Results 191 to 200 of about 58,900 (264)

Sub‐Terahertz Memristor Switches Using MoS2 by Liquid–Liquid Interface Assembly

open access: yesAdvanced Science, EarlyView.
This work introduces application‐ready sub‐terahertz memristor switches fabricated from electrochemically exfoliated MoS2 nanosheets assembled at a liquid–liquid interface. The devices exhibit robust unipolar resistive switching, low insertion loss, and high isolation across 10–110 GHz.
Tomás Mingates   +15 more
wiley   +1 more source

ProSiteHunter: A Unified Framework for Sequence‐Based Prediction of Protein‐Nucleic Acid and Protein‐Protein Binding Sites

open access: yesAdvanced Science, EarlyView.
This study proposed a unified sequence‐based framework for protein binding site prediction, which adopted a tri‐track semantic multi‐source feature fusion strategy to effectively capture diverse macromolecular interaction sites and further improved the accuracy of antibody‐antigen interaction prediction.
Dongliang Hou   +8 more
wiley   +1 more source

The Wine of Circe

open access: yesEmerging Infectious Diseases
Terence Chorba
doaj   +1 more source

A Foundation Model Based CT Biomarker for Non‐Invasive Prediction of Response to Neoadjuvant Immunochemotherapy in Non‐Small Cell Lung Cancer

open access: yesAdvanced Science, EarlyView.
This study introduces a foundation model‐based biomarker for risk stratification of pathological response in non‐small cell lung cancer. A Vision Mamba super‐resolution model standardizes heterogeneous CT images. A multi‐task Swin Transformer then fine‐tunes a pre‐trained lung foundation model to jointly optimize tumor segmentation and response ...
Yanglan Xu   +10 more
wiley   +1 more source

A history of addiction through the six editions of Kandel's <i>Principles of Neural Science</i> and their scientific context. [PDF]

open access: yesFront Behav Neurosci
Santiago-Martinez P   +5 more
europepmc   +1 more source

Accurately Deciphering Tissue Heterogeneity From Spatial Multi‐Modal and Multi‐Omics With STransformer

open access: yesAdvanced Science, EarlyView.
STransformer is a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short‐range cellular interactions and tissue‐wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity.
Xingyi Li   +9 more
wiley   +1 more source

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