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 .

The local resolving neighborhood  of a pair of vertices  for  and  is if there is a vertex  in a connected graph  where the distance from  to  is not equal to the distance from  to , or defined by . A local resolving function  of  is a real valued function   such that  for  and . The local fractional metric dimension of graph  denoted by , defined by  In this research, the author discusses about the local fractional metric dimension of comb product are two graphs, namely graph  and graph , where graph  is a connected graphs and graph  is a complate graph &

The research discussed the topic of the functional role of responsive materials in being elements of a functional transformation in the design of industrial products, based on the study of the structures of smart materials and their performance capabilities at the level of action and self-reaction that characterize this type of materials.

Basic features of responsive materials have been identified to be elements of self-functional insertion into the industrial product design, which contributes to raising the efficiency and functional capacity of the industrial product and enhancing the ability of products to perform self-acting interactions in the structural structure of the material structure of the product and its ability to res

The increased size of grayscale images or upscale plays a central role in various fields such as medicine, satellite imagery, and photography. This paper presents a technique for improving upscaling gray images using a new mixing wavelet generation by tensor product. The proposed technique employs a multi-resolution analysis provided by a new mixing wavelet transform algorithm to decompose the input image into different frequency components. After processing, the low-resolution input image is effectively transformed into a higher-resolution representation by adding a zeroes matrix. Discrete wavelets transform (Daubechies wavelet Haar) as a 2D matrix is used but is mixed using tensor product with another wavelet matrix’s size. MATLAB R2021

 Film condensation of steam on a vertical tube is investigated numerically and experimentally,   in the present work. A mathematical model was set based on the basic conservation laws of mass   and energy, Nusselts analysis of film condensation, and empirical equations available in the   literature. Then, a simulation program in FORTRAN language was developed which simulates the   film condensation of steam on a vertical tube. A complete steam tables subprogram was also   developed and incorporated with the main program. The experimental work was carried out using a   steam condensation test bench. The inlet and outlet cooling water temperatures, steam temperature   and pressure, tube surface temperature at center, and co

Chemical analysis for evaluation of Nigella sativa L. (black cumin) seeds showed a composition of Fat 39% ; Protein 28% ; Carbohydrate 21% ; Moisture 6% and Ash 4.5% . It was found that the black seed contains the following mineral element : Magnesium 0.26 gm /100gm seed ; Calcium 0.25 gm /100gm seed and Iron 25 ?g / gm /100gm seed ; zinc 4.51?g /gm /100gm seed and Copper 3.60 ?g /gm /100gm seed. The analysis also showed that mineral element I. e. ; lead ; Cobalt ; Nickel ; Chrom ; Cadmium and Aresenic are not present . It was found that the fat of the black seed contains the following fatty acids : Myristic 2.8%; Palmtic 16.6%; Stearic 0.8 % ; Oleic 13.79% ; Linoleic 64.2% and Arachidic 1.9% .

Density functional theory (DFT) with B3LYP level and 6-311G[Formula: see text] basis sets for light atoms like N and O and SDD basis sets for heavy atoms like Sn is used to examine the interaction of tin dioxide nanocrystals with nitrogen dioxide as a function of temperature from 273[Formula: see text]K to 373[Formula: see text]K through a Gaussian 09W software program. Gibbs free energy, enthalpy, and entropy of activation and reaction are calculated. The situation of transition of SnO₂ clusters toward nitrogen dioxide is investigated. According to the findings, the activation energy of SnO₂ clusters with nitrogen dioxide increases as the temperature rises (in negative value). Gauss view 0

The research dealt with the effect of Kut Barrage on the geomorphological processes and the natural environment system in the course of the Tigris between the cities of Al-Ahrar and Kut in central Iraq. It was clear from the research the contribution of Kut Barrage in changing the surface runoff system between the front and back of the barrage, as well as changing the type of processes and the prevailing geomorphic forms, as the sedimentation activates the front of the barrage and erosion at its back, which affected the change in the morphology of the river, sediment retention at the front of the barrage, the burial of the bottom and reducing the validity of the stream. This also affects the efficiency of the barrage’s work and coastal er

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D