Modeling the Behavior of Novice Young Drivers Using Data from In- Vehicle Data Recorders

Novice young drivers suffer from increased crash risk that translates into over-representation in road injuries. A better understanding of the driving behavior of novice young drivers and of their determinants is needed to tackle this problem. To this extent, this study analyzes the behavior of novice young drivers within a Graduated Driver Licensing (GDL) program. Data on driving behavior of novice drivers and their parents is collected using in-vehicle data recorders, which calculate compound risk indices as measures of the risk taking behavior of the various drivers. Data is used to estimate a negative binomial model to identify the major factors that affect the driving behavior of the young drivers. Estimation results suggest that the risk taking behavior of young drivers is influenced by that of their parents and decreases with higher levels of supervised driving and stricter monitoring by the parents

Isolated Gallbladder Rupture Due to Blunt Abdominal Trauma

Traumatic injury to the extrahepatic biliary system is rare and usually diagnosed at laparotomy when it is associated with other visceral injuries. Isolated gallbladder rupture due to blunt abdominal trauma is even rarer. The clinical presentation of gallbladder injury is variable, resulting in a delay in diagnosis and treatment. Awareness to the possibilty of trauma to the extrahepatic biliary system enables early surgical intervention and eliminates the high morbidity associated with delated diagnosis

Cerebral Venous Thrombosis in the Mediterranean Area in Children

Cerebral Venous Sinus (sinovenous) Thrombosis (CSVT) is a serious and rare disorder, increasingly recognized and diagnosed in pediatric patients. The etiology and pathophisiology has not yet been completely clarified, and unlike adults with CSVT, management in children and neonates remains controversial. However, morbidity and mortality are significant, highlighting the continued need for high-quality studies within this field. The following review will highlight aspects of CSVT in the mediteranian area in children

A customisable pipeline for continuously harvesting socially-minded Twitter users

On social media platforms and Twitter in particular, specific classes of users such as influencers have been given satisfactory operational definitions in terms of network and content metrics. Others, for instance online activists, are not less important but their characterisation still requires experimenting. We make the hypothesis that such interesting users can be found within temporally and spatially localised contexts, i.e., small but topical fragments of the network containing interactions about social events or campaigns with a significant footprint on Twitter. To explore this hypothesis, we have designed a continuous user profile discovery pipeline that produces an ever-growing dataset of user profiles by harvesting and analysing contexts from the Twitter stream. The profiles dataset includes key network and content-based users metrics, enabling experimentation with user-defined score functions that characterise specific classes of online users. The paper describes the design and implementation of the pipeline and its empirical evaluation on a case study consisting of healthcare-related campaigns in the UK, showing how it supports the operational definitions of online activism, by comparing three experimental ranking functions. The code is publicly available.Comment: Procs. ICWE 2019, June 2019, Kore

Hashtags Functions in the Protests Across Brazil

In this article, we discuss the communicative functions of hashtags during a period of major social protests in Brazil. Drawing from a theoretical background of the use of Twitter and hashtags in protests and the functions of language, we extracted a sample of 46,090 hashtags from 2,321,249 tweets related to Brazilian protests in June 2013. We analyzed the hashtags through content analysis, focusing on functions, and co-occurrences. We also qualitatively analyzed a group of 500 most retweeted tweets to understand the users’ tagging behavior. Our results show how users appropriate tags to accomplish different effects on the narrative of the protests

Analyzing Users' Activity in On-line Social Networks over Time through a Multi-Agent Framework

[EN] The number of people and organizations using online social networks as a new way of communication is continually increasing. Messages that users write in networks and their interactions with other users leave a digital trace that is recorded. In order to understand what is going on in these virtual environments, it is necessary systems that collect, process, and analyze the information generated. The majority of existing tools analyze information related to an online event once it has finished or in a specific point of time (i.e., without considering an in-depth analysis of the evolution of users activity during the event). They focus on an analysis based on statistics about the quantity of information generated in an event. In this article, we present a multi-agent system that automates the process of gathering data from users activity in social networks and performs an in-depth analysis of the evolution of social behavior at different levels of granularity in online events based on network theory metrics. We evaluated its functionality analyzing users activity in events on Twitter.This work is partially supported by the PROME-TEOII/2013/019, TIN2014-55206-R, TIN2015-65515-C4-1-R, H2020-ICT-2015-688095.Del Val Noguera, E.; Martínez, C.; Botti, V. (2016). Analyzing Users' Activity in On-line Social Networks over Time through a Multi-Agent Framework. Soft Computing. 20(11):4331-4345. https://doi.org/10.1007/s00500-016-2301-0S433143452011Ahn Y-Y, Han S, Kwak H, Moon S, Jeong H (2007) Analysis of topological characteristics of huge online social networking services. In: Proceedings of the 16th WWW, pp 835–844Bastiaensens S, Vandebosch H, Poels K, Cleemput KV, DeSmet A, Bourdeaudhuij ID (2014) Cyberbullying on social network sites. an experimental study into behavioural intentions to help the victim or reinforce the bully. Comput Hum Behav 31:259–271Benevenuto F, Rodrigues T, Cha M, Almeida V (2009) Characterizing user behavior in online social networks. In: Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference. ACM, pp 49–62Borge-Holthoefer J, Rivero A, García I, Cauhé E, Ferrer A, Ferrer D, Francos D, Iñiguez D, Pérez MP, Ruiz G et al (2011) Structural and dynamical patterns on online social networks: the Spanish may 15th movement as a case study. PLoS One 6(8):e23883Borondo J, Morales AJ, Losada JC, Benito RM (2013) Characterizing and modeling an electoral campaign in the context of Twitter: 2011 Spanish presidential election as a case studyCatanese SA, De Meo P, Ferrara E, Fiumara G, Provetti A (2011) Crawling facebook for social network analysis purposes. In: Proceedings of the international conference on web intelligence, mining and semantics. ACM, p 52Cha M, Mislove A, Gummadi KP (2009) A measurement-driven analysis of information propagation in the flickr social network. In: Proceedings of the 18th international conference on World Wide Web. ACM, pp 721–730del Val E, Martínez C, Botti V (2015a) A multi-agent framework for the analysis of users behavior over time in on-line social networks. In: 10th International conference on soft computing models in industrial and environmental applications. Springer, Berlin, pp 191–201del Val E, Rebollo M, Botti V (2015b) Does the type of event influence how user interactions evolve on twitter? PLOS One 10(5):e0124049Eurostat (2016a) Internet use statistics—individuals. http://ec.europa.eu/eurostat/statistics-explained/index.php/Internet_use_statistics_-_individuals . Accessed 29 April 2016Eurostat (2016b) Social media—statistics on the use by enterprises. http://ec.europa.eu/eurostat/statistics-explained/index.php/Social_media_-_statistics_on_the_use_by_enterprises#Further_Eurostat_information . Accessed 29 April 2016García Fornes AM, Rodrigo Solaz M, Terrasa Barrena AM, Inglada J, Javier V, Jorge Cano J, Mulet Mengual L, Palomares Chust A, Búrdalo Rapa LA, Giret Boggino AS et al (2015) Magentix 2 user’s manualGolbeck J, Robles C, Turner K (2011) Predicting personality with social media. In: CHI’11, pp 253–262Guimerà R, Llorente A, Moro E, Sales-Pardo M (2012) Predicting human preferences using the block structure of complex social networks. PloS One 7(9):e44620Huberman BA, Romero DM, Wu F (2008) Social networks that matter: Twitter under the microscope. arXiv preprint arXiv:0812.1045Jamali M, Abolhassani H (2006) Different aspects of social network analysis. In: 2006 IEEE/WIC/ACM international conference on web intelligence (WI 2006 main conference proceedings)(WI’06). IEEE, pp 66–72Jiang Y, Jiang J (2014) Understanding social networks from a multiagent perspective. Parallel Distrib Syst IEEE Trans 25(10):2743–2759Kossinets G, Watts D (2006) Empirical analysis of an evolving social network. Science 311(5757):88–90Kumar R, Novak J, Tomkins A (2010) Structure and evolution of online social networks. In: Yu PS, Han J, Faloutsos C (eds) Link mining: models, algorithms, and applications. Springer, New York, pp 337–357Lazer D (2009) Life in the network: the coming age of computational social science. Science 323(5915):721–723Leskovec J, Adamic LA, Huberman BA (2007) The dynamics of viral marketing. ACM Trans Web 1(1):5Licoppe C, Smoreda Z (2005) Are social networks technologically embedded? How networks are changing today with changes in communication technology. Soc Netw 27(4):317–335Lotan G, Graeff E, Ananny M, Gaffney D, Pearce I, Boyd D (2011) The revolutions were tweeted: information flows during the 2011 tunisian and egyptian revolutions. Int J Commun 5:1375–1405Peña-López I, Congosto M, Aragón P (2013) Spanish indignados and the evolution of 15M: towards networked para-institutions. Big data: challenges and opportunities, pp 25–26Perliger A, Pedahzur A (2011) Social network analysis in the study of terrorism and political violence. PS Polit Sci Polit 44:45–50Romero DM, Galuba W, Asur S, Huberman BA (2011a) Influence and passivity in social media. In: Proceedings of the 20th WWW, pp 113–114Romero DM, Meeder B, Kleinberg J (2011b) Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on Twitter. In: Proceedings of the 20th WWW, pp 695–704Stockman FN, Doreian P, (1997) Evolution of social networks: processes and principles. In: Doreian P, Stokman FN (eds) Evolution of social networks. Routledge, London, pp 233–250Traud AL, Mucha PJ, Porter MA (2012) Social structure of facebook networks. Phys A Stat Mech Its Appl 391(16):4165–4180Ugander J, Karrer B, Backstrom L, Marlow C (2011) The anatomy of the Facebook social graph. arXiv preprint arXiv:1111.4503Valero S, del Val E, Alemany J, Botti V (2015) Using magentix2 in smart-home environments. In: 10th International conference on soft computing models in industrial and environmental applications. Springer, Berlin, pp 27–37Wasserman S, Faust K (1994) Social network analysis: methods and applications. Cambridge University Press, CambridgeWersm (2015) How much data is generated every minute on social media? http://wersm.com/how-much-data-is-generated-every-minute-on-social-media/ . Accessed 29 April 201

