Background: Plasma-activated water (PAW) is considered one of the emerging strategies that has been highlighted recently in the food industry for microbial decontamination and mycotoxin detoxification, due to its unique provisional characteristics. Aim: The effectiveness of PAW for aflatoxin B1 (AFB1), ochratoxin A (OTA), and fumonisin B1 (FB1) detoxification in naturally contaminated poultry feeds with its impacts on the feed quality were inspected. Methods: PAW-30 and PAW-60 were utilized for feed treatment for six time durations (5, 10, 15, 20, 40 and 60 min) each. The alterations in the physicochemical properties of PAW after different time durations of plasma inducement and treatment with and without feed samples were monit

In this work magnetite/geopolymer composite (MGP) were synthesized using a chemical co-precipitation technique. The synthesized materials were characterized using several techniques such as: “X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), vibrating sample-magnetometer (VSM), field-emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), Brunauer–Emmett–Teller (BET) and Barrentt-Joyner-Halenda (BJH)” to determine the structure and morphology of the obtained material. The analysis indicated that metal oxide predominantly appeared at the shape of the spinel structure of magnetite, and that the presence of nano-magnetite had a substantial impact on the surface area and pore st

Abstract

This work involves studying corrosion resistance of AA 6061T6 butt welded joints using Two different welding processes, tungsten inert gas (TIG) and a solid state welding process known as friction stir welding, TIG welding process carried out by using Rolled sheet of thickness6mm to obtain a weld joint with dimension of (100, 50, 5) mm using ER4043 DE (Al Si₅) as filler metal and argon as shielding gas, while Friction stir welding process carried out using CNC milling machine with a tool of rotational speed 1000 rpm and welding speed of 50mm/min to obtain the same butt joint dimensions. Also one of weld joint in the same dimensions subjected to synergistic weld

THE Schiff base reaction played an important role of the condensation reaction between 2-aminophenol and Glyoxylic acid in the presence of calculated amounts of KOH as a catalyst. The reaction has been carried out in ethanol under reflux and stirring condition for 3.5 hrs. All syntheses were carried out under hydrogen gas forming a new potassium (E)-1-hydroxy-2-(2-hydroxyphenylimino)ethanolate ligand type [NO2]. The ligand of the general formula K2[Mn(L2)] type and its Mnп complex K2[Mn(N2O4)] type, has been characterized by spectroscopic methods (F.T-I.R. and U.V-Vis.), elemental analysis (C.H.N) metal content, magnetic susceptibility measurement, Thin-layer chromatography (T.L.C), X-RD powder diffraction, 1H-NMR, 13C-NMR molar conductanc

New complexes of the type [ML2(H2O)2] ,[FeL2(H2O)Cl] and [VOL2] were M=Co(II),Ni(II) and Cu(II) ,L=4-(2-methyl-4-oxoquinazoline-3(4H)-yl) benzoic acid were synthesized and characterized by element analysis, magnetic susceptibility ,molar conductance ,FT-IR and UV-visible. The studies indicate that the L acts as doubly monodentate bridge for metal ions and form mononuclear complexes. The complexes are found to be octahedral except V(IV) complex is square pyrimde shape . The structural geometries of compounds were also suggested in gas phase by theoretical treatments, using Hyper chem-6 program for the molecular mechanics and semi-empirical calculations, addition heat of formation(?Hf ?) and binding energy (?Eb)for the free ligan

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

        In this paper, an estimate has been made for parameters and the reliability function for Transmuted power function (TPF) distribution through using some estimation methods as proposed new technique for white, percentile, least square, weighted least square and modification moment methods. A simulation was used to generate random data that follow the (TPF) distribution on three experiments (E₁ , E₂ , E₃)  of the real values of the parameters, and with sample size (n=10,25,50 and 100) and iteration samples (N=1000), and taking reliability times (0< t < 0) . Comparisons have been made between the obtained results from the estimators using mean square error (MSE). The results showed the