Directional Detection of Dark Matter with MIMAC

Directional detection is a promising search strategy to discover galactic Dark Matter. We present a Bayesian analysis framework dedicated to Dark Matter phenomenology using directional detection. The interest of directional detection as a powerful tool to set exclusion limits, to authentify a Dark Matter detection or to constrain the Dark Matter properties, both from particle physics and galactic halo physics, will be demonstrated. However, such results need highly accurate track reconstruction which should be reachable by the MIMAC detector using a dedicated readout combined with a likelihood analysis of recoiling nuclei.Comment: 4 pages, 2 figures, to appear in the proceedings of the TAUP 2011 conference held in Munich (5 - 9 September, 2011

Rate-Control or Rhythm-Contol: Where do we stand?

Atrial fibrillation is the most common sustained rhythm disturbance and its prevalence is increasing worldwide due to the progressive aging of the population. Current guidelines clearly depict the gold standard management of acute symptomatic atrial fibrillation but the best-long term approach for first or recurrent atrial fibrillation is still debated with regard to quality of life, risk of new hospitalizations, and possible disabling complications, such as thromboembolic stroke, major bleeds and death. Some authors propose that regaining sinus rhythm in all cases, thus re-establishing a physiologic cardiac function not requiring a prolonged antithrombotic therapy, avoids the threat of intracranial or extracranial haemorrhages due to Vitamin K antagonists or aspirin. On the contrary, advocates of a rate control approach with an accurate antithrombotic prophylaxis propose that such a strategy may avoid the risk of cardiovascular and non cardiovascular side effects related to antiarrhythmic drugs. This review aims to explore the state of our knowledge in order to summarize evidences and issues that need to be furthermore clarified

The effect of local optically thick regions in the long-wave emission of young circumstellar disks

Multi-wavelength observations of protoplanetary disks in the sub-millimeter continuum have measured spectral indices values which are significantly lower than what is found in the diffuse interstellar medium. Under the assumption that mm-wave emission of disks is mostly optically thin, these data have been generally interpreted as evidence for the presence of mm/cm-sized pebbles in the disk outer regions. In this work we investigate the effect of possible local optically thick regions on the mm-wave emission of protoplanetary disks without mm/cm-sized grains. A significant local increase of the optical depth in the disk can be caused by the concentration of solid particles, as predicted to result from a variety of proposed physical mechanisms. We calculate the filling factors and implied overdensities these optically thick regions would need to significantly affect the millimeter fluxes of disks, and we discuss their plausibility. We find that optically thick regions characterized by relatively small filling factors can reproduce the mm-data of young disks without requesting emission from mm/cm-sized pebbles. However, these optically thick regions require dust overdensities much larger than what predicted by any of the physical processes proposed in the literature to drive the concentration of solids. We find that only for the most massive disks it is possible and plausible to imagine that the presence of optically thick regions in the disk is responsible for the low measured values of the mm spectral index. For the majority of the disk population, optically thin emission from a population of large mm-sized grains remains the most plausible explanation. The results of this analysis further strengthen the scenario for which the measured low spectral indices of protoplanetary disks at mm wavelengths are due to the presence of large mm/cm-sized pebbles in the disk outer regions.Comment: 13 pages, 2 figures, A&A in pres

The impact of priors and observables on parameter inferences in the Constrained MSSM

We use a newly released version of the SuperBayeS code to analyze the impact of the choice of priors and the influence of various constraints on the statistical conclusions for the preferred values of the parameters of the Constrained MSSM. We assess the effect in a Bayesian framework and compare it with an alternative likelihood-based measure of a profile likelihood. We employ a new scanning algorithm (MultiNest) which increases the computational efficiency by a factor ~200 with respect to previously used techniques. We demonstrate that the currently available data are not yet sufficiently constraining to allow one to determine the preferred values of CMSSM parameters in a way that is completely independent of the choice of priors and statistical measures. While b->s gamma generally favors large m_0, this is in some contrast with the preference for low values of m_0 and m_1/2 that is almost entirely a consequence of a combination of prior effects and a single constraint coming from the anomalous magnetic moment of the muon, which remains somewhat controversial. Using an information-theoretical measure, we find that the cosmological dark matter abundance determination provides at least 80% of the total constraining power of all available observables. Despite the remaining uncertainties, prospects for direct detection in the CMSSM remain excellent, with the spin-independent neutralino-proton cross section almost guaranteed above sigma_SI ~ 10^{-10} pb, independently of the choice of priors or statistics. Likewise, gluino and lightest Higgs discovery at the LHC remain highly encouraging. While in this work we have used the CMSSM as particle physics model, our formalism and scanning technique can be readily applied to a wider class of models with several free parameters.Comment: Minor changes, extended discussion of profile likelihood. Matches JHEP accepted version. SuperBayeS code with MultiNest algorithm available at http://www.superbayes.or

