Entwicklung einer real-time RT-PCR zum Nachweis von equinem Influenzavirus

Equine Influenza ist eine durch Influenza A-Viren verursachte, kontagiöse Respirationserkrankung beim Pferd. In dieser Arbeit wurde eine real-time RT-PCR in einem konservierten Abschnitt des Matrix-Segments des viralen Genoms für die schnelle und sensitive Diagnose von equinen Influenzaviren (EIV) und je eine RT-PCR Methode im Matrix- und im HA-Segment für die molekular-epidemiologische Charakterisierung der Viren entwickelt. Die Primer der real-time RT-PCR sind zu 99.4% der bekannten EIV-Sequenzen und zu 97.7% aller Influenza A-Sequenzen homolog. Die Homologie der Minor Groove Binder (MGB)-Sonde lag bei 99.3% und 99.6%. Diese hohen Werte ermöglichen die Anwendung des Assays für Influenzaviren bei anderen Spezies. Die diagnostische Eignung der Methode wurde mit Hilfe von 20 equinen, 11 porcinen sowie 2 aviären Proben verifiziert. Eine hohe Spezifität für Influenzaviren wurde experimentell und mittels Software-Simulation gezeigt. Die analytische Sensitivität des Tests lag bei 102–103 RNA-Kopien und 100–101 DNA-Kopien, was den Virusnachweis auch bei geringer Virusausscheidung ermöglicht. Alle amplifizierten EIV-Sequenzen konnten phylogenetisch den bekannten Linien zugeordnet werden.

Knowledge transfer in software-maintenance offshore outsourcing

Software-maintenance offshore outsourcing (SMOO) projects have been plagued by tedious knowledge transfer during the service transition to the vendor. Vendor engineers risk being over-strained by the high amounts of novel information, resulting in extra costs that may erode the business case behind offshoring. Although stakeholders may desire to avoid these extra costs by implementing appropriate knowledge transfer practices, little is known on how effective knowledge transfer can be designed and managed in light of the high cognitive loads in SMOO transitions. The dissertation at hand addresses this research gap by presenting and integrating four studies. The studies draw on cognitive load theory, attributional theory, and control theory and they apply qualitative, quantitative, and simulation methods to qualitative data from eight in-depth longitudinal cases. The results suggest that the choice of appropriate learning tasks may be more central to knowledge transfer than the amount of information shared with vendor engineers. Moreover, because vendor staff may not be able to and not dare to effectively self-manage learn-ing tasks during early transition, client-driven controls may be initially required and subsequently faded out. Collectively, the results call for people-based rather than codification-based knowledge management strategies in at least moderately specific and complex software environments.

Space debris attitude simulation - ιOTA (In-Orbit Tumbling Analysis)

Today, there is little knowledge on the attitude state of decommissioned intact objects in Earth orbit. Observational means have advanced in the past years, but are still limited with respect to an accurate estimate of motion vector orientations and magnitude. Especially for the preparation of Active Debris Removal (ADR) missions as planned by ESA’s Clean Space initiative or contingency scenarios for ESA spacecraft like ENVISAT, such knowledge is needed. ESA's “Debris Attitude Motion Measurements and Modelling” project (ESA Contract No. 40000112447), led by the Astronomical Institute of the University of Bern (AIUB), addresses this problem. The goal of the project is to achieve a good understanding of the attitude evolution and the considerable internal and external effects which occur. To characterize the attitude state of selected targets in LEO and GTO, multiple observation methods are combined. Optical observations are carried out by AIUB, Satellite Laser Ranging (SLR) is performed by the Space Research Institute of the Austrian Academy of Sciences (IWF) and radar measurements and signal level determination are provided by the Fraunhofer Institute for High Frequency Physics and Radar Techniques (FHR). The In-Orbit Tumbling Analysis tool (ιOTA) is a prototype software, currently in development by Hyperschall Technologie Göttingen GmbH (HTG) within the framework of the project. ιOTA will be a highly modular software tool to perform short-(days), medium-(months) and long-term (years) propagation of the orbit and attitude motion (six degrees-of-freedom) of spacecraft in Earth orbit. The simulation takes into account all relevant acting forces and torques, including aerodynamic drag, solar radiation pressure, gravitational influences of Earth, Sun and Moon, eddy current damping, impulse and momentum transfer from space debris or micro meteoroid impact, as well as the optional definition of particular spacecraft specific influences like tank sloshing, reaction wheel behaviour, magnetic torquer activity and thruster firing. The purpose of ιOTA is to provide high accuracy short-term simulations to support observers and potential ADR missions, as well as medium-and long-term simulations to study the significance of the particular internal and external influences on the attitude, especially damping factors and momentum transfer. The simulation will also enable the investigation of the altitude dependency of the particular external influences. ιOTA's post-processing modules will generate synthetic measurements for observers and for software validation. The validation of the software will be done by cross-calibration with observations and measurements acquired by the project partners.