272 research outputs found

    When equity matters for marital stability: Comparing German and U.S. couples

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    none3siComparing West Germany and the U.S., we analyze the association between equity—in terms of the relative gender division of paid and unpaid work hours—and the risk of marriage dissolution. Our aim is to identify under what conditions equity influences couple stability. We apply event-history analysis to marriage histories using data from the German Socio-Economic Panel for West Germany and the Panel Study of Income Dynamics for the U.S. for the period 1986–2009/10. For the U.S., we find that deviation from equity is particularly destabilizing when the wife underbenefits, especially when both partners’ paid work hours are similar. In West Germany, equity is less salient. Instead, we find that the male breadwinner model remains the single most stable couple arrangement.mixedBellani D.; Esping Andersen G.; Pessin L.Bellani D.; Esping Andersen G.; Pessin L

    NCS-1 Inhibits insulin stimulated GLUT4 translocation in 3T3L1 adipocytes through a phosphatidylinositol 4-kinase dependent pathway

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    Expression of NCS-1 (neuronal calcium sensor-1, also termed frequenin) in 3T3L1 adipocytes strongly inhibited insulin-stimulated translocation of GLUT4 and insulin-responsive aminopeptidase. The effect of NCS-1 was specific for GLUT4 and the insulin-responsive aminopeptidase translocation as there was no effect on the trafficking of the cation-independent mannose 6-phosphate receptor or the GLUT1 glucose transporter isoform. Moreover, NCS-1 showed partial colocalization with GLUT4-EGFP in the perinuclear region. The inhibitory action of NCS-1 was independent of calcium sequestration since neither treatment with ionomycin nor endothelin-1, both of which elevated the intracellular calcium concentration, restored insulin-stimulated GLUT4 translocation. Furthermore, NCS-1 did not alter the insulin-stimulated protein kinase B (PKB/Akt) phosphorylation or the recruitment of Cbl to the plasma membrane. In contrast, expression of the NCS-1 effector phosphatidylinositol 4-kinase (PI 4-kinase) inhibited insulin-stimulated GLUT4 translocation, whereas co-transfection with an inactive PI 4-kinase mutant prevented the NCS-1-induced inhibition. These data demonstrate that PI 4-kinase functions to negatively regulate GLUT4 translocation through its interaction with NCS-1

    Towards Safer Industrial Serial Networks: An Expert System Framework for Anomaly Detection

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    Cyber security is a topic of increasing relevance in relation to industrial networks. The higher intensity and intelligent use of data pushed by smart technology (Industry 4.0) together with an augmented integration between the operational technology (production) and the information technology (business) parts of the network have considerably raised the level of vulnerabilities. On the other hand, many industrial facilities still use serial networks as underlying communication system, and they are notoriously limited from a cyber security perspective since protection mechanisms available for TCP/IP communication do not apply. Therefore, an attacker gaining access to a serial network can easily control the industrial components, potentially causing catastrophic incidents, jeopardizing assets and human lives. This study proposes a framework to act as an anomaly detection system (ADS) for industrial serial networks. It has three ingredients: an unsupervised K-means component to analyse message content, a knowledge-based expert system component to analyse message metadata, and a voting process to generate alerts for security incidents, anomalous states, and faults. The framework was evaluated using the Profibus-DP, a network simulator which implements a serial bus system. Results for the simulated traffic were promising: 99.90% for accuracy, 99,64% for precision, and 99.28% for F1-Score. They indicate feasibility of the framework applied to serial-based industrial networks

    Cybersecurity in Industrial Networks: Artificial Intelligence Techniques Applied to Intrusion Detection Systems

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    Industrial control systems (ICS) operate on serial based networks which lack proper security safeguards by design. They are also becoming more integrated to corporate networks, creating new vulnerabilities which expose ICS networks to increasing levels of risk with potentially significant impact. Despite those risks, only a few mechanisms have been suggested and are available in practice as cybersecurity safeguards for the ICS network layer, maybe because they might not be commercially viable. Intrusion detection systems (IDS) are typically deployed in the corporate networks to protect against attacks since they are based on TCP/IP. However, IDS are not used in serial based ICS networks yet. This study examines and compares modern Artificial Intelligence (AI) techniques applied in IDS that are potentially useful for serial-based ICS networks. The results showed that current AI-based IDS methods are viable in such networks. A mix of AI techniques would be the best way forward to detect known attacks via rules and novel attacks, not previously mapped, via supervised and unsupervised techniques. Despite these strategies’ limited use in serial-based networks, their adoption could significantly strengthen cybersecurity of ICS networks
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