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Supermassive black holes reside in the hearts of almost all massive galaxies. Their evolutionary path seems to be strongly linked to the evolution of their host galaxies, as implied by several empirical relations between the black hole mass (M BH ) and different host galaxy properties. The physical driver of this co-evolution is, however, still not understood. More mass measurements over homogeneous samples and a detailed understanding of systematic uncertainties are required to fathom the origin of the scaling relations.
In this thesis, I present the mass estimations of supermassive black holes in the nuclei of one late-type and thirteen early-type galaxies. Our SMASHING sample extends from the intermediate to the massive galaxy mass regime and was selected to fill in gaps in number of galaxies along the scaling relations. All galaxies were observed at high spatial resolution, making use of the adaptive-optics mode of integral field unit (IFU) instruments on state-of-the-art telescopes (SINFONI, NIFS, MUSE). I extracted the stellar kinematics from these observations and constructed dynamical Jeans and Schwarzschild models to estimate the mass of the central black holes robustly. My new mass estimates increase the number of early-type galaxies with measured black hole masses by 15%. The seven measured galaxies with nuclear light deficits (’cores’) augment the sample of cored galaxies with measured black holes by 40%. Next to determining massive black hole masses, evaluating the accuracy of black hole masses is crucial for understanding the intrinsic scatter of the black hole- host galaxy scaling relations. I tested various sources of systematic uncertainty on my derived mass estimates.
The M BH estimate of the single late-type galaxy of the sample yielded an upper limit, which I could constrain very robustly. I tested the effects of dust, mass-to-light ratio (M/L) variation, and dark matter on my measured M BH . Based on these tests, the typically assumed constant M/L ratio can be an adequate assumption to account for the small amounts of dark matter in the center of that galaxy. I also tested the effect of a variable M/L variation on the M BH measurement on a second galaxy. By considering stellar M/L variations in the dynamical modeling, the measured M BH decreased by 30%. In the future, this test should be performed on additional galaxies to learn how an as constant assumed M/L flaws the estimated black hole masses.
Based on our upper limit mass measurement, I confirm previous suggestions that resolving the predicted BH sphere-of-influence is not a strict condition to measure black hole masses. Instead, it is only a rough guide for the detection of the black hole if high-quality, and high signal-to-noise IFU data are used for the measurement. About half of our sample consists of massive early-type galaxies which show nuclear surface brightness cores and signs of triaxiality. While these types of galaxies are typically modeled with axisymmetric modeling methods, the effects on M BH are not well studied yet. The massive galaxies of our presented galaxy sample are well suited to test the effect of different stellar dynamical models on the measured black hole mass in evidently triaxial galaxies. I have compared spherical Jeans and axisymmetric Schwarzschild models and will add triaxial Schwarzschild models to this comparison in the future. The constructed Jeans and Schwarzschild models mostly disagree with each other and cannot reproduce many of the triaxial features of the galaxies (e.g., nuclear sub-components, prolate rotation). The consequence of the axisymmetric-triaxial assumption on the accuracy of M BH and its impact on the black hole - host galaxy relation needs to be carefully examined in the future.
In the sample of galaxies with published M BH , we find measurements based on different dynamical tracers, requiring different observations, assumptions, and methods. Crucially, different tracers do not always give consistent results. I have used two independent tracers (cold molecular gas and stars) to estimate M BH in a regular galaxy of our sample. While the two estimates are consistent within their errors, the stellar-based measurement is twice as high as the gas-based. Similar trends have also been found in the literature. Therefore, a rigorous test of the systematics associated with the different modeling methods is required in the future. I caution to take the effects of different tracers (and methods) into account when discussing the scaling relations.
I conclude this thesis by comparing my galaxy sample with the compilation of galaxies with measured black holes from the literature, also adding six SMASHING galaxies, which were published outside of this thesis. None of the SMASHING galaxies deviates significantly from the literature measurements. Their inclusion to the published early-type galaxies causes a change towards a shallower slope for the M BH - effective velocity dispersion relation, which is mainly driven by the massive galaxies of our sample. More unbiased and homogenous measurements are needed in the future to determine the shape of the relation and understand its physical origin.
Massive Open Online Courses (MOOCs) open up new opportunities to learn a wide variety of skills online and are thus well suited for individual education, especially where proffcient teachers are not available locally. At the same time, modern society is undergoing a digital transformation, requiring the training of large numbers of current and future employees. Abstract thinking, logical reasoning, and the need to formulate instructions for computers are becoming increasingly relevant. A holistic way to train these skills is to learn how to program. Programming, in addition to being a mental discipline, is also considered a craft, and practical training is required to achieve mastery. In order to effectively convey programming skills in MOOCs, practical exercises are incorporated into the course curriculum to offer students the necessary hands-on experience to reach an in-depth understanding of the programming concepts presented. Our preliminary analysis showed that while being an integral and rewarding part of courses, practical exercises bear the risk of overburdening students who are struggling with conceptual misunderstandings and unknown syntax. In this thesis, we develop, implement, and evaluate different interventions with the aim to improve the learning experience, sustainability, and success of online programming courses. Data from four programming MOOCs, with a total of over 60,000 participants, are employed to determine criteria for practical programming exercises best suited for a given audience.
Based on over five million executions and scoring runs from students' task submissions, we deduce exercise difficulties, students' patterns in approaching the exercises, and potential flaws in exercise descriptions as well as preparatory videos. The primary issue in online learning is that students face a social gap caused by their isolated physical situation. Each individual student usually learns alone in front of a computer and suffers from the absence of a pre-determined time structure as provided in traditional school classes. Furthermore, online learning usually presses students into a one-size-fits-all curriculum, which presents the same content to all students, regardless of their individual needs and learning styles. Any means of a personalization of content or individual feedback regarding problems they encounter are mostly ruled out by the discrepancy between the number of learners and the number of instructors. This results in a high demand for self-motivation and determination of MOOC participants. Social distance exists between individual students as well as between students and course instructors. It decreases engagement and poses a threat to learning success. Within this research, we approach the identified issues within MOOCs and suggest scalable technical solutions, improving social interaction and balancing content difficulty.
Our contributions include situational interventions, approaches for personalizing educational content as well as concepts for fostering collaborative problem-solving. With these approaches, we reduce counterproductive struggles and create a universal improvement for future programming MOOCs. We evaluate our approaches and methods in detail to improve programming courses for students as well as instructors and to advance the state of knowledge in online education.
Data gathered from our experiments show that receiving peer feedback on one's programming problems improves overall course scores by up to 17%. Merely the act of phrasing a question about one's problem improved overall scores by about 14%. The rate of students reaching out for help was significantly improved by situational just-in-time interventions. Request for Comment interventions increased the share of students asking for help by up to 158%. Data from our four MOOCs further provide detailed insight into the learning behavior of students. We outline additional significant findings with regard to student behavior and demographic factors. Our approaches, the technical infrastructure, the numerous educational resources developed, and the data collected provide a solid foundation for future research.
This thesis presents new approaches of SAR methods and their application to tectonically active systems and related surface deformation. With 3 publications two case studies are presented:
(1) The coseismic deformation related to the Nura earthquake (5th October 2008, magnitude Mw 6.6) at the eastern termination of the intramontane Alai valley. Located between the southern Tien Shan and the northern Pamir the coseismic surface displacements are analysed using SAR (Synthetic Aperture RADAR) data. The results show clear gradients in the vertical and horizontal directions along a complex pattern of surface ruptures and active faults. To integrate and to interpret these observations in the context of the regional active tectonics a SAR data analysis is complemented with seismological data and geological field observations. The main moment release of the Nura earthquake appears to be on the Pamir Frontal thrust, while the main surface displacements and surface rupture occurred in the footwall and along of the NE–SW striking Irkeshtam fault. With InSAR data from ascending and descending satellite tracks along with pixel offset measurements the Nura earthquake source is modelled as a segmented rupture. One fault segment corresponds to high-angle brittle faulting at the Pamir Frontal thrust and two more fault segments show moderate-angle and low-friction thrusting at the Irkeshtam fault. The integrated analysis of the coseismic deformation argues for a rupture segmentation and strain partitioning associated to the earthquake. It possibly activated an orogenic wedge in the easternmost segment of the Pamir-Alai collision zone. Further, the style of the segmentation may be associated with the presence of Paleogene evaporites.
