Results 101 to 110 of about 97,243 (265)

Genipin‐Crosslinked, Silane‐Anchored 3D Tumor–Stroma Microtissues for High‐Content On‐Chip Drug Testing

Advanced Healthcare Materials, EarlyView.
We describe a microfluidic tumor‐stroma co‐culture model, engineered to resist collagen‐hydrogel contraction driven by fibroblast activity. Surface silanization with APTES covalently anchors the matrix to the chip, while Genipin crosslinking progressively increases stiffness and elasticity without harming cells. This supports >10 days of co‐culture and
Doriane Le Manach, Reza Kowsari‐Esfahan, Emilia Reszczyńska, Philippe Nghe, Matthias Nees   +4 more
wiley   +1 more source

Microengineered Gradient Hydrogels for Mechanobiology

Advanced Healthcare Materials, EarlyView.
Gradient hydrogels are used to mimic the mechanical heterogeneity in native tissues, offering powerful in vitro platforms to study cell‐material interactions in diverse pathophysiological contexts. Here, we present a comprehensive review of the design and experimental considerations for stiffness gradient hydrogels, discussing exemplary achievements ...
Shin Wei Chong, Deepu Ashok, Anna Waterhouse, Marcela M. M. Bilek, Daniele Vigolo   +4 more
wiley   +1 more source

Unsupervised end-to-end training with a self-defined target

Neuromorphic Computing and Engineering
Designing algorithms for versatile AI hardware that can learn on the edge using both labeled and unlabeled data is challenging. Deep end-to-end training methods incorporating phases of self-supervised and supervised learning are accurate and adaptable to
Dongshu Liu, Jérémie Laydevant, Adrien Pontlevy, Damien Querlioz, Julie Grollier   +4 more
doaj   +1 more source

Enhancing Self-Supervised Learning through Explainable Artificial Intelligence Mechanisms: A Computational Analysis

Big Data and Cognitive Computing
Self-supervised learning continues to drive advancements in machine learning. However, the absence of unified computational processes for benchmarking and evaluation remains a challenge.
Elie Neghawi, Yan Liu
doaj   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Self-Supervised Learning as Discrete Communication

CoRR
Most self-supervised learning (SSL) methods learn continuous visual representations by aligning different views of the same input, offering limited control over how information is structured across representation dimensions. In this work, we frame visual self-supervised learning as a discrete communication process between a teacher and a student ...
Kawtar Zaher, Ilyass Moummad, Olivier Buisson, Alexis Joly   +3 more
openaire   +2 more sources

Polymorph‐Specific Electronic Transduction in WO3 during Molecular Sensing

Advanced Materials, EarlyView.
Metal‐oxide polymorphs with similar surface chemistry can nevertheless exhibit distinct sensing properties. In γ‐ and ε‐WO3, analyte adsorption appears comparable; yet, only ε‐WO3 induces a pronounced lattice electronic perturbation that accommodates charge in sub‐conduction band minimum states.
Matteo D'Andria, Meng Yin, Stefan Neuhauser, Vlasis G. Mavrantzas, Ying Chen, Ken Suzuki, Andreas T. Güntner   +6 more
wiley   +1 more source

Self-supervised Face Representation Learning

, 2020
This thesis investigates fine-tuning deep face features in a self-supervised manner for discriminative face representation learning, wherein we develop methods to automatically generate pseudo-labels for training a neural network. Most importantly solving this problem helps us to advance the state-of-the-art in representation learning and can be ...
openaire   +4 more sources

Audio-Based Emotion Recognition Using Self-Supervised Learning on an Engineered Feature Space

AI
Emotion recognition models using audio input data can enable the development of interactive systems with applications in mental healthcare, marketing, gaming, and social media analysis.
Peranut Nimitsurachat, Peter Washington
doaj   +1 more source

Inverse Design of Amorphous Materials With Targeted Properties

Advanced Materials, EarlyView.
AMDEN is a diffusion model framework for the inverse design of amorphous materials with targeted properties. By incorporating Hamiltonian Monte Carlo refinement into the denoising process, the framework overcomes the challenge of generating thermally relaxed disordered structures.
Jonas A. Finkler, Yan Lin, Tao Du, Jilin Hu, Morten M. Smedskjaer   +4 more
wiley   +1 more source