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Coronary Artery Disease (CAD) leads to Angina and Myocardial Infarction (MI). Premature mortality on Coronary Heart Disease (CHD) is more common in diabetic atherosclerosis. In the present study serum level was Microalbuminuria estimated in patients of CAD with DM, CAD without DM, DM without CAD and CAD with DM and other risk factors compared to healthy normal subjects. The level of Microalbuminuria was significantly increased in all four groups of patients as compared to control group. On the basis of our results we conclude that microalbuminuria is a marker of vascular damage and thus is an early finding in atherosclerosis. Microalbuminuria is associated with wide spread abnormalities in the vasculature that may manifest as altered vascular reactivity and endothelial dysfunction.

Social Network is one of the most popular interactive medium to share, communicate and distribute information. It is the platform to build social relations among people. Users have ability to keep in touch with friends by exchanging different types of information or messages. Sometimes people post messages which may cause a serious problem to user's reputation. There is one fundamental issue in Social Network is to give users ability to control the messages posted on their own private space. To avoid the problem of unwanted messages, the proposed system called filter wall able to filter messages from user walls. In order to make social network user wall a secured wall, introducing a rule based system wall as well as Machine Learning approach, neural text classification applied on user wall.