(2) The second focus is put on slope instabilities and consequent landslides in the area of prominent topographic transition between the Fergana basin and high-relief Alai range. The Alai range constitutes an active orogenic wedge of the Pamir – Tien Shan collision zone that described as a progressively northward propagating fold-and-thrust belt. The interferometric analysis of ALOS/PALSAR radar data integrates a period of 4 years (2007-2010) based on the Small Baseline Subset (SBAS) time-series technique to assess surface deformation with millimeter surface change accuracy. 118 interferograms are analyzed to observe spatially-continuous movements with downslope velocities up to 71 mm/yr. The obtained rates indicate slow movement of the deep-seated landslides during the observation time. We correlated these movements with precipitation and seismic records. The results suggest that the deformation peaks correlate with rainfall in the 3 preceding months and with one earthquake event. In the next step, to understand the spatial pattern of landslide processes, the tectonic morphologic and lithologic settings are combined with the patterns of surface deformation. We demonstrate that the lithological and tectonic structural patterns are the main controlling factors for landslide occurrence and surface deformation magnitudes. Furthermore active contractional deformation in the front of the orogenic wedge is the main mechanism to sustain relief. Some of the slower but continuously moving slope instabilities are directly related to tectonically active faults and unconsolidated young Quaternary syn-orogenic sedimentary sequences. The InSAR observed slow moving landslides represent active deep-seated gravitational slope deformation phenomena which is first time observed in the Tien Shan mountains. Our approach offers a new combination of InSAR techniques and tectonic aspects to localize and understand enhanced slope instabilities in tectonically active mountain fronts in the Kyrgyz Tien Shan.
The contractile vacuole (CV) is an osmoregulatory organelle found exclusively in algae and protists. In addition to expelling excessive water out of the cell, it also expels ions and other metabolites and thereby contributes to the cell's metabolic homeostasis. The interest in the CV reaches beyond its immediate cellular roles. The CV's function is tightly related to basic cellular processes such as membrane dynamics and vesicle budding and fusion; several physiological processes in animals, such as synaptic neurotransmission and blood filtration in the kidney, are related to the CV's function; and several pathogens, such as the causative agents of sleeping sickness, possess CVs, which may serve as pharmacological targets. The green alga Chlamydomonas reinhardtii has two CVs. They are the smallest known CVs in nature, and they remain relatively untouched in the CV-related literature. Many genes that have been shown to be related to the CV in other organisms have close homologues in C. reinhardtii. We attempted to silence some of these genes and observe the effect on the CV. One of our genes, VMP1, caused striking, severe phenotypes when silenced. Cells exhibited defective cytokinesis and aberrant morphologies. The CV, incidentally, remained unscathed. In addition, mutant cells showed some evidence of disrupted autophagy. Several important regulators of the cell cycle as well as autophagy were found to be underexpressed in the mutant. Lipidomic analysis revealed many meaningful changes between wild-type and mutant cells, reinforcing the compromised-autophagy observation. VMP1 is a singular protein, with homologues in numerous eukaryotic organisms (aside from fungi), but usually with no relatives in each particular genome. Since its first characterization in 2002 it has been associated with several cellular processes and functions, namely autophagy, programmed cell-death, secretion, cell adhesion, and organelle biogenesis. It has been implicated in several human diseases: pancreatitis, diabetes, and several types of cancer. Our results reiterate some of the observations in VMP1's six reported homologues, but, importantly, show for the first time an involvement of this protein in cell division. The mechanisms underlying this involvement in Chlamydomonas, as well as other key aspects, such as VMP1's subcellular localization and interaction partners, still await elucidation.
The creation of complex polymer structures has been one of the major research topics over the last couple of decades. This work deals with the synthesis of (block co-)polymers, the creation of complex and stimuli-responsive aggregates by self-assembly, and the cross-linking of these structures. Also the higher-order self-assembly of the aggregates is investigated. The formation of poly-2-oxazoline based micelles in aqueous solution and their simultaneous functionalization and cross-linking using thiol-yne chemistry is e.g. presented. By introducing pH responsive thiols in the core of the micelles the influence of charged groups in the core of micelles on the entire structure can be studied. The charging of these groups leads to a swelling of the core and a decrease in the local concentration of the corona forming block (poly(2-ethyl-2-oxazoline)). This decrease in concentration yields a shift in the cloud point temperature to higher temperatures for this Type I thermoresponsive polymer. When the swelling of the core is prohibited, e.g. by the introduction of sufficient amounts of salt, this behavior disappears. Similar structures can be prepared using complex coacervate core micelles (C3Ms) built through the interaction of weakly acidic and basic polymer blocks. The advantage of these structures is that two different stabilizing blocks can be incorporated, which allows for more diverse and complex structures and behavior of the micelles. Using block copolymers with either a polyanionic or a polycationic block C3Ms could be created with a corona which contains two different soluble nonionic polymers, which either have a mixed corona or a Janus type corona, depending on the polymers that were chosen. Using NHS and EDC the micelles could easily be cross-linked by the formation of amide bonds in the core of the micelles. The higher-order self-assembly behavior of these core cross-linked complex coacervate core micelles (C5Ms) was studied. Due to the cross-linking the micelles are stabilized towards changes in pH and ionic strength, but polymer chains are also no longer able to rearrange. For C5Ms with a mixed corona likely network structures were formed upon the collapse of the thermoresponsive poly(N-isopropylacrylamide) (PNIPAAm), whereas for Janus type C5Ms well defined spherical aggregates of micelles could be obtained, depending on the pH of the solution. Furthermore it could be shown that Janus micelles can adsorb onto inorganic nanoparticles such as colloidal silica (through a selective interaction between PEO and the silica surface) or gold nanoparticles (by the binding of thiol end-groups). Asymmetric aggregates were also formed using the streptavidin-biotin binding motive. This is achieved by using three out of the four binding sites of streptavidin for the binding of one three-arm star polymer, end-functionalized with biotin groups. A homopolymer with one biotin end-group can be used to occupy the last position. This binding of two different polymers makes it possible to create asymmetric complexes. This phase separation is theoretically independent of the kind of polymer since the structure of the protein is the driving force, not the intrinsic phase separation between polymers. Besides Janus structures also specific cross-linking can be achieved by using other mixing ratios.
The role of biogenic carbonate producers in the evolution of the geometries of carbonate systems has been the subject of numerous research projects. Attempts to classify modern and ancient carbonate systems by their biotic components have led to the discrimination of biogenic carbonate producers broadly into Photozoans, which are characterised by an affinity for warm tropical waters and high dependence on light penetration, and Heterozoans which are generally associated with both cool water environments and nutrient-rich settings with little to no light penetration. These broad categories of carbonate sediment producers have also been recognised to dominate in specific carbonate systems. Photozoans are commonly dominant in flat-topped platforms with steep margins, while Heterozoans generally dominate carbonate ramps. However, comparatively little is known on how these two main groups of carbonate producers interact in the same system and impact depositional geometries responding to changes in environmental conditions such as sea level fluctuation, antecedent slope, sediment transport processes, etc. This thesis presents numerical models to investigate the evolution of Miocene carbonate systems in the Mediterranean from two shallow marine domains: 1) a Miocene flat-topped platform dominated by Photozoans, with a significant component of Hetrozoans in the slope and 2) a Heterozoan distally steepened ramp, with seagrass-influenced (Photozoan) inner ramp. The overarching aim of the three articles comprising this cumulative thesis is to provide a numerical study of the role of Photozoans and Heterozoans in the evolution of carbonate system geometries and how these biotas respond to changes in environmental conditions. This aim was achieved using stratigraphic forward modelling, which provides an approach to quantitatively integrate multi-scale datasets to reconstruct sedimentary processes and products during the evolution of a sedimentary system.
In a Photozoan-dominated carbonate system, such as the Miocene Llucmajor platform in Western Mediterranean, stratigraphic forward modelling dovetailed with a robust set of sensitivity tests reveal how the geometry of the carbonate system is determined by the complex interaction of Heterozoan and Photozoan biotas in response to variable conditions of sea level fluctuation, substrate configuration, sediment transport processes and the dominance of Photozoan over Heterozoan production. This study provides an enhanced understanding of the different carbonate systems that are possible under different ecological and hydrodynamic conditions. The research also gives insight into the roles of different biotic associations in the evolution of carbonate geometries through time and space. The results further show that the main driver of platform progradation in a Llucmajor-type system is the lowstand production of Heterozoan sediments, which form the necessary substratum for Photozoan production.
