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Cooperative Competitive Advantages of International Supply Networks
No full textInternational Supply Networks (ISN) will compete with each other increasingly in the future through Cooperative Competitive Advantage (CCA) on the network level as a result of the cooperative interplays on the individual level. Therewith, a multilevel consideration is needed for investigating the potential emerging characteristics on the network level and the effects of an ISN on the company success that can be summarised in the following two research questions: What are CCA and what are the causal relations between an ISN and the company success?
The theoretical relevance of these two research questions is the result of an identified gap of knowledge concerning definitions about CCA and a gap of knowledge about theoretical explanations in the meaning of cause-and-effect relations between ISN and the company success as well as assigning competitiveness to a whole ISN. With regard to the scientific modus operandi the Thesis comprises a complexity-based research model for hypothesizing the effects of the structural complexities on the network and the individual level, a Network Science-based Structural Equation Model with measurement models for the structural complexity, for CCA and for the company success and an empirical data set collected from secondary data containing over 55.000 supply relationships of the German automotive industry for the empirical validation. As a result of the computation with MATLAB, the falsifiable assumptions of the complexity-based research model cannot be completely statistically falsified but the directions of the causal relations are confirmed by trend so that first potential functional relations for the Strategic Complexity Management can be drawn.
Consequently, the research contributes to scientific insights to that effect that an explanation approach is developed able to draw conclusions concerning the two research questions. Future research will focus on a deepening and widening of theoretical, methodological and empirical aspects
Identification of regulatory proteins involved in the expression of levansucrase in Pseudomonas syringae
No full textPseudomonas syringae is a phytopathogenic γ-proteobacterium that induces a wide variety of diseases on various agronomically significant crops, as well as on an unknown number of wild plant species. Virulence of the bacterial blight pathogen of soybean, P. syringae pv. glycinea PG4180, is favored by cold and humid conditions. This bacterium can synthesize the exopolysaccharide levan when it encounters moderate to high concentrations of sucrose. Although the presence of multiple alleles for levansucrase gene in P. syringae PG4180 has been the focus of many previous studies, no regulators have been described for expression of levansucrase. In the first study, the genome of P. syringae PG4180 was screened for transcriptional activators and results revealed that the prophage-borne transcriptional regulator, LscR, mediates expression of levansucrase. A lscR-deficient mutant was generated and exhibited a levan-negative phenotype when grown on a sucrose-rich medium. Furthermore, genomic analysis of the region surrounding the lscR gene revealed that LscR resides on a ~25 kb fragment of a bacteriophage origin. To determine its nature and function, the prophage region was subjected to nucleotide sequencing followed by BLAST analysis. Results showed that this region does not encode for an active phage as it only possesses genes involved in phage tail morphogenesis. In the last section of this study, we investigated a potential repressor for the transcription of lsc. Potential binding sites for the hexose metabolism repressor, HexR, were found in the PAPE region upstream of both lsc genes. A hexR mutant of P. syringae PG4180 was generated and transcriptional analysis revealed a slight increase in the expression levels of lsc. Our data proposed that genes engaged in extra-cellular sugar acquisition are co-regulated with those involved in intra-cellular energy-providing metabolic pathways in P. syringae
Preparation and Characterization of Grafted Adsorbents and their Applications in Biomolecule Purification
No full textThis doctoral research focuses on the preparation and characterization of grafted adsorbents and their performance evaluation as chromatography adsorbents for the purification of biomolecules. Most downstream bioprocesses include several chromatographic steps amongst other traditional purification steps in order to produce highly purified bioproducts like plasmid DNA, virus-like particles, and monoclonal antibodies. Currently, there is an enormous demand for developing innovative and cost-effective bioprocessing techniques for reducing production costs, which mostly lie in downstream bioprocessing (up to 80% of the entire production cost). In recent years, fiber-based and cryogel-based adsorbents have been promoted as an additional alternative to conventional packed-bed resins. Cryogels are the product of cryogelation technology, having interconnected macropores in the range of 10--200 um. Due to the macroporous structures, efficient mass transfer and good flow through properties are expected. The macroporous nature and the different chemistry embedded within the cryogels plays a significant role in separating a broad range of therapeutic biomolecules. Even, fiber-based materials also show excellent physicochemical properties and offer several advantages, including large surface areas, high swelling capacities, mechanically robustness, and convenient usage.
