Dr John Beavis
- 01202 964202
- jbeavis at bournemouth dot ac dot uk
- Principal Academic Quantitative Research Design and Data Analysis
- Dorset House DG13, Talbot Campus, Fern Barrow, Poole, BH12 5BB
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- Vassallo, J., Beavis, J., Smith, J.E. and Wallis, L.A., 2017. Major incident triage: Derivation and comparative analysis of the Modified Physiological Triage Tool (MPTT). Injury, 48 (5), 992-999.
- Morakabati, Y. and Beavis, J., 2017. Do Terrorist Attacks Leave an Identifiable ‘Fingerprint’ on International Tourist Arrival Data? International Journal of Tourism Research, 19 (2), 179-190.
- Morakabati, Y., Beavis, J. and Fletcher, J., 2014. Planning for a Qatar Without Oil: Tourism and Economic Diversification, a Battle of Perceptions. Tourism Planning and Development, 11 (4), 415-434.
- Hartwell, H.J., Edwards, J.S.A. and Beavis, J., 2007. Plate versus bulk trolley food service in a hospital: comparison of patients' satisfaction. Nutrition, 23 (3), 211-218.
- Beavis, J. and Mott, C.J.B., 1999. Effects of land use on the amino acid composition of soils: 2. Soils from the Park Grass experiment and Broadbalk Wilderness, Rothamsted, England. Geoderma, 91 (1-2), 173-190.
- Allen, G. and Beavis, J., 1996. Building on the past. CHEMISTRY IN BRITAIN, 32 (9), 24-28.
- Beavis, J. and Mott, C.J.B., 1996. Effects of land use on the amino acid composition of soils: 1. Manured and unmanured soils from the broadbalk continuous wheat experiment, Rothamsted, England. Geoderma, 72 (3-4), 259-270.
- Moynehan, C.R., Allen, G.C., Brown, I.T., Church, S.R., Beavis, J. and Ashurst, J., 1995. Surface Analysis Of Architectural Terracotta: Including New And Soiled Examples, And Pieces Treated With A Hydrofluoric Acid-Based Cleaning Solution. Journal of Architectural Conservation, 1 (1), 56-69.
- Beavis, J., 1985. Amino acids in buried soils. Palaeoenvironmental investigations. Symposia of the Association for Environmental Archaeology 5A, 113-124.
- Dave, J.M., Dubey, V.N., Coppini, D.V. and Beavis, J., 2019. Predicting diabetic neuropathy risk level using artificial neural network based on clinical characteristics of subjects with diabetes. 144.
- Dave, J.M., Dubey, V.N., Lowes, V., Beavis, J. and Coppini, D.V., 2018. A ‘smarter’ way of diagnosing the at risk foot: Development of a novel tool based on vibratory measurements in subjects with diabetes. In: Diabetes UK Professional Conference 14-18 March 2018 London.
- Davies, S.J., Russ, B., Beavis, J. and Coppini, D.V., 2016. SGLT2 inhibitors in overweight patients with Type 2 diabetes with problematic glycaemic control: a welcome opening to a dead end? A hospital clinic audit. 163.
The data on this page was last updated at 04:14 on February 27, 2020.