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bsj-4494
Extraction, Purification and Characterization of Peroxidase from Pseudomonas aeruginosa and Utility as Antioxidant and Anticancer
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        Peroxidase is a class of oxidation-reduction reaction enzyme that is useful for accelerating many oxidative reactions that protect cells from the harmful effects of free radicals. Peroxidase is found in many common sources like plants, animals and microbes and have extensive uses in numerous industries such as industrial, medical and food processing. In this study, P. aeruginosa was harvested to utilize and study its peroxidases. P. aeruginosa was isolated from a burn patient, and the isolate was verified as P. aeruginosa using staining techniques, biochemical assay, morphological, and a sensitivity test. The gram stain and biochemical test result show rod pink gram-negative bacteria, and ensure that the isolate was that of P. aeruginosa. Optimization for bacterial growth  were done by used more than pH (5,7,9) and temperatures (32,35,37°C), and it was found that the best growth conditions were at pH 5.5, producing (4.5x108cells), and a temperature of 37°C, with (5.25x108cells) being produced. Intracellular enzymes were extracted by ultra-sonication that used frequencies of ultrasound 30 kHz for 20 min in 4 °C, and was centrifuged at 13000×g for 5min. The supernatant was then re-used as a crude enzymatic extract and the cell pellet was discarded. Purification of peroxidase was accomplished by using salt precipitation, dialysis, gel filtrations and ion exchange chromatographic techniques. The result shows that gel filtration has optimal specific activity and purification fold at (61 U/ml), purification fold 6 times and then the improvement enzyme was applied as H2O2 scavenging activity antioxidant by used three concentration of enzyme (10,40,60 µg/ml), and show higher scavenging activity at 60 µg/ml, which reached to 45% scavenging activity. The enzyme was also used as anticancer agent, which was verified by using three concentration of enzyme (10,15,20 µg/ml) which show a significant kill for Mcf-7cells at (15µg/ml), with cytotoxicity activity reaching (45%).                        

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
A Modified Vigenère Cipher based on Time and Biometrics features
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Biometrics is widely used with security systems nowadays; each biometric modality can be useful and has distinctive properties that provide uniqueness and ambiguity for security systems especially in communication and network technologies. This paper is about using biometric features of fingerprint, which is called (minutiae) to cipher a text message and ensure safe arrival of data at receiver end. The classical cryptosystems (Caesar, Vigenère, etc.) became obsolete methods for encryption because of the high-performance machines which focusing on repetition of the key in their attacks to break the cipher. Several Researchers of cryptography give efforts to modify and develop Vigenère cipher by enhancing its weaknesses.

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Publication Date
Wed Jan 23 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Refused Derived Fuel RDF and its role in reducing production
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Refuse derived fuel (RDF) is considered one of the most important types of low cost thermal energy which can be tapped in the industry, especially the cement industry in particular being the need of high thermal energy during the production processes, and in this paper we have implemented the use of a derivative of the fuel RDF  as a substitute for gasoline , to reduce production costs and thereby achieve production efficiency, and the methodology used in this research statistical analysis as well as the use of the cost of kaizen target for the purpose of reducing costs and achieve production efficiency, and this has reduced the cost total cement production by which led to reduce total costs of cement production by 8.4% and an incre

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Sun Oct 11 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Oral hygiene practices and self-perceived halitosis among dental students
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Background: Halitosis represents a common dental condition, although sufferers are often not conscious of it. It is common among humans around the world and is usually caused by an accumulation of bacteria in the mouth as a result of gum disease, food, or plaque. This study aimed to determine the prevalence of oral hygiene practices, smoking habits and halitosis among undergraduate dental students and correlate the oral hygiene practices, oral health conditions to the prevalence of self perceived oral malodor. Materials and Methods: Clinical examination of 250 dental students and a self-administered questionnaire were included in this study. A questionnaire was developed to assess the self-reported perception of oral breath, awareness of b

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Publication Date
Sat Jul 03 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Comparison between VG-levy and Kernel function estimation with application
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Publication Date
Thu Nov 01 2012
Journal Name
2012 International Conference On Advanced Computer Science Applications And Technologies (acsat)
Data Missing Solution Using Rough Set theory and Swarm Intelligence
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This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima

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Publication Date
Sun Jun 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Carbonized Copolymers Nonwoven Nanofibers Composite: Surface Morphology and Fibers Orientation
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Carbonized nonwoven nanofibers composite were fabricated using the electrospinning method of a polymeric solution composite followed by heat treatment including stabilization and calcination steps. The spun polymeric solution was a binary polymer mixture/organic solvent. In this study, two types of polymers (Polymethylmethacrylate (PMMA) and Polyethylene glycol (PEG)) were used separately as a copolymer with the base polymer (Polyacrylonitrile (PAN)) to prepare a binary polymer mixture in a mixing ratio of 50:50. The prepared precursor solutions were used to prepare the precursor nanofibers composite (PAN: PMMA) and (PAN: PEG).  The fabricated precursors nonwoven fibers composite were stabilized and carbonized to produce carbon nonw

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Publication Date
Tue Oct 01 2013
Journal Name
Sensors And Actuators A: Physical
Enhanced energy harvesting using multiple piezoelectric elements: Theory and experiments
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Publication Date
Fri May 15 2026
Journal Name
International Journal Of Engineering Pedagogy (ijep)
Generative AI Effects on Academic Achievement and Sustainable Professional Development
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This quasi-experimental study investigated generative AI (GenAI) tools—Copilot for chemistry and GitHub Copilot for mathematics—on academic achievement and sustainable professional development among 160 undergraduates (40 experimental/control per department) at the University of Baghdad’s Ibn Al-Haitham College of Education for Pure Sciences (2024–2025). Non-random assignment controlled for covariates. Pre/post validated tests (α ≥ .85; 15 MCQ + 5 essay items) measured outcomes. ANOVA revealed significant gains for experimental groups (p < .001, η2 = .41, Cohen’s d = 0.72 [95% CI: 0.45–0.98]). Chemistry excelled in affective domains; mathematics in cognitive/skills. Findings affirm GenAI’s domain-specific efficacy, prov

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Publication Date
Fri May 15 2026
Journal Name
International Journal Of Engineering Pedagogy (ijep)
Generative AI Effects on Academic Achievement and Sustainable Professional Development
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This quasi-experimental study investigated generative AI (GenAI) tools—Copilot for chemistry and GitHub Copilot for mathematics—on academic achievement and sustainable professional development among 160 undergraduates (40 experimental/control per department) at the University of Baghdad’s Ibn Al-Haitham College of Education for Pure Sciences (2024–2025). Non-random assignment controlled for covariates. Pre/post validated tests (α ≥ .85; 15 MCQ + 5 essay items) measured outcomes. ANOVA revealed significant gains for experimental groups (p < .001, η2 = .41, Cohen’s d = 0.72 [95% CI: 0.45–0.98]). Chemistry excelled in affective domains; mathematics in cognitive/skills. Findings affirm GenAI’s domain-specific effica

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