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

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

In this study, a new adsorbent derived from sunflower husk powder and coated in CuO nanoparticles (CSFH) was investigated to evaluate the simultaneous adsorption of Levofloxacin (LEV), Meropenem (MER), and Tetracycline (TEC) from an aqueous solution. Significant improvements in the adsorption capacity of the sunflower husk were identified after the powder particles had been coated in CuO nanoparticles. Kinetic data were correlated using a pseudo-second-order model, and was successful for the three antibiotics. Moreover, high compatibility was identified between the LEV, MER, and TEC, isotherm data, and the Langmuir model, which produced a better fit to suit the isotherm curves. In addition, the spontaneous and exothermic nature of the adsor

Some genetic factors are not only involved in some autoimmune diseases but also interfere with their treatment, Such as Crohn's disease (CD), Rheumatoid Arthritis (RA), ankylosing spondylitis (AS), and psoriasis (PS). Tumor Necrosis Factor (TNF) is a most important pro-inflammatory cytokine, which has been recognized as a main factor that participates in the pathogenesis and development of autoimmune disorders. Therefore, TNF could be a prospective target for treating these disorders, and many anti-TNF were developed to treat these disorders. Although the high efficacy of many anti-TNF biologic medications, the Patients' clinical responses to the autoimmune treatment showed significant heterogeneity. Two types of TNF receptor (TNFR); 1 an

All the prepared metal complexes of Pt (IV), Au(III), Rh (III), Co (II) and V(IV) with new ligand sodium [5-(p-nitro phenyl)-/4-phenyl-1,2,4-triazole-3-dithiocarbamato hydrazide] (TRZ.DTC) have been synthesized and characterized in solid state by using flame atomic absorption, elemental analysis C.H.N.S, FT-IR ,UV-Vis Spectroscopy, conductivity and magnetic susceptibility measurements. The nature of the complexes formed in ethanolic solution has been studied following the molar ratio method also was studied stability constant and found to be stable in molar ratio1:1 of VL (IV) and CoL(II) while Pt(IV), Au(III) and Rh(III) complexes stable in molar ratio 1:2 as well as the molar absorptivity for these complexes were calculated. From the prev

The effects of essential oilNigella sativa and Menthawas study on the chemical, microbial and sensory properties for soft white cheese that produced from it during storage at 0, 7 and 14 days .The results show significantly percent decrease in moisture for all samplesand maximum decrease was at the latest storage period for all them .The reduced in moisture was accompanied with increase in percentage of protein and fat during of storage period for all samples.
The control sample showed increased in bacterial logarithmic for total count bacterial, coliform, Staphylococcus aureus, proteolytic bacteria, lipolytic bacteria and mold and yeasts during of storage period , the highest results showed at the latest storage period 14days, it w