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2006


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ARTS: Accurate Recognition of Transcription Starts in Human

Sonnenburg, S., Zien, A., Rätsch, G.

Bioinformatics, 22(14):e472-e480, July 2006 (article)

Abstract
Motivation: One of the most important features of genomic DNA are the protein-coding genes. While it is of great value to identify those genes and the encoded proteins, it is also crucial to understand how their transcription is regulated. To this end one has to identify the corresponding promoters and the contained transcription factor binding sites. TSS finders can be used to locate potential promoters. They may also be used in combination with other signal and content detectors to resolve entire gene structures. Results: We have developed a novel kernel based method - called ARTS - that accurately recognizes transcription start sites in human. The application of otherwise too computationally expensive Support Vector Machines was made possible due to the use of efficient training and evaluation techniques using suffix tries. In a carefully designed experimental study, we compare our TSS finder to state-of-the-art methods from the literature: McPromoter, Eponine and FirstEF. For given false positive rates within a reasonable range, we consistently achieve considerably higher true positive rates. For instance, ARTS finds about 24% true positives at a false positive rate of 1/1000, where the other methods find less than half (10.5%). Availability: Datasets, model selection results, whole genome predictions, and additional experimental results are available at http://www.fml.tuebingen.mpg.de/raetsch/projects/arts

ei

Web DOI [BibTex]

2006


Web DOI [BibTex]


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Large Scale Multiple Kernel Learning

Sonnenburg, S., Rätsch, G., Schäfer, C., Schölkopf, B.

Journal of Machine Learning Research, 7, pages: 1531-1565, July 2006 (article)

Abstract
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic combinations of kernel matrices for classification, leading to a convex quadratically constrained quadratic program. We show that it can be rewritten as a semi-infinite linear program that can be efficiently solved by recycling the standard SVM implementations. Moreover, we generalize the formulation and our method to a larger class of problems, including regression and one-class classification. Experimental results show that the proposed algorithm works for hundred thousands of examples or hundreds of kernels to be combined, and helps for automatic model selection, improving the interpretability of the learning result. In a second part we discuss general speed up mechanism for SVMs, especially when used with sparse feature maps as appear for string kernels, allowing us to train a string kernel SVM on a 10 million real-world splice data set from computational biology. We integrated multiple kernel learning in our machine learning toolbox SHOGUN for which the source code is publicly available at http://www.fml.tuebingen.mpg.de/raetsch/projects/shogun.

ei

PDF [BibTex]

PDF [BibTex]


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Factorial coding of natural images: how effective are linear models in removing higher-order dependencies?

Bethge, M.

Journal of the Optical Society of America A, 23(6):1253-1268, June 2006 (article)

Abstract
The performance of unsupervised learning models for natural images is evaluated quantitatively by means of information theory. We estimate the gain in statistical independence (the multi-information reduction) achieved with independent component analysis (ICA), principal component analysis (PCA), zero-phase whitening, and predictive coding. Predictive coding is translated into the transform coding framework, where it can be characterized by the constraint of a triangular filter matrix. A randomly sampled whitening basis and the Haar wavelet are included into the comparison as well. The comparison of all these methods is carried out for different patch sizes, ranging from 2x2 to 16x16 pixels. In spite of large differences in the shape of the basis functions, we find only small differences in the multi-information between all decorrelation transforms (5% or less) for all patch sizes. Among the second-order methods, PCA is optimal for small patch sizes and predictive coding performs best for large patch sizes. The extra gain achieved with ICA is always less than 2%. In conclusion, the `edge filters‘ found with ICA lead only to a surprisingly small improvement in terms of its actual objective.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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MCMC inference in (Conditionally) Conjugate Dirichlet Process Gaussian Mixture Models

Rasmussen, C., Görür, D.

