Filtern
Erscheinungsjahr
Dokumenttyp
Sprache
- Englisch (519) (entfernen)
Schlagworte
- Stress (27)
- Modellierung (19)
- Fernerkundung (18)
- Optimierung (18)
- Deutschland (16)
- Hydrocortison (13)
- Satellitenfernerkundung (13)
- Cortisol (9)
- Europäische Union (9)
- Finanzierung (9)
Institut
- Raum- und Umweltwissenschaften (99)
- Psychologie (94)
- Fachbereich 4 (54)
- Mathematik (47)
- Fachbereich 6 (38)
- Wirtschaftswissenschaften (29)
- Fachbereich 1 (24)
- Informatik (19)
- Anglistik (15)
- Rechtswissenschaft (14)
The study analyzes the long-term trends (1998–2019) of concentrations of the air pollutants ozone (O3) and nitrogen oxides (NOx) as well as meteorological conditions at forest sites in German midrange mountains to evaluate changes in O3 uptake conditions for trees over time at a plot scale. O3 concentrations did not show significant trends over the course of 22 years, unlike NO2 and NO, whose concentrations decreased significantly since the end of the 1990s. Temporal analyses of meteorological parameters found increasing global radiation at all sites and decreasing precipitation, vapor pressure deficit (VPD), and wind speed at most sites (temperature did not show any trend). A principal component analysis revealed strong correlations between O3 concentrations and global radiation, VPD, and temperature. Examination of the atmospheric water balance, a key parameter for O3 uptake, identified some unusually hot and dry years (2003, 2011, 2018, and 2019). With the help of a soil water model, periods of plant water stress were detected. These periods were often in synchrony with periods of elevated daytime O3 concentrations and usually occurred in mid and late summer, but occasionally also in spring and early summer. This suggests that drought protects forests against O3 uptake and that, in humid years with moderate O3 concentrations, the O3 flux was higher than in dry years with higher O3 concentrations.
Influence of Ozone and Drought on Tree Growth under Field Conditions in a 22 Year Time Series
(2022)
Studying the effect of surface ozone (O3) and water stress on tree growth is important for planning sustainable forest management and forest ecology. In the present study, a 22-year long time series (1998–2019) on basal area increment (BAI) and fructification severity of European beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) H.Karst.) at five forest sites in Western Germany (Rhineland Palatinate) was investigated to evaluate how it correlates with drought and stomatal O3 fluxes (PODY) with an hourly threshold of uptake (Y) to represent the detoxification capacity of trees (POD1, with Y = 1 nmol O3 m−2 s−1). Between 1998 and 2019, POD1 declined over time by on average 0.31 mmol m−2 year−1. The BAI showed no significant trend at all sites, except in Leisel where a slight decline was observed over time (−0.37 cm2 per year, p < 0.05). A random forest analysis showed that the soil water content and daytime O3 mean concentration were the best predictors of BAI at all sites. The highest mean score of fructification was observed during the dry years, while low level or no fructification was observed in most humid years. Combined effects of drought and O3 pollution mostly influence tree growth decline for European beech and Norway spruce.
Formulations of macrocyclic lactone anthelmintics such as moxidectin are regularly administered to sheep to combat parasites. A disadvantage of these pharmaceuticals are their side effects on non-target organisms when entering the environment. Little is known about anthelmintic effects on plant reproduction and whether the effects depend on environmental factors. For ecological and methodological reasons, we aimed at testing whether temperature affects the efficacy of a common moxidectin-based formulation on seed germination. We carried out a germination experiment including three typical species of temperate European grasslands (Centaurea jacea, Galium mollugo, Plantago lanceolata). We applied three temperature regimes (15/5, 20/10, 30/20°C), and a four-level dilution series (1:100–1:800) of formulated moxidectin (i.e., Cydectin oral drench). These solutions represent seed-anthelmintic contacts in the digestive tract of sheep shortly after deworming. In addition, a control was carried out with purified water only. We regularly counted emerging seedlings and calculated final germination percentage, mean germination time and synchrony of germination. Formulated moxidectin significantly reduced percentage, speed and synchrony of germination. A 1:100 dilution of the formulation reduced germination percentage by a quarter and increased mean germination time by six days compared to the control. Temperature moderated effects of the anthelmintic drug on germination in all response variables and all species, but in different patterns and magnitudes (significant anthelmintic x temperature x species interactions). In all response variables, the two more extreme temperature regimes (15/5, 30/20°C) led to the strongest effects of formulated moxidectin. With respect to germination percentage, G. mollugo was more sensitive to formulated moxidectin at the warmest temperature regime, whereas P. lanceolata showed the highest sensitivity at the coldest regime. This study shows that it is important to consider temperature dependencies of the effects of pharmaceuticals on seed germination when conducting standardised germination experiments.
In this study, candidate loci for periodic catatonia (SCZD10, OMIM #605419) on chromosome 15q15 and 22q13.33 have been fine mapped and investigated. Previously, several studies found evidences for a major susceptibility locus on chromosome 15q15 and a further potential locus on 22q13.33 pointing to genetic heterogeneity. Fine mapping was done in our multiplex families through linkage and mutational analysis using genomic markers selected from public databases. Positional candidate genes like SPRED1 and BRD1, and ultra-conserved elements were investigated by direct sequencing in these families. The results narrow down the susceptibility locus on chromosome 15q14-15q15.1 to a region between markers D15S1042 and D15S968, as well as exclusion of SPRED1 and ultra-conserved elements as susceptibility candidates. Fine mapping for two chromosome 23q13.33-linked families showed that the recombination events would place the disease-causing gene to a telomeric ~577 Kb interval and SNP rs138880 investigation revealed an A-allele in the affected person, therefore excludes BRD1 as well as confirmed MLC1 to be the candidate gene for periodic catatonia.
Early life adversity (ELA) is associated with a higher risk for diseases in adulthood. Changes in the immune system have been proposed to underlie this association. Although higher levels of inflammation and immunosenescence have been reported, data on cell-specific immune effects are largely absent. In addition, stress systems and health behaviors are altered in ELA, which may contribute to the generation of the "ELA immune phenotype". In this thesis, we have investigated the ELA immune phenotype on a cellular level and whether this is an indirect consequence of changes in behavior or stress reactivity. To address these questions the EpiPath cohort was established, consisting of 115 young adults with or without ELA. ELA participants had experienced separation from their parents in early childhood and were subsequently adopted, which is a standard model for ELA, whereas control participants grew up with their biological parents. At a first visit, blood samples were taken for analysis of epigenetic markers and immune parameters. A selection of the cohort underwent a standardized laboratory stress test (SLST). Endocrine, immune, and cardiovascular parameters were assessed at several time points before and after stress. At a second visit, participants underwent structural clinical interviews and filled out psychological questionnaires. We observed a higher number of activated T cells in ELA, measured by HLA-DR and CD25 expression. Neither cortisol levels nor health-risk behaviors explained the observed group differences. Besides a trend towards higher numbers of CCR4+CXCR3-CCR6+ CD4 T cells in ELA, relative numbers of immune cell subsets in circulation were similar between groups. No difference was observed in telomere length or in methylation levels of age-related CpGs in whole blood. However, we found a higher expression of senescence markers (CD57) on T cells in ELA. In addition, these cells had an increased cytolytic potential. A mediation analysis demonstrated that cytomegalovirus infection " an important driving force of immunosenescence " largely accounted for elevated CD57 expression. The psychological investigations revealed that after adoption, family conditions appeared to have been similar to the controls. However, PhD thesis MMC Elwenspoek 18 ELA participants scored higher on a depression index, chronic stress, and lower on self-esteem. Psychological, endocrine, and cardiovascular parameters significantly responded to the SLST, but were largely similar between the two groups. Only in a smaller subset of groups matched for gender, BMI, and age, the cortisol response seemed to be blunted in ELA participants. Although we found small differences in the methylation level of the GR promoter, GR sensitivity and mRNA expression levels GR as well as expression of the GR target genes FKBP5 and GILZ were similar between groups. Taken together, our data suggest an elevated state of immune activation in ELA, in which particularly T cells are affected. Furthermore, we found higher levels of T cells immunosenescence in ELA. Our data suggest that ELA may increase the risk of cytomegalovirus infection in early childhood, thereby mediating the effect of ELA on T cell specific immunosenescence. Importantly, we found no evidence of HPA dysregulation in participants exposed to ELA in the EpiPath cohort. Thus, the observed immune phenotype does not seem to be secondary to alterations in the stress system or health-risk behaviors, but rather a primary effect of early life programming on immune cells. Longitudinal studies will be necessary to further dissect cause from effect in the development of the ELA immune phenotype.
Background: Increasing exposure to engineered inorganic nanoparticles takes actually place in both terrestric and aquatic ecosystems worldwide. Although we already know harmful effects of AgNP on the soil bacterial community, information about the impact of the factors functionalization, concentration, exposure time, and soil texture on the AgNP effect expression are still rare. Hence, in this study, three soils of different grain size were exposed for up to 90 days to bare and functionalized AgNP in concentrations ranging from 0.01 to 1.00 mg/kg soil dry weight. Effects on soil microbial community were quantified by various biological parameters, including 16S rRNA gene, photometric, and fluorescence analyses.
Results: Multivariate data analysis revealed significant effects of AgNP exposure for all factors and factor combinations investigated. Analysis of individual factors (silver species, concentration, exposure time, soil texture) in the unifactorial ANOVA explained the largest part of the variance compared to the error variance. In depth analysis of factor combinations revealed even better explanation of variance. For the biological parameters assessed in this study, the matching of soil texture and silver species, and the matching of soil texture and exposure time were the two most relevant factor combinations. The factor AgNP concentration contributed to a lower extent to the effect expression compared to silver species, exposure time and physico–chemical composition of soil.
