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MAS.630 Affective Computing, Spring 2002
Published 2002Subjects: “…Neuroscience findings…”
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Predicting cognitive scores from wearable-based digital physiological features using machine learning: data from a clinical trial in mild cognitive impairment
Published 2024“…The model predicted the actual executive function scores with correlation r = 0.69 and intra-individual changes in executive function scores with r = 0.61. Conclusions: Our findings demonstrated that wearable-based physiological measures, primarily HRV, have potential to be used for the continuous assessments of cognitive function in individuals with MCI.…”
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Towards an optimal and unbiased approach for tumor cell isolation
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Current state-of-the-art of non-reverse osmosis-like forward osmosis technology
Published 2024Article -
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Lorenzo Ghiberti and contested views of perspectiva in Renaissance concepts of space
Published 2021Subjects: Get full text
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Preparation and magnetic properties of L10–FePt/TiO2 nanocomposite thin films
Published 2013Get full text
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Microfluidic platform for negative enrichment of circulating tumor cells
Published 2016Get full text
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Combined knee osteoarthritis and diabetes is associated with reduced muscle strength, physical inactivity, and poorer quality of life
Published 2024“…Knee osteoarthritis+diabetes-was independently associated with reduced Timed Up and Go test and social isolation. Conclusion: The findings revealed the diabetic knee osteoarthritis subgroup’s unique physical and psychosocial features of reduced muscle strength and physical inactivity. …”
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Ceramicized NASICON-based solid-state electrolytes for lithium metal batteries
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Vertical split-ring resonators for plasmon coupling, sensing and metasurface
Published 2018Get full text
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Machine learning driven synthesis of few-layered WTe₂ with geometrical control
Published 2022“…Notably, the growth mechanism of 1T' few-layered WTe2 NRs is further proposed, which provides new insights for the growth of intriguing 2D and 1D tellurides and may inspire the growth strategies for other 1D nanostructures. Our findings suggest the effectiveness and capability of ML in guiding the synthesis of 1D nanostructures, opening up new opportunities for intelligent materials development.…”
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Journal Article