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Nanotemplates for the combined structural and functional analysis of membrane-associated proteins
(2019)
Plasma membranes are essential for life because they give cells an identity. Plasma membranes are almost impermeable to fluids and substances. Still, transport between inside and outside needs to be possible. An important transport way is endocytosis. This mechanism relies on membrane-associated proteins that sense and induce curvature to the plasma membrane. However, the physics and structural dynamics behind proteins acting on membranes is not well understood. There is a standard method in vitro to investigate membrane-associated proteins sensing spherical geometries: They are incubated on unilamellar vesicles. This procedure allows to analyze these proteins in their bound state. This approach is inappropriate for GRAF1 (GTPase Regulator Associated with Focal Adhesion Kinase-1), a key player in endocytosis because it senses tubular geometries instead. However, GRAF1 extrudes lipid tubes from vesicles that can be analyzed. Still, this is a limited method because these tubes suffer from inhomogeneity and they do not enable the observation of intermediate and lower concentration binding states. To overcome this issue they can be incubated on pre-tubular structures called nanotemplates. There have been studies using carbon nanotubes and Galactosylceramide lipid tubes as nanotemplates. These approaches require complex chemical modifications or expensive components and they are not necessarily flexible. In this work we present a simple and easy new approach to prepare nanotemplates using Folch lipid mixture. We show on the basis of BPG, a truncate of GRAF1, that our nanotemplates are suitable for Cryo-EM and that it is possible to use IHRSR (Iterative Helical Real Space Reconstruction) to analyze the structure of BPG in its bound state. Moreover, the qualification for Cryo-EM allows to use plunge freezing to interrupt the incubation on our nanotemplates abruptly. This enables the analysis of intermediate binding states to understand the binding process.
Tracking is an integral part of many modern applications, especially in areas like autonomous systems and Augmented Reality. For performing tracking there are a wide array of approaches. One that has become a subject of research just recently is the utilization of Neural Networks. In the scope of this master thesis an application will be developed which uses such a Neural Network for the tracking process. This also requires the creation of training data as well as the creation and training of a Neural Network. Subsequently the usage of Neural Networks for tracking will be analyzed and evaluated. This includes several aspects. The quality of the tracking for different degrees of freedom will be checked as well as the the impact of the Neural Network on the applications performance. Additionally the amount of required training data is investigated, the influence of the network architecture and the importance of providing depth data as part of the networks input. This should provide an insight into how relevant this approach could be for its adoption in future products.
Belief revision is the subarea of knowledge representation which studies the dynamics of epistemic states of an agent. In the classical AGM approach, contraction, as part of the belief revision, deals with the removal of beliefs in knowledge bases. This master's thesis presents the study and the implementation of concept contraction in the Description Logic EL. Concept contraction deals with the following situation. Given two concept C and D, assuming that C is subsumed by D, how can concept C be changed so that it is not subsumed by D anymore, but is as similar as possible to C? This approach of belief change is different from other related work because it deals with contraction in the level of concepts and not T-Boxes and A-Boxes in general. The main contribution of the thesis is the implementation of the concept contraction. The implementation provides insight into the complexity of contraction in EL, which is tractable since the main inference task in EL is also tractable. The implementation consists of the design of five algorithms that are necessary for concept contraction. The algorithms are described, illustrated with examples, and analyzed in terms of time complexity. Furthermore, we propose an new approach for a selection function, adapt for the concept contraction. The selection function uses metadata about the concepts in order to select the best from an input set. The metadata is modeled in a framework that we have designed, based on standard metadata frameworks. As an important part of the concept contraction, the selection function is responsible for selecting the best concepts that are as similar as possible to concept C. Lastly, we have successfully implemented the concept contraction in Python, and the results are promising.
Streams are coupled with their riparian area. Emerging insects from streams can be an important prey in the riparian area. Such aquatic subsidies can cause predators to switch prey or increase predator abundances. This can impact the whole terrestrial food web. Stressors associated with agricultural land use can alter insect communities in water and on land, resulting in complex response patterns of terrestrial predators that rely on prey from both systems.
