Sobre los subsistemas input-output en el análisis de emisiones contaminantes. Una aplicación a las emisiones de CH4 en Cataluña

En el presente trabajo se desarrolla un estudio de las emisiones de CH4 relacionadas con el sector agroalimentario catalán a través de un análisis alternativo, o al menos complementario, de subsistemas input-output. Una herramienta de gran utilidad para estudiar la estructura productiva de los diferentes sectores que componen una economía. La aplicación de esta técnica permite las descomposición del subsistema en distintos efectos en función de los vínculos intersectoriales existentes con el conjunto de las ramas productivas de la economía, dentro y fuera del subsistema. De los resultados obtenidos destaca la importancia de las relaciones intrasectoriales del subsistema agroalimentario, que muestra una relevante autonomía en cuanto a este tipo de emisiones respecto al resto de la economía. Esta característica orienta el tipo de políticas medioambientales a implementar con el objetivo de reducir el impacto atmosférico de dicha actividad.

Estimation of lean meat content in pig carcasses using X-ray Computed Tomography and PLS regression

Lean meat percentage (LMP) is an important carcass quality parameter. The aim of this work is to obtain a calibration equation for the Computed Tomography (CT) scans with the Partial Least Square Regression (PLS) technique in order to predict the LMP of the carcass and the different cuts and to study and compare two different methodologies of the selection of the variables (Variable Importance for Projection — VIP- and Stepwise) to be included in the prediction equation. The error of prediction with cross-validation (RMSEPCV) of the LMP obtained with PLS and selection based on VIP value was 0.82% and for stepwise selection it was 0.83%. The prediction of the LMP scanning only the ham had a RMSEPCV of 0.97% and if the ham and the loin were scanned the RMSEPCV was 0.90%. Results indicate that for CT data both VIP and stepwise selection are good methods. Moreover the scanning of only the ham allowed us to obtain a good prediction of the LMP of the whole carcass.

Hierarchical Shrinkage in Time-Varying Parameter Models

In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time-varying parameter models. Our approach allows for the coefficient on each predictor to be: i) time varying, ii) constant over time or iii) shrunk to zero. The econometric methodology decides automatically which category each coefficient belongs in. Our empirical results indicate the benefits of such an approach.

Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty

This paper extends the Nelson-Siegel linear factor model by developing a flexible macro-finance framework for modeling and forecasting the term structure of US interest rates. Our approach is robust to parameter uncertainty and structural change, as we consider instabilities in parameters and volatilities, and our model averaging method allows for investors' model uncertainty over time. Our time-varying parameter Nelson-Siegel Dynamic Model Averaging (NS-DMA) predicts yields better than standard benchmarks and successfully captures plausible time-varying term premia in real time. The proposed model has significant in-sample and out-of-sample predictability for excess bond returns, and the predictability is of economic value.

Fractional Integration of the Price-Dividend Ratio in a Present-Value Model of Stock Prices

We re-examine the dynamics of returns and dividend growth within the present-value framework of stock prices. We find that the finite sample order of integration of returns is approximately equal to the order of integration of the first-differenced price-dividend ratio. As such, the traditional return forecasting regressions based on the price-dividend ratio are invalid. Moreover, the nonstationary long memory behaviour of the price-dividend ratio induces antipersistence in returns. This suggests that expected returns should be modelled as an AFIRMA process and we show this improves the forecast ability of the present-value model in-sample and out-of-sample.

Modelling Housing Prices using a Present Value State Space Model

This paper introduces a State Space approach to explain the dynamics of rent growth, expected returns and Price-Rent ratio in housing markets. According to the present value model, movements in price to rent ratio should be matched by movements in expected returns and expected rent growth. The state space framework assume that both variables follow an autoregression process of order one. The model is applied to the US and UK housing market, which yields series of the latent variables given the behaviour of the Price-Rent ratio. Resampling techniques and bootstrapped likelihood ratios show that expected returns tend to be highly persistent compared to rent growth. The filtered expected returns is considered in a simple predictability of excess returns model with high statistical predictability evidence for the UK. Overall, it is found that the present value model tends to have strong statistical predictability in the UK housing markets.

