42 research outputs found

    Mapping Data Flow Models to the Palladio Component Model

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    Data Stream Operations as First-Class Entities in Palladio

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    Detecting Violations of Access Control and Information Flow Policies in Data Flow Diagrams

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    The security of software-intensive systems is frequently attacked. High fines or loss in reputation are potential consequences of not maintaining confidentiality, which is an important security objective. Detecting confidentiality issues in early software designs enables cost-efficient fixes. A Data Flow Diagram (DFD) is a modeling notation, which focuses on essential, functional aspects of such early software designs. Existing confidentiality analyses on DFDs support either information flow control or access control, which are the most common confidentiality mechanisms. Combining both mechanisms can be beneficial but existing DFD analyses do not support this. This lack of expressiveness requires designers to switch modeling languages to consider both mechanisms, which can lead to inconsistencies. In this article, we present an extended DFD syntax that supports modeling both, information flow and access control, in the same language. This improves expressiveness compared to related work and avoids inconsistencies. We define the semantics of extended DFDs by clauses in first-order logic. A logic program made of these clauses enables the automated detection of confidentiality violations by querying it. We evaluate the expressiveness of the syntax in a case study. We attempt to model nine information flow cases and six access control cases. We successfully modeled fourteen out of these fifteen cases, which indicates good expressiveness. We evaluate the reusability of models when switching confidentiality mechanisms by comparing the cases that share the same system design, which are three pairs of cases. We successfully show improved reusability compared to the state of the art. We evaluated the accuracy of confidentiality analyses by executing them for the fourteen cases that we could model. We experienced good accuracy

    Detecting Violations of Access Control and Information Flow Policies in Data Flow Diagrams

    Get PDF
    The security of software-intensive systems is frequently attacked. High fines or loss in reputation are potential consequences of not maintaining confidentiality, which is an important security objective. Detecting confidentiality issues in early software designs enables cost-efficient fixes. A Data Flow Diagram (DFD) is a modeling notation, which focuses on essential, functional aspects of such early software designs. Existing confidentiality analyses on DFDs support either information flow control or access control, which are the most common confidentiality mechanisms. Combining both mechanisms can be beneficial but existing DFD analyses do not support this. This lack of expressiveness requires designers to switch modeling languages to consider both mechanisms, which can lead to inconsistencies. In this article, we present an extended DFD syntax that supports modeling both, information flow and access control, in the same language. This improves expressiveness compared to related work and avoids inconsistencies. We define the semantics of extended DFDs by clauses in first-order logic. A logic program made of these clauses enables the automated detection of confidentiality violations by querying it. We evaluate the expressiveness of the syntax in a case study. We attempt to model nine information flow cases and six access control cases. We successfully modeled fourteen out of these fifteen cases, which indicates good expressiveness. We evaluate the reusability of models when switching confidentiality mechanisms by comparing the cases that share the same system design, which are three pairs of cases. We successfully show improved reusability compared to the state of the art. We evaluated the accuracy of confidentiality analyses by executing them for the fourteen cases that we could model. We experienced good accuracy

    Combined endoscopic and microsurgical approach for the drainage of a multisegmental thoracolumbar epidural abscess: illustrative case

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    BACKGROUND Spinal epidural abscess is a rare but serious infectious disease that can rapidly develop into a life-threatening condition. Therefore, the appropriate treatment is indispensable. Although conservative treatment is justifiable in certain cases, surgical treatment needs to be considered as an alternative early on because of complications such as (progressive) neurological deficits or sepsis. However, traditional surgical techniques usually include destructive approaches up to (multilevel) laminectomies. Such excessive approaches do have biomechanical effects potentially affecting the long-term outcomes. Therefore, minimally invasive approaches have been described as alternative strategies, including endoscopic approaches. OBSERVATIONS The authors describe a surgical technique involving a combination of two minimally invasive approaches (endoscopic and microsurgical) to drain a multisegmental (thoracolumbar) abscess using the physical phenomenon of continuous pressure difference to minimize collateral tissue damage. LESSONS The combination of minimally invasive approaches, including the endoscopic technique, may be an alternative in draining selected epidural abscesses while achieving a similar amount of abscess removal and causing less collateral approach damage in comparison with more traditional techniques

    Agrin isoforms and their role in synaptogenesis

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    Agrin is thought to mediate the motor neuron-induced aggregation of synaptic proteins on the surface of muscle fibers at neuromuscular junctions. Recent experiments provide direct evidence in support of this hypothesis, reveal the nature of agrin immunoreactivity at sites other than neuromuscular junctions, and have resulted in findings that are consistent with the possibility that agrin plays a role in synaptogenesis throughout the nervous system

