Results 101 to 110 of about 33,441 (257)
Understanding protein sequence–function relationships remains challenging due to poorly defined motifs and limited residue‐level annotations. An annotation‐agnostic framework is introduced that segments protein sequences into “protein words” using attention patterns from protein language models.
Hedi Chen +9 more
wiley +1 more source
Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare
Multimodal biosensing meets multidomain AI. Wearable biosensors capture complementary biochemical and physiological signals, while cross‐device, population‐aware learning aligns noisy, heterogeneous streams. This Review distills key sensing modalities, fusion and calibration strategies, and privacy‐preserving deployment pathways that transform ...
Chenshu Liu +10 more
wiley +1 more source
CGMNet: Semantic Change Detection via a Change-Aware Guided Multi-Task Network
Change detection (CD) is the main task in the remote sensing field. Binary change detection (BCD), which only focuses on the region of change, cannot meet current needs.
Li Tan, Xiaolong Zuo, Xi Cheng
doaj +1 more source
The Faraday Scalpel: Electrochemical Nerve Lesioning Mechanisms Studied in Invertebrate Models
Direct‐current produces nerve lesioning through discrete electrochemical reactions. Using hypoxia‐sensitive locust nerves and hypoxia‐tolerant leech nerves, we map three injury pathways: cathodic oxygen reduction, cathodic alkalization, and anodic chloride oxidation. These findings establish electrochemical lesioning—the “Faraday Scalpel”—as a precise,
Petra Ondráčková +5 more
wiley +1 more source
Semantic Change Detection (SCD) in Remote Sensing Images (RSI) aims to identify changes in the type of Land Cover/Land Use (LCLU). The “from-to” information of the acquired image has more profound practical significance than Binary Change ...
Yuhang Zhang +4 more
doaj +1 more source
Stable Diffusion Models Reveal a Persisting Human–AI Gap in Visual Creativity
This study examines visual creativity in humans and generative AI using the TCIA framework. Human artists outperform AI overall, yet structured human guidance substantially improves AI outputs and evaluations. Findings reveal that alignment with human creativity depends critically on contextual framing, highlighting both the promise and current ...
Silvia Rondini +8 more
wiley +1 more source
Remote sensing image change detection plays an important role in urban planning and environmental monitoring. However, the existing change detection algorithms have limited ability in feature extraction, feature relationship understanding, and capture of
Hongjin Ren +4 more
doaj +1 more source
Peroxidase‐Mimicking Nanozymes for Rapid Detection of Infectious Diseases
Peroxidase‐mimicking nanozymes (PMNs) have emerged as robust and versatile materials for rapid infectious disease diagnostics. This review highlights the rational design and controlled synthesis of PMNs, summarizes key biomarkers relevant to infectious diseases, examines their integration into diverse rapid detection platforms, and highlights ...
Shikuan Shao +5 more
wiley +1 more source
Discovering Interpretable Semantics from Radio Signals for Contactless Cardiac Monitoring
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
Change Detection Network Based on Transformer and Transfer Learning
The purpose of the change detection(CD) task is to contrast the change information of a specific object in remote sensing images from different time periods. The deep-learning-based change-detection algorithm can extract pixel-level semantic segmentation
Hua Li +5 more
doaj +1 more source

