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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
Sun Sep 01 2013
Journal Name
Baghdad Science Journal
Isolation of some active materials and aqueous, alcoholic and oil seed extracts of the plant (Curcuma longa (and study Antibacterial and anticancer activity
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This study included isolation of some active materials from Curcuma longa such as tannins, saponins and volatile oils with percentage of 59%, 31%, and 9% respectively. Also the study included the determination of minerals in Curcuma longa such as " Na, Ca and K" using Flame photometer. The concentrations of these minerals were (14 ppm),(10 ppm) and )76 ppm) respectively. The anti-bacterial activity study was performed for the active materials isolated from Curcuma longa against two genus of pathogenic bacteria, Escherichia Coli and Staphylococcus aurous by using agar-well diffusion method. It appeared from this study that all of the extraction have inhibitory effect on bacteria was used. The inhibition zone diameter varies with

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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
Thu Jun 27 2019
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
A SURVEY OF WEEVILS (COLEOPTERA, CURCULIONOIDEA) FROM SOME LOCALITES OF KURDISTAN REGION- IRAQ, WITH NEW RECORDS TO THE ENTOMOFAUNA OF IRAQ
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This work is the first study of the Curculionoidea fauna from Kurdistan region of Iraq, based on the intensive survey in different localities of Kurdistan from March 2016 to November 2017. In total, 41 species belonging to 28 genera, 21 tribes and 3 families were collected and identified, including 25 species newly recorded for the Iraqi fauna.

 

General distribution, collecting localities and methods, with plant association data for each species are given.

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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
Sat Feb 11 2023
Journal Name
Applied Sciences
A Preliminary Study and Implementing Algorithm Using Finite State Automaton for Remote Identification of Drones
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Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene

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