Does facial soft tissue protect against zygomatic fractures?: results of a finite element analysis

Introduction: Zygomatic fractures form a major entity in craniomaxillofacial traumatology. Few studies have dealt with biomechanical basics and none with the role of the facial soft tissues. Therefore this study should investigate, whether facial soft tissue plays a protecting role in lateral midfacial trauma

Mobile Kommunikation. Teilvorhaben: Halbleitersendemodule fuer Kommunikationssysteme im 30-50 GHz-Bereich Abschlussbericht

The project 'GaAs Power Modules for Communication Systems in the Frequency Range 30-50 GHz' is embedded in the research program 'Mobile Communication' founded by the german Ministry of Education and Research (BMBF). In this work theoretical studies and basic technologies for the integration of 1 Watt power modules with cascaded power cells in flip chip technology were realized. In order to remove the power losses of the unthinned coplanar power cells, additionally to the electrical bump interconnects thermal bumps near the gate fingers on the source pads and high thermal conductive aluminum nitride substrates have been used. The influence of the thermal bump interconnects to the electrical characteristics of the power cells at high frequencies was determined by on wafer measurements. In order to establish a substrate integrated housing technology for frequencies up to 70 GHz coplanar feed through transmission lines have been realized by use of thin film multilayer technology with 25 #mu#m thick polyimide dielectrics. Manufacturing of the GaAs power cells was done in cooperation with Fraunhofer Institute IAF, Freiburg, and electromagnetic simulation of feed throughs, bump connections and parasitic modes in cooperation with Ferdinand braun Institute, Berlin. (orig.)Available from TIB Hannover: F99B1319+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEBundesministerium fuer Bildung und Forschung (BMBF), Bonn (Germany)DEGerman

QCD on the Cell Broadband Engine.

We evaluate IBM's Enhanced Cell Broadband Engine (BE) as a possible building block of a new generation of lattice QCD machines. The Enhanced Cell BE will provide full support of double-precision floating-point arithmetics, including IEEE-compliant rounding. We have developed a performance model and applied it to relevant lattice QCD kernels. The performance estimates are supported by micro- and application-benchmarks that have been obtained on currently available Cell BE-based computers, such as IBM QS20 blades and PlayStation 3. The results are encouraging and show that this processor is an interesting option for lattice QCD applications. For a massively parallel machine on the basis of the Cell BE, an application-optimized network needs to be developed.Comment: 7 pages, 3 figures, contribution to Lattice 2007 (Regensburg, Germany

QCD on the Cell Broadband Engine

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MIA - A free and open source software for gray scale medical image analysis

Background Gray scale images make the bulk of data in bio-medical image analysis, and hence, the main focus of many image processing tasks lies in the processing of these monochrome images. With ever improving acquisition devices, spatial and temporal image resolution increases, and data sets become very large. Various image processing frameworks exists that make the development of new algorithms easy by using high level programming languages or visual programming. These frameworks are also accessable to researchers that have no background or little in software development because they take care of otherwise complex tasks. Specifically, the management of working memory is taken care of automatically, usually at the price of requiring more it. As a result, processing large data sets with these tools becomes increasingly difficult on work station class computers. One alternative to using these high level processing tools is the development of new algorithms in a languages like C++, that gives the developer full control over how memory is handled, but the resulting workflow for the prototyping of new algorithms is rather time intensive, and also not appropriate for a researcher with little or no knowledge in software development. Another alternative is in using command line tools that run image processing tasks, use the hard disk to store intermediate results, and provide automation by using shell scripts. Although not as convenient as, e.g. visual programming, this approach is still accessable to researchers without a background in computer science. However, only few tools exist that provide this kind of processing interface, they are usually quite task specific, and don’t provide an clear approach when one wants to shape a new command line tool from a prototype shell script. Results The proposed framework, MIA, provides a combination of command line tools, plug-ins, and libraries that make it possible to run image processing tasks interactively in a command shell and to prototype by using the according shell scripting language. Since the hard disk becomes the temporal storage memory management is usually a non-issue in the prototyping phase. By using string-based descriptions for filters, optimizers, and the likes, the transition from shell scripts to full fledged programs implemented in C++ is also made easy. In addition, its design based on atomic plug-ins and single tasks command line tools makes it easy to extend MIA, usually without the requirement to touch or recompile existing code. Conclusion In this article, we describe the general design of MIA, a general purpouse framework for gray scale image processing. We demonstrated the applicability of the software with example applications from three different research scenarios, namely motion compensation in myocardial perfusion imaging, the processing of high resolution image data that arises in virtual anthropology, and retrospective analysis of treatment outcome in orthognathic surgery. With MIA prototyping algorithms by using shell scripts that combine small, single-task command line tools is a viable alternative to the use of high level languages, an approach that is especially useful when large data sets need to be processed