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1.The Discursive Construction of Black Masculinity: Intersections of Race, Gender, and Sexuality
1.1.The Plight of Black Men: A History of Lynchings and Castrations
1.2.The Discursive Construction of the Black Man as Otherrn
1.3.Black Corporeality and the Scopic Regime of Racism
2. Ralph Ellison's 'Invisible man'
2.1.Invisible Black Men: Between Emasculation and Hypermasculinityrn
2.2.Transcending Invisibility
On the Influence of Ignored Stimuli: Generalization and Application of Distractor-Response Binding.
(2011)
In selection tasks where target stimuli are accompanied by distractors, responses to target stimuli, target stimuli and the distractor stimuli can be encoded together as one episode in memory. Subsequent repetition of any aspect of such an episode can lead to the retrieval of the whole episode including the response. Thus, repeating a distractor can retrieve responses given to previous targets; this mechanism was labeled distractor-response binding and has been evidenced in several visual setups. Three experiments of the present thesis implemented a priming paradigm with an identification task to generalize this mechanism to auditory and tactile stimuli as well as to stimulus concepts. In four more experiments the possible effect of distractor-response binding on drivers' reactions was investigated. The same paradigm was implemented using more complex stimuli, foot responses, go/no-go responses, and a dual task setup with head-up and head-down displays. The results indicate that distractor-response binding effects occur with auditory and tactile stimuli and that the process is mediated by a conceptual representation of the distractor stimuli. Distractor-response binding effects also revealed for stimuli, responses, and framework conditions likely to occur in a driving situation. It can be concluded that the effect of distractor-response binding needs to be taken into account for the design of local danger warnings in driver assistance systems.
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.
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.
This dissertation focuses on the link between labour market institutions and precautionary savings. It is evaluated whether private households react to changes in social insurance provision such as the income replacement in case of unemployment by increased savings for precautionary reasons. The dissertation consists of three self-contained chapters, each focusing on slightly different aspects of the topic. The first chapter titled "Precautionary saving and the (in)stability of subjective earnings uncertainty" empirically looks at the influence of future income uncertainty on household saving behavior. Numerous cross-section studies on precautionary saving use subjective expectations regarding the income variance one year ahead as a proxy for income uncertainty. Using such proxies observed only at one point in time, however, may give rise to biased estimates for precautionary wealth if expectations are not stable over time. Survey data from the Dutch DNB Household Survey suggest that subjective future income distributions are not stable over the mid-term. Moreover, in this study I contrast estimates of precautionary wealth using the variation coefficient observed at one point in time with those using a simple mid-term average. Estimates of precautionary wealth based on the average are about 40% to 80% higher than the estimates using the variation coefficient observed only once. In addition to that, wealth accumulation for precautionary reasons is estimated for different parts of the income distribution. The share of precautionary wealth is highest for households at the center of the income distribution. By linking saving behaviour with unemployment insurance, the following chapters then shed some light on an issue that has largely been neglected in the literature on labour market institutions so far. Whereas the third chapter models the relevance of unemployment insurance for income uncertainty and intertemporal decision making during institutional reform processes, chapter 4 seeks to establish empirically a relationship between saving behavior and unemployment insurance. Social insurance, especially unemployment insurance, provides agents with income insurance against not marketable income risks. Since the early 1990s, reform measures like more activating policies as suggested by the OECD Jobs Study in 1994 have been observed in Europe. In the third chapter it is argued that such changes in unemployment insurance reduce public insurance and increase income uncertainty. Moreover, a simple three period model is discussed which shows a link between a welfare state reform and agents' saving decisions as one possible reaction of agents to self-insure against income risk. Two sources of uncertainty seem to be important in this context: (1) uncertain results of the reform process concerning the replacement rate, and (2) uncertainty regarding the timing of information about the content of the reform. It can be shown that the precautionary motive for saving explains an increased accumulation of capital in times of reform activities. In addition to that, early information about the expected replacement rate increases agents' utility and reduces under and oversaving. Following the argument of the previous chapters, that an important feature of labour market institutions in modern welfare states is to provide cash transfers as income replacement in case of unemployment, it is hypothesised that unemployment benefits reduce the motive to save for precautionary reasons. Based on consumer sentiment data from the European Commission's Consumer Survey, chapter four finally provides some evidence that aggregate saving intentions are significantly influenced by unemployment benefits. It can be shown that higher benefits lower the intention to save.
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.
Cortisol is a stress hormone that acts on the central nervous system in order to support adaptation and time-adjusted coping processes. Whereas previous research has focused on slow emerging, genomic effects of cortisol likely mediated by protein synthesis, there is only limited knowledge about rapid, non-genomic cortisol effects on in vivo neuronal cell activity in humans. Three independent placebo-controlled studies in healthy men were conducted to test effects of 4 mg cortisol on central nervous system activity, occurring within 15 minutes after intravenous administration. Two of the studies (N = 26; N = 9) used continuous arterial spin labeling as a magnetic resonance imaging sequence, and found rapid bilateral thalamic perfusion decrements. The third study (N = 14) revealed rapid cortisol-induced changes in global signal strength and map complexity of the electroencephalogram. The observed changes in neuronal functioning suggest that cortisol may act on the thalamic relay of non-relevant background as well as on task specific sensory information in order to facilitate the adaptation to stress challenges. In conclusion, these results are the first to coherently suggest that a physiologically plausible amount of cortisol profoundly affects functioning and perfusion of the human CNS in vivo by a rapid, non-genomic mechanism.
The 22nd annual conference of the European Consortium for Church and State Research took place from 11 to 14 November 2010 in Trier, Germany. Founded in 1989, the Consortium unites experts of law and religion of all Member States of the European Union. In annual meetings, various topics of the relations between religions and states within the European Union are discussed. This year- conference was dedicated to the topic "Religion in Public Education". Scholars from 27 European countries discussed inter alia the role of religion in the European member states" educational systems, opting out of school obligations for religious reasons, home schooling as well as religious dress and symbols in public schools. The present proceedings contain the opening lectures, all country reports and a report on the European Union law.
In a case of robbery, some people actually use violence to steal - but others may supply information or weapons, make the plans, act as lookouts, provide transport. Certainly the actual robbers are guilty - but what of the others? How does Hong Kong's version of the common law answer this question now? How should the question be answered in the future?
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.