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

    Coral reef area in northwest of the Arabian Gulf was investigated for mineralogy and geochemistry to throw lights on such unique Iraqi Marine Environment; six specimens of two main species of coral reefs, Platygyra pini Chevalier, 1975 and Octocoral Menella were collected at two sites. While eight samples of the surrounding sediments are chosen from other two sites. The mineralogy is determined by XRD, and reveals that calcite, low magnesium-calcite, and aragonite are the main minerals that comprise the Octocoral Menella in site 1, whilst aragonite and calcite are dominate in the P. pini coral reef at site 4.

    The non–carbonate fractions indicate that thes

Curcumin is a yellow pigment produced from the rhizomes of the Curcuma longa plant and a primary chemo preventive component of turmeric is used as a spice and food coloring ingredient. Curcumin has a large number of pharmacological activities, such as anticancer, anti-diabetic, antioxidant, anti-infectious, and anti-inflammatory properties.Investigation of the geno-protective effect of curcumin on methotrexate induces chromosomal aberrations of spleen and bone marrow cells. In this study, 32 mice were used and divided into four groups (eight mice at each group) as follows: Group1 (negative control): Dimethyl sulfoxide was given intraperitoneally to mice every day for ten days.Group2 (positive control): Mice were received a single do

This study investigates the role of identity as a critical factor in mediating the relationship between local and regional politics within the broader context of international relations (IR). While identity is frequently acknowledged as a catalyst for political instability and conflict, its function in fostering interdependence across political levels remains underexplored, particularly through empirical research. To address this gap, the study adopts a quantitative methodology, drawing on theories of identity politics and interdependence. A structured survey was administered to assess public perceptions of identity's influence on international engagement and its bridging role between domestic and regional political dynamics. The fi

Non-alcoholic fatty liver disease (NAFLD) has become one of the most common chronic liver diseases worldwide, which characterized by steatosis, inflammation, and fibrosis. The aim of this designed study is to evaluate the ability of guggulsterone to prevent high fat diet induced steatohepatitis in mice. Five groups of male mice were selected and treated as the following: group I, mice had free access to standard commercial diet and considered as control group, group II, mice were fed a specially formulated high-fat diet for 12 weeks to induce non-alcoholic liver disease, while groups III, IV and V the mice were administered high fat diet containing guggulsterone at 500, 1000 and 2000 ppm concentration respectively for 12 weeks. Maintaini

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

This study aimed to evaluate oral health (OH) and periodontal diseases (PD) awareness in the Iraqi population.