This research attempts to find the association between single nucleotide polymorphism (SNP) of IL2+166 gene (rs2069763) and type 2 diabetes mellitus (T2DM) in a sample of Iraqi patients. A total of 44 patients and 55 apparently healthy volunteers were genotyped for the SNP using polymerase chain reaction test. Three genotypes (GG, GT, and TT) corresponding to two alleles (G and T) were found to have SNP. Both study groups’ genotypes had a good agreement for the analysis of Hardy-Weinberg Equilibrium. The results revealed increased frequencies between the observed and expected GG and TT genotypes and IL2+166 SNP T allele in T2DM  patients (40.9 vs. 40.0 %; OR = 1.04; 95% CI, 0.47 - 2.31), whereas the values in the control group were

Background. Neutrophils play an important role in maintaining periodontal status in conditions of healthy homeostasis. They achieve their surveillance function by continuously migrating to the gingival sulcus and eradicating periodontal pathogens. In addition, neutrophils are considered an integral element in the pathogenesis of periodontal diseases. Among several neutrophil subsets, low‐density neutrophils (LDN) have recently received attention and are linked with cancer, immunological, inflammatory, and infectious diseases. However, the presence, phenotypes, and potential role of LDN in the pathogenesis of periodontitis have not yet been investigated. Objectives. To investiga

Today, the success or failure of organizations depends to possess the wisdom of their managers promised that the key to organizational success of the business environment, making the right decisions, and create the ability to work and think towards discrimination of products and services the organization . Seek this research to investigation the relationship between the wisdom management and differentiation strategy for service operations . It was a test of that relationship in light of the results of the analysis of the data collected through the questionnaire distributed on a sample from (98) Director Mangers, head of department and head of division in  the General Establishment of Civil Aviation . The research used descriptive st

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T

Today’s academics have a major hurdle in solving combinatorial problems in the actual world. It is nevertheless possible to use optimization techniques to find, design, and solve a genuine optimal solution to a particular problem, despite the limitations of the applied approach. A surge in interest in population-based optimization methodologies has spawned a plethora of new and improved approaches to a wide range of engineering problems. Optimizing test suites is a combinatorial testing challenge that has been demonstrated to be an extremely difficult combinatorial optimization limitation of the research. The authors have proposed an almost infallible method for selecting combinatorial test cases. It uses a hybrid whale–gray wol

Intended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted

Optimizing the Access Point (AP) deployment has a great role in wireless applications due to the need for providing an efficient communication with low deployment costs. Quality of Service (QoS), is a major significant parameter and objective to be considered along with AP placement as well the overall deployment cost. This study proposes and investigates a multi-level optimization algorithm called Wireless Optimization Algorithm for Indoor Placement (WOAIP) based on Binary Particle Swarm Optimization (BPSO). WOAIP aims to obtain the optimum AP multi-floor placement with effective coverage that makes it more capable of supporting QoS and cost-effectiveness. Five pairs (coverage, AP deployment) of weights, signal thresholds and received s

The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu