scispace - formally typeset
Search or ask a question

Showing papers by "Open University of Catalonia published in 2019"


Journal ArticleDOI
TL;DR: Results of this study led to improve the content validity of this tool, revise it, and propose a new version (MMAT version 2018) by identifying relevant methodological criteria for appraising the quality of qualitative, survey, and mixed methods studies.

367 citations


Journal ArticleDOI
TL;DR: In this paper, a systematic literature review shows that many highly cited sensitivity analysis methods fail to properly explore the space of the input factors, leading to a worrying lack of standards and recognized good practices.
Abstract: Sensitivity analysis provides information on the relative importance of model input parameters and assumptions. It is distinct from uncertainty analysis, which addresses the question ‘How uncertain is the prediction?’ Uncertainty analysis needs to map what a model does when selected input assumptions and parameters are left free to vary over their range of existence, and this is equally true of a sensitivity analysis. Despite this, many uncertainty and sensitivity analyses still explore the input space moving along one-dimensional corridors leaving space of the input factors mostly unexplored. Our extensive systematic literature review shows that many highly cited papers (42% in the present analysis) fail the elementary requirement to properly explore the space of the input factors. The results, while discipline-dependent, point to a worrying lack of standards and recognized good practices. We end by exploring possible reasons for this problem, and suggest some guidelines for proper use of the methods.

321 citations


Proceedings ArticleDOI
15 Jun 2019
TL;DR: This work proposes a Recurrent network for multiple object Video Object Segmentation (RVOS) that is fully end-to-end trainable and achieves faster inference runtimes than previous methods, reaching 44ms/frame on a P100 GPU.
Abstract: Multiple object video object segmentation is a challenging task, specially for the zero-shot case, when no object mask is given at the initial frame and the model has to find the objects to be segmented along the sequence. In our work, we propose a Recurrent network for multiple object Video Object Segmentation (RVOS) that is fully end-to-end trainable. Our model incorporates recurrence on two different domains: (i) the spatial, which allows to discover the different object instances within a frame, and (ii) the temporal, which allows to keep the coherence of the segmented objects along time. We train RVOS for zero-shot video object segmentation and are the first ones to report quantitative results for DAVIS-2017 and YouTube-VOS benchmarks. Further, we adapt RVOS for one-shot video object segmentation by using the masks obtained in previous time steps as inputs to be processed by the recurrent module. Our model reaches comparable results to state-of-the-art techniques in YouTube-VOS benchmark and outperforms all previous video object segmentation methods not using online learning in the DAVIS-2017 benchmark. Moreover, our model achieves faster inference runtimes than previous methods, reaching 44ms/frame on a P100 GPU.

202 citations


Journal ArticleDOI
08 Oct 2019
TL;DR: The relationship between people and nature has been experienced and conceptualized in mul... as mentioned in this paper, where the relationship between humans and nature is discussed in the context of human existence and wellbeing, and people depend on functioning ecosystems, which provide benefits that support human existence.
Abstract: People depend on functioning ecosystems, which provide benefits that support human existence and wellbeing. The relationship between people and nature has been experienced and conceptualized in mul...

138 citations


Journal ArticleDOI
TL;DR: A conceptual model suggests a dual route of influence of VR on consumers' purchase intention in virtual stores: one through emotions and sense of presence and the other through the affect evoked by the virtual environment and brand recall.

103 citations


Journal ArticleDOI
TL;DR: This article analyses the pre-existing works to determine their role in Decentralised Cloud and future computing development and indicates which models represent a significant breakthrough from a Cloud perspective.
Abstract: Cloud computing emerged as a centralised paradigm that made “infinite” computing resources available on demand. Nevertheless, the ever-increasing computing capacities present on smart connected things and devices calls for the decentralisation of Cloud computing to avoid unnecessary latencies and fully exploit accessible computing capacities at the edges of the network. Whilst these decentralised Cloud models represent a significant breakthrough from a Cloud perspective, they are rooted in existing research areas such as Mobile Cloud Computing, Mobile Ad hoc Computing, and Edge computing. This article analyses the pre-existing works to determine their role in Decentralised Cloud and future computing development.

