Die Innenraumpositionierung kommt in der heutigen Zeit immer mehr Aufmerksamkeit zu teil. Neben der Navigation durch das Gebäude sind vor allem Location Based Services von Bedeutung, welche Zusatzinformationen zu spezifischen Objekten zur Verfügung stellen Da für eine Innenraumortung das GPS Signal jedoch zu schwach ist, müssen andere Techniken zur Lokalisierung gefunden werden. Neben der häufig verwendeten Positionierung durch Auswertung von empfangenen Funkwellen existieren Methoden zur optischen Lokalisierung mittels Landmarken. Das kamerabasierte Verfahren bietet den Vorteil, dass eine oft zentimetergenaue Positionierung möglich ist. In dieser Masterarbeit erfolgt die Bestimmung der Position im Gebäude mittels Detektion von ArUco-Markern und Türschildern aus Bilddaten. Als Evaluationsgeräte sind zum einen die Kinect v2 von Microsoft, als auch das Lenovo Phab 2 Pro Smartphone verwendet worden. Neben den Bilddaten stellen diese auch mittels Time of Flight Sensoren generierte Tiefendaten zur Verfügung. Durch den Vergleich von aus dem Bild extrahierten Eckpunkten der Landmarke, mit den aus einer Datenbank entnommenen realen geometrischen Maßen des Objektes, kann die Entfernung zu einer gefundenen Landmarke bestimmt werden. Neben der optischen Distanzermittlung wird die Position zusätzlich anhand der Tiefendaten ermittelt. Abschließend werden beiden Verfahren miteinander verglichen und eine Aussage bezüglich der Genauigkeit und Zuverlässigkeit des in dieser Arbeit entwickelten Algorithmus getroffen. / Indoor Positioning is receiving more and more attention nowadays. Beside the navigation through a building, Location Bases Services offer the possibility to get more information about certain objects in the enviroment. Because GPS signals are too weak to penetrate buildings, other techniques for localization must be found. Beneath the commonly used positioning via the evaluation of received radio signals, optical methods for localization with the help of landmarks can be used. These camera-based procedures have the advantage, that an inch-perfect positioning is possible. In this master thesis, the determination of the position in a building is chieved through the detection of ArUco-Marker and door signs in images gathered by a camera. The evaluation is done with the Microsoft Kinect v2 and the Lenovo Phab 2 Pro Smartphone. They offer depth data gained by a time of flight sensor beside the color images. The range to a detected landmark is calculated by comparing the object´s corners in the image with the real metrics, extracted from a database. Additionally, the distance is determined by the evaluation of the depth data. Finally, both procedures are compared with each other and a statement about the accuracy and responsibility is made.

No description available.

A subgroup of non-small cell lung cancer (NSCLC) cases harbour mutations in classical oncogenes, which can affect therapy response and prognosis. By therapeutically targeting the corresponding proteins with inhibitory drugs, the clinical outcome for these lung cancer patients may be improved. One of these oncogenes is the phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA) which encodes the catalytic subunit of the phosphatidylinositol 3 kinase (PI3K). PIK3CA is a central regulator in the PI3K/Akt/mTOR pathway, which controls cell growth and apoptosis. Mutations in the PIK3CA gene are considered to up-regulate the kinase activity in tumour cells and through that dysregulate fundamental cellular processes. PI3K inhibitors are currently tested in clinical trials and present a promising therapy option in lung cancer patients. In this study, a pyrosequencing assay for detection of PIK3CA mutations in tumours from patients with NSCLC was established. The three "hot-spot" codons 542, 545 and 1047 of the PIK3CA gene were analysed. The sensitivity of this assay was determined to the presence of 5 % of mutant alleles. In agreement with previous reports, three of the 60 lung cancer cases revealed PIK3CA mutations (5 %). All mutations occurred in exon 9 codon 542 or 545. In line with previous reports, two of the three samples harboured concurrent mutation in the EGFR or KRAS gene. The established pyrosequencing analysis for PI3KCA mutations provides a reliable and cost-effective assay for clinical diagnostics. The determination of the PI3KCA mutation status may help to distinguish patients for treatment targeting the PI3K pathway.

The aim of this thesis is to examine the current Dutch modal particles and ascertain if this word class is fully translatable into Czech and Slovak language. The first, theoretical part of this thesis focuses primarily on the Dutch modal particles as such; explains what is modality, classifies particles as a word class, describes the characteristics of modal particles, which specific words are considered as modal particles, what kinds of modal particles exist in the Dutch language and what are their attributes both from a pragmatic and syntactic perspective. The theoretical part explains in detail the ways in which modality is expressed in Czech and Slovak, what kinds of particles in these two languages exist, and if there exist modal particles, which words are considered as these. In the conclusion of the theoretical part of the thesis is summarized what do have these three languages in common in this area, whether by the term modal particles is understood the same word class in each of these languages and whether it appears that the Dutch modal particles do have in Czech and Slovak their exact equivalents and are therefore fully translatable into these two languages. This claim will be verified in the practical part of the thesis. In the second, practical part of the thesis are the Dutch modal...

In den vergangenen Jahren etablierte sich der Marker „internal transcribed spacer 2" (ITS2) zu einem häufig genutzten Werkzeug in der molekularen Phylogenetik der Eukaryoten. Seine schnell evolvierende Sequenz eignet sich bestens für den Einsatz in niedrigeren phylogenetischen Ebenen. Die ITS2 faltet jedoch auch in eine sehr konservierte Sekundärstruktur. Diese ermöglicht die Unterscheidung weit entfernter Arten. Eine Kombination aus beiden in einer Sequenzstrukturanalyse verbessert die Auflösung des Markers und ermöglicht die Rekonstruktion von robusteren Bäumen auf höherer taxonomischer Breite. Jedoch war die Durchführung solch einer Analyse, die die Nutzung unterschiedlichster Programme und Datenbanken vorraussetzte, für den klassischen Biologen nicht einfach durchführbar. Um diese Hürde zu umgehen, habe ich den „ITS2 Workbench“ entwickelt, eine im Internet nutzbare Arbeitsplattform zur automatisierten sequenzstrukturbasierten phylogenetischen Analyse basierend auf der ITS2 (http://its2.bioapps.biozentrum.uni-wuerzburg.de). Die Entwicklung begann mit der Längenoptimierung unterschiedlicher „Hidden Markov Model“ (HMM)-Topologien, die erfolgreich auf ein Modell zur Sequenzstrukturvorhersage der ITS2 angewandt wurden. Hierbei wird durch die Analyse von Sequenzbestandteilen in Kombination mit der Längenverteilung verschiedener Helixregionen die Struktur vorhergesagt. Anschließend konnte ich HMMs auch bei der Sequenzstrukturgenerierung einsetzen um die ITS2 innerhalb einer gegebenen Sequenz zu lokalisieren. Dieses neu implementierte Verfahren verdoppelte die Anzahl vorhergesagter Strukturen und verkürzte die Laufzeit auf wenige Tage. Zusammen mit weiteren Optimierungen des Homologiemodellierungsprozesses kann ich nun erschöpfend Sekundärstrukturen in mehreren Interationen vorhersagen. Diese Optimierungen liefern derzeit 380.000 annotierte Sequenzen einschließlich 288.000 Strukturvorhersagen. Um diese Strukturen für die Berechnung von Alignments und phylogenetischen Bäumen zu verwenden hab ich das R-Paket „treeforge“ entwickelt. Es ermöglicht die Generierung von Sequenzstrukturalignments auf bis zu vier unterschiedlich kodierten Alphabeten. Damit können erstmals auch strukturelle Basenpaarungen in die Alignmentberechnung mit einbezogen werden, die eine Schätzung neuer Scorematrizen vorraussetzten. Das R-Paket ermöglicht zusätzlich die Rekonstruktion von „Maximum Parsimony“, „Maximum Likelihood“ und „Neighbour Joining“ Bäumen auf allen vier Alphabeten mittels weniger Zeilen Programmcode. Das Paket wurde eingesetzt, um die noch umstrittene Phylogenie der „chlorophyceae“ zu rekonstruieren und könnte in zukünftigen Versionen des ITS2 workbench verwendet werden. Die ITS2 Plattform basiert auf einer modernen und sehr umfangreichen Web 2.0 Oberfläche und beinhaltet neuste AJAX und Web-Service Technologien. Sie umfasst die HMM basierte Sequenzannotation, Strukturvorhersage durch Energieminimierung bzw. Homologiemodellierung, Alignmentberechnung und Baumrekonstruktion basierend auf einem flexiblen Datenpool, der Änderungen am Datensatz automatisch aktualisiert. Zusätzlich wird eine Detektion von Sequenzmotiven ermöglicht, die