Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo"

In recent years, many accurate decision support systems have been constructed as black boxes, that is as systems that hide their internal logic to the user. This lack of explanation constitutes both a practical and an ethical issue. The literature reports many approaches aimed at overcoming this crucial weakness, sometimes at the cost of sacrificing accuracy for interpretability. The applications in which black box decision systems can be used are various, and each approach is typically developed to provide a solution for a specific problem and, as a consequence, it explicitly or implicitly delineates its own definition of interpretability and explanation. The aim of this article is to provide a classification of the main problems addressed in the literature with respect to the notion of explanation and the type of black box system. Given a problem definition, a black box type, and a desired explanation, this survey should help the researcher to find the proposals more useful for his own work. The proposed classification of approaches to open black box models should also be useful for putting the many research open questions in perspective.

In this work we present SENTIWORDNET 3.0, a lexical resource explicitly devised for supporting sentiment classification and opinion mining applications. SENTIWORDNET 3.0 is an improved version of SENTIWORDNET 1.0, a lexical resource publicly available for research purposes, now currently licensed to more than 300 research groups and used in a variety of research projects worldwide. Both SENTIWORDNET 1.0 and 3.0 are the result of automatically annotating all WORDNET synsets according to their degrees of positivity, negativity, and neutrality. SENTIWORDNET 1.0 and 3.0 differ (a) in the versions of WORDNET which they annotate (WORDNET 2.0 and 3.0, respectively), (b) in the algorithm used for automatically annotating WORDNET, which now includes (additionally to the previous semi-supervised learning step) a random-walk step for refining the scores. We here discuss SENTIWORDNET 3.0, especially focussing on the improvements concerning aspect (b) that it embodies with respect to version 1.0. We also report the results of evaluating SENTIWORDNET 3.0 against a fragment of WORDNET 3.0 manually annotated for positivity, negativity, and neutrality; these results indicate accuracy improvements of about 20 % with respect to SENTIWORDNET 1.0. 1.

Opinion mining (OM) is a recent subdiscipline at the crossroads of information retrieval and computational linguistics which is concerned not with the topic a document is about, but with the opinion it expresses.OM has a rich set of applications, ranging from tracking users' opinions about products or about political candidates as expressed in online forums, to customer relationship management.In order to aid the extraction of opinions from text, recent research has tried to automatically determine the "PN-polarity" of subjective terms, i.e. identify whether a term that is a marker of opinionated content has a positive or a negative connotation.Research on determining whether a term is indeed a marker of opinionated content (a subjective term) or not (an objective term) has been, instead, much more scarce.In this work we describe SENTIWORDNET, a lexical resource in which each WORDNET synset s is associated to three numerical scores Obj(s), P os(s) and N eg(s), describing how objective, positive, and negative the terms contained in the synset are.The method used to develop SENTIWORDNET is based on the quantitative analysis of the glosses associated to synsets, and on the use of the resulting vectorial term representations for semi-supervised synset classification.The three scores are derived by combining the results produced by a committee of eight ternary classifiers, all characterized by similar accuracy levels but different classification behaviour.SENTIWORDNET is freely available for research purposes, and is endowed with a Web-based graphical user interface.

Here we sketch the rudiments of what constitutes a smart city which we define as a city in which ICT is merged with traditional infrastructures, coordinated and integrated using new digital technologies. We first sketch our vision defining seven goals which concern: developing a new understanding of urban problems; effective and feasible ways to coordinate urban technologies; models and methods for using urban data across spatial and temporal scales; developing new technologies for communication and dissemination; developing new forms of urban governance and organisation; defining critical problems relating to cities, transport, and energy; and identifying risk, uncertainty, and hazards in the smart city. To this, we add six research challenges: to relate the infrastructure of smart cities to their operational functioning and planning through management, control and optimisation; to explore the notion of the city as a laboratory for innovation; to provide portfolios of urban simulation which inform future designs; to develop technologies that ensure equity, fairness and realise a better quality of city life; to develop technologies that ensure informed participation and create shared knowledge for democratic city governance; and to ensure greater and more effective mobility and access to opportunities for urban populations. We begin by defining the state of the art, explaining the science of smart cities. We define six scenarios based on new cities badging themselves as smart, older cities regenerating themselves as smart, the development of science parks, tech cities, and technopoles focused on high technologies, the development of urban services using contemporary ICT, the use of ICT to develop new urban intelligence functions, and the development of online and mobile forms of participation. Seven project areas are then proposed: Integrated Databases for the Smart City, Sensing, Networking and the Impact of New Social Media, Modelling Network Performance, Mobility and Travel Behaviour, Modelling Urban Land Use, Transport and Economic Interactions, Modelling Urban Transactional Activities in Labour and Housing Markets, Decision Support as Urban Intelligence, Participatory Governance and Planning Structures for the Smart City. Finally we anticipate the paradigm shifts that will occur in this research and define a series of key demonstrators which we believe are important to progressing a science of smart cities. Graphical abstract

