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In dieser Arbeit wurde der Frage nachgegangen, ob der Arbeitgeber nach ausgewählten Impfungen fragen darf bzw. unter welchen Umständen der Bewerber von sich aus seinen Impfstatus offenlegen muss. Bei den ausgewählten Impfungen handelt es sich um die FSME-Impfung, die Grippeimpfung, die Corona-Impfung und die Masernimpfung. Um hier zu einem Ergebnis zu kommen, wurde ein Überblick über das Fragerecht und die Offenbarungspflicht sowie deren Grenzen gegeben. Mit den daraus gewonnenen Erkenntnissen wurde im Hauptteil dieser Arbeit untersucht, ob der Bewerber ein Geheimhaltungsinteresse hinsichtlich seines Impfstatus hat und ob der Arbeitgeber ein sachliches Interesse am Impfstatus des Bewerbers haben kann. Im letzten Teil der Arbeit wurde anhand der vorstehenden Ergebnisse beurteilt, ob die jeweilige Frage zulässig ist oder nicht. eingereicht von Felix Paul Langergraber Diplomarbeit Universität Linz 2023 Arbeit auf den öffentlichen PCs in den Bibliotheken der JKU+Medizin abrufbar

We numerically study QCD with a single quark flavour on the lattice probing predictions from effective field theories that are equivalent to minimal super-symmetric Yang-Mills theory in the large $N_c$ limit. The hadronic spectrum including excited states is analysed using one gauge coupling and several physical volumes and fermion masses. We use the LapH method and also compute disconnected diagrams. Lattice simulations with an odd number of Wilson fermions give rise to regions of configuration space with a negative fermionic weight entailing a sign problem. We perform a detailed analysis on the spectrum of the Wilson-Dirac operator and report on observed cases of a negative fermion determinant in our ensembles., 9 pages, 10 figures

24th International Spin Symposium, SPIN2021, Matsue, Japan, 18 Oct 2021 - 22 Oct 2021; JPS conference proceedings 37, 021104 (2022). doi:10.7566/JPSCP.37.021104, In recent years, Laser Plasma Acceleration (LPA) has become a promising alternative toconventional RF accelerators. However, so far, it has only been theoretically shown thatgenerating polarized LPA beams is possible. The LEAP (Laser Electron Acceleration withPolarization) project at DESY aims to demonstrate this experimentally for the first time,using a pre-polarized plasma target.The electron polarization will be measured with photon transmission polarimetry, whichmakes use of the production of circularly polarized bremsstrahlung during the passage ofthe electron beams through a suitable converter target. The photon polarization is thenmeasured with the aid of transmission asymmetry arising from reversing the magnetizationdirection of an iron absorber.In this contribution an overview of the LEAP project is presented, detailing the generation ofthe polarized electron beams along with the design and simulation studies of the polarimeter., Published by The Physical Society of Japan, Tokyo

