Structure-preserving space-time discretization in a mixed framework for multi-field problems in large strain elasticity

The present work deals with the design of structure-preserving numerical methods in the field of nonlinear elastodynamics with an extension to multi-field problems. A new approach to the design of energy-momentum (EM) consistent time-stepping schemes for nonlinear elastodynamics is proposed. Moreover, we extend the formalism to multi-field problems

Heterogene Goldkatalyse: Aerobe Oxidation von Fettsäurederivaten und theoretische Betrachtungen zur Bestimmung der spezifischen Goldoberfläche

Diese Arbeit beschäftigt sich mit der Umsetzung von oxidierten Fettsäurederivaten an Gold-Trägerkatalysatoren. Dabei wird erstmals die Gold-katalysierte aerob-oxidative Spaltung von dihydroxylierten Fettsäurespezies zu mittellangen Mono- und Dicarbonsäuren beschrieben. Daneben liegt ein Fokus auf der Bestimmung der spezifischen Goldoberfläche des Katalysators, die einen präziseren Zugang zur katalytischen Aktivität ermöglicht. Die zur Ermittlung der spezifischen Goldoberfläche notwendige Berechnungsformel wurde unter Berücksichtigung aktueller Erkenntnisse weiterentwickelt.This Ph.D. thesis deals with the conversion of oxidized fatty acid derivatives on supported Gold catalysts. For the first time, the Gold catalyzed aerobic oxidative cleavage of dihydroxylated fatty acid species was described. Furthermore, it was focused on the determination of the specific Gold surface, which allows a more precise excess to the catalytic activity of those catalysts. The calculation formula for the specific Gold surface, taking latest scientific findings into account, was further enhanced

Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent

Gaussian processes are a powerful framework for quantifying uncertainty and for sequential decision-making but are limited by the requirement of solving linear systems. In general, this has a cubic cost in dataset size and is sensitive to conditioning. We explore stochastic gradient algorithms as a computationally efficient method of approximately solving these linear systems: we develop low-variance optimization objectives for sampling from the posterior and extend these to inducing points. Counterintuitively, stochastic gradient descent often produces accurate predictions, even in cases where it does not converge quickly to the optimum. We explain this through a spectral characterization of the implicit bias from non-convergence. We show that stochastic gradient descent produces predictive distributions close to the true posterior both in regions with sufficient data coverage, and in regions sufficiently far away from the data. Experimentally, stochastic gradient descent achieves state-of-the-art performance on sufficiently large-scale or ill-conditioned regression tasks. Its uncertainty estimates match the performance of significantly more expensive baselines on a large-scale Bayesian optimization task

Stochastic Gradient Descent for Gaussian Processes Done Right

We study the optimisation problem associated with Gaussian process regression using squared loss. The most common approach to this problem is to apply an exact solver, such as conjugate gradient descent, either directly, or to a reduced-order version of the problem. Recently, driven by successes in deep learning, stochastic gradient descent has gained traction as an alternative. In this paper, we show that when done right\unicode{x2014}by which we mean using specific insights from the optimisation and kernel communities\unicode{x2014}this approach is highly effective. We thus introduce a particular stochastic dual gradient descent algorithm, that may be implemented with a few lines of code using any deep learning framework. We explain our design decisions by illustrating their advantage against alternatives with ablation studies and show that the new method is highly competitive. Our evaluations on standard regression benchmarks and a Bayesian optimisation task set our approach apart from preconditioned conjugate gradients, variational Gaussian process approximations, and a previous version of stochastic gradient descent for Gaussian processes. On a molecular binding affinity prediction task, our method places Gaussian process regression on par in terms of performance with state-of-the-art graph neural networks

Odour Maps in the Brain of Butterflies with Divergent Host-Plant Preferences

Butterflies are believed to use mainly visual cues when searching for food and oviposition sites despite that their olfactory system is morphologically similar to their nocturnal relatives, the moths. The olfactory ability in butterflies has, however, not been thoroughly investigated. Therefore, we performed the first study of odour representation in the primary olfactory centre, the antennal lobes, of butterflies. Host plant range is highly variable within the butterfly family Nymphalidae, with extreme specialists and wide generalists found even among closely related species. Here we measured odour evoked Ca2+ activity in the antennal lobes of two nymphalid species with diverging host plant preferences, the specialist Aglais urticae and the generalist Polygonia c-album. The butterflies responded with stimulus-specific combinations of activated glomeruli to single plant-related compounds and to extracts of host and non-host plants. In general, responses were similar between the species. However, the specialist A. urticae responded more specifically to its preferred host plant, stinging nettle, than P. c-album. In addition, we found a species-specific difference both in correlation between responses to two common green leaf volatiles and the sensitivity to these compounds. Our results indicate that these butterflies have the ability to detect and to discriminate between different plant-related odorants

The psychosocial experiences of breast cancer amongst Black, South Asian and White survivors: do differences exist between ethnic groups?

