This research deals with the topic of "the status of women" in the literature of Sufism. The researcher cites a bundle of mystical yarns, and examples of verses and poems from this high literature that look at women with reverence and appreciation. The researcher tried to find an appropriate explanation and away from the arbitrariness of the symbols used by the poets of Islamic Sufism In their poems.

    The research is considered a comparative study of the Arabic and Kurdish dialects, by selecting six famous poets from the literature of literature, three of them from Arabic literature, and the other three from Kurdish literature, so the research is di

This research deals with the topic (the position of women) in the literature literature, and the researcher cites a bouquet of woolen yarn, examples of verses and poems from this fine literature that looks at the woman with respect and appreciation. In their poems.
The research is a comparative search for Arab and Kurdish literature, by selecting six famous poets in the literature, three of them are from Arabic literature, and the other three are from Kurdish literature, and thus the research is divided into two subjects and six demands.
Finally, the researcher tried to set a brick that would be an entry point to find an indicative explanation and a suitable explanation that would break those symbols and signs that caused the exp

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

This study was aimed to investigate the response of two types of ornamental herbaceous plants (Wedelia trilobata and Jacobaea maritima 'Cirrus') to different agricultural environments and the application of potassium silicates to the living walls system LWS (Felt layer system) under the climate conditions of Baghdad city. Each experiment involved the cultivation of a different plant species, and the study duration was from September 15, 2021, to August 1, 2022. A Strip-Plot Design experiment was conducted using two factors: factor M with four levels of substrates (50% peatmoss and perlite (M1), 50% Vermicompost and perlite (M2), 50% Water hyacinth compost and perlite (M3), 50% wheat straw compost and perlite (M4)) and factor S with

Doppler assessment may lead to intervention that reduces the risk of fetal brain damage. Aim of thestudy: to assess the relation between ultrasonic hemodynamic Doppler indices of middle cerebral and umbilical arteries (PI, RI), growth indices to immediate neonatal outcomes (weight, head & abdominal circumference, APGAR scores at 1 and 5 minutes and neonatal unit admission) in women with mild, moderate and severe anemia during pregnancy. Present study is a clinical prospective study carried out in Al-Elwiya Maternity Teaching Hospital during (January-Jun) 2019, all anemic pregnant women presented to Obstetrical wards in hospitals for emergency cesarean section were the study population. The final sample selected was 120 pregnant women. Ultra

Breast cancer (BC) is one of the most frequently observed malignancy in females worldwide. Today, tamoxifen (TAM) is considered as the highly effective therapy for treatment of breast tumors. Oxidative stress has implicated strongly in the pathophysiology of malignancies. This study aimed to investigate the changes in the levels of oxidants and antioxidants in patients with newly diagnosed and TAM-treated BC. Sixty newly diagnosed and 60 TAM-treated women with BC and 50 healthy volunteers were included in this study. Parameters including total oxidant capacity (TOC), total antioxidant capacity (TAC), and catalase (CAT) activity were determined before and after treatment with TAM. The serum levels of TOC and oxidative stress index (OSI) were

Irisin is a novel myokine and adipokine, its role during pregnancy and its association with some metabolic risk factors especially pre-pregnancy body mass index (pre-BMI) need more evaluation. The aim of the study is to find whether the pre-BMI could predict irisin levels during normal pregnancy and to clarify associations of irisin with some pathological parameters.

Irisin levels were estimated by ELISA in sera of 59 normal pregnant women who enrolled from December 2016 to May 2017 at Maternity Hospital, Zakho city, Kurdistan region (Iraq). Thirty-two normal-weight pregnant (pre-BMI≤24.9 kg/m², Age=24.03 mean±3.7standard deviation) and 27 overweight/obese-pregnant (pre-BMI>25 kg/m², Age=27.6 mean±3.9