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Sarin chemical warfare agent detection by Sc-decorated XN nanotubes (X = Al or Ga)
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In order to scrutinize the impact of the decoration of Sc upon the sensing performance of an XN nanotube (X = Al or Ga, and XNNT) in detecting sarin (SN), the density functionals M06-2X, τ-HCTHhyb, and B3LYP were utilized. The interaction of the pristine XNNT with SN was a physical adsorption with the sensing response (SR) of approximately 5.4. Decoration of the Sc metal into the surface of the AlN and GaN led to an increase in the adsorption energy of SN from −3.4 to −18.9, and −3.8 to −20.1 kcal/mol, respectively. Also, there was a significant increase in the corresponding SR to 38.0 and 100.5, the sensitivity of metal decorated XNNT (metal@XNNT) is increased. So, we found that Sc-decorating more increases the sensitivity of GaNNT toward SN compare to AlNNT. Also, the recovery time for SN to be desorbed from the Sc@GaNNT surface was found to be short, i.e., 4.4 s. Based on the energy decomposing analysis, the interaction between the SN and metal@nanotubes was of electrostatic nature, which is also called a cation-lone pair interaction.

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Publication Date
Wed Dec 12 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Detection of Polyomavirus BK and JC in kidney Transplant Recipients
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objectives: To investigate the polyomaviruses (BK, JC) in asymptomatic kidney transplant recipients and healthy persons as control. It is one of the first reports on serological detection and molecular characterization that describes the circulation of polyomaviruses (BKV, JCV) have been done in Iraq recently. Methodology: The present study was designed as prospective case control study was done during the period from November 2015 to August 2016. Total of 97 serum and urine samples were collected randomly from 25 healthy control person and 72 renal transplant recipients, attending Iraqi Renal Transplantatio

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Publication Date
Sun Aug 13 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Different Parameters for Alkaloid detection in Catharanthus roseus tissue culture
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    Tissue culture of Catharanthus  roseus  was established under many parameters to insure good results for detection of the alkaloids present in this plant . It was found that NItsch and Nitsch medium containing 8µM Benzyladeninpurine plus Naphalene acetic acid were the best and the callus of C.roseus left to grow in the dark and had much better influence for the production of Alkloids. The precursor phenylalanine showed a better result than other precursor( tryptophan ) . Abscisic acid has an inhibitory effect on the production of Alkaloid

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Publication Date
Wed Nov 24 2021
Journal Name
Iraqi Journal Of Science
Molecular Detection of Suspected Leishmania Isolates Using Polymerase Chain Reaction
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Leishmaniasis is a widespread parasitic disease that occurs as a result of infection with a unicellular parasite belonging to the genus Leishmania. Diagnosis by conventional methods is inaccurate and is not sensitive to confirm the genus infection. Here, we have investigated a methods for Leishmania genus diagnosis, which includes the technique of polymerase chain reaction to detect the presence of the parasite at in vitro for promastigote cultures using three genus-specific primer pairs to amplify HSP70, ITS, and ITS2. The results showed single band of ~1422, ~1020, and ~550 respectively. This study has proved the ability of these primer pairs to detect Leishmania infection and recommend them to be used for detection of leishmaniasis in

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Publication Date
Sat Jan 30 2021
Journal Name
Iraqi Journal Of Science
Detection of the Antiseptic Resistance Gene among Pseudomonas aeruginosa Isolates
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Pseudomonas aeruginosa is an opportunistic pathogen that causes a number of infections in immunocompromised patients. This organism appears to improve resistance  to many antimicrobial agents and a high percentage of clinical isolates of P. aeruginosa exhibit multidrug resistance (MDR) phenotype . The purpose of this study is to screen the antibiotic susceptibility patterns and the prevalence of qacE delta1 gene among bacterial isolates. Accordingly, 145 samples were collected from different clinical sources from patients who admitted to different hospitals in Baghdad city in a period ranged 23/8/2018-1/1/2019. The isolates were diagnosed as P. aeruginosa based on routine b

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Photoacoustic Imaging for Tumor Detection: An in vitro Simulation Study
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Photoacoustic is a unique imaging method that combines the absorption contrast of light or radio frequency waves with ultrasound resolution. When the deposition of this energy is sufficiently short, a thermo-elastic expansion takes place whereby acoustic waves are generated. These waves can be recorded and stored to construct an image. This work presents experimental procedure of laser photoacoustic two dimensional imaging to detect tumor embedded within normal tissue. The experimental work is accomplished using phantoms that are sandwiched from fish heart or blood sac (simulating a tumor) 1-14mm mean diameter embedded within chicken breast to simulate a real tissue. Nd: YAG laser of 1.064μm and 532nm wavelengths, 10ns pulse duration, 4

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Development an Anomaly Network Intrusion Detection System Using Neural Network
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Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Sequential feature selection for heart disease detection using random forest
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Heart disease identification is one of the most challenging task that requires highly experienced cardiologists. However, in developing nations such as Ethiopia, there are a few cardiologists and heart disease detection is more challenging. As an alternative solution to cardiologist, this study proposed a more effective model for heart disease detection by employing random forest and sequential feature selection (SFS). SFS is an effective approach to improve the performance of random forest model on heart disease detection. SFS removes unrelated features in heart disease dataset that tends to mislead random forest model on heart disease detection. Thus, removing inappropriate and duplicate features from the training set with sequential f

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Matching Algorithms for Intrusion Detection System based on DNA Encoding
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Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o

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Scopus
Publication Date
Fri May 17 2019
Journal Name
Lecture Notes In Networks And Systems
Features Selection for Intrusion Detection System Based on DNA Encoding
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Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

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Scopus (2)
Scopus
Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Online Sumarians Cuneiform Detection Based on Symbol Structural Vector Algorithm
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The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

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