Measurement properties of the CHAMPS physical activity questionnaire in a sample of older Australians

Background: The effective evaluation of physical activity interventions for older adults requires measurement instruments with acceptable psychometric properties that are sufficiently sensitive to detect changes in this population. Aim: To assess the measurement properties (reliability and validity) of the Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire in a sample of older Australians. Methods: CHAMPS data were collected from 167 older adults (mean age 79.1 S.D. 6.3 years) and validated with tests of physical ability and the SF-12 measures of physical and mental health. Responses from a sub-sample of 43 older adults were used to assess 1-week test-retest reliability. Results: Approximately 25% of participants needed assistance to complete the CHAMPS questionnaire. There were low but significant correlations between the CHAMPS scores and the physical performance measures (rho=0.14-0.32) and the physical health scale of the SF-12 (rho=0.12-0.24). Reliability coefficients were highest for moderate-intensity (ICC=0.81-0.88) and lowest for vigorous-intensity physical activity (ICC=0.34-0.45). Agreement between test-retest estimates of sufficient physical activity for health benefits (>= 150 min and >= 5 sessions per week) was high (percent agreement = 88% and Cohen's kappa = 0.68). Conclusion: These findings suggest that the CHAMPS questionnaire has acceptable measurement properties, and is therefore suitable for use among older Australian adults, as long as adequate assistance is provided during administration. (c) 2006 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Effect of deposition conditions on mechanical properties of low-temperature PECVD silicon nitride films

The effect of deposition conditions on characteristic mechanical properties - elastic modulus and hardness - of low-temperature PECVD silicon nitrides is investigated using nanoindentation. lt is found that increase in substrate temperature, increase in plasma power and decrease in chamber gas pressure all result in increases in elastic modulus and hardness. Strong correlations between the mechanical properties and film density are demonstrated. The silicon nitride density in turn is shown to be related to the chemical composition of the films, particularly the silicon/nitrogen ratio. (c) 2006 Elsevier B.V. All rights reserved.

Bed expansion:extending correlations for fluidized beds with inserts to open fluidized beds

Bed expansion occurs during the operation of gas-fluidized beds and is influenced by particle properties, gas properties and distributor characteristics. It has a significant bearing on heat and mass transfer phenomena within the bed. A method of predicting bed expansion behavior from other fluidizing parameters would be a useful tool in the design process, dispensing with the need for small-scale trials. This study builds on previous work on fluidized beds with vertical inserts to produce a correlation that links a modified particle terminal velocity, minimum fluidizing velocity and distributor characteristics with bed voidage in the relationship with P as the pitch between holes in the perforated distributor plate. © 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structure-reactivity correlations in sulphated-zirconia catalysts for the isomerisation of α-pinene

A range of mesoporous sulphated zirconias with tuneable structural and catalytic properties have been prepared by direct impregnation. The surface sulphate coverage can be readily varied, achieving a maximum value of ∼0.2 monolayers. High-temperature calcination induces the crystallisation of tetragonal zirconia while suppressing the monoclinic phase and enhances surface acidity. Superacid sites only appear above a critical threshold SO4 coverage of 0.08 mL (corresponding to 0.44 wt% total S). Sulphated zirconias show good activity towards α-pinene isomerisation of under mild conditions. Conversion correlates with the number Brønsted acid sites, while the selectivity towards mono- versus polycyclic products depends on the corresponding acid site strength; superacidity promotes limonene formation over camphene.

Revealing statistical properties of quasi-CW fibre lasers in bandwidth-limited measurements

We introduce a general technique how to reveal in experiments of limited electrical bandwidth which is lower than the optical bandwidth of the optical signal under study, whether the statistical properties of the light source obey Gaussian distribution or mode correlations do exist. To do that one needs to perform measurements by decreasing the measurement bandwidth. We develop a simple model of bandwidth-limited measurements and predict universal laws how intensity probability density function and intensity auto-correlation function of ideal completely stochastic source of Gaussian statistics depend on limited measurement bandwidth and measurement noise level. Results of experimental investigation are in good agreement with model predictions. In particular, we reveal partial mode correlations in the radiation of quasi-CW Raman fibre laser.

Reference list of 265 sources used for the discovery of relationships between data clusters and metadata properties

Visual cluster analysis provides valuable tools that help analysts to understand large data sets in terms of representative clusters and relationships thereof. Often, the found clusters are to be understood in context of belonging categorical, numerical or textual metadata which are given for the data elements. While often not part of the clustering process, such metadata play an important role and need to be considered during the interactive cluster exploration process. Traditionally, linked-views allow to relate (or loosely speaking: correlate) clusters with metadata or other properties of the underlying cluster data. Manually inspecting the distribution of metadata for each cluster in a linked-view approach is tedious, specially for large data sets, where a large search problem arises. Fully interactive search for potentially useful or interesting cluster to metadata relationships may constitute a cumbersome and long process. To remedy this problem, we propose a novel approach for guiding users in discovering interesting relationships between clusters and associated metadata. Its goal is to guide the analyst through the potentially huge search space. We focus in our work on metadata of categorical type, which can be summarized for a cluster in form of a histogram. We start from a given visual cluster representation, and compute certain measures of interestingness defined on the distribution of metadata categories for the clusters. These measures are used to automatically score and rank the clusters for potential interestingness regarding the distribution of categorical metadata. Identified interesting relationships are highlighted in the visual cluster representation for easy inspection by the user. We present a system implementing an encompassing, yet extensible, set of interestingness scores for categorical metadata, which can also be extended to numerical metadata. Appropriate visual representations are provided for showing the visual correlations, as well as the calculated ranking scores. Focusing on clusters of time series data, we test our approach on a large real-world data set of time-oriented scientific research data, demonstrating how specific interesting views are automatically identified, supporting the analyst discovering interesting and visually understandable relationships.

Measuring, Modeling, and Forecasting Volatility and Correlations from High-Frequency Data

This dissertation contains four essays that all share a common purpose: developing new methodologies to exploit the potential of high-frequency data for the measurement, modeling and forecasting of financial assets volatility and correlations. The first two chapters provide useful tools for univariate applications while the last two chapters develop multivariate methodologies. In chapter 1, we introduce a new class of univariate volatility models named FloGARCH models. FloGARCH models provide a parsimonious joint model for low frequency returns and realized measures, and are sufficiently flexible to capture long memory as well as asymmetries related to leverage effects. We analyze the performances of the models in a realistic numerical study and on the basis of a data set composed of 65 equities. Using more than 10 years of high-frequency transactions, we document significant statistical gains related to the FloGARCH models in terms of in-sample fit, out-of-sample fit and forecasting accuracy compared to classical and Realized GARCH models. In chapter 2, using 12 years of high-frequency transactions for 55 U.S. stocks, we argue that combining low-frequency exogenous economic indicators with high-frequency financial data improves the ability of conditionally heteroskedastic models to forecast the volatility of returns, their full multi-step ahead conditional distribution and the multi-period Value-at-Risk. Using a refined version of the Realized LGARCH model allowing for time-varying intercept and implemented with realized kernels, we document that nominal corporate profits and term spreads have strong long-run predictive ability and generate accurate risk measures forecasts over long-horizon. The results are based on several loss functions and tests, including the Model Confidence Set. Chapter 3 is a joint work with David Veredas. We study the class of disentangled realized estimators for the integrated covariance matrix of Brownian semimartingales with finite activity jumps. These estimators separate correlations and volatilities. We analyze different combinations of quantile- and median-based realized volatilities, and four estimators of realized correlations with three synchronization schemes. Their finite sample properties are studied under four data generating processes, in presence, or not, of microstructure noise, and under synchronous and asynchronous trading. The main finding is that the pre-averaged version of disentangled estimators based on Gaussian ranks (for the correlations) and median deviations (for the volatilities) provide a precise, computationally efficient, and easy alternative to measure integrated covariances on the basis of noisy and asynchronous prices. Along these lines, a minimum variance portfolio application shows the superiority of this disentangled realized estimator in terms of numerous performance metrics. Chapter 4 is co-authored with Niels S. Hansen, Asger Lunde and Kasper V. Olesen, all affiliated with CREATES at Aarhus University. We propose to use the Realized Beta GARCH model to exploit the potential of high-frequency data in commodity markets. The model produces high quality forecasts of pairwise correlations between commodities which can be used to construct a composite covariance matrix. We evaluate the quality of this matrix in a portfolio context and compare it to models used in the industry. We demonstrate significant economic gains in a realistic setting including short selling constraints and transaction costs.