Improving the platinum (Pt) mass activity for the oxygen reduction reaction (ORR) requires optimization of both the specific activity and the electrochemically active surface area (ECSA). We found that solution-synthesized Pt/NiO core/shell nanowires can be converted into PtNi alloy nanowires through a thermal annealing process and then transformed into jagged Pt nanowires via electrochemical dealloying. The jagged nanowires exhibit an ECSA of 118 square meters per gram of Pt and a specific activity of 11.5 milliamperes per square centimeter for ORR (at 0.9 volts versus reversible hydrogen electrode), yielding a mass activity of 13.6 amperes per milligram of Pt, nearly double previously reported best values. Reactive molecular dynamics simulations suggest that highly stressed, undercoordinated rhombus-rich surface configurations of the jagged nanowires enhance ORR activity versus more relaxed surfaces.

The European Space Agency’s Planck satellite, dedicated to studying the early Universe and its subsequent evolution, was launched 14 May 2009 and has been scanning the microwave and submillimetre sky continuously since 12 August 2009. In March 2013, ESA and the Planck Collaboration released the initial cosmology products based on the first 15.5 months of Planck data, along with a set of scientific and technical papers and a web-based explanatory supplement. This paper gives an overview of the mission and its performance, the processing, analysis, and characteristics of the data, the scientific results, and the science data products and papers in the release. The science products include maps of the cosmic microwave background (CMB) and diffuse extragalactic foregrounds, a catalogue of compact Galactic and extragalactic sources, and a list of sources detected through the Sunyaev-Zeldovich effect. The likelihood code used to assess cosmological models against the Planck data and a lensing likelihood are described. Scientific results include robust support for the standard six-parameter ΛCDM model of cosmology and improved measurements of its parameters, including a highly significant deviation from scale invariance of the primordial power spectrum. The Planck values for these parameters and others derived from them are significantly different from those previously determined. Several large-scale anomalies in the temperature distribution of the CMB, first detected by WMAP, are confirmed with higher confidence. Planck sets new limits on the number and mass of neutrinos, and has measured gravitational lensing of CMB anisotropies at greater than 25σ. Planck finds no evidence for non-Gaussianity in the CMB. Planck’s results agree well with results from the measurements of baryon acoustic oscillations. Planck finds a lower Hubble constant than found in some more local measures. Some tension is also present between the amplitude of matter fluctuations (σ8) derived from CMB data and that derived from Sunyaev-Zeldovich data. The Planck and WMAP power spectra are offset from each other by an average level of about 2% around the first acoustic peak. Analysis of Planck polarization data is not yet mature, therefore polarization results are not released, although the robust detection of E-mode polarization around CMB hot and cold spots is shown graphically.

This paper presents a new tool, Metro, designed to compensate for a deficiency in many simplification methods proposed in literature. Metro allows one to compare the difference between a pair of surfaces (e.g. a triangulated mesh and its simplified representation) by adopting a surface sampling approach. It has been designed as a highly general tool, and it does no assumption on the particular approach used to build the simplified representation. It returns both numerical results (meshes areas and volumes, maximum and mean error, etc.) and visual results, by coloring the input surface according to the approximation error.