Although the potentials for cryogel- and fiber-based are high, the lower binding capacity of these adsorbents compared to resin-based adsorbents has hampered their usage as a chromatography adsorbents. The primary objectives of my dissertation was to investigate how grafting initiation techniques influences the binding capacities of surface-modified adsorbents
Reliable taxonomic classification of metagenome fragments from varying marine bacterial communities
No full textThe introduction of next-generation sequencing technologies had impact on the whole field of microbial genomics. Where yesterday sequencing was an expensive technology and the analysis of a single bacterial genome required whole workgroups of scientists, nowadays PhD students struggle with the analyses of their own (meta-)genomes. Metagenomics describes the analysis of DNA obtained directly from environmental samples allowing to study communities of organisms by their genetic material circumventing the problem of isolation and cultivation. Taxonomic classification of metagenomic DNA fragments is one of the key challenges in the field of microbial ecology used for diversity analysis of whole microbial communities by associating a DNA fragment with a taxonomic position. Cross-linking biodiversity analysis, expression analysis and functional analysis enables scientists to answer the key questions in environmental microbiology: "Who is out there? How many of them? What are they doing?". Taxonomic classification of metagenomic sequences is a crucial step within this process, because it glues together the three methods. Various tools addressing taxonomic classification of DNA fragments emerged during the last decade, each having its advantages and disadvantages.
The aim of this thesis was to enhance taxonomic classification methods by combining multiple existing tools to achieve reliable description of the diversity of marine microbial communities. The design, implementation and application of the new technique to real-world data obtained in the frame of the two comprehensive marine studies, MIMAS and COGITO, was the main accomplishment of this work. Finally a pipeline for the taxonomic classification of metagenomic DNA fragments was constructed for the operation in a daily scientific workflow
Identification, molecular cloning and biophysical characterization of channel forming proteins in Caulobacter crescentus and Legionella pneumophila
No full textCaulobacter crescentus is well-known for its unique dimorphic life style. It is used as a model organism to study cell division and differentiation. A range of interesting features constitute its unique nature. It is normally found in dilute organic environments and was believed to be lacking any genes coding for porin like proteins. We found channel forming activity in the enriched cell wall extracts of the organism. The protein responsible for the porin like activity was found to be a member of the OmpW family. The protein formed small cation selective channels in artificial lipid bilayers. In order to confirm that the studied protein is responsible for the channel forming activity, an ompW knockout strain of C. crescentus was developed. Enriched outer membrane extracts from the mutant strain did not show channel forming activity.
We also identified and characterized a homologue of hVDAC-1 in Legionella pneumophila. L. pneumophila has genes coding for a range of eukaryotic like protein. We were especially interested in the gene lpg1974 which codes for Lpg1974, a protein which had reasonable similarity to hVDAC-1. The protein was found to produce large anion selective channels in artificial lipid bilayers. We also developed a homology structure for the protein which had remarkable similarity to hVDAC-1. Here we further studied the properties of the protein, by expressing the protein without its predicted N-terminal signal peptide (Lpg1974Δ1-21). There are a series of diverse reports about the importance of the N-terminal sequence. The truncated protein formed large anion selective channels. The voltage sensitivity of the protein was not affected by the signal peptide deletion
Towards the understanding of transcriptional regulation and characterization of levansucrase in Pseudomonas syringae
No full textPseudomonas syringae pv. glycinea PG4180 causes bacterial blight on soybean plants and enters the leaf tissue through stomata or open wounds, where it encounters a sucrose-rich milieu. Sucrose is utilized by invading bacteria via the secreted enzyme, levansucrase (Lsc), liberating glucose and forming polyfructan levan. During this study, it was found that lsc is under the control of the hexose metabolic repressor, HexR. The DNA binding sequence of this regulator was found upstream of lsc genes. During in vitro growth analysis using sucrose as sole carbon source and in planta growth, it was observed that the growth of the hexR mutant was impaired as compared to wild type. We could conclude that HexR acts as an in planta fitness factor and that the genes involved in extra-cellular sugar acquisition might be co-regulated with those involved in intra-cellular metabolic pathways in P. syringae.
