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The paper aimed to investigate the influence, on the assessment of the structural safety level of an existing r.c building, of the different choices that the technician in charge of a structural evaluation (the "analyst") can make regarding the structural elements to be tested to obtain a prescribed level of knowledge. To this end, the case study of a reinforced concrete framed structure built in the 1960s in Italy was investigated by means of numerical analyses. The probability distribution of the estimated safety levels was evaluated in the paper by means of a Monte Carlo approach, considering the alternative selections of elements done by a large number of analysts, and the probability of unsuccessful safety estimations is discussed for the knowledge levels considered in the Italian technical codes and the Eurocodes. [ABSTRACT FROM AUTHOR]

This paper deals with precipitation events, particularly the problem of recognising events individually, of distinguishing one local meteorological/precipitation event from another. The final aim was to arrive at a more appropriate conceptualization of "distance" between individual annual events. A criterion for identifying annual precipitation events, inside a 5 min-timestep series of pluviometric data, was proposed. Using this numerical criterion, a series of annual distances between events were obtained and compared with those obtained by other two known and applied statistical methods. This comparison would be important for linking the so-called statistical methods to the real data of the series, analysed through a numerical process. This would make it possible to provide a kind of "measure" for the understanding of real data via a statistical model. Results showed that distances between events, obtained through numerical analyses, are almost always different from those obtained by statistical methods. The supposed Poisson-process, generally matched to, and widely applied in the field of rainfall data, showed some contradiction with the analysis conducted in this paper. The so-called Lag method shows a numerical method type distribution, but produces some important internal deviations from numerical results. It seems that the method proposed in this paper can reproduce the real distances between events more realistically compared to the statistical methods considered here. Exponential distribution does not seem highly performing, at least in the case of the annual analysis, with series of a 5-min time-step resolution, obtained from rain gauges installed in the Veneto Region of Italy. It is believed that the numerical criterion presented in this paper can be considered adequate for determining the distances between events, within an annual time-window. [ABSTRACT FROM AUTHOR]

The estimation of the slope (b -value) of the frequency–magnitude distribution of earthquakes is based on a formula derived by Aki decades ago, assuming a continuous exponential distribution. However, as the magnitude is usually provided with a limited resolution, its distribution is not continuous but discrete. In the literature, this problem was initially solved by an empirical correction (due to Utsu) to the minimum magnitude, and later by providing an exact formula such as that by Tinti and Mulargia, based on the geometric distribution theory. A recent paper by van der Elst showed that the b -value can be estimated also by considering the magnitude differences (which are proven to follow an exponential discrete Laplace distribution) and that in this case the estimator is more resilient to the incompleteness of the magnitude data set. In this work, we provide the complete theoretical formulation including (i) the derivation of the means and standard deviations of the discrete exponential and Laplace distributions; (ii) the estimators of the decay parameter of the discrete exponential and trimmed Laplace distributions and (iii) the corresponding formulas for the parameter b. We deduce (iv) the standard 1 σ intervals for the estimated b. Moreover, we are able (v) to quantify the error associated with the Utsu minimum-magnitude correction. Furthermore, we have discussed the formulas to produce statistically independent magnitude differences. We tested extensively the b -value estimators on simulated synthetic data sets including complete catalogues as well as catalogues affected by a strong incompleteness degree such as aftershock sequences where the incompleteness is made to vary from one event to the next. We have also analysed the real aftershock sequence of the 30/10/2016 Norcia (central Italy) to integrate the finding of the simulations. To judge the performance of the various estimators we have introduced an index p that can be seen as a non-parametric extension of the Student's t index. The main outcomes of this paper are that (1) the b -value estimators devised for continuous magnitude data are not adequate for binned magnitudes, (2) for complete data sets, estimators based on magnitudes and on magnitude differences provide substantially equivalent results, (3) for incomplete magnitude data sets, estimators based on magnitude differences provide better results and (4) for incomplete aftershock sequences there is no evidence that methods based on positive magnitude differences are superior than other methods using differences. This conclusion is further confirmed by our analysis of the above-mentioned Norcia seismic sequence. This last finding contrasts with the van der Elst's claim that the so called |${{b}_ + }$| method is the most adequate to treat real aftershock sequences. [ABSTRACT FROM AUTHOR]

Remote images are useful tools for detecting and monitoring landslides, including shallow landslides in agricultural environments. However, the use of non-commercial satellite images to detect the latter is limited because their spatial resolution is often comparable to or greater than landslide sizes, and the spectral characteristics of the pixels within the landslide body (LPs) are often comparable to those of the surrounding pixels (SPs). The buried archaeological remains are also often characterized by sizes that are comparable to image spatial resolutions and the spectral characteristics of the pixels overlying them (OBARPs) are often comparable to those of the pixels surrounding them (SBARPs). Despite these limitations, satellite images have been used successfully to detect many buried archaeological remains since the late 19th century. In this research context, some methodologies, which examined the values of OBARPs and SBARPs, were developed to rank images according to their capability to detect them. Based on these previous works, this paper presents an updated methodology to detect shallow landslides in agricultural environments. Sentinel-2 and Google Earth (GE) images were utilized to test and validate the methodology. The landslides were mapped using GE images acquired simultaneously or nearly simultaneously with the Sentinel-2 data. A total of 52 reference data were identified by monitoring 14 landslides over time. Since remote sensing indices are widely used to detect landslides, 20 indices were retrieved from Sentinel-2 images to evaluate their capability to detect shallow landslides. The frequency distributions of LPs and SPs were examined, and their differences were evaluated. The results demonstrated that each index could detect shallow landslides with sizes comparable to or smaller than the spatial resolution of Sentinel-2 data. However, the overall accuracy values of the indices varied from 1 to 0.56 and two indices (SAVI and RDVI) achieved overall accuracy values equal to 1. Therefore, to effectively distinguish areas where shallow landslides are present from those where they are absent, it is recommended to apply the methodology to many image processing products. In conclusion, given the significant impact of these landslides on agricultural activity and surrounding infrastructures, this methodology provides a valuable tool for detecting and monitoring landslide presence in such environments. [ABSTRACT FROM AUTHOR]

Inverted distributions, also known as inverse distributions, are essential statistical models for analyzing real-life data in biomedical sciences, engineering, and other fields. In this paper, we use the odd beta prime-G family and the inverted Kumaraswamy distribution to introduce a new inverted distribution called the odd beta prime inverted Kumaraswamy. The new distribution exhibits right-skewed, J-shaped densities and features increasing-constant, concave-convex, and bathtub hazard functions. Some of its statistical properties are explored. The parameters are estimated via the maximum likelihood method. The empirical importance of the new model is proved through its application to COVID-19 mortality data from Italy. Numerical results demonstrate that the proposed model outperforms its competitors. We hope that this proposed distribution can be considered as a viable alternative to some well-established distributions for modeling real-life data across various application areas. [ABSTRACT FROM AUTHOR]

