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Detection of mexB Multidrug Efflux Gene in Some Local Isolates of Pseudomonas aeruginosa
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According to the prevalence of multidrug resistance bacteria, especially Pseudomonas aeruginosa, in which the essential mechanism of drug resistance is the ability to possess an efflux pump by which extrusion of antimicrobial agents usually occurs, this study aims to detect the presence of mexB multidrug efflux gene in some local isolates of this bacteria that show resistance towards three antibiotics, out of five. Sensitivity test to antibiotics was performed on all isolates by using meropenem (10μg/disc), imipenem (10μg/disc), amikacin (30 μg/disc), ciprofloxacin (5μg/disc) and ceftazidime (30 μg/disc). Conventional PCR results showed the presence of mexB gene (244bp) in four isolates out of ten (40%). In addition,25, 50μg/ml of curcumin was used to detect its efficacy with the antibiotics that the bacteria showed resistance towards. Results showed the highest resistance for ciprofloxacin (80%), while all of them were sensitive to imipenem. In addition, the present results show that both concentrations of curcumin (25, 50μg/ml) were effective in increasing the zone of inhibition from zero to 10 mm for isolates towards amikacin. Same result was obtained towards ciprofloxacin, except for an increase of inhibition zone from zero to 7 mm to one isolate (38T) when treated with 50 μg/ml, and finally an increase in sensitivity to ceftazidime was found and inhibition zone was increased from 8 to 11 for the second isolate (42E), which revealed that curcumin potentiates antibiotics activity by inhibition of efflux pump mechanisms that can be related to the synergetic activity between antibiotics and curcumin.

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Publication Date
Mon Mar 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Hurst Exponent and Tsallis Entropy Markers for Epileptic Detection from Children
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The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Brain Tumour Detection using Fine-Tuning Mechanism for Magnetic Resonance Imaging
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In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

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Publication Date
Tue Jul 01 2014
Journal Name
Computer Engineering And Intelligent Systems
Static Analysis Based Behavioral API for Malware Detection using Markov Chain
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Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
GIS as A Tool for Expansive Soil Detection at Sulaymaniyah City
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Geotechnical engineering like any other engineering field has to develop and cope with new technologies. This article intends to investigate the spatial relationships between soil’s liquid limit (LL), plasticity index (PI) and Liquidity index (LI) for particular zones of Sulaymaniyah City. The main objective is to study the ability to produce digital soil maps for the study area and determine regions of high expansive soil. Inverse Distance Weighting (IDW) interpolation tool within the GIS (Geographic Information System) program was used to produce the maps. Data from 592 boreholes for LL and PI and 245 boreholes for LI were used for this study. Layers were allocated into three depth ranges (1 to 2, 2 to 4 and 4 to 6)

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Publication Date
Mon Jun 30 2025
Journal Name
Iraqi Journal Of Science
New Weighted Synthetic Oversampling Method for Improving Credit Card Fraud Detection
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The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th

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Publication Date
Mon Aug 04 2014
Journal Name
Iraqi National Journal Of Chemistry
Comparative Study for Antibacterial Activity of Some Maleamic acid Derivatives with Some Commercial Antibiotic
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Publication Date
Mon Sep 01 2014
Journal Name
Ibn Al-haitham Jour. For Pure & Appl. Sci
Studying the Biological Activity of Some Oxazepine Derivatives Against Some G(+) and G(-) Bacteria.
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The preliminary test of the compounds N [2– (3,4–dimethoxy nitrobenzene oxazepine– 2,3–dihydro–4,7–dione]–5–mercupto–2–amino–1,3,4–thiadiazol [A] and N [ 2–anthralidene– 5– ( 2–nitrophenyl ) –1,3–oxazepine–4,7–dione–2–d](5–mercapto–1,3,4–thiadiazole–2–amin) [B] , showed that they possess high activity against some positive and negative bacteria , like pseudomonas aeruginosa (pseudo.), Escherichia coli (E-coli), staphylococcus aureus (sta.) and Bacillus subtilis (Ba.) and finally there is a study of the effect of some antibiotics like streptomycin (S), gentamycin (GN), chloramphenicol (C) and Nalitixic acid (NA) in order to compare the differences in effects. In the present study, results

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Publication Date
Tue Apr 14 2015
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
The Effect of Using Ginger (Zingiber officinale) to Prevente Salmonella typhi. in Some Food Products.: The Effect of Using Ginger (Zingiber officinale) to Prevente Salmonella typhi. in Some Food Products.
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This study was conducted in order to statement the effect of ginger (Zingiber officinale) extracts in reducing the presence of the bacterium Salmonella typhimurium in some foods products.
Qualitative disclosures effective chemical compounds (alkaloids, flavonoids, phenols, tannins, terpenes) showed that the extracts of ginger an effective compounds as follows: oil extract and fresh juice> aqueous extract warm> aqueous extract cold. And studied the impact extract of fresh ginger juice, hot water ,cold water and oil rates extracts (1,2,3)% in bacteria test has shown that all s of extracts clear impact inhibition has oily extract of ginger recorded the highest value to inhibition zone reaching 35 mm when the concentration of 3%, f

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