814 resultados para Explanatory Variables Effect


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Background: Minority ethnic groups in the UK are reported to have a poor experience of mental health services, but comparative information is scarce. Aims: To examine ethnic differences in patients’ experience of community mental health services. Method: Trusts providing mental health services in England conducted surveys in 2004 and 2005 of users of community mental health services. Multiple regression was used to examine ethnic differences in responses. Results: About 27 000 patients responded to each of the surveys, of whom 10% were of minority ethnic origin. In the 2004 survey, age, living alone, the 2004 survey, age, living alone, detention and hospital admissions were stronger predictors of patient experience than ethnicity. Self-reported mental health status had the strongest explanatory effect. In the 2005 survey, the main negative differences relative to the White British were for Asians. Conclusions: Ethnicity had a smaller effect on patient experience than other variables. Relative to the White British, the Black group did not report negative experiences whereas the Asian group were most likely to respond negatively. However, there is a need for improvements in services for minority ethnic groups, including access to talking therapies and better recording of ethnicity.

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The effect of environmental variables on blue shark Prionace glauca catch per unit effort (CPUE) in a recreational fishery in the western English Channel, between June and September 1998–2011, was quantified using generalized additive models (GAMs). Sea surface temperature (SST) explained 1·4% of GAM deviance, and highest CPUE occurred at 16·7° C, reflecting the optimal thermal preferences of this species. Surface chlorophyll a concentration (CHL) significantly affected CPUE and caused 27·5% of GAM deviance. Additionally, increasing CHL led to rising CPUE, probably due to higher productivity supporting greater prey biomass. The density of shelf-sea tidal mixing fronts explained 5% of GAM deviance, but was non-significant, with increasing front density negatively affecting CPUE. Time-lagged frontal density significantly affected CPUE, however, causing 12·6% of the deviance in a second GAM and displayed a positive correlation. This outcome suggested a delay between the evolution of frontal features and the subsequent accumulation of productivity and attraction of higher trophic level predators, such as P. glauca.

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The effect of environmental variables on blue shark Prionace glauca catch per unit effort (CPUE) in a recreational fishery in the western English Channel, between June and September 1998–2011, was quantified using generalized additive models (GAMs). Sea surface temperature (SST) explained 1·4% of GAM deviance, and highest CPUE occurred at 16·7° C, reflecting the optimal thermal preferences of this species. Surface chlorophyll a concentration (CHL) significantly affected CPUE and caused 27·5% of GAM deviance. Additionally, increasing CHL led to rising CPUE, probably due to higher productivity supporting greater prey biomass. The density of shelf-sea tidal mixing fronts explained 5% of GAM deviance, but was non-significant, with increasing front density negatively affecting CPUE. Time-lagged frontal density significantly affected CPUE, however, causing 12·6% of the deviance in a second GAM and displayed a positive correlation. This outcome suggested a delay between the evolution of frontal features and the subsequent accumulation of productivity and attraction of higher trophic level predators, such as P. glauca.

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Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However, with the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, few assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data. In this study, we compare Bayesian network modelling approaches accounting for latent effects to reveal species dynamics for 7 geographically and temporally varied areas within the North Sea. We also apply structure learning techniques to identify functional relationships such as prey–predator between trophic groups of species that vary across space and time. We examine if the use of a general hidden variable can reflect overall changes in the trophic dynamics of each spatial system and whether the inclusion of a specific hidden variable can model unmeasured group of species. The general hidden variable appears to capture changes in the variance of different groups of species biomass. Models that include both general and specific hidden variables resulted in identifying similarity with the underlying food web dynamics and modelling spatial unmeasured effect. We predict the biomass of the trophic groups and find that predictive accuracy varies with the models' features and across the different spatial areas thus proposing a model that allows for spatial autocorrelation and two hidden variables. Our proposed model was able to produce novel insights on this ecosystem's dynamics and ecological interactions mainly because we account for the heterogeneous nature of the driving factors within each area and their changes over time. Our findings demonstrate that accounting for additional sources of variation, by combining structure learning from data and experts' knowledge in the model architecture, has the potential for gaining deeper insights into the structure and stability of ecosystems. Finally, we were able to discover meaningful functional networks that were spatially and temporally differentiated with the particular mechanisms varying from trophic associations through interactions with climate and commercial fisheries.

