Results 131 to 140 of about 148,863 (263)

SERS Facemask for Rapid and Portable Sensing Mycobacterium Tuberculosis Antigens for TB Screening

Advanced Science, EarlyView.
Our study introduced an Au─Ag embedded covalent organic framework (U@COF) ‐mediated facemask for sensing TB antigen ESAT‐6/CFP‐10 complex in clinical droplet samples toward TB screening. Practical analysis of clinical samples demonstrated the availability of our facemask, which is capable of identifying the TB subjects (N = 17) from healthy candidates (
Lingzhi Chen, Jiaqi Yu, Jing Xu, Lingqi Chen, Ninghao Zhang, Wenrui Li, Runmin Zeng, Xiaomin Luo, Yiqun Chang, Jiayin Lai, Wenshi Huang, Xiaochen Liang, Ting Zhao, Shanze Chen, Huaihong Cai, Yanguang Cong, Pinghua Sun, Jiang Pi, Xueqin Huang, Haibo Zhou, Junxia Zheng   +20 more
wiley   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

Advanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu, Longfei Lv, Fan Zhang, Si Zhou, Weiwei Gao, Jijun Zhao   +5 more
wiley   +1 more source

Nonlinear KCCA in fMRI activation analysis: Self-supervised optimization and robust back-reconstruction. [PDF]

Imaging Neurosci (Camb)
Han C, Yang Z, Zhuang X, Cordes D.
europepmc   +1 more source

Transferable Deep Reinforcement Learning With Edge‐Contour‐Depth Fusion for Autonomous Wireless Capsule Endoscopy Navigation

Advanced Science, EarlyView.
This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu, Haitao Gao, Qingyang Liu, Sishen Yuan, Haiyang Fang, Mingwu Su, Baijia Liang, Yongzun Yang, Long Bai, Wenzhen Dong, Dihong Xie, Shijian Su, Jiewen Lai, Shing Shin Cheng, Zhen Li, Xiuli Zuo, Hongliang Ren   +16 more
wiley   +1 more source

Inverse Statistics of Active Matter Trajectories to Distinguish Interaction Kernel Anisotropy from Emergent Correlations. [PDF]

Bull Math Biol
Martina-Perez SF.
europepmc   +1 more source

WS2 Optoelectronic Memristive Reservoir Enabling Ultra‐Low‐Power, Multi‐Task, and Environmentally Stable Neuromorphic Computing

Advanced Science, EarlyView.
WS2‐based in‐memory sensing reservoir computing integrates sensing, memory, and computation in one compact device. It achieves ∼94% N‐MNIST, ∼93% eye motion perception, and ∼89% speech recognition with ultra‐low energy (∼25.5 fJ/spike). The system shows stability at 95% humidity, endurance over 1.5M cycles, and supports synaptic plasticity, enabling ...
Dayanand Kumar, Hanrui Li, Divyanshu Divyanshu, Dhananjay D. Kumbhar, Manoj Kumar Rajbhar, Amit Singh, Abdul Momin Syed, Selma Amara, Gianluca Setti, Nazek El‐Atab   +9 more
wiley   +1 more source

Kernel embeddings and the separation of measure phenomenon. [PDF]

Proc Natl Acad Sci U S A
Santoro LV, Waghmare KG, Panaretos VM.
europepmc   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +1 more source

A robust multi-location evaluation of a machine learning framework for wind power forecasting. [PDF]

PLoS One
Ali U, Sufyan M, Ali S, Ahmad M, Rehman Khan SU, Raza N, Sultana J, Habib MA.   +7 more
europepmc   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source