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Different properties of programs, implemented in Constraint Handling Rules (CHR), have already been investigated. Proving these properties in CHR is fairly simpler than proving them in any type of imperative programming language, which triggered the proposal of a methodology to map imperative programs into equivalent CHR. The equivalence of both programs implies that if a property is satisfied for one, then it is satisfied for the other. The mapping methodology could be put to other beneficial uses. One such use is the automatic generation of global constraints, at an attempt to demonstrate the benefits of having a rule-based implementation for constraint solvers.
The aim of this work was the generation of carbon materials with high surface area, exhibiting a hierarchical pore system in the macro- and mesorange. Such a pore system facilitates the transport through the material and enhances the interaction with the carbon matrix (macropores are pores with diameters > 50 nm, mesopores between 2 – 50 nm). Thereto, new strategies for the synthesis of novel carbon materials with designed porosity were developed that are in particular useful for the storage of energy. Besides the porosity, it is the graphene structure itself that determines the properties of a carbon material. Non-graphitic carbon materials usually exhibit a quite large degree of disorder with many defects in the graphene structure, and thus exhibit inherent microporosity (d < 2nm). These pores are traps and oppose reversible interaction with the carbon matrix. Furthermore they reduce the stability and conductivity of the carbon material, which was undesired for the proposed applications. As one part of this work, the graphene structures of different non-graphitic carbon materials were studied in detail using a novel wide-angle x-ray scattering model that allowed precise information about the nature of the carbon building units (graphene stacks). Different carbon precursors were evaluated regarding their potential use for the synthesis shown in this work, whereas mesophase pitch proved to be advantageous when a less disordered carbon microstructure is desired. By using mesophase pitch as carbon precursor, two templating strategies were developed using the nanocasting approach. The synthesized (monolithic) materials combined for the first time the advantages of a hierarchical interconnected pore system in the macro- and mesorange with the advantages of mesophase pitch as carbon precursor. In the first case, hierarchical macro- / mesoporous carbon monoliths were synthesized by replication of hard (silica) templates. Thus, a suitable synthesis procedure was developed that allowed the infiltration of the template with the hardly soluble carbon precursor. In the second case, hierarchical macro- / mesoporous carbon materials were synthesized by a novel soft-templating technique, taking advantage of the phase separation (spinodal decomposition) between mesophase pitch and polystyrene. The synthesis also allowed the generation of monolithic samples and incorporation of functional nanoparticles into the material. The synthesized materials showed excellent properties as an anode material in lithium batteries and support material for supercapacitors.
Monolayers of rod-shaped and disc-shaped liquid crystalline compounds at the air-water interface
(1986)
Calamitic (rod-shaped) and discotic (disc-shaped) thermotropic liquid crystalline (LC) compounds were spread at the air-water interface, and their ability to form monolayers was studied. The calamitic LCs investigated were found to form monolayers which behave analogously to conventional amphiphiles such as fatty acids. The spreading of the discotic LCs produced monolayers as well, but with a behaviour different from classical amphiphiles. The areas occupied per molecule are too small to allow the contact of all hydrophilic groups with the water surface and the packing of all hydrophobic chains. Various molecular arrangements of the discotics at the water surface to fit the spreading data are discussed.
In order to investigate the temporal characteristics of cognitive processing, we apply multivariate phase synchronization analysis to event-related potentials. The experimental design combines a semantic incongruity in a sentence context with a physical mismatch (color change). In the ERP average, these result in an N400 component and a P300-like positivity, respectively. The synchronization analysis shows an effect of global desynchronization in the theta band around 288ms after stimulus presentation for the semantic incongruity, while the physical mismatch elicits an increase of global synchronization in the alpha band around 204ms. Both of these effects clearly precede those in the ERP average. Moreover, the delay between synchronization effect and ERP component correlates with the complexity of the cognitive processes.
We investigate how inviting students to set task-based goals affects usage of an online learning platform and course performance. We design and implement a randomized field experiment in a large mandatory economics course with blended learning elements. The low-cost treatment induces students to use the online learning system more often, more intensively, and to begin earlier with exam preparation. Treated students perform better in the course than the control group: they are 18.8% (0.20 SD) more likely to pass the exam and earn 6.7% (0.19 SD) more points on the exam. There is no evidence that treated students spend significantly more time, rather they tend to shift to more productive learning methods. The heterogeneity analysis suggests that higher treatment effects are associated with higher levels of behavioral bias but also with poor early course behavior.
High growth firms (HGFs) are important for job creation and considered to be precursors of economic growth. We investigate how formal institutions, like product- and labor-market regulations, as well as the quality of regional governments that implement these regulations, affect HGF development across European regions. Using data from Eurostat, OECD, WEF, and Gothenburg University, we show that both regulatory stringency and the quality of the regional government influence the regional shares of HGFs. More importantly, we find that the effect of labor- and product-market regulations ultimately depends on the quality of regional governments: in regions with high quality of government, the share of HGFs is neither affected by the level of product market regulation, nor by more or less flexibility in hiring and firing practices. Our findings contribute to the debate on the effects of regulations by showing that regulations are not, per se, “good, bad, and ugly”, rather their impact depends on the efficiency of regional governments. Our paper offers important building blocks to develop tailored policy measures that may influence the development of HGFs in a region.
Adsorption layers of soluble surfactants enable and govern a variety of phenomena in surface and colloidal sciences, such as foams. The ability of a surfactant solution to form wet foam lamellae is governed by the surface dilatational rheology. Only systems having a non-vanishing imaginary part in their surface dilatational modulus, E, are able to form wet foams. The aim of this thesis is to illuminate the dissipative processes that give rise to the imaginary part of the modulus. There are two controversial models discussed in the literature. The reorientation model assumes that the surfactants adsorb in two distinct states, differing in their orientation. This model is able to describe the frequency dependence of the modulus E. However, it assumes reorientation dynamics in the millisecond time regime. In order to assess this model, we designed a SHG pump-probe experiment that addresses the orientation dynamics. Results obtained reveal that the orientation dynamics occur in the picosecond time regime, being in strong contradiction with the two states model. The second model regards the interface as an interphase. The adsorption layer consists of a topmost monolayer and an adjacent sublayer. The dissipative process is due to the molecular exchange between both layers. The assessment of this model required the design of an experiment that discriminates between the surface compositional term and the sublayer contribution. Such an experiment has been successfully designed and results on elastic and viscoelastic surfactant provided evidence for the correctness of the model. Because of its inherent surface specificity, surface SHG is a powerful analytical tool that can be used to gain information on molecular dynamics and reorganization of soluble surfactants. They are central elements of both experiments. However, they impose several structural elements of the model system. During the course of this thesis, a proper model system has been identified and characterized. The combination of several linear and nonlinear optical techniques, allowed for a detailed picture of the interfacial architecture of these surfactants.
This paper sheds new light on the role of communication for cartel formation. Using machine learning to evaluate free-form chat communication among firms in a laboratory experiment, we identify typical communication patterns for both explicit cartel formation and indirect attempts to collude tacitly. We document that firms are less likely to communicate explicitly about price fixing and more likely to use indirect messages when sanctioning institutions are present. This effect of sanctions on communication reinforces the direct cartel-deterring effect of sanctions as collusion is more difficult to reach and sustain without an explicit agreement. Indirect messages have no, or even a negative, effect on prices.
The boundary paradigm (Rayner, 1975) with a novel preview manipulation was used to examine the extent of parafoveal processing of words to the right of fixation. Words n+1 and n+2 had either correct or incorrect previews prior to fixation (prior to crossing the boundary location). In addition, the manipulation utilized either a high or low frequency word in word n+1 location on the assumption that it would be more likely that n+2 preview effects could be obtained when word n+1 was high frequency. The primary findings were that there was no evidence for a preview benefit for word n+2 and no evidence for parafoveal-on-foveal effects when word n+1 is at least four letters long. We discuss implications for models of eye-movement control in reading.
The concept of hydrologic connectivity summarizes all flow processes that link separate regions of a landscape. As such, it is a central theme in the field of catchment hydrology, with influence on neighboring disciplines such as ecology and geomorphology. It is widely acknowledged to be an important key in understanding the response behavior of a catchment and has at the same time inspired research on internal processes over a broad range of scales. From this process-hydrological point of view, hydrological connectivity is the conceptual framework to link local observations across space and scales.
This is the context in which the four studies this thesis comprises of were conducted. The focus was on structures and their spatial organization as important control on preferential subsurface flow. Each experiment covered a part of the conceptualized flow path from hillslopes to the stream: soil profile, hillslope, riparian zone, and stream.
For each study site, the most characteristic structures of the investigated domain and scale, such as slope deposits and peat layers were identified based on preliminary or previous investigations or literature reviews. Additionally, further structural data was collected and topographical analyses were carried out. Flow processes were observed either based on response observations (soil moisture changes or discharge patterns) or direct measurement (advective heat transport). Based on these data, the flow-relevance of the characteristic structures was evaluated, especially with regard to hillslope to stream connectivity.
Results of the four studies revealed a clear relationship between characteristic spatial structures and the hydrological behavior of the catchment. Especially the spatial distribution of structures throughout the study domain and their interconnectedness were crucial for the establishment of preferential flow paths and their relevance for large-scale processes. Plot and hillslope-scale irrigation experiments showed that the macropores of a heterogeneous, skeletal soil enabled preferential flow paths at the scale of centimeters through the otherwise unsaturated soil. These flow paths connected throughout the soil column and across the hillslope and facilitated substantial amounts of vertical and lateral flow through periglacial slope deposits.
In the riparian zone of the same headwater catchment, the connectivity between hillslopes and stream was controlled by topography and the dualism between characteristic subsurface structures and the geomorphological heterogeneity of the stream channel. At the small scale (1 m to 10 m) highest gains always occurred at steps along the longitudinal streambed profile, which also controlled discharge patterns at the large scale (100 m) during base flow conditions (number of steps per section). During medium and high flow conditions, however, the impact of topography and parafluvial flow through riparian zone structures prevailed and dominated the large-scale response patterns.
In the streambed of a lowland river, low permeability peat layers affected the connectivity between surface water and groundwater, but also between surface water and the hyporheic zone. The crucial factor was not the permeability of the streambed itself, but rather the spatial arrangement of flow-impeding peat layers, causing increased vertical flow through narrow “windows” in contrast to predominantly lateral flow in extended areas of high hydraulic conductivity sediments.
These results show that the spatial organization of structures was an important control for hydrological processes at all scales and study areas. In a final step, the observations from different scales and catchment elements were put in relation and compared. The main focus was on the theoretical analysis of the scale hierarchies of structures and processes and the direction of causal dependencies in this context. Based on the resulting hierarchical structure, a conceptual framework was developed which is capable of representing the system’s complexity while allowing for adequate simplifications.
The resulting concept of the parabolic scale series is based on the insight that flow processes in the terrestrial part of the catchment (soil and hillslopes) converge. This means that small-scale processes assemble and form large-scale processes and responses. Processes in the riparian zone and the streambed, however, are not well represented by the idea of convergence. Here, the large-scale catchment signal arrives and is modified by structures in the riparian zone, stream morphology, and the small-scale interactions between surface water and groundwater. Flow paths diverge and processes can better be represented by proceeding from large scales to smaller ones. The catchment-scale representation of processes and structures is thus the conceptual link between terrestrial hillslope processes and processes in the riparian corridor.
The end of the cold war division of the Baltic Sea in 1989, and the three Baltic states’ return to independence in 1991 created new opportunities for the decision-makers of the area, as well as new possibilities for fashioning security in the region. This article will examine the security debate affecting the Baltic Sea region in the post-cold war period, and in particular, the relevance of the European Union to that debate. The following section will examine various concepts of security relevant to the Baltic region; the third section looks at the EU and the Baltic area; and the last part deals with the implications that EU membership by the Baltic Sea states may have for the security of the Baltic Sea zone.
In two experiments, many annotators marked antecedents for discourse deixis as unconstrained regions of text. The experiments show that annotators do converge on the identity of these text regions, though much of what they do can be captured by a simple model. Demonstrative pronouns are more likely than definite descriptions to be marked with discourse antecedents. We suggest that our methodology is suitable for the systematic study of discourse deixis.
Many methods have been proposed for the simulation of constrained mechanical systems. The most obvious of these have mild instabilities and drift problems. Consequently, stabilization techniques have been proposed A popular stabilization method is Baumgarte's technique, but the choice of parameters to make it robust has been unclear in practice. Some of the simulation methods that have been proposed and used in computations are reviewed here, from a stability point of view. This involves concepts of differential-algebraic equation (DAE) and ordinary differential equation (ODE) invariants. An explanation of the difficulties that may be encountered using Baumgarte's method is given, and a discussion of why a further quest for better parameter values for this method will always remain frustrating is presented. It is then shown how Baumgarte's method can be improved. An efficient stabilization technique is proposed, which may employ explicit ODE solvers in case of nonstiff or highly oscillatory problems and which relates to coordinate projection methods. Examples of a two-link planar robotic arm and a squeezing mechanism illustrate the effectiveness of this new stabilization method.
Many methods have been proposed for the stabilization of higher index differential-algebraic equations (DAEs). Such methods often involve constraint differentiation and problem stabilization, thus obtaining a stabilized index reduction. A popular method is Baumgarte stabilization, but the choice of parameters to make it robust is unclear in practice. Here we explain why the Baumgarte method may run into trouble. We then show how to improve it. We further develop a unifying theory for stabilization methods which includes many of the various techniques proposed in the literature. Our approach is to (i) consider stabilization of ODEs with invariants, (ii) discretize the stabilizing term in a simple way, generally different from the ODE discretization, and (iii) use orthogonal projections whenever possible. The best methods thus obtained are related to methods of coordinate projection. We discuss them and make concrete algorithmic suggestions.
