Fairness-Aware Training of Decision Trees by Abstract Interpretation

International audienceWe study the problem of formally verifying individual fairness of decision tree ensembles, as well as training tree models which maximize both accuracy and individual fairness. In our approach, fairness verification and fairness-aware training both rely on a notion of stability of a classifier, which is a generalization of the standard notion of robustness to input perturbations used in adversarial machine learning. Our verification and training methods leverage abstract interpretation, a well-established mathematical framework for designing computable, correct, and precise approximations of potentially infinite behaviors. We implemented our fairness-aware learning method by building on a tool for adversarial training of decision trees. We evaluated it in practice on the reference datasets in the literature on fairness in machine learning. The experimental results show that our approach is able to train tree models exhibiting a high degree of individual fairness with respect to the natural state-of-the-art CART trees and random forests. Moreover, as a by-product, these fairness-aware decision trees turn out to be significantly compact, which naturally enhances their interpretability

Abstract Interpretation-Based Feature Importance for SVMs

We propose a symbolic representation for support vector machines (SVMs) by means of abstract interpretation, a well-known and successful technique for designing and implementing static program analyses. We leverage this abstraction in two ways: (1) to enhance the interpretability of SVMs by deriving a novel feature importance measure, called abstract feature importance (AFI), that does not depend in any way on a given dataset of the accuracy of the SVM and is very fast to compute, and (2) for verifying stability, notably individual fairness, of SVMs and producing concrete counterexamples when the verification fails. We implemented our approach and we empirically demonstrated its effectiveness on SVMs based on linear and nonlinear (polynomial and radial basis function) kernels. Our experimental results show that, independently of the accuracy of the SVM, our AFI measure correlates much more strongly with the stability of the SVM to feature perturbations than feature importance measures widely available in machine learning software such as permutation feature importance. It thus gives better insight into the trustworthiness of SVMs

West Nile virus transmission. results from the integrated surveillance system in Italy, 2008 to 2015

IIn Italy a national Plan for the surveillance of imported and autochthonous human vector-borne diseases (chikungunya, dengue, Zika virus disease and West Nile virus (WNV) disease) that integrates human and veterinary (animals and vectors) surveillance, is issued and revised annually according with the observed epidemiological changes. Here we describe results of the WNV integrated veterinary and human surveillance systems in Italy from 2008 to 2015. A real time data exchange protocol is in place between the surveillance systems to rapidly identify occurrence of human and animal cases and to define and update the map of affected areas i.e. provinces during the vector activity period from June to October. WNV continues to cause severe illnesses in Italy during every transmission season, albeit cases are sporadic and the epidemiology varies by virus lineage and geographic area. The integration of surveillance activities and a multidisciplinary approach made it possible and have been fundamental in supporting implementation of and/or strengthening preventive measures aimed at reducing the risk of transmission of WNV trough blood, tissues and organ donation and to implementing further measures for vector control

IAU Office of Astronomy for Education, OAE Center Italy - Annual Report 2022

Annual report 2023 of the the IAU OAE Center Italy, an international office addressed to education and hosted and financed by Inaf. OAE Center Italy was established on the 3rd of March 2021, thanks to a Memorandum of Understanding signed by three parties: IAU, the Office of Astronomy for Education and INAF. OAE Center Italy is a joint project of a consortium of Italian partners, led and represented by INAF and of the IAU OAE, and is operated by INAF. The Italian partners are INAF, the Italian Astronomical Society (SAIt) and the University of Rome Tor Vergata (ToV). Index of contents 1. Professionalize astronomy education 11 1.1 The 4th Shaw-IAU workshop of Astronomy for Education 12 1.2 “Officina degli Errori” Pilot Programme 14 1.3 Educational path for transversal skills and professional orientation through Game-Based Learning 16 2. Provide access to good resources 18 2.1 astroEDU 19 2.2 Shared astronomical Glossary 21 2.3 Astrophotography contest 23 3. Promote astronomy in curricula 24 3.1 MIRTO - Mediterranean Informal Round Table – online 25 3.2 STEAM-MED - Lampedusa workshop on Astronomy Education 2022 27 3.3 Teacher Training Pilot Program (TTPP) 35 3.4 Organisation and delivery of the 16 hour-course for PhD students "Designing innovative public-engagement activities", at the University of Padova. 36 3.5 Castellaro Lagusello Astronomy Festival 37 4. OAE Networking 38 4.1 Participation in Expo 2020, Dubai, Italian Pavilion 39 4.2 Under the same Moon: building bridges through sky and astronomy 40 5. Spread the news 41 5.1 Under the same sky: an exhibition in Rome 42 5.2 Il Cielo itinerante – Italy shines 42 5.3 Universe World / EduINAF column 43 5.4 Time machines, an astronomy exhibition 43 5.5 Workshops 43 5.6 Press release, announcements and new

IAU Office of Astronomy for Education, OAE Center Italy - Annual Report 2021

First annual report of the the IAU OAE Center Italy, an international office addressed to education and hosted and financed by Inaf. OAE Center Italy was established on the 3rd of March 2021, thanks to a Memorandum of Understanding signed by three parties: IAU, the Office of Astronomy for Education and INAF. OAE Center Italy is a joint project of a consortium of Italian partners, led and represented by INAF and of the IAU OAE, and is operated by INAF. The Italian partners are INAF, the Italian Astronomical Society (SAIt) and the University of Rome Tor Vergata (ToV)

IAU Office of Astronomy for Education OAE Center Italy - Quarterly Report 1 January-March 2022

The IAU O!ce of Astronomy for Education Center Italy (I-OAE) is a joint project of a consortium of Italian partners led and represented by Istituto Nazionale di Astrofisica (INAF, National Institute for Astrophysics), the International Astronomical Union (IAU) and the IAU O!ce of Astronomy for Education. The Italian consortium is constituted by: INAF, the Italian Astronomical Society (SAIt) and the University of Rome Tor Vergata (ToV). I-OAE HQ are hosted by the INAF - Rome Astronomical Observatory, in Monteporzio. Personnel is selected on voluntary bases according to their interests and competence, in agreement with the Institutes they work for. Brochure of the 2021 activities: https://www.flipsnack.com/eduinaf/oaei-brochure.htmlQuarterly Report 1 January-March 2022 is the report of the activities from January to March 2022 of the IAU Office of Astronomy for Education OAE Center Italy Attachment: brochure of the activities and project 202

Effect of high-pressure torsion on microstructure, mechanical properties and corrosion resistance of cast pure Mg

© 2018, The Author(s). High-pressure torsion (HPT) processing was applied to cast pure magnesium, and the effects of the deformation on the microstructure, hardness, tensile properties and corrosion resistance were evaluated. The microstructures of the processed samples were examined by electron backscatter diffraction, and the mechanical properties were determined by Vickers hardness and tensile testing. The corrosion resistance was studied using electrochemical impedance spectroscopy in a 3.5% NaCl solution. The results show that HPT processing effectively refines the grain size of Mg from millimeters in the cast structure to a few micrometers after processing and also creates a basal texture on the surface. It was found that one or five turns of HPT produced no significant difference in the grain size of the processed Mg and the hardness was a maximum after one turn due to recovery in some grains. Measurements showed that the yield strength of the cast Mg increased by about seven times whereas the corrosion resistance was not significantly affected by the HPT processing