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Author Correction: A consensus protocol for functional connectivity analysis in the rat brain

Nature neuroscience 2023年 2023 Apr 18页

作者： Joanes Grandjean Gabriel Desrosiers-Gregoire Cynthia Anckaerts Diego Angeles-Valdez Fadi Ayad David A Barrière Ines Blockx Aleksandra Bortel Margaret Broadwater Beatriz M Cardoso Marina Célestine Jorge E Chavez-Negrete Sangcheon Choi Emma Christiaen Perrin Clavijo Luis Colon-Perez Samuel Cramer Tolomeo Daniele Elaine Dempsey Yujian Diao Arno Doelemeyer David Dopfel Lenka Dvořáková Claudia Falfán-Melgoza Francisca F Fernandes Caitlin F Fowler Antonio Fuentes-Ibañez Clément M Garin Eveline Gelderman Carla E M Golden Chao C G Guo Marloes J A G Henckens Lauren A Hennessy Peter Herman Nita Hofwijks Corey Horien Tudor M Ionescu Jolyon Jones Johannes Kaesser Eugene Kim Henriette Lambers Alberto Lazari Sung-Ho Lee Amanda Lillywhite Yikang Liu Yanyan Y Liu Alejandra López-Castro Xavier López-Gil Zilu Ma Eilidh MacNicol Dan Madularu Francesca Mandino Sabina Marciano Matthew J McAuslan Patrick McCunn Alison McIntosh Xianzong Meng Lisa Meyer-Baese Stephan Missault Federico Moro Daphne M P Naessens Laura J Nava-Gomez Hiroi Nonaka Juan J Ortiz Jaakko Paasonen Lore M Peeters Mickaël Pereira Pablo D Perez Marjory Pompilus Malcolm Prior Rustam Rakhmatullin Henning M Reimann Jonathan Reinwald Rodrigo Triana Del Rio Alejandro Rivera-Olvera Daniel Ruiz-Pérez Gabriele Russo Tobias J Rutten Rie Ryoke Markus Sack Piergiorgio Salvan Basavaraju G Sanganahalli Aileen Schroeter Bhedita J Seewoo Erwan Selingue Aline Seuwen Bowen Shi Nikoloz Sirmpilatze Joanna A B Smith Corrie Smith Filip Sobczak Petteri J Stenroos Milou Straathof Sandra Strobelt Akira Sumiyoshi Kengo Takahashi Maria E Torres-García Raul Tudela Monica van den Berg Kajo van der Marel Aran T B van Hout Roberta Vertullo Benjamin Vidal Roël M Vrooman Victora X Wang Isabel Wank David J G Watson Ting Yin Yongzhi Zhang Stefan Zurbruegg Sophie Achard Sarael Alcauter Dorothee P Auer Emmanuel L Barbier Jürgen Baudewig Christian F Beckmann Nicolau Beckmann Guillaume J P C Becq Erwin L A Blezer Radu Bolbos Susann Boretius Sandrine Bouvard Eike Budinger Joseph D Buxbaum Diana Cash Victor Donders Institute for Brain Behaviour and Cognition Radboud University Nijmegen The Netherlands. joanes.grandjean@radboudumc.nl. Department for Medical Imaging Radboud University Medical Center Nijmegen The Netherlands. joanes.grandjean@radboudumc.nl. Cerebral Imaging Centre Douglas Mental Health University Institute Verdun QC Canada. Integrated Program in Neuroscience McGill University Montreal QC Canada. Bio-imaging Lab University of Antwerp Antwerp Belgium. µNEURO Research Centre of Excellence University of Antwerp Antwerp Belgium. Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro Mexico. Biological and Biomedical Engineering McGill University Montreal QC Canada. McConnell Brain Imaging Centre McGill University Montreal QC Canada. Montreal Neurological Institute McGill University Montreal QC Canada. UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction Physiologie de la reproduction et des comportements Centre de recherche INRAE de Nouzilly Tours France. Department of Neurology and Neurosurgery McGill University Montreal QC Canada. Center for Animal MRI University of North Carolina at Chapel Hill Chapel Hill NC USA. Department of Neurology University of North Carolina at Chapel Hill Chapel Hill NC USA. Biomedical Research Imaging Center University of North Carolina at Chapel Hill Chapel Hill NC USA. Preclinical MRI Champalimaud Research Champalimaud Centre for the Unknown Lisbon Portugal. Laboratoire des Maladies Neurodégénératives Molecular Imaging Research Center (MIRCen) Université Paris-Saclay Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA) CNRS Fontenay-aux-Roses France. Departamento de Neurobiología Conductual y Cognitiva Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro México. Translational Neuroimaging and Neural Control Group High-Field Magnetic Resonance Max Planck Institute for Biological Cyberneti

