ABSTRACT : This research involves the synthesis of five to seven heterocyclic compounds starting with Schiff’s bases which derived from oxime as a starting material. 1.3-oxazepine derivatives were prepared from adding different anhydrides to the Schiff bases, tetrazole and thiazolidinone derivatives synthesized from add sodium azide and thioglycolic acid to the same Schiff’s bases as a five members ring. Pyrimidine derivatives were prepared after the reaction of the azomethine group with acetyl chloride and then urea and thiourea to synthesis on derivatives contain the six members ring. Another step included identified and confirmed these compounds by FT- IR, 1HNMR, TLC and 13CNMR finally, step included the assay of biological activity

Abstract

The current research aims to identify the most prominent beliefs about coronavirus of Baghdad University students, as well as to identify the prominent beliefs toward coronavirus of male and female students. To achieve the research objectives, a questionnaire of (15) items was administered to a sample of (600) male and female students collected from ten different colleges at the university of Baghdad. The findings of the research illustrated that item (8) took priority as students believe there is a misleading about coronavirus spreading by governments, item (2) which indicated that coronavirus is man-made took level two, followed by item (10), it proposes that coronavirus emerged from the American milit

Objective(s): To evaluate of nurses practice toward orthopaedic wound infection and to determine the
relationship between orthopaedic nurses practice and their demographic data characteristic
Methodology: A descriptive study was carried out at orthopaedic wards of Baghdad Teaching Hospital started
from February 1
st, 2011 to August 30th, 2011. A non-probability sample of (39) orthopaedic nurses who were
working in orthopaedic wards were selected from Baghdad Teaching Hospital. The data were collected through
the use of questionnaire , which consists of two parts (1)Demographic data form that consists of a(10) items
and (2) orthopaedic nurses practice form that consists of (4)sections contain (69) items, by mean of di

Objectives: To evaluate the families’ attitudes toward environment pollution, and determine the relationship
between families’ attitudes towards environment pollution and their demographic characteristics of age,
education, type of family, and socioeconomic status.
Methodology: A descriptive design is carried throughout the present study to evaluate families’ attitudes toward
environment pollution for the period of October 5th2013 to May 7th2014. A non-probability "purposive" sample of
(110) families’ is selected. The sample is comprised of two groups; (75) urban families’ and (35) rural ones. An
evaluation tool is designed and constructed for the purpose of the study. It is consisted of (4) main parts;
dem

Objectives: During the COVID-19 pandemic, dentists have had to work under stressful conditions due to the nature of their work. Personal protection equipment (PPE) has become mandatory for work in the dentistry field. This study aimed to examine dentists' practices and attitudes regarding the use of PPE and the associated drawbacks and cost implications during the pandemic.

Methods: A questionnaire-based survey was used and was divided into five sections dedicated to collect demographic variables and to examine the dentists' practices, attitudes toward PPE, drawbacks, and cost of using PPE. Mann-Whitney U and Kruskal-Wallis tests were used to compare different sections of

A variety of new phenolic Schiff bases derivatives have been synthesized starting from Terephthaladehyde compound, all proposed structures were supported by FTIR, 1H-NMR, 13C-NMR, Elemental analysis, some derivatives evaluated by Thermal analysis (TGA).

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod