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Agriculture covers one third of the world land area and has become a major source of water pollution due to its heavy reliance on chemical inputs, namely fertilisers and pesticides. Several thousands of tonnes of these chemicals are applied worldwide annually and partly reach freshwaters. Despite their widespread use and relatively unspecific modes of action, fungicides are the least studied group of pesticides. It remains unclear whether the taxonomic groups used in pesticide risk assessment are protective for non-target freshwater fungi. Fungi and bacteria are the main microbial decomposers converting allochthonous organic matter (litter) into a more nutritious food resource for leaf-shredding macroinvertebrates. This process of litter decomposition (LD) is central for aquatic ecosystem because it fuels local and downstream food webs with energy and nutrients. Effects of fungicides on decomposer communities and LD have been mainly analysed under laboratory conditions with limited representation of the multiple factors that may moderate effects in the field.
In this thesis a field study was conducted in a German vineyard area to characterise recurrent episodic exposure to fungicides in agricultural streams (chapter 2) and its effects on decomposer communities and LD (chapter 3). Additionally, potential interaction effects of nutrient enrichment and fungicides on decomposer communities and LD were analysed in a mesocosm experiment (chapter 4).
In the field study event-driven water sampling (EDS) and passive sampling with EmporeTM styrene-divinylbenzene reverse phase sulfonated disks (SDB disks) were used to assess exposure to 15 fungicides and 4 insecticides. A total of 17 streams were monitored during 4 rainfall events within the local application period of fungicides in 2012. EDS exceeded the time-weighted average concentrations provided by the SDB disks by a factor of 3, though high variability among compounds was observed. Most compounds were detected in more than half of the sites and mean and maximum peak (EDS) concentrations were under 1 and 3 µg/l, respectively. Besides, SDB disk-sampling rates and a free-software solution to derive sampling rates under time-variable exposure were provided.
Several biotic endpoints related to decomposers and LD were measured in the same sampling sites as the fungicide monitoring, coinciding with the major litter input period. Our results suggest that polar organic fungicides in streams change the structure of the fungal community. Causality of this finding was supported by a subsequent microcosm experiment. Whether other effects observed in the field study, such as reduced fungal biomass, increased bacterial density or reduced microbial LD can be attributed to fungicides remains speculative and requires further investigation. By contrast, neither the invertebrate LD nor in-situ measured gammarid feeding rates correlated with water-borne fungicide toxicity, but both were negatively associated with sediment copper concentrations. The mesocosm experiment showed that fungicides and nutrients affect microbial decomposers differently and that they can alter community structure, though longer experiments are needed to determine whether these changes may propagate to invertebrate communities and LD. Overall, further studies should include representative field surveys in terms of fungicide pollution and physical, chemical and biological conditions. This should be combined with experiments under controlled conditions to test for the causality of field observations.
The work presented in this thesis investigated interactions of selected biophysical processes that affect zooplankton ecology at smaller scales. In this endeavour, the extent of changes in swimming behaviour and fluid disturbances produced by swimming Daphnia in response to changing physical environments were quantified. In the first research question addressed within this context, size and energetics of hydrodynamic trails produced by Daphnia swimming in non-stratified still waters were characterized and quantified as a function of organisms’ size and their swimming patterns.
The results revealed that neither size nor the swimming pattern of Daphnia affects the width of induced trails or dissipation rates. Nevertheless, as the size and swimming velocity of the organisms increased, trail volume increased in proportional to the cubic power of Reynolds number, and the biggest trail volume was about 500 times the body volume of the largest daphnids. Larger spatial extent of fluid perturbation and prolonged period to decay caused by bigger trail volumes would play a significant role in zooplankton ecology, e.g. increasing the risk of predation.
The study also found that increased trail volume brought about significantly enhanced total dissipated power at higher Reynolds number, and the magnitudes of total dissipated power observed varied in the range of (1.3-10)X10-9 W.
Furthermore, this study provided strong evidence that swimming speed of Daphnia and total dissipated power in Daphnia trails exceeded those of some other selected zooplankton species.
