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Evaluation of The Nuclear Data on(α,n)Reaction for Natural Molybdenum
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The cross section evaluation for (α,n) reaction was calculated according to the available International Atomic Energy Agency (IAEA) and other experimental published data . These cross section are the most recent data , while the well known international libraries like ENDF , JENDL , JEFF , etc. We considered an energy range from threshold to 25 M eV in interval (1 MeV). The average weighted cross sections for all available experimental and theoretical(JENDL) data and for all the considered isotopes was calculated . The cross section of the element is then calculated according to the cross sections of the isotopes of that element taking into account their abundance . A mathematical representative equation for each of the element and their isotopes are "formulated" they represent the variation of the cross section with energy . The evaluated (α,n) cross sections which was used to calculate the neutron yield for (Mo) for the first time ,which are very important in nuclear technology .

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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Scopus (46)
Scopus
Publication Date
Thu Nov 08 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation the effect of burning investment and black sand materials on the surface roughness of acrylic resin denture base
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Objective: The aim of this study was to evaluate the effect of pumice, burning investment material
and black sand on the surface roughness of heat cure acrylic resin.
Methodology: Sixty specimens were prepared from pink heat cure acrylic resin, the specimens
where grouped into; 20 specimens which polished with pumice and water (control group); 20
specimens which polished with investment material (after burning it) and water; and 20 specimens
which polished with black sand and water. The average surface roughness of specimens after
polishing procedure had been determined by profilometer (surface roughness tester).
Results: Through the application of ANOVA and LSD tests, the result of this study showed that there
wa

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Evaluation of the Influence of De-sanding (Recycling System) Process on the Pile Bearing Capacity Using Full Scale Models
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The present study investigates the effect of the de-sanding (recycling system) on the bearing capacity of the bored piles. Full-scale models were conducted on two groups of piles, the first group was implemented without using this system, and the second group was implemented using the recycling system. All piles were tested by static load test, considering the time factor for which the piles were implemented. The test results indicated a significant and clear difference in the bearing capacity of the piles when using this system. The use of the recycling system led to a significant increase in the bearing capacity of the piles by 50% or more. Thus it was possible to reduce the pile length by (15 % or more) thus, and implementation c

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Crossref
Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Evaluation of the Influence of De-sanding (Recycling System) Process on the Pile Bearing Capacity Using Full Scale Models
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The present study investigates the effect of the de-sanding (recycling system) on the bearing capacity of the bored piles. Full-scale models were conducted on two groups of piles, the first group was implemented without using this system, and the second group was implemented using the recycling system. All piles were tested by static load test, considering the time factor for which the piles were implemented. The test results indicated a significant and clear difference in the bearing capacity of the piles when using this system. The use of the recycling system led to a significant increase in the bearing capacity of the piles by 50% or more. Thus it was possible to reduce the pile length by (15 % or more) thus, and implementation costs

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Crossref
Publication Date
Thu Nov 16 2017
Journal Name
Joiv : International Journal On Informatics Visualization
Multilayered Framework to Enhance Management Information Systems Decision on Sensitive Data in Cloud Computing Environment
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The purpose of this research is defining the main factors influencing on decision of management system on sensitive data in cloud. The framework is proposed to enhance management information systems decision on sensitive information in cloud environment. The structured interview with several security experts working on cloud computing security to investigate the main objective of framework and suitability of instrument, a pilot study conducts to test the instrument. The validity and reliability test results expose that study can be expanded and lead to final framework validation. This framework using multilevel related to Authorization, Authentication, Classification and identity anonymity, and save and verify, to enhance management

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Scopus (3)
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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Applied Study on Analysis of Fixed, Random and Mixed Panel Data Models Measured at specific time intervals
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This research sought to present a concept of cross-sectional data models,  A crucial double data to take the impact of the change in time and obtained from the measured phenomenon of repeated observations in different time periods, Where the models of the panel  data were defined by different types of fixed , random and mixed, and Comparing them by studying and analyzing the mathematical relationship between the influence of time with a set of basic variables Which are the main axes on which the research is based and is represented by the monthly revenue of the working individual and the profits it generates, which represents the variable response And its relationship to a set of explanatory variables represented by the

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Crossref
Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Scopus (51)
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Publication Date
Wed Sep 27 2023
Journal Name
Journal Of Optics
Studying the responsivity and detectivity of GO/PSi/n-Si photo detector via drop casting technique
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Publication Date
Wed Sep 27 2023
Journal Name
Journal Of Optics
Studying the responsivity and detectivity of GO/PSi/n-Si photo detector via drop casting technique
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Publication Date
Wed Jul 01 2020
Journal Name
Proceedings Of The Institution Of Mechanical Engineers, Part H: Journal Of Engineering In Medicine
Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury
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Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

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