Conclusions: The factors functionalization, concentration, exposure time, and soil texture significantly impacted the effect expression of AgNP on the soil microbial community. Especially long-term exposure scenarios are strongly needed for the reliable environmental impact assessment of AgNP exposure in various soil types.
The influence of the dopamine agonist Ritalin-® on performance in a card sorting task involving a monetary reward component was tested in 43 healthy male participants. It was investigated whether Ritalin-® would have differential behavioral effects as a function of the participants' parental bonding experiences and the personality variable "Novelty Seeking". When activity and performance accuracy were stimulated my monetary reward, Ritalin-® reduced activity in response to reward and added to the reward-induced increase in performance accuracy. However, performance accuracy after drug challenge was improved only in the low care participants. In the high care participants, it was contrarily impaired. This observation suggests that the successful therapeutic administration of Ritalin-® in ADHD may be influenced by early life parental care. Suggesting an association between the personality dimension of "Novelty Seeking" and the dopamine system, high "Novelty Seeking" scores positively correlated with sensitivity to Ritalin-® challenge.
In recent years, Islamic banking has been one of the fastest growing markets in the financial world. Even to German banks, Islamic finance is not as 'foreign' as one might think. Indeed, several banks are already operating so-called "Islamic windows" in various Arab countries. However, German banks are still reluctant to offer 'Islamic' products in Germany, despite the fact that approximately 3.5 million Muslims currently live there. Potential reasons for this reluctance include widespread misunderstanding of Islamic banking in Germany and prevailing cultural prejudice towards Islam generally. The author seeks to address these concerns and to take an objective approach towards understanding the potential for Islamic banking in Germany. Legally, Islamic law cannot be the governing law of any contract in Germany. Therefore, the aim must be to draft contracts that are both enforceable under German law and consistent with the principles of Shari'a " the Islamic law. In this paper, the author gives a detailed legal analysis of the most common Islamic banking products and how they could be given effect under German law, while attempting to address widespread concerns about arbitration or parallel Shari'a courts. This publication is one of the first legal analysis of Islamic banking products in Germany. As such, its goal is not to be the final word, but rather to begin the conversation about potential problems and conflicts of Islamic banking in Germany that require further investigation.
Family firms play a crucial role in the DACH region (Germany, Austria, Switzerland). They are characterized by a long tradition, a strong connection to the region, and a well-established network. However, family firms also face challenges, especially in finding a suitable successor. Wealthy entrepreneurial families are increasingly opting to establish Single Family Offices (SFOs) as a solution to this challenge. An SFO takes on the management and protection of family wealth. Its goal is to secure and grow the wealth over generations. In Germany alone, there are an estimated 350 to 450 SFOs, with 70% of them being established after the year 2000. However, research on SFOs is still in its early stages, particularly regarding the role of SFOs as firm owners. This dissertation delves into an exploration of SFOs through four quantitative empirical studies. The first study provides a descriptive overview of 216 SFOs from the DACH-region. Findings reveal that SFOs exhibit a preference for investing in established companies and real estate. Notably, only about a third of SFOs engage in investments in start-ups. Moreover, SFOs as a group are heterogeneous. Categorizing them into three groups based on their relationship with the entrepreneurial family and the original family firm reveals significant differences in their asset allocation strategies. Subsequent studies in this dissertation leverage a hand-collected sample of 173 SFO-owned firms from the DACH region, meticulously matched with 684 family-owned firms from the same region. The second study focusing on financial performance indicates that SFO-owned firms tend to exhibit comparatively poorer financial performance than family-owned firms. However, when members of the SFO-owning family hold positions on the supervisory or executive board of the firm, there's a notable improvement. The third study, concerning cash holdings, reveals that SFO-owned firms maintain a higher cash holding ratio compared to family-owned firms. Notably, this effect is magnified when the SFO has divested its initial family firms. Lastly, the fourth study regarding capital structure highlights that SFO-owned firms tend to display a higher long-term debt ratio than family-owned firms. This suggests that SFO-owned firms operate within a trade-off theory framework, like private equity-owned firms. Furthermore, this effect is stronger for SFOs that sold their original family firm. The outcomes of this research are poised to provide entrepreneurial families with a practical guide for effectively managing and leveraging SFOs as a strategic long-term instrument for succession and investment planning.
The Eurosystem's Household Finance and Consumption Survey (HFCS) collects micro data on private households' balance sheets, income and consumption. It is a stylised fact that wealth is unequally distributed and that the wealthiest own a large share of total wealth. For sample surveys which aim at measuring wealth and its distribution, this is a considerable problem. To overcome it, some of the country surveys under the HFCS umbrella try to sample a disproportionately large share of households that are likely to be wealthy, a technique referred to as oversampling. Ignoring such types of complex survey designs in the estimation of regression models can lead to severe problems. This thesis first illustrates such problems using data from the first wave of the HFCS and canonical regression models from the field of household finance and gives a first guideline for HFCS data users regarding the use of replicate weight sets for variance estimation using a variant of the bootstrap. A further investigation of the issue necessitates a design-based Monte Carlo simulation study. To this end, the already existing large close-to-reality synthetic simulation population AMELIA is extended with synthetic wealth data. We discuss different approaches to the generation of synthetic micro data in the context of the extension of a synthetic simulation population that was originally based on a different data source. We propose an additional approach that is suitable for the generation of highly skewed synthetic micro data in such a setting using a multiply-imputed survey data set. After a description of the survey designs employed in the first wave of the HFCS, we then construct new survey designs for AMELIA that share core features of the HFCS survey designs. A design-based Monte Carlo simulation study shows that while more conservative approaches to oversampling do not pose problems for the estimation of regression models if sampling weights are properly accounted for, the same does not necessarily hold for more extreme oversampling approaches. This issue should be further analysed in future research.
This dissertation is dedicated to the analysis of the stabilty of portfolio risk and the impact of European regulation introducing risk based classifications for investment funds.
The first paper examines the relationship between portfolio size and the stability of mutual fund risk measures, presenting evidence for economies of scale in risk management. In a unique sample of 338 fund portfolios we find that the volatility of risk numbers decreases for larger funds. This finding holds for dispersion as well as tail risk measures. Further analyses across asset classes provide evidence for the robustness of the effect for balanced and fixed income portfolios. However, a size effect did not emerge for equity funds, suggesting that equity fund managers simply scale their strategy up as they grow. Analyses conducted on the differences in risk stability between tail risk measures and volatilities reveal that smaller funds show higher discrepancies in that respect. In contrast to the majority of prior studies on the basis of ex-post time series risk numbers, this study contributes to the literature by using ex-ante risk numbers based on the actual assets and de facto portfolio data.
The second paper examines the influence of European legislation regarding risk classification of mutual funds. We conduct analyses on a set of worldwide equity indices and find that a strategy based on the long term volatility as it is imposed by the Synthetic Risk Reward Indicator (SRRI) would lead to substantial variations in exposures ranging from short phases of very high leverage to long periods of under investments that would be required to keep the risk classes. In some cases, funds will be forced to migrate to higher risk classes due to limited means to reduce volatilities after crises events. In other cases they might have to migrate to lower risk classes or increase their leverage to ridiculous amounts. Overall, we find if the SRRI creates a binding mechanism for fund managers, it will create substantial interference with the core investment strategy and may incur substantial deviations from it. Fruthermore due to the forced migrations the SRRI degenerates to a passive indicator.
The third paper examines the impact of this volatility based fund classification on portfolio performance. Using historical data on equity indices we find initially that a strategy based on long term portfolio volatility, as it is imposed by the Synthetic Risk Reward Indicator (SRRI), yields better Sharpe Ratios (SRs) and Buy and Hold Returns (BHRs) for the investment strategies matching the risk classes. Accounting for the Fama-French factors reveals no significant alphas for the vast majority of the strategies. In our simulation study where volatility was modelled through a GJR(1,1) - model we find no significant difference in mean returns, but significantly lower SRs for the volatility based strategies. These results were confirmed in robustness checks using alternative models and timeframes. Overall we present evidence which suggests that neither the higher leverage induced by the SRRI nor the potential protection in downside markets does pay off on a risk adjusted basis.
The discretization of optimal control problems governed by partial differential equations typically leads to large-scale optimization problems. We consider flow control involving the time-dependent Navier-Stokes equations as state equation which is stamped by exactly this property. In order to avoid the difficulties of dealing with large-scale (discretized) state equations during the optimization process, a reduction of the number of state variables can be achieved by employing a reduced order modelling technique. Using the snapshot proper orthogonal decomposition method, one obtains a low-dimensional model for the computation of an approximate solution to the state equation. In fact, often a small number of POD basis functions suffices to obtain a satisfactory level of accuracy in the reduced order solution. However, the small number of degrees of freedom in a POD based reduced order model also constitutes its main weakness for optimal control purposes. Since a single reduced order model is based on the solution of the Navier-Stokes equations for a specified control, it might be an inadequate model when the control (and consequently also the actual corresponding flow behaviour) is altered, implying that the range of validity of a reduced order model, in general, is limited. Thus, it is likely to meet unreliable reduced order solutions during a control problem solution based on one single reduced order model. In order to get out of this dilemma, we propose to use a trust-region proper orthogonal decomposition (TRPOD) approach. By embedding the POD based reduced order modelling technique into a trust-region framework with general model functions, we obtain a mechanism for updating the reduced order models during the optimization process, enabling the reduced order models to represent the flow dynamics as altered by the control. In fact, a rigorous convergence theory for the TRPOD method is obtained which justifies this procedure also from a theoretical point of view. Benefiting from the trust-region philosophy, the TRPOD method guarantees to save a lot of computational work during the control problem solution, since the original state equation only has to be solved if we intend to update our model function in the trust-region framework. The optimization process itself is completely based on reduced order information only.
