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Isolation and Identification of Fungi from Clinical Samples of Diabetic Patients and Studying the Anti-Fungal Activity of Some Natural Oils on Isolated Fungi
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Isolation of fungi was performed from February to July, 2019. One hundred clinical specimens were collected from King Abdullah Hospital (KAH) Bisha, Saudi Arabia. Samples were collected from twenty patients of different ages (30 - 70 years old) ten males and ten females. The samples were collected from patients with the two types of diabetics. Specimens included blood, hair, nail, oral swabs and skin.  Specimens were inoculated on Sabourauds Dextrose agar containing chloramphenicol. Thirteen fungal species were isolated and identified. The isolated species were: Aspergillus flavus, A. niger, A. terrus, A. nidulans, A. fumigatus, Candida albicans, C. krusei, C. parapsilosis, C. Tropicalis, Curvularia lunata, Fusarium solani, Penicillium marneffei and Saccharomyces cerevisiae. Identification of molds was carried out morphologically and microscopically using available methods and books of identification, while identification of yeasts was carried out using API system. C. albicans recorded the highest isolated number where 31 colonies were isolated from 18 patients, representing relative density of 22.5%. (R. D.: is the number of a certain fungal species divided by the total number of fungi). Other isolated fungal species recorded relative density less than 16 %. The most common isolated fungus Candida albicans was molecularly identified using the 5.8S and flanking ITS regions. The antifungal activity of some natural essential oils (cinnamon, thyme, coconut, almond and clove) was assayed against isolated fungi using disk diffusion method. The used concentration was 5 µl / plate. The MIC values were also determined using different oil concentrations (1, 2.5, 5, 10, 20 and 40 µl / disc).

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
First principles calculations of Al AsxP1-x ternary nanocrystal alloying composition
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III-V zinc-blende AlP, AlAs semiconductors and their alloy Aluminum Arsenide phosphide Al AsxP1-x ternary nanocrystals have been investigated using Ab- initio density functional theory (Ab-initio-DFT) at the generalized-gradient approximation (GGA) level with STO-3G basis set coupled with large unit cell method (LUC). The dimension of crystal is found around (1.56 – 2.24) nm at a function of increasing the sizes (8, 16, 54, 64) with different concentration of arsenide (x=0, 0.25, 0.5, 0.75 and 1) respectively. Gaussian 03 code program has been used throughout this study to calculate some of the physical properties such as the electronic properties energy gap, lattice constant, valence and conduction band as well as density of state. Re

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Publication Date
Thu Jul 01 2021
Journal Name
Journal Of Applied Sciences And Nanotechnology
Homogeneity of Lithium Metasilicate-Copper Oxide Glass-Ceramics by Weibull Modulus
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Publication Date
Wed Nov 07 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Early detection of first degree relatives to type-II diabetes mellitus
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Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio

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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Wed Apr 01 2020
Journal Name
Biochem. Cell. Arch.
6-Mercaptopurine Derivatives: Maintenance Therapy Of Acute Lymphoblastic Leukemia: A Review
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Publication Date
Sat Feb 28 2015
Journal Name
Al-khwarizmi Engineering Journal
Stabilizing Gap of Pole Electric Arc Furnace Using Smart Hydraulic System
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Abstract

Electric arc furnace applications in industry are related to position system of its pole, up and down of pole. The pole should be set the certain gap. These setting are needed to calibrate. It is done manually. In this research will proposed smart hydraulic to make this pole works as intelligent using proportional directional control valve. The output of this research will develop and improve the working of the electric arc furnace. This research requires study and design of the system to achieve the purpose and representation using Automation Studio software (AS), in addition to mathematically analyzed and where they were building a laboratory device similar to the design and conduct experiments to stud

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Publication Date
Sun Apr 30 2023
Journal Name
Sabrao Journal Of Breeding And Genetics
PATH COEFFICIENT ANALYSES OF INTRODUCED RICE VARIETIES UNDER DIFFERENT PLANTING DISTANCES
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Five rice (Oryza sativa L.) cultivars (N22, Amber, Moroberekan, Kinandang Patong, and Azucena) underwent path coefficient analysis across three plant spacings (15 cm × 15 cm, 20 cm × 20 cm, and 25 cm× 25 cm) in the summer of 2017 at the College of Agricultural Engineering Sciences, University of Baghdad, Al-Jadriya, Iraq. The experiment proceeded in a randomized complete block design (RCBD) with a split-plot arrangement and three replications. The main plots included three planting distances, and the subplot comprised five varieties. The traits studied were plant height, flag leaf area, number of tillers, panicle number, length and branches, grains per panicle, 1000-grain weight, and the percentage of unfilled grains. The results

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering
Load-settlement Behavior of Steel Piles in Different Sandy Soil Configurations
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In the case where a shallow foundation does not satisfy with design requirements alone, the addition of a pile may be suitable to improve the performance of the foundation design. The lack of in-situ data and the complexity of the issues caused by lagging in the research area of pile foundations are notable. In this study, different types of piles were used under the same geometric conditions to determine the load-settlement relationships with various sandy soil relative densities. The ultimate pile capacity for each selected pile is obtained from a modified California Bearing Ratio (CBR) machine to be suitable for axial pile loading. Based on the results, the values of Qu for close-ended square pile were increased by 15

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
Pulse Profile Rule in Laser Heating of Opaque Targets in Air
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A theoretical model is developed to determine time evolution of temperature at the surface of an opaque target placed in air for cases characterized by the formation of laser supported absorption waves (LSAW) plasmas. The model takes into account the power temporal variation throughout an incident laser pulse, (i.e. pulse shape, or simply: pulse profile).
Three proposed profiles are employed and results are compared with the square pulse approximation of a constant power.

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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Solving multicollinearity problem of gross domestic product using ridge regression method
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This study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq. This data has normal distribution. The best linear regression model is obtained after solving multicollinearity problem with the suggesting of 10 k value.

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