Refine
Year of publication
- 2023 (518) (remove)
Document Type
- Doctoral Thesis (210)
- Article (191)
- Part of a Book (23)
- Postprint (22)
- Working Paper (17)
- Monograph/Edited Volume (16)
- Conference Proceeding (14)
- Review (8)
- Habilitation Thesis (6)
- Part of Periodical (3)
Language
- English (518) (remove)
Keywords
- digital education (34)
- Digitale Bildung (32)
- Kursdesign (32)
- MOOC (32)
- Micro Degree (32)
- Online-Lehre (32)
- Onlinekurs (32)
- Onlinekurs-Produktion (32)
- e-learning (32)
- micro degree (32)
Institute
- Institut für Biochemie und Biologie (65)
- Extern (62)
- Fachgruppe Betriebswirtschaftslehre (59)
- Hasso-Plattner-Institut für Digital Engineering GmbH (57)
- Fachgruppe Volkswirtschaftslehre (35)
- Institut für Chemie (32)
- Institut für Geowissenschaften (32)
- Institut für Physik und Astronomie (32)
- Fachgruppe Politik- & Verwaltungswissenschaft (26)
- Historisches Institut (19)
The emerging threat of antibiotic-resistant bacteria has become a global challenge in the last decades, leading to a rising demand for alternative treatments for bacterial infections. One approach is to target the bacterial cell envelope, making understanding its biophysical properties crucial. Specifically, bacteriophages use the bacterial envelope as an entry point to initiate infection, and they are considered important building blocks of new antibiotic strategies against drug-resistant bacteria.. Depending on the structure of the cell wall, bacteria are classified as Gram-negative and Gram-positive. Gram-negative bacteria are equipped with a complex cell envelope composed of two lipid membranes enclosing a rigid peptidoglycan layer. The synthesis machinery of the Gram-negative cell envelope is the target of antimicrobial agents, including new physical sanitizing procedures addressing the outer membrane (OM). It is therefore very important to study the biophysical properties of the Gram-negative bacterial cell envelope. The high complexity of the Gram-negative OM sets the demand for a model system in which the contribution of individual components can be evaluated separately. In this respect, giant unilamellar vesicles (GUVs) are promising membrane systems to study membrane properties while controlling parameters such as membrane composition and surrounding medium conditions.
The aim of this work was to develop methods and approaches for the preparation and characterization of a GUV-based membrane model that mimics the OM of the Gram-negative cell envelope. A major component of the OM is the lipopolysaccharide (LPS) on the outside of the OM heterobilayer. The vesicle model was designed to contain LPS in the outer leaflet and lipids in the inner leaflet. Furthermore, the interaction of the prepared LPS-GUVs with bacteriophages was tested. LPS containing GUVs were prepared by adapting the inverted emulsion technique to meet the challenging properties of LPS, namely their high self-aggregation rate in aqueous solutions. Notably, an additional emulsification step together with the adaption of solution conditions was employed to asymmetrically incorporate LPS containing long polysaccharide chains into the artificial membranes. GUV membrane asymmetry was verified with a fluorescence quenching assay. Since the necessary precautions for handling the quenching agent sodium dithionite are often underestimated and poorly described, important parameters were tested and identified to obtain a stable and reproducible assay. In the context of varied LPS incorporation, a microscopy-based technique was introduced to determine the LPS content on individual GUVs and to directly compare vesicle properties and LPS coverage. Diffusion coefficient measurements in the obtained GUVs showed that increasing LPS concentrations in the membranes resulted in decreased diffusivity.
Employing LPS-GUVs we could demonstrate that a Salmonella bacteriophage bound with high specificity to its LPS receptor when presented at the GUV surface, and that the number of bound bacteriophages scaled with the amount of presented LPS receptor. In addition to binding, the bacteriophages were able to eject their DNA into the vesicle lumen. LPS-GUVs thus provide a starting platform for bottom-up approaches for the generation of more complex membranes, in which the effects of individual components on the membrane properties and the interaction with antimicrobial agents such as bacteriophages could be explored.
Successful sentence comprehension requires the comprehender to correctly figure out who did what to whom. For example, in the sentence John kicked the ball, the comprehender has to figure out who did the action of kicking and what was being kicked. This process of identifying and connecting the syntactically-related words in a sentence is called dependency completion. What are the cognitive constraints that determine dependency completion? A widely-accepted theory is cue-based retrieval. The theory maintains that dependency completion is driven by a content-addressable search for the co-dependents in memory. The cue-based retrieval explains a wide range of empirical data from several constructions including subject-verb agreement, subject-verb non-agreement, plausibility mismatch configurations, and negative polarity items.
However, there are two major empirical challenges to the theory: (i) Grammatical sentences’ data from subject-verb number agreement dependencies, where the theory predicts a slowdown at the verb in sentences like the key to the cabinet was rusty compared to the key to the cabinets was rusty, but the data are inconsistent with this prediction; and, (ii) Data from antecedent-reflexive dependencies, where a facilitation in reading times is predicted at the reflexive in the bodybuilder who worked with the trainers injured themselves vs. the bodybuilder who worked with the trainer injured themselves, but the data do not show a facilitatory effect.
The work presented in this dissertation is dedicated to building a more general theory of dependency completion that can account for the above two datasets without losing the original empirical coverage of the cue-based retrieval assumption. In two journal articles, I present computational modeling work that addresses the above two empirical challenges.
To explain the grammatical sentences’ data from subject-verb number agreement dependencies, I propose a new model that assumes that the cue-based retrieval operates on a probabilistically distorted representation of nouns in memory (Article I). This hybrid distortion-plus-retrieval model was compared against the existing candidate models using data from 17 studies on subject-verb number agreement in 4 languages. I find that the hybrid model outperforms the existing models of number agreement processing suggesting that the cue-based retrieval theory must incorporate a feature distortion assumption.
To account for the absence of facilitatory effect in antecedent-reflexive dependencies, I propose an individual difference model, which was built within the cue-based retrieval framework (Article II). The model assumes that individuals may differ in how strongly they weigh a syntactic cue over a number cue. The model was fitted to data from two studies on antecedent-reflexive dependencies, and the participant-level cue-weighting was estimated. We find that one-fourth of the participants, in both studies, weigh the syntactic cue higher than the number cue in processing reflexive dependencies and the remaining participants weigh the two cues equally. The result indicates that the absence of predicted facilitatory effect at the level of grouped data is driven by some, not all, participants who weigh syntactic cues higher than the number cue. More generally, the result demonstrates that the assumption of differential cue weighting is important for a theory of dependency completion processes. This differential cue weighting idea was independently supported by a modeling study on subject-verb non-agreement dependencies (Article III).
Overall, the cue-based retrieval, which is a general theory of dependency completion, needs to incorporate two new assumptions: (i) the nouns stored in memory can undergo probabilistic feature distortion, and (ii) the linguistic cues used for retrieval can be weighted differentially. This is the cumulative result of the modeling work presented in this dissertation.
The dissertation makes an important theoretical contribution: Sentence comprehension in humans is driven by a mechanism that assumes cue-based retrieval, probabilistic feature distortion, and differential cue weighting. This insight is theoretically important because there is some independent support for these three assumptions in sentence processing and the broader memory literature. The modeling work presented here is also methodologically important because for the first time, it demonstrates (i) how the complex models of sentence processing can be evaluated using data from multiple studies simultaneously, without oversimplifying the models, and (ii) how the inferences drawn from the individual-level behavior can be used in theory development.
National Action Plans (NAPs) have been increas-ingly adopted world-wide after the Vienna Dec-laration in 1993, where it was urged to consider the improvement and promotion of Human Rights. In this paper, we discuss their usefulness and success by analysing the challenges present-ed during NAP processes as well as the benefits this set of actions entails: The challenges for their implementation outweigh its actual benefits. Nevertheless, NAPs have great potential. Based on new research, we elaborate a set of recom-mendations for improving the design and imple-mentation of national action planning. In order to effectively bring NAP into practice, we consider it crucial to plan and analyse every state local circumstances in detail. The latter is important, since the implementation of a concrete set of actions is intended to directly transform and improve the local living conditions of the people. In a long-term perspective, we defend the benefit of NAP’s implementation for complying obliga-tions set up by HR treaties.
The last years have been affected by Covid-19 and the international emergency mecha-nism to deal with health-related threats. The effects of this period manifested differ-ently worldwide, depending on matters such as international relations, national policies, power dynamics etc. Additionally, the impact of this time will likely have long-term effects which are yet to be known. This paper gives a critical overview of the Public Health Emergency of International Concern (PHEIC) mechanism in the context of Covid-19. It does so by explaining the legal framework for states of emergency, specifically in the context of a PHEIC, while considering its restrictions and limitations on human rights. It further outlines issues in the manifestation of global protections and limitations on human rights during Covid-19. Lastly, considering the likelihood of future PHEICs and the known systemic obstructions, this paper offers ways to im-prove this mechanism from a holistic, non-zero-sum perspective.
The MOOChub is a joined web-based catalog of all relevant German and Austrian MOOC platforms that lists well over 750 Massive Open Online Courses (MOOCs). Automatically building such a catalog requires that all partners describe and publicly offer the metadata of their courses in the same way. The paper at hand presents the genesis of the idea to establish a common metadata standard and the story of its subsequent development. The result of this effort is, first, an open-licensed de-facto-standard, which is based on existing commonly used standards and second, a first prototypical platform that is using this standard: the MOOChub, which lists all courses of the involved partners. This catalog is searchable and provides a more comprehensive overview of basically all MOOCs that are offered by German and Austrian MOOC platforms. Finally, the upcoming developments to further optimize the catalog and the metadata standard are reported.
The CH2Cl2/MeOH (1:1) extract of Zanthoxylum holstzianum stem bark showed good antiplasmodial activity (IC50 2.5 +/- 0.3 and 2.6 +/- 0.3 mu g/mL against the W2 and D6 strains of Plasmodium falciparum, respectively). From the extract five benzophenanthridine alkaloids [8-acetonyldihydrochelerythrine (1), nitidine (2), dihydrochelerythine (3), norchelerythrine (5), arnottianamide (8)]; a 2-quinolone alkaloid [N-methylflindersine (4)]; a lignan [4,4 '-dihydroxy-3,3 '-dimethoxylignan-9,9 '-diyl diacetate (7)] and a dimer of a benzophenanthridine and 2-quinoline [holstzianoquinoline (6)] were isolated. The CH2Cl2/MeOH (1:1) extract of the root bark afforded 1, 3-6, 8, chelerythridimerine (9) and 9-demethyloxychelerythrine (10). Holstzianoquinoline (6) is new, and is the second dimer linked by a C-C bond of a benzophenanthridine and a 2-quinoline reported thus far. The compounds were identified based on spectroscopic evidence. Amongst five compounds (1-5) tested against two strains of P. falciparum, nitidine (IC50 0.11 +/- 0.01 mu g/mL against W2 and D6 strains) and norchelerythrine (IC50 value of 0.15 +/- 0.01 mu g/mL against D6 strain) were the most active.