In recognizing turbulence as an intrinsic environmental perturbation in aquatic habitats, this thesis also examined the response of Daphnia to a range of turbulence flows, which correspond to turbu-lence levels that zooplankton generally encounter in their habitats. Results indicated that within the range of turbulent intensities to which the Daphnia are likely to be exposed in their natural habitats, increasing turbulence compelled the organisms to enhance their swimming activity and swim-ming speed. However, as the turbulence increased to extremely high values (10-4 m2s-3), Daphnia began to withdraw from their active swimming behaviour. Findings of this work also demonstrated that the threshold level of turbulence at which animals start to alleviate from largely active swimming is about 10-6 m2s-3. The study further illustrated that during the intermediate range of turbu-lence; 10-7 - 10-6 m2s-3, kinetic energy dissipation rates in the vicinity of the organisms is consistently one order of magnitude higher than that of the background turbulent flow.
Swarming, a common conspicuous behavioural trait observed in many zooplankton species, is considered to play a significant role in defining freshwater ecology of their habitats from food exploitation, mate encountering to avoiding predators through hydrodynamic flow structures produced by them, therefore, this thesis also investigated implications of Daphnia swarms at varied abundance & swarm densities on their swimming kinematics and induced flow field.
The results showed that Daphnia aggregated in swarms with swarm densities of (1.1-2.3)x103 L-1, which exceeded the abundance densities by two orders of magnitude (i.e. 1.7 - 6.7 L-1). The estimated swarm volume decreased from 52 cm3 to 6.5 cm3, and the mean neighbouring distance dropped from 9.9 to 6.4 body lengths. The findings of this work also showed that mean swimming trajectories were primarily horizontal concentric circles around the light source. Mean flow speeds found to be one order of magnitude lower than the corresponding swimming speeds of Daphnia. Furthermore, this study provided evidences that the flow fields produced by swarming Daphnia differed considerably between unidirectional vortex swarming and bidirectional swimming at low and high abundances respectively.
In Part I: "The flow-decomposition problem", we introduce and discuss the flow-decomposition problem. Given a flow F, this problem consists of decomposing the flow into a set of paths optimizing specific properties of those paths. We introduce different types of decompositions, such as integer decompositions and alpha-decompositions, and provide two formulations of the set of feasible decompositions.
We show that the problem of minimizing the longest path in a decomposition is NP-hard, even for fractional solutions. Then we develop an algorithm based on column generation which is able to solve the problem.
Tight upper bounds on the optimal objective value help to improve the performance.
To find upper bounds on the optimal solution for the shortest longest path problem, we develop several heuristics and analyze their quality. On pearl graphs we prove a constant approximation ratio of 2 and 3 respectively for all heuristics. A numerical study on random pearl graphs shows that the solutions generated by the heuristics are usually much better than this worst-case bound.
In Part II: "Construction and analysis of evacuation models using flows over time", we consider two optimization models in the context of evacuation planning. The first model is a parameter-based quickest flow model with time-dependent supply values. We give a detailed description of the network construction and of how different scenarios are modeled by scenario parameters. In a second step we analyze the effect of the scenario parameters on the evacuation time. Understanding how the different parameters influence the evacuation time allows us to provide better advice for evacuation planning and allows us to predict evacuation times without solving additional optimization problems. To understand the effect of the time-dependent supply values, we consider the quickest path problem with time-dependent supply values and provide a solution algorithm. The results from this consideration are generalized to approximate the behavior of the evacuation times in the context of quickest flow problems.
The second model we consider is a path-based model for evacuation in the presence of a dynamic cost function. We discuss the challenges of this model and provide ideas for how to approach the problem from different angles. We relate the problem to the flow-decomposition problem and consider the computation of evacuation paths with dynamic costs for large capacities. For the latter method we provide heuristics to find paths and compare them to the optimal solutions by applying the methods to two evacuation scenarios. An analysis shows that the paths generated by the heuristic yield close to optimal solutions and in addition have several desirable properties for evacuation paths which are not given for the optimal solution.
