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Despite several quality management tools, none or very few systematic operations are taken into account to assure the quality of the pharmaceutical products. Plan Do Check Act (PDCA) analysis is performed based on the problems encountered during the product development. In each step, some of the quality control tools are used for better maintenance of corrective and preventive actions. However, systematic use of these tools is still not made. Here we portray an example of nanoemulsion that will help justify the correct or systematic use of all the seven quality control tools in each section of PDCA cycle for better maintenance of Corrective and Preventive Actions (CAPA). The major limitations associated with the nanoemulsion i.e. non-uniform size distribution, lower encapsulation efficiency, lower magnitude of zeta potential, non-scalable and expensive synthesis procedures have taken into consideration for this portray. This review summarizes the productive use of 7 QC tools in PDCA cycle to ensure the optimum quality of nanoemulsion in an industry.

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The continuous growth of email users has resulted in the increasing of unsolicited emails also known as Spam. In current, server side and client side anti spam filters are introduced for detecting different features of spam emails. However, recently spammers introduced some effective tricks consisting of embedding spam contents into digital image, pdf and doc as attachment which can make ineffective to current techniques that is based on analysis digital text in the body and subject fields of email. Many of proposed working strategy provides an anti spam filtering approach that is based on data mining techniques which classify the spam and ham emails. The effectiveness of these approaches is evaluated on large corpus of simple text dataset as well as text embedded image dataset. But most of the filtering techniques are unable to handle frequent changing scenario of spam mails adopted by the spammers over the time. Therefore improved spam control algorithms or enhancing the efficiency of various existing data mining algorithms to its fullest extent are the utmost requirement. A comparative study is presented on various spam filtering techniques adopted on the basis of various attributes to find best among all to extract the best results.

Diabetes is a severe chronic disease that arises when insulin generation is insufficient, or the generated insulin cannot be used in the body, making it a long-term metabolic disorder. Diabetes affects an estimated 537 million adults worldwide between the age of 20 to 79 (10.5% of all adults in this age range). By 2030, 643 million people will have diabetes globally, increasing to 783 million by 2045. According to the IDF 10th edition, the incidence of diabetes has been rising in South-East Asia (SEA) nations for at least 20 years, and current estimates have outperformed all previous forecasts. This review aims to provide updated estimates and future projections of diabetes prevalence at the national and global levels by using data from the 10th edition of the IDF Diabetes Atlas 2021. For this review, we studied more than 60 previously published related articles from various sources, such as PubMed and Google Scholar, and we extracted 35 studies out of 60. however, we used only 34 studies directly related to diabetes and its prevalence at the global, SEA, and Indian levels. This review article concludes that in 2021 more than 1 in 10 adults worldwide developed diabetes. The estimated prevalence of diabetes in adults (20 to 79 years) has more than tripled since the first edition in 2000, rising from an estimated 151 million (4.6% of the world’s population at the time) to 537.5 million (10.5%) of the world’s population today. The prevalence rate will be higher than 12.8% by 2045. In addition, this study indicates that the incidence of diabetes in the world, Southeast Asia, and India was 10.5%, 8.8%, and 9.6%, respectively, throughout 2021 and will rise to 12.5%, 11.5%, and 10.9%, respectively by 2045.

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