The dynamics of murid gammaherpesvirus 4 within wild, sympatric populations of bank voles and wood mice

Murid gammaherpesvirus 4 (MuHV-4) is widely used as a small animal model for understanding gammaherpesvirus infections in man. However, there have been no epidemiological studies of the virus in wild populations of small mammals. As MuHV-4 both infects cells associated with the respiratory and immune systems and attempts to evade immune control via various molecular mechanisms, infection may reduce immunocompetence with potentially serious fitness consequences for individuals. Here we report a longitudinal study of antibody to MuHV-4 in a mixed assemblage of bank voles (Clethrionomys glareolus) and wood mice (Apodemus sylvaticus) in the UK. The study was conducted between April 2001 and March 2004. Seroprevalence was higher in wood mice than bank voles, supporting earlier work that suggested wood mice were the major host even though the virus was originally isolated from a bank vole. Analyses of both the probability of having antibodies and the probability of initial seroconversion indicated no clear seasonal pattern or relationship with host density. Instead, infection risk was most closely associated with individual characteristics, with heavier males having the highest risk. This may reflect individual variation in susceptibility, potentially related to variability in the ability to mount an effective immune response.

Validating the use of intrinsic markers in body feathers to identify inter‑individual differences in non‑breeding areas of northern fulmars

Many wildlife studies use chemical analyses to explore spatio-temporal variation in diet, migratory patterns and contaminant exposure. Intrinsic markers are particularly valuable for studying non-breeding marine predators, when direct methods of investigation are rarely feasible. However, any inferences regarding foraging ecology are dependent upon the time scale over which tissues such as feathers are formed. In this study, we validate the use of body feathers for studying non-breeding foraging patterns in a pelagic seabird, the northern fulmar. Analysis of carcasses of successfully breeding adult fulmars indicated that body feathers moulted between September and March, whereas analyses of carcasses and activity patterns suggested that wing feather and tail feather moult occurred during more restricted periods (September to October and September to January, respectively). By randomly sampling relevant body feathers, average values for individual birds were shown to be consistent. We also integrated chemical analyses of body feather with geolocation tracking data to demonstrate that analyses of δ13C and δ15N values successfully assigned 88 % of birds to one of two broad wintering regions used by breeding adult fulmars from a Scottish study colony. These data provide strong support for the use of body feathers as a tool for exploring non-breeding foraging patterns and diet in wide-ranging, pelagic seabirds.

Face Recognition in the Scrambled Domain via Salience-Aware Ensembles of Many Kernels

With the rapid development of internet-of-things (IoT), face scrambling has been proposed for privacy protection during IoT-targeted image/video distribution. Consequently in these IoT applications, biometric verification needs to be carried out in the scrambled domain, presenting significant challenges in face recognition. Since face models become chaotic signals after scrambling/encryption, a typical solution is to utilize traditional data-driven face recognition algorithms. While chaotic pattern recognition is still a challenging task, in this paper we propose a new ensemble approach – Many-Kernel Random Discriminant Analysis (MK-RDA) to discover discriminative patterns from chaotic signals. We also incorporate a salience-aware strategy into the proposed ensemble method to handle chaotic facial patterns in the scrambled domain, where random selections of features are made on semantic components via salience modelling. In our experiments, the proposed MK-RDA was tested rigorously on three human face datasets: the ORL face dataset, the PIE face dataset and the PUBFIG wild face dataset. The experimental results successfully demonstrate that the proposed scheme can effectively handle chaotic signals and significantly improve the recognition accuracy, making our method a promising candidate for secure biometric verification in emerging IoT applications.

Variable Window Power Spectral Density Attack

Side channel attacks permit the recovery of the secret key held within a cryptographic device. This paper presents a new EM attack in the frequency domain, using a power spectral density analysis that permits the use of variable spectral window widths for each trace of the data set and demonstrates how this attack can therefore overcome both inter-and intra-round random insertion type countermeasures. We also propose a novel re-alignment method exploiting the minimal power markers exhibited by electromagnetic emanations. The technique can be used for the extraction and re-alignment of round data in the time domain.