Results 221 to 230 of about 760,515 (274)

Multi-temporal dimension prediction of new energy electricity demand based on chaos-LSSVM neural network. [PDF]

Sci Rep
Wu Y, Wang W, Ma X, Zhao R, Wu B, Chen P, An Q.   +6 more
europepmc   +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

Photorefractive keratectomy in patients with thin corneas: systematic review and meta-analysis of clinical outcomes and complications. [PDF]

J Cataract Refract Surg
Semnani F, Semnani F, Rayati Damavandi A, Abdollahi M, Sajadi M, Sadoughi MM, Hassanpour K.   +6 more
europepmc   +1 more source

Complex Cryptographic and User‐Centric Physically Unclonable Functions Enabled by Strain‐Sensitive Nanocrystals via Selective Ligand Exchange

Advanced Functional Materials, EarlyView.
This study investigates electromechanical PUFs that improve on traditional electric PUFs. The electron transport materials are coated randomly through selective ligand exchange. It produces multiple keys and a key with motion dependent on percolation and strain, and approaches almost ideal inter‐ and intra‐hamming distances.
Seungshin Lim, Hanseok Seo, Taesung Park, Byung Ku Jung, Junhyeok Park, Young Kyun Choi, Dae Yang Oh, Soong Ju Oh   +7 more
wiley   +1 more source

Designing a residual-enhanced hybrid Prophet-LSTM framework for urban air pollution forecasting in Beijing. [PDF]

Sci Rep
Milli M.
europepmc   +1 more source

Thermal Phase‐Modulation of Thickness‐Dependent CVD‐Grown 2D In2Se3

Advanced Functional Materials, EarlyView.
A comprehensive study of CVD‐grown 2D In2Se3 reveals a distinct thickness‐dependent phase landscape and a reversible, thermally driven transformation between β″ and β* variants. In situ TEM electron diffraction and Raman spectroscopy reveal structural dynamics, while the structural invariance of the α‐phase in ultrathin regimes highlights its stability—
Dasun P. W. Guruge, Zhenhuan Chen, Joseph F. S. Fernando, Chao Zhang, Liangzhi Kou, Konstantin L. Firestein, Dmitri V. Golberg   +6 more
wiley   +1 more source

A Gas Production Classification Method for Cable Insulation Materials Based on Deep Convolutional Neural Networks. [PDF]

Polymers (Basel)
Wang Z, Chai Y, Gong J, Xie W, Chen Y, Gong W.   +5 more
europepmc   +1 more source

Application of residual power series method to time fractional gas dynamics equations

Journal of Physics: Conference Series, 2018
openaire   +1 more source

Covalent Organic Frameworks for Water Sorption: The Importance of Framework Physical Stability

Advanced Functional Materials, EarlyView.
This study explores the water‐vapor stability of 2D covalent organic frameworks (COFs) with varying pore sizes. Results reveal microporous COFs demonstrate superior stability compared to mesoporous ones, despite lower water uptake. Mesoporous keto‐enamine‐linked COFs show enhanced stability due to intralayer hydrogen bonds, confirmed by simulations and
Wei Zhao, He Li, Bui Duc Thuan, Weidong Chen, Qiang Zhu, Mounib Bahri, Boyu Li, Kexin Yu, Chengjun Kang, Ting Chen, Zekun Wang, Nigel D. Browning, Kian Jon Chua, Dan Zhao   +13 more
wiley   +1 more source

Exploring the relationship between space weather conditions and power performance of EgyptSat-1 using machine learning. [PDF]

Sci Rep
Elfiky D, Ali MAB, Mostafa MS, Hesham N, Ahmed AM, Ibrahim SK.   +5 more
europepmc   +1 more source