Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data.

Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders.

Revisiting the S-index for soil physical quality and its use in Brazil

The S-index was introduced in 2004 in a publication by A.R. Dexter. S was proposed as an indicator of soil physical quality. A critical value delimiting soils with rich and poor physical quality was proposed. At present, Brazil is world leader in citations of Dexter's publication. In this publication the S-theory is mathematically revisited and extended. It is shown that S is mathematically correlated to bulk density and total porosity. As an absolute indicator, the value of S alone has proven to be incapable of predicting soil physical quality. The critical value does not always hold under boundary conditions described in the literature. This is to be expected because S is a static parameter, therefore implicitly unable to describe dynamic processes. As a relative indicator of soil physical quality, the S-index has no additional value over bulk density or total porosity. Therefore, in the opinion of the author, the fact that bulk density or total porosity are much more easily determined than the water retention curve for obtaining S disqualifies S as an advantageous indicator of relative soil physical quality. Among the several equations available for the fitting of water retention curves, the Groenevelt-Grant equation is preferable for use with S since one of its parameters and S are linearly correlated. Since efforts in soil physics research have the purpose of describing dynamic processes, it is the author's opinion that these efforts should shift towards mechanistic soil physics as opposed to the search for empirical correlations like S which, at present, represents far more than its reasonable share of soil physics in Brazil.

Effect of elective antibiotic therapy on resting energy expenditure and inflammation in cystic fibrosis.

Cystic fibrosis (CF) patients often present with malnutrition which may partly be due to increased resting energy expenditure (REE) secondary to inflammation. Both REE and tumour necrosis factor-alpha (TNF-alpha), as other markers of inflammation, are elevated during respiratory exacerbations and decrease after antibiotic treatment. However, the effect of antibiotic therapy on REE and inflammation in patients without respiratory exacerbation is not known. The aim of our study was to determine the effect of such an elective antibiotic therapy on REE, TNF-alpha, and other serum markers of inflammation. Twelve CF patients 5F/7M, age 15.9 +/- 6.1 years, weight for height ratio 89 +/- 8% without clinically obvious exacerbation and treated by intravenous antibiotics were studied. Both before (D0) and after (D14) treatment, pulmonary function tests were performed. REE was measured by indirect calorimetry and blood taken to measure inflammation parameters. Body weight increased by 1.1 kg from D0 to D14 (P < 0.001), composed of 0.3 kg fat mass and 0.8 kg fat-free mass (FFM). The forced expiratory volume at 1 s increased from 43 +/- 15% of predicted at D0 to 51 +/- 15% of predicted at D14 (P < 0.01). Mean REE was 41.1 +/- 7.6 kcal/kg FFM per day at D0 and did not change significantly at D14 (40.6 +/- 8.5 kcal/kg FFM per day). Serum markers of inflammation decreased from D0 to D14: C-reactive protein 17 +/- 17 mg/l to 4 +/- 7 mg/l (P < 0.05), elastase 62 +/- 29 microg/l to 45 +/- 18 microg/l (P < 0.02), orosomucoid acid 1.25 +/- 0.11 g/l to 0.80 +/- 0.15 g/l (P < 0.001), and TNF-alpha 37 +/- 14 pg/ml to 29 +/- 6 pg/ml (P = 0.05). Individual values showed a correlation between changes in REE and in TNF-alpha (P < 0.02). The contribution of inflammation to energy expenditure is possible but appears to be minimal in cystic fibrosis patients treated by antibiotics on a regular basis in the absence of clinically obvious exacerbation.

Numerical algorithm for spectroscopic ellipsometry of thick transparent films

We present a numerical method for spectroscopic ellipsometry of thick transparent films. When an analytical expression for the dispersion of the refractive index (which contains several unknown coefficients) is assumed, the procedure is based on fitting the coefficients at a fixed thickness. Then the thickness is varied within a range (according to its approximate value). The final result given by our method is as follows: The sample thickness is considered to be the one that gives the best fitting. The refractive index is defined by the coefficients obtained for this thickness.

Procedure to characterize microroughness of optical thin films: application to ion-beam-sputtered vacuum-ultraviolet coatings

A method for characterizing the microroughness of samples in optical coating technology is developed. Measurements over different spatial-frequency ranges are composed into a single power spectral density (PSD) covering a large bandwidth. This is followed by the extraction of characteristic parameters through fitting of the PSD to a suitable combination of theoretical models. The method allows us to combine microroughness measurements performed with different techniques, and the fitting procedure can be adapted to any behavior of a combined PSD. The method has been applied to a set of ion-beam-sputtered fluoride vacuum-UV coatings with increasing number of alternative low- and high-index layers. Conclusions about roughness development and microstructural growth are drawn.

Regression analysis of spatial data.

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.

