Detecting and Reducing Biases in Cellular-Based Mobility Data Sets

Correctly estimating the features characterizing human mobility from mobile phone traces is a key factor to improve the performance of mobile networks, as well as for mobility model design and urban planning. Most related works found their conclusions on location data based on the cells where each user sends or receives calls or messages, data known as Call Detail Records (CDRs). In this work, we test if such data sets provide enough detail on users' movements so as to accurately estimate some of the most studied mobility features. We perform the analysis using two different data sets, comparing CDRs with respect to an alternative data collection approach. Furthermore, we propose three filtering techniques to reduce the biases detected in the fraction of visits per cell, entropy and entropy rate distributions, and predictability. The analysis highlights the need for contextualizing mobility results with respect to the data used, since the conclusions are biased by the mobile phone traces collection approach.This research was partially funded by the Spanish Ministry of Economy, Industry and Competitiveness through TEC2017-84197-C4-1-R (Inteligencia de fuentes abiertas para redes electricas inteligentes seguras), TEC2014-54335-C4-2-R (INRISCO: INcident monitoRing In Smart COmmunities), and IPT-2011-1272-430000 (MONOLOC) projects

A Bandwidth-Efficient Dissemination Scheme of Non-Safety Information in Urban VANETs

The recent release of standards for vehicular communications will hasten the development of smart cities in the following years. Many applications for vehicular networks, such as blocked road warnings or advertising, will require multi-hop dissemination of information to all vehicles in a region of interest. However, these networks present special features and difficulties that may require special measures. The dissemination of information may cause broadcast storms. Urban scenarios are especially sensitive to broadcast storms because of the high density of vehicles in downtown areas. They also present numerous crossroads and signal blocking due to buildings, which make dissemination more difficult than in open, almost straight interurban roadways. In this article, we discuss several options to avoid the broadcast storm problem while trying to achieve the maximum coverage of the region of interest. Specifically, we evaluate through simulations different ways to detect and take advantage of intersections and a strategy based on store-carry-forward to overcome short disconnections between groups of vehicles. Our conclusions are varied, and we propose two different solutions, depending on the requirements of the application.This work was partially founded by the Spanish Ministry of Science and Innovation within the framework of projects TEC2010-20572-C02-01 “CONSEQUENCE” and TEC2014-54335-C4-2-R “INRISCO” and by the Regional Government of Madrid within the “eMadrid” project under Grants S2009/TIC-1650 and S2013/ICE-2715, including the costs to publish in open access

A hybrid analysis of LBSN data to early detect anomalies in crowd dynamics

Undoubtedly, Location-based Social Networks (LBSNs) provide an interesting source of geo-located data that we have previously used to obtain patterns of the dynamics of crowds throughout urban areas. According to our previous results, activity in LBSNs reflects the real activity in the city. Therefore, unexpected behaviors in the social media activity are a trustful evidence of unexpected changes of the activity in the city. In this paper we introduce a hybrid solution to early detect these changes based on applying a combination of two approaches, the use of entropy analysis and clustering techniques, on the data gathered from LBSNs. In particular, we have performed our experiments over a data set collected from Instagram for seven months in New York City, obtaining promising results.Ministerio de Economía y Competitividad | Ref. TEC2014-54335-C4-2-RMinisterio de Economía y Competitividad | Ref. TEC2014-54335-C4-3-RAgencia Estatal de Investigación | Ref. TEC2017-84197-C4-2-RAgencia Estatal de Investigación | Ref. TEC2017-84197-C4-3-

