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Geobio interactions in hydrothermal fluids from the Mid-Atlantic Ridge the role of organic ligands
No full textThis dissertation deals with the interaction between biological and hydrothermal processes in deep-sea hydrothermal environments, focusing on the topic of metal-organic complexation in hydrothermal fluids. Amino acids (AAs) could serve as ligands for metal complexation. In my first project, I found that most of the hydrothermal fluid samples contain significant amounts of AAs. This suggests that AAs are stable in solution under hydrothermal conditions. The presence of elevated AA concentrations in hydrothermal fluids implies that they are available as a nutrient source to vent organisms and as potential complexing agents for metals, possibly influencing their bioavailability and solubility. The second project was carried out to study the role of metal-organic complexation in detoxifying the hydrothermal vent environment characterised by high levels of heavy metals. Hydrothermal vent microbes were cultured to investigate the influence of increasing Cu concentrations on microorganisms and organic Cu-ligand formation. The result suggests that the cultured microbes can adapt to the supplemented range of Cu concentrations. The results of Cu-ligand analyses support the hypothesis that the microbes produce more Cu-binding ligands with increasing Cu stress, thus increasing Cu solubility and avoiding Cu uptake. These results point to a microbial influence on dissolved metal concentrations, speciation and mineral precipitation in the hydrothermal vent environment. The third project was carried out to study black smoker particulates precipitating from hot hydrothermal fluids upon mixing with seawater as an important feature of the hydrothermal habitat, influencing hydrothermal animals. Results indicate the dominance of sulphide minerals in all samples. However, pronounced differences were detected in the mineralogy of the particles between Logatchev and 5 S that could be attributed to differences in fluid chemistry
A multi-disciplinary approach to study the molecular basis of antibiotic translocation through bacterial porins
No full textBacterial resistance to antibiotics correlates with the reduced drug accumulation. Influx of antibiotics into the periplasm of gram-negative bacteria is facilitated by porins that form channels in the outer membrane. Some antibiotics take advantage of the charge distribution in non-specific porins to achieve binding and thereby facilitating their uptake in bacteria. We investigated the permeation pathways of antibiotics into bacteria by reconstitution of a single porin into an artificial lipid bilayer and measuring the binding of antibiotic molecules through the time-resolved interruption of a small ion current. We have been able to characterize facilitated translocation of several clinically relevant antibiotics through Enterobacter aerogenes, Escherichia coli and Providencia stuartii porins. Titration with effective antibiotics revealed concentration and voltage dependent ion current blockages and single channel analysis revealed binding kinetics and transport parameters. We have been able to characterize the effect of temperature on the antibiotic translocation through porin and show direct calculation of activation energy barriers of a relevant translocation at a single-molecular level. Results obtained from bilayer measurements can be successfully combined with molecular dynamics simulations that revealed microscopic and molecular details of the pathway. Microbiological assays have been used to study the rate of antibiotic action on live bacterial cells that correlates with the results obtained from conductance measurements. Miniaturized bilayer system was introduced to achieve high-resolution single channel recordings for the rapid screening of the antibiotics. We obtained molecular details of the antibiotic permeation through channels by combining different techniques in a proper way and the information can be used for antibacterial drug design with enhanced permeation properties
Object-Oriented or Object-Relational? An Experience Report from a High-Complexity, Long-Term Case Study
No full textThe discussion between object-oriented and object-relational DBMS technology seems to be decided since some time, in favor of the second candidate. We unroll this question based on our experience with the design and implementation of the array DBMS rasdaman which offers storage and query language retrieval on large, multi-dimensional arrays such as 2-D remote sensing imagery and 4-D atmospheric simulation results. This information category is sufficiently far from both relational tuples and object-oriented pointer networks to achieve a "fair" comparison where no approach has an immediate advantage.