In Heterozoan systems, sediment production is mainly characterised by high transport deposits, that are prone to redistribution by waves and gravity, thereby precluding the development of steep margins. However, in the Menorca ramp, the occurrence of sediment trapping by seagrass led to the evolution of distal slope steepening. We investigated, through numerical modelling, how such a seagrass-influenced ramp responds to the frequency and amplitude of sea level changes, variable carbonate production between the euphotic and oligophotic zone, and changes in the configuration of the paleoslope. The study reinforces some previous hypotheses and presents alternative scenarios to the established concepts of high-transport ramp evolution. The results of sensitivity experiments show that steep slopes are favoured in ramps that develop in high-frequency sea level fluctuation with amplitudes between 20 m and 40 m. We also show that ramp profiles are significantly impacted by the paleoslope inclination, such that an optimal antecedent slope of about 0.15 degrees is required for the Menorca distally steepened ramp to develop.
The third part presents an experimental case to argue for the existence of a Photozoan sediment threshold required for the development of steep margins in carbonate platforms. This was carried out by developing sensitivity tests on the forward models of the flat-topped (Llucmajor) platform and the distally steepened (Menorca) platform. The results show that models with Photozoan sediment proportion below a threshold of about 40% are incapable of forming steep slopes. The study also demonstrates that though it is possible to develop steep margins by seagrass sediment trapping, such slopes can only be stabilized by the appropriate sediment fabric and/or microbial binding. In the Photozoan-dominated system, the magnitude of slope steepness depends on the proportion of Photozoan sediments in the system. Therefore, this study presents a novel tool for characterizing carbonate systems based on their biogenic components.
Partial synchronous states exist in systems of coupled oscillators between full synchrony and asynchrony. They are an important research topic because of their variety of different dynamical states. Frequently, they are studied using phase dynamics. This is a caveat, as phase dynamics are generally obtained in the weak coupling limit of a first-order approximation in the coupling strength. The generalization to higher orders in the coupling strength is an open problem. Of particular interest in the research of partial synchrony are systems containing both attractive and repulsive coupling between the units. Such a mix of coupling yields very specific dynamical states that may help understand the transition between full synchrony and asynchrony. This thesis investigates partial synchronous states in mixed-coupling systems. First, a method for higher-order phase reduction is introduced to observe interactions beyond the pairwise one in the first-order phase description, hoping that these may apply to mixed-coupling systems. This new method for coupled systems with known phase dynamics of the units gives correct results but, like most comparable methods, is computationally expensive. It is applied to three Stuart-Landau oscillators coupled in a line with a uniform coupling strength. A numerical method is derived to verify the analytical results. These results are interesting but give importance to simpler phase models that still exhibit exotic states. Such simple models that are rarely considered are Kuramoto oscillators with attractive and repulsive interactions. Depending on how the units are coupled and the frequency difference between the units, it is possible to achieve many different states. Rich synchronization dynamics, such as a Bellerophon state, are observed when considering a Kuramoto model with attractive interaction in two subpopulations (groups) and repulsive interactions between groups. In two groups, one attractive and one repulsive, of identical oscillators with a frequency difference, an interesting solitary state appears directly between full and partial synchrony. This system can be described very well analytically.
In plant cells, subcellular transport of cargo proteins relies to a large extent on post-Golgi transport pathways, many of which are mediated by clathrin-coated vesicles (CCVs). Vesicle formation is facilitated by different factors like accessory proteins and adaptor protein complexes (APs), the latter serving as a bridge between cargo proteins and the coat protein clathrin. One type of accessory proteins is defined by a conserved EPSIN N-TERMINAL HOMOLOGY (ENTH) domain and interacts with APs and clathrin via motifs in the C-terminal part. In Arabidopsis thaliana, there are three closely related ENTH domain proteins (EPSIN1, 2 and 3) and one highly conserved but phylogenetically distant outlier, termed MODIFIED TRANSPORT TO THE VACUOLE1 (MTV1). In case of the trans-Golgi network (TGN) located MTV1, clathrin association and a role in vacuolar transport have been shown previously (Sauer et al. 2013). In contrast, for EPSIN1 and EPSIN2 limited functional and localization data were available; and EPSIN3 remained completely uncharacterized prior to this study (Song et al. 2006; Lee et al. 2007). The molecular details of ENTH domain proteins in plants are still unknown. In order to systematically characterize all four ENTH proteins in planta, we first investigated expression and subcellular localization by analysis of stable reporter lines under their endogenous promotors. Although all four genes are ubiquitously expressed, their subcellular distribution differs markedly. EPSIN1 and MTV1 are located at the TGN, whereas EPSIN2 and EPSIN3 are associated with the plasma membrane (PM) and the cell plate. To examine potential functional redundancy, we isolated knockout T-DNA mutant lines and created all higher order mutant combinations. The clearest evidence for functional redundancy was observed in the epsin1 mtv1 double mutant, which is a dwarf displaying overall growth reduction. These findings are in line with the TGN localization of both MTV1 and EPS1. In contrast, loss of EPSIN2 and EPSIN3 does not result in a growth phenotype compared to wild type, however, a triple knockout of EPSIN1, EPSIN2 and EPSIN3 shows partially sterile plants. We focused mainly on the epsin1 mtv1 double mutant and addressed the functional role of these two genes in clathrin-mediated vesicle transport by comprehensive molecular, biochemical, and genetic analyses. Our results demonstrate that EPSIN1 and MTV1 promote vacuolar transport and secretion of a subset of cargo. However, they do not seem to be involved in endocytosis and recycling. Importantly, employing high-resolution imaging, genetic and biochemical experiments probing the relationship of the AP complexes, we found that EPSIN1/AP1 and MTV1/AP4 define two spatially and molecularly distinct subdomains of the TGN. The AP4 complex is essential for MTV1 recruitment to the TGN, whereas EPSIN1 is independent of AP4 but presumably acts in an AP1-dependent framework. Our findings suggest that this ENTH/AP pairing preference is conserved between animals and plants.
Predators can have numerical and behavioral effects on prey animals. While numerical effects are well explored, the impact of behavioral effects is unclear. Furthermore, behavioral effects are generally either analyzed with a focus on single individuals or with a focus on consequences for other trophic levels. Thereby, the impact of fear on the level of prey communities is overlooked, despite potential consequences for conservation and nature management. In order to improve our understanding of predator-prey interactions, an assessment of the consequences of fear in shaping prey community structures is crucial.
In this thesis, I evaluated how fear alters prey space use, community structure and composition, focusing on terrestrial mammals. By integrating landscapes of fear in an existing individual-based and spatially-explicit model, I simulated community assembly of prey animals via individual home range formation. The model comprises multiple hierarchical levels from individual home range behavior to patterns of prey community structure and composition. The mechanistic approach of the model allowed for the identification of underlying mechanism driving prey community responses under fear.
My results show that fear modified prey space use and community patterns. Under fear, prey animals shifted their home ranges towards safer areas of the landscape. Furthermore, fear decreased the total biomass and the diversity of the prey community and reinforced shifts in community composition towards smaller animals. These effects could be mediated by an increasing availability of refuges in the landscape. Under landscape changes, such as habitat loss and fragmentation, fear intensified negative effects on prey communities. Prey communities in risky environments were subject to a non-proportional diversity loss of up to 30% if fear was taken into account. Regarding habitat properties, I found that well-connected, large safe patches can reduce the negative consequences of habitat loss and fragmentation on prey communities. Including variation in risk perception between prey animals had consequences on prey space use. Animals with a high risk perception predominantly used safe areas of the landscape, while animals with a low risk perception preferred areas with a high food availability. On the community level, prey diversity was higher in heterogeneous landscapes of fear if individuals varied in their risk perception compared to scenarios in which all individuals had the same risk perception.
Overall, my findings give a first, comprehensive assessment of the role of fear in shaping prey communities. The linkage between individual home range behavior and patterns at the community level allows for a mechanistic understanding of the underlying processes. My results underline the importance of the structure of the landscape of fear as a key driver of prey community responses, especially if the habitat is threatened by landscape changes. Furthermore, I show that individual landscapes of fear can improve our understanding of the consequences of trait variation on community structures. Regarding conservation and nature management, my results support calls for modern conservation approaches that go beyond single species and address the protection of biotic interactions.
Ferroic materials have attracted a lot of attention over the years due to their wide range of applications in sensors, actuators, and memory devices. Their technological applications originate from their unique properties such as ferroelectricity and piezoelectricity. In order to optimize these materials, it is necessary to understand the coupling between their nanoscale structure and transient response, which are related to the atomic structure of the unit cell.
