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Detection and biocontrol of Tobamovirus tabaci infecting tomato in Iraq
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The antiviral activity of leaf extracts from Datura stramonium and tomato plants inoculated with TMV, combined with 20% skimmed milk, was investigated. A TMV isolate was confirmed using bioassay, serological, and molecular approaches and subsequently used to inoculate plants. Tomato plants, both pre- and post-inoculated with TMV, were sprayed with leaf extracts from either TMV-free or infected plants, alone or mixed with 20% skimmed milk. Enzyme-linked immunosorbent assay (ELISA) using tobamovirus-specific antibodies and local lesion tests were conducted to assess antiviral activity based on virus concentration and infectivity in treated plants. The experiment followed a completely randomized design (CRD), and the Least Significant Difference (LSD) test was applied to evaluate ELISA optical density (OD) values. OD data revealed that the combination treatment (inoculated tomato leaf extract + 20% skimmed milk) inhibited TMV in tomato plants by up to 56%, showing the highest antiviral activity. This study is the first to investigate the antiviral potential of leaf extracts from TMV-infected plants.

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
Calculation of Salinity and Soil Moisture indices in south of Iraq - Using Satellite Image Data
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A band rationing method is applied to calculate the salinity index (SI) and Normalized Multi-Band Drought Index (NMDI) as pre-processing to take Agriculture decision in these areas is presented. To separate the land from other features that exist in the scene, the classical classification method (Maximum likelihood classification) is used by classified the study area to multi classes (Healthy vegetation (HV), Grasslands (GL), Water (W), Urban (U), Bare Soil (BS)). A Landsat 8 satellite image of an area in the south of Iraq are used, where the land cover is classified according to indicator ranges for each (SI) and (NMDI).

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
The effect of unsecured use of chemical pesticides on the environment and health in Iraq
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The wide use of pesticides in recent years leads to rapid distribution of these pollutants in the environment (air, water and soil).They were transported by means of air or water to biological ecosystems. They become more toxic through the processes of biological magnification while some of them persist for along period.The aim of this work is to show the negative effect that chemical pesticides causes, and in the same to show their side effect on the environment and health in Iraq. We could conclude that the bad use of these chemicals could cause an urgent impact now or in the future. Governmental offices dealing with these materials should take the right measures to minimize the danger and the misuse of these chemicals by seeking alternat

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Publication Date
Wed Mar 15 2023
Journal Name
Bionatura
Isolation and identification of intestinal parasites from Goats in some areas of Wasit Province, Iraq
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The current study was conducted on goats in various parts of Wasit Province, Iraq, from November 2021 to April 2022. The study aims to find and identify intestinal parasites (IPs) in goats in Wasit province. The goat's fresh fecal specimens (n=180) include cysts, eggs, oocysts, trophozoites and larval stages. One hundred eighty sheep feces samples were collected, and more than one parasite was isolated from one sample (mixed infection). According to the data acquired, the overall prevalence of intestinal parasites in goats was 52.77 (95 samples). In the current investigation, eleven distinct (IPs) species with infection rates were identified, including Toxocara vitulorum (Goeze, 1782) (16.66 %), Cryptosporidium sp.( Tyzzer, 1907) (1

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Publication Date
Mon Apr 01 2019
Journal Name
Plant Archives
Surface epidermis of leaf and indumentum for five species of the genus Galium in Iraq
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The current investigation included study of leaf surface epidermis beside indumentum for the species Galium aparine L., G. ceratopodum Boiss, G. setaceum Lam., G. spurium L., and G. tricornatum Dandy, the study showed that paracytic type of stomatal complex is the only type occur in leaf. The indumentum compose of eglandular hairs vary in their apices, length and occurrence of different part of plant body

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Publication Date
Fri Dec 01 2017
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
HOST PLANTS AND DISTRIBUTION OF SOME WHITEFLIES SPECIES (HEMIPTERA, ALEYRODIDAE) IN THE MIDDLE OF IRAQ
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    Ten species of whiteflies (Hemiptera, Aleyrodidae) representing six genera were studied from a collection from different localities in the middle of Iraq. These species are Acaudaleyrodes rachipora (Singh, 1931); Bemisia afer  (Priesner and Hosny,1934); Bemisia tabaci (Gennadius, 1889); Dialeurodes citri (Ashmead,1885); Dialeurodes kirkaldy (Kotinsky, 1907); Neomaskellia andropogonis Corbett, 1926;  Siphoninus phillyreae (Haliday, 1835); Trialeurodes ricini (Misra, 1924); Trialeurodes vapovariorum (Westwood,1856) and Trialeurodes irakeensis (Al-Malo and Abdul-Rassoul, 2000). Notes are given on their localities, date of c

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Publication Date
Wed Oct 10 2018
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
TWO NEW RECORDS OF DWARF SNAKES OF THE GENUS EIRENIS JAN, (REPTTILIA, COLUBRIDAE) IN IRAQI KURDISTAN (NORTH AND NORTHEASTERN OF IRAQ) WITH ANNOTATED CHECKLIST, FOR THE GENUS EIRENIS IN IRAQ
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    Two dwarf snakes were discovered, Eirenis thospitis Schmidtler & Lanza from Sereen mountain, north east of Arbil  and E. rothii Jan from Saffin mountain North of Arbil  city  North of Iraqi Kurdistan. Supported by description and important notes on variation. In addition summarized list for 9 species of the genus Eirenis Jan in Iraq is also presented.  

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Publication Date
Mon Apr 19 2010
Journal Name
Computer And Information Science
Quantitative Detection of Left Ventricular Wall Motion Abnormality by Two-Dimensional Echocardiography
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Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

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Publication Date
Sun May 11 2014
Journal Name
World Journal Of Experimental Biosciences
Detection of hydrolytic enzymes produced by Azospirillum brasiliense isolated from root soil
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Publication Date
Wed Jun 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Haemoglobin Epsilon as a Biomarker for the Molecular Detection of Canine ‎Lymphoma
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Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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