Results 31 to 40 of about 11,915,044 (298)
Receding horizon control strategy for an electric vehicle with dual-motor coupling system in consideration of stochastic vehicle mass. [PDF]
Additional degrees of freedom existed in dual-motor coupling system bring considerable challenge to the optimal control of electric vehicles. Moreover, the stochastic characteristic of vehicle mass can further increase this challenge.
Hongqiang Guo +4 more
doaj +1 more source
Nonlinear Optimal Control for Stochastic Dynamical Systems
This paper presents a comprehensive framework addressing optimal nonlinear analysis and feedback control synthesis for nonlinear stochastic dynamical systems.
Manuel Lanchares, Wassim M. Haddad
doaj +1 more source
We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation
Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang +2 more
wiley +1 more source
Golgi enzymes are retrieved from the plasma membrane to the trans‐Golgi network
Golgi enzymes are traditionally considered resident proteins retained within the Golgi apparatus. Here, we demonstrate that a subset transiently reaches the cell surface and is subsequently retrieved to the trans‐Golgi network via retrograde transport. Using a nanobody‐based toolkit, we uncover a dynamic trafficking cycle of several Golgi enzymes.
Dominik P. Buser, Tina Junne
wiley +1 more source
Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry
EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri +5 more
wiley +1 more source
Membrane composition and thermodynamic identity as boundaries of life for synthetic cell research
What makes a cell a cell? The boundary of a living cell is not just a wall. Read as a Markov blanket, the membrane separates internal from external states, generating identity and non‐equilibrium order. Can this identity be rebuilt from scratch in a synthetic cell?
Caterina Presutti, Bert Poolman
wiley +1 more source
With the penetration of renewable generation, electric vehicles and other random factors in power systems, the stochastic disturbances are increasing significantly, which are necessary to be handled for guarantying the security of systems.
Xue Lin, Lixia Sun, Ping Ju, Hongyu Li
doaj +1 more source
A Stochastic Gradient Descent Approach for Stochastic Optimal Control
Summary: In this work, we introduce a stochastic gradient descent approach to solve the stochastic optimal control problem through stochastic maximum principle. The motivation that drives our method is the gradient of the cost functional in the stochastic optimal control problem is under expectation, and numerical calculation of such an expectation ...
Archibald, Richard +2 more
openaire +2 more sources
Diffusion Approximation and Optimal Stochastic Control [PDF]
By the same goal with the previous paper of these authors [SIAM J. Control Optimization 34, No. 1, 161-178 (1996; Zbl 0867.93085)] but considering the case of a stochastic control model admitted a diffusion approximation, they show in the present paper that an optimal Lipschitz feedback control of the limit model \[ dX_t = [A_0 (t,X_t)+ a_1 (t,X_t)u_t]
Liptser, R. +2 more
openaire +2 more sources

