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A Criticism and study of “The Arabic translations of contemporary Persian novels” (“Translations of Muhammad Alauddin Mansour” as a model): قنقـــد و بررسی ترجمـــــه¬ی عربی رمــــان¬های معـــــاصر فــــارسی (ترجمه¬های محمد علاء الدین منصور- بررسی نمونه¬ای)
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     Arab translators have always paid great attention to the translation of the Persian literary genres, in particular, contemporary Iranian novels. They have always translated for the most prominent Iranian novelists such as Jalal Al Ahmad, Sadiq Hidayat, Mahmoud Dowlatabadi, Bozorg Alavi, Ismail Fasih‎, Houshang Golshiri, Gholam-Hossein Saedi, Simin Daneshvar, Sadiq Chubak, Samad Behrangi and others that have succeeded in perfectly picturing the Iranian society.

      Within the perspectives of Arab translators and by using the descriptive - analytical approach, the present study provides an analytical study of the translation into Arabic some of the modern Persian novels. Moreover, the study also gives a critical analysis of the translation of the  Egyptian Muhammad Alauddin Mansour into Arabic two of the selected models of the Iranian novels: (Termite) by Bozorg Alavi and (Winter 84) by Ismail Fasih.  The study also elucidates a critical analysis of some semantic and stylistic aspects of the translation as well as some of the translator’s committed mistakes between the original and the translated texts.

چکیده

رمان فارسی یکی از ژانرهای ادبی است که مترجمان عرب­زبان به آن توجه زیادی نشان داده­اند و می­توان گفت که به ویژه رمان­های معاصر ایرانی همواره مورد اقبال مترجمان عرب بوده­اند. و مترجمان عرب بسیاری ازرمان­های نویسندگان مشهور ایرانی را ترجمه کردند که از طریق آن­ها تصویر جامعه ایران را به جهان عرب منتقل می­کردند.

در این تحقیق با روش توصیفی - تحلیلی به نقد و بررسی " ترجمه­ی عربی رمان­های معاصرفارسی" در قالب بررسی موضوعاتی همچون نگاهی به ترجمه­های مترجمین عرب از رمان­های معاصر فارسی ، نقدی کوتاه بر ترجمه­ی رمان­های معاصر فارسی به عربی و نقد وبررسی نمونه­های برگزیده­ای از ترجمه­ی مترجم مصری محمد علاء الدین منصور از رمان (موریانه) نوشته بزرگ علوی رمان (زمستان 62) نوشته اسماعیل فصیح پرداخته­ایم. بدین ترتیب که ضمن مطالعه­ی دو رمان مذکور و مقابله متن ترجمه شده با متن اصلی ، برخی مسائل معنایی و سبک­شناختی و اشتباهات مترجم را با مقایسه متن ترجمه شده با متن اصلی بررسی و تحلیل کرده­ایم.

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Publication Date
Wed May 10 2023
Journal Name
Biomass Conversion And Biorefinery
Lactic acid-based deep eutectic solvents and activated carbon for soap removal from crude biodiesel
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Sun Jul 01 2018
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Mathematical-procedural Knowledge ant its relation to logical-mathematical intelligence among students at the third stage in mathematics department
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Sun Jul 01 2018
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Mathematical-procedural Knowledge ant its relation to logical-mathematical intelligence among students at the third stage in mathematics department
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Sun Feb 25 2024
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Optimizing Blockchain Consensus: Incorporating Trust Value in the Practical Byzantine Fault Tolerance Algorithm with Boneh-Lynn-Shacham Aggregate Signature
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Thu Dec 01 2016
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The Numerical Technique Based on Shifted Jacobi-Gauss-Lobatto Polynomials for Solving Two Dimensional Multi-Space Fractional Bioheat Equations
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Sat Sep 30 2023
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Petrophysical Analysis Based on Well Logging Data for Tight Carbonate Reservoir: The SADI Formation Case in Halfaya Oil Field
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Tue Sep 01 2020
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Uptake of Three Pharmaceuticals by Beans (Phaseolus vulgaris L.) from Contaminated Soils: امتصاص ثلاثة انواع من الادوية بواسطة نبات الفاصولياء في التربة الملوثة
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The ability of beans (Phaseolus vulgaris L.) to uptake three pharmaceuticals (diclofenac, mefenamic acid and metronidazole) from two types of soil (clay and sandy soil) was investigated in this study to explore the human exposure to these pharmaceuticals via the consumption of beans. A pot experiment was conducted with beans plants which were grown in two types of soil for six weeks under controlled conditions. During the experiment period, the soil pore water was collected weekly and the concentrations of the test compounds in soil pore water as well as in plant organs (roots, stems and leaves) were weekly determined.
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Fri Jan 01 2021
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Indonesian Journal Of Electrical Engineering And Computer Science
BotDetectorFW: an optimized botnet detection framework based on five features-distance measures supported by comparisons of four machine learning classifiers using CICIDS2017 dataset
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