Variational Methods for the Estimation of Transport Fields with Application to the Recovery of Physics-Based Optical Flows Across Boundaries

In this thesis we develop a method for the estimation of the flow behaviour of an incom- pressible fluid based on observations of the brightness intensity of a transported visible substance which does not influence the flow. The observations are given in a subregion of the flow as a sequence of discrete images with in- and outflow across the image boundaries. The resulting mathematical problem is ill-posed and has to be regularised with information of the underlying fluid flow model. We consider a constrained optimisation problem, namely the minimisation of a tracking type data term for the brightness distribution and a regularisation term subject to a system of weakly coupled partial differential equations. The system consists of the time- dependent incompressible Navier-Stokes equations coupled by the velocity vector field to a convection-diffusion equation, which describes the transport of brightness patterns in the image sequence. Due to the flow across the boundaries of the computational domain we solve a boundary identification problem. The usage of (strong) Dirichlet boundary controls for this purpose leads to theoretical and numerical complications, so that we will instead use Robin-type controls, which allow for a more convenient theoretical and numerical framework. We will prove well-posedness and investigate the functionality of the proposed approach by means of numerical examples. Furthermore, we discuss the connection to Dirichlet-control problems, e. g. the approximation of Dirichlet-controls by the so-called penalised Neumann method, which is based on the Robin-type controls for a varying penalty parameter. We will show via numerical tests that Robin-type controls are suitable for the identifi- cation of the correct fluid flow. Moreover, the examples indicate that the underlying physical model used for the regularisation influences the flow reconstruction process. Thus appropriate knowledge of the model is essential, e. g. the viscosity parameter. For a time- independent example we will present a heuristic, which, beside the boundary identification, automatically evaluates the viscosity in case the parameter is unknown. The developed physics-based optical flow estimation approach is finally used for the data set of a prototypical application. The background of the application is the approximation of horizontal wind fields in sparsely populated areas like desert regions. A sequence of satellite images documenting the brightness intensity of an observable substance distributed by the wind (e. g. dust plumes) is thereby assumed to be the only available data. Wind field information is for example needed to simulate the distribution of other, not directly observ- able, substances in the lower atmosphere. For the prototypical example we compute a high quality reconstruction of the underlying fluid flow by a (discrete) sequence of consecutive spatially distributed brightness intensities. Thereby, we compare three different models (heat equation, Stokes system and the original fluid flow model) in the reconstruction process and show that using as much model knowledge as possible is essential for a good reconstruction result

CD19 expression in pediatric patients with relapsed/refractory B-cell precursor acute lymphoblastic leukemia pre- and post-treatment with blinatumomab.

AbstractBlinatumomab is a BiTE® (bispecific T‐cell engager) immuno‐oncology therapy, which has demonstrated significant activity in patients with relapsed or refractory B‐cell precursor acute lymphoblastic leukemia (R/R B‐ALL); however, a subset of patients relapse. Monitoring expression of cluster of differentiation (CD)19 in relapsed patients is critical to inform sequencing of subsequent therapies. The expression of CD19 in 59 pediatric patients with R/R B‐ALL was analyzed on the day of diagnosis of R/R B‐ALL and on days 15 and 29 of cycle 1 of blinatumomab. Most patients treated with one cycle of blinatumomab retained expression of CD19, and would therefore be eligible for subsequent anti‐CD19 CAR T‐cell therapy

Radioprotective effect of lidocaine on neurotransmitter agonist-induced secretion in irradiated salivary glands.

Previously we verified the radioprotective effect of lidocaine on the function and ultrastructure of salivary glands in rabbits. However, the underlying mechanism of lidocaine's radioprotective effect is unknown. We hypothesized that lidocaine, as a membrane stabilization agent, has a protective effect on intracellular neuroreceptor-mediated signaling and hence can help preserve the secretory function of salivary glands during radiotherapy. Rabbits were irradiated with or without pretreatment with lidocaine before receiving fractionated radiation to a total dose of 35 Gy. Sialoscintigraphy and saliva total protein assay were performed before radiation and 1 week after the last radiation fraction. Isolated salivary gland acini were stimulated with either carbachol or adrenaline. Ca(2+) influx in response to the stimulation with these agonists was measured using laser scanning confocal microscopy. The uptake of activity and the excretion fraction of the parotid glands were significantly reduced after radiation, but lidocaine had a protective effect. Saliva total protein concentration was not altered after radiation. For isolated acini, Ca(2+) influx in response to stimulation with carbachol, but not adrenaline, was impaired after irradiation; lidocaine pretreatment attenuated this effect. Lidocaine has a radioprotective effect on the capacity of muscarinic agonist-induced water secretion in irradiated salivary glands

The Impact of Various Reactive Oxygen Species on the Formation of Neutrophil Extracellular Traps