The Italian peninsula offers an excellent case study within which to investigate long-term regional demographic trends and their response to climate fluctuations, especially given its diverse landscapes, latitudinal range and varied elevations. In the past two decades, summed probability distributions of calibrated radiocarbon dates have become an important method for inferring population dynamics in prehistory. Recent advances in this approach also allow for statistical assessment of spatio-temporal patterning in demographic trends. In this paper we reconstruct population change for the whole Italian peninsula from the Late Mesolithic to the Early Iron Age (10,000–2800 cal yr BP). How did population patterns vary across time and space? Were fluctuations in human population related to climate change? In order to answer these questions, we have collated a large list of published radiocarbon dates (n = 4010) and use this list firstly to infer the demographic trends for the Italian peninsula as a whole, before addressing each of five sub-regions in turn (northern, central, and southern Italy, Sicily, Sardinia). We also compare population fluctuations with local paleoclimate proxies (cave, lake, marine records). At a pan-regional scale, the results show a general rapid and substantial increase in population in the Early Neolithic with the introduction of farming at around 8000 cal yr BP and further dramatic increases during the Bronze and Iron Age (~ 3800–2800 cal yr BP). However, different regional demographic trajectories exist across different regions of Italy, suggesting a variety of localised human responses to climate shifts. Population and climate appear to have been more closely correlated during the early–mid Holocene (Mesolithic–Neolithic), while later in the Holocene (Bronze–Iron Ages) they decouple. Overall, across the Holocene the population dynamics varied by region and depended on the long-term socio-ecological dynamics prevailing in a given area. Finally, we include a brief response to the paper 'Radiocarbon dated trends and central Mediterranean prehistory' by Parkinson et al. (J Word Prehist 34(3), 2021)—synchronously published by Journal of World Prehistory but wholly independently developed—indicating how our conclusions accord with or differ from one another. [ABSTRACT FROM AUTHOR]

In this paper, we tackle the problem of the intensity attenuation at Ischia, a critical parameter in a high seismic risk area such as this volcanic island. Starting from the new revised catalogue of local earthquakes, we select a dataset of 118 macroseismic observations related to the four main historical events and analyse the characteristics of the intensity attenuation according to both the deterministic and probabilistic approaches, under the assumption of a point seismic source and isotropic decay (circular spreading). In the deterministic analysis, we derive the attenuation law through an empirical model fitting the average values of ΔI (the difference between epicentral intensity I0 and intensities observed at a site IS) versus the epicentral distances by the least-square method. In the probabilistic approach, the distribution of IS conditioned on the epicentre-site distance is given through a binomial-beta model for each class of I0. In the Bayesian framework, the model parameter p is considered as a random variable to which we assign a Beta probability distribution on the basis of our prior belief derived from investigations on the attenuation in Italy. The mode of the binomial distribution is taken as the intensity expected at that site (Iexp). The entire calculation procedure has been implemented in a python plugin for QGIS® software that, given location and I0 (or magnitude) of the earthquake to be simulated, generates a probabilistic seismic scenario according to the deterministic or probabilistic models of attenuation. This tool may be applied in seismic risk analyses at a local scale or in the seismic surveillance to produce real-time intensity shake-maps for this volcanic area. [ABSTRACT FROM AUTHOR]

In the operational, strategic and tactical decision-making problems of the agri-food supply chain, the perishable nature of the commodities can represent a problem of particular complexity. It is therefore appropriate to consider decision support tools that take into account the characteristics of the products, the needs and requirements of producers, sellers and final consumers. The paper presents an age-based model for the inventory-routing problem of perishable commodities with stochastic demands. In particular, we propose a dynamic decision-making approach with a "moving" horizon that advances over time taking into account the more recent available information. This approach allows future decisions to be rescheduled in relation to new data, over a planning horizon of the same duration. To address a problem as realistic as possible, we assume that the demand for products of each age is unknown and we model this uncertainty by means of random variables with a probability distribution that can be estimated from historical data. Computational experiments on test cases based on a real-life agri-food company located in Southern Italy show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Flash Flood Guidance (FFG) is a rainfall threshold which initiates flooding in streams. It merely provides a binary output (yes or no) which has large uncertainties in forecasting. In this paper, we propose a new method by combining FFG with the Frequentist method to present the probability of flash flood occurrence based on historical rainfall events. We first calculated deviation from the log transform rainfall data leading to flash floods. Kernel Density Estimation (KDE) was used to describe the deviation. Normal Distribution Function (NDF) was chosen to fit the KDE output and to calculate probabilities of flooding as per the Frequentist FFG. In order to aid decision making, three probability thresholds (10, 20 and 60%) were used for defining four flood risk classes, namely very low, low, significant and high, and were colour coded respectively as green, yellow, orange and red. The proposed Frequentist FFG method was then applied to the Posina River basin in Italy. Comparison of forecasts from the conventional FFG (with probability 0 or 1) and Frequentist FFG for 94 6-hourly rainfall events, including 23 flood events, shows that the Frequentist FFG presented a probability of flooding varying from 0 to 100% and the corresponding risk class can be used to reduce false alarms while still reducing the disaster risk. The application of the developed approach to the Posina basin shows that decision making regarding flash forecasting is easier with the presented approach compared to the traditional FFG approach. [ABSTRACT FROM AUTHOR]

Drought is ranked second in type of natural phenomena associated with billion dollars weather disaster during the past years. It is estimated that in EU countries the number of people affected by drought was increased by 20% over the last decades. It is widely recognized that the Standardized Precipitation Index (SPI) can effectively provide drought characteristics in time and space. The paper questions the standard approach to estimate the SPI based on the Gamma probability distribution function, assessing the fitting performance of different biparametric distribution laws to monthly precipitation data. We estimate SPI time series, for different scale of temporal aggregation, on an unprecedented dataset consisting of 332 rain gauge stations deployed across Italy with observations recorded between 1951 and 2000. Results show that the Lognormal distribution performs better than the Gamma in fitting the monthly precipitation data at all time scales, affecting drought characteristics estimated from SPI signals. However, drought events detected using the original and the best fitting approaches does not diverge consistently in terms of return period. This suggests that the SPI in its original formulation can be applied for a reliable detection of drought events and for promoting mitigation strategies over the Italian peninsula. [ABSTRACT FROM AUTHOR]

In the agri-food supply chain, the perishable nature of the commodities opens a series of challenges at all decision levels: strategical, tactical and operational. This paper presents an age-based model for the inventory-routing problem of perishable commodities with stochastic demands. To deal with this source of uncertainty, the conditional value-at-risk (CVaR) has been adopted as a risk measure, and then the model has been applied to the agri-food supply chain under investigation. The model is the core of a dynamic approach for the optimal distribution and inventory planning over a short-medium horizon. To address a problem as realistic as possible, we assume that the demand for products of each age is unknown and we model this uncertainty by means of random variables with a probability distribution that can be estimated from historical data. Computational experiments on test cases based on a real-life agri-food company located in Italy show the effectiveness of the proposed approach for evaluating different risk attitudes. [ABSTRACT FROM AUTHOR]