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Author Correction: The power of genetic diversity in genome-wide association studies of lipids

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Nature 2023年第7965期618卷 E19-E20页

作者： Sarah E Graham Shoa L Clarke Kuan-Han H Wu Stavroula Kanoni Greg J M Zajac Shweta Ramdas Ida Surakka Ioanna Ntalla Sailaja Vedantam Thomas W Winkler Adam E Locke Eirini Marouli Mi Yeong Hwang Sohee Han Akira Narita Ananyo Choudhury Amy R Bentley Kenneth Ekoru Anurag Verma Bhavi Trivedi Hilary C Martin Karen A Hunt Qin Hui Derek Klarin Xiang Zhu Gudmar Thorleifsson Anna Helgadottir Daniel F Gudbjartsson Hilma Holm Isleifur Olafsson Masato Akiyama Saori Sakaue Chikashi Terao Masahiro Kanai Wei Zhou Ben M Brumpton Humaira Rasheed Sanni E Ruotsalainen Aki S Havulinna Yogasudha Veturi QiPing Feng Elisabeth A Rosenthal Todd Lingren Jennifer Allen Pacheco Sarah A Pendergrass Jeffrey Haessler Franco Giulianini Yuki Bradford Jason E Miller Archie Campbell Kuang Lin Iona Y Millwood George Hindy Asif Rasheed Jessica D Faul Wei Zhao David R Weir Constance Turman Hongyan Huang Mariaelisa Graff Anubha Mahajan Michael R Brown Weihua Zhang Ketian Yu Ellen M Schmidt Anita Pandit Stefan Gustafsson Xianyong Yin Jian'an Luan Jing-Hua Zhao Fumihiko Matsuda Hye-Mi Jang Kyungheon Yoon Carolina Medina-Gomez Achilleas Pitsillides Jouke Jan Hottenga Gonneke Willemsen Andrew R Wood Yingji Ji Zishan Gao Simon Haworth Ruth E Mitchell Jin Fang Chai Mette Aadahl Jie Yao Ani Manichaikul Helen R Warren Julia Ramirez Jette Bork-Jensen Line L Kårhus Anuj Goel Maria Sabater-Lleal Raymond Noordam Carlo Sidore Edoardo Fiorillo Aaron F McDaid Pedro Marques-Vidal Matthias Wielscher Stella Trompet Naveed Sattar Line T Møllehave Betina H Thuesen Matthias Munz Lingyao Zeng Jianfeng Huang Bin Yang Alaitz Poveda Azra Kurbasic Claudia Lamina Lukas Forer Markus Scholz Tessel E Galesloot Jonathan P Bradfield E Warwick Daw Joseph M Zmuda Jonathan S Mitchell Christian Fuchsberger Henry Christensen Jennifer A Brody Mary F Feitosa Mary K Wojczynski Michael Preuss Massimo Mangino Paraskevi Christofidou Niek Verweij Jan W Benjamins Jorgen Engmann Rachel L Kember Roderick C Slieker Ken Sin Lo Nuno R Zilhao Phuong Le Marcus E Kleber Graciela E Delgado Shaofeng Huo Dai Department of Internal Medicine Division of Cardiology University of Michigan Ann Arbor MI USA. VA Palo Alto Health Care System Palo Alto CA USA. Department of Medicine Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Department of Biostatistics and Center for Statistics Genetics University of Michigan Ann Arbor MI USA. Department of Genetics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Clinical Pharmacology William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK. Endocrinology Boston Children's Hospital Boston MA USA. Medical and Population Genetics Broad Institute Cambridge MA USA. Department of Genetic Epidemiology University of Regensburg Regensburg Germany. McDonnell Genome Institute and Department of Medicine Washington University St Louis MO USA. Department of Precision Medicine Division of Genome Science National Institute of Health Cheongju-si South Korea. Tohoku Medical Megabank Organization Tohoku University Sendai Japan. Sydney Brenner Institute for Molecular Bioscience Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa. Center for Research on Genomics and Global Health National Human Genome Research Institute National Institutes of Health Bethesda MD USA. Blizard Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Wellcome Sanger Institute Hinxton UK. Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA. Atlanta VA Health Care System Decatur GA USA. Malcolm Randall VA Medical Center Gainesville FL USA. Division of Vascular Sur

