Results 131 to 140 of about 39,328 (263)

Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring

Advanced Intelligent Discovery, EarlyView.
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira, Marcos de C. Leite, Pedro H. M. Zanineli, Juliana N. Y. Costa, Débora M. Cunha, Sophia P. Serra, Pedro H. Sophia, Flávio M. Shimizu, Yasmin W. Moura, Célio C. Oliveira, Gabriel R. Schleder, Gabriela F. Persinoti, Leandro Merces, Renato S. Lima   +13 more
wiley   +1 more source

A robust, real‑time telemetry protocol for miniaturized neural implants using off‑the‑shelf hardware. [PDF]

Bioelectron Med
Elgohary M, Recine M, Wong J, Datta-Chaudhuri T.   +3 more
europepmc   +1 more source

Advancing Efficient Error Reduction in DNA Data Storage Systems with Deep Learning‐Based Denoising Models

Advanced Intelligent Discovery, EarlyView.
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo, Anshula Tandon, Nguyen Kim Uyen, Quoc Nam Le, Jee‐Hyong Lee, Sung Ha Park   +5 more
wiley   +1 more source

Three-Basis Loop-Back QKD: A Passive Architecture for Secure and Scalable Quantum Mobile Networks. [PDF]

Entropy (Basel)
Lizama-Pérez LA, Morales-Calvo P.
europepmc   +1 more source

Majority‐Voting Overlapping Method for Error Correction in DNA Data Storage

Advanced Intelligent Discovery, EarlyView.
We propose an overlapping‐based majority‐voting method for DNA data storage error correction. By aligning multiple reads and choosing the most frequent base per position, it suppresses substitution errors without prior models. Validated on synthetic and real sequencing data, it achieves high‐fidelity, scalable, and cost‐effective reconstruction ...
Thi Bich Ngoc Nguyen, Seongjun Seo, Anshula Tandon, Nguyen Kim Uyen, Thi Hong Nhung Vu, Sung Ha Park   +5 more
wiley   +1 more source

Machine Learning based OTN Network Performance Degradation Prediction

Guangtongxin yanjiu
【Objective】This paper aims to address the challenge of predicting performance degradation (frame transmission errors) in Optical Transport Network (OTN).
CHEN Liping, LIAO Liang, ZHANG Peng, ZHU Dehan, PENG Zhichong, ZHOU Hao   +5 more
doaj  

Hybrid quantum-chaotic key expansion enhances QKD rates using the Lorenz system. [PDF]

Sci Rep
Danvirutai P, Wongthanavasu S, Hoang TM, Srichan C.   +3 more
europepmc   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Safe image transmission with hybrid quantum key-genetic encryption via spatial modulation assisted NOMA. [PDF]

Sci Rep
Thennavan S, Jayapalan A.
europepmc   +1 more source

Dual‐Mode Oscillations in SiOx‐Based Threshold Switching Devices for Unconventional Probabilistic Computing

Advanced Intelligent Discovery, EarlyView.
To enable versatile unconventional computing, a single SiOx threshold switching device is engineered to exhibit controllable dual‐mode oscillation. By modulating the input voltage, the device selectively provides stable full oscillation for oscillatory neural networks and stochastic probabilistic oscillation for probabilistic bits and true random ...
Hyeonsik Choi, Jihyun Kim, Yonghun Kim, Jiyong Woo   +3 more
wiley   +1 more source