16 research outputs found

    Artificial pancreas systems for people with type 2 diabetes: Conception and design of the european CLOSE project

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    In the last 10 years tremendous progress has been made in the development of artificial pancreas (AP) systems for people with type 1 diabetes (T1D). The pan-European consortium CLOSE (Automated Glucose Control at Home for People with Chronic Disease) is aiming to develop integrated AP solutions (APplus) tailored to the needs of people with type 2 diabetes (T2D). APplus comprises a product and service package complementing the AP system by obligatory training as well as home visits and telemedical consultations on demand. Outcome predictors and performance indicators shall help to identify people who could benefit most from AP usage and facilitate the measurement of AP impact in diabetes care. In a first step CLOSE will establish a scalable APplus model case working at the interface between patients, homecare service providers, and payers in France. CLOSE will then scale up APplus by pursuing geographic distribution, targeting additional audiences, and enhancing AP functionalities and interconnectedness. By being part of the European Institute of Innovation and Technology (EIT) Health public-private partnership, CLOSE is committed to the EIT “knowledge triangle” pursuing the integrated advancement of technology, education, and business creation. Putting stakeholders, education, and impact into the center of APplus advancement is considered key for achieving wide AP use in T2D care

    Low aerobic mitochondrial energy metabolism in poorly- or undifferentiated neuroblastoma

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    <p>Abstract</p> <p>Background</p> <p>Succinate dehydrogenase (SDH) has been associated with carcinogenesis in pheochromocytoma and paraganglioma. In the present study we investigated components of the oxidative phosphorylation system in human neuroblastoma tissue samples.</p> <p>Methods</p> <p>Spectrophotometric measurements, immunohistochemical analysis and Western blot analysis were used to characterize the aerobic mitochondrial energy metabolism in neuroblastomas (NB).</p> <p>Results</p> <p>Compared to mitochondrial citrate synthase, SDH activity was severely reduced in NB (n = 14) versus kidney tissue. However no pathogenic mutations could be identified in any of the four subunits of SDH. Furthermore, no genetic alterations could be identified in the two novel SDH assembly factors SDHAF1 and SDH5. Alterations in genes encoding nfs-1, frataxin and isd-11 that could lead to a diminished SDH activity have not been detected in NB.</p> <p>Conclusion</p> <p>Because downregulation of other complexes of the oxidative phosphorylation system was also observed, a more generalized reduction of mitochondrial respiration seems to be present in neuroblastoma in contrast to the single enzyme defect found in hereditary pheochromocytomas.</p

    HyperText-orientierte Teachware für das Grundstudium in Operations Research

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    A defect classification scheme for the inspection of QUASAR requirements documents

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    Software inspection play a crucial role in achieving high quality software right from the beginning. Especially for requirements documents inspections are beneficial as defects can be detected and removed at an early point in time before they can leak into subsequent phases of the development process, where those defects can cause high rework cost and quality problems [Boehm and Basili, 2001]. In order to fully exploit the beneficial aspect of inspections it is necessary to control them: Based on an analysis of the inspection effectiveness (e.g., what type or number of defects have been detected and what type and number might be remaining) it has to be decided whether development can proceed as planned or controlling actions, such as reinspections, have to be performed. Defect classification is a technique that can support this activity. Using appropriate defect classification schemes it is possible to get a quantitative statement of the inspection effectiveness (i.e., what type of defects have been found). Examples in the literature demonstrated beneficial applications but are hard to adopt without tailoring the underlying defect classification scheme to the environment. In this report a defect classification scheme is developed that is to support the control of the inspection of QUASAR requirements documents. In particular we discuss our approach to define the scheme, its underlying rationale, the scheme itself, and our experience from using it in a case study. The scheme consist of two defect attributes that are to be used when inspecting use cases and recording defects in these documents, and three attributes for state chart documents

    An industrial case study of implementing and validating defect classification for process improvement and quality management

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    Defect measurement plays a crucial role when assessing quality assurance processes such as inspections and testing. To systematically combine these processes in the context of an integrated quality assurance strategy, measurement must provide empirical evidence on how effective these processes are and which types of defects are detected by which quality assurance process. Typically, defect classification schemes, such as ODC or the Hewlett-Packard scheme, are used to measure defects for this purpose. However, we found it difficult to transfer existing schemes to an embedded software context, where specific document- and defect types have to be considered. This paper presents an approach to define, introduce, and validate a customized defect classification scheme that considers the specifics of an industrial environment. The core of the approach is to combine the software engineering know-how of measurement experts and the domain know-how of developers. In addition to the approach, we present the results and experiences of using the approach in an industrial setting. The results indicate that our approach results in a defect classification scheme that allows classifying defects with good reliability, that allows identifying process improvement actions, and that can serve as a baseline for evaluating the impact of process improvements

