Jianguang Lu
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View article: TMolNet: A Task-Aware Multimodal Neural Network for Molecular Property Prediction
TMolNet: A Task-Aware Multimodal Neural Network for Molecular Property Prediction Open
Molecular property prediction plays a vital role in drug discovery, materials science, and chemical biology. Although molecular data are intrinsically multi-modal—comprising 1D sequences or fingerprints, 2D topological graphs, and 3D geome…
View article: Identification and factor analysis of rocky desertification severity levels in large-scale karst areas based on deep learning image segmentation
Identification and factor analysis of rocky desertification severity levels in large-scale karst areas based on deep learning image segmentation Open
Land rocky desertification (RD) is one of the most serious environmental disasters in karst landforms. Identifying the rocky desertification severity level (RDSL) is a key task in the prevention and control projects of rocky desertificatio…
View article: Molecular subgraph representation learning based on spatial structure transformer
Molecular subgraph representation learning based on spatial structure transformer Open
In the field of molecular biology, graph representation learning is crucial for molecular structure analysis. However, challenges arise in recognising functional groups and distinguishing isomers due to a lack of spatial structure informat…
View article: An imbalanced learning method based on graph tran-smote for fraud detection
An imbalanced learning method based on graph tran-smote for fraud detection Open
View article: Spatial-temporal graph neural ODE networks for skeleton-based action recognition
Spatial-temporal graph neural ODE networks for skeleton-based action recognition Open
View article: Physics-Informed Neural Networks for Solving High-Index Differential-Algebraic Equation Systems Based on Radau Methods
Physics-Informed Neural Networks for Solving High-Index Differential-Algebraic Equation Systems Based on Radau Methods Open
As is well known, differential algebraic equations (DAEs), which are able to describe dynamic changes and underlying constraints, have been widely applied in engineering fields such as fluid dynamics, multi-body dynamics, mechanical system…
View article: Dual convolutional network based on hypergraph and multilevel feature fusion for road extraction from high-resolution remote sensing images
Dual convolutional network based on hypergraph and multilevel feature fusion for road extraction from high-resolution remote sensing images Open
Road extraction from high-resolution remote sensing images (HRSI) is confronted with the challenge that roads are occluded by other objects, including opaque obstructions and similarly colored areas. This paper proposes a dual convolutiona…
View article: Spatial-Temporal Graph Neural Ode Networks for Skeleton-Based Action Recognition
Spatial-Temporal Graph Neural Ode Networks for Skeleton-Based Action Recognition Open
View article: Physical Information Neural Networks for Solving High-index Differential-algebraic Equation Systems Based on Radau Methods
Physical Information Neural Networks for Solving High-index Differential-algebraic Equation Systems Based on Radau Methods Open
As is well known, differential algebraic equations (DAEs), which are able to describe dynamic changes and underlying constraints, have been widely applied in engineering fields such as fluid dynamics, multi-body dynamics, mechanical system…
View article: Modified Extended Lie-Group Method for Hessenberg Differential Algebraic Equations with Index-3
Modified Extended Lie-Group Method for Hessenberg Differential Algebraic Equations with Index-3 Open
Hessenberg differential algebraic equations (Hessenberg-DAEs) with a high index play a critical role in the modeling of mechanical systems and multibody dynamics. Motivated by the widely used Lie-group differential algebraic equation (LGDA…
View article: Modified Extended Lie Group Method for Hessenberg Differential Algebraic Equations with Index 3
Modified Extended Lie Group Method for Hessenberg Differential Algebraic Equations with Index 3 Open
Hessenberg differential algebraic equations (Hessenberg-DAEs) with high index play a critical role in the modeling of mechanical systems and multibody dynamics. Motivated by the widely used Lie Group Differential Algebraic Equation (LGDAE)…
View article: Optimization of Magnetically Coupled Resonant Wireless Power Transfer Based on Improved Whale Optimization Algorithm
Optimization of Magnetically Coupled Resonant Wireless Power Transfer Based on Improved Whale Optimization Algorithm Open
This study aimed to address the optimization of magnetically coupled resonant wireless power transfer. An equivalent circuit for the wireless power transfer was established and the factors affecting the transmission efficiency were analyze…