101 citations


Journal ArticleDOI
TL;DR: The changes in brain structure and function that a woman undergoes during the peripartum period are reviewed, outlining associations between these neural alterations and different aspects of maternal care.
Abstract: Pregnancy and the postpartum period involve numerous physiological adaptations that enable the development and survival of the offspring A distinct neural plasticity characterizes the female brain during this period, and dynamic structural and functional changes take place that accompany fundamental behavioral adaptations, stimulating the female to progress from an individual with self-directed needs to being responsible for the care of another life While many animal studies detail these modifications, an emerging body of research reveals the existence of reproduction-related brain plasticity in human mothers too Additionally, associations with aspects of maternal caregiving point to adaptive changes that benefit a woman’s transition to motherhood However, the dynamic changes that affect a woman’s brain are not merely adaptive, and they likely confer a vulnerability for the development of mental disorders Here, we review the changes in brain structure and function that a woman undergoes during the peripartum period, outlining associations between these neural alterations and different aspects of maternal care We additionally discuss peripartum mood disorders and postpartum psychosis, and review the neuroimaging studies that investigate the neural bases of these conditions

101 citations


Journal ArticleDOI
01 Aug 2019-Brain
TL;DR: Established MRI measures, available in routine clinical practice, may be useful in counselling patients with early multiple sclerosis about long-term prognosis, and personalizing treatment plans.
Abstract: The clinical course of relapse-onset multiple sclerosis is highly variable. Demographic factors, clinical features and global brain T2 lesion load have limited value in counselling individual patients. We investigated early MRI predictors of key long-term outcomes including secondary progressive multiple sclerosis, physical disability and cognitive performance, 15 years after a clinically isolated syndrome. A cohort of patients with clinically isolated syndrome (n = 178) was prospectively recruited within 3 months of clinical disease onset and studied with MRI scans of the brain and spinal cord at study entry (baseline) and after 1 and 3 years. MRI measures at each time point included: supratentorial, infratentorial, spinal cord and gadolinium-enhancing lesion number, brain and spinal cord volumetric measures. The patients were followed-up clinically after ∼15 years to determine disease course, and disability was assessed using the Expanded Disability Status Scale, Paced Auditory Serial Addition Test and Symbol Digit Modalities Test. Multivariable logistic regression and multivariable linear regression models identified independent MRI predictors of secondary progressive multiple sclerosis and Expanded Disability Status Scale, Paced Auditory Serial Addition Test and Symbol Digit Modalities Test, respectively. After 15 years, 166 (93%) patients were assessed clinically: 119 (72%) had multiple sclerosis [94 (57%) relapsing-remitting, 25 (15%) secondary progressive], 45 (27%) remained clinically isolated syndrome and two (1%) developed other disorders. Physical disability was overall low in the multiple sclerosis patients (median Expanded Disability Status Scale 2, range 0-10); 71% were untreated. Baseline gadolinium-enhancing (odds ratio 3.16, P < 0.01) and spinal cord lesions (odds ratio 4.71, P < 0.01) were independently associated with secondary progressive multiple sclerosis at 15 years. When considering 1- and 3-year MRI variables, baseline gadolinium-enhancing lesions remained significant and new spinal cord lesions over time were associated with secondary progressive multiple sclerosis. Baseline gadolinium-enhancing (β = 1.32, P < 0.01) and spinal cord lesions (β = 1.53, P < 0.01) showed a consistent association with Expanded Disability Status Scale at 15 years. Baseline gadolinium-enhancing lesions was also associated with performance on the Paced Auditory Serial Addition Test (β = - 0.79, P < 0.01) and Symbol Digit Modalities Test (β = -0.70, P = 0.02) at 15 years. Our findings suggest that early focal inflammatory disease activity and spinal cord lesions are predictors of very long-term disease outcomes in relapse-onset multiple sclerosis. Established MRI measures, available in routine clinical practice, may be useful in counselling patients with early multiple sclerosis about long-term prognosis, and personalizing treatment plans.