Reaktiv lokale Algorithmen sind verteilte Algorithmen, die den Anforderungen großer, batteriebetriebener, Drahtloser Ad Hoc und Sensornetzwerke im besonderen Maße gerecht werden. Durch Vermeidung überflüssiger Nachrichtenübertragungen sowie Verzicht auf proaktive Ermittlung von Nachbarschaftstabellen (d.h. beaconing) minimieren solche Algorithmen den Kommunikationsaufwand und skalieren gut bei wachsender Netzgröße. Auf diese Weise werden Ressourcen wie Bandbreite und Energie geschont, es kommt seltener zu Nachrichtenkollisionen und dadurch zu einer Erhöhung der Paketempfangsrate, sowie einer Reduktion der Latenzen.
Derzeit wird diese Algorithmenklasse hauptsächlich für Geografisches Routing, sowie zur Topologiekontrolle, insbesondere zur Ermittlung der Adjazenzliste eines Knotens in zusammenhängenden, kantenschnittfreien (planaren) Repräsentationen des Netzgraphen, eingesetzt. Ersteres ermöglicht drahtlose multi-hop Kommunikation auf Grundlage von geografischen Knotenpositionen ohne Zuhilfenahme zusätzlicher Netzwerkinfrastruktur, wohingegen Letzteres eine hinreichende Grundlage für effiziente, lokale Lösungen einer Reihe algorithmischer Problemstellungen ist.
Die vorliegende Dissertation liefert neue Erkenntnisse zum Forschungsgebiet der reaktiven Algorithmen, zum Einen auf einer abstrakten Ebene und zum Anderen durch die Einführung neuer Algorithmen.
Erstens betrachtet diese Arbeit reaktive Algorithmen erstmalig im Ganzen und als eigenständiges Forschungsfeld. Es wird eine umfangreiche Literaturstudie zu dieser Thematik präsentiert, welche die aus der Literatur bekannten Algorithmen, Techniken und Anwendungsfelder systematisch auflistet, klassifiziert und einordnet. Weiterhin wird das mathematische Konzept der O- und Omega-reaktiv lokalen Topologiekontrolle eingeführt. Dieses Konzept ermöglicht erstmals die eindeutige Unterscheidung reaktiver von konventionellen, beacon-basierten, verteilten Topologiekontrollalgorithmen. Darüber hinaus dient es als Klassifikationsschema für existierende, sowie zukünftige Algorithmen dieser Art. Zu guter Letzt ermöglicht dieses Konzept grundlegende Aussagen über die Mächtigkeit des reaktiven Prinzips, welche über Entwurf und Analyse von Algorithmen hinaus reichen.
Zweitens werden in dieser Arbeit neue reaktiv lokale Algorithmen zur Topologiekontrolle und Geografischem Routing eingeführt, wobei drahtlose Netze durch Unit Disk bzw. Quasi Unit Disk Graphen modelliert werden. Diese Algorithmen berechnen für einen gegebenen Knoten die lokale Sicht auf zusammenhängende, planare, Euklidische bzw. Topologische Spanner mit konstanter Spannrate bzgl. des Netzgraphen und routen Nachrichten reaktiv entlang der Kanten dieser Spanner, wobei die Nachrichtenauslieferung garantiert wird. Alle bisher bekannten Verfahren sind entweder nicht reaktiv oder gewährleisten keine konstanten Euklidischen oder Topologischen Spannraten. Ein wesentliches Teilergebnis dieser Arbeit ist der Nachweis, dass die partielle Delaunay Triangulierung (PDT) ein Euklidischer Spanner mit konstanter Spannrate für Unit Disk Graphen ist.
Die in dieser Dissertation gewonnenen Erkenntnisse bilden die Basis für grundlegende und strukturierte Forschung auf diesem Gebiet und zeigen, dass das reaktive Prinzip ein wichtiges Werkzeug des Algorithmenentwurfs für Drahtlose Ad Hoc und Sensornetzwerke ist.
