Breast cancer is one of the most widespread cancers,depending on World Health Organization, cancer calculated for approximately 7.6 million incidences in 2008, whoever expected elevation in incidence is about 13.1 million in 2030. So that the current research investigates vitamin D role in the occurrence of this disease and explains if vitamin D has a positive effect on the incidence of disease, as well as measuring parathyroid hormone and estrogen levels. Three groups were included in this analysis: control healthy women, benign and malignant breast tumor women. All cases that were selected at the beginning of the disease diagnosis. According to statistical values vitamin D showed highly significant (P<0.001) decrease in benign (3.74±2.33

This study included 46 patients with liver hydatid cyst diagnosed clinically and surgically, control group consist of 22 were naïve from infection had been confirmed by specialist. The patients were divided according to the size of the cysts into more and less than 5 cm diameter size, were 33 and 13 respectively. Also it divided into primary and secondary hydatid cyst infection which were 30 and 16 respectively. The role of immunological response against hydatid cyst parasite, showed a significant increased in humoral immunoglobulins (IgG, IgA, IgM and IgE) which were significantly higher in the hydatid cyst infection than control. Also significant increased in immunoglobulins in secondary infection than primary infection, beside significa

Background: Dietary intakes are critical during pregnancy, because inadequate amounts of key nutrients may compromise fetal development or maternal health. In addition to that maternal diet could be one of the methods to select the gender of the baby. The aim of the study is to correlate the level of the minerals in the mother’s blood with the gender and wellbeing of the baby after delivery.Patients and Methods: Fifty women were involved in this study with a mean age (23.92 ± 4.75), collected from the labor room during labor in the period between December 2013 and May 2014, in Baghdad teaching hospital. After taking a full history from the women, 10 ml of blood was withdrawn from them, 2ml in EDTA tubes for lead estimation and 8 ml in pl

Pots experiment was conducted in the green house of Biology Department, College of Education ( Ibn-AL-Haithum), University of Baghdad , during the growing season of 2005-2006 , to study the effect of five levels of urea fertilizer (0,50,100,150and 200) mg/pot in on vegetative growth of one wheat cultivar (Adanania) upon randomized complete block design with four replications. The results showed that significant difference between urea fertilizer levels above in vegetative growth characteristics ( plant height , leaf area , chlorophyll content, dry matter weight , relative efficiency and relative yield ) It was also showed that 200 mg/pot level was superior to urea fertilizer levels others in above charac

Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that

The load shedding  scheme has been extensively implemented as a fast solution for unbalance conditions. Therefore, it's crucial to investigate supply-demand balancing in order to protect the network from collapsing and to sustain stability as possible, however its implementation is mostly undesirable. One of the solutions to minimize the amount of load shedding is the integration renewable energy  resources, such as wind power, in the electric power generation could contribute significantly to minimizing power cuts as it is ability to positively improving the stability of the electric grid. In this paper propose a method for shedding the load base on the priority demands with incorporating the wind po

The accurate identification of internal and external pressures in thick-walled hyperelastic vessels is a challenging inverse problem with significant implications for structural health monitoring, biomedical devices, and soft robotics. Conventional analytical and numerical approaches address the forward problem effectively but offer limited means for recovering unknown load conditions from observable deformations. In this study, we introduce a Graph-FEM/ML framework that couples high-fidelity finite element simulations with machine learning models to infer normalized internal and external pressures from measurable boundary deformations. A dataset of 1386 valid samples was generated through Latin Hypercube Sampling of geometric and l