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Investigating the Color Distribution of Young and Old Galaxies Using Observations from SDSS
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     This research aims to investigate the color distribution of a huge sample of 613654 galaxies from the Sloan Digital Sky Survey (SDSS). Those galaxies are at a redshift of 0.001 - 0.5 and have magnitudes of g = 17 - 20. Five subsamples of galaxies at redshifts of (0.001 - 0.1), (0.1 - 0.2), (0.2 - 0.3), (0.3 - 0.4) and (0.4 - 0.5) have been extracted from the main sample. The color distributions (u-g), (g-r) and (u-r) have been produced and analysed using a Matlab code for the main sample as well as all five subsamples. Then a bimodal Gaussian fit to color distributions of data that have been carried out using minimum chi-square in Microsoft Office Excel. The results showed that the color distributions of the main sample and all subsamples are bimodal. This indicates that the color distribution is an ideal tool to differentiate between young and old galaxies. The young and blue star-forming galaxies are represented by one of the two peaks, while the old and red non-star-forming galaxies are represented by the other peaks of the color distribution.

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Protection of Galvanized steel from corrosion in salt media using sulfur nanoparticles
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                The characteristics of sulfur nanoparticles were studied by using atomic force microscope (AFM) analysis. The atomic force microscope (AFM) measurements showed that the average size of sulfur nanoparticles synthesized using thiosulfate sodium solution through the extract of cucurbita pepo extra was 93.62 nm. Protecting galvanized steel from corrosion in salt media was achieved by using sulfur nanoparticles in different temperatures. The obtained data of thermodynamic in the presence of sulfur nanoparticles referred to high value as compares to counterpart in the absence of sulfur nanoparticles, the high inhibition efficiency (%IE) and corrosion resistance were at high temperature, the corrosion rate or weig

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Publication Date
Wed May 25 2022
Journal Name
Iraqi Journal Of Science
Removing of Copper ions from Industrial Wastewater Using Graphene oxide/Chitosan Nanocomposite
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     A simple method was used to create a graphene oxide/chitosan (GO/CS) nanocomposite, which was then used in batch experiments to remove copper ions from industrial wastewater under various conditions of initial concentration, adsorbent weight, pH, and contact time. Maximum removal percentage equal to 99.4 % for initial copper ion concentration of 5x10-2 mol/L at pH 6, time 75 min, temperature 25 °C, and adsorbing dose 0.1 g. The pseudo-second order kinetic model and the Freundlich isotherm adequately fit the experimental results. The process was spontaneous and endothermic, according to thermodynamic studies.

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Publication Date
Sun Dec 01 2019
Journal Name
2019 First International Conference Of Computer And Applied Sciences (cas)
A Comparison for Some of the estimation methods of the Parallel Stress-Strength model In the case of Inverse Rayleigh Distribution
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Publication Date
Wed May 01 2024
Journal Name
Journal Of Ecological Engineering
Explore the Impact of Surfactant Type on the Stability and Separation Efficiency of Oil–Water Emulsions of Real Wastewater from Al-Basrah Crude Oil Using Microbubble Air Flotation
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Among several separation processes, the air flotation distinguish as remarkably high potential separation process related to its high separation efficiency and throughput, energy-efficient, simple process, cost-effective, applicable to a wide range of oily wastewater and no by-products. The current study aimed to investigate the effect of the type and concentration of surfactant on the stability of oil-water emulsion and efficiency of the separation process. For this purpose, three types of surfactant where used (anionic SDS, mixed nonionic Span 85/Tween 80, and cationic CTAB). The results demonstrated that the Span 85/Tween 80 surfactant has the best stability, and it increases with the surfactant concentration augmentation. The removal ef

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Science
Distribution and Enrichments of Abundant and Trace Elements in Al-Khassa Sub Basin Soil, Kirkuk, Northeastern of Iraq
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     This study focused on the soil  of the Al-Khassa Sub Basin,  thirty-four soil samples were collected from different areas of land use and differences in human activity.

 Physicochemical properties of the soil were examined Hydrogen Potential (pH), Organic Matter (O.M), Loss Of  Ignition (L.O.I), Total Organic Carbon (TOC), Cation Exchange Capacity (CEC) and Total Hydrocarbon (THC).

  Hydrogen Potential (pH)  showed that the soil is alkaline above seven with  a mean 7.98.

Organic Matter (O.M) of the study area with a mean  1.28 % and high value found in Agricultural areas.Cation Exchange Capacity (CEC)  with a mean  42.64  (cmol/kg) that is proportional to the granular size of the soil that silty c

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Publication Date
Sun Jul 02 2017
Journal Name
Journal Of Educational And Psychological Researches
Prevalence of Posttraumatic Stress Symptomatology and Distribution of Attachment Patterns 1 and 5 Months after a Terrorist Attack
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As a consequence of a terrorist attack, people may experience posttraumatic stress disorder (PTSD) and lack of feeling secure in relationships. This longitudinal study aimed to examine the prevalence of PTSD symptoms over time, the relationship between adult attachment styles and PTSD, as well as their association with degree of exposure, and finally to consider the distribution and the trajectory of attachment styles. The sample consisted of 235 students (M=125, F=110) who were exposed to different levels of trauma intensity in response to a bombing attack. Participants were recruited and assessed approximately 1 month and 5 months after the attack using a battery of questionnaires. Findings revealed, as expected, that 79.5% of the part

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Publication Date
Fri Sep 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Removal of Ciprofloxacin Antibiotic from Synthesized Aqueous Solution Using Three Different Metals Nanoparticles Synthesized Through the Green Method
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This study investigates the possibility of removing ciprofloxacin (CIP) using three types of adsorbent based on green-prepared iron nanoparticles (Fe.NPs), copper nanoparticles (Cu. NPS), and silver nanoparticles (Ag. NPS) from synthesized aqueous solution. They were characterized using different analysis methods. According to the characterization findings, each prepared NPs has the shape of a sphere and with ranges in sizes from of 85, 47, and 32 nanometers and a surface area of 2.1913, 1.6562, and 1.2387 m2/g for Fe.NPs, Cu.NPs and Ag.NPs, respectively. The effects of various parameters such as pH, initial CIP concentration, temperature, NPs dosage, and time on CIP removal were investigated through batch experiments. The res

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Publication Date
Wed Jan 01 2020
Journal Name
Desalination And Water Treatment
Reducing endotoxin from dialysis water by using different disinfection processes
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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Using some Natural Minerals to Remove Cadmium from Polluted Water
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Water scarcity is one of the most important problems facing humanity in various fields such as economics, industry, agriculture, and tourism. This may push people to use low-quality water like industrial-wastewater. The application of some chemical compounds to get rid of heavy metals such as cadmium is an environmentally harmful approach. It is well-known that heavy metals as cadmium may induce harmful problems when present in water and invade to soil, plants and food chain of a human being. In this case, man will be forced to use the low quality water in irrigation. Application of natural materials instead of chemicals to remove cadmium from polluted water is an environmental friendly approach. Attention was drawn in this research wor

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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