Results 71 to 80 of about 324,327 (273)

Low‐Ru‐Content CuCoRu Aerogel for Boosted Electrocatalytic Nitrate Reduction to Ammonia

EcoEnergy, EarlyView.
Low‐Ru‐content Cu5Co5Ru aerogel with enhanced hydrogenation ability and 3D robust aerogel skeletons enables high‐efficiency and long‐term electrocatalytic nitrate reduction to ammonia at low overpotential, achieving an exceptional ammonia yield rate of 2.7 ± 0.1 mmol cm−2 h−1 and a high Faradaic efficiency of ∼97% at −0.1 V versus RHE as well as an ...
Jinjie Tan, Wenjun Ning, Jiashu Chen, Dongyang Lou, Zhehang Jiang, Shurong Li, Rui Zhou, Weichun Chang, Xiu‐Zhi Tang, Libin Zeng, Wei Huang, Jing Yang   +11 more
wiley   +1 more source

Migration speed, timing, and long‐term shifts in age structure in North American passerines during fall migration

Ecography, EarlyView.
Migration is challenging for birds, especially juveniles, who experience high mortality rates during migration. The challenge is exacerbated in the Anthropocene, contributing to widespread population declines. Conservation efforts focused on increasing juvenile survival could bolster population recovery.
Dylan M. Osterhaus, Martha J. Desmond, Timothy F. Wright   +2 more
wiley   +1 more source

Numerical Experience with Damped Quasi-Newton Optimization Methods when the Objective Function is Quadratic

Sultan Qaboos University Journal for Science, 2012
A class of damped quasi-Newton methods for nonlinear optimization has recently been proposed by extending the damped-technique of Powell for the BFGS method to the Broyden family of quasi-Newton methods.
Mehiddin Al-Baali, Anton Purnama
doaj   +1 more source

Local Polynomial Regression and Filtering for a Versatile Mesh‐Free PDE Solver

International Journal for Numerical Methods in Fluids, EarlyView.
A high‐order, mesh‐free finite difference method for solving differential equations is presented. Both derivative approximation and scheme stabilisation is carried out by parametric or non‐parametric local polynomial regression, making the resulting numerical method accurate, simple and versatile. Numerous numerical benchmark tests are investigated for
Alberto M. Gambaruto
wiley   +1 more source

Forecasting Count Data With Varying Dispersion: A Latent‐Variable Approach

Journal of Forecasting, EarlyView.
ABSTRACT Count data, such as product sales and disease case counts, are common in business forecasting and many areas of science. Although the Poisson distribution is the best known model for such data, its use is severely limited by its assumption that the dispersion is a fixed function of the mean, which rarely holds in real‐world scenarios.
Easton Huch, Candace Berrett, Mason Ferlic, Kimberly F. Sellers   +3 more
wiley   +1 more source

An Efficient Limited Memory Multi-Step Quasi-Newton Method

Mathematics
This paper is dedicated to the development of a novel class of quasi-Newton techniques tailored to address computational challenges posed by memory constraints. Such methodologies are commonly referred to as “limited” memory methods.
Issam A. R. Moghrabi, Basim A. Hassan
doaj   +1 more source

Memoryless quasi-Newton methods based on spectral-scaling Broyden family for unconstrained optimization

Journal of Industrial and Management Optimization, 2019
Memoryless quasi-Newton methods are studied for solving large-scale unconstrained optimization problems. Recently, memoryless quasi-Newton methods based on several kinds of updating formulas were proposed.
Shummin Nakayama, Yasushi Narushima, H. Yabe   +2 more
semanticscholar   +1 more source

Observation of Linear and Nonlinear Light Trapping on Topological Dislocations

Laser &Photonics Reviews, EarlyView.
Topological dislocations are global lattice defects found in various systems ranging from crystals to photonic lattices. This work reports the first observation at optical frequencies of linear modes with tunable localization bound to edge dislocations and their nonlinear counterparts ‐ dislocation solitons. These results reveal an intriguing interplay
S. K. Ivanov, A. V. Kireev, K. Sabour, N. S. Kostyuchenko, S. A. Zhuravitskii, N. N. Skryabin, I. V. Dyakonov, A. A. Kalinkin, V. O. Kompanets, S. P. Kulik, S. V. Chekalin, A. Ferrando, V. N. Zadkov, Y. V. Kartashov   +13 more
wiley   +1 more source

Structure‐Aware Machine Learning for Polymers: A Hierarchical Graph Network for Predicting Properties From Statistical Ensembles

Macromolecular Rapid Communications, EarlyView.
This work presents a structure‐aware graph convolutional network that models polymers as statistical ensembles to predict macroscopic properties. By combining topologically realistic graphs generated via kinetic Monte Carlo simulations with explicit molar mass distributions, the framework achieves high accuracy in classifying architectures and ...
Julian Kimmig, Yannik Köster, Timo Koswig, Punith Raviswamy, Subhash V. S. Ganti, Stefan Zechel, Christopher Kuenneth, Ulrich S. Schubert   +7 more
wiley   +1 more source

A Family of Newton and Quasi-Newton Methods for Power Flow Analysis in Bipolar Direct Current Networks with Constant Power Loads

Mathematical and Computational Applications
This paper presents a comprehensive study on the formulation and solution of the power flow problem in bipolar direct current (DC) distribution networks with unbalanced constant power loads.
Oscar Danilo Montoya, Juan Diego Pulgarín Rivera, Luis Fernando Grisales-Noreña, Walter Gil-González, Fabio Andrade-Rengifo   +4 more
doaj   +1 more source