306 research outputs found

    Case Report: Pulmonary Typical Carcinoid with Multi-organ Metastasis

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    Self-supervised Heterogeneous Graph Variational Autoencoders

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    Heterogeneous Information Networks (HINs), which consist of various types of nodes and edges, have recently demonstrated excellent performance in graph mining. However, most existing heterogeneous graph neural networks (HGNNs) ignore the problems of missing attributes, inaccurate attributes and scarce labels for nodes, which limits their expressiveness. In this paper, we propose a generative self-supervised model SHAVA to address these issues simultaneously. Specifically, SHAVA first initializes all the nodes in the graph with a low-dimensional representation matrix. After that, based on the variational graph autoencoder framework, SHAVA learns both node-level and attribute-level embeddings in the encoder, which can provide fine-grained semantic information to construct node attributes. In the decoder, SHAVA reconstructs both links and attributes. Instead of directly reconstructing raw features for attributed nodes, SHAVA generates the initial low-dimensional representation matrix for all the nodes, based on which raw features of attributed nodes are further reconstructed to leverage accurate attributes. In this way, SHAVA can not only complete informative features for non-attributed nodes, but rectify inaccurate ones for attributed nodes. Finally, we conduct extensive experiments to show the superiority of SHAVA in tackling HINs with missing and inaccurate attributes

    Enhancement of Interfacial Thermal Conductance of SiC by Overlapped Carbon Nanotubes and Intertube Atoms

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    A new way was proposed to enhance the interfacial thermal conductance (ITC) of silicon carbide (SiC) composite through the overlapped carbon nanotubes (CNTs) and intertube atoms. By nonequilibrium molecular dynamics (NEMD) simulations, the dependence of ITC on both the number of intertube atoms and the temperature was studied. It is indicated that the ITC can be significantly enhanced by adding intertube atoms and finally becomes saturated with the increase of the number of intertube atoms. And the mechanism is discussed by analyzing the probability distributions of atomic forces and vibrational density of states (VDOS). This work may provide some guidance on enhancing the ITC of CNT-based composites

    A review of the spider genus Sinoalaria (Araneae, Theridiosomatidae), with the descriptions of four new species and two new combinations

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    The spider genus Sinoalaria Zhao & Li, 2014 is redefined and reviewed. A total of ten species are studied, including four new species: S. chi Yu & Lin, sp. nov. (♂♀), S. shenhei Yu & Lin, sp. nov. (♀), S. shuidi Yu & Lin, sp. nov. (♀), S. xiaotu Yu & Lin, sp. nov. (♂♀). Two new combinations are proposed: Sinoalaria nitida (Zhao & Li, 2012), comb. nov. and S. prolata (Zhao & Li, 2012), comb. nov., both transferred from Karstia Chen, 2010. The material of six known species were re-examined and photographed, including the type species, S. chengguanensis (Zhao & Li, 2012). A key is provided for all species of the genus, as well as diagnoses, illustrations, and a distribution map
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