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Efficient and predictable thread synchronization mechanisms for mixed-criticality systems on shared-memory multi-processor platforms (2021)
Züpke, Alexander
Real-time operating systems for mixed-criticality systems must support different types of software, such as real-time applications and general purpose applications, and, at the same time, must provide strong spatial and temporal isolation between independent software components. Therefore, state-of-the-art real-time operating systems focus mainly on predictability and bounded worst-case behavior. However, general purpose operating systems such as Linux often feature more efficient---but less deterministic---mechanisms that significantly improve the average execution time. This thesis addresses the combination of the two contradicting requirements and shows thread synchronization mechanisms with efficient average-case behavior, but without sacrificing predictability and worst-case behavior. This thesis explores and evaluates the design space of fast paths in the implementation of typical blocking synchronization mechanisms, such as mutexes, condition variables, counting semaphores, barriers, or message queues. The key technique here is to avoid unnecessary system calls, as system calls have high costs compared to other processor operations available in user space, such as low-level atomic synchronization primitives. In particular, the thesis explores futexes, the state-of-the-art design for blocking synchronization mechanisms in Linux that handles the uncontended case of thread synchronization by using atomic operations in user space and calls into the kernel only to suspend and wake up threads. The thesis also proposes non-preemptive busy-waiting monitors that use an efficient priority ceiling mechanism to prevent the lock holder preemption problem without using system calls, and according low-level kernel primitives to construct efficient wait and notify operations. The evaluation shows that the presented approaches improve the average performance comparable to state-of-the-art approaches in Linux. At the same time, a worst-case timing analysis shows that the approaches only need constant or bounded temporal overheads at the operating system kernel level. Exploiting these fast paths is a worthwhile approach when designing systems that not only have to fulfill real-time requirements, but also best-effort workloads.
Method development for the quantification of pharmaceuticals in aqueous environmental matrices (2021)
Boulard, Lise
As a consequence of the world population increase and the resulting water scarcity, water quality is the object of growing attention. In that context, organic anthropogenic molecules — often defined as micropollutants— represent a threat for water resources. Among them, pharmaceuticals are the object of particular concerns due to their permanent discharge, their increasing consumption and their effect-based structures. Pharmaceuticals are mainly introduced in the environment via wastewater treatment plants (WWTPs), along with their metabolites and the on-site formed transformation products (TPs). Once in the aquatic environment, they partition between the different environmental compartments in particular the aqueous phase, suspended particulate matter(SPM) and biota. In the last decades, pharmaceuticals have been widely investigated in the water phase. However, extreme polar pharmaceuticals have rarely been monitored due to the lack of robust analytical methods. Moreover, metabolites and TPs have seldom been included in routine analysis methods although their environmental relevance is proven. Furthermore, pharmaceuticals have been only sporadically investigated in SPM and biota and adequate multi-residue methods are lacking to obtain comprehensive results about their occurrence in these matrices. This thesis endeavors to cover these gaps of knowledge by the development of generic multi-residue methods for pharmaceuticals determination in the water phase, SPM and biota and to evaluate the occurrence and partition of pharmaceuticals into these compartments. For a complete overview, a particular focus was laid on extreme polar pharmaceuticals, pharmaceutical metabolites and TPs. In total, three innovative multi-residue methods were developed, they include analytes covering a broad range of physico-chemical properties. First, a reliable multi-residue method was developed for the analysis of extreme polar pharmaceuticals, metabolites and TPs dissolved in water. The selected analytes covered a significant range of elevated polarity and the method would be easily expendable to further analytes. This versatility could be achieved by the utilization of freeze-drying as sample preparation and zwitterionic hydrophilic interaction liquid chromatography (HILIC) in gradient elution mode. The suitability of HILIC chromatography to simultaneously quantify a large range of micropollutants in aqueous environmental samples was thoroughly studied. Several limitations were pointed out: a very complex and time-consuming method development, a very high sensitivity with regards to modification of the acetonitrile to water ratio in the eluent or the diluent and high positive matrix effects for certain analytes. However, these limitations can be overcome by the utilization of a precise protocol and appropriate labeled internal standards. They are overmatched by the benefits of HILIC which permits the chromatographic separation of extreme polar micropollutants. Investigation of environmental samples showed elevated concentrations of the analytes in the water phase. In particular, gabapentin, metformin, guanylurea and oxypurinol were measured at concentrations in the µg/L range in surface water. Subsequently, a reliable multi-residue method was established for the determination of 57 pharmaceuticals, 47 metabolites and TPs sorbed to SPM down to the low ng/g range. This method was conceived to cover a large range of polarity in particular with the inclusion of extreme polar pharmaceuticals. The extraction procedure was based on pressurized liquid extraction (PLE) followed by a clean-up via solvent exchange and detection via direct injection-reversed-phase LC-MS/MS and freeze-drying HILIC-MS/MS. Pharmaceutical sorption was examined using laboratory experiments. Derived distribution coefficients Kd varied by five orders of magnitude among the analytes and confirmed a high sorption potential for positively charged and nonpolar pharmaceuticals. The occurrence of pharmaceuticals in German rivers SPM was evaluated by the investigation of annual composite SPM samples taken at four sites at the river Rhine and one site at the river Saar between the years 2005 and 2015. It revealed the ubiquitous presence of pharmaceuticals sorbed to SPM in these rivers. In particular, positively charged analytes, even very polar and nonpolar pharmaceuticals showed appreciable concentrations. For many pharmaceuticals, a distinct correlation was observed between the annual quantities consumed in Germany and the concentrations measured in SPM. Studies of composite SPM spatial distribution permitted to get hints about specific industrial discharge by comparing the pollution pattern along the river. For the first time, these results showed the potential of SPM for the monitoring of positively charged and nonpolar pharmaceuticals in surface water. Finally, a reliable and generic multi residue method was developed to investigate 35 pharmaceuticals and 28 metabolites and TPs in fish plasma, fish liver and fish fillet. For this matrix, it was very challenging to develop an adequate clean-up allowing for the sufficient separation of the matrix disturbances from the analytes. In the final method, fish tissue extraction was performed by cell disruption followed by a non-discriminating clean-up based on silica gel solid-phase extraction(SPE) and restrictive access media (RAM) chromatography. Application of the developed method to the measurement of bream and carp tissues from German rivers revealed that even polar micropollutants such as pharmaceuticals are ubiquitously present in fish tissues. In total, 17 analytes were detected for the first time in fish tissues, including 10 metabolites/TPs. The importance of monitoring metabolites and TPs in fish tissues was confirmed with their detection at similar concentrations as their parents. Liver and fillet were shown to be appropriate for the monitoring of pharmaceuticals in fish, whereas plasma is more inconvenient due to very low concentrations and collection difficulties. Elevated concentrations of certain metabolites suggest possible formation of human metabolites in fish. Measured concentrations indicate a low bioaccumulation potential for pharmaceuticals in fish tissues.
Effects of damming and reservoir operation on hydrodynamics and thermal regimes in large cascade reservoirs of the Yangtze River, China (2021)
Long, Lianghong
Rivers play an important role in the global water cycle, support biodiversity and ecological integrity. However, river flow and thermal regimes are heavily altered in dammed rivers. These impacts are being exacerbated and become more apparent in rivers fragmented by multiple dams. Recent studies mainly focused on evaluating the cumulative impact of cascade reservoirs on flow or thermal regimes, but the role of upstream reservoirs in shaping the hydrology and hydrodynamics of downstream reservoirs remains poorly understood. To improve the understanding of the hydrodynamics in cascade reservoirs, long-term observational data are used in combination with numerical modeling to investigate the changes in flow and thermal regime in three cascade reservoirs at the upper reach of the Yangtze River. The three studied reservoirs are Xiluodu (XLD), Xiangjiaba (XJB) and Three Gorges Reservoir (TGR). In addition, the effects of single reservoir operation (at seasonal/daily time scale) on hydrodynamics are examined in a large tributary of TGR. The results show that the inflow of TGR has been substantially altered by the two upstream reservoirs with a higher discharge in spring and winter and a reduced peak flow in summer. XJB had no obvious contribution to the variations in inflow of TGR. The seasonal water temperature of TGR was also widely affected by the upstream two reservoirs, i.e., an increase in winter and decrease in spring, associated with a delay in water temperature rise and fall. These effects will probably be intensified in the coming years due to the construction of new reservoirs. The study also underlines the importance of reservoir operation in shaping the hydrodynamics of TGR. The seasonal dynamics of density currents in a tributary bay of TGR are closely related to seasonal reservoir operations. In addition, high-frequency water level fluctuations and flow velocity variations were observed in response to periodic tributary bay oscillations, which are driven by the diurnal discharge variations caused by the operation of TGR. As another consequence of operation of cascade reservoirs, the changes in TGR inflow weakened spring thermal stratification and caused warming in spring, autumn and winter. In response to this change, the intrusions from TGR occurred more frequently as overflow and earlier in spring, which caused a sharp reduction in biomass and frequency of phytoplankton blooms in tributary bays of TGR. This study suggests that high-frequency bay oscillations can potentially be used as an efficient management strategy for controlling algal blooms, which can be included in future multi-objective ecological conservation strategies.