    Conducting on-line surveys in software engineering

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    One purpose of empirical software engineering is to enable an understanding of factors that influence software development. Surveys are an appropriate empirical strategy to gather data from a large population (e.g., about methods, tools, developers, companies) and to achieve an understanding of that population. Although surveys are quite often performed, for example, in social sciences and marketing research, they are underrepresented in empirical software engineering research, which most often uses controlled experiments and case studies. Consequently, also the methodological support how to perform such studies in software engineering, is rather low. However, with the increasing pervasion of the Internet it is possible to perform surveys easily and cost-effectively over Internet pages (i.e., on-line), while at the same time the interest in performing surveys is growing. The purpose of this paper is twofold. First we want to arise the awareness of on-line surveys and discuss methods how to perform these in the context of software engineering. Second, we report our experience in performing on-line surveys in the form of lessons learned and guidelines

    An industrial case study of implementing and validating defect classification for process improvement and quality management

    No full text
    Defect measurement plays a crucial role when assessing quality assurance processes such as inspections and testing. To systematically combine these processes in the context of an integrated quality assurance strategy, measurement must provide empirical evidence on how effective these processes are and which types of defects are detected by which quality assurance process. Typically, defect classification schemes, such as ODC or the Hewlett-Packard scheme, are used to measure defects for this purpose. However, we found it difficult to transfer existing schemes to an embedded software context, where specific document- and defect types have to be considered. This paper presents an approach to define, introduce, and validate a customized defect classification scheme that considers the specifics of an industrial environment. The core of the approach is to combine the software engineering know-how of meas-urement experts and the domain know-how of developers. In addition to the approach, we present the results and experiences of using the approach in an industrial setting. The results indicate that our approach results in a defect classification scheme that allows classifying defects with good reliability that allows identifying process improvement actions and that can serve as a baseline for evaluating the impact of process improvements

    Investigating the impact of reading techniques on the accuracy of different defect content estimation techniques

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    Software inspections have established an impressive track record for early defect detection and correction. To increase their benefits, recent research efforts have focused on two different areas: systematic reading techniques and defect content estimation techniques. While reading techniques are to provide guidance for inspection participants on how to scrutinize a software artifact in a systematic manner, defect content estimation techniques aim at controlling and evaluating the inspection process by providing an estimate of the total number of defects in an inspected document. Although several empirical studies have been conducted to evaluate the accuracy of defect content estimation techniques, only few consider the reading approach as an influential factor. In this paper we examine the impact of two specific reading techniques - a scenario-based reading technique and checklist-based reading - on the accuracy of different defect content estimation techniques. The examination is based on data that were collected in a large experiment with students of the Vienna University of Technology. The results suggest that the choice of the reading technique has little impact on the accuracy of defect content estimation techniques. Although more empirical work is necessary to corroborate this finding, it implies that practitioners can use defect content estimation techniques without any consideration of their current reading technique

    A Comprehensive Evaluation of Capture-Recapture Models for Estimating Software Defect Content

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    An important requirement to control the inspection of software artifacts is to be able to decide, based on more objective information, whether the inspection can stop or whether it should continue to achieve a suitable level of artifact quality. A prediction of the number of remaining defects in an inspected artifact can be used for decision making. Several studies in software engineering have considered capture-recapture models, originally proposed by biologists to estimate animal populations, to make a prediction. However, few studies compare the actual number of remaining defects to the one predicted by a capture-recapture model on real software engineering artifacts. Thus, there is little work looking at the robustness of capture-recapture models under realistic software engineering conditions, where it is expected that some of their assumptions will be violated. Simulations have been performed but no definite conclusions can be drawn regarding the degree of accuracy of such models under realistic inspection conditions, and the factors affecting this accuracy. Furthermore, the existing studies focused on a subset of the existing capture-recapture models. Thus a more exhaustive comparison is still missing. In this study, we focus on traditional inspections and estimate, based on actual inspections&apos; data, the degree of accuracy of relevant, state-of-the-art capture-recapture models, as they have been proposed in biology and for which statistical estimators exist. In order to assess their robustness, we look at the impact of the number of inspectors and the number of actual defects on the estimators&apos; accuracy based on actual inspection data. Our results show that models are strongly affected by the number of inspectors and, therefore, one must consider this factor befo..
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