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Optimization Kerosene Bio-degradation by a Local Soil Bacterium Isolate Klebsiella pneumoniae Sp. pneumonia
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Isolated Bacteria from the roots of barley were studied; two stages of processes Isolated and screening were applied in order to find the best bacteria to remove kerosene from soil. The active bacteria are isolated for kerosene degradation process. It has been found that Klebsiella pneumoniae sp. have the highest kerosene degradation which is 88.5%. The optimum conditions of kerosene degradation by Klebsiella pneumonia sp. are pH5, 48hr incubation period, 35°C temperature and 10000ppm the best kerosene concentration. The results 10000ppm showed that the maximum kerosene degradation can reach 99.58% after 48 h of incubation. Higher Kerosene degradation which was 99.83% was obtained at pH5. Kerosene degradation was found to be maximum at 35°C with 98.63%, where 10000ppm kerosene showed the highest degradation at 99.527%. The results indicate that the isolated Klebsiella pneumonia sp. is extremely efficient in degrading kerosene hydrocarbons.

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Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Improving Treatment Performance of Dissolved Air Flotation System by Using Ionic Liquids as Surfactants
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The effect of three ionic liquids viz., 1-hexyl-3-methylimidazolium tetrafluoroborate (ILE), 1-hexyl-3-metylimidazolium hexafluorophosphate (ILF) and 1-octyl-3-methylimidazolium tetrafluoroborate (ILG) when used as surfactants on the performance of dissolved air floatation (DAF) was investigated.

   Experiments were conducted at a temperature of 30-35 ºC, 10ppm ferric chloride as coagulant, 50% recycle ratio, pH 8, and 10 minutes treatment time  to find oil and grease (OG) and turbidity removal efficiencies at saturation pressure (2-6) bar.

ILs were used at concentration of 50 µl/liter of treated water in two positions in DAF system; the saturation vessel and the treatment tank. The performance using ILs

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Physics: Conference Series
Study electron transport coefficients for Ar, O2 and their mixtures by using EEDF program
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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Eliminate harmful side – effects of Controls System by designing Activity – Based Responsibility Accounting model
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This research has come out with that, function-based responsibility accounting system has harmful side – effects preventing it of achieving its controlling objective, that is, goal congruence, which are due to its un integrated measures, its focus on measuring measurable behaviors while neglecting behaviors that are hardly measured, and its dependence on standard operating procedures.

In addition, the system hypotheses and measures are designed to fit previous business environment, not the current environment.

The research has also concluded that the suggestive model, that is, activity-based responsibility accounting is designed to get ride of harmful side – effects of functi

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Publication Date
Wed Mar 02 2022
Journal Name
Journal Of Educational And Psychological Researches
The Nature of Non-verbal Communication Skills Practiced by Educational Counselors in Individual Guidance
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This research is an attempt to achieve the following objectives: 1. identifying the nature of the non-verbal communication skills practiced by educational counselors in individual guidance. 2. Identifying the significant differences between non-verbal communication skills exercised by educational counselors from their point of view in regard to their gender (male-female). The researcher used a questionnaire as a tool prepared based on exploratory questions of educational counselors and literature. It has consisted of (26) items over four domains applied to a sample of (50) educational counselors (male and female) who have been chosen randomly from schools located in Baghdad Education Directorate Rusafa / 2. It was treated statistically u

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Materials
Characterization of Multilayer Highly-Pure Metal Oxide Structures Prepared by DC Reactive Magnetron Sputtering
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In this work, multilayer nanostructures were prepared from two metal oxide thin films by dc reactive magnetron sputtering technique. These metal oxide were nickel oxide (NiO) and titanium dioxide (TiO2). The prepared nanostructures showed high structural purity as confirmed by the spectroscopic and structural characterization tests, mainly FTIR, XRD and EDX. This feature may be attributed to the fine control of operation parameters of dc reactive magnetron sputtering system as well as the preparation conditions using the same system. The nanostructures prepared in this work can be successfully used for the fabrication of nanodevices for photonics and optoelectronics requiring highly-pure nanomaterials.

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computing
Twitter Location-Based Data: Evaluating the Methods of Data Collection Provided by Twitter Api
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Twitter data analysis is an emerging field of research that utilizes data collected from Twitter to address many issues such as disaster response, sentiment analysis, and demographic studies. The success of data analysis relies on collecting accurate and representative data of the studied group or phenomena to get the best results. Various twitter analysis applications rely on collecting the locations of the users sending the tweets, but this information is not always available. There are several attempts at estimating location based aspects of a tweet. However, there is a lack of attempts on investigating the data collection methods that are focused on location. In this paper, we investigate the two methods for obtaining location-based dat

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Publication Date
Mon Oct 21 2024
Journal Name
Iraqi Statisticians Journal
On Inference of Finite Mixture of Rayleigh Distribution by Gibbs Sampler and Metropolis-Hastings
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Inferential methods of statistical distributions have reached a high level of interest in recent years. However, in real life, data can follow more than one distribution, and then mixture models must be fitted to such data. One of which is a finite mixture of Rayleigh distribution that is widely used in modelling lifetime data in many fields, such as medicine, agriculture and engineering. In this paper, we proposed a new Bayesian frameworks by assuming conjugate priors for the square of the component parameters. We used this prior distribution in the classical Bayesian, Metropolis-hasting (MH) and Gibbs sampler methods. The performance of these techniques were assessed by conducting data which was generated from two and three-component mixt

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Publication Date
Sun Jun 01 2008
Journal Name
Baghdad Science Journal
Study of Spectral and thermal properties of Selenium Diatomic Halides by Semi-empirical Treatment
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The spectroscopic properties, potential energy curve, dipole moments, total charge density, Electrostatic potential as well as the thermodynamic properties of selenium diatomic halides have been studied using code Mopac.7.21 and hyperchem, semi-empirical molecular orbital of MNDO-method (modified neglected of differential overlap) of parameterization PM3 involving quantum mechanical semi-empirical Hamiltonian. The relevant molecular parameters like interatomic distance, bond angle, dihedral angle and net charge were also calculated.

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Publication Date
Mon Oct 01 2012
Journal Name
Iraqi Journal Of Physics
Effect of Cu doping on optical properties of Mn2O3 films prepared by spray pyrolysis
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Thin films of Mn2O3 doped with Cu have been fabricated using the simplest and cheapest chemical spray pyrolysis technique onto a glass substrate heated up to 250 oC. Transmittance and absorptance spectra were studied in the wavelength range (300 -1100) nm. The average transmittance at low energy was about 60% and decrease with Cu doping, Optical constants like refractive index, extinction coefficient and dielectric constants (εr), (εi) are calculated and correlated with doping process.

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

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