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Recent non-comparative studies diverge in their assessments of the extent to which German and Japanese post-Cold War foreign policies are characterized by continuity or change. While the majority of analyses on Germany find overall continuity in policies and guiding principles, prominent works on Japan see the country undergoing drastic and fundamental change. Using an explicitly comparative framework for analysis based on a role theoretical approach, this study reevaluates the question of change and continuity in the two countries" regional foreign policies, focusing on the time period from 1990 to 2010. Through a qualitative content analysis of key foreign policy speeches, this dissertation traces and compares German and Japanese national role conceptions (NRCs) by identifying policymakers" perceived duties and responsibilities of their country in international politics. Furthermore, it investigates actual foreign policy behavior in two case studies about German and Japanese policies on missile defense and on textbook disputes. The dissertation examines whether the NRCs identified in the content analysis are useful to understand and explain each country- particular conduct. Both qualitative content analysis and case studies demonstrate the influence of normative and ideational variables in foreign policymaking. Incremental adaptations in foreign policy preferences can be found in Germany as well as Japan, but they are anchored in established normative guidelines and represent attempts to harmonize existing preferences with the conditions of the post-Cold War era. The dissertation argues that scholars have overstated and misconstrued the changes underway by asserting that Japan is undergoing a sweeping transformation in its foreign policy.
In addition to the well-recognised effects of both, genes and adult environment, it is now broadly accepted that adverse conditions during pregnancy contribute to the development of mental and somatic disorders in the offspring, such as cardiovascular disorders, endocrinological disorders, metabolic disorders, schizophrenia, anxious and depressive behaviour and attention deficit hyperactivity disorder (ADHD). Early life events may have long lasting impact on tissue structure and function and these effects appear to underlie the developmental origins of vulnerability to chronic diseases. The assumption that prenatal adversity, such as maternal emotional states during pregnancy, may have adverse effects on the developing infant is not new. Accordant references can be found in an ancient Indian text (ca. 1050 before Christ), in biblical texts and in documents originating during the Middle Ages. Even Hippocrates stated possible effects of maternal emotional states on the developing fetus. Since the mid-1950s, research examining the effects of maternal psychosocial stress during pregnancy appeared in the literature. Extensive research in this field has been conducted since the early 1990s. Thus, the relationship between early life events and long-term health outcomes was already postulated over 20 years ago. David Barker and colleagues demonstrated that children of lower birth weight - which represents a crude marker of an adverse intrauterine environment - were at increased risk of high blood pressure, cardiovascular disorders, and type-2 diabetes later in life. These provocative findings led to a large amount of subsequent research, initially focussing on the role of undernutrition in determining fetal outcomes. The phenomenon of prenatal influences that determine in part the risk of suffering from chronic disease later in life has been named the "fetal origins of health and disease" paradigm. The concept of "prenatal programming" has now been extended to many other domains, such as the effects of prenatal maternal stress, prenatal tobacco exposure, alcohol intake, medication, toxins, as well as maternal infection and diseases. During the process of prenatal programming, environmental agents are transmitted across the placenta and act on specific fetal tissues during sensitive periods of development. Thus, developmental trajectories are changed and the organisation and function of tissue structure and organ system is altered. The biological purpose of those "early life programming" may consist in evolutionary advantages. The offspring adapts its development to the expected extrauterine environment which is forecast by the clues available during fetal life. If the fetus receives signals of a challenging environment, e.g. due to maternal stress hormones or maternal undernutrition, its survival may be promoted due to developmental adaptation processes. However, if the expected environment does not match with the real environment, maladapation and later disease risk may result. For example, a possible indicator of a "response ready" trait, such as hyperactivity/inattention may have been advantageous in an adverse ancient environment. However, it is of