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A Computational Model of the Brain Cortex and Its Synchronization
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Obtaining the computational models for the functioning of the brain gives us a chance to understand the brain functionality thoroughly. This would help the development of better treatments for neurological illnesses and disorders. We created a cortical model using Python language using the Brian simulator. The Brian simulator is specialized in simulating the neuronal connections and synaptic interconnections. The dynamic connection model has multiple parameters in order to ensure an accurate simulation (Bowman, 2016). We concentrated on the connection weights and studied their effect on the interactivity and connectivity of the cortical neurons in the same cortical layer and across multiple layers. As synchronization helps us to measure the degree of correlation between two or more neuronal groups, the synchronization between the neuronal groups, which are connected across layers, is considered. Despite its obvious importance, there are no sufficient studies concerned about the synchronization in the simulated cortical models. Such studies can help in examining the hypothesis and the dynamical behavior of the simulated model. In this paper, we simulated a cortical model and dynamical behavior and then studied the effect of input noise on its internal neuronal networks and their synchronization.

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Publication Date
Fri Jan 01 2021
Journal Name
Materials Today: Proceedings
Response surface methodology: A review on its applications and challenges in microbial cultures
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Publication Date
Fri Feb 13 2026
Journal Name
Iraqi Journal Of Agricultural Sciences
PURIFICATION OF PHYTASE PRODUCED FROM A LOCAL FUNGAL ISOLATE AND ITS APPLICATIONS IN FOOD SYSTEMS
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Publication Date
Fri Jun 02 2017
Journal Name
Applied Organometallic Chemistry
A new azo‐Schiff base: Synthesis, characterization, biological activity and theoretical studies of its complexes
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A new Azo‐Schiff base ligand L was prepared by reaction of m‐hydroxy benzoic acid with (Schiff base B) of 3‐[2‐(1H–indol‐3‐yl)‐ethylimino]‐1.5‐dimethyl‐2‐phenyl‐2,3‐dihydro‐1H‐pyrazol‐4‐ylamine. This synthesized ligand was used for complexation with different metal ions like Ni(II), Co(II), Pd(II) and Pt(IV) by using a molar ratio of ligand: metal as 1:1. Resulted compounds were characterized by NMR (1H and 13C), UV–vis spectroscopy, TGA, FT‐IR, MS, elemental analysis, magnetic moment and molar conductivity studies. The activation thermodynamic parameters, such as ΔE*, ΔH*, ΔS*, ΔG*and

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Publication Date
Sun Jan 01 2017
Journal Name
Dissertation/thesis
A Model To Evaluate the Online Training for Global Virtual Teams in Global Software Projects
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Publication Date
Fri Feb 13 2026
Journal Name
Iraqi Journal Of Science
Magnetohydrodynyamic Flow for a Viscoclastic Fluid with the Generalized Oldroyd-B Model with Fractional Derivative
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This paper deals with the Magnetohydrodynyamic (Mill)) flow for a viscoclastic fluid of the generalized Oldroyd-B model. The fractional calculus approach is used to establish the constitutive relationship of the non-Newtonian fluid model. Exact analytic solutions for the velocity and shear stress fields in terms of the Fox H-function are obtained by using discrete Laplace transform. The effect of different parameter that controlled the motion and shear stress equations are studied through plotting using the MATHEMATICA-8 software.

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Publication Date
Tue Jan 30 2024
Journal Name
International Journal Of Pharmacy Practice
A Comprehensive Review of Drivers influencing Flu Vaccine Acceptance in the Middle East: Using Health Belief Model
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Rationale, aims and objectives: A review of studies published over the last six years gives update about this hot topic. In the middle of COVID-19 pandemic, this study findings can help understand how population may perceive vaccinations. The objectives of this study were to review the literature covering the perceptions about influenza vaccines and to determine factors influencing the acceptance of vaccination using Health Belief Model (HBM). Methods: A comprehensive literature search was performed utilizing PubMed and Google Scholar databases. Three keywords were used: Influenza vaccine, perceptions, and Middle East. Empirical studies that dealt with people/ HCW perceptions of influenza vaccine in the Middle East and writt

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using a hybrid SARIMA-NARNN Model to Forecast the Numbers of Infected with (COVID-19) in Iraq
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Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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Publication Date
Mon Feb 21 2022
Journal Name
Applied Sciences
The Behavior of Hybrid Fiber-Reinforced Concrete Elements: A New Stress-Strain Model Using an Evolutionary Approach
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Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti

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