88 resultados para Ethnographic Methods
Resumo:
Background: Many factors need to be considered in a food-based intervention. Vitamin A deficiency and chronic diseases, such as diabetes, heart disease and cancer, have become serious problems in the Federated States of Micronesia (FSM) following the decreased production and consumption of locally grown foods. However, agricultural and social conditions are still favourable for local food production. Aim: To identify key factors to consider in a Micronesian food-based intervention focusing on increased production and consumption of four major Micronesian staple foods: banana, breadfruit, giant swamp taro and pandanus. Methods: Ethnographic methods including key informant interviews and a literature review. Results: Pacific and Micronesian values, concepts of food and disease, and food classifications differ sharply from Western concepts. There are few FSM professionals with nutrition expertise. Traditional foods and food cultivars vary in nutrient content, consumption level, cost, availability, status, convenience in growing, storing and cooking, and organoleptic factors. Conclusions: A systematic consideration of the factors that relate to a food-based intervention is critical to its success. The evaluation of which food and cultivar of that food that might be most effectively promoted is also critical. Regional differences, for example FSM inter-island differences between the staple foods and cultivars, must be considered carefully. The evaluation framework presented here may be relevant to Pacific island and other countries with similar foods where food-based interventions are being planned. An ethnographic approach was found to be essential in understanding the cultural context and in data collection and analysis.
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For researchers investigating online communities, the existence of the internet has made the activities and opinions of community members visible in a public domain. FPS gaming culture is a highly literate culture - members communicate and represent themselves in textual forms online, and the culture makes use of a wide variety of communication and publishing technologies. While a significant amount of insider knowledge is required to understand and interpret such online content, a large body of material is available to researchers online, and sometimes provides more reliable and enlightening information than that generated by more traditional research methods. While the abundance of data available online in some ways makes research far easier, it also creates new dilemmas and challenges for researchers. What extra knowledge is required of the researcher? How can one ensure that one's interpretations of member statements are made with an understanding of meaning within that culture? What responsibilities does the researcher have in their representation of the culture under examination? What ethical issues must be considered?
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This paper critically assesses several loss allocation methods based on the type of competition each method promotes. This understanding assists in determining which method will promote more efficient network operations when implemented in deregulated electricity industries. The methods addressed in this paper include the pro rata [1], proportional sharing [2], loss formula [3], incremental [4], and a new method proposed by the authors of this paper, which is loop-based [5]. These methods are tested on a modified Nordic 32-bus network, where different case studies of different operating points are investigated. The varying results obtained for each allocation method at different operating points make it possible to distinguish methods that promote unhealthy competition from those that encourage better system operation.
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We propose quadrature rules for the approximation of line integrals possessing logarithmic singularities and show their convergence. In some instances a superconvergence rate is demonstrated.
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There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.
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The artificial dissipation effects in some solutions obtained with a Navier-Stokes flow solver are demonstrated. The solvers were used to calculate the flow of an artificially dissipative fluid, which is a fluid having dissipative properties which arise entirely from the solution method itself. This was done by setting the viscosity and heat conduction coefficients in the Navier-Stokes solvers to zero everywhere inside the flow, while at the same time applying the usual no-slip and thermal conducting boundary conditions at solid boundaries. An artificially dissipative flow solution is found where the dissipation depends entirely on the solver itself. If the difference between the solutions obtained with the viscosity and thermal conductivity set to zero and their correct values is small, it is clear that the artificial dissipation is dominating and the solutions are unreliable.
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Conferences that deliver interactive sessions designed to enhance physician participation, such as role play, small discussion groups, workshops, hands-on training, problem- or case-based learning and individualised training sessions, are effective for physician education.
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An investigation was undertaken to test the effectiveness of two procedures for recording boundaries and plot positions for scientific studies on farms on Leyte Island, the Philippines. The accuracy of a Garmin 76 Global Positioning System (GPS) unit and a compass and chain was checked under the same conditions. Tree canopies interfered with the ability of the satellite signal to reach the GPS and therefore the GPS survey was less accurate than the compass and chain survey. Where a high degree of accuracy is required, a compass and chain survey remains the most effective method of surveying land underneath tree canopies, providing operator error is minimised. For a large number of surveys and thus large amounts of data, a GPS is more appropriate than a compass and chain survey because data are easily up-loaded into a Geographic Information System (GIS). However, under dense canopies where satellite signals cannot reach the GPS, it may be necessary to revert to a compass survey or a combination of both methods.