ICML Workshop on Learning with Nonparametric Bayesian Methods, June 2006 (talk)

Abstract
We compare the predictive accuracy of the Dirichlet Process Gaussian mixture models using conjugate and conditionally conjugate priors and show that better density models result from using the wider class of priors. We explore several MCMC schemes exploiting conditional conjugacy and show their computational merits on several multidimensional density estimation problems.

ei

Web [BibTex]

Web [BibTex]


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Sampling for non-conjugate infinite latent feature models

Görür, D., Rasmussen, C.

(Editors: Bernardo, J. M.), 8th Valencia International Meeting on Bayesian Statistics (ISBA), June 2006 (talk)

Abstract
Latent variable models are powerful tools to model the underlying structure in data. Infinite latent variable models can be defined using Bayesian nonparametrics. Dirichlet process (DP) models constitute an example of infinite latent class models in which each object is assumed to belong to one of the, mutually exclusive, infinitely many classes. Recently, the Indian buffet process (IBP) has been defined as an extension of the DP. IBP is a distribution over sparse binary matrices with infinitely many columns which can be used as a distribution for non-exclusive features. Inference using Markov chain Monte Carlo (MCMC) in conjugate IBP models has been previously described, however requiring conjugacy restricts the use of IBP. We describe an MCMC algorithm for non-conjugate IBP models. Modelling the choice behaviour is an important topic in psychology, economics and related fields. Elimination by Aspects (EBA) is a choice model that assumes each alternative has latent features with associated weights that lead to the observed choice outcomes. We formulate a non-parametric version of EBA by using IBP as the prior over the latent binary features. We infer the features of objects that lead to the choice data by using our sampling scheme for inference.

ei

PDF [BibTex]

PDF [BibTex]


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Classifying EEG and ECoG Signals without Subject Training for Fast BCI Implementation: Comparison of Non-Paralysed and Completely Paralysed Subjects

Hill, N., Lal, T., Schröder, M., Hinterberger, T., Wilhelm, B., Nijboer, F., Mochty, U., Widman, G., Elger, C., Schölkopf, B., Kübler, A., Birbaumer, N.

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 14(2):183-186, June 2006 (article)

Abstract
We summarize results from a series of related studies that aim to develop a motor-imagery-based brain-computer interface using a single recording session of EEG or ECoG signals for each subject. We apply the same experimental and analytical methods to 11 non-paralysed subjects (8 EEG, 3 ECoG), and to 5 paralysed subjects (4 EEG, 1 ECoG) who had been unable to communicate for some time. While it was relatively easy to obtain classifiable signals quickly from most of the non-paralysed subjects, it proved impossible to classify the signals obtained from the paralysed patients by the same methods. This highlights the fact that though certain BCI paradigms may work well with healthy subjects, this does not necessarily indicate success with the target user group. We outline possible reasons for this failure to transfer.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]


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SCARNA: Fast and Accurate Structural Alignment of RNA Sequences by Matching Fixed-Length Stem Fragments

Tabei, Y., Tsuda, K., Kin, T., Asai, K.

Bioinformatics, 22(14):1723-1729, May 2006 (article)

Abstract
The functions of non-coding RNAs are strongly related to their secondary structures, but it is known that a secondary structure prediction of a single sequence is not reliable. Therefore, we have to collect similar RNA sequences with a common secondary structure for the analyses of a new non-coding RNA without knowing the exact secondary structure itself. Therefore, the sequence comparison in searching similar RNAs should consider not only their sequence similarities but their potential secondary structures. Sankoff‘s algorithm predicts the common secondary structures of the sequences, but it is computationally too expensive to apply to large-scale analyses. Because we often want to compare a large number of cDNA sequences or to search similar RNAs in the whole genome sequences, much faster algorithms are required. We propose a new method of comparing RNA sequences based on the structural alignments of the fixed-length fragments of the stem candidates. The implemented software, SCARNA (Stem Candidate Aligner for RNAs), is fast enough to apply to the long sequences in the large-scale analyses. The accuracy of the alignments is better or comparable to the much slower existing algorithms.

ei

PDF Web DOI [BibTex]


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The Effect of Artifacts on Dependence Measurement in fMRI

Gretton, A., Belitski, A., Murayama, Y., Schölkopf, B., Logothetis, N.

