Results 111 to 120 of about 977,934 (315)
A Formulation of nonlinear model predictive control using automatic differentiation [PDF]
An efficient algorithm is developed to alleviate the computational burden associated with nonlinear model predictive control (NMPC). The new algorithm extends an existing algorithm for solutions of dynamic sensitivity from autonomous to non-autonomous ...
Cao, Yi
core +1 more source
The typical control strategy for wind energy conversion systems (WECS) is the maximum power coefficient tracking method. However, this method limits the participation of wind turbines in power quality improvement in the network.
Lea Riachy +3 more
doaj +1 more source
Investigating transcription factor dynamics in health and disease using FRAP
FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
The role of miR‐335‐5p in the redifferentiation of BRAF p.V600E thyroid cancers
The BRAF p.V600E mutation promotes thyroid cancer dedifferentiation and radioiodine resistance. Using a network approach, we identified miR‐335‐5p as a key regulator of BRAF‐mutated thyroid tumors. Restoring miR‐335‐5p increased thyroid‐specific gene expression and iodine uptake in cells and organoids.
Valeria Pecce +11 more
wiley +1 more source
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat +8 more
wiley +1 more source
Predictive feedback control using a multiple model approach [PDF]
A new method of designing predictive controllers for SISO systems is presented. The controller selects the model used in the design of the control law from a given set of models according to a switching rule based on output prediction errors. The goal is
Giovanini, L., Grimble, M.J.
core
High-order volterra model predictive control and its application to a nonlinear polymerisation process [PDF]
Model Predictive Control (MPC) has recently found wide acceptance in the process industry, but the existing design and implementation methods are restricted to linear process models. A chemical process involves, however, severe nonlinearity which cannot
Kashiwagi, H., Li, Y.
core +1 more source
Enhanced Model Predictive Control Using State Variable Feedback for Steady-State Error Cancellation
The rapid dynamic responses of predictive control algorithms are widely acknowledged. However, achieving accurate steady-state reference tracking hinges not just on a precise mathematical model of the system but also on its parameters.
Marcos Andreu +5 more
doaj +1 more source
Estimation and control using sampling-based Bayesian reinforcement learning
Real-world autonomous systems operate under uncertainty about both their pose and dynamics. Autonomous control systems must simultaneously perform estimation and control tasks to maintain robustness to changing dynamics or modelling errors.
Patrick Slade +3 more
doaj +1 more source
Tumour–host interactions in Drosophila: mechanisms in the tumour micro‐ and macroenvironment
This review examines how tumour–host crosstalk takes place at multiple levels of biological organisation, from local cell competition and immune crosstalk to organism‐wide metabolic and physiological collapse. Here, we integrate findings from Drosophila melanogaster studies that reveal conserved mechanisms through which tumours hijack host systems to ...
José Teles‐Reis, Tor Erik Rusten
wiley +1 more source

