Capital process and optimality properties of a Bayesian Skeptic in coin-tossing games

We study capital process behavior in the fair-coin game and biased-coin games in the framework of the game-theoretic probability of Shafer and Vovk (2001). We show that if Skeptic uses a Bayesian strategy with a beta prior, the capital process is lucidly expressed in terms of the past average of Reality's moves. From this it is proved that the Skeptic's Bayesian strategy weakly forces the strong law of large numbers (SLLN) with the convergence rate of O(\sqrt{\log n/n})$ and if Reality violates SLLN then the exponential growth rate of the capital process is very accurately described in terms of the Kullback divergence between the average of Reality's moves when she violates SLLN and the average when she observes SLLN. We also investigate optimality properties associated with Bayesian strategy

Superstars and Giant Gravitons in M-theory

Following hep-th/0109127, we show that a certain class of BPS naked singularities (superstars) found in compactifications of M-theory can be interpreted as being composed of giant gravitons. More specifically, we study superstars which are asymptotically AdS_7 x S^4 and AdS_4 x S^7 and show that these field configurations can be interpreted as being sourced by continuous distributions of spherical M2- and M5-branes, respectively, which carry internal momenta and have expanded on the spherical component of the space-time.Comment: 13 page

A Parameterization Invariant Approach to the Statistical Estimation of the CKM Phase α\alpha

In contrast to previous analyses, we demonstrate a Bayesian approach to the estimation of the CKM phase $\alpha$ that is invariant to parameterization. We also show that in addition to {\em computing} the marginal posterior in a Bayesian manner, the distribution must also be {\em interpreted} from a subjective Bayesian viewpoint. Doing so gives a very natural interpretation to the distribution. We also comment on the effect of removing information about $\mathcal{B}^{00}$.Comment: 14 pages, 3 figures, 1 table, minor revision; to appear in JHE

Quantum symmetries and exceptional collections

We study the interplay between discrete quantum symmetries at certain points in the moduli space of Calabi-Yau compactifications, and the associated identities that the geometric realization of D-brane monodromies must satisfy. We show that in a wide class of examples, both local and compact, the monodromy identities in question always follow from a single mathematical statement. One of the simplest examples is the Z_5 symmetry at the Gepner point of the quintic, and the associated D-brane monodromy identity

Real-Time Correlators and Non-Relativistic Holography

We consider Lorentzian correlation functions in theories with non-relativistic Schrodinger symmetry. We employ the method developed by Skenderis and van Rees in which the contour in complex time defining a given correlation function is associated holographically with the gluing together of Euclidean and Lorentzian patches of spacetimes. This formalism extends appropriately to geometries with Schrodinger isometry.Comment: 13 pages, 3 pdf figure

Volumetric real-time particle-based representation of large unstructured tetrahedral polygon meshes

In this paper we propose a particle-based volume rendering approach for unstructured, three-dimensional, tetrahedral polygon meshes. We stochastically generate millions of particles per second and project them on the screen in real-time. In contrast to previous rendering techniques of tetrahedral volume meshes, our method does not need a prior depth sorting of geometry. Instead, the rendered image is generated by choosing particles closest to the camera. Furthermore, we use spatial superimposing. Each pixel is constructed from multiple subpixels. This approach not only increases projection accuracy, but allows also a combination of subpixels into one superpixel that creates the well-known translucency effect of volume rendering. We show that our method is fast enough for the visualization of unstructured three-dimensional grids with hard real-time constraints and that it scales well for a high number of particles

Phase II control charts for autocorrelated processes

A large amount of SPC procedures are based on the assumption that the process subject to monitoring consists of independent observations. Chemical processes as well as many non-industrial processes exhibit autocorrelation, for which the above-mentioned control procedures are not suitable. This paper proposes a Phase II control procedure for autocorrelated and possibly locally stationary processes. A time-varying autoregressive (AR) model is proposed, which is capable of dealing with the autocorrelation as well as with local non-stationarities of the temporal process. Such non-stationarities are induced by the time-varying nature of the AR coefficients. The model is optimized during Phase I when it is assured that the process is in control and as a result the model describes accurately the process. The Phase II proposed control procedure is based on a comparison of the current time series model with an alternative model, measuring deviations from it. This comparison is carried out using Bayes factors, which help to establish the in-control or out-of-control state of the process in Phase II. Using the threshold rules of the Bayes factors, we propose a binomial-type control procedure for the monitoring of the process. The methodology of this paper is illustrated using two data sets consisting of temperature measurements at two different stages in the manufacturing of a plastic mould

Brownian Confidence Bands on Monte Carlo Output

International audienceWhen considering a Monte Carlo estimation procedure, the path produced by successive partial estimates is often used as a guide for informal convergence diagnostics. However the confidence region associated with that path cannot be derived simplistically from the confidence interval for the estimate itself. An asymptotically correct approach can be based on the Brownian motion approximation of the path, but no exact formula for the corresponding area-minimizing confidence region is yet known. We construct proxy regions based on local time arguments and consider numerical approximations. These are then available for a more incisive assessment of the Monte Carlo procedure and thence of the estimate itself

Dried blood spot analysis for the quantification of vancomycin and creatinine using liquid chromatography – tandem mass spectrometry:Method development and validation

Background: Vancomycin is a widely used antibiotic for the treatment of gram-positive bacterial infections, especially for methicillin-resistant Staphylococcus aureus (MRSA) infections. Due to a small therapeutic range and large inter-patient variability, therapeutic drug monitoring (TDM) of vancomycin is required to minimize toxicity and maximize treatment efficacy. Venous blood sampling is mostly applied for TDM of vancomycin, although this widely used sampling method is more invasive compared to less painful alternatives, such as the dried blood spot (DBS) method, which can be performed at home. Method: We developed an UPLC-MS/MS method for the quantification of vancomycin and creatinine in DBS. A fast sample preparation and short analysis run time of 5.2 min were applied, which makes this method highly suitable for clinical settings. Validation was performed according to international (FDA and EMA) guidelines. Results: The validated concentration range was found linear for creatinine from 41.8 µmol/L to 722 µmol/L and for vancomycin from 3.8 mg/L to 76.6 mg/L (r2 &gt; 0.990) and the inaccuracies, imprecisions, hematocrit effects, and recoveries were &lt; 15 % for both compounds. No significant carryover effect was observed. Conclusion: Hence, we successfully validated a quantification method for the simultaneous determination of creatinine and vancomycin in DBS.</p