The research aimed mainly to discover the effectiveness of the (PEOE) model in teaching science to develop the skills of generating and evaluating information and the emotional side of the scientific sense of the intermediate first grade students. An experimental approach with a quasi-experimental design called pre-test and post-test control design was used. The research sample consisted of (60) students, who were selected in a random cluster method, (30) students in the experimental group studied the unit "The Nature of Material" using the (PEOE) model, and (30) students in the control group studied according to the prevailing method of teaching. The research materials and tools were represented in: a teacher's guide for teaching the un

The aim of this research is to find out the influence of Daniel's model on the skills of the twenty-first century among the students of the scientific-fifth grade at the secondary and preparatory government morning schools for the academic year 2022- 2023. Two groups were chosen out of five groups for the fifth-scientific grade, one of which represents the experimental group that is taught by the Daniel model, and the other is the control group that is taught in the traditional method. The equivalence of the two research groups was verified with a set of variables. As for the research tool, a scale was developed by the researchers for the skills of the twenty-first century, in which they adopted the framework of the Partnership Organizat

Abstract The results showed that after treating <italic>C. albicans</italic> with Artemisinin (0.104 mg/ml) for 3 hours the number of <italic>C. albicans</italic> decreased and affected the morphology hyphae and growth of <italic>Candida</italic> compared with Fluconazole (150 mg/ml) and control (infected mice). The biomarker levels in the tongue showed high levels of MDA and TGFβ (623±1.5pg/ml, 586.1±0.13pg/ml respectively) in (infected mice with fungi). IL-37 was recorded high level (49.21±0.21pg/ml) in (Neoral +Fungi + artemisinin + fluconazole) compared with negative control. The finding biomarker levels in stomach showed high levels of MDA and IL-37 (533.8±1.9, 69.76±0.39pg/ml) in (Neor

Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust  M method after their development through the use of sequential  approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate

Background: Methotrexate is one of the mainstays for treating rheumatoid arthritis (RA) with a wide range of adverse drug reactions, however, it’s the relationship between adverse drug reactions and genetic polymorphism remains to be highlighted, and there is a lack of studies concerning Arabic Iraqi population regarding this aspect.

Objective: Evaluate the association between genetic mutations in the MTHFR gene in SNPs (rs1801133G&gt;A and rs1801131T&gt;G) on the adverse drug reaction for RA Iraqi patients.

Methods: An observational study, that involved 95 Iraqi RA patients with established RA. Patien

HR Al-Hamamy, AA Noaimi, IA Al-Turfy, AI Rajab, Journal of Cosmetics, Dermatological Sciences and Applications, 2015

Autorías: Hadeer Idan Ghanim, Ishraq Mahmood. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 3, 2021. Artículo de Revista en Dialnet.

DAIRMD Professor Hayder R. Al-Hamamy, **Professor Adil A. Noaimi, **Dr. Ihsan A. Al-Turfy, IOSR Journal of Dental and Medical Sciences (IOSR-JDMS), 2015

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve