Results 101 to 110 of about 156,769 (285)

Generalized decomposition and cross entropy methods for many-objective optimization [PDF]

, 2012
Decomposition-based algorithms for multi-objective optimization problems have increased in popularity in the past decade. Although their convergence to the Pareto optimal front (PF) is in several instances superior to that of Pareto-based algorithms ...
Fleming, P.J., Giagkiozis, I., Purshouse, R.C.   +2 more
core  

Supraparticles Composed of Graphitic Carbon Nitride Nanoparticles and Silica‐Supported Horseradish Peroxidase as Customizable Hybrid Catalysts for Photo‐Biocatalytic Cascade Reactions in Continuous Flow

Advanced Functional Materials, EarlyView.
Herein presented supraparticles combine the nanoparticulate photocatalyst graphitic carbon nitride with the enzyme horseradish peroxidase, which is immobilized on silica nanoparticles. In an optimized compatibility range, both catalysts operate effectively within the hybrid supraparticles and catalyze a cascade reaction consisting of the photocatalytic
Bettina Herbig, Egzon Cermjani, Doris Hanselmann, Johannes Prieschl, Angelika Schmitt, Michael S. Moritz, Christian Papp, Greta Nölke, Stefano Di Fiore, Christoph Deckers, Thomas H. Rehm, Susanne Wintzheimer   +11 more
wiley   +1 more source

Mutation Control and Convergence in Evolutionary Multi-Object Optimization [PDF]

, 2001
This paper addresses the problem of controlling mutation strength in multi-objective evolutionary algorithms and its implications for the convergence to the Pareto set.
Laumanns, Marco, Rudolph, Günter, Schwefel, Hans-Paul   +2 more
core  

Optimizing Brain Networks Topologies Using Multi-objective Evolutionary Computation

Neuroinformatics, 2010
The analysis of brain network topological features has served to better understand these networks and reveal particular characteristics of their functional behavior. The distribution of brain network motifs is particularly useful for detecting and describing differences between brain networks and random and computationally optimized artificial networks.
Santana Hermida, Roberto, Bielza Lozoya, María Concepción, Larrañaga Múgica, Pedro María   +2 more
openaire   +3 more sources

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

Efficient Hill Climber for Multi-Objective Pseudo-Boolean Optimization [PDF]

, 2016
Chicano, F., Whitley D., & Tinós R. (2016). Efficient Hill Climber for Multi-Objective Pseudo-Boolean Optimization. 16th European Conference on Evolutionary Computation for Combinatorial Optimization (LNCS 9595), pp.
Chicano, Francisco, Tinós, Renato, Whitley, Darrell   +2 more
core  

An Open Framework for Constructing Continuous Optimization Problems [PDF]

Many artificial benchmark problems have been proposed for different kinds of continuous optimization, e.g., global optimization, multi-modal optimization, multi-objective optimization, dynamic optimization, and constrained optimization. However, there is
Li, C, Nguyen, TT, Wu, M, Yang, M, Zeng, S   +4 more
core   +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

CLMOAS: collaborative large-scale multi-objective optimization algorithms with adaptive strategies

Frontiers in Computer Science
In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of decision variables.
Peng Wang, Yanxiu Fu, Huiping Yuan, Zhongyang Xiao, Chi Huang, Zhao Yang, Yijing Zhang, Fenglin Zhou   +7 more
doaj   +1 more source

A Smart Bio‐Battery Facilitates Diabetic Bone Defect Repair Via Inducing Macrophage Reprogramming and Synergistically Modulating Bone Remodeling Coupling

Advanced Functional Materials, EarlyView.
This research presents a novel implantable bio‐battery, GF‐OsG, tailored for diabetic bone repair. GF‐OsG generates microcurrents in high‐glucose conditions to enhance vascularization, shift macrophages to the M2 phenotype, and regulate immune responses.
Nanning Lv, Haifu Sun, Wenxiang Tang, Yonggang Li, Zhonglai Qian, Lihui Hong, Chong Chen, Hongye Li, Jiaxiang Bai, Yusen Qiao, Mingming Liu   +10 more
wiley   +1 more source