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-

Manufacturing industry is constantly looking for ways to improve the efficiency of production processes so as to lower production costs, maintain product quality, and improve production planning. This study aims to provide an integrated optimization and forecasting framework that combines Cutting Optimization Pro5, linear programming, and an Enhanced N-BEATS deep learning model to minimize material waste and manufacturing cost and to predict the number of production items with a price-reduction strategy. The real industrial case study is based on production and pricing data from the Akad factory of the General Company for Electrical and Electronic Products in Iraq for the period from 2014 to 2025, concerning the manufacture of 80 L

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.

The current study investigated the stability and the extraction efficiency of emulsion liquid membrane (ELM) for Abamectin pesticide removal from aqueous solution. The stability was investigated in terms of droplet emulsion size distribution and emulsion breakage percent. The proposed ELM included a mixture of corn oil and kerosene (1:1) as a diluent, Span 80 (sorbitan monooleate) as a surfactant and hydrochloric acid (HCl) as a stripping agent without utilizing a carrier agent. Parameters such as homogenizer speed, surfactant concentration, emulsification time and internal to organic volume ratio (I/O) were evaluated. Results show that the lower droplet size of 0.9 µm and higher stable emulsion in terms of breakage percent of 1.12 % were

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