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joe-2894
PHYSICAL MODEL OF KEROSENE PLUME MIGRATION IN AN UNSATURATED ZONE OF THE SANDY SOIL
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Physical model tests were simulated non-aqueous phase liquid (NAPL) spill in two-dimensional
domain above the water table. Four laboratory experiments were carried out in the sand-filled
tank. The evolution of the plume was observed through the transparent side of this tank and the
contaminant front was traced at appropriate intervals. The materials used in these experiments
were Al-Najaf sand as a porous medium and kerosene as contaminant.
The results of the experiments showed that after kerosene spreading comes to a halt (ceased) in
the homogeneous sand, the bulk of this contaminant is contained within a pancake-shaped lens
situated on top of the capillary fringe.

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Publication Date
Thu Jun 29 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications (ijnaa)
Applying a suitable approximate-simulation technique of an epidemic model with random parameters
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Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

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Publication Date
Sat Dec 14 2019
Journal Name
International Journal On Emerging Technologies
Utilizing an Artificial Neural Network Model to Predict Bearing Capacity of Stone Columns
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ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel

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Publication Date
Sat Apr 30 2022
Journal Name
Sport Tk-revista Euroamericana De Ciencias Del Deporte
Effect of a training program on the development of physical abilities in football goalkeepers
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The primary aim of this study was to find out the effect of a training program on the development of physical abilities in football goalkeepers. The current study was conducted on goalkeepers of the Academy of Espanyol Sports Club in the premises of Haifa Sports Club Stadium. The study was completed by the researchers within the timeline of May 2021 to August 2021. A total of 7 goalkeepers falling within the age group of 15-17 years were recruited as the sample participants for the study. Out of 7 goalkeepers, 5 goalkeepers were included in the primary experiment and 2 of them were excluded. The training program applied had a positive effect on the development of physical abilities in the football goalkeepers of the sa

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Word Cloud Model based on Hate Speech in an Online Social Media Environment
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Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq

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Publication Date
Wed Sep 27 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Assessing the reliability of serum macrophage migration inhibitory factor as a marker for diabetic nephropathy prediction in type 2 diabetes patients and the effect of ACE inhibitors on its level
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Abstract Diabetic nephropathy (DN) is a prevalent chronic microvascular diabetic complication. As inflammation plays a vital role in the development and progress of DN the macrophages migration inhibitory factor (MIF), a proinflammatory multifunctional cytokine approved to play a critical function in inflammatory responses in various pathologic situations like DN. This study aimed To assess serum levels of MIF in a sample of Iraqi diabetic patients with nephropathy supporting its validity as a marker for predicting nephropathy in T2DM patients. In addition, to evaluate the nephroprotective effect of angiotensin-converting enzyme (ACE) inhibitors in terms of their influence on MIF levels. This is a case-control study involving ninety

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Estimation the Radioactive Pollution by Uranium in the Soil of Al-Kut City/ Iraq
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The aim of the present work, was measuring of uranium concentrations in 25 soil samples from five locations of Al-Kut city. The samples taken from different depths ranged from soil surface to 60cm step 15 cm, for this measurement of uranium concentrations .The most widely used technique SSNTDs was chosen to be the measurement technique. Results showed that the higher concentrations were in Hai Al- Kafaat which recorded 1.49 ± 0.054 ppm . The uranium content in soil samples were less than permissible limit of UNSCEAR(11.7ppm).

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Publication Date
Sat Feb 14 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Immunohistochemical expression of MMP1 and TIMP1 as markers of migration in Hodgkin’s and non-Hodgkin’s lymphoma of the head and neck region (A comparative study)
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Background: Malignant lymphoma is a term that describes primary tumors of the lymphoreticular system, almost all of which arise from lymphocytes.MMP-1 is the most ubiquitously expressed interstitial collagenase, a subfamily of MMPs that cleaves stromal collagens. It is also called collagenase-1.TIMPs which inhibits MMP activity and thereby restrict extracellular matrix breakdown, TIMP-1 is a stromal factor that has a wide spectrum of functions in different tissues. Material and Methods: This study was performed on (68) formalin-fixed, paraffin-embedded blocks, histopathologically diagnosed as lymphoma (head and neck lesions). Immunohistochemical staining of MMP1and TIMP1 was performed on each case of the study sample. Results: The expressio

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Publication Date
Fri Jan 01 2021
Journal Name
E3s
Performance of Under-Reamed Piles in Collapsible Soil
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One of the Iraqi geotechnical problems is the presence of gypseous soils covering about (27-36) percentage of Iraq soils containing gypsum between (10-70) ratios. The main reason for soil problematic is the gypsum dissolution when these soils are inundated. However, the soluble gypsum can be leached out of the soil particles, so these problems can be led to cracking, tilting, and collapsing the related soil structure and changing the soil properties. The aim of this work is to investigate the performance of under-reamed piles as a new, improved method to reduce the moisture sensitive and the primary triggering mechanism for the volume reduction of collapsible soil, which is considered as a non-elastic deformation; this was done by c

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