The topic of (pilgrims) of the old and modern subjects at the same time, as it extends his foot and is associated with the beginning of speech and argument, a modern because it is based on studies and research (and the theory of pilgrims) from (Austin and Cyril) through (Charles Breman) to (Aristotle) ), It is worth mentioning here to mention the role of (Hazem al - Qartagni) in mentioning the value of the pilgrimage of hair and saying the use of persuasion in the hair, is palatable and acceptable. Hence our research applied these views, and we chose the pendants as a model for that matter.

Gender and culture are among the factors that influence the process of understanding and interpreting different types of communication, especially images. The current study, which is a part of a master’s thesis, aims at investigating the role of gender and culture in interpreting and understanding the caricatures that deal with women’s issues in Arab societies. To this end, the researchers adopted Barthes’ (1957) concepts of denotation and connotation in his theory of mythologies in addition to Langacker’s (1987) theory of (Domains). The research concludes that the female subjects have better cognitive abilities in investing the signs within the selected caricatures. The other factor the study reached to is that the respondents

المواقف افي الدول العربية قراءة تحليلية في مواقف لدولية من التغيير (الولايات المتحدة - الاتحاد الاوروبي - روسيا)

حزب العمال الكردستاني ودوره في تطوير القضية الكردية في تركيا من 1991-2013

In this paper we proposed the method of X-ray fluorescence (XRF) determination of some essential trace elements in medicinal herbs and vitamin-mineral complexes at the level of 10⁰-10¹ mg/ml. To increase sensitivity and selectivity of the determination we simple and effective approach based on the extraction of metal ions from aqueous solutions with chemically modified polyurethane foam sorbents followed by direct XRF analysis. The conditions of sorption preconcentration of Co(II), Ni(II) and Zn(II) ions with modified sorbents were optimized. The proposed approach is used for the determination of trace elements in several kinds of medicinal herbs (coltsfoot leaves, nettle leaves and yarrow herb) and vitamin-mineral

The Ligand 6,6--(1,2-benzenediazo) bis (3-aminobenzoicacid) derived from o-phenylenediamine and 3-aminobenzoicacid was synthesized. The prepared ligand was identified by Microelemental Analysis, 1HNMR, FT-IR and UV-Vis spectroscopic techniques. Treatment of the ligand with the following metal ions (CoII, NiII, CuII and ZnII ) in aqueous ethanol with a 1:1 M:L ratio and at optimum pH. Characterization of these compounds has been done on the basis of elemental analysis, electronic data, FT-IR and UV-Vis, as well as magnetic susceptibility and conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range (1×10-4 - 3×10-4 M). H

In the current study, a direct method was used to create a new series of charge-transfer complexes of chemicals. In a good yield, new charge-transfer complexes were produced when different quinones reacted with acetonitrile as solvent in a 1:1 mole ratio with N-phenyl-3,4-selenadiazo benzophenone imine. By using analysis techniques like UV, IR, and 1H, 13C-NMR, every substance was recognized. The analysis's results matched the chemical structures proposed for the synthesized substances. Functional theory of density (DFT)
has been used to analyze the molecular structure of the produced Charge-Transfer Complexes, and the energy gap, HOMO surfaces, and LUMO surfaces have all been created throughout the geometry optimization process ut

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F