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Populärwissenschaftlicher Abstract: Bislang gibt es in der beobachtenden optischen Astronomie zwei verschiedene Herangehensweisen: Einerseits werden Objekte durch Kameras abbildend erfaßt, andererseits werden durch die wellenlängenabhängige Zerlegung ihres Lichtes Spektren gewonnen. Das Integral - Field - Verfahren ist eine relativ neue Technik, welche die genannten Beobachtungsmethoden vereint. Das Objektbild im Teleskopfokus wird in räumlich zerlegt und jedes Ortselement einem gemeinsamen Spektrografen zugeführt. Hierdurch wird das Objekt nicht nur zweidimensional räumlich erfaßt, sondern zusätzlich die spektrale Kompenente als dritte Dimension erhalten, weswegen das Verfahren auch als 3D-Methode bezeichnet wird. Anschaulich kann man sich das Datenresultat als eine Abbildung vorstellen, in der jeder einzelne Bildpunkt nicht mehr nur einen Intensitätswert enthält, sondern gleich ein ganzes Spektrum. Diese Technik ermöglicht es, ausgedehnte Objekte im Unterschied zu gängigen Spaltspektrografen komplett zu erfassen. Die besondere Stärke der Methode ist die Möglichkeit, die Hintergrundkontamination der unmittelbaren Umgebung des Objektes zu erfassen und in der Auswertung zu berücksichtigen. Durch diese Fähigkeit erscheint die 3D-Methode prädestiniert für den durch moderne Großteleskope erschlossenen Bereich der extragalaktischen Stellarastronomie. Die detaillierte Untersuchung aufgelöster stellare Populationen in nahegelegenen Galaxien ist erst seit kurzer Zeit dank der Fortschritte mit modernen Grossteleskopen und fortschrittlicher Instrumentierung möglich geworden. Wegen der Bedeutung für die Entstehung und Evolution von Galaxien werden diese Arbeiten zukünftig weiter an Bedeutung gewinnen. In der vorliegenden Arbeit wurde die Integral-Field-Spektroskopie an zwei planetarischen Nebeln in der nächstgelegenen großen Spiralgalaxie M31 (NGC 224) getestet, deren Helligkeiten und Koordinaten aus einer Durchmusterung vorlagen. Hierzu wurden Beobachtungen mit dem MPFS-Instrument am russischen 6m - Teleskop in Selentschuk/Kaukasus sowie mit INTEGRAL/WYFFOS am englischen William-Herschel-Teleskop auf La Palma gewonnen. Ein überraschendes Ergebnis war, daß eins der beiden Objekte falsch klassifiziert wurde. Sowohl die meßbare räumliche Ausdehnung des Objektes als auch das spektrale Erscheinungsbild schlossen die Identität mit einem planetarischen Nebel aus. Mit hoher Wahrscheinlichkeit handelt es sich um einen Supernovaüberrest, zumal im Rahmen der Fehler an gleicher Stelle eine vom Röntgensatelliten ROSAT detektierte Röntgenquelle liegt. Die in diesem Projekt verwendeten Integral-Field-Instrumente wiesen zwei verschiedene Bauweisen auf, die sich miteinander vergleichen ließen. Ein Hauptkritikpunkt der verwendeten Instrumente war ihre geringe Lichtausbeute. Die gesammelten Erfahrung fanden Eingang in das Konzept des derzeit in Potsdam in der Fertigung befindlichen 3D-Instruments PMAS (Potsdamer Multi - Apertur - Spektrophotometer), welcher zunächst für das 3.5m-Teleskop des Calar - Alto - Observatoriums in Südspanien vorgesehen ist. Um die Effizienz dieses Instrumentes zu verbessern, wurde in dieser Arbeit die Kopplung der zum Bildrasterung verwendeten Optik zu den Lichtleitfasern im Labor untersucht. Die Untersuchungen zur Maximierung von Lichtausbeute und Stabilität zeigen, daß sich die Effizienz durch Auswahl einer geeigneten Koppelmethode um etwa 20 Prozent steigern lässt.
