13 research outputs found

    OBSAPS data acquisition system : operator's manual and system overview

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    On the Ocean Bottom Seismometer Augmentation to the Philippine Sea Experiment (OBSAPS, April-May, 2011, R/V Revelle), a VLA and six OBSs were deployed to listen to an active acoustic source, a J15-3. This report describes the hardware and software used to control and record the acoustic transmissions from the source. Some significant features of the system are: 1) The system transmits general user-defined source functions, such as Msequences (.SIO files). 2) In addition to controlling the source waveform, the system also records six real-time channels in binary files with user-selectable lengths: the monitor hydrophone mounted near the source, the power amplifier voltage and current, the depth of the source, sonobuoy data (when deployed) and an IRIG-B time reference. Files are output in .AUV format with a precision GPS-based time stamp in the file name. 3) The transmission start time along with ADC and DAC sample rates are disciplined to GPS time. 4) A convenient, Labview based, user interface provides real-time source control and monitoring. 5) The software provides parsing and logging of gyro and GPS NMEA sentences. The system, which was based on an earlier system from Scripps MPL, worked well on OBSAPS and is available for future projects.Funding was provided by the Office of Naval Research under Contract Nos. N00014-10-1-0994 and N00014-10-1-0987

    OBSANP data acquisition system : operator's manual and system overview

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    On the Ocean Bottom Seismometer Augmentation in the North Pacific Experiment (OBSANP, June-July, 2013, R/V Melville), a VLA and twelve OBSs were deployed to listen to an active acoustic source, a J15-3. This report describes the hardware and software used to control and record the acoustic transmissions from the source. Some significant features of the system are: 1) The system transmits general user-defined source functions, such as M-sequences (.SIO files). 2) In addition to controlling the source waveform, the system also records six real-time channels in binary files with user-selectable lengths: the monitor hydrophone mounted near the source, the power amplifier voltage and current, the depth of the source, Vref signal driving the power amplifiers and an IRIG-B time reference. Files are output in .AUV format with a precision GPSbased time stamp in the file name. 3) The transmission start time along with ADC and DAC sample rates are disciplined to GPS time. 4) A convenient, Labview based, user interface provides real-time source control and monitoring. 5) The software provides parsing and logging of gyro and GPS NMEA sentences. The system, which was based on an earlier system from Scripps MPL, worked well on OBSANP and is available for future projects.Funding was provided by the Office of Naval Research under contract N00014-10-1-0987 and N00014-10-1-0510

    Deep water towed array measurements at close range

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    Author Posting. © Acoustical Society of America, 2013. This article is posted here by permission of Acoustical Society of America for personal use, not for redistribution. The definitive version was published in Journal of the Acoustical Society of America 134 (2013): 3230, doi:10.1121/1.4818869.During the North Pacific Acoustic Laboratory Philippine Sea 2009 experiment, towed array receptions were made from a towed source as the two ships transited from a separation of several Convergence Zones through a Closest Point of Approach at 3 km. A combination of narrowband tones and broadband pulses were transmitted covering the frequency band 79–535 Hz. The received energy arrives from two general paths—direct path and bottom bounce. Bearing-time records of the narrowband arrivals at times show a 35° spread in the angle of arrival of the bottom bounce energy. Doppler processing of the tones shows significant frequency spread of the bottom bounce energy. Two-dimensional modeling using measured bathymetry, a geoacoustic parameterization based upon the geological record, and measured sound-speed field was performed. Inclusion of the effects of seafloor roughness and surface waves shows that in-plane scattering from rough interfaces can explain much of the observed spread in the arrivals. Evidence of out-of-plane scattering does exist, however, at short ranges. The amount of out-of-plane scattering is best observed in the broadband impulse-beam response analysis, which in-plane surface roughness modeling cannot explain.This work was supported by the Office of Naval Research, Ocean Acoustics, under contract N00014-11-M-0170

    Estimating the horizontal and vertical direction-of-arrival of water-borne seismic signals in the northern Philippine Sea

