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2003


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Feature selection and transduction for prediction of molecular bioactivity for drug design

Weston, J., Perez-Cruz, F., Bousquet, O., Chapelle, O., Elisseeff, A., Schölkopf, B.

Bioinformatics, 19(6):764-771, April 2003 (article)

Abstract
Motivation: In drug discovery a key task is to identify characteristics that separate active (binding) compounds from inactive (non-binding) ones. An automated prediction system can help reduce resources necessary to carry out this task. Results: Two methods for prediction of molecular bioactivity for drug design are introduced and shown to perform well in a data set previously studied as part of the KDD (Knowledge Discovery and Data Mining) Cup 2001. The data is characterized by very few positive examples, a very large number of features (describing three-dimensional properties of the molecules) and rather different distributions between training and test data. Two techniques are introduced specifically to tackle these problems: a feature selection method for unbalanced data and a classifier which adapts to the distribution of the the unlabeled test data (a so-called transductive method). We show both techniques improve identification performance and in conjunction provide an improvement over using only one of the techniques. Our results suggest the importance of taking into account the characteristics in this data which may also be relevant in other problems of a similar type.

ei

Web [BibTex]


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Rademacher and Gaussian averages in Learning Theory

Bousquet, O.

Universite de Marne-la-Vallee, March 2003 (talk)

ei

PDF [BibTex]

PDF [BibTex]


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Use of the Zero-Norm with Linear Models and Kernel Methods

Weston, J., Elisseeff, A., Schölkopf, B., Tipping, M.

Journal of Machine Learning Research, 3, pages: 1439-1461, March 2003 (article)

Abstract
We explore the use of the so-called zero-norm of the parameters of linear models in learning. Minimization of such a quantity has many uses in a machine learning context: for variable or feature selection, minimizing training error and ensuring sparsity in solutions. We derive a simple but practical method for achieving these goals and discuss its relationship to existing techniques of minimizing the zero-norm. The method boils down to implementing a simple modification of vanilla SVM, namely via an iterative multiplicative rescaling of the training data. Applications we investigate which aid our discussion include variable and feature selection on biological microarray data, and multicategory classification.

ei

PDF PostScript PDF [BibTex]

PDF PostScript PDF [BibTex]


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Introduction: Robots with Cognition?

Franz, MO.

6, pages: 38, (Editors: H.H. Bülthoff, K.R. Gegenfurtner, H.A. Mallot, R. Ulrich, F.A. Wichmann), 6. T{\"u}binger Wahrnehmungskonferenz (TWK), February 2003 (talk)

Abstract
Using robots as models of cognitive behaviour has a long tradition in robotics. Parallel to the historical development in cognitive science, one observes two major, subsequent waves in cognitive robotics. The first is based on ideas of classical, cognitivist Artificial Intelligence (AI). According to the AI view of cognition as rule-based symbol manipulation, these robots typically try to extract symbolic descriptions of the environment from their sensors that are used to update a common, global world representation from which, in turn, the next action of the robot is derived. The AI approach has been successful in strongly restricted and controlled environments requiring well-defined tasks, e.g. in industrial assembly lines. AI-based robots mostly failed, however, in the unpredictable and unstructured environments that have to be faced by mobile robots. This has provoked the second wave in cognitive robotics which tries to achieve cognitive behaviour as an emergent property from the interaction of simple, low-level modules. Robots of the second wave are called animats as their architecture is designed to closely model aspects of real animals. Using only simple reactive mechanisms and Hebbian-type or evolutionary learning, the resulting animats often outperformed the highly complex AI-based robots in tasks such as obstacle avoidance, corridor following etc. While successful in generating robust, insect-like behaviour, typical animats are limited to stereotyped, fixed stimulus-response associations. If one adopts the view that cognition requires a flexible, goal-dependent choice of behaviours and planning capabilities (H.A. Mallot, Kognitionswissenschaft, 1999, 40-48) then it appears that cognitive behaviour cannot emerge from a collection of purely reactive modules. It rather requires environmentally decoupled structures that work without directly engaging the actions that it is concerned with. This poses the current challenge to cognitive robotics: How can we build cognitive robots that show the robustness and the learning capabilities of animats without falling back into the representational paradigm of AI? The speakers of the symposium present their approaches to this question in the context of robot navigation and sensorimotor learning. In the first talk, Prof. Helge Ritter introduces a robot system for imitation learning capable of exploring various alternatives in simulation before actually performing a task. The second speaker, Angelo Arleo, develops a model of spatial memory in rat navigation based on his electrophysiological experiments. He validates the model on a mobile robot which, in some navigation tasks, shows a performance comparable to that of the real rat. A similar model of spatial memory is used to investigate the mechanisms of territory formation in a series of robot experiments presented by Prof. Hanspeter Mallot. In the last talk, we return to the domain of sensorimotor learning where Ralf M{\"o}ller introduces his approach to generate anticipatory behaviour by learning forward models of sensorimotor relationships.