This thesis comprises studies on the impact of aquatic nsects on a terrestrial model ecosystem (Objective 1, hapter 2), the influence of agricultural land use on riparian spiders’ traits and community (Objective 2, Chapter 3), and on the impact of agricultural land use on the contribution of different prey to spider diet (Objective 3, Chapter 4).
In chapter 2, I present a study where we conducted a mesocosm experiment to examine the effects of aquatic subsidies on a simplified terrestrial food web consisting of two types of herbivores (leafhoppers and weevils), plants and predators (spiders). I focused on the prey choice of the spiders by excluding predator immigration and reproduction. In accordance with predator switching, survival of leafhoppers increased in the presence of aquatic subsidies. By contrast, the presence of aquatic subsidies indirectly reduced weevils and herbivory.
In chapter 3, I present the results on the taxonomic and trait response of riparian spider communities to gradients of agricultural stressors and environmental variables, with a particular emphasis on pesticides. To capture spiders with different traits and survival strategies, we used multiple collection methods. Spider community composition was best explained by in-stream pesticide toxicity and shading of the stream bank, a proxy for the quality of the habitat. Species richness and the number of spider individuals, as well as community ballooning ability, were negatively associated with in-stream pesticide toxicity. In contrast, mean body size and shading preference of spider communities responded strongest to shading,
whereas mean niche width (habitat preference for moisture and shading) responded strongest to other environmental variables.
In chapter 4, I describe aquatic-terrestrial predator-prey relations with gradients of agricultural stressors and environmental variables. I sampled spiders, as well as their aquatic and terrestrial prey along streams with an assumed pesticide pollution gradient and determined their stable carbon and nitrogen signals. Potential aquatic prey biomass correlated positively with an increasing aquatic prey contribution of T. montana. The contribution of aquatic prey to the diet of P. amentata showed a positive relationship with increasing toxicity in streams.
Overall, this thesis contributes to the emerging discipline of cross-ecosystem ecology and shows that aquatic-terrestrial linkages and riparian food webs can be influenced by land use related stressors. Future manipulative field studies on aquatic-terrestrial linkages are required that consider the quality of prey organisms, fostering mechanistic understanding of such crossecosystem effects. Knowledge on these linkages is important to improve understanding of consequences of anthropogenic stressors and to prevent further losses of ecosystems and their biodiversity.
Student misbehavior and its treatment is a major challenge for teachers and a threat to their well-being. Indeed, teachers are obliged to punish student misbehavior on a regular basis. Additionally, teachers’ punishment decisions are among the most frequently reported situations when it comes to students’ experiences of injustice in school. By implication, it is crucial to understand teachers’ treatment of student misbehavior vis-à-vis students’ perceptions. One key dimension of punishment behavior reflects its underlying motivation and goals. People generally intend to achieve three goals when punishing misbehavior, namely, retribution (i.e., evening out the harm caused), special prevention (i.e., preventing recidivism of the offender), and general prevention (i.e., preventing imitation of others). Importantly, people’s support of these punishment goals is subject to hierarchy and power, implying that teachers’ and students’ punishment goal preferences differ. In this dissertation, I present three research projects that shed first light on teachers’ punishment and its goals along with the students’ perception of classroom intervention strategies pursuing these goals. More specifically, I first examined students’ (i.e., children’s) general support of each of the three punishment goals sketched above. Furthermore, I applied an attributional approach to understand and study the goals teachers intend to achieve when punishing student misbehavior. Finally, I investigated teachers’ and students’ support of the punishment goals regarding the same student misbehavior to directly compare their views on these goals and reactions pursuing them. In sum, the findings show that students generally prefer retribution and special prevention to general prevention, whereas teachers prefer general prevention and special prevention to retribution. This ultimately translates into a "mismatch" of teachers and students in their preferences for specific punishment goals, and the findings suggest that this may indeed enhance students’ perception of injustice. Overall, the results of the present research program may be valuable for the development of classroom intervention strategies that may reduce rather than enhance conflicts in student-teacher-interactions.
