The aim of this thesis was to establish methods for selected PAPP-A (Pregnancy- Associated Plasma Protein A) gene polymorphisms analysis and to study genetic background of PAPP-A and biochemical background of PAPP-A and PlGF (Placental Growth Factor) in relation to risk pregnancy. Secondly, the aim was to establish method for two-dimensional (2D) electrophoresis of amniotic fluid. Methods for analysis of ten PAPP-A gene polymorphisms were established. These polymorphisms, PAPP-A and PlGF levels were studied in together 165 women in third trimester pregnancies complicated with threatening preterm labor (n=98), preeclampsia (n=35), IUGR (Intrauterine Growth Restriction) (n=34) and ICP (Intrahepatic Cholestasis of Pregnancy) (n=15). 114 healthy pregnant women served as controls. The method for 2D electrophoresis of amniotic fluid was established. Preeclamptic patients had significantly higher frequency of TT genotype of Cys327Cys (C/T) PAPP-A gene polymorphism compared to controls. Patients with ICP had increased serum levels of PAPP-A compared to controls, in patients with threatening preterm labor PAPP-A levels were rather decreased. PlGF levels did not differ from control group in patients with ICP and threatening preterm labor. Positive correlation was found between PAPP-A and PlGF in group of...

<p>Apstrakt je obrađen tehnologijama za optičko prepoznavanje teksta OCR.</p><p>Uzajamnim djelovanjem i nrožimanjem faktora i elemenata prirodne osnove, te relevantnih dru&scaron;tveno-sreografskih procesa, izdiferencirala se posebna regionalna cjelina Semberija, koju karekteri&scaron;u homogenost i integrativnost.</p> / <p>The abstract has been processed with OCR optical text recognition technology.</p><p>Reciprocal operation and permeation of the natural basis /base/ factors and elements and relevant social geographic (al) procceses, the regional urit of Semberia, kxsvohose characteristics are homogesity and integrity has espe daily diferentiated frou the other anes.</p>

Erstmals seit dem 2. Weltkrieg wird mit der Karte eine vollständige Übersicht über die im genannten Raum bebauten oder noch vorhandenen o. g. mineralischen Rohstoffe gegeben. Auf der Karte im Maßstab 1:100.000 kommen Verbreitung, Intensität und Genese dieser Rohstoffe zur Darstellung. Die Karte liegt der Broschüre nicht bei, sondern kann beim Staatsbetrieb Geobasisinformation und Vermessung Sachsen erworben werden. Redaktionsschluss: 30.11.1996

V této práci je prezentována inovativní metoda zvaná \textit{Zobrazovací Reflektometrie}, která je založena na principu spektroskopické reflektometrie a je určena pro vyhodnocování optických vlastností tenkých vrstev .\ Spektrum odrazivosti je získáno z map intenzit zaznamenaných CCD kamerou. Každý záznam odpovídá předem nastavené vlnové délce a spektrum odrazivosti může být určeno ve zvoleném bodu nebo ve vybrané oblasti.\ Teoretický model odrazivosti se fituje na naměřená data pomocí Levenberg~-~Marquardtova algoritmu, jehož výsledky jsou optické vlastnosti vrstvy, jejich přesnost, a určení spolehlivosti dosažených výsledků pomocí analýzy citlivosti změn počátečních nastavení optimalizačního algoritmu.

This thesis deals with the solution problem of fitting a window in the wall, especially for passive houses. It provides options to optimize the window connection joints, improve the thermal transmittance of the window frame, thereby reducing the total heat loss through the window. In the first part of the thesis is a research literature on the windows and heat technical and physical mechanisms. Are described equations and physical processes taking place in the windows and related building structures. This section describes the basic points in history, technical description of windows, etc. and present ways of assembly Installation the window and the influence of the thermal properties of the heat loss. The next part deals with the description of the work and the results obtained in the course of doctoral study. Describes the main objectives of the dissertation thesis, calculations and simulations of temperature fields and the results of the calculated values. Furthermore are described and analyzed measurement data and compared with the calculated values. At the end dissertation thesis are given opportunities to improve the current solution regarding the heat transfer coefficient of the frame, the optimal way of installation fillers windows in the perimeter wall and improve the thermal properties of the connecting joint.