Organohalide lead perovskites have revolutionized the scenario of emerging photovoltaic technologies. The prototype MAPbI3 perovskite (MA = CH3NH3(+)) has dominated the field, despite only harvesting photons above 750 nm (∼1.6 eV). Intensive research efforts are being devoted to find new perovskites with red-shifted absorption onset, along with good charge transport properties. Recently, a new perovskite based on the formamidinium cation ((NH2)2CH(+) = FA) has shown potentially superior properties in terms of band gap and charge transport compared to MAPbI3. The results have been interpreted in terms of the cation size, with the larger FA cation expectedly delivering reduced band-gaps in Pb-based perovskites. To provide a full understanding of the interplay among size, structure, and organic/inorganic interactions in determining the properties of APbI3 perovskites, in view of designing new materials and fully exploiting them for solar cells applications, we report a fully first-principles investigation on APbI3 perovskites with A = Cs(+), MA, and FA. Our results evidence that the tetragonal-to-quasi cubic structural evolution observed when moving from MA to FA is due to the interplay of size effects and enhanced hydrogen bonding between the FA cations and the inorganic matrix altering the covalent/ionic character of Pb-I bonds. Most notably, the observed cation-induced structural variability promotes markedly different electronic and optical properties in the MAPbI3 and FAPbI3 perovskites, mediated by the different spin-orbit coupling, leading to improved charge transport and red-shifted absorption in FAPbI3 and in general in pseudocubic structures. Our theoretical model constitutes the basis for the rationale design of new and more efficient organohalide perovskites for solar cells applications.

We address the issue of compressing and indexing data. We devise a data structure whose space occupancy is a function of the entropy of the underlying data set. We call the data structure opportunistic since its space occupancy is decreased when the input is compressible and this space reduction is achieved at no significant slowdown in the query performance. More precisely, its space occupancy is optimal in an information-content sense because text T[1,u] is stored using O(H/sub k/(T))+o(1) bits per input symbol in the worst case, where H/sub k/(T) is the kth order empirical entropy of T (the bound holds for any fixed k). Given an arbitrary string P[1,p], the opportunistic data structure allows to search for the occurrences of P in T in O(p+occlog/sup /spl epsiv//u) time (for any fixed /spl epsiv/>0). If data are uncompressible we achieve the best space bound currently known (Grossi and Vitter, 2000); on compressible data our solution improves the succinct suffix array of (Grossi and Vitter, 2000) and the classical suffix tree and suffix array data structures either in space or in query time or both. We also study our opportunistic data structure in a dynamic setting and devise a variant achieving effective search and update time bounds. Finally, we show how to plug our opportunistic data structure into the Glimpse tool (Manber and Wu, 1994). The result is an indexing tool which achieves sublinear space and sublinear query time complexity.

The increasing pervasiveness of location-acquisition technologies (GPS, GSM networks, etc.) is leading to the collection of large spatio-temporal datasets and to the opportunity of discovering usable knowledge about movement behaviour, which fosters novel applications and services. In this paper, we move towards this direction and develop an extension of the sequential pattern mining paradigm that analyzes the trajectories of moving objects. We introduce trajectory patterns as concise descriptions of frequent behaviours, in terms of both space (i.e., the regions of space visited during movements) and time (i.e., the duration of movements). In this setting, we provide a general formal statement of the novel mining problem and then study several different instantiations of different complexity. The various approaches are then empirically evaluated over real data and synthetic benchmarks, comparing their strengths and weaknesses.

We report a colloidal synthesis approach to CsPbBr3 nanoplatelets (NPLs). The nucleation and growth of the platelets, which takes place at room temperature, is triggered by the injection of acetone in a mixture of precursors that would remain unreactive otherwise. The low growth temperature enables the control of the plate thickness, which can be precisely tuned from 3 to 5 monolayers. The strong two-dimensional confinement of the carriers at such small vertical sizes is responsible for a narrow PL, strong excitonic absorption, and a blue shift of the optical band gap by more than 0.47 eV compared to that of bulk CsPbBr3. We also show that the composition of the NPLs can be varied all the way to CsPbBr3 or CsPbI3 by anion exchange, with preservation of the size and shape of the starting particles. The blue fluorescent CsPbCl3 NPLs represent a new member of the scarcely populated group of blue-emitting colloidal nanocrystals. The exciton dynamics were found to be independent of the extent of 2D confinement in these platelets, and this was supported by band structure calculations.

