Derivational word formation process is one of the most substantial linguistic procedures that solves many problems in the translation of the language new vocabulary and helps to comprehend the smallest language component that not simply semantically and structurally explain the elements  of both Russian and Arabic but also enables translators to comprehend the derivational method procedures of both languages. It also reveals the structural aspects of translation equivalences, cognitive and semantic foundations of translation. The rapid development of languages and the appearance of a new vocabulary like ṭabaʿa "print → ṭābiʿat "printer", kataba "to write" → kātib → kātibat, rafaʿa "to raise" → rāfiʿat "a crane" d

Objectives:
To evaluate mothers’ attitudes toward readiness for discharge care at home for a premature baby in Intensive Care Unit at teaching hospitals in Medical City Complex and to find out the relationship between mothers’ attitudes and their socio-demographic characteristics.
Methodology: A quasi-experimental study design was carried out through the period of 6th January 2020 to 2021 to 11th March 2021, to evaluate mother’s attitude toward discharge care plan for premature babies. The study carried out in Welfare Teaching Hospital, Nursing Home Hospital and Baghdad Teaching Hospital at Medical City Complex in Baghdad City on 30 mother of premature babies in neonatal intensive care units using the nonprobability sampling

Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

Background: Polycystic ovary syndrome (PCOS) is
the most common form of chronic anovulation
associated with androgen excess; it occurs in about 5
– 10% 0f reproductive age women. Metabolic
syndrome is characterized by insulin resistance,
hypertension, obesity, abnormalities of blood clotting
and dyslipidemia.
Adult women with PCOS have an increased
prevalence of the metabolic syndrome(MBS).
Objectives: To detect the prevalence of metabolic
syndrome in women with proved PCOS, attending the
Specialized Center for Endocrinology and Diabetes, in
Baghdad.
Materials and methods : A total number of 40
women with proved PCOS were included in this study
which was conducted in the Specialized Center f

synthesis and characterization of New Bidentate schiff base Ligand Type(NO)Donor Atoms Derived from isatin and 3-Amino benzoic acid and Its complexes with Co(||),Cu(||),Cd(||)and Hg(||)Ions

Objective: The aim of this study was to compare the marginal microleakage between bulk-fill, preheated bulk-fill, and bulk-fill flowable composite resins above and below cemento-enamel junction (CEJ) using micro-computed tomography. Methods: Sixty freshly extracted premolar teeth were prepared with a slot shaped cavities of a total of 120 Class II: 3mm (bucco-lingual), 2mm (mesio-distal) with mesial-gingival margin located 1mm coronal to CEJ, and distal gingival margin located 1mm apical to the CEJ. The samples were randomly divided into two main groups according to the restorative material (Tetric EvoCeram and 3M Filtek), and each group was further sub-divided into three subgroups according to the consistency (bulk fill, preheated bulk fil

A new Schiff base o-hydroxybenzylidene-1-phenyl-2,3-dimethyl-4-amino-3-pyrazolin-5-on (HL) ,have been prepared and characterization.(HL) has been used as a chelating ligand to prepare a number of metal complexes VO(II) ,Cr(III) ,Mn(II),Fe(II),Hg(II) and UO2(II) .and mixed ligands complexes have been prepared between o-hydroxybenzylidene-1-phenyl-2,3-dimethyl-4-amino-3-pyrazolin-5-on and 8- hydroxy quinoline with VO(II),Zn(II),Cd(II), Hg(II) and UO2(II) the prepared complexes were isolated and characterized by (FT-IR)and (UV-Vis) spectroscopy. Elemental analysis (C.H.N) Chloride contents, Flame atomic absorption technique. in addition to magnetic susceptibility and conductivity measurement. Molar ratio measurement in solution gave comparabl