Evolution of Privacy Loss in Wikipedia

The cumulative effect of collective online participation has an important and adverse impact on individual privacy. As an online system evolves over time, new digital traces of individual behavior may uncover previously hidden statistical links between an individual's past actions and her private traits. To quantify this effect, we analyze the evolution of individual privacy loss by studying the edit history of Wikipedia over 13 years, including more than 117,523 different users performing 188,805,088 edits. We trace each Wikipedia's contributor using apparently harmless features, such as the number of edits performed on predefined broad categories in a given time period (e.g. Mathematics, Culture or Nature). We show that even at this unspecific level of behavior description, it is possible to use off-the-shelf machine learning algorithms to uncover usually undisclosed personal traits, such as gender, religion or education. We provide empirical evidence that the prediction accuracy for almost all private traits consistently improves over time. Surprisingly, the prediction performance for users who stopped editing after a given time still improves. The activities performed by new users seem to have contributed more to this effect than additional activities from existing (but still active) users. Insights from this work should help users, system designers, and policy makers understand and make long-term design choices in online content creation systems

An ERP Study in English Relative Clause Processing by Chinese-English Bilinguals*

Abstract The processing of relative clauses receives much concern from linguists. The finding that object relatives are easier to process than subject relatives in Chinese challenges the notion that subject relative clauses are preferred universally. A large body of literature provides theories related to sentence processing mechanisms for native speakers but leaves one area relatively untouched: how bilinguals process sentences. This study is designed to examine the case where the individuals with a Chinese L1 language background process subject-extracted subject relative clauses (SS) and subject-extracted object relative clauses (SO) by using eventrelated potentials (ERPs) to probe into the real-time language processing and presents a direct manifestation of brain activity. The findings from this study support the subject relative clause preference due to the strong influence of English relative clause markedness and bilinguals' relative lower working memory capacity

A Consensus List of Ultrasound Competencies for Graduating Emergency Medicine Residents

Objectives: Emergency ultrasound (EUS) is a critical component of emergency medicine (EM) resident education. Currently, there is no consensus list of competencies for EUS training, and graduating residents have varying levels of skill and comfort. The objective of this study was to define a widely accepted comprehensive list of EUS competencies for graduating EM residents through a modified Delphi method. Methods: We developed a list of EUS applications through a comprehensive literature search, the American College of Emergency Physicians list of core EUS benchmarks, and the Council of Emergency Medicine Residency-Academy of Emergency Ultrasound consensus document. We assembled a multi-institutional expert panel including 15 faculty members from diverse practice environments and geographical regions. The panel voted on the list of competencies through two rounds of a modified Delphi process using a modified Likert scale (1 = not at all important, 5 = very important) to determine levels of agreement for each application-with revisions occurring between the two rounds. High agreement for consensus was set at \u3e80%. Results: Fifteen of 15 panelists completed the first-round survey (100%) that included 359 topics related to EUS. After the first round, 195 applications achieved high agreement, four applications achieved medium agreement, and 164 applications achieved low agreement. After the discussion, we removed three questions and added 13 questions. Fifteen of 15 panelists completed the second round of the survey (100%) with 209 of the 369 applications achieving consensus. Conclusion: Our final list represents expert opinion on EUS competencies for graduating EM residents. We hope to use this consensus list to implement a more consistent EUS curriculum for graduating EM residents and to standardize EUS training across EM residency programs

Mining Big Data for Tourist Hot Spots: Geographical Patterns of Online Footprints

Understanding the complex, and often unequal, spatiality of tourist demand in urban contexts requires other methodologies, among which the information base available online and in social networks has gained prominence. Innovation supported by Information and Communication Technologies in terms of data access and data exchange has emerged as a complementary supporting tool for the more traditional data collection techniques currently in use, particularly, in urban destinations where there is the need to more (near)real-time monitoring. The capacity to collect and analise massive amounts of data on individual and group behaviour is leading to new data-rich research approaches. This chapter addresses the potential for discovering geographical insights regarding tourists’ spatial patterns within a destination, based on the analysis of geotagged data available from two social networks. ·info:eu-repo/semantics/publishedVersio

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Transition of ductile and brittle fracture during DWTT by FEM

Globally, steel pipelines are widely used to transport energy in the form of liquid petroleum and natural gas. The steel used in the manufacture of these pipelines must have high strength and toughness, and high resistance to fracture. The Drop Weight Tear Test (DWTT) is the most widely used test to assess brittle fracture characteristics in steel. The zones of ductile and brittle fracture during DWTT characterize the quality of pipeline steels. In this paper, the Gurson-Tvergaard-Needleman (GTN) fracture models are coupled in a Finite Element model. The ductile and brittle fracture zones in the samples are analyzed under different conditions. The results show that the change in fracture mode during the DWTT is from the brittle to the ductile, then again to the brittle. The calculated absorbed energies during DWTT compare well with experimental findings. Finally, we present an analysis of the transition from ductile to brittle fracture under different conditions