BackgroundHeated tobacco products (HTPs) may compromise decades-long efforts to marginalise the tobacco industry. Their appeal to adolescents imposes a risk of a new tobacco epidemic. Empirical evidence on the behavioural patterns of HTP use among adolescents is required. We investigated the prevalence of HTP use and the association between use of HTPs and e-cigarettes and attempts to quit smoking cigarettes.MethodsNationally representative cross-sectional survey data of South Korean adolescents aged 12–18 years (mean age: 15 years) were used. The survey was conducted 1 year after the introduction of HTPs in Korea. A total of 59 532 adolescents were identified. Descriptive statistics and multiple logistic regression results are presented.ResultsIn all, 2.8% of South Korean adolescents were ever HTP users. Among these, 75.5% were current cigarette users, 45.6% were current e-cigarette users and 40.3% were concurrent users of cigarettes and e-cigarettes. Unlike ever use of e-cigarettes, which was associated with a higher likelihood of cigarette quit attempts (adjusted OR (aOR)=1.35, 95% CI: 1.16 to 1.58), no difference in cigarette quit attempts was found for ever use of HTPs (aOR=1.07, 95% CI: 0.91 to 1.26).ConclusionConsidering the recent introduction of HTPs to the Korean market and less than 1% prevalence of e-cigarette when first introduced, the prevalence of ever HTP use among Korean adolescents is an important concern. The results showing high polytobacco use and the lack of an association between HTP use and cigarette quit attempts call for a ban on HTP advertisements with modified harm claims.

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A wearable silent speech interface (SSI) is a promising platform that enables verbal communication without vocalization. The most widely studied methodology for SSI focuses on surface electromyography (sEMG). However, sEMG suffers from low scalability because of signal quality-related issues, including signal-to-noise ratio and interelectrode interference. Hence, here, we present a novel SSI by utilizing crystalline-silicon-based strain sensors combined with a 3D convolutional deep learning algorithm. Two perpendicularly placed strain gauges with minimized cell dimension (<0.1 mm2) could effectively capture the biaxial strain information with high reliability. We attached four strain sensors near the subject’s mouths and collected strain data of unprecedently large wordsets (100 words), which our SSI can classify at a high accuracy rate (87.53%). Several analysis methods were demonstrated to verify the system’s reliability, as well as the performance comparison with another SSI using sEMG electrodes with the same dimension, which exhibited a relatively low accuracy rate (42.60%).

Background: The coronavirus disease 2019 (COVID-19) pandemic has posed significant global public health challenges and created a substantial economic burden. Korea has experienced an extensive outbreak, which was linked to a religion-related super-spreading event. However, the implementation of various non-pharmaceutical interventions (NPIs), including social distancing, spring semester postponing, and extensive testing and contact tracing controlled the epidemic. Herein, we estimated the effectiveness of each NPI using a simulation model. Methods: A compartment model with a susceptible-exposed-infectious-quarantinedhospitalized structure was employed. Using the Monte-Carlo-Markov-Chain algorithm with Gibbs' sampling method, we estimated the time-varying effective contact rate to calibrate the model with the reported daily new confirmed cases from February 12th to March 31st (7 weeks). Moreover, we conducted scenario analyses by adjusting the parameters to estimate the effectiveness of NPI. Results: Relaxed social distancing among adults would have increased the number of cases 27.4-fold until the end of March. Spring semester non-postponement would have increased the number of cases 1.7-fold among individuals aged 0-19, while lower quarantine and detection rates would have increased the number of cases 1.4-fold. Conclusion: Among the three NPI measures, social distancing in adults showed the highest effectiveness. The substantial effect of social distancing should be considered when preparing for the 2nd wave of COVID-19.