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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.
In dieser Arbeit untersuchen wir das Optimierungsproblem der optimalen Materialausrichtung orthotroper Materialien in der Hülle von dreidimensionalen Schalenkonstruktionen. Ziel der Optimierung ist dabei die Minimierung der Gesamtnachgiebigkeit der Konstruktion, was der Suche nach einem möglichst steifen Design entspricht. Sowohl die mathematischen als auch die mechanischen Grundlagen werden in kompakter Form zusammengetragen und basierend darauf werden sowohl gradientenbasierte als auch auf mechanischen Prinzipien beruhende, neue Erweiterungen punktweise formulierter Optimierungsverfahren entwickelt und implementiert. Die vorgestellten Verfahren werden anhand des Beispiels des Modells einer Flugzeugtragfläche mit praxisrelevanter Problemgröße getestet und verglichen. Schließlich werden die untersuchten Methoden in ihrer Koppelung mit einem Verfahren zur Topologieoptimierung, basierend auf dem topologischen Gradienten untersucht.
Monetary Policy During Times of Crisis - Frictions and Non-Linearities in the Transmission Mechanism
(2017)
For a long time it was believed that monetary policy would be able to maintain price stability and foster economic growth during all phases of the business cycle. The era of the Great Moderation, often also called the Volcker-Greenspan period, beginning in the mid 1980s was characterized by a decline in volatility of output growth and inflation among the industrialized countries. The term itself is first used by Stock and Watson (2003). Economist have long studied what triggered the decline in volatility and pointed out several main factors. An important research strand points out structural changes in the economy, such as a decline of volatility in the goods producing sector through better inventory controls and developments in the financial sector and government spending (McConnell2000, Blanchard2001, Stock2003, Kim2004, Davis2008). While many believed that monetary policy was only 'lucky' in terms of their reaction towards inflation and exogenous shocks (Stock2003, Primiceri2005, Sims2006, Gambetti2008), others reveal a more complex picture of the story. Rule based monetary policy (Taylor1993) that incorporates inflation targeting (Svensson1999) has been identified as a major source of inflation stabilization by increasing transparency (Clarida2000, Davis2008, Benati2009, Coibion2011). Apart from that, the mechanics of monetary policy transmission have changed. Giannone et al. (2008) compare the pre-Great Moderation era with the Great Modertation and find that the economies reaction towards monetary shocks has decreased. This finding is supported by Boivin et al. (2011). Similar to this, Herrera and Pesavento (2009) show that monetary policy during the Volcker-Greenspan period was very effective in dampening the effects of exogenous oil price shocks on the economy, while this cannot be found for the period thereafter. Yet, the subprime crisis unexpectedly hit worldwide economies and ended the era of Great Moderation. Financial deregulation and innovation has given banks opportunities for excessive risk taking, weakened financial stability (Crotty2009, Calomiris2009) and led to the build-up of credit-driven asset price bubbles (SchularickTaylor2012). The Federal Reserve (FED), that was thought to be the omnipotent conductor of price stability and economic growth during the Great Moderation, failed at preventing a harsh crisis. Even more, it did intensify the bubble with low interest rates following the Dotcom crisis of the early 2000s and misjudged the impact of its interventions (Taylor2009, Obstfeld2009). New results give a more detailed explanation on the question of latitude for monetary policy raised by Bernanke and suggest the existence of non-linearities in the transmission of monetary policy. Weise (1999), Garcia and Schaller (2002), Lo and Piger (2005), Mishkin (2009), Neuenkirch (2013) and Jannsen et al. (2015) find that monetary policy is more potent during times of financial distress and recessions. Its effectiveness during 'normal times' is much weaker or even insignificant. This prompts the question if these non-linearities limit central banks ability to lean against bubbles and financial imbalances (White2009, Walsh2009, Boivin2010, Mishkin2011).