A hybrid analysis of LBSN data to early detect anomalies in crowd dynamics

Undoubtedly, Location-based Social Networks (LBSNs) provide an interesting source of geo-located data that we have previously used to obtain patterns of the dynamics of crowds throughout urban areas. According to our previous results, activity in LBSNs reflects the real activity in the city. Therefore, unexpected behaviors in the social media activity are a trustful evidence of unexpected changes of the activity in the city. In this paper we introduce a hybrid solution to early detect these changes based on applying a combination of two approaches, the use of entropy analysis and clustering techniques, on the data gathered from LBSNs. In particular, we have performed our experiments over a data set collected from Instagram for seven months in New York City, obtaining promising results.This work is funded by: the European Regional Development Fund (ERDF) and the Galician Regional Government under agreement for funding the Atlantic Research Center for Information and Communication Technologies (AtlantTIC), Spain, the Spanish Ministry of Economy and Competitiveness under the National Science Program (TEC2014-54335-C4-3-R, TEC2014-54335-C4-2-R, TEC2017-84197-C4-3-R and TEC2017-84197-C4-2-R), and by the Madrid Regional Government eMadrid Excellence Network, Spain (S2013/ICE-2715)

Impact of COVID-19 lockdown in telecommunications engineering competency-based alumni ranking

[EN] Higher education, as other social and economic sectors in Spain, was disrupted on 15th March 2020 following health emergency Laws enacted related to COVID-19. Non-presential lecturing was stablished country-wide until the end of the academic year 2019-20, as society was set in lockdown. In this context, it is necessary to evaluate the impact of the mandatory changes implemented in the education paradigm in order to assess the degree of acquisition of general and specific competencies altogether the acquisition of transversal competencies, as an important factor for the alumni career. This paper reports a comprehensive study on the competencies degree of acquisition considering the lockdown scenario in Spain. The results from the last four academic years have been comparatively evaluated in the core subject `Teoría de la Comunicación¿, lectured in the fourth semester of the Telecommunications Engineering Integrated Program (Bachelor and Master) in the Universitat Politècnica de València, Spain, comprising data from 745 alumni. The results indicate that the degree of acquisition of technical competencies in this scenario has been adequate, being marginally better compared to previous academic year, probably due to new lecturing materials prepared. Nevertheless, the acquisition of the transversal competency `analysis and problem solving¿ exhibits degraded results, indicating inhomogeneous acquisition probably due to limitations in the group-based problem-solving practice. The results suggest that specific materials and remote lecturing strategies should be developed and implemented to guarantee adequate acquisition levels.The support by the 2020 Science Parks program from the Consellería de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana, Spain, is acknowledged.Llorente, R.; Rodríguez-Hernández, MA.; Hernandez Franco, CA.; Sastre, J.; Carrión García, A.; Madrigal-Madrigal, J. (2020). Impact of COVID-19 lockdown in telecommunications engineering competency-based alumni ranking. IATED Academy. 9599-9607. https://doi.org/10.21125/iceri.2020.2139S9599960

Entropy-based privacy against profiling of user mobility

Location-based services (LBSs) flood mobile phones nowadays, but their use poses an evident privacy risk. The locations accompanying the LBS queries can be exploited by the LBS provider to build the user profile of visited locations, which might disclose sensitive data, such as work or home locations. The classic concept of entropy is widely used to evaluate privacy in these scenarios, where the information is represented as a sequence of independent samples of categorized data. However, since the LBS queries might be sent very frequently, location profiles can be improved by adding temporal dependencies, thus becoming mobility profiles, where location samples are not independent anymore and might disclose the user's mobility patterns. Since the time dimension is factored in, the classic entropy concept falls short of evaluating the real privacy level, which depends also on the time component. Therefore, we propose to extend the entropy-based privacy metric to the use of the entropy rate to evaluate mobility profiles. Then, two perturbative mechanisms are considered to preserve locations and mobility profiles under gradual utility constraints. We further use the proposed privacy metric and compare it to classic ones to evaluate both synthetic and real mobility profiles when the perturbative methods proposed are applied. The results prove the usefulness of the proposed metric for mobility profiles and the need for tailoring the perturbative methods to the features of mobility profiles in order to improve privacy without completely loosing utility.This work is partially supported by the Spanish Ministry of Science and Innovation through the CONSEQUENCE (TEC2010-20572-C02-01/02) and EMRISCO (TEC2013-47665-C4-4-R) projects.The work of Das was partially supported by NSF Grants IIS-1404673, CNS-1355505, CNS-1404677 and DGE-1433659. Part of the work by Rodriguez-Carrion was conducted while she was visiting the Computer Science Department at Missouri University of Science and Technology in 2013–2014

