Inference on copula-based correlation structures

We propose an extension of the approach provided by Kluppelberg and Kuhn (2009) for inference on second-order structure moments. As in Kluppelberg and Kuhn (2009) we adopt a copula-based approach instead of assuming normal distribution for the variables, thus relaxing the equality in distribution assumption. A new copula-based estimator for structure moments is investigated. The methodology provided by Kluppelberg and Kuhn (2009) is also extended considering the copulas associated with the family of Eyraud-Farlie-Gumbel-Morgenstern distribution functions (Kotz, Balakrishnan, and Johnson, 2000, Equation 44.73). Finally, a comprehensive simulation study and an application to real financial data are performed in order to compare the different approaches.

Nonlinear Control Strategies for Cooperative Control of Multi-Robot Systems

This thesis deals with distributed control strategies for cooperative control of multi-robot systems. Specifically, distributed coordination strategies are presented for groups of mobile robots. The formation control problem is initially solved exploiting artificial potential fields. The purpose of the presented formation control algorithm is to drive a group of mobile robots to create a completely arbitrarily shaped formation. Robots are initially controlled to create a regular polygon formation. A bijective coordinate transformation is then exploited to extend the scope of this strategy, to obtain arbitrarily shaped formations. For this purpose, artificial potential fields are specifically designed, and robots are driven to follow their negative gradient. Artificial potential fields are then subsequently exploited to solve the coordinated path tracking problem, thus making the robots autonomously spread along predefined paths, and move along them in a coordinated way. Formation control problem is then solved exploiting a consensus based approach. Specifically, weighted graphs are used both to define the desired formation, and to implement collision avoidance. As expected for consensus based algorithms, this control strategy is experimentally shown to be robust to the presence of communication delays. The global connectivity maintenance issue is then considered. Specifically, an estimation procedure is introduced to allow each agent to compute its own estimate of the algebraic connectivity of the communication graph, in a distributed manner. This estimate is then exploited to develop a gradient based control strategy that ensures that the communication graph remains connected, as the system evolves. The proposed control strategy is developed initially for single-integrator kinematic agents, and is then extended to Lagrangian dynamical systems.

Microarray based real-time analysis of nucleic acid hybridization kinetics and thermodynamics

Ziel dieser Dissertation ist die experimentelle Charakterisierung und quantitative Beschreibung der Hybridisierung von komplementären Nukleinsäuresträngen mit oberflächengebundenen Fängermolekülen für die Entwicklung von integrierten Biosensoren. Im Gegensatz zu lösungsbasierten Verfahren ist mit Microarray Substraten die Untersuchung vieler Nukleinsäurekombinationen parallel möglich. Als biologisch relevantes Evaluierungssystem wurde das in Eukaryoten universell exprimierte Actin Gen aus unterschiedlichen Pflanzenspezies verwendet. Dieses Testsystem ermöglicht es, nahe verwandte Pflanzenarten auf Grund von geringen Unterschieden in der Gen-Sequenz (SNPs) zu charakterisieren. Aufbauend auf dieses gut studierte Modell eines House-Keeping Genes wurde ein umfassendes Microarray System, bestehend aus kurzen und langen Oligonukleotiden (mit eingebauten LNA-Molekülen), cDNAs sowie DNA und RNA Targets realisiert. Damit konnte ein für online Messung optimiertes Testsystem mit hohen Signalstärken entwickelt werden. Basierend auf den Ergebnissen wurde der gesamte Signalpfad von Nukleinsärekonzentration bis zum digitalen Wert modelliert. Die aus der Entwicklung und den Experimenten gewonnen Erkenntnisse über die Kinetik und Thermodynamik von Hybridisierung sind in drei Publikationen zusammengefasst die das Rückgrat dieser Dissertation bilden. Die erste Publikation beschreibt die Verbesserung der Reproduzierbarkeit und Spezifizität von Microarray Ergebnissen durch online Messung von Kinetik und Thermodynamik gegenüber endpunktbasierten Messungen mit Standard Microarrays. Für die Auswertung der riesigen Datenmengen wurden zwei Algorithmen entwickelt, eine reaktionskinetische Modellierung der Isothermen und ein auf der Fermi-Dirac Statistik beruhende Beschreibung des Schmelzüberganges. Diese Algorithmen werden in der zweiten Publikation beschrieben. Durch die Realisierung von gleichen Sequenzen in den chemisch unterschiedlichen Nukleinsäuren (DNA, RNA und LNA) ist es möglich, definierte Unterschiede in der Konformation des Riboserings und der C5-Methylgruppe der Pyrimidine zu untersuchen. Die kompetitive Wechselwirkung dieser unterschiedlichen Nukleinsäuren gleicher Sequenz und die Auswirkungen auf Kinetik und Thermodynamik ist das Thema der dritten Publikation. Neben der molekularbiologischen und technologischen Entwicklung im Bereich der Sensorik von Hybridisierungsreaktionen oberflächengebundener Nukleinsäuremolekülen, der automatisierten Auswertung und Modellierung der anfallenden Datenmengen und der damit verbundenen besseren quantitativen Beschreibung von Kinetik und Thermodynamik dieser Reaktionen tragen die Ergebnisse zum besseren Verständnis der physikalisch-chemischen Struktur des elementarsten biologischen Moleküls und seiner nach wie vor nicht vollständig verstandenen Spezifizität bei.

Next-Generation Sequencing-Based Mutations Scanning Strategy of the BCR-ABL Kinase Domain in Patients with PhiladelPhia-Chromosome Positive Leukemias Treated with Tyrosine Kinase Inhibitors

In chronic myeloid leukemia and Philadelphia-positive acute lymphoblastic leukemia patients resistant to tyrosine kinase inhibitors (TKIs), BCR-ABL kinase domain mutation status is an essential component of the therapeutic decision algorithm. The recent development of Ultra-Deep Sequencing approach (UDS) has opened the way to a more accurate characterization of the mutant clones surviving TKIs conjugating assay sensitivity and throughput. We decided to set-up and validated an UDS-based for BCR-ABL KD mutation screening in order to i) resolve qualitatively and quantitatively the complexity and the clonal structure of mutated populations surviving TKIs, ii) study the dynamic of expansion of mutated clones in relation to TKIs therapy, iii) assess whether UDS may allow more sensitive detection of emerging clones, harboring critical 2GTKIs-resistant mutations predicting for an impending relapse, earlier than SS. UDS was performed on a Roche GS Junior instrument, according to an amplicon sequencing design and protocol set up and validated in the framework of the IRON-II (Interlaboratory Robustness of Next-Generation Sequencing) International consortium.Samples from CML and Ph+ ALL patients who had developed resistance to one or multiple TKIs and collected at regular time-points during treatment were selected for this study. Our results indicate the technical feasibility, accuracy and robustness of our UDS-based BCR-ABL KD mutation screening approach. UDS was found to provide a more accurate picture of BCR-ABL KD mutation status, both in terms of presence/absence of mutations and in terms of clonal complexity and showed that BCR-ABL KD mutations detected by SS are only the “tip of iceberg”. In addition UDS may reliably pick 2GTKIs-resistant mutations earlier than SS in a significantly greater proportion of patients.The enhanced sensitivity as well as the possibility to identify low level mutations point the UDS-based approach as an ideal alternative to conventional sequencing for BCR-ABL KD mutation screening in TKIs-resistant Ph+ leukemia patients

Tissue engineering strategies for biomaterial-based anticancer drug delivery and enhancement of angiogenesis in tumor-resected bone

