From the sustainability point of view a combination of using water absorption polymer balls in concrete mix produce from Portland limestone cement (IL) is worth to be perceived. Compressive strength and drying shrinkage behavior for the mixes of concrete prepared by Ordinary Portland Cement (O.P.C) and Portland limestone cement (IL) were investigated in this research. Water absorbent polymer balls (WAPB) are innovative module in producing building materials due to the internal curing which eliminates autogenous shrinkage, enhances the strength at early age, improve the durability, give higher compressive strength at early age, and reduce the effect of insufficient external curing. Polymer balls (WAPB) had been used in the mixes of this research to provide good progress in compressive strength with time. Water absorption polymer balls have the ability to absorb water and after usage in concrete it will spill it out and shrink leaving voids of their own diameter before shrinking that lead to provide internal curing. The required quantity of water for the mixes were reduced due to the addition of water from the absorption polymers. Mixes produced from Portland limestone cement in this research show drying shrinkage results and compressive strength results lower than mixes made from ordinary Portland cement.
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The current research was aimed at the following:
1. Measurement of Personality Type Observer of the University students.
2. Identify the differences in Personality Type Observer among the University students according to variable of Sex (male / female). And according to variable of Specialization (scientific / literary)
3. Measurement of Withdrawal of the University students.
4. Identify the differences in Withdrawal among the University students according to variable of Sex (male / female). And according to variable of Specialization (scientific / literary).
5. Identify the relationship between Personality Type Observer and Withdrawal.
To achieve this aims of the research, the researchers set up the instrument is scale
The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue
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BACKGROUND: Preeclampsia (PE) is a possible etiology of obstetrical and neonatal complications which are increased in resource-limited settings and developing countries. AIM: We aimed to find out the prevalence of PE in Iraqi ladies and specific outcomes, including gestational weight gain (GWG), cesarean section (CS), preterm delivery (PD), and low birth weight (LBW). METHODS: All singleton pregnant women visiting our tertiary center for delivery were involved over 3 years. PE women were compared with non-PE ladies. Complete history and examination were done during pregnancy and after delivery by the attending obstetrician and neonatologist with full documentation in medical records. RESULTS: PE prevalence was 4.79
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In this paper, a discrete SIS epidemic model with immigrant and treatment effects is proposed. Stability analysis of the endemic equilibria and disease-free is presented. Numerical simulations are conformed the theoretical results, and it is illustrated how the immigrants, as well as treatment effects, change current model behavior
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The study was conducted at research station A, department of field crops, college of agricultural engineering sciences, university of Baghdad during summer 2021 to evaluate the effect of boron and some growth regulators on some growth criteria and yield of soybean crop (cv. shimaa). The experiment was carried out according to split plots by using randomized complete block design with three replications. The main plots included three concentrations of boron (75, 150 and 225) mg.L-1, the sub-plots included three levels of growth regulators, spraying kinetin (100 mg. L-1), spraying ethrel (200 mg.L-1) and spraying kinetin (100 mg.L-1) + spraying ethrel (200 mg.L-1) as
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Water pollution has created a critical threat to the environment. A lot of research has been done recently to use surface-enhanced Raman spectroscopy (SERS) to detect multiple pollutants in water. This study aims to use Ag colloid nanoflowers as liquid SERS enhancer. Tri sodium phosphate (Na3PO4) was investigated as a pollutant using liquid SERS based on colloidal Ag nanoflowers. The chemical method was used to synthesize nanoflowers from silver ions. Atomic Force Microscope (AFM), Scanning Electron Microscope (SEM), and X-ray diffractometer (XRD) were employed to characterize the silver nanoflowers. This nanoflowers SERS action in detecting Na3PO4 was reported and analyzed
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