Dimensionality, Reliability and Validity of the InterRAI Depression Rating Scale in a Canadian Palliative Care Population

A reliable and valid instrument is needed to screen for depression in palliative patients. The interRAI Depression Rating Scale (DRS) is based on seven items in the interRAI Palliative Care instrument. This study is the first to explore the dimensionality, reliability and validity of the DRS in a palliative population. Palliative home care patients (n = 5,175) residing in Ontario (Canada) were assessed with the interRAI Palliative Care instrument. Exploratory factor analysis and Mokken scale analysis were used to identify candidate conceptual models and evaluate scale homogeneity/performance. Confirmatory factor analysis compared models using standard goodness-of-fit indices. Convergent and divergent validity were investigated by examining polychoric correlations between the DRS and other items. The “known groups” test determined if the DRS meaningfully distinguished among client subgroups. The non-hierarchical two factor model showed acceptable fit with the data, and ordinal alpha coefficients of 0.83 and 0.82 were observed for the two DRS subscales. Omega hierarchical (ωh) was 0.78 for the bifactor model, with the general factor explaining three quarters of the common variance. Despite the multidimensionality evident in the factor analyses, bifactor modelling and the Mokken homogeneity coefficient (0.34) suggest that the DRS is a coherent scale that captures important information on sub-constructs of depression (e.g., somatic symptoms). Higher correlations were seen between the DRS and mood and psychosocial well-being items, and lower correlations with functional status and demographic variables. The DRS distinguished in the expected manner for known risk factors (e.g., social support, pain). The results suggest that the DRS is primarily unidimensional and reliable for use in screening for depression in palliative care patients.

Integration of shading and texture cues: testing the linear model

One of the first attempts to develop a formal model of depth cue integration is to be found in Maloney and Landy's (1989) "human depth combination rule". They advocate that the combination of depth cues by the visual sysetem is best described by a weighted linear model. The present experiments tested whether the linear combination rule applies to the integration of texture and shading. As would be predicted by a linear combination rule, the weight assigned to the shading cue did vary as a function of its curvature value. However, the weight assigned to the texture cue varied systematically as a function of the curvature value of both cues. Here we descrive a non-linear model which provides a better fit to the data. Redescribing the stimuli in terms of depth rather than curvature reduced the goodness of fit for all models tested. These results support the hypothesis that the locus of cue integration is a curvature map, rather than a depth map. We conclude that the linear comination rule does not generalize to the integration of shading and texture, and that for these cues it is likely that integration occurs after the recovery of surface curvature.

Coefficient of consolidation by plotting velocity against displacement

A method is presented for estimating the initial compression, the final compression and the coefficient of consolidation from an observed, experimental consolidation response, using a plot of velocity versus displacement and the conventional Taylor plot of compression versus the square root of time. Goodness of fit measures indicate that the method produces good agreement between fitted and measured displacement values, at least up until the point where the impact of secondary compression on the overall displacement response becomes significant.

Remediation of phenol-contaminated water by adsorption using poly(methyl methacrylate) (PMMA)

Recently polymeric adsorbents have been emerging as highly effective alternatives to activated carbons for pollutant removal from industrial effluents. Poly(methyl methacrylate) (PMMA), polymerized using the atom transfer radical polymerization (ATRP) technique has been investigated for its feasibility to remove phenol from aqueous solution. Adsorption equilibrium and kinetic investigations were undertaken to evaluate the effect of contact time, initial concentration (10-90 mg/L), and temperature (25-55 degrees C). Phenol uptake was found to increase with increase in initial concentration and agitation time. The adsorption kinetics were found to follow the pseudo-second-order kinetic model. The intra-particle diffusion analysis indicated that film diffusion may be the rate controlling step in the removal process. Experimental equilibrium data were fitted to five different isotherm models namely Langmuir, Freundlich, Dubinin-Radushkevich, Temkin and Redlich-Peterson by non-linear least square regression and their goodness-of-fit evaluated in terms of mean relative error (MRE) and standard error of estimate (SEE). The adsorption equilibrium data were best represented by Freundlich and Redlich-Peterson isotherms. Thermodynamic parameters such as Delta G degrees and Delta H degrees indicated that the sorption process is exothermic and spontaneous in nature and that higher ambient temperature results in more favourable adsorption. (C) 2011 Elsevier B.V. All rights reserved.

