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Liquid-Metal-Based Multichannel Strain Sensor for Sign Language Gesture Classification Using Machine Learning.
ACS Appl Mater Interfaces
January 2025
Centre for Robotics and Automation, Department of Biomedical Engineering, City University of Hong Kong, Hong Kong 999077, China.
Liquid metals are highly conductive like metallic materials and have excellent deformability due to their liquid state, making them rather promising for flexible and stretchable wearable sensors. However, patterning liquid metals on soft substrates has been a challenge due to high surface tension. In this paper, a new method is proposed to overcome the difficulties in fabricating liquid-state strain sensors.
View Article and Find Full Text PDFCharacterizing brain dynamic functional connectivity (dFC) patterns from functional Magnetic Resonance Imaging (fMRI) data is of paramount importance in neuroscience and medicine. Recently, many graph neural network (GNN) models, combined with transformers or recurrent neural networks (RNNs), have shown great potential for modeling the dFC patterns. However, these methods face challenges in effectively characterizing the modularity organization of brain networks and capturing varying dFC state patterns.
View Article and Find Full Text PDFObjective: Bile acids may contribute to pathophysiologic markers of Alzheimer's disease, including disruptions of the executive control network (ECN) and the default mode network (DMN). Cognitive dysfunction is common in major depressive disorder (MDD), but whether bile acids impact these networks in MDD patients is unknown.
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Response and variation mechanisms of RDX crystals under strong magnetic loading.
RSC Adv
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The Second Department, Xi' an Modern Chemistry Research Institute Xi'an 710065 China
To fully understand the variation in performance of cyclotrimethylenetrinitramine (RDX) crystals under strong magnetic field exposure, the strong magnetic loading of RDX was conducted in both stable and alternating magnetic fields. The morphological changes of RDX crystals exposed to magnetic fields were studied under a scanning electron microscope. Then, the lattice changes of RDX exposed to magnetic fields were analyzed through X-ray diffraction and Raman spectroscopy.
View Article and Find Full Text PDFIncreasing evidence suggests the involvement of metabolic alterations in neurological disorders, including Alzheimer's disease (AD), and highlights the significance of the peripheral metabolome, influenced by genetic factors and modifiable environmental exposures, for brain health. In this study, we examined 1,387 metabolites in plasma samples from 1,082 dementia-free middle-aged participants of the population-based Rotterdam Study. We assessed the relation of metabolites with general cognition (G-factor) and magnetic resonance imaging (MRI) markers using linear regression and estimated the variance of these metabolites explained by genes, gut microbiome, lifestyle factors, common clinical comorbidities, and medication using gradient boosting decision tree analysis.
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