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The Water Footprint and Virtual Water and Their Effect on Food Security in Iraq
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Abstract<p>The study aimed to explaining the concepts of water footprint and virtual water and how these two concepts could use to achieve water savings at the local level to meet the water supply deficit in Iraq, which is expected to increase in the coming years and influence of that on food security in Iraq by using these concepts when drawing production, irrigated and import plans in Iraq. The study aimed to studying the water footprint and virtual water and their impact on the foreign trade for wheat and rice crops during the period 2000-2022 and estimating the most important indicators of virtual water and the water footprint of the study crops due to the importance of these criteria in determining the amount of increase or decrease in the area of the studied crops, according to the foreign trade policy. This study was concluded that the average total water footprint of the wheat and rice crops during the study period is (20.27,13.89) billion m3 respectively, and the average percentage of dependence on external water resources for both crops are (20.49%,67.98%) respectively, and the average percentage of self-sufficiency in water resources are (79.51%,32.01%) respectively, and the average unit productivity of irrigation water for both crops is (0.19,0.10) kg/m3 respectively during 2000-2022.The average for the water needs of wheat and rice crops during the study period were (6.04,10.19) m3/kg respectively, the average amounts of water used in local production for both crops are (14.23,4.01) billion m3 respectively, the average amounts of virtual water imported for both crops are (6.19,10.03) billion m3 respectively, and the average value of the imported virtual water for both crops is (382,529) thousand dollars during the period 2000-2022. The study recommended to taking in account these concepts in plans of production and distributing irrigation water.</p>
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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Increasing of Some Medical Flavonoid Compounds of Dodonaea viscosa L. using AgNO3 Nanoparticles In Vitro
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The research was conducted to study the effect of adding different concentrations of AgNo3 Nanoparticles (0,0.5,1.0,1.5,2.0) mg/ l in the production of some secondary metabolic compounds(Quercetin, Luetolin and Apigenin) of plant Dodonaea viscosa L. Quantitative and qualitative analysis of secondary metabolites were estimated by using( HPLC ). The explants from leaves were culture on MS media supplemented with 2mg/l of 2,4-D, 0.5mg/l of NAA and 0.5 mg/l of BA for callus induction. Adding AgNo3 Nanoparticles (2 mg/l) cause in significant increase of Quercetin and Luetolin production, while adding AgNo3 Nanoparticles (0.5mg/l) led to significant increase of Apigenin in callus extract.

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Publication Date
Sun Aug 24 2014
Journal Name
Wireless Personal Communications
Multi-layer Genetic Algorithm for Maximum Disjoint Reliable Set Covers Problem in Wireless Sensor Networks
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Publication Date
Wed May 11 2022
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Some Methods For A single Imputed A missing Observation In Estimating Nonparametric Regression Function
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In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

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Publication Date
Fri Jan 01 2016
Journal Name
Computational Intelligence And Neuroscience
A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)
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This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl

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Publication Date
Mon Jan 01 2018
Journal Name
Ndt &amp; E International
Porosity evaluation of in-service thermal barrier coated turbine blades using a microwave nondestructive technique
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Publication Date
Wed Jul 29 2020
Journal Name
Iraqi Journal Of Science
Use of Two Aquatic Snail Species as Bioindicators of Heavy Metals in Tigris River-Baghdad
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     Thirty individuals of Bellamya bengalensis and Physella acuta were collected and identified from the Tigris River in Baghdad during the period between October to November 2017. The efficiency of bioaccumulation of the two species as bioindicators for aquatic heavy metal pollution with Cd, Ni, Pb and Cu was investigated. Both snail species had the ability to accumulate heavy metals. The mean of Ni concentration in soft tissues of both snails was 1.53 ppm while the mean concentration of other heavy metals was significantly lower; they reached 0.51 ppm, 0.36 ppm and 0.29 ppm, respectively. While no significant differences between B. bengalensis and  P.acuta were noticed in th

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Publication Date
Thu Dec 05 2019
Journal Name
Advances In Intelligent Systems And Computing
An Enhanced Evolutionary Algorithm for Detecting Complexes in Protein Interaction Networks with Heuristic Biological Operator
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Publication Date
Sun Jun 05 2022
Journal Name
Network
A Computationally Efficient Gradient Algorithm for Downlink Training Sequence Optimization in FDD Massive MIMO Systems
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Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve

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Publication Date
Wed Jan 01 2020
Journal Name
2nd International Conference On Materials Engineering &amp; Science (iconmeas 2019)
A kinetic model for prodigiosin production by Serratia marcescens as a bio-colorant in bioreactor
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Publication Date
Mon Jan 28 2019
Journal Name
Soft Computing
Bio-inspired multi-objective algorithms for connected set K-covers problem in wireless sensor networks
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