Results 221 to 230 of about 574,847 (308)

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

Discovering Interpretable Semantics from Radio Signals for Contactless Cardiac Monitoring

open access: yesAdvanced Science, EarlyView.
This study presents a semantic representation framework for clinically interpretable cardiac monitoring from contactless radio signals. It formulates radio semantic learning as an information‐bottleneck problem and approximates the objective via intra‐modal compression and cross‐modal alignment, structuring radio measurements into meaningful semantic ...
Jinbo Chen   +10 more
wiley   +1 more source

Annealing‐Induced Plasticity and Strengthening in Metallic Glasses

open access: yesAdvanced Science, EarlyView.
This work challenges the dogma that annealing inevitably embrittles metallic glasses. We demonstrate that sub‐Tg annealing, guided by positive mixing enthalpy and constrained kinetics, can drive a self‐organized compositional fluctuation that creates an interface‐free heterogeneous structure.
Yingjie Zhang   +17 more
wiley   +1 more source

PAIR: Reconstructing Single‐Cell Open‐Chromatin Landscapes for Transcription Factor Regulome Mapping

open access: yesAdvanced Science, EarlyView.
scATAC‐seq analysis is often constrained by limited sequencing depth, extreme sparsity, and pervasive technical missingness. PAIR is a probabilistic framework that restores scATAC‐seq accessibility profiles by directly modeling the native cell–peak bipartite structure of chromatin accessibility.
Yanchi Su   +7 more
wiley   +1 more source

Model‐Inversion‐Resistant Physical Unclonable Neural Network Using Vertical NAND Flash Memory

open access: yesAdvanced Science, EarlyView.
Schematic and key features of the proposed forward‐forward physical unclonable neural network (FF‐PUNN), incorporating a concealable physical unclonable function (PUF) layer and forward‐forward (FF) learning. ABSTRACT The growing use of neural networks in privacy‐sensitive applications necessitates architectures that inherently protect both data and ...
Sung‐Ho Park   +8 more
wiley   +1 more source

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