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Performance Evaluation of field and genetic for genotype selection from Tomato Lycopersicon esculeuntum Mill.
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The study was conducted at the fields of the Department of Horticulture and Landscape Gardening,College of Agriculture, University of Baghdad during the growing seasons of 2013- 2014 .forPerformance of Evaluation Vegetative growth and yield traits and estimate some important geneticparameter on seven selected breed of tomato which (S1-S7 ) Pure line. the results found significantdifferences between breeds in all study trails except clusters flowering number .S1 significantly plantlength which reached 227.3 .Also S1,S2 and S4 were significantly increased the number fruit for plant,Fruit weight Increased in S3 ,S6 and plant yield. Increased in S1, S4 ,S5. Genetic variation valueswere low in Floral clusters , TSS and fruit firmest and medium in Stem diameter . and high in therest of traits .Percentage of inheritance in the broad sense was height ,in all traits except Floral clustersand fruit firmest 8.41%, 33.10% respectively and the environmental variation was higher than geneticvariation in this two traits. while phenotype variation values were low in TSS and fruit ferment andhigh in the rest of the study traits. Analysis Hierarchical clustering showed the Average convergencebreeds S3 and S6 also between S2 and S4 While diverged between S1, S5, S7.

Publication Date
Sun Mar 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Employment of the genetic algorithm in some methods of estimating survival function with application
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Intended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted

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Publication Date
Tue Dec 19 2017
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm
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In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad.  One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process.

The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and a

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Publication Date
Tue Jul 06 2021
Journal Name
Animals
Comparison of the Genetic Structure of Invasive Bigheaded Carp (Hypophthalmichthys spp.) Populations in Central-European Lacustrine and Riverine Habitats
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Bigheaded carps (bighead carp, Hypophthalmichthys molitrix, and silver carp, Hypophthalmichthys nobilis) and their hybrids play an important ecological and economic role in their original habitat, while their introduced stocks may pose serious ecological risks. To address questions about the persistence and invasiveness of these fish, we need to better understand their population structures. The genetic structures of bigheaded carp populations inhabiting Lake Balaton and the Tisza River were examined with ten microsatellite markers and a mitochondrial DNA marker (COI). The Lake Balaton stock showed higher genetic diversity compared with the Tisza River stock. Based on hierarchical clustering, the Tisza population was characterized o

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Publication Date
Fri Mar 01 2024
Journal Name
Results In Engineering
Experimental and analytical study of the energy and exergy performance for different evaporative pads in hot and dry climate
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In this work, effects of using different evaporative cooling pads (ECPs) on the energetic and exergetic efficiency of a direct evaporative air cooler (DEAC) have been theoretically and experimentally investigated. Three types of ECPs were used, i.e., honeycomb cellulose cooler pad (HCCP), shading-cloth cooler pad (SCCP), and aspen wood wool cooler pad (AWWCP). For SCCP and AWWCP, a 3-cm pad thickness was used, while for the HCCP, three different values of pad thickness were used, i.e., 3, 5, and 7 cm. Tests were carried out using air velocities of 8, 14, and 19 m/s, measured at the DEAC outlet. Engineering equation solver (EES) used for performing the required calculations of the various parameters affecting the thermal performance of the D

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Publication Date
Wed Jun 21 2023
Journal Name
Bionanoscience
Evaluation the Antimicrobial Action of Kiwifruit Zinc Oxide Nanoparticles Against Staphylococcus aureus Isolated from Cosmetics Tools
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Publication Date
Sun Sep 30 2001
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Study the Characteristic Performance of Trickling Filter for Pharmaceutical Waste Treatment
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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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Publication Date
Fri Aug 18 2023
Journal Name
Pharmacia
Synthesis, characterization, and antimicrobial evaluation of new Schiff bases derived from vanillic acid conjugated to heterocyclic 4H-1,2,4-triazole-3-thiol
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A multistep synthesis was established for the preparation of a new vanillic acid-1, 2, 4-1triazole-3-thiol conjugate (4). Finally, several aromatized aldehydes reacted with compound (4) to produce Schiff bases derivatives (5–11). The purpose of this research is to prepare new vanillic acid derivatives with 1, 2, 4-triazole-3-thiol heterocyclic ring structures and to evaluate their antimicrobial activity in a preliminary assessment. Fourier-transform infrared (FT-IR) and proton nuclear magnetic resonance spectroscopy (1H-NMR) were used to verify the structures of the newly synthesized compounds. all the final synthesized compounds (

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Evaluation of Amygdalin (B17) and Cucurbita pepo (Pumpkin seed) Activity Against Blastocystis from Diarrheic Patients in Baghdad, Iraq: in Vitro Study
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Blastocystis is a ubiquitous human and animal protozoa that inhabit the gastrointestinal tract. Metronidazole is considered the standard drug for the treatment of Blastocystis infection; however, there is growing evidence of treatment failure, hazardous side effects, and appearance of strains resistant to metronidazole. In the last era, many studies have been implicated in the quest for new treatments for Blastocystis infection, especially natural products. Attention has been focused on the effect of Amygdalin (B17) and pumpkin seed on eradicating parasitic infections. The current work was built up to explore the in vitro efficacy of two natural compounds, Amygdalin (B17) and pumpkin seeds against

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Publication Date
Mon Jul 28 2025
Journal Name
Applied Physics Letters
Theoretical defect engineering in AgBiI4 for enhanced photovoltaic performance
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Silver-bismuth iodide (ABI) ternary semiconductors, such as AgBi2I7, AgBiI4, Ag2BiI5, and Ag3BiI6, have emerged as promising lead-free light absorbers for photovoltaic applications due to their favorable optoelectronic properties. Despite recent advances that have improved power conversion efficiencies from ∼1% to over 5%, ABI-based solar cells still show substantial open-circuit voltage (VOC) losses of up to ∼1 V, which significantly hinder the device performance. These losses have been experimentally attributed to the non-radiative recombination originating from intrinsic defects, however, theoretical understanding of these defect mechanisms remains limited. Here, using density functional theory calculations, we systematical

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