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Erratum to: Methods for evaluating medical tests and biomarkers

Diagnostic and prognostic research 2017年第1期1卷 11页

作者： Gowri Gopalakrishna Miranda Langendam Rob Scholten Patrick Bossuyt Mariska Leeflang Anna Noel-Storr James Thomas Iain Marshall Byron Wallace Penny Whiting Clare Davenport Gowri GopalaKrishna Isabel de Salis Sue Mallett Robert Wolff Richard Riley Marie Westwood Jos Kleinen Gary Collins Hans Reitsma Karel Moons Antonia Zapf Annika Hoyer Katharina Kramer Oliver Kuss J Ensor J J Deeks E C Martin R D Riley Gerta Rücker Susanne Steinhauser Martin Schumacher Joie Ensor Kym Snell Brian Willis Thomas Debray Jon Deeks Lavinia Ferrante di Ruffano Sian Taylor-Phillips Chris Hyde Stuart A Taylor Gauraang Batnagar Lavinia Ferrante Di Ruffano Farah Seedat Aileen Clarke Sarah Byron Frances Nixon Rebecca Albrow Thomas Walker Carla Deakin Zhivko Zhelev Harriet Hunt Yaling Yang Lucy Abel James Buchanan Thomas Fanshawe Bethany Shinkins Laure Wynants Jan Verbakel Sabine Van Huffel Dirk Timmerman Ben Van Calster Aeliko Zwinderman Jason Oke Jack O'Sullivan Rafael Perera Brian Nicholson Hannah L Bromley Tracy E Roberts Adele Francis Denniis Petrie G Bruce Mann Kinga Malottki Holly Smith Lucinda Billingham Alice Sitch Oke Gerke Mie Holm-Vilstrup Eivind Antonsen Segtnan Ulrich Halekoh Poul Flemming Høilund-Carlsen Bernard G Francq Jac Dinnes Julie Parkes Walter Gregory Jenny Hewison Doug Altman William Rosenberg Peter Selby Julien Asselineau Paul Perez Aïssatou Paye Emilie Bessede Cécile Proust-Lima Christiana Naaktgeboren Joris de Groot Anne Rutjes Johannes Reitsma Emmanuel Ogundimu Jonathan Cook Yannick Le Manach Yvonne Vergouwe Romin Pajouheshnia Rolf Groenwold Karen Moons Linda Peelen Daan Nieboer Bavo De Cock Micael J Pencina Ewout W Steyerberg Jennifer Cooper Nick Parsons Chris Stinton Steve Smith Andy Dickens Rachel Jordan Alexandra Enocson David Fitzmaurice Peymane Adab Charles Boachie Gaj Vidmar Karoline Freeman Martin Connock Rachel Court Carl Moons Jessica Harris Andrew Mumford Zoe Plummer Kurtis Lee Barnaby Reeves Chris Rogers Veerle Verheyden Gianni D Angelini Gavin J Murphy Jeremy Huddy Melody Ni Katherine Good Graham Cooke 1Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 2Cochrane Netherlands Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht Netherlands. 234Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 49Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 3Cochrane Dementia and Cognitive Improvement Group University of Oxford Oxford UK. 4EPPI-Centre Department of Social Science University College London London UK. 5Division of Health and Social Care Research King's College London London UK. 6College of Computer and Information Science Northeastern University Boston USA. 13University Hospitals Bristol NHS Foundation Trust School of Social and Community Medicine Bristol UK. 275Institute of Applied Health Research University of Birmingham Birmingham UK. 9Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 10School of Social and Community Medicine University of Bristol Bristol UK. 179Institute of Applied Health Research University of Birmingham Birmingham UK. 12Kleijnen Systematic Reviews Ltd York UK. 25Research Institute for Primary Care and Health Sciences Keele University Keele UK. 188Centre for Statistics in Medicine Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences University of Oxford Oxford UK. 191Julius Center for Health Sciences and Primary Care University Medical Center Utrecht 3584 CG Utrecht Netherlands. 237Julius Center for Health Sciences and Primary Care University Medical Center Utrecht 3584 CG Utrecht Netherlands. 18Department of Medical Statistics University Medical Center Göttingen Göttingen Germany. 19Institute for B

[This corrects the article DOI: 10.1186/s41512-016-0001-y.].

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The differential geometry of shape from shading: Biology reveals curvature structure

The differential geometry of shape from shading: Biology rev...

