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See detailMetaheuristics-based Exploration Strategies for Multi-Objective Reinforcement Learning
Felten, Florian UL; Danoy, Grégoire; Talbi, El-Ghazali UL et al

in Proceedings of the 14th International Conference on Agents and Artificial Intelligence (2022)

The fields of Reinforcement Learning (RL) and Optimization aim at finding an optimal solution to a problem, characterized by an objective function. The exploration-exploitation dilemma (EED) is a well ... [more ▼]

The fields of Reinforcement Learning (RL) and Optimization aim at finding an optimal solution to a problem, characterized by an objective function. The exploration-exploitation dilemma (EED) is a well known subject in those fields. Indeed, a consequent amount of literature has already been proposed on the subject and shown it is a non-negligible topic to consider to achieve good performances. Yet, many problems in real life involve the optimization of multiple objectives. Multi-Policy Multi-Objective Reinforcement Learning (MPMORL) offers a way to learn various optimised behaviours for the agent in such problems. This work introduces a modular framework for the learning phase of such algorithms, allowing to ease the study of the EED in Inner- Loop MPMORL algorithms. We present three new exploration strategies inspired from the metaheuristics domain. To assess the performance of our methods on various environments, we use a classical benchmark - the Deep Sea Treasure (DST) - as well as propose a harder version of it. Our experiments show all of the proposed strategies outperform the current state-of-the-art ε-greedy based methods on the studied benchmarks. [less ▲]

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See detailPreface
Böhmer, Matthias UL; Steffgen, Georges UL

in Böhmer, Matthias; Steffgen, Georges (Eds.) Grief in schools - Basic knowledge and advice on dealing with dying and death (2022)

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See detailChanging Routinized Household Energy Consumption Using the Example of Washing, Cooking, and Standby: A Randomized Controlled Field Experiment of Home Energy Advice
Hess, Ann-Kathrin; Schubert, Iljana; Samuel, Robin UL et al

in Cleaner and Responsible Consumption (2022)

Despite advances in understanding routines, there is little knowledge about which aspects of routinized behavior people adjust during interventions. In this study, we applied an adjusted social practice ... [more ▼]

Despite advances in understanding routines, there is little knowledge about which aspects of routinized behavior people adjust during interventions. In this study, we applied an adjusted social practice theory framework to disentangle routinized energy consumption, focusing on energy services related to washing, standby, and cooking. We investigate the potential of home energy advice to change elements of routinized behaviors, namely meanings, knowledge, and technologies. Using a randomized controlled field trial on a probabilistic sample of households, we found short-term treatment effects related to increased usage of lids during cooking and improved knowledge of IT-related energy consumption, as well as negative effects regarding multi-sockets and washing frequency. Our findings suggest that meanings (e.g., preferences underlying routinized behaviors) are less subject to change, and that sociodemographic variables are associated with routinized behaviors in complex ways. Our disentangling of energy demand into elements of routines enables us to show how home energy advice may change behaviors and knowledge. This study highlights the benefits of a multifaceted perspective for understanding household energy consumption and can be used to inform intervention and policy design. [less ▲]

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See detailBias in the eye of beholder? 25 years of election monitoring in Europe
Mochtak, Michal UL; Drnovsky, Adam; Lesschaeve, Christophe UL

in Democratization (2022), Online

Building on the original corpus of OSCE monitoring reports, the article analyses quarter of century of election monitoring in Europe and assesses the congruence of OSCE written assessments with expert ... [more ▼]

Building on the original corpus of OSCE monitoring reports, the article analyses quarter of century of election monitoring in Europe and assesses the congruence of OSCE written assessments with expert views. We show that, overall, the OSCE monitoring reports are highly correlated and congruent with expert assessments. More importantly, the level of congruence between the two increases with time. However, we also identify various forms of biases rooted in strategic interests and institutional preconditions. Mainly, we show that OSCE has a strong and positive bias towards Russia and its allies when it comes to election assessments indicating defensive and lenient stances. We theorize this mechanism as a pushback effect and show that although Russia’s effort to cripple the activities of OSCE in the past two decades was not successful, OSCE was effectively forced into a defensive position producing less critical assessments than reality warrants. [less ▲]

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See detailAn Empirical Study on Data Distribution-Aware Test Selection for Deep Learning Enhancement
Hu, Qiang UL; Guo, Yuejun UL; Cordy, Maxime UL et al

in ACM Transactions on Software Engineering and Methodology (2022)

Similar to traditional software that is constantly under evolution, deep neural networks (DNNs) need to evolve upon the rapid growth of test data for continuous enhancement, e.g., adapting to distribution ... [more ▼]

