2-hydrazinylbenzo[d]thiazole compound [1] is produced from reaction of 2-mercapto-benzothiazole with hydrazine hydride in ethanol. Compound [1] reacted with maleic anhydride in DMF to produce (Z)-4-(2-(benzo[d] thiazol-2yl) hydrazinyl)-4-oxobut-2-enoic acid [compound (2)]. While the treatment of compound [2] with the ammonium persulfate (NH4)2S2O8 (as the initiator) in order to produce compound [3], then compound [3] reacted with thionyl chloride in benzene to produce compound [4], finally compound [4] reaction with various drugs: cephalexin, amoxicillin, sulfamethizole, elecoxib obtained polymers [5–8]. The structure of synthesized compounds identified by spectral data: fourier transform infrared (FTIR) and proton nuclear magnetic resonance (1HNMR) spectroscopy. The polymers [5–8] have been screened for their antibacterial activities against Staphylococcus aureus (G+), Escherichia coli (G-) and compared with the drug (amoxicillin). The anticancer activity (Hep G2 (human liver cancer cell line) of some prepared polymers were also studied.
A 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.
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 MoreAs one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord
... Show MoreExperienced organizations in recent years, significant challenges , especially with the spread of economic globalization, making it required to provide new and better through experience , creativity and innovation to achieve the quality and high-quality products of all kinds , in order to achieve the objectives of the study and to answer its questions tested the study in the woolen Industries sector in Baghdad . The study was applied to a sample of 30 people in the senior management and the middle and lower in the company (managers of sections , and managers of people , and managers of the units , and office managers ) and for the processing of data and information used several statistical methods and extracted result
... Show Moreخلاصة (استطاعت اليابان بعد الحرب العالمية الثانية ان تنهض من جديد، وان تحقق تجربة تحديث سياسي جعلها تشهد تبدلات جذرية من الفقر الى الغنى ومن سيطرة الحكم العسكري الى الدولة المنزوعة السلاح ومن التخلف الى التكنولوجيا الاكثر تطورا في العالم, ومن الانغلاق والعزلة وذهنية سكان الجزر الى الانفتاح على ثقافات عصر العولمة ووسائل اعلامها. فكيف يمكن الاستفادة من هذه التجربة الحديثة سياسيا بل وحتى اقت
... 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 MoreIn this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I
... 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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