Leiden University Scholary Publications
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Do emerging guidelines for automotive life cycle assessment lead to consistent results?: The case of battery electric vehicles
Get PDFRoad transportation is responsible for one fifth of European Union’'s total greenhouse gases (GHGs), besides other environmental concerns. Thus, Life Cycle Assessment (LCA) is increasingly used in the automotive sector to guide environmental strategies and policy compliance, emphasizing the importance of methodological choices and their standardization. This study examines three recent and influential LCA guidelines in Europe developed through major harmonization initiatives: TranSensus LCA, Catena-X, and the United Nations Economic Commission for Europe Automotive LCA guidelines. A qualitative comparison of methodological choices and assumptions in these guidelines was conducted to identify areas of overlap, divergences, and flexibilities within each guideline. The analysis showed broad alignment across guidelines, with divergences mainly in electricity modeling and addressing multifunctionality problems, where also degrees of freedom within guidelines remain. Applied to a battery electric vehicle LCA, a quantitative comparison across guidelines (based on a basic expected application of each guideline) demonstrated less than a 10 % difference in most impact categories. Furthermore, the intra-guideline choices (flexibilities) were tested in the LCA model, showing larger variations relative to the basic application of each guideline (e.g., −27 % and +11 % change in climate change impacts when shifting to the Circular Footprint Formula (CFF) and static electricity modeling, respectively, in UNECE guidelines). These findings suggest that horizontal harmonization across guidelines is well advanced, but vertical harmonization within guidelines requires improvement. Future improvements could include more detailed guidance in some parts like CFF application to reduce subjectivity, automation of application, and comprehensiveness in impact categories and life cycle stages coverage.Horizon 2020(H2020)101056715Industrial Ecolog
Learning in automated negotiation
Get PDFThis dissertation advances automated negotiation by developing agents that can learn and adapt across diverse negotiation settings through three increasingly sophisticated approaches: automated algorithm configuration, portfolio-based strategy selection, and end-to-end reinforcement learning with graph neural networks. We demonstrate that while each of our developed methods successfully pushes the boundaries of what negotiation agents can achieve, our end-to-end reinforcement learning approach shows particular promise in reducing human-induced bias while maintaining conceptual simplicity. In the second part, we evaluate negotiating agents through extensive empirical research, including organising the Automated Negotiating Agents Competition (ANAC) and demonstrate that learning agents generally outperform non-learning agents. Our analysis reveals fundamental limitations in standard evaluation metrics for negotiation agents, particularly showing that rankings based on average utility are highly dependent on opponent group composition. The dissertation concludes by proposing multi-agent meeting scheduling as a concrete application domain that could provide clear performance criteria and drive meaningful progress in automated negotiation research.NWO024.004.022Computer Systems, Imagery and Medi
An examination of the suitability of PADev as a method for effective participatory assessment of the development of higher education institutions: the case of Eduardo Mondlane University (1976-2016)
Get PDFThe thesis examines the suitability of PADev method for effective participatory assessment of the development of Eduardo Mondlane University (EMU). The PADev experiment conducted at EMU aimed at assessing its development from an inner perspective. As a bottom-up approach that enabled tracking factors and actors that influenced the transformation of the university, PADev tools allowed tracing events, changes and development interventions implemented at the university in the last 4 decades.The PADev experiment succeeded in enabling collective reconstruction of the history of the university, particularly the history of the sampled units by making primary beneficiaries of development interventions recall their experiential and factual knowledge, to build up a shared vision on the development path of EMU.The findings concerning the effectiveness of the PADev method showed that PADev conceived as a community development evaluation tool, did not fully suit the assessment of a higher education institution such as EMU. The dimension and complexity of its processes, organisation and structure jeopardised the successful application of the method. The lack of commitment of the study participants compromised its capability to gather data, and PADev alone did not convey the wider context of change and development.NFP-NufficASC – Publicaties niet-programma gebonde
Leveraging targeted protein degradation for G protein-coupled receptors: the development of CCR2 molecular degraders
Get PDFTargeted protein degradation (TPD) is one of the most prominent and rapidly advancing modalities in drug discovery. However, only few degraders have been reported for the membrane-bound G protein-coupled receptors (GPCRs). Therefore, using CC chemokine receptor 2 (CCR2) as a GPCR model, we synthesized potential CCR2 molecular degraders. The putative proteolysis-targeting chimeras (PROTACs) employed an allosteric intracellular CCR2 ligand tethered to commonly used E3 ligase ligands. Among these compounds, LUF7996 (8) demonstrated engagement of both CCR2 and the E3 ligase cereblon and displayed sustained and concentration-dependent degradation of CCR2 over 24 h. Mechanistic studies revealed the reliance of LUF7996 on the lysosomal pathway to induce CCR2 degradation. Finally, LUF7996 (8) efficiently inhibited monocyte migration in a transwell assay. Collectively, the developed assessment workflow led to identification of the first CCR2 molecular degraders and has the potential to expand the repertoire of degraders targeting the pharmacologically rich GPCRs.Toxicolog
Pollinators in complex landscapes: modelling and mapping the distribution of wild bees and hoverflies in the Netherlands
Get PDFThis thesis explores how bees and hoverflies are distributed across the Dutch landscape and how ecological and landscape factors shape their occurrence. Because these insects are essential pollinators for wild plants and crops, understanding their spatial distribution is vital for conservation and food security. Using species distribution models (SDMs), the research addresses key challenges such as incorporating landscape complexity, accounting for biotic interactions, and integrating fine-scale habitat features.First, the thesis compares threatened and non-threatened bee species, revealing that threatened bees have smaller ranges, occupy more extreme climates, rely on fewer natural habitat types, and benefit less from urban green spaces. These patterns underscore their vulnerability under environmental change. Next, the work demonstrates that including biotic interaction, such as plant–pollinator relationships and parasitism, significantly improves SDM performance, especially depending on specialization and data resolution.The research also incorporates small-scale agricultural landscape features like hedges and ditch banks, showing that these elements increase predicted species richness and serve as biodiversity hotspots along field edges. Field data from three agricultural regions further confirm that landscape elements support higher abundance and diversity of bees and hoverflies, influenced by floral composition, vegetation structure, region, and season.Overall, the thesis enhances ecological understanding and provides improved tools and insights for conserving pollinators in complex, changing landscapes.Naturali
Knowledge multiplies when shared — when calling things by their right name: improving the validation and exchange of genetic data in research and diagnostics
Get PDFGenetic disorders and hereditary disease risks pose major challenges for healthcare worldwide. Yet only a small portion of all collected genetic data is shared, and much of the shared information is incomplete or inaccurately described. As a result, valuable knowledge is lost. This thesis focuses on improving the way genetic data is standardized and shared, so that researchers and clinicians can collaborate more effectively and reach faster, more reliable diagnoses. A key element of this work is the development of the Leiden Open Variation Database (LOVD), a freely available platform for storing and sharing genetic variants in a standardized format. Used globally, LOVD helps bridge the gap between scientific research and clinical diagnostics. The thesis also contributes to improving international standards for describing genetic variants, making data easier to compare and reuse. To further enhance data quality, new software tools were developed to automatically detect and correct errors in variant descriptions. Collaborations with scientific publishers were established to enable these checks during the publication process, preventing mistakes from entering the scientific literature. Together, these developments make it easier to share and interpret genetic information, ultimately supporting more accurate diagnoses, stronger research outcomes, and better patient care worldwide.LUMC / Geneeskund
Combining bayesian and evidential uncertainty quantification for improved bioactivity modeling
Get PDFUncertainty quantification (UQ) has been recognized as a prerequisite for reliable and trustworthy computational modeling in drug discovery. Two widely considered paradigms, Bayesian methods (deep ensemble and MC dropout) and evidential learning, differ in their computational demands and expressivity of uncertainties, excelling in complementary settings. Here, we propose hybrid approaches that combine both paradigms and benchmark them on the Papyrus++ data set across two end points (xC50, Kx) and multiple split strategies. Our ensemble of evidential models (EOE) consistently achieves the best overall performance, yielding the lowest RMSE and leading CRPS and interval scores, including under the most challenging distributional shifts. While large ensembles often excel in rejection-based utility, EOE matches or surpasses them at a fraction of the computational cost. Statistical tests confirm its advantage, and a hardware-agnostic compute analysis highlights favorable performance-efficiency trade-offs. These results demonstrate that combining evidential and Bayesian principles yields more accurate and informative uncertainties for bioactivity modeling, with EOE offering a robust─and computationally practical─default for uncertainty-aware decision-making in drug discovery.Medicinal Chemistr
Electrocatalysis in confinement: metal-organic frameworks for oxygen reduction
Get PDFThe confinement of molecular catalysts in metal-organic frameworks has the potential to lead to significant improvements in selectivity, long term activity and catalyst stability. The efficiency of electrocatalysis in MOFs is expected to be limited by either the activity of the catalyst, mass transport through the framework or electron transfer. Although initial strategies to improve electron transfer throughout MOFs have been described, major knowledge gaps still exist. For example, it remains unclear how electron transport in MOFs affects electrocatalysis and how mass transport of reactants limits electrocatalysis, and what the effects are of confinement in a MOF on the catalyst structure. It is expected that these research questions remain an important area of research in the future. The research described in this thesis concerns the oxygen-reduction catalyst Cu-tmpaCOOH confined in MOFs. The Cu-tmpa catalyst and its catalytic performance are well characterized.[117–119] The main challenge regarding this catalyst concerns its long-term stability, which may be improved through immobilization in MOFs. The research described in this thesis addresses a number of the challenges mentioned in Section 1.7. In Chapter 2 the effect is discussed of incorporation of the Cu-tmpaCOOH catalyst in a MOF on its catalytic activity and selectivity. In Chapter 3 the effect of confinement on the catalyst itself is described. The homogeneity of the catalyst and the identity of the true active species are discussed. Chapter 4 discusses the effect of electron transport through the MOF on the catalyst and its catalytic performance. This chapter provides a comparison between a redox inert MOF and a MOF containing redox-active linkers. The efficiency of electron transfer to the catalyst, the homogeneity of the catalyst and catalytic activity and selectivity have been investigated. Chapter 5 contains a detailed discussion of the effect of pH on charge transport in redox active MOFs. Chapter 6 provides a summary of the results in this thesis as well as a conclusion and outlook.Metals in Catalysis, Biomimetics & Inorganic Material
Kroniek van het constitutioneel recht
No full textThe Legitimacy and Effectiveness of Law & Governance in a World of Multilevel Jurisdiction