zur Kontrolle von Annotation und Strukturvorhersage dienen kann. Eine BLAST basierte Suche auf Sequenz- und Strukturebene bietet zusätzlich eine Vereinfachung des Taxonsamplings. Alle Funktionen sowie die Nutzung der ITS2 Webseite sind in einer kurzen Videoanleitung dargestellt. Die Plattform lässt jedoch nur eine bestimmte Größe von Datensätzen zu. Dies liegt vor allem an der erheblichen Rechenleistung, die bei diesen Berechnungen benötigt wird. Um die Funktion dieses Verfahrens auch auf großen Datenmengen zu demonstrieren, wurde eine voll automatisierte Rekonstruktion des Grünalgenbaumes (Chlorophyta) durchgeführt. Diese erfolgreiche, auf dem ITS2 Marker basierende Studie spricht für die Sequenz-Strukturanalyse auf weiteren Daten in der Phylogenetik. Hier bietet der ITS2 Workbench den idealen Ausgangspunkt. / During the past years, the internal transcribed spacer 2 (ITS2) was established as a commonly used molecular phylogenetic marker for the eukaryotes. Its fast evolving sequence is predestinated for the use in low-level phylogenetics. However, the ITS2 also consists of a very conserved secondary structure. This enables the discrimination between more distantly related species. The combination of both in a sequence-structure based analysis increases the resolution of the marker and enables even more robust tree reconstructions on a broader taxonomic range. But, performing such an analysis required the application of different programs and databases making the use of the ITS2 non trivial for the typical biologist. To overcome this hindrance, I have developed the ITS2 Workbench, a completely web-based tool for automated phylogenetic sequence-structure analyses using the ITS2 (http://its2.bioapps.biozentrum.uni-wuerzburg.de). The development started with an optimization of length modelling topologies for Hidden Markov Models (HMMs), which were successfully applied on a secondary structure prediction model of the ITS2 marker. Here, structure is predicted by considering the sequences' composition in combination with the length distribution of different helical regions. Next, I integrated HMMs into the sequence-structure generation process for the delineation of the ITS2 within a given sequence. This re-implemented pipeline could more than double the number of structure predictions and reduce the runtime to a few days. Together with further optimizations of the homology modelling process I can now exhaustively predict secondary structures in several iterations. These modifications currently provide 380,000 annotated sequences including 288,000 structure predictions. To include these structures in the calculation of alignments and phylogenetic trees, I developed the R-package "treeforge". It generates sequence-structure alignments on up to four different coding alphabets. For the first time also structural bonds were considered in alignments, which required the estimation of new scoring matrices. Now, the reconstruction of Maximum Parsimony, Maximum Likelihood as well as Neighbour Joining trees on all four alphabets requires just a few lines of code. The package was used to resolve the controversial chlorophyceaen dataset and could be integrated into future versions of the ITS2 workbench. The platform is based on a modern, feature-rich Web 2.0 user interface equipped with the latest AJAX and Web-service technologies. It performs HMM-based sequence annotation, structure prediction by energy minimization or homology modelling, alignment calculation and tree reconstruction on a flexible data pool that repeats calculations according to data changes. Further, it provides sequence motif detection to control annotation and structure prediction and a sequence-structure based BLAST search, which facilitates the taxon sampling process. All features and the usage of the ITS2 workbench are explained in a video tutorial. However, the workbench bears some limitations regarding the size of datasets. This is caused mainly due to the immense computational power needed for such extensive calculations. To demonstrate the validity of the approach also for large-scale analyses, a fully automated reconstruction of the Chlorophyta (Green Algal) Tree of Life was performed. The successful application of the marker even on large datasets underlines the capabilities of ITS2 sequence-structure analysis and suggests its utilization on further datasets. The ITS2 workbench provides an excellent starting point for such endeavours.

