The efficiency of solar energy absorption in solar heaters is increased by the use of selective absorption coating that possesses high absorption of solar radiation in the UV-visible spectrum as well as low emission at the operating temperature in the infrared region. In this work, novel selective coatings were synthesized by improving the selectivity of chromium oxide (Cr₂O₃) nanoparticles by doping with carbon nanoparticles using the exploding wire technique for carbon rods by high current in suspended Cr₂O₃ particles. The structural properties and surface topography were studied by XRD and FE-SEM, which illustrate the carbon-coated Cr₂O₃ nanoparticles. The prepar

This paper deals with the blow-up properties of positive solutions to a parabolic system of two heat equations, defined on a ball in  associated with coupled Neumann boundary conditions of exponential type. The upper bounds of blow-up rate estimates are derived. Moreover, it is proved that the blow-up in this problem can only occur on the boundary.

The aim of this research is to study the effect of heat transfer on the oscillating flow of the hydrodynamics magnetizing Eyring-Powell fluid through a porous medium under the influence of temperature and concentration for two types of engineering conditions "Poiseuille flow and Couette flow". We used the perturbation method to obtain a clear formula for fluid motion. The results obtained are illustrated by graphs.

A prey-predator interaction model has been suggested in which the population of a predator consists of a two-stage structure. Modified Holling's disk equation is used to describe the consumption of the prey so that it involves the additional source of food for the predator. The fear function is imposed on prey. It is supposed that the prey exhibits anti-predator behavior and may kill the adult predator due to their struggle against predation. The proposed model is investigated for existence, uniqueness, and boundedness. After determining all feasible equilibrium points, the local stability analyses are performed. In addition, global stability analyses for this model using the Lyapunov method are investigated. The chance of occurrence of loc

Low-temperature stratification, high-volumetric storage capacity, and less-complicated material processing make phase-changing materials (PCMs) very suitable candidates for solar energy storage applications. However, their poor heat diffusivities and suboptimal containment designs severely limit their decent storage capabilities. In these systems, the arrangement of tubes conveying the heat transport fluid (HTF) plays a crucial role in heat communication between the PCM and HTF during phase transition. This study investigates a helical coil tube-and-shell thermal storage system integrated with a novel central return tube to enhance heat transfer effectiveness. Three-dimensional computational fluid dynamics simulations compare the proposed d

The aim of the present study was to demonstrate the possible role of statins on the inflammatory biomarkers in patients with periodontal disease (PD) This cross-sectional study involved 74 patients with PD and/or dyslipidemia divided into Group A: 34 patients with PD (nonstatins users); Group B: 40 patients with PD (statins users); and Group C: 30 healthy controls. Total cholesterol (TC), triglyceride (TG) and high-density lipoprotein, C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and malondialdehyde (MDA) were measured . Blood pressure prolife and indices of PD were evaluated in each group. Statistical analysis was conducted by using SPSS version 20.0.

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise