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.
Dialysis is a stressful process and follows various psychological and social problems, which can lead to psychological disturbances. Patients on dialysis experience psychological distress, and the reduction of stress in patients provides psychological resources to cope with their physical condition. The study aimed to evaluate the effect of deep-breathing exercise training on the level of stress among maintenance hemodialysis patients.
This study is a randomized
The research aims to identify the importance of using analytical procedures in the detection of creative accounting practices. To achieve this goal, (100) questionnaires were prepared and distributed to the auditors in the Federal Financial Supervision Bureau and the authorized auditors' offices and practitioners of the auditing profession in Iraq. For the purpose of testing the research hypothesis and analyzing data, some appropriate statistical methods have been used and the use of the statistical program (SPSS) to analyze the data. The results of the research showed that the analytical procedures and tests applied by the auditor have a role in revealing and limiting creative accounting practices and methods and that auditors u
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La disciplina sémantica siendo una rama de la lingüística y relacionada con los significados que residen detrás de los vocablos sería muy intereseante ser estudiada y investigada, sobre todo cuando tratamos de penetrarnos dentro de la evolución semántica y los motivos por los que se suceden estos cambios. Pues, es injusto dejar de dar una definición aclaratoria sobre esta disciplina y sus componentes.
El significado de los léxicos que se forma por un conjunto de semas o rasgos significativos mínimos. Sin embargo, no todos esos semas son igualmente intervenidos por los hablantes de una comunidad lingüística, sino que hay algunos de ellos que siempre están presentes, mientras que otros varían. Es decir, el significado
... Show MoreVariation order plays an important role in calculating the final cost and time. The paper aims to determine the causes of variation orders in projects performed between 2007-2014 in Erbil governorate projects. Data was collected from contract documents. Performed in the Erbil governorate projects from 2007-2014. The study seeks to identify the most significant causes of delays by assessing the common causes of delays in terms of frequency, severity and
important indices of owners, consultants and contractors related to&n
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Large language models (LLMs) are a rapidly evolving class of artificial intelligence with significant potential in clinical healthcare. Despite accelerating adoption, rigorous systematic evidence on clinical utility, patient safety, and implementation feasibility remains fragmented. To systematically review LLM applications across clinical domains, evaluate performance with appropriate contextual caveats, characterize implementation barriers, and identify ethical and regulatory considerations. Scientific databases were searched from January 2020 to January 2025. Studies evaluating transformer-based LLMs (≥10M parameters) in clinical settings were eligible. Data were independently double-extracted; quality was assessed using QUADAS-2, RE-A
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Objective: The aim of this study was to assess the knowledge and attitude of Iraqi dentists towards cone beam computed tomography (CBCT) applications in endodontics by using an online survey. Materials and Methods: A questionnaire, consisting of 31 questions, targeted general dental practitioners and specialists in different dental specialities. A total of 306 participants were included. Data were assessed according to the frequency of distribution and the chi-square test was applied to analyse the difference in responses between two independent groups. Results: Among the participants 63.4% were using digital radiography in their daily practice, and 84% had awareness about CBCT's uses, with higher statistically significant responses among e
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