Pichia pastoris (syn. Komagataella phaffi) is a distinguished expression system widely used in industrial production processes. Recent molecular research has focused on numerous approaches to increase recombinant protein yield in P. pastoris. For example, the design of expression vectors and synthetic genetic elements, gene copy number optimization, or co-expression of helper proteins
(transcription factors, chaperones, etc.). However, high clonal variability of transformants and low screening throughput have hampered significant success.
To enhance screening capacities, display-based methodologies inherit the potential for efficient isolation of producer clones via fluorescence-activated cell sorting (FACS). Therefore, this study focused on developing a novel clone selection method that is based on the non-covalent attachment of Fab fragments on the P. pastoris cell surface to be applicable for FACS.
Initially, a P. pastoris display system was developed, which is a prerequisite for the surface capture of secreted Fabs. A Design of Experiments approach was applied to analyze the influence of various genetic elements on antibody fragment display. The combined P. pastoris formaldehyde dehydrogenase promoter (PFLD1), Saccharomyces cerevisiae invertase 2 signal peptide (ScSUC2), - agglutinin (ScSAG1) anchor protein, and the ARS of Kluyveromyces lactis (panARS) conferred highest display levels.
Subsequently, eight single-chain variable fragments (scFv) specific for the constant part of the Fab heavy or light chain were individually displayed in P. pastoris. Among the tested scFvs, the anti-human CH1 IgG domain scFv allowed the most efficient Fab capture detected by flow cytometry.
Irrespective of the Fab sequence, exogenously added as well as simultaneously secreted Fabs were successfully captured on the cell surface. Furthermore, Fab secretion capacities were shown to correlate to the level of surface-bound Fabs as demonstrated for characterized producer clones.
Flow-sorted clones presenting high amounts of Fabs showed an increase in median Fab titers (factor of 21 to 49) compared to unsorted clones when screened in deep-well plates. For selected candidates, improved functional Fab yields of sorted cells vs. unsorted cells were confirmed in an upscaled shake flask production. Since the scFv capture matrix was encoded on an episomal plasmid with inherently unstable autonomously replicating sequences (ARS), efficient plasmid curing was observed after removing the selective pressure. Hence, sorted clones could be immediately used for production without the need to modify the expression host or vector. The resulting switchable display/secretion system provides a streamlined approach for the isolation of Fab producers and subsequent Fab production.
The integration of MOOCs into the Moroccan Higher Education (MHE) took place in 2013 by developing different partnerships and projects at national and international levels. As elsewhere, the Covid-19 crisis has played an important role in accelerating distance education in MHE. However, based on our experience as both university professors and specialists in educational engineering, the effective execution of the digital transition has not yet been implemented. Thus, in this article, we present a retrospective feedback of MOOCs in Morocco, focusing on the policies taken by the government to better support the digital transition in general and MOOCs in particular. We are therefore seeking to establish an optimal scenario for the promotion of MOOCs, which emphasizes the policies to be considered, and which recalls the importance of conducting a delicate articulation taking into account four levels, namely environmental, institutional, organizational and individual. We conclude with recommendations that are inspired by the Moroccan academic contex that focus on the major role that MOOCs plays for university students and on maintaining lifelong learning.
A right to research?
(2023)
As a result of CMOS scaling, radiation-induced Single-Event Effects (SEEs) in electronic circuits became a critical reliability issue for modern Integrated Circuits (ICs) operating under harsh radiation conditions. SEEs can be triggered in combinational or sequential logic by the impact of high-energy particles, leading to destructive or non-destructive faults, resulting in data corruption or even system failure. Typically, the SEE mitigation methods are deployed statically in processing architectures based on the worst-case radiation conditions, which is most of the time unnecessary and results in a resource overhead. Moreover, the space radiation conditions are dynamically changing, especially during Solar Particle Events (SPEs). The intensity of space radiation can differ over five orders of magnitude within a few hours or days, resulting in several orders of magnitude fault probability variation in ICs during SPEs. This thesis introduces a comprehensive approach for designing a self-adaptive fault resilient multiprocessing system to overcome the static mitigation overhead issue. This work mainly addresses the following topics: (1) Design of on-chip radiation particle monitor for real-time radiation environment detection, (2) Investigation of space environment predictor, as support for solar particle events forecast, (3) Dynamic mode configuration in the resilient multiprocessing system. Therefore, according to detected and predicted in-flight space radiation conditions, the target system can be configured to use no mitigation or low-overhead mitigation during non-critical periods of time. The redundant resources can be used to improve system performance or save power. On the other hand, during increased radiation activity periods, such as SPEs, the mitigation methods can be dynamically configured appropriately depending on the real-time space radiation environment, resulting in higher system reliability. Thus, a dynamic trade-off in the target system between reliability, performance and power consumption in real-time can be achieved. All results of this work are evaluated in a highly reliable quad-core multiprocessing system that allows the self-adaptive setting of optimal radiation mitigation mechanisms during run-time. Proposed methods can serve as a basis for establishing a comprehensive self-adaptive resilient system design process. Successful implementation of the proposed design in the quad-core multiprocessor shows its application perspective also in the other designs.
Higher eco-efficiency will not be enough to slow global warming caused by climate change. To keep global warming to 2 degrees, people also need to reduce their consumption. At present, however, many who would be able to do so seem unwilling to comply. Given the threats of a runaway climate change, urgent measures are needed to promote less personal consumption. This study, therefore, examines whether social marketing consume-less appeals can be used to encourage consumers to voluntarily abstain from consumption. As part of an online experiment with nearly 2000 randomly sampled users of an online platform for sustainable consumption, we tested the effectiveness of five different “consume-less” appeals based on traditional advertising formats (including emotional, informational, and social claims). The study shows that consume-less appeals are capable of limiting personal desire to buy. However, significant differences in the effectiveness of the appeal formats used in this study were observed. In addition, we found evidence of rebound effects, which leads us to critically evaluate the overall potential of social marketing to promote more resource-conserving lifestyles. While commercial consumer-free appeals have previously been studied (e.g., Patagonia’s “Don’t Buy This Jacked”), this study on the effectiveness of non-commercial consume-free appeals is novel and provides new insights.
This research paper aims to introduce a novel practitioner-oriented and research-based taxonomy of video genres. This taxonomy can serve as a scaffolding strategy to support educators throughout the entire educational system in creating videos for pedagogical purposes. A taxonomy of video genres is essential as videos are highly valued resources among learners. Although the use of videos in education has been extensively researched and well-documented in systematic research reviews, gaps remain in the literature. Predominantly, researchers employ sophisticated quantitative methods and similar approaches to measure the performance of videos. This trend has led to the emergence of a strong learning analytics research tradition with its embedded literature. This body of research includes analysis of performance of videos in online courses such as Massive Open Online Courses (MOOCs). Surprisingly, this same literature is limited in terms of research outlining approaches to designing and creating educational videos, which applies to both video-based learning and online courses. This issue results in a knowledge gap, highlighting the need for developing pedagogical tools and strategies for video making. These can be found in frameworks, guidelines, and taxonomies, which can serve as scaffolding strategies. In contrast, there appears to be very few frameworks available for designing and creating videos for pedagogica purposes, apart from a few well-known frameworks. In this regard, this research paper proposes a novel taxonomy of video genres that educators can utilize when creating videos intended for use in either video-based learning environments or online courses. To create this taxonomy, a large number of videos from online courses were collected and analyzed using a mixed-method research design approach.
The crises of both the climate and the biosphere are manifestations of the imbalance between human extractive, and polluting activities and the Earth’s regenerative capacity. Planetary boundaries define limits for biophysical systems and processes that regulate the stability and life support capacity of the Earth system, and thereby also define a safe operating space for humanity on Earth. Budgets associated to planetary boundaries can be understood as global commons: common pool resources that can be utilized within finite limits. Despite the analytical interpretation of planetary boundaries as global commons, the planetary boundaries framework is missing a thorough integration into economic theory. We aim to bridge the gap between welfare economic theory and planetary boundaries as derived in the natural sciences by presenting a unified theory of cost-benefit and cost-effectiveness analysis. Our pragmatic approach aims to overcome shortcomings of the practical applications of CEA and CBA to environmental problems of a planetary scale. To do so, we develop a model framework and explore decision paradigms that give guidance to setting limits on human activities. This conceptual framework is then applied to planetary boundaries. We conclude by using the realized insights to derive a research agenda that builds on the understanding of planetary boundaries as global commons.
Many complex systems that we encounter in the world can be formalized using networks. Consequently, they have been in the focus of computer science for decades, where algorithms are developed to understand and utilize these systems.
Surprisingly, our theoretical understanding of these algorithms and their behavior in practice often diverge significantly. In fact, they tend to perform much better on real-world networks than one would expect when considering the theoretical worst-case bounds. One way of capturing this discrepancy is the average-case analysis, where the idea is to acknowledge the differences between practical and worst-case instances by focusing on networks whose properties match those of real graphs. Recent observations indicate that good representations of real-world networks are obtained by assuming that a network has an underlying hyperbolic geometry.
In this thesis, we demonstrate that the connection between networks and hyperbolic space can be utilized as a powerful tool for average-case analysis. To this end, we first introduce strongly hyperbolic unit disk graphs and identify the famous hyperbolic random graph model as a special case of them. We then consider four problems where recent empirical results highlight a gap between theory and practice and use hyperbolic graph models to explain these phenomena theoretically. First, we develop a routing scheme, used to forward information in a network, and analyze its efficiency on strongly hyperbolic unit disk graphs. For the special case of hyperbolic random graphs, our algorithm beats existing performance lower bounds. Afterwards, we use the hyperbolic random graph model to theoretically explain empirical observations about the performance of the bidirectional breadth-first search. Finally, we develop algorithms for computing optimal and nearly optimal vertex covers (problems known to be NP-hard) and show that, on hyperbolic random graphs, they run in polynomial and quasi-linear time, respectively.
Our theoretical analyses reveal interesting properties of hyperbolic random graphs and our empirical studies present evidence that these properties, as well as our algorithmic improvements translate back into practice.
In the present thesis, AC electrokinetic forces, like dielectrophoresis and AC electroosmosis, were demonstrated as a simple and fast method to functionalize the surface of nanoelectrodes with submicrometer sized biological objects. These nanoelectrodes have a cylindrical shape with a diameter of 500 nm arranged in an array of 6256 electrodes. Due to its medical relevance influenza virus as well as anti-influenza antibodies were chosen as a model organism. Common methods to bring antibodies or proteins to biosensor surfaces are complex and time-consuming. In the present work, it was demonstrated that by applying AC electric fields influenza viruses and antibodies can be immobilized onto the nanoelectrodes within seconds without any prior chemical modification of neither the surface nor the immobilized biological object. The distribution of these immobilized objects is not uniform over the entire array, it exhibits a decreasing gradient from the outer row to the inner ones. Different causes for this gradient have been discussed, such as the vortex-shaped fluid motion above the nanoelectrodes generated by, among others, electrothermal fluid flow. It was demonstrated that parts of the accumulated material are permanently immobilized to the electrodes. This is a unique characteristic of the presented system since in the literature the AC electrokinetic immobilization is almost entirely presented as a method just for temporary immobilization. The spatial distribution of the immobilized viral material or the anti-influenza antibodies at the electrodes was observed by either the combination of fluorescence microscopy and deconvolution or by super-resolution microscopy (STED). On-chip immunoassays were performed to examine the suitability of the functionalized electrodes as a potential affinity-based biosensor. Two approaches were pursued: A) the influenza virus as the bio-receptor or B) the influenza virus as the analyte. Different sources of error were eliminated by ELISA and passivation experiments. Hence, the activity of the immobilized object was inspected by incubation with the analyte. This resulted in the successful detection of anti-influenza antibodies by the immobilized viral material. On the other hand, a detection of influenza virus particles by the immobilized anti-influenza antibodies was not possible. The latter might be due to lost activity or wrong orientation of the antibodies. Thus, further examinations on the activity of by AC electric fields immobilized antibodies should follow. When combined with microfluidics and an electrical read-out system, the functionalized chips possess the potential to serve as a rapid, portable, and cost-effective point-of-care (POC) device. This device can be utilized as a basis for diverse applications in diagnosing and treating influenza, as well as various other pathogens.
In social networks or, more specifically, online communities on tech-products, opinion leaders are important sources of advice for other consumers in the adoption and diffusion of new products. However, possibilities for potential users to exert their influence on opinion leadership are ignored. This study determines whether and how lead users may serve as opinion leaders in social networks and advise other consumers in the adoption and diffusion of new products. Our survey with 308 users in the Xiaomi and Huawei communities suggests that higher lead userness is positively and significantly associated with the likelihood of opinion giving and passing. Product-possessing innovativeness has a higher impact compared with information-possessing innovativeness. Product involvement does not enhance the effect of information-possessing innovativeness. The findings provide a better understanding of the formation of opinion leadership in social networks for an accelerated diffusion of new products.
Background and aims:
To succeed in competition, elite team and individual athletes often seek the development of both, high levels of muscle strength and power as well as cardiorespiratory endurance. In this context, concurrent training (CT) is a commonly applied and effective training approach. While being exposed to high training loads, youth athletes (≤ 18 years) are yet underrepresented in the scientific literature. Besides, immunological responses to CT have received little attention. Therefore, the aims of this work were to examine the acute (< 15min) and delayed (≥ 6 hours) effects of dif-ferent exercise order in CT on immunological stress responses, muscular fitness, metabolic response, and rating of perceived exertion (RPE) in highly trained youth male and female judo athletes.
Methods:
A total of twenty male and thirteen female participants, with an average age of 16 ± 1.8 years and 14.4 ± 2.1 years, respectively, were included in the study. They were randomly assigned to two CT sessions; power-endurance versus endurance-power (i.e., study 1), or strength-endurance versus endurance-strength (i.e., study 2). Markers of immune response (i.e., white-blood-cells, granulocytes, lymphocytes, mon-ocytes, and lymphocytes, granulocyte-lymphocyte-ratio, and systemic-inflammation-index), muscular fitness (i.e., counter-movement jump [CMJ]), metabolic responses (i.e., blood lactate, glucose), and RPE were collected at different time points (i.e., PRE12H, PRE, MID, POST, POST6H, POST22H).
Results (study 1):
There were significant time*order interactions for white-blood-cells, lymphocytes, granulocytes, monocytes, granulocyte-lymphocyte-ratio, and systemic-inflammation-index. The power-endurance order resulted in significantly larger PRE-to-POST increases in white-blood-cells, monocytes, and lymphocytes while the endur-ance-power order resulted in significantly larger PRE-to-POST increases in the granu-locyte-lymphocyte-ratio and systemic-inflammation-index. Likewise, significantly larger increases from PRE-to-POST6H in white-blood-cells and granulocytes were observed following the power-endurance order compared to endurance-power. All markers of immune response returned toward baseline values at POST22H. Moreover, there was a significant time*order interaction for blood glucose and lactate. Following the endur-ance-power order, blood lactate and glucose increased from PRE-to-MID but not from PRE-to-POST. Meanwhile, in the power-endurance order blood lactate and glucose increased from PRE-to-POST but not from PRE-to-MID. A significant time*order inter-action was observed for CMJ-force with larger PRE-to-POST decreases in the endur-ance-power order compared to power-endurance order. Further, CMJ-power showed larger PRE-to-MID performance decreases following the power-endurance order, com-pared to the endurance-power order. Regarding RPE, significant time*order interactions were noted with larger PRE-to-MID values following the endurance-power order and larger PRE-to-POST values following the power-endurance order.
Results (study 2):
There were significant time*order interactions for lymphocytes, monocytes, granulocyte-lymphocyte-ratio, and systemic-inflammation-index. The strength-endurance order resulted in significantly larger PRE-to-POST increases in lymphocytes while the endurance-strength order resulted in significantly larger PRE-to-POST increases in the granulocyte-lymphocyte-ratio and systemic-inflammation-index. All markers of the immune system returned toward baseline values at POST22H. Moreover, there was a significant time*order interaction for blood glucose and lactate. From PRE-to-MID, there was a significantly greater increase in blood lactate and glu-cose following the endurance-strength order compared to strength-endurance order. Meanwhile, from PRE-to-POST there was a significantly higher increase in blood glu-cose following the strength-endurance order compared to endurance-strength order. Regarding physical fitness, a significant time*order interaction was observed for CMJ-force and CMJ-power with larger PRE-to-MID increases following the endurance-strength order compared to the strength-endurance order. For RPE, significant time*order interactions were noted with larger PRE-to-MID values following the endur-ance-power order and larger PRE-to-POST values following the power-endurance or-der.
Conclusions:
The primary findings from both studies revealed order-dependent effects on immune responses. In male youth judo athletes, the results demonstrated greater immunological stress responses, both immediately (≤ 15 min) and delayed (≥ 6 hours), following the power-endurance order compared to the endurance-power order. For female youth judo athletes, the results indicated higher acute, but not delayed, order-dependent changes in immune responses following the strength-endurance order compared to the endurance-strength order. It is worth noting that in both studies, all markers of immune system response returned to baseline levels within 22 hours. This suggests that successful recovery from the exercise-induced immune stress response was achieved within 22 hours. Regarding metabolic responses, physical fitness, and perceived exertion, the findings from both studies indicated acute (≤ 15 minutes) alterations that were dependent on the exercise order. These alterations were primarily influ-enced by the endurance exercise component. Moreover, study 1 provided substantial evidence suggesting that internal load measures, such as immune markers, may differ from external load measures. This indicates a disparity between immunological, perceived, and physical responses following both concurrent training orders. Therefore, it is crucial for practitioners to acknowledge these differences and take them into consideration when designing training programs.
The electrical resistivity tomography (ERT) method is widely used to investigate geological, geotechnical, and hydrogeological problems in inland and aquatic environments (i.e., lakes, rivers, and seas). The objective of the ERT method is to obtain reliable resistivity models of the subsurface that can be interpreted in terms of the subsurface structure and petrophysical properties. The reliability of the resulting resistivity models depends not only on the quality of the acquired data, but also on the employed inversion strategy. Inversion of ERT data results in multiple solutions that explain the measured data equally well. Typical inversion approaches rely on different deterministic (local) strategies that consider different smoothing and damping strategies to stabilize the inversion. However, such strategies suffer from the trade-off of smearing possible sharp subsurface interfaces separating layers with resistivity contrasts of up to several orders of magnitude. When prior information (e.g., from outcrops, boreholes, or other geophysical surveys) suggests sharp resistivity variations, it might be advantageous to adapt the parameterization and inversion strategies to obtain more stable and geologically reliable model solutions. Adaptations to traditional local inversions, for example, by using different structural and/or geostatistical constraints, may help to retrieve sharper model solutions. In addition, layer-based model parameterization in combination with local or global inversion approaches can be used to obtain models with sharp boundaries.
In this thesis, I study three typical layered near-surface environments in which prior information is used to adapt 2D inversion strategies to favor layered model solutions. In cooperation with the coauthors of Chapters 2-4, I consider two general strategies. Our first approach uses a layer-based model parameterization and a well-established global inversion strategy to generate ensembles of model solutions and assess uncertainties related to the non-uniqueness of the inverse problem. We apply this method to invert ERT data sets collected in an inland coastal area of northern France (Chapter~2) and offshore of two Arctic regions (Chapter~3). Our second approach consists of using geostatistical regularizations with different correlation lengths. We apply this strategy to a more complex subsurface scenario on a local intermountain alluvial fan in southwestern Germany (Chapter~4). Overall, our inversion approaches allow us to obtain resistivity models that agree with the general geological understanding of the studied field sites. These strategies are rather general and can be applied to various geological environments where a layered subsurface structure is expected. The flexibility of our strategies allows adaptations to invert other kinds of geophysical data sets such as seismic refraction or electromagnetic induction methods, and could be considered for joint inversion approaches.