Random Regret Minimization: Exploration of a New Choice Model for Environmental and Resource Economics

This paper introduces the discrete choice model-paradigm of Random Regret Minimization (RRM) to the field of environmental and resource economics. The RRM-approach has been very recently developed in the context of travel demand modelling and presents a tractable, regret-based alternative to the dominant choice-modelling paradigm based on Random Utility Maximization-theory (RUM-theory). We highlight how RRM-based models provide closed form, logit-type formulations for choice probabilities that allow for capturing semi-compensatory behaviour and choice set-composition effects while being equally parsimonious as their utilitarian counterparts. Using data from a Stated Choice-experiment aimed at identifying valuations of characteristics of nature parks, we compare RRM-based models and RUM-based models in terms of parameter estimates, goodness of fit, elasticities and consequential policy implications.

Statistical-mechanical description of classical test-particle dynamics in the presence of an external force field: modelling noise and damping from first principles

Aiming to establish a rigorous link between macroscopic random motion (described e.g. by Langevin-type theories) and microscopic dynamics, we have undertaken a kinetic-theoretical study of the dynamics of a classical test-particle weakly coupled to a large heat-bath in thermal equilibrium. Both subsystems are subject to an external force field. From the (time-non-local) generalized master equation a Fokker-Planck-type equation follows as a "quasi-Markovian" approximation. The kinetic operator thus defined is shown to be ill-defined; in specific, it does not preserve the positivity of the test-particle distribution function f(x, v; t). Adopting an alternative approach, previously introduced for quantum open systems, is proposed to lead to a correct kinetic operator, which yields all the expected properties. A set of explicit expressions for the diffusion and drift coefficients are obtained, allowing for modelling macroscopic diffusion and dynamical friction phenomena, in terms of an external field and intrinsic physical parameters.

A prospective randomised trial of a "test and treat" policy versus endoscopy based management in young Helicobacter pylori positive patients with ulcer-like dyspepsia, referred to a hospital clinic

Management of dyspepsia remains a controversial area. Although the European Helicobacter pylori study group has advised empirical eradication therapy without oesophagogastroduodenoscopy (OGD) in young H pylori positive dyspeptic patients who do not exhibit alarm symptoms, this strategy has not been subjected to clinical trial.

Inverse Gaussian Modeling of Turbulence-Induced Fading in Free-Space Optical Systems

We propose the inverse Gaussian distribution, as a less complex alternative to the classical log-normal model, to describe turbulence-induced fading in free-space optical (FSO) systems operating in weak turbulence conditions and/or in the presence of aperture averaging effects. By conducting goodness of fit tests, we define the range of values of the scintillation index for various multiple-input multiple-output (MIMO) FSO configurations, where the two distributions approximate each other with a certain significance level. Furthermore, the bit error rate performance of two typical MIMO FSO systems is investigated over the new turbulence model; an intensity-modulation/direct detection MIMO FSO system with Q-ary pulse position modulation that employs repetition coding at the transmitter and equal gain combining at the receiver, and a heterodyne MIMO FSO system with differential phase-shift keying and maximal ratio combining at the receiver. Finally, numerical results are presented that validate the theoretical analysis and provide useful insights into the implications of the model parameters on the overall system performance. © 2011 IEEE.

Clinical and Cost-Effectiveness of Procalcitonin Test for Prodromal Meningococcal Disease-A Meta-Analysis

BACKGROUND: Despite vaccines and improved medical intensive care, clinicians must continue to be vigilant of possible Meningococcal Disease in children. The objective was to establish if the procalcitonin test was a cost-effective adjunct for prodromal Meningococcal Disease in children presenting at emergency department with fever without source.

METHODS AND FINDINGS: Data to evaluate procalcitonin, C-reactive protein and white cell count tests as indicators of Meningococcal Disease were collected from six independent studies identified through a systematic literature search, applying PRISMA guidelines. The data included 881 children with fever without source in developed countries.The optimal cut-off value for the procalcitonin, C-reactive protein and white cell count tests, each as an indicator of Meningococcal Disease, was determined. Summary Receiver Operator Curve analysis determined the overall diagnostic performance of each test with 95% confidence intervals. A decision analytic model was designed to reflect realistic clinical pathways for a child presenting with fever without source by comparing two diagnostic strategies: standard testing using combined C-reactive protein and white cell count tests compared to standard testing plus procalcitonin test. The costs of each of the four diagnosis groups (true positive, false negative, true negative and false positive) were assessed from a National Health Service payer perspective. The procalcitonin test was more accurate (sensitivity=0.89, 95%CI=0.76-0.96; specificity=0.74, 95%CI=0.4-0.92) for early Meningococcal Disease compared to standard testing alone (sensitivity=0.47, 95%CI=0.32-0.62; specificity=0.8, 95% CI=0.64-0.9). Decision analytic model outcomes indicated that the incremental cost effectiveness ratio for the base case was £-8,137.25 (US $ -13,371.94) per correctly treated patient.

CONCLUSIONS: Procalcitonin plus standard recommended tests, improved the discriminatory ability for fatal Meningococcal Disease and was more cost-effective; it was also a superior biomarker in infants. Further research is recommended for point-of-care procalcitonin testing and Markov modelling to incorporate cost per QALY with a life-time model.