ei

Web [BibTex]

Web [BibTex]


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Hierarchical Spatio-Temporal Morphable Models for Representation of complex movements for Imitation Learning

Ilg, W., Bakir, GH., Franz, MO., Giese, M.

In 11th International Conference on Advanced Robotics, (2):453-458, (Editors: Nunes, U., A. de Almeida, A. Bejczy, K. Kosuge and J.A.T. Machado), 11th International Conference on Advanced Robotics, January 2003 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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An Introduction to Variable and Feature Selection.

Guyon, I., Elisseeff, A.

Journal of Machine Learning, 3, pages: 1157-1182, 2003 (article)

ei

[BibTex]

[BibTex]


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Feature Selection for Support Vector Machines by Means of Genetic Algorithms

Fröhlich, H., Chapelle, O., Schölkopf, B.

In 15th IEEE International Conference on Tools with AI, pages: 142-148, 15th IEEE International Conference on Tools with AI, 2003 (inproceedings)

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[BibTex]

[BibTex]


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Propagation of Uncertainty in Bayesian Kernel Models - Application to Multiple-Step Ahead Forecasting

Quiñonero-Candela, J., Girard, A., Larsen, J., Rasmussen, CE.

In IEEE International Conference on Acoustics, Speech and Signal Processing, 2, pages: 701-704, IEEE International Conference on Acoustics, Speech and Signal Processing, 2003 (inproceedings)

Abstract
The object of Bayesian modelling is the predictive distribution, which in a forecasting scenario enables improved estimates of forecasted values and their uncertainties. In this paper we focus on reliably estimating the predictive mean and variance of forecasted values using Bayesian kernel based models such as the Gaussian Process and the Relevance Vector Machine. We derive novel analytic expressions for the predictive mean and variance for Gaussian kernel shapes under the assumption of a Gaussian input distribution in the static case, and of a recursive Gaussian predictive density in iterative forecasting. The capability of the method is demonstrated for forecasting of time-series and compared to approximate methods.

ei

PDF PostScript [BibTex]

PDF PostScript [BibTex]


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Unsupervised Clustering of Images using their Joint Segmentation

Seldin, Y., Starik, S., Werman, M.

In The 3rd International Workshop on Statistical and Computational Theories of Vision (SCTV 2003), pages: 1-24, 3rd International Workshop on Statistical and Computational Theories of Vision (SCTV), 2003 (inproceedings)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Kernel Methods and Their Applications to Signal Processing

Bousquet, O., Perez-Cruz, F.

In Proceedings. (ICASSP ‘03), Special Session on Kernel Methods, pages: 860 , ICASSP, 2003 (inproceedings)

Abstract
Recently introduced in Machine Learning, the notion of kernels has drawn a lot of interest as it allows to obtain non-linear algorithms from linear ones in a simple and elegant manner. This, in conjunction with the introduction of new linear classification methods such as the Support Vector Machines has produced significant progress. The successes of such algorithms is now spreading as they are applied to more and more domains. Many Signal Processing problems, by their non-linear and high-dimensional nature may benefit from such techniques. We give an overview of kernel methods and their recent applications.

ei

PDF PostScript [BibTex]

PDF PostScript [BibTex]


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Predictive control with Gaussian process models

Kocijan, J., Murray-Smith, R., Rasmussen, CE., Likar, B.

In Proceedings of IEEE Region 8 Eurocon 2003: Computer as a Tool, pages: 352-356, (Editors: Zajc, B. and M. Tkal), Proceedings of IEEE Region 8 Eurocon: Computer as a Tool, 2003 (inproceedings)

Abstract
This paper describes model-based predictive control based on Gaussian processes.Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of non-linear dynamic systems. It offers more insight in variance of obtained model response, as well as fewer parameters to determine than other models. The Gaussian processes can highlight areas of the input space where prediction quality is poor, due to the lack of data or its complexity, by indicating the higher variance around the predicted mean. This property is used in predictive control, where optimisation of control signal takes the variance information into account. The predictive control principle is demonstrated on a simulated example of nonlinear system.

ei

PDF PostScript [BibTex]

PDF PostScript [BibTex]


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New Approaches to Statistical Learning Theory

Bousquet, O.

Annals of the Institute of Statistical Mathematics, 55(2):371-389, 2003 (article)

Abstract
We present new tools from probability theory that can be applied to the analysis of learning algorithms. These tools allow to derive new bounds on the generalization performance of learning algorithms and to propose alternative measures of the complexity of the learning task, which in turn can be used to derive new learning algorithms.

ei

PostScript [BibTex]

PostScript [BibTex]


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Distance-based classification with Lipschitz functions

von Luxburg, U., Bousquet, O.

In Learning Theory and Kernel Machines, Proceedings of the 16th Annual Conference on Computational Learning Theory, pages: 314-328, (Editors: Schölkopf, B. and M.K. Warmuth), Learning Theory and Kernel Machines, Proceedings of the 16th Annual Conference on Computational Learning Theory, 2003 (inproceedings)

Abstract
The goal of this article is to develop a framework for large margin classification in metric spaces. We want to find a generalization of linear decision functions for metric spaces and define a corresponding notion of margin such that the decision function separates the training points with a large margin. It will turn out that using Lipschitz functions as decision functions, the inverse of the Lipschitz constant can be interpreted as the size of a margin. In order to construct a clean mathematical setup we isometrically embed the given metric space into a Banach space and the space of Lipschitz functions into its dual space. Our approach leads to a general large margin algorithm for classification in metric spaces. To analyze this algorithm, we first prove a representer theorem. It states that there exists a solution which can be expressed as linear combination of distances to sets of training points. Then we analyze the Rademacher complexity of some Lipschitz function classes. The generality of the Lipschitz approach can be seen from the fact that several well-known algorithms are special cases of the Lipschitz algorithm, among them the support vector machine, the linear programming machine, and the 1-nearest neighbor classifier.

ei

PDF PostScript [BibTex]

PDF PostScript [BibTex]


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Mixing in Cu/Ge system by swift heavy ions

Kumar, S., Chauhan, R. S., Singh, R. P., Kabiraj, D., Sahoo, P. K., Rumbolz, C., Srivastava, S. K., Bolse, W., Avasthi, D. K.

{Nuclear Instruments \& Methods in Physics Research Section B-Beam Interactions with Materials and Atoms}, 212, pages: 242-245, 2003 (article)

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[BibTex]

[BibTex]


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Magnetic properties of [NdFeBx/Nbz]n multilayer films

Tsai, J. L., Chin, T. S., Yao, Y. D., Melsheimer, A., Fischer, S. F., Dragon, T., Kelsch, M., Kronmüller, H.

{Journal of Applied Physics}, 93(10):6915-6917, 2003 (article)

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[BibTex]

[BibTex]


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Analysis of the temperature dependence of the coercive field of Sm2Co17 based magnets

Kronmüller, H., Goll, D.

{Scripta Materialia}, 48(7):833-838, 2003 (article)

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[BibTex]

[BibTex]


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NMR studies of hydrogen motion in nanostructured hydrogen-graphite systems

Majer, G., Stanik, E., Orimo, S.

{Journal of Alloys and Compounds}, 356-357, pages: 617-621, 2003 (article)

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[BibTex]

[BibTex]


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Hydrogen diffusion in metallic and nanostructured materials

Majer, G., Eberle, U., Kimmerle, F., Stanik, E., Orimo, S.

{Physica B}, 328, pages: 81-89, 2003 (article)

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[BibTex]

[BibTex]


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Grain boundary phase transitions in the Al-Mg system and their influence on high-strain rate superplasticity

Straumal, B. B., Lopez, G. A., Mittemeijer, E. J., Gust, W., Zhilyaev, A. P.

In 216-217, pages: 307-312, Moscow, Russia, 2003 (inproceedings)

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[BibTex]

[BibTex]


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Electron density-of-states and the metal-insulator transition in LaHx

Barnes, R. G., Chang, C. T., Majer, G., Kaess, U.

