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This model utilized the neutron diffraction measurements to predict the stress distribution inside each phase and at the interface.
Most work that has been published using this model utilized a prophylactic dosing regimen, where treatment was started prior to disease onset.
Because this model utilized a cell-free perfusate, the mtDNA : nDNA ratio is not confounded by potential contributions from immune cells – a point that has been raised as a possible explanation for changes in mtDNA : nDNA ratio.
Initial calibration of this model utilized the Ferguson et al. approach with data from historical (1957 58, 1968 69) influenza pandemics and targeted an epidemic with a 35% attack rate seen in the 1957 58 pandemic [ 33- 36].
This model utilized the same Monte Carlo methodology as that described above and used a random number generator to determine the various journeys made the HCWs (e.g. from Patient A to Patient D; from Patient B to Patient C; etc).
This model utilized data on system-specific escapements, system-specific age compositions, district catch, and genetic estimates of catch composition (Dann et al. 2009) to estimate parameters for run size at length, gear selectivity, and stock availability.
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This model utilizes the evaporation momentum force and receding contact angle β as parameters.
This model utilizes the k ɛ turbulence model to solve the flow equations.
This model utilizes the recruitment and activation of neutrophils into bronchial alveolar lavage fluid (BALF) as the efficacy endpoint.
This model utilizes and applies concepts from social theorist Michel Foucault, including the use of discourse and networked power relations in order to normalize and modify thoughts and behaviors.
This model utilizes a neural network in prediction of airtightness and is obtained based on in situ measurements at 58 units in the local Osijek area (Croatia) carried out during 2013.
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