A solid Phase Extraction (SPE) cartridges followed by HPLC-UV method is described for the simultaneous quantitative determination of benzidine (BZ) and its substituted 3, 3’-dichlorobenzidine (DCB) and 3, 3’-Dimethylbenzidine (DMB). The Benzidines were separated by liquid chromatography using a C-18 column with UV detector at wave length of 280nm. The mode of Flow was isocratic. The mobile phase was consisted of 75:25 methanol: water, column temperature 50C°, and Flow Rate 1.8ml/min. Calibration curves were linear (R2 = 0.9979-0.9995). LOD (26.36-33.67) µg/L, LOQ (109.98-186.11) µg/L, the Robustness (2.99-4.35), Ruggedness (2.93-3.65).Conditions of extraction by (SPE) cartridges were optimized, the resin used is Octadecyl silica (ODS

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

level of effectiveness of Glutathione - S - Transferees (GST), Glutathione peroxides (GPX),Malondialdehyde (MDA) the product of lipid peroxidation and some trace elements ( zinc,seleinum,iron ,copper ) had been measured in sera of (50) women with breast disease.which had been divided to : Control group (25),The first group (A) benign breast tumors (25),the second group (B) breast cancer (25). The results showed a clear moral high level of Glutathione - S - Transferees (GST), Glutathione peroxidase (GPX) , and Malondialdehyde (MDA) level in breast cancer group while a slight increase were observed in the levels of these enzymes and(MDA) in benign breast group. A significant reduction was evident in the levels of selenium and zinc

Background: Vitamin D deficiency is a problem for pregnant women, and it affects general and oral health. This problem increases as vitamin D requirements increase during pregnancy. This study was conducted among pregnant women in urban and rural areas in order to assess the relation between salivary vitamin D3 and dental caries. Materials and methods: In this comparative cross-sectional study, all women participating were attending the primary Health Care Centers in Baghdad city in AL-Karkh sector, they were with age ranged from (15-44) years old. The total number 90 pregnant women in the second trimester only which include: The first group consists of (45) pregnant women attendance seeking dental treatment in urban areas, The second gr

The research problem arose from the researchers’ sense of the importance of Digital Intelligence (DI), as it is a basic requirement to help students engage in the digital world and be disciplined in using technology and digital techniques, as students’ ideas are sufficiently susceptible to influence at this stage in light of modern technology. The research aims to determine the level of DI among university students using Artificial Intelligence (AI) techniques. To verify this, the researchers built a measure of DI. The measure in its final form consisted of (24) items distributed among (8) main skills, and the validity and reliability of the tool were confirmed. It was applied to a sample of 139 male and female students who were chosen

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co