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Dense sampling of bird diversity increases power of comparative genomics (vol 587, pg 252, 2020)

NATURE 2021年第7856期592卷 E24-E24页

作者： Feng, Shaohong Stiller, Josefin Deng, Yuan Armstrong, Joel Fang, Qi Reeve, Andrew Hart Xie, Duo Chen, Guangji Guo, Chunxue Faircloth, Brant C. Petersen, Bent Wang, Zongji Zhou, Qi Diekhans, Mark Chen, Wanjun Andreu-Sanchez, Sergio Margaryan, Ashot Howard, Jason Travis Parent, Carole Pacheco, George Sinding, Mikkel-Holger S. Puetz, Lara Cavill, Emily Ribeiro, Angela M. Eckhart, Leopold Fjeldsa, Jon Hosner, Peter A. Brumfield, Robb T. Christidis, Les Bertelsen, Mads F. Sicheritz-Ponten, Thomas Tietze, Dieter Thomas Robertson, Bruce C. Song, Gang Borgia, Gerald Claramunt, Santiago Lovette, Irby J. Cowen, Saul J. Njoroge, Peter Dumbacher, John Philip Ryder, Oliver A. Fuchs, Jerome Bunce, Michael Burt, David W. Cracraft, Joel Meng, Guanliang Hackett, Shannon J. Ryan, Peter G. Jonsson, Knud Andreas Jamieson, Ian G. da Fonseca, Rute R. Braun, Edward L. Houde, Peter Mirarab, Siavash Suh, Alexander Hansson, Bengt Ponnikas, Suvi Sigeman, Hanna Stervander, Martin Frandsen, Paul B. van der Zwan, Henriette van der Sluis, Rencia Visser, Carina Balakrishnan, Christopher N. Clark, Andrew G. Fitzpatrick, John W. Bowman, Reed Chen, Nancy Cloutier, Alison Sackton, Timothy B. Edwards, Scott V. Foote, Dustin J. Shakya, Subir B. Sheldon, Frederick H. Vignal, Alain Soares, Andre E. R. Shapiro, Beth Gonzalez-Solis, Jacob Ferrer-Obiol, Joan Rozas, Julio Riutort, Marta Tigano, Anna Friesen, Vicki Dalen, Love Urrutia, Araxi O. Szekely, Tamas Liu, Yang Campana, Michael G. Corvelo, Andre Fleischer, Robert C. Rutherford, Kim M. Gemmell, Neil J. Dussex, Nicolas Mouritsen, Henrik Thiele, Nadine Delmore, Kira Liedvogel, Miriam Franke, Andre Hoeppner, Marc P. Krone, Oliver Fudickar, Adam M. Mila, Borja Ketterson, Ellen D. Fidler, Andrew Eric Friis, Guillermo Parody-Merino, Angela M. Battley, Phil F. Cox, Murray P. Lima, Nicholas Costa Barroso Prosdocimi, Francisco Parchman, Thomas Lee Schlinger, Barney A. Loiselle, Bette A. Blake, John G. Lim, Haw Chuan Day, Lainy B. Fuxjager, Matthew J. Baldwin, Maude W. Braun, Michael J. Wirthlin, Morgan Dikow, China National GeneBank BGI-Shenzhen Shenzhen China State Key Laboratory of Genetic Resources and Evolution Kunming Institute of Zoology Chinese Academy of Sciences Kunming China BGI-Shenzhen Shenzhen China Villum Centre for Biodiversity Genomics Section for Ecology and Evolution Department of Biology University of Copenhagen Copenhagen Denmark BGI Education Center University of Chinese Academy of Sciences Shenzhen China MOE Laboratory of Biosystems Homeostasis and Protection Life Sciences Institute Zhejiang University Hangzhou China Department of Neuroscience and Developmental Biology University of Vienna Vienna Austria Center for Excellence in Animal Evolution and Genetics Chinese Academy of Sciences Kunming China James D. Watson Institute of Genome Sciences Hangzhou China UC Santa Cruz Genomics Institute UC Santa Cruz Santa Cruz CA USA Natural History Museum of Denmark University of Copenhagen Copenhagen Denmark Center for Macroecology Evolution and Climate GLOBE Institute University of Copenhagen Copenhagen Denmark Department of Biological Sciences Louisiana State University Baton Rouge LA USA Museum of Natural Science Louisiana State University Baton Rouge LA USA Centre of Excellence for Omics-Driven Computational Biodiscovery (COMBio) Faculty of Applied Sciences AIMST University Kedah Malaysia Section for Evolutionary Genomics The GLOBE Institute Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Institute of Molecular Biology National Academy of Sciences Yerevan Armenia University Museum Norwegian University of Science and Technology Trondheim Norway Center for Reproductive Medicine The 2nd Affiliated Hospital School of Medicine Zhejiang University Hangzhou China Novogene Durham NC USA Duke University Medical Center Durham NC USA The Rockefeller University New York NY USA Howard Hughes Medical Institute Chevy Chase MD USA Department of Dermatology Medical University of Vienna Vienna Austria

