In this work; Silicon dioxide (SiO2) were fabricated by pulsed
laser ablation (PLA). The electron temperature was calculated by
reading the data of I-V curve of Langmuir probe which was
employed as a diagnostic technique for measuring plasma properties.
Pulsed Nd:YA Glaser was used for measuring the electron
temperature of SiO2 plasma plume under vacuum environment with
varying both pressure and axial distance from the target surface. The
electron temperature has been measured experimentally and the
effects of each of pressure and Langmuir probe distance from the
target were studied. An inverse relationship between electron
temperature and both pressure and axial distance was observed.

In Iraq, breast cancer incidence exceeds any other type of cancers and the etiology not understood well.Epstein Barr virus is a gamma herpesviruses and one of carcinogenic viruses that may implicated tobreast carcinogenesis. The nuclear antigen-1 (EBNA-1) protein is the sole EBV antigen that presentedin all tumors related to EBV and plays pivotal roles in carcinogenesis of the virus. Examination appliedby immunohistochemistry (IHC) to detect and demonstrate the correlation between (EBNA-1) and tumorsuppressor protein (P53) expression. The study includes paraffin-embedded tissue blocks of ninety 90malignant breast tissues and thirty 30 normal breast autopsies. EBNA-1 was significantly expressed in 40/90(44.4%) of malignant tissues wh

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

In this study, the concentrations of uranium for four species of plants; Spinacia, Brassica Oleracea, BEASSICA Oleracea Var Capitata and Beta Vulgaris were measured in addition to the measurement of uranium concentrations in the selected soil by calculating the number of significant traces of alpha in CR-39. The 2.455 Bq/kg in Spinacia plant were the highest concentration while the lowest concentration of uranium were 1.91 Bq/kg in BEASSICA Oleracea Var Capitata plant. As for the transfer factor, the highest value 0.416 were found in Spinacia plant and the lowest value 0.323 were found in BEASSICA Oleracea Var Capitata plant. The uranium in the models studied in it did not exceed the international limit, according to the International Atomi

KE Sharquie, AA Noaimi, MS Younis, BS Al-Sultani, Journal of Cosmetics, Dermatological Sciences and Applications, 2014 - Cited by 5

This work, in fact, is an English language teaching study (henceforth, ELT) which may provide the inspiration for much –needed research on issues such as testing students' level of achievement in articulatory phonetics at the university level. It attempts to answer two questions: 1)What is college students' level of achievement in articulatory phonetics? 2- Are there any statistical significant differences in the achievement of college students in articulatory phonetics between the production and recognition testing techniques? This research falls into three sections: Section one indicates the problem, the aims, the hypotheses, the procedures, the limits and the value of the study. Section two provides a general overview of the articul

It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological