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jih-714
Detection of Bacteriocin Production and Induction by Brassica rapa extract
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  The present study aimed to try to find natural substances stimulate the production of bacteriocin, as well as "for detection of bacteriocin producing isolates. Two hundred and eighty ( 280)  bacterial isolates, gram negative only, were collected from 760 different pathogenic samples, consist: (Urinary tract infection, septicemia, Vaginal inflammation and diarrhea).  The isolated bacteria are: Escherichia coli, Klebsiella  pneumonia Pseudomonas  aeruginosa,, Salmonella typhi, Enterobacter cloacae, Acinetobacter baumannii, Serratia  liquefaciens, Citrobacter  freundii,  Proteus  mirabilis and Serrattia  odorifera.  Cup assay method was  used to detect bacteriocin production. Locally media prepared (  Nutriernt agar + Brassica rapa   roots extract ) to detect bacterial bacteriocin production, compared with ( N. agar ) only. The results showed, the percentage of bacteria production of  bacteriocin were (28.57%)/(80)  isolates only on  N. agar, while the ratio reached to (82.5%)/ (231) isolates by local media.Also this media gave (45 mm) in dimeter of inhibition zone in E. coli. Brassica rapa roots extract was used to stimulate bacteriocin production compared with mitomycin-c (Mt-c )  in five isolates of the E. coli. It was found the extract emulate Mt-, in dimeter of inhibition zone , protein concentration and activity. But it was better than Mt-c in some isolates.                                                                                                                                                         

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Publication Date
Wed Sep 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Recovery of Catalyst from Tar Formed in Phenol Production Unit
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This work was conducted to study the recovery of catalyst and desirable components from tar formed in phenol production unit and more particularly relates to such a method whereby better recovery of copper salts, phenol, benzoic acid and benzoate salts from tar by aqueous acid solution was accomplished.
The effect of solvent type, solvent concentration (5, 10, 15, 20, 25 and 30 wt%), agitation speed (100, 200, 300 and 400 rpm), agitation time (5, 10, 15, 20 and 25 min), temperature (90, 100, 110, 120, 130 and 140 oC) , phase ratio (1/1, 2/1, 3/1, 4/1 and 5/1) and number of extraction (1, 2, 3, 4, and 5) were examined in order to increase the catalyst and desirable components extraction.
Four types of solvent were used; hydrochloric

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Publication Date
Sun May 21 2023
Journal Name
Journal Of Namibian Studies : History Politics Culture
The role of cleaner production costs to reducing failure costs
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Economic units can benefit from the cleaner production strategy, which aims to reduce the environmental impact of economic activities while improving efficiency and profitability. Accordingly, the aim of the research was to clarify the knowledge foundations of cleaner production costs and to indicate their role in reducing the costs of poor quality (the costs of failure). A set of conclusions has been reached, the most important of which is that cleaner production has achieved a reduction in the costs of external failure, represented by the costs of guarantee, by an amount of 12,339,000 dinars. Contributes to reducing the costs of failure, and based on the conclusions, a set of recommendations were presented, the most important of w

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Effect of nanocapsules and extract of Metarhizium anisopliae in inhibiting acetylcholine esterase enzyme in Musca domestica larvae.
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M. domestica is the most important insect that transmit pathogens for diseases in the world. The use of nanotechnology is eco-friendly method in control pests. The study aims to investigate the feasibility of bio-manufacturing nanocapsules of fungal secondary metabolites in order to improve the efficiency of metabolite and assess their inhibitory effect on the acetylcholine esterase enzyme in housefly larvae. An equal mixture of organic solvents, ethyl acetate and dichloromethane, was used to extract the metabolic products of the fungus M. anisopliae, (PEG4000) and chitosan was used in the preparation of nanocapsules. The results of the DLS granular size assay showed that the size of the extract particles and the size of the chitosan and

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Publication Date
Sat May 20 2023
Journal Name
Baghdad Science Journal
Effect of nanocapsules and extract of Metarhizium anisopliae in inhibiting acetylcholine esterase enzyme in Musca domestica larvae.
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M. domestica is the most important insect that transmit pathogens for diseases in the world. The use of nanotechnology is eco-friendly method in control pests. The study aims to investigate the feasibility of bio-manufacturing nanocapsules of fungal secondary metabolites in order to improve the efficiency of metabolite and assess their inhibitory effect on the acetylcholine esterase enzyme in housefly larvae. An equal mixture of organic solvents, ethyl acetate and dichloromethane, was used to extract the metabolic products of the fungus M. anisopliae, (PEG4000) and chitosan was used in the preparation of nanocapsules. The results of the DLS granular size assay showed that the size of the extract particles and the size of the chitosa

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Publication Date
Fri Oct 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Detection of Lead (Pb) and Cadmium (Cd) Concentrations and Hazards in Some Baby Food Samples
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This study was conducted to detect the concentration of lead and cadmium in baby foods, (18) samples were examined, which are the most available from various local markets in the city of Baghdad (at a rate of (9) samples of baby food consisting of cereals and (9) samples of baby foods consisting of vegetables). All samples were examined using an atomic flame absorptiometry (AAS-7000), all results showed the presence of lead and cadmium and the highest concentration value of lead in baby foods consisting of cereals (1.0986) and cadmium in baby foods consisting of vegetables (0.0015) ppm. Lead exceeded 100% limitations and cadmium did not exceed that. The results reported on the risks of contamination, as the mean daily intake (g/kg/d) for

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Design and construction of anair pollution detection system using a laser beam and absorption spectroscopy
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Air pollution is one of the important problems facing Iraq. Air pollution is the result of uncontrolled emissions from factories, car exhaust electric generators, and oil refineries and often reaches unacceptable limits by international standards. These pollutants can greatly affect human health and regular population activities. For this reason, there is an urgent need for effective devices to monitor the molecular concentration of air pollutants in cities and urban areas. In this research, an optical system has been built consisting of aHelium-Neonlaser,5mWand at 632.8 nm, a glass cell with a defined size, and a power meter(Gentec-E-model: uno) where a scattering of the laser beam occurs due to air pollution. Two pollutants were examin

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Engineering
Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fully Automated Magnetic Resonance Detection and Segmentation of Brain using Convolutional Neural Network
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     The brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s

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Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
Detection of Some Active compounds and Vitamins Increasing in Aloe vera Callus culture
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This study was aimed to use plant tissue culture technique to induce callus formation of Aloe vera on MS. Medium supplied with 10 mg/l NAA and 5 mg/l BA that exhibit the best results even with subculturing. As the method of [1] 1g. dru weight of callus induced from A. vera crown and in vivo crown were extracted then injected in HPLC using the standards of Ascorbic acid (vit. C), Salysilic acid and Nicotenic acid (vit. B5) to compare with the plant extracts. Results showed high potential of increasing some secondary products using the crown callus culture of A. vera as compared with in vivo crown, Ascorbic acid was 1.829 ?g/l in in vivo crown and increased to 3.905 ?g/l crown callus culture . Salysilic acid raised from 3.54 ?g/l in in vivo c

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
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Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

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