1,721,003 research outputs found
Cambiamenti climatici a livello locale: stima economica del danno da alluvioni sul sistema delle infrastrutture lombarde
No full textA comparative analysis of link removal strategies in real complex weighted networks
Full text linkIn this report we offer the widest comparison of links removal (attack) strategies efficacy in impairing the robustness of six real-world complex weighted networks. We test eleven different link removal strategies by computing their impact on network robustness by means of using three different measures, i.e. the largest connected cluster (LCC), the efficiency (Eff) and the total flow (TF). We find that, in most of cases, the removal strategy based on the binary betweenness centrality of the links is the most efficient to disrupt the LCC. The link removal strategies based on binary-topological network features are less efficient in decreasing the weighted measures of the network robustness (e.g. Eff and TF). Removing highest weight links first is the best strategy to decrease the efficiency (Eff) in most of the networks. Last, we found that the removal of a very small fraction of links connecting higher strength nodes or of highest weight does not affect the LCC but it determines a rapid collapse of the network efficiency Eff and the total flow TF. This last outcome raises the importance of both to adopt weighted measures of network robustness and to focus the analyses on network response to few link removals
The heterogeneity in link weights may decrease the robustness of real-world complex weighted networks
Full text linkHere we report a comprehensive analysis of the robustness of seven high-quality real-world complex weighted networks to errors and attacks toward nodes and links. We use measures of the network damage conceived for a binary (e.g. largest connected cluster LCC, and binary efficiency Effbin) or a weighted network structure (e.g. the efficiency Eff, and the total flow TF). We find that removing a very small fraction of nodes and links with respectively higher strength and weight triggers an abrupt collapse of the weighted functioning measures while measures that evaluate the binary-topological connectedness are almost unaffected. These findings unveil a problematic response-state where the attack toward a small fraction of nodes-links returns the real-world complex networks in a connected but inefficient state. Our findings unveil how the robustness may be overestimated when focusing on the connectedness of the components only. Last, to understand how the networks robustness is affected by link weights heterogeneity, we randomly assign link weights over the topological structure of the real-world networks and we find that highly heterogeneous networks show a faster efficiency decrease under nodes-links removal: i.e. the robustness of the real-world complex networks against nodes-links removal is negatively correlated with link weights heterogeneity
L’ANGUILLA EUROPEA NEL BACINO IDROGRAFICO MARTA-BOLSENA VALUTAZIONI PRELIMINARI DI COLONIZZAZIONE ED EMIGRAZIONE AI FINI DELLA GESTIONE PER LA SALVAGUARDIA DELLA BIODIVERSITÁ.
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Shifts in the thermal niche of fruit trees under climate change: The case of peach cultivation in France
No full textClimate influences plant phenological traits, thus playing a key role in defining the geographical range of crops. Foreseeing the impact of climate change on fruit trees is essential to inform policy decisions to guide the adaptation to new climatic conditions. To this end, we propose and use a phenological process-based model to assess the impacts of climate change upon the phenology, the suitability and the distribution of economically important cultivars of peach (Prunus persica), across the entire continental France. The model combines temperature dependent sub-models of dormancy, blooming, fruit survival and ripening, using chilling units, forcing units, frost occurrence and growing degree days, respectively. We find that climate change could have divergent impacts on peach production. On the one hand, blooming would occur earlier, warmer temperatures would decrease spring frost occurrence and fruit ripening would be easily achieved before the start of fall. On the other hand, milder winters would impede the plant buds from breaking endodormancy, with consequent abnormal patterns of fruit development or even blooming failure. This latter impact would dramatically shift the geographic range of sites where peach production will be profitable. This shift would mainly be from the south of France (Languedoc-Roussillon, Rhône-Alpes and Provence-Alpes-Côte d'Azur), to northwestern areas where the winter chilling requirement would still be fulfilled. Our study provides novel insights for understanding and forecasting climate change impacts on peach phenology and it is the first framework that maps the ecological thermal niche of peach at a national level
Modeling the Consequences of Social Distancing Over Epidemics Spreading in Complex Social Networks: From Link Removal Analysis to SARS-CoV-2 Prevention
Full text linkIn this perspective, we describe how the link removal (LR) analysis in social complex networks may be a promising tool to model non-pharmaceutical interventions (NPIs) and social distancing to prevent epidemics spreading. First, we show how the extent of the epidemic spreading and NPIs effectiveness over complex social networks may be evaluated with a static indicator, that is, the classic largest connected component (LCC). Then we explain how coupling the LR analysis and type SIR epidemiological models (EM) provide further information by including the temporal dynamics of the epidemic spreading. This is a promising approach to investigate important aspects of the recent NPIs applied by government to contain SARS-CoV-2, such as modeling the effect of the social distancing severity and timing over different network topologies. Further, implementing different link removal strategies to halt epidemics spreading provides information to individuate more effective NPIs, representing an important tool to offer a rationale sustaining policies to prevent SARS-CoV-2 and similar epidemics
Link and Node Removal in Real Social Networks: A Review
Full text linkWe review the main results from the literature on the consequences of link and node removal in real social networks. We restrict our review to only those works that adopted the two most common measures of network robustness, i.e., the largest connected component (LCC) and network efficiency (Eff). We consider both binary and weighted network approaches. We show that the study of the response of social networks subjected to link/node removal turns out to be extremely useful for managing a number of real problems. For instance, we show that the consequences of the imposition of social distancing in many states to control the spread of COVID-19 could be analyzed within the framework of social network analysis. Our mini-review outlines that in social networks, it is necessary to consider the weight of links between persons to perform reliable analyses. Finally, we propose promising lines for future research in social network science
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
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