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    Author Posting. © Acoustical Society of America, 2013. This article is posted here by permission of Acoustical Society of America for personal use, not for redistribution. The definitive version was published in Journal of the Acoustical Society of America 134 (2013): 3282, doi:10.1121/1.4818843.Conventional and adaptive plane-wave beamforming with simultaneous recordings by large-aperture horizontal and vertical line arrays during the 2009 Philippine Sea Engineering Test (PhilSea09) reveal the rate of occurrence and the two-dimensional arrival structure of seismic phases that couple into the deep ocean. A ship-deployed, controlled acoustic source was used to evaluate performance of the horizontal array for a range of beamformer adaptiveness levels. Ninety T-phases from unique azimuths were recorded between Yeardays 107 to 119. T-phase azimuth and S-minus-P-phase time-of-arrival range estimates were validated using United States Geological Survey seismic monitoring network data. Analysis of phases from a seismic event that occurred on Yearday 112 near the east coast of Taiwan approximately 450 km from the arrays revealed a 22° clockwise evolution of T-phase azimuth over 90 s. Two hypotheses to explain such evolution—body wave excitation of multiple sources or in-water scattering—are presented based on T-phase origin sites at the intersection of azimuthal great circle paths and ridge/coastal bathymetry. Propagation timing between the source, scattering region, and array position suggests the mechanism behind the evolution involved scattering of the T-phase from the Ryukyu Ridge and a T-phase formation/scattering location estimation error of approximately 3.2 km.This research is supported by the Office of Naval Research, both the Applied Research Laboratory program and Code 322(OA)

    Entropic Forces Drive Clustering and Spatial Localization of Influenza A M2 During Viral Budding

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    The influenza A matrix 2 (M2) transmembrane protein facilitates virion release from the infected host cell. In particular, M2 plays a role in the induction of membrane curvature and/or in the scission process whereby the envelope is cut upon virion release. Here we show using coarse-grained computer simulations that various M2 assembly geometries emerge due to an entropic driving force, resulting in compact clusters or linearly extended aggregates as a direct consequence of the lateral membrane stresses. Conditions under which these protein assemblies will cause the lipid membrane to curve are explored and we predict that a critical cluster size is required for this to happen. We go on to demonstrate that under the stress conditions taking place in the cellular membrane as it undergoes large-scale membrane remodeling, the M2 protein will in principle be able to both contribute to curvature induction and sense curvature in order to line up in manifolds where local membrane line tension is high. M2 is found to exhibit linactant behavior in liquid-disordered/liquid-ordered phase-separated lipid mixtures and to be excluded from the liquid-ordered phase, in near-quantitative agreement with experimental observations. Our findings support a role for M2 in membrane remodeling during influenza viral budding both as an inducer and a sensor of membrane curvature, and they suggest a mechanism by which localization of M2 can occur as the virion assembles and releases from the host cell, independent of how the membrane curvature is produced

    Calibrating passive acoustic monitoring: correcting humpback whale call detections for site-specific and time-dependent environmental characteristics.

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    This paper demonstrates the importance of accounting for environmental effects on passive underwater acoustic monitoring results. The situation considered is the reduction in shipping off the California coast between 2008-2010 due to the recession and environmental legislation. The resulting variations in ocean noise change the probability of detecting marine mammal vocalizations. An acoustic model was used to calculate the time-varying probability of detecting humpback whale vocalizations under best-guess environmental conditions and varying noise. The uncorrected call counts suggest a diel pattern and an increase in calling over a two-year period; the corrected call counts show minimal evidence of these features

    Site specific probability of passive acoustic detection of humpback whale calls from single fixed hydrophones.

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    Passive acoustic monitoring of marine mammal calls is an increasingly important method for assessing population numbers, distribution, and behavior. A common mistake in the analysis of marine mammal acoustic data is formulating conclusions about these animals without first understanding how environmental properties such as bathymetry, sediment properties, water column sound speed, and ocean acoustic noise influence the detection and character of vocalizations in the acoustic data. The approach in this paper is to use Monte Carlo simulations with a full wave field acoustic propagation model to characterize the site specific probability of detection of six types of humpback whale calls at three passive acoustic monitoring locations off the California coast. Results show that the probability of detection can vary by factors greater than ten when comparing detections across locations, or comparing detections at the same location over time, due to environmental effects. Effects of uncertainties in the inputs to the propagation model are also quantified, and the model accuracy is assessed by comparing calling statistics amassed from 24,690 humpback units recorded in the month of October 2008. Under certain conditions, the probability of detection can be estimated with uncertainties sufficiently small to allow for accurate density estimates
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