There is a great risk of cardiovascular disease (CVD) and vascular thrombosis in patients with End-Stage Renal Disease (ESRD). These patients exhibit numerous abnormalities in coagulation, fibrinolytic, inhibitory protein abnormalities in multiple levels. The study aimed to assess hypercoagulable changes by measuring the levels of antithrombin, plasma fibrinogen and FXII activity in patients with ESRD, and to find their correlation with Hemoglobin (Hb) level, WBC count, reticulocyte percentage and platelet count. This study was conducted at Al-Hayat center, Al Karama Teaching Hospital on 50 ESRD patients aged < 60 years of both genders. In addition, 20 apparently healthy individuals were included as a control group. The mean Hb level, total

   In this paper, a mathematical model for the oxidative desulfurization of kerosene had been developed. The mathematical model and simulation process is a very important process due to it provides a better understanding of a real process. The mathematical model in this study was based on experimental results which were taken from literature to calculate the optimal kinetic parameters where simulation and optimization were conducted using gPROMS software. The optimal kinetic parameters were Activation energy 18.63958 kJ/mol, Pre-exponential factor  2201.34 (wt)^-0.76636. min^-1  and the reaction order 1.76636. These optimal kinetic parameters were used to find the optimal reaction conditions which

                The characteristics of sulfur nanoparticles were studied by using atomic force microscope (AFM) analysis. The atomic force microscope (AFM) measurements showed that the average size of sulfur nanoparticles synthesized using thiosulfate sodium solution through the extract of cucurbita pepo extra was 93.62 nm. Protecting galvanized steel from corrosion in salt media was achieved by using sulfur nanoparticles in different temperatures. The obtained data of thermodynamic in the presence of sulfur nanoparticles referred to high value as compares to counterpart in the absence of sulfur nanoparticles, the high inhibition efficiency (%IE) and corrosion resistance were at high temperature, the corrosion rate or weig

New Azo ligands HL1 [2-Hydroxy-3-((5-mercapto-1,3,4-thiadiazol-2-yl)diazenyl)-1-naphth aldehyde] and HL2 [3-((1,5-Dimethyl-3-oxo-2-phenyl-2,3-dihydro-1H-pyrazol-4-yl)diazenyl)-2-hydroxy-1-naphthaldehyde] have been synthesized from reaction (2-hydroxy-1-naphthaldehyde) and (5-amino-1,3,4-thiadiazole-2-thiol) for HL1 and (4-amino-1,5-dimethyl-2-phenyl-1H-pyrazol-3(2H)-one) for HL2. Then, its metal ions complexes are synthesized with the general formula; [CrHL1Cl3(H2O)], [VOHL1(SO4)] [ML1Cl(H2O)] where M = Mn(II), Co(II), Ni(II) and Cu(II), and general formula; [Cr(L2)2 ]Cl and [M(L2)2] where M = VO(II), Mn(II), Co(II), Ni(II) and Cu(II) are reported. The ligands and their metal complexes are characterized by phisco- chemical spectroscopic

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Leaching scheduling techniques are one of the suggested solutions for water scarcity problems .The aim of the study is to show the possibility of using leaching scheduling, when applying the irrigation scheduling program for a certain irrigation project, which was prepare by Water Resources Engineering –University of Baghdad with some modifications to generalized it and it make applicable to various climatic zone and different soil types.
The objectives of this research is to build a system that concerns the prediction of the leaching scheduling (depth and date of leaching water), illustrating the main problems (soil salinity, save the amount of leaching requirement, and to maintain crops growth).The other objective is to compare be

Abstract

 Experimental work from Magnetic Abrasive Finishing (MAF) tests was carried out design parameters (amplitude, and number of cycle which are formed the shape of electromagnetic pole), and technological parameters (current, cutting speed, working gap, and finishing time) all have an influence on the mechanical properties of the surface layer in MAF process. This research has made to study the effect of design and technological parameters on the surface roughness (Ra), micro hardness (Hv) and material removal (MR) in working zone. A set of experimental tests has been planned using response surface methodology according to Taguchi matrix (3⁶) with three levels and six factors