Retainers have the potential to detrimentally impact periodontal health and contribute to tooth decay.

New metal ion complexes were synthesized with the general formula; K[PtLCl4], [ReLCl4] and K[ML(Cl)2] where M = Pd(II), Cd(II), Zn(II) and Hg(II), from the Azo ligand (HL) [2-Hydroxy-3-((5-mercapto-1,3,4-thiadiazol-2-yl)diazenyl)- 1-naphth aldehyde] (HL) the ligand was synthesized from (2-hydroxy-1- naphthaldehyde) and (5-amino-1,3,4-thiadiazole-2-thiol). The ligand and its metal complexes are characterized by phisco- chemical spectroscopic techniques (FT.IR, UV-Vis and Mass spectra, elemental analysis, molar conductivity, Atomic Absorption, Chloride contain and magnetic susceptibility). The spectral data suggest that the (HL) behaves as a bidentate ligand in all complexes. These studies revealed tetrahedral geometries for all metal complex

In this study, a packed bed was used to remove pathogenic bacteria from synthetic contaminated water. Two types of packing material substrates, sand and zeolite, were used. These substrates were coated with silver nanoparticles (AgNPs), which were prepared by decomposition of Ag ions from AgNO3 solution. The prepared coated packings were characterized using scanning electron microscopy, energy-dispersive X-ray spectroscopy and transmission electron microscopy. The packed column consisted of a PVC cylinder of 2 cm diameter and 20 cm in length. The column was packed with silver nanoparticlecoated substrates (sand or zeolite) at a depth of 10 cm. Four types of bacteria were studied: Escherichia coli, Shigella dysenteriae, Pseudomonas aerugi

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

Objective: The study aimed to determine the sources and level of job stress experienced by nurses who were
working in intensive care units, and to find-out the relationship between work-related stress and some variables
such as age, gender, educational level, marital status, and years of experience in cardiac surgical intensive care
unit.
Metl]odo]ogy: A descriptive study was conducted on nurses working in the cardiosurgical intensive care units in
Baghdad hospitals. The study sample was selected purposively and consisted of (60) nurses who were working
in cardiosurgical intensive care units in Baghdad city (Ibm Al-Betar Hospital for Cardiac Surgery, Ibn A1-Nafis
Hospital for Cardiovascular Diseases, and the Iraqi Ce