Background: Irrigation of the canal system permits removal of residual tissue in the canal anatomy that cannot be reached by instrumentation of the main canals so the aim of this study was to compare and evaluate the efficiency of conventional irrigation system, endoactivator sonic irrigation system,P5 Newtron Satelec passive ultrasonic irrigation and Endovac irrigation system in removing of dentin debris at three levels of root canals and to compare the percentage of dentin debris among the three levels for each irrigation system. Materials and methods: Forty extracted premolars with approximately straight single root canals were randomly distributed into 4 tested groups of 10 teeth each. All canals were prepared with Protaper Universal hand files to size #F4, and irrigated with 2.5% NaOCI 1 ml between files and 5ml for 60 seconds as a final irrigant by different irrigation devices; group one, by using conventional system; group two, by using Endoactivator sonic irrigation system, group three, by using Satelec Passive Ultrasonic irrigation and group four by using the Endovac system. After the final irrigation, the roots were split longitudinally and photographed with a digital microscope. The roots were magnified to 100X; a percentage of debris was calculated for the apical 0-3, middle 3-6 and coronal 6-9 mm. The debris score was calculated as a percentage of the total area of the canal that contained debris as determined by pixels in Adobe PhotoshopCS5. Data were analyzed statistically by ANOVA and LSD at 5% significant level. Results: when comparing the debris remaining, the Endovac, Endoactivator and Satelec groups showed significantly less debris than the conventional group at all three levels (p < 0.01). The Endovac group showed significantly less debris than the Endoactivator group at middle and coronal levels while no significant difference found between the Endovac system and Endoactivator system at apical level. The apical 0-3 mm showed significantly more debris than both the middle and coronal level for all groups. Conclusion: The EndoVac system showed a higher cleaning capacity of the canal at all levels, followed by the protocols that used Endoactivator sonic irrigation system. The conventional irrigation system with maxi-i-probe needles showed inferior results. The apical three millimeters showed a greater amount of debris than the 3-9 millimetres from the working length, regardless of the irrigation device used.
Implementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.
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Protein arginine methyltransferases (PRMTs) play important roles in transcription, splicing, DNA damage repair, RNA biology, and cellular metabolism. Thus, PRMTs have been attractive targets for various diseases. In this study, we reported the design and synthesis of a potent pan-inhibitor for PRMTs that tethers a thioadenosine and various substituted guanidino groups through a propyl linker. Compound II757 exhibits a half-maximal inhibition concentration (IC50) value of 5 to 555 nM for eight tested PRMTs, with the highest inhibition for PRMT4 (IC50 = 5 nM). The kinetic study demonstrated that II757 competitively binds at the SAM binding site of PRMT1. Notably, II757 is selective for PRMTs over a panel of other methyltransferases, w
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreBackground: In the past, an association between Tuberculosis (TB) and Diabetes Mellitus (DM) was widely accepted, today the potential public health and clinical importance of this relationship seems to be largely ignored. The national clinical and policy guidance in the UK on the central of TB, for example, does not consider the relationship with DM.Objectives: To determine the risk of association between diabetes mellitus and pulmonary TB.Methods: A retrospective study conducted in Ibn Zuhr hospital for chest diseases from Jan 2008 – sep 2010 , included in the study 402 patients with TB divided into diabetic & non diabetic, 96 (23.8%) were diabetic while other 306 were TB not diabetic.Results: Risk of TB among DM patients were cle
... Show MoreIn this study an experimental work was done to study the possibility of using aluminum rubbish material as a coagulant to remove the colloidal particles from oily wastewater by dissolving this rubbish in sodium hydroxide solution. The experiments were carried out on simulated oily wastewater that was prepared at different oil concentrations and hardness levels (50, 250, 500, and 1000) ppm oil for (2000, 2500, 3000, and 3500) ppm CaCo3 respectively. The initial turbidity values were (203, 290, 770, and 1306) NTU, while the minimum values of turbidity that have been gained from the experiments in NTU units were (1.67, 1.95, 2.10, and 4.01) at best sodium aluminate dosages in milliliters (12, 20, 24, and 28) for
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
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