Each year, Science Node travels the world to talk to scientists in their labs and bring you the stories of their groundbreaking research—from deep inside the human body to the farthest reaches of space, and everywhere in between.
We delved into our archives to find out which stories our readers found the most engaging. Today we’re counting down from 10 to 6. Check back tomorrow for the Top 5.
10. Sky taxis
Rush hour traffic is enough to make anyone daydream about flying high above the honking horns and packed streets. Even densely-packed urban areas have a lot of empty space if you look up.
Patricia Ventura Diaz and her colleagues at NASA Ames Research Center are closing in on the technology to make flying commutes possible. The NASA Urban Air Mobility Grand Challenge is designing technologies that would allow for aerial transport within cities.
Ventura turns to computational fluid dynamics (CFD) to model airflow around the rotors and to predict the sounds these flying vehicles would create. Unlike existing airplanes and helicopters, the urban air mobility challenge calls for completely new designs.
The use of social media to meddle in election campaigns is an absolute fact at this point. But despite the gloomy reality of this technology, there’s still hope for it within the political space. Dr. Srijith Rajamohan, a computational scientist at Virginia Tech, is building a visualization tool that could help you with your decision on election day.
Rajamohan and his colleague Alana Romanella are trying to chart political ideology based on Twitter history. A machine learning algorithm paired with natural language understanding plugs into Twitter’s API (application programming interface) and spits out a chart created from a person’s tweets.
The idea is to align the user’s perspective with those of some sort of public figure. Defining a person as “Republican” or “Democrat” is hard, but someone’s thoughts on Bernie Sanders would probably tell researchers a lot about their other political opinions.
Although we like to think of it as a human trait, monogamy is actually found throughout the animal kingdom. The relationship offers inherent advantages to both parents helping to raise offspring, such as higher levels of protection for young as well as the sharing of parental responsibilities.
That said, researchers from UT Austin’s Department of Integrative Biology wanted to see exactly what drives some animals to monogamy. By conducting a genetic study of both monogamous and non-monogamous animals – all of which had a common ancestor 450 million years ago – the scientists found that similar changes in gene expression occurred across multiple monogamous animals.
“Most people wouldn’t expect that across 450 million years, transitions to such complex behaviors would happen the same way every time,” says integrative biologist Rebecca Young.
Have you ever wondered why Jimi Hendrix’s rendition of Voodoo Child can send a shiver up your spine, but your cousin Bobby’s version just makes your skin crawl? Sure, Bobby’s guitar-playing face looks like he just smelled a dead skunk, but what is the X factor that makes two versions of the same song so different?
To get a baseline, the researchers decided to focus on Johann Sebastian Bach’s Trio Sonatas for Organ. The same songs performed by multiple players have been digitized and then visualized in order to see how their different playing styles can be mapped out. Hopefully, this will help us learn more about the exact science behind music’s beauty.
While the brain may be the most important organ in the body, we’re still unwrapping its mysteries. For instance, we’ve known for some time that synaptic connections in the brain aren’t hard wired. New connections grow as old ones wither, but what we don’t fully understand is how these connections are formed.
Scientists from TU Darmstadt are working hard to better understand this conundrum. Because the brain has billions of neurons working in tandem, it’s difficult to simulate all of them with a single computer model.
But by looking to an algorithm designed to simulate the movement of the stars, the researchers believe they have found a solution. Just as the distance between corresponding particles determines the forces they exert on each other, the probabilities of connections in the brain depend on the distance between neurons. The new algorithm uses a tree structure to organize the neurons into groups that reduce the computational load.
Ultimately, this work could reveal how the brain reacts to an injury or inform the development of more sophisticated artificial intelligence.
Visit us again tomorrow to see the rest of the list...