An AdS/QCD model from tachyon condensation: II

A simple holographic model is presented and analyzed that describes chiral symmetry breaking and the physics of the meson sector in QCD. This is a bottom-up model that incorporates string theory ingredients like tachyon condensation which is expected to be the main manifestation of chiral symmetry breaking in the holographic context. As a model for glue the Kuperstein-Sonnenschein background is used. The structure of the flavor vacuum is analyzed in the quenched approximation. Chiral symmetry breaking is shown at zero temperature. Above the deconfinement transition chiral symmetry is restored. A complete holographic renormalization is performed and the chiral condensate is calculated for different quark masses both at zero and non-zero temperatures. The 0++, 0¿+, 1++, 1¿¿ meson trajectories are analyzed and their masses and decay constants are computed. The asymptotic trajectories are linear. The model has one phenomenological parameter beyond those of QCD that affects the 1++, 0¿+ sectors. Fitting this parameter we obtain very good agreement with data. The model improves in several ways the popular hard-wall and soft wall bottom-up models.

Reproducibility of twitch mouth pressure, sniff nasal inspiratory pressure, and maximal inspiratory pressure.

Twitch mouth pressure (Pmo,tw) during magnetic phrenic nerve stimulation and sniff nasal inspiratory pressure (SNIP) were recently proposed as alternative noninvasive methods for assessing inspiratory muscle strength. This study aimed to compare their reproducibility with maximal inspiratory pressure (MIP) in normal subjects. Ten healthy subjects were studied at functional residual capacity in semirecumbent position. Cervical magnetic phrenic nerve stimulation was performed during gentle expiration against an occlusion incorporating a small leak. Constancy of stimulation was controlled by recording diaphragmatic electromyogram. Within and between-session reproducibility of pressure were studied for Pmo,tw, SNIP, and MIP. The subjects were studied during a session of 10 manoeuvres repeated after 1 day and 1 month. The mean values were 16 cmH2O for Pmo,tw, 118 cmH2O for SNIP, and 115 cmH2O for MIP. For the three tests, the within subject variation was small in relation to between-subject variation, with the intraclass correlation coefficient ranging 0.79-0.90 for Pmo,tw, 0.85-0.92 for SNIP, and 0.88-0.92 for MIP. At 1 day interval, the coefficient of repeatability (2 SD of differences) was 3.6 cmH2O for Pmo,tw, 32 cmH2O for SNIP and 28 cmH2O for MIP. At 1 month interval, the coefficient of repeatability was 5.8 cmH2O for Pmo,tw, 23 cmH2O for SNIP and 21 cmH2O for MIP. We conclude that the within session reproducibility of the new tests twitch mouth pressure and sniff nasal inspiratory pressure is sufficient to be clinically useful. For sniff nasal inspiratory pressure, the between session reproducibility established after 1 day was maintained after 1 month. For twitch mouth pressure, the between session reproducibility declined slightly after 1 month. These characteristics should be considered when using these methods to follow an individual patient over time.

Quantitative Assessment of Soil Physical Quality in Northern China Based on S-theory

ABSTRACT Quantitative assessment of soil physical quality is of great importance for eco-environmental pollution and soil quality studies. In this paper, based on the S-theory, data from 16 collection sites in the Haihe River Basin in northern China were used, and the effects of soil particle size distribution and bulk density on three important indices of theS-theory were investigated on a regional scale. The relationships between unsaturated hydraulic conductivityKi at the inflection point and S values (S/hi) were also studied using two different types of fitting equations. The results showed that the polynomial equation was better than the linear equation for describing the relationships between -log Ki and -logS, and -log Kiand -log (S/hi)2; and clay content was the most important factor affecting the soil physical quality index (S). The variation in the S index according to soil clay content was able to be fitted using a double-linear-line approach, with decrease in the S index being much faster for clay content less than 20 %. In contrast, the bulk density index was found to be less important than clay content. The average S index was 0.077, indicating that soil physical quality in the Haihe River Basin was good.

Surface Complexation Modeling in Variable Charge Soils: Charge Characterization by Potentiometric Titration

ABSTRACT Intrinsic equilibrium constants of 17 representative Brazilian Oxisols were estimated from potentiometric titration measuring the adsorption of H+ and OH− on amphoteric surfaces in suspensions of varying ionic strength. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. The former was fitted by calculating total site concentration from curve fitting estimates and pH-extrapolation of the intrinsic equilibrium constants to the PZNPC (hand calculation), considering one and two reactive sites, and by the FITEQL software. The latter was fitted only by FITEQL, with one reactive site. Soil chemical and physical properties were correlated to the intrinsic equilibrium constants. Both surface complexation models satisfactorily fit our experimental data, but for results at low ionic strength, optimization did not converge in FITEQL. Data were incorporated in Visual MINTEQ and they provide a modeling system that can predict protonation-dissociation reactions in the soil surface under changing environmental conditions.