In this thesis, synchrotron X-ray diffraction is used to investigate the structure of ferroelectric thin film capacitors during application of a periodic electric field. Combining electrical measurements with time-resolved X-ray diffraction on a working device allows for visualization of the interplay between charge flow and structural motion. This constitutes the core of this work. The first part of this thesis discusses the electrical and structural dynamics of a ferroelectric Pt/Pb(Zr0.2,Ti0.8)O3/SrRuO3 heterostructure during charging, discharging, and polarization reversal. After polarization reversal a non-linear piezoelectric response develops on a much longer time scale than the RC time constant of the device. The reversal process is inhomogeneous and induces a transient disordered domain state. The structural dynamics under sub-coercive field conditions show that this disordered domain state can be remanent and can be erased with an appropriate voltage pulse sequence. The frequency-dependent dynamic characterization of a Pb(Zr0.52,Ti0.48)O3 layer, at the morphotropic phase boundary, shows that at high frequency, the limited domain wall velocity causes a phase lag between the applied field and both the structural and electrical responses. An external modification of the RC time constant of the measurement delays the switching current and widens the electromechanical hysteresis loop while achieving a higher compressive piezoelectric strain within the crystal.
In the second part of this thesis, time-resolved reciprocal space maps of multiferroic BiFeO3 thin films were measured to identify the domain structure and investigate the development of an inhomogeneous piezoelectric response during the polarization reversal. The presence of 109° domains is evidenced by the splitting of the Bragg peak.
The last part of this work investigates the effect of an optically excited ultrafast strain or heat pulse propagating through a ferroelectric BaTiO3 layer, where we observed an additional current response due to the laser pulse excitation of the metallic bottom electrode of the heterostructure.
What are the consequences of unemployment and precarious employment for individuals' health in Europe? What are the moderating factors that may offset (or increase) the health consequences of labor-market risks? How do the effects of these risks vary across different contexts, which differ in their institutional and cultural settings? Does gender, regarded as a social structure, play a role, and how? To answer these questions is the aim of my cumulative thesis. This study aims to advance our knowledge about the health consequences that unemployment and precariousness cause over the life course. In particular, I investigate how several moderating factors, such as gender, the family, and the broader cultural and institutional context, may offset or increase the impact of employment instability and insecurity on individual health.
In my first paper, 'The buffering role of the family in the relationship between job loss and self-perceived health: Longitudinal results from Europe, 2004-2011', I and my co-authors measure the causal effect of job loss on health and the role of the family and welfare states (regimes) as moderating factors. Using EU-SILC longitudinal data (2004-2011), we estimate the probability of experiencing 'bad health' following a transition to unemployment by applying linear probability models and undertake separate analyses for men and women. Firstly, we measure whether changes in the independent variable 'job loss' lead to changes in the dependent variable 'self-rated health' for men and women separately. Then, by adding into the model different interaction terms, we measure the moderating effect of the family, both in terms of emotional and economic support, and how much it varies across different welfare regimes. As an identification strategy, we first implement static fixed-effect panel models, which control for time-varying observables and indirect health selection—i.e., constant unobserved heterogeneity. Secondly, to control for reverse causality and path dependency, we implement dynamic fixed-effect panel models, adding a lagged dependent variable to the model.
We explore the role of the family by focusing on close ties within households: we consider the presence of a stable partner and his/her working status as a source of social and economic support. According to previous literature, having a partner should reduce the stress from adverse events, thanks to the symbolic and emotional dimensions that such a relationship entails, regardless of any economic benefits. Our results, however, suggest that benefits linked to the presence of a (female) partner also come from the financial stability that (s)he can provide in terms of a second income. Furthermore, we find partners' employment to be at least as important as the mere presence of the partner in reducing the negative effect of job loss on the individual's health by maintaining the household's standard of living and decreasing economic strain on the family. Our results are in line with previous research, which has highlighted that some people cope better than others with adverse life circumstances, and the support provided by the family is a crucial resource in that regard.
We also reported an important interaction between the family and the welfare state in moderating the health consequences of unemployment, showing how the compensation effect of the family varies across welfare regimes. The family plays a decisive role in cushioning the adverse consequences of labor market risks in Southern and Eastern welfare states, characterized by less developed social protection systems and –especially the Southern – high level of familialism.
The first paper also found important gender differences concerning job loss, family and welfare effects. Of particular interest is the evidence suggesting that health selection works differently for men and women, playing a more prominent role for women than for men in explaining the relationship between job loss and self-perceived health. The second paper, 'Gender roles and selection mechanisms across contexts: A comparative analysis of the relationship between unemployment, self-perceived health, and gender.' investigates more in-depth the gender differential in health driven by unemployment.
Being a highly contested issue in literature, we aim to study whether men are more penalized than women or the other way around and the mechanisms that may explain the gender difference. To do that, we rely on two theoretical arguments: the availability of alternative roles and social selection. The first argument builds on the idea that men and women may compensate for the detrimental health consequences of unemployment through the commitment to 'alternative roles,' which can provide for the resources needed to fulfill people's socially constructed needs. Notably, the availability of alternative options depends on the different positions that men and women have in society.
Further, we merge the availability of the 'alternative roles' argument with the health selection argument. We assume that health selection could be contingent on people's social position as defined by gender and, thus, explain the gender differential in the relationship between unemployment and health. Ill people might be less reluctant to fall or remain (i.e., self-select) in unemployment if they have alternative roles. In Western societies, women generally have more alternative roles than men and thus more discretion in their labor market attachment. Therefore, health selection should be stronger for them, explaining why unemployment is less menace for women than for their male counterparts.
Finally, relying on the idea of different gender regimes, we extended these arguments to comparison across contexts. For example, in contexts where being a caregiver is assumed to be women's traditional and primary roles and the primary breadwinner role is reserved to men, unemployment is less stigmatized, and taking up alternative roles is more socially accepted for women than for men (Hp.1). Accordingly, social (self)selection should be stronger for women than for men in traditional contexts, where, in the case of ill-health, the separation from work is eased by the availability of alternative roles (Hp.2).
By focusing on contexts that are representative of different gender regimes, we implement a multiple-step comparative approach. Firstly, by using EU-SILC longitudinal data (2004-2015), our analysis tests gender roles and selection mechanisms for Sweden and Italy, representing radically different gender regimes, thus providing institutional and cultural variation. Then, we limit institutional heterogeneity by focusing on Germany and comparing East- and West-Germany and older and younger cohorts—for West-Germany (SOEP data 1995-2017). Next, to assess the differential impact of unemployment for men and women, we compared (unemployed and employed) men with (unemployed and employed) women. To do so, we calculate predicted probabilities and average marginal effect from two distinct random-effects probit models. Our first step is estimating random-effects models that assess the association between unemployment and self-perceived health, controlling for observable characteristics. In the second step, our fully adjusted model controls for both direct and indirect selection. We do this using dynamic correlated random-effects (CRE) models. Further, based on the fully adjusted model, we test our hypotheses on alternative roles (Hp.1) by comparing several contexts – models are estimated separately for each context. For this hypothesis, we pool men and women and include an interaction term between unemployment and gender, which has the advantage to allow for directly testing whether gender differences in the effect of unemployment exist and are statistically significant. Finally, we test the role of selection mechanisms (Hp.2), using the KHB method to compare coefficients across nested nonlinear models. Specifically, we test the role of selection for the relationship between unemployment and health by comparing the partially-adjusted and fully-adjusted models. To allow selection mechanisms to operate differently between genders, we estimate separate models for men and women.
We found support to our first hypotheses—the context where people are embedded structures the relationship between unemployment, health, and gender. We found no gendered effect of unemployment on health in the egalitarian context of Sweden. Conversely, in the traditional context of Italy, we observed substantive and statistically significant gender differences in the effect of unemployment on bad health, with women suffering less than men. We found the same pattern for comparing East and West Germany and younger and older cohorts in West Germany.
On the contrary, our results did not support our theoretical argument on social selection. We found that in Sweden, women are more selected out of employment than men. In contrast, in Italy, health selection does not seem to be the primary mechanism behind the gender differential—Italian men and women seem to be selected out of employment to the same extent. Namely, we do not find any evidence that health selection is stronger for women in more traditional countries (Hp2), despite the fact that the institutional and the cultural context would offer them a more comprehensive range of 'alternative roles' relative to men. Moreover, our second hypothesis is also rejected in the second and third comparisons, where the cross-country heterogeneity is reduced to maximize cultural differences within the same institutional context. Further research that addresses selection into inactivity is needed to evaluate the interplay between selection and social roles across gender regimes.
