The snthesis and characterization of cobalt(II), nickel(II), copper(II) and zinc(II) complexes of azo ligand 4-[(5-acetyl-2-aminophenyl)- diazenyl]-1,5-dimethyl-2-phenyl-1H-pyrazol-3(2H)-one derived from 4-aminoantipyrine and 4-aminoacetophenone are reported. The nature of the compounds have been studied followed by mole ratio and methods of continuous contrast, Beer′s law followed during a condensation rate (1 × 10-4 – 3 × 10-4 M). The analytical data showed that all the complexes are in 1:2 metal-ligand ratio. An octahedral geometry have been suggested for all the compounds and biological studies of all the complexes were evaluated against different types of antimicrobial strains.

Two series of bent core mesogen containing 1,2,4-traizole ring [X]a-e and [XI]a-e were synthesized by many steps starting from esterification of isophthalic acid with methanol to yield diester compound [I] which was converted to their acid hydrazide [II] and the acid hydrazide reacted with ammonium thiocyanate or phenyl isothiocyanate to yield compounds [III] and [IV] , respectively . Then cyclization by 4% NaOH to yielded 1,2,4 traizole-3- thiol compounds [V] and [VI], respectively, afterword adding hydrazine hydrate to yield compounds [VII] and [VIII] .These compounds condensated with different substituted aldehyde to give new Schiff bases[X]a-e and [XI]a-e,respectively. The synthesized compounds were characterized by melting points ,

2,2'-(1-(3,4-bis(carboxydichloromethoxy)-5-oxo-2,5-dihydrofuran-2-yl)ethane-1,2-diyl)bis(oxy)bis(2,2-dichloroacetic acid) a derivative of L-ascorbic acid was prepared by reaction of L-ascorbic acid with trichloroacetic acid (1:4) ratio, in the presence of potassium hydroxide. A series of new metal complexes of this ligand were prepared by a reaction with the chlorides of Cd(II), Co(II), Ni(II), Cu(II) and Zn(II). The new ligand and its complexes were identified by C.H.N., IR, UV-visible spectra, Thermogravimetric analysis (TGA), as well as 1H, 13C-NMR and Mass spectra for ligand L. The complexes were also identified by molar conductance, atomic absorption, magnetic susceptibility and X-ray diffraction for Cu (II) complex. FT-IR spectra

     In this paper, ZnO NPs were prepared using D.C high-voltage and high frequency with an output of 6 kHz at two different preparation times preparation (10,12) minutes. Transmission electron microscopy (TEM) with (FE-SEM) was used to examine the homogenous, compact, and dense surface of the zinc oxide nanoparticles created with apparent grain size determined by (XRD), XRD results explain that the increase of the preparation time from 10 minutes to 12-minute caused an increase in crystallite size. In addition, FE-SEM showed that the increase in the ZnO NPs cluster distribution with particle size increases with increasing the preparation time. AFM was also utilized to determine the degree of cooperation between the surfaces of the z

   A new nano-sized NiMo/TiO₂-γ-Al₂O₃ was prepared as a Hydrodesulphurization catalyst for Iraqi gas oil with sulfur content of 8980 ppm, supplied from Al-Dura Refinery. Sol-gel method was used to prepare TiO₂- γ-Al₂O₃ nano catalyst support with 64% TiO_2, 32% Al₂O₃, Ni-Mo/TiO-γ-Al₂O₃ catalyst was prepared under vacuum impregnation conditions to loading metals with percentage 3.8 wt.% and 14 wt.% for nickel and molybdenum respectively while the percentage for alumina, and titanium became 21.7, and 58.61 respectively. The synthesized TiO₂- γ-Al₂O₃ nanocomposites and Ni-Mo /TiO₂

Nowadays nanoparticles are used in many fields of life all over the world, and there are numerous ways to obtain them: chemical, physical and biological processes. In recent times, the biological method for the synthesis of nanoparticles associated with using plant extract is widely spread. Optimal conditions for synthesis of silver nanoparticles using aqueous seeds extract of Myristica fragrance were highlighted in this research, such as type of plant extract, weight of extracted plant material, volume ratio of plant extract to AgNO3 and temperature of reaction. The study proved that the optimal status for AgNPs synthesis by using 10 g of M. fragrance seeds powder were added to 100 mL boiled distilled water, then homogenized and filt

Guanine has a variety of roles in chemistry, from its basic function in the storing and transferring genetic information to its usages in synthetic chemistry and other fields. Because of its distinct structure and biological importance, it is a fundamental component of contemporary study in organic chemistry and molecular biology. In this review, we focused on covering the synthetic pathways of various derivatives of guanine from the year 2000 until the present. As a result of the guanine molecule containing multiple functional groups, this gives us the ability to prepare several guanines such as O6-alkylating guanines, O6-benzylguanines, 8-aza-O6-benzylguanines, 9-substituted guanines, guanine-azo derivatives, guanine Schiff bases, guanin

One of the important differences between multiwavelets and scalar wavelets is that each channel in the filter bank has a vector-valued input and a vector-valued output. A scalar-valued input signal must somehow be converted into a suitable vector-valued signal. This conversion is called preprocessing. Preprocessing is a mapping process which is done by a prefilter. A postfilter just does the opposite.

The most obvious way to get two input rows from a given signal is to repeat the signal. Two rows go into the multifilter bank. This procedure is called “Repeated Row” which introduces oversampling of the data by a factor of 2.

 For data compression, where one is trying to find compact transform representations for a

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc