Micro-perforated panel (MPP) absorber is increasingly gaining popularity as an alternative sound absorber in buildings compared to the well-known synthetic porous materials. A single MPP has a typical feature of a Helmholtz resonator with a high amplitude of absorption but a narrow absorption frequency bandwidth. To improve the bandwidth, a single MPP can be cascaded with another single MPP to form a double-layer MPP. This paper proposes the introduction of inhomogeneous perforation in the double-layer MPP system (DL-iMPP) to enhance the absorption bandwidth of a double-layer MPP. Mathematical models are proposed using the equivalent electrical circuit model and are validated with experiments with good agreement. It is revealed that the DL-

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

To evaluate and improve the efficiency of photovoltaic solar modules connected with linear pipes for water supply, a three-dimensional numerical simulation is created and simulated via commercial software (Ansys-Fluent). The optimization utilizes the principles of the 1st and 2nd laws of thermodynamics by employing the Response Surface Method (RSM). Various design parameters, including the coolant inlet velocity, tube diameter, panel dimensions, and solar radiation intensity, are systematically varied to investigate their impacts on energetic and exergitic efficiencies and destroyed exergy. The relationship between the design parameters and the system responses is validated through the development of a predictive model. Both single and mult

The present study aims to study the correlation between visfatin levels and metabolic syndrome in Iraqi obese adolescence (with and without metabolic syndrome) and its relation with other studied biochemical parameters. Sixty obese adolescences were depended in this study (with and without metabolic syndrome), compared with (30) non-obese children as control group. This study was done in the period from April 2020 until the end of December 2020, in the National Diabetes Centre/Mustansiriya University, Baghdad/Iraq. There were no significant differences in age, height, waist circumferences (WC), and diastolic blood pressure (DBP) in the patients' groups. In contrast, a significant increase differs (p<0.05) was recorded in the values of

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Background: fixed orthodontic appliances deleterious influence on gingival health is well documented. Association between weight status and gingival health is presented in many studies. This study aimed to evaluate how early the impact of fixed orthodontic therapy on patients` gingival health, and if there are differences of that impact among different weight status groups. Materials and Methods: Sample consisted of 54 patients (25 males, 29 females; age limits are 16 -18 years) going under the course of treatment with fixed orthodontic appliance. Patients were categorized according to their Body Mass Index (BMI) into 3 weight status groups considering WHO charts in 2007 (underweight, normal weight, overweight and obese), then determinat

The Bi2Se3 compound was synthesis by fusing initial compounds consisting of
extra pure elements in stoichiometric ratio from elements compound, charged inside
quartz ampoule. The crystal growth of Bi2Se3 carried out using Brighaman technique
process from melting f (Bi+Se ) at temperature of 810 ºC for about 48 hrs. Single crystal
of Bi2Se3 has been grown in direction (211) after slow cooling on account of heat
gradient to zone furnaces at cooling rate (1-3) C/hr. The structure study of the compound
was determined by x-ray diffraction technique, which it has bismuthinite structure and
orthorhombic unit cell with lattice parameters of a=10.2678 Å, b=11.2392 Å and
c=5.1737 Å