Conversion of natural vegetation into cattle pastures and croplands results in altered emissions of greenhouse gases (GHG), such as carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Their atmospheric concentration increase is attributed the main driver of climate change. Despite of successful private initiatives, e.g. the Soy Moratorium and the Cattle Agreement, Brazil was ranked the worldwide second largest emitter of GHG from land use change and forestry, and the third largest emitter from agriculture in 2012. N2O is the major GHG, in particular for the agricultural sector, as its natural emissions are strongly enhanced by human activities (e.g. fertilization and land use changes). Given denitrification the main process for N2O production and its sensitivity to external changes (e.g. precipitation events) makes Brazil particularly predestined for high soil-derived N2O fluxes.
In this study, we followed a bottom-up approach based on a country-wide literature research, own measurement campaigns, and modeling on the plot and regional scale, in order to quantify the scenario-specific development of GHG emissions from soils in the two Federal States Mato Grosso and Pará. In general, N2O fluxes from Brazilian soils were found to be low and not particularly dynamic. In addition to that, expected reactions to precipitation events stayed away. These findings emphasized elaborate model simulations in daily time steps too sophisticated for regional applications. Hence, an extrapolation approach was used to first estimate the influence of four different land use scenarios (alternative futures) on GHG emissions and then set up mitigation strategies for Southern Amazonia. The results suggested intensification of agricultural areas (mainly cattle pastures) and, consequently, avoided deforestation essential for GHG mitigation.
The outcomes of this study provide a very good basis for (a) further research on the understanding of underlying processes causing low N2O fluxes from Brazilian soils and (b) political attempts to avoid new deforestation and keep GHG emissions low.
The global problematic issue of the olive oil industry is in its generation of large amounts of olive mill wastewater (OMW). The direct discharge of OMW to the soil is very common which presents environmental problems for olive oil producing countries. Both, positive as well as negative effects on soil have been found in earlier studies. Therefore, the current study hypothesized that whether beneficial effects or negative effects dominate depends on the prevailing conditions before and after OMW discharge to soil. As such, a better understanding of the OMW-soil interaction mechanisms becomes essential for sustainable safe disposal of OMW on soil and sustainable soil quality.
A field experiment was carried out in an olive orchard in Palestine, over a period of 24 months, in which the OMW was applied to the soil as a single application of 14 L m-2 under four different environmental conditions: in winter (WI), spring (SP), and summer with and without irrigation (SUmoist and SUdry). The current study investigated the effects of seasonal conditions on the olive mill wastewater (OMW) soil interaction in the short-term and the long-term. The degree and persistence of soil salinization, acidification, accumulation of phenolic compounds and soil water repellency were investigated as a function of soil depth and time elapsed after the OMW application. Moreover, the OMW impacts on soil organic matter SOM quality and quantity, total organic carbon (SOC), water-extractable soil organic carbon (DOC), as well as specific ultraviolet absorbance analysis (SUVA254) were also investigated for each seasonal application in order to assess the degree of OMW-OM decomposition or accumulation in soil, and therefore, the persisting effects of OMW disposal to soil.
The results of the current study demonstrate that the degree and persistence of relevant effects due to OMW application on soil varied significantly between the different seasonal OMW applications both in the short-term and the long-term. The negative effects of the potentially hazardous OMW residuals in the soil were highly dependent on the dominant transport mechanisms and transformation mechanisms, triggered by the ambient soil moisture and temperature which either intensified or diminished negative effects of OMW in the soil during and after the application season. The negative effects of OMW disposal to the soil decreased by increasing the retention time of OMW in soil under conditions favoring biological activity. The moderate conditions of soil moisture and temperature allowed for a considerable amount of applied OMW to be biologically degraded, while the prolonged application time under dry conditions and high temperature resulted in a less degradable organic fraction of the OMW, causing the OMW constituents to accumulate and polymerize without being degraded. Further, the rainfall during winter season diminished negative effects of OMW in the soil; therefore, the risk of groundwater contamination by non-degraded constituents of OMW can be highly probable during the winter season.
While reading this sentence, you probably gave (more or less deliberately) instructions to approximately 100 to 200 muscles of your body. A sceptical face or a smile, your fingers scrolling through the text or holding a printed version of this work, holding your head, sitting, and much more.
All these processes take place almost automatically, so they seem to be no real achievement. In the age of digitalization it is a defined goal to transfer human (psychological and physiological) behavior to machines (robots). However, it turns out that it is indeed laborious to obtain human facial expression or walking from robots. To optimize this transfer, a deeper understanding of a muscle's operating principle is needed (and of course an understanding of the human brain, which will, however, not be part of this thesis).
