Examining data from the first six weeks of their landmark DETECT study, a team of scientists from the Scripps Research Translational Institute sees encouraging signs that wearable fitness devices can improve public health efforts to control COVID-19.
The DETECT study, launched on March 25, uses a mobile app to collect smartwatch and activity tracker data from consenting participants, and also gathers their self-reported symptoms and diagnostic test results. Any adult living in the United States is eligible to participate in the study by downloading the research app, MyDataHelps.
In a study published October 29 in Nature Medicine, the Scripps Research team reports that wearable devices like Fitbit are capable of identifying cases of COVID-19 by evaluating changes in heart rate, sleep and activity levels, along with self-reported symptom data—and can identify cases with greater success than looking at symptoms alone.
National Institutes of Health (NIH), Data Ab Initio blog, Kristin Britney
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All NIH grants will be required to have a 2-page maximum data management plan (DMP). NIH expects researchers to: be clear in the DMP about where they plan to share (“to be determined” is no longer acceptable), notify them if plans change, and actually follow the plan.
You will be sharing more data, as NIH not only wants the data that underlies publications but all data that verifies results.
You will be sharing data sooner. NIH prefers if you share as soon as possible, but at the latest sharing should occur with publication or at the end of the grant period, which ever comes first. That last part is a huge change.
You will share your data in a repository. Criteria for data repositories are provided in a supplement and I expect to see more in this area between now and 2023.
University of Oxford (UK), Department of Computer Science
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DeepMind, the leading British artificial intelligence company, has renewed and extended its commitment to supporting research in AI at the University of Oxford by funding a new post, the DeepMind Professorship of Artificial Intelligence.
The DeepMind Chair will enable a world-leading AI researcher to establish a new group within Oxford’s thriving AI community, with the opportunity to pursue their own research interests. AI research at Oxford has strengths across the whole spectrum of contemporary AI, ranging from the philosophical and ethical foundations of the field through to reasoning, robotics, vision understanding, and deep learning.
Fiona Fidler, a metaresearcher at the University of Melbourne, was outraged. She had discovered that her appraisal of a submitted paper had been changed before being sent to the author, sometimes drastically. The words “very sympathetic” had become “generally sympathetic.” “This one is a good example” ended up as “this one still needs work.” Worst of all, she felt that the bottom line of her peer-review report to the journal Educational and Psychological Measurement, recommending that it accept the paper with minor revisions, was misrepresented in the editor’s rejection letter to the author.
“I had never experienced anything like this before,” Fidler says about the 2012 incident. She demanded explanations from the journal editor. And she later partnered with the snubbed paper author, Rink Hoekstra, a psychologist at the University of Groningen, to find out how widespread this practice was.
With colleagues, they’ve now surveyed 322 editors at high-impact journals across ecology, economics, medicine, physics, and psychology on when they think altering peer-review reports is justified.
The increase in online education has allowed a new type of teacher to emerge — an artificial one. But just how accepting students are of an artificial instructor remains to be seen.
That’s why researchers at the University of Central Florida’s Nicholson School of Communication and Media are working to examine student perceptions of artificial intelligence-based teachers.
Some of their findings, published recently in the International Journal of Human-Computer Interaction, indicate that for students to accept an AI teaching assistant, it needs to be effective and easy to talk to.
The hope is that by understanding how students relate to AI-teachers, engineers and computer scientists can design them to easily integrate into the education experience, says Jihyun Kim, an associate professor in the school and lead author of the study.
For decades, the U.S. National Science Foundation has funded infrastructure that allows scientists to push the frontiers of science and engineering. Agency-wide programs have supported construction of large facilities and small instruments, but until recently, NSF had no such program dedicated to mid-scale projects that fall between those categories. Mid-scale infrastructure projects enable breakthroughs that can only be achieved by this scale of investment. NSF has identified the need to fill this nationwide gap in mid-scale infrastructure and is awarding $125 million to support three new projects that address critical challenges. … This year’s $125 million in awards are for a class of “shovel ready” projects in the $20 to $70 million range. The projects will combine equipment, instrumentation and research staff with the expertise necessary for innovation. Each will also provide opportunities for community engagement, education and training.
For height, DNA is largely destiny. Studies of identical and fraternal twins suggest up to 80% of variation in height is genetic. But the genes responsible have largely eluded researchers. Now, by amassing genome data for 4 million people—the largest such study ever—geneticists have accounted for a major share of this “missing heritability,” at least for people of European ancestry. In this group, they’ve identified nearly 10,000 DNA markers that appear to fully explain the influence of common genetic variants over height.
Harvard University, John A. Paulson School of Engineering and Applied Sciences
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Data visualization pioneers Fernanda Viégas and Martin Wattenberg will join the Harvard faculty. Their research has helped define visualization as a field, creating interactive and open-source tools for examining a wide range of scientific, social, and artistic questions.
First Monday; Eszter Hargittai, Elissa M. Redmiles, Jessica Vitak, Michael Zimmer
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The COVID-19 global pandemic led governments, health agencies, and technology companies to work on solutions to minimize the spread of the disease. One such solution concerns contact-tracing apps whose utility is tied to widespread adoption. Using survey data collected a few weeks into lockdown measures in the United States, we explore Americans’ willingness to install a COVID-19 tracking app. Specifically, we evaluate how the distributor of such an app (e.g., government, health-protection agency, technology company) affects people’s willingness to adopt the tool. While we find that 67 percent of respondents are willing to install an app from at least one of the eight providers included, the factors that predict one’s willingness to adopt differ. Using Nissenbaum’s theory of privacy as contextual integrity, we explore differences in responses across distributors and discuss why some distributors may be viewed as less appropriate than others in the context of providing health-related apps during a global pandemic. We conclude the paper by providing policy recommendations for wide-scale data collection that minimizes the likelihood that such tools violate the norms of appropriate information flows.
