Technology Shock and Employment: Do We Really Need DSGE Models with a Fall in Hours?

The recent empirical literature that uses Structural Vector Autoregressions (SVAR) has shown that productivity shocks identified using long--run restrictions lead to a persistent and significant decline in hours worked. This evidence calls into question standard RBC models in which a positive technology shock leads to a rise in hours. In this paper, we estimate and test a standard RBC model using Indirect Inference on impulse responses of hours worked after technology and non-technology shocks. We find that this model is not rejected by the data and is able to produce impulse responses in SVAR from simulated data similar to impulse responses in SVAR from actual data. Moreover, technology shocks represent the main contribution to the variance of the business cycle component of output under the estimated DSGE model. Our results suggest that we do not necessarily need DSGE models with a fall in hours to reproduce the results deriving from SVAR models.SVARs ; Long--Run Restrictions ; RBC models ; Indirect Inference

Logarithmic mathematical morphology: a new framework adaptive to illumination changes

A new set of mathematical morphology (MM) operators adaptive to illumination changes caused by variation of exposure time or light intensity is defined thanks to the Logarithmic Image Processing (LIP) model. This model based on the physics of acquisition is consistent with human vision. The fundamental operators, the logarithmic-dilation and the logarithmic-erosion, are defined with the LIP-addition of a structuring function. The combination of these two adjunct operators gives morphological filters, namely the logarithmic-opening and closing, useful for pattern recognition. The mathematical relation existing between ``classical'' dilation and erosion and their logarithmic-versions is established facilitating their implementation. Results on simulated and real images show that logarithmic-MM is more efficient on low-contrasted information than ``classical'' MM

Spinoza

"Spinoza", second edition. Encyclopedia entry for the Springer Encyclopedia of EM Phil and the Sciences, ed. D. Jalobeanu and C. T. Wolfe

The A+B -> 0 annihilation reaction in a quenched random velocity field

Using field-theoretic renormalization group methods the long-time behaviour of the A+B -> 0 annihilation reaction with equal initial densities n_A(0) = n_B(0) = n_0 in a quenched random velocity field is studied. At every point (x, y) of a d-dimensional system the velocity v is parallel or antiparallel to the x-axis and depends on the coordinates perpendicular to the flow. Assuming that v(y) have zero mean and short-range correlations in the y-direction we show that the densities decay asymptotically as n(t) ~ A n_0^(1/2) t^(-(d+3)/8) for d<3. The universal amplitude A is calculated at first order in \epsilon = 3-d.Comment: 19 pages, LaTeX using IOP-macros, 5 eps-figures. It is shown that the amplitude of the density is universal, i.e. independent of the reaction rat

Reconstruction of three-dimensional porous media using generative adversarial neural networks

To evaluate the variability of multi-phase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a novel method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image datasets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that GANs can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.Comment: 21 pages, 20 figure

Density of States for a Specified Correlation Function and the Energy Landscape

The degeneracy of two-phase disordered microstructures consistent with a specified correlation function is analyzed by mapping it to a ground-state degeneracy. We determine for the first time the associated density of states via a Monte Carlo algorithm. Our results are described in terms of the roughness of the energy landscape, defined on a hypercubic configuration space. The use of a Hamming distance in this space enables us to define a roughness metric, which is calculated from the correlation function alone and related quantitatively to the structural degeneracy. This relation is validated for a wide variety of disordered systems.Comment: Accepted for publication in Physical Review Letter

Influence of the amount of fine particles on rheological properties of uranium dioxide powders

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Invisibility in billiards

The question of invisibility for bodies with mirror surface is studied in the framework of geometrical optics. We construct bodies that are invisible/have zero resistance in two mutually orthogonal directions, and prove that there do not exist bodies which are invisible/have zero resistance in all possible directions of incidence

Induced vertical disparity effects on local and global stereopsis

Purpose: Although significant amounts of vertical misalignment could have a noticeable effect on visual performance, there is no conclusive evidence about the effect of very small amount of vertical disparity on stereopsis and binocular vision. Hence, the aim of this study was to investigate the effects of induced vertical disparity on local and global stereopsis at near. Materials and Methods: Ninety participants wearing best-corrected refraction had local and global stereopsis tested with 0.5 and 1.0 prism diopter (Δ) vertical prism in front of their dominant and non-dominant eye in turn. This was compared to local and global stereopsis in the same subjects without vertical prism. Data were analyzed in SPSS.17 software using the independent samples T and the repeated measures ANOVA tests. Results: Induced vertical disparity decreases local and global stereopsis. This reduction is greater when vertical disparity is induced in front of the non-dominant eye and affects global more than local stereopsis. Repeated measures ANOVA showed differences in the mean stereopsis between the different measured states for local and global values. Local stereopsis thresholds were reduced by 10s of arc or less on average with 1.0Δ of induced vertical prism in front of either eye. However, global stereopsis thresholds were reduced by over 100s of arc by the same 1.0Δ of induced vertical prism. Conclusion: Induced vertical disparity affects global stereopsis thresholds by an order of magnitude (or a factor of 10) more than local stereopsis. Hence, using a test that measures global stereopsis such as the TNO is more sensitive to vertical misalignment than a test such as the Stereofly that measures local stereopsis. © 2014 Informa Healthcare USA, Inc. All rights reserved: reproduction in whole or part not permitted