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Experimental and Simulation for the Effect of Partial Shading on Solar Panel Performance
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Partial shading is one of the problems that affects the power production and the efficiency of photovoltaic module. A series of experimental work have been done of partial shading of   monocrystalline PV module; 50W, Isc: 3.1A, Voc: 22V with 36 cells in series is achieved. Non-linear power output responses of the module are observed by applying various cases of partial shading (vertical and horizontal shading of solar cells in the module). Shading a single cell (corner cell) has the greatest impact on output energy. Horizontal shading or vertical shading reduced the power from 41W to 18W at constant solar radiation 1000W/m2 and steady state condition. Vertical blocking a column of cells (9 cells) in a module reduces the power from 41W to 18W (53% power reduction); while, blocking one or two cell in the row reduces the power from 41 W to 18W (53% power reduction). Shading three or four cells in the same row reduces the power from 41W to 1W or 0.006W (94% power reduction). A complete Matlab / Simulink model are achieved to simulate the effect of partial shading on power output of module. It is found that shading a single cell reduces the power from 50 W to 25 W (50%) using Matlab/Simulink model. Comparisons have been made between the I-V and P-V characteristic curves from the simulation with the practical (experimental) curves. The results showed that the percentage of error between the Simulink results and the corresponding experimental measurement are 22% without shading effect and, 32% with partial shading.

 

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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Biological Activity of Levan Produced from Rhizospheric Soil Bacterium Brachybacterium phenoliresistens KX139300
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Levan is an exopolysaccharide produced by various microorganisms and has a variety of applications. In this research, the aim was to demonstrate the biological activity of levan which produced from B. phenoliresistens KX139300. These were done via study the antioxidant, anti-inflammatory, anticancer and antileishmanial activities in vitro. The antioxidant levan was shown 80.9% activity at 1250 µg/mL concentration. The efficient anti-inflammatory activity of 88% protein inhibition was noticed with levan concentration at 35 µg/mL. The cytotoxic activity of levan at 2500 µg/mL concentration showed a maximum cytotoxic effect on L20B cell line and promastigotes of Leishmani tropica. Levan has dose-dependent anticancer and antileishman

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Publication Date
Thu Jun 01 2023
Journal Name
Results In Engineering
Effectiveness of embedded through-section technique in strengthening reinforced concrete spandrel beams
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Publication Date
Thu Sep 01 2022
Journal Name
International Journal Of Engineering Transactions C: Aspects
Axial Behavior of Concrete Filled-steel Tube Columns Reinforced with Steel Fibers
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Concrete filled steel tube (CFST) columns are being popular in civil engineering due to their superior structural characteristics. This paper investigates enhancement in axial behavior of CFST columns by adding steel fibers to plain concrete that infill steel tubes. Four specimens were prepared: two square columns (100*100 mm) and two circular columns (100 mm in diameter). All columns were 60 cm in length. Plain concrete mix and concrete reinforced with steel fibers were used to infill steel tube columns. Ultimate axial load capacity, ductility and failure mode are discussed in this study. The results showed that the ultimate axial load capacity of CFST columns reinforced with steel fibers increased by 28% and 20 % for circular and square c

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Publication Date
Mon Sep 23 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Buckling analysis of reinforced composite plates with a multiwall carbon nanotube (MWCNT)
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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Estimation levels of CTHRC1and some cytokines in Iraqi patients with Rheumatoid Arthritis
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Collagen triple helix repeat containing-1 (CTHRC1) is an essential marker for Rheumatoid Arthritis (RA), but its relationship with pro-inflammatory, anti-inflammatory, and inflammatory markers has been scantily covered in extant literature. To evaluate the level of CTHRC1 protein in the sera of 100 RA patients and 25 control and compare levels of tumour necrosis factor alpha (TNF-α), interleukin 10 (IL-10), RA disease activity (DAS28), and inflammatory factors. Higher significant serum levels of CTHRC1 (29.367 ng/ml), TNF-α (63.488 pg/ml), and IL-10 (67.1 pg/ml) were found in patient sera as compared to that in control sera (CTHRC1 = 15.732 ng/ml, TNF-α = 33.788 pg/ml, and IL-10 = 25.122 pg/ml). There was no significant correlati

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Publication Date
Sun Dec 25 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Role of Topical Ritodrine Hydrochloride in Experimentally Induced Hypertrophic Scar in Rabbits
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Hypertrophic scars are fibroproliferative illnesses caused by improper wound healing, during that, excessive inflammation, angiogenesis, and differentiated human dermal fibroblast (HDF ) function contribute to scarring, whereas hyperpigmentation negatively affects scar quality. Over 100 million patients heal with a scar every year. To investigate the role of the beta 2 adrenergic receptor (β2AR); Ritodrine, in wound scarring, the ability of beta 2 adrenergic receptor agonist (β2ARag) to alter HDF differentiation and function, wound inflammation, angiogenesis, and wound scarring was explored in HDFs, zebrafish, chick chorioallantoic membrane assay (CAM), and a porcine skin wound model, respectively. A study identify a β2AR-mediated m

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Publication Date
Wed Mar 16 2022
Journal Name
Journal Of Communicable Diseases
Immune Response among Different Types of SARS-CoV-2 Vaccines in Iraq
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Introduction: COVID-19 vaccine have been indicated to successfully decrease the hazard for symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection furthermore associated hospitalisations. Objective: To study the immune response among different types of SARS-CoV-2 vaccines. Methods: This study includes 100 vaccinated individuals (43 Sinopharm, 30 AstraZeneca and 27 Pfizer) with one or two doses from different health centres in Baghdad. During the period from April 2021 to the end of May 2021, SARS-CoV-2 IgG and SARS-CoV-2 IgM levels were detected using AFIAS-6 device depending on FIA (Fluorescence Immunoassay) technique. Results: 93% of the cases were positive for IgG levels, and negative in 7% case

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Publication Date
Thu May 07 2015
Journal Name
Journal Of Infrared, Millimeter, And Terahertz Waves
Distinguishing Gasoline Engine Oils of Different Viscosities Using Terahertz Time-Domain Spectroscopy
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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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