This dissertation looked at both design-based and model-based estimation for rare and clustered populations using the idea of the ACS design. The ACS design (Thompson, 2012, p. 319) starts with an initial sample that is selected by a probability sampling method. If any of the selected units meets a pre-specified condition, its neighboring units are added to the sample and observed. If any of the added units meets the pre-specified condition, its neighboring units are further added to the sample and observed. The procedure continues until there are no more units that meet the pre-specified condition. In this dissertation, the pre-specified condition is the detection of at least one animal in a selected unit. In the design-based estimation, three estimators were proposed under three specific design setting. The first design was stratified strip ACS design that is suitable for aerial or ship surveys. This was a case study in estimating population totals of African elephants. In this case, units/quadrant were observed only once during an aerial survey. The Des Raj estimator (Raj, 1956) was modified to obtain an unbiased estimate of the population total. The design was evaluated using simulated data with different levels of rarity and clusteredness. The design was also evaluated on real data of African elephants that was obtained from an aerial census conducted in parts of Kenya and Tanzania in October (dry season) 2013. In this study, the order in which the samples were observed was maintained. Re-ordering the samples by making use of the Murthy's estimator (Murthy, 1957) can produce more efficient estimates. Hence a possible extension of this study. The computation cost resulting from the n! permutations in the Murthy's estimator however, needs to be put into consideration. The second setting was when there exists an auxiliary variable that is negatively correlated with the study variable. The Murthy's estimator (Murthy, 1964) was modified. Situations when the modified estimator is preferable was given both in theory and simulations using simulated and two real data sets. The study variable for the real data sets was the distribution and counts of oryx and wildbeest. This was obtained from an aerial census that was conducted in parts of Kenya and Tanzania in October (dry season) 2013. Temperature was the auxiliary variable for two study variables. Temperature data was obtained from R package raster. The modified estimator provided more efficient estimates with lower bias compared to the original Murthy's estimator (Murthy, 1964). The modified estimator was also more efficient compared to the modified HH and the modified HT estimators of (Thompson, 2012, p. 319). In this study, one auxiliary variable is considered. A fruitful area for future research would be to incorporate multi-auxiliary information at the estimation phase of an ACS design. This could, in principle, be done by using for instance a multivariate extension of the product estimator (Singh, 1967) or by using the generalized regression estimator (Särndal et al., 1992). The third case under design-based estimation, studied the conjoint use of the stopping rule (Gattone and Di Battista, 2011) and the use of the without replacement of clusters (Dryver and Thompson, 2007). Each of these two methods was proposed to reduce the sampling cost though the use of the stopping rule results in biased estimates. Despite this bias, the new estimator resulted in higher efficiency gain in comparison to the without replacement of cluster design. It was also more efficient compared to the stratified design which is known to reduce final sample size when networks are truncated at stratum boundaries. The above evaluation was based on simulated and real data. The real data was the distribution and counts of hartebeest, elephants and oryx obtained in the same census as above. The bias attributed by the stopping rule has not been evaluated analytically. This may not be direct since the truncated network formed depends on the initial unit sampled (Gattone et al., 2016a). This and the order of the bias however, deserves further investigation as it may help in understanding the effect of the increase in the initial sample size together with the population characteristics on the efficiency of the proposed estimator. Chapter four modeled data that was obtained using the stratified strip ACS (as described in sub-section (3.1)). This was an extension of the model of Rapley and Welsh (2008) by modeling data that was obtained from a different design, the introduction of an auxiliary variable and the use of the without replacement of clusters mechanism. Ideally, model-based estimation does not depend on the design or rather how the sample was obtained. This is however, not the case if the design is informative; such as the ACS design. In this case, the procedure that was used to obtain the sample was incorporated in the model. Both model-based and design-based simulations were conducted using artificial and real data. The study and the auxiliary variable for the real data was the distribution and counts of elephants collected during an aerial census in parts of Kenya and Tanzania in October (dry season) and April (wet season) 2013 respectively. Areas of possible future research include predicting the population total of African elephants in all parks in Kenya. This can be achieved in an economical and reliable way by using the theory of SAE. Chapter five compared the different proposed strategies using the elephant data. Again the study variable was the elephant data from October (dry season) 2013 and the auxiliary variable was the elephant data from April (wet season) 2013. The results show that the choice of particular strategy to use depends on the characteristic of the population under study and the level and the direction of the correlation between the study and the auxiliary variable (if present). One general area of the ACS design that is still behind, is the implementation of the design in the field especially on animal populations. This is partly attributed by the challenges associated with the field implementation, some of which were discussed in section 2.3. Green et al. (2010) however, provides new insights in undertaking the ACS design during an aerial survey such as how the aircraft should turn while surveying neighboring units. A key point throughout the dissertation is the reduction of cost during a survey which can be seen by the reduction in the number of units in the final sample (through the use of stopping rule, use of stratification and truncating networks at stratum boundaries) and ensuring that units are observed only once (by using the without replacement of cluster sampling technique). The cost of surveying an edge unit(s) is assumed to be low in which case the efficiency of the ACS design relative to the non-adaptive design is achieved (Thompson and Collins, 2002). This is however not the case in aerial surveys as the aircraft flies at constant speed and height (Norton-Griffiths, 1978). Hence the cost of surveying an edge unit is the same as the cost of surveying a unit that meets the condition of interest. The without replacement of cluster technique plays a greater role of reducing the cost of sampling in such surveys. Other key points that motivated the sections in the dissertation include gains in efficiency (in all sections) and practicability of the designs in the specific setting. Even though the dissertation focused on animal populations, the methods can as well be implemented in any population that is rare and clustered such as in the study of forestry, plants, pollution, minerals and so on.
The development of our society contributed to increased occurrence of emerging substances (pesticides, pharmaceuticals, personal care products, etc.) in wastewater. Because of their potential hazard on ecosystems and humans, Wastewater Treatment Plants (WWTPs) need to adapt to better remove these compounds. Technology or policy development should however comply with sustainable development, e.g. based on Life Cycle Assessment (LCA) metrics. Nevertheless, the reliability or consistency of LCA results can sometimes be debatable. The main objective of this work was to explore how LCA can better support the implementation of innovative wastewater treatment options, in particular including removal benefits. The method was applied to support solutions for pharmaceuticals elimination from wastewater, regarding: (i) UV technology design, (ii) choice of advanced technology and (iii) centralized or decentralized treatment policy. The assessment approach followed by previous authors based on net impacts calculation seemed very promising to consider both environmental effects induced by treatment plant operation and environmental benefits obtained from pollutants removal. It was therefore applied to compare UV configuration types. LCA outcomes were consistent with degradation kinetics analysis. For the comparison of advanced technologies and policy scenarios, the common practice (net impacts based on EDIP method) was compared to other assessments, to better consider elimination benefits. First, USEtox consensus was applied for the avoided (eco)toxicity impacts, in combination with the recent method ReCiPe for generated impacts. Then, an eco-efficiency indicator (EFI) was developed to weigh the treatment efforts (generated impacts based on EDIP and ReCiPe methods) by the average removal efficiency (overcoming (eco)toxicity uncertainty issues). In total, the four types of comparative assessment showed the same trends: (i) ozonation and activated carbon perform better than UV irradiation, and (ii) no clear advantage distinguished between policy scenarios. It cannot be however concluded that advanced treatment of pharmaceuticals is not necessary because other criteria should be considered (risk assessment, bacterial resistance, etc.) and large uncertainties were embedded in calculations. Indeed, a significant part of this work was dedicated to the discussion of uncertainty and limitations of the LCA outcomes. At the inventory level, it was difficult to model technology operation at development stage. For impact assessment, the newly developed characterization factors for pharmaceuticals (eco)toxicity showed large uncertainties, mainly due to the lack of data and quality for toxicity tests. The use of information made available under REACH framework to develop CFs for detergent ingredients tried to cope with this issue but the benefits were limited due to the mismatch of information between REACH and USEtox method. The highlighted uncertainties were treated with sensitivity analyses to understand their effects on LCA results. This research work finally presents perspectives on the use of transparently generated data (technology inventory and (eco)toxicity factors) and further development of EFI indicator. Also, an accent is made on increasing the reliability of LCA outcomes, in particular through the implementation of advanced techniques for uncertainty management. To conclude, innovative technology/product development (e.g. based on circular economy approach) needs the involvement of all types of actors and the support from sustainability metrics.