Predictive models of species distribution, including several parakeets, may be very useful for understanding the actual and potential distribution of alien species. The Ring-necked Parakeet and the Monk Parakeet are two alien species found in the Veneto region (north-east Italy) that are well-suited for conducting potential distribution studies to identify suitable areas of occurrence. In this paper, I use the MAXENT algorithm to predict the potential distribution maps of these species in the Veneto region, which finds the probability distribution of maximum entropy that is constrained by the ecological parameters considered. The authors of the Veneto photo-sound atlas kindly provided presence data for the two species. The potential distribution models for the two parakeets performed very well overall (AUC = 0.966 for Ring-necked Parakeet and AUC = 0.987 for Monk Parakeet) and indicated that high suitability areas correspond primarily to areas near known occurrences of the species. Overall, the study found that the presence of the species in provinces other than those with large populations is highly unlikely. The distribution maps produced can aid in the selection of monitoring areas for these two alien species' populations and potential expansion. [ABSTRACT FROM AUTHOR]

This paper delivers a reliability-based method for the assessment of the elastic modulus (EM) of concrete in simply supported girders from dynamic identification. The correlation between the natural frequencies of the first bending modes and the concrete EM supports the use of the first natural frequency as a predictor of the EM value, which is a well-acknowledged indicator of the state of concrete. In the current application, the EMs of seven girders provide the prior state of knowledge about the considered bridge class, possibly to be obtained by more samples in working applications. The identified natural frequencies update the prior probability distribution of the EMs using Bayes inference. The resulting probability of exceeding a specific EM value expresses the degree of belief of the inspector in the obtained EM. The posterior probability, compared to a proper threshold, could be used in decision-making processes when prioritising the interventions in the maintenance plans. [ABSTRACT FROM AUTHOR]

Enhanced temperature-index distributed models for snowpack simulation, incorporating air temperature and a term for clear sky potential solar radiation, are increasingly used to simulate the spatial variability of the snow water equivalent. This paper presents a new snowpack model (termed TOPMELT) which integrates an enhanced temperature-index model into the ICHYMOD semi-distributed basin-scale hydrological model by exploiting a statistical representation of the distribution of clear sky potential solar radiation. This is obtained by discretizing the full spatial distribution of clear sky potential solar radiation into a number of radiation classes. The computation required to generate a spatially distributed water equivalent reduces to a single calculation for each radiation class. This turns into a potentially significant advantage when parameter sensitivity and uncertainty estimation procedures are carried out. The radiation index may be also averaged in time over given time periods. Thus, the model resembles a classical temperature-index model when only one radiation class for each elevation band and a temporal aggregation of 1 year is used, whereas it approximates a fully distributed model by increasing the number of the radiation classes and decreasing the temporal aggregation. TOPMELT is integrated within the semi-distributed ICHYMOD model and is applied at an hourly time step over the Aurino Basin (also known as the Ahr River) at San Giorgio (San Giorgio Aurino), a 614 km 2 catchment in the Upper Adige River basin (eastern Alps, Italy) to examine the sensitivity of the snowpack and runoff model results to the spatial and temporal aggregation of the radiation fluxes. It is shown that the spatial simulation of the snow water equivalent is strongly affected by the aggregation scales. However, limited degradation of the snow simulations is achieved when using 10 radiation classes and 4 weeks as spatial and temporal aggregation scales respectively. Results highlight that the effects of space–time aggregation of the solar radiation patterns on the runoff response are scale dependent. They are minimal at the scale of the whole Aurino Basin, while considerable impact is seen at a basin scale of 5 km 2. [ABSTRACT FROM AUTHOR]

The assemblage of a building inventory is necessary for the evaluation of seismic impact scenarios at the territorial scale. Building inventory, representing the distribution of building vulnerability classes at the territorial scale, could be performed at different levels of detail, depending on the size of the building stock, the territorial unit of analysis and on the adopted vulnerability model. Census-based data are usually employed as primary source for building inventory. A recent advancement towards compilation of regional scale inventories is provided by the interview-based Cartis approach, implemented in Italy within "Territorial themes" Reluis project, financed by the Italian Civil Protection Department. This paper proposes a first comparison of the results in terms of building inventory and the subsequent impact assessment that are obtained using Census (CE) and Cartis-based (CA) data for a town in southern Italy; a probabilistic framework for inventory is applied. Different vulnerability models are adopted and results compared. Moreover, a simple procedure that combines the informative levels present in the two approaches is proposed, allowing a mixed-type inventory from Census and Cartis data (CC) to be used for seismic impact assessment. Results of the application show that the inventory and related damage distribution changes as a function of the method adopted and in relation to the parameters considered for building classification in the vulnerability model. Comparing the impact in terms of a mean value of damage over the entire municipality, d m , calculated for various seismic intensities and starting from CE, CA and CC inventory, it is seen that the CC inventory is generally more conservative with respect to CA and CE for all the vulnerability methods, and a maximum scatter of approximately 45% in terms of d m is obtained for the considered application with one of the vulnerability methods. • The paper presents simplified methods to assemble building inventory. • Initial considered databases for building inventory are census returns and a newly developed interview-based database. • First comparison of the results on building inventory and damage assessment obtained using three types of building inventory. • Different vulnerability methods are considered for building classification and expected damage calculation. • The method is applied for a case study town in southern Italy. [ABSTRACT FROM AUTHOR]

• We propose a new method to quantify Climate Change Effects at hydrological scales. • The method allows to assimilate climatic projections in CDFs at rain gauge scale. • The initial (i.e., before any change scenario begins) skewness plays a crucial role. • A strong increase of outliers frequency is expected for series EV1 alike skewed. Quantifying the potential effects of Climate Change (CC) on hydrological scales is a topic with a more and more increasing interest for the scientific community, given the CC impact on agriculture, industry, economy, human health, ecosystems, among the others. In this context, the paper focuses on the sub-daily Annual Maxima (AM) of rainfall height time series, and specifically on the crucial role played by initial skewness, i.e. the skewness of the observed rainfall series used to evaluate potential parametric trends. Here a quick and user-friendly methodology is proposed, that is aimed at quantifying plausible future changes in terms of probability distributions assumed at rain gauge scale, from projections of any climatic model. In detail, the Generalized Extreme Value (GEV) and the Two-Component Extreme Value (TCEV) distributions are adopted as probability functions suitable for modelling observed rainfall AM series, which could increase their frequency and magnitude into future horizons under CC. EURO-CORDEX projections for Europe are considered, under the hypothesis that the values of the change factor, i.e. the ratio between the values of a specific quantile at two specific time horizons, are invariant when moving from an areally-averaged scale (typical for any climate model) to a point rain gauge scale, which induces that future changes are provided (in terms of frequency and magnitude of extreme events) without the need of any spatial downscaling from the assumed projections. The proposed methodology can contribute to hazard quantification associated to potential climate changes, and thus it can play a crucial role in the assessment of hydraulic structures resilience; the obtained results, specific for the study area of Italy, but easily extendable on a global scale, showed that larger increases in frequency of future heavy events are expected for time series with "EV1 alike" values of initial skewness. [ABSTRACT FROM AUTHOR]

