The compact, ∼1 kpc host galaxy of a quasar at a redshift of 7.1

We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of the [C ii] fine-structure line and the underlying far-infrared (FIR) dust continuum emission in J1120+0641, the most distant quasar currently known ($z=7.1$). We also present observations targeting the CO(2–1), CO(7–6), and [C i] 369 μm lines in the same source obtained at the Very Large Array and Plateau de Bure Interferometer. We find a [C ii] line flux of ${F}_{[{\rm{C}}{\rm{II}}]}=1.11\pm 0.10$ Jy $\mathrm{km}\,{{\rm{s}}}^{-1}$ and a continuum flux density of ${S}_{227\mathrm{GHz}}=0.53\pm 0.04$ mJy beam−1, consistent with previous unresolved measurements. No other source is detected in continuum or [C ii] emission in the field covered by ALMA (~ 25''). At the resolution of our ALMA observations (0farcs23, or 1.2 kpc, a factor of ~70 smaller beam area compared to previous measurements), we find that the majority of the emission is very compact: a high fraction (~80%) of the total line and continuum flux is associated with a region 1–1.5 kpc in diameter. The remaining ~20% of the emission is distributed over a larger area with radius lesssim4 kpc. The [C ii] emission does not exhibit ordered motion on kiloparsec scales: applying the virial theorem yields an upper limit on the dynamical mass of the host galaxy of $(4.3\pm 0.9)\times {10}^{10}$ ${M}_{\odot }$, only ~20 × higher than the central black hole (BH). The other targeted lines (CO(2–1), CO(7–6), and [C i]) are not detected, but the limits of the line ratios with respect to the [C ii] emission imply that the heating in the quasar host is dominated by star formation, and not by the accreting BH. The star formation rate (SFR) implied by the FIR continuum is 105–340 ${M}_{\odot }\,{\mathrm{yr}}^{-1}$, with a resulting SFR surface density of ~100–350 ${M}_{\odot }\,{\mathrm{yr}}^{-1}$ kpc−2, well below the value for Eddington-accretion-limited star formation

Context Detection, Categorization and Connectivity for Advanced Adaptive Integrated Navigation

Context is the environment that a navigation system operates in and the behaviour of its host vehicle or user. The type and quality of signals and environmental features available for positioning varies with the environment. For example, GNSS provides high-quality positioning in open environments, low-quality positioning in dense urban environments and no solution at all deep indoors. The behaviour of the host vehicle (or pedestrian) is also important. For example, pedestrian, car and train navigation all require different map-matching techniques, different motion constraints to limit inertial navigation error growth, and different dynamic models in a navigation filter [1]. A navigation system design should therefore be matched to its context. However, the context can change, particularly for devices, such as smartphones, which move between indoor and outdoor environments and can be stationary, on a pedestrian, or in a vehicle. For best performance, a navigation system should therefore be able to detect its operating context and adapt accordingly; this is context-adaptive positioning [1]. Previous work on context-adaptive navigation and positioning has focused on individual subsystems. For example, there has been substantial research into determining the motion type and sensor location for pedestrian dead reckoning using step detection [2-4]. Researchers have also begun to investigate context-adaptive (or cognitive) GNSS [5-7]. However, this paper considers context adaptation across an integrated navigation system as a whole. The paper addresses three aspects of context-adaptive integrated navigation: context detection, context categorization and context connectivity. It presents experimental results showing how GNSS C/N0 measurements, frequency-domain MEMS inertial sensor measurements and Wi-Fi signal availability could be used to detect both the environmental and behavioural contexts. It then looks at how context information could be shared across the different components of an integrated navigation system. Finally, the concept of context connectivity is introduced to improve the reliability of context detection. GNSS C/N0 measurement distributions, obtained using a smartphone, and Wi-Fi reception data collected over a range of indoor, urban and open environments will be compared to identify suitable features from which the environmental context may be derived. In an open environment, strong GNSS signals will be received from all directions. In an urban environment, fewer strong signals will be received and only from certain directions. Inside a building, nearly all GNSS signals will be much weaker than outside. Wi-Fi signals essentially vary with the environment in the opposite way to GNSS. Indoors, more access points (APs) can be received at higher signal strengths and there is greater variation in RSS. In urban environments, large numbers of APs can still be received, but at lower signal strengths [6]. Finally, in open environments, few APs, if any, will be received. Behavioural context is studied using an IMU. Although an Xsens MEMS IMU is used in this study, smartphone inertial sensors are also suitable. Pedestrian, car and train data has been collected under a range of different motion types and will be compared to identify context-dependent features. Early indications are that, as well as detecting motion, it is also possible to distinguish nominally-stationary IMUs that are placed in a car, on a person or on a table from the frequency spectra of the sensor measurements. The exchange of context information between subsystems in an integrated navigation system requires agreement on the definitions of those contexts. As different subsystems are often supplied by different organisations, it is desirable to standardize the context definitions across the whole navigation and positioning community. This paper therefore proposes a framework upon which a “context dictionary” could be constructed. Environmental and behavioural contexts are categorized separately and a hierarchy of attributes is proposed to enable some subsystems to work with highly specific context categories and others to work with broader categories. Finally, the concept of context connectivity is introduced. This is analogous to the road link connectivity used in map matching [8]. As context detection involves the matching of measurement data to stored context profiles, there will always be occurrences of false or ambiguous context identification. However, these may be minimized by using the fact that it is only practical to transition directly between certain pairs of contexts. For example, it is not normally possible to move directly from an airborne to an indoor environment as an aircraft must land first. Thus, the air and land contexts are connected, as are the land and indoor contexts, but the air and indoor contexts are not. Thus, by only permitting contexts that are connected to the previous context, false and ambiguous context detection is reduced. Robustness may be further enhanced by considering location-dependent connectivity. For example, people normally board and leave trains at stations and fixed-wing aircraft typically require an airstrip to take off and land. / References [1] Groves, P. D., Principles of GNSS, inertial, and multi-sensor integrated navigation systems, Second Edition, Artech House, 2013. [2] Park, C. G., et al., “Adaptive Step Length Estimation with Awareness of Sensor Equipped Location for PNS,” Proc. ION GNSS 2007. [3] Frank, K., et al., “Reliable Real-Time Recognition of Motion Related Human Activities Using MEMS Inertial Sensors,” Proc. ION GNSS 2010. [4] Pei, L., et al., “Using Motion-Awareness for the 3D Indoor Personal Navigation on a Smartphone,” Proc. ION GNSS 2011. [5] Lin, T., C. O’Driscoll, and G. Lachapelle, “Development of a Context-Aware Vector-Based High-Sensitivity GNSS Software Receiver,” Proc. ION ITM 2011. [6] Shafiee, M., K., O’Keefe, and G. Lachapelle, “Context-aware Adaptive Extended Kalman Filtering Using Wi-Fi Signals for GPS Navigation,” Proc. ION GNSS 2011. [7] Shivaramaiah, N. C., and A. G. Dempster, “Cognitive GNSS Receiver Design: Concept and Challenges,” Proc. ION GNSS 2011. [8] Quddus, M. A., High Integrity Map Matching Algorithms for Advanced Transport Telematics Applications, PhD Thesis, Imperial College London, 2006