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穿山甲可能不是新型冠状病毒的中间宿主

引用

中国预防兽医学报 2020年第12期42卷 1311-1311页

作者： LIU PING JIANG JING-ZHE WANXIU-FENG Guangdong Key Laboratory of Animal Conservation and Resource Utilization Guangdong Public Laboratory of Wild Animal Conservation and Utilization Guangdong Institute of Applied Biological Resources Guangdong Academy of Science Guangzhou Guangdong Province China. Key Laboratory of South China Sea Fishery Resources Exploitation & Utilization Ministry of Agriculture South China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Guangzhou Guangdong Province China. Department of Molecular Microbiology and Immunology School of Medicine University of Missouri Columbia Missouri United States of America. Department of Electrical Engineering & Computer Science College of Engineering University of Missouri Columbia Missouri United States of America. MU Center for Research on Influenza Systems Biology (CRISB) University of Missouri Columbia Missouri United States of America. Bond Life Sciences Center University of Missouri Columbia Missouri United States of America. MU Institute for Data Science and Informatics University of Missouri Columbia Missouri United States of America. Guangdong Provincial Key Laboratory of Silviculture Protection and Utilization Guangdong Academy of Forestry Guangzhou Guangdong Province China. Institute of Animal Health Guangdong Academy of Agricultural Sciences Guangzhou Guangdong Province China. Guangdong Provincial Wildlife Rescue Center Guangzhou Guangdong Province China.

当前,新型冠状病毒肺炎(COVID-19)疫情仍在全球范围内肆虐,新冠肺炎的防控工作依然是重中之重。研究表明新型冠状病毒与中菊头蝠携带的Bat-CoV-RaTG13冠状病毒全基因组核苷酸一致性高达96%,推测该病毒可能起源于蝙蝠,再由中间野生动物... 详细信息

当前,新型冠状病毒肺炎(COVID-19)疫情仍在全球范围内肆虐,新冠肺炎的防控工作依然是重中之重。研究表明新型冠状病毒与中菊头蝠携带的Bat-CoV-RaTG13冠状病毒全基因组核苷酸一致性高达96%,推测该病毒可能起源于蝙蝠,再由中间野生动物宿主进一步传播,但目前中间宿主仍然未知。

关键词：中间宿主防控工作动物宿主穿山甲冠状病毒全球范围全基因组肺炎

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A question answering approach to emotion cause extraction

A question answering approach to emotion cause extraction

引用

2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017

作者： Gui, Lin Hu, Jiannan He, Yulan Xu, Ruifeng Lu, Qin Du, Jiachen Shenzhen Graduate School Harbin Institute of Technology China College of Mathematics and Computer Science Fuzhou University China School of Engineering and Applied Science Aston University United Kingdom Guangdong Provincial Engineering Technology Research Center for Data Science China Department of Computing Hong Kong Polytechnic University Hong Kong

ISBN: (纸本)9781945626838

Emotion cause extraction aims to identify the reasons behind a certain emotion expressed in text. It is a much more difficult task compared to emotion classification. Inspired by recent advances in using deep memory networks for question answering (QA), we propose a new approach which considers emotion cause identification as a reading comprehension task in QA. Inspired by convolutional neural networks, we propose a new mechanism to store relevant context in different memory slots to model context information. Our proposed approach can extract both word level sequence features and lexical features. Performance evaluation shows that our method achieves the state-of-the-art performance on a recently released emotion cause dataset, outperforming a number of competitive baselines by at least 3.01% in F-measure. © 2017 Association for Computational Linguistics.

关键词： Extraction

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Prediction of facebook post metrics using machine learning

arXiv

引用

arXiv 2018年

作者： Sam, Emmanuel Yarushev, Sergey Basterrech, Sebastián Averkin, Alexey Faculty of Computing and Information Technology Wisconsin International University College Accra Ghana Department of Informatics Plekhanov Russian University of Economics Moscow Russia Department of Computer Science Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Institute of Informatics Problems FRC CSC RAS Moscow Russia

