Applying linear time-varying constraints to econometric models: With an application to demand systems

When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Seroprevalence of Human Papillomavirus 6, 11, 16, and 18 in Young Primiparous Women in Sao Paulo, Brazil

Introduction: Data on epidemiology of HPV infection are needed for the development of human papillomavirus (HPV) vaccine recommendations, especially in countries where HPV vaccination is not yet included in public vaccination programs. The aim of this study was to determine the prevalence of serum antibodies to HPV types 6, 11, 16, and 18 and associated factors among young women after birth of the first child. Methods: This cross-sectional study was carried out in a large public maternity hospital in Sao Paulo, Brazil. Three hundred one women aged 15 to 24 years who gave birth to their first child were recruited between 43 and 60 days after delivery. Seroprevalence was performed using a type-specific enzyme-linked immunosorbent assay based on HPV Late protein 1 viruslike particles. The association of seroreactivity with these 4 HPV types with selected demographic and behavioral factors was assessed by Generalized Linear Model analysis. Results: Fifty-eight (19.3%) women (95% confidence interval, 15.0%-24.2%) had antibodies to any of the 4 viruslike particles tested. The overall seroprevalence rates of the HPV types were: HPV16, 9.0%; HPV18, 7.0%; and HPV 6+11, 7.7%, which are targeted by the HPV prophylactic vaccines. In the multivariate analysis, only age (inversely, P = 0.044 for trend) and previous sexually transmitted disease (P = 0.008) were 2 factors independently associated with HPV seropositivity. Conclusions: These data offer additional information on the epidemiology of HPV in a group of young Brazilian women after first delivery and contribute to establish a baseline of HPV seroprevalence against which post-HPV vaccine era seroprevalence can be compared.

Exploring the knowledge contained in neuroimages: Statistical discriminant analysis and automatic segmentation of the most significant changes

Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. All rights reserved.

Implications of prevalent and incident diabetes mellitus on left ventricular geometry and function in the ageing heart: The MONICA/KORA Augsburg cohort study

Background and Aim: It is unclear to what extent diabetes modulates the ageing-related adaptations of cardiac geometry and function. Methods and Results: We examined 1005 adults, aged 25-74 years, from a population-based survey at baseline in 1994/5 and at follow-up in 2004/5. We compared persistently non-diabetic individuals (ND; no diabetes at baseline and at follow-up, n = 833) with incident (ID; non-diabetic at baseline and diabetic at follow-up, n = 36) and with prevalent diabetics (PD; diabetes at baseline and follow-up examination, n = 21). Left ventricular (LV) geometry and function were evaluated by echocardiography. Statistical analyses were performed with multivariate linear regression models. Over ten years the PD group displayed a significantly stronger relative increase of LV mass (+9.34% vs. +23.7%) that was mediated by a more pronounced increase of LV end-diastolic diameter (+0% vs. +6.95%) compared to the ND group. In parallel, LA diameter increased (+4.50% vs. +12.7%), whereas ejection fraction decreased (+3.02% vs. -4.92%) more significantly in the PD group. Moreover, at the follow-up examination the PD and ID groups showed a significantly worse diastolic function, indicated by a higher E/EM ratio compared with the ND group (11.6 and 11.8 vs. 9.79, respectively). Conclusions: Long-standing diabetes was associated with an acceleration of age-related changes of left ventricular geometry accumulating in an eccentric remodelling of the left ventricle. Likewise, echocardiographic measures of systolic and diastolic ventricular function deteriorated more rapidly in individuals with diabetes. (C) 2009 Elsevier B.V. All rights reserved.

Vitamin D status in a sunny country: Where has the sun gone?

