Second order ancillary: A differential view from continuity

Second order approximate ancillaries have evolved as the primary ingredient for recent likelihood development in statistical inference. This uses quantile functions rather than the equivalent distribution functions, and the intrinsic ancillary contour is given explicitly as the plug-in estimate of the vector quantile function. The derivation uses a Taylor expansion of the full quantile function, and the linear term gives a tangent to the observed ancillary contour. For the scalar parameter case, there is a vector field that integrates to give the ancillary contours, but for the vector case, there are multiple vector fields and the Frobenius conditions for mutual consistency may not hold. We demonstrate, however, that the conditions hold in a restricted way and that this verifies the second order ancillary contours in moderate deviations. The methodology can generate an appropriate exact ancillary when such exists or an approximate ancillary for the numerical or Monte Carlo calculation of $p$-values and confidence quantiles. Examples are given, including nonlinear regression and several enigmatic examples from the literature.Comment: Published in at http://dx.doi.org/10.3150/10-BEJ248 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

Vortex motion phase separator for zero gravity liquid transfer

A vortex motion phase separator is disclosed for transferring a liquid in a zero gravity environment while at the same time separating the liquid from vapors found within either the sender or the receiving tanks. The separator comprises a rigid sender tank having a circular cross-section and rigid receiver tank having a circular cross-section. A plurality of ducts connects the sender tank and the receiver tank. Disposed within the ducts connecting the receiver tank and the sender tank is a pump and a plurality of valves. The pump is powered by an electric motor and is adapted to draw either the liquid or a mixture of the liquid and the vapor from the sender tank. Initially, the mixture drawn from the sender tank is directed through a portion of the ductwork and back into the sender tank at a tangent to the inside surface of the sender tank, thereby creating a swirling vortex of the mixture within the sender tank. As the pumping action increases, the speed of the swirling action within the sender tank increases creating an increase in the centrifugal force operating on the mixture. The effect of the centrifugal force is to cause the heavier liquid to migrate to the inside surface of the sender tank and to separate from the vapor. When this separation reaches a predetermined degree, control means is activated to direct the liquid conveyed by the pump directly into the receiver tank. At the same time, the vapor within the receiver tank is directed from the receiver tank back into the sender tank. This flow continues until substantially all of the liquid is transferred from the sender tank to the receiver tank

Higher Accuracy for Bayesian and Frequentist Inference: Large Sample Theory for Small Sample Likelihood

Recent likelihood theory produces $p$-values that have remarkable accuracy and wide applicability. The calculations use familiar tools such as maximum likelihood values (MLEs), observed information and parameter rescaling. The usual evaluation of such $p$-values is by simulations, and such simulations do verify that the global distribution of the $p$-values is uniform(0, 1), to high accuracy in repeated sampling. The derivation of the $p$-values, however, asserts a stronger statement, that they have a uniform(0, 1) distribution conditionally, given identified precision information provided by the data. We take a simple regression example that involves exact precision information and use large sample techniques to extract highly accurate information as to the statistical position of the data point with respect to the parameter: specifically, we examine various $p$-values and Bayesian posterior survivor $s$-values for validity. With observed data we numerically evaluate the various $p$-values and $s$-values, and we also record the related general formulas. We then assess the numerical values for accuracy using Markov chain Monte Carlo (McMC) methods. We also propose some third-order likelihood-based procedures for obtaining means and variances of Bayesian posterior distributions, again followed by McMC assessment. Finally we propose some adaptive McMC methods to improve the simulation acceptance rates. All these methods are based on asymptotic analysis that derives from the effect of additional data. And the methods use simple calculations based on familiar maximizing values and related informations. The example illustrates the general formulas and the ease of calculations, while the McMC assessments demonstrate the numerical validity of the $p$-values as percentage position of a data point. The example, however, is very simple and transparent, and thus gives little indication that in a wide generality of models the formulas do accurately separate information for almost any parameter of interest, and then do give accurate $p$-value determinations from that information. As illustration an enigmatic problem in the literature is discussed and simulations are recorded; various examples in the literature are cited.Comment: Published in at http://dx.doi.org/10.1214/07-STS240 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Plasma Sterilization Technology for Spacecraft Applications

