Results 161 to 170 of about 663,545 (232)

Memristive Physical Reservoir Computing

open access: yesAdvanced Science, EarlyView.
Memristors’ nonlinear dynamics and input‐dependent memory effects make them ideal candidates for high‐performance physical reservoir computing (RC). Based on their conductance modulation, memristors can be classified as electronic or optoelectronic types.
Dian Jiao   +9 more
wiley   +1 more source

Complex excitability and "flipping" of granule cells: An experimental and computational study. [PDF]

open access: yesPLoS One
Danielewicz J   +5 more
europepmc   +1 more source

SpaMode: A Broadly Applicable Framework for Deciphering Spatial Multi‐Omics Using Multimodal Mixture of Disentangled Experts

open access: yesAdvanced Science, EarlyView.
SpaMode introduces a versatile framework for spatial multi‐omics integration across vertical, horizontal, and mosaic scenarios. By disentangling modality‐invariant and variant features through a mixture‐of‐experts mechanism, it adaptively reconfigures spatially heterogeneous signals.
Xubin Zheng   +6 more
wiley   +1 more source

Sticky Yet Slippery: Molecular Ordering Reconciles Bubble‐Surface Affinity With Ultralow Friction at the Nanoscale

open access: yesAdvanced Science, EarlyView.
By engineering the molecular order and thickness of PDMS layers, we reconcile the stickiness and slipperiness during bubble transport. AFM measurements and MD simulations further reveal how these nanoscale architectures tune hydrophobic interaction FHB and friction force f.
Shishuang Zhang   +7 more
wiley   +1 more source

Advanced Multiscale Modeling for Revealing Anomalous Fluid Transport Induced by Confinement Interfacial Layer Reconstruction in Sub‐10 nm Space

open access: yesAdvanced Science, EarlyView.
Integrating experimental insights with molecular dynamics simulations, we establish an advanced mathematical model for fluids confined in sub‐10‐nm channels, enabling quantitative prediction of interfacial layer thickness and viscosity by accounting for channel material, temperature, and fluid properties.
Xiang Zhang   +3 more
wiley   +1 more source

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

open access: yesAdvanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu   +5 more
wiley   +1 more source

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