A spatial panel data version of the knowledge capital model

This paper attempts to analyze the impact of knowledge and knowledge spillovers on regional total factor productivity (TFP) in Europe. Regional patent stocks are used as a proxy for knowledge, and TFP is measured in terms of a superlative index. We follow Fischer et. al (2008) by using a spatial-spillover model and a data set covering 203 regions for six time periods. In order to estimate the impact of knowledge stocks we use a spatial autoregressive model with random effects, which allows for three kinds of spatial dependence: Spatial correlation in the innovations, the exogenous and the endogenous variables. The results suggest that there is a significant positive impact of knowledge on regional TFP levels, and that knowledge spills over to neighboring regions. These spillovers decay exponentially with distance at a rate of 8%. Using Monte Carlo simulations we calculate the distribution of direct and indirect effects. The average elasticity of a region's TFP with respect to its own knowledge stock is 0.2 and highly significant. The average effect of all other regions' TFP is about 50% higher, which confirms that the cross-country externalities are important in the measuring of the impact.

Consumer willingness to pay for traditional food products

Reflecting the growing interest from both consumers and policymakers, and building on recent developments in Willingness to Pay (WTP) methodologies, we evaluate consumer preferences for an archetypal traditional food product. Specifically we draw on stated preference data from a discrete choice experiment, considering the traditional Hungarian mangalitza salami. A WTP space specification of the generalized multinomial logit model is employed, which accounts for not only heterogeneity in preferences but also differences in the scale of the idiosyncratic error term. Results indicate that traditional food products can command a substantial premium, albeit contingent on effective quality certification, authentic product composition and effective choice of retail outlet. Promising consumer segments and policy implications are identified. (authors' abstract

Corneal viscoelastic properties from finite-element analysis of in vivo air-puff deformation

Biomechanical properties are an excellent health marker of biological tissues, however they are challenging to be measured in-vivo. Non-invasive approaches to assess tissue biomechanics have been suggested, but there is a clear need for more accurate techniques for diagnosis, surgical guidance and treatment evaluation. Recently air-puff systems have been developed to study the dynamic tissue response, nevertheless the experimental geometrical observations lack from an analysis that addresses specifically the inherent dynamic properties. In this study a viscoelastic finite element model was built that predicts the experimental corneal deformation response to an air-puff for different conditions. A sensitivity analysis reveals significant contributions to corneal deformation of intraocular pressure and corneal thickness, besides corneal biomechanical properties. The results show the capability of dynamic imaging to reveal inherent biomechanical properties in vivo. Estimates of corneal biomechanical parameters will contribute to the basic understanding of corneal structure, shape and integrity and increase the predictability of corneal surgery. © 2014 Kling et al.Spanish Government FIS2011-25637, European Research Council ERC-2011 AdG-294099 to SM. FPI-BES-2009-024560 Pre-doctoral Fellowship to SK.Peer Reviewe

Geometrical parameters of deformed corneas and the corresponding mesh size.

<p>Geometrical parameters of deformed corneas and the corresponding mesh size.</p

Temporal (a, c) and spatial (c, d) corneal deformation with air-puff.

<p>Dotted lines represent experimental corneal deformations and continuous lines simulated corneal deformations Panels (a, b) show data for porcine corneas: simulated and experimental data at different IOPs. Panels (c, d) show data for human corneas: simulated response with and without ocular muscle damping, compared to in vivo experimental deformations measured in patients and ex vivo deformations measured in an enucleated whole globe.</p

Spatial pressure distribution of the air-puff along the corneal surface for different deformed shapes.

<p>Spatial pressure distribution of the air-puff along the corneal surface for different deformed shapes.</p

Geometrical parameters of deformed corneas and the corresponding mesh size.

<p>Geometrical parameters of deformed corneas and the corresponding mesh size.</p

Schematic illustration of the simulation procedure.

<p>(a) Corneal geometrical data from Scheimpflug images are used to define the model geometry. Inverse modeling is performed to account for the effect of applying the IOP. (b) The temporal pressure profile measured experimentally and the spatial pressure profile obtained from CFD (Computation Fluid Dynamics) simulation are applied to the cornea as a function of time, location and current deformed shape. (c) The finite element model is solved for the current parameter set and simulation results are compared to the experimentally measured deformation. A step-wise optimization approach is used to find the parameter set that leads to the most similar deformation.</p

Effect of the change of different biomechanical parameters on the spatial deformation profiles (upper row) and temporal deformation profiles (lower row) at IOP = 15 mmHg.

<p>(a) Elastic properties dominate the maximal indentation depth. (b) Viscoelastic properties dominate the amount of hysteresis when the air-pressure has decreased to zero. (c) The ratio between anterior and posterior stiffness dominates the distance between corneal apex and bending points.</p

Air-puff characterization.

<p>(a) Experimentally measured temporal air-puff profile; (b) Results from CFD simulation showing the air-puff as a function of apex indentation and location along the cornea (horizontal distance from the apex).</p