Results 131 to 140 of about 6,143,323 (339)

Selection Strategies for Flexible Pressure Sensor Electrode Materials Toward Ultrafast Response

Advanced Functional Materials, EarlyView.
This study reveals, for the first time, how the electrode–organic interface governs the temporal performance of flexible pressure sensors. By pairing high‐conductivity CVD PEDOT with commonly used metal electrodes, the authors demonstrate that interfacial energy alignment dictates microsecond‐scale response, providing a straightforward design strategy ...
Jinwook Baek, Yuxuan Zhang, Hyeondong Yang, Minyoung Kim, Pavlos P. Vlachos, Jeongok Choe, Bo‐Gyu Bok, Kejie Zhao, Han‐Wook Song, Min‐Seok Kim, Martin Byung‐Guk Jun, Sunghwan Lee   +11 more
wiley   +1 more source

Bayesian modeling of ChIP-chip data using latent variables [PDF]

, 2009
Mingqi Wu, Faming Liang, Yanan Tian
openalex   +1 more source

PRELIVE: A Framework for Predicting Lipid Nanoparticles In Vivo Efficacy and Reducing Reliance on Animal Testing

Advanced Functional Materials, EarlyView.
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy, Chuan‐En Lu, Kai Liu, Audrey Gallud   +3 more
wiley   +1 more source

MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus

Structural equation modeling : a multidisciplinary journal, 2018
M. Hallquist, J. Wiley
semanticscholar   +1 more source

A Class of Two-Timescale Stochastic EM Algorithms for Nonconvex Latent Variable Models [PDF]

, 2022
Belhal Karimi, Ping Li
openalex   +1 more source

Universal Electronic‐Structure Relationship Governing Intrinsic Magnetic Properties in Permanent Magnets

Advanced Functional Materials, EarlyView.
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley   +1 more source

Conductance‐Dependent Photoresponse in a Dynamic SrTiO3 Memristor for Biorealistic Computing

Advanced Functional Materials, EarlyView.
A nanoscale SrTiO3 memristor is shown to exhibit dynamic synaptic behavior through the interaction of local electrical and global optical signals. Its photoresponse depends quantitatively on the conductance state, which evolves and decays over tunable timescales, enabling ultralow‐power, biorealistic learning mechanisms for advanced in‐memory and ...
Christoph Weilenmann, Hanglin He, Marko Mladenović, Till Zellweger, Kevin Portner, Klemens Bauer, Guillaume Bellec, Mathieu Luisier, Alexandros Emboras   +8 more
wiley   +1 more source

Likelihood Inference for Factor Copula Models with Asymmetric Tail Dependence

Entropy
For multivariate non-Gaussian involving copulas, likelihood inference is dominated by the data in the middle, and fitted models might not be very good for joint tail inference, such as assessing the strength of tail dependence.
Harry Joe, Xiaoting Li
doaj   +1 more source

Intrinsic Nanopore‐Assisted SnP2S6 Memristors With Ti Ion Dynamics for Compact Logic‐In‐Memory Hardware

Advanced Functional Materials, EarlyView.
Tin hexathiophosphate memristors leverage intrinsic nanopores together with a guided filament formation strategy to regulate titanium ion motion and switching behavior. The devices support reliable nonvolatile memory and reconfigurable logic‐in‐memory, demonstrating 14 Boolean logic functions in a single cell.
Thaw Tint Te Tun, Sanchali Mitra, Hongxi Su, Jiali Huo, Haofei Zheng, Michel Bosman, Yee Sin Ang, Kah‐Wee Ang   +7 more
wiley   +1 more source

Probabilistic Distributional Semantics with Latent Variable Models

Computational Linguistics, 2021
Diarmuid Ó Séaghdha, Anna Korhonen
doaj   +1 more source