The objective of study was determining the most prevalent Salmonella spp. and their antimicrobial susceptibility in broilers and laying chickens and their feed and drinking water in five chicken farms in Karbala, Iraq over the period from August to October 2020. A total of 289 samples, including 217 cloaca swabs, 46 water and 26 feed samples were collected. Salmonella spp. was identified firstly by routine diagnostic methods, followed by applying the API 20E kit, the Vitek2 system, and serology. There was significant differences in Salmonella prevalence among different types of samples, mainly cloaca swabs reported a high isolation rate (21.7%). In contrast, feed samples were completely free of contamination. The highest rate of isolation w

In this study, novel Schiff base complexes with Zn(II) and Co(II) ions were successfully synthesized. The malonic acid dihydrazide was converted into the Schiff base ligand by combining it with 1-hydroxy-2-naphthaldehyde, and the last step required reacting it with the appropriate metal(II) chloride to produce pure target complexes. The generated complexes were thoroughly characterized using FTIR, 1H-NMR, 13C-NMR, GC-mass, and UV-Vis spectroscopies. In order to photo-stabilize polystyrene (PS) and reduce the photodegradation of its polymeric chains, these chemicals have been used in this work. The efficiency of the generated complexes as photo-stabilizers was evaluated using a variety of techniques, including FTIR, weight loss, visc

Abstract

This Research aims for harnessing critical and innovative thinking approaches besides innovative problem solving tools in pursuing continual quality improvement initiatives for the benefit of achieving operations results effectively in water treatment plants in Baghdad Water Authority. Case study has been used in fulfilling this research in the sadr city water treatment plant, which was chosen as a study sample as it facilitates describing and analyzing its current operational situation, collecting and analyzing its own data, in order to get its own desired improvement opportunity be done. Many statistical means and visual thinking promoting methods has been used to fulfill research task.

Polyacrylamide Solutions of different concentrations (0.2, 0.4, 0.6, 0.8, 1.0 %) of Ag nanoparticles and ZnO nanoparticles were prepared, the viscosities and surface tension were measured for all solutions, where measurements indicated an increase in these properties with increased concentration, where the relative viscosity of polyacrylamide/zinc nanoparticles increased from 1.275 to 2.243, and the relative viscosity of polyacrylamide/silver nanoparticles increased from 1.178 to 1.934. Viscosity is significant parameters during electrospinning process. While the surface tension of the polyacrylamide/zinc nanoparticles has changed from 0.0343 Nm-1 to .0.0.0 Nm-1 and changed from .0.000Nm-1 to.0.0.0 Nm-1. Also the constants KH and KK were

A novel ligand, (E)-5-((2-hydroxy-4,6-dimethylphenyl)diazenyl)-2,3-dihydrophthalazine-1,4- dione, was synthesized through the reaction of 3,5-dimethylphenol with the diazonium salt of 5-amino-2,3-dihydrophthalazine-1,4-dione. The ligand underwent characterization through the utilization of diverse spectroscopic methods, including UV-Vis, FT-IR, 13C, and 1H-NMR, alongside Mass spectroscopy and micro elemental analysis (Carbon, Hydrogen, Nitrogen, and Oxygen). Metal chelates of transition metals were prepared and analyzed using elemental analysis, mass spectra, atomic absorption, UV-Vis, FT-IR spectral analysis, as well as conductivity and magnetic measurements. The investigation into the compounds’ nature was conducted by utilizing mole r

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