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The complexity of interaction patterns among individuals in social systems plays a fundamental role on the inception and spreading of epidemic outbreaks. Empirical evidence has shown that the network of social interactions may co-evolve with the spread of the disease at comparable time-scales. Time-varying features have also been documented in the study of the propensity of individuals toward social activity, leading to the emergence of burstiness and temporal clustering. These temporal network dynamics are not independent of the disease evolution, whereby infected individuals could experience changes in their tendency to form connections, spontaneously or due to exogenous control policies. Neglecting these phenomena in modeling epidemics could lead to dangerous mispredictions of an outbreak and ineffective control interventions. In this paper, we propose a mathematically tractable modeling framework that relies on a limited number of parameters and encapsulates all these instances of complex phenomena through the lens of activity driven networks. Hawkes processes, Markov chains, and stability theory are leveraged to assist in the analysis of the framework and the formulation of theory-based control interventions. Our mathematical findings confirm the intuition that bursty activity patterns, typical of humans, facilitate epidemic spreading, while behavioral changes aiming at individual isolation could accelerate the eradication of epidemics. The proposed tools are demonstrated on a real-world case of influenza spreading in Italy. Overall, this work contributes new insight into the theory of temporal networks, laying the foundations for the analysis and control of spreading processes over networks with complex interaction patterns. [ABSTRACT FROM AUTHOR]

This paper deals with the rocking and sliding behavior of a monolithic stone block or a system of stone blocks under earthquakes, a problem commonly observed for ancient temples in Greece and Southern Italy. The analysis for the above monolithic or multi-drum columns is conducted by a simple process based on generally accepted simplifications. The effects of column geometry, earthquake characteristics and restitution ratio due to impact are also studied herein. Furthermore, an analytical approach for the solution of the complete nonlinear equations of motion (including the one for the vertical earthquake excitation) for the subject considered is proposed. Finally, characteristic representative examples are presented with useful conclusions drawn. It was found that the stability criteria based on static conditions are reliable, while the corresponding dynamic criteria may lead to erroneous results. [ABSTRACT FROM AUTHOR]

• Irrigation detection is investigated through remote sensing soil moisture. • Diagnostic indices derived by the temporal stability theory are used. • High-resolution (100 m) maps of irrigated areas are produced through the k -means algorithm. • The spatial matching between the irrigation extent and the data resolution is crucial. Despite a detailed knowledge of the spatial-temporal dynamics of irrigation being necessary to optimize the agricultural production without exacerbating the pressure exercised on the water resource, such information is still often lacking worldwide. In this study, a double-scale analysis on the detectability of the irrigation occurrence over an area in central Italy through remote sensing soil moisture is proposed; the period of interest is a 3-year time span from 2017 to 2019. The detectability of district- or sub-district-scale irrigation signals through remotely sensed soil moisture data is investigated at two different spatial resolutions: 1 km and plot scale. Three soil moisture products sampled at 1 km resolution are evaluated: a DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled version of SMAP (Soil Moisture Active Passive) and two Sentinel-1-derived products, namely the 1 km version delivered by Copernicus and a plot-scale-born version developed by THEIA and aggregated at 1 km. The THEIA Sentinel-1 product aggregated at 100 m is used in the plot-scale analysis. Over the study area, the irrigation extent is determined by the fragmentation of the agricultural fields and the complex topography, making the adoption of plot-scale data necessary. Satisfactory results are obtained by comparing maps of irrigated areas at 100 m spatial resolution produced through the k -means clustering algorithm with ground-truth data, since the method fails only once out of seven in properly reproducing the irrigated or non-irrigated conditions occurred over four pilot agricultural fields. [Display omitted] [ABSTRACT FROM AUTHOR]

In the present paper a review of some mathematical models for the ecological evaluation of environmental systems is considered. Moreover a new model, capable to furnish more detailed information at the level of landscape units, is proposed. Numerical tests are then performed for a case study in the province of Viterbo (central Italy). [ABSTRACT FROM AUTHOR]

Abstract: Phase I of GERDA, aimed at investigating neutrino-less double beta decay of 76Ge is in the active phase since November 2011 at the Gran Sasso National Laboratory of INFN—Italy. GERDA Ge detectors are non-encapsulated and operate immersed in liquid argon, equipped with a front-end readout electronics consisting of cryogenic charge sensitive preamplifiers designed and manufactured to cope with the characteristics of the GERDA experiment (radio-purity, long and resistive cables, etc.). The presentation will report on the current status of the GERDA experiment phase I, focusing on Ge detectors performance in terms of energy resolution, stability over time, counting rate and related issues. [Copyright &y& Elsevier]