Multiband OFDM modulation and demodulation for ultra wideband communications

This chapter considers the Multiband Orthogonal Frequency Division Multiplexing (MB- OFDM) modulation and demodulation with the intention to optimize the Ultra-Wideband (UWB) system performance. OFDM is a type of multicarrier modulation and becomes the most important aspect for the MB-OFDM system performance. It is also a low cost digital signal component efficiently using Fast Fourier Transform (FFT) algorithm to implement the multicarrier orthogonality. Within the MB-OFDM approach, the OFDM modulation is employed in each 528 MHz wide band to transmit the data across the different bands while also using the frequency hopping technique across different bands. Each parallel bit stream can be mapped onto one of the OFDM subcarriers. Quadrature Phase Shift Keying (QPSK) and Dual Carrier Modulation (DCM) are currently used as the modulation schemes for MB-OFDM in the ECMA-368 defined UWB radio platform. A dual QPSK soft-demapper is suitable for ECMA-368 that exploits the inherent Time-Domain Spreading (TDS) and guard symbol subcarrier diversity to improve the receiver performance, yet merges decoding operations together to minimize hardware and power requirements. There are several methods to demap the DCM, which are soft bit demapping, Maximum Likelihood (ML) soft bit demapping, and Log Likelihood Ratio (LLR) demapping. The Channel State Information (CSI) aided scheme coupled with the band hopping information is used as a further technique to improve the DCM demapping performance. ECMA-368 offers up to 480 Mb/s instantaneous bit rate to the Medium Access Control (MAC) layer, but depending on radio channel conditions dropped packets unfortunately result in a lower throughput. An alternative high data rate modulation scheme termed Dual Circular 32-QAM that fits within the configuration of the current standard increasing system throughput thus maintaining the high rate throughput even with a moderate level of dropped packets.

Interaction between vitamin D receptor gene polymorphisms and 25-hydroxyvitamin D concentrations on metabolic and cardiovascular disease outcomes

AIM: 25-hydroxyvitamin D (25OHD) concentrations have been shown to be associated with major clinical outcomes, with a suggestion that individual risk may vary according to common genetic differences in the vitamin D receptor (VDR) gene. Hence, we tested for the interactions between two previously studied VDR polymorphisms and 25OHD on metabolic and cardiovascular disease-related outcomes in a large population-based study. METHODS: Interactions between two previously studied VDR polymorphisms (rs7968585 and rs2239179) and 25OHD concentrations on metabolic and cardiovascular disease-related outcomes such as obesity- (body mass index, waist circumference, waist-hip ratio (WHR)), cardiovascular- (systolic and diastolic blood pressure), lipid- (high- and low-density lipoprotein, triglycerides, total cholesterol), inflammatory- (C-reactive protein, fibrinogen, insulin growth factor-1, tissue plasminogen activator) and diabetes- (glycated haemoglobin) related markers were examined in the 1958 British Birth cohort (n up to 5160). Interactions between each SNP and 25OHD concentrations were assessed using linear regression and the likelihood ratio test. RESULTS: After Bonferroni correction, none of the interactions reached statistical significance except for the interaction between the VDR SNP rs2239179 and 25OHD concentrations on waist-hip ratio (WHR) (P=0.03). For every 1nmol/L higher 25OHD concentrations, the association with WHR was stronger among those with two major alleles (-4.0%, P=6.26e-24) compared to those with either one or no major alleles (-2.3%, P≤8.201e-07, for both) of the VDR SNP rs2239179. CONCLUSION: We found no evidence for VDR polymorphisms acting as major modifiers of the association between 25OHD concentrations and cardio-metabolic risk. Interaction between VDR SNP rs2239179 and 25OHD on WHR warrants further confirmation.

