INURA as a village - urban research and action in urgent times

Report (2023)

Game of Brains: Examining Researcher Brain Gain and Brain Drain and Research University Policy

in Higher Education Policy (2023), 36

We leverage a rich bibliometric dataset on Taiwanese academia to explore scientific migration patterns. We investigate the movement and productivity of 21,051 highly active researchers who served in ... [more ▼]

We leverage a rich bibliometric dataset on Taiwanese academia to explore scientific migration patterns. We investigate the movement and productivity of 21,051 highly active researchers who served in Taiwanese higher education institutions based on 30 years’ worth of publication and affiliation records from 1991 to 2020. The analysis shows evidence of brain drain in Taiwan since the 2010s, with the U.S. being both the biggest source of inbound researchers to Taiwan and top destination for researchers emigrating from Taiwan. China comes a close second to the U.S. as the top destination for outbound scholars. We also study how Taiwan’s universities recruited talent after the country adopted the 2005 excellence initiative and confirm the converging number of scholars recruited by World Class Universities (WCUs) and non-WCUs as WCUs, surprisingly, exhibit a dramatic decrease in new recruits. Our evidence uncovers that inbound scholars, after their move, are more productive than non-mobile colleagues; however, this effect declines over time. We discuss implications for the study of excellence initiatives and mechanisms of talent circulation that greatly impact research production and research university development. [less ▲]

Recensie van: Sieger Vreeling, Geen stijl: Een rijkere architectuurgeschiedenis

in Bijdragen en Mededelingen Betreffende de Geschiedenis der Nederlanden (2023), 138

Guest Editor, Journal of Risk and Financial Management

Diverse speeches and writings (2023)

Remarks on Johan van der Walt’s Concept of Liberal Democratic Law. With Kelsen, Beyond Kelsen and the Unexplored Issue of Independent Technocratic Institutions

in Netherlands Journal of Legal Philosophy (2023), (1), 120-133

Towards assimilating SAR data into an anisotropic model of an underground aquifer

Scientific Conference (2023)

In this study, we aim to shed light on the feasibility of assimilating synthetic aperture radar (SAR) data into a partial differential equation-based model of a poroelastic homogeneous aquifer with ... [more ▼]

In this study, we aim to shed light on the feasibility of assimilating synthetic aperture radar (SAR) data into a partial differential equation-based model of a poroelastic homogeneous aquifer with anisotropic hydraulic conductivity (AHC). Although other authors [1] have considered the problem of assimilating SAR data into a poroelastic model that uses an inhomogeneous isotropic random field model for hydraulic conductivity, to the best of our knowledge, our study is the first to consider assimilating SAR data into a poroelastic model with AHC. Our study is inspired by the work of [2] where an aquifer test is performed on the Anderson Junction aquifer in southwestern Utah. Due to the inherent preferential direction of the fractured sandstone at the Anderson Junction site, the ratio of hydraulic conductivity along the principal axes can be on the order of 24 to 1. We build an anisotropically conductive poroelastic finite element model of the Anderson Junction site that can predict the coupled fluid flow and mechanical displacements. Our results show that the effective elastic response of the aquifer on the Earth’s surface has an anisotropic nature driven by the underlying anisotropy in the fluid problem, even when the elasticity problem is assumed to be isotropic. We interpret these results in the context of using SAR data to improve the characterization of aquifer systems, like the Anderson Junction site, with strongly anisotropic behavior. The Doctoral Training Unit Data-driven computational modelling and applications (DRIVEN) is funded by the Luxembourg National Research Fund under the PRIDE programme (PRIDE17/12252781). [1] Amal Alghamdi. Bayesian inverse problems for quasi-static poroelasticity with application to ground water aquifer characterization from geodetic data. PhD thesis, 2020. https://repositories.lib.utexas.edu/handle/2152/86231. [2] Victor M. Heilweil and Paul A. Hsieh. Determining Anisotropic Transmissivity Using a Simplified Papadopulos Method. Groundwater, 44(5):749–753, 2006. 10.1111/j.1745-6584.2006.00210.x [less ▲]

The impact of traumatic childhood experiences on interoception: disregarding one’s own body

in Borderline Personality Disorder and Emotion Dysregulation (2023), 10(1), 5

Background Deficient interoception, the processing and perception of internal bodily signals, has been discussed as a mechanism underlying various mental disorders. First results indicate a mediating role ... [more ▼]

