Zobrazeno 1 - 10
of 46
pro vyhledávání: '"A Brett Roberts"'
Autor:
Madeline Behr, Layla Alizadeh, Lyndsey Buckner-Baiamonte, Brett Roberts, Andrew B Sholl, J Quincy Brown
Publikováno v:
PLoS ONE, Vol 19, Iss 5, p e0302600 (2024)
Breast cancer is the second most common cancer diagnosed in women in the US with almost 280,000 new cases anticipated in 2023. Currently, on-site pathology for location guidance is not available during the collection of breast biopsies or during surg
Externí odkaz:
https://doaj.org/article/d375b23990ec4e15895786c04cf1d2cc
Publikováno v:
Journal of Clinical and Translational Science, Vol 7, Pp 79-79 (2023)
OBJECTIVES/GOALS: In this study, the ability of a pathologist to detect malignancy on digital pseudo-H&E slides obtained via structured illumination microscopy (SIM) imaging of fresh diagnostic breast biopsies was assessed. The speed of imaging and p
Externí odkaz:
https://doaj.org/article/ab450bdddb9842e990aede584eaaff23
Autor:
Brett Roberts, Adam J. Clark, Israel L. Jirak, Burkely T. Gallo, Caroline Bain, David L. A. Flack, James Warner, Craig S. Schwartz, Larissa J. Reames
Publikováno v:
Weather and Forecasting. 38:99-123
As part of NOAA’s Hazardous Weather Testbed Spring Forecasting Experiment (SFE) in 2020, an international collaboration yielded a set of real-time convection-allowing model (CAM) forecasts over the contiguous United States in which the model config
Autor:
Adam J. Clark, Israel L. Jirak, Burkely T. Gallo, Brett Roberts, Kent H. Knopfmeier, Jake Vancil, David Jahn, Makenzie Krocak, Christopher D. Karstens, Eric D. Loken, Nathan A. Dahl, David Harrison, David Imy, Andrew R. Wade, Jeffrey M. Milne, Kimberly A. Hoogewind, Montgomery Flora, Joshua Martin, Brian C. Matilla, Joseph C. Picca, Corey K. Potvin, Patrick S. Skinner, Patrick Burke
Publikováno v:
Bulletin of the American Meteorological Society. 104:E456-E458
Autor:
Corey K. Potvin, Burkely T. Gallo, Anthony E. Reinhart, Brett Roberts, Patrick S. Skinner, Ryan A. Sobash, Katie A. Wilson, Kelsey C. Britt, Chris Broyles, Montgomery L. Flora, William J. S. Miller, Clarice N. Satrio
Publikováno v:
Journal of Atmospheric and Oceanic Technology. 39:999-1013
Thunderstorm mode strongly impacts the likelihood and predictability of tornadoes and other hazards, and thus is of great interest to severe weather forecasters and researchers. It is often impossible for a forecaster to manually classify all the sto
Publikováno v:
Water, Vol 12, Iss 10, p 2860 (2020)
Probabilistic streamflow forecasts using precipitation derived from ensemble-based Probabilistic Quantitative Precipitation Forecasts (PQPFs) are examined. The PQPFs provide rainfall amounts associated with probabilities of exceedance for all grid po
Externí odkaz:
https://doaj.org/article/43456671101a4992a35da0b4157c47dd
Autor:
Adam J. Clark, Israel L. Jirak, Burkely T. Gallo, Kent H. Knopfmeier, Brett Roberts, Makenzie Krocak, Jake Vancil, Kimberly A. Hoogewind, Nathan A. Dahl, Eric D. Loken, David Jahn, David Harrison, David Imy, Patrick Burke, Louis J. Wicker, Patrick S. Skinner, Pamela L. Heinselman, Patrick Marsh, Katie A. Wilson, Andrew R. Dean, Gerald J. Creager, Thomas A. Jones, Jidong Gao, Yunheng Wang, Montgomery Flora, Corey K. Potvin, Christopher A. Kerr, Nusrat Yussouf, Joshua Martin, Jorge Guerra, Brian C. Matilla, Thomas J. Galarneau
Publikováno v:
Bulletin of the American Meteorological Society. 103:E1114-E1116
Autor:
Jamie K. Wolff, Burkely T. Gallo, Tim Supinie, Yunheng Wang, Chunxi Zhang, Israel L. Jirak, Linjiong Zhou, Adam J. Clark, Ming Xue, Lindsay R. Blank, Lucas M. Harris, Curtis R. Alexander, Brett Roberts
Publikováno v:
Weather and Forecasting. 36:3-19
Verification methods for convection-allowing models (CAMs) should consider the finescale spatial and temporal detail provided by CAMs, and including both neighborhood and object-based methods can account for displaced features that may still provide
Autor:
Brett Roberts, David C. Dowell, Burkely T. Gallo, Adam J. Clark, Yongming Wang, Israel L. Jirak, Xuguang Wang
Publikováno v:
Weather and Forecasting. 35:2293-2316
The High Resolution Ensemble Forecast v2.1 (HREFv2.1), an operational convection-allowing model (CAM) ensemble, is an “ensemble of opportunity” wherein forecasts from several independently designed deterministic CAMs are aggregated and postproces
Autor:
Andrew R. Dean, William Miller, Pamela L. Heinselman, Kimberly A. Hoogewind, Katie A. Wilson, Montgomery L. Flora, Joshua Martin, Jake Vancil, Christopher A. Kerr, Adam J. Clark, Jidong Gao, Scott R. Dembek, Brian Matilla, David Harrison, Brett Roberts, Yunheng Wang, Nusrat Yussouf, Patrick S. Skinner, Nathan A. Dahl, Gerald J. Creager, Eric D. Loken, Burkely T. Gallo, Michael C. Coniglio, Kent H. Knopfmeier, David A. Imy, Louis J. Wicker, David E. Jahn, Jorge E. Guerra, Makenzie J. Krocak, Israel L. Jirak, Thomas A. Jones
Publikováno v:
Bulletin of the American Meteorological Society. 102:E814-E816