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From Brock to Brett
(2021)
This master's thesis in US American cultural studies posits that the phenomenon of rape culture represents a socio-cultural system of social power structures and cultural myths. Based on so-called rape myths, this system also constitutes an ideology. The thesis aims to demonstrate how these rape myths are instrumentalized in order to protect (primarily white, cis-male) perpetrators and instead assign responsibility to those affected by sexualized violence. In doing so, the thesis shows that young men like Brock Turner, who benefit from patriarchal power structures, grow up to become men like Brett Kavanaugh, who not only benefit from the fact that rape culture excuses their abusive behavior, but also from the fact that this enables them to reach positions of power through which they, as decision-makers, can in turn maintain the structures underlying rape culture.
The thesis focuses on the rape myths of so-called victim blaming and shaming as well as the victimization of perpetrators. These myths are examined by analyzing 19th-century newspaper articles and then traced into the 21st century. Based on Mary Douglas' theory on ideas of purity, the thesis shows the extent to which not only social categories, namely gender, race, socio-economic status, and age, but also the sexual purity or impurity of those affected have an impact on the societal response to rape cases.
Furthermore, the thesis demonstrates how female bodies function as an ideological battleground for political and social change in the US, and how perceived threats to the patriarchal status quo are framed in public discourse as moral dangers posed by female bodies. The paper argues that rape culture is driven by (white cis) male entitlement to female bodies but moreover to positions of power in the patriarchal system. The thesis shows how this system instrumentalizes rape culture to maintain its underlying structures that favor (cis) men and, in contrast, disadvantage (cis) women and other marginalized and non-heteronormative groups. This is illustrated by analyzing the 2016 Stanford rape case and the 2018 Kavanaugh hearing.
Both horizontal-to-vertical (H/V) spectral ratios and the spatial autocorrelation method (SPAC) have proven to be valuable tools to gain insight into local site effects by ambient noise measurements. Here, the two methods are employed to assess the subsurface velocity structure at the Piano delle Concazze area on Mt Etna. Volcanic tremor records from an array of 26 broadband seismometers is processed and a strong variability of H/V ratios during periods of increased volcanic activity is found. From the spatial distribution of H/V peak frequencies, a geologic structure in the north-east of Piano delle Concazze is imaged which is interpreted as the Ellittico caldera rim. The method is extended to include both velocity data from the broadband stations and distributed acoustic sensing data from a co-located 1.5 km long fibre optic cable. High maximum amplitude values of the resulting ratios along the trajectory of the cable coincide with known faults. The outcome also indicates previously unmapped parts of a fault. The geologic interpretation is in good agreement with inversion results from magnetic survey data. Using the neighborhood algorithm, spatial autocorrelation curves obtained from the modified SPAC are inverted alone and jointly with the H/V peak frequencies for 1D shear wave velocity profiles. The obtained models are largely consistent with published models and were able to validate the results from the fibre optic cable.
The aesthetic phenomenon of the uncanny in literature and art is a spatial and gendered aesthetic concept, which is expressed in the spatial characteristics of a literary or photographic narrative. The intention of this thesis is to evaluate the entanglement of the uncanny, space, domesticity and femininity in the context of Gothic literature and photography. These four objects can only be read in their interplay with each other and how they each function as structural principles in the framework of Gothic fiction and photography. The literary texts, Charlotte Perkins Gilman’s “The Yellow Wall-Paper” (1892) and Shirley Jackson’s “The Lovely House” (1950) and The Haunting of Hill House (1959) as well as Francesca Woodman’s self-portraits that will be discussed further share one particular quality; they use the haunted house motif to express the protagonist’s psychological state by transferring mental hauntings onto the narrative’s spatial layer. The establishment of a connection between the concepts at hand, the uncanny, domesticity, spatiality and femininity, is the basis for the first half of the thesis. What follows is an overview of how domestic politics and gendered perceptions of and behaviors in spaces are expressed in the Gothic mode in particular. In the literary analysis two ways in which the Freudian uncanny constitutes itself in the haunted house narrative, first the house as the site of repetition and second the house as a stand-in for the maternal body, are examined. Drawing from Gernot Böhme’s and Martina Löw’s theoretic work on space and atmosphere the thesis focuses on the different aesthetic strategies that produce the uncanny atmosphere associated with the Gothic haunted house. The female subjects at the narratives’ center are in the ambiguous process of disappearing or becoming, this (dis)appearing act is facilitated by their haunted surroundings. In the case of the unnamed narrator in “Wall-Paper” her suppressed rage at her husband is mirrored in the strangled woman trapped inside the yellow wallpaper. Once she recognizes her doppelganger the union of her two selves takes place in the short story’s dramatic climax. In Shirley Jackson’s literary works the haunted houses, protagonists in themselves, entrap, transform, and ultimately devour their female daughter-victims. The haunted houses are symbols, means and places of the continuous tradition of female entrapment within the domestic sphere, be it as wives, mothers or daughters. In Francesca Woodman’s self-portraits the themes of creation/destruction and becoming/disappearing within the ruinous (post)domestic sphere are acted out by the fragmented and blurry female figure who intriguingly oscillates between self-empowerment and submission to destruction.
Hunting Down Animal Verbs
(2022)
Language change is an essential feature of human language, and it is therefore one of the focal areas of the scientific study of language. Language change is always tacitly at work in all languages of the world and at all levels of a given language, be it phonology, morphology, syntax, semantics, etc. It has been suggested that it is precisely the capacity to constantly change and adjust that allows language to keep serving the communicative goals of its users, from ancient to modern times (Fauconnier & Turner, 2003, p. 179).
This thesis investigates an especially salient pattern of lexicogrammatical change, namely word-formation of verbs from animal nouns by zero-derivation, in the process of which such nouns as, for example, dog, horse, or beaver change their usage and meaning to produce animal verbs: to dog ‘to follow someone persistently and with a malicious intent’, to horse about/around ‘to make fun of, to ‘rag’, to ridicule someone’ and to beaver away ‘to work at working with great enthusiasm’ respectively. In the previous literature this pattern of language change has been termed verbal zoosemy (e.g. Kiełtyka, 2016), i.e. metaphorical construal of human actions by means of linguistic material from the domain of animals.
The approach taken in this study is not to simply report on the objective changes in the morphology, syntactic distribution and meaning of such linguistic units before and after conversion, but to uncover the complexity of cognitive mechanisms which allow the speakers of English to reclassify such well-established nominal units as animal noun into verbs. It is assumed that the grammatical change in these lexical units is predicated on and triggered by preceding semantic change. Thus, the study is set in the framework of Cognitive Historical Semantics and employs the Conceptual Metaphor and Metonymy Theory (CMMT) to untangle the intricacies of the semantic change making the grammatical change of animal nouns into verbs possible and acceptable in the minds of English speakers.
To this end, this study employed the Oxford English Dictionary Online (OED Online) to compile a glossary of 96 denominal animal verbal forms tied to 209 verbal senses (most verbs in the dataset displayed polysemy). The data collected from the OED Online included not only the senses of the verbs, but also the date of the earliest recorded use of the verbal form with the given sense (regarded in the study as the date of conversion), the earliest usage examples for individual senses and morphologically or semantically related linguistic units from the lexical field of the respective parent noun which were amenable to explaining the observed instances of semantic change. Each instance of zoosemisation, i.e. of the creation of a separate metaphorical verbal sense, was then carefully analysed on the basis of the data collected and classified with the help of the CMMT. In the final stage, a comprehensive and systematic classification of the senses of animal verbs in accordance with the cognitive mechanisms of their creation (metaphor, metonymy, or a combination thereof) was produced together with a timeline of the first appearance of individual metaphorical senses of animal verbs recorded in the OED.
The results show that animal verbs are produced through the interaction of conceptual metaphor and metonymy. Specifically, it was established that two major patterns of metaphor-metonymy interaction underpinning the process of verbal zoosemisation are metaphor from metonymy and metonymy from metaphor. In the former pattern, either an already existing metonymic animal verb is expanded to include the target domain PEOPLE, or the animal noun itself acts as a metonymic vehicle to a certain element of the idealised cognitive model of the given animal, which is metaphorically projected onto people. In the latter mechanism, a metaphorical projection of an animal term initially enters the lexicon in the form of a metaphorical animal noun referring to a human entity, and later in the course of language development it comes to metonymically stand for the action, which the given entity either performs or is involved in. Secondarily, it was observed that individual animal nouns can undergo multiple rounds of zoosemic conversion over time depending on the semantic frame in which the given linguistic unit undergoes denominal conversion, and that results in the polysemy of most animal verbs.
