The study is done in the period between (February 20 and October 20) by using ten adult quail Coturnix coturnix (Linnaeus, 1758). The sections are preparing by paraffin method then stain in Harris haematoxylin-eosin. The histological aspects of spinal cord in quail (Coturnix coturnix) the white matter is in the outer part, while the gray matter is arranged in from of X represents its internal part, the dorsal region is called the dorsal horns while the ventral region is called the ventral horns and the central canal cavity, the spinal cord areas appeared as follows: The medial column, column of von Lenhossek, lateral column, dorsal magnocellular column and marginal paragriseal, columns are also called Hoffmann’s nuclei.

Objective: Many studies focused on clinical cases such as ovariohysterectomy of bitches and scarcely mentioned the histological features. The present study describes the cytoarchitecture characteristics of a local dog’s mature adult reproductive tract. Materials and Methods: Sixteen samples of uterus and cervix were obtained from local breed bitches to conduct this study. The organs were processed according to routine histopathological protocol and stained with hematoxylin and eosin, Masson’s trichrome, and combined Alcian blue (2.5 pH) and PAS (AB-PAS) stains. Results: The mature endometrium formed numerous short epithelial folds and epithelial crypts composed of mucous cells and cuboidal cells. The core of the endometrium is c

Allium ampeloprasum extract has the potential to facilitate wound healing due to its anti-inflammatory, antioxidant, and antibacterial properties. In this study, we aimed to investigate the potential wound-healing activity of the methanol extract derived from Allium ampeloprasum. Using 30 healthy male Wester rats; control group: 15 rats; normal saline applied locally instead of plant-extract. Experimental group: 15 rats received a daily local application of 200 mg/kg of the plant extract. Then, for each healing period of 0, 5, or 10 days, each group was divided into three-subgroups: A, B, and C, each with five rats. There was a significant difference in the percentage of wound contraction between the control and experimental groups (p 0.02)

Sludge worm samples were collected from the Tigers River sediment during the period from November 2018 to June 2019 in Al Sarafiya District/ Baghdad- Iraq. Biometric morphological measurements focusing on the form of penis sheath and chaetal morphology were used for species identification, in addition to molecular analysis by amplification of conserved 18s rRNA encoding gene using ITS1 and ITS4 universal primers.According to the morphological measurement records, the results revealed the existence of Limnodrilus hoffmeisteri Claparede 1862, L. claparedeianus Ratzel, 1868 and L. cervix Brinkhurst 1963. Other two groups of specimens, with short penis sheath, were identified by molecular technology as L

Leuciscidae species are the abundant and widely distributed fish species in Iraq's inland waters. They are complex species, and morphology makes them difficult to identify. Molecular analysis achieved and confirmed the morphological characters. Twenty specimens of Acanthobrama marmid were collected from two localities at Tigris River, in the middle of Iraq; 15 specimens from the Al-Zubaydia sub-district and five specimens from Al-Tharthar Lake. We used the mitochondrial DNA cytochrome b (cytb) gene to sequence the DNA of A. marmid. The following analysis are compared the sequences with those of other fish genera and species found in the Gene Bank. The barcoding result (DNA sequencing) in fishes found in the same family (Leuciscidae) showed

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet