875 resultados para Data and Information Technology


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Aims and objectives: To assess the level of confidence that rheumatology patients would have in nurse prescribing, the effects on likely adherence and particular concerns that these patients have. In addition, given that information provision has been cited as a potential benefit of nurse prescribing, the present study assessed the extent to which these patients would want an explanation for the selected medicine, as well as which types of information should be included in such an explanation. Background: Nurse prescribing has been successfully implemented in the UK in several healthcare settings. Existing research has not addressed the effects on patients' confidence and likely adherence, nor have patients' information needs been established. However, we know that inadequate medicines information provision by health professionals is one of the largest causes of patient dissatisfaction. Methods: Fifty-four patients taking disease-modifying drugs for inflammatory joint disease attending a specialist rheumatology clinic self-completed a written questionnaire. Results: Patients indicated a relatively high level of confidence in nurse prescribing and stated that they would be very likely to take the selected medication. The level of concern was relatively low and the majority of concerns raised did not relate to the nurse's status. Strong support was expressed for the nurse providing an explanation for medicine choice. Conclusion: This research provides support for the prescription of medicines by nurses working in the area of rheumatology, the importance of nurses providing a full explanation about the selected medicines they prescribe for these patients and some indication as to which categories of information should be included. Relevance to clinical practice: Rheumatology patients who have not yet experienced nurse prescribing are, in general, positive about nurses adopting this role. It is important that nurses provide appropriate information about the prescribed medicines, in a form that can be understood.

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In this paper, a fuzzy Markov random field (FMRF) model is used to segment land-objects into free, grass, building, and road regions by fusing remotely, sensed LIDAR data and co-registered color bands, i.e. scanned aerial color (RGB) photo and near infra-red (NIR) photo. An FMRF model is defined as a Markov random field (MRF) model in a fuzzy domain. Three optimization algorithms in the FMRF model, i.e. Lagrange multiplier (LM), iterated conditional mode (ICM), and simulated annealing (SA), are compared with respect to the computational cost and segmentation accuracy. The results have shown that the FMRF model-based ICM algorithm balances the computational cost and segmentation accuracy in land-cover segmentation from LIDAR data and co-registered bands.

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In this paper a look is taken at the relatively new area of culturing neural tissue and embodying it in a mobile robot platform—essentially giving a robot a biological brain. Present technology and practice is discussed. New trends and the potential effects of and in this area are also indicated. This has a potential major impact with regard to society and ethical issues and hence some initial observations are made. Some initial issues are also considered with regard to the potential consciousness of such a brain.

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Infrared optical-multilayer filters and materials were exposed to the space environment of low Earth orbit on LDEF. This paper summarizes the effects of that environment on the physical and optical properties of the filters and materials flown.

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Infrared multilayer interference filters have been used extensively in satellite radiometers for about 15 years. Filters manufactured by the University of Reading have been used in Nimbus 5, 6, and 7, TIROS N, and the Pioneer Venus orbiter. The ability of the filters to withstand the space environment in these applications is critical; if degradation takes place, the effects would range from worsening of signal-to-noise performance to complete system failure. An experiment on the LDEF will enable the filters, for the first time, to be subjected to authoritative spectral measurements following space exposure to ascertain their suitability for spacecraft use and to permit an understanding of degradation mechanisms.

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Svalgaard and Cliver (2010) recently reported a consensus between the various reconstructions of the heliospheric field over recent centuries. This is a significant development because, individually, each has uncertainties introduced by instrument calibration drifts, limited numbers of observatories, and the strength of the correlations employed. However, taken collectively, a consistent picture is emerging. We here show that this consensus extends to more data sets and methods than reported by Svalgaard and Cliver, including that used by Lockwood et al. (1999), when their algorithm is used to predict the heliospheric field rather than the open solar flux. One area where there is still some debate relates to the existence and meaning of a floor value to the heliospheric field. From cosmogenic isotope abundances, Steinhilber et al. (2010) have recently deduced that the near-Earth IMF at the end of the Maunder minimum was 1.80 ± 0.59 nT which is considerably lower than the revised floor of 4nT proposed by Svalgaard and Cliver. We here combine cosmogenic and geomagnetic reconstructions and modern observations (with allowance for the effect of solar wind speed and structure on the near-Earth data) to derive an estimate for the open solar flux of (0.48 ± 0.29) × 1014 Wb at the end of the Maunder minimum. By way of comparison, the largest and smallest annual means recorded by instruments in space between 1965 and 2010 are 5.75 × 1014 Wb and 1.37 × 1014 Wb, respectively, set in 1982 and 2009, and the maximum of the 11 year running means was 4.38 × 1014 Wb in 1986. Hence the average open solar flux during the Maunder minimum is found to have been 11% of its peak value during the recent grand solar maximum.

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Satellite measurements and numerical forecast model reanalysis data are used to compute an updated estimate of the cloud radiative effect on the global multi-annual mean radiative energy budget of the atmosphere and surface. The cloud radiative cooling effect through reflection of shortwave radiation dominates over the longwave heating effect, resulting in a net cooling of the climate system of –21 Wm-2. The shortwave radiative effect of cloud is primarily manifest as a reduction in the solar radiation absorbed at the surface of -53 Wm-2. Clouds impact longwave radiation by heating the moist tropical atmosphere (up to around 40 Wm-2 for global annual means) while enhancing the radiative cooling of the atmosphere over other regions, in particular higher latitudes and sub-tropical marine stratocumulus regimes. While clouds act to cool the climate system during the daytime, the cloud greenhouse effect heats the climate system at night. The influence of cloud radiative effect on determining cloud feedbacks and changes in the water cycle are discussed.