Analytic Description of the Low‐Frequency Attenuation Coefficient

1967 ◽  
Vol 42 (1) ◽  
pp. 270-270 ◽  
Author(s):  
William H. Thorp
Keyword(s):  
Attenuation Coefficient ◽  
Low Frequency ◽  
Analytic Description

Bottom Attenuation Coefficient Inversion Based on the Modal Phase Difference Between Pressure and Vertical Velocity from a Single Vector Sensor

2021 ◽  
pp. 2150008
Author(s):  
Alexandre L. Guarino ◽  
Kevin B. Smith ◽  
Oleg A. Godin
Keyword(s):  
Attenuation Coefficient ◽  
Phase Difference ◽  
Vertical Velocity ◽  
Low Frequency ◽  
Propagation Model ◽  
Time Warping ◽  
Vector Sensor ◽  
Eigen Values ◽  
Sediment Bottom ◽  
Homogeneous Environment

An inversion scheme based on time-warping is presented for estimating the attenuation coefficient of a sediment bottom using a single vector sensor, restricted to shallow water and using low-frequency impulsive sources. The attenuation information is extracted from the modal phase difference between pressure and vertical velocity. The method is derived from Pekeris waveguide theoretical equations and the eigen values are obtained using the normal mode model Kraken. Some changes are made to the time-warping process to mitigate the inherent interference between adjacent modes, which improves the phase extraction capabilities. Results are presented for a two-layer, homogeneous environment using the RAM propagation model for depth-dependent sound speed profile simulations. This version of RAM was updated to provide radial and vertical velocities. For additional generality, the technique is evaluated in the presence of white noise.

DETERMINATION OF SPATIAL ATTENUATION OF NORMAL WAVES IN A SHALLOW SEA

2019 ◽  
pp. 37-42
Author(s):  
U.V. Makhnev ◽  
O.I. Piskunova ◽  
A.T. Trofimov
Keyword(s):  
Attenuation Coefficient ◽  
Low Frequency ◽  
Sound Field ◽  
Pulse Method ◽  
Dispersion Curves ◽  
Frequency Region ◽  
Shallow Sea ◽  
Normal Waves ◽  
Spatial Attenuation

This article discusses the possibility of estimating the spatial attenuation coefficient in the low-frequency region (<100 Hz) for individual normal waves and for the integral sound field created by a moving ship. A pulse method was used to resolve and obtain dispersion curves of normal waves. Estimates of the attenuation coefficient were obtained, and the possibility of determining the attenuation coefficient from noise signals of navigation was investigated.

A generalized O’Doherty‐Anstey formula for waves in finely layered media

Geophysics ◽  
1994 ◽  
Vol 59 (11) ◽  
pp. 1750-1762 ◽  
Author(s):  
Serge A. Shapiro ◽  
Holger Zien ◽  
Peter Hubral
Keyword(s):  
Layered Medium ◽  
Perturbation Technique ◽  
Finite Thickness ◽  
Low Frequency ◽  
Variable Density ◽  
Analytic Description ◽  
Mean Values ◽  
Time Harmonic ◽  
Backus Averaging ◽  
Theory Result

We investigate the angle‐dependent plane wave transmissivity of a pressure wave in a random, multilayered, acoustic, variable velocity and variable density medium. The main result of our consideration is a simple, explicit analytic description of the influence of such a medium on the transmissivity kinematics and dynamics for the whole frequency range. We assume that the velocity and density dependencies on depth are typical realizations of random stationary processes. Moreover, the fluctuations in both values must be relatively small compared to their constant mean values (of the order of 30 percent or smaller). In our derivation, we combine the small perturbation technique with the localization and self‐averaging theory. We obtain the attenuation and the phase of the time‐harmonic transmissivity, as well as the pulse form of the transient transmissivity from an angle‐dependent combination of the auto‐ and crosscorrelation functions of both the sonic and density logs. Our results for the kinematics of the transmissivity yield the wellknown “Backus averaging” in the low‐frequency limit. Likewise, they provide the ray theory result as the high‐frequency asymptotic value. The analytic expression for the transmissivity can be viewed as a generalization of the O’Doherty‐Anstey formula. Numerical computations of the actual transmissivity show fluctuations around the theoretical prediction given by our formula, which is strictly valid only in the case of infinitely thick media. The larger the layered medium, the smaller are these fluctuations. They can be well estimated with a formula which we derive to describe the deviations between the analytic and the exact transmissivity obtained for a layered medium of finite thickness.