Interaction between allelic variations in vitamin D receptor and retinoid X receptor genes on metabolic traits

BACKGROUND: Low vitamin D status has been shown to be a risk factor for several metabolic traits such as obesity, diabetes and cardiovascular disease. The biological actions of 1, 25-dihydroxyvitamin D, are mediated through the vitamin D receptor (VDR), which heterodimerizes with retinoid X receptor, gamma (RXRG). Hence, we examined the potential interactions between the tagging polymorphisms in the VDR (22 tag SNPs) and RXRG (23 tag SNPs) genes on metabolic outcomes such as body mass index, waist circumference, waist-hip ratio (WHR), high- and low-density lipoprotein (LDL) cholesterols, serum triglycerides, systolic and diastolic blood pressures and glycated haemoglobin in the 1958 British Birth Cohort (1958BC, up to n = 5,231). We used Multifactor- dimensionality reduction (MDR) program as a non-parametric test to examine for potential interactions between the VDR and RXRG gene polymorphisms in the 1958BC. We used the data from Northern Finland Birth Cohort 1966 (NFBC66, up to n = 5,316) and Twins UK (up to n = 3,943) to replicate our initial findings from 1958BC. RESULTS: After Bonferroni correction, the joint-likelihood ratio test suggested interactions on serum triglycerides (4 SNP - SNP pairs), LDL cholesterol (2 SNP - SNP pairs) and WHR (1 SNP - SNP pair) in the 1958BC. MDR permutation model testing analysis showed one two-way and one three-way interaction to be statistically significant on serum triglycerides in the 1958BC. In meta-analysis of results from two replication cohorts (NFBC66 and Twins UK, total n = 8,183), none of the interactions remained after correction for multiple testing (Pinteraction >0.17). CONCLUSIONS: Our results did not provide strong evidence for interactions between allelic variations in VDR and RXRG genes on metabolic outcomes; however, further replication studies on large samples are needed to confirm our findings.

Development and validation of a parent report measure for detection of cognitive delay in infancy

Aim To develop a brief, parent-completed instrument (‘ERIC’) for detection of cognitive delay in 10-24 month-olds born preterm, or with low birth weight, or with perinatal complications, and to establish its diagnostic properties. Method Scores were collected from parents of 317 children meeting ≥1 inclusion criteria (birth weight <1500g; gestational age <34 completed weeks; 5-minute Apgar <7; presence of hypoxic-ischemic encephalopathy) and meeting no exclusion criteria. Children were assessed for cognitive delay using a criterion score on the Bayley Scales of Infant and Toddler Development Cognitive Scale III1 <80. Items were retained according to their individual associations with delay. Sensitivity, specificity, Positive and Negative Predictive Values were estimated and a truncated ERIC was developed for use <14 months. Results ERIC detected 17 out of 18 delayed children in the sample, with 94.4% sensitivity (95% CI [confidence interval] 83.9-100%), 76.9% specificity (72.1-81.7%), 19.8% positive predictive value (11.4-28.2%); 99.6% negative predictive value (98.7-100%); 4.09 likelihood ratio positive; and 0.07 likelihood ratio negative; the associated Area under the Curve was .909 (.829-.960). Interpretation ERIC has potential value as a quickly-administered diagnostic instrument for the absence of early cognitive delay in preterm or premature infants of 10-24 months, and as a screen for cognitive delay. Further research may be needed before ERIC can be recommended for wide-scale use.

Interactions between uncoupling protein 2 gene polymorphisms, obesity and alcohol intake on liver function: a large meta-analysed population-based study

