Measurement of a reciprocal four-port transmission line structure using the 16-term error model

A new method to measure reciprocal four-port structures, using a 16-term error model, is presented. The measurement is based on 5 two-port calibration standards connected to two of the ports, while the network analyzer is connected to the two remaining ports. Least-squares-fit data reduction techniques are used to lower error sensitivity. The effect of connectors is deembedded using closed-form equations. (C) 2007 Wiley Periodicals, Inc.

Investigation of the permeation of model formulations and a commercial ibuprofen formulation in Carbosil® and human skin using ATR-FTIR and multivariate spectral analysis

The purpose of the present study was to use attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) and target factor analysis (TFA) to investigate the permeation of model drugs and formulation components through Carbosil® membrane and human skin. Diffusion studies of saturated solutions in 50:50 water/ethanol of methyl paraben (MP), ibuprofen (IBU) and caffeine (CF) were performed on Carbosil® membrane. The spectroscopic data were analysed by target factor analysis, and evolution profiles of the signal for each component (i.e. the drug, water, ethanol and membrane) over time were obtained. Results showed that the data were successfully deconvoluted as correlations between factors from the data and reference spectra of the components, were above 0.8 in all cases. Good reproducibility over three runs for the evolution profiles was obtained. From the evolution profiles it was observed that water diffused better through the Carbosil® membrane than ethanol, confirming the hydrophilic properties of the Carbosil® membrane used. IBU diffused slower compared with MP and CF. The evolution profile of CF was very similar to that of water, probably because of the high solubility of CF in water, indicating that both compounds are diffusing concurrently. The second part of the work involved a study of the evolution profiles of the components of a commercial topical gel containing 5% (w/w) of ibuprofen as it permeated through human skin. Although the system was much more complex, data were still successfully deconvoluted and the different components of the formulation identified except for benzyl alcohol which might be attributed to the low concentrations of benzyl alcohol used in topical formulations. (C) 2009 Elsevier B.V. All rights reserved.

Multivariate Statistical Analysis Applied to an IL6 Signal Transduction Model in Hepatocytes

This paper introduces the application of linear multivariate statistical techniques, including partial least squares (PLS), canonical correlation analysis (CCA) and reduced rank regression (RRR), into the area of Systems Biology. This new approach aims to extract the important proteins embedded in complex signal transduction pathway models.The analysis is performed on a model of intracellular signalling along the janus-associated kinases/signal transducers and transcription factors (JAK/STAT) and mitogen activated protein kinases (MAPK) signal transduction pathways in interleukin-6 (IL6) stimulated hepatocytes, which produce signal transducer and activator of transcription factor 3 (STAT3).A region of redundancy within the MAPK pathway that does not affect the STAT3 transcription was identified using CCA. This is the core finding of this analysis and cannot be obtained by inspecting the model by eye. In addition, RRR was found to isolate terms that do not significantly contribute to changes in protein concentrations, while the application of PLS does not provide such a detailed picture by virtue of its construction.This analysis has a similar objective to conventional model reduction techniques with the advantage of maintaining the meaning of the states prior to and after the reduction process. A significant model reduction is performed, with a marginal loss in accuracy, offering a more concise model while maintaining the main influencing factors on the STAT3 transcription.The findings offer a deeper understanding of the reaction terms involved, confirm the relevance of several proteins to the production of Acute Phase Proteins and complement existing findings regarding cross-talk between the two signalling pathways.

Developing a conceptual model of lead performance measurement and benchmarking: A multiple case analysis

Purpose: Environmental turbulence including rapid changes in technology and markets has resulted in the need for new approaches to performance measurement and benchmarking. There is a need for studies that attempt to measure and benchmark upstream, leading or developmental aspects of organizations. Therefore, the aim of this paper is twofold. The first is to conduct an in-depth case analysis of lead performance measurement and benchmarking leading to the further development of a conceptual model derived from the extant literature and initial survey data. The second is to outline future research agendas that could further develop the framework and the subject area.

Design/methodology/approach: A multiple case analysis involving repeated in-depth interviews with managers in organisational areas of upstream influence in the case organisations.

Findings: It was found that the effect of external drivers for lead performance measurement and benchmarking was mediated by organisational context factors such as level of progression in business improvement methods. Moreover, the legitimation of the business improvement methods used for this purpose, although typical, had been extended beyond their original purpose with the development of bespoke sets of lead measures.

Practical implications: Examples of methods and lead measures are given that can be used by organizations in developing a programme of lead performance measurement and benchmarking.

Originality/value: There is a paucity of in-depth studies relating to the theory and practice of lead performance measurement and benchmarking in organisations.

