First comparison of wave observations from CoMP and AIA/SDO

Waves have long been thought to contribute to the heating of the solar corona and the generation of the solar wind. Recent observations have demonstrated evidence of quasi-periodic longitudinal disturbances and ubiquitous transverse wave propagation in many different coronal environments. This paper investigates signatures of different types of oscillatory behaviour, both above the solar limb and on-disk, by comparing findings from the Coronal Multi-channel Polarimeter (CoMP) and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) for the same active region. We study both transverse and longitudinal motion by comparing and contrasting time-distance images of parallel and perpendicular cuts along/across active region fan loops. Comparisons between parallel space-time features in CoMP Doppler velocity and transverse oscillations in AIA images are made, together with space-time analysis of propagating quasi-periodic intensity features seen near the base of loops in AIA. Signatures of transverse motions are observed along the same magnetic structure using CoMP Doppler velocity (Vphase=600-750km/s, P=3-6mins) and in AIA/SDO above the limb (P=3-8mins). Quasi-periodic intensity features (Vphase=100-200km/s, P=6-11mins) also travel along the base of the same structure. On the disk, signatures of both transverse and longitudinal intensity features were observed by AIA; both show similar properties to signatures found along structures anchored in the same active region three days earlier above the limb. Correlated features are recovered by space-time analysis of neighbouring tracks over perpendicular distances of <2.6Mm.Comment: 14 pages, 14 figures, 1 tabl

Explanatory debugging: Supporting end-user debugging of machine-learned programs

Many machine-learning algorithms learn rules of behavior from individual end users, such as task-oriented desktop organizers and handwriting recognizers. These rules form a “program” that tells the computer what to do when future inputs arrive. Little research has explored how an end user can debug these programs when they make mistakes. We present our progress toward enabling end users to debug these learned programs via a Natural Programming methodology. We began with a formative study exploring how users reason about and correct a text-classification program. From the results, we derived and prototyped a concept based on “explanatory debugging”, then empirically evaluated it. Our results contribute methods for exposing a learned program's logic to end users and for eliciting user corrections to improve the program's predictions

Spectroscopic applications and frequency locking of THz photomixing with distributed-Bragg-reflector diode lasers in low-temperature-grown GaAs

A compact, narrow-linewidth, tunable source of THz radiation has been developed for spectroscopy and other high-resolution applications. Distributed-Bragg-reflector (DBR) diode lasers at 850 nm are used to pump a low-temperature-grown GaAs photomixer. Resonant optical feedback is employed to stabilize the center frequencies and narrow the linewidths of the DBR lasers. The heterodyne linewidth full-width at half-maximum of two optically locked DBR lasers is 50 kHz on the 20 ms time scale and 2 MHz over 10 s; free-running DBR lasers have linewidths of 40 and 90 MHz on such time scales. This instrument has been used to obtain rotational spectra of acetonitrile (CH3CN) at 313 GHz. Detection limits of 1 × 10^–4 Hz^1/2 (noise/total power) have been achieved, with the noise floor dominated by the detector's noise equivalent power

End-user feature labeling: a locally-weighted regression approach

When intelligent interfaces, such as intelligent desktop assistants, email classifiers, and recommender systems, customize themselves to a particular end user, such customizations can decrease productivity and increase frustration due to inaccurate predictions - especially in early stages, when training data is limited. The end user can improve the learning algorithm by tediously labeling a substantial amount of additional training data, but this takes time and is too ad hoc to target a particular area of inaccuracy. To solve this problem, we propose a new learning algorithm based on locally weighted regression for feature labeling by end users, enabling them to point out which features are important for a class, rather than provide new training instances. In our user study, the first allowing ordinary end users to freely choose features to label directly from text documents, our algorithm was both more effective than others at leveraging end users' feature labels to improve the learning algorithm, and more robust to real users' noisy feature labels. These results strongly suggest that allowing users to freely choose features to label is a promising method for allowing end users to improve learning algorithms effectively

The 'Settlers and Colonists' Affair

In the final weeks of 2012, media reports on Alasdair Gray&rsquo;s essay &lsquo;Settlers and Colonists&rsquo; sparked a heated debate concerning Scottish cultural governance and &lsquo;anti-Englishness&rsquo;. This chapter documents and contextualizes the controversy vis-&agrave;-vis the campaigns for and against Scottish independence, and several related cultural debates. A detailed chronology of initial media coverage and political reaction (extraordinary in its volume and vehemence) is supplemented by a list of recommended essays and blogs providing further insight. The lasting impact of this episode on Gray&rsquo;s reputation and public standing is unclear; this chapter examines the role of politicians, the media and Gray himself in a process by which the author became (and was made to become) a casualty of his own incautious words, but also rendered curiously voiceless

End-User Feature Labeling via Locally Weighted Logistic Regression

Applications that adapt to a particular end user often make inaccurate predictions during the early stages when training data is limited. Although an end user can improve the learning algorithm by labeling more training data, this process is time consuming and too ad hoc to target a particular area of inaccuracy. To solve this problem, we propose a new learning algorithm based on Locally Weighted Logistic Regression for feature labeling by end users, enabling them to point out which features are important for a class, rather than provide new training instances. In our user study, the first allowing ordinary end users to freely choose features to label directly from text documents, our algorithm was more effective than others at leveraging end users’ feature labels to improve the learning algorithm. Our results strongly suggest that allowing users to freely choose features to label is a promising method for allowing end users to improve learning algorithms effectively

A temperature dependent virus binding assay reveals the presence of neutralising antibodies in human cytomegalovirus gB vaccine recipients’ sera

Human cytomegalovirus (HCMV) remains an important cause of mortality in immune-compromised transplant patients and following congenital infection. Such is the burden, an effective vaccine strategy is considered to be of the highest priority. The most successful vaccines to date have focused on generating immune responses against glycoprotein B (gB) – a protein essential for HCMV fusion and entry. We have previously reported that an important component of the humoral immune response elicited by gB/MF59 vaccination of patients awaiting transplant is the induction of non-neutralizing antibodies that target cell-associated virus with little evidence of concomitant classical neutralizing antibodies. Here we report that a modified neutralization assay that promotes prolonged binding of HCMV to the cell surface reveals the presence of neutralizing antibodies in sera taken from gB-vaccinated patients that cannot be detected using standard assays. We go on to show that this is not a general feature of gB-neutralizing antibodies, suggesting that specific antibody responses induced by vaccination could be important. Although we can find no evidence that these neutralizing antibody responses are a correlate of protection in vivo in transplant recipients their identification demonstrates the utility of the approach in identifying these responses. We hypothesize that further characterization has the potential to aid the identification of functions within gB that are important during the entry process and could potentially improve future vaccine strategies directed against gB if they prove to be effective against HCMV at higher concentrations

Pamela: development of the RF system for a non-relativistic non-scaling FFAG

The PAMELA project(Particle Accelerator For MEdical Applications) currently consists of the design of a particle therapy facility. The project, which is in the design phase, contains Non-Scaling FFAG, particle accelerator capable of rapid beam acceleration, giving a pulse repetition rate of 1kHz, far beyond that of a conventional synchrotron. To realise the repetition rate, a key component of the accelerator is the rf accelerating system. The combination of a high energy gain per turn and a high repetition rate is a significant challenge. In this paper, options for the rf system of the proton ring and the status of development are presented

The incidence of malignancy in the residual rectum of IBD patients after colectomy : a systematic review and meta-analysis

Acknowledgements The authors would like to kindly thank Mr. Rob Polson for his valuable assistance with the search strategy. Funding There was no funding provided for this study.Peer reviewedPublisher PD