Evaluating Cultivars of Subterranean Clover in Monoculture or with Perennial Ryegrass

Over four years, sowing perennial ryegrass (Lolium perenne) with a range of subterranean clover (“sub clover”, Trifolium subterraneum) cultivars was found to reduce the yield of clover per se by 31% and increase pasture yield by 11%. For one high-producing experimental variety, the presence of grass did not reduce clover yield (P\u3c0.001). Clover yield in monoculture plots was poorly correlated with that measured in mixed swards (r = 0.44), but clover yield (± grass) was correlated with total herbage yield (r = 0.94). Clover seed yield was not reduced by the presence of grass. However, in year 2 - but not in the establishment year - grass reduced seed weight. Irrespective of grass treatment, the new late maturing cultivar, Leura outyielded the other commercial cultivars (P\u3c0.05). Enfield and Enfield x Daliak crosses set the most seed and regenerated with a greater density than other cultivars (P\u3c0.05) - apart from Leura. It was concluded that the winter-active, late maturing cultivar, Leura, will compete most successfully with perennial ryegrass

Structural Transitions in a Classical Two-Dimensional Molecule System

The ground state of a classical two-dimensional (2D) system with finite number of charged particles, trapped by two positive impurities charges localized at a distance (zo) from the 2D plane and separated from each other by a distance xp are obtained. The impurities are allowed to carry more than one positive charge. This classical system can form a 2D-like classical molecule that exhibits structural transitions and spontaneous symmetry breaking as a function of the separation between the positive charges before it transforms into two independent 2D-like classical atoms. We also observe structural transitions as a function of the dielectric constant of the substrate which supports the charged particles, in addition to broken symmetry states and unbinding of particles.Comment: 9 pages, 7 figure

Physician diagnosed arthritis, reported arthritis and radiological non-axial osteoarthritis

SummaryObjectiveTo determine the question that best predicts radiographic evidence of non-axial osteoarthritis (OA).DesignThe Melbourne Women's Mid-life Health Project (MWMHP), commenced in 1991, is a population-based prospective study of 438 Australian-born. Two hundred and fifty-seven (57%) women remained in longitudinal assessment in 2002 and 224 (87%) women agreed to undergo X-rays of their hands and knees between 2002 and 2003.MethodsAnnually participants were asked about aches and stiff joints and arthritis or rheumatism. In the eleventh year of follow-up X-rays were scored for evidence of OA using a validated scale, by two investigators who were blinded to questionnaire results. Information on hormone therapy use, physical activity, mood, smoking, body mass index (BMI) and age were obtained by both self-administered and face-to-face questionnaires.ResultsPatient reported physician diagnosed arthritis was the best predictor of radiological OA (ROA). The question had a specificity of 64%, a positive predictive value of 57% and a negative predictive value of 71%. Even the most reliable question about arthritis still had a relatively low specificity for radiologically diagnosed OA. Reporting symptoms were significantly more common in participants who were depressed, those who had a higher negative affect and those with a higher BMI.ConclusionIn large epidemiological studies where questionnaire assessment of OA is required, the greatest accuracy is achieved by asking about physician diagnosed arthritis. Concurrent application of a validated scale for mood is important

Eimeria species occurrence varies between geographic regions and poultry production systems and may influence parasite genetic diversity

Coccidiosis is one of the biggest challenges faced by the global poultry industry. Recent studies have highlighted the ubiquitous distribution of all Eimeria species which can cause this disease in chickens, but intriguingly revealed a regional divide in genetic diversity and population structure for at least one species, Eimeria tenella. The drivers associated with such distinct geographic variation are unclear, but may impact on the occurrence and extent of resistance to anticoccidial drugs and future subunit vaccines. India is one of the largest poultry producers in the world and includes a transition between E. tenella populations defined by high and low genetic diversity. The aim of this study was to identify risk factors associated with the prevalence of Eimeria species defined by high and low pathogenicity in northern and southern states of India, and seek to understand factors which vary between the regions as possible drivers for differential genetic variation. Faecal samples and data relating to farm characteristics and management were collected from 107 farms from northern India and 133 farms from southern India. Faecal samples were analysed using microscopy and PCR to identify Eimeria occurrence. Multiple correspondence analysis was applied to transform correlated putative risk factors into a smaller number of synthetic uncorrelated factors. Hierarchical cluster analysis was used to identify poultry farm typologies, revealing three distinct clusters in the studied regions. The association between clusters and presence of Eimeria species was assessed by logistic regression. The study found that large-scale broiler farms in the north were at greatest risk of harbouring any Eimeria species and a larger proportion of such farms were positive for E. necatrix, the most pathogenic species. Comparison revealed a more even distribution for E. tenella across production systems in south India, but with a lower overall occurrence. Such a polarised region- and system-specific distribution may contribute to the different levels of genetic diversity observed previously in India and may influence parasite population structure across much of Asia and Africa. The findings of the study can be used to prioritise target farms to launch and optimise appropriate anticoccidial strategies for long-term control

