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The Antarctic ice sheet is the largest freshwater reservoir worldwide. If it were to melt completely, global sea levels would rise by about 58 m. Calculation of projections of the Antarctic contribution to sea level rise under global warming conditions is an ongoing effort which
yields large ranges in predictions. Among the reasons for this are uncertainties related to the physics of ice sheet modeling. These
uncertainties include two processes that could lead to runaway ice retreat: the Marine Ice Sheet Instability (MISI), which causes rapid grounding line retreat on retrograde bedrock, and the Marine Ice Cliff Instability (MICI), in which tall ice cliffs become unstable and calve off, exposing even taller ice cliffs.
In my thesis, I investigated both marine instabilities (MISI and MICI) using the Parallel Ice Sheet Model (PISM), with a focus on MICI.
In recent decades, astronomy has seen a boom in large-scale stellar surveys of the Galaxy. The detailed information obtained about millions of individual stars in the Milky Way is bringing us a step closer to answering one of the most outstanding questions in astrophysics: how do galaxies form and evolve? The Milky Way is the only galaxy where we can dissect many stars into their high-dimensional chemical composition and complete phase space, which analogously as fossil records can unveil the past history of the genesis of the Galaxy. The processes that lead to large structure formation, such as the Milky Way, are critical for constraining cosmological models; we call this line of study Galactic archaeology or near-field cosmology.
At the core of this work, we present a collection of efforts to chemically and dynamically characterise the disks and bulge of our Galaxy. The results we present in this thesis have only been possible thanks to the advent of the Gaia astrometric satellite, which has revolutionised the field of Galactic archaeology by precisely measuring the positions, parallax distances and motions of more than a billion stars. Another, though not less important, breakthrough is the APOGEE survey, which has observed spectra in the near-infrared peering into the dusty regions of the Galaxy, allowing us to determine detailed chemical abundance patterns in hundreds of thousands of stars. To accurately depict the Milky Way structure, we use and develop the Bayesian isochrone fitting tool/code called StarHorse; this software can predict stellar distances, extinctions and ages by combining astrometry, photometry and spectroscopy based on stellar evolutionary models. The StarHorse code is pivotal to calculating distances where Gaia parallaxes alone cannot allow accurate estimates.
We show that by combining Gaia, APOGEE, photometric surveys and using StarHorse, we can produce a chemical cartography of the Milky way disks from their outermost to innermost parts. Such a map is unprecedented in the inner Galaxy. It reveals a continuity of the bimodal chemical pattern previously detected in the solar neighbourhood, indicating two populations with distinct formation histories. Furthermore, the data reveals a chemical gradient within the thin disk where the content of 𝛼-process elements and metals is higher towards the centre. Focusing on a sample in the inner MW we confirm the extension of the chemical duality to the innermost regions of the Galaxy. We find stars with bar shape orbits to show both high- and low-𝛼 abundances, suggesting the bar formed by secular evolution trapping stars that already existed. By analysing the chemical orbital space of the inner Galactic regions, we disentangle the multiple populations that inhabit this complex region. We reveal the presence of the thin disk, thick disk, bar, and a counter-rotating population, which resembles the outcome of a perturbed proto-Galactic disk. Our study also finds that the inner Galaxy holds a high quantity of super metal-rich stars up to three times solar suggesting it is a possible repository of old super-metal-rich stars found in the solar neighbourhood.
We also enter into the complicated task of deriving individual stellar ages. With StarHorse, we calculate the ages of main-sequence turn-off and sub-giant stars for several public spectroscopic surveys. We validate our results by investigating linear relations between chemical abundances and time since the 𝛼 and neutron capture elements are sensitive to age as a reflection of the different enrichment timescales of these elements. For further study of the disks in the solar neighbourhood, we use an unsupervised machine learning algorithm to delineate a multidimensional separation of chrono-chemical stellar groups revealing the chemical thick disk, the thin disk, and young 𝛼-rich stars. The thick disk is shown to have a small age dispersion indicating its fast formation contrary to the thin disk that spans a wide range of ages.
