195 research outputs found

    Enabling Proactive Adaptation through Just-in-time Testing of Conversational Services

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    Service-based applications (SBAs) will increasingly be composed of third-party services available over the Internet. Reacting to failures of those third-party services by dynamically adapting the SBAs will become a key enabler for ensuring reliability. Determining when to adapt an SBA is especially challenging in the presence of conversational (aka. stateful) services. A conversational service might fail in the middle of an invocation sequence, in which case adapting the SBA might be costly; e.g., due to the necessary state transfer to an alternative service. In this paper we propose just-in-time testing of conversational services as a novel approach to detect potential problems and to proactively trigger adaptations, thereby preventing costly compensation activities. The approach is based on a framework for online testing and a formal test-generation method which guarantees functional correctness for conversational services. The applicability of the approach is discussed with respect to its underlying assumptions and its performance. The benefits of the approach are demonstrated using a realistic example

    Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively Validated

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    PURPOSE: Meningiomas are the most frequent primary intracranial tumors. Patient outcome varies widely from benign to highly aggressive, ultimately fatal courses. Reliable identification of risk of progression for individual patients is of pivotal importance. However, only biomarkers for highly aggressive tumors are established (CDKN2A/B and TERT), whereas no molecularly based stratification exists for the broad spectrum of patients with low- and intermediate-risk meningioma. METHODS: DNA methylation data and copy-number information were generated for 3,031 meningiomas (2,868 patients), and mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNVs), mutations, and WHO grading were analyzed. Prediction power for outcome was assessed in a retrospective cohort of 514 patients, validated on a retrospective cohort of 184, and on a prospective cohort of 287 multicenter cases. RESULTS: Both CNV- and methylation family-based subgrouping independently resulted in increased prediction accuracy of risk of recurrence compared with the WHO classification (c-indexes WHO 2016, CNV, and methylation family 0.699, 0.706, and 0.721, respectively). Merging all risk stratification approaches into an integrated molecular-morphologic score resulted in further substantial increase in accuracy (c-index 0.744). This integrated score consistently provided superior accuracy in all three cohorts, significantly outperforming WHO grading (c-index difference P = .005). Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grade 1 and grade 2 tumors (hazard ratio 4.34 [2.48-7.57] and 3.34 [1.28-8.72] retrospective and prospective validation cohorts, respectively). CONCLUSION: Merging these layers of histologic and molecular data into an integrated, three-tiered score significantly improves the precision in meningioma stratification. Implementation into diagnostic routine informs clinical decision making for patients with meningioma on the basis of robust outcome prediction

    On three-dimensional misorientation spaces.

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    Determining the local orientation of crystals in engineering and geological materials has become routine with the advent of modern crystallographic mapping techniques. These techniques enable many thousands of orientation measurements to be made, directing attention towards how such orientation data are best studied. Here, we provide a guide to the visualization of misorientation data in three-dimensional vector spaces, reduced by crystal symmetry, to reveal crystallographic orientation relationships. Domains for all point group symmetries are presented and an analysis methodology is developed and applied to identify crystallographic relationships, indicated by clusters in the misorientation space, in examples from materials science and geology. This analysis aids the determination of active deformation mechanisms and evaluation of cluster centres and spread enables more accurate description of transformation processes supporting arguments regarding provenance

    Desperately seeking niches: Grassroots innovations and niche development in the community currency field

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    The sustainability transitions literature seeks to explain the conditions under which technological innovations can diffuse and disrupt existing socio-technical systems through the successful scaling up of experimental ‘niches’; but recent research on ‘grassroots innovations’ argues that civil society is a promising but under-researched site of innovation for sustainability, albeit one with very different characteristics to the market-based innovation normally considered in the literature. This paper aims to address that research gap by exploring the relevance of niche development theories in a civil society context. To do this, we examine a growing grassroots innovation – the international field of community currencies – which comprises a range of new socio-technical configurations of systems of exchange which have emerged from civil society over the last 30 years, intended to provide more environmentally and socially sustainable forms of money and finance. We draw on new empirical research from an international study of these initiatives comprising primary and secondary data and documentary sources, elite interviews and participant observation in the field. We describe the global diffusion of community currencies, and then conduct a niche analysis to evaluate the utility of niche theories for explaining the development of the community currency movement. We find that some niche-building processes identified in the existing literature are relevant in a grassroots context: the importance of building networks, managing expectations and the significance of external ‘landscape’ pressures, particularly at the level of national-type. However, our findings suggest that existing theories do not fully capture the complexity of this type of innovation: we find a diverse field addressing a range of societal systems (money, welfare, education, health, consumerism), and showing increasing fragmentation (as opposed to consolidation and standardisation); furthermore, there is little evidence of formalised learning taking place but this has not hampered movement growth. We conclude that grassroots innovations develop and diffuse in quite different ways to conventional innovations, and that niche theories require adaptation to the civil society context

    Variations in strain affect friction and microstructure evolution in copper under a reciprocating tribological load

