3,039 research outputs found
Managing the island territory : a historical perspective on sub-state nationalism in Corsica and Sardinia
Corsica (France) and Sardinia (Italy) are two islands of the western Mediterranean basin separated by a narrow strait. They share a problematic relationship with the mainland states to which they are associated, and from which they obtained their status of subnational island jurisdiction (SNIJ). The metropole/island relationship of these two islands is characterized by centrifugal tensions and the presence of sub-state nationalisms. These movements are different in terms of characteristics, strategies and electoral results, because of how France and Italy have managed the integration of the two islands, how the two island nationalisms have evolved, and how both metropolitan states have dealt with them. This article proposes a comparative history of Sardinian and Corsican nationalism and the relationship of Italy and France with these island territories. The intention is to analyse the two nationalisms, based almost exclusively on political science, with an historical perspective, highlighting the impact caused by the central states’ attitudes. In this way, the article points out how the differences between the political context of the two islands is defined by the different approach taken by France and Italy in managing their island territories.peer-reviewe
Wide band observations of the X-ray burster GS 1826-238
GS 1826-238 is a well-studied X-ray bursting neutron star in a low mass
binary system. Thermal Comptonisation by a hot electron cloud is a widely
accepted mechanism accounting for its high energy emission, while the nature of
most of its soft X-ray output is not completely understood. A further low
energy component is typically needed to model the observed spectra: pure
blackbody and Comptonisation-modified blackbody radiation by a lower
temperature (a few keV) electron plasma were suggested to explain the low
energy data. We studied the steady emission of GS 1826-238 by means of broad
band (X to soft Gamma-rays) measurements obtained by the INTEGRAL observatory
in 2003 and 2006. The newly developed, up-to-date Comptonisation model CompTB
is applied for the first time to study effectively the low-hard state
variability of a low-luminosity neutron star in a low-mass X-ray binary system.
We confirm that the 3-200 keV emission of \GS is characterised by
Comptonisation of soft seed photons by a hot electron plasma. A single spectral
component is sufficient to model the observed spectra. At lower energies, no
direct blackbody emission is observed and there is no need to postulate a low
temperature Compton region. Compared to the 2003 measurements, the plasma
temperature decreased from 20 to 14 keV in 2006, together with the seed photons
temperature. The source intensity was also found to be 30% lower in 2006,
whilst the average recurrence frequency of the X-ray bursts significantly
increased. Possible explanations for this apparent deviation from the typical
limit-cycle behaviour of this burster are discussed.Comment: 6 pages, 2 figures. Accepted for publication in A&
A new model for the X-ray continuum of the magnetized accreting pulsars
Accreting highly magnetized pulsars in binary systems are among the brightest
X-ray emitters in our Galaxy. Although a number of high statistical quality
broad-band (0.1-100 keV) X-ray observations are available, the spectral energy
distribution of these sources is usually investigated by adopting pure
phenomenological models, rather than models linked to the physics of accretion.
In this paper, a detailed spectral study of the X-ray emission recorded from
the high-mass X-ray binary pulsars Cen X-3, 4U 0115+63, and Her X-1 is carried
out by using BeppoSAX and joined Suzaku+NuStar data, together with an advanced
version of the compmag model. The latter provides a physical description of the
high energy emission from accreting pulsars, including the thermal and bulk
Comptonization of cyclotron and bremsstrahlung seed photons along the neutron
star accretion column. The compmag model is based on an iterative method for
solving second-order partial differential equations, whose convergence
algorithm has been improved and consolidated during the preparation of this
paper. Our analysis shows that the broad-band X-ray continuum of all considered
sources can be self-consistently described by the compmag model. The cyclotron
absorption features, not included in the model, can be accounted for by using
Gaussian components. From the fits of the compmag model to the data we inferred
the physical properties of the accretion columns in all sources, finding values
reasonably close to those theoretically expected according to our current
understanding of accretion in highly magnetized neutron stars. The updated
version of the compmag model has been tailored to the physical processes that
are known to occur in the columns of highly magnetized accreting neutron stars
and it can thus provide a better understanding of the high energy radiation
from these sources.Comment: 19 pages, 10 figures, accepted for publication in A&
From Sardinian autonomist movement to the defense of the Second Republic
