan Li Jia Li Deming Ren Fuping Zhao Lixian Wang Ligang Wang 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2026年第2期775-787,共13页
The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects acc... The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects accurately.Machine learning models have demonstrated remarkable potential in addressing these challenges.In this study,we introduced the concept of mixed kernel functions to explore the performance of support vector machine regression(SVR) in GS.Six single kernel functions(SVR_L,SVR_C,SVR_G,SVR_P,SVR_S,SVR_L) and four mixed kernel functions(SVR_GS,SVR_GP,SVR_LS,SVR_LP) were used to predict genome breeding values.The prediction accuracy,mean squared error(MSE) and mean absolute error(MAE) were used as evaluation indicators to compare with two traditional parametric models(GBLUP,BayesB) and two popular machine learning models(RF,KcRR).The results indicate that in most cases,the performance of the mixed kernel function model significantly outperforms that of GBLUP,BayesB and single kernel function.For instance,for T1 in the pig dataset,the predictive accuracy of SVR_GS is improved by 10% compared to GBLUP,and by approximately 4.4 and 18.6% compared to SVR_G and SVR_S respectively.For E1 in the wheat dataset,SVR_GS achieves 13.3% higher prediction accuracy than GBLUP.Among single kernel functions,the Laplacian and Gaussian kernel functions yield similar results,with the Gaussian kernel function performing better.The mixed kernel function notably reduces the MSE and MAE when compared to all single kernel functions.Furthermore,regarding runtime,SVR_GS and SVR_GP mixed kernel functions run approximately three times faster than GBLUP in the pig dataset,with only a slight increase in runtime compared to the single kernel function model.In summary,the mixed kernel function model of SVR demonstrates speed and accuracy competitiveness,and the model such as SVR_GS has important application potential for GS. 展开更多
关键词 genome selection machine learning support vector machine kernel function mixed kernel function
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Non-landslide sample for landslide susceptibility prediction modeling:A review of selection strategies and their influence rules 认领 引用 被引量：1
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作者 Zhuo Jia Zhijin Cheng +3 位作者 Zhilu Chang Qin Li Faming Huang Yuhao Peng 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第4期2859-2880,共22页
A proper non-landslide sample selection strategy can improve landslide susceptibility prediction(LSP)accuracy.However,there may be uncertainties regarding the compatibility between different selection strategies and m... A proper non-landslide sample selection strategy can improve landslide susceptibility prediction(LSP)accuracy.However,there may be uncertainties regarding the compatibility between different selection strategies and machine learning models,as well as in the extent of LSP performance enhancement after their coupling.To overcome these uncertainties,this study takes Wuning county of China as a case area,collecting 24 conditioning factors and 379 landslides data.Four non-landslide sample selection strategies,namely random selection,low-slope,buffer zone,and semi-supervised strategies,are then combined with landslide samples in a 1:1 ratio to serve as input variables for constructing LSP models using support vector machine(SVM),logistic regression(LR),random forest(RF)and extreme gradient boosting(XGBoost).Finally,the uncertainty of semi-supervised machine learning coupled models with a 1:2 ratio of landslide to non-landslide samples is analyzed and compared.The results show that:(1)The semi-supervised and low-slope strategies demonstrate higher prediction accuracy compared to the buffer zone and random selection strategies.Moreover,the RF coupled models are the most reliable,followed by the XGBoost,SVM,and LR coupled models;(2)Compared to a 1:1 ratio,a 1:2 ratio of landslide to non-landslide samples significantly improves prediction accuracy,suggesting that appropriately increasing the proportion of non-landslide samples helps to mitigate overfitting and enhance the identification of landslide samples;and(3)LSP is more sensitive to non-landslide sample selection strategies than to the choice of machine learning models.In conclusion,prioritizing reliable non-landslide samples is crucial for improving accuracy of LSP. 展开更多
关键词 Landslide susceptibility prediction Non-landslide sample selection Machine learning models Uncertainty analysis
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OptimizationDesign and Numerical Simulation of Variable Tube Diameter Heat Exchanger for Split Air Conditioning Indoor Unit 认领 引用 被引量：1
