Nexus - an open global infrastructure for spatial-aware applications

Due to the lack of a generic platform for location- and spatial-aware systems, many basic services have to be reimplemented in each application that uses spatial-awareness. A cooperation among different applications is also difficult to achieve without a common platform. In this paper we present a platform that solves these problems. It provides an infrastructure that is based on computer models of regions of the physical world, which are augmented by virtual objects. We show how virtual objects make the integration of existing information systems and services in spatial-aware systems easier. Furthermore, our platform supports interactions between the computer models and the real world and integrates single models in a global 'Augmented World'

The iPlant Collaborative: Cyberinfrastructure for Plant Biology

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services

Biomarkers of the involvement of mast cells, basophils and eosinophils in asthma and allergic diseases

Biomarkers of disease activity have come into wide use in the study of mechanisms of human disease and in clinical medicine to both diagnose and predict disease course; as well as to monitor response to therapeutic intervention. Here we review biomarkers of the involvement of mast cells, basophils, and eosinophils in human allergic inflammation. Included are surface markers of cell activation as well as specific products of these inflammatory cells that implicate specific cell types in the inflammatory process and are of possible value in clinical research as well as within decisions made in the practice of allergy-immunology

Hoarding of location-dependent information to support mobile systems

Mit der zunehmenden Verbreitung mobiler Endgeräte wächst auch der Bedarf in mobilen Umgebungen auf entfernt gespeicherte Informationen zuzugreifen. Wie aktuelle Studien belegen, kommt dabei zukünftig ortsbezogenen Diensten (Location-Based Services, LBS) eine besondere Bedeutung zu. Diese Dienste ermöglichen es dem Benutzer, abhängig von seinem gegenwärtigen Aufenthaltsort, auf lokale Informationen, beispielsweise Informationen zu Restaurants, Kinoprogramme oder Staumeldungen, zuzugreifen. Mobile Informationszugriffe erfolgen meist über drahtlose Netzwerke, in denen häufig Probleme wie geringe Bandbreite, große Verzögerungen oder Verbindungsausfälle auftreten. In dieser Arbeit wird ein Verfahren vorgeschlagen, das diese Probleme weitgehend löst, indem es vorhersagt, welche Informationen ein Benutzer voraussichtlich benötigten wird und sie im Voraus auf sein mobiles Endgerät überträgt. Greift der Benutzer dann tatsächlich auf die vorab übertragenen Informationsobjekte zu, sind sie bereits lokal auf dem mobilen Endgerät vorhanden und stehen somit unmittelbar zur Verfügung. Für eine möglichst präzise Vorhersage der benötigten Informationen nutzt das beschriebene Verfahren Beziehungen zwischen Informationen und Orten, wie sie in mobilen Informationssystemen, insbesondere in ortsbezogenen Systemen, häufig zu finden sind, aus. Sie erlauben es, aus Kenntnissen über den aktuellen und zukünftigen Aufenthaltsort eines Benutzers Rückschlüsse auf die benötigten Informationen zu ziehen. Die Kenntnisse über den Aufenthaltsort erhält das Verfahren durch eigene Beobachtung oder wahlweise aus externen Informationsquellen. Ferner werden die Beziehungen zwischen Informationen und Orten selbständig erkannt. Das Verfahren reagiert sogar dynamisch auf Veränderungen in diesen Beziehungen.Recent market projections indicate that the need for mobile information access, especially in location-based services, will be the driving force for the future development of the mobile communication market as well as the market for mobile devices. Hence many location-dependent information systems have been developed recently. The mobile information access always turned out to be one of the basic research challenges in such systems, since the deployed wireless communication technologies often led to problems like high delays, low bandwidths, or frequent disconnections. In this thesis, a mechanism is proposed that overcomes these problems as far as possible. The basic idea is to predict the information objects that a user will probably need and to transfer these objects to his mobile device before they are actually accessed. This anticipatory information transfer is called information hoarding. If the user accesses one of the prefetched objects, it is already stored locally on his device and is available immediately. The problem with hoarding is to predict what information a user will need (hoarding problem''). The mechanism proposed in this work uses relationships between information objects and locations to solve the hoarding problem. It uses these relationships to derive the information objects the user will probably need from knowledge about his current and future location. In contrast to existing approaches, these relationships neither have to be fixed nor do they have to be well known, but the proposed mechanism recognizes them on its own and can even adapt dynamically to changes in these relationships. The knowledge about a user's future location is either gained autonomously by the mechanism through observation of the user or it is specified by external information sources like the application or the user himself

Exploiting Location Information for Infostation-Based Hoarding

With the increasing popularity of mobile computing devices, the need to access information in mobile environments has grown rapidly. Since the information has to be accessed over wireless networks, mobile information systems often have to deal with problems likelow bandwidth, high delay, and frequent disconnections. Information hoarding is a method that tries to overcome these problems by transferring information, which the user will probably need, in advance. The hoarding mechanism that we describe in this paper exploits the location dependence of the information access, which is often found in mobile information systems. Our simulation results show that it is beneficial to do so and that we achieve higher hit ratios than with a caching mechanism