With groundbreaking data, this thesis encloses a detailed chemo-dynamical view of the disk and bulge of our Galaxy. Our findings on the Milky Way can be linked to the evolution of high redshift disk galaxies, helping to solve the conundrum of galaxy formation.
In this Thesis, the properties of aqueous hemicellulose polysaccharides are investigated using computer simulations. The high swelling capacity of materials composed of these molecules allows the generation of directed motion in plant materials entirely controlled by water uptake.
To explore the molecular origin of this swelling capacity, a computational model with atomistic resolution for hemicellulose polysaccharides is build and validated in comparison with experiments. Using this model, simulations of small polysaccharides are employed to gain an understanding of the interactions of these molecules with water, the influence of water on their conformational freedom, and the swelling capacity quantified in terms of osmotic pressure. It is revealed that the branched hemicellulose polysaccharides show different hydration characteristics compared to linear polysaccharides.
To study swelling properties on length and time scales that exceed the limitations imposed by atomistic simulations, a procedure to obtain transferable coarse-grain models is developed. The transferability of the coarse-grain models over both different degrees of polymerization as well as different solute concentrations is demonstrated. Therefore, the procedure allows the construction of large coarse-grained systems based on small atomistic reference systems. Finally, the coarse-grain model is applied to demonstrate that linear and branched polysaccharides show a different swelling behavior when coupled to a water bath.
The cytoskeleton is an essential component of living cells. It is composed of different types of protein filaments that form complex, dynamically rearranging, and interconnected networks. The cytoskeleton serves a multitude of cellular functions which further depend on the cell context. In animal cells, the cytoskeleton prominently shapes the cell's mechanical properties and movement. In plant cells, in contrast, the presence of a rigid cell wall as well as their larger sizes highlight the role of the cytoskeleton in long-distance intracellular transport. As it provides the basis for cell growth and biomass production, cytoskeletal transport in plant cells is of direct environmental and economical relevance. However, while knowledge about the molecular details of the cytoskeletal transport is growing rapidly, the organizational principles that shape these processes on a whole-cell level remain elusive.
This thesis is devoted to the following question: How does the complex architecture of the plant cytoskeleton relate to its transport functionality? The answer requires a systems level perspective of plant cytoskeletal structure and transport. To this end, I combined state-of-the-art confocal microscopy, quantitative digital image analysis, and mathematically powerful, intuitively accessible graph-theoretical approaches.
This thesis summarizes five of my publications that shed light on the plant cytoskeleton as a transportation network: (1) I developed network-based frameworks for accurate, automated quantification of cytoskeletal structures, applicable in, e.g., genetic or chemical screens; (2) I showed that the actin cytoskeleton displays properties of efficient transport networks, hinting at its biological design principles; (3) Using multi-objective optimization, I demonstrated that different plant cell types sustain cytoskeletal networks with cell-type specific and near-optimal organization; (4) By investigating actual transport of organelles through the cell, I showed that properties of the actin cytoskeleton are predictive of organelle flow and provided quantitative evidence for a coordination of transport at a cellular level; (5) I devised a robust, optimization-based method to identify individual cytoskeletal filaments from a given network representation, allowing the investigation of single filament properties in the network context. The developed methods were made publicly available as open-source software tools.
Altogether, my findings and proposed frameworks provide quantitative, system-level insights into intracellular transport in living cells. Despite my focus on the plant cytoskeleton, the established combination of experimental and theoretical approaches is readily applicable to different organisms. Despite the necessity of detailed molecular studies, only a complementary, systemic perspective, as presented here, enables both understanding of cytoskeletal function in its evolutionary context as well as its future technological control and utilization.
