Low conversion copolymerization of N-vinyl-2-pyrrolidon M.W = (111.14) VP (monomer-1) has been conducted with acrylic acid AA and methymethacrylate MMA in ethanol at 70ºC , using Benzoyl peroxide BPO as initiator . The copolymer composition has been determined by elemental analysis. The monomer reactivity ratios have been calculated by the Kelen-Tudos and Finman-Ross graphical procedures . The derived reactivity ratios (r1 , r2 ) are : (0.51 , 4.85) for (VP / AA ) systems and (0.34 , 7.58) for (VP , MMA) systems , and found the reactivity ratios of the monomer AA , MMA is mor than the monomer VP in the copolymerization of (VP / AA) and (VP /MMA) systems respectly . The reactivity ratios values were used for microstructures calculation.

Fourteen morphologically varied Ricinus communis L. seeds were collected from different localities in Egypt, El-Sudan and Saudi Arabia. Seed morphology and ITS barcoding analysis were performed to assess their diversity and phylogenetic relationship. Sequence’s alignment of nrITS region from different accessions display high levels of genetic similarities. Cluster analysis could not group different accessions according to their geographical distribution. Nevertheless, the genetic barcodes are interestingly matched with the morphological features of the Ricinus seeds. In conclusion, seed morphology proved to be a valuable tool in evaluating biodiversity and phylogenetic relationship in plant species with different loca

DBNRHM Sami, International Journal of Research in Social Sciences and Humanities, 2020

The aim of the work is synthesis and characterization of new bidentate chalcone ligand type (NO):[(E)-1-(3-aminophenyl)-3-(4-chlorophenyl) prop-2-en-1-one] [H2L], from the reaction of 3-amino acetophenone with 4-chloro benzaldehyde to produce the ligand [H2L], the reaction was carried out in ethanol as a solvent under stirring. The prepared ligand [H2L] was characterized by FT-IR, UV-Vis spectroscopy, 1H, 13C-NMR spectra, Mass spectra, (C.H.N) and melting point. The complexes of ligand [H2L] were prepared with metal ion M(Π).Where M(Π) = (Mn ,Co ,Ni and Cu) at reflux ,using ethanol as a solvent and KOH as a base with molecular formula [M (H2L)2] +2 where: H2L= (C15H12NOCl). All the complexes were characterized by spectroscopic met

Objective(s): To determine the quality of life for adults with a chronic obstructive pulmonary disease.
Methodology: A descriptive study was carried out on (80) patients with a chronic obstructive pulmonary disease from
December 2008 through October 2009 with special inclusion criteria (adult paƟents from 18 years and above exclude
the patients who suffer complication related of disease and from psychological problems and other chronic illnesses.
The data were analyzed through the application of descriptive data analysis approach and inferential data approach.
Result: The study indicated that the determination of QoL for COPD depended on the level of effect .The grades
according to R.S are: "high" effect of disease in

Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c