Background: The present work investigated the profile and biodiversity of the pathogenic streptococci species isolated from local and imported mozzarella soft cheese in Baghdad City from October 2022 to January 2023. The study aimed to examine the molecular characterization of 16Sr RNA gene in some streptococcus species isolates from mozzarella soft cheese in Baghdad city Methods: From 50 samples, 8 isolates in all were found and identified based on the VITEK, molecular, and sequencing of the 16SrRNA gene. The eight isolates represented Lactococcus cremoris. Streptococcus alactolyticus, Streptococcus sanguinis, and Streptococcus thoraltensis. The isolates were subjected to conventional PCR and electrophoresis to detect the 16SrRNA gene usi

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.

The new bidentate Schiff base ligand namely [(E)-N1-(4-methoxy benzylidene) benzene-1, 2-diamine] was prepared from condensation of 4-Methoxy benzaldehyde with O-Phenylene diamine at 1:1 molar ratio in ethanol as a solvent in presence of drops of 48% HBr. The structure of ligand (L) was characterized by, FT-IR, U.V-Vis., 1H-, 13C- NMR spectrophotometer, melting point and elemental microanalysis C.H.N. Metal complexes of the ligand (L) in general molecular formula [M(L)3], where M= Mn(II), Co(II), Ni(II),Cu(II) and Hg(II); L=(C14H14N2O) in ratio (1:3)(Metal:Ligand) were synthesized and characterized by Atomic absorption, FT- IR, U.V-Vis. spectra, molar conductivity, chloride content, melting point and magnetic susceptibility from the above d

Iron slag is a byproduct generated in huge quantities from recycled remnants of iron and steel factories; therefore, the possibility of using this waste in the removal of benzaldehyde from contaminated water offers an excellent topic in sustainability field. Results reveal that the removal efficiency was equal to 85% for the interaction of slag and water contaminated with benzaldehyde at the best operational conditions of 0.3 g/100 mL, 6, 180 min, and 250 rpm for the sorbent dosage, initial pH, agitation time, and speed, respectively with 300 mg/L initial concentration. The maximum uptake capacity of iron slag was 118.25 mg/g which was calculated by the Langmuir model. Physical sorption may be the major mechanism for the removal of

This paper is concerned with introducing and studying the new approximation operators based on a finite family of d. g. 'swhich are the core concept in this paper. In addition, we study generalization of some Pawlak's concepts and we offer generalize the definition of accuracy measure of approximations by using a finite family of d. g. 's.

Two homopolymeric and three copolymeric additives for base oil were synthesized using octyl acrylate (OA) and tert-butyl acrylamide (TBA) monomers. The two additives named P1 and P2 are the homopolymers of TBA and OA, respectively, whereas copolymeric additives named Co1, Co2, and Co3 were synthesized by varying the ratios of TBA:OA as 1:3, 3:1 and 1:1, respectively. The prepared polymers were characterized by Fourier Transform Infrared (FTIR). Based on the solubility of synthesized polymers in base oil and reactivity ratios of TBA/OA copolymer (0.222, 0.434) calculated by Fineman-Ross method, P2, Co1, Co2 and Co3 were selected to evaluate their performance as pour point depressant (PPD), viscosity improver (VII), and anticorrosion addit

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D