Weighted Euclidean biplots

We construct a weighted Euclidean distance that approximates any distance or dissimilarity measure between individuals that is based on a rectangular cases-by-variables data matrix. In contrast to regular multidimensional scaling methods for dissimilarity data, the method leads to biplots of individuals and variables while preserving all the good properties of dimension-reduction methods that are based on the singular-value decomposition. The main benefits are the decomposition of variance into components along principal axes, which provide the numerical diagnostics known as contributions, and the estimation of nonnegative weights for each variable. The idea is inspired by the distance functions used in correspondence analysis and in principal component analysis of standardized data, where the normalizations inherent in the distances can be considered as differential weighting of the variables. In weighted Euclidean biplots we allow these weights to be unknown parameters, which are estimated from the data to maximize the fit to the chosen distances or dissimilarities. These weights are estimated using a majorization algorithm. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing the matrix and displaying its rows and columns in biplots.

Biomass estimation of Triplectides egleri Sattler (Trichoptera, Leptoceridae) in a stream at Ducke Reserve, Central Amazonia

ABSTRACT Biomass is a fundamental measure for understanding the structure and functioning (e.g. fluxes of energy and nutrients in the food chain) of aquatic ecosystems. We aim to provide predictive models to estimate the biomass of Triplectides egleri Sattler, 1963, in a stream in Central Amazonia, based on body and case dimensions. We used body length, head-capsule width, interocular distance and case length and width to derive biomass estimations. Linear, exponential and power regression models were used to assess the relationship between biomass and body or case dimensions. All regression models used in the biomass estimation of T. egleri were significant. The best fit between biomass and body or case dimensions was obtained using the power model, followed by the exponential and linear models. Body length provided the best estimate of biomass. However, the dimensions of sclerotized structures (interocular distance and head-capsule width) also provided good biomass predictions, and may be useful in estimating biomass of preserved and/or damaged material. Case width was the dimension of the case that provided the best estimate of biomass. Despite the low relation, case width may be useful in studies that require low stress on individuals.

Effects of the playing surface on plantar pressures during the first serve in tennis.

PURPOSE: This study aimed at examining the influence of different playing surfaces on in-shoe loading patterns in each foot (back and front) separately during the first serve in tennis. METHODS: Ten competitive tennis players completed randomly five first (ie, flat) serves on two different playing surfaces: clay vs GreenSet. Maximum and mean force, peak and mean pressure, mean area, contact area and relative load were recorded by Pedar insoles divided into 9 areas for analysis. RESULTS: Mean pressure was significantly lower (123 ± 30 vs 98 ± 26 kPa; -18.5%; P < .05) on clay than on GreenSet when examining the entire back foot. GreenSet induced higher mean pressures under the medial forefoot, lateral forefoot and hallux of the back foot (+9.9%, +3.5% and +15.9%, respectively; both P < .01) in conjunction with a trend toward higher maximal forces in the back hallux (+15.1%, P = .08). Peak pressures recorded under the central and lateral forefoot (+21.8% and +25.1%; P < .05) of the front foot but also the mean area values measured on the back medial and lateral midfoot were higher (P < .05) on clay. No significant interaction between foot region and playing surface on relative load was found. CONCLUSIONS: It is suggested that in-shoe loading parameters characterizing the first serve in tennis are adjusted according to the ground type surface. A lesser asymmetry in peak (P < .01) and mean (P < .001) pressures between the two feet was found on clay, suggesting a greater need for stability on this surface.

Scaling of semivariograms and the kriging estimation of field-measured properties

Two methods were evaluated for scaling a set of semivariograms into a unified function for kriging estimation of field-measured properties. Scaling is performed using sample variances and sills of individual semivariograms as scale factors. Theoretical developments show that kriging weights are independent of the scaling factor which appears simply as a constant multiplying both sides of the kriging equations. The scaling techniques were applied to four sets of semivariograms representing spatial scales of 30 x 30 m to 600 x 900 km. Experimental semivariograms in each set successfully coalesced into a single curve by variances and sills of individual semivariograms. To evaluate the scaling techniques, kriged estimates derived from scaled semivariogram models were compared with those derived from unscaled models. Differences in kriged estimates of the order of 5% were found for the cases in which the scaling technique was not successful in coalescing the individual semivariograms, which also means that the spatial variability of these properties is different. The proposed scaling techniques enhance interpretation of semivariograms when a variety of measurements are made at the same location. They also reduce computational times for kriging estimations because kriging weights only need to be calculated for one variable. Weights remain unchanged for all other variables in the data set whose semivariograms are scaled.

Sampling strategies for tropical forest nutrient cycling studies: a case study in São Paulo, Brazil

The precise sampling of soil, biological or micro climatic attributes in tropical forests, which are characterized by a high diversity of species and complex spatial variability, is a difficult task. We found few basic studies to guide sampling procedures. The objective of this study was to define a sampling strategy and data analysis for some parameters frequently used in nutrient cycling studies, i. e., litter amount, total nutrient amounts in litter and its composition (Ca, Mg, Κ, Ν and P), and soil attributes at three depths (organic matter, Ρ content, cation exchange capacity and base saturation). A natural remnant forest in the West of São Paulo State (Brazil) was selected as study area and samples were collected in July, 1989. The total amount of litter and its total nutrient amounts had a high spatial independent variance. Conversely, the variance of litter composition was lower and the spatial dependency was peculiar to each nutrient. The sampling strategy for the estimation of litter amounts and the amount of nutrient in litter should be different than the sampling strategy for nutrient composition. For the estimation of litter amounts and the amount of nutrients in litter (related to quantity) a large number of randomly distributed determinations are needed. Otherwise, for the estimation of litter nutrient composition (related to quality) a smaller amount of spatially located samples should be analyzed. The determination of sampling for soil attributes differed according to the depth. Overall, surface samples (0-5 cm) showed high short distance spatial dependent variance, whereas, subsurface samples exhibited spatial dependency in longer distances. Short transects with sampling interval of 5-10 m are recommended for surface sampling. Subsurface samples must also be spatially located, but with transects or grids with longer distances between sampling points over the entire area. Composite soil samples would not provide a complete understanding of the relation between soil properties and surface dynamic processes or landscape aspects. Precise distribution of Ρ was difficult to estimate.

Comparison of the polynomial model against explicit measurements of noise components for different mammography systems.

Given the adverse impact of image noise on the perception of important clinical details in digital mammography, routine quality control measurements should include an evaluation of noise. The European Guidelines, for example, employ a second-order polynomial fit of pixel variance as a function of detector air kerma (DAK) to decompose noise into quantum, electronic and fixed pattern (FP) components and assess the DAK range where quantum noise dominates. This work examines the robustness of the polynomial method against an explicit noise decomposition method. The two methods were applied to variance and noise power spectrum (NPS) data from six digital mammography units. Twenty homogeneously exposed images were acquired with PMMA blocks for target DAKs ranging from 6.25 to 1600 µGy. Both methods were explored for the effects of data weighting and squared fit coefficients during the curve fitting, the influence of the additional filter material (2 mm Al versus 40 mm PMMA) and noise de-trending. Finally, spatial stationarity of noise was assessed.Data weighting improved noise model fitting over large DAK ranges, especially at low detector exposures. The polynomial and explicit decompositions generally agreed for quantum and electronic noise but FP noise fraction was consistently underestimated by the polynomial method. Noise decomposition as a function of position in the image showed limited noise stationarity, especially for FP noise; thus the position of the region of interest (ROI) used for noise decomposition may influence fractional noise composition. The ROI area and position used in the Guidelines offer an acceptable estimation of noise components. While there are limitations to the polynomial model, when used with care and with appropriate data weighting, the method offers a simple and robust means of examining the detector noise components as a function of detector exposure.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.

Fat oxidation in nonobese and obese adolescents: effect of body composition and pubertal development.

OBJECTIVES: To measure postabsorptive fat oxidation (F(ox)) and to assess its association with body composition (lean body mass [LBM] and body fat mass [BFM]) and pubertal development. DESIGN: We studied 235 control (male/female ratio = 116/119; age [mean +/- SD]: 13.1 +/- 1.7 years; weight: 45.3 +/- 10.5 kg; LBM: 34.3 +/- 7.1 kg; BFM: 11.0 +/- 4.5 kg) and 159 obese (male/female ratio = 93/66; age: 12.9 +/- 2.1 years; weight: 76.2 +/- 19.1 kg; LBM: 47.4 +/- 10.9 kg; BFM: 28.8 +/- 9.2 kg) adolescents. Postabsorptive F(ox) was calculated from oxygen consumption, carbon dioxide production, and urinary nitrogen as measured by indirect calorimetry and Kjeldahl's method, respectively. Body composition was determined by anthropometry. RESULTS: Postabsorptive F(ox) (absolute value and percentage of resting metabolic rate) was significantly (p < 0.001) higher in the obese adolescents (76.7 +/- 26.3 gm/24 hours, 42.3% +/- 18.7%) than in the control subjects (40.0 +/- 26.3 gm/24 hours, 28.7% +/- 17.0%), even if adjusted for LBM. F(ox) corrected for BFM was similar in control and in obese children, but was significantly lower in girls compared with boys (control male subjects: 62.1 +/- 29.1 gm/24 hours, control female subjects: 51.6 +/- 28.4 gm/24 hours, obese male subjects: 57.3 +/- 29 gm/24 hour, obese female subjects: 45.0 +/- 28.4 gm/24 hours). BFM and LBM showed a significant positive correlation with F(ox). By stepwise regression analysis the most important determinant of F(ox) was BFM in obese and LBM in control children. There was a significant rise in F(ox) during puberty; however, it was mainly explained by changes in body composition. CONCLUSIONS: Obese adolescents have higher F(ox) rates than their normal-weight counterparts. Both LBM and fat mass are important determinants of F(ox).

