Patch-recovery filters for curvature in discontinuous Galerkin-based level-set methods

In two-phase flow simulations, a difficult issue is usually the treatment of surface tension effects. These cause a pressure jump that is proportional to the curvature of the interface separating the two fluids. Since the evaluation of the curvature incorporates second derivatives, it is prone to numerical instabilities. Within this work, the interface is described by a level-set method based on a discontinuous Galerkin discretization. In order to stabilize the evaluation of the curvature, a patch-recovery operation is employed. There are numerous ways in which this filtering operation can be applied in the whole process of curvature computation. Therefore, an extensive numerical study is performed to identify optimal settings for the patch-recovery operations with respect to computational cost and accuracy.Comment: 25 pages, 8 figures, submitted to Communications in Computational Physic

Comprehensive epigenetic landscape of rheumatoid arthritis fibroblast-like synoviocytes.

Epigenetics contributes to the pathogenesis of immune-mediated diseases like rheumatoid arthritis (RA). Here we show the first comprehensive epigenomic characterization of RA fibroblast-like synoviocytes (FLS), including histone modifications (H3K27ac, H3K4me1, H3K4me3, H3K36me3, H3K27me3, and H3K9me3), open chromatin, RNA expression and whole-genome DNA methylation. To address complex multidimensional relationship and reveal epigenetic regulation of RA, we perform integrative analyses using a novel unbiased method to identify genomic regions with similar profiles. Epigenomically similar regions exist in RA cells and are associated with active enhancers and promoters and specific transcription factor binding motifs. Differentially marked genes are enriched for immunological and unexpected pathways, with "Huntington's Disease Signaling" identified as particularly prominent. We validate the relevance of this pathway to RA by showing that Huntingtin-interacting protein-1 regulates FLS invasion into matrix. This work establishes a high-resolution epigenomic landscape of RA and demonstrates the potential for integrative analyses to identify unanticipated therapeutic targets

Simulator adaptation at runtime for component-based simulation software

Component-based simulation software can provide many opportunities to compose and configure simulators, resulting in an algorithm selection problem for the user of this software. This thesis aims to automate the selection and adaptation of simulators at runtime in an application-independent manner. Further, it explores the potential of tailored and approximate simulators - in this thesis concretely developed for the modeling language ML-Rules - supporting the effectiveness of the adaptation scheme.Komponenten-basierte Simulationssoftware kann viele Möglichkeiten zur Komposition und Konfiguration von Simulatoren bieten und damit zu einem Konfigurationsproblem für Nutzer dieser Software führen. Das Ziel dieser Arbeit ist die Entwicklung einer generischen und automatisierten Auswahl- und Adaptionsmethode für Simulatoren. Darüber hinaus wird das Potential von spezifischen und approximativen Simulatoren anhand der Modellierungssprache ML-Rules untersucht, welche die Effektivität des entwickelten Adaptionsmechanismus erhöhen können

ATMP: An Adaptive Tolerance-based Mixed-criticality Protocol for Multi-core Systems

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted ncomponent of this work in other works.The challenge of mixed-criticality scheduling is to keep tasks of higher criticality running in case of resource shortages caused by faults. Traditionally, mixedcriticality scheduling has focused on methods to handle faults where tasks overrun their optimistic worst-case execution time (WCET) estimate. In this paper we present the Adaptive Tolerance based Mixed-criticality Protocol (ATMP), which generalises the concept of mixed-criticality scheduling to handle also faults of other nature, like failure of cores in a multi-core system. ATMP is an adaptation method triggered by resource shortage at runtime. The first step of ATMP is to re-partition the task to the available cores and the second step is to optimise the utility at each core using the tolerance-based real-time computing model (TRTCM). The evaluation shows that the utility optimisation of ATMP can achieve a smoother degradation of service compared to just abandoning tasks

Optimal resource allocation in stochastic activity networks via the electromagnetism approach: a platform implementation in Java

An optimal resource allocation approach to stochastic multimodal projects had been previously developed by applying a Dynamic Programming model which proved to be very demanding computationally. A new approach, the Electromagnetism-like Mechanism, has also been adopted and implemented in Mat lab, to solve this problem. This paper presents the implementation of the Electromagnetism approach using an Object Oriented language, Java, and a distributed version to be run in a computer network, in order to take advantage of available computational resources.info:eu-repo/semantics/publishedVersio

Ranked Enumeration of MSO Logic on Words

In the last years, enumeration algorithms with bounded delay have attracted a lot of attention for several data management tasks. Given a query and the data, the task is to preprocess the data and then enumerate all the answers to the query one by one and without repetitions. This enumeration scheme is typically useful when the solutions are treated on the fly or when we want to stop the enumeration once the pertinent solutions have been found. However, with the current schemes, there is no restriction on the order how the solutions are given and this order usually depends on the techniques used and not on the relevance for the user. In this paper we study the enumeration of monadic second order logic (MSO) over words when the solutions are ranked. We present a framework based on MSO cost functions that allows to express MSO formulae on words with a cost associated with each solution. We then demonstrate the generality of our framework which subsumes, for instance, document spanners and adds ranking to them. The main technical result of the paper is an algorithm for enumerating all the solutions of formulae in increasing order of cost efficiently, namely, with a linear preprocessing phase and logarithmic delay between solutions. The novelty of this algorithm is based on using functional data structures, in particular, by extending functional Brodal queues to suit with the ranked enumeration of MSO on words