Hepcidin-25 (Hep-25) plays a crucial role in the control of iron homeostasis. Since the dysfunction of the hepcidin pathway leads to multiple diseases as a result of iron imbalance, hepcidin represents a potential target for the diagnosis and treatment of disorders of iron metabolism. Despite intense research in the last decade targeted at developing a selective immunoassay for iron disorder diagnosis and treatment and better understanding the ferroportin-hepcidin interaction, questions remain. The key to resolving these underlying questions is acquiring exact knowledge of the 3D structure of native Hep-25. Since it was determined that the N-terminus, which is responsible for the bioactivity of Hep-25, contains a small Cu(II)-binding site known as the ATCUN motif, it was assumed that the Hep-25-Cu(II) complex is the native, bioactive form of the hepcidin. This structure has thus far not been elucidated in detail. Owing to the lack of structural information on metal-bound Hep-25, little is known about its possible biological role in iron metabolism. Therefore, this work is focused on structurally characterizing the metal-bound Hep-25 by NMR spectroscopy and molecular dynamics simulations. For the present work, a protocol was developed to prepare and purify properly folded Hep-25 in high quantities. In order to overcome the low solubility of Hep-25 at neutral pH, we introduced the C-terminal DEDEDE solubility tag. The metal binding was investigated through a series of NMR spectroscopic experiments to identify the most affected amino acids that mediate metal coordination. Based on the obtained NMR data, a structural calculation was performed in order to generate a model structure of the Hep-25-Ni(II) complex. The DEDEDE tag was excluded from the structural calculation due to a lack of NMR restraints. The dynamic nature and fast exchange of some of the amide protons with solvent reduced the overall number of NMR restraints needed for a high-quality structure. The NMR data revealed that the 20 Cterminal Hep-25 amino acids experienced no significant conformational changes, compared to published results, as a result of a pH change from pH 3 to pH 7 and metal binding. A 3D model of the Hep-25-Ni(II) complex was constructed from NMR data recorded for the hexapeptideNi(II) complex and Hep-25-DEDEDE-Ni(II) complex in combination with the fixed conformation of 19 C-terminal amino acids. The NMR data of the Hep-25-DEDEDE-Ni(II) complex indicates that the ATCUN motif moves independently from the rest of the structure. The 3D model structure of the metal-bound Hep-25 allows for future works to elucidate hepcidin’s interaction with its receptor ferroportin and should serve as a starting point for the development of antibodies with improved selectivity.
3D from 2D touch
(2013)
While interaction with computers used to be dominated by mice and keyboards, new types of sensors now allow users to interact through touch, speech, or using their whole body in 3D space. These new interaction modalities are often referred to as "natural user interfaces" or "NUIs." While 2D NUIs have experienced major success on billions of mobile touch devices sold, 3D NUI systems have so far been unable to deliver a mobile form factor, mainly due to their use of cameras. The fact that cameras require a certain distance from the capture volume has prevented 3D NUI systems from reaching the flat form factor mobile users expect. In this dissertation, we address this issue by sensing 3D input using flat 2D sensors. The systems we present observe the input from 3D objects as 2D imprints upon physical contact. By sampling these imprints at very high resolutions, we obtain the objects' textures. In some cases, a texture uniquely identifies a biometric feature, such as the user's fingerprint. In other cases, an imprint stems from the user's clothing, such as when walking on multitouch floors. By analyzing from which part of the 3D object the 2D imprint results, we reconstruct the object's pose in 3D space. While our main contribution is a general approach to sensing 3D input on 2D sensors upon physical contact, we also demonstrate three applications of our approach. (1) We present high-accuracy touch devices that allow users to reliably touch targets that are a third of the size of those on current touch devices. We show that different users and 3D finger poses systematically affect touch sensing, which current devices perceive as random input noise. We introduce a model for touch that compensates for this systematic effect by deriving the 3D finger pose and the user's identity from each touch imprint. We then investigate this systematic effect in detail and explore how users conceptually touch targets. Our findings indicate that users aim by aligning visual features of their fingers with the target. We present a visual model for touch input that eliminates virtually all systematic effects on touch accuracy. (2) From each touch, we identify users biometrically by analyzing their fingerprints. Our prototype Fiberio integrates fingerprint scanning and a display into the same flat surface, solving a long-standing problem in human-computer interaction: secure authentication on touchscreens. Sensing 3D input and authenticating users upon touch allows Fiberio to implement a variety of applications that traditionally require the bulky setups of current 3D NUI systems. (3) To demonstrate the versatility of 3D reconstruction on larger touch surfaces, we present a high-resolution pressure-sensitive floor that resolves the texture of objects upon touch. Using the same principles as before, our system GravitySpace analyzes all imprints and identifies users based on their shoe soles, detects furniture, and enables accurate touch input using feet. By classifying all imprints, GravitySpace detects the users' body parts that are in contact with the floor and then reconstructs their 3D body poses using inverse kinematics. GravitySpace thus enables a range of applications for future 3D NUI systems based on a flat sensor, such as smart rooms in future homes. We conclude this dissertation by projecting into the future of mobile devices. Focusing on the mobility aspect of our work, we explore how NUI devices may one day augment users directly in the form of implanted devices.