Software engineering comprehends several disciplines devoted to prevent and remedy malfunctions and to warrant adequate behaviour. Testing, the subject of this paper, is a widespread validation approach in industry, but it is still largely ad hoc, expensive, and unpredictably effective. Indeed, software testing is a broad term encompassing a variety of activities along the development cycle and beyond, aimed at different goals. Hence, software testing research faces a collection of challenges. A consistent roadmap of the most relevant challenges to be addressed is here proposed. In it, the starting point is constituted by some important past achievements, while the destination consists of four identified goals to which research ultimately tends, but which remain as unreachable as dreams. The routes from the achievements to the dreams are paved by the outstanding research challenges, which are discussed in the paper along with interesting ongoing work.

The minitrack presents six papers related to the design, modeling and performance evaluation of architectures and protocols for Mobile Ad-hoc Networks. The first two papers refer to the technologies for single-hop wireless networks, while the other papers focus on multi-hop networks.

Our understanding of how individual mobility patterns shape and impact the social network is limited, but is essential for a deeper understanding of network dynamics and evolution. This question is largely unexplored, partly due to the difficulty in obtaining large-scale society-wide data that simultaneously capture the dynamical information on individual movements and social interactions. Here we address this challenge for the first time by tracking the trajectories and communication records of 6 Million mobile phone users. We find that the similarity between two individuals' movements strongly correlates with their proximity in the social network. We further investigate how the predictive power hidden in such correlations can be exploited to address a challenging problem: which new links will develop in a social network. We show that mobility measures alone yield surprising predictive power, comparable to traditional network-based measures. Furthermore, the prediction accuracy can be significantly improved by learning a supervised classifier based on combined mobility and network measures. We believe our findings on the interplay of mobility patterns and social ties offer new perspectives on not only link prediction but also network dynamics.

Neurogenesis continues to occur in the adult mammalian hippocampus and is regulated by both genetic and environmental factors. It is known that exposure to an enriched environment enhances the number of newly generated neurons in the dentate gyrus. However, the mechanisms by which enriched housing produces these effects are poorly understood. To test a role for neurotrophins, we used heterozygous knockout mice for brain-derived neurotrophic factor (BDNF+/-) and mice lacking neurotrophin-4 (NT-4-/-) together with their wild-type littermates. Mice were either reared in standard laboratory conditions or placed in an enriched environment for 8 weeks. Animals received injections of the mitotic marker bromodeoxyuridine (BrdU) to label newborn cells. Enriched wild-type and enriched NT-4-/- mice showed a two-fold increase in hippocampal neurogenesis as assessed by stereological counting of BrdU-positive cells in the dentate gyrus and double labelling for BrdU and the neuronal marker NeuN. Remarkably, this enhancement of hippocampal neurogenesis was not seen in enriched BDNF+/- mice. Failure to up-regulate BDNF accompanied the lack of a neurogenic response in enriched BDNF heterozygous mice. We conclude that BDNF but not NT-4 is required for the environmental induction of neurogenesis.

Abstract We have developed a colloidal synthesis of nearly monodisperse nanocrystals of pure Cs4PbX6 (X = Cl, Br, I) and their mixed halide compositions with sizes ranging from 9 to 37 nm. The optical absorption spectra of these nanocrystals display a sharp, high energy peak due to transitions between states localized in individual PbX64– octahedra. These spectral features are insensitive to the size of the particles and in agreement with the features of the corresponding bulk materials. Samples with mixed halide composition exhibit absorption bands that are intermediate in spectral position between those of the pure halide compounds. Furthermore, the absorption bands of intermediate compositions broaden due to the different possible combinations of halide coordination around the Pb2+ ions. Both observations are supportive of the fact that the [PbX6]4– octahedra are electronically decoupled in these systems. Because of the large band gap of Cs4PbX6 (>3.2 eV), no excitonic emission in the visible range was observed. The Cs4PbBr6 nanocrystals can be converted into green fluorescent CsPbBr3 nanocrystals by their reaction with an excess of PbBr2 with preservation of size and size distributions. The insertion of PbX2 into Cs4PbX6 provides a means of accessing CsPbX3 nanocrystals in a wide variety of sizes, shapes, and compositions, an important aspect for the development of precisely tuned perovskite nanocrystal inks.

