This study aims to conduct an exhaustive comparison between the performance of human translators and artificial intelligence-powered machine translation systems, specifically examining the top three systems: Spider-AI, Metacate, and DeepL. A variety of texts from distinct categories were evaluated to gain a profound understanding of the qualitative differences, as well as the strengths and weaknesses, between human and machine translations. The results demonstrated that human translation significantly outperforms machine translation, with larger gaps in literary texts and texts characterized by high linguistic complexity. However, the performance of machine translation systems, particularly DeepL, has improved and in some contexts

Regression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well-  Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.

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Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

Autorías: Nadeema Badr Mohammed, Missaa Nadem, Huda Badwe Shbeeb, Iqbal Abdul Hussein Neamah, Najlaa Abbas AL Zuhairi, Nihad Mohammed Alwan. Localización: Retos: nuevas tendencias en educación física, deporte y recreación. Nº. 63, 2025. Artículo de Revista en Dialnet.

Previous studies indicated that supplementation with antioxidants has a protective effects against oxidative stress–induced damage in type 2 diabetes. In this study we evaluated the antioxidant effects of melatonin on the oxidative stress parameters and microalbuminuria in type 2 DM patients. 30 patients with type 2 DM were treated with 3mg/day melatonin for 90 days. Erythrocytes and plasma MDA and glutathione, fasting plasma glucose, %Hb_AIC, microalbuminuria, total plasma protein and lipid profile were measured each 30 days and compared with those obtained from 20 healthy controls.

A decrease in MDA levels associated with the elevation in GSH levels were observed, compared with the pre–treatment levels.

Arbuscular mycorrhizal fungi and sulphur foam added either at direct seeding or at transplanting decreased the effects of nematode (Meloidogyne javanica) on eggplant growth, and improved plant health. Experiments were conducted to study the possible interactions between the Mycorrhizal fungi (Glomus mossae and Gigaspora spp.) and sulphur foam to control M. javanica on eggplant at seed or seedling stage. Experiment at seed stage treated with Mycorrhiza or sulphur foam alone or together stimulated the growth and reduced Nematode infestation significantly. Treated plant at seedling stage increased plant growth and reduced the number of galls /gm of root system. The interaction between Mycorrhiza and sulpher foam treatments was not significant