Within the inferential context of predicting a distribution of potential outcomes P[y(t)] under a uniform treatment assignment tϵT, this paper deals with partial identification of the α-quantile of he distribution of interest Qα[y(t)] under relatively weak and credible monotonicity-type assumptions on he individual response unctions and the population selection process. On the theoretical side, the paper adds o the existing results on on-parametric bounds on quantiles with no prior information and under monotone treatment response (MTR) by introducing and studying the identifying properties of α-quantile monotone treatment selection (α-QMTS), α-quantile monotone instrumental variables (α-QMIV) and their combinations. The main result parallels that for the mean; MTR and α-QMTS aid identification in a complementary fashion, so that combining them greatly increases identification power. The theoretical results are illustrated through an empirical application on the Italian returns to educational qualifications. Bounds on several quantiles of l (wage) under different qualifications and on quantile treatments effects (QTE) are estimated and compared with parametric quantile regression (α-QR) and α-IVQR estimates from the same sample. Remarkably, the α QMTS & MTR upper bounds on the α-QTE of a college degree versus elementary education imply smaller year-by-year returns than the corresponding α-IVQR point estimates. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents multilevel models that utilize the Coxian phase-type distribution in order to be able to include a survival component in the model. The approach is demonstrated by modeling patient length of stay and in-hospital mortality in geriatric wards in Italy. The multilevel model is used to provide a means of controlling for the existence of possible intra-ward correlations, which may make patients within a hospital more alike in terms of experienced outcome than patients coming from different hospitals, everything else being equal. Within this multilevel model we introduce the use of the Coxian phase-type distribution to create a covariate that represents patient length of stay or stage (of hospital care). Results demonstrate that the use of the multilevel model for representing the in-patient mortality is successful and further enhanced by the inclusion of the Coxian phase-type distribution variable (stage covariate). [ABSTRACT FROM PUBLISHER]

Background: On December 2017 the Italian Parliament approved law n. 219/2017 "Provisions for informed consent and advance directives" regarding challenging legal and bioethical issues related to healthcare decisions and end-of life choices. The law promotes the person's autonomy as a right and provides for the centrality of the individual in every scenario of health care by mean of three tools: informed consent, shared care planning and advance directives. Few years after the approval of the law, we conducted a survey among physicians working in four health care facilities specific for the care of people suffering from psychiatric disorders, cognitive disorders and dementia located in the North of Italy aiming to investigate their perceived knowledge and training need, attitudes regarding law n. 219/2017 provisions, and practices of implementation of the law. Methods: A semi-structured questionnaire was developed on an online platform. The invitation to participate in the survey was sent by email to the potential participants. Information was collected by means of the online platform (Google Forms) which allows to export data in a spreadsheet (Windows Excel) to perform basic statistical analysis (frequency distributions, bar chart representation). Results: Twenty-five out of sixty physicians participated in the survey. None of the respondents value their knowledge of the law as very good, 10 good, 13 neither poor nor good, 1 poor and 1 very poor. All the respondents want to learn more about the law (21 yes and 4 absolutely yes). The majority of respondents agrees with the content of the law as a whole (3 absolutely agree, 13 agree), and on each provision. The question on the clarity of the concept of capacity in the law received mixed answers and this impacted on the physicians' opinion regarding the legitimacy in principle for our groups of patients to realize shared care planning and write advance directives. Thirteen physicians neither introduced the theme of shared care planning nor arranged for shared care planning and the main reason for this was that no patient was in a clinical situation to require it. When shared care planning is realized, a variability in terms of type and number of meetings, mode of tracking and communication is registered. Conclusions: Our survey results indicate a need for more clarity regarding the interpretation and implementation of the law in the patient groups under study. There are in particular two related areas that deserve further discussion: (1) the question of whether these patient groups are in principle legitimized by the law to realize shared care planning or write advance directives; (2) the notion of capacity required by the law and how this notion can be declined in real-life situations. [ABSTRACT FROM AUTHOR]

A series of recent papers have introduced some explorative methods based on Ripley's K-function (Ripley in J R Stat Soc B 39(2):172-212, ) analyzing the micro-geographical patterns of firms. Often the spatial heterogeneity of an area is handled by referring to a case-control design, in which spatial clusters occur as over-concentrations of firms belonging to a specific industry as opposed to the distribution of firms in the whole economy. Therefore, positive, or negative, spatial dependence between firms occurs when a specific sector of industry is seen to present a more aggregated pattern (or more dispersed) than is common in the economy as a whole. This approach has led to the development of relative measures of spatial concentration which, as a consequence, are not straightforwardly comparable across different economies. In this article, we explore a parametric approach based on the inhomogeneous K-function (Baddeley et al. in Statistica Nederlandica 54(3):329-350, ) that makes it possible to obtain an absolute measure of the industrial agglomeration that is also able to capture spatial heterogeneity. We provide an empirical application of the approach taken with regard to the spatial distribution of high-tech industries in Milan (Italy) in 2001. [ABSTRACT FROM AUTHOR]

In this paper we present a comparison of statistical and spatial distributions between Pb, Cu and Zn concentration data and clr-transformed data of 3669 topsoil samples from the Campanian Region. Results show that both approaches, the classical univariate analysis and the compositional data analysis, are necessary to understand the real structure of the data and shed light on different aspects. In particular, the spatial distributions of concentration ('raw') data and clr-transformed data of the three elements differ completely. Raw data essentially represent a high anthropogenic impact, requiring an additional human health risk assessment for the three investigated elements. The information obtained by the clr-coefficient maps reveals the geogenic contribution to the element distribution. To better constrain the degree of contamination due to these potentially toxic elements and their impact on human health, we present an RGB composite map of Pb, Cu and Zn. This map unravels potential sources of contamination and locates the areas where concentrations exceed thresholds established by the Italian legislation. [ABSTRACT FROM AUTHOR]

This is a methodological paper aimed at comparing methods to assess regional biodiversity. In more detail we compared the effectiveness of hotspots of species richness, of rarity and complementarity in evaluating local animal diversity. Species distributions were sampled over a 10×10 km UTM grid across the Italian territory. We considered 471 species of zygaenids, butterflies, carabines, amphibians and reptiles. Hotspots were analysed at national and regional levels and considered taxa either all together, or separately. To test the predictive value of complementarity analysis, we initially excluded zygaenids. At national level, of 3218 10×10 km UTM quadrats sampled, 161 (5% of total) had highest species richness. Islands included only 1 hotspot (Sicily). Sixty-eight species (14.4%) were not represented. They were mainly endemic (65%), insular (73.5%), or rare (25%). Working taxon by taxon, hotspots numbered 433. Only 85 (19.6%) were hotspots contemporaneously for two taxa and only 9 were hotspots for 3 taxa. Missing species were fundamentally insular species. The regional-level approach generated 467 hotspots. Eleven species were not represented (2.3%). They had marginal distributions, or were insular endemites. Hotspots of rarity numbered 235 and 10 species were not included. Results demonstrated that hotspots are poor predictors of overall biodiversity. The complementarity method identified 67 quadrats. By definition, these quadrats accounted for all species investigated. They failed, however, to predict the occurrence of three zygaenids. As expected, complementarity provided better results than hotspots analysis. Combining the two methods assures that areas having the highest biodiversity are identified, even working with incomplete databases. Regional or rarity hotspots should generally be preferred to hotspots of species richness. [ABSTRACT FROM AUTHOR]

The model proposed in this paper combines a logistic regression model and a Weibull regression model for the analysis of current-status data. This joint model allows a simultaneous estimation of two sets of effects on the covariates: one on the probability that the event occurs (also known as quantum) and the other on the timing of the event. Thus, the model can be seen either as an extension of a survival-analysis model for use with current-status data where a survival fraction is added in order explicitly to take into account the possibility that the event may never occur, or as an extension of survival analysis with long-term survivors to the analysis of current-status data. As an illustrative application we apply our model to a study of nuptiality in seventeenth-century Italy. [ABSTRACT FROM AUTHOR]

