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Correction to: a network method to identify the dynamic changes of the data flow with spatio-temporal feature

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Applied Intelligence 2021年第5期52卷 5594-5594页

作者： Wang, Li-Na Tan, Gui-Min Zang, Chen-Rui Science College Inner Mongolia University of Technology Hohhot China Inner Mongolia Key Laboratory of Statistical Analysis Theory for Life Data and Neural Network Modeling Hohhot China Inner Mongolia Branch China Unicom Hohhot China

iSplit LBI: Individualized partial ranking with ties via split LBI

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arXiv 2019年

作者： Xu, Qianqian Sun, Xinwei Yang, Zhiyong Cao, Xiaochun Huang, Qingming Yao, Yuan Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS Microsoft Research Asia State Key Laboratory of Information Security Institute of Information Engineering CAS School of Cyber Security University of Chinese Academy of Sciences School of Computer Science and Tech. University of Chinese Academy of Sciences Key Laboratory of Big Data Mining and Knowledge Management CAS Peng Cheng Laboratory Department of Mathematics Hong Kong University of Science and Technology Hong Kong

Due to the inherent uncertainty of data, the problem of predicting partial ranking from pairwise comparison data with ties has attracted increasing interest in recent years. However, in real-world scenarios, different individuals often hold distinct preferences. It might be misleading to merely look at a global partial ranking while ignoring personal diversity. In this paper, instead of learning a global ranking which is agreed with the consensus, we pursue the tie-aware partial ranking from an individualized perspective. Particularly, we formulate a unified framework which not only can be used for individualized partial ranking prediction, but also be helpful for abnormal user selection. This is realized by a variable splitting-based algorithm called iSplitLBI. Specifically, our algorithm generates a sequence of estimations with a regularization path, where both the hyperparameters and model parameters are updated. At each step of the path, the parameters can be decomposed into three orthogonal parts, namely, abnormal signals, personalized signals and random noise. The abnormal signals can serve the purpose of abnormal user selection, while the abnormal signals and personalized signals together are mainly responsible for individual partial ranking prediction. Extensive experiments on simulated and real-world datasets demonstrate that our new approach significantly outperforms state-of-the-art alternatives. The code is now availiable at https://***/qianqianxu010/ NeurIPS2019-iSplitLBI. Copyright © 2019, The Authors. All rights reserved.

关键词： Forecasting

Transferring knowledge distillation for multilingual social event detection

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arXiv 2021年

作者： Ren, Jiaqian Peng, Hao Jiang, Lei Wu, Jia Tong, Yongxin Wang, Lihong Bai, Xu Wang, Bo Yang, Qiang Institute of Information Engineering Chinese Academy of Sciences The School of Cyber Security University of Chinese Academy of Sciences Beijing100041 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China The School of Cyber Science and Technology Beihang University Beijing100083 China Institute of Information Engineering Chinese Academy of Sciences Beijing100041 China The Department of Computing Macquarie University Sydney Australia The State Key Laboratory of Software Development Environment The School of Computer Science and Engineering Beihang University Beijing100083 China The National Computer Network Emergency Response Technical Team Coordination Center of China Beijing100029 China The Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong AI Group WeBank Co. Ltd. China

Recently published graph neural networks (GNNs) show promising performance at social event detection tasks. However, most studies are oriented toward monolingual data in languages with abundant training samples. This has left the more common multilingual settings and lesser-spoken languages relatively unexplored. Thus, we present a GNN that incorporates cross-lingual word embeddings for detecting events in multilingual data streams. The first exploit is to make the GNN work with multilingual data. For this, we outline a construction strategy that aligns messages in different languages at both the node and semantic levels. Relationships between messages are established by merging entities that are the same but are referred to in different languages. Non-English message representations are converted into English semantic space via the cross-lingual word embeddings. The resulting message graph is then uniformly encoded by a GNN model. In special cases where a lesser-spoken language needs to be detected, a novel cross-lingual knowledge distillation framework, called CLKD, exploits prior knowledge learned from similar threads in English to make up for the paucity of annotated data. Experiments on both synthetic and real-world datasets show the framework to be highly effective at detection in both multilingual data and in languages where training samples are scarce. © 2021, CC BY.

