The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was first detected in China at the end of 2019 and it has since spread in few months all over the World. Italy was one of the first ...Western countries who faced the health emergency and is one of the countries most severely affected by the pandemic. The diffusion of Coronavirus disease 2019 (COVID-19) in Italy has followed a peculiar spatial pattern, however the attention of the scientific community has so far focussed almost exclusively on the prediction of the evolution of the disease over time.
Official freely available data about the number of infected at the finest possible level of spatial areal aggregation (Italian provinces) are used to model the spatio-temporal distribution of COVID-19 infections at local level. An endemic-epidemic time-series mixed-effects generalized linear model for areal disease counts has been implemented to understand and predict spatio-temporal diffusion of the phenomenon.
Three subcomponents characterize the fitted model. The first describes the transmission of the illness within provinces; the second accounts for the transmission between nearby provinces; the third is related to the evolution of the disease over time. At the local level, the provinces first concerned by containment measures are those that are not affected by the effects of spatial neighbours. On the other hand, the component accounting for the spatial interaction with surrounding areas is prevalent for provinces that are strongly involved by contagions. Moreover, the proposed model provides good forecasts for the number of infections at local level while controlling for delayed reporting.
A strong evidence is found that strict control measures implemented in some provinces efficiently break contagions and limit the spread to nearby areas. While containment policies may potentially be more effective if planned considering the peculiarities of local territories, the effective and homogeneous enforcement of control measures at national level is needed to prevent the disease control being delayed or missed as a whole. This may also apply at international level where, as it is for the European Union or the United States, the internal border checks among states have largely been abolished.
This paper aims at investigating empirically whether and to what extent the containment measures adopted in Italy had an impact in reducing the diffusion of the COVID-19 disease across provinces. For ...this purpose, we extend the multivariate time-series model for infection counts proposed in Paul and Held (Stat Med 30(10):118–1136, 2011) by augmenting the model specification with B-spline regressors in order to account for complex nonlinear spatio-temporal dynamics in the propagation of the disease. The results of the model estimated on the time series of the number of infections for the Italian provinces show that the containment measures, despite being globally effective in reducing both the spread of contagion and its self-sustaining dynamics, have had nonlinear impacts across provinces. The impact has been relatively stronger in the northern local areas, where the disease occurred earlier and with a greater incidence. This evidence may be explained by the shared popular belief that the contagion was not a close-to-home problem but rather restricted to a few distant northern areas, which, in turn, might have led individuals to adhere less strictly to containment measures and lockdown rules.
In September 2015, the Volkswagen Group was involved in a massive scandal regarding vehicles’ emissions of substances harmful to the environment. This scandal, known as Dieselgate, caused a commotion ...in the automotive sector and raised the question of whether or not there exists consumer demand for cleaner cars. This paper aims to investigate consumers’ willingness to pay a premium price for lower CO
2
emitting cars. To do so, it adopts a discrete choice methodological approach and an exploratory survey involving 278 potential Italian car buyers. The results provide strong support for the primary hypothesis of the research that consumers are willing to pay more for cleaner vehicles, as expressed by a positive marginal willingness to pay for lower emissions. Potential car buyers indeed appear willing to pay a price premium of about € 2100 for a 20% CO
2
reduction per kilometre from the current standard level that car industry has to comply with. In particular, we estimate a willingness to pay approximately € 88 for 1-g of CO
2
reduction per kilometre (with a 95% confidence interval ranging between € 54 and € 122).
This paper presents the R package plot3logit which enables the covariate effects of trinomial regression models to be represented graphically by means of a ternary plot. The aim of the plot is ...helping the interpretation of regression coefficients in terms of the effects that a change in values of regressors has on the probability distribution of the dependent variable. Such changes may involve either a single regressor, or a group of them (composite changes), and the package permits both cases to be handled in a user-friendly way. Moreover, plot3logit can compute and draw confidence regions of the effects of covariate changes and enables multiple changes and profiles to be represented and compared jointly. Upstream and downstream compatibility makes the package able to work with other R packages or applications other than R.