Magnetic Resonance Imaging, 24(4):401-409, April 2006 (article)

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Phase noise and the classification of natural images

Wichmann, F., Braun, D., Gegenfurtner, K.

Vision Research, 46(8-9):1520-1529, April 2006 (article)

Abstract
We measured the effect of global phase manipulations on a rapid animal categorization task. The Fourier spectra of our images of natural scenes were manipulated by adding zero-mean random phase noise at all spatial frequencies. The phase noise was the independent variable, uniformly and symmetrically distributed between 0 degree and ±180 degrees. Subjects were remarkably resistant to phase noise. Even with ±120 degree phase noise subjects were still performing at 75% correct. The high resistance of the subjects’ animal categorization rate to phase noise suggests that the visual system is highly robust to such random image changes. The proportion of correct answers closely followed the correlation between original and the phase noise-distorted images. Animal detection rate was higher when the same task was performed with contrast reduced versions of the same natural images, at contrasts where the contrast reduction mimicked that resulting from our phase randomization. Since the subjects’ categorization rate was better in the contrast experiment, reduction of local contrast alone cannot explain the performance in the phase noise experiment. This result obtained with natural images differs from those obtained for simple sinusoidal stimuli were performance changes due to phase changes are attributed to local contrast changes only. Thus the global phasechange accompanying disruption of image structure such as edges and object boundaries at different spatial scales reduces object classification over and above the performance deficit resulting from reducing contrast. Additional colour information improves the categorization performance by 2 %.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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A Direct Method for Building Sparse Kernel Learning Algorithms

Wu, M., Schölkopf, B., BakIr, G.

Journal of Machine Learning Research, 7, pages: 603-624, April 2006 (article)

Abstract
Many Kernel Learning Algorithms(KLA), including Support Vector Machine (SVM), result in a Kernel Machine (KM), such as a kernel classifier, whose key component is a weight vector in a feature space implicitly introduced by a positive definite kernel function. This weight vector is usually obtained by solving a convex optimization problem. Based on this fact we present a direct method to build Sparse Kernel Learning Algorithms (SKLA) by adding one more constraint to the original convex optimization problem, such that the sparseness of the resulting KM is explicitly controlled while at the same time the performance of the resulting KM can be kept as high as possible. A gradient based approach is provided to solve this modified optimization problem. Applying this method to the SVM results in a concrete algorithm for building Sparse Large Margin Classifiers (SLMC). Further analysis of the SLMC algorithm indicates that it essentially finds a discriminating subspace that can be spanned by a small number of vectors, and in this subspace, the different classes of data are linearly well separated. Experimental results over several classification benchmarks demonstrate the effectiveness of our approach.

ei

PDF PDF [BibTex]

PDF PDF [BibTex]


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An Inventory of Sequence Polymorphisms For Arabidopsis

Clark, R., Ossowski, S., Schweikert, G., Rätsch, G., Shinn, P., Zeller, G., Warthmann, N., Fu, G., Hinds, D., Chen, H., Frazer, K., Huson, D., Schölkopf, B., Nordborg, M., Ecker, J., Weigel, D.

17th International Conference on Arabidopsis Research, April 2006 (talk)

Abstract
We have used high-density oligonucleotide arrays to characterize common sequence variation in 20 wild strains of Arabidopsis thaliana that were chosen for maximal genetic diversity. Both strands of each possible SNP of the 119 Mb reference genome were represented on the arrays, which were hybridized with whole genome, isothermally amplified DNA to minimize ascertainment biases. Using two complementary approaches, a model based algorithm, and a newly developed machine learning method, we identified over 550,000 SNPs with a false discovery rate of ~ 0.03 (average of 1 SNP for every 216 bp of the genome). A heuristic algorithm predicted in addition ~700 highly polymorphic or deleted regions per accession. Over 700 predicted polymorphisms with major functional effects (e.g., premature stop codons, or deletions of coding sequence) were validated by dideoxy sequencing. Using this data set, we provide the first systematic description of the types of genes that harbor major effect polymorphisms in natural populations at moderate allele frequencies. The data also provide an unprecedented resource for the study of genetic variation in an experimentally tractable, multicellular model organism.

ei

[BibTex]

[BibTex]


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Statistical Properties of Kernel Principal Component Analysis

Blanchard, G., Bousquet, O., Zwald, L.

