Acute lung injury in paediatric intensive care: course and outcome

Introduction: Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) carry a high morbidity and mortality (10-90%). ALI is characterised by non-cardiogenic pulmonary oedema and refractory hypoxaemia of multifactorial aetiology [1]. There is limited data about outcome particularly in children. Methods This retrospective cohort study of 85 randomly selected patients with respiratory failure recruited from a prospectively collected database represents 7.1% of 1187 admissions. They include those treated with High Frequency Oscillation Ventilation (HFOV). The patients were admitted between 1 November 1998 and 31 October 2000. Results: Of the 85, 49 developed acute lung injury and 47 had ARDS. There were 26 males and 23 females with a median age and weight of 7.7 months (range 1 day-12.8 years) and 8 kg (range 0.8-40 kg). There were 7 deaths giving a crude mortality of 14.3%, all of which fulfilled the Consensus I [1] criteria for ARDS. Pulmonary occlusion pressures were not routinely measured. The A-a gradient and PaO2/FiO2 ratio (median + [95% CI]) were 37.46 [31.82-43.1] kPa and 19.12 [15.26-22.98] kPa respectively. The non-survivors had a significantly lower PaO2/FiO2 ratio (13 [6.07-19.93] kPa) compared to survivors (23.85 [19.57-28.13] kPa) (P = 0.03) and had a higher A-a gradient (51.05 [35.68-66.42] kPa) compared to survivors (36.07 [30.2-41.94]) kPa though not significant (P = 0.06). Twenty-nine patients (59.2%) were oscillated (Sensormedics 3100A) including all 7 non-survivors. There was no difference in ventilation requirements for CMV prior to oscillation. Seventeen of the 49 (34.7%) were treated with Nitric Oxide including 5 out of 7 non-survivors (71.4%). The median (95% CI) number of failed organs was 3 (1.96-4.04) for non-survivors compared to 1 (0.62-1.62) for survivors (P = 0.03). There were 27 patients with isolated respiratory failure all of whom survived. Six (85.7%) of the non-survivors also required cardiovascular support.Conclusion: A crude mortality of 14.3% compares favourably to published data. The A-a gradient and PaO2/FiO2 ratio may be of help in morbidity scoring in paediatric ARDS. Use of Nitric Oxide and HFOV is associated with increased mortality, which probably relates to the severity of disease. Multiple organ failure particularly respiratory and cardiac disease is associated with increased mortality. ARDS with isolated respiratory failure carries a good prognosis in children

Mining Meaning from Wikipedia

Wikipedia is a goldmine of information; not just for its many readers, but also for the growing community of researchers who recognize it as a resource of exceptional scale and utility. It represents a vast investment of manual effort and judgment: a huge, constantly evolving tapestry of concepts and relations that is being applied to a host of tasks. This article provides a comprehensive description of this work. It focuses on research that extracts and makes use of the concepts, relations, facts and descriptions found in Wikipedia, and organizes the work into four broad categories: applying Wikipedia to natural language processing; using it to facilitate information retrieval and information extraction; and as a resource for ontology building. The article addresses how Wikipedia is being used as is, how it is being improved and adapted, and how it is being combined with other structures to create entirely new resources. We identify the research groups and individuals involved, and how their work has developed in the last few years. We provide a comprehensive list of the open-source software they have produced.Comment: An extensive survey of re-using information in Wikipedia in natural language processing, information retrieval and extraction and ontology building. Accepted for publication in International Journal of Human-Computer Studie

Spin liquid mediated RKKY interaction

Funding: DFG under CRC 1238 and Bonn-Cologne Graduate School of Physics and Astronomy (BCGS).We propose an RKKY-type interaction that is mediated by a spin liquid. If a spin liquid exists such an interaction could leave a fingerprint by ordering underlying localised moments such as nuclear spins. This interaction has a unique phenomenology that is distinct from the RKKY interaction found in fermionic systems; most notably the lack of a Fermi surface and absence of the requirement for itinerant electrons, since most spin liquids are insulators. We demonstrate that the interaction is predominately shaped by the lattice symmetries of the underlying spin liquid. As a working example we investigate the possible ordering of nuclear spins that interact through an underlying lattice of the two-dimensional spin-1/2 kagome antiferromagnet (KHAF), although the treatment remains general and can be extended to other spin liquids and dimensions. We find that several different nuclear spin orderings minimise the RKKY-type energy induced by the KHAF but are unstable due to a zero-energy flat magnon band in linear spin-wave theory. Despite this we show that a small magnetic field is able to gap out this magnon spectrum resulting in an intricate nuclear magnetism.Publisher PDFPeer reviewe

Nanoscale structuring of tungsten tip yields most coherent electron point-source

This report demonstrates the most spatially-coherent electron source ever reported. A coherence angle of 14.3 +/- 0.5 degrees was measured, indicating a virtual source size of 1.7 +/-0.6 Angstrom using an extraction voltage of 89.5 V. The nanotips under study were crafted using a spatially-confined, field-assisted nitrogen etch which removes material from the periphery of the tip apex resulting in a sharp, tungsten-nitride stabilized, high-aspect ratio source. The coherence properties are deduced from holographic measurements in a low-energy electron point source microscope with a carbon nanotube bundle as sample. Using the virtual source size and emission current the brightness normalized to 100 kV is found to be 7.9x10^8 A/sr cm^2

