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Shell model study of neutron rich 18-28O isotopes using effective interactions
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We employ a simple effective nucleon-nucleon interaction for sd-shell model calculations derived from the Reid soft-core potential folded with two-body correlation functions which take account of the strong short-range repulsion and large tensor component in the Reid force. Shell model calculations for ground and low lying energy states of neutron rich oxygen isotopes 18-28O are performed using OXBASH code. Generally, this interaction predicts correct ordering of levels, yields reasonable energies for ground states of considered isotopes and predicts very well the newly observed excitation energy of
in 26O. Besides, it produces reasonable energy spectra for 23-27O and compressed energy spectra for 18-22O isotopes. This is mainly due entirely to defects in the
diagonal matrix elements of employed interaction. To improve the present calculations, we modify the interaction through replacing the 14 diagonal matrix elements of
with those of the USD interaction. Mostly, our modified interaction predicts well the ordering of levels, the ground state energies and low lying energy spectra for all selected oxygen isotopes. The modified interaction confirms the location of the neutron drip line at
and also identifies the presence of the shell gap at
and
which proves the doubly magic behavior of 22O and 24O. The spins in 24O of several excitation energies around 7.5 MeV are predicted by our interactions. The calculated results obtained with the modified interaction are very close to those obtained with the empirical interactions of USDB and WPN.

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Measurement of the Radon Concentration and Annual Effective Dose in Malva sylvestris (Khabbaz) Plant Used in Traditional Medicine and Food
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In this study, the radon gas concentration as well as the annual effective dose in leaves of the Malvasylvestris (Khabbaz) plant used in the traditional treatment and as food in Iraq, for this, it is necessary to evaluate the concentrations radon gas, which were measured using solid state nuclear track detectors (SSNTDs) CR-39 technique.  The  concentration and annual effective dose in samples were collected from Baghdad city ranged from minimum to maximum value 15.815 , 0.498 , 54.445 , 1.717  respectively, while the values of  concentration and annual effective dose in a sample collected from Karbala are 15.297 ,0.482 . These values of  concentration and annual effective dose less were compared with th

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Publication Date
Fri Nov 24 2023
Journal Name
Iraqi Journal Of Science
Monte Carlo Simulation of the Effective Solid Angle and the HPGe Response to Different Mono-Energetic Protons from Extended Source
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A program using Mont Carlo techniques has been written to calculate the effective solid angle of the detection system and simulate the response of the HPGe to mono-energetic protons from an extend source. It has been found that the fraction of the protons which leave through the cylindrical surface and deposit only part of their kinetic energy in the crystal increases with proton energy and the consequent increase in their range.

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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Sun Oct 01 2023
Journal Name
Applied Sciences
Multiobjective Optimization of Stereolithography for Dental Bridge Based on a Simple Shape Model Using Taguchi and Response Surface Methods
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Stereolithography (SLA) has become an essential photocuring 3D printing process for producing parts of complex shapes from photosensitive resin exposed to UV light. The selection of the best printing parameters for good accuracy and surface quality can be further complicated by the geometric complexity of the models. This work introduces multiobjective optimization of SLA printing of 3D dental bridges based on simple CAD objects. The effect of the best combination of a low-cost resin 3D printer’s machine parameter settings, namely normal exposure time, bottom exposure time and bottom layers for less dimensional deviation and surface roughness, was studied. A multiobjective optimization method was utilized, combining the Taguchi me

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Effects of Macroeconomic Variables on Gross Domestic Product in Saudi Arabia using ARDL model for the period 1993-2019
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This paper analyses the relationship between selected macroeconomic variables and gross domestic product (GDP) in Saudi Arabia for the period 1993-2019. Specifically, it measures the effects of interest rate, oil price, inflation rate, budget deficit and money supply on the GDP of Saudi Arabia. The method employs in this paper is based on a descriptive analysis approach and ARDL model through the Bounds testing approach to cointegration. The results of the research reveal that the budget deficit, oil price and money supply have positive significant effects on GDP, while other variables have no effects on GDP and turned out to be insignificant. The findings suggest that both fiscal and monetary policies should be fo

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Publication Date
Tue May 07 2019
Journal Name
Proteomics
Proteomic Analysis of Stromal and Epithelial Cell Communications in Human Endometrial Cancer Using a Unique 3D Co‐Culture Model
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Abstract<p>Epithelial and stromal communications are essential for normal uterine functions and their dysregulation contributes to the pathogenesis of many diseases including infertility, endometriosis, and cancer. Although many studies have highlighted the advantages of culturing cells in 3D compared to the conventional 2D culture system, one of the major limitations of these systems is the lack of incorporation of cells from non‐epithelial lineages. In an effort to develop a culture system incorporating both stromal and epithelial cells, 3D endometrial cancer spheroids are developed by co‐culturing endometrial stromal cells with cancerous epithelial cells. The spheroids developed by this method are phenot</p> ... Show More
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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Publication Date
Fri Jan 20 2023
Journal Name
Journal Of Electronic Materials
Influence of Dry and Wet Etching on AlInSb Contact Resistivity, Transfer Length, and Sheet Resistance Using Circular Transmission Model
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Publication Date
Fri May 07 2021
Journal Name
Journal Of Evaluation In Clinical Practice
Exploring the acceptance of <scp>COVID</scp>‐19 vaccine among healthcare workers and general population using health belief model
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Abstract<sec><title>Rationale, aims and objectives

Little is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.

Methods

This was a cross‐sectional study based on electronic survey data that was collected in Iraq during December first‐19th, 2020. The electronic surve

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Publication Date
Thu Dec 15 2022
Journal Name
Journal Of Petroleum Research And Studies
Selection of an Optimum Drilling Fluid Model to Enhance Mud Hydraulic System Using Neural Networks in Iraqi Oil Field
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In drilling processes, the rheological properties pointed to the nature of the run-off and the composition of the drilling mud. Drilling mud performance can be assessed for solving the problems of the hole cleaning, fluid management, and hydraulics controls. The rheology factors are typically termed through the following parameters: Yield Point (Yp) and Plastic Viscosity (μp). The relation of (YP/ μp) is used for measuring of levelling for flow. High YP/ μp percentages are responsible for well cuttings transportation through laminar flow. The adequate values of (YP/ μp) are between 0 to 1 for the rheological models which used in drilling. This is what appeared in most of the models that were used in this study. The pressure loss

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