Gas-phase photoinduced graft polymerization of acrylic acid onto polyacrylonitrile ultrafiltration membranes

Heterogeneous surface modification of polyacrylonitrile (PAN) ultrafiltration (UF) membranes is realized with UV irradiation-initiated graft polymerization of acrylic acid (AA) from the gas phase onto photoinitiator (benzophenone, BP)-coated samples. In the absence of monomer, PAN functionalization by ketyl radicals dominates after UV excitation of sorbed BP. With AA, graft and total polymer yield increase with BP loading and UV irradiation time. Average molecular weight and distribution of PAA homopolymer—formed in parallel during graft polymerization—are analyzed with gel permeation chromatography. Morphology of PAN-gr-AA UF membranes is checked with scanning electron micrographs (SEMs) and atomic force microscopy. Chemical changes are characterized with FTIR-ATR spectroscopy and SEM/EDX analyses, indicating a pronounced surface selctivity of the graft polymer modification (localized in the upper 5-μm membrane thickness). The amount of grafted PAA systematically reduces membrane permeability and increases dextrane retention, as verified in UF experiments. Photo graft polymer modificationof UF membranes will be applied to adjust membrane performance by controlling surface hydrophilicity and permeability using other monomers and/or further graft polymer functionalization. © 1995 John Wiley & Sons, Inc.     

High resolution fMRI of subcortical regions during visual erotic stimulation at 7 T

Object Involvement of distinct subcortical structures during sexual arousal was shown in animals and functional imaging studies gave coarse evidence for a similar organisation in humans. In contrast to previous imaging studies at lower field strengths, we tried to investigate activation in distinguishable subcortical structures at high spatial resolution during a short stimulating paradigm to further account for potential effects of attenuation or adaptation. Materials and methods Seven healthy subjects were investigated using functional magnetic resonance imaging (fMRI) on a 7 T scanner. High resolution EPI images of 1.4 × 1.4 mm² inplane resolution were acquired in a single functional session of 13.6 minutes. During the session erotic and non-erotic pictures were presented in an event-related design. Results In the unsmoothed data with preserved high spatial resolution significant effects were detected in relevant structures, including anterior caudate and mediodorsal thalamus. These effects were restricted to subcortical target structures and their anatomical boundaries. Conclusion This study demonstrates that fMRI at high fields provides an ideal tool to investigate functional anatomy of subcortical structures. Due to an increased signal-to-noise ratio, functional scans of short duration can be acquired at high resolution without the need for further spatial smoothing.     

Magnetization transfer short inversion time inversion recovery enhanced 1H MRI of the human lung

The unique characteristics of the human lung arising from low proton density and multiple air-tissue interfaces of the alveoli cause difficulty in¹H lung magnetic resonance imaging. In addition, the dominating signal from sources such as the thoracic muscle and subcutaneous fat hampers the visualization of the lung parenchyma. In this contribution, an efficient tissue suppression technique is presented which allows one to significantly enhance lung parenchyma visibility. A short inversion time inversion recovery (STIR) experiment combined with a magnetization transfer (MT) experiment was used for magnetization preparation in order to suppress the signal from muscle. A half-Fourier single-shot turbo spin-echo sequence was used as acquisition module. This approach was used to perform lung anatomical imaging in eight healthy human subjects and five patients withcystic fibrosis. The results obtained demonstrate that with MT-STIR approach high quality human lung images can be obtained and that this approach has the potential for the evaluation of lung pathologies.     

Dynamic rough clustering and its applications

Dynamic data mining has gained increasing attention in the last decade. It addresses changing data structures which can be observed in many real-life applications, e.g. buying behavior of customers. As opposed to classical, i.e. static data mining where the challenge is to discover pattern inherent in given data sets, in dynamic data mining the challenge is to understand – and in some cases even predict – how such pattern will change over time. Since changes in general lead to uncertainty, the appropriate approaches for uncertainty modeling are needed in order to capture, model, and predict the respective phenomena considered in dynamic environments. As a consequence, the combination of dynamic data mining and soft computing is a very promising research area. The proposed algorithm consists of a dynamic clustering cycle when the data set will be refreshed from time to time. Within this cycle criteria check if the newly arrived data have structurally changed in comparison to the data already analyzed. If yes, appropriate actions are triggered, in particular an update of the initial settings of the cluster algorithm. As we will show, rough clustering offers strong tools to detect such changing data structures. To evaluate the proposed dynamic rough clustering algorithm it has been applied to synthetic as well as to real-world data sets where it provides new insights regarding the underlying dynamic phenomena.     

