Myths, Machines, and Ancient Dreams of Technology, explored ancient myths and folklore about creating automation, artificial ...
A new computational breakthrough is giving scientists a clearer view into how dark matter structures evolve. Dark matter has ...
Quantum spin liquids are exotic states of matter in which spins (i.e., the intrinsic angular momentum of electrons) do not ...
Three 17-year-old Moravian Academy students founded a company that uses AI-powered cameras to alert construction companies to ...
Radiative cooling technologies scatter heat and light into space, which could cut air-conditioning demand and keep people ...
An interactive toolbox for standardizing, validating, simulating, reducing, and exploring detailed biophysical models that can be used to reveal how morpho-electric properties map to dendritic and ...
Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...
Ling, A. and Pandya, N. (2025) Quantum Computing and Quantum Sensing: A Pedagogical Introduction to Emerging Quantum ...
University of Illinois Urbana-Champaign corn breeders know profitability is about more than yield. By tweaking kernel composition ...
Ripples maintain time-locked occurrence across the septo-temporal axis and hemispheres while showing local phase coupling, revealing a dual mode of synchrony in CA1 network dynamics.
Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
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