Some of the largest firms in the DACH region (Germany, Austria, Switzerland) are (partially) owned by a foundation and/or a family office, such as Aldi, Bosch, or Rolex. Despite their growing importance, prior research neglected to analyze the impact of these intermediaries on the firms they own. This dissertation closes this research gap by contributing to a deeper understanding of two increasingly used family firm succession vehicles, through four empirical quantitative studies. The first study focuses on the heterogeneity in foundation-owned firms (FOFs) by applying a descriptive analysis to a sample of 169 German FOFs. The results indicate that the family as a central stakeholder in a family foundation fosters governance that promotes performance and growth. The second study examines the firm growth of 204 FOFs compared to matched non-FOFs from the DACH region. The findings suggest that FOFs grow significantly less in terms of sales but not with regard to employees. In addition, it seems that this negative effect is stronger for the upper than for the middle or lower quantiles of the growth distribution. Study three adopts an agency perspective and investigates the acquisition behavior within the group of 164 FOFs. The results reveal that firms with charitable foundations as owners are more likely to undertake acquisitions and acquire targets that are geographically and culturally more distant than firms with a family foundation as owner. At the same time, they favor target companies from the same or related industries. Finally, the fourth study scrutinizes the capital structure of firms owned by single family-offices (SFOs). Drawing on a hand-collected sample of 173 SFO-owned firms in the DACH region, the results show that SFO-owned firms display a higher long-term debt ratio than family-owned firms, indicating that SFO-owned firms follow trade-off theory, similar to private equity-owned firms. Additional analyses show that this effect is stronger for SFOs that sold their original family firm. In conclusion, the outcomes of this dissertation furnish valuable research contributions and offer practical insights for families navigating such intermediaries or succession vehicles in the long term.
The stress hormone cortisol as the end-product of the hypothalamic-pituitary-adrenal (HPA) axis has been found to play a crucial role in the release of aggressive behavior (Kruk et al., 2004; Böhnke et al., 2010). In order to further explore potential mechanisms underlying the relationship between stress and aggression, such as changes in (social) information processing, we conducted two experimental studies that are presented in this thesis. In both studies, acute stress was induced by means of the Socially Evaluated Cold Pressor Test (SECP) designed by Schwabe et al. (2008). Stressed participants were classified as either cortisol responders or nonresponders depending on their rise in cortisol following the stressor. Moreover, basal HPA axis activity was measured prior to the experimental sessions and EEG was recorded throughout the experiments. The first study dealt with the influence of acute stress on cognitive control processes. 41 healthy male participants were assigned to either the stress condition or the non-stressful control procedure of the SECP. Before as well as after the stress induction, all participants performed a cued task-switching paradigm in order to measure cognitive control processes. Results revealed a significant influence of acute and basal cortisol levels, respectively, on the motor preparation of the upcoming behavioral response, that was reflected in changes in the magnitude of the terminal Contingent Negative Variation (CNV). In the second study, the effect of acute stress and subsequent social provocation on approach-avoidance motivation was examined. 72 healthy students (36 males, 36 females) took part in the study. They performed an approach-avoidance task, using emotional facial expressions as stimuli, before as well as after the experimental manipulation of acute stress (again via the SECP) and social provocation realized by means of the Taylor Aggression Paradigm (Taylor, 1967). Additionally to salivary cortisol, testosterone samples were collected at several points in time during the experimental session. Results indicated a positive relationship between acute testosterone levels and the motivation to approach social threat stimuli in highly provoked cortisol responders. Similar results were found when the testosterone-to-cortisol ratio at baseline was taken into account instead of acute testosterone levels. Moreover, brain activity during the approach-avoidance task was significantly influenced by acute stress and social provocation, as reflected in reductions of early (P2) as well as of later (P3) ERP components in highly provoked cortisol responders. This may indicate a less accurate, rapid processing of socially relevant stimuli due to an acute increase in cortisol and subsequent social provocation. In conclusion, the two studies presented in this thesis provide evidence for significant changes in information processing due to acute stress, basal cortisol levels and social provocation, suggesting an enhanced preparation for a rapid behavioral response in the sense of a fight-or-flight reaction. These results confirm the model of Kruk et al. (2004) proposing a mediating role of changed information processes in the stress-aggression-link.
Climate change is expected to cause mountain species to shift their ranges to higher elevations. Due to the decreasing amounts of habitats with increasing elevation, such shifts are likely to increase their extinction risk. Heterogeneous mountain topography, however, may reduce this risk by providing microclimatic conditions that can buffer macroclimatic warming or provide nearby refugia. As aspect strongly influences the local microclimate, we here assess whether shifts from warm south-exposed aspects to cool north-exposed aspects in response to climate change can compensate for an upward shift into cooler elevations.
Every day we are exposed to a large set of appetitive food cues, mostly of high caloric, high carbohydrate content. Environmental factors like food cue exposition can impact eating behavior, by triggering anticipatory endocrinal responses and reinforcing the reward value of food. Additionally, it has been shown that eating behavior is largely influence by neuroendocrine factors. Energy homeostasis is of great importance for survival in all animal species. It is challenged under the state of food deprivation which is considered to be a metabolic stressor. Interestingly, the systems regulating stress and food intake share neural circuits. Adrenal glucocorticoids, as cortisol, and the pancreatic hormone insulin have been shown to be crucial to maintain catabolic and anabolic balance. Cortisol and insulin can cross the blood-brain barrier and interact with receptors distributed throughout the brain, influencing appetite and eating behavior. At the same time, these hormones have an important impact on the stress response. The aim of the current work is to broaden the knowledge on reward related food cue processing. With that purpose, we studied how food cue processing is influenced by food deprivation in women (in different phases of the menstrual cycle) and men. Furthermore, we investigated the impact of the stress/metabolic hormones, insulin and cortisol, at neural sites important for energy metabolism and in the processing of visual food cues. The Chapter I of this thesis details the underlying mechanisms of the startle response and its application in the investigation of food cue processing. Moreover, it describes the effects of food deprivation and of the stress-metabolic hormones insulin and cortisol in reward related processing of food cues. It explains the rationale for the studies presented in Chapter II-IV and describes their main findings. A general discussion of the results and recommendations for future research is given. In the study described in Chapter II, startle methodology was used to study the impact of food deprivation in the processing of reward related food cues. Women in different phases of the menstrual cycle and men were studied, in order to address potential effects of sex and menstrual cycle. All participants were studied either satiated or food deprived. Food deprivation provoked enhanced acoustic startle (ASR) response during foreground presentation of visual food cues. Sex and menstrual cycle did not influence this effect. The startle pattern towards food cues during fasting can be explained by a frustrative nonreward effect (FNR), driven by the impossibility to consume the exposed food. In Chapter III, a study is described, which was carried out to explore the central effects of insulin and cortisol, using continuous arterial spin labeling to map cerebral blood flow patterns. Following standardized periods of fasting, male participants received either intranasal insulin, oral cortisol, both, or placebo. Intranasal insulin increased resting regional cerebral blood flow in the putamen and insular cortex, structures that are involved in the regulation of eating behavior. Neither cortisol nor interaction effects were found. These results demonstrate that insulin exerts an action in metabolic centers during resting state, which is not affected by glucocorticoids. The study described in Chapter IV uses a similar pharmacological manipulation as the one presented in Chapter III, while assessing processing of reward related food cues through the startle paradigm validated in Chapter II. A sample of men was studied during short-term food deprivation. Considering the importance of both cortisol and insulin in glucose metabolism, food pictures were divided by glycemic index. Cortisol administration enhanced ASR during foreground presentation of "high glycemic" food pictures. This result suggests that cortisol provokes an increase in reward value of high glycemic food cues, which is congruent with previous research on stress and food consumption. This thesis gives support to the FNR hypothesis towards food cues during states of deprivation. Furthermore, it highlights the potential effects of stress related hormones in metabolism-connected neuronal structures, and in the reward related mechanisms of food cue processing. In a society marked by increased food exposure and availability, alongside with increased stress, it is important to better understand the impact of food exposition and its interaction with relevant hormones. This thesis contributes to the knowledge in this field. More research in this direction is needed.
As a target for condemnation, the thematic prevalence of racism in African American novels of satire is not surprising. In order to confront this vice in its shifting manifestations, however, the African American satirist has to employ special techniques. This thesis examines some of these devices as they occur in George Schuyler- Black No More, Charles Wright- The Wig, and Percival Everett- Erasure. Given the reciprocity of target and technique in the satiric context, close attention is paid to how the authors under study locate and interrogate racism in their narratives. In this respect, the significance of anti-essentialist Marxist criticism in Schuyler- Black No More and the author- portrayal of the society of his time as capitalist machinery is examined. While Schuyler is concerned with exposing the general socioeconomic workings of the 1920s from a Marxist perspective, Wright offers the reader perspective into how this oppressive machinery psychologically manipulates and corrupts the individual in the historic context of Lyndon B. Johnson- political vision of the Great Society. Everett then elaborates on the epistemological concern which is traceable in Wright- work and addresses the role media representation plays in manufacturing images and rigid categories that shape systematic racism. As such, the present study not only highlights the versatility of satire as a rhetorical secret weapon and thus ventures toward the idiosyncrasies of the African American novel of satire, it also makes an effort to trace the ever-changing face of racial discrimination.
The following dissertation contains three studies examining academic boredom development in five high-track German secondary schools (AVG-project data; Study 1: N = 1,432; Study 2: N = 1,861; Study 3: N = 1,428). The investigation period spanned 3.5 years, with four waves of measurement from grades 5 to 8 (T1: 5th grade, after transition to secondary school; T2: 5th grade, after mid-term evaluations; T3: 6th grade, after mid-term evaluations; T4: 8th grade, after mid-term evaluations). All three studies featured cross-sectional and longitudinal analyses, separating, and comparing the subject domains of mathematics and German.
Study 1 provided an investigation of academic boredom’s factorial structure alongside correlational and reciprocal relations of different forms of boredom and academic self-concept. Analyses included reciprocal effects models and latent correlation analyses. Results indicated separability of boredom intensity, boredom due to underchallenge and boredom due to overchallenge, as separate, correlated factors. Evidence for reciprocal relations between boredom and academic self-concept was limited.
