University of Stuttgart

About: University of Stuttgart is a education organization based out in Stuttgart, Germany. It is known for research contribution in the topics: Laser & Finite element method. The organization has 27715 authors who have published 56370 publications receiving 1363382 citations. The organization is also known as: Universität Stuttgart.

Globalization and labor market outcomes: Wage bargaining, search frictions, and firm heterogeneity

Abstract: We introduce search unemployment a la Pissarides into Melitz’ (2003) model of trade with heterogeneous firms. We allow wages to be individually or collectively bargained and analytically solve for the equilibrium. We find that the selection effect of trade influences labor market outcomes. Trade liberalization lowers unemployment and raises real wages as long as it improves aggregate productivity net of transport costs. We show that this condition is likely to be met by a reduction in variable trade costs or the entry of new trading countries. On the other hand, the gains from a reduction in fixed market access costs are more elusive. Calibrating the model shows that the positive impact of trade openness on employment is significant when wages are bargained at the individual level but much smaller when wages are bargained at the collective level.

Extrapolating MP2 and CCSD explicitly correlated correlation energies to the complete basis set limit with first and second row correlation consistent basis sets

Abstract: Accurate extrapolation to the complete basis set (CBS) limit of valence correlation energies calculated with explicitly correlated MP2-F12 and CCSD(T)-F12b methods have been investigated using a Schwenke-style approach for molecules containing both first and second row atoms. Extrapolation coefficients that are optimal for molecular systems containing first row elements differ from those optimized for second row analogs, hence values optimized for a combined set of first and second row systems are also presented. The new coefficients are shown to produce excellent results in both Schwenke-style and equivalent power-law-based two-point CBS extrapolations, with the MP2-F12/cc-pV(D,T)Z-F12 extrapolations producing an average error of just 0.17 mE(h) with a maximum error of 0.49 for a collection of 23 small molecules. The use of larger basis sets, i.e., cc-pV(T,Q)Z-F12 and aug-cc-pV(Q,5)Z, in extrapolations of the MP2-F12 correlation energy leads to average errors that are smaller than the degree of confidence in the reference data (approximately 0.1 mE(h)). The latter were obtained through use of very large basis sets in MP2-F12 calculations on small molecules containing both first and second row elements. CBS limits obtained from optimized coefficients for conventional MP2 are only comparable to the accuracy of the MP2-F12/cc-pV(D,T)Z-F12 extrapolation when the aug-cc-pV(5+d)Z and aug-cc-pV(6+d)Z basis sets are used. The CCSD(T)-F12b correlation energy is extrapolated as two distinct parts: CCSD-F12b and (T). While the CCSD-F12b extrapolations with smaller basis sets are statistically less accurate than those of the MP2-F12 correlation energies, this is presumably due to the slower basis set convergence of the CCSD-F12b method compared to MP2-F12. The use of larger basis sets in the CCSD-F12b extrapolations produces correlation energies with accuracies exceeding the confidence in the reference data (also obtained in large basis set F12 calculations). It is demonstrated that the use of the 3C(D) Ansatz is preferred for MP2-F12 CBS extrapolations. Optimal values of the geminal Slater exponent are presented for the diagonal, fixed amplitude Ansatz in MP2-F12 calculations, and these are also recommended for CCSD-F12b calculations.

A review of the influence of freeze-thaw cycles on soil geotechnical properties

Abstract: Freeze-thaw cycling affects the geotechnical properties of soils and must be taken into account when selecting soil parameters for stability and deformation analysis of slopes, embankments and cuts in cold regions, especially those underlain by permafrost. This review examines methods of investigation, testing techniques and the impact of freeze-thaw processes on the physical and mechanical properties of soils. Copyright © 2006 John Wiley & Sons, Ltd.

Expression of Macrophage Migration Inhibitory Factor in Different Stages of Human Atherosclerosis

Abstract: Background - Atherosclerosis is a chronic inflammatory response of the arterial wall to injury. Macrophage migration inhibitory factor (MIF), a cytokine with potent inflammatory functions, was thus considered to be important in atherosclerotic lesion evolution. Methods and Results - We studied the presence and distribution of MIF immunoreactivity (MIF-IR) and MIF mRNA in internal mammary arteries with a normal histology and arteries with plaques in different stages of human atherosclerosis. To address a potential role for the coactivator Jab1 as a cellular mediator of MIF effects in vascular tissue, we correlated the expression of MIF to that of Jab1 by using immunohistochemistry and coimmunoprecipitation. We further sought to determine a potential functional role for endothelium-derived MIF in early atherogenesis by studying the effects of oxidized LDL on MIF expression in cultured human umbilical vascular endothelial cells. The results showed that MIF-IR and Jab1-IR are found in all cell types present in atherosclerotic lesions, that MIF-IR is upregulated during progression of atherosclerosis, that MIF is produced locally in the arterial wall, and that all MIF+ cells are simultaneously Jab1 +. Coimmunoprecipitation experiments demonstrated in vivo complex formation between MIF and Jab1 in plaques. MIF expression in human umbilical vascular endothelial cells and a macrophage line was upregulated after stimulation with oxidized LDL. Conclusions - MIF is produced abundantly by various cells in all types of human atherosclerotic lesions and thus may play an important role in early plaque development and advanced complicated lesions. MIF-Jab1 complexes could serve critical regulatory functions in atherosclerotic lesion evolution. Chemicals/CAS: COPS5 protein, human, EC 3.4.-.-; DNA-Binding Proteins; Intracellular Signaling Peptides and Proteins; Lipoproteins, LDL; Macrophage Migration-Inhibitory Factors; oxidized low density lipoprotein; Peptide Hydrolases, EC 3.4.-; Transcription Factors

On Deep Learning-Based Channel Decoding

Abstract: We revisit the idea of using deep neural networks for one-shot decoding of random and structured codes, such as polar codes. Although it is possible to achieve maximum a posteriori (MAP) bit error rate (BER) performance for both code families and for short codeword lengths, we observe that (i) structured codes are easier to learn and (ii) the neural network is able to generalize to codewords that it has never seen during training for structured, but not for random codes. These results provide some evidence that neural networks can learn a form of decoding algorithm, rather than only a simple classifier. We introduce the metric normalized validation error (NVE) in order to further investigate the potential and limitations of deep learning-based decoding with respect to performance and complexity.