Educational assessment tends to rely on more or less standardized tests, teacher judgments, and observations. Although teachers spend approximately half of their professional conduct in assessment-related activities, most of them enter their professional life unprepared, as classroom assessment is often not part of their educational training. Since teacher judgments matter for the educational development of students, the judgments should be up to a high standard. The present dissertation comprises three studies focusing on accuracy of teacher judgments (Study 1), consequences of (mis-)judgment regarding teacher nomination for gifted programming (Study 2) and teacher recommendations for secondary school tracks (Study 3), and individual student characteristics that impact and potentially bias teacher judgment (Studies 1 through 3). All studies were designed to contribute to a further understanding of classroom assessment skills of teachers. Overall, the results implied that, teacher judgment of cognitive ability was an important constant for teacher nominations and recommendations but lacked accuracy. Furthermore, teacher judgments of various traits and school achievement were substantially related to social background variables, especially the parents" educational background. However, multivariate analysis showed social background variables to impact nomination and recommendation only marginally if at all. All results indicated differentiated but potentially biased teacher judgments to impact their far-reaching referral decisions directly, while the influence of social background on the referral decisions itself seems mediated. Implications regarding further research practices and educational assessment strategies are discussed. The implications on the needs of teachers to be educated on judgment and educational assessment are of particular interest and importance.
The main achievement of this thesis is an analysis of the accuracy of computations with Loader's algorithm for the binomial density. This analysis in later progress of work could be used for a theorem about the numerical accuracy of algorithms that compute rectangle probabilities for scan statistics of a multinomially distributed random variable. An example that shall illustrate the practical use of probabilities for scan statistics is the following, which arises in epidemiology: Let n patients arrive at a clinic in d = 365 days, each of the patients with probability 1/d at each of these d days and all patients independently from each other. The knowledge of the probability, that there exist 3 adjacent days, in which together more than k patients arrive, helps deciding, after observing data, if there is a cluster which we would not suspect to have occurred randomly but for which we suspect there must be a reason. Formally, this epidemiological example can be described by a multinomial model. As multinomially distributed random variables are examples of Markov increments, which is a fact already used implicitly by Corrado (2011) to compute the distribution function of the multinomial maximum, we can use a generalized version of Corrado's Algorithm to compute the probability described in our example. To compute its result, the algorithm for rectangle probabilities for Markov increments always uses transition probabilities of the corresponding Markov Chain. In the multinomial case, the transition probabilities of the corresponding Markov Chain are binomial probabilities. Therefore, we start an analysis of accuracy of Loader's algorithm for the binomial density, which for example the statistical software R uses. With the help of accuracy bounds for the binomial density we would be able to derive accuracy bounds for the computation of rectangle probabilities for scan statistics of multinomially distributed random variables. To figure out how sharp derived accuracy bounds are, in examples these can be compared to rigorous upper bounds and rigorous lower bounds which we obtain by interval-arithmetical computations.