Comparison of the HadGEM2 climate-chemistry model against in situ and SCIAMACHY atmospheric methane data

Wetlands are a major emission source of methane (CH4) globally. In this study, we evaluate wetland emission estimates derived using the UK community land surface model (JULES, the Joint UK Land Earth Simulator) against atmospheric observations of methane, including, for the first time, total methane columns derived from the SCIAMACHY instrument on board the ENVISAT satellite. Two JULES wetland emission estimates are investigated: (a) from an offline run driven with Climatic Research Unit–National Centers for Environmental Prediction (CRU-NCEP) meteorological data and (b) from the same offline run in which the modelled wetland fractions are replaced with those derived from the Global Inundation Extent from Multi-Satellites (GIEMS) remote sensing product. The mean annual emission assumed for each inventory (181 Tg CH4 per annum over the period 1999–2007) is in line with other recently published estimates. There are regional differences as the unconstrained JULES inventory gives significantly higher emissions in the Amazon (by ~36 Tg CH4 yr−1) and lower emissions in other regions (by up to 10 Tg CH4 yr−1) compared to the JULES estimates constrained with the GIEMS product. Using the UK Hadley Centre's Earth System model with atmospheric chemistry (HadGEM2), we evaluate these JULES wetland emissions against atmospheric observations of methane. We obtain improved agreement with the surface concentration measurements, especially at high northern latitudes, compared to previous HadGEM2 runs using the wetland emission data set of Fung et al. (1991). Although the modelled monthly atmospheric methane columns reproduce the large-scale patterns in the SCIAMACHY observations, they are biased low by 50 part per billion by volume (ppb). Replacing the HadGEM2 modelled concentrations above 300 hPa with HALOE–ACE assimilated TOMCAT output results in a significantly better agreement with the SCIAMACHY observations. The use of the GIEMS product to constrain the JULES-derived wetland fraction improves the representation of the wetland emissions in JULES and gives a good description of the seasonality observed at surface sites influenced by wetlands, especially at high latitudes. We find that the annual cycles observed in the SCIAMACHY measurements and at many of the surface sites influenced by non-wetland sources cannot be reproduced in these HadGEM2 runs. This suggests that the emissions over certain regions (e.g. India and China) are possibly too high and/or the monthly emission patterns for specific sectors are incorrect. The comparisons presented in this paper show that the performance of the JULES wetland scheme is comparable to that of other process-based land surface models. We identify areas for improvement in this and the atmospheric chemistry components of the HadGEM Earth System model. The Earth Observation data sets used here will be of continued value in future evaluations of JULES and the HadGEM family of models

Patient-reported barriers to accepting a technological adherence package in the MAGNIFY trial.

Peer reviewedPostprin

Green functions for generalized point interactions in 1D: A scattering approach

Recently, general point interactions in one dimension has been used to model a large number of different phenomena in quantum mechanics. Such potentials, however, requires some sort of regularization to lead to meaningful results. The usual ways to do so rely on technicalities which may hide important physical aspects of the problem. In this work we present a new method to calculate the exact Green functions for general point interactions in 1D. Our approach differs from previous ones because it is based only on physical quantities, namely, the scattering coefficients, $R$ and $T$, to construct $G$. Renormalization or particular mathematical prescriptions are not invoked. The simple formulation of the method makes it easy to extend to more general contexts, such as for lattices of $N$ general point interactions; on a line; on a half-line; under periodic boundary conditions; and confined in a box.Comment: Revtex, 9 pages, 3 EPS figures. To be published in PR

