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Agricultural pesticides, especially insecticides, are an integral part of modern farming. However, these may often leave their target ecosystems and cause adverse effects in non- target, especially freshwater ecosystems, leading to their deterioration. In this thesis, the focus will be on Insect Growth Regulators (IGRs) that can in many ways cause disruption of the endocrine system of invertebrates. Freshwater invertebrates play important ecological, economic and medical roles, and disruption of their endocrine systems may be crucial, considering the important role hormones play in the developmental and reproductive processes in organisms. Although Endocrine Disruption Chemicals (EDCs) can affect moulting, behaviour, morphology, sexual maturity, time to first brood, egg development time, brood size (fecundity), and sex determination in invertebrates, there is currently no agreement upon how to characterize and assess endocrine disruption (ED). Current traditional ecotoxicity tests for Ecological Risk Assessment (ERA) show limitations on generating data at the population level that may be relevant for the assessment of EDCs, which effects may be sublethal, latent and persist for several generations of species (transgenerational).
It is therefore the primary objective of this thesis to use a test method to investigate adverse effects of EDCs on endpoints concerning development and reproduction in freshwater invertebrates. The full life-cycle test over two generations that includes all sensitive life stages of C. riparius (a sexual reproductive organism) allows an assessment of its reproduction and should be suitable for the investigation of long-term toxicity of EDCs in freshwater invertebrates. C. riparius is appropriate for this purpose because of its short life cycle that enables the assessment of functional endpoints of the organism over several generations. Moreover, the chironomid life cycle consists of a complete metamorphosis controlled by a well-known endocrine mechanism and the endocrine system of insects has been most investigated in great detail among invertebrates. Hence, the full life-cycle test with C. riparius provides an approach to assess functional endpoints (e.g. reproduction, sex ratio) that are population-relevant as a useful amendment to the ERA of EDCs. In the laboratory, C. riparius was exposed to environmentally-relevant concentrations of the selected IGRs in either spiked water or spiked sediment scenario over two subsequent generations.
The results reported in this thesis revealed significant effects of the IGRs on the development and the reproduction of C. riparius with the second (F1) generation showing greater sensitivity. These findings indicated for the first time the suitability of multigenerational testing for various groups of EDCs and strongly suggested considering the full life-cycle of C. riparius as an appropriate test method for a better assessment of EDCs in the freshwater environment. In conclusion, this thesis helps to detect additional information that can be extrapolated at population level and, thus, might contribute to better protection of freshwater ecosystems against the risks of Endocrine Disrupting Chemicals (EDCs.) It may furthermore contribute to changes in the ERA process that are necessary for a real implementation of the new European chemical legislation, REACH (Registration, Evaluation Authorization and Restriction of Chemicals). Finally, significant interactions between temperature, chemical exposure and generation were reported for the first time and, may help predict impacts that may occur in the future, in the field, under predicted climate change scenarios.
Worldwide one third to one half of the freshwater crayfish species are threatened with population decline or extinction. Besides habitat deterioration, pollution, and other man-made environmental changes, invasive species and pathogens are major threats to the survival of European crayfish species. Freshwater crayfish are the largest freshwater invertebrates and strongly influence the structure of food webs. The disappearance of crayfish from a water body may change the food web and could have dramatic consequences for an ecosystem.rnOne goal in modern species conservation strategies is the conservation of genetic diversity, since genetic diversity is an advantage for the long-term survival of a species. The main aim of my thesis was to reveal the genetic structure and to identify genetic hotspots of the endangered noble crayfish (Astacus astacus) throughout Europe (part 1 of my thesis). Since the most significant threat to biodiversity of European crayfish species is the crayfish plague pathogen Aphanomyces astaci I studied new aspects in the distribution of A. astaci (part two of my thesis). The results serve as a basis for future conservation programs for freshwater crayfish. In the first part of my thesis I conducted a phylogeographic analysis of noble crayfish using mitochondrial DNA and nuclear microsatellite data. With these methods I aimed to identify its genetic hotspots and to reconstruct the recolonization history of central Europe by this species. I detected high genetic diversities in southestern Europe indicating that noble crayfish outlasted the cold climate phases during the Pleistocene in this region (Appendix 1). Because of the high genetic diversity found there, southeastern Europe is of particular importance for the conservation of noble crayfish. The mitochondrial DNA analysis points to a bifurcated colonization process from the eastern Black Sea basin to a) the North Sea and to b) the Baltic Sea basin (Appendix 2). A second independent refugium that was localized on the Western Balkans did not contribute to the colonization of central Europe. Furthermore, I found that the natural genetic structure is dissolved, probably due to the high human impact on the distribution of noble crayfish (e.g. artificial translocation). In the second part of this thesis using real-time PCR I identified calico crayfish (Orconectes immunis) as the fourth North American crayfish species to be carrier of the agent of the crayfish plague (Appendix 3). Furthermore I detected the crayfish plague pathogen in American spiny-cheek crayfish (Orconectes limosus) and native narrow-clawed crayfish (Astacus leptodactylus) in the lower Danube in Romania (Appendix 4). The distribution of infected spiny-cheek crayfish poses a threat to the native biodiversity in southeastern Europe and shows the high invasion potential of this crayfish species. Moreover, I found that even the native narrow-clawed crayfish in the Danube Delta, about 970 km downstream of the current invasion front of American crayfish, is a carrier of A. astaci (Appendix 5). This finding is of high importance, as the native species do not seem to suffer from the infection. In Appendix 6 I elucidate demonstrate that the absence of the crayfish plague agent is the most likely explanation for the coexistence of populations of European and American crayfish in central Europe. In my thesis I show that the common assumption that all North American crayfish are carrier of A. astaci and that all native crayfish species die when infected with A. astaci does not hold true. The studies presented in my thesis reveal new aspects that are crucial for native crayfish conservation: 1) The genetic diversity of noble crayfish is highest in southeastern Europe where noble crayfish outlasted the last glacial maximum in at least two different refugia. 2) Not all American crayfish populations are carrier of A. astaci and 3) not all Europen crayish populations die shortly after being infected with the crayfish plague pathogen.rnTo conserve native crayfish species and their (genetic) diversity in the long term, further introductions of American crayfish into European waters must be avoided. However, the introduction will only decrease if the commercial trade with non-indigenous crayfish species is prohibited.
This dissertation investigates the usage of theorem provers in automated question answering (QA). QA systems attempt to compute correct answers for questions phrased in a natural language. Commonly they utilize a multitude of methods from computational linguistics and knowledge representation to process the questions and to obtain the answers from extensive knowledge bases. These methods are often syntax-based, and they cannot derive implicit knowledge. Automated theorem provers (ATP) on the other hand can compute logical derivations with millions of inference steps. By integrating a prover into a QA system this reasoning strength could be harnessed to deduce new knowledge from the facts in the knowledge base and thereby improve the QA capabilities. This involves challenges in that the contrary approaches of QA and automated reasoning must be combined: QA methods normally aim for speed and robustness to obtain useful results even from incomplete of faulty data, whereas ATP systems employ logical calculi to derive unambiguous and rigorous proofs. The latter approach is difficult to reconcile with the quantity and the quality of the knowledge bases in QA. The dissertation describes modifications to ATP systems in order to overcome these obstacles. The central example is the theorem prover E-KRHyper which was developed by the author at the Universität Koblenz-Landau. As part of the research work for this dissertation E-KRHyper was embedded into a framework of components for natural language processing, information retrieval and knowledge representation, together forming the QA system LogAnswer.
Also presented are additional extensions to the prover implementation and the underlying calculi which go beyond enhancing the reasoning strength of QA systems by giving access to external knowledge sources like web services. These allow the prover to fill gaps in the knowledge during the derivation, or to use external ontologies in other ways, for example for abductive reasoning. While the modifications and extensions detailed in the dissertation are a direct result of adapting an ATP system to QA, some of them can be useful for automated reasoning in general. Evaluation results from experiments and competition participations demonstrate the effectiveness of the methods under discussion.
English prepositions take only a small proportion of the language but play a substantial role. Although prepositions are of course also frequently used in English textbooks for secondary school, students fail to incidentally acquire them and often show low achievements in using prepositions correctly. The strategy commonly employed by language instructors is teaching the multiple senses of prepositions by rote which fails to help the students to draw links between the different meanings in usage. New findings in Cognitive Linguistics (CL) suggest a different approach to teaching prepositions and thus might have a strong impact on the methodologies of foreign language teaching and learning on the aspects of meaningful learning. Based on the Theory of Domains (Langacker, 1987), the notions of image schemas (Johnson, 1987) as well as the Conceptual Metaphor Theory (Lakoff & Johnson, 1980), the present study developed a CL-inspired approach to teaching prepositions, which was compared to the traditional teaching method by an empirical study conducted in a German school setting. Referring to the participants from the higher track and the medium track, who are at different proficiency levels, the results indicate that the CL-inspired teaching approach improved students" performance significantly more than the traditional approach in all the cases for the higher track and in some cases for the medium track. Thus, these findings open up a new perspective of the CL-inspired meaningful learning approach on language teaching. In addition, the CL-inspired approach demonstrates the unification of the integrated model of text and picture comprehension (the ITPC model) in integrating the new knowledge with related prior knowledge in the cognitive structure. According to the learning procedure of the ITPC model, the image schema as visual image is first perceived through the sensory register, then is processed in the working memory by conceptual metaphor, and finally it is integrated with cognitive schemata in the long term memory. Moreover, deep-seated factors, such as transfer of mother tongue, the difficulty of teaching materials, and the influence of prior knowledge, have strong effects on the acquisition of English prepositions.
