Multi-Scale Aggregation Graph Neural Networks Based on Feature Similarity for Semi-Supervised Learning

The problem of extracting meaningful data through graph analysis spans a range of different fields, such as social networks, knowledge graphs, citation networks, the World Wide Web, and so on. As increasingly structured data become available, the importance of being able to effectively mine and learn from such data continues to grow. In this paper, we propose the multi-scale aggregation graph neural network based on feature similarity (MAGN), a novel graph neural network defined in the vertex domain. Our model provides a simple and general semi-supervised learning method for graph-structured data, in which only a very small part of the data is labeled as the training set. We first construct a similarity matrix by calculating the similarity of original features between all adjacent node pairs, and then generate a set of feature extractors utilizing the similarity matrix to perform multi-scale feature propagation on graphs. The output of multi-scale feature propagation is finally aggregated by using the mean-pooling operation. Our method aims to improve the model representation ability via multi-scale neighborhood aggregation based on feature similarity. Extensive experimental evaluation on various open benchmarks shows the competitive performance of our method compared to a variety of popular architectures.     

FTRLIM: Distributed Instance Matching Framework for Large-Scale Knowledge Graph Fusion

Instance matching is a key task in knowledge graph fusion, and it is critical to improving the efficiency of instance matching, given the increasing scale of knowledge graphs. Blocking algorithms selecting candidate instance pairs for comparison is one of the effective methods to achieve the goal. In this paper, we propose a novel blocking algorithm named MultiObJ, which constructs indexes for instances based on the Ordered Joint of Multiple Objects’ features to limit the number of candidate instance pairs. Based on MultiObJ, we further propose a distributed framework named Follow-the-Regular-Leader Instance Matching (FTRLIM), which matches instances between large-scale knowledge graphs with approximately linear time complexity. FTRLIM has participated in OAEI 2019 and achieved the best matching quality with significantly efficiency. In this research, we construct three data collections based on a real-world large-scale knowledge graph. Experiment results on the constructed data collections and two real-world datasets indicate that MultiObJ and FTRLIM outperform other state-of-the-art methods.     

基于维纳滤波的同轴电缆脉冲信号传输畸变补偿研究

由于同轴电缆的低通传输特性,脉冲信号在同轴电缆中传输时不可避免地会出现畸变,并且畸变程度会随着脉冲信号频率、带宽以及传输距离的增加而增大。创新性地将图像处理领域中的一种图像复原方法——维纳滤波法应用于脉冲信号同轴电缆传输畸变补偿,仅利用同轴电缆的S参数和输出信号即可完成输入信号的重构。并以10 m同轴电缆为对象,采用该方法分别对双指数脉冲信号、高斯调制脉冲信号、调制方波信号进行传输畸变补偿。结果表明：对于不同样式的信号,该方法均具有优异的补偿性能;并且,与工程上常用的衰减补偿法相比,该方法不仅补偿精度高,还具有高的计算效率,在同轴电缆脉冲信号传输畸变补偿中具有很好的实用价值。     

Discovery potentials of double-charm tetraquarks

In this study, we investigate the discovery potential of double-charm tetraquarks \begin{document}$ T^{\{cc\}}_{[\bar{q}\bar{q}']} $\end{document}. We find that their production cross sections at the LHCb with \begin{document}$ \sqrt{s} = 13 $\end{document} TeV reach \begin{document}$ \mathcal{O}(10^4) $\end{document} pb, which indicates that the LHCb has collected \begin{document}$ \mathcal{O}(10^8) $\end{document} such particles. Through the decay channels of \begin{document}$ T^{\{cc\}}_{[\bar{u}\bar{d}]}\to D^{+}K^{-}\pi^{+} $\end{document} or \begin{document}$ D^0D^+\gamma $\end{document} (if stable) or \begin{document}$ T^{\{cc\}}_{[\bar{u}\bar{d}]}\to D^0D^{*+}\to D^0D^0\pi^+ $\end{document} (if unstable), it is highly expected that they get discovered at the LHCb in the near future. We also discuss the productions and decays of the double-charm tetraquarks at future Tera-\begin{document}$ Z $\end{document} factories.     

