Several new derivatives of 1, 2, 4-triazoles linked to phthalimide moiety were synthesized through following multisteps. The first step involved preparation of 2, 2-diphthalimidyl ethanoic acid [2] via reaction of two moles of phthalimide with dichloroacetic acid. Treatment of the resulted imide with ethanol in the second step afforded 2, 2-diphthalimidyl ester [3] which inturn was introduced in reaction with hydrazine hydrate in the third step, producing the corresponding hydrazide derivative [4]. The synthesized hydazide was introduced in different synthetic paths including treatment with carbon disulfide in alkaline solution then with hydrazine hydrate to afford the new 1, 2, 4-triazole [10]. Reaction of compound [10] with different aldehydes produced a new Schiff base derivatives [11, 12]. Reaction of derivative [4] with different aldehydes produced a new derivatives [5-8]. All the synthesized compounds have been characterized by melting points, FTIR, 1HNMR (some of them) and mass spectroscopy of compound [2]. Derivatives [5, 6, 7, 10, 11, 12] were tested against inhibition of E-coli, staphyloccus aureus and were all found to be active. Schem1, 2 illustrated the reaction steps
In 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
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As 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
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The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita
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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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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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New two experiments of the three factors, in this study were constructed to investigate the effects, of the fixed variations to the box plot on subjects' judgments of the box lengths. These two experiments were constructed as an extension to the group B experiments, the ratio experiments the experiments with two variables carried out previously by Hussin, M.M. (1989, 2006, 2007). The first experiment box notch experiment, and the second experiment outlier values experiment. Subjects were asked to judge what percentage the shorter represented of the longer length in pairs of box lengths and give an estimate of percentage, one being a standard plot and the other being of a different box lengths and
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Abstract Ternary Silver Indium selenide Sulfur AgInSe1.8S0.2 in pure form and with a 0.2 ratio of Sulfur were fabricated via thermal evaporation under vacuum 3*10-6 torr on glasses substrates with a thickness of (550) nm. These films were investigated to understand their structural, optical, and Hall Characteristics. X-ray diffraction analysis was employed to examine the impact of varying Sulfur ratios on the structural properties. The results revealed that the AgInSe1.8S0.2 thin films in their pure form and with a 0.2 Sulfur ratio, both at room temperature and after annealing at 500 K, exhibited a polycrystalline nature with a tetragonal structure and a predominant orientation along the (112) plane, indicating an enhanced de
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The art of synthesis is one of the most important pillars in cinematic art, as the director combines cinematic shots to produce a third shot in the mind of the recipient by various methods such as mental synthesis, analogous synthesis, rhythm synthesis, parallel synthesis and repetitive synthesis, Repetitive synthesis is one of the most important techniques in cinematic montage. Through repetitive synthesis, the director is able to link the shots and scenes with each other, and this is what we see in the poetic imagery of Adnan Al-Sayegh when he links the visual images to each other, especially those images that manifest the manifestations of grief and misery following the misfortunes that befell in His homeland. This study follows the d
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Based on nonlinear self- diffraction technique, the nonlinear optical properties of thin slice of matter can be obtained. Here, nonlinear characterization of nano-fluids consist of hybrid Single Wall Carbon Nanotubes and Silver Nanoparticles (SWCNTs/Ag-NPs) dispersed in acetone at volume fraction of 6x10-6, 9x10-6, 18x10-6 have been investigated experimentally. Therefore, CW DPSS laser at 473 nm focused into a quartz cuvette contains the previous nano-fluid was utilized. The number of diffraction ring patterns (N) has been counted using Charge - Coupled- Device (CCD) camera and Pc with a certain software, in order to find the maximum change of refractive index ( of fluids. Our result show that the fraction volume of 18x10-6 is more nonli
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