To construct a business process model manually is a highly complex and error-prone task which takes a lot of time and deep insights into the organizational structure, its operations and business rules. To improve the output of business analysts dealing with this process, different techniques have been introduced by researchers to support them during construction with helpful recommendations. These supporting recommendation systems vary in their way of what to recommend in the first place as well as their calculations taking place under the hood to recommend the most fitting element to the user. After a broad introduction into the field of business process modeling and its basic recommendation structures, this work will take a closer look at diverse proposals and descriptions published in current literature regarding implementation strategies to effectively and efficiently assist modelers during their business process model creation. A critical analysis of presentations in the selected literature will point out strengths and weaknesses of their approaches, studies and descriptions of those. As a result, the final concept matrix in this work will give a precise and helpful overview about the key features and recommendation methods used and implemented in previous research studies to pinpoint an entry into future works without the downsides already spotted by fellow researchers.
This paper describes the robots TIAGo and Lisa used by
team homer@UniKoblenz of the University of Koblenz-Landau, Germany,
for the participation at the RoboCup@Home 2019 in Sydney,
Australia. We ended up first at RoboCup@Home 2019 in the Open Platform
League and won the competition in our league now three times
in a row (four times in total) which makes our team the most successful
in RoboCup@Home. We demonstrated approaches for learning from
demonstration, touch enforcing manipulation and autonomous semantic
exploration in the finals. A special focus is put on novel system components
and the open source contributions of our team. We have released
packages for object recognition, a robot face including speech synthesis,
mapping and navigation, speech recognition interface, gesture recognition
and imitation learning. The packages are available (and new packages
will be released) on http://homer.uni-koblenz.de.
The Internet of Things is still one of the most relevant topics in the field of economics and research powered by the increasing demand of innovative services. Cost reductions in manufacturing of IoT hardware and the development of completely new communication ways has led to the point of bil-lions of devices connected to the internet. But in order to rule this new IoT landscape a standardized solution to conquer these challenges must be developed, the IoT Architecture.
This thesis examines the structure, purpose and requirements of IoT Architecture Models in the global IoT landscape and proposes an overview across the selected ones. For that purpose, a struc-tured literature analysis on this topic is conducted within this thesis, including an analysis on three existing research approaches trying to frame this topic and a tool supported evaluation of IoT Archi-tecture literature with over 200 accessed documents.
Furthermore, a coding of literature with the help of the specialised coding tool ATLAS.ti 8 is conduct-ed on 30 different IoT Architecture Models. In a final step these Architecture Models are categorized and compared to each other showing that the environment of IoT and its Architectures gets even more complex the further the research goes.
The loss of biodiversity is recognised on a global scale and also in the anthropogenic landscapes used for agriculture, now covering almost 50% of the global terrestrial land surface. In agriculture pesticides, biologically active chemicals are deliberately distributed to control pests, disease and weeds in the cropped areas. The quantification of remaining semi-naturals structures such as field margins and hedges is a prerequisite to understand the impact of pesticides on biodiversity, since these structures represent habitats for many organisms in agricultural landscapes. The presence of organisms in these habitats and crops is required to obtain an estimate of their potential pesticide exposure. In this text I provide studies on animal groups so far not addressed in risk assessment procedures for the regulation of pesticides such as amphibians, moths and bats. For all groups it becomes apparent that they are present in agricultural landscapes and potentially coincide with pesticide applications indicating a risk. Risk quantification also requires data on the sensitivity of organisms and here data for plants, amphibians and bees are presented. Effects translating to community level were studied for herbicide, insecticide and fertiliser effects in a natural system. After three years the treatments resulted in simplified plant communities with lower species numbers and a reduction in flowering plants. This reduction of flowers is used as an example for an indirect effect and was especially obvious for the effect of an herbicide on the common buttercup. Sublethal herbicide effects for a plant translated in an impact on feeding caterpillars, indicating a reduction in food quality. Insecticide inputs realistic for field margins also reduced moth pollination of white champion flowers by 30%. These indirect effects by distortions of food web characteristics are playing a critical role to understand declines in organism groups, however so far are not accounted for in pesticide risk assessment schemes. The current intense use of pesticides in agriculture and their inherent toxicity may lead to