Index of soil physical quality of hardsetting soils on the brazilian coast

Many soils have a hard-setting behavior, also known as cohesive or "coesos". In such soils, the penetration resistance increases markedly when dry and decreases considerably when moist, creating serious limitations for plant emergence and growth. To evaluate the level of structure degradation in hard-setting soils with different texture classes and to create an index for assessing soil hardness levels in hard-setting soils, six soil representative profiles were selected in the field in various regions of Brazil. The following indices were tested: S, which measures soil physical quality, and H , which analyzes the degree of hardness and the effective stress in the soil during drying. Both indices were calculated using previously described functions based on data from the water-retention curves for the soils. The hard-setting values identified in different soils of the Brazilian Coastal Tablelands have distinct compaction (hardness) levels and can be satisfactorily measured by the H index. The S index was adequate for evaluating the structural characteristics of the hard-setting soils, classifying them as suitable or poor for cultivation, but only when the moisture level of the soil was near the inflection point. The H index showed that increases in density in hard-setting soils result from increases in effective stress and not from the soil texture. Values for Bd > 1.48 kg dm-3 classify the soil as hard-setting, and the structural organization is considered "poor".

How to measure cortical folding from MR images: a step-by-step tutorial to compute local gyrification index.

Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will be identifiable at any age. As recently reviewed by Mangin and colleagues(2), several methods exist to quantify different characteristics of gyrification. For instance, sulcal morphometry can be used to measure shape descriptors such as the depth, length or indices of inter-hemispheric asymmetry(3). These geometrical properties have the advantage of being easy to interpret. However, sulcal morphometry tightly relies on the accurate identification of a given set of sulci and hence provides a fragmented description of gyrification. A more fine-grained quantification of gyrification can be achieved with curvature-based measurements, where smoothed absolute mean curvature is typically computed at thousands of points over the cortical surface(4). The curvature is however not straightforward to comprehend, as it remains unclear if there is any direct relationship between the curvedness and a biologically meaningful correlate such as cortical volume or surface. To address the diverse issues raised by the measurement of cortical folding, we previously developed an algorithm to quantify local gyrification with an exquisite spatial resolution and of simple interpretation. Our method is inspired of the Gyrification Index(5), a method originally used in comparative neuroanatomy to evaluate the cortical folding differences across species. In our implementation, which we name local Gyrification Index (lGI(1)), we measure the amount of cortex buried within the sulcal folds as compared with the amount of visible cortex in circular regions of interest. Given that the cortex grows primarily through radial expansion(6), our method was specifically designed to identify early defects of cortical development. In this article, we detail the computation of local Gyrification Index, which is now freely distributed as a part of the FreeSurfer Software (http://surfer.nmr.mgh.harvard.edu/, Martinos Center for Biomedical Imaging, Massachusetts General Hospital). FreeSurfer provides a set of automated reconstruction tools of the brain's cortical surface from structural MRI data. The cortical surface extracted in the native space of the images with sub-millimeter accuracy is then further used for the creation of an outer surface, which will serve as a basis for the lGI calculation. A circular region of interest is then delineated on the outer surface, and its corresponding region of interest on the cortical surface is identified using a matching algorithm as described in our validation study(1). This process is repeatedly iterated with largely overlapping regions of interest, resulting in cortical maps of gyrification for subsequent statistical comparisons (Fig. 1). Of note, another measurement of local gyrification with a similar inspiration was proposed by Toro and colleagues(7), where the folding index at each point is computed as the ratio of the cortical area contained in a sphere divided by the area of a disc with the same radius. The two implementations differ in that the one by Toro et al. is based on Euclidian distances and thus considers discontinuous patches of cortical area, whereas ours uses a strict geodesic algorithm and include only the continuous patch of cortical area opening at the brain surface in a circular region of interest.

