Dynamic Set Intersection

Consider the problem of maintaining a family $F$ of dynamic sets subject to insertions, deletions, and set-intersection reporting queries: given $S,S'\in F$, report every member of $S\cap S'$ in any order. We show that in the word RAM model, where $w$ is the word size, given a cap $d$ on the maximum size of any set, we can support set intersection queries in $O(\frac{d}{w/\log^2 w})$ expected time, and updates in $O(\log w)$ expected time. Using this algorithm we can list all $t$ triangles of a graph $G=(V,E)$ in $O(m+\frac{m\alpha}{w/\log^2 w} +t)$ expected time, where $m=|E|$ and $\alpha$ is the arboricity of $G$. This improves a 30-year old triangle enumeration algorithm of Chiba and Nishizeki running in $O(m \alpha)$ time. We provide an incremental data structure on $F$ that supports intersection {\em witness} queries, where we only need to find {\em one} $e\in S\cap S'$. Both queries and insertions take O\paren{\sqrt \frac{N}{w/\log^2 w}} expected time, where $N=\sum_{S\in F} |S|$. Finally, we provide time/space tradeoffs for the fully dynamic set intersection reporting problem. Using $M$ words of space, each update costs $O(\sqrt {M \log N})$ expected time, each reporting query costs $O(\frac{N\sqrt{\log N}}{\sqrt M}\sqrt{op+1})$ expected time where $op$ is the size of the output, and each witness query costs $O(\frac{N\sqrt{\log N}}{\sqrt M} + \log N)$ expected time.Comment: Accepted to WADS 201

Explicit Solution of the Time Domain Volume Integral Equation Using a Stable Predictor-Corrector Scheme

An explicit marching-on-in-time (MOT) scheme for solving the time domain volume integral equation is presented. The proposed method achieves its stability by employing, at each time step, a corrector scheme, which updates/corrects fields computed by the explicit predictor scheme. The proposedmethod is computationally more efficient when compared to the existing filtering techniques used for the stabilization of explicit MOT schemes. Numerical results presented in this paper demonstrate that the proposed method maintains its stability even when applied to the analysis of electromagnetic wave interactions with electrically large structures meshed using approximately half a million discretization elements

A discrete element method representation of an anisotropic elastic continuum

A method for modeling cubically anisotropic elasticity within the discrete element method is presented. The discrete element method (DEM) is an approach originally intended for modeling granular materials (sand, soil, and powders); however, recent developments have usefully extended it to model stochastic mechanical processes in monolithic solids which, to date, have been assumed to be elastically isotropic. The method presented here for efficiently capturing cubic elasticity in DEM is an important prerequisite for further extending DEM to capture the influence of elastic anisotropy on the mechanical response of polycrystals, composites, etc. The system demonstrated here uses a directionally assigned stiffness in the bonds between adjacent elements and includes separate schemes for achieving anisotropy with Zener ratios greater and smaller than one. The model framework is presented along with an analysis of the accessible space of elastic properties that can be modeled and an artificial neural network interpolation scheme for mapping input parameters to model elastic behavior

A molecular target for viral killer toxin: TOK1 potassium channels.

Killer strains of S. cerevisiae harbor double-stranded RNA viruses and secrete protein toxins that kill virus-free cells. The K1 killer toxin acts on sensitive yeast cells to perturb potassium homeostasis and cause cell death. Here, the toxin is shown to activate the plasma membrane potassium channel of S. cerevisiae, TOK1. Genetic deletion of TOK1 confers toxin resistance; overexpression increases susceptibility. Cells expressing TOK1 exhibit toxin-induced potassium flux; those without the gene do not. K1 toxin acts in the absence of other viral or yeast products: toxin synthesized from a cDNA increases open probability of single TOK1 channels (via reversible destabilization of closed states) whether channels are studied in yeast cells or X. laevis oocytes

Si elegans: a computational model of C. elegans muscle response to light

It has long been the goal of computational neuroscientists to understand animal nervous systems, but their vast complexity has made it very difficult to fully understand even basic functions such as movement. The C. elegans nematode offers the opportunity to study a fully described connectome and link neural network to behaviour. In this paper a model of the responses of the body wall muscle in C. elegans to a random light stimulus is presented. An algorithm has been developed that tracks synapses in the nematode nervous system from the stimulus in the phototaxis sensory neurons to the muscles cells. A linear second order model was used to calculate the isometric force in each of the C. elegans body wall muscle cells. The isometric force calculated resembles that of previous investigations in muscle modelling

Colored Non-Crossing Euclidean Steiner Forest

Given a set of $k$-colored points in the plane, we consider the problem of finding $k$ trees such that each tree connects all points of one color class, no two trees cross, and the total edge length of the trees is minimized. For $k=1$, this is the well-known Euclidean Steiner tree problem. For general $k$, a $k\rho$-approximation algorithm is known, where $\rho \le 1.21$ is the Steiner ratio. We present a PTAS for $k=2$, a $(5/3+\varepsilon)$-approximation algorithm for $k=3$, and two approximation algorithms for general~$k$, with ratios $O(\sqrt n \log k)$ and $k+\varepsilon$

Cytolethal distending toxin (CDT)-negative Campylobacter jejuni strains and anti-CDT neutralising antibodies induced during human infection but not chicken colonisation