Chemical labelling of oyster shells used for time-calibrated high-resolution Mg/Ca ratios: A tool for estimation of past seasonal temperature variations

The geochemical compositions of biogenic carbonates are increasingly used for palaeoenvironmental reconstructions. The skeletal delta O-18 temperature relationship is dependent on water salinity, so many recent studies have focused on the Mg/Ca and Sr/Ca ratios because those ratios in water do not change significantly on short time scales. Thus, those elemental ratios are considered to be good palaeotemperature proxies in many biominerals, although their use remains ambiguous in bivalve shells. Here, we present the high-resolution Mg/Ca ratios of two modern species of juvenile and adult oyster shells, Crassostrea gigas and Ostrea edulis. These specimens were grown in controlled conditions for over one year in two different locations. In situ monthly Mn-marking of the shells has been used for day calibration. The daily Mg/Ca.ratios in the shell have been measured with an electron microprobe. The high frequency Mg/Ca variation of all specimens displays good synchronism with lunar cycles, suggesting that tides strongly influence the incorporation of Mg/Ca into the shells. Highly significant correlation coefficients (0.70<R<0.83, p<0.0001) between the Mg/Ca ratios and the seawater temperature are obtained only for juvenile C. gigas samples, while metabolic control of Mg/Ca incorporation and lower shell growth rates preclude the use of the Mg/Ca ratio in adult shells as a palaeothermometer. Data from three juvenile C. gigas shells from the two study sites are selected to establish a relationship: T = 3.77Mg/Ca + 1.88, where T is in degrees C and Mg/Ca in mmol/mol. (c) 2012 Elsevier B.V. All rights reserved.

Carbamazepine augmentation in depressive patients non-responding to citalopram: a pharmacokinetic and clinical pilot study

Citalopram is a chiral antidepressant drug. Its eutomer, S-citalopram (escitalopram), has recently been introduced as an antidepressant. In an open pilot study, four outpatients and two inpatients with a major depressive episode (ICD-10), and who were nonresponders to a 4-week pretreatment with 40-60 mg/day citalopram, were comedicated for another 4-week period with carbamazepine (200-400 mg/day). Some of the patients suffered also from comorbidities: Phobic anxiety disorder with panic attacks (n=2), generalised anxiety disorder, alcohol abuse, dependent personality disorder, hypertension (n=1). After a 4-week augmentation therapy with carbamazepine, a significant (P<0.03) decrease of the plasma concentrations of S-citalopram and R-citalopram, by 27 and 31%, respectively, was observed. Apparently, the probable induction of CYP3A4 by carbamazepine results in a nonstereoselective increase in N-demethylation of citalopram. Moreover, there was a significant (P<0.03) decrease of the ratio S/R-citalopram propionic acid derivative, the formation of it being partly regulated by MAO-A and MAO-B. Already, within 1 week after addition of carbamazepine, there was a slight but significant (P<0.03) decrease of the MADRS depression scores, from 27.0+/-7.7 (mean+/-S.D.) to 23.3+/-6.6, and the final score on day 56 was 18.8+/-10.9. The treatment was generally well tolerated. There was no evidence of occurrence of a serotonin syndrome. After augmentation with carbamazepine, treatment related adverse events were: Nausea in one case, diarrhea in one case, and rash in two cases. In conclusion, the results of this pilot study suggest that carbamazepine augmentation of a citalopram treatment in previous nonresponders to citalopram may be clinically useful, but that in addition carbamazepine can lead to a decrease of the plasma concentrations of the active enantiomer escitalopram.