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作者 Zheming Cheng Xinping Ou Yang +2 位作者 Leren Tao Zihao Wang Ke Sun 《Frontiers in Heat and Mass Transfer》 EI CAS 2026年第1期288-313,共26页
Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers of... Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost. 展开更多
关键词 Split air condition variable tube diameter enhanced heat transfer numerical simulation structural design optimization
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A data-and expert-driven framework for establishing land cover-related essential variables for SDG monitoring and assessment 认领 引用
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作者 Hao Wu Ping Zhang +6 位作者 Jun Chen Songnian Li Jing Li Shu Peng Dongyang Hou Jun Zhang Hao Chen 《Geography and Sustainability》 CSCD 2026年第1期236-246,共11页
Sustained and spatially explicit monitoring of the United Nations 2030 Agenda for Sustainable Development is critical for effectively tracking progress toward the global Sustainable Development Goals(SDGs).Although la... Sustained and spatially explicit monitoring of the United Nations 2030 Agenda for Sustainable Development is critical for effectively tracking progress toward the global Sustainable Development Goals(SDGs).Although land cover information has long been recognized as an essential component for monitoring SDGs,a standardized scientific framework for identifying and prioritizing land cover related essential variables does not exist.Therefore,we propose a novel expert-and data-driven framework for identifying,refining,and selecting a priority list of Essential Land cover-related Variables for SDGs(ELcV4SDGs).This framework integrates methods including expert knowledge-based analysis,clustering of variables with similar attributes,and quantified index calculation to establish the priority list.Applying the framework to 15 specific SDG indicators,we found that the ELcV4SDGs priority list comprises three main categories,type and structure,pattern and intensity,and process and evolution of land cover,which are further divided into 19 subcategories and ultimately encompass 50 general variables.The ELcV4SDGs will support detailed spatial monitoring and enhance their scientific applications for SDG monitoring and assessment,thereby guiding future SDG priority actions and informing decision-making to advance the 2030 SDGs agenda at local,national,and global levels. 展开更多
关键词 Essential variable Land cover SDG Spatial monitoring and assessment Interactive analysis Refinement and selection
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Breaking the boundaries of affinity selection-mass spectrometry:From ligand screening to target-ligand interaction insights 认领 引用 被引量：1
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作者 Pamella Christina Ortega de Oliveira Bruno Sergio do Amaral +2 位作者 Carmen Lucia Cardoso Quezia Bezerra Cass Marcela Cristina De Moraes 《Journal of Pharmaceutical Analysis》 SCIE CAS CSCD 2026年第2期347-358,共12页
Affinity selection mass spectrometry(AS-MS)has emerged as a powerful label-free technique for identifying and characterizing ligand-target interactions.This review explores the diverse applications of AS-MS in drug di... Affinity selection mass spectrometry(AS-MS)has emerged as a powerful label-free technique for identifying and characterizing ligand-target interactions.This review explores the diverse applications of AS-MS in drug discovery,including its role in selective screening,binding site characterization,and quantitative affinity determination.We discuss the use of AS-MS for determining equilibrium dissociation constants(KD)and competitive binding parameters(affinity competition experiment 50%(ACE50)),highlighting its ability to rank ligand affinities efficiently.The review also examines AS-MS applications in fragment-based drug discovery(FBDD),screening for molecular glues,and investigating interactions with membrane proteins.Moreover,we address key technical challenges,including competitive binding effects,protein stability,and ligand dissociation kinetics,along with recent advancements in automation and artificial intelligence(AI)integration.Rather than providing a comprehensive literature review,this work aims to broaden the applicability of AS-MS assays and encourage researchers to explore its use in underutilized contexts.By providing rapid and high-sensitivity affinity measurements,AS-MS continues to expand its role in drug discovery and structural biology,complementing conventional biophysical techniques. 展开更多
关键词 Affinity selection mass spectrometry Competition assays Drug discovery Fragment screening KD determination Ligand-target interactions Molecular glues
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GENERALIZING SUBDIFFUSIVE BLACK-SCHOLES MODEL BY VARIABLE EXPONENT:MODEL TRANSFORMATION AND NUMERICAL APPROXIMATION 认领 引用
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作者 Meihui ZHANG Yaxue LIU +2 位作者 Mengmeng LIU Wenlin QIU Xiangcheng ZHENG 《Acta Mathematica Scientia》 SCIE CSCD 2026年第2期993-1010,共18页
This work generalizes the subdiffusive Black-Scholes model by introducing the variable exponent in order to provide adequate descriptions for the option pricing,where the variable exponent may account for the variatio... This work generalizes the subdiffusive Black-Scholes model by introducing the variable exponent in order to provide adequate descriptions for the option pricing,where the variable exponent may account for the variation of the memory property.In addition to standard nonlinear-to-linear transformation,we apply a further spatial-temporal transformation to convert the model to a more tractable form in order to circumvent the difficulties caused by the"non-positive,non-monotonic"variable-exponent memory kernel.An interesting phenomenon is that the spatial transformation not only eliminates the advection term but naturally turns the original noncoercive spatial operator into a coercive one due to the specific structure of the Black-Scholes model,which thus avoids imposing constraints on coefficients.Then we perform numerical analysis for both the semi-discrete and fully discrete schemes to support numerical simulation.Numerical experiments are carried out to substantiate the theoretical results. 展开更多
关键词 Black-Scholes model subdiffusion variable exponent error estimate option pricing
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Analysis of bilateral constrained sliding contact problems with variable friction coefficients via a cumulative frictional dissipation approach 认领 引用
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作者 Ling Tao Ling Wang +3 位作者 Ning Hu Shaowei Tong Hong Wen Qingshui Qiu 《Theoretical & Applied Mechanics Letters》 EI CAS CSCD 2026年第2期104-114,共11页
This work investigates the bidirectional relationship between contact mechanics and frictional wear behavior in bilateral constrained sliding contact.An internal state variable representing the contact surface conditi... This work investigates the bidirectional relationship between contact mechanics and frictional wear behavior in bilateral constrained sliding contact.An internal state variable representing the contact surface condition is incorporated into the Coulomb friction law to account for wear phenomena.A contact detection method has been constructed to identify the positional relationship between two elements during contact,leveraging vectorrelated features of the vertices on the contact area between the slideway and the slider.A bipotential function for rigid bilateral constraints is formulated by introducing a stability factor.Combining the potential-Coulomb contact force model,a numerical algorithm is developed for variable friction contact problems on the basis of cumulative frictional dissipation and is initially implemented for rigid body bilateral contact problems.The algorithm is subsequently applied to bilateral constraint analysis in a sliding mechanism under both constant and variable friction conditions,and the influences of the wear and contact clearance factors are studied.The numerical results demonstrate consistency with energy conservation principles and dynamic laws,validating the effectiveness of the proposed algorithm.This work extends the applicability of the bipotential function approach and provides a theoretical foundation and analytical tools for optimizing bilateral nonideal contact structures and predicting equipment service life. 展开更多
关键词 Wear Bilateral constraint Bipotential function Variable friction Frictional dissipation
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A Survey on Rough Feature Selection:Recent Advances and Challenges 认领 引用
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作者 Keyu Liu Xibei Yang +4 位作者 Weiping Ding Hengrong Ju Tianrui Li Jie Wang Tengyu Yin 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第3期521-542,共22页
Advances in data acquisition and accumulation on a massive scale are fueling“the curse of dimensionality”which may deteriorate the generalization performance of machine learning models.Such a dilemma gives birth to ... Advances in data acquisition and accumulation on a massive scale are fueling“the curse of dimensionality”which may deteriorate the generalization performance of machine learning models.Such a dilemma gives birth to the technique of feature selection excelling in the presence of high-dimensional data.As a specific method based on rough set theory,rough feature selection(RFS)has been widely concerned and fruitfully applied.In this survey,we provide a comprehensive review of RFS algorithms that have proliferated in recent years.Firstly,we briefly introduce some typical rough set models especially neighborhood rough