Location-Quality-aware Policy Optimisation for Relay Selection in Mobile Networks

Relaying can improve the coverage and performance of wireless access networks. In presence of a localisation system at the mobile nodes, the use of such location estimates for relay node selection can be advantageous as such information can be collected by access points in linear effort with respect to number of mobile nodes (while the number of links grows quadratically). However, the localisation error and the chosen update rate of location information in conjunction with the mobility model affect the performance of such location-based relay schemes; these parameters also need to be taken into account in the design of optimal policies. This paper develops a Markov model that can capture the joint impact of localisation errors and inaccuracies of location information due to forwarding delays and mobility; the Markov model is used to develop algorithms to determine optimal location-based relay policies that take the aforementioned factors into account. The model is subsequently used to analyse the impact of deployment parameter choices on the performance of location-based relaying in WLAN scenarios with free-space propagation conditions and in an measurement-based indoor office scenario.Comment: Accepted for publication in ACM/Springer Wireless Network

Model-Free Detection of Cyberattacks on Voltage Control in Distribution Grids

Incorporating information and communication technology in the operation of the electricity grid is undoubtedly contributing to a more cost-efficient, controllable, and flexible power grid. Although this technology is promoting flexibility and convenience, its integration with the electricity grid is rendering this critical infrastructure inherently vulnerable to cyberattacks that have potential to cause large-scale and far-reaching damage. In light of the growing need for a resilient smart grid, developing suitable security mechanisms has become a pressing matter. In this work, we investigate the effectiveness of a model-free state-of-the-art attack-detection method recently proposed by the cybersecurity community in detecting common types of cyberattacks on voltage control in distribution grids. Experimental results show that, by monitoring raw controller and smart-meter data in real time, it is possible to detect denial of service, replay, and integrity attacks, thus contributing to a resilient and more secure grid

Combining electro- and magnetoencephalography data using directional archetypal analysis

Metastable microstates in electro- and magnetoencephalographic (EEG and MEG) measurements are usually determined using modified k-means accounting for polarity invariant states. However, hard state assignment approaches assume that the brain traverses microstates in a discrete rather than continuous fashion. We present multimodal, multisubject directional archetypal analysis as a scale and polarity invariant extension to archetypal analysis using a loss function based on the Watson distribution. With this method, EEG/MEG microstates are modeled using subject- and modality-specific archetypes that are representative, distinct topographic maps between which the brain continuously traverses. Archetypes are specified as convex combinations of unit norm input data based on a shared generator matrix, thus assuming that the timing of neural responses to stimuli is consistent across subjects and modalities. The input data is reconstructed as convex combinations of archetypes using a subject- and modality-specific continuous archetypal mixing matrix. We showcase the model on synthetic data and an openly available face perception event-related potential data set with concurrently recorded EEG and MEG. In synthetic and unimodal experiments, we compare our model to conventional Euclidean multisubject archetypal analysis. We also contrast our model to a directional clustering model with discrete state assignments to highlight the advantages of modeling state trajectories rather than hard assignments. We find that our approach successfully models scale and polarity invariant data, such as microstates, accounting for intersubject and intermodal variability. The model is readily extendable to other modalities ensuring component correspondence while elucidating spatiotemporal signal variability

Human Herpesvirus 6B

Abstract Infection with human herpesvirus (HHV)-6B alters cell cycle progression and stabilizes tumor suppressor protein p53. In this study, we have analyzed the activity of p53 after stimulation with p53-dependent and -independent DNA damaging agents during HHV-6B infection. Microarray analysis, Western blotting and confocal microscopy demonstrated that HHV-6B-infected cells were resistant to p53-dependent arrest and cell death after c irradiation in both permissive and nonpermissive cell lines. In contrast, HHV-6B-infected cells died normally through p53-independet DNA damage induced by UV radiation. Moreover, we identified a viral protein involved in inhibition of p53 during HHV-6B-infection. The protein product from the U19 ORF was able to inhibit p53-dependent signaling following c irradiation in a manner similar to that observed during infection. Similar to HHV-6B infection, overexpression of U19 failed to rescue the cells from p53-independent death induced by UV radiation. Hence, infection with HHV-6B specifically blocks DNA damage-induced cell death associated with p53 without inhibiting the p53-independent cell death response. This block in p53 function can in part be ascribed to the activities of the viral U19 protein

Inhibition of p53-Dependent, but Not p53-Independent, Cell Death by U19 Protein from Human Herpesvirus 6B

Infection with human herpesvirus (HHV)-6B alters cell cycle progression and stabilizes tumor suppressor protein p53. In this study, we have analyzed the activity of p53 after stimulation with p53-dependent and -independent DNA damaging agents during HHV-6B infection. Microarray analysis, Western blotting and confocal microscopy demonstrated that HHV-6B-infected cells were resistant to p53-dependent arrest and cell death after γ irradiation in both permissive and non-permissive cell lines. In contrast, HHV-6B-infected cells died normally through p53-independet DNA damage induced by UV radiation. Moreover, we identified a viral protein involved in inhibition of p53 during HHV-6B-infection. The protein product from the U19 ORF was able to inhibit p53-dependent signaling following γ irradiation in a manner similar to that observed during infection. Similar to HHV-6B infection, overexpression of U19 failed to rescue the cells from p53-independent death induced by UV radiation. Hence, infection with HHV-6B specifically blocks DNA damage-induced cell death associated with p53 without inhibiting the p53-independent cell death response. This block in p53 function can in part be ascribed to the activities of the viral U19 protein