Study 2 examined the effectiveness and efficacy of full-time ability grouping for as a boredom intervention directed at the intellectually gifted. Analyses included propensity score matching, and latent growth curve modelling. Results pointed to limited effectiveness and efficacy for full-time ability grouping regarding boredom reduction.
Study 3 explored gender differences in academic boredom development, mediated by academic interest, academic self-concept, and previous academic achievement. Analyses included measurement invariance testing, and multiple-indicator-multi-cause-models. Results showed one-sided gender differences, with boys reporting less favorable boredom development compared to girls, even beyond the inclusion of relevant mediators.
Findings from all three studies were embedded into the theoretical framework of control-value theory (Pekrun, 2006; 2019; Pekrun et al., 2023). Limitations, directions for future research, and practical implications were acknowledged and discussed.
Overall, this dissertation yielded important insights into boredom’s conceptual complexity. This concerned factorial structure, developmental trajectories, interrelations to other learning variables, individual differences, and domain specificities.
Keywords: Academic boredom, boredom intensity, boredom due to underchallenge, boredom due to overchallenge, ability grouping, gender differences, longitudinal data analysis, control-value theory
Entrepreneurial ventures are associated with economic growth, job creation, and innovation. Most entrepreneurial ventures need external funding to succeed. However, they often find it difficult to access traditional forms of financing, such as bank loans. To overcome this hurdle and to provide entrepreneurial ventures with badly-needed external capital, many types of entrepreneurial finance have emerged over the past decades and continue to emerge today. Inspired by these dynamics, this postdoctoral thesis contains five empirical studies that address novel questions regarding established (e.g., venture capital, business angels) and new types of entrepreneurial finance (i.e., initial coin offerings).
The microbial enzyme alkaline phosphatase contributes to the removal of organic phosphorus compounds from wastewaters. To cope with regulatory threshold values for permitted maximum phosphor concentrations in treated wastewaters, a high activity of this enzyme in the biological treatment stage, e.g., the activated sludge process, is required. To investigate the reaction dynamics of this enzyme, to analyze substrate selectivities, and to identify potential inhibitors, the determination of enzyme kinetics is necessary. A method based on the application of the synthetic fluorogenic substrate 4-methylumbelliferyl phosphate is proven for soils, but not for activated sludges. Here, we adapt this procedure to the latter. The adapted method offers the additional benefit to determine inhibition kinetics. In contrast to conventional photometric assays, no particle removal, e.g., of sludge pellets, is required enabling the analysis of the whole sludge suspension as well as of specific sludge fractions. The high sensitivity of fluorescence detection allows the selection of a wide substrate concentration range for sound modeling of kinetic functions.
- Fluorescence array technique for fast and sensitive analysis of high sample numbers
- No need for particle separation – analysis of the whole (diluted) sludge suspension
- Simultaneous determination of standard and inhibition kinetics
Building Fortress Europe Economic realism, China, and Europe’s investment screening mechanisms
(2023)
This thesis deals with the construction of investment screening mechanisms across the major economic powers in Europe and at the supranational level during the post-2015 period. The core puzzle at the heart of this research is how, in a traditional bastion of economic liberalism such as Europe, could a protectionist tool such as investment screening be erected in such a rapid manner. Within a few years, Europe went from a position of being highly welcoming towards foreign investment to increasingly implementing controls on it, with the focus on China. How are we to understand this shift in Europe? I posit that Europe’s increasingly protectionist shift on inward investment can be fruitfully understood using an economic realist approach, where the introduction of investment screening can be seen as part of a process of ‘balancing’ China’s economic rise and reasserting European competitiveness. China has moved from being the ‘workshop of the world’ to becoming an innovation-driven economy at the global technological frontier. As China has become more competitive, Europe, still a global economic leader, broadly situated at the technological frontier, has begun to sense a threat to its position, especially in the context of the fourth industrial revolution. A ‘balancing’ process has been set in motion, in which Europe seeks to halt and even reverse the narrowing competitiveness gap between it and China. The introduction of investment screening measures is part of this process.
Academic achievement is a central outcome in educational research, both in and outside higher education, has direct effects on individual’s professional and financial prospects and a high individual and public return on investment. Theories comprise cognitive as well as non-cognitive influences on achievement. Two examples frequently investigated in empirical research are knowledge (as a cognitive determinant) and stress (as a non-cognitive determinant) of achievement. However, knowledge and stress are not stable, what raises questions as to how temporal dynamics in knowledge on the one hand and stress on the other contribute to achievement. To study these contributions in the present doctoral dissertation, I used meta-analysis, latent profile transition analysis, and latent state-trait analysis. The results support the idea of knowledge acquisition as a cumulative and long-term process that forms the basis for academic achievement and conceptual change as an important mechanism for the acquisition of knowledge in higher education. Moreover, the findings suggest that students’ stress experiences in higher education are subject to stable, trait-like influences, as well as situational and/or interactional, state-like influences which are differentially related to achievement and health. The results imply that investigating the causal networks between knowledge, stress, and academic achievement is a promising strategy for better understanding academic achievement in higher education. For this purpose, future studies should use longitudinal designs, randomized controlled trials, and meta-analytical techniques. Potential practical applications include taking account of students’ prior knowledge in higher education teaching and decreasing stress among higher education students.
Amphibian diversity in the Amazonian floating meadows: a Hanski core-satellite species system
(2021)
The Amazon catchment is the largest river basin on earth, and up to 30% of its waters flow across floodplains. In its open waters, floating plants known as floating meadows abound. They can act as vectors of dispersal for their associated fauna and, therefore, can be important for the spatial structure of communities. Here, we focus on amphibian diversity in the Amazonian floating meadows over large spatial scales. We recorded 50 amphibian species over 57 sites, covering around 7000 km along river courses. Using multi-site generalised dissimilarity modelling of zeta diversity, we tested Hanski's core-satellite hypothesis and identified the existence of two functional groups of species operating under different ecological processes in the floating meadows. ‘Core' species are associated with floating meadows, while ‘satellite' species are associated with adjacent environments, being only occasional or accidental occupants of the floating vegetation. At large scales, amphibian diversity in floating meadows is mostly determined by stochastic (i.e. random/neutral) processes, whereas at regional scales, climate and deterministic (i.e. niche-based) processes are central drivers. Compared with the turnover of ‘core' species, the turnover of ‘satellite' species increases much faster with distances and is also controlled by a wider range of climatic features. Distance is not a limiting factor for ‘core' species, suggesting that they have a stronger dispersal ability even over large distances. This is probably related to the existence of passive long-distance dispersal of individuals along rivers via vegetation rafts. In this sense, Amazonian rivers can facilitate dispersal, and this effect should be stronger for species associated with riverine habitats such as floating meadows.
Earth observation (EO) is a prerequisite for sustainable land use management, and the open-data Landsat mission is at the forefront of this development. However, increasing data volumes have led to a "digital-divide", and consequently, it is key to develop methods that account for the most data-intensive processing steps, then used for the generation and provision of analysis-ready, standardized, higher-level (Level 2 and Level 3) baseline products for enhanced uptake in environmental monitoring systems. Accordingly, the overarching research task of this dissertation was to develop such a framework with a special emphasis on the yet under-researched drylands of Southern Africa. A fully automatic and memory-resident radiometric preprocessing streamline (Level 2) was implemented. The method was applied to the complete Angolan, Zambian, Zimbabwean, Botswanan, and Namibian Landsat record, amounting 58,731 images with a total data volume of nearly 15 TB. Cloud/shadow detection capabilities were improved for drylands. An integrated correction of atmospheric, topographic and bidirectional effects was implemented, based on radiative theory with corrections for multiple scatterings, and adjacency effects, as well as including a multilayered toolset for estimating aerosol optical depth over persistent dark targets or by falling back on a spatio-temporal climatology. Topographic and bidirectional effects were reduced with a semi-empirical C-correction and a global set of correction parameters, respectively. Gridding and reprojection were already included to facilitate easy and efficient further processing. The selection of phenologically similar observations is a key monitoring requirement for multi-temporal analyses, and hence, the generation of Level 3 products that realize phenological normalization on the pixel-level was pursued. As a prerequisite, coarse resolution Land Surface Phenology (LSP) was derived in a first step, then spatially refined by fusing it with a small number of Level 2 images. For this purpose, a novel data fusion technique was developed, wherein a focal filter based approach employs multi-scale and source prediction proxies. Phenologically normalized composites (Level 3) were generated by coupling the target day (i.e. the main compositing criterion) to the input LSP. The approach was demonstrated by generating peak, end and minimum of season composites, and by comparing these with static composites (fixed target day). It was shown that the phenological normalization accounts for terrain- and land cover class-induced LSP differences, and the use of Level 2 inputs enables a wide range of monitoring options, among them the detection of within state processes like forest degradation. In summary, the developed preprocessing framework is capable of generating several analysis-ready baseline EO satellite products. These datasets can be used for regional case studies, but may also be directly integrated into more operational monitoring systems " e.g. in support of the Reducing Emissions from Deforestation and Forest Degradation (REDD) incentive. In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of Trier University's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink.
