Background: Dentin removed during root canal system instrumentation for creating adequate geometry for the canal and cleaning the canal. A new instrument had been marketed with the aim of optimum shaping of all parts of the canal system, however, no information present about the amount of dentin removal compared to conventional rotary system. This study investigated the amount of dentin removal when the canal instrumented by SAF compared with ProTaper by using high resolution computed tomography (micro CT). Materials and Methods: Twenty extracted single canalled teeth were utilized for this study; and randomly divided into 2 groups. In the first group, the root canals were prepared by using protaper rotary system till F2 and the root canal

Biosorpion of lead (Pb), Cadmium (Cd) and Nickl(Ni) by dried biomass of Chara sp. for sample of BMP was used as alternative approach of conventional method. The range of removal percentages was between 92-97%, 70-98.7% and 46.6-96.6% for Pb, Cd and Ni respectively at 3h.Treatment time, with 300-500 mg dried weight from Chara sp. powder at pH 4, with 60 rpm at shaker. FTIR analysis showed the active groups which are responsible for sequestration of heavy metals represented by carboxyl, hydroxyl alkyl, amine and amide. The Biosorption equilibrium experiment for elements showed that the highest sorption percentage for three elements was, Pb 96.6% after 30 minute, for Cd was 100% after 15 minute and 40% to Ni after 75 minute, while the biosorp

         A new method for the determination of the drug cefalexin in some Pharmaceuticals using (UV-Vis) and  indirect Flame Atomic Absorption Spectrophotometer (FAAS) , Fe III should forms a chelating complex with cefalexin (CEX –Fe III) at pH (1-8) and the best pH for the formation of (CEX –Fe III) chelating complex was (2) .The complex extracted with Methanol  and  Dimethy-Sulphoxide .The mole-ratio method has been used to determine the structure of chelate (CEX - Fe III) and found to be 2:1 LM ( Ligand : Metal.) .

Keywords : Cefalexin , chelating complex.

Background: Selenium-73 with half- life of 7.15 hour emits β⁺ in nature and has six stable isotopes which are ( ⁷⁴Se,⁷⁶Se,⁷⁷Se,⁷⁸Se,⁸⁰Se and ⁸²Se ). Selenium-73 has many applications in technology and radioselenium compounds of metallic have found various applications in medicine.

Objective:  To make a comparison between different reactions that produced cross sections of Se-73 radioisotopes.

Subjects and methods: The feasibility of the production of Selenium -73 via various nuclear reactions was investigated. Excitation functions of ⁷³Se production by the re

ZnO nanostructures were synthesized by hydrothermal method at different temperatures and growth times. The effect of increasing the temperature on structural and optical properties of ZnO were analyzed and discussed. The prepared ZnO nanostructures were characterized by X-ray diffraction (XRD), UV–Vis. absorption spectroscopy (UV–Vis.), Photoluminescence (PL), and scanning electron microscopy (SEM). In this work, hexagonal crystal structure prepared ZnO nanostructures was observed using X-ray diffraction (XRD) and the average crystallite size equal 14.7 and 23.8 nm for samples synthesized at growth time 7 and 8 hours respectively. A nanotubes-shaped surface morphology was found using scanning electron microscopy (SEM). The optic

In this paper we use Bernstein polynomials for deriving the modified Simpson's 3/8 , and the composite modified Simpson's 3/8 to solve one dimensional linear Volterra integral equations of the second kind , and we find that the solution computed by this procedure is very close to exact solution.

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This