Common knowledge of payoff uncertainty in games

Using epistemic logic, we provide a non-probabilistic way to formalise payoff uncertainty, that is, statements such as 'player i has approximate knowledge about the utility functions of player j.' We show that on the basis of this formalisation common knowledge of payoff uncertainty and rationality (in the sense of excluding weakly dominated strategies, due to Dekel and Fudenberg (1990)) characterises a new solution concept we have called 'mixed iterated strict weak dominance.'</p

GAOS: Spatial optimisation of crop and nature within agricultural fields

This paper proposes and demonstrates a spatial optimiser that allocates areas of inefficient machine manoeuvring to field margins thus improving the use of available space and supporting map-based Controlled Traffic Farming. A prototype web service (GAOS) allows farmers to optimise tracks within their fields and explore planning alternatives prior to downloading the plans to their RTK GPS-guided steering system. GAOS retrieves accurate data on field geometry from a geo-database. Via a web interface, the farmer sets options regarding operation properties, potential locations for field margins and headlands, etc. Next, an optimisation script that employs an open source geospatial library (osgeo.ogr) is called. The objective function considers costs involved with un-cropped areas, turning at headlands and subsidies received for field margins. Optimisation results are stored in a database and are available for (1) viewing via the web interface, (2) downloading to the GPS-guided steering system and (3) communication to third parties

Overleving van Coxiella burnetii in geitenmest : eindrapportage

De afname van het aantal bacteriën in geitenmest is bestudeerd onder omstandigheden, zoals die zich in opgeslagen geitenmest voordoen. De afname van het aantal bacteriën bij verschillende temperaturen wordt weergegeven door middel van de decimale reductietijd (DRT of Dwaarde). De DRT is de tijd die nodig is om het aantal bacteriën met een factor 10 te laten afnemen bij een bepaalde temperatuur. In dit onderzoek is de DRT voor C. burnetii in geitenpotstalmest bij verschillende temperaturen bepaald

Detection of Coxiella burnetii in complex matrices by using multiplex quantitative PCR during a major Q fever outbreak in the Netherlands

Q fever, caused by Coxiella burnetii, is a zoonosis with a worldwide distribution. A large rural area in the southeast of the Netherlands was heavily affected by Q fever between 2007 and 2009. This initiated the development of a robust and internally controlled multiplex quantitative PCR (qPCR) assay for the detection of C. burnetii DNA in veterinary and environmental matrices on suspected Q fever-affected farms. The qPCR detects three C. burnetii targets (icd, com1, and IS1111) and one Bacillus thuringiensis internal control target (cry1b). Bacillus thuringiensis spores were added to samples to control both DNA extraction and PCR amplification. The performance of the qPCR assay was investigated and showed a high efficiency; a limit of detection of 13.0, 10.6, and 10.4 copies per reaction for the targets icd, com1, and IS1111, respectively; and no crossreactivity with the nontarget organisms tested. Screening for C. burnetii DNA on 29 suspected Q fever-affected farms during the Q fever epidemic in 2008 showed that swabs from dust-accumulating surfaces contained higher levels of C. burnetii DNA than vaginal swabs from goats or sheep. PCR inhibition by coextracted substances was observed in some environmental samples, and 10- or 100-fold dilutions of samples were sufficient to obtain interpretable signals for both the C. burnetii targets and the internal control. The inclusion of an internal control target and three C. burnetii targets in one multiplex qPCR assay showed that complex veterinary and environmental matrices can be screened reliably for the presence of C. burnetii DNA during an outbreak. © 2011, American Society for Microbiology