Results 131 to 140 of about 60,047 (288)

The mediating role of coping styles between physical activity and sense of meaning in life among Chinese college students

Scientific Reports
Many college students may face a lost or diminished sense of meaning in life (SML) in a rapidly changing and highly competitive society. This study aimed to investigate the relationship between physical activity (PA) and college students’ SML, as well as
Chaowei Zhang, Jingyu Zhang, Wenqi Lin
doaj   +1 more source

UAV Airborne Network Intrusion Detection Method Based on Improved Stratified Sampling and Ensemble Learning

Drones
UAV airborne network intrusion detection faces challenges due to highly imbalanced datasets, where normal samples significantly outnumber intrusion instances.
Lin Lin, Hongjuan Ge, Yuefei Zhou, Runzong Shangguan   +3 more
doaj   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +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

Model accuracy and data heterogeneity shape uncertainty quantification in machine learning interatomic potentials

Machine Learning: Science and Technology
Machine learning interatomic potentials (MLIPs) enable accurate atomistic modeling, but reliable uncertainty quantification (UQ) remains elusive. In this study, we investigate two UQ strategies, ensemble learning and D-optimality, within the atomic ...
Fei Shuang, Zixiong Wei, Kai Liu, Wei Gao, Poulumi Dey   +4 more
doaj   +1 more source

Laser Powder Bed Fusion of Alumina: Effects of Scanning Strategies on External and Internal Defects

Advanced Engineering Materials, EarlyView.
This study investigates how scanning strategies affect pure alumina in laser powder bed fusion. Linear 45° scanning yields uniform surfaces but high porosity, while the island‐concentric strategy provides higher density with through‐holes favorable for infiltration. Findings highlight pathways toward optimizing defect‐free alumina parts.
Mohamed Abdelmoula, Gökhan Küçüktürk, Duran Kaya, David Grossin, Christophe Tenailleau, Benjamin Duployer, Enrique Juste, Fabrice Petit   +7 more
wiley   +1 more source

Low‐Cost, Large‐Scale Nanoporous Metals by Mechanical Alloying, Oxide Reduction, and Dealloying of Powders

Advanced Engineering Materials, EarlyView.
Powder metal processing provides scalable advantages in nanoporous (np) metal development. Mechanical alloying is used to produce unique precursors for hybrid nanopore formation by oxide reduction and dealloying. As demonstrated in np Ag, this approach improves process efficiency while promoting smaller ligaments and larger pores, both of which are ...
Mark A. Atwater, Oliver A. Fowler
wiley   +1 more source

On the Lightweight Potential of Laser Additive Manufactured NiTi Triply Periodic Minimal Sheet Lattices

Advanced Engineering Materials, EarlyView.
This study explores the lightweight potential of laser additive‐manufactured NiTi triply periodic minimal surface sheet lattices. It systematically investigates the effects of relative density and unit cell size on surface quality, deformation recovery, compression behavior, and energy absorption.
Haoming Mo, Shuo Qu, Shiming Gao, Xu Song   +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

Air‐Pressure–Actuated Vibroacoustic Metamaterial With Tunable Bandgap: Design, Modeling, and Characterization

Advanced Engineering Materials, EarlyView.
This article presents the design, modeling, and characterization of air‐pressure–actuated programmable vibroacoustic metamaterials (PVAMM). The study focuses on leveraging air pressure to dynamically tune resonance frequencies for effective noise attenuation.
William Kaal, Michael M. Becker, Sarah C. L. Fischer   +2 more
wiley   +1 more source