140 research outputs found
A Decision-Theoretic Approach to Resource Allocation in Wireless Multimedia Networks
The allocation of scarce spectral resources to support as many user
applications as possible while maintaining reasonable quality of service is a
fundamental problem in wireless communication. We argue that the problem is
best formulated in terms of decision theory. We propose a scheme that takes
decision-theoretic concerns (like preferences) into account and discuss the
difficulties and subtleties involved in applying standard techniques from the
theory of Markov Decision Processes (MDPs) in constructing an algorithm that is
decision-theoretically optimal. As an example of the proposed framework, we
construct such an algorithm under some simplifying assumptions. Additionally,
we present analysis and simulation results that show that our algorithm meets
its design goals. Finally, we investigate how far from optimal one well-known
heuristic is. The main contribution of our results is in providing insight and
guidance for the design of near-optimal admission-control policies.Comment: To appear, Dial M for Mobility, 200
A Privacy-Aware Architecture for Demand Response Systems
We explore the privacy issues implicated by the development of demand response systems. We begin by highlighting the invasive nature of fine-granularity power consumption data, showing that the data collected by Advanced Metering Infrastructure (AMI) reveals detailed information about behavior within the home. We then show how privacy-aware design principles lead to novel system architectures that realize the benefits of demand response without requiring that AMI data be centrally collected. The resulting systems avoid both harm to subscribers and the potential need to scrap AMI-based demand response efforts in the face of public outcry. We also show that Trusted Platform Modules can be used to develop privacy-sensitive metering infrastructure
On the Asymptotic Behavior of Selfish Transmitters Sharing a Common Channel
This paper analyzes the asymptotic behavior of a multiple-access network
comprising a large number of selfish transmitters competing for access to a
common wireless communication channel, and having different utility functions
for determining their strategies. A necessary and sufficient condition is given
for the total number of packet arrivals from selfish transmitters to converge
in distribution. The asymptotic packet arrival distribution at Nash equilibrium
is shown to be a mixture of a Poisson distribution and finitely many Bernoulli
distributions.Comment: Proceedings of the 2008 IEEE International Symposium on Information
Theory, Toronto, ON, Canada, July 6 - 11, 200
Dissection of a Complex Disease Susceptibility Region Using a Bayesian Stochastic Search Approach to Fine Mapping.
Identification of candidate causal variants in regions associated with risk of common diseases is complicated by linkage disequilibrium (LD) and multiple association signals. Nonetheless, accurate maps of these variants are needed, both to fully exploit detailed cell specific chromatin annotation data to highlight disease causal mechanisms and cells, and for design of the functional studies that will ultimately be required to confirm causal mechanisms. We adapted a Bayesian evolutionary stochastic search algorithm to the fine mapping problem, and demonstrated its improved performance over conventional stepwise and regularised regression through simulation studies. We then applied it to fine map the established multiple sclerosis (MS) and type 1 diabetes (T1D) associations in the IL-2RA (CD25) gene region. For T1D, both stepwise and stochastic search approaches identified four T1D association signals, with the major effect tagged by the single nucleotide polymorphism, rs12722496. In contrast, for MS, the stochastic search found two distinct competing models: a single candidate causal variant, tagged by rs2104286 and reported previously using stepwise analysis; and a more complex model with two association signals, one of which was tagged by the major T1D associated rs12722496 and the other by rs56382813. There is low to moderate LD between rs2104286 and both rs12722496 and rs56382813 (r2 ≃ 0:3) and our two SNP model could not be recovered through a forward stepwise search after conditioning on rs2104286. Both signals in the two variant model for MS affect CD25 expression on distinct subpopulations of CD4+ T cells, which are key cells in the autoimmune process. The results support a shared causal variant for T1D and MS. Our study illustrates the benefit of using a purposely designed model search strategy for fine mapping and the advantage of combining disease and protein expression data.We acknowledge use of DNA from The UK Blood Services collection of Common Controls (UKBS-CC collection), which is funded by the Wellcome Trust grant 076113/C/04/Z and by the USA National Institute for Health Research program grant to the National Health Service Blood and Transplant (RP-PG-0310-1002). We acknowledge the use of DNA from the British 1958 Birth Cohort collection, which is funded by the UK Medical Research Council grant G0000934 and the Wellcome Trust grant 068545/Z/02. This research utilized resources provided by the Type 1
