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Regression Analysis Models to Predict the 28 -day Compressive Strength Using Accelerated Curing Tests
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Regression analysis models are adopted by using SPSS program to predict the 28-day compressive strength as dependent variable and the accelerated compressive strength as independent variable. Three accelerated curing method was adopted, warm water (35ºC) and autogenous according to ASTM C C684-99 and the British method (55ºC) according to BS1881: Part 112:1983. The experimental concrete mix design was according to ACI 211.1. Twenty eight concrete mixes with slump rang (25-50) mm and (75-100)mm for rounded and crushed coarse aggregate with cement content (585, 512, 455, 410, 372 and 341)Kg/m3.

      The experimental results showed that the accelerated strength were equal to about (0.356), (0.492) and (0.595) of the 28-day compressive strength for warm water, autogenous and British curing methods respectively. A statistical regression analysis using SPSS program is implemented for the experimental results of the 28-day compressive strength ranging from (16 to 55.2)Mpa and accelerated strength for different curing methods. The linear models with high R2 and F-value are adopted for different curing methods while the Power model with constant is the best model for non parametric analysis.

 

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Publication Date
Fri Feb 13 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Oral manifestations, biochemical, and IL-6 analysis of saliva in major depressive disorder patients under treatment
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Background: Major depressive disorder (MDD) is mental disorder characterized by an all-encompassing low mood accompanied by low self-esteem, and by loss of interest or pleasure in normally enjoyable activities. The aims of the study: were to determine the prevalence of oral manifestation among patients with major depressive disorder receiving antidepressant drugs, and detect alkaline phosphatase (ALP), Total Salivary proteins (TSP), and Interleukin-6 (IL-6) in relation to MDD patients under treatment and to compare with healthy controls. Materials and method: (50) MDD patients; between the ages of 20 years and 60 years.The depression patients are divided into (25) patients under treatment with fluoxetine (Prozac), and (25) patients under tr

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Publication Date
Fri Sep 26 2025
Journal Name
Applied Data Science And Analysis
Deep Learning in Genomic Sequencing: Advanced Algorithms for HIV/AIDS Strain Prediction and Drug Resistance Analysis
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Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

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Publication Date
Fri Oct 01 2021
Journal Name
Physica E: Low-dimensional Systems And Nanostructures
In-situ lattice structure analysis in sp2 hybridization of stable carbon isotopes: Precision modelling of temperature
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Publication Date
Sat Dec 01 2018
Journal Name
International Journal Of Greenhouse Gas Control
Experimental pore-scale analysis of carbon dioxide hydrate in sandstone via X-Ray micro-computed tomography
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Carbon dioxide geo-sequestration (CGS) into sediments in the form of (gas) hydrates is one proposed method for reducing anthropogenic carbon dioxide emissions to the atmosphere and, thus reducing global warming and climate change. However, there is a serious lack of understanding of how such CO2 hydrate forms and exists in sediments. We thus imaged CO2 hydrate distribution in sandstone, and investigated the hydrate morphology and cluster characteristics via x-ray micro-computed tomography in 3D in-situ. A substantial amount of gas hydrate (∼17% saturation) was observed, and the stochastically distributed hydrate clusters followed power-law relations with respect to their size distributions and surface area-volume relationships. The layer-

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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Engineering
Numerical analysis of a concrete foundation under a combination of a dynamic and a seismic load
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Improving in assembling technology has provided machines of higher evaluation with better resistances and managed behavior. This machinery led to remarkably higher dynamic forces and therefore higher stresses. In this paper, a dynamic investigation of rectangular machine diesel and gas engines foundation at the top surface of one-layer dry sand with various states (i.e., loose, medium and dense) was carried out. The dynamic investigation is performed numerically by utilizing limited component programming, PLAXIS 3D. The soil is accepted as flexible totally plastic material submits to Mohr-Coulomb yield basis. A harmonic load is applied at the foundation with amplitude of 10 kPa at a frequency of (10, 15 and 20) HZ and se

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Analysis and Control of PWM Buck-Boost AC Chopper Fed Single-Phase Capacitor Run Induction Motor
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Single phase capacitor-run induction motors (IMs) are used in various applications such as home appliances and machine tools; they are affected by the sags or swells and any fault that can lead to disturb the supply and make it produce rms voltage below or above the rated motor voltage, which is 220V. A control system is designed to regulate the output voltage of the converter irrespective to the variation of the load and within a specific range of supply voltage variation. The steady-state equivalent circuit of the Buck-Boost chopper type AC voltage regulator, as well as the analysis of this circuit are presented in this paper. Switching device for the regulator is an IGBT Module. The proposed chopper uses pulse width modulation (PWM) c

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Publication Date
Fri Jun 29 2018
Journal Name
Journal Of Engineering
Experimental Study and Analysis on Degradation of Oily Sludge from Process Equipment by Continuous Hybrid Treatment
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It is well known that petroleum refineries are considered the largest generator of oily sludge which may cause serious threats to the environment if disposed of without treatment. Throughout the present research, it can be said that a hybrid process including ultrasonic treatment coupled with froth floatation has been shown as a green efficient treatment of oily sludge waste from the bottom of crude oil tanks in Al-Daura refinery and able to get high yield of base oil recovery which is 65% at the optimum operating conditions (treatment time = 30 min, ultrasonic wave amplitude = 60 micron, and (solvent: oily sludge) ratio = 4). Experimental results showed that 83% of the solvent used was recovered meanwhile the main water

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Publication Date
Mon Jun 04 2018
Journal Name
Baghdad Science Journal
Structural Analysis of Chemical and Green Synthesis of CuO Nanoparticles and their Effect on Biofilm Formation
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Copper oxide nanoparticles (CuO NPs) were synthesized by two methods. The first was chemical method by using copper nitrate Cu (NO3)2 and NaOH, while the second was green method by using Eucalyptus camaldulensis leaves extract and Cu (NO3)2. These methods easily give a large scale production of CuO nanoparticles. X-ray diffraction pattern (XRD) reveals single phase monoclinic structure. The average crystalline size of CuO NPs was measured and used by Scherrer equation which found 44.06nm from chemical method, while the average crystalline size was found from green method was 27.2nm. The morphology analysis using atomic force microscopy showed that the grain size for CuO NPs was synthesized by chemical and green methods were 77.70 and 89.24

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Publication Date
Mon Jan 01 2024
Journal Name
Optical Materials
Design and analysis of a high sensitivity open microchannel PCF-based surface plasmon resonance refractometric sensor
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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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