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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Benjamin Kunsberg Steven W. Zucker Applied Mathematics Program Yale University USA Departments of Computer Science and Applied Mathematics Yale University USA

Shape from shading is a classical inverse problem in computer vision. We introduce a novel mathematical formulation for calculating local surface shape based on covariant derivatives, rather than the customary integral minimization or P.D.E approaches. Motivated by neurobiology, we introduce the shading flow field (the tangent map to the image isophotes) between the image and the surface levels. Just as in the perceptual organization of texture, we use the parallel transport of our shading flow field to move the isophote field at different points on the unknown surface to a single point, amassing restrictions on our surface curvatures. Under simplifying assumptions we solve exactly for the light source/surface pairs needed for a local image patch to have a given shading flow. The magnitude of the brightness gradient then restricts this family to a single light source and surface estimate pair, up to the concave/convex ambiguity and an additional elliptical/saddle ambiguity. Example calculations illustrate our approach.

关键词： Light sources Mathematical model Equations Shape Vectors Brightness computer vision

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Heart wall myofibers are arranged in minimal surfaces to optimize organ function (vol 109, pg 9253, 2012)

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PROCEEDINGS OF THE NATIONAL ACADEMY OF scienceS OF THE UNITED STATES OF AMERICA 2012年第49期109卷 20166-20166页

作者： Savadjiev, Peter Strijkers, Gustav J. Bakermans, Adrianus J. Piuze, Emmanuel Zucker, Steven W. Siddiqi, Kaleem [a]Psychiatry Neuroimaging Laboratory and Laboratory for Mathematics in Imaging Brigham and Women’s Hospital Harvard Medical School Boston MA 02215 [b]Department of Biomedical Engineering Eindhoven University of Technology 5600 MB Eindhoven The Netherlands [c]School of Computer Science and Centre for Intelligent Machines McGill University Montréal Canada H3A 2A7 and [d]Departments of Computer Science and Biomedical Engineering and Program in Applied Mathematics Yale University New Haven CT 06520-8285

Heart wall myofibers wind as helices around the ventricles, strengthening them in a manner analogous to the reinforcement of concrete cylindrical columns by spiral steel cables [Richart FE, et al. (1929) Univ of Illinois, Eng Exp Stn Bull 190]. A multitude of such fibers, arranged smoothly and regularly, contract and relax as an integrated functional unit as the heart beats. To orchestrate this motion, fiber tangling must be avoided and pumping should be efficient. Current models of myofiber orientation across the heart wall suggest groupings into sheets or bands, but the precise geometry of bundles of myofibers is unknown. Here we show that this arrangement takes the form of a special minimal surface, the generalized helicoid [Blair DE, Vanstone JR (1978) Minimal Submanifolds and Geodesics 13-16], closing the gap between individual myofibers and their collective wall structure. The model holds across species, with a smooth variation in its three curvature parameters within the myocardial wall providing tight fits to diffusion magnetic resonance images from the rat, the dog, and the human. Mathematically it explains how myofibers are bundled in the heart wall while economizing fiber length and optimizing ventricular ejection volume as they contract. The generalized helicoid provides a unique foundation for analyzing the fibrous composite of the heart wall and should therefore find applications in heart tissue engineering and in the study of heart muscle diseases. [PUBLICATION ABSTRACT]

关键词： myocardium myofiber geometry diffusion tensor MRI

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Singularities of quantum control landscapes

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Physical Review A 2012年第1期86卷 013405-013405页

作者： Re-Bing Wu Ruixing Long Jason Dominy Tak-San Ho Herschel Rabitz Department of Automation Tsinghua University Beijing 100084 China and Center for Quantum Information Science and Technology TNList Beijing 100084 China Department of Chemistry Princeton University Princeton New Jersey 08544 USA Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA

Quantum control landscape theory was formulated to assess the ease of finding optimal control fields in simulations and in the laboratory. The landscape is the observable as a function of the controls, and a primary goal of the theory is the analysis of landscape features. In what is referred to as the kinematic picture of the landscape, prior work showed that the landscapes are generally free of traps that could halt the search for an optimal control at a suboptimal observable value. The present paper considers the dynamical picture of the landscape, seeking the existence of singular controls, especially of a nonkinematic nature along with an assessment of whether they correspond to traps. We analyze the necessary and sufficient conditions for singular controls to be kinematic or nonkinematic critical solutions and the likelihood of their being encountered while maximizing an observable. An algorithm is introduced to seek singular controls on the landscape in simulations along with an associated Hessian landscape analysis. Simulations are performed for a large number of model finite-level quantum systems, showing that all the numerically identified kinematic and nonkinematic singular critical controls are not traps, in support of the prior empirical observations on the ease of finding high-quality optimal control fields.

