Hydro cracking of heavy oil is used in refinery to produce invaluable products. In this research, a model of hydro cracking reactor has been used to study the behavior of heavy oil in hydro cracking under the conditions recommended by literature in terms lumping of feed and products. The lumping scheme is based on five lumps include: heavy oil, vacuum oil, distillates, naphtha and gases. The first order kinetics was assumed for the conversion in the model and the system is modeled as an isothermal tubular reactor. MATLAB 6.1 was used to solve the model for a five lump scheme for different values of feed velocity, and temperature.

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

Aim: To evaluation the effect of Lactobacillus acidophilus on Enterohemorrhagic Escherichia coli (EHEC) serotype O157:H7 with detection of some virulence factors. Methods: Two hundred and fifty specimens (stool) from children under five years for both sexes were collected from some hospitals. All isolates were diagnosed according to morphological characteristics, biochemical tests. Monoplex pattern of PCR was used also for detection different genes in (7) Escherichia coli )O157:H7 (isolates; include 16SrRNA, eae, lifA, Stx1,Stx2 that encoded for ribosomal RNA, intimin, lymphocyte inhibitory factor, shiga toxins. Three types of probiotics strains were obtained, Lactobacillus fermentum, Lactobacillus plantarum and Lactobacillus acidophilus (A

Many studies of the relationship between COVID-19 and different factors have been conducted since the beginning of the corona pandemic. The relationship between COVID-19 and different biomarkers including ABO blood groups, D-dimer, Ferritin and CRP, was examined. Six hundred (600) patients, were included in this trial among them, 324 (56%) females and the rest 276 (46%) were males. The frequencies of blood types A, B, AB, and O were 25.33, 38.00, 31.33, and 5.33%, respectively, in the case group. Association analysis between the ABO blood group and D-dimer, Ferritin and CRP of COVID-19 patients indicated that there was a statistically significant difference for Ferritin (P≤0.01), but no-significant differences for both D-dimer and CRP.

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

Systole merazvensis sp. n. from Iraq, is described, figuri4 and differentiated from ,other species of the genus Systok.