Results 91 to 100 of about 379,537 (253)

Unveiling Multidimensional Physicochemical Design Principles for Tissue Processing Hydrogels

Advanced Functional Materials, EarlyView.
This study establishes a materials‐based design framework for polymer hydrogels in tissue clearing, linking physicochemical properties to performance in tissue processing, labeling, and imaging. By analyzing rheology, swelling, porosity, antibody diffusion, mechanical performance, and thermochemical stability across platforms, this work provides a ...
Sangjae Kim, Siheon Lee, Jinsoo Na, James Sangmin Choo, Inho Kim, Junsang Doh, Jeong‐Yun Sun, Chang Yeol Lee, Juhyuk Park   +8 more
wiley   +1 more source

Data-Driven Identification of Crane Dynamics Using Regularized Genetic Programming

Applied Sciences
The meaningful problem of improving crane safety, reliability, and efficiency is extensively studied in the literature and targeted via various model-based control approaches.
Tom Kusznir, Jarosław Smoczek, Bolesław Karwat   +2 more
doaj   +1 more source

Bioinspired Stabilization of Fluorescent Au@SiO2 Tracers for Multimodal Biological Imaging

Advanced Functional Materials, EarlyView.
This study demonstrates a bioinspired stabilization strategy for fluorescent gold‐silica nanoparticles. Inspired by natural biosilica maturation, high‐temperature calcination transforms the silica shells, preventing dissolution in cell culture media and intracellular environments.
Wang Sik Lee, Henry Lee, Patricia Taladriz‐Blanco, Dimitri Vanhecke, Barbara Rothen‐Rutishauser, Alke Petri‐Fink   +5 more
wiley   +1 more source

Multiclass Sparse Bayesian Regression for fMRI-Based Prediction

International Journal of Biomedical Imaging, 2011
Inverse inference has recently become a popular approach for analyzing neuroimaging data, by quantifying the amount of information contained in brain images on perceptual, cognitive, and behavioral parameters.
Vincent Michel, Evelyn Eger, Christine Keribin, Bertrand Thirion   +3 more
doaj   +1 more source

Hyperspectral Unmixing with Robust Collaborative Sparse Regression

Remote Sensing, 2016
Recently, sparse unmixing (SU) of hyperspectral data has received particular attention for analyzing remote sensing images. However, most SU methods are based on the commonly admitted linear mixing model (LMM), which ignores the possible nonlinear ...
Chang Li, Yong Ma, Xiaoguang Mei, Chengyin Liu, Jiayi Ma   +4 more
doaj   +1 more source

Programmable In‐Situ Interactions Between Resins and Photopolymerized Structures for Seamlessly Integrated Optical Manufacturing of Microlenses

Advanced Functional Materials, EarlyView.
This study presents a dynamic interaction between liquid resins and photopolymerized structures enabled by an in situ light‐writing setup. By controlling a three‐phase interface through localized photopolymerization, which provides physical confinement for the remaining uncured resin regions, the approach establishes a programmable pathway that ...
Kibeom Kim, Sangmin Oh, Kahyun Hur, Hyesung Cho   +3 more
wiley   +1 more source

Sparse Logistic Regression: Comparison of Regularization and Bayesian Implementations

Algorithms, 2020
In knowledge-based systems, besides obtaining good output prediction accuracy, it is crucial to understand the subset of input variables that have most influence on the output, with the goal of gaining deeper insight into the underlying process.
Mattia Zanon, Giuliano Zambonin, Gian Antonio Susto, Seán McLoone   +3 more
doaj   +1 more source

Artificial Intelligence as the Next Visionary in Liquid Crystal Research

Advanced Functional Materials, EarlyView.
The functions of AI in the research laboratory are becoming increasingly sophisticated, allowing the entire process of hypothesis formulation, material design, synthesis, experimental design, and reiterative testing to be automated. In our work, we conceive how the incorporation of AI in the laboratory environment will transform the role and ...
Mert O. Astam, Ouassim L'Karkouri, Danqing Liu   +2 more
wiley   +1 more source

Electric Cable Insulator Damage Monitoring by Lasso Regression

Machines
Since the discovery of electricity, electric cables have become ubiquitous in human constructions, from machines to buildings. Insulators play a crucial role in ensuring the proper functioning of these cables, so it is important to monitor their possible
Qinghua Zhang, Monssef Drissi-Habti
doaj   +1 more source

Regularized Maximum Likelihood Estimation and Feature Selection in Mixtures-of-Experts Models [PDF]

, 2018
Mixture of Experts (MoE) are successful models for modeling heterogeneous data in many statistical learning problems including regression, clustering and classification.
Chamroukhi, Faicel, Huynh, Bao-Tuyen
core   +1 more source