This study has three parts, the first one is the synthesis of a novel Schiff bases by the condensation of guanine or 9-[{2-hydroxyethoxy}methyl]-9H-guanine with variety aldehydes to yield four different bases as follows: (E)-2-((4-nitrobenzylidene)amino)-1,9-dihydro-6H-purin-6-one (S1), (E)-2-((4-methoxybenzylidene)amino)-1,9-dihydro-6H-purin-6-one (S2), (E)-2-((2-hydroxybenzylidene) amino)-9-((2-hydroxy ethoxy)methyl)-1,9-dihydro-6H-purin-6-one (S3), and (E)-2-(((9-((2-hydroxy ethoxy)methyl)-6-oxo-6,9-dihydro-1H-purin-2-yl)imino)methyl)benzoic acid (S4). Then, spectroscopic analyses such as Elemental Analysis, UV/VIS, Mass spectra, FTIR, 1H,13C-NMR were made to recognize these bases. In the second part, the ability of synthesized bases to undergo a charge transfer reaction was examined in an ethanolic solution at 28℃ with Iodine (I2) and 2,3-Dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) acceptors. The nonbonding interactions were studied using Benesi–Hildebrand method to estimate the stability parameters for all formed charge transfer complexes. The results of CT-energies and Gibbs free energies (ΔG˚) confirmed the stability of these complexes, and all complexes follow the Benesi–Hildebrand equation. The results showed that the DDQ-complexes have an affinity constant ranging from (916.6–24,400) mol−1.L higher than the affinity constant of I2-complexes which ranges from (428.5–7000) mol−1.L. Moreover, the KCT of S2 > S1 and KCT of S4 > S3 were as follows [1222.2 for S1-I2, 4333.3 for S1-DDQ, 2812.5 for S2-I2, 4800 for S2-DDQ] and [3809.5 for S3-I2, 12,200 for S3-DDQ, 7000 for S4-I2, 24,400 for S4-DDQ] due to the specific properties of each compound. The direct energy gap (Egdir) of each complex was also obtained by applying Tauc's method. Iodine complexes with S1, S2, S3, S4, as well as S1-DDQ displayed energy gaps equal to (5.14, 5.11, 4.61, 4.51, and 3.90) eV, respectively, and are likely to act as insulators. In contrast, the DDQ complexes of (S2/S3/S4) bases exhibited Egdir values at (2.85–2.24) electron volts which makes them suitable for semiconductor material usage. Finally, the third part of this work included a theoretical study using DFT/B3LYP/3-21G method to illustrate and prove the experimental findings, which were consistent with the theoretical results.
Copper nanoparticles (CuNPs) were prepared with different diameters by sonoelectrodeposition technique using Electrodeposition process coupled with high-power ultrasound horn (Sonoelectrodeposition). The particle diameter of the CuNPs was adjusted by varying CuSO4 solution acidity (pH) and current density. The morphology and structure of the CuNPs were examined by X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM). It was found that the size of the produced copper nanoparticles ranged between 22 to 77 nm, where the diameter of CuNPs increases with reduction the solution acidity from 0.5 to 1.5 pH and increasing the current density of the deposition from 100 to 400 nm. Finally the produced CuNPs were pressed to fabricate disc
... Show MoreThe paper presents the results of the research on the influence of the adjuvant concentration on the size of the drops produced by the spray nozzles of agricultural sprayers. For the tests, adjuvant Normaton with the composition of total nitrogen, amide nitrogen (N-NH2) and phosphorus pentoxide (P2O5) was used. The adjuvant was added to the water taken from the municipal water supply system of the city of Lublin. The tests were carried out for three concentrations, i.e. 75%, 100%, and 125% of the adjuvant concentration recommended by the manufacturer, and water without the adjuvant. The surface tension of water with adjuva
Coupling reaction of m-and p- amino acetop henone and p-amino benzoic acid with (LHistidine) gave the new bidentate azo ligands (L1, L2 and L3). The prepared ligands were identified by FT-IR, UV-Vis, 1HNMR and GC- mass sp ectroscopic technique. Treatment of the prepared ligands with the following metal ions (CoII, NiII, CuII, ZnII, CdII and HgII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M (L)2 Cl2]. The prepared complexes were characterized by using flame atomic absorption, FT-IR, UV-Vis and 1HNMR spectroscopic methods as well as magnetic susceptibility and conductivity measurements. Chloride ion content was also evaluated by (Mohr method). The nature of the com
... Show MoreBackground: 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
... 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
... Show MoreThis search includes the preparation of Schiff base ligand (SB) from condensation primary amine with vanillin. The new ligand was diagnosed by spectroscopic methods as Mass, NMR, CHN and FTIR. Ligand complexes were mixed from new (SB) and Anthranillic acid (A) with five metal (II) chlorides. The preparation and diagnosis were conducted by FTIR, CHN, UV-visible, molar conductivity, atomic absorption and magnetic moment. The octahedral geometrical shape of the complexes was proposed. The ligands and their new complexes were screened with two different types of bacteria.
Three scolopacids out of 150 are found infected with Haemoproteus scolopaci Galli-
Valerio 1929 and H. tringae n. sp. A detailed description of the new taxon is presented along
with a comparison of the diagnostic measurements between the two species.