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Major Drivers for COVID-19 Vaccine Acceptance: A Scoping Review
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Objective: To review and identify the major drivers for COVID-19 vaccine acceptance. Methods: A scoping review of studies of COVID-19 vaccine perceptions and barriers to using the COVID-19 vaccines. Two search engines, including PubMed and Google Scholar, were purposefully searched. Results: Eight studies from different countries were reviewed to categorize factors influencing people's acceptance of COVID-19 according to the Health Belief Model (HBM). Perceived susceptibility, and severity of the disease (COVID-19), in addition to perceived benefits of COVID-19 vaccination and "cues to action", can enhance vaccination acceptance. In contrast, perceived barriers to the COVID-19 vaccine can increase people's hesitancy to be vaccinated. Conclusions: The HBM domains are successful in the prediction of human behaviors toward preventive measures, including vaccination. In general, high perceived susceptibility, severity, benefits, and minimum barriers should always be maintained to keep the vaccination rate high. Reducing the hesitancy to get the vaccine can be achieved by increasing awareness campaigns about the vaccine's efficacy in preventing infection.

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Publication Date
Tue Jan 01 2019
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees19gr
Theoretical calculations involving a standard neutron yield distribution for the T-T nuclear fusion reaction
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A standard theoretical neutron energy flux distribution is achieved for the triton-triton nuclear fusion reaction in the range of triton energy about ≤10 MeV. This distribution give raises an evidence to provide the global calculations including the characteristics fusion parameters governing the T-T fusion reaction.

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Publication Date
Wed Aug 03 2022
Journal Name
Egyptian Journal Of Chemistry
A Novel Bio-electrochemical Cell with Rotating Cylinder Cathode for Cadmium Removal from Simulated Wastewater
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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Serum ceruloplasmin ,copper and iron levels as a risk factors for coronary heart diseases(CHD)
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Ceruloplasmin (Cp) is one of the acute phase protein, in this review ,we studied the level of ceruloplasmin with copper (Cu) and iron in 90 patients with coronary heart diseas ( those patients are divided into three groups, whom are stable angina , unstable angina and myocardial infarction compared with 30 healthy volunteers) and the roles of them as diagnostic and prognostic tools.The diagnosis was attend by a clinical examination carried out by the consult medical staff in Ibn AL-Nafis hospital. The result: ceruloplasmin recorded a significantly(p<0.05)higher level in all patient groups compared with the control, so this result supports the hypothesis that a high serum ceruloplasmin level is a risk factor for coronary heart di

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Study of A Improve Model For The D-D Nuclear Fusion Reaction Cross Section
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     The study of improved model for measuring the total nuclear fusion cross section characteristics  the D-D reaction may play an important role in deciding  or determining the hot plasma parameters such as mean free path , the reaction rate , reactivity and energy for emitted neutrons or protons in our work we see the it is necessary to modify the empirical formulas included the total cross section in order to arrive or achieve good agreement with the international publish result.    

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Intelligent Systems
Trip generation modeling for a selected sector in Baghdad city using the artificial neural network
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Abstract<p>This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to</p> ... Show More
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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
Search for Identity in Michael Ondaatje's Post colonial Novel In the Skin of a Lion
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In his post colonial novel, In the Skin of a lion, the Canadian/Sri Lankan writer,
Michael Ondaatje is so interested in the term "Post colonialism" because he wants to show
that the term doesn't only refer to a period of time that comes after colonialism. In other
words, post colonialism is not only referred to as a literal description of formerly colonial
societies. He deals with the termas a literary genre and an academic construct that describes
the global conditions of a man after a period of colonialism. He shows that post colonialism is
a theory that tries to examine and explore the different styles and faces of European authority
to control the colonized. Ondaatje's attempt through such term is to unmask Europ

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Publication Date
Sat Dec 01 2018
Journal Name
Applied Soft Computing
A new evolutionary algorithm with locally assisted heuristic for complex detection in protein interaction networks
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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Design and Development of Smart List: A Mobile App for Creating and Managing Grocery Lists
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Research in consumer science has proven that grocery shopping is a complex and distressing process. Further, the task of generating the grocery lists for the grocery shopping is always undervalued as the effort and time took to create and manage the grocery lists are unseen and unrecognized. Even though grocery lists represent consumers’ purchase intention, research pertaining the grocery lists does not get much attention from researchers; therefore, limited studies about the topic are found in the literature. Hence, this study aims at bridging the gap by designing and developing a mobile app (application) for creating and managing grocery lists using modern smartphones. Smartphones are pervasive and become a necessity for everyone tod

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
A noval SVR estimation of figarch modal and forecasting for white oil data in Iraq
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The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

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Publication Date
Thu Oct 13 2022
Journal Name
Computation
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

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