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Distribution and Classification of Medicinal Plants in Zakhikhah Area of Al-Anbar Desert
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This study included the Zakhikhah area in the Al- Anbar desert, which it bounded on the north, east, and west by the Euphrates River and on the south by the Ramadi-Qaim road. Several exploratory field trips were taken to the study area. During this time, a semi-detailed area survey was carried out based on satellite imagery captured by American Land sat-7, topographic maps, and natural vegetation variance. All necessary field tools, including a digital camera and GPS device, were brought to determine the soil type and collect plant samples. All of these visits are planned to cover the entire state of Zakhikhah. All vegetation cover observations, identifying sampling sites and attempting to inventory and collect medicinal plants in the study area at all stages were recorded. The reasons for the variation in the distribution of medicinal plants in the Zakhikhah area were also presented in this study concerning their distribution sites. The total number of species collected in all stages, according to the findings of this study, was 12. The most abundant plant was the hibiscus, which accounted for 35.40% of the total area and covered 4210.8 acres. The samples were identified, named, and preserved in the University of Anbar’s College of Education for Pure Sciences/Department of Life Sciences herbarium. How to Cite: Fatin H. Al-Dulaimi, 2023. "Distribution and Classification of Medicinal Plants in Zakhikhah Area of Al-Anbar Desert." Journal of Agriculture and Crops, vol. 9, pp. 257-265.

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Sun Nov 15 2020
Journal Name
Anbar Journal Of Engineering Sciences
Numerical Modelling and Experimental Investigation of Water Distribution in Stratified Soil Under Subsurface Trickle
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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Concentrations, Sources and Distribution of Polycyclic Aromatic Hydrocarbon (PAHs) Compounds in Basrah soils, Iraq
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  Anthropogenic activities cause soil pollution with different serious pollutants, such as polycyclic aromatic hydrocarbon (PAHs) compounds. This study assessed the contamination of PAHs in soil samples collected from 30 sites divided into eight groups (residential areas, oil areas, agricultural areas, roads, petrol stations, power plants, public parks and electrical generators) in Basrah city-Iraq during 2019-2020. The soil characteristics including (moisture, pH, EC and TOC) were measured. Results showed the following ranges (soil moisture (0.03-0.18%),pH (6.90-8.16), EC (2.48-104.80) mS/cm and TOC (9.90-20.50%)). Gas Chromatography (GC) was used to measure PAHs in extracted soil samples. The total PAH range (499.96 - 5864.86) ng/g dr

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Publication Date
Sun Jun 01 2025
Journal Name
Microbial Biosystems
Distribution and association of an usp genotoxin gene with biofilm formation in E. coli
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Uropathogenic specific protein is a genotoxic protein targeting the DNA, leading to mutations and modifications in the normal cell's DNA and subsequently, cancer development. This study aims to determine the prevalence of the usp gene in Uropathogenic Escherichia coli isolated from females with urinary tract infections and study its correlation with biofilm formation. One hundred and five urine specimens were collected from female patients (20 to 55 years old) with urinary tract infections attending hospitals. Traditional laboratory methods using selective and differential culture media were used for initial bacterial isolation and identification, and molecular techniques that targeted a segment of the 16SrRNA gene with a specific primer pa

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Publication Date
Sun Jan 27 2019
Journal Name
Journal Of The College Of Education For Women
The issue of creation of AL-Muatazala and AL-Shaira
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words of God the Quranic text , is genera words have many faces and connotations a ccording to references, cutures and Ages.That the Quranic text is fixed , But the connotations are moveable the scientists agreed about the miracle of the Qurantic text , But they differd of the Position of miracLe including the muatazala and Al- Ashaira who have adopted the idea of sytem and miracle of linguistic . Most of them were lingustics, grammerians and writers as: AL- Jahith, AL- Faraa Abivbeida , Ibn kutaba , AL -Rumani , AL -katabi , AL- Bakilaai , AL- Gargani and Others.
They also differed in what the words of Allaah mean . Is the Quranic text creature or updated ,it is the issue that exhausted the effort.of muslim scientists though its imbo

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Publication Date
Sat Jan 01 2022
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees21gr
Challenges facing the transition of traditional cities to smart: Studying the challenges faced by the transition of a traditional area such as Al-Kadhimiya city center to the smart style
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Challenges facing the transition of traditional cities to smart: Studying the challenges faced by the transition of a traditional area such as Al-Kadhimiya city center to the smart style

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Publication Date
Mon Jan 01 2018
Journal Name
Ultramicroscopy
Characterization of trapped charges distribution in terms of mirror plot curve
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Publication Date
Tue Jun 21 2022
Journal Name
Journal Of Planner And Development
Estimation of Traffic Volumes Distribution of Urban Streets in Baghdad City
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The aim of this research is to explore the time and space distribution of traffic volume demand and investigate its vehicle compositions. The four selected links presented the activity of transportation facilities and different congestion points according to directions. The study area belongs to Al-Rusafa sector in Baghdad city that exhibited higher rate of traffic congestions of working days at peak morning and evening periods due to the different mixed land uses. The obtained results showed that Link (1) from Medical city intersection to Sarafiya intersection, demonstrated the highest traffic volume in both peak time periods morning AM and afternoon PM where the demand exceeds the capacity along the link corridor. Also, higher values f

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Distribution of Some Heavy Metals in Tigris River middle of Iraq
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This study was conducted from February 2010 to December 2010. Water Samples were collected every two months in three stations in Baghdad city. The study involved the assessment of concentrations of some heavy metals such as: Chromium, Cadmium, Copper, Iron, Lead, Manganese, Nickel and Zinc. the values of chromium were undetected for the entire of the study, while the rest of the heavy metal were ranged between 0.001 -0.438 mg / l, ND -0.077 mg / L, ND -0.778 mg / l, 0.36 - 0.011 mg / l, 0.011-0 .08mg/ l, ND - 0.1985 mg / l, ND -0.0416 mg / l, respectively. The results showed that the concentrations of heavy metals were fluctuated during the study period, except Lead which have high concentrations and exceeded the permit limits in all statio

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Using Fuzzy Clustering to Detect the Tumor Area in Stomach Medical Images
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Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t

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