In this work, we address the challenge of developing statistical shape models that account for the non-Euclidean nature inherent to (anatomical) shape variation and at the same time offer fast, numerically robust processing and as much invariance as possible regarding translation and rotation, i.e. Euclidean motion. With the aim of doing that we formulate a continuous and physically motivated notion of shape space based on deformation gradients. We follow two different tracks endowing this differential representation with a Riemannian structure to establish a statistical shape model. (1) We derive a model based on differential coordinates as elements in GL(3)+. To this end, we adapt the notion of bi-invariant means employing an affine connection structure on GL(3)+. Furthermore, we perform second-order statistics based on a family of Riemannian metrics providing the most possible invariance, viz. GL(3)+-left-invariance and O(3)-right-invariance. (2) We endow the differential coordinates with a non-Euclidean structure, that stems from a product Lie group of stretches and rotations. This structure admits a bi-invariant metric and thus allows for a consistent analysis via manifold-valued Riemannian statistics. This work further presents a novel shape representation based on discrete fundamental forms that is naturally invariant under Euclidean motion, namely the fundamental coordinates. We endow this representation with a Lie group structure that admits bi-invariant metrics and therefore allows for consistent analysis using manifold-valued statistics based on the Riemannian framework. Furthermore, we derive a simple, efficient, robust, yet accurate (i.e. without resorting to model approximations) solver for the inverse problem that allows for interactive applications. Beyond statistical shape modeling the proposed framework is amenable for surface processing such as quasi-isometric flattening. Additionally, the last part of the thesis aims on shape-based, continuous disease stratification to provide means that objectify disease assessment over the current clinical practice of ordinal grading systems. Therefore, we derive the geodesic B-score, a generalization of the of the Euclidean B-score, in order to assess knee osteoarthritis. In this context we present a Newton-type fixed point iteration for projection onto geodesics in shape space. On the application side, we show that the derived geodesic B-score features, in comparison to its Euclidean counterpart, an improved predictive performance on assessing the risk of total knee replacement surgery., Die vorliegende Arbeit beschäftigt sich mit der Herausforderung der Entwicklung statistischer Formmodelle, welche die inhärente nichteuklidische Struktur (anatomischer) Formvariation berücksichtigen, gleichzeitig eine effiziente, numerisch robuste Verarbeitung erlauben und zusätzlich möglichst viel Invarianz unter euklidischen Bewegungen der verwendeten Daten bieten. Dazu schlagen wir einen kontinuierlichen und physikalisch motivierten Formenraum basierend auf Deformationsgradienten vor. Wir verfolgen zwei verschiedene Ansätze, um auf diesem eine Riemannsche Struktur und damit ein statistisches Formmodell zu etablieren. (1) Wir entwickeln ein Modell für die differentiellen Koordinaten als Elemente in GL(3)+. Zu diesem Zweck adaptieren wir den Begriff des biinvarianten Mittelwerts bezüglich eines affinen Zusammenhanges auf GL(3)+ und führen Statistik zweiter Ordnung basierend auf einer Familie maximal invarianter, d.h. GL(3)+-links- und O(3)-rechts-invarianter, Riemannscher Metriken durch. (2) Wir versehen die differentiellen Koordinaten mit einer nichteuklidischen Struktur, die angelehnt an die Lie-Produktgruppe aus Streckungen und Rotationen ist. Diese lässt eine biinvariante Metrik und damit eine konsistente Analyse mittels mannigfaltigkeitswertiger Statistik im Riemannschen Rahmen zu. Die vorliegende Arbeit präsentiert überdies die fundamentalen Koordinaten, eine neue Formrepräsentation basierend auf diskreten Flächenfundamentalformen, welche auf natürliche Weise invariant unter euklidischen Bewegungen ist. Wir versehen diese Repräsentation mit einer Lie-Gruppenstruktur, die eine biinvariante Metrik und somit Riemannsche Statistik erlaubt. Darüber hinaus entwickeln wir einen einfachen, effizienten, robusten, sowie akkuraten (d.h. ohne Rückgriff auf Modellapproximationen) Löser für die Rückabbildung von den Koordinaten zur Form im Raum. Neben der statistischen Formanalyse erlaubt der beschriebene Ansatz auch Anwendungen in der Geometrieverarbeitung, insbesondere zur quasi-isometrischen Oberflächenverflachung. Der letzte Abschnitt der Arbeit befasst sich mit der Entwicklung kontinuierlicher formbasierter Erkrankungsstratifikationen, um die Krankheitsbewertung über die aktuelle klinische Praxis ordinaler Bewertungssysteme hinaus zu objektivieren. Hierzu entwickeln wir den geodesic B-score in gekrümmten Formenräumen zur Bewertung von Kniegelenksarthrose als Generalisierung des euklidischen B-scores. In diesem Rahmen beschreiben wir eine Newton-Typ-Fixpunktiteration zur Bestimmung der Projektion auf Geodätische im Formenraum. Als Anwendung zeigen wir, dass der geodätische B-score gegenüber seinem euklidischen Gegenstück eine verbesserte Vorhersageleistung hinsichtlich der Risikobewertung bezüglich einer totalen Kniearthroplastie besitzt.

In agile Production Systems Engineering (PSE), multi/disciplinary teams work concurrently on a variety of PSE artifacts in an iterative process, which can be supported by common concept and Product-Process-Resource (PPR) modeling. However, keeping track of the interactions and effects of changes across engineering disciplines on the one hand, and their implications for risk assessment on the other hand, is exceedingly difficult in such settings. To tackle this challenge and systematically co-evolve Failure Mode and Effects Analysis (FMEA) and PPR models during PSE, it is necessary to propagate and validate changes across engineering artifacts. To this end, we design and evaluate a FMEA-linked-to-PPR assets (FMEA+PPR) meta model to represent relationships between FMEA elements and PSE assets and trace their change states and dependencies in the design and validation lifecycle. Furthermore, we design and evaluate the FMEA+PPR method to efficiently re-validate FMEA models upon changes in multi-view PSE models. We evaluate the model and method in a feasibility study on the quality of a joining process, automated by a robot cell in automotive PSE. The study results indicate that the FMEA+PPR method is feasible and addresses requirements for FMEA re-validation better than alternative traditional approaches. Thereby, the FMEA+PPR approach facilitates a paradigm shift from traditional, isolated PSE and FMEA activities towards an integrated agile PSE method.