Machine Learning, 66(2-3):259-294, March 2006 (article)

Abstract
We study the properties of the eigenvalues of Gram matrices in a non-asymptotic setting. Using local Rademacher averages, we provide data-dependent and tight bounds for their convergence towards eigenvalues of the corresponding kernel operator. We perform these computations in a functional analytic framework which allows to deal implicitly with reproducing kernel Hilbert spaces of infinite dimension. This can have applications to various kernel algorithms, such as Support Vector Machines (SVM). We focus on Kernel Principal Component Analysis (KPCA) and, using such techniques, we obtain sharp excess risk bounds for the reconstruction error. In these bounds, the dependence on the decay of the spectrum and on the closeness of successive eigenvalues is made explicit.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]


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Network-based de-noising improves prediction from microarray data

Kato, T., Murata, Y., Miura, K., Asai, K., Horton, P., Tsuda, K., Fujibuchi, W.

BMC Bioinformatics, 7(Suppl. 1):S4-S4, March 2006 (article)

Abstract
Prediction of human cell response to anti-cancer drugs (compounds) from microarray data is a challenging problem, due to the noise properties of microarrays as well as the high variance of living cell responses to drugs. Hence there is a strong need for more practical and robust methods than standard methods for real-value prediction. We devised an extended version of the off-subspace noise-reduction (de-noising) method to incorporate heterogeneous network data such as sequence similarity or protein-protein interactions into a single framework. Using that method, we first de-noise the gene expression data for training and test data and also the drug-response data for training data. Then we predict the unknown responses of each drug from the de-noised input data. For ascertaining whether de-noising improves prediction or not, we carry out 12-fold cross-validation for assessment of the prediction performance. We use the Pearson‘s correlation coefficient between the true and predicted respon se values as the prediction performance. De-noising improves the prediction performance for 65% of drugs. Furthermore, we found that this noise reduction method is robust and effective even when a large amount of artificial noise is added to the input data. We found that our extended off-subspace noise-reduction method combining heterogeneous biological data is successful and quite useful to improve prediction of human cell cancer drug responses from microarray data.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]


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Model-based Design Analysis and Yield Optimization

Pfingsten, T., Herrmann, D., Rasmussen, C.

IEEE Transactions on Semiconductor Manufacturing, 19(4):475-486, February 2006 (article)

Abstract
Fluctuations are inherent to any fabrication process. Integrated circuits and micro-electro-mechanical systems are particularly affected by these variations, and due to high quality requirements the effect on the devices’ performance has to be understood quantitatively. In recent years it has become possible to model the performance of such complex systems on the basis of design specifications, and model-based Sensitivity Analysis has made its way into industrial engineering. We show how an efficient Bayesian approach, using a Gaussian process prior, can replace the commonly used brute-force Monte Carlo scheme, making it possible to apply the analysis to computationally costly models. We introduce a number of global, statistically justified sensitivity measures for design analysis and optimization. Two models of integrated systems serve us as case studies to introduce the analysis and to assess its convergence properties. We show that the Bayesian Monte Carlo scheme can save costly simulation runs and can ensure a reliable accuracy of the analysis.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Weighting of experimental evidence in macromolecular structure determination

Habeck, M., Rieping, W., Nilges, M.

Proceedings of the National Academy of Sciences of the United States of America, 103(6):1756-1761, February 2006 (article)

Abstract
The determination of macromolecular structures requires weighting of experimental evidence relative to prior physical information. Although it can critically affect the quality of the calculated structures, experimental data are routinely weighted on an empirical basis. At present, cross-validation is the most rigorous method to determine the best weight. We describe a general method to adaptively weight experimental data in the course of structure calculation. It is further shown that the necessity to define weights for the data can be completely alleviated. We demonstrate the method on a structure calculation from NMR data and find that the resulting structures are optimal in terms of accuracy and structural quality. Our method is devoid of the bias imposed by an empirical choice of the weight and has some advantages over estimating the weight by cross-validation.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Classification of Faces in Man and Machine

Graf, A., Wichmann, F., Bülthoff, H., Schölkopf, B.