Similar to traditional software that is constantly under evolution, deep neural networks (DNNs) need to evolve upon the rapid growth of test data for continuous enhancement, e.g., adapting to distribution shift in a new environment for deployment. However, it is labor-intensive to manually label all the collected test data. Test selection solves this problem by strategically choosing a small set to label. Via retraining with the selected set, DNNs will achieve competitive accuracy. Unfortunately, existing selection metrics involve three main limitations: 1) using different retraining processes; 2) ignoring data distribution shifts; 3) being insufficiently evaluated. To fill this gap, we first conduct a systemically empirical study to reveal the impact of the retraining process and data distribution on model enhancement. Then based on our findings, we propose a novel distribution-aware test (DAT) selection metric. Experimental results reveal that retraining using both the training and selected data outperforms using only the selected data. None of the selection metrics perform the best under various data distributions. By contrast, DAT effectively alleviates the impact of distribution shifts and outperforms the compared metrics by up to 5 times and 30.09% accuracy improvement for model enhancement on simulated and in-the-wild distribution shift scenarios, respectively. [less ▲]

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See detailHomological projective duality for the Segre cubic
Beckmann, Thorsten; Belmans, Pieter UL

E-print/Working paper (2022)

The Segre cubic and Castelnuovo-Richmond quartic are two projectively dual hypersurfaces in P^4, with a long and rich history starting in the 19th century. We will explain how Kuznetsov's theory of ... [more ▼]

The Segre cubic and Castelnuovo-Richmond quartic are two projectively dual hypersurfaces in P^4, with a long and rich history starting in the 19th century. We will explain how Kuznetsov's theory of homological projective duality lifts this projective duality to a relationship between the derived category of a small resolution of the Segre cubic and a small resolution of the Coble fourfold, the double cover of P^4 ramified along the Castelnuovo-Richmond quartic. Homological projective duality then provides a description of the derived categories of linear sections, which we will describe to illustrate the theory. The case of the Segre cubic and Coble fourfold is non-trivial enough to exhibit interesting behavior, whilst being easy enough to explain the general machinery in this special and very classical case. [less ▲]

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See detailAn Evolving International Research Collaboration Network: Spatial and Thematic Developments in Co-Authored Higher Education Research, 1998–2018
Fu, Yuan Chih; Marques, Marcelo; Tseng, Yuen-Hsien et al

in Scientometrics (2022), 127

Co-authored research articles in the disciplinarily heterogeneous field of higher education have dramatically increased in this century, largely driven, as in other fields, by rising international co ... [more ▼]

Co-authored research articles in the disciplinarily heterogeneous field of higher education have dramatically increased in this century, largely driven, as in other fields, by rising international co-authorships. We examine this evolving international collaboration network in higher education research over two decades. To do so, we apply automated bibliometric topic identification and social network analysis of 9,067 papers in 13 core higher education journals (1998–2018). Remarkable expansion in the volume of papers and co-authorships has, surprisingly, not resulted in a more diverse network. Rather, existing co-authorship patterns are strengthened, with the dominance of scholars from a few Anglophone countries largely maintained. Researchers globally seek to co-author with leading scholars in these countries, especially the US, UK, and Australia—at least when publishing in the leading general HE journals based there. Further, the two-mode social network analysis of countries and topics suggests that while Anglophone countries have led the development of higher education research, China and Germany, as leading research-producing countries, are increasingly influential within this world-spanning network. Topically, the vast majority of co-authored papers in higher education research focuses on individual-level phenomena, with organizational and system-level or country-level analysis constituting a (much) smaller proportion, despite policymakers’ emphasis on cross-national comparisons and the growing importance of university actorhood. We discuss implications thereof for the future of the multidisciplinary higher education field. [less ▲]

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See detailThe Effect of Noise Level on the Accuracy of Causal Discovery Methods with Additive Noise Models
Kap, Benjamin; Aleksandrova, Marharyta UL; Engel, Thomas UL

in Communications in Computer and Information Science (2022), 1530

In recent years a lot of research was conducted within the area of causal inference and causal learning. Many methods were developed to identify the cause-effect pairs. These methods also proved their ... [more ▼]

In recent years a lot of research was conducted within the area of causal inference and causal learning. Many methods were developed to identify the cause-effect pairs. These methods also proved their ability to successfully determine the direction of causal relationships from observational real-world data. Yet in bivariate situations, causal discovery problems remain challenging. A class of methods, that also allows tackling the bivariate case, is based on Additive Noise Models (ANMs). Unfortunately, one aspect of these methods has not received much attention until now: what is the impact of different noise levels on the ability of these methods to identify the direction of the causal relationship? This work aims to bridge this gap with the help of an empirical study. We consider a bivariate case and two specific methods Regression with Subsequent Independence Test and Identification using Conditional Variances. We perform a set of experiments with an exhaustive range of ANMs where the additive noises’ levels gradually change from 1% to 10000% of the causes’ noise level (the latter remains fixed). Additionally, we consider several different types of distributions as well as linear and non-linear ANMs. The results of the experiments show that these causal discovery methods can fail to capture the true causal direction for some levels of noise. [less ▲]

