Le fratture multifocali di omero

Le fratture multifocali di omero possono interessare l'epifisi prossimale e la diafisi, punti diversi della diafisi, epifisi distale e diafisi. In questa tesi abbiamo confrontato i nostri dati con quelli presenti in letteratura

Building an Urban Theft Map by Analyzing Newspaper Crime Reports

One of the main issues in today's cities is related to public safety, which can be improved by implementing a systematic analysis for identifying and analyzing patterns and trends in crime also called crime mapping. Mapping crime allows police analysts to identify crime hot spots, moreover it increases public confidence and citizen engagement and promotes transparency.This paper is focused on analyzing and mapping thefts through on-line newspaper using text mining techniques for an Italian city

Topic detection in multichannel Italian newspapers

Nowadays, any person, company or public institution uses and exploits different channels to share private or public information with other people (friends, customers, relatives, etc.) or institutions. This context has changed the journalism, thus, the major newspapers report news not just on its own web site, but also on several social media such as Twitter or YouTube. The use of multiple communication media stimulates the need for integration and analysis of the content published globally and not just at the level of a single medium. An analysis to achieve a comprehensive overview of the information that reaches the end users and how they consume the information is needed. This analysis should identify the main topics in the news flow and reveal the mechanisms of publication of news on different media (e.g. news timeline). Currently, most of the work on this area is still focused on a single medium. So, an analysis across different media (channels) should improve the result of topic detection. This paper shows the application of a graph analytical approach, called Keygraph, to a set of very heterogeneous documents such as the news published on various media. A preliminary evaluation on the news published in a 5 days period was able to identify the main topics within the publications of a single newspaper, and also within the publications of 20 newspapers on several on-line channels

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

Using real sensors data to calibrate a traffic model for the city of Modena

In Italy, road vehicles are the preferred mean of transport. Over the last years, in almost all the EU Member States, the passenger car fleet increased. The high number of vehicles complicates urban planning and often results in traffic congestion and areas of increased air pollution. Overall, efficient traffic control is profitable in individual, societal, financial, and environmental terms. Traffic management solutions typically require the use of simulators able to capture in detail all the characteristics and dependencies associated with real-life traffic. Therefore, the realization of a traffic model can help to discover and control traffic bottlenecks in the urban context. In this paper, we analyze how to better simulate vehicle flows measured by traffic sensors in the streets. A dynamic traffic model was set up starting from traffic sensors data collected every minute in about 300 locations in the city of Modena. The reliability of the model is discussed and proved with a comparison between simulated values and real values from traffic sensors. This analysis pointed out some critical issues. Therefore, to better understand the origin of fake jams and incoherence with real data, we approached different configurations of the model as possible solutions

Semantic Traffic Sensor Data: The TRAFAIR Experience

Modern cities face pressing problems with transportation systems including, but not limited to, traffic congestion, safety, health, and pollution. To tackle them, public administrations have implemented roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. In the case of traffic sensor data not only the real-time data are essential, but also historical values need to be preserved and published. When real-time and historical data of smart cities become available, everyone can join an evidence-based debate on the city’s future evolution. The TRAFAIR (Understanding Traffic Flows to Improve Air Quality) project seeks to understand how traffic affects urban air quality. The project develops a platform to provide real-time and predicted values on air quality in several cities in Europe, encompassing tasks such as the deployment of low-cost air quality sensors, data collection and integration, modeling and prediction, the publication of open data, and the development of applications for end-users and public administrations. This paper explicitly focuses on the modeling and semantic annotation of traffic data. We present the tools and techniques used in the project and validate our strategies for data modeling and its semantic enrichment over two cities: Modena (Italy) and Zaragoza (Spain). An experimental evaluation shows that our approach to publish Linked Data is effective

TRAFAIR: Understanding Traffic Flow to Improve Air Quality

Environmental impacts of traffic are of major concern throughout many European metropolitan areas. Air pollution causes 400 000 deaths per year, making it first environmental cause of premature death in Europe. Among the main sources of air pollution in Europe, there are road traffic, domestic heating, and industrial combustion. The TRAFAIR project brings together 9 partners from two European countries (Italy and Spain) to develop innovative and sustainable services combining air quality, weather conditions, and traffic flows data to produce new information for the benefit of citizens and government decision-makers. The project is started in November 2018 and lasts two years. It is motivated by the huge amount of deaths caused by the air pollution. Nowadays, the situation is particularly critical in some member states of Europe. In February 2017, the European Commission warned five countries, among which Spain and Italy, of continued air pollution breaches. In this context, public administrations and citizens suffer from the lack of comprehensive and fast tools to estimate the level of pollution on an urban scale resulting from varying traffic flow conditions that would allow optimizing control strategies and increase air quality awareness. The goals of the project are twofold: monitoring urban air quality by using sensors in 6 European cities and making urban air quality predictions thanks to simulation models. The project is co-financed by the European Commission under the CEF TELECOM call on Open Data

Predictors of Central Compartment Involvement in Patients with Positive Lateral Cervical Lymph Nodes According to Clinical and/or Ultrasound Evaluation

Lymph node neck metastases are frequent in papillary thyroid carcinoma (PTC). Current guidelines state, on a weak level of evidence, that level VI dissection is mandatory in the presence of latero-cervical metastases. The aim of our study is to evaluate predictive factors for the absence of level VI involvement despite the presence of metastases to the lateral cervical stations in PTC. Eighty-eight patients operated for PTC with level II-V metastases were retrospectively enrolled in the study. Demographics, thyroid function, autoimmunity, nodule size and site, cancer variant, multifocality, Bethesda and EU-TIRADS, number of central and lateral lymph nodes removed, number of positive lymph nodes and outcome were recorded. At univariate analysis, PTC location and number of positive lateral lymph nodes were risk criteria for failure to cure. ROC curves demonstrated the association of the number of positive lateral lymph nodes and failure to cure. On multivariate analysis, the protective factors were PTC located in lobe center and number of positive lateral lymph nodes < 4. Kaplan-Meier curves confirmed the absence of central lymph nodes as a positive prognostic factor. In the selected cases, Central Neck Dissection (CND) could be avoided even in the presence of positive Lateralcervical Lymph Nodes (LLN+)