Estimation of the viscoelastic properties of vessel walls using a computational model and Doppler ultrasound

Human arteries affected by atherosclerosis are characterized by altered wall viscoelastic properties. The possibility of noninvasively assessing arterial viscoelasticity in vivo would significantly contribute to the early diagnosis and prevention of this disease. This paper presents a noniterative technique to estimate the viscoelastic parameters of a vascular wall Zener model. The approach requires the simultaneous measurement of flow variations and wall displacements, which can be provided by suitable ultrasound Doppler instruments. Viscoelastic parameters are estimated by fitting the theoretical constitutive equations to the experimental measurements using an ARMA parameter approach. The accuracy and sensitivity of the proposed method are tested using reference data generated by numerical simulations of arterial pulsation in which the physiological conditions and the viscoelastic parameters of the model can be suitably varied. The estimated values quantitatively agree with the reference values, showing that the only parameter affected by changing the physiological conditions is viscosity, whose relative error was about 27% even when a poor signal-to-noise ratio is simulated. Finally, the feasibility of the method is illustrated through three measurements made at different flow regimes on a cylindrical vessel phantom, yielding a parameter mean estimation error of 25%.

Swain: Stata module to correct the SEM chi-square overidentification test in small sample sizes or complex models. Statistical Software Components S457617, Boston College Department of Economics.

Swain corrects the chi-square overidentification test (i.e., likelihood ratio test of fit) for structural equation models whethr with or without latent variables. The chi-square statistic is asymptotically correct; however, it does not behave as expected in small samples and/or when the model is complex (cf. Herzog, Boomsma, & Reinecke, 2007). Thus, particularly in situations where the ratio of sample size (n) to the number of parameters estimated (p) is relatively small (i.e., the p to n ratio is large), the chi-square test will tend to overreject correctly specified models. To obtain a closer approximation to the distribution of the chi-square statistic, Swain (1975) developed a correction; this scaling factor, which converges to 1 asymptotically, is multiplied with the chi-square statistic. The correction better approximates the chi-square distribution resulting in more appropriate Type 1 reject error rates (see Herzog & Boomsma, 2009; Herzog, et al., 2007).

Méthodes sismiques actives adaptées à l'étude de milieux hétérogènes : application aux glissements de terrain

