The article considers metaphors as one of the fundamental means used by L. Ulitskaya when writing the family chronicle "Medea and her Children" (1996), for the formation of images of heroines - representatives of the pronounced feminine principle in the work. Here I describe the results of the next stage of research related to the work of Lyudmila Evgenievna Ulitskaya as a representative of modern Russian prose.

This study is targeting the new developed materials and techniques and how they were affected by the scientific and technological developments that contributed to revelated new and varied developed materials and techniques. And from the artist’s formulation by using the materials and techniques and through its embodiment and sensor the values, artistic and aesthetic standards by breaking from the familiar in aesthetic contemporary way.
The studies on questioning what’s the role of The New Developed Materials and Techniques in exposing the aesthetic of the art work?

This study is to show the aesthetic of the art work through the new developed materials and techniques. Which was based on descriptive analyzing method and hig

In spite of the contemporary development over the world in pertaining of modernization and its differences about the transformation of the knowledge but, the important instrument to transfer the thoughts and information did not have change except the language. So the evolutionary process became as a torrent or fusillade above the cliff which drifted anything. So that the objective inquiry and impressed with varieties of development the casement to evaluate the linguistic or re - correction highlight article in order to preserve on the origins of the language and its sobriety.
Today, we have different correspondence and social media as

Personality regard as one of the human soul pillars that has been built throughout the life of people, starting from the fertilizing process to different stages of people ages. Over time, numerous scientific studies have shown that fetus has the ability to hear and feel and he is being stereotyped since the first stages of formation. Accordingly, the process of forming human personality set up since that date. Besides, the socialization means that take different resources to enhance human personality such as holy Quran, school, social media, and social environment. The emergence of social media made the world as a small village which gives the chance for all people, over the world, to obtain the knowledge easily and limitless. Thus, the

The contribution rate of tax revenues in the federal budget is very small compared to the rate of contribution of oil revenues and this leads to negative repercussions on the Iraqi economy and the budget becomes a prisoner of high and low oil prices, and this is a problem that needs to be studied to know the extent of the impact of economic and political decisions on the size of tax revenue and The research goal is determined in studying the effect of amending the Unified Law No (26) of 2019 on the size of annual tax revenues .                                   &

Abstract
Objectives: this study aims to: (1). Assess self-esteem level and academic achievement for students of nursing colleges in southern Iraq. (2). Determine the relationship between levels of self-esteem and academic achievement of the student in the first semester. (3). Identify differences of self-esteem with gender and different age groups.
Methodology: a sample of (426 students) was purposively selected then collected by using a questionnaire which consisted of: I- Sociodemographic characteristics for assessing some important aspects of students, II- Rosenberg's Self-Esteem Scale (RSES) III- Iraq Grading Scale for assessing student achievement. Finally statistical analysis (SPSS) for data processing.
Results: study resu

The research aimed to identify “The impact of an instructional-learning design based on the brain- compatible model in systemic thinking among first intermediate grade female students in Mathematics”, in the day schools of the second Karkh Educational directorate.In order to achieve the research objective, the following null hypothesis was formulated:There is no statistically significant difference at the significance level (0.05) among the average scores of the experimental group students who will be taught by applying an (instructional- learning) design based to on the brain–compatible model and the average scores of the control group students who will be taught through the traditional method in the systemic thinking test.The resear

Experiment Factorial conducted with two factor in field texture silt clay loam soil, the first factor were Two Rotavator plow which different in number of rotary blades on flanges, weight, width, made and type, the second factor were four speeds tractor 2.62, 5.10, 7.55, 9.23 km/hr to compare performance two Rotavator under depth 12 cm and knowledge slippage, distance between beat blades, practical productivity, disturbed soil volume, percentage of the soil clods which have diameter less than 5 cm under complete block design with three replications using Least Significant Design 0.05. Results showed Galucho Rotavator recorder the higher practical productivity 0>7089 ha/hr, disturbed soil volume 809.8 m3/hr, percentage of the soil clods 96.1

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system