Handling Inconsistency in Business Rule Bases (2021)
Corea, Carl
Within the field of Business Process Management, business rules are commonly used to model company decision logic and govern allowed company behavior. An exemplary business rule in the financial sector could be for example: ”A customer with a mental condition is not creditworthy”. Business rules are usually created and maintained collaboratively and over time. In this setting, modelling errors can occur frequently. A challenging problem in this context is that of inconsistency, i.e., contradictory rules which cannot hold at the same time. For instance, regarding the exemplary rule above, an inconsistency would arise if a (second) modeller entered an additional rule: ”A customer with a mental condition is always creditworthy”, as the two rules cannot hold at the same time. In this thesis, we investigate how to handle such inconsistencies in business rule bases. In particular, we develop methods and techniques for the detection, analysis and resolution of inconsistencies in business rule bases
What impedes Consumers’ Delivery Drone Service Adoption? (2020)
Knobloch, Marius ; Schaarschmidt, Mario
Despite widespread plans of big companies like Amazon and Google to develop unmanned delivery drones, scholarly research in this field is scarce, especially in the information systems field. From technical and legal perspectives, drone delivery in last-mile scenarios is in a quite mature state. However, estimates of user acceptance are varying between high skepticism and exaggerated optimism. This research follows a mixed method approach consisting both qualitative and quantitative research, to identify and test determinants of consumer delivery drone service adoption. The qualitative part rests on ten interviews among average consumers, who use delivery services on a regular basis. Insights gained from the qualitative part were used to develop an online survey and to assess the influence of associated risks on adoption intentions. The quantitative results show that especially financial and physical risks impede drone delivery service adoption. Delivery companies who are currently thinking about providing a delivery drone service may find these results useful when evaluating usage behaviors in the future market for delivery drones.
Railway Safety Research – A Cross-Disciplinary Literature Review (2020)
Schneider, André
Railway safety is a topic which gains the public attention only if major railway accidents happen. This is because railway is considered as a safe mode of travel by the public. However, to ensure the safety of the railway system railway companies as well as universities conduct a broad spectrum of research. An overview of this research has not yet been provided in the scholarly literature. Therefore, this thesis follows two objectives. First an overview and ranking of railway safety research universities should be provided. Second, based on these universities, it should be identified which are the most relevant and influential research topics. The ranking is based on the research method “literature review” which forms the methodical basis for this thesis. To evaluate the universities based on a measurable and objective criterion, the number of citations of the researchers from each university is gathered. As a result, the University of Leuven for the civil engineering, Milan Politechnico for mechanical enginering and the University of Loughborough for electrical engineering are identified as the leading university in their field of railway safety research. The top universities for each discipline are distributed all over Europe, North America and Asia. However, a clear focus on the US and British universities is observed. For identification of the most relevant and influential topics the keywords from the publications which are considered in the ranking procedure are analyzed. Focus areas among these keywords are revealed by calculating the count of each keyword. High-speed trains as well as maintenance are recognized as the highly relevant topics in both civil and mechanical engineering. Furthermore, the topic of railway dynamics for mechanical engineering and noise and vibration for civil engineering are identified as the leading topics in the respective discipline. Achieving both research goals required exploratory approaches. Therefore, this thesis leaves open space for future research to deepen the individual topics which are approached in each section. A validation of the results through experts interviews as well as a deepening of the analysis through increasing the number of analyzed universities as well as applying statistical methods is recommended.
Model-based privacy by design (2020)
Ahmadian, Amirshayan
Nowadays, almost any IT system involves personal data processing. In such systems, many privacy risks arise when privacy concerns are not properly addressed from the early phases of the system design. The General Data Protection Regulation (GDPR) prescribes the Privacy by Design (PbD) principle. As its core, PbD obliges protecting personal data from the onset of the system development, by effectively integrating appropriate privacy controls into the design. To operationalize the concept of PbD, a set of challenges emerges: First, we need a basis to define privacy concerns. Without such a basis, we are not able to verify whether personal data processing is authorized. Second, we need to identify where precisely in a system, the controls have to be applied. This calls for system analysis concerning privacy concerns. Third, with a view to selecting and integrating appropriate controls, based on the results of system analysis, a mechanism to identify the privacy risks is required. Mitigating privacy risks is at the core of the PbD principle. Fourth, choosing and integrating appropriate controls into a system are complex tasks that besides risks, have to consider potential interrelations among privacy controls and the costs of the controls. This thesis introduces a model-based privacy by design methodology to handle the above challenges. Our methodology relies on a precise definition of privacy concerns and comprises three sub-methodologies: model-based privacy analysis, modelbased privacy impact assessment and privacy-enhanced system design modeling. First, we introduce a definition of privacy preferences, which provides a basis to specify privacy concerns and to verify whether personal data processing is authorized. Second, we present a model-based methodology to analyze a system model. The results of this analysis denote a set of privacy design violations. Third, taking into account the results of privacy analysis, we introduce a model-based privacy impact assessment methodology to identify concrete privacy risks in a system model. Fourth, concerning the risks, and taking into account the interrelations and the costs of the controls, we propose a methodology to select appropriate controls and integrate them into a system design. Using various practical case studies, we evaluate our concepts, showing a promising outlook on the applicability of our methodology in real-world settings.
