1,464 research outputs found

    Percentile Queries in Multi-Dimensional Markov Decision Processes

    Get PDF
    Markov decision processes (MDPs) with multi-dimensional weights are useful to analyze systems with multiple objectives that may be conflicting and require the analysis of trade-offs. We study the complexity of percentile queries in such MDPs and give algorithms to synthesize strategies that enforce such constraints. Given a multi-dimensional weighted MDP and a quantitative payoff function ff, thresholds viv_i (one per dimension), and probability thresholds αi\alpha_i, we show how to compute a single strategy to enforce that for all dimensions ii, the probability of outcomes ρ\rho satisfying fi(ρ)vif_i(\rho) \geq v_i is at least αi\alpha_i. We consider classical quantitative payoffs from the literature (sup, inf, lim sup, lim inf, mean-payoff, truncated sum, discounted sum). Our work extends to the quantitative case the multi-objective model checking problem studied by Etessami et al. in unweighted MDPs.Comment: Extended version of CAV 2015 pape

    Maximizing the Conditional Expected Reward for Reaching the Goal

    Full text link
    The paper addresses the problem of computing maximal conditional expected accumulated rewards until reaching a target state (briefly called maximal conditional expectations) in finite-state Markov decision processes where the condition is given as a reachability constraint. Conditional expectations of this type can, e.g., stand for the maximal expected termination time of probabilistic programs with non-determinism, under the condition that the program eventually terminates, or for the worst-case expected penalty to be paid, assuming that at least three deadlines are missed. The main results of the paper are (i) a polynomial-time algorithm to check the finiteness of maximal conditional expectations, (ii) PSPACE-completeness for the threshold problem in acyclic Markov decision processes where the task is to check whether the maximal conditional expectation exceeds a given threshold, (iii) a pseudo-polynomial-time algorithm for the threshold problem in the general (cyclic) case, and (iv) an exponential-time algorithm for computing the maximal conditional expectation and an optimal scheduler.Comment: 103 pages, extended version with appendices of a paper accepted at TACAS 201

    Association between the c.*229C>T polymorphism of the topoisomerase IIb binding protein 1 (TopBP1) gene and breast cancer

    Get PDF
    Topoisomerase IIb binding protein 1 (TopBP1) is involved in cell survival, DNA replication, DNA damage repair and cell cycle checkpoint control. The biological function of TopBP1 and its close relation with BRCA1 prompted us to investigate whether alterations in the TopBP1 gene can influence the risk of breast cancer. The aim of this study was to examine the association between five polymorphisms (rs185903567, rs116645643, rs115160714, rs116195487, and rs112843513) located in the 30UTR region of the TopBP1 gene and breast cancer risk as well as allele-specific gene expression. Five hundred thirty-four breast cancer patients and 556 population controls were genotyped for these SNPs. Allele-specific Top- BP1 mRNA and protein expressions were determined by using real time PCR and western blotting methods, respectively. Only one SNP (rs115160714) showed an association with breast cancer. Compared to homozygous common allele carriers, heterozygous and homozygous for the T variant had significantly increased risk of breast cancer (adjusted odds ratio = 3.81, 95 % confidence interval: 1.63–8.34, p = 0.001). Mean TopBP1 mRNA and protein expression were higher in the individuals with the CT or TT genotype. There was a significant association between the rs115160714 and tumor grade and stage. Most carriers of minor allele had a high grade (G3) tumors classified as T2-T4N1M0. Our study raises a possibility that a genetic variation of TopBP1 may be implicated in the etiology of breast cancer

    Analytic philosophy for biomedical research: the imperative of applying yesterday's timeless messages to today's impasses

    Get PDF
    The mantra that "the best way to predict the future is to invent it" (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in this chapter is that philosophy is essential in this process. By reviewing select examples from the history of science and philosophy, disciplines which were indistinguishable until the mid-nineteenth century, I argue that progress toward the many impasses in biomedicine can be achieved by emphasizing theoretical work (in the true sense of the word 'theory') as a vital foundation for experimental biology. Furthermore, a philosophical biology program that could provide a framework for theoretical investigations is outlined

    Performance of the CMS Cathode Strip Chambers with Cosmic Rays

    Get PDF
    The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

    The role of planetary formation and evolution in shaping the composition of exoplanetary atmospheres