A Coverage Study of the CMSSM Based on ATLAS Sensitivity Using Fast Neural Networks Techniques

We assess the coverage properties of confidence and credible intervals on the CMSSM parameter space inferred from a Bayesian posterior and the profile likelihood based on an ATLAS sensitivity study. In order to make those calculations feasible, we introduce a new method based on neural networks to approximate the mapping between CMSSM parameters and weak-scale particle masses. Our method reduces the computational effort needed to sample the CMSSM parameter space by a factor of ~ 10^4 with respect to conventional techniques. We find that both the Bayesian posterior and the profile likelihood intervals can significantly over-cover and identify the origin of this effect to physical boundaries in the parameter space. Finally, we point out that the effects intrinsic to the statistical procedure are conflated with simplifications to the likelihood functions from the experiments themselves.Comment: Further checks about accuracy of neural network approximation, fixed typos, added refs. Main results unchanged. Matches version accepted by JHE

Hunting Down the Best Model of Inflation with Bayesian Evidence

We present the first calculation of the Bayesian evidence for different prototypical single field inflationary scenarios, including representative classes of small field and large field models. This approach allows us to compare inflationary models in a well-defined statistical way and to determine the current "best model of inflation". The calculation is performed numerically by interfacing the inflationary code FieldInf with MultiNest. We find that small field models are currently preferred, while large field models having a self-interacting potential of power p>4 are strongly disfavoured. The class of small field models as a whole has posterior odds of approximately 3:1 when compared with the large field class. The methodology and results presented in this article are an additional step toward the construction of a full numerical pipeline to constrain the physics of the early Universe with astrophysical observations. More accurate data (such as the Planck data) and the techniques introduced here should allow us to identify conclusively the best inflationary model.Comment: 12 pages, 2 figures, uses RevTeX. Misprint corrected, references added. Matches published versio

Pippi - painless parsing, post-processing and plotting of posterior and likelihood samples

Interpreting samples from likelihood or posterior probability density functions is rarely as straightforward as it seems it should be. Producing publication-quality graphics of these distributions is often similarly painful. In this short note I describe pippi, a simple, publicly-available package for parsing and post-processing such samples, as well as generating high-quality PDF graphics of the results. Pippi is easily and extensively configurable and customisable, both in its options for parsing and post-processing samples, and in the visual aspects of the figures it produces. I illustrate some of these using an existing supersymmetric global fit, performed in the context of a gamma-ray search for dark matter. Pippi can be downloaded and followed at http://github.com/patscott/pippi .Comment: 4 pages, 1 figure. v3: Updated for pippi 2.0. New features include hdf5 support, out-of-core processing, inline post-processing with arbitrary Python code in the input file, and observable-specific data cuts. Pippi can be downloaded from http://github.com/patscott/pipp

Pyromellitic dianhydride crosslinked cyclodextrin nanosponges for curcumin controlled release; formulation, physicochemical characterization and cytotoxicity investigations

Aim: In this study, a nanosponge structure was synthesised with capability of encapsulating curcumin as a model polyphenolic compound and one of the herbal remedies that have widely been considered due to its ability to treat cancer. Methods: FTIR, DSC and XRD techniques were performed to confirm the formation of the inclusion complex of the nanosponge-drug. Results: DSC and XRD patterns showed an increasing stability and a decreasing crystallinity of curcumin after formation of inclusion complex. Encapsulation efficiency was 98% (w/w) and a significant increase was observed in loading capacity (184% w/w). The results of cytotoxicity assessments demonstrated no cell toxicity on the healthy cell line, while being toxic against cancer cells. Haemolysis test was performed to evaluate the blood-compatibility characteristic of nanosponge and complex and the results showed 0.54% haemolysis in the lowest complex concentration (50μgml−1) and 5.09% at the highest concentration (200μgml−1). Conclusions: Thus, the introduced system could be widely considered in cancer treatment as a drug delivery system