A DETAILED PHOTOMETRIC AND SPECTROSCOPIC STUDY OF THE 2011 OUTBURST OF THE RECURRENT NOVA T Pyxidis FROM 0.8 TO 250 DAYS AFTER DISCOVERY

We investigated the optical light curve of T Pyx during its 2011 outburst through compiling a database of Solar Mass Ejection Imager (SMEI) and AAVSO observations. The SMEI light curve, providing unprecedented detail covering t=1.5-49 days post-discovery, was divided into four phases based on the idealised nova optical light curve; the initial rise (1.5-3.3 days), the pre-maximum halt (3.3-13.3 days), the final rise (14.7-27.9 days), and the early decline (27.9 days - -). The SMEI light curve contains a strongly detected period of 1.44_0.05 days during the pre-maximum halt phase. These oscillations resemble those found in recent TNR models arising from instabilities in the expanding envelope. No spectral variations that mirror the light curve periodicity were found however. The marked dip at t_22-24 days just before light curve maximum at t=27.9 days may represent the same (shorter duration) phenomenon seen in other novae observed by SMEI and present in some model light curves. The spectra from the 2m Liverpool Telescope and SMARTS 1.5m telescope were obtained from t=0.8-80.7 and 155.1-249.9 days, covering the major phases of development. The nova was observed very early in its rise where a distinct high velocity ejection phase was evident with derived Vej_4000 km

