What The Study Did: The findings of this simulation model suggest that the U.S. COVID-19 vaccination program was associated with an estimated reduction in total hospitalizations and deaths by nearly half during the first six months of 2021.
- JAMA Network Open
A new Northwestern Medicine study that analyzed 20 years of fatal opioid overdose data in adults 55 and older found that between 1999 and 2019, opioid-related overdose deaths increased exponentially in U.S. adults ages 55 and older, from 518 deaths in 1999 to 10,292 deaths in 2019: a 1,886% increase.
- JAMA Network Open
Quantum startups Pasqal and Qu&Co announce merger to leverage complementary solutions for global market
People with type 2 diabetes are living longer, with a new study suggesting that health management strategies developed in recent decades may be working.
- The Lancet Diabetes & Endocrinology
- US Centers for Disease Control and Prevention, Diabetes Australia, State Government of Victoria
The quest to discover how some people can compare or “match” the intricate details of faces, fingerprints and even firearms only by sight has taken a new, exciting twist.
- Psychonomic Bulletin & Review
Considerations of symmetry underpin the mathematical representations of the atomic configurations that are used by machine learning models to predict properties of various molecular structures. Though these models generally rely on a description of atom-centered environments, many of the quantities that are relevant for quantum mechanical calculations – notably the single-particle Hamiltonian Ĥ matrix when written in an atomic-orbital basis – aren’t associated with a single center, but rather with two or more atoms in the structure. In the paper “Equivariant representations for molecular Hamiltonians and N-center atomic-scale properties,” recently published in the Journal of Chemical Physics, NCCR MARVEL researchers discuss a family of structural descriptors that generalize atom-centered density correlation features to the N-centers case and show how it can be applied to efficiently learn the matrix elements of Ĥ. These N-centers features are fully equivariant in terms of both translations and rotations as well as in terms of permutations of the indices associated with the atoms and are therefore suitable for use in constructing symmetry-adapted machine-learning models of new classes of properties of molecules and materials.
- Chemical Physics
- NCCR MARVEL, Swiss National Science Foundation, European Research Council