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Some Ur III Texts from Irisagrig in the Iraq Museum
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This article publishes seven cuneiform tablets in the collection of the Iraq Museum Baghdad. Six of the tablets have an Irisagrig/Al Sarraki provenance, the seventh is of uncertain origin. They are dated to the reigns of Amar-Suen (AS) and Ibbi-Suen (IS) of the Ur III Dynasty. The texts represent administrative texts of the governing institutions and account for economic activities including the assignment of female workers for wool plucking, the remuneration of canal work with barley and the selection of wool for textiles. Three tablets record offerings in respect of cultic observances, two of which describe the disbursement of foodstuffs for the king's monthly 83-63 offerings to the new moon.

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Publication Date
Tue Jan 01 2013
Journal Name
Iraqi Journal Of Science
Effect of LPS Extracted from Campylobacter coli on Lymphocyte Transformation
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Publication Date
Sat Apr 25 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Production, Analysis and Optimization of Inulin Produced from Pseudomonas fluorescens
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Publication Date
Thu Jun 01 2017
Journal Name
Process Biochemistry
Microbial levan from Brachybacterium phenoliresistens : Characterization and enhancement of production
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Publication Date
Fri Dec 01 2023
Journal Name
Environmental Processes
Removal of Dyes from Aqueous Solutions using Non-Thermal Plasma
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Publication Date
Thu May 25 2023
Journal Name
Asian Journal Of Water, Environment And Pollution
Microbial Simultaneous Eradication from Wastewater of Sulphate and Heavy Metals
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Hazardous materials, heavy metals, and organic toxins released into the environment have caused considerable harm to microbes, plants, animals, and humans. Wastewater is one of the most contaminated ecosystems due to heavy metals emitted mostly by human activity. Bioremediation of wastewater is an ecologically acceptable and cost-effective method of removing heavy metals from sewage; the general purpose of this study is to analyse the dependability of anaerobic sludge biomass in removing sulfur compounds and heavy metals from waste water. The anaerobic sludge biomass evaluated in this work was taken from a wastewater treatment plant (WWTP) in Al-Rustumiya, Baghdad, and grown in the mineral medium for anaerobic growth. In serum bottl

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
New algorithms to Enhanced Fused Images from Auto-Focus Images
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Enhancing quality image fusion was proposed using new algorithms in auto-focus image fusion. The first algorithm is based on determining the standard deviation to combine two images. The second algorithm concentrates on the contrast at edge points and correlation method as the criteria parameter for the resulted image quality. This algorithm considers three blocks with different sizes at the homogenous region and moves it 10 pixels within the same homogenous region. These blocks examine the statistical properties of the block and decide automatically the next step. The resulted combined image is better in the contras

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Activated Bentonite for Removal Nickle and Vanadium from Petroleum Distillates
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The present work is to investigate the feasibility of removal vanadium (V) and nickel (Ni) from Iraqi heavy gas oil using activated bentonite. Different operating parameters such as the degree of bentonite activation, activated bentonite loading, and operating time was investigated on the effect of heavy metal removal efficiency. Experimental results of adsorption test show that Langmuir isotherm predicts well the experimental data and the maximum bentonite uptake of vanadium was 30 mg/g. The bentonite activated with 50 wt% H2SO4 shows a (75%) removal for both Ni and V. Results indicated that within approximately 5 hrs, the vanadium removal efficiencies were 33, 45, and 60% at vanadium loadings of 1

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Publication Date
Sun May 05 2024
Journal Name
Review Of Clinical Pharmacology And Pharmacokinetics - International Edition
Isolation and characterization of a tetrahydroprotoberberine alkaloid from Crassula ovata
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The presence of alkaloids in Crassula ovata is a topic that is still unexplored, as there are no published studies on the matter. This study demonstrates the presence of an alkaloid compound (and its class) for the first time in Crassula ovata. The plant material was defatted with n-hexane, and a Soxhlet apparatus was used for the extraction process, while the acid-base method was used for the isolation of alkaloids from the chloroform fractions. The quaternary alkaloid was precipitated from the aqueous layer spontaneously, in high quantity. By using standard spectroscopic methods (including liquid chromatography - mass spectroscopy) we were able to clarify the structure of the precipi¬tated compound as a tetrahydroprotoberberine a

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Power Generation from Utilizing Thermal Energy of Hazardous Waste Incinerators
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A large amount of thermal energy is generated from burning hazardous chemical wastes, and the temperature of the flue gases in hazardous waste incinerators reaches up to (1200 °C). The flue gases are cooled to (40°C) and are treated before emission. This thermal energy can be utilized to produce electrical power by designing a system suitable for dangerous flue gases in the future depending on the results of much research about using a proto-type small steam power plant that uses safe fuel to study and develop the electricity generation process with water tube boiler which is manufactured experimentally with theoretical development for some of its parts which are inefficient in experimental work. The studied system gen

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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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