Results 101 to 110 of about 4,294 (215)

Bias Correction Can Strongly Shape California's Projected Megaflood Risk

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 16, 28 August 2026.
Abstract A California “megaflood”—a weeks‐long cluster of storms with centuries‐long return times—would be catastrophic, yet its timing and magnitude under climate change remains uncertain. A central source of uncertainty is whether Earth System Model boundary conditions should be bias corrected before dynamical downscaling.
Stefan Rahimi, Lei Huang, Chad W. Thackeray, Mark D. Risser, Emilie Tarouilly, Jesse Norris, Alan Rhoades, Benjamin Bass, Alex Hall, Zachary J. Lebo, Weichen Liu, Flavio Lehner, Tim Corrie, Ankur Dixit   +13 more
wiley   +1 more source

Open educational resources for distributed hands-on teaching in molecular biology. [PDF]

PLoS One
Cerda A, Aravena A, Zapata V, Arce A, Araya W, Gallardo D, Aviles J, Quero F, Nuñez I, Matute T, Navarro F, Ferrando V, Blanco M, Velozo S, Rodriguez S, Aguilera S, Chateau F, Olivares-Donoso R, Molloy JC, Aidelberg G, Lindner AB, Castro F, Cremades P, Ramirez-Sarmiento C, Federici F.   +24 more
europepmc   +1 more source

Self‐Similar Blowup for the Cubic Schrödinger Equation

Communications on Pure and Applied Mathematics, Volume 79, Issue 8, Page 1831-1918, August 2026.
ABSTRACT We give a rigorous proof for the existence of a finite‐energy, self‐similar solution to the focusing cubic Schrödinger equation in three spatial dimensions. The proof is computer‐assisted and relies on a fixed point argument that shows the existence of a solution in the vicinity of a numerically constructed approximation.
Roland Donninger, Birgit Schörkhuber
wiley   +1 more source

Genus-wide Homologous Recombination of Tail Fibers Maintains Tailocin Diversity in Pectobacterium. [PDF]

Genome Biol Evol
Pardeshi LA, Kupczok A, de Ridder D, Smit S, van der Lee TAJ.   +4 more
europepmc   +1 more source

Gradient‐Free Online Learning of Subgrid‐Scale Dynamics With Neural Emulators

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.
Abstract In this paper, we propose a generic algorithm to train machine learning‐based subgrid parametrizations online, that is, with a posteriori loss functions, but for non‐differentiable numerical solvers. The proposed approach leverages a neural emulator to approximate the reduced state‐space solver, which is then used to allow gradient propagation
H. Frezat, R. Fablet, G. Balarac, J. Le Sommer   +3 more
wiley   +1 more source

Supervised Machine Learning Approach to Iron Meteorite Classification Using Random Forest: A Predictive Model to Classify Ungrouped Irons

Earth and Space Science, Volume 13, Issue 8, August 2026.
Abstract Iron meteorites provide insight into the formation processes of planetary cores from the early Solar System. Through further classifying individual irons into specific groups, which are assumed to represent a common parent body, greater information can be yielded into the formation processes of those bodies.
A. F. Rogers, L. Doucet, L. V. Forman, K. Rankenburg, G. K. Benedix   +4 more
wiley   +1 more source

Ten simple rules for making biomedical data resources accessible. [PDF]

PLoS Comput Biol
Smits TC, Weru L, Gehlenborg N, L'Yi S.
europepmc   +1 more source

Transformation of Hermeneutics in Heidegger's Black Notebooks

Kritike: An Online Journal of Philosophy, 2023
openaire   +1 more source

Replacing Tunable Parameters in Weather and Climate Models With State‐Dependent Functions Using Reinforcement Learning

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.
Abstract Weather and climate models rely on parameterizations to represent unresolved sub‐grid processes. Traditional schemes rely on fixed coefficients that are weakly constrained and tuned offline, contributing to persistent biases that limit their ability to adapt to underlying physics.
Pritthijit Nath, Sebastian Schemm, Henry Moss, Peter Haynes, Emily Shuckburgh, Mark J. Webb   +5 more
wiley   +1 more source

Real‐Time Prediction of Two Geomagnetic Storms Using Solar Orbiter as a Far Upstream Solar Wind Monitor

Space Weather, Volume 24, Issue 8, August 2026.
Abstract We present the first real‐time predictions of coronal mass ejection (CME) magnetic structure and resulting geomagnetic impact at Earth for two events using far‐upstream observations from Solar Orbiter during March 2024. While our approach assumes idealized conditions for CME propagation and scaling, in situ magnetic field data from upstream ...
Emma E. Davies, Eva Weiler, Christian Möstl, Satabdwa Majumdar, Hannah T. Rüdisser, Timothy S. Horbury, Helen O'Brien, Jean Morris, Alastair Crabtree   +8 more
wiley   +1 more source