Search

AGIAS Generalised Interval Arithmetic Simulator (AGIAS) is a specialised simulator which uses affine arithmetic to model parameter variations. It uses a specialised root-finding algorithm to simulate analogue circuits with parameter variations in one single simulation run. This is a significant speed-up compared to the multiple runs needed by industrialised solutions such as Monte-Carlo (MC) or Worst-Case Analysis (WCA). Currently, AGIAS can simulate analogue circuits only under very specific conditions. In many cases, circuits can only be simulated for certain operating points. If the circuits is to be evaluated in other operating points, the solver becomes numerically unstable and simulation fails. In these cases, interval widths approach infinity. Behavioural modelling of analogue circuits was introduced by researchers working around limitations of simulators. Most early approaches require expert knowledge and insight into the circuit which is modelled. In recent years, Machine Learning techniques for automatic generation of behavioural models have made their way into the field. This thesis combines Machine Learning techniques with affine arithmetic to include the effects of parameter variations into models. Support Vector Machines (SVMs) train two sets of parameters: one slope parameter and one offset parameter. These parameters are replaced by affine forms. Using these two parameters allows affine SVMs to model effects of parameter variations with varying widths. Training requires additional information about maximum and minimum values in addition to the nominal values in the data set. Based on these changes, affine ε Support Vector Machine (ε̂SVR) and ν Support Vector Machine (ν̂SVR) algorithms for regression are presented. To train the affine parameters directly and profit from the Sequential Minimal Optimisation algorithm (SMO)’s selectivity, the SMO is extended to handle the new, larger optimisation problems. The new affine SVMs are tested on analogue circuits that have been chosen based on whether they could be simulated with AGIAS and how strongly non-linear their characteristic function is.

A salience network (SN) anchored in the anterior insula (AI) and dorsal anterior cingulate cortex (dACC) plays a key role in switching between brain networks during salience detection and attention regulation. Previous fMRI studies have associated expectancy behaviors and SN activation with novelty seeking (NS) and reward dependence (RD) personality traits. To address the question of how functional connectivity (FC) in the SN is modulated by internal (expectancy-related) salience assignment and different personality traits, 68 healthy participants performed a salience expectancy task using functional magnetic resonance imaging, and psychophysiological interaction analysis (PPI) was conducted to determine salience-related connectivity changes during these anticipation periods. Correlation was then evaluated between PPI and personality traits, assessed using the temperament and character inventory of 32 male participants. During high salience expectancy, SN-seed regions showed reduced FC to visual areas and parts of the default mode network, but increased FC to the central executive network. With increasing NS, participants showed significantly increasing disconnection between right AI and middle cingulate cortex when expecting high-salience pictures as compared to low-salience pictures, while increased RD also predicted decreased right dACC and caudate FC for high salience expectancy. Our findings suggest a direct link between personality traits and internal salience processing mediated by differential network integration of the SN. SN activity and coordination may therefore be moderated by novelty seeking and reward dependency personality traits, which are associated with risk of addiction. Hum Brain Mapp 38:4064-4077, 2017. © 2017 Wiley Periodicals, Inc.

Compared to childless (nulliparous) women, the breast cancer risk of mothers can be 50% lower. The cause of the protective effect of parity is not yet clarified. However, it has been shown that immune cells of mothers show an enhanced cytotoxicity against tumor cells. Hence, it was assumed that T cells mediate the anti-cancer effect via the recognition of tumor-associated antigens (TAA). Moreo-ver, regulatory T cells (Treg), being essential for the prevention of pathological immune responses, can also suppress anti-tumor immunity. In breast cancer patients, the intratumoral accumulation of Treg cells is associated with a lower overall survival and an increased risk of relapse. Previous studies have revealed the presence of TAA-specific T cells in the blood of breast cancer patients. On the downside, the anti-tumor immunity of these patients is frequently suppressed by TAA-specific Treg cells. The aim of this study was to investigate the induction and characteristics of spontaneous T cell re-sponses against TAA during pregnancy, which may form a lifelong immune protection against breast cancer. Furthermore, we asked whether previous pregnancies may also have an impact on the anti-tumor immunity of breast cancer patients. We isolated peripheral blood T cells from nulliparous and primigravid women, mothers and breast cancer patients and analyzed their TAA specificity, functional properties and phenotype. IFN-γ ELISpot analyses with long synthetic peptides were performed to detect the frequency of TAA specif-ic T cells in blood samples. The impact of TAA-specific Treg cells on anti-tumor immunity was as-sessed by performing the IFN-γ ELISpot analyses before and after depletion of CD4+CD25+ T cells. By applying the Treg-specificity assay, we analyzed the antigenic specificities of these Treg cells. The results of this study indicate a spontaneous induction of anti-tumor immune responses during the first trimester of pregnancy. Highly functional TAA-specific memory T cells were detected in 85% of healthy mothers, but in none of the nulliparous controls. Furthermore, we found that a lifelong immunological memory is formed, that positively impacts on anti-tumor immunity, since TAA-specific T cell responses in mothers with breast cancer were significantly stronger and less impaired by Treg cells, as compared to nullipara. The findings obtained in this thesis support the implementation of a prospective study, which corre-lates the prevalence of TAA-specific T cells with the incidence of breast cancer. Based on this study, the potential benefit of a preventive vaccine is to be estimated, which may be applied to nulliparous women.