Results 71 to 80 of about 169,559 (249)

Developing a comprehensive framework for multimodal feature extraction

, 2017
Feature extraction is a critical component of many applied data science workflows. In recent years, rapid advances in artificial intelligence and machine learning have led to an explosion of feature extraction tools and services that allow data ...
de la Vega, Alejandro, McNamara, Quinten, Yarkoni, Tal   +2 more
core   +1 more source

Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives

Advanced Functional Materials, EarlyView.
AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu, Junyuan Lu, Jian Hui, Ziyuan Rao, Yang Ren, Hong Wang   +5 more
wiley   +1 more source

DALiuGE: A Graph Execution Framework for Harnessing the Astronomical Data Deluge

, 2017
The Data Activated Liu Graph Engine - DALiuGE - is an execution framework for processing large astronomical datasets at a scale required by the Square Kilometre Array Phase 1 (SKA1).
An, Tao, Boulton, Mark, Cooper, Ian, Dodson, Richard, Dolensky, Markus, Lao, Baoqiang, Mei, Ying, Pallot, Dave, Tobar, Rodrigo, Vinsen, Kevin, Wang, Feng, Wang, Ruonan, Wicenec, Andreas, Wu, Chen   +13 more
core  

High-level Cryptographic Abstractions

, 2019
The interfaces exposed by commonly used cryptographic libraries are clumsy, complicated, and assume an understanding of cryptographic algorithms. The challenge is to design high-level abstractions that require minimum knowledge and effort to use while ...
Chand, Saksham, Kane, Christopher, Lin, Bo, Liu, Yanhong A., Stoller, Scott D.   +4 more
core   +1 more source

Experimentally Validated Design Principles of D‐Block Transition Metal Single‐Atom Non‐Dissociative Chemisorption Solid‐State Hydrogen Storage Materials

Advanced Functional Materials, EarlyView.
A novel descriptor and a bottom‐up design principle are established to enable the rational design of hydrogen storage materials based on d‐block transition metal single‐atom COFs. By modulating H₂ adsorption through d‐orbital tuning, this approach achieves both high storage capacity and fast kinetics, while revealing a volcano‐type relationship between
Qiuyan Yue, Chao Li, Yong Gao, Zhenglong Li, Wen‐Gang Cui, Xinqiang Wang, Guoquan Na, Xiaowei Wang, Yiyang Wan, Mingchang Zhang, Yanxia Liu, Fulai Qi, Chenchen Li, Xu Xue, Jian Miao, Jing Zhang, Xiao Han, Pan Wang, Chang Guo, Xiacui Liu, Mingxia Gao, Wenping Sun, Jian Chen, Zhenhai Xia, Hongge Pan   +24 more
wiley   +1 more source

AFLOW-ML: A RESTful API for machine-learning predictions of materials properties

, 2017
Machine learning approaches, enabled by the emergence of comprehensive databases of materials properties, are becoming a fruitful direction for materials analysis.
Carrete, Jesús, Curtarolo, Stefano, Gossett, Eric, Isayev, Olexandr, Legrain, Fleur, Mingo, Natalio, Oses, Corey, Rose, Frisco, Toher, Cormac, Tropsha, Alexander, Zurek, Eva   +10 more
core   +1 more source

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

Refactoring to Pythonic Idioms: A Hybrid Knowledge-Driven Approach Leveraging Large Language Models [PDF]

Proc. ACM Softw. Eng.
Pythonic idioms are highly valued and widely used in the Python programming community. However, many Python users find it challenging to use Pythonic idioms.
Zejun Zhang, Zhenchang Xing, Xiaoxue Ren, Qinghua Lu, Xiwei Xu   +4 more
semanticscholar   +1 more source

Novel Drug‐Testing Platform for Vascular Injury‐induced Intimal Hyperplasia Using a Microphysiological System

Advanced Healthcare Materials, EarlyView.
This study develops a 3D vascular injury model using a microphysiological system that mimics key features of intimal hyperplasia. Antiproliferative drugs reduced VSMC proliferation but worsened endothelialdenudation. A combination of diphenyleneiodonium and quercetin effectively reduced proliferation and migration of VSMC and inflammation while ...
Ungsig Nam, HyeMi Kim, Jeong Ah Kim, Ki‐Hwan Nam, Kye‐Sung Lee, Hwan Hur, Jessie S. Jeon, Ji Yong Bae   +7 more
wiley   +1 more source

Synthetic Antiferromagnetic Designer Nanodisks for High‐Performance Magnetic Separation

Advanced Healthcare Materials, EarlyView.
Micromagnetic‐modeling‐based design and scalable fabrication of synthetic antiferromagnet (SAF) magnetic disk particles (MDPs) using sputter deposition enable high‐performance magnetic separation. The SAF MDPs achieve high colloidal stability and magnetic responsiveness and enable efficient magnetic separation, outperforming conventional particles ...
Subas Scheibler, Sebastian Habermann, Alexander Gogos, Santiago Helbig, Lukas R. H. Gerken, Anna L. Neuer, Vera M. Kissling, Michal Krupinski, Mohammad Alinezhadfar, Rowena Crockett, Nico Kummer, Erik M. Mayr, Dieter Süss, Hans J. Hug, Inge K. Herrmann   +14 more
wiley   +1 more source