set and fuzzy rough set,as well as representative rough feature evaluation criteria.We then systematically discuss several emerging topics of RFS including accelerated,ensemble,incremental,label ambiguous,weakly-supervised,and multi-granularity RFS.Additionally,we illuminate the regular performance validation scheme of RFS and conduct a number of experiments to present benchmarking results of state-of-the-art RFS algorithms.Finally,we summarize the pros and cons of existing research efforts and outline the open challenges and opportunities of class imbalance,multi-modal scenario,causality inference,and highlevel representation for RFS.By providing in-depth knowledge of RFS,we anticipate this survey will:1)serve as a guidebook for newcomers intending to delve into RFS and a stepping-stone for researchers and practitioners to solve domain-specific problems;2)gain insights into the state-of-the-art published findings,triggering a series of breakthroughs in RFS;3)underscore some challenges ahead of RFS,directing future efforts toward punctuating advances beyond questions currently pursued. 展开更多
关键词 Attribute reduction feature selection granular computing rough set theory
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Analytical solution for longitudinal seismic response of variable stiffness tunnel with isolation layers under shear waves 认领 引用
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作者 LIU Xiang YANG Jiao-jiao +3 位作者 LI Kui-chen LU Tong JIANG An-nan FANG Qian 《Journal of Central South University》 SCIE EI CAS CSCD 2026年第6期2844-2867,共24页
Seismic isolation design typically emphasizes transverse responses of tunnels,with comparatively limited research on longitudinal isolation responses.Previous analytical solutions for isolation response are inapplicab... Seismic isolation design typically emphasizes transverse responses of tunnels,with comparatively limited research on longitudinal isolation responses.Previous analytical solutions for isolation response are inapplicable to variable stiffness tunnels.To address research gaps,analytical solutions for longitudinal seismic responses of variable stiffness tunnels with isolation layers are proposed.The solution can be applied to engineering practice.The mechanical model of isolation layers is developed using the Kelvin model.The variable stiffness tunnel is simplified as two semi-infinite beams embedded in homogeneous and isotropic soil layers.Governing equations are solved using integral transformations and continuity conditions.Analytical expressions are obtained by introducing displacement phase angles to simulate traveling wave effects.The proposed analytical solutions are validated through comparisons with results from existing literature and verified using numerical simulations.Parametric sensitivity analyses are conducted to investigate effects of tunnels with and without an isolation layer,isolation layer thickness and elastic modulus,tunnel stiffness ratio,and wavelength and amplitude of shear waves on seismic responses of variable stiffness tunnels.Changes in stiffness have a more significant effect on internal forces than displacements.Additionally,isolation layer's thickness and elastic modulus can be optimized through our method to balance structural performance and economic efficiency. 展开更多
关键词 isolation layer variable stiffness tunnel analytical solution seismic response shear waves
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Aerodynamic characteristics and dual load suppression/trim maintenance method of variable trailing-edge camber rotor 认领 引用
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作者 Xiayang ZHANG Chencheng GAO +1 位作者 Qijun ZHAO Kai ZHANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第7期264-282,共19页
To investigate the unsteady aerodynamic characteristics of rotor with Variable TrailingEdge Camber(VTEC),an unsteady rotor flowfield simulation method is established based on the URANS equation by introducing a deform... To investigate the unsteady aerodynamic characteristics of rotor with Variable TrailingEdge Camber(VTEC),an unsteady rotor flowfield simulation method is established based on the URANS equation by introducing a deformable moving-embedded grid method.The influence mechanisms of variable-camber amplitude Am,frequency k,and phaseφ0 on the unsteady aerodynamic characteristics of rotor are analyzed thoroughly,and whereby a VTEC optimization method is proposed through cross-iteration of variable-camber parameters to achieve the dual objectives of hub load suppression and trim maintenance.The numerical experiments indicate that the k=3 harmonic plays a dominant role in controlling the fluctuation of vertical hub load,which corresponds to the three-bladed rotor.The feasibility of dual load suppressionrim maintenance of VTEC is demonstrated,in which the fluctuation amplitudes of hub loads increments exhibit quasi-linear relationships with Am for k=0-4 and the fluctuation phase of vertical hub load variation shifts synchronously with the adjustment of φ0 for k=2-4.The results demonstrate that the proposed load suppression method can effectively decrease the fundamental 3ev vertical hub load and simultaneously maintain the rotor trim state. 展开更多
关键词 Load suppression Rotor Trim maintenance Unsteady aerodynamic characteristics Variable trailing-edge camber
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Mechanical responses of super-large-span variable cross-section tunnels in weak surrounding rock:A case study and the application of a novel constitutive model 认领 引用
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作者 CAO Wenxin ZHAO Wen +5 位作者 LIU Keqi SHAO Binghua BAI Qian ZHANG Yongfeng LU Bo WANG Yantao 《Journal of Mountain Science》 SCIE CSCD 2026年第6期2835-2855,共21页
Super-large-span and variable cross-section tunnels have proliferated in urban expressway systems across China.However,the deformation behavior and load distribution mechanisms in super-large and variable cross-sectio... Super-large-span and variable cross-section tunnels have proliferated in urban expressway systems across China.However,the deformation behavior and load distribution mechanisms in super-large and variable cross-section tunnels remain inadequately understood.This study systematically analyzed the mechanical response characteristics of super-large-span and variable cross-section tunnels in weak surrounding rock based on extensive field monitoring data.Mechanical tests were conducted to reveal the strain-softening characteristics of weak surrounding rock,and the nonlinear evolution of strength parameters was summarized.Through secondary development,a novel constitutive model based on the Hoek-Brown strength criterion was proposed and successfully implemented in FLAC3D.Furthermore,numerical simulations were conducted using an improved constitutive model.These simulations investigated the evolution of deformation and internal forces within the support system,accounting for the coupled effects of multiple factors.The research shows that the rock pillar compensates for the insufficient stiffness of temporary middle diaphragms.However,it also alters the mechanical behavior of the steel frame system,which leads to significant stress concentrations at the arch shoulders.Additionally,the"asymmetrical loading effect"commonly observed at variable cross-sections substantially impacts the support system within these span transition zones. 展开更多
关键词 Weak surrounding rock Super-large-span tunnel Variable cross-sections Field monitoring Mechanical tests Secondary development
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Analytical solutions on dynamic response of a thin-walled curved beam subjected to two-axle moving load with variable speed 认领 引用
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作者 Xiaoyong Lv Liupeng Li +1 位作者 Zhiwu Yu Peng Liu 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第2期237-251,共15页
This paper proposes the analytical solutions involving damping effects for the dynamic response of a simply supported thin-walled curved beam under uniformly variable two-axle moving loads in four directions:vertical,... This paper proposes the analytical solutions involving damping effects for the dynamic response of a simply supported thin-walled curved beam under uniformly variable two-axle moving loads in four directions:vertical,torsional,radial,and axial.The warping stiffness and damping of the thin-walled beam were comprehensively considered in the vibration control equations.Unlike traditional one-axle load cases,this study employs a more realistic two-axle vehicle load model.Based on the modal superposition method,the control vibration equations for thin-walled curved beams in-plane and out-ofplane under variable speed moving loads were solved using a combination of the Fourier sine transform method,the Galerkin method,and the Laplace transform method.Analytical solutions for the dynamic responses were derived in integral form,facilitating direct numerical computation.The proposed computational method’s effectiveness and accuracy were validated against published research.Subsequently,the dynamic responses of the thin-walled curved beam under one-axle and two-axle moving load models were compared,and the effects of initial load velocity,load acceleration,and center angle of the curved beam on the dynamic responses were investigated through extensive parameter research.The research results provide valuable insights into the structural behavior of thin-walled curved beams under the moving loading with variable speed. 展开更多
关键词 Thin-walled curved beam Dynamic response Variable speed Two-axle moving load Analytical solution
