Results 141 to 150 of about 23,529 (258)

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 Simple Framework for Collaborative Development of Predictive Models Trained on Proprietary Data. [PDF]

J Chem Inf Model
Rodríguez-Belenguer P, Amberg A, Bringezu F, Frericks M, Hemmerich J, Monecke P, Oberhauser N, Trairatphisan P, Pastor M.   +8 more
europepmc   +1 more source

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

Advanced Intelligent Discovery, EarlyView.
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri, Leala Carbonneau, Eric M. Roberts, Alison W. Roberts, Candace H. Haigler, Alexey V. Gulyuk, Yaroslava G. Yingling   +6 more
wiley   +1 more source

Pictorial spacecrafts - the Ames' Glass. [PDF]

Iperception
Wijntjes MWA, Pinkse LME.
europepmc   +1 more source

Harnessing Phase Dynamics Across Diverse Frequencies with Multifrequency Oscillatory Neural Networks

Advanced Intelligent Discovery, EarlyView.
Oscillatory Neural Networks (ONNs) are an emerging computing paradigm that encodes information in the phases of coupled oscillators. Traditionally, ONNs have been investigated using homogeneous frequency oscillators. However, physical hardware implementations are inherently subject to frequency mismatches, device variability, and nonuniformities.
Nil Dinç, Filip Sabo, Aida Todri‐Sanial   +2 more
wiley   +1 more source

Biomass pyrolysis-derived aqueous phase as a laccase inducer in Pleurotus ostreatus: laccase production, properties, and applications. [PDF]

Bioresour Bioprocess
Rahic E, Hess CJ, Brown RC, Wen Z.
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Healing of ischemic injury in the retina. [PDF]

Sci Adv
Becker S, L'Ecuyer Morison Z, Allen J, Saeid S, Sturgis L, Adderley A, Koskelainen A, Vinberg F.   +7 more
europepmc   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

A Phase I Clinical Study and In Vivo Findings with PT-112, a Novel Immunogenic Cell Death-Inducing Small Molecule, in Relapsed or Refractory Multiple Myeloma. [PDF]

Clin Cancer Res
Kourelis T, Ailawadhi S, Vogl DT, Gibson SE, Sharik ME, Du MT, Ames TD, Yim CY, Baeck J, Price MR, Jimeno JM, Chesi M, Bergsagel PL.   +12 more
europepmc   +1 more source