In this research we study a variance component model, Which is the one of the most important models widely used in the analysis of the data, this model is one type of a multilevel models, and it is considered as linear models , there are three types of linear variance component models ,Fixed effect of linear variance component model, Random effect of linear variance component model and Mixed effect of linear variance component model . In this paper we will examine the model of mixed effect of linear variance component model with one –way random effect ,and the mixed model is a mixture of fixed effect and random effect in the same model, where it contains the parameter (μ) and treatment effect (τ_i ) which  has

Six mixed ligand complexes were prepared from malonic acid (MA), nicotinic acid (NA), and 2-aminopyridine (AP) in a (1:1:1:1) molar ratio (M: MA: NA: AP.), using aqueous ethanol as a reaction medium. The prepared compounds were analyzed by flame atomic absorption, (C.H.N.) analysis, and FTIR, UV-Vis, and mass spectroscopy, as well as conductivity measurement and magnetic susceptibility studies. Based on the combined analytical data, the prepared complexes were proposed to adopt an octahedral geometry.   A urinary tract infection (UTI) is a bacterial infection that affects any part of the urinary tract.   The emergence of antibiotic-resistant bacteria and fungi has led to poor patient outcomes and limited treatment options, prompting int

Six mixed ligand complexes were prepared from malonic acid (MA), nicotinic acid (NA), and 2-aminopyridine (AP) in a (1:1:1:1) molar ratio (M: MA: NA: AP.), using aqueous ethanol as a reaction medium. The prepared compounds were analyzed by flame atomic absorption, (C.H.N.) analysis, and FTIR, UV-Vis, and mass spectroscopy, as well as conductivity measurement and magnetic susceptibility studies. Based on the combined analytical data, the prepared complexes were proposed to adopt an octahedral geometry.   A urinary tract infection (UTI) is a bacterial infection that affects any part of the urinary tract.   The emergence of antibiotic-resistant bacteria and fungi has led to poor patient outcomes and limited treatment options, promp

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

This study aimed to study the effect of Ziziphus spina christi Aqueous cold and Alcoholic leaves and fruits extracts on the growth and activities of the following types of bacteria :( Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Streptococcus pyogenes ). The results appeared outweigh the alcoholic extract of leaves and fruits of Sidr that prepared by saxholate extractor by addition of ethanol 95% significant superiority as compared with aqueous extract that prepared by using distilled water as was its influence inhibitor to the growth and effectiveness of bacteria , about the treatment of in-vivo to cause injury to these types of bacteria diagnosed laboratory mice and treated with alcoholic extract of the leaves o

Isolation of fungi was performed from February to July, 2019. One hundred clinical specimens were collected from King Abdullah Hospital (KAH) Bisha, Saudi Arabia. Samples were collected from twenty patients of different ages (30 - 70 years old) ten males and ten females. The samples were collected from patients with the two types of diabetics. Specimens included blood, hair, nail, oral swabs and skin.  Specimens were inoculated on Sabourauds Dextrose agar containing chloramphenicol. Thirteen fungal species were isolated and identified. The isolated species were: Aspergillus flavus, A. niger, A. terrus, A. nidulans, A. fumigatus, Candida albicans, C. krusei, C. parapsilosis, C. Tropicalis, Curvularia lunata, Fusarium solani, Penicill

Background: Strangles is a highly contagious equine respiratory disease caused by Streptococcus equi subsp. equi. It is a globally significant pathogen and one of the most common infectious agents in horses. In Iraq, no sequencing data on this pathogen are available, and only two molecular studies have been published to date. This study provides preliminary insights into strain diversity and provides a foundation for future large-scale investigations. Aim: This study aimed to investigate the molecular characteristics, identify SeM gene alleles, and perform a phylogenetic analysis of S. equi isolates from horses in Baghdad, Iraq. Methods: We analyzed 59 Streptococcus spp. isolates previously obtained from equine clinical sample

Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

The synthesized ligand (3-(2-amino-5-(3,4,5-tri-methoxybenzyl)pyrimidin-4-ylamino)-5,5-dimethylcyclohex-2-enone] [H1L1] was characterized via fourier transform infrared spectroscopy (FTIR), 1H, 13C – NMR, Mass spectra, (CHN analysis), UV-vis spectroscopic approaches. Analytical and spectroscopic techniques like chloride content, micro-analysis, magnetic susceptibility UV-visible, conductance, and FTIR spectra were used to identify mixed ligand complexes. Its (ML13ph) mixed ligand complexes [M= Co (II), Ni (II), Cu (II), Zn (II), and Cd (II); (H1L1) = β-enaminone ligand=L1 and (3ph) =3-aminophenol= L2]. The results demonstrate that the complexes are produced with a molar ratio of M: L1:L2 (1:1:1). To generate the appropriate compl