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Seepage on 3D active earth pressure of unsaturated soils considering spatially variable hydraulic properties 认领 引用
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作者 Hui Chen Qihao Jiang +2 位作者 Dongming Zhang Yadong Xue Hongwei Huang 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第5期3949-3965,共17页
Traditional active earth pressure evaluations considering seepage are typically deterministic,assuming uniform soil layers.However,soil hydraulic properties exhibit the obvious spatial variability due to geomorphologi... Traditional active earth pressure evaluations considering seepage are typically deterministic,assuming uniform soil layers.However,soil hydraulic properties exhibit the obvious spatial variability due to geomorphological processes or poor construction control.To address this,the random limit analysis method(RLAM)is employed to investigate the influence of spatial variability of saturated hydraulic conductivity on active earth pressure.To combine random field simulations with the limit analysis based evaluation method,this study discretizes the conventional three-dimensional(3D)rotational failure mechanism.Owing to the energy dissipation principle,the explicit expression of 3D active earth pressures can be derived.The proposed method's validity is demonstrated through comparisons with available analytical solutions,deterministic numerical calculations,and random finite difference method(RFDM).RLAM integrating with Monte Carlo simulations(MCS)in MATLAB,facilitates the probabilistic analysis of the active earth pressure to be evaluated.The findings indicate that the present method not only incorporates the spatial variability of hydraulic properties,but also enhances the computational efficiency of calculating active earth pressures compared to the RFDM.Based on extensive uncertainty analyses,this study proposes a system reliability evaluation method for semi-gravity retaining walls,accounting for the spatial variability of saturated hydraulic conductivity.The results reveal that under different random field design scenarios,all decay curves of system failure probabilities for a semi-gravity retaining wall intersect within a specific range,referred to herein as the“turning region”.Furthermore,as the normalized horizontal autocorrelation distance,anisotropic ratio and coefficient of variation increase,the effective influence zone of the wall design index on system failure probability gradually expands,offering valuable guidance for the design and construction of semi-gravity retaining walls. 展开更多
关键词 Active earth pressure Saturated hydraulic conductivity Random field Spatial variability Retaining wall
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A Fast Algorithm for Matrix-Variable Triconvex Optimization With Application to Blind Image Deblurring 认领 引用
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作者 Songchuan Zhang Liqing Huang +1 位作者 Youshen Xia Jun Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第5期1184-1206,共23页
Matrix-variable triconvex optimization is a significant generalization of vector-variable triconvex or biconvex optimization and has been found to have popular applications.To reduce computation time and storage requi... Matrix-variable triconvex optimization is a significant generalization of vector-variable triconvex or biconvex optimization and has been found to have popular applications.To reduce computation time and storage requirements,this paper presents a matrix-form iterative method for quickly solving matrix-variable constrained triconvex optimization problems.The proposed method is based on a matrix-form alternating projection iteration scheme in the form of matrix state spaces,where an efficient line search strategy is adopted by exploiting the optimality conditions of the problem for a larger step length.Compared with the existing vector-form alternating projection gradient method,the proposed method reduces storage requirements and computational cost,and thus is more computationally efficient.Each sequence generated by the proposed method is guaranteed to be globally convergent to a partial optimum under mild conditions.Finally,the proposed method is effectively applied to blind image deblurring problems.Computed results show that the proposed algorithm is superior to related iterative algorithms in terms of computation time and solution quality. 展开更多
关键词 Blind image deblurring global convergence matrixform iterative method matrix variable multiconvex optimization
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Cathode catalyst-assisted microbial electrosynthesis of acetate from carbon dioxide:promising material selection 认领 引用