The rasdaman system is implemented in a strictly object-oriented manner. We discuss rasdaman on model, interface, and implementation level and contrast our experience with concepts and concrete systems of object-relational technology. To underpin and justify rasdaman design decisions we also present rasdaman performance results. The rasdaman system is in operational use and available in open source, so our results can easily be reproduced
Investigation of ice formation and water mass modification in eastern Laptev Sea polynyas by means of satellites and models
No full textSalt expelled during the formation of ice in polynyas leads to a downward precipitation of brine that causes thermohaline convection and erodes the density stratification of the water column. In this thesis we investigate by means of flux models and satellite data the ability of the Western New Siberian (WNS) flaw polynya to modify the stratification of the water column and to form saline bottom water. The accuracy of existent microwave satellite-based polynya monitoring methods is assessed by a comparison of derived estimates with airborne electromagnetic ice thicknessmeasurements and aerial photographs taken across the polynya. The crossvalidation indicates that in the narrow flaw polynyas of the Laptev Sea the coarse resolution of commonly used microwave channel combinations provokes errors through mixed signals at the fast and pack ice edges. Likewise, the accuracy of flux models is tested by comparing model results to ice thickness and ice production estimates derived from high-resolution thermal infrared satellite observations. We find that if a realistic fast ice boundary and parameterization of the collection depth H is used and if themovement of the pack ice edge is prescribed correctly, the model is an appropriate tool for studying polynya dynamics and estimating associated fluxes. Hence, a flux model is used to examine the effect of ice production on the stratification of the water column. The ability of the polynya to formdense shelf bottomwater is investigated by adding the brine released during an exceptionally strongWNS polynya event in 2004 to the average winter density stratification of the water body. Owing to the strong density stratification and the apparent lack of extreme polynya events in the eastern Laptev Sea, we find the likelihood of convective mixing down to the bottom to be extremely low. We conclude that the recently observed breakdown of the stratification during polynya events is therefore predominantly related to wind- and tidally-driven turbulent mixing
On quantifying multisensory interaction effects in the vicinity of detection thresholds
No full textResponses to multiple stimuli from different modalities tend to be faster compared to responses to each of these stimuli alone. In Study 1 we report two visuo-tactile experiments investigating the relation between stimulus duration and the relative amount of response enhancement. Results suggest that the amount of reaction time (RT) facilitation was largest for the shortest stimulus duration and decreases with increasing stimulus duration, replicating the so-called principle of inverse effectiveness (Stein & Meredith, 1993). In Study 2 we present two novel methods for the quantification of multisensory interaction effects in the vicinity of detection thresholds. Both approaches quantify overall performance from RT and detection rates (DR) and provide converging evidence. One measure, inverse efficiency scores (IES), is based on an arithmetical combination of RT and DR, and the other utilizes sequential sampling models. Statistical properties of both measures are investigated via bootstrapping procedures. In Study 3 we report an audio-visual detection experiment investigating the influence of different experimental instructions (respond to any stimulus vs. respond only to visual stimuli) and the presented modalities (visual and audio-visual stimuli vs. visual, audio-visual, and auditory stimuli) on overall performance and the amount of multisensory interaction. Results suggest that both the experimental instructions and the presented modalities influence overall performance in terms of IFE. In Study 4 we investigated the influence of censored RT distributions on the diagnosticity of the race model inequality test (Miller, 1982). It is shown that inferences from this inequality test may become invalid when the experimenter misses a proportion of the responses by limiting the recording interval (right-censoring) or excludes outliers from analysis (left- and/or right-censoring). A correction of the inequality test for right-censored RT distributions is proposed
Cluster Analysis for Large, High-Dimensional Datasets: Methodology and Applications
No full textCluster analysis represents one of the most versatile methods in statistical science. It is employed in empirical sciences for the summarization of datasets into groups of similar objects, with the purpose of facilitating the interpretation and further analysis of the data. Cluster analysis is of particular importance in the exploratory investigation of data of high complexity, such as that derived from molecular biology or image databases. Consequently, recent work in the field of cluster analysis has focused on designing algorithms that can provide meaningful solutions for data with high cardinality and/or dimensionality, under the natural restriction of limited resources. The present thesis aims to develop improved methods for the clustering of high-dimensional datasets, as well as further applications of such algorithms in practical settings.