Copyright © 2016 John Wiley & Sons, Ltd. Background: Very little UK-based research has examined breast cancer-related experiences of Black and Minority Ethnic populations, and we do not know whether the psychosocial impact of diagnosis and treatment in this group is any different to that of White women. Therefore, this study examined similarities and differences amongst Black, South Asian and White breast cancer survivors. Methods: A quantitative, cross-sectional survey was conducted; 173 breast cancer survivors (80 White, 53 South Asian and 40 Black) completed a questionnaire, which assessed psychological functioning, social support, body image and beliefs about cancer. Results: Significant differences (p < 0.05) were reported between White and South Asian participants: compared with White women, South Asian participants reported higher levels of anxiety and depression, poorer quality of life and held higher levels of internal and fatalistic beliefs pertaining to cancer. Black and South Asian women reported higher levels of body image concerns than White women, and held stronger beliefs that God was in control of their cancer. South Asian women turned to religion as a source of support more than Black and White women. Conclusion: This study enhances current understanding of the experience and impact of breast cancer amongst Black and South Asian women, and demonstrates similarities and differences between the ethnic groups. The findings highlight implications for healthcare professionals, particularly in relation to providing culturally sensitive care and support to their patients. Copyright © 2016 John Wiley & Sons, Ltd

Characterization of ARF-BP1/HUWE1 Interactions with CTCF, MYC, ARF and p53 in MYC-Driven B Cell Neoplasms

Transcriptional activation of MYC is a hallmark of many B cell lineage neoplasms. MYC provides a constitutive proliferative signal but can also initiate ARF-dependent activation of p53 and apoptosis. The E3 ubiquitin ligase, ARF-BP1, encoded by HUWE1, modulates the activity of both the MYC and the ARF-p53 signaling pathways, prompting us to determine if it is involved in the pathogenesis of MYC-driven B cell lymphomas. ARF-BP1 was expressed at high levels in cell lines from lymphomas with either wild type or mutated p53 but not in ARF-deficient cells. Downregulation of ARF-BP1 resulted in elevated steady state levels of p53, growth arrest and apoptosis. Co-immunoprecipitation studies identified a multiprotein complex comprised of ARF-BP1, ARF, p53, MYC and the multifunctional DNA-binding factor, CTCF, which is involved in the transcriptional regulation of MYC, p53 and ARF. ARF-BP1 bound and ubiquitylated CTCF leading to its proteasomal degradation. ARF-BP1 and CTCF thus appear to be key cofactors linking the MYC proliferative and p53-ARF apoptotic pathways. In addition, ARF-BP1 could be a therapeutic target for MYC-driven B lineage neoplasms, even if p53 is inactive, with inhibition reducing the transcriptional activity of MYC for its target genes and stabilizing the apoptosis-promoting activities of p53

The population-based oncological health care study OVIS – recruitment of the patients and analysis of the non-participants

<p>Abstract</p> <p>Background</p> <p>The ageing of the population is expected to bring an enormous growth in demand for oncological health care. In order to anticipate and respond to future trends, cancer care needs to be critically evaluated. The present study explores the possibility of conducting representative and population-based research on cancer care on the basis of data drawn from the Cancer Registry.</p> <p>Methods</p> <p>A population-based state-wide cohort study (OVIS) has been carried out in Schleswig-Holstein, Germany. All patients with malignant melanoma, breast, or prostate cancer were identified in the Cancer Registry. Epidemiological data were obtained for all the patients and screened for study eligibility. A postal questionnaire requesting information on diagnosis, therapy, QoL and aftercare was sent to eligible patients.</p> <p>Results</p> <p>A total of 11,489 persons diagnosed with the cancer types of interest in the period from January 2002 to July 2004 were registered in the Cancer Registry. Of the 5,354 (47%) patients who gave consent for research, 4,285 (80% of consenters) completed the questionnaire. In terms of relevant epidemiological variables, participants with melanoma were not found to be different from non-participants with the same diagnosis. However, participants with breast or prostate cancer were slightly younger and had smaller tumours than patients who did not participate in our study.</p> <p>Conclusion</p> <p>Population-based cancer registry data proved to be an invaluable resource for both patient recruitment and non-participant analysis. It can help improve our understanding of the strength and nature of differences between participants and non-respondents. Despite minor differences observed in breast and prostate cancer, the OVIS-sample seems to represent the source population adequately.</p