818 resultados para Farmer, Doug


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A procedure is presented for fitting incoherent scatter radar data from non-thermal F-region ionospheric plasma, using theoretical spectra previously predicted. It is found that values of the shape distortion factor D∗, associated with deviations of the ion velocity distribution from a Maxwellian distribution, and ion temperatures can be deduced (the results being independent of the path of iteration) if the angle between the line-of-sight and the geomagnetic field is larger than about 15–20°. The procedure can be used with one or both of two sets of assumptions. These concern the validity of the adopted model for the line-of-sight ion velocity distribution in the one case or for the full three-dimensional ion velocity distribution function in the other. The distribution function employed was developed to describe the line-of-sight velocity distribution for large aspect angles, but both experimental data and Monte Carlo simulations indicate that the form of the field-perpendicular distribution can also describe the distribution at more general aspect angles. The assumption of this form for the line-of-sight velocity distribution at a general aspect angle enables rigorous derivation of values of the one-dimensional, line-of-sight ion temperature. With some additional assumptions (principally that the field-parallel distribution is always Maxwellian and there is a simple relationship between the ion temperature anisotropy and the distortion of the field-perpendicular distribution from a Maxwellian), fits to data for large aspect angles enable determination of line-of-sight temperatures at all aspect angles and hence, of the average ion temperature and the ion temperature anisotropy. For small aspect angles, the analysis is restricted to the determination of the line-of-sight ion temperature because the theoretical spectrum is insensitive to non-thermal effects when the plasma is viewed along directions almost parallel to the magnetic field. This limitation is expected to apply to any realistic model of the ion velocity distribution function and its consequences are discussed. Fit strategies which allow for mixed ion composition are also considered. Examples of fits to data from various EISCAT observing programmes are presented.

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Incoherent scatter data from non-thermal F-region ionospheric plasma are analysed, using theoretical spectra predicted by Raman et al. It is found that values of the semi-empirical drift parameter D∗, associated with deviations of the ion velocity distribution from a Maxwellian, and the plasma temperatures can be rigorously deduced (the results being independent of the path of iteration) if the angle between the line-of-sight and the geomagnetic field is larger than about 15–20 degrees. For small aspect angles, the deduced value of the average (or 3-D) ion temperature remains ambiguous and the analysis is restricted to the determination of the line-of-sight temperature because the theoretical spectrum is insensitive to non-thermal effects when the plasma is viewed along directions almost parallel to the magnetic field. This limitation is expected to apply to any realistic model of the ion velocity distribution, and its consequences are discussed. Fit strategies which allow for mixed ion composition are also considered. Examples of fits to data from various EISCAT observing programmes are presented.

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The recent identification of non-thermal plasmas using EISCAT data has been made possible by their occurrence during large, short-lived flow bursts. For steady, yet rapid, ion convection the only available signature is the shape of the spectrum, which is unreliable because it is open to distortion by noise and sampling uncertainty and can be mimicked by other phenomena. Nevertheless, spectral shape does give an indication of the presence of non-thermal plasma, and the characteristic shape has been observed for long periods (of the order of an hour or more) in some experiments. To evaluate this type of event properly one needs to compare it to what would be expected theoretically. Predictions have been made using the coupled thermosphere-ionosphere model developed at University College London and the University of Sheffield to show where and when non-Maxwellian plasmas would be expected in the auroral zone. Geometrical and other factors then govern whether these are detectable by radar. The results are applicable to any incoherent scatter radar in this area, but the work presented here concentrates on predictions with regard to experiments on the EISCAT facility.

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A 24 h period of observations by the EISCAT radar and other ground-based instrumentation is used to study the role of plasma convection in determining the morphology of the high-latitude F-region during winter. It is suggested that, in the afternoon sector of the polar convection pattern, rapid zonal (westward) flows caused low F-region electron densities due to an extension of the mid-latitude trough far into the sunlit hemisphere. Low densities on the dawn side prior to 0600 UT may also have been due to a trough-like feature. Although the generation mechanism is unclear, the trough may be the fossil remnant of a substorm. Around midnight, high F-region densities were seen, probably due to plasma flow emerging from the cap through soft particle precipitation in the auroral oval. Two substorms occurred at times when the radar was south of the auroral oval. Both caused enhanced convection speeds, a swing to equatorward flow, enhanced E-region densities and a depleted F-region. The first was seen as a Westward Travelling Surge, and the swing to purely southward flow which followed the surge front did not return to westward flows until 80–110 min later. The Harang discontinuity was observed co-rotating eastwards between the substorms, 65 ± 30 min before the separatrix between the dawn and dusk convection cells.

