: zonal are included in phraseological units, form metaphorical names for a person, give him various emotional and evaluative characteristics. This article examines the topic of zoomorphic metaphors that characterize a person in the Russian and Arabic languages in the aspect of their comparative analysis, since the comparative analysis of the metaphorical meanings of animalisms is an important method for studying cultural linguistics, since zoomorphic metaphors are a reflection of culture in a language.

This study was undertaken to introduce a fast, accurate, selective, simple and environment-friendly colorimetric method to determine iron (II) concentration in different lipstick brands imported or manufactured locally in Baghdad, Iraq. The samples were collected from 500-Iraqi dinars stores to establish routine tests using the spectrophotometric method and compared with a new microfluidic paper-based analytical device (µPAD) platform as an alternative to cost-effective conventional instrumentation such as Atomic Absorption Spectroscopy (AAS). This method depends on the reaction between iron (II) with iron(II) selective chelator 1, 10-phenanthroline(phen) in the presence of reducing agent hydroxylamine (HOA) and sodium acetate (NaOAc) b

Background: This study compared in vitro the marginal adaptation of three different, low shrink, direct posterior composites Filtekâ„¢ P60 (packable composite), Filtekâ„¢ P90 (Silorane-based composite) and Sonic fillâ„¢ (nanohybrid composite) at three different composite/enamel interface regions (occlusal, proximal and gingival regions) of a standardized Class II MO cavity after thermal changes and mechanical load cycling by scanning electron microscopy. Materials and methods:Thirty six sound human maxillary first premolars of approximately comparable sizes were divided into three main groups of (12 teeth) in each according to the type of restorative material that was used: group (A) the teeth were restored with Filtekâ„¢ P6

The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional quality.

The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional

Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

Precision irrigation applications are used to optimize the use of water resources, by controlling plant water requirements through using different systems according to soil moisture and plant growth periods. In precision irrigation, different rates of irrigation water are applied to different places of the land in comparison with traditional irrigation methods. Thus the cost of irrigation water is reduced. As a result of the fact that precise irrigation can be used and applied in all irrigation systems, it spreads rapidly in all irrigation systems. The purpose of the Precision Agriculture Technology System (precision irrigation) , is to apply the required level of irrigation according to agricultural inputs to the specified location , by us

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz