Eldorado - Repository of the TU Dortmund
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Leveraging open source land use and land cover data for urban and regional planning in transforming areas
(2024-11-26) Klopfer, Florian; Gruehn, Dietwald
A steadily growing repository of publicly available land use and land cover (LULC) data holds great potential for addressing pressing challenges, e.g., associated with climate change or profound societal and economic transformations. However, significant portions of this data remain underutilised. This article exemplifies the practical applicability of harnessing such data for advancing spatial planning within the Rhineland mining area, Germany – a region currently undergoing significant structural shifts induced by the upcoming coal phase-out. The study features a three-pronged approach, integrating and overlaying numerous diverse datasets. First, we conduct a comprehensive assessment of ecosystem services (ES) in the region (1). Moreover, we present an evaluation of areas (un)suitable for future settlement development based on multiple constraints (2). Finally, we offer community-level analyses assessing the most suitable future land use focus, considering current LULC and ES information presenting three primary options: settlement, agriculture and natural/recreation (3). Findings are conveyed at various levels of spatial and informational granularity. We show spatially differentiated patterns of combined ES pronunciation, constraints for settlement development, and the suitability for the mentioned land use categories being meaningful in both the detailed and the reduced representation. This accommodates distinct planning requirements and audiences, spanning from regional to urban land use planning and from informing laypersons to providing knowledge to planning professionals. The approach possesses wide-ranging applicability and adaptability. It should encourage practitioners/planners to explore untapped potentials within open data for shaping planning processes and informing stakeholders. Primary benefits include objectifying and optimising planning processes while promoting their acceptance.
Strong and tough double network hydrogels based on poly(2-oxazoline) and polyacrylates
(2025) Benitez-Duif, Paola Andrea; Tiller, Jörg C.; Vogt, Dieter
Double network hydrogels (DNHs) are known for their exceptional stiffness, toughness, and tunable characteristics, making them valuable for applications in membrane technology, energy storage, and, of significant importance, in biomedicine. These materials show great potential for replicating complex biomaterials such as cartilage. This work presents, for the first time, the development of DNHs based on poly(2-oxazoline) as the primary network and various polyacrylates as the secondary network, resulting in materials with remarkable toughness. The thesis is structured into three main parts, each addressing different features and challenges involved in developing these DNHs.
The first section focuses on the synthesis and optimization of DNHs using poly(2-oxazoline)s (POx) and poly(acrylic acid) (PAA), yielding materials with biomechanical properties comparable to cartilage, including high compressive strength and durability under physiological conditions. The second section further explores the potential of POx-based DNHs by incorporating various polyacrylates as secondary networks. This part emphasizes the investigation of interactions, functional groups, and the structural influence of the networks involved on the mechanical performance of the resulting hydrogels, achieving superior mechanical properties compared to conventional DNHs composed solely of polyacrylate networks.
Additionally, the thesis addresses the critical challenge of maintaining hydrogel functionality across a wide pH range, essential for implantable materials exposed to varying tissue environments and inflammatory responses. A novel DNH formulation, comprising poly(2-methyl-2-oxazoline) and poly(acrylic acid-co-acrylamide) P(AA-co-AAm), is developed, demonstrating remarkable stability and mechanical integrity across pH levels from 3.4 to 10.5.
Through extensive mechanical testing, this research highlights the robustness and versatility of these advanced DNHs, positioning them as strong candidates for use in tissue regeneration, implants, and other biomedical applications where durability and adaptability are crucial. This work contributes significantly to the understanding and application of DNHs in complex physiological environments.
Development of subjective well-being in adolescents before and during the COVID-19 pandemic
(2025-01-30) Eckert, Helene; Paschke, Patrick; Wirthwein, Linda; Steinmayr, Ricarda
Previous studies have already revealed detrimental effects of the COVID-19 pandemic on school students’ subjective well-being (SWB). However, there is a lack of studies examining the development of various facets of SWB such as life satisfaction, mood as well as domain satisfactions regarding peers, family, or school before and during the pandemic among adolescents longitudinally. Furthermore, the present study aims to shed further light on various moderators such as gender, age, migration background and socioeconomic status. Data from N = 207 students (Grade 5 to 9) from two German schools were assessed on four measurement time points, three before and one after the onset of the pandemic. Piecewise latent growth curve models with three time slopes were conducted to investigate the development of SWB and its moderators. They showed significant declines in general mood and domain-specific satisfaction with family, peers and school before the COVID-19 pandemic. However, during the COVID-19 pandemic, only satisfaction with family decreased significantly. Among the moderators, especially the socioeconomic status indicated interindividual differences in the variation of different SWB facets.
Improvement of protein quantification for proteins with shared peptides by using bipartite peptide-protein graphs
(2024) Schork, Karin Ulrike; Rahnenführer, Jörg; Eisenacher, Martin
In bottom-up proteomics, proteins are enzymatically digested to peptides, smaller amino acid chains, which are then measured via mass spectrometry. The received peptide quantities need to be summarized to protein quantities to obtain biological insights (protein quantification). This is complicated by the presence of shared peptides that occur in multiple protein sequences. The relationship between peptides and corresponding proteins can be represented as bipartite graphs. A novel protein quantification method, called bppgQuant, is proposed which calculates protein ratios from peptide ratios. It uses the structures of the bipartite peptide-protein graphs to build an equation system. As this system is not exactly solvable in many cases, an optimization problem is formulated to find solutions which minimize the sum of squared error terms. bppgQuant is evaluated and compared to the methods SCAMPI and PQP using four different quantitative datasets from different organisms, that contain known protein ratios. In summary, bppgQuant showed good results in comparison to SCAMPI and PQP, especially when protein nodes not needed to explain the measured peptide ratios were removed before optimization.
Coworking Best Practices for European Universities
(2025-02) Hensellek, Simon; Weißwange, Jonah; Orel, Marko; Válek, Lukáš; Diller, Sandra J.; Weber, Magdalena; Capdevila, Ignasi; Mérindol, Valérie