The research aims to find out the effect of PEDODE Strategy on the acquisition of historical concepts of First Intermediate Grade. To achieve this goal, the researcher has put forward this zero hypothesis: There is no statistically significant difference at the level of (05,0) between the mean of the students' marks in the experimental group who study the history subject using PEDODE strategy and that of the students' marks in the control group who study the subject according to the traditional method in the post-testing on the acquisition of historical concepts. The sample of the study consists of (62 female-students) of First Intermediate Grade in the Directorate of Baghdad Education/ Karkh2nd for the academic year 2016-2017. The sampl

This study was aimed to extract the effective material from the dry nests of termites and detect its antibacterial activity against some pathogenic bacterial isolates and inhibit synthesis of its biofilm. Termites dry nests were collected and the effective material was extracted then the antibacterial activity was detected using the disc diffusion assay. Results were showed that the extract have antibacterial material from the Termites dry nests, this extract showed antibacterial activity against Gram positive bacteria (Staphylococcus aureus) at (21.5mm) and Gram negative bacteria ( Enterobacter sp. and Pseudomonas aeruginosa) at (26 mm and 20 mm) respectively by inhibiting their growth, as well as its effect on biofilm production o

The study aimed to evaluate injuries and economic losses which caused by rose beetle Maladerainsanabilis (Brenske) on ornamental and fruit plants as introduced insect in Iraq during 2015 and determine infested host plants in addition to evaluate efficacy of pathogenic fungi Metarhiziumanisopiliae (1x10⁹ spore/ ml) and Beauvariabassiana (1x10⁸spore/ ml) in mortality of insect larvae in laboratory and field.The results showed that the insect was polyphagous infested many host plants (20 host plant)Which caused degradation and dead the plants through adult feeding on leaves and flower but large injury caused by larvae feeding on root plants which caused obligate dead to infested plant, the percentage mortality of rose plants 68.6%, pear

The experiment was carried out in the green house of botanical garden belong to Department of Biology/College of Education for Pure Science Ibn AL-Haitham, University of Baghdad for growing season 2017-2018 to evaluate effect of lead stress with concentrations (0, 50, 100, 150) mg.L -1 and Selenium concentrations (0, 15, 30) mg.L-1 on growth of dill plant using pots. The experiment was designed according to completely randomized design (CRD) with three replications. Result indicated that dill plants subjected to lead stress with height concentrations caused decrease in plant parameters (plant height, no. of branches. plant-1, root length, shoot dry weight, the content of nitrogen, phosphorus and potassium, protein concentration, no. of umbe

؛ ١٨his study male and female albino mice werdministr^d doses of alkaloid and phenolic extracts of Allium cepa at doses of( 25 ,50,100, 200) mg / kg of( body weight). males and females were divided into four groups and each croup comprised mice were injected intra^ritonially daily for one week and orally ٢٠٢ one month . After which animals were killed and the serum was separated for biochemical analysis (total blood suger, total protein , otal cholesterol). Results showed significant decrease ( p< 0,05) in the total blood suger and total cholesterol on the serum of both males and females and significant increase( p< 0,05) in the total serum protein of both males and females of the two types of injection and oral administr

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par