􀀤􀁅􀁖􀁗􀁕􀁄􀁆􀁗􀀑􀀃􀀬􀁑􀀃􀁗􀁋􀁌􀁖􀀃􀁕􀁈􀁖􀁈􀁄􀁕􀁆􀁋􀀏􀀃􀀤􀁊􀀤􀁏􀀔􀀐􀁛􀀬􀁑􀁛􀀶􀁈􀀕􀀃􀀋􀀤􀀤􀀬􀀶􀀌􀀃􀁆􀁒􀁐􀁓􀁒􀁘􀁑􀁇􀀃􀁄􀁏􀁏􀁒􀁜􀁖􀀃􀁓􀁕􀁈􀁓􀁄􀁕􀁈􀁇􀀃􀁉􀁒􀁕􀀃􀁇􀁌􀁉􀁉􀁈􀁕􀁈􀁑􀁗􀀃􀁛􀀃􀀋􀀓􀀑􀀖􀀏􀀃􀀓􀀑􀀙􀀃􀁄􀁑􀁇􀀃􀀓􀀑􀀜􀀌􀀃􀁅􀁜􀀃􀁐􀁈􀁏􀁗􀁌􀁑􀁊􀀃 􀁗􀁋􀁈􀁐􀀃 􀁌􀁑􀀃 􀁄􀁑􀀃 􀁈􀁙􀁄􀁆􀁘􀁄􀁗􀁈􀁇􀀃 􀁔􀁘􀁄􀁕􀁗􀁝􀀃 􀁗􀁘􀁅􀁈􀀃 􀀋􀀕􀀑􀀘􀀍􀀔􀀓􀀐􀀖􀀃 􀁗􀁒􀁕􀁕􀀌􀀑􀀃 􀀤􀀤􀀬􀀶􀀃 􀁚􀁌􀁗􀁋􀀃 􀁇􀁌􀁉􀁉

     The main parameters and methods influencing the removal of Gentian Violet (GV) dye from aqueous media were investigated using a stachy plant in this study. The surface of the stachy plant was determined using FTIR spectra. Adsorption is influenced by the adsorbent's characteristic groups. The research took into account the usual conditions for GV dye adsorption by the stachy plant, such as the impact of contact time. Mass dosage , after 0.3 g the amount of adsorbed dye declines. Study pH and ionic strength, the results obtained showed that at pH 3 the largest adsorption of (GV) was seen, while at pH 9, the lowest adsorption was observed  at 298 K, the adsorption kinetics and equilibrium constants were achieved, and the equilibr

The extraction of Cupressus sempervirens L. or cypress essential oil was studied in this paper. This cypress oil was extracted by using the hydro-distillation method, using a clevenger apparatus. Cupressus sempervirens L. leaves were collected from Hit city in Al-Anbar province – Iraq. The influences of three important parameters on the process of oil extraction; water which used as a solvent to the solid ratio (5:1 and 14:1 (ml solvent/g plant), temperature (30 to 100 °C) and processing time, were examined to obtain the best processing conditions to achieve the maximum yield of the essential oil. Also, the mathematical model was described to calculate the mass transfer coefficient. Therefore, the best conditions, that were obtained in

A particulate polymer composite material was prepared by reinforcing with the Aluminum Oxide (Al₂O₃) or Aluminum (Al) metallic particles with a particle size of (30) µm to an unsaturated Polyester Resin with a weight fraction of (5%, 10%, 15%, 20%).

Tensile test results showed the maximum value of elastic modulus reached (2400MPa.)  in the case of reinforcing with (Al) particles with weight fraction (20%) and (1500 MPa.)  in the case of reinforcing with (Al₂O₃) particles of the same weight fraction.

  When the impact and the flexural strength tests were done, the results showed that flexural strength (F.S), maximum shear stress (τ_max), impact strength

The composites were manufactured and study the effect of addition of filler (nanoparticles SiO2 treated with silane) at different weight ratios (1, 2, 3, 4 and 5) %, on electrical, mechanical and thermal properties. Materials were mixed with each other using an ultrasound, and then pour the mixture into the molds to suit all measurements. The electrical characteristics were studied within a range of frequencies (50-1M) Hz at room temperature, where the best results were shown at the fill ratio (1%), and thermal properties at (X=3 %), the mechanical properties at the filler ratio (2%).

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

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This