Results 101 to 110 of about 70,698 (256)

Autofocusing of Maneuvering Targets in Terahertz Inverse Synthetic Aperture Radar Imaging Based on Damped Newton Method. [PDF]

Sensors (Basel), 2022
Wang H, Yang Q, Wang H, Deng B.
europepmc   +1 more source

Trump Tariffs 2.0: Assessing the Impacts on US Distilled Spirits Imports

Agribusiness, EarlyView.
ABSTRACT The proposed 25% tariff on Mexico and Canada could have significant repercussions on US imports of distilled spirits. This study estimates US import demand across various spirit categories (e.g., tequila, whiskey) and assesses the potential impact of the proposed tariff.
Andrew Muhammad
wiley   +1 more source

Minimizing Uniformly Convex Functions by Cubic Regularization of Newton Method. [PDF]

J Optim Theory Appl, 2021
Doikov N, Nesterov Y.
europepmc   +1 more source

Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization

AIChE Journal, EarlyView.
Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed, Tao Chen, Antonio del Rio Chanona, Lorenz T. Biegler, Michael Short   +4 more
wiley   +1 more source

Cluster Gauss-Newton method analyses of PBPK model parameter combinations of coproporphyrin-I based on OATP1B-mediated rifampicin interaction studies. [PDF]

CPT Pharmacometrics Syst Pharmacol, 2022
Yoshikado T, Aoki Y, Mochizuki T, Rodrigues AD, Chiba K, Kusuhara H, Sugiyama Y.   +6 more
europepmc   +1 more source

Proximal Gauss–Newton method

, 2018
Capítulo del libro "Contemporary study of iterative methods: convergence, dynamics and applications" In this chapter we extend the solvability of penalized nonlinear least squares problems using the proximal Gauss–Newton method. Moreover, a numerical example validating the theoretical results is also presented.
Magreñán, Á. Alberto (1), Argyros, Ioannis K   +1 more
openaire   +2 more sources

Monitoring and control of a continuous, integrated filtration‐drying system with in‐line mass spectrometry via PharmaPy

AIChE Journal, EarlyView.
Abstract This article demonstrates the integration of in‐line mass spectrometry as a process analytical technology (PAT) tool with model‐based soft sensors in a continuous filtration‐drying carousel system for solid–liquid separation (SLS) of crystal slurries.
Inyoung Hur, Daniel Casas‐Orozco, Gintaras Reklaitis, Zoltan K. Nagy   +3 more
wiley   +1 more source

A Weighted and Distributed Algorithm for Range-Based Multi-Hop Localization Using a Newton Method. [PDF]

Sensors (Basel), 2021
Diaz-Roman J, Mederos B, Sifuentes E, Gonzalez-Landaeta R, Cota-Ruiz J.   +4 more
europepmc   +1 more source

Scale‐up of Streptomyces species cultivations based on the morphological response to the energy dissipation rate

AIChE Journal, EarlyView.
Abstract Filamentous microorganisms exhibit complex morphologies that influence product formation and are affected by various bioprocess parameters. Consistent morphology is therefore essential for comparable results during scale‐up. This study investigates the scale‐up of Streptomyces species (Streptomyces spp.) cultivations from shake flasks to ...
Gesa Brauneck, Anton Brass, Artiom Boreiko, Marvin Ueßeler, Marcel Mann, Johannes Pastoors, Valentin Steier, Philipp Eibl, Christian Witz, Dorothea M. Schütterle, Ivan Schlembach, Miriam A. Rosenbaum, Jorgen Magnus   +12 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source