1,721,446 research outputs found
Utilizzo di tecniche di machine learning e previsioni stagionali per la stima dei volumi di invaso
No full textSmoothing spatio-temporal data with complex missing data patterns
Full text linkWe consider spatio-temporal data and functional data with spatial dependence, characterized by complicated missing data patterns. We propose a new method capable to efficiently handle these data structures, including the case where data are missing over large portions of the spatio-temporal domain. The method is based on regression with partial differential equation regularization. The proposed model can accurately deal with data scattered over domains with irregular shapes and can accurately estimate fields exhibiting complicated local features. We demonstrate the consistency and asymptotic normality of the estimators. Moreover, we illustrate the good performances of the method in simulations studies, considering different missing data scenarios, from sparse data to more challenging scenarios where the data are missing over large portions of the spatial and temporal domains and the missing data are clustered in space and/or in time. The proposed method is compared to competing techniques, considering predictive accuracy and uncertainty quantification measures. Finally, we show an application to the analysis of lake surface water temperature data, that further illustrates the ability of the method to handle data featuring complicated patterns of missingness and highlights its potentiality for environmental studies
Analysis of high-resolution rain records in FVG, northeastern Italy
Full text linkThe Friuli Venezia Giulia (FVG) region, northeastern Italy, records the heaviest precipitation annual totals of the country. The region counts on a dense ground-station network constituted by 2 main rain-gauges networks, whose sampling frequency has been progressively increased from 60 up to 1min step. In this work, we propose a comprehensive analysis of the available dataset of continuous series at high temporal resolution (i.e. 60, 30, 5 and 1min) to verify whether trends in very short rainfalls are underway. We adopt the quantile regression (QR) method which allows to detect changes in the tails of the rainfall distributions and to screen the whole rainfall time series. At this aim, we first introduce a method to check and correct the continuous series by removing the suspicious outliers, based on references values. Significant increasing trends at 5% of significant level have been detected on some of the analysed stations. Copyright
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Analisi della relazione fra estremi di precipitazione sub-oraria e temperatura superficiale in Sicilia
Full text linkLa temperatura atmosferica influenza fortemente la precipitazione, in quanto l'aria più calda è in grado di contenere, sotto forma di vapore, più acqua rispetto all'aria più fredda e quindi ha un potenziale maggiore in termini di acqua disponibile per eventuali eventi meteorici. L’equazione termodinamica di Clausius-Clapeyron (CC) descrive la relazione tra pressione di vapore saturo e temperatura assoluta dell’aria. Considerando solo la zona superficiale dell’atmosfera a contatto con il suolo, in cui la pressione di vapore è pressoché costante e nell’ordine dell’1% della pressione assoluta, si può ipotizzare che l’umidità dell’aria cresca esponenzialmente con la temperatura secondo un tasso (CC-rate) pari a quello derivabile dall’equazione CC, cioè pari a circa il 7% per °C per temperature prossime a 0°C e 6%°C-1 per temperature superiori ai 24°C.
Nell’ultimo decennio, la comunità scientifica ha dedicato grande attenzione alla verifica dell’esistenza di tale tipo di relazione in varie parti del mondo e all’analisi del rate e dei fattori che lo influenzano. Lenderink e van Meijgaard (2008) sono tra i pionieri di tale ricerca, avendo condotto un’analisi nei Paesi Bassi su un database di precipitazioni massime orarie con intensità sopra un determinato percentile e corrispondente temperatura superficiale. La stessa metodologia, con opportune varianti, è stata utilizzata in altri studi in varie regioni del mondo, dall’Europa (Lenderink and Van Meijgaard, 2008; Berg and Haerter, 2013; Berg et al., 2013; Loriaux et al., 2013; Blenkinsop et al., 2015) all’Oceania (Hardwick-Jones et al., 2010), dal Nord America (Shaw et al., 2011; Mishra et al., 2012b) all’Asia (Utsumi et al., 2011; Yu and Li, 2012). Dai vari studi emerge che la relazione tra temperature e precipitazioni estreme osservate non sempre è caratterizzabile dal tasso teorico (CC-rate), mostrando talvolta valori significativamente diversi, sia superiori (super-CC) che inferiori (sub-CC).
Studi di questo tipo in regioni aride e semi-aride sono piuttosto limitati in letteratura; pertanto, l’obiettivo di questo lavoro è di valutare lo scaling-rate tra temperatura giornaliera e precipitazioni estreme (sia sub-orarie che orarie) in una regione semi-arida come la Sicilia (Italia)
On the Leonardo's rule for the assessment of root profile
No full textLeonardo's rule (Lrule) applied to below-ground systems defines a simple topological scheme that describes how the branches of root architectures develop within the soil. The approach does not consider the soil-climate-root interactions. From another hand, eco-hydrological approaches exploit physically-based formulations to derive the dynamic evolution of root profile based on soil and climate characteristics. In homogenous soil and simplified hydrological conditions, analytical solutions can be derived, as demonstrated by Laio's model, who proposed a simple exponential formulation to derive the Root Area (AR) profile. Apart from Laio's model, more generalized functions, i.e. derived by two and three parameters gamma distribution or others, can be efficiently used to derive the AR profile. This communication proposes a combination of the Lrule and eco-hydrological approaches to derive the AR profile, at given soil and climate conditions, allowing to identify a physical and theoretical meaning of the Lrule's parameters. A comprehensive root dataset from field measurements carried out in the region of Tuscany (Italy) is used. Results demonstrate that values of Lrule's parameters derived throughout the proposed mathematical relationships tend to constant values in case of exponential function, which is valid for homogenous soils. Moreover, in a realistic vegetated soil, where top-soil is different than deep-soil, functions derived from a two and three parameters gamma distribution may reproduce better root data observations
A roughness penalty approach to estimate densities over two-dimensional manifolds
Full text linkAn innovative nonparametric method for density estimation over general two-dimensional
Riemannian manifolds is proposed. The method follows a functional data analysis approach,
combining maximum likelihood estimation with a roughness penalty that involves a
differential operator appropriately defined over the manifold domain, thus controlling the
smoothness of the estimate. The proposed method can accurately handle point pattern
data over complicated curved domains. Moreover, it is able to capture complex multimodal
signals, with strongly localized and highly skewed modes, with varying directions and
intensity of anisotropy. The estimation procedure exploits a discretization in finite element
bases, enabling great flexibility on the spatial domain. The method is tested through
simulation studies, showing the strengths of the proposed approach. Finally, the density
estimation method is illustrated with an application to the distribution of earthquakes in
the world
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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