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Prediction of The Chemical Composition and Physical properties of Aged Asphalt Cement
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In the present work a modification was made on three equations to represent the
experiment data which results for Iraqi petroleum and natural asphalt. The equations
have been developed for estimating the chemical composition and physical properties
of asphalt cement at different temperature and aging time. The standard deviations of
all equations were calculated.
The modified correlation related to the aging time and temperature with penetration
index and durability index of aged petroleum and natural asphalts were developed.
The first equation represents the relationship between the durability index with aging
time and temperature.

loge(DI)=a1+0.0123(2loge T-a3(1/30.t2+1/2.t))


The second equation represents the relationship between the penetration index with
aging time and temperature.

Log(PI)e=b1-0.2013(T-(b3+b4t))2
The third equation represents the relationship between the durability index with
penetration index.

Logeloge(PI)=a-0.5627loge(DI)
The values of penetration index and durability index for all aged samples were
compared with predicted values. These correlations give a percent of error in the
range of 1.2 to 7.4%.

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Publication Date
Tue Oct 12 2021
Journal Name
Engineering, Technology & Applied Science Research
The Effect of Nanomaterials on the Properties of Limestone Dust Green Concrete
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Portland cement is considered the most involved product in environmental pollution. It is responsible for about 10% of global CO2 emissions [1]. Limestone dust is a by-product of limestone plants and it is produced in thousands of tons annually as waste material. To fulfill sustainability requirements, concrete production is recommended to reduce Portland cement usage with the use of alternative or waste materials. The production of sustainable high strength concrete by using nanomaterials is one of the aims of this study. Limestone dust in 12, 16, and 20% by weight of cement replaced cement in this study. The study was divided into two parts: the first was devoted to the investigation of the best percentage of replacement of waste

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Determining ACE-2 Level and Some Relevant Biochemical Parameters and studying the effect of Gender in Iraqi Diabetic Patients with Glomeruli and Renal Tubules Fibrosis as Early Prediction Marker
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     Diabetic kidney disease is an illness of the glomerulus that interferes with the glomerular filtration barrier (GFB), which is worked to enable kidney to selective purification of water and solutes in addition to limiting the movement of large macromolecules such as albumin. In the glomerular endothelium, mesangial cells, foot cells, and the brush border of the proximal tubules, ACE-2 is expressed and that the kidneys represent the highest-expressing region of this enzyme. Thus, the current study aimed to evaluate ACE-2 level in this case compared to healthy condition. The study Conducted with 120 male and female ranging in age (30-65) years old. Ninety patients with type 2 diabetes subdivided into three groups on the basis of A

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Effect of Metakaolin on the geotechnical properties of Expansive Soil
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Expansive soil spreads in Iraq and some countries of the world. But there are many problems can be occurred to the structures that built on, so we must study the characteristics of these soils due to the  problems that may be caused to these structures which built on these kinds of soil and then study the methods of treatment. The present study focuses on improving  the geotechnical properties of expansive soils by treating it Metakaolin(M). Metakaolin (M) has never been used before as an improvement material  for stabilizing the expansive soil . Metakaolin  is a pozzolanic material. It’s obtained by calcination of kaolinite clay at temperatures from 700°C to 800°C. Kaolin chemical composition is

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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Physical Education
Body Image and Its Relationship With Self–Confidence In Female College of Physical Education and Sport Sciences Students
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سها علي حسين, هويدة إسماعيل إبراهيم, Journal of Physical Education, 2017 - Cited by 1

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Publication Date
Fri Apr 15 2022
Journal Name
Sustainability
Evaluation of Physio-Chemical Characteristics of Bio Fertilizer Produced from Organic Solid Waste Using Composting Bins
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Background: The possibility of converting the organic fraction of municipal solid waste to mature compost using the composting bin method was studied. Nine distinct treatments were created by combining municipal solid waste (MSW) with animal waste (3:1, 2:1), poultry manure (3:1, 2:1), mixed waste (2:1:1), agricultural waste (dry leaves), biocont (Trichoderm hazarium), and humic acid. Weekly monitoring of temperature, pH, EC, organic matter (OM percent), and the C/N ratio was performed, and macronutrients (N, P, K) were measured. Trace elements, including heavy metals (Cd and Pb), were tested in the first and final weeks of maturity. Results: Temperatures in the first days of composting reached the thermophilic phase in MSW compost

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Publication Date
Wed Jul 26 2017
Journal Name
Chemistry - A European Journal
Asymmetric Synthesis of Pyrrolidine-Containing Chemical Scaffolds via Tsuji-Trost Allylation of N-tert-Butanesulfinyl Imines
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Publication Date
Fri Apr 15 2022
Journal Name
Sustainability
Evaluation of Physio-Chemical Characteristics of Bio Fertilizer Produced from Organic Solid Waste Using Composting Bins
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Background: The possibility of converting the organic fraction of municipal solid waste to mature compost using the composting bin method was studied. Nine distinct treatments were created by combining municipal solid waste (MSW) with animal waste (3:1, 2:1), poultry manure (3:1, 2:1), mixed waste (2:1:1), agricultural waste (dry leaves), biocont (Trichoderm hazarium), and humic acid. Weekly monitoring of temperature, pH, EC, organic matter (OM percent), and the C/N ratio was performed, and macronutrients (N, P, K) were measured. Trace elements, including heavy metals (Cd and Pb), were tested in the first and final weeks of maturity. Results: Temperatures in the first days of composting reached the thermophilic phase in MSW compost

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Publication Date
Sun Mar 26 2023
Journal Name
Wasit Journal Of Pure Sciences
Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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Publication Date
Mon Mar 13 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Computer Assisted Immunohistochemical Score Prediction Via Simplified Image Acquisition Technique
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Background: techniques of image analysis have been used extensively to minimize interobserver variation of immunohistochemical scoring, yet; image acquisition procedures are often demanding, expensive and laborious. This study aims to assess the validity of image analysis to predict human observer’s score with a simplified image acquisition technique. Materials and methods: formalin fixed- paraffin embedded tissue sections for ameloblastomas and basal cell carcinomas were immunohistochemically stained with monoclonal antibodies to MMP-2 and MMP-9. The extent of antibody positivity was quantified using Imagej® based application on low power photomicrographs obtained with a conventional camera. Results of the software were employed

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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