98 citations


Journal ArticleDOI
TL;DR: Adherence to the MD significantly decreased between 1961–65 and 2000–03, whereas from 2004–2011 there was a stabilization of MAI values and even an increase among 16 countries.
Abstract: From the 1960s to the early 21st-century adherence to the Mediterranean diet (MD) declined around the world. This was partly due to the westernization of eating habits. However, in the last decade a new variable came into play, the economic crisis, which may have affected dietary patterns. We analyzed worldwide trends of adherence to the MD between the periods 1961–1965, 2000–2003 and 2004–2011. Data was obtained from the Food and Agriculture Organization Food Balance Sheets in three study periods: 1961–1965, 2000–2003 and 2004–2011. The Mediterranean Adequacy Index (MAI) was calculated for 41 selected countries using the averages of available energy intake for different food groups. Changes in MAI indicated the trends in adherence in the different periods. In many countries, MAI deteriorated from 1961 to 1965 and 2004 to 2011, yet an increase was observed in 16 countries. Between the last two observation periods, MAI values stabilized in 16 of the 41 selected countries. Regional rankings for the three study periods based on descending MAI scores were: Southern Mediterranean, Mediterranean Europe, Central Europe and Northern Europe. Adherence to the MD significantly decreased between 1961–65 and 2000–03, whereas from 2004–2011 there was a stabilization of MAI values and even an increase among 16 countries. Efforts are needed to preserve the dietary traditions and lifestyle habits within the Mediterranean region in order to counteract increasing rates of chronic disease.

98 citations


Journal ArticleDOI
TL;DR: Empirically explore the boundaries of narrow band-Internet of Things technology, analyzing from a user’s point of view critical characteristics such as energy consumption, reliability, and delays, and show that its performance in terms of energy is comparable and even outperforms an LPWAN reference technology like LoRa.
Abstract: Narrow band-Internet of Things (NB-IoT) has just joined the low power wide area network (LPWAN) community. Unlike most of its competitors, NB-IoT did not emerge from a blank slate. Indeed, it is closely linked to Long Term Evolution (LTE), from which it inherits many of the features that undoubtedly determine its behavior. In this paper, we empirically explore the boundaries of this technology, analyzing from a user’s point of view critical characteristics such as energy consumption, reliability, and delays. The results show that its performance in terms of energy is comparable and even outperforms, in some cases, an LPWAN reference technology like LoRa, with the added benefit of guaranteeing delivery. However, the high variability observed in both energy expenditure and network delays call into question its suitability for some applications, especially those subject to service-level agreements.

96 citations


Journal ArticleDOI
TL;DR: IFN1 and IFN2 pathways are differentially activated in different forms of myositis, which may have therapeutic implications because immunosuppressive medications may preferentially target each of these pathways.
Abstract: Objective Activation of the type 1 interferon (IFN1) pathway is a prominent feature of dermatomyositis (DM) muscle and may play a role in the pathogenesis of this disease. However, the relevance of the IFN1 pathway in patients with other types of myositis such as the antisynthetase syndrome (AS), immune-mediated necrotizing myopathy (IMNM), and inclusion body myositis (IBM) is largely unknown. Moreover, the activation of the type 2 interferon (IFN2) pathway has not been comprehensively explored in myositis. In this cross-sectional study, our objective was to determine whether IFN1 and IFN2 pathways are differentially activated in different types of myositis by performing RNA sequencing on muscle biopsy samples from 119 patients with DM, IMNM, AS, or IBM and on 20 normal muscle biopsies. Methods The expression of IFN1- and IFN2-inducible genes was compared between the different groups. Results The expression of IFN1-inducible genes was high in DM, moderate in AS, and low in IMNM and IBM. In contrast, the expression of IFN2-inducible genes was high in DM, IBM, and AS but low in IMNM. The expression of IFN-inducible genes correlated with the expression of genes associated with inflammation and muscle regeneration. Of note, ISG15 expression levels alone performed as well as composite scores relying on multiple genes to monitor activation of the IFN1 pathway in myositis muscle biopsies. Conclusions IFN1 and IFN2 pathways are differentially activated in different forms of myositis. This observation may have therapeutic implications because immunosuppressive medications may preferentially target each of these pathways.