Pea populations derived from ten crosses were scored by coupling phase linked sequence characterized amplified region (SCAR) markers A001 and A002, and repulsion phase linked SCAR marker A004 for lodging resistance during the F2 generation. The objective of this project was to test the efficiency of implementation of these three SCAR markers in marker-assisted selection (MAS) for lodging resistance in pea breeding. Chi-square tests showed that A001 and A004 followed a two independent gene segregation model in all of the eight populations that segregated for these two markers. In the F3 field trial, the differences between mean lodging score of A001 (DNA band present) and a001 (DNA band absent) classes varied from -0.5 to -0.9 with an average of -0.6, based on a 1 to 9 lodging scale, across the eight populations surveyed. The differences between mean lodging score of a004 (DNA band absent) and A004 (DNA band present) classes varied from -0.4 to -1.1 with an average of -0.7, across the eight populations surveyed. In comparison, when the combination of two markers (A001; a004 vs. a001; A004) was used, lodging score differences varied from -0.7 to -1.5, with an average of -1.0 across the eight populations. T-test results showed that significant differences (P<0.05) in lodging score were observed between A001 and a001 classes in seven out of eight populations, and between A004 and a004 classes in six out of eight populations. Further T-tests showed that significant lodging differences were observed among the four classes of the A001 and A004 marker combination in seven out of eight populations assessed, including differences at P<0.01 level in six populations. The greater differences among marker combination classes than between individual marker classes showed that combining two markers was more effective than use of each marker alone in MAS. The marker combination explained (R2) 19-57% of lodging and 4-43% of plant height variation in the eight populations surveyed. The high temperature and potential nitrogen leaching in the summer of 2003, reduced plant growth and lodging. Under optimal growth conditions, differences in lodging between resistant and susceptible cultivars could have been greater. Five new markers generated by simple sequence repeat (SSR) primers SAD134, SAB81 and SAD141 were identified in the recombinant inbred line (RIL) population derived from MP1401 × Carneval. The markers generated from primers SAD134 and SAB81 explained 12% and 13% of lodging variation in the RILs, respectively. Primer SAD141 produced three markers which explained 19%, 11% and 25% of lodging variation in the RILs, respectively. Linkage analysis showed that none of the three markers derived from primer SAD141 were allelic. The combination of the three markers from primer SAD141 explained 28% of lodging variation. However, utilization of any of these new markers with A001 and A004 did not substantially increase the proportion of lodging variation being explained. Thus, the new markers have limited potential to improve the efficiency of MAS for lodging resistance in pea breeding.

Pea populations derived from ten crosses were scored by coupling phase linked sequence characterized amplified region (SCAR) markers A001 and A002, and repulsion phase linked SCAR marker A004 for lodging resistance during the F2 generation. The objective of this project was to test the efficiency of implementation of these three SCAR markers in marker-assisted selection (MAS) for lodging resistance in pea breeding. Chi-square tests showed that A001 and A004 followed a two independent gene segregation model in all of the eight populations that segregated for these two markers. In the F3 field trial, the differences between mean lodging score of A001 (DNA band present) and a001 (DNA band absent) classes varied from -0.5 to -0.9 with an average of -0.6, based on a 1 to 9 lodging scale, across the eight populations surveyed. The differences between mean lodging score of a004 (DNA band absent) and A004 (DNA band present) classes varied from -0.4 to -1.1 with an average of -0.7, across the eight populations surveyed. In comparison, when the combination of two markers (A001; a004 vs. a001; A004) was used, lodging score differences varied from -0.7 to -1.5, with an average of -1.0 across the eight populations. T-test results showed that significant differences (P<0.05) in lodging score were observed between A001 and a001 classes in seven out of eight populations, and between A004 and a004 classes in six out of eight populations. Further T-tests showed that significant lodging differences were observed among the four classes of the A001 and A004 marker combination in seven out of eight populations assessed, including differences at P<0.01 level in six populations. The greater differences among marker combination classes than between individual marker classes showed that combining two markers was more effective than use of each marker alone in MAS. The marker combination explained (R2) 19-57% of lodging and 4-43% of plant height variation in the eight populations surveyed. The high temperature and potential nitrogen leaching in the summer of 2003, reduced plant growth and lodging. Under optimal growth conditions, differences in lodging between resistant and susceptible cultivars could have been greater. Five new markers generated by simple sequence repeat (SSR) primers SAD134, SAB81 and SAD141 were identified in the recombinant inbred line (RIL) population derived from MP1401 × Carneval. The markers generated from primers SAD134 and SAB81 explained 12% and 13% of lodging variation in the RILs, respectively. Primer SAD141 produced three markers which explained 19%, 11% and 25% of lodging variation in the RILs, respectively. Linkage analysis showed that none of the three markers derived from primer SAD141 were allelic. The combination of the three markers from primer SAD141 explained 28% of lodging variation. However, utilization of any of these new markers with A001 and A004 did not substantially increase the proportion of lodging variation being explained. Thus, the new markers have limited potential to improve the efficiency of MAS for lodging resistance in pea breeding.

