READ ME File For 'Dataset supporting the University of Southampton Doctoral Thesis "Ultra-high speed imaging of cell-microbubble interactions for bone repair"- MatchID DIC Data' Dataset DOI: 10.5258/SOTON/D2955 ReadMe Author: OLIVER PATTINSON, University of Southampton 0009-0009-3399-2177 This dataset supports the thesis entitled Ultra-high speed imaging of cell-microbubble interactions for bone repair" AWARDED BY: Univeristy of Southampton DATE OF AWARD: [2024] DESCRIPTION OF THE DATA [This should include a detailed description of the data, how it was collected/created, any specialist software needed to view the data] This dataset contains: Excel data files for deformation data within cell microbubble interactions as measured by DIC using MatchID software for a range of different 5 million FPS ultra-high speed videos over 127 frames. Individual videos are cross-referenced with the 'UHS Image' data set using date and time stamps. Excel files each represent indiviual interactions, recording the time point(1-127), the cartesian position within the image, the horizontal deformation and the vertical deformation. Date of data collection: 09/2019-02/2023 Information about geographic location of data collection: Southampton Matlab Anaylis Results A collection of graphical results generated using matlab analysis on the numerical data found in the 'MatchID DIC' data set. Each folder refrenecd by a date and time stamp corresponds to an individual UHS video of cell mircobubble interactions, and contains 3x deformation sine fits, visual representation of the deformation directions, and multiple plots showing the displacement or the phase of the sine fit vs distance from microbubble. Licence: Related projects/Funders: EP/R513325/1, NE/W503150/1 Related publication: An Acoustic Device for Ultrahigh Speed Quantification of Cell Strain During Cell−Microbubble Interaction Date that the file was created: January, 2024 -------------- Notes: 1. Rename file, giving it an appropriate name and removing the word 'template'. 2. Remove [] adding in information where required. 3. Remove any sections not relevant to your dataset 4. Remove these notes before saving