Results 211 to 220 of about 7,724,255 (252)

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

Astrocytic LMP2 Coordinates NF‐κB and TGF‐β1/Smad3 Signaling to Drive Neuroinflammation after Cerebral Ischemia/Reperfusion

open access: yesAdvanced Science, EarlyView.
ABSTRACT Astrocyte reactivity critically shapes neuroinflammatory outcomes after ischemic stroke, yet the upstream regulators governing astrocyte state transitions remain incompletely defined. Here, we identify the immunoproteasome subunit low molecular weight protein 2 (LMP2) as an important modulator of astrocyte functional remodeling following ...
Yanguang Mao   +7 more
wiley   +1 more source

Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers

open access: yesAdvanced Science, EarlyView.
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao   +9 more
wiley   +1 more source

Overcoming Artificial Structures in Resolution‐Enhanced Hi‐C Data by Signal Decomposition and Multi‐Scale Attention

open access: yesAdvanced Science, EarlyView.
Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li   +6 more
wiley   +1 more source

Toward Prostate Cancer Early Warning with a Self‐Powered Wearable Biosensing Platform Integrated with Machine Learning

open access: yesAdvanced Science, EarlyView.
ABSTRACT Current prostate cancer detection methods remain limited in non‐invasiveness and specificity, prompting interest in urinary biomarkers such as sarcosine. Here, we report a urine‐powered wearable platform for non‐invasive sarcosine detection as a proof‐of‐concept for decentralized early warning.
Jing Xu   +10 more
wiley   +1 more source

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