Background: Oral cancer is a highly lethal and disfiguring disease. Squamous cell carcinoma of the oral cavity constitutes about 90% of all oral malignancies. The aims of the study was to achieve an epidemiological description of the oral squamous cell carcinoma in Iraq in general and in Iraqi governorates except Kurdistan region retrospectively during period 2001-2013 Materials and Methods: Data were collected from department of oral and maxillofacial pathology, college of dentistry, university of Baghdad, Nuclear medicine and radiotherapy hospital, Iraqi cancer registry center, Main hospitals in Baghdad and Iraqi governorates, Private labs. for histopathological examinations. The descriptive and inferential statistical methods were used

A field experiment was conducted during winter season of 2021 at a research station of college of agricultural engineering sciences, university of Baghdad to determine the response of active fertility percentage and seed yield and its components of faba bean (Vicia faba L. cv. Aguadulce) to distance between plants and spraying of nano and traditional boron. A Randomized Complete Block Design according to split-plots arrangement was used at three replicates. The main plots were three distances between plants (25, 35 and 45 cm), while the sub plots including spraying of distilled water only (control treatment), spraying of boron at a 100 mg L-1 and spraying of nano boron at two concentrations (10 and 15 mg L-1). The results showed that the 25

Trimethoprim derivative Schiff bases are versatile ligands synthesized with carbonyl groups from the condensation of primary amines (amino acids). Because of their broad range of biological activity, these compounds are very important in the medical and pharmaceutical fields. Biological activities such as antibacterial, antifungal and antitumor activity are often seen. Transition metal complexes derived from biological activity Schiff base ligands have been commonly used

A composite section is made up of a concrete slab attached to a steel beam by means of shear connectors. Under positive and negative bending moment, part of the slab will act as a flange of the beam, resisting the longitudinal compression or tension force. When the spacing between girders becomes large, it is evident that the simple beam theory does not strictly apply because the longitudinal stress in the flange will vary with distance from the girder web, the flange being more highly stressed over the web than in the extremities. This phenomenon is termed "shear lag". In this paper, a nonlinear three-dimensional finite element analysis is employed to evaluate and determine the actual effective slab width of the composite steel-concrete

Salivary peroxidases have biological functions of particular importance to oral health. The aim of this paper is to shed the light on saliva and serum total peroxidases activity as well as the activity of each of salivary peroxidase (SPO) and myeloperoxidase (MPO) in patients with oral tumors. The studied participants were divided into two groups: the first group included 18 oral squamous cell carcinoma patients and 20 age and gender-matched healthy controls while the second group consisted of 20 oral ossifying fibroma patients and 23 age and gender-matched healthy controls. Total peroxidases activity was determined, and its specific activity was calculated in serum and whole mixed saliva as well as in the supernatant and pellet fractions

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c