Unternehmen aus güterproduzierenden Industrien und Sektoren entdecken in immer stärkerem Maße das Differenzierungs- und Erlöspotenzial des Angebots ergänzender Dienstleistungen zur Erlangung von strategischen Wettbewerbsvorteilen. In vielen Branchen ist dies bereits ein notwendiger Bestandteil im Angebotsportfolios der Hersteller um sich zu positionieren und wettbewerbsfähig zu bleiben. Ein besonders prägnantes Beispiel stellt die Automobilbranche dar, die schon vor Jahren begonnen hat in ihr Geschäftsmodell um das Kernprodukt "Automobil" auch sog. produktbegleitende Dienstleistungen (wie beispielsweise Finanzierungsdienstleistungen) zu integrieren, um sich durch Erhöhung des Kundennutzens von den Angeboten der Mitbewerber zu differenzieren. Vor dem Hintergrund, dass Marketingkonstrukte, wie Marke, Reputation, Kundenloyalität, aber auch technische Spezifikationen wie Motorisierung, Ausstattung und Zubehör die Fahrzeugwahl beeinflussen, stellt sich die Autorin die Frage, inwiefern ein Zusatzangebot von reinen produktbegleitenden Dienstleistungen einen Einfluss auf die Marken- und Fahrzeugwahl beim Autokauf hat. In diesem Zusammenhang ist ein Forschungsziel der vorliegenden Untersuchung die Konzeption einer branchenunabhängigen Wertschöpfungskette für produktbegleitende Dienstleistungen, um eine Identifikation des strategischen Differenzierungspotenzials produktbegleitender Dienstleistungen zu ermöglichen. Den Bezugsrahmen der Forschungsarbeit wird dabei aus Perspektive des Endkonsumenten bei der Automobilkaufentscheidung konstruiert, um Aussagen zur Wahrnehmung existierender Angebote produktbegleitender Dienstleistungen den individuellen Phasen der Kaufentscheidung zuordnen zu können. Dies bildet das methodische Fundament dieses empirisch geprägten Forschungsbeitrags, um die folgende Frage der Untersuchung beantworten zu können: "Haben produktbegleitende Dienstleistungen einen Einfluss auf die Kaufwahrscheinlichkeit beim konsumentenseitigen Kaufentscheidungsprozess bei Automobilen im Segment des Privat-PKW?" Als Forschungsstrategie wird die Anwendung der Kausalanalyse gewählt, um anhand zwei aufeinander aufbauenden Primärerhebungen (quantitative Datenerhebung anhand eines Online-Fragebogens) potenzielle Autokäufer hinsichtlich ihres Wissens und ihrer Wahrnehmung bezüglich produktbegleitender Dienstleistungen der einzelnen Automobilherstellermarken zu untersuchen. Die Ergebnisse der Datenauswertung lassen die Schlussfolgerung zu, dass produktbegleitende Dienstleistungen zwar einen positiven Einfluss auf die Kaufentscheidung beim potentiellen Automobilkäufer ausüben, jedoch aufseiten der Automobilhersteller und -händler durchaus großes Verbesserungspotenzial bezüglich der Kommunikation von solchen Value-Added-Leistungen vorliegt. Die vorliegende Dissertationsschrift wurde am Lehrstuhl für Organisation und Strategisches Dienstleistungsmanagement verfasst und beim Fachbereich IV der Universität Trier eingereicht.
Psychotherapie hat sich in der Behandlung psychischer Störungen als wirksam erwiesen. Im Rahmen der klinisch-psychologischen Forschung und der Psychotherapieforschung sind die Erforschung von Ursachen und Mechanismen psychischer Störungen sowie die Identifikation von Wirkmechanismen von Psychotherapie von zentraler Bedeutung. Wichtiges Element in der Psychotherapie ist die Sprache, sodass die Betrachtung von Sprache bereits sehr früh Eingang in die Forschung fand. Beschäftigten sich frühe Forschungsarbeiten jedoch hauptsächlich mit der sehr zeitaufwendigen qualitativen Auswertung von Sprache, ermöglichen Entwicklungen im Bereich der Computer neue Ansätze wie beispielsweise die quantitative Sprachanalyse mittels Programmen wie dem Linguistic Inquiry and Word Count (LIWC). Dieses wörterbuchbasierte Auswertungsprogramm fand Anwendung in den unterschiedlichsten Bereichen wie beispielsweise der Erforschung von Motiven, Gruppenprozessen, Sprache in sozialen Netzwerken und ersten subklinischen Untersuchungen psychischer Störungen. Eine systematische Anwendung auf die Sprache von Patienten und Therapeuten im Rahmen vollständiger Therapiesitzung ist bislang jedoch nicht bekannt. Ziel der vorliegenden Arbeit war es deshalb in drei Projekten die Anwendbarkeit des Programmes in der klinisch-psychologischen Forschung und Psychotherapieforschung zu untersuchen. Das erste Projekt beschäftigte sich mit der Psychometrie von mittels LIWC ausgewerteter Sprache und fand, dass die Erkennungsraten des Wörterbuchs für die Sprache in Therapiesitzungen über den in der Literatur für das deutsche LIWC berichteten Erkennungsraten jedoch unter denen der aktuellsten englischen Versionen lag. Außerdem wurde angenommen, dass Sprache sowohl eine zeitlich stabile Komponente im Sinne eines Persönlichkeitsmerkmals als auch eine situative Komponente besitzt. Dies ist insbesondere vor dem Hintergrund relevant in der Psychotherapieforschung sowohl Patientenmerkmale als auch