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  • 65V05  (1)
  • Chickens  (1)
  • 1985-1989  (2)
  • 1940-1944
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  • 1985-1989  (2)
  • 1940-1944
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  • 1
    Publication Date: 1985-07-19
    Description: Post-infectious or post-vaccinal demyelinating encephalomyelitis and neuritis may be due to immunological cross-reactions evoked by specific viral antigenic determinants (epitopes) that are homologous to regions in the target myelins of the central and peripheral nervous systems. Such homologies have been found by computer searches in which decapeptides in two human myelin proteins were compared with proteins of viruses known to infect humans. These viruses include measles, Epstein-Barr, influenza A and B, and others that cause upper respiratory infections. Several regions identified in myelin basic protein and P2 protein can be related to experimental allergic encephalomyelitis or neuritis in laboratory animals.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Jahnke, U -- Fischer, E H -- Alvord, E C Jr -- AM07902/AM/NIADDK NIH HHS/ -- New York, N.Y. -- Science. 1985 Jul 19;229(4710):282-4.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/2409602" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Base Sequence ; Chickens ; Encephalomyelitis/etiology/immunology/*metabolism ; Epitopes ; Guinea Pigs ; Haplorhini ; Humans ; Measles/metabolism ; Myelin Basic Protein/genetics ; Myelin P2 Protein ; Neuritis/etiology/immunology/*metabolism ; Rabbits ; Rats ; Rats, Inbred Lew ; Viral Proteins/*genetics ; Viral Vaccines/adverse effects/immunology
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Computing 41 (1989), S. 261-265 
    ISSN: 1436-5057
    Keywords: 65V05 ; 65K10 ; 68C25 ; Automatic differentiation ; complexity
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Description / Table of Contents: Zusammenfassung Die Arbeit behandelt ein spezielles Problem des Automatischen Differenzierens. Seif eine rationale Funktion vonn Variablen, sei #(f) die Anzahl der Operationen in der Auswertung vonf(x), seig der Gradient vonf. Viele Algorithmen zur Minimierung vonf(x) benötigen das Skalarproduktg(u) tv. In der Standardmethode zur Berechnung vong(u) tv wächst der Arbeitsaufwand mitn·#(f). In der vorliegenden Arbeit wird eine neue Methode zur Berechnung vong(u) tv angegeben. Die neue Methode erweist sich als wesentlich schneller, ihr Arbeitsaufwand wächst nur mit #(f).
    Notes: Abstract The paper deals with a special problem in Automatic Differentiation. Letf be a rational function ofn variables, let #(f) denote the number of operations to evaluatef(x), letg denote the gradient off. Many algorithms for minimizingf(x) require the scalar productg(u) tv. In the standard method for computingg(u) tv the amount of work grows withn·#(f). In this note a new method for computingg(u) tv is presented. The new method is considerably faster, its amount of work only grows with #(f).
    Type of Medium: Electronic Resource
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