Results 221 to 230 of about 1,043 (255)

Physics‐Informed Generative Machine Learning for Designing Crack‐Free γ′‐Strengthened Ni‐Based Superalloys for Laser Powder Bed Fusion

Materials Genome Engineering Advances, EarlyView.
This research proposes a physics‐informed generative machine learning framework to design SHA800, a crack‐free γ′‐strengthened nickel‐based superalloy for laser powder bed fusion, achieving a 43% γ′ volume fraction and 587 HV0.2 hardness. ABSTRACT Fabricating γ′‐strengthened nickel‐based superalloys via laser powder bed fusion (LPBF) faces significant ...
Kai Guo, Dongwei Guan, Tao Hu, Yaqing Hou, Xiaoqun Li, Zhongnan Bi, Songzhe Xu, Hao Yu, Wei Xu, Weidong Xuan, Chaoyue Chen, Zhongming Ren   +11 more
wiley   +1 more source

Accelerated land surface greening caused by earlier permafrost thawing. [PDF]

Nat Commun
Hua H, Wang J, Zohner CM, Peñuelas J, Ran Y, Wu C.   +5 more
europepmc   +1 more source

Symbolic Regression‐Guided Feature Engineering for Predicting Magnetization in Cu‐Based Alloys Under Data‐Scarce Conditions

Materials Genome Engineering Advances, EarlyView.
A symbolic regression approach (SISSO) with physics‐informed feature engineering achieves high‐accuracy prediction of magnetic properties in Cu‐based alloys under data‐scarce conditions. The framework offers an interpretable and transferable strategy for accelerated alloy design.
Buyang Ma, Jiejie Li, Qiuju Zhang, Fenghua Chen, Bo Li, Ziqi Tian, Liang Chen   +6 more
wiley   +1 more source

Opening the Black Box of Nonprofit Reputation and Volunteer Attraction With Supervised Machine Learning

Nonprofit Management and Leadership, EarlyView.
ABSTRACT With the aim to explore the potential of machine learning for nonprofit research, this article contrasts traditional linear regression with four contemporary supervised machine learning approaches. Concretely, we predict (1) reputation ratings and (2) the total number of volunteers for 4021 non‐profit organizations in the U.S.
Moritz Schmid, Hannes Lampe, Jurgen Willems   +2 more
wiley   +1 more source

Stem microanatomical phenomic uncovers a potential role for ZmLSM2 in regulating maize stem bending strength. [PDF]

J Integr Plant Biol
Zhang Y, Wang Z, Du J, Li J, Huang G, Zhao Y, Wang Y, Men Q, Guo M, Zhang M, Lu X, Wang C, Liu Q, Guo X, Zhao C.   +14 more
europepmc   +1 more source

Influence of Thermal Cycling on Friction, Wear, and Damage Evolution of Fused Deposition Modeling of 3D‐Printed Glass Fiber Reinforced Polylactic Acid Composites

Polymer Composites, EarlyView.
Schematic illustration of the experimental procedure of the specimens. ABSTRACT This research work investigated the effect of the cyclic thermo‐hygrometric aging regime between −20°C and +40°C with 0–400 cycles on the reciprocating tribological properties of fused deposition modeling (FDM) printed polylactic acid (PLA) and the same material reinforced ...
Sinan Fidan, Satılmış Ürgün, Nevin Gamze Karsli, Taner Yılmaz, Mustafa Özgür Bora, Mehmet İskender Özsoy   +5 more
wiley   +1 more source

A principal-weighted penalized regression model and its application in economic modeling. [PDF]

J Appl Stat
Sun M, Xu M.
europepmc   +1 more source

Predicting brain age in children aged 2–6 years with autism spectrum disorders using routine T1‐ and T2‐weighted magnetic resonance imaging

Pediatric Investigation, EarlyView.
The routine magnetic resonance imaging‐based model accurately predicted brain age in children aged 2–6. Children with autism spectrum disorder (ASD) exhibited maturational delays at ages 3–5, shifting toward accelerated aging by age 5–6. This exploratory result highlights the dynamic, age‐related developmental heterogeneity in ASD.
Zunying Hu, Rongjia Xiang, Huanyu Luo, Di Hu, Huiying Kang, Huanjie Li, Xin Fan, Yun Peng   +7 more
wiley   +1 more source

Simulation study to evaluate when Plasmode simulation is superior to parametric simulation in comparing classification methods on high-dimensional data. [PDF]

PLoS One
Stolte M, Schreck N, Slynko A, Saadati M, Benner A, Rahnenführer J, Bommert A, topic group “High-dimensional data” (TG9) of the STRATOS Initiative.   +7 more
europepmc   +1 more source

TSSS: A Novel Triangulated Spherical Spline Smoothing for Surface-Based Data. [PDF]

J Nonparametr Stat
Gu Z, Yu S, Wang G, Lai MJ, Wang L.
europepmc   +1 more source