Surfaces quality is one of the most specified customer requirements for machine parts. The major indication of surfaces quality on machined parts is surface roughness. The research aim is to study the cutting conditions and their effects on the surface roughness. This paper utilizes regression models to predict surface roughness over the machining time for variety of cutting conditions in turning. In the experimental part for turning, different types of materials (Aluminum alloy, Copper alloy, and Gray cast iron) were considered with different cutting speed ( ) and feed rate ( ). A mathematical Model depending on statistical-mathematical method between surface roughness (Rz ) and cutting condition ( , ) were derived, for the three materials. The matrix of test conditions included cutting speeds of the 16, 30, 45 and 60 m/min, feed rates of 0.17, 0.35 and 0.7 mm/rev while the depth of cut has been kept constant. The effect of cutting parameters on surface roughness is evaluated and the optimum cutting condition for minimizing the surface roughness is determined. Mathematical model has been established between the cutting conditions and surface roughness using regression. The predicted values and measured values are fairly close, which indicates that the developed model can be effectively used to predict the surface roughness in the turning machining. As the results of this work, the mathematical models were used in predicting surface roughness, can be used in CAD-CAM manufacturing systems, this mathematical model helps engineer to reduce the efforts. Mathematical models shows that the decreasing in the feed rate resulted in better surface roughness and increasing cutting speed resulted in better surface roughness. The goal of this work is to identify a relationship between experimental results and theoretical model, and study the proper process values for machining, to increasing the rates for raising the quality (better surface roughness).
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused enormous issues worldwide and is the most infectious pandemic. This study included 50 subjects (evenly distributed between sexes) and their range of ages starting from 2 to 67 years. According to the study's result, the ages and genders of subjects include susceptibility to COVID-19. Males were found to be more infected than females, and the ages of 36 to 67 were more common than other age ranges. Also, BMI calculations revealed that male patients with COVID-19 have the highest percentage of obesity. The clinical parameter results have been found serum C‐reactive protein (CRP) as an essential indicator that changes significantly in infection with COVID‐19 an
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The study of the distribution of major oxides and heavy metals in some plants collecting and analyzing eighteen plant samples of vegetables including carrot, onion, eggplant, cucumber, and okra obtained from Abu Ghraib land located about 20 km west of Baghdad, Iraq. Eighteen plant samples of vegetables,.Heavy metals can have a severe impact if released into the environment, even in trace quantities. These can enter the food chain from aquatic and agricultural ecosystems and indirectly threaten human health.. Trace elements and oxides of As, Cd, Co, Cr, Cu, Mn, Mo, Ni, Pb, Se, Th, U, V, and Zn were measured in plant samples using an X-Ray Fluorescence Instrument (XRF). TEs analyses of vegetables were performed in the Iraqi German Lab
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A laboratory experiment was carried out at the College of Agriculture University of Baghdad in 2017. The aim was to improve the anatomical and physiological traits of broad bean seedling under salt stress by soaking it in salicylic acid. The concentrations of salicylic acid were 0, 10, and 20 mg L-1 and the electrical conductivity levels were 0, 3, and 6 dS m-1. The complete randomized design was used with four replications. The increasing of salicylic acid concentration up to 10 mg L-1 led to increasing the stem cortex thickness, stem vascular bundles thickness, and root cortex thickness significantly by (34.9,36.7,and 55 μm) respectively, while the treatment of 20 mg L-1 led to decreasing these traits by (28.2, 27.8, and 48.1 μm), compa
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There is currently a pressing need to create an electro-analytical approach capable of detecting and monitoring genosensors in a highly sensitive, specific, and selective way. In this work, Functionalized Multiwall Carbon Nanotubes, Graphene, Polypyrrole, and gold nanoparticles nanocomposite (f-MWCNTs-GR-PPy-AuNP) were effectively deposited on the surface of the ITO electrode using a drop-casting process to modify it. The structural, morphological, and optical analysis of the modified ITO electrodes was carried out at room temperature using X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM) images, atomic force microscopy (AFM) and Fourier transform infrared (FTIR) spectra. Cyclic voltammetry (CV) and electrochemi
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