Résumé Les glissements de terrain représentent un des principaux risques naturels dans les régions montagneuses. En Suisse, chaque année les glissements de terrains causent des dégâts qui affectent les infrastructures et ont des coûts financiers importants. Une bonne compréhension des mécanismes des glissements peut permettre d'atténuer leur impact. Celle-ci passe notamment par la connaissance de la structure interne du glissement, la détermination de son volume et de son ou ses plans de glissement. Dans un glissement de terrain, la désorganisation et la présence de fractures dans le matériel déplacé engendre un changement des paramètres physiques et en particulier une diminution des vitesses de propagation des ondes sismiques ainsi que de la densité du matériel. Les méthodes sismiques sont de ce fait bien adaptées à l'étude des glissements de terrain. Parmi les méthodes sismiques, l'analyse de la dispersion des ondes de surface est une méthode simple à mettre en oeuvre. Elle présente l'avantage d'estimer les variations des vitesses de cisaillement avec la profondeur sans avoir spécifiquement recours à l'utilisation d'une source d'onde S et de géophones horizontaux. Sa mise en oeuvre en trois étapes implique la mesure de la dispersion des ondes de surface sur des réseaux étendus, la détermination des courbes de dispersion pour finir par l'inversion de ces courbes. Les modèles de vitesse obtenus à partir de cette procédure ne sont valides que lorsque les milieux explorés ne présentent pas de variations latérales. En pratique cette hypothèse est rarement vérifiée, notamment pour un glissement de terrain dans lequel les couches remaniées sont susceptibles de présenter de fortes hétérogénéités latérales. Pour évaluer la possibilité de déterminer des courbes de dispersion à partir de réseaux de faible extension des mesures testes ont été effectuées sur un site (Arnex, VD) équipé d'un forage. Un profil sismique de 190 m de long a été implanté dans une vallée creusée dans du calcaire et remplie par des dépôts glacio-lacustres d'une trentaine de mètres d'épaisseur. Les données acquises le long de ce profil ont confirmé que la présence de variations latérales sous le réseau de géophones affecte l'allure des courbes de dispersion jusqu'à parfois empêcher leur détermination. Pour utiliser l'analyse de la dispersion des ondes de surface sur des sites présentant des variations latérales, notre approche consiste à déterminer les courbes de dispersions pour une série de réseaux de faible extension, à inverser chacune des courbes et à interpoler les différents modèles de vitesse obtenus. Le choix de la position ainsi que de l'extension des différents réseaux de géophones est important. Il tient compte de la localisation des hétérogénéités détectées à partir de l'analyse de sismique réfraction, mais également d'anomalies d'amplitudes observées sur des cartes qui représentent dans le domaine position de tir - position du récepteur, l'amplitude mesurée pour différentes fréquences. La procédure proposée par Lin et Lin (2007) s'est avérée être une méthode efficace permettant de déterminer des courbes de dispersion à partir de réseaux de faible extension. Elle consiste à construire à partir d'un réseau de géophones et de plusieurs positions de tir un enregistrement temps-déports qui tient compte d'une large gamme de distances source-récepteur. Au moment d'assembler les différentes données une correction de phase est appliquée pour tenir compte des hétérogénéités situées entre les différents points de tir. Pour évaluer cette correction nous suggérons de calculer pour deux tir successif la densité spectrale croisée des traces de même offset: Sur le site d'Arnex, 22 courbes de dispersions ont été déterminées pour de réseaux de géophones de 10 m d'extension. Nous avons également profité du forage pour acquérir un profil de sismique verticale en ondes S. Le modèle de vitesse S déduit de l'interprétation du profil de sismique verticale est utilisé comme information à priori lors l'inversion des différentes courbes de dispersion. Finalement, le modèle en deux dimension qui a été établi grâce à l'analyse de la dispersion des ondes de surface met en évidence une structure tabulaire à trois couches dont les limites coïncident bien avec les limites lithologiques observées dans le forage. Dans celui-ci des argiles limoneuses associées à une vitesse de propagation des ondes S de l'ordre de 175 m/s surmontent vers 9 m de profondeur des dépôts de moraine argilo-sableuse caractérisés par des vitesses de propagation des ondes S de l'ordre de 300 m/s jusqu'à 14 m de profondeur et supérieur ou égal à 400 m/s entre 14 et 20 m de profondeur. Le glissement de la Grande Combe (Ballaigues, VD) se produit à l'intérieur du remplissage quaternaire d'une combe creusée dans des calcaires Portlandien. Comme dans le cas du site d'Arnex les dépôts quaternaires correspondent à des dépôts glacio-lacustres. Dans la partie supérieure la surface de glissement a été localisée à une vingtaine de mètres de profondeur au niveau de l'interface qui sépare des dépôts de moraine jurassienne et des dépôts glacio-lacustres. Au pied du glissement 14 courbes de dispersions ont été déterminées sur des réseaux de 10 m d'extension le long d'un profil de 144 m. Les courbes obtenues sont discontinues et définies pour un domaine de fréquence de 7 à 35 Hz. Grâce à l'utilisation de distances source-récepteur entre 8 et 72 m, 2 à 4 modes de propagation ont été identifiés pour chacune des courbes. Lors de l'inversion des courbes de dispersion la prise en compte des différents modes de propagation a permis d'étendre la profondeur d'investigation jusqu'à une vingtaine de mètres de profondeur. Le modèle en deux dimensions permet de distinguer 4 couches (Vs1 < 175 m/s, 175 m/s < Vs2 < 225 m/s, 225 m/s < Vs3 < 400 m/s et Vs4 >.400 m/s) qui présentent des variations d'épaisseur. Des profils de sismiques réflexion en ondes S acquis avec une source construite dans le cadre de ce travail, complètent et corroborent le modèle établi à partir de l'analyse de la dispersion des ondes de surface. Un réflecteur localisé entre 5 et 10 m de profondeur et associé à une vitesse de sommation de 180 m/s souligne notamment la géométrie de l'interface qui sépare la deuxième de la troisième couche du modèle établi à partir de l'analyse de la dispersion des ondes de surface. Abstract Landslides are one of the main natural hazards in mountainous regions. In Switzerland, landslides cause damages every year that impact infrastructures and have important financial costs. In depth understanding of sliding mechanisms may help limiting their impact. In particular, this can be achieved through a better knowledge of the internal structure of the landslide, the determination of its volume and its sliding surface or surfaces In a landslide, the disorganization and the presence of fractures in the displaced material generate a change of the physical parameters and in particular a decrease of the seismic velocities and of the material density. Therefoe, seismic methods are well adapted to the study of landslides. Among seismic methods, surface-wave dispersion analysis is a easy to implement. Through it, shearwave velocity variations with depth can be estimated without having to resort to an S-wave source and to horizontal geophones. Its 3-step implementation implies measurement of surface-wave dispersion with long arrays, determination of the dispersion curves and finally inversion of these curves. Velocity models obtained through this approach are only valid when the investigated medium does not include lateral variations. In practice, this assumption is seldom correct, in particular for landslides in which reshaped layers likely include strong lateral heterogeneities. To assess the possibility of determining dispersion curves from short array lengths we carried out tests measurements on a site (Arnex, VD) that includes a borehole. A 190 m long seismic profile was acquired in a valley carved into limestone and filled with 30 m of glacio-lacustrine sediments. The data acquired along this profile confirmed that the presence of lateral variations under the geophone array influences the dispersion-curve shape so much that it sometimes preventes the dispersion curves determination. Our approach to use the analysis of surface-wave dispersion on sites that include lateral variations consists in obtaining dispersion curves for a series of short length arrays; inverting each so obtained curve and interpolating the different obtained velocity model. The choice of the location as well as the geophone array length is important. It takes into account the location of the heterogeneities that are revealed by the seismic refraction interpretation of the data but also, the location of signal amplitude anomalies observed on maps that represent, for a given frequency, the measured amplitude in the shot position - receiver position domain. The procedure proposed by Lin and Lin (2007) turned out to be an efficient one to determine dispersion curves using short extension arrays. It consists in building a time-offset from an array of geophones with a wide offset range by gathering seismograms acquired with different source-to-receiver offsets. When assembling the different data, a phase correction is applied in order to reduce static phase error induced by lateral variation. To evaluate this correction, we suggest to calculate, for two successive shots, the cross power spectral density of common offset traces. On the Arnex site, 22 curves were determined with 10m in length geophone-arrays. We also took advantage of the borehole to acquire a S-wave vertical seismic profile. The S-wave velocity depth model derived from the vertical seismic profile interpretation is used as prior information in the inversion of the dispersion-curves. Finally a 2D velocity model was established from the analysis of the different dispersion curves. It reveals a 3-layer structure in good agreement with the observed lithologies in the borehole. In it a clay layer with a shear-wave of 175 m/s shear-wave velocity overlies a clayey-sandy till layer at 9 m depth that is characterized down to 14 m by a 300 m/s S-wave velocity; these deposits have a S-wave velocity of 400 m/s between depths of 14 to 20 m. The La Grand Combe landslide (Ballaigues, VD) occurs inside the Quaternary filling of a valley carved into Portlandien limestone. As at the Arnex site, the Quaternary deposits correspond to glaciolacustrine sediments. In the upper part of the landslide, the sliding surface is located at a depth of about 20 m that coincides with the discontinuity between Jurassian till and glacio-lacustrine deposits. At the toe of the landslide, we defined 14 dispersion curves along a 144 m long profile using 10 m long geophone arrays. The obtained curves are discontinuous and defined within a frequency range of 7 to 35 Hz. The use of a wide range of offsets (from 8 to 72 m) enabled us to determine 2 to 4 mode of propagation for each dispersion curve. Taking these higher modes into consideration for dispersion curve inversion allowed us to reach an investigation depth of about 20 m. A four layer 2D model was derived (Vs1< 175 m/s, 175 m/s <Vs2< 225 m/s, 225 m/s < Vs3 < 400 m/s, Vs4> 400 m/s) with variable layer thicknesses. S-wave seismic reflection profiles acquired with a source built as part of this work complete and the velocity model revealed by surface-wave analysis. In particular, reflector at a depth of 5 to 10 m associated with a 180 m/s stacking velocity image the geometry of the discontinuity between the second and third layer of the model derived from the surface-wave dispersion analysis.