Background & aims: Hypovitaminosis D [serum 25 vitamin D < 30 ng/ml] is related to the development of metabolic bone disease and greater risk of chronic illnesses. However, it is frequently under-diagnosed, mainly in countries where UV radiation is abundant. We prospectively determined the prevalence and the predictors of serum 25 vitamin D (s25(OH)D) in a healthy Brazilian population after the winter and after the summer. Methods: 603 (118M and 485F) healthy Brazilian volunteers aged 18-90 years from a universitary hospital were selected after the winter of 2006. From the initial sample, 209 volunteers (31M and 178F) accepted to participate in a second health check after the subsequent summer. Results: After the winter, median s25(OH)D was 21.4 ng/mL and 77.4% of the population presented hypovitaminosis D. s25(OH)D was significantly related to age, BMI, PTH and race. In multivariate linear regression analysis, s25(OH)D was significantly and independently dependent on age, glycemia and skin color. Significant increase in s25(OH)D was verified after summer [10.6 (3.7-19.3 ng/ml); p < 0.001] and this improvement was dependent on age. We also observed a significant decrease in hyperparathyroidism prevalence (20.8% vs. 4.9%; P < 0.0001). Conclusion: In Sao Paulo, at the end of winter, we observed a high prevalence of hypovitaminosis D and secondary hyperparathyroidism in healthy adults. s25(OH)D was dependent on age and skin color. After summer, we observed a decrease in the prevalence of hypovitaminosis D. This unexpected finding emphasizes the need for a strong recommendation to monitor s25(OH)D, even in a sunny country such as Brazil. (C) 2010 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Methods for exploring the morpho-functional relations of the aortic depressor nerve in experimental diabetes

The present study investigated morpho-functional relations of the aortic depressor nerve (ADN) 5, 15 and 120 days after the onset of streptozotocin-induced diabetes in rats. Time control animals received vehicle. Under pentobarbital anesthesia, ADN activity was recorded simultaneously with arterial pressure. After the recordings, nerves were prepared for light microscopy study and morphometry. ADN function was accessed by means of pressure-nerve activity curve (fitted by sigmoidal regression) and cross-spectral analysis between mean arterial pressure (MAP) and ADN activity. The relation between morphological (myelinated fibers number and density, total myelin area, total fiber area and percentage of occupancy) and functional (gain, signal/noise relation, frequency) parameters were accessed by linear regression analysis and correlation coefficient calculations. Functional parameters obtained by means of the sigmoidal regression curve as well as by cross-spectral analysis were similar in diabetic and control rats. Morphometric parameters of the ADN were similar between groups 5 days after the onset of diabetes. Average myelin area and myelinated fiber area were significantly smaller on diabetic rats 15 and 120 days after the onset of diabetes, being the myelinated fiber and respective axons area and diameter also smaller on 120 days group. Nevertheless, G ratio (ratio between axon and fiber diameter) was nearly 0.6 and not different between groups or experimental times. No significant relationship between morphological and functional parameters was detected in all experimental groups. The present study suggests that ADN diabetic neuropathy was time-dependent, with damage to myelinated fibers to be the primary event, not evidenced by physiological methods. (C) 2010 Elsevier B.V. All rights reserved.

Obesity due to Melanocortin 4 Receptor (MC4R) Deficiency Is Associated with Increased Linear Growth and Final Height, Fasting Hyperinsulinemia, and Incompletely Suppressed Growth Hormone Secretion

Context: Melanocortin receptor 4 (MC4R) deficiency is characterized by increased linear growth greater than expected for the degree of obesity. Objective: The objective of the investigation was to study the somatotroph axis in obese MC4R-deficient patients and equally obese controls. Patients and Methods: We obtained anthropometric measurements and insulin concentrations in 153 MC4R-deficient subjects and 1392 controls matched for age and severity of obesity. We measured fasting IGF-I, IGF-II, IGF binding protein (IGFBP)-1, IGFBP-3, and acid-labile subunit levels in a subset of 33 MC4R-deficient patients and 36 control subjects. We examined pulsatile GH secretion in six adult MC4R-deficient subjects and six obese controls. Results: Height so score was significantly greater in MC4R-deficient children under 5 yr of age compared with controls (mean +/- SEM: 2.3 +/- 0.06 vs. 1.8 +/- 0.04, P < 0.001), an effect that persisted throughout childhood. Final height (cm) was greater in MC4R-deficient men (mean +/- SEM 173 +/- 2.5 vs. 168 +/- 2.1, P < 0.001) and women (mean 165 +/- 2.1 vs. 158 +/- 1.9, P < 0.001). Fasting IGF-I, IGF-II, acid-labile subunit, and IGFBP-3 concentrations were similar in the two groups. GH levels were markedly suppressed in obese controls, but pulsatile GH secretion was retained in MC4R deficiency. The mean maximal GH secretion rate per burst (P < 0.05) and mass per burst (P < 0.05) were increased in MC4R deficiency, consistent with increased pulsatile and total GH secretion. Fasting insulin levels were markedly elevated in MC4R-deficient children. Conclusions: In MC4R deficiency, increased linear growth in childhood leads to increased adult final height, greater than predicted by obesity alone. GH pulsatility is maintained in MC4R deficiency, a finding consistent with animal studies, suggesting a role for MC4R in controlling hypothalamic somatostatinergic tone. Fasting insulin levels are significantly higher in children carrying MC4R mutations. Both of these factors may contribute to the accelerated growth phenotype characteristic of MC4R deficiency. (J Clin Endocrinol Metab 96: E181-E188, 2011)

