Results 141 to 150 of about 2,854,398 (286)

Single‐Cell Dissection of Microglial Dysfunction in Diabetes‐Associated Neurodegenerative Vulnerability

Advanced Science, EarlyView.
Using single‐cell transcriptomic and epigenomic profiling, researchers mapped microglial dysfunction across the lifespan of db/db mice. The authors uncovered a nonlinear microglial remodeling featuring early inflammatory priming, a mid‐stage transcriptional inflection, and late dysfunction.
Jizhou Zhang, Tsz Kwan Yau, Joyce Tse, Tsz Ho Li, Dongjie Hu, Yong Juan Zhao, Ting‐Fung Chan   +6 more
wiley   +1 more source

Friend, Not Foe: Lowered Tissue Reactivity to Long‐Term Polyimide Implants

Advanced Science, EarlyView.
The choice of optimal neural probe designs remains a major challenge in the field of neurotechnology. This study investigated the biocompatibility of several probe variations, including material, thickness, width, and implantation strategy. It highlights the clear advantage of soft polyimide probes over stiff silicon probes for better device ...
Corinne Orlemann, Laura M. De Santis, Paul Neering, Christian Boehler, Kirti Sharma, Arno Aarts, Tobias Holzhammer, Rik J. J. van Daal, Patrick Ruther, Maria Asplund, Roxana N. Kooijmans, Pieter R. Roelfsema   +11 more
wiley   +1 more source

Exploring Symbolic Regression and Genetic Algorithms for Astronomical Object Classification

The Open Journal of Astrophysics
This study explores the use of symbolic regression (SR) combined with genetic algorithms (GA) to classify astronomical objects. Using the SDSS17 dataset from Kaggle, which includes 100,000 observations of stars, galaxies, and quasars, we applied SR to 10%
Fabio Ricardo Llorella, José Antonio Cebrian   +1 more
doaj   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

SPINEX-symbolic regression: similarity-based symbolic regression with explainable neighbors exploration

The Journal of Supercomputing
Abstract This article introduces a new symbolic regression algorithm based on the SPINEX (similarity-based predictions with explainable neighbors exploration) family. This new algorithm (SPINEX_SymbolicRegression) adopts a similarity-based approach to identifying high-merit expressions that satisfy accuracy- and structural similarity metrics.
Mohannad Z. Naser, Ahmad Z. Naser
openaire   +2 more sources

Scalable Neural Symbolic Regression using Control Variables [PDF]

Symbolic regression (SR) is a powerful technique for discovering the analytical mathematical expression from data, finding various applications in natural sciences due to its good interpretability of results.
Qi, Hairong, Zhao, Hongjue, Chu, Xieting, Xu, Enze, Chen, Minghan, Shao, Huajie   +5 more
core   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source

Construction of Sabatier Volcanoes for CO2 Hydrogenation to C1‐2 Oxygenates Using Data‐Efficient Machine Learning

Advanced Science, EarlyView.
A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
wiley   +1 more source

A Generative Neuro‐Symbolic AI for Protein Sequence Design

Advanced Science, EarlyView.
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, Delphine Dessaux, Samuel Buchet, Lucie Barthe, Liza Ammar‐Khodja, Bessam Azizi, Valentin Durante, Gianluca Cioci, Simon de Givry, Alain Roussel, Luis F. Garcia‐Alles, Thomas Schiex, Sophie Barbe   +12 more
wiley   +1 more source

Machine Learning‐Driven Design of Multicomponent Bone Inorganic Matrix Mimicking Scaffolds for Osteogenesis Enhanced by Neurogenesis

Advanced Science, EarlyView.
Schematic illustration of development of experimental datasets and algorithm models, screening and preparation of the scaffolds and their applications in vivo. ABSTRACT Bone defects require materials with osteogenic, neurogenic, and angiogenic activity, yet designing such materials within high‐dimensional compositional spaces remains challenging. Here,
Kunlu Lin, Ying Yang, Chuyao Zhou, Hanyue Mao, Zhiquan Zhang, Libangxi Liu, Xiaoying Yu, Haoming Liu, Long Liu, Xiaoyan Wang   +9 more
wiley   +1 more source