关键词： QUANTUM theory LANDSCAPES computer simulation OPTIMAL control theory ALGORITHMS

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Optimal control for reconstruction of curves without cusps

Optimal control for reconstruction of curves without cusps

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IEEE Conference on Decision and Control

作者： Ugo Boscain Remco Duits Francesco Rossi Yuri Sachkov Center for Applied Mathematics Ecole Polytechnique France Department of Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands LSIS Aix-Marseille Universite Marseilles France Program Systems Institute Pereslavl-Zalessky Russia

ISBN: (纸本)9781467320658

We consider the problem of minimizing ∫ 0 ℓ √(ξ 2 +K 2 (s)ds) for a planar curve having fixed initial and final positions and directions. The total length ℓ is free. Here s is the variable of arclength parametrization, K(s) is the curvature of the curve and ξ >; 0 a parameter. This problem comes from a model of geometry of vision due to Petitot, Citti and Sarti. We study existence of local and global minimizers for this problem. We prove that if for a certain choice of boundary conditions there is no global minimizer, then there is neither a local minimizer nor a stationary curve (geodesic). Our main tool is the construction of the optimal synthesis for the Reed and Shepp car with quadratic cost.

关键词： Brain modeling Boundary conditions Visualization Trajectory Aerospace electronics Optimal control Biological system modeling

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Secondary structure predictions for long RNA sequences based on inversion excursions - Preliminary results 12

Secondary structure predictions for long RNA sequences based...

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2012 ACM Conference on Bioinformatics, computational Biology and Biomedicine, BCB 2012

作者： Yehdego, Daniel T. Zhang, Boyu Taufer, Michela Kodimala, Vikram Kumar Reddy Vegesna, Rahulsimham Viswakula, Sameera Johnson, Kyle L. Leung, Ming-Ying Computational Science Program University of Texas El Paso United States Department of Computer and Information Sciences University of Delaware United States Bioinformatics Program Border Biomedical Research Center University of Texas El Paso United States Department of Mathematical Sciences University of Texas El Paso United States Department of Biological Sciences University of Texas El Paso United States Department of Mathematics and Statistics Old Dominion University Norfolk VA United States University of Texas M. D. Anderson Cancer Center Houston TX United States

ISBN: (纸本)9781450316705

The tremendous demand on computer memory and computing time for prediction of complex secondary structures limits the applicability of most RNA secondary structure prediction programs available to short RNA sequences. We propose to approach this problem by segmenting a long RNA sequence into shorter non-overlapping chunks, predicting the secondary structures of each chunk individually, and then assembling the prediction results to give the structure of the original sequence. The selection of cutting points is a crucial component of the approach. Noting that stem-loops and pseudoknots always contain an inversion, we developed two cutting methods, the centered and optimized methods, for segmenting long RNA sequences based on inversion excursions. For the majority of the sequences in a dataset of 50 RNAs from the RFAM database, the prediction algorithm PKnotsRG used with these cutting methods produces more accurate secondary structures than those predicted for the whole sequence without segmentation. Both the centered and optimized cutting methods outperform the naïve regular segmentation. These results support our claim that cutting is a promising approach for the prediction of long RNA sequences, and choosing the cutting points intelligently by considering sequence features such as inversion excursions can further enhance prediction accuracy.

关键词： Forecasting

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Improving parallel scalability for edge plasma transport simulations with neutral gas species

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computational science and Discovery 2012年第1期5卷

作者： McCourt, M. Rognlien, T.D. McInnes, L.C. Zhang, H. Center for Applied Mathematics 657 Rhodes Hall Cornell University Ithaca NY 14853 United States Fusion Energy Sciences Program Lawrence Livermore National Laboratory 7000 East Avenue Livermore CA 94550 United States Argonne National Laboratory Mathematics and Computer Science Division 9700 South Cass Avenue Argonne IL 60439 United States

Simulating the transport of multi-species plasma and neutral species in the edge region of a tokamak magnetic fusion energy device is computationally intensive and difficult due to coupling among various components, strong nonlinearities and a broad range of temporal scales. In addition to providing boundary conditions for the core plasma, such models aid in the understanding and control of the associated plasma/material-wall interactions, a topic that is essential for the development of a viable fusion power plant. The governing partial differential equations are discretized to form a large nonlinear system that typically must be evolved in time to obtain steady-state solutions. Fully implicit techniques using preconditioned Jacobian-free Newton-Krylov methods with parallel domain-based preconditioners are shown to be robust and efficient for the plasma components. Inclusion of neutral gas components, however, increases the condition number of the system to the point where improved parallel preconditioning is needed. Standard algebraic preconditioners that provide sufficient coupling throughout the global domain to handle the neutrals are not generally scalable. We present a new preconditioner, termed FieldSplit, which exploits the character of the neutral equations to improve the scalability of the combined plasma/neutral system. © 2012 IOP Publishing Ltd.