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The effect of a prolonged period of strongly northward Interplanetary Magnetic Field (IMF) on the high-latitude F-region is studied using data from the EISCAT Common Programme Zero mode of operation on 11–12 August 1982. The analysis of the raw autocorrelation functions is kept to the directly derived parameters Ne, Te, Ti and velocity, and limits are defined for the errors introduced by assumptions about ion composition and by changes in the transmitted power and system constant. Simple data-cleaning criteria are employed to eliminate problems due to coherent signals and large background noise levels. The observed variations in plasma densities, temperatures and velocities are interpreted in terms of supporting data from ISEE-3 and local riometers and magnetometers. Both field-aligned and field-perpendicular plasma flows at Tromsø showed effects of the northward IMF: convection was slow and irregular and field-aligned flow profiles were characteristic of steady-state polar wind outflow with flux of order 1012 m−2 s−1. This period followed a strongly southward IMF which had triggered a substorm. The substorm gave enhanced convection, with a swing to equatorward flow and large (5 × 1012 m−2 s−1), steady-state field-aligned fluxes, leading to the possibility of O+ escape into the magnetosphere. The apparent influence of the IMF over both field-perpendicular and field-aligned flows is explained in terms of the cross-cap potential difference and the location of the auroral oval.

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One of the prerequisites for achieving skill in decadal climate prediction is to initialize and predict the circulation in the Atlantic Ocean successfully. The RAPID array measures the Atlantic Meridional Overturning Circulation (MOC) at 26°N. Here we develop a method to include these observations in the Met Office Decadal Prediction System (DePreSys). The proposed method uses covariances of overturning transport anomalies at 26°N with ocean temperature and salinity anomalies throughout the ocean to create the density structure necessary to reproduce the observed transport anomaly. Assimilating transport alone in this way effectively reproduces the observed transport anomalies at 26°N and is better than using basin-wide temperature and salinity observations alone. However, when the transport observations are combined with in situ temperature and salinity observations in the analysis, the transport is not currently reproduced so well. The reasons for this are investigated using pseudo-observations in a twin experiment framework. Sensitivity experiments show that the MOC on monthly time-scales, at least in the HadCM3 model, is modulated by a mechanism where non-local density anomalies appear to be more important for transport variability at 26°N than local density gradients.

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Observational analyses of running 5-year ocean heat content trends (Ht) and net downward top of atmosphere radiation (N) are significantly correlated (r~0.6) from 1960 to 1999, but a spike in Ht in the early 2000s is likely spurious since it is inconsistent with estimates of N from both satellite observations and climate model simulations. Variations in N between 1960 and 2000 were dominated by volcanic eruptions, and are well simulated by the ensemble mean of coupled models from the Fifth Coupled Model Intercomparison Project (CMIP5). We find an observation-based reduction in N of -0.31±0.21 Wm-2 between 1999 and 2005 that potentially contributed to the recent warming slowdown, but the relative roles of external forcing and internal variability remain unclear. While present-day anomalies of N in the CMIP5 ensemble mean and observations agree, this may be due to a cancellation of errors in outgoing longwave and absorbed solar radiation.

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Dynamic electricity pricing can produce efficiency gains in the electricity sector and help achieve energy policy goals such as increasing electric system reliability and supporting renewable energy deployment. Retail electric companies can offer dynamic pricing to residential electricity customers via smart meter-enabled tariffs that proxy the cost to procure electricity on the wholesale market. Current investments in the smart metering necessary to implement dynamic tariffs show policy makers’ resolve for enabling responsive demand and realizing its benefits. However, despite these benefits and the potential bill savings these tariffs can offer, adoption among residential customers remains at low levels. Using a choice experiment approach, this paper seeks to determine whether disclosing the environmental and system benefits of dynamic tariffs to residential customers can increase adoption. Although sampling and design issues preclude wide generalization, we found that our environmentally conscious respondents reduced their required discount to switch to dynamic tariffs around 10% in response to higher awareness of environmental and system benefits. The perception that shifting usage is easy to do also had a significant impact, indicating the potential importance of enabling technology. Perhaps the targeted communication strategy employed by this study is one way to increase adoption and achieve policy goals.

