Bangor University
- Article › Research › Peer-reviewed
- Published
Predictable hydrodynamic conditions explain temporal variations in the density of benthic foraging seabirds in a tidal stream environment
Waggitt, J. J., Cazenave, P. W., Torres, R., Williamson, B. J. & Scott, B. E., Nov 2016, In: ICES Journal of Marine Science. 73, 10, p. 2677-2686Research output: Contribution to journal › Article › peer-review
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Predicted Deep-Sea Coral Habitat Suitability for the U.S. West Coast
Guinotte, J. M. & Davies, A. J., 23 Apr 2014, In: PLoS ONE. 9, 4Research output: Contribution to journal › Article › peer-review
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Predicting "real world" effectiveness by integrating adherence with pharmacodynamic modelling.
Hughes, D., Hughes, D. A. & Walley, T., 1 Jul 2003, In: Clinical Pharmacology and Therapeutics. 74, 1, p. 1-8Research output: Contribution to journal › Article › peer-review
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Predicting Adherence to Medications Using Health Psychology Theories: A Systematic Review of 20 Years of Empirical Research
Holmes, E. A., Morrison, V. L. & Hughes, D., 8 Dec 2014, In: Value in Health. 17, 8, p. 863-876Research output: Contribution to journal › Article › peer-review
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Predicting Language Outcomes in Bilingual Children with Down Syndrome
Ward, B. & Sanoudaki, E., 3 Jul 2024, In: Child Neuropsychology. 30, 5, p. 760-782 23 p.Research output: Contribution to journal › Article › peer-review
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Predicting Muscularity-Related Behavior, Emotions, and Cognitions in Men: The Role of Psychological Need Thwarting, Drive for Muscularity, and Mesomorphic Internalization
Edwards, C., Tod, D., Molnar, G. & Markland, D., 1 Sept 2016, In: Body Image. 18, September, p. 108-112Research output: Contribution to journal › Article › peer-review
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Predicting bedforms and primary current stratification in cohesive mixtures of mud and sand
Baas, J. H., Best, J. L. & Peakall, J., Jan 2016, In: Journal of the Geological Society. 173, 1, p. 12-45Research output: Contribution to journal › Article › peer-review
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Predicting caregiver gains: A longitudinal study
Morrison, V. L., Parveen, S. & Morrison, V., 1 Nov 2012, In: British Journal of Health Psychology. 17, 4, p. 711-723Research output: Contribution to journal › Article › peer-review
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Predicting diurnal outdoor performance and degradation of organic photovoltaics via machine learning; relating degradation to outdoor stress conditions
David, T., Soares, G., Bristow, N., Bagnis, D. & Kettle, J., Dec 2021, In: Progress in Photovoltaics. 29, 12, p. 1274-1284Research output: Contribution to journal › Article › peer-review
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Predicting function from sequence in a large multifunctional toxin family
Malhotra, A., Creer, S., Harris, J. B., Stöcklin, R., Favereau, P. & Thorpe, R. S., 3 Jul 2013, In: Toxicon. 72, p. 113-125Research output: Contribution to journal › Article › peer-review
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Predicting impacts of climate-induced range expansion: an experimental framework and a test involving key grazers on temperate rocky shores.
Firth, L. B., Crowe, T. P., Moore, P., Thompson, R. C. & Hawkins, S. J., 1 Jun 2009, In: Global Change Biology. 15, 6, p. 1413-1422Research output: Contribution to journal › Article › peer-review
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Predicting leaf traits of temperate broadleaf deciduous trees from hyperspectral reflectance: can a general model be applied across a growing season?
Chen, L., Zhang, Y., Nunes, M. H., Stoddart, J., Khoury, S., Chan, A. H. Y. & Coomes, D. A., 1 Feb 2022, In: Remote Sensing of Environment. 112767.Research output: Contribution to journal › Article › peer-review
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Predicting others’ actions via grasp and gaze: Evidence for distinct brain networks
Ramsey, R., Cross, E. S. & Hamilton, A., 1 Jul 2012, In: Psychological Research. 76, 4, p. 494-502Research output: Contribution to journal › Article › peer-review
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Predicting point-light actions in real-time.
