n this work, a series of new nucleoside analogues (β-glucose liked to pyrazoline moiety) was synthesized. In the beginning, chalcone [1-3] was formed from the reaction of acetophenone and benzaldehyde derivatives in the presence of sodium hydroxide. Pyrazolines [4-6] were obtained from the reaction of the prepared chalcones and hydrazine hydrate in the presence of ethanol absolute. These pyrazolines were treated with β-glucose pentaacetate to afford a series of desirable protected nucleoside analogues [8-10]. After that hydrolysis of protected nuclioside analogues in sodium methoxide gave free nucleoside analogues [11-13]. These new formed compounds were diagnosed by 13C-NMR and 1H- NMR for some of them and FT-IR spectroscopy.
In this study, chemical oxidation was employed for the synthesis of polypyrrole (PPy) nanofiber. Furthermore, PPy has been subjected to treatment using nanoparticles of neodymium oxide (Nd2O3), which were produced and added in a certain ratio. The inquiry centered on the structural characteristics of the blend of polypyrrole and neodymium oxide after their combination. The investigation utilises X-ray diffraction (XRD), FTIR, and Field Emission Scanning Electron Microscopy (FE-SEM) for PPy, 10%, 30%, and 50% by volume of Nd2O3. According to the electrochemical tests, it has been noted that the nanocomposites exhibit a substantial amount of pseudocapacitive activity.
The new Schiff base (L) “4‐[(2,4‐dimethoxy‐benzylidene)‐amino]‐1,5‐dimethyl‐2‐phenyl‐1,2‐dihydro‐pyrazol‐3‐one” was synthesized from 2,4‐dimethoxy‐benzaldehyde and 4‐amino‐1,5‐dimethyl‐2‐phenyl‐1,2‐dihydropyrazol‐3‐one, and the geometry of Schiff base was characterized and determined by proton nuclear magnetic resonance (1H‐NMR), mass, Fourier transform infrared (FT‐IR), and ultraviolet‐visible (UV‐vis) spectroscopy. Schiff complexes of Ni(II), Pd(II), Pt(IV), Zn(II), Cd(II), and Mg(II) have been prepared by reaction of ion metals with as‐prepared Schiff base. The results showed that synthesized complexes offered 1:2 m
The physical and morphological characteristics of porous silicon (PS) synthesized via gas sensor was assessed by electrochemical etching for a Si wafer in diluted HF acid in water (1:4) at different etching times and different currents. The morphology for PS wafers by AFM show that the average pore diameter varies from 48.63 to 72.54 nm with increasing etching time from 5 to 15min and from 72.54 to 51.37nm with increasing current from 10 to 30 mA. From the study, it was found that the gas sensitivity of In2O3: CdO semiconductor, against NO2 gas, directly correlated to the nanoparticles size, and its sensitivity increases with increasing operating temperature.
Therapeutically and prophylactically using Microspheres containing doxycycline isolated from shell of shrimp. Low molecule weight poly lactic acid was prepared. In this study, Poly lactic acid (PLA)/ poly vinyl alcohol (PVA)/poly ethyleneglycol(PEG) loading doxycycline blend solutions was prepared. Also Poly lactic acid (PLA)-Tannin blend via solvent evaporation method was prepared. Microspheres of chitosan/gelatin microsphere loading doxycycline was prepared by emulsion crosslinking technique. Both microsphere and blends were characterized by Fourier transform infrared (FTIR) spectrophotometer. The FTIR spectra were shown distinguish bands. The in vitro release of doxcycline from its matrix at pH 7 was studied. The prophylactic
... Show MoreA survey of haemoproteids among the eight species of Iraq rallids were carried out in the
middle, south, and west of Iraq. Two haemoproteods were recorded, Haeomproteus porzanae
(Galli-Valerio, 1907) as a new record for Iraq and the new species H. baghdadensis described
from Fulica atra L. collected in the middle of Iraq.
New vision of Mr. Abdul Mahdi Al-Muttafiqi in the light of unpublished documents
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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