Background: Diabetes mellitus (DM) accompanied with an increase in the death rate and represents a significant public health challenge. It is the cause of other disorders and infection in many body organs. Hence, it is important to study the possible changes in the immunological components in the serum of diabetic patients which are not well understood. In this work, serum C3, C4, IgA, IgG, and IgM were estimated in the patients with insulin dependent diabetes mellitus (IDDM) and compared with healthy persons. Patients and Methods: Twenty-one insulin dependent diabetic patients in addition to twenty-four healthy persons as control group were participated in this study. Serum C3, C4, IgA, IgG, and IgM were measured by using immunodiffusio

Background: H.pylori colonized gastric mucosal
epithelium will virtually develop gastritis and had the
capacity to persist for decades. Pathogenesis is
dependent upon strain, virulence host genetic
susceptibility, and environmental cofactors. Leptin is
a member of the class 1 cytokine family so altered
leptin production during ifnect and inflammation that
leptin part of the cytokine cascade ,which
orchestrates the defense mechanism.
Objective: Examin the effect of H.pylori infection
on serum leptin level.
Methods: One hundred and thirty(130) Patients
attending the Endoscopic Unit at "Gastroenterology
and Hepatology Teaching Hospital/ Baghdad Medical
City"were included in this study with ages rang

The possible effect of the collective motion in heavy nuclei has been investigated in the framework of Nilson model. This effect has been searched realistically by calculating the level density, which plays a significant role in the description of the reaction cross sections in the statistical nuclear theory. The nuclear level density parameter for some deformed radioisotopes of (even- even) target nuclei (Dy, W and Os) is calculated, by taking into consideration the collective motion for excitation modes for the observed nuclear spectra near the neutron binding energy. The method employed in the present work assumes equidistant spacing of the collective coupled state bands of the considered isotopes. The present calculated results for f

Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t

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