Observation of Free-Space Single-Atom Matterwave Interference

We observe matterwave interference of a single cesium atom in free fall. The interferometer is an absolute sensor of acceleration and we show that this technique is sensitive to forces at the level of $3.2\times10^{-27}$ N with a spatial resolution at the micron scale. We observe the build up of the interference pattern one atom at a time in an interferometer where the mean path separation extends far beyond the coherence length of the atom. Using the coherence length of the atom wavepacket as a metric, we directly probe the velocity distribution and measure the temperature of a single atom in free fall.Comment: 5 pages, 4 figure

Photo-electrochemical Hydrogen Sulfide Splitting using SnIV-doped Hematite Photo-anodes

© 2016 The Authors. Published by Elsevier B.V.Spray-pyrolysed SnIV-doped α-Fe2O3 photo-anodes were used for photo-assisted splitting of HS- ions in alkaline aqueous solutions, producing polysulfide (Sn2 -) ions together with hydrogen at the cathode. Subsequent aerial oxidation of polysulfide could be used to produce elemental sulfur. At an applied electrode potential of 1.07 V (RHE) and an irradiance of 5.6 kW m- 2, stable photocurrents of ca. 11 A m- 2 (2 × 10- 3 A W- 1) were recorded over 75 h, polysulfide concentrations increasing linearly with time. Despite being predicted thermodynamically to form iron sulfide(s) in sulfide solutions, such photo-anodes appeared to be stable. In comparison with conventional water splitting under alkaline conditions, the coupled processes of hydrogen sulfide ion oxidation and water reduction had a lower energy requirement

En route to a unified model for photo-electrochemical reactor optimization. I - Photocurrent and H₂ yield predictions

A semi-empirical model was developed for prediction of photocurrent densities and implemented to predict the performance of a photo-electrochemical reactor for water splitting in alkaline solutions, using Sn-doped α-Fe₂O₃ photo-anodes produced by spray pyrolysis. Photo-anodes annealed at different temperatures were characterized using photo-electrochemical impedance spectroscopy, cyclic voltammetry in the presence and absence of a hole scavenger and also the open circuit potential under high intensity illumination. Mott-Schottky analysis was used cautiously to estimate charge carrier concentration and the flat band potential. In addition to overpotential/current distribution and ohmic potential losses, the model also accounts for absorbed photon flux, surface and bulk electron-hole recombination rates, gas desorption, bubble formation and (H₂-O₂) cross-over losses. This allows the model to estimate the total yield of hydrogen, charge and gas collection efficiencies. A methodology is presented here in order to evaluate parameters required to assess the performance of a photo-electrochemical reactor in 1D and 2D geometries. The importance of taking into account bubble generation and gas desorption is discussed, together with the difficulties of measuring charge carrier concentration and electron-hole recombination in the bulk of the semiconductor, which are of major importance in the prediction of photocurrent densities

History-sensitive versus future-sensitive approaches to security in distributed systems

We consider the use of aspect-oriented techniques as a flexible way to deal with security policies in distributed systems. Recent work suggests to use aspects for analysing the future behaviour of programs and to make access control decisions based on this; this gives the flavour of dealing with information flow rather than mere access control. We show in this paper that it is beneficial to augment this approach with history-based components as is the traditional approach in reference monitor-based approaches to mandatory access control. Our developments are performed in an aspect-oriented coordination language aiming to describe the Bell-LaPadula policy as elegantly as possible. Furthermore, the resulting language has the capability of combining both history- and future-sensitive policies, providing even more flexibility and power.Comment: In Proceedings ICE 2010, arXiv:1010.530

Using machine learning to infer reasoning provenance from user interaction log data: based on the data/frame theory of sensemaking

The reconstruction of analysts’ reasoning processes (reasoning provenance) during complex sensemaking tasks can support reflection and decision making. One potential approach to such reconstruction is to automatically infer reasoning from low-level user interaction logs. We explore a novel method for doing this using machine learning. Two user studies were conducted in which participants performed similar intelligence analysis tasks. In one study, participants used a standard web browser and word processor; in the other, they used a system called INVISQUE (Interactive Visual Search and Query Environment). Interaction logs were manually coded for cognitive actions based on captured think-aloud protocol and posttask interviews based on Klein, Phillips, Rall, and Pelusos’s data/frame model of sensemaking as a conceptual framework. This analysis was then used to train an interaction frame mapper, which employed multiple machine learning models to learn relationships between the interaction logs and the codings. Our results show that, for one study at least, classification accuracy was significantly better than chance and compared reasonably to a reported manual provenance reconstruction method. We discuss our results in terms of variations in feature sets from the two studies and what this means for the development of the method for provenance capture and the evaluation of sensemaking systems

The impact of educational interventions on clinicians' knowledge of radiation protection: An integrative review

The aim of this review is to explore the impact of educational interventions on clinicians' knowledge of radiation protection. Following a comprehensive search of MEDLINE and EMBASE from 2000 to 2018, 1795 studies were identified, eight of which met the criteria for this review. All eight studies utilised pretest-posttest designs and involved the education of medical students or doctors. All studies reported an increase in participants' knowledge of radiation protection, five of which were statistically significant. In two studies, over half of participants stated that education received would impact on their future imaging requesting practice. Whilst a range of educational interventions have been shown to improve knowledge of radiation protection, there was wide variation in the study settings and type of educational programmes delivered. No studies assessed long-term knowledge retention or the impact on clinical practice. Therefore, robust research is needed to accurately measure the impact of educational programmes on knowledge of radiation protection in the UK and the implications this may have on referral practices. This review revealed that educational interventions are effective in increasing participants' knowledge levels of radiation protection. It is necessary to assess and ensure that this improvement in knowledge actually translates into an impact on referral practice/behaviour. The ideal outcome being that fewer unnecessary examinations are requested and our patients are protected from a needless increased radiation burden. [Abstract copyright: Copyright © 2020 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.