A case study and method development research of online simulation gaming to enhance youth care knowlegde exchange. Youth care professionals affirm that the application used has enough relevance as an additional tool for knowledge construction about complex cases. They state that the usability of the application is suitable, however some remarks are given to adapt the virtual environment to the special needs of youth care knowledge exchange. The method of online simulation gaming appears to be useful to improve network competences and to explore the hidden professional capacities of the participant as to the construction of situational cognition, discourse participation and the accountability of intervention choices.
Business model innovations emerge over time and are influenced by managerial interaction with stakeholders. Especially with regard to business model innovation for sustainability, manager-stakeholder interaction can radically change a company’s business model and underlying logic. However, the majority of the literature shows how manager–stakeholder interaction may limit business model innovation when stakeholders reinforce existing managerial cognitions. In this chapter we study how stakeholders can also stimulate business model innovation by affecting managerial cognitive change. Through three case studies, we find that this can occur through three shaping processes: market approach shaping, product/service offering shaping, and credibility shaping. We also find that the impact of new or latent stakeholders is greater than that of existing stakeholders. We end the chapter by sketching a research agenda to further unravel the role of stakeholders affecting managerial cognition around business model innovation for sustainability.
PurposeCancer-related cognitive impairment (CRCI) following chemotherapy is commonly reported in breast cancer survivors, even years after treatment. Data from preclinical studies suggest that exercise during chemotherapy may prevent or diminish cognitive problems; however, clinical data are scarce.MethodsThis is a pragmatic follow-up study of two original randomized trials, which compares breast cancer patients randomized to exercise during chemotherapy to non-exercise controls 8.5 years post-treatment. Cognitive outcomes include an online neuropsychological test battery and self-reported cognitive complaints. Cognitive performance was compared to normative data and expressed as age-adjusted z-scores.ResultsA total of 143 patients participated in the online cognitive testing. Overall, cognitive performance was mildly impaired on some, but not all, cognitive domains, with no significant differences between groups. Clinically relevant cognitive impairment was present in 25% to 40% of all participants, regardless of study group. We observed no statistically significant effect of exercise, or being physically active during chemotherapy, on long-term cognitive performance or self-reported cognition, except for the task reaction time, which favored the control group (β = -2.04, 95% confidence interval: -38.48; -2.38). We observed no significant association between self-reported higher physical activity levels during chemotherapy or at follow-up and better cognitive outcomes.ConclusionIn this pragmatic follow-up study, exercising and being overall more physically active during or after adjuvant chemotherapy for breast cancer was not associated with better tested or self-reported cognitive functioning, on average, 8.5 years after treatment. Future prospective studies are needed to document the complex relationship between exercise and CRCI in cancer survivors.
MULTIFILE
Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
In recent years, ArtEZ has worked on a broadly supported strategic research agenda on the themes New Ecologies of Matter (ecological challenges), Social Equity (social-societal issues), (Un)Learning Practices (educational innovations) and (Non)CybernEtic Fabric (technological developments). Building on these strategic themes, the ArtEZ Research Collective as developed an international research strategy to become a valuable partner in the relevant Horizon Europe (HEU) areas of Environment, Industry and Social science and humanities. With its specific knowledge position and approach from arts and creativity, ArtEZ is convinced that it can play a distinctive role in European consortia to tackle various challenges in these areas, in particular from the perspective and research topics of the professorships Fashion and Tactical Design. To achieve its ambitions and goals in its targeted research topics, ArtEZ is convinced that a combination of international connections and local applications is key for successful impact. Building upon existing relations and extending the international research position requires extra efforts, e.g., by developing a strong international framework of state-of-the-art research results, impacts and ambitions. Therefore ArtEZ needs to (further) build on both its international network and its supportive infrastructure. With this proposal ArtEZ is presenting its goals and efforts to work on its international recognition as a valuable research partner, and to broaden its international network in cutting-edge research and other stakeholders. With regards to its supporting infrastructure, ArtEZ has the ambition to expand the impact of the Subsidy Desk to become a professional partner to the professorships. This approach requires a further professionalization and extension of both the Subsidy Desk organization and its services, and developing and complementing skills, expertise and competences to comply to the European requirements.
The project aim is to improve collusion resistance of real-world content delivery systems. The research will address the following topics: • Dynamic tracing. Improve the Laarhoven et al. dynamic tracing constructions [1,2] [A11,A19]. Modify the tally based decoder [A1,A3] to make use of dynamic side information. • Defense against multi-channel attacks. Colluders can easily spread the usage of their content access keys over multiple channels, thus making tracing more difficult. These attack scenarios have hardly been studied. Our aim is to reach the same level of understanding as in the single-channel case, i.e. to know the location of the saddlepoint and to derive good accusation scores. Preferably we want to tackle multi-channel dynamic tracing. • Watermarking layer. The watermarking layer (how to embed secret information into content) and the coding layer (what symbols to embed) are mostly treated independently. By using soft decoding techniques and exploiting the “nuts and bolts” of the embedding technique as an extra engineering degree of freedom, one should be able to improve collusion resistance. • Machine Learning. Finding a score function against unknown attacks is difficult. For non-binary decisions there exists no optimal procedure like Neyman-Pearson scoring. We want to investigate if machine learning can yield a reliable way to classify users as attacker or innocent. • Attacker cost/benefit analysis. For the various use cases (static versus dynamic, single-channel versus multi-channel) we will devise economic models and use these to determine the range of operational parameters where the attackers have a financial benefit. For the first three topics we have a fairly accurate idea how they can be achieved, based on work done in the CREST project, which was headed by the main applicant. Neural Networks (NNs) have enjoyed great success in recognizing patterns, particularly Convolutional NNs in image recognition. Recurrent NNs ("LSTM networks") are successfully applied in translation tasks. We plan to combine these two approaches, inspired by traditional score functions, to study whether they can lead to improved tracing. An often-overlooked reality is that large-scale piracy runs as a for-profit business. Thus countermeasures need not be perfect, as long as they increase the attack cost enough to make piracy unattractive. In the field of collusion resistance, this cost analysis has never been performed yet; even a simple model will be valuable to understand which countermeasures are effective.