关键词： Scalability

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ESICM LIVES 2016: part two

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Intensive Care Medicine Experimental 2016年第1期4卷 205-404页

作者： S. Sivakumar F. S. Taccone K. A. Desai C. Lazaridis M. Skarzynski M. Sekhon W. Henderson D. Griesdale L. Chapple A. Deane L. Williams R. Strickland K. Lange D. Heyland M. Chapman M. J. Rowland P. Garry J. Westbrook R. Corkill C. A. Antoniades K. T. Pattinson G. Fatania A. J. Strong R. B. Myers C. M. Jermaine C. S. Robertson C. G. Rusin J. Hofmeijer L. Sondag M. C. Tjepkema-Cloostermans A. Beishuizen F. H. Bosch M. J. A. M. van Putten L. Carteron C. Patet D. Solari M. Oddo M. A. Ali C. Dias R. Almeida A. Vaz-Ferreira J. Silva E. Monteiro A. Cerejo A. P. Rocha A. A. Elsayed A. M. Abougabal B. N. Beshey K. M. Alzahaby S. Pozzebon A. Blandino Ortiz S. Cristallini O. Lheureux A. Brasseur J. L. Vincent J. Creteur M. Hravnak K. Yousef Y. Chang E. Crago R. M. Friedlander S. A. Abdelmonem S. A. Tahon T. A. Helmy H. S. Meligy F. Puig I. Dunn-Siegrist J. Pugin S. Gupta D. Govil S. Srinivasan S. J. Patel J. K. N A. Gupta D. S. Tomar M. Shafi R. Harne D. P. Arora N. Talwar S. Mazumdar E. E. Papakrivou D. Makris E. Manoulakas B. Tsolaki B. Karadodas E. Zakynthinos I. Palacios Garcia A. Diaz Martin V. Sanchez Encinares M. Pachón Ibañez J. Garnacho Montero G. Labrador T. Cebrero Cangueiro V. Poulose J. Koh J. W. Kam H. Yeter A. Kara O. Aktepe A. Topeli I. Tsolakoglou G. Intas P. Stergiannis A. A. Kolaros E. Chalari E. Athanasiadou A. Martika G. Fildisis V. Faivre C. Mengelle B. Favier D. Payen A. Poppe M. S. Winkler E. Mudersbach J. Schreiber M. L. Wruck E. Schwedhelm S. Kluge C. Zöllner T. Tavladaki A. M. Spanaki H. Dimitriou E. Kondili C. Choulaki E. Meleti D. Kafetzopoulos D. Georgopoulos G. Briassoulis A. García-de la Torre M. V. de la Torre-Prados T. Tsvetanova-Spasova P. Nuevo-Ortega C. Rueda-Molina A. Fernández-Porcel E. Camara-Sola L. Salido-Díaz A. García-Alcántara D. E. Meleti B. Suberviola J. Riera L. Rellan M. Sanchez J. C. Robles E. Lopez R. Vicente E. Miñambres M. Santibañez M. Le Guen J. Moore N. Mason M. Windpassinger O. Plattner E. Mascha D. I. Sessler Outcomes Research U. Melia J. Fontanet J. P. van den Berg M. Baylor College of Medicine Neurology/Neurocritical Care Houston USA Erasmus Hospital Intensive Care Medicine Brussels Belgium Centre Hospitalier Régional Orléans Réaimation Médicale Orléans France University of British Columbia Vancouver Canada University of Adelaide Discipline of Acute Care Medicine Adelaide Australia Royal Adelaide Hospital Intensive Care Adelaide Australia Griffith University Menzies Health Institute of Queensland Gold Coast Australia University of Adelaide Discipline of Medicine Adelaide Australia Kingston General Hospital Clinical Evaluation Research Unit Kingston Canada University of Oxford Nuffield Department of Clinical Neurosciences Oxford UK Oxford University Hospitals NHS Foundation Trust Neurosciences Intensive Care Unit Oxford UK King’s College Hospital Department of Neurosurgery London UK King’ College London Institute of Psychiatry Psychology and Neuroscience Department of Clinical Neuroscience London UK Rice University Computer Science Houston USA Baylor College of Medicine Neurosurgery Houston USA Baylor College of Medicine Pediatric Cardiology Houston USA University of Twente Clinical Neurophysiology Enschede Netherlands Rijnstate Hospital Neurology Arnhem Netherlands Medical Spectrum Twente Clinical Neurophysiology Enschede Netherlands Medical Spectrum Twente Intensive Care Enschede Netherlands Rijnstate Hospital Intensive Care Arnhem Netherlands CHUV Department of Intensive Care Medicine Neuroscience Critical Care Research Group Lausanne Switzerland Aga Khan University Hospital Anaesthesiology Karachi Pakistan Centro Hospitalar São João Intensive Care Porto Portugal Faculty of Medicine University of Porto Medicine Porto Portugal Faculdade de Ciências Universidade do Porto Departamento de Matemática Porto Portugal Centro de Matemática Universidade do Porto Porto Portugal The Biomedical Research Networking Center in Bioengineering Biomaterials and Nanomedicine Zaragoza Spain Centro Hospitalar

