Muonic atoms and the nuclear structure

High-precision laser spectroscopy of atomic energy levels enables the measurement of nuclear properties. Sensitivity to these properties is particularly enhanced in muonic atoms which are bound systems of a muon and a nucleus. Exemplary is the measurement of the proton charge radius from muonic hydrogen performed by the CREMA collaboration which resulted in an order of magnitude more precise charge radius as extracted from other methods but at a variance of 7 standard deviations. Here, we summarize the role of muonic atoms for the extraction of nuclear charge radii, we present the status of the so called "proton charge radius puzzle", and we sketch how muonic atoms can be used to infer also the magnetic nuclear radii, demonstrating again an interesting interplay between atomic and particle/nuclear physics.Comment: ICOLS 2015, Singapore. arXiv admin note: text overlap with arXiv:1509.0323

Multi-objective optimal designs in comparative clinical trials with covariates: The reinforced doubly adaptive biased coin design

The present paper deals with the problem of allocating patients to two competing treatments in the presence of covariates or prognostic factors in order to achieve a good trade-off among ethical concerns, inferential precision and randomness in the treatment allocations. In particular we suggest a multipurpose design methodology that combines efficiency and ethical gain when the linear homoscedastic model with both treatment/covariate interactions and interactions among covariates is adopted. The ensuing compound optimal allocations of the treatments depend on the covariates and their distribution on the population of interest, as well as on the unknown parameters of the model. Therefore, we introduce the reinforced doubly adaptive biased coin design, namely a general class of covariate-adjusted response-adaptive procedures that includes both continuous and discontinuous randomization functions, aimed to target any desired allocation proportion. The properties of this proposal are described both theoretically and through simulations.Comment: Published in at http://dx.doi.org/10.1214/12-AOS1007 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

On the almost sure convergence of adaptive allocation procedures

In this paper, we provide some general convergence results for adaptive designs for treatment comparison, both in the absence and presence of covariates. In particular, we demonstrate the almost sure convergence of the treatment allocation proportion for a vast class of adaptive procedures, also including designs that have not been formally investigated but mainly explored through simulations, such as Atkinson's optimum biased coin design, Pocock and Simon's minimization method and some of its generalizations. Even if the large majority of the proposals in the literature rely on continuous allocation rules, our results allow to prove via a unique mathematical framework the convergence of adaptive allocation methods based on both continuous and discontinuous randomization functions. Although several examples of earlier works are included in order to enhance the applicability, our approach provides substantial insight for future suggestions, especially in the absence of a prefixed target and for designs characterized by sequences of allocation rules.Comment: Published at http://dx.doi.org/10.3150/13-BEJ591 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

How many operating rooms are needed to manage non-elective surgical cases? A Monte Carlo simulation study.

BackgroundPatients often wait to have urgent or emergency surgery. The number of operating rooms (ORs) needed to minimize waiting time while optimizing resources can be determined using queuing theory and computer simulation. We developed a computer program using Monte Carlo simulation to determine the number of ORs needed to minimize patient wait times while optimizing resources.MethodsWe used patient arrival data and surgical procedure length from our institution, a tertiary-care academic medical center that serves a large diverse population. With ~4800 patients/year requiring non-elective surgery, and mean procedure length 185 min (median 150 min) we determined the number of ORs needed during the day and evening (0600-2200) and during the night (2200-0600) that resulted in acceptable wait times.ResultsSimulation of 4 ORs at day/evening and 3 ORs at night resulted in median wait time = 0 min (mean = 19 min) for emergency cases requiring surgery within 2 h, with wait time at the 95th percentile = 109 min. Median wait time for urgent cases needing surgery within 8-12 h was 34 min (mean = 136 min), with wait time at the 95th percentile = 474 min. The effect of changes in surgical length and volume on wait times was determined with sensitivity analysis.ConclusionsMonte Carlo simulation can guide decisions on how to balance resources for elective and non-elective surgical procedures

Thin-disk laser scaling limit due to thermal-lens induced misalignment instability

We present an obstacle in power scaling of thin-disk lasers related with self-driven growth of misalignment due to thermal lens effects. This self-driven growth arises from the changes of the optical phase difference at the disk caused by the excursion of the laser eigen-mode from the optical axis. We found a criterion based on a simplified model of this phenomenon which can be applied to design laser resonators insensitive to this effect. Moreover, we propose several resonator architectures which are not affected by this effect.Comment: 19 pages, 13 figure