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An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperature exerted the most significant influence at 100%, while sample dimensions had a minimal impact at 17.9%. In addition, the mathematical model closest to the proposed was the Bazli model, because the latter depends on two variables (thickness and temperature). The ANN accurately predicted the residual tensile strength of GFRP at elevated temperatures, achieving a correlation coefficient of 97.3% and a determination coefficient of 94.3%.

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Publication Date
Thu Dec 31 2020
Journal Name
College Of Islamic Sciences
The most important and important rule in the Quranic perspective "An applied study"
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Abstract

    All of us are indispensable for this rule (the most important and important) individuals, whether we were groups of leaders or followers of peoples or countries because the rule provides adequate guarantees for the correct positions and drawing the plan for successful decision-makers matching with the balances of Sharia without incompatibility between religious or worldly interests or legal positions and therefore in the framework of the most important appointment And distinguish it from the important from the interests or the appointment of the most important and distinguish from the important from the evils and through this rule we learn about the scientific and practical solutions t

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Publication Date
Fri May 04 2018
Journal Name
Wireless Personal Communications
IFRS: An Indexed Face Recognition System Based on Face Recognition and RFID Technologies
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Publication Date
Mon Aug 29 2022
Journal Name
Eurasian Chem. Commun.
Removing some alizarin dyes from an aqueous solution using a polyacrylic acid hydrogel
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The present work utilizes polyacrylic acid beads (PAA) to remove Alizarin yellow R (AYR)] and Alizarin Red S (ARS) from its solution. The isotherms of adsorption were investigated and the factors that impact them, such as temperature, ionic strength effect, shaking effect, and wet PAA. The isotherms of adsorption of (ARS) were found obeys the Freundlich equation. The isotherms of adsorption of (AYR) were found obeys the Langmuir equation. At various temperatures, the adsorption process on (PAA) was investigated. According to our data, there is a positive correlation between the (ARS and AYR) adsorption on the PAA and temperature (Endothermic process). The computation of the thermodynamic functions (ΔH, ΔG, and ΔS) is based on the foregoi

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Publication Date
Tue Feb 14 2023
Journal Name
Journal Of Educational And Psychological Researches
Panic Attacks Over COVID 19 : A Survey Study on An Iraqi University Sample
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Abstract

The present paper attempts to detect the level of (COVID-19) pandemic panic attacks among university students, according to gender and stage variables.

To achieve this objective, the present paper adopts the scale set up by (Fathallah et al., 2021), which has been applied electronically to a previous cross-cultural sample consisting of (2285) participants from Arab countries, including Iraq. The scale includes, in its final form, (69) optional items distributed on (6) dimensions:  physical symptoms (13) items, psychological and emotional symptoms (12) items, cognitive and mental symptoms (11) items, social symptoms (8) items, general symptoms (13) items and daily living practices (12) items

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Image And Graphics
Normalized-UNet Segmentation for COVID-19 Utilizing an Encoder-Decoder Connection Layer Block
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The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is fre

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Composites Science
Sawdust-Based Concrete Composite-Filled Steel Tube Beams: An Experimental and Analytical Investigation
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Incorporating waste byproducts into concrete is an innovative and promising way to minimize the environmental impact of waste material while maintaining and/or improving concrete’s mechanical characteristics and strength. The proper application of sawdust as a pozzolan in the building industry remains a significant challenge. Consequently, this study conducted an experimental evaluation of sawdust as a fill material. In particular, sawdust as a fine aggregate in concrete offers a realistic structural and economical possibility for the construction of lightweight structural systems. Failure under four-point loads was investigated for six concrete-filled steel tube (CFST) specimens. The results indicated that recycled lightweight co

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Publication Date
Tue Apr 27 2021
Journal Name
Cells
DNMT3B Is an Oxygen-Sensitive De Novo Methylase in Human Mesenchymal Stem Cells
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The application of physiological oxygen (physoxia) concentrations is becoming increasingly commonplace within a mammalian stem cell culture. Human mesenchymal stem cells (hMSCs) attract widespread interest for clinical application due to their unique immunomodulatory, multi-lineage potential, and regenerative capacities. Descriptions of the impact of physoxia on global DNA methylation patterns in hMSCs and the activity of enzymatic machinery responsible for its regulation remain limited. Human bone marrow-derived mesenchymal stem cells (BM-hMSCs, passage 1) isolated in reduced oxygen conditions displayed an upregulation of SOX2 in reduced oxygen conditions vs. air oxygen (21% O2, AO), while no change was noted for either OCT-4 or NA

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Publication Date
Mon Jun 26 2023
Journal Name
Journal Of Contemporary Medical Sciences
Glyceryl Trinitrate, a Vasodilating Drug Acts as an Antibiofilm Agent in Serratia marcescens
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Objectives: Serratia marcescens is a gram-negative pathogen of many species. The ability of S. marcescens to form biofilms and its potent innate resistance to antimicrobials and cleaning solutions are both essential for its pathogenicity and survival. The present study was conducted to investigate the effect of glyceryl trinitrate (GTN) on the biofilm of S. marcescens, as an alternative for antibiotic therapy. Methods: Different specimens, including ear swabs, burns, mid-stream urine, wound swabs, and sputum, were collected from patients who were brought to Al-Ramadi Hospital, Iraq. All samples were cultured, and the colonies that were obtained were detected using the VITEK® 2 compact. The ability of biofilms to develop was e

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Publication Date
Sun Nov 01 2020
Journal Name
2020 2nd Annual International Conference On Information And Sciences (aicis)
An Enhanced Multi-Objective Evolutionary Algorithm with Decomposition for Signed Community Detection Problem
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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Community Detection in Modular Complex Networks Using an Improved Particle Swarm Optimization Algorithm
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     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

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