920 resultados para measurement techniques of Aerosoles


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Research on the physiological adaptation process has found that stress is associated with the rate of cortisol secretion, the main hormone that reflects stress. However, considerable variation among subjects has been reported. Using a sample of older adults (N=46), we tested the hypothesis that cortisol reactivity is composed of (1) a situation-related component representing hypothalamic influence on cortisol secretion observed on three different occasions, and (2) a stable component representing a general trait responsible for cortisol responses observed from occasion to occasion. LISREL VIII was used to test this hypothesis. Results indicated that a homogeneous reliability model was not supported by the data. A congeneric measurement model represented a better fit to the data. Results suggest that subjects have consistent patterns of response during separate experimental occasions. However, results do not suggest a consistent pattern of response over time. The main implication of these results is that salivary cortisol measures are sensitive to experimental stress situations. As such, this noninvasive method may be useful in examining adaptive responses to stress.

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This study evaluated the five-factor measurement model of the abbreviated Multidimensional Observation Scale for Elderly Subjects (MOSES), originally proposed by Pruchno, Kleban, and Resch in 1988. Modifications of the five-factor model were examined and evaluated with regard to their practical significance. A confirmatory second-order factor analysis was performed to examine whether the correlations among the first-order factors were adequately accounted for by a global dysfunction factor. Findings indicated that the proposed measurement model was replicated adequately. Although post hoc modifications resulted in significant improvements in overall model fit, the minor parameters had only a trivial influence on the major parameters of the baseline model. Results from the second-order factor analysis showed that a global dysfunc tion factor accounted adequately for the intercorrelations among the first-order factors.

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Workshop Overview The use of special effects (moulage) is a way to augment the authenticity of a scenario in simulation. This workshop will introduce different techniques of moulage (oil based cream colors, watercolors, transfer tattoos and 3D Prosthetics). The participants will have the opportunity to explore these techniques by applying various moulages. They will compare the techniques and discuss their advantages and disadvantages. Moreover, strategies for standardization and quality assurance will be discussed. Workshop Rationale Moulage supports the sensory perception in an scenario (1). It can provide evaluation clues (2) and help learners (and SPs) to engage in the simulation. However, it is of crucial importance that the simulated physical pathologies are represented accurate and reliable. Accuracy is achieved by using the appropriate technique, which requires knowledge and practice . With information about different moulage techniques, we hope to increases the knowledge of moulage during the workshop. By applying moulages in various techniques we will practice together. As standardization is critical for simulation scenarios in assessment (3, 4) strategies for standardization of moulage will be introduced and discussed. Workshop Objectives During the workshop participants will: - gain knowledge about different techniques of moulages - practice moulages in various techniques - discuss the advantages and disadvantages of moulage techniques - describe strategies for standardization and quality assurance of moulage Planned Format 5 min Introduction 15 min Overview – Background & Theory (presentation) 15 min Application of moulage for ankle sprain in 4 different techniques (oil based cream color, water color, temporary tatoo, 3D prosthetic) in small groups 5 min Comparing the results by interactive viewing of prepared moulages 15 min Application of moulages for burn in different techniques in small groups 5 min Comparing results the results by interactive viewing of prepared moulages 5 min Sharing experiences with different techniques in small groups 20 min Discussion of the techniques including standardization and quality assurance strategies (plenary discussion) 5 min Summary / Take home points

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Objectives. This paper seeks to assess the effect on statistical power of regression model misspecification in a variety of situations. ^ Methods and results. The effect of misspecification in regression can be approximated by evaluating the correlation between the correct specification and the misspecification of the outcome variable (Harris 2010).In this paper, three misspecified models (linear, categorical and fractional polynomial) were considered. In the first section, the mathematical method of calculating the correlation between correct and misspecified models with simple mathematical forms was derived and demonstrated. In the second section, data from the National Health and Nutrition Examination Survey (NHANES 2007-2008) were used to examine such correlations. Our study shows that comparing to linear or categorical models, the fractional polynomial models, with the higher correlations, provided a better approximation of the true relationship, which was illustrated by LOESS regression. In the third section, we present the results of simulation studies that demonstrate overall misspecification in regression can produce marked decreases in power with small sample sizes. However, the categorical model had greatest power, ranging from 0.877 to 0.936 depending on sample size and outcome variable used. The power of fractional polynomial model was close to that of linear model, which ranged from 0.69 to 0.83, and appeared to be affected by the increased degrees of freedom of this model.^ Conclusion. Correlations between alternative model specifications can be used to provide a good approximation of the effect on statistical power of misspecification when the sample size is large. When model specifications have known simple mathematical forms, such correlations can be calculated mathematically. Actual public health data from NHANES 2007-2008 were used as examples to demonstrate the situations with unknown or complex correct model specification. Simulation of power for misspecified models confirmed the results based on correlation methods but also illustrated the effect of model degrees of freedom on power.^

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One of the most significant aspects of a building?s acoustic behavior is the airborne sound insulation of the room façades, since this determines the protection of its inhabitants against environmental noise. For this reason, authorities in most countries have established in their acoustic regulations for buildings the minimum value of sound insulation that must be respected for façades. In order to verify compliance with legal requirements it is usual to perform acoustic measurements in the finished buildings and then compare the measurement results with the established limits. Since there is always a certain measurement uncertainty, this uncertainty must be calculated and taken into account in order to ensure compliance with specifications. The most commonly used method for measuring sound insulation on façades is the so-called Global Loudspeaker Method, specified in ISO 140-5:1998. This method uses a loudspeaker placed outside the building as a sound source. The loudspeaker directivity has a significant influence on the measurement results, and these results may change noticeably by choosing different loudspeakers, even though they all fulfill the directivity requirements of ISO 140-5. This work analyzes the influence of the loudspeaker directivity on the results of façade sound insulation measurement, and determines its contribution to measurement uncertainty. The theoretical analysis is experimentally validated by means of an intermediate precision test according to ISO 5725-3:1994, which compares the values of sound insulation obtained for a façade using various loudspeakers with different directivities. Keywords: Uncertainty, Façade, Insulation