An improved geometric inequality via vanishing moments, with applications to singular Liouville equations

We consider a class of singular Liouville equations on compact surfaces motivated by the study of Electroweak and Self-Dual Chern-Simons theories, the Gaussian curvature prescription with conical singularities and Onsager's description of turbulence. We analyse the problem of existence variationally, and show how the angular distribution of the conformal volume near the singularities may lead to improvements in the Moser-Trudinger inequality, and in turn to lower bounds on the Euler-Lagrange functional. We then discuss existence and non-existence results.Comment: some references adde

Snow cover monitoring by machine processing of multitemporal LANDSAT MSS data

LANDSAT frames were geometrically corrected and data sets from six different dates were overlaid to produce a 24 channel (six dates and four wavelength bands) data tape. Changes in the extent of the snowpack could be accurately and easily determined using a change detection technique on data which had previously been classified by the LARSYS software system. A second phase of the analysis involved determination of the relationship between spatial resolution or data sampling frequency and accuracy of measuring the area of the snowpack

A spatio-temporal model based on discrete latent variables for the analysis of COVID-19 incidence

We propose a model based on discrete latent variables, which are spatially associated and time specific, for the analysis of incident cases of SARS-CoV-2 infections. We assume that for each area the sequence of latent variables across time follows a Markov chain with initial and transition probabilities that also depend on latent variables in neighboring areas. The model is estimated by a Markov chain Monte Carlo algorithm based on a data augmentation scheme, in which the latent states are drawn together with the model parameters for each area and time. As an illustration we analyze incident cases of SARS-CoV-2 collected in Italy at regional level for the period from February 24, 2020, to January 17, 2021, corresponding to 48 weeks, where we use number of swabs as an offset. Our model identifies a common trend and, for every week, assigns each region to one among five distinct risk groups

How distant? An experimental analysis of students’ COVID-19 exposure and physical distancing in university buildings

University buildings are significant closed built environments for COVID-19 spreading. As universities prepare to re-start in-class activities, students' adherence to physical distancing requirements is a priority topic. While physical distancing in classrooms can be easily managed, the movement of students inside common spaces can pose higher risks due to individuals' proximity. This paper provides an experimental analysis of unidirectional student flow inside a case-study university building, by investigating students' movements and grouping behaviour according to physical distancing requirements. Results show general adherence with the minimum required physical distancing guidance, but some spaces, such as corridors, pose higher exposure than doorways. Their width, in combination with group behaviour, affects the students' capacity to keep the recommended distance. Furthermore, students report higher perceived vulnerability while moving along corridors. Evidence-based results can support decision-makers in understanding individuals' exposure in universities and researchers in developing behavioural models in preparation of future outbreaks and pandemics.Comment: 22 pages, 5 figures, 1 table. Currently submitted to "International Journal of Disaster Risk Reduction

How distant? An experimental analysis of students’ COVID-19 exposure and physical distancing in university buildings

Closed university buildings proved to be one of the main hot spots for virus transmission during pandemics. As shown during the COVID-19 pandemic, physical distancing is one of the most effective measures to limit such transmission. As universities prepare to manage in-class activities, students’ adherence to physical distancing requirements is a priority topic. Unfortunately, while physical distancing in classrooms can be easily managed, the movement of students inside common spaces can pose high risk of close proximity. This paper provides an experimental analysis of unidirectional student movement inside a case-study university building to investigate how physical distancing requirements impact student movement and grouping behaviour. Results show general adherence with the minimum required physical distancing guidance, but spaces such as corridors pose higher risk of exposure than doorways. Doorway width, in combination with group behaviour, affect the students' capacity to keep the recommended physical distance. Furthermore, questionnaire results show that students report higher perceived vulnerability while moving along corridors. Evidence-based results can support decision-makers in understanding individuals’ exposure to COVID-19 in universities and researchers in developing behavioural models in preparation of future outbreaks and pandemics

New improved Moser-Trudinger inequalities and singular Liouville equations on compact surfaces

We consider a singular Liouville equation on a compact surface, arising from the study of Chern-Simons vortices in a self dual regime. Using new improved versions of the Moser-Trudinger inequalities (whose main feature is to be scaling invariant) and a variational scheme, we prove new existence results.Comment: to appear in GAF

A nonparametric multidimensional latent class IRT model in a Bayesian framework

We propose a nonparametric Item Response Theory model for dichotomously scored items in a Bayesian framework. Partitions of the items are defined on the basis of inequality constraints among the latent class success probabilities. A Reversible Jump type algorithm is described for sampling from the posterior distribution. A consequence is the possibility to make inference on the number of dimensions (i.e., number of groups of items measuring the same latent trait) and to cluster items when unidimensionality is violated