Neural Computation, 18(1):143-165, January 2006 (article)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Combining a Filter Method with SVMs

Lal, T., Chapelle, O., Schölkopf, B.

In Feature Extraction: Foundations and Applications, Studies in Fuzziness and Soft Computing, Vol. 207, pages: 439-446, Studies in Fuzziness and Soft Computing ; 207, (Editors: I Guyon and M Nikravesh and S Gunn and LA Zadeh), Springer, Berlin, Germany, 2006 (inbook)

Abstract
Our goal for the competition (feature selection competition NIPS 2003) was to evaluate the usefulness of simple machine learning techniques. We decided to use the correlation criteria as a feature selection method and Support Vector Machines for the classification part. Here we explain how we chose the regularization parameter C of the SVM, how we determined the kernel parameter and how we estimated the number of features used for each data set. All analyzes were carried out on the training sets of the competition data. We choose the data set Arcene as an example to explain the approach step by step. In our view the point of this competition was the construction of a well performing classifier rather than the systematic analysis of a specific approach. This is why our search for the best classifier was only guided by the described methods and that we deviated from the road map at several occasions. All calculations were done with the software Spider [2004].

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Embedded methods

Lal, T., Chapelle, O., Weston, J., Elisseeff, A.

In Feature Extraction: Foundations and Applications, pages: 137-165, Studies in Fuzziness and Soft Computing ; 207, (Editors: Guyon, I. , S. Gunn, M. Nikravesh, L. A. Zadeh), Springer, Berlin, Germany, 2006 (inbook)

Abstract
Embedded methods are a relatively new approach to feature selection. Unlike filter methods, which do not incorporate learning, and wrapper approaches, which can be used with arbitrary classifiers, in embedded methods the features selection part can not be separated from the learning part. Existing embedded methods are reviewed based on a unifying mathematical framework.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Chiral molecules split light: Reflection and refraction in a chiral liquid

Ghosh, A., Fischer, P.

PHYSICAL REVIEW LETTERS, 97(17), 2006, Featured highlight ‘Fundamental optical physics: Refraction’ Nature Photonics, Nov. 2006. (article)

Abstract
A light beam changes direction as it enters a liquid at an angle from another medium, such as air. Should the liquid contain molecules that lack mirror symmetry, then it has been predicted by Fresnel that the light beam will not only change direction, but will actually split into two separate beams with a small difference in the respective angles of refraction. Here we report the observation of this phenomenon. We also demonstrate that the angle of reflection does not equal the angle of incidence in a chiral medium. Unlike conventional optical rotation, which depends on the path-length through the sample, the reported reflection and refraction phenomena arise within a few wavelengths at the interface and thereby suggest a new approach to polarimetry that can be used in microfluidic volumes.

Featured highlight ‘Fundamental optical physics: Refraction’ Nature Photonics, Nov. 2006.

pf

DOI [BibTex]

DOI [BibTex]


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Direct chiral discrimination in NMR spectroscopy

Buckingham, A., Fischer, P.