In the first part of the thesis, a more detailed review of the representative clustering algorithms focused on the analysis of very large or high-dimensional datasets is provided. Subsequently, a newly developed method for this purpose is described and evaluated. The developed algorithm is based on the principles of projection pursuit and grid partitioning, and focuses on reducing computational requirements for large datasets without loss of performance. In the second part of the thesis, a novel method for generating synthetic datasets with variable structure and clustering difficulty, that is aimed at evaluating clustering algorithms is presented. In the third part of the thesis, the applications of cluster analysis to the field of automatic image classification are investigated. A novel system for the semi-supervised annotation of images is described and evaluated. The system is based on a vocabulary of clusters of visual features extracted from images with known classification
Change Management on Semi-Structured Documents
No full textAn overwhelming amount of documents is produced and changed every day in most areas of our everyday life, such as, for instance, business, education, research or administration. The documents are seldom isolated artifacts but are related to other documents. Therefore changing one document possibly requires adaptations to other documents. Although dedicated tools may provide some assistance when changing documents, they often ignore other documents or documents of a different type. To resolve that discontinuity, we present a framework that embraces existing document types and supports the declarative specification of semantic annotation and propagation rules inside and across documents of different types, and on which basis we define semantic annotation and change impact analysis for heterogeneous collections of documents. The framework is implemented in the tool locutor, an extension to the well-known Subversion client, which can be used to semantically annotate collections of documents and to analyze the impacts of changes made in different documents of a collection
Time-frequency localized functions and operators in Gabor analysis
No full textAnalyzing a signal in regard to its time-varying frequency content is a classical method in science. Recently this method has grown into a rich mathematical theory within applied harmonic analysis, with applications ranging from radio and mobile communications to medical image processing and geophysics. This thesis addresses the following three fundamental, but not yet fully understood questions. The first one is the construction of Gabor frames with smooth and compactlysupported window functions defined on the Euclidean plane for separable lattices. In addition, we review the crucial applications of the theory of operator algebra representations for proving the general statement of the density theorem for Gabor frames. Second, we study identification of incompletely known linear operators based on the observation of restricted input and output signals. We develop a general setup for identification of general classes of time-frequency localizing operators based on a discretization method. The third question is the uncertainty principle for the joint time-frequency representation of functions on finite Abelian groups. Algebraic properties of such groups lead to results relating the support sizes of functions and their short-time Fourier transforms, with applications in the construction of a class of equal norm tight Gabor frames that are maximally robust to erasures, and consequences in the theory of recovering and storing signals with sparse time-frequency representations
Methane fluxes and associated biogeochemical processes in cold seep ecosystems
No full textMethane is an important greenhouse gas and in the oceans cold seeps such as mud volcanoes or pockmarks are important methane emission sites. By using the chemical energy of hydrocarbons rising up with mud, gas or fluids from the deep subsurface, diverse seep communities with high biomasses develop at these structures. Therefore, cold seeps are fascinating hot-spot ecosystems as they link the deep geosphere with the biosphere at the seafloor surface.
During this PhD study, methane efflux and consumption as well as related processes such as sulfate reduction and oxygen consumption were investigated at four different deep-sea by focusing on in situ quantification. The results showed that cold seeps are spatially heterogeneous ecosystems controlled by variations of fluid flow intensity influencing benthic biogeochemical processes. The highest fluid flow velocities are found at the central outflow of mud volcanoes in combination with high methane emission but low consumption rates. Outside of these main emission sites, chemosynthetic organisms such as mat-forming thiotrophic bacteria or siboglinid tubeworms are abundant. Here, medium to low fluid flow velocities with high methane oxidation rates were measured. Within one seep ecosystem there are spatial variations in methane emission and consumption, and the benthic biological methane filter of the different seep habitats removes a significant fraction of the total methane flow (up to 90%). For the methane budgets of geostructures and ocean basins, diffusive methane effluxes were previously not considered. However, based on the data of this PhD study, diffusive methane discharge significantly contributes to the total methane emission. Considering the diffusive methane release of the investigated deep-sea mud volcanoes, only mud volcanoes would release up to 15 ×10 12 g methane per year to the water column, which is a significant fraction of the total annual methane flux from the ocean to the atmosphere
School-To-Work Transitions of Second Generation Migrants in West Germany and the Netherlands
No full textThe thesis deals with the question whether children of labour migrants in West Germany and the Netherlands who have been born in the receiving countries―2.gen. migrants―ended up in worse first jobs than natives with similar background characteristics. It describes immigration histories and national institutional arrangements that shape labour market entrances of 2.gen. migrants in the countries, who both have large groups of Turkish migrants, similar vocational training systems and labour market structures. In addition to school and firm-based apprenticeships, the Dutch vocational training system offers exclusively school-based vocational training. The question was whether firm- and school-based apprenticeships bridge labour market entrances in both countries. The thesis presents the theoretical mechanisms that shape labour market entrances of specific ethnic groups in a framework of ‘composition’ and ‘distribution’ factors. Based on SOEP and Dutch register data different event history analyses techniques were used to analyse timing and quality of entrances jointly and with regard to first full-/part-time, temporary, permanent and low/high occupational status jobs. Two ethnic groups could be distinguished (DE: Turkish vs. Italian/Spanish/Greek; NL: Turkish/Moroccan vs. Arubean/Surinamese/Netherlands Antillean). Disadvantages of Turkish 2.gen. migrants in Germany were due to their worse written language proficiency, while they persisted for Turkish and Moroccan 2.gen. migrants in the Netherlands. German apprenticeships significantly facilitated labour market entrances, while this did not apply to firm and school-based vocational training in the Netherlands. One main conclusion is that policy measures targeted at the human capital composition are not sufficient, but that additional measures supporting job search and hiring processes are necessary to improve school-to-work transitions of 2.gen. migrants in Germany and the Netherlands