Results 181 to 190 of about 3,169,064 (307)

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

Interactive Inductive Learning Service for Indirect Analysis of Study Subject Compatibility

open access: yes
Inductive learning enables to use machine procedures for the classification of objects of interest into predefined groups or classes. Study subjects of a study course may be viewed as a knowledge classification where each subject is relatively ...
Birzniece, Ilze, Kirikova, Mārīte
core  

WT1‐Targeted Oral Bifidobacterium longum Vaccine Enhances Checkpoint Blockade Efficacy in Pancreatic Cancer

open access: yesAdvanced Science, EarlyView.
Oral WT1‐targeted Bifidobacterium longum vaccine promotes WT1‐associated cellular immunity and enhances anti‐PD‐1/anti‐CTLA‐4 efficacy in pancreatic cancer. ABSTRACT Pancreatic ductal adenocarcinoma (PDAC) remains largely unresponsive to immune checkpoint inhibitors (ICI) due to its profoundly immunosuppressive tumor microenvironment.
Taiki Yamazaki   +7 more
wiley   +1 more source

Magnetoelectric Nanoparticle‐Based Wireless Brain–Computer Interface: Underlying Physics and Projected Technology Pathway

open access: yesAdvanced Science, EarlyView.
Magnetoelectric nanoparticles (MENPs) enable fully wireless, minutely invasive neuromodulation, and potentially neural recording, by converting magnetic into electric and, conversely, electric into magnetic fields, respectively, at high spatiotemporal resolution.
Elric Zhang   +14 more
wiley   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

open access: yesAdvanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin   +12 more
wiley   +1 more source

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