The African weakly electric fish genus Campylomormyrus includes 15 described species mostly native to the Congo River and its tributaries. They are considered sympatric species, because their distribution area overlaps. These species generate species-specific electric organ discharges (EODs) varying in waveform characteristics, including duration, polarity, and phase number. They exhibit also pronounced divergence in their snout, i.e. the length, thickness, and curvature. The diversifications in these two phenotypical traits (EOD and snout) have been proposed as key factors promoting adaptive radiation in Campylomormyrus. The role of EODs as a pre-zygotic isolation mechanism driving sympatric speciation by promoting assortative mating has been examined using behavioral, genetical, and histological approaches. However, the evolutionary effects of the snout morphology and its link to species divergence have not been closely examined. Hence, the main objective of this study is to investigate the effect of snout morphology diversification and its correlated EOD to better understand their sympatric speciation and evolutionary drivers. Moreover, I aim to utilize the intragenus and intergenus hybrids of Campylomormyrus to better understand trait divergence as well as underlying molecular/genetic mechanisms involved in the radiation scenario. To this end, I utilized three different approaches: feeding behavior analysis, diet assessment, and geometric morphometrics analysis. I performed feeding behavior experiments to evaluate the concept of the phenotype-environment correlation by testing whether Campylomormyrus species show substrate preferences. The behavioral experiments showed that the short snout species exhibits preference to sandy substrate, the long snout species prefers a stone substrate, and the species with intermediate snout size does not exhibit any substrate preference. The experiments suggest that the diverse feeding apparatus in the genus Campylomormyrus may have evolved in adaptation to their microhabitats. I also performed diet assessments of sympatric Campylomormyrus species and a sister genus species (Gnathonemus petersii) with markedly different snout morphologies and EOD using NGS-based DNA metabarcoding of their stomach contents. The diet of each species was documented showing that aquatic insects such as dipterans, coleopterans and trichopterans represent the major diet component. The results showed also that all species are able to exploit diverse food niches in their habitats. However, comparing the diet overlap indices showed that different snout morphologies and the associated divergence in the EOD translated into different prey spectra. These results further support the idea that the EOD could be a ‘magic trait’ triggering both adaptation and reproductive isolation. Geometric morphometrics method was also used to compare the phenotypical shape traits of the F1 intragenus (Campylomormyrus) and intergenus (Campylomormyrus species and Gnathonemus petersii) hybrids relative to their parents. The hybrids of these species were well separated based on the morphological traits, however the hybrid phenotypic traits were closer to the short-snouted species. In addition, the likelihood that the short snout expressed in the hybrids increases with increasing the genetic distance of the parental species. The results confirmed that additive effects produce intermediate phenotypes in F1-hybrids. It seems, therefore, that morphological shape traits in hybrids, unlike the physiological traits, were not expressed straightforward.
Nowadays, innovative and entrepreneurial activities and their actors are embedded in interdependent systems to drive joint value creation. Innovation ecosystems and entrepreneurial ecosystems have become established system-level concepts in management research to explain how value transpires between different actors and institutions in distinct contexts. Despite the popularity of the concepts, researchers have critiqued their theoretical depth, conceptual distinctiveness, as well as operationalization and measurement (Autio & Thomas, 2022; Klimas & Czakon, 2022). Furthermore, in light of current-day challenges, research has yet to address how context impacts innovation and entrepreneurial ecosystems and their actors and elements (Wurth et al., 2022).
The aim of this cumulative thesis is to provide a deeper understanding of the conceptualization, operationalization, and measurement of innovation and entrepreneurial ecosystems and investigate how contextual factors can influence the overall ecosystem and its key actors. To this end, bibliometric and empirical-qualitative methods, as well as narrative and systematic literature reviews, are employed. After introducing the research scope and key concepts in Chapter 1, a systematic literature review to operationalize and measure the concept of innovation ecosystems is conducted, and an integrative framework of its composition is introduced in Chapter 2. In Chapter 3, the innovation journal network is outlined by means of science mapping to determine current and emerging research areas characterizing innovation studies. In Chapters 4 and 5, the interplay between the temporal context of the Covid-19 pandemic and the spatial context of entrepreneurial ecosystems is assessed by focusing on the role of organizational resilience and affordances. The findings shed new light on the dynamics and boundaries of entrepreneurial ecosystems as they move between the spatial and digital realm. Building on this, an integrative framework of digital entrepreneurial ecosystems is presented in Chapter 6. The concluding Chapter 7 summarizes my thesis’s conceptual, theoretical, and empirical insights, highlighting implications, limitations, and promising future research avenues.
The findings of this cumulative thesis contribute to the theoretical and conceptual advancement of ecosystems in innovation and entrepreneurship by providing insights into the measurement and operationalization of its elements. Furthermore, the results show that contextual factors, such as crisis events or institutional circumstances, influence innovation and entrepreneurial ecosystems and their actors, calling for a more nuanced consideration of ecosystem configurations and dynamics. By drawing from the theory of affordances, the elements that actually afford value to the actors and how they shift between the physical and digital realm are portrayed. Based on these findings, this thesis introduces novel frameworks and conceptual advancements of the configurations and boundaries of innovation and (digital) entrepreneurial ecosystems, laying the foundation for a renewed understanding of how to design, orchestrate, and evaluate ecosystems today and in the future.
Process mining (PM) has established itself in recent years as a main method for visualizing and analyzing processes. However, the identification of knowledge has not been addressed adequately because PM aims solely at data-driven discovering, monitoring, and improving real-world processes from event logs available in various information systems. The following paper, therefore, outlines a novel systematic analysis view on tools for data-driven and machine learning (ML)-based identification of knowledge-intensive target processes. To support the effectiveness of the identification process, the main contributions of this study are (1) to design a procedure for a systematic review and analysis for the selection of relevant dimensions, (2) to identify different categories of dimensions as evaluation metrics to select source systems, algorithms, and tools for PM and ML as well as include them in a multi-dimensional grid box model, (3) to select and assess the most relevant dimensions of the model, (4) to identify and assess source systems, algorithms, and tools in order to find evidence for the selected dimensions, and (5) to assess the relevance and applicability of the conceptualization and design procedure for tool selection in data-driven and ML-based process mining research.
Advances in hydrogravimetry
(2023)
The interest of the hydrological community in the gravimetric method has steadily increased within the last decade. This is reflected by numerous studies from many different groups with a broad range of approaches and foci. Many of those are traditionally rather hydrology-oriented groups who recognized gravimetry as a potential added value for their hydrological investigations. While this resulted in a variety of interesting and useful findings, contributing to extend the respective knowledge and confirming the methodological potential, on the other hand, many interesting and unresolved questions emerged.
This thesis manifests efforts, analyses and solutions carried out in this regard. Addressing and evaluating many of those unresolved questions, the research contributes to advancing hydrogravimetry, the combination of gravimetric and hydrological methods, in showing how gravimeters are a highly useful tool for applied hydrological field research.
In the first part of the thesis, traditional setups of stationary terrestrial superconducting gravimeters are addressed. They are commonly installed within a dedicated building, the impermeable structure of which shields the underlying soil from natural exchange of water masses (infiltration, evapotranspiration, groundwater recharge). As gravimeters are most sensitive to mass changes directly beneath the meter, this could impede their suitability for local hydrological process investigations, especially for near-surface water storage changes (WSC). By studying temporal local hydrological dynamics at a dedicated site equipped with traditional hydrological measurement devices, both below and next to the building, the impact of these absent natural dynamics on the gravity observations were quantified. A comprehensive analysis with both a data-based and model-based approach led to the development of an alternative method for dealing with this limitation. Based on determinable parameters, this approach can be transferred to a broad range of measurement sites where gravimeters are deployed in similar structures. Furthermore, the extensive considerations on this topic enabled a more profound understanding of this so called umbrella effect.
The second part of the thesis is a pilot study about the field deployment of a superconducting gravimeter. A newly developed field enclosure for this gravimeter was tested in an outdoor installation adjacent to the building used to investigate the umbrella effect. Analyzing and comparing the gravity observations from both indoor and outdoor gravimeters showed performance with respect to noise and stable environmental conditions was equivalent while the sensitivity to near-surface WSC was highly increased for the field deployed instrument. Furthermore it was demonstrated that the latter setup showed gravity changes independent of the depth where mass changes occurred, given their sufficiently wide horizontal extent. As a consequence, the field setup suits monitoring of WSC for both short and longer time periods much better. Based on a coupled data-modeling approach, its gravity time series was successfully used to infer and quantify local water budget components (evapotranspiration, lateral subsurface discharge) on the daily to annual time scale.
The third part of the thesis applies data from a gravimeter field deployment for applied hydrological process investigations. To this end, again at the same site, a sprinkling experiment was conducted in a 15 x 15 m area around the gravimeter. A simple hydro-gravimetric model was developed for calculating the gravity response resulting from water redistribution in the subsurface. It was found that, from a theoretical point of view, different subsurface water distribution processes (macro pore flow, preferential flow, wetting front advancement, bypass flow and perched water table rise) lead to a characteristic shape of their resulting gravity response curve. Although by using this approach it was possible to identify a dominating subsurface water distribution process for this site, some clear limitations stood out. Despite the advantage for field installations that gravimetry is a non-invasive and integral method, the problem of non-uniqueness could only be overcome by additional measurements (soil moisture, electric resistivity tomography) within a joint evaluation. Furthermore, the simple hydrological model was efficient for theoretical considerations but lacked the capability to resolve some heterogeneous spatial structures of water distribution up to a needed scale. Nevertheless, this unique setup for plot to small scale hydrological process research underlines the high potential of gravimetery and the benefit of a field deployment.
The fourth and last part is dedicated to the evaluation of potential uncertainties arising from the processing of gravity observations. The gravimeter senses all mass variations in an integral way, with the gravitational attraction being directly proportional to the magnitude of the change and inversely proportional to the square of the distance of the change. Consequently, all gravity effects (for example, tides, atmosphere, non-tidal ocean loading, polar motion, global hydrology and local hydrology) are included in an aggregated manner. To isolate the signal components of interest for a particular investigation, all non-desired effects have to be removed from the observations. This process is called reduction. The large-scale effects (tides, atmosphere, non-tidal ocean loading and global hydrology) cannot be measured directly and global model data is used to describe and quantify each effect. Within the reduction process, model errors and uncertainties propagate into the residual, the result of the reduction. The focus of this part of the thesis is quantifying the resulting, propagated uncertainty for each individual correction. Different superconducting gravimeter installations were evaluated with respect to their topography, distance to the ocean and the climate regime. Furthermore, different time periods of aggregated gravity observation data were assessed, ranging from 1 hour up to 12 months. It was found that uncertainties were highest for a frequency of 6 months and smallest for hourly frequencies. Distance to the ocean influences the uncertainty of the non-tidal ocean loading component, while geographical latitude affects uncertainties of the global hydrological component. It is important to highlight that the resulting correction-induced uncertainties in the residual have the potential to mask the signal of interest, depending on the signal magnitude and its frequency. These findings can be used to assess the value of gravity data across a range of applications and geographic settings.
In an overarching synthesis all results and findings are discussed with a general focus on their added value for bringing hydrogravimetric field research to a new level. The conceptual and applied methodological benefits for hydrological studies are highlighted. Within an outlook for future setups and study designs, it was once again shown what enormous potential is offered by gravimeters as hydrological field tools.
The field of exercise psychology has established robust evidence on the health benefits of physical activity. However, interventions to promote sustained exercise behavior have often proven ineffective. This dissertation addresses challenges in the field, particularly the neglect of situated and affective processes in understanding and changing exercise behavior. Dual process models, considering both rational and affective processes, have gained recognition. The Affective Reflective Theory of Physical Inactivity and Exercise (ART) is a notable model in this context, positing that situated processes in-the-moment of choice influence exercise decisions and subsequent exercise behavior.
