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As the long‐term consequences of coronavirus disease 2019 (COVID‐19) have not been defined, it is necessary to explore persistent symptoms, long‐term respiratory impairment, and impact on quality of life over time in COVID‐19 survivors. In this prospective cohort study, convalescent individuals diagnosed with COVID‐19 were followed‐up 2 and 3 years after discharge from hospital. Participants completed an in‐person interview to assess persistent symptoms and underwent blood tests, pulmonary function tests, chest high‐resolution computed tomography, and the 6‐min walking test. There were 762 patients at the 2‐year follow‐up and 613 patients at the 3‐year follow‐up. The mean age was 60 years and 415 (54.5%) were men. At 3 years, 39.80% of the participants had at least one symptom; most frequently, fatigue, difficulty sleeping, joint pain, shortness of breath, muscle aches, and cough. The participants experienced different degrees of pulmonary function impairment, with decreased carbon monoxide diffusion capacity being the main feature; results remained relatively stable over the 2–3 years. Multiple logistic regression analysis demonstrated that female sex and smoking were independently associated with impaired diffusion capacity. A subgroup analysis based on disease severity was performed, indicating that there was no difference in other parameters of lung function except forced vital capacity at 3‐year follow‐up. Persistent radiographic abnormalities, most commonly fibrotic‐like changes, were observed at both timepoints. At 3 years, patients had a significantly improved Mental Component Score compared with that at 2 years, with a lower percentage with anxiety. Our study indicated that symptoms and pulmonary abnormalities persisted in COVID‐19 survivors at 3 years. Further studies are warranted to explore the long‐term effects of COVID‐19 and develop appropriate rehabilitation strategies. [ABSTRACT FROM AUTHOR]

Compared with traditional methods, the action recognition model based on 3D convolutional deep neural network captures spatio-temporal features more accurately, resulting in higher accuracy. However, the large number of parameters and computational requirements of 3D models make it difficult to deploy on mobile devices with limited computing power. In order to achieve an efficient video action recognition model, we have analyzed and compared classic lightweight network principles and proposed the 3D-ShuffleViT network. By deeply integrating the self-attention mechanism with convolution, we have introduced an efficient ACISA module that further enhances the performance of our proposed model. This has resulted in exceptional performance in both context-sensitive and context-independent action recognition, while reducing deployment costs. It is worth noting that our 3D-ShuffleViT network, with a computational cost of only 6% of that of SlowFast-ResNet101, achieved 98% of the latter's Top1 accuracy on the EgoGesture dataset. Furthermore, on the same CPU (Intel i5-8300H), its speed was 2.5 times that of the latter. In addition, when we deployed our model on edge devices, our proposed network achieved the best balance between accuracy and speed among lightweight networks of the same order. [ABSTRACT FROM AUTHOR]

Introduction: We evaluated the impact of heating conventional cigarettes with a novel heated tobacco product (HTP) device on biomarkers and cigarette use patterns in Chinese adult smokers unwilling to quit smoking., Methods: In this pilot randomized controlled trial, 50 eligible participants were allocated to either Control group (smoking conventional cigarettes) or HTP device group (switching to using heated conventional cigarettes by the HTP device). Participants in the HTP device group went through a 2-day run-in period then used heated conventional cigarettes exclusively for 5 days, followed by flexible use for 14 days. Five biomarkers of exposure (BoEs) were measured at baseline and on Day 7. Thirteen biomarkers of biological effect (BoBEs) were measured at baseline and on Day 21. Safety, daily cigarette consumption, craving, withdrawal symptoms, and device acceptability, were assessed., Results: BoE levels decreased by 26.4 % to 71.4% from baseline in the HTP device group, while BoBE levels did not significantly change in either group. In the HTP group, 56% exclusively used heated conventional cigarettes during the flexible use period, experiencing reduced cravings and withdrawal symptoms, while dual users consumed more cigarettes. Mild to moderate device-related reactions were reported in 36% of users. Satisfaction, taste, and harm reduction belief scores averaged 7.4, 6.6, and 8.7 (out of 10), respectively., Conclusions: Switching to heated cigarettes with the HTP device may reduce short-term exposure to smoke toxicants. However, it can lead to increased tobacco use among dual users. Further investigation is needed to confirm these preliminary findings., Implications: This study is the first to evaluate the impact of heating conventional cigarettes with a novel heated tobacco product (HTP) device on health-related biomarkers and cigarette use patterns among Chinese adult smokers. This novel HTP device can directly heat conventional cigarettes without the necessity for specifically designed tobacco products, avoiding potential additive risks of traditional HTPs. If the results of this study could be further verified by randomized controlled clinical trials with larger sample sizes, this novel HTP device could serve as a short-term harm reduction alternative for smokers unwilling to quit., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)