S Khalifa E, AR Jamal R, N Adil A, J Munqithe M…, 2009

The aim of the present study is to evaluate the change in the levels of glucagon, GLP-1 and GPCR in diabetic patient's and diabetic with dyslipidemia as metabolic syndrome. The study included 75 male aged ranged (30-50) years and with BMI (25-29) kg/m2 which divided into three groups as follows: group one (G1): consist of 25 subjects as healthy control group. Group two (G2): consist of 25 patient's with diabetes mellitus and group three (G3): consist of 25 patient's with diabetic and dyslipidemia as metabolic syndrome. Serum was used in determination of FBG, lipid profile, insulin, glucagon, GLP-1 and GPCR. Whole blood was determination of HbA1c. The results revealed significant elevation in FBG and HbA1c in G2 and G3 comparing to G1. While

To investigate the role of IL-6 and IL-8 in the immune-regulatory mechanisms involved in the recurrent spontaneous abortion of the first trimester of pregnancy. Serum level of IL-6 and IL-8 were determined in 25 women of age (20-35) years who had a spontaneous abortion of unknown aetiology during the first trimester of pregnancy .They were compared with the corresponding levels of 20 pregnant and non-pregnant women as control groups .cytokine levels were measured by (ELISA) technique .The women with spontaneous abortion had highly significant (P < 0.01) increased serum level of IL-8 and highly significant (P < 0.01 ) decreased level of IL-6 compared to those with normal pregnant and non-pregnant women. The results of this study ma

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from

     Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them.  This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, c