82623 research outputs found
Sort by
Heiliges Handwerk oder symbolische Gabe? Deutungsversuche der Textilwerkzeuge im Artemisheiligtum von Amarynthos
No full textEin letzter Aufenthalt in Basel. Die Erforschung von Biographien jüdischer Flüchtlinge im Zweiten Weltkrieg, die auf dem Israelitischen Friedhof in Basel bestattet wurden
No full textEntre prestigio y prejuicio: la percepción de las variedades de la lengua española y las actitudes lingüísticas del alumnado de bach illerato en Suiza Noroccidental - Un estudio basado en cuestionarios
No full text«nothing in him that appeared barbarous»: Eine sinnesgeschichtliche Analyse der Zivilisiertheit in William Snelgraves Reisebericht "A new account of some parts of Guinea, and the slave trade", 1734
No full text
Creating social innovation in urban development through collaborative processes
Get PDFUncertainty is a major factor in urban development as a consequence of a changing society. Major theoretical approaches to urban development, such as place-based leadership or coproduction, emphasize the importance of the public sector. This study aims to enhance the understanding of urban development processes as a collaborative and participatory concept through social innovation. We apply the concept of socially creative milieus to analyze the emergence of social innovation under the constraint of uncertainty. The criteria 'agents of innovation', 'adopters', 'diffusion channels', 'constraints', 'inertia', and 'impacts' are analyzed using a holistic case study in the field of urban development. Our results show that the presence of high social capital supersedes the coercive power of the public sector. By applying the creative milieus approach, environments like the density of networks and contacts in the governance of urban places make innovative development possible
Post mortem temperature and its effect on quantitative magnetic resonance imaging
Get PDFPost mortem magnetic resonance imaging (PMMRI) has the ability to enrich au- topsy results in forensic death investigations and to reveal otherwise undetectable findings due to its high soft tissue contrast. Additionally, PMMRI enables the validation and development of in vivo magnetic resonance imaging (MRI) by the possibility of subsequent histopathological examinations. Nevertheless, due to the cooling of the deceased, PMMRI of the intact body (so called in situ PMMRI) is limited by the temperature sensitivity of the MRI parameters. Therefore, in order to exploit the benefits of PMMRI, temperature correction is inevitable. Prior studies proposed temperature correction methods for PMMRI of the brain using the rectal temperature. However, it is known that the cooling of the body is inhomogenous after death. Thus, the goal of this thesis was to develop an accurate temperature correction model for PMMRI of the brain.
The relations between brain temperature and the in situ PMMRI relaxation param- eters T1, T2 and T∗2, as well as the diffusion parameters mean diffusivity (MD), and fractional anisotropy (FA) were investigated in the first study of this thesis (Publi- cation 1; status accepted). Significant linear relations have been found between the brain temperature and T1, T∗2, MD, and FA in gray matter, as well as T2, T∗2, and MD in white matter. The findings allow the correction of these MRI parameters for the brain temperature and, thus, the analysis of PMMRI independently of the deceased’s temperature. The second study (Publication 2; status accepted) exam- ined to which extent white matter fiber orientation dependent R∗2 depends on the brain temperature and differs between in vivo and post mortem in situ examinations. Decreased R∗2 fiber orientation dependency has been observed post mortem in situ compared to in vivo subjects, which may be attributed primarily to the deceased’s lower brain temperature. The third study (Publication 3; status accepted) revealed the relation between the brain temperature and null point inversion time (TInull) (time point at which the longitudinal magnetization of cerebral spinal fluid (CSF) is zero). A significant linear relation has been found between CSF’s TInull and the temperature. This allows the adaption of TInull for the temperature, leading to an optimal suppression of the CSF signal and, hence, enabling the application of the fluid attenuated inversion recovery (FLAIR) sequence post mortem. Nevertheless, brain temperature measurement is invasive and cannot be acquired in real-time dur- ing the MRI scan due to its required MRI incompatible temperature measurement method. Therefore, in the fourth study (Publication 4; status submitted) the post mortem temperature cooling of different body sites was investigated, in order to find a non invasive and real-time brain temperature model during the MRI scan. It has been found that the forehead temperature correlates linearly with the brain temperature. Thus, a temperature correction model for the MRI parameters using the forehead temperature has been examined (Publication 5; status submitted). A significant temperature sensitivity was found for T2 and MD in white matter, for T1 in cerebral cortex, as well as for T1 and MD in deep gray matter. This enables a real-time and non invasive temperature correction of the parameters taking into account temperature variations during the MRI scan.