CHEMICAL PHYSICS, 324(1):111-116, 2006 (article)

Abstract
Conventional nuclear magnetic resonance spectroscopy is unable to distinguish between the two mirror-image forms (enantiomers) of a chiral molecule. This is because the NMR spectrum is determined by the chemical shifts and spin-spin coupling constants which - in the absence of a chiral solvent - are identical for the two enantiomers. We discuss how chirality may nevertheless be directly detected in liquid-state NMR spectroscopy: In a chiral molecule, the rotating nuclear magnetic moment induces an electric dipole moment in the direction perpendicular to itself and to the permanent magnetic field of the spectrometer. We present computations of the precessing electric polarization following a pi/2 pulse. Our estimates indicate that the electric polarization should be detectable in favourable cases. We also predict that application of an electrostatic field induces a chirally sensitive magnetization oscillating in the direction of the permanent magnetic field. We show that the electric-field-perturbed chemical shift tensor, the nuclear magnetic shielding polarizability, underlies these chiral NMR effects. (c) 2005 Elsevier B.V. All rights reserved.

pf

DOI [BibTex]

DOI [BibTex]


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An ultrasonic standing-wave-actuated nano-positioning walking robot: piezoelectric-metal composite beam modeling

Son, K. J., Kartik, V., Wickert, J. A., Sitti, M.

Journal of vibration and control, 12(12):1293-1309, Sage Publications, 2006 (article)

pi

[BibTex]

[BibTex]


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NONLINEAR OPTICAL PROPERTIES OF CHIRAL LIQUIDS Electric-dipolar pseudoscalars in nonlinear optics

Fischer, P., Champagne, B.

In NON-LINEAR OPTICAL PROPERTIES OF MATTER: FROM MOLECULES TO CONDENSED PHASES, 1, pages: 359-381, Challenges and Advances in Computational Chemistry and Physics, 2006 (incollection)

Abstract
We give all overview of linear and nonlinear optical processes that can be specific to chiral molecules in isotropic media. Specifically, we discuss the pseudoscalars that underlie nonlinear optical activity and chiral frequency conversion processes in fluids. We show that nonlinear optical techniques open entirely new ways of exploring chirality: Sum-frequency-generation (SFG) at second-order and BioCARS at fourth-order arise in the electric-dipole approximation and do not require circularly polarized light to detect chiral molecules in solution. Here the frequency conversion in itself is a measure of chirality. This is in contrast to natural optical activity phenomena which are based on the interference of radiation from induced oscillating electric and magnetic dipoles, and which are observed as a differential response to right and left circularly polarized light. We give examples from our SFG experiments in optically active solutions and show how the application of an additional static electric field to sum-frequency generation allows the absolute configuration of the chiral solute to be determined via all electric-dipolar process. Results from ab initio calculations of the SFG pseudoscalar are presented for a number of chiral molecules

pf

[BibTex]

[BibTex]


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Ring-resonator-based frequency-domain optical activity measurements of a chiral liquid

Vollmer, F., Fischer, P.

OPTICS LETTERS, 31(4):453-455, 2006 (article)

Abstract
Chiral liquids rotate the plane of polarization of linearly polarized light and are therefore optically active. Here we show that optical rotation can be observed in the frequency domain. A chiral liquid introduced in a fiber-loop ring resonator that supports left and right circularly polarized modes gives rise to relative frequency shifts that are a direct measure of the liquid's circular birefringence and hence of its optical activity. The effect is in principle not diminished if the circumference of the ring is reduced. The technique is similarly applicable to refractive index and linear birefringence measurements. (c) 2006 Optical Society of America.

pf

DOI [BibTex]


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Sign of the refractive index in a gain medium with negative permittivity and permeability

Chen, Y., Fischer, P., Wise, F.

JOURNAL OF THE OPTICAL SOCIETY OF AMERICA B-OPTICAL PHYSICS, 23(1):45-50, 2006 (article)

Abstract
We show how the sign of the refractive index in any medium may be derived using a rigorous analysis based on Einstein causality. In particular, we consider left-handed materials, i.e., media that have negative permittivities and permeabilities at the frequency of interest. We find that the consideration of gain in such media can give rise to a positive refractive index. (c) 2006 Optical Society of America.

pf

DOI [BibTex]

DOI [BibTex]


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IEEE TRANSACTIONS ON ROBOTICS

VOLZ, RICHARD A, TARN, TJ, MACIEJEWSKI, ANTHONY A, LEE, SUKHAN, BICCHI, ANTONIO, DE LUCA, ALESSANDRO, LUH, PETER B, TAYLOR, RUSSELL H, BEKEY, GEORGE A, ARAI, HIROHIKO, others

2006 (article)

pi

[BibTex]

[BibTex]


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Design methodology for biomimetic propulsion of miniature swimming robots

Behkam, B., Sitti, M.