This habilitation thesis deals with the effects of toxicants on freshwater ecosystems and considers different toxicant classes (pesticides, organic toxicants, salinity) and biotic endpoints (taxonomic community structure, trait community structure, ecosystem functions).
The thesis comprises 12 peer-reviewed international publications on these topics. All of the related studies rely on mesocosm or field investigations, or the analysis of field biomonitoring or chemical monitoring data. Publications I and II are devoted to passive sampling of a neonicotinoid insecticide and polycyclic aromatic hydrocarbons (PAHs), respectively. They show that biofouling and a diffusion-limiting membrane can reduce the sampling rate of the pulsed insecticide exposure and that receiving phases of different thicknesses can be used to assess the kinetic regime during field deployment of passive samplers. Publications III to VI mainly focus on trait-based approaches to reveal toxicant effects on invertebrates in streams. An overview on the framework and several applications of a trait-based approach to detect effects of pesticides (SPEARpesticides index) are given in publication III. Publication IV describes the development of a trait database for South-East Australian stream invertebrates and its successful application in the adaptation of SPEARpesticides as well as the development of a salinity index. Moreover, a conceptual model for the future development of trait-based biomonitoring indices is proposed. Publication V reports a mesocom study on the effects of a neonicotinoid insecticide on field-realistic invertebrate communities. The insecticide had long-term effects on the invertebrate communities, which were only detected when grouping the taxa according to their life-history traits. A comprehensive field study employing different pesticide sampling methods including passive sampling and biomonitoring of the invertebrate and microbial communities is presented in publication VI. The study did not find pesticide-induced changes in the microbial communities, but detected adverse effects of current-use pesticides on the invertebrate communities using the trait-based SPEARpesticides index. This index is also applied in a meta-analysis on thresholds for the effects of pesticides on invertebrate communities in publication VII. It is shown that there is a similar dose-response relationship between SPEARpesticides and pesticide toxicity over different biogeographical regions and continents. In addition, the thresholds for effects of pesticides are lower than derived from most mesocosm studies and than considered in regulatory pesticide risk assessment. The publications VIII to X use statistical data analysis approaches to examine effects of toxicants in freshwater ecosystems. Using governmental monitoring data on 331 organic toxicants monitored monthly in 4 rivers over 11 years, publication VIII finds that organic toxicants frequently occurred in concentrations envisaging acute toxic effects on invertebrates and algae even in large rivers. Insecticides and herbicides were the chemical groups mainly contributing to the ecotoxicological risk. Publication IX introduces a novel statistical method based on a similarity index to estimate thresholds for the effects of toxicants or other stressors on ecological communities. The application of the method for deriving thresholds for salinity, heavy metals and pesticides in streams is presented in three case studies. Publication X tackles the question of interactive effects between different toxicants using data from a field study on stream invertebrates in 24 sites of South-East Australia. Both salinity and pesticides exhibited statistically significant effects on the invertebrate communities, but no interaction between the stressors was found. Moreover, salinity acted on a higher taxonomical level than pesticides suggesting evolutionary adaptation of stream invertebrates compared to pesticide stress. Publications XI and XII concentrate on the effects of toxicants on biodiversity, ecosystem functions and ecosystem services, with publication XI summarising different studies related to the ecological risk assessment for these endpoints. A field study on the effects of pesticides and salinity on the ecosystem functions of allochthonous organic matter decomposition, gross primary production and ecosystem respiration is presented in publication XII. Both pesticides and salinity reduced the breakdown of allochthonous organic matter, whereas no effects on the other ecosystem functions were detected. A chapter following these publications synoptically discusses all studies of this habilitation thesis and draws general conclusions. It is stressed that in order to advance the understanding of effects of toxicants on freshwater ecosystems more ecological realism is needed in ecotoxicological approaches and that the spatiotemporal extent of toxicant effects needs more scrutiny.
Large amounts of qualitative data make the utilization of computer-assisted methods for their analysis inevitable. In this thesis Text Mining as an interdisciplinary approach, as well as the methods established in the empirical social sciences for analyzing written utterances are introduced. On this basis a process of extracting concept networks from texts is outlined and the possibilities of utilitzing natural language processing methods within are highlighted. The core of this process is text processing, to whose execution software solutions supporting manual as well as automated work are necessary. The requirements to be met by these solutions, against the background of the initiating project GLODERS, which is devoted to investigating extortion racket systems as part of the global fiσnancial system, are presented, and their fulσlment by the two most preeminent candidates reviewed. The gap between theory and pratical application is closed by a prototypical application of the method to a data set of the research project utilizing the two given software solutions.
