Mapping of international and national funding agencies and strategies for that support societal impact and knowledge mobilisation

TrygFonden has commissioned this report to explore how knowledge mobilization and societal impact are incorporated into funding strategies by Danish and international foundations. The report aims to explore how foundations use knowledge mobilization to strengthen the practical implementation of knowledge and impact within research environments and projects. Knowledge mobilization provides a conceptual framework for systematically understanding how knowledge is exchanged and co-created between research and practice. The concepts and structures used to describe different scales and tools for knowledge mobilization are identified across foundations and we show how an increasing strategic focus on research-to-practice partnerships and instrumets are permeating the funding lancscabe. TeamArbejdsliv (Ulrik Gensby) and Aalborg University (David Budtz Pedersen) have jointly prepared the report “Mapping of international and national funding agencies and strategies for that support societal impact and knowledge mobilisation.” The mapping documents how eight Danish and international foundations support knowledge mobilization in the research activities they fund.TrygFonden has commissioned this report to explore how knowledge mobilization and societal impact are incorporated into funding strategies by Danish and international foundations. The report aims to explore how foundations use knowledge mobilization to strengthen the practical implementation of knowledge and impact within research environments and projects. Knowledge mobilization provides a conceptual framework for systematically understanding how knowledge is exchanged and co-created between research and practice. The concepts and structures used to describe different scales and tools for knowledge mobilization are identified across foundations and we show how an increasing strategic focus on research-to-practice partnerships and instrumets are permeating the funding lancscabe. TeamArbejdsliv (Ulrik Gensby) and Aalborg University (David Budtz Pedersen) have jointly prepared the report “Mapping of international and national funding agencies and strategies for that support societal impact and knowledge mobilisation.” The mapping documents how eight Danish and international foundations support knowledge mobilization in the research activities they fund

Deep reinforcement learning tuned type-3 fuzzy PID controller:AC microgrid case study

This paper proposes an adaptive type-3 fuzzy controller for controlling uncertain power systems. The controller, named type-3 fuzzy PID (T3FPID), has an input–output (I/O) relationship similar to the traditional PID controller but can better handle uncertainty and nonlinearity in systems. In the proposed design, controller parameters, such as I/O scaling factors (SFs) that affect transient and steady-state performance, are adjusted using the deep deterministic policy gradient (DDPG) reinforcement learning (RL) algorithm. The RL agent is initially trained offline under different operating conditions, then used online to tune the T3FPID controller’s parameters. The proposed RL-tuned T3FPID controller’s effectiveness is demonstrated by applying it to the load–frequency control problem of a microgrid system in simulations across various operating points. Results show that this approach outperforms other controllers

An Auto Battler Game to Engage High School Student's Understanding of Ionic Bonds in Chemistry

This paper describes the development and evaluation of a serious game to help high school students understand the topic of ionic bonds in chemistry. Chemistry is among the lowest-scoring subjects for high school students due to complex chemistry concepts and syntax difficulties. The novelty of this study is a developed auto battler game that includes specific learning objectives regarding ionic bonds. 27 Danish high school students participated in the evaluation. The evaluation consisted of a knowledge test and a questionnaire with items from the user engagement scale. The findings revealed that the high school students were positively engaged in the battle game. The grand mean for eight engagement items, based on a 5-point Likert scale, was 3.78. Specifically, the participants perceived the graphics and visual elements as highly positive. Further, they were concentrated while playing and were interested in the game. The students provided positive statements in the open-ended comments, including a good, creative, cozy, well-made, engaging, and fun game. However, the learning outcomes were not as satisfactory as expected. In the paper, we outline reflections on difficulties when measuring learning outcomes in game-based learning

Unpacking dimensions of a tiering typology:delegation, direction and strength

Within environmental assessment (EA), tiering between higher-tier strategic environmental assessment at the plan and program level and lower-tier environmental impact assessment at the project level creates effective communication, ensuring that insights are not isolated to the planning level in which they were derived, but can inform and guide other levels. Tiering can travel in many directions – ensuring that strategic goals make it into implemented projects and that information gained in project levels inform future strategic planning. This research extends the tiering concept along three dimensions, ‘delegation’, ‘direction’ and ‘strength’. It does so to further existing conceptual understandings and gain a nuanced understanding of the role that especially strategic levels have in ensuring meaningful tiering. To illustrate the new conceptual tiering typologies, the research draws upon a case study of three Danish EA reports on spatial planning to understand how tiering is delegated between planning levels. The illustrative case study concludes that a procedurally effective referral of information between planning tiers calls for tiering practice that is explicit and is both delegated and successfully implemented in the appropriate planning levels. Consequently, this paper not only furthers theoretical perspectives; it also demonstrates how the proposed typology can be applied and opens for further reflection on the potentials and limitations of the typology as well as avenues for future research

Clinical likelihood models calibrated against observed obstructive coronary artery disease on computed tomography angiography