This thesis investigates the stress inside Retroreflective Raised Pavement Markers (RRPMs) under tire-marker impact and laboratory testing scenarios. Many RRPMs have poor durability although they meet certain standards of the existing laboratory tests. It has been suspected that the current testing procedures might not be adequate to decide the field performance of RRPMs. Thus, it is necessary to evaluate the existing laboratory testing procedures and develop additional ones that could simulate the field performance of RRPMs more accurately. The tire-marker impact on rigid and flexible pavement will be investigated to identify the critical locations and magnitudes of stress inside markers during the impact. Various external factors, such as tire loading, tire speed, contact angle and contact location, might have effects on the stress inside markers during the impact and be considered as critical factors when developing a laboratory test. On the other hand, RRPMs have different profiles in terms of height, lens slope, and size etc, which affect the structure and field performance as well. The study explores the stress inside markers during the impact by varying the external factors and marker profile. In addition, the interface forces between RRPMs and pavement surface will be studied. Furthermore, the tire-marker impact simulation on rigid and flexible pavement will be compared so that specific testing procedures can be distinguished based on pavement type. Finally, the existing laboratory tests will be examined and additional tests be recommended based on the tire-marker impact analysis. The researcher found that the critical compressive stress is produced at the top edges of the markers on both types of pavement, while the patterns of critical tensile stress can be different between the two types of pavement. In addition, tire loading and contact location were determined to have effect on the stress inside the markers. Furthermore, different loading rates should be used in laboratory test based on pavement type. Finally, the researcher evaluated four laboratory tests and found that each test has its merit but none of them can test RRPMs comprehensively, so it is recommended that the four tests are used together to test RRPMs.

No description available.

Glucosinolates are amino acid derived secondary metabolites found in the order Capparales. It is an important class of phytochemicals involved in plant-microbe, plant-insect, plant-animal and plant-human interactions. It is, therefore, important to understand genetic mechanism of glucosinolate biosynthesis in Brassica for efficient manipulation. In this study, QTL mapping of leaf and seed glucosinolates was performed in B. rapa using two RIL populations, SR-RILs and BU-RILs. QTL mapping was performed using SR-RILs developed from a cross of Chinese cabbage and turnip rapeseed and a genetic map in B.rapa. Genetic map was developed using a total 1,579 molecular markers including 9 markers specific to glucosinolate genes, GSL-ELONG, GSL-PRO, GSL-FMOOX1, and GSL-AOP/ALK. Several QTL for progoitrin, gluconapin, glucoalyssin, glucobrassicanapin, 2-methylpropyl and 4-hydoxyglucobrassicin glucosinolates were identified with phenotype variance between 6 and 54%. Interestingly, a major QTL for 5C aliphatic glucosinolates was co-localized with a candidate Br-GSL-ELONG locus on linkage group A3, displayed co-segregation with co-dominant SCAR marker BrMAM1-1. The Br-GSL-ELONG locus was identified to regulate 20 µmole/g seed 5C glucosinolate biosynthesis. BU-RILs derived from a cross of yellow sarson and USU9 was segregated for glucoerucin, gluconapin and progoitrin 4C aliphatic glucosinolates with 4-hydoxyglucobrassicin. Phenotyping was performed in controlled and field environments for seed glucosinolates and controlled environments for leaf glucosinolates. Genetic map was developed using SRAP markers and glucosinolate gene, GSL-ELONG and GSL-PRO specific 4 loci were integrated on map. Four and three QTL were identified for seed glucoerucin and gluconapin, respectively in both environments with phenotypic variance up to 49%. Additionally, genetic manipulation of glucosinolates was performed by backcross with MAS in B. rapa. Resynthesized B. napus line was backcrossed with B. rapa genotypes, RI16, BAR6 and USU9 for replacement or introgression of glucosinolate genes, GSL-ELONG- and GSL-PRO+. In RI16 genotype, 15 to 25 µmole/g seed 5C glucosinolates reduced in 15 BC3F2 lines those were positive with GSL-ELONG- marker and negative with the A-genome and gene specific marker BrMAM1-1. This suggests that the functional allele has replaced by non-functional from B. oleracea. GSL-PRO+ positive backcross lines in RI16 genotype displayed sinigrin 3C aliphatic glucosinolate in B. rapa. This suggests introgression of GSL-PRO+ in B. rapa.