Das erste Kapitel "ECOWAS" capability and potential to overcome constraints to growth and poverty reduction of its member states" diskutiert die Analyse wirtschaftlicher und sozialer Barrieren für ökonomisches Wachstum " eine der Hauptelemente für Entwicklungs- und Armutsreduktionsstrategien in Entwicklungsländern. Die Form der länderspezifischen Analyse von Wachstumsbarrieren wurde nach dem Scheitern der auf alle Länder generalisierten Entwicklungsstrategie des Washington Consensus insbesondere durch den Ansatz der "Growth Diagnostics" der Harvard Professoren Hausman, Rodrik und Velasco eingeführt. Es zeigt sich jedoch, dass bisher der Fokus rein auf den länderspezifischen Analysen bzw. Strategieentwicklungen liegt. Diese Arbeit erweiterte die Diskussion auf die regionale Ebene, indem es beispielhaft an der Economic Community of West African States (ECOWAS) die länderspezifischen Wachstumsbarrieren mit den regionalen Wachstumsbarrieren vergleicht. Dies erfolgt mittels einer Darstellung der in Studien und Strategien bereits identifizierten, länderspezifischen Wachstumsbarrieren in den jeweiligen Ländern sowie mit der Auswertung der regionalen Strategien der ECOWAS. Dazu wird ermittelt, inwieweit auf der regionalen Ebene auch messbare Ergebnisse bei der Bekämpfung von Wachstumsbarrieren erzielt werden. Es zeigt sich, dass ,trotz der wirtschaftlichen und sozialen Diversität der Region, die ECOWAS den Großteil der in den Ländern identifizierten Wachstumsbarrieren ebenfalls auflistet und darüber hinaus sogar mit messbaren Ergebnissen dazu beiträgt, Veränderungen des Status Quo zu erreichen. Die Erweiterung des Ansatzes der Growth Diagnostics auf die regionale Ebene sowie die Erweiterung um das vergleichende Element von länderspezifischen und regionalen Wachstumsbarrieren zeigen sich als praktikabler Weg, Entwicklungsstrategien auf regionaler Ebene zu prüfen und subsidiär weiterzuentwickeln. Das zweite Kapitel "Simplifying evaluation of potential causalities in development projects using Qualitative Comparative Analysis (QCA)" diskutiert die Methode der qualitativen komperativen Analyse (QCA) als Evaluierungsmethodik für Projekte der Entwicklungszusammenarbeit. Hierbei stehen die adäquate Messung sowie die verständliche Darstellung der Wirkung von Entwicklungszusammenarbeit im Vordergrund. Dies ist ein Beitrag zu der intensiv geführten Diskussion, wie Wirkung von Hilfe in Entwicklungsländern gemessen und daraus für weitere Projekte gelernt werden kann. Mit der beispielhaften Anwendung der QCA auf einen Datensatz der deutschen Entwicklungszusammenarbeit im Senegal wird erstmalig diese Methode für die Entwicklungszusammenarbeit in der Praxis angewandt. Der Fokus liegt dabei auf der Überprüfung von bestimmten Programmtheorien, d.h. der Annahme bestimmter Zusammenhänge zwischen eingesetzten Mitteln, äußeren Umständen und den Projektergebnissen bei der Implementierung von Projekten. Während solche Programmtheorien in dem Großteil der Projektskizzen der deutschen Entwicklungszusammenarbeit enthalten sind, werden die wenigsten dieser Programmtheorien geprüft. Diese Arbeit zeigt QCA als eine effiziente Methode für diese Überprüfung. Eine eindeutige Bestätigung oder Falsifizierung dieser Theorien ist mittels dieser Methodik möglich. Dazu können die Ergebnisse bei den beiden einfacheren Formen der QCA, der crisp-set sowie der multi-value QCA, leicht nachvollziehbar vermittelt werden. Des Weiteren zeigt die Arbeit, dass QCA ebenfalls die Weiterentwicklung einer Programmtheorie ermöglicht, allerdings ist diese Weiterentwicklung nur begrenzt effizient und stark von den vorliegenden Daten sowie der Datenstruktur abhängig. Die Arbeit zeigt somit das Potential der QCA insbesondere für den Test von Programmtheorien auf und stellt die praktische Anwendung für mögliche Replizierung beispielhaft dar. Das dritte und letzte Kapitel der Doktorarbeit "The regional trade dynamics of Turkey: a panel data gravity model" analysiert den türkischen Handel, um die Veränderungen der letzten Jahrzehnte aufzuzeigen und daran zu diskutieren, inwieweit sich die Türkei als aufstrebendes Schwellenland von den bestehenden Handelsstrukturen loslöst. Diese Arbeit ist ein Beitrag zur Diskussion der sich Verschiebenden Machtkonstellationen durch das wirtschaftliche Aufholen der Schwellenländer. Bei der Türkei ist diese Diskussion zusätzlich interessant, da die Frage, ob die Türkei sich von der westlichen Welt, Nordamerika und Europa, abwendet, berücksichtigt wird. Mittels Dummy-Variablen für verschiedene Regionen in einem Gravitätsmodell werden die türkischen Handelsdaten zuerst insgesamt und nach Sektoren analysiert und die Veränderungen über verschieden Perioden des türkischen Außenhandels betrachtet. Es zeigt sich, dass in den türkischen Handelsbeziehungen eine Regionalisierung und eine Diversifizierung der Handelspartner stattfinden. Allerdings geht dies nicht mit einer Abkehr von westlichen Handelspartnern einher.
Both water scarcity and flood risk are increasingly turning into safety concerns for many urban dwellers and, consequently, become increasingly politicised. This development involves a reconfiguration of the academic land- scape around urban risk, vulnerability and adaptation to climate change research. This paper is a literature assessment of concepts on disaster risk, vulnerability and adaptation and their applicability to the context of studying water in an African city. An overview on water-related risk in African cities is presented and concepts and respective disciplinary backgrounds reviewed. Recent debates that have emerged from the application of risk, vulnerability and adaptation concepts in research and policy practice are presented. Finally the applicability of these concepts as well as the relevance and implications of recent debates for studying water in African cities is discussed. ‘Riskscape’ is proposed as a conceptual frame for close and integrated analysis of water related risk in an African city.
GIS – what can and what can’t it say about social relations in adaptation to urban flood risk?
(2017)
Urban flooding cannot be avoided entirely and in all areas, particularly in coastal cities. Therefore adaptation to the growing risk is necessary. Geographical Information Systems (GIS) based knowledge on risk informs location-based approach to adaptation to climate risk. It allows managing city- wide coordination of adaptation measures, reducing adverse impacts of local strategies on neighbouring areas to the minimum. Quantitative assessments dominate GIS applications in flood risk management, for instance to demonstrate the distribution of people and assets in a flood prone area. Qualitative, participatory approaches to GIS are on the rise but have not been applied in the context of flooding yet. The overarching research question of this working paper is: what can GIS, and what can it not say about relationships / social relations in adaptation to urban flood risk? The use of GIS in risk mapping has exposed environmental injustices. Applications of GIS further allow model- ling future flood risk in function of demographic and land use changes, and combining it with decision support systems (DSS). While such GIS applications provide invaluable information for urban planners steering adaptation they however fall short on revealing the social relations that shape individual and household adaptation decisions. The relevance of networked social relations in adaptation to flood risk has been demonstrated in case studies, and extensively in the literature on organizational learning and adaptation to change. The purpose of this literature review is to identify the type of social relations that shape adaptive capacities towards urban flood risk which can- not be identified in a conventional GIS application.
The present dissertation was developed to emphasize the importance of self-regulatory abilities and to derive novel opportunities to empower self-regulation. From the perspective of PSI (Personality Systems Interactions) theory (Kuhl, 2001), interindividual differences in self-regulation (action vs. state orientation) and their underlying mechanisms are examined in detail. Based on these insights, target-oriented interventions are derived, developed, and scientifically evaluated. The present work comprises a total of four studies which, on the one hand, highlight the advantages of a good self-regulation (e.g., enacting difficult intentions under demands; relation with prosocial power motive enactment and well-being). On the other hand, mental contrasting (Oettingen et al., 2001), an established self-regulation method, is examined from a PSI perspective and evaluated as a method to support individuals that struggle with self-regulatory deficits. Further, derived from PSI theory`s assumptions, I developed and evaluated a novel method (affective shifting) that aims to support individuals in overcoming self-regulatory deficits. Thereby affective shifting supports the decisive changes in positive affect for successful intention enactment (Baumann & Scheffer, 2010). The results of the present dissertation show that self-regulated changes between high and low positive affect are crucial for efficient intention enactment and that methods such as mental contrasting and affective shifting can empower self-regulation to support individuals to successfully close the gap between intention and action.
The benefits of prosocial power motivation in leadership: Action orientation fosters a win-win
(2023)
Power motivation is considered a key component of successful leadership. Based on its dualistic nature, the need for power (nPower) can be expressed in a dominant or a prosocial manner. Whereas dominant motivation is associated with antisocial behaviors, prosocial motivation is characterized by more benevolent actions (e.g., helping, guiding). Prosocial enactment of the power motive has been linked to a wide range of beneficial outcomes, yet less has been investigated what determines a prosocial enactment of the power motive. According to Personality Systems Interactions (PSI) theory, action orientation (i.e., the ability to self-regulate affect) promotes prosocial enactment of the implicit power motive and initial findings within student samples verify this assumption. In the present study, we verified the role of action orientation as an antecedent for prosocial power enactment in a leadership sample (N = 383). Additionally, we found that leaders personally benefited from a prosocial enactment strategy. Results show that action orientation through prosocial power motivation leads to reduced power-related anxiety and, in turn, to greater leader well-being. The integration of motivation and self-regulation research reveals why leaders enact their power motive in a certain way and helps to understand how to establish a win-win situation for both followers and leaders.
A lack of ability to inhibit prepotent responses, or more generally a lack of impulse control, is associated with several disorders such as attention-deficit/hyperactivity disorder and schizophrenia as well as general damage to the prefrontal cortex. A stop-signal task (SST) is a reliable and established measure of response inhibition. However, using the SST as an objective assessment in diagnostic or research-focused settings places significant stress on participants as the task itself requires concentration and cognitive effort and is not particularly engaging. This can lead to decreased motivation to follow task instructions and poor data quality, which can affect assessment efficacy and might increase drop-out rates. Gamification—the application of game-based elements in nongame settings—has shown to improve engaged attention to a cognitive task, thus increasing participant motivation and data quality.