Novel Environmental Features for Robust Multisensor Navigation

Many navigation techniques have now become so reliant on GNSS that there is no back up when there is limited or no signal reception. If there is interference, intentional or otherwise, with the signal, navigation could be lost or become misleading [1]. Other navigation techniques harness different technologies such as Wi-Fi [2], eLoran and inertial navigation. However, each of these techniques has its own limitations, such as coverage, degradation in urban areas or solution drift [3]. Therefore there is a need for new navigation and positioning techniques that may be integrated with GNSS to increase the reliability of the system as a whole. This paper presents the results of a feasibility study to identify a set of novel environmental features that could be used for navigation in the temporary absence of GNSS or degradation of the signal. By measuring these features during times of GNSS availability a map can be produced. This can be referred to during times of limited reception, a principle already used for some Wi-Fi positioning techniques [2]. Therefore a “measurable” can be defined as a feature either man-made or natural that is spatially distinct and has limited temporal variation. Possibilities considered include magnetic anomalies [4], light intensity and road signs. Firstly, a brainstorming exercise and a literature study were conducted to generate a list of possible environmental features that was assessed for the viability of each candidate. The features were ranked according to three criteria: practicality, precision and coverage. The definition of practicality for each measurable was that a suitable detector must be installable on a road vehicle, particularly an emergency vehicle, at a reasonable cost with minimal alterations to the vehicle. Precision was defined in terms of the spatial variation of the environmental feature and thus the accuracy with which position information might be derived from it. Coverage was assessed in terms of the availability of the feature over a range of different environments. Continuous coverage is not required because the new measurables may be used in combination and integrated with dead reckoning techniques, such as odometry and inertial navigation [3]. The outcome of the viability study was used to determine which features are to be experimentally tested. Magnetic anomalies, road texture and a dozen other environmental features were found to be worth investigation. Features which were discounted include wind speed and pulsars [5]. The initial experiment was carried out on foot in Central London. The same tests were repeated on two separate days, with a closed loop circuit walked three times on each occasion. This experiment used an Inertial Measurement Unit (IMU), comprising accelerometer and gyro triads, together with a barometer, three-axis magnetometer and GNSS receiver. The experiment was also recorded using a camcorder from the point of view of a pedestrian, enabling visual and audio features of the environment to be assessed. Magnetic anomalies were found to be a promising source of position information. Peaks in the magnetometer data were observed on all rounds at approximately the same positions. There were also similarities seen in the temperature profiles after correcting for the temporal variation of the background temperature. Another potential source of position information was found to be text-based signs. It is relatively simple to extract text from camera images and it is easily stored in a feature database. However, methods of dealing with identically-worded signs in close proximity will need to be developed. Sound levels were analysed in 10s intervals for the mean, minimum and maximum sound volume. There was no clear correlation observed between the different rounds of the experiment. Due to the pedestrian experimental results sound levels of the surroundings will not be used in further experimentation. An alternative area of enquiry for using sound (in the vehicular experiments) is using microphones to indirectly measure road texture based on the noise from the wheel contact with the road [6]. The paper will also present results of road vehicle experiments. Multiple circuits of the same routes will be compared. Different environments will be assessed including rural, dual carriageways, suburban and urban roads. Sensors to be used include the IMU and 3-axis magnetometer from the pedestrian experiment, a barometer, gas sensors, a microphone, an axle-mounted accelerometer, an ambient light sensor and a thermometer. These will be placed either on, inside or under the vehicle as determined by the individual needs of the sensors. The results will be used to determine which of these sensors could be potentially used for a multisensor integrated navigation system and also the environments in which they work optimally. Using the results of the three feasibility study phases (literature review, pedestrian and road experiment) the next project stage will be to produce a demonstration system that uses the most feasible features of the environment and creates a map database during times GNSS is present. This database will then be used for navigation in times of need. In the long term, it is envisaged that this technique will be implemented cooperatively, with a batch of vehicles collecting feature data and contributing it to a common shared database. / References [1] Thomas, M., et al., Global Navigation Space Systems: Reliance and Vulnerabilities, London, UK: Royal Academy of Engineering, 2011. [2] Jones, K., L. Liu, and F. Alizadeh-Shabdiz, “Improving Wireless Positioning with Look-ahead Map-Matching,” Proc. MobiQuitous 2007, Phildaelphia, PA, February 2008, pp. 1-8. [3] Groves, P.D., Principles of GNSS, Inertial, and Multisensor Intergrated Navigation Systems, Second Edition, Artech House, 2013. [4] Judd, T., and T. Vu, “Use of a New Pedometric Dead Reckoning Module in GPS Denied Environments,” Proc. IEEE/ION PLANS, Monterey, CA, May 2008, pp. 120?128. [5] Walter, D. J., "Feasibility study of novel environmental feature mapping to bridge GNSS outage," Young Navigator Conference, London, 2012. [6] Mircea, M., et al., “Strategic mapping of the ambient noise produced by road traffic, accordingly to European regulations,” Proc. IEEE International Conference on Automation, Quality and Testing, Robotics, Cluj Napoca, Romania, May 2008

Spectroscopic and Photometric Development of T Pyxidis (2011) from 0.8 to 250 Days After Discovery