One of the biggest challenges in managing crops, especially in large fields, is knowing how much water each section of a field needs. Determining that accurately is a cumbersome process that requires people to hand-pluck individual leaves from plants, put them in pressure chambers and apply air pressure to see when water begins to leak from the leaf stems.
That kind of testing is time consuming and means that farmers can only reach so many areas of a field each day and cannot test as frequently as they should.
Computer Science and Engineering Chair Professor Stefano Carpin, Environmental Engineering Professor Joshua Viers and professors Konstantinos Karydis and Amit K. Roy-Chowdhury at UC Riverside recently received a more than $1 million grant from the U.S. Department of Agriculture through the National Science Foundation’s National Robotics Initiative to address these challenges.
A new program aimed to help researchers validate and find commercial value in their ideas has officially launched at three Canadian universities. The Lab2Market program was developed to support researchers working in deep technology sectors.
The program has received $2.6 million in funding from the federal government. Of the $2.6 million, $1.3 million was invested through the FedDev Ontario regional development agency, while the remaining $1.3 million was invested through the Atlantic Canada Opportunities Agency. The program will also receive support from Mitacs, a national research organization, however, the amount of funding Mitacs is providing was not disclosed.
Lab2Market is a 16-week cohort program that offers selected researchers access to mentors, a community of entrepreneurs, and $15,000 in funding to help researchers explore the commercial potential of their work.
There have been many documented cases of Covid-19 “super-spreading” events, in which one person infected with the SARS-CoV-2 virus infects many other people. But how much of a role do these events play in the overall spread of the disease? A new study from MIT suggests that they have a much larger impact than expected.
The study of about 60 super-spreading events shows that events where one person infects more than six other people are much more common than would be expected if the range of transmission rates followed statistical distributions commonly used in epidemiology.
Based on their findings, the researchers also developed a mathematical model of Covid-19 transmission, which they used to show that limiting gatherings to 10 or fewer people could significantly reduce the number of super-spreading events and lower the overall number of infections.
As health care systems increasingly adopt AI technologies, data governance structures must evolve to ensure that ethical principles are applied to all clinical, information technology, education, and research endeavors. A data governance framework based on the following 10 steps can assist health care systems embrace artificial intelligence applications in ways that reduces ethical risks to patients, providers, and payers. This approach can also enhance public trust and transform patient and provider experiences by improving patient satisfaction scores, building better relationships between patients and providers, activating patients, and improving self-management of chronic care.
If you want a job as a graduate in an investment bank in 2021, you’ll need to play some games.
Employers are increasingly using the games invented by pymetrics to help them choose between student candidates.
JPMorgan rolled out the suite of 12 pymetrics games as part of its graduate recruitment process in 2019. Students now encounter the games when they apply for most jobs at the bank, including in technology. PWC, Boston Consulting Group and Accenture all use pymetrics too, along with various other banks and consulting firms.
JPMorgan still isn’t commenting on how the games are being used, but the has released this web page explaining that the 12 games will take 25-35 minutes and that there are no right or wrong answers. The games measure ‘social, cognitive and behavioural traits’ and are presented to students straight after their initial application. It’s still not clear whether a ‘bad outcome’ in pymetric will nix your whole application, but if you demonstrate the correct traits in the pymetrics games, you can expect to receive an invitiation to a digital Hirevue Interview. Students who’ve already graduated have complained that they’ve been rejected after the games are completed.
Online November 11-15. “The PyData Global approach is to pre-record all talks and tutorials so that you can watch them at your own pace. Live events will complement pre-recorded content, and will take place during business hours of our four geographic focus areas. To learn more, click here.” [$$]
National Academies of Sciences, Engineering, and Medicine
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Online November 5, starting at 11 a.m. Eastern time. “A virtual public workshop on developing a toolkit for fostering open science practices will take place on Thursday, November 5, 2020 in conjunction with the Fall 2020 meeting of the Roundtable on Aligning Incentives for Open Science. The workshop will explore the information and resource needs of researchers, research institutions, government agencies, philanthropies, professional societies, and other stakeholders interested in fostering open science practices.” [free, registration required]
Online November 11, starting at 12 p.m. Eastern time. “NISS has invited department heads from three academic institutions. They include Kate Calder (University of Texas at Austin), Abel Rodriguez (University of Washington) and Jiayang Sun (George Mason University). This session will be moderated by Lingzhou Xue (Penn State University). You will be glad to hear that each of these departments currently have tenure track positions posted!” [registration required]
There’s a proposal to add Software Transactional Memory, or STM, to the Ruby programming language. This is part of a wider effort to add better support for concurrency and parallelism in Ruby, and in particular the idea of ractors. A concept has been proposed and implemented by Koichi Sasada.
This article gives some context on what STM is, how you use it, and why you might want to use it. We’ll show an application which is well-suited to STM and we’ll use this to talk about the benefits, issues, and some open questions.
In “Automatic Video Creation From a Web Page”, published at UIST 2020, we introduce URL2Video, a research prototype pipeline to automatically convert a web page into a short video, given temporal and visual constraints provided by the content owner. URL2Video extracts assets (text, images, or videos) and their design styles (including fonts, colors, graphical layouts, and hierarchy) from HTML sources and organizes the visual assets into a sequence of shots, while maintaining a look-and-feel similar to the source page. Given a user-specified aspect ratio and duration, it then renders the repurposed materials into a video that is ideal for product and service advertising.