As a conclusion, the findings allow the temperature correction in PMMRI, either based on the brain temperature or in real-time based on the forehead temperature
Medical image retrieval for augmenting diagnostic radiology
Get PDFEven though the use of medical imaging to diagnose patients is ubiquitous in clinical settings, their interpretations are still challenging for radiologists. Many factors make this interpretation task difficult, one of which is that medical images sometimes present subtle clues yet are crucial for diagnosis. Even worse, on the other hand, similar clues could indicate multiple diseases, making it challenging to figure out the definitive diagnoses. To help radiologists quickly and accurately interpret medical images, there is a need for a tool that can augment their diagnostic procedures and increase efficiency in their daily workflow. A general-purpose medical image retrieval system can be such a
tool as it allows them to search and retrieve similar cases that are already diagnosed to make comparative analyses that would complement their diagnostic decisions. In this thesis, we contribute to developing such a system by proposing approaches to be integrated as modules of a single system, enabling it to handle various information needs of radiologists and thus augment their diagnostic processes during the interpretation of medical images.
We have mainly studied the following retrieval approaches to handle radiologists’different information needs; i) Retrieval Based on Contents, ii) Retrieval Based on Contents, Patients’ Demographics, and Disease Predictions, and iii) Retrieval Based on Contents and Radiologists’ Text Descriptions. For the first study, we aimed to find an effective feature representation method to distinguish medical images considering their semantics and modalities. To do that, we have experimented different representation techniques based on handcrafted methods (mainly texture features) and deep learning (deep features). Based on the experimental results, we propose an effective feature representation approach and deep learning architectures for learning and extracting medical image contents. For the second study, we present a multi-faceted method that complements image contents with patients’ demographics and deep learning-based disease predictions, making it able to identify similar cases accurately considering the clinical context the radiologists seek.
For the last study, we propose a guided search method that integrates an image with a radiologist’s text description to guide the retrieval process. This method guarantees that the retrieved images are suitable for the comparative analysis to confirm or rule
out initial diagnoses (the differential diagnosis procedure). Furthermore, our method is based on a deep metric learning technique and is better than traditional content-based approaches that rely on only image features and, thus, sometimes retrieve insignificant random images
Shape optimization under constraints on the probability of a quadratic functional to exceed a given treshold
Get PDFThis article is dedicated to shape optimization of elastic materials under random loadings where the particular focus is on the minimization of failure probabilities. Our approach relies on the fact that the area of integration is an ellipsoid in the high-dimensional parameter space when the shape functional of interest is quadratic. We derive the respective expressions for the shape functional and the related shape gradient. As showcase for the numerical implementation, we assume that the random loading is a Gaussian random field. By exploiting the specialties of this setting, we derive an efficient shape optimization algorithm. Numerical results in three spatial dimensions validate the feasibility of our approach
Contrastive analysis of English fan and professional subtitles of Korean TV Drama
Get PDFWe compare fan subtitles and subtitles produced by professionals in order to detect what concepts each of them foreground, and how they differ in register and in translation strategy. Differences are systematically explored with the help of corpus-assisted discourse analysis to contrast two sets of English subtitles from 26 Korean dramas and 451 episodes - fan subtitles from Viki and professional subtitles from Netflix. Results reveal that professional translators show more target text orientation, whereas fan translators position themselves and their readers as expert members of their community, aiming for access to the source text. We find no clear difference in register, but professional subtitles are more concise, whereas Viki subtitles are longer and employ, e.g., hedges and disfluency markers