The Nuclear Science References (NSR) Database and Web Retrieval System

The Nuclear Science References (NSR) database together with its associated Web interface, is the world's only comprehensive source of easily accessible low- and intermediate-energy nuclear physics bibliographic information for more than 200,000 articles since the beginning of nuclear science. The weekly-updated NSR database provides essential support for nuclear data evaluation, compilation and research activities. The principles of the database and Web application development and maintenance are described. Examples of nuclear structure, reaction and decay applications are specifically included. The complete NSR database is freely available at the websites of the National Nuclear Data Center http://www.nndc.bnl.gov/nsr and the International Atomic Energy Agency http://www-nds.iaea.org/nsr.Comment: 16 pages, 5 figure

Exploring relapse through a network analysis of residual depression and anxiety symptoms after cognitive behavioural therapy : a proof-of-concept study

Objective: Many patients relapse within one year of completing effective cognitive behavioural therapy (CBT) for depression and anxiety. Residual symptoms at treatment completion have been demonstrated to predict relapse, and so this study used network analyses to improve specificity regarding which residual anxiety and depression symptoms predict relapse. Method: A cohort study identified relapse cases following low- and high-intensity CBT in a stepped care psychological therapy service. The sample included N=867 ‘recovered’ treatment completers that attended a six-month follow-up review. At follow-up, N=93 patients had relapsed and N=774 remained in-remission. Networks of final treatment session depression (PHQ-9) and anxiety (GAD-7) symptoms were estimated for both sub-groups. Results: Qualitatively similar symptom networks were found. Difficulty concentrating was a highly central symptom in the relapse network, whilst of only average centrality in the remission network. In contrast, trouble relaxing was highly central in the remission network, whilst of only average centrality in the relapse network. Discussion: Identification of central residual symptoms holds promise in improving the specificity of prognostic models and the design of evidence-based relapse prevention strategies. The small sample of relapse cases limits this study’s ability to draw firm conclusions

An Intelligent Empowering Agent (IEA) to Provide Easily Understood and Trusted Health Information Appropriate to the User Needs

Most members of the public, including patients, usually obtain health information from Web searches using generic search engines, which is often overwhelming, too generic, and of poor quality. Although patients may be better informed, they are often none the wiser and not empowered to communicate with medical professionals so that their care is compatible with their needs, values, and best interests. Intelligent Empowering Agents (IEA) use AI to filter medical information and assist the user in the understanding of health information about specific complaints or health in general. We have designed and developed a prototype of an IEA that dialogues with the user in simple language, collects health information from the Web, and provides tailored, easily understood, and trusted information. It empowers users to create their own comprehensive and objective opinion on health matters that concern them. This paper describes the IEA main characteristics and presents the results of subjective and objective tests carried out to assess the effectiveness of the IEA

Initial results from the C1XS X-ray spectrometer on Chandrayaan-1

This article does not have an abstract

A comparison between ion characteristics observed by the POLAR and DMSP spacecraft in the high-latitude magnetosphere

We study here the injection and transport of ions in the convection-dominated region of the Earth’s magnetosphere. The total ion counts from the CAMMICE MICS instrument aboard the POLAR spacecraft are used to generate occurrence probability distributions of magnetospheric ion populations. MICS ion spectra are characterised by both the peak in the differential energy flux, and the average energy of ions striking the detector. The former permits a comparison with the Stubbs et al. (2001) survey of He2+ ions of solar wind origin within the magnetosphere. The latter can address the occurrences of various classifications of precipitating particle fluxes observed in the topside ionosphere by DMSP satellites (Newell and Meng, 1992). The peak energy occurrences are consistent with our earlier work, including the dawn-dusk asymmetry with enhanced occurrences on the dawn flank at low energies, switching to the dusk flank at higher energies. The differences in the ion energies observed in these two studies can be explained by drift orbit effects and acceleration processes at the magnetopause, and in the tail current sheet. Near noon at average ion energies of _1 keV, the cusp and open LLBL occur further poleward here than in the Newell and Meng survey, probably due to convectionrelated time-of-flight effects. An important new result is that the pre-noon bias previously observed in the LLBL is most likely due to the component of this population on closed field lines, formed largely by low energy ions drifting earthward from the tail. There is no evidence here of mass and momentum transfer from the solar wind to the LLBL by nonreconnection coupling. At higher energies (_2–20 keV), we observe ions mapping to the auroral oval and can distinguish between the boundary and central plasma sheets. We show that ions at these energies relate to a transition from dawnward to duskward dominated flow, this is evidence of how ion drift orbits in the tail influence the location and behaviour of the plasma populations in the magnetosphere

