Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification

Multiple kernel learning (MKL) method is generally believed to perform better than single kernel method. However, some empirical studies show that this is not always true: the combination of multiple kernels may even yield an even worse performance than using a single kernel. There are two possible reasons for the failure: (i) most existing MKL methods assume that the optimal kernel is a linear combination of base kernels, which may not hold true; and (ii) some kernel weights are inappropriately assigned due to noises and carelessly designed algorithms. In this paper, we propose a novel MKL framework by following two intuitive assumptions: (i) each kernel is a perturbation of the consensus kernel; and (ii) the kernel that is close to the consensus kernel should be assigned a large weight. Impressively, the proposed method can automatically assign an appropriate weight to each kernel without introducing additional parameters, as existing methods do. The proposed framework is integrated into a unified framework for graph-based clustering and semi-supervised classification. We have conducted experiments on multiple benchmark datasets and our empirical results verify the superiority of the proposed framework.Comment: Accepted by IJCAI 2018, Code is availabl

Finite element simulation of deformation behavior of prefabricated holes in ultra-heavy plates by gradient temperature rolling

Based on the Deform-3D finite element simulation software, the numerical analysis of prefabricated holes in the core of ultra-heavy plates is carried out in different rolling schemes. In this paper, the deformation of the hole in core under uniform temperature rolling (UTR) is compared by different gradient temperature rolling (GTR) processes. The results show that the GTR can improve the core deformation compared with the UTR. The increase of the number of water cooling can accelerate the welding of the core holes and the healing of the final gap, and multi-pass watercooled GTR should be used for ultra-heavy plate rolling

Finite element simulation of deformation behavior of prefabricated holes in ultra-heavy plates by gradient temperature rolling

Based on the Deform-3D finite element simulation software, the numerical analysis of prefabricated holes in the core of ultra-heavy plates is carried out in different rolling schemes. In this paper, the deformation of the hole in core under uniform temperature rolling (UTR) is compared by different gradient temperature rolling (GTR) processes. The results show that the GTR can improve the core deformation compared with the UTR. The increase of the number of water cooling can accelerate the welding of the core holes and the healing of the final gap, and multi-pass watercooled GTR should be used for ultra-heavy plate rolling

Numerical simulation of the influence of welding direction on residual stress after double welding of Q345 stacked-plates

Based on the welding numerical simulation software Visual-environment, this paper calculates and analyzes the residual stress field for the double pass welding of Q345 stacked plates. The paper mainly studies the influence of different welding directions on the residual stress after welding. The results show that different welding methods have little effect on the lateral residual stress, while the longitudinal residual stress and the initial and end of the weld have a greater influence, while the post-weld residual stress distribution of the anisotropic two-pass weld is more uniform

NMI inhibits cancer stem cell traits by downregulating hTERT in breast cancer.

N-myc and STAT interactor (NMI) has been proved to bind to different transcription factors to regulate a variety of signaling mechanisms including DNA damage, cell cycle and epithelial-mesenchymal transition. However, the role of NMI in the regulation of cancer stem cells (CSCs) remains poorly understood. In this study, we investigated the regulation of NMI on CSCs traits in breast cancer and uncovered the underlying molecular mechanisms. We found that NMI was lowly expressed in breast cancer stem cells (BCSCs)-enriched populations. Knockdown of NMI promoted CSCs traits while its overexpression inhibited CSCs traits, including the expression of CSC-related markers, the number of CD44+CD24- cell populations and the ability of mammospheres formation. We also found that NMI-mediated regulation of BCSCs traits was at least partially realized through the modulation of hTERT signaling. NMI knockdown upregulated hTERT expression while its overexpression downregulated hTERT in breast cancer cells, and the changes in CSCs traits and cell invasion ability mediated by NMI were rescued by hTERT. The in vivo study also validated that NMI knockdown promoted breast cancer growth by upregulating hTERT signaling in a mouse model. Moreover, further analyses for the clinical samples demonstrated that NMI expression was negatively correlated with hTERT expression and the low NMI/high hTERT expression was associated with the worse status of clinical TNM stages in breast cancer patients. Furthermore, we demonstrated that the interaction of YY1 protein with NMI and its involvement in NMI-mediated transcriptional regulation of hTERT in breast cancer cells. Collectively, our results provide new insights into understanding the regulatory mechanism of CSCs and suggest that the NMI-YY1-hTERT signaling axis may be a potential therapeutic target for breast cancers