DeepGeoMap
(2021)
In recent years, deep learning improved the way remote sensing data is processed. The classification of hyperspectral data is no exception. 2D or 3D convolutional neural networks have outperformed classical algorithms on hyperspectral image classification in many cases. However, geological hyperspectral image classification includes several challenges, often including spatially more complex objects than found in other disciplines of hyperspectral imaging that have more spatially similar objects (e.g., as in industrial applications, aerial urban- or farming land cover types). In geological hyperspectral image classification, classical algorithms that focus on the spectral domain still often show higher accuracy, more sensible results, or flexibility due to spatial information independence. In the framework of this thesis, inspired by classical machine learning algorithms that focus on the spectral domain like the binary feature fitting- (BFF) and the EnGeoMap algorithm, the author of this thesis proposes, develops, tests, and discusses a novel, spectrally focused, spatial information independent, deep multi-layer convolutional neural network, named 'DeepGeoMap’, for hyperspectral geological data classification. More specifically, the architecture of DeepGeoMap uses a sequential series of different 1D convolutional neural networks layers and fully connected dense layers and utilizes rectified linear unit and softmax activation, 1D max and 1D global average pooling layers, additional dropout to prevent overfitting, and a categorical cross-entropy loss function with Adam gradient descent optimization. DeepGeoMap was realized using Python 3.7 and the machine and deep learning interface TensorFlow with graphical processing unit (GPU) acceleration. This 1D spectrally focused architecture allows DeepGeoMap models to be trained with hyperspectral laboratory image data of geochemically validated samples (e.g., ground truth samples for aerial or mine face images) and then use this laboratory trained model to classify other or larger scenes, similar to classical algorithms that use a spectral library of validated samples for image classification. The classification capabilities of DeepGeoMap have been tested using two geological hyperspectral image data sets. Both are geochemically validated hyperspectral data sets one based on iron ore and the other based on copper ore samples. The copper ore laboratory data set was used to train a DeepGeoMap model for the classification and analysis of a larger mine face scene within the Republic of Cyprus, where the samples originated from. Additionally, a benchmark satellite-based dataset, the Indian Pines data set, was used for training and testing. The classification accuracy of DeepGeoMap was compared to classical algorithms and other convolutional neural networks. It was shown that DeepGeoMap could achieve higher accuracies and outperform these classical algorithms and other neural networks in the geological hyperspectral image classification test cases. The spectral focus of DeepGeoMap was found to be the most considerable advantage compared to spectral-spatial classifiers like 2D or 3D neural networks. This enables DeepGeoMap models to train data independently of different spatial entities, shapes, and/or resolutions.
The involvement of the two German states in Korea during the 1950s in the context of the Cold War
(2020)
This master thesis will analyze the background of the involvement of the Federal Republic of Germany (FRG) and the German Democratic Republic (GDR) in Korea during the 1950s in the context of the Cold War. In both Korean states, the Democratic People’s Republic of Korea (DPRK) as well as the Republic of Korea (ROK), the so-called humanitarian aid that was provided to them in the form of medical and economic assistance to help surmount the hardship of the postwar period is remembered with great appreciation to this day. However, critical views on the German engagement in Korea are still relatively hard to find. In this paper, two exemplary cases will be studied: the GDR’s city reconstruction project in the North Korean cities of Hamheung and Heungnam and the FRG’s medical assistance to the ROK by means of the West German Red Cross Hospital in Busan. By looking at primary sources like governmental documents, this thesis will examine the geopolitical conditions and particular national interests that stood behind the German development and humanitarian aid for the Korean states at that time, thus shedding light on the political goals the two German states pursued, and the benefit they expected to derive from their engagement in Korea. Sources consulted include primary archival materials, secondary sources like monographs, journal articles, contemporary newspaper articles, and interviews with contemporary witnesses.
Midbrain dopamine neurons invigorate responses by signaling opportunity costs (tonic dopamine) and promote associative learning by encoding a reward prediction error signal (phasic dopamine). Recent studies on Bayesian sensorimotor control have implicated midbrain dopamine concentration in the integration of prior knowledge and current sensory information. The present behavioral study addressed the contributions of tonic and phasic dopamine in a Bayesian decision-making task by alternating reward magnitude and inferring reward prediction errors. Twenty-four participants were asked to indicate the position of a hidden target stimulus under varying prior and likelihood uncertainty. Trial-by-trial rewards were allocated based on performance and two different reward maxima. Overall, participants’ behavior agreed with Bayesian decision theory, but indicated excessive reliance on likelihood information. These results thus
oppose accounts of statistically optimal integration in sensorimotor control, and suggest that the sensorimotor system is subject to additional decision heuristics. Moreover, higher reward magnitude was not observed to induce enhanced response vigor, and was associated with less Bayes-like integration. In addition, the weighting of prior knowledge and current sensory information proceeded independently of reward prediction errors.
