Background: Chemotherapeutic medication treatment for cancer is typically used in conjunction with other techniques as part of a routine regimen. It is well established that the capacity of different chemotherapeutic drugs to induce apoptosis is correlated with their anticancer efficacy. Quinazolinone-based drugs have demonstrated excellent responses from several cancer cell types. These substances have a lot of potential for use as building blocks in the creation of apoptosis inducers. Objective: To assess the new quinazolinone derivatives (M1 and M2) that were recently synthesized for their potential to halt wound healing and to use the acridine orange/propidium iodide (AO/PI) double stain to assess their capacity to induce apopto

To synthesize new hydrazone derivatives of naproxen with enhanced anti-inflammatory activity and devoid the ulcerogenic side effects. Hydrazones were synthesized by conjugation of naproxen hydrazide with seven natural and synthetic aldehyde and ketone by using glacial acetic acid as catalyst. The synthesis has been carried out following simple methodology in excellent isolated yields.The structure of the synthesized derivatives has been characterized by elemental microanalysis (CHN), FTIR Spectroscopy, and other physicochemical properties.The anti- inflammatory activity of the synthesized compounds was evaluated in vivo using the egg-white induced edema model in rats, and the results of the biological assay was found to be comparable to Nap

 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

In this research, cyclic compounds derived from 2- furfural mercaptan (oxazole, triazoles) were synthesized, and their biological efficacy was measured and compared with standard drugs. Also, their effectiveness as anti-oxidant was measured and compared with ascorbic acid as a standard substance. Some of the synthesized compounds were deduced with good efficacy. © 2021 Sami Publishing Company. All rights reserved

The synthesis of new substituted cobalt Phthalocyanine (CoPc) was carried out using starting materials Naphthalene-1,4,5, tetracarbonic acid dianhydride (NDI) employing dry process method. Metal oxides (MO) alloy of (60%Ni₃O₄ 40%-Co₃O₄ ) have been functionalized with multiwall carbon nanotubes (F-MWCNTs) to produce (F-MWCNTs/MO) nanocomposite (E2) and mixed with  CoPc to yield (F-MWCNT/CoPc/MO) (E3). These composites were investigated using different analytical and spectrophotometric methods such as ¹H-NMR (0-18 ppm), FTIR spectroscopy in the range of (400-4000cm-1), powder X-rays diffraction (PXRD, 2θ ^o = 10-80), Raman spectroscopy (0-4000 cm^-1), and UV-Visib

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

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