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1

Kuan, Chung-Ming. A recurrent Newton algorithm and its convergence properties. Champaign: University of Illinois at Urbana-Champaign, 1993.

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2

Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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3

D, Gropp W., i Langley Research Center, red. Globalized Newton-Krylov-Schwarz algorithms and software for parallel implicit CFD. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.

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4

1962-, Cai Xiao-Chuan, Institute for Computer Applications in Science and Engineering. i Langley Research Center, red. Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.

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5

D, Gropp W., i Langley Research Center, red. Globalized Newton-Krylov-Schwarz algorithms and software for parallel implicit CFD. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.

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6

1962-, Cai Xiao-Chuan, i Langley Research Center, red. Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation: NASA contract no. NAS1-19480. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.

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7

1962-, Cai Xiao-Chuan, i Langley Research Center, red. Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation: NASA contract no. NAS1-19480. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.

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8

1962-, Cai Xiao-Chuan, i Langley Research Center, red. Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation: NASA contract no. NAS1-19480. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.

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9

Paul, Casasent David, Hall Ernest L i Society of Photo-optical Instrumentation Engineers., red. Intelligent robots and computer vision XX: Algorithms, techniques, and active vision : 29-31 October, 2001, Newton [Massachusetts] USA. Bellingham, Wash., USA: SPIE, 2001.

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10

Kostyukov, Viktor. Molecular mechanics of biopolymers. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1010677.

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The monograph is devoted to molecular mechanics simulations of biologically important polymers like proteins and nucleic acids. It is shown that the algorithms based on the classical laws of motion of Newton, with high-quality parameterization and sufficient computing resources is able to correctly reproduce and predict the structure and dynamics of macromolecules in aqueous solution. Summarized the development path of biopolymers molecular mechanics, its theoretical basis, current status and prospects for further progress. It may be useful to researchers specializing in molecular Biophysics and molecular biology, as well as students of senior courses of higher educational institutions, studying the biophysical and related areas of training.
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11

Gaudrat, Veronique F. A Newton type algorithm for plastic limit analysis. New York: Courant Institute of Mathematical Sciences, New York University, 1988.

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12

Isono, Sammy. Fourth-order implicit Runge-Kutta time marching using a Newton-Krylov algorithm. Ottawa: National Library of Canada, 2003.

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13

Edwards, Jack R. A nonlinear relaxation / quasi-Newton algorithm for the compressible Navier-Stokes equations. [Washington, D. C.]: American Institute of Aeronautics and Astronautics, 1992.

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14

Isono, Sammy. Fourth-order implicit Runge-Kutta time marching using a Newton-Krylov algorithm. [Downsview, Ont: University of Toronto, Institute for Aerospace Studies], 2003.

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15

Quick, S. V. The computational demands of the modified Newton-Raphson algorithm in electrical impedance tomography. Manchester: UMIST, 1993.

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16

Li, Yuying. A Newton acceleration of the Weiszfeld algorithm for minimizing the sum of Euclidean distances. Ithaca, N.Y: Cornell Theory Center, Cornell University, 1995.

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17

1957-, Gurvits Leonid, i Banff International Research Station for Mathematics Innovation & Discovery, red. Randomization, relaxation, and complexity in polynomial equation solving: Banff International Research Station Workshop on Randomization, Relaxation, and Complexity, February 28--March 5, 2010, Banff, Ontario [i.e. Alberta], Canada. Providence, R.I: American Mathematical Society, 2011.

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18

I, Balandin Sergeĭ, Koucheryavy Yevgeni i SpringerLink (Online service), red. Internet of Things, Smart Spaces, and Next Generation Networking: 12th International Conference, NEW2AN 2012, and 5th Conference, ruSMART 2012, St. Petersburg, Russia, August 27-29, 2012. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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19

Deuflhard, Peter. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms. Springer, 2010.

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20

Michel, Bierlaire. Optimization: Principles and Algorithms. EPFL Press, 2015. http://dx.doi.org/10.55430/6116v1mb.

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Every engineer and decision scientist must have a good mastery of optimization, an essential element in their toolkit. Thus, this articulate introductory textbook will certainly be welcomed by students and practicing professionals alike. Drawing from his vast teaching experience, the author skillfully leads the reader through a rich choice of topics in a coherent, fluid and tasteful blend of models and methods anchored on the underlying mathematical notions (only prerequisites: first year calculus and linear algebra). Topics range from the classics to some of the most recent developments in smooth unconstrained and constrained optimization, like descent methods, conjugate gradients, Newton and quasi-Newton methods, linear programming and the simplex method, trust region and interior point methods. Furthermore elements of discrete and combinatorial optimization like network optimization, integer programming and heuristic local search methods are also presented. This book presents optimization as a modeling tool that beyond supporting problem formulation plus design and implementation of efficient algorithms, also is a language suited for interdisciplinary human interaction. Readers further become aware that while the roots of mathematical optimization go back to the work of giants like Newton, Lagrange, Cauchy, Euler or Gauss, it did not become a discipline on its own until World War Two. Also that its present momentum really resulted from its symbiosis with modern computers, which made it possible to routinely solve problems with millions of variables and constraints. With his witty, entertaining, yet precise style, Michel Bierlaire captivates his readers and awakens their desire to try out the presented material in a creative mode. One of the outstanding assets of this book is the unified, clear and concise rendering of the various algorithms, which makes them easily readable and translatable into any high level programming language. ''This is an addictive book that I am very pleased to recommend.'' Prof. Thomas M. Liebling
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21

Globalized Newton-Krylov-Schwarz algorithms and software for parallel implicit CFD. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.

