Cutaneous manifestations of systemic methotrexate toxicity

Autor: Shivani Jain, MPhil, MSc, Hunter J. Pyle, MD, Jessica C. Evans, MS, Whitney Gao, MD, Melissa M. Mauskar, MD

Publikováno v: JAAD International, Vol 15, Iss , Pp 179-181 (2024)

Externí odkaz: https://doaj.org/article/7fb8d6b934604dc8ae474fdbc1500cac

Edematous pink plaque in a patient on immunosuppression

Autor: Mehvish Khan, BS, Hunter J. Pyle, BBA, MD, Travis W. Vandergriff, MD, Cristina Thomas, MD

Publikováno v: JAAD Case Reports, Vol 39, Iss , Pp 158-160 (2023)

Externí odkaz: https://doaj.org/article/d725b1c9f8594398ba9b7c24577fcc97

Facility level measurement of offshore oil and gas installations from a medium-sized airborne platform: method development for quantification and source identification of methane emissions

Autor: J. L. France, P. Bateson, P. Dominutti, G. Allen, S. Andrews, S. Bauguitte, M. Coleman, T. Lachlan-Cope, R. E. Fisher, L. Huang, A. E. Jones, J. Lee, D. Lowry, J. Pitt, R. Purvis, J. Pyle, J. Shaw, N. Warwick, A. Weiss, S. Wilde, J. Witherstone, S. Young

Publikováno v: Atmospheric Measurement Techniques, Vol 14, Pp 71-88 (2021)

Emissions of methane (CH4) from offshore oil and gas installations are poorly ground-truthed, and quantification relies heavily on the use of emission factors and activity data. As part of the United Nations Climate & Clean Air Coalition (UN CCAC) ob

Externí odkaz: https://doaj.org/article/33f53815977f45be9919dee2bc7abba0

Interpretable and Explainable Machine Learning for Ultrasonic Defect Sizing

Autor: Richard J. Pyle, Robert R. Hughes, Paul D. Wilcox

Publikováno v: Pyle, R, Hughes, R R & Wilcox, P D 2023, ' Interpretable and Explainable Machine Learning for Ultrasonic Defect Sizing ', IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 70, no. 4, pp. 277-290 . https://doi.org/10.1109/TUFFC.2023.3248968

Despite its popularity in literature, there are few examples of machine learning (ML) being used for industrial nondestructive evaluation (NDE) applications. A significant barrier is the ‘black box’ nature of most ML algorithms. This paper aims t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5a459d6c1e32da7fb0536b0ab1f4dcf
https://doi.org/10.1109/tuffc.2023.3248968

Quasi-Newton methods for atmospheric chemistry simulations: implementation in UKCA UM vn10.8

Autor: E. Esentürk, N. L. Abraham, S. Archer-Nicholls, C. Mitsakou, P. Griffiths, A. Archibald, J. Pyle

Publikováno v: Geoscientific Model Development, Vol 11, Pp 3089-3108 (2018)

A key and expensive part of coupled atmospheric chemistry–climate model simulations is the integration of gas-phase chemistry, which involves dozens of species and hundreds of reactions. These species and reactions form a highly coupled network

Externí odkaz: https://doaj.org/article/8c13dc1378e840ffa34676f6f7dd400d