The use of the
K-functions (Ripley, 1977) has recently become popular in the analysis of the spatial pattern of firms. It was first introduced in the economic literature by Arbia and Espa (1996) and ...then popularized by Marcon and Puech (2003), Quah and Simpson (2003), Duranton and Overman (2005), and Arbia et al. (2008). In particular in Arbia et al. (2008) we used Ripley's
K-functions as instruments to study the inter-sectoral co-agglomeration pattern of firms in a single moment of time. All this research has followed a static approach by disregarding the time dimension. Temporal dynamics, on the other hand, play a crucial role in understanding the economic and social phenomena particularly when referring to the analysis of the individual choices leading to the observed clusters of economic activities. With respect to previous contributions to the literature, this paper uncovers the process of firm demography by studying the dynamics of localization through space–time
K-functions. The empirical part of the paper will focus on the study of the long run localization of firms in the area of Rome (Italy), by concentrating on the
Information and Communication Technology (
ICT) sector data collected by the Italian Industrial Union in the period 1920–2005.
In many microeconometric models we use distances. For instance, in modelling the individual behavior in labor economics or in health studies, the distance from a relevant point of interest (such as a ...hospital or a workplace) is often used as a predictor in a regression framework. However, in order to preserve confidentiality, spatial micro-data are often geo-masked, thus reducing their quality and dramatically distorting the inferential conclusions. In particular in this case, a measurement error is introduced in the independent variable which negatively affects the properties of the estimators. This paper studies these negative effects, discusses their consequences, and suggests possible interpretations and directions to data producers, end users, and practitioners.
In this paper, speaker adaptive acoustic modeling is investigated by using a novel method for speaker normalization and a well known vocal tract length normalization method. With the novel ...normalization method, acoustic observations of training and testing speakers are mapped into a normalized acoustic space through speaker-specific transformations with the aim of reducing inter-speaker acoustic variability. For each speaker, an affine transformation is estimated with the goal of reducing the mismatch between the acoustic data of the speaker and a set of target hidden Markov models. This transformation is estimated through constrained maximum likelihood linear regression and then applied to map the acoustic observations of the speaker into the normalized acoustic space.
Recognition experiments made use of two corpora, the first one consisting of adults’ speech, the second one consisting of children’s speech. Performing training and recognition with normalized data resulted in a consistent reduction of the word error rate with respect to the baseline systems trained on unnormalized data. In addition, the novel method always performed better than the reference vocal tract length normalization method adopted in this work.
When unsupervised static speaker adaptation was applied in combination with each of the two speaker normalization methods, a different behavior was observed on the two corpora: in one case performance became very similar while in the other case the difference remained significant.
•A sunspace was coupled to an experimental energy-efficient building.•The design parameters affecting potential energy saving were investigated.•On-site monitoring data were collected for different ...sunspace configurations.•Convective, double-glazed sunspace achieved the best energy performance.
This research paper collects the outcomes of an experimental study focused on the energy benefits achieved by coupling an energy efficient building with a sunspace in winter season and Mediterranean climate.
Acting as passive Solar heating elements, sunspaces are intended to be a valuable tool among sustainable and energy-efficient constructive and/or retrofitting strategies.
In order to assess the energy saving potential of the above-mentioned coupling and relate it to the main design parameters, two operative steps were carried out: the numerical step allowed different simulated configurations to be evaluated in order to identify the optimal one from an energy perspective and physically realize it; the monitoring phase served the double purpose of calibrating the simulation model and provide on-site validated data for subsequent assessments and comparisons. Three main sunspace configurations were tested: irradiative single-glazed, irradiative double-glazed and convective double-glazed.
The convective double glazed configuration was found to outperform the others since the daily energy consumption reduction exceeded the 27% (compared to the irradiative, double glazed counterpart) for all weather conditions. Besides, the activation of a mechanical ventilation system was slightly counterproductive in terms of discomfort phenomena since a less stable indoor air temperature was guaranteed.
Comparing the two irradiative configurations, it was found that the addition of an extra glass layer was responsible of a quite constant reduction of 1kWh/day, thus increasing the percent heating energy demand saving achieved through the insertion of the sunspace from approximately 3,3%–8,7%, while minimizing indoor air temperature fluctuations too.
This paper presents several acoustic analyses carried out on read speech collected from Italian children aged from 7 to 13 years and North American children aged from 5 to 17 years. These analyses ...aimed at achieving a better understanding of spectral and temporal changes in speech produced by children of various ages in view of the development of automatic speech recognition applications. The results of these analyses confirm and complement the results reported in the literature, showing that characteristics of children’s speech change with age and that spectral and temporal variability decrease as age increases. In fact, younger children show a substantially higher intra- and inter-speaker variability with respect to older children and adults. We investigated the use of several methods for speaker adaptive acoustic modeling to cope with inter-speaker spectral variability and to improve recognition performance for children. These methods proved to be effective in recognition of read speech with a vocabulary of about 11k words.
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