Results 191 to 200 of about 3,113,242 (314)

Bayesian uncertainty quantification for machine-learned models in physics

Nature Reviews Physics, 2022
Y. Gal, P. Koumoutsakos, François Lanusse, Gilles Louppe, C. Papadimitriou   +4 more
semanticscholar   +1 more source

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

Advanced Functional Materials, EarlyView.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva, Giulio Fatti, Emanuel Carlos, Guilherme Ferreira, Sumita Goswami, Suman Nandy, Luiz H. C. Mattoso, Elvira Fortunato, Caio G. Otoni, Rodrigo Martins   +9 more
wiley   +1 more source

Bayesian deep reinforcement learning for uncertainty quantification and adaptive support optimization in deep foundation pit engineering. [PDF]

Sci Rep
Gu W.
europepmc   +1 more source

Quantification of uncertainties in the parameters of a long-term energy model

, 1979
R.W. Peelle, Darryl J. Downing, D.J. Bjornstad   +2 more
openalex   +1 more source

Heterogeneous Cell Population Dynamics: Equation-Free Uncertainty Quantification Computations

, 2006
Katherine A. Bold, Yu Zou, Ioannis G. Kevrekidis, Michael A. Henson   +3 more
openalex   +2 more sources

Chapter 2 Quantifying Uncertainty and Sampling Quality in Biomolecular Simulations [PDF]

, 2009
Alan Grossfield, Daniel M. Zuckerman
openalex   +1 more source

Nanostructured Hydrogen‐Selective Palladium “Plug” Membranes Capable of Withstanding High Temperatures

Advanced Functional Materials, EarlyView.
A nanostructured palladium membrane is developed for high‐temperature hydrogen separation, comprising isolated, thermally‐stable palladium plugs embedded within nanopores of a porous support. The membrane withstands high temperatures (1000 K for 100 h) without structural failure, demonstrating exceptional robustness over conventional metal membranes ...
Lohyun Kim, Aaron H. Persad, Chun Man Chow, Randall Field, Rohit Karnik   +4 more
wiley   +1 more source

Conformal prediction for uncertainty quantification in dynamic biological systems. [PDF]

PLoS Comput Biol
Portela A, Banga JR, Matabuena M.
europepmc   +1 more source

MODEL VALIDATION AND UNCERTAINTY QUANTIFICATION.

, 2000
François Hemez, Scott W. Doebling
openalex   +1 more source

High‐Spatiotemporal‐Resolution Transparent Thermoelectric Temperature Sensor Arrays Reveal Temperature‐Dependent Windows for Reversible Photothermal Neuromodulation

Advanced Functional Materials, EarlyView.
Thermoelectric temperature sensors are developed that directly measure heat changes during optical‐based neural stimulation with millisecond precision. The sensors reveal the temperature windows for safe reversible neural modulation: 1.4–4.5 °C enables reversible neural inhibition, while temperatures above 6.1 °C cause permanent thermal damage.
Junhee Lee, Dongjo Yoon, Jungha Lee, Duhee Kim, Eunui Kim, Jong‐Hyeok Yoon, Hyuk‐Jun Kwon, Seungjun Chung, Yoonkey Nam, Hongki Kang   +9 more
wiley   +1 more source