Results 251 to 260 of about 1,529,309 (330)

Reflected fractional Brownian motion in one and higher dimensions. [PDF]

open access: yesPhys Rev E, 2020
Vojta T   +5 more
europepmc   +1 more source

Real‐time cardiac cine MRI: A comparison of a diffusion probabilistic model with alternative state‐of‐the‐art image reconstruction techniques for undersampled spiral acquisitions

open access: yesMagnetic Resonance in Medicine, EarlyView.
Abstract Purpose Electrocardiogram (ECG)‐gated cine imaging in breath‐hold enables high‐quality diagnostics in most patients but can be compromised by arrhythmia and inability to hold breath. Real‐time cardiac MRI offers faster and robust exams without these limitations.
Oliver Schad   +8 more
wiley   +1 more source

Electrical Behavior of Green‐Synthesized Nano Silver Particles Embedded in Polyurethane: Numerical and Experimental Studies

open access: yesPolymer Composites, EarlyView.
AgNPs were synthesized using Urtica dioica. AgNPs‐PU was prepared using a solution mixing method followed by spin coating. Microscopy Optical image of AgNPs‐PU composite with different concentrations of AgNPs. Electrical behaviour versus pressure. ABSTRACT This study explores the electrical properties of a nanocomposite composed of green‐synthesized ...
Saeid Mehvari   +6 more
wiley   +1 more source

A stochastic differential equation framework for gravity wave parametrisation with testing in an idealised setting

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
Parametrisations of unresolved gravity waves used in general circulation models can be made more computationally efficient by introducing a stochastic component to the forcing. Additionally, it is believed that intermittency associated with a stochastic parametrisation could be tuned to resemble the intermittency of observed gravity wave sources to ...
K. Xie, M. Ewetola, J. G. Esler
wiley   +1 more source

Quantum‐Noise‐Driven Generative Diffusion Models

open access: yesAdvanced Quantum Technologies, EarlyView.
Diffusion Models (DMs) are today a very popular class of generative models for Machine Learning (ML), using a noisy dynamics to learn an unknown density probability of a finite set of samples in order to generate new synthetic data. This study proposes a method to generalize them into the quantum domain by introducing and investigating what are termed ...
Marco Parigi   +2 more
wiley   +1 more source

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