Evaluation of an airborne alpha and beta particle detection capability using an environmental continuous air monitor system.

We evaluate the ability of the Canberra Alpha Beta Environmental Continuous Air Monitor (ECAM) to detect and quantify airborne radiological contamination. The ECAM essentially consists of a passively-implanted planar silicon (PIPS) detector near a particulate filter through which outside air is pulled. Three years' worth of background measurements on three different systems were assessed and calibrated to compensate for changing conditions and develop an average background response for the systems. The ECAM was also exposed to several radionuclides of interest, including 235U and 239Pu, to measure the response to alpha and beta particle sources. Both standard calibration sources and custom sources consisting of aqueous radioisotope solutions absorbed into clean filters. The ECAM responses to these sources were then scaled to quantities of interest and injected on the averaged background. Various alarm algorithms were evaluated on the source-injected spectra for minimum detectable air concentration for a given false alarm rate. Even in the worst case, the ECAM was able to detect radionuclides of interest at 10% of the Derived Response Level (DRL) for each isotope based on early-phase Protective Action Guides (PAG). Quantification of the radionuclides was also evaluated for the various algorithms, with mixed results, but overall clearly indicating the optimal algorithms for alpha and beta particle alarm and quantification. Finally, a limited evaluation of the beta particle detection efficiency points to a detection energy threshold of approximately 290 keV.

The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository.

This data descriptor describes a repository of openly shared data from an experiment to assess inter-individual differences in default mode network (DMN) activity. This repository includes cross-sectional functional magnetic resonance imaging (fMRI) data from the Multi Source Interference Task, to assess DMN deactivation, the Moral Dilemma Task, to assess DMN activation, a resting state fMRI scan, and a DMN neurofeedback paradigm, to assess DMN modulation, along with accompanying behavioral and cognitive measures. We report technical validation from n=125 participants of the final targeted sample of 180 participants. Each session includes acquisition of one whole-brain anatomical scan and whole-brain echo-planar imaging (EPI) scans, acquired during the aforementioned tasks and resting state. The data includes several self-report measures related to perseverative thinking, emotion regulation, and imaginative processes, along with a behavioral measure of rapid visual information processing. Technical validation of the data confirms that the tasks deactivate and activate the DMN as expected. Group level analysis of the neurofeedback data indicates that the participants are able to modulate their DMN with considerable inter-subject variability. Preliminary analysis of behavioral responses and specifically self-reported sleep indicate that as many as 73 participants may need to be excluded from an analysis depending on the hypothesis being tested. The present data are linked to the enhanced Nathan Kline Institute, Rockland Sample and builds on the comprehensive neuroimaging and deep phenotyping available therein. As limited information is presently available about individual differences in the capacity to directly modulate the default mode network, these data provide a unique opportunity to examine DMN modulation ability in relation to numerous phenotypic characteristics.