Ginzburg–Landau models of nonlinear electric transmission networks
Abstract Complex Ginzburg–Landau (CGL) equations serve as canonical models in a great
variety of physical settings, such as nonlinear photonics, dynamical phase transitions …
variety of physical settings, such as nonlinear photonics, dynamical phase transitions …
[HTML][HTML] Rhodopsin, light-sensor of vision
KP Hofmann, TD Lamb - Progress in Retinal and Eye Research, 2023 - Elsevier
The light sensor of vertebrate scotopic (low-light) vision, rhodopsin, is a G-protein-coupled
receptor comprising a polypeptide chain with bound chromophore, 11-cis-retinal, that …
receptor comprising a polypeptide chain with bound chromophore, 11-cis-retinal, that …
Calibrating deep neural networks using focal loss
Miscalibration--a mismatch between a model's confidence and its correctness--of Deep
Neural Networks (DNNs) makes their predictions hard to rely on. Ideally, we want networks …
Neural Networks (DNNs) makes their predictions hard to rely on. Ideally, we want networks …
Joint offloading and computing optimization in wireless powered mobile-edge computing systems
Mobile-edge computing (MEC) and wireless power transfer (WPT) have been recognized as
promising techniques in the Internet of Things era to provide massive low-power wireless …
promising techniques in the Internet of Things era to provide massive low-power wireless …
Underwater optical wireless communications, networking, and localization: A survey
Underwater wireless communications can be carried out through acoustic, radio frequency
(RF), and optical waves. Compared to its bandwidth limited acoustic and RF counterparts …
(RF), and optical waves. Compared to its bandwidth limited acoustic and RF counterparts …
On the root mean square error (RMSE) calculation for parameter estimation of photovoltaic models: A novel exact analytical solution based on Lambert W function
In the literature, one can find a lot of methods and techniques employed to estimate single
diode solar photovoltaic (PV) cell parameters. The efficiency of these methods is usually …
diode solar photovoltaic (PV) cell parameters. The efficiency of these methods is usually …
UAV-assisted relaying and edge computing: Scheduling and trajectory optimization
In this paper, we study an unmanned aerial vehicle (UAV)-assisted mobile edge computing
(MEC) architecture, in which a UAV roaming around the area may serve as a computing …
(MEC) architecture, in which a UAV roaming around the area may serve as a computing …
Optimal Hamiltonian simulation by quantum signal processing
The physics of quantum mechanics is the inspiration for, and underlies, quantum
computation. As such, one expects physical intuition to be highly influential in the …
computation. As such, one expects physical intuition to be highly influential in the …
Constrained variational policy optimization for safe reinforcement learning
Safe reinforcement learning (RL) aims to learn policies that satisfy certain constraints before
deploying them to safety-critical applications. Previous primal-dual style approaches suffer …
deploying them to safety-critical applications. Previous primal-dual style approaches suffer …
The emergence proposal in quantum gravity and the species scale
A bstract In the Emergence Proposal in Quantum Gravity it is conjectured that all light-
particle kinetic terms are absent in the fundamental ultraviolet theory and are generated by …
particle kinetic terms are absent in the fundamental ultraviolet theory and are generated by …