The study involved preparing a new compound by combining between 2-hydroxybenzaldehyde and (Z)-3-hydrazineylideneindolin-2-one resulting in Schiff bases and metal ions: Mn(II), Co(II), Ni(II), Cu(II), and Zn(II) forming stable minerals-based-Schiff complexes. The formation of resulting Schiff bases is detected spectrally using LC-Mss which gave corresponding results with theoretical results, 1H-NMR proves the founding of N=CH signal, FT-IR indicates the occurrence of imine band and UV-VIs mean is proved the ligand formation. On the other hand, minerals-based-Schiff was characterized using the same spectral means that relied with ligand (Schiff bases). Those means gave satisfactory results and proved the suggested distinguishable geometries. Finally, and according to the antibiotic feature of Schiff bases and its minerals, we have also examined such character against (-Bacteria and +Bacteria) giving an acceptable inhibition efficiencies.
Due to its importance in physics and applied mathematics, the non-linear Sturm-Liouville problems
witnessed massive attention since 1960. A powerful Mathematical technique called the Newton-Kantorovich
method is applied in this work to one of the non-linear Sturm-Liouville problems. To the best of the authors’
knowledge, this technique of Newton-Kantorovich has never been applied before to solve the non-linear
Sturm-Liouville problems under consideration. Accordingly, the purpose of this work is to show that this
important specific kind of non-linear Sturm-Liouville differential equations problems can be solved by
applying the well-known Newton-Kantorovich method. Also, to show the efficiency of appl
The aim of this work is to calculate the one- electron expectation value of the electronic charge of atomic system Z=2,3….7 and we compare with He atom . the electronic density function D(r1) of He atom and like ions are evaluated . using Hartree –Fock wave.
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Rheumatoid arthritis is a chronic systemic inflammatory disease. Inflammation leads to joint damage and increases the risk of cardiovascular diseases. Neutrophil lymphocyte ratio (NLR) is a measure of inflammation in many diseases. Therefore, we aimed to evaluate the usefulness of NLR to detect inflammation in RA, and its correlation to RA disease activity indices and some hematological parameters. A cross-sectional study involving 24 patients with active rheumatoid arthritis (RA) who are using MTX participated in this study. All patients were clinically evaluated using disease activity score of 28 joints (DAS28) and simplified disease activity index (SDAI), whereas functional disability was assessed by health assessment questionnaire di
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Background: Hyperthyroidism refers to overactive of thyroid gland leading to excessive synthesis of thyroid hormones and accelerated metabolism in the peripheral tissue. Objective: The aim of this study is to evaluate a new member of the IL-1 super family of cytokines interleukin-33(IL-33) levels in serum .in order to evaluate its utility as clinical bio marker of autoimmune disease (i.e. hyperthyroidism) Methods: The present study was conducted on 30 patients from the Iraqi female patients with hyperthyroidism attending Baghdad teaching hospital, in addition to 30 healthy controls. All subjects were (35-65) years old. Parameters measured in the sera of patients and healthy groups, were interleukin -33 (IL-33), Thyroxin (T4), Thyroxin (T3)
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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In this study, an unknown force function dependent on the space in the wave equation is investigated. Numerically wave equation splitting in two parts, part one using the finite-difference method (FDM). Part two using separating variables method. This is the continuation and changing technique for solving inverse problem part in (1,2). Instead, the boundary element method (BEM) in (1,2), the finite-difference method (FDM) has applied. Boundary data are in the role of overdetermination data. The second part of the problem is inverse and ill-posed, since small errors in the extra boundary data cause errors in the force solution. Zeroth order of Tikhonov regularization, and several parameters of regularization are employed to decrease error
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