Organic Matter Fractions and Quality of the Surface Layer of a Constructed and Vegetated Soil After Coal Mining. I - Humic Substances and Chemical Characterization

After open coal mining, soils are “constructed”, which usually contain low levels and quality of organic matter (OM). Therefore, the use of plant species for revegetation and reclamation of degraded areas is essential. This study evaluated the distribution of carbon (C) in the chemical fractions as well as the chemical characteristics and humification degree of OM in a soil constructed after coal mining under cultivation of perennial grasses. The experiment was established in 2003 with the following treatments: Hemarthria altissima (T1), Paspalum notatum (T2), Cynodon dactilon (T3), Urochloa brizantha (T4), bare constructed soil (T5), and natural soil (T6). In 2009, soil samples were collected from the 0.00-0.03 m layer and the total organic carbon stock (TOC) and C stock in the chemical fractions: acid extract (CHCl), fulvic acid (CFA), humic acid (CHA), and humin (CHU) were determined. The humic acid (HA) fraction was characterized by infrared spectroscopy and the laser-induced fluorescence index (ILIF) of OM was also calculated. After six years, differences were only observed in the CHA stocks, which were highest in T1 (0.89 Mg ha-1) and T4 (1.06 Mg ha-1). The infrared spectra of HA in T1, T2 and T4 were similar to T6, with greater contribution of aliphatic organic compounds than in the other treatments. In this way, ILIF decreased in the sequence T5>T3>T4>T1>T2>T6, indicating higher OM humification in T3 and T5 and more labile OM in the other treatments. Consequently, the potential of OM quality recovery in the constructed soil was greatest in treatments T1 and T4.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Glial and axonal body fluid biomarkers are related to infarct volume, severity, and outcome.

Body fluid biomarkers of central nervous system damage may help improve the prognostic and diagnostic accuracy in ischemic stroke. We studied 53 patients. Stroke severity and outcome was rated using the National Institutes of Health Stroke Scale and modified Rankin scale. Ferritin, S100B, and NfH were measured in cerebrospinal fluid (CSF) and serum. Infarct volume was calculated from T2W images. CSF S100B (median 1.00 ng/mL) and CSF ferritin (10.0 ng/mL) levels were elevated in patients with stroke compared with control subjects (0.62 ng/mL, P < .0001; 2.34 ng/mL, P < .0001). Serum S100B (0.09 ng/mL) was higher in patients with stroke compared with control subjects (0.01 ng/mL). CSF S100B levels were higher in patients with a cardioembolic stroke (2.88 ng/mL) than in those with small-vessel disease (0.89 ng/mL, P < .05). CSF S100B levels correlated with the National Institutes of Health Stroke Scale score on admission (R = 0.56, P < .01) and the stroke volume (R = 0.44, P = .01). CSF S100B and NfH-SMI35 levels correlated with outcome on the modified Rankin scale. CSF S100B levels were related to stroke severity and infarct volume and highest in cardioembolic stroke.

Carotid-subclavian arteries Index (CSI), a new echocardiographic index to recognize coarctation of the aorta in neonates and infants

Introduction: Coarctation of the aorta is a common congenital heart malformation. Mode of diagnosis changed from clinically to almost exclusively by echocardiogram and MRI. We claim to find a new echocardiographic index, based on simple and reliable morphologic measurements, to facilitate the diagnosis of aortic coarctation in the newborn.We reproduce the same procedure for older child to validate this new index. Material and Methods: We reviewed echocardiographic studies of 47 neonates with diagnosis of coarctation who underwent cardiac surgery between January 1997 and February 2003 and compared them with a matched control group. We measured 12 different sites of the aorta, aortic arch and the great vessels on the echocardiographic bands. In a second time we reviewed 23 infants for the same measurements and compare them with a matched control group. Results: 47 neonates with coarctation were analysed, age 11.8 _ 10 days,weight 3.0 _ 0.6 kg, body surface 0.20 _ 0.02m2. The control group was of 16 newborns aged 15.8 _ 10 days,weight 3.2 _ 0.9 kg and body surface 0.20 _ 0.04m2. A significant difference was noted in many morphologic measurement between the both groups, the most significant being the distance between the left carotid artery and the left subclavian artery (coarctation vs control: 7.3 _ 3mm vs 2.4 _ 0.8mm, p _ 0.0001). We then defined a new index, the carotid-subclavian arteries index (CSI) as the diameter of the distal tranverse aortic arch divided to the distance left carotid artery to left subclavian artery being also significaly different (coarctation vs control: 0.76 _ 0.86 vs 2.95 _ 1.24, p _ 0.0001). With the cutoff value of this index of 1.5 the sensitivity for aortic coarctation was 98% and the specificity of 92%. In an older group of infant with coarctation (16 patients) we apply the same principle and find for a cut-off value of 1.5 a sensitivity of 95% and a specificity of 100%. Conclusions: The CSI allows to evaluate newborns and infants for aortic coarctation with simple morphologic measurement that are not depending of the left ventricular function, presence of a patent ductus arteriosus or not. Further aggressive evaluation of these patient with a CSI _ 1.5 is indicated.

