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20 pages, 1686 KB  
Article
Dynamic Security-Aware Resource Allocation in Quantum Key Distribution-Enabled Optical Networks
by Vimal Bhatia, Adolph Kasegenya and Bowen Chen
Photonics 2025, 12(7), 645; https://doi.org/10.3390/photonics12070645 - 25 Jun 2025
Cited by 1 | Viewed by 1132
Abstract
The demand for secure communication in the age of quantum technologies has driven progress in quantum key distribution (QKD) techniques for optical networks. This research addresses the issues of high blocking probabilities (BPs) and the proper utilization of quantum resources in varying network [...] Read more.
The demand for secure communication in the age of quantum technologies has driven progress in quantum key distribution (QKD) techniques for optical networks. This research addresses the issues of high blocking probabilities (BPs) and the proper utilization of quantum resources in varying network loads by introducing a novel heuristic approach, termed dynamic security-aware quantum resource allocation (D-SQRA), designed for dynamic resource allocation in QKD-enabled optical networks. We propose two D-SQRA algorithms to employ an adaptive resource assignment (RA) strategy that concurrently addresses routing, wavelength, and time-slot selection while dynamically modifying security levels according to the real-time network load and resource availability. We evaluate the proposed D-SQRA performance against two conventional methods, namely, fixed security quantum resource allocation (F-SQRA) and baseline quantum resource allocation (B-QRA). We discuss the results for NSFNET and UBN24 topologies for network security performance metrics such as network security performance (NSP), BP, quantum key utilization (QKU), and time-slot utilization. The results show that the proposed D-SQRA algorithms provide significant improvement with respect to conventional techniques in addressing proper resource utilization and management by reducing BPs of the new incoming connection requests. Full article
(This article belongs to the Special Issue Enabling Technologies for Optical Communications and Networking)
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13 pages, 9534 KB  
Article
Coarse-Grained MD Simulations of Opioid Interactions with the μ-Opioid Receptor and the Surrounding Lipid Membrane
by Sourav Ray, Konstantin Fackeldey, Christoph Stein and Marcus Weber
Biophysica 2023, 3(2), 263-275; https://doi.org/10.3390/biophysica3020017 - 6 Apr 2023
Cited by 1 | Viewed by 3356
Abstract
In our previous studies, a new opioid (NFEPP) was developed to only selectively bind to the μ-opoid receptor (MOR) in inflamed tissue and thus avoid the severe side effects of fentanyl. We know that NFEPP has a reduced binding affinity to MOR [...] Read more.
In our previous studies, a new opioid (NFEPP) was developed to only selectively bind to the μ-opoid receptor (MOR) in inflamed tissue and thus avoid the severe side effects of fentanyl. We know that NFEPP has a reduced binding affinity to MOR in healthy tissue. Inspired by the modelling and simulations performed by Sutcliffe et al., we present our own results of coarse-grained molecular dynamics simulations of fentanyl and NFEPP with regards to their interaction with the μ-opioid receptor embedded within the lipid cell membrane. For technical reasons, we have slightly modified Sutcliffe’s parametrisation of opioids. The pH-dependent opioid simulations are of interest because while fentanyl is protonated at the physiological pH, NFEPP is deprotonated due to its lower pKa value than that of fentanyl. Here, we analyse for the first time whether pH changes have an effect on the dynamical behaviour of NFEPP when it is inside the cell membrane. Besides these changes, our analysis shows a possible alternative interaction of NFEPP at pH 7.4 outside the binding region of the MOR. The interaction potential of NFEPP with MOR is also depicted by analysing the provided statistical molecular dynamics simulations with the aid of an eigenvector analysis of a transition rate matrix. In our modelling, we see differences in the XY-diffusion profiles of NFEPP compared with fentanyl in the cell membrane. Full article
(This article belongs to the Special Issue Molecular Structure and Simulation in Biological System)
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