a chemical landscape fragmentation, where populations may not be connected anymore. Source-sink dynamics are important ecological processes and as a final result not only population size but also genetic population structure might be affected. Including potential pesticide impacts as costs in a model for amphibians migrating to breeding ponds in vineyards in Rhineland-Palatinate indicated the isolation of investigated populations. A first validation by analyzing the population structure of the European common frog confirmed the model prediction for some sites. For the regulation of pesticides in Europe a risk assessment is required and for the organisms of the terrestrial habitat a multitude of guidance documents is in place or is recently developed or improved. The results of the presented research indicate that wild plants and especially their reproductive flower stage are highly sensitive and risks are underestimated. Population recovery of arthropods needs a reevaluation at landscape scale and the addition of amphibian risk assessment in regulation procedures is suggested. However, developing or adopting risk assessment procedures and test systems is a time consuming task and therefore the establishment of risk management options is a pragmatic alternative with immediate effects. Artificial wetlands in the agricultural landscape proved to be important foraging sites for bats and their creation could mitigate negative pesticide effects. The integration of direct and indirect effects in a risk assessment scheme for all organism groups addressing also landscape scale and pesticide mixtures requires a long developing time. The establishment of model landscapes where management options and integrated pest management are applied on a larger scale would allow us to study pesticide effects in a realistic scenario and to develop an approach for the agriculture of the future.
The goal of this master thesis was to develop a CRM system for the Assist team of CompuGroup Medical that is aiding in integrating open innovation into the development of the Minerva 2.0 software. To achieve this, CRM methodology has been combined with Social Networking Systems, following the research of Lin and Chen (2010, pp. 11 – 30). To achieve the predefined goals literature has been analyzed on how to successfully im- plement a CRM system as well as an online community. Subsequently the results have been applied to the development of the Minerva Community according to the guidelines of Design Science suggested by Hevner et al. (2004, pp. 75 – 104). The finished product is designed based on customer and management requirements and evaluated from a customer and company perspective.
Despite the inception of new technologies at a breakneck pace, many analytics projects fail mainly due to the use of incompatible development methodologies. As big data analytics projects are different from software development projects, the methodologies used in software development projects could not be applied in the same fashion to analytics projects. The traditional agile project management approaches to the projects do not consider the complexities involved in the analytics. In this thesis, the challenges involved in generalizing the application of agile methodologies will be evaluated, and some suitable agile frameworks which are more compatible with the analytics project will be explored and recommended. The standard practices and approaches which are currently applied in the industry for analytics projects will be discussed concerning enablers and success factors for agile adaption. In the end, after the comprehensive discussion and analysis of the problem and complexities, a framework will be recommended that copes best with the discussed challenges and complexities and is generally well suited for the most data-intensive analytics projects.
The erosion of the closed innovation paradigm in conjunction with increasing competitive pressure has boosted the interest of both researchers and organizations in open innovation. Despite such rising interest, several companies remain reluctant to open their organizational boundaries to practice open innovation. Among the many reasons for such reservation are the pertinent complexity of transitioning toward open innovation and a lack of understanding of the procedures required for such endeavors. Hence, this thesis sets out to investigate how organizations can open their boundaries to successfully transition from closed to open innovation by analyzing the current literature on open innovation. In doing so, the transitional procedures are structured and classified into a model comprising three phases, namely unfreezing, moving, and institutionalizing of changes. Procedures of the unfreezing phase lay the foundation for a successful transition to open innovation, while procedures of the moving phase depict how the change occurs. Finally, procedures of the institutionalizing phase contribute to the sustainability of the transition by employing governance mechanisms and performance measures. Additionally, the individual procedures are characterized along with their corresponding barriers and critical success factors. As a result of this structured depiction of the transition process, a guideline is derived. This guideline includes the commonly employed actions of successful practitioners of open innovation, which may serve as a baseline for interested parties of the paradigm. With the derivation of the guideline and concise depiction of the individual transitional phases, this thesis consequently reduces the overall complexity and increases the comprehensibility of the transition and its implications for organizations.