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See detailBeyond the bubble: will NFTs and digital proof of ownership empower creative industry entrepreneurs
Chalmers, Dominic; Fisch, Christian UL; Matthews, Russell et al

in Journal of Business Venturing Insights (2022), 17

Non-fungible Tokens (NFTs) are blockchain-enabled cryptographic assets that represent proof-of-ownership for digital objects. The use of NFTs has been pioneered by creative industry entrepreneurs who have ... [more ▼]

Non-fungible Tokens (NFTs) are blockchain-enabled cryptographic assets that represent proof-of-ownership for digital objects. The use of NFTs has been pioneered by creative industry entrepreneurs who have sought to generate new revenue streams and modes of stakeholder engagement. Despite rapid growth in popularity, concerns have been raised around the legal ownership of NFT assets and the prevalence of speculation and fraud associated with NFT trading. In this rapid response article, we explore the value of NFTs for creative industry entrepreneurs. First, we examine the novel digital affordances of the technology; second, we analyse NFTs through the prism of the recent Initial Coin Offering (ICO) boom and bust; and finally, we take a longer-term historical perspective to consider how past speculative waves inform the present NFT economy. While we identify some potentially valuable artistic and financial opportunities for creative industry entrepreneurs, we conclude that NFTs should be approached with caution. [less ▲]

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See detailNeurodegeneration and neuroinflammation are linked, but independent of a-synuclein inclusions, in a seeding/spreading mouse model of Parkinson's disease
Garcia, Pierre UL; Wemheuer, W.; Uriarte, O. et al

in Glia (2022)

A key pathological process in Parkinson's disease (PD) is the transneuronal spreading of α-synuclein. Alpha-synuclein (α-syn) is a presynaptic protein that, in PD, forms pathological inclusions. Other ... [more ▼]

A key pathological process in Parkinson's disease (PD) is the transneuronal spreading of α-synuclein. Alpha-synuclein (α-syn) is a presynaptic protein that, in PD, forms pathological inclusions. Other hallmarks of PD include neurodegeneration and microgliosis in susceptible brain regions. Whether it is primarily transneuronal spreading of α-syn particles, inclusion formation, or other mechanisms, such as inflammation, that cause neurodegeneration in PD is unclear. We used a model of spreading of α-syn induced by striatal injection of α-syn preformed fibrils into the mouse striatum to address this question. We performed quantitative analysis for α-syn inclusions, neurodegeneration, and microgliosis in different brain regions, and generated gene expression profiles of the ventral midbrain, at two different timepoints after disease induction. We observed significant neurodegeneration and microgliosis in brain regions not only with, but also without α-syn inclusions. We also observed prominent microgliosis in injured brain regions that did not correlate with neurodegeneration nor with inclusion load. Using longitudinal gene expression profiling, we observed early gene expression changes, linked to neuroinflammation, that preceded neurodegeneration, indicating an active role of microglia in this process. Altered gene pathways overlapped with those typical of PD. Our observations indicate that α-syn inclusion formation is not the major driver in the early phases of PD-like neurodegeneration, but that microglia, activated by diffusible, oligomeric α-syn, may play a key role in this process. Our findings uncover new features of α-syn induced pathologies, in particular microgliosis, and point to the necessity for a broader view of the process of α-syn spreading. [less ▲]

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See detailProject-based learning course on metabolic network modelling in computational systems biology.
Sauter, Thomas UL; Bintener, Tamara; Kishk, Ali UL et al

in PLoS computational biology (2022), 18(1), 1009711

Project-based learning (PBL) is a dynamic student-centred teaching method that encourages students to solve real-life problems while fostering engagement and critical thinking. Here, we report on a PBL ... [more ▼]

Project-based learning (PBL) is a dynamic student-centred teaching method that encourages students to solve real-life problems while fostering engagement and critical thinking. Here, we report on a PBL course on metabolic network modelling that has been running for several years within the Master in Integrated Systems Biology (MISB) at the University of Luxembourg. This 2-week full-time block course comprises an introduction into the core concepts and methods of constraint-based modelling (CBM), applied to toy models and large-scale networks alongside the preparation of individual student projects in week 1 and, in week 2, the presentation and execution of these projects. We describe in detail the schedule and content of the course, exemplary student projects, and reflect on outcomes and lessons learned. PBL requires the full engagement of students and teachers and gives a rewarding teaching experience. The presented course can serve as a role model and inspiration for other similar courses. [less ▲]

