Results 191 to 200 of about 472,892 (253)

Defining "critical" maternal health information for healthy lifestyle self-management in pregnancy: perspectives of pregnant women and obstetricians in China and Malaysia. [PDF]

BMC Pregnancy Childbirth
Yu X, Ramli SHB, Hamid HA, Norowi NM, Surip SS, Yu G, Zhang C, Liu Z.   +7 more
europepmc   +1 more source

Computational study of permeability in cardboard coating layers

AIChE Journal, EarlyView.
Abstract We develop a virtual material structure model based on a combination of tessellations and Gaussian random fields for a coating layer of paperboard used for packaging and designed to facilitate printing on the surface. To fit the model to tomographic image data acquired using combined focused ion beam and scanning electron microscopy (FIB‐SEM),
Sandra Barman, Torben Nilsson Pingel, Niklas Lorén, Tobias Gebäck, Eva Olsson, Aila Särkkä, Magnus Röding   +6 more
wiley   +1 more source

Energy-efficient path planning for Robotic Bulkhead Inspection using Residual-Enhanced UKF and Hierarchical MPC. [PDF]

PLoS One
Wang J, Li L, Gao R, Yang L.
europepmc   +1 more source

Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites

Advanced Intelligent Discovery, EarlyView.
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir, Miguel Hernández‐del‐Valle, Christina Schenk, De‐Yi Wang, Maciej Haranczyk   +4 more
wiley   +1 more source

A novel distributed gradient algorithm for composite constrained optimization over directed network. [PDF]

Sci Rep
Ou M, Zhang H, Yan Z, Yang Z, Ran H.
europepmc   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Advanced thermal management for next-generation engineering heat control using magnetized ternary nanofluid transport between two coaxial disks. [PDF]

Discov Nano
Alharbi AF, Areshi M, Mohammad F, Usman M.   +3 more
europepmc   +1 more source

Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

Advanced Intelligent Discovery, EarlyView.
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun, Tong Wu, Baian Chen, Zikang Li, Qiuyang Lu, Lu Lu, Hon Ho Wong, Cheuk Hei Chan, Bolong Huang   +8 more
wiley   +1 more source

Large-scale stochastic simulation of open quantum systems. [PDF]

Nat Commun
Sander A, Fröhlich M, Eigel M, Eisert J, Gelß P, Hintermüller M, Milbradt RM, Wille R, Mendl CB.   +8 more
europepmc   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source