Deep eutectic solvents formed with unconventional carbon precursors were used for the preparation of hierarchical carbon monoliths and proved effective for doping the resulting carbons with nitrogen.
}}, author = {{Lopez Salas, Nieves and Gutiérrez, María C. and Ania, Conchi O. and Fierro, José Luís G. and Luisa Ferrer, M. and Monte, Francisco del}}, issn = {{2050-7488}}, journal = {{J. Mater. Chem. A}}, keywords = {{General Materials Science, Renewable Energy, Sustainability and the Environment, General Chemistry}}, number = {{41}}, pages = {{17387--17399}}, publisher = {{Royal Society of Chemistry (RSC)}}, title = {{{Efficient nitrogen-doping and structural control of hierarchical carbons using unconventional precursors in the form of deep eutectic solvents}}}, doi = {{10.1039/c4ta03266g}}, volume = {{2}}, year = {{2014}}, } @article{40592, author = {{Lopez Salas, Nieves and Jardim, E. O. and Silvestre-Albero, A. and Gutiérrez, M. C. and Ferrer, M. L. and Rodríguez-Reinoso, F. and Silvestre-Albero, J. and del Monte, F.}}, issn = {{0743-7463}}, journal = {{Langmuir}}, keywords = {{Electrochemistry, Spectroscopy, Surfaces and Interfaces, Condensed Matter Physics, General Materials Science}}, number = {{41}}, pages = {{12220--12228}}, publisher = {{American Chemical Society (ACS)}}, title = {{{Use of Eutectic Mixtures for Preparation of Monolithic Carbons with CO2-Adsorption and Gas-Separation Capabilities}}}, doi = {{10.1021/la5034146}}, volume = {{30}}, year = {{2014}}, } @article{40593, author = {{Lopez Salas, Nieves and del Monte, Francisco and Tamayo, Aitana and Fierro, José Luís G. and De Lacey, Antonio L. and Ferrer, M. Luisa and Gutiérrez, María C.}}, issn = {{1864-5631}}, journal = {{ChemSusChem}}, keywords = {{General Energy, General Materials Science, General Chemical Engineering, Environmental Chemistry}}, number = {{12}}, pages = {{3347--3355}}, publisher = {{Wiley}}, title = {{{Sulfur-Doped Carbons Prepared from Eutectic Mixtures Containing Hydroxymethylthiophene as Metal-Free Oxygen Reduction Catalysts}}}, doi = {{10.1002/cssc.201402753}}, volume = {{7}}, year = {{2014}}, } @inbook{40631, author = {{Kottmann, Brigitte and Miller, Susanne}}, booktitle = {{Individuelle Förderung und Lernen in der Gemeinschaft }}, editor = {{Kopp, Bärbel and Martschinke, Sabine and Kirschhock, Eva-Maria and Ranger, Gwenda and Renner, Günter and Munser-Kiefer, Maike and Haider, Michael}}, isbn = {{9783658044787}}, pages = {{218--221}}, title = {{{Grundschullehrkräfte im Entscheidungsdilemma zwischen Fördern und Selektieren}}}, year = {{2014}}, } @inbook{40630, author = {{Kottmann, Brigitte}}, booktitle = {{Kompetenz - Bildung. Soziale, emotionale und kommunikative Kompetenzen von Kindern und Jugendlichen }}, editor = {{Rohlfs, Carsten and Harring, Marius and Palentien , Christian}}, pages = {{375--384}}, publisher = {{Verlag für Sozialwissenschaften}}, title = {{{"Schule für alle" - ein Projekt zur Förderung fachlicher und überfachlicher Kompetenzen}}}, year = {{2014}}, } @article{40629, author = {{Kottmann, Brigitte}}, issn = {{0937-7239}}, journal = {{Schulverwaltung Nordrhein-Westfalen}}, number = {{4}}, pages = {{100--101}}, title = {{{Lehrer in zwei Lehrämtern. Plädoyer für einen gestuften Lehramtsstudiengang}}}, volume = {{23}}, year = {{2014}}, } @inproceedings{40766, abstract = {{Amplitude-to-amplitude interactions between neural oscillations are of a special interest as they show how the strength of spatial synchronization in different neuronal populations relates to each other during a given task. While, previously, amplitude-to-amplitude correlations were studied primarily on the sensor level, we present a source separation approach using spatial filters which maximize the correlation between the envelopes of brain oscillations recorded with electro-/magnetencephalography (EEG/MEG) or intracranial multichannel recordings. Our approach, which is called canonical source power correlation analysis (cSPoC), is thereby capable of extracting genuine brain oscillations solely based on their assumed coupling behavior even when the signal-to-noise ratio of the signals is low.}}, author = {{Dähne, S. and Nikulin, V. V. and Ramírez, D. and Schreier, P. J. and Müller, K.-R. and Haufe, S.