Results 161 to 170 of about 28,952 (292)
A graphene oxide/collagen scaffold is developed for chronic massive rotator cuff tear repair. The scaffold improves compressive stability, supports reparative mesenchymal differentiation, and modulates the immune microenvironment. In chronic MRCT models, it reduces muscle degeneration, enhances tendon–bone regeneration, and improves functional recovery,
Renwen Wan +24 more
wiley +1 more source
Non-Iterative Phase-Only Hologram Generation via Stochastic Gradient Descent Optimization
In this work, we explored, for the first time, to the best of our knowledge, the potential of stochastic gradient descent (SGD) to optimize random phase functions for application in non-iterative phase-only hologram generation.
Alejandro Velez-Zea +1 more
doaj +1 more source
Sentiment classification for employees reviews using regression vector- stochastic gradient descent classifier (RV-SGDC). [PDF]
Gaye B, Zhang D, Wulamu A.
europepmc +1 more source
Gradient Descent, Stochastic Optimization, and Other Tales
The goal of this paper is to debunk and dispel the magic behind black-box optimizers and stochastic optimizers. It aims to build a solid foundation on how and why the techniques work.
Lu, Jun
core
Multimodal Imaging Reveals Rapid Catecholamine Uptake and Release by Neutrophils
We show that immune cells (neutrophils) synthesize, uptake, and store catecholamine neurotransmitters such as dopamine or adrenaline. They also release them in response to specific stimuli (serotonin), which we directly visualize using fluorescent nanosensors. We further demonstrate that catecholamines affect neutrophil functions (NETosis) and platelet
Jennifer Mohr +19 more
wiley +1 more source
An Improved Reacceleration Optimization Algorithm Based on the Momentum Method for Image Recognition
The optimization algorithm plays a crucial role in image recognition by neural networks. However, it is challenging to accelerate the model’s convergence and maintain high precision.
Haijing Sun +6 more
doaj +1 more source
Theoretical Analysis of Stochastic Gradient Descent in Stochastic Optimization
Stochastic Gradient Descent (SGD) type algorithms have been widely applied to many stochastic optimization problems, such as machine learning. Despite its empirical success, there is still a lack of theoretical understanding of convergence properties of ...
Liu, Tianyi
core
Diverse Landscape of Tunable Magnetic, Topological, and Ferroelectric States in 2D Ti3Se3Te2
Ti3Se3Te2 emerges as a multifunctional 2D van der Waals platform. The monolayer is a dynamically stable ferromagnetic quantum anomalous Hall insulator. In bilayers, two stacking configurations yield distinct phases: AA‐stacking hosts an altermagnetic quantum spin Hall insulator, while AA′‐stacking exhibits three‐state in‐plane ferroelectricity ...
Jiangtao Yu +5 more
wiley +1 more source
Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu +5 more
wiley +1 more source
This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu +16 more
wiley +1 more source