The Arctic is the hot spot of the ongoing, global climate change. Over the last decades, near-surface temperatures in the Arctic have been rising almost four times faster than on global average. This amplified warming of the Arctic and the associated rapid changes of its environment are largely influenced by interactions between individual components of the Arctic climate system. On daily to weekly time scales, storms can have major impacts on the Arctic sea-ice cover and are thus an important part of these interactions within the Arctic climate. The sea-ice impacts of storms are related to high wind speeds, which enhance the drift and deformation of sea ice, as well as to changes in the surface energy budget in association with air mass advection, which impact the seasonal sea-ice growth and melt.
The occurrence of storms in the Arctic is typically associated with the passage of transient cyclones. Even though the above described mechanisms how storms/cyclones impact the Arctic sea ice are in principal known, there is a lack of statistical quantification of these effects. In accordance with that, the overarching objective of this thesis is to statistically quantify cyclone impacts on sea-ice concentration (SIC) in the Atlantic Arctic Ocean over the last four decades. In order to further advance the understanding of the related mechanisms, an additional objective is to separate dynamic and thermodynamic cyclone impacts on sea ice and assess their relative importance. Finally, this thesis aims to quantify recent changes in cyclone impacts on SIC. These research objectives are tackled utilizing various data sets, including atmospheric and oceanic reanalysis data as well as a coupled model simulation and a cyclone tracking algorithm.
Results from this thesis demonstrate that cyclones are significantly impacting SIC in the Atlantic Arctic Ocean from autumn to spring, while there are mostly no significant impacts in summer. The strength and the sign (SIC decreasing or SIC increasing) of the cyclone impacts strongly depends on the considered daily time scale and the region of the Atlantic Arctic Ocean. Specifically, an initial decrease in SIC (day -3 to day 0 relative to the cyclone) is found in the Greenland, Barents and Kara Seas, while SIC increases following cyclones (day 0 to day 5 relative to the cyclone) are mostly limited to the Barents and Kara Seas.
For the cold season, this results in a pronounced regional difference between overall (day -3 to day 5 relative to the cyclone) SIC-decreasing cyclone impacts in the Greenland Sea and overall SIC-increasing cyclone impacts in the Barents and Kara Seas. A cyclone case study based on a coupled model simulation indicates that both dynamic and thermodynamic mechanisms contribute to cyclone impacts on sea ice in winter. A typical pattern consisting of an initial dominance of dynamic sea-ice changes followed by enhanced thermodynamic ice growth after the cyclone passage was found. This enhanced ice growth after the cyclone passage most likely also explains the (statistical) overall SIC-increasing effects of cyclones in the Barents and Kara Seas in the cold season.
Significant changes in cyclone impacts on SIC over the last four decades have emerged throughout the year. These recent changes are strongly varying from region to region and month to month. The strongest trends in cyclone impacts on SIC are found in autumn in the Barents and Kara Seas. Here, the magnitude of destructive cyclone impacts on SIC has approximately doubled over the last four decades. The SIC-increasing effects following the cyclone passage have particularly weakened in the Barents Sea in autumn. As a consequence, previously existing overall SIC-increasing cyclone impacts in this region in autumn have recently disappeared. Generally, results from this thesis show that changes in the state of the sea-ice cover (decrease in mean sea-ice concentration and thickness) and near-surface air temperature are most important for changed cyclone impacts on SIC, while changes in cyclone properties (i.e. intensity) do not play a significant role.
The COVID-19 pandemic created the largest experiment in working from home. We study how persistent telework may change energy and transport consumption and costs in Germany to assess the distributional and environmental implications when working from home will stick. Based on data from the German Microcensus and available classifications of working-from-home feasibility for different occupations, we calculate the change in energy consumption and travel to work when 15% of employees work full time from home. Our findings suggest that telework translates into an annual increase in heating energy expenditure of 110 euros per worker and a decrease in transport expenditure of 840 euros per worker. All income groups would gain from telework but high-income workers gain twice as much as low-income workers. The value of time saving is between 1.3 and 6 times greater than the savings from reduced travel costs and almost 9 times higher for high-income workers than low-income workers. The direct effects on CO₂ emissions due to reduced car commuting amount to 4.5 millions tons of CO₂, representing around 3 percent of carbon emissions in the transport sector.
National Action Plans (NAPs) have been increas-ingly adopted world-wide after the Vienna Dec-laration in 1993, where it was urged to consider the improvement and promotion of Human Rights. In this paper, we discuss their usefulness and success by analysing the challenges present-ed during NAP processes as well as the benefits this set of actions entails: The challenges for their implementation outweigh its actual benefits. Nevertheless, NAPs have great potential. Based on new research, we elaborate a set of recom-mendations for improving the design and imple-mentation of national action planning. In order to effectively bring NAP into practice, we consider it crucial to plan and analyse every state local circumstances in detail. The latter is important, since the implementation of a concrete set of actions is intended to directly transform and improve the local living conditions of the people. In a long-term perspective, we defend the benefit of NAP’s implementation for complying obliga-tions set up by HR treaties.
Antarctic glacier forfields are extreme environments and pioneer sites for ecological succession. The Antarctic continent shows microbial community development as a natural laboratory because of its special environment, geographic isolation and little anthropogenic influence. Increasing temperatures due to global warming lead to enhanced deglaciation processes in cold-affected habitats and new terrain is becoming exposed to soil formation and accessible for microbial colonisation. This study aims to understand the structure and development of glacier forefield bacterial communities, especially how soil parameters impact the microorganisms and how those are adapted to the extreme conditions of the habitat. To this effect, a combination of cultivation experiments, molecular, geophysical and geochemical analysis was applied to examine two glacier forfields of the Larsemann Hills, East Antarctica. Culture-independent molecular tools such as terminal restriction length polymorphism (T-RFLP), clone libraries and quantitative real-time PCR (qPCR) were used to determine bacterial diversity and distribution. Cultivation of yet unknown species was carried out to get insights in the physiology and adaptation of the microorganisms. Adaptation strategies of the microorganisms were studied by determining changes of the cell membrane phospholipid fatty acid (PLFA) inventory of an isolated bacterium in response to temperature and pH fluctuations and by measuring enzyme activity at low temperature in environmental soil samples. The two studied glacier forefields are extreme habitats characterised by low temperatures, low water availability and small oligotrophic nutrient pools and represent sites of different bacterial succession in relation to soil parameters. The investigated sites showed microbial succession at an early step of soil formation near the ice tongue in comparison to closely located but rather older and more developed soil from the forefield. At the early step the succession is influenced by a deglaciation-dependent areal shift of soil parameters followed by a variable and prevalently depth-related distribution of the soil parameters that is driven by the extreme Antarctic conditions. The dominant taxa in the glacier forefields are Actinobacteria, Acidobacteria, Proteobacteria, Bacteroidetes, Cyanobacteria and Chloroflexi. The connection of soil characteristics with bacterial community structure showed that soil parameter and soil formation along the glacier forefield influence the distribution of certain phyla. In the early step of succession the relative undifferentiated bacterial diversity reflects the undifferentiated soil development and has a high potential to shift according to past and present environmental conditions. With progressing development environmental constraints such as water or carbon limitation have a greater influence. Adapting the culturing conditions to the cold and oligotrophic environment, the number of culturable heterotrophic bacteria reached up to 108 colony forming units per gram soil and 148 isolates were obtained. Two new psychrotolerant bacteria, Herbaspirillum psychrotolerans PB1T and Chryseobacterium frigidisoli PB4T, were characterised in detail and described as novel species in the family of Oxalobacteraceae and Flavobacteriaceae, respectively. The isolates are able to grow at low temperatures tolerating temperature fluctuations and they are not specialised to a certain substrate, therefore they are well-adapted to the cold and oligotrophic environment. The adaptation strategies of the microorganisms were analysed in environmental samples and cultures focussing on extracellular enzyme activity at low temperature and PLFA analyses. Extracellular phosphatases (pH 11 and pH 6.5), β-glucosidase, invertase and urease activity were detected in the glacier forefield soils at low temperature (14°C) catalysing the conversion of various compounds providing necessary substrates and may further play a role in the soil formation and total carbon turnover of the habitat. The PLFA analysis of the newly isolated species C. frigidisoli showed that the cold-adapted strain develops different strategies to maintain the cell membrane function under changing environmental conditions by altering the PLFA inventory at different temperatures and pH values. A newly discovered fatty acid, which was not found in any other microorganism so far, significantly increased at decreasing temperature and low pH and thus plays an important role in the adaption of C. frigidisoli. This work gives insights into the diversity, distribution and adaptation mechanisms of microbial communities in oligotrophic cold-affected soils and shows that Antarctic glacier forefields are suitable model systems to study bacterial colonisation in connection to soil formation.
Abstract interpretation-based model checking provides an approach to verifying properties of infinite-state systems. In practice, most previous work on abstract model checking is either restricted to verifying universal properties, or develops special techniques for temporal logics such as modal transition systems or other dual transition systems. By contrast we apply completely standard techniques for constructing abstract interpretations to the abstraction of a CTL semantic function, without restricting the kind of properties that can be verified. Furthermore we show that this leads directly to implementation of abstract model checking algorithms for abstract domains based on constraints, making use of an SMT solver.
This article describes a HMM-based word-alignment method that can selectively enforce a contiguity constraint. This method has a direct application in the extraction of a bilingual terminological lexicon from a parallel corpus, but can also be used as a preliminary step for the extraction of phrase pairs in a Phrase-Based Statistical Machine Translation system. Contiguous source words composing terms are aligned to contiguous target language words. The HMM is transformed into a Weighted Finite State Transducer (WFST) and contiguity constraints are enforced by specific multi-tape WFSTs. The proposed method is especially suited when basic linguistic resources (morphological analyzer, part-of-speech taggers and term extractors) are available for the source language only.
This paper describes a two-level formalism where feature structures are used in contextual rules. Whereas usual two-level grammars describe rational sets over symbol pairs, this new formalism uses tree structured regular expressions. They allow an explicit and precise definition of the scope of feature structures. A given surface form may be described using several feature structures. Feature unification is expressed in contextual rules using variables, like in a unification grammar. Grammars are compiled in finite state multi-tape transducers.
Data dependencies, or integrity constraints, are used to improve the quality of a database schema, to optimize queries, and to ensure consistency in a database. In the last years conditional dependencies have been introduced to analyze and improve data quality. In short, a conditional dependency is a dependency with a limited scope defined by conditions over one or more attributes. Only the matching part of the instance must adhere to the dependency. In this paper we focus on conditional inclusion dependencies (CINDs). We generalize the definition of CINDs, distinguishing covering and completeness conditions. We present a new use case for such CINDs showing their value for solving complex data quality tasks. Further, we define quality measures for conditions inspired by precision and recall. We propose efficient algorithms that identify covering and completeness conditions conforming to given quality thresholds. Our algorithms choose not only the condition values but also the condition attributes automatically. Finally, we show that our approach efficiently provides meaningful and helpful results for our use case.
Data obtained from foreign data sources often come with only superficial structural information, such as relation names and attribute names. Other types of metadata that are important for effective integration and meaningful querying of such data sets are missing. In particular, relationships among attributes, such as foreign keys, are crucial metadata for understanding the structure of an unknown database. The discovery of such relationships is difficult, because in principle for each pair of attributes in the database each pair of data values must be compared. A precondition for a foreign key is an inclusion dependency (IND) between the key and the foreign key attributes. We present with Spider an algorithm that efficiently finds all INDs in a given relational database. It leverages the sorting facilities of DBMS but performs the actual comparisons outside of the database to save computation. Spider analyzes very large databases up to an order of magnitude faster than previous approaches. We also evaluate in detail the effectiveness of several heuristics to reduce the number of necessary comparisons. Furthermore, we generalize Spider to find composite INDs covering multiple attributes, and partial INDs, which are true INDs for all but a certain number of values. This last type is particularly relevant when integrating dirty data as is often the case in the life sciences domain - our driving motivation.
Local Orders, Global Chaos
(1999)
Hyperspectral remote sensing of the spatial and temporal heterogeneity of low Arctic vegetation
(2019)
Arctic tundra ecosystems are experiencing warming twice the global average and Arctic vegetation is responding in complex and heterogeneous ways. Shifting productivity, growth, species composition, and phenology at local and regional scales have implications for ecosystem functioning as well as the global carbon and energy balance. Optical remote sensing is an effective tool for monitoring ecosystem functioning in this remote biome. However, limited field-based spectral characterization of the spatial and temporal heterogeneity limits the accuracy of quantitative optical remote sensing at landscape scales. To address this research gap and support current and future satellite missions, three central research questions were posed:
• Does canopy-level spectral variability differ between dominant low Arctic vegetation communities and does this variability change between major phenological phases?
• How does canopy-level vegetation colour images recorded with high and low spectral resolution devices relate to phenological changes in leaf-level photosynthetic pigment concentrations?
• How does spatial aggregation of high spectral resolution data from the ground to satellite scale influence low Arctic tundra vegetation signatures and thereby what is the potential of upcoming hyperspectral spaceborne systems for low Arctic vegetation characterization?
To answer these questions a unique and detailed database was assembled. Field-based canopy-level spectral reflectance measurements, nadir digital photographs, and photosynthetic pigment concentrations of dominant low Arctic vegetation communities were acquired at three major phenological phases representing early, peak and late season. Data were collected in 2015 and 2016 in the Toolik Lake Research Natural Area located in north central Alaska on the North Slope of the Brooks Range. In addition to field data an aerial AISA hyperspectral image was acquired in the late season of 2016. Simulations of broadband Sentinel-2 and hyperspectral Environmental and Mapping Analysis Program (EnMAP) satellite reflectance spectra from ground-based reflectance spectra as well as simulations of EnMAP imagery from aerial hyperspectral imagery were also obtained.
