This study investigates the corrosion inhibition performance of a newly synthesized quinazolinone derivative, AMQ, on mild steel in a hydrochloric acid medium. The inhibition efficiency was evaluated using potentiodynamic polarization at varying inhibitor concentrations (100–250 ppm) and temperatures (303– 333 K). The results showed that AMQ exhibited effective corrosion inhibition, with the highest efficiency of 74% observed at 250 ppm and 323 K. Density Functional Theory (DFT) calculations were conducted to study the electronic properties of AMQ and its adsorption behavior. The thermodynamic parameters, including activation energy, enthalpy, and Gibbs free energy, were calculated, indicating spontaneous adsorption of AMQ onto the meta

This research studies the Saudi women participation in the visual arts, presents descriptive and analytical overview on their artworks and assess development through their participation in the said exhibition, frequency of participation, and aims to understand the most important stages and changes of the subjects addressed, artistic styles and the factors affecting these results in view of female artist's attitude pertaining to several aspects such as administrative organization, judging committees etc.

Interviews were held with a sample of female artists, 17 artists from different regions and generations out of 182 participants and reviewed relevant exhibition literature during the period 1979-2018. The research problem is to id

In this research, annealed nanostructured ZnO catalyst water putrefaction system was built using sun light and different wavelength lasers as stimulating light sources to enhance photocatalytic degradation activity of methylene blue (MB) dye as a model based on interfacial charges transfer. The structural, crystallite size, morphological, particle size, optical properties and degradation ability of annealed nanostructured ZnO were characterized by X-Ray Diffraction (XRD), Atomic Force Microscopy (AFM) and UV-VIS Spectrometer, respectively. XRD results demonstrated a pure crystalline hexagonal wurtzite with crystalline size equal to 23 nm. From AFM results, the average particle size was 79.25nm. All MB samples and MB with annealed nanostr

     In the present work effect of recycled heating and cooling on the values of concrete compressive strength due to high temperature of 400⁰C was studied.

    The tests show that the percent of reduction in compressive strength of the samples which exposed to a temperature of 400⁰C for one cycle was 32.5%, while the reduction was 52.7% for the samples which were exposed to recycled heating and cooling of ten times .      

   Moreover a study of the effect of specimen sizes on the percentages of compressive strength reduction due to high temperature

Cervical ectropion is considered to be a physiologic condition caused by columnar epithelium migration from the cervical canal into the vaginal portion of the cervix and usually there is no treatement for clinically asymptomatic cervical ectropion . Treatment can be achieved by thermal cauterization (Electrocautery), Cryosurgery or laser vaporization. Aim of the study: To study the effectiveness of CO2 laser (10600nm) in treatment of symptomatic cervical ectropion . Setting: The study was carried out at Laser Medicine Research Clinic at the Institute of Laser for Postgraduate Studies, University of Baghdad between the first of August 2013 to the end of October 2013. Patients and Methods: Ten female Patients with age range between 25-48 y

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm