From Sensors Data to Urban Traffic Flow Analysis

By 2050, almost 70% of the population will live in cities. As the population grows, travel demand increases and this might affect air quality in urban areas. Traffic is among the main sources of pollution within cities. Therefore, monitoring urban traffic means not only identifying congestion and managing accidents but also preventing the impact on air pollution. Urban traffic modeling and analysis is part of the advanced traffic intelligent management technologies that has become a crucial sector for smart cities. Its main purpose is to predict congestion states of a specific urban transport network and propose improvements in the traffic network that might result into a decrease of the travel times, air pollution and fuel consumption. This paper describes the implementation of an urban traffic flow model in the city of Modena based on real traffic sensor data. This is part of a wide European project that aims at studying the correlation among traffic and air pollution, therefore at combining traffic and air pollution simulations for testing various urban scenarios and raising citizen awareness about air quality where necessary

Dealing with Uncertainty in Lexical Annotation

We present ALA, a tool for the automatic lexical annotation (i.e.annotation w.r.t. a thesaurus/lexical resource) of structured and semi-structured data sources and the discovery of probabilistic lexical relationships in a data integration environment. ALA performs automatic lexical annotation through the use of probabilistic annotations, i.e. an annotation is associated to a probability value. By performing probabilistic lexical annotation, we discover probabilistic inter-sources lexical relationships among schema elements. ALA extends the lexical annotation module of the MOMIS data integration system. However, it may be applied in general in the context of schema mapping discovery, ontology merging and data integration system and it is particularly suitable for performing “on-the-fly” data integration or probabilistic ontology matching

Freezing of gait in Parkinson’s disease patients treated with bilateral subthalamic nucleus deep brain stimulation: A long-term overview

Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment in advanced Parkinson’s Disease (PD). However, the effects of STN-DBS on freezing of gait (FOG) are still debated, particularly in the long-term follow-up (>/=5-years). The main aim of the current study is to evaluate the long-term effects of STN-DBS on FOG. Twenty STN-DBS treated PD patients were included. Each patient was assessed before surgery through a detailed neurological evaluation, including FOG score, and reevaluated in the long-term (median follow-up: 5-years) in different stimulation and drug conditions. In the long term follow-up, FOG score significantly worsened in the off-stimulation/off-medication condition compared with the preoperative off-medication assessment (z = -1.930; p = 0.05) but not in the on-stimulation/off-medication (z = -0.357; p = 0.721). There was also a significant improvement of FOG at long-term assessment by comparing on-stimulation/off-medication and off-stimulation/off-medication conditions (z = -2.944; p = 0.003). These results highlight the possible beneficial long-term effects of STN-DBS on FOG

Freezing of Gait in Parkinson's Disease Patients Treated with Bilateral Subthalamic Nucleus Deep Brain Stimulation: A Long-Term Overview

Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment in advanced Parkinson's Disease (PD). However, the effects of STN-DBS on freezing of gait (FOG) are still debated, particularly in the long-term follow-up (≥5-years). The main aim of the current study is to evaluate the long-term effects of STN-DBS on FOG. Twenty STN-DBS treated PD patients were included. Each patient was assessed before surgery through a detailed neurological evaluation, including FOG score, and revaluated in the long-term (median follow-up: 5-years) in different stimulation and drug conditions. In the long term follow-up, FOG score significantly worsened in the off-stimulation/off-medication condition compared with the pre-operative off-medication assessment (z = -1.930; p = 0.05) but not in the on-stimulation/off-medication (z = -0.357; p = 0.721). There was also a significant improvement of FOG at long-term assessment by comparing on-stimulation/off-medication and off-stimulation/off-medication conditions (z = -2.944; p = 0.003). These results highlight the possible beneficial long-term effects of STN-DBS on FOG

Octopus, a computational framework for exploring light-driven phenomena and quantum dynamics in extended and finite systems

