The (CTLA-4) encodes of the T cell receptor involved in the control of T cell
proliferation and mediates T cell apoptosis. The contribution of CTLA-4 gene
variants to type 1 diabetes has been analyzed in several ethnic groups. In this study,
the association of CTLA-4 +49 A/G polymorphism with type 1 diabetes was
investigated in Egyptian patients. Sixty type 1 diabetic patients (25 males and 35
females) and 60 healthy individuals (33 males and 27 females) subjects formed the
studied populations. CTLA-4 A/G polymorphism at position 49 in exon 1 was
identified using allele specific methods. Patient numbers with A/G, A/A and G/G
genotypes were 45 (75.0 %), 6 (10.0 %) and 9 (15.0%) while in healthy controls,
these w

     Structure of network, which is known as community detection in networks, has received a great attention in diverse topics, including social sciences, biological studies, politics, etc. There are a large number of studies and practical approaches that were designed to solve the problem of finding the structure of the network. The definition of complex network model based on clustering is a non-deterministic polynomial-time hardness (NP-hard) problem. There are no ideal techniques to define the clustering. Here, we present a statistical approach based on using the likelihood function of a Stochastic Block Model (SBM). The objective is to define the general model and select the best model with high quality. Therefor

In this paper, we will give another class of normal operator which is (K-N)*
quasi-n-normal operator in Hilbert space, and give some properties of this concept
as well as discussion the relation between this class with another class of normal
operators.

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

This research deals  with the detection of possible surface soil pollution by radon emissions for an area located inside the university of Baghdad campus at AL-Jadiriyah / Baghdad. The area is about 5625 m² and located near the College of Science for Women. The area used as construction rubbles dump yard in the past, while recently it is covered with Silty - Clayey soil furnished with grass and used as a playground. A surface survey performed on October 2018 by gridding the area into 36 stations where surface radiometric pollution readings recorded and soil samples collected by using an auger for the top 30 Cm which represents the root zone of the area. Soil samples tested in the laboratory by using can technique with CR-

In this paper a new technique based on dynamic stream cipher algorithm is introduced. The mathematical model of dynamic stream cipher algorithm is based on the idea of changing the structure of the combined Linear Feedback Shift Registers (LFSR's) with each change in basic and message keys to get more complicated encryption algorithm, and this is done by use a bank of LFSR's stored in protected file and we select a collection of LFSR's randomly that are used in algorithm to generate the encryption (decryption) key.

We implement Basic Efficient Criteria on the suggested Key Generator (KG) to test the output key results. The results of applying BEC prove the robustness and efficiency of the proposed stream cipher cryptosystem.

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust EA wit