Results showed that canopy-level spectral variability within and between vegetation communities differed by phenological phase. The late season was identified as the most discriminative for identifying many dominant vegetation communities using both ground-based and simulated hyperspectral reflectance spectra. This was due to an overall reduction in spectral variability and comparable or greater differences in spectral reflectance between vegetation communities in the visible near infrared spectrum.
Red, green, and blue (RGB) indices extracted from nadir digital photographs and pigment-driven vegetation indices extracted from ground-based spectral measurements showed strong significant relationships. RGB indices also showed moderate relationships with chlorophyll and carotenoid pigment concentrations. The observed relationships with the broadband RGB channels of the digital camera indicate that vegetation colour strongly influences the response of pigment-driven spectral indices and digital cameras can track the seasonal development and degradation of photosynthetic pigments.
Spatial aggregation of hyperspectral data from the ground to airborne, to simulated satel-lite scale was influenced by non-photosynthetic components as demonstrated by the distinct shift of the red edge to shorter wavelengths. Correspondence between spectral reflectance at the three scales was highest in the red spectrum and lowest in the near infra-red. By artificially mixing litter spectra at different proportions to ground-based spectra, correspondence with aerial and satellite spectra increased. Greater proportions of litter were required to achieve correspondence at the satellite scale.
Overall this thesis found that integrating multiple temporal, spectral, and spatial data is necessary to monitor the complexity and heterogeneity of Arctic tundra ecosystems. The identification of spectrally similar vegetation communities can be optimized using non-peak season hyperspectral data leading to more detailed identification of vegetation communities. The results also highlight the power of vegetation colour to link ground-based and satellite data. Finally, a detailed characterization non-photosynthetic ecosystem components is crucial for accurate interpretation of vegetation signals at landscape scales.
Revisiting public investment
(2004)
The consumption equivalence method is the theoretical basis of public cost-benefit analysis. Consumption equivalence public capital prices are explicitly introduces in order to sufficiently care for the opportunity cost of public expenditure. This can solve the dispute about the social rate of discount within public cost-benefit analysis witch was generated on a criterion looking similar to the capital value formula, known as Lind’s approach. The social rate of discount is liberated from opportunity costs considerations and the discounting away of the effects for future welfare vanishes. The corresponding question whether one should accept a positive value of the pure rate of social time preference is an old issue. Its current state between the prescriptive and descriptive view can also be interpreted as a consequence of the oversimplification of standard cost– benefit analysis. But apart from an economic self-process the pure rate of social time preference is also defined as a business-as-usual value of social distance discounting. Hence, a political choice has to be made about this rate which is free in principal.
An exhaustive and disjoint decomposition of social choice situations is derived in a general set theoretical framework using the new tools of the Lifted Pareto relation on the power set of social states representing a pre-choice comparison of choice option sets. The main result is the classification of social choice situations which include three types of social choice problems. First, we usually observe the common incompleteness of the Pareto relation. Second, a kind of non-compactness problem of a choice set of social states can be generated. Finally, both can be combined. The first problem root can be regarded as natural everyday dilemma of social choice theory whereas the second may probably be much more due to modeling technique implications. The distinction is enabled at a very general set theoretical level. Hence, the derived classification of social choice situations is applicable on almost every relevant economic model.
Causes for slow weathering and erosion in the steep, warm, monsoon-subjected Highlands of Sri Lanka
(2018)
In the Highlands of Sri Lanka, erosion and chemical weathering rates are among the lowest for global mountain denudation. In this tropical humid setting, highly weathered deep saprolite profiles have developed from high-grade metamorphic charnockite during spheroidal weathering of the bedrock. The spheroidal weathering produces rounded corestones and spalled rindlets at the rock-saprolite interface. I used detailed textural, mineralogical, chemical, and electron-microscopic (SEM, FIB, TEM) analyses to identify the factors limiting the rate of weathering front advance in the profile, the sequence of weathering reactions, and the underlying mechanisms. The first mineral attacked by weathering was found to be pyroxene initiated by in situ Fe oxidation, followed by in situ biotite oxidation. Bulk dissolution of the primary minerals is best described with a dissolution – re-precipitation process, as no chemical gradients towards the mineral surface and sharp structural boundaries are observed at the nm scale. Only the local oxidation in pyroxene and biotite is better described with an ion by ion process. The first secondary phases are oxides and amorphous precipitates from which secondary minerals (mainly smectite and kaolinite) form. Only for biotite direct solid state transformation to kaolinite is likely. The initial oxidation of pyroxene and biotite takes place in locally restricted areas and is relatively fast: log J = -11 molmin/(m2 s). However, calculated corestone-scale mineral oxidation rates are comparable to corestone-scale mineral dissolution rates: log R = -13 molpx/(m2 s) and log R = -15 molbt/(m2 s). The oxidation reaction results in a volume increase. Volumetric calculations suggest that this observed oxidation leads to the generation of porosity due to the formation of micro-fractures in the minerals and the bedrock allowing for fluid transport and subsequent dissolution of plagioclase. At the scale of the corestone, this fracture reaction is responsible for the larger fractures that lead to spheroidal weathering and to the formation of rindlets. Since these fractures have their origin from the initial oxidational induced volume increase, oxidation is the rate limiting parameter for weathering to take place. The ensuing plagioclase weathering leads to formation of high secondary porosity in the corestone over a distance of only a few cm and eventually to the final disaggregation of bedrock to saprolite. As oxidation is the first weathering reaction, the supply of O2 is a rate-limiting factor for chemical weathering. Hence, the supply of O2 and its consumption at depth connects processes at the weathering front with erosion at the surface in a feedback mechanism. The strength of the feedback depends on the relative weight of advective versus diffusive transport of O2 through the weathering profile. The feedback will be stronger with dominating diffusive transport. The low weathering rate ultimately depends on the transport of O2 through the whole regolith, and on lithological factors such as low bedrock porosity and the amount of Fe-bearing primary minerals. In this regard the low-porosity charnockite with its low content of Fe(II) bearing minerals impedes fast weathering reactions. Fresh weatherable surfaces are a pre-requisite for chemical weathering. However, in the case of the charnockite found in the Sri Lankan Highlands, the only process that generates these surfaces is the fracturing induced by oxidation. Tectonic quiescence in this region and low pre-anthropogenic erosion rate (attributed to a dense vegetation cover) minimize the rejuvenation of the thick and cohesive regolith column, and lowers weathering through the feedback with erosion.
In this paper we report on our experiments in teaching computer science concepts with a mix of tangible and abstract object manipulations. The goal we set ourselves was to let pupils discover the challenges one has to meet to automatically manipulate formatted text. We worked with a group of 25 secondary school pupils (9-10th grade), and they were actually able to “invent” the concept of mark-up language. From this experiment we distilled a set of activities which will be replicated in other classes (6th grade) under the guidance of maths teachers.
A method is presented of acquiring the principles of three sorting algorithms through developing interactive applications in Excel.
Cargo transport by molecular motors is ubiquitous in all eukaryotic cells and is typically driven cooperatively by several molecular motors, which may belong to one or several motor species like kinesin, dynein or myosin. These motor proteins transport cargos such as RNAs, protein complexes or organelles along filaments, from which they unbind after a finite run length. Understanding how these motors interact and how their movements are coordinated and regulated is a central and challenging problem in studies of intracellular transport. In this thesis, we describe a general theoretical framework for the analysis of such transport processes, which enables us to explain the behavior of intracellular cargos based on the transport properties of individual motors and their interactions. Motivated by recent in vitro experiments, we address two different modes of transport: unidirectional transport by two identical motors and cooperative transport by actively walking and passively diffusing motors. The case of cargo transport by two identical motors involves an elastic coupling between the motors that can reduce the motors’ velocity and/or the binding time to the filament. We show that this elastic coupling leads, in general, to four distinct transport regimes. In addition to a weak coupling regime, kinesin and dynein motors are found to exhibit a strong coupling and an enhanced unbinding regime, whereas myosin motors are predicted to attain a reduced velocity regime. All of these regimes, which we derive both by analytical calculations and by general time scale arguments, can be explored experimentally by varying the elastic coupling strength. In addition, using the time scale arguments, we explain why previous studies came to different conclusions about the effect and relevance of motor-motor interference. In this way, our theory provides a general and unifying framework for understanding the dynamical behavior of two elastically coupled molecular motors. The second mode of transport studied in this thesis is cargo transport by actively pulling and passively diffusing motors. Although these passive motors do not participate in active transport, they strongly enhance the overall cargo run length. When an active motor unbinds, the cargo is still tethered to the filament by the passive motors, giving the unbound motor the chance to rebind and continue its active walk. We develop a stochastic description for such cooperative behavior and explicitly derive the enhanced run length for a cargo transported by one actively pulling and one passively diffusing motor. We generalize our description to the case of several pulling and diffusing motors and find an exponential increase of the run length with the number of involved motors.
Verbal or visual? : How information is distributed across speech and gesture in spatial dialog
(2006)
In spatial dialog like in direction giving humans make frequent use of speechaccompanying gestures. Some gestures convey largely the same information as speech while others complement speech. This paper reports a study on how speakers distribute meaning across speech and gesture, and depending on what factors. Utterance meaning and the wider dialog context were tested by statistically analyzing a corpus of direction-giving dialogs. Problems of speech production (as indicated by discourse markers and disfluencies), the communicative goals, and the information status were found to be influential, while feedback signals by the addressee do not have any influence.
The challenge is providing teachers with the resources they need to strengthen their instructions and better prepare students for the jobs of the 21st Century. Technology can help meet the challenge. Teachers’ Tryscience is a noncommercial offer, developed by the New York Hall of Science, TeachEngineering, the National Board for Professional Teaching Standards and IBM Citizenship to provide teachers with such resources. The workshop provides deeper insight into this tool and discussion of how to support teaching of informatics in schools.
In the most abstract definition of its operational semantics, the declarative and concurrent programming language CHR is trivially non-terminating for a significant class of programs. Common refinements of this definition, in closing the gap to real-world implementations, compromise on declarativity and/or concurrency. Building on recent work and the notion of persistent constraints, we introduce an operational semantics avoiding trivial non-termination without compromising on its essential features.
We present a new analysis of illocutionary forces in dialogue. We analyze them as complex conversational moves involving two dimensions: what Speaker commits herself to and what she calls on Addressee to perform. We start from the analysis of speech acts such as confirmation requests or whimperatives, and extend the analysis to seemingly simple speech acts, such as statements and queries. Then, we show how to integrate our proposal in the framework of the Grammar for Conversation (Ginzburg, to app.), which is adequate for modelling agents' information states and how they get updated.
In the living cell, the organization of the complex internal structure relies to a large extent on molecular motors. Molecular motors are proteins that are able to convert chemical energy from the hydrolysis of adenosine triphosphate (ATP) into mechanical work. Being about 10 to 100 nanometers in size, the molecules act on a length scale, for which thermal collisions have a considerable impact onto their motion. In this way, they constitute paradigmatic examples of thermodynamic machines out of equilibrium. This study develops a theoretical description for the energy conversion by the molecular motor myosin V, using many different aspects of theoretical physics. Myosin V has been studied extensively in both bulk and single molecule experiments. Its stepping velocity has been characterized as a function of external control parameters such as nucleotide concentration and applied forces. In addition, numerous kinetic rates involved in the enzymatic reaction of the molecule have been determined. For forces that exceed the stall force of the motor, myosin V exhibits a 'ratcheting' behaviour: For loads in the direction of forward stepping, the velocity depends on the concentration of ATP, while for backward loads there is no such influence. Based on the chemical states of the motor, we construct a general network theory that incorporates experimental observations about the stepping behaviour of myosin V. The motor's motion is captured through the network description supplemented by a Markov process to describe the motor dynamics. This approach has the advantage of directly addressing the chemical kinetics of the molecule, and treating the mechanical and chemical processes on equal grounds. We utilize constraints arising from nonequilibrium thermodynamics to determine motor parameters and demonstrate that the motor behaviour is governed by several chemomechanical motor cycles. In addition, we investigate the functional dependence of stepping rates on force by deducing the motor's response to external loads via an appropriate Fokker-Planck equation. For substall forces, the dominant pathway of the motor network is profoundly different from the one for superstall forces, which leads to a stepping behaviour that is in agreement with the experimental observations. The extension of our analysis to Markov processes with absorbing boundaries allows for the calculation of the motor's dwell time distributions. These reveal aspects of the coordination of the motor's heads and contain direct information about the backsteps of the motor. Our theory provides a unified description for the myosin V motor as studied in single motor experiments.
Since Harris’ parser in the late 50s, multiword units have been progressively integrated in parsers. Nevertheless, in the most part, they are still restricted to compound words, that are more stable and less numerous. Actually, language is full of semi-fixed expressions that also form basic semantic units: semi-fixed adverbial expressions (e.g. time), collocations. Like compounds, the identification of these structures limits the combinatorial complexity induced by lexical ambiguity. In this paper, we detail an experiment that largely integrates these notions in a finite-state procedure of segmentation into super-chunks, preliminary to a parser.We show that the chunker, developped for French, reaches 92.9% precision and 98.7% recall. Moreover, multiword units realize 36.6% of the attachments within nominal and prepositional phrases.
The self-employed faced strong income losses during the Covid-19 pandemic. Many governments introduced programs to financially support the self-employed during the pandemic, including Germany. The German Ministry for Economic Affairs announced a €50bn emergency-aid program in March 2020, offering one-off lump-sum payments of up to €15,000 to those facing substantial revenue declines. By reassuring the self- employed that the government ‘would not let them down’ during the crisis, the program had also the important aim of motivating the self-employed to get through the crisis. We investigate whether the program affected the confidence of the self-employed to survive the crisis using real-time online-survey data comprising more than 20,000 observations. We employ propensity score matching, making use of a rich set of variables that influence the subjective survival probability as main outcome measure. We observe that this program had significant effects, with the subjective survival probability of the self- employed being moderately increased. We reveal important effect heterogeneities with respect to education, industries, and speed of payment. Notably, positive effects only occur among those self-employed whose application was processed quickly. This suggests stress-induced waiting costs due to the uncertainty associated with the administrative processing and the overall pandemic situation. Our findings have policy implications for the design of support programs, while also contributing to the literature on the instruments and effects of entrepreneurship policy interventions in crisis situations.