While the health consequences of unemployment have been on the research agenda for a pretty long time, the interest in precarious employment—defined as the linking of the vulnerable worker to work that is characterized by uncertainty and insecurity concerning pay, the stability of the work arrangement, limited access to social benefits, and statutory protections—has emerged only later. Since the 80s, scholars from different disciplines have raised concerns about the social consequences of de-standardization of employment relationships. However, while work has become undoubtedly more precarious, very little is known about its causal effect on individual health and the role of gender as a moderator. These questions are at the core of my third paper : 'Bad job, bad health? A longitudinal analysis of the interaction between precariousness, gender and self-perceived health in Germany'. Herein, I investigate the multidimensional nature of precarious employment and its causal effect on health, particularly focusing on gender differences.
With this paper, I aim at overcoming three major shortcomings of earlier studies: The first one regards the cross-sectional nature of data that prevents the authors from ruling out unobserved heterogeneity as a mechanism for the association between precarious employment and health. Indeed, several unmeasured individual characteristics—such as cognitive abilities—may confound the relationship between precarious work and health, leading to biased results. Secondly, only a few studies have directly addressed the role of gender in shaping the relationship. Moreover, available results on the gender differential are mixed and inconsistent: some found precarious employment being more detrimental for women's health, while others found no gender differences or stronger negative association for men. Finally, previous attempts to an empirical translation of the employment precariousness (EP) concept have not always been coherent with their theoretical framework. EP is usually assumed to be a multidimensional and continuous phenomenon; it is characterized by different dimensions of insecurity that may overlap in the same job and lead to different "degrees of precariousness." However, researchers have predominantly focused on one-dimensional indicators—e.g., temporary employment, subjective job insecurity—to measure EP and study the association with health. Besides the fact that this approach partially grasps the phenomenon's complexity, the major problem is the inconsistency of evidence that it has produced. Indeed, this line of inquiry generally reveals an ambiguous picture, with some studies finding substantial adverse effects of temporary over permanent employment, while others report only minor differences.
To measure the (causal) effect of precarious work on self-rated health and its variation by gender, I focus on Germany and use four waves from SOEP data (2003, 2007, 2011, and 2015). Germany is a suitable context for my study. Indeed, since the 1980s, the labor market and welfare system have been restructured in many ways to increase the German economy's competitiveness in the global market. As a result, the (standard) employment relationship has been de-standardized: non-standard and atypical employment arrangements—i.e., part-time work, fixed-term contracts, mini-jobs, and work agencies—have increased over time while wages have lowered, even among workers with standard work. In addition, the power of unions has also fallen over the last three decades, leaving a large share of workers without collective protection. Because of this process of de-standardization, the link between wage employment and strong social rights has eroded, making workers more powerless and more vulnerable to labor market risks than in the past. EP refers to this uneven distribution of power in the employment relationship, which can be detrimental to workers' health. Indeed, by affecting individuals' access to power and other resources, EP puts precarious workers at risk of experiencing health shocks and influences their ability to gain and accumulate health advantages (Hp.1).
Further, the focus on Germany allows me to investigate my second research question on the gender differential. Germany is usually regarded as a traditionalist gender regime: a context characterized by a configuration of roles. Here, being a caregiver is assumed to be women's primary role, whereas the primary breadwinner role is reserved for men. Although many signs of progress have been made over the last decades towards a greater equalization of opportunities and more egalitarianism, the breadwinner model has barely changed towards a modified version. Thus, women usually take on the double role of workers (the so-called secondary earner) and caregivers, and men still devote most of their time to paid work activities. Moreover, the overall upward trend towards more egalitarian gender ideologies has leveled off over the last decades, moving notably towards more traditional gender ideologies.
In this setting, two alternative hypotheses are possible. Firstly, I assume that the negative relationship between EP and health is stronger for women than for men. This is because women are systematically more disadvantaged than men in the public and private spheres of life, having less access to formal and informal sources of power. These gender-related power asymmetries may interact with EP-related power asymmetries resulting in a stronger effect of EP on women's health than on men's health (Hp.2).
An alternative way of looking at the gender differential is to consider the interaction that precariousness might have with men's and women's gender identities. According to this view, the negative relationship between EP and health is weaker for women than for men (Hp.2a). In a society with a gendered division of labor and a strong link between masculine identities and stable and well-rewarded job—i.e., a job that confers the role of primary family provider—a male worker with precarious employment might violate the traditional male gender role. Men in precarious jobs may perceive themselves (and by others) as possessing a socially undesirable characteristic, which conflicts with the stereotypical idea of themselves as the male breadwinner. Engaging in behaviors that contradict stereotypical gender identity may decrease self-esteem and foster feelings of inferiority, helplessness, and jealousy, leading to poor health.
I develop a new indicator of EP that empirically translates a definition of EP as a multidimensional and continuous phenomenon. I assume that EP is a latent construct composed of seven dimensions of insecurity chosen according to the theory and previous empirical research: Income insecurity, social insecurity, legal insecurity, employment insecurity, working-time insecurity, representation insecurity, worker's vulnerability. The seven dimensions are proxied by eight indicators available in the four waves of the SOEP dataset. The EP composite indicator is obtained by performing a multiple correspondence analysis (MCA) on the eight indicators. This approach aims to construct a summary scale in which all dimensions contribute jointly to the measured experience of precariousness and its health impact.
Further, the relationship between EP and 'general self-perceived health' is estimated by applying ordered probit random-effects estimators and calculating average marginal effect (further AME). Then, to control for unobserved heterogeneity, I implement correlated random-effects models that add to the model the within-individual means of the time-varying independent variables. To test the significance of the gender differential, I add an interaction term between EP and gender in the fully adjusted model in the pooled sample.
My correlated random-effects models showed EP's negative and substantial 'effect' on self-perceived health for both men and women. Although nonsignificant, the evidence seems in line with previous cross-sectional literature. It supports the hypothesis that employment precariousness could be detrimental to workers' health. Further, my results showed the crucial role of unobserved heterogeneity in shaping the health consequences of precarious employment. This is particularly important as evidence accumulates, yet it is still mostly descriptive.
Moreover, my results revealed a substantial difference among men and women in the relationship between EP and health: when EP increases, the risk of experiencing poor health increases much more for men than for women. This evidence falsifies previous theory according to whom the gender differential is contingent on the structurally disadvantaged position of women in western societies. In contrast, they seem to confirm the idea that men in precarious work could experience role conflict to a larger extent than women, as their self-standard is supposed to be the stereotypical breadwinner worker with a good and well-rewarded job. Finally, results from the multiple correspondence analysis contribute to the methodological debate on precariousness, showing that a multidimensional and continuous indicator can express a latent variable of EP.
All in all, complementarities are revealed in the results of unemployment and employment precariousness, which have two implications: Policy-makers need to be aware that the total costs of unemployment and precariousness go far beyond the economic and material realm penetrating other fundamental life domains such as individual health. Moreover, they need to balance the trade-off between protecting adequately unemployed people and fostering high-quality employment in reaction to the highlighted market pressures. In this sense, the further development of a (universalistic) welfare state certainly helps mitigate the adverse health effects of unemployment and, therefore, the future costs of both individuals' health and welfare spending. In addition, the presence of a working partner is crucial for reducing the health consequences of employment instability. Therefore, policies aiming to increase female labor market participation should be promoted, especially in those contexts where the welfare state is less developed.
Moreover, my results support the significance of taking account of a gender perspective in health research. The findings of the three articles show that job loss, unemployment, and precarious employment, in general, have adverse effects on men's health but less or absent consequences for women's health. Indeed, this suggests the importance of labor and health policies that consider and further distinguish the specific needs of the male and female labor force in Europe. Nevertheless, a further implication emerges: the health consequences of employment instability and de-standardization need to be investigated in light of the gender arrangements and the transforming gender relationships in specific cultural and institutional contexts. My results indeed seem to suggest that women's health advantage may be a transitory phenomenon, contingent on the predominant gendered institutional and cultural context. As the structural difference between men's and women's position in society is eroded, egalitarianism becomes the dominant normative status, so will probably be the gender difference in the health consequences of job loss and precariousness. Therefore, while gender equality in opportunities and roles is a desirable aspect for contemporary societies and a political goal that cannot be postponed further, this thesis raises a further and maybe more crucial question: What kind of equality should be pursued to provide men and women with both good life quality and equal chances in the public and private spheres? In this sense, I believe that social and labor policies aiming to reduce gender inequality in society should focus on improving women's integration into the labor market, implementing policies targeting men, and facilitating their involvement in the private sphere of life. Equal redistribution of social roles could activate a crucial transformation of gender roles and the cultural models that sustain and still legitimate gender inequality in Western societies.