Assessing the influence of abiotic factors and leaf-level properties on the stability of growing-season canopy greenness in a deciduous forest

Maps depicting spatial pattern in the stability of summer greenness could advance understanding of how forest ecosystems will respond to global changes such as a longer growing season. Declining summer greenness, or “greendown”, is spectrally related to declining near-infrared reflectance and is observed in most remote sensing time series to begin shortly after peak greenness at the end of spring and extend until the beginning of leaf coloration in autumn,. Understanding spatial patterns in the strength of greendown has recently become possible with the advancement of Landsat phenology products, which show that greendown patterns vary at scales appropriate for linking these patterns to proposed environmental forcing factors. This study tested two non-mutually exclusive hypotheses for how leaf measurements and environmental factors correlate with greendown and decreasing NIR reflectance across sites. At the landscape scale, we used linear regression to test the effects of maximum greenness, elevation, slope, aspect, solar irradiance and canopy rugosity on greendown. Secondly, we used leaf chemical traits and reflectance observations to test the effect of nitrogen availability and intrinsic water use efficiency on leaf-level greendown, and landscape-level greendown measured from Landsat. The study was conducted using Quercus alba canopies across 21 sites of an eastern deciduous forest in North America between June and August 2014. Our linear model explained greendown variance with an R2=0.47 with maximum greenness as the greatest model effect. Subsequent models excluding one model effect revealed elevation and aspect were the two topographic factors that explained the greatest amount of greendown variance. Regression results also demonstrated important interactions between all three variables, with the greatest interaction showing that aspect had greater influence on greendown at sites with steeper slopes. Leaf-level reflectance was correlated with foliar δ13C (proxy for intrinsic water use efficiency), but foliar δ13C did not translate into correlations with landscape-level variation in greendown from Landsat. Therefore, we conclude that Landsat greendown is primarily indicative of landscape position, with a small effect of canopy structure, and no measureable effect of leaf reflectance. With this understanding of Landsat greendown we can better explain the effects of landscape factors on vegetation reflectance and perhaps on phenology, which would be very useful for studying phenology in the context of global climate change

Estimates of genetic parameters for growth and wood properties in Eucalyptus pellita F. Muell. to support tree breeding in Vietnam

Eucalyptus pellita demonstrated good growth and wood quality traits in this study, with young plantation grown timber being suitable for both solid and pulp wood products. All traits examined were under moderate levels of genetic control with little genotype by environment interaction when grown on two contrasting sites in Vietnam. Eucalyptus pellita currently has a significant role in reforestation in the tropics. Research to support expanded of use of this species is needed: particularly, research to better understand the genetic control of key traits will facilitate the development of genetically improved planting stock. This study aimed to provide estimates of the heritability of diameter at breast height over bark, wood basic density, Kraft pulp yield, modulus of elasticity and microfibril angle, and the genetic correlations among these traits, and understand the importance of genotype by environment interactions in Vietnam. Data for diameter and wood properties were collected from two 10-year-old, open-pollinated progeny trials of E. pellita in Vietnam that evaluated 104 families from six native range and three orchard sources. Wood properties were estimated from wood samples using near-infrared (NIR) spectroscopy. Data were analysed using mixed linear models to estimate genetic parameters (heritability, proportion of variance between seed sources and genetic correlations). Variation among the nine sources was small compared to additive variance. Narrow-sense heritability and genetic correlation estimates indicated that simultaneous improvements in most traits could be achieved from selection among and within families as the genetic correlations among traits were either favourable or close to zero. Type B genetic correlations approached one for all traits suggesting that genotype by environment interactions were of little importance. These results support a breeding strategy utilizing a single breeding population advanced by selecting the best individuals across all seed sources. Both growth and wood properties have been evaluated. Multi-trait selection for growth and wood property traits will lead to more productive populations of E. pellita both with improved productivity and improved timber and pulp properties.

Development and preliminary psychometric properties of the Care Experience Feedback Improvement Tool (CEFIT).

Objective To develop a structurally valid and reliable, yet brief measure of patient experience of hospital quality of care, the Care Experience Feedback Improvement Tool (CEFIT). Also, to examine aspects of utility of CEFIT. Background Measuring quality improvement at the clinical interface has become a necessary component of healthcare measurement and improvement plans, but the effectiveness of measuring such complexity is dependent on the purpose and utility of the instrument used. Methods CEFIT was designed from a theoretical model, derived from the literature and a content validity index (CVI) procedure. A telephone population surveyed 802 eligible participants (healthcare experience within the previous 12 months) to complete CEFIT. Internal consistency reliability was tested using Cronbach's α. Principal component analysis was conducted to examine the factor structure and determine structural validity. Quality criteria were applied to judge aspects of utility. Results CVI found a statistically significant proportion of agreement between patient and practitioner experts for CEFIT construction. 802 eligible participants answered the CEFIT questions. Cronbach's α coefficient for internal consistency indicated high reliability (0.78). Interitem (question) total correlations (0.28–0.73) were used to establish the final instrument. Principal component analysis identified one factor accounting for 57.3% variance. Quality critique rated CEFIT as fair for content validity, excellent for structural validity, good for cost, poor for acceptability and good for educational impact. Conclusions CEFIT offers a brief yet structurally sound measure of patient experience of quality of care. The briefness of the 5-item instrument arguably offers high utility in practice. Further studies are needed to explore the utility of CEFIT to provide a robust basis for feedback to local clinical teams and drive quality improvement in the provision of care experience for patients. Further development of aspects of utility is also required.