Emotions are a complex concept and they are present in our everyday life. Persons on the autism spectrum are said to have difficulties in social interactions, showing deficits in emotion recognition in comparison to neurotypically developed persons. But social-emotional skills are believed to be positively augmented by training. A new adaptive social cognition training tool “E.V.A.” is introduced which teaches emotion recognition from face, voice and body language. One cross-sectional and one longitudinal study with adult neurotypical and autistic participants were conducted. The aim of the cross-sectional study was to characterize the two groups and see if differences in their social-emotional skills exist. The longitudinal study, on the other hand, aimed for detecting possible training effects following training with the new training tool. In addition, in both studies usability assessments were conducted to investigate the perceived usability of the new tool for neurotypical as well as autistic participants. Differences were found between autistic and neurotypical participants in their social-emotional and emotion recognition abilities. Training effects for neurotypical participants in an emotion recognition task were found after two weeks of home training. Similar perceived usability was found for the neurotypical and autistic participants. The current findings suggest that persons with ASC do not have a general deficit in emotion recognition, but are in need for more time to correctly recognize emotions. In addition, findings suggest that training emotion recognition abilities is possible. Further studies are needed to verify if the training effects found for neurotypical participants also manifest in a larger ASC sample.
In the first section of the thesis graphitic carbon nitride was for the first time synthesised using the high-temperature condensation of dicyandiamide (DCDA) – a simple molecular precursor – in a eutectic salt melt of lithium chloride and potassium chloride. The extent of condensation, namely next to complete conversion of all reactive end groups, was verified by elemental microanalysis and vibrational spectroscopy. TEM- and SEM-measurements gave detailed insight into the well-defined morphology of these organic crystals, which are not based on 0D or 1D constituents like known molecular or short-chain polymeric crystals but on the packing motif of extended 2D frameworks. The proposed crystal structure of this g-C3N4 species was derived in analogy to graphite by means of extensive powder XRD studies, indexing and refinement. It is based on sheets of hexagonally arranged s-heptazine (C6N7) units that are held together by covalent bonds between C and N atoms. These sheets stack in a graphitic, staggered fashion adopting an AB-motif, as corroborated by powder X-ray diffractometry and high-resolution transmission electron microscopy. This study was contrasted with one of many popular – yet unsuccessful – approaches in the last 30 years of scientific literature to perform the condensation of an extended carbon nitride species through synthesis in the bulk. The second section expands the repertoire of available salt melts introducing the lithium bromide and potassium bromide eutectic as an excellent medium to obtain a new phase of graphitic carbon nitride. The combination of SEM, TEM, PXRD and electron diffraction reveals that the new graphitic carbon nitride phase stacks in an ABA’ motif forming unprecedentedly large crystals. This section seizes the notion of the preceding chapter, that condensation in a eutectic salt melt is the key to obtain a high degree of conversion mainly through a solvatory effect. At the close of this chapter ionothermal synthesis is seen established as a powerful tool to overcome the inherent kinetic problems of solid state reactions such as incomplete polymerisation and condensation in the bulk especially when the temperature requirement of the reaction in question falls into the proverbial “no man’s land” of classical solvents, i.e. above 250 to 300 °C. The following section puts the claim to the test, that the crystalline carbon nitrides obtained from a salt melt are indeed graphitic. A typical property of graphite – namely the accessibility of its interplanar space for guest molecules – is transferred to the graphitic carbon nitride system. Metallic potassium and graphitic carbon nitride are converted to give the potassium intercalation compound, K(C6N8)3 designated according to its stoichiometry and proposed crystal structure. Reaction of the intercalate with aqueous solvents triggers the exfoliation of the graphitic carbon nitride material and – for the first time – enables the access of singular (or multiple) carbon nitride sheets analogous to graphene as seen in the formation of sheets, bundles and scrolls of carbon nitride in TEM imaging. The thus exfoliated sheets form a stable, strongly fluorescent solution in aqueous media, which shows no sign in UV/Vis spectroscopy that the aromaticity of individual sheets was subject to degradation. The final section expands on the mechanism underlying the formation of graphitic carbon nitride by literally expanding the distance between the covalently linked heptazine units which constitute these materials. A close examination of all proposed reaction mechanisms to-date in the light of exhaustive DSC/MS experiments highlights the possibility that the heptazine unit can be formed from smaller molecules, even if some of the designated leaving groups (such as ammonia) are substituted by an element, R, which later on remains linked to the nascent heptazine. Furthermore, it is suggested that the key functional groups in the process are the triazine- (Tz) and the carbonitrile- (CN) group. On the basis of these assumptions, molecular precursors are tailored which encompass all necessary functional groups to form a central heptazine unit of threefold, planar symmetry and then still retain outward functionalities for self-propagated condensation in all three directions. Two model systems based on a para-aryl (ArCNTz) and para-biphenyl (BiPhCNTz) precursors are devised via a facile synthetic procedure and then condensed in an ionothermal process to yield the heptazine based frameworks, HBF-1 and HBF-2. Due to the structural motifs of their molecular precursors, individual sheets of HBF-1 and HBF-2 span cavities of 14.2 Å and 23.0 Å respectively which makes both materials attractive as potential organic zeolites. Crystallographic analysis confirms the formation of ABA’ layered, graphitic systems, and the extent of condensation is confirmed as next-to-perfect by elemental analysis and vibrational spectroscopy.
Finite state methods for natural language processing often require the construction and the intersection of several automata. In this paper, we investigate the question of determining the best order in which these intersections should be performed. We take as an example lexical disambiguation in polarity grammars. We show that there is no efficient way to minimize the state complexity of these intersections.
We study the effect of energy and transport policies on pollution in two developing country cities. We use a quantitative equilibrium model with choice of housing, energy use, residential location, transport mode, and energy technology. Pollution comes from commuting and residential energy use. The model parameters are calibrated to replicate key variables for two developing country cities, Maputo, Mozambique, and Yogyakarta, Indonesia. In the counterfactual simulations, we study how various transport and energy policies affect equilibrium pollution. Policies may be induce rebound effects from increasing residential energy use or switching to high emission modes or locations. In general, these rebound effects tend to be largest for subsidies to public transport or modern residential energy technology.
Property tax competition
(2022)
We develop a model of property taxation and characterize equilibria under three alternative taxa-tion regimes often used in the public finance literature: decentralized taxation, centralized taxation, and “rent seeking” regimes. We show that decentralized taxation results in inefficiently high tax rates, whereas centralized taxation yields a common optimal tax rate, and tax rates in the rent-seeking regime can be either inefficiently high or low. We quantify the effects of switching from the observed tax system to the three regimes for Japan and Germany. The decentralized or rent-seeking regime best describes the Japanese tax system, whereas the centralized regime does so for Germany. We also quantify the welfare effects of regime changes.
Urban pollution
(2022)
We use worldwide satellite data to analyse how population size and density affect urban pollution. We find that density significantly increases pollution exposure. Looking only at urban areas, we find that population size affects exposure more than density. Moreover, the effect is driven mostly by population commuting to core cities rather than the core city population itself. We analyse heterogeneity by geography and income levels. By and large, the influence of population on pollution is greatest in Asia and middle-income countries. A counterfactual simulation shows that PM2.5 exposure would fall by up to 36% and NO2 exposure up to 53% if within countries population size were equalized across all cities.
Metals are often used in environments that are conducive to corrosion, which leads to a reduction in their mechanical properties and durability. Coatings are applied to corrosion-prone metals such as aluminum alloys to inhibit the destructive surface process of corrosion in a passive or active way. Standard anticorrosive coatings function as a physical barrier between the material and the corrosive environment and provide passive protection only when intact. In contrast, active protection prevents or slows down corrosion even when the main barrier is damaged. The most effective industrially used active corrosion inhibition for aluminum alloys is provided by chromate conversion coatings. However, their toxicity and worldwide restriction provoke an urgent need for finding environmentally friendly corrosion preventing systems. A promising approach to replace the toxic chromate coatings is to embed particles containing nontoxic inhibitor in a passive coating matrix. This work presents the development and optimization of effective anticorrosive coatings for the industrially important aluminum alloy, AA2024-T3 using this approach. The protective coatings were prepared by dispersing mesoporous silica containers, loaded with the nontoxic corrosion inhibitor 2-mercaptobenzothiazole, in a passive sol-gel (SiOx/ZrOx) or organic water-based layer. Two types of porous silica containers with different sizes (d ≈ 80 and 700 nm, respectively) were investigated. The studied robust containers exhibit high surface area (≈ 1000 m² g-1), narrow pore size distribution (dpore ≈ 3 nm) and large pore volume (≈ 1 mL g-1) as determined by N2 sorption measurements. These properties favored the subsequent adsorption and storage of a relatively large amount of inhibitor as well as its release in response to pH changes induced by the corrosion process. The concentration, position and size of the embedded containers were varied to ascertain the optimum conditions for overall anticorrosion performance. Attaining high anticorrosion efficiency was found to require a compromise between delivering an optimal amount of corrosion inhibitor and preserving the coating barrier properties. This study broadens the knowledge about the main factors influencing the coating anticorrosion efficiency and assists the development of optimum active anticorrosive coatings doped with inhibitor loaded containers.
Parsing costs as predictors of reading difficulty: An evaluation using the Potsdam Sentence Corpus
(2008)
The surprisal of a word on a probabilistic grammar constitutes a promising complexity metric for human sentence comprehension difficulty. Using two different grammar types, surprisal is shown to have an effect on fixation durations and regression probabilities in a sample of German readers’ eye movements, the Potsdam Sentence Corpus. A linear mixed-effects model was used to quantify the effect of surprisal while taking into account unigram and bigram frequency, word length, and empirically-derived word predictability; the so-called “early” and “late” measures of processing difficulty both showed an effect of surprisal. Surprisal is also shown to have a small but statistically non-significant effect on empirically-derived predictability itself. This work thus demonstrates the importance of including parsing costs as a predictor of comprehension difficulty in models of reading, and suggests that a simple identification of syntactic parsing costs with early measures and late measures with durations of post-syntactic events may be difficult to uphold.
Eye fixation durations during normal reading correlate with processing difficulty but the specific cognitive mechanisms reflected in these measures are not well understood. This study finds support in German readers’ eyefixations for two distinct difficulty metrics: surprisal, which reflects the change in probabilities across syntactic analyses as new words are integrated, and retrieval, which quantifies comprehension difficulty in terms of working memory constraints. We examine the predictions of both metrics using a family of dependency parsers indexed by an upper limit on the number of candidate syntactic analyses they retain at successive words. Surprisal models all fixation measures and regression probability. By contrast, retrieval does not model any measure in serial processing. As more candidate analyses are considered in parallel at each word, retrieval can account for the same measures as surprisal. This pattern suggests an important role for ranked parallelism in theories of sentence comprehension.
We have analyzed the spectra of seven Galactic O4 supergiants, with the NLTE wind code CMFGEN. For all stars, we have found that clumped wind models match well lines from different species spanning a wavelength range from FUV to optical, and remain consistent with Hα data. We have achieved an excellent match of the P V λλ1118, 1128 resonance doublet and N IV λ1718, as well as He II λ4686 suggesting that our physical description of clumping is adequate. We find very small volume filling factors and that clumping starts deep in the wind, near the sonic point. The most crucial consequence of our analysis is that the mass loss rates of O stars need to be revised downward significantly, by a factor of 3 and more compared to those obtained from smooth-wind models.
Deductive databases need general formulas in rule bodies, not only conjuctions of literals. This is well known since the work of Lloyd and Topor about extended logic programming. Of course, formulas must be restricted in such a way that they can be effectively evaluated in finite time, and produce only a finite number of new tuples (in each iteration of the TP-operator: the fixpoint can still be infinite). It is also necessary to respect binding restrictions of built-in predicates: many of these predicates can be executed only when certain arguments are ground. Whereas for standard logic programming rules, questions of safety, allowedness, and range-restriction are relatively easy and well understood, the situation for general formulas is a bit more complicated. We give a syntactic analysis of formulas that guarantees the necessary properties.
The Milky Way is only one out of billions of galaxies in the universe. However, it is a special galaxy because it allows to explore the main mechanisms involved in its evolution and formation history by unpicking the system star-by-star. Especially, the chemical fingerprints of its stars provide clues and evidence of past events in the Galaxy’s lifetime. These information help not only to decipher the current structure and building blocks of the Milky Way, but to learn more about the general formation process of galaxies.
In the past decade a multitude of stellar spectroscopic Galactic surveys have scanned millions of stars far beyond the rim of the solar neighbourhood. The obtained spectroscopic information provide unprecedented insights to the chemo-dynamics of the Milky Way. In addition analytic models and numerical simulations of the Milky Way provide necessary descriptions and predictions suited for comparison with observations in order to decode the physical properties that underlie the complex system of the Galaxy.
In the thesis various approaches are taken to connect modern theoretical modelling of galaxy formation and evolution with observations from Galactic stellar surveys. With its focus on the chemo-kinematics of the Galactic disk this work aims to determine new observational constraints on the formation of the Milky Way providing also proper comparisons with two different models. These are the population synthesis model TRILEGAL based on analytical distribution functions, which aims to simulate the number and distribution of stars in the Milky Way and its different components, and a hybrid model (MCM) that combines an N-body simulation of a Milky Way like galaxy in the cosmological framework with a semi-analytic chemical evolution model for the Milky Way. The major observational data sets in use come from two surveys, namely the “Radial Velocity Experiment” (RAVE) and the “Sloan Extension for Galactic Understanding and Exploration” (SEGUE).
