The work involves synthesis of new Schiff bases ([V] a, b and [VI] a, b), pyrazoles [VII] a, b and pyrazolines [VIII] a, b derivatives containing isoxazoline unit starting with chalcones. 4-bromoacetophenone was reacted with 4-hydroxybenzaldehyde or 4-hydroxyacetophenone was reacted with 4-bromobenzaldehyde in basic medium to give chalcone by Claisen-Schemidt reaction. The chalcons [I] a, b was reacted with hydroxylamine hydrochloride to form isoxazolines [II] a, b. which were reacted with ethyl chloro acetate in basic medium to get ester compounds [III] a, b. The condensation new ester [III] a, b with hydrazine hydrate80% yieldedacid hydrazide [IV] a, b. The later compound refluxing with 4-substituted benzaldehyde in dry benzene to give Sc

A new series of Fe (III) , Co (II) , Ni (II) and Cu (II) complexes of the Schiff base, 5 (2-hydroxy benzylidine) -2-thio ether -1, 3, 4-thiadiazole were prepared and characterized .The imine behaves as a bidentate. The nature of bonding and the stereochemistry of the complexes were deduced from metal analyses, infrared, electronic spectra,magnetic susceptibility and conductivity measurements, an octahedral geometry was suggested for all complexes except the copper complex has a square planar geometry .preliminary in vitro tests for antimicrobial activity show that all the prepared compounds except iron complex display good activity to gram positive Staphelococcus aures and gram negative Escherchia coli.

Friction stir spot welding (FSSW) is a relatively new welding process that may have significant advantages compared to the fusion processes as follows joining of conventionally non-fusion weldable alloys, reduced distortion and improved mechanical properties of weldable alloys joints due to the pure solidstate joining of metals. In this paper, a three-dimensional model based on finite element analysis is used to study the thermal history in the spot-welding of aluminum alloy 2024. The model take place the thermomechanical property on the process of the welded metals. The thermal history and the evolution results with numerical model at the measured point in the friction stirred spot weld have a good matching, then the prediction of the t

 Abstract   

Lightweight materials is used in the sheet metal hydroforming process,  because it can be adapted to the manufacturing of complex structural components into a single body with high structural stiffness. Sheet hydroforming has been successfully developed in industry such as in the manufacturing of the components of automotive.The aim of this study is to simulate the experimental results ( such as the amount of pressure required to hydroforming process, stresses, and strains distribution)  with results  of finite element analyses (FEA)  (ANSYS 11)  for aluminum alloy (AA5652) sheets with  thickness (1.2mm) before heat treatm

study the effect of radiation microwave (MW) in inhibition the growth of some types of bacteria in a minced meat and barker were exposed to MW for different times included (0, 10, 20, 30 and 40) sec.The results showed a high inhibition rate for 40 sec, reached to 100%. It is the other side studied the effect of microwave radiation against four types of bacteria included (Staphylococcus aureus, Escherichia coli, Proteus mirabilis and Klebsiella spp), when were exposed to for (0, 5, 10, 20, 30 and 40) sec the inhibition ratio reached to 100% in each of the Proteus mirabilis and Klebsiella spp at 30 sec and Staphylococcus aureus and Escherichia coli at 40sec. using MW in the sterilization media, such as Nutrient agar, Macconkey agar and Man

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

This research involves the preparation of new ligands 1,1,2,2- tetrakis (sodium acetate thio)ethylene(L1) and 1,1,2- tris(sodiumacetatethio) ethylene(L2), through the reaction of disodium thioglycolate) with tetra chloro ethylene or tri chloro ethylene in (1:4) or (1:3) moler ratio . Homodinucliar complexes of general formlu [M2(L1)] and [M2(L2)ClH2O] , when M= Co(II), Ni(II), Cu (II) and Zn(II) also mono nuclear complexes of general formula [M(L2)] . The prepared complexes were characterized using spectral method (UV/Visible/ IR) , metal content analysis , magnetic and atomic measurements . The spectral and magnetic measurement indicats that some complexes have tetrahedral or square planar complexes environtment .