The aim of this paper is to find out the effects of the strategy of productive thinking upon the student’s achievement for the subject of research methodology in the College of Islamic Sciences. Achieving this objective, the researchers set the null hypotheses: (1) No difference is noticed to be statistically significant at the level of significance (0.05) among the student’s mean scores in the experimental group who were taught by the strategy of productive thinking, and the student’s mean scores in the control group who studied by the traditional method in the achievement test. (2) At level of sig. (0.05), there is no statistically significant difference in the mean of scores of the pre-tests and post ones in the achievement test of the experimental group students. The 3rd class students in the Dept of Islamic Creed and Thought at the College of Islamic Sciences / University of Baghdad for the academic year (2022-2023) represented the research sample. The pre-test (productive thinking) was applied to all students of the 3rd class in the Dept, who were (150) students. They were distributed into two groups: (70) undergraduates in an experimental group, and (80) undergraduates in a control group. The experimental group were taught by the strategy of productive thinking, whereas the control group who were taught by the traditional method. After the end of the experiment, the t-test was used for two independent and interrelated samples. The results revealed that there was a statistically significant difference among the student’s mean scores in the experimental group studying research methods subject by productive thinking, and among the student’s scores in the controlling group who were taught the same subject in the traditional method in the post-test for the experimental group. Moreover, the results also showed that there was a statistically significant difference among the mean scores of the students of the experimental group studying research methods subject according to the productive thinking, and the students’ scores in the experimental group in the pre-test and their scores in the post-test. This indicates that the experimental group student’s achievement got increased.
One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed
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The current study suggested a thermal treatment as a necessary proactive step in improving the adsorption capacity of bio-waste for contaminants removal in wastewater. This approach was based on the experimental and histological investigation of biowaste pods shell. This investigation showed that these shells compose of parenchyma cells that store secondary metabolites compounds produced from cells were exhibited in present study. The results also reported that these compounds are extracted directly from the cells as soon as they are exposed to an aqueous solution, hampering their use as an adsorbent material. The increase in the weight of bio-waste adsorbent at unit liquid volume increases the production of secondary metabolites compounds
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Is in this research review of the way minimum absolute deviations values based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.
The Neutron Fermi Age, t, and the neutron slowing down density, q (r, t) , have been measured for some materials such as Graphite and Iron by using gamma spectrometry system UCS-30 with NaI (Tl) detector. This technique was applied for Graphite and Iron materials by using Indium foils covered by Cadmium and the measurements done at the Indium resonance of 1.46 eV. These materials are exposed to a plane 241Am/Be neutron source with recent activity 38 mCi. The measurements of the Fermi Age were found to be t = 297 ± 21 cm2 for Graphite, t = 400 ± 28 cm2 for Iron. Neutron slowing down density was also calculated depending on the recent experimental t value and distance.
This investigation pertains to the evaluation of water quality in SAWA Lake, located in the Al-Muthanna province of Southern Iraq, from 1977 to 2020. Understanding the water quality and assessments of this Lake is of great importance. The Lake is home to small, transparent, blind fish measuring approximately 10 cm and is often referred to as the "wonderful" or "strange" Lake due to its many unique features. The study focuses on several elements to represent water quality, including total dissolved solids (TDS), electrical conductivity (EC), pH, and temperature (T), which were measured directly in the field. Additionally, scientific concepts such as K+, Ca2+, Cl-, HCO
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The present study combines UV-Vis spectrophotometry and dispersive liquid-liquid microextraction (DLLME) for the preconcentration and determination of trace level clidinium bromide (Clid) in pharmaceutical preparation and real samples. The method is based on ion-pair formation between Clid and bromocresol green in aqueous solution using citrate buffer (pH = 3). The colored product was first extracted using a mixture of 800 µL acetonitrile and 300 µL chloroform solvents. Then, a spectrophotometric measurement of sediment phase was performed at λ = 420 nm. The important parameters affecting the efficiency of DLLME were optimized. Under the optimum conditions, the calibration graphs of standard -1 (Std.), drug, urine and serum were ranged
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B Saleem, H Alwan, L Khalid, Journal of Engineering, 2011 - Cited by 2
The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting
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