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Genetic Analysis by Using Partial Diallel Crossing of Maize In High Plant Densities (Estimation GCA, SCA and Some Genetic Parameters)
Abstract<p>The experiment was carried out at the Field Crops Research Station, College of Agricultural Engineering Sciences - University of Baghdad in Jadiriyah, with the aim of evaluating the performance of partial diallel hybrids and inbred lines of maize and estimating general combining ability(GCA), specific combining ability (SCA) and some genetic parameters. The experiment was carried out in two seasons, spring and fall 2020. Eight inbred lines of maize were used in the study (BI9/834, BSW18, LW/5 L8/844, ZA17W194, Z117W, ZI17W9, ZI7W4), numbered (1,2,3,4,5,6,7,8), It was sowed in the spring season and entered into a cross-program according to a partial diallel crossing system to obtain twelve partially cross-hybrids, and it was compared with its eight parents in a comparison experiment in the fall season using a Randomized Complete Block Design (RCBD) with split plots arrangement with three replication. The plant densities of 70 and 90 thousand plants ha<sup>-1</sup> represented the main plots, while the partial diallel hybrids and their parents represented the secondary plots. The results of the study showed that the ratio between GCA and SCA) GCA/SCA) It was more than 1 for yield traits, ear length, number of rows and number of row grains in both low and high densities, which indicates the control of the additive genetic action on these traits. While the ratio was less than one for the traits of the ear diameter under the low density, which indicates the control of dominance genes on this trait in the mentioned density, while the trait of the number of ear grains, the ratio between the general and specific combining abilities was less than one in the high density. Inbred line 8 had the highest effect for the general ability to combine under low density, which amounted to 11.075, while inbred line 2 was superior by giving the highest effect to the general ability to combine at low density, which amounted to 17.80, followed by inbred 8.</p>
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Publication Date
Wed Aug 01 2018
Journal Name
Parasitology International
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Publication Date
Sun Dec 29 2019
Journal Name
Iraqi Journal Of Science
Genetic Polymorphisms rs643627 in Serotonin Receptor Gene (5-HTR2A) with Schizophrenia

Schizophrenia(SCZ) is oneof the most destructive and complicated chronic diseases of the human nervous system. Serotonin receptors have been involved in the pathophysiology of psychiatric disorders including schizophrenia. Fortyschizophrenia subjects (14females and 26 males) with an age range of 23– 57 years were enrolled, in addition to twenty healthy control subjects (10female and 10 male) with an age range of 19-44 years.

This study aimed to evaluate the frequency of one single nucleotide polymorphism (SNP), namelyrs643627 in HTR2Agene,inIraqi patients with schizophrenia in comparison with controls, along with the association between this SNP and the incidence of schizophrenia.

The genetic variantrs6436

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Publication Date
Mon Jul 31 2023
Journal Name
Iraqi Geological Journal
Estimation of the Fracturing Parameters and Reservoir Permeability Using Diagnostic Fracturing Injection Test

The term "tight reservoir" is commonly used to refer to reservoirs with low permeability. Tight oil reservoirs have caused worry owing to its considerable influence upon oil output throughout the petroleum sector. As a result of its low permeability, producing from tight reservoirs presents numerous challenges. Because of their low permeability, producing from tight reservoirs is faced with a variety of difficulties. The research aim is to performing hydraulic fracturing treatment in single vertical well in order to study the possibility of fracking in the Saady reservoir. Iraq's Halfaya oil field's Saady B reservoir is the most important tight reservoir. The diagnostic fracture injection test is determined for HF55using GOHFER soft

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Publication Date
Wed Aug 31 2022
Journal Name
Iraqi Journal Of Science
Generating Streams of Random Key Based on Image Chaos and Genetic Algorithm

    Today the Genetic Algorithm (GA) tops all the standard algorithms in solving complex nonlinear equations based on the laws of nature. However, permute convergence is considered one of the most significant drawbacks of GA, which is known as increasing the number of iterations needed to achieve a global optimum. To address this shortcoming, this paper proposes a new GA based on chaotic systems. In GA processes, we use the logistic map and the Linear Feedback Shift Register (LFSR) to generate chaotic values to use instead of each step requiring random values. The Chaos Genetic Algorithm (CGA) avoids local convergence more frequently than the traditional GA due to its diversity. The concept is using chaotic sequences with LFSR to gene

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Engineering
OPTIMAL DESIGN OF MODERATE THICK LAMINATED COMPOSITE PLATES UNDER STATIC CONSTRAINTS USING REAL CODING GENETIC ALGORITHM

The objective of the current research is to find an optimum design of hybrid laminated moderate thick composite plates with static constraint. The stacking sequence and ply angle is required for optimization to achieve minimum deflection for hybrid laminated composite plates consist of glass and carbon long fibers reinforcements that impeded in epoxy matrix with known plates dimension and loading. The analysis of plate is by adopting the first-order shear deformation theory and using Navier's solution with Genetic Algorithm to approach the current objective. A program written with MATLAB to find best stacking sequence and ply angles that give minimum deflection, and the results comparing with ANSYS.

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Optimal Location of Static Synchronous Compensator (STATCOM) for IEEE 5-Bus Standard System Using Genetic Algorithm

Heuristic approaches are traditionally applied to find the optimal size and optimal location of Flexible AC Transmission Systems (FACTS) devices in power systems. Genetic Algorithm (GA) technique has been applied to solve power engineering optimization problems giving better results than classical methods. This paper shows the application of GA for optimal sizing and allocation of a Static Compensator (STATCOM) in a power system. STATCOM devices used to increase transmission systems capacity and enhance voltage stability by regulate the voltages at its terminal by controlling the amount of reactive power injected into or absorbed from the power system. IEEE 5-bus standard system is used as an example to illustrate the te

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
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Publication Date
Tue Nov 19 2024
Journal Name
Al-rafidain University College For Sciences
“Simple Regression Analysis by using Linear Programming Technique and illustration of Absolute Residuals method with another Estimation Techniques”

This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to

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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Journal Of Science
A Genetic Algorithm for Task Allocation Problem in the Internet of Things

In the last few years, the Internet of Things (IoT) is gaining remarkable attention in both academic and industrial worlds. The main goal of the IoT is laying on describing everyday objects with different capabilities in an interconnected fashion to the Internet to share resources and to carry out the assigned tasks. Most of the IoT objects are heterogeneous in terms of the amount of energy, processing ability, memory storage, etc. However, one of the most important challenges facing the IoT networks is the energy-efficient task allocation. An efficient task allocation protocol in the IoT network should ensure the fair and efficient distribution of resources for all objects to collaborate dynamically with limited energy. The canonical de

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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Journal Of Science
A Genetic Algorithm for Task Allocation Problem in the Internet of Things

In the last few years, the Internet of Things (IoT) is gaining remarkable attention in both academic and industrial worlds. The main goal of the IoT is laying on describing everyday objects with different capabilities in an interconnected fashion to the Internet to share resources and to carry out the assigned tasks. Most of the IoT objects are heterogeneous in terms of the amount of energy, processing ability, memory storage, etc. However, one of the most important challenges facing the IoT networks is the energy-efficient task allocation. An efficient task allocation protocol in the IoT network should ensure the fair and efficient distribution of resources for all objects to collaborate dynamically with limited energy. The canonic

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