INESC-ID

About: INESC-ID is a nonprofit organization based out in Lisbon, Portugal. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 932 authors who have published 2618 publications receiving 37658 citations.

Parameter optimization in S-system models

Abstract: The inverse problem of identifying the topology of biological networks from their time series responses is a cornerstone challenge in systems biology. We tackle this challenge here through the parameterization of S-system models. It was previously shown that parameter identification can be performed as an optimization based on the decoupling of the differential S-system equations, which results in a set of algebraic equations.

RISOTTO: fast extraction of motifs with mismatches

Abstract: We present in this paper an exact algorithm for motif extraction. Efficiency is achieved by means of an improvement in the algorithm and data structures that applies to the whole class of motif inference algorithms based on suffix trees. An average case complexity analysis shows a gain over the best known exact algorithm for motif extraction. A full implementation was developed and made available online. Experimental results show that the proposed algorithm is more than two times faster than the best known exact algorithm for motif extraction.

Healthy Apps: Mobile Devices for Continuous Monitoring and Intervention

Abstract: It is now known that nearly half of the toll that illness takes in developed countries is linked to four unhealthy behaviors: smoking, excess alcohol intake, poor diet, and physical inactivity. These common risk behaviors cause preventable, delayed illness that then manifests as chronic disease, requiring extended medical care with associated financial costs. Chronic disease already accounts for 75% of U.S. health-care costs, foreshadowing an unsustainable financial burden for the aging population [1]. We are facing an urgent need to re-engineer health systems to improve public health through behavior change, and technology-supported behavioral change interventions will be a part of 21st-century health care. As new technical capabilities to observe behavior continuously in context make it possible to tailor interventions in real time, the way we understand and try to influence behavior will change fundamentally.

FearNot!: an emergent narrative approach to virtual dramas for anti-bullying education

Abstract: FearNot! is a story-telling application originally created in the EU FP5 project VICTEC and now extended in the FP6 project eCIRCUS [eCIRCUS 07]. It has applied ideas from Forum Theatre [Boal 79] to the domain of education against bullying. In Forum Theatre, sections of an audience take responsibility for a specific character in the unfolding drama, played by an actor who always stays in role. Episodes in which the actors improvise within an overall narrative framework are broken by interaction sections in which the audience sections talk over with 'their' character what they should do in the next dramatic segment. The actor is free to reject advice that seems incompatible with their role, and may also suspend a dramatic episode if it seems necessary to get further advice.

Virtual learning intervention to reduce bullying victimization in primary school : a controlled trial

Abstract: Background: Anti-bullying interventions to date have shown limited success in reducing victimization and have rarely been evaluated using a controlled trial design. This study examined the effects of the FearNot! anti-bullying virtual learning intervention on escaping victimization, and reducing overall victimization rates among primary school students using a nonrandomized controlled trial design. The program was designed to enhance the coping skills of children who are known to be, or are likely to be, victimized. Methods: One thousand, one hundred twenty-nine children (mean age 8.9 years) in 27 primary schools across the UK and Germany were assigned to the FearNot! intervention or the waiting control condition. The program consisted of three sessions, each lasting approximately 30 minutes over a three-week period. The participants were assessed on self-report measures of victimization before and one and four weeks after the intervention or the normal curriculum period. Results: In the combined sample, baseline victims in the intervention group were more likely to escape victimization at the first follow-up compared with baseline victims in the control group (adjusted RR, 1.41; 95% CI, 1.02–1.81). A dose–response relationship between the amount of active interaction with the virtual victims and escaping victimization was found (adjusted OR, 1.09; 95% CI, 1.003–1.18). Subsample analyses found a significant effect on escaping victimization only to hold for UK children (adjusted RR, 1.90; CI, 1.23–2.57). UK children in the intervention group experienced decreased victimization rates at the first follow-up compared with controls, even after adjusting for baseline victimization, gender and age (adjusted RR, .60; 95% CI, .36–.93). Conclusions: A virtual learning intervention designed to help children experience effective strategies for dealing with bullying had a short-term effect on escaping victimization for a priori identified victims, and a short-term overall prevention effect for UK children. Keywords: Anti-bullying intervention, victimization, virtual learning, controlled trial. Abbreviation: FearNot!: Fun with Empathic Agents to achieve Novel Outcomes in Teaching. School bullying, defined as intentional and repeated aggression towards weaker peers, is a widespread phenomenon that is most prevalent among primary school children (Olweus, 1993). In particular, bullying victimization is associated with behavior and school adjustment problems, high levels of depression and anxiety, and poor physical health (Arse