Patienten, die an Osteosarkom leiden werden derzeit mit intravenös applizierten krebstherapeutischen Mitteln nach Tumorresektion behandelt, was oftmals mit schweren Nebenwirkungen und einem verzögerten Knochenheilungsprozess einhergeht. Darüber hinaus treten vermehrt Rezidive aufgrund von verbleibenden neoplastischen Zellen an der Tumorresektionsstelle auf. Erfolgreiche Knochenregeneration und die Kontrolle von den im Gewebe verbleibenden Krebszellen stellt eine Herausforderung für das Tissue Engineering nach Knochenverlust durch Tumorentfernung dar. In dieser Hinsicht scheint der Einsatz von Hydroxyapatit als Knochenersatzmaterial in Kombination mit Cyclodextrin als Medikamententräger, vielversprechend. Chemotherapeutika können an Biomaterial gebunden und direkt am Tumorbett über einen längeren Zeitraum freigesetzt werden, um verbliebene neoplastische Zellen zu eliminieren. Lokal applizierte Chemotherapie hat diverse Vorteile, einschließlich der direkten zytotoxischen Auswirkung auf lokale Zellen, sowie die Reduzierung schwerer Nebenwirkungen. Diese Studie wurde durchgeführt, um die Funktionsfähigkeit eines solchen Arzneimittelabgabesystems zu bewerten und um Strategien im Bereich des Tissue Engineerings zu entwickeln, die den Knochenheilungsprozess und im speziellen die Vaskularisierung fördern sollen. Die Ergebnisse zeigen, dass nicht nur Krebszellen von der chemotherapeutischen Behandlung betroffen sind. Primäre Endothelzellen wie zum Beispiel HUVEC zeigten eine hohe Sensibilität Cisplatin und Doxorubicin gegenüber. Beide Medikamente lösten in HUVEC ein tumor-unterdrückendes Signal durch die Hochregulation von p53 und p21 aus. Zudem scheint Hypoxie einen krebstherapeutischen Einfluss zu haben, da die Behandlung sensitiver HUVEC mit Hypoxie die Zellen vor Zytotoxizität schützte. Der chemo-protektive Effekt schien deutlich weniger auf Krebszelllinien zu wirken. Diese Resultate könnten eine mögliche chemotherapeutische Strategie darstellen, um den Effekt eines zielgerichteten Medikamenteneinsatzes auf Krebszellen zu verbessern unter gleichzeitiger Schonung gesunder Zellen. Eine erfolgreiche Integration eines Systems, das Arzneimittel abgibt, kombiniert mit einem Biomaterial zur Stabilisierung und Regeneration, könnte gesunden Endothelzellen die Möglichkeit bieten zu proliferieren und Blutgefäße zu bilden, während verbleibende Krebszellen eliminiert werden. Da der Prozess der Knochengeweberemodellierung mit einer starken Beeinträchtigung der Lebensqualität des Patienten einhergeht, ist die Beschleunigung des postoperativen Heilungsprozesses eines der Ziele des Tissue Engineerings. Die Bildung von Blutgefäßen ist unabdingbar für eine erfolgreiche Integration eines Knochentransplantats in das Gewebe. Daher ist ein umfangreich ausgebildetes Blutgefäßsystem für einen verbesserten Heilungsprozess während der klinischen Anwendung wünschenswert. Frühere Experimente zeigen, dass sich die Anwendung von Ko-Kulturen aus humanen primären Osteoblasten (pOB) und humanen outgrowth endothelial cells (OEC) im Hinblick auf die Bildung stabiler gefäßähnlicher Strukturen in vitro, die auch effizient in das mikrovaskuläre System in vivo integriert werden konnten, als erfolgreich erweisen. Dieser Ansatz könnte genutzt werden, um prä-vaskularisierte Konstrukte herzustellen, die den Knochenheilungsprozess nach der Implantation fördern. Zusätzlich repräsentiert das Ko-Kultursystem ein exzellentes in vitro Model, um Faktoren, welche stark in den Prozess der Knochenheilung und Angiogenese eingebunden sind, zu identifizieren und zu analysieren. Es ist bekannt, dass Makrophagen eine maßgebliche Rolle in der inflammatorisch-induzierten Angiogenese spielen. In diesem Zusammenhang hebt diese Studie den positiven Einfluss THP-1 abgeleiteter Makrophagen in Ko-Kultur mit pOB und OEC hervor. Die Ergebnisse zeigten, dass die Anwendung von Makrophagen als inflammatorischer Stimulus im bereits etablierten Ko-Kultursystem zu einer pro-angiogenen Aktivierung der OEC führte, was in einer signifikant erhöhten Bildung blutgefäßähnlicher Strukturen in vitro resultierte. Außerdem zeigte die Analyse von Faktoren, die in der durch Entzündung hervorgerufenen Angiogenese eine wichtige Rolle spielen, eine deutliche Hochregulation von VEGF, inflammatorischer Zytokine und Adhäsionsmoleküle, die letztlich zu einer verstärkten Vaskularisierung beitragen. Diese Resultate werden dem Einfluss von Makrophagen zugeschrieben und könnten zukünftig im Tissue Engineering eingesetzt werden, um den Heilungsprozess zu beschleunigen und damit die klinische Situation von Patienten zu verbessern. Darüber hinaus könnte die Kombination der auf Ko-Kulturen basierenden Ansätze für das Knochen Tissue Engineering mit einem biomaterial-basierenden Arzneimittelabgabesystem zum klinischen Einsatz kommen, der die Eliminierung verbliebener Krebszellen mit der Förderung der Knochenregeneration verbindet.

