Hypergraph Node Representation Learning with One-Stage Message Passing

Hypergraphs as an expressive and general structure have attracted considerable attention from various research domains. Most existing hypergraph node representation learning techniques are based on graph neural networks, and thus adopt the two-stage message passing paradigm (i.e. node -> hyperedge -> node). This paradigm only focuses on local information propagation and does not effectively take into account global information, resulting in less optimal representations. Our theoretical analysis of representative two-stage message passing methods shows that, mathematically, they model different ways of local message passing through hyperedges, and can be unified into one-stage message passing (i.e. node -> node). However, they still only model local information. Motivated by this theoretical analysis, we propose a novel one-stage message passing paradigm to model both global and local information propagation for hypergraphs. We integrate this paradigm into HGraphormer, a Transformer-based framework for hypergraph node representation learning. HGraphormer injects the hypergraph structure information (local information) into Transformers (global information) by combining the attention matrix and hypergraph Laplacian. Extensive experiments demonstrate that HGraphormer outperforms recent hypergraph learning methods on five representative benchmark datasets on the semi-supervised hypernode classification task, setting new state-of-the-art performance, with accuracy improvements between 2.52% and 6.70%. Our code and datasets are available.Comment: 11 page

Region Normalization for Image Inpainting

Feature Normalization (FN) is an important technique to help neural network training, which typically normalizes features across spatial dimensions. Most previous image inpainting methods apply FN in their networks without considering the impact of the corrupted regions of the input image on normalization, e.g. mean and variance shifts. In this work, we show that the mean and variance shifts caused by full-spatial FN limit the image inpainting network training and we propose a spatial region-wise normalization named Region Normalization (RN) to overcome the limitation. RN divides spatial pixels into different regions according to the input mask, and computes the mean and variance in each region for normalization. We develop two kinds of RN for our image inpainting network: (1) Basic RN (RN-B), which normalizes pixels from the corrupted and uncorrupted regions separately based on the original inpainting mask to solve the mean and variance shift problem; (2) Learnable RN (RN-L), which automatically detects potentially corrupted and uncorrupted regions for separate normalization, and performs global affine transformation to enhance their fusion. We apply RN-B in the early layers and RN-L in the latter layers of the network respectively. Experiments show that our method outperforms current state-of-the-art methods quantitatively and qualitatively. We further generalize RN to other inpainting networks and achieve consistent performance improvements.Comment: Accepted by AAAI-202

Kernel mapping for mitigating nonlinear impairments in optical short-reach communications

Nonlinear impairments induced by the opto-electronic components are one of the fundamental performance-limiting factors in high-speed optical short-reach communications, significantly hindering capacity improvement. This paper proposes to employ a kernel mapping function to map the signals in a Hilbert space to its inner product in a reproducing kernel Hilbert space, which has been successfully demonstrated to mitigate nonlinear impairments in optical short-reach communication systems. The operation principle is derived. An intensity modulation/direct detection system with 1.5-mu m vertical cavity surface emitting laser and 10-km 7-core fiber achieving 540.68-Gbps (net-rate 505.31-Gbps) has been carried out. The experimental results reveal that the kernel mapping based schemes are able to realize comparable transmission performance as the Volterra filtering scheme even with a high order. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreemen

Experimental Demonstration of 503.61-Gbit/s DMT over 10-km 7-Core Fiber with 1.5-\mu m SM-VCSEL for Optical Interconnects

We experimentally demonstrate a net-rate 503.61-Gbit/s discrete multitone (DMT) transmission over 10-km 7-core fiber with 1.5-\mu m single mode VCSEL, where low-complexity kernelrecursive-least-squares algorithm is employed for nonlinear channel equalization.Comment: 3 pages, 44th European Conference on Optical Communication (ECOC 2018), Rome, Italy, 201

Ultrafast Macroscopic Assembly of High-Strength Graphene Oxide Membranes by Implanting an Interlaminar Superhydrophilic Aisle

[EN] A macroscopic-assembled graphene oxide (GO)membrane with sustainable high strength presents a brightfuture for its applications in ionic and molecularfiltration forwater purification or fast force response for sensors. Tradition-ally, the bottom-up macroscopic assembly of GO sheets isoptimized by widening the interlaminar space for expeditingwater passage, frequently leading to a compromise in strength,assembly time, and ensemble thickness. Herein, we rationalizethis strategy by implanting a superhydrophilic bridge of cobalt-based metal−organic framework nanosheets (NMOF-Co) as anadditional water“aisle”into the interlaminar space of GOsheets (GO/NMOF-Co), resulting in a high-strength macro-scopic membrane ensemble with tunable thickness from the nanometer scale to the centimeter scale. The GO/NMOF-Comembrane assembly time is only 18 s, 30800 times faster than that of pure GO (154 h). More importantly, the obtainedmembrane attains a strength of 124.4 MPa, which is more than 3 times higher than that of the GO membrane preparedthroughfiltration. The effect of hydrophilicity on membrane assembly is also investigated by introducing different intercalants,suggesting that, except for the interlamellar spacing, the interlayered hydrophilicity plays a more decisive role in themacroscopic assembly of GO membranes. Our results give a fundamental implication for fast macroscopic assembly of high-strength 2D materials.The authors acknowledge financial support from the National Natural Science Foundation of China (51672204), the Fundamental Research Funds for the Central Universities(WUT: 2020IB005), 2018 National Key R&D Program of China (257), Foundation of National Key Laboratory on Electromagnetic Environment Effects (No.614220504030617), and ComFuturo Program second Edition-Fundacion General CSIC. The authors also acknowledgethe Center for Materials Research and Analysis at the Wuhan University of Technology for the TEM and image suggestionsfrom Dr. Xiaoqing LiuPeer reviewe

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Finite-Element Performance Degradation Behavior of a Suspension Prestressed Concrete Arch Bridge with Grouting Defects

In response to the difficulty in effectively dealing with grouting defects in corrugated pipes within a suspension prestressed concrete arch bridge, a method for assessing the deterioration in the performance of prestressed concrete girders afflicted with grouting defects was established in the present study. Specifically, a time-varying model of steel strand corrosion within grouting defects was constructed by investigating the corrosion theory of steel strands. In addition, a full-scale numerical simulation model of the long-span prestressed concrete bridge was established based on a practical project. Through the described means, the long-term impact of steel strand corrosion at various locations, lengths, and quantities on the vertical displacement and axial stress of girders was elucidated. The results reveal that in the presence of corrosion affecting 16 steel strands located in the midspan bottom plate, a vertical displacement alteration of 17.55 mm was observed in the midpoint region of the girder over a 30-year period following the bridge’s construction. Further, when considering the combined effects of concrete shrinkage, creep, and the corrosion of 16 steel strands in the midspan bottom plate, the axial compressive stress within the midpoint region of the girder decreased from an initial 6.30 MPa to 0.79 MPa over the same 30-year timeframe post-construction. It was observed that two indicators of vertical displacement and axial stress can be employed to evaluate the performance degradation of prestressed concrete bridge girders with grouting defects. The present findings may provide a reference for the operation and management of bridges with grouting defects