scholarly journals Calibration and 21-cm power spectrum estimation in the presence of antenna beam variations

2019 ◽  
Vol 492 (2) ◽  
pp. 2017-2028 ◽  
Author(s):  
Ronniy C Joseph ◽  
C M Trott ◽  
R B Wayth ◽  
A Nasirudin
Keyword(s):  
Data Analysis ◽  
Power Spectrum ◽  
Low Frequency ◽  
Analytic Description ◽  
Spectral Features ◽  
Spectrum Estimation ◽  
Power Spectrum Estimation ◽  
Murchison Widefield Array ◽  
The Impact ◽  
Expected Signal

ABSTRACT Detecting a signal from the Epoch of Reionization (EoR) requires an exquisite understanding of Galactic and extragalactic foregrounds, low-frequency radio instruments, instrumental calibration, and data analysis pipelines. In this work, we build upon existing work that aims to understand the impact of calibration errors on 21-cm power spectrum (PS) measurements. It is well established that calibration errors have the potential to inhibit EoR detections by introducing additional spectral features that mimic the structure of EoR signals. We present a straightforward way to estimate the impact of a wide variety of modelling residuals in EoR PS estimation. We apply this framework to the specific case of broken dipoles in Murchison Widefield Array (MWA) to understand its effect and estimate its impact on PS estimation. Combining an estimate of the percentage of MWA tiles that have at least one broken dipole (15–40 per cent) with an analytic description of beam errors induced by such dipoles, we compute the residuals of the foregrounds after calibration and source subtraction. We find that that incorrect beam modelling introduces bias in the 2D-PS on the order of $\sim 10^3\, \mathrm{mK}^2 \, h^{-3}\, \mathrm{Mpc}^{3}$. Although this is three orders of magnitude lower than current lowest limits, it is two orders of magnitude higher than the expected signal. Determining the accuracy of both current beam models and direction-dependent calibration pipelines is therefore crucial in our search for an EoR signal.

A Study on the Fine Structure of the Lateral Line Organ of the Sea Eel

1973 ◽  
Vol 31 ◽  
pp. 648-649
Author(s):  
K. Hama
Keyword(s):  
Fine Structure ◽  
Electron Microscope ◽  
Lateral Line ◽  
Low Frequency ◽  
Sensory Cells ◽  
Apical Surface ◽  
Voltage Electron ◽  
Sensory Epithelia ◽  
Low Frequency Vibration ◽  
Transmission Electron

The lateral line organs of the sea eel consist of canal and pit organs which are different in function. The former is a low frequency vibration detector whereas the latter functions as an ion receptor as well as a mechano receptor.The fine structure of the sensory epithelia of both organs were studied by means of ordinary transmission electron microscope, high voltage electron microscope and of surface scanning electron microscope.The sensory cells of the canal organ are polarized in front-caudal direction and those of the pit organ are polarized in dorso-ventral direction. The sensory epithelia of both organs have thinner surface coats compared to the surrounding ordinary epithelial cells, which have very thick fuzzy coatings on the apical surface.

Lectin Binding to Human Breast Tumor Cells

1976 ◽  
Vol 34 ◽  
pp. 34-35
Author(s):  
Robert E. Nordquist ◽  
J. Hill Anglin ◽  
Michael P. Lerner
Keyword(s):  
Carcinoma Cell ◽  
Ricinus Communis ◽  
Lectin Binding ◽  
Low Frequency ◽  
Breast Carcinoma Cell Line ◽  
Human Breast ◽  
Human Breast Tumor ◽  
Duct Carcinoma ◽  
Specific Antigens ◽  
Ricin Agglutinin

A human breast carcinoma cell line (BOT-2) was derived from an infiltrating duct carcinoma (1). These cells were shown to have antigens that selectively bound antibodies from breast cancer patient sera (2). Furthermore, these tumor specific antigens could be removed from the living cells by low frequency sonication and have been partially characterized (3). These proteins have been shown to be around 100,000 MW and contain approximately 6% hexose and hexosamines. However, only the hexosamines appear to be available for lectin binding. This study was designed to use Concanavalin A (Con A) and Ricinus Communis (Ricin) agglutinin for the topagraphical localization of D-mannopyranosyl or glucopyranosyl and D-galactopyranosyl or DN- acetyl glactopyranosyl configurations on BOT-2 cell surfaces.