{Journal of Alloys and Compounds}, 356-357, pages: 137-141, 2003 (article)

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[BibTex]

[BibTex]


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Electronic sputtering from HOPG: A study of angular dependence

Tripathi, A., Khan, S. A., Srivastava, S. K., Kumar, M., Kumar, S., Rao, S. V. S. N., Lakshmi, G. B. V. S., Siddiqui, A. M., Bajwa, N., Nagaraja, H. S., Mittal, V. K., Szökefalvi, A., Kurth, M., Pandey, A. C., Avasthi, D. K., Carstanjen, H. D.

{Nuclear Instruments and Methods B}, 212, pages: 402-406, 2003 (article)

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[BibTex]

[BibTex]


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Stress-induced relaxation mechanisms in single-crystalline titanomagnetites

Walz, F., Brabers, V. A. M., Brabers, J. H. V. J., Kronmüller, H.

{Journal of Physics-Condensed Matter}, 15(41):7029-7045, 2003 (article)

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[BibTex]


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Morphology and interdiffusion behavior of evaporated metal films on crystalline diindenoperylene thin films

Dürr, A. C., Schreiber, F., Kelsch, M., Carstanjen, H. D., Dosch, H., Seeck, O. H.

{Journal of Applied Physics}, 93(9):5201-5209, 2003 (article)

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[BibTex]


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Recent progress with high resolution X-ray microscopy at the XM-1

Denbeaux, G., Schneider, G., Pearson, A., Chao, W., Bates, B., Harteneck, B., Olynick, D., Anderson, E., Fischer, P., Juenger, M.

{Journal de Physique IV}, 104, pages: 9-9, 2003 (article)

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[BibTex]


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Comment on the analysis of angle-dependent X-ray magnetic circular dichroism in systems with reduced dimensionality

Ederer, C., Komelj, M., Davenport, J. W., Fähnle, M.

{Journal of Electron Spectroscopy and Related Phenomena}, 130(1-3):97-100, 2003 (article)

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[BibTex]

[BibTex]


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The electron theory of magnetism in monoatomic nanowires

Komelj, M., Ederer, C., Fähnle, M.

{Advances in Solid State Science}, 43, pages: 781-788, 2003 (article)

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[BibTex]

[BibTex]


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Influence of grain boundary phase transitions on the diffusion-related properties

Straumal, B., Baretzky, B.

In Proceedings of the International Conference on Diffusion, Segregation and Stresses in Materials, pages: 53-64, Defect and Diffusion Forum, Scitec Publications Ltd., Moscow, Russia, 2003 (inproceedings)

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[BibTex]

[BibTex]


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Are carbon nanostructures an efficient hydrogen storage medium?

Hirscher, M., Becher, M., Haluska, M., von Zeppelin, F., Chen, X., Dettlaff-Weglikowska, U., Roth, S.

In 356-357, pages: 433-437, Annecy, France, 2003 (inproceedings)

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[BibTex]


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Nuclear relaxation in the dideuteride of hafnium and titanium

Majer, G., Gottwald, J., Peterson, D. T., Barnes, R. G.

{Physical Review B}, 68, 2003 (article)

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[BibTex]

[BibTex]


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Magnetism in systems with various dimensionalities: A comparison between Fe and Co

Ederer, C., Komelj, M., Fähnle, M.

{Physical Review B}, 68, 2003 (article)

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[BibTex]


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Characterization of free volumes in amorphous and nanostructured Pr2Fe14B using positron lifetime spectroscopy

Wu, Y. C., Ye, F., Barbe, V., Sprengel, W., Reimann, K., Reichle, K. J., Goll, D., Würschum, R., Schaefer, H. E.

{Physica Status Solidi A-Applied Research}, 198(1):204-209, 2003 (article)

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[BibTex]

[BibTex]


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The magnetization behavior of nanocrystalline permanent magnets based on the Stoner-Wohlfarth model

Zhang, H. W., Zhang, S. Y., Shen, B. G., Kronmüller, H.

{Journal of Magnetism and Magnetic Materials}, 260(3):352-360, 2003 (article)

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[BibTex]

[BibTex]


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X-ray magnetic microscopy for correlations between magnetic domains and crystal structure

Denbeaux, G., Anderson, E., Bates, B., Chao, W., Liddle, J. A., Harteneck, B., Pearson, A., Salmassi, F., Schneider, G., Fischer, P., Eimüller, T., Taylor, S., Chang, H., Kusinski, G. J.

