Hundert Jahre Gebrüder Gutmann Philippsburg.

An article (clipping) on occasion of the 100th anniversary of the company ‘Gebrüder Gutmann’ in Philippsburg, Baden, Germany.

Purification and properties of Image -mandelate-4-hydroxylase from Pseudomonas convexa

An inducible Image -mandelate-4-hydroxylase has been partially purified from crude extracts of Pseudomonas convexa. This enzyme catalyzed the hydroxylation of Image -mandelic acid to 4-hydroxymandelic acid. It required tetrahydropteridine, NADPH, Fe2+, and O2 for its activity. The approximate molecular weight of the enzyme was assessed as 91,000 by gel filtration on Sephadex G-150. The enzyme was optimally active at pH 5.4 and 38 °C. A classical Michaelis-Menten kinetic pattern was observed with Image -mandelate, NADPH, and ferrous sulfate and Km values for these substrates were found to be 1 × 10−4, 1.9 × 10−4, and 4.7 × 10−5 Image , respectively. The enzyme is very specific for Image -mandelate as substrate. Thiol inhibitors inhibited the enzyme reaction, indicating that the sulfhydryl groups may be essential for the enzyme action. Treatment of the partially purified enzyme with denaturing agents inactivated the enzyme.

Enhancing the shopping experience with ambient displays: A field study in a retail store

This paper discusses the prototypical implementation of an ambient display and the results of an empirical study in a retail store. It presents the context of shopping as an application area for Ambient Intelligence (AmI) technologies. The prototype consists of an ambient store map that enhances the awareness of customer activity. The results of our study indicate potentials and challenges for an improvement of the shopping experience with AmI technologies. Based on our findings we discuss challenges and future developments for applying AmI technologies to shopping environments.

Self-image (autoidolon) techniques for the realisation of optical computing type operations

Abstract is not available.

Image, Political

Political communication scholars, journalists, and political actors alike, argue that the political process, and deliberative democracy (democracy founded on informed discussion inclusive of citizens), have lost their rational authenticity in that image and media spectacle have become more central to public opinion formation and electoral outcomes than policy. This entry examines the validity of that perception, and the extent to which “image” has emerged as a more significant factor in the political process. And if image is so important in political culture, what the impacts might be on the functioning of democratic processes.

Beyond Gauss: Image-set matching on the Riemannian manifold of PDFs

State-of-the-art image-set matching techniques typically implicitly model each image-set with a Gaussian distribution. Here, we propose to go beyond these representations and model image-sets as probability distribution functions (PDFs) using kernel density estimators. To compare and match image-sets, we exploit Csiszar´ f-divergences, which bear strong connections to the geodesic distance defined on the space of PDFs, i.e., the statistical manifold. Furthermore, we introduce valid positive definite kernels on the statistical manifold, which let us make use of more powerful classification schemes to match image-sets. Finally, we introduce a supervised dimensionality reduction technique that learns a latent space where f-divergences reflect the class labels of the data. Our experiments on diverse problems, such as video-based face recognition and dynamic texture classification, evidence the benefits of our approach over the state-of-the-art image-set matching methods.

A discrete wavelet transform approach to multiresolution complex SAR image generation

We present a signal processing approach using discrete wavelet transform (DWT) for the generation of complex synthetic aperture radar (SAR) images at an arbitrary number of dyadic scales of resolution. The method is computationally efficient and is free from significant system-imposed limitations present in traditional subaperture-based multiresolution image formation. Problems due to aliasing associated with biorthogonal decomposition of the complex signals are addressed. The lifting scheme of DWT is adapted to handle complex signal approximations and employed to further enhance the computational efficiency. Multiresolution SAR images formed by the proposed method are presented.

Eye-view: A retinal image acquisition system

This paper presents a low cost but high resolution retinal image acquisition system of the human eye. The images acquired by a CMOS image sensor are communicated through the Universal Serial Bus (USB) interface to a personal computer for viewing and further processing. The image acquisition time was estimated to be 2.5 seconds. This system can also be used in telemedicine applications.

Memory-efficient spatial prediction image compression scheme

In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates the predicted error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. In quantization phase, we used a modified SPIHT algorithm to achieve efficiency in memory requirements. The memory constraint plays a vital role in wireless and bandwidth-limited applications. A single reusable list is used instead of three continuously growing linked lists as in case of SPIHT. This method is error resilient. The performance is measured in terms of PSNR and memory requirements. The algorithm shows good compression performance and significant savings in memory. (C) 2006 Elsevier B.V. All rights reserved.

