Online-Literaturdatenbanken im Bereich der Wirtschaftsinformatik: Bereitstellung wissenschaftlicher Literatur und Analyse von Interaktionen der Wissensteilung

Knowledge sharing is fundamental for innovations in the scientific community. The paper examines how the interaction of knowledge sharing is supported by online services. With respect to business information systems, a survey of online literature databases is given, providing an aggregation of various publication sources, a direct access to publications, and which are available to the public. Furthermore, special analysis services are presented which describe competitive interactions of knowledge sharing via rankings on the one hand, and cooperative interactions of knowledge sharing via co-authorship evaluation on the other.     

A biologically inspired active compliant joint using local positive velocity feedback (LPVF).

Starting from studies which revealed that positive feedback is found in the control system for walking in arthropods, we have constructed a new positive feedback driven joint that can be used for solving compliant motion tasks. We propose two different joint constructions each of which shows passive compliance. Based on these joints we introduce three different local positive velocity feedback (LPVF) controllers and discuss their properties in the context of motion generation in closed kinematic chains. The third circuit named undelayed dLPVF is used for the control of a compliant planar manipulator which turns a crank. Our concept is of highly decentralized nature and follows the idea of embodiment. In our case this means that a process which is controlled by LPVF controllers reveals its nature when the controllers interact with this process.     

Integrated MRI assessment of regional function and perfusion in canine myocardial infarction

A single integrated examination using regional measurements of perfusion from contrast-enhanced MRI and three-dimensional (3D) strain from tissue-tagged MRI was developed to differentiate infarcted myocardium from adjacent tissue with functional abnormalities. Ten dogs were studied at baseline and 10 days after a 2-hour occlusion of the left anterior descending coronary artery (LAD). Strain was determined using a 3D finite element model. Two-dimensional measurements of hypoenhancing regions were highly correlated with myocardial viability (r = 0.96). Signal intensity versus time curves obtained from contrast-enhanced MRI were used for quantitative perfusion analysis. The remote and adjacent noninfarcted tissue of the dogs with LAD occlusion, as well as the infarcted tissue, exhibited abnormal deformation patterns as compared to normal dogs (positive predictive value (PPV) of strain determination of infarction = 66%). Integration of contrast-enhanced MRI results with 3D strain analysis enabled the delineation of the myocardial infarction (PPV = 100%) from functionally compromised myocardium. This integrated cardiac examination shows promise for noninvasive serial assessment of potentially jeopardized noninfarcted myocardium to study the process of infarct remodeling and expansion.     

Deriving tabular event-based specifications from goal-oriented requirements models

Goal-oriented methods are increasingly popular for elaborating software requirements. They offer systematic support for incrementally building intentional, structural and operational models of the software and its environment. They also provide various techniques for early analysis, notably, to manage conflicting goals or to anticipate abnormal environment behaviours that prevent goals from being achieved. On the other hand, tabular event-based methods are well-established for specifying operational requirements for control software. They provide sophisticated techniques and tools for late analysis of software behaviour models through simulation, model checking or table exhaustiveness checks. The paper proposes to take the best out of these two worlds to engineer requirements for control software. It presents a technique for deriving event-based specifications, written in the SCR tabular language, from operational specifications built according to the KAOS goal-oriented method. The technique consists of a series of transformation steps each of which resolves semantic, structural or syntactic differences between the KAOS source language and the SCR target language. Some of these steps need human intervention and illustrate the kind of semantic subtleties that need to be taken into account when integrating multiple formalisms. As a result of our technique SCR specifiers may use upstream goal-based processes à la KAOS for the incremental elaboration, early analysis, organization and documentation of their tables, while KAOS modelers may use downstream tables à la SCR for later analysis of the behaviour models derived from goal specifications.     

THE QSM ALGORITHM AND ITS APPLICATION TO SOFTWARE BEHAVIOR MODEL INDUCTION

This article presents a novel application of grammatical inference techniques to the synthesis of behavior models of software systems. This synthesis is used for the elicitation of software requirements. This problem is formulated as a deterministic finite-state automaton induction problem from positive and negative scenarios provided by an end user of the software-to-be. A query-driven state merging (QSM) algorithm is proposed. It extends the Regular Positive and Negative Inference (RPNI) and blue-fringe algorithms by allowing membership queries to be submitted to the end user. State merging operations can be further constrained by some prior domain knowledge formulated as fluents, goals, domain properties, and models of external software components. The incorporation of domain knowledge both reduces the number of queries and guarantees that the induced model is consistent with such knowledge. The proposed techniques are implemented in the ISIS tool and practical evaluations on standard requirements engineering test cases and synthetic data illustrate the interest of this approach.     

Clinical proteomics: Promises,challenges and limitations of affinity arrays

After the establishment of DNA/RNA sequencing as a means of clinical diagnosis, the analysis of the proteome is next in line. As a matter of fact, proteome-based diagnostics is bound to be even more informative, since proteins are directly involved in the actual cellular processes that are responsible for disease. However, the structural variation and the biochemical differences between proteins, the much wider range in concentration and their spatial distribution as well as the fact that protein activity frequently relies on interaction increase the methodological complexity enormously, particularly if an accuracy and robustness is required that is sufficient for clinical utility. Here, we discuss the contribution that protein microarray formats could play towards proteome-based diagnostics.     

A data model for managing drug therapy within a patient data management system for intensive care units

The major intent of this article was to describe the design principles of the drug-therapy documentation module of the Patient Data Management System (PDMS) ICUData, in routine use at the intensive care unit (ICU) of the Department of Anesthesiology and Intensive Care Medicine at the University Hospital of Giessen, Germany, since February 1999. The new drug management system has been in routine use since March 2000. Until 8 January 2001, 1140 patients have been documented using this approach. It could be demonstrated that it was possible to transform the formerly unstructured text-based documentation into a detailed and structured model. The mediated benefit resulted in the automatic calculation of fluid balance. Further, detailed statistical analyses of therapeutic behavior in drug administration are now possible.     

Comparison of Two Enzyme Sequences for a Novel L-Malate Biosensor

Two novel amperometric biosensors for the determination of L -malic acid in food samples have been compared. Both sensors make use of a Clark-type O₂-electrode but differ in the enzymes used. The first sensor is composed of malate dehydrogenase (decarboxylating), also known as ‘malic enzyme’ (MDH(dec.), EC 1.1.1.40) and pyruvate oxidase (POP, EC 1.2.3.3). It covers a linear detection range from 1 μmol dm⁻³ to 0·9 mmol dm⁻³ L -malate, with a response time of 1·5 min (t₉₀) and a relative standard deviation of 3·5%. Measurements with real samples offered a good correlation with the standard enzymatic assay (difference ±7%). Stored at room temperature, the response of the sensor is constant for 8 days. The second biosensor is based on the three enzyme sequence malate dehydrogenase (MDH, EC 1.1.1.37), oxaloacetate decarboxylase (OAC, EC 4.1.1.3) and pyruvate oxidase (POP, EC 1.2.3.3). It has a non-linear calibration curve. Concentrations from 5 μmol dm⁻³ to 1 mmol dm⁻³ L -malate can be detected, within a response time of 1·5 min and with a relative standard deviation of 20%. The lower detection limit for L -malate is 2 μmol dm⁻³. The response is constant for 10 days when the sensor is stored at room temperature.