Northwestern University and University of California, Los Angeles (UCLA) scientists have developed a new process-based ...

For decades, medium-range weather forecasting—predicting conditions 1 to 5 days ahead—has relied heavily on traditional ...

Mathematics may not be the first thing people associate with Alzheimer’s disease research. But for Pedro Maia, an assistant ...

NEW YORK, July 18, 2025 /PRNewswire/ -- The Financial Modeling & Valuation Analyst (FMVA®) certification by Corporate Finance ...

Achieving high efficiency, long operational lifetime, and excellent color purity is essential for organic light-emitting ...

In an era where artificial intelligence, autonomous vehicles, and high-performance computing push the boundaries of ...

If you ever stumble upon the mysterious code 297.2/234 and wondered what on earth it means, you’re not alone. This article, ...

While the open-source Seismometer tool does not provide ROI metrics, it can surface insights on an algorithm's quality and utility, say early users at Michigan Medicine.

A study by Squake and tClara found significant discrepancies among six aviation carbon emission models, with variations up to ...

Sigmetrix champions early-stage tolerance analysis to help engineers create manufacturable, high performance products without ...

A Tribune reporter and data nerd went looking for a smarter way to evaluate and draft NBA players. From Cooper Flagg to a few under-the-radar risers, here's what he found.

Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the fly—a step toward building AI that continually improves itself.