Furthermore, an in-depth study using different lsc knock-out mutants was conducted to characterize them phenotypically and biochemically. It was observed that M6 (lscB/lscC mutant) had a significantly lower in planta survival as compared to the wild type or mutants M3 (lscB mutant) and M5 (lscC mutant). The biochemical characterization of mutant-derived levan polymers by HPLC-microTOF revealed that the levan polymerized by LscB/LscC on 5% sucrose had a higher fructose-to-glucose ratio as compared to levans polymerized by LscB or LscC, respectively, suggesting a concerted action of both enzymes. Additionally, levan polymerized by LscB/LscC produced on 5% sucrose accumulated a higher amount of fed antibiotics as compared to any of the levan polymers derived from LscB or LscC alone. We concluded that levansucrases are important for the survival and symptom development of PG4180 in in planta.
The thesis additionally dealt with method development for identification of protein translocation across the membrane for levansucrase
Dynamic modeling and simulation of biogas production based on anaerobic digestion of gelatine, sucrose and rapeseed oil
No full textSome aspects of the anaerobic digestion (AD) process still remain unclear, basically due to complexity of microbial and physicochemical reaction. Thus, there is a need for understanding of the AD mechanisms which can improve stability and enhance the process performance. The process stability and velocity are influenced by the chemical composition of the feedstock and the full supply of the microbial community with essential elements. Modeling and simulation represents an appropriate analytical tool for studying and improving the biogas process generation and reduces the expenditure of time and cost for the laboratory experiments. A variety of biogas models contains unknown parameters and complex structure which makes the parameterization step difficult and requires many assumptions. In order to overcome this problem, in this study, a relatively simple model was formulated in order to represent accurately the dynamics of AD by adjusting three master substrates (proteins, carbohydrates and lipids). The model was calibrated using three sets of experimental data in batch: mono-fermentations of gelatine, sucrose and rapeseed oil. The parameterized model accurately predicts the AD of the substrates mixture of gelatine, sucrose and rapeseed oil for the volume of biogas and methane, the volumetric flow rate of biogas, the volumetric concentration dynamics of methane and the total chemical oxygen. Furthermore, the model was cross-validated by experimental data where potato waste water (PWW) and starch were digested and tested for two ways of the substrates replacement in continuous laboratory-scale biogas fermenter. The model accurately predicts the dynamics of the CH4 concentration and the volume of biogas.The developed model was adopted for the tank cascade system with the biogas fermenter at the end with total capacity of 2500 m3. We managed to generate the annual prognosis for continuous long-term the AD process only by arrangement of three components
Optimization of the economic viability of the production and harvesting of microalgae by bioprocess engineering
No full textEven though microalgae show great potential for biomass production, industrial application has been limited in the past due to high production costs. Two major bottlenecks affecting cost effectiveness are the choice of a suitable production strain and the biomass harvest. Three manuscripts were published in the framework of the PhD Thesis, scientifically investigating new methods for strain selection and biomass harvest.
In “Isolation and Characterization of New Temperature Tolerant Microalgal Strains for Biomass Production”, 130 environmental samples were taken in Germany, Spain, Italy and Portugal, purified and strains with a high growth rate and thermos tolerance were identified. 21 of the isolated strains were able to grow at 40 °C with the highest growth rate of 1.16 per day and 13 of those were even growing at 45 °C with a maximum growth rate of 0.053 per day at 45 °C. Sequencing showed that the isolates were all chlorophytes belonging to four different families.