Focal and linear endocardial and epicardial catheter-based cryoablation of normal and infarcted ventricular tissue

Background: This study of a chronic porcine postinfarction model examined whether linear epicardial cryoablation was capable of creating large, homogenous lesions in regions of the myocardium including scarred ventricle. Endocardial and epicardial focal cryolesions were also compared to determine if there were significant differences in lesion characteristics. Methods: Eighty focal endocardial and 28 focal epicardial cryoapplications were delivered to eight normal caprine and four normal porcine ventricular myocardium, and 21 linear cryolesions were applied along the border of infarcted epicardial tissue in a chronic porcine infarct model in six swines. Results: Focal endocardial cryolesions in normal animals measured 9.7 +/- 0.4 mm (length) by 7.3 +/- 1.4 mm (width) by 4.8 +/- 0.2 mm (depth), while epicardial lesions measured 10.2 +/- 1.4 mm (length) by 7.7 +/- 2 mm (width) by 4.6 +/- 0.9 mm (depth); P > 0.05. Linear epicardial cryolesions in the chronic porcine infarct model measured 36.5 +/- 7.8 mm (length) by 8.2 +/- 1.3 mm (width) by 6.0 +/- 1.2 mm (depth). The mean depth of linear cryolesions applied to the border of the infarct scar was 7 +/- 0.7 mm, as measured by magnetic resonance imaging. Conclusions:Cryoablation can create deep lesions when delivered to the ventricular epicardium. Endocardial and epicardial cryolesions created by a focal cryoablation catheter are similar in size and depth. The ability to rapidly create deep linear cryolesions may prove to be beneficial in substrate-based catheter ablation of ventricular arrhythmias.

Application of Petrov-Galerkin methods to transient boundary value problems in chemical engineering: adsorption with steep gradients in bidisperse solids

Petrov-Galerkin methods are known to be versatile techniques for the solution of a wide variety of convection-dispersion transport problems, including those involving steep gradients. but have hitherto received little attention by chemical engineers. We illustrate the technique by means of the well-known problem of simultaneous diffusion and adsorption in a spherical sorbent pellet comprised of spherical, non-overlapping microparticles of uniform size and investigate the uptake dynamics. Solutions to adsorption problems exhibit steep gradients when macropore diffusion controls or micropore diffusion controls, and the application of classical numerical methods to such problems can present difficulties. In this paper, a semi-discrete Petrov-Galerkin finite element method for numerically solving adsorption problems with steep gradients in bidisperse solids is presented. The numerical solution was found to match the analytical solution when the adsorption isotherm is linear and the diffusivities are constant. Computed results for the Langmuir isotherm and non-constant diffusivity in microparticle are numerically evaluated for comparison with results of a fitted-mesh collocation method, which was proposed by Liu and Bhatia (Comput. Chem. Engng. 23 (1999) 933-943). The new method is simple, highly efficient, and well-suited to a variety of adsorption and desorption problems involving steep gradients. (C) 2001 Elsevier Science Ltd. All rights reserved.