Carbohydrates are found in every living organism, where they are responsible for numerous, essential biological functions and processes. Synthetic polymers with pendant saccharides, called glycopolymers, mimic natural glycoconjugates in their special properties and functions. Employing such biomimetics furthers the understanding and controlling of biological processes. Hence, glycopolymers are valuable and interesting for applications in the medical and biological field. However, the synthesis of carbohydrate-based materials can be very challenging. In this thesis, the synthesis of biofunctional glycopolymers is presented, with the focus on aqueous-based, protecting group free and short synthesis routes to further advance in the field of glycopolymer synthesis.
A practical and versatile precursor for glycopolymers are glycosylamines. To maintain biofunctionality of the saccharides after their amination, regioselective functionalization was performed. This frequently performed synthesis was optimized for different sugars. The optimization was facilitated using a design of experiment (DoE) approach to enable a reduced number of necessary experiments and efficient procedure. Here, the utility of using DoE for optimizing the synthesis of glycosylamines is discussed.
The glycosylamines were converted to glycomonomers which were then polymerized to yield biofunctional glycopolymers. Here, the glycopolymers were aimed to be applicable as layer-by-layer (LbL) thin film coatings for drug delivery systems. To enable the LbL technique, complimentary glycopolymer electrolytes were synthesized by polymerization of the glycomonomers and subsequent modification or by post-polymerization modification. For drug delivery, liposomes were embedded into the glycopolymer coating as potential cargo carriers. The stability as well as the integrity of the glycopolymer layers and liposomes were investigated at physiological pH range.
Different glycopolymers were also synthesized to be applicable as anti-adhesion therapeutics by providing advanced architectures with multivalent presentations of saccharides, which can inhibit the binding of pathogene lectins. Here, the synthesis of glycopolymer hydrogel particles based on biocompatible poly(N-isopropylacrylamide) (NiPAm) was established using the free-radical precipitation polymerization technique. The influence of synthesis parameters on the sugar content in the gels and on the hydrogel morphology is discussed. The accessibility of the saccharides to model lectins and their enhanced, multivalent interaction were investigated.
At the end of this work, the synthesis strategies for the glycopolymers are generally discussed as well as their potential application in medicine.
Synthesis, assembly and thermo-responsivity of polymer-functionalized magnetic cobalt nanoparticles
(2018)
This thesis mainly covers the synthesis, surface modification, magnetic-field-induced assembly and thermo-responsive functionalization of superparamagnetic Co NPs initially stabilized by hydrophobic small molecules oleic acid (OA) and trioctylphosphine oxide (TOPO), as well as the synthesis of both superparamagnetic and ferromagnetic Co NPs by using end-functionalized-polystyrene as stabilizer.
Co NPs, due to their excellent magnetic and catalytic properties, have great potential application in various fields, such as ferrofluids, catalysis, and magnetic resonance imaging (MRI). Superparamagnetic Co NPs are especially interesting, since they exhibit zero coercivity. They get magnetized in an external magnetic field and reach their saturation magnetization rapidly, but no magnetic moment remains after removal of the applied magnetic field. Therefore, they do not agglomerate in the body when they are used in biomedical applications. Normally, decomposition of metallic precursors at high temperature is one of the most important methods in preparation of monodisperse magnetic NPs, providing tunability in size and shape. Hydrophobic ligands like OA, TOPO and oleylamine are often used to both control the growth of NPs and protect them from agglomeration. The as-prepared magnetic NPs can be used in biological applications as long as they are transferred into water. Moreover, their supercrystal assemblies have the potential for high density data storage and electronic devices. In addition to small molecules, polymers can also be used as surfactants for the synthesis of ferromagnetic and superparamagnetic NPs by changing the reaction conditions. Therefore, chapter 2 gives an overview on the basic concept of synthesis, surface modification and self-assembly of magnetic nanoparticles. Various examples were used to illustrate the recent work.
The hydrophobic Co NPs synthesized with small molecules as surfactants limit their biological applications, which require a hydrophilic or aqueous environment. Surface modification (e.g., ligand exchange) is a general idea for either phase transition or surface-functionalization. Therefore, in chapter 3, a ligand exchange process was conducted to functionalize the surface of Co NPs. PNIPAM is one of the most popular smart polymers and its lower critical solution temperature (LCST) is around 32 °C, with a reversible change in the conformation structure between hydrophobic and hydrophilic. The novel nanocomposites of superparamagnetic Co NPs and thermo-responsive PNIPAM are of great interest. Thus, well-defined superparamagnetic Co NPs were firstly synthesized through the thermolysis of cobalt carbonyl by using OA and TOPO as surfactants. A functional ATRP initiator, containing an amine (as anchoring group) and a 2-bromopropionate group (SI-ATRP initiator), was used to replace the original ligands. This process is rapid and facial for efficient surface functionalization and afterwards the Co NPs can be dispersed into polar solvent DMF without aggregation. FT-IR spectroscopy showed that the TOPO was completely replaced, but a small amount of OA remained on the surface. A TGA measurement allowed the calculation of the grafting density of the initiator as around 3.2 initiator/nm2. Then, the surface-initiated ATRP was conducted for the polymerization of NIPAM on the surface of Co NPs and rendered the nanocomposites water-dispersible. A temperature-dependent dynamic light scattering study showed the aggregation behavior of PNIPAM-coated Co NPs upon heating and this process was proven to be reversible. The combination of superparamagnetic and thermo-responsive properties in these hybrid nanoparticles is promising for future applications e.g. in biomedicine.
In chapter 4, the magnetic-field-induced assembly of superparamagnetic cobalt nanoparticles both on solid substrates and at liquid-air interface was investigated. OA- and TOPO-coated Co NPs were synthesized via the thermolysis of cobalt carbonyl and dispersed into either hexane or toluene. The Co NP dispersion was dropped onto substrates (e.g., TEM grid, silicon wafer) and at liquid-air (water-air or ethylene glycol-air) interface. Due to the attractive dipolar interaction, 1-D chains formed in the presence of an external magnetic field. It is known that the concentration and the strength of the magnetic field can affect the assembly behavior of superparamagnetic Co NPs. Therefore, the influence of these two parameters on the morphology of the assemblies was studied. The formed 1-D chains were shorter and flexible at either lower concentration of the Co NP dispersion or lower strength of the external magnetic field due to thermal fluctuation. However, by increasing either the concentration of the NP dispersion or the strength of the applied magnetic field, these chains became longer, thicker and straighter. The reason could be that a high concentration led to a high fraction of short dipolar chains, and their interaction resulted in longer and thicker chains under applied magnetic field. On the other hand, when the magnetic field increased, the induced moments of the magnetic nanoparticles became larger, which dominated over the thermal fluctuation. Thus, the formed short chains connected to each other and grew in length. Thicker chains were also observed through chain-chain interaction. Furthermore, the induced moments of the NPs tended to direct into one direction with increased magnetic field, thus the chains were straighter. In comparison between the assembly on substrates, at water-air interface and at ethylene glycol-air interface, the assembly of Co NPs in hexane dispersion at ethylene glycol-air interface showed the most regular and homogeneous chain structures due to the better spreading of the dispersion on ethylene glycol subphase than on water subphase and substrates. The magnetic-field-induced assembly of superparamagnetic nanoparticles could provide a powerful approach for applications in data storage and electronic devices.
Chapter 5 presented the synthesis of superparamagnetic and ferromagnetic cobalt nanoparticles through a dual-stage thermolysis of cobalt carbonyl (Co2(CO)8) by using polystyrene as surfactant. The amine end-functionalized polystyrene surfactants with different molecular weight were prepared via atom transfer radical polymerization technique. The molecular weight determination of polystyrene was conducted by gel permeation chromatography (GPC) and matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) mass spectrometry techniques. The results showed that, when the molecular weight distribution is low (Mw/Mn < 1.2), the measurement by GPC and MALDI-ToF MS provided nearly similar results. For example, the molecular weight of 10600 Da was obtained by MALDI-ToF MS, while GPC gave 10500 g/mol (Mw/Mn = 1.17). However, if the polymer is poly distributed, MALDI-ToF MS cannot provide an accurate value. This was exemplified for a polymer with a molecular weight of 3130 Da measured by MALDI-TOF MS, while GPC showed 2300 g/mol (Mw/Mn = 1.38). The size, size distribution and magnetic properties of the hybrid particles were different by changing either the molecular weight or concentration of the polymer surfactants. The analysis from TEM characterization showed that the size of cobalt nanoparticles stabilized with polystyrene of lower molecular weight (Mn = 2300 g/mol) varied from 12–22 nm, while the size with middle (Mn = 4500 g/mol) and higher molecular weight (Mn = 10500 g/mol) of polystyrene-coated cobalt nanoparticles showed little change. Magnetic measurements exhibited that the small cobalt particles (12 nm) were superparamagnetic, while larger particles (21 nm) were ferromagnetic and assembled into 1-D chains. The grafting density calculated from thermogravimetric analysis showed that a higher grafting density of polystyrene was obtained with lower molecular weight (Mn = 2300 g/mol) than those with higher molecular weight (Mn = 10500 g/mol). Due to the larger steric hindrance, polystyrene with higher molecular weight cannot form a dense shell on the surface of the nanoparticles, which resulted in a lower grafting density. Wide angle X-ray scattering measurements revealed the epsilon cobalt crystalline phases of both superparamagnetic Co NPs coated with polystyrene (Mn = 2300 g/mol) and ferromagnetic Co NPs coated with polystyrene (Mn = 10500 g/mol). Furthermore, a stability study showed that PS-Co NPs prepared with higher polymer concentration and polymer molecular weight exhibited a better stability.