Dynamic prediction and identification of cases at risk of relapse following completion of low-intensity cognitive behavioural therapy

Objective: Low-intensity cognitive behavioural therapy (LiCBT) can help to alleviate acute symptoms of depression and anxiety, but some patients relapse after completing treatment. Little is known regarding relapse risk factors, limiting our ability to predict its occurrence. Therefore, this study aimed to develop a dynamic prediction tool to identify cases at high risk of relapse. Method: Data from a longitudinal cohort study of LiCBT patients was analysed using a machine learning approach (XGBoost). The sample included n=317 treatment completers who were followed-up monthly for 12 months (n=223 relapsed; 70%). An ensemble of XGBoost algorithms was developed in order to predict and adjust the estimated risk of relapse (vs maintained remission) in a dynamic way, at four separate time-points over the course of a patient’s journey. Results: Indices of predictive accuracy in a cross-validation design indicated adequate generalizability (AUC range = 0.72-0.84; PPV range = 71.2%-75.3%; NPV range = 56.0%-74.8%). Younger age, unemployment, (non-)linear treatment responses, and residual symptoms were identified as important predictors. Discussion: It is possible to identify cases at risk of relapse and predictive accuracy improves over time as new information is collected. Early identification coupled with targeted relapse prevention could considerably improve the longer-term effectiveness of LiCBT

CU Virginis - The First Stellar Pulsar

CU Virginis is one of the brightest radio emitting members of the magnetic chemically peculiar (MCP) stars and also one of the fastest rotating. We have now discovered that CU Vir is unique among stellar radio sources in generating a persistent, highly collimated, beam of coherent, 100% polarised, radiation from one of its magnetic poles that sweeps across the Earth every time the star rotates. This makes the star strikingly similar to a pulsar. This similarity is further strengthened by the observation that the rotating period of the star is lengthening at a phenomenal rate (significantly faster than any other astrophysical source - including pulsars) due to a braking mechanism related to its very strong magnetic field.Comment: 10 pages including 2 figure

Is clinical decision-making in stepped-care psychological services influenced by heuristics and biases?

Background. The manner in which heuristics and biases influence clinical decision-making has not been fully investigated and the methods previously used have been rudimentary. Aims. Two studies were conducted to design and test a trial-based methodology to assess the influence of heuristics and biases. Specifically, with a focus on how practitioners make decisions about suitability for therapy, treatment fidelity and treatment continuation in psychological services. Method. Study one (N=12) used a qualitative design to develop two clinical vignette-based tasks that had the aim of triggering heuristics and biases during clinical decision making. Study two (N=133) then used a randomised crossover experimental design and involved psychological wellbeing practitioners (PWPs) working in the Improving Access to Psychological Therapies (IAPT) programme in England. Vignettes evoked heuristics (anchoring and halo effects) and biased responses away from normative decisions. Participants completed validated measures of decision-making style. The two decision-making tasks from the vignettes yielded a clinical decision score (CDS; higher scores being more consistent with normative/unbiased decisions). Results. Experimental manipulations used to evoke heuristics did not significantly bias CDS. Decision-making style was not consistently associated with CDS. Clinical decisions were generally normative, although with some variability. Conclusions. Clinical decision-making can be “noisy” (i.e., variable across practitioners and occasions), but there was little evidence that this variability was systematically influenced by anchoring and halo effects in a stepped-care context