Results 61 to 70 of about 274,124 (332)

Combinatorial Synthesis of Next Generation Water‐Soluble Quaternized N‐Halamine Oligomers with Long‐Lasting Antiviral Properties

Advanced Functional Materials, EarlyView.
A combinatorial library of dual‐functional antiviral oligomers incorporating N‐halamine and quaternary ammonium functionalities is developed for long‐lasting antiviral activity. The lead materials exhibit rapid and durable antiviral activity against SARS‐CoV‐2 variants and influenza H1N1, with 4 to 5 log reduction in viral copies at 5 mg mL−1 ...
Eid Nassar‐Marjiya, Konda Reddy Kunduru, Krishanu Ghosal, Luna Rizik, Nofar Atari, Mahran Daifa, Neta Kutner, Bassma Khamaisi, Qi Wu, Simran Jindal, Merna Shaheen‐Mualim, Ranabir Majumder, Mahitosh Mandal, Michal Mandelboim, Shady Farah   +14 more
wiley   +1 more source

MODELING OF KOVAZHNY FLOW AND TAYLOR – GREEN VORTEX ON PHYSICS-INFORMED RADIAL BASIS FUNCTION NETWORKS

Модели, системы, сети в экономике, технике, природе и обществе
Background. An analysis of physics-informed neural networks for solving partial differential equations has been conducted, and the advantages of physics-informed radial basis function networks have been demonstrated.
Dmitry A. Stenkin
doaj   +1 more source

Artificial analysis of molecular marker loci linked to tree resistance response by an artificial neural network [PDF]

, 2015
One of the biggest challenges that software developers face is to make an accurate estimate of the project effort. Radial basis function neural networks have been used to software effort estimation in this work using NASA dataset.
Castellanos Peñuela, Angel Luis, Castellanos Peñuela, Juan Bautista, Fernández, Jorge   +2 more
core   +1 more source

Electroactive Metal–Organic Frameworks for Electrocatalysis

Advanced Functional Materials, EarlyView.
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska, Yutong Luo, Ruyan Zhao, Jianjun Zhang, Mingchao Wang, Xinliang Feng, Eike Brunner, Stefan Kaskel   +7 more
wiley   +1 more source

RbfCon: Construct Radial Basis Function Neural Networks with Grammatical Evolution

Software
Radial basis function networks are considered a machine learning tool that can be applied on a wide series of classification and regression problems proposed in various research topics of the modern world.
Ioannis G. Tsoulos, Ioannis Varvaras, Vasileios Charilogis   +2 more
doaj   +1 more source

Electrochemically Driven Dissipative Growth of Affinity Hydrogels for Bioresponsive Interfaces

Advanced Functional Materials, EarlyView.
Voltage pulses drive the growth and reinforcement of hydrogel films under dissipative conditions. This biocompatible strategy enables efficient integration of affinity ligands into the hydrogel matrix, enhancing the selective capture of growth factors and allowing precise temporal control over their release, making them well‐suited as adaptive ...
Roberto Baretta, Marco Frasconi
wiley   +1 more source

Reconstruction of Daily Sea Surface Temperature Based on Radial Basis Function Networks

Remote Sensing, 2017
A radial basis function network (RBFN) method is proposed to reconstruct daily Sea surface temperatures (SSTs) with limited SST samples. For the purpose of evaluating the SSTs using this method, non-biased SST samples in the Pacific Ocean (10°N–30°N, 115°
Zhihong Liao, Qing Dong, Cunjin Xue, Jingwu Bi, Guangtong Wan   +4 more
doaj   +1 more source

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

Advanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi, Sumukh Shankar Sharadaprasad, Rochus Schmid   +2 more
wiley   +1 more source

A Novel Deep Reinforcement Learning Based Extended Fractal Radial Basis Function Network for State‐of‐Charge Estimation

IET Power Electronics
This paper presents a novel deep reinforcement learning based extended fractal radial basis function (DRL‐EFRBF) network for accurate state‐of‐charge (SOC) estimation in lithium iron phosphate (LiFePO4) batteries. Unlike conventional methods such as open
Syed M. Ali, Muhammad Bilal, Ayman Alharbi, Rooh ul Amin   +3 more
doaj   +1 more source

Electroencephalography Artifact Removal using Optimized Radial Basis Function Neural Networks

Majlesi Journal of Electrical Engineering
Electroencephalography (EEG) is a major clinical tool to diagnose, monitor and manage neurological disorders which is mostly affected by artifacts.
Shoorangiz Shams Shamsabad Farahani, Mohammad Mahdi Arefi, Amir Hossein Zaeri   +2 more
doaj   +1 more source