3-Amino-N-benzyl-6-(4-fluoro­phen­yl)thieno[2,3-b]pyridine-2-carboxamide

In the title compound, C21H16FN3OS, the thieno[2,3-b]pyridine system forms dihedral angles of 10.57 (12) and 83.87 (5)° with the fluoro­phenyl ring at the 6-position and the phenyl ring of the benzyl group, respectively. In the crystal, mol­ecules are linked by weak N—H⋯N anf N—H⋯O hydrogen bonds and π–π stacking inter­actions involving fluoro­phenyl rings of adjacent mol­ecules, with a centroid–centroid distance of 3.648 (10) Å. In addition, intra­molecular N—H⋯S and N—H⋯O hydrogen bonds contribute to the stability of the mol­ecular conformation

VIGraph: Self-supervised Learning for Class-Imbalanced Node Classification

Class imbalance in graph data poses significant challenges for node classification. Existing methods, represented by SMOTE-based approaches, partially alleviate this issue but still exhibit limitations during imbalanced scenario construction. Self-supervised learning (SSL) offers a promising solution by synthesizing minority nodes from the data itself, yet its potential remains unexplored. In this paper, we analyze the limitations of SMOTE-based approaches and introduce VIGraph, a novel SSL model based on the self-supervised Variational Graph Auto-Encoder (VGAE) that leverages Variational Inference (VI) to generate minority nodes. Specifically, VIGraph strictly adheres to the concept of imbalance when constructing imbalanced graphs and utilizes the generative VGAE to generate minority nodes. Moreover, VIGraph introduces a novel Siamese contrastive strategy at the decoding phase to improve the overall quality of generated nodes. VIGraph can generate high-quality nodes without reintegrating them into the original graph, eliminating the "Generating, Reintegrating, and Retraining" process found in SMOTE-based methods. Experiments on multiple real-world datasets demonstrate that VIGraph achieves promising results for class-imbalanced node classification tasks

A novel approach for 3D discrete element modelling the progressive delamination in unidirectional CFRP composites

This study proposed a novel approach based on the 3D discrete element method (DEM) to simulate the progressive delamination in unidirectional carbon fibre reinforced polymer (CFRP) composite laminates. A hexagonal packing strategy was used for modelling 0∘ representative plies, the interface between different plies was modelled with one bond and seven bonds following the conservation of energy principle and a power law. The number of representative layers and the stiffness of bonds within these layers were calibrated with a comparison of results obtained from finite element method and theoretical analysis. DEM simulations of delamination with both interface models were conducted on unidirectional composites for double cantilever beam (DCB), end-loaded split (ELS) and fixed-ratio mixed-mode (FRMM) tests. It was found that the seven-bond interface model has a better agreement with experimental data in all three tests than the one-bond interface model by adopting the proposed seven-bond arrangement in terms of the progressive delamination process. The main advantages of the present interface model are its simplicity, robustness and computational efficiency when elastic bonds are used in the DEM models

Methyl 6-chloro­nicotinate

The mol­ecule of the title compound, C7H6ClNO2, is almost planar, with a dihedral angle of 3.34 (14)° between the COOMe group and the aromatic ring. In the crystal, the mol­ecules are arranged into (12) layers by C—H⋯N hydrogen bonds and there are π–π stacking inter­actions between the aromatic rings in adjacent layers [centroid–centroid distance 3.8721 (4) Å