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Cognitive bias and its relation to emotional thinking among university students
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The study aims to identify the cognitive bias and the level of emotional thinking among university students, besides, identifying the significant differences between male and female students regarding those two variables, and determine if there is a correlation between cognitive bias and emotional thinking. To this end, two scales were adopted to collect needed data: cognitive bias scale designed by (Al-any, 2015), composed of (14) items, and emotional thinking scale designed by (Abdu Allah, 2017), consisted of (27) items. These two scales were administered to (140) students composed the study sample. They were chosen from four different colleges at Al-mustansiriyah University for the academic year (2017-1018). The findings revealed that study sample did not show any cognitive bias, but they have a level of emotional thinking. Additionally, there is no significant difference between male and female students in term of cognitive bias and emotional thinking. The findings also exposed there is no correlation between cognitive bias and emotional thinking

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Publication Date
Thu Jun 01 2023
Journal Name
Iraqi Journal Of Physics
Cytotoxic Activity of CuO NPs Prepared by PLAL Against Liver Cancer (Hep-G2) Cell Line and HdFn Cell Lines
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A simple physical technique was used in this study to create stable and cost-effective copper oxide (CuO) nanoparticles from pure copper metal using the pulsed laser ablation technique. The synthesis of crystalline CuO nanoparticles was confirmed by various analytical techniques such as particle concentration measurement using atomic absorption spectrometry (AAS), field emission scanning electron microscopy (FE-SEM), the energy dispersive X-ray (EDX), and X-ray diffraction (XRD) to determine the crystal size and identify of the crystal structure of the prepared particles. The main characteristic diffraction peaks of the three samples were consistent. The corresponding 2θ is also consistent, and the cytotoxicity of the nanoparticles was

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Publication Date
Wed Oct 29 2025
Journal Name
The Indonesian Biomedical Journal
Genotype Combination of rs1042044 and rs6458093 in GLP-1R as A Genetic Risk for Osteoporosis in Postmenopausal Iraqi Women
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BACKGROUND: Many genetic factors are known to be related to osteoporosis, and currently the role of the glucagon-like peptide-1 receptor (GLP-1R) gene in bone health has been studied intensively. Some variation of this gene, such as rs1042044 and rs6458093, are known to be linked to metabolic diseases and lower bone mineral density, however their specific contribution to osteoporosis remains largely unexplored. Therefore, this study was conducted to investigate the combined genotypic effect of rs1042044 and rs6458093 as a genetic risk factor for osteoporosis in postmenopausal Iraqi women.METHODS: Blood samples from 75 osteoporosis patients and 75 healthy controls, aged 45-85, were collected. DNA was extracted, and a region of GLP-1R

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Publication Date
Wed Nov 01 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Protective Effects of Citronellol Against Rhabdomyolysis-Induced Acute Kidney Injury in Mice by Inhibiting NF-κB and IL-1β
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Objectives: acute kidney injury (AKI) is a serious pathophysiology side effect of rhabdomyolysis. Inflammatory mechanisms play a role in the development of rhabdomyolysis-induced AKI. Citronellol (CT) is a naturally occurring monoterpene alcohol (3,7-Dimethyl-6-often-1-ol) found in aromatic plant species' essential oils. In this study, we explored the protective effects of Citronellol on glycerol-induced AKI.

Methods: Four groups of eight mice each (n=8) were formed by randomly dividing the animals into the groups, glycerol-induced AKI model group, low-dose CT-treated group (50mg/kg), high-dose CT-treated group (100mg/kg), and control group. The renal functions of mice from all groups were evalua

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Publication Date
Tue May 13 2025
Journal Name
Energies
Thermal and Thermo-Hydraulic Performance of a Semi-Circular Solar Air Collector Utilizing an Innovative Configuration of Metal Foams
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The enhancement of the thermal and thermo-hydraulic performance of a semi-circular solar air collector (SCSAC) is numerically investigated using porous semi-circular obstacles made of metal foam with and without longitudinal porous Y-shaped fins. Two 10 and 40 PPI porous material samples are examined. Three-dimensional models are built to simulate the performance of SCSAC: model (I) with clear air passage; model (II) with only metal foam obstacles, and model (III) with metal foam obstacles as well as porous Y-fins. COMSOL Multiphysics software version 6.2 based on finite element methodology is employed. A conjugate heat transfer with a (k-ε) turbulence model is selected to simulate both heat transfer and fluid flow across the entir

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Publication Date
Sun Sep 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
The Economic Conditions of Living in the City of Mosul: Income and Labor Market during the Period 2004-2007
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Abstract

 

This study cares for the economic living conditions in Mosul City. Its importance lies in the critical period that has been covered
(2002-2007), which was dominated by far–reaching events at political economic and social levels.
Among the main results that have been revealed are the following: the rate of economic growth in the City has been the lowest among major urban centers in Iraq. Besides, real income per capita in the City has stayed stagnant during the period of the study. However, the inequality in distribution of income has decreased. The main bulk of the city's population rely on their income from wages and salari

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Publication Date
Thu Aug 01 2024
Journal Name
Water Practice & Technology
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe</p> ... Show More
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Publication Date
Sat May 01 2021
Journal Name
Pharmacological Research
Resveratrol-mediated attenuation of superantigen-driven acute respiratory distress syndrome is mediated by microbiota in the lungs and gut
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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research &amp; Development
Effect of <i>Olea europea</i> L Extraction and TiO<sub>2</sub> Nanoparticles against <i>Pseudomonas aeruginosa</i>
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Publication Date
Tue May 27 2025
Journal Name
Bulletin Of The Chemical Society Of Ethiopia
Preparation, kinetics, and thermodynamic investigation of Janus green dye removal from aqueous solutions using MnO2 nanoparticles as an adsorbent
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In this study, manganese dioxide (MnO₂) nanoparticles (NPs) were synthesized via the hydrothermal method and utilized for the adsorption of Janus green dye (JG) from aqueous solutions. The effects of MnO₂ NPs on kinetics and diffusion were also analyzed. The synthesized NPs were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray analysis (EDX), and Fourier-transform infrared spectroscopy (FT-IR), with XRD confirming the nanoparticle size of 6.23 nm. The adsorption kinetics were investigated using three models: pseudo-first-order (PFO), pseudo-second-order (PSO), and the intraparticle diffusion model. The PSO model provided the best fit (R² = 0.999), indicating that the adsorpti

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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