CHOP Researchers Demonstrate How Dynamic Changes in Early Childhood Development May Lead to Changes in Autism Diagnosis

Researchers found that difficulties in diagnosing toddlers with autism spectrum disorder (ASD) might be due to the dynamic nature of the disorder during child development. Children with clinical characteristics that put them on the diagnostic border of autism have an increased susceptibility to gaining or losing that diagnosis at later ages.

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NIH Awards UC San Diego $33 Million for Five COVID-19 Diagnostic Projects

UC San Diego was awarded five COVID-19 Rapid Acceleration of Diagnostics (RADx) projects by the National Institutes of Health totaling nearly $33 million, which will fund efforts that range from managing a large data center to expanding testing in disadvantaged communities.

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Federal COVID-19 response taps UCI Health as a model for delivering monoclonal antibody therapy

Irvine, Calif., Feb. 9, 2021 — Monoclonal antibodies are showing promise for improving outcomes for COVID-19 patients, but when a hospital is already beyond capacity, administering them can be a challenge. As hospitalizations soared across California, clinicians with UCI Health created a system for delivering monoclonal antibodies that is keeping hospital beds available for patients with the greatest need.

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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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NEW PROJECT OFFERS REAL-WORLD CASE STUDIES TO TEACH BIG DATA LESSONS TO HELP SOLVE PRESSING HEALTH ISSUES

Researchers at the Johns Hopkins Bloomberg School of Public Health have developed a series of case studies for urgent public health issues to help students and practitioners across the U.S. learn how to apply big-data analysis approaches in their work.

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New research solves Parker Solar Probe’s solar switchbacks surprise

In newly published research, scientists have for the first time modeled the nature of solar switchbacks – the large and long-duration isolated velocity spikes in the solar wind that surprised researchers when data arrived from the Solar Wind Electrons Alphas and Protons (SWEAP) instruments aboard NASA’s Parker Solar Probe (PSP).

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Globus Moves 1 Exabyte

Globus, a leading research data management service, reached a huge milestone by breaking the exabyte barrier. While it took over 2,000 days for the service to transfer the first 200 petabytes (PB) of data, the last 200PB were moved in just 247 days. This rapidly accelerating growth is reflected by the more than 150,000 registered users who have now transferred over 120 billion files using Globus.

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How Technological, Socioeconomic and Geopolitical Forces are Altering Everything We Know about Marketing

A new study examines technological, socioeconomic and geopolitical forces altering the marketing industry — including deepening consumer relationships — and the implications for marketing managers, educators and researchers.

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As hospitals walk the tightrope of patient data-sharing, one system offers a new balance

Every major medical center in America sits on a gold mine of patient data that could be worth millions of dollars to companies that could use it to develop new treatments and technologies. A new framework could help them do so more responsibly, going beyond the minimum legal requirements and respecting patients by giving them more say in how their individual data may be used.

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Using Big Data to Design Gas Separation Membranes

Researchers at Columbia Engineering and the University of South Carolina have developed a method that combines big data and machine learning to selectively design gas-filtering polymer membranes to reduce greenhouse gas emissions. Their study, published today in Science Advances, is the first to apply an experimentally validated machine learning method to rapidly design and develop advanced gas separation membranes.

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Major upgrades of particle detectors and electronics prepare CERN experiment to stream a data tsunami

For an experiment that will generate big data at unprecedented rates, physicists led design, development, mass production and delivery of an upgrade of novel particle detectors and state-of-the art electronics.

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Researchers work on early warning system for COVID-19

To better understand early signs of coronavirus and the virus’ spread, physicians around the country and data scientists at UC San Diego are working together to use a wearable device to monitor more than 12,000 people, including thousands of healthcare workers. The effort has started at hospitals in the San Francisco Bay Area and at the University of West Virginia.

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Staying Two Steps Ahead of the Coronavirus

A method of predicting the coronavirus spread – pioneered and developed by Weizmann Institute scientists – may enable authorities to focus efforts on areas where an outbreak is anticipated and relieve measures taken in others. Several countries, including the U.S., are adopting the new method

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UAH’s Center for Space Plasma and Aeronomic Research has central role in 2024 IMAP mission

The Center for Space Plasma and Aeronomic Research (CSPAR) at The University of Alabama in Huntsville (UAH) will be central to the modeling and data crunching that follow the scheduled launch of NASA’s Interstellar Mapping and Acceleration Probe (IMAP) mission in 2024.

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UAH prepares for massive data stream following coming launch of ESA Solar Orbiter

The University of Alabama in Huntsville (UAH) will have a major role in exploring an expected massive data stream that will follow the launch of the European Space Agency (ESA) Solar Orbiter, a mission that will fly over the sun’s poles and on which UAH’s Dr. Gary Zank is a co-primary investigator.

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Cornell co-leads effort to use big data to combat catastrophes

With a team of experts in fields including data science, statistics, computer science, finance, energy, agriculture, ecology, hydrology, climate and space weather, The Predictive Risk Investigation System for Multilayer Dynamic Interconnection Analysis (PRISM), funded by the National Science Foundation (NSF), will integrate data across different areas to improve risk prediction.

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AI-analyzed blood test can predict the progression of neurodegenerative disease

Evaluating the effectiveness of therapies for neurodegenerative diseases is often difficult because each patient’s progression is different. A new study shows artificial intelligence (AI) analysis of blood samples can predict and explain disease progression, which could one day help doctors choose more appropriate and effective treatments for patients.

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BP Looks to ORNL, ADIOS to Help Rein in Data

British Petroleum researchers invited ORNL data scientists to give the company’s high-performance computing team a tutorial of the laboratory’s ADIOS I/O middleware. ADIOS has helped researchers achieve scientific breakthroughs by providing a simple, flexible way to describe data in their code that may need to be written, read, or processed outside of the running simulation. ORNL researchers Scott Klasky and Norbert Podhorszki demonstrated how it could help the BP team accelerate their science by helping tackle their large, unique seismic datasets.

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What 26,000 books reveal when it comes to learning language

What can reading 26,000 books tell researchers about how language environment affects language behavior? Brendan T. Johns, an assistant professor of communicative disorders and sciences at UB has published a computational modeling study that suggests our experience and interaction with specific learning environments, like the characteristics of what we read, leads to differences in language behavior that were once attributed to differences in cognition.

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Research to Prevent Blindness and American Academy of Ophthalmology Award Grants for Big Data Research to Improve Patient Care

The American Academy of Ophthalmology (the Academy) and Research to Prevent Blindness (RPB) today announced this year’s recipients of the Research to Prevent Blindness/American Academy of Ophthalmology Award for IRIS® Registry Research. The grant supports researchers who want to conduct big data research in ophthalmology and blindness prevention.

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