The current study examines the combined impacts of ultrasonic waves and nano silica (NS) on reducing the viscosity Sharqy Baghdad heavy crude oil with an API gravity of 20.32. NS of an average particle size of 59.93 nm and 563.23 m²/g surface area were produced utilizing the sol-gel technique from Iraqi sand. The XRD analysis indicates the existence of an amorphous silica, the SEM analysis showed that NS tends to agglomerate, and the FTIR spectra exhibited the presence of siloxane and silanol groups. In addition, the TGA analysis demonstrated a total weight loss of 15.62%, validating the thermal stability of the NS. The experiments included a study of the impact of ultrasonic power, exposure time, duty cycle, temperature, and the c

Dyslexia is a learning disability in which people face difficulty reading though they are intelligent and have motivation for reading. Therefore; it impacts the portion of the brain responsible for processing language. Such a condition compromises the learning efficiency of the affected person, which generally gets unnoticed. Even affected children are unaware of their state. The study investigates the knowledge and awareness of dyslexia among teachers of English in Iraqi primary schools. this study has three objectives: (i) To investigate the amount of awareness and knowledge among the primary school teachers of English in Baghdad City about dyslexia.; (ii) To examine how English teachers’ awareness of dyslexia is affected by the

Archives of Razi Institute (ARI)

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