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第35届中国控制会议

作者： LIU Hongjie CHEN Lijie Eckehard Schnieder State Key Lab of Rail Traffic Control & Safety Beijing Jiaotong University National Engineering Research Center of Rail Transportation Operation & Control System Beijing Jiaotong University Institute of Standards & Measurements China Academy of Railway Sciences Institute for traffic safety and automation engineering Technical University Braunschweig

ISBN: (纸本)9781509009107

The safety communication protocol is a main factor affecting the train control system. Its performance analysis is of great significance to the train control system. After introducing the procedure of safety communication protocol in the train control system briefly, this paper first explores the application of hierarchy timed Colored Petri Net(CPN) to establish the models of the protocol, including the models of state transition process and the models with time delay and packet loss to imply the influent factors, then collects related performance data such as time for establishment of safety connection, with different time delay and probability of packet loss via simulation. The simulation results could provide a certain reference for the safety communication protocol design and development. Finally, this paper finds how the time delay and packet loss could influent the time for the establishment of safety connection through data interaction process based on theory of probability and mathematical statistic, which is reasonable.

关键词： Safety communication protocol Train control system Petri net Theory of probability Mathematical statistic

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Model-based test case generation for function testing of CTCS-3 onboard subsystem

International Journal of Control and Automation

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International Journal of control and Automation 2015年第10期8卷 171-178页

作者： Lv, Jidong Ren, Pengcheng Lei, Chen Li, Kaicheng Tang, Tao National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China State1 Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School Of Electronics Electrical and Computer Engineering The University of Birmingham Birmingham United Kingdom

The CTCS-3(Chinese Train control system level 3) is an automatic system which is an integrated of advanced control technology, advanced communication technology, advanced computer technology and railway signal technology. It plays an important role in assuring safety and improving efficiency in railway. As a core subsystem in CTCS-3, the onboard subsystem is a typical safety-critical system, in which any fault can lead to huge human injury or wealth losing. Function testing method which is mainly focus on the conformance relation between the specification and the system Under Test (SUT) has been widely used in testing onboard subsystem in the past few years. However, most of the test cases are manually generated which can 1 be reused and leads to repeated works when the specification is changed. To improve the testing efficiency and quality, model-based testing method is introduced. We use a tool chain to generate test case automatically based on Timed Automata theory and then apply in function testing of onboard subsystem. Firstly, we establish the scenario-tree by analyzing the specification of onboard subsystem and Vital Computer and Environment (V-E) timed automata network model of mode transition using tool Uppaal. Then, according to the relation between train modes and operational scenarios, test cases are automatically generated by tool CoVer with definition coverage criteria based on the Observer Automata theory. Finally, a selection algorithm is given to choose a complete test sequence from the test cases. Different test suitss of onboard subsystem are acquired and compared with different coverage criteria and coverage items. A complete model transition function test suits are derived which is proven very useful for testing the onboard subsystem. © 2015 SERSC.

关键词： Specifications

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Trends of Extreme Precipitation in Eastern China and Their Possible Causes

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Advances in Atmospheric Sciences 2015年第8期32卷 1027-1037页

作者： LIU Run LIU Shaw Chen Ralph J.CICERONE SHIU Chein-Jung LI Jun WANG Jingli ZHANG Yuanhang State Key Joint Laboratory of Environmental Simulation and Pollution Control College of Environmental Sciences and Engineering Peking University Research Center for Environmental Changes Academia Sinica Department of Atmospheric Science NCU National Academy of Sciences Earth System Science University of California Institute of Urban Meteorology of China Meteorological Administration

Significant increases of heavy precipitation and decreases of light precipitation have been reported over widespread regions of the globe. Global warming and effects of anthropogenic aerosols have both been proposed as possible causes of these changes. We examine data from urban and rural meteorological stations in eastern China （1955-2011） and compare them with Global Precipitation Climatology Project （GPCP） data （1979-2007） and reanalysis data in various latitude zones to study changes in precipitation extremes. Significant decreases in light precipitation and increases in heavy precipitation are found at both rural and urban stations, as well as low latitudes over the ocean, while total precipitation shows little change. Characteristics of these changes and changes in the equatorial zone and other latitudes suggest that global warming rather than aerosol effects is the primary cause of the changes. In eastern China, increases of annual total dry days （28 days） and ） 10 consecutive dry days （36%） are due to the decrease in light precipitation days, thereby establishing a causal link among global warming, changes in precipitation extremes, and higher meteorological risk of floods and droughts. Further, results derived from the GPCP data and reanalysis data suggest that the causal link exists over widespread regions of the globe.