The purpose of dissertation is the analysis of the calculation of fracture parameters using Double-K fracture model for quasi-brittle specimens with the stress concentrator loaded by three-point bending or wedge splitting. To calculation of these parameters was used the developed DKFM_BUT software in Microsoft Excel application with using of Visual Basic programming language. Furthermore, the adequate shape functions and compliance functions were introduced for the selected wedge splitting test configurations. Main part of this dissertation is the series of comprehensively implemented and evaluated fracture experiments on specimens from advanced building materials, while the attention was paid to the analysis of experimental data. Finally, the selected results obtained using mentioned software support were presented and discussed.

Identification of biomarkers involved in the pathophysiology of gestational diabetes mellitus ABSTRACT Gestational diabetes mellitus is a disorder of glucose metabolism that occurs in pregnancy and resolves after delivery. Increasing production of pregnancy-related hormones leads to insulin resistance which is not adequately compensated by increased insulin secretion. Since obesity is an important risk factor for gestational diabetes and is also associated with adipose tissue dysfunction and increased peripheral insulin resistance, the question arises as to what extent is the adipose tissue involved in the development of gestational diabetes. The first part of the thesis focuses on the identification of changes in plasma concentration and mRNA expression of adipokines fetuin A, fetuin B and FGF21. In our study we did not show that the presence of gestational diabetes significantly influenced the plasma concentration of fetuin A, fetuin B and FGF21 during pregnancy. An important finding was that women who had pregnancy complicated with gestational diabetes had a significantly higher concentration of FGF21 several months after delivery in comparison to healthy pregnant women. We have been able to demonstrate the production of fetuin A in the placenta and fetuin B in perineal and subcutaneous tissue. However,...

Die Dissertation untersucht das Potenzial von Machine-Learning-Methoden zur Verwaltung von Schwanzrisiken in nicht-stationären und hochdimensionalen Umgebungen. Dazu vergleichen wir auf robuste Weise datenabhängige Ansätze aus parametrischer oder nicht-parametrischer Statistik mit datenadaptiven Methoden. Da datengetriebene Methoden reproduzierbar sein müssen, um Vertrauen und Transparenz zu gewährleisten, schlagen wir zunächst eine neue Plattform namens Quantinar vor, die einen neuen Standard für wissenschaftliche Veröffentlichungen setzen soll. Im zweiten Kapitel werden parametrische, lokale parametrische und nicht-parametrische Methoden verglichen, um eine dynamische Handelsstrategie für den Schutz vor Schwanzrisiken in Bitcoin zu entwickeln. Das dritte Kapitel präsentiert die Portfolio-Allokationsmethode NMFRB, die durch eine Dimensionsreduktionstechnik hohe Dimensionen bewältigt. Im Vergleich zu klassischen Machine-Learning-Methoden zeigt NMFRB in zwei Universen überlegene risikobereinigte Renditen. Das letzte Kapitel kombiniert bisherige Ansätze zu einer Schwanzrisikoschutzstrategie für Portfolios. Die erweiterte NMFRB berücksichtigt Schwanzrisikomaße, behandelt nicht-lineare Beziehungen zwischen Vermögenswerten während Schwanzereignissen und entwickelt eine dynamische Schwanzrisikoschutzstrategie unter Berücksichtigung der Nicht-Stationarität der Vermögensrenditen. Die vorgestellte Strategie reduziert erfolgreich große Drawdowns und übertrifft andere moderne Schwanzrisikoschutzstrategien wie die Value-at-Risk-Spread-Strategie. Die Ergebnisse werden durch verschiedene Data-Snooping-Tests überprüft. / This dissertation shows the potential of machine learning methods for managing tail risk in a non-stationary and high-dimensional setting. For this, we compare in a robust manner data-dependent approaches from parametric or non-parametric statistics with data-adaptive methods. As these methods need to be reproducible to ensure trust and transparency, we start by proposing a new platform called Quantinar, which aims to set a new standard for academic publications. In the second chapter, we dive into the core subject of this thesis which compares various parametric, local parametric, and non-parametric methods to create a dynamic trading strategy that protects against tail risk in Bitcoin cryptocurrency. In the third chapter, we propose a new portfolio allocation method, called NMFRB, that deals with high dimensions thanks to a dimension reduction technique, convex Non-negative Matrix Factorization. This technique allows us to find latent interpretable portfolios that are diversified out-of-sample. We show in two universes that the proposed method outperforms other classical machine learning-based methods such as Hierarchical Risk Parity (HRP) concerning risk-adjusted returns. We also test the robustness of our results via Monte Carlo simulation. Finally, the last chapter combines our previous approaches to develop a tail-risk protection strategy for portfolios: we extend the NMFRB to tail-risk measures, we address the non-linear relationships between assets during tail events by developing a specific non-linear latent factor model, finally, we develop a dynamic tail risk protection strategy that deals with the non-stationarity of asset returns using classical econometrics models. We show that our strategy is successful at reducing large drawdowns and outperforms other modern tail-risk protection strategies such as the Value-at-Risk-spread strategy. We verify our findings by performing various data snooping tests.