The application of plasma gas technology to sterilization and decontamination of spacecraft components is considered. Areas investigated include: effective sterilizing ranges of four separate gases; lethal constituents of a plasma environment; effectiveness of plasma against a diverse group of microorganisms; penetrating efficiency of plasmas for sterilization; and compatibility of spacecraft materials with plasma environments. Results demonstrated that plasma gas, specifically helium plasma, is a highly effective sterilant and is compatible with spacecraft materials

Thermal Desorption of Water-Ice in the Interstellar Medium

Water (H2O) ice is an important solid constituent of many astrophysical environments. To comprehend the role of such ices in the chemistry and evolution of dense molecular clouds and comets, it is necessary to understand the freeze-out, potential surface reactivity, and desorption mechanisms of such molecular systems. Consequently, there is a real need from within the astronomical modelling community for accurate empirical molecular data pertaining to these processes. Here we give the first results of a laboratory programme to provide such data. Measurements of the thermal desorption of H2O ice, under interstellar conditions, are presented. For ice deposited under conditions that realistically mimic those in a dense molecular cloud, the thermal desorption of thin films (~50 molecular layers) is found to occur with zero order kinetics characterised by a surface binding energy, E_{des}, of 5773 +/- 60 K, and a pre-exponential factor, A, of 10^(30 +/- 2) molecules cm^-2 s^-1. These results imply that, in the dense interstellar medium, thermal desorption of H2O ice will occur at significantly higher temperatures than has previously been assumed.Comment: 9 pages, 4 figures, accepted for publication in MNRA

Potential solar axion signatures in X-ray observations with the XMM-Newton observatory

The soft X-ray flux produced by solar axions in the Earth's magnetic field is evaluated in the context of ESA's XMM-Newton observatory. Recent calculations of the scattering of axion-conversion X-rays suggest that the sunward magnetosphere could be an observable source of 0.2-10 keV photons. For XMM-Newton, any conversion X-ray intensity will be seasonally modulated by virtue of the changing visibility of the sunward magnetic field region. A simple model of the geomagnetic field is combined with the ephemeris of XMM-Newton to predict the seasonal variation of the conversion X-ray intensity. This model is compared with stacked XMM-Newton blank sky datasets from which point sources have been systematically removed. Remarkably, a seasonally varying X-ray background signal is observed. The EPIC count rates are in the ratio of their X-ray grasps, indicating a non-instrumental, external photon origin, with significances of 11(pn), 4(MOS1) and 5(MOS2) sigma. After examining the constituent observations spatially, temporally and in terms of the cosmic X-ray background, we conclude that this variable signal is consistent with the conversion of solar axions in the Earth's magnetic field. The spectrum is consistent with a solar axion spectrum dominated by bremsstrahlung- and Compton-like processes, i.e. axion-electron coupling dominates over axion-photon coupling and the peak of the axion spectrum is below 1 keV. A value of 2.2e-22 /GeV is derived for the product of the axion-photon and axion-electron coupling constants, for an axion mass in the micro-eV range. Comparisons with limits derived from white dwarf cooling may not be applicable, as these refer to axions in the 0.01 eV range. Preliminary results are given of a search for axion-conversion X-ray lines, in particular the predicted features due to silicon, sulphur and iron in the solar core, and the 14.4 keV transition line from 57Fe.Comment: Accepted for publication in MNRAS. 67 pages total, including 39 figures, 6 table

Enabling Future Sustainability Transitions: An Urban Metabolism Approach to Los Angeles Pincetl et al. Enabling Future Sustainability Transitions

Summary: This synthesis article presents an overview of an urban metabolism (UM) approach using mixed methods and multiple sources of data for Los Angeles, California. We examine electric energy use in buildings and greenhouse gas emissions from electricity, and calculate embedded infrastructure life cycle effects, water use and solid waste streams in an attempt to better understand the urban flows and sinks in the Los Angeles region (city and county). This quantification is being conducted to help policy-makers better target energy conservation and efficiency programs, pinpoint best locations for distributed solar generation, and support the development of policies for greater environmental sustainability. It provides a framework to which many more UM flows can be added to create greater understanding of the study area's resource dependencies. Going forward, together with policy analysis, UM can help untangle the complex intertwined resource dependencies that cities must address as they attempt to increase their environmental sustainability