Background: periodontitis is a chronic inflammatory disease causing destruction of the tooth supporting structures, initiated by dental plaque and modified by environmental and genetic risk factors. Cyclooxygenase-2 (COX-2) enzyme is responsible for the production of prostaglandin E2, an important mediator in the chronic periodontitis (CP) pathogenesis. Polymorphisms in COX-2 gene have linked to CP in different populations. Aim: To study the association between Cyclooxygenase-2 single nucleotide polymorphism rs689466 (-1195A/G SNP) and chronic periodontitis in a sample of Iraqi population. Methods: One hundred Iraqi subjects divided into two groups: case group consisted of 70 CP patient (35 males and 35 females) with age range 30-55 year

Optimizing system performance in dynamic and heterogeneous environments and the efficient management of computational tasks are crucial. This paper therefore looks at task scheduling and resource allocation algorithms in some depth. The work evaluates five algorithms: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Firefly Algorithm (FA) and Simulated Annealing (SA) across various workloads achieved by varying the task-to-node ratio. The paper identifies Finish Time and Deadline as two key performance metrics for gauging the efficacy of an algorithm, and a comprehensive investigation of the behaviors of these algorithms across different workloads was carried out. Results from the experiment

The aim of the research is to know the effect of a training program based on interactive teaching strategies on achievement and creative problem solving among fourth-grade students in chemistry of the directorate of education Rusafa first, the sample was divided into two groups, one experimental and numbering (29) students and the other control group numbering (30) students. The experimental group underwent the training program in the first semester of the year (2021-2022) and the control one studied according to the usual method. Two tools were built, the first being an academic achievement test consisting of (40) multiple-choice items, and the second a test of creative problem-solving skills in a chemistry subject and consisting o

A network (or formally a graph) can be described by a set of nodes and a set of edges connecting these nodes. Networks model many real-world phenomena in various research domains, such as biology, engineering and sociology. Community mining is discovering the groups in a network where individuals group of membership are not explicitly given. Detecting natural divisions in such complex networks is proved to be extremely NP-hard problem that recently enjoyed a considerable interest. Among the proposed methods, the field of evolutionary algorithms (EAs) takes a remarkable interest. To this end, the aim of this paper is to present the general statement of community detection problem in social networks. Then, it visits the problem as an optim

     In this paper, we design a fuzzy neural network to solve fuzzy singularly perturbed Volterra integro-differential equation by using a High Performance Training Algorithm such as the Levenberge-Marqaurdt (TrianLM) and the sigmoid function of the hidden units which is the hyperbolic tangent activation function. A fuzzy trial solution to fuzzy singularly perturbed Volterra integro-differential equation is written as a sum of two components. The first component meets the fuzzy requirements, however, it does not have any fuzzy adjustable parameters. The second component is a feed-forward fuzzy neural network with fuzzy adjustable parameters. The proposed method is compared with the analytical solutions. We find that the proposed meth

In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route f

Energy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit

Acceptable Bit Error rate can be maintained by adapting some of the design parameters such as modulation, symbol rate, constellation size, and transmit power according to the channel state.

An estimate of HF propagation effects can be used to design an adaptive data transmission system over HF link. The proposed system combines the well known Automatic Link Establishment (ALE) together with variable rate transmission system. The standard ALE is modified to suite the required goal of selecting the best carrier frequency (channel) for a given transmission. This is based on measuring SINAD (Signal plus Noise plus Distortion to Noise plus Distortion), RSL (Received Signal Level), multipath phase distortion and BER (Bit Error Rate) fo