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bijps-1249
Isolation and Identification of Phenolic Compounds from Dianthus orientalis Wildly Grown in Iraq.
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The plant Dianthus Orientalis that belongs to the Caryphyllaceae family is one of the useful plants in Iraq. Its seeds are commonly used for toothache. This project provides the first comprehensive research done in Iraq and the world to study the phytochemicals and the methods of extraction and isolation of active constituents from Dianthus orientalis wildly grown in Iraq. The plant was harvested from Penjwin in AL-Sulaymaniyah city, Iraq in September 2019.The whole plant were washed carefully, dried in shade area for two weeks, and milled in a mechanical grinder to a coarse powder. The plant was defatted by maceration with hexane for 7days and dried after that extracted by cold extraction methods using 80% methanol solvent for 9 days then fractionation with chloroform, ethyl acetate and n-butanol to separate the active constituents according to the change in polarities. The chloroform, ethyl acetate fractions were used for identification and isolation of phenolic compounds by TLC, PTLC, HPLC and LC/mass, FTIR. Results of the phytochemical screening exposed the presence of, phenols in the plant extract. The phenolic compound (vanillic acid, coumaric acid, cinnamic acid, genistein, oleuropein) were separated and purified by PTLC. The isolated compounds were subjected to several chemical, chromatographic and spectral analytical techniques for their identification such as TLC, HPLC, FTIR and LC/mass.

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Publication Date
Thu Aug 01 2019
Journal Name
2019 2nd International Conference On Engineering Technology And Its Applications (iiceta)
Human Gait Identification System Based on Average Silhouette
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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
System Identification Algorithm for Systems with Interval Coefficients
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In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

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Publication Date
Wed Oct 10 2018
Journal Name
Al-kindy College Medical Journal
Recurrent Laryngeal Nerve Injury With Versus Without Nerve Identification In Different Thyroidectomy Procedures
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Background: The world health organization estimates that worldwide 2 billion people still have iodine deficiency Objectives: Is to make comparison between the effect of identification of recurrent laryngeal nerve (RLN) and non-identification of the nerve on incidence of recurrent laryngeal nerve injury (RLNI) in different thyroidectomy procedures.

Type of the study: cross –sectional study.

Methods: 132 patients with goiters underwent thyroidectomy .Identification of RLN visually by exposure were done for agroup of them and non-identification of the nerves for the other group. The outcomes of RLNI in the two groupsanalyzed statistically for the effect of

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Publication Date
Thu Oct 22 2020
Journal Name
2020 4th International Symposium On Multidisciplinary Studies And Innovative Technologies (ismsit)
Artificial Intelligence in Smart Agriculture: Modified Evolutionary Optimization Approach for Plant Disease Identification
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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Molecular identification of dermatophytes by arbitrarily primed polymerase chain reaction
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Publication Date
Mon Jan 01 2024
Journal Name
Communications In Computer And Information Science
Automatic Identification of Ear Patterns Based on Convolutional Neural Network
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Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

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Publication Date
Sun Jan 01 2017
Journal Name
The Iraqi Journal Of Agricultural Science 48 (5), 1197-1205‏
Sex identification of date palm by using dna molecular markers
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Publication Date
Wed Jun 18 2014
Journal Name
Geological Quarterly
Stable carbon and nitrogen isotopes and elemental composition and origin of organic matter from the Euphrates, Injana and Dibdibba formations in Iraq: discrimination between marine and terrestrial environments
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Publication Date
Thu Apr 27 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn: 2789-3219 )
Anticancer Activities of Some Heterocyclic Compounds Containing an Oxygen Atom: A Review
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The purpose of this study is to underline the progression and development of research regarding oxygen-containing heterocycles as well as the contribution that some oxygen-containing heterocycles have made as anticancer medicines. A series of publications about the antitumor effects of derivatives of heterocyclic compounds containing an oxygen atom, such as furan, benzofuran, oxazole, benzoxazole, and oxadiazole, were evaluated, and their anticancer activities showed encouraging results when compared to those of established standard treatments.

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