Thesis is devoted to the topic of challenges and solutions for human resources management (HRM) in international organizations. The aim is to investigate methodological approaches to assessment of HRM challenges and solutions, and to apply them on practice, to develop ways of improvement of HRM of a particular enterprise. The practical research question investigated is “Is the Ongoing Professional Development – Strategic HRM (OPD-SHRM) model a better solution for HRM system of PrJSC “Philip Morris Ukraine”?”
To achieve the aim of this work and to answer the research question, we have studied theoretical approaches to explaining and assessing HRM in section 1, analyzed HRM system of an international enterprise in section 2, and then synthesized theory and practice to find intersection points in section 3.
Research findings indicate that the main challenge of HRM is to balance between individual and organizational interests. Implementation of OPD-SHRM is one of the solutions. Switching focus from satisfaction towards success will bring both tangible and intangible benefits for individuals and organization. In case of PrJSC “Philip Morris Ukraine”, the maximum forecasted increase is 330% in net profit, 350% in labor productivity, and 26% in Employee Development and Engagement Index.
Software systems have an increasing impact on our daily lives. Many systems process sensitive data or control critical infrastructure. Providing secure software is therefore inevitable. Such systems are rarely being renewed regularly due to the high costs and effort. Oftentimes, systems that were planned and implemented to be secure, become insecure because their context evolves. These systems are connected to the Internet and therefore also constantly subject to new types of attacks. The security requirements of these systems remain unchanged, while, for example, discovery of a vulnerability of an encryption algorithm previously assumed to be secure requires a change of the system design. Some security requirements cannot be checked by the system’s design but only at run time. Furthermore, the sudden discovery of a security violation requires an immediate reaction to prevent a system shutdown. Knowledge regarding security best practices, attacks, and mitigations is generally available, yet rarely integrated part of software development or covering evolution.
This thesis examines how the security of long-living software systems can be preserved taking into account the influence of context evolutions. The goal of the proposed approach, S²EC²O, is to recover the security of model-based software systems using co-evolution.
An ontology-based knowledge base is introduced, capable of managing common, as well as system-specific knowledge relevant to security. A transformation achieves the connection of the knowledge base to the UML system model. By using semantic differences, knowledge inference, and the detection of inconsistencies in the knowledge base, context knowledge evolutions are detected.
A catalog containing rules to manage and recover security requirements uses detected context evolutions to propose potential co-evolutions to the system model which reestablish the compliance with security requirements.
S²EC²O uses security annotations to link models and executable code and provides support for run-time monitoring. The adaptation of running systems is being considered as is round-trip engineering, which integrates insights from the run time into the system model.
S²EC²O is amended by prototypical tool support. This tool is used to show S²EC²O’s applicability based on a case study targeting the medical information system iTrust.
This thesis at hand contributes to the development and maintenance of long-living software systems, regarding their security. The proposed approach will aid security experts: It detects security-relevant changes to the system context, determines the impact on the system’s security and facilitates co-evolutions to recover the compliance with the security requirements.
The development of a game engine is considered a non-trivial problem. [3] The architecture of such simulation software must be able to manage large amounts of simulation objects in real-time while dealing with “crosscutting concerns” [3,p. 36] between subsystems. The use of object oriented paradigms to model simulation objects in class hierarchies has been reported as incompatible with constantly changing demands during game development [2, p. 9], resulting in anti-patterns and eventual, messy refactoring.[13]
Alternative architectures using data oriented paradigms revolving around object composition and aggregation have been proposed as a result. [13, 9, 1, 11]
This thesis describes the development of such an architecture with the explicit goals to be simple, inherently compatible with data oriented design, and to make reasoning about performance characteristics possible. Concepts are formally defined to help analyze the problem and evaluate results. A functional implementation of the architecture is presented together with use cases common to simulation software.
While the existing literature on cooperative R&D projects between firms and public research institutes (PRI) has made valuable contributions by examining various factors and their influence on different outcome measures, there has been no investigation of cooperative R&D project success between firms and PRI from a product competitive advantage perspective. However, insights into the development of a meaningful and superior product (i.e., product competitive advantage) are particularly important in the context of cooperative R&D projects between PRI and (mainly small and medium-sized) firms in the biotechnology industry in response to increasing competition to raise capital funds necessary for survival.