Environmental processes transforming inorganic nanoparticles: implications on aquatic invertebrates (2020)
Lüderwald, Simon
Engineered inorganic nanoparticles (EINPs) are produced and utilized on a large scale and will end up in surface waters. Once in surface waters, EINPs are subjected to transformations induced by environmental processes altering the particles’ fate and inherent toxicity. UV irradiation of photoactive EINPs is defined as one effect-inducing pathway, leading to the formation of reactive oxygen species (ROS), increasing EINP toxicity by exerting oxidative stress in aquatic life. Simultaneously, UV irradiation of photoactive EINP alters the toxicity of co-occurring micropollutants (e.g. pesticides) by affecting their degradation. The presence of natural organic matter (NOM) reduces the agglomeration and sedimentation of EINPs, extending the exposure of pelagic species, while delaying the exposure of benthic species living in and on the sediment, which is suggested as final sink for EINPs. However, the joint impact of NOM and UV irradiation on EINP-induced toxicity, but also EINP-induced degradation of micropollutants, and the resulting risk for aquatic biota, is poorly understood. Although potential effects of EINPs on benthic species are increasingly investigated, the importance of exposure pathways (waterborne or dietary) is unclear, along with the reciprocal pathway of EINPs, i.e. the transport back from aquatic to terrestrial ecosystems. Therefore, this thesis investigates: (i) how the presence of NOM affects the UV-induced toxicity of the model EINP titanium dioxide (nTiO2) on the pelagic organism Daphnia magna, (ii) to which extent UV irradiation of nTiO2 in the presence and absence of NOM modifies the toxicity of six selected pesticides in D. magna, (iii) potential exposure pathway dependent effects of nTiO2 and silver (nAg) EINPs on the benthic organism Gammarus fossarum, and (iv) the transport of nTiO2 and gold EINPs (nAu) via the merolimnic aquatic insect Chaetopteryx villosa back to terrestrial ecosystems. nTiO2 toxicity in D. magna increased up to 280-fold in the presence of UV light, and was mitigated by NOM up to 12-fold. Depending on the pesticide, UV irradiation of nTiO2 reduced but also enhanced pesticide toxicity, by (i) more efficient pesticide degradation, and presumably (ii) formation of toxic by-products, respectively. Likewise, NOM reduced and increased pesticide toxicity, induced by (i) protection of D. magna against locally acting ROS, and (ii) mitigation of pesticide degradation, respectively. Gammarus’ energy assimilation was significantly affected by both EINPs, however, with distinct variation in direction and pathway dependence between nTiO2 and nAg. EINP presence delayed C. villosa emergence by up to 30 days, and revealed up to 40% reduced lipid reserves, while the organisms carried substantial amounts of nAu (~1.5 ng/mg), and nTiO2 (up to 2.7 ng/mg). This thesis shows, that moving test conditions of EINPs towards a more field-relevant approach, meaningfully modifies the risk of EINPs for aquatic organisms. Thereby, more efforts need to be made to understand the relative importance of EINP exposure pathways, especially since a transferability between different types of EINPs may not be given. When considering typically applied risk assessment factors, adverse effects on aquatic systems might already be expected at currently predicted environmental EINP concentrations in the low ng-µg/L range.
Deep learning techniques applied to constituency parsing of German (2020)
Rajasekaran, Kandhasamy
Constituent parsing attempts to extract syntactic structure from a sentence. These parsing systems are helpful in many NLP applications such as grammar checking, question answering, and information extraction. This thesis work is about implementing a constituent parser for German language using neural networks. Over the past, recurrent neural networks have been used in building a parser and also many NLP applications. In this, self-attention neural network modules are used intensively to understand sentences effectively. With multilayered self-attention networks, constituent parsing achieves 93.68% F1 score. This is improved even further by using both character and word embeddings as a representation of the input. An F1 score of 94.10% was the best achieved by constituent parser using only the dataset provided. With the help of external datasets such as German Wikipedia, pre-trained ELMo models are used along with self-attention networks achieving 95.87% F1 score.
Study on Data Placement Strategies in Distributed RDF Stores (2020)
Janke, Daniel
The distributed setting of RDF stores in the cloud poses many challenges. One such challenge is how the data placement on the compute nodes can be optimized to improve the query performance. To address this challenge, several evaluations in the literature have investigated the effects of existing data placement strategies on the query performance. A common drawback in theses evaluations is that it is unclear whether the observed behaviors were caused by the data placement strategies (if different RDF stores were evaluated as a whole) or reflect the behavior in distributed RDF stores (if cloud processing frameworks like Hadoop MapReduce are used for the evaluation). To overcome these limitations, this thesis develops a novel benchmarking methodology for data placement strategies that uses a data-placement-strategy-independent distributed RDF store to analyze the effect of the data placement strategies on query performance. With this evaluation methodology the frequently used data placement strategies have been evaluated. This evaluation challenged the commonly held belief that data placement strategies that emphasize local computation, such as minimal edge-cut cover, lead to faster query executions. The results indicate that queries with a high workload may be executed faster on hash-based data placement strategies than on, e.g., minimal edge-cut covers. The analysis of the additional measurements indicates that vertical parallelization (i.e., a well-distributed workload) may be more important than horizontal containment (i.e., minimal data transport) for efficient query processing. Moreover, to find a data placement strategy with a high vertical parallelization, the thesis tests the hypothesis that collocating small connected triple sets on the same compute node while balancing the amount of triples stored on the different compute nodes leads to a high vertical parallelization. Specifically, the thesis proposes two such data placement strategies. The first strategy called overpartitioned minimal edge-cut cover was found in the literature and the second strategy is the newly developed molecule hash cover. The evaluation revealed a balanced query workload and a high horizontal containment, which lead to a high vertical parallelization. As a result these strategies showed a better query performance than the frequently used data placement strategies.
Analysis of medical images using deep learning (2020)
Utegulov, Almat
Since the invention of U-net architecture in 2015, convolutional networks based on its encoder-decoder approach significantly improved results in image analysis challenges. It has been proven that such architectures can also be successfully applied in different domains by winning numerous championships in recent years. Also, the transfer learning technique created an opportunity to push state-of-the-art benchmarks to a higher level. Using this approach is beneficial for the medical domain, as collecting datasets is generally a difficult and expensive process. In this thesis, we address the task of semantic segmentation with Deep Learning and make three main contributions and release experimental results that have practical value for medical imaging. First, we evaluate the performance of four neural network architectures on the dataset of the cervical spine MRI scans. Second, we use transfer learning from models trained on the Imagenet dataset and compare it to randomly initialized networks. Third, we evaluate models trained on the bias field corrected and raw MRI data. All code to reproduce results is publicly available online.
Gel effect induced by mucilage in the pore space and consequences on soil physical properties (2020)
Brax, Mathilde
Water uptake, respiration and exudation are some of the biological functions fulfilled by plant roots. They drive plant growth and alter the biogeochemical parameters of soil in the vicinity of roots, the rhizosphere. As a result, soil processes such as water fluxes, carbon and nitrogen exchanges or microbial activity are enhanced in the rhizosphere in comparison to the bulk soil. In particularly, the exudation of mucilage as a gel-like substance by plant roots seems to be a strategy for plants to overcome drought stress by increasing soil water content and soil unsaturated hydraulic conductivity at negative water potentials. Although the variations of soil properties due to mucilage are increasingly understood, a comprehensive understanding of the mechanisms in the pore space leading to such variations is lacking. The aim of this work was to elucidate the gel properties of mucilage in the pore space, i.e. interparticulate mucilage, in order to link changes of the physico-chemical properties in the rhizosphere to mucilage. The fulfilment of this goal was confronted to the three following challenges: The lack of methods for in situ detection of mucilage in soil; The lack of knowledge concerning the properties of interparticulate mucilage; The unknown relationship between the composition and the properties of model substances and root mucilage produced by various species. These challenges are addressed in several chapters. In a first instance, a literature review picked information from various scientific fields about methods enabling the characterization of gels and gel phases in soil. The variation of soil properties resulting from biohydrogel swelling in soil was named the gel effect. The combined study of water entrapment of gels and gel phases in soil and soil structural properties in terms of mechanical stability or visual structures proved promising to disentangle the gel effect in soil. The acquired methodical knowledge was used in the next experiments to detect and characterize the properties of interparticulate gel. 1H NMR relaxometry allows the non-invasive measure of water mobility in porous media. A conceptual model based on the equations describing the relaxation of water protons in porous media was developed to integrate the several gel effects into the NMR parameters and quantify the influence of mucilage on proton relaxation. Rheometry was additionally used to assess mucilage viscosity and soil microstructural stability and ESEM images to visualize the network of interparticulate gel. Combination of the results enabled to identify three main interparticulate gel properties: The spider-web effect restricts the elongation of the polymer chains due to the grip of the polymer network to the surface of soil particles. The polymer network effect illustrates the organization of the polymer network in the pore space according to the environment. The microviscosity effect describes the increased viscosity of interparticulate gel in contrast to free gel. The impact of these properties on soil water mobility and microstructural stability were investigated. Consequences on soil hydraulic and soil mechanical properties found in the literature are further discussed. The influence of the chemical properties of polymers on gel formation mechanism and gel properties was also investigated. For this, model substances with various uronic acid content, degree of esterification and amount of calcium were tested and their amount of high molecular weight substances was measured. The substances investigated included pectic polysaccharides and chia seed mucilage as model polymers and wheat and maize root mucilage. Polygalacturonic acid and low-methoxy pectin proved as non-suitable model polymers for seed and root mucilage as ionic interactions with calcium control their properties. Mucilage properties rather seem to be governed by weak electrostatic interactions between the entangled polymer chains. The amount of high molecular weight material varies considerably depending on mucilage´s origin and seems to be a straight factor for mucilage’s gel effect in soil. Additionally to the chemical characterization of the high molecular weight compounds, determination of their molecular weight and of their conformation in several mucilages types is needed to draw composition-property profiles. The variations measured between the various mucilages also highlight the necessity to study how the specific properties of the various mucilages fulfill the needs of the plant from which they are exuded. Finally, the integration of molecular interactions in gel and interparticulate gel properties to explain the physical properties of the rhizosphere was discussed. This approach offers numerous perspectives to clarify for example how water content or hydraulic conductivity in the rhizosphere vary according to the properties of the exuded mucilage. The hypothesis that the gel effect is general for all soil-born exudates showing gel properties was considered. As a result, a classification of soil-born gel phases including roots, seeds, bacteria, hyphae and earthworm’s exuded gel-like material according to their common gel physico-chemical properties is recommended for future research. An outcome could be that the physico-chemical properties of such gels are linked with the extent of the gel effect, with their impact on soil properties and with the functions of the gels in soil.
