This work presents a multimodal dataset containing synchronized electroencephalography (EEG), electromyography (EMG), and kinematic recordings acquired during wrist motor tasks performed with a three degree of freedom robotic exoskeleton (BiomechWris... read more
The pelagic environment represents a mosaic of biogeographical domains shaped by regional oceanographic processes. Here, a coastal-to-open ocean microbiome investigation was conducted from 64 water samples of the Santos Basin (SB), located in the sub... read more
Accurate prediction of drug release kinetics from polysaccharide-based delivery systems is essential for rational formulation design. In this study, a hybrid machine learning framework integrating Raman spectroscopy with formulation descriptors is de... read more
Cloud and cloud shadow masking is a crucial preprocessing step in hyperspectral satellite imaging, enabling the extraction of high-quality, analysis-ready data. This study investigates several lightweight machine learning models that require fewer re... read more
Cuproptosis is a novel form of regulated cell death driven by intracellular copper accumulation, leading to lipoylated protein aggregation and Fe-S cluster destabilization. Dysregulation of this process has been implicated in various pathological con... read more
Hypertension is a major global health burden and a leading driver of cardiovascular disease, yet reliable blood-based biomarkers for early disease are still limited. We combined plasma proteomics with explainable machine learning to identify circulat... read more
To effectively communicate and collaborate with others, we must monitor not only other people's cognitive states (e.g., what someone thinks or believes) but also their metacognitive states (e.g., how confident they are in their beliefs). While humans... read more
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