Refine
Year of publication
- 2013 (23) (remove)
Document Type
- Doctoral Thesis (10)
- Bachelor Thesis (4)
- Part of Periodical (4)
- Master's Thesis (2)
- Conference Proceedings (1)
- Diploma Thesis (1)
- Habilitation (1)
Language
- English (23) (remove)
Keywords
- Pflanzenschutzmittel (3)
- ABox (1)
- Abduktion <Logik> (1)
- Agrochemikalien (1)
- Bach (1)
- Boden (1)
- Bodenchemie (1)
- Bodenökologie (1)
- C++ (1)
- Calculus (1)
- Cations (1)
- Chironomus riparius (1)
- Computational Toxicology (1)
- Compute Shader (1)
- Computergraphik (1)
- Computervisualistik (1)
- Crayfish (1)
- Crayfish plague (1)
- Deduktion (1)
- Defi-Now! (1)
- Defibrillator (1)
- Differentia Scanning Calorimetry (1)
- Differential scanning calorimetry (1)
- E-KRHyper (1)
- E-KRHyper theorem prover (1)
- Edelkrebs (1)
- Emergenz (1)
- Endokrine Regulation (1)
- Englisch (1)
- Environmental Risk Assessment (1)
- Erste Hilfe (1)
- Fabric Simulation (1)
- First aid (1)
- Fledermäuse (1)
- Fluss (1)
- Fragebeantwortung (1)
- Gefrierpunktserniedrigung (1)
- Genetic diversity (1)
- Genetische Variabilität (1)
- Gewässer (1)
- Glasumwandlung (1)
- Glasübergang (1)
- Graphik (1)
- Hyaluronan (1)
- Hyaluronsäure (1)
- Hydratation (1)
- Hydration (1)
- Informatik (1)
- Integrated Model (1)
- Kation-Brücken (1)
- Kationen (1)
- Kognitive Linguistik (1)
- Konturfindung (1)
- Konzept (1)
- Krebspest (1)
- Landwirtschaft (1)
- Limology (1)
- Line Space (1)
- Linespace (1)
- Linked Data Modeling (1)
- Logischer Schluss (1)
- Magnetis (1)
- Methode (1)
- Mikroorganismus (1)
- Mixture Toxicity (1)
- N-Body Simulation (1)
- N-Körper Simulation (1)
- NMR-Spektroskopie (1)
- Non-freezing water (1)
- Nuclear Magnetic R (1)
- OWL (1)
- OpenGL (1)
- OpenGL Shading Language (1)
- Organische Bodensubstanz (1)
- Pestizid (1)
- Pestizide (1)
- Phylogeographie (1)
- Plasticization; Glass transition (1)
- Plastifizieren (1)
- Plastifizierung (1)
- Politik (1)
- Polysaccharide (1)
- Polysaccharides (1)
- Predictive Model (1)
- Programmierung (1)
- Prädikatenlogik (1)
- Präposition (1)
- RDF (1)
- Risikoabschätzung (1)
- Risikoanalyse (1)
- Risikomanagement (1)
- Schlussfolgern (1)
- Semantic Web (1)
- Simulation (1)
- Smartphone Applikation (1)
- Softwareergonomie (1)
- Steuerung (1)
- Stoffsimulation (1)
- Streams (1)
- Support System (1)
- Säugetiere (1)
- Süßwasserhaushalt (1)
- TBox (1)
- Text Analysis (1)
- Text Mining (1)
- Theorem prover (1)
- Theorembeweiser (1)
- Torf (1)
- Umweltchemikalie (1)
- Umwelttoxikologie (1)
- Umweltwissenschaften (1)
- Usability (1)
- Vocabulary Mapping (1)
- Wachstumsregler (1)
- Wirbellose (1)
- Wissensbasis (1)
- Zuckmücken (1)
- agent-based simulation (1)
- agriculture (1)
- aquatic ecotoxicology (1)
- automated theorem prover (1)
- bats (1)
- by-stander effect (1)
- cation bridges (1)
- cognitive linguistic approach (1)
- concept (1)
- ecological risk management (1)
- ecosystem functions (1)
- emergence (1)
- endocrine disrupting chemicals (1)
- endokrine Regulation (1)
- english prepositions (1)
- freshwater ecosystem (1)
- governance (1)
- invertebrates (1)
- knowledge base (1)
- landscape (1)
- life cycle test (1)
- mammals (1)
- microorganisms (1)
- minimum self-contained graphs (1)
- modelling (1)
- nicht gefrierbares Wasser (1)
- norm (1)
- peat (1)
- pesticide (1)
- pesticides (1)
- plant protection products (1)
- policy modelling (1)
- probabilistic (1)
- question answering (1)
- risk assessment (1)
- smartphone app (1)
- soil (1)
- soil organic matter (1)
- teaching (1)
- usability study (1)
- Ökosystem (1)
- Ökotoxologie (1)
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.