Practical High Resolution Microscopy

1968 ◽  
Vol 26 ◽  
pp. 302-303
Author(s):  
P. A. Marsh ◽  
T. Mullens ◽  
D. Price
Keyword(s):  
High Resolution ◽  
Magnetic Fields ◽  
Low Frequency ◽  
Resolving Power ◽  
Careful Attention ◽  
Electron Microscopes ◽  
The Relationship ◽  
High Resolution Microscopy ◽  
New Facilities

It is possible to exceed the guaranteed resolution on most electron microscopes by careful attention to microscope parameters essential for high resolution work. While our experience is related to a Philips EM-200, we hope that some of these comments will apply to all electron microscopes.The first considerations are vibration and magnetic fields. These are usually measured at the pre-installation survey and must be within specifications. It has been our experience, however, that these factors can be greatly influenced by the new facilities and therefore must be rechecked after the installation is completed. The relationship between the resolving power of an EM-200 and the maximum tolerable low frequency interference fields in milli-Oerstedt is 10 Å - 1.9, 8 Å - 1.4, 6 Å - 0.8.

Simulations of high-resolution images of amorphous silicon films

1986 ◽  
Vol 44 ◽  
pp. 544-545
Author(s):  
G. Y. Fan ◽  
J. M. Cowley
Keyword(s):  
Electron Microscope ◽  
High Frequency ◽  
Fourier Transformation ◽  
Amorphous Materials ◽  
Low Frequency ◽  
Chromatic Aberration ◽  
Structure Information ◽  
Frequency Components ◽  
High Resolution Images ◽  
Spatial Frequency Spectrum

It is well known that the structure information on the specimen is not always faithfully transferred through the electron microscope. Firstly, the spatial frequency spectrum is modulated by the transfer function (TF) at the focal plane. Secondly, the spectrum suffers high frequency cut-off by the aperture (or effectively damping terms such as chromatic aberration). While these do not have essential effect on imaging crystal periodicity as long as the low order Bragg spots are inside the aperture, although the contrast may be reversed, they may change the appearance of images of amorphous materials completely. Because the spectrum of amorphous materials is continuous, modulation of it emphasizes some components while weakening others. Especially the cut-off of high frequency components, which contribute to amorphous image just as strongly as low frequency components can have a fundamental effect. This can be illustrated through computer simulation. Imaging of a whitenoise object with an electron microscope without TF limitation gives Fig. 1a, which is obtained by Fourier transformation of a constant amplitude combined with random phases generated by computer.

SEM image sharpness analysis

1996 ◽  
Vol 54 ◽  
pp. 142-143
Author(s):  
M. T. Postek ◽  
A. E. Vladar
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Quantitative Information ◽  
Primary Electron ◽  
Image Sharpness ◽  
Critical Dimensions ◽  
Sem Image ◽  
Frequency Changes ◽  
Electron Microscopes ◽  
Scanning Electron

Fully automated or semi-automated scanning electron microscopes (SEM) are now commonly used in semiconductor production and other forms of manufacturing. The industry requires that an automated instrument must be routinely capable of 5 nm resolution (or better) at 1.0 kV accelerating voltage for the measurement of nominal 0.25-0.35 micrometer semiconductor critical dimensions. Testing and proving that the instrument is performing at this level on a day-by-day basis is an industry need and concern which has been the object of a study at NIST and the fundamentals and results are discussed in this paper.In scanning electron microscopy, two of the most important instrument parameters are the size and shape of the primary electron beam and any image taken in a scanning electron microscope is the result of the sample and electron probe interaction. The low frequency changes in the video signal, collected from the sample, contains information about the larger features and the high frequency changes carry information of finer details. The sharper the image, the larger the number of high frequency components making up that image. Fast Fourier Transform (FFT) analysis of an SEM image can be employed to provide qualitiative and ultimately quantitative information regarding the SEM image quality.

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