Shape change is a fundamental process occurring in biological tissues during embryonic development and regeneration of tissues and organs. This process is regulated by cells that are constrained within a complex environment of biochemical and physical cues. The spatial constraint due to geometry has a determining role on tissue mechanics and the spatial distribution of force patterns that, in turn, influences the organization of the tissue structure. An understanding of the underlying principles of tissue organization may have wide consequences for the understanding of healing processes and the development of organs and, as such, is of fundamental interest for the tissue engineering community.
This thesis aims to further our understanding of how the collective behaviour of cells is influenced by the 3D geometry of the environment. Previous research studying the role of geometry on tissue growth has mainly focused either on flat surfaces or on substrates where at least one of the principal curvatures is zero. In the present work, tissue growth from MC3T3-E1 pre-osteoblasts was investigated on surfaces of controlled mean curvature.
One key aspect of this thesis was the development of substrates of controlled mean curvature and their visualization in 3D. It was demonstrated that substrates of controlled mean curvature suitable for cell culture can be fabricated using liquid polymers and surface tension effects.
Using these substrates, it was shown that the mean surface curvature has a strong impact on the rate of tissue growth and on the organization of the tissue structure. It was thereby not only demonstrated that the amount of tissue produced (i.e. growth rates) by the cells depends on the mean curvature of the substrate but also that the tissue surface behaves like a viscous fluid with an equilibrium shape governed by the Laplace-Young-law. It was observed that more tissue was formed on highly concave surfaces compared to flat or convex surfaces.
Motivated by these observations, an analytical model was developed, where the rate of tissue growth is a function of the mean curvature, which could successfully describe the growth kinetics. This model was also able to reproduce the growth kinetics of previous experiments where tissues have been cultured in straight-sided prismatic pores.
A second part of this thesis focuses on the tissue structure, which influences the mechanical properties of the mature bone tissue. Since the extracellular matrix is produced by the cells, the cell orientation has a strong impact on the direction of the tissue fibres. In addition, it was recently shown that some cell types exhibit collective alignment similar to liquid crystals.
Based on this observation, a computational model of self-propelled active particles was developed to explore in an abstract manner how the collective behaviour of cells is influenced by 3D curvature. It was demonstrated that the 3D curvature has a strong impact on the self-organization of active particles and gives, therefore, first insights into the principles of self-organization of cells on curved surfaces.
Today, near-surface investigations are frequently conducted using non-destructive or minimally invasive methods of applied geophysics, particularly in the fields of civil engineering, archaeology, geology, and hydrology. One field that plays an increasingly central role in research and engineering is the examination of sedimentary environments, for example, for characterizing near-surface groundwater systems. A commonly employed method in this context is ground-penetrating radar (GPR). In this technique, short electromagnetic pulses are emitted into the subsurface by an antenna, which are then reflected, refracted, or scattered at contrasts in electromagnetic properties (such as the water table). A receiving antenna records these signals in terms of their amplitudes and travel times. Analysis of the recorded signals allows for inferences about the subsurface, such as the depth of the groundwater table or the composition and characteristics of near-surface sediment layers. Due to the high resolution of the GPR method and continuous technological advancements, GPR data acquisition is increasingly performed in three-dimensional (3D) fashion today.