disadvantage when the postnatal environment demands oppositional skills, such as attention and concentration " e.g. in the classroom, at school, to achieve academic success. Borderline personality disorder (BPD) is a prevalent psychiatric disorder, characterized by impulsivity, affective instability, dysfunctional interpersonal relationships and identity disturbance. Although many studies report different risk factors, the exact etiologic mechanisms are not yet understood. In addition to the well-recognised effects of genetic components and adverse childhood experiences, BPD may potentially be co-determined by further environmental influences, acting very early in life: during pre- and perinatal period. There are several hints that may suggest possible prenatal programming processes in BPD. For example, patients with BPD are characterized by elevated stress sensitivity and reactivity and dysfunctions of the neuroendocrine stress system, such as the hypothalamic pituitary adrenal (HPA) axis. Furthermore, patients with BPD show a broad range of somatic comorbidities " especially those disorders for which prenatal programming processes have been described. During infancy and childhood, BPD patients already show behavioural and emotional abnormalities as well as pronounced temperamental traits, such as impulsivity, emotional dysregulation and inattention that may potentially be co-determined by prenatal programming processes. Such temperamental traits - similar to those, seen in patients with ADHD - have been described to be associated with low birthweight which indicates a suboptimal intrauterine environment. Moreover, the functional and structural alterations in the central nervous system (CNS) in patients with BPD might also be mediated in part by prenatal agents, such as prenatal tobacco exposure. Prenatal adversity may thus constitute a further, additional component in the multifactorial genesis of BPD. The association between BPD and prenatal risk factors has not yet been studied in such detail. We are not aware of any further study that assessed pre- and perinatal risk factors, such as maternal psychoscocial stress, smoking, alcohol intake, obstetric complications and lack of breastfeeding in patients with BPD.
Die Ménage-Polynome (engl.: ménage hit polynomials) ergeben sich in natürlicher Weise aus den in der Kombinatorik auftretenden Ménage-Zahlen. Eine Verbindung zu einer gewissen Klasse hypergeometrischer Polynome führt auf die Untersuchung spezieller Folgen von Polynomen vom Typ 3-F-1. Unter Verwendung einer Modifikation der komplexen Laplace-Methode zur gleichmäßigen asymptotischen Auswertung von Parameterintegralen sowie einiger Hilfsmittel aus der Potentialtheorie der komplexen Ebene werden starke und schwache Asymptotiken für die in Rede stehenden Polynomfolgen hergeleitet.
The demand for reliable statistics has been growing over the past decades, because more and more political and economic decisions are based on statistics, e.g. regional planning, allocation of funds or business decisions. Therefore, it has become increasingly important to develop and to obtain precise regional indicators as well as disaggregated values in order to compare regions or specific groups. In general, surveys provide the information for these indicators only for larger areas like countries or administrative divisions. However, in practice, it is more interesting to obtain indicators for specific subdivisions like on NUTS 2 or NUTS 3 levels. The Nomenclature of Units for Territorial Statistics (NUTS) is a hierarchical system of the European Union used in statistics to refer to subdivisions of countries. In many cases, the sample information on such detailed levels is not available. Thus, there are projects such as the European Census, which have the goal to provide precise numbers on NUTS 3 or even community level. The European Census is conducted amongst others in Germany and Switzerland in 2011. Most of the participating countries use sample and register information in a combined form for the estimation process. The classical estimation methods of small areas or subgroups, such as the Horvitz-Thompson (HT) estimator or the generalized regression (GREG) estimator, suffer from small area-specific sample sizes which cause high variances of the estimates. The application of small area methods, for instance the empirical best linear unbiased predictor (EBLUP), reduces the variance of the estimates by including auxiliary information to increase the effective sample size. These estimation methods lead to higher accuracy of the variables of interest. Small area estimation is also used in the context of business data. For example during the estimation of the revenues of specific subgroups like on NACE 3 or NACE 4 levels, small sample sizes can occur. The Nomenclature statistique des activités économiques dans la Communauté européenne (NACE) is a system of the European Union which defines an industry standard classification. Besides small sample sizes, business