This study has been focused on the detection of phenolic compound in aerial parts (stem and leaves)of the species belonging the genus Arabis L. A.Caucasica Willd, A.Sagittata (Bertol)DC, A.Aucheri Boiss, A.nova Vill of family cruciferou (Brassicaceae) which were collected during field trips of the districted of Iraq. Phenolic compounds have been identified by using High Performance Liquid Chromatography (HPLC). Nine standard compounds used for comparison five of them flavonoids ( Rutin, Quercetin, kaempferol, Luteolin and Apigenin) and the other phenolic acid ( Chlorogenic acid, Caffeic acid, Ferulic acid and Rosmarinic acid) , results showed that species vary in containing phenolic compound which can be counted as a taxonomic evidence s

Objective: To measure the effect of the pharmacist-led medication reconciliation service before hospital discharge on preventing potential medication errors. Methods: This behavioral interventional study took place in a public teaching hospital in Iraq between December 2022 and January 2023. It included inpatients who were taking four or more medications upon discharge from the internal medicine ward and the cardiac care unit. The researcher provided the patients with a medication reconciliation form and reconciliation form (including medication regimen and pharmacist instructions) before discharging them home. Any discrepancies between the patients’ understanding and the actual medication recommendations prescribed by the physici

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

In this paper, a numerical approximation for a time fractional one-dimensional bioheat equation (transfer paradigm) of temperature distribution in tissues is introduced. It deals with the Caputo fractional derivative with order for time fractional derivative and new mixed nonpolynomial spline for second order of space derivative. We also analyzed the convergence and stability by employing Von Neumann method for the present scheme.

Background:In this study,TiO2 layer was thermally grown as a diffusion barrier on CP Ti substrate prior to electrophoretic deposition of HA coatings, to improve the coating’s compatibility also macro and micro pores in nano Hydroxyapatite dual coatings were created and their effect on the bond strength between the bone and implant was evaluated. Materials and methods: Electrophoretic Deposition technique (EPD) was used to obtain coatings for each one of four types of Hydroxyapatite(HA)on CP Ti screws (micro HA, nano HA, dual nano HA with micro pores, dual nano HA with macro pores) where carbon particles used as fugitive material to be removed by thermal treatment to create porosity.For examination of the changes occurred on the subs

   The  objective of this study was to determine the concentration of trace element chromium(III) and thyroid peroxidase activity in human serum , and    to find a relationship between the concentration of chromium(III) and thyroid peroxidase activity in serum of patients with hypothyroidism, hyperthyroidism and healthy subjects. Serum thyroid peroxidase was measured by enzyme linked radioimmunoassay(ELISA) method and chromium determination was by atomic absorption spectrophotometer .Comparing the values of chromium concentration and thyroid peroxidase activity in both samples showed that there were significant positive correlations between chromium levels and thyroid peroxidase activity(P<0.01, r=0.11).