Correction: Topographical Body Fat Distribution Links to Amino Acid and Lipid Metabolism in Healthy Obese Women.

This corrects the article on p. e73445 in vol. 8.]. This corrects the article "Topographical Body Fat Distribution Links to Amino Acid and Lipid Metabolism in Healthy Non-Obese Women" , e73445. There was an error in the title of the article. The correct version of the title in the article is: Topographical Body Fat Distribution Links to Amino Acid and Lipid Metabolism in Healthy Obese Women The correct citation is: Martin F-PJ, Montoliu I, Collino S, Scherer M, Guy P, et al. (2013) Topographical Body Fat Distribution Links to Amino Acid and Lipid Metabolism in Healthy Obese Women. PLoS ONE 8(9): e73445. doi:10.1371/journal.pone.0073445

Adaptive model selection using empirical complexities

Given $n$ independent replicates of a jointly distributed pair $(X,Y)\in {\cal R}^d \times {\cal R}$, we wish to select from a fixed sequence of model classes ${\cal F}_1, {\cal F}_2, \ldots$ a deterministic prediction rule $f: {\cal R}^d \to {\cal R}$ whose risk is small. We investigate the possibility of empirically assessingthe {\em complexity} of each model class, that is, the actual difficulty of the estimation problem within each class. The estimated complexities are in turn used to define an adaptive model selection procedure, which is based on complexity penalized empirical risk.The available data are divided into two parts. The first is used to form an empirical cover of each model class, and the second is used to select a candidate rule from each cover based on empirical risk. The covering radii are determined empirically to optimize a tight upper bound on the estimation error. An estimate is chosen from the list of candidates in order to minimize the sum of class complexity and empirical risk. A distinguishing feature of the approach is that the complexity of each model class is assessed empirically, based on the size of its empirical cover.Finite sample performance bounds are established for the estimates, and these bounds are applied to several non-parametric estimation problems. The estimates are shown to achieve a favorable tradeoff between approximation and estimation error, and to perform as well as if the distribution-dependent complexities of the model classes were known beforehand. In addition, it is shown that the estimate can be consistent,and even possess near optimal rates of convergence, when each model class has an infinite VC or pseudo dimension.For regression estimation with squared loss we modify our estimate to achieve a faster rate of convergence.

Interpolation-free Coregistration and Phase-Correction of Airborne SAR Interferograms

This letter discusses the detection and correction ofresidual motion errors that appear in airborne synthetic apertureradar (SAR) interferograms due to the lack of precision in the navigationsystem. As it is shown, the effect of this lack of precision istwofold: azimuth registration errors and phase azimuth undulations.Up to now, the correction of the former was carried out byestimating the registration error and interpolating, while the latterwas based on the estimation of the phase azimuth undulations tocompensate the phase of the computed interferogram. In this letter,a new correction method is proposed, which avoids the interpolationstep and corrects at the same time the azimuth phase undulations.Additionally, the spectral diversity technique, used to estimateregistration errors, is critically analyzed. Airborne L-bandrepeat-pass interferometric data of the German Aerospace Center(DLR) experimental airborne SAR is used to validate the method

