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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 Transplantation Society. “New experimental indirect ELISA kit" had been designed and synthesized manually for detection Anti-JCV IgM and IgG, Urea and creatinine level had been measured for total study groups for estimation of renal functions. Results: All of the samples were submitted to a Nested-PCR. A significantly difference had been seen (P < 0.01) of PyV was found in renal transplant patients 2(2.8%) in comparison to the control group 4(16.0%). JCV was detected in.6 (6.2%) samples (2 patients/ 4 controls).by conventional PCR, BKV was detected in 2(2.8%) of renal transplant group and not detected with any one of control group. result for IgM revealed positivity for 25(25.8%) out of 72cases of renal transplant subject and 8(8.2%) person out of 25control groups. for IgG the result show that 21(29.2%) out of 72 cases of renal transplant Subjects have a positive result for IgG but this antibody was not detected in the control. Recommendations: Success diagnosis required sensitive assay typically Nested-PCR to detect extremely low viral load present in potential kidney donor before access as a donor, Because of the potentially harmful effects of polyomavirus which may cause loss of the transplanted kidney

 
 

 

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Keratoconus Severity Detection From Elevation, Topography and Pachymetry Raw Data Using a Machine Learning Approach
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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Mixed Micelles of Binary Mixtures of Sodium Dodecylbenzene Sulfate and Tween 80 Surfactants in Aqueous Solutions
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In the present work, the surface properties of mixed binary surfactants containing sodium dodecylbenzene sulfate (SDBS) and Tween 80 (TW80) surfactants in aqueous solutions were studied at temperature 293 K using surface tension measurements. The critical micelle concentration (cmc) magnitude for both individual surfactants and their mixtures were established the obtained results revealed  that the magnitude of cmc of the mixtures are less than the magnitude of individual surfactants and decrease with the increase in Tween 80 percent in solution which indicate the nonideal  mixing of the two surfactants. The values of molecular interaction parameters  and the mole fraction of surfactants in the micelle (X1) were calculated

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Extent of the Commitment with Accounting Disclosure for Contingent Assets, Liabilities and Provisions in the Shareholding Companies Listed in Iraq Stock Exchange Analytical Entrance
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Accounting changes have taken place in either the local or international level has led to more disclosure from companies, and that many of the economic units in order to attract investors to negotiate on its shares price in the stock market require amendments with respect to the information disclosed, Thus, the objective of this research is to analyze whether companies were research sample disclose contingent assets and liabilities and provisions in their annual financial reports with what brought him International Accounting Standards. It has been used descriptive analysis of annual financial reports for a sample of (50) listed company on the Iraq Stock Exchange were identified companies that disclose contingent assets and liabi

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Nano Fluid Detection for HPHE System Using Different Lasers
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Among the different passive techniques heat pipe heat exchanger (HPHE) seems to be the most effective one for energy saving in heating ventilation and air conditioning system (HVAC). The applications for nanofluids with high conductivity are favorable to increase the thermal performance in HPHE. Even though the nanofluid has the higher heat conduction coefficient that dispels more heat theoretically but the higher concentration will make clustering .Clustering is a problem that must be solved before nanofluids can be considered for long-term practical uses. Results showed that the maximum value of relative power is 0.13 mW at nanofluid compared with other concentrations due to the low density of nanofluid at this concentration. For highe

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Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Partial Encryption for Colored Images Based on Face Detection
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Publication Date
Tue Apr 02 2024
Journal Name
Advances In Systems Science And Applications
A New Face Swap Detection Technique for Digital Images
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Publication Date
Fri Nov 05 2021
Journal Name
Semiconductor Science And Information Devices
Cladding Modified Fiber Bragg Grating for Copper Ions Detection
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This paper reports a fiber Bragg grating (FBG) as a biosensor. The FBGs were etched using a chemical agent,namely,hydrofluoric acid (HF). This implies the removal of some part of the cladding layer. Consequently, the evanescent field propagating out of the core will be closer to the environment and become more sensitive to the change in the surrounding. The proposed FBG sensor was utilized to detect toxic heavy metal ions aqueous medium namely, copper ions (Cu2+). Two FBG sensors were etched with 20 and 40 μm diameters and fabricated. The sensors were studied towards Cu2+ with different concentrations using wavelength shift as a result of the interaction between the evanescent field and copper ions. The FBG sensors showed

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Moving Objects Detection Based on Frequency Domain: image processing
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In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

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Publication Date
Tue Apr 16 2019
Journal Name
Proceedings Of The 2019 5th International Conference On Computer And Technology Applications
Four Char DNA Encoding for Anomaly Intrusion Detection System
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Recent research has shown that a Deoxyribonucleic Acid (DNA) has ability to be used to discover diseases in human body as its function can be used for an intrusion-detection system (IDS) to detect attacks against computer system and networks traffics. Three main factor influenced the accuracy of IDS based on DNA sequence, which is DNA encoding method, STR keys and classification method to classify the correctness of proposed method. The pioneer idea on attempt a DNA sequence for intrusion detection system is using a normal signature sequence with alignment threshold value, later used DNA encoding based cryptography, however the detection rate result is very low. Since the network traffic consists of 41 attributes, therefore we proposed the

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Cybersecurity And Information Management
Machine Learning-based Information Security Model for Botnet Detection
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Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

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