The formation of neutrophil extracellular traps (NETs) depends on the generation of reactive oxygen species (ROS). Previous studies revealed that both NADPH oxidase and myeloperoxidase (MPO) are required for NET release. However, the contribution of various ROS as well as the role of mitochondria-derived ROS has not been addressed so far. In the present study we aimed to investigate in a systematic and comprehensive manner the contribution of various ROS and ROS-generating pathways to the PMA-induced NET release. By using specific inhibitors, the role of both NADPH oxidase- and mitochondria-derived ROS as well as the contribution of superoxide dismutase (SOD) and MPO on the NET release was assessed. We could demonstrate that NADPH oxidase function is crucial for the formation of NETs. In addition, we could clearly show the involvement of MPO-derived ROS in NET release. Our results, however, did not provide evidence for the role of SOD- or mitochondria-derived ROS in NET formation

Intelligente Gebäudesysteme: eingebettete Intelligenz, Integration durch Vernetzung, neue Nutzeffekte durch Systemfunktionen

In intelligente Gebäudesysteme wird Informationstechnik in systematisch geplanter Form eingesetzt, um die Eigenschaften von Gebäuden in den Bereichen Betriebskosten, Sicherheit und Flexibilität begl. der Nutzung zu verbessern. So müssen Gebäude während ihres Lebenszyklus Nutzer- und Nutzungsänderungen bewältigen. Dies gilt nicht nur für Zweckbauten, sondern auch für Wohngebäude, die früher auf den klassischen Familientyp (4-köpfige Familie) hin optimiert wurden. Heute ist mehr eine nutzungsneutrale, funktionsoptimierbare Gestaltung von Gebäuden gefordert. Die Kleinfamilie löst sich mehr und mehr zugunsten anderer Haushaltsformen auf, ein Gebäude soll auch für Single- oder Zweipersonenhaushalte gut geeignet sein, es soll eine optimale Verbindung von Wohnen und Arbeiten zulassen oder später älteren, pflegebedürftigen Personen ein möglichst langes selbstbestimmtes Leben ermöglichen. Das System intelligentes Gebäude besteht aus der Gebäudehülle und einer Kommunikations- und Informationsverarbeitungs-Infrastruktur, zu der alle im Gebäude eingebauten Geräte gehören, die zum Betrieb des Gebäudes erforderlich sind. Die Koordination der Funktion von Einzelkomponenten erfolgt dabei weniger durch den Nutzer, sondern durch eine spezielle Software, die auf die Knoten im System verteilt ist. Diese Architektur ist Grundlage der Verbesserung der Gebäudeeigenschaften in den genannten Bereichen, die möglichen Funktionen und die damit verbundene Flexibilität in der Nutzung wird mit dem Ausdruck Intelligenz des Gebäudes assoziiiert. Der Beitrag versucht zunächst, auf Basis der Konzepte und Erfahrungen des Innovationszentrums Intelligentes Haus Duisburg, kurz inHaus, und des vom Fraunhofer-Institut IMS seit 1993 gewonnenen einschlägigen Know-Hows einen Überblick über den aktuellen Entwicklungsstand bei Systemintegrations-Technologien und -funktionen für ganzheitliche, intelligente Haus- und Gebäudesysteme zu geben, insbesondere für den Bereich der integrierten Bedienung und der Nutzung der Internet-Anbindun

Predicting Disease-Gene Associations using Cross-Document Graph-based Features

ter Horst H, Hartung M, Klinger R, Zwick M, Cimiano P. Predicting Disease-Gene Associations using Cross-Document Graph-based Features. Bielefeld: Bielefeld University; 2016.In the context of personalized medicine, text mining methods pose an interesting option for identifying disease-gene associations, as they can be used to generate novel links between diseases and genes which may complement knowledge from structured databases. The most straightforward approach to extract such links from text is to rely on a simple assumption postulating an association between all genes and diseases that co-occur within the same document. However, this approach (i) tends to yield a number of spurious associations, (ii) does not capture different relevant types of associations, and (iii) is incapable of aggregating knowledge that is spread across documents. Thus, we propose an approach in which disease-gene co-occurrences and gene-gene interactions are represented in an RDF graph. A machine learning-based classifier is trained that incorporates features extracted from the graph to separate disease-gene pairs into valid disease-gene associations and spurious ones. On the manually curated Genetic Testing Registry, our approach yields a 30 points increase in F 1 score over a plain co-occurrence baseline

Ranking right-wing extremist social media profiles by similarity to democratic and extremist groups

Hartung M, Klinger R, Schmidtke F, Vogel L. Ranking right-wing extremist social media profiles by similarity to democratic and extremist groups. In: Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA). Stroudsburg PA: Association for Computational Linguistics; 2017: 24-33.Social media are used by an increasing number of political actors. A small subset of these is interested in pursuing extrem- ist motives such as mobilization, recruiting or radicalization activities. In order to counteract these trends, online providers and state institutions reinforce their monitoring efforts, mostly relying on manual workflows. We propose a machine learning approach to support manual attempts towards identifying right-wing extremist content in German Twitter profiles. Based on a fine-grained conceptualization of right- wing extremism, we frame the task as ranking each individual profile on a continuum spanning different degrees of right-wing extremism, based on a nearest neighbour approach. A quantitative evaluation reveals that our ranking model yields robust performance (up to 0.81 F1 score) when being used for predicting discrete class labels. At the same time, the model provides plausible continuous ranking scores for a small sample of borderline cases at the division of right-wing extremism and New Right political movements