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

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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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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Dynamic fuzzy modelling for organic rankine cycle systems

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ICIC Express Letters 2014年第11期8卷 3007-3013页

作者： Zhang, Jianhua Wang, Zhuofei Li, Bo Wang, Rui Lin, Mingming State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University No. 2 Beinong Road Changping District Beijing China Shisanling Pumped Storage Power Station Changping District Beijing China School of Control and Computer Engineering North China Electric Power University No. 2 Beinong Road Changping District Beijing China

Based on recursive fuzzy c-means (FCM) algorithm, the Takagi-Sugeno model is established for Organic Rankine Cycle (ORC) based waste heat recovery systems. The premise parameters are obtained by FCM algorithm while the consequent parameters are identified by forgetting factor least-square (FFLS) algorithm. The validity of identification algorithm is tested and verified. Simulation results show that the established T-S model can characterize the dynamic characteristics of the ORC system well.

关键词： Waste heat

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A molecular cryptography model based on structures of DNA self-assembly

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Chinese Science Bulletin 2014年第11期59卷 1192-1198页

作者： Yang, Jing Ma, Jingjing Liu, Shi Zhang, Cheng Beijing Key Laboratory of New Technology and System on Measuring and Control for Industrial Process School of Control and Computer Engineering North China Electric Power University Beijing China Key Laboratory of High Confidence Software Technologies Ministry of Education Institute of Software School of Electronics Engineering and Computer Science Peking University Beijing China

With the progress of DNA computing, DNA-based cryptography becomes an emerging interdisciplinary research field. In this paper, we present a novel DNA cryptography that takes advantage of DNA self-assembled structure. Making use of the toehold strands recognition and strand displacement, the bit-wise exclusive-or (XOR) operation is carried out to fulfill the information encryption and decryption in the form of a one-time-pad. The security of this system mainly comes from the physical isolation and specificity of DNA molecules. The system is constructed by using complex DNA self-assembly, in which technique of fluorescent detection is utilized to implement the signal processing. In the proposed DNA cryptography, the XOR operation at each bit is carried out individually, thus the encryption and decryption process could be conducted in a massive, parallel way. This work may demonstrate that DNA cryptography has the great potential applications in the field of information security.

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On overcoming limitations of a class of linear systems with first-order reset elements

On overcoming limitations of a class of linear systems with ...

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World Congress on Intelligent control and Automation (WCICA)

作者： Guanglei Zhao Jingcheng Wang Kang Li Department of Automation Key Laboratory of System Control and Information Processing China Electrical Engineering and Computer Science Queens University Belfast UK

This paper considers using reset control to improve transient performance and overcome some fundamental limitations of linear systems. First, an auxiliary system is presented, then, based on which, a new reset control model is proposed, such that the non-overshoot performance specification can be met for any minimum phase relative degree one plants, the results imply some limitations of linear systems are overcome and clearly illustrate the advantages of reset control. A numerical example is given to show the effectiveness.

关键词： Closed loop systems Stability analysis Gold Linear systems Steady-state Educational institutions

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Robust control reconfiguration of resource allocation systems with Petri nets and integer programming

Robust control reconfiguration of resource allocation system...

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作者： Li, Jun Zhou, Mengchu Guo, Tao Gan, Yahui Dai, Xianzhong Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China School of Automation Southeast University Nanjing 210096 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States

Supervisory control reconfiguration can handle the uncertainties including resource failures and task changes in discrete event systems. It was not addressed to exploit the robustness of closed-loop systems to accommodate some uncertainties in the prior studies. Such exploitation can cost-efficiently achieve reconfigurability and flexibility for real systems. This paper presents a robust reconfiguration method based on Petri nets (PNs) and integer programming for supervisory control of resource allocation systems (RASs) subject to varying resource allocation relationships. An allocation relationship is seen as a control specification while the execution processes requiring resources as an uncontrolled plant. First, a robust reconfiguration mechanism is proposed. It includes updating the P-invariant-based supervisor and evolving the state of the closed-loop system. The latter adapts to the control specification changes by the self-regulation of the closed-loop system's state. Next, two novel integer programming models for control reconfiguration are proposed, called a reconfiguration model with acceptability and reconfiguration one with specification correction. Since both models integrate the firability condition of transitions, no additional efforts are required for the state reachability analysis. Finally, a hospital emergency service system is used as an example to illustrate them. © 2014 Elsevier Ltd. All rights reserved.

