Results 81 to 90 of about 325,176 (282)

A Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller

International Journal of Adaptive Control and Signal Processing, EarlyView.
Block Diagram of the Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller. ABSTRACT This article introduces a discrete‐time robust adaptive one‐sample‐ahead preview super‐twisting sliding mode controller. A stability analysis of the controller by Lyapunov criteria is developed to demonstrate its robustness in handling both ...
Guilherme Vieira Hollweg, Paulo Jefferson Dias de Oliveira Evald, Shivam Chaturvedi, Hilton Abilio Gründling, Rodrigo Varella Tambara, Wencong Su   +5 more
wiley   +1 more source

Paper 50: Biceps Autograft Patch Augmentation for Rotator Cuff Repair: The Effect of Point of Care Compression on Tenocyte Viability.

Orthopaedic Journal of Sports Medicine, 2023
Objectives: Augmentation of rotator cuff repair in patients at risk for retear has gained popularity. These techniques have generally consisted of allograft and xenograft patches.
Gregory Colbath, jeremy mercuri, Patrick Denard MD, John Tokish MD   +3 more
doaj   +1 more source

β‐Catenin/c‐Myc Axis Modulates Autophagy Response to Different Ammonia Concentrations

Advanced Biology, Volume 9, Issue 3, March 2025.
Ammonia, detoxified by the liver into urea and glutamine, impacts autophagy differently at varying levels. Low ammonia activates autophagy via c‐Myc and β‐catenin, while high levels suppress it. Using Huh7 cells and Spf‐ash mice, c‐Myc's role in cytoprotective autophagy is revealed, offering insights into hyperammonemia and potential therapeutic ...
S. Sergio, B. Spedicato, G. Corallo, A. Inguscio, M. Greco, D. Musarò, D. Vergara, A. F. Muro, G. De Sabbata, L. R. Soria, N. Brunetti Pierri, M. Maffia   +11 more
wiley   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Improving Photometric Redshift Estimates with Training Sample Augmentation

The Astrophysical Journal Letters
Large imaging surveys will rely on photometric redshifts (photo- z 's), which are typically estimated through machine-learning methods. Currently planned spectroscopic surveys will not be deep enough to produce a representative training sample for Legacy
Irene Moskowitz, Eric Gawiser, John Franklin Crenshaw, Brett H. Andrews, Alex I. Malz, Samuel Schmidt, The LSST Dark Energy Science Collaboration   +6 more
doaj   +1 more source

Parkinson’s Disease Detection Based on Spectrogram-Deep Convolutional Generative Adversarial Network Sample Augmentation

IEEE Access, 2020
As an essential biological feature of human beings, voiceprint is increasingly used in medical research and diagnosis, especially in identifying Parkinson's Disease (PD). This paper proposes a Spectrogram Deep Convolutional Generative Adversarial Network
Zhi-Jing Xu, Rong-Fei Wang, Juan Wang, Da-Hai Yu   +3 more
doaj   +1 more source

How to Fine-tune Models with Few Samples: Update, Data Augmentation, and Test-time Augmentation

, 2022
Most of the recent few-shot learning (FSL) algorithms are based on transfer learning, where a model is pre-trained using a large amount of source data, and the pre-trained model is fine-tuned using a small amount of target data. In transfer learning-based FSL, sophisticated pre-training methods have been widely studied for universal representation ...
Kim, Yujin, Oh, Jaehoon, Kim, Sungnyun, Yun, Se-Young   +3 more
openaire   +2 more sources

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Dimensionality-modulated generative AI for safe biomedical dataset augmentation

iScience
Summary: Generative AI can expand small biomedical datasets but may amplify noise and distort statistical relationships. We developed genESOM, a framework integrating an error control system into a generative AI method based on emergent self-organizing ...
Jörn Lötsch, André Himmelspach, Dario Kringel   +2 more
doaj   +1 more source

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

Advanced Engineering Materials, EarlyView.
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell, Martha Leach, Hongtao Song, Carolyn Seepersad   +3 more
wiley   +1 more source