This paper examines the mechanical properties of a composite material made of modified Iraqi gypsum (juss) reinforced with polypropylene fibers. The modified juss was prepared by adding two percentages of cement (5, 10) %. Two percentages of polypropylene fibers were used, to reinforce the modified juss (1, 2) %. The water/dry compound ratio used was equal to 0.53%. The composite was evaluated based on compressive strength, flexural strengths, absorption percentage, density, acoustic impedance, ultra - pulse velocity, longitudinal shrinkage and setting time tests. The results indicated that the inclusion of cement on to juss increases the compressive strength, absorption percentage, density, acoustic impedance, ultra - pulse velocity, longitudinal shrinkage and a reduction in flexural strength and setting time were observed by adding the cement. In addition, the inclusion of polypropylene fiber was significant in improving mechanical performance of the composite material, it shows a great improvement in longitudinal shrinkage, modulus of rupture and absorption percentages.
The recent studies suggested the possible toxicities or genetic alterations associated with biological and medical applications of silver nanoparticles (AgNPs). The current research is directed to see if AgNPs administration can lead to some changes in expression of BRAF gene in selected body organs tissues. Fifty-six male of musmusculs (Balb/C) mice from the animal house of Al-Nahrain Centre of Biotechnology were used. These animals were divided randomly to seven groups (eight mouse in each group), one of these groups represented the control group, three groups were subjected to different doses of AgNPs (0.25, 0.5and 1 mg/kg of body weight) for one week, and the remaining three groups were subjected to three different doses of AgNP
... Show MoreThe aim of this paper is to determine the effect of internal marketing through three dimensions: vision, development, and reward - on organizational citizenship behavior in three private universities in Iraq. Organizations’ view of their members as internal customers could be made them more realistic in dealing with the reasons for leaving and going to other organizations. This can promote business organizations to build an organizational environment that contributes to making the organization look like the homeland of those workers. The research method is descriptive and analytical. The tool for data collection was the questionnaire. Statistical software (SPSS V.23 and AMOS V.23) was used to analyze the data. The research sample was r
... Show MoreThe aim of this paper is to determine the effect of nostalgia marketing on consumers’ purchase intention and demographic factors. Nostalgia marketing is one of the marketing ideas that some organizations use it to attract customers by evoking memories or heritage in their minds. This method would affect the emotions and feelings of people, which may raise their desire to buy. The questionnaire was used as a tool for data collection, and it was distributed to a random sample of 512 individuals. A sample is a group of individuals who have seen small sculptures displayed in shops inside Babylon Mall in Baghdad. The small sculptures show the life of Baghdadis in the fifties and sixties of the last century. Statistical software was used for
... Show MoreSpatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati
... Show MoreThe aim of research is to show the effect of Ferric Oxide (Fe2O3) on the electricity production and wastewater treatment, since 2.5% of Ferric Oxide (Fe2O3) (heated and non heated) nanoparticles has been used. Characterization of nanoparticles was done using X-ray Diffraction (XRD) and Scan Electron Microscopy (SEM). The influence of acidity was also studied on both wastewater treatmenton the Chemical Oxygen demand (COD) and Biological Oxygen Demand (BOD) and voltage output was studied. From the results, it was infused that the dosage of 0.025 g/l and an initial pH 7 were founded to be optimum for the effective degradation of effluents. The results concluded that the treatment of anaerobic sludge wastewater using Ferric Oxide (Fe2O3) in
... Show MoreStone Matrix Asphalt (SMA) is a gap-graded asphalt concrete hot blend combining high-quality coarse aggregate with a rich asphalt cement content. This blend generates a stable paving combination with a powerful stone-on-stone skeleton that offers excellent durability and routing strength. The objectives of this work are: Studying the durability performance of stone matrix asphalt (SMA) mixture in terms of moisture damage and temperature susceptibility and Discovering the effect of stabilized additive (Fly Ash ) on the performance of stone matrix asphalt (SMA) mixture. In this investigation, the durability of stone matrix asphalt concrete was assessed in terms of temperature susceptibility, resistance to moisture damage, and sensitivity t
... Show MoreIn this paper the modified trapezoidal rule is presented for solving Volterra linear Integral Equations (V.I.E) of the second kind and we noticed that this procedure is effective in solving the equations. Two examples are given with their comparison tables to answer the validity of the procedure.
Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
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