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OBJECTIVE: To determine the effect of dietary supplementation with omega-3 fish oils with or without copper on disease activity in systemic lupus erythematosus (SLE). Fish oil supplementation has a beneficial effect on murine models of SLE, while exogenous copper can decrease the formation of lupus erythematosus cells in rats with a hydralazine-induced collagen disease. METHODS: A double blind, double placebo controlled factorial trial was performed on 52 patients with SLE. Patients were randomly assigned to 4 treatment groups. Physiological doses of omega-3 fish oils and copper readily obtainable by dietary means were used. One group received 3 g MaxEPA and 3 mg copper, another 3 g MaxEPA and placebo copper, another 3 mg copper and placebo fish oil, and the fourth group received both placebo capsules. Serial measurements of disease activity using the revised Systemic Lupus Activity Measure (SLAM-R) and peripheral blood samples for routine hematological, biochemical, and immunological indices were taken at baseline, 6, 12, and 24 weeks. RESULTS: There was a significant decline in SLAM-R score from 6.12 to 4.69 (p <0.05) in those subjects taking fish oil compared to placebo. No significant effect on SLAM-R was observed in subjects taking copper. Laboratory variables were unaffected by either intervention. CONCLUSION: In the management of SLE, dietary supplementation with fish oil may be beneficial in modifying symptomatic disease activity.

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With tougher sentencing laws, an increasing number of individuals are finding themselves spending their final years in life in prison. Drawing on a sample of 327 women over the age of 50 incarcerated in 5 Southern states, the present study investigates the relationship between numerous health variables and the Templer Death Anxiety Scale (TDAS). Qualitatively, the article also provides personal accounts from inmates that serve to reinforce death fears when engaging the prison health care system. Participants reported a mean of 6.40 on the TDAS indicating a substantial degree of death and anxiety when compared to community samples. both mental and physical health measures were important indicators of death anxiety. Qualitative information discovered that respondents' concerns about dying in prison were often influenced by the perceived lack of adequate health care and the indifference of prison staff and other instances of penal harm.

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This study investigated the effect of statistics anxiety and attitudes on first year psychology students’ predicted and actual statistics class test scores. A total of 52 students completed the Statistics Anxiety Rating Scale and estimated their class test scores one week before their test at the end of first year. Regression models were conducted with the six attitude and anxiety subscales as predictors and the predicted and actual test scores as criterion variables. The results showed that computation self concept and fear of asking for help accounted for 37% of the variance in predicted test scores. However, when actual test scores were analysed the significant predictors were worth of statistics and interpretation anxiety, which accounted for 20% of the variance. These results suggested that while statistics anxiety does influence students’ perceptions of their competence it appears to have less effect on their actual performance. Results also suggested that students were unaware of their own statistical competence. Remedial action is required to address the level of statistics anxiety experienced by first year undergraduate psychology students, as it appears to result in unrealistic assessments of their ability and has detrimental effects on their statistics self-efficacy.

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Background-Associations between genotype and intellectual outcome in patients with phenylketonuria are complicated because intelligence is influenced by many variables, including environmental factors and other genetic determinants. Intellectual changes with age, both on and after relaxation of diet, vary within the patient population. This study aims to determine whether a significant association exists between genotype and change in intelligence after relaxation of diet.

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Spectral signal intensities, especially in 'real-world' applications with nonstandardized sample presentation due to uncontrolled variables/factors, commonly require additional spectral processing to normalize signal intensity in an effective way. In this study, we have demonstrated the complexity of choosing a normalization routine in the presence of multiple spectrally distinct constituents by probing a dataset of Raman spectra. Variation in absolute signal intensity (90.1% of total variance) of the Raman spectra of these complex biological samples swamps the variation in useful signals (9.4% of total variance), degrading its diagnostic and evaluative potential.

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C17 polyacetylenes are a group of bioactive compounds present in carrots which have recently gained scientific attention due to their cytotoxicity against cancer cells. In common with many bioactive compounds, their levels may be influenced by thermal processes, such as boiling or water immersion. This study investigated the effect of a number of water immersion time/temperature combinations on concentrations of these compounds and attempted to model the changes. Carrot samples were thermally treated by heating in water at temperatures from 50–100 °C and holding times of 2–60 min. Following heating, levels of falcarinol (FaOH), falcarindiol (FaDOH), falcarindiol-3-acetate (FaDOAc) and Hunter colour parameters (L*a*b*) were determined. FaOH, FaDOH, FaDOAc levels were significantly reduced at lower temperatures (50–60 °C). In contrast, samples heated at temperatures from 70–100 °C exhibited higher levels of polyacetylenes (p < 0.05) than did raw unprocessed samples. Regression modelling was used to model the effects of temperature and holding time on the levels of the variables measured. Temperature treatment and holding time were found to significantly affect the polyacetylene content of carrot disks. Predicted models were found to be significant (p < 0.05) with high coefficients of determination (R2).

