Vaping Behavior in Young Adults During the COVID-19 Pandemic.

BACKGROUND: Electronic nicotine delivery systems (ENDS) continue to be popular among young adults. These devices are often advertised as a healthy alternative to quitting tobacco cigarettes. However, young adults represent a population who view it as a novel behavior that provides a sense of popularity, social acceptance, and desired physiologic properties. The objective of this study was to examine characteristics of vaping behavior among college students and explore possible associations between groups of vaping behavior (stopped, initiated, increased, decreased, stayed the same). METHODS: In a multi-center cross-sectional study, 656 students from University of Tampa in the United States and University of Applied Sciences in Germany (IST) were recruited to answer a 31-item online questionnaire. A chi-square test was used to evaluate associations between the groups. RESULTS: Prevalence rates indicated approximately 31% of all students were currently using ENDS. Even though more negative than positive experiences with ENDS were reported, most students stated their vaping increased during COVID-19 lockdowns. Addiction and stress relief emerged to be predictors (P < .001) of an increase in vaping, whereas social motives were not statistically significant. Living situation (P = .63) and depression (P = .10) were not significantly associated with vaping behavior. CONCLUSIONS: ENDS products continue to yield very high levels of nicotine creating addiction in young adults. Addiction counseling and evidenced-based practices should be employed at every level (individual, community, and school). Additionally, mental health counseling for students in pandemic and high-stress environments may help to combat stress in a more proactive manner than self-medicating.

Digital Twinning remote laboratories for online practical learning

The COVID19 pandemic has demonstrated a need for remote learning and virtual learning applications such as virtual reality (VR) and tablet-based solutions. Creating complex learning scenarios by developers is highly time-consuming and can take over a year. It is also costly to employ teams of system analysts, developers and 3D artists. There is a requirement to provide a simple method to enable lecturers to create their own content for their laboratory tutorials. Research has been undertaken into developing generic models to enable the semi-automatic creation of virtual learning tools for subjects that require practical interactions with the lab resources. In addition to the system for creating digital twins, a case study describing the creation of a virtual learning application for an electrical laboratory tutorial is presented, demonstrating the feasibility of this approach. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

THE ROLE OF ASYMPTOMATIC INFECTIONS IN THE COVID-19 EPIDEMIC VIA COMPLEX NETWORKS AND STABILITY ANALYSIS

Italy was the first country to be affected by the COVID-19 epidemic in Europe. In the past months, predictive mathematical models have been used to understand the proportion of this epidemic and identify effective policies to control it, but few have considered the impact of asymptomatic or paucisymptomatic infections in a structured setting. A critical problem that hinders the accuracy of these models is indeed given by the presence of a large number of asymptomatic individuals in the population. This number is estimated to be large, sometimes between 3 and 10 times the diagnosed patients. We focus on this aspect through the formulation of a model that captures two types of interactions onewith asymptomatic individuals and another with symptomatic infected. We also extend the original model to capture the interactions in the population via complex networks, and, in particular, the Watts-Strogatz model, which is the most suitable for social networks. The contributions of this paper include (i) the formulation of an epidemic model, which we call SAIR, that discriminates between asymptomatic and symptomatic infected through different measures of interactions and the corresponding stability analysis of the system in feedback form through the calculation of the R-0 as H-infinity gain;(ii) the analysis of the corresponding structured model involving the Watts and Strogatz interaction topology, to study the case of heterogeneous connectivity in the population;(iii) a case study on the Italian case, where we take into account the Istat seroprevalence study in the homogeneous case first, and then we analyze the impact of summer tourism and of the start of school in September in the heterogeneous case.

Incorporating human behavior in VR compartmental simulation models

A novel strand of Coronavirus has affected a large number of individuals worldwide, putting a considerable stress to national health services and causing many deaths. Many control measures have been put in place across different countries with the aim to save lives at the cost of personal freedom. Computer simulations have played a role in providing policy makers with critical information about the virus. However, despite their importance in applied epidemiology, general simulation models, are difficult to validate because of how hard it is to predict and model human behavior. To this end, we propose a different approach by developing a virtual reality (VR) multi-agent virus propagation system where a group of agents interact with the user in a university setting. We created a VR digital twin replica of a building in the University of Derby campus, to enhance the user’s immersion in our study. Our work integrates human behavior seamlessly in a simulation model and we believe that this approach is crucial to have a deeper understanding on how to control the spread of a virus such as COVID-19. © 2021 Copyright held by the owner/author(s).

Risk-Aware Control and Games in Engineering

We present a brief tutorial on risk-aware control and game theory applied to engineering problems by solving a backward-forward partial-integro differential system composed of the Hamilton-Jacobi-Bellman and Fokker-Planck coupled equations. First, we discuss about the role that risk terms play in the engineering field. Then, both the risk-aware control and game problems are stated and the computation of the corresponding solutions is presented. We mainly focus on a basic propagation regulation of the coronavirus disease by using mean-field-type control. Hence, we discuss other engineering applications that can be addressed by using the same risk-aware perspective. Among such applications, we discuss about the electric vehicles, and the bio-inspired collective decision-making.