Structure of mesuaferrone-b a new biflavanone from the stamens of mesua ferrea linn.

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A survey on smart automated computer-aided process planning (ACAPP) techniques

© 2018, The Author(s). The concept of smart manufacturing has become an important issue in the manufacturing industry since the start of the twenty-first century in terms of time and production cost. In addition to high production quality, a quick response could determine the success or failure of many companies and factories. One the most effective concepts for achieving a smart manufacturing industry is the use of computer-aided process planning (CAPP) techniques. Computer-aided process planning refers to key technology that connects the computer-aided design (CAD) and the computer-aided manufacturing (CAM) processes. Researchers have used many approaches as an interface between CAD and CAPP systems. In this field of research, a lot of effort has been spent to take CAPP systems to the next level in the form of automatic computer-aided process planning (ACAPP). This is to provide complete information about the product, in a way that is automated, fast, and accurate. Moreover, automatic feature recognition (AFR) techniques are considered one of the most important tasks to create an ACAPP system. This article presents a comprehensive survey about two main aspects: the degree of automation in each required input and expected output of computer-aided process planning systems as well as the benefits and the limitations of the different automatic feature recognition techniques. The aim is to demonstrate the missing aspects in smart ACAPP generation, the limitations of current systems in recognising new features, and justifying the process of selection.The authors of the paper would like to sincerely thank the Republic of Iraq Ministry of Higher Education & Scientific Research and the University of Technology, Baghdad for funding the project

Impact of the 2017 ACC/AHA guidelines on the prevalence of hypertension among Indian adults: Results from a cross-sectional survey

BackgroundThe impact of the 2017 American College of Cardiology (ACC)/American Heart Association (AHA) guidelines for diagnosis and management of hypertension on the prevalence of hypertension in India is unknown.MethodsWe analyzed data from the Cardiac Prevent 2015 survey to estimate the change in the prevalence of hypertension. The JNC8 guidelines defined hypertension as a systolic blood pressure of ≥140 ​mmHg or diastolic blood pressure of ≥90 ​mmHg. The 2017 ACC/AHA guidelines define hypertension as a systolic blood pressure of ≥130 ​mmHg or diastolic blood pressure of ≥80 ​mmHg. We standardized the prevalence as per the 2011 census population of India. We also calculated the prevalence as per the World Health Organization (WHO) World Standard Population (2000-2025).ResultsAmong 180,335 participants (33.2% women), the mean age was 40.6 ​± ​14.9 years (41.1 ​± ​15.0 and 39.7 ​± ​14.7 years in men and women, respectively). Among them, 8,898 (4.9%), 99,791 (55.3%), 35,694 (11.9%), 23,084 (12.8%), 9,989 (5.5%) and 2,878 (1.6%) participants belonged to age group 18-19, 20-44, 45-54, 55-64, 65-74 and ​≥ ​75 years respectively. The prevalence of hypertension according to the JNC8 and 2017 ACC/AHA guidelines was 29.7% and 63.8%, respectively- an increase of 115%. With the 2011 census population of India, this suggests that currently, 486 million Indian adults have hypertension according to the 2017 ACC/AHA guidelines, an addition of 260 million as compared to the JNC8 guidelines.ConclusionAccording to the 2017 ACC/AHA guidelines, 3 in every 5 Indian adults have hypertension