Results 131 to 140 of about 15,920 (255)

A selection index with minimal genetic relatedness for multi-trait data via binary quadratic programming. [PDF]

Plant Methods
Montesinos-López OA, Montesinos-López A, Hernández-Suárez CM, Alemu A.   +3 more
europepmc   +1 more source

Population balance modeling and digital design of degree of agglomeration in industrial crystallization

AIChE Journal, EarlyView.
Abstract This study presents a coupled population balance model (PBM) for describing the degree‐of‐agglomeration (DoA) in crystallization by independently tracking total particle and agglomerate number densities. Applied to an industrial active pharmaceutical ingredient, the model outperformed bridge‐counting methods and accurately captured DoA trends ...
Yung‐Shun Kang, Hemalatha Kilari, Neda Nazemifard, C. Benjamin Renner, Yihui Yang, Charles Papageorgiou, Zoltan K. Nagy   +6 more
wiley   +1 more source

A meta-interactive neural network for solving time-varying quadratic programming problems. [PDF]

Nat Commun
Zhang Z, Sun X, Liu Y, Luo Y.
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Walking Pattern Generation Through Step-by-Step Quadratic Programming for Biped Robots. [PDF]

Biomimetics (Basel)
Liu G, Lu Z, Zhang H, Liu Z.
europepmc   +1 more source

Numerical solution of a general interval quadratic programming model for portfolio selection. [PDF]

PLoS One, 2019
Wang J, He F, Shi X.
europepmc   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

Optimization of Pulsed Saturation Transfer MR Fingerprinting (ST MRF) Acquisition Using the Cramér-Rao Bound and Sequential Quadratic Programming. [PDF]

Magn Reson Med
Vladimirov N, Zaiss M, Perlman O.
europepmc   +1 more source

Factorization Machine with Iterative Quantum Reverse Annealing: A Python Package for Batch Black‐Box Optimization With Reverse Quantum Annealing

Advanced Intelligent Discovery, EarlyView.
Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley   +1 more source

Computing the alpha complex using dual active set quadratic programming. [PDF]

Sci Rep
Carlsson E, Carlsson J.
europepmc   +1 more source