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22

Globalized Newton-Krylov-Schwarz algorithms and software for parallel implicit CFD. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.

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23

National Aeronautics and Space Administration (NASA) Staff. Parallel Newton-Krylov-Schwarz Algorithms for the Transonic Full Potential Equation. Independently Published, 2018.

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24

Mishra, Akshansh. Quasi Newton Algorithms Based Neural Networks in Friction Stir Welding Process. Independently published, 2019.

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25

Kelley, C. T. Solving Nonlinear Equations with Newton's Method (Fundamentals of Algorithms). Society for Industrial Mathematics, 1987.

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26

Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation: NASA contract no. NAS1-19480. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.

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27

Gaudrat, Veronique F. Newton Type Algorithm for Plastic Limit Analysis. Creative Media Partners, LLC, 2018.

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28

Mann, Peter. Newton’s Three Laws. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198822370.003.0001.

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This chapter introduces Newton’s laws, the Newtonian formulation of mechanics and key concepts such as configuration space and phase space for later development. In 1687, the natural philosopher Sir Isaac Newton published the Principia Mathematica and, with it, sparked the revolutionary ideas key to all branches of classical physics. In this chapter, the system is the object of interest and is considered to be either a single or a collection of generic particles that are not governed by quantum mechanics, for quantum systems do not follow these laws explicitly. Results for systems of particles and conservation laws are presented as the invariance of a given quantity under time evolution. The N-body problem, first integrals, initial value problems and Galilean transformations are all introduced and the Picard iteration and the Verlet algorithm are discussed.
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29

Feld, Leonard G., i John D. Mahan. Succinct Pediatrics: Evaluation and Management for Newborn, Genetic, Neurologic, and Developmental-Behavioral Disorders. American Academy of Pediatrics, 2017. http://dx.doi.org/10.1542/9781610021258.

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Obtain evidence-based information to make timely and accurate diagnoses and treatment decisions. Continuing with this volume, Succinct Pediatrics is an ongoing series covering the entire scope of pediatric medicine. Each volume includes concise chapters with key features and invaluable tables and algorithms--resources health care professionals can use to deliver the highest quality of care. This third volume features 41 topics with key points and detailed therapies in neonatology, genetics, neurology, and developmental and behavioral disorders. Evidence-based levels of decision support are also provided throughout the book to provide insight into diagnostic tests and treatment modalities. Topics include Apnea of Prematurity Birth Injuries Respiratory Distress Syndrome Down Syndrome and Turner Syndrome Ataxia and Movement Disorders Cerebral Palsy Febrile Seizures Hydrocephalus Autism Spectrum Disorders Behavior Patterns And more...
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30

Boulton, Jill E., Kevin Coughlin, Debra O'Flaherty i Alfonso Solimano, red. ACoRN: Acute Care of at-Risk Newborns. Wyd. 2. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780197525227.001.0001.

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The Acute Care of at-Risk Newborns (ACoRN) program trains health care providers to stabilize that most challenging and enigmatic of medical patients: the unwell newborn. Early assessment, intervention, and management of at-risk or unstable infants can be critical for their survival and long-term health. Clinical care standards and educational programs to address these requirements are needed. The ACoRN program provides a unique, prioritized, and systematic approach to newborn stabilization for health care professionals with any degree of experience. ACoRN-trained providers learn to gather information, prioritize, intervene appropriately, and deliver high quality care to at-risk and unwell newborns in any setting. Because research and practice have advanced dramatically in recent years, the need for a new ACoRN text, the program’s centrepiece, became essential—hence the development of this new edition, which reflects current guidelines and evidence-based best practices. ACoRN teaches the concepts and skills required to stabilize unwell newborns through system-based algorithms (Sequences), each with its own chapter: respiratory, cardiovascular, neurology, surgical conditions, fluid and glucose, jaundice, thermoregulation, and infection. The ACoRN mnemonic defines stabilization steps and chapter structure: alerting signs, core steps, organization of care, response, next steps, and specific diagnosis and management. Each chapter includes educational objectives, key concepts, learning points, and at least one case scenario with questions and answers to reinforce content and learnings. This book is written for any health professional who may be required to participate in the stabilization of sick or preterm babies within their scope of practice.
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31

Koucheryavy, Yevgeni, Sergey Balandin i Sergey Andreev. Internet of Things, Smart Spaces, and Next Generation Networking: 12th International Conference, NEW2AN 2012, and 5th Conference, ruSMART 2012, St. ... Springer, 2012.

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32

Koucheryavy, Yevgeni, Sergey Balandin i Sergey Andreev. Internet of Things, Smart Spaces, and Next Generation Networking: 12th International Conference, NEW2AN 2012, and 5th Conference, ruSMART 2012, St. Petersburg, Russia, August 27-29, 2012, Proceedings. Springer, 2012.

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