ABSTRACT
The large consumption of food travel vlogs during the COVID-19 pandemic shows its potential for destination promotion. However, little research has been done on this video form. This study explores the difference in food travel vlogs, short videos, live videos, and DMO promotion videos (DPVs) and concludes four distinctive characteristics of food travel vlogs (storytelling, authenticity, intimacy, and presence) through 38 semi-structured interviews. A Stimulus-Organism-Response (SOR) model-based conceptual framework is proposed to help understand the mechanism underlying the influence of food travel vlogs on travellers. This study hopes to provide theoretical and practical implications for destination management and vlogging practices. © 2023, The Author(s).
ABSTRACT
As we all know, the COVID-19 pandemic brought a great challenge to manufacturing industry, especially for some fraditional and unstable manufacturing systems. It reminds us that intelligent manufacturing certainly will play a key role in the future. Dynamic shop scheduling is also an inevitable hot topic in intelligent manufacturing. However, fraditional dynamic scheduling is a kind ofpassive scheduling mode which takes measures to adjust disturbed scheduling processes after the occurrence of dynamic events. It is difficult to ensure the stability of production because of lack of proactivity. To overcome these shortcomings, manufacturing big data and data technologies as the core driving force of intelligent manufacturing will be used to guide production. Thus, a datadriven proactive scheduling approach is proposed to deal with the dynamic events, especially for machine breakdown. In this paper, the overall procedure of the proposed approach is introduced. More specifically, we first use collected manufacturing data to predict the occurrence of machine breakdowns and provide reliable input for dynamic scheduling. Then a proactive scheduling model is constructed for the hybrid flow shop problem, and an intelligent optimization algorithm is used to solve the problem to realize proactive scheduling. Finally, we design comparative experiments with two fraditional rescheduling strategies to verify the effectiveness and stability of the proposed approach.
ABSTRACT
Heparin is a kind of glycosaminoglycan drug with a complex structure, which is a mixture of polysaccharides with different chain lengths composed of hexuronic acid, aminohexose and its derivatives.Hexuronic acids are L-aduronic acid and D-glucuronic acid, aminohexose is α -D-glucosamine, and the modification of derivatives includes sulfation and acetylation.As a natural biomacromolecule, heparin has a variety of biological activities.It has been discovered for more than a hundred years and has good anticoagulant effect, which is clinically the first choice for anticoagulant and prevention and treatment of thromboembolic diseases.It has been discovered that there are more than one hundred functional proteins that interact with heparin.Heparin can bind to a variety of proteins and exert a variety of biological activities such as anticoagulant, anti-inflammatory, antiviral, and anti-tumor. The anticoagulant mechanism of heparin has been explained in detail, but its anti-inflammatory, antiviral, anti-tumor and other non-anticoagulant biolo-gical activities are still under extensive research, and these activities also have the potential to be developed into new drugs and new materials.Derivatives which with low anticoagulant activity and high antiangiogenic activity have been developed.In addition, sepsis-induced coagulopathy was common in patients with severe pneumonia caused by COVID-19 during the global outbreak of novel coronavirus epidemic.Heparin is effective in improving coagulation disorders and is likely to provide a better prognosis in patients with severe pneumonia.Due to its better biological activity, it also has potential applications in the field of new materials, such as being a cross-linking agent in the formation of hydrogels, and as a surface modifier of nanoparticles. This article consists of five parts, through which the author will first review the pharmacological activities of heparin in anticoagulation, anti-inflammatory and anti-tumor activities, then introduce the application of heparin in the new coronavirus, and finally give an overview of the application of heparin in new materials.
ABSTRACT
OBJECTIVES: Cigarette smoking is an established risk factor for illness severity and adverse outcomes in patients with COVID-19. Alcohol drinking may also be a potential risk factor for disease severity. However, the combined and interactive effects of drinking and smoking on COVID-19 have not yet been reported. This study aimed to examine the combined and interactive effects of alcohol drinking and cigarette smoking on the risk of severe illness and poor outcomes in patients with COVID-19. STUDY DESIGN: This was a multicentre retrospective cohort study. METHODS: This study retrospectively reviewed the data of 1399 consecutive hospitalised COVID-19 patients from 43 designated hospitals. Patients were grouped according to different combinations of drinking and smoking status. Multivariate mixed-effects logistic regression models were used to estimate the combined and interactive effects of drinking and smoking on the risk of severe COVID-19 and poor clinical outcomes. RESULTS: In the study population, 7.3% were drinkers/smokers, 4.3% were drinkers/non-smokers and 4.9% were non-drinkers/smokers. After controlling for potential confounders, smokers or drinkers alone did not show a significant increase in the risk of severe COVID-19 or poor clinical outcomes compared with non-drinkers/non-smokers. Moreover, this study did not observe any interactive effects of drinking and smoking on COVID-19. Drinkers/smokers had a 62% increased risk (odds ratio = 1.62, 95% confidence interval: 1.01-2.60) of severe COVID-19 but did not have a significant increase in the risk for poor clinical outcomes compared with non-drinkers/non-smokers. CONCLUSIONS: Combined exposure to drinking and smoking increases the risk of severe COVID-19, but no direct effects of drinking or smoking, or interaction effects of drinking and smoking, were detected.