A human skeletal muscle can be shortened willingly, but not lengthened, thereto it takes an antagonist. The muscle's change in length is dependent on the incoming stimulus from the central nervous system, the current length of the muscle itself, and certain muscle--specific quantities (parameters) such as the maximum force. Hence, a muscle can be mathematically described by a differential equation (or more exactly a coupled differential--algebraic system, DAE), whose structure will be revealed in the following chapters. The theory of differential equations is well-elaborated. A multitude of applicable methods exist that may not be known by muscle modelers. The purpose of this work is to link the methods from applied mathematics to the actual application in biomechanics.
The first part of this thesis addresses stability theory. Let us remember the prominent example from middle school physics, in which the resting position of a ball was obviously less susceptible towards shoves when lying in a bowl rather than balancing at the tip of a hill. Similarly, a dynamical (musculo-skeletal) system can attain equilibrium states that react differently towards perturbations.
We are going to compute and classify these equilibria.
In the second part, we investigate the influence of individual parameters on model equations or more exactly their solutions. This method is known as sensitivity analysis.
Take for example the system "car" containing a value for the quantity "pressure on the break pedal while approaching a traffic light". A minor deviation of this quantity upward or downward may lead to an uncomfortable, abrupt stop or even to a collision, instead of a smooth stop with a sufficient gap.
The considered muscle model contains over 20 parameters that, if changed slightly, have varying effects on the model equation solutions at different instants of time. We will investigate the sensitivity of those parameters regarding different sub--models, as well as the whole model among different dynamical boundary conditions.
The third and final part addresses the \textit{optimal control} problem (OCP).
The muscle turns a nerve impulse (input or control) into a length change and therefore a force response (output). This forward process is computable by solving the respective DAE. The reverse direction is more difficult to manage. As an everyday example, the OCP is present regarding self-parking cars, where a given path is targeted and the controls are the position of the
steering wheel as well as the gas pedal.
We present two methods of solving OCPs in muscle modeling: the first is a conjunction of variational calculus and optimization in function spaces, the second is a surrogate-based optimization.
Leaf litter breakdown is a fundamental process in aquatic ecosystems, being mainly mediated by decomposer-detritivore systems that are composed of microbial decomposers and leaf-shredding, detritivorous invertebrates. The ecological integrity of these systems can, however, be disturbed, amongst others, by chemical stressors. Fungicides might pose a particular risk as they can have negative effects on the involved microbial decomposers but may also affect shredders via both waterborne toxicity and their diet; the latter by toxic effects due to dietary exposure as a result of fungicides’ accumulation on leaf material and by negatively affecting fungal leaf decomposers, on which shredders’ nutrition heavily relies. The primary aim of this thesis was therefore to provide an in-depth assessment of the ecotoxicological implications of fungicides in a model decomposer-detritivore system using a tiered experimental approach to investigate (1) waterborne toxicity in a model shredder, i.e., Gammarus fossarum, (2) structural and functional implications in leaf-associated microbial communities, and (3) the relative importance of waterborne and diet-related effects for the model shredder.
Additionally, knowledge gaps were tackled that were related to potential differences in the ecotoxicological impact of inorganic (also authorized for organic farming in large parts of the world) and organic fungicides, the mixture toxicity of these substances, the field-relevance of their effects, and the appropriateness of current environmental risk assessment (ERA).
In the course of this thesis, major differences in the effects of inorganic and organic fungicides on the model decomposer-detritivore system were uncovered; e.g., the palatability of leaves for G. fossarum was increased by inorganic fungicides but deteriorated by organic substances. Furthermore, non-additive action of fungicides was observed, rendering mixture effects of these substances hardly predictable. While the relative importance of the waterborne and diet-related effect pathway for the model shredder seems to depend on the fungicide group and the exposure concentration, it was demonstrated that neither path must be ignored due to additive action. Finally, it was shown that effects can be expected at field-relevant fungicide levels and that current ERA may provide insufficient protection for decomposer-detritivore systems. To safeguard aquatic ecosystem functioning, this thesis thus recommends including leaf-associated microbial communities and long-term feeding studies using detritus feeders in ERA testing schemes, and identifies several knowledge gaps whose filling seems mandatory to develop further reasonable refinements for fungicide ERA.