The following thesis analyses the functionality and programming capabilitiesrnof compute shaders. For this purpose, chapter 2 gives an introductionrnto compute shaders by showing how they work and how they can be programmed. In addition, the interaction of compute shaders and OpenGL 4.3 is shown through two introductory examples. Chapter 3 describes an NBodyrnsimulation that has been implemented in order to show the computational power of compute shaders and the use of shared memory. Then it is shown in chapter 4 how compute shaders can be used for physical simulationsrnand where problems may arise. In chapter 5 a specially conceived and implemented algorithm for detecting lines in images is described and then compared with the Hough transform. Lastly, a final conclusion is drawn in chapter 6.
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.
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.
Structure of soil organic matter (SOM) is a hot topic of discussion among scientific community for several decades. The mostly discussed models, among many, are polymer model and supramolecular model. While the former considers SOM as macromolecules consisting of amorphous and crystalline domains, the latter explains SOM as a physicochemical entity dominated by weak hydrophobic and H-bond interactions in the secondary level, which holds individual molecules of primary structure together. The weak forces in secondary level impart characteristic mobility of SOM. Very important consequence of this multidimensional formulation is that physicochemical structure plays a crucial role in most biogeochemical functions of SOM, apart from the chemical composition. Recently introduced concept of cation and water molecule mediated bridges between OM molecular segments (CaB and WaMB, respectively) evolved from physicochemical understanding of SOM structure. Even though several indirect evidences were produced for CaB and WaMB during last years, no clear-cut understanding of these processes has been achieved yet. Experimental difficulty due to overlapping effects of equally important CaB-governing parameters such a pH and competing cations raises huge challenge in investigating CaB-related influences. This thesis, therefore, aims to validate an experimental set-up for inducing CaB within OM structures and assessing it from various chemical and physicochemical aspects.
The method involved removal of omnipresent cations and adjustment of pH before cation addition. This helped to separate pH effects and cation effects. Based on results obtained on two different types of organic matter, it can be deduced that multivalent cations can cross-link SOM, given that functional group density of the SOM material is enough for the functional groups to be arranged in sufficient spatial proximity to each other. Physicochemical structural reorganisation during aging causes formation of more and/or stronger CaB and WaMB. As for inducing CaB directly after cation treatment, cationic size and valency were found determinant also for aging effect. A strongly cross-linked system in the beginning is less vulnerable to structural changes and undergoes aging with lower intensity, than an initially weakly cross-linked system. Responsible for the structural changes is, the inherent mobility of SOM within its physicochemical assemblage. Thus the information on structural requirement of CaB and its consequences on OM matrix rigidity will help to obtain insight into the physicochemical SOM structure. Additionally, organic matter quality (assessed by thermal analysis) and pore structure of SOM formed in a set of artificial soils showed that mineral materials are important for the chemical nature of SOM molecules, but not for the physical structure of organo-mineral associations, at least after several months of SOM development.
Furthermore, nanothermal analysis using atomic force microscopy (AFM-nTA) was implemented in soils for the first time to reveal nanoscale thermal properties and their spatial distribution in nano- and micrometer scales. This helped to identify physicochemical processes, such as disruption of WaMB, in low-organic soils, in which bulk methods fail due to their low sensitivity. Further, various types of materials constituting in soils were distinguished with high resolution by advanced application of the method, in combination with other AFM parameters. Attempts were done to identify various materials, with the usage of defined test materials. Above all, the method is potent to reveal microspatial heterogeneity on sample surfaces, which could help understanding process-relevant hotspots, for example.
This thesis thus contributes to the scientific understanding on physicochemical structural dynamics via cross-linking by cations and via nanoscale thermal properties. Direct investigation on CaB demonstrated here will potentially help making a big leap in knowledge about the interaction. The observed aging effects add well to the understanding of supramolecular consideration of SOM. By introducing nanothermal analysis to the field of soil science, it is made possible to face the problem of heterogeneity and spatial distribution of thermal characteristics. Another important achievement of AFM-nTA is that it can be used to detect physicochemical processes, which are of low intensity.
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.
