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Anti-Angiogenic Screening of Moringa Oleifera Leaves Extract Using Chorioallantonic Membrane Assay
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Background: Angiogenesis is defined as the formation of new blood vessels. However, angiogenesis in cancer will lead to tumour growth and metastasis. Therefore, anti-angiogenesis is one of the ways to slow down growth and spreading of tumour. Moringa oleifera is also known as a “Miracle tree” which has high nutritive value and various therapeutics effect in different parts of the plant. This study aims to determine the anti-angiogenic property of Moringa oleifera leaves extract by using chick chorioallantoic membrane (CAM) assay. Materials and Methods: The extracts were prepared by decoction method using methanol and water. The qualitative phytochemical screening was carried out for both methanol and aqueous extracts. The fertilised chicken eggs were divided into six groups which include negative control group (phosphate-buffer saline with pH 7.4), positive control group (sunitinib), 50% and 100% methanol extract, 50% and 100% aqueous extract. The anti-angiogenic effect of Moringa oleifera leaves extract was determined by calculating the number and percentage decrease in blood vessels in post-24 and post-48 hours of treatment. Results: Statistical analysis by one-way ANOVA has shown significant (p<0.05) percentage reduction in the blood vessels between each treatment group after 48 hours of treatment. Among all the extracts, 100% aqueous extract of Moringa oleifera was found to have highest anti-angiogenic effect with the greater percentage decrease in blood vessels (81.33%) in post-48 hours of treatment. Furthermore, the anti-angiogenic effect of Moringa oleifera leaves was found to increased when the concentration of the Moringa oleifera extract was increased. Conclusion: Moringa oleifera leaves with various phytochemicals was found to possess anti-angiogenic potential.

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Publication Date
Sat Dec 17 2022
Journal Name
Iraqi Journal Of Laser
PDF Cavity Disinfection Using Er,Cr:YSGG Laser Induced Photoacoustic Streaming Technique: Rand kareem Jassim Hussein Ali Jawad*
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Abstract:

Aim: The goal of this research was to study the influence of Er,Cr:YSGG laser at short pulse duration (60 µsec) on the number of streptococcus mutans bacteria in vitro.

Material and Methods:  twenty-eight extracted third molars free of caries, cracks, and other irregularities were used. For the testing of the materials, both the agar well technique and a tooth cavity model were employed. The agar wells of plates that had been inoculated with Streptococcus mutans previously were stuffed with the test materials, in order to conduct the tests. The zones of inhibition were assessed using millimeter measurements, after an incubation period of 48 hours .In order to a

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Publication Date
Wed Feb 01 2023
Journal Name
Chemical Engineering Research And Design
Nickel removal from simulated wastewater using a novel bio-electrochemical cell with packed bed rotating cylinder cathode
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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
comparison between the methods estimate nonparametric and semiparametric transfer function model in time series the Using simulation
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 The transfer function model the basic concepts in the time series. This model is used in the case of multivariate time series. As for the design of this model, it depends on the available data in the time series and other information in the series so when the representation of the transfer function model depends on the representation of the data In this research, the transfer function has been estimated using the style nonparametric represented in two method  local linear regression and cubic smoothing spline method The method of semi-parametric represented use semiparametric single index model, With four proposals, , That the goal of this research is comparing the capabilities of the above mentioned m

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Publication Date
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Some Estimation Methods for Mixed-Random Panel Data Regression Models with Serially Correlated Errors with Application
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This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Estimating Stock Returns Using Rough Set Theory: An Exploratory study With An Evidence From Iraq Stock Exchange
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‎ This research aims to estimate stock returns, according to the ‎Rough Set Theory ‎approach, ‎test ‎its effectiveness and accuracy in predicting stock returns and their potential in the ‎field of ‎financial ‎markets, and rationalize investor decisions. The research sample is totaling (10) ‎companies traded at Iraq Stock Exchange. The results showed a remarkable ‎ ‎Rough Set Theory application in data reduction, contributing to the rationalization of ‎investment ‎decisions. The most prominent conclusions are the capability of rough set theory ‎in ‎dealing with financial data and applying it for forecasting stock ‎returns.‎The ‎research provides those interested in investing stocks in financial

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Publication Date
Mon Oct 01 2018
Journal Name
2018 International Conference On Advanced Science And Engineering (icoase)
Real-Time Face Tracking and Recognition System Using Kanade-Lucas-Tomasi and Two-Dimensional Principal Component Analysis
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Tue Sep 07 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Wellbore instability management using geomechanical modeling and wellbore stability analysis for Zubair shale formation in Southern Iraq
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Abstract<p>Wellbore instability problems cause nonproductive time, especially during drilling operations in the shale formations. These problems include stuck pipe, caving, lost circulation, and the tight hole, requiring more time to treat and therefore additional costs. The extensive hole collapse problem is considered one of the main challenges experienced when drilling in the Zubair shale formation. In turn, it is caused by nonproductive time and increasing well drilling expenditure. In this study, geomechanical modeling was used to determine a suitable mud weight window to overpass these problems and improve drilling performance for well development. Three failure criteria, including Mohr–Coulomb, modifie</p> ... Show More
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Robust Color Image Encryption Scheme Based on RSA via DCT by Using an Advanced Logic Design Approach
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Information security in data storage and transmission is increasingly important. On the other hand, images are used in many procedures. Therefore, preventing unauthorized access to image data is crucial by encrypting images to protect sensitive data or privacy. The methods and algorithms for masking or encoding images vary from simple spatial-domain methods to frequency-domain methods, which are the most complex and reliable. In this paper, a new cryptographic system based on the random key generator hybridization methodology by taking advantage of the properties of Discrete Cosine Transform (DCT) to generate an indefinite set of random keys and taking advantage of the low-frequency region coefficients after the DCT stage to pass them to

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Publication Date
Wed Oct 29 2025
Journal Name
Clean Energy Science And Technology
Edge-intelligent leak detection in water distribution systems using CatBoost: A sustainable solution for reducing infrastructure losses
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Water supply networks are marred by serious risks of imperceptible pipeline leakage, posing ‎sustainability ‎and ‎performance ‎threats.  This article highlights the use of vibratory signal features to get around the drawbacks of traditional methods in a highly detailed framework for leak detection based on CatBoost. demonstrated excellent diagnostic performance and carried out a thorough test performance evaluation on five leakage configurations  . The expected system achieved an accuracy of 98.1% (variance (well within x/3% of expected):, beating traditional competitors such as Random Forest (97.3%) and Support Vector Machine (93.8%). ‎For example, the area under the receiver-operating characteristic curve was 0.995, in

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