Abstract The League of Arab States took many procedures against the Syrian political system, like suspended Syria's membership in the League of Arab States and sent a team of Arab observers headed by Dabi to discuss the situation there and issued some decisions and statements that called the Syrian regime to stop the use of violence and repression against the Syrian opposition.Through these steps, the Arab League has tried to help the Syrian parties to resolve the crisis. However, the role of the league in the Syrian crisis was characterized by weakness in general, and lack of seriousness, which contributed in the aggravation of the situation in Syria, and the intervention of major powers in the internal affairs of Syria.

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                 The research aims to improve the insurance service through the marketing commission as a tool that enables the insurance companies to achieve a competitive advantage. The researcher, by observing the challenges faced by insurance companies, insurance agents and brokers, raised the main question of the research: Is there an effect of the marketing commission on the competitive advantage of insurance companies? The data was obtained through the financial statements and annual reports of the research sample companies (the National General Insurance Company, the Iraqi General Insurance Company, Al-Hamra Private

                The research aims to shed light on the importance of forensic accounting and its role in winning compensation claims against the company because of the ability of the forensic accountant (the judicial expert) to interpret and analyze the data. The research community represents the insurance companies in Iraq. The research sample was represented by the National Insurance Company. Coverage of the theoretical and deductive approach in covering the practical side, based on the financial records of the National Insurance Company for years of research.One of the most important conclusions reached by the researchers was that forensic accounting has a role

The business process re-engineering is one of the popular concepts at this time because its provide a radical solution for the problems that companies faces. This method appeared because the changes of competition and costumers 'desires at the two last decades. The markets become wider because of the globalization so the companies must change its way to stay a life.

        The research aim is to concentrate on the  BPR  because it's a  philosophy aims to re-organize the company's business process to achieve the competitive advantage, the research also aims to a plicate  the BPR using cost management technique  in the State Company of Vegetable Oils Industry.

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The research includes the synthesis and identification of the mixed ligands complexes of M(II) Ions in general composition [M(Lyn)2(phen)] Where L- lysine (C6H14N2O2) commonly abbreviated (LynH) as a primary ligand and 1,10-phenanthroline(C12H8N2) commonly abbreviated as "phen," as a secondary ligand . The ligands and the metal chlorides were brought in to reaction at room temperature in ethanol as solvent. The reaction required the following molar ratio [(1:1:2) (metal): phen:2 Lyn -] with M(II) ions, were M = Mn(II),Cu(II), Ni(II), Co(II), Fe(II) and Cd(II). Our research also includes studying the bio–activity of the some complexes prepared against pathogenic bacteria Escherichia coli(-),Staphylococcus(-) , Pseudomonas (-), Bacillus (-)

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