Graf, M., Reitzner, B., Corves, C., Casile, A., Giese, M. A. & Prinz, W., 1 May 2007, In: Neuroimage. 36, Supplement 2, p. T22-T32Research output: Contribution to journal › Article › peer-review
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Predicting postdischarge opiate abstinence from admission measures of motivation and confidence.
Murphy, P. N., Bentall, R. P., Ryley, L. D. & Ralley, R., 1 Jun 2003, In: Psychology of Addictive Behaviors. 17, 2, p. 167-170Research output: Contribution to journal › Article › peer-review
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Predicting potential spawning areas of European bass, Dicentrarchus labrax, in the Irish and Celtic Seas
Lincoln, H., Robins, P., Wilmes, S-B., Pérez-Mayol, S., Moore, A., Simpson, S., Goward Brown, A., Heney, C., Malham, S., Morales-Nin, B., Hold, N. & McCarthy, I., 1 Feb 2024, In: Fisheries Research. 270, 106884.Research output: Contribution to journal › Article › peer-review
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Predicting species response to disturbance from size class distributions of adults and saplings in a Jamaican tropical dry forest.
McLaren, K. P., McDonald, M. A., Hall, J. B. & Healey, J. R., 1 Nov 2005, In: Plant Ecology. 181, 1, p. 69-84Research output: Contribution to journal › Article › peer-review
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Predicting speed at traffic lights-the problem with static assessments of frailty
Subbe, C. P. & Jones, S., 14 Jan 2015, In: Age and Ageing. 44, 2, p. 180-181Research output: Contribution to journal › Article › peer-review
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Predicting suitability of cockle Austrovenus stutchburyi restoration sites using hydrodynamic models of larval dispersal
Lundquist, C. J., Oldman, J. W. & Lewis, M. J., 6 Mar 2009, In: New Zealand Journal of Marine and Freshwater Research. 43, 3, p. 735-748Research output: Contribution to journal › Article › peer-review
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Predicting suitable habitat for the cold-water coral Lophelia pertusa (Scleractinia)
Davies, A., Wisshak, M., Orr, J. C. & Roberts, J. M., Aug 2008, In: Deep Sea Research Part I: Oceanographic Research Papers. 55, 8, p. 1048-1062Research output: Contribution to journal › Article › peer-review
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Predicting the dispersal of SARS-CoV-2 RNA from the wastewater treatment plant to the coast
Robins, P., Dickson, N., Kevill, J., Malham, S., Singer, A., Quilliam, R. & Jones, D. L., Sept 2022, In: Heliyon. 8, 9, E10547.Research output: Contribution to journal › Article › peer-review
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Predicting the dispersal of wild Pacific oysters Crassostrea gigas (Thunberg, 1793) from an existing frontier population—a numerical study
Robins, P., King, J., Jenkins, S. & Tita, A., 2017, In: Aquatic Invasions. 12, 2, p. 117-131Research output: Contribution to journal › Article › peer-review
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Predicting the distribution of a portunid crab in Patagonian coastal waters
de la Barra, P., Svendsen, G., Romero, M. A., Avaca, M. S. & Narvarte, M., 19 Mar 2020, In: Marine Ecology Progress Series. 638, p. 95-105Research output: Contribution to journal › Article › peer-review
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Predicting the distribution of vulnerable marine ecosystems in the deep sea using presence-background models
Vierod, A. D., Guinotte, J. M. & Davies, A. J., Jan 2014, In: Deep Sea Research Part II: Topical Studies in Oceanography. 99, p. 6-18Research output: Contribution to journal › Article › peer-review
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Predicting the effects of area closures and fishing effort restrictions on the production, biomass, and species richness of benthic invertebrate communities
Hiddink, J. G., Hutton, T., Jennings, S. & Kaiser, M. J., 1 Jun 2006, In: ICES Journal of Marine Science. 63, 5, p. 822-830Research output: Contribution to journal › Article › peer-review