In the first approach the chemo-kinematic properties of the thin and thick disk of the Galaxy as traced by a selection of about 20000 SEGUE G-dwarf stars are directly compared to the predictions by the MCM model. As a necessary condition for this, SEGUE's selection function and its survey volume are evaluated in detail to correct the spectroscopic observations for their survey specific selection biases. Also, based on a Bayesian method spectro-photometric distances with uncertainties below 15% are computed for the selection of SEGUE G-dwarfs that are studied up to a distance of 3 kpc from the Sun.
For the second approach two synthetic versions of the SEGUE survey are generated based on the above models. The obtained synthetic stellar catalogues are then used to create mock samples best resembling the compiled sample of observed SEGUE G-dwarfs. Generally, mock samples are not only ideal to compare predictions from various models. They also allow validation of the models' quality and improvement as with this work could be especially achieved for TRILEGAL. While TRILEGAL reproduces the statistical properties of the thin and thick disk as seen in the observations, the MCM model has shown to be more suitable in reproducing many chemo-kinematic correlations as revealed by the SEGUE stars. However, evidence has been found that the MCM model may be missing a stellar component with the properties of the thick disk that the observations clearly show. While the SEGUE stars do indicate a thin-thick dichotomy of the stellar Galactic disk in agreement with other spectroscopic stellar studies, no sign for a distinct metal-poor disk is seen in the MCM model.
Usually stellar spectroscopic surveys are limited to a certain volume around the Sun covering different regions of the Galaxy’s disk. This often prevents to obtain a global view on the chemo-dynamics of the Galactic disk. Hence, a suitable combination of stellar samples from independent surveys is not only useful for the verification of results but it also helps to complete the picture of the Milky Way. Therefore, the thesis closes with a comparison of the SEGUE G-dwarfs and a sample of RAVE giants. The comparison reveals that the chemo-kinematic relations agree in disk regions where the samples of both surveys show a similar number of stars. For those parts of the survey volumes where one of the surveys lacks statistics they beautifully complement each other. This demonstrates that the comparison of theoretical models on the one side, and the combined observational data gathered by multiple surveys on the other side, are key ingredients to understand and disentangle the structure and formation history of the Milky Way.
Recurrences in past climates
(2023)
Our ability to predict the state of a system relies on its tendency to recur to states it has visited before. Recurrence also pervades common intuitions about the systems we are most familiar with: daily routines, social rituals and the return of the seasons are just a few relatable examples. To this end, recurrence plots (RP) provide a systematic framework to quantify the recurrence of states. Despite their conceptual simplicity, they are a versatile tool in the study of observational data. The global climate is a complex system for which an understanding based on observational data is not only of academical relevance, but vital for the predurance of human societies within the planetary boundaries. Contextualizing current global climate change, however, requires observational data far beyond the instrumental period. The palaeoclimate record offers a valuable archive of proxy data but demands methodological approaches that adequately address its complexities. In this regard, the following dissertation aims at devising novel and further developing existing methods in the framework of recurrence analysis (RA). The proposed research questions focus on using RA to capture scale-dependent properties in nonlinear time series and tailoring recurrence quantification analysis (RQA) to characterize seasonal variability in palaeoclimate records (‘Palaeoseasonality’).
In the first part of this thesis, we focus on the methodological development of novel approaches in RA. The predictability of nonlinear (palaeo)climate time series is limited by abrupt transitions between regimes that exhibit entirely different dynamical complexity (e.g. crossing of ‘tipping points’). These possibly depend on characteristic time scales. RPs are well-established for detecting transitions and capture scale-dependencies, yet few approaches have combined both aspects. We apply existing concepts from the study of self-similar textures to RPs to detect abrupt transitions, considering the most relevant time scales. This combination of methods further results in the definition of a novel recurrence based nonlinear dependence measure. Quantifying lagged interactions between multiple variables is a common problem, especially in the characterization of high-dimensional complex systems. The proposed ‘recurrence flow’ measure of nonlinear dependence offers an elegant way to characterize such couplings. For spatially extended complex systems, the coupled dynamics of local variables result in the emergence of spatial patterns. These patterns tend to recur in time. Based on this observation, we propose a novel method that entails dynamically distinct regimes of atmospheric circulation based on their recurrent spatial patterns. Bridging the two parts of this dissertation, we next turn to methodological advances of RA for the study of Palaeoseasonality. Observational series of palaeoclimate ‘proxy’ records involve inherent limitations, such as irregular temporal sampling. We reveal biases in the RQA of time series with a non-stationary sampling rate and propose a correction scheme.
In the second part of this thesis, we proceed with applications in Palaeoseasonality. A review of common and promising time series analysis methods shows that numerous valuable tools exist, but their sound application requires adaptions to archive-specific limitations and consolidating transdisciplinary knowledge. Next, we study stalagmite proxy records from the Central Pacific as sensitive recorders of mid-Holocene El Niño-Southern Oscillation (ENSO) dynamics. The records’ remarkably high temporal resolution allows to draw links between ENSO and seasonal dynamics, quantified by RA. The final study presented here examines how seasonal predictability could play a role for the stability of agricultural societies. The Classic Maya underwent a period of sociopolitical disintegration that has been linked to drought events. Based on seasonally resolved stable isotope records from Yok Balum cave in Belize, we propose a measure of seasonal predictability. It unveils the potential role declining seasonal predictability could have played in destabilizing agricultural and sociopolitical systems of Classic Maya populations.
The methodological approaches and applications presented in this work reveal multiple exciting future research avenues, both for RA and the study of Palaeoseasonality.
Recent years witnessed a vast advent of stalagmites as palaeoclimate archives. The multitude of geochemical and physical proxies and a promise of a precise and accurate age model greatly appeal to palaeoclimatologists. Although substantial progress was made in speleothem-based palaeoclimate research and despite high-resolution records from low-latitudinal regions, proving that palaeo-environmental changes can be archived on sub-annual to millennial time scales our comprehension of climate dynamics is still fragmentary. This is in particular true for the summer monsoon system on the Indian subcontinent. The Indian summer monsoon (ISM) is an integral part of the intertropical convergence zone (ITCZ). As this rainfall belt migrates northward during boreal summer, it brings monsoonal rainfall. ISM strength depends however on a variety of factors, including snow cover in Central Asia and oceanic conditions in the Indic and Pacific. Presently, many of the factors influencing the ISM are known, though their exact forcing mechanism and mutual relations remain ambiguous. Attempts to make an accurate prediction of rainfall intensity and frequency and drought recurrence, which is extremely important for South Asian countries, resemble a puzzle game; all interaction need to fall into the right place to obtain a complete picture. My thesis aims to create a faithful picture of climate change in India, covering the last 11,000 ka. NE India represents a key region for the Bay of Bengal (BoB) branch of the ISM, as it is here where the monsoon splits into a northwestward and a northeastward directed arm. The Meghalaya Plateau is the first barrier for northward moving air masses and receives excessive summer rainfall, while the winter season is very dry. The proximity of Meghalaya to the Tibetan Plateau on the one hand and the BoB on the other hand make the study area a key location for investigating the interaction between different forcings that governs the ISM. A basis for the interpretation of palaeoclimate records, and a first important outcome of my thesis is a conceptual model which explains the observed pattern of seasonal changes in stable isotopes (d18O and d2H) in rainfall. I show that although in tropical and subtropical regions the amount effect is commonly called to explain strongly depleted isotope values during enhanced rainfall, alone it cannot account for observed rainwater isotope variability in Meghalaya. Monitoring of rainwater isotopes shows no expected negative correlation between precipitation amount and d18O of rainfall. In turn I find evidence that the runoff from high elevations carries an inherited isotopic signature into the BoB, where during the ISM season the freshwater builds a strongly depleted plume on top of the marine water. The vapor originating from this plume is likely to memorize' and transmit further very negative d18O values. The lack of data does not allow for quantication of this plume effect' on isotopes in rainfall over Meghalaya but I suggest that it varies on seasonal to millennial timescales, depending on the runoff amount and source characteristics. The focal point of my thesis is the extraction of climatic signals archived in stalagmites from NE India. High uranium concentration in the stalagmites ensured excellent age control required for successful high-resolution climate reconstructions. Stable isotope (d18O and d13C) and grey-scale data allow unprecedented insights into millennial to seasonal dynamics of the summer and winter monsoon in NE India. ISM strength (i. e. rainfall amount) is recorded in changes in d18Ostalagmites. The d13C signal, reflecting drip rate changes, renders a powerful proxy for dry season conditions, and shows similarities to temperature-related changes on the Tibetan Plateau. A sub-annual grey-scale profile supports a concept of lower drip rate and slower stalagmite growth during dry conditions. During the Holocene, ISM followed a millennial-scale decrease of insolation, with decadal to centennial failures resulting from atmospheric changes. The period of maximum rainfall and enhanced seasonality corresponds to the Holocene Thermal Optimum observed in Europe. After a phase of rather stable conditions, 4.5 kyr ago, the strengthening ENSO system dominated the ISM. Strong El Nino events weakened the ISM, especially when in concert with positive Indian Ocean dipole events. The strongest droughts of the last 11 kyr are recorded during the past 2 kyr. Using the advantage of a well-dated stalagmite record at hand I tested the application of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to detect sub-annual to sub-decadal changes in element concentrations in stalagmites. The development of a large ablation cell allows for ablating sample slabs of up to 22 cm total length. Each analyzed element is a potential proxy for different climatic parameters. Combining my previous results with the LAICP- MS-generated data shows that element concentration depends not only on rainfall amount and associated leaching from the soil. Additional factors, like biological activity and hydrogeochemical conditions in the soil and vadose zone can eventually affect the element content in drip water and in stalagmites. I present a theoretical conceptual model for my study site to explain how climatic signals can be transmitted and archived in stalagmite carbonate. Further, I establish a first 1500 year long element record, reconstructing rainfall variability. Additionally, I hypothesize that volcanic eruptions, producing large amounts of sulfuric acid, can influence soil acidity and hence element mobilization.
Sustainable urban growth
(2022)
This dissertation explores the determinants for sustainable and socially optimalgrowth in a city. Two general equilibrium models establish the base for this evaluation, each adding its puzzle piece to the urban sustainability discourse and examining the role of non-market-based and market-based policies for balanced growth and welfare improvements in different theory settings. Sustainable urban growth either calls for policy actions or a green energy transition. Further, R&D market failures can pose severe challenges to the sustainability of urban growth and the social optimality of decentralized allocation decisions. Still, a careful (holistic) combination of policy instruments can achieve sustainable growth and even be first best.
Technological progress allows for producing ever more complex predictive models on the basis of increasingly big datasets. For risk management of natural hazards, a multitude of models is needed as basis for decision-making, e.g. in the evaluation of observational data, for the prediction of hazard scenarios, or for statistical estimates of expected damage. The question arises, how modern modelling approaches like machine learning or data-mining can be meaningfully deployed in this thematic field. In addition, with respect to data availability and accessibility, the trend is towards open data. Topic of this thesis is therefore to investigate the possibilities and limitations of machine learning and open geospatial data in the field of flood risk modelling in the broad sense. As this overarching topic is broad in scope, individual relevant aspects are identified and inspected in detail.
A prominent data source in the flood context is satellite-based mapping of inundated areas, for example made openly available by the Copernicus service of the European Union. Great expectations are directed towards these products in scientific literature, both for acute support of relief forces during emergency response action, and for modelling via hydrodynamic models or for damage estimation. Therefore, a focus of this work was set on evaluating these flood masks. From the observation that the quality of these products is insufficient in forested and built-up areas, a procedure for subsequent improvement via machine learning was developed. This procedure is based on a classification algorithm that only requires training data from a particular class to be predicted, in this specific case data of flooded areas, but not of the negative class (dry areas). The application for hurricane Harvey in Houston shows the high potential of this method, which depends on the quality of the initial flood mask.
Next, it is investigated how much the predicted statistical risk from a process-based model chain is dependent on implemented physical process details. Thereby it is demonstrated what a risk study based on established models can deliver. Even for fluvial flooding, such model chains are already quite complex, though, and are hardly available for compound or cascading events comprising torrential rainfall, flash floods, and other processes. In the fourth chapter of this thesis it is therefore tested whether machine learning based on comprehensive damage data can offer a more direct path towards damage modelling, that avoids explicit conception of such a model chain. For that purpose, a state-collected dataset of damaged buildings from the severe El Niño event 2017 in Peru is used. In this context, the possibilities of data-mining for extracting process knowledge are explored as well. It can be shown that various openly available geodata sources contain useful information for flood hazard and damage modelling for complex events, e.g. satellite-based rainfall measurements, topographic and hydrographic information, mapped settlement areas, as well as indicators from spectral data. Further, insights on damaging processes are discovered, which mainly are in line with prior expectations. The maximum intensity of rainfall, for example, acts stronger in cities and steep canyons, while the sum of rain was found more informative in low-lying river catchments and forested areas. Rural areas of Peru exhibited higher vulnerability in the presented study compared to urban areas. However, the general limitations of the methods and the dependence on specific datasets and algorithms also become obvious.
In the overarching discussion, the different methods – process-based modelling, predictive machine learning, and data-mining – are evaluated with respect to the overall research questions. In the case of hazard observation it seems that a focus on novel algorithms makes sense for future research. In the subtopic of hazard modelling, especially for river floods, the improvement of physical models and the integration of process-based and statistical procedures is suggested. For damage modelling the large and representative datasets necessary for the broad application of machine learning are still lacking. Therefore, the improvement of the data basis in the field of damage is currently regarded as more important than the selection of algorithms.
