Analysis of red and yellow ochre samples from Clearwell Caves and Catalhoyuk by vibrational spectroscopy and other techniques

Ochre samples excavated from the neolithic site at Qatalhoyuk, Turkey have been compared with "native" ochres from Clearwell Caves, UK using infrared spectroscopy backed up by Raman spectroscopy, scanning electron microscopy (with energy-dispersive X-rays (EDX) analysis), powder X-ray diffraction, diffuse reflection UV-Vis and atomic absorption spectroscopies. For the Clearwell Caves ochres, which range in colour from yellow-orange to red-brown, it is shown that the colour is related to the nature of the chromophore present and not to any differences in particle size. The darker red ochres contain predominantly haematite while the yellow ochre contains only goethite. The ochres from Qatalhoyuk contain only about one-twentieth of the levels of iron found in the Clearwell Caves ochres. The iron oxide pigment (haematite in all cases studied here) has been mixed with a soft lime plaster which also contains calcite and silicate (clay) minerals. (C) 2003 Elsevier B.V. All rights reserved.

A singular vector perspective of 4D-Var: Filtering and interpolation

Four-dimensional variational data assimilation (4D-Var) combines the information from a time sequence of observations with the model dynamics and a background state to produce an analysis. In this paper, a new mathematical insight into the behaviour of 4D-Var is gained from an extension of concepts that are used to assess the qualitative information content of observations in satellite retrievals. It is shown that the 4D-Var analysis increments can be written as a linear combination of the singular vectors of a matrix which is a function of both the observational and the forecast model systems. This formulation is used to consider the filtering and interpolating aspects of 4D-Var using idealized case-studies based on a simple model of baroclinic instability. The results of the 4D-Var case-studies exhibit the reconstruction of the state in unobserved regions as a consequence of the interpolation of observations through time. The results also exhibit the filtering of components with small spatial scales that correspond to noise, and the filtering of structures in unobserved regions. The singular vector perspective gives a very clear view of this filtering and interpolating by the 4D-Var algorithm and shows that the appropriate specification of the a priori statistics is vital to extract the largest possible amount of useful information from the observations. Copyright © 2005 Royal Meteorological Society

Energy separation of neutrons scattered at small angles from silicon using time-of-flight techniques

The time-of-flight technique is used on a small-angle neutron scattering instrument to separate the energies of the scattered neutrons, in order to determine the origin of the temperature-dependent scattering observed from silicon at Q > similar to 0.1 angstrom(-1). A quantitative analysis of the results in comparison with the phonon dispersion curves, determined by Dolling using a triple-axis neutron spectrometer, shows that the temperature-dependent scattering can be understood in terms of Umklapp processes whereby neutrons gain energy from phonons.

