TY - JOUR T1 - Drivers of change in biodiversity and ecosystem services in the Cantareira System Protected Area : A prospective analysis of the implementation of public policies JF - Biota Neotropica Y1 - 2020 A1 - Viviane Dib A1 - Marco Aurélio Nalon A1 - Nino Tavares Amazonas A1 - Cristina Yuri Vidal A1 - Iván A. Ortiz-Rodríguez A1 - Jan Daněk A1 - Maíra Formis de Oliveira A1 - Paola Alberti A1 - Rafaela Aparecida da Silva A1 - Raíza Salomão Precinoto A1 - Taciana Figueiredo Gomes KW - Biodiversity KW - Cantareira System Protected Area KW - Ecosystem services KW - GLOBIO KW - InVEST KW - Modeling KW - Scenarios AB - The lack of implementation of well-designed public policies aimed at the conservation of natural ecosystems has resulted, at a global level, in the decline of ecosystem functioning and, consequently, of the contributions they make to people. The poor enforcement of important environmental legislation in Brazil - for instance, the “Atlantic Forest Law” (Law n.11.428/2006) and the “Forest Code” (Law n.12.651/2012) - could compromise the overall maintenance of ecosystems and the services they provide. To explore the implications of different levels of federal laws’ enforcement within the Cantareira System Protected Area (PA) - a PA in southeastern Brazil that provides fresh water for 47% of the Sao Paulo Metropolitan Area -, we developed a conceptual framework to identify indirect and direct drives of biodiversity and ecosystem changes. We also projected four land-use scenarios to 2050 to test the effects of deforestation control and forest restoration practices on biodiversity and ecosystem services maintenance: the “business-as-usual” scenario (BAU), which assumes that all trends in land-use cover changes observed in the past will continue in the future, and three alternative exploratory scenarios considering the Atlantic Forest Law implementation, the partial implementation of the Forest Code and the full implementation of the Forest Code. Using the land-use maps generated for each scenario, we assessed the impacts of land-use changes on biodiversity conservation and soil retention. Our results revealed all alternative scenarios could increase biodiversity conservation (by 7%; 12%; and 12%, respectively), reduce soil loss (by 24.70%; 34.70%; and 38.12%, respectively) and sediment exportation to water (by 27.47%; 55.06%; and 59.28%, respectively), when compared to the BAU scenario. Our findings highlight the importance of restoring and conserving native vegetation for the maintenance and improvement of biodiversity conservation and for the provision of ecosystem services. VL - 20 UR - https://www.scielo.br/scielo.php?script=sci_arttext&pid=S1676-06032020000500201 IS - 1 ER - TY - JOUR T1 - Measuring objective and subjective well-being: dimensions and data sources JF - International Journal of Data Science and Analytics (JDSA) Y1 - 2020 A1 - Vasiliki Voukelatou A1 - Gabrielli, Lorenzo A1 - Miliou, Ioanna A1 - Cresci, Stefano A1 - Sharma, Rajesh A1 - Tesconi, Maurizio A1 - Pappalardo, Luca AB - Well-being is an important value for people’s lives, and it could be considered as an index of societal progress. Researchers have suggested two main approaches for the overall measurement of well-being, the objective and the subjective well-being. Both approaches, as well as their relevant dimensions, have been traditionally captured with surveys. During the last decades, new data sources have been suggested as an alternative or complement to traditional data. This paper aims to present the theoretical background of well-being, by distinguishing between objective and subjective approaches, their relevant dimensions, the new data sources used for their measurement and relevant studies. We also intend to shed light on still barely unexplored dimensions and data sources that could potentially contribute as a key for public policing and social development. ER - TY - JOUR T1 - Self-supervised pre-training of CNNs for flatness defect classification in the steelworks industry JF - International Journal of Advances in Intelligent Informatics Y1 - 2020 A1 - Filippo Galli A1 - Antonio Ritacco A1 - Giacomo Lanciano A1 - Marco Vannocci A1 - Valentina Colla A1 - Marco Vannucci KW - CNN KW - Deep learning KW - Self-supervision KW - Steelworks AB - Classification of surface defects in the steelworks industry plays a significant role in guaranteeing the quality of the products. From an industrial point of view, a serious concern is represented by the hot-rolled products shape defects and particularly those concerning the strip flatness. Flatness defects are typically divided into four sub-classes depending