BACKGROUND AND OBJECTIVE: Given the role of uncoupling protein 2 (UCP2) in the accumulation of fat in the hepatocytes and in the enhancement of protective mechanisms in acute ethanol intake, we hypothesised that UCP2 polymorphisms are likely to cause liver disease through their interactions with obesity and alcohol intake. To test this hypothesis, we investigated the interaction between tagging polymorphisms in the UCP2 gene (rs2306819, rs599277 and rs659366), alcohol intake and obesity traits such as BMI and waist circumference (WC) on alanine aminotransferase (ALT) and gamma glutamyl transferase (GGT) in a large meta-analysis of data sets from three populations (n=20 242). DESIGN AND METHODS: The study populations included the Northern Finland Birth Cohort 1966 (n=4996), Netherlands Study of Depression and Anxiety (n=1883) and LifeLines Cohort Study (n=13 363). Interactions between the polymorphisms and obesity and alcohol intake on dichotomised ALT and GGT levels were assessed using logistic regression and the likelihood ratio test. RESULTS: In the meta-analysis of the three cohorts, none of the three UCP2 polymorphisms were associated with GGT or ALT levels. There was no evidence for interaction between the polymorphisms and alcohol intake on GGT and ALT levels. In contrast, the association of WC and BMI with GGT levels varied by rs659366 genotype (Pinteraction=0.03 and 0.007, respectively; adjusted for age, gender, high alcohol intake, diabetes, hypertension and serum lipid concentrations). CONCLUSION: In conclusion, our findings in 20 242 individuals suggest that UCP2 gene polymorphisms may cause liver dysfunction through the interaction with body fat rather than alcohol intake.

A cautionary note on the use of Ornstein Uhlenbeck models in macroevolutionary studies

Phylogenetic comparative methods are increasingly used to give new insights into the dynamics of trait evolution in deep time. For continuous traits the core of these methods is a suite of models that attempt to capture evolutionary patterns by extending the Brownian constant variance model. However, the properties of these models are often poorly understood, which can lead to the misinterpretation of results. Here we focus on one of these models – the Ornstein Uhlenbeck (OU) model. We show that the OU model is frequently incorrectly favoured over simpler models when using Likelihood ratio tests, and that many studies fitting this model use datasets that are small and prone to this problem. We also show that very small amounts of error in datasets can have profound effects on the inferences derived from OU models. Our results suggest that simulating fitted models and comparing with empirical results is critical when fitting OU and other extensions of the Brownian model. We conclude by making recommendations for best practice in fitting OU models in phylogenetic comparative analyses, and for interpreting the parameters of the OU model.

Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.

Power series generalized nonlinear models

We introduce in this paper a new class of discrete generalized nonlinear models to extend the binomial, Poisson and negative binomial models to cope with count data. This class of models includes some important models such as log-nonlinear models, logit, probit and negative binomial nonlinear models, generalized Poisson and generalized negative binomial regression models, among other models, which enables the fitting of a wide range of models to count data. We derive an iterative process for fitting these models by maximum likelihood and discuss inference on the parameters. The usefulness of the new class of models is illustrated with an application to a real data set. (C) 2008 Elsevier B.V. All rights reserved.

Statistical analysis of proficiency testing results under elliptical distributions

The use of inter-laboratory test comparisons to determine the performance of individual laboratories for specific tests (or for calibration) [ISO/IEC Guide 43-1, 1997. Proficiency testing by interlaboratory comparisons - Part 1: Development and operation of proficiency testing schemes] is called Proficiency Testing (PT). In this paper we propose the use of the generalized likelihood ratio test to compare the performance of the group of laboratories for specific tests relative to the assigned value and illustrate the procedure considering an actual data from the PT program in the area of volume. The proposed test extends the test criteria in use allowing to test for the consistency of the group of laboratories. Moreover, the class of elliptical distributions are considered for the obtained measurements. (C) 2008 Elsevier B.V. All rights reserved.

Size and power properties of some tests in the Birnbaum-Saunders regression model

The Birnbaum-Saunders distribution has been used quite effectively to model times to failure for materials subject to fatigue and for modeling lifetime data. In this paper we obtain asymptotic expansions, up to order n(-1/2) and under a sequence of Pitman alternatives, for the non-null distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the Birnbaum-Saunders regression model. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters and for testing the shape parameter. Monte Carlo simulation is presented in order to compare the finite-sample performance of these tests. We also present two empirical applications. (C) 2010 Elsevier B.V. All rights reserved.

Small-Sample Corrections for Score Tests in Birnbaum-Saunders Regressions

In this article, we deal with the issue of performing accurate small-sample inference in the Birnbaum-Saunders regression model, which can be useful for modeling lifetime or reliability data. We derive a Bartlett-type correction for the score test and numerically compare the corrected test with the usual score test and some other competitors.

