In this work, a CW CO2 laser was used for cutting samples of the fiber-reinforced
plastics (FRP) of three different types of reinforcing material; aramide, glass and carbon.
Cutting process was investigated throughout the variation of some parameters of cutting
process and their effects on cutting quality as well as the effect of an inert gas exist in the
interaction region and finally using a mechanical chopper in order to enhance the cutting
quality. Results obtained explained the possibility to perform laser cutting with high
quality in these materials by good control of the parameters and conditions of the process.

This study was designed to evaluate the ability of bioemulsifier to inhibit the growth of some pathogenic microorganisms. Fourteen isolates belonged to Serratia sp. were collected and tested for their ability to produce bioemulsifier. Results showed that Serratia marcescens S10 (isolated from the gut of the American cockroach) had the highest ability to produce bioemulsifier, among 14 isolates belong to Serratia spp. and it had the ability to inhibit the growth of some microorganisms. The production of bioemulsifier was detected by determination of emulsification index (E24%), qualitative drop-collapse test, emulsification activity (E.A) and measuring the surface tension (S.T). The results of bioemulsifier produced by Serratia marcescens S1

In this paper, we characterize normal composition operators induced by holomorphic self-map , when and .Moreover, we study other related classes of operators, and then we generalize these results to polynomials of degree n.

The CdS quantum dots were prepared by chemical reaction
of cadmium oleylamine (Cd –oleylamine complex) with the
sulfite-oleylamine (S-oleylamine) with 1:6 mole ratios. The
optical properties structure and spectroscopy of the product
quantum dot were studied. The results show the dependence of the
optical properties on the crystal dimension and the formation of
the trap states in the energy band gap.

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

This study came to discuss the subject of industries dependent on petrochemical industries in Iraq (plastic as a model) during the period 2005–2020, and the study concluded that the plastic industries contribute to areas of advancement and progress and opportunities to deal efficiently with the challenges posed by the new variables, the most important of which is the information revolution. communications and trade liberalization, and this is what contributes to the competitiveness of these industries. And because the petrochemical industry in Iraq has an active role in establishing plastic industrial clusters and clusters of micro, small, and medium industries by providing the necessary feedstock for these industries in various fields

Acute appendicitis is one of the commonest causes of acute abdomen. There is a wide discussion and controversy on the surgical and nonsurgical treatment of acute uncomplicated appendicitis. The aim of this study was to evaluate the efficacy and outcomes of the conservative management of selected cases of acute appendicitis with an antibiotic first plan.