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Showing 109 to 110 of 110 entries
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Physics-informed machine learning: case studies for weather and climate modelling.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences

Kashinath K, Mustafa M, Albert A, Wu JL, Jiang C, Esmaeilzadeh S, Azizzadenesheli K, Wang R, Chattopadhyay A, Singh A, Manepalli A, Chirila D, Yu R, Walters R, White B, Xiao H, Tchelepi HA, Marcus P, Anandkumar A, Hassanzadeh P, Prabhat.
PMID: 33583262
Philos Trans A Math Phys Eng Sci. 2021 Apr 05;379(2194):20200093. doi: 10.1098/rsta.2020.0093. Epub 2021 Feb 15.

Machine learning (ML) provides novel and powerful ways of accurately and efficiently recognizing complex patterns, emulating nonlinear dynamics, and predicting the spatio-temporal evolution of weather and climate processes. Off-the-shelf ML models, however, do not necessarily obey the fundamental governing...

The Physico-Chemical Properties and Exploratory Real-Time Cell Analysis of Hydroxyapatite Nanopowders Substituted with Ce, Mg, Sr, and Zn (0.5-5 at.%).

Materials (Basel, Switzerland)

Chirică IM, Enciu AM, Tite T, Dudău M, Albulescu L, Iconaru SL, Predoi D, Pasuk I, Enculescu M, Radu C, Mihalcea CG, Popa AC, Rusu N, Niţă S, Tănase C, Stan GE.
PMID: 34300727
Materials (Basel). 2021 Jul 08;14(14). doi: 10.3390/ma14143808.

Cation-substituted hydroxyapatite (HA), standalone or as a composite (blended with polymers or metals), is currently regarded as a noteworthy candidate material for bone repair/regeneration either in the form of powders, porous scaffolds or coatings for endo-osseous dental and orthopaedic...

Showing 109 to 110 of 110 entries