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Background: The validity of ensemble averaging on event-related potential (ERP) data has been questioned, due to its assumption that the ERP is identical across trials. Thus, there is a need for preliminary testing for cluster structure in the data. New method: We propose a complete pipeline for the cluster analysis of ERP data. To increase the signalto-noise (SNR) ratio of the raw single-trials, we used a denoising method based on Empirical Mode Decomposition (EMD). Next, we used a bootstrap-based method to determine the number of clusters, through a measure called the Stability Index (SI). We then used a clustering algorithm based on a Genetic Algorithm (GA)to define initial cluster centroids for subsequent k-means clustering. Finally, we visualised the clustering results through a scheme based on Principal Component Analysis (PCA). Results: After validating the pipeline on simulated data, we tested it on data from two experiments – a P300 speller paradigm on a single subject and a language processing study on 25 subjects. Results revealed evidence for the existence of 6 clusters in one experimental condition from the language processing study. Further, a two-way chi-square test revealed an influence of subject on cluster membership.

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Abstract Background: Advancing age is linked to a decrease in beneficial bacteria such as Bifidobacterium spp. and reduced aspects of innate immune function. Objectives: We investigated whether daily consumption of a probiotic [Bacillus coagulans GBI-30, 6086 (BC30); GanedenBC30] could improve immune function and gut function in men and women aged 65–80 y, using a double-blind, placebo-controlled crossover design. Method: Thirty-six volunteers were recruited and randomly assigned to receive either a placebo (microcrystalline cellulose) or the probiotic BC30 (1 3 109 colony-forming units/capsule). Volunteers consumed 1 treatment capsule per day for 28 d, followed by a 21-d washout period before switching to the other treatment. Blood and fecal samples were collected at the beginning and end of each treatment period. Fecal samples were used to enumerate bacterial groups and concentrations of calprotectin. Peripheral blood mononuclear cells (PBMCs) were extracted from whole blood to assess natural killer cell activity and lipopolysaccharide (LPS)-stimulated cytokine production. C-reactive protein concentrations were measured in plasma. Results: Consumption of BC30 significantly increased populations of Faecalibacterium prausnitzii by 0.1 log10 cells/mL more than during consumption of the placebo (P = 0.03), whereas populations of Bacillus spp. increased significantly by 0.5 log10 cells/mL from baseline in volunteers who consumed BC30 (P = 0.007). LPS-stimulated PBMCs showed a 0.2 ng/mL increase in the anti-inflammatory cytokine IL-10 28 d after consumption of BC30 (P < 0.05), whereas the placebo did not affect IL-10, and no overall difference was found in the effect of the treatments. Conclusions: Daily consumption of BC30 by adults aged 65–80 y can increase beneficial groups of bacteria in the human gut and potentially increase production of anti-inflammatory cytokines. This study shows the potential benefits of a probiotic to improve dysbiosis via modulation of the microbiota in older persons. J Nutr doi: 10.3945/jn.114.199802.

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In advancing age, gut populations of beneficial microbes, notably Bifidobacterium spp., show a marked decline. This contributes to an environment less capable of maintaining homoeostasis. This in vitro investigation studied the possible synergistic effects of probiotic supplementation in modulating the gut microbiota enabling prebiotic therapy to in elderly persons. Single stage batch culture anaerobic fermenters were used and inoculated with fecal microbiota obtained from volunteers after taking a 28 day treatment of Bacillus coagulans GBI-30, 6086 (GanedenBC30 (BC30)) or a placebo. The response to prebiotic supplements fructooligosaccharides (FOS) and galactooligosaccharides (GOS) in the fermenters was assessed. Bacterial enumeration was carried out using fluorescent in situ hybridisation and organic acids measured by gas chromatography. Baseline populations of Faecalibacterium prausnitzii, Clostridium lituseburense and Bacillus spp. were significantly higher in those having consumed BC30 compared to the placebo. Both prebiotics increased populations of several purportedly beneficial bacterial groups in both sets of volunteers. Samples from volunteers having ingested the BC30 also increased populations of C. lituseburense, Eubacterium rectale and F. prausnitzii more so than in persons who had consumed the placebo, this also resulted in significantly higher concentrations of butyrate, acetate and propionate. This shows that consumption of BC30 and subsequent use of prebiotics resulted in elevated populations of beneficial genres of bacteria as well as organic acid production

