@article{63951, abstract = {{The parameters describing the quadrupolar and CSA interactions of 51V solid-state MAS NMR investigations of model complexes mimicking vanadoenzymes as well as vanadium containing catalysts and enzyme complexes are interpreted with respect to the chemical structure. The interpretation is based on the data of 15 vanadium complexes including two new complexes with previously unpublished data and 13 complexes with data previously published by us. Correlations between the chemical structure and the 51V solid-state NMR data of this class of compounds have been established. Especially for the isotropic chemical shift δ iso and the chemical shift anisotropy δ σ , correlations with specific structural features like the coordination number of the vanadium atom, the number of coordinating nitrogens, the number of oxygen atoms and the chemical surrounding of the complex could be established for these compounds. Moreover, quantitative correlations between the solid-state NMR parameters and specific bond angles and bond lengths have been obtained. Our results can be of particular interest for future investigations concerning the structure and the mode of action of related vanadoenzymes and vanadate protein assemblies, including the use of vanadate adducts as transition state analogs for phosphate metabolizing systems.}}, author = {{Fenn, Annika and Wächtler, Maria and Gutmann, Torsten and Breitzke, Hergen and Buchholz, Axel and Lippold, Ines and Plass, Winfried and Buntkowsky, Gerd}}, journal = {{Solid State Nuclear Magnetic Resonance}}, keywords = {{51V NMR, Cis-dioxovanadium (v) complex, Model system, Vanadate}}, number = {{4}}, pages = {{192–201}}, title = {{{Correlations between 51V solid-state NMR parameters and chemical structure of vanadium (V) complexes as models for related metalloproteins and catalysts}}}, doi = {{10.1016/j.ssnmr.2009.11.003}}, volume = {{36}}, year = {{2009}}, } @inproceedings{11939, abstract = {{In this paper a switching linear dynamical model (SLDM) approach for speech feature enhancement is improved by employing more accurate models for the dynamics of speech and noise. The model of the clean speech feature trajectory is improved by augmenting the state vector to capture information derived from the delta features. Further a hidden noise state variable is introduced to obtain a more elaborated model for the noise dynamics. Approximate Bayesian inference in the SLDM is carried out by a bank of extended Kalman filters, whose outputs are combined according to the a posteriori probability of the individual state models. Experimental results on the AURORA2 database show improved recognition accuracy.}}, author = {{Windmann, Stefan and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)}}, keywords = {{a posteriori probability, AURORA2 database, Bayesian inference, Bayes methods, channel bank filters, extended Kalman filter banks, hidden noise state variable, Kalman filters, noise dynamics, speech enhancement, speech feature enhancement, speech feature trajectory, switching linear dynamical model approach}}, pages = {{4409--4412}}, title = {{{Modeling the dynamics of speech and noise for speech feature enhancement in ASR}}}, doi = {{10.1109/ICASSP.2008.4518633}}, year = {{2008}}, } @article{64041, abstract = {{Three cis-dioxovanadium(V) complexes with similar N -salicylidenehydrazide ligands modeling hydrogen bonding interactions of vanadate relevant for vanadium haloperoxidases are studied by 51V solid-state NMR spectroscopy. Their parameters describing the quadrupolar and chemical shift anisotropy interactions (quadrupolar coupling constant C Q , asymmetry of the quadrupolar tensor η Q , isotropic chemical shift δ iso , chemical shift anisotropy δ σ , asymmetry of the chemical shift tensor η σ and the Euler angles α , β and γ ) are determined both experimentally and theoretically using DFT methods. A comparative study of different methods to determine the NMR parameters by numerical simulation of the spectra is presented. Detailed theoretical investigations on the DFT level using various basis sets and structural models show that by useful choice of the methodology, the calculated parameters agree to the experimental ones in a very good manner.}}, author = {{Schweitzer, Annika and Gutmann, Torsten and Wächtler, Maria and Breitzke, Hergen and Buchholz, Axel and Plass, Winfried and Buntkowsky, Gerd}}, journal = {{Solid State Nuclear Magnetic Resonance}}, keywords = {{51V NMR, Model system, Ab initio calculation, Cis-dioxovanadium(V) complex, Haloperoxidase, Numerical optimization, Quadrupolar interaction}}, number = {{1–2}}, pages = {{52–67}}, title = {{{51V solid-state NMR investigations and DFT studies of model compounds for vanadium haloperoxidases}}}, doi = {{10.1016/j.ssnmr.2008.02.003}}, volume = {{34}}, year = {{2008}}, } @inproceedings{11943, abstract = {{A marginalized particle filter is proposed for performing single channel speech enhancement with a non-linear dynamic state model. The system consists of a particle filter for tracking line spectral pair (LSP) parameters and a Kalman filter per particle for speech enhancement. The state model for the LSPs has been learnt on clean speech training data. In our approach parameters and speech samples are processed at different time scales by assuming the parameters to be constant for small blocks of data. Further enhancement is obtained by an iteration which can be applied on these small blocks. The experiments show that similar SNR gains are obtained as with the Kalman-LM-iterative algorithm. However better values of the noise level and the log-spectral distance are achieved}}, author = {{Windmann, Stefan and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)}}, keywords = {{clean speech training data, iterative methods, iterative speech enhancement, Kalman filter, Kalman filters, Kalman-LM-iterative algorithm, line spectral pair parameters, log-spectral distance, marginalized particle filter, noise level, nonlinear dynamic state speech model, particle filtering (numerical methods), single channel speech enhancement, SNR gains, speech enhancement, speech samples}}, pages = {{I}}, title = {{{Iterative Speech Enhancement using a Non-Linear Dynamic State Model of Speech and its Parameters}}}, doi = {{10.1109/ICASSP.2006.1660058}}, volume = {{1}}, year = {{2006}}, } @inproceedings{39352, abstract = {{The recently adopted OCL 2.0 specification comes with a formal semantics that is based on set theory with a notion of an object model and system states. System states keep the runtime information relevant for the evaluation of OCL expressions. However, not all new language concepts of OCL 2.0 are already addressed in that formal semantics. We show how to overcome this by introducing new components to the object model and system states defining a dynamic semantics of OCL. In order to give precise rules that determine when the current system state has to be updated according to a change in the referred UML model, we make use of adequate mathematical means, namely Abstract State Machines (ASMs). Though our ASM specification also gives a clear definition for the evaluation of OCL constraints, it leaves sufficient flexibility for application specific implementations that have to determine when constraints are to be checked.}}, author = {{Flake, Stephan and Müller, Wolfgang}}, booktitle = {{Proceedings of the UML 2004}}, keywords = {{System State Formal Semantic Object Management Group Denotational Semantic Dynamic Semantic}}, title = {{{An ASM Definition of the Dynamic OCL 2.0 Semantics}}}, doi = {{10.1007/978-3-540-30187-5_17}}, year = {{2004}}, }