Dust Devil Tracks

Dust devils that leave dark- or light-toned tracks are common on Mars and they can also be found on the Earth’s surface. Dust devil tracks (hereinafter DDTs) are ephemeral surface features with mostly sub-annual lifetimes. Regarding their size, DDT widths can range between ∼1 m and ∼1 km, depending on the diameter of dust devil that created the track, and DDT lengths range from a few tens of meters to several kilometers, limited by the duration and horizontal ground speed of dust devils. DDTs can be classified into three main types based on their morphology and albedo in contrast to their surroundings; all are found on both planets: (a) dark continuous DDTs, (b) dark cycloidal DDTs, and (c) bright DDTs. Dark continuous DDTs are the most common type on Mars. They are characterized by their relatively homogenous and continuous low albedo surface tracks. Based on terrestrial and martian in situ studies, these DDTs most likely form when surficial dust layers are removed to expose larger-grained substrate material (coarse sands of ≥500 μm in diameter). The exposure of larger-grained materials changes the photometric properties of the surface; hence leading to lower albedo tracks because grain size is photometrically inversely proportional to the surface reflectance. However, although not observed so far, compositional differences (i.e., color differences) might also lead to albedo contrasts when dust is removed to expose substrate materials with mineralogical differences. For dark continuous DDTs, albedo drop measurements are around 2.5 % in the wavelength range of 550–850 nm on Mars and around 0.5 % in the wavelength range from 300–1100 nm on Earth. The removal of an equivalent layer thickness around 1 μm is sufficient for the formation of visible dark continuous DDTs on Mars and Earth. The next type of DDTs, dark cycloidal DDTs, are characterized by their low albedo pattern of overlapping scallops. Terrestrial in situ studies imply that they are formed when sand-sized material that is eroded from the outer vortex area of a dust devil is redeposited in annular patterns in the central vortex region. This type of DDT can also be found in on Mars in orbital image data, and although in situ studies are lacking, terrestrial analog studies, laboratory work, and numerical modeling suggest they have the same formation mechanism as those on Earth. Finally, bright DDTs are characterized by their continuous track pattern and high albedo compared to their undisturbed surroundings. They are found on both planets, but to date they have only been analyzed in situ on Earth. Here, the destruction of aggregates of dust, silt and sand by dust devils leads to smooth surfaces in contrast to the undisturbed rough surfaces surrounding the track. The resulting change in photometric properties occurs because the smoother surfaces have a higher reflectance compared to the surrounding rough surface, leading to bright DDTs. On Mars, the destruction of surficial dust-aggregates may also lead to bright DDTs. However, higher reflective surfaces may be produced by other formation mechanisms, such as dust compaction by passing dust devils, as this may also cause changes in photometric properties. On Mars, DDTs in general are found at all elevations and on a global scale, except on the permanent polar caps. DDT maximum areal densities occur during spring and summer in both hemispheres produced by an increase in dust devil activity caused by maximum insolation. Regionally, dust devil densities vary spatially likely controlled by changes in dust cover thicknesses and substrate materials. This variability makes it difficult to infer dust devil activity from DDT frequencies. Furthermore, only a fraction of dust devils leave tracks. However, DDTs can be used as proxies for dust devil lifetimes and wind directions and speeds, and they can also be used to predict lander or rover solar panel clearing events. Overall, the high DDT frequency in many areas on Mars leads to drastic albedo changes that affect large-scale weather patterns

The non-random walk of stock prices: The long-term correlation between signs and sizes

We investigate the random walk of prices by developing a simple model relating the properties of the signs and absolute values of individual price changes to the diffusion rate (volatility) of prices at longer time scales. We show that this benchmark model is unable to reproduce the diffusion properties of real prices. Specifically, we find that for one hour intervals this model consistently over-predicts the volatility of real price series by about 70%, and that this effect becomes stronger as the length of the intervals increases. By selectively shuffling some components of the data while preserving others we are able to show that this discrepancy is caused by a subtle but long-range non-contemporaneous correlation between the signs and sizes of individual returns. We conjecture that this is related to the long-memory of transaction signs and the need to enforce market efficiency.Comment: 9 pages, 5 figures, StatPhys2