The dissertation identifies current challenges within exercise psychology and proposes methodological and theoretical advancements. It emphasizes the importance of momentary affective states and situated processes, offering alternatives to self-reported measures and advocating for a more comprehensive modeling of individual variability. The focus is on the affective processes during exercise, theorized to reappear in momentary decision-making, shaping overall exercise behavior.
The first publication introduces a new method by using automated facial action analysis to measure variable affective responses during exercise. It explores how these behavioral indicators covary with self-reported measures of affective valence and perceived exertion. The second publication delves into situated processes at the moment of choice between exercise and non-exercise options, revealing that intraindividual factors play a crucial role in explaining exercise-related choices. The third publication presents an open-source research tool, the Decisional Preferences in Exercising Test (DPEX), designed to capture repeated situated decisions and predict exercise behavior based on past experiences.
The findings challenge previous assumptions and provide insights into the complex interplay of affective responses, situated processes, and exercise choices. The dissertation underscores the need for individualized interventions that manipulate affective responses during exercise and calls for systematic testing to establish causal links to automatic affective processes and subsequent exercise behavior. This dissertation highlights the necessity for methodological and conceptual refinements in understanding and promoting exercise behavior, ultimately contributing to the broader goal of combating increasing inactivity trends.
Against the pain
(2023)
Faced with the triad of time-cost-quality, the realization of production tasks under economic conditions is not trivial. Since the number of Artificial-Intelligence-(AI)-based applications in business processes is increasing more and more nowadays, the efficient design of AI cases for production processes as well as their target-oriented improvement is essential, so that production outcomes satisfy high quality criteria and economic requirements. Both challenge production management and data scientists, aiming to assign ideal manifestations of artificial neural networks (ANNs) to a certain task. Faced with new attempts of ANN-based production process improvements [8], this paper continues research about the optimal creation, provision and utilization of ANNs. Moreover, it presents a mechanism for AI case-based reasoning for ANNs. Experiments clarify continuously improving ANN knowledge bases by this mechanism empirically. Its proof-of-concept is demonstrated by the example of four production simulation scenarios, which cover the most relevant use cases and will be the basis for examining AI cases on a quantitative level.
This short paper sets out to propose a novel and interesting learning design that facilitates for cooperative learning in which students do not conduct traditional group work in an asynchronous online education setting. This learning design will be explored in a Small Private Online Course (SPOC) among teachers and school managers at a teacher education. Such an approach can be made possible by applying specific criteria commonly used to define collaborative learning. Collaboration can be defined, among other things, as a structured way of working among students that includes elements of co-laboring. The cooperative learning design involves adapting various traditional collaborative learning approaches for use in an online learning environment. A critical component of this learning design is that students work on a self-defined case project related to their professional practices. Through an iterative process, students will receive ongoing feedback and formative assessments from instructors and follow students at specific points, meaning that co-constructing of knowledge and learning takes place as the SPOC progresses. This learning design can contribute to better learning experiences and outcomes for students, and be a valuable contribution to current research discussions on learning design in Massive Open Online Courses (MOOCs).
Seasonal forecasts are of great interest in many areas. Knowing the amount of precipitation for the upcoming season in regions of water scarcity would facilitate a better water management. If farmers knew the weather conditions of the upcoming summer at sowing time, they could select those cereal species that are best adapted to these conditions. This would allow farmers to improve the harvest and potentially even reduce the amount of pesticides used. However, the undoubted advantages of seasonal forecasts are often opposed by their high degree of uncertainty. The great challenge of generating seasonal forecasts with lead times of several months mainly originates from the chaotic nature of the earth system. In a chaotic system, even tiny differences in the initial conditions can lead to strong deviations in the system’s state in the long run.
In this dissertation we propose an emergent machine learning approach for seasonal forecasting, called the AnlgModel. The AnlgModel combines the analogue method with myopic feature selection and bootstrapping. To benchmark the abilities of the AnlgModel we apply it to seasonal cyclone activity forecasts in the North Atlantic and Northwest Pacific. The AnlgModel demonstrates competitive hindcast skills with two operational forecasts and even outperforms these for long lead times.
In the second chapter we comprehend the forecasting strategy of the Anlg-Model. We thereby analyse the analogue selection process for the 2017 North Atlantic and the 2018 Northwest Pacific seasonal cyclone activity. The analysis shows that those climate indices which are known to influence the seasonal cyclone activity, such as the Niño 3.4 SST, are correctly represented among the selected analogues. Furthermore the selected analogues reflect large-scale climate patterns that were identified by expert reports as being determinative for these particular seasons.
In the third chapter we analyse the features that are used by the AnlgModel for its predictions. We therefore inspect the feature relevance (FR). The FR patterns learned by the AnlgModel show a high congruence with the predictor regions used by the operational forecasts. However, the AnlgModel also discovered new features, such as the SST anomaly in the Gulf of Guinea during November. This SST pattern exhibits a remarkably high predictive potential for the upcoming Atlantic hurricane activity.
In the final chapter we investigate potential mechanisms, that link two of these regions with high feature relevance to the Atlantic hurricane activity. We mainly focus on ocean surface transport. The ocean surface flow paths are calculated using Lagrangian particle analysis. We demonstrate that the FR patterns in the region of the Canary islands do not correspond with ocean surface transport. It is instead likely that these FR patterns fingerprint a wind transport of latent heat. The second region to be studied is situated in the Gulf of Guinea. Our analysis shows that the FR patterns seen there do fingerprint ocean surface transport. However, our simulations also show that at least one other mechanism is involved in linking the Gulf of Guinea SST anomaly in November to the hurricane activity of the upcoming season.
In this work the AnlgModel does not only demonstrate its outstanding forecast skills but also shows its capabilities as research tool for detecting oceanic and atmospheric mechanisms.
Loss of expertise in the fields of Nuclear- and Radio-Chemistry (NRC) is problematic at a scientific and social level. This has been addressed by developing a MOOC, in order to let students in scientific matters discover all the benefits of NRC to society and improving their awareness of this discipline. The MOOC “Essential Radiochemistry for Society” includes current societal challenges related to health, clean and sustainable energy for safety and quality of food and agriculture.
NRC teachers belonging to CINCH network were invited to use the MOOC in their teaching, according to various usage models: on the basis of these different experiences, some usage patterns were designed, describing context characteristics (number and age of students, course), activities’ scheduling and organization, results and students’ feedback, with the aim of encouraging the use of MOOCs in university teaching, as an opportunity for both lecturers and students. These models were the basis of a “toolkit for teachers”. By experiencing digital teaching resources created by different lecturers, CINCH teachers took a first meaningful step towards understanding the worth of Open Educational Resources (OER) and the importance of their creation, adoption and sharing for knowledge progress. In this paper, the entire path from MOOC concept to MOOC different usage models, to awareness-raising regarding OER is traced in conceptual stages.
An exploration of activity and therapist preferences and their predictors in German-speaking samples
(2023)
According to current definitions of evidence-based practice, patients’ preferences play an important role for the psychotherapeutic process and outcomes. However, whereas a significant body of research investigated preferences regarding specific treatments, research on preferred activities or therapist characteristics is rare, investigated heterogeneous aspects with inconclusive results, lacked validated assessment tools, and neglected relevant preferences, their predictors as well as the perspective of mental health professionals. Therefore, the three studies of this dissertation aimed to address the most fundamental drawbacks in current preference research by providing a validated questionnaire, focus efforts on activity and therapist preferences and add preferences of psychotherapy trainees. To this end, Paper I reports the translation and validation of the 18-item Cooper-Norcross Inventory of Preference (C-NIP) in a broad, heterogeneous sample of N = 969 laypeople, resulting in good to acceptable reliabilities and first evidence of validity. However, the original factor structure was not replicated. Paper II assesses activity preferences of psychotherapists in training using the C-NIP and compares them with the initial laypeople sample. There were significant differences between both samples, with trainees preferring a more patient-directed, emotionally intense and confrontational approach than laypeople. CBT trainees preferred a more therapist-directed, present-focused, challenging and less emotional intense approach than psychodynamic or -analytic trainees. Paper III explores therapist preferences and tests predictors for specific preference choices. For most characteristics, more than half of the participants did not have specific preferences. Results pointed towards congruency effects (i.e., preference for similar characteristics), especially for members of marginalized groups. The dissertation provides both researchers and practitioners with a validated questionnaire, shows potentially obstructive differences between patients and therapists and underlines the importance of therapist characteristics for marginalized groups, thereby laying the foundation for future applications and implementations in research and practice.
Starch is an essential biopolymer produced by plants. Starch can be made inside source tissue (such as leaves) and sink tissue (such as fruits and tubers). Nevertheless, understanding how starch metabolism is regulated in source and sink tissues is fundamental for improving crop production.
Despite recent advances in the understanding of starch and its metabolism, there is still a knowledge gap in the source and sink metabolism. Therefore, this study aimed to summarize the state of the art regarding starch structure and metabolism inside plants. In addition, this study aimed to elucidate the regulation of starch metabolism in the source tissue using the leaves of a model organism, Arabidopsis thaliana, and the sink tissue of oil palm (Elaeis guineensis) fruit as a commercial crop.
The research regarding the source tissue will focus on the effect of the blockage of starch degradation on the starch parameter in leaves, especially in those of A. thaliana, which lack both disproportionating enzyme 2 (DPE2) and plastidial glucan phosphorylase 1 (PHS1) (dpe2/phs1). The additional elimination of phosphoglucan water dikinase (PWD), starch excess 4 (SEX4), isoamylase 3 (ISA3), and disproportionating enzyme 1 (DPE1) in the dpe2/phs1 mutant background demonstrates the alteration of starch granule number per chloroplast. This study provides insights into the control mechanism of granule number regulation in the chloroplast.
The research regarding the sink tissue will emphasize the relationship between starch metabolism and the lipid metabolism pathway in oil palm fruits. This study was conducted to observe the alteration of starch parameters, metabolite abundance, and gene expression during oil palm fruit development with different oil yields. This study shows that starch and sucrose can be used as biomarkers for oil yield in oil palms. In addition, it is revealed that the enzyme isoforms related to starch metabolism influence the oil production in oil palm fruit.
Overall, this thesis presents novel information regarding starch metabolism in the source tissue of A.thaliana and the sink tissue of E.guineensis. The results shown in this thesis can be applied to many applications, such as modifying the starch parameter in other plants for specific needs.
In nature, plants often encounter biotic and abiotic stresses, which can cause reduced crop yield and quality, and threaten the nutrition of a growing human population. As heat stress (HS) is one of the main abiotic stresses, and is projected to increase due to global warming, it is necessary to better understand how plants respond and survive under HS. In Arabidopsis thaliana, plants can survive under severe HS if primed by a non-lethal HS, a process called acquisition of thermotolerance. This primed stated can be maintained for several days, and the ability of plants to maintain the primed state is called maintenance of acquired thermotolerance (mATT) or HS memory. According to current research, two Heat shock factors (HSFs) HSFA2 and HSFA3 are known to account for the majority of mATT capability, and there are other HSFs e.g. HSFA1b and HSFA6b in HSF complexes containing HSFA2 and/or HSFA3, however, the roles of these HSFs in HS memory is not clearly understood. Moreover, the mechanism of these HSFs in regulating HS memory is unclear, whether transcriptional machinery e.g. the Mediator complex contributes to transcriptional memory. This work investigates the role of HSFs and Mediator subunits in HS memory in A. thaliana. For the role of HSFs, the interaction between HSFA1b and HSFA2 during HS memory phase was confirmed by in vivo co- immunoprecipitation (Co-IP). HSFA1b, HSFA2, HSFA3 and HSFA6b targeted HS memory-related genes according to DNA affinity purification sequencing (DAP-seq) data, and targets of HSFA1b were confirmed in vivo by chromatin immunoprecipitation qPCR (ChIP-qPCR). The mutant of hsfa6b showed an HS memory deficiency phenotype in mATT survival assay. These data confirmed the role for HSFA2 and HSFA3 in HS memory, and suggest that HSFA1b and HSFA6b also function in HS memory. The Mediator complex functions as an RNA Polymerase II (RNA Pol II) co-regulator, and includes Head, Middle, Tail and Kinase modules. Both MED23 and MED32 belong to the Tail module, and they have a positive role in HS memory. MED23 interacted with HSFA3, as determined by yeast two hybrid (Y2H) and in vivo Co-IP assays. The med23 mutant showed a decreased HS memory phenotype, reduced expression of Type I (sustained expression) memory genes following HS, and reduced accumulation of the memory-associated Tri-methylation of histone H3 lysine 4 (H3K4me3)histone modification at HS memory-related gene loci after HS. MED23 was recruited to HS-inducible memory and non-memory genes after HS, as determined by ChIP-qPCR. The med32
mutant showed a reduced HS memory phenotype, decreased expression of Type I and Type II (hyper-induction) memory genes, and lower accumulation of H3K4me3 at memory gene lociafter HS. However, MED32 did not show interaction with any tested HSF in Y2H or in vivo Co-IP. MED32 regulated the recruitment of RNA Pol II at HS-inducible genes after HS, but was not itself recruited to HS memory genes after HS. These results provided more evidence
that the Mediator subunits MED23 and MED32 regulate HS memory on transcriptional and epigenetic levels. In general, this work provides a better insight into the molecular mechanism of how HSFs and Mediator subunits regulate HS memory in plants and will provide new perspectives to breed crops with improved thermotolerance.
Anchored in ink
(2023)
This book serves as a gateway to the Elementa grammaticae Huronicae, an eighteenth-century grammar of the Wendat (‘Huron’) language by Jesuit Pierre-Philippe Potier (1708–1781). The volume falls into three main parts. The first part introduces the grammar and some of its contexts, offering information about the Huron-Wendat and Wyandot, the early modern Jesuit mission in New France and the Jesuits’ linguistic output. The heart of the volume is made up by its second part, a text edition of the Elementa. The third part presents some avenues of research by way of specific case studies.
Aquatic ecosystems are frequently overlooked as fungal habitats, although there is increasing evidence that their diversity and ecological importance are greater than previously considered. Aquatic fungi are critical and abundant components of nutrient cycling and food web dynamics, e.g., exerting top-down control on phytoplankton communities and forming symbioses with many marine microorganisms. However, their relevance for microphytobenthic communities is almost unexplored. In the light of global warming, polar regions face extreme changes in abiotic factors with a severe impact on biodiversity and ecosystem functioning. Therefore, this study aimed to describe, for the first time, fungal diversity in Antarctic benthic habitats along the salinity gradient and to determine the co-occurrence of fungal parasites with their algal hosts, which were dominated by benthic diatoms. Our results reveal that Ascomycota and Chytridiomycota are the most abundant fungal taxa in these habitats. We show that also in Antarctic waters, salinity has a major impact on shaping not just fungal but rather the whole eukaryotic community composition, with a diversity of aquatic fungi increasing as salinity decreases. Moreover, we determined correlations between putative fungal parasites and potential benthic diatom hosts, highlighting the need for further systematic analysis of fungal diversity along with studies on taxonomy and ecological roles of Chytridiomycota.
Scholars have argued that visionary leadership is an effective tool to motivate followers because it provides them with meaning and purpose. However, previous research tells us little about which leaders and under which circumstances leaders engage in visionary leadership. We draw on theories of human and social capital to argue that leader work centrality is an important antecedent of visionary leadership, and especially so for leaders with low organizational tenure. Moreover, we propose that visionary leadership then provides followers with meaningfulness and thereby decreases their turnover intentions. Our predictions were confirmed by data from a two-wave, lagged-design field study with 101 leader-follower dyads. Overall, our research identifies an important antecedent of visionary leadership, a specific situation in which this antecedent is particularly important, and provides empirical evidence for why visionary leadership can bind followers to an organization.
The light reactions of photosynthesis are carried out by a series of multiprotein complexes embedded in thylakoid membranes. Among them, photosystem I (PSI), acting as plastocyanin-ferderoxin oxidoreductase, catalyzes the final reaction. Together with light-harvesting antenna I, PSI forms a high-molecular-weight supercomplex of ~600 kDa, consisting of eighteen subunits and nearly two hundred co-factors. Assembly of the various components into a functional thylakoid membrane complex requires precise coordination, which is provided by the assembly machinery. Although this includes a small number of proteins (PSI assembly factors) that have been shown to play a role in the formation of PSI, the process as a whole, as well as the intricacy of its members, remains largely unexplored.
In the present work, two approaches were used to find candidate PSI assembly factors. First, EnsembleNet was used to select proteins thought to be functionally related to known PSI assembly factors in Arabidopsis thaliana (approach I), and second, co-immunoprecipitation (Co-IP) of tagged PSI assembly factors in Nicotiana tabacum was performed (approach II).
Here, the novel PSI assembly factors designated CO-EXPRESSED WITH PSI ASSEMBLY 1 (CEPA1) and Ycf4-INTERACTING PROTEIN 1 (Y4IP1) were identified. A. thaliana null mutants for CEPA1 and Y4IP1 showed a growth phenotype and pale leaves compared with the wild type. Biophysical experiments using pulse amplitude modulation (PAM) revealed insufficient electron transport on the PSII acceptor side. Biochemical analyses revealed that both CEPA1 and Y4IP1 are specifically involved in PSI accumulation in A. thaliana at the post-translational level but are not essential. Consistent with their roles as factors in the assembly of a thylakoid membrane protein complex, the two proteins localize to thylakoid membranes. Remarkably, cepa1 y4ip1 double mutants exhibited lethal phenotypes in early developmental stages under photoautotrophic growth. Finally, co-IP and native gel experiments supported a possible role for CEPA1 and Y4IP1 in mediating PSI assembly in conjunction with other PSI assembly factors (e.g., PPD1- and PSA3-CEPA1 and Ycf4-Y4IP1). The fact that CEPA1 and Y4IP1 are found exclusively in green algae and higher plants suggests eukaryote-specific functions. Although the specific mechanisms need further investigation, CEPA1 and Y4IP1 are two novel assembly factors that contribute to PSI formation.
Background: Assessing short-term growth in humans is still fraught with difficulties. Especially when looking for small variations and increments, such as mini growth spurts, high precision instruments or frequent measurements are necessary. Daily measurements however require a lot of effort, both for anthropologists and for the subjects. Therefore, new sophisticated approaches are needed that reduce fluctuations and reveal underlying patterns.
Objectives: Changepoints are abrupt variations in the properties of time series data. In the context of growth, such variations could be variation in mean height. By adjusting the variance and using different growth models, we assessed the ability of changepoint analysis to analyse short-term growth and detect mini growth spurts.
Sample and Methods: We performed Bayesian changepoint analysis on simulated growth data using the bcp package in R. Simulated growth patterns included stasis, linear growth, catch-up growth, and mini growth spurts. Specificity and a normalised variant of the Matthews correlation coefficient (MCC) were used to assess the algorithm’s performance. Welch’s t-test was used to compare differences of the mean.
Results: First results show that changepoint analysis can detect mini growth spurts. However, the ability to detect mini growth spurts is highly dependent on measurement error. Data preparation, such as ranking and rotating time series data, showed negligible improvements. Missing data was an issue and may affect the prediction quality of the classification metrics.
Conclusion: Changepoint analysis is a promising tool to analyse short-term growth. However, further optimisation and analysis of real growth data is needed to make broader generalisations.
Plant metabolism serves as the primary mechanism for converting assimilated carbon into essential compounds crucial for plant growth and ultimately, crop yield. This renders it a focal point of research with significant implications. Despite notable strides in comprehending the genetic principles underpinning metabolism and yield, there remains a dearth of knowledge regarding the genetic factors responsible for trait variation under varying environmental conditions. Given the burgeoning global population and the advancing challenges posed by climate change, unraveling the intricacies of metabolic and yield responses to water scarcity became increasingly important in safeguarding food security.
Our research group has recently started to work on the genetic resources of legume species. To this end, the study presented here investigates the metabolic diversity across five different legume species at a tissue level, identifying species-specific biosynthesis of alkaloids as well as iso-/flavonoids with diverse functional groups, namely prenylation, phenylacylation as well as methoxylation, to create a resource for follow up studies investigation the metabolic diversity in natural diverse populations of legume species.
Following this, the second study investigates the genetic architecture of drought-induced changes in a global common bean population. Here, a plethora of quantitative trait loci (QTL) associated with various traits are identified by performing genome-wide association studies (GWAS), including for lipid signaling. On this site, overexpression of candidates highlighted the induction of several oxylipins reported to be pivotal in coping with harsh environmental conditions such as water scarcity.
Diverging from the common bean and GWAS, the following study focuses on identifying drought-related QTL in tomato using a bi-parental breeding population. This descriptive study highlights novel multi-omic QTL, including metabolism, photosynthesis as well as fruit setting, some of which are uniquely assigned under drought. Compared to conventional approaches using the bi-parental IL population, the study presented improves the resolution by assessing further backcrossed ILs, named sub-ILs.