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作者 Rujing Lin Xiaomei Zheng +3 位作者 Huai Zhang Yingying He Mingxian Liu Li Xie 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2026年第2期394-404,共11页
As the core of cathode materials,sensitive metals play important roles in the optimization of acetate production from carbon dioxide(CO2)in microbial electrochemical system(MES).In this work,iron(Fe),copper(Cu),and... As the core of cathode materials,sensitive metals play important roles in the optimization of acetate production from carbon dioxide(CO2)in microbial electrochemical system(MES).In this work,iron(Fe),copper(Cu),and nickel(Ni)as sensitive metal cathode materials were evaluated for CO2 conversion in MES.The MES with Feelectrode as a promising electrode material demonstrated a superior CO2 reduction performance with a maximum acetate accumulation of 417.9±39.2 mg/L,which was 1.5 and 1.7 folds higher than that in the Ni-electrode and Cu-electrode groups,respectively.Furthermore,an outstanding electron recovery efficiency of 67.7%was shown in the Fe-electrode group.The electron transfer between electrode-suspended sludge was systematically cross-evaluated by the electrochemical behavior and extracellular polymeric substances.The Fe-electrode group had the highest electron transfer rate with 0.194 s-1(kapp),which was 17.6 and 21.5 times higher than that of the Cu-and Ni-electrode groups,respectively.Fe-electrode was beneficial for reducing electrochemical impedance between the electrode and suspended sludge.Additionally,redox substances in extracellular polymeric substances of the Fe-electrode group were increased,implying more favorable electron transport dynamics.Simultaneously,enrichments of functional bacteria Acetoanerobium and increased key enzymes involved in the carbonyl pathway of the Fe-electrode group were observed,which also promoted CO2 conversion in MES.This study provides a perspective on evaluating the promising sensitive metal electrode material for the process of CO2 valorization in MES and offers a reference for the subsequent electrode modification. 展开更多
关键词 Acetate synthesis Microbial electrochemical system Carbon dioxide fixation Sensitive metal selection Cathode material
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Intelligent Fault Diagnosis of Rolling Bearing With Variable Speed Based on ASTFrFT and Time-Frequency BoTNet Model 认领 引用
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作者 Jie Ma Jun Wei Xinyu Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第7期1761-1763,共3页
Dear Editor,This letter presents an intelligent fault diagnosis method for variable speed rolling bearings based on the adaptive short-time fractional Fourier transform(ASTFrFT)and the time-frequency BoTNet(TFB)to add... Dear Editor,This letter presents an intelligent fault diagnosis method for variable speed rolling bearings based on the adaptive short-time fractional Fourier transform(ASTFrFT)and the time-frequency BoTNet(TFB)to address the challenge of extracting fault characteristics of rolling bearings under variable speed conditions and the poor classification of classical deep learning models.Firstly,to address the limitations of FrFT in time-varying signal processing,the physical mechanism of traditional STFT is extended into the FrFT domain by minimizing fuzzy entropy values to construct the order matrix. 展开更多
关键词 variable speed rolling bearings time frequency botnet rolling bearings deep learning modelsfirstlyto variable speed adaptive short time fractional fourier transform extracting fault characteristics intelligent fault diagnosis
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GSLDWOA: A Feature Selection Algorithm for Intrusion Detection Systems in IIoT 认领 引用
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作者 Wanwei Huang Huicong Yu +3 位作者 Jiawei Ren Kun Wang Yanbu Guo Lifeng Jin 《Computers, Materials & Continua》 SCIE EI 2026年第1期2006-2029,共24页
Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from... Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%. 展开更多
关键词 Industrial Internet of Things intrusion detection system feature selection whale optimization algorithm Gaussian mutation
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Progress in local-variable-based transition-turbulence models for subsonic and transonic boundary layers 认领 引用
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作者 Jiakuan XU Xi JIANG +3 位作者 Yutian WANG Ningjuan DONG Lei QIAO Junqiang BAI 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第4期26-53,共28页