In this short paper, we evaluate the performance of three well-known Machine Learning techniques for predicting the impact of a post in Facebook. Social medias have a huge influence in the social behaviour. Therefore to develop an automatic model for predicting the impact of posts in social medias can be useful to the society. In this article, we analyze the efficiency for predicting the post impact of three popular techniques: Support Vector Regression (SVR), Echo State Network (ESN) and Adaptive Network Fuzzy Inject System (ANFIS). The evaluation was done over a public and well-known benchmark dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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Convolutional phase retrieval via gradient descent

arXiv

引用

arXiv 2017年

作者： Qu, Qing Zhang, Yuqian Eldar, Yonina C. Wright, John Center for Data Science New York University Department of Computer Science Cornell University Weizmann Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel Department of Electrical Engineering Department of Applied Physics and Applied Mathematics Data Science Institute Columbia University Department of Electrical Engineering and Data Science Institute Columbia University

We study the convolutional phase retrieval problem, of recovering an unknown signal x ∈ Cn from m measurements consisting of the magnitude of its cyclic convolution with a given kernel a ∈ Cm. This model is motivated by applications such as channel estimation, optics, and underwater acoustic communication, where the signal of interest is acted on by a given channel/filter, and phase information is difficult or impossible to acquire. We show that when a is random and the number of observations m is sufficiently large, with high probability x can be efficiently recovered up to a global phase shift using a combination of spectral initialization and generalized gradient descent. The main challenge is coping with dependencies in the measurement operator. We overcome this challenge by using ideas from decoupling theory, suprema of chaos processes and the restricted isometry property of random circulant matrices, and recent analysis of alternating minimization methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Convolution

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Quality Assessment of DEM Generated from SAR Radargrammetry Based on Cross-Correlation and Spatial Resolution Setting

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Journal of Physics: Conference Series 2019年第1期1201卷

作者： R Arief A Setiyoko R Maulana S Ali D Sudiana A M Arymurthy Remote Sensing Technology and Data Center Indonesian National Institute of Aeronautics and Space (LAPAN) Jakarta Indonesia Faculty of Computer Science Universitas Indonesia Depok West Java Indonesia Department of Electrical Engineering Universitas Indonesia Depok West Java Indonesia

DEM as a model of earth's surface model plays an important role in the environmental analysis. The most common recent technology in producing DEM is SAR. Even though it has advantages compared to optical approach, DEM generated from SAR still has issues regarding process setting regarding cross-correlation and spatial resolution determination. Both aspects will affect the volume of output data and computational effort. This research project is aimed to analyze the effects of cross-correlation and spatial resolution determination in DEM generation process to its accuracy. Several experiment scenarios of cross-correlation and spatial resolution setting had been applied to TerraSAR-X data. Overall output is shown that determination of cross-correlation threshold and spatial resolution in processing stages will have a significant effect on the accuracy of DEM generated. Gaps of data often occur in several sets of both aspects.

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Searching for GRBs at VHE with MAGIC: The status before CTA

arXiv

引用

arXiv 2019年

作者： Berti, Alessio Antonelli, Lucio Angelo Bošnjak, Zeljka Cortina, Juan Covino, Stefano D’Elia, Valerio do Souto Espiñeira, Elia Fukami, Satoshi Inoue, Susumu Longo, Francesco Miceli, Davide Moretti, Elena Nava, Lara Noda, Koji Nozaki, Seya Peresano, Michele Suda, Yusuke Will, Martin University of Torino INFN Torino Torino Italy INAF National Institute for Astrophysics Rome Italy Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia CIEMAT Madrid Spain INAF Osservatorio Astronomico di Brera Merate Italy Space Science Data Center - Agenzia Spaziale Italiana Rome Italy Spain ICRR University of Tokyo Kashiwa Chiba Japan RIKEN Wako Saitama Japan University of Trieste INFN Trieste Trieste Italy University of Udine INFN Trieste Udine Italy Department of Physics Kyoto University Kyoto Japan Max-Planck-Institut für Physik Munich Germany

Gamma-Ray Bursts (GRBs) are one of the main targets for current and next generation Imaging Atmospheric Cherenkov Telescopes (IACTs). Given their transient behavior, especially in the case of their prompt emission phase, performing fast follow-up observations is challenging for IACTs, which have a narrow field of view and limited duty cycle. Despite this, MAGIC plays a major role in the search for Very High Energy (VHE, E>100 GeV) gamma-ray emission from GRBs: this is possible thanks to its fast repositioning speed, low energy threshold and high sensitivity at the lowest energies. In 2013 the MAGIC GRB automatic procedure was upgraded, increasing the number of GRBs followed in the prompt and early afterglow phases and decreasing dramatically hardware failures during fast repositioning. Currently, only GRB 190114C was firmly detected in the VHE band, while for other GRBs no significant detection was achieved. In such a case, upper limits (ULs) can give insight into the physics driving such eluding sources, especially on their emission mechanisms. In this contribution we report on the status of the GRB follow-up with MAGIC and focus on the ULs and results obtained from a sample of GRBs observed between 2013 and 2018. This GRB catalog is the result of the MAGIC well-designed and tested follow-up procedure, and it serves as a precursor of GRBs observation with the next generation IACT system, the Cherenkov Telescope Array (CTA). Copyright © 2019, The Authors. All rights reserved.

