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Nature communications 2020年第1期11卷 2891页

作者： Brandon Jew Marcus Alvarez Elior Rahmani Zong Miao Arthur Ko Kristina M Garske Jae Hoon Sul Kirsi H Pietiläinen Päivi Pajukanta Eran Halperin Bioinformatics Interdepartmental Program UCLA Los Angeles CA 90095 USA. Department of Human Genetics David Geffen School ofMedicine at UCLA Los Angeles CA 90095 USA. Department of Computer Science School of Engineering UCLA Los Angeles CA 90095 USA. Department of Psychiatry and Biobehavioral Sciences UCLA Los Angeles CA 90095 USA. Obesity Research Unit Research Program for Clinical and Molecular Metabolism University of Helsinki Helsinki 00014 Finland. Obesity Center Endocrinology Abdominal Center Helsinki University Central Hospital and University of Helsinki Helsinki 00260 Finland. Bioinformatics Interdepartmental Program UCLA Los Angeles CA 90095 USA. ppajukanta@mednet.ucla.edu. Department of Human Genetics David Geffen School ofMedicine at UCLA Los Angeles CA 90095 USA. ppajukanta@mednet.ucla.edu. Institute for Precision Health School of Medicine UCLA Los Angeles CA 90095 USA. ppajukanta@mednet.ucla.edu. Department of Human Genetics David Geffen School ofMedicine at UCLA Los Angeles CA 90095 USA. ehalperin@cs.ucla.edu. Department of Computer Science School of Engineering UCLA Los Angeles CA 90095 USA. ehalperin@cs.ucla.edu. Department of Anesthesiology UCLA Health Los Angeles CA 90095 USA. ehalperin@cs.ucla.edu. Department of Computational Medicine School of Medicine UCLA Los Angeles CA 90095 USA. ehalperin@cs.ucla.edu.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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The pathogenicity of COVID-19 and the role of pentraxin-3: An updated review study

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Pathology - Research and Practice 2022年 238卷

作者： Ria Margiana Satish Kumar Sharma Bilal Irshad Khan Ameer A. Alameri Maria Jade Catalan Opulencia Ali Thaeer Hammid Thulfeqar Ahmed Hamza Sharaf Khamrakulovich Babakulov Walid Kamal Abdelbasset Zanko Hassan Jawhar Department of Anatomy Faculty of Medicine Universitas Indonesia Jakarta Indonesia Master's Programme Biomedical Sciences Faculty of Medicine Universitas Indonesia Jakarta Indonesia Andrology Program Faculty of Medicine Universitas Airlangga Surabaya Indonesia Dr. Soetomo General Academic Hospital Surabaya Indonesia Department of Pharmacology Glocal School of Pharmacy The Glocal University Saharanpur India Mbbs Rawalpindi Medical University Rawalpindi Pakistan Department of Chemistry University of Babylon Iraq College of Business Administration Ajman University Ajman United Arab Emirates Computer Engineering Techniques Department Faculty of Information Technology Imam Ja’afar Al-Sadiq University Baghdad Iraq Medical laboratory techniques department Al-Mustaqbal University College Babylon Iraq Tashkent State Dental Institute Makhtumkuli Street 103 Tashkent 100047 Uzbekistan Research scholar Department of Scientific affairs Samarkand State Medical Institute Amir Temur Street 18 Samarkand Uzbekistan Department of Health and Rehabilitation Sciences College of Applied Medical Sciences Prince Sattam bin Abdulaziz University Al Kharj Saudi Arabia Department of Physical Therapy Kasr Al-Aini Hospital Cairo University Giza Egypt Department of Medical Laboratory Science College of Health Science Lebanese French University Kurdistan Region Iraq

In recent years, the COVID-19 pandemic has become one of the most crucial scientific issues in the world, and efforts to eradicate the disease are still ongoing. The acute inflammatory reaction associated with this disease is associated with several complications such as cytokine storm, multiple organ damage, lung fibrosis, and blood clots. PTX3, as part of the humoral innate immune systems, is one of the acute-phase proteins that perform various functions, such as modulating inflammation, repairing tissue, and recruiting immune cells. PTX3 is increased in people with SARS-CoV-2, and its level decreases with proper treatment. Therefore, it can be regarded as a suitable marker for the prognosis of the COVID-19 and evaluating the effectiveness of the treatment method applied. However, some studies have shown that PTX3 can be a double-edged sword and develop tumors by providing an immunosuppressive environment.

关键词： COVID-19 SARS-CoV-2 Pentraxin-3 Acute-phase proteins

A task-oriented and parameterized (semi) autonomous navigation framework for the development of simulation systems

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Procedia computer Science 2017年 112卷 534-543页

作者： Juliana R. Brondani Edison P. de Freitas Luis A.L. Silva Graduate Program in Electrical Engineering Federal University of Rio Grande do Sul Av. Paulo Gama 110 Porto Alegre 90040-060 Brazil Graduate Program in Computer Science Federal University of Santa Maria“ Av. Roraima 1000 Santa Maria 97105-900 Brazil

Agent behaviors in simulation systems are related to fundamental capabilities of realistically developing (semi) autonomous navigation actions. This is particularly important when dealing with the implementation of computer Generated Forces (CGFs) for simulation systems in tactical military training applications. Moreover, these systems take into consideration the particularities of the domain-specific simulation tasks and the numerous heterogeneous CGFs inserted on them in order to generate better knowledge and learning experience to simulation system users. Based on these reasons, this paper reviews recurrent navigation problems as to propose a task-oriented and parameterized (semi) autonomous navigation framework to deal with CGF navigation needs in military simulation. Combining global and local navigation techniques, and controlled transition between alternative degrees of navigation autonomy, the framework aims to overcome the challenges of implementing customizable CGF navigation behaviors and, at the same time, to allow interaction with both users and other simulation systems in distributed simulation settings. A case study is presented in which the proposed techniques are analyzed in a domain-specific simulation problem providing evidence of their suitability to address the studied military simulation problems.

关键词： Navigation problems task-oriented navigation semi-autonomous algorithms simulation systems

Eavesdropping and countermeasures for backflash side channel in quantum cryptography

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arXiv 2018年

作者： Pinheiro, Paulo Vinicius Pereira Chaiwongkhot, Poompong Sajeed, Shihan Horn, Rolf T. Bourgoin, Jean-Philippe Jennewein, Thomas Lütkenhaus, Norbert Makarov, Vadim Engineering Department Paraíso Faculty of Ceará Juazeiro do Norte Ceará63010-465 Brazil Department of Teleinformatic Engineering Federal University of Ceará C.P.6007 Campus do Pici Fortaleza Brazil Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Computer Engineering University of Toronto M5S 3G4 Canada Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Quantum Information Science Program Canadian Institute for Advanced Research TorontoON Canada Russian Quantum Center MISIS University Moscow Russia

Quantum key distribution (QKD) promises information theoretic secure key as long as the device performs as assumed in the theoretical model. One of the assumptions is an absence of information leakage about individual photon detection outcomes of the receiver unit. Here we investigate the information leakage from a QKD receiver due to photon emission caused by detection events in single-photon detectors (backflash). We test commercial silicon avalanche photodiodes and a photomultiplier tube, and find that the former emit backflashes. We study the spectral, timing and polarization characteristics of these backflash photons. We experimentally demonstrate on a free-space QKD receiver that an eavesdropper can distinguish which detector has clicked inside it, and thus acquire secret information. A set of countermeasures both in theory and on the physical devices are discussed. Copyright © 2018, The Authors. All rights reserved.

关键词： Quantum cryptography

Color naming reflects both perceptual structure and communicative need

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arXiv 2018年

作者： Zaslavsky, Noga Kemp, Charles Tishby, Naftali Regier, Terry Edmond and Lily Safra Centre for Brain Sciences Hebrew University Jerusalem9190401 Israel Department of Psychology Carnegie Mellon University PittsburghPA15213 United States Benin School of Computer Science and Engineering Hebrew University Jerusalem9190401 Israel Department of Linguistics University of California BerkeleyCA94720 United States Cognitive Science Program University of California BerkeleyCA94720 United States

Gibson et al. (2017) argued that color naming is shaped by patterns of communicative need. In support of this claim, they showed that color naming systems across languages support more precise communication about warm colors than cool colors, and that the objects we talk about tend to be warm-colored rather than cool-colored. Here, we present new analyses that alter this picture. We show that greater communicative precision for warm than for cool colors, and greater communicative need, may both be explained by perceptual structure. However, using an information-theoretic analysis, we also show that color naming across languages bears signs of communicative need beyond what would be predicted by perceptual structure alone. We conclude that color naming is shaped both by perceptual structure, as has traditionally been argued, and by patterns of communicative need, as argued by Gibson et al. - although for reasons other than those they advanced. Copyright © 2018, The Authors. All rights reserved.