data have further special characteristics. The main challenge is that business data have skewed distributions with a few large companies and many small businesses. For instance, in the automotive industry in Germany, there are many small suppliers but only few large original equipment manufacturers (OEM). Altogether, highly influential units and outliers can be observed in business statistics. These extreme values in connection with small sample sizes cause severe problems when standard small area models are applied. These models are generally based on the normality assumption, which does not hold in the case of outliers. One way to solve these peculiarities is to apply outlier robust small area methods. The availability of adequate covariates is important for the accuracy of the above described small area methods. However, in business data, the auxiliary variables are hardly available on population level. One of several reasons for that is the fact that in Germany a lot of enterprises are not reflected in business registers due to truncation limits. Furthermore, only listed enterprises or companies which trespass specific thresholds are obligated to publish their results. This limits the number of potential auxiliary variables for the estimation. Even though there are issues with available covariates, business data often include spatial dependencies which can be used to enhance small area methods. Next to spatial information based on geographic characteristics, group-specific similarities like related industries based on NACE codes can be used. For instance, enterprises from the same NACE 2 level, e.g. sector 47 retail trade, behave more similar than two companies from different NACE 2 levels, e.g. sector 05 mining of coal and sector 64 financial services. This spatial correlation can be incorporated by extending the general linear mixed model trough the integration of spatially correlated random effects. In business data, outliers as well as geographic or content-wise spatial dependencies between areas or domains are closely linked. The coincidence of these two factors and the resulting consequences have not been fully covered in the relevant literature. The only approach that combines robust small area methods with spatial dependencies is the M-quantile geographically weighted regression model. In the context of EBLUP-based small area models, the combination of robust and spatial methods has not been considered yet. Therefore, this thesis provides a theoretical approach to this scientific and practical problem and shows its relevance in an empirical study.
The role of cortisol and cortisol dynamics in patients after aneurysmal subarachnoid hemorrhage
(2011)
Spontaneous aneurysmal subarachnoid hemorrhage (SAH) is a form of stroke which constitutes a severe trauma to the brain and often leads to serious long-term medical and psychosocial sequels which persist for years after the acute event. Recently, adrenocorticotrophic hormone deficiency has been identified as one possible consequence of the bleeding and is assumed to occur in around 20% of all survivors. Additionally, a number of studies report a high prevalence of post-SAH symptoms such as lack of initiative, fatigue, loss of concentration, impaired quality of life and psychiatric symptoms such as depression. The overlap of these symptoms and those of patients with untreated partial or complete hypopituitarism lead to the suggestion that neuroendocrine dysregulations may contribute to the psychosocial sequels of SAH. Therefore, one of the aims of this work is to gain insights into the role of neuroendocrine dysfunction on quality of life and the prevalence of psychiatric sequels in SAH-patients. Additionally, as data on cortisol dynamics after SAH are scarce, diurnal cortisol profiles are investigated in patients in the acute and chronic phase, as well as the cortisol awakening response and feedback sensitivity in the chronic phase after SAH. As a result, it can be shown that some SAH patients exhibit lower serum cortisol levels but at the same time a higher cortisol awakening response in saliva than healthy controls. Also, patients in the chronic phase after SAH do have a stable diurnal cortisol rhythm while there are disturbances in around 50% of all patients in the acute phase, leading to the conclusion that a single baseline measurement of cortisol is of no substantial use for diagnosing cortisol dysregulations in the acute phase after SAH. It is assumed that in SAH patients endocrine changes occur over time and that a combination of adrenal exhaustion and a subsequent downregulation of corticosteroid binding globulin may be the most probable causes for the dissociation of serum cortisol concentrations and salivary cortisol profiles in the investigated SAH patients. These changes may be an emergency response after SAH and, as elevated free cortisol levels are connected to a better psychosocial outcome in patients in the chronic phase after SAH, this reaction may even be adaptive.
Die Auswirkungen von Rahmenfehlern in Zensen werden bereits seit vielen Jahren untersucht. Eine Methode, um aktuelle Bevölkerungszahlen zu gewinnen, basiert auf Fortschreibung. Wegen Ungenauigkeiten in der Fortschreibung wurden aber auch andere Modelle entwickelt - die capture-recapture-Modelle. Am 29. August 2006 hat die Bundesregierung beschlossen, dass in Deutschland 2011 ein registergestützter Zensus durchgeführt wird. Der Schwerpunkt dieser Dissertation liegt in der Anwendung des capture-recapture-Modelles im deutschen Zensus 2011. Die Dissertation vergleicht den dual system estimator (DSE) und alternative Schätzer (Verallgemeinerter-Regressionsschätzer, Verhältnis-synthetischer Schätzer, Schätzer basierend auf dem Unit-level Modell) für die Schätzung der Anzahl der tatsächlich vorhandenen Personen. Die empirische Untersuchung der Güte der Schätzer basiert auf Monte Carlo Simulationen synthetischer Populationen des Bundeslandes Saarland.
Die Vertrauens-Trias erlaubt salutogentische Aussagen über personale Ressourcen. Die kulturvergleichende Anwendung der Vertrauens-Trias wurde bei Jugendlichen in drei Ländern (Deutschland, Luxemburg, Spanien) überprüft. Dabei wurde die Konstruktvalidität der Vertrauens-Trias als auch Zusammenhänge zu symptomatischen Belastungen insgesamt bestätigt. Vergleiche zwischen den Kulturen zeigen keine Unterschiede zwischen deutschen und luxemburgischen Schülern, jedoch zwischen deutschen und spanischen Schülern.
Psychiatric/Behavioral disorders/traits are usually polygenic in nature, where a particular phenotype is the manifestation of multiple genes. However, the existence of large families with numerous members who are affected by these disorders/traits steers us towards a Mendelian (or monogenic) possibility, where the phenotype is caused by a single gene. In order to better understand the genetic architecture of general psychiatric/behavioral disorders/traits, this thesis investigates large pedigrees that display a Mendelian pattern for attention-deficit/hyperactivity disorder, schizophrenia and bipolar disorder. Numerous challenges in the field of psychiatric and behavioral sciences have impeded the genetic investigation of such disorders/traits. Examples include frequent cross-disorders, genetic heterogeneity across subjects as well as the use of diagnostic tools that can be subjective at times. To overcome these challenges, this thesis investigates large multi-generational pedigrees, which comprise a significant number of members who exhibit specific psychiatric/behavioral phenotypes. These pedigrees provide high-resolution experimental setups that can dissect the genetic complexities of psychiatric/behavioral disorders/traits. This thesis adopts a classical two-stage genetic approach to investigate the various psychiatric/behavioral disorders/traits in large pedigrees. The classical two-stage genetic approach is commonly used by many human geneticists to study a wide spectrum of human physiological disorders but is only being applied to the field of psychiatric and behavioral genetics recently. Through the study of large pedigrees, this thesis discovers the genomic regions that may play a causative role in the expression of certain psychiatric/behavioral disorders/traits within the vast genome.
