@proceedings {1091,
	title = {Quantile Regression Forest for Value-at-Risk Forecasting Via Mixed-Frequency Data},
	year = {2022},
	publisher = {Springer, Cham},
	doi = {https://doi.org/10.1007/978-3-030-99638-3},
	author = {Mila Andreani and Candila, Vincenzo and Petrella, Lea}
}
@article {300,
	title = {Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach},
	journal = {Risks},
	volume = {9},
	year = {2021},
	pages = {144},
	issn = {2227-9091},
	doi = {10.3390/risks9080144},
	url = {https://www.mdpi.com/2227-9091/9/8/144},
	author = {Mila Andreani and Candila, Vincenzo and Morelli, Giacomo and Petrella, Lea}
}
@proceedings {299,
	title = {Quantile Regression Forest with mixed-frequency data},
	volume = {Book of Short Papers SIS 2021},
	year = {2021},
	month = {06/2021},
	publisher = {Pearson},
	issn = {9788891927361},
	url = {https://it.pearson.com//docenti/universita/partnership/sis.html},
	author = {Mila Andreani and Vincenzo Candila and Lea Petrella}
}
@article {271,
	title = {Drivers of change in biodiversity and ecosystem services in the Cantareira System Protected Area : A prospective analysis of the implementation of public policies},
	journal = {Biota Neotropica},
	volume = {20},
	year = {2020},
	month = {05/2020},
	type = {Article},
	abstract = {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 {\textquotedblleft}Atlantic Forest Law{\textquotedblright} (Law n.11.428/2006) and the {\textquotedblleft}Forest Code{\textquotedblright} (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{\textquoteright} 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 {\textquotedblleft}business-as-usual{\textquotedblright} 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.},
	keywords = {Biodiversity, Cantareira System Protected Area, Ecosystem services, GLOBIO, InVEST, Modeling, Scenarios},
	issn = {1676-0611},
	doi = {https://doi.org/10.1590/1676-0611-bn-2019-0915 },
	url = {https://www.scielo.br/scielo.php?script=sci_arttext\&pid=S1676-06032020000500201},
	author = {Viviane Dib and Marco Aur{\'e}lio Nalon and Nino Tavares Amazonas and Cristina Yuri Vidal and Iv{\'a}n A. Ortiz-Rodr{\'\i}guez and Jan Dan{\v e}k and Ma{\'\i}ra Formis de Oliveira and Paola Alberti and Rafaela Aparecida da Silva and Ra{\'\i}za Salom{\~a}o Precinoto and Taciana Figueiredo Gomes}
}
@proceedings {288,
	title = {Dynamic Quantile Regression Forest},
	volume = {Book of Short Papers SIS 2020},
	year = {2020},
	month = {10/2020},
	publisher = {Pearson},
	issn = {9788891910776},
	url = {https://it.pearson.com/content/dam/region-core/italy/pearson-italy/pdf/Docenti/Universit\%C3\%A0/Pearson-SIS-2020-atti-convegno.pdf},
	author = {Mila Andreani and Lea Petrella}
}
@article {264,
	title = {Human migration: the big data perspective},
	journal = {International Journal of Data Science and Analytics},
	year = {2020},
	pages = {1{\textendash}20},
	abstract = {How can big data help to understand the migration phenomenon? In this paper, we try to answer this question through an analysis of various phases of migration, comparing traditional and novel data sources and models at each phase. We concentrate on three phases of migration, at each phase describing the state of the art and recent developments and ideas. The first phase includes the journey, and we study migration flows and stocks, providing examples where big data can have an impact. The second phase discusses the stay, i.e. migrant integration in the destination country. We explore various data sets and models that can be used to quantify and understand migrant integration, with the final aim of providing the basis for the construction of a novel multi-level integration index. The last phase is related to the effects of migration on the source countries and the return of migrants.},
	author = {Alina Sirbu and Andrienko, Gennady and Andrienko, Natalia and Boldrini, Chiara and Conti, Marco and Giannotti, Fosca and Guidotti, Riccardo and Bertoli, Simone and Jisu Kim and Muntean, Cristina Ioana and others}
}
@conference {259,
	title = {SOM-Based Behavioral Analysis for Virtualized Network Functions},
	booktitle = {Proceedings of the 35th Annual ACM Symposium on Applied Computing},
	year = {2020},
	publisher = {Association for Computing Machinery},
	organization = {Association for Computing Machinery},
	address = {New York, NY, USA},
	abstract = {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.},
	keywords = {machine learning, network function virtualization, self-organizing maps},
	isbn = {9781450368667},
	doi = {10.1145/3341105.3374110},
	url = {https://doi.org/10.1145/3341105.3374110},
	author = {Giacomo Lanciano and Antonio Ritacco and Tommaso Cucinotta and Marco Vannucci and Antonino Artale and Luca Basili and Enrica Sposato and Joao Barata}
}
@article {251,
	title = {The calorimeter of the Mu2e experiment at Fermilab},
	journal = {Journal of Instrumentation},
	volume = {12},
	year = {2017},
	abstract = {The Mu2e experiment at Fermilab looks for Charged Lepton Flavor Violation (CLFV) improving by 4 orders of magnitude the current experimental sensitivity for the muon to electron conversion in a muonic atom. A positive signal could not be explained in the framework of the current Standard Model of particle interactions and therefore would be a clear indication of new physics. In 3 years of data taking, Mu2e is expected to observe less than one background event mimicking the electron coming from muon conversion. Achieving such a level of background suppression requires a deep knowledge of the experimental apparatus: a straw tube tracker, measuring the electron momentum and time, a cosmic ray veto system rejecting most of cosmic ray background and a pure CsI crystal calorimeter, that will measure time of flight, energy and impact position of the converted electron. The calorimeter has to operate in a harsh radiation environment, in a 10-4 Torr vacuum and inside a 1 T magnetic field. The results of the first qualification tests of the calorimeter components are reported together with the energy and time performances expected from the simulation and measured in beam tests of a small scale prototype.},
	doi = {10.1088/1748-0221/12/01/c01061},
	url = {https://doi.org/10.1088\%2F1748-0221\%2F12\%2F01\%2Fc01061},
	author = {N. Atanov and V. Baranov and J. Budagov and F. Cervelli and F. Colao and M. Cordelli and G. Corradi and E. Dan{\'e} and Y.I. Davydov and S. Di Falco and E. Diociaiuti and S. Donati and R. Donghia and B. Echenard and K. Flood and S. Giovannella and V. Glagolev and F. Grancagnolo and F. Happacher and D.G. Hitlin and M. Martini and S. Miscetti and T. Miyashita and L. Morescalchi and P. Murat and G. Pezzullo and F. Porter and F. Raffaelli and Tommaso Radicioni and M. Ricci and A. Saputi and I. Sarra and F. Spinella and G. Tassielli and V. Tereshchenko and Z. Usubov and R.Y. Zhu}
}
