The use of the word “war” alone raises horror and fear in the hearts of the recipients, especially if this war aimed at human’s life, his health and his future. It is the electronic advertising war among rival international companies that use cyberspace to create fear and horror in the hearts of the recipients because it connects the use of the product with human’s death or serious illness.
The problem of this research sheds light on the new uses of cyberspace which fucked by international companies to strike the interests of each other by displaying the defects of their products and its negative impact on citizen’s life. Despite the fact that those wars have opposed strongly, there are supporters for those wars. Their argument is that those advertisements help to improve the products and services, reduce their prices on one hand, and on the other, it exposes the flaws to the normal users who does not have the means to detect them while international companies have these means due to their technical and physical capabilities. But that has not prevented the existence of bypass consumer protection laws.
The aim of this research is to detect these wars highlight them and stir the readers ‘ attention depending on the survey method in analyzing the data and using content analysis form of both categories “what was said?” and “how it was said?” . The sample is limited to 61 advertisements which was recorded for the last three months of 2015. The researcher concludes the following:
1-the advertiser does not hesitate to use any means in citing and provoking horror and fear of the recipients in order to oust the competitive company and prevent the consumers from buying its product.
2-the interest and utility of the consumer have no existence among these companies.
Therefore, the researcher recommends that the government must protect the Iraqi consumers from those ads since no one can check their truth claims only under the supervision of experts and specialists, legislate laws and resolutions to protect the citizen’s life and his life of the futility of these global companies and subjecting their products for testing and quality control.
Background: One of the most common problem associated with the used of soft denture lining material is microorganisms and fungal growth especially Candida albicans, which can result in chronic mucosal inflammation. The aim of this study was to evaluate the influence of chlorhexidine diacetate (CDA) salt Incorporation into soft denture lining material on antifungal activity; against Candida albicans, and the amount of chlorhexidine di-acetate salt leached out of soft liner/CDA composite. Furthermore, evaluate shear bond strength and hardness after CDA addition to soft liner Materials and methods: chlorhexidine diacetate salt was added to soft denture lining material at four different concentrations (0.05%, 0.1% and 0.2% by weight). Four hund
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... Show MoreThirteen morphometric characters of catfish
أن التطور العلمي الحاصل فيما يخص المجال الرياضي أرسى آفاق جديدة لمواكبة التطور الكبير في مجا ل الألعاب والفعاليات الرياضية المختلفة ,و أن تحقيق النتائج الجيدة في فعاليات العاب القوى بشكل عام والثلاثية بشكل خاص في التدريب الرياضي يتطلب إتباع الأساليب العلمية الدقيقة والموضوعية بشكل سليم ومخطط له،فضلا عنة تطبيق نظريات ومنحى جديد لمواكبة الاتجاهات الحديثة في تحقيق النتائج الجيدة للوصول إلى المستويات العالية
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... Show MoreBackground: Metabolic syndrome (Mets) is partially heritable. High mobility group AT-hook1 (HMGA1), an architectural transcription factor, affects the homeostasis of glucose. The marked inter-individual differences between T
... Show MoreDiscriminant analysis is a technique used to distinguish and classification an individual to a group among a number of groups based on a linear combination of a set of relevant variables know discriminant function. In this research discriminant analysis used to analysis data from repeated measurements design. We will deal with the problem of discrimination and classification in the case of two groups by assuming the Compound Symmetry covariance structure under the assumption of normality for univariate repeated measures data.
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