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Improving Water Use Efficiency and Water Productivity for Okra Crop by using Subsurface Water Retention Technology
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Utilizing the modern technologies in agriculture such as subsurface water retention techniques were developed to improve water storage capacities in the root zone depth. Moreover, this technique was maximizing the reduction in irrigation losses and increasing the water use efficiency. In this paper, a polyethylene membrane was installed within the root zone of okra crop through the spring growing season 2017 inside the greenhouse to improve water use efficiency and water productivity of okra crop. The research work was conducted in the field located in the north of Babylon Governorate in Sadat Al Hindiya Township seventy-eight kilometers from Baghdad city. Three treatments plots were used for the comparison using surface trickle irrigation system: Polyethylene sheet (SWRT) was used in plot T1, controlled irrigation in plot T2 and uncontrolled irrigation in plot T3. Irrigation quantities, time of irrigation, soil water contents were measured for all treatments plots. The results indicated that water use efficiency for the three experimental plots, T1, T2, and T3 were: 2.43, 1.94 and 0.98 kg/m3, respectively.  The increasing value in water use efficiency of T1 plot compared with T2 and T3 plots were 25 and 148 %, respectively. Additionally, the water productivity of okra crop for T1, T2, and T3 plots was: 12800.9, 8744.8, and 4736.3 ID/m3, respectively. The increasing value of the water productivity of T1 compared with plots T2 and T3 was 46 and 170 %, respectively. From this study, the benefit of using membrane sheet below the soil surface resulted in an increase in the value of yield, water use efficiency and water productivity. Moreover, saving water and reduced the water losses by deep percolation were resulted.   

  

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Publication Date
Sun Jan 14 2024
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
Using Nonparametric Procedure to Develop an OCMT Estimator for Big Data Linear Regression Model with Application Chemical Pollution in the Tigris River
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Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Pharmaceutical Research
New method for the evaluation of propranolol with phosphotungstic acidvialong distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis
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A new, simple and sensitive method was used forevaluation of propranolol withphosphotungstic acidto prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on reaction between propranolol and phosphotungstic acid in an aqueous medium to obtain a yellow precipitate. Optimum parameters was studied to increase the sensitivity for developed method. A linear range for calibration graph was 0.007-13 mmol/L for cell A and 5-15 mmol/L for cell B, and LOD 207.4792 ng/160 µL and 1.2449 µg/160 µL respectively to cell A and cell B with correlation coefficient (r) 0.9988 for cell A, 0.9996 for cell B, RSD% was lower than 1%, (n=8) for the

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Publication Date
Sun Mar 18 2018
Journal Name
Https://www.iasj.net/iasj/article/170012#:~:text=al.qadisiya%20journal%20for%20the%20sciences%20of%20physical%20education
The Effect Of Using Two Strategies For Active Learning ( Jigsaw Strategy & Problems Solving) In Learning Some Balanced Beam's Skills In Artistic Gymnastics
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The aim of this study to identify the effect of using two strategies for active learning ( Jigsaw Strategy & Problems Solving) in learning some balanced beam's skills in artistic gymnastics for women , as well as to identify the best of the three methods (jigsaw strategy , problems solving and the traditional method) in learning some skills balance beam , the research has used the experimental methodology, and the subject included the students of the college of Physical Education and Sports Sciences / University of Baghdad / third grade and by the lot was selected (10) students for each group of groups Search three and The statistical package for social sciences (SPSS) was used means, the standard deviation and the (T.test), the one way a n

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Publication Date
Wed Jan 01 2020
Journal Name
Materials Chemistry And Physics
Natural dye extracted from Areca catechu fruits as a new sensitiser for dye-sensitised solar cell fabrication: Optimisation using D-Optimal design
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Sport Sciences
The effect of using the McCarthy model according to cognitive style (rigid- flexibility) in learning some skills in artistic gymnastics for women
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The aim of the research is to identify the cognitive method (rigidity flexibility) of third-stage students in the collage of Physical Education and Sports Sciences at The University of Baghdad, as well as to recognize the impact of using the McCarthy model in learning some of skills in gymnastics, as well as to identify the best groups in learning skills, the experimental curriculum was used to design equal groups with pre test and post test and the research community was identified by third-stage students in academic year (2020-2021), the subject was randomly selected two divisions after which the measure of cognitive method was distributed to the sample, so the subject (32) students were distributed in four groups, and which the pre te

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Hydrogen Energy
Improvement of bioenergy generation using innovative application of food waste materials for coating carbon nanotubes-loaded bioanode in 3D-microbial fuel cells
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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

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Publication Date
Thu Feb 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Qualitative and Quantitative Estimation or Chemical Constituents from Leaves and Roots of Iraqi Agave Attenuata by GC-MS and RP-HPLC(Conference Paper) #
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This research concentrate on cultivated Iraqi Agave attenuata dried leaves and roots, because of little studies on this plant especially on the root that lead to the eager of study and comparison of phytochemical constituents between leaves and root. Extraction of bioactive constituents was carried out using several solvents with increasing polarity (n-hexane, ethyl acetate and methanol) by soxhlet apparatus. Steroidal saponins in Agave genus is well documented in many species, lightening the minds in this research on extraction method which is specific for steroidal saponins. Phytochemical screening was done by GC/MS for n-hexane fraction, qualitative and quantitative estimation of several bioactive constituents (caffe

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