780 research outputs found
Climate Change Risk Perception Among Citizens Living in a Central Region of Italy
No full textAdequate knowledge of climate change and correct perception of the associated risks by the population are crucial factors for the effectiveness of climate policies.
We analyze this topic by collecting information on the degree of current risk perception and its evolution over the last ten years among citizens living in five municipalities in an area of Abruzzo, a central Italian region. In addition, we gather information on the willingness of citizens to stipulate public insurance against damages caused by extreme events.
The paper offers a descriptive analysis of the association between outcomes and individual/household characteristics. We find the degree of risk perception is relatively high, as around 2/3 of respondents believe the current risk of suffering damage from extreme events related to climate change is high or very high. More than 90% also believe that this risk has increased in the last ten years. The perception, however, is heterogeneous across population subgroups. Finally, citizens’ inclination toward public insurance covering damage from extreme events is also high.
We also provide a quantitative analysis of the factors affecting the current risk perception by adopting a probit model. The related results essentially confirm evidence from the qualitative analysis and stress, in line with previous studies, the importance of previous damages as a predictor of risk perception
Multivariate Fuzzy Maps for Air Pollution in the Milan District
No full textThe aim of the present paper is the delineation of air pollution maps taking into account a set of
pollutants. For this purpose a combination of geostatistical techniques and fuzzy methods is used.
Given an irregular sampling network, the construction of fuzzy pollution maps needs the interpolation of the
observed data onto a regular grid. In this paper with the aim of generating a gridded surface, conditional
indicator simulation has been used. Given the predicted map and the normative levels, for each node of the
grid it is possible to obtain the membership grade to the polluted fuzzy set with respect to each pollutant. The
union of various fuzzy sets leads to a pollution synthetic map. The methodology proposed is used for the
construction of air pollution fuzzy maps in the Milan district with respect to CO, NO2 and SO2
Visioni degli anni Novanta. I casi di 'Prima puntata' e 'Arte video TV'
No full text'Prima Puntata' e 'Arte Video TV' sono i titoli di due significative rassegne video trasmesse a Fuori Orario, su RAI 3, intorno alla metà degli anni Novanta. Alla base di queste due operazioni vi sono l’intenzione di canalizzare i processi dell’arte d’avanguardia in un’esperienza quotidiana e domestica, la volontà di ripensare la separazione tra arte e intrattenimento e l’esigenza di ridurre i confini tra le nicchie creative e la cultura visiva di massa. Tramite la contestualizzazione di queste due imprese nell’ambito del dibattito sul rapporto tra video e televisione e in quello relativo alla situazione artistica del decennio, questo contributo mira a individuare le ripercussioni che esse esercitano sulla percezione del mezzo televisivo, ridefinendo la posizione del telespettatore di fronte alla prospettiva di una fruttuosa osmosi tra arte e cultura massmediale
Predictive functional ANOVA models for longitudinal analysis of mandibular shape changes
No full textIn this paper, we introduce a Bayesian statistical model for the analysis of functional data observed at several time points. Examples of such data include the Michigan growth study where we wish to characterize the shape changes of human mandible profiles. The formof the mandible is often used by clinicians as an aid in predicting the mandibular growth. However, whereas many studies have demonstrated the changes in size that may occur during the period of pubertal growth spurt, shape changes have been less well investigated. Considering a group of subjects presenting normal occlusion, in this paperwe thus describe a Bayesian functionalANOVAmodel that provides information about where and when the shape changes of the mandible occur during different stages of development. The model is developed by defining the notion of predictive process models for Gaussian process (GP) distributions used as priors over the random functional effects. We show that the predictive approach is computationally appealing and that it is useful to analyze multivariate functional data with unequally spaced observations that differ among subjects and times. Graphical posterior summaries show that our model is able to provide a biological interpretation of the morphometric findings and that they comprehensively describe the shape changes of the human mandible profiles. Compared with classical cephalometric analysis, this paper represents a significant methodological advance for the study of mandibular shape changes in two dimensions
Environmental Pollution Analysis by Dynamic Structural Equation Models
No full textAs requested by the framework EU Directive on air quality assessment and management (96/62/EC) and
related ‘daughter’ directives, air quality standards for specific pollutants are designed to protect public health
and environment. Modeling is one of the main activities to evaluate air quality and to prepare future control
programs. Of course, this is not an easy task since a variety of pollutants may undergo chemical reactions between
themselves and with other species. Nevertheless, in this paper we attempt to discuss a framework to construct
a multivariate model which is able to capture the dynamical interactions among pollutants and meteorological
variables. Specifically, assuming that latent or background effects underlying the fluctuation of observations can
be estimated, a dynamic structural equation model is developed in a state-space form. A research study on
the Milan district for data provided by the Lombardia Environmental Protection Agency (ARPA) is presented
Space–time modelling of coupled spatiotemporal environmental variables
No full textThe paper is concerned with a dynamic factor model for spatiotemporal coupled
environmental variables. The model is proposed in a state space formulation which, through
Kalman recursions, allows a unified approach to prediction and estimation. Full probabilistic inference
for the model parameters is facilitated by adapting standard Markov chain Monte Carlo
algorithms for dynamic linear models to our model formulation.The predictive ability of the model
is discussed for two different data sets with variables measured at two different scales. Some
possibilities for further research are also outlined
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