930 resultados para Diseases that affect the body’s bones


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Objective:To identify aspects that affect the quality of life of nursing caregivers and their relationship with care in an Intensive Care Unit for Adults (A-ICU). Methods:This was a descriptive study with qualitative approach, taking as subjects 21 professionals who constitute the nursing staff of the A-ICU of a school hospital in Maringá-PR. Unstructured interview was used as a strategy to collect data, conducted between May and June 2009. Data analysis was based on the method of content analysis. The categories identified were: overlooking improvement in quality of life related to the resources in an A-ICU; the quality of life influencing the form of care; interpersonal relationships into the health team reflecting on the quality of life and care. Results:The analysis of caregivers’ speech and the results of the observation showed that there is correlation between the aspects they consider influential in their quality of life and the way of caring for patients in an A-ICU.Conclusion: The findings indicate that, among the influential aspects, the stressful factors overlap the enhancing ones. From this perspective, dealing with caregiver’s suffering might be the starting point for the improvement in quality of care in an A-ICU.

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Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting the location and timing of the bloom events in lakes and rivers. In this article, a new deterministic model is introduced which simulates the growth and movement of cyanobacterial blooms in river systems. The model focuses on the mathematical description of the bloom formation, vertical migration and lateral transport of colonies within river environments by taking into account the four major factors that affect the cyanobacterial bloom formation in freshwaters: light, nutrients, temperature and river flow. The model consists of two sub-models: a vertical migration model with respect to growth of cyanobacteria in relation to light, nutrients and temperature; and a hydraulic model to simulate the horizontal movement of the bloom. This article presents the model algorithms and highlights some important model results. The effects of nutrient limitation, varying illumination and river flow characteristics on cyanobacterial movement are simulated. The results indicate that under high light intensities and in nutrient-rich waters colonies sink further as a result of carbohydrate accumulation in the cells. In turbulent environments, vertical migration is retarded by vertical velocity component generated by turbulent shear stress. (c) 2006 Elsevier B.V. All rights reserved.

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Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting the location and timing of the bloom events in lakes and rivers. A new deterministic-mathematical model was developed, which simulates the growth and movement of cyanobacterial blooms in river systems. The model focuses on the mathematical description of the bloom formation, vertical migration and lateral transport of colonies within river environments by taking into account the major factors that affect the cyanobacterial bloom formation in rivers including, light, nutrients and temperature. A technique called generalised sensitivity analysis was applied to the model to identify the critical parameter uncertainties in the model and investigates the interaction between the chosen parameters of the model. The result of the analysis suggested that 8 out of 12 parameters were significant in obtaining the observed cyanobacterial behaviour in a simulation. It was found that there was a high degree of correlation between the half-saturation rate constants used in the model.

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Plant root mucilages contain powerful surfactants that will alter the interaction of soil solids with water and ions, and the rates of microbial processes. The lipid composition of maize, lupin and wheat root mucilages was analysed by thin layer chromatography and gas chromatography-mass spectrometry. A commercially available phosphatidylcholine (lecithin), chemically similar to the phospholipid surfactants identified in the mucilages, was then used to evaluate its effects on selected soil properties. The lipids found in the mucilages were principally phosphatidylcholines, composed mainly of saturated fatty acids, in contrast to the lipids extracted from root tissues. In soil at low tension, lecithin reduced the water content at any particular tension by as much as 10 and 50% in soil and acid-washed sand, respectively. Lecithin decreased the amount of phosphate adsorption in soil and increased the phosphate concentration in solution by 10%. The surfactant also reduced net rates of ammonium consumption and nitrate production in soil. These experiments provide the first evidence we are aware of that plant-released surfactants will significantly modify the biophysical environment of the rhizosphere.

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The traditional independent variable in the multinationality and performance literature is the ratio of foreign (F) to total (T) sales, (F/T). This can now be supplemented by a new regional variable, the ratio of regional (R) to total (T) sales, i.e. (R/T). Data are presented on both (F/T) and (R/T) for both sales and assets for a 5-year period, 2001–2005. New tests are reported on (R/T) as it affects a financial measure of performance, the Tobin's Q. Implications are drawn for future research on the S-curve relationship between multinationality and performance in the light of this regional phenomenon.

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Whilst much is known of new technology adopters, little research has addressed the role of their attitudes in adoption decisions; particularly, for technologies with evident economic potential that have not been taken up by farmers. This paper presents recent research that has used a new approach which examines the role that adopters' attitudes play in identifying the drivers of and barriers to adoption. The study was concerned with technologies for livestock farming systems in SW England, specifically oestrus detection, nitrogen supply management, and, inclusion of white clover. The adoption behaviour is analysed using the social-psychology theory of reasoned action to identify factors that affect the adoption of technologies, which are confirmed using principal components analysis. The results presented here relate to the specific adoption behaviour regarding the Milk Development Council's recommended observation times for heat detection. The factors that affect the adoption of this technology are: cost effectiveness, improved detection and conception rates as the main drivers, whilst the threat to demean the personal knowledge and skills of a farmer in 'knowing' their cows is a barrier. This research shows clearly that promotion of a technology and transfer of knowledge for a farming system need to take account of the beliefs and attitudes of potential adopters. (C) 2006 Elsevier Ltd. All rights reserved.

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We show that for any sample size, any size of the test, and any weights matrix outside a small class of exceptions, there exists a positive measure set of regression spaces such that the power of the Cli-Ord test vanishes as the autocorrelation increases in a spatial error model. This result extends to the tests that dene the Gaussian power envelope of all invariant tests for residual spatial autocorrelation. In most cases, the regression spaces such that the problem occurs depend on the size of the test, but there also exist regression spaces such that the power vanishes regardless of the size. A characterization of such particularly hostile regression spaces is provided.