As part of the 2019 Southern oCean seAsonal Experiment (SCALE) Winter Cruise of the South African icebreaker SA Agulhas II first-year ice was sampled at the advancing outer edge of the Antarctic marginal ice zone along a 150 km-Good Hope Line transect. Ice cores were extracted from four solitary pancake ice floes of 1.83–2.95 m diameter and 0.37–0.45 m thickness as well as a 12 × 4 m2 pancake ice floe of 0.31–0.76 m thickness part of a larger consolidated pack ice domain. The ice cores were subsequently analyzed for temperature, salinity, texture, anisotropic elastic properties and compressive strength. All ice cores from both, solitary pancake ice floes and consolidated pack ice, exhibited predominantly granular textures. The vertical distributions of salinity, brine volume and mechanical properties were significantly different for the two ice types. High salinity values of 12.6 ± 4.9 PSU were found at the topmost layer of the solitary pancake ice floes but not for the consolidated pack ice. The uniaxial compressive strength for pancake ice and consolidated pack ice were determined as 2.3 ± 0.5 MPa and 4.1 ± 0.9 MPa, respectively. The Young’s and shear moduli in longitudinal core direction of solitary pancake ice were obtained as 3.7 ± 2.0 GPa and 1.3 ± 0.7 GPa, and for consolidated pack ice as 6.4 ± 1.6 GPa and 2.3 ± 0.6 GPa, respectively. Comparing Young’s and shear moduli measured in longitudinal and transverse core directions, a clear directional dependency was found, in particular for the consolidated pack ice.

[EN] Sea ice growth in the Marginal Ice Zone of the Antarctic is one of the largest annual changes on earth with a huge impact on the global climate and ecology system. The principles of sea ice growth and melting in the MIZ of the Antarctic is yet not as well researched as its polar counterpart in the north.For this study, pancake ice, consolidated ice and floe ice were analyzed with a compression test in July, October and November 2019 in the marginal ice zone of the Antarctic. Newly formed pancake ice in July showed the highest compressive strength in the bottom layer (3 MPa), whereas consolidated ice was strongest at the top (5 MPa). Consolidated ice in October and November had the highest compressive strength in a middle layer with up to 13.5 MPa, the maximum strength at the top was 3 MPa. Floe ice, consisting of destroyed pack ice, did not show a clear strength development over sea ice depth., The SCALE cruises are funded by the South African National Research Foundation (NRF) through the South African National Antarctic Programme (SANAP), with contributions from the Department of Science and Innovation and the Department of Environmental Affairs. We are very grateful to the teams that have contributed to the success of the SCALE cruise in particular under the guidance of Marcello Vichi and J¨org Schröder.

Frazil ice, consisting of loose disc-shaped ice crystals, is the very first ice that forms in the annual cycle in the marginal ice zone (MIZ) of the Antarctic. A sufficient number of frazil ice crystals forms the surface grease ice layer taking a fundamental role in the freezing processes in the MIZ. As soon as the ocean waves are sufficiently damped, a closed ice cover can form. In this brief communication we investigate the rheological properties of frazil ice, which has a crucial influence on the growth of sea ice in the MIZ. Grease ice shows shear thinning flow behavior.

Condition monitoring of critical components in wind turbines is of utmost importance to enable low cost and preventive maintenance and to minimize downtime. In this paper we propose DEEPWIND, an end-to-end condition monitoring and fault detection framework that can be implemented on resource-constrained embedded platforms. DEEPWIND exploits multi-channel convolutional neural networks to automatically extract features from sensor data without any need of human feature engineering, and utilizes the features to classify faults occurring in rotor blades of wind turbines. Experiments on a real-world dataset provided by Weidmuller Monitoring Systems GmbH reveal an average F1-score of 0.94 and thus underline the suitability of the approach for fault detection in wind turbines.

In this thesis we study strongly correlated quantum systems in extreme temperature and density conditions. A prominent example is the quark-gluon plasma produced in ultra- relativistic heavy-ion collisions. Since the degrees of freedom in the systems of interest are strongly coupled the use of non-perturbative methods is required. Our working method is lattice field theory allowing for high precision ab-initio calculations of physical quan- tities based on Monte Carlo simulations. We study QCD-like theories at finite density. This introduces the sign problem to the lattice preventing the applicability of importance sampling algorithms. Promising methods to tackle the sign problem are the Complex Langevin evolution on the one hand and Lefschetz Thimbles on the other hand. In this work we propose novel algorithmic ideas to both approaches which are put to work in simple models with a sign problem as well as in lattice gauge theories. Moreover, we in- vestigate real-time properties of quantum systems at finite temperature which is necessary for the computation of transport coefficients. To that end we conduct lattice simulations in imaginary time which are aimed at improving the spectral reconstruction of thermal features. Moreover, we study simulations directly in real-time by means of the Complex Langevin evolution equipped with variable transformations.