关键词： Integer programming

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On infinite time performance of nonlinear model predictive controllers 19

On infinite time performance of nonlinear model predictive c...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Cai, Xin Li, Shaoyuan Li, Ning Li, Kang Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China School of Electronics Electrical Engineering and Computer Science Queen's University Belfast BelfastBT7 1NN United Kingdom

ISBN: (纸本)9783902823625

This paper addresses the problem of infinite time performance of model predictive controllers applied to constrained nonlinear systems. The total performance is compared with a finite horizon optimal cost to reveal performance limits of closed-loop model predictive control systems. Based on the Principle of Optimality, an upper and a lower bound of the ratio between the total performance and the finite horizon optimal cost are obtained explicitly expressed by the optimization horizon. The results also illustrate, from viewpoint of performance, how model predictive controllers approaches to infinite optimal controllers as the optimization horizon increases. © IFAC.

关键词： controllers

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A Method to Calculate the Change of Turbine Power Output Caused by the Condenser Pressure Adjustment

A Method to Calculate the Change of Turbine Power Output Cau...

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2014 International Conference on Energy, Environment and Materials Engineering(EEME 2014)

作者： Wei WANG Yong HU De-liang ZENG State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer EngineeringNorth China Electric Power University

It is necessary to acquire the relationship between the turbine power output and condenser pressure under the certain steam load since the condenser pressure has a great influence on the turbine power *** paper first analyzes the varying parameters of the regenerative extraction cycle system caused by condenser pressure adjustment,and then sets up their calculating models through mechanism analysis and formula *** this basis,this paper attains the change of turbine power output caused by condenser pressure adjustment through the power expression.

关键词： Condenser pressure Turbine power output Steam-water distribution

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Research on optimization of flight scheduling problem based on the combination of ant colony optimization and genetic algorithm

Research on optimization of flight scheduling problem based ...

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IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Wenkuai Liang Yi Li College of Computer Science Sichuan University Chengdu Sichuan China National Key Laboratory of Air Traffic Control Automation System Technology Chengdu Sichuan China

As the flight scheduling has always been a key technology which reduces flight delays and costs. Rational and efficient flight sorting method not only can effectively improve the utilization of the airport, reduce flight delay, but also ensure flight safety and reduce the incidence of sudden accidents. Firstly, we studied the application of ant colony algorithm in flight sorting, and proposed a new flight sorting method which is combined with ant colony algorithm and genetic algorithm depending on the mutation characteristic of genetic algorithm; Secondly, the minimization objective model that the flight total delay was minimum was established based on the sorting method; Finally, the simulation experiment was done based on the model. The simulation results show that the proposed method can effectively reduce flight delay. Comparing with ant colony algorithm, the global optimal flight sequence can be found in a shorter time.

关键词： Genetic algorithms Sorting Optimal scheduling Educational institutions Delays Algorithm design and analysis

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Research on flight scheduling of two runways based on the fusion of artificial fish school algorithm and genetic algorithm

Research on flight scheduling of two runways based on the fu...

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IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Jingjing Li Wenkuai Liang Yi Li College of Computer Science Sichuan University Chengdu Sichuan China System Technology National Key Laboratory of Air Traffic Control Automation Chengdu Sichuan China

The fusion of artificial fish algorithm and genetic algorithm is proposed to optimize the flight scheduling of two-runway in large airport in which the problems are difficult, inefficient and serious flight delays. First, in this paper, the shortcomings of artificial fish algorithm and genetic algorithm are analyzed, and combing the advantages of two algorithms, optimization algorithm is proposed based on the fusion of artificial fish swarm algorithm and genetic algorithm; Secondly, the objective function model of the total of time-consuming which is minimum about dual runway is established; Finally, the simulation results show that the fusion algorithm in operating efficiency, the reduction of flight delays and other aspects is better than first-come, first-served (FCFS), artificial fish algorithm and genetic algorithm, and can get better convergence results.

关键词： Marine animals Algorithm design and analysis Genetic algorithms Aircraft Scheduling Delays Heuristic algorithms

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