Decreased Resting-State Functional Complexity in Elderly with Subjective Cognitive Decline

Individuals with subjective cognitive decline (SCD) are at high risk of developing preclinical or clinical state of Alzheimer’s disease (AD). Resting state functional magnetic resonance imaging, which can indirectly reflect neuron activities by measuring the blood-oxygen-level-dependent (BOLD) signals, is promising in the early detection of SCD. This study aimed to explore whether the nonlinear complexity of BOLD signals can describe the subtle differences between SCD and normal aging, and uncover the underlying neuropsychological implications of these differences. In particular, we introduce amplitude-aware permutation entropy (AAPE) as the novel measure of brain entropy to characterize the complexity in BOLD signals in each brain region of the Brainnetome atlas. Our results demonstrate that AAPE can reflect the subtle differences between both groups, and the SCD group presented significantly decreased complexities in subregions of the superior temporal gyrus, the inferior parietal lobule, the postcentral gyrus, and the insular gyrus. Moreover, the results further reveal that lower complexity in SCD may correspond to poorer cognitive performance or even subtle cognitive impairment. Our findings demonstrated the effectiveness and sensitiveness of the novel brain entropy measured by AAPE, which may serve as the potential neuroimaging marker for exploring the subtle changes in SCD.     

磁控溅射制备W掺杂VO2/FTO复合薄膜及其性能分析

为了获得相变温度低且热致变色性能优越的光学材料, 室温下在F:SnO₂ (FTO)导电玻璃基板表面沉积钨钒金属膜, 再经空气气氛下的热氧化处理, 制备了W掺杂VO₂/FTO复合薄膜, 利用X射线光电子能谱、X射线衍射和扫描电镜对薄膜的结构和表面形貌进行了分析. 结果表明: 高温热氧化处理过程中没有生成W, F, V混合氧化物, W以替换V原子的方式掺杂. 与采用相同工艺和条件制备的纯VO₂/FTO复合薄膜相比, W掺杂VO₂薄膜没有改变晶面取向, 仍具有(110)晶面择优取向, 相变温度下降到35 ℃左右, 热滞回线收窄到4 ℃, 高低温下的近红外光透过率变化量提高到28%. 薄膜的结晶程度明显提高, 表面变得平滑致密, 具有很好的一致性, 对光电薄膜器件的设计开发和工业化生产具有重要意义. 关键词： W掺杂 2')" href="#">VO₂ FTO导电玻璃 磁控溅射     

An order-by-disorder process in the cyclic phase of spin-2 condensate with a weak magnetic field

We present in this paper a model study on the “order-by-disorder” process in the cyclic phase of spin-2 condensate, which forms a family of incommensurable, spiral degenerate ground states. On the basis of the ordering mechanism of entropic splitting, it is demonstrated that the energy corrections resulting from quantum fluctuations of disorder lift the accidental degeneracy of the cyclic configurations and thus lead to an eventual spiral order called the cyclic order. The order-by-disorder phenomenon is then realized even if the magnetic field exists. Finally, we show that our theoretic observations can be verified experimentally by direct detection of the cyclic order in the ⁸⁷Rb condensate of a spin-2 manifold with a weak magnetic field.     

The Effect of OMMT on the Morphology and Mechanical Properties of PVC/ABS Blends

Poly(vinyl chloride) (PVC)/acrylonitrile-butadiene-styrene (ABS) blends containing organically modified montmorillonite (OMMT) were prepared using a twin-screw extruder followed by injection molding. The OMMT dispersion was evaluated by X-ray diffraction and transmission electron microscopy. The clay was preferentially situated in the PVC phase and across the interfaces of PVC/ABS. The effect of the addition of OMMT on the morphology and mechanical properties was also evaluated. Scanning electron microscopy revealed a large reduction in domain size when OMMT was used. The mechanical properties were studied through tensile and impact tests. The yield stress increased when an appropriate amount of OMMT was used without impairing the impact strength.