Flower-visiting insects in Europe: Evaluating the environmental consequences of agricultural pesticide use in the context of risk assessment (2020)
Uhl, Philipp
The European landscape is dominated by intensive agriculture which leads to widespread impact on the environment. The frequent use of agricultural pesticides is one of the major causes of an ongoing decline in flower-visiting insects (FVIs). The conservation of this ecologically diverse assemblage of mobile, flying insect species is required by international and European policy. To counteract the decrease in species numbers and their abundances, FVIs need to be protected from anthropogenic stressors. European pesticide risk assessment was devised to prevent unacceptable adverse consequences of pesticide use on FVIs. However, there is an ongoing discussion by scientists and policy-makers if the current risk assessment actually provides adequate protection for FVI species. The first main objective of this thesis was to investigate pesticide impact on FVI species. The scientific literature was reviewed to identify groups of FVIs, summarize their ecology, and determine their habitat. This was followed by a synthesis of studies about the exposure of FVIs in their habitat and subsequent effects. In addition, the acute sensitivity of one FVI group, bee species, to pesticides was studied in laboratory experiments. The second main objective was to evaluate the European risk assessment for possible deficits and propose improvements to the current framework. Regulatory documents were screened to assess the adequacy of the guidance in place in light of the scientific evidence. The suitability of the honey bee Apis mellifera as the currently only regulatory surrogate species for FVIs was discussed in detail. The available scientific data show that there are far more groups of FVIs than the usually mentioned bees and butterflies. FVIs include many groups of ecologically different species that live in the entire agricultural landscape. Their habitats in crops and adjacent semi-natural areas can be contaminated by pesticides through multiple pathways. Environmentally realistic exposure of these habitats can lead to severe effects on FVI population parameters. The laboratory studies of acute sensitivity in bee species showed that pesticide effects on FVIs can vary greatly between species and pesticides. The follow-up critical evaluation of the European FVI risk assessment revealed major shortcomings in exposure and effect assessment. The honey bee proved to be a sufficient surrogate for bee species in lower tier risk assessment. Additional test species may be chosen for higher tier risk assessment to account for ecological differences. This thesis shows that the ecology of FVIs should generally be considered to a greater extent to improve the regulatory process. Data-driven computational approaches could be used as alternative methods to incorporate ecological trait data in spatio-temporal scenarios. Many open questions need to be answered by further research to better understand FVI species and promote necessary changes to risk assessment. In general, other FVI groups than bees need to be investigated. Furthermore, comprehensive data on FVI groups and their ecology need to be collected. Contamination of FVI habitat needs to be linked to exposure of FVI individuals and ecologically complex effects on FVI populations should receive increased attention. In the long term, European FVI risk assessment would benefit from shifting its general principles towards more scientifically informed regulatory decisions. This would require a paradigm shift from arbitrary assumptions and unnecessarily complicated schemes to a substantiated holistic framework.
Molecular Dynamics Simulations Utilizing the GPU (2020)
Krieg, Christina
Molecular dynamics (MD) as a field of molecular modelling has great potential to revolutionize our knowledge and understanding of complex macromolecular structures. Its field of application is huge, reaching from computational chemistry and biology over material sciences to computer-aided drug design. This thesis on one hand provides insights into the underlying physical concepts of molecular dynamics simulations and how they are applied in the MD algorithm, and also briefly illustrates different approaches, as for instance the molecular mechanics and molecular quantum mechanics approaches. On the other hand an own all-atom MD algorithm is implemented utilizing and simplifying a version of the molecular mechanics based AMBER force field published by \big[\cite{cornell1995second}\big]. This simulation algorithm is then used to show by the example of oxytocin how individual energy terms of a force field function. As a result it has been observed, that applying the bond stretch forces alone caused the molecule to be compacted first in certain regions and then as a whole, and that with adding more energy terms the molecule got to move with increasing flexibility.