Confidentiality, integrity, and availability are often listed as the three major requirements for achieving data security and are collectively referred to as the C-I-A triad. Confidentiality of data restricts the data access to authorized parties only, integrity means that the data can only be modified by authorized parties, and availability states that the data must always be accessible when requested. Although these requirements are relevant for any computer system, they are especially important in open and distributed networks. Such networks are able to store large amounts of data without having a single entity in control of ensuring the data's security. The Semantic Web applies to these characteristics as well as it aims at creating a global and decentralized network of machine-readable data. Ensuring the confidentiality, integrity, and availability of this data is therefore also important and must be achieved by corresponding security mechanisms. However, the current reference architecture of the Semantic Web does not define any particular security mechanism yet which implements these requirements. Instead, it only contains a rather abstract representation of security.
This thesis fills this gap by introducing three different security mechanisms for each of the identified security requirements confidentiality, integrity, and availability of Semantic Web data. The mechanisms are not restricted to the very basics of implementing each of the requirements and provide additional features as well. Confidentiality is usually achieved with data encryption. This thesis not only provides an approach for encrypting Semantic Web data, it also allows to search in the resulting ciphertext data without decrypting it first. Integrity of data is typically implemented with digital signatures. Instead of defining a single signature algorithm, this thesis defines a formal framework for signing arbitrary Semantic Web graphs which can be configured with various algorithms to achieve different features. Availability is generally supported by redundant data storage. This thesis expands the classical definition of availability to compliant availability which means that data must only be available as long as the access request complies with a set of predefined policies. This requirement is implemented with a modular and extensible policy language for regulating information flow control. This thesis presents each of these three security mechanisms in detail, evaluates them against a set of requirements, and compares them with the state of the art and related work.
This study had two main aims. The first one was to investigate the quality of lesson plans. Two important features of lesson plans were used as a basis to determine the quality of lesson plans. These are adaptability to preconditions and cognitive activation of students. The former refers to how the planning teacher considers the diversity of students pre-existing knowledge and skills. The latter refers to how the planning teacher sequences deep learning tasks and laboratory activities to promote the cognitive activation of students.
The second aim of the study was to explore teachers thinking about and explanation of externally generated feedback data on their students’ performance. The emphasis here was to understand how the teachers anticipate planning differentiated lessons to accommodate the variations in students learning outcomes revealed by the feedback data.
The study followed a qualitative approach with multiple sources of data. Concept maps, questionnaires, an online lesson planning tool, standardized tests, and semi-structured interviews were the main data collection instruments used in the study. Participants of this study were four physics teachers teaching different grade levels. For the purpose of generating feedback for the participant teachers, a test was administered to 215 students. Teachers were asked to plan five lessons for their ongoing practices. The analysis showed that the planned lessons were not adapted to the diversity in students pre-existing knowledge and skills. The analysis also indicated that the lessons planned had limitations with regard to cognitive activation of students. The analysis of the interview data also revealed that the participant teachers do not normally consider differentiating lessons to accommodate the differences in students learning, and place less emphasis on the cognitive activation of students. The analysis of the planned lessons showed a variation in teachers approach in integrating laboratory activities in the sequence of the lessons ranging from a complete absence through a demonstrative to an investigative approach. Moreover, the findings from the interviews indicated differences between the participant teachers espoused theory (i.e. what they said during interview) and their theory- in –use (i.e. what is evident from the planned lessons). The analysis of the interview data demonstrated that teachers did not interpret the data, identify learning needs, draw meaningful information from the data for adapting (or differentiating) instruction. They attributed their students’ poor performance to task difficulty, students’ ability, students’ motivation and interest. The teachers attempted to use the item level and subscale data only to compare the relative position of their class with the reference group. However, they did not read beyond the data, like identifying students learning needs and planning for differentiated instruction based on individual student’s performance.