In the final study, a photosynthetic gene, namely a PetM subunit of the cytochrome b6f complex encoding gene, involved in electron flow is characterized in an horticultural important crop. While several advances have been made in model organisms, this study highlights the transition of this fundamental knowledge to horticultural important crops, such as tomato, and investigates its function under differing light conditions. Overall, the presented thesis combines different strategies in unveiling the genetic components in multi-omic traits under drought using conventional breeding populations as well as a diverse global population. To this end, it allows a comparison of either approach and highlights their strengths and weaknesses.
Although hate speech is widely recognized as an online phenomenon, very few studies have investigated hate speech among adolescents in offline settings (e.g., schools). At the same time, not much is known about countering hate speech (counterspeech) among adolescents and which factors are associated with it. To this end, the present study used the socio-ecological framework to investigate the direct and indirect links among one contextual factor (i.e., classroom climate) and two intrapersonal factors (i.e., empathy for victims of hate speech, self-efficacy regarding intervention in hate speech) to understand counterspeech among adolescents. The sample is based on self-reports of 3,225 students in Grades 7 to 9 (51.7% self-identified as female) from 36 schools in Germany and Switzerland. Self-report questionnaires were administered to measure classroom climate, empathy, self-efficacy, and counterspeech. After controlling for adolescents' grade, gender, immigrant background, and socioeconomic status (SES), the 2-(1-1)-1 multilevel mediation analysis showed that classroom climate (L2), empathy for victims of hate speech (L1), and self-efficacy toward intervention in hate speech (L1) had a positive effect on countering hate speech (L1). Classroom climate (L2) was also positively linked to empathy for victims of hate speech (L1), and self-efficacy toward intervention in hate speech (L1). Furthermore, classroom climate (L2) was indirectly associated with countering hate speech (L1) via greater empathy (L1) and self-efficacy (L1). The findings highlight the need to focus on contextual and intrapersonal factors when trying to facilitate adolescents' willingness to face hate speech with civic courage and proactively engage against it.
A degree course in IT and business administration solely for women (FIW) has been offered since 2009 at the HTW Berlin – University of Applied Sciences. This contribution discusses student motivations for enrolling in such a women only degree course and gives details of our experience over recent years. In particular, the approach to attracting new female students is described and the composition of the intake is discussed. It is shown that the women-only setting together with other factors can attract a new clientele for computer science.
This research investigated the relationship between frequent engagement in industrial action (also known as ‘employee strikes’) and the internal attractiveness of government employment. It focused on a special group of public employees: public university lecturers and public-school teachers in Uganda who frequently engaged in industrial action. At the very basic level, the research explored whether public employees frequently engaged in industrial action because they considered public service employment to be unattractive or whether frequent engagement in industrial action was in fact part of the attractiveness of government employment. Beyond exploring these relationships, it also explained why (or why not) such relationships existed.
Methodologically, the research was conducted using an exploratory sequential design – a mixed methods study design that starts with a qualitative followed by a quantitative phase. It is the results of the initial qualitative phase that determined the direction of the subsequent quantitative phase. The qualitative phase started with an exploration of the relationship between industrial action and internal public service attractiveness, resulting into two specific research questions:
1) Why do public employees engage in industrial action and what role does frequent engagement in industrial action play in their perception of public service attractiveness?
2) Why and how is organizational justice related to public employees’ perception of public service attractiveness?
The above questions were answered both qualitatively and quantitatively. The theoretical postulations of the Social Movements Theories, Social Exchange Theory, and the Signaling Theory were used to structure the research assumptions and hypotheses.
The results showed that public employees engaged in industrial action mostly because of relative, rather than absolute deprivation. An established culture of workplace militancy was also found to be key in actualizing industrial action as was the (perceived) absence of alternatives to achieve workplace justice. Importantly, there was a clear dichotomy between absolute working conditions and frequent engagement in industrial action. Frequent engagement in industrial action was itself found to have both positive and negative effects on internal public service attractiveness. It was also found that public service attractiveness from the perspective of current public employees might be different from what it is from the perspective of prospective employees. This is because current public employees do not assume what it feels like to work for government, but mostly use their day-to-day lived experiences to judge the attractiveness of their employer. The existing literature is particularly deficient on analyzing public service attractiveness from an internal perspective, which is surprising given the public sector’s high reliance on internal recruitment.
The research results underlined key implications for theory, practice, and research. At theory level, the results suggested that public employee ratings of internal public service attractiveness were heavily affected by halo effects and should therefore not be taken at face value. The complex workplace social exchanges which are deeply rooted in organizational justice and the ‘personification metaphor’ were also emphasized. From an empirical perspective, the results underlined the need to prioritize internal public service attractiveness as recent research has confirmed the value of family socialization and internal recommendations in making public sector employment attractive, even to external applicants. This research argues that the centrality of organizational justice in public sector employee relations requires public sector organizations to be intentional in their bid to create fair, just, and attractive workplaces. Beyond assessing the fairness of personnel policies, procedures, and interactional relationships, it is also important to prepare and equip public managers with the right skills to promote and practice justice in their day-to-day interactions with public employees, and to encourage, improve, and facilitate alternative public employee feedback mechanisms.
Depressive disorders are associated with reduced life satisfaction and ability to work. The waiting time for psychotherapy in Germany is currently between three and six months. Accordingly, there is a need for alternative, evidence-based treatment options that are made accessible to patients at a low threshold. A large number of empirical studies prove the effectiveness of exercise in mild and moderate depression. For further conceptualization and quality assurance of exercise as a treatment option, it is necessary to understand the concrete mechanisms of action. In addition to physiological factors, psychological factors also play a role in the effect. As a meta-theory of human experience and behavior, Self-Determination Theory (SDT) provides a useful frame for understanding psychological mechanisms of action with concrete implications for treatment practice. The conceptual extension of SDT to include the frustration of basic psychological needs in addition to need satisfaction is proving useful in the study of mental illness. The first part of this dissertation consists of two publications that validate relevant measurement instruments in this context. The first questionnaire measures the extent of generally experienced satisfaction and frustration of the basic psychological needs for autonomy, competence, and relatedness. The second questionnaire measures the experienced satisfaction of needs by the instructor (here: exercise therapist). The second part of the dissertation includes two publications that examine and classify the satisfaction and frustration of basic psychological needs in depressive symptoms. Differences in the extent of need satisfaction and need frustration between a sample with depression and a sample without depressive symptoms are examined. Further, the relationship between need frustration and depressive symptoms is placed in the context of established pathological processes (emotional dysregulation, rumination). The main findings of this work show that by adding the dimension of need frustration to Basic Psychological Needs Theory, SDT now covers a broader spectrum on the health-disease continuum. In doing so, SDT focuses on the psychological impact of social environments. In addition to the nonfulfillment of basic psychological needs, it is primarily experienced need frustration that is a general vulnerability factor for the occurrence of psychological illness. Moreover, the unbalanced satisfaction of basic psychological needs possibly indicates a conflicting experience between the needs. For the treatment practice it can be deduced that an autonomy-supporting atmosphere, which enables the balanced satisfaction of all three needs, is central for the treatment success.
Point processes are a common methodology to model sets of events. From earthquakes to social media posts, from the arrival times of neuronal spikes to the timing of crimes, from stock prices to disease spreading -- these phenomena can be reduced to the occurrences of events concentrated in points. Often, these events happen one after the other defining a time--series.
Models of point processes can be used to deepen our understanding of such events and for classification and prediction. Such models include an underlying random process that generates the events. This work uses Bayesian methodology to infer the underlying generative process from observed data. Our contribution is twofold -- we develop new models and new inference methods for these processes.
We propose a model that extends the family of point processes where the occurrence of an event depends on the previous events. This family is known as Hawkes processes. Whereas in most existing models of such processes, past events are assumed to have only an excitatory effect on future events, we focus on the newly developed nonlinear Hawkes process, where past events could have excitatory and inhibitory effects. After defining the model, we present its inference method and apply it to data from different fields, among others, to neuronal activity.
The second model described in the thesis concerns a specific instance of point processes --- the decision process underlying human gaze control. This process results in a series of fixated locations in an image. We developed a new model to describe this process, motivated by the known Exploration--Exploitation dilemma. Alongside the model, we present a Bayesian inference algorithm to infer the model parameters.
Remaining in the realm of human scene viewing, we identify the lack of best practices for Bayesian inference in this field. We survey four popular algorithms and compare their performances for parameter inference in two scan path models.
The novel models and inference algorithms presented in this dissertation enrich the understanding of point process data and allow us to uncover meaningful insights.
Behavioral strategy
(2023)
Purpose: Behavioral strategy, as a cognitive- and social-psychological view on strategic management, has gained increased attention. However, its conceptualization is still fuzzy and deserves an in-depth investigation. The authors aim to provide a holistic overview and classification of previous research and identify gaps to be addressed in future research.
Design/methodology/approach: The authors conducted a systematic literature review on behavioral strategy. The final sample includes 46 articles from leading management journals, based on which the authors develop a research framework.
Findings: The results reveal cognition and traits as major internal factors. Besides, organizational and environmental contingencies are major external factors of behavioral strategy.
Originality/value: To the authors’ best knowledge, this is the first holistic systematic literature review on behavioral strategy, which categorizes previous research.
This research examines the impact of firms’ decision-making, crisis management, and risk-taking behaviors on their sustainability and circular economy behaviors through the mediating role of their eco-innovation behavior in the energy industry in Iraq. Firms are exploring applicable mechanisms to increase green practices. This requires the industry to possess the essential skills to overcome the challenges that reduce sustainable activities. We applied a dual-stage structural equation modeling (PLS-SEM) and a multi-criteria decision-making (MCDM) approach to explore the linear relationships between variables, determine the weight of the criteria, and rank energy companies based on a circular economy. The online questionnaire was sent to 549 managers and heads of departments of Iraqi electric power companies. Out of these, 384 questionnaires were collected. The results indicate that firms’ crisis management, decision-making, and risk-taking behaviors are significantly and positively linked to their eco-innovation behavior. This study confirms the significant and positive impact of firms’ eco-innovation behavior on their sustainability and circular economy behaviors. Likewise, eco-innovation behavior has a fully mediating role. For the MCDM methods, ranking energy companies according to the circular economy can support policymakers’ decisions to renew contracts with leading companies in the ranking. Practitioners can also impose government regulations on low-ranked companies. Thus, governments can reduce the problems of greenhouse gas emissions and other environmental pollution.
