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The Minimum Inhibitory Concentration (MIC) and Minimum fungicidal concentration(MFC) of extracted oil of lemon grass and thyme against Candida spp. and Bacteria Spp. Isolated from children with oral thrush
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120 samples were collected from children (ages between new born and 10 years) who infected with oral thrush. The results revealed that the Minimum Inhibitory Concentration (MIC) and Minimum Fungicidal Concentration (MFC) of extracted oil of lemon grass against C.albicans, C.tropicalis, C.keyfr, C.glabrata and C.guilliermondii were 1.25,1.25,1.25,2.5 and 2.5µl/ml and 2.5, 2.5, 2.5, 5 and 5 µl /ml respectively. while the (MIC) and (MFC) for the extraction oil of thyme against C.albicans, C.tropicalis, C.keyfr, C.glabrata and C.guilliermondii were 0.6, 0.6, 1.25, 1.25, and 1.25µl/ml and 1.25, 1.25, 2.5, 2.5, and 2.5µl/ml respectively . While the value of (MIC) and (MFC) for Nystatin against Candida species were 32 and 64 µg / ml respectively. On the other hand the Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) value of exctracted oil for lemon grass against E.coli, S. aureus and S. pyogenes were 5, 2.5 and 2.5 µl/ml and 10 , 5 and 5µl /ml respectively. while the (MIC) and (MBC) value of exctracted oil for thyme against E.coli, S. aureus and S. pyogenes were 2.5, 2.5 and 1.25 µl/ml and 5 , 5 and 2.5µl /ml respectively.

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Publication Date
Mon May 01 2023
Journal Name
Journal Of Pure And Applied Microbiology
The Immunohistochemical Staining of Vimentin and E-Cadherin in Bladder Cancer Patients Infected with Hepatitis C Virus
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Publication Date
Thu May 18 2023
Journal Name
J Pure Appl Microbiol.
The Immunohistochemical Staining of Vimentin and E-Cadherin in Bladder Cancer Patients Infected with Hepatitis C Virus
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The invasion and spread of cancer cells are two of the most notable characteristics of malignant tumors. Recent studies suggest that the epithelial-mesenchymal transition (EMT) has been linked to this significant occurrence. It is linked to the absence of the epithelial brow and the presence of mesenchymal facial hair. The aims of the present study were to explore the immunohistochemical staining of vimentin and E-cadherin ex vivo as EMT markers and assess their potential as predictive biomarkers for transitional cell cancer (TCC). In this study, 55 paraffin-embedded biopsies from TCC patients and 10 autopsies that appeared to be normal were included. Immunohistochemistry was used to produce patterns of vimentin and E-cadherin expression. W

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Publication Date
Thu Apr 01 2021
Journal Name
Biochemical And Cellular Archives
Improvement in the Growth of Cumin Plant, Cuminum Cyminum L. with Spraying Tryptophan and Iq Combi Nanofertilizer
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The experiment was carried out in the Department of Biology, College of Education for Pure Science –Ibn AL Haitham, University of Baghdad, Iraq, during the growing season 2017 – 2018. The objective was to find out the effect of foliar spraying of tryptophan and IQ COMBI nano fertilizer on cumin plants. The obtained results show that both tryptophan and IQ COMBI nano fertilizer increased plant height, root length, shoot dry weight, the content of nitrogen, phosphorus, potassium, protein percentage, no. compound umbel.plant-1, wt. seeds. plant-1. The optimum treatment combination was calculated as 30 mg.L-1 tryptophan, 1000mg.L-1 IQ COMBI nano fertilizer, which gave the highest values for most of the parameters studied

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Publication Date
Sun Dec 05 2010
Journal Name
Baghdad Science Journal
Pre-Test Single and Double Stage Shrunken Estimators for the Mean of Normal Distribution with Known Variance
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This paper is concerned with pre-test single and double stage shrunken estimators for the mean (?) of normal distribution when a prior estimate (?0) of the actule value (?) is available, using specifying shrinkage weight factors ?(?) as well as pre-test region (R). Expressions for the Bias [B(?)], mean squared error [MSE(?)], Efficiency [EFF(?)] and Expected sample size [E(n/?)] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants included in these expressions. Comparisons between suggested estimators, with respect to classical estimators in the sense of Bias and Relative Efficiency, are given. Furthermore, comparisons with the earlier existing works are drawn.

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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Investigating the correlation of AE-index with different solar wind parameters during strong and severe geomagnetic storms
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Publication Date
Thu May 16 2019
Journal Name
Al-khwarizmi Engineering Journal
Study of Transverse and Longitudinal Crack Propagation in Human Bone Using the Finite Element Method with MATLAB
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A finite element is a study that is capable of predicting crack initiation and simulating crack propagation of human bone. The material model is implemented in MATLAB finite element package, which allows extension to any geometry and any load configuration. The fracture mechanics parameters for transverse and longitudinal crack propagation in human bone are analyzed. A fracture toughness as well as stress and strain contour are generated and thoroughly evaluated. Discussion is given on how this knowledge needs to be extended to allow prediction of whole bone fracture from external loading to aid the design of protective systems.

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Publication Date
Fri Feb 20 2026
Journal Name
Journal Of Engineering
Parametric Study Of Laminar Free Convection In Horizontal Annulus With And Without Fins On The Inner Cylinder
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Publication Date
Sun May 05 2024
Journal Name
Review Of Clinical Pharmacology And Pharmacokinetics - International Edition
Emergency department presentation and management of patients with acute decompensated heart failure at the Baghdad Teaching Hospital
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Acute decompensated heart failure (ADHF) is a leading cause of hospital admission and many factors are known to precipitate decompensation. We aimed to assess the decompensating factors of heart failure and the management of patients admitted to the emergency department (ED). A total of 107 patients were examined, all diagnosed with ADHF in the ED of the Baghdad Teaching Hospital, from June 2017 to December 2017, and presenting with decom¬pensation (pulmonary oedema, peripheral oedema, and fatigue). The mean patient age was 62.5 ± 9.8 years (range: 43–85 years); the majority of them were in their 7th decade (37.4%), and men were slightly more than women. Hy¬pertension was the most commonly associated comorbidity (68.2%), follow

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Publication Date
Sun Sep 22 2019
Journal Name
Baghdad Science Journal
Investigating the Histological Changes in Heart, Lung, Liver and Kidney of Male Albino Mice Treated with Ivabradine
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            The present study aimed to investigate the histological changes of heart, lung, liver and kidney which caused by different concentrations (10, 20 and 40 mg/kg) of Ivabradine. Results of the study revealed some histological changes represented by aggregation of the lymphocytes around respiratory bronchioles of the lung. In the liver, the drug caused hepatocyte necrosis and infiltration of the lymphocytes. In Kidney, there are no histopathological modifications in the tissue after the animals treated with 10 mg\kg of Ivabradine. When the animals treated with Ivabradine drug at 20mg/kg of bw, dose showed vascular congestion between myocardial fibers of heart. Emphysematous c

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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