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Determination of essential and trace elements in various vegetables using ICP-MS
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Metal contents in vegetables are interesting because of issues related to food safety and ‎potential health risks. The availability of these metals in the human body ‎may perform many biochemical functions and some of them linked with various diseases at ‎high levels. The current study aimed to evaluate the concentration of various metals in ‎common local consumed vegetables using ICP-MS. The concentrations of metals in vegetables ‎of tarragon, Bay laurel, dill, Syrian mesquite, vine leaves, thymes, arugula, basil, common ‎purslane and parsley of this study were found to be in the range of, 76-778 for Al, 10-333 for B, 4-119 for ‎Ba, ‎2812‎-24645 for Ca, 0.1-0.32 for Co, 201-464 for Fe, 3661-46400 for K, 0.31–‎‎1.53 for Li, 860-14330 for Mg, 16.20-71.5 for Mn, 612-4725 for Na and 15.8-46 µg ‎g-1 for Zn. The results revealed that the concentration of Al, B except in Syrian mesquite, Ba, Ca, ‎Fe, K, Mg and Mn in all analysed vegetables is higher than the recommended value, Li is ‎well-within the safe limit, and Co, Na except in dill, arugula and common purslane, Zn are ‎lower than the recommended intake of these elements. From health point of view, the HQ values for Al, Fe ‎‎(for all vegetables) and Ba (in dill, vine leaves, thymes, arugula, basil, common ‎‎purslane and ‎parsley) were higher than one, indicating potential non-cancer health risk due to exposure to ‎these metals. Furthermore, the HI value for all vegetables was higher than one, indicating ‎potential non-cancer health risk due to long-term exposure to these metals.

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Intelligent Congestion Control of 5G Traffic in SDN using Dual-Spike Neural Network
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Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

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Publication Date
Mon Nov 09 2020
Journal Name
Heat Transfer
Experimental performance of cooling photovoltaic panels using geothermal energy in an arid climate
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Intelligent Congestion Control of 5G Traffic in SDN using Dual-Spike Neural Network
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Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification. Different

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Publication Date
Sat Apr 19 2025
Journal Name
Plos One
Early Detection of Autism Spectrum Disorder in Children Using Different Machine Learning Algorithms
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Abstract<p>Autism spectrum disorder(ASD) is a neurological condition marked by impaired communication abilities, social detachment, and repetitive behaviors in individuals. Global health organization facing difficulties in establishing an effective ASD diagnostic system that facilitates precise analysis and early autism prediction. It is a scientific issue that necessitates resolution. This research presents an approach for the early prediction of children with ASD utilizing significant variables through machine learning (ML) methods. Three stages comprise the suggested technique. First, a 1250-case ASD dataset was identified and preprocessed. Five extremely effective traits with high Pearson c</p> ... Show More
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Publication Date
Thu Mar 20 2025
Journal Name
Tikrit Journal Of Engineering Sciences
Effect of Different Compressor Speeds on the Energy and Exergy of an Automobile Air-Conditioner Using R134a in the Absence and Presence of a Liquid-Suction Heat Exchanger
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Refrigerant R134a has been widely utilized in automotive air conditioning systems (AACSs); R134a has a high global warming potential (GWP) of 1430 despite having zero ozone depletion potential (ODP). Coming refrigeration systems must include refrigerants with low GWP and zero ODP. The aim of this experimental study is to evaluate the thermal performance of an (AAC) with different values of compressor speeds, i.e., (1000, 1700, and 2400 rpm) and two thermal loads, i.e., (500 and 1000 Watt) with the absence and presence of liquid suction heat exchanger (LSHX) using R134a. The results showed that adding LSHX enhanced the COP cycle by 7.18%, 10.7%, and 3.09% for the first, second, and third speed, respectively, at 500 Watt, while the en

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Publication Date
Thu Jun 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Prevalence and localization of the posterior superior alveolar artery in relation to the floor of the maxillary sinus and alveolar crest among sample of Iraqis using computed tomography
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Background: Posterior superior alveolar artery (PSAA) is branch of the maxillary artery. It usually supplies the lateral wall of the sinus and overlying membrane. Evaluation and awareness of the anatomy of maxillary sinus before surgery is crucial to avoid surgical complications. The aim of this study is to examine the prevalence, location of the (PSAA) in relation to the floor of the maxillary sinus and alveolar crest using computerized tomography (CT) scans. Materials and Methods: This study included 180 Iraqi subjects (99 males and 81 females) with age more than 16 years old. CT scans for (right and left) Maxillary sinuses were done for each patient. The information obtained was assessed in a coronal multi planar reconstructions images (

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Publication Date
Tue Oct 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Using Benford’s law to detecting earnings management Application on a sample of listed companies in the Iraqi market for securities
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Abstract

The net profit reported in the annual financial statements of the companies listed in the financial markets, is considered one of the Sources of information relied upon by users of accounting information in making their investment decisions. At the same time be relied upon in calculating the bonus (Incentives) granted to management, therefore the management of companies to manipulate those numbers in order to increase those bonuses associated to earnings, This practices are called earnings management practices. the manipulation in the figures of earnings by management will mislead the users  of financial statements who depend on reported earnings in their deci

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Publication Date
Sun Jan 01 2023
Journal Name
Food Science And Technology
Modelling of inactivation of microorganisms in the process of sterilization using high pressure supercritical fluids
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Publication Date
Wed Feb 15 2023
Journal Name
Full Text Book Of Minar Congress 7
EVALUATING THE CHANGE DETECTION OF(NDVI) FOR BABYLON CITY USING REMOTE SENSING AND GIS TECHNIQUES (2015-2020)
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The normalized difference vegetation index (NDVI) is an effective graphical indicator that can be used to analyze remote sensing measurements using a space platform, in order to investigate the trend of the live green vegetation in the observed target. In this research, the change detection of vegetation in Babylon city was done by tracing the NDVI factor for temporal Landsat satellite images. These images were used and utilized in two different terms: in March 19th in 2015 and March 5th in 2020. The Arc-GIS program ver. 10.7 was adopted to analyze the collected data. The final results indicate a spatial variation in the (NDVI), where it increases from (1666.91 𝑘𝑚2) in 2015 to (1697.01 𝑘𝑚2)) in 2020 between the t

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Publication Date
Fri Dec 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
The Effect of Oral Contraceptive Pill on Cortical Thickness and Bone Mineral Density of The Mandibular Mental and Gonial Regions in Premenopausal Females Using Spiral Computed Tomography
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Background: Prolonged use of low-dose estrogen ''20 micrograms or less" Combined oral contraceptive pill (that have estrogen and progesterone steroid hormone) had an effect on bone turnover .Bone mineral density is used in clinical medicine as an indirect indicator of osteoporosis and fracture risk. The aim of the study: The aim of this study was to investigate the effect of low dose oral contraceptive pill on the cortical thickness (in millimeter) and bone mineral density at the mandibular cortex of mental and gonial regions in Hounsfield unit(HU) using spiral computed tomography. Material and method: This prospective study was conducted on computed tomographic image of 100 women aged between (20-40) years .The collected sample includes

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