The purpose of this subject is to identify what is being studied in the article, which is the involvement of human Metapneumovirus in children with respiratory illnesses. During the period November 2020 to February 2021, 100 patients with respiratory tract infections were admitted to Al Zahra Teaching Hospital and AL-Forat AL-Awsat Teaching Hospital in Najaf Governorate. Nasopharyngeal swabs were collected from patients for molecular diagnosis of human metapneumovirus using Real-Time-PCR. The patients were distributed based on age into five groups as follows (Less than one, 1-2, 2-3, 3-4, and 4-5 years), and twenty samples of healthy individuals were approved as a control group without any clinical signs of infection. the children of age gr

To produce Zinc Oxide NanoParticles, ZnO-NPs, different methods can be used. However, the utilization of Liquid-Phase Pulsed Laser Ablation, LP-PLA, methodology of three distinct environment of aqueous using pure zinc plate will be one of the approaches for this job. Thus, in this work, concentrates on the influence of the results after employing some changes on the environment in other words, the influence of the NPs size and/or the NPs availability/appearance. Cetyltrimethylammonium Bromide, CTAB, is one of the three surfactants that have been used in the water-based solution. That is, the Sodium Dodecyl Sulfate, SDS, besides the Distilled Water, DW, the three surfactants will be ready when the molarity of the DW is around 10− 3 M. Th

Biodiesel production process was attracted more attention recently due to the surplus quantity of glycerol (G) as a byproduct from the process. Glycerol Utilization must take in to consideration to fix this issue also, to ensure biodiesel industry sustainability. Highly amount of Glycerol converted to more benefit material Glycerol carbonate (GC) was one of the most allurement compound derived from glycerol by transesterification of glycerol with dimethyl carbonate (DMC). Various parameters have highly impact on transesterification was investigated like catalyst loading (1-5) %wt., molar ratio of DMC: glycerol (5:1 – 1:1), reaction time (30 - 150) min and temperature (40 – 80) ᴼC. The Optimum glycerol carbonate yie

Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

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

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