The recent widespread novel network technologies for programming data planes are remarkably enhancing the customization of data packet processing. In this direction, the Programming Protocol-independent Packet Processors (P4) is envisioned as a disruptive technology, capable of configuring network devices in a highly customizable way. P4 enables network devices to adapt their behaviors to mitigate malicious attacks (e.g., denial of service). Distributed ledger technologies (DLTs), such as blockchain, allow secure reporting alerts on malicious actions detected across different areas. However, the blockchain suffers from major scalability concerns due to the consensus protocols needed to agree on a global state of the network. To overcome these limitations, new solutions have recently emerged. IOTA is a next-generation distributed ledger engineered to tackle the scalability limits while still providing the same security capabilities such as immutability, traceability, and transparency. This article proposes an architecture that integrates a P4-based data plane software-defined network (SDN) and an IOTA layer employed to notify about networking attacks. Specifically, we propose a fast, secure, and energy-efficient DLT-enabled architecture that combines the IOTA data structure, named Tangle, with the SDN layer to detect and notify about network threats.
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http://dx.doi.org/10.3390/s23062955 | DOI Listing |
ACS Nano
January 2025
College of Chemistry Chemical Engineering and Materials Science, Shandong Normal University, Jinan, Shandong 250014, China.
Coastal/offshore renewable energy sources combined with seawater splitting offer an attractive means for large-scale H electrosynthesis in the future. However, designing anodes proves rather challenging, as surface chlorine chemistry must be blocked, particularly at high current densities (). Additionally, waste seawater with increased salinity produced after long-term electrolysis would impair the whole process sustainability.
View Article and Find Full Text PDFMater Horiz
January 2025
College of Chemistry and Materials Science, Sichuan Normal University, Chengdu, 610068, China.
Hydrogels are promising materials for wearable electronics, artificial skins and biomedical engineering, but their limited stretchability, self-recovery and crack resistance restrict their performance in demanding applications. Despite efforts to enhance these properties using micelle cross-links, nanofillers and dynamic interactions, it remains a challenge to fabricate hydrogels that combine high stretchability, self-healing and strong adhesion. Herein, we report a novel hydrogel synthesized the copolymerization of acrylamide (AM), maleic acid (MA) and acrylonitrile (AN), designed to address these limitations.
View Article and Find Full Text PDFNat Sci Sleep
December 2024
Department of Orthopedics, University of Colorado School of Medicine, Aurora, CO, USA.
Background: Poor sleep is associated with longer recovery following adolescent concussion, making the longitudinal assessment of sleep important for monitoring recovery and identifying sleep disruptions. An important consideration for successful monitoring of sleep following concussion is the feasibility and adherence of a given sleep monitoring tool when used in an at-home environment. Understanding the usability of different sleep monitoring tools is essential for determining their applicability for longitudinal assessment in an ecologically valid environment.
View Article and Find Full Text PDFFront Plant Sci
December 2024
School of Software, Henan Institute of Science and Technology, Xinxiang, Henan, China.
Introduction: Pests are important factors affecting the growth of cotton, and it is a challenge to accurately detect cotton pests under complex natural conditions, such as low-light environments. This paper proposes a low-light environments cotton pest detection method, DCP-YOLOv7x, based on YOLOv7x, to address the issues of degraded image quality, difficult feature extraction, and low detection precision of cotton pests in low-light environments.
Methods: The DCP-YOLOv7x method first enhances low-quality cotton pest images using FFDNet (Fast and Flexible Denoising Convolutional Neural Network) and the EnlightenGAN low-light image enhancement network.
Small
January 2025
Department of Chemical Engineering, Toronto Metropolitan University, 350 Victoria Street, Toronto, ON, M5B 2K3, Canada.
Research into flexible solid-state supercapacitors for wearable electronics focuses on achieving high performance and safety. Gel polymer electrolytes (GPEs) are preferred over fully solid-state electrolytes due to their better ionic conductivity while addressing safety concerns associated with liquid electrolytes. This study aims to enhance high-performance gel polymer electrolytes (HP-GPEs) by improving the ion transfer rate of polyvinyl alcohol (PVA) with sulfonated hexagonal boron nitride (known as white-graphene) and exploring how rheology influences ion-conduction within HP-GPEs.
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