Results 71 to 80 of about 1,308,678 (317)
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
Implementing physics-informed neural networks with deep learning for differential equations
Frontiers in Artificial IntelligencePhysics-aware machine learning integrates domain-specific physical knowledge into machine learning models, leading to the development of physics-informed neural networks (PINNs).
Frank Emmert-Streib +4 more
doaj +1 more source
A FRACTIONAL MODEL PREDICTIVE CONTROL DESIGN FOR 2-D GANTRY CRANE SYSTEM [PDF]
Journal of Engineering Science and Technology, 2018 Fractional calculus has been a research focus since the last four decades to control the dynamical systems. Advances in fractional calculus such as Fractional Model Predictive Control had shown that system dynamics could be controlled even more ...
ABHAYA P. SINGH, H. AGRAWAL
doaj
Predictive Model Evaluation for PHM
International Journal of Prognostics and Health Management, 2014 In the past decades, machine learning techniques or algorithms, particularly, classifiers have been widely applied to various real-world applications such as PHM.
Chunsheng Yang +3 more
doaj +1 more source
A new optimization algotithm with application to nonlinear MPC [PDF]
Modeling, Identification and Control, 2005 This paper investigates application of SQP optimization algorithm to nonlinear model predictive control. It considers feasible vs. infeasible path methods, sequential vs. simultaneous methods and reduced vs full space methods.
Frode Martinsen +2 more
doaj +1 more source
Synthesizing benchmarks for predictive modeling [PDF]
2017 IEEE/ACM International Symposium on Code Generation and Optimization (CGO), 2017 Predictive modeling using machine learning is an effective method for building compiler heuristics, but there is a shortage of benchmarks. Typical machine learning experiments outside of the compilation field train over thousands or millions of examples.
Cummins, C +3 more
openaire +6 more sources
Model Predictive Control for changing economic targets [PDF]
, 2012 The objective of this paper is to present recent results on model predictive control for tracking in the context of economic operation of a industrial plants.
Ferramosca, Antonio
core +1 more source
FEBS Letters, EarlyView.The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li +2 more
wiley +1 more source
APPLICATION OF MODEL PREDICTIVE CONTROL (MPC) TUNING STRATEGY IN MULTIVARIABLE CONTROL OF DISTILLATION COLUMN [PDF]
, 2007 A model predictive control strategy is proposed for multivariable nonlinear control problem in a distillation column. The aim is to provide a solution to nonlinear control problem that is favorable in terms of industrial implementation.
Wahid, A., Ahmad, A., A. Wahid, A. Ahmad
core +1 more source
FEBS Letters, EarlyView.In this study, we found that human cervical‐derived adipocytes maintain intracellular iron level by regulating the expression of iron transport‐related proteins during adrenergic stimulation. Melanotransferrin is predicted to interact with transferrin receptor 1 based on in silico analysis.
Rahaf Alrifai +9 more
wiley +1 more source