Entrepreneurship education has gained widespread attention in both education practice and research over the past three decades. However, whereas research has a strong focus on its effects and many normative concepts exist, little is known about how entrepreneurship is actually taught. To address this research gap, we conduct a curriculum analysis of the 50 best programs in entrepreneurship, according to the 2018 Financial Times ranking “Top MBAs for Entrepreneurship 2018”. In particular, we examine their objectives, learning contents and teaching as well as assessment methods as four major dimensions of a graduate entrepreneurship curriculum. The results show that the programs are primarily business and management programs, with a comparatively small share of entrepreneurship itself. Entrepreneurship-specific goals are entrepreneurial attitudes and competences, such as entrepreneurial leadership, entrepreneurial mindset, entrepreneurial skills, opportunity creation, opportunity identification, and transforming uncertainty into opportunity. The learning contents also focus on business, management, and law, whereas the contents relating to entrepreneurship include entrepreneurial failure, entrepreneurial management, entrepreneurial thinking, and entrepreneurship in general. Teaching methods are mainly the ones usually found in higher education, with business plans and prototyping as additional entrepreneurial ones. Assessment methods do not differ from those in business and management education.
Background:
Like most countries, Germany is currently recruiting international nurses due to staff shortages. While these are mostly academic, the academisation of nursing in Germany has only just begun. This allows for a broader look at the participation of migrant nurses: How do care teams deal with the fact that immigrant colleagues are theoretically more highly qualified than long-established colleagues?
Methods:
Case studies were conducted in four inpatient care teams of two hospitals in 2022. Qualitative data include 26 observation protocols, 4 group discussions and 17 guided interviews. These were analysed using the documentary method and validated intersubjectively.
Results:
Due to current academisation efforts in Germany and the immigration of academised nursing staff from abroad, the areas of activity and responsibility of nursing in Germany are under negotiating pressure. This concerns basic care for example, which in Germany is provided by skilled workers, but in other countries is mostly provided by assistants or relatives. The question of who should provide basic care, whether all nurses or only nursing assistants, documents the struggle between an established and a new understanding of care. In this context, the knowledge and skills of migrant and academicised care workers become a crucial aspect in the struggle for a new professional identity for care in Germany.
Conclusions:
The specific situation in Germany makes it possible to show the potential for change that international care migration can constitute for destination countries. The far-reaching process of change of German nursing is given a further dimension not only by its academization, but by the immigration of international and academically trained nursing staff, where inclusive or exclusive effects can already be observed.
Key messages: The increasing proportion of migrant nurses accelerates the current discussion on nursing in Germany. Conflict areas show up in everyday work of care teams and must be addressed there.
Climate change of anthropogenic origin is affecting Earth’s biodiversity and therefore ecosystems and their services. High latitude ecosystems are even more impacted than the rest of Northern Hemisphere because of the amplified polar warming. Still, it is challenging to predict the dynamics of high latitude ecosystems because of complex interaction between abiotic and biotic components. As the past is the key to the future, the interpretation of past ecological changes to better understand ongoing processes is possible. In the Quaternary, the Pleistocene experienced several glacial and interglacial stages that affected past ecosystems. During the last Glacial, the Pleistocene steppe-tundra was covering most of unglaciated northern hemisphere and disappeared in parallel to the megafauna’s extinction at the transition to the Holocene (~11,700 years ago). The origin of the steppe-tundra decline is not well understood and knowledge on the mechanisms, which caused shifts in past communities and ecosystems, is of high priority as they are likely comparable to those affecting modern ecosystems. Lake or permafrost core sediments can be retrieved to investigate past biodiversity at transitions between glacial and interglacial stages. Siberia and Beringia were the origin of dispersal of the steppe-tundra, which make investigation this area of high priority. Until recently, macrofossils and pollen were the most common approaches. They are designed to reconstruct past composition changes but have limit and biases. Since the end of the 20th century, sedimentary ancient DNA (sedaDNA) can also be investigated. My main objectives were, by using sedaDNA approaches to provide scientific evidence of compositional and diversity changes in the Northern Hemisphere ecosystems at the transition between Quaternary glacial and interglacial stages.
In this thesis, I provide snapshots of entire ancient ecosystems and describe compositional changes between Quaternary glacial and interglacial stages, and confirm the vegetation composition and the spatial and temporal boundaries of the Pleistocene steppe-tundra. I identify a general loss of plant diversity with extinction events happening in parallel of megafauna’ extinction. I demonstrate how loss of biotic resilience led to the collapse of a previously well-established system and discuss my results in regards to the ongoing climate change. With further work to constrain biases and limits, sedaDNA can be used in parallel or even replace the more established macrofossils and pollen approaches as my results support the robustness and potential of sedaDNA to answer new palaeoecological questions such as plant diversity changes, loss and provide snapshots of entire ancient biota.
Controlling bioenergy-induced land-use-change emissions is key to exploiting bioenergy for climate change mitigation. However, the effect of different land-use and energy sector policies on specific bioenergy emissions has not been studied so far. Using the global integrated assessment model REMIND-MAgPIE, we derive a biofuel emission factor (EF) for different policy frameworks. We find that a uniform price on emissions from both sectors keeps biofuel emissions at 12 kg CO2 GJ−1. However, without land-use regulation, the EF increases substantially (64 kg CO2 GJ−1 over 80 years, 92 kg CO2 GJ−1 over 30 years). We also find that comprehensive coverage (>90%) of carbon-rich land areas worldwide is key to containing land-use emissions. Pricing emissions indirectly on the level of bioenergy consumption reduces total emissions by cutting bioenergy demand but fails to reduce the average EF. In the absence of comprehensive and timely land-use regulation, bioenergy thus may contribute less to climate change mitigation than assumed previously.
Biogeochemical analyses of lacustrine environments are well-established methods that allow exploring and understanding complex systems in the lake ecosystem. However, most were conducted in temperate lakes controlled by entirely different physical conditions than in tropical climates. The most important difference between the temperate and tropical lakes is lacking seasonal temperature fluctuations in the latter, which leads to a stable temperature gradient in the water column. Thus, the water column in tropical latitudes generally is void of perturbations that can be seen in their temperate counterparts. Permanent stratification in the water column provides optimal conditions for intact sedimentation. The geochemical processes in the water column and the weathering process in the distinct lithology in the catchment leads to the different biogeochemical characteristic in the sediment. Conducting a biogeochemical study in this lake sediment, especially in the Sediment Water Interface (SWI) helps reveal the sedimentation and diagenetic process records influenced by the internal or external loading. Lake Sentani, the study area, is one of the thousands of lakes in Indonesia and located in the Papua province. This tropical lake has a unique feature, as it consists of four interconnected sub-basins with different water depths. More importantly, its catchment is comprised of various different lithologies. Hence, its lithological characteristics are highly diverse, and range from mafic and ultramafic rocks to clastic sediment and carbonates. Each sub-basin receives a distinct sediment input. Equally important, besides the natural loading, Lake Sentani is also influenced by anthropogenic input. Previous studies have elaborated that there is an increase in population growth rate around the lake which has direct consequences on eutrophication. Considering these factors, the government of The Republic of Indonesia put Lake Sentani on the list of national priority lakes for restoration. This thesis aims to develop a fundamental understanding of Lake Sentani's sedimentary geochemistry and geomicrobiology with a special focus on the effects of different lithologies and anthropogenic pressures in the catchment area. We conducted geochemical and geomicrobiology research on Lake Sentani to meet this objective. We investigated geochemical characteristics in the water column, porewater, and sediment core of the four sub-basins. Additional to direct investigations of the lake itself, we also studied the sediments in the tributary rivers, of which some are ephemeral, as well as the river mouths, as connections between riverine and the lacustrine habitat. The thesis is composed of three main publications about Lake Sentani and supported by several publications that focus on other tropical lakes in Indonesia. The first main publication investigates the geochemical characterization of the water column, porewater, and surface sediment (upper 40-50 cm) from the center of the four sub-basins. It reveals that besides catchment lithology, the water column heavily influences the geochemical characteristics in the lake sediments and their porewater. The findings indicate that water column stratification has a strong influence on overall chemistry. The four sub-basins are very different with regard to their water column chemistry. Based on the physicochemical profiles, especially dissolved oxygen, one sub-basin is oxygenated, one intermediate i.e. just reaches oxygen depletion at the sediment-water interface, and two sub-basins are fully meromictic. However, all four sub-basins share the same surface water chemistry. The structure of the water column creates differences on the patterns of anions and cations in the porewater. Likewise, the distinct differences in geochemical composition between the sub-basins show that the lithology in the catchment affects the geochemical characteristic in the sediment. Overall, water column stratification and particularly bottom water oxygenation strongly influence the overall elemental composition of the sediment and porewater composition. The second publication reveals differences in surface sediment composition between habitats, influenced by lithological variations in the catchment area. The macro-element distribution shows that the geochemical characteristics between habitats are different. Furthermore, the geochemical composition also indicates a distinct distribution between the sub-basins. The geochemical composition of the eastern sub-basin suggests that lithogenic elements are more dominant than authigenic elements. This is also supported by sulfide speciation, particle distribution, and smear slide data. The third publication is a geomicrobiological study of the surface sediment. We compare the geochemical composition of the surface sediment and its microbiological composition and compare the different signals. Next Generation Sequencing (NGS) of the 16S rRNA gene was applied to determine the microbial community composition of the surface sediment from a great number of locations. We use a large number of sampling sites in all four sub-basins as well as in the rivers and river mouths to illustrate the links between the river, the river mouth, and the lake. Rigorous assessment of microbial communities across the diverse Lake Sentani habitats allowed us to study some of these links and report novel findings on microbial patterns in such ecosystems. The main result of the Principal Coordinates Analysis (PCoA) based on microbial community composition highlighted some commonalities but also differences between the microbial community analysis and the geochemical data. The microbial community in rivers, river mouths and sub-basins is strongly influenced by anthropogenic input from the catchment area. Generally, Bacteroidetes and Firmicutes could be an indicator for river sediments. The microbial community in the river is directly influenced by anthropogenic pressure and is markedly different from the lake sediment. Meanwhile, the microbial community in the lake sediment reflects the anoxic environment, which is prevalent across the lake in all sediments below a few mm burial depth. The lake sediments harbour abundant sulfate reducers and methanogens. The microbial communities in sediments from river mouths are influenced by both rivers and lake ecosystems. This study provides valuable information to understand the basic processes that control biogeochemical cycling in Lake Sentani. Our findings are critical for lake managers to accurately assess the uncertainties of the changing environmental conditions related to the anthropogenic pressure in the catchment area. Lake Sentani is a unique study site directly influenced by the different geology across the watershed and morphometry of the four studied basins. As a result of these factors, there are distinct geochemical differences between the habitats (river, river mouth, lake) and the four sub-basins. In addition to geochemistry, microbial community composition also shows differences between habitats, although there are no obvious differences between the four sub-basins. However, unlike sediment geochemistry, microbial community composition is impacted by human activities. Therefore, this thesis will provide crucial baseline data for future lake management.