Strategic uncertainty is the uncertainty that players face with respect to the purposeful behavior of other players in an interactive decision situation. Our paper develops a new method for measuring strategic-uncertainty attitudes and distinguishing them from risk and ambiguity attitudes. We vary the source of uncertainty (whether strategic or not) across conditions in a ceteris paribus manner. We elicit certainty equivalents of participating in two strategic 2x2 games (a stag-hunt and a market-entry game) as well as certainty equivalents of related lotteries that yield the same possible payoffs with exogenously given probabilities (risk) and lotteries with unknown probabilities (ambiguity). We provide a structural model of uncertainty attitudes that allows us to measure a preference for or an aversion against the source of uncertainty, as well as optimism or pessimism regarding the desired outcome. We document systematic attitudes towards strategic uncertainty that vary across contexts. Under strategic complementarity [substitutability], the majority of participants tend to be pessimistic [optimistic] regarding the desired outcome. However, preferences for the source of uncertainty are distributed around zero.
Leadership plays an important role for the efficient and fair solution of social dilemmas but the effectiveness of a leader can vary substantially. Two main factors of leadership impact are the ability to induce high contributions by all group members and the (expected) fair use of power. Participants in our experiment decide about contributions to a public good. After all contributions are made, the leader can choose how much of the joint earnings to assign to herself; the remainder is distributed equally among the followers. Using machine learning techniques, we study whether the content of initial open statements by the group members predicts their behavior as a leader and whether groups are able to identify such clues and endogenously appoint a “good” leader to solve the dilemma. We find that leaders who promise fairness are more likely to behave fairly, and that followers appoint as leaders those who write more explicitly about fairness and efficiency. However, in their contribution decision, followers focus on the leader’s first-move contribution and place less importance on the content of the leader’s statements.
The use of nano zerovalent iron (nZVI) for environmental remediation is a promising new technique for in situ remediation. Due to its high surface area and high reactivity, nZVI is able to dechlorinate organic contaminants and render them harmless. Limited mobility, due to fast aggregation and sedimentation of nZVI, limits the capability for source and plume remediation. Carbo-Iron is a newly developed material consisting of activated carbon particles (d50 = 0,8 µm) that are plated with nZVI particles. These particles combine the mobility of activated carbon and the reactivity of nZVI. This paper presents the first results of the transport experiments.
We introduce and discuss a number of issues that arise in the process of building a finite-state morphological analyzer for Urdu, in particular issues with potential ambiguity and non-concatenative morphology. Our approach allows for an underlyingly similar treatment of both Urdu and Hindi via a cascade of finite-state transducers that transliterates the very different scripts into a common ASCII transcription system. As this transliteration system is based on the XFST tools that the Urdu/Hindi common morphological analyzer is also implemented in, no compatibility problems arise.
Controlling interactions in synthetic polymers as precisely as in proteins would have a strong impact on polymer science. Advanced structural and functional control can lead to rational design of, integrated nano- and microstructures. To achieve this, properties of monomer sequence defined oligopeptides were exploited. Through their incorporation as monodisperse segments into synthetic polymers we learned in recent four years how to program the structure formation of polymers, to adjust and exploit interactions in such polymers, to control inorganic-organic interfaces in fiber composites and induce structure in Biomacromolecules like DNA for biomedical applications.
In this paper we consider a simple syntactic extension of Answer Set Programming (ASP) for dealing with (nested) existential quantifiers and double negation in the rule bodies, in a close way to the recent proposal RASPL-1. The semantics for this extension just resorts to Equilibrium Logic (or, equivalently, to the General Theory of Stable Models), which provides a logic-programming interpretation for any arbitrary theory in the syntax of Predicate Calculus. We present a translation of this syntactic class into standard logic programs with variables (either disjunctive or normal, depending on the input rule heads), as those allowed by current ASP solvers. The translation relies on the introduction of auxiliary predicates and the main result shows that it preserves strong equivalence modulo the original signature.
We provide the first estimates of the impact of managers’ risk preferences on their training allocation decisions. Our conceptual framework links managers’ risk preferences to firms’ training decisions through the bonuses they expect to receive. Risk-averse managers are expected to select workers with low turnover risk and invest in specific rather than general training. Empirical evidence supporting these predictions is provided using a novel vignette study embedded in a nationally representative survey of firm managers. Risk-tolerant and risk-averse decision makers have significantly different training preferences. Risk aversion results in increased sensitivity to turnover risk. Managers who are risk-averse offer significantly less general training and, in some cases, are more reluctant to train workers with a history of job mobility. All managers, irrespective of their risk preferences, are sensitive to the investment risk associated with training, avoiding training that is more costly or targets those with less occupational expertise or nearing retirement. This suggests the risks of training are primarily due to the risk that trained workers will leave the firm (turnover risk) rather than the risk that the benefits of training do not outweigh the costs (investment risk).
We investigate the effect of the COVID-19 pandemic on self-employed people’s mental health. Using representative longitudinal survey data from Germany, we reveal differential effects by gender: whereas self-employed women experienced a substantial deterioration in their mental health, self-employed men displayed no significant changes up to early 2021. Financial losses are important in explaining these differences. In addition, we find larger mental health responses among self-employed women who were directly affected by government-imposed restrictions and bore an increased childcare burden due to school and daycare closures. We also find that self-employed individuals who are more resilient coped better with the crisis.
Predicting entrepreneurial development based on individual and business-related characteristics is a key objective of entrepreneurship research. In this context, we investigate whether the motives of becoming an entrepreneur influence the subsequent entrepreneurial development. In our analysis, we examine a broad range of business outcomes including survival and income, as well as job creation, expansion and innovation activities for up to 40 months after business formation. Using self-determination theory as conceptual background, we aggregate the start-up motives into a continuous motivational index. We show – based on a unique dataset of German start-ups from unemployment and non-unemployment – that the later business performance is better, the higher they score on this index. Effects are particularly strong for growth oriented outcomes like innovation and expansion activities. In a next step, we examine three underlying motivational categories that we term opportunity, career ambition, and necessity. We show that individuals driven by opportunity motives perform better in terms of innovation and business expansion activities, while career ambition is positively associated with survival, income, and the probability of hiring employees. All effects are robust to the inclusion of a large battery of covariates that are proven to be important determinants of entrepreneurial performance.
Subsidizing the geographical mobility of unemployed workers may improve welfare by relaxing their financial constraints and allowing them to find jobs in more prosperous regions. We exploit regional variation in the promotion of mobility programs along administrative borders of German employment agency districts to investigate the causal effect of offering such financial incentives on the job search behavior and labor market integration of unemployed workers. We show that promoting mobility – as intended – causes job seekers to increase their search radius, apply for and accept distant jobs. At the same time, local job search is reduced with adverse consequences for reemployment and earnings. These unintended negative effects are provoked by spatial search frictions. Overall, the unconditional provision of mobility programs harms the welfare of unemployed job seekers.
While a growing body of literature finds positive impacts of Start-Up Subsidies (SUS) on labor market outcomes of participants, little is known about how the design of these programs shapes their effectiveness and hence how to improve policy. As experimental variation in program design is unavailable, we exploit the 2011 reform of the current German SUS program for the unemployed which strengthened case-workers’ discretionary power, increased entry requirements and reduced monetary support. We estimate the impact of the reform on the program’s effectiveness using samples of participants and non-participants from before and after the reform. To control for time-constant unobserved heterogeneity as well as differential selection patterns based on observable characteristics over time, we combine Difference-in-Differences with inverse probability weighting using covariate balancing propensity scores. Holding participants’ observed characteristics as well as macroeconomic conditions constant, the results suggest that the reform was successful in raising employment effects on average. As these findings may be contaminated by changes in selection patterns based on unobserved characteristics, we assess our results using simulation-based sensitivity analyses and find that our estimates are highly robust to changes in unobserved characteristics. Hence, the reform most likely had a positive impact on the effectiveness of the program, suggesting that increasing entry requirements and reducing support in-creased the program’s impacts while reducing the cost per participant.
In the frame of a world fighting a dramatic global warming caused by human-related activities, research towards the development of renewable energies plays a crucial role. Solar energy is one of the most important clean energy sources and its role in the satisfaction of the global energy demand is set to increase. In this context, a particular class of materials captured the attention of the scientific community for its attractive properties: halide perovskites. Devices with perovskite as light-absorber saw an impressive development within the last decade, reaching nowadays efficiencies comparable to mature photovoltaic technologies like silicon solar cells. Yet, there are still several roadblocks to overcome before a wide-spread commercialization of this kind of devices is enabled. One of the critical points lies at the interfaces: perovskite solar cells (PSCs) are made of several layers with different chemical and physical features. In order for the device to function properly, these properties have to be well-matched.
This dissertation deals with some of the challenges related to interfaces in PSCs, with a focus on the interface between the perovskite material itself and the subsequent charge transport layer. In particular, molecular assemblies with specific properties are deposited on the perovskite surface to functionalize it. The functionalization results in energy level alignment adjustment, interfacial losses reduction, and stability improvement.
First, a strategy to tune the perovskite’s energy levels is introduced: self-assembled monolayers of dipolar molecules are used to functionalize the surface, obtaining simultaneously a shift in the vacuum level position and a saturation of the dangling bonds at the surface. A shift in the vacuum level corresponds to an equal change in work function, ionization energy, and electron affinity. The direction of the shift depends on the direction of the collective interfacial dipole. The magnitude of the shift can be tailored by controlling the deposition parameters, such as the concentration of the solution used for the deposition. The shift for different molecules is characterized by several non-invasive techniques, including in particular Kelvin probe. Overall, it is shown that it is possible to shift the perovskite energy levels in both directions by several hundreds of meV. Moreover, interesting insights on the molecules deposition dynamics are revealed.
Secondly, the application of this strategy in perovskite solar cells is explored. Devices with different perovskite compositions (“triple cation perovskite” and MAPbBr3) are prepared. The two resulting model systems present different energetic offsets at the perovskite/hole-transport layer interface. Upon tailored perovskite surface functionalization, the devices show a stabilized open circuit voltage (Voc) enhancement of approximately 60 meV on average for devices with MAPbBr3, while the impact is limited on triple-cation solar cells. This suggests that the proposed energy level tuning method is valid, but its effectiveness depends on factors such as the significance of the energetic offset compared to the other losses in the devices.
Finally, the above presented method is further developed by incorporating the ability to interact with the perovskite surface directly into a novel hole-transport material (HTM), named PFI. The HTM can anchor to the perovskite halide ions via halogen bonding (XB). Its behaviour is compared to that of another HTM (PF) with same chemical structure and properties, except for the ability of forming XB. The interaction of perovskite with PFI and PF is characterized through UV-Vis, atomic force microscopy and Kelvin probe measurements combined with simulations. Compared to PF, PFI exhibits enhanced resilience against solvent exposure and improved energy level alignment with the perovskite layer. As a consequence, devices comprising PFI show enhanced Voc and operational stability during maximum-power-point tracking, in addition to hysteresis reduction. XB promotes the formation of a high-quality interface by anchoring to the halide ions and forming a stable and ordered interfacial layer, showing to be a particularly interesting candidate for the development of tailored charge transport materials in PSCs.
Overall, the results exposed in this dissertation introduce and discuss a versatile tool to functionalize the perovskite surface and tune its energy levels. The application of this method in devices is explored and insights on its challenges and advantages are given. Within this frame, the results shed light on XB as ideal interaction for enhancing stability and efficiency in perovskite-based devices.
We summarize Chandra observations of the emission line profiles from 17 OB stars. The lines tend to be broad and unshifted. The forbidden/intercombination line ratios arising from Helium-like ions provide radial distance information for the X-ray emission sources, while the H-like to He-like line ratios provide X-ray temperatures, and thus also source temperature versus radius distributions. OB stars usually show power law differential emission measure distributions versus temperature. In models of bow shocks, we find a power law differential emission measure, a wide range of ion stages, and the bow shock flow around the clumps provides transverse velocities comparable to HWHM values. We find that the bow shock results for the line profile properties, consistent with the observations of X-ray line emission for a broad range of OB star properties.
The utilization of lignin as renewable electrode material for electrochemical energy storage is a sustainable approach for future batteries and supercapacitors. The composite electrode was fabricated from Kraft lignin and conductive carbon and the charge storage contribution was determined in terms of electrical double layer (EDL) and redox reactions. The important factors at play for achieving high faradaic charge storage capacity contribute to high surface area, accessibility of redox sites in lignin and their interaction with conductive additives. A thinner layer of lignin covering the high surface area of carbon facilitates the electron transfer process with a shorter pathway from the active sites of nonconductive lignin to the current collector leading to the improvement of faradaic charge storage capacity.
Composite electrodes from lignin and carbon would be even more sustainable if the fluorinated binder can be omitted. A new route to fabricate a binder-free composite electrode from Kraft lignin and high surface area carbon has been proposed by crosslinking lignin with glyoxal. A high molecular weight of lignin is obtained to enhance both electroactivity and binder capability in composite electrodes. The order of the processing step of crosslinking lignin on the composite electrode plays a crucial role in achieving a stable electrode and high charge storage capacity. The crosslinked lignin based electrodes are promising since they allow for more stable, sustainable, halogen-free and environmentally benign devices for energy storage applications. Furthermore, improvement of the amount of redox active groups (quinone groups) in lignin is useful to enhance the capacity in lithium battery applications. Direct oxidative demethylation by cerium ammonium nitrate has been carried out under mild conditions. This proves that an increase of quinone groups is able to enhance the performance of lithium battery. Thus, lignin is a promising material and could be a good candidate for application in sustainable energy storage devices.