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Robust Event-Triggered MPC for Constrained Linear Discrete-Time systems with Guaranteed Average Sampling Rate

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IFAC-PapersOnLine 2015年第23期48卷 117-122页

作者： Brunner, Florian D. Heemels, W.P.M.H. Allgöwer, Frank Institute for Systems Theory and Automatic Control University of Stuttgart Pfaffenwaldring 9 Stuttgart70569 Germany Control System Technology Group Department of Mechanical Engineering Eindhoven University of Technology Netherlands

We propose a robust event-triggered model predictive control (MPC) scheme for linear time-invariant discrete-time systems subject to bounded additive stochastic disturbances and hard constraints on the input and state. For given probability distributions of the disturbances acting on the system, we design event conditions such that the average frequency of communication between the controller and the actuator in the closed-loop system attains a given value. We employ Tube MPC methods to guarantee robust constraint satisfaction and a robust asymptotic bound on the system state. Moreover, we show that based on a given periodically updated Tube MPC scheme, an appropriate event-triggered MPC scheme can be designed, with the same guarantees on constraints and region of attraction, but with a reduced number of average communications. © 2015, IFAC (International Federation of automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Discrete time control systems Closed loop systems Digital control systems Linear control systems Model predictive control Predictive control systems Probability distributions Robustness (control systems) Stochastic models Stochastic systems Constraint Satisfaction Discrete time systems Event triggered controls Linear discrete time systems Linear time invariant Predictive control Region of attraction Stochastic disturbances

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Magnetic swirls and associated fast magnetoacoustic kink waves in a solar chromospheric flux tube

arXiv

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arXiv 2017年

作者： Murawski, K. Kayshap, P. Srivastava, A.K. Pascoe, D.J. Jelínek, P. Kuźma, B. Fedun, V. Maria Curie-Sklodowska University Institute of Physics Group of Astrophysics Radziszewskiego 10 LublinPL–20 031 Poland Centre for Fusion Space and Astrophysics Department of Physics University of Warwick CV4 7AL United Kingdom Department of Physics Indian Institute of Technology Banaras Hindu University Varanasi221005 India University of South Bohemia Faculty of Science Institute of Physics and Biophysics Branišovská 1760 České BudějoviceCZ – 370 05 Czech Republic Space Systems Laboratory Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom

