@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}
}
@article {276,
	title = {Measuring objective and subjective well-being: dimensions and data sources},
	journal = {International Journal of Data Science and Analytics (JDSA)},
	year = {2020},
	abstract = {Well-being is an important value for people{\textquoteright}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.},
	doi = {https://doi.org/10.1007/s41060-020-00224-2},
	author = {Vasiliki Voukelatou and Gabrielli, Lorenzo and Miliou, Ioanna and Cresci, Stefano and Sharma, Rajesh and Tesconi, Maurizio and Pappalardo, Luca}
}
@article {253,
	title = {Maximum entropy approach to link prediction in bipartite networks},
	journal = {arXiv preprint arXiv:1805.04307},
	year = {2018},
	author = {Baltakiene, M and Baltakys, K and Cardamone, D and Parisi, F and Tommaso Radicioni and Torricelli, M and de Jeude, JA and Saracco, F}
}
@article {258,
	title = {Models and Logs used in the paper {\textquoteleft}Aligning Partially-Ordered Process-Execution Traces and Models Using Automated Planning{\textquoteright} accepted for ICAPS 2018},
	year = {2018},
	publisher = {TU Eindhoven},
	keywords = {Computation Theory and Mathematics, Event Logs, Petri nets},
	doi = {10.4121/UUID:A02AFEC8-B7C7-42B7-8DFF-36D3DE3032BE},
	url = {https://data.4tu.nl/repository/uuid:a02afec8-b7c7-42b7-8dff-36d3de3032be},
	author = {Giacomo Lanciano and Massimiliano de Leoni}
}
