Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

A new AI model learns to "think" longer on hard problems, achieving more robust reasoning and better generalization to novel, unseen tasks.

Seabed-origin oil spills pose distinct challenges in marine pollution management due to their complex transport dynamics and ...

A deep generative model based on a variational autoencoder (VAE), conditioned simultaneously by two target properties, is developed to inverse design stable magnetic materials. The structure of the ...

Dual-Stage Graph Instruction Tuning. The dual-stage graph instruction tuning paradigm proposed in this work builds upon the concept of instruction tuning, which has been recently introduced to enhance ...

Parameter Estimation of Photovoltaic Models Based on Improvement of Moutain Gazelle Optimizer Algorithm Provisionally accepted Diaa Salama 1* Ala Saleh Alluhaidan 2 Walaa H. Elashmawi 3 Ibrahim Shawky ...

The proposed method combines dynamic learner models, real-time performance tracking, and predictive analytics, allowing for a highly adaptive educational system. By employing reinforcement learning ...

Mt-KaHyPar (Multi-Threaded Karlsruhe Hypergraph Partitioner) is a shared-memory multilevel graph and hypergraph partitioner equipped with parallel implementations of techniques used in the best ...

Algorithm streamlines vascular system design for 3D printed hearts by Laura Castañón, Stanford University edited by Robert Egan Editors' notes ...

Mathematical programming models rely on familiar concepts of nonlinear optimization and are generally the most accessible. Network models (disjunctive graphs) are best suited to the development of ...