A limited area model intercomparison on the "Montserrat-2000" flash-flood event using statistical and deterministic methods

In the scope of the European project Hydroptimet, INTERREG IIIB-MEDOCC programme, limited area model (LAM) intercomparison of intense events that produced many damages to people and territory is performed. As the comparison is limited to single case studies, the work is not meant to provide a measure of the different models' skill, but to identify the key model factors useful to give a good forecast on such a kind of meteorological phenomena. This work focuses on the Spanish flash-flood event, also known as "Montserrat-2000" event. The study is performed using forecast data from seven operational LAMs, placed at partners' disposal via the Hydroptimet ftp site, and observed data from Catalonia rain gauge network. To improve the event analysis, satellite rainfall estimates have been also considered. For statistical evaluation of quantitative precipitation forecasts (QPFs), several non-parametric skill scores based on contingency tables have been used. Furthermore, for each model run it has been possible to identify Catalonia regions affected by misses and false alarms using contingency table elements. Moreover, the standard "eyeball" analysis of forecast and observed precipitation fields has been supported by the use of a state-of-the-art diagnostic method, the contiguous rain area (CRA) analysis. This method allows to quantify the spatial shift forecast error and to identify the error sources that affected each model forecasts. High-resolution modelling and domain size seem to have a key role for providing a skillful forecast. Further work is needed to support this statement, including verification using a wider observational data set.

Enhanced radar precipitation estimates using a combined clutter and beam blockage correction technique

Weather radar observations are currently the most reliable method for remote sensing of precipitation. However, a number of factors affect the quality of radar observations and may limit seriously automated quantitative applications of radar precipitation estimates such as those required in Numerical Weather Prediction (NWP) data assimilation or in hydrological models. In this paper, a technique to correct two different problems typically present in radar data is presented and evaluated. The aspects dealt with are non-precipitating echoes - caused either by permanent ground clutter or by anomalous propagation of the radar beam (anaprop echoes) - and also topographical beam blockage. The correction technique is based in the computation of realistic beam propagation trajectories based upon recent radiosonde observations instead of assuming standard radio propagation conditions. The correction consists of three different steps: 1) calculation of a Dynamic Elevation Map which provides the minimum clutter-free antenna elevation for each pixel within the radar coverage; 2) correction for residual anaprop, checking the vertical reflectivity gradients within the radar volume; and 3) topographical beam blockage estimation and correction using a geometric optics approach. The technique is evaluated with four case studies in the region of the Po Valley (N Italy) using a C-band Doppler radar and a network of raingauges providing hourly precipitation measurements. The case studies cover different seasons, different radio propagation conditions and also stratiform and convective precipitation type events. After applying the proposed correction, a comparison of the radar precipitation estimates with raingauges indicates a general reduction in both the root mean squared error and the fractional error variance indicating the efficiency and robustness of the procedure. Moreover, the technique presented is not computationally expensive so it seems well suited to be implemented in an operational environment.

A new estimator to minimize the error due to breathing in the measurement of respiratory impedance

This paper presents a new respiratory impedance estimator to minimize the error due to breathing. Its practical reliability was evaluated in a simulation using realistic signals. These signals were generated by superposing pressure and flow records obtained in two conditions: 1) when applying forced oscillation to a resistance- inertance- elastance (RIE) mechanical model; 2) when healthy subjects breathed through the unexcited forced oscillation generator. Impedances computed (4-32 Hz) from the simulated signals with the new estimator resulted in a mean value which was scarcely biased by the added breathing (errors less than 1 percent in the mean R, I , and E ) and had a small variability (coefficients of variation of R, I, and E of 1.3, 3.5, and 9.6 percent, respectively). Our results suggest that the proposed estimator reduces the error in measurement of respiratory impedance without appreciable extracomputational cost.

