Results 91 to 100 of about 198,332 (267)

Multilayer Self‐Limiting Electrospray Deposition via Stepped Voltage Bias

Advanced Engineering Materials, EarlyView.
Self‐limiting electrospray deposition (SLED) uses a high voltage to generate and deposit a charged payload on a target surface. The coating retains its charge, repelling newly arriving material. SLED thickness can be decreased by applying a secondary bias to the target.
Madhuri Deb, S. Rahman Pejman, Alexander Jakimowicz, Jonathan P. Singer   +3 more
wiley   +1 more source

Understanding Alzheimer's disease in the context of aging: Findings from applications of stochastic process models to the Health and Retirement Study. [PDF]

Mech Ageing Dev, 2023
Arbeev KG, Bagley O, Yashkin AP, Duan H, Akushevich I, Ukraintseva SV, Yashin AI.   +6 more
europepmc   +1 more source

The Onset of a Boiling Crisis as a Stochastic Three-Dimensional Off-Lattice Percolation Transition

Fluids
Boiling crises are complex stochastic processes that are influenced by the physical phenomena of heat transfer and evaporation, as well as the shape and roughness of the boiling surface.
Oleg Penyazkov, Pavel Grinchuk
doaj   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Rethinking statistical learning as a continuous dynamic stochastic process, from the motor systems perspective. [PDF]

Front Neurosci, 2022
Vaskevich A, Torres EB.
europepmc   +1 more source

Graph-Conditioned Stochastic Modeling of Twitter Information Cascades with Dual-Head Transformers for Early Virality Prediction

Mathematics
Information cascades in online social networks arise from stochastic interactions among user behavior, temporal activation, and graph-structured exposure.
Bowen Dong, Xinyu Zhang, Chaoya Yan, Weiyan Zhu, Lingmin Hou, Yifan Feng   +5 more
doaj   +1 more source

Intermediate Resistive State in Wafer‐Scale Vertical MoS2 Memristors Through Lateral Silver Filament Growth for Artificial Synapse Applications

Advanced Functional Materials, EarlyView.
In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa, Milan Buttberg, Ke Ran, Rana Walied Ahmad, Dennis Braun, Lukas Völkel, Jimin Lee, Sofía Cruces, Bart Macco, Bárbara Canto, Holger Lerch, Thorsten Wahlbrink, Holger Kalisch, Michael Heuken, Andrei Vescan, Joachim Mayer, Zhenxing Wang, Ilia Valov, Stephan Menzel, Max C. Lemme   +19 more
wiley   +1 more source

Mathematical model of the cell signaling pathway based on the extended Boolean network model with a stochastic process. [PDF]

BMC Bioinformatics, 2022
Kim M, Kim E.
europepmc   +1 more source

Qualitative Analysis and Numerical Simulations of γ-Hilfer Fractional Stochastic Dynamical Systems

Axioms
This study presents findings on the existence, uniqueness, averaging principle, and numerical solutions for fractional stochastic systems influenced by both Brownian motion and Poisson jumps within the pth-moment framework.
Muhammad Imran Liaqat, Ramy M. Hafez
doaj   +1 more source

Convergence of stochastic process with Markov switching [PDF]

Математичні Студії, 2012
It has been established sufficient conditions for the convergence of a multi-dimensional stochastic process in the case of dependence of the regression function on the environment, which is described by Markov switchings.
O. I. Kiykovska, Ya. M. Chabanyuk
doaj