This article is an endeavour to highlight the relationship between social media and language evolution. It reviews the current theoretical efforts on communication and language change. The descriptive design, which is theoretically based on technological determision, is used. The assumption behind this review is that the social media plays a significant role in language evolution. Moreover, different platforms of social media are characterized by being the easiest and fastest means of communication. It concludes that the current theoretical efforts have paid much attention to the relationship between social media and language evolution. Such efforts have highlighted the fact that social media platforms are awash with a lot of acronyms, cyber slangs, initialisms, morphological shortenings, etc. Much importantly, previous research has suggested that the larger the network size is, the more will be its effect on language evolution.
The field experiment was conducted in garden of Department of Biology, College of Education for Pure Sciences (Ibn- Al-Haitham), University of Baghdad during the season of growth (2014-2015). The experiment aimed to study the effect of citric acid with two concentration 10, 20 mg. L-1 and glutamic acid with two concentration 50, 100 mg. L-1 on growth and yield of broad bean (Vicia faba). The results were showed an increased in plant height, leaves number. Plant dry weight, chlorophyll content flowers number, absolute growth rate, crop growth rate, legume length and dry weight, legumes number, seed dry weight compared with control plants.
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To investigate the effect of spraying some plant extraction and anti-oxidants on growth and yield of two cultivars of sunflower, a field experiment was conducted during fall season of 2009 and spring season of 2010 at the Experimental Farm, Department of Field Crop Science, College of Agriculture/ University of Baghdad. RCBD with three replications as factorial at two factors was used. First factor was cultivars Akmar and Shmoss, second was spraying with extraction of karkade at 25%, liquorices at 50%, vitamin C at concentration 1.5 mg.l-1 and nutrient which content 15 elements at concentration 15 % in addition to control treatment which sprayed with distilled water only. The result showed no significant differences between the two cultivar
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Four metal compounds mixed ligand of azo dye ligand (L) and metformin.(Met) were produced at aquatic ethanol for (1:1:1) (M:L:Met). The prepared compounds were identified by utilizing atomic absorption flame, FT.IR and UV–Vis spectrum manners as well as conductivity mensuration. These compounds was assayed of the gained datum the octahedral geometry was proposed into whole prepared complexes.Also in this research was studied represented examining the antibacterial and antifungal impact of the azo dye ligand (L), metformin.(Met) and (Co,Ni, Cu and Cd complexes) on four types of pathogenic, clinically isolated bacteria that are resistant to antibiotic, like Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli, Klebsiella pneu
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Molecular dynamics (MD) simulations were carried out in order to investigate the binding mode of axillaridine-A at the active site of human acetylcholinesterase (AChE) enzyme. 2.0 nanosecond of MD simulations was made for the protein and the complex to dynamically explore the active site and the behavior of the ligand at the peripheral AChE binding site. These calculations for the enzyme alone showed that the active site of AChE is located at the bottom of a deep and narrow cavity whose surface is lined with rings of aromatic residues and Tyr72 is almost perpendicular to the Trp286 ring and forms a stable - interaction. The size of the active site of the complex decreases with time due to increase the interaction. Axillaridine-A forms
... Show MoreThe field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
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In this paper fractional Maxwell fluid equation has been solved. The solution is in the Mettag-Leffler form. For the corresponding solutions for ordinary Maxwell fluid are obtained as limiting case of general solutions. Finally, the effects of different parameters on the velocity and shear stress profile are analyzed through plotting the velocity and shear stress profile.
