Secure channel estimation model for cognitive radio network physical layer security using two-level shared key authentication.

Physical Layer Security (PLS) in Cognitive Radio Networks (CRN) improves the confidentiality, availability, and integrity of the external communication between the devices/ users. The security models for sensing and beamforming reduce the impact of adversaries such as eavesdroppers in the signal processing layer. To such an extent, this article introduces a Secure Channel Estimation Model (SCEM) using Channel State Information (CSI) and Deep Learning (DL) to improve the PLS.

Effect of surface-engineered AuNPs on gene expression, bacterial interaction, protein denaturation, and toxicology assay: an and model.

We investigated the and uses of pamoic acid functionalized gold nanoparticles (PA@AuNPs), with a focus on determining their safety and potential toxicity in living beings. To test this theory, the bacterial interaction of PA@AuNPs was studied using , , and cultures, as well as the inhibition of the bovine serum albumin (BSA) protein. The real-time polymerase chain reaction (RT-PCR) is used to measure the expression of target genes.

Design and SAR Analysis of an AMC-Integrated Wearable Cavity-Backed SIW Antenna.

Wearable communication technologies necessitate antenna designs that harmonize ergonomic compatibility, reliable performance, and minimal interaction with human tissues. However, high specific absorption rate (SAR) levels, limited radiation efficiency, and challenges in integration with flexible materials have significantly constrained widespread deployment. To address these limitations, this manuscript introduces a novel wearable cavity-backed substrate-integrated waveguide (SIW) antenna augmented with artificial magnetic conductor (AMC) structures.

A review on effect of nanoparticle addition on thermal behavior of natural fiber-reinforced composites.

Always, the environment in which humans live needs to be saved from various calamities, and one such calamity is usage of petroleum-based products. Petroleum-based products are derived from various synthetic processes that adversely affect the environment. It may not reflect immediately, but it affects in the near future.

Comparative investigation of structural properties and biological applications of chemical and biogenic synthesis of zirconium dioxide (ZrO) nanoparticles using Passiflora edulis.

Over the last decade, the environmental and wellness cost of antibiotic drug resistance to the societies have been astounding and require urgent attention Metal oxide nanomaterials have been achieved a pull-on deal with its entire applications in biological and photocatalytic applications. The present study conducts a comparative investigation on chemical and biogenic synthesis of zirconium dioxide (ZrO) nanoparticles aimed at enhancing their efficacy in their applications. The plant extract of Passiflora edulis act as a reducing and capping properties offering a sustainable and eco-friendly alternative.

An intelligent magnetic resonance imagining-based multistage Alzheimer's disease classification using swish-convolutional neural networks.

Alzheimer's disease (AD) refers to a neurological disorder that causes damage to brain cells and results in decreasing cognitive abilities and memory. In brain scans, this degeneration can be seen in different ways. The disease can be classified into four stages: Non-demented (ND), moderate demented (MoD), mild demented (MiD), and very mild demented (VMD).

Facet dependent ultralow thermal conductivity of zinc oxide coated silver fabric for thermoelectric devices.

The conversion efficiency of a thermoelectric power generator depends on the dimensionless figure-of-merit (ZT) of the constituent thermoelectric materials, which is mainly determined by their Seebeck coefficient as well as the electrical and thermal conductivity. ZnO holds promise for thermoelectric applications, yet its use is currently limited by low electrical conductivity and high thermal conductivity. Herein, we demonstrate how thermal conductivity of ZnO can be significantly reduced by intelligently combining it with a cellulose-based Ag fabric using a one-step hydrothermal method, and how different ratios of zinc nitrate hexahydrate (ZNH) to hexamethylenetetramine (HMT) can be used to fine-tune the thermoelectric performance of the resulting composite.

Bioaerogels from biomass waste: An alternative sustainable approach for wastewater treatment.