关键词： extreme precipitation global warming aerosols meteorological risk of floods and droughts

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Response to Comments by Yuan WANG on “Trends of Extreme Precipitation in Eastern China and Their Possible Causes”

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Advances in Atmospheric Sciences 2015年第10期32卷 1447-1448页

作者： LIU Run LIU Shaw Chen Ralph J.CICERONE SHIU Chein-Jung LI Jun WANG Jingli ZHANG Yuanhang State Key Joint Laboratory of Environmental Simulation and Pollution Control College of Environmental Sciences and EngineeringPeking University Research Center for Environmental Changes Academia Sinica Department of Atmospheric Science NCU National Academy of Sciences Earth System Science University of California Institute of Urban Meteorology of China Meteorological Administration

In his comments, Wang cites a number of works to dispute the conclusion in our previous work, which attributes the observed decreases/increases in light/heavy precipitation in eastern China primarily to global warming rather than the regional aerosol effect. However, most of the cited works （admittedly, including our previous work）, employ correlation analysis, which has little bearing on the cause--effect relationship. Theoretical analyses and/or modeling studies are needed to ascertain the cause-effect relationship. We argue that theoretical analyses and modeling results show that global warming is the primary cause of the widely observed phenomena of suppression of light precipitation and enhancement of heavy precipitation across the globe, including in eastern China.

关键词： extreme precipitation global warming aerosols

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基于指令域电控数据分析的数控机床工作过程CPS建模及应用

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engineering 2015年第2期 173-199页

作者：陈吉红杨建中周会成向华朱志红李叶松李振瀚许光达 National Numerical Control System Engineering Research Center Huazhong University of Science and Technology

建立机器的信息物理系统(CPS)模型是智能制造的关键技术。本文指出了数控机床工作过程中数控系统内部的海量电控数据是构建数控机床工作过程CPS模型的大数据的主要来源;提出了基于指令域电控数据分析方法,利用被加工零件的G指令对数控... 详细信息

建立机器的信息物理系统(CPS)模型是智能制造的关键技术。本文指出了数控机床工作过程中数控系统内部的海量电控数据是构建数控机床工作过程CPS模型的大数据的主要来源;提出了基于指令域电控数据分析方法,利用被加工零件的G指令对数控加工的工作任务进行定量描述,在指令域内建立数控机床的工作任务、制造资源和运行状态之间的实时、精准的映射关系,以此为基础进一步构建数控机床工作过程的CPS模型;利用这一模型,进行了数控加工工艺参数优化、数控机床健康保障等智能化应用的案例研究。

关键词：信息物理系统(CPS) 大数据数控机床工作过程电控数据指令域智能化应用

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Stackelberg Game Model of Wind Farm and Electric Vehicle Battery Switch Station

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IOP Conference Series: Materials Science and engineering 2017年第1期199卷

作者： Zhe Jiang Zhimin Li Wenbo Li Mingqiang Wang Mengxia Wang Department of Electrical Engineering Harbin Institute of Technology Harbin 150001 China. Electric Power Research Institute State Grid Shandong Electric Power Company Jinan 250003 China. Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan 250061 China. Collaborative Innovation Center for Global Energy Interconnection (Shandong) Jinan 250061 China.

In this paper, a cooperation method between wind farm and Electric vehicle battery switch station (EVBSS) was proposed. In the pursuit of maximizing their own benefits, the cooperation between wind farm and EVBSS was formulated as a Stackelberg game model by treating them as decision makers in different status. As the leader, wind farm will determine the charging/discharging price to induce the charging and discharging behavior of EVBSS reasonably. Through peak load shifting, wind farm could increase its profits by selling more wind power to the power grid during time interval with a higher purchase price. As the follower, EVBSS will charge or discharge according to the price determined by wind farm. Through optimizing the charging /discharging strategy, EVBSS will try to charge with a lower price and discharge with a higher price in order to increase its profits. Since the possible charging /discharging strategy of EVBSS is known, the wind farm will take the strategy into consideration while deciding the charging /discharging price, and will adjust the price accordingly to increase its profits. The case study proved that the proposed cooperation method and model were feasible and effective.