We examined the long-term relationship of psychosocial risk and health behaviors on clinical events in patients awaiting heart transplantation (HTx). Psychosocial characteristics (e.g., depression), health behaviors (e.g., dietary habits, smoking), medical factors (e.g., creatinine), and demographics (e.g., age, sex) were collected at the time of listing in 318 patients (82% male, mean age = 53 years) enrolled in the Waiting for a New Heart Study. Clinical events were death/delisting due to deterioration, high-urgency status transplantation (HU-HTx), elective transplantation, and delisting due to clinical improvement. Within 7 years of follow-up, 92 patients died or were delisted due to deterioration, 121 received HU-HTx, 43 received elective transplantation, and 39 were delisted due to improvement. Adjusting for demographic and medical characteristics, the results indicated that frequent consumption of healthy foods (i.e., foods high in unsaturated fats) and being physically active increased the likelihood of delisting due improvement, while smoking and depressive symptoms were related to death/delisting due to clinical deterioration while awaiting HTx. In conclusion, psychosocial and behavioral characteristics are clearly associated with clinical outcomes in this population. Interventions that target psychosocial risk, smoking, dietary habits, and physical activity may be beneficial for patients with advanced heart failure waiting for a cardiac transplant.
Data used for the purpose of machine learning are often erroneous. In this thesis, p-quasinorms (p<1) are employed as loss functions in order to increase the robustness of training algorithms for artificial neural networks. Numerical issues arising from these loss functions are addressed via enhanced optimization algorithms (proximal point methods; Frank-Wolfe methods) based on the (non-monotonic) Armijo-rule. Numerical experiments comprising 1100 test problems confirm the effectiveness of the approach. Depending on the parametrization, an average reduction of the absolute residuals of up to 64.6% is achieved (aggregated over 100 test problems).
Optimal mental workload plays a key role in driving performance. Thus, driver-assisting systems that automatically adapt to a drivers current mental workload via brain–computer interfacing might greatly contribute to traffic safety. To design economic brain computer interfaces that do not compromise driver comfort, it is necessary to identify brain areas that are most sensitive to mental workload changes. In this study, we used functional near-infrared spectroscopy and subjective ratings to measure mental workload in two virtual driving environments with distinct demands. We found that demanding city environments induced both higher subjective workload ratings as well as higher bilateral middle frontal gyrus activation than less demanding country environments. A further analysis with higher spatial resolution revealed a center of activation in the right anterior dorsolateral prefrontal cortex. The area is highly involved in spatial working memory processing. Thus, a main component of drivers’ mental workload in complex surroundings might stem from the fact that large amounts of spatial information about the course of the road as well as other road users has to constantly be upheld, processed and updated. We propose that the right middle frontal gyrus might be a suitable region for the application of powerful small-area brain computer interfaces.
In addition to flood disasters on major rivers, damage caused by the flooding of smaller and medium-sized tributaries is also of considerable significance. To ensure that flood protection measures are effective, engineering flood prevention measures on the rivers must be supported by integrated catchment management. This includes decentralised water retention measures implemented in the sectors of forestry, agriculture and in residential areas. Within this scope new instruments have to be elaborated and introduced, such as GIS-based systems and systems for the evaluation of economic consequences and eco-efficiency of flood damage precaution measures associated with land-use. These are extremely significant for improving information management, the prevention of advice to the general public and for the acceptance of flood precaution measures. The conference intends to promote scientific exchange between specialists working on all areas concerning integrated catchment management. This includes the methodology for identification of catchment types prone to flooding hazards, the control and validation of land-use concepts for decentralised water retention as well as its combination and upscaling procedures up to mesoscale catchments. As catchment management is not only the concern of natural scientists the strategies for enhancing catchment management and the development of decision-support tools will also be important topics of the conference. ***Addenda *1. The articles from page 136 to 161 belong to session 5 *2. Article page 107: Ancient irrigation strategies: land use and hazard mitigation in Ma-´rib, Yemen (New list of authors: Ueli Brunner (a) , Michael Schütz (b), Dana Pietsch (c), Peter Kühn (c), Thomas Scholten (c), Iris Gerlach (d))
My dissertation is concerned with contemporary (Anglo-)Canadian immigrant fiction and proposes an analytic grid with which it may be appreciated and compared more adequately. As a starting-point serves the general observation that the works of many Canadian immigrant writers are characterised by a focus on their respective home cultures as well as on their Canadian host culture. Following the ground-breaking work of Northrop Frye, Margaret Atwood and David Staines, the categories of "there" and "here" are suggested in order to reflect this double encoding of Canadian immigrant literature. However, "here" and "there" are more than spatial configurations in that they represent a concern with issues of multiculturalism and postcolonialism. Both of which are informed by an emphasis on difference and identity, and difference and identity are also what the narratives of M.G. Vassanji, Neil Bissoondath and Rohinton Mistry are preoccupied with. My study sets out to show two things: On the one hand, it attempts to exemplify the complexity and interrelatedness of "there" and "here" in a representative fashion. Hence in their treatments of difference, M.G. Vassanji, Neil Bissoondath and Rohinton Mistry come up with comparable identity constructions "here" and "there" respectively. On the other hand, special attention is paid to the strategies by which Vassanji, Bissoondath and Mistry construct difference and corroborate their respective understandings of identity.
Because EU water quality policy can result in infrastructure creation or adaptation at the local level across member states, compliance cases are worth examining critically from a sustainable spatial planning perspective. In this study, the 2000 EU Water Framework Directive’s (WFD) reach to local implementation efforts in average towns and cities is shown through the case study of nonconforming household wastewater infrastructure in the German state of Rhineland Palatinate. Seeing wastewater as a socio-technical infrastructure, we ask how the WFD implementation can be understood in the context of local infrastructure development, sustainability, and spatial planning concepts. In particular, this study examines what compliance meant for the centralization or decentralization of local wastewater infrastructure systems—and the sustainability implications for cities
from those choices.
During pregnancy every eighth woman is treated with glucocorticoids. Glucocorticoids inhibit cell division but are assumed to accelerate the differentiation of cells. In this review animal models for the development of the human fetal and neonatal hypothalamic-pituitary-adrenal (HPA) axis are investigated. It is possible to show that during pregnancy in humans, as in most of the here-investigated animal models, a stress hyporesponsive period (SHRP) is present. In this period, the fetus is facing reduced glucocorticoid concentrations, by low or absent fetal glucocorticoid synthesis and by reduced exposure to maternal glucocorticoids. During that phase, sensitive maturational processes in the brain are assumed, which could be inhibited by high glucocorticoid concentrations. In the SHRP, species-specific maximal brain growth spurt and neurogenesis of the somatosensory cortex take place. The latter is critical for the development of social and communication skills and the secure attachment of mother and child. Glucocorticoid treatment during pregnancy needs to be further investigated especially during this vulnerable SHRP. The hypothalamus and the pituitary stimulate the adrenal glucocorticoid production. On the other hand, glucocorticoids can inhibit the synthesis of corticotropin-releasing hormone (CRH) in the hypothalamus and of adrenocorticotropic hormone (ACTH) in the pituitary. Alterations in this negative feedback are assumed among others in the development of fibromyalgia, diabetes and factors of the metabolic syndrome. In this work it is shown that the fetal cortisol surge at the end of gestation is at least partially due to reduced glucocorticoid negative feedback. It is also assumed that androgens are involved in the control of fetal glucocorticoid synthesis. Glucocorticoids seem to prevent masculinization of the female fetus by androgens during the sexual gonadal development. In this work a negative interaction of glucocorticoids and androgens is detectable.
Water-deficit stress, usually shortened to water- or drought stress, is one of the most critical abiotic stressors limiting plant growth, crop yield and quality concerning food production. Today, agriculture consumes about 80-90% of the global freshwater used by humans and about two thirds are used for crop irrigation. An increasing world population and a predicted rise of 1.0-2.5-°C in the annual mean global temperature as a result of climate change will further increase the demand of water in agriculture. Therefore, one of the most challenging tasks of our generation is to reduce the amount water used per unit yield to satisfy the second UN Sustainable Development Goal and to ensure global food security. Precision agriculture offers new farming methods with the goal to improve the efficiency of crop production by a sustainable use of resources. Plant responses to water stress are complex and co-occur with other environmental stresses under natural conditions. In general, water stress causes plant physiological and biochemical changes that depend on the severity and the duration of the actual plant water deficit. Stomatal closure is one of the first responses to plant water stress causing a decrease in plant transpiration and thus an increase in plant temperature. Prolonged or severe water stress leads to irreversible damage to the photosynthetic machinery and is associated with decreasing chlorophyll content and leaf structural changes (e.g., leaf rolling). Since a crop can already be irreversibly damaged by only mild water deficit, a pre-visual detection of water stress symptoms is essential to avoid yield loss. Remote sensing offers a non-destructive and spatio-temporal method for measuring numerous physiological, biochemical and structural crop characteristics at different scales and thus is one of the key technologies used in precision agriculture. With respect to the detection of plant responses to water stress, the current state-of-the-art hyperspectral remote sensing imaging techniques are based on measurements of thermal infrared emission (TIR; 8-14 -µm), visible, near- and shortwave infrared reflectance (VNIR/SWIR; 0.4-2.5 -µm), and sun-induced fluorescence (SIF; 0.69 and 0.76 -µm). It is, however, still unclear how sensitive these techniques are with respect to water stress detection. Therefore, the overall aim of this dissertation was to provide a comparative assessment of remotely sensed measures from the TIR, SIF, and VNIR/SWIR domains for their ability to detect plant responses to water stress at ground- and airborne level. The main findings of this thesis are: (i) temperature-based indices (e.g., CWSI) were most sensitive for the detection of plant water stress in comparison to reflectance-based VNIR/SWIR indices (e.g., PRI) and SIF at both, ground- and airborne level, (ii) for the first time, spectral emissivity as measured by the new hyperspectral TIR instrument could be used to detect plant water stress at ground level. Based on these findings it can be stated that hyperspectral TIR remote sensing offers great potential for the detection of plant responses to water stress at ground- and airborne level based on both TIR key variables, surface temperature and spectral emissivity. However, the large-scale application of water stress detection based on hyperspectral TIR measures in precision agriculture will be challenged by several problems: (i) missing thresholds of temperature-based indices (e.g., CWSI) for the application in irrigation scheduling, (ii) lack of current TIR satellite missions with suitable spectral and spatial resolution, (iii) lack of appropriate data processing schemes (including atmosphere correction and temperature emissivity separation) for hyperspectral TIR remote sensing at airborne- and satellite level.