This work is concerned with two kinds of objects: regular expressions and finite automata. These formalisms describe regular languages, i.e., sets of strings that share a comparatively simple structure. Such languages - and, in turn, expressions and automata - are used in the description of textual patterns, workflow and dependence modeling, or formal verification. Testing words for membership in any given such language can be implemented using a fixed - i.e., finite - amount of memory, which is conveyed by the phrasing finite-automaton. In this aspect they differ from more general classes, which require potentially unbound memory, but have the potential to model less regular, i.e., more involved, objects. Other than expressions and automata, there are several further formalisms to describe regular languages. These formalisms are all equivalent and conversions among them are well-known.However, expressions and automata are arguably the notions which are used most frequently: regular expressions come natural to humans in order to express patterns, while finite automata translate immediately to efficient data structures. This raises the interest in methods to translate among the two notions efficiently. In particular,the direction from expressions to automata, or from human input to machine representation, is of great practical relevance. Probably the most frequent application that involves regular expressions and finite automata is pattern matching in static text and streaming data. Common tools to locate instances of a pattern in a text are the grep application or its (many) derivatives, as well as awk, sed and lex. Notice that these programs accept slightly more general patterns, namely ''POSIX expressions''. Concerning streaming data, regular expressions are nowadays used to specify filter rules in routing hardware.These applications have in common that an input pattern is specified in form a regular expression while the execution applies a regular automaton. As it turns out, the effort that is necessary to describe a regular language, i.e., the size of the descriptor,varies with the chosen representation. For example, in the case of regular expressions and finite automata, it is rather easy to see that any regular expression can be converted to a finite automaton whose size is linear in that of the expression. For the converse direction, however, it is known that there are regular languages for which the size of the smallest describing expression is exponential in the size of the smallest describing automaton.This brings us to the subject at the core of the present work: we investigate conversions between expressions and automata and take a closer look at the properties that exert an influence on the relative sizes of these objects.We refer to the aspects involved with these consideration under the titular term of Relative Descriptional Complexity.
There is a lot of evidence for the impact of acute glucocorticoid treatment on hippocampus-dependent explicit learning and memory (memory for facts and events). But there have been few studies, investigating the effect of glucocorticoids on implicit learning and memory. We conducted three studies with different methodology to investigate the effect of glucocorticoids on different forms of implicit learning. In Study 1, we investigated the effect of cortisol depletion on short-term habituation in 49 healthy subjects. 25 participants received oral metyrapone (1500 mg) to suppress endogenous cortisol production, while 24 controls received oral placebo. Eye blink electromyogram (EMG) responses to 105 dB acoustic startle stimuli were assessed. Effective endogenous cortisol suppression had no effect on short-term habituation of the startle reflex, but startle eye blink responses were significantly increased in the metyrapone group. The latter findings are in line with previous human studies, which have shown that excess cortisol, sufficient to fully occupy central nervous system (CNS) corticosteroid receptors, may reduce startle eye blink. This effect may be mediated by CNS mechanisms controlling cortisol feedback. In Study 2, we investigated delay or trace eyeblink conditioning in a patient group with a relative hypocortisolism (30 patients with fibromyaligia syndrome/FMS) compared to 20 healthy control subjects. Conditioned eyeblink response probability was assessed by EMG. Morning cortisol levels, ratings of depression, anxiety and psychosomatic complaints as well as general symptomatology and psychological distress were assessed. As compared to healthy controls FMS patients showed lower morning cortisol levels, and trace eyeblink conditioning was facilitated whereas delay eyeblink conditioning was reduced. Cortisol measures correlate significantly only with trace eyeblink conditioning. Our results are in line with studies of pharmacologically induced hyper- and hypocortisolism, which affected trace eyeblink conditioning. We suggest that endocrine mechanisms affecting hippocampus-mediated forms of associative learning may play a role in the generation of symptoms in these patients.rnIn Study 3, we investigated the effect of excess cortisol on implicit sequence learning in healthy subjects. Oral cortisol (30 mg) was given to 29 participants, whereas 31 control subjects received placebo. All volunteers performed a 5-choice serial reaction time task (SRTT). The reaction speed of every button-press was determined and difference-scores were calculated as a proof of learning. Compared to the control group, we found a delayed learning in the cortisol group at the very beginning of the task. This study is the first human investigation, indicating impaired implicit memory function after exogenous administration of the stress hormone cortisol. Our findings support a previous neuroimaging study, which suggested that the medial temporal lobe (including the hippocampus) is also active in implicit sequence learning, but our results may also depend on the engagement of other brain structures.