Background: Dental caries is the most common oral problem, although dental caries is not life threating, it has aharmful effect on quality of life. Socioeconomic factors were found to be strong predictors of the prevalence of oral diseases in children, likes family income, occupational prestige, and education. The aim of this study is to assess the effect of socioeconomic factors on occurrence dental caries in their children. Materials and methods: The sample consists of 550 kindergartens children aged between (4-5) years were selected randomly, girls and boys. The kindergartens selection was randomly from different geographical areas in Al-Najaf governorate. Information was taken from children's parents using questionnaire with the help of the kindergartens managers. Examination of dental caries severity was performed according to the World Health Organization (1987). Children were examined in a suitable room in their school. Day light was used for illumination. Results: High caries prevalence was recorded (84.7%); females had higher caries prevalence as compared to males. Mean dmfs was (10.05±0.40) and ds value was the highest component. Age differences were recorded for both indicators with no gender differences.Secondary and high schools arethe highest percentage of the education of the child’s parents and the differences were not significant regarding dental caries between parent factors. Conclusion: Children in this study were in need of preventive programs that are to say in need of recall for regular visits and the prophylactic application of fluoride therapy and fissure sealant to prevent initiation of dental caries.
This current study was built on creating four electrodes based on molecularly imprinted polymers (MIPs). As the template using Cefalexin (CFX), 1-vinyl imidazole (VIZ) and vinyl acetate (VA) as monomer, and N, N-methylene bis acrylamide (MBAA) as cross-linkers and benzoyl peroxide as the initiator, two MIPs were prepared. The same composition was used in non-impressed polymers (NIPs) preparation, but without the template (Cefalexin). For the membranes preparation, numerous plasticizers, such as tri-oly phosphate (TOP) and di-octyl phthalate (DOP), were used in the PVC matrix, slop, detection limit, lifetime, and linearity range of CFX-MIPs electrodes are characteristics &nb
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Bajila regarded as descending from Anmar Ibn Nizar. Al-Masudi accepts
Bajila and Khath”am as being of Nizar, and asserts that it was only out of the
enmity that they were said to be from the Yemen.
Al-Ya”qubi tries to harmonize this by assuming that Anmar married a
women of the Yemen and that his sons Bajila and Khath”am are thus
connected to the people of this region only through their mothers line.
Bajila embraced Islam in the period of the prophet. Omar 1 forced this
tribe to go to Iraq instead of Al-_Sham, and gave them the quarter of Al- Saw
ad. Then they prohibited from that quarter by given money as reward that
made them against omar1.
This tribe assisted the forth rightly guided ca
The study was carried out to study the quality of 7 samples of imported frozen chicken that are available in locally markets. These samples were collected from Baghdad markets in June 2010. The results were showed that the all samples were not content the name of company and batch number one the labeling, while the microbial test refer to found contamination in all samples, but it in the limited of Iraqi standers specification for frozen chicken, also note Staphylococcus aureus in all samples, the samples C1 and C2 have Salmonella ohio, while not observe Coliform bacteria in all samples.
The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables. The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.
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Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables
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In the present work, bentonite clay was used as an adsorbent for the removal of a new prepared mono azo dye, 4-[6-bromo benzothiazolyl azo] thymol (BTAT) using batch adsorption method. The effect of many factors like adsorption time, adsorbent weight, initial BTAT concentration and temperature has been studied. The equilibrium adsorption data was described using Langmuir and frundlich adsorption isotherm. Based on kinetics study, it was found that the adsorption process follow pseudo second order kinetics. Thermodynamics data such as Gibbes Free energy ∆Gᵒ, entropy ∆Sᵒ and ∆Hᵒ were also determined using Vant Hoff plot.
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