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1. Agri-environment schemes remain a controversial approach to reversing biodiversity losses, partly because the drivers of variation in outcomes are poorly understood. In particular, there is a lack of studies that consider both social and ecological factors. 2. We analysed variation across 48 farms in the quality and biodiversity outcomes of agri-environmental habitats designed to provide pollen and nectar for bumblebees and butterflies or winter seed for birds. We used interviews and ecological surveys to gather data on farmer experience and understanding of agri-environment schemes, and local and landscape environmental factors. 3. Multimodel inference indicated social factors had a strong impact on outcomes and that farmer experiential learning was a key process. The quality of the created habitat was affected positively by the farmer’s previous experience in environmental management. The farmer’s confidence in their ability to carry out the required management was negatively related to the provision of floral resources. Farmers with more wildlife-friendly motivations tended to produce more floral resources, but fewer seed resources. 4. Bird, bumblebee and butterfly biodiversity responses were strongly affected by the quantity of seed or floral resources. Shelter enhanced biodiversity directly, increased floral resources and decreased seed yield. Seasonal weather patterns had large effects on both measures. Surprisingly, larger species pools and amounts of semi-natural habitat in the surrounding landscape had negative effects on biodiversity, which may indicate use by fauna of alternative foraging resources. 5. Synthesis and application. This is the first study to show a direct role of farmer social variables on the success of agri-environment schemes in supporting farmland biodiversity. It suggests that farmers are not simply implementing agri-environment options, but are learning and improving outcomes by doing so. Better engagement with farmers and working with farmers who have a history of environmental management may therefore enhance success. The importance of a number of environmental factors may explain why agri-environment outcomes are variable, and suggests some – such as the weather – cannot be controlled. Others, such as shelter, could be incorporated into agri-environment prescriptions. The role of landscape factors remains complex and currently eludes simple conclusions about large-scale targeting of schemes.

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Two methods are developed to estimate net surface energy fluxes based upon satellite-based reconstructions of radiative fluxes at the top of atmosphere and the atmospheric energy tendencies and transports from the ERA-Interim reanalysis. Method 1 applies the mass adjusted energy divergence from ERA-Interim while method 2 estimates energy divergence based upon the net energy difference at the top of atmosphere and the surface from ERA-Interim. To optimise the surface flux and its variability over ocean, the divergences over land are constrained to match the monthly area mean surface net energy flux variability derived from a simple relationship between the surface net energy flux and the surface temperature change. The energy divergences over the oceans are then adjusted to remove an unphysical residual global mean atmospheric energy divergence. The estimated net surface energy fluxes are compared with other data sets from reanalysis and atmospheric model simulations. The spatial correlation coefficients of multi-annual means between the estimations made here and other data sets are all around 0.9. There are good agreements in area mean anomaly variability over the global ocean, but discrepancies in the trend over the eastern Pacific are apparent.

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The study examined the contribution of the Cocoa Disease and Pest Control Programme (CODAPEC), which is a cocoa production-enhancing government policy, to reducing poverty and raising the living standards of cocoa farmers in Ghana. One hundred and fifty (150) cocoa farmers were randomly selected from five communities in the Bibiani-Anhwiaso-Bekwai district of the Western Region of Ghana and interviewed using structured questionnaires. Just over half of the farmers (53%) perceived the CODAPEC programme as being effective in controlling pests and diseases, whilst 56.6% felt that their yields and hence livelihoods had improved. In some cases pesticides or fungicides were applied later in the season than recommended and this had a detrimental effect on yields. To determine the level of poverty amongst farmers, annual household consumption expenditure was used as a proxy indicator. The study found that 4.7% of cocoa farmers were extremely poor having a total annual household consumption expenditure of less than GH¢ 623.10 ($310.00) while 8.0% were poor with less than GH¢ 801.62 ($398.81). An amount of money ranging from GH¢ 20.00 ($9.95) to GH¢ 89.04 ($44.29) per annum was needed to lift the 4.7% of cocoa farmers out of extreme poverty, which could be achieved through modest increases in productivity. The study highlighted how agricultural intervention programmes, such as CODAPEC, have the potential to contribute to improved farmer livelihoods.