Calcifying epithelial odontogenic tumour (CEOT) is a benign odontogenic neoplasm of epithelial origin that secretes an amyloid‐like protein tending towards calcification. This study aims to describe a case series from Iraq of one of the rarest odontogenic tumours.

    This study was based on the determination of aphid species that infested Chrysanthemum sp. (Asterales, Asteraceae) in the middle of Iraq; five aphid species belong to subfamily Aphidinae were recorded: Aphis fabae Scopoli, 1763, Aphis gossypii Glover, 1877,  Coloradoa rufomaculata (Wilson, 1908), Macrosiphoniella sanborni (Gillette, 1908) and Myzus persicae (Sulzer, 1776). A. gossypii was the most dominant species throughout the study period while M. persicae  is the lesser species.

    A summary of  the main taxonomic characters is presented here and a pictorial key which was designed to separate aphi

The genus of Chrysobothris Eschscholtz, 1829 is one of the most diverse and widespread genera of the family Buprestidae of some 700 described species distributed throughout the world. In Iraq, particularly in the Kurdistan region, about 4 species had been recorded so far, many of these species are sympatric, share larval host plants, and are difficult to reliably separate morphologically. The current study investigates species limits and relationships among the recognized species occurring within the Erbil Province; mitochondrial cytochrome C oxidase (COX I) molecular analysis confirmed the monophyly of two Chrysobothris species, Ch. affinis (Fabricius, 1794) and Ch. chrysostigma (Linnaeus, 1758). Implications of the resultant larval mor

Increased diseases and obesity currently due to increased production and excessive consumption of foods manufactured from non-food sweeteners without attention to the risk of consuming those additional high calories due to consuming these refreshing products such as juices and other various drinks, especially in the summer season by most segments of Iraqi society, especially workers, children and school students the aim of this study. Therefore, the study designed to replace sucrose with 0.03, 0.04 and 0.05% of each of the white stevia crystals and milled dry stevia leaves in the laboratory manufacture of juices and its effect on the general and sensory characteristics and the extent of their acceptability among the specialized r

In this study a polymeric composite material was prepared by hand
lay-up technique from epoxy resin as a matrix and magnesium oxide
(MgO) as a reinforcement with different weight fraction (5,10,15,
and 20)% to resin. Then the prepared samples were immersed under
normal condition in H₂So₄(1 M) solution, for periods ranging up to
10 weeks. The result revealed that the diffusion coefficient
decreasing as the concentration of MgO increase. Also we studied
Hardness for the prepared samples before and after immersion. The
result revealed that the hardness values increase as the concentration
of MgO increase, while the hardness for the samples after immersion
in H₂SO₄ dec

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: Few updated retrospective histopathological-based studies in Iraq evaluate a comprehensive spectrum of oro-maxillofacial lesions. Also, there was a need for a systematic way of categorizing the diseases and reporting results in codes according to the WHO classification that helps occupational health professionals in the clinical-epidemiological approach.

Objectives: to establish an electronic archiving database according to the ICD-10 that encompasses oro-maxillofacial lesions in Sulaimani city for the last 12 years, then to study the prevalence trend and correlation with clinicopathological parameters.

Subjects and Methods:  A descri