In this paper we analyze the relationship between the distribution of firm size and stochastic processes of growth. Three main models have been suggested by Gibrat (1931), Kalecki (1945) and Champernowne (1973). The first two lead to lognormal distribution and the last to Pareto distribution. We fitted lognormal and Pareto distribution to two Italian sectors: ICT and mechanical. For ICT we found that lognormal distribution must be rejected and Pareto fits reasonably well to the last 30% of largest companies. For mechanical sector we can not reject lognormal distribution. Furthermore, we perform some experiments o corroborate the theoretical models. By means of transition matrices we found that ICT shows features very close to Gibrat's and Champernowne's models, while Kalecki's model strongly fits to mechanical. [ABSTRACT FROM AUTHOR]

Soil moisture is an important variable controlling many land surface processes and is used to quantify precipitation, drought, flooding, irrigation and other factors that influence decision making and risk-assessment. This paper presents the retrieval of high resolution (∼ 1 km) soil moisture data from Sentinel-1 C-band Synthetic Aperture Radar (SAR) backscatter measurements using a new bistatic radiative transfer modeling framework (RT1) previously only tested for scatterometer data. The model is applied over a diverse set of landcover types across the entire Po-Valley in Italy over a 4-year time-period from 2016 to 2019. The performance of the soil moisture retrievals is analyzed with respect to the ERA5-Land reanalysis dataset. The model parameterisation and retrieval method are chosen such as to constitute a trade-off between a physically plausible and a computationally feasible modeling approach. The results demonstrate the potential of RT1 for the retrieval of high-resolution soil moisture data from SAR time series. • Radiative transfer based soil moisture retrievals from Sentinel-1 at 1 km spatial resolution. • Incidence-angle dependent scattering characteristics modeled via (bistatic) distribution functions. • Dynamic vegetation correction via auxiliary Leaf Area Index timeseries. • Overall good retrieval results among different landcover types. [ABSTRACT FROM AUTHOR]

Raw counts of archaeological sites, estimates of changing settlement size and summed radiocarbon probability distributions have all become popular ways to investigate long-term regional trends in human population. Nevertheless, these three archaeological proxies have rarely been compared. This paper therefore explores the strengths and weaknesses of different kinds of archaeological evidence for population patterns, as well as how they address related issues such as taphonomic loss, chronological uncertainty and uneven sampling. Our overall substantive goal is to reconstruct demographic fluctuations in central Italy from the Late Mesolithic to the fall of the Roman Empire (7500 BC-AD 500), and with this in mind, we bring to bear an unusually detailed and extensive dataset of published central Italian archaeological surveys, consisting of some 10,971 occupation phases at 7383 different sites. The comparative results demonstrate reassuring consistency in the suggested demographic patterns, and where such patterns diverge across different proxies (e.g. Late Bronze Age/Iron Age) they often do so in useful ways that suggest changes in population structure such as site nucleation or dispersal. [ABSTRACT FROM AUTHOR]

The research presented in this paper has analyzed 50 years of urban evolution in Italy and noted a considerable difference of geographic patterns of settlement growth compared to other countries of the World. The model of sprawl, recognized as international standard and a territorial disease, largely concerns the industrialized countries, but also developing countries, and in particular the entire European area, but distribution patterns in southern Europe, especially in countries in the Iberian, Mediterranean and Balkan areas, are significantly different from those found in northern Europe and other continents. Our study has investigated and diagnosed the forms of urban growth focusing on the Italian model, one of the most significant in Western Europe and for which we propose an alternative definition (urban sprinkling). It is important to highlight that the damage caused on the landscape, environment and communities by urban sprinkling is much more serious and irreversible than what notoriously caused by urban sprawl. Furthermore, there has been a drastic change in numerous rural, mountain and coastal landscapes, which today are profoundly different from those historically appreciated by culture and international tourism. The settlement configuration called “sprinkling” introduces the difficult methodological and planning aspects of its retrofit (de-sprinkling), a true challenge for land management, arguing that the even partial inversion of many negative effects is basically impossible in the short term; whereas, in a medium-long term, organized and politically coordinated programmes can tackle the various issues. [ABSTRACT FROM AUTHOR]

This article presents an innovative dynamic model that describes the probability distributions of ordered categorical variables observed over time. For this purpose, we extend the definition of the mixture distribution obtained from the combination of a uniform and a shifted binomial distribution (CUB model), introducing time-varying parameters. The model parameters identify the main components ruling the respondent evaluation process: the degree of attraction towards the object under assessment, the uncertainty related to the answer, and the weight of the refuge category that is selected when a respondent is unwilling to elaborate a thoughtful judgement. The method provides a tool to quantify the data from qualitative surveys. For illustrative purposes, the dynamic CUB model is applied to the consumers' perceptions and expectations of inflation in Italy to investigate: (a) the effect of the COVID pandemic on inflation beliefs; (b) the impact of income level on respondents' expectations. [ABSTRACT FROM AUTHOR]

In being aware that some factors (i.e. increasing pollution levels, Urban Heat Island (UHI), extreme climate events) threaten the quality of life in cities, this paper intends to study the Atmospheric UHI phenomenon in Bari, a Mediterranean coastal city in Southern Italy. An experimental investigation at the micro-scale was conducted to study and quantify the UHI effect by considering several spots in the city to understand how the urban and physical characteristics of these areas modify air temperatures and lead to different UHI configurations. Air temperature data provided by fixed weather stations were first compared to assess the UHI distribution and its daily, monthly, seasonal and annual intensity in five years (from 2014 to 2018) to draw local climate information, and then compared with the relevant national standard. The study has shown that urban characteristics are crucial to the way the UHI phenomenon manifests itself. UHI reaches its maximum intensity in summer and during night-time. The areas with higher density (station 2—Local Climate Zone (LCZ) 2) record high values of UHI intensity both during daytime (4.0 °C) and night-time (4.2 °C). Areas with lower density (station 3—LCZ 5) show high values of UHI during daytime (up to 4.8 °C) and lower values of UHI intensity during night-time (up to 2.8 °C). It has also been confirmed that sea breezes—particularly noticeable in the coastal area—can mitigate temperatures and change the configuration of the UHI. Finally, by analysing the frequency distribution of current and future weather scenarios, up to additional 4 °C of increase of urban air temperature is expected, further increasing the current treats to urban liveability. [ABSTRACT FROM AUTHOR]

This study examines the wind-wave characteristics along the Emilia-Romagna coasts (northern Adriatic Sea, Italy) with a 10-year wave simulation for the period 2010–2019 performed with the high-resolution unstructured-grid WAVEWATCH III (WW3) coastal wave model. The wave parameters (significant wave height, mean and peak wave period, and wave direction) were validated with the in situ measurements at a coastal station, Cesenatico. In the coastal belt, the annual mean wave heights varied from 0.2–0.4 m, and the seasonal mean was highest for the winter period (>0.4 m). The Emilia-Romagna coastal belt was characterized by wave and spectra seasonal signals with two dominant frequencies of the order of 10 and 5–6 s for autumn and winter and 7–9 and 4 s for spring and summer. The wavelet power spectra of significant wave height for 10 years show considerable variability, having monthly and seasonal periods. This validated and calibrated data set enabled us to study the probability distributions of the significant wave height along the coasts and define a hazard index based on a fitted Weibull probability distribution function. [ABSTRACT FROM AUTHOR]

