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  • 1
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Alimentary pharmacology & therapeutics 4 (1990), S. 0 
    ISSN: 1365-2036
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Medicine
    Notes: Stimulation of mucosal alkaline secretion represents an opportunity for discovering novel drugs of potential benefit in maintenance therapy of duodenal ulcer disease. We screened over 200 agents representing the full spectrum of pharmacological categories in order to characterize stimulatory pathways and identify mechanistic leads. A variety of eicosanoids, phospho-diesterase inhibitors and adrenoreceptor agonists together with forskolin, 6–hydroxy-dopamine, 2–chloroadenosine, diazepam, testosterone, dipyridamole and dihydropyridazinone caused a reproducible increase in the metabolism-dependent component of alkaline secretion in bullfrog proximal duodenum. PGE2 (ED50 0.02 μg/ml) was the most potent agent in vitro and was also the most effective stimulant of duodenal alkalinization in vivo in an anaesthetized cat preparation. Agents without effect on spontaneous alkaline secretion by amphibian duodenum included agonists and antagonists of histamine, 5–hydroxy-tryptamine, γ-aminobutyric acid, dopamine, muscarinic and nicotinic receptors, inhibitors of amine uptake, monoamine oxidase and cholinesterase, plus various corticoids, diuretics, oestrogens, chemotherapeutic (anticancer) and antimicrobial agents. The major mechanism of stimulating alkaline secretion in the isolated duodenum is by increasing intracellular cyclic AMP levels. This may occur by either inhibiting metabolism of the nucleotide or by stimulating its formation.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    [s.l.] : Nature Publishing Group
    Nature 202 (1964), S. 1215-1216 
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] In an attempt to characterize the lipid components of the formalin extracts, we have used sheep lungs, and have prepared nuclei by the method of Frazer and Davidson7. Nuclei prepared in this way from 100 g of fresh lung were stirred overnight with 200 ml. of 4 per cent aqueous formaldehyde ...
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 53 (1986), S. 203-217 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract Three different representations for a thresholded linear equation are developed. For binary input they are shown to be representationally equivalent though their training characteristics differ. A training algorithm for linear equations is discussed. The similarities between its simplest mathematical representation (perceptron training), a formal model of animal learning (Rescorla-Wagner learning), and one mechanism of neural learning (Aplysia gill withdrawal) are pointed out. For d input features, perceptron training is shown to have a lower bound of 2 d and an upper bound of d d adjusts. It is possible that the true upper bound is 4 d , though this has not been proved. Average performance is shown to have a lower bound of 1.4 d . Learning time is shown to increase linearly with the number of irrelevant or replicated features. The (X of N) function (a subset of linearly separable functions containing OR and AND) is shown to be learnable in d 3 time. A method of utilizing conditional probability to accelerate learning is proposed. This reduces the observed growth rate from 4 d to the theoretical minimum (for the unmodified version) of 2 d . A different version reduces the growth rate to about 1.7 d . The linear effect of irrelevant features can also be eliminated. Whether such an approach can be made provably convergent is not known.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 54 (1986), S. 393-406 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract Several distinct connectionistic/neural representations capable of computing arbitrary Boolean functions are described and discussed in terms of possible tradeoffs between time, space, and expressive clarity. It is suggested that the ability of a threshold logic unit (TLU) to represent prototypical groupings has significant advantages for representing real world categories. Upper and lower bounds on the number of nodes needed for Boolean completeness are demonstrated. The necessary number of nodes is shown to increase exponentially with the number of input features, the exact rate of increase depending on the representation scheme. In addition, in non-recurrent networks, connection weights are shown to increase exponentially with a linear reduction in the number of nodes below approximately 2d. This result suggests that optimum memory efficiency may require unacceptable learning time. Finally, two possible extensions to deal with non-Boolean values are considered.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 56 (1987), S. 121-137 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract Four connectionistic/neural models which are capable of learning arbitrary Boolean functions are presented. Three are provably convergent, but of differing generalization power. The fourth is not necessarily convergent, but its empirical behavior is quite good. The time and space characteristics of the four models are compared over a diverse range of functions and testing conditions. These include the ability to learn specific instances, to effectively generalize, and to deal with irrelevant or redundant information. Trade-offs between time and space are demonstrated by the various approaches.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 57 (1987), S. 57-71 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract A biologically plausible method for rapidly learning specific instances is described. It is contrasted with a formal model of classical conditioning (Rescorla-Wagner learning/perception training), which is shown to be relatively good for learning generalizations, but correspondingly poor for learning specific instances. A number of behaviorally relevant applications of specific instance learning are considered. For category learning, various combinations of specific instance learning and generalization are described and analyzed. Two general approaches are considered: the simple inclusion of Specific Instance Detectors (SIDs) as additional features during perception training, and specialized treatment in which SID-based categorization takes precedence over generalization-based categorization. Using the first approach, analysis and empirical results demonstrate a potential problem in representing feature presence and absence in a symmetric fashion when the frequencies of feature presence and absence are very different. However, it is shown that by using the proper representation, the addition of SIDs can only improve the convergence rate of perceptron training, the greatest improvement being achieved when SIDs are preferentially allocated for peripheral positive and negative instances. Some further improvement is possible if SIDs are treated in a specialized manner.
    Type of Medium: Electronic Resource
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  • 7
    ISSN: 1573-2568
    Source: Springer Online Journal Archives 1860-2000
    Topics: Medicine
    Type of Medium: Electronic Resource
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