Switched Diversity Techniques for Indoor Off-body Communications Channels: An Experimental Analysis and Modeling

This paper investigates the potential improvement in signal reliability for indoor off-body communications channels operating at 5.8 GHz using switched diversity techniques. In particular we investigate the performance of switch-and-stay combining (SSC), switch-and-examine combining (SEC) and switch-and-examine combining with post-examining selection (SECps) schemes which utilize multiple spatially separated antennas at the base station. During the measurements a test subject, wearing an antenna on his chest, performed a number of walking movements towards and then away from a uniform linear array. It was found that all of the considered diversity schemes provided a worthwhile signal improvement. However, the performance of the diversity systems varied according to the switching threshold that was adopted. To model the fading envelope observed at the output of each of the combiners, we have applied diversity specific equations developed under the assumption of Nakagami-$m$ fading. As a measure of the goodness-of-fit, the Kullback-Leibler divergence between the empirical and theoretical probability density functions (PDFs) was calculated and found to be close to 0. To assist with the interpretation of the goodness-of-fit achieved in this study, the standard deviation, $\sigma$, of a zero-mean, $\sigma^2$ variance Gaussian PDF used to approximate a zero-mean, unit variance Gaussian PDF is also presented. These were generally quite close to 1 indicating that the theoretical models provided an adequate fit to the measured data.

B-type supergiants in the Small Magellanic Cloud: rotational velocities and implications for evolutionary models

High-resolution spectra for 24 SMC and Galactic B-type supergiants have been analysed to estimate the contributions of both macroturbulence and rotation to the broadening of their metal lines. Two different methodologies are considered, viz. goodness-of-fit comparisons between observed and theoretical line profiles and identifying zeros in the Fourier transforms of the observed profiles. The advantages and limitations of the two methods are briefly discussed with the latter techniques being adopted for estimating projected rotational velocities ( v sin i) but the former being used to estimate macroturbulent velocities. The projected rotational velocity estimates range from approximately 20 to 60 kms(-1), apart from one SMC supergiant, Sk 191, with a v sin i similar or equal to 90 km s(-1). Apart from Sk 191, the distribution of projected rotational velocities as a function of spectral type are similar in both our Galactic and SMC samples with larger values being found at earlier spectral types. There is marginal evidence for the projected rotational velocities in the SMC being higher than those in the Galactic targets but any differences are only of the order of 5 - 10 km s(-1), whilst evolutionary models predict differences in this effective temperature range of typically 20 to 70 km s(-1). The combined sample is consistent with a linear variation of projected rotational velocity with effective temperature, which would imply rotational velocities for supergiants of 70 kms(-1) at an effective temperature of 28 000 K ( approximately B0 spectral type) decreasing to 32 km s(-1) at 12 000 K (B8 spectral type). For all targets, the macroturbulent broadening would appear to be consistent with a Gaussian distribution ( although other distributions cannot be discounted) with an 1/e half-width varying from approximately 20 km s(-1) at B8 to 60 km s(-1) at B0 spectral types.

Radiocarbon peat chronologies and environmental change

Raised bog peat deposits form important archives for reconstructing past changes in climate. Precise and reliable age models are of vital importance for interpreting such archives. We propose enhanced, Markov chain Monte Carlo based methods for obtaining age models from radiocarbon-dated peat cores, based on the assumption of piecewise linear accumulation. Included are automatic choice of sections, a measure of the goodness of fit and outlier downweighting. The approach is illustrated by using a peat core from the Netherlands.

Experimenting with the Coxian Phase-Type Distribution to Uncover Suitable Fits

In the past few decades, Coxian phase-type distributions have become increasingly more popular as a means of representing survival times. In healthcare, they are considered suitable for modelling the length of stay of patients in hospital and more recently for modelling the patient waiting times in Accident and Emergency Departments. The Coxian phase-type distribution has not only been shown to provide a good representation of real survival data, but its interpretation seems reasonably initiative to the medical experts. The drawback, however, is fitting the distribution to the data. There have been many attempts at accurately estimating the Coxian phase-type parameters. This paper wishes to examine the most promising of the approaches reported in the literature to determine the most accurate. Three performance measures are introduced to assess the fitting process of the algorithms along with the likelihood values and AIC to examine the goodness of fit and complexity of the model. Previous research suggests that the fitting process is strongly influenced by the initial parameter estimates and the data itself being quite variable. To overcome this, one experiment in this research paper will use the same initial parameter values for each estimation and perform the fits on the data simulated from a Coxian phase-type distribution with known parameters.

Incorporating uncertainty in predictive species distribution modelling

Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.