The two hallmark features of Brownian motion are the linear growth < x2(t)> = 2Ddt of the mean squared displacement (MSD) with diffusion coefficient D in d spatial dimensions, and the Gaussian distribution of displacements. With the increasing complexity of the studied systems deviations from these two central properties have been unveiled over the years. Recently, a large variety of systems have been reported in which the MSD exhibits the linear growth in time of Brownian (Fickian) transport, however, the distribution of displacements is pronouncedly non-Gaussian (Brownian yet non-Gaussian, BNG). A similar behaviour is also observed for viscoelastic-type motion where an anomalous trend of the MSD, i.e., <x2(t)> ~ ta, is combined with a priori unexpected non-Gaussian distributions (anomalous yet non-Gaussian, ANG). This kind of behaviour observed in BNG and ANG diffusions has been related to the presence of heterogeneities in the systems and a common approach has been established to address it, that is, the random diffusivity approach.
This dissertation explores extensively the field of random diffusivity models. Starting from a chronological description of all the main approaches used as an attempt of describing BNG and ANG diffusion, different mathematical methodologies are defined for the resolution and study of these models. The processes that are reported in this work can be classified in three subcategories, i) randomly-scaled Gaussian processes, ii) superstatistical models and iii) diffusing diffusivity models, all belonging to the more general class of random diffusivity models. Eventually, the study focuses more on BNG diffusion, which is by now well-established and relatively well-understood. Nevertheless, many examples are discussed for the description of ANG diffusion, in order to highlight the possible scenarios which are known so far for the study of this class of processes.
The second part of the dissertation deals with the statistical analysis of random diffusivity processes. A general description based on the concept of moment-generating function is initially provided to obtain standard statistical properties of the models. Then, the discussion moves to the study of the power spectral analysis and the first passage statistics for some particular random diffusivity models. A comparison between the results coming from the random diffusivity approach and the ones for standard Brownian motion is discussed. In this way, a deeper physical understanding of the systems described by random diffusivity models is also outlined.
To conclude, a discussion based on the possible origins of the heterogeneity is sketched, with the main goal of inferring which kind of systems can actually be described by the random diffusivity approach.
When Galactic microlensing events of stars are observed, one usually measures a symmetric light curve corresponding to a single lens, or an asymmetric light curve, often with caustic crossings, in the case of a binary lens system. In principle, the fraction of binary stars at a certain separation range can be estimated based on the number of measured microlensing events. However, a binary system may produce a light curve which can be fitted well as a single lens light curve, in particullary if the data sampling is poor and the errorbars are large. We investigate what fraction of microlensing events produced by binary stars for different separations may be well fitted by and hence misinterpreted as single lens events for various observational conditions. We find that this fraction strongly depends on the separation of the binary components, reaching its minimum at between 0.6 and 1.0 Einstein radius, where it is still of the order of 5% The Einstein radius is corresponding to few A.U. for typical Galactic microlensing scenarios. The rate for misinterpretation is higher for short microlensing events lasting up to few months and events with smaller maximum amplification. For fixed separation it increases for binaries with more extreme mass ratios. Problem of degeneracy in photometric light curve solution between binary lens and binary source microlensing events was studied on simulated data, and data observed by the PLANET collaboration. The fitting code BISCO using the PIKAIA genetic algorithm optimizing routine was written for optimizing binary-source microlensing light curves observed at different sites, in I, R and V photometric bands. Tests on simulated microlensing light curves show that BISCO is successful in finding the solution to a binary-source event in a very wide parameter space. Flux ratio method is suggested in this work for breaking degeneracy between binary-lens and binary-source photometric light curves. Models show that only a few additional data points in photometric V band, together with a full light curve in I band, will enable breaking the degeneracy. Very good data quality and dense data sampling, combined with accurate binary lens and binary source modeling, yielded the discovery of the lowest-mass planet discovered outside of the