7,591 research outputs found
The arable farmer as the assessor of within-field soil variation
Feasible, fast and reliable methods of mapping within-field variation are required for precision agriculture. Within precision agriculture research much emphasis has been put on technology, whereas the knowledge that farmers have and ways to explore it have received little attention. This research characterizes and examines the spatial knowledge arable farmers have of their fields and explores whether it is a suitable starting point to map the within-field variation of soil properties. A case study was performed in the Hoeksche Waard, the Netherlands, at four arable farms. A combination of semi-structured interviews and fieldwork was used to map spatially explicit knowledge of within-field variation. At each farm, a field was divided into internally homogeneous units as directed by the farmer, the soil of the units was sampled and the data were analysed statistically. The results show that the farmers have considerable spatial knowledge of their fields. Furthermore, they apply this knowledge intuitively during various field management activities such as fertilizer application, soil tillage and herbicide application. The sample data on soil organic matter content, clay content and fertility show that in general the farmers’ knowledge formed a suitable starting point for mapping within-field variation in the soil. Therefore, it should also be considered as an important information source for highly automated precision agriculture systems
Multiphase sampling using expected value of information
This paper explores multiphase or infill sampling to reduce uncertainty after an initial sample has been taken and analysed to produce a map of the probability of some hazard. New observations are iteratively added by maximising the global expected value of information of the points. This is equivalent to minimisation of global misclassification costs. The method accounts for measurement error and different costs of type I and type II errors. Constraints imposed by a mobile sensor web can be accommodated using cost distances rather than Euclidean distances to decide which sensor moves to the next sample location. Calculations become demanding when multiple sensors move simultaneously. In that case, a genetic algorithm can be used to find sets of suitable new measurement locations. The method was implemented using R software for statistical computing and contributed libraries and it is demonstrated using a synthetic data set
Fluctuation, time-correlation function and geometric Phase
We establish a fluctuation-correlation theorem by relating the quantum
fluctuations in the generator of the parameter change to the time integral of
the quantum correlation function between the projection operator and force
operator of the ``fast'' system. By taking a cue from linear response theory we
relate the quantum fluctuation in the generator to the generalised
susceptibility. Relation between the open-path geometric phase, diagonal
elements of the quantum metric tensor and the force-force correlation function
is provided and the classical limit of the fluctuation-correlation theorem is
also discussed.Comment: Latex, 12 pages, no figures, submitted to J. Phys. A: Math & Ge
Process developments in electrochemical arc machining.
SIGLEAvailable from British Library Document Supply Centre- DSC:DX84146 / BLDSC - British Library Document Supply CentreGBUnited Kingdo
Methodology to generate landscape configurations for use in multi-actor plan-making processes
Imaging of RNA in situ hybridization by atomic force microscopy
In this study we investigated the possibility of imaging internal cellular molecules after cytochemical detection with atomic force microscopy (AFM). To this end, rat 9G and HeLa cells were hybridized with haptenized probes for 28S ribosomal RNA, human elongation factor mRNA and cytomegalovirus immediate early antigen mRNA. The haptenized hybrids were subsequently detected with a peroxidase-labelled antibody and visualized with 3,3'-diaminobenzidine (DAB). The influence of various scanning conditions on cell morphology and visibility of the signal was investigated. In order to determine the influence of ethanol dehydration on cellular structure and visibility of the DAB precipitate, cells were kept in phosphate-buffered saline (PBS) and scanned under fluid after DAB development or dehydrated and subsequently scanned dry or submerged in PBS. Direct information on the increase in height of cellular structures because of internally precipitated DAB and the height of mock-hybridized cells was available. Results show that internal DAB precipitate can be detected by AFM, with the highest sensitivity in the case of dry cells. Although a relatively large amount of DAB had to be precipitated inside the cell before it was visible by AFM, the resolution of AFM for imaging of RNA–in situ hybridization signals was slightly better than that of conventional optical microscopy. Furthermore, it is concluded that dehydration of the cells has irreversible effects on cellular structure. Therefore, scanning under fluid of previously dehydrated samples cannot be considered as a good representation of the situation before dehydration.\ud
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Environmental factors influencing the spread of the highly pathogenic avian influenza H5N1 virus in wild birds in Europe
A large number of occurrences of the highly pathogenic avian influenza (HPAI) H5N1 virus in wild birds were reported in Europe. The relationship between the occurrence pattern and environmental factors has, however, not yet been explored. This research uses logistic regression to quantify the relationships between anthropogenic or physical environmental factors and HPAI H5N1 occurrences. Our results indicate that HPAI H5N1 occurrences are highly correlated with the following: the increased normalized difference vegetation index (NDVI) in December; intermediate NDVI in March; lower elevations; increased minimum temperatures in January; and reduced precipitation in January. A predictive risk map of HPAI H5N1 occurrences in wild birds in Europe was generated on the basis of five key environmental factors. Independent validation of the risk map showed the predictive model to be of high accuracy (79%). The analysis suggests that HPAI H5N1 occurrences in wild birds are strongly influenced by the availability of food resources and are facilitated by increased temperatures and reduced precipitation. We therefore deduced that HPAI H5N1 occurrences in wild birds in Europe are probably caused by contact with other wild birds and not by contact with domestic poultry. These findings are important considerations for the global surveillance of HPAI H5N1 occurrences in wild birds
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