The whole world and the Arab world, especially an important part of this international system, is undergoing a radical transformation at all levels. This mosaic of political, economic, social and military relations and alliances, whether based on the special interests of the major Powers or on the basis of mutual interests, The major transformations to social, economic, political and military conflict and these transformations still bear more surprises, at all levels, nothing remains constant, all changed, relations changed and alliances changed and loyalties fell and the principles of the M changed and the spectacular imperial economies collapsed and the will of the masses was no longer fixed.

This systematic review aimed to investigate the relation between orthodontic treatment (OT) and the incidence of the gingival black triangle (GBT) after completing treatment with a fixed orthodontic appliance, as well as the associated risk factors and the level of alveolar bone. Electronic and hand searches were conducted in three electronic databases for relevant articles published up to March 2022. Retrieved articles went through a two-step screening procedure, and the risk of bias (RoB) was assessed by the Joanna Briggs Institute checklists. The incidence of GBT after OT was set as the primary outcome, while the secondary outcomes were the risk factors associated with GBT and alveolar bone loss following OT. Out of 421 papers, 5

Volumetric chemical adsorption was done in a volumetric apparatus using hydrogen gas at room temperature on eleven platinum catalyst, commercial catalysts (RG-412,RG-402 ,RG-432, RG-451, RG-482, and PS-10) and prepared platinum catalysts with 0.1, 0.2 , 0.45 , and 0.55% by weight of Pt supported with Y-alumina. The results show that the metal crystallite area increases with increasing platinum content. The dispersion and particle size of metal crystallite located between 48.2-96.1% and 3.85-12.72 nm, respectively. For bimetallic catalysts, the hydrogen intake decrease in the following order : Re < Sn < Ir.

The research aims to delve into the nature of international financial reporting standards and the unified accounting system adopted in the Iraqi environment and financial ratios in the theoretical side. In the practical aspect, the results of some financial ratios of Basrah Gas Company were compared with the adoption of the financial statements prepared on the basis of the consolidated accounting system with the prepared financial statements Based on the International Financial Reporting Standards (IFRS). The research has reached a number of conclusions, including a difference in the accounting rules and practices between IFRS and the consolidated accounting system in force in Iraq. The adoption of IFRS has led to a decrease in profitabi

This research seeks to clarify the regulatory and educational role of the regulatory and educational institutions in reducing the phenomenon of financial and administrative corruption as a dangerous phenomenon of the communities, as it touched search kinds of financial and administrative corruption and the causes and effects, as well as to the role of educational institutions in reducing this phenomenon, and finally between experiments some SAIs and accounting Arab and foreign countries on how to reduce the phenomenon of financial and administrative corruption.The research aims to several targets which shed light on the role of educational and supervisory institutions in reducing corruption, a statement origins and evolution of and justi

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