Evaluation of the intensity of cigarette odors based on the perception of consumers.

INTRODUCTION: We evaluated the tobacco odor intensity of cigarettes based on a large consumer panel and explored the differences of odor intensity perception based on sex, age and smoking habits. METHODS: The perceived intensity of tobacco odor of cigarettes was evaluated using a consumer group method. A consumer panel of 240 volunteers (80 smokers, 80 ex-smokers and 80 non-smokers) was asked to smell eleven unlit cigarettes and then report their tobacco odor intensity in a specific questionnaire. RESULTS: All volunteers clearly determined the presence of tobacco odor in all cigarettes. There is a general decrease of the perceived odor intensity with age, for both males and females. Moreover, tobacco odor perceived intensity, among all volunteer groups (smokers, non-smokers, ex-smokers), was higher for females than for males. Non-smokers declared the highest perceived tobacco odor intensities, followed by ex-smokers and smokers, who recorded the lowest perceived odor intensity. Perceived odor intensity decreased with age, with a higher rate for females compared to males, but independently of the smoking habits. CONCLUSIONS: Regular and untrained consumers confirmed that a tobacco odor of different intensity can be perceived during the smelling of unlit cigarettes. This perceived intensity depends on sex, age and smoking habits.

Clustering analysis of countries using the COVID-19 cases dataset.

There is a worldwide effort of the research community to explore the medical, economic and sociologic impact of the COVID-19 pandemic. Many different disciplines try to find solutions and drive strategies to a great variety of different very crucial problems. The present study presents a novel analysis which results to clustering countries with respect to active cases, active cases per population and active cases per population and per area based on Johns Hopkins epidemiological data. The presented cluster results could be useful to a variety of different policy makers, such as physicians and managers of the health sector, economy/finance experts, politicians and even to sociologists. In addition, our work suggests a new specially designed clustering algorithm adapted to the request for comparison of the various COVID time-series of different countries.