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2019

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Medicine and Health Sciences

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Engineering Faculty Articles and Research

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Full-Text Articles in Engineering

Using Green Emitting Ph-Responsive Nanogels To Report Environmental Changes Within Hydrogels: A Nanoprobe For Versatile Sensing, Mingning Zhu, Dongdong Lu, Shanglin Wu, Qing Lian, Wenkai Wang, L. Andrew Lyon, Weiguang Wang, Paulo Bártolo, Brian R. Saunders May 2019

Using Green Emitting Ph-Responsive Nanogels To Report Environmental Changes Within Hydrogels: A Nanoprobe For Versatile Sensing, Mingning Zhu, Dongdong Lu, Shanglin Wu, Qing Lian, Wenkai Wang, L. Andrew Lyon, Weiguang Wang, Paulo Bártolo, Brian R. Saunders

Engineering Faculty Articles and Research

Remotely reporting the local environment within hydrogels using inexpensive laboratory techniques has excellent potential to improve our understanding of the nanometer-scale changes that cause macroscopic swelling or deswelling. Whilst photoluminescence (PL) spectroscopy is a popular method for such studies this approach commonly requires bespoke and time-consuming synthesis to attach fluorophores which may leave toxic residues. A promising and more versatile alternative is to use a pre-formed nanogel probe that contains a donor/acceptor pair and then “dope” that into the gel during gel assembly. Here, we introduce green-emitting methacrylic acid-based nanogel probe particles and use them to report the local ...


Applications Of Supervised Machine Learning In Autism Spectrum Disorder Research: A Review, Kayleigh K. Hyde, Marlena N. Novack, Nicholas Lahaye, Chelsea Parlett-Pelleriti, Raymond Anden, Dennis R. Dixon, Erik Linstead Feb 2019

Applications Of Supervised Machine Learning In Autism Spectrum Disorder Research: A Review, Kayleigh K. Hyde, Marlena N. Novack, Nicholas Lahaye, Chelsea Parlett-Pelleriti, Raymond Anden, Dennis R. Dixon, Erik Linstead

Engineering Faculty Articles and Research

Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing ASD, exploring its genetic underpinnings, and designing effective interventions. This paper provides a comprehensive review of 45 papers utilizing supervised machine learning in ASD, including algorithms for classification and text analysis. The goal of the paper is to identify and describe supervised machine learning trends in ASD literature as ...