View article: Process Study on the Enzyme-Catalyzed Preparation of Key Chiral Intermediates for Saxagliptin
Process Study on the Enzyme-Catalyzed Preparation of Key Chiral Intermediates for Saxagliptin Open
Saxagliptin is a therapeutic drug for diabetes. The key synthesis process of the drug involves catalyzing 2-(3-hydroxy-1-adamantyl)-2-oxoacetic acid (A) into (S)-3-hydroxyadamantane glycine (B), during which enzymes phenylalanine dehydroge…
View article: Exosomal lncRNA HOTAIR induce macrophages to M2 polarization via PI3K/ p-AKT /AKT pathway and promote EMT and metastasis in laryngeal squamous cell carcinoma
Exosomal lncRNA HOTAIR induce macrophages to M2 polarization via PI3K/ p-AKT /AKT pathway and promote EMT and metastasis in laryngeal squamous cell carcinoma Open
View article: Stochastic Approximate Algorithms for Uncertain Constrained K-Means Problem
Stochastic Approximate Algorithms for Uncertain Constrained K-Means Problem Open
The k-means problem has been paid much attention for many applications. In this paper, we define the uncertain constrained k-means problem and propose a (1+ϵ)-approximate algorithm for the problem. First, a general mathematical model of th…
View article: A Novel Bearing Fault Diagnosis Method Based on GL-mRMR-SVM
A Novel Bearing Fault Diagnosis Method Based on GL-mRMR-SVM Open
A convolutional neural network (CNN) has been used to successfully realize end-to-end bearing fault diagnosis due to its powerful feature extraction ability. However, the CNN is prone to focus on local information, ignoring the relationshi…
View article: Nanodetection of Head and Neck Cancer on Titanium Oxide Sensing Surface
Nanodetection of Head and Neck Cancer on Titanium Oxide Sensing Surface Open
Head and neck cancer is a heterogeneous disease, originating in the squamous cells lining the larynx (voice box), mouth, pharynx (throat), nasal cavity and salivary glands. Head and neck cancer diagnosis at the later stage is greatly influ…
View article: A Bearing Fault Diagnosis Method Based on Feature Selection Feedback Network and Improved D-S Evidence Fusion
A Bearing Fault Diagnosis Method Based on Feature Selection Feedback Network and Improved D-S Evidence Fusion Open
Bearings running state affects the normal operation of mechanical equipment. It is of great theoretical and practical value to carry out bearing fault diagnosis. In bearing fault diagnosis research, the extraction and selection of fault fe…
View article: A Novel Method for Intelligent Single Fault Detection of Bearings Using SAE and Improved D–S Evidence Theory
A Novel Method for Intelligent Single Fault Detection of Bearings Using SAE and Improved D–S Evidence Theory Open
In order to realize single fault detection (SFD) from the multi-fault coupling bearing data and further research on the multi-fault situation of bearings, this paper proposes a method based on features self-extraction of a Sparse Auto-Enco…
View article: Improving Bearing Fault Diagnosis Using Maximum Information Coefficient Based Feature Selection
Improving Bearing Fault Diagnosis Using Maximum Information Coefficient Based Feature Selection Open
Effective feature selection can help improve the classification performance in bearing fault diagnosis. This paper proposes a novel feature selection method based on bearing fault diagnosis called Feature-to-Feature and Feature-to-Category…
View article: An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis
An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis Open
Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis approaches mostly depend on expert-designed features for building prediction models.…
View article: Co-inhibition of miRNA-21 and miRNA-221 induces apoptosis by enhancing the p53-mediated expression of pro-apoptotic miRNAs in laryngeal squamous cell carcinoma
Co-inhibition of miRNA-21 and miRNA-221 induces apoptosis by enhancing the p53-mediated expression of pro-apoptotic miRNAs in laryngeal squamous cell carcinoma Open
Dysregulation of a numerous microRNAs (miRNAs) has been implicated in laryngeal squamous cell carcinoma (LSCC). Among those miRNAs, miR‑21 and miR‑221 are co‑overexpressed and commonly target the phosphatase and tensin homolog protein (PTE…
View article: Cyr61/CCN1 Overexpression Induces Epithelial-Mesenchymal Transition Leading to Laryngeal Tumor Invasion and Metastasis and Poor Prognosis
Cyr61/CCN1 Overexpression Induces Epithelial-Mesenchymal Transition Leading to Laryngeal Tumor Invasion and Metastasis and Poor Prognosis Open
Cyr61 expression is closely associated with LSCC invasion and lymph node metastasis. Overexpression of Cyr61 may induce EMT and therefore leads to LSCC invasion and metastasis and poor prognosis. Cyr61 may become a new maker for clinical p…