Landrace added value and accessibility in Europe: what a collection of case studies tells us

In the actual climate change scenario, in situ conservation of plant genetic resources for food and agriculture can significantly contribute broadening the diversity of our food system as well as increasing its resilience; nevertheless, landrace cultivation has been dramatically reduced in the last decades all over Europe. One of the most effective approaches to counteract the loss of landrace diversity in situ is facilitating its use. Aims of this study were to (i) describe how in situ maintenance of landraces occurs in different agro-environmental conditions in Europe and (ii) identify the main factors influencing landrace added values and accessibility as means to increase their adoption by new farmers. To the purpose, a collection of 95 case studies of both garden and open field landraces maintained in situ was analysed. A first description was obtained by classifying the information into 18 purposely defined categories. Data on landraces added values and accessibility were further transformed into weighted variables; the derived quantitative scores were then used as dependent variables in univariate and multivariate analyses. Results showed that farmers alone are still the main actors maintaining landraces in situ across different European biogeographical regions, mainly carrying out their activity under organic or low-input conditions, often in marginal areas. Results of the multivariate analysis showed that (i) type of actor involved in the multiplication, (ii) the main use of the product and (iii) presence of promotion actions significantly affect garden landraces added value and accessibility; presence of promotion actions was the only factor affecting added value of open field entries. Evidence arising from this work can contribute to the establishment of a fruitful ground of discussion for future European policies and strategies to protect and increase landrace use

Prevalence of COVID 19 like symptoms in Italy and Lombardy, March-April 2020, and their implications on cancer prevention, diagnosis and management

Two population-based surveys on coronavirus disease-2019 (Covid-19)-like symptoms were conducted by BVA-Doxa on representative samples of the general population from Italy and its largest region, Lombardy, with over 10 million inhabitants and heavily struck by Covid-19, on 27-30 March and 3-7 April, on a total of 2000 individuals - 353 from Lombardy. Overall, 14.2% of Italians - and 19.6% in Lombardy - reported Covid-19-like symptoms. The estimated prevalence was higher in the young, in smokers, and in Lombardy over the period 20 March to 7 April. Although the influenza season was ended by mid-March, at least part of the symptoms may be not Covid-19 related. Even assuming that only half are, at least 7% of Italians and 10% in Lombardy had been affected by Covid-19. To these, asymptomatic or paucisymptomatic cases have to be added. These estimates are at least one or two orders of magnitude larger than official registered cases. This has major implications for cancer prevention, management and treatment

The LAUE project for broadband gamma-ray focusing lenses

We present the LAUE project devoted to develop an advanced technology for building a high focal length Laue lens for soft gamma--ray astronomy (80-600 keV). The final goal is to develop a focusing optics that can improve the current sensitivity in the above energy band by 2 orders of magnitude.Comment: 7 pages, 6 figures, presented at the SPIE conference on "Optics for EUV, X-ray, and Gamma-ray Astronomy". To be published in the Proceedings of SPIE, vol.8147, 201

Comparison of Algorithms for the AI-Based Fault Diagnostic of Cable Joints in MV Networks

Abstract Electrical utilities and system operators (SOs) are constantly looking for solutions to problems in the management and control of the power network. For this purpose, SOs are exploring new research fields, which might bring contributions to the power system environment. A clear example is the field of computer science, within which artificial intelligence (AI) has been developed and is being applied to many fields. In power systems, AI could support the fault prediction of cable joints. Despite the availability of many legacy methods described in the literature, fault prediction is still critical, and it needs new solutions. For this purpose, in this paper, the authors made a further step in the evaluation of machine learning methods (ML) for cable joint health assessment. Six ML algorithms have been compared and assessed on a consolidated test scenario. It simulates a distributed measurement system which collects measurements from medium-voltage (MV) cable joints. Typical metrics have been applied to compare the performance of the algorithms. The analysis is then completed considering the actual in-field conditions and the SOs’ requirements. The results demonstrate: (i) the pros and cons of each algorithm; (ii) the best-performing algorithm; (iii) the possible benefits from the implementation of ML algorithms

Development status of the LAUE project

We present the status of LAUE, a project supported by the Italian Space Agency (ASI), and devoted to develop Laue lenses with long focal length (up to 100 meters), for hard X--/soft gamma--ray astronomy (80-600 keV). Thanks to their focusing capability, the design goal is to improve the sensitivity of the current instrumention in the above energy band by 2 orders of magnitude, down to a few times $10^{-8}$ photons/(cm$^2$ s keV).Comment: 9 pages, 9 figures, presented at the Space Telescopes and Instrumentation Symposium in Amsterdam, 2012: Ultraviolet to Gamma Ray Conference. Published in the Proceedings of the SPIE, Volume 8443, id. 84430B-84430B-9 (2012