关键词： Embeddings

Searching for low-redshift faint galaxies with MMT/Hectospec

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arXiv 2021年

作者： Cheng, Cheng Huang, Jia-Sheng Willmer, Christopher N.A. Zhang, Hong-Xin Ashby, Matthew L.N. Xu, Hai Sawicki, Marcin Arnouts, Stephane Gwyn, Stephen Desprez, Guillaume Coupon, Jean Golob, Anneya Liang, Piaoran Cao, Tianwen Shi, Yaru Jin, Gaoxiang He, Chuan Wu, Shumei Li, Zijian Sophia Dai, Y. Kevin Xu, C. Shao, Xu Musin, Marat Chinese Academy of Sciences South America Center for Astronomy National Astronomical Observatories CAS Beijing100101 China CAS Key Laboratory of Optical Astronomy National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Steward Observatory University of Arizona 933 N. Cherry Avenue TucsonAZ85721 United States CAS Key Laboratory for Research in Galaxies and Cosmology Department of Astronomy University of Science and Technology of China Anhui Hefei230026 China School of Astronomy and Space Science University of Science and Technology of China Hefei230026 China Center for Astrophysics Harvard and Smithsonian 60 Garden St CambridgeMA02138 United States Institute for Computational Astrophysics Department of Astronomy and Physics Saint Mary's University 923 Robie Street HalifaxNSB3H 3C3 Canada Aix Marseille Université CNRS Laboratoire d'Astrophysique de Marseille UMR 7326 MarseilleF-13388 France Canadian Astronomy Data Centre NRC-Herzberg 5071 West Saanich Road VictoriaBCV9E 2E7 Canada Department of Astronomy University of Geneva ch. d'Écogia 16 Versoix CH-1290 Switzerland

We present redshifts for 2753 low-redshift galaxies between 0.03 zspec 0.5 with 18 ≤ r ≤ 22 obtained with Hectospec at the Multi-Mirror Telescope (MMT). The observations targeted the XMMLSS, ELAIS-N1 and DEEP2-3 fields, each of which covers ∼ 1 deg2. These fields are also part of the recently completed CFHT Large Area U-band Deep Survey (CLAUDS) and on-going Hyper Suprime-Cam deep fields surveys. The efficiency of our technique for selecting low-redshift galaxies is confirmed by the redshift distribution of our sources. In addition to redshifts, these high S/N spectra are used to measure ages, metallicities, and nuclear activity levels. In combination with the photometric catalogue in u, g, r, i, z, y down to 27 AB mag, we are able to study the galaxy population down to stellar masses of ∼ 108Mo. This paper presents the observational strategy, the reduction procedure and properties of the galaxy sample. © 2021, CC BY.

关键词： Surveys

863 genomes reveal the origin and domestication of chicken

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细胞研究（英文版） 2020年第8期30卷 693-701页

作者： Ming-Shan Wang Mukesh Thakur Min-Sheng Peng Yu Jiang Laurent Alain Fran(c)ois Frantz Ming Li Jin-Jin Zhang Sheng Wang Joris Peters Newton Otieno Otecko Chatmongkon Suwannapoom Xing Guo Zhu-Qing Zheng Ali Esmailizadeh Nalini Yasoda Hirimuthugoda Hidayat Ashari Sri Suladari Moch Syamsul Arifin Zein Szilvia Kusza Saeed Sohrabi Hamed Kharrati-Koopaee Quan-Kuan Shen Lin Zeng Min-Min Yang Ya-Jiang Wu Xing-Yan Yang Xue-Mei Lu Xin-Zheng Jia Qing-Hua Nie Susan Joy Lamont Emiliano Lasagna Simone Ceccobelli Humpita Gamaralalage Thilini Nisanka Gunwardana Thilina Madusanka Senasige Shao-Hong Feng Jing-Fang Si Hao Zhang Jie-Qiong Jin Ming-Li Li Yan-Hu Liu Hong-Man Chen Cheng Ma Shan-Shan Dai Abul Kashem Fazlul Haque Bhuiyan Muhammad Sajjad Khan Gamamada Liyanage Lalanie Pradeepa Silva Thi-Thuy Le Okeyo Ally Mwai Mohamed Nawaz Mohamed Ibrahim Megan Supple Beth Shapiro Olivier Hanotte Guojie Zhang Greger Larson Jian-Lin Han Dong-Dong Wu Ya-Ping Zhang State Key Laboratory of Genetic Resources and Evolution Yunnan Laboratory of Molecular Biology of Domestic Animals Kunming Institute of Zoology Chinese Academy of Sciences Kunming Yunnan China Kunming College of Life Science University of Chinese Academy of Sciences Kunming Yunnan China Department of Ecology and Evolutionary Biology Howard Hughes Medical Institute University of California Santa Cruz Santa Cruz CA USA Zoological Survey of India New Alipore Kolkata West Bengal India Center for Excellence in Animal Evolution and Genetics Chinese Academy of Sciences Kunming Yunnan China Key Laboratory of Animal Genetics Breeding and Reproduction of Shaanxi Province College of Animal Science and Technology Northwest A&F University Yangling Shaanxi China The Palaeogenomics and Bio-Archaeology Research Network Research Laboratory for Archaeology and History of Art University of Oxford Oxford UK School of Biological and Chemical Sciences Queen Mary University of London London UK ArchaeoBioCenter and Department of Veterinary Sciences Institute of Palaeoanatomy Domestication Research and the History of Veterinary Medicine LMU Munich Munich Germany SNSB Bavarian State Collection of Anthropology and Palaeoanatomy Munich Germany School of Agriculture and Natural Resources University of Phayao Phayao Thailand College of Animal Science and Technology Anhui Agricultural University Hefei Anhui China Department of Animal Science Shahid Bahonar University of Kerman Kerman Iran Faculty of Agriculture University of Ruhuna Matara Sri Lanka Museum Zoologicum Bogoriense Research Center for Biology Indonesian Institute of Science (LIPI) Cibinong Indonesia CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources Institute of Animal Science Chinese Academy of Agricultural Sciences (CAAS) Beijing China Institute of Animal Husbandry Biotechnology and Nature Conservation University of Debrecen Debrecen Hungary Institute of Biotechnology School of Agriculture Shi