Journal ArticleDOI
TL;DR: Anti-Ro52 autoantibodies are present in 14% of patients with juvenile myositis and are strongly associated with anti-MDA5 and antiaminoacyl tRNA synthetase autoantibia, which are associated with more severe interstitial lung disease and a poorer prognosis.
Abstract: Objectives Anti-Ro52 autoantibodies are associated with more severe interstitial lung disease (ILD) in adult myositis patients with antiaminoacyl transfer (t)RNA synthetase autoantibodies. However, few studies have examined anti-Ro52 autoantibodies in juvenile myositis. The purpose of this study was to define the prevalence and clinical features associated with anti-Ro52 autoantibodies in a large cohort of patients with juvenile myositis. Methods We screened sera from 302 patients with juvenile dermatomyositis (JDM), 25 patients with juvenile polymyositis (JPM) and 44 patients with juvenile connective tissue disease–myositis overlap (JCTM) for anti-Ro52 autoantibodies by ELISA. Clinical characteristics were compared between myositis patients with and without anti-Ro52 autoantibodies. Results Anti-Ro52 autoantibodies were found in 14% patients with JDM, 12% with JPM and 18% with JCTM. Anti-Ro52 autoantibodies were more frequent in patients with antiaminoacyl tRNA synthetase (64%, p Conclusions Anti-Ro52 autoantibodies are present in 14% of patients with juvenile myositis and are strongly associated with anti-MDA5 and antiaminoacyl tRNA synthetase autoantibodies. In all patients with juvenile myositis, those with anti-Ro52 autoantibodies were more likely to have ILD. Furthermore, patients with anti-Ro52 autoantibodies have more severe disease and a poorer prognosis.

Journal ArticleDOI
TL;DR: This work contributes to HCI research by further validating the utility of the Gamification User Types Hexad scale, potentially affording researchers a deeper understanding of the mechanisms and effects of gameful interventions.
Abstract: Gamification, the use of game elements in non-game systems, is now established as a relevant research field in human-computer interaction (HCI). Several empirical studies have shown that gameful interventions can increase engagement and generate desired behavioral outcomes in HCI applications. However, some inconclusive results indicate that we need a fuller understanding of the mechanisms and effects of gamification. The Gamification User Types Hexad scale allows us to parse different user motivations in participants’ interactions with gameful applications, which are measured using a self-report questionnaire. Each user type represents a style of interaction with gameful applications, for example, if the interactions are more focused on achievements, socialization, or rewards. Thus, by scoring an individual in each one of the user types of the Hexad model, we can establish a profile of user preferences for gameful interactions. However, we still lack a substantial empirical validation of this scale. Therefore, we set out to validate the factor structure of the scale, in both English and Spanish, by conducting three studies, which also investigated the distribution of the Hexad's user types in the sample. Our findings support the structural validity of the scale, as well as suggesting opportunities for improvement. Furthermore, we demonstrate that some user types are more common than others and that gender and age correlate with a person's user types. Our work contributes to HCI research by further validating the utility of the Gamification User Types Hexad scale, potentially affording researchers a deeper understanding of the mechanisms and effects of gameful interventions.

Journal ArticleDOI
TL;DR: In this article, the authors explored the sustainability beliefs, attitudes, social norms, perceived behavioral controls, and behavioral intentions of accommodation managers and considered how these relate to their uptake of water-related innovations.
Abstract: Drawing on Taylor and Todd’s “decomposed theory of planned behavior,” this study explores the sustainability beliefs, attitudes, social norms, perceived behavioral controls, and behavioral intentions of accommodation managers and considers how these relate to their uptake of water-related innovations. An online survey is used to capture data from more than 300 accommodation establishments located in Catalonia (Spain). Using a structural equation model to interpret the data, 17 hypotheses are established, of which 15 are found to be significant. The findings show how the second-order constructs informed by organizational innovation literature explain the attitudes, social norms, and perceived behavioral controls of the managers; these factors inform 56% of the sustainability behavioral intentions. We explore the cognitive mechanisms that motivate managers to introduce sustainability practices in their businesses. We contribute to theory by demonstrating the benefits of studying the belief structures that inform taking sustainability actions from the perspective of innovation

