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Green synthesis of gold nanoparticles using Pelargonium Graveolens leaf extract: characterization and anti-microbial properties (An in-vitro study)
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Background In recent years, there has been a notable increase in the level of attention devoted to exploring capabilities of nanoparticles, specifically gold nanoparticles AuNPs, within context of modern times. AuNPs possess distinct biophysical properties, as a novel avenue as an antibacterial agent targeting Streptococcus Mutans and Candida Albicans. The aim of this study to create a nano-platform that has the potential to be environmentally sustainable, in addition to exhibiting exceptional antimicrobial properties against Streptococcus Mutans as well as Candida Albicans. Methods this study involved utilization of Pelargonium Graveolens leaves extract as a cost effective and environmentally sustainable approach for the green synthesis of AuNPs. Subsequently, physicochemical characteristics were assessed employing a variety of analytical methods, including as transmission electron microscopy, X-ray diffraction, Field Emission Scanning Electron Microscope, Zeta potential, Ultraviolet visible absorption spectroscopy, and Energy dispersive X-ray spectroscopy and Fourier transform infrared spectroscopy. The antimicrobial efficacy against Streptococcus Mutans and Candida Albicans was evaluated. Nanoparticles of various shapes, including hexagonal, spherical, semi-spherical, and triangular, were synthesized. These nanoparticles exhibited a mean particle size of 294nm and demonstrated low degree of aggregation. These nanoparticles exhibited long-term stability and were capable of facilely combining with diverse bioactive compounds. Results The study demonstrated that AuNPs which is synthesized by green methods display potent antimicrobial properties. Conclusion Utilization of Pelargonium Graveolens AuNPs may exhibit a promising potential as an antibacterial agent against Streptococcus Mutans and Candida Albicans. Nanoparticles (NPs) have the potential to serve as a novel approach for addressing pathogen infections as well as for biomedical, dental and pharmaceutical purposes in the future.

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Publication Date
Wed Jan 29 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The impact of operational risks in electronic banking In the light of the principles of Basel (II): An Empirical Study in some Iraqi banks
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Banks represents financial institutions that influence the economy of any country and their evolution and development is the need to seek all states , communities, maintain and control a guarantee of the beneficiaries investors and to promote confidence, so the specialized organizations trying to set principles and rules must be adhered to and are Basel (II) of the necessary effects to be introduced and work on their application.  Banks exposed by various risks one of them operational risks that have multiple effects on the activity of the institution itself, as well as the national economy, so this study was to find out what those effects and to find solutions and appropriate proposals to avoid Iraqi banks from the effects of risk,

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
The effect of liquidity on the profitability and value of banks listed on Iraq stock market (An analytical study)
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  The purpose of the study is to analyze the extent of the impact of liquidity as an independent variable on profitability as an intermediate variable and the value of banks listed in the Iraq Stock Exchange as a dependent variable, as the research problem is summarized by the fact that most banks focus on profitability as a phased goal without focusing on maximizing its value as a strategic goal by enhancing the wealth of owners and shareholders. On the long term, the research community is represented by the banks listed on the Iraq Stock Exchange, while the research sample was deliberately chosen, which included three private banks such as Baghdad Commercial Bank, the Iraqi Commercial Bank and the Iraqi Investment Bank, an

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
An Exploratory Study of the Relationships between Advertising Appeals, Attitudes toward Advertising , and Consumer buying Behavior of Smart phone
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Abstract

Purpose of this study is to investigate the relationship between Advertising Appeals, Attitudes toward Advertising, and Consumer Buying Behavior for Smart Phone The study was carried out on the students of Middle East University (MEU) In Amman- Jordan.  A measurement scales  with acceptable reliability and validity is developed to capture the dimensions of study variables.  Four hypotheses were tested using Statistical package (SPSS-17).  A two-step detailed statistical analysis of data was involved. First, descriptive statistics was performed to understand the underlying components of study variables; second, regression analysis and Path analysis using AMOS 7 were performed t

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Study the Spectral Properties of Coumarine -47 Dissolved in Chloroform: Rafah Abdul Hadi Omer|Mohammed T. Hussian|Lamia Kand Kalif
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The spectral propetties (absorption and fluorescence) of Coumarine-47 laser dye have been studied. This type of laser dye belong the Coumarine family and it has dissolved in chloroform at different concentrations (1x10-5, 5x10-5, and 1x10-4 M) at room temperature. The achieved results have been pointed out to increase in the absorption and fluorescence as the concentration increased which are agreements with Beer – Lambert law. These have been also showed an expansion in the spectral range of absorption and fluorescence with a noticed shift in the direction of longer wavelength (Red-shift) with increasing concentration. The quantum efficiency of the dissolved C47 in chloroform has been computed by using the brevious concentrations

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Publication Date
Sat Feb 12 2022
Journal Name
Engineering, Technology & Applied Science Research
Prestressing Effects on Full Scale Deep Beams with Large Web Openings¨: An Experimental and Numerical Study
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Most studies on deep beams have been made with reinforced concrete deep beams, only a few studies investigate the response of prestressed deep beams, while, to the best of our knowledge, there is not a study that investigates the response of full scale (T-section) prestressed deep beams with large web openings. An experimental and numerical study was conducted in order to investigate the shear strength of ordinary reinforced and partially prestressed full scale (T-section) deep beams that contain large web openings in order to investigate the prestressing existence effects on the deep beam responses and to better understand the effects of prestressing locations and opening depth to beam depth ratio on the deep beam performance and b

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Publication Date
Tue Nov 01 2016
Journal Name
Materials Science Forum
Study the Effect of Liquid Layer Level on the Formation of Zinc Oxide Nanoparticles Synthesized by Liquid-Phase Pulsed Laser Ablation
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This work is focused on studying the effect of liquid layer level (height above a target material) on zinc oxide nanoparticles (ZnO and ZnO2) production using liquid-phase pulsed laser ablation (LP-PLA) technique. A plate of Zn metal inside different heights of an aqueous environment of cetyl trimethyl ammonium bromide (CTAB) with molarity (10-3 M) was irradiated with femtosecond pulses. The effect of liquid layer height on the optical properties and structure of ZnO was studied and characterized through UV-visible absorption test at three peaks at 213 nm, 216 nm and 218 nm for three liquid heights 4, 6 and 8 mm respectively. The obtained results of UV–visible spectra test show a blue shift accomp

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Publication Date
Sat Aug 31 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Credit Card Fraud Detection Using an Autoencoder Model with New Loss Function
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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Designing a Quality System using the Goals Programming Method -An Applied Research
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Due to the continuous development in society and the multiplicity of customers' desires and their keeping pace with this development and their search for the quality and durability of the commodity that provides them with the best performance and that meets their needs and desires, all this has led to the consideration of quality as one of the competitive advantages that many industrial companies compete for and which are of interest to customers and are looking for. The research problem showed that the Diyala State Company for Electrical Industries relies on some simple methods and personal experience to monitor the quality of products and does not adopt scientific methods and modern programs. The aim of this research is to desi

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Publication Date
Tue Nov 01 2022
Journal Name
2022 International Conference On Data Science And Intelligent Computing (icdsic)
An improved Bi-LSTM performance using Dt-WE for implicit aspect extraction
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In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

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Publication Date
Thu Apr 20 2023
Journal Name
Fire
An Efficient Wildfire Detection System for AI-Embedded Applications Using Satellite Imagery
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

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