Abstract: Thermal infrared (TIR) multi-/hyperspectral and sun-induced fluorescence (SIF) approaches together with classic solar-reflective (visible, near-, and shortwave infrared reflectance (VNIR)/SWIR) hyperspectral remote sensing form the latest state-of-the-art techniques for the detection of crop water stress. Each of these three domains requires dedicated sensor technology currently in place for ground and airborne applications and either have satellite concepts under development (e.g., HySPIRI/SBG (Surface Biology and Geology), Sentinel-8, HiTeSEM in the TIR) or are subject to satellite missions recently launched or scheduled within the next years (i.e., EnMAP and PRISMA (PRecursore IperSpettrale della Missione Applicativa, launched on March 2019) in the VNIR/SWIR, Fluorescence Explorer (FLEX) in the SIF). Identification of plant water stress or drought is of utmost importance to guarantee global water and food supply. Therefore, knowledge of crop water status over large farmland areas bears large potential for optimizing agricultural water use. As plant responses to water stress are numerous and complex, their physiological consequences affect the electromagnetic signal in different spectral domains. This review paper summarizes the importance of water stress-related applications and the plant responses to water stress, followed by a concise review of water-stress detection through remote sensing, focusing on TIR without neglecting the comparison to other spectral domains (i.e., VNIR/SWIR and SIF) and multi-sensor approaches. Current and planned sensors at ground, airborne, and satellite level for the TIR as well as a selection of commonly used indices and approaches for water-stress detection using the main multi-/hyperspectral remote sensing imaging techniques are reviewed. Several important challenges are discussed that occur when using spectral emissivity, temperature-based indices, and physically-based approaches for water-stress detection in the TIR spectral domain. Furthermore, challenges with data processing and the perspectives for future satellite missions in the TIR are critically examined. In conclusion, information from multi-/hyperspectral TIR together with those from VNIR/SWIR and SIF sensors within a multi-sensor approach can provide profound insights to actual plant (water) status and the rationale of physiological and biochemical changes. Synergistic sensor use will open new avenues for scientists to study plant functioning and the response to environmental stress in a wide range of ecosystems.
Agricultural monitoring is necessary. Since the beginning of the Holocene, human agricultural
practices have been shaping the face of the earth, and today around one third of the ice-free land
mass consists of cropland and pastures. While agriculture is necessary for our survival, the
intensity has caused many negative externalities, such as enormous freshwater consumption, the
loss of forests and biodiversity, greenhouse gas emissions as well as soil erosion and degradation.
Some of these externalities can potentially be ameliorated by careful allocation of crops and
cropping practices, while at the same time the state of these crops has to be monitored in order
to assess food security. Modern day satellite-based earth observation can be an adequate tool to
quantify abundance of crop types, i.e., produce spatially explicit crop type maps. The resources to
do so, in terms of input data, reference data and classification algorithms have been constantly
improving over the past 60 years, and we live now in a time where fully operational satellites
produce freely available imagery with often less than monthly revisit times at high spatial
resolution. At the same time, classification models have been constantly evolving from
distribution based statistical algorithms, over machine learning to the now ubiquitous deep
learning.
In this environment, we used an explorative approach to advance the state of the art of crop
classification. We conducted regional case studies, focused on the study region of the Eifelkreis
Bitburg-Prüm, aiming to develop validated crop classification toolchains. Because of their unique
role in the regional agricultural system and because of their specific phenologic characteristics
we focused solely on maize fields.
In the first case study, we generated reference data for the years 2009 and 2016 in the study
region by drawing polygons based on high resolution aerial imagery, and used these in
conjunction with RapidEye imagery to produce high resolution maize maps with a random forest
classifier and a gaussian blur filter. We were able to highlight the importance of careful residual
analysis, especially in terms of autocorrelation. As an end result, we were able to prove that, in
spite of the severe limitations introduced by the restricted acquisition windows due to cloud
coverage, high quality maps could be produced for two years, and the regional development of
maize cultivation could be quantified.
In the second case study, we used these spatially explicit datasets to link the expansion of biogas
producing units with the extended maize cultivation in the area. In a next step, we overlayed the
maize maps with soil and slope rasters in order to assess spatially explicit risks of soil compaction
and erosion. Thus, we were able to highlight the potential role of remote sensing-based crop type
classification in environmental protection, by producing maps of potential soil hazards, which can
be used by local stakeholders to reallocate certain crop types to locations with less associated
risk.
In our third case study, we used Sentinel-1 data as input imagery, and official statistical records
as maize reference data, and were able to produce consistent modeling input data for four
consecutive years. Using these datasets, we could train and validate different models in spatially
iv
and temporally independent random subsets, with the goal of assessing model transferability. We
were able to show that state-of-the-art deep learning models such as UNET performed
significantly superior to conventional models like random forests, if the model was validated in a
different year or a different regional subset. We highlighted and discussed the implications on
modeling robustness, and the potential usefulness of deep learning models in building fully
operational global crop classification models.
We were able to conclude that the first major barrier for global classification models is the
reference data. Since most research in this area is still conducted with local field surveys, and only
few countries have access to official agricultural records, more global cooperation is necessary to
build harmonized and regionally stratified datasets. The second major barrier is the classification
algorithm. While a lot of progress has been made in this area, the current trend of many appearing
new types of deep learning models shows great promise, but has not yet consolidated. There is
still a lot of research necessary, to determine which models perform the best and most robust,
and are at the same time transparent and usable by non-experts such that they can be applied
and used effortlessly by local and global stakeholders.
In order to discuss potential sustainability issues of expanding silage maize cultivation in Rhineland-Palatinate, spatially explicit monitoring is necessary. Publicly available statistical records are often not a sufficient basis for extensive research, especially on soil health, where risk factors like erosion and compaction depend on variables that are specific to every site, and hard to generalize for larger administrative aggregates. The focus of this study is to apply established classification algorithms to estimate maize abundance for each independent pixel, while at the same time accounting for their spatial relationship. Therefore, two ways to incorporate spatial autocorrelation of neighboring pixels are combined with three different classification models. The performance of each of these modeling approaches is analyzed and discussed. Finally, one prediction approach is applied to the imagery, and the overall predicted acreage is compared to publicly available data. We were able to show that Support Vector Machine (SVM) classification and Random Forests (RF) were able to distinguish maize pixels reliably, with kappa values well above 0.9 in most cases. The Generalized Linear Model (GLM) performed substantially worse. Furthermore, Regression Kriging (RK) as an approach to integrate spatial autocorrelation into the prediction model is not suitable in use cases with millions of sparsely clustered training pixels. Gaussian Blur is able to improve predictions slightly in these cases, but it is possible that this is only because it smoothes out impurities of the reference data. The overall prediction with RF classification combined with Gaussian Blur performed well, with out of bag error rates of 0.5% in 2009 and 1.3% in 2016. Despite the low error rates, there is a discrepancy between the predicted acreage and the official records, which is 20% in 2009 and 27% in 2016.
With the ongoing trend towards deep learning in the remote sensing community, classical pixel based algorithms are often outperformed by convolution based image segmentation algorithms. This performance was mostly validated spatially, by splitting training and validation pixels for a given year. Though generalizing models temporally is potentially more difficult, it has been a recent trend to transfer models from one year to another, and therefore to validate temporally. The study argues that it is always important to check both, in order to generate models that are useful beyond the scope of the training data. It shows that convolutional neural networks have potential to generalize better than pixel based models, since they do not rely on phenological development alone, but can also consider object geometry and texture. The UNET classifier was able to achieve the highest F1 scores, averaging 0.61 in temporal validation samples, and 0.77 in spatial validation samples. The theoretical potential for overfitting geometry and just memorizing the shape of fields that are maize has been shown to be insignificant in practical applications. In conclusion, kernel based convolutions can offer a large contribution in making agricultural classification models more transferable, both to other regions and to other years.
Floods are hydrological extremes that have enormous environmental, social and economic consequences.The objective of this thesis was a contribution to the implementation of a processing chain that integrates remote sensing information into hydraulic models. Specifically, the aim was to improve water elevation and discharge simulations by assimilating microwave remote sensing-derived flood information into hydraulic models. The first component of the proposed processing chain is represented by a fully automated flood mapping algorithm that enables the automated, objective, and reliable flood extent extraction from Synthetic Aperture Radar images, providing accurate results in both rural and urban regions. The method operates with minimum data requirements and is efficient in terms of computational time. The map obtained with the developed algorithm is still subject to uncertainties, both introduced by the flood mapping algorithm and inherent in the image itself. In this work, particular attention was given to image uncertainty deriving from speckle. By bootstrapping the original satellite image pixels, several synthetic images were generated and provided as input to the developed flood mapping algorithm. From the analysis performed on the mapping products, speckle uncertainty can be considered as a negligible component of the total uncertainty. In the final step of the proposed processing chain real event water elevations, obtained from satellite observations, were assimilated in a hydraulic model with an adapted version of the Particle Filter, modified to work with non-Gaussian distribution of observations. To deal with model structure error and possibly biased observations, a global and a local weight variant of the Particle Filter were tested. The variant to be preferred depends on the level of confidence that is attributed to the observations or to the model. This study also highlighted the complementarity of remote sensing derived and in-situ data sets. An accurate binary flood map represents an invaluable product for different end users. However, deriving from this binary map additional hydraulic information, such as water elevations, is a way of enhancing the value of the product itself. The derived data can be assimilated into hydraulic models that will fill the gaps where, for technical reasons, Earth Observation data cannot provide information, also enabling a more accurate and reliable prediction of flooded areas.