Diese Dissertation zielt darauf ab, ein besseres Verständnis für Anomalien und Insiderhandel zu schaffen, sowie die Verfügbarkeit von qualitativ hochwertigen Daten für den deutschen Aktienmarkt zu verbessern. Der erste Aufsatz beinhaltet eine verzerrungsfreie Zeitreihe von monatlichen Renditen deutscher Aktien für die Jahre 1954 bis 2013, die auf der Basis stabiler Regeln berechnet und gut dokumentiert ist. Im Weiteren enthält der Aufsatz eine detaillierte Beschreibung des deutschen Aktienmarktes und dessen Besonderheiten, insbesondere im Vergleich zu den USA. Der zweite Aufsatz zeigt am Beispiel des Fama/French Drei-Faktoren-Modells die Probleme auf, die Anbieter und Nutzer von Faktorendaten haben, die sich nicht auf die USA beziehen. Die empirische Analyse von sieben Faktorensets für Deutschland zeigt, dass die Übernahme von Faktormodellen in einen anderen Kapitalmarkt eine komplexe Thematik ist. Der Aufsatz gibt Anregungen für Nutzer und Anbieter von Faktorensets und zeigt, wie die Wahl des Faktorensets das Ergebnis einer Studie beeinflussen kann. Im dritten Aufsatz werden verschiedene zyklische und antizyklische Handelsstrategien hinsichtlich ihrer Performance im deutschen Aktienmarkt untersucht. Von den untersuchten Strategien erscheint nur Momentum konsequent abnormale Renditen zu erzielen, dies auch nach Transaktionskosten. Die vierte Arbeit untersucht öffentlich bekannt gegebene Aktientransaktionen von Insidern börsennotierter deutscher Unternehmen. Der Aufsatz zeigt, dass Insider von TecDAX-Unternehmen und ihre Imitatoren hohe und statistisch signifikante abnormale Renditen erzielen. Insgesamt zeigt die Dissertation, dass methodische Variationen, die Verwendung verschiedener Untersuchungsdesigns, die Datenqualität und die Sorgfalt beim Erstellen von empirischen Analysen zur Beurteilung der Robustheit und der Stabilität der Ergebnisse unerlässlich sind. Der deutsche Aktienmarkt scheint effizienter zu sein als bisherigere Studien typischerweise nahelegen. / This doctoral thesis aims to contribute to a better understanding of stock market anomalies and insider trading as well as to improve the availability of high quality data for the German stock market. The first paper provides a sixty-year time series of monthly returns on German stocks that is constructed on the basis of stable rules, is well documented, includes all return components, and is free of biases. The paper also contains a detailed description of the German stock market, its peculiarities, regulation and differences as compared to the U.S. The second paper uses the Fama/French three-factor model as an example to point out the problems that providers and users of non-U.S factor data sets face. The empirical analysis of seven different factor data sets available for Germany shows that exporting a specific factor model from the U.S. to another capital market is neither an easy nor well-defined task. The paper gives suggestions to users and creators of factor sets and shows how the choice of a factor set affects the result of an empirical study. The third paper provides evidence on how various contrarian, momentum and seasonality strategies perform in the German stock market. Among these strategies, only momentum investing appears to earn persistently non-zero returns, even after transaction costs. The fourth paper studies publicly disclosed stock transactions by insiders of listed German firms. The paper finds that insiders of TecDAX firms earn large and statistically significant abnormal returns net of transaction costs; for DAX insiders they are indistinguishable from zero. Overall, this thesis illustrates that methodological variations, the use of different specifications, data quality and care when preparing empirical analyses is essential in the assessment of the robustness and stability of results. In sum, the German stock market appears to be more efficient than previous studies have typically suggested.

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