Multivariate Moments Expansion Density: Application of the Dynamic Equicorrelation Model

In this study, we propose a new semi-nonparametric (SNP) density model for describing the density of portfolio returns. This distribution, which we refer to as the multivariate moments expansion (MME), admits any non-Gaussian (multivariate) distribution as its basis because it is specified directly in terms of the basis density’s moments. To obtain the expansion of the Gaussian density, the MME is a reformulation of the multivariate Gram-Charlier (MGC), but the MME is much simpler and tractable than the MGC when positive transformations are used to produce well-defined densities. As an empirical application, we extend the dynamic conditional equicorrelation (DECO) model to an SNP framework using the MME. The resulting model is parameterized in a feasible manner to admit two-stage consistent estimation and it represents the DECO as well as the salient non-Gaussian features of portfolio return distributions. The in- and out-of-sample performance of a MME-DECO model of a portfolio of 10 assets demonstrate that it can be a useful tool for risk management purposes.

Actuarial applications of multivariate phase-type distributions : model calibration and credibility

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

Model Diagnostics in the presence of measurement error

The problem of using information available from one variable X to make inferenceabout another Y is classical in many physical and social sciences. In statistics this isoften done via regression analysis where mean response is used to model the data. Onestipulates the model Y = µ(X) +ɛ. Here µ(X) is the mean response at the predictor variable value X = x, and ɛ = Y - µ(X) is the error. In classical regression analysis, both (X; Y ) are observable and one then proceeds to make inference about the mean response function µ(X). In practice there are numerous examples where X is not available, but a variable Z is observed which provides an estimate of X. As an example, consider the herbicidestudy of Rudemo, et al. [3] in which a nominal measured amount Z of herbicide was applied to a plant but the actual amount absorbed by the plant X is unobservable. As another example, from Wang [5], an epidemiologist studies the severity of a lung disease, Y , among the residents in a city in relation to the amount of certain air pollutants. The amount of the air pollutants Z can be measured at certain observation stations in the city, but the actual exposure of the residents to the pollutants, X, is unobservable and may vary randomly from the Z-values. In both cases X = Z+error: This is the so called Berkson measurement error model.In more classical measurement error model one observes an unbiased estimator W of X and stipulates the relation W = X + error: An example of this model occurs when assessing effect of nutrition X on a disease. Measuring nutrition intake precisely within 24 hours is almost impossible. There are many similar examples in agricultural or medical studies, see e.g., Carroll, Ruppert and Stefanski [1] and Fuller [2], , among others. In this talk we shall address the question of fitting a parametric model to the re-gression function µ(X) in the Berkson measurement error model: Y = µ(X) + ɛ; X = Z + η; where η and ɛ are random errors with E(ɛ) = 0, X and η are d-dimensional, and Z is the observable d-dimensional r.v.

Multilevel multitrait-multimethod model: application to the measurement of egocentered social networks

Our goal in this paper is to assess reliability and validity of egocentered network data using multilevel analysis (Muthen, 1989, Hox, 1993) under the multitrait-multimethod approach. The confirmatory factor analysis model for multitrait-multimethod data (Werts & Linn, 1970; Andrews, 1984) is used for our analyses. In this study we reanalyse a part of data of another study (Kogovšek et al., 2002) done on a representative sample of the inhabitants of Ljubljana. The traits used in our article are the name interpreters. We consider egocentered network data as hierarchical; therefore a multilevel analysis is required. We use Muthen's partial maximum likelihood approach, called pseudobalanced solution (Muthen, 1989, 1990, 1994) which produces estimations close to maximum likelihood for large ego sample sizes (Hox & Mass, 2001). Several analyses will be done in order to compare this multilevel analysis to classic methods of analysis such as the ones made in Kogovšek et al. (2002), who analysed the data only at group (ego) level considering averages of all alters within the ego. We show that some of the results obtained by classic methods are biased and that multilevel analysis provides more detailed information that much enriches the interpretation of reliability and validity of hierarchical data. Within and between-ego reliabilities and validities and other related quality measures are defined, computed and interpreted

Measurement Quality in Indicators of Compositions: a Compositional Multitrait-Multimethod Approach

Compositional data, also called multiplicative ipsative data, are common in survey research instruments in areas such as time use, budget expenditure and social networks. Compositional data are usually expressed as proportions of a total, whose sum can only be 1. Owing to their constrained nature, statistical analysis in general, and estimation of measurement quality with a confirmatory factor analysis model for multitrait-multimethod (MTMM) designs in particular are challenging tasks. Compositional data are highly non-normal, as they range within the 0-1 interval. One component can only increase if some other(s) decrease, which results in spurious negative correlations among components which cannot be accounted for by the MTMM model parameters. In this article we show how researchers can use the correlated uniqueness model for MTMM designs in order to evaluate measurement quality of compositional indicators. We suggest using the additive log ratio transformation of the data, discuss several approaches to deal with zero components and explain how the interpretation of MTMM designs di ers from the application to standard unconstrained data. We show an illustration of the method on data of social network composition expressed in percentages of partner, family, friends and other members in which we conclude that the faceto-face collection mode is generally superior to the telephone mode, although primacy e ects are higher in the face-to-face mode. Compositions of strong ties (such as partner) are measured with higher quality than those of weaker ties (such as other network members)