Uniform approach to linear and nonlinear interrelation patterns in multivariate time series

Currently, a variety of linear and nonlinear measures is in use to investigate spatiotemporal interrelation patterns of multivariate time series. Whereas the former are by definition insensitive to nonlinear effects, the latter detect both nonlinear and linear interrelation. In the present contribution we employ a uniform surrogate-based approach, which is capable of disentangling interrelations that significantly exceed random effects and interrelations that significantly exceed linear correlation. The bivariate version of the proposed framework is explored using a simple model allowing for separate tuning of coupling and nonlinearity of interrelation. To demonstrate applicability of the approach to multivariate real-world time series we investigate resting state functional magnetic resonance imaging (rsfMRI) data of two healthy subjects as well as intracranial electroencephalograms (iEEG) of two epilepsy patients with focal onset seizures. The main findings are that for our rsfMRI data interrelations can be described by linear cross-correlation. Rejection of the null hypothesis of linear iEEG interrelation occurs predominantly for epileptogenic tissue as well as during epileptic seizures.

Mesh-based vs. Image-based Statistical Appearance Model of the Human Femur: a Preliminary Comparison Study for the Creation of Finite Element Meshes

Statistical models have been recently introduced in computational orthopaedics to investigate the bone mechanical properties across several populations. A fundamental aspect for the construction of statistical models concerns the establishment of accurate anatomical correspondences among the objects of the training dataset. Various methods have been proposed to solve this problem such as mesh morphing or image registration algorithms. The objective of this study is to compare a mesh-based and an image-based statistical appearance model approaches for the creation of nite element(FE) meshes. A computer tomography (CT) dataset of 157 human left femurs was used for the comparison. For each approach, 30 finite element meshes were generated with the models. The quality of the obtained FE meshes was evaluated in terms of volume, size and shape of the elements. Results showed that the quality of the meshes obtained with the image-based approach was higher than the quality of the mesh-based approach. Future studies are required to evaluate the impact of this finding on the final mechanical simulations.

Suicide in breast cancer patients: an individual-centered approach provides insight beyond epidemiology

Epidemiologic studies have identified increased suicide rates among breast cancer (BC) patients. The population-based approach, however, has considerable methodic shortcomings. None of the studies have been carried out in a prospective manner and none reported suicide rates from a country in which physician-assisted suicide (PAS) is legal.

ON THE MERITS OF VOXEL-BASED MORPHOMETRIC PATH-ANALYSIS FOR INVESTIGATING VOLUMETRIC MEDIATION OF A TOXICANT'S INFLUENCE ON COGNITIVE FUNCTION

We previously showed that lifetime cumulative lead dose, measured as lead concentration in the tibia bone by X-ray fluorescence, was associated with persistent and progressive declines in cognitive function and with decreases in MRI-based brain volumes in former lead workers. Moreover, larger region-specific brain volumes were associated with better cognitive function. These findings motivated us to explore a novel application of path analysis to evaluate effect mediation. Voxel-wise path analysis, at face value, represents the natural evolution of voxel-based morphometry methods to answer questions of mediation. Application of these methods to the former lead worker data demonstrated potential limitations in this approach where there was a tendency for results to be strongly biased towards the null hypothesis (lack of mediation). Moreover, a complimentary analysis using anatomically-derived regions of interest volumes yielded opposing results, suggesting evidence of mediation. Specifically, in the ROI-based approach, there was evidence that the association of tibia lead with function in three cognitive domains was mediated through the volumes of total brain, frontal gray matter, and/or possibly cingulate. A simulation study was conducted to investigate whether the voxel-wise results arose from an absence of localized mediation, or more subtle defects in the methodology. The simulation results showed the same null bias evidenced as seen in the lead workers data. Both the lead worker data results and the simulation study suggest that a null-bias in voxel-wise path analysis limits its inferential utility for producing confirmatory results.

Applied Graph Theory in Computer Vision and Pattern Recognition

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.

Hospital use of young children in Switzerland: a nation-wide study based on a complete survey over 4 years

Background Young children are known to be the most frequent hospital users compared to older children and young adults. Therefore, they are an important population from economic and policy perspectives of health care delivery. In Switzerland complete hospitalization discharge records for children [<5 years] of four consecutive years [2002–2005] were evaluated in order to analyze variation in patterns of hospital use. Methods Stationary and outpatient hospitalization rates on aggregated ZIP code level were calculated based on census data provided by the Swiss federal statistical office (BfS). Thirty-seven hospital service areas for children [HSAP] were created with the method of "small area analysis", reflecting user-based health markets. Descriptive statistics and general linear models were applied to analyze the data. Results The mean stationary hospitalization rate over four years was 66.1 discharges per 1000 children. Hospitalizations for respiratory problem are most dominant in young children (25.9%) and highest hospitalization rates are associated with geographical factors of urban areas and specific language regions. Statistical models yielded significant effect estimates for these factors and a significant association between ambulatory/outpatient and stationary hospitalization rates. Conclusion The utilization-based approach, using HSAP as spatial representation of user-based health markets, is a valid instrument and allows assessing the supply and demand of children's health care services. The study provides for the first time estimates for several factors associated with the large variation in the utilization and provision of paediatric health care resources in Switzerland.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.

A comparison of pixel and object-based land cover classification. A case study of the Asmara region, Eritrea

In this paper we compare the performance of two image classification paradigms (object- and pixel-based) for creating a land cover map of Asmara, the capital of Eritrea and its surrounding areas using a Landsat ETM+ imagery acquired in January 2000. The image classification methods used were maximum likelihood for the pixel-based approach and Bhattacharyya distance for the object-oriented approach available in, respectively, ArcGIS and SPRING software packages. Advantages and limitations of both approaches are presented and discussed. Classifications outputs were assessed using overall accuracy and Kappa indices. Pixel- and object-based classification methods result in an overall accuracy of 78% and 85%, respectively. The Kappa coefficient for pixel- and object-based approaches was 0.74 and 0.82, respectively. Although pixel-based approach is the most commonly used method, assessment and visual interpretation of the results clearly reveal that the object-oriented approach has advantages for this specific case-study.