Diffusion-weighted MR imaging of the spine at 3-T: feasibility, optimization of b-value and utility to differentiate benign from pathological vertebral compression fractures

Purpose: To evaluate the feasibility, determine the optimal b-value, and assess the utility of 3-T diffusion-weighted MR imaging (DWI) of the spine in differentiating benign from pathologic vertebral compression fractures.Methods and Materials: Twenty patients with 38 vertebral compression fractures (24 benign, 14 pathologic) and 20 controls (total: 23 men, 17 women, mean age 56.2years) were included from December 2010 to May 2011 in this IRB-approved prospective study. MR imaging of the spine was performed on a 3-T unit with T1-w, fat-suppressed T2-w, gadolinium-enhanced fat-suppressed T1-w and zoomed-EPI (2D RF excitation pulse combined with reduced field-of-view single-shot echo-planar readout) diffusion-w (b-values: 0, 300, 500 and 700s/mm2) sequences. Two radiologists independently assessed zoomed-EPI image quality in random order using a 4-point scale: 1=excellent to 4=poor. They subsequently measured apparent diffusion coefficients (ADCs) in normal vertebral bodies and compression fractures, in consensus.Results: Lower b-values correlated with better image quality scores, with significant differences between b=300 (mean±SD=2.6±0.8), b=500 (3.0±0.7) and b=700 (3.6±0.6) (all p<0.001). Mean ADCs of normal vertebral bodies (n=162) were 0.23, 0.17 and 0.11×10-3mm2/s with b=300, 500 and 700s/mm2, respectively. In contrast, mean ADCs were 0.89, 0.70 and 0.59×10-3mm2/s for benign vertebral compression fractures and 0.79, 0.66 and 0.51×10-3mm2/s for pathologic fractures with b=300, 500 and 700s/mm2, respectively. No significant difference was found between ADCs of benign and pathologic fractures.Conclusion: 3-T DWI of the spine is feasible and lower b-values (300s/mm2) are recommended. However, our preliminary results show no advantage of DWI in differentiating benign from pathologic vertebral compression fractures.

Generating controlled image sets in cognitive neuroscience research.

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

The value of ultrasonography in assessment of portal hypertension in hepatosplenic schistosomiasis

Ultrasonography can reveal most of the manifestations of portal hypertension complicating hepatosplenic, schistosomiasis. However, direct demonstration of gastroesophageal varices by ultrasonography is still very difficult. An attempt was done to correlate sonographic features of portal hypertension with the degree of fibrosis to screen patients having varices and predicting their chance of bleeding. The results obtained were found to be consistent with the esophagogastric endoscopy and with history of hematemesis. Four parameters were used, size of spleen, degree of periportal fibrosis, presence of collaterals and portal vein diameter. A pilot field survey was also done adopting the same principle.

GNSS array: diseño de una antena con polarización circular

Aquest projecte es centra en el disseny d’una antena microstrip per a GNSS. Una antena per a GNSS ha de tenir adaptació de impedància d’entrada i polarització circular a dretes, com a principals especificacions, en el rang de 1.15-1.6 GHz. El tipus d’alimentació d’una antena microstrip amb el major ample de banda d’adaptació és l’alimentació mitjançant acoblament per apertura. Si a l’antena s’introdueixen dos apertures de forma ortogonal, alimentades amb un desfasament de 90º entre elles, s’aconsegueix polarització circular. L’opció de separar les apertures redueix la transferència de potència entre elles, i disminueix el guany de polarització creuada. La xarxa d’alimentació dissenyada és un divisor de Wilkinson amb una línia de λ/4 a la freqüència central, encara que el desfasament als extrems de la banda no sigui de 90º. Com a xarxa d’alimentació es va provar un hibrid de 90º, però l’elevat valor del paràmetre S21 de l’antena impossibilita l’adaptació a l’entrada del hibrid.

Context-dependent interpretation of the prognostic value of BRAF and KRAS mutations in colorectal cancer.

