Results 171 to 180 of about 656,338 (284)

ESCRT‐Mimetic Nanodegrader Targets STING for Anti‐Inflammatory Therapy

open access: yesAdvanced Science, EarlyView.
A nanoplatform‐enabled targeted protein degradation strategy is presented to regulate aberrant STING signaling. STING‐ATTEC induces selective autophagic degradation of STING via formation of a STING–ATTEC–LC3 ternary complex, while the cationic FA‐LNP+ system enhances LC3 generation and targeted delivery. Together, this synergistic approach efficiently
Fuyuan Zhou   +9 more
wiley   +1 more source

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

INB3P: A Multi‐Modal and Interpretable Co‐Attention Framework Integrating Property‐Aware Explanations and Memory‐Bank Contrastive Fusion for Blood–Brain Barrier Penetrating Peptide Discovery

open access: yesAdvanced Science, EarlyView.
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv   +11 more
wiley   +1 more source

Microstructure‐Resolved Modeling to Predicting and Regulating Lithium Plating‐Stripping Dynamics on Graphite Electrodes

open access: yesAdvanced Science, EarlyView.
ABSTRACT The lithium plating reaction in graphite electrodes acts as a root cause for the accelerated degradation and the internal short circuits in lithium‐ion batteries. Here, an electrochemical model based on multi‐scale microstructural images was established to identify lithium plating‐stripping processes, thereby supporting the predictive outcomes
Heng Huang   +9 more
wiley   +1 more source

Customizing Tactile Sensors via Machine Learning‐Driven Inverse Design

open access: yesAdvanced Science, EarlyView.
ABSTRACT Replicating the sophisticated sense of touch in artificial systems requires tactile sensors with precisely tailored properties. However, manually navigating the complex microstructure‐property relationship results in inefficient and suboptimal designs.
Baocheng Wang   +15 more
wiley   +1 more source

Acute Physical Activity for Motor and Academic Learning in Education-based Settings

open access: yesJournal of Neuroeducation
Numerous studies have shown that engaging in physical activity significantly benefits several cognitive domains. Among them, research findings indicate that even a single bout of physical activity positively impacts executive functions, motor learning ...
Eric Roig   +2 more
doaj  

Physical education in secondary schools [PDF]

open access: yes, 2012
Davies, Stephen   +3 more
core  

Ethical Precision in Nanoscale Brain Interfacing

open access: yesAdvanced Science, EarlyView.
As brain interfaces approach the nanoscale, precision no longer only measures—it knows, predicts, and potentially reshapes the mind. This work argues that traditional ethics fails under such conditions and proposes a shift toward continuous, operation‐based governance using the recovery–discovery framework to track, constrain, and responsibly steer ...
Guilherme Wood
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

open access: yesAdvanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu   +8 more
wiley   +1 more source

Physical Implementation of Optical Material‐Based Neural Networks Processing Enabled by Long‐Persistent Luminescence

open access: yesAdvanced Science, EarlyView.
This study reports on the physical implementation of optical material‐based neural processing using long‐persistent luminescence as memory‐retention and nonlinear optical material. The system performs optical‐domain preprocessing with opto‐electronic interfaces for stimulus delivery and readout, enabling real‐time demonstrations including Pong gameplay
Sangwon Wi, Yunsang Lee
wiley   +1 more source

Home - About - Disclaimer - Privacy