Urban satellite image classification using biologically inspired techniques

This paper focuses on optimisation algorithms inspired by swarm intelligence for satellite image classification from high resolution satellite multi- spectral images. Amongst the multiple benefits and uses of remote sensing, one of the most important has been its use in solving the problem of land cover mapping. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Image classification forms the core of the solution to the land cover mapping problem. No single classifier can prove to satisfactorily classify all the basic land cover classes of an urban region. In both supervised and unsupervised classification methods, the evolutionary algorithms are not exploited to their full potential. This work tackles the land map covering by Ant Colony Optimisation (ACO) and Particle Swarm Optimisation (PSO) which are arguably the most popular algorithms in this category. We present the results of classification techniques using swarm intelligence for the problem of land cover mapping for an urban region. The high resolution Quick-bird data has been used for the experiments.

Automatic Road Extraction using High Resolution Satellite Image Based on Texture Progressive Analysis and Normalized Cut Method

In this paper the approach for automatic road extraction for an urban region using structural, spectral and geometric characteristics of roads has been presented. Roads have been extracted based on two levels: Pre-processing and road extraction methods. Initially, the image is pre-processed to improve the tolerance by reducing the clutter (that mostly represents the buildings, parking lots, vegetation regions and other open spaces). The road segments are then extracted using Texture Progressive Analysis (TPA) and Normalized cut algorithm. The TPA technique uses binary segmentation based on three levels of texture statistical evaluation to extract road segments where as, Normalizedcut method for road extraction is a graph based method that generates optimal partition of road segments. The performance evaluation (quality measures) for road extraction using TPA and normalized cut method is compared. Thus the experimental result show that normalized cut method is efficient in extracting road segments in urban region from high resolution satellite image.

Efficient content-based image retrieval based on multi-feature fusion

The increased availability of image capturing devices has enabled collections of digital images to rapidly expand in both size and diversity. This has created a constantly growing need for efficient and effective image browsing, searching, and retrieval tools. Pseudo-relevance feedback (PRF) has proven to be an effective mechanism for improving retrieval accuracy. An original, simple yet effective rank-based PRF mechanism (RB-PRF) that takes into account the initial rank order of each image to improve retrieval accuracy is proposed. This RB-PRF mechanism innovates by making use of binary image signatures to improve retrieval precision by promoting images similar to highly ranked images and demoting images similar to lower ranked images. Empirical evaluations based on standard benchmarks, namely Wang, Oliva & Torralba, and Corel datasets demonstrate the effectiveness of the proposed RB-PRF mechanism in image retrieval.

The dynamics of solvation of an electron in the image potential state by a layer of polar adsorbates

Recently, ultrafast two-photon photoemission has been used to study electron solvation at a two-dimensional metal/polar adsorbate interfaces [A. Miller , Science 297, 1163 (2002)]. The electron is bound to the surface by the image interaction. Earlier we have suggested a theoretical description of the states of the electron interacting with a two-dimensional layer of the polar adsorbate [K. L. Sebastian , J. Chem. Phys. 119, 10350 (2003)]. In this paper we have analyzed the dynamics of electron solvation, assuming a trial wave function for the electron and the solvent polarization and then using the Dirac-Frenkel variational method to determine it. The electron is initially photoexcited to a delocalized state, which has a finite but large size, and causes the polar molecules to reorient. This reorientation acts back on the electron and causes its wave function to shrink, which will cause further reorientation of the polar molecules, and the process continues until the electron gets self-trapped. For reasonable values for the parameters, we are able to obtain fair agreement with the experimental observations. (c) 2005 American Institute of Physics.

Inhibitory activity of Image -asparaginase from Mycobcacterium tuberculosis on Yoshida ascites sarcoma in rats

The antitumor activity of Image -asparagine amidohydrolases (EC 3.5.1.1) from Mycobacterium tuberculosis H37Rv and H37Ra strains has been tested on Yoshida ascites sarcoma in rats. The enzyme specific to M. tuberculosis H37Ra but not to H37Rv has proved to be effective in inhibiting the growth of the sarcoma. Comparative studies on the activity of this enzyme with that of similar enzyme from Escherichia coli B, has shown that at the same levels the former is more effective than the latter. Long-lived immunity to this tumor in A/IISc Wistar rats following treatment of tumor bearing animals with M. tuberculosis H37Ra, pH 9.6 Image -asparaginase has been observed. Immunity in these rats was demonstrated by tumor rejection and detection of humoral antibodies in the sera to the antigen of the cell-free extract of the tumor. The enzyme was ineffective in inhibiting fibrosarcoma in mice at the dose levels tested.