In recent years, there has been increasing interest in theoretical descriptions of seismicity in terms of statistical physics. Most aspects of these studies are encompassed by the concept of 'intermittent criticality', in which a region alternately approaches and retreats from a critical point. In this study, we analyse a descriptor of seismic activity that acts as a measure of the criticality of a system, such that its variations can be associated with changes in the state of the system. As some classical methods of analysis are not suitable for dealing with some of the features of complex systems such as the Earth's crust, we derive the probability distribution of the magnitude by maximizing a non-extensive generalization of the Boltzmann–Gibbs entropy given by the Tsallis entropy. In particular, the shape parameter q of this distribution, called the entropic index, characterizes the subadditive q > 1 and superadditive q < 1 regimes. Following the Bayesian approach for parameter estimation, we examine the seismic activity that has affected two seismogenic areas in central Italy that were hit recently by destructive earthquakes: L'Aquila in 2009, and Amatrice–Norcia in 2016. To analyse in detail the variations of the q index and the entropy, we estimate these for time windows of a fixed number of events that shift at each new event. Both the q index and the Tsallis entropy show significant and lasting decreases before the first strong earthquake in the sequences, and sudden increases after them. This indicates that these quantities can be considered as indicators of the level of concentration of energy, and hence of the activation state of the systems. More reliable results need to come from further studies of different cases in different seismotectonic settings. [ABSTRACT FROM AUTHOR]

This paper presents the results of an environmental geochemical investigation of the Gulfs of Naples and Salerno, near the Campania plain (Southern Italy). Surface marine sediment samples were collected during three field campaigns: 96 from the Gulfs of Naples and Salerno (NaSa); 123 from the Bagnoli site coastal area (BaSi); and 11 from the ports around the Gulf of Naples (PoNa). Elemental concentrations were determined and their interpolated distribution maps were compiled. Three geochemical sources (or processes) were determined associating elemental distribution with the results obtained from a R-mode factor analysis: 1) geogenic, 2) water kinetics and 3) anthropogenic. The results are presented as raw data single element distributions of eight potential toxic elements (PTEs) (As, Cd, Cr, Cu, Hg, Pb, Ni and Zn) in the forms of raw data and additive log-ratio transformed data. The latter showed advantages in revealing the actual distribution patterns. Geochemical background reference values of PTEs were determined from the median value of local background reference values. Based on these values, pollution impact analysis was carried out to both BaSi and PoNa samples, indicating most of BaSi and PoNa sediments were affected by moderate to strong Pb, Zn, Cd and Hg pollution. An ecological risk assessment was subsequently carried out on the entire database, pointing a toxic risk ranking in the order Pb > As > Ni > Cd > Hg > Cr. [ABSTRACT FROM AUTHOR]

Abstract: Theoretical developments in political economy analyses of intergovernmental transfers identify several factors previously ignored in the empirical literature and emphasize the importance of institutional details. Combined, these two developments create a degrees of freedom problem and make cross country samples less meaningful. This paper circumvents these problems by examining an Italian regional panel that minimizes the set of institutional conditioning factors and is large enough to examine a comprehensive set of explanatory variables. The estimates confirm the relevance of most political determinants and of standard economic and socio-demographic determinants of interregional redistribution. Differences in type of expenditures and intergovernmental relations are also considered. [Copyright &y& Elsevier]

Abstract: An extraordinary plan of official control was carried out in 2008 in Campania (Italy) with the aim to monitor polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs) and dioxin-like polychlorinated biphenyls (dl-PCBs) levels in buffalo milk and to detect the contaminated farms, most of which are located in Caserta province. For these companies has been ordered seizure and execution of additional analyses has been requested in farms falling in the nearness, within a distance of 3km, for a total of 304 farms examined. Moreover, all non-compliant farms were subjected to a periodic sampling in order to monitor trends in the levels of contamination. In this paper the distribution and the concentrations of 17 PCDD/Fs and 12 dioxin-like PCBs in 460 samples of buffalo milk collected in the province of Caserta (Italy) are presented. The range of WHO-TEQ values for the PCDD/Fs in milk was 0.17pgTEQg−1 fat and 87.0pgTEQg−1 fat with a mean value 3.63pgTEQg−1 fat and medium value 2.25pgTEQg−1 fat. The concentrations of dioxin-like PCBs in the analysed samples ranged from 0.21pgTEQg−1 fat to 15.9pgTEQg−1 fat and the WHO-TEQ values of sum of PCDDs, PCDFs and dl-PCBs ranged from 0.45pgTEQg−1 fat to 103.0pgTEQg−1 fat. The geo-referencing analysis allowed to individuate a restricted area of the region object of the present study where is located the majority of the non-compliant farms. The study of the congeners distribution has finally suggested that the likely cause of contamination is to be attributed to the illegal burning of waste. [Copyright &y& Elsevier]

Three methods for identifying, characterizing, and controlling active sonar clutter are described and demonstrated on broadband, low-frequency (<1800 Hz) normalized data collected in two range-dependent, shallow-water environments: the Malta Plateau off Sicily and the Stanton Banks off Scotland. One method examines short time-scale clutter persistence to stabilize/minimize coherent propagation effects. A second method correlates strong clutter echoes with the depth-weighted topographic slope (relative to the sonar) to help predict the significant scatterers. A third method involves moment-based statistical measures [Poisson-Rayleigh-inspired method (PRIM), K-distribution shape parameter, kurtosis] to distinguish between spatially compact and spatially extended clutter objects. As illustrated with the isolation of several anthropogenic objects from widespread topographic clutter on the Malta Plateau, the new Poisson-Rayleigh (P-R)-based method appears to offer some promise in regards to reducing the false alarm rate. [ABSTRACT FROM AUTHOR]

Summary: The probability distribution of the annual maximum peak flows on the River Tiber at the town of Rome (Ripetta) can be evaluated using the information available since the XV century. In this paper the probability distribution of two series of annual peak flows maxima observed at the Ripetta gauge is analysed: the systematic series, including all the data observed since the beginning of the systematic stage record in 1782, and the censored series of the exceptional floods that inundated the town of Rome, starting from the XV century. In order to find a criterion for choosing the “optimum” distribution law for the high return period quantiles, an index that takes into account both the accuracy and the uncertainty of the quantiles estimation is proposed. [Copyright &y& Elsevier]

