Background: Molars and premolars are considered as the most vulnerable teeth of caries attack, which is related to the morphology of their occlusal surfaces along with the difficulty of plaque removal. different methods were used for early caries detection that provide sensitive, accurate preoperative diagnosis of caries depths to establish adequate preventive measures and avoid premature tooth treatment by restoration. The aim of the present study was to evaluate the clinical sensitivity and specificity rates of DIAGNOdent and visual inspection as opposed to the ICDAS for the detection of initial occlusal caries in noncavitated first permanent molars. Materials and Methods: This study examined 139 occlusal surface of the first permanent molar pooled from fifty patients aged 8-9 years by three methods. The selected criteria include one occlusal site per tooth (first permanent molars) with carious lesions range from 0 to 3 according to ICDASII (gold standard) visual criteria then the clinical sensitivity and specificity of visual inspection according to Ekstrand et al.in 1997 and DIAGNOdent were performed. . Results: the highest correlation was found between the ICDASII and DIAGNOdent. The sensitivity of the DIAGNOdent for the enamel caries detection (D1) was better than that of visual inspection. The sensitivity and the specificity for the DIAGNOdent at D3 threshold were better than the D1 threshold and the visual inspection method. Conclusion: DIAGNOden pen can be used as a tool for early caries detection in cases of difficult diagnosis that provide good additional sensitivity to the visual inspection.
The species Bostrichus capucinus (L.) (Coleoptera:Bostrichidae) was reported as a new record for Iraq. Diagnostic characters and some information are given .
Objectives: The study aims to assess the school refusal behavior of first class pupils at primary schools and identifying the relationship between the school refusal behavior and some of socio-demographic characteristics for the pupils.
Methodology: A descriptive-analytic study was initiated from November 1st, 2012 to April 1st, 2013. A random sample of 411 students is selected from a probability stratified sample of 17 primary schools for both sexes in 4 sectors in Baghdad Al-Rasafa and Al-Karkh districts which are selected randomly from first class of primary school. A Self administrative questionnaire (Parents' Version) which constructed by the rese
... Show MoreIn today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har
... Show MoreCosmochthonius reticulatus Grandjean, 1947 (Acari: Oribatei: Cosmochthoniidae) and Rhysotritia ardua ardua C. L. Koch, 1841 ( Acari : Oribate : Euphthiracari¬dae), are two species of oribatids mites first recorded in Iraq from a woodland in the central part of Iraq. The two species are described and illustrated.
Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the
... Show MoreThe investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
... Show MoreThe current research aims to identify the most important green productivity tools GPT and the possibility of applied in industrial companies in general and the companies operating in the province of Nineveh, in particular, as well as the study of some personality characteristics and functional, which is believed to be an impact on the application of these tools in industrial companies. Accordingly, the research community of managers in the company of medicines and medical supplies ready-made clothes _ operating in the province of Nineveh, who are (80) while the manager was subjected to research procedures (49) Director representing (61.25%)
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