Improving flood models using LiDAR: progress and problems

Airborne scanning laser altimetry (LiDAR) is an important new data source for river flood modelling. LiDAR can give dense and accurate DTMs of floodplains for use as model bathymetry. Spatial resolutions of 0.5m or less are possible, with a height accuracy of 0.15m. LiDAR gives a Digital Surface Model (DSM), so vegetation removal software (e.g. TERRASCAN) must be used to obtain a DTM. An example used to illustrate the current state of the art will be the LiDAR data provided by the EA, which has been processed by their in-house software to convert the raw data to a ground DTM and separate vegetation height map. Their method distinguishes trees from buildings on the basis of object size. EA data products include the DTM with or without buildings removed, a vegetation height map, a DTM with bridges removed, etc. Most vegetation removal software ignores short vegetation less than say 1m high. We have attempted to extend vegetation height measurement to short vegetation using local height texture. Typically most of a floodplain may be covered in such vegetation. The idea is to assign friction coefficients depending on local vegetation height, so that friction is spatially varying. This obviates the need to calibrate a global floodplain friction coefficient. It’s not clear at present if the method is useful, but it’s worth testing further. The LiDAR DTM is usually determined by looking for local minima in the raw data, then interpolating between these to form a space-filling height surface. This is a low pass filtering operation, in which objects of high spatial frequency such as buildings, river embankments and walls may be incorrectly classed as vegetation. The problem is particularly acute in urban areas. A solution may be to apply pattern recognition techniques to LiDAR height data fused with other data types such as LiDAR intensity or multispectral CASI data. We are attempting to use digital map data (Mastermap structured topography data) to help to distinguish buildings from trees, and roads from areas of short vegetation. The problems involved in doing this will be discussed. A related problem of how best to merge historic river cross-section data with a LiDAR DTM will also be considered. LiDAR data may also be used to help generate a finite element mesh. In rural area we have decomposed a floodplain mesh according to taller vegetation features such as hedges and trees, so that e.g. hedge elements can be assigned higher friction coefficients than those in adjacent fields. We are attempting to extend this approach to urban area, so that the mesh is decomposed in the vicinity of buildings, roads, etc as well as trees and hedges. A dominant points algorithm is used to identify points of high curvature on a building or road, which act as initial nodes in the meshing process. A difficulty is that the resulting mesh may contain a very large number of nodes. However, the mesh generated may be useful to allow a high resolution FE model to act as a benchmark for a more practical lower resolution model. A further problem discussed will be how best to exploit data redundancy due to the high resolution of the LiDAR compared to that of a typical flood model. Problems occur if features have dimensions smaller than the model cell size e.g. for a 5m-wide embankment within a raster grid model with 15m cell size, the maximum height of the embankment locally could be assigned to each cell covering the embankment. But how could a 5m-wide ditch be represented? Again, this redundancy has been exploited to improve wetting/drying algorithms using the sub-grid-scale LiDAR heights within finite elements at the waterline.

Best Available Techniques (BAT) and coal fired power stations: Can the energy gap be plugged without increasing emissions?

At present, there is much anxiety regarding the security of energy supplies; for example, the UK and other European States are set to become increasingly dependant upon imports of natural gas from states with which political relations are often strained. These uncertainties are felt acutely by the electricity generating sector, which is facing major challenges regarding the choice of fuel mix in the years ahead. Nuclear energy may provide an alternative; however, in the UK, progress in replacing the first generation reactors is exceedingly slow. A number of operators are looking to coal as a means of plugging the energy gap. However, in the light of ever more stringent legal controls on emissions, this step cannot be taken without the adoption of sophisticated pollution abatement technology. This article examines the role which legal concepts such as Best Available Techniques (BAT) must play in bringing about these changes.

Particle filtering in geophysical systems

The application of particle filters in geophysical systems is reviewed. Some background on Bayesian filtering is provided, and the existing methods are discussed. The emphasis is on the methodology, and not so much on the applications themselves. It is shown that direct application of the basic particle filter (i.e., importance sampling using the prior as the importance density) does not work in high-dimensional systems, but several variants are shown to have potential. Approximations to the full problem that try to keep some aspects of the particle filter beyond the Gaussian approximation are also presented and discussed.

Whole crop cereals 2. Prediction of apparent digestibility and energy value from in vitro digestion techniques and near infrared reflectance spectroscopy and of chemical composition by near infrared reflectance spectroscopy

Samples of whole crop wheat (WCW, n = 134) and whole crop barley (WCB, n = 16) were collected from commercial farms in the UK over a 2-year period (2003/2004 and 2004/2005). Near infrared reflectance spectroscopy (NIRS) was compared with laboratory and in vitro digestibility measures to predict digestible organic matter in the dry matter (DOMD) and metabolisable energy (ME) contents measured in vivo using sheep. Spectral models using the mean spectra of two scans were compared with those using individual spectra (duplicate spectra). Overall NIRS accurately predicted the concentration of chemical components in whole crop cereals apart from crude protein. ammonia-nitrogen, water-soluble carbohydrates, fermentation acids and solubility values. In addition. the spectral models had higher prediction power for in vivo DOMD and ME than chemical components or in vitro digestion methods. Overall there Was a benefit from the use of duplicate spectra rather than mean spectra and this was especially so for predicting in vivo DOMD and ME where the sample population size was smaller. The spectral models derived deal equally well with WCW and WCB and Would he of considerable practical value allowing rapid determination of nutritive value of these forages before their use in diets of productive animals. (C) 2008 Elsevier B.V. All rights reserved.

Farmers' attitudes towards techniques for improving oestrus detection in dairy herds in South West England

Unidentified heats contribute to declining fertility rates in English dairy herds. Several techniques have been advocated to improve heat detection rates. Despite demonstrable technical efficacy and cost-effectiveness, uptake is low. A study in South West England used the Theory of Reasoned Action (TORA) to explore dairy farmers' attitudes and beliefs towards heat detection techniques. Few farmers were convinced that following prescribed observation times, milk progesterone testing and using pedometers would fit their system or improve on their current heat detection practices. Perceived difficulty of using a technique was not a constraint on adoption. Without promotion that addresses identified barriers and drivers to adoption, little change in current practice can be expected. (c) 2006 Elsevier B.V. All rights reserved.

Time patterns in UK demand for alcohol and tobacco: an application of the EM algorithm

Capturing the pattern of structural change is a relevant task in applied demand analysis, as consumer preferences may vary significantly over time. Filtering and smoothing techniques have recently played an increasingly relevant role. A dynamic Almost Ideal Demand System with random walk parameters is estimated in order to detect modifications in consumer habits and preferences, as well as changes in the behavioural response to prices and income. Systemwise estimation, consistent with the underlying constraints from economic theory, is achieved through the EM algorithm. The proposed model is applied to UK aggregate consumption of alcohol and tobacco, using quarterly data from 1963 to 2003. Increased alcohol consumption is explained by a preference shift, addictive behaviour and a lower price elasticity. The dynamic and time-varying specification is consistent with the theoretical requirements imposed at each sample point. (c) 2005 Elsevier B.V. All rights reserved.

In vitro cumulative gas production techniques: History, methodological considerations and challenges

Methodology used to measure in vitro gas production is reviewed to determine impacts of sources of variation on resultant gas production profiles (GPP). Current methods include measurement of gas production at constant pressure (e.g., use of gas tight syringes), a system that is inexpensive, but may be less sensitive than others thereby affecting its suitability in some situations. Automated systems that measure gas production at constant volume allow pressure to accumulate in the bottle, which is recorded at different times to produce a GPP, and may result in sufficiently high pressure that solubility of evolved gases in the medium is affected, thereby resulting in a recorded volume of gas that is lower than that predicted from stoichiometric calculations. Several other methods measure gas production at constant pressure and volume with either pressure transducers or sensors, and these may be manual, semi-automated or fully automated in operation. In these systems, gas is released as pressure increases, and vented gas is recorded. Agitating the medium does not consistently produce more gas with automated systems, and little or no effect of agitation was observed with manual systems. The apparatus affects GPP, but mathematical manipulation may enable effects of apparatus to be removed. The amount of substrate affects the volume of gas produced, but not rate of gas production, provided there is sufficient buffering capacity in the medium. Systems that use a very small amount of substrate are prone to experimental error in sample weighing. Effect of sample preparation on GPP has been found to be important, but further research is required to determine the optimum preparation that mimics animal chewing. Inoculum is the single largest source of variation in measuring GPP, as rumen fluid is variable and sampling schedules, diets fed to donor animals and ratios of rumen fluid/medium must be selected such that microbial activity is sufficiently high that it does not affect rate and extent of fermentation. Species of donor animal may also cause differences in GPP. End point measures can be mathematically manipulated to account for species differences, but rates of fermentation are not related. Other sources of inocula that have been used include caecal fluid (primarily for investigating hindgut fermentation in monogastrics), effluent from simulated rumen fermentation (e.g., 'Rusitec', which was as variable as rumen fluid), faeces, and frozen or freeze-dried rumen fluid (which were both less active than fresh rumen fluid). Use of mixtures of cell-free enzymes, or pure cultures of bacteria, may be a way of increasing GPP reproducibility, while reducing reliance on surgically modified animals. However, more research is required to develop these inocula. A number of media have been developed which buffer the incubation and provide relevant micro-nutrients to the microorganisms. To date, little research has been completed on relationships between the composition of the medium and measured GPP. However, comparing GPP from media either rich in N or N-free, allows assessment of contributions of N containing compounds in the sample. (c) 2005 Published by Elsevier B.V.