Diabetes Genetics Consortium, a collaborative clinical study sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Allergy and Infectious Diseases, the National Human Genome Research Institute, the National Institute of Child Health and Human Development and the JDRF and is supported by the USA National Institutes of Health grant U01-DK062418. The JDRF/Wellcome Trust Diabetes and Inflammation Laboratory is funded by the JDRF (9-2011-253), the Wellcome Trust (091157) and the National Institute for Health Research
Cambridge Biomedical Centre. The research leading to these results has received funding from the European Union's 7th Framework Programme (FP7/2007-2013) under grant agreement no.241447 (NAIMIT). The Cambridge Institute for Medical Research (CIMR) is in receipt of a Wellcome Trust Strategic Award (100140). CW is supported by the Wellcome Trust (089989). We acknowledge the National Institute for Health Research Cambridge Biomedical Research Centre for funding.This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pgen.100527
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IL2RA Genetic Heterogeneity in Multiple Sclerosis and Type 1 Diabetes Susceptibility and Soluble Interleukin-2 Receptor Production
Multiple sclerosis (MS) and type 1 diabetes (T1D) are organ-specific autoimmune disorders with significant heritability, part of which is conferred by shared alleles. For decades, the Human Leukocyte Antigen (HLA) complex was the only known susceptibility locus for both T1D and MS, but loci outside the HLA complex harboring risk alleles have been discovered and fully replicated. A genome-wide association scan for MS risk genes and candidate gene association studies have previously described the IL2RA gene region as a shared autoimmune locus. In order to investigate whether autoimmunity risk at IL2RA was due to distinct or shared alleles, we performed a genetic association study of three IL2RA variants in a DNA collection of up to 9,407 healthy controls, 2,420 MS, and 6,425 T1D subjects as well as 1,303 MS parent/child trios. Here, we report “allelic heterogeneity” at the IL2RA region between MS and T1D. We observe an allele associated with susceptibility to one disease and risk to the other, an allele that confers susceptibility to both diseases, and an allele that may only confer susceptibility to T1D. In addition, we tested the levels of soluble interleukin-2 receptor (sIL-2RA) in the serum from up to 69 healthy control subjects, 285 MS, and 1,317 T1D subjects. We demonstrate that multiple variants independently correlate with sIL-2RA levels
Phenotypic plasticity of nest-mate recognition cues in formica exsecta ants
It is well established that many ant species have evolved qualitatively distinct species-specific chemical profile that are stable overlarge geographical distances. Within these species profiles quantitative variations in the chemical profile allows distinct colony-specific odours to arise (chemotypes) that are shared by all colony members. This help maintains social cohesion, includingdefence of their colonies against all intruders, including con-specifics. How these colony -level chemotypes are maintainedamong nest-mates has long been debated. The two main theories are; each ant is able to biochemically adjust its chemical profileto‘match’that of its nest-mates and or the queen, or all nest-mates share their individually generated chemical profile viatrophollaxis resulting in an average nest-mate profile. This‘mixing’idea is better known as theGestaltmodel. Unfortunately,it has been very difficult to experimentally test these two ideas in a single experimental design. However, it is now possible usingthe antFormica exsectabecause the compounds used in nest-mate recognition compounds are known. We demonstrate thatworkers adjust their profile to‘match’the dominant chemical profile within that colony, hence maintaining the colony-specificchemotype and indicates that a‘gestalt’mechanism, i.e. profile mixing, plays no or only a minor role
The genomes of two key bumblebee species with primitive eusocial organization
Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation
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