Results 141 to 150 of about 55,506 (254)
Spatiotemporal Machine Learning Approaches for Atmospheric Composition Emulation in NASA GISS ModelE
Abstract Earth System Models (ESMs) rely on parameterizations to represent sub‐grid scale processes that cannot be explicitly resolved at typical model resolutions. However, maintaining full coupling between these parameterizations and other model components creates substantial computational demands. This challenge is particularly acute for atmospheric
Mohammad H. Erfani +5 more
wiley +1 more source
Eruption Source Parameters in Volcanic Plume Modeling: Advances, Challenges, and Future Directions
Abstract Accurately predicting the atmospheric dispersion of volcanic ash and gases is crucial for both scientific understanding and hazard mitigation. Estimating Eruption Source Parameters (ESP), such as mass eruption rate, plume height, duration, and particle size distribution and properties, remains challenging due to the complex nature of volcanic ...
A. Costa +4 more
wiley +1 more source
Exploring Lived Experiences of Men Diagnosed With Prostate Cancer in Oman: A Qualitative Study
ABSTRACT Background Life after prostate cancer treatment may extend across decades; however, qualitative evidence describing how men in Oman navigate treatment sequelae, disclosure, family involvement, and religious coping remains limited. This study explored the lived experiences of Omani men who had completed primary therapy for prostate cancer ...
Khalood Al‐Abri +6 more
wiley +1 more source
Toward Predictive Theory in Single‐Atom Catalysis
A lifecycle‐oriented framework reframes modeling in single‐atom catalysis. By combining ensemble‐based descriptions with explicit validation against experimental observables, the approach defines the scope of theory across catalyst synthesis, activity, stability, and safety, clarifying where quantitative insight is possible and where interpretation ...
Andrea Ruiz‐Ferrando +3 more
wiley +1 more source
The tribo‐hygroelectric generator (THEG) consists of a water‐infused porous cellulose layer between asymmetric Al and Cu electrodes. Water adsorption induces a hydrogen‐bonded network within the cellulose and enhances charge transport, while mechanical deformation increases charge generation.
Quang Tan Nguyen +6 more
wiley +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Assessing Flight Angle and Rotor Speed Effects on Drying Efficiency and Power Consumption of the Centrifugal Dryer of Pelletizing Systems. [PDF]
Aali M +3 more
europepmc +1 more source
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella +5 more
wiley +1 more source
Coupling finite volume-lattice Boltzmann methods for advanced heat transfer simulations. [PDF]
Zhou Y, De Rosis A, Revell A.
europepmc +1 more source
Abstract ChatGPT and related technologies have revived an old issue in information science (IS) concerning information retrieval (IR) versus document retrieval. Since 1950, the term IR has primarily been used as a misnomer for document retrieval. This problematic terminology reflects a desire to go beyond documents and provide, in response to user ...
Birger Hjørland
wiley +1 more source