Journal ArticleDOI
TL;DR: There is high level of evidence showing that MedDiet adherence plays a role in the primary and secondary prevention of cardiovascular disease (CVD) and improves health in overweight and obese patients, and moderate-to-high evidence that the MedD diet prevents increases in weight and waist circumference in non-obese individuals, and improves metabolic syndrome (MetS) and reduces its incidence.
Abstract: The Mediterranean Diet (MedDiet) has been promoted as a means of preventing and treating cardiodiabesity. The aim of this study was to answer a number of key clinical questions (CQs) about the role of the MedDiet in cardiodiabesity in order to provide a framework for the development of clinical practice guidelines. A systematic review was conducted to answer five CQs formulated using the Patient, Intervention, Comparison, and Outcome (PICO) criteria. Twenty articles published between September 2013 and July 2016 were included, adding to the 37 articles from the previous review. There is a high level of evidence showing that MedDiet adherence plays a role in the primary and secondary prevention of cardiovascular disease (CVD) and improves health in overweight and obese patients. There is moderate-to-high evidence that the MedDiet prevents increases in weight and waist circumference in non-obese individuals, and improves metabolic syndrome (MetS) and reduces its incidence. Finally, there is moderate evidence that the MedDiet plays primary and secondary roles in the prevention of type 2 diabetes mellitus (T2DM). The MedDiet is effective in preventing obesity and MetS in healthy and at-risk individuals, in reducing mortality risk in overweight or obese individuals, in decreasing the incidence of T2DM and CVD in healthy individuals, and in reducing symptom severity in individuals with T2DM or CVD.

Journal ArticleDOI
TL;DR: This paper analyzes different cooperation scenarios concerning integrated routing and facility-location decisions in road transportation and proposes a hybrid metaheuristic algorithm, combining biased randomization with a variable neighborhood search framework, to solve each scenario.

Journal ArticleDOI
TL;DR: A simheuristic algorithm, which integrates Monte Carlo simulation within an iterated local search, is proposed, which can improve the initial solution with reasonable computational times and is applicable to other domains where a multi-period PIRP with stochastic demands may appear.

Journal ArticleDOI
TL;DR: How analytic indicators of engagement have previously been applied across clinical and technological contexts are consolidated to inform how they might be optimally applied in future evaluations of consumer mHealth apps for chronic conditions is consolidated.
Abstract: Background: There is mixed evidence to support current ambitions for mobile health (mHealth) apps to improve chronic health and well-being. One proposed explanation for this variable effect is that users do not engage with apps as intended. The application of analytics, defined as the use of data to generate new insights, is an emerging approach to study and interpret engagement with mHealth interventions. Objective: This study aimed to consolidate how analytic indicators of engagement have previously been applied across clinical and technological contexts, to inform how they might be optimally applied in future evaluations. Methods: We conducted a scoping review to catalog the range of analytic indicators being used in evaluations of consumer mHealth apps for chronic conditions. We categorized studies according to app structure and application of engagement data and calculated descriptive data for each category. Chi-square and Fisher exact tests of independence were applied to calculate differences between coded variables. Results: A total of 41 studies met our inclusion criteria. The average mHealth evaluation included for review was a two-group pretest-posttest randomized controlled trial of a hybrid-structured app for mental health self-management, had 103 participants, lasted 5 months, did not provide access to health care provider services, measured 3 analytic indicators of engagement, segmented users based on engagement data, applied engagement data for descriptive analyses, and did not report on attrition. Across the reviewed studies, engagement was measured using the following 7 analytic indicators: the number of measures recorded (76%, 31/41), the frequency of interactions logged (73%, 30/41), the number of features accessed (49%, 20/41), the number of log-ins or sessions logged (46%, 19/41), the number of modules or lessons started or completed (29%, 12/41), time spent engaging with the app (27%, 11/41), and the number or content of pages accessed (17%, 7/41). Engagement with unstructured apps was mostly measured by the number of features accessed (8/10, P=.04), and engagement with hybrid apps was mostly measured by the number of measures recorded (21/24, P=.03). A total of 24 studies presented, described, or summarized the data generated from applying analytic indicators to measure engagement. The remaining 17 studies used or planned to use these data to infer a relationship between engagement patterns and intended outcomes. Conclusions: Although researchers measured on average 3 indicators in a single study, the majority reported findings descriptively and did not further investigate how engagement with an app contributed to its impact on health and well-being. Researchers are gaining nuanced insights into engagement but are not yet characterizing effective engagement for improved outcomes. Raising the standard of mHealth app efficacy through measuring analytic indicators of engagement may enable greater confidence in the causal impact of apps on improved chronic health and well-being.

Journal ArticleDOI
TL;DR: While the crisis of statistics has made it to the headlines, that of mathematical modelling hasn’t, something can be learned comparing the two, and looking at other instances of production of numbers can help.
Abstract: While the crisis of statistics has made it to the headlines, that of mathematical modelling hasn’t. Something can be learned comparing the two, and looking at other instances of production of numbers.Sociology of quantification and post-normal science can help.

Journal ArticleDOI
TL;DR: The authors applied the findings obtained in a need analysis in the domain of a hotel receptionist's job to the design of pedagogic tasks to obtain insights into what tasks are done in this domain (task selection), what kind of language use is associated with these tasks, and how the information about perceived difficulty of tasks can be translated into instructionally manipulable variables.
Abstract: Needs analysis (NA) has long been argued to be the prerequisite for the design of language curricula or syllabi and the selection of tasks. According to Long (2005), a one-size-fits-all approach should be substituted by a careful examination of learners’ needs in a particular domain or learner community. Despite the increasing practice of carrying out a NA as a first step in curriculum design, it is still unclear how exactly the insights obtained from NA can be used in meaningful ways to take informed decisions about task and syllabus design. This study attempts to fill this gap by applying the findings obtained in a NA in the domain of a hotel receptionist’s job to the design of pedagogic tasks. The goals of this study were to obtain insights into what tasks are done in this domain (task selection), what kind of language use is associated with these tasks (task discourse analysis), how the information about perceived difficulty of tasks can be translated into instructionally manipulable variables (task d...

Journal ArticleDOI
TL;DR: It is pointed out that Internet technologies enhance job satisfaction by improving access to data and information, creating new activities and opportunities, and facilitating communication and social interactions, however, the results also suggest that these positive effects are skewed.

Journal ArticleDOI
TL;DR: The usefulness of learning analytics tools are revealed to gain a more wide and holistic view of the learning process of students, discovering new aspects that affect students’ learning results.

Journal ArticleDOI
TL;DR: A new adaptive predictive model is presented based only on students’ grades specifically trained for each course, focusing on dashboards visualization for stakeholders and an early feedback prediction system to intervene in the case of at-risk identification.
Abstract: Identifying at-risk students as soon as possible is a challenge in educational institutions. Decreasing the time lag between identification and real at-risk state may significantly reduce the risk of failure or disengage. In small courses, their identification is relatively easy, but it is impractical on larger ones. Current Learning Management Systems store a large amount of data that could help to generate predictive models to early identification of students in online and blended learning. The contribution of this paper is twofold: First, a new adaptive predictive model is presented based only on students’ grades specifically trained for each course. A deep analysis is performed in the whole institution to evaluate its performance accuracy. Second, an early warning system is developed, focusing on dashboards visualization for stakeholders (i.e., students and teachers) and an early feedback prediction system to intervene in the case of at-risk identification. The early warning system has been evaluated in a case study on a first-year undergraduate course in computer science. We show the accuracy of the correct identification of at-risk students, the students’ appraisal, and the most common factors that lead to at-risk level.

Journal ArticleDOI
TL;DR: The results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon.
Abstract: The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75 th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future.

Journal ArticleDOI
TL;DR: This work aims to determine the long‐term clinical outcomes in MS, and to identify early prognostic features of these outcomes.
Abstract: Objective Clinical outcomes in multiple sclerosis (MS) are highly variable. We aim to determine the long-term clinical outcomes in MS, and to identify early prognostic features of these outcomes. Methods One hundred thirty-two people presenting with a clinically isolated syndrome were prospectively recruited between 1984 and 1987, and followed up clinically and radiologically 1, 5, 10, 14, 20, and now 30 years later. All available notes and magnetic resonance imaging scans were reviewed, and MS was defined according to the 2010 McDonald criteria. Results Clinical outcome data were obtained in 120 participants at 30 years. Eighty were known to have developed MS by 30 years. Expanded Disability Status Scale (EDSS) scores were available in 107 participants, of whom 77 had MS; 32 (42%) remained fully ambulatory (EDSS scores ≤3.5), all of whom had relapsing-remitting MS (RRMS), 3 (4%) had RRMS and EDSS scores >3.5, 26 (34%) had secondary progressive MS (all had EDSS scores >3.5), and MS contributed to death in 16 (20%). Of those with MS, 11 received disease-modifying therapy. The strongest early predictors (within 5 years of presentation) of secondary progressive MS at 30 years were presence of baseline infratentorial lesions and deep white matter lesions at 1 year. Interpretation Thirty years after onset, in a largely untreated cohort, there was a divergence of MS outcomes; some people accrued substantial disability early on, whereas others ran a more favorable long-term course. These outcomes could, in part, be predicted by radiological findings from within 1 year of first presentation. ANN NEUROL 2020;87:63-74.

