Results 101 to 110 of about 6,244,533 (247)
As a result of the calls for reform in mathematics education and the ever-changing nature of mathematics, today's teachers face the challenge of teaching unfamiliar content in ways that are equally unfamiliar.
Swenson, Karen A.
core +3 more sources
Anisotropic Memristive Switching in NbOCl2 Enabled by Directional Oxygen Ion Migration
This study investigates strongly orientation‐dependent memristive switching in anisotropic NbOCl2, observed exclusively along the in‐plane c‐axis. The switching originates from direction‐selective oxygen‐ion migration and vacancy propagation that modulate the Pd/NbOCl2 Schottky barrier, enabling short‐term plasticity.
Caokun Wang +6 more
wiley +1 more source
A Generative Neuro‐Symbolic AI for Protein Sequence Design
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne +12 more
wiley +1 more source
The graphics calculator and the curriculum: The case of probability [PDF]
A graphics calculator may influence the curriculum in three kinds of ways: offering new opportunities for teaching and learning, providing new ways of performing mathematical procedures, and suggesting changes of emphasis and content in the curriculum ...
Kissane, B.
core
Department of Applied Mathematics and Statistics newsletter, September 18, 2023
Newsletter of the Department of Applied Mathematics and Statistics at Colorado School of ...
core
Using a minimal set of experimentally labeled antimicrobial and non‐antimicrobial peptides, we reconstruct the effective lipid composition of a pathogenic membrane ‐demonstrated at the example of bacterial membranes‐ through a physics‐based evolutionary molecular dynamics (Evo‐MD) approach. Optimization based on peptide insertion reveals broad‐spectrum
Maximilian Krebs, Herre Jelger Risselada
wiley +1 more source
A latent diffusion‐based framework is proposed for designing functionally graded metamaterials with perfect connectivity. By integrating vector‐quantized latent representations with mechanistic guidance, the framework enables accurate inverse design toward target elastic properties.
Jongbin Yu, Dosung Lee, Namjung Kim
wiley +1 more source
The Mathematical Theory of Probabilities. [PDF]
L. I., Arne Fisher
openaire +1 more source
Second course of a two-semester sequence on the fundamental concepts of elementary mathematics: 2- and 3-dimensional geometry, measurement, probability, statistics, linear and non-linear functions.
Mathematics
core
CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model
In this work, CoSP (contrastive multi‐state pretrain), an intelligent inverse design method for reconfigurable metamaterials based on a contrastive pretrained large language model, is proposed. Numerical experiments demonstrate that CoSP can design reconfigurable metamaterial structures for multi‐state, multi‐band optical responses, showing great ...
Shujie Yang +4 more
wiley +1 more source