Veränderungen abbilden zu wollen. Die Arbeit ging davon aus, dass insbesondere Funktionsworte, also Worte, die Sprache strukturieren jedoch keine inhaltliche Bedeutung besitzen, eher individuell stabil sind, als Inhaltsworte. Entsprechend konnten für einige Wortkategorien ein Bifaktor-Modell mit einem Personen- sowie einem Zeitfaktor und adäquate Omega-Werte als Maß der Messgenauigkeit gefunden werden, für andere Kategorien zeigte sich dies nicht. Hypothesenkonform zeigten die Modelle bessere Passungen für Funktionsworte. Bezüglich der Frage nach der benötigten Länge von Sprachausschnitten aus Therapiesitzung erwies sich die Verwendung der gesamten Sitzung als beste Lösung. Im zweiten Projekt wurden Unterschiede in der Verwendung von Sprache zwischen depressiven Patienten, Patienten mit Angststörung und solchen mit beiden Störungsbildern untersucht. Es zeigten sich Unterschiede in Bezug auf Worte im Zusammenhang mit Traurigkeit und Worte im Zusammenhang mit Angst. Die Unterschiede zeigten sich derart, dass Depressive vermehrt mit Traurigkeit assoziierte Worte verwendeten, wohingegen Angstpatienten verstärkt Worte aus dem Bereich Angst verwendeten. Dies spricht für eine unterschiedliche inhaltliche Orientierung der beiden Störungsbilder. Darüber hinaus zeigten sich bei dimensionaler Betrachtung negative Zusammenhänge zwischen der Gesamtbelastung und Optimismus, positive Zusammenhänge Depression und Pronomengebrauch sowie negative Zusammenhänge zwischen Angst und unterschiedlichen Kategorien sozialer Worte. Im dritten Projekt wurden unterschiedliche weitere Fragestellungen der Psychotherapieforschung wie beispielsweise die Prädiktion von Therapieerfolgt mittels Sprache oder Zusammenhänge zwischen sprachlicher Synchronizität und der therapeutischen Beziehung untersucht. Es zeigten sich einzelne Zusammenhänge allerdings ergab sich kein einheitliches Muster. Die vorliegende Arbeit kommt zusammenfassend zu dem Schluss, dass quantitative Sprachanalyse eine Bereicherung der Psychotherapieforschung darstellt und Sprache als Datenquelle Berücksichtigung finden sollte. Allerdings bedarf es der Weiterentwicklung des LIWC sowie der Erprobung weiterer Verfahren und eine routinemäßige Erhebung von Sprache wird voraussichtlich erst im Zuge neuerer Entwicklungen im Bereich der automatischen Spracherkennung möglich werden.
Phase-amplitude cross-frequency coupling is a mechanism thought to facilitate communication between neuronal ensembles. The mechanism could underlie the implementation of complex cognitive processes, like executive functions, in the brain. This thesis contributes to answering the question, whether phase-amplitude cross-frequency coupling - assessed via electroencephalography (EEG) - is a mechanism by which executive functioning is implemented in the brain and whether an assumed performance effect of stress on executive functioning is reflected in phase-amplitude coupling strength. A huge body of studies shows that stress can influence executive functioning, in essence having detrimental effects. In two independent studies, each being comprised of two core executive function tasks (flexibility and behavioural inhibition as well as cognitive inhibition and working memory), beta-gamma phase-amplitude coupling was robustly detected in the left and right prefrontal hemispheres. No systematic pattern of coupling strength modulation by either task demands or acute stress was detected. Beta-gamma coupling might also be present in more basic attention processes. This is the first investigation of the relationship between stress, executive functions and phase-amplitude coupling. Therefore, many aspects have not been explored yet. For example, studying phase precision instead of coupling strength as an indicator for phase-amplitude coupling modulations. Furthermore, data was analysed in source space (independent component analysis); comparability to sensor space has still to be determined. These as well as other aspects should be investigated, due to the promising finding of very robust and strong beta-gamma coupling for all executive functions. Additionally, this thesis tested the performance of two widely used phase-amplitude coupling measures (mean vector length and modulation index). Both measures are specific and sensitive to coupling strength and coupling width. The simulation study also drew attention to several confounding factors, which influence phase-amplitude coupling measures (e. g. data length, multimodality).