We investigated the optical light curve of T Pyx during its 2011 outburst through compiling a database of SMEI and AAVSO observations. The SMEI light curve, providing unprecedented detail with high cadence data during t=1.5-49 days post-discovery, was divided into four phases based on the idealised nova optical light curve; the initial rise, the pre-maximum halt (or the 'plateau'), the final rise, and the early decline. Variation in the SMEI light curve reveals a strongly detected period of 1.44\pm0.04 days before the visual maximum. The spectra from the LT and SMARTS telescopes were investigated during t=0.8-80.7 and 155.1-249.9 days. The nova was observed very early in its rise and a distinct high velocity ejection phase was evident. A marked drop and then gradual increase in derived ejection velocities were present. Here we propose two different stages of mass loss, a short-lived phase occurring immediately after outburst followed by a more steadily evolving and higher mass loss phase. The overall spectral development follows that typical of a Classical Nova and comparison to the photometric behaviour reveals consistencies with the simple evolving pseudo-photosphere model of the nova outburst. The optical spectra are also compared to X-ray and radio light curves. Weak [Fe X] 6375A emission was marginally detected before the rise in X-ray emission. The middle of the plateau in the X-ray light curve is coincident with the appearance of high ionization species detected in optical spectra and the peak of the high frequency radio flux

Clustering in surgical trials : database of intracluster correlations

PMID: 22217216 [PubMed - indexed for MEDLINE] PMCID: PMC3311136 Free PMC ArticlePeer reviewedPublisher PD

Observation of an unexpected third receptor molecule in the crystal structure of human interferon-γ receptor complex

AbstractBackground: Molecular interactions among cytokines and cytokine receptors form the basis of many cell-signaling pathways relevant to immune function. Interferon-γ (IFN-γ) signals through a multimeric receptor complex consisting of two different but structurally related transmembrane chains: the high-affinity receptor-binding subunit (IFN-γRα) and a species-specific accessory factor (AF-1 or IFN-γRβ). In the signaling complex, the two receptors probably interact with one another through their extracellular domains. Understanding the atomic interactions of signaling complexes enhances the ability to control and alter cell signaling and also provides a greater understanding of basic biochemical processes.Results: The crystal structure of the complex of human IFN-γ with the soluble, glycosylated extracellular part of IFN-γRα has been determined at 2.9 Å resolution using multiwavelength anomalous diffraction methods. In addition to the expected 2:1 complex, the crystal structure reveals the presence of a third receptor molecule not directly associated with the IFN-γ dimer. Two distinct intermolecular contacts, involving the edge strands of the C-terminal domains, are observed between this extra receptor and the 2:1 receptor–ligand complex thereby forming a 3:1 complex.Conclusions: The observed interactions in the 2:1 complex of the high-affinity cell-surface receptor with the IFN-γ cytokine are similar to those seen in a previously reported structure where the receptor chains were not glycosylated. The formation of β-sheet packing interactions between pairs of IFN-γRα receptors in these crystals suggests a possible model for receptor oligomerization of Rα and the structurally homologous Rβ receptors in the fully active IFN-γ signaling complex

Protocol for the CHEST Australia trial: A phase II randomised controlled trial of an intervention to reduce time-to-consult with symptoms of lung cancer

© 2015, BMJ Publishing Group. All rights reserved. Introduction: Lung cancer is the most common cancer worldwide, with 1.3 million new cases diagnosed every year. It has one of the lowest survival outcomes of any cancer because over two-thirds of patients are diagnosed when curative treatment is not possible. International research has focused on screening and community interventions to promote earlier presentation to a healthcare provider to improve early lung cancer detection. This paper describes the protocol for a phase II, multisite, randomised controlled trial, for patients at increased risk of lung cancer in the primary care setting, to facilitate early presentation with symptoms of lung cancer. Methods/analysis: The intervention is based on a previous Scottish CHEST Trial that comprised of a primary-care nurse consultation to discuss and implement a self-help manual, followed by selfmonitoring reminders to improve symptom appraisal and encourage help-seeking in patients at increased risk of lung cancer. We aim to recruit 550 patients from two Australian states: Western Australia and Victoria. Patients will be randomised to the Intervention (a health consultation involving a self-help manual, monthly prompts and spirometry) or Control (spirometry followed by usual care). Eligible participants are long-term smokers with at least 20 pack years, aged 55 and over, including ex-smokers if their cessation date was less than 15 years ago. The primary outcome is consultation rate for respiratory symptoms. Ethics and dissemination: Ethical approval has been obtained from The University of Western Australia's Human Research Ethics Committee (RA/4/1/6018) and The University of Melbourne Human Research Committee (1 441 433). A summary of the results will be disseminated to participants and we plan to publish the main trial outcomes in a single paper. Further publications are anticipated after further data analysis. Findings will be presented at national and international conferences from late 2016. Trial registration number: Australian New Zealand Clinical Trial Registry ACTRN 1261300039 3752

A systematic review of the use of an expertise-based randomised controlled trial design

Acknowledgements JAC held a Medical Research Council UK methodology (G1002292) fellowship, which supported this research. The Health Services Research Unit, Institute of Applied Health Sciences (University of Aberdeen), is core-funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. Views express are those of the authors and do not necessarily reflect the views of the funders.Peer reviewedPublisher PD