Results 241 to 250 of about 370,928 (312)

Beyond Exponential Decay: How Biphasic and Delayed Decay Dynamics Shape Marine eDNA Dispersal. [PDF]

Ecol Evol
Zanni MY, Trenkel VM, Albouy C, Vaz AC, Paris CB, Faillettaz R.   +5 more
europepmc   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Metric, edge-metric, mixed-metric, and fault-tolerant metric dimensions of geometric networks with potential applications. [PDF]

Sci Rep
Hayat S, Naeem R, Afzal Siddiqui HM, Riaz A, Imran M, Belay MB, Klai Z.   +6 more
europepmc   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Materials Database from All-electron Hybrid Functional DFT Calculations. [PDF]

Sci Data
Nair AS, Foppa L, Scheffler M.
europepmc   +1 more source

FMA-MADDPG: Constrained Multi-Agent Resource Optimization with Channel Prediction in 6G Non-Terrestrial Networks. [PDF]

Sensors (Basel)
Yang C, Song K, Bai J, Li C, Zhao Y, Xiao Z, Sun Y.   +6 more
europepmc   +1 more source

A Study of Deep Clustering in Spike Sorting. [PDF]

Neuroinformatics
Ardelean ER, Portase RL.
europepmc   +1 more source

Data-driven acceleration of mixed-integer bilinear programs: a comparative study for robot motion planning. [PDF]

Front Robot AI
Lin X.
europepmc   +1 more source