BACKGROUND: The COVID-19 pandemic is favoring digital transitions in many industries and in society as a whole. Health care organizations have responded to the first phase of the pandemic by rapidly adopting digital solutions and advanced technology tools. OBJECTIVE: The aim of this review is to describe the digital solutions that have been reported in the early scientific literature to mitigate the impact of COVID-19 on individuals and health systems. METHODS: We conducted a systematic review of early COVID-19-related literature (from January 1 to April 30, 2020) by searching MEDLINE and medRxiv with appropriate terms to find relevant literature on the use of digital technologies in response to the pandemic. We extracted study characteristics such as the paper title, journal, and publication date, and we categorized the retrieved papers by the type of technology and patient needs addressed. We built a scoring rubric by cross-classifying the patient needs with the type of technology. We also extracted information and classified each technology reported by the selected articles according to health care system target, grade of innovation, and scalability to other geographical areas. RESULTS: The search identified 269 articles, of which 124 full-text articles were assessed and included in the review after screening. Most of the selected articles addressed the use of digital technologies for diagnosis, surveillance, and prevention. We report that most of these digital solutions and innovative technologies have been proposed for the diagnosis of COVID-19. In particular, within the reviewed articles, we identified numerous suggestions on the use of artificial intelligence (AI)-powered tools for the diagnosis and screening of COVID-19. Digital technologies are also useful for prevention and surveillance measures, such as contact-tracing apps and monitoring of internet searches and social media usage. Fewer scientific contributions address the use of digital technologies for lifestyle empowerment or patient engagement. CONCLUSIONS: In the field of diagnosis, digital solutions that integrate with traditional methods, such as AI-based diagnostic algorithms based both on imaging and clinical data, appear to be promising. For surveillance, digital apps have already proven their effectiveness; however, problems related to privacy and usability remain. For other patient needs, several solutions have been proposed, such as telemedicine or telehealth tools. These tools have long been available, but this historical moment may actually be favoring their definitive large-scale adoption. It is worth taking advantage of the impetus provided by the crisis; it is also important to keep track of the digital solutions currently being proposed to implement best practices and models of care in future and to adopt at least some of the solutions proposed in the scientific literature, especially in national health systems, which have proved to be particularly resistant to the digital transition in recent years.

Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application. This trend has promoted semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies. This survey provides the definitions of the basic concepts about mobility data, an analysis of the issues in mobility data management, and a survey of the approaches and techniques for: (i) constructing trajectories from movement tracks, (ii) enriching trajectories with semantic information to enable the desired interpretations of movements, and (iii) using data mining to analyze semantic trajectories and extract knowledge about their characteristics, in particular the behavioral patterns of the moving objects. Last but not least, the article surveys the new privacy issues that arise due to the semantic aspects of trajectories.

The pervasiveness of mobile devices and location based services is leading to an increasing volume of mobility data.This side eect provides the opportunity for innovative methods that analyse the behaviors of movements. In this paper we propose WhereNext, which is a method aimed at predicting with a certain level of accuracy the next location of a moving object. The prediction uses previously extracted movement patterns named Trajectory Patterns, which are a concise representation of behaviors of moving objects as sequences of regions frequently visited with a typical travel time. A decision tree, named T-pattern Tree, is built and evaluated with a formal training and test process. The tree is learned from the Trajectory Patterns that hold a certain area and it may be used as a predictor of the next location of a new trajectory finding the best matching path in the tree. Three dierent best matching methods to classify a new moving object are proposed and their impact on the quality of prediction is studied extensively. Using Trajectory Patterns as predictive rules has the following implications: (I) the learning depends on the movement of all available objects in a certain area instead of on the individual history of an object; (II) the prediction tree intrinsically contains the spatio-temporal properties that have emerged from the data and this allows us to define matching methods that striclty depend on the properties of such movements. In addition, we propose a set of other measures, that evaluate a priori the predictive power of a set of Trajectory Patterns. This measures were tuned on a real life case study. Finally, an exhaustive set of experiments and results on the real dataset are presented.

The European Space Agency’s Planck satellite was launched on 14 May 2009, and has been surveying the sky stably and continuously since 13 August 2009. Its performance is well in line with expectations, and it will continue to gather scientific data until the end of its cryogenic lifetime. We give an overview of the history of Planck in its first year of operations, and describe some of the key performance aspects of the satellite. This paper is part of a package submitted in conjunction with Planck’s Early Release Compact Source Catalogue, the first data product based on Planck to be released publicly. The package describes the scientific performance of the Planck payload, and presents results on a variety of astrophysical topics related to the sources included in the Catalogue, as well as selected topics on diffuse emission.