Results 201 to 210 of about 2,026,688 (333)

TYTAN: Taylor-series based Non-Linear Activation Engine for Deep Learning Accelerators

open access: green
Soham Pramanik   +5 more
openalex   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

open access: yesCarbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su   +4 more
wiley   +1 more source

Shedding Light on Synthetic Autocatalysis: From Conventional Closed‐Shell Chemistries to Overlooked Open‐Shell Occurrences

open access: yesChemistry – A European Journal, EarlyView.
Why add another catalyst when the product itself holds the power to catalyze its own formation? Autocatalysis in synthetic chemistry enhances reaction efficiency and uncovers novel catalytic behavior across both closed‐shell and open‐shell systems, expanding reactivity and enabling innovative design strategies.
Jaspreet Kaur, Joshua P. Barham
wiley   +1 more source

Defining biceps chondromalacia: An arthroscopic descriptive study. [PDF]

open access: yesShoulder Elbow
Bryan MR   +5 more
europepmc   +1 more source

Quantitative NMR Spectroscopy under High Hydrostatic Pressure

open access: yesChemistry – A European Journal, EarlyView.
Solvent compression leads to an increase in integrals and signal heights characterizing (bio)molecules that are studied using high‐pressure NMR spectroscopy. So far, solvent compression has not been considered when quantitative high‐pressure NMR spectroscopy was used to characterize (bio)molecules.
Frederic Berner, Michael Kovermann
wiley   +1 more source

Synapse types are spatially associated with regional hemodynamics in the mouse brain. [PDF]

open access: yesPLoS Biol
Hansen JY   +7 more
europepmc   +1 more source

On subset least squares estimation and prediction in vector autoregressive models with exogenous variables

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract We establish the consistency and the asymptotic distribution of the least squares estimators of the coefficients of a subset vector autoregressive process with exogenous variables (VARX). Using a martingale central limit theorem, we derive the asymptotic normal distribution of the estimators. Diagnostic checking is discussed using kernel‐based
Pierre Duchesne   +2 more
wiley   +1 more source

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