关键词： Gamma rays

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Random asynchronous iterations in distributed coordination algorithms

arXiv

引用

arXiv 2018年

作者： Chen, Yao Xia, Weiguo Cao, Ming Lü, Jinhu Department of Computer Science Southwestern University of Finance and Economics Chengdu611130 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China Faculty of Science and Engineering ENTEG University of Groningen Groningen9747 AG Netherlands School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

Distributed coordination algorithms (DCA) carry out information processing processes among a group of networked agents without centralized information fusion. Though it is well known that DCA characterized by an SIA (stochastic, indecomposable, aperiodic) matrix generate consensus asymptotically via synchronous iterations, the dynamics of DCA with asynchronous iterations have not been studied extensively, especially when viewed as stochastic processes. This paper aims to show that for any given irreducible stochastic matrix, even non-SIA, the corresponding DCA lead to consensus successfully via random asynchronous iterations under a wide range of conditions on the transition probability. Particularly, the transition probability is neither required to be independent and identically distributed, nor characterized by a Markov chain. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

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On buildings that compute. A proposal

arXiv

引用

arXiv 2018年

作者： Adamatzky, Andrew Szacilowski, Konrad Przyczyna, Dawid Konkoli, Zoran Sirakoulis, Georgios C. Werner, Liss C. Unconventional Computing Laboratory UWE Bristol United Kingdom AGH University of Science and Technology Academic Centre for Materials and Nanotechnology Kraków Poland AGH University of Science and Technology Faculty of Physics and Applied Computer Science Kraków Poland Chalmers University of Technology Department of Microtechnology and Nanoscience Göthenburg Sweden Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Institute of Architecture Technical University of Berlin Germany

We present ideas aimed at bringing revolutionary changes on architectures and buildings of tomorrow by radically advancing the technology for the building material concrete and hence building components. We propose that by using nanotechnology we could embed computation and sensing directly into the material used for construction. Intelligent concrete blocks and panels advanced with stimuli-responsive smart paints are the core of the proposed architecture. In particular, the photo-responsive paint would sense the buildings internal and external environment while the nano-materialconcrete composite material would be capable of sensing the building environment and implement massive-parallel information processing resulting in distributed decision making. A calibration of the proposed materials with in-materio suitable computational methods and corresponding building in-formation modelling, computer-aided design and digital manufacturing tools could be achieved via models and prototypes of information processing at nano-level. The emergent technology sees a building as high-level massiveparallel computer - assembled of computing concrete blocks. Based on the generic principles of neuromorphic computation and reservoir computing we envisage a single building or an urban quarter to turn into a large-scale sensing substrate. It could behave as a universal computer, collecting and processing environmental information in situ enabling appropriate data fusion. The broad range of spatio-temporal effects include infrastructural and human mobility, energy, bio-diversity, digital activity, urban management, art and socializing, robustness with regard to damage and noise or real-time monitoring of environmental changes. The proposed intelligent architectures will increase sustainability and viability in digitised urban environments by decreasing information transfer bandwidth by e.g, utilising 5G networks. The emergence of socio-cultural effect will create a cybernetic relationsh

关键词： Decision making

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The first Hadamard variation of Neumann-Poincaré eigenvalues on the sphere

arXiv

引用

arXiv 2018年

作者： Ando, Kazunori Kang, Hyeonbae Miyanishi, Yoshihisa Ushikoshi, Erika Department of Electrical and Electronic Engineering and Computer Science Ehime University Ehime790-8577 Japan Department of Mathematics Institute of Applied Mathematics Inha University Incheon22212 Korea Republic of Center for Mathematical Modeling and Data Science Osaka University Osaka560-8531 Japan Faculty of Environment and Information Sciences Yokohama National University Kanagawa240-8501 Japan

The Neumann-Poincaré operator on the sphere has 2\(2k1+1\), k = 0, 1, 2,..., as its eigenvalues and the corresponding multiplicity is 2k + 1. We consider the bifurcation of eigenvalues under deformation of domains, and show that Frechét derivative of the sum of the bifurcations is zero. We then discuss the connection of this result with some conjectures regarding the Neumann-Poincaré *** Codes 47A45, 31B25 Copyright © 2018, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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