The objectives of this thesis are: (1) to elaborate the theoretical foundations which explain the achievement of a product competitive advantage in cooperative R&D projects between biotechnology firms and PRI, (2) to identify and empirically evaluate the determining factors for achieving a product competitive advantage in cooperative R&D projects between biotechnology firms and PRI, and (3) to show how cooperative R&D projects between biotechnology firms and PRI should be designed and executed to support the achievement of a product competitive advantage.
To accomplish these objectives, a model of determinants of product competitive advantage in cooperative R&D projects between biotechnology firms and PRI is developed by drawing from the theoretical foundations of resource-based theory and information-processing theory. The model is evaluated using data from 517 questionnaires on cooperative R&D projects between at least one biotechnology firm and one PRI. The data are analyzed using variance-based structural equation modeling (i.e., PLS-SEM) in order to conduct hypotheses testing. The evaluation of the empirical data includes an additional mediation analysis and the comparison of effects in subsamples.
The results demonstrate the importance of available resources and skills, as well as the proficient execution of marketing-related and technical activities for the achievement of a product competitive advantage in cooperative R&D projects between biotechnology firms and PRI. By identifying project-related and process-related factors affecting product competitive advantage and empirically testing their relationships, the research findings should be valuable for both researchers and practitioners. After discussing contributions and implications for research and practice, the present thesis concludes with limitations and avenues for future research.
Lakes and reservoirs are important sources of methane, a potent greenhouse gas. Although freshwaters cover only a small fraction of the global surface, their contribution to global methane emission is significant and this is expected to increase, as a positive feedback to climate warming and exacerbated eutrophication. Yet, global estimates of methane emission from freshwaters are often based on point measurements that are spatio-temporally biased. To better constrain the uncertainties in quantifying methane fluxes from inland waters, a closer examination of the processes transporting methane from sediment to atmosphere is necessary. Among these processes, ebullition (bubbling) is an important transport pathway and is a primary source of uncertainty in quantifying methane emissions from freshwaters. This thesis aims to improve our understanding of ebullition in freshwaters by studying the processes of methane bubble formation, storage and release in aquatic sediments. The laboratory experiments demonstrate that aquatic sediments can store up to ~20% (volumetric content) gas and the storage capacity varies with sediment properties. The methane produced is stored as gas bubbles in sediment with minimal ebullition until the storage capacity is reached. Once the sediment void spaces are created by gas bubble formation, they are stable and available for future bubble storage and transport. Controlled water level drawdown experiments showed that the amounts of gas released from the sediment scaled with the total volume of sediment gas storage and correlated linearly to the drop in hydrostatic pressure. It was hypothesized that not only the timing of ebullition is controlled by sediment gas storage, but also the spatial distribution of ebullition. A newly developed freeze corer, capable of characterizing sediment gas content under in situ environments, enabled the possibility to test the hypothesis in a large subtropical lake (Lake Kinneret, Israel). The results showed that gas content was variable both vertically and horizontally in the lake sediment. Sediment methane production rate and sediment characteristics could explain these variabilities. The spatial distribution of ebullition generally was in a good agreement with the horizontal distribution of depth-averaged (surface 1 m) sediment gas content. While discrepancies were found between sediment depth-integrated methane production and the snapshot ebullition rate, they were consistent in a long term (multiyear average). These findings provide a solid basis for the future development of a process-based ebullition model. By coupling a sediment transport model with a sediment diagenetic model, general patterns of ebullition hotspots can be predicted at a system level and the uncertainties in ebullition flux measurements can be better constrained both on long-term (months to years) and short-term (minutes to hours) scales.
The mitral valve is one of four human heart valves. It is located in the left heart and acts as a unidirectional passageway for blood between the left atrium and the left ventricle. A correctly functioning mitral valve prevents a backflow of blood into the pulmonary circulation (lungs) and thus constitutes a vital part of the cardiac cycle. Pathologies of the mitral valve can manifest in a variety of symptoms with severity ranging from chest pain and fatigue to pulmonary edema (fluid accumulation in the tissue and air space of lungs), which may ultimately cause respiratory failure.