We perform numerical simulations of impulsively generated magnetic swirls in an isolated flux tube which is rooted in the solar photosphere. These swirls are triggered by an initial pulse in a horizontal component of the velocity. The initial pulse is launched either: (a) centrally, within the localized magnetic flux tube;or (b) off-central, in the ambient medium. The evolution and dynamics of the flux tube is described by three-dimensional, ideal magnetohydrodynamic equations. These equations are numerically solved to reveal that in case (a) dipole-like swirls associated with the fast magnetoacoustic kink and m = 1 Alfvén waves are generated. In case (b), the fast magnetoacoustic kink and m = 0 Alfvén modes are excited. In both these cases, the excited fast magnetoacoustic kink and Alfvén waves consist of similar flow pattern and magnetic shells are also generated with clockwise and counter-clockwise rotating plasma within them, which can be the proxy of dipole-shaped chromospheric swirls. The complex dynamics of vortices and wave perturbations reveals the channelling of sufficient amount of energy to fulfill energy losses in the chromosphere (∼ 104 W m−1) and in the corona (∼ 102 W m−1). Some of these numerical findings are reminiscent of signatures in recent observational data. Copyright © 2017, The Authors. All rights reserved.

关键词： Magnetic flux

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A second update on mapping the human genetic architecture of COVID-19

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Nature 2023年第7977期621卷 E7-E26页

作者： Masahiro Kanai Christine Stevens Benjamin M. Neale Mark Daly Andrea Ganna Amy Trankiem Mary K. Balaconis Samuli Ripatti Lindo Nkambul Mark J. Daly Sam Bryant Matthew Solomonson Shea J. Andrews Mattia Cordioli Juha Karjalainen Juha Mehtonen Matti Pirinen Andrea Corbetta Bradley Jermy Kati Donner Katja Kivinen Aarno Palotie Mari Kaunisto Kumar Veerapen Konrad J. Karczewski Alicia R. Martin Elizabeth G. Atkinson Kristin Tsuo Nikolas Baya Rahul Gupta Raymond K. Walters Duncan S. Palmer Gopal Sarma Nathan Cheng Wenhan Lu Claire Churchhouse Jacqueline I. Goldstein Daniel King Wei Zhou Cotton Seed Hilary Finucane F. Kyle Satterstrom Gita A. Pathak Akiko Iwasaki Karolina Chwialkowska Karolina Chwiałkowska Brooke N. Wolford Hajar Fauzan Ahmad Shea Andrews Kathrin Aprile von Hohenstaufen Puoti Palwende R. Boua Guillaume Butler-Laporte Celia M. T. Greenwood Bartha M. Knoppers Mark Lathrop Carmen L. Cadilla Francesca Colombo Nicole Dueker Chloe Kirk Atanu Kumar Dutta Yasser M. El-Sherbiny Jehan J. El-Jawhari Doaa Shahin Ahmed Elzeiny Tamer A. Mansour Madonna M. Eltoukhy Attia A. S. Mohamed Sahar Esmaeeli Annika Faucon Israel Fernández Cadenas Israel Fernandez-Cadenas Laia Llucià-Carol Natalia Cullell Elena Muiño Jara Cárcel-Márquez Margherita Francescatto Laurent Francioli Lindokuhle Nkambule Jatin Arora Soumya Raychaudhuri Caroline Cusick Lude Franke Macarena Fuentes Macarena Fuentes-Guajardo David Gómez Cabrero Emi N. Harry Philip Jansen József L. Szentpéteri Réka Várnai Elżbieta Kaja Athanasios Kousathanas Dorote Pasko Mark J. Caulfield Alex Stuckey Christopher A. Odhams Susan Walker Daniel Rhodes Richard H. Scott Loukas Moutsianas Afshan Siddiq Peter Goddard Sally Donovan Tala Zainy Fiona Maleady-Crowe Linda Todd Shahla Salehi Greg Elgar Georgia Chan Prabhu Arumugam Christine Patch Augusto Rendon Tom A. Fowler Jose E. Krieger Sanjay K. Patel Audrey Lemaçon Sophie Limou Pietro Lió Eirini Marouli Charles Hinds Minttu M. Marttila Carolina Medina-Gómez Isabelle Migeotte Soumyajit Mondal Andrés Moreno-Estrada Leire Moya Tomok Broad Institute of MIT and Harvard Cambridge MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Program in Bioinformatics and Integrative Genomics Harvard Medical School Boston MA USA Institute for Molecular Medicine Finland (FIMM) University of Helsinki Helsinki Finland Institute for Molecular Medicine Finland University of Helsinki Helsinki Finland Institute for Molecular Medicine Finland (FIMM) HiLIFE University of Helsinki Helsinki Finland Public Health Faculty of Medicine University of Helsinki Helsinki Finland Analytic & Translational Genetics Unit Massachusetts General Hospital Boston MA USA Stanley Center for Psychiatric Research & Program in Medical and Population Genetics Cambridge UK Institute for Molecular Medicine Finland (FIMM) Univerisity of Helsinki Helsinki Finland University of California San Francisco San Francisco CA USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA Department of Psychiatry School of Medicine Yale University New Haven CT USA Veteran Affairs Connecticut Healthcare System West Haven CT USA Yale University New Haven CT USA Centre for Bioinformatics and Data Analysis Medical University of Bialystok Bialystok Poland Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA Faculty of Industrial Sciences and Technology Universiti Malaysia Pahang Pahang Malaysia Icahn School of Medicine at Mount Sinai New York NY USA Genolier Innovation Network and Hub Swiss Medical Network Genolier Healthcare Campus Genolier Switzerland Immediate Independent Multidisciplinary Med & Biotech Research Association Milan Italy Clinical Research Unit of Nanor

