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Analysis of fatty acids of liver in the embryo and adult of domesticated chicken gallus gallus domesticus
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The fatty acids in the embryo's liver at ages (7, 11, 14 and 19) days incubation, small chicken aged (14) days after hatching and adult were analyzed, and found (5) fatty acids, the highest concentration of fatty acid in the adult of domesticated chicken and lowest concentration in small chicken age (14) days after hatching. Statistically, there were high significant differences at the probability level (P≤0.001) between all ages together, and the highest concentrations of Oleic acid (C18:1) and Linoleic acid (C18:2) were in embryo age (7) days incubation, while in embryo age (11) days incubation Stearic acid (C18:0) and α-Linolenic acid (C18:3) were higher concentration and Palmitic acid (C16:0) was the highest concentration in the adult. Stearic, Palmitic, Linoleic and α-Linolenic acids were recorded as the lowest concentration as well as in a small chicken age (14) days after hatching. Oleic acid had the lowest concentration in the embryo (19) days incubation, as well as α-Linolenic acid in the embryos age (7, 19) days incubation and the adult chicken did not record any concentration.

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Publication Date
Mon Jan 01 2018
Journal Name
Communications In Computer And Information Science
Automatically Recognizing Emotions in Text Using Prediction by Partial Matching (PPM) Text Compression Method
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

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Publication Date
Sun Dec 15 2019
Journal Name
Al-academy
Revitalizing Interior Designs in Religious Shrines: رؤى صلاح الدين حامد فريد-فاتن عباس الاسدي
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  The current research is interested in the objective study of revitalizing the religious sites and the extent to which they achieve the pragmatic and semantic ends, because they are derived from history and civilization and have a clear impact over the recipient. The research question is (what are the techniques of developing the spaces of the religious shrines in accordance with revitalizing the interior spaces within them?).
The research aims at determining the weak and strong points in the process of revitalizing the interior spaces in the religious shrines.
The theoretical framework consists of two parts: the first addressed the revitalization in the interior design, and the second addressed the religious shrines and th

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Publication Date
Wed Dec 12 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment Pregnant Women’s Knowledge Regarding Syphilis at Primary Health care centers in Baghdad City
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Objectives: To assess pregnant women’s knowledge regarding syphilisand to find out the relationship between women’s knowledge regarding syphilis infection and demographic and reproductive variables. Methodology: A descriptive analytical study of non probable (purposive sample) of 250 pregnant women during their different gestational ages for the period (October 2nd to April 25th 2013) by using questionnaire format consists of demographic variables and items of women's knowledge regarding syphilis who are visiting primary health care centers in Al-Kharkh and Al-Rrusafa in Baghdad city. The coefficient relia

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm
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Publication Date
Sun Dec 04 2016
Journal Name
Baghdad Science Journal
Biochemical Study on Anti Thyroid Peroxidase in Type 2 Diabetic patients with thyroid disorders
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Type 2 diabetes mellitus (T2DM) is the most frequent endocrinal disease commonly associated with thyroid disorders .The study is conducted at the Specialized Center for Endocrinology and Diabetes in Baghdad ,during December 2014 up to October 2015.This study was done to investigate the prevalence of anti- thyroid peroxidase (Anti-TPO) antibody in patients suffered from type 2 diabetes with thyroid disorders .The study groups included a total number of 80 subjects consisting of 60 type 2 diabetic patients divided into 20 hyperthyroidism subjects (group 1) ,20 hypothyroidism subjects (group 2), 20 euthyroidism subjects (group 3) and 20 healthy controls (group 4) . The fasting blood samples were analyzed for (T3,T4,TSH) by using Vitek Immuno d

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Publication Date
Mon Nov 01 2021
Journal Name
Energies
Solidification Enhancement in a Triple-Tube Latent Heat Energy Storage System Using Twisted Fins
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This work evaluates the influence of combining twisted fins in a triple-tube heat exchanger utilised for latent heat thermal energy storage (LHTES) in three-dimensional numerical simulation and comparing the outcome with the cases of the straight fins and no fins. The phase change material (PCM) is in the annulus between the inner and the outer tube, these tubes include a cold fluid that flows in the counter current path, to solidify the PCM and release the heat storage energy. The performance of the unit was assessed based on the liquid fraction and temperature profiles as well as solidification and the energy storage rate. This study aims to find suitable and efficient fins number and the optimum values of the Re and the inlet tem

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Ecological Engineering
Contaminants Removal from Real Refinery Wastewater Associated with Energy Generation in Microbial Fuel Cell
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Publication Date
Sun Sep 01 2024
Journal Name
Journal Of Energy Storage
Nanofluid-assisted enhanced sealing security for efficient geological hydrogen storage in Saudi Arabian basalt
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The modification of hydrophobic rock surfaces to the water-wet state via nanofluid treatment has shown promise in enhancing their geological storage capabilities and the efficiency of carbon dioxide (CO2) and hydrogen (H2) containment. Despite this, the specific influence of silica (SiO2) nanoparticles on the interactions between H2, brine, and rock within basaltic formations remains underexplored. The present study focuses on the effect of SiO2 nanoparticles on the wettability of Saudi Arabian basalt (SAB) under downhole conditions (323 K and pressures ranging from 1 to 20 MPa) by using the tilted plate technique to measure the contact angles between H2/brine and the rock surfaces. The findings reveal that the SAB's hydrophobicity intensif

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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