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Evaluated the level density for proton induced nuclear resonances in (P+48Ti) reaction using different models
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The experimental proton resonance data for the reaction P+48Ti have been used to calculate and evaluate the level density by employed the Gaussian Orthogonal Ensemble, GOE version of RMT, Constant Temperature, CT and Back Shifted Fermi Gas, BSFG models at certain spin-parity and at different proton energies. The results of GOE model are found in agreement with other, while the level density calculated using the BSFG Model showed less values with spin dependence more than parity, due the limitation in the parameters (level density parameter, a, Energy shift parameter, E1and spin cut off parameter, σc). Also, in the CT Model the level density results depend mainly on two parameters (T and ground state back shift energy, E0), which are approximately constant in their behavior with the proton energy compared with GOE model. The RMT estimation used to calculate the corrections of the incompleteness proton resonance measurement data by using two methods; the conventional analysis method, which depends on the resonance widths and the updated, developed, tested and applied a new analysis method, which depends mainly on the resonance spacings. The spacing analysis method is found much less sensitive to non-statistical phenomena than is the width analysis method. Where the analysis of a given data set via these two independent analysis methods indicated the increasing in the reliability of the determination of the missing fraction of levels, the observed fraction f between 0.87+0.13−0.11 – 0.68+0.12−0.12 for different spin-parity of this reaction and then the distinguishability in the level density calculations can be achieved. The modified Porter Thomas distribution along with the maximum likelihood function have been used to get the missing levels corrections for 5 proton resonance sequences in the present reaction. To estimate the present long-range correlations for pure sequence of levels the mean square of the deviation of the cumulative number of levels from a fitted straight line represented by the Dyson and Mehta Δ3 statistic has been employed for spin parity 12+, and calculated the <Δ3> against the cumulative number of proton levels.

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Publication Date
Wed Apr 28 2021
Journal Name
Journal Of Engineering
Deasphalting of Atmospheric Iraqi Residue using Different Solvents
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Different solvents (light naphtha, n-heptane, and n-hexane) are used to treat Iraqi Atmospheric oil residue by the deasphalting process. Oil residue from Al-Dura refinery with specific gravity 0.9705, API 14.9, and 0.5 wt. % sulfur content was used. Deasphalting oil (DAO) was examined on a laboratory scale by using solvents with different operation conditions (temperature, concentration of solvent, solvent to oil ratio, and duration time). This study investigates the effects of these parameters on asphaltene yield. The results show that an increase in temperature for all solvents increases the extraction of asphaltene yield. The higher reduction in asphaltene content is obtained with hexane solvent at operating conditions of (90 °C

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Publication Date
Tue Dec 05 2017
Journal Name
Asian Journal Of Biological And Life Sciences
Bioethanol Production from Banana Peels using Different Pretreatments
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Publication Date
Sun Mar 30 2025
Journal Name
Iraqi Journal Of Science
Segmentation of Aerial Images Using Different Clustering Techniques
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The segmentation of aerial images using different clustering techniques offers valuable insights into interpreting and analyzing such images. By partitioning the images into meaningful regions, clustering techniques help identify and differentiate various objects and areas of interest, facilitating various applications, including urban planning, environmental monitoring, and disaster management. This paper aims to segment color aerial images to provide a means of organizing and understanding the visual information contained within the image for various applications and research purposes. It is also important to look into and compare the basic workings of three popular clustering algorithms: K-Medoids, Fuzzy C-Mean (FCM), and Gaussia

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Publication Date
Sat Dec 11 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Safranal Effect against Cyclophosphamide-Induced Liver Injury
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The liver is the primary organ for drug metabolism, elimination, Cyclophosphamid is the classical alkylating agent nitrogen mustard, its metabolism into two cytotoxic metabolites, and increase reactive oxygen species that is make liver toxicity. Safranal as the most abundant chemical in saffron essential oil, it have anti-oxidant, anti-inflammatory, antiapoptic and free radical scavenger activity. The aim of study is to assess the protective effects of safranal on the cyclophosphamide-induce liver toxicity in rat model. This occur by using five different groups of rats; control group, treatment group, cyclophosamide group (intraperitoneal i.p), cyclophosamide and (50mg and 100mg) oral safranal treatment groups. This study showed this pro

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Publication Date
Fri Nov 09 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Detection the level of YKL-40 biochemical marker and vitamin D level in sera of Iraqi Uterine cancer females' patients
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Objective: Detection the level of YKL-40 biochemical marker and vitamin D level in sera of Iraqi uterine cancer
females' patients.
Methodology: This study included 90 female volunteers, 30 of them were healthy volunteers who were
considered as a control group, while sixty serum samples were collected from women patients suffering from
uterine tumors (30 malignant and 30 fibroid benign tumors), benign cases were considered as a disease
control group for malignant tumors. The average age of those females was 30-75 years, which matched the
control group. All the samples were collected from Azady hospital in Kirkuk and the gynecologic department at
Medical City in Baghdad during October /2012 to May /2013. All the serum

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Total Dissolved Salt Prediction Using Neurocomputing Models: Case Study of Gypsum Soil Within Iraq Region
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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayes Estimators for the Parameter of the Inverted Exponential Distribution Under different Double informative priors
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In this paper, we present a comparison of double informative priors which are assumed for the parameter of inverted exponential distribution.To estimate the parameter of inverted exponential distribution by using Bayes estimation ,will be  used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of inverted exponential distribution. Also assumed Chi-squared - Gamma distribution, Chi-squared - Erlang distribution, and- Gamma- Erlang distribution as double priors. The results are the derivations of these estimators under the squared error loss function with three different double priors.

Additionally Maximum likelihood estimation method

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Publication Date
Mon Jan 01 2018
Journal Name
Proceedings Of The 10th International Joint Conference On Computational Intelligence
Deep Classifier Structures with Autoencoder for Higher-level Feature Extraction
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Publication Date
Tue Jan 25 2011
Journal Name
Journal Of Cellular Biochemistry
Phytoestrogens directly inhibit TNF-α-induced bone resorption in RAW264.7 cells by suppressing c-fos-induced NFATc1 expression
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TNF-α-induced osteoclastogenesis is central to post-menopausal and inflammatory bone loss, however, the effect of phytoestrogens on TNF-α-induced bone resorption has not been studied. The phytoestrogens genistein, daidzein, and coumestrol directly suppressed TNF-α-induced osteoclastogenesis and bone resorption. TRAP positive osteoclast formation and resorption area were significantly reduced by genistein (10(-7) M), daidzein (10(-5) M), and coumestrol (10(-7) M), which was prevented by the estrogen antagonist ICI 182,780. TRAP expression in mature TNF-α-induced osteoclasts was also significantly reduced by these phytoestrogen concentrations. In addition, in the presence of ICI 182,780 genistein and coumestrol (10(-5) -10(-6) M) augmente

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