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Natural variation in the parameters of innate immune cells is preferentially driven by genetic factors (vol 19, pg 302, 2018)

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NATURE IMMUNOLOGY 2018年第6期19卷 645-645页

作者： Patin, Etienne Hasan, Milena Bergstedt, Jacob Rouilly, Vincent Libri, Valentina Urrutia, Alejandra Alanio, Cecile Scepanovic, Petar Hammer, Christian Joensson, Friederike Beitz, Benoit Quach, Helene Lim, Yoong Wearn Hunkapiller, Julie Zepeda, Magge Green, Cherie Piasecka, Barbara Leloup, Claire Rogge, Lars Huetz, Francois Peguillet, Isabelle Lantz, Olivier Fontes, Magnus Di Santo, James P. Thomas, Stephanie Fellay, Jacques Duffy, Darragh Quintana-Murci, Lluis Albert, Matthew L. Unit of Human Evolutionary Genetics Department of Genomes & Genetics Institut Pasteur Paris France CNRS UMR 2000 Paris France Center of Bioinformatics Biostatistics and Integrative Biology Institut Pasteur Paris France Center for Translation Research Institut Pasteur Paris France Department of Automatic Control Lund University Lund Sweden International Group for Data Analysis Institut Pasteur Paris France Laboratory of Dendritic Cell Immunobiology Department of Immunology Institut Pasteur Paris France INSERM U1223 Paris France Department of Cancer Immunology Genentech South San Francisco CA USA School of Life Sciences École Polytechnique Fédérale de Lausanne Lausanne Switzerland Swiss Institute of Bioinformatics Lausanne Switzerland Antibodies in Therapy and Pathology Department of Immunology Institut Pasteur Paris France INSERM U760 Paris France Department of Human Genetics Genentech South San Francisco CA USA Employee Donation Program Genentech South San Francisco CA USA Department of Development Sciences Genentech South San Francisco CA USA Immunoregulation Unit Department of Immunology Institut Pasteur Paris France INSERM U783 Faculté de Médecine Site Necker-Enfants Malades Université Paris Descartes Paris France Lymphocyte Population Biology CNRS URA 1961 Institut Pasteur Paris France Center of Clinical Investigations CIC-BT1428 IGR/Curie Paris France Department of Biopathology Institut Curie Paris France Equipe Labellisée de la Ligue de Lutte Contre le Cancer Institut Curie Paris France INSERM/Institut Curie U932 Paris France Centre for Mathematical Sciences Lund University Lund Sweden Innate Immunity Unit Institut Pasteur Paris France St. Giles Laboratory of Human Genetics of Infectious Diseases Rockefeller Branch Rockefeller University New York NY USA Laboratory of Human Genetics of Infectious Diseases Necker Branch INSERM U1163 Necker Hospital for Sick Children Paris France Paris Descartes University Imagine Insti