Potential of Spectroradiometry to Classify Soil Clay Content

ABSTRACT Diffuse reflectance spectroscopy (DRS) is a fast and cheap alternative for soil clay, but needs further investigation to assess the scope of application. The purpose of the study was to develop a linear regression model to predict clay content from DRS data, to classify the soils into three textural classes, similar to those defined by a regulation of the Brazilian Ministry of Agriculture, Livestock and Food Supply. The DRS data of 412 soil samples, from the 0.0-0.5 m layer, from different locations in the state of Rio Grande do Sul, Brazil, were measured at wavelengths of 350 to 2,500 nm in the laboratory. The fitting of the linear regression model developed to predict soil clay content from the DRS data was based on a R2 value of 0.74 and 0.75, with a RMSE of 7.82 and 8.51 % for the calibration and validation sets, respectively. Soil texture classification had an overall accuracy of 79.0 % (calibration) and 80.9 % (validation). The heterogeneity of soil samples affected the performance of the prediction models. Future studies should consider a previous classification of soil samples in different groups by soil type, parent material and/or sampling region.

Sniff nasal inspiratory pressure in patients with chronic obstructive pulmonary disease.

In subjects with normal lung mechanics, inspiratory muscle strength can be reliably and easily assessed by the sniff nasal inspiratory pressure (SNIP), which is the pressure measured in an occluded nostril during a maximal sniff performed through the contralateral nostril. The aim of this study was to assess the validity of the SNIP in patients with chronic obstructive pulmonary disease (COPD), where pressure transmission from alveoli to upper airways is likely to be dampened. Twenty eight patients with COPD were studied (mean forced expiratory volume in one second (FEV1) = 36% of predicted). The SNIP and the sniff oesophageal pressure (sniff Poes) were measured simultaneously during maximal sniffs, and were compared to the maximal inspiratory pressure obtained against an occlusion (MIP). All measurements were performed from functional residual capacity in the sitting position. The ratio SNIP/sniff Poes was 0.80, and did not correlate with the degree of airflow limitation. The ratio MIP/sniff Poes was 0.87, and the ratio SNIP/MIP was 0.97. Inspiratory muscle weakness, as defined by a low sniff Poes, was present in 17 of the 28 patients. A false diagnosis of weakness was made in eight patients when MIP was considered alone, in four when SNIP was considered alone, and in only three patients when MIP and SNIP were combined. We conclude that both the sniff nasal inspiratory pressure and the maximal inspiratory pressure moderately underestimate sniff oesophageal pressure in chronic obstructive pulmonary disease. Although suboptimal in this condition, the sniff nasal inspiratory pressure appears useful to complement the maximal inspiratory pressure for assessing inspiratory muscle strength in patients with chronic obstructive pulmonary disease.

A comparison of in vivo 13C MR brain glycogen quantification at 9.4 and 14.1 T.

The high molecular weight and low concentration of brain glycogen render its noninvasive quantification challenging. Therefore, the precision increase of the quantification by localized (13) C MR at 9.4 to 14.1 T was investigated. Signal-to-noise ratio increased by 66%, slightly offset by a T(1) increase of 332 ± 15 to 521 ± 34 ms. Isotopic enrichment after long-term (13) C administration was comparable (≈ 40%) as was the nominal linewidth of glycogen C1 (≈ 50 Hz). Among the factors that contributed to the 66% observed increase in signal-to-noise ratio, the T(1) relaxation time impacted the effective signal-to-noise ratio by only 10% at a repetition time = 1 s. The signal-to-noise ratio increase together with the larger spectral dispersion at 14.1 T resulted in a better defined baseline, which allowed for more accurate fitting. Quantified glycogen concentrations were 5.8 ± 0.9 mM at 9.4 T and 6.0 ± 0.4 mM at 14.1 T; the decreased standard deviation demonstrates the compounded effect of increased magnetization and improved baseline on the precision of glycogen quantification.

Diffusion in spatially and temporarily inhomogeneous media

In this paper we consider diffusion of a passive substance C in a temporarily and spatially inhomogeneous two-dimensional medium. As a realization for the latter we choose a phase-separating medium consisting of two substances A and B, whose dynamics is determined by the Cahn-Hilliard equation. Assuming different diffusion coefficients of C in A and B, we find that the variance of the distribution function of the said substance grows less than linearly in time. We derive a simple identity for the variance using a probabilistic ansatz and are then able to identify the interface between A and B as the main cause for this nonlinear dependence. We argue that, finally, for very large times the here temporarily dependent diffusion "constant" goes like t-1/3 to a constant asymptotic value D¿. The latter is calculated approximately by employing the effective-medium approximation and by fitting the simulation data to the said time dependence.