Over the last few years, extraordinary advances in experimental and theoretical tools have allowed us to monitor and control matter at short time and atomic scales with a high degree of precision. An appealing and challenging route toward engineering materials with tailored properties is to find ways to design or selectively manipulate materials, especially at the quantum level. To this end, having a state-of-the-art ab initio computer simulation tool that enables a reliable and accurate simulation of light-induced changes in the physical and chemical properties of complex systems is of utmost importance. The first principles real-space-based Octopus project was born with that idea in mind, i.e., to provide a unique framework that allows us to describe non-equilibrium phenomena in molecular complexes, low dimensional materials, and extended systems by accounting for electronic, ionic, and photon quantum mechanical effects within a generalized time-dependent density functional theory. This article aims to present the new features that have been implemented over the last few years, including technical developments related to performance and massive parallelism. We also describe the major theoretical developments to address ultrafast light-driven processes, such as the new theoretical framework of quantum electrodynamics density-functional formalism for the description of novel light–matter hybrid states. Those advances, and others being released soon as part of the Octopus package, will allow the scientific community to simulate and characterize spatial and time-resolved spectroscopies, ultrafast phenomena in molecules and materials, and new emergent states of matter (quantum electrodynamical-materials).This work was supported by the European Research Council (Grant No. ERC-2015-AdG694097), the Cluster of Excellence “Advanced Imaging of Matter” (AIM), Grupos Consolidados (IT1249-19), and SFB925. The Flatiron Institute is a division of the Simons Foundation. X.A., A.W., and A.C. acknowledge that part of this work was performed under the auspices of the U.S. Department of Energy at Lawrence Livermore National Laboratory under Contract No. DE-AC52-07A27344. J.J.-S. gratefully acknowledges the funding from the European Union Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie Grant Agreement No. 795246-StrongLights. J.F. acknowledges financial support from the Deutsche Forschungsgemeinschaft (DFG Forschungsstipendium FL 997/1-1). D.A.S. acknowledges University of California, Merced start-up funding.Peer reviewe

Dealing with Uncertainty in Lexical Annotation

We present ALA, a tool for the automatic lexical annotation (i.e.annotation w.r.t. a thesaurus/lexical resource) of structured and semi-structured data sources and the discovery of probabilistic lexical relationships in a data integration environment. ALA performs automatic lexical annotation through the use of probabilistic annotations, i.e. an annotation is associated to a probability value. By performing probabilistic lexical annotation, we discover probabilistic inter-sources lexical relationships among schema elements. ALA extends the lexical annotation module of the MOMIS data integration system. However, it may be applied in general in the context of schema mapping discovery, ontology merging and data integration system and it is particularly suitable for performing “on-the-fly” data integration or probabilistic ontology matching

MOMIS: un sistema di Description Logics per l'integrazione del sistema informativo d'impresa

Taormin

ALA: Dealing with Uncertainty in Lexical Annotation

We present ALA, a tool for the automatic lexical annotation (i.e. annotation w.r.t. a thesaurus/lexical resource) of structured and semi-structured data sources and the discovery of probabilistic lexical relationships in a data integration environment. ALA performs automatic lexical annotation through the use of probabilistic annotations, i.e. an annotation is associated to a probability value. By performing probabilistic lexical annotation, we discover probabilistic inter-sources lexical relationships among schema elements. ALA extends the lexical annotation module of the MOMIS data integration system. However, it may be applied in general in the context of schema mapping discovery, ontology merging and data integration system and it is particularly suitable for performing “on-the-fly” data integration or probabilistic ontology matching

ODB-Tool: validazione di schemi e ottimizzazione semantica on-line per basi di dati object oriented

. In questo lavoro viene presentato ODB-Tool, uno strumento software per la validazione di schemi e l'ottimizzazione semantica di interrogazioni per le Basi di Dati Orientate agli Oggetti (OODB), che sfrutta le potenzialit `a di Internet e del linguaggio JAVA per la rappresentazione grafica on-line dei risultati ottenuti. Gli algoritmi operanti in ODB-Tool sono basati su tecniche di inferenza che sfruttano il calcolo della sussunzione e la nozione di espansione semantica di interrogazioni per la trasformazione delle query al fine di ottenere inferiori tempi di risposta. Entrambi i concetti sono stati introdotti nell'area dell'Intelligenza Artificiale, pi`u precisamente nell'ambito delle Logiche Descrittive, e sono stati studiati e formalizzati in OCDL (Object Constraint Description Logics), un linguaggio che permette di esprimere descrizioni di classi, vincoli d'integrit`a ed interrogazioni. Sia per quanto riguarda il linguaggio di definizione degli schemi che il linguaggio di inte..