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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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PSFcheck ring pattern at various SNR

Authors: Damián Martínez;

PSFcheck ring pattern at various SNR

Abstract

The imaged PSFcheck pattern consists of a nanometric set of ring-like laser-written structures with a separation of 10 µm between each. The mean FWHM of these patterns was calculated to be 208 nm. A NanoImager-S microscope (ONI, Oxford Nanoimaging), equipped with a 100X 1.4 NA, oil-immersion objective (Olympus) was used to image the PSFcheck patterns in widefield fluorescence mode. Sample excitation was provided by a 561 nm laser and emission was collected with a 575-616.5 emission filter. A sCMOS sensor (Hamamatsu, Orca-0Flash4.0 V3) was used for image aquisition at 30 fps and 117 nm pixel size.

Three files are provided. 'Raw PSFcheck pattern' corresponds to the imaged sample with the intensity displayed as gray levels. 'Photons PSFcheck pattern' displays the intensity as the number of detected photons during image acquisition (see Methods section of the article associated to this dataset). 'ACsN-corrected PSFcheck pattern' contains the ring pattern images after noise correction with the ACsN algorithm [1]. 1. Mandracchia, B., Hua, X., Guo, C. et al. Fast and accurate sCMOS noise correction for fluorescence microscopy. Nat Commun 11, 94 (2020).

{"references": ["Alexander D. Corbett, Michael Shaw, Andrew Yacoot, Andrew Jefferson, Lothar Schermelleh, Tony Wilson, Martin Booth, and Patrick S. Salter, \"Microscope calibration using laser written fluorescence,\" Opt. Express 26, 21887-21899 (2018)"]}

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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