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The ability to predict leaf area and leaf area index is crucial in crop simulation models that predict crop growth and yield. Previous studies have shown existing methods of predicting leaf area to be inadequate when applied to a broad range of cultivars with different numbers of leaves. The objectives of the study were to (i) develop generalised methods of modelling individual and total plant leaf area, and leaf senescence, that do not require constants that are specific to environments and/or genotypes, (ii) re-examine the base, optimum, and maximum temperatures for calculation of thermal time for leaf senescence, and (iii) assess the method of calculation of individual leaf area from leaf length and leaf width in experimental work. Five cultivars of maize differing widely in maturity and adaptation were planted in October 1994 in south-eastern Queensland, and grown under non-limiting conditions of water and plant nutrient supplies. Additional data for maize plants with low total leaf number (12-17) grown at Katumani Research Centre, Kenya, were included to extend the range in the total leaf number per plant. The equation for the modified (slightly skewed) bell curve could be generalised for modelling individual leaf area, as all coefficients in it were related to total leaf number. Use of coefficients for individual genotypes can be avoided, and individual and total plant leaf area can be calculated from total leaf number. A single, logistic equation, relying on maximum plant leaf area and thermal time from emergence, was developed to predict leaf senescence. The base, optimum, and maximum temperatures for calculation of thermal time for leaf senescence were 8, 34, and 40 degrees C, and apply for the whole crop-cycle when used in modelling of leaf senescence. Thus, the modelling of leaf production and senescence is simplified, improved, and generalised. Consequently, the modelling of leaf area index (LAI) and variables that rely on LAI will be improved. For experimental purposes, we found that the calculation of leaf area from leaf length and leaf width remains appropriate, though the relationship differed slightly from previously published equations.
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Appropriate ways to monitor the availability and use of illicit drugs were examined. Four methods were tested concurrently: (1) a quantitative survey of injecting drug users, (2) a qualitative key informant study of illicit drug users and professionals working in the drug field, (3) examination of existing sources of survey, health and law enforcement data and (4) an ethnographic study of a high risk group of illicit drug users. The first three methods were recommended for inclusion in an ongoing national monitoring system, enabling the collection of both quantitative and qualitative data on a range of illicit drugs in a relatively brief, quick and cost-effective manner. A degree of convergent validity was also noted among these methods, improving the degree of confidence in drug trends. The importance of injecting drug users as a sentinel population of illicit drug users was highlighted, along with optimal methods for qualitative research.
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Conotoxins are valuable probes of receptors and ion channels because of their small size and highly selective activity. alpha-Conotoxin EpI, a 16-residue peptide from the mollusk-hunting Conus episcopatus, has the amino acid sequence GCCSDPRCNMNNPDY(SO3H)C-NH2 and appears to be an extremely potent and selective inhibitor of the alpha 3 beta 2 and alpha 3 beta 4 neuronal subtypes of the nicotinic acetylcholine receptor (nAChR). The desulfated form of EpI ([Tyr(15)]EpI) has a potency and selectivity for the nAChR receptor similar to those of EpI. Here we describe the crystal structure of [Tyr(15)]EpI solved at a resolution of 1.1 Angstrom using SnB. The asymmetric unit has a total of 284 non-hydrogen atoms, making this one of the largest structures solved de novo try direct methods. The [Tyr(15)]EpI structure brings to six the number of alpha-conotoxin structures that have been determined to date. Four of these, [Tyr(15)]EpI, PnIA, PnIB, and MII, have an alpha 4/7 cysteine framework and are selective for the neuronal subtype of the nAChR. The structure of [Tyr(15)]EpI has the same backbone fold as the other alpha 4/7-conotoxin structures, supporting the notion that this conotoxin cysteine framework and spacing give rise to a conserved fold. The surface charge distribution of [Tyr(15)]EpI is similar to that of PnIA and PnIB but is likely to be different from that of MII, suggesting that [Tyr(15)]EpI and MII may have different binding modes for the same receptor subtype.