Religious attitudes and home bias: theory and evidence from a pilot study

This paper examines the relationship between religion and home bias. We propose a simple theoretical framework that suggests that countries interacting via their representative individuals might show a certain degree of religion-driven international altruism that in turn affects trade. We test these predictions exploiting data from a survey on religious attitudes and individuals' preferences over consumption of home-produced versus foreign goods that we designed and carried out in 15 different countries. We find evidence that religious openness and home bias are negatively correlated. This appears to provide some support to the hypothesis that religious openness, through trust and altruism, may have a pro-trade effect.

NODDI-SH: a computational efficient NODDI extension for fODF estimation in diffusion MRI

Diffusion Magnetic Resonance Imaging (DMRI) is the only non-invasive imaging technique which is able to detect the principal directions of water diffusion as well as neurites density in the human brain. Exploiting the ability of Spherical Harmonics (SH) to model spherical functions, we propose a new reconstruction model for DMRI data which is able to estimate both the fiber Orientation Distribution Function (fODF) and the relative volume fractions of the neurites in each voxel, which is robust to multiple fiber crossings. We consider a Neurite Orientation Dispersion and Density Imaging (NODDI) inspired single fiber diffusion signal to be derived from three compartments: intracellular, extracellular, and cerebrospinal fluid. The model, called NODDI-SH, is derived by convolving the single fiber response with the fODF in each voxel. NODDI-SH embeds the calculation of the fODF and the neurite density in a unified mathematical model providing efficient, robust and accurate results. Results were validated on simulated data and tested on \textit{in-vivo} data of human brain, and compared to and Constrained Spherical Deconvolution (CSD) for benchmarking. Results revealed competitive performance in all respects and inherent adaptivity to local microstructure, while sensibly reducing the computational cost. We also investigated NODDI-SH performance when only a limited number of samples are available for the fitting, demonstrating that 60 samples are enough to obtain reliable results. The fast computational time and the low number of signal samples required, make NODDI-SH feasible for clinical application

The relationship between forgone health care and high school dropout:evidence from US adolescents

High school dropout is an important policy issue and its determinants are a longstanding interest of economics. However, very little is known on the roles of noncognitive traits in influencing school dropout decisions. We employ voluntary forgone health care as a proxy for the underlying noncognitive traits that may induce adolescents to dropout and estimate its effects on early school attrition. We exploit data from the US National Longitudinal Study of Adolescent to Adult Health (Add Health) and employ a series of flexible specifications with school fixed effects and cohort effects. Our models account for well-established determinants of dropout, including individual and parental characteristics, together with personality traits. Forgone health care consistently appears to be a statistically significant and substantial predictor of dropout among adolescents. We suggest that forgone health care could be used as a signaling device for policy makers targeting potential high school dropouts

Absolute determination of D_s branching ratios and f_{D_s} extraction at a neutrino factory

A method for a direct measurement of the exclusive D_s branching ratios and of the decay constant f_{D_s} with a systematical error better than 5% is presented. The approach is based on the peculiar vertex topology of the anti-neutrino induced diffractive charm events. The statistical accuracy achievable with a neutrino factory is estimated

The effects of non-adherence on health care utilisation:panel data evidence on uncontrolled diabetes

Despite size and relevance of non-adherence to health treatments, robust evidence on its effects on health care utilisation is very limited. We focus on non-adherence to diabetes treatments, a widespread problem, and employ longitudinal administrative data from Spain (2004-2010) to identify and quantify the effects of uncontrolled type 2 diabetes on health care utilisation. We use a biomarker (glycated haemoglobin, HbA1c) to detect the presence of uncontrolled diabetes and explore its effects on both primary and secondary health care. We estimate a range of panel count data models, including negative binomials with random effects, dynamic and hurdle specifications to account for unobserved heterogeneity, previous utilisation and selection. We find uncontrolled diabetes in around 30% of patients of both genders. Although women appear to systematically consume more health care compared to men, their consumption levels do not appear to be influenced by uncontrolled diabetes. Conversely, among men uncontrolled diabetes increases the average number of GP visits per year by around 4%, specialist visits by 4.4% and greatly extends hospital length of stay

Three-flavor analysis of long-baseline experiments

We compare the analysis of existing and future neutrino oscillation long-baseline experiments, where we point out that the analysis of future experiments actually implies a 12-dimensional parameter space. Within the three-flavor neutrino oscillation framework, six of these parameters are the fit parameters, and six are the simulated parameters. This high-dimensional parameter space requires the condensation of information and the definition of performance indicators for the purpose needed. As the most sophisticated example for such an indicator, we choose the precision of the leptonic CP phase, and discuss some of the complications of its computation and interpretation.Comment: Talk given at the 6th International Workshop on Neutrino Factories & Superbeams, July 26-Aug 1, 2004, Osaka, Japan. 3 page

Evaluation of the first automated thyroglobulin assay

The aim of this study was to investigate technical and analytical performance of the first automated thyroglobulin (Tg) assay (DPC-Immulite(R); Diagnostic Products Corporation, Los Angeles, USA). In imprecision studies using several human serum pools ranging from 21 to 58 replicates, a coefficient of variation of 9.0 % was obtained at a mean Tg concentration of 0.84 ng/ml and of 6.1 % at a Tg concentration of 62.1 ng/ml. In a method comparison with a non-automated assay (BRAHMS LUMItest Tg(R), BRAHMS, Berlin, Germany) using 383 sera of 303 patients with thyroid carcinoma, regression analysis according to Passing and Bablock yielded in the following equation: Immulite Tg=1.6 x BRAHMS Tg - 0.1 ng/ml (Pearson's r=0.979). Sera obtained from 59 patients with thyroid carcinoma enabled comparative follow-up studies; in all cases qualitative agreement was found with regard to increase or decrease of serum Tg; in eight cases, however, Tg was detected with the Immulite assay but not with the BRAHMS assay. Further follow-up proved the presence of thyroid tissue in these patients. From these and further methodological data (dilution linearity, interference studies, carry-over study, high-dose hook properties, and short report time) it is concluded that the DPC-Immulite Tg assay meets the requirements of routine diagnostic use