Explaining Dynamic Graph Neural Networks via Relevance Back-propagation

Graph Neural Networks (GNNs) have shown remarkable effectiveness in capturing abundant information in graph-structured data. However, the black-box nature of GNNs hinders users from understanding and trusting the models, thus leading to difficulties in their applications. While recent years witness the prosperity of the studies on explaining GNNs, most of them focus on static graphs, leaving the explanation of dynamic GNNs nearly unexplored. It is challenging to explain dynamic GNNs, due to their unique characteristic of time-varying graph structures. Directly using existing models designed for static graphs on dynamic graphs is not feasible because they ignore temporal dependencies among the snapshots. In this work, we propose DGExplainer to provide reliable explanation on dynamic GNNs. DGExplainer redistributes the output activation score of a dynamic GNN to the relevances of the neurons of its previous layer, which iterates until the relevance scores of the input neuron are obtained. We conduct quantitative and qualitative experiments on real-world datasets to demonstrate the effectiveness of the proposed framework for identifying important nodes for link prediction and node regression for dynamic GNNs

Influence of cutting parameters on the depth of subsurface deformed layer in nano-cutting process of single crystal copper

Large-scale molecular dynamics simulation is performed to study the nano-cutting process of single crystal copper realized by single-point diamond cutting tool in this paper. The centro-symmetry parameter is adopted to characterize the subsurface deformed layers and the distribution and evolution of the subsurface defect structures. Three-dimensional visualization and measurement technology are used to measure the depth of the subsurface deformed layers. The influence of cutting speed, cutting depth, cutting direction, and crystallographic orientation on the depth of subsurface deformed layers is systematically investigated. The results show that a lot of defect structures are formed in the subsurface of workpiece during nano-cutting process, for instance, stair-rod dislocations, stacking fault tetrahedron, atomic clusters, vacancy defects, point defects. In the process of nano-cutting, the depth of subsurface deformed layers increases with the cutting distance at the beginning, then decreases at stable cutting process, and basically remains unchanged when the cutting distance reaches up to 24 nm. The depth of subsurface deformed layers decreases with the increase in cutting speed between 50 and 300 m/s. The depth of subsurface deformed layer increases with cutting depth, proportionally, and basically remains unchanged when the cutting depth reaches over 6 nm

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Sepiolite-Supported WS₂ Nanosheets for Synergistically Promoting Photocatalytic Rhodamine B Degradation

Pristine tungsten disulfide (WS2) nanosheets are extremely prone to agglomeration, leading to blocked active sites and the decrease of catalytic activity. In this work, highly dispersed WS2 nanosheets were fabricated via a one-step in situ solvothermal method, using sepiolite nanofibers as a functional carrier. The ammonium tetrathiotungstate was adopted as W and S precursors, and N,N-dimethylformamide could provide a neutral reaction environment. The electron microscope analysis revealed that the WS2 nanosheets were stacked compactly in the shape of irregular plates, while they were uniformly grown on the surface of sepiolite nanofibers. Meanwhile, the BET measurement confirmed that the as-prepared composite has a larger specific surface area and is more mesoporous than the pure WS2. Due to the improved dispersion of WS2 and the synergistic effect between WS2 and the mesoporous sepiolite mineral which significantly facilitated the mass transport, the WS2/sepiolite composite exhibited ca. 2.6 times the photocatalytic efficiency of the pure WS2 for rhodamine B degradation. This work provides a potential method for low-cost batch preparation of high-quality 2D materials via assembling on natural materials

Influence of cutting parameters on the depth of subsurface deformed layer in nano-cutting process of single crystal copper

Large-scale molecular dynamics simulation is performed to study the nano-cutting process of single crystal copper realized by single-point diamond cutting tool in this paper. The centro-symmetry parameter is adopted to characterize the subsurface deformed layers and the distribution and evolution of the subsurface defect structures. Three-dimensional visualization and measurement technology are used to measure the depth of the subsurface deformed layers. The influence of cutting speed, cutting depth, cutting direction, and crystallographic orientation on the depth of subsurface deformed layers is systematically investigated. The results show that a lot of defect structures are formed in the subsurface of workpiece during nano-cutting process, for instance, stair-rod dislocations, stacking fault tetrahedron, atomic clusters, vacancy defects, point defects. In the process of nano-cutting, the depth of subsurface deformed layers increases with the cutting distance at the beginning, then decreases at stable cutting process, and basically remains unchanged when the cutting distance reaches up to 24 nm. The depth of subsurface deformed layers decreases with the increase in cutting speed between 50 and 300 m/s. The depth of subsurface deformed layer increases with cutting depth, proportionally, and basically remains unchanged when the cutting depth reaches over 6 nm

Application of Improved YOLOv5 in Aerial Photographing Infrared Vehicle Detection

Aiming to solve the problems of false detection, missed detection, and insufficient detection ability of infrared vehicle images, an infrared vehicle target detection algorithm based on the improved YOLOv5 is proposed. The article analyzes the image characteristics of infrared vehicle detection, and then discusses the improved YOLOv5 algorithm in detail. The algorithm uses the DenseBlock module to increase the ability of shallow feature extraction. The Ghost convolution layer is used to replace the ordinary convolution layer, which increases the redundant feature graph based on linear calculation, improves the network feature extraction ability, and increases the amount of information from the original image. The detection accuracy of the whole network is enhanced by adding a channel attention mechanism and modifying loss function. Finally, the improved performance and comprehensive improved performance of each module are compared with common algorithms. Experimental results show that the detection accuracy of the DenseBlock and EIOU module added alone are improved by 2.5% and 3% compared with the original YOLOv5 algorithm, respectively, and the addition of the Ghost convolution module and SE module alone does not increase significantly. By using the EIOU module as the loss function, the three modules of DenseBlock, Ghost convolution and SE Layer are added to the YOLOv5 algorithm for comparative analysis, of which the combination of DenseBlock and Ghost convolution has the best effect. When adding three modules at the same time, the mAP fluctuation is smaller, which can reach 73.1%, which is 4.6% higher than the original YOLOv5 algorithm

Diversity of lettered words of the chinese language in the chinese digital media discourse

© 2020 ACM. The article is devoted to the analysis of the lettered words of the Chinese language and their use in the Chinese digital media discourse. Previously, this phenomenon was unusual for the traditional system of the Chinese language, in view of both the closed nature of China itself and the careful preservation of its national foundations. Active international contacts inevitably led to changes in the Chinese language, a large number of neologisms and foreign borrowings appear in it. The aim of the present study is to study the process of integrating lettered words into the Chinese language system and their features as new lexical units of the Chinese language, as well as studying the variety of lettered words of the Chinese language presented in a digital media discourse. The increasingly active penetration of the analyzed phenomenon into various areas of communication is due, in addition to globalization, to the principle of economy-a foreign, lettered term-easier to pronounce and spell than the generally accepted foreign loan word or the Chinese term itself. In addition, foreign-language lettered words often perform a euphemistic function in the modern Chinese language. With the spread of lettered words in the everyday oral and written communication of native Chinese speakers, their presence in the language began to cause both positive and negative response from the Chinese public