The quantification and characterization of circulating immune cells provide key indicators of human health and disease. To identify the relative effects of environmental and genetic factors on variation in the parameters of innate and adaptive immune cells in homeostatic conditions, we combined standardized flow cytometry of blood leukocytes and genome-wide DNA genotyping of 1,000 healthy, unrelated people of Western European ancestry. We found that smoking, together with age, sex and latent infection with cytomegalovirus, were the main non-genetic factors that affected variation in parameters of human immune cells. Genome-wide association studies of 166 immunophenotypes identified 15 loci that showed enrichment for disease-associated variants. Finally, we demonstrated that the parameters of innate cells were more strongly controlled by genetic variation than were those of adaptive cells, which were driven by mainly environmental exposure. Our data establish a resource that will generate new hypotheses in immunology and highlight the role of innate immunity in susceptibility to common autoimmune diseases.

关键词： Activated Lymphocyte Genetic factors Immunity Nonspecific Immune Cell Variation

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Communication scheduling in robust self-triggered MPC for linear discrete-time systems 5

Communication scheduling in robust self-triggered MPC for li...

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5th IFAC Workshop on Distributed Estimation and control in Networked systems, NecSys 2015

作者： Brunner, Florian D. Gommans, T.M.P. Heemels, W.P.M.H. Allgöwer, Prank Institute for Systems Theory and Automatic Control University of Stuttgart Pfaffenwaldring 9 Stuttgart70569 Germany Control System Technology Group Department of Mechanical Engineering Eindhoven University of Technology Netherlands

We consider a networked control system consisting of a physical plant, an actuator, a sensor, and a controller that is connected to the actuator and sensor via a communication network. The plant is described by a linear discrete-time system subject to additive disturbances. In order to reduce the required number of communications in the system, we propose a robust self-triggered model predictive controller based on rollout techniques that robustly asymptotically stabilizes a certain periodic sequence of sets in the state space while guaranteeing robust satisfaction of hard state and input constraints. At periodically occurring scheduling times, the self-triggered model predictive control algorithm determines the times at which the control input and plant measurement are updated in the time span until the next scheduling time. We establish a certain upper bound on the average sampling rate in the closed-loop system. Moreover, we show how increasing the asymptotic bound on the system state, which is a design parameter in the control scheme, can be used to further reduce the average number of communications in the system. © 2015, IF AC (International Federation of automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Closed loop systems

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Publisher Correction: Transcriptomic alterations during ageing reflect the shift from cancer to degenerative diseases in the elderly

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Nature communications 2019年第1期10卷 2459页

