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Trends of poetic purposes towards praise: Dabal al-Khuzai's poetry is a model
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Poetic objects may go towards a specific purpose and dissolve and interact with them to produce
A purpose characterized by the title but belongs to the U from afar.
The yarn goes towards praise with a purely horizontal relationship that mentions virtues but crowns them towards women.
In lamentation remember the virtues but crown them towards the dead.
In wisdom remember the virtues but crown them towards time.
In the description remember the virtues but crown them towards nature. All objects are inline
Horizontal We will prove this in the axes of research has required the plan to be a blind, five
The preamble, a brief overview of the life of Dabal All Khuzaie and the works and poets of the first axis
The direction of praise towards spinning and the second axis included the direction of praise towards lamentation, either axis
The third was entitled the direction of praise towards wisdom, came the fourth axis entitled the direction of praise towards
The fifth section included the trend of praise towards the yeasts, and the conclusion came to include the totality
The findings of the research, after the conclusion provided a list of sources and references that inspired them
Literary, artistic and historical material, and then the conclusion of the message in English.

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Publication Date
Sun Sep 01 2024
Journal Name
Green Analytical Chemistry
Green methods for determination of paracetamol in drug samples: A comparative study
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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Synthesis, Characterization, and Thermal Analysis of a New Acidicazo Ligand's Metal Complexes
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The researchers wanted to make a new azo imidazole as a follow-up to their previous work. The ligand 4-[(2-Amino-4-phenylazo)-methyl]-cyclohexane carboxylic acid as a derivative of trans-4-(aminomethyl) cyclohexane carboxylic acid diazonium salt, and synthesis a series of its chelate complexes with metalions, characterized these compounds using a variety technique, including elemental analysis, FTIR, LC-Mass, 1H-NMRand UV-Vis spectral process as well TGA, conductivity and magnetic quantifications. Analytical data showed that the Co (II) complex out to 1:1 metal-ligand ratio with square planner and tetrahedral geometry, respectively while 1:2 metal-ligand ratio in the Cu(II), Cr(III), Mn(II), Zn(II), Ru(III)and Rh(III)complexes

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Publication Date
Wed Apr 01 2020
Journal Name
Applied Acoustics
Wideband sound absorption of a double-layer microperforated panel with inhomogeneous perforation
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Micro-perforated panel (MPP) absorber is increasingly gaining popularity as an alternative sound absorber in buildings compared to the well-known synthetic porous materials. A single MPP has a typical feature of a Helmholtz resonator with a high amplitude of absorption but a narrow absorption frequency bandwidth. To improve the bandwidth, a single MPP can be cascaded with another single MPP to form a double-layer MPP. This paper proposes the introduction of inhomogeneous perforation in the double-layer MPP system (DL-iMPP) to enhance the absorption bandwidth of a double-layer MPP. Mathematical models are proposed using the equivalent electrical circuit model and are validated with experiments with good agreement. It is revealed that the DL-

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Publication Date
Tue Aug 01 2017
Journal Name
International Journal Of Agriculture And Biology
Molecular Characterization of a Leaf Curl Disease Infecting Zucchini Squash in Iraq
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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Exploring the Impact of Petrophysical Uncertainties on Recoverable Reserves: A Case Study
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Reliable estimation of critical parameters such as hydrocarbon pore volume, water saturation, and recovery factor are essential for accurate reserve assessment. The inherent uncertainties associated with these parameters encompass a reasonable range of estimated recoverable volumes for single accumulations or projects. Incorporating this uncertainty range allows for a comprehensive understanding of potential outcomes and associated risks. In this study, we focus on the oil field located in the northern part of Iraq and employ a Monte Carlo based petrophysical uncertainty modeling approach. This method systematically considers various sources of error and utilizes effective interpretation techniques. Leveraging the current state of a

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Publication Date
Wed Mar 05 2025
Journal Name
Lecture Notes In Networks And Systems
Leveraging AI for Disaster Management: A Comprehensive Review of Applications and Challenges
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Publication Date
Thu Oct 26 2023
Journal Name
Farmacia
THE DEVELOPMENT OF A BRAIN TARGETED MUCOADHESIVE AMISULPRIDE LOADED NANOSTRUCTURED LIPID CARRIER
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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Removal of Water Turbidity by using Aluminum Filings as a Filter Media
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The ability of using aluminum filings which is locally solid waste was tested as a mono media in gravity rapid filter. The present study was conducted to evaluate the effect of variation of influent water turbidity (10, 20and 30 NTU); flow rate(30, 40, and 60 l/hr) and bed height (30and60)cm on the performance of aluminum filings filter media for 5 hours run time and compare it with the conventional sand filter. The results indicated that aluminum filings filter showed better performance than sand filter in the removal of turbidity and in the reduction of head loss. Results showed that the statistical model developed by the multiple linear regression was proved to be
valid, and it could be used to predict head loss in aluminum filings

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Publication Date
Wed Mar 04 2015
Journal Name
Environmental Earth Sciences
Isotopic study of water resources in a semi-arid region, western Iraq
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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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