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Dendrochronological report

This replication package contains all code, documentation and metadata for the study "ESG did not immunize stocks during the COVID-19 crisis, but investments in intangible assets did", as published in the Journal of Business Finance & Accounting. Due to contractual limitations, the data are stored in a secure location at Tilburg University and cannot be shared. Additional documentation and metadata can be found in the 'metadata' folder.

Quantitative and qualitative data from 51 hosts and 53 refugee guests via TakeCareBnB, all anonimized. The Research Question of this study was: How does a temporal stay with local hosts influence the integration of refugee guests?

The best-possible-self (BPS) intervention is one of the most widely used positive psychological interventions. It has been shown to promote well-being, optimism and positive affect and to decrease negative affect. However, most research has been conducted in western countries and its effectiveness in people from Eastern countries has been questioned. In this study, we examined the effect of the BPS in young adults from mainland China. Moreover, we investigated the moderating effect of cultural orientation, self-efficacy, and trait optimism and the mediating effect of state optimism and goal-related cognitions. Seventy participants were randomly assigned to the BPS or the control condition. In contrast to previous studies, the BPS did not lead to higher positive affect or well-being in Chinese, but rather to decreased negative affect and negative future expectancies. No significant moderating or mediating effect was found. This study indicates that the effects of the BPS might differ across cultures.

The Wind in our Sails. Places dataset converted to RDF. This deposit contains the resulting RDF triples in separate zip archives as well as scripts used for conversion and linking.

Graph neural networks and other machine learning models offer a promising direction for interpretable machine learning on relational and multimodal data. Until now, however, progress in this area is difficult to gauge. This is primarily due to a limited number of datasets with (a) a high enough number of labeled nodes in the test set for precise measurement of performance, and (b) a rich enough variety of of multimodal information to learn from. Here, we introduce a set of new benchmark tasks for node classification on knowledge graphs. We focus primarily on node classification, since this setting cannot be solved purely by node embedding models, instead requiring the model to pool information from several steps away in the graph. However, the datasets may also be used for link prediction. For each dataset, we provide test and validation sets of at least 1000 instances, with some containing more than 10\;000 instances. Each task can be performed in a purely relational manner, to evaluate the performance of a relational graph model in isolation, or with multimodal information, to evaluate the performance of multimodal relational graph models. All datasets are packaged in a CSV format that is easily consumable in any machine learning environment, together with the original source data in RDF and pre-processing code for full provenance. We provide code for loading the data into \texttt{numpy} and \texttt{pytorch}. We compute performance for several baseline models.

Dendrochronological report

Communities around the world are facing an increasing number of ‘wicked problems’, many of which are spatial issues. Therefore, high expectations are placed on the role of planning in addressing them. However, such complex challenges cannot be easily solved with the traditional, sectoral planning approaches, or by planners and decision-makers alone; they require a cross-sectoral and societal-inclusive understanding and collaboration of various kinds of stakeholders. Consequently, in the search for new approaches and tools that favour experimentation, flexibility, and collaboration, planners and decision-makers are turning their attention towards the private sector, where Living Labs have been extensively used in open and user-oriented innovation. Despite the growing number of studies that picture them as a ‘magic recipe’ for experimentation and development of creative solutions for ‘wicked problems’, Living Labs have only recently started gaining attention in the spatial domain. In this chapter, we position Living Labs as a creative and collaborative planning approach. Based on a literature review on Living Labs, and on empirical research carried out in three spatial planning and water infrastructure projects from the Netherlands, we propose a five-phased ‘living lab way of working’ and reflect on the role of Living Labs as a planning method. We end by outlining several recommendations that could be useful when considering the use of Living Labs as a planning method. The conclusion of this chapter shows that despite the challenges they pose, Living Labs represent a relevant and growing practice in spatial planning, especially because they provide a conducive way of connecting local-scale and larger-scale planning issues and solutions.

Self-voice attribution can become difficult when voice characteristics are ambiguous, but functional magnetic resonance imaging (fMRI) investigations of such ambiguity are sparse. We utilized voice-morphing (self-other) to manipulate (un-) certainty in self-voice attribution in a button-press paradigm. This allowed investigating how levels of self-voice certainty alter brain activation in brain regions monitoring voice identity and unexpected changes in voice playback quality. FMRI results confirmed a self-voice suppression effect in the right anterior superior temporal gyrus (aSTG) when self-voice attribution was unambiguous. Although the right inferior frontal gyrus (IFG) was more active during a self-generated compared to a passively heard voice, the putative role of this region in detecting unexpected self-voice changes during the action was demonstrated only when hearing the voice of another speaker and not when attribution was uncertain. Further research on the link between right aSTG and IFG is required and may establish a threshold monitoring voice identity in action. The current results have implications for a better understanding of the altered experience of self-voice feedback in auditory verbal hallucinations.