Results 41 to 50 of about 1,503,716 (266)
Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization [PDF]
, 2013 Majorization-minimization algorithms consist of iteratively minimizing a majorizing surrogate of an objective function. Because of its simplicity and its wide applicability, this principle has been very popular in statistics and in signal processing.
Mairal, Julien
core +2 more sources
Memetic Artificial Bee Colony Algorithm for Large-Scale Global Optimization
, 2012 Memetic computation (MC) has emerged recently as a new paradigm of efficient algorithms for solving the hardest optimization problems. On the other hand, artificial bees colony (ABC) algorithms demonstrate good performances when solving continuous and ...
Brest, Janez +3 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background B‐cell lymphoblastic lymphoma (B‐LBL) represents a rare variety of non‐Hodgkin lymphoma, with limited research on its biology, progression, and management. Methods A retrospective analysis was performed on the clinical characteristics of 256 patients aged ≤18 years who received treatment under the China Net Childhood Lymphoma (CNCL)‐
Zhijuan Liu +20 more
wiley +1 more source
Design optimization of a large-scale thermoelectric generator
Journal of King Saud University: Engineering Sciences, 2018 The optimum implementation of a thermoelectric generator (TEG) is investigated. In order to study the feasibility of such system, a model for a large-scale TEG is designed and optimized to convert thermal energy into electricity.
O.M. Al-Habahbeh +4 more
doaj +1 more source
Topology Optimization of Large-Scale 3D Morphing Wing Structures
Actuators, 2021 This work proposes a systematic topology optimization approach for simultaneously designing the morphing functionality and actuation in three-dimensional wing structures.
Peter Dørffler Ladegaard Jensen +3 more
doaj +1 more source
Optimization Methods for Large-Scale Machine Learning
, 2018 This paper provides a review and commentary on the past, present, and future of numerical optimization algorithms in the context of machine learning applications.
Bottou, Léon +2 more
core +1 more source
Organoids in pediatric cancer research
FEBS Letters, EarlyView.Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley +1 more source
Real‐time assay of ribonucleotide reductase activity with a fluorescent RNA aptamer
FEBS Letters, EarlyView.Ribonucleotide reductases (RNR) synthesize DNA building blocks de novo, making them crucial in DNA replication and drug targeting. FLARE introduces the first single‐tube real‐time coupled RNR assay, which enables isothermal tracking of RNR activity at nanomolar enzyme levels and allows the reconstruction of allosteric regulatory patterns and rapid ...
Jacopo De Capitani +4 more
wiley +1 more source
Protein pyrophosphorylation by inositol pyrophosphates — detection, function, and regulation
FEBS Letters, EarlyView.Protein pyrophosphorylation is an unusual signaling mechanism that was discovered two decades ago. It can be driven by inositol pyrophosphate messengers and influences various cellular processes. Herein, we summarize the research progress and challenges of this field, covering pathways found to be regulated by this posttranslational modification as ...
Sarah Lampe +3 more
wiley +1 more source
Large scale active-learning-guided exploration for in vitro protein production optimization
Nature Communications, 2020 Cell-free lysates are a major platform for in vitro protein production but batch-to-batch variation makes production difficult to predict. Here the authors develop an active learning approach to optimising buffer conditions to bring homemade lysates up ...
Olivier Borkowski +6 more
doaj +1 more source