A Parallel General Purpose Multi-Objective Optimization Framework, with Application to Beam Dynamics

Particle accelerators are invaluable tools for research in the basic and applied sciences, in fields such as materials science, chemistry, the biosciences, particle physics, nuclear physics and medicine. The design, commissioning, and operation of accelerator facilities is a non-trivial task, due to the large number of control parameters and the complex interplay of several conflicting design goals. We propose to tackle this problem by means of multi-objective optimization algorithms which also facilitate a parallel deployment. In order to compute solutions in a meaningful time frame a fast and scalable software framework is required. In this paper, we present the implementation of such a general-purpose framework for simulation-based multi-objective optimization methods that allows the automatic investigation of optimal sets of machine parameters. The implementation is based on a master/slave paradigm, employing several masters that govern a set of slaves executing simulations and performing optimization tasks. Using evolutionary algorithms as the optimizer and OPAL as the forward solver, validation experiments and results of multi-objective optimization problems in the domain of beam dynamics are presented. The high charge beam line at the Argonne Wakefield Accelerator Facility was used as the beam dynamics model. The 3D beam size, transverse momentum, and energy spread were optimized

Computationally-Optimized Bone Mechanical Modeling from High-Resolution Structural Images

Image-based mechanical modeling of the complex micro-structure of human bone has shown promise as a non-invasive method for characterizing bone strength and fracture risk in vivo. In particular, elastic moduli obtained from image-derived micro-finite element (μFE) simulations have been shown to correlate well with results obtained by mechanical testing of cadaveric bone. However, most existing large-scale finite-element simulation programs require significant computing resources, which hamper their use in common laboratory and clinical environments. In this work, we theoretically derive and computationally evaluate the resources needed to perform such simulations (in terms of computer memory and computation time), which are dependent on the number of finite elements in the image-derived bone model. A detailed description of our approach is provided, which is specifically optimized for μFE modeling of the complex three-dimensional architecture of trabecular bone. Our implementation includes domain decomposition for parallel computing, a novel stopping criterion, and a system for speeding up convergence by pre-iterating on coarser grids. The performance of the system is demonstrated on a dual quad-core Xeon 3.16 GHz CPUs equipped with 40 GB of RAM. Models of distal tibia derived from 3D in-vivo MR images in a patient comprising 200,000 elements required less than 30 seconds to converge (and 40 MB RAM). To illustrate the system's potential for large-scale μFE simulations, axial stiffness was estimated from high-resolution micro-CT images of a voxel array of 90 million elements comprising the human proximal femur in seven hours CPU time. In conclusion, the system described should enable image-based finite-element bone simulations in practical computation times on high-end desktop computers with applications to laboratory studies and clinical imaging

Bamberger Federführer. Die besten Texte aus drei Jahren Literaturwettbewerb an der Universität Bamberg (2009-2011)

Im Kreise des Redaktions-Teams der studentischen Hochschulgruppe Feki.de entstand im November 2008 die Idee, einen Literaturwettbewerb an der Universität Bamberg zu etablieren. Das Projekt sollte es Studierenden aller Fachrichtungen ermöglichen, literarisch tätig zu werden und sich mit ihren Texten dem Urteil einer Jury bzw. der Leser zu stellen. Insgesamt drei Mal wurde der Wettbewerb durchgeführt: 2009 wurde die beste Kurzgeschichte zum Thema „Um 20 Uhr am Gabelmoo“ gesucht, im Jahr darauf lautete das Thema schlicht „fertig. Der letzte Wettbewerb stand schließlich unter dem Motto „Heimat“. Die Auswahl der Siegertexte übernahm eine Jury, bestehend aus Vertretern verschiedener Hochschulgruppen – Feki.de, Rezensöhnchen und Ottfried –, Prof. Dr. Andrea Bartl, Inhaberin der Professur für Neuere deutsche Literaturwissenschaft, dem Autor und Kritiker Rolf Bernhard Essig sowie wechselnd den Autoren Nora Gomringer, Kurt Kreiler und Nefvel Cumart. Daneben konnten die Feki.de-Leser über den jeweiligen Publikumspreisträger abstimmen. Neben den Studierenden der Universität Bamberg waren ab dem zweiten Jahr auch Teilnehmer der Schreibwerkstatt der JVA Ebrach eingeladen, ihre Texte einzu­senden. Im Vergleich mit den studentischen Texten boten die Beiträge der Gefangenen einen interessanten Perspektivwechsel für alle Teil­nehmer und Leser. Insgesamt 24 Kurzgeschichten aus den Jahren 2009 bis 2011 haben wir in diesem Band zusammengestellt. Neben den jeweiligen Siegertexten finden sich in der Anthologie auch die Beiträge der JVA-Bewohner zum Thema „fertig“, sowie ausgewählte Texte Studierender, die die Podestplätze nur knapp verfehlten

Utility of the Health of the Nation Outcome Scales (HoNOS) in Predicting Mental Health Service Costs for Patients with Common Mental Health Problems : Historical Cohort Study

BACKGROUND: Few countries have made much progress in implementing transparent and efficient systems for the allocation of mental health care resources. In England there are ongoing efforts by the National Health Service (NHS) to develop mental health 'payment by results' (PbR). The system depends on the ability of patient 'clusters' derived from the Health of the Nation Outcome Scales (HoNOS) to predict costs. We therefore investigated the associations of individual HoNOS items and the Total HoNOS score at baseline with mental health service costs at one year follow-up.METHODS: An historical cohort study using secondary care patient records from the UK financial year 2012-2013. Included were 1,343 patients with 'common mental health problems', represented by ICD-10 disorders between F32-48. Costs were based on patient contacts with community-based and hospital-based mental health services. The costs outcome was transformed into 'high costs' vs 'regular costs' in main analyses.RESULTS: After adjustment for covariates, 11 HoNOS items were not associated with costs. The exception was 'self-injury' with an odds ratio of 1.41 (95% CI 1.10-2.99). Population attributable fractions (PAFs) for the contribution of HoNOS items to high costs ranged from 0.6% (physical illness) to 22.4% (self-injury). After adjustment, the Total HoNOS score was not associated with costs (OR 1.03, 95% CI 0.99-1.07). However, the PAF (33.3%) demonstrated that it might account for a modest proportion of the incidence of high costs.CONCLUSIONS: Our findings provide limited support for the utility of the self-injury item and Total HoNOS score in predicting costs. However, the absence of associations for the remaining HoNOS items indicates that current PbR clusters have minimal ability to predict costs, so potentially contributing to a misallocation of NHS resources across England. The findings may inform the development of mental health payment systems internationally, especially since the vast majority of countries have not progressed past the early stages of this development. Discrepancies between our findings with those from Australia and New Zealand point to the need for further international investigations