A multitype Dawson-Watanabe process is conditioned, in subcritical and critical cases, on non-extinction in the remote future. On every finite time interval, its distribution is absolutely continuous with respect to the law of the unconditioned process. A martingale problem characterization is also given. Several results on the long time behavior of the conditioned mass process - the conditioned multitype Feller branching diffusion - are then proved. The general case is first considered, where the mutation matrix which models the interaction between the types, is irreducible. Several two-type models with decomposable mutation matrices are analyzed too .
The higher education structure in Malaysia has experienced significant changes since the implementation of the Private Higher Educational Institutions Act of 1996. The unprecedented expansion of the higher education sector and the increasing autonomy conferred to universities have created a huge demand for competent university leadership that supports the development of higher education in Malaysia. This article discusses the very first national multiplication training in Malaysia in 2014 and analyses such out-comes as the identification of good practices for future initiatives and applications in university leadership training.
We study the time variability of emission lines in three WNE stars : WR 2 (WN2), WR 3 (WN3ha) and WR152 (WN3). While WR 2 shows no variability above the noise level, the other stars do show variation, which are like other WR stars in WR 152 but very fast in WR 3. From these motions, we deduce a value of β ∼1 for WR 3 that is like that seen in O stars and β ∼2–3 for WR 152, that is intermediate between other WR stars and WR 3.
Two-photon polymerization of hydrogels – versatile solutions to fabricate well-defined 3D structures
(2014)
Hydrogels are cross-linked water-containing polymer networks that are formed by physical, ionic or covalent interactions. In recent years, they have attracted significant attention because of their unique physical properties, which make them promising materials for numerous applications in food and cosmetic processing, as well as in drug delivery and tissue engineering. Hydrogels are highly water-swellable materials, which can considerably increase in volume without losing cohesion, are biocompatible and possess excellent tissue-like physical properties, which can mimic in vivo conditions. When combined with highly precise manufacturing technologies, such as two-photon polymerization (2PP), well-defined three-dimensional structures can be obtained. These structures can become scaffolds for selective cell-entrapping, cell/drug delivery, sensing and prosthetic implants in regenerative medicine. 2PP has been distinguished from other rapid prototyping methods because it is a non-invasive and efficient approach for hydrogel cross-linking. This review discusses the 2PP-based fabrication of 3D hydrogel structures and their potential applications in biotechnology. A brief overview regarding the 2PP methodology and hydrogel properties relevant to biomedical applications is given together with a review of the most important recent achievements in the field.
Organisms often employ ecophysiological strategies to exploit environmental conditions and ensure bio-energetic success. However, the many complexities involved in the differential expression and flexibility of these strategies are rarely fully understood. Therefore, for the first time, using a three-part cross-disciplinary laboratory experimental analysis, we investigated the diversity and plasticity of photoresponsive traits employed by one family of environmentally contrasting, ecologically important phytoflagellates. The results demonstrated an extensive inter-species phenotypic diversity of behavioural, physiological, and compositional photoresponse across the Chlamydomonadaceae, and a multifaceted intra-species phenotypic plasticity, involving a broad range of beneficial photoacclimation strategies, often attributable to environmental predisposition and phylogenetic differentiation. Deceptively diverse and sophisticated strong (population and individual cell) behavioural photoresponses were observed, with divergence from a general preference for low light (and flexibility) dictated by intra-familial differences in typical habitat (salinity and trophy) and phylogeny. Notably, contrasting lower, narrow, and flexible compared with higher, broad, and stable preferences were observed in freshwater vs. brackish and marine species. Complex diversity and plasticity in physiological and compositional photoresponses were also discovered. Metabolic characteristics (such as growth rates, respiratory costs and photosynthetic capacity, efficiency, compensation and saturation points) varied elaborately with species, typical habitat (often varying more in eutrophic species, such as Chlamydomonas reinhardtii), and culture irradiance (adjusting to optimise energy acquisition and suggesting some propensity for low light). Considerable variations in intracellular pigment and biochemical composition were also recorded. Photosynthetic and accessory pigments (such as chlorophyll a, xanthophyll-cycle components, chlorophyll a:b and chlorophyll a:carotenoid ratios, fatty acid content and saturation ratios) varied with phylogeny and typical habitat (to attune photosystem ratios in different trophic conditions and to optimise shade adaptation, photoprotection, and thylakoid architecture, particularly in freshwater environments), and changed with irradiance (as reaction and harvesting centres adjusted to modulate absorption and quantum yield). The complex, concomitant nature of the results also advocated an integrative approach in future investigations. Overall, these nuanced, diverse, and flexible photoresponsive traits will greatly contribute to the functional ecology of these organisms, addressing environmental heterogeneity and potentially shaping individual fitness, spatial and temporal distribution, prevalence, and ecosystem dynamics.
Microswimmers, i.e. swimmers of micron size experiencing low Reynolds numbers, have received a great deal of attention in the last years, since many applications are envisioned in medicine and bioremediation. A promising field is the one of magnetic swimmers, since magnetism is biocom-patible and could be used to direct or actuate the swimmers. This thesis studies two examples of magnetic microswimmers from a physics point of view.
The first system to be studied are magnetic cells, which can be magnetic biohybrids (a swimming cell coupled with a magnetic synthetic component) or magnetotactic bacteria (naturally occurring bacteria that produce an intracellular chain of magnetic crystals). A magnetic cell can passively interact with external magnetic fields, which can be used for direction. The aim of the thesis is to understand how magnetic cells couple this magnetic interaction to their swimming strategies, mainly how they combine it with chemotaxis (the ability to sense external gradient of chemical species and to bias their walk on these gradients). In particular, one open question addresses the advantage given by these magnetic interactions for the magnetotactic bacteria in a natural environment, such as porous sediments. In the thesis, a modified Active Brownian Particle model is used to perform simulations and to reproduce experimental data for different systems such as bacteria swimming in the bulk, in a capillary or in confined geometries. I will show that magnetic fields speed up chemotaxis under special conditions, depending on parameters such as their swimming strategy (run-and-tumble or run-and-reverse), aerotactic strategy (axial or polar), and magnetic fields (intensities and orientations), but it can also hinder bacterial chemotaxis depending on the system.
The second example of magnetic microswimmer are rigid magnetic propellers such as helices or random-shaped propellers. These propellers are actuated and directed by an external rotating magnetic field. One open question is how shape and magnetic properties influence the propeller behavior; the goal of this research field is to design the best propeller for a given situation. The aim of the thesis is to propose a simulation method to reproduce the behavior of experimentally-realized propellers and to determine their magnetic properties. The hydrodynamic simulations are based on the use of the mobility matrix. As main result, I propose a method to match the experimental data, while showing that not only shape but also the magnetic properties influence the propellers swimming characteristics.
By quantitatively fitting simple emission line profile models that include both atomic opacity and porosity to the Chandra X-ray spectrum of ζ Pup, we are able to explore the trade-offs between reduced mass-loss rates and wind porosity. We find that reducing the mass-loss rate of ζ Pup by roughly a factor of four, to 1.5 × 10−6 M⊙ yr−1, enables simple non-porous wind models to provide good fits to the data. If, on the other hand, we take the literature mass-loss rate of 6×10−6 M⊙ yr−1, then to produce X-ray line profiles that fit the data, extreme porosity lengths – of h∞ ≈ 3 R∗ – are required. Moreover, these porous models do not provide better fits to the data than the non-porous, low optical depth models. Additionally, such huge porosity lengths do not seem realistic in light of 2-D numerical simulations of the wind instability.
The birth of the Yishuv’s national shipping company, ZIM was preceded by private enterprise; the sea had not traditionally been a focus of the Zionist movement. In the 1930s, a five-year span of private commercial shipping saw three companies in the Jewish community in Palestine – Palestine Shipping Company, Palestine Maritime Lloyd, and Atid – before shipping was cut short by the outbreak of the Second World War. Despite their brief lifespans and their negligible contribution to general shipping, these companies constituted an important milestone. Their existence helped shift the Yishuv leadership’s attitudes about shipping’s importance for the community and the need for it to be supported by national institutions.
Transitional justice is conventionally theorized as how a society deals with past injustices after regime change and alongside democratization. Nonetheless, scholars have not reached a consensus on what is to be included or excluded. Recent ideas of transformative justice seek to expand the understanding of transitional justice to include systemic restructuring and socioeconomic considerations. In the context of Nicaragua — where two transitions occurred within an 11-year span — very little transitional justice took place, in terms of the conventional concept of top-down legalistic mechanisms; however, distinct structural changes and socioeconomic policies can be found with each regime change. By analyzing the transformative justice elements of Nicaragua’s dual transition, this chapter seeks to expand the understanding of transitional justice to include how these factors influence goals of transitions such as sustainable peace and reconciliation for past injustices. The results argue for increased attention to transformative justice theories and a more nuanced conception of justice.
American occupying forces made the promotion of Jewish-Christian dialogue part of their plans for postwar German reconstruction. They sought to export American models of Jewish-Christian cooperation to Germany, while simultaneously validating and valorizing claims about the connection between democracy and tri-faith religious pluralism in the United States. The small size of the Jewish population in Germany meant that Jews did not set the terms of these discussions, and evidence shows that both German and American Jews expressed skepticism about participating in dialogue in the years immediately following the Holocaust. But opting out would have meant that discussions in Germany about the Judeo-Christian tradition that the American government advanced as the centerpiece of postwar democratic reconstruction would take place without a Jewish contribution. American Jewish leaders, present in Germany and in the US, therefore decided to opt in, not because they supported the project, but because it seemed far riskier to be left out.
Habsburg Central Europe
(2024)
Central Europe is characterized by linguistic and cultural density as well as by endogenous and exogenous cultural influences. These constellations were especially visible in the former Habsburg Empire, where they influenced the formation of individual and collective identities. This led not only to continual crises and conflicts, but also to an equally enormous creative potential as became apparent in the culture of the fin-de-siècle.
KEYCIT 2014
(2015)
In our rapidly changing world it is increasingly important not only to be an expert in a chosen field of study but also to be able to respond to developments, master new approaches to solving problems, and fulfil changing requirements in the modern world and in the job market. In response to these needs key competencies in understanding, developing and using new digital technologies are being brought into focus in school and university programmes. The IFIP TC3 conference "KEYCIT – Key Competences in Informatics and ICT (KEYCIT 2014)" was held at the University of Potsdam in Germany from July 1st to 4th, 2014 and addressed the combination of key competencies, Informatics and ICT in detail. The conference was organized into strands focusing on secondary education, university education and teacher education (organized by IFIP WGs 3.1 and 3.3) and provided a forum to present and to discuss research, case studies, positions, and national perspectives in this field.
In Search of Belonging
(2021)
More than 200,000 Jews left the Habsburg province of Galicia between 1881 and 1910. No longer living in the places of their childhood, they settled in urban centers, such as in New York’s Lower East Side. In this neighborhood, Galician Jews began to search for new relationships that linked the places they left and the ones where they arrived and settled. By looking at Galicia through the lens of autobiographical writings by former Jewish immigrants who became established residents of New York, this article emphasizes the role of regionalism in the context of transnational conceptions of a new American Jewish self-understanding. It argues that the key to analyzing the evolution of “eastern Europe” as a common place of origin for American Jewry is the constant dialogue between the places of origin and arrival. Specifically, philanthropic efforts during and after the First World War and the proliferation of tourism both enabled these settled immigrants to gradually replace regional notions, such as the idea of Galicia, with a mythical image of eastern Europe to create a sense of community as American Jews.
We present an algorithm that computes a function that assigns consecutive integers to trees recognized by a deterministic, acyclic, finite-state, bottom-up tree automaton. Such function is called minimal perfect hashing. It can be used to identify trees recognized by the automaton. Its value may be seen as an index in some other data structures. We also present an algorithm for inverted hashing.
A comparison of current trends within computer science teaching in school in Germany and the UK
(2013)
In the last two years, CS as a school subject has gained a lot of attention worldwide, although different countries have differing approaches to and experiences of introducing CS in schools. This paper reports on a study comparing current trends in CS at school, with a major focus on two countries, Germany and UK. A survey was carried out of a number of teaching professionals and experts from the UK and Germany with regard to the content and delivery of CS in school. An analysis of the quantitative data reveals a difference in foci in the two countries; putting this into the context of curricular developments we are able to offer interpretations of these trends and suggest ways in which curricula in CS at school should be moving forward.
Improving permafrost dynamics in land surface models: insights from dual sensitivity experiments
(2024)
The thawing of permafrost and the subsequent release of greenhouse gases constitute one of the most significant and uncertain positive feedback loops in the context of climate change, making predictions regarding changes in permafrost coverage of paramount importance. To address these critical questions, climate scientists have developed Land Surface Models (LSMs) that encompass a multitude of physical soil processes. This thesis is committed to advancing our understanding and refining precise representations of permafrost dynamics within LSMs, with a specific focus on the accurate modeling of heat fluxes, an essential component for simulating permafrost physics.
The first research question overviews fundamental model prerequisites for the representation of permafrost soils within land surface modeling. It includes a first-of-its-kind comparison between LSMs in CMIP6 to reveal their differences and shortcomings in key permafrost physics parameters. Overall, each of these LSMs represents a unique approach to simulating soil processes and their interactions with the climate system. Choosing the most appropriate model for a particular application depends on factors such as the spatial and temporal scale of the simulation, the specific research question, and available computational resources.
The second research question evaluates the performance of the state-of-the-art Community Land Model (CLM5) in simulating Arctic permafrost regions. Our approach overcomes traditional evaluation limitations by individually addressing depth, seasonality, and regional variations, providing a comprehensive assessment of permafrost and soil temperature dynamics. I compare CLM5's results with three extensive datasets: (1) soil temperatures from 295 borehole stations, (2) active layer thickness (ALT) data from the Circumpolar Active Layer Monitoring Network (CALM), and (3) soil temperatures, ALT, and permafrost extent from the ESA Climate Change Initiative (ESA-CCI). The results show that CLM5 aligns well with ESA-CCI and CALM for permafrost extent and ALT but reveals a significant global cold temperature bias, notably over Siberia. These results echo a persistent challenge identified in numerous studies: the existence of a systematic 'cold bias' in soil temperature over permafrost regions. To address this challenge, the following research questions propose dual sensitivity experiments.
