Characterization of the Noise in Secondary Ion Mass Spectrometry Depth Profiles

The noise in the depth profiles of secondary ion mass spectrometry (SIMS) is studied using different samples under various experimental conditions. Despite the noise contributions from various parts of the dynamic SIMS process, its overall character agrees very well with the Poissonian rather than the Gaussian distribution in all circumstances. The Poissonian relation between the measured mean-square error (MSE) and mean can be used to describe our data in the range of four orders. The departure from this relation at high counts is analyzed and found to be due to the saturation of the channeltron used. Once saturated, the detector was found to exhibit hysteresis between rising and falling input flux and output counts.Comment: 14 pages, 4 postscript figures, to appear on J. Appl. Phy

Infrared astronomical satellite (IRAS) catalogs and atlases. Volume 1: Explanatory supplement

The Infrared Astronomical Satellite (IRAS) was launched on January 26, 1983. During its 300-day mission, IRAS surveyed over 96 pct of the celestial sphere at four infrared wavelengths, centered approximately at 12, 25, 60, and 100 microns. Volume 1 describes the instrument, the mission, and data reduction

Using a Bayesian approach to reconstruct graph statistics after edge sampling

Often, due to prohibitively large size or to limits to data collecting APIs, it is not possible to work with a complete network dataset and sampling is required. A type of sampling which is consistent with Twitter API restrictions is uniform edge sampling. In this paper, we propose a methodology for the recovery of two fundamental network properties from an edge-sampled network: the degree distribution and the triangle count (we estimate the totals for the network and the counts associated with each edge). We use a Bayesian approach and show a range of methods for constructing a prior which does not require assumptions about the original network. Our approach is tested on two synthetic and three real datasets with diverse sizes, degree distributions, degree-degree correlations and triangle count distributions.Comment: Extended version of the paper accepted in Complex Networks 202

Exploring the role of need for cognition, field independence and locus of control on the incidence of lucid dreams during a 12 week induction study

This article reports an investigation of two proposed theories, the predispositional and experiential, regarding the association of personality variables to lucid dreaming incidence during a 12-week lucid dreaming induction programme. The study found no differences between those who did and did not report lucid dreams during the programme on baseline measures of Field Independence, Locus of Control or Need for Cognition. There was an observed significant change towards a Field Independent orientation between baseline and post tests for those successful at inducing a lucid dream; with no statistically significant differences for either Locus of Control or Need for Cognition. Results suggest that Field Independence may not be a predispositional characteristic for the successful induction of lucid dreaming, but an experiential result of having lucid dream experiences. We conclude that experiences within a dream state may have appreciable effects on waking cognition

Lucid dreaming incidence: a quality effects meta-analysis of 50 years of research

We report a quality effects meta-analysis on studies from the period 1966–2016 measuring either (a) lucid dreaming prevalence (one or more lucid dreams in a lifetime); (b) frequent lucid dreaming (one or more lucid dreams in a month) or both. A quality effects meta-analysis allows for the minimisation of the influence of study methodological quality on overall model estimates. Following sensitivity analysis, a heterogeneous lucid dreaming prevalence data set of 34 studies yielded a mean estimate of 55%, 95% C. I. [49%, 62%] for which moderator analysis showed no systematic bias for suspected sources of variability. A heterogeneous lucid dreaming frequency data set of 25 studies yielded a mean estimate of 23%, 95% C. I. [20%, 25%], moderator analysis revealed no suspected sources of variability. These findings are consistent with earlier estimates of lucid dreaming prevalence and frequent lucid dreaming in the population but are based on more robust evidence