{Journal de Physique IV}, 104, pages: 477-481, 2003 (article)

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[BibTex]


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Statistical mechanics of inhomogeneous model colloid-polymer mixtures

Brader, J. M., Evans, R., Schmidt, M.

{Molecular Physics}, 101, pages: 3349-3384, 2003 (article)

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[BibTex]


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Cluster expansion technique: An efficient tool to search for ground-state configurations of adatoms on plane surfaces

Drautz, R., Singer, R., Fähnle, M.

{Physical Review B}, 67, 2003 (article)

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Hydrogen strorage in carbon nanotubes

Becher, M., Haluska, M., Hirscher, M., Quintel, A., Skakalova, V., Dettlaff-Weglikovska, U., Chen, X., Hulman, M., Choi, Y., Roth, S., Meregalli, V., Parrinello, M., Ströbel, R., Jörissen, L., Kappes, M., Fink, J., Züttel, A., Stepanek, I., Bernier, P.

{Comptes Rendus Physique}, 4, pages: 1055-1062, 2003 (article)

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[BibTex]


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Grain boundary faceting phase transition and thermal grooving in Cu

Straumal, B. B., Polyakov, S. A., Bischoff, E., Mittemeijer, E. J., Gust, W.

In Proceedings of the International Conference on Diffusion, Segregation and Stresses in Materials, 216/217, pages: 93-100, Diffusion and Defect Data, Pt. A, Defect and Diffusion Forum, Scitec Publ., Moscow, 2003 (inproceedings)

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[BibTex]


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Thermal desorption spectroscopy as a quantitative tool to determine the hydrogen content in solids

von Zeppelin, F., Haluska, M., Hirscher, M.

{Thermochimica Acta}, 404, pages: 251-258, 2003 (article)

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[BibTex]


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Surface adsorbed atoms suppressing hydrogen permeation of Pd membranes

Yamakawa, K., Ege, M., Ludescher, B., Hirscher, M.

{Journal of Alloys and Compounds}, 352, pages: 57-59, 2003 (article)

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[BibTex]

[BibTex]


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Experiment with a crystal-assisted positron source using 6 and 10 GeV electrons

Artru, X., Baier, V., Beloborodov, K., Bochek, G., Bogdanov, A., Bozhenok, A., Bukin, A., Burdin, S., Chehab, R., Chevallier, M., Cizeron, R., Dauvergne, D., Dimova, T., Drozdetsky, A., Druzhinin, V., Dubrovin, M., Gatignon, L., Golubev, V., Jejcic, A., Keppler, P., Kirsch, R., Kulibaba, V., Lautesse, P., Major, J., Maslov, N., Poizat, J. C., Potylitsin, A., Remillieux, J., Serednyakov, S., Shary, V., Strakhovenko, V., Sylvia, C., Vnukov, I.

{Nuclear Instruments and Methods in Physics Research B}, 201, pages: 243-252, 2003 (article)

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[BibTex]


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Surface patterning of SrTiO3 by 30 keV ion irradiation

Albrecht, J., Leonhardt, S., Spolenak, R., Täffner, U., Habermeier, H. U., Schütz, G.

{Surface Science Letters}, 547, pages: L847-L852, 2003 (article)

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Magnetization reversal study of CoCrPt alloy thin films on a nanogranular-length scale using magnetic transmission soft x-ray microscopy

Im, M. Y., Fischer, P., Eimüller, T., Denbeaux, G., Shin, S. C.

{Applied Physics Letters}, 83(22):4589-4591, 2003 (article)

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Temperature-dependent pinning of vortices in low-angle grain boundaries in YBa2Cu3O7-δ

Albrecht, J.

{Physical Review B}, 68, 2003 (article)

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Magnetic soft X-ray transmission microscopy

Fischer, P.

{Current Opinion in Solid State \& Materials Science}, 7(2):173-179, 2003 (article)

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The magnetic transmission X-ray microscopy project at BESSY II

Eimüller, T., Niemann, B., Guttmann, P., Fischer, P., Englisch, U., Vatter, R., Wolter, C., Seiffert, S., Schmahl, G., Schütz, G.

{Journal de Physique IV}, 104, pages: 91-94, 2003 (article)

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Ab-initio statistical mechanics for ordered compounds: single-defect theory vs. cluster-expansion techniques

Drautz, R., Schultz, I., Lechermann, F., Fähnle, M.

{Physica Status Solidi B}, 240(1):37-44, 2003 (article)

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