Reduction of pre-Hamiltonian actions

We prove a reduction theorem for the tangent bundle of a Poisson manifold $(M, \pi)$ endowed with a pre-Hamiltonian action of a Poisson Lie group $(G, \pi_G)$. In the special case of a Hamiltonian action of a Lie group, we are able to compare our reduction to the classical Marsden-Ratiu reduction of $M$. If the manifold $M$ is symplectic and simply connected, the reduced tangent bundle is integrable and its integral symplectic groupoid is the Marsden-Weinstein reduction of the pair groupoid $M \times \bar{M}$.Comment: 18 pages, final version, to appear in Journal of Geometry and Physic

A Semantic Similarity Measure for Expressive Description Logics

A totally semantic measure is presented which is able to calculate a similarity value between concept descriptions and also between concept description and individual or between individuals expressed in an expressive description logic. It is applicable on symbolic descriptions although it uses a numeric approach for the calculus. Considering that Description Logics stand as the theoretic framework for the ontological knowledge representation and reasoning, the proposed measure can be effectively used for agglomerative and divisional clustering task applied to the semantic web domain.Comment: 13 pages, Appeared at CILC 2005, Convegno Italiano di Logica Computazionale also available at http://www.disp.uniroma2.it/CILC2005/downloads/papers/15.dAmato_CILC05.pd

Visualizing and Understanding Sum-Product Networks

Sum-Product Networks (SPNs) are recently introduced deep tractable probabilistic models by which several kinds of inference queries can be answered exactly and in a tractable time. Up to now, they have been largely used as black box density estimators, assessed only by comparing their likelihood scores only. In this paper we explore and exploit the inner representations learned by SPNs. We do this with a threefold aim: first we want to get a better understanding of the inner workings of SPNs; secondly, we seek additional ways to evaluate one SPN model and compare it against other probabilistic models, providing diagnostic tools to practitioners; lastly, we want to empirically evaluate how good and meaningful the extracted representations are, as in a classic Representation Learning framework. In order to do so we revise their interpretation as deep neural networks and we propose to exploit several visualization techniques on their node activations and network outputs under different types of inference queries. To investigate these models as feature extractors, we plug some SPNs, learned in a greedy unsupervised fashion on image datasets, in supervised classification learning tasks. We extract several embedding types from node activations by filtering nodes by their type, by their associated feature abstraction level and by their scope. In a thorough empirical comparison we prove them to be competitive against those generated from popular feature extractors as Restricted Boltzmann Machines. Finally, we investigate embeddings generated from random probabilistic marginal queries as means to compare other tractable probabilistic models on a common ground, extending our experiments to Mixtures of Trees.Comment: Machine Learning Journal paper (First Online), 24 page

Interlocking directorates and different power forms: An explorative analysis in the Italian context

The purpose of the present paper is twofold. The first is to update the contribution by Drago et al. (2011) about cross-shareholdings and interlocking directorates in Italian listed companies (FTSE MIB) to 31 December 2016 and to reinforce theory of enlarged collusion. The second is to find how interlocking directorates can contribute to understanding the power structure. By using the social network analysis, we map the network structure of interlocking boards and employ centrality measures like degree, eigenvector and betweenness centrality along with the network density and average degree. We interpret eigenvector centrality as a measure of “effective power” of the connections because it can be seen as a weighted sum of not only direct connections but indirect connections, while betweenness centrality as a measure of “potential power” because it is a proxy of the volume of information that passes through the nodes. In this way, we provide a framework for selecting Italian firms with effective and potential power – around whom interactions and processes can be traced and analysed. In addition, we find that the position assumed by the controlling group of the Mediobanca Galaxy is definitely downsized

X-ray emission from hot subdwarfs with compact companions

We review the X-ray observations of hot subdwarf stars. While no X-ray emission has been detected yet from binaries containing B-type subdwarfs, interesting results have been obtained in the case of the two luminous O-type subdwarfs HD 49798 and BD +37 442. Both of them are members of binary systems in which the X-ray luminosity is powered by accretion onto a compact object: a rapidly spinning (13.2 s) and massive (1.28 M_sun) white dwarf in the case of HD 49798 and most likely a neutron star, spinning at 19.2 s, in the case of BD +37 442. Their study can shed light on the poorly known processes taking place during common envelope evolutionary phases and on the properties of wind mass loss from hot subdwarfs.Comment: To be published in the proceedings of the 40th Liege International Astrophysical Colloquium "Ageing low mass stars: from red giants to white dwarfs

Social innovation practices: focus on success factors for crowdfunding

This article explores what are the success factor for interaction with platforms of crowdfunding in Italy. Through a Principal Component Analysis we outline three variables and through a multiple regression analysis we demonstrate that the interaction on crowdfunding is positive correlated with socio-economic propensity and cultural level. The analysis has been conducted on a sample of 316 of projects funded in the Crowdfunding platform Produzioni dal Basso, the first platform born in Italy. We draw on SD logic and relationship marketing to underscore the importance of networks of actors and integration to create a co-creation of value. This view emphasizes the social and economic factors that influence, and are influenced by, crowdfundin

The High Mass X-ray Binaries in star-forming galaxies

The high mass X-ray binaries (HMXBs) provide an exciting framework to investigate the evolution of massive stars and the processes behind binary evolution. HMXBs have shown to be good tracers of recent star formation in galaxies and might be important feedback sources at early stages of the Universe. Furthermore, HMXBs are likely the progenitors of gravitational wave sources (BH--BH or BH--NS binaries that may merge producing gravitational waves). In this work, we investigate the nature and properties of HMXB population in star-forming galaxies. We combine the results from the population synthesis model MOBSE (Giacobbo et al. 2018) together with galaxy catalogs from EAGLE simulation (Schaye et al. 2015). Therefore, this method describes the HMXBs within their host galaxies in a self-consistent way. We compute the X-ray luminosity function (XLF) of HMXBs in star-forming galaxies, showing that this methodology matches the main features of the observed XLF.Comment: 4 pages, 2 figures. To appear in Proc. IAUS 346: High-mass X-ray binaries: illuminating the passage from massive binaries to merging compact object

early vaccination a provisional measure to prevent measles in infants

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