5,157 research outputs found

    Development and field testing of a Light Aircraft Oil Surveillance System (LAOSS)

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    An experimental device consisting of a conventional TV camera with a low light level photo image tube and motor driven polarized filter arrangement was constructed to provide a remote means of discriminating the presence of oil on water surfaces. This polarized light filtering system permitted a series of successive, rapid changes between the vertical and horizontal components of reflected polarized skylight and caused the oil based substances to be more easily observed and identified as a flashing image against a relatively static water surface background. This instrument was flight tested, and the results, with targets of opportunity and more systematic test site data, indicate the potential usefulness of this airborne remote sensing instrument

    Experience applicable to the Viking lander from a study of related space flight projects

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    Related space mission data for baseline evaluation of Viking Lander design and operatio

    Earthquake cycles and neural reverberations

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    Driven systems of interconnected blocks with stick-slip friction capture main features of earthquake processes. The microscopic dynamics closely resemble those of spiking nerve cells. We analyze the differences in the collective behavior and introduce a class of solvable models. We prove that the models exhibit rapid phase locking, a phenomenon of particular interest to both geophysics and neurobiology. We study the dependence upon initial conditions and system parameters, and discuss implications for earthquake modeling and neural computation

    Simultaneous current-, force- and work function measurement with atomic resolution

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    The local work function of a surface determines the spatial decay of the charge density at the Fermi level normal to the surface. Here, we present a method that enables simultaneous measurements of local work function and tip-sample forces. A combined dynamic scanning tunneling microscope and atomic force microscope is used to measure the tunneling current between an oscillating tip and the sample in real time as a function of the cantilever's deflection. Atomically resolved work function measurements on a silicon (111)-(7×77\times 7) surface are presented and related to concurrently recorded tunneling current- and force- measurements.Comment: 8 pages, 4 figures, submitted to Applied Physics Letter

    Statistical mechanics of temporal association in neural networks with transmission delays

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    We study the representation of static patterns and temporal sequences in neural networks with signal delays and a stochastic parallel dynamics. For a wide class of delay distributions, the asymptotic network behavior can be described by a generalized Gibbs distribution, generated by a novel Lyapunov functional for the determination dynamics. We extend techniques of equilibrium statistical mechanics so as to deal with time-dependent phenomena, derive analytic results for both retrieval quality and storage capacity, and compare them with numerical simulations

    Charge trapping in polymer transistors probed by terahertz spectroscopy and scanning probe potentiometry

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    Terahertz time-domain spectroscopy and scanning probe potentiometry were used to investigate charge trapping in polymer field-effect transistors fabricated on a silicon gate. The hole density in the transistor channel was determined from the reduction in the transmitted terahertz radiation under an applied gate voltage. Prolonged device operation creates an exponential decay in the differential terahertz transmission, compatible with an increase in the density of trapped holes in the polymer channel. Taken in combination with scanning probe potentionmetry measurements, these results indicate that device degradation is largely a consequence of hole trapping, rather than of changes to the mobility of free holes in the polymer.Comment: 4 pages, 3 figure

    Optimal Population Codes for Space: Grid Cells Outperform Place Cells

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    Rodents use two distinct neuronal coordinate systems to estimate their position: place fields in the hippocampus and grid fields in the entorhinal cortex. Whereas place cells spike at only one particular spatial location, grid cells fire at multiple sites that correspond to the points of an imaginary hexagonal lattice. We study how to best construct place and grid codes, taking the probabilistic nature of neural spiking into account. Which spatial encoding properties of individual neurons confer the highest resolution when decoding the animal’s position from the neuronal population response? A priori, estimating a spatial position from a grid code could be ambiguous, as regular periodic lattices possess translational symmetry. The solution to this problem requires lattices for grid cells with different spacings; the spatial resolution crucially depends on choosing the right ratios of these spacings across the population. We compute the expected error in estimating the position in both the asymptotic limit, using Fisher information, and for low spike counts, using maximum likelihood estimation. Achieving high spatial resolution and covering a large range of space in a grid code leads to a trade-off: the best grid code for spatial resolution is built of nested modules with different spatial periods, one inside the other, whereas maximizing the spatial range requires distinct spatial periods that are pairwisely incommensurate. Optimizing the spatial resolution predicts two grid cell properties that have been experimentally observed. First, short lattice spacings should outnumber long lattice spacings. Second, the grid code should be self-similar across different lattice spacings, so that the grid field always covers a fixed fraction of the lattice period. If these conditions are satisfied and the spatial “tuning curves” for each neuron span the same range of firing rates, then the resolution of the grid code easily exceeds that of the best possible place code with the same number of neurons

    Mesoscopic order and the dimentionality of long-range resonance energy transfer in supramolecular semiconductors

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    We present time-resolved photoluminescence measurements on two series of oligo-p-phenylenevinylene materials that self-assemble into supramolecular nanostructures with thermotropic reversibility in dodecane. One set of derivatives form chiral, helical stacks while the second set form less organised, frustrated stacks. Here we study the effects of supramolecular organisation on the resonance energy transfer rates. We measure these rates in nanoassemblies formed with mixed blends of oligomers and compare them with the rates predicted by Foerster theory. Our results and analysis show that control of supramolecular order in the nanometre lengthscale has a dominant effect on the efficiency and dimentionality of resonance energy transfer.Comment: 17 Pages, 5 Figures, Submitted to J. Chem. Phy
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