Abstract This study aims to compare British war poetry of the First World War with Iraqi poetry from the mid-20th century with special reference to Iraqi war poetry of the 1980’s Iraq-Iran War and the period that followed it. It will also investigate the influence of the designated British war poetry on the chosen body of Iraqi poetry. Through the comparison of sample poems the study presents, firstly, the direct influence of the British poetry of the Great War and its translation which formed the seeds of a more radical movement in Iraqi poetry during the 1980’s Iran/Iraq War and the period that followed it. The study also presents a comparison of the works of British and Iraqi civilian poets during and after the war time and their contribution in setting the ground for the younger generation to create more subversive poetic forms with special reference to women as influential characters and inspirations in their works. The moment of the 1980’s war marks the break with the clear direct influence of British war poetry and starts another phase of the comparison of a universal bond of similar reactions, conscious and unconscious expression reflecting the lives of the combatant group of men first and then of poets sharing a devastating war reality. The study reveals a remarkable, more radical change of poetic forms in Iraqi poetry between the time of the first seeds planted by the influence of translations from European poetry until the time of the Iran/Iraq war and the Gulf War in 1991 and the rise of the new nihilistic generation of the 1990s subverting war, politics and cultural life through their innovation in prose poem writing and its significance as an alternative space for their political and social subversion.
To evaluate the shear bond strength and interfacial morphology of sound and caries-affected dentin (CAD) bonded to two resin-modified glass ionomer cements (RMGICs) after 24 hours and two months of storage in simulated body fluid at 37°C.
Sixty-four permanent human mandibular first molars (32 sound and 32 with occlusal caries, following the International Caries Detection and Assessment System) were selected. Each prepared substrate (sound and CAD) was co
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This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed
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The δ-mixing of γ-transitions in 70As populated in the 32 70 70 33 Ge p n As (, ) γ reaction is calculated in the present work by using the a2-ratio methods. In one work we applied this method for two cases, the first one is for pure transition and the sacend one is for non pure transition, We take into account the experimental a2-coefficient for previous works and δ -values for one transition only.The results obtained are, in general, in a good agreement within associated errors, with those reported previously , the discrepancies that occur are due to inaccuracies existing in the experimental data of the previous works.
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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
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