UV index measurement and model agreement: uncertainties and limitations

En les últimes dècades, l'increment dels nivells de radiació solar ultraviolada (UVR) que arriba a la Terra (principalment degut a la disminució d'ozó estratosfèric) juntament amb l'augment detectat en malalties relacionades amb l'exposició a la UVR, ha portat a un gran volum d'investigacions sobre la radiació solar en aquesta banda i els seus efectes en els humans. L'índex ultraviolat (UVI), que ha estat adoptat internacionalment, va ser definit amb el propòsit d'informar al públic general sobre els riscos d'exposar el cos nu a la UVR i per tal d'enviar missatges preventius. L'UVI es va definir inicialment com el valor màxim diari. No obstant, el seu ús actual s'ha ampliat i té sentit referir-se a un valor instantani o a una evolució diària del valor d'UVI mesurat, modelitzat o predit. El valor concret d'UVI està afectat per la geometria Sol-Terra, els núvols, l'ozó, els aerosols, l'altitud i l'albedo superficial. Les mesures d'UVI d'alta qualitat són essencials com a referència i per estudiar tendències a llarg termini; es necessiten també tècniques acurades de modelització per tal d'entendre els factors que afecten la UVR, per predir l'UVI i com a control de qualitat de les mesures. És d'esperar que les mesures més acurades d'UVI s'obtinguin amb espectroradiòmetres. No obstant, com que els costs d'aquests dispositius són elevats, és més habitual trobar dades d'UVI de radiòmetres eritemàtics (de fet, la majoria de les xarxes d'UVI estan equipades amb aquest tipus de sensors). Els millors resultats en modelització s'obtenen amb models de transferència radiativa de dispersió múltiple quan es coneix bé la informació d'entrada. No obstant, habitualment no es coneix informació d'entrada, com per exemple les propietats òptiques dels aerosols, la qual cosa pot portar a importants incerteses en la modelització. Sovint, s'utilitzen models més simples per aplicacions com ara la predicció d'UVI o l'elaboració de mapes d'UVI, ja que aquests són més ràpids i requereixen menys paràmetres d'entrada. Tenint en compte aquest marc de treball, l'objectiu general d'aquest estudi és analitzar l'acord al qual es pot arribar entre la mesura i la modelització d'UVI per condicions de cel sense núvols. D'aquesta manera, en aquest estudi es presenten comparacions model-mesura per diferents tècniques de modelització, diferents opcions d'entrada i per mesures d'UVI tant de radiòmetres eritemàtics com d'espectroradiòmeters. Com a conclusió general, es pot afirmar que la comparació model-mesura és molt útil per detectar limitacions i estimar incerteses tant en les modelitzacions com en les mesures. Pel que fa a la modelització, les principals limitacions que s'han trobat és la falta de coneixement de la informació d'aerosols considerada com a entrada dels models. També, s'han trobat importants diferències entre l'ozó mesurat des de satèl·lit i des de la superfície terrestre, la qual cosa pot portar a diferències importants en l'UVI modelitzat. PTUV, una nova i simple parametrització pel càlcul ràpid d'UVI per condicions de cel serens, ha estat desenvolupada en base a càlculs de transferència radiativa. La parametrització mostra una bona execució tant respecte el model base com en comparació amb diverses mesures d'UVI. PTUV ha demostrat la seva utilitat per aplicacions particulars com ara l'estudi de l'evolució anual de l'UVI per un cert lloc (Girona) i la composició de mapes d'alta resolució de valors d'UVI típics per un territori concret (Catalunya). En relació a les mesures, es constata que és molt important saber la resposta espectral dels radiòmetres eritemàtics per tal d'evitar grans incerteses a la mesura d'UVI. Aquest instruments, si estan ben caracteritzats, mostren una bona comparació amb els espectroradiòmetres d'alta qualitat en la mesura d'UVI. Les qüestions més importants respecte les mesures són la calibració i estabilitat a llarg termini. També, s'ha observat un efecte de temperatura en el PTFE, un material utilitzat en els difusors en alguns instruments, cosa que potencialment podria tenir implicacions importants en el camp experimental. Finalment, i pel que fa a les comparacions model-mesura, el millor acord s'ha trobat quan es consideren mesures d'UVI d'espectroradiòmetres d'alta qualitat i s'usen models de transferència radiativa que consideren les millors dades disponibles pel que fa als paràmetres òptics d'ozó i aerosols i els seus canvis en el temps. D'aquesta manera, l'acord pot ser tan alt dins un 0.1º% en UVI, i típicament entre menys d'un 3%. Aquest acord es veu altament deteriorat si s'ignora la informació d'aerosols i depèn de manera important del valor d'albedo de dispersió simple dels aerosols. Altres dades d'entrada del model, com ara l'albedo superficial i els perfils d'ozó i temperatura introdueixen una incertesa menor en els resultats de modelització.