Despite the considerable temporal and technical efforts involved in data acquisition and processing, the resulting 3D data sets (providing high-resolution images of the subsurface) are typically interpreted manually. This is generally an extremely time-consuming analysis step. Therefore, representative 2D sections highlighting distinctive reflection structures are often selected from the 3D data set. Regions showing similar structures are then grouped into so-called radar facies. The results obtained from 2D sections are considered representative of the entire investigated area. Interpretations conducted in this manner are often incomplete and highly dependent on the expertise of the interpreters, making them generally non-reproducible.
A promising alternative or complement to manual interpretation is the use of GPR attributes. Instead of using the recorded data directly, derived quantities characterizing distinctive reflection structures in 3D are applied for interpretation. Using various field and synthetic data sets, this thesis investigates which attributes are particularly suitable for this purpose. Additionally, the study demonstrates how selected attributes can be utilized through specific processing and classification methods to create 3D facies models. The ability to generate attribute-based 3D GPR facies models allows for partially automated and more efficient interpretations in the future. Furthermore, the results obtained in this manner describe the subsurface in a reproducible and more comprehensive manner than what has typically been achievable through manual interpretation methods.
The study of outcrop modeling is located at the interface between two fields of expertise, Sedimentology and Computing Geoscience, which respectively investigates and simulates geological heterogeneity observed in the sedimentary record. During the last past years, modeling tools and techniques were constantly improved. In parallel, the study of Phanerozoic carbonate deposits emphasized the common occurrence of a random facies distribution along single depositional domain. Although both fields of expertise are intrinsically linked during outcrop simulation, their respective advances have not been combined in literature to enhance carbonate modeling studies. The present study re-examines the modeling strategy adapted to the simulation of shallow-water carbonate systems, based on a close relationship between field sedimentology and modeling capabilities. In the present study, the evaluation of three commonly used algorithms Truncated Gaussian Simulation (TGSim), Sequential Indicator Simulation (SISim), and Indicator Kriging (IK), were performed for the first time using visual and quantitative comparisons on an ideally suited carbonate outcrop. The results show that the heterogeneity of carbonate rocks cannot be fully simulated using one single algorithm. The operating mode of each algorithm involves capabilities as well as drawbacks that are not capable to match all field observations carried out across the modeling area. Two end members in the spectrum of carbonate depositional settings, a low-angle Jurassic ramp (High Atlas, Morocco) and a Triassic isolated platform (Dolomites, Italy), were investigated to obtain a complete overview of the geological heterogeneity in shallow-water carbonate systems. Field sedimentology and statistical analysis performed on the type, morphology, distribution, and association of carbonate bodies and combined with palaeodepositional reconstructions, emphasize similar results. At the basin scale (x 1 km), facies association, composed of facies recording similar depositional conditions, displays linear and ordered transitions between depositional domains. Contrarily, at the bedding scale (x 0.1 km), individual lithofacies type shows a mosaic-like distribution consisting of an arrangement of spatially independent lithofacies bodies along the depositional profile. The increase of spatial disorder from the basin to bedding scale results from the influence of autocyclic factors on the transport and deposition of carbonate sediments. Scale-dependent types of carbonate heterogeneity are linked with the evaluation of algorithms in order to establish a modeling strategy that considers both the sedimentary characteristics of the outcrop and the modeling capabilities. A surface-based modeling approach was used to model depositional sequences. Facies associations were populated using TGSim to preserve ordered trends between depositional domains. At the lithofacies scale, a fully stochastic approach with SISim was applied to simulate a mosaic-like lithofacies distribution. This new workflow is designed to improve the simulation of carbonate rocks, based on the modeling of each scale of heterogeneity individually. Contrarily to simulation methods applied in literature, the present study considers that the use of one single simulation technique is unlikely to correctly model the natural patterns and variability of carbonate rocks. The implementation of different techniques customized for each level of the stratigraphic hierarchy provides the essential computing flexibility to model carbonate systems. Closer feedback between advances carried out in the field of Sedimentology and Computing Geoscience should be promoted during future outcrop simulations for the enhancement of 3-D geological models.