The K-Server Dual and Loose Competitiveness for Paging

This paper has two results. The first is based on the surprising observation that the well-known ``least-recently-used'' paging algorithm and the ``balance'' algorithm for weighted caching are linear-programming primal-dual algorithms. This observation leads to a strategy (called ``Greedy-Dual'') that generalizes them both and has an optimal performance guarantee for weighted caching. For the second result, the paper presents empirical studies of paging algorithms, documenting that in practice, on ``typical'' cache sizes and sequences, the performance of paging strategies are much better than their worst-case analyses in the standard model suggest. The paper then presents theoretical results that support and explain this. For example: on any input sequence, with almost all cache sizes, either the performance guarantee of least-recently-used is O(log k) or the fault rate (in an absolute sense) is insignificant. Both of these results are strengthened and generalized in``On-line File Caching'' (1998).Comment: conference version: "On-Line Caching as Cache Size Varies", SODA (1991

Oat-enriched diet reduces inflammatory status assessed by circulating cell-derived microparticle concentrations in type 2 diabetes

This work was funded by the Chief Scientists Office of the Scottish Government by a joint grant to the University of the Highland and Islands, Grampian Health Board, Biomathematics and Statistics Scotland and the Rowett Institute of Nutrition and Health, University of Aberdeen. Additional support was provided by Provexis plc.Peer reviewedPublisher PD

A multi-site method to capture turnover in rare to common interactions in bipartite species networks

1. Ecological network structure is maintained by a generalist core of common species. However, rare species contribute substantially to both the species and functional diversity of networks. Capturing changes in species composition and interactions, measured as turnover, is central to understanding the contribution of rare and common species and their interactions. Due to a large contribution of rare interactions, the pairwise metrics used to quantify interaction turnover are, however, sensitive to compositional change in the interactions of, often rare, peripheral specialists rather than common generalists in the network. 2. Here we expand on pairwise interaction turnover using a multi-site metric that enables quantifying turnover in rare to common interactions (in terms of occurrence of interactions). The metric further separates this turnover into interaction turnover due to species turnover and interaction rewiring. 3. We demonstrate the application and value of this method using a host–parasitoid system sampled along gradients of environmental modification. 4. In the study system, both the type and amount of habitat needed to maintain interaction composition depended on the properties of the interactions considered, that is, from rare to common. The analyses further revealed the potential of host switching to prevent or delay species loss, and thereby buffer the system from perturbation. 5. Multi-site interaction turnover provides a comprehensive measure of network change that can, for example, detect ecological thresholds to habitat loss for rare to common interactions. Accurate description of turnover in common, in addition to rare, species and their interactions is particularly relevant for understanding how network structure and function can be maintained

Using scale–area curves to quantify the distribution, abundance and range expansion potential of an invasive species

Aim: Invasive species distribution and abundance data are essential for management decisions on mitigating impacts but is seldom available. Here, we use scale–area curves to assess the distribution, abundance and consequent management implications of an invasive plant (Acacia longifolia) within selected occupancy grid cells, spread across regional ranges and representing the full national extent. We determine whether occupancy patterns are explained by climatic suitability or range structure and identify areas where A. longifolia can still be regarded as an important invasive based on contiguous occupancy. Location: South Africa including the Fynbos, Thicket, Savanna and Grassland biomes. Methods: The quarter degree occupancy of A. longifolia was used to select core, edge, and climatically unsuitable grid cells within different regions of the national range. Cells were surveyed across a linear resolution from 25 km to 2.5 m allowing the first multi-scales description of an invasive species’ space-filling properties. Patterns from grid cells in turn were viewed regionally to describe regional variation in spatial structure. Results: In regions with contiguous areas of favourable habitat, scale–area curves indicated greater occupancy in core than edge areas, whereas patterns were reversed when suitable areas were more fragmented. Also, at times climatically suitable areas were unoccupied, while unsuitable areas were occupied. Within cells, occupancy was well explained by the presence of fynbos vegetation types, while nationally, contiguous occupancy was almost exclusive to the Fynbos Biome. Main conclusions: Scale–area curves can advance the understanding of biological invasions and invasive plant distributions. Here, we detected potential areas of invasive concern, plus differences in abundance and distribution patterns, and associated correlates, at landscape and national scales. As there was no general relationship between range position or climatic suitability and A. longifolia’s spatial structure, we propose habitat suitability as an alternative explanation which, in turn, suggests limited range expansion potential.Centre of Excellence for Invasion Biolog

Comparison of Langevin and Markov channel noise models for neuronal signal generation

The stochastic opening and closing of voltage-gated ion channels produces noise in neurons. The effect of this noise on the neuronal performance has been modelled using either approximate or Langevin model, based on stochastic differential equations or an exact model, based on a Markov process model of channel gating. Yet whether the Langevin model accurately reproduces the channel noise produced by the Markov model remains unclear. Here we present a comparison between Langevin and Markov models of channel noise in neurons using single compartment Hodgkin-Huxley models containing either $Na^{+}$ and $K^{+}$, or only $K^{+}$ voltage-gated ion channels. The performance of the Langevin and Markov models was quantified over a range of stimulus statistics, membrane areas and channel numbers. We find that in comparison to the Markov model, the Langevin model underestimates the noise contributed by voltage-gated ion channels, overestimating information rates for both spiking and non-spiking membranes. Even with increasing numbers of channels the difference between the two models persists. This suggests that the Langevin model may not be suitable for accurately simulating channel noise in neurons, even in simulations with large numbers of ion channels

Risk Prediction Models for Colorectal Cancer Incorporating Common Genetic Variants: A Systematic Review.

Colorectal cancer screening reduces colorectal cancer incidence and mortality. Risk models based on phenotypic variables have relatively good discrimination in external validation and may improve efficiency of screening. Models incorporating genetic variables may perform better. In this review, we updated our previous review by searching Medline and EMBASE from the end date of that review (January 2014) to February 2019 to identify models incorporating at least one SNP and applicable to asymptomatic individuals in the general population. We identified 23 new models, giving a total of 29. Of those in which the SNP selection was on the basis of published genome-wide association studies, in external or split-sample validation the AUROC was 0.56 to 0.57 for models that included SNPs alone, 0.61 to 0.63 for SNPs in combination with other risk factors, and 0.56 to 0.70 when age was included. Calibration was only reported for four. The addition of SNPs to other risk factors increases discrimination by 0.01 to 0.06. Public health modeling studies suggest that, if determined by risk models, the range of starting ages for screening would be several years greater than using family history alone. Further validation and calibration studies are needed alongside modeling studies to assess the population-level impact of introducing genetic risk-based screening programs