Beryllium Zinc Oxide (Be_xZn_1-xO) ternary nano thin films were deposited using the pulsed laser deposition (PLD) technique under a vacuum condition of 10^-3 torr at room temperature on glass substrates with different films thicknesses, (300, 600 and 900 nm). UV-Vis spectra study found the optical band gap for Be_0.2Zn_0.8O to be  (3.42, 3.51 and 3.65 eV) for the (300, 600 and 900nm) film thicknesses, respectively which is larger than the value of zinc oxide ZnO (3.36eV) and smaller than that of beryllium oxide BeO (10.6eV). While the X-ray diffraction (XRD) pattern analysis of ZnO, BeO and Be _0.2 Zn _0.8 O powder and nano-thin films indicated a hexa

This work has been done to prepare a series of new alkene compounds derived from 4-thiozolidinones by substituting different aldehydes, P-acetamido-phenol, and 2-mercapto-benzoimidazole, which were used as starting materials to form ester [I]a,b and then make hydrazides [II]a,b, which were used to prepare 1, 3, and 4-oxadiazoles [III]a,b, which were then used for prepared Schiff bases [IV]a-f, The next step was the synthesis of 4-thiazoldinone derivatives [V]a-f  from Schiff bases. The final step was the synthesis of alkenes [VII]a-f, the prepared derivatives were identified with spectral methods (FT-IR, 1H-NMR, mass, and CHNS). The antibacterial activity of the prepared derivatives was evaluated against four types of bacteria, pos

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

The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

Abstract

This study investigates the mechanical compression properties of tin-lead and lead-free alloy spherical balls, using more than 500 samples to identify statistical variability in the properties in each alloy. Isothermal aging was done to study and compare the aging effect on the microstructure and properties.

The results showed significant elastic and plastic anisotropy of tin phase in lead-free tin based solder and that was compared with simulation using a Crystal Plasticity Finite Element (CPEF) method that has the anisotropy of Sn installed. The results and experiments were in good agreement, indicating the range of values expected with anisotropic properties.

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Background: Obesity is a serious public health concern that has reached epidemic proportions; the prevalence, as well as the severity of obesity in adolescents is increasing at an alarming rate. A close relationship was found between weight status and dental caries. Thus this research aimed to assess the prevalence and severity of dental caries among overweight adolescent females in relation to physicochemical characteristics of stimulated whole saliva in comparison with normal weight adolescent females. Materials and methods: The total sample involved for nutritional status assessment is composed of 2678 females aged 13-15 years. This was performed using Body Mass Index specific for age and gender according to CDC growth chart (2000). The

In present work, new tetra-dentate ligand, titled 3,5-bis ((E)-5-Bromo-2-hydroxy benzylidene amino) benzoic acid (H₃L), was prepared via an acid-catalyzed condensation process. New four metallic ligand complexes with Co(II), Ni(II), Cu(II) and Zn(II) ions, were also prepared from the refluxing of equivalent moles. Ligand's structure and its complexes; were confirmed by numerous characterization methods, including Ultraviolet-Visible, Infrared, Mass Spectrometer, ¹H and ¹³C Nuclear Magnetic Resonance spectra, atomic absorption, magnetic moments, and molar conductivity measurements. The results of the spectroscopic analyzes proved that the prepared ligand acts as tetradentate bi-ionic ligand and it was bond

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col