By all accounts, this was a memorable year for science. Researchers all over the world dropped what they were doing to join the fight against COVID-19, and those people deserve to have their praises sung.
However, science is anything but singular, and there were many stories of triumph and reflection this year that didn’t involve COVID-19. Those people deserve to be recognized, too.
As such, we present to you the 10 most popular Science Node articles of 2020, starting with a countdown from 10-6. Check back tomorrow for the Top 5.
The Internet of Things (IoT) is a term that’s rapidly gaining a spotlight, as everything from your doorbell to your refrigerator is connected to the internet. Smart devices may make life easier, but Bruce Schneier of Harvard’s Kennedy School is quick to point out that they can also be threat vectors.
An expert on a variety of security fields, including Security Theater, Schneier has the knowledge to plainly explain that inviting IoT devices into our house means computers can physically affect things in the world.
“We're used to computers that sit quietly and process data. Not ones that could freeze your pipes in a Minnesota winter,” says Schneier.
This interesting conversation begins with a very simple fact. It’s not that IoT security is handled differently than any other device; “it’s just done at a lower price point.”
A defining feature of the early stages of the pandemic were empty streets. We didn’t entirely understand how the virus spread, so our best option was to hunker down at home. This meant fewer cars on the road, and that seems to have translated to less pollution.
Brian McDonald, an environmental engineer out of the National Oceanic and Atmospheric Administration (NOAA), noticed a decrease in nitrous oxides that correlated with the stay-at-home orders.
At the time this article was posted, McDonald was in the middle of a previous air study that got interrupted by his pandemic observations. While he couldn’t make hard conclusions based on what he saw, he seems confident that the drop in airborne pollutants was related to people staying home.
We had previously interviewed Paul Dabbar, Under Secretary of Science at the Department of Energy, about the department’s push toward exascale computing. He mentioned working with private partners, and we never would have guessed how relevant that conversation would be in the future.
Dabbar spoke with us again this year about the COVID-19 HPC Consortium, which is a group of private and public organizations with the goal of combining HPC resources to fight COVID-19.
He remarked on how academic institutions had legions of researchers ready to take on this disease, and he looked forward to combining these resources with the massive funding of the federal government.
What’s more, these researchers haven’t been sitting on their collective hands. The consortium recently announced that they were now working to identify therapies that could help patients in the next six months.
The Paths to HPC series has a special place in our heart, and for good reason. We love being able to showcase the many wonderful and talented women who regularly rely on HPC to learn more about the world we live in.
Sandra Gesing, an associate research professor at the University of Notre Dame, is a perfect example of the scientific spirit we wanted to embody with this series.
Her story begins in high school, where an interest in programming would eventually flourish into an apprenticeship in computer science. After some time as a head of a systems programming group, Gesing eventually found bioinformatics. She stated that she enjoys interdisciplinary work, and she remarks on how HPC’s versatility makes it a unique and powerful tool for science.
Despite making up about 70% of our universe, scientists are still trying to better understand dark energy. Our best chance for learning more is to use telescopes to gaze into the night sky.
The Dark Energy Survey (DES) used a powerful camera to observe 5,000 square degrees of the Southern sky from a mountaintop in the Chilean Andes. Operating for 100 nights every year between 2013 and 2019, the DES produced nearly 2 terabytes of data every night.
Of course, raw data isn’t enough to draw conclusions. All of this information is sent to the National Center for Supercomputing Applications (NCSA) to be prepared for use. The hope is that these datasets contain the information needed to learn more about dark energy.