Discovering Network Topology in the Presence of Byzantine Faults

We pose and study the problem of Byzantine-robust topology discovery in an arbitrary asynchronous network. The problem is an abstraction of fault-tolerant routing. We formally state the weak and strong versions of the problem. The weak version requires that either each node discovers the topology of the network or at least one node detects the presence of a faulty node. The strong version requires that each node discovers the topology regardless of faults. We focus on noncryptographic solutions to these problems. We explore their bounds. We prove that the weak topology discovery problem is solvable only if the connectivity of the network exceeds the number of faults in the system. Similarly, we show that the strong version of the problem is solvable only if the network connectivity is more than twice the number of faults. We present solutions to both versions of the problem. The presented algorithms match the established graph connectivity bounds. The algorithms do not require the individual nodes to know either the diameter or the size of the network. The message complexity of both programs is low polynomial with respect to the network size. We describe how our solutions can be extended to add the property of termination, handle topology changes, and perform neighborhood discovery.     

Filtering with clouds

Selecting a particular kernel to filter a given digital signal can be a difficult task. One solution to solve this difficulty is to filter with multiple kernels. However, this solution can be computationally costly. Using the fact that most kernels used for low-pass signal filtering can be assimilated to probability distributions (or linear combinations of probability distributions), we propose to model sets of kernels by convex sets of probabilities. In particular, we use specific representations that allow us to perform a robustness analysis without added computational costs. The result of this analysis is an interval-valued filtered signal. Among such representations are possibility distributions, from which have been defined maxitive kernels. However, one drawback of maxitive kernels is their limited expressiveness. In this paper, we extend this approach by considering another representation of convex sets of probabilities, namely clouds, from which we define cloudy kernels. We show that cloudy kernels are able to represent sets of kernels whose bandwidth is upper and lower bounded, and can therefore be used as a good trade-off between the classical and the maxitive approach, avoiding some of their respective shortcomings without making computations prohibitive. Finally, the benefits of using cloudy filters is demonstrated through some experiments.     

Effect of Helium Elasticity on Torsional Oscillator Measurements

In 2004 Kim and Chan performed a torsional oscillator measurement of the rotational inertia of solid helium-4. They found frequency changes which were interpreted in terms of a non-classical rotational inertia, that is a partial superfluidity or ??supersolidity?? of solid helium-4. Since then there have been many further studies using various versions of this technique. One important question that arises in these experiments is the possible effect on the oscillator frequency of changes in the elasticity of the solid helium; this can produce a change in frequency that adds to any effect due to superfluidity. In this paper we give a general discussion of the effect of changes in elasticity on the oscillator frequency and consider how the magnitude of the effect is influenced by the oscillator design. Our results should help make it possible to discriminate between frequency changes due to changes in elasticity and changes due to supersolidity.     

Modelling the effect of carbon on deformation behaviour of twinning induced plasticity steels

In this article, a physical model describing the deformation behaviour of Twinning Induced Plasticity (TWIP) steels has been extended to include the effect of carbon content. The experimental validation and the analysis show that carbon mainly controls the maximum number of dislocations piled up at the twin boundary, resulting in the increase of back-stresses (i.e. kinematic hardening) and therefore the work hardening rate. This explanation seems to be in agreement with recent TEM observations.     

Increased Sulfur Precursors and Volatiles Production by the Leek <Emphasis Type="Italic">Allium porrum</Emphasis> in Response to Specialist Insect Attack

To defend themselves against herbivory, plants use a variety of direct and indirect strategies involving induced increases in secondary substances. Species of the Allium genus (Alliaceae), such as the leek Allium porrum (L.), produce nonprotein sulfur amino acids derived from cysteine, i.e., alk(en)yl-cysteine sulfoxides that are precursors of volatile thiosulfinates and disulfides. These defend most species including the specialist leek moth, Acrolepiopsis assectella. We determined by measuring the increase in the sulfur precursor propyl-cysteine sulfoxide (PCSO) if production of this precursor is induced in response to moth attack and mechanical wounding. The concentration of PCSO was determined by HPLC in 2- or 6-mo-old leeks after attacks of various intensity either by the specialist leek moth or by a generalist moth, Agrotis ipsilon. Injury-induced release of sulfur volatiles was measured by GC/MS after the attacks. Results showed an increase in the production of sulfur compounds in both the precursor and volatile form, occurring only in association with intensive attacks by leek moths. The increase in sulfur precursors also led to an increase in the release of sulfur volatiles. This induced response may provide an effective defense strategy against the plant’s main natural enemy, both directly and indirectly by attracting entomophagous insects.     

Topographical variations of pulmonary and pleural asbestos fiber concentrations in variously exposed subjects

The authors study three groups of subjects with different exposures to asbestos dust. The lung content in asbestos fibres is measured by optical and electron microscopy, the latter technique revealing preferential concentration of asbestos fibres in the peripheral zones of the lung, in particular in individuals subject to a moderate degree of professional exposure.     

High-frequency homogenization for checkerboard structures: defect modes, ultrarefraction, and all-angle negative refraction

The counterintuitive properties of photonic crystals, such as all-angle negative refraction (AANR) [J. Mod. Opt.34, 1589 (1987)] and high-directivity via ultrarefraction [Phys. Rev. Lett.89, 213902 (2002)], as well as localized defect modes, are known to be associated with anomalous dispersion near the edge of stop bands. We explore the implications of an asymptotic approach to uncover the underlying structure behind these phenomena. Conventional homogenization is widely assumed to be ineffective for modeling photonic crystals as it is limited to low frequencies when the wavelength is long relative to the microstructural length scales. Here a recently developed high-frequency homogenization (HFH) theory [Proc. R. Soc. Lond. A466, 2341 (2010)] is used to generate effective partial differential equations on a macroscale, which have the microscale embedded within them through averaged quantities, for checkerboard media. For physical applications, ultrarefraction is well described by an equivalent homogeneous medium with an effective refractive index given by the HFH procedure, the decay behavior of localized defect modes is characterized completely, and frequencies at which AANR occurs are all determined analytically. We illustrate our findings numerically with a finite-size checkerboard using finite elements, and we emphasize that conventional effective medium theory cannot handle such high frequencies. Finally, we look at light confinement effects in finite-size checkerboards behaving as open resonators when the condition for AANR is met [J. Phys. Condens. Matter 15, 6345 (2003)].