Background: Salivary immunoglobulin IgA plays an essential role in the immune response against dental caries. This studywas conducted to compare the salivary IgA levels and flow rate of stimulated saliva in caries active and caries free children. Materials and methods: The present study included sixty healthy children age 7-10 yearswho were divided into two groups. They were caries free and caries active children (30 children in each group). Assessment and recording of caries – experience were through the application of Decayed, Missing and Filled Tooth Index (DMFT) and (dmft) index, for permanent and deciduous teeth respectively. After dental examination, stimulated saliva samples were collected from the subjects and performed under standard condition following instruction cited by Tenovuo and Lagerlof, and chemically analyzed for the detection of salivary immunoglobulin (IgA).In addition, salivary flow rate for the children were evaluated. Data was then statistically analyzed using SPSSversion 18. Results: Salivary IgA levels were significantly higher in caries free children than caries active children and the flow rate were lower in caries active children in both gender as compared to caries free children. Conclusions: Within the limitation of this study, it can be concluded that that the flow rate and salivary IgA levels of the whole stimulated saliva have some role in protection against dental carie
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The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed
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The δ-mixing of γ-transitions in 70As populated in the 32 70 70 33 ( , ) Ge p n As γ
reaction is
calculated in the present work by using the a2-ratio methods. In one work we applied this method for two cases, the first one is for pure transition and the sacend one is for non pure transition, We take into account the experimental a2-coefficient for previous works and δ -values for one transition only.The results obtained are, in general, in a good agreement within associated errors, with those reported previously , the discrepancies that occur are due to inaccuracies existing in the experimental data of the previous works.