Austrian Research Promotion Agency

Purpose:Although many studies have demonstrated that prolonged cognitive load can impair subsequent cognitive and physical performance, commonly described as mental fatigue, more recent findings suggest that the relationship is more nuanced. Moreover, significant heterogeneity between different smaller studies makes it difficult to summarize definitive conclusions. The aim of the present study was to provide a more robust examination of the detrimental effects of sustained cognitive demands on cognitive and physical performance fatigability using a large sample within a controlled environment.Methods:One hundred seventeen participants (57 female; 32 ± 9 yr) were included in this randomized counterbalanced crossover experiment (NCT05576935) consisting of familiarization, intervention (45-min individualized Stroop task), and control (45-min self-chosen documentary) sessions. Performance was evaluated using a 6-min GoNoGo task and a 20-min cycling time trial. Multiple secondary outcomes, such as rate of perceived exertion (RPE), feelings of fatigue, and motivation, were incorporated to explore their relationship to possible behavioral effects.Results:There was a significant worsening of GoNoGo reaction time between conditions (P < 0.001; ηp2 = 0.07). A trend toward significance was found regarding the negative influence of the Stroop task on time trial distance (P = 0.059; d = 0.20), which was linked to a significant decrease in cadence (P = 0.042; d = 0.22) in the intervention condition. Moreover, the feelings of physical fatigue (P < 0.001; ηp2 = 0.01), mental fatigue (P < 0.001; r = 0.37–0.47), and RPE (P = 0.002; ηp2 = 0.01) remained higher during the time trial in the intervention condition compared with the control condition.Conclusions:In the present study, prolonged cognitive effort impaired specific cognitive and physical performance outcomes, consistent with the characteristics of mental fatigue. Secondary outcomes show an important role for the feeling of fatigue in the determination of physical performance.

Abstract The mission of THCS activities with respect to strengthening ecosystems is based on the understanding that the actual transformation of health and care systems is dependent on the ability of numerous actors to align their goals and actions so that they are complementary. At the same time, it is also true that the transformation takes place at national, regional and local levels, making activities and support at these levels essential for the success of THCS. Therefore, the focus lies on connecting and supporting the broad community and other stakeholders in developing ecosystem-wide approaches and creating awareness and urgency among ecosystem layers and components, thus serving as a platform for transformation. One strand of activities for strengthening ecosystems aims at identifying, analysing, describing and disseminating key learnings from successful transformative ecosystems (TE’s). TE’s are broad constellations of interacting organisations and people who are committed, and through aligned actions, able to reach joint, explicitly defined goals in long-term. Making not only the most successful TE’s but also the dynamics explaining their achievements visible, value is being added through three main routes. Firstly, the experiences are distributed widely on European arenas and platforms as well as through national, regional and local channels to inspire ecosystem building processes in earlier stages of maturity. Secondly, collaboration between identified forerunner ecosystems is supported to enable mutual peer-learning. Thirdly, the examples are used to give guidance and inspiration to consortia that are applying for or receiving THCS project funding. As strategic partners of the ecosystem strengthening activities, other work packages of the THCS programme as well as the THCS National Mirror Groups are of great importance.

This study draws on evaluation data to investigate the success of collaborative R&amp;D project proposals submitted to Horizon 2020, the European Union’s Framework Programme for Research and Innovation (FP). Data on project status and evaluation score are used to identify successful and rejected project proposals. We hypothesize that the social or institutional composition of the project consortium explains the outcome of an early-stage R&amp;D collaboration. Using regression analysis, we identify “success factors” at the consortium level, related to (a) the network visibility; (b) level of experience and degree of acquaintance; and (c) the research capabilities and excellence or reputation of consortium members. We show that consortia with high levels of experience and reputation, involving a large share of Western European partners and engaged in more application-oriented consortia, have greater chances of success in acquiring H2020 project funding. This result has implications for the scientific community, as well as for the direction of EU research policy.

An open source software-based solution for Finite Element Model Updating is presented. The calculation technique has been carried out by developing VCUPDATE, a Scilab (MATLAB-like software) code performing the iterative updating algorithm interfaced with OpenSees executing the Finite Element analysis. The code has been verified by many different applications on stay cables. The dynamic test results from real structures are applied if available. Otherwise, the investigated structures are numerically generated by OpenSees.