Results 51 to 60 of about 150,011 (287)

A Wearable Brain–Computer Interface for Mitigating Car Sickness via Attention Shifting

Advanced Science, EarlyView.
Car sickness poses a major challenge in vehicular travel, yet effective nonpharmacological solutions are scarce. We developed a wearable, closed‐loop mindfulness BCI that uses real‐time EEG‐based neurofeedback to shift attention away from motion‐induced discomfort. Validated in real‐car experiments involving >100$>100$ susceptible individuals, over 83%
Jiawei Zhu, Xiaoyu Bao, Qiyun Huang, Tao Wang, Li Huang, Haiyun Huang, Junbiao Zhu, Jun Qu, Kendi Li, Di Chen, Ya Jiang, Kailin Xu, Zijian Wang, Wei Wu, Yuanqing Li   +14 more
wiley   +1 more source

Application of Constrained Robust Independent Component Analysis in the Fault Diagnosis of Rolling Element Bearing

Jixie chuandong, 2015
The method of independent component analysis is widely used in mechanical equipment fault diagnosis domain.A novel method named as constrained robust independent component analysis（ cRobust ICA）based on Robust ICA algorithm is proposed which utilized ...
Liao Qiang, Li Xunbo, Huang Bo
doaj  

Unique estimation in EEG analysis by the ordering ICA

PLoS ONE, 2022
Independent Component Analysis (ICA) is a method for solving blind source separation problems. Because ICA only needs weak assumptions to estimate the unknown sources from only the observed signals, it is suitable for Electroencephalography (EEG ...
Yoshitatsu Matsuda, Kazunori Yamaguchi
doaj  

Decoding the Integrated Stress Response of Pancreatic Cancer: Identifying a Serine‐dependent Tumor Subset Under Metabolic Relationships With CAFs.

Advanced Science, EarlyView.
Researchers identified a pancreatic cancer subset with low global protein synthesis but heightened translation of stress‐response genes like ATF4, rendering cells resistant to chemotherapy and apoptosis. These tumors depend on serine and cysteine from surrounding cancer‐associated fibroblasts (CAFs), which shift to produce serine by curbing collagen ...
Sauyeun Shin, Mehdi Liauzun, Jacobo Solorzano, Morgane Le Bras, Christine Jean, Benjamin Fourneaux, Margaux Dore, Lea Fevrier, Ismahane Belhabib, Alexia Brunel, Cindy Neuzillet, Marion Larroque, Carine Joffre, Stephane Rocchi, Nicolas Fraunhoffer, Aurelie Perraud, Muriel Mathonnet, Vera Pancaldi, Laetitia Linares, Juan Iovanna, Nelson Dusetti, Ola Larsson, Remy Nicolle, Stephane Pyronnet, Corinne Bousquet, Yvan Martineau   +25 more
wiley   +1 more source

Harmonic Source Localization Approach Based on Fast Kernel Entropy Optimization ICA and Minimum Conditional Entropy

Entropy, 2016
Based on the fast kernel entropy optimization independent component analysis and the minimum conditional entropy, this paper proposes a harmonic source localization method which aims at accurately estimating harmonic currents and identifying harmonic ...
Tianlei Zang, Zhengyou He, Ling Fu, Jing Chen, Qingquan Qian   +4 more
doaj   +1 more source

Independent Component Extraction from the Incomplete Coordinate Time Series of Regional GNSS Networks

Sensors, 2021
Independent component analysis (ICA) is one of the most effective approaches in extracting independent signals from a global navigation satellite system (GNSS) regional station network.
Tengfei Feng, Yunzhong Shen, Fengwei Wang   +2 more
doaj   +1 more source

CanICA: Model-based extraction of reproducible group-level ICA patterns from fMRI time series [PDF]

, 2009
Spatial Independent Component Analysis (ICA) is an increasingly used data-driven method to analyze functional Magnetic Resonance Imaging (fMRI) data. To date, it has been used to extract meaningful patterns without prior information.
Poline, Jean Baptiste, Sadaghiani, Sepideh, Thirion, Bertrand, Varoquaux, Gaël   +3 more
core   +3 more sources

High-Performance FPGA Implementation of Equivariant Adaptive Separation via Independence Algorithm for Independent Component Analysis

, 2017
Independent Component Analysis (ICA) is a dimensionality reduction technique that can boost efficiency of machine learning models that deal with probability density functions, e.g. Bayesian neural networks. Algorithms that implement adaptive ICA converge
Nazarian, Shahin, Nazemi, Mahdi, Pedram, Massoud   +2 more
core   +1 more source

Iron Oxide Nanozyme as Reactive Oxygen and Nitrogen Species Scavenger to Regulate Microglial Homeostasis in Stroke

Advanced Science, EarlyView.
6 nm iron oxide nanoparticles (IONP6) exhibit enzyme‐like activities that scavenge reactive oxygen and nitrogen species (RONS), including nitric oxide (NO). In stroke models, IONP6 promotes microglial polarization toward the M2 phenotype, reduces neuroinflammation, and improves neurological outcomes, offering a promising drug‐free approach to mitigate ...
Yilin Qi, Chunxiao Wang, Yuqing Miao, Jiamin Li, Zengyu Xun, Di Sun, Fei Xu, Minrui Liu, Heping Wang, Galong Li, Xuyi Chen, Haiming Fan, Xue Xue   +12 more
wiley   +1 more source

Compensating for Channel Fading in DS-CDMA Communication Systems Employing ICA Neural Network Detectors [PDF]

Journal of Systemics, Cybernetics and Informatics, 2005
In this paper we examine the impact of channel fading on the bit error rate of a DS-CDMA communication system. The system employs detectors that incorporate neural networks effecting methods of independent component analysis (ICA), subspace estimation of
David Overbye, Roland Priemer
doaj