关键词： Color

High-Throughput Screening: One-Step Generation of a Drug-Releasing Hydrogel Microarray-On-A-Chip for Large-Scale Sequential Drug Combination Screening (Adv. Sci. 3/2019)

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Advanced Science 2019年第3期6卷 1970014-1970014页

作者： Seo Woo Song Su Deok Kim Dong Yoon Oh Yongju Lee Amos Chungwon Lee Yunjin Jeong Hyung Jong Bae Daewon Lee Sumin Lee Jiyun Kim Sunghoon Kwon Department of Electrical and Computer Engineering Seoul National University Seoul 08826 South Korea Institutes of Entrepreneurial BioConvergence Seoul National University Seoul 08826 South Korea Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign Urbana IL 61801 USA Nano Systems Institute Seoul National University Seoul 08826 South Korea Interdisciplinary Program in Bioengineering Seoul National University Seoul 08826 South Korea School of Materials Science and Engineering Ulsan National Institute of Science and Technology Ulsan 44919 South Korea

Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

Hybrid approach of relation network and localized graph convolutional filtering for breast cancer subtype classification

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arXiv 2017年

作者： Rhee, Sungmin Seo, Seokjun Kim, Sun Department of Computer Science and Engineering Seoul National University Bioinformatics Institute Seoul National University Seoul Korea Republic of Interdisciplinary Program in Bioinformatics Seoul National University

Network biology has been successfully used to help reveal complex mechanisms of disease, especially cancer. On the other hand, network biology requires in-depth knowledge to construct diseasespecific networks, but our current knowledge is very limited even with the recent advances in human cancer biology. Deep learning has shown an ability to address the problem like this. However, it conventionally used grid-like structured data, thus application of deep learning technologies to the human disease subtypes is yet to be explored. To overcome the issue, we propose a hybrid model, which integrates two key components 1) graph convolution neural network (graph CNN) and 2) relation network (RN). Experimental results on synthetic data and breast cancer data demonstrate that our proposed method shows better performances than existing methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Diseases

Author Correction: Effect of de novo transcriptome assembly on transcript quantification

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Scientific reports 2019年第1期9卷 18041页

作者： Ping-Han Hsieh Yen-Jen Oyang Chien-Yu Chen Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei 10617 Taiwan. Department of Computer Science and Information Engineering National Taiwan University Taipei 10617 Taiwan. Department of Bio-Industrial Mechatronics Engineering National Taiwan University Taipei 10617 Taiwan. chienyuchen@ntu.edu.tw. Genome and Systems Biology Program National Taiwan University and Academia sinica Taipei 10617 Taiwan. chienyuchen@ntu.edu.tw.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Quantized memory-augmented neural networks

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arXiv 2017年

作者： Park, Seongsik Kim, Seijoon Lee, Seil Bae, Ho Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Interdisciplinary Program in Bioinformatics Seoul National University Seoul08826 Korea Republic of

Memory-augmented neural networks (MANNs) refer to a class of neural network models equipped with external memory (such as neural Turing machines and memory networks). These neural networks outperform conventional recurrent neural networks (RNNs) in terms of learning long-term dependency, allowing them to solve intriguing AI tasks that would otherwise be hard to address. This paper concerns the problem of quantizing MANNs. Quantization is known to be effective when we deploy deep models on embedded systems with limited resources. Furthermore, quantization can substantially reduce the energy consumption of the inference procedure. These benefits justify recent developments of quantized multilayer perceptrons, convolutional networks, and RNNs. However, no prior work has reported the successful quantization of MANNs. The in-depth analysis presented here reveals various challenges that do not appear in the quantization of the other networks. Without addressing them properly, quantized MANNs would normally suffer from excessive quantization error which leads to degraded performance. In this paper, we identify memory addressing (specifically, content-based addressing) as the main reason for the performance degradation and propose a robust quantization method for MANNs to address the challenge. In our experiments, we achieved a computation-energy gain of 22× with 8-bit fixed-point and binary quantization compared to the floating-point implementation. Measured on the bAbI dataset, the resulting model, named the quantized MANN (Q-MANN), improved the error rate by 46% and 30% with 8-bit fixed-point and binary quantization, respectively, compared to the MANN quantized using conventional techniques. Copyright © 2017, The Authors. All rights reserved.

关键词： Recurrent neural networks