Missing data mechanisms and their implications on the analysis of categorical data

We review some issues related to the implications of different missing data mechanisms on statistical inference for contingency tables and consider simulation studies to compare the results obtained under such models to those where the units with missing data are disregarded. We confirm that although, in general, analyses under the correct missing at random and missing completely at random models are more efficient even for small sample sizes, there are exceptions where they may not improve the results obtained by ignoring the partially classified data. We show that under the missing not at random (MNAR) model, estimates on the boundary of the parameter space as well as lack of identifiability of the parameters of saturated models may be associated with undesirable asymptotic properties of maximum likelihood estimators and likelihood ratio tests; even in standard cases the bias of the estimators may be low only for very large samples. We also show that the probability of a boundary solution obtained under the correct MNAR model may be large even for large samples and that, consequently, we may not always conclude that a MNAR model is misspecified because the estimate is on the boundary of the parameter space.

Inference for a skew extension of the Grubbs model

In this paper, we discuss inferential aspects for the Grubbs model when the unknown quantity x (latent response) follows a skew-normal distribution, extending early results given in Arellano-Valle et al. (J Multivar Anal 96:265-281, 2005b). Maximum likelihood parameter estimates are computed via the EM-algorithm. Wald and likelihood ratio type statistics are used for hypothesis testing and we explain the apparent failure of the Wald statistics in detecting skewness via the profile likelihood function. The results and methods developed in this paper are illustrated with a numerical example.

Local power of some tests in exponential family nonlinear models

In this paper we obtain asymptotic expansions up to order n(-1/2) for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in exponential family nonlinear models (Cordeiro and Paula, 1989), under a sequence of Pitman alternatives. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters and for testing the dispersion parameter, thus generalising the results given in Cordeiro et al. (1994) and Ferrari et al. (1997). We also present Monte Carlo simulations in order to compare the finite-sample performance of these tests. (C) 2010 Elsevier B.V. All rights reserved.

Estudo comparativo da viabilidade miocárdica em áreas dissinérgicas ao ecocardiograma basal : cintilografia tomográfica com Tecnécio 99m-mibi sob baixa dose de Dobutamina versus Tálio em repouso-redistribuição

A cintilografia com radioisótopos em repouso tem despertado muito interesse nos últimos anos para pesquisa da viabilidade miocárdica na disfunção isquêmica avançada do VE, porque esta pode ser reversível e porque há melhora prognóstica neste contexto. O objetivo desse trabalho é buscar identificar a acurácia da cintilografia tomográfica Tc-99m-Sestamibi, sob a infusão de dobutamina em baixa dose. Foram protocolados trinta pacientes que sofreram um infarto do miocárdio com padrão “Q”, com dissinergia ao ecocardiograma, e submetidos a estudos perfusionais em dias diferentes, com Tc-99m-Sestamibi − dobutamina e Tl-201 em repouso-redistribuição 4 horas, usado como padrão ouro. Não ocorreram complicações com nenhum paciente submetido ao protocolo do estudo. Os resultados revelaram: sensibilidade = 85%, especificidade = 87%, valor preditivo positivo = 96%, valor preditivo negativo = 65 % e acurácia de = 85,2%. A razão de probabilidade positiva foi de 6,68 e a razão de probabilidade negativa de 0,17. Confrontando-se nossos dados com uma metanálise de resultados para o Tc-99m-Sestamibi em repouso, a sensibilidade no presente estudo foi 85% vs. 81% e a especificidade de 87% vs. 60%. Em relação aos dados da literatura para Tl-201: 85% vs. 90% e 87% vs. 54%, sensibilidade e especificidade, respectivamente. Em conclusão, o Tc-99m-Sestamibi sob a infusão de dobutamina parece ser um método promissor para detectar viabilidade superior a esta modalidade de cintilografia em repouso, com valores preditivos comparáveis à literatura disponível para esse mesmo método: 85,2% vs. 87%, 96% vs. 90% e 65% vs. 83%, para acurácia, valor preditivo positivo e valor preditivo negativo, respectivamente.