File:Agent-Based-Model-of-Human-Alveoli-Predicts-Chemotactic-Signaling-by-Epithelial-Cells-during-Early-pone.0111630.s010.ogv

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Original file ‎(Ogg Theora video file, length 13 s, 1,280 × 720 pixels, 354 kbps, file size: 577 KB)

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English: Virtual infection scenario with biased persistent random walk migration of alveolar macrophages. Alveolar macrophages (green) perform biased persistent random walk migration with parameters and in order to find the conidium of A. fumigatus (red) in the alveolus. The alveolar macrophages realized the first-passage in 90 min of time. The video is sampled at a rate of 25 frames per second and the time between two frames corresponds to 0.5 min real time.
Date
Source Video S4 from Pollmacher J, Figge M (2014). "Agent-Based Model of Human Alveoli Predicts Chemotactic Signaling by Epithelial Cells during Early Aspergillus fumigatus Infection". PLOS ONE. DOI:10.1371/journal.pone.0111630. PMID 25360787. PMC: 4216106.
Author Pollmacher J, Figge M
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This file is licensed under the Creative Commons Attribution 4.0 International license.
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This file was transferred to Wikimedia Commons from PubMed Central by way of the Open Access Media Importer.
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Date/TimeThumbnailDimensionsUserComment
current04:03, 14 November 201413 s, 1,280 × 720 (577 KB)Open Access Media Importer Bot (talk | contribs)Automatically uploaded media file from Open Access source. Please report problems or suggestions here.

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Format Bitrate Download Status Encode time
VP9 720P 170 kbps Completed 22:56, 16 August 2018 9.0 s
Streaming 720p (VP9) 170 kbps Completed 07:17, 25 January 2024 2.0 s
VP9 480P 71 kbps Completed 22:56, 16 August 2018 8.0 s
Streaming 480p (VP9) 72 kbps Completed 16:58, 17 December 2023 1.0 s
VP9 360P 50 kbps Completed 22:56, 16 August 2018 5.0 s
Streaming 360p (VP9) 50 kbps Completed 23:48, 1 January 2024 1.0 s
VP9 240P 33 kbps Completed 22:56, 16 August 2018 4.0 s
Streaming 240p (VP9) 34 kbps Completed 18:31, 9 December 2023 1.0 s
WebM 360P 168 kbps Completed 04:05, 14 November 2014 8.0 s
Streaming 144p (MJPEG) 792 kbps Completed 23:52, 29 October 2023 1.0 s

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