Background: The bond strength of root canal sealers to dentin was important for maintaining the integrity of the seal in root canal filling in both static and dynamic situations. In a static situation, it should eliminate any space that allowed the percolation of fluids between the filling and the wall while in a dynamic situation; it was needed to resist dislodgement of the filling during subsequent manipulation. Materials and Methods: Forty mandibular premolars were selected for this study. All canals were instrumented using ProTaper rotary instruments. Instrumentation was done with copious irrigation of 5.25% sodium hypochlorite. Roots were randomly divided into four groups according to the type of cleaning and method of root canal irrig

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

An optical spectroscopic study is reported in this article to study the correlation between the supermassive black hole (SMBH) and the star formation rate (SFR) for a sample of Seyfert galaxies type (I and II). The study focused on 45 galaxy of Seyfert 1, in addition to 45 galaxy of Seyfert 2, where these samples have been selected form different survey of Salon Digital Sky Survey (SDSS). The redshift (z) of these objects were between (0.02 – 0.26). The results of Seyfert 1 galaxies shows that there good correlation between the SMBH and the SFR depending on statistical analysis parameter named Spearman’s Rank Correlation in a factor of (ρ=0.609), as well as the Seyfert 2 galaxies results show a good correlation between the SMBH and

It was rumored in the grammatical circles that the (short) refrigerant is only a copy of (book) Sibweh, except some of the views that violated it, or some of the evidence that increased it; On the (brief) or not, the researcher has chosen the subject (what is going away and not leave) a field of study of the budget, has come on three demands, the first devoted to the study of the term, and the second to explain the methodology of scientists in the presentation of the topic, and the third was limited to the study of the evidence they invoked .
God grants success

Abstract :In this study, amygdaline in Iraqi plant seeds was extracted and isolated from their seeds matrix using reflux procedure and subsequently identified and determined by high performance liquid chromatography (HPLC) on reversed phase column of LC-18 (150mm x 4.6mm, 5?m )with actonitrile :water ( 50 : 50 ) as mobile phase at flow rate of ( 0.5 mL/min ) and detection at wavelength of 215 nm.The experimental results indicated that the linearity of calibration is in the range of 1.0-30.0 mg L-1amygdaline with the correlation coefficient of 0.9949. The limit of detection (LOD) and limit of quantitation (LOQ) for amygdaline were of 0.88 and 2.93 mg L-1 in standard pure sample. The mean recovery percent is 97.34±0.58 at 95% confidence inte

Simultaneous determination of Furosemide, Carbamazepine, Diazepam, and Carvedilol in bulk and pharmaceutical formulation using the partial least squares regression (PLS-1 and PLS-2) is described in this study. The two methods were successfully applied to estimate the four drugs in their quaternary mixture using UV spectral data of 84synthetic mixtures in the range of 200-350nm with the intervals Δλ=0.5nm. The linear concentration range were 1-20 μg.mL-1 for all, with correlation coefficient (R2) and root mean squares error for the calibration (RMSE) for FURO, CARB, DIAZ, and CARV were 0.9996, 0.9998, 0.9997, 0.9997, and 0.1128, 0.1292, 0.1868,0.1562 respectively for PLS-1, and for PLS-2 were 0.9995, 0.9999, 0.9997, 0.9998, and 0.1127, 0.