Influence of multiple scattering on the measurement of light attenuation by water filled with bubbles

Author(s):  
Sun Chunsheng ◽  
Zhang Xiaohui ◽  
Zhang Shuang
Author(s):  
S. Golladay

The theory of multiple scattering has been worked out by Groves and comparisons have been made between predicted and observed signals for thick specimens observed in a STEM under conditions where phase contrast effects are unimportant. Independent measurements of the collection efficiencies of the two STEM detectors, calculations of the ratio σe/σi = R, where σe, σi are the total cross sections for elastic and inelastic scattering respectively, and a model of the unknown mass distribution are needed for these comparisons. In this paper an extension of this work will be described which allows the determination of the required efficiencies, R, and the unknown mass distribution from the data without additional measurements or models. Essential to the analysis is the fact that in a STEM two or more signal measurements can be made simultaneously at each image point.


Author(s):  
C P Scott ◽  
A J Craven ◽  
C J Gilmore ◽  
A W Bowen

The normal method of background subtraction in quantitative EELS analysis involves fitting an expression of the form I=AE-r to an energy window preceding the edge of interest; E is energy loss, A and r are fitting parameters. The calculated fit is then extrapolated under the edge, allowing the required signal to be extracted. In the case where the characteristic energy loss is small (E < 100eV), the background does not approximate to this simple form. One cause of this is multiple scattering. Even if the effects of multiple scattering are removed by deconvolution, it is not clear that the background from the recovered single scattering distribution follows this simple form, and, in any case, deconvolution can introduce artefacts.The above difficulties are particularly severe in the case of Al-Li alloys, where the Li K edge at ~52eV overlaps the Al L2,3 edge at ~72eV, and sharp plasmon peaks occur at intervals of ~15eV in the low loss region. An alternative background fitting technique, based on the work of Zanchi et al, has been tested on spectra taken from pure Al films, with a view to extending the analysis to Al-Li alloys.


1986 ◽  
Vol 47 (C8) ◽  
pp. C8-589-C8-592
Author(s):  
N. BINSTED ◽  
S. L. COOK ◽  
J. EVANS ◽  
R. J. PRICE ◽  
G. N. GREAVES

2020 ◽  
Vol 642 ◽  
pp. 133-146
Author(s):  
PC González-Espinosa ◽  
SD Donner

Warm-water growth and survival of corals are constrained by a set of environmental conditions such as temperature, light, nutrient levels and salinity. Water temperatures of 1 to 2°C above the usual summer maximum can trigger a phenomenon known as coral bleaching, whereby disruption of the symbiosis between coral and dinoflagellate micro-algae, living within the coral tissue, reveals the white skeleton of coral. Anomalously cold water can also lead to coral bleaching but has been the subject of limited research. Although cold-water bleaching events are less common, they can produce similar impacts on coral reefs as warm-water events. In this study, we explored the effect of temperature and light on the likelihood of cold-water coral bleaching from 1998-2017 using available bleaching observations from the Eastern Tropical Pacific and the Florida Keys. Using satellite-derived sea surface temperature, photosynthetically available radiation and light attenuation data, cold temperature and light exposure metrics were developed and then tested against the bleaching observations using logistic regression. The results show that cold-water bleaching can be best predicted with an accumulated cold-temperature metric, i.e. ‘degree cooling weeks’, analogous to the heat stress metric ‘degree heating weeks’, with high accuracy (90%) and fewer Type I and Type II errors in comparison with other models. Although light, when also considered, improved prediction accuracy, we found that the most reliable framework for cold-water bleaching prediction may be based solely on cold-temperature exposure.


2011 ◽  
Vol 181 (7) ◽  
pp. 681 ◽  
Author(s):  
V.B. Molodkin ◽  
A.P. Shpak ◽  
M.V. Kovalchuk ◽  
V.F. Machulin ◽  
V.L. Nosik
Keyword(s):  

2010 ◽  
Vol 20 (2) ◽  
pp. 133-139 ◽  
Author(s):  
Edouard Berrocal ◽  
Elias Kristensson ◽  
Mattias Richter ◽  
Mark Linne ◽  
Marcus Alden

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