Running Experiments with Confidence and Sanity

Analyzing data from large experimental suites is a daily task for anyone doing experimental algorithmics. In this paper we report on several approaches we tried for this seemingly mundane task in a similarity search setting, reflecting on the challenges it poses. We conclude by proposing a workflow, which can be implemented using several tools, that allows to analyze experimental data with confidence. The extended version of this paper and the support code are provided at https://github.com/Cecca/running-experiments

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

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

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

Distribution of TT virus (TTV), TTV-like minivirus, and related viruses in humans and nonhuman primates

AbstractTT virus (TTV) and TTV-like minivirus (TLMV) are small DNA viruses with single-stranded, closed circular, antisense genomes infecting man. Despite their extreme sequence heterogeneity (>50%), a highly conserved region in the untranslated region (UTR) allows both viruses to be amplified by polymerase chain reaction (PCR). TTV/TLMV infection was detected in 88 of 100 human plasma samples; amplified sequences were differentiated into TTV and TLMV by analysis of melting profiles, showing that both viruses were similarly prevalent. PCR with UTR primers also detected frequent infection with TTV/TLMV-related viruses in a wide range of apes (chimpanzees, gorillas, orangutans, gibbons) and African monkey species (mangabeys, drills, mandrills). These findings support the hypothesis for the co-evolution of TTV-like viruses with their hosts over the period of primate speciation, potentially analogous to the evolution of primate herpesviruses

Kuksa*: Self-Adaptive Microservices in Automotive Systems

In pervasive dynamic environments, vehicles connect to other objects to send operational data and receive updates so that vehicular applications can provide services to users on demand. Automotive systems should be self-adaptive, thereby they can make real-time decisions based on changing operating conditions. Emerging modern solutions, such as microservices could improve self-adaptation capabilities and ensure higher levels of quality performance in many domains. We employed a real-world automotive platform called Eclipse Kuksa to propose a framework based on microservices architecture to enhance the self-adaptation capabilities of automotive systems for runtime data analysis. To evaluate the designed solution, we conducted an experiment in an automotive laboratory setting where our solution was implemented as a microservice-based adaptation engine and integrated with other Eclipse Kuksa components. The results of our study indicate the importance of design trade-offs for quality requirements' satisfaction levels of each microservices and the whole system for the optimal performance of an adaptive system at runtime