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Now showing items 208-227 of 1716
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Data for paper, Upscaling diffusion through first-order volumetric sinks: a homogenization of bacterial nutrient uptake
(The University of Nottingham, 2018-03-12)Data for the SIAP paper "Upscaling diffusion through first-order volumetric sinks: a homogenization of bacterial nutrient uptake". -
Data for paper: Dispersive detection of radio-frequency dressed states, arxiv:1801.07016
(The University of Nottingham, 2018-04-09)We introduce a method to dispersively detect alkali atoms in radio-frequency dressed states. In particular, we use dressed detection to measure populations and population differences of atoms prepared in their clock states. ... -
Data for paper: Mathematical modelling of chemical agent removal by reaction with an immiscible cleanser
(The University of Nottingham, 2017-09-04)This file provides the data for the figures in the paper 'Mathematical modelling of chemical agent removal by reaction with an immiscible cleanser', published in the SIAM Journal on Applied Mathematics, accepted on 31 August 2017. -
Data for paper: The effect of weak inertia in rotating high-aspect-ratio vessel bioreactors
(The University of Nottingham, 2017-11-07)This file provides the data for the figures in the paper 'The effect of weak inertia in rotating high-aspect-ratio vessel bioreactors', published in the Journal of Fluid Mechanics accepted on 14 September 2017. -
Data for surface-controlled spatially heterogeneous physical properties of a supramolecular gel with homogeneous chemical composition
(University of Nottingham, 2021-10-15)Data related to the research article entitled 'Surface-controlled spatially heterogeneous physical properties of a supramolecular gel with homogeneous chemical composition '. -
DATA for: Conforming with peers in honesty and cooperation
(The University of Nottingham, 2023-02-03)This dataset contains the data and analysis files of experiments conducted on the online platform Prolific. -
Data for: Coordinate based meta-analysis of networks in neuroimaging studies
(Mendeley, 2020) -
Data for: Listeners are better at predicting speakers similar to themselves
(Figshare, 2020)