Even though in most cases time is a good metric to measure costs of algorithms, there are cases where theoretical worst-case time and experimental running time do not match. Since modern CPUs feature an innate memory hierarchy, the location of data is another factor to consider. When most operations of an algorithm are executed on data which is already in the CPU cache, the running time is significantly faster than algorithms where most operations have to load the data from the memory. The topic of this thesis is a new metric to measure costs of algorithms called memory distance—which can be seen as an abstraction of the just mentioned aspect. We will show that there are simple algorithms which show a discrepancy between measured running time and theoretical time but not between measured time and memory distance. Moreover we will show that in some cases it is sufficient to optimize the input of an algorithm with regard to memory distance (while treating the algorithm as a black box) to improve running times. Further we show the relation between worst-case time, memory distance and space and sketch how to define "the usual" memory distance complexity classes.
For grape canopy pixels captured by an unmanned aerial vehicle (UAV) tilt-mounted RedEdge-M multispectral sensor in a sloped vineyard, an in situ Walthall model can be established with purely image-based methods. This was derived from RedEdge-M directional reflectance and a vineyard 3D surface model generated from the same imagery. The model was used to correct the angular effects in the reflectance images to form normalized difference vegetation index (NDVI)orthomosaics of different view angles. The results showed that the effect could be corrected to a certain scope, but not completely. There are three drawbacks that might restrict a successful angular model construction and correction: (1) the observable micro shadow variation on the canopy enabled by the high resolution; (2) the complexity of vine canopies that causes an inconsistency between reflectance and canopy geometry, including effects such as micro shadows and near-infrared (NIR) additive effects; and (3) the resolution limit of a 3D model to represent the accurate real-world optical geometry. The conclusion is that grape canopies might be too inhomogeneous for the tested method to perform the angular correction in high quality.
A matrix A is called completely positive if there exists an entrywise nonnegative matrix B such that A = BB^T. These matrices can be used to obtain convex reformulations of for example nonconvex quadratic or combinatorial problems. One of the main problems with completely positive matrices is checking whether a given matrix is completely positive. This is known to be NP-hard in general. rnrnFor a given matrix completely positive matrix A, it is nontrivial to find a cp-factorization A=BB^T with nonnegative B since this factorization would provide a certificate for the matrix to be completely positive. But this factorization is not only important for the membership to the completely positive cone, it can also be used to recover the solution of the underlying quadratic or combinatorial problem. In addition, it is not a priori known how many columns are necessary to generate a cp-factorization for the given matrix. The minimal possible number of columns is called the cp-rank of A and so far it is still an open question how to derive the cp-rank for a given matrix. Some facts on completely positive matrices and the cp-rank will be given in Chapter 2. Moreover, in Chapter 6, we will see a factorization algorithm, which, for a given completely positive matrix A and a suitable starting point, computes the nonnegative factorization A=BB^T. The algorithm therefore returns a certificate for the matrix to be completely positive. As introduced in Chapter 3, the fundamental idea of the factorization algorithm is to start from an initial square factorization which is not necessarily entrywise nonnegative, and extend this factorization to a matrix for which the number of columns is greater than or equal to the cp-rank of A. Then it is the goal to transform this generated factorization into a cp-factorization. This problem can be formulated as a nonconvex feasibility problem, as shown in Section 4.1, and solved by a method which is based on alternating projections, as proven in Chapter 6. On the topic of alternating projections, a survey will be given in Chapter 5. Here we will see how to apply this technique to several types of sets like subspaces, convex sets, manifolds and semialgebraic sets. Furthermore, we will see some known facts on the convergence rate for alternating projections between these types of sets. Considering more than two sets yields the so called cyclic projections approach. Here some known facts for subspaces and convex sets will be shown. Moreover, we will see a new convergence result on cyclic projections among a sequence of manifolds in Section 5.4. In the context of cp-factorizations, a local convergence result for the introduced algorithm will be given. This result is based on the known convergence for alternating projections between semialgebraic sets. To obtain cp-facrorizations with this first method, it is necessary to solve a second order cone problem in every projection step, which is very costly. Therefore, in Section 6.2, we will see an additional heuristic extension, which improves the numerical performance of the algorithm. Extensive numerical tests in Chapter 7 will show that the factorization method is very fast in most instances. In addition, we will see how to derive a certificate for the matrix to be an element of the interior of the completely positive cone. As a further application, this method can be extended to find a symmetric nonnegative matrix factorization, where we consider an additional low-rank constraint. Here again, the method to derive factorizations for completely positive matrices can be used, albeit with some further adjustments, introduced in Section 8.1. Moreover, we will see that even for the general case of deriving a nonnegative matrix factorization for a given rectangular matrix A, the key aspects of the completely positive factorization approach can be used. To this end, it becomes necessary to extend the idea of finding a completely positive factorization such that it can be used for rectangular matrices. This yields an applicable algorithm for nonnegative matrix factorization in Section 8.2. Numerical results for this approach will suggest that the presented algorithms and techniques to obtain completely positive matrix factorizations can be extended to general nonnegative factorization problems.
This thesis is divided into three main parts: The description of the calibration problem, the numerical solution of this problem and the connection to optimal stochastic control problems. Fitting model prices to given market prices leads to an abstract least squares formulation as calibration problem. The corresponding option price can be computed by solving a stochastic differential equation via the Monte-Carlo method which seems to be preferred by most practitioners. Due to the fact that the Monte-Carlo method is expensive in terms of computational effort and requires memory, more sophisticated stochastic predictor-corrector schemes are established in this thesis. The numerical advantage of these predictor-corrector schemes ispresented and discussed. The adjoint method is applied to the calibration. The theoretical advantage of the adjoint method is discussed in detail. It is shown that the computational effort of gradient calculation via the adjoint method is independent of the number of calibration parameters. Numerical results confirm the theoretical results and summarize the computational advantage of the adjoint method. Furthermore, provides the connection to optimal stochastic control problems is proven in this thesis.
Currently, new business models created in the sharing economy differ considerably and they differ in the formation of trust as well. If and how trust can be created is shown by a comparison of two examples which diverge in their founding philosophy. The chosen example of community-based economy, Community Supported Agriculture (CSA), no longer trusts the capitalist system and therefore distances itself and creates its own environment including a new business model. It is implemented within rather small groups where trust is created by personal relations and face-to-face communication. On the contrary, the example of a platform economy, the accommodation-provider company Airbnb, shows trust in the system and pushes technological innovations through the use of platform applications. It promotes trust and confidence in the progress of technology. For the conceptual analysis, the distinction between personal trust and system trust defined by Niklas Luhmann is adopted. The analysis describes two different modes of trust formation and how they push distrust or improve trust. Grounded on these analyses, assumptions on the process of trust formation within varying models of the sharing economy are formulated as well as a hypothesis about possible developments is introduced for further research.
Traditional workflow management systems support process participants in fulfilling business tasks through guidance along a predefined workflow model.
Flexibility has gained a lot of attention in recent decades through a shift from mass production to customization. Various approaches to workflow flexibility exist that either require extensive knowledge acquisition and modelling effort or an active intervention during execution and re-modelling of deviating behaviour. The pursuit of flexibility by deviation is to compensate both of these disadvantages through allowing alternative unforeseen execution paths at run time without demanding the process participant to adapt the workflow model. However, the implementation of this approach has been little researched so far.
This work proposes a novel approach to flexibility by deviation. The approach aims at supporting process participants during the execution of a workflow through suggesting work items based on predefined strategies or experiential knowledge even in case of deviations. The developed concepts combine two renowned methods from the field of artificial intelligence - constraint satisfaction problem solving with process-oriented case-based reasoning. This mainly consists of a constraint-based workflow engine in combination with a case-based deviation management. The declarative representation of workflows through constraints allows for implicit flexibility and a simple possibility to restore consistency in case of deviations. Furthermore, the combined model, integrating procedural with declarative structures through a transformation function, increases the capabilities for flexibility. For an adequate handling of deviations the methodology of case-based reasoning fits perfectly, through its approach that similar problems have similar solutions. Thus, previous made experiences are transferred to currently regarded problems, under the assumption that a similar deviation has been handled successfully in the past.
Necessary foundations from the field of workflow management with a focus on flexibility are presented first.
As formal foundation, a constraint-based workflow model was developed that allows for a declarative specification of foremost sequential dependencies of tasks. Procedural and declarative models can be combined in the approach, as a transformation function was specified that converts procedural workflow models to declarative constraints.
One main component of the approach is the constraint-based workflow engine that utilizes this declarative model as input for a constraint solving algorithm. This algorithm computes the worklist, which is proposed to the process participant during workflow execution. With predefined deviation handling strategies that determine how the constraint model is modified in order to restore consistency, the support is continuous even in case of deviations.
The second major component of the proposed approach constitutes the case-based deviation management, which aims at improving the support of process participants on the basis of experiential knowledge. For the retrieve phase, a sophisticated similarity measure was developed that integrates specific characteristics of deviating workflows and combines several sequence similarity measures. Two alternative methods for the reuse phase were developed, a null adaptation and a generative adaptation. The null adaptation simply proposes tasks from the most similar workflow as work items, whereas the generative adaptation modifies the constraint-based workflow model based on the most similar workflow in order to re-enable the constraint-based workflow engine to suggest work items.
The experimental evaluation of the approach consisted of a simulation of several types of process participants in the exemplary domain of deficiency management in construction. The results showed high utility values and a promising potential for an investigation of the transfer on other domains and the applicability in practice, which is part of future work.
Concluding, the contributions are summarized and research perspectives are pointed out.