We present the conceptual and technological foundations of a distributed natural language interface employing a graph-based parsing approach. The parsing model developed in this thesis generates a semantic representation of a natural language query in a 3-staged, transition-based process using probabilistic patterns. The semantic representation of a natural language query is modeled in terms of a graph, which represents entities as nodes connected by edges representing relations between entities. The presented system architecture provides the concept of a natural language interface that is both independent in terms of the included vocabularies for parsing the syntax and semantics of the input query, as well as the knowledge sources that are consulted for retrieving search results. This functionality is achieved by modularizing the system's components, addressing external data sources by flexible modules which can be modified at runtime. We evaluate the system's performance by testing the accuracy of the syntactic parser, the precision of the retrieved search results as well as the speed of the prototype.
Chemical plant protection is an essential element in integrated pest management and hence, in current crop production. The use of Plant Protection Products (PPPs) potentially involves ecological risk. This risk has to be characterised, assessed and managed.
For the coming years, an increasing need for agricultural products is expected. At the same time, preserving our natural resources and biodiversity per se is of equally fundamental importance. The relationship of our economic success and cultural progress to protecting the environment has been made plain in the Ecosystem Service concept. These distinct 'services' provide the foundation for defining ecological protection goals (Specific Protection Goals, SPGs) which can serve in the development of methods for ecological risk characterisation, assessment and management.
Ecological risk management (RM) of PPPs is a comprehensive process that includes different aspects and levels. RM is an implicit part of tiered risk assessment (RA) schemes and scenarios, yet RM also explicitly occurs as risk mitigation measures. At higher decision levels, RM takes further risks, besides ecological risk, into account (e.g., economic). Therefore, ecological risk characterisation can include RM (mitigation measures) and can be part of higher level RM decision-making in a broader Ecosystem Service context.
The aim of this thesis is to contribute to improved quantification of ecological risk as a basis for RA and RM. The initial general objective had been entitled as "… to estimate the spatial and temporal extent of exposure and effects…" and was found to be closely related to forthcoming SPGs with their defined 'Risk Dimension'.
An initial exploration of the regulatory framework of ecological RA and RM of PPPs and their use, carried out in the present thesis, emphasised the value of risk characterisation at landscape-scale. The landscape-scale provides the necessary and sufficient context, including abiotic and biotic processes, their interaction at different scales, as well as human activities. In particular, spatially (and temporally) explicit landscape-scale risk characterisation and RA can provide a direct basis for PPP-specific or generic RM. From the general need for tiered landscape-scale context in risk characterisation, specific requirements relevant to a landscape-scale model were developed in the present thesis, guided by the key objective of improved ecological risk quantification. In principle, for an adverse effect (Impact) to happen requires a sensitive species and life stage to co-occur with a significant exposure extent in space and time. Therefore, the quantification of the Probability of an Impact occurring is the basic requirement of the model. In a landscape-scale context, this means assessing the spatiotemporal distribution of species sensitivity and their potential exposure to the chemical.
The core functionality of the model should reflect the main problem structures in ecological risk characterisation, RA and RM, with particular relationship to SPGs, while being adaptable to specific RA problems. This resulted in the development of a modelling framework (Xplicit-Framework), realised in the present thesis. The Xplicit-Framework provides the core functionality for spatiotemporally explicit and probabilistic risk characterisation, together with interfaces to external models and services which are linked to the framework using specific adaptors (Associated-Models, e.g., exposure, eFate and effect models, or geodata services). From the Xplicit-Framework, and using Associated-Models, specific models are derived, adapted to RA problems (Xplicit-Models).
Xplicit-Models are capable of propagating variability (and uncertainty) of real-world agricultural and environmental conditions to exposure and effects using Monte Carlo methods and, hence, to introduce landscape-scale context to risk characterisation. Scale-dependencies play a key role in landscape-scale processes and were taken into account, e.g., in defining and sampling Probability Density Functions (PDFs). Likewise, evaluation of model outcome for risk characterisation is done at ecologically meaningful scales.
Xplicit-Models can be designed to explicitly address risk dimensions of SPGs. Their definition depends on the RA problem and tier. Thus, the Xplicit approach allows for stepwise introduction of landscape-scale context (factors and processes), e.g., starting at the definitions of current standard RA (lower-tier) levels by centring on a specific PPP use, while introducing real-world landscape factors driving risk. With its generic and modular design, the Xplicit-Framework can also be employed by taking an ecological entity-centric perspective. As the predictive power of landscape-scale risk characterisation increases, it is possible that Xplicit-Models become part of an explicit Ecosystem Services-oriented RM (e.g., cost/benefit level).
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.