Gas identification with tin oxide sensor array and self-organizing maps: adaptive correction of sensor drifts

Low-cost tin oxide gas sensors are inherently nonspecific. In addition, they have several undesirable characteristics such as slow response, nonlinearities, and long-term drifts. This paper shows that the combination of a gas-sensor array together with self-organizing maps (SOM's) permit success in gas classification problems. The system is able to determine the gas present in an atmosphere with error rates lower than 3%. Correction of the sensor's drift with an adaptive SOM has also been investigated

Estudi de l'estat de Salut autopercebut: Modelització de l'índex d'utilitat EQ-5D mitjançant un model tobit

Objective: Health status measures usually have an asymmetric distribution and present a highpercentage of respondents with the best possible score (ceiling effect), specially when they areassessed in the overall population. Different methods to model this type of variables have beenproposed that take into account the ceiling effect: the tobit models, the Censored Least AbsoluteDeviations (CLAD) models or the two-part models, among others. The objective of this workwas to describe the tobit model, and compare it with the Ordinary Least Squares (OLS) model,that ignores the ceiling effect.Methods: Two different data sets have been used in order to compare both models: a) real datacomming from the European Study of Mental Disorders (ESEMeD), in order to model theEQ5D index, one of the measures of utilities most commonly used for the evaluation of healthstatus; and b) data obtained from simulation. Cross-validation was used to compare thepredicted values of the tobit model and the OLS models. The following estimators werecompared: the percentage of absolute error (R1), the percentage of squared error (R2), the MeanSquared Error (MSE) and the Mean Absolute Prediction Error (MAPE). Different datasets werecreated for different values of the error variance and different percentages of individuals withceiling effect. The estimations of the coefficients, the percentage of explained variance and theplots of residuals versus predicted values obtained under each model were compared.Results: With regard to the results of the ESEMeD study, the predicted values obtained with theOLS model and those obtained with the tobit models were very similar. The regressioncoefficients of the linear model were consistently smaller than those from the tobit model. In thesimulation study, we observed that when the error variance was small (s=1), the tobit modelpresented unbiased estimations of the coefficients and accurate predicted values, specially whenthe percentage of individuals wiht the highest possible score was small. However, when theerrror variance was greater (s=10 or s=20), the percentage of explained variance for the tobitmodel and the predicted values were more similar to those obtained with an OLS model.Conclusions: The proportion of variability accounted for the models and the percentage ofindividuals with the highest possible score have an important effect in the performance of thetobit model in comparison with the linear model.

Local and global error models to improve uncertainty quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

Tc-99m-MAA SPECT-derived tumor-to-normal liver ratios for partition model dosimetry in selective internal radiation therapy (SIRT)

Aim: When planning SIRT using 90Y microspheres, the partition model is used to refine the activity calculated by the body surface area (BSA) method to potentially improve the safety and efficacy of treatment. For this partition model dosimetry, accurate determination of mean tumor-to-normal liver ratio (TNR) is critical since it directly impacts absorbed dose estimates. This work aimed at developing and assessing a reliable methodology for the calculation of 99mTc-MAA SPECT/CT-derived TNR ratios based on phantom studies. Materials and methods: IQ NEMA (6 hot spheres) and Kyoto liver phantoms with different hot/background activity concentration ratios were imaged on a SPECT/CT (GE Infinia Hawkeye 4). For each reconstruction with the IQ phantom, TNR quantification was assessed in terms of relative recovery coefficients (RC) and image noise was evaluated in terms of coefficient of variation (COV) in the filled background. RCs were compared using OSEM with Hann, Butterworth and Gaussian filters, as well as FBP reconstruction algorithms. Regarding OSEM, RCs were assessed by varying different parameters independently, such as the number of iterations (i) and subsets (s) and the cut-off frequency of the filter (fc). The influence of the attenuation and diffusion corrections was also investigated. Furthermore, both 2D-ROIs and 3D-VOIs contouring were compared. For this purpose, dedicated Matlab© routines were developed in-house for automatic 2D-ROI/3D-VOI determination to reduce intra-user and intra-slice variability. Best reconstruction parameters and RCs obtained with the IQ phantom were used to recover corrected TNR in case of the Kyoto phantom for arbitrary hot-lesion size. In addition, we computed TNR volume histograms to better assess uptake heterogeneityResults: The highest RCs were obtained with OSEM (i=2, s=10) coupled with the Butterworth filter (fc=0.8). Indeed, we observed a global 20% RC improvement over other OSEM settings and a 50% increase as compared to the best FBP reconstruction. In any case, both attenuation and diffusion corrections must be applied, thus improving RC while preserving good image noise (COV<10%). Both 2D-ROI and 3D-VOI analysis lead to similar results. Nevertheless, we recommend using 3D-VOI since tumor uptake regions are intrinsically 3D. RC-corrected TNR values lie within 17% around the true value, substantially improving the evaluation of small volume (<15 mL) regions. Conclusions: This study reports the multi-parameter optimization of 99mTc MAA SPECT/CT images reconstruction in planning 90Y dosimetry for SIRT. In phantoms, accurate quantification of TNR was obtained using OSEM coupled with Butterworth and RC correction.