Blockchain in Healthcare (2020)
K.C., Biplov
The underlying characteristics of blockchain can facilitate data provenance, data integrity, data security, and data management. It has the potential to transform the healthcare sector. Since the introduction of Bitcoin in the fintech industry, the blcockhain technology has been gaining a lot of traction and its purpose is not just limited to finance. This thesis highlights the inner workings of blockchain technology and its application areas with possible existing solutions. Blockchain could lay the path for a new revolution in conventional healthcare systems. We presented how individual sectors within the healthcare industry could use blockchain and what solution persists. Also, we have presented our own concept to improve the existing paper-based prescription management system which is based on Hyperledger framework. The results of this work suggest that healthcare can benefit from blockchain technology bringing in the new ways patients can be treated.
Effects of Silver Nanoparticles on Bacterial Biofilms (2020)
Grün, Alexandra Yvonne
Because silver nanoparticles (Ag NPs) are broadly applied in consumer products, their leaching will result in the continuous release of Ag NPs into the natural aquatic environment. Therefore, bacterial biofilms, as the prominent life form of microorganisms in the aquatic environment, are most likely confronted with Ag NPs as a pollutant stressor. Notwithstanding the significant ecological relevance of bacterial biofilms in aquatic systems, and though Ag NPs are expected to accumulate within these biofilms in the environment, the knowledge on the environmental and ecological impact of Ag NPs, is still lagging behind the industrial growth of nanotechnology. Consequently, aim of this thesis was to perform effect assessment of Ag NP exposure on bacterial biofilms with ambient Ag NPs concentrations and under environmentally relevant conditions. Therefore, a comprehensive set of methods was applied in this work to study if and how Ag NPs of two different sizes (30 and 70 nm) affect bacterial biofilms i.e. both monospecies biofilms and freshwater biofilms in environmentally relevant concentrations (600 - 2400 µg l-1). Within the first part of this work, a newly developed assay to test the mechanical stability of monospecies biofilms of the freshwater model bacterium Aquabacterium citratiphilum was validated. In the first study, to investigate the impact of Ag NPs on the mechanical stability of bacterial biofilms, sublethal effects on the mechanical stability of the biofilms were observed with negative implications for biostabilization. Furthermore, as it is still challenging to monitor the ecotoxicity of Ag NPs in natural freshwater environments, a mesocosm study was performed in this work to provide the possibility for the detailed investigation of effects of Ag NPs on freshwater biofilms under realistic environmental conditions. By applying several approaches to analyze biofilms as a whole in response to Ag NP treatment, insights into the resilience of bacterial freshwater biofilms were obtained. However, as revealed by t-RFLP fingerprinting combined with phylogenetic studies based on the 16S gene, a shift in the bacterial community composition, where Ag NP-sensitive bacteria were replaced by more Ag NP-tolerant species with enhanced adaptability towards Ag NP stress was determined. This shift within the bacterial community may be associated with potential detrimental effects on the functioning of these biofilms with respect to nutrient loads, transformation and/or degradation of pollutants, and biostabilization. Overall, bringing together the key findings of this thesis, 4 general effect mechanisms of Ag NP treatment have been identified, which can be extrapolated to natural freshwater biofilms i.e. (i) the identification of Comamonadaceae as Ag NP-tolerant, (ii) a particular resilient behaviour of the biofilms, (iii) the two applied size fractions of Ag NPs exhibited similar effects independent of their sizes and their synthesis method, and (iv) bacterial biofilms show a high uptake capacity for Ag NPs, which indicates cumulative enrichment.
Prototyping a Verification Tool for Decision Model and Notation (2020)
Blatt, Jonas
The industry standard Decision Model and Notation (DMN) has enabled a new way for the formalization of business rules since 2015. Here, rules are modeled in so-called decision tables, which are defined by input columns and output columns. Furthermore, decisions are arranged in a graph-like structure (DRD level), which creates dependencies between them. With a given input, the decisions now can be requested by appropriate systems. Thereby, activated rules produce output for future use. However, modeling mistakes produces erroneous models, which can occur in the decision tables as well as at the DRD level. According to the Design Science Research Methodology, this thesis introduces an implementation of a verification prototype for the detection and resolution of these errors while the modeling phase. Therefore, presented basics provide the needed theoretical foundation for the development of the tool. This thesis further presents the architecture of the tool and the implemented verification capabilities. Finally, the created prototype is evaluated.