Distributed decision-making studies the choices made among a group of interactive and self-interested agents. Specifically, this thesis is concerned with the optimal sequence of choices an agent makes as it tries to maximize its achievement on one or multiple objectives in the dynamic environment. The optimization of distributed decision-making is important in many real-life applications, e.g., resource allocation (of products, energy, bandwidth, computing power, etc.) and robotics (heterogeneous agent cooperation on games or tasks), in various fields such as vehicular network, Internet of Things, smart grid, etc.
This thesis proposes three multi-agent reinforcement learning algorithms combined with game-theoretic tools to study strategic interaction between decision makers, using resource allocation in vehicular network as an example. Specifically, the thesis designs an interaction mechanism based on second-price auction, incentivizes the agents to maximize multiple short-term and long-term, individual and system objectives, and simulates a dynamic environment with realistic mobility data to evaluate algorithm performance and study agent behavior.
Theoretical results show that the mechanism has Nash equilibria, is a maximization of social welfare and Pareto optimal allocation of resources in a stationary environment. Empirical results show that in the dynamic environment, our proposed learning algorithms outperform state-of-the-art algorithms in single and multi-objective optimization, and demonstrate very good generalization property in significantly different environments. Specifically, with the long-term multi-objective learning algorithm, we demonstrate that by considering the long-term impact of decisions, as well as by incentivizing the agents with a system fairness reward, the agents achieve better results in both individual and system objectives, even when their objectives are private, randomized, and changing over time. Moreover, the agents show competitive behavior to maximize individual payoff when resource is scarce, and cooperative behavior in achieving a system objective when resource is abundant; they also learn the rules of the game, without prior knowledge, to overcome disadvantages in initial parameters (e.g., a lower budget).
To address practicality concerns, the thesis also provides several computational performance improvement methods, and tests the algorithm in a single-board computer. Results show the feasibility of online training and inference in milliseconds.
There are many potential future topics following this work. 1) The interaction mechanism can be modified into a double-auction, eliminating the auctioneer, resembling a completely distributed, ad hoc network; 2) the objectives are assumed to be independent in this thesis, there may be a more realistic assumption regarding correlation between objectives, such as a hierarchy of objectives; 3) current work limits information-sharing between agents, the setup befits applications with privacy requirements or sparse signaling; by allowing more information-sharing between the agents, the algorithms can be modified for more cooperative scenarios such as robotics.
Towards greener stationary phases : thermoresponsive and carbonaceous chromatographic supports
(2011)
Polymers which are sensitive towards external physical, chemical and electrical stimuli are termed as ‘intelligent materials’ and are widely used in medical and engineering applications. Presently, polymers which can undergo a physical change when heat is applied at a certain temperature (cloud point) in water are well-studied for this property in areas of separation chemistry, gene and drug delivery and as surface modifiers. One example of such a polymer is the poly (N-isopropylacrylamide) PNIPAAM, where it is dissolved well in water below 32 oC, while by increasing the temperature further leads to its precipitation. In this work, an alternative polymer poly (2-(2-methoxy ethoxy)ethyl methacrylate-co- oligo(ethylene glycol) methacrylate) (P(MEO2MA-co-OEGMA)) is studied due to its biocompatibility and the ability to vary its cloud points in water. When a layer of temperature responsive polymer was attached to a single continuous porous piece of silica-based material known as a monolith, the thermoresponsive characteristic was transferred to the column surfaces. The hybrid material was demonstrated to act as a simple temperature ‘switch’ in the separation of a mixture of five steroids under water. Different analytes were observed to be separated under varying column temperatures. Furthermore, more complex biochemical compounds such as proteins were also tested for separation. The importance of this work is attributed to separation processes utilizing environmentally friendly conditions, since harsh chemical environments conventionally used to resolve biocompounds could cause their biological activities to be rendered inactive.
Infants' lexical processing is modulated by featural manipulations made to words, suggesting that early lexical representations are sufficiently specified to establish a match with the corresponding label. However, the precise degree of detail in early words requires further investigation due to equivocal findings. We studied this question by assessing children’s sensitivity to the degree of featural manipulation (Chapters 2 and 3), and sensitivity to the featural makeup of homorganic and heterorganic consonant clusters (Chapter 4). Gradient sensitivity on the one hand and sensitivity to homorganicity on the other hand would suggest that lexical processing makes use of sub-phonemic information, which in turn would indicate that early words contain sub-phonemic detail. The studies presented in this thesis assess children’s sensitivity to sub-phonemic detail using minimally demanding online paradigms suitable for infants: single-picture pupillometry and intermodal preferential looking. Such paradigms have the potential to uncover lexical knowledge that may be masked otherwise due to cognitive limitations. The study reported in Chapter 2 obtained a differential response in pupil dilation to the degree of featural manipulation, a result consistent with gradient sensitivity. The study reported in Chapter 3 obtained a differential response in proportion of looking time and pupil dilation to the degree of featural manipulation, a result again consistent with gradient sensitivity. The study reported in Chapter 4 obtained a differential response to the manipulation of homorganic and heterorganic consonant clusters, a result consistent with sensitivity to homorganicity. These results suggest that infants' lexical representations are not only specific, but also detailed to the extent that they contain sub-phonemic information.
Deep learning has seen widespread application in many domains, mainly for its ability to learn data representations from raw input data. Nevertheless, its success has so far been coupled with the availability of large annotated (labelled) datasets. This is a requirement that is difficult to fulfil in several domains, such as in medical imaging. Annotation costs form a barrier in extending deep learning to clinically-relevant use cases. The labels associated with medical images are scarce, since the generation of expert annotations of multimodal patient data at scale is non-trivial, expensive, and time-consuming. This substantiates the need for algorithms that learn from the increasing amounts of unlabeled data. Self-supervised representation learning algorithms offer a pertinent solution, as they allow solving real-world (downstream) deep learning tasks with fewer annotations. Self-supervised approaches leverage unlabeled samples to acquire generic features about different concepts, enabling annotation-efficient downstream task solving subsequently.
Nevertheless, medical images present multiple unique and inherent challenges for existing self-supervised learning approaches, which we seek to address in this thesis: (i) medical images are multimodal, and their multiple modalities are heterogeneous in nature and imbalanced in quantities, e.g. MRI and CT; (ii) medical scans are multi-dimensional, often in 3D instead of 2D; (iii) disease patterns in medical scans are numerous and their incidence exhibits a long-tail distribution, so it is oftentimes essential to fuse knowledge from different data modalities, e.g. genomics or clinical data, to capture disease traits more comprehensively; (iv) Medical scans usually exhibit more uniform color density distributions, e.g. in dental X-Rays, than natural images. Our proposed self-supervised methods meet these challenges, besides significantly reducing the amounts of required annotations.
We evaluate our self-supervised methods on a wide array of medical imaging applications and tasks. Our experimental results demonstrate the obtained gains in both annotation-efficiency and performance; our proposed methods outperform many approaches from related literature. Additionally, in case of fusion with genetic modalities, our methods also allow for cross-modal interpretability. In this thesis, not only we show that self-supervised learning is capable of mitigating manual annotation costs, but also our proposed solutions demonstrate how to better utilize it in the medical imaging domain. Progress in self-supervised learning has the potential to extend deep learning algorithms application to clinical scenarios.