Self-reported calcium intake and bone mineral content in children and adolescents

Objective: We examined the relationship between self-reported calcium (Cal intake and bone mineral content (BMC) in children and adolescents. We hypothesized that an expression of Ca adjusted for energy intake (El), i.e., Ca density, would be a better predictor of BMC than unadjusted Ca because of underreporting of EI. Methods: Data were obtained on dietary intakes (repeated 24-hour recalls) and BMC (by DEXA) in a cross-section of 227 children aged 8 to 17 years. Bivariate and multivariate analyses were used to examine die relationship between Ca, Ca density, and the dependent variables total body BMC and lumbar spine BMC. Covariates included were height, weight, bone area, maturity age, activity score and El. Results: Reported El compared to estimated basal metabolic rate suggested underreporting of El. Total body and lumbar spine BMC were significantly associated with El, but not Ca or Ca density, in bivariate analyses. After controlling for size and maturity, multiple linear regression analysis revealed unadjusted Ca to be a predictor of BMC in males in the total body (p = 0.08) and lumbar spine (p = 0.01). Unadjusted Ca was not a predictor of BMC at either site in females. Ca density was not a better predictor of BMC at either site in males or females. Conclusions: The relationship observed in male adolescents in this study between Ca intake and BMC is similar to that seen in clinical trials. Ca density did not enable us to see a relationship between Ca intake and BMC in females, which may reflect systematic reporting errors or that diet is not a limiting factor in this group of healthy adolescents.

Detection and description of non-linear interdependence in normal multichannel human EEG data

Objectives: This study examines human scalp electroencephalographic (EEG) data for evidence of non-linear interdependence between posterior channels. The spectral and phase properties of those epochs of EEG exhibiting non-linear interdependence are studied. Methods: Scalp EEG data was collected from 40 healthy subjects. A technique for the detection of non-linear interdependence was applied to 2.048 s segments of posterior bipolar electrode data. Amplitude-adjusted phase-randomized surrogate data was used to statistically determine which EEG epochs exhibited non-linear interdependence. Results: Statistically significant evidence of non-linear interactions were evident in 2.9% (eyes open) to 4.8% (eyes closed) of the epochs. In the eyes-open recordings, these epochs exhibited a peak in the spectral and cross-spectral density functions at about 10 Hz. Two types of EEG epochs are evident in the eyes-closed recordings; one type exhibits a peak in the spectral density and cross-spectrum at 8 Hz. The other type has increased spectral and cross-spectral power across faster frequencies. Epochs identified as exhibiting non-linear interdependence display a tendency towards phase interdependencies across and between a broad range of frequencies. Conclusions: Non-linear interdependence is detectable in a small number of multichannel EEG epochs, and makes a contribution to the alpha rhythm. Non-linear interdependence produces spatially distributed activity that exhibits phase synchronization between oscillations present at different frequencies. The possible physiological significance of these findings are discussed with reference to the dynamical properties of neural systems and the role of synchronous activity in the neocortex. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data

Binning and truncation of data are common in data analysis and machine learning. This paper addresses the problem of fitting mixture densities to multivariate binned and truncated data. The EM approach proposed by McLachlan and Jones (Biometrics, 44: 2, 571-578, 1988) for the univariate case is generalized to multivariate measurements. The multivariate solution requires the evaluation of multidimensional integrals over each bin at each iteration of the EM procedure. Naive implementation of the procedure can lead to computationally inefficient results. To reduce the computational cost a number of straightforward numerical techniques are proposed. Results on simulated data indicate that the proposed methods can achieve significant computational gains with no loss in the accuracy of the final parameter estimates. Furthermore, experimental results suggest that with a sufficient number of bins and data points it is possible to estimate the true underlying density almost as well as if the data were not binned. The paper concludes with a brief description of an application of this approach to diagnosis of iron deficiency anemia, in the context of binned and truncated bivariate measurements of volume and hemoglobin concentration from an individual's red blood cells.

Bridging the gap between different statistical approaches: An integrated framework for modelling

This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.

Product form approximations for highly linear loss networks with trunk reservation

Admission controls, such as trunk reservation, are often used in loss networks to optimise their performance. Since the numerical evaluation of performance measures is complex, much attention has been given to finding approximation methods. The Erlang Fixed-Point (EFP) approximation, which is based on an independent blocking assumption, has been used for networks both with and without controls. Several more elaborate approximation methods which account for dependencies in blocking behaviour have been developed for the uncontrolled setting. This paper is an exploratory investigation of extensions and synthesis of these methods to systems with controls, in particular, trunk reservation. In order to isolate the dependency factor, we restrict our attention to a highly linear network. We will compare the performance of the resulting approximations against the benchmark of the EFP approximation extended to the trunk reservation setting. By doing this, we seek to gain insight into the critical factors in constructing an effective approximation. (C) 2003 Elsevier Ltd. All rights reserved.