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Making circularity work:The employee side of organizational change towards the circular economy
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A twin transition or a flagship policy? Emergent constellations and dominant blocks in green and digital technologies
No full textThis paper seeks to understand whether what has been labeled the "twin transition", a flagship EU policy, emerges as a new endogenous technological trajectory involving the convergence of green and digital technologies, or whether this policy is in fact having little impact. Embracing an evolutionary approach to technology, we first identify the set of relevant technologies defined as "green" and then analyze their evolution in terms of the dominant blocks within the green technology sector and their intertwining with digital technologies, drawing on 560,720 patents granted by the US Patent Office from 1976 to 2024. Three dominant blocks emerge as relevant in defining the direction of innovation, namely energy, transport, and production processes. We assess the technological concentration and underlying complexity of the dominant blocks, interpreting this through the construction of counterfactual scenarios. We find hardly any evidence for a pattern of actual endogenous convergence of green and digital technologies in the period under analysis. On the whole, for the time being, the "twin transition" appears to be a flagship policy in name only, rather than an endogenous technological trajectory driving structural change
Weighing Parenthood Wishes:A Conjoint Analysis of Criteria to Prioritize Infertile Couples for Publicly Funded Fertility Treatment
No full textBackground: Parenthood is a key life goal for many, but infertility affects about 1 in 6 globally. While fertility treatments offer solutions, their high costs limit access. Many health systems provide public funding, yet budget constraints prevent fully funded access, often leaving patients with significant out-of-pocket costs. Policy makers face the challenge of prioritizing individuals for publicly funded treatments, but how to do this remains unclear and underresearched. Worldwide, funding policies vary widely, often adopting controversial access criteria. Methods: We investigated Belgian population preferences for prioritizing in vitro fertilization (IVF) funding through a discrete-choice experiment with a representative sample of 3,000 Belgians. Attributes included maternal and partner age, infertility cause, civil status, prior biological children, and treatment cost. Using a Bayesian D-optimal design and panel mixed logit model, we assessed criteria relevance. The resulting multiattribute utility function created a priority ranking of couples, which we compared to the ranking under the current Belgian policy, which focuses only on maternal age (&lt;43 y). Results: Analysis of 29,670 prioritization choices identified maternal age, infertility cause, and prior biological children as key criteria. Maternal age of 35 y was prioritized highest, age 25 y as high as 40 y, followed by declining priority until 55 y. Biomedical malfunctions were prioritized over same-sex relationships or unhealthy lifestyles, with the latter prioritized lowest. Having no prior biological children was prioritized categorically higher than having 1, 2, or 3 children, all prioritized equally. Preferences were homogeneous across sociodemographic groups. Conclusions: How to set IVF funding priorities remains a matter of debate. Our study shows that the Belgian population considers multiple criteria beyond maternal age to prioritize couples, calling for further discussion on ethical justifiability and access implications. Highlights: Parenthood is a key life goal to many, but about 1 in 6 are affected by infertility. However, in most countries, public funding for fertility treatment is not provided to everyone who could benefit, and hard choices are inevitable. This study used a discrete-choice experiment in a representative sample of the Belgian population to investigate which criteria should be used for prioritization. Results indicated that maternal age, cause of infertility, and the number of prior biological children were the most significant factors in determining public support for IVF funding. Partner age, civil status of the couple, and cost of IVF treatment were not important. People use multiple criteria to set IVF funding priorities, beyond maternal age (the only criterion used in the current Belgian funding policy). Future research should explore the ethical justifiability and practical implications of using cause of infertility and number of prior children as additional criteria.</p
Individual hearts:computational models for improved management of cardiovascular disease
No full textCardiovascular disease remains a leading cause of morbidity and mortality worldwide, with conventional management often applying standardised approaches that struggle to address individual variability in increasingly complex patient populations. Computational models, both knowledge-driven and data-driven, have the potential to reshape cardiovascular medicine by offering innovative tools that integrate patient-specific information with physiological understanding or statistical inference to generate insights beyond conventional diagnostics. This review traces how computational modelling has evolved from theoretical research tools into clinical decision support systems that enable personalised cardiovascular care. We examine this evolution across three key domains: enhancing diagnostic accuracy through improved measurement techniques, deepening mechanistic insights into cardiovascular pathophysiology and enabling precision medicine through patient-specific simulations. The review covers the complementary strengths of data-driven approaches, which identify patterns in large clinical datasets, and knowledge-driven models, which simulate cardiovascular processes based on established biophysical principles. Applications range from artificial intelligence-guided measurements and model-informed diagnostics to digital twins that enable in silico testing of therapeutic interventions in the digital replicas of individual hearts. This review outlines the main types of cardiovascular modelling, highlighting their strengths, limitations and complementary potential through current clinical and research applications. We also discuss future directions, emphasising the need for interdisciplinary collaboration, pragmatic model design and integration of hybrid approaches. While progress is promising, challenges remain in validation, regulatory approval and clinical workflow integration. With continued development and thoughtful implementation, computational models hold the potential to enable more informed decision-making and advance truly personalised cardiovascular care
Slimme huizen in een empathische zorgomgeving?