Despite the substantial role that chickens have played in human societies across the world,both the geographic and temporal origins of their domestication remain *** address this issue,we analyzed 863 genomes from a worldwide sampling of chickens and representatives of all four species of wild jungle fowl and each of the five subspecies of red jungle fowl (RJF).Our study suggests that domestic chickens were initially derived from the RJF subspecies Gallus gallus spadiceus whose present-day distribution is predominantly in southwestern China,northern Thailand and *** their domestication,chickens were translocated across Southeast and South Asia where they interbred locally with both RJF subspecies and other jungle fowl *** addition,our results show that the White Leghorn chicken breed possesses a mosaic of divergent ancestries inherited from other subspecies of *** the strong episodic gene flow from geographically divergent lineages of jungle fowls,our analyses show that domestic chickens undergo genetic adaptations that underlie their unique behavioral,morphological and reproductive *** study provides novel insights into the evolutionary history of domestic chickens and a valuable resource to facilitate ongoing genetic and functional investigations of the world's most numerous domestic animal.

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A network security entity recognition method based on feature template and CNN-BiLSTM-CRF

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Frontiers of Information technology & Electronic Engineering 2019年第6期20卷 872-884页

作者： Ya QIN Guo-wei SHEN Wen-bo ZHAO Yan-ping CHEN Miao YU Xin JIN College of Computer Science and Technology Guizhou University Guiyang 550025 China Guizhou Provincial Key Laboratory of Public Big Data Guiyang 550025 China Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 China National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing 100029 China

By network security threat intelligence analysis based on a security knowledge graph(SKG), multi-source threat intelligence data can be analyzed in a fine-grained manner. This has received extensive attention. It is difficult for traditional named entity recognition methods to identify mixed security entities in Chinese and English in the field of network security, and there are difficulties in accurately identifying network security entities because of insufficient features extracted. In this paper, we propose a novel FT-CNN-BiLSTM-CRF security entity recognition method based on a neural network CNN-BiLSTM-CRF model combined with a feature template(FT). The feature template is used to extract local context features, and a neural network model is used to automatically extract character features and text global features. Experimental results showed that our method can achieve an F-score of 86% on a large-scale network security dataset and outperforms other methods.

关键词： network security entity Security knowledge graph (SKG) Entity recognition Feature template Neural network

A Fully Amorphous, Dynamic Cross-Linked Polymer Electrolyte for Lithium-Sulfur Batteries Operating at Subzero-Temperatures

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Angewandte Chemie 2023年第5期136卷

作者： Juan Zhang Jia Chou Xiao-Xi Luo Dr. Yi-Ming Yang Ming-Yan Yan Prof. Di Jia Chao-Hui Zhang Ya-Hui Wang Wen-Peng Wang Shuang-Jie Tan Jun-Chen Guo Prof. Yao Zhao Prof. Fuyi Wang Prof. Sen Xin Prof. Li-Jun Wan Prof. Yu-Guo Guo CAS Key Laboratory of Molecular Nanostructure and Nanotechnology CAS Research/Education Centre for Excellence in Molecular Sciences Beijing National Laboratory for Molecular Sciences (BNLMS) Institute of Chemistry Chinese Academy of Sciences (CAS) 100190 Beijing P. R. China Contribution: Conceptualization (supporting) Data curation (lead) Formal analysis (supporting) Funding acquisition (supporting) Investigation (equal) Methodology (lead) Visualization (lead) Writing - original draft (equal) Writing - review & editing (equal) Contribution: Data curation (equal) Formal analysis (supporting) Investigation (supporting) Methodology (supporting) Visualization (supporting) Writing - original draft (supporting) Contribution: Data curation (supporting) Key Laboratory of Science and Technology on High-tech Polymer Materials Institute of Chemistry Chinese Academy of Sciences 100190 Beijing P. R. China University of Chinese Academy of Sciences (UCAS) 100049 Beijing P. R. China Beijing National Laboratory for Molecular Sciences State Key Laboratory of Polymer Physics and Chemistry Institute of Chemistry Chinese Academy of Sciences 100190 Beijing P. R. China Contribution: Data curation (supporting) Visualization (supporting) Beijing National Laboratory for Molecular Sciences National Centre for Mass Spectrometry in Beijing CAS Key Laboratory of Analytical Chemistry for Living Biosystems Institute of Chemistry Chinese Academy of Sciences 100190 Beijing P. R. China Contribution: Conceptualization (supporting) Formal analysis (equal) Funding acquisition (supporting) Investigation (supporting) Supervision (equal) Validation (equal) Writing - review & editing (equal) Contribution: Investigation (supporting) Supervision (supporting) Validation (supporting) Contribution: Conceptualization (lead) Formal analysis (equal) Funding acquisition (lead) Investigation (equal) Project administration (lead) Resources (lead) Supervision (lead) Validation (equal) Writing - review & editi

