Intelligent regulation of university faculty interdisciplinary collaboration networks based on complex network topology evolution and stochastic differential equations. [PDF]
Ren S.
europepmc +1 more source
Abstract Emulsion separation remains a persistent challenge in chemical and process industries due to the metastable nature of dispersed droplets. In gravity separators, the overall separation rate is governed by the formation of a densely packed zone (DPZ) of deforming and coalescing droplets that mediates between the dispersed and continuous phases ...
Andrei Zlobin +8 more
wiley +1 more source
Deep learning for adaptive chemotherapy: A DDPG-based approach to optimizing tumor-immune dynamics. [PDF]
Zhu W +7 more
europepmc +1 more source
A new drag and lift correlation for spherocylinders from fully resolved Immersed Boundary Method
Abstract Many industrial processes deal with non‐spherical particles, e.g., mineral mining and biomass conversion. It is crucial to understand the particles' hydrodynamics to control and optimize these processes. To extend the current state‐of‐the‐art from arrays of spherical particles to spherocylindrical particles, we performed extensive particle ...
A. H. Huijgen +4 more
wiley +1 more source
Information-Theoretic Dual Adaptive Control Revisited: Multivariable Extension with Applications to Fault-Tolerant Control. [PDF]
Yamé JJ.
europepmc +1 more source
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi +5 more
wiley +1 more source
Analysis of a household-scale model for the invasion of Wolbachia into a resident mosquito population. [PDF]
Barlow A, Penington S, Adams B.
europepmc +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Accelerated Stochastic Conjugate Gradient for a class of convex optimization. [PDF]
He L, Du Y.
europepmc +1 more source