Abstract: This paper performs annual runoff frequency analysis in Sicily, Italy using the index runoff method. Homogeneous regions, not necessarily defined by geographical boundaries but sharing common features from a morphologic and climatic standpoint, have been identified. For each region a single probability distribution function can be fitted to the available annual runoff data scaled by the index runoff. Starting from an initial dataset of 105 hydrometric stations, 57 stations have been selected using heuristic criteria associated with the Hosking and Wallis’s discordancy measure. The Mantel tests have been then applied to find out the physical and morphological parameters best correlated with the runoff using the distances matrix approach. These parameters have been successively used in the cluster analysis to delineate homogeneous regions and the Hosking and Wallis’s heterogeneity test has been applied to the clusters in order to verify their homogeneity. Further analysis has been carried out to test the goodness-of-fit of four different candidate distributions of the scaled annual runoff using the chi-square test. For all the identified homogeneous regions the three-parameters lognormal distribution has been proved the most suitable distribution for the dimensionless annual runoff. In order to predict the runoff quantiles at ungauged sites, the procedure finally envisages the estimation of mean annual runoff (index runoff) by multiple regression analysis, providing expressions that relate mean annual runoff to some climatic and morphologic features of the basins. [Copyright &y& Elsevier]

Summary: The main objective of this paper is to evaluate a threshold-based flash flood warning method, by considering a wide range of climatic and physiographic conditions, and by focusing on ungauged basins. The method is derived from the flash flood guidance (FFG, hereafter) approach. The FFG is the depth of rain of a given duration, taken as uniform in space and time on a certain basin, necessary to cause minor flooding at the outlet of the considered basin. This rainfall depth, which is computed based on a hydrological model, is compared to either real-time-observed or forecasted rainfall of the same duration and on the same basin. If the nowcasted or forecasted rainfall depth is greater than the FFG, then flooding in the basin is considered likely. The study provides an assessment of this technique based on operational quality data from 11 mountainous basins (six nested included in five larger parent basins) located in north-eastern Italy and central France. The model used in this study is a semi-distributed conceptual rainfall–runoff model, following the structure of the PDM (probability distributed moisture) model. Two general questions are addressed: (1) How does the efficiency of the method evolve when the simulation parameters can not be calibrated but must be transposed from parent gauged basins to ungauged basins? (2) How sensitive are the results to the method used to estimate the initial soil moisture status? System performances are evaluated by means of categorical statistics, such as the critical success index (CSI). Results show that overall CSI is equal to 0.43 for the parent basins, where the hydrological model has been calibrated. CSI reduces to 0.28 for the interior basins, when model parameters are transposed from parent basins, and to 0.21, when both model parameters and soil moisture status is transposed from parent basins. Performance differences between FFG and use of time-constant soil moisture status are very high for the parent basins and decrease with decreasing the system accuracy. The percent difference amounts to 53% for the parent basins, to 25% for interior basins with parameter transposition, and to 19% for interior basins with parameter and soil moisture status transposition. These results improve our understanding of the applicability and reliability of this method at various scales and under various scenarios of data availability. [Copyright &y& Elsevier]

Recent research in Umbria, Italy, has shown that landslide susceptibility is controlled by a process called path-dependency, which describes how past landslides control the locations of future landslides. To date, landslide path-dependency has only been characterised in Italy. This raises the question of whether this process occurs in other geomorphic settings, and thus whether path-dependency should be more universally included in landslide susceptibility assessments. Therefore, the main aim of this paper is to investigate and quantify landslide path dependency in the Nepal Himalaya. This is achieved by applying several path dependent metrics to three monsoon-triggered landslide inventories for the central-eastern Nepal Himalaya. These inventories were developed at two different spatial and temporal resolutions. As such, we aim not just to quantify landslide path-dependency, but also to assess whether path dependency characteristics are resolution-dependent. We find strong evidence that landslide path dependency is occurring in Nepal, with all three inventories having more overlap between past and new landslides than expected from a random distribution, and a tentative observation that the expected degree of overlap between landslides decreases with time. Finally, whilst path-dependency is observable across both of the investigated inventory resolutions, we find that the rates and magnitudes of the quantified path dependent metrics are sensitive to inventory length, study region size and the size/type of landslides mapped. Overall, our results corroborate the path-dependency observations from Italy, confirming that this process does occur in other geomorphic settings, and thus suggesting that path-dependency should be explicitly and universally considered in landslide susceptibility approaches. [ABSTRACT FROM AUTHOR]

The classical procedure of the probabilistic seismic hazard analysis (PSHA) requires a Poissonian distribution of earthquakes. Seismic catalogues follow a Poisson distribution just after the application of a declustering algorithm that leaves only one earthquake for each seismic sequence (usually the stronger, i.e. the main shock). Removing earthquakes from the seismic catalogues leads to underestimation of the annual rates of the events and consequently associate with low seismic hazard as indicated by several studies. In this study, we aim investigating the performance of two declustering methods on the Italian instrumental catalogue and the impact of declustering on estimation of the b- value and on the seismic hazard analysis. To this end, first the spatial variation in the seismicity rate was estimated from the declustered catalogues using the adaptive smoothed seismicity approach, considering small earthquakes (M w ≥ 3.0). We then corrected the seismicity rates using new approach that allows for counting all events in the complete seismic catalogue by simply changing the magnitude frequency distribution. The impact of declustering on seismic hazard analysis is illustrated using PSHA maps in terms of peak ground acceleration and spectral acceleration in 2 s, with 10 per cent and 2 per cent probability of exceedance in 50 yr, for Italy. We observed that the hazard calculated from the declustered catalogues was always lower than the hazard computed using the complete catalogue. These results are in agreement with previous results obtained in different parts of the world. [ABSTRACT FROM AUTHOR]

The 100 year discharge series of the Caposele karst spring in southern Italy enables insight into variations in water resource availability under climate change, given the length of the series, the systematic quality of the records and the absence of human-made alteration of the natural conditions of the aquifer. With this scope, frequency and trend analyses of hydro-meteorological variables were conducted. Various three-parameter probability distribution functions were fitted to the data to calculate the Standardized Discharge Index, which describes spring discharge variations in a standardized manner. Common goodness-of-fit tests were applied to evaluate the performance of each distribution. In addition, a new criterion based on the frequency of events exceeding specific extreme Z values is proposed to quantify the deviation of the calculated index from the theoretical Standard Normal Distribution. The Weibull distribution was found to be best for calculating standardized series of spring discharge as it fits the extreme values of both tails well. The relationship between spring discharge and climatic variables was investigated by using least square linear regression, Mann–Kendall and Sen's slope trend detection tests, applied to the entire series and to 30-year moving time series. A statistically significant decrease of spring discharge of −0.0045 m3 s–1/year has occurred over the last 100 years, whereas no statistically significant trends were found in annual or seasonal precipitation series. However, temperature has constantly been above the mean during the past two decades. An analysis of trends in the moving time series of all variables suggests a connection between the observed spring discharge decay and temperature increase, which can be considered common to other areas of central-southern Italy. [ABSTRACT FROM AUTHOR]