Solid-state lithium-sulfur batteries have shown prospects as safe, high-energy electrochemical storage technology for powering regional electrified transportation. Owing to limited ion mobility in crystalline polymer electrolytes, the battery is incapable of operating at subzero temperature. Addition of liquid plasticizer into the polymer electrolyte improves the Li-ion conductivity yet sacrifices the mechanical strength and interfacial stability with both electrodes. In this work, we showed that by introducing a spherical hyperbranched solid polymer plasticizer into a Li + -conductive linear polymer matrix, an integrated dynamic cross-linked polymer network was built to maintain fully amorphous in a wide temperature range down to subzero. A quasi-solid polymer electrolyte with a solid mass content >90 % was prepared from the cross-linked polymer network, and demonstrated fast Li + conduction at a low temperature, high mechanical strength, and stable interfacial chemistry. As a result, solid-state lithium-sulfur batteries employing the new electrolyte delivered high reversible capacity and long cycle life at 25 °C, 0 °C and −10 °C to serve energy storage at complex environmental conditions.

关键词： Interface Stability Li−S Batteries Low-Temperature Performance Solid Electrolyte Interfaces Solid-State Batteries

Experimental authentication of quantum key distribution with post-quantum cryptography

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arXiv 2020年

作者： Wang, Liu-Jun Zhang, Kai-Yi Wang, Jia-Yong Cheng, Jie Yang, Yong-Hua Tang, Shi-Biao Yan, Di Tang, Yan-Lin Liu, Zhen Yu, Yu Zhang, Qiang Pan, Jian-Wei Hefei National Laboratory for Physical Sciences at Microscale Department of Modern Physics University of Science and Technology of China Hefei230026 China Shanghai Branch CAS Center for Excellence Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai201315 China School of Physics and Astronomy Yunnan Key Laboratory for Quantum Information Yunnan University Kunming650500 China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China Shanghai Qizhi Institute Shanghai200232 China CAS Quantum Network Co. Ltd Shanghai201315 China QuantumCTek Co. Ltd Hefei230088 China

Quantum key distribution (QKD) can provide information theoretically secure key exchange even in the era of quantum computer [1–3]. However, QKD requires the classical channel to be authenticated, and the current method is pre-sharing symmetric keys [4]. For a QKD network of n users, this method requires Cn2 = n(n − 1)/2 pairs of symmetric keys to realize pairwise interconnection. In contrast, with the help of mature public key infrastructure (PKI) and post-quantum cryptography (PQC) with quantum resistant security, each user only needs to apply for a digital certificate from certificate authority (CA) to achieve efficient and secure authentication for QKD. We only need to assume the short-term security of the PQC algorithm to achieve the long-term security of the distributed keys. Here, we experimentally verified the feasibility, efficiency and stability of the PQC algorithm in QKD authentication, and demonstrated the advantages when new users join the QKD network. Using PQC authentication we only need to believe the CA is safe, rather than all trusted relays. QKD combined with PQC authentication will greatly promote and extend the application prospects of quantum safe communication. Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum cryptography

Front Cover: International Journal of Intelligent Systems, Volume 37 Issue 11 November 2022

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International Journal of Intelligent Systems 2022年第11期37卷

作者： Xianjia Meng Yong Yang Ximeng Liu Nan Jiang School of Information Science and Technology Northwest University Xi'an People's Republic of China Fujian Province Key Laboratory of Information Security of Network System and College of Computer and Data Science Fuzhou University Fuzhou People's Republic of China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen People's Republic of China Department of Internet of Things School of Information Engineering East China Jiao Tong University Nanchang People's Republic of China