The generation of municipal solid waste is projected to increase from 2.1 billion tonnes in 2023 to 3.8 billion tonnes by 2050.

Analysis and control of grid-interactive PV-fed BLDC water pumping system with optimized MPPT for DC-DC converter.

In this study, a novel water pumping module fed by grid interactive Photo-Voltaic with a bidirectional Power Flow Control was proposed. In addition to improving the pumping system's reliability, a water pump is powered by a brushless DC motor drive. This method enables the pump to work at its maximum capacity for the entirety of that day, regardless of the weather.

Aggregation induced emission "Turn on" ultra-low detection of anti-inflammatory drug flufenamic acid in human urine samples by carbon dots derived from bamboo stem waste.

Carbon dot-based fluorescence sensors have attracted research interest for the selective determination of anti-inflammatory drugs in biological fluids and environments. The overdose and accumulation of anti-inflammatory drugs in tissues can cause chronic side effects including abdominal pain, and renal damage. Herein, we report a new fluorescent probe, bamboo stem waste-derived carbon dots (BS-CDs) for highly sensitive detection of Flufenamic acid (FA), a hazardous anti-inflammatory drug.

Experimental investigations of dual functional substrate integrated waveguide antenna with enhanced directivity for 5G mobile communications.

Antennas with higher gain and efficiency deliver superior performance across a wide frequency range. Achieving these characteristics at high frequencies while keeping a compact size necessitates sophisticated design approaches. This research presents a substrate-integrated waveguide (SIW) cavity-backed slotted patch antenna (SPA) tailored for the 28 GHz and 34 GHz frequency bands.

Variational Autoencoders for Network Lifetime Enhancement in Wireless Sensors.

Wireless sensor networks (WSNs) are structured for monitoring an area with distributed sensors and built-in batteries. However, most of their battery energy is consumed during the data transmission process. In recent years, several methodologies, like routing optimization, topology control, and sleep scheduling algorithms, have been introduced to improve the energy efficiency of WSNs.

Synthesis of a novel AlBeSiTiV light weight HEA coating on SS316 using atmospheric plasma spray process.

High Entropy Alloys (HEAs) are currently a subject of significant research interest in the fields of materials science and engineering. They are rapidly evolving due to their exceptional properties, and there is considerable focus on expanding their application potential by developing HEA coatings on various substrate materials. This area of study holds promise for advancing technology and innovation in diverse industries.

Machine Learning Meets Meta-Heuristics: Bald Eagle Search Optimization and Red Deer Optimization for Feature Selection in Type II Diabetes Diagnosis.

This article investigates the effectiveness of feature extraction and selection techniques in enhancing the performance of classifier accuracy in Type II Diabetes Mellitus (DM) detection using microarray gene data. To address the inherent high dimensionality of the data, three feature extraction (FE) methods are used, namely Short-Time Fourier Transform (STFT), Ridge Regression (RR), and Pearson's Correlation Coefficient (PCC). To further refine the data, meta-heuristic algorithms like Bald Eagle Search Optimization (BESO) and Red Deer Optimization (RDO) are utilized for feature selection.

Environmental water quality prediction based on COOT-CSO-LSTM deep learning.

Water resource management relies heavily on reliable water quality predictions. Predicting water quality metrics in the watershed system, including dissolved oxygen (DO), is the main emphasis of this work. The enhanced long short-term memory (LSTM) model was suggested to improve the model's performance.

Low-Cost Self-Reconstructed High Entropy Oxide as an Ultra-Durable OER Electrocatalyst for Anion Exchange Membrane Water Electrolyzer.

Future energy loss can be minimized to a greater extent via developing highly active electrocatalysts for alkaline water electrolyzers. Incorporating an innovative design like high entropy oxides, dealloying, structural reconstruction, in situ activation can potentially reduce the energy barriers between practical and theoretical potentials. Here, a Fd-3m spinel group high entropy oxide is developed via a simple solvothermal and calcination approach.