This thesis describes the implementation of a Path-planning algorithm for multi-axle vehicles using machine learning algorithms. For that purpose, a general overview over Genetic Algorithms is given and alternative machine learning algorithms are briefly explained. The software developed for this purpose is based on the EZSystem Simulation Software developed by the AG Echtzeitysteme at the University Koblenz-Landau and a path correction algorithm developed by Christian Schwarz, which is also detailed in this paper. This also includes a description of the vehicle used in these simulations. Genetic Algorithms as a solution for path-planning in complex scenarios are then evaluated based on the results of the developed simulation software and compared to alternative, non-machine learning solutions, which are also shortly presented.
Iterative Signing of RDF(S) Graphs, Named Graphs, and OWL Graphs: Formalization and Application
(2013)
When publishing graph data on the web such as vocabulariesrnusing RDF(S) or OWL, one has only limited means to verify the authenticity and integrity of the graph data. Today's approaches require a high signature overhead and do not allow for an iterative signing of graph data. This paper presents a formally defined framework for signing arbitrary graph data provided in RDF(S), Named Graphs, or OWL. Our framework supports signing graph data at different levels of granularity: minimum self-contained graphs (MSG), sets of MSGs, and entire graphs. It supports for an iterative signing of graph data, e. g., when different parties provide different parts of a common graph, and allows for signing multiple graphs. Both can be done with a constant, low overhead for the signature graph, even when iteratively signing graph data.
Studies on the toxicity of chemical mixtures find that components at levels below no-observed-effect concentrations (NOECs) may cause toxicity resulting from the combined effects of mixed chemicals. However, chemical risk assessment frequently focuses on individual chemical substances, although most living organisms are substantially exposed to chemical mixtures rather than single substances. The concepts of additive toxicity, concentration addition (CA), and independent action (IA) models are often applied to predict the mixture toxicity of similarly and dissimilarly acting chemicals, respectively. However, living organisms and the environment may be exposed to both types of chemicals at the same time and location. In addition, experimental acquisition of toxicity data for every conceivable mixture is unfeasible since the number of chemical combinations is extremely large. Therefore, an integrated model to predict mixture toxicity on the basis of single mixture components having various modes of toxic action (MoAs) needs to be developed. The objectives of the present study were to analyze the challenges in predicting mixture toxicity in the environment, and to develop integrated models that overcome the limitations of the existing prediction models for estimating the toxicity of non-interactive mixtures through computational models. For these goals, four sub-topics were generated in this study. Firstly, applicable domains and limitations of existing integrated models were analyzed and grouped into three kinds of categories in this study. There are current approaches used to assess mixture toxicity; however, there is a need for a new research concept to overcome challenges associated with such approaches, which recent studies have addressed. These approaches are discussed with particular emphasis on those studies involved in computational approaches to predict the toxicity of chemical mixtures based on the toxicological data of individual chemicals. Secondly, through a case study and a computational simulation, it was found that the Key Critical Component (KCC) and Composite Reciprocal (CR) methods (as described in the European Union (EU) draft technical guidance notes for calculating the Predicted No Effect Concentration (PNEC) and Derived No Effect Level (DNEL) of mixtures) could derive significantly different results. As the third and fourth sub-topics of this study, the following two integrated addition models were developed and successfully applied to overcome the inherent limitations of the CA and IA models, which could be theoretically used for either similarly or dissimilarly acting chemicals: i) a Partial Least Squares-Based Integrated Addition Model (PLS-IAM), and, ii) a Quantitative Structure-Activity Relationship-Based Two-Stage Prediction (QSAR-TSP) model. In this study, it was shown that the PLS-IAM might be useful to estimate mixture toxicity when the toxicity data of similar mixtures having the same compositions were available. In the case of the QSAR-TSP model, it showed the potential to overcome the critical limitation of the conventional TSP model, which requires knowledge of the MoAs for all chemicals. Therefore, this study presented good potential for the advanced integrated models (e.g., PLS-IAM and QSAR-TSP), while considering various non-interactive constituents that have different MoAs in order to increase the reliance of conventional models and simplify the procedure for risk assessment of mixtures.
This paper presents a method for the evolution of SHI ABoxes which is based on a compilation technique of the knowledge base. For this the ABox is regarded as an interpretation of the TBox which is close to a model. It is shown, that the ABox can be used for a semantically guided transformation resulting in an equisatisfiable knowledge base. We use the result of this transformation to effciently delete assertions from the ABox. Furthermore, insertion of assertions as well as repair of inconsistent ABoxes is addressed. For the computation of the necessary actions for deletion, insertion and repair, the E-KRHyper theorem prover is used.