Aims: Models predicting the likelihood of obstructive coronary artery disease (CAD) on invasive coronary angiography exist. However, as stable patients with new-onset chest pain frequently have lower clinical likelihood and preferably undergo index testing by non-invasive tests such as coronary computed tomography angiography (CCTA), clinical likelihood models calibrated against observed obstructive CAD at CCTA are warranted. The aim was to develop CCTA-calibrated risk-factor- and coronary artery calcium score-weighted clinical likelihood models (i.e. RF-CLCCTA and CACS-CLCCTA models, respectively). Methods and results: Based on age, sex, symptoms, and cardiovascular risk factors, an advanced machine learning algorithm utilized a training cohort (n = 38 269) of symptomatic outpatients with suspected obstructive CAD to develop both a RF-CLCCTA model and a CACS-CLCCTA model to predict observed obstructive CAD on CCTA. The models were validated in several cohorts (n = 28 340) and compared with a currently endorsed basic pre-test probability (Basic PTP) model. For both the training and pooled validation cohorts, observed obstructive CAD at CCTA was defined as &gt;50% diameter stenosis. Observed obstructive CAD at CCTA was present in 6443 (22.7%) patients in the pooled validation cohort. While the Basic PTP underestimated the prevalence of observed obstructive CAD at CCTA, the RF-CLCCTA and CACS-CLCCTA models showed superior calibration. Compared with the Basic PTP model, the RF-CLCCTA and CACS-CLCCTA models showed superior discrimination (area under the receiver operating curves 0.71 [95% confidence interval (CI) 0.70-0.72] vs. 0.74 (95% CI 0.73-0.75) and 0.87 (95% CI 0.86-0.87), P &lt; 0.001 for both comparisons). Conclusion: CCTA-calibrated clinical likelihood models improve calibration and discrimination of observed obstructive CAD at CCTA.</p

Certolizumab pegol, abatacept, tocilizumab or active conventional treatment in early rheumatoid arthritis: 48-week clinical and radiographic results of the investigator-initiated randomised controlled NORD-STAR trial

Background: The optimal first-line treatment in early rheumatoid arthritis (RA) is debated. We compared clinical and radiographic outcomes of active conventional therapy with each of three biological treatments with different modes of action.Methods: Investigator-initiated, randomised, blinded-assessor study. Patients with treatment-naïve early RA with moderate-severe disease activity were randomised 1:1:1:1 to methotrexate combined with (1) active conventional therapy: oral prednisolone (tapered quickly, discontinued at week 36) or sulfasalazine, hydroxychloroquine and intra-articular glucocorticoid injections in swollen joints; (2) certolizumab pegol; (3) abatacept or (4) tocilizumab. Coprimary endpoints were week 48 Clinical Disease Activity Index (CDAI) remission (CDAI ≤2.8) and change in radiographic van der Heijde-modified Sharp Score, estimated using logistic regression and analysis of covariance, adjusted for sex, anticitrullinated protein antibody status and country. Bonferroni's and Dunnet's procedures adjusted for multiple testing (significance level: 0.025).Results: Eight hundred and twelve patients were randomised. Adjusted CDAI remission rates at week 48 were: 59.3% (abatacept), 52.3% (certolizumab), 51.9% (tocilizumab) and 39.2% (active conventional therapy). Compared with active conventional therapy, CDAI remission rates were significantly higher for abatacept (adjusted difference +20.1%, p&lt;0.001) and certolizumab (+13.1%, p=0.021), but not for tocilizumab (+12.7%, p=0.030). Key secondary clinical outcomes were consistently better in biological groups. Radiographic progression was low, without group differences.The proportions of patients with serious adverse events were abatacept, 8.3%; certolizumab, 12.4%; tocilizumab, 9.2%; and active conventional therapy, 10.7%.Conclusions: Compared with active conventional therapy, clinical remission rates were superior for abatacept and certolizumab pegol, but not for tocilizumab. Radiographic progression was low and similar between treatments

Coalition Formation and Firm Representatives’ Answers to Complainers on Social Media: Their Interplay and the Coalition Ripple Effect

We ask whether complaint answers by firm representatives depend on coalition formation—others taking sides with complainers or firm representatives—and whether coalition formation by third actors depends on complaint answers. An online field study revealed that, from the firm representative perspective, the 73.2% probability of a complaint answer in the absence of any coalition decreases to 10.9%–12.8% in the presence of a prior coalition with a firm representative or complainer. From the third actor perspective, the probability of the formation of a coalition with a firm representative decreases by one-third in the presence versus absence of a prior complaint answer; coalitions with complainers are not curtailed. Furthermore, a coalition with a firm representative shifts the average complaint answer from somewhat favorable to unfavorable, which facilitates coalitions with complainers, creating a coalition ripple effect. The results offer managerial guidance, as dissatisfying online complaint handling remains problematic