on which part of the strip is affected and the corresponding shape. In the context of this research, the primary objective is evaluating the improvements of exploiting the self-supervised learning paradigm for defects classification, taking advantage of unlabelled, real, steel strip flatness maps. Different pre-training methods are compared, as well as architectures, taking advantage of well-established neural subnetworks, such as Residual and Inception modules. A systematic approach in evaluating the different performances guarantees a formal verification of the self-supervised pre-training paradigms evaluated hereafter. In particular, pre-training neural networks with the EgoMotion meta-algorithm shows classification improvements over the AutoEncoder technique, which in turn is better performing than a Glorot weight initialization. VL - 6 UR - http://ijain.org/index.php/IJAIN/article/view/410 ER - TY - CONF T1 - SOM-Based Behavioral Analysis for Virtualized Network Functions T2 - Proceedings of the 35th Annual ACM Symposium on Applied Computing Y1 - 2020 A1 - Giacomo Lanciano A1 - Antonio Ritacco A1 - Tommaso Cucinotta A1 - Marco Vannucci A1 - Antonino Artale A1 - Luca Basili A1 - Enrica Sposato A1 - Joao Barata KW - machine learning KW - network function virtualization KW - self-organizing maps AB - In this paper, we propose a mechanism based on Self-Organizing Maps for analyzing the resource consumption behaviors and detecting possible anomalies in data centers for Network Function Virtualization (NFV). Our approach is based on a joint analysis of two historical data sets available through two separate monitoring systems: system-level metrics for the physical and virtual machines obtained from the monitoring infrastructure, and application-level metrics available from the individual virtualized network functions. Experimental results, obtained by processing real data from one of the NFV data centers of the Vodafone network operator, highlight some of the capabilities of our system to identify interesting points in space and time of the evolution of the monitored infrastructure. JF - Proceedings of the 35th Annual ACM Symposium on Applied Computing PB - Association for Computing Machinery CY - New York, NY, USA SN - 9781450368667 UR - https://doi.org/10.1145/3341105.3374110 ER - TY - JOUR T1 - Spatiotemporal effects of Hurricane Ivan on an endemic epiphytic orchid: 10 years of follow-up JF - Plant Ecology & Diversity Y1 - 2020 A1 - Iván A. Ortiz-Rodríguez A1 - Jose Raventós A1 - Ernesto Mújica A1 - Elaine González-Hernández A1 - Ernesto Vega-Peña A1 - Pilar Ortega-Larrocea A1 - Andreu Bonet A1 - Cory Merow KW - Caribbean KW - cyclones KW - integral projection models KW - management strategies KW - plant population dynamics KW - stochastic growth rate KW - transfer functions KW - transient behaviour AB - Background: Hurricanes have a strong influence on the ecological dynamics and structure of tropical forests. Orchid populations are especially vulnerable to these perturbations due to their canopy exposure and lack of underground storage organs and seed banks. Aims: We evaluated the effects of Hurricane Ivan on the population of the endemic epiphytic orchid Encyclia bocourtii to propose a management strategy. Methods: Using a pre- and post-hurricane dataset (2003–2013), we assessed the population asymptotic and transient dynamics. We also identified the individual size-stages that maximise population inertia and E. bocourtii’s spatial arrangement relative to phorophytes and other epiphytes. Results: Hurricane Ivan severely affected the survival and growth of individuals of E. bocourtii, and caused an immediate decline of the population growth rate from λ = 1.05 to λ = 0.32, which was buffered by a population reactivity of ρ1 = 1.42. Our stochastic model predicted an annual population decrease of 14%. We found an aggregated spatial pattern between E. bocourtii and its host trees, and a random pattern relative to other epiphytes. Conclusion: Our findings suggest that E. bocourtii is not safe from local extinction. We propose the propagation and reintroduction of reproductive specimens, the relocation of surviving individuals, and the establishment of new plantations of phorophytes. VL - 13, 2020 UR - https://www.tandfonline.com/doi/full/10.1080/17550874.2019.1673495 IS - 1 ER - TY - CONF T1 - Is this Sentence Difficult? Do you Agree? T2 - Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing Y1 - 2018 A1 - Brunato, Dominique A1 - De Mattei, Lorenzo A1 - Dell’Orletta, Felice A1 - Iavarone, Benedetta A1 - Venturi, Giulia JF - Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing ER -