An X-Ray Study of the Supernova Remnant G290.1-0.8

G290.1-0.8 (MSH 11-61A) is a supernova remnant (SNR) whose X-ray morphology is centrally bright. However, unlike the class of X-ray composite SNRs whose centers are dominated by nonthermal emission, presumably driven by a central pulsar, we show that the X-ray emission from G290.1-0.8 is thermal in nature, placing the remnant in an emerging class which includes such remnants as W44, W28, 3C391, and others. The evolutionary sequence which leads to such X-ray properties is not well understood. Here we investigate two scenarios for such emission: evolution in a cloudy interstellar medium, and early-stage evolution of a remnant into the radiative phase, including the effects of thermal conduction. We construct models for these scenarios in an attempt to reproduce the observed center-filled X-ray properties of G290.1-0.8, and we derive the associated age, energy, and ambient density conditions implied by the models. We find that for reasonable values of the explosion energy, the remnant age is of order (1 - 2) x 10^{4} yr. This places a fairly strong constraint on any association between G290.1-0.8 and PSR J1105-610, which would require an anomalously large velocity for the pulsar.Comment: 7 pages, 7 figures, ApJ, accepte

TOPLESS Regulates Apical Embryonic Fate in Arabidopsis

The embryos of seed plants develop with an apical shoot pole and a basal root pole. In Arabidopsis, the topless-1 (tpl-1) mutation transforms the shoot pole into a second root pole. Here, we show that TPL resembles known transcriptional corepressors and that tpl-1 acts as a dominant negative mutation for multiple TPL-related proteins. Mutations in the putative coactivator HISTONE ACETYLTRANSFERASE GNAT SUPERFAMILY1 suppress the tpl-1 phenotype. Mutations in HISTONE DEACETYLASE19, a putative corepressor, increase the penetrance of tpl-1 and display similar apical defects. These data point to a transcriptional repression mechanism that prevents root formation in the shoot pole during Arabidopsis embryogenesis

PREPARE: guidelines for planning animal research and testing

There is widespread concern about the quality, reproducibility and translatability of studies involving research animals. Although there are a number of reporting guidelines available, there is very little overarching guidance on how to plan animal experiments, despite the fact that this is the logical place to start ensuring quality. In this paper we present the PREPARE guidelines: Planning Research and Experimental Procedures on Animals: Recommendations for Excellence. PREPARE covers the three broad areas which determine the quality of the preparation for animal studies: formulation, dialogue between scientists and the animal facility, and quality control of the various components in the study. Some topics overlap and the PREPARE checklist should be adapted to suit specific needs, for example in field research. Advice on use of the checklist is available on the Norecopa website, with links to guidelines for animal research and testing, at https://norecopa.no/PREPARE

Cellular Dynamical Mean Field Approach to Strongly Correlated Systems

We propose a cellular version of dynamical-mean field theory which gives a natural generalization of its original single-site construction and is formulated in different sets of variables. We show how non-orthogonality of the tight-binding basis sets enters the problem and prove that the resulting equations lead to manifestly causal self energies.Comment: RevTex, 4 pages, 1 embedded figur

Machine learning to refine decision making within a syndromic surveillance service

Background: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical alarms highlighting potential activity of public health importance. All alarms must be assessed to confirm whether they are of public health importance. In England, approximately 100 alarms are generated daily and, although their analysis is formalised through a risk assessment process, the process requires notable time, training, and maintenance of an expertise base to determine which alarms are of public health importance. The process is made more complicated by the observation that only 0.1% of statistical alarms are deemed to be of public health importance. Therefore, the aims of this study were to evaluate machine learning as a tool for computer-assisted human decision-making when assessing statistical alarms. Methods: A record of the risk assessment process was obtained from Public Health England for all 67505 statistical alarms between August 2013 and October 2015. This record contained information on the characteristics of the alarm (e.g. size, location). We used three Bayesian classifiers- naïve Bayes, tree-augmented naïve Bayes and Multinets - to examine the risk assessment record in England with respect to the final ‘Decision’ outcome made by an epidemiologist of ‘Alert’, ‘Monitor’ or ‘No-action’. Two further classifications based upon tree-augmented naïve Bayes and Multinets were implemented to account for the predominance of ‘No-action’ outcomes. Results: The attributes of each individual risk assessment were linked to the final decision made by an epidemiologist, providing confidence in the current process. The naïve Bayesian classifier performed best, correctly classifying 51.5% of ‘Alert’ outcomes. If the ‘Alert’ and ‘Monitor’ actions are combined then performance increases to 82.6% correctly classified. We demonstrate how a decision support system based upon a naïve Bayes classifier could be operationalised within an operational syndromic surveillance system. Conclusions: Within syndromic surveillance systems, machine learning techniques have the potential to make risk assessment following statistical alarms more automated, robust, and rigorous. However, our results also highlight the importance of specialist human input to the process

Syndromic surveillance of influenza-like illness in Scotland during the influenza A H1N1v pandemic and beyond

Syndromic surveillance refers to the rapid monitoring of syndromic data to highlight and follow outbreaks of infectious diseases, increasing situational awareness. Such systems are based upon statistical models to described routinely collected health data. We describe a working exception reporting system (ERS) currently used in Scotland to monitor calls received to the NHS telephone helpline, NHS24. We demonstrate the utility of the system to describe the time series data from NHS24 both at an aggregated Scotland level and at the individual health board level for two case studies, firstly during the initial phase of the 2009 Influenza A H1N1v and secondly for the emergence of seasonal influenza in each winter season from 2006/07 and 2010/11. In particular, we focus on a localised cluster of infection in the Highland health board and the ability of the system to highlight this outbreak. Caveats of the system, including the effect of media reporting of the pandemic on the results and the associated statistical issues, will be discussed. We discuss the adaptability and timeliness of the system and how this continues to form part of a suite of surveillance used to give early warnings to public health decision makers

Positive youth development in swimming: clarification and consensus of key psychosocial assets

The purpose of this study was to gain a more cohesive understanding of the assets considered necessary to develop in young swimmers to ensure both individual and sport specific development. This two stage study involved (a) a content analysis of key papers to develop a list of both psychosocial skills for performance enhancement and assets associated with positive youth development, and (b) in-depth interviews involving ten expert swim coaches, practitioners and youth sport scholars. Five higher order categories containing seventeen individual assets emerged. These results are discussed in relation to both existing models of positive youth development and implications for coaches, practitioners and parents when considering the psychosocial development of young British swimmers