Breast cancer is the commonest cancer affecting women worldwide. Different studies have dealt with the etiological factors of that cancer aiming to find a way for early diagnosis and satisfactory therapy. The present study clarified the relationship between genetic polymorphisms of BRCA1 & BRCA2 genes and some etiological risk factors among breast cancer patients in Iraq. This investigation was carried out on 25 patients (all were females) who were diagnosed as breast cancer patients attended AL-Kadhemya Teaching Hospital in Baghdad and 10 apparently healthy women were used as a control, all women (patients and control) aged above 40 years. The Wizard Promega kit was used for DNA isolation from breast patients and normal individuals. B

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

   This research aims to introduce the general tax on sales in gordan and the most important concepts related to this type of taxes and identify the  most  on characteristics and stand on its role in supplying the general budget of the necessary fundig to cover the over head of the state and the factorsinfluencing it and whether such a tax has been able to chieve the desired goals.including in contribute to an important and growing role in puplic revenues or not to be able to achieve these goals through the use of descriptive and analytical technique based on the data and information relevant.wasreached some conclusion and  recommendations was most important is that the general sales tax comes in

Background: The excessive use and abuse of antibiotics contribute to bacterial resistance, raising the risk of complications and treatment failures. This study investigates adherence to antibiotic prescriptions among Iraqi dental patients, highlighting implications for antimicrobial resistance.Objective: To assess adherence levels and identify factors influencing antibiotic therapy compliance among dental patients.Methods: A cross-sectional survey was conducted in which adult dental patients aged 18 and older, who had been prescribed antibiotics within the past year, participated. The modified Morisky Medication Adherence Scale-8 items was used to evaluate adherence, and data were analyzed with IBM SPSS Statistics software V26.Results: Amon

This work involves separating and studying the aminoacylase-1 (ACY1) of amniotic fluid from healthy pregnant, mainly one peak with higher activity has been isolated by DEAE-Cellulose ion exchange from the proteinous supernatant produced by deposition of proteins using ammonium sulfate  (65%) after dialysis. The purification folds reaching to 19 folds also gave one protein peak when injected into the gel filtration column, a high ACY1 purity was obtained, with 38 folds of purification. It was found that the molecular weight of the isolated ACY1 was up to 46698 Dalton when using gel chromatography technique.The effect of ACY1 isolate was studied on rats with oxidative stress caused by lead acetate(LA) at 40 mg / kg body weight and compare

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

: 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.

Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th