Solid-phase microextraction for bioconcentration studies according to OECD TG 305

An important aim of the European Community Regulation on chemicals and their safe use is the identification of (very) persistent, (very) bioaccumulative, and toxic substances. In other regulatory chemical safety assessments (pharmaceuticals, biocides, pesticides), the identification of such (very) persistent, (very) bioaccumulative, and toxic substances is of increasing importance. Solid-phase microextraction is especially capable of extracting total water concentrations as well as the freely dissolved fraction of analytes in the water phase, which is available for bioconcentration in fish. However, although already well established in environmental analyses to determine and quantify analytes mainly in aqueous matrices, solid-phase microextraction is still a rather unusual method in regulatory ecotoxicological research. Here, the potential benefits and drawbacks of solid-phase microextraction are discussed as an analytical routine approach for aquatic bioconcentration studies according to OECD TG 305, with a special focus on the testing of hydrophobic organic compounds characterized by log KOW > 5

Topic Map Generation Using Text Mining

Starting from text corpus analysis with linguistic and statistical analysis algorithms, an infrastructure for text mining is described which uses collocation analysis as a central tool. This text mining method may be applied to different domains as well as languages. Some examples taken form large reference databases motivate the applicability to knowledge management using declarative standards of information structuring and description. The ISO/IEC Topic Map standard is introduced as a candidate for rich metadata description of information resources and it is shown how text mining can be used for automatic topic map generation

Business Model Innovation in Times of Crisis: Highway2Hybrid – A Trade Fairs Digital Transformation

The business event industry was hit particularly hard by the COVID-19 pandemic. Within a few weeks, all trade fairs, congresses and events were cancelled in the spring of 2020 and partly replaced by video-conferencing formats as fastest possible alternative in order to reach the goals of the respective industries at least digitally. After more than a year of pandemic, many marketing and business travel budgets were forced to either be cut, frozen, or shifted into online initiatives. The crisis winners of shifted budgets were, for example, the advertising business segments of social media business networks such as LinkedIn. Trade fairs were forced to leverage digital technologies and undergo a significant transformation of their business model in order to survive. This teaching case addresses various aspects of modern live communication in the business event industry and the challenge of combining these elements with digital technologies and services to create added value

Messaging Rules as a Programming Model for Enterprise Application Integration

Rule-based systems and languages are successful in many application areas such as business rules or active database systems. The goal of the Demaq project is to investigate the feasibility and benefits of using a declarative, rule-based programming language to simplify the development of complex, distributed applications. For this purpose, we propose a novel programming paradigm based on messaging, queues and declarative rules. We focus on evaluating whether the proposed, rule-based approach can be used to implement complex application patterns. We use Enterprise Application Integration (EAI) as an example application domain, as EAI applications involve multiple, heterogeneous systems with complex interaction patterns. We discuss whether and how these application patterns can be implemented using our rule language

Scalability Transformations on Declarative Applications

Many current distributed applications are based on the exchange of XML messages. Scaling such applications to the high processing volume demanded by Internet-scale deployment typically requires costly redesign and coding. In this paper, we investigate how a declarative specification of such applications can simplify the task of deploying them on a large number of host machines. In our model, applications are represented as a graph of message queues connected by message flow rules. The state of application instances is encoded in the message history of the queues and accessed using XQuery expressions. We show how to split such an application into distributable fragments using graph partitioning and discuss different algorithms for placing the fragments on hosts. Typically, an initial application specification contains data dependencies that place an upper limit on the number of fragments, and hence the number of usable machines. We describe transformations that increase the number of possible fragments by converting data dependencies into message flow. An evaluation using the TPC-App benchmark and a runtime system prototype confirms the feasibility and performance benefits of this approach

A flexible architecture for privacy-aware trust management

In service-oriented systems a constellation of services cooperate, sharing potentially sensitive information and responsibilities. Cooperation is only possible if the different participants trust each other. As trust may depend on many different factors, in a flexible framework for Trust Management (TM) trust must be computed by combining different types of information. In this paper we describe the TAS3 TM framework which integrates independent TM systems into a single trust decision point. The TM framework supports intricate combinations whilst still remaining easily extensible. It also provides a unified trust evaluation interface to the (authorization framework of the) services. We demonstrate the flexibility of the approach by integrating three distinct TM paradigms: reputation-based TM, credential-based TM, and Key Performance Indicator TM. Finally, we discuss privacy concerns in TM systems and the directions to be taken for the definition of a privacy-friendly TM architecture.\u