Social determinants of content selection in the age of (mis)information

Despite the enthusiastic rhetoric about the so called \emph{collective intelligence}, conspiracy theories -- e.g. global warming induced by chemtrails or the link between vaccines and autism -- find on the Web a natural medium for their dissemination. Users preferentially consume information according to their system of beliefs and the strife within users of opposite narratives may result in heated debates. In this work we provide a genuine example of information consumption from a sample of 1.2 million of Facebook Italian users. We show by means of a thorough quantitative analysis that information supporting different worldviews -- i.e. scientific and conspiracist news -- are consumed in a comparable way by their respective users. Moreover, we measure the effect of the exposure to 4709 evidently false information (satirical version of conspiracy theses) and to 4502 debunking memes (information aiming at contrasting unsubstantiated rumors) of the most polarized users of conspiracy claims. We find that either contrasting or teasing consumers of conspiracy narratives increases their probability to interact again with unsubstantiated rumors.Comment: misinformation, collective narratives, crowd dynamics, information spreadin

Intravesical rAd-IFNα/Syn3 for Patients With High-Grade, Bacillus Calmette-Guerin-Refractory or Relapsed Non-Muscle-Invasive Bladder Cancer: A Phase II Randomized Study.

Purpose Many patients with high-risk non-muscle-invasive bladder cancer (NMIBC) are either refractory to bacillus Calmette-Guerin (BCG) treatment or may experience disease relapse. We assessed the efficacy and safety of recombinant adenovirus interferon alfa with Syn3 (rAd-IFNα/Syn3), a replication-deficient recombinant adenovirus gene transfer vector, for patients with high-grade (HG) BCG-refractory or relapsed NMIBC. Methods In this open-label, multicenter (n = 13), parallel-arm, phase II study ( ClinicalTrials.gov identifier: NCT01687244), 43 patients with HG BCG-refractory or relapsed NMIBC received intravesical rAd-IFNα/Syn3 (randomly assigned 1:1 to 1 × 10(11) viral particles (vp)/mL or 3 × 10(11) vp/mL). Patients who responded at months 3, 6, and 9 were retreated at months 4, 7, and 10. The primary end point was 12-month HG recurrence-free survival (RFS). All patients who received at least one dose were included in efficacy and safety analyses. Results Forty patients received rAd-IFNα/Syn3 (1 × 10(11) vp/mL, n = 21; 3 × 10(11) vp/mL, n = 19) between November 5, 2012, and April 8, 2015. Fourteen patients (35.0%; 90% CI, 22.6% to 49.2%) remained free of HG recurrence 12 months after initial treatment. Comparable 12-month HG RFS was noted for both doses. Of these 14 patients, two experienced recurrence at 21 and 28 months, respectively, after treatment initiation, and one died as a result of an upper tract tumor at 17 months without a recurrence. rAd-IFNα/Syn3 was well tolerated; no grade four or five adverse events (AEs) occurred, and no patient discontinued treatment because of an adverse event. The most frequently reported drug-related AEs were micturition urgency (n = 16; 40%), dysuria (n = 16; 40%), fatigue (n = 13; 32.5%), pollakiuria (n = 11; 28%), and hematuria and nocturia (n = 10 each; 25%). Conclusion rAd-IFNα/Syn3 was well tolerated. It demonstrated promising efficacy for patients with HG NMIBC after BCG therapy who were unable or unwilling to undergo radical cystectomy

Relevance of positive cardiovascular outcome trial results in clinical practice: perspectives from the Academy for Cardiovascular Risk, Outcomes and Safety Studies in Type 2 Diabetes (ACROSS T2D).

Type 2 diabetes (T2D) imposes a substantial disease burden, predominantly from cardiovascular disease (CVD), which accounts for >50% of deaths in this population and leads to a 12-year reduction in the life expectancy of a 60-year-old male patient with T2D and CVD compared with the general population. The results from mandatory cardiovascular outcome trials (CVOTs) are therefore of great interest in the field. The Academy for Cardiovascular Risk, Outcomes and Safety Studies in Type 2 Diabetes meeting program aims to bring together experts from several associated disciplines to provide fair and balanced resources for those involved in the management of patients with T2D. This publication represents the opinions of the faculty on the key learnings from the meeting held in Vienna in the spring of 2017. In particular, we detail how data from the EMPA-REG OUTCOME® [cardiovascular outcomes trial of empagliflozin] and Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results (LEADER®) (liraglutide) CVOTs can be practically interpreted across clinical specialities. It is hoped that this translation of CVOT data will achieve a dual treatment paradigm for the management of both raised glucose levels and CV risk in patients with T2D