Dialgebra cohomology as a G-algebra

It is well known that the Hochschild cohomology of an associative algebra admits a G-algebra structure. In this paper we show that the dialgebra cohomology of an associative dialgebra has a similar structure, which is induced from a homotopy G-algebra structure on the dialgebra cochain complex .

     

Minmax robustness for multi-objective optimization problems

In real-world applications of optimization, optimal solutions are often of limited value, because disturbances of or changes to input data may diminish the quality of an optimal solution or even render it infeasible. One way to deal with uncertain input data is robust optimization, the aim of which is to find solutions which remain feasible and of good quality for all possible scenarios, i.e., realizations of the uncertain data. For single objective optimization, several definitions of robustness have been thoroughly analyzed and robust optimization methods have been developed. In this paper, we extend the concept of minmax robustness (Ben-Tal, Ghaoui, & Nemirovski, 2009) to multi-objective optimization and call this extension robust efficiency for uncertain multi-objective optimization problems. We use ingredients from robust (single objective) and (deterministic) multi-objective optimization to gain insight into the new area of robust multi-objective optimization. We analyze the new concept and discuss how robust solutions of multi-objective optimization problems may be computed. To this end, we use techniques from both robust (single objective) and (deterministic) multi-objective optimization. The new concepts are illustrated with some linear and quadratic programming instances.     

Absolute and relative cut-off in adaptive approximation by wavelets

Given the wavelet expansion of a function v, a non-linear adaptive approximation of v is obtained by neglecting those coefficients whose size drops below a certain threshold. We propose several ways to define the threshold: all are based on the characterization of the local regularity of v (in a Sobolev or Besov scale) in terms of summability of properly defined subsets of its coefficients. A-priori estimates of the approximation error are derived. For the Haar system the asymptotic behavior of both the approximation error and the number of survived coefficients is thoroughly investigated for a class of functions having Hölder-type singularities.     

Predicting thermal displacements in modular tool systems

In the last decade, there has been an increasing interest in compensating thermally induced errors to improve the manufacturing accuracy of modular tool systems. These modular tool systems are interfaces between spindle and workpiece and consist of several complicatedly formed parts. Their thermal behavior is dominated by nonlinearities, delay and hysteresis effects even in tools with simpler geometry and it is difficult to describe it theoretically. Due to the dominant nonlinear nature of this behavior the so far used linear regression between the temperatures and the displacements is insufficient. Therefore, in this study we test the hypothesis whether we can reliably predict such thermal displacements via nonlinear temperature-displacement regression functions. These functions are estimated first from learning measurements using the alternating conditional expectation (ACE) algorithm and then tested on independent data sets. First, we analyze data that were generated by a finite element spindle model. We find that our approach is a powerful tool to describe the relation between temperatures and displacements for simulated data. Next, we analyze the temperature-displacement relationship in a silent real experimental setup, where the tool system is thermally forced. Again, the ACE algorithm is powerful to estimate the deformation with high precision. The corresponding errors obtained by using the nonlinear regression approach are 10-fold lower in comparison to multiple linear regression analysis. Finally, we investigate the thermal behavior of a modular tool system in a working milling machine and again get promising results. The thermally induced errors can be estimated with 1-2 microm accuracy using this nonlinear regression analysis. Therefore, this approach seems to be very useful for the development of new modular tool systems.     

Carbonates,thiocarbonates, and the corresponding monoalkyl derivatives: III. The 13C chemical shift tensors in potassium carbonate,bicarbonate and related monomethyl derivatives

The principal values of the 13C chemical shift tensors in potassium carbonate (K2CO3), trithiocarbonate (K2CS3), bicarbonate (KHCO3), methylcarbonate (KO2COCH3), S-methyl-monothiocarbonate (KO2CSCH3), O-methyl-monothiocarbonate (KOSCOCH3), S-methyl-dithiocarbonate (KOSCSCH3), and O-methyl-dithiocarbonate (KS2COCH3), were measured in solid-state nuclear magnetic resonance experiments. Chemical shift tensor calculations on the corresponding isolated anions were used to assign the chemical shift tensor orientations in the molecular frames of all anions. The correlation between experimental and calculated principal values improves significantly when the calculations are performed on isolated anions with proton-optimized X-ray geometries rather than on isolated anions with fully optimized geometries. Further considerable improvement in the correlation is achieved by utilizing the embedded ion method, which was recently developed to include electrostatic crystal potentials in chemical shift tensor calculations on ionic compounds. Similarities and differences in the chemical shift tensor orientations and principal values of the trigonal sp2 carbon atoms in the carbonate and thiocarbonate anions are compared with those known for condensed polyaromatic hydrocarbons.