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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.