Automatic image annotation using visual content and folksonomies

Automatic image annotation is an important and challenging task, and becomes increasingly necessary when managing large image collections. This paper describes techniques for automatic image annotation that take advantage of collaboratively annotated image databases, so called visual folksonomies. Our approach applies two techniques based on image analysis: First, classification annotates images with a controlled vocabulary and second tag propagation along visually similar images. The latter propagates user generated, folksonomic annotations and is therefore capable of dealing with an unlimited vocabulary. Experiments with a pool of Flickr images demonstrate the high accuracy and efficiency of the proposed methods in the task of automatic image annotation. Both techniques were applied in the prototypical tag recommender “tagr”.     

Ontological query answering under expressive Entity-Relationship schemata

The Entity-Relationship (ER) model is a fundamental tool for database design, recently extended and employed in knowledge representation and reasoning due to its expressiveness and comprehensibility. We address the problem of answering conjunctive queries under constraints representing schemata expressed in an extended version of the Entity-Relationship model. This extended model, called ER⁺, comprises is-a constraints among entities and relationships, plus functional and mandatory participation constraints. In particular, it allows for arbitrary permutations of the roles in is-a among relationships. A key notion that ensures high tractability in ER⁺ schemata is separability, i.e., the absence of interaction between the functional participation constraints and the other constructs of ER⁺. We provide a precise syntactic characterization of separable ER⁺ schemata by means of a necessary and sufficient condition. We present a complete complexity analysis of the conjunctive query answering problem under separable ER⁺ schemata, and also under several sublanguages of ER⁺. We show that the addition of so-called negative constraints does not increase the complexity of query answering. With such constraints, our model properly generalizes the most widely adopted tractable ontology languages, including those in the DL-Lite family.     

MOBSY: Integration of vision and dialogue in service robots

Abstract. This contribution introduces MOBSY, a fully integrated, autonomous mobile service robot system. It acts as an automatic dialogue-based receptionist for visitors to our institute. MOBSY incorporates many techniques from different research areas into one working stand-alone system. The techniques involved range from computer vision over speech understanding to classical robotics. Along with the two main aspects of vision and speech, we also focus on the integration aspect, both on the methodological and on the technical level. We describe the task and the techniques involved. Finally, we discuss the experiences that we gained with MOBSY during a live performance at our institute.     

Real-time triangulation of point streams

Hand-held laser scanners are commonly used in industry for reverse engineering and quality measurements. In this process, it is difficult for the human operator to scan the target object completely and uniformly. Therefore, an interactive triangulation of the scanned points can assist the operator in this task. In this paper, we describe the technical and implementational details of our real-time triangulation approach for point streams, presented at the 17th International Meshing Roundtable. Our method computes a triangulation of the point stream generated by the laser scanner online, i.e., the data points are added to the triangulation as they are received from the scanner. Multiple scanned areas and areas with a higher point density result in a finer mesh and a higher accuracy. On the other hand, the vertex density adapts to the estimated surface curvature. To guide the operator, the resulting triangulation is rendered with a visualization of its uncertainty and the display of an optimal scanning direction.     

OXPath: A language for scalable data extraction, automation, and crawling on the deep web

The evolution of the web has outpaced itself: A growing wealth of information and increasingly sophisticated interfaces necessitate automated processing, yet existing automation and data extraction technologies have been overwhelmed by this very growth. To address this trend, we identify four key requirements for web data extraction, automation, and (focused) web crawling: (1) interact with sophisticated web application interfaces, (2) precisely capture the relevant data to be extracted, (3) scale with the number of visited pages, and (4) readily embed into existing web technologies. We introduce OXPath as an extension of XPath for interacting with web applications and extracting data thus revealed—matching all the above requirements. OXPath’s page-at-a-time evaluation guarantees memory use independent of the number of visited pages, yet remains polynomial in time. We experimentally validate the theoretical complexity and demonstrate that OXPath’s resource consumption is dominated by page rendering in the underlying browser. With an extensive study of sublanguages and properties of OXPath, we pinpoint the effect of specific features on evaluation performance. Our experiments show that OXPath outperforms existing commercial and academic data extraction tools by a wide margin.