Using high-resolution quantitative mapping of R1 as an index of cortical myelination

A fundamental tenet of neuroscience is that cortical functional differentiation is related to the cross-areal differences in cyto-, receptor-, and myeloarchitectonics that are observed in ex-vivo preparations. An ongoing challenge is to create noninvasive magnetic resonance (MR) imaging techniques that offer sufficient resolution, tissue contrast, accuracy and precision to allow for characterization of cortical architecture over an entire living human brain. One exciting development is the advent of fast, high-resolution quantitative mapping of basic MR parameters that reflect cortical myeloarchitecture. Here, we outline some of the theoretical and technical advances underlying this technique, particularly in terms of measuring and correcting for transmit and receive radio frequency field inhomogeneities. We also discuss new directions in analytic techniques, including higher resolution reconstructions of the cortical surface. We then discuss two recent applications of this technique. The first compares individual and group myelin maps to functional retinotopic maps in the same individuals, demonstrating a close relationship between functionally and myeloarchitectonically defined areal boundaries (as well as revealing an interesting disparity in a highly studied visual area). The second combines tonotopic and myeloarchitectonic mapping to localize primary auditory areas in individual healthy adults, using a similar strategy as combined electrophysiological and post-mortem myeloarchitectonic studies in non-human primates.

Testing the bivariate distribution of daily equity returns using copulas: an application to the Spanish stock market

In this paper we deal with the identification of dependencies between time series of equity returns. Marginal distribution functions are assumed to be known, and a bivariate chi-square test of fit is applied in a fully parametric copula approach. Several families of copulas are fitted and compared with Spanish stock market data. The results show that the t-copula generally outperforms other dependence structures, and highlight the difficulty in adjusting a significant number of bivariate data series

Determinants of the omega-3 index in a Mediterranean population at increased risk for CHD.

The omega-3 index, defined as the sum of EPA and DHA in erythrocyte membranes expressed as a percentage of total fatty acids, has been proposed as both a risk marker and risk factor for CHD death. A major determinant of the omega-3 index is EPA þ DHA intake, but the impact of other dietary fatty acids has not been investigated. In a cross-sectional study on 198 subjects (102 men and 96 women, mean age 66 years) at high cardiovascular risk living in Spain, the country with low rates of cardiac death despite a high prevalence of cardiovascular risk factors, dietary data were acquired from FFQ and blood cell membrane fatty acid composition was measured by GC. The average consumption of EPA þ DHA was 0·9 g/d and the mean omega-3 index was 7·1%. In multivariate models, EPA þ DHA intake was the main predictor of the omega-3 index but explained only 12% of its variability (P,0·001). No associations with other dietary fatty acids were observed. Although the single most influential determinant of the omega-3 index measured here was the intake of EPA þ DHA, it explained little of the former"s variability; hence, the effects of other factors (genetic, dietary and lifestyle) remain to be determined. Nevertheless, the high omega-3 index could at least partially explain the paradox of low rates of fatal CHD in Spain despite a high background prevalence of cardiovascular risk factors.

