This has prompted researchers to revisit a more fundamental question: As rarefaction effects become more significant and the temporal and spatial scales of interest shrink, are the Navier–Stokes (NS) ...

How can the tiniest particles and the vast structure of the universe be explained using the same kind of mathematics? This puzzle is the focus of recent research by mathematicians Claudia Fevola ...

Stemflow hydrodynamics offers rich physics that seeks to describe water and matter cycling within the ...

Andy recommends favorite resources for basic op amp circuits and includes a portion of TI's AN-20. Test your knowledge with ...

The view that MSTR underperforms Bitcoin is a product of investor biases and a disregard for longer-term performance metrics.

According to the matrix differentiation property, the system of linear equations for the optimized first-order derivative condition of Equation 11 is equivalent as: ...

A study by University of Hawaiʻi researchers is advancing how we learn the laws that govern complex systems—from ...

We're often told it is "unscientific" or "meaningless" to ask what happened before the Big Bang. But a new paper by FQxI ...

A mathematician at Carnegie Mellon University has developed an easier way to solve quadratic equations. The mathematician hopes this method will help students avoid memorizing obtuse formulas. His ...

The study presents valuable theoretical insights by attempting to classify pattern-forming gene subnetworks and exploring their potential mechanisms. However, the results are incomplete, as they rely ...

This study presents valuable computational findings on the neural basis of learning new motor memories and the savings using recurrent neural networks. The evidence supporting the claims of the ...

P. Deift, X. Zhou, A Steepest Descent Method for Oscillatory Riemann–Hilbert Problems. Asymptotics for the MKdV Equation, Annals of Mathematics, Vol. 137, No. 2 ...