The third research question represents the first study to apply a Plant Functional Type (PFT)-based approach to derive soil texture and soil organic matter (SOM), departing from the conventional use of coarse-resolution global data in LSMs. This novel method results in a more uniform distribution of soil organic matter density (OMD) across the domain, characterized by reduced OMD values in most regions. However, changes in soil texture exhibit a more intricate spatial pattern. Comparing the results to observations reveals a significant reduction in the cold bias observed in the control run. This method shows noticeable improvements in permafrost extent, but at the cost of an overestimation in ALT. These findings emphasize the model's high sensitivity to variations in soil texture and SOM content, highlighting the crucial role of soil composition in governing heat transfer processes and shaping the seasonal variation of soil temperatures in permafrost regions.
Expanding upon a site experiment conducted in Trail Valley Creek by \citet{dutch_impact_2022}, the fourth research question extends the application of the snow scheme proposed by \citet{sturm_thermal_1997} to cover the entire Arctic domain. By employing a snow scheme better suited to the snow density profile observed over permafrost regions, this thesis seeks to assess its influence on simulated soil temperatures. Comparing this method to observational datasets reveals a significant reduction in the cold bias that was present in the control run. In most regions, the Sturm run exhibits a substantial decrease in the cold bias. However, there is a distinctive overshoot with a warm bias observed in mountainous areas. The Sturm experiment effectively addressed the overestimation of permafrost extent in the control run, albeit resulting in a substantial reduction in permafrost extent over mountainous areas. ALT results remain relatively consistent compared to the control run. These outcomes align with our initial hypothesis, which anticipated that the reduced snow insulation in the Sturm run would lead to higher winter soil temperatures and a more accurate representation of permafrost physics.
In summary, this thesis demonstrates significant advancements in understanding permafrost dynamics and its integration into LSMs. It has meticulously unraveled the intricacies involved in the interplay between heat transfer, soil properties, and snow dynamics in permafrost regions. These insights offer novel perspectives on model representation and performance.
Many hot stars exhibit stochastic polarimetric variability, thought to arise from clumping low in the wind. Here we investigate the wind properties required to reproduce this variability using analytic models, with particular emphasis on Luminous Blue Variables. We find that the winds must be highly structured, consisting of a large number of optically-thin clumps; while we find that the overall level of polarization should scale with mass-loss rate – consistent with observations of LBVs. The models also predict variability on very short timescales, which is supported by the results of a recent polarimetric monitoring campaign.
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.
We present the latest results on the observational dependence of the mass-loss rate in stellar winds of O and early-B stars on the metal content of their atmospheres, and compare these with predictions. Absolute empirical rates for the mass loss of stars brighter than 10$^{5.2} L_{\odot}$, based on H$\alpha$ and ultraviolet (UV) wind lines, are found to be about a factor of two higher than predictions. If this difference is attributed to inhomogeneities in the wind this would imply that luminous O and early-B stars have clumping factors in their H$\alpha$ and UV line forming regime of about a factor of 3--5. The investigated stars cover a metallicity range $Z$ from 0.2 to 1 $Z_{\odot}$. We find a hint towards smaller clumping factors for lower $Z$. The derived clumping factors, however, presuppose that clumping does not impact the predictions of the mass-loss rate. We discuss this assumption and explain how we intend to investigate its validity in more detail.
Under Brazil's ex-president Bolsonaro, deforestation of the Amazon increased dramatically. An Austrian NGO filed a complaint to the Prosecutor of the International Criminal Court (ICC) against Bolsonaro in October 2021, accusing him of crimes against humanity against the backdrop of his involvement in environmental destruction. This paper deals with the question of whether this initi-ative constitutes a promising means of juridification to mitigate conflicts revolving around mass deforestation in Brazil. It thematizes attempts to juridify environmental destruction in international criminal law and examines the Climate Fund Case at the Brazilian Supreme Court. Finally, emerging problems and arguments in favour of starting preliminary examinations at the ICC against Bolsonaro are illuminated. This paper provides arguments as to why the initiative might be a promising undertaking, even though it is unlikely that Bolsonaro will be arrested.
We investigate numerically the appearance of heteroclinic behavior in a three-dimensional, buoyancy-driven fluid layer with stress-free top and bottom boundaries, a square horizontal periodicity with a small aspect ratio, and rotation at low to moderate rates about a vertical axis. The Prandtl number is 6.8. If the rotation is not too slow, the skewed-varicose instability leads from stationary rolls to a stationary mixed-mode solution, which in turn loses stability to a heteroclinic cycle formed by unstable roll states and connections between them. The unstable eigenvectors of these roll states are also of the skewed-varicose or mixed-mode type and in some parameter regions skewed-varicose like shearing oscillations as well as square patterns are involved in the cycle. Always present weak noise leads to irregular horizontal translations of the convection pattern and makes the dynamics chaotic, which is verified by calculating Lyapunov exponents. In the nonrotating case, the primary rolls lose, depending on the aspect ratio, stability to traveling waves or a stationary square pattern. We also study the symmetries of the solutions at the intermittent fixed points in the heteroclinic cycle.
In this thesis we mainly generalize two theorems from Mackaay-Picken and Picken (2002, 2004). In the first paper, Mackaay and Picken show that there is a bijective correspondence between Deligne 2-classes $\xi \in \check{H}^2(M,\mathcal{D}^2)$ and holonomy maps from the second thin-homotopy group $\pi_2^2(M)$ to $U(1)$. In the second one, a generalization of this theorem to manifolds with boundaries is given: Picken shows that there is a bijection between Deligne 2-cocycles and a certain variant of 2-dimensional topological quantum field theories. In this thesis we show that these two theorems hold in every dimension. We consider first the holonomy case, and by using simplicial methods we can prove that the group of smooth Deligne $d$-classes is isomorphic to the group of smooth holonomy maps from the $d^{th}$ thin-homotopy group $\pi_d^d(M)$ to $U(1)$, if $M$ is $(d-1)$-connected. We contrast this with a result of Gajer (1999). Gajer showed that Deligne $d$-classes can be reconstructed by a different class of holonomy maps, which not only include holonomies along spheres, but also along general $d$-manifolds in $M$. This approach does not require the manifold $M$ to be $(d-1)$-connected. We show that in the case of flat Deligne $d$-classes, our result differs from Gajers, if $M$ is not $(d-1)$-connected, but only $(d-2)$-connected. Stiefel manifolds do have this property, and if one applies our theorem to these and compare the result with that of Gajers theorem, it is revealed that our theorem reconstructs too many Deligne classes. This means, that our reconstruction theorem cannot live without the extra assumption on the manifold $M$, that is our reconstruction needs less informations about the holonomy of $d$-manifolds in $M$ at the price of assuming $M$ to be $(d-1)$-connected. We continue to show, that also the second theorem can be generalized: By introducing the concept of Picken-type topological quantum field theory in arbitrary dimensions, we can show that every Deligne $d$-cocycle induces such a $d$-dimensional field theory with two special properties, namely thin-invariance and smoothness. We show that any $d$-dimensional topological quantum field theory with these two properties gives rise to a Deligne $d$-cocycle and verify that this construction is surjective and injective, that is both groups are isomorphic.
Received views of utterance context in pragmatic theory characterize the occurrent subjective states of interlocutors using notions like common knowledge or mutual belief. We argue that these views are not compatible with the uncertainty and robustness of context-dependence in humanhuman dialogue. We present an alternative characterization of utterance context as objective and normative. This view reconciles the need for uncertainty with received intuitions about coordination and meaning in context, and can directly inform computational approaches to dialogue.
This paper describes the key aspects of the system SynCoP (Syntactic Constraint Parser) developed at the Berlin-Brandenburgische Akademie der Wissenschaften. The parser allows to combine syntactic tagging and chunking by means of constraint grammar using weighted finite state transducers (WFST). Chunks are interpreted as local dependency structures within syntactic tagging. The linguistic theories are formulated by criteria which are formalized by a semiring; these criteria allow structural preferences and gradual grammaticality. The parser is essentially a cascade of WFSTs. To find the most likely syntactic readings a best-path search is used.
A new method is used in an eye-tracking pilot experiment which shows that it is possible to detect differences in common ground associated with the use of minimally different types of indefinite anaphora. Following Richardson and Dale (2005), cross recurrence quantification analysis (CRQA) was used to show that the tandem eye movements of two Swedish-speaking interlocutors are slightly more coupled when they are using fully anaphoric indefinite expressions than when they are using less anaphoric indefinites. This shows the potential of CRQA to detect even subtle processing differences in ongoing discourse.
Microsaccades are very small, involuntary flicks in eye position that occur on average once or twice per second during attempted visual fixation. Microsaccades give rise to EMG eye muscle spikes that can distort the spectrum of the scalp EEG and mimic increases in gamma band power. Here we demonstrate that microsaccades are also accompanied by genuine and sizeable cortical activity, manifested in the EEG. In three experiments, high-resolution eye movements were corecorded with the EEG: during sustained fixation of checkerboard and face stimuli and in a standard visual oddball task that required the counting of target stimuli. Results show that microsaccades as small as 0.15° generate a field potential over occipital cortex and midcentral scalp sites 100 –140 ms after movement onset, which resembles the visual lambda response evoked by larger voluntary saccades. This challenges the standard assumption of human brain imaging studies that saccade-related brain activity is precluded by fixation, even when fully complied with. Instead, additional cortical potentials from microsaccades were present in 86% of the oddball task trials and of similar amplitude as the visual response to stimulus onset. Furthermore, microsaccade probability varied systematically according to the proportion of target stimuli in the oddball task, causing modulations of late stimulus-locked event-related potential (ERP) components. Microsaccades present an unrecognized source of visual brain signal that is of interest for vision research and may have influenced the data of many ERP and neuroimaging studies.
ANNIS
(2004)
In this paper, we discuss the design and implementation of our first version of the database "ANNIS" ("ANNotation of Information Structure"). For research based on empirical data, ANNIS provides a uniform environment for storing this data together with its linguistic annotations. A central database promotes standardized annotation, which facilitates interpretation and comparison of the data. ANNIS is used through a standard web browser and offers tier-based visualization of data and annotations, as well as search facilities that allow for cross-level and cross-sentential queries. The paper motivates the design of the system, characterizes its user interface, and provides an initial technical evaluation of ANNIS with respect to data size and query processing.
Complex emulsions are dispersions of kinetically stabilized multiphasic emulsion droplets comprised of two or more immiscible liquids that provide a novel material platform for the generation of active and dynamic soft materials. In recent years, the intrinsic reconfigurable morphological behavior of complex emulsions, which can be attributed to the unique force equilibrium between the interfacial tensions acting at the various interfaces, has become of fundamental and applied interest. As such, particularly biphasic Janus droplets have been investigated as structural templates for the generation of anisotropic precision objects, dynamic optical elements or as transducers and signal amplifiers in chemo- and bio-sensing applications. In the present thesis, switchable internal morphological responses of complex droplets triggered by stimuli-induced alterations of the balance of interfacial tensions have been explored as a universal building block for the design of multiresponsive, active, and adaptive liquid colloidal systems. A series of underlying principles and mechanisms that influence the equilibrium of interfacial tensions have been uncovered, which allowed the targeted design of emulsion bodies that can alter their shape, bind and roll on surfaces, or change their geometrical shape in response to chemical stimuli. Consequently, combinations of the unique triggerable behavior of Janus droplets with designer surfactants, such as a stimuli-responsive photosurfactant (AzoTAB) resulted for instance in shape-changing soft colloids that exhibited a jellyfish inspired buoyant motion behavior, holding great promise for the design of biological inspired active material architectures and transformable soft robotics.
In situ observations of spherical Janus emulsion droplets using a customized side-view microscopic imaging setup with accompanying pendant dropt measurements disclosed the sensitivity regime of the unique chemical-morphological coupling inside complex emulsions and enabled the recording of calibration curves for the extraction of critical parameters of surfactant effectiveness. The deduced new "responsive drop" method permitted a convenient and cost-efficient quantification and comparison of the critical micelle concentrations (CMCs) and effectiveness of various cationic, anionic, and nonionic surfactants. Moreover, the method allowed insightful characterization of stimuli-responsive surfactants and monitoring of the impact of inorganic salts on the CMC and surfactant effectiveness of ionic and nonionic surfactants. Droplet functionalization with synthetic crown ether surfactants yielded a synthetically minimal material platform capable of autonomous and reversible adaptation to its chemical environment through different supramolecular host-guest recognition events. Addition of metal or ammonium salts resulted in the uptake of the resulting hydrophobic complexes to the hydrocarbon hemisphere, whereas addition of hydrophilic ammonium compounds such as amino acids or polypeptides resulted in supramolecular assemblies at the hydrocarbon-water interface of the droplets. The multiresponsive material platform enabled interfacial complexation and
thus triggered responses of the droplets to a variety of chemical triggers including metal ions, ammonium compounds, amino acids, antibodies, carbohydrates as well as amino-functionalized solid surfaces.
In the final chapter, the first documented optical logic gates and combinatorial logic circuits based on complex emulsions are presented. More specifically, the unique reconfigurable and multiresponsive properties of complex emulsions were exploited to realize droplet-based logic gates of varying complexity using different stimuli-responsive surfactants in combination with diverse readout methods. In summary, different designs for multiresponsive, active, and adaptive liquid colloidal systems were presented and investigated, enabling the design of novel transformative chemo-intelligent soft material platforms.