Sign Up to like & get
recommendations!
0
Published in 2025 at "Advanced Healthcare Materials"
DOI: 10.1002/adhm.202501753
Abstract: The treatment of osteosarcoma remains challenging due to limitations of chemotherapy. Anticancer peptides present a promising avenue as alternative therapeutic agents; however, they encounter significant drawbacks, including susceptibility to proteolytic degradation and constrained selectivity toward…
read more here.
Keywords:
cancer;
gradient dynamics;
tumor;
peptide ... See more keywords
Sign Up to like & get
recommendations!
0
Published in 2025 at "Quantum Information Processing"
DOI: 10.1007/s11128-025-04995-0
Abstract: Designing a mixed quantum channel is challenging due to the complexity of the transformations and the probabilistic mixtures of more straightforward channels involved. Fully characterizing a quantum channel generally requires preparing a complete set of…
read more here.
Keywords:
gradient dynamics;
quantum;
quantum channel;
mixed quantum ... See more keywords
Sign Up to like & get
recommendations!
0
Published in 2017 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2017.08.2023
Abstract: Abstract We derive a novel stability criterion for nonsmooth dynamical systems by virtue of a new set-valued Lie derivative of nonsmooth Lyapunov functions. This set-valued Lie derivative requires no computation of generalized gradients. Instead, it…
read more here.
Keywords:
criterion;
projected gradient;
stability criterion;
stability ... See more keywords
Sign Up to like & get
recommendations!
0
Published in 2021 at "Soft matter"
DOI: 10.1039/d1sm01032h
Abstract: The wetting of soft elastic substrates exhibits many features that have no counterpart on rigid surfaces. Modelling the detailed elastocapillary interactions is challenging, and has so far been limited to single contact lines or single…
read more here.
Keywords:
dynamics model;
elastic substrates;
liquid drops;
drops elastic ... See more keywords
Sign Up to like & get
recommendations!
0
Published in 2022 at "Physical review. E"
DOI: 10.1103/physreve.106.025315
Abstract: Despite the success achieved by the analysis of supervised learning algorithms in the framework of statistical mechanics, reinforcement learning has remained largely untouched by physicists. Here we move towards closing the gap by analyzing the…
read more here.
Keywords:
reinforcement learning;
equation;
dynamics reinforcement;
gradient ... See more keywords
Sign Up to like & get
recommendations!
0
Published in 2024 at "Physical Review Fluids"
DOI: 10.1103/physrevfluids.10.014003
Abstract: We present a mesoscopic hydrodynamic model for a spreading drop of volatile partially wetting liquid on a solid porous layer of small thickness. Thereby, evaporation takes place under strong confinement, i.e., we consider a drop…
read more here.
Keywords:
drop;
porous layer;
gradient dynamics;
porous substrate ... See more keywords
Sign Up to like & get
recommendations!
0
Published in 2019 at "IEEE Control Systems Letters"
DOI: 10.1109/lcsys.2018.2851375
Abstract: Continuous time primal-dual gradient dynamics (PDGD) that find a saddle point of a Lagrangian of an optimization problem have been widely used in systems and control. While the global asymptotic stability of such dynamics has…
read more here.
Keywords:
dual gradient;
primal dual;
stability;
gradient dynamics ... See more keywords
Sign Up to like & get
recommendations!
0
Published in 2024 at "IEEE Transactions on Automatic Control"
DOI: 10.1109/tac.2024.3397167
Abstract: In this article, we connect cognitive hierarchy theory with the pseudo-gradient dynamics in noncooperative systems to extend the pseudo-gradient dynamics with some prediction behaviors under level-$k$ thinking. In this framework, each agent believes that he…
read more here.
Keywords:
dynamics noncooperative;
incorporation likely;
pseudo gradient;
gradient dynamics ... See more keywords
Sign Up to like & get
recommendations!
1
Published in 2022 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2022.3179519
Abstract: This article studies the finite-time (FT) convergence of a fast primal–dual gradient dynamics (PDGD), called FT-PDGD, for solving constrained optimization with general constraints and cost functions. Based on the nonsmooth analysis and augmented Lagrangian function,…
read more here.
Keywords:
primal dual;
finite time;
dual gradient;
optimization ... See more keywords