No full textDoor de combinatie van Informatie en Communicatie Technologie (ICT), slimme sensoren, big data en Artificiële Intelligentie (AI) lijkt het mogelijk om mensen met een beginnende maar snel toenemende zorgvraag (cognitief, fysiek of in combinatie) te ondersteunen. Er wordt in dit verband wel gesproken over slimme huizen die een onderdeel vormen van een ‘empathische omgeving’, waarbij een huis, mantelzorgers en professionele verzorgers samen een optimale combinatie van autonomie, zelfredzaamheid en zorg mogelijk proberen te maken
The role of co-benefits in motivating climate change mitigation - Experimental evidence
No full textWe study the role of co-benefits - positive effects of climate change mitigation projects in addition to CO2 reduction - in motivating individuals to donate to such projects. In two artefactual field experiments conducted with large population samples (n = 2400 in total), we test how the existence and specific nature of co-benefits affect donations. In both experiments, we find that co-benefits have a positive impact on participants' willingness to donate. Moreover, our second experiment shows that contributions respond to the nature of co-benefits, and these responses seem to be driven by individuals' preferences for specific types of co-benefits. We further observe that co-benefits also increase donations when making carbon footprints and thus individual responsibility for environmental externalities more salient. In sum, our study provides a comprehensive picture of the potential of co-benefits for increasing donations to climate change mitigation projects and has several implications for the provision of co-benefits information in practice
Seeing Cold, Eating Warm:Food Perception in Imaginative Storytelling and Immersive Virtual Reality Winter Contexts
No full textFood intake is a fundamental daily activity. Its relationship to external factors such as social and environmental contexts has been widely investigated in consumer studies. Virtual reality (VR) technology enables the realistic simulation of real-life conditions and, therefore, holds promise as an ecologically valid method for understanding eating intentions and behavior. This study examines whether contextual exposure to VR or text-based storytelling influences food liking and desire in alignment with the presented environment. A total of 117 participants, either online or in a laboratory setting, viewed and rated eight food items varying in calorie density while exposed to one of three conditions: a VR-simulated winter forest, a text-based storytelling winter forest, or a control group without winter cues. Accounting for individual characteristics such as eating habits and body mass index, the results showed that participants’ food perceptions —defined here as evaluative responses toward digitally presented food items—followed a similar pattern across both winter forest contexts, with a stronger desire and liking for high-calorie over low-calorie foods. However, the intensity of their perceptual responses varied significantly between conditions. Participants in the VR forest reported greater familiarity, liking, and desire for all food items, as well as a stronger sense of spatial presence, compared to those in the storytelling condition. While VR elicited heightened and more affective responses, both VR and storytelling seem to be useful interventions for assessing contextual effects on product consumption. These findings provide insights into how different modes of contextual presentation shape food perception and encourage the integration of multiple sensory modalities to further bridge the gap between virtual and real food experiences
Full Integer Arithmetic Online Training for Spiking Neural Networks
No full textSpiking Neural Networks (SNNs) are promising for neuromorphic computing due to their biological plausibility and energy efficiency. However, training methods like Backpropagation Through Time (BPTT) and Real Time Recurrent Learning (RTRL) remain computationally intensive. This work introduces an integer-only, online training algorithm using a mixed-precision approach to improve efficiency and reduce memory usage by over 60%. The method replaces floating-point operations with integer arithmetic to enable hardware-friendly implementation. It generalizes to Convolutional and Recurrent SNNs (CSNNs, RSNNs), showing versatility across architectures. Evaluations on MNIST and the Spiking Heidelberg Digits (SHD) dataset demonstrate that mixed-precision models achieve accuracy comparable to or better than full-precision baselines using 16-bit shadow and 8- or 12-bit inference weights. Despite some limitations in low-precision and deeper models, performance remains robust. In conclusion, the proposed integer-only online learning algorithm presents an effective solution for efficiently training SNNs, enabling deployment on resource-constrained neuromorphic hardware without sacrificing accuracy