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Cover Feature: Ultrasensitive, Sustainable, and Selective Electrochemical Hydrazine Detection by ALD-Developed Two-Dimensional WO3(ChemElectroChem 2/2018)

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ChemElectroChem 2017年第2期5卷

作者： Zihan Wei Zhenyin Hai Mohammad Karbalaei Akbari Prof. Jie Hu Lachlan Hyde Prof. Stephen Depuydt Prof. Francis Verpoort Prof. Serge Zhuiykov Ghent University Global Campus Department of Applied Analytical & Physical Chemistry 119 Songdomunhwa-ro Yeonsu-gu Incheon South Korea Micro and Nano System Research Center Key Lab of Advanced Transducers and Intelligent Control System (Ministry of Education) & College of Information Engineering Taiyuan University of Technology Taiyuan 030024 Shanxi PR China Factory of the Future Swinburne University of Technology Hawthorn Australia National Research Tomsk Polytechnic University Lenin Avenue 30 634050 Tomsk Russian Federation Laboratory of Organometallics Catalysis and Ordered Materials State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Center for Chemical and Material Engineering Wuhan University of Technology Wuhan P.R. China

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Proceedings from the 9th annual conference on the science of dissemination and implementation: Washington, DC, USA. 14-15 December 2016

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Implement Sci 2017年第SUPPL 1期12卷 48-48页

作者： David Chambers Lisa Simpson Gila Neta Ulrica von Thiele Schwarz Antoinette Percy-Laurry Gregory A. Aarons Ross Brownson Amanda Vogel Shannon Wiltsey Stirman Kenneth Sherr Rachel Sturke Wynne E. Norton Allyson Varley Cynthia Vinson Lisa Klesges Suzanne Heurtin-Roberts M. Rashad Massoud Leighann Kimble Arne Beck Claire Neely Jennifer Boggs Carmel Nichols Wen Wan Erin Staab Neda Laiteerapong Nathalie Moise Ravi Shah Susan Essock Margaret Handley Amy Jones Jay Carruthers Karina Davidson Lauren Peccoralo Lloyd Sederer Todd Molfenter Ashley Scudder Sarah Taber-Thomas Kristen Schaffner Amy Herschell Eva Woodward Jeffery Pitcock Mona Ritchie JoAnn Kirchner Julia E. Moore Sobia Khan Shusmita Rashid Jamie Park Melissa Courvoisier Sharon Straus Daniel Blonigen Allison Rodriguez Luisa Manfredi Andrea Nevedal Joel Rosenthal David Smelson Christine Timko Nicole Stadnick Jennifer Regan Miya Barnett Anna Lau Lauren Brookman-Frazee Erick Guerrero Karissa Fenwick Yinfei Kong Gregory Aarons Rebecca Lengnick-Hall Benjamin Henwood Nina Sayer Craig Rosen Robert Orazem Brandy Smith Lindsey Zimmerman David Lounsbury Rachel Kimerling Jodie A. Trafton Steven Lindley Rahul Bhargava Hal Roberts Laura Gibson Gabriel J. Escobar Vincent Liu Benjamin Turk Arona Ragins Patricia Kipnis Ashley Ketterer Gruszkowski Michael W. Kennedy Emily Rentschler Drobek Lior Turgeman Aleksandra Sasha Milicevic Terrence L. Hubert Larissa Myaskovsky Youxu C. Tjader Robert J. Monte Kathryn G. Sapnas Edmond Ramly Diane R Lauver Christie M Bartels Shereef Elnahal Andrea Ippolito Hillary Peabody Carolyn Clancy Randall Cebul Thomas Love Douglas Einstadter Shari Bolen Brook Watts Vera Yakovchenko Angela Park William Lukesh Donald R. Miller David Thornton Mari-Lynn Drainoni Allen L. Gifford Shawna Smith Julia Kyle Mark S Bauer Daniel Eisenberg Celeste Liebrecht Michelle Barbaresso Amy Kilbourne Elyse Park Giselle Perez Jamie Ostroff Sarah Greene Michael Parchman Brian Austin Eric Larson Stefanie Ferreri Chris Shea Megan Smith Kea Turner Jennifer Bacci Kyle Bigham Geoffr Division of Cancer Control and Population Sciences National Cancer Institute Rockville MD 20850 USA AcademyHealth Washington DC 20009 USA Department of Learning Informatics Management and Ethics Karolinska Institutet Stockholm 17177 Sweden Department of Psychiatry University of California San Diego San Diego CA 92093 USA George Warren Brown School of Social Work Washington University in St. Louis St. Louis MO 63130 USA Center for Global Health National Cancer Institute Rockville MD 20850 USA Dissemination and Training Division VA National Center for PTSD Palo Alto CA 94305 USA Department of Global Health University of Washington Seattle WA 98105 USA Center for Global Health Studies Fogarty International Center National Institutes of Health Bethesda MD 20912 USA School of Public Health University of Alabama at Birmingham Birmingham AL 35243 USA School of Public Health University of Memphis Memphis TN 38152 USA USAID Applying Science to Strengthen and Improve Systems (ASSIST) Project Bethesda Maryland 20814 USA Institute for Health Research Kaiser Permanente Denver CO 80231 USA ICSI Institute for Clinical Systems Improvement Bloomington MN 55425 USA Medicine University of Chicago Chicago IL 60637 USA Medicine Columbia University Medical Center New York NY 10032 USA Psychiatry Columbia University New York NY 10032 USA General Internal Medicine Epidemiology and Biostatistics University of California San Francisco San Francisco CA 94110 USA New York State Office of Mental Health New York NY 10001 USA Medicine Icahn School of Medicine at Mount Sinai New York NY 10029 USA Center for Health Enhancement System Studies University of Wisconsin Madison WI 53706 USA Department of Psychiatry University of Pittsburgh Pittsburgh PA 15213 USA Psychology University at Buffalo Buffalo NY 14260 USA Department of Psychology West Virginia University Morgantown WV 26506 USA MIRECC VA North Little Rock AR 72114 USA QUERI for Team-Based Behavioral Health Centr