Visual analytics for collaborative human-machine confidence in human-centric active learning tasks

Active machine learning is a human-centric paradigm that leverages a small labelled dataset to build an initial weak classifier, that can then be improved over time through human-machine collaboration. As new unlabelled samples are observed, the machine can either provide a prediction, or query a human ‘oracle’ when the machine is not confident in its prediction. Of course, just as the machine may lack confidence, the same can also be true of a human ‘oracle’: humans are not all-knowing, untiring oracles. A human’s ability to provide an accurate and confident response will often vary between queries, according to the duration of the current interaction, their level of engagement with the system, and the difficulty of the labelling task. This poses an important question of how uncertainty can be expressed and accounted for in a human-machine collaboration. In short, how can we facilitate a mutually-transparent collaboration between two uncertain actors - a person and a machine - that leads to an improved outcome?In this work, we demonstrate the benefit of human-machine collaboration within the process of active learning, where limited data samples are available or where labelling costs are high. To achieve this, we developed a visual analytics tool for active learning that promotes transparency, inspection, understanding and trust, of the learning process through human-machine collaboration. Fundamental to the notion of confidence, both parties can report their level of confidence during active learning tasks using the tool, such that this can be used to inform learning. Human confidence of labels can be accounted for by the machine, the machine can query for samples based on confidence measures, and the machine can report confidence of current predictions to the human, to further the trust and transparency between the collaborative parties. In particular, we find that this can improve the robustness of the classifier when incorrect sample labels are provided, due to unconfidence or fatigue. Reported confidences can also better inform human-machine sample selection in collaborative sampling. Our experimentation compares the impact of different selection strategies for acquiring samples: machine-driven, human-driven, and collaborative selection. We demonstrate how a collaborative approach can improve trust in the model robustness, achieving high accuracy and low user correction, with only limited data sample selections

Siting prisons, sighting communities: geographies of objection in a planning process

This paper reviews the planning process for a Scottish prison located near a former mining village. Analysing the letters of objection submitted by residents offers an opportunity to explore local views about prison and community and to relate these to the unique social and spatial history of the area. The planning process itself structured how residents were able to express themselves and defined what counted as a relevant objection. After deconstructing this process, the paper then restores and uses as a framework for analysis three geographies of objection stripped from local responses to the development proposal: the emotional, temporal, and spatial. Emotional expressions of objection added intensity and gave meaning to claims about the historical decline of the region and also conveyed a deep sense of the proposed building site as a lived space. Particular grounds of opposition—over fear of strangers, the fragility of a local orchid, and the pollution from mining—provide an opportunity to explore the complex nature of place meaning and community identity, ultimately leading to a conclusion that the meaning of place is always in flux. The paper argues that Simmel’s classic concept of the stranger, as the outsider who comes to stay, offers a useful analytic in understanding how the quality of proximal remoteness that prisons and other unwanted developments constitute participates in a constantly evolving sense of the local

Spatial Analysis of Temporal Changes in the Pandemic of Severe Cassava Mosaic Disease in Northwestern Tanzania

Published online: 8 Sept 2017To improve understanding of the dynamics of the cassava mosaic disease (CMD) pandemic front, geospatial approaches were applied to the analysis of 3 years’ data obtained from a 2-by-2° (approximately 222-by-222 km) area of northwestern Tanzania. In total, 80 farmers’ fields were assessed in each of 2009, 2010, and 2011, with 20 evenly distributed fields per 1-by-1° quadrant. CMD-associated variables (CMD incidence, CMD severity, vector-borne CMD infection, and vector abundance) increased in magnitude from 2009 to 2010 but showed little change from 2010 to 2011. Increases occurred primarily in the two westernmost quadrants of the study area. A pandemic “front” was defined by determining the values of CMD incidence and whitefly abundance where predicted disease gradients were greatest. The pandemic-associated virus (East African cassava mosaic virus-Uganda) and vector genotype (Bemisia tabaci sub-Saharan Africa 1–subgroup 1) were both present within the area bounded by the CMD incidence front but both also occurred ahead of the front. The average speed and direction of movement of the CMD incidence front (22.9 km/year; southeast) and whitefly abundance front (46.6 km/year; southeast) were calculated, and production losses due to CMD were estimated to range from US$4.3 million to 12.2 million

Miniaturized photoacoustic trace gas sensing using a raman fiber amplifier

This paper presents the development of a Raman fiber amplifier optical source with a maximum output power of 1.1 W centered around 1651 nm, and its application in miniaturized 3D printed photoacoustic spectroscopy (PAS) trace gas sensing of methane. The Raman amplifier has been constructed using 4.5 km of dispersion shifted fiber, a 1651 nm DFB seed laser and a commercial 4W EDFA pump. The suppression of stimulated Brillouin scattering (SBS) using a high frequency modulation of the seed laser is investigated for a range of frequencies, leading to an increase in optical output power of the amplifier and reduction of its noise content. The amplifier output was used as the source for a miniature PAS sensor by applying a second modulation to the seed laser at the resonant frequency of 15.2 kHz of the miniature 3D printed gas cell. For the targeted methane absorption line at 6057 cm-1 the sensor system performance and influence of the SBS suppression is characterized, leading to a detection limit (1σ) of 17 ppb methane for a signal acquisition time of 130 s, with a normalized noise equivalent absorption coefficient of 4.1•10-9 cm-1 W Hz-1/2 for the system