Mutans streptococci (MS) are a group of oral bacteria considered as the main cariogenic organisms. MS consists of several species of genus Streptococcus which are sharing similar phenotypes and genotypes. The aim of this study is to determine the genetic diversity of the core species of clinical strains of Streptococcus mutans, Streptococcus sobrinus and Streptococcus downei by using repitative extragenic palindromic (REP) primer. The DNA of the clinical strains of S. mutans (n=10), S. sobrinus (n=05) and S. downei (n=04) have been employed in the present study, which have been previously isolated from caries active subjects. The DNA of the clinical and reference strains was subjected to PCR amplification using REP primer. The phylogenetic dendrogram is constructed from the REP PCR banding profile by neighbour-joining method using PyElph 1.4 software. The size of the DNA amplicons generated by using REP primer were S. mutans (1500 bp to 250 bp), S. sobrinus (6000 bp to 250 bp) and S. downei (5000 bp to 400 bp). The results present common band at 480 bp in all the clinical strains of S. sobrinus. The current study is the first to demonstrate the genetic variety of S. sobrinus and S. downei by using REP primer. REP-PCR have been found to be a powerful method to study the molecular diversity of S. mutans, S. sobrinus and S. downei. Additionally, further studies are suggested to analyze the species specific bands and also to find the possibility to produce a new specific primer for S. sobrinus.
The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.
The phenomenon of negative behavior has studied as a social and psychological phenomenon that effect on the performance and life of workers inside and outside the organization. The adoption of this phenomenon is studied in terms of the role of the internal environment of the organization in addressing this behavior, being the variables belong to the field of organizational behavior to see the results of those variables on the Iraqi organizations, since the specificities of it differ from the rest of the Arab and foreign environments. Therefore, this study focused on testing the relationship of the internal environment of the organization and its role in addressing the negative behavior of the workers.
thi
... Show MoreGlobal oceanic anoxic events (OAEs) are events of immense importance for a variety of reasons. For instance, they are not only behind most if not all of the mass extinctions which took place during the Cenozoic era, but they are the harbinger for the world's best oil source beds, which humanity depends on to satisfy its energy need. In spite of this, there was little effort to document their presence in Iraq, to fill in for the void here, and as a first step, this paper will attempt to establish a cause and effect relationship between OAE 2 and the Gulneri Formation timing of deposition and organic matter richness. This was done by showing the prevalent occurrence of the globally known OAE 2 positive ∂13Corg excursion and the unique ro
... Show MoreToday, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate
... Show MoreArtificial Neural Network (ANN) model's application is widely increased for wastewater treatment plant (WWTP) variables prediction and forecasting which can enable the operators to take appropriate action and maintaining the norms. It is much easier modeling tool for dealing with complex nature WWTP modeling comparing with other traditional mathematical models. ANN technique significance has been considered at present study for the prediction of sequencing batch reactor (SBR) performance based on effluent's (BOD5/COD) ratio after collecting the required historical daily SBR data for two years operation (2015-2016) from Baghdad Mayoralty and Al-Rustamiya WWTP office, Iraq. The prediction was gotten by the application of a feed-forwa
... Show MoreIncreasing demands on producing environmentally friendly products are becoming a driving force for designing highly active catalysts. Thus, surfaces that efficiently catalyse the nitrogen reduction reactions are greatly sought in moderating air-pollutant emissions. This contribution aims to computationally investigate the hydrodenitrogenation (HDN) networks of pyridine over the γ-Mo2N(111) surface using a density functional theory (DFT) approach. Various adsorption configurations have been considered for the molecularly adsorbed pyridine. Findings indicate that pyridine can be adsorbed via side-on and end-on modes in six geometries in which one adsorption site is revealed to have the lowest adsorption energy (–45.3 kcal/mol). Over a nitr
... Show More