The accurate prediction of boundary layer transition represents a persistent and extensively studied challenge in fluid mechanics and aircraft aerodynamic design.It is well recognized that,due to the limitations in co... The accurate prediction of boundary layer transition represents a persistent and extensively studied challenge in fluid mechanics and aircraft aerodynamic design.It is well recognized that,due to the limitations in computational efficiency and shape complexity,high-resolution numerical simulation techniques and classical stability theory are hard to be applied in the numerical simulation and optimization of complex aircraft designs.The classical correlation-based Langtry and Menter model and laminar kinetic energy model,incorporating stability analysis results,offer efficient solution strategies under the Reynolds-averaged Navier-Stokes framework.Nonetheless,these models rely heavily on the range of available experimental data,which significantly restricts their applicability.Therefore,the Amplification Factor Transport(AFT)transition model anchored in linear stability theory foundations was derived from the findings of Coder and Maughmer and has since been adopted for transition prediction across a variety of complex geometries.This model not only incorporates the analytical foundation of linear stability theory,but also predicts the maximum envelope N value through a transport equation.It enables all non-local variables to be solved locally,ensuring compatibility with massively parallel computational fluid dynamics solvers.This paper systematically introduces the modeling concepts and key variable solution strategies of the currently prevalent transition-turbulence models based on local variables.It emphasizes the evolution of AFT transition frameworks,highlighting their progression from applications in the transition from 2D to 3D compressible boundary layer Tollmien-Schlichting waves,together with the formation of stationary crossflow vortices.In conclusion,this paper addresses the remaining challenges of the amplification factor transport transition model and explores potential directions for its future development. 展开更多
关键词 Boundary layer transition Computational fluid dynamics Linear stability theory Local variable Transition-turbulence model
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Genomic selection and genome-wide association studies using UAV-derived plant height and aboveground biomass of maize 认领 引用
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作者 Kai Zhou Yuxin Jiao +14 位作者 Guangning Yu Xin Wang Weijun Zhang Shaolong Zhu Yuxiang Zhang Wenyan Yang Shujun Hu Xinyi Wang Yulin Yin Ziqiu Wang Xuecai Zhang Zefeng Yang Tao Liu Chenwu Xu Yang Xu 《The Crop Journal》 SCIE CSCD 2026年第4期1318-1329,共12页
Plant height(PH)and aboveground biomass(AGB)are critical agronomic traits that determine the yield potential of maize(Zea mays L.).However,the application of genomic selection(GS)and genome-wide association studies(GW... Plant height(PH)and aboveground biomass(AGB)are critical agronomic traits that determine the yield potential of maize(Zea mays L.).However,the application of genomic selection(GS)and genome-wide association studies(GWAS)in maize breeding is often hindered by the limitations of phenotypic data collection,which is typically characterized by low throughput and inadequate accuracy.To address this challenge,we employed an unmanned aerial vehicle(UAV)equipped with LiDAR and RGB cameras for high-throughput assessment of PH and AGB in a panel of 817 maize hybrids derived from 364 inbred lines over two growing seasons.Our results demonstrated that the integration of UAV-derived LiDAR point clouds with crop surface models(CSMs)enabled robust estimation of PH across multiple years(R2>0.90).Furthermore,a three-dimensional AGB estimation model was developed using UAVderived PH and canopy coverage(CC),achieving high estimation accuracy(R2>0.83).Subsequently,the UAV-derived PH and AGB were utilized for GS and GWAS analyses.Replicated 10-fold crossvalidation showed that the mean predictability was 0.504 for PH and 0.402 for AGB across eight commonly used GS models.Moreover,of the 66,066 potential crosses derived from the 364 inbred lines,the top 200 crosses selected for AGB showed up to twice the AGB of the bottom 200 crosses.Field validation demonstrated that the mean ear weight(EW)in the AGB top group was 39.0% higher than that in the bottom group.A total of 16 and 11 significant SNPs were identified by at least two GWAS methods for PH and AGB,respectively.Based on these SNPs,81 candidate genes were functionally annotated,six of which were simultaneously associated with both traits.The candidate gene association analysis suggested that variations in the promoter region of ZmFLA9 may affect both traits.Overall,our study highlights the potential of UAV-based high-throughput phenotyping to accelerate maize genomic breeding by enabling rapid,precise,and large-scale trait assessment. 展开更多
关键词 Unmanned aerial vehicle Plant height Aboveground biomass Genomic selection Genome-wide association studies
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