Results 101 to 110 of about 374,822 (264)

Shortcutting from self-motion signals reveals a cognitive map in mice

eLife
Animals navigate by learning the spatial layout of their environment. We investigated spatial learning of mice in an open maze where food was hidden in one of a hundred holes.
Jiayun Xu, Mauricio Girardi-Schappo, Jean-Claude Beique, André Longtin, Leonard Maler   +4 more
doaj   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

Prefrontal serotonin depletion delays reversal learning and increases theta synchronization of the infralimbic-prelimbic-orbitofrontal prefrontal cortex circuit

Frontiers in Pharmacology
IntroductionPrefrontal serotonin plays a role in the expression of flexible behavior during reversal learning tasks as its depletion delays reversal learning.
Yoana Estrada-Reyes, Yoana Estrada-Reyes, José Miguel Cervantes-Alfaro, Miguel Ángel López-Vázquez, María Esther Olvera-Cortés   +4 more
doaj   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

Advanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky, Marcelo Sallese, Leander Kläber, Clemens Kuhn, Keming Du, Andrés Fabián Lasagni   +5 more
wiley   +1 more source

Zein‐Based Adhesives: Sustainable Extraction and Application in Bioadhesive Technologies

Advanced Engineering Materials, EarlyView.
Zein is extracted from corn gluten meal using a simple and scalable process with high yield (~90%). The resulting protein is applied in bioadhesives modified with Ca2+ and Fe3+ ions, exhibiting substrate‐dependent adhesion. The findings demonstrate competitive bonding performance and highlight the role of ionic interactions in tuning adhesion ...
Paula Bertolino Sanvezzo, Daniela Winsley Valereto Friozi, Vinícius de Oliveira, Marcia Cristina Branciforti   +3 more
wiley   +1 more source

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

Advanced Engineering Materials, EarlyView.
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell, Martha Leach, Hongtao Song, Carolyn Seepersad   +3 more
wiley   +1 more source

Qualitative Analysis of the Student Perspectives on AnaVu – A Three-dimensional Stereoscopic Neuroanatomy Visualization Tool

National Journal of Clinical Anatomy
Background: Prior research by the authors studied the objective impact on medical students’ academic course, the perceived cognitive load, quantified subjective feedback while teaching using AnaVu, a low resource stereoscopic projection system.
Nithin Kadakampallil Raju, Doris George Yohannan, Aswathy Maria Oommen, Amruth S. Kumar, S. Devanand, U. T. Minha Resivi, Navya Sajan, Neha Elizabeth Thomas, Nasreen Anzer, Bejoy Thomas, Jayadevan Enakshy Rajan, Umesan Kannanvilakom Govindapillai, Pawan Harish, Tirur Raman Kapilamoorthy, Chandrasekharan Kesavadas, Jayanthi Sivaswamy   +15 more
doaj   +1 more source