671 research outputs found

    Extent and mechanism of sealing in transected giant axons of squid and earthworms

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    Transected axons are often assumed to seal at their cut ends by the formation of continuous membrane barriers that allow for the restoration of function in the axonal stumps. We have used several electrophysiological measures (membrane potential, input resistance, injury current density) and several morphological measures (phase-contrast, video-enhanced differential interference contrast, light, and electron microscopies) of living and fixed material to assess the extent and mechanism of sealing within hours after transecting giant axons of squid (Loligo pealeiand Sepioteuthis lessoniana) and earthworms (Lumbricus terrestris). Our electrophysiological data suggest that the proximal and distal ends of transected squid giant axons do not completely seal within 2.5 hr in physiological saline. In contrast, the same set of measures suggest that proximal and distal ends of transected earthworm giant axons seal within 1 hr in physiological saline. Our morphological data show that the cut ends of both squid and earthworm axons constrict, but that a 20- 70-am-diameter opening always remains at the cut end that is filled with vesicles. Axonal transection induces the formation of vesicles that are observed in the axoplasm within minutes in standard salines and that rapidly migrate to the cut ends. These injury-induced vesicles are loosely packed near the cut ends of squid giant axons, which do not functionally seal within 2.5 hr of transection. In contrast, vesicles formed a tightly packed plug at the cut ends of earthworm medial giant axons, which do functionally seal within 1 hr of transection in physiological saline. Since we detect no single continuous membrane that spans the cut end, sealing does not appear to occur by the fusion of constricted axolemmal membrane or the formation of a membranous partition at the cut end. Rather, our data are consistent with the hypothesis that a tightly packed vesicular plug is responsible for sealing of earthworm giant axons.This work was supported in part by NIH Grant NS31256 and ONR Grant N00014-90-J-1137 to H.M.F., an NIAAA fellowship to T.L.K., and an ATP grant to G.D.B.Neuroscienc

    Interface roughness and planar doping in superlattices: weak localization effects

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    We examine the effects of interface roughness and/or planar impurity doping in a superlattice, in the frame of a weak disorder description. We find that these two types of disorder are equivalent, and that they can be viewed as effective "bulk" disorder, with anisotropic diffusion coefficients. Our results offer quantitative insight to transport properties of multilayers and devices, which contain inadvertently structural disorder at the interfaces.Comment: 4 page

    How Errors in Component Reliability Affect System Reliability

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    This paper studies how sampling variation in component reliability estimates affects the computation of system reliability that uses these estimates as input. Results show that relative bias in system reliability grows quadratically with the number of components for which each component reliability estimate is used, whereas the corresponding coefficient of variation grows linearly with this number of components. If these components are in parallel they lead to an understatement of system reliability. In series, they lead to an overstatement. The paper describes resampling schemes that eliminate bias without increasing the dominant variance term

    A Monte Carlo Sampling Plan for Estimating Network Reliability

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    Consider an acyclic undirected network G = (V,E) with node set V and arc set E whose arcs are subject to random failure. Let s be a node in V and T a set of nodes in V such that s ⊄ T. This paper presents a relatively complete and comprehensive description of a general class of Monte Carlo sampling plans for estimating g = g(s,T), the probability that s is connected to all nodes in T. The paper also provides procedures for implementing these plans. Each plan uses known lower and upper bounds [B,A] on g to produce an estimator of g that has a smaller variance (A-g)(g-B)/K than one obtains for crude Monte Carlo sampling (B-O, A-1) on K independent replications. The paper describes worst case bounds on sample sizes K, in terms of B and A, for meeting absolute and relative error criteria. It also gives the worst case bound on the amount of variance reduction that can be expected when compared with crude Monte Carlo sampling. Two plans are studied in detail for the case T - {t}. An example illustrates the variance reductions achievable with these plans. The paper next shows how to assess the credibility that a specified error criterion for g is met as the Monte Carlo experiment progresses and then shows how confidence intervals can be computed for g. Lastly, the paper summarizes the steps needed toimplement the proposed technique

    Estimating critical path and arc probabilities in stochastic activity networks

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    This paper describes a new procedure for estimating parameters of a stochastic activity network of N arcs. The parameters include the probability that path m is the longest path, the probability that path m is the shortest path, the probability that arc i is on the longest path and the probability that arc i is on the shortest path. The proposed procedure uses quasirandom points together with information on a cutset H of the network to produce an upper bound of O((log K)N-IHI+l/K) on the absolute error of approximation where K denotes the number of replications. This is a deterministic bound and is more favorable than the convergence rate of I/K1/2 that one obtains for the standard error for K independent replications using random sampling. It is also shown how series reduction can improve the convergence rate by reducing the exponent on log K . The technique is illustrated using a Monte Carlo sampling experiment for a network of 16 relevant arcs with a cutset of H=7 arcs. The illustration shows the superior performance of using quasirandom points with a cutset (plan A) and the even better performance of using quasirandom points with the cutset together with series reduction (plan B) with regard to mean-square error. However, it also shows that computation time considerations favor plan A when K is small and plan B when K is large

    Do Gamma-Ray Burst Sources Repeat?

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    The demonstration of repeated gamma-ray bursts from an individual source would severely constrain burst source models. Recent reports (Quashnock and Lamb 1993; Wang and Lingenfelter 1993) of evidence for repetition in the first BATSE burst catalog have generated renewed interest in this issue. Here, we analyze the angular distribution of 585 bursts of the second BATSE catalog (Meegan et al. 1994). We search for evidence of burst recurrence using the nearest and farthest neighbor statistic and the two-point angular correlation function. We find the data to be consistent with the hypothesis that burst sources do not repeat; however, a repeater fraction of up to about 20% of the observed bursts cannot be excluded.Comment: ApJ Letters, in press, 13 pages, including three embedded figures. uuencoded Unix-compressed PostScrip

    The Fermi GBM Gamma-Ray Burst Spectral Catalog: Four Years Of Data

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    In this catalog we present the updated set of spectral analyses of GRBs detected by the Fermi Gamma-Ray Burst Monitor (GBM) during its first four years of operation. It contains two types of spectra, time-integrated spectral fits and spectral fits at the brightest time bin, from 943 triggered GRBs. Four different spectral models were fitted to the data, resulting in a compendium of more than 7500 spectra. The analysis was performed similarly, but not identically to Goldstein et al. 2012. All 487 GRBs from the first two years have been re-fitted using the same methodology as that of the 456 GRBs in years three and four. We describe, in detail, our procedure and criteria for the analysis, and present the results in the form of parameter distributions both for the observer-frame and rest-frame quantities. The data files containing the complete results are available from the High-Energy Astrophysics Science Archive Research Center (HEASARC).Comment: Accepted for publication in ApJ
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