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See detailMechanistically Coupled PK (MCPK) Model to Describe Enzyme Induction and Occupancy Dependent DDI of Dabrafenib Metabolism.
Albrecht, Marco; Kogan, Yuri; Kulms, Dagmar et al

in Pharmaceutics (2022), 14(2),

Dabrafenib inhibits the cell proliferation of metastatic melanoma with the oncogenic BRAF(V600)-mutation. However, dabrafenib monotherapy is associated with pERK reactivation, drug resistance, and ... [more ▼]

Dabrafenib inhibits the cell proliferation of metastatic melanoma with the oncogenic BRAF(V600)-mutation. However, dabrafenib monotherapy is associated with pERK reactivation, drug resistance, and consequential relapse. A clinical drug-dose determination study shows increased pERK levels upon daily administration of more than 300 mg dabrafenib. To clarify whether such elevated drug concentrations could be reached by long-term drug accumulation, we mechanistically coupled the pharmacokinetics (MCPK) of dabrafenib and its metabolites. The MCPK model is qualitatively based on in vitro and quantitatively on clinical data to describe occupancy-dependent CYP3A4 enzyme induction, accumulation, and drug-drug interaction mechanisms. The prediction suggests an eight-fold increase in the steady-state concentration of potent desmethyl-dabrafenib and its inactive precursor carboxy-dabrafenib within four weeks upon 150 mg b.d. dabrafenib. While it is generally assumed that a higher dose is not critical, we found experimentally that a high physiological dabrafenib concentration fails to induce cell death in embedded 451LU melanoma spheroids. [less ▲]

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See detailDrug targeting opportunities en route to Ras nanoclusters.
Pavic, Karolina UL; Chippalkatti, Rohan UL; Abankwa, Daniel UL

in Advances in cancer research (2022), 153

Disruption of the native membrane organization of Ras by the farnesyltransferase inhibitor tipifarnib in the late 1990s constituted the first indirect approach to drug target Ras. Since then, our ... [more ▼]

Disruption of the native membrane organization of Ras by the farnesyltransferase inhibitor tipifarnib in the late 1990s constituted the first indirect approach to drug target Ras. Since then, our understanding of how dynamically Ras shuttles between subcellular locations has changed significantly. Ras proteins have to arrive at the plasma membrane for efficient MAPK-signal propagation. On the plasma membrane Ras proteins are organized into isoform specific proteo-lipid assemblies called nanocluster. Recent evidence suggests that Ras nanocluster have a specific lipid composition, which supports the recruitment of effectors such as Raf. Conversely, effectors possess lipid-recognition motifs, which appear to serve as co-incidence detectors for the lipid domain of a given Ras isoform. Evidence suggests that dimeric Raf proteins then co-assemble dimeric Ras in an immobile complex, thus forming the minimal unit of an active nanocluster. Here we review established and novel trafficking chaperones and trafficking factors of Ras, along with the set of lipid and protein modulators of Ras nanoclustering. We highlight drug targeting approaches and opportunities against these determinants of functional Ras membrane organization. Finally, we reflect on implications for Ras signaling in polarized cells, such as epithelia, which are a common origin of tumorigenesis. [less ▲]

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See detailThe Pandemic Worsens Europe’s Housing Problems
Flynn, Lindsay UL

in Current History (2022), 121(833), 83-89

Housing is a flash point in many European countries, with protests erupting and citizens voting to wrench properties from big investors. Inequality is driving the explosive debate, as households across ... [more ▼]

Housing is a flash point in many European countries, with protests erupting and citizens voting to wrench properties from big investors. Inequality is driving the explosive debate, as households across the income distribution face very different kinds of challenges and opportunities in today’s unequal housing markets. The COVID-19 pandemic has amplified the risks and rewards already present across different subgroups. This housing-generated inequality creates a conundrum for governments that must balance the interests of competing constituencies with complex housing markets, and points to fundamental questions about how to order society. [less ▲]

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See detailA topological Paley-Wiener-Schwartz Theorem for sections of homogeneous vector bundles on G/K
Palmirotta, Guendalina UL; Olbrich, Martin UL

E-print/Working paper (2022)

We study the Fourier transform for compactly supported distributional sections of complex homogeneous vector bundles on symmetric spaces of non-compact type X = G/K. We prove a characterisation of their ... [more ▼]

We study the Fourier transform for compactly supported distributional sections of complex homogeneous vector bundles on symmetric spaces of non-compact type X = G/K. We prove a characterisation of their range. In fact, from Delorme’s Paley-Wiener theorem for compactly supported smooth functions on a real reductive group of Harish-Chandra class, we deduce topological Paley-Wiener and Paley-Wiener- Schwartz theorems for sections. [less ▲]

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See detailInclusion Dialogue with Justin J.W. Powell
Powell, Justin J W UL

Speeches/Talks (2022)

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