Blockchain technology to optimize P2P energy trading

A Tokyo Tech research team led by Specially Appointed Professor Takuya Oda of the Institute of Innovative Research and Professor Keisuke Tanaka of the School of Computing, in collaboration with Mitsubishi Electric Corporation, has developed a new technology an original blockchain[1] technology that can optimize peer-to-peer (P2P) energy trading[2].

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Study Finds Neglected Mutations May Play Important Role in Autism Spectrum Disorder

Mutations that occur in certain DNA regions, called tandem repeats, may play a significant role in autism spectrum disorders, according to research led by Melissa Gymrek, assistant professor in the UC San Diego Department of Computer Science and Engineering and School of Medicine. The study, which was published in Nature on Jan. 14, was co-authored by UCLA professor of human genetics Kirk Lohmueller and highlights the contributions these understudied mutations can make to disease.

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UCI researchers use deep learning to identify gene regulation at single-cell level

Irvine, Calif., Jan. 5, 2021 — Scientists at the University of California, Irvine have developed a new deep-learning framework that predicts gene regulation at the single-cell level. Deep learning, a family of machine-learning methods based on artificial neural networks, has revolutionized applications such as image interpretation, natural language processing and autonomous driving.

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UCI researchers create model to calculate COVID-19 health outcomes

Irvine, Calif., Dec. 17, 2020 —University of California, Irvine health sciences researchers have created a machine-learning model to predict the probability that a COVID-19 patient will need a ventilator or ICU care. The tool is free and available online for any healthcare organization to use. “The goal is to give an earlier alert to clinicians to identify patients who may be vulnerable at the onset,” said Daniel S.

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