}}, booktitle = {{Proc. Int. Work. Pattern Recognition In Neuroimaging}}, title = {{{Optimizing spatial filters for the extraction of envelope-coupled neural oscillations}}}, doi = {{10.1109/PRNI.2014.6858514}}, year = {{2014}}, } @article{40775, abstract = {{The separation of a complex mixture based solely on second-order statistics can be achieved using the Strong Uncorrelating Transform (SUT) if and only if all sources have distinct circularity coefficients. However, in most problems we do not know the circularity coefficients, and they must be estimated from observed data. In this work, we propose a detector, based on the generalized likelihood ratio test (GLRT), to test the separability of a complex Gaussian mixture using the SUT. For the separable case (distinct circularity coefficients), the maximum likelihood (ML) estimates are straightforward. On the other hand, for the non-separable case (at least one circularity coefficient has multiplicity greater than one), the ML estimates are much more difficult to obtain. To set the threshold, we exploit Wilks’ theorem, which gives the asymptotic distribution of the GLRT under the null hypothesis. Finally, numerical simulations show the good performance of the proposed detector and the accuracy of Wilks’ approximation.}}, author = {{Ramírez, D. and Schreier, P. J. and Vía, J. and Santamaría, I.}}, journal = {{Signal Process.}}, pages = {{49–57}}, title = {{{Testing blind separability of complex Gaussian mixtures}}}, doi = {{10.1016/j.sigpro.2013.08.010}}, volume = {{95}}, year = {{2014}}, } @article{40771, author = {{Manco-Vásquez, J. and Lázaro-Gredilla, M. and Ramírez, D. and Vía, J. and Santamaría, I.}}, journal = {{Signal Process.}}, pages = {{228–240}}, title = {{{A Bayesian approach for adaptive multiantenna sensing in cognitive radio networks}}}, doi = {{10.1016/j.sigpro.2013.10.005}}, volume = {{96, Part B}}, year = {{2014}}, } @inproceedings{40770, author = {{Stein, Manuel and Lenz, Andreas and Mezghani, Amine and Nossek, Josef A.}}, booktitle = {{Proc.\ IEEE Int.\ Conf.\ Acoustics, Speech and Signal Process.}}, title = {{{Optimum analog receive filters for detection and inference under a sampling rate constraint}}}, year = {{2014}}, } @inproceedings{40772, author = {{Lameiro, Christian and Utschick, Wolfgang and Santamaría, Ignacio}}, booktitle = {{Proc. Int. ITG Work. Smart Antennas}}, title = {{{Spatial Shaping and Precoding Design for Underlay MIMO Interference Channels}}}, year = {{2014}}, } @inproceedings{40773, author = {{Stein, Manuel and Castañeda, Mario and Nossek, Josef A.}}, booktitle = {{Proc.\ ITG Int.\ Work. Smart Ant.}}, title = {{{Information-preserving spatial filtering for direction-of-arrival estimation}}}, year = {{2014}}, } @article{40776, author = {{Schreier, Peter J.}}, journal = {{ForschungsForum Paderborn}}, pages = {{24–30}}, title = {{{Neue Anwendungsgebiete für Computer Assisted Surgery (CAS)}}}, volume = {{17}}, year = {{2014}}, } @inproceedings{40774, author = {{Stein, Manuel and Nossek, Josef A.}}, booktitle = {{Proc. of IEEE/ION PLANS 2014}}, title = {{{Will the 1-bit GNSS receiver prevail?}}}, year = {{2014}}, } @inproceedings{40768, abstract = {{We derive the generalized likelihood ratio test (GLRT) for detecting cyclostationarity in scalar-valued time series. The main idea behind our approach is Gladyshev’s relationship, which states that when the scalar-valued cyclostationary sig- nal is blocked at the known cycle period it produces a vector- valued wide-sense stationary process. This result amounts to saying that the covariance matrix of the vector obtained by stacking all observations of the time series is block-Toeplitz if the signal is cyclostationary, and Toeplitz if the signal is wide- sense stationary. The derivation of the GLRT requires the maximum likelihood estimates of Toeplitz and block-Toeplitz matrices. This can be managed asymptotically (for large num- berofsamples)exploitingSzego ̈’stheoremanditsgeneraliza- tion for vector-valued processes. Simulation results show the good performance of the proposed GLRT.}}, author = {{Ramírez, D. and Scharf, L. L. and Vía, J. and Santamaría, I. and Schreier, P. J.}}, booktitle = {{Proc.\ IEEE Int.\ Conf.\ Acoustics, Speech and Signal Process.}}, title = {{{An asymptotic GLRT for the detection of cyclostationary signals}}}, doi = {{10.1109/ICASSP.2014.6854234}}, year = {{2014}}, } @inproceedings{40767, abstract = {{Successive interference cancellation (SIC) has been extensively applied to estimate transmit signals in communication systems. When the channel state information (CSI) and noise statistics are imperfectly estimated, the standard SIC estimators that ignore the model mismatch may perform poorly. This paper introduces regularized SIC estimation to provide robustness against the model mismatch. Suboptimal, low-complexity implementations using (sorted) QR decomposition and approximate choice of regularization parameters are also introduced. Simulation examples demonstrate that the regularized SIC estimators can significantly outperform the standard version.}}, author = {{Tong, Jun and Guo, Qinghua and Schreier, Peter J. and Xi, Jiangtao}}, booktitle = {{Proc.\ IEEE Work.\ Stat.\ Signal Process.}}, title = {{{Regularized successive interference cancellation (SIC) under mismatched modeling}}}, doi = {{10.1109/SSP.2014.6884642}}, year = {{2014}}, }