Malfunctioning mitral valves can be restored through complex surgical interventions, which greatly benefit from intensive planning and pre-operative analysis. Visualization techniques provide a possibility to enhance such preparation processes and can also facilitate post-operative evaluation. The work at hand extends current research in this field, building upon patient-specific mitral valve segmentations developed at the German Cancer Research Center, which result in triangulated 3D models of the valve surface. The core of this work will be the construction of a 2D-view of these models through global parameterization, a method that can be used to establish a bijective mapping between a planar parameter domain and a surface embedded in higher dimensions.
A flat representation of the mitral valve provides physicians with a view of the whole surface at once, similar to a map. This allows assessment of the valve's area and shape without the need for different viewing angles. Parts of the valve that are occluded by geometry in 3D become visible in 2D.
An additional contribution of this work will be the exploration of different visualizations of the 3D and 2D mitral valve representations. Features of the valve can be highlighted by associating them with specified colors, which can for instance directly convey pathology indicators.
Quality and effectiveness of the proposed methods were evaluated through a survey conducted at the Heidelberg University Hospital.
Groundwater is essential for the provision of drinking water in many areas around the world. The ecosystem services provided by groundwater-related organisms are crucial for the quality of groundwater-bearing aquifers. Therefore, if remediation of contaminated groundwater is necessary, the remediation method has to be carefully selected to avoid risk-risk trade-offs that might impact these valuable ecosystems. In the present thesis, the ecotoxicity of the in situ remediation agent Carbo-Iron (a composite of zero valent nano-iron and active carbon) was investigated, an estimation of its environmental risk was performed, and the risk and benefit of a groundwater remediation with Carbo-Iron were comprehensively analysed.
At the beginning of the work on the present thesis, a sound assessment of the environmental risks of nanomaterials was impeded by a lack of guidance documents, resulting in many uncertainties on selection of suitable test methods and a low comparability of test results from different studies with similar nanomaterials. The reasons for the low comparability were based on methodological aspects of the testing procedures before and during the toxicity testing. Therefore, decision trees were developed as a tool to systematically decide on ecotoxicity test procedures for nanomaterials. Potential effects of Carbo-Iron on embryonic, juvenile and adult life stages of zebrafish (Danio rerio) and the amphipod Hyalella azteca were investigated in acute and chronic tests. These tests were based on existing OECD and EPA test guidelines (OECD, 1992a, 2013a, 2013b; US EPA, 2000) to facilitate the use of the obtained effect data in the risk assessment. Additionally, the uptake of particles into the test organisms was investigated using microscopic methods. In zebrafish embryos, effects of Carbo-Iron on gene expression were investigated. The obtained ecotoxicity data were complemented by studies with the waterflea Daphnia magna, the algae Scenedesmus vacuolatus, larvae of the insect species Chironomus riparius and nitrifying soil microorganisms.
In the fish embryo test, no passage of Carbo-Iron particles into the perivitelline space or the embryo was observed. In D. rerio and H. azteca, Carbo-Iron was detected in the gut at the end of exposure, but no passage into the surrounding tissue was detected. Carbo-Iron had no significant effect on soil microorganisms and on survival and growth of fish. However, it had significant effects on the growth, feeding rate and reproduction of H. azteca and on survival and reproduction in D. magna. Additionally, the development rate of C. riparius and the cell volume of S. vacuolatus were negatively influenced.
A predicted no effect concentration of 0.1 mg/L was derived from the ecotoxicity studies based on the no-effect level determined in the reproduction test with D. magna and an assessment factor of 10. It was compared to measured and modelled environmental concentrations for Carbo-Iron after application to an aquifer contaminated with chlorohydrocarbons in a field study. Based on these concentrations, risk quotients were derived. Additionally, the overall environmental risk before and after Carbo-Iron application was assessed to verify whether the chances for a risk-risk trade-off by the remediation of the contaminated site could be minimized. With the data used in the present study, a reduced environmental risk was identified after the application of Carbo-Iron. Thus, the benefit of remediation with Carbo-Iron outweighs potential negative effects on the environment.