Results 81 to 90 of about 5,527,579 (363)

Central Dysmyelination in SSADH‐Deficient Humans and Mice

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Succinic semialdehyde dehydrogenase deficiency (SSADHD) is an inherited metabolic disorder characterized by an accumulation of γ‐aminobutyric (GABA). In addition to its synaptic role as an inhibitory neurotransmitter, GABA also plays an important role in myelination.
Itay Tokatly Latzer, Henry H. C. Lee, Edward Yang, Cesar Alves, Mariarita Bertoldi, Caitlyn Fung, Spencer V. Steele, Eren Kule, Zijie Jin, Alexander Rotenberg, Jean‐Baptiste Roullet, Phillip L. Pearl   +11 more
wiley   +1 more source

A New Two-Stage Evolutionary Algorithm for Many-Objective Optimization

IEEE Transactions on Evolutionary Computation, 2019
Convergence and diversity are interdependently handled during the evolutionary process by most existing many-objective evolutionary algorithms (MaOEAs).
Y. Sun, Bing Xue, Mengjie Zhang, G. Yen
semanticscholar   +1 more source

Quantitative Iron Measurements in the Basal Ganglia of NBIA Patients Using QSM: Insights From a Tertiary Center

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Neurodegeneration with brain iron accumulation (NBIA) comprises rare genetic disorders characterized by predominantly extrapyramidal symptoms and iron deposition in the basal ganglia. Conventional magnetic resonance imaging (MRI) detects qualitative changes but cannot accurately quantify iron accumulation. Quantitative susceptibility
Özge Uygun, Alpay Özcan, Fuat Kaan Aras, Evrim Bozdemir, Sibel Uğur İşeri, Murat Gültekin, Nihan Hande Akçakaya, Orkhan Mammadov, Gülay Kır, Dilek İnce Günal, Neşe Tuncer, Fatma Betül Özdilek, Banu Özen Barut, Ercan Köse, Hülya Apaydın, Asuman Ali, Sultan Çağırıcı, Pınar Topaloğlu, Alp Dinçer, Zuhal Yapıcı   +19 more
wiley   +1 more source

The Method to Integrate Species Explode and Deracinate Algorithm With Particle Swarm Optimization Algorithm

IEEE Access
Effectively combining various evolutionary computing algorithms and leveraging the advantages of each can significantly enhance the convergence speed and solution quality of the algorithm.
Yongjian Yang, Youwei Deng, Bingsong Xiao, Xiaohong Zhao   +3 more
doaj   +1 more source

How to analyse evolutionary algorithms

Theoretical Computer Science, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ingo Wegener, Hans-Paul Schwefel, Hans-Georg Beyer   +2 more
openaire   +3 more sources

Evolutionary Algorithms in Intelligent Systems [PDF]

Mathematics, 2020
Evolutionary algorithms and metaheuristics are widely used to provide efficient and effective approximate solutions to computationally difficult optimization problems [...]
openaire   +3 more sources

Hydroxychloroquine Associated with Lower Glomerular Filtration Rate Decline in Lupus Nephritis

Arthritis Care &Research, Accepted Article.
Background Hydroxychloroquine (HCQ) protects kidney function in lupus nephritis (LN) by preventing flares, yet some cohort studies show no significant benefit in kidney function with HCQ. Clarifying these conflicting findings by showing early and long‐term benefits of HCQ on kidney function preservation is critical. Therefore, we analyzed data from our
Shivani Garg, Brad Rovin, Brad C. Astor, Tripti Singh, Fauzia Hollnagel, Megan Kuik, Lexie Kolton, Callie Saric, S. Sam Lim, Christie M. Bartels   +9 more
wiley   +1 more source

Evolutionary Algorithms for Reinforcement Learning

Journal of Artificial Intelligence Research, 1999
There are two distinct approaches to solving reinforcement learning problems, namely, searching in value function space and searching in policy space. Temporal difference methods and evolutionary algorithms are well-known examples of these approaches.
Alan C. Schultz, John J. Grefenstette, David E. Moriarty   +2 more
openaire   +4 more sources

A Strength Pareto Evolutionary Algorithm Based on Reference Direction for Multiobjective and Many-Objective Optimization

IEEE Transactions on Evolutionary Computation, 2017
While Pareto-based multiobjective optimization algorithms continue to show effectiveness for a wide range of practical problems that involve mostly two or three objectives, their limited application for many-objective problems, due to the increasing ...
Shouyong Jiang, Shengxiang Yang
semanticscholar   +1 more source

Data‐driven forecasting of ship motions in waves using machine learning and dynamic mode decomposition

International Journal of Adaptive Control and Signal Processing, EarlyView.
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez, Mauro Gaggero, Andrea Serani   +2 more
wiley   +1 more source