Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

Herein, a biocomposite of crosslinked chitosan polyethylene glycol diglycidyl ether (CS-PEDGE), montmorillonite (MMT), and foodgrade algae (FGA) was successfully prepared by a hydrothermal technique. The resulting absorbent (CS-PEDGE/FGA/MMT) was assessed for its adsorption property with methyl violet 2B (MV 2B) a toxic cationic dye. The physicochemical properties of CS-EDGE/ FGA/MMT were assessed via various analytical techniques, including BET, Elemental analysis, pHpzc, and spectroscopy (FTIR, XRD, SEM-EDX). The influence of three adsorption variables, namely adsorbent dose (A: 0.02–0.1 g/100 mL), solution pH (B: 4–10), and contact time (C: 10–420 min) on the rate of MV 2B dye removal was examined using the Box-Behnken design (RSM-

Pressure ulcers are one of the most common hospital-acquired major conditions that occur in patients with mobility limitations and result in endangering patient safety, prolonging hospital stay, disability, and death. This study aims to examine the level of nurses’ practices and perceived barriers for preventing pressure ulcers among critically ill patients.

This study refers to the development and characterization of silver oxide nanoparticles obtained by X-ray diffraction, nanostructured silver oxide was used in order to calculate the micro strain and crystal size by Halder-Wagner method and by relying on X-ray diffraction diagram of the nonstructural silver oxide, where the results of the crystal size and the micro-strain were 4nm and 0.33 respectively. Other analysis techniques, such as the Size-strain plot, The X-ray diffraction study confirmed that the crystalline nature of silver oxide nanoparticles has a cubic structure. Through the X-ray diffraction results, the crystal size was calculated using Debye-Scherrer and Williamson-Hall methods. Halder-Wagner (HW), Size-strain plot, D