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    The microstructure of the materials constituting a metallic frictional contact strongly influences tribological performance. Being able to tailor friction and wear is challenging due to the complex microstructure evolution associated with tribological loading. Here, we investigate the effect of the strain distribution on these processes. High-purity copper plates were morphologically surface textured with two parallel rectangles—referred to as membranes—over the entire sample length by micro-milling. By keeping the width of these membranes constant and only varying their height, reciprocating tribological loading against sapphire discs resulted in different elastic and plastic strains. Finite element simulations were carried out to evaluate the strain distribution in the membranes. It was found that the maximum elastic strain increases with decreasing membrane stiffness. The coefficient of friction decreases with increasing membrane aspect ratio. By analyzing the microstructure and local crystallographic orientation, we found that both show less change with decreasing membrane stiffness

    Uncovering three-dimensional gradients in fibrillar orientation in an impact-resistant biological armour

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    The complex hierarchical structure in biological and synthetic fibrous nanocomposites entails considerable difficulties in the interpretation of the crystallographic texture from diffraction data. Here, we present a novel reconstruction method to obtain the 3D distribution of fibres in such systems. An analytical expression is derived for the diffraction intensity from fibres, explaining the azimuthal intensity distribution in terms of the angles of the three dimensional fibre orientation distributions. The telson of stomatopod (mantis shrimp) serves as an example of natural biological armour whose high impact resistance property is believed to arise from the hierarchical organization of alpha chitin nanofibrils into fibres and twisted plywood (Bouligand) structures at the sub-micron and micron scale. Synchrotron microfocus scanning X-ray diffraction data on stomatopod telson were used as a test case to map the 3D fibre orientation across the entire tissue section. The method is applicable to a range of biological and biomimetic structures with graded 3D fibre texture at the sub-micron and micron length scales

    Kallikrein-related peptidase 6 regulates epithelial-to-mesenchymal transition and serves as prognostic biomarker for head and neck squamous cell carcinoma patients

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    Background: Dysregulated expression of Kallikrein-related peptidase 6 (KLK6) is a common feature for many human malignancies and numerous studies evaluated KLK6 as a promising biomarker for early diagnosis or unfavorable prognosis. However, the expression of KLK6 in carcinomas derived from mucosal epithelia, including head and neck squamous cell carcinoma (HNSCC), and its mode of action has not been addressed so far. Methods: Stable clones of human mucosal tumor cell lines were generated with shRNA-mediated silencing or ectopic overexpression to characterize the impact of KLK6 on tumor relevant processes in vitro. Tissue microarrays with primary HNSCC samples from a retrospective patient cohort (n = 162) were stained by immunohistochemistry and the correlation between KLK6 staining and survival was addressed by univariate Kaplan-Meier and multivariate Cox proportional hazard model analysis. Results: KLK6 expression was detected in head and neck tumor cell lines (FaDu, Cal27 and SCC25), but not in HeLa cervix carcinoma cells. Silencing in FaDu cells and ectopic expression in HeLa cells unraveled an inhibitory function of KLK6 on tumor cell proliferation and mobility. FaDu clones with silenced KLK6 expression displayed molecular features resembling epithelial-to-mesenchymal transition, nuclear β-catenin accumulation and higher resistance against irradiation. Low KLK6 protein expression in primary tumors from oropharyngeal and laryngeal SCC patients was significantly correlated with poor progression-free (p = 0.001) and overall survival (p < 0.0005), and served as an independent risk factor for unfavorable clinical outcome. Conclusions: In summary, detection of low KLK6 expression in primary tumors represents a promising tool to stratify HNSCC patients with high risk for treatment failure. These patients might benefit from restoration of KLK6 expression or pharmacological targeting of signaling pathways implicated in EMT

    Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively Validated

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    PURPOSE: Meningiomas are the most frequent primary intracranial tumors. Patient outcome varies widely from benign to highly aggressive, ultimately fatal courses. Reliable identification of risk of progression for individual patients is of pivotal importance. However, only biomarkers for highly aggressive tumors are established (CDKN2A/B and TERT), whereas no molecularly based stratification exists for the broad spectrum of patients with low- and intermediate-risk meningioma. METHODS: DNA methylation data and copy-number information were generated for 3,031 meningiomas (2,868 patients), and mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNVs), mutations, and WHO grading were analyzed. Prediction power for outcome was assessed in a retrospective cohort of 514 patients, validated on a retrospective cohort of 184, and on a prospective cohort of 287 multicenter cases. RESULTS: Both CNV- and methylation family-based subgrouping independently resulted in increased prediction accuracy of risk of recurrence compared with the WHO classification (c-indexes WHO 2016, CNV, and methylation family 0.699, 0.706, and 0.721, respectively). Merging all risk stratification approaches into an integrated molecular-morphologic score resulted in further substantial increase in accuracy (c-index 0.744). This integrated score consistently provided superior accuracy in all three cohorts, significantly outperforming WHO grading (c-index difference P = .005). Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grade 1 and grade 2 tumors (hazard ratio 4.34 [2.48-7.57] and 3.34 [1.28-8.72] retrospective and prospective validation cohorts, respectively). CONCLUSION: Merging these layers of histologic and molecular data into an integrated, three-tiered score significantly improves the precision in meningioma stratification. Implementation into diagnostic routine informs clinical decision making for patients with meningioma on the basis of robust outcome prediction
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