In the frame of SAFENUT AGRI GEN RES Action, which was a European strategy for the recovery, characterization and conservation of genetic resources, the fatty acids and the tocopherol profiles of a set of 75 hazelnut accessions were analyzed. The aim of this study was to assess the genetic differences among the European germplasm, contributing to the definition of nut quality in traditional European areas of cultivation. Significant differences were found between accessions for oil amount and contents of most fatty acids. As expected, monounsaturated fatty acids made up the largest portion (mean 80.85 %) followed by polyunsaturated fatty acids (10.70 %). The saturated ones were the minor components and accounted for only 8.43 % of the total fatty acids. On the basis of Student's test, significant differences between the 2 years of harvest were found for fatty acid content, except for linoleic acid, the ratio of polyunsaturated, a-tocopherol and the stability index. When the oil content was studied in cultivars from the same site of cultivation, the mean values of the genetic pools from central Italy (60.8 %), Slovenia (59.3 %) and Portugal (58.2 %) showed highest values than those of cultivars grown in Greece (56.8 %), Spain (55.9 %) and France (51.5 %). A chemometric approach based on principal component and clustering analyses was developed to identify the most interesting cultivars for breeding programs.

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When considering a mixed probability measure on [0, 1] with atoms in zero and one, the frontier points have to be treated (and "weighted") differently and separately with respect to the interior points. In order to avoid the troublesome consequences of a mixed model, an easily interpretable discretization of [0, 1] on uniformly spaced atoms is here proposed. This "homogeneous support" is used to define two discrete models, a parametric and a nonparametric one. An application to real data on recovery risk of the Bank of Italy's loans is here considered to exemplify both discretization and proposed models. Finally, a simulation study is performed to analyze the behavior of the nonparametric proposal in terms of goodness-of-fit.

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Remote working is increasingly seen as an effective model in several countries in the last decade, mainly thanks to the development of information and communication technologies in support of common daily working tasks. The emergence of the COVID-19 pandemic has represented a pivotal moment for the adoption of remote working in multiple sectors, with positive effects on the environmental impacts caused by the daily commuting of workers. However, due to the fact that pandemic-induced remote working has represented a major forced experiment on a global scale, and that it has often been imposed rather than chosen by employees, workers’ well-being has not always been ensured. This research work presents an analysis of a wide survey of remote workers in public administrations in four different provinces in Italy, with the aim of assessing the main characteristics of the users and the related environmental benefits. Survey data refer to remote workers before COVID-19, thus representing workers who have freely chosen to work from home for different reasons. The results of this work represent a useful tool with which to support the definition of new remote work strategies that could help policy makers reduce a part of the systematic mobility demand. We have also calculated average energy and emission savings to provide useful indicators for a preliminary estimation of the potential environmental benefits of remote working. Considering the entire sample of respondents, workers who would have commuted at least partially by car have saved on average 6 kg of CO2 per day thanks to remote working (with an average round-trip commuting distance of approximately 35 km). The current results will be supplemented by the results of a new survey underway, aimed at evaluating the differences of remote working experiences during the emergency response to COVID-19.