Simpson-Golabi-Behmel syndrome type 1 in a 27-week macrosomic preterm newborn: the diagnostic value of rib malformations and index nail and finger hypoplasia.

The Simpson-Golabi-Behmel syndrome type 1 (SGBS1, OMIM #312870) is an X-linked overgrowth condition comprising abnormal facial appearance, supernumerary nipples, congenital heart defects, polydactyly, fingernail hypoplasia, increased risk of neonatal death and of neoplasia. It is caused by mutation/deletion of the GPC3 gene. We describe a macrosomic 27-week preterm newborn with SGBS1 who presents a novel GPC3 mutation and emphasize the phenotypic aspects which allow a correct diagnosis neonatally in particular the rib malformations, hypoplasia of index finger and of the same fingernail, and 2nd-3rd finger syndactyly.

Determinants of the omega-3 index in a Mediterranean population at increased risk for CHD.

The omega-3 index, defined as the sum of EPA and DHA in erythrocyte membranes expressed as a percentage of total fatty acids, has been proposed as both a risk marker and risk factor for CHD death. A major determinant of the omega-3 index is EPA þ DHA intake, but the impact of other dietary fatty acids has not been investigated. In a cross-sectional study on 198 subjects (102 men and 96 women, mean age 66 years) at high cardiovascular risk living in Spain, the country with low rates of cardiac death despite a high prevalence of cardiovascular risk factors, dietary data were acquired from FFQ and blood cell membrane fatty acid composition was measured by GC. The average consumption of EPA þ DHA was 0·9 g/d and the mean omega-3 index was 7·1%. In multivariate models, EPA þ DHA intake was the main predictor of the omega-3 index but explained only 12% of its variability (P,0·001). No associations with other dietary fatty acids were observed. Although the single most influential determinant of the omega-3 index measured here was the intake of EPA þ DHA, it explained little of the former"s variability; hence, the effects of other factors (genetic, dietary and lifestyle) remain to be determined. Nevertheless, the high omega-3 index could at least partially explain the paradox of low rates of fatal CHD in Spain despite a high background prevalence of cardiovascular risk factors.

An index to identify stroke-related vs incidental patent foramen ovale in cryptogenic stroke.

OBJECTIVE: We aimed to create an index to stratify cryptogenic stroke (CS) patients with patent foramen ovale (PFO) by their likelihood that the stroke was related to their PFO. METHODS: Using data from 12 component studies, we used generalized linear mixed models to predict the presence of PFO among patients with CS, and derive a simple index to stratify patients with CS. We estimated the stratum-specific PFO-attributable fraction and stratum-specific stroke/TIA recurrence rates. RESULTS: Variables associated with a PFO in CS patients included younger age, the presence of a cortical stroke on neuroimaging, and the absence of these factors: diabetes, hypertension, smoking, and prior stroke or TIA. The 10-point Risk of Paradoxical Embolism score is calculated from these variables so that the youngest patients with superficial strokes and without vascular risk factors have the highest score. PFO prevalence increased from 23% (95% confidence interval [CI]: 19%-26%) in those with 0 to 3 points to 73% (95% CI: 66%-79%) in those with 9 or 10 points, corresponding to attributable fraction estimates of approximately 0% to 90%. Kaplan-Meier estimated stroke/TIA 2-year recurrence rates decreased from 20% (95% CI: 12%-28%) in the lowest Risk of Paradoxical Embolism score stratum to 2% (95% CI: 0%-4%) in the highest. CONCLUSION: Clinical characteristics identify CS patients who vary markedly in PFO prevalence, reflecting clinically important variation in the probability that a discovered PFO is likely to be stroke-related vs incidental. Patients in strata more likely to have stroke-related PFOs have lower recurrence risk.

Novel Approach Identifies SNPs in SLC2A10 and KCNK9 with Evidence for Parent-of-Origin Effect on Body Mass Index.

The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.