作者： Peer Aramillo Irizar Sascha Schäuble Daniela Esser Marco Groth Christiane Frahm Steffen Priebe Mario Baumgart Nils Hartmann Shiva Marthandan Uwe Menzel Jule Müller Silvio Schmidt Volker Ast Amke Caliebe Rainer König Michael Krawczak Michael Ristow Stefan Schuster Alessandro Cellerino Stephan Diekmann Christoph Englert Peter Hemmerich Jürgen Sühnel Reinhard Guthke Otto W Witte Matthias Platzer Eytan Ruppin Christoph Kaleta Research Group Medical Systems Biology Institute of Experimental Medicine Christian-Albrechts-University Kiel D-24105 Kiel Germany. Jena University Language and Information Engineering Lab Friedrich-Schiller-University Jena D-07743 Jena Germany. GerontoSys JenAge Consortium D-07745 Jena Germany. Genome Analysis Lab Leibniz Institute on Aging-Fritz-Lipmann-Institute D-07745 Jena Germany. Hans Berger Department of Neurology Jena University Hospital D-07747 Jena Germany. Systems Biology and Bioinformatics Group Leibniz Institute for Natural Product Research and Infection Biology-Hans-Knöll-Institute D-07745 Jena Germany. Biology of Ageing Lab Leibniz Institute on Aging-Fritz-Lipmann-Institute D-07745 Jena Germany. Molecular Genetics Lab Leibniz Institute on Aging-Fritz-Lipmann-Institute D-07745 Jena Germany. Imageing Facility Leibniz Institute on Aging-Fritz-Lipmann-Institute D-07745 Jena Germany. Integrated Research and Treatment Center Center for Sepsis Control and Care (CSCC) Jena University Hospital D-07747 Jena Germany. Network Modeling Leibniz Institute for Natural Product Research and Infection Biology-Hans Knöll Institute D-07745 Jena Germany. Institute for Medical Informatics and Statistics Christian-Albrechts-University Kiel D-24105 Kiel Germany. Energy Metabolism Laboratory Swiss Federal Institute of Technology (ETH) Zurich Schwerzenbach/Zürich CH-8603 Switzerland. Department of Bioinformatics Friedrich-Schiller-University Jena D-07743 Jena Germany. Laboratory of Neurobiology Scuola Normale Superiore University of Pisa I-56100 Pisa Italy. Molecular Biology Lab Leibniz Institute on Aging-Fritz-Lipmann-Institute D-07745 Jena Germany. Faculty of Biology and Pharmacy Friedrich-Schiller-University Jena D-07743 Jena Germany. Biocomputing Lab Leibniz Institute on Aging-Fritz-Lipmann-Institute D-07745 Jena Germany. Department of Computer Science and Center for Bioinformatics and Computational Biology University of Maryland College Park M

The original version of this Article contained an error in the spelling of the author Jule Müller, which was incorrectly given as Julia Müller. Additionally, in Fig. 4a, the blue-red colour scale for fold change in ageing/disease regulation included a blue stripe in place of a red stripe at the right-hand end of the scale. These errors have been corrected in both the PDF and HTML versions of the Article.

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Online fault diagnosis for nonlinear power systems

Online fault diagnosis for nonlinear power systems

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作者： Pan, Wei Yuan, Ye Sandberg, Henrik Gonçalves, Jorge Stan, Guy-Bart Centre for Synthetic Biology and Innovation Department of Bioengineering Imperial College London United Kingdom Control Group Department of Engineering University of Cambridge United Kingdom Department of Automatic Control School of Electrical Engineering KTH Royal Institute of Technology Sweden Luxembourg Centre for Systems Biomedicine Luxembourg

This paper considers the problem of automatic fault diagnosis for transmission lines in large scale power networks. Since faults in transmission lines threatens stability of the entire power network, fast and reliable fault diagnosis is an important problem in transmission line protection. This work is the first paper exploiting sparse signal recovery for the fault-diagnosis problem in power networks with nonlinear swing-type dynamics. It presents a novel and scalable technique to detect, isolate and identify transmission faults using a relatively small number of observations by exploiting the sparse nature of the faults. Buses in power networks are typically described by second-order nonlinear swing equations. Based on this description, the problem of fault diagnosis for transmission lines is formulated as a compressive sensing or sparse signal recovery problem, which is then solved using a sparse Bayesian formulation. An iterative reweighted 1-minimisation algorithm based on the sparse Bayesian learning update is then derived to solve the fault diagnosis problem efficiently. With the proposed framework, a real-time fault monitoring scheme can be built using only measurements of phase angles at the buses.

关键词： Electric lines

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Communication Scheduling in Robust Self-Triggered MPC for Linear Discrete-Time systems ∗

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IFAC-PapersOnLine 2015年第22期48卷 132-137页

作者： Florian D. Brunner T.M.P. Gommans W.P.M.H. Heemels Frank Allgöwer Institute for Systems Theory and Automatic Control University of Stuttgart Pfaffenwaldring 9 70569 Stuttgart Germany Control System Technology Group Department of Mechanical Engineering Eindhoven University of Technology The Netherlands

关键词： predictive control self-triggered control robustness

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