Trans.-ASME Journal of Dynamic Systems Measurement and Control, 128(1):36, ASME, 2006 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Augmented reality user interface for an atomic force microscope-based nanorobotic system

Vogl, W., Ma, B. K., Sitti, M.

IEEE transactions on nanotechnology, 5(4):397-406, IEEE, 2006 (article)

pi

[BibTex]

[BibTex]


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Friction enhancement via micro-patterned wet elastomer adhesives on small intestinal surfaces

Kwon, J., Cheung, E., Park, S., Sitti, M.

Biomedical Materials, 1(4):216, IOP Publishing, 2006 (article)

pi

[BibTex]

[BibTex]


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Influence of the substrate on the magnetic anisotropy of monatomic wires

Komelj, M., Steiauf, D., Fähnle, M.

{Physical Review B}, 73, 2006 (article)

mms

[BibTex]

[BibTex]


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Mechanical properties of single-walled carbon nanotubes based on higher order Cauchy-Born rule

Guo, X., Wang, J. B., Zhang, H. W.

{International Journal of Solids and Structures}, 43, pages: 1276-1290, 2006 (article)

mms

[BibTex]

[BibTex]


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Vanishing Fe 3d orbital moments in single-crystalline magnetite

Goering, E., Gold, S., Lafkioti, M., Schütz, G.

{Europhysics Letters}, 73(1):97-103, 2006 (article)

mms

[BibTex]

[BibTex]


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Enhancement of L10 phase formation in FePt nanoparticles by nitrogenization

Dmitrieva, O., Acet, M., Dumpich, G., Kästner, J., Antoniak, C., Farle, M., Fauth, K.

{Journal of Physics D}, 39, pages: 4741-4745, 2006 (article)

mms

[BibTex]

[BibTex]


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Structure of historical brass tonques and shallots from baroque organs

Baretzky, B., Friesel, M., Petelin, A., Mazilkin, A., Straumal, B.

{Defect and Diffusion Forum}, 249, pages: 275-280, 2006 (article)

mms

[BibTex]

[BibTex]


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Three-dimensional modeling of mechanical forces in the extra-cellular matrix during epithelial lumen formation

Zeng, D., Ferrari, A., Ulmer, J., Veligodskiy, A., Fischer, P., Spatz, J. P., Ventikos, Y., Poulikakos, D., Kroschewski, R.

{Biophysical Journal}, 90(12):4380-4391, 2006 (article)

mms

[BibTex]

[BibTex]


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Compliant and low-cost humidity nanosensors using nanoporous polymer membranes

Yang, B., Aksak, B., Lin, Q., Sitti, M.

Sensors and Actuators B: Chemical, 114(1):254-262, Elsevier, 2006 (article)

pi

[BibTex]

[BibTex]


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Task-based and stable telenanomanipulation in a nanoscale virtual environment

Kim, S., Sitti, M.

IEEE Transactions on automation science and engineering, 3(3):240-247, IEEE, 2006 (article)

pi

[BibTex]

[BibTex]


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Drawing suspended polymer micro-/nanofibers using glass micropipettes

Nain, A. S., Wong, J. C., Amon, C., Sitti, M.

Applied Physics Letters, 89(18):183105, AIP, 2006 (article)

pi

[BibTex]

[BibTex]


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Dynamic Hebbian learning in adaptive frequency oscillators

Righetti, L., Buchli, J., Ijspeert, A.