    Get PDF
    Over the last twenty years, the search for extrasolar planets revealed us the rich diversity of the outcomes of the formation and evolution of planetary systems. In order to fully understand how these extrasolar planets came to be, however, the orbital and physical data we possess are not enough, and they need to be complemented with information on the composition of the exoplanets. Ground-based and space-based observations provided the first data on the atmospheric composition of a few extrasolar planets, but a larger and more detailed sample is required before we can fully take advantage of it. The primary goal of the Exoplanet Characterization Observatory (EChO) is to fill this gap, expanding the limited data we possess by performing a systematic survey of hundreds of extrasolar planets. The full exploitation of the data that EChO and other space-based and ground-based facilities will provide in the near future, however, requires the knowledge of what are the sources and sinks of the chemical species and molecules that will be observed. Luckily, the study of the past history of the Solar System provides several indications on the effects of processes like migration, late accretion and secular impacts, and on the time they occur in the life of planetary systems. In this work we will review what is already known about the factors influencing the composition of planetary atmospheres, focusing on the case of gaseous giant planets, and what instead still need to be investigated.Comment: 26 pages, 9 figures, 1 table. Accepted for publication on Experimental Astronomy, special issue on the M3 EChO mission candidat

    Do regional brain volumes and major depressive disorder share genetic architecture?:A study of Generation Scotland (<i>n</i>=19,762), UK Biobank (<i>n</i>=24,048) and the English Longitudinal Study of Ageing (<i>n</i>=5,766)

    Get PDF
    Major depressive disorder (MDD) is a heritable and highly debilitating condition. It is commonly associated with subcortical volumetric abnormalities, the most replicated of these being reduced hippocampal volume. Using the most recent published data from Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium's genome-wide association study of regional brain volume, we sought to test whether there is shared genetic architecture between seven subcortical brain volumes and intracranial volume (ICV) and MDD. We explored this using linkage disequilibrium score regression, polygenic risk scoring (PRS) techniques, Mendelian randomisation (MR) analysis and BUHMBOX. Utilising summary statistics from ENIGMA and Psychiatric Genomics Consortium, we demonstrated that hippocampal volume was positively genetically correlated with MDD (rG=0.46, P=0.02), although this did not survive multiple comparison testing. None of the other six brain regions studied were genetically correlated and amygdala volume heritability was too low for analysis. Using PRS analysis, no regional volumetric PRS demonstrated a significant association with MDD or recurrent MDD. MR analysis in hippocampal volume and MDD identified no causal association, however, BUHMBOX analysis identified genetic subgrouping in GS:SFHS MDD cases only (P=0.00281). In this study, we provide some evidence that hippocampal volume and MDD may share genetic architecture in a subgroup of individuals, albeit the genetic correlation did not survive multiple testing correction and genetic subgroup heterogeneity was not replicated. In contrast, we found no evidence to support a shared genetic architecture between MDD and other regional subcortical volumes or ICV

    Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

    Get PDF
    The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

    Site-selective protein-modification chemistry for basic biology and drug development.

    Get PDF
    Nature has produced intricate machinery to covalently diversify the structure of proteins after their synthesis in the ribosome. In an attempt to mimic nature, chemists have developed a large set of reactions that enable post-expression modification of proteins at pre-determined sites. These reactions are now used to selectively install particular modifications on proteins for many biological and therapeutic applications. For example, they provide an opportunity to install post-translational modifications on proteins to determine their exact biological roles. Labelling of proteins in live cells with fluorescent dyes allows protein uptake and intracellular trafficking to be tracked and also enables physiological parameters to be measured optically. Through the conjugation of potent cytotoxicants to antibodies, novel anti-cancer drugs with improved efficacy and reduced side effects may be obtained. In this Perspective, we highlight the most exciting current and future applications of chemical site-selective protein modification and consider which hurdles still need to be overcome for more widespread use.We thank FCT Portugal (FCT Investigator to G.J.L.B.), the EU (Marie-Curie CIG to G.J.L.B. and Marie-Curie IEF to O.B.) and the EPSRC for funding. G.J.L.B. is a Royal Society University Research Fellow.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/nchem.239

    An HDAC9-MALAT1-BRG1 complex mediates smooth muscle dysfunction in thoracic aortic aneurysm

    Get PDF
    Thoracic aortic aneurysm (TAA) has been associated with mutations affecting members of the TGF-β signaling pathway, or components and regulators of the vascular smooth muscle cell (VSMC) actomyosin cytoskeleton. Although both clinical groups present similar phenotypes, the existence of potential common mechanisms of pathogenesis remain obscure. Here we show that mutations affecting TGF-β signaling and VSMC cytoskeleton both lead to the formation of a ternary complex comprising the histone deacetylase HDAC9, the chromatin-remodeling enzyme BRG1, and the long noncoding RNA MALAT1. The HDAC9–MALAT1–BRG1 complex binds chromatin and represses contractile protein gene expression in association with gain of histone H3-lysine 27 trimethylation modifications. Disruption of Malat1 or Hdac9 restores contractile protein expression, improves aortic mural architecture, and inhibits experimental aneurysm growth. Thus, we highlight a shared epigenetic pathway responsible for VSMC dysfunction in both forms of TAA, with potential therapeutic implication for other known HDAC9-associated vascular diseases
    corecore