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Association between GWAS-identified lung adenocarcinoma susceptibility loci and EGFR mutations in never-smoking Asian women, and comparison with findings from Western populations

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Human molecular genetics 2017年第2期26卷 454-465页

作者： Wei Jie Seow Keitaro Matsuo Chao Agnes Hsiung Kouya Shiraishi Minsun Song Hee Nam Kim Maria Pik Wong Yun-Chul Hong H Dean Hosgood Zhaoming Wang I-Shou Chang Jiu-Cun Wang Nilanjan Chatterjee Margaret Tucker Hu Wei Tetsuya Mitsudomi Wei Zheng Jin Hee Kim Baosen Zhou Neil E Caporaso Demetrius Albanes Min-Ho Shin Lap Ping Chung She-Juan An Ping Wang Hong Zheng Yasushi Yatabe Xu-Chao Zhang Young Tae Kim Xiao-Ou Shu Young-Chul Kim Bryan A Bassig Jiang Chang James Chung Man Ho Bu-Tian Ji Michiaki Kubo Yataro Daigo Hidemi Ito Yukihide Momozawa Kyota Ashikawa Yoichiro Kamatani Takayuki Honda Hiromi Sakamoto Hideo Kunitoh Koji Tsuta Shun-Ichi Watanabe Hiroshi Nokihara Yohei Miyagi Haruhiko Nakayama Shingo Matsumoto Masahiro Tsuboi Koichi Goto Zhihua Yin Jianxin Shi Atsushi Takahashi Akiteru Goto Yoshihiro Minamiya Kimihiro Shimizu Kazumi Tanaka Tangchun Wu Fusheng Wei Jason Y Y Wong Fumihiko Matsuda Jian Su Yeul Hong Kim In-Jae Oh Fengju Song Victor Ho Fun Lee Wu-Chou Su Yuh-Min Chen Gee-Chen Chang Kuan-Yu Chen Ming-Shyan Huang Pan-Chyr Yang Hsien-Chih Lin Yong-Bing Xiang Adeline Seow Jae Yong Park Sun-Seog Kweon Chien-Jen Chen Haixin Li Yu-Tang Gao Chen Wu Biyun Qian Daru Lu Jianjun Liu Hyo-Sung Jeon Chin-Fu Hsiao Jae Sook Sung Ying-Huang Tsai Yoo Jin Jung Huan Guo Zhibin Hu Wen-Chang Wang Charles C Chung Charles Lawrence Laurie Burdett Meredith Yeager Kevin B Jacobs Amy Hutchinson Sonja I Berndt Xingzhou He Wei Wu Junwen Wang Yuqing Li Jin Eun Choi Kyong Hwa Park Sook Whan Sung Li Liu Chang Hyun Kang Lingmin Hu Chung-Hsing Chen Tsung-Ying Yang Jun Xu Peng Guan Wen Tan Chih-Liang Wang Alan Dart Loon Sihoe Ying Chen Yi Young Choi Jen-Yu Hung Jun Suk Kim Ho-Il Yoon Qiuyin Cai Chien-Chung Lin In Kyu Park Ping Xu Jing Dong Christopher Kim Qincheng He Reury-Perng Perng Chih-Yi Chen Roel Vermeulen Junjie Wu Wei-Yen Lim Kun-Chieh Chen John K C Chan Minjie Chu Yao-Jen Li Jihua Li Hongyan Chen Chong-Jen Yu Li Jin Yen-Li Lo Ying-Hsiang Chen Joseph F Fraumeni Jie Liu Taiki Yamaji Yang Yang Belynda Hicks Kathleen Wyatt Shengchao A Li Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda MD USA. Saw Swee Hock School of Public Health National University of Singapore and National University Health System Singapore. Division of Molecular Medicine Aichi Cancer Center Research Institute Nagoya Japan. Institute of Population Health Sciences National Health Research Institutes Zhunan Taiwan. Division of Genome Biology National Cancer Center Research Institute Tokyo Japan. Department of Statistics