Physica D: Nonlinear Phenomena, 216(2):269-281, 2006 (article)

Abstract
Nonlinear oscillators are widely used in biology, physics and engineering for modeling and control. They are interesting because of their synchronization properties when coupled to other dynamical systems. In this paper, we propose a learning rule for oscillators which adapts their frequency to the frequency of any periodic or pseudo-periodic input signal. Learning is done in a dynamic way: it is part of the dynamical system and not an offline process. An interesting property of our model is that it is easily generalizable to a large class of oscillators, from phase oscillators to relaxation oscillators and strange attractors with a generic learning rule. One major feature of our learning rule is that the oscillators constructed can adapt their frequency without any signal processing or the need to specify a time window or similar free parameters. All the processing is embedded in the dynamics of the adaptive oscillator. The convergence of the learning is proved for the Hopf oscillator, then numerical experiments are carried out to explore the learning capabilities of the system. Finally, we generalize the learning rule to non-harmonic oscillators like relaxation oscillators and strange attractors.

mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Theoretical justification of ground-state moment analysis of magnetic dichroic x-ray absorption spectra for 3d transition metals

Dörfler, F., Fähnle, M.

{Physical Review B}, 74, 2006 (article)

Abstract
{(6 pages)}

mms

[BibTex]


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Vortex dynamics in coupled ferromagnetic multilayer structures

Chou, K., Puzic, A., Stoll, H., Schütz, G., Van Waeyenberge, B., Tyliszczak, T., Rott, K., Reiss, G., Brückl, H., Neudecker, I., Weiss, D., Back, C. H.

{Journal of Applied Physics}, 99, 2006 (article)

mms

[BibTex]

[BibTex]


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Electrical transport, magnetic and thermal properties of icosahedral Al-Pd-Mn quasicrystals

Poddar, A., Das, S., Plachke, D., Carstanjen, H.D.

{Journal of Magnetism and Magnetic Materials}, 300(2):263-272, 2006 (article)

mms

[BibTex]

[BibTex]


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Aqueous solution deposition of indium hydroxide and indium oxide columnar type thin films

Qiu, Y., Gerstel, P., Jiang, L., Lipowsky, P., Pitta Bauermann, L., Bill, J.

{International Journal of Materials Research}, 97(6):808-811, 2006 (article)

mms

[BibTex]

[BibTex]


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Enhanced orbital magnetism in Fe50Pt50 nanoparticles

Antoniak, C., Lindner, J., Spasova, M., Sudfeld, D., Acet, M., Farle, M., Fauth, K., Wiedwald, U., Boyen, H.-G., Ziemann, P., Wilhelm, F., Rogalev, A., Sun, S.

{Physical Review Letters}, 97, 2006 (article)

mms

[BibTex]

[BibTex]


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Approximate nearest neighbor regression in very high dimensions

Vijayakumar, S., DSouza, A., Schaal, S.

In Nearest-Neighbor Methods in Learning and Vision, pages: 103-142, (Editors: Shakhnarovich, G.;Darrell, T.;Indyk, P.), Cambridge, MA: MIT Press, 2006, clmc (inbook)

am

link (url) [BibTex]

link (url) [BibTex]


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Biologically inspired polymer microfibers with spatulate tips as repeatable fibrillar adhesives

Kim, S., Sitti, M.

Applied Physics Letters, 89(26):261911-261911, AIP, 2006 (article)

pi

Project Page [BibTex]


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Converting polycrystals into single crystals - Selective grain growth by high-energy ion bombardment

Olliges, S., Gruber, P., Bardill, A., Ehrler, D., Carstanjen, H. D., Spolenak, R.

{Acta Materialia}, 54(20):5393-5399, 2006 (article)

mms

[BibTex]

[BibTex]


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Topological k-space refinement of the configurational energy of alloys

Shchyglo, O., Bugaev, V.N., Drautz, R., Udyanskyy, A., Reichert, H., Dosch, H.

{Physical Review B}, 72, 2006 (article)

mms

[BibTex]

[BibTex]


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Synthesis of MgB2 films in Mg vapour flow and their characterization

Matveev, A. T., Albrecht, J., Konuma, M., Christiani, G., Krockenberger, Y., Starke, U., Schütz, G., Habermeier, H.

{Superconductor Science and Technology}, 19, pages: 299-305, 2006 (article)

mms

[BibTex]

[BibTex]