“Optimization of freshwater microalgal biomass harvest using polymeric flocculants” investigates 15 polyelectrolytes for their harvesting capability.
Cationic, anionic and non-ionic flocculants were analyzed at varying concentrations and incubation times. Three chlorophytes were tested to verify the influence of different sizes, morphologies and motilities. In a recycling experiment the impact of flocculant residues was monitored over eight weeks. Cationic flocculants were most effective with flocculant PK55H showing the highest efficiency at the lowest concentration. Anionic and non-ionic flocculants were ineffective.
“Effect of voltage and electrode material on electroflocculation of Scenedesmus acuminatus” tested six electrode materials for electroflocculation. Besides aluminum and iron electrodes, magnesium, copper, zinc and brass electrodes were tested and compared. The influence of 10, 20, 30 and 40 V was examined and evaluated.
Maximum flocculation efficiency was reached with magnesium
Object-based Image Analysis for Detection and Segmentation Tasks in Biomedical Imaging
No full textObject-based image analysis (OBIA) is a concept for analyzing images based on regions instead of pixels. OBIA allows to effectively incorporate features of regions as well as their contextual and hierarchical relations into the analysis process. While object-based image analysis is common in the field of geographic information science and remote sensing, it has rarely found its was into biomedical image analysis. This thesis explores the applicability and capabilities of OBIA for addressing image processing and analysis tasks on biomedical images, by approaching several relevant and challenging tasks from different imaging domains.
First a formalization as well as a powerful and flexible implementation of the OBIA concept is proposed. This is the foundation on which the applications are based. The addressed applications are: detection of the spine and vertebrae in CT images; detection of pregnancy in pigs on ultrasound images; reconstruction of vessels from histological whole slide sections of murine liver samples.
One of the major contributions of this thesis is the demonstration of the capability and applicability of OBIA to tackle biomedical image analysis problems. Together with the OBIA foundation, the presented solutions for three different applications reveal the strength of OBIA, but also some challenges. Furthermore, the developed algorithms also pose a valuable scientific contribution in their own right, with some of them even presenting world-novel algorithms that have already found their way into commercial application
Myocardium Segmentation and Motion Analysis from Time-varying Cardiac Magnetic Resonance Imaging
No full textMagnetic Resonance Imaging (MRI) is a reference method for noninvasive examination of the global and local cardiac function. Using the latest real-time MRI sequences, cardiac function can be monitored over multiple consecutive heart beats, enabling the study of cardiac cycle variability, for example, in patients with arrhythmia. An essential precondition for the analysis of cardiac functional is the segmentation of the heart muscle (myocardium).
To address this challenging task, a hierarchical object-based segmentation approach was devised, which combines bottom-up region grouping with a top-down optimization strategy. This principle takes steps towards bridging the semantic gap between low-level image features and high-level, complex and heterogeneous structures. The optimization process is based on a supervised classifier which rates candidate regions. In a gradient descent manner, the parameters guiding the region grouping are iteratively adapted to a-posteriori maximize the supervised classifier's output. The proposed algorithm represents the central part of a comprehensive, self-contained pipeline for automatic segmentation of the myocardium from functional real-time MRI.
Furthermore, tissue phase mapping (TPM) MRI offers the means to inspect local cardiac motion by acquiring the velocity of each individual myocardium voxel. This work proposes a semi-automatic probabilistic segmentation approach for TPM that combines contour displacement with particle tracing, also estimating the uncertainty of the segmentation result. An automatic quantification method was additionally developed to compute global myocardial torsion. Moreover, a 3D glyph-based visualization approach was presented which provides a global overview of the local myocardial velocities in their original 3D setting.
The algorithmic solutions were evaluated on clinical data from patients and healthy control subjects and integrated into prototypes which enable the use in clinical research