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pro vyhledávání: '"H. Shau"'
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Advancing material property prediction: using physics-informed machine learning models for viscosity
Autor:
Alex K. Chew, Matthew Sender, Zachary Kaplan, Anand Chandrasekaran, Jackson Chief Elk, Andrea R. Browning, H. Shaun Kwak, Mathew D. Halls, Mohammad Atif Faiz Afzal
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-14 (2024)
Abstract In materials science, accurately computing properties like viscosity, melting point, and glass transition temperatures solely through physics-based models is challenging. Data-driven machine learning (ML) also poses challenges in constructin
Externí odkaz:
https://doaj.org/article/d431eabc630d4e9b849181689578969e
Publikováno v:
Journal of Asian Earth Sciences. 145:605-612
Clinoenstatite is an uncommon mineral, and has been documented in Sulu ultrahigh-pressure (UHP) garnet pyroxenite. However, clinoenstatite (CLEN) was rarely reported in the previous studies of ophiolitic mantle peridotites. The studied ophiolitic per
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1dfc45f0a718f31b7d3b471dfc5abb16
https://doi.org/10.1016/j.jseaes.2017.07.003
https://doi.org/10.1016/j.jseaes.2017.07.003
Publikováno v:
Interleukin-2 and Killer Cells in Cancer ISBN: 9781351073790
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be9c56dceab7af649489c0003eb34910
https://doi.org/10.1201/9781351073790-8
https://doi.org/10.1201/9781351073790-8
Autor:
Yen H. Shau, Hwo Shuenn Sheu, Ping Hua Shao, Kai Yin Chiang, Kai Shuan Shea, Ming Kuang Wang, Hua Wen Chen, Yue-Ming Chen, Tsung Ming Tsao, Shung Yao Zhuang
Publikováno v:
Journal of Soils and Sediments. 12:1054-1065
Information on the physicochemical properties, mineral species and micromorphology of lateritic soils and gravel soil layers in paleo-environmental soil profile is severely lacking. Red soil profile of the Taoyuan terrace was employed to demonstrate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc26974e3acb858be7d5e8cadc209332
https://doi.org/10.1007/s11368-012-0495-z
https://doi.org/10.1007/s11368-012-0495-z
Publikováno v:
American Mineralogist. 87:867-874
Transmission electron microscopy (TEM) reveals that some enstatites from garnet-pyroxenites in the Chinese Dabie-Sulu ultrahigh-pressure (UHP) terrane consist of intimate intergrowths of orthoenstatite (OREN) and clinoenstatite (CLEN), and some grain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a601c021f88bb3e61317cf7bc8617ed7
https://doi.org/10.2138/am-2002-0709
https://doi.org/10.2138/am-2002-0709
Autor:
R C Moen, Donald B. Kohn, William H. McBride, A R Miller, G J Dougherty, M J Walker, Roland K. Chiu, H Shau, S M Dubinett, J D Thacker
Publikováno v:
Blood, 82(12), 3686-94. AMER SOC HEMATOLOGY
Two human melanoma cell lines were transduced with the human interleukin (IL)-7 and IL-2 genes using retroviral-mediated gene transfer. Stable, high-level cytokine expression was achieved. The in vitro growth of transduced tumors was unaltered. Neith
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25d5c61041a071e64059019f3da94344
https://doi.org/10.1182/blood.v82.12.3686.3686
https://doi.org/10.1182/blood.v82.12.3686.3686
Publikováno v:
Immunopharmacology and Immunotoxicology. 15:525-538
Recent studies combining chemotherapeutic agents with various biological response modifiers for the treatment of cancer have shown promising results. Cyclophosphamide (Cy) is the most widely used alkylating agent and a major constituent of combinatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc2e036c67ddcfafa25b06774d493c84
https://doi.org/10.3109/08923979309019729
https://doi.org/10.3109/08923979309019729
Autor:
Hadi Abroshan, H. Shaun Kwak, Yuling An, Christopher Brown, Anand Chandrasekaran, Paul Winget, Mathew D. Halls
Publikováno v:
Frontiers in Chemistry, Vol 9 (2022)
Data-driven methods are receiving increasing attention to accelerate materials design and discovery for organic light-emitting diodes (OLEDs). Machine learning (ML) has enabled high-throughput screening of materials properties to suggest new candidat
Externí odkaz:
https://doaj.org/article/d4c36d13675c4d7dadb86e2818ce9771