Modeling changes in organic carbon stocks for distinct soils in southeastern brazil after four eucalyptus rotations using the century model

Soil organic matter (SOM) plays an important role in carbon (C) cycle and soil quality. Considering the complexity of factors that control SOM cycling and the long time it usually takes to observe changes in SOM stocks, modeling constitutes a very important tool to understand SOM cycling in forest soils. The following hypotheses were tested: (i) soil organic carbon (SOC) stocks would be higher after several rotations of eucalyptus than in low-productivity pastures; (ii) SOC values simulated by the Century model would describe the data better than the mean of observations. So, the aims of the current study were: (i) to evaluate the SOM dynamics using the Century model to simulate the changes of C stocks for two eucalyptus chronosequences in the Rio Doce Valley, Minas Gerais State, Brazil; and (ii) to compare the C stocks simulated by Century with the C stocks measured in soils of different Orders and regions of the Rio Doce Valley growing eucalyptus. In Belo Oriente (BO), short-rotation eucalyptus plantations had been cultivated for 4.0; 13.0, 22.0, 32.0 and 34.0 years, at a lower elevation and in a warmer climate, while in Virginópolis (VG), these time periods were 8.0, 19.0 and 33.0 years, at a higher elevation and in a milder climate. Soil samples were collected from the 0-20 cm layer to estimate C stocks. Results indicate that the C stocks simulated by the Century model decreased after 37 years of poorly managed pastures in areas previously covered by native forest in the regions of BO and VG. The substitution of poorly managed pastures by eucalyptus in the early 1970´s led to an average increase of C of 0.28 and 0.42 t ha-1 year-1 in BO and VG, respectively. The measured C stocks under eucalyptus in distinct soil Orders and independent regions with variable edapho-climate conditions were not far from the values estimated by the Century model (root mean square error - RMSE = 20.9; model efficiency - EF = 0.29) despite the opposite result obtained with the statistical procedure to test the identity of analytical methods. Only for lower soil C stocks, the model over-estimated the C stock in the 0-20 cm layer. Thus, the Century model is highly promising to detect changes in C stocks in distinct soil orders under eucalyptus, as well as to indicate the impact of harvest residue management on SOM in future rotations.

Superheavy nuclei in relativistic effective Lagrangian model

Isotopic and isotonic chains of superheavy nuclei are analyzed to search for spherical double shell closures beyond Z=82 and N=126 within the new effective field theory model of Furnstahl, Serot, and Tang for the relativistic nuclear many-body problem. We take into account several indicators to identify the occurrence of possible shell closures, such as two-nucleon separation energies, two-nucleon shell gaps, average pairing gaps, and the shell correction energy. The effective Lagrangian model predicts N=172 and Z=120 and N=258 and Z=120 as spherical doubly magic superheavy nuclei, whereas N=184 and Z=114 show some magic character depending on the parameter set. The magicity of a particular neutron (proton) number in the analyzed mass region is found to depend on the number of protons (neutrons) present in the nucleus.