Results 51 to 60 of about 80,384 (191)
Data‐Driven Distributed Safe Control Design for Multi‐Agent Systems
This paper presents a data‐driven control barrier function (CBF) technique for ensuring safe control of multi‐agent systems (MASs) with uncertain linear dynamics. A data‐driven quadratic programming (QP) optimization is first developed for CBF‐based safe control of single‐agent systems using a nonlinear controller. This approach is then extended to the
Marjan Khaledi, Bahare Kiumarsi
wiley +1 more source
Dengue infection alters mosquito flight behavior, enabling detection using machine learning classifiers. This study analyzes 3D flight trajectories and evaluates multiple models, showing that longer sequence lengths improve classification performance.
Nouman Javed +3 more
wiley +1 more source
Infrared (IR) light evokes distinct calcium and water transport responses in astrocytes, depending on stimulation duration and protocol. This study uses widefield imaging and pharmacology to reveal differential engagement of astroglial signaling pathways.
Wilson R. Adams +7 more
wiley +1 more source
Amide local anesthetics (LA) affect tumor burden in various preclinical studies, possibly via their anti‐inflammatory properties. However, a translation into clinical evidence is still lacking. The current study demonstrates that LA ‐ even at clinically relevant concentrations – exert a strong anti‐tumoral effect in a complex ex vivo model patient ...
Juliane Krömer +8 more
wiley +1 more source
Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani +2 more
wiley +1 more source
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi +4 more
wiley +1 more source
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source
3D‐Printed Architected Material for the Generation of Foam‐Based Protective Equipment
This study investigates 3D‐printed architected structures as alternatives to traditional foams in protective gear. It focuses on customizing impact strength and damping through design and manufacturing integration. Testing shows these structures outperform conventional foams, offering enhanced customizability, lower weight, and tunable performance ...
Ali Zolfagharian +5 more
wiley +1 more source
Primary phases and a fatigue crack are studied in a forged blank of an aluminum alloy using synchrotron and laboratory X‐ray computed tomography. To image the crack, the fatigue test is interrupted, and a static tensile load is applied to open the crack.
Jakob Schröder +6 more
wiley +1 more source

