Results 51 to 60 of about 155,627 (235)

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Discovering Cancer Subtypes via an Accurate Fusion Strategy on Multiple Profile Data

Frontiers in Genetics, 2019
Discovering cancer subtypes is useful for guiding clinical treatment of multiple cancers. Progressive profile technologies for tissue have accumulated diverse types of data. Based on these types of expression data, various computational methods have been
Limin Jiang, Yongkang Xiao, Yijie Ding, Jijun Tang, Jijun Tang, Fei Guo   +5 more
doaj   +1 more source

Photon Avalanching Nanoparticles: The Next Generation of Upconverting Nanomaterials?

Advanced Functional Materials, EarlyView.
This Perspective outlines the mechanistic foundations that enable photon‐avalanche (PA) behavior in lanthanide nanomaterials and contrasts them with emerging application spaces and forward‐looking design strategies. By bridging threshold engineering, energy‐transfer dynamics, and materials engineering, we provide a coherent roadmap for advancing the ...
Kimoon Lee, Yunseo Kim, Hyeong‐ku Jo, Dongjoon Yoon, Byeonghyeok Im, WonJeong Yu, Eui‐Rim On, Changhwan Lee   +7 more
wiley   +1 more source

Texoskeletons: Developing the Fundamental Technologies for Creating Intelligent Soft Robotic Clothing With Integrated 1D Sensors and Actuators

Advanced Functional Materials, EarlyView.
ABSTRACT Traditional wearable exoskeletons rely on rigid structures, which limit comfort, flexibility, and everyday usability. This work introduces the fundamental technologies to create the first soft, lightweight, intelligent textile‐based exoskeletons (Texoskeletons) built using 1D sensors and actuators.
Amy Lukomiak, Rameesh Bulathsinghala, Jack Varga, Shuxin Meng, Kalana Marasinghe, Imaad Refai, Biyon Fernando, Amitkumar Patel, Chamika M. Halloluwa‐Arachchige, Carlos Oliveira, Arash M. Shahidi, Zahra Rahemtulla, Alexander Turner, Ziyun Ding, Bernard X. W. Liew, Andy Kerr, Ezio Preatoni, Theo Hughes‐Riley, Ishara Dharmasena, Pasindu Lugoda   +19 more
wiley   +1 more source

Adaptive Anchor-Based Partial Multiview Clustering

IEEE Access, 2020
Partial multiview clustering, which aims to effectively merge multiple prespecified incomplete views to improve clustering performance, is a research hotspot and difficulty in the field of machine learning. Guo et al.
Xia Ji, Lei Yang, Sheng Yao
doaj   +1 more source

A Data Driven Review of In Vitro Electrical and Mechanical Stimulation for Post‐Acute Phase Wound Healing

Advanced Healthcare Materials, EarlyView.
This review examines how in vitro electrical and mechanical stimulation modulates wound healing in fibroblasts and keratinocytes. Analyzing over 560 experimental data points, we relate stimulation parameters to proliferation and migration outcomes, evaluate platform designs, and highlight the need for multi‐parameter optimization to advance targeted ...
Matthew K. Burgess, Ellen F. Marsh, Veronica M. Lucian, Malavika Nair   +3 more
wiley   +1 more source

Unveiling the Role of Curvature in Carbon for Improved Energy Release of Ammonium Perchlorate

Advanced Materials, EarlyView.
High‐curvature carbon materials identified via machine learning and simulation can enhance the heat release and combustion performance of ammonium perchlorate. ABSTRACT The catalytic role of carbon curvature in the thermal decomposition of ammonium perchlorate (AP) remains largely unexplored. To address this gap, this study employs machine learning and
Dan Liu, Keliang Song, Haorui Zhang, Zhipeng Liu, Guansong He, Junru Wang, Wenming Yang, Xu Zhao, Zhijian Yang   +8 more
wiley   +1 more source

Triply‐Twinned Metamaterials: Unraveling the Mechanics and Failure Pathways Through High‐Resolution XCT

Advanced Materials, EarlyView.
Triply‐twinned architected lattices transform deformation from bending to stretching of struts, delivering up to threefold increases in stiffness and strength across polymeric and metallic systems. High‐resolution synchrotron XCT and image‐based simulations reveal how meta‐grain architecture, defects, and AM build orientation govern failure pathways ...
David McArthur, George Maddison, Jaianth Vijayakumar, Paul Tafforeau, Kathy Christofidou, Peter David Lee, PJ Tan, Chu Lun Alex Leung   +7 more
wiley   +1 more source

Join multiple Riemannian manifold representation and multi‐kernel non‐redundancy for image clustering

CAAI Transactions on Intelligence Technology
Image clustering has received significant attention due to the growing importance of image recognition. Researchers have explored Riemannian manifold clustering, which is capable of capturing the non‐linear shapes found in real‐world datasets.
Mengyuan Zhang, Jinglei Liu
doaj   +1 more source

Improved kernel density peaks clustering for plant image segmentation applications

Journal of Intelligent Systems, 2023
In order to better solve the shortcomings of the k-means clustering method and density peaks clustering (DPC) method in agricultural image segmentation, this work proposes a method to divide points in a high-dimensional space, and a clustering method is ...
Bi Jiaze, Zhang Pingzhe, Gao Yujia, Dong Menglong, Zhuang Yongzhi, Liu Ao, Zhang Wei, Chen Yiqiong   +7 more
doaj   +1 more source