L’article vol evidenciar, en el marc de la intervenció dels antifeixistes italians en la Guerra Civil Espanyola, el paper jugat pels militants del Partit Sard d’Acció (PSd’A) i per alguns dels seus lÃders: Emilio Lussu (1890-1945) i Dino Giacobbe (1900-1985). En particular es tracta la contribució de Lussu en el debat teòric entre els antifeixistes italians sobre com organitzar la intervenció, aixà com les gestions dels dos militants per organitzar una unitat militar que representés la nació sarda dins del conflicte.The article deal with the italian antifascist intervention during the war, but wants to highlight the role played by the Sardinian Action Party and some of his leaders: Emilio Lussu (1890-1945) and Dino Giacobbe (1900-1985). It speaks about the positions of Lussu in the discussions between italians antifascists over the organization of the intervent, and then about the attempts carried out by the two militants to create a military unit that represents the sardinian nation in the spanish civil war
Algorithms for Graph-Constrained Coalition Formation in the Real World
Coalition formation typically involves the coming together of multiple,
heterogeneous, agents to achieve both their individual and collective goals. In
this paper, we focus on a special case of coalition formation known as
Graph-Constrained Coalition Formation (GCCF) whereby a network connecting the
agents constrains the formation of coalitions. We focus on this type of problem
given that in many real-world applications, agents may be connected by a
communication network or only trust certain peers in their social network. We
propose a novel representation of this problem based on the concept of edge
contraction, which allows us to model the search space induced by the GCCF
problem as a rooted tree. Then, we propose an anytime solution algorithm
(CFSS), which is particularly efficient when applied to a general class of
characteristic functions called functions. Moreover, we show how CFSS can
be efficiently parallelised to solve GCCF using a non-redundant partition of
the search space. We benchmark CFSS on both synthetic and realistic scenarios,
using a real-world dataset consisting of the energy consumption of a large
number of households in the UK. Our results show that, in the best case, the
serial version of CFSS is 4 orders of magnitude faster than the state of the
art, while the parallel version is 9.44 times faster than the serial version on
a 12-core machine. Moreover, CFSS is the first approach to provide anytime
approximate solutions with quality guarantees for very large systems of agents
(i.e., with more than 2700 agents).Comment: Accepted for publication, cite as "in press
HMM-based anomaly interpretation for intelligent robots in Industry 4.0
We apply an anomaly detection method based on Hidden Markov Models and Hellinger distance to a Kairos mobile robot operating in the ICE lab, a research laboratory for Industry 4.0. Two main contributions are proposed: i) a decomposition of the Hellinger distance which allows to identify the causes of anomalous behaviours detected, ii) a graphical user interface that synchronously shows the robot movements in a map and the evolution of the Hellinger distance components, allowing a quick investigation of the causes of the detected anomalies. The tools are applied to a real-world dataset allowing to discover that an anomalous movement of the Kairos robot is caused by a wrong reading of the lidar from a window in the environment
Learning state-variable relationships for improving POMCP performance
We address the problem of learning state-variable relationships across different episodes in Partially Observable Markov Decision Processes (POMDPs) to improve planning performance. Specifically, we focus on Partially Observable Monte Carlo Planning (POMCP) and we represent the acquired knowledge with Markov Random Fields (MRFs). We propose three different methods to compute MRF parameters while the agent acts in the environment. Our tech- niques acquire information from agent action outcomes, and from the belief of the agent, which summarizes the knowledge acquired from observations. We also propose a stopping criterion to deter- mine when the MRF is accurate enough and the learning process can be stopped. Results show that the proposed approach allows to effectively learn state-variable probabilistic constraints and to outperform standard POMCP with no computational overhead
Influence of State-Variable Constraints on Partially Observable Monte Carlo Planning
Online planning methods for partially observable Markov decision processes (POMDPs) have re- cently gained much interest. In this paper, we pro- pose the introduction of prior knowledge in the form of (probabilistic) relationships among dis- crete state-variables, for online planning based on the well-known POMCP algorithm. In particu- lar, we propose the use of hard constraint net- works and probabilistic Markov random fields to formalize state-variable constraints and we extend the POMCP algorithm to take advantage of these constraints. Results on a case study based on Rock- sample show that the usage of this knowledge pro- vides significant improvements to the performance of the algorithm. The extent of this improvement depends on the amount of knowledge encoded in the constraints and reaches the 50% of the average discounted return in the most favorable cases that we analyzed
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