Taken together, these findings suggest that the process of combining prior and likelihood uncertainties in sensorimotor control is largely robust to variations in reward.
In many regions of the world, snow accumulation and melt constitute important components of the hydrologic cycle. With the objective to improve model performance of the hydrological model WASA-SED (Water Availability in Semi-Arid environments - SEDiments) in catchments affected by snow and ice, a physically-based snow routine has been implemented into the model. The snow routine bases on the energy-balance method of the ECHSE (Eco-hydrological Simulation Environment) software. A first test application has been conducted in two sub-basins of the Isábena river catchment (Central Spanish Pre-Pyrenees). Results were validated using satellite-derived snow cover data. Furthermore, a rainfall gauge correction algorithm to restore the liquid precipitation signal of measurements affected by solid precipitation was applied. The snow module proved to be able to capture the dynamics of the snow cover forming during the cold months of the year. The temporary storage of water in the snow cover is able to improve simulations of river discharge. General patterns of the temporal evolution of observed and simulated snow cover fractions coincide. The work conducted only represents a first step in the process of implementation and evaluation of a physically-based snow routine into WASA-SED. Future work is necessary to further improve and test the snow routine and to resolve difficulties that occurred during model applications in the catchment.
Emotions are a complex concept and they are present in our everyday life. Persons on the autism spectrum are said to have difficulties in social interactions, showing deficits in emotion recognition in comparison to neurotypically developed persons. But social-emotional skills are believed to be positively augmented by training. A new adaptive social cognition training tool “E.V.A.” is introduced which teaches emotion recognition from face, voice and body language. One cross-sectional and one longitudinal study with adult neurotypical and autistic participants were conducted. The aim of the cross-sectional study was to characterize the two groups and see if differences in their social-emotional skills exist. The longitudinal study, on the other hand, aimed for detecting possible training effects following training with the new training tool. In addition, in both studies usability assessments were conducted to investigate the perceived usability of the new tool for neurotypical as well as autistic participants. Differences were found between autistic and neurotypical participants in their social-emotional and emotion recognition abilities. Training effects for neurotypical participants in an emotion recognition task were found after two weeks of home training. Similar perceived usability was found for the neurotypical and autistic participants. The current findings suggest that persons with ASC do not have a general deficit in emotion recognition, but are in need for more time to correctly recognize emotions. In addition, findings suggest that training emotion recognition abilities is possible. Further studies are needed to verify if the training effects found for neurotypical participants also manifest in a larger ASC sample.
The forcing from the anthropogenic heat flux (AHF), i.e. the dissipation of primary energy consumed by the human civilisation, produces a direct climate warming. Today, the globally averaged AHF is negligibly small compared to the indirect forcing from greenhouse gas emissions. Locally or regionally, though, it has a significant impact. Historical observations show a constant exponential growth of worldwide energy production. A continuation of this trend might be fueled or even amplified by the exploration of new carbon-free energy sources like fusion power. In such a scenario, the impacts of the AHF become a relevant factor for anthropogenic post-greenhouse gas climate change on the global scale, as well.
This master thesis aims at estimating the climate impacts of such a growing AHF forcing. In the first part of this work, the AHF is built into simple and conceptual, zero- and one-dimensional Energy Balance Models (EBMs), providing quick order of magnitude estimations of the temperature impact. In the one-dimensional EBM, the ice-albedo feedback from enhanced ice melting due to the AHF increases the temperature impact significantly compared to the zero-dimensional EBM.
Additionally, the forcing is built into a climate model of intermediate complexity, CLIMBER-3α. This allows for the investigation of the effect of localised AHF and gives further insights into the impact of the AHF on processes like the ocean heat uptake, sea ice and snow pattern changes
and the ocean circulation.
The global mean temperature response from the AHF today is of the order of 0.010 − 0.016 K in all reasonable model configurations tested. A transient tenfold increase of this forcing heats up the Earth System additionally by roughly 0.1 − 0.2 K in the presented models. Further growth
can also affect the tipping probability of certain climate elements.
Most renewable energy sources do not or only partially contribute to the AHF forcing as the energy from these sources dissipates anyway. Hence, the transition to a (carbon-free) renewable energy mix, which, in particular, does not rely on nuclear power, eliminates the local and global climate impacts from the increasing AHF forcing, independent of the growth of energy production.