Background: Beta thalassemia major is an inherited disorder that may affect general and oral health.The purpose of this study was toassess the severity of dental caries in relation to oral cleanliness, mutans streptococciamong a group of boys with beta thalassemia majorin comparison with a control group. Materials and Methods: The study involved 30 boys with BTM aged 10-12 years compared to 30 healthy boys with the same age group. d1-4mfs and D1-4 MFS indices were applied (Muhlemann, 1976), the viable counts of mutans streptococci in stimulated saliva were also determined. Results: The entire thalassemic group was caries-active. For both dentitions, a higher dmfs/DMFS values were recorded for study compared to control group, difference was statistically not significantconcerning dmfs, while it was statistically significant concerning DMFS (P<0.05). Salivary bacterial counts of mutans streptococci were found to be higher in the study compared to control group and the difference was statistically highly significant (P<0.01).All correlations between bacterial counts and dmfs/DMFS indices in study group were statistically not significant. Conclusion: Patients with Beta thalasemic major had more caries severity compared to normal subjects.
The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach
... Show MoreIt has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlight
... Show MoreIt has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlighting the diff
... Show MoreThe clinical impact of interaction between body iron status (serum iron and ferritin) and type 2 diabetes has been investigated in this study. Thirty-six females were enrolled, eighteen type 2 diabetes and eighteen apparently healthy. These two groups were matched for age and body mass index BMI. The eighteen diabetes females were matched for age, BMI, pharmacological treatment (oral hypoglycemic agent), and chronic diabetes complications. The biochemical parameters measured for both groups (control and diabetes patient) were fasting insulin (Io), fasting blood glucose (Go), serum iron and ferritin. A significant increase in all parameters in patients compared to healthy control was noticed. The insulin resistance (IR) which was calculat
... Show MoreThe research problem revolves around the failure of Maysan Oil Company to have a strategy that enables it to keep up with work in a mysterious and highly dynamic environment. Therefore, the research aims to present a proposed strategy that is comprehensive and realistic to the Maysan Oil Company for the next five years (2020-2024) based on the position and conditions of the company Current and future by adopting the scientific foundations for formulating the strategy, and the importance of research lies in the company's situational analysis to know its internal capabilities from strengths or weaknesses and diagnosing the surrounding elements of opportunities or threats so that this analysis represents a s
... Show MoreBackground: Smoking is considering a major risk factor for development and progression of periodontal disease. Investigations regarding the association between smoking and periodontal disease have consistently demonstrated negative periodontal effects and greater probabilities of established periodontal disease among smokers in comparison with non smokers. The purpose of this study was to evaluate the effects of smoking on periodontal health status and on the salivary levels of alkaline phosphatase (ALP), lactate dehydrogenase (LDH) and creatine kinase (CK), and to correlate the clinical parameters of periodontal health with the biochemical findings in smokers and non-smokers. Materials and methods: Unstimulated saliva sample was collected
... Show MoreSupport vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
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