With the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual and cultural quality. Our results show that our model, ChatGPT, consistently achieves performance gains over DeepSeek, especially when applied to technical and journalistic text and with higher BLEU scores and lower TER values. But neither these models nor any of the state-of-the-art models perform well for the literary texts, the ones that can hint to the difficulties these models face to deal with idiomatic expressions, metaphor, narrative tone. The results illustrate genre sensitivity in AI translation quality and emphasize the ongoing importance of human supervision, particularly in cultural and stylistic contexts. This work aims to contribute to the growing corpus of AI translation literature by providing a genrespecific, empirically grounded comparison of two of the most highprofile models, and to draw attention to the necessity of greater context-sensitive and culturally sensitive translation algorithms.
This study evaluates the flexural behavior of ultra-thin (50 mm) one‑way reinforced‑concrete (RC) slabs retrofitted with near‑surface mounted (NSM) carbon‑fiber‑reinforced polymer (CFRP) rods under quasi‑static loading. T300‑grade CFRP rods (≈4 mm diameter) were bonded in pre‑cut 7 mm × 7 mm grooves using a two‑part epoxy. As a proof-of-concept experimental baseline, three simply‑supported specimens (1000 mm × 500 mm × 50 mm) were tested in a six‑point bending configuration (four applied loads + two reactions): two conventional controls and one strengthened slab. A load‑control rate of ~15 kN/min was applied; the controls were cycled twice and the strengthened slab four times. Relative to the average of
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In this study, the photodegradation of Congo red dye (CR) in aqueous solution was investigated using Au-Pd/TiO2 as photocatalyst. The concentration of dye, dosage of photocatalyst, amount of H2O2, pH of the medium and temperature were examined to find the optimum values of these parameters. It has been found that 28 ppm was the best dye concentration. The optimum amount of photocatalyst was 0.09 g/75 mL of dye solution when the degradation percent was ~ 96 % after irradiation time of 12 hours, while the best amount of hydrogen peroxide was 7μl/75 mL of dye solution at degradation percent ~97 % after irradiation time of 10 hours, whereas pH 5 was the best value to carry out the reaction at the highest degradation percent. In additio
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Medicinal plants are a source for a wide variety of natural active compounds and are used for the treatment of diseases throughout the world. Conocarpus erectus L. widely planted all over Iraq and has different secondary metabolites, which has been used in treatment of anemia, cancer, fever and diarrhea. The present study aims to estimate the antibacterial activity of Conocarpus erectus leaves extracts on some microorganisms collected from patients with burn infection. The study began with the collection of Conocarpus erectus leaves in June 2018 from the trees in university of Baghdad. Maceration method was used to prepare aqueous extract, while Soxhelt apparatus was used to prepare methanolic extract. The results of phytochemical test show
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Biologically active natural compounds are molecules produced by plants or plant-related microbes, such as endophytes. Many of these metabolites have a wide range of antimicrobial activities and other pharmaceutical properties. This study aimed to evaluate (in vitro) the antifungal activities of the secondary metabolites obtained from Paecilomyces sp. against the pathogenic fungus Rhizoctonia solani. The endophytic fungus Paecilomyces was isolated from Moringa oleifera leaves and cultured on potato dextrose broth for the production of the fungal metabolites. The activity of Paecilomyces filtrate against the radial growth of Rhizoctonia solani was tested by mixing the filtrate with potato dextrose agar medium at concentrations of 15%,
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Biologically active natural compounds are molecules produced by plants or plant-related microbes, such as endophytes. Many of these metabolites have a wide range of antimicrobial activities and other pharmaceutical properties. This study aimed to evaluate (in vitro) the antifungal activities of the secondary metabolites obtained from Paecilomyces sp. against the pathogenic fungus Rhizoctonia solani. The endophytic fungus Paecilomyces was isolated from Moringa oleifera leaves and cultured on potato dextrose broth for the production of the fungal metabolites. The activity of Paecilomyces filtrate against the radial growth of Rhizoctonia solani was tested by mixing the filtrate with potato dextrose agar medium at concentrations of 15%,
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Background: Bone density is a major factor that affect mini implant primarily stability; no Iraqi studies have evaluated bone density related to mini-implant placement for orthodontic anchorage at age 13 -15 years. The present research aims to evaluate gender, side and site differences in the bone density at various orthodontic implant sites for the maxillary alveolar bone. Materials and methods: Twenty nine individuals (16 males and 13 females) had subjected to clinical examination, then 64-multislice computed tomography scan data were evaluated and bone density was measured in Hounsfield unit at 21 points (9 points for each side and 3 points between the right and left central incisors) . Results: The results obtained showed that there ar
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The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival
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