Abstraction of Bio-Medical Surface Data for Enhanced Comprehension and Analysis (2020)
Lichtenberg, Nils
Bio-medical data comes in various shapes and with different representations. Domain experts use such data for analysis or diagnosis, during research or clinical applications. As the opportunities to obtain or to simulate bio-medical data become more complex and productive, the experts face the problem of data overflow. Providing a reduced, uncluttered representation of data, that maintains the data’s features of interest falls into the area of Data Abstraction. Via abstraction, undesired features are filtered out to give space - concerning the cognitive and visual load of the viewer - to more interesting features, which are therefore accentuated. To address this challenge, the dissertation at hand will investigate methods that deal with Data Abstraction in the fields of liver vasculature, molecular and cardiac visualization. Advanced visualization techniques will be applied for this purpose. This usually requires some pre-processing of the data, which will also be covered by this work. Data Abstraction itself can be implemented in various ways. The morphology of a surface may be maintained, while abstracting its visual cues. Alternatively, the morphology may be changed to a more comprehensive and tangible representation. Further, spatial or temporal dimensions of a complex data set may be projected to a lower space in order to facilitate processing of the data. This thesis will tackle these challenges and therefore provide an overview of Data Abstraction in the bio-medical field, and associated challenges, opportunities and solutions.
Face and Gaze Controlled Onscreen Presentations (FAGCOP) (2020)
Bukhari, Syed Nabil Afaraz
On-screen interactive presentations have got immense popularity in the domain of attentive interfaces recently. These attentive screens adapt their behavior according to the user's visual attention. This thesis aims to introduce an application that would enable these attentive interfaces to change their behavior not just according to the gaze data but also facial features and expressions. The modern era requires new ways of communications and publications for advertisement. These ads need to be more specific according to people's interests, age, and gender. When advertising, it's important to get a reaction from the user but not every user is interested in providing feedback. In such a context more, advance techniques are required that would collect user's feedback effortlessly. The main problem this thesis intends to resolve is, to apply advanced techniques of gaze and face recognition to collect data about user's reactions towards different ads being played on interactive screens. We aim to create an application that enables attentive screens to detect a person's facial features, expressions, and eye gaze. With eye gaze data we can determine the interests and with facial features, age and gender can be specified. All this information will help in optimizing the advertisements.
Relations between climate sensitive factors and fecally derived microorganisms in rivers (2020)
Herrig, Ilona
Microbial pollution of surface waters poses substantial risks for public health, amongst others during recreational use. Microbial pollution was studied at selected sampling sites in rivers Rhine, Moselle and Lahn (Germany) on the basis of commonly used fecal indicator organisms (FIO) indicating bacterial (Escherichia coli, intestinal enterococci) and viral (somatic coliphages) fecal contamination. In addition, blaCTX-Mantibiotic resistance genes (ARG) were quantified at twosites in river Lahn and were used as markers for tracking the spread of antibiotic resistance in the aquatic environment. The impact of changes in climate-related parameters on FIO was examined by studying monitoring results of contrasting flow conditions at rivers Rhine and Moselle. Analyses at all studied river sites clearly indicate that high discharge and precipitation enhance the influx of FIO, ARG and thus potentially (antibiotic resistant) pathogens into rivers. In contrast, a decrease in hygienic microbial pollution was observed under high solar irradiation and increasing water temperatures. Based on identified contributing key factors, multiple linear regression (MLR) models for five sites at a stretch of river Lahn were established that allow a timely assessment of fecal indicator abundances. An interaction between abiotic and biotic factors (i.e. enhanced grazing pressure) considerably contributed to the formation of seasonal patterns among FIO abundances. This was enhanced during extraordinary low flow conditions in rivers with pronounced trophic interactions, clearly hampering a transfer of model approaches between rivers of different biological and hydrological characteristics. Bacterial indicatorswere stronger influenced by grazing pressure than phages. Hence, bacterial indicators alone do not sufficiently describe viral pollution in rivers. BlaCTX-Mgenes were omnipresent in Lahn River water and corresponded to distribution patterns of FIO, indicating fecal sources. Agriculture and waste watertreatment plant effluents contributed to ARG loads and participants in non-bathing water sports were found to be at risk of ingesting antibiotic resistant bacteria (ARB) including ARG, bearing the risk of infection or colonization. Results of the present study highlight the need to be aware of such risks not only in designated bathing waters. ARG abundance at both riverine sampling sites could largely be explained by E. coliabundance and may thus also be incorporated into multiple regression models using E. colispecific environmental predictors. It can be expected that the frequency of short-term microbial pollution events will increase over the next decades due to climate change. Several challenges were identified with regard to the implementation of early warning systems to protect the public from exposure to pathogens in rivers. Most importantly, the concept of the Bathing Water Directive (Directive 2006/7/EC) itself as well as the lack of harmonization in the regulatory framework at European Union (EU) level are major drawbacks and require future adjustments to reliably manage health risks related to microbial water pollution in waters used in multifunctional ways.
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