Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Brian R. Hu"'
Autor:
Julie W. Cheng, Jonathan Maldonado, Ruth E. Belay, Daniel P. Srikureja, Naveenraj L. Solomon, Patrick Hogue, Matthew J. Selleck, Brian R. Hu
Publikováno v:
Urology Video Journal, Vol 9, Iss , Pp 100077- (2021)
Objective: To demonstrate a minimally-invasive method for excision of retrocrural masses. The patient was a 31-year-old male with mixed germ cell testicular cancer underwent left radical orchiectomy, chemotherapy, and open extraperitoneal retroperito
Externí odkaz:
https://doaj.org/article/009518dc0cb14aafb3ab71ef906a8cf3
Autor:
Julie W. Cheng, Hillary Wagner, Barbara C. Hernandez, Brian R. Hu, Edmund Y. Ko, Herbert C. Ruckle
Publikováno v:
Urology. 139:35-36
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d879c3044ef152b83489d75fa4ca648
https://doi.org/10.1016/j.urology.2019.11.077
https://doi.org/10.1016/j.urology.2019.11.077
Autor:
Lynne E. Stenzel, Brian R. Hudgens, Gary W. Page, Kristina K. Neuman, Amy L. Palkovic, Jennifer L. Erbes, Carleton R. Eyster, Bernadette A. Ramer, Douglas E. George
Publikováno v:
Ecosphere, Vol 14, Iss 7, Pp n/a-n/a (2023)
Abstract Managing for the effects of climate change on species whose populations are currently imperiled requires detailed knowledge of the relationship between their demographic rates and climate variables. We sought this information for the West Co
Externí odkaz:
https://doaj.org/article/ac907f58ee114bb780247fdab53df029
Publikováno v:
Geophysical Research Letters, Vol 50, Iss 8, Pp n/a-n/a (2023)
Abstract It is shown that a recently developed hybrid modeling approach that combines machine learning (ML) with an atmospheric global circulation model (AGCM) can serve as a basis for capturing atmospheric processes not captured by the AGCM. This po
Externí odkaz:
https://doaj.org/article/1e14606858b9495284e4878224d07ac2
Publikováno v:
Reviews in neurological diseases. 2(4)
Central nervous system (CNS) manifestations of Echinococcus and Schistosoma infections occur throughout the world, with incidence increasing in developed regions. A detailed literature review generated a current summary on epidemiology, parasitology,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::456cb5e8bdaa4a471a350f03241a23cc
https://pubmed.ncbi.nlm.nih.gov/16622395
https://pubmed.ncbi.nlm.nih.gov/16622395
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 14, Iss 3, Pp n/a-n/a (2022)
Abstract This paper describes an implementation of the combined hybrid‐parallel prediction (CHyPP) approach of Wikner et al. (2020), https://doi.org/10.1063/5.0005541 on a low‐resolution atmospheric global circulation model (AGCM). The CHyPP appr
Externí odkaz:
https://doaj.org/article/2f149eae2cb04ebd9c87e534fa378e53
Publikováno v:
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 67, Iss 0, Pp 1-7 (2015)
Idealised perfect model experiments suggest that performing data assimilation on a ‘composite’ state vector, constructed from global and limited-area model states, can be beneficial to both model states. Here, an illustrative scheme is implemente
Externí odkaz:
https://doaj.org/article/5497fbb3c5914f089b8a99b7160e1189
Publikováno v:
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 67, Iss 0, Pp 1-9 (2015)
Ensemble data assimilation methods are potentially attractive because they provide a computationally affordable (and computationally parallel) means of obtaining flow-dependent background-error statistics. However, a limitation of these methods is th
Externí odkaz:
https://doaj.org/article/efd40924d1b14970aff23fc2c622943d
Autor:
Matthew Kretschmer, Brian R. Hunt, Edward Ott, Craig H. Bishop, Sabrina Rainwater, Istvan Szunyogh
Publikováno v:
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 67, Iss 0, Pp 1-17 (2015)
Limited-area models (LAMs) allow high-resolution forecasts to be made for geographic regions of interest when resources are limited. Typically, boundary conditions for these models are provided through one-way boundary coupling from a coarser resolut
Externí odkaz:
https://doaj.org/article/0be95b4f76ee416d971208e8b70c03eb
Autor:
Sabrina Rainwater, Brian R. Hunt
Publikováno v:
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 65, Iss 0, Pp 1-14 (2013)
Ensemble data assimilation typically evolves an ensemble of model states whose spread is intended to represent the algorithm's uncertainty about the state of the physical system that produces the data. The analysis phase treats the forecast ensemble
Externí odkaz:
https://doaj.org/article/6c92cd5e23a94dd7a828b12e0aeaa0ca