BACKGROUND: The mutation status of the BRAF and KRAS genes has been proposed as prognostic biomarker in colorectal cancer. Of them, only the BRAF V600E mutation has been validated independently as prognostic for overall survival and survival after relapse, while the prognostic value of KRAS mutation is still unclear. We investigated the prognostic value of BRAF and KRAS mutations in various contexts defined by stratifications of the patient population. METHODS: We retrospectively analyzed a cohort of patients with stage II and III colorectal cancer from the PETACC-3 clinical trial (N = 1,423), by assessing the prognostic value of the BRAF and KRAS mutations in subpopulations defined by all possible combinations of the following clinico-pathological variables: T stage, N stage, tumor site, tumor grade and microsatellite instability status. In each such subpopulation, the prognostic value was assessed by log rank test for three endpoints: overall survival, relapse-free survival, and survival after relapse. The significance level was set to 0.01 for Bonferroni-adjusted p-values, and a second threshold for a trend towards statistical significance was set at 0.05 for unadjusted p-values. The significance of the interactions was tested by Wald test, with significance level of 0.05. RESULTS: In stage II-III colorectal cancer, BRAF mutation was confirmed a marker of poor survival only in subpopulations involving microsatellite stable and left-sided tumors, with higher effects than in the whole population. There was no evidence for prognostic value in microsatellite instable or right-sided tumor groups. We found that BRAF was also prognostic for relapse-free survival in some subpopulations. We found no evidence that KRAS mutations had prognostic value, although a trend was observed in some stratifications. We also show evidence of heterogeneity in survival of patients with BRAF V600E mutation. CONCLUSIONS: The BRAF mutation represents an additional risk factor only in some subpopulations of colorectal cancers, in others having limited prognostic value. However, in the subpopulations where it is prognostic, it represents a marker of much higher risk than previously considered. KRAS mutation status does not seem to represent a strong prognostic variable.

Análisis multi-región input-output (MRIO) de emisiones de gases efecto invernadero (GEI) incorporado en el comercio. Un modelo birregional aplicado a Cataluña y el resto de España

El siguiente trabajo realiza un análisis regional y sectorial para el estudio de la emisiones de gases efecto invernadero (GEI) incorporadas en el comercio entre las regiones de Cataluña y el resto de España para el año 2001, estimando así el Balance Neto en GEI incorporado. El objetivo es el desarrollo de un metodología que nos permita realizar esta estimación de forma rigurosa, con la intención de efectuar un análisis comparativo de ambas estructuras productivas territoriales, en cuanto a la intensidad de emisión y el impacto de la demanda final de las regiones consideradas. Para este propósito se utiliza el marco metodológico del análisis input-output, en particular se aplica dos tipologías de modelos: el modelo básico o single-región y el multi-región, lo que nos permite la comparabilidad entre ambos, demostrando como el modelo MRIO (multi-región input-output) es el método más apropiado para dicho propósito, permitiendo, entre otras ventajas, analizar los vínculos interregionales e intersectoriales de las regiones consideradas. La incorporación de la técnica de la integración vertical o subsistemas, nos permite un enfoque alternativo para el Balance Neto resultante, no tenemos constancia de que este enfoque haya sido utilizado con anterioridad en los análisis MRIO aplicados al estudio de los impactos medioambientales incorporados en el comercio. Tampoco la tenemos sobre la aplicación de los MRIO de forma general para estos impactos a nivel interregional de la economía española. El principal resultado obtenido nos indica que aún teniendo Cataluña un importante superávit comercial con el resto de España, hemos comprobado la existencia de un importante déficit para la primera en cuanto a la polución incorporada en este comercio.

The value of selected in vitro and in silico methods to predict acute oral toxicity in a regulatory context: results from the European Project ACuteTox.

ACuteTox is a project within the 6th European Framework Programme which had as one of its goals to develop, optimise and prevalidate a non-animal testing strategy for predicting human acute oral toxicity. In its last 6 months, a challenging exercise was conducted to assess the predictive capacity of the developed testing strategies and final identification of the most promising ones. Thirty-two chemicals were tested blind in the battery of in vitro and in silico methods selected during the first phase of the project. This paper describes the classification approaches studied: single step procedures and two step tiered testing strategies. In summary, four in vitro testing strategies were proposed as best performing in terms of predictive capacity with respect to the European acute oral toxicity classification. In addition, a heuristic testing strategy is suggested that combines the prediction results gained from the neutral red uptake assay performed in 3T3 cells, with information on neurotoxicity alerts identified by the primary rat brain aggregates test method. Octanol-water partition coefficients and in silico prediction of intestinal absorption and blood-brain barrier passage are also considered. This approach allows to reduce the number of chemicals wrongly predicted as not classified (LD50>2000 mg/kg b.w.).