Solar System so far, OGLE-2005-BLG-390Lb, having only 5.5 Earth masses. This was the first observed microlensing event in which the degeneracy between a planetary binary-lens and an extreme flux ratio binary-source model has been successfully broken. For events OGLE-2003-BLG-222 and OGLE-2004-BLG-347, the degeneracy was encountered despite of very dense data sampling. From light curve modeling and stellar evolution theory, there was a slight preference to explain OGLE-2003-BLG-222 as a binary source event, and OGLE-2004-BLG-347 as a binary lens event. However, without spectra, this degeneracy cannot be fully broken. No planet was found so far around a white dwarf, though it is believed that Jovian planets should survive the late stages of stellar evolution, and that white dwarfs will retain planetary systems in wide orbits. We want to perform high precision astrometric observations of nearby white dwarfs in wide binary systems with red dwarfs in order to find planets around white dwarfs. We selected a sample of observing targets (WD-RD binary systems, not published yet), which can possibly have planets around the WD component, and modeled synthetic astrometric orbits which can be observed for these targets using existing and future astrometric facilities. Modeling was performed for the astrometric accuracy of 0.01, 0.1, and 1.0 mas, separation between WD and planet of 3 and 5 A.U., binary system separation of 30 A.U., planet masses of 10 Earth masses, 1 and 10 Jupiter masses, WD mass of 0.5M and 1.0 Solar masses, and distances to the system of 10, 20 and 30 pc. It was found that the PRIMA facility at the VLTI will be able to detect planets around white dwarfs once it is operating, by measuring the astrometric wobble of the WD due to a planet companion, down to 1 Jupiter mass. We show for the simulated observations that it is possible to model the orbits and find the parameters describing the potential planetary systems.
Theory of mRNA degradation
(2012)
One of the central themes of biology is to understand how individual cells achieve a high fidelity in gene expression. Each cell needs to ensure accurate protein levels for its proper functioning and its capability to proliferate. Therefore, complex regulatory mechanisms have evolved in order to render the expression of each gene dependent on the expression level of (all) other genes. Regulation can occur at different stages within the framework of the central dogma of molecular biology. One very effective and relatively direct mechanism concerns the regulation of the stability of mRNAs. All organisms have evolved diverse and powerful mechanisms to achieve this. In order to better comprehend the regulation in living cells, biochemists have studied specific degradation mechanisms in detail. In addition to that, modern high-throughput techniques allow to obtain quantitative data on a global scale by parallel analysis of the decay patterns of many different mRNAs from different genes. In previous studies, the interpretation of these mRNA decay experiments relied on a simple theoretical description based on an exponential decay. However, this does not account for the complexity of the responsible mechanisms and, as a consequence, the exponential decay is often not in agreement with the experimental decay patterns. We have developed an improved and more general theory of mRNA degradation which provides a general framework of mRNA expression and allows describing specific degradation mechanisms. We have made an attempt to provide detailed models for the regulation in different organisms. In the yeast S. cerevisiae, different degradation pathways are known to compete and furthermore most of them rely on the biochemical modification of mRNA molecules. In bacteria such as E. coli, degradation proceeds primarily endonucleolytically, i.e. it is governed by the initial cleavage within the coding region. In addition, it is often coupled to the level of maturity and the size of the polysome of an mRNA. Both for S. cerevisiae and E. coli, our descriptions lead to a considerable improvement of the interpretation of experimental data. The general outcome is that the degradation of mRNA must be described by an age-dependent degradation rate, which can be interpreted as a consequence of molecular aging of mRNAs. Within our theory, we find adequate ways to address this much debated topic from a theoretical perspective. The improvements of the understanding of mRNA degradation can be readily applied to further comprehend the mRNA expression under different internal or environmental conditions such as after the induction of transcription or stress application. Also, the role of mRNA decay can be assessed in the context of translation and protein synthesis. The ultimate goal in understanding gene regulation mediated by mRNA stability will be to identify the relevance and biological function of different mechanisms. Once more quantitative data will become available, our description allows to elaborate the role of each mechanism by devising a suitable model.