The cytolethal distending toxin (CDT) of Campylobacter jejuni was detectable, using an in vitro assay, in most but not all of 24 strains tested. The reason for the absence of toxin activity in these naturally occurring CDT-negative C. jejuni strains was then investigated at the genetic level. CDT is encoded by three highly conserved genes, cdtA, -B, and -C. In the CDT-negative strains, two types of mutation were identified. The CDT activities of C. jejuni strains possessing both types of mutation were successfully complemented with the functional genes of C. jejuni 11168. The first type of mutation comprised a 667-bp deletion across cdtA and cdtB and considerable degeneration in the remainder of the cdt locus. Using a PCR technique to screen for this deletion, this mutation occurred in fewer than 3% of 147 human, veterinary, and environmental strains tested. The second type of mutation involved at least four nonsynonymous nucleotide changes, but only the replacement of proline with serine at CdtB position 95 was considered important for CDT activity. This was confirmed by site-directed mutagenesis. This type of mutation also occurred in fewer than 3% of strains as determined using a LightCycler biprobe assay. The detection of two CDT-negative clinical isolates raised questions about the role of CDT in some cases of human campylobacteriosis. To determine if anti-CDT antibodies are produced in human infection, a toxin neutralization assay was developed and validated using rabbit antisera. Pooled human sera from infected patients neutralized the toxin, indicating expression and immunogenicity during infection. However, no neutralizing antibodies were detected in colonized chickens despite the expression of CDT in the avian gut as indicated by reverse transcription-PCR

Injectable polypeptide hydrogels via methionine modification for neural stem cell delivery.

Injectable hydrogels with tunable physiochemical and biological properties are potential tools for improving neural stem/progenitor cell (NSPC) transplantation to treat central nervous system (CNS) injury and disease. Here, we developed injectable diblock copolypeptide hydrogels (DCH) for NSPC transplantation that contain hydrophilic segments of modified l-methionine (Met). Multiple Met-based DCH were fabricated by post-polymerization modification of Met to various functional derivatives, and incorporation of different amino acid comonomers into hydrophilic segments. Met-based DCH assembled into self-healing hydrogels with concentration and composition dependent mechanical properties. Mechanical properties of non-ionic Met-sulfoxide formulations (DCHMO) were stable across diverse aqueous media while cationic formulations showed salt ion dependent stiffness reduction. Murine NSPC survival in DCHMO was equivalent to that of standard culture conditions, and sulfoxide functionality imparted cell non-fouling character. Within serum rich environments in vitro, DCHMO was superior at preserving NSPC stemness and multipotency compared to cell adhesive materials. NSPC in DCHMO injected into uninjured forebrain remained local and, after 4 weeks, exhibited an immature astroglial phenotype that integrated with host neural tissue and acted as cellular substrates that supported growth of host-derived axons. These findings demonstrate that Met-based DCH are suitable vehicles for further study of NSPC transplantation in CNS injury and disease models

Strain- and Adsorption-Dependent Electronic States and Transport or Localization in Graphene

The chapter generalizes results on influence of uniaxial strain and adsorption on the electron states and charge transport or localization in graphene with different configurations of imperfections (point defects): resonant (neutral) adsorbed atoms either oxygen- or hydrogen-containing molecules or functional groups, vacancies or substitutional atoms, charged impurity atoms or molecules, and distortions. To observe electronic properties of graphene-admolecules system, we applied electron paramagnetic resonance technique in a broad temperature range for graphene oxides as a good basis for understanding the electrotransport properties of other active carbons. Applied technique allowed observation of possible metal-insulator transition and sorption pumping effect as well as discussion of results in relation to the granular metal model. The electronic and transport properties are calculated within the framework of the tight-binding model along with the Kubo-Greenwood quantum-mechanical formalism. Depending on electron density and type of the sites, the conductivity for correlated and ordered adsorbates is found to be enhanced in dozens of times as compared to the cases of their random distribution. In case of the uniaxially strained graphene, the presence of point defects counteracts against or contributes to the band-gap opening according to their configurations. The band-gap behaviour is found to be nonmonotonic with strain in case of a simultaneous action of defect ordering and zigzag deformation. The amount of localized charge carriers (spins) is found to be correlated with the content of adsorbed centres responsible for the formation of potential barriers and, in turn, for the localization effects. Physical and chemical states of graphene edges, especially at a uniaxial strain along one of them, play a crucial role in electrical transport phenomena in graphene-based materials.Comment: 16 pages, 10 figure

Avoiding the misuse of BLUP in behavioral ecology

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Having recognized that variation around the population-level “Golden Mean” of labile traits contains biologically meaningful information, behavioural ecologists have focused increasingly on exploring the causes and consequences of individual variation in behaviour. These are exciting new directions for the field, assisted in no small part by the adoption of mixed-effects modelling techniques that enable the partitioning of among- and within-individual behavioural variation. It has become commonplace to extract predictions of individual random effects from such models for use in subsequent analyses (for example, between a personality trait and other individual traits such as cognition, physiology, or fitness-related measures). However, these predictions are made with large amounts of error that is not carried forward, rendering further tests susceptible to spurious P values from these individual-level point estimates. We briefly summarize the problems with such statistical methods that are used regularly by behavioural ecologists, and highlight the robust solutions that exist within the mixed model framework, providing tutorials to aid in their implementation.This work was supported by a Biotechnology and Biological Sciences Research Council grant (BB/L022656/1