Background Deficient interoception, the processing and perception of internal bodily signals, has been discussed as a mechanism underlying various mental disorders. First results indicate a mediating role of interoception in the interplay of traumatic childhood experiences and adult mental disorders. Traumatic childhood experiences may hinder the adequate processing, integration, and trust in bodily signals that are important in order to understand and regulate own needs and emotions, thereby increasing the vulnerability for mental disorders. However, an overarching study investigating alterations in different interoceptive measures and trauma-related disorders as well as their mediating role between early trauma and emotion dysregulation is still missing. Methods One hundred thirty-six individuals with varying levels of traumatic childhood experiences who either had a current diagnosis of major depression, posttraumatic stress disorder, or somatic symptom disorder, or no mental disorder, took part in a multidimensional assessment of interoceptive processes, including interoceptive accuracy, sensibility, and awareness. Kruskal–Wallis tests were used to compare groups regarding interoceptive processes and associations with traumatic childhood experiences and emotion dysregulation were analyzed with Spearman correlations. Furthermore, mediation analyses were computed to examine and compare interoceptive processes as potential mediators between traumatic childhood experiences and emotion dysregulation. Results Only body dissociation, a measure for interoceptive sensibility, was significantly reduced in individuals with a current mental disorder. Body dissociation was also the only interoceptive measure significantly associated with traumatic childhood experiences and emotion dysregulation and the only significant mediator in the relationship between traumatic childhood experiences and emotion dysregulation across groups. Conclusion Results suggest body dissociation, but not other interoceptive measures, as an important feature linking traumatic childhood experiences to current emotion dysregulation, an important transdiagnostic feature. As body dissociation refers to a habitual non-attendance or disregard of interoceptive signals, integrative therapeutic interventions could help affected individuals to overcome difficulties in emotion perception and regulation. [less ▲]

Children’s perspectives on their learning experiences during the pandemic

in Developmental and Adolescent Health (2023), 2(4),

The present paper is based on two online surveys of the mix-method projects COVID-Kids I and II which investigated children’s school experiences, emotional responses, and subjective well-being during the ... [more ▼]

The present paper is based on two online surveys of the mix-method projects COVID-Kids I and II which investigated children’s school experiences, emotional responses, and subjective well-being during the Covid-19 pandemic in 2020 and 2021. The data of the 2020 questionnaire stem from 1,773 children aged 6-16 from Luxembourg, Germany and Switzerland (Kirsch et al., 2021) and those of the second questionnaire from 502 children of the same age group in Luxembourg (Kirsch et al., 2022). The presentation will examine some of the participants’ challenges with home schooling as well as selected outcomes and conclude with a few implications. [less ▲]

Expanding the Disease Network of Glioblastoma Multiforme via Topological Analysis.

in International journal of molecular sciences (2023), 24(4),

Glioblastoma multiforme (GBM), a grade IV glioma, is a challenging disease for patients and clinicians, with an extremely poor prognosis. These tumours manifest a high molecular heterogeneity, with ... [more ▼]

Glioblastoma multiforme (GBM), a grade IV glioma, is a challenging disease for patients and clinicians, with an extremely poor prognosis. These tumours manifest a high molecular heterogeneity, with limited therapeutic options for patients. Since GBM is a rare disease, sufficient statistically strong evidence is often not available to explore the roles of lesser-known GBM proteins. We present a network-based approach using centrality measures to explore some key, topologically strategic proteins for the analysis of GBM. Since network-based analyses are sensitive to changes in network topology, we analysed nine different GBM networks, and show that small but well-curated networks consistently highlight a set of proteins, indicating their likely involvement in the disease. We propose 18 novel candidates which, based on differential expression, mutation analysis, and survival analysis, indicate that they may play a role in GBM progression. These should be investigated further for their functional roles in GBM, their clinical prognostic relevance, and their potential as therapeutic targets. [less ▲]

UNTAG: Learning Generic Features for Unsupervised Type-Agnostic Deepfake Detection

in IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings (2023)

This paper introduces a novel framework for unsupervised type-agnostic deepfake detection called UNTAG. Existing methods are generally trained in a supervised manner at the classification level, focusing ... [more ▼]

This paper introduces a novel framework for unsupervised type-agnostic deepfake detection called UNTAG. Existing methods are generally trained in a supervised manner at the classification level, focusing on detecting at most two types of forgeries; thus, limiting their generalization capability across different deepfake types. To handle that, we reformulate the deepfake detection problem as a one-class classification supported by a self-supervision mechanism. Our intuition is that by estimating the distribution of real data in a discriminative feature space, deepfakes can be detected as outliers regardless of their type. UNTAG involves two sequential steps. First, deep representations are learned based on a self-supervised pretext task focusing on manipulated regions. Second, a one-class classifier fitted on authentic image embeddings is used to detect deepfakes. The results reported on several datasets show the effectiveness of UNTAG and the relevance of the proposed new paradigm. The code is publicly available. [less ▲]