Overall, the results showed that the application of ClO2 twice daily provided the most effective means of satisfying the Taiwan EPA guidelines for the indoor air quality of hospital medical wards.[This corrects the article DOI 10.1016/j.recesp.2020.03.027.].There is growing evidence of risks associated with excessive technology use, especially among teens and young adults. However, little is known about the characteristics of those who are at elevated risk of being problematic users. Using data from the 2012 Current Population Survey Internet Use Supplement and Educational Supplement for teens and young adults, this study developed a conceptual framework for modeling technology use. A three-part categorization of use was posited for utilitarian, social and entertainment purposes, which fit observed data well in confirmatory factor analysis. Seemingly unrelated regression was used to examine the demographic characteristics associated with each of the three categories of use. Exploratory factor analysis uncovered five distinct types of users, including one user type that was hypothesized to likely be at elevated risk of problematic use. Regression results indicated that females in their twenties who are in school and have greater access to technology were most likely to fall into this higher-risk category. Young people who live with both parents were less likely to belong to this category. This study highlighted the importance of constructing models that facilitate identification of patterns of use that may characterize a subset of users at high risk of problematic use. The findings can be applied to other contexts to inform policies related to technology and society as well.

The online version of this article (10.1007/s11293-020-09683-1) contains supplementary material, which is available to authorized users.

The online version of this article (10.1007/s11293-020-09683-1) contains supplementary material, which is available to authorized users.During the COVID-19 pandemic crisis, the experience of quarantine has been an undesirable condition for people and it can have a negative impact on mental health and psychological wellbeing. Social isolation has led to an increase in time spent on social network sites, with people interacting more frequently with each other, and comparing online the way in which they are experiencing the same state of home confinement. Our study aimed to investigate the role of online social comparison on individuals’ psychological distress and life satisfaction during the COVID-19-related quarantine. Specifically, a cross-lagged panel study at three-waves was conducted in Italy in order to examine the change in psychosocial distress levels (e.g. depression, anxiety, stress, loneliness, low life-satisfaction) from before the quarantine for a period of one month, as well as the predictive role of online social comparison to ameliorate individual distress. An online survey was distributed through a social media platform three times after the initial lockdown and at the epidemic’s peak two and five weeks later. A total of 113 participants participated in an online survey between the 7th of March and 14th of April 2020. The results showed an increase in the levels of loneliness, depression, stress, anxiety and a decrease in the level of life satisfaction in the pre/post quarantine comparison. Our cross-lagged results also showed that online social comparison at T1 and T2 predicted the individual’s improvement in levels of anxiety, stress, loneliness and life satisfaction over time. Overall, the results of the current study underline the positive effects of online social comparison on the reduction of psychological distress during the COVID-19 quarantine.The new Covid-19 pandemic has left traces of suffering and devastation to individuals of almost all countries worldwide and severe impact on the global economy. Understanding the clinical characteristics, interactions with the environment, and the variables that favor or hinder its dissemination help the public authorities in the fight and prevention, leading for a rapid response in society. Using models to estimate contamination scenarios in real time plays an important role. Population compartments models based on ordinary differential equations (ODE) for a given region assume two homogeneous premises, the contact mechanisms and diffusion rates, disregarding heterogeneous factors as different contact rates for each municipality and the flow of contaminated people among them. #link# This work considers a hybrid model for covid-19, based on local SIR models and the population flow network among municipalities, responsible for a complex lag dynamic in their contagion curves. Based on actual infection data, local contact rates ( β ) are evaluated. The epidemic evolution at each municipality depends on the local SIR parameters and on the inter-municipality transport flow. When heterogeneity of β values and flow network are included, forecasts differ from those of the homogeneous ODE model. This effect is more relevant when more municipalities are considered, hinting that the latter overestimates new cases. In addition, mitigation scenarios are assessed to evaluate the effect of earlier interventions reducing the inter-municipality flux. Restricting the flow between municipalities in the initial stage of the epidemic is fundamental for flattening the contamination curve, highlighting advantages of a contamination lag between the capital curve and those of other municipalities in the territories.Systematic assessment of scientific events has become increasingly important for research communities. A range of metrics (e.g., citations, h-index) have been developed by different research communities to make such assessments effectual. However, LMK-235 ic50 of the metrics for assessing the quality of less formal publication venues and events have not yet deeply investigated. It is also rather challenging to develop respective metrics because each research community has its own formal and informal rules of communication and quality standards. In this article, we develop a comprehensive framework of assessment metrics for evaluating scientific events and involved stakeholders. The resulting quality metrics are determined with respect to three general categories-events, persons, and bibliometrics. Our assessment methodology is empirically applied to several series of computer science events, such as conferences and workshops, using publicly available data for determining quality metrics. We show that the metrics’ values coincide with the intuitive agreement of the community on its “top conferences”.