• Construction of a thermal model of the vertical temperature distribution in the shallow aquifer. • Variable temperature zone is identified in 0–25 m depth range in NW Italy alluvial plain. • Constant temperature zone is identified in 25–50 m depth range in NW Italy alluvial plain. • Elaboration of simple equations useful to design geothermal systems in the western Po Plain. This study analyses the temperature distribution underneath the Piedmont Po Plain (NW Italy), where an important shallow aquifer exists due to fluvial and outwash deposits. A total of 118 thermal logs, for a total of 513 temperature measurements in spring 2008 and 585 in autumn 2008, were used to propose the conceptual thermal model of the vertical temperature distribution in the shallow aquifer of the western Po Plain. A constant temperature depth between 30 and 50 m below ground level was observed, under which aquifer temperatures were constant in the range 13−15 °C during the year independent of the external climatic condition. Above the constant temperature depth, the variable temperature zone , where the temperature is strongly influenced by external seasonal variations, was observed. Moreover, the collected thermometric data were processed, and the solution to the heat diffusion equation underground allowed us to determine the average distribution of temperature at different depths over time. This study provides a more detailed conceptual model of the temperature distribution in the Piedmont Po Plain. The model can be applied to other areas with similar hydrogeological characteristics (e.g., the eastern Po Plain or large plain alluvial aquifers). The paper also furnishes a description of the physical processes of heat diffusion in the shallow aquifer, as supported by statistical analysis. The proposed methodology may be adopted as a simple statistical method for the assessment of temperature values for the low-enthalpy geothermal exploitation of groundwater resources. [ABSTRACT FROM AUTHOR]

The assessment of the radiological impact of decommissioning activities at a nuclear power plant requires a detailed analysis of the distribution of radionuclides in the environment surrounding it. The present work concerns data of three campaigns carried out during the last twenty years in the plain of the Garigliano river surrounding the Garigliano Nuclear Power Plant (GNPP), which is located in Southern Italy and shut down in 1979. Moreover, some data from surveys held in the eighties, across the Chernobyl accident, have been taken in account. The results for the soil samples, in particular for 137Cs and 236U specific activity, were analyzed for their extension in space and in time. Some of the problems related to the classical analysis of environmental radiological data (non-normal distribution of the values, small number of sample points, multiple comparison and presence of values lesser than the minimum detectable activity) have been overcome with the use of Bayesian methods. The scope of the paper is threefold: (1) to introduce the data of the last campaign held in the Garigliano plain; (2) to insert these data in a larger spatio-temporal frame; (3) to show how the Bayesian approach can be applied to radiological environmental surveys, stressing out its advantages over other approaches, using the data of the campaigns. The results show that radionuclides specific activity in soil is dominated by the natural sources with the contribution of the atmospheric fallout. A detailed study was performed on the 137Cs data to evaluate both their statistical distribution and the trend over the space and the time. It results that (i) no new contribution there was in the last decades, (ii) specific activity values of the area surrounding the GNPP are consistent with those obtained in other farther areas, (iii) the effective depletion half-life factor for 137Cs is much lower than the half-life of the radionuclide. • The Bayesian approach in the study of environment has some clear-cut benefits. • Specific activity in soil is dominated by the atmospheric fallout. • Effective half-life factor for 137Cs is much lower than that of the radionuclide. [ABSTRACT FROM AUTHOR]

Background: Next-generation sequencing (NGS) needs to be validated and standardized to ensure that cancer patients are reliably selected for target treatments. In Italy, NGS is performed in several institutions and harmonization of wet and dry procedures is needed. To this end, a consortium of five different laboratories, covering the most part of the Italian peninsula, was constituted. A narrow gene panel (SiRe®) covering 568 clinically relevant mutations in six different genes (EGFR, KRAS, NRAS, BRAF, cKIT , and PDGFR α) with a predictive role for therapy selection in non-small cell lung cancer (NSCLC), gastrointestinal stromal tumor, colorectal carcinoma (CRC), and melanoma was evaluated in each participating laboratory. Methods: To assess the NGS inter-laboratory concordance, the SiRe® panel, with a related kit and protocol for library preparation, was used in each center to analyze a common set of 20 NSCLC and CRC routine samples. Concordance rate, in terms of mutation detected and relative allelic frequencies, was assessed. Then, each institution prospectively analyzed an additional set of 40 routine samples (for a total of 160 specimens) to assess the reproducibility of the NGS run parameters in each institution. Results: An inter-laboratory agreement of 100% was reached in analyzing the data obtained from the 20 common sample sets; the concordance rate of allelic frequencies distribution was 0.989. The prospective analysis of the run metric parameters obtained by each center locally showed that the analytical performance of the SiRe® panel in the different institutions was highly reproducible. Conclusions: The SiRe® panel represents a robust diagnostic tool to harmonize the NGS procedure in different Italian laboratories. [ABSTRACT FROM AUTHOR]

Debris flow events, generated by surface runoff, occur with great frequency in the Dolomites (Northeastern Italian Alps) during the summer season. Summer thunderstorms, which are common in the region, can quickly generate runoff at the base of rocky cliffs, which then entrains and propagates downstream the underlying unconsolidated material. In the past, the main atmospheric feature considered in evaluating the initiation of debris flow events was rainfall. Observations led to the development of rainfall intensity–duration thresholds for sediment mobilization, which compared incoming severe rainfalls with the potential for triggering debris flows. This study works toward the examination of another characteristic of the atmosphere, the atmospheric electric field. In particular, the behavior of the electric field prior to convective rainfall is investigated as an indicator of rainfall intensities capable of triggering debris flows, in a basin near Cortina d'Ampezzo (Italy). Results suggest that prior to bursts of intense rainfall, the electric field derivative frequency distribution exhibits a recurrent pattern roughly half the time. When it occurs, the amplitude of derivative frequency distribution intersects the zero axis twice before rainfall reaches maximum intensity. A regression model is designed which considers the amplitude maximum and the difference in time between the crossings of the zero axis. The validation of this model suggests a mild relationship between electric field and rainfall intensity in an alpine environment. [ABSTRACT FROM AUTHOR]

We consider sparse random networks of Kuramoto phase oscillators with inertia in order to mimic and investigate the dynamics emerging in high-voltage power grids. The corresponding natural frequencies are assumed to be bimodally Gaussian distributed, thus modeling the distribution of both power generators and consumers, which must be in balance. Our main focus is on the theoretical analysis of the linear stability of the frequency-synchronized state, which is necessary for the stable operation of power grids and the control of unstable synchronous states. We demonstrate by numerical simulations that unstable frequency-synchronized states can be stabilized by feedback control. Further, we extend our study to include stochastic temporal power fluctuations and discuss the interplay of topological disorder and Gaussian white noise for various model configurations and finally demonstrate that our control scheme also works well under the influence of noise. Results for synthetic Erdös–Renyi random networks with low average connectivity and with symmetric or asymmetric bimodal frequency distributions are compared with those obtained by considering a real power grid topology, namely, the grid of Italy. [ABSTRACT FROM AUTHOR]

In this work, we compare the performance of an hydrological model when driven by probabilistic rain forecast derived from two different post-processing techniques. The region of interest is Piemonte, northwestern Italy, a complex orography area close to the Mediterranean Sea where the forecast are often a challenge for weather models. The May 2008 flood is here used as a case study, and the very dense weather station network allows us for a very good description of the event and initialization of the hydrological model. The ensemble probabilistic forecasts of the rainfall fields are obtained with the Bayesian model averaging, with the classical poor man ensemble approach and with a new technique, the Multimodel SuperEnsemble Dressing. In this case study, the meteo-hydrological chain initialized with the Multimodel SuperEnsemble Dressing is able to provide more valuable discharge ranges with respect to the one initialized with Bayesian model averaging multi-model. [ABSTRACT FROM AUTHOR]