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The flow patterns in a high shear granulator depend on the fill volume. For example, DEM simulations reported by Terashita et al. [1] show that fill volume affects the velocities and kinetic energies of the particles. It also influences the granule size distribution [2]. Here the effects on the properties of the granule are described. The total mass of the granulate material was varied without changing the other variables such as impeller speed, granulation time and liquid to solid ratio. The resulting mechanical properties, such as strength, yield stress and Young's modulus, of the granules were measured. For the materials studied in the current work, increasing the fill factor (batch size) increased the values of these material parameters. This could be explained by the relative increase in the number and intensity of collisions between the particles, when the size of a batch was increased, leading to smaller porosities. (c) 2010 Elsevier B.V. All rights reserved.

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The effects of the process variables, pH of aqueous phase, rate of addition of organic, polymeric, drug-containing phase to aqueous phase, organic:aqueous phase volume ratio and aqueous phase temperature on the entrapment of propranolol hydrochloride in ethylcellulose (N4) microspheres prepared by the solvent evaporation method were examined using a factorial design. The observed range of drug entrapment was 1.43 +/- 0.02%w/w (pH 6, 25 degrees C, phase volume ratio 1:10, fast rate of addition) to 16.63 +/- 0.92%w/w (pH 9, 33 degrees C, phase volume ratio 1:10, slow rate of addition) which corresponded to mean entrapment efficiencies of 2.86 and 33.26, respectively. Increased pH, increased temperature and decreased rate of addition significantly enhanced entrapment efficiency. However, organic:aqueous phase volume ratio did not significantly affect drug entrapment. Statistical interactions were observed between pH and rate of addition, pH and temperature, and temperature and rate of addition. The observed interactions involving pH are suggested to be due to the abilities of increased temperature and slow rate of addition to sufficiently enhance the solubility of dichloromethane in the aqueous phase, which at pH 9, but not pH 6, allows partial polymer precipitation prior to drug partitioning into the aqueous phase. The interaction between temperature and rate of addition is due to the relative lack of effect of increased temperature on drug entrapment following slow rate of addition of the organic phase. In comparison to the effects of pH on drug entrapment, the contributions of the other physical factors examined were limited.

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The effects of four process factors: pH, emulsifier (gelatin) concentration, mixing and batch, on the % w/w entrapment of propranolol hydrochloride in ethylcellulose microcapsules prepared by the solvent evaporation process were examined using a factorial design. In this design the minimum % w/w entrapments of propranolol hydrochloride were observed whenever the external aqueous phase contained 1.5% w/v gelatin at pH 6.0 (0.71-0.91% w/w) whereas maximum entrapments occurred whenever the external aqueous phase was composed of 0.5% w/v gelatin at pH 9.0,(8.9-9.1% w/w). The theoretical maximum loading was 50% w/w. Statistical evaluation of the results by analysis of variance showed that emulsifer (gelatin) concentration and pH, but not mixing and batch significantly affected entrapment. An interaction between pH and gelatin concentration was observed in the factorial design which was accredited to the greater effect of gelatin concentration on % w/w entrapment at pH 9.0 than at pH 6.0. Maximum theoretical entrapment was achieved by increasing the pH of the external phase to 12.0. Marked increases in drug entrapment were observed whenever the pH of the external phase exceeded the pK(2) of propranolol hydrochloride. It was concluded that pH, and hence ionisation, was the greatest determinant of entrapment of propranolol hydrochloride into microcapsules prepared by the solvent evaporation process.

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The strength development of mortars containing ground granulated blast-furnace slag (ggbs) and portland cement was investigated. Variables were the level of ggbs in the binder, water-binder ratio and curing temperature. All mortars gain strength more rapidly at higher temperatures and have a lower calculated ultimate strength. The early age strength is much more sensitive to temperature for higher levels of ground granulated blast-furnace slag. The calculated ultimate strength is affected to a similar degree for all ggbs levels and water-binder ratios, with only the curing temperature having a significant effect. Apparent activation energies were determined according to ASTM C1074 and were found to vary approximately linearly with ggbs level from 34 kJ/mol for portland cement mortars to around 60 kJ/mol for mortars containing 70% ggbs. The water-binder ratio appears to have little or no effect oil the apparent activation energy. (c) 2005 Elsevier Ltd. All rights reserved.

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Cold-formed steel portal frames are a popular form of construction for low-rise commercial, light industrial and agricultural buildings with spans of up to 20 m. In this article, a real-coded genetic algorithm is described that is used to minimize the cost of the main frame of such buildings. The key decision variables considered in this proposed algorithm consist of both the spacing and pitch of the frame as continuous variables, as well as the discrete section sizes.A routine taking the structural analysis and frame design for cold-formed steel sections is embedded into a genetic algorithm. The results show that the real-coded genetic algorithm handles effectively the mixture of design variables, with high robustness and consistency in achieving the optimum solution. All wind load combinations according to Australian code are considered in this research. Results for frames with knee braces are also included, for which the optimization achieved even larger savings in cost.