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Detection of charcoal rot (Macrophomina phaseolina) toxin effects in soybean (Glycine max) seedlings using hyperspectral spectroscopy
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Publication Date
Mon Mar 15 2021
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of an Educational Program on Nursing Staffs' Knowledge about Uses of Steroids and Their Side Effects in Al-Diwaniya Teaching hospital
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Objective: To determine the effectiveness of the educational program on nursing staffs' knowledge about uses of steroids and their side effects.
Methodology: A pre-experimental study design (one group design: pre-test and post-test) was used. This study was conducted in Al-Diwaniya Teaching Hospital for the period from ( 28th May to 10 th June, 2020) on a non-probability (purposive) sample consisting of (30 nurses) working in Oncology unit. A questionnaire was built as a data collection tool and consisted of two parts:
First part: The demographic characteristics of the nursing staff (gender, age, level of education, years of experience in hospital, participation in training courses related to nursing care for a patients undergoing

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Publication Date
Wed Jan 01 2020
Journal Name
Systematic Reviews In Pharmacy
Anti-Oxidoreductive stress Effects of Iraqi Olea Europaea L. Leaves extract against low double doses of alloxan induced diabetes mellitus in rats
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Olive leaves extract is famous for its antioxidant and protective effects. In this study, the aqueous extract of Iraqi Olea europaea L. Leaves was investigated for its anti-diabetic effects against low double doses of alloxan induced Diabetes Mellitus in rats. Low double doses (75 mg\Kg body weight) of alloxan were injected intraperitoneally at day 1&29 of the experimental period in rats, whereas an aqueous extract of Iraqi Olea europaea L. Leaves was added continuously to their drinking water. Serum malondialdehyde concentration, total oxidative stress and oxidative stress index as oxidoreductive stress biomarker, activities of certain antioxidoreductive stress enzymes (glutathione peroxidase, super oxide dismutase and catalase) and concen

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Publication Date
Wed Jan 01 2020
Journal Name
Systematic Reviews In Pharmacy
Anti-Oxidoreductive stress Effects of Iraqi Olea Europaea L. Leaves Extract against Low Double Doses of Alloxan Induced Diabetes Mellitus in Rats
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Olive leaves extract is famous for its antioxidant and protective effects. In this study, the aqueous extract of Iraqi Olea europaea L. Leaves was investigated for its anti-diabetic effects against low double doses of alloxan induced Diabetes Mellitus in rats. Low double doses (75 mgKg body weight) of alloxan were injected intraperitoneally at day 1&29 of the experimental period in rats, whereas an aqueous extract of Iraqi Olea europaea L. Leaves was added continuously to their drinking water. Serum malondialdehyde concentration, total oxidative stress and oxidative stress index as oxidoreductive stress biomarker, activities of certain anti-oxidoreductive stress enzymes (glutathione peroxidase, super oxide dismutase and catalase) and concen

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Publication Date
Thu May 10 2018
Journal Name
Global Journal Of Health Science; Issn 1916-9736 E-issn 1916-9744
Effects of Biological and Non Biological Agents (Disease Modifying Antirheumatic Drugs) on Bone Mineral Density in a Sample of Rheumatoid Arthritis Patients
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Background: Osteoporosis is an extra-articular complication of rheumatoid arthritis that results in increased risk of fractures and associated morbidity, mortality, and healthcare costs. Objective: To evaluate changes in bone mineral density in a sample of rheumatoid arthritis (RA) patients on biological (anti tumor necrosis factor (TNF) alpha) and non-biological agent disease modifying antirheumatic drugs (DMARDs). Patients and Methods: A cross sectional study enrolled 60 RA patients diagnosed by rheumatologist according to the 2010 American College of Rheumatology/European League Against Rheumatism (2010 ACR/EULAR) classification criteria for RA. Thirty patient on biological agent (anti TNF alpha) and 30 patient on non-biological agent (D

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Publication Date
Fri Apr 30 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
SMS Spam Detection Based on Fuzzy Rules and Binary Particle Swarm Optimization
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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Fast Shot Boundary Detection Based on Separable Moments and Support Vector Machine
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Publication Date
Sat Jan 13 2018
Journal Name
Journal Of Engineering
Producing Coordinate Time Series for Iraq's CORS Site for Detection Geophysical Phenomena
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Global Navigation Satellite Systems (GNSS) have become an integral part of wide range of applications. One of these applications of GNSS is implementation of the cellular phone to locate the position of users and this technology has been employed in social media applications. Moreover, GNSS have been effectively employed in transportation, GIS, mobile satellite communications, and etc. On the other hand, the geomatics sciences use the GNSS for many practical and scientific applications such as surveying and mapping and monitoring, etc.

In this study, the GNSS raw data of ISER CORS, which is located in the North of Iraq, are processed and analyzed to build up coordinate time series for the purpose of detection the

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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