Background: Cigarette smoking is an important risk factor that has a clear strong association with the prevalence and severity of chronic periodontitis (CP). Salivary biochemical parameters may be affected by both smoking and CP together. Materials and methods: Eighty systematically healthy male patients were included in this study. They were grouped based on their periodontal and smoking status. Unstimulated whole saliva (UWS) was collected from all subject. Salivary flow rate (FR) was measured during sample collection. Parameters such as salivary pH, total protein (TP), albumin (Alb), total fucose (TF), protein bound fucose (PBF) and C-reactive protein (CRP) were estimated. Results: Salivary flow rate was not altered regarding to smoking status or periodontal health status. Salivary pH was lower in smokers comparing to non- smokers, while salivary pH was not affected by periodontal health status. TF, TP and Alb were higher in CP and PBF was lower in CP comparing to healthy control, while these parameters concentrations did not affect by smoking status except for Alb (smokers with CP had lower Alb concentration comparing to non-smokers with CP). CRP was higher in smokers comparing to non- smokers, while its value was not affected by periodontal health status. Both smoking and chronic periodontitis together affect some salivary biochemical parameters, thus the concentrations of these parameters could be used as indicators for periodontal disease progression and severity in smoker with CP. Both smoking and periodontal health status together should be taken in consideration when salivary composition is studied.
The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue
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In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.
BACKGROUND: Preeclampsia (PE) is a possible etiology of obstetrical and neonatal complications which are increased in resource-limited settings and developing countries. AIM: We aimed to find out the prevalence of PE in Iraqi ladies and specific outcomes, including gestational weight gain (GWG), cesarean section (CS), preterm delivery (PD), and low birth weight (LBW). METHODS: All singleton pregnant women visiting our tertiary center for delivery were involved over 3 years. PE women were compared with non-PE ladies. Complete history and examination were done during pregnancy and after delivery by the attending obstetrician and neonatologist with full documentation in medical records. RESULTS: PE prevalence was 4.79
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In light of the increasing importance of interim financial statements they provided these lists of information that enables users of accounting information to make wise investment decisions and predict the company's activities in light of changes the updated rather than wait until the end of the year and accessing information provided by the annual financial statements. In light of this research has come to the most important set of conclusions the adoption of interim financial information has been audited by the external auditor to the availability of basic qualitative characteristics in the accounting information contained in the (appropriate and timely manner, reliability and comparability) and this in turn leads to the impact on reli
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The herein research was carried out in order to identified the presence of bacteria in cervix and uterine lumen in Iraqi cattle during the different estrus phase with focusing on Protus and E coli. Estrus phases were determined by the structures which found on ovary (follicular growth for pro-estrus, mature growing follicle for estrus, hemorrhagic corpus luteam for meta-estrus and active corpus luteam for di-eatrus). Forty cervical swabs (ten for each estrus phase) and forty uterine swabs (ten for each estrus phase) were taken from macroscopically healthy reproductive animals after slaughtering and cultivated on nutrient agar and blood agar, the bacterial isolation were identified with biochemical teats. The present study found that
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CUPPER(||)AND MERCURY (||)Complexes WITH SCHIFF BASE LIGAND FROM BENZIDIN WITH ISATIN AND BENZOIN:SYNTHESIS,SPECTRAL CHARACTERIZATION, THERMAL STUDIES AND BIOLOGICAL ACTIVITIES
The 3D electro-Fenton technique is, due to its high efficiency, one of the technologies suggested to eliminate organic pollutants in wastewater. The type of particle electrode used in the 3D electro-Fenton process is one of the most crucial variables because of its effect on the formation of reactive species and the source of iron ions. The electrolytic cell in the current study consisted of graphite as an anode, carbon fiber (CF) modified with graphene as a cathode, and iron foam particles as a third electrode. A response surface methodology (RSM) approach was used to optimize the 3D electro-Fenton process. The RSM results revealed that the quadratic model has a high R2 of 99.05 %. At 4 g L-1 iron foam particles, time of 5 h, and
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