Proceedings ArticleDOI
02 Jul 2019
TL;DR: In this article, the balance of the pair of nodes of a given channel (i.e., the bandwidth of the channel in each direction) is kept secret to preserve users' privacy.
Abstract: The Lightning Network is a second layer technology running on top of Bitcoin and other Blockchains. It is composed of a peer-to-peer network, used to transfer raw information data. Some of the links in the peer-to-peer network are identified as payment channels, used to conduct payments between two Lightning Network clients (i.e., the two nodes of the channel). Payment channels are created with a fixed credit amount, the channel capacity. The channel capacity, together with the IP address of the nodes, is published to allow a routing algorithm to find an existing path between two nodes that do not have a direct payment channel. However, to preserve users' privacy, the precise balance of the pair of nodes of a given channel (i.e. the bandwidth of the channel in each direction), is kept secret. Since balances are not announced, second-layer nodes probe routes iteratively, until they find a successful route to the destination for the amount required, if any. This feature makes the routing discovery protocol less efficient but preserves the privacy of channel balances. In this paper, we present an attack to disclose the balance of a channel in the Lightning Network. Our attack is based on performing multiple payments ensuring that none of them is finalized, minimizing the economical cost of the attack. We present experimental results that validate our claims, and countermeasures to handle the attack.


Journal ArticleDOI
TL;DR: Findings support RV as a candidate for inducing resilience and protection against AD, and reinforce the value of LCLs as a feasible peripheral cell model for understanding the protective mechanisms of nutraceuticals against oxidative stress in aging and AD.
Abstract: Oxidative damage is involved in the pathophysiology of age-related ailments, including Alzheimer’s disease (AD). Studies have shown that the brain tissue and also lymphocytes from AD patients present increased oxidative stress compared to healthy controls (HCs). Here, we use lymphoblastoid cell lines (LCLs) from AD patients and HCs to investigate the role of resveratrol (RV) and selenium (Se) in the reduction of reactive oxygen species (ROS) generated after an oxidative injury. We also studied whether these compounds elicited expression changes in genes involved in the antioxidant cell response and other aging-related mechanisms. AD LCLs showed higher ROS levels than those from HCs in response to H2O2 and FeSO4 oxidative insults. RV triggered a protective response against ROS under control and oxidizing conditions, whereas Se exerted antioxidant effects only in AD LCLs under oxidizing conditions. RV increased the expression of genes encoding known antioxidants (catalase, copper chaperone for superoxide dismutase 1, glutathione S-transferase zeta 1) and anti-aging factors (sirtuin 1 and sirtuin 3) in both AD and HC LCLs. Our findings support RV as a candidate for inducing resilience and protection against AD, and reinforce the value of LCLs as a feasible peripheral cell model for understanding the protective mechanisms of nutraceuticals against oxidative stress in aging and AD.

Journal ArticleDOI
TL;DR: Two facility–location models are proposed that represent alternative distribution policies in e-commerce (one based on outsourcing and another based on in-house distribution) that take into account stochastic demands as well as more than one regular supplier per customer.

Journal ArticleDOI
01 Mar 2019
TL;DR: The 6TiSCH Simulator as discussed by the authors is a simulator for the IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) with IPv6 standardization.
Abstract: 6TiSCH is a working group at the IETF which is standardizing how to combine IEEE802.15.4 Time-Slotted Channel Hopping (TSCH) with IPv6. The result is a solution which offers both industrial performance and seamless integration into the Internet, and is therefore seen as a key technology for the Industrial Internet of Things. This article presents the 6TiSCH Simulator, created as part of the standardization activity, and which has been used extensively by the working group. The goal of the simulator is to benchmark 6TiSCH against realistic scenarios, something which is hard to do using formal models or real-world deployments. This article discusses the overall architecture of the simulator, details the different models it uses (i.e. energy, propagation), compares it to other simulation/emulation platforms, and presents 5 published examples of how the 6TiSCH Simulator has been used.