Results 181 to 190 of about 117,066,488 (245)

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

open access: yesAdvanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen   +7 more
wiley   +1 more source

Single‐Cell RNA Editing Identifies T Cell ADAR1 as a Key Regulator of Immune Exhaustion and Anti‐PD‐1 Resistance in Colorectal Cancer

open access: yesAdvanced Science, EarlyView.
Single‐cell RNA editing analysis identifies ADAR1 as a regulator of dysfunctional T cell states in colorectal cancer. Elevated ADAR1 activity promotes T cell exhaustion and impairs antitumor immunity partly through TGF‐β‐SMAD signaling, contributing to anti‐PD‐1 resistance and highlighting T cell ADAR1 as a potential therapeutic target and biomarker ...
Da Kang   +10 more
wiley   +1 more source

Computerized adaptive testing of neurocognitive deficits in psychosis. [PDF]

open access: yesPsychol Assess
Thomas ML   +9 more
europepmc   +1 more source

Brain‐Computer Interface Training Fosters Perceptual Skills to Detect Errors

open access: yesAdvanced Science, EarlyView.
Accurate perception of visuomotor errors underpins motor precision and learning, yet conventional behavioral training fails to improve sensitivity to subtle errors. Real‐time EEG‐based brain‐computer interface feedback targeting the error positivity component enhances perceptual learning of small errors.
Deland H. Liu   +4 more
wiley   +1 more source

Exploring quantum Heider balance theory. [PDF]

open access: yesSci Rep
Kiani A, Fazeli SM, Jafari GR.
europepmc   +1 more source

Condition‐Associated Pattern Extraction and Recovery From Multi‐Condition Single‐Cell RNA‐seq Data With CAPER

open access: yesAdvanced Science, EarlyView.
Decoupling biological signals from unwanted variation in multi‑condition single‑cell RNA sequencing data remains challenging. CAPER disentangles condition‑associated biological effects from sample heterogeneity through matrix factorization, producing interpretable latent factors and a batch‑corrected expression matrix.
Ye Li   +6 more
wiley   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

open access: yesAdvanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai   +3 more
wiley   +1 more source

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