EoE CONNECT, the European Registry of Clinical, Environmental, and Genetic Determinants in Eosinophilic Esophagitis: rationale, design, and study protocol of a large-scale epidemiological study in Europe

Background: The growing prevalence of eosinophilic esophagitis (EoE) represents a considerable burden to patients and health care systems. Optimizing cost-effective management and identifying mechanisms for disease onset and progression are required. However, the paucity of large patient cohorts and heterogeneity of practice hinder the defining of optimal management of EoE. Methods: EoE CONNECT is an ongoing, prospective registry study initiated in 2016 and currently managed by EUREOS, the European Consortium for Eosinophilic Diseases of the Gastrointestinal Tract. Patients are managed and treated by their responsible specialists independently. Data recorded using a web-based system include demographic and clinical variables; patient allergies; environmental, intrapartum, and early life exposures; and family background. Symptoms are structurally assessed at every visit; endoscopic features and histological findings are recorded for each examination. Prospective treatment data are registered sequentially, with new sequences created each time a different treatment (active principle, formulation, or dose) is administered to a patient. EoE CONNECT database is actively monitored to ensure the highest data accuracy and the highest scientific and ethical standards. Results: EoE CONNECT is currently being conducted at 39 centers in Europe and enrolls patients of all ages with EoE. In its aim to increase knowledge, to date EoE CONNECT has provided evidence on the effectiveness of first- and second-line therapies for EoE in clinical practice, the ability of proton pump inhibitors to induce disease remission, and factors associated with improved response. Drug effects to reverse fibrous remodeling and endoscopic features of fibrosis in EoE have also been assessed. Conclusion: This prospective registry study will provide important information on the epidemiological and clinical aspects of EoE and evidence as to the real-world and long-term effectiveness and safety of therapy. These data will potentially be a vital benchmark for planning future EoE health care services in Europe

Accurate and timely diagnosis of Eosinophilic Esophagitis improves over time in Europe. An analysis of the EoE CONNECT Registry

BACKGROUND: Poor adherence to clinical practice guidelines for eosinophilic esophagitis (EoE) has been described and the diagnostic delay of the disease continues to be unacceptable in many settings. OBJECTIVE: To analyze the impact of improved knowledge provided by the successive international clinical practice guidelines on reducing diagnostic delay and improving the diagnostic process for European patients with EoE. METHODS: Cross‐sectional analysis of the EoE CONNECT registry based on clinical practice. Time periods defined by the publication dates of four major sets of guidelines over 10 years were considered. Patients were grouped per time period according to date of symptom onset. RESULTS: Data from 1,132 patients was analyzed and median (IQR) diagnostic delay in the whole series was 2.1 (0.7‐6.2) years. This gradually decreased over time with subsequent release of new guidelines (p < 0.001), from 12.7 years up to 2007 to 0.7 years after 2017. The proportion of patients with stricturing of mixed phenotypes at the point of EoE diagnosis also decreased over time (41.3% vs. 16%; p < 0.001), as did EREFS scores. The fibrotic sub‐score decreased from a median (IQR) of 2 (1‐2) to 0 (0‐1) when patients whose symptoms started up to 2007 and after 2017 were compared (p < 0.001). In parallel, symptoms measured with the Dysphagia Symptoms Score reduced significantly when patients with symptoms starting before 2007 and after 2012 were compared. A reduction in the number of endoscopies patients underwent before the one that achieved an EoE diagnosis, and the use of allergy testing as part of the diagnostic workout of EoE, also reduced significantly over time (p = 0.010 and p < 0.001, respectively). CONCLUSION: The diagnostic work‐up of EoE patients improved substantially over time at the European sites contributing to EoE CONNECT, with a dramatic reduction in diagnostic delay

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio