Sometimes, what seems like a good way to explain the world--a model--turns out to be wrong. CSHL machine learning researchers developed a way to find the best answers to complicated questions, rather than answers that only appear to be right when tested in a few ways.
Applying the new screening index could improve efforts to monitor for chronic, long-term exposure to low levels of lead.
In Physics of Fluids, researchers used a model to understand airborne transmission that is designed to be accessible to a wide range of people, including nonscientists. Employing concepts of fluid dynamics and factors in airborne transmission, they propose the Contagion Airborne Transmission inequality model. While not all factors may be known, it can still be used to assess relative risks. The researchers determined protection from transmission increases with physical distancing in an approximately linear proportion.
A team led by scientists at Scripps Research has developed a theoretical approach that could ease the process of making highly complex, compact molecules. Such molecules are often found in plants and other organisms, and many are considered desirable starting points for developing potential new drugs. But they also tend to be highly challenging for chemists to construct and modify in the lab--a process called synthesis.
A new mathematical modeling study by Ashish Goyal and colleagues, informed by data collected from 25 patients hospitalized with COVID-19 in 4 different countries, offers some important new insights into the optimal timing of 4 different antiviral therapies to combat the disease. The results indicate that
Time crystals sound like something out of science fiction, but they may be the next major leap in quantum network research. A team based in Japan has proposed a method to use time crystals to simulate massive networks with very little computing power. They published their results on October 16 Science Advances.
The new model, created by computational social scientist Ivan Smirnov of HSE University, predicts the academic success of Russian high school students with an accuracy of 94%. The model generates its predictions based on users' distinctive vocabulary and speech patterns, and the predictions have strongly correlated with students' Unified State Exam (USE) scores.
Tiny movements in Earth's outermost layer may provide a Rosetta Stone for deciphering the physics and warning signs of big quakes. New algorithms that work a little like human vision are now detecting these long-hidden microquakes in the growing mountain of seismic data.
Among the loads to which the plasma vessel in a fusion device may be exposed, so-called edge localised modes are particularly undesirable. By computer simulations the origin and the course of this plasma-edge instability could now be explained for the first time in detail.
Researcher makes 'little data' act big through, the application of mathematical techniques normally used for time-series, to spatial processes. The study, 'An information-theoretic approach to study spatial dependencies in small datasets,' featured on the cover of Proceedings of the Royal Society.