Virtualized cloud data centers provide on-demand resources, enable agile resource provisioning, and host heterogeneous applications with different resource requirements. These data centers consume enormous amounts of energy, increasing operational expenses, inducing high thermal inside data centers, and raising carbon dioxide emissions. The increase in energy consumption can result from ineffective resource management that causes inefficient resource utilization. This dissertation presents detailed models and novel techniques and algorithms for virtual resource management in cloud data centers. The proposed techniques take into account Service Level Agreements (SLAs) and workload heterogeneity in terms of memory access demand and communication patterns of web applications and High Performance Computing (HPC) applications. To evaluate our proposed techniques, we use simulation and real workload traces of web applications and HPC applications and compare our techniques against the other recently proposed techniques using several performance metrics. The major contributions of this dissertation are the following: proactive resource provisioning technique based on robust optimization to increase the hosts' availability for hosting new VMs while minimizing the idle energy consumption. Additionally, this technique mitigates undesirable changes in the power state of the hosts by which the hosts' reliability can be enhanced in avoiding failure during a power state change. The proposed technique exploits the range-based prediction algorithm for implementing robust optimization, taking into consideration the uncertainty of demand. An adaptive range-based prediction for predicting workload with high fluctuations in the short-term. The range prediction is implemented in two ways: standard deviation and median absolute deviation. The range is changed based on an adaptive confidence window to cope with the workload fluctuations. A robust VM consolidation for efficient energy and performance management to achieve equilibrium between energy and performance trade-offs. Our technique reduces the number of VM migrations compared to recently proposed techniques. This also contributes to a reduction in energy consumption by the network infrastructure. Additionally, our technique reduces SLA violations and the number of power state changes. A generic model for the network of a data center to simulate the communication delay and its impact on VM performance, as well as network energy consumption. In addition, a generic model for a memory-bus of a server, including latency and energy consumption models for different memory frequencies. This allows simulating the memory delay and its influence on VM performance, as well as memory energy consumption. Communication-aware and energy-efficient consolidation for parallel applications to enable the dynamic discovery of communication patterns and reschedule VMs using migration based on the determined communication patterns. A novel dynamic pattern discovery technique is implemented, based on signal processing of network utilization of VMs instead of using the information from the hosts' virtual switches or initiation from VMs. The result shows that our proposed approach reduces the network's average utilization, achieves energy savings due to reducing the number of active switches, and provides better VM performance compared to CPU-based placement. Memory-aware VM consolidation for independent VMs, which exploits the diversity of VMs' memory access to balance memory-bus utilization of hosts. The proposed technique, Memory-bus Load Balancing (MLB), reactively redistributes VMs according to their utilization of a memory-bus using VM migration to improve the performance of the overall system. Furthermore, Dynamic Voltage and Frequency Scaling (DVFS) of the memory and the proposed MLB technique are combined to achieve better energy savings.
Galaxy clusters are the largest known gravitationally bound objects, their study is important for both an intrinsic understanding of their systems and an investigation of the large scale structure of the universe. The multi- component nature of galaxy clusters offers multiple observable signals across the electromagnetic spectrum. At X-ray wavelengths, galaxy clusters are simply identified as X-ray luminous, spatially extended, and extragalactic sources. X-ray observations offer the most powerful technique for constructing cluster catalogues. The main advantages of the X-ray cluster surveys are their excellent purity and completeness and the X-ray observables are tightly correlated with mass, which is indeed the most fundamental parameter of clusters. In my thesis I have conducted the 2XMMi/SDSS galaxy cluster survey, which is a serendipitous search for galaxy clusters based on the X-ray extended sources in the XMM-Newton Serendipitous Source Catalogue (2XMMi-DR3). The main aims of the survey are to identify new X-ray galaxy clusters, investigate their X-ray scaling relations, identify distant cluster candidates, and study the correlation of the X-ray and optical properties. The survey is constrained to those extended sources that are in the footprint of the Sloan Digital Sky Survey (SDSS) in order to be able to identify the optical counterparts as well as to measure their redshifts that are mandatory to measure their physical properties. The overlap area be- tween the XMM-Newton fields and the SDSS-DR7 imaging, the latest SDSS data release at the starting of the survey, is 210 deg^2. The survey comprises 1180 X-ray cluster candidates with at least 80 background-subtracted photon counts, which passed the quality control process. To measure the optical redshifts of the X-ray cluster candidates, I used three procedures; (i) cross-matching these candidates with the recent and largest optically selected cluster catalogues in the literature, which yielded the photometric redshifts of about a quarter of the X-ray cluster candidates. (ii) I developed a finding algorithm to search for overdensities of galaxies at the positions of the X-ray cluster candidates in the photometric redshift space and to measure their redshifts from the SDSS-DR8 data, which provided the photometric redshifts of 530 groups/clusters. (iii) I developed an algorithm to identify the cluster candidates associated with spectroscopically targeted Luminous Red Galaxies (LRGs) in the SDSS-DR9 and to measure the cluster spectroscopic redshift, which provided 324 groups and clusters with spectroscopic confirmation based on spectroscopic redshift of at least one LRG. In total, the optically confirmed cluster sample comprises 574 groups and clusters with redshifts (0.03 ≤ z ≤ 0.77), which is the largest X-ray selected cluster catalogue to date based on observations from the current X-ray observatories (XMM-Newton, Chandra, Suzaku, and Swift/XRT). Among the cluster sample, about 75 percent are newly X-ray discovered groups/clusters and 40 percent are new systems to the literature. To determine the X-ray properties of the optically confirmed cluster sample, I reduced and analysed their X-ray data in an automated way following the standard pipelines of processing the XMM-Newton data. In this analysis, I extracted the cluster spectra from EPIC(PN, MOS1, MOS2) images within an optimal aperture chosen to maximise the signal-to-noise ratio. The spectral fitting procedure provided the X-ray temperatures kT (0.5 - 7.5 keV) for 345 systems that have good quality X-ray data. For all the optically confirmed cluster sample, I measured the physical properties L500 (0.5 x 10^42 – 1.2 x 10^45 erg s-1 ) and M500 (1.1 x 10^13 – 4.9 x 10^14 M⊙) from an iterative procedure using published scaling relations. The present X-ray detected groups and clusters are in the low and intermediate luminosity regimes apart from few luminous systems, thanks to the XMM-Newton sensitivity and the available XMM-Newton deep fields The optically confirmed cluster sample with measurements of redshift and X-ray properties can be used for various astrophysical applications. As a first application, I investigated the LX - T relation for the first time based on a large cluster sample of 345 systems with X-ray spectroscopic parameters drawn from a single survey. The current sample includes groups and clusters with wide ranges of redshifts, temperatures, and luminosities. The slope of the relation is consistent with the published ones of nearby clusters with higher temperatures and luminosities. The derived relation is still much steeper than that predicted by self-similar evolution. I also investigated the evolution of the slope and the scatter of the LX - T relation with the cluster redshift. After excluding the low luminosity groups, I found no significant changes of the slope and the intrinsic scatter of the relation with redshift when dividing the sample into three redshift bins. When including the low luminosity groups in the low redshift subsample, I found its LX - T relation becomes after than the relation of the intermediate and high redshift subsamples. As a second application of the optically confirmed cluster sample from our ongoing survey, I investigated the correlation between the cluster X-ray and the optical parameters that have been determined in a homogenous way. Firstly, I investigated the correlations between the BCG properties (absolute magnitude and optical luminosity) and the cluster global proper- ties (redshift and mass). Secondly, I computed the richness and the optical luminosity within R500 of a nearby subsample (z ≤ 0.42, with a complete membership detection from the SDSS data) with measured X-ray temperatures from our survey. The relation between the estimated optical luminosity and richness is also presented. Finally, the correlation between the cluster optical properties (richness and luminosity) and the cluster global properties (X-ray luminosity, temperature, mass) are investigated.
The demand for learning Design Thinking (DT) as a path towards acquiring 21st-century skills has increased globally in the last decade. Because DT education originated in the Silicon Valley context of the d.school at Stanford, it is important to evaluate how the teaching of the methodology adapts to different cultural contexts.The thesis explores the impact of the socio-cultural context on DT education.
DT institutes in Cape Town, South Africa and Kuala Lumpur, Malaysia, were visited to observe their programs and conduct 22 semistructured interviews with local educators regarding their adaption strategies. Grounded theory methodology was used to develop a model of Socio-Cultural Adaptation of Design Thinking Education that maps these strategies onto five dimensions: Planning, Process, People, Place, and Presentation. Based on this model, a list of recommendations is provided to help DT educators and practitioners in designing and delivering culturally inclusive DT education.