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DETECTION OF Staphylococcus aureus CAUSED OF FOOD POISONING IN RED & WHITE MEAT OFFERED IN LOCAL MARKETS: DETECTION OF Staphylococcus aureus CAUSED OF FOOD POISONING IN RED & WHITE MEAT OFFERED IN LOCAL MARKETS
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This study was conducted to investigate the presence of Staphylococcus aureus in the red and white meat available in local markets. They were selected ten samples of red and white meat randomly (Iraq, Saudi Arabia, Turkey, and Brazil) from different markets in Baghdad, and the results of reading the nutrition facts of media indication card showed that all models confirm to the Iraqi standard quality in terms of scanning all data of the media indication card, except for the birds of Bayader, where the date of expire & production date of the product was not mentioned. Also, the results of the study showed that there is no Staphylococcus aureus in local red and white meat as well as imported.

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Publication Date
Wed Jun 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Haemoglobin Epsilon as a Biomarker for the Molecular Detection of Canine ‎Lymphoma
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Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Detection and interpretation of clouds types using visible and infrared satellite images
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One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Change detection of remotely sensed image using NDVI subtractive and classification methods.
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Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

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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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Publication Date
Tue Jan 01 2019
Journal Name
Biochemical And Cellular Archives
Phenotypic and molecular detection of Escherichia coli efflux pumps from UTI patients
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Publication Date
Wed Jan 01 2025
Journal Name
Computers, Materials & Continua
A Comprehensive Review of Dynamic Community Detection: Taxonomy, Challenges, and Future Directions
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In recent years, the evolution of the community structure in social networks has gained significant attention. Due to the rapid and continuous evolution of real-world networks over time. This makes the process of identifying communities and tracking their topology changes challenging. To tackle these challenges, it is necessary to find efficient methodologies for analyzing the behavior patterns of dynamic communities. Several previous reviews have introduced algorithms and models for community detection. However, these methods have not been very accurate in identifying communities. Moreover, none of the reviewed papers made an apparent effort to link algorithms that can accurately detect dynamic communities. This review aims to present a ta

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The Reflection Of The Financial Reporting Of Intellectual Capital Investment Decisions
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Abstract

The intellectual capital an important variable in the equation of the success of seeking economic units to achieve a competitive advantage, since it is a real capital for economic unity it constitutes a strategic importance as the main source to achieve high profitability in the economic unit and highlights the importance of showing intellectual capital components of the main Represent of human capital and structural capital and relational capital, through effective and the prominent role played by intellectual capital within the economic unity in order to achieve a sustainable competitive advantage contribute to attracting investors with longer investment decision of the most important and difficult decisions ta

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Publication Date
Thu Mar 31 2022
Journal Name
Journal Of The College Of Education For Women
The Reality of Evaluating Teacher Performance in the Sultanate of Oman in Light of Global Models
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The aim of the research is to reveal the reality of teacher performance evaluation in the Sultanate of Oman in light of some global models. The study followed a qualitative descriptive research design. Seven forms of teacher formative and summative assessments were analyzed. Besides, an analytical template was developed, consisting of six areas related to the teaching performance of teachers. These included: lesson planning and preparation, learning environment, education, professional development, student academic, and community and parental partnership. The study reached a number of results; the most notable is the lack of change of forms for more than a decade despite the rapid development of the educational system in the sultanate in

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Publication Date
Fri Aug 14 2026
Journal Name
International Journal Of Medical Toxicology And Forensic Medicine
Anthocyanin Extraction and Purification from Red Onion Peels (Allium cepa) and Its Applications Against the CAL-51 Cell Line
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Background: Red onion (Allium cepa L.) peels represent an abundant agricultural byproduct rich in bioactive flavonoids, yet their therapeutic potential against aggressive breast cancer models remains poorly characterized. This study aimed to extract and purify anthocyanins from red onion peels, characterize their active constituents, and evaluate their selective in vitro cytotoxicity against the triple-negative breast cancer (TNBC) cell line CAL-51 relative to non-tumorigenic Normal Human Fibroblast (NHF) cells. Methods: Anthocyanins were extracted with acidified aqueous ethanol, purified using silica gel G60 column chromatography and characterized by reversed-phase high-performance liquid chromatography (RP-HPLC). Cytotoxicity was evaluate

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