Sookmyung Women's University Seoul Republic of Korea. Department of Preventive Medicine Chonnam National University Medical School Gwangju Republic of Korea. Department of Pathology The University of Hong Kong Queen Mary Hospital Hong Kong. Department of Preventive Medicine Seoul National University College of Medicine Seoul Republic of Korea. Department of Epidemiology and Population Health Albert Einstein College of Medicine Bronx NY USA. Department of Computational Biology St. Jude Children's Research Hospital Memphis TN 38105 USA. National Institute of Cancer Research National Health Research Institutes Zhunan Taiwan. Ministry of Education Key Laboratory of Contemporary Anthropology School of Life Sciences Fudan University Shanghai People's Republic of China. State Key Laboratory of Genetic Engineering School of Life Sciences Fudan University Shanghai People's Republic of China. Division of Thoracic Surgery Kinki University School of Medicine Sayama Japan. Division of Epidemiology Department of Medicine Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center Nashville TN USA. Department of Integrative Bioscience & Biotechnology Sejong University Seoul Republic of Korea. Department of Epidemiology School of Public Health China Medical University Shenyang People's Republic of China. Guangdong Lung Cancer Institute Medical Research Center and Cancer Center of Guangdong General Hospital Guangdong Academy of Medical Sciences Guangzhou People's Republic

To evaluate associations by EGFR mutation status for lung adenocarcinoma risk among never-smoking Asian women, we conducted a meta-analysis of 11 loci previously identified in genome-wide association studies (GWAS). Genotyping in an additional 10,780 never-smoking cases and 10,938 never-smoking controls from Asia confirmed associations with eight known single nucleotide polymorphisms (SNPs). Two new signals were observed at genome-wide significance (P < 5 × 10-8), namely, rs7216064 (17q24.3, BPTF), for overall lung adenocarcinoma risk, and rs3817963 (6p21.3, BTNL2) which is specific to cases with EGFR mutations. In further sub-analyses by EGFR status, rs9387478 (ROS1/DCBLD1) and rs2179920 (HLA-DPB1) showed stronger estimated associations in EGFR-positive compared to EGFR-negative cases. Comparison of the overall associations with published results in Western populations revealed that the majority of these findings were distinct, underscoring the importance of distinct contributing factors for smoking and non-smoking lung cancer. Our results extend the catalogue of regions associated with lung adenocarcinoma in non-smoking Asian women and highlight the importance of how the germline could inform risk for specific tumour mutation patterns, which could have important translational implications.

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