Results 141 to 150 of about 8,002 (268)

Small disturbance oscillation suppression strategy for doubly-fed wind turbine based on joint control of LADRC and AQPR. [PDF]

Sci Rep
Li C, Liang C, Zhang J, Liu R, Huang C, Zhang S, Zhang S.   +6 more
europepmc   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Discovery of Small-Molecule Inhibitors of the KCNQ1/Kv7.1 Potassium Channel with Virtual Screening and Functional Validation in Electrophysiological Assays and KCNQ1-Knockout Neural Stem Cells. [PDF]

ACS Chem Neurosci
Alam KA, Martí-Solans J, Schall D, Kumar S, Iqbal SM, Teigen K, Berkel S, Mauceri D, Haug BE, Liin SI, Lynagh T, Martinez A, Haavik J.   +12 more
europepmc   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

An optimal multi-objective control architecture of PMSM drives. [PDF]

Sci Rep
Mohapatra BK, Sharma V, Bhowmik P, Mishra R.   +3 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 CNTFET based process variation resilient SRAM design for stable low power and half select free operation. [PDF]

Sci Rep
Haq SU, Aminzadeh A, Darabi A, Abbasian E, Shah OA, Sreenivasulu VB.   +5 more
europepmc   +1 more source

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

An AC voltage sensorless predictive current control method for grid-tied inverter with enhanced robustness against current DC offset. [PDF]

Sci Rep
Zhang G, Dong W, Meng L, Li J, Wang J.
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