    Effects of bifrontal transcranial direct current stimulation on brain glutamate levels and resting state connectivity: multimodal MRI data for the cathodal stimulation site

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    Transcranial direct current stimulation (tDCS) over prefrontal cortex (PFC) regions is currently proposed as therapeutic intervention for major depression and other psychiatric disorders. The in-depth mechanistic understanding of this bipolar and non-focal stimulation technique is still incomplete. In a pilot study, we investigated the effects of bifrontal stimulation on brain metabolite levels and resting state connectivity under the cathode using multiparametric MRI techniques and computational tDCS modeling. Within a double-blind cross-over design, 20 subjects (12 women, 23.7 ± 2~years) were randomized to active tDCS with standard bifrontal montage with the anode over the left dorsolateral prefrontal cortex (DLPFC) and the cathode over the right DLPFC. Magnetic resonance spectroscopy (MRS) was acquired before, during, and after prefrontal tDCS to quantify glutamate (Glu), Glu + glutamine (Glx) and gamma aminobutyric acid (GABA) concentration in these areas. Resting-state functional connectivity MRI (rsfcMRI) was acquired before and after the stimulation. The individual distribution of tDCS induced electric fields (efields) within the MRS voxel was computationally modelled using SimNIBS 2.0. There were no significant changes of Glu, Glx and GABA levels across conditions but marked differences in the course of Glu levels between female and male participants~were observed. Further investigation yielded a significantly stronger Glu reduction after active compared to sham stimulation~in female participants, but not in male participants. For rsfcMRI neither significant changes nor correlations with MRS data were observed. Exploratory analyses of the effect of efield intensity distribution on Glu changes showed distinct effects in different efield groups. Our findings are limited by the small sample size, but correspond to previously published results of cathodal tDCS. Future studies should address gender and efield intensity as moderators of tDCS induced effects

    Specific proteolytic cleavage of agrin regulates maturation of the neuromuscular junction

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    During the initial stage of neuromuscular junction (NMJ) formation, nerve-derived agrin cooperates with muscle-autonomous mechanisms in the organization and stabilization of a plaque-like postsynaptic specialization at the site of nerve-muscle contact. Subsequent NMJ maturation to the characteristic pretzel-like appearance requires extensive structural reorganization. We found that the progress of plaque-to-pretzel maturation is regulated by agrin. Excessive cleavage of agrin via transgenic overexpression of an agrin-cleaving protease, neurotrypsin, in motoneurons resulted in excessive reorganizational activity of the NMJs, leading to rapid dispersal of the synaptic specialization. By contrast, expression of cleavage-resistant agrin in motoneurons slowed down NMJ remodeling and delayed NMJ maturation. Neurotrypsin, which is the sole agrin-cleaving protease in the CNS, was excluded as the physiological agrin-cleaving protease at the NMJ, because NMJ maturation was normal in neurotrypsin-deficient mice. Together, our analyses characterize agrin cleavage at its proteolytic α- and β-sites by an as-yet-unspecified protease as a regulatory access for relieving the agrin-dependent constraint on endplate reorganization during NMJ maturation

    Prediction of grip and key pinch strength in 978 healthy subjects

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    <p>Abstract</p> <p>Background</p> <p>Hand strength is an important independent surrogate parameter to assess outcome and risk of morbidity and mortality. This study aimed to determine the predictive power of cofactors and to predict population-based normative grip and pinch strength.</p> <p>Methods</p> <p>A representative population survey was used as the basis for prediction analyses (n = 978). Bivariate relationships between grip/pinch strengths of the dominate hand were explored by means of all relevant mathematical functions to maximize prediction. The resulting best functions were combined into a multivariate regression.</p> <p>Results</p> <p>Polynoms (up to the third degree) were the best predictive functions. On the bivariate level, height was best correlated to grip (46.2% explained variance) and pinch strength (37.7% explained variance) in a linear relationship, followed by sex, age, weight, and occupational demand on the hand. Multivariate regression provided predicted values close to the empirical ones explaining 76.6% of the variance for grip strength and 67.7% for pinch strength.</p> <p>Conclusion</p> <p>The five easy-to-measure cofactors sex, age, body height, categorized occupational demand on the hand, and body weight provide a highly accurate prediction of normative grip and pinch strength.</p
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