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bsj-547
The relation between some of phenotype characteristics of corn and infection by corn stem borer Sesamia cretica.
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This study was conducted to know the effect of some phenotype characteristics of corn plant on infection by (CSB), using 13 genotypes of corn plant, planting during autumn season 1997 and 1998. The result revealed that the mean of plant height (with male flowering) was (183-219) cm, the mean of leaf No./ plant in all genotypes was (16-18) leaf but the leaf area of plant was (4350-6249) cm2, there were significant differences of phenotype characteristics between genotypes ,the percentage of infection by (CSB) was (5.9-35.9),% the result showed that the phenotype characteristics had non effect on the infection percentage by (CSB) and the correlation coefficient was not significant.

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Improvement of Earth Canals Constructed on Gypseous Soil by Soil Cement Mixture
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The gypseous soil may be one of the problems that face the engineers especially when it used as a foundation for hydraulic structures, roads, and other structures. Gypseous soil is strong soil and has good properties when it is dry, but the problem arises when building hydraulic installations or heavy buildings on this soil after wetting the water to the soil by raising the water table level from any source or from rainfall which leads to dissolve the gypsum content.

Cement-stabilized soil has been successfully used as a facing or lining for earth channel, highway embankments and drainage ditches to reduce the risk of erosion and collapsibility of soil. This study is deliberate the treatment of gypseous soil by u

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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Genotypic Variations of Mutans Streptococci Isolated from Dental Caries by REP-PCR
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Mutans streptococci (MS) are a group of oral bacteria considered as the main cariogenic organisms. MS consists of several species of genus Streptococcus which are sharing similar phenotypes and genotypes. The aim of this study is to determine the genetic diversity of the core species of clinical strains of Streptococcus mutans, Streptococcus sobrinus and Streptococcus downei by using repitative extragenic palindromic (REP) primer. The DNA of the clinical strains of S. mutans (n=10), S. sobrinus (n=05) and S. downei (n=04) have been employed in the present study, which have been previously isolated from caries active subjects. The DNA of the clinical and reference strains was

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Publication Date
Sun Apr 02 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
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Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Colloid And Interface Science
Removal of monoethylene glycol from wastewater by using Zr-metal organic frameworks
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Publication Date
Tue Feb 01 2022
Journal Name
Case Studies In Thermal Engineering
Robust composite temperature control of electrical tube furnaces by using disturbance observer
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As one type of resistance furnace, the electrical tube furnace (ETF) typically experiences input noise, measurement noise, system uncertainties, unmodeled dynamics and external disturbances, which significantly degrade its temperature control performance. To provide precise, and robust temperature tracking performance for the ETF, a robust composite control (RCC) method is proposed in this paper. The overall RCC method consists of four elements: First, the mathematical model of the ETF system is deduced, then a state feedback control (SFC) is constructed. Third, a novel disturbance observer (DO) is designed to estimate the lumped disturbance with one observer parameter. Moreover, the stability of the closed loop system including controller

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Enhancement of Electron Temperature under Dense Homogenous Plasma by Pulsed Laser Beam
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The applications of hot plasma are many and numerous applications require high values of the temperature of the electrons within the plasma region. Improving electron temperature values is one of the important processes for using this specification in plasma for being adopted in several modern applications such as nuclear fusion, plating operations and in industrial applications. In this work, theoretical computations were performed to enhance electron temperature under dense homogeneous plasma. The effect of   power and duration time of pulsed Nd:YAG laser   was studied on the heating of   plasmas  by inverse bremsstrahlung  for  several values for the electron density ratio. There results for these ca

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Publication Date
Fri Dec 07 2018
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Effects of Aldosterone, Osteoprotegerin and Fibroblast Growth Factor-23 and Some Biochemical Markers in Chronic Kidney Disease Patients (Stage II-IV) among Patients with or without Cardiovascular Events
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Chronic Kidney Disease (CKD) is a public health problem and many studies support the link between kidney dysfunction and cardiovascular events.  Aldosterone has been shown for decades that a plasma aldosterone concentration is elevated in CKD. Whilst, Osteoprotegerin (OPG), after its capacity to protect bone, also osteoprotegerin is elevated in patients with chronic kidney disease (CKD), where it could predict the deterioration of kidney function, cardiovascular, vascular events and all-cause mortality. On the other hand, fibroblast growth factors (FGFs), in patients with CKD, its levels seem to increase progressively as kidney function worsens. The aim of the present study is to assess the correlations between serum osteoprotegerin

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Global Pharma Technology,
Doppler study and cell free DNA biomarkers by using PCR in hypertensive and diabetic pregnant iraqi women
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Publication Date
Sat Mar 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Caffeine Extraction from Spent Coffee Grounds by Solid-liquid and Ultrasound-assisted Extraction: Kinetic and Thermodynamic Study
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Coffee is the most essential drink today, aside from water, the high consumption of coffee and the byproducts of its soluble industries such as spent coffee grounds can have a negative effect on the environment as a source of toxic organic compounds. Therefore, caffeine removal from the spent coffee ground can be applied as a method to limit the effect of its production on the environment. The aim of this study is to determine the kinetics and thermodynamics parameters and develop models for both processes based on the process parameters by using traditional solid-liquid extraction and Ultrasound-assisted extraction methods. The processes were performed at a temperature range of 25 to 55 °C for traditional and ultrasound baths, and

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