Results 121 to 130 of about 27,144 (290)

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

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

Advanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah, Muhammad Zulqarnain Zeb, Muhammad Husnain Zeb, Babar Shabbir   +3 more
wiley   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +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

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

Advanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

Robust and Minimum Norm Pole Assignment with Periodic State Feedback [PDF]

, 2000
A computational approach is proposed to solve the minimum norm or robust pole assignment problem for linear periodic discrete-time systems. The proposed approach uses a periodic Sylvester-equation-based parametrization of the periodic pole assignment ...
Varga, A.
core  

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai, Yefeng Yang, Tao Huang, Boyang Li   +3 more
wiley   +1 more source

Sound‐Based Assembly of Magnetically Actuated Soft Robots Toward Enhanced Release of Extracellular Vesicles

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Magnetic soft robots offer promise in biomedicine due to their wireless actuation and rapid response, but current fabrication methods are complex and have limited cellular compatibility. A new, contactless bioassembly strategy using hydrodynamic instabilities is introduced, enabling customizable, centimeter‐scale robots.
Wei Gao, Riccardo Tognato, Micaela Natta, Elena Della Bella, Alessandro Cianciosi, Tiziano Serra   +5 more
wiley   +1 more source