A novel, safe and efficient method was developed to encapsulate a blend of essential oils (EOs) into biodegradable nanoparticles (NPs). The biodegradable and biocompatible nanoparticles were made from chitosan (CH) and lecithin (LE) . The quality of the essential oils was verified using gas chromatography/mass spectrometry (GC/MS). The synthesis of nanoparticles included emulsification, followed by sonication, homogenization, and extrusion. Transmission electron microscopy (TEM) indicated that the nanoparticles were spherical in shape with sizes ranging from 25 to 70 nm, while dynamic light scattering (DLS) showed high negative zeta potentials. The stability of the final formula was evaluated in gastric and intes

Background: Whey protein is the green-yellow colored, liquid portion of the milk, and it is also called the cheese serum, it is obtained after the separation of curd, during the coagulation of the milk. It contains a considerable amount of α-helix pattern with an evenly distributed hydrophobic and hydrophilic as well as basic and acidic amino acids along with their polypeptide chain. The major whey protein constituents include β-lactoglobulin (β-LG),α-lactalbumin (α-LA), immunoglobulins (IG), bovine serum albumin (BSA), bovine lactoperoxidase (LP), bovine lactoferrin (BLF) and minor amounts of a glycol macro peptide (GMP). Osseointegration can be defined as a process that is immune driven which leads to the formatio

     Widespread COVID-19 infections have sparked global attempts to contain the virus and eradicate it. Most researchers utilize machine learning (ML) algorithms to predict this virus. However, researchers face challenges, such as selecting the appropriate parameters and the best algorithm to achieve an accurate prediction. Therefore, an expert data scientist is needed. To overcome the need for data scientists and because some researchers have limited professionalism in data analysis, this study concerns developing a COVID-19 detection system using automated ML (AutoML) tools to detect infected patients. A blood test dataset that has 111 variables and 5644 cases was used. The model is built with three experiments using Python's Auto-

This study includes the preparation of the ferrite nano ferrite Cu_xAl_0.3-XNi_0.7Fe₂O₄ (where: x = 0, 0.05, 0.1, 0.15, 0.2, 0.25, 0.3) M using the auto combustion method (sol-gel), and citric acid was used as fuel for auto combustion. The ferrite samples were checked by X-ray diffraction (XRD), Field Emission Scanning Electron Microscopes (FE-SEM), and energy dispersive X-ray analyzer (EDX). They showed that the prepared compound has a face-centered cubic structure (FCC). The lattice constant increases with an increase in the percentage of doping of the copper ions, and a decrease for the aluminum ion and that the compound is porous and its grains are spherical, and there are no other

Nanocrystal-ZnS-loaded graphene was synthesized by a facile co-precipitation route. The Graphene was affected on the characterization of ZnS which has been investigated. XRD results reveal that ZnS has a cubic system while the hexagonal structure has been observed by loading graphene during preparation ZnS. D.c-conductivity proves that ZnS and ZnS/Gr have semiconductor behavior. The sensing properties of ZnS/Gr against NO₂ gas were investigated as a function of operating temperature and time under optimal condition. The sensitivity, response time and recovery time were calculated with different operating temperatures (100, 150, 200)^oC.

The conjugate coefficient optimal is the very establishment of a variety of  conjugate gradient methods. This paper proposes a new class coefficient of conjugate gradient (CG) methods for impulse noise removal, which is based on the quadratic model. Our proposed method ensures descent independent of the accuracy of the line search and it is globally convergent under some conditions, Numerical experiments are also presented for the impulse noise removal in images.

In this work a study was made in centrifugal fan blower to investigate the effect of impeller blade design on sound pressure level (SPL). Shroud and unshroud impeller of nine blades are used. The sound generation from flow inside the test rig at different positions was displayed by using spectral analyzer. The experiments were carried out in anechoic chamber with small holes in its walls, under ambient condition about (25-27) C ° to avoid the effect of temperature on the sound pressure level. The results showed that (SPL) decreased with the increase of distance from the source about (3-4)dB when distance varied about (0.8-1.06)m, and the (SPL) decreased with the decrease of velocity about (8-12)dB when velocity varied between (13000-260

This study aims to explain the role of green target costing technique in improving the relationship with suppliers in a sample of industrial companies listed on the Iraq Stock Exchange. The descriptive analytical approach was used, where a questionnaire was designed that included a set of questions that were directed to a sample of 84 individuals including production managers, finance managers, quality managers, and purchasing managers in these companies. The study uses some statistical analyzes such as correlation analysis and regression analysis to analyze the questionnaires. The study finds a positive impact of the green target costing technique on improving the relationship with suppliers. The results indicate that the relation