This study was designed to investigate the effect of aqueous extract of ginger Zingiber officinale Roscoe on the histology of corpus luteum and the concentration of the hormones progesterone and estrogen during the first trimester of pregnancy (0 - 7) days from fertilization. 30 pregnant mice were divided into five experimental groups: control group (administrated with distilled water), and four groups treated at doses (284, 568, 1136,1420 mg / kg), orally administrated , daily with (0.1 ml). Microscopic examination results have shown histopathological changes in corpus luteum included: Pyknosis in some nuclei of granulosa cells, Karyorrhexis, Karyolysis in some granulosa cells, and necrosis in corpus luteum, with additional significant dec

The problem of research lies in answering some of the question: What is the reality of (vital conscience) in some colleges and departments of physical education and sports science in Baghdad from the viewpoint of the teachers? And The aim of the research is to prepare a scale (the vitality of the conscience) and learn about its reality in colleges and departments of physical education and sports science in Baghdad from the viewpoint of teachers and The researcher relied on the descriptive method in the survey method and the relationships related to the nature of the research problem and The sample of the research was senior administrators teaching some colleges and departments of physical education and sports science in Baghdad , Th

This research aims to underscore the significance of women's emotional intelligence in enhancing the effectiveness of the Board of Directors, a crucial component of internal governance, particularly during crises. Despite strides made in recent decades in appointing women to senior roles in government, business, and education, challenges persist in improving women's leadership opportunities, especially in developing countries. The study utilizes statistical methods, including Pearson's correlation, to analyze the relationships between variables within a sample of banks listed on the Iraqi securities market, comparing periods before and during the COVID-19 pandemic (2019 and 2020). The goal is to measure the impact of female emotiona

In recent years, literary studies have witnessed a remarkable shift towards employing digital technologies, particularly artificial intelligence tools, in analyzing literary texts and exploring their linguistic and semantic structures. This trend has provided researchers with new possibilities for understanding texts in quantitative and qualitative ways that transcend traditional methods based solely on critical reading. The current research aims to introduce professors and students of Arabic to artificial intelligence tools that contribute to the analysis of literary texts, focusing on exploring their mechanisms for studying style, meaning, structure, and emotion. It also seeks to highlight the most prominent challenges facing researchers

The present paper deals with studying the effect of electrical discharge machining (EDM) and shot blast peening parameters on work piece fatigue lives using copper and graphite electrodes. Response surface methodology (RSM) and the design of experiment (DOE) were used to plan and design the experimental work matrices for two EDM groups of experiments using kerosene dielectric alone, while the second was treated by the shot blast peening processes after EDM machining. To verify the experimental results, the analysis of variance (ANOVA) was used to predict the EDM models for high carbon high chromium AISI D2 die steel. The work piece fatigue lives in terms of safety factors after EDM models were developed by FEM using ANSY

     This paper develops the work of Mary Florence et.al. on centralizer of semiprime semirings and presents reverse centralizer of semirings with several propositions and lemmas. Also introduces the notion of dependent element and free actions on semirings with some results of free action of centralizer and reverse centralizer on semiprime semirings and some another mappings.

        Peroxidase is a class of oxidation-reduction reaction enzyme that is useful for accelerating many oxidative reactions that protect cells from the harmful effects of free radicals. Peroxidase is found in many common sources like plants, animals and microbes and have extensive uses in numerous industries such as industrial, medical and food processing. In this study, P. aeruginosa was harvested to utilize and study its peroxidases. P. aeruginosa was isolated from a burn patient, and the isolate was verified as P. aeruginosa using staining techniques, biochemical assay, morphological, and a sensitivity test. The gram stain and biochemical test result show rod pink gram-ne

Global concerns are rising due to complications associated with the use of chemical agents and antibiotic resistance. Consequently, research focus has shifted towards the quest for effective agents of biological origin. The aim of the present study was to assess the antioxidant and antimicrobial potentials of aqueous and organic extracts derived from various parts of Alcea kurdica. Different parts of A. kurdica were obtained and prepared into leaf, flower and root powders. The powders were extracted with aqueous and organic solvents. The antimicrobial activity of these extracts was assessed against bacterial pathogens using the agar well-diffusion assay. Additionally, the antioxidant effects of the extracts were evaluated using the

Thermomechanical analysis (TMA) and differential scanning calorimetry (DSC) are used to investigate the effect of molding and annealing of polyester on the behavior of thermal expansion and crystallization since these factors play role in the reprocessing or recycling of the polymer. The dynamic mode of the TMA provides enhanced characterization information about the polyester since it separates the transitions into reversible and irreversible signals, and also reveals the progress of the amorphous regions as the polyester loses strength with the increasing temperature approaching melting. Slow cooling after annealing brings crystallization that may be attributed to molecular chain straightening due to orientation.

     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