Children's Separation Anxiety Scale (CSAS): Psychometric Properties

This study describes the psychometric properties of the Children's Separation Anxiety Scale (CSAS), which assesses separation anxiety symptoms in childhood. Participants in Study 1 were 1,908 schoolchildren aged between 8 and 11. Exploratory factor analysis identified four factors: worry about separation, distress from separation, opposition to separation, and calm at separation, which explained 46.91% of the variance. In Study 2, 6,016 children aged 8–11 participated. The factor model in Study 1 was validated by confirmatory factor analysis. The internal consistency (α = 0.82) and temporal stability (r = 0.83) of the instrument were good. The convergent and discriminant validity were evaluated by means of correlations with other measures of separation anxiety, childhood anxiety, depression and anger. Sensitivity of the scale was 85% and its specificity, 95%. The results support the reliability and validity of the CSAS.

Statistical properties of radiation of multiwavelength random DFB fiber laser

In the presented paper, the temporal and statistical properties of a Lyot filter based multiwavelength random DFB fiber laser with a wide flat spectrum, consisting of individual lines, were investigated. It was shown that separate spectral lines forming the laser spectrum have mostly Gaussian statistics and so represent stochastic radiation, but at the same time the entire radiation is not fully stochastic. A simple model, taking into account phenomenological correlations of the lines' initial phases was established. Radiation structure in the experiment and simulation proved to be different, demanding interactions between different lines to be described via a NLSE-based model.

Computing the structural and vibrational properties of polymorphic organic molecular crystals through van der Waals corrected density functional theory and the electronic properties of organic thin films through microelectrostatic calculations.

The present Thesis reports on the various research projects to which I have contributed during my PhD period, working with several research groups, and whose results have been communicated in a number of scientific publications. The main focus of my research activity was to learn, test, exploit and extend the recently developed vdW-DFT (van der Waals corrected Density Functional Theory) methods for computing the structural, vibrational and electronic properties of ordered molecular crystals from first principles. A secondary, and more recent, research activity has been the analysis with microelectrostatic methods of Molecular Dynamics (MD) simulations of disordered molecular systems. While only very unreliable methods based on empirical models were practically usable until a few years ago, accurate calculations of the crystal energy are now possible, thanks to very fast modern computers and to the excellent performance of the best vdW-DFT methods. Accurate energies are particularly important for describing organic molecular solids, since they often exhibit several alternative crystal structures (polymorphs), with very different packing arrangements but very small energy differences. Standard DFT methods do not describe the long-range electron correlations which give rise to the vdW interactions. Although weak, these interactions are extremely sensitive to the packing arrangement, and neglecting them used to be a problem. The calculations of reliable crystal structures and vibrational frequencies has been made possible only recently, thanks to development of some good representations of the vdW contribution to the energy (known as “vdW corrections”).

The Crosslinking Degree Controls The Mechanical, Rheological, And Swelling Properties Of Hyaluronic Acid Microparticles.

Viscosupplements, used for treating joint and cartilage diseases, restore the rheological properties of synovial fluid, regulate joint homeostasis and act as scaffolds for cell growth and tissue regeneration. Most viscosupplements are hydrogels composed of hyaluronic acid (HA) microparticles suspended in fluid HA. These microparticles are crosslinked with chemicals to assure their stability against enzyme degradation and to prolong the action of the viscosupplement. However, the crosslinking also modifies the mechanical, swelling and rheological properties of the HA microparticle hydrogels, with consequences on the effectiveness of the application. The aim of this study is to correlate the crosslinking degree (CD) with these properties to achieve modulation of HA/DVS microparticles through CD control. Because divinyl sulfone (DVS) is the usual crosslinker of HA in viscosupplements, we examined the effects of CD by preparing HA microparticles at 1:1, 2:1, 3:1, and 5:1 HA/DVS mass ratios. The CD was calculated from inductively coupled plasma spectrometry data. HA microparticles were previously sized to a mean diameter of 87.5 µm. Higher CD increased the viscoelasticity and the extrusion force and reduced the swelling of the HA microparticle hydrogels, which also showed Newtonian pseudoplastic behavior and were classified as covalent weak. The hydrogels were not cytotoxic to fibroblasts according to an MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide) assay. © 2014 Wiley Periodicals, Inc. J Biomed Mater Res Part A, 2014.