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Updating preconditioner for iterative method in time domain simulation of power systems

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science China(Technological sciences) 2011年第4期54卷 1024-1034页

作者： WANG Ke XUE Wei LIN HaiXiang XU ShiMing ZHENG WeiMin Laboratory of Parallel Software and Computational Science Institute of SoftwareChinese Academy of SciencesBeijing 000China Department of Computer Science and Technology Tsinghua UniversityBeijing 000China Tsinghua National Laboratory for Information Science and Technology(TNList) Beijing 100084China Delft Institute of Applied Mathematics Delft University of TechnologyDelft 2628 CDThe Netherlands

The numerical solution of the differential-algebraic equations(DAEs) involved in time domain simulation(TDS) of power systems requires the solution of a sequence of large scale and sparse linear *** use of iterative methods such as the Krylov subspace method is imperative for the solution of these large and sparse linear *** motivation of the present work is to develop a new algorithm to efficiently precondition the whole sequence of linear systems involved in *** an improvement of dishonest preconditioner(DP) strategy,updating preconditioner strategy(UP) is introduced to the field of TDS for the first *** idea of updating preconditioner strategy is based on the fact that the matrices in sequence of the linearized systems are continuous and there is only a slight difference between two consecutive *** order to make the linear system sequence in TDS suitable for UP strategy,a matrix transformation is applied to form a new linear sequence with a good shape for preconditioner *** algorithm proposed in this paper has been tested with 4 cases from real-life power systems in *** show that the proposed UP algorithm efficiently preconditions the sequence of linear systems and reduces 9%-61% the iteration count of the GMRES when compared with the DP method in all test *** experiments also show the effectiveness of UP when combined with simple preconditioner reconstruction strategies.

关键词： differential-algebraic equations GMRES updating preconditioner power system simulation

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A framework for relating neural activity to freely moving behavior

A framework for relating neural activity to freely moving be...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Justin D. Foster Paul Nuyujukian Oren Freifeld Stephen I. Ryu Michael J. Black Krishna V. Shenoy Department of Electrical Engineering University of Stanford Stanford CA USA Bioengineering and Stanford Medical School University of Stanford Stanford CA USA Division of Applied Mathematics Brown University Providence RI USA Department of Neurosurgery Palo Alto Medical Foundation Palo Alto CA USA Department of Computer Science Brown University Providence RI USA Departments of Electrical Engineering Bioengineering and Neurobiology Neurosciences Program Neurosciences Program University of Stanford Stanford CA USA

Two research communities, motor systems neuroscience and motor prosthetics, examine the relationship between neural activity in the motor cortex and movement. The former community aims to understand how the brain controls and generates movement; the latter community focuses on how to decode neural activity as control signals for a prosthetic cursor or limb. Both have made progress toward understanding the relationship between neural activity in the motor cortex and behavior. However, these findings are tested using animal models in an environment that constrains behavior to simple, limited movements. These experiments show that, in constrained settings, simple reaching motions can be decoded from small populations of spiking neurons. It is unclear whether these findings hold for more complex, full-body behaviors in unconstrained settings. Here we present the results of freely-moving behavioral experiments from a monkey with simultaneous intracortical recording. We investigated neural firing rates while the monkey performed various tasks such as walking on a treadmill, reaching for food, and sitting idly. We show that even in such an unconstrained and varied context, neural firing rates are well tuned to behavior, supporting findings of basic neuroscience. Further, we demonstrate that the various behavioral tasks can be reliably classified with over 95% accuracy, illustrating the viability of decoding techniques despite significant variation and environmental distractions associated with unconstrained behavior. Such encouraging results hint at potential utility of the freely-moving experimental paradigm.

关键词： Legged locomotion Maximum likelihood decoding Kinematics Animals Educational institutions Cameras Neuroscience

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