404 research outputs found

    Numerical analysis and prediction of cloud and precipitation patterns

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    Present numerical weather methods do not include a current analysis or a forecast of larger scale occurrence of cloudiness and precipitation. The model used in this paper uses vertical velocities and dew-point depressions at the levels of 850, 700, and 100 mb as inputs to a diagram which determines the accompanying weather parameter. Good results were obtained for a current analysis, but the prognosis scheme used proved to be unsatisfactory at the present time. The model is programmed for the Control Data Corporation 1604 digital computer to utilize the operational output of machine-processed data and analysis produced by U.S. Navy Fleet Numerical Weather Facility (FNWF), Monterey, California. The writers wish to express their appreciation to Professor George J. Haltiner of the U.S. Naval Postgraduate School for his assistance, guidance and encouragement in this work. Appreciation is also expressed to the personnel of FNWF for their cooperation and especially Mr. Harry Farnsworth for his aid and advice in programming and performing the machine computations. We also wish to express our thanks to Mrs. E.L. Geraldson and Mrs. C.D. Clower for their work in plotting numerous weather charts used in the verifications.http://www.archive.org/details/numericalanalysi00geraLieutenant, United States NavyApproved for public release; distribution is unlimited

    Incorporating inventories into supply and demand analysis

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    While the paper lacks a formal abstract, it draws the important distinction between stocks and flows in supply and demand to better understand the business cycle

    Incorporating inventories into supply and demand analysis

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    While the paper lacks a formal abstract, it draws the important distinction between stocks and flows in supply and demand to better understand the business cycle.Inventories; supply and demand; business cycles; stocks versus flows

    Integrating incremental learning and episodic memory models of the hippocampal region.

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    By integrating previous computational models of corticohippocampal function, the authors develop and test a unified theory of the neural substrates of familiarity, recollection, and classical conditioning. This approach integrates models from 2 traditions of hippocampal modeling, those of episodic memory and incremental learning, by drawing on an earlier mathematical model of conditioning, SOP (A. Wagner, 1981). The model describes how a familiarity signal may arise from parahippocampal cortices, giving a novel explanation for the finding that the neural response to a stimulus in these regions decreases with increasing stimulus familiarity. Recollection is ascribed to the hippocampus proper. It is shown how the properties of episodic representations in the neocortex, parahippocampal gyrus, and hippocampus proper may explain phenomena in classical conditioning. The model reproduces the effects of hippocampal, septal, and broad hippocampal region lesions on contextual modulation of classical conditioning, blocking, learned irrelevance, and latent inhibition

    How Emotion Strengthens the Recollective Experience: A Time-Dependent Hippocampal Process

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    Emotion significantly strengthens the subjective recollective experience even when objective accuracy of the memory is not improved. Here, we examine if this modulation is related to the effect of emotion on hippocampal-dependent memory consolidation. Two critical predictions follow from this hypothesis. First, since consolidation is assumed to take time, the enhancement in the recollective experience for emotional compared to neutral memories should become more apparent following a delay. Second, if the emotion advantage is critically dependent on the hippocampus, then the effects should be reduced in amnesic patients with hippocampal damage. To test these predictions we examined the recollective experience for emotional and neutral photos at two retention intervals (Experiment 1), and in amnesics and controls (Experiment 2). Emotional memories were associated with an enhancement in the recollective experience that was greatest after a delay, whereas familiarity was not influenced by emotion. In amnesics with hippocampal damage the emotion effect on recollective experience was reduced. Surprisingly, however, these patients still showed a general memory advantage for emotional compared to neutral items, but this effect was manifest primarily as a facilitation of familiarity. The results support the consolidation hypothesis of recollective experience, but suggest that the effects of emotion on episodic memory are not exclusively hippocampally mediated. Rather, emotion may enhance recognition by facilitating familiarity when recollection is impaired due to hippocampal damage
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