Bringing values back into evidence-based nursing: the role of patients in resisting empiricism

We examine problems resulting from the narrow empirical focus associated with evidence-based nursing, including the deleterious influence of vested interests, disattention to patients’ experiences, underestimation of the importance of social processes, lack of an individualized research perspective, marginalization of other forms of knowledge, and the undermining of patients’ autonomy. Addressing each problem in turn, we argue that inclusion of patients at all stages of evidence-based practice can counter or ameliorate these problems. While we concede that patient involvement is not a complete solution to the problem of empiricism, it is the most effective means available to defend nursing values.

Independent Discovery of the Transiting Exoplanet HAT-P-14b

We present SuperWASP observations of HAT-P-14b, a hot Jupiter discovered by Torres et al. The planet was found independently by the SuperWASP team and named WASP-27b after follow-up observations had secured the discovery, but prior to the publication by Torres et al. Our analysis of HAT-P-14/WASP-27 is in good agreement with the values found by Torres et al. and we provide additional evidence against astronomical false positives. Due to the brightness of the host star, V-mag = 10, HAT-P-14b is an attractive candidate for further characterization observations. The planet has a high impact parameter and the primary transit is close to grazing. This could readily reveal small deviations in the orbital parameters indicating the presence of a third body in the system, which may be causing the small but significant orbital eccentricity. Our results suggest that the planet may undergo a grazing secondary eclipse. However, even a non-detection would tightly constrain the system parameters.

WASP-35b, WASP-48b, and HAT-P-30b/WASP-51b: Two New Planets and an Independent Discovery of a Hat Planet

We report the detection of WASP-35b, a planet transiting a metal-poor ([Fe/H] = -0.15) star in the Southern hemisphere, WASP-48b, an inflated planet which may have spun-up its slightly evolved host star of 1.75 R sun in the Northern hemisphere, and the independent discovery of HAT-P-30b/WASP-51b, a new planet in the Northern hemisphere. Using WASP, RISE, Faulkes Telescope South, and TRAPPIST photometry, with CORALIE, SOPHIE, and NOT spectroscopy, we determine that WASP-35b has a mass of 0.72 ± 0.06 MJ and radius of 1.32 ± 0.05RJ , and orbits with a period of 3.16 days, WASP-48b has a mass of 0.98 ± 0.09 MJ , radius of 1.67 ± 0.10 RJ , and orbits in 2.14 days, while HAT-P-30b/WASP-51b, with an orbital period of 2.81 days, is found to have a mass of 0.76 ± 0.05 MJ and radius of 1.42 ± 0.03 RJ , agreeing with values of 0.71 ± 0.03 MJ and 1.34 ± 0.07 RJ reported for HAT-P-30b.

Multicamera sport player tracking with Bayesian estimation of measurements

We propose a complete application capable of tracking multiple objects in an environment monitored by multiple cameras. The system has been specially developed to be applied to sport games, and it has been evaluated in a real association-football stadium. Each target is tracked using a local importance-sampling particle filter in each camera, but the final estimation is made by combining information from the other cameras using a modified unscented Kalman filter algorithm. Multicamera integration enables us to compensate for bad measurements or occlusions in some cameras thanks to the other views it offers. The final algorithm results in a more accurate system with a lower failure rate. (C) 2009 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3114605]

Risk-informed decision-making in the presence of epistemic uncertainty

An important issue in risk analysis is the distinction between epistemic and aleatory uncertainties. In this paper, the use of distinct representation formats for aleatory and epistemic uncertainties is advocated, the latter being modelled by sets of possible values. Modern uncertainty theories based on convex sets of probabilities are known to be instrumental for hybrid representations where aleatory and epistemic components of uncertainty remain distinct. Simple uncertainty representation techniques based on fuzzy intervals and p-boxes are used in practice. This paper outlines a risk analysis methodology from elicitation of knowledge about parameters to decision. It proposes an elicitation methodology where the chosen representation format depends on the nature and the amount of available information. Uncertainty propagation methods then blend Monte Carlo simulation and interval analysis techniques. Nevertheless, results provided by these techniques, often in terms of probability intervals, may be too complex to interpret for a decision-maker and we, therefore, propose to compute a unique indicator of the likelihood of risk, called confidence index. It explicitly accounts for the decisionmaker’s attitude in the face of ambiguity. This step takes place at the end of the risk analysis process, when no further collection of evidence is possible that might reduce the ambiguity due to epistemic uncertainty. This last feature stands in contrast with the Bayesian methodology, where epistemic uncertainties on input parameters are modelled by single subjective probabilities at the beginning of the risk analysis process.

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data

The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.

Serum eosinophil cationic protein (ECP):reference values in healthy nonatopic children

BACKGROUND: Although serum ECP concentrations have been reported in normal children, there are currently no published upper cutoff reference limits for serum ECP in normal, nonatopic, nonasthmatic children aged 1-15 years.
METHODS: We recruited 123 nonatopic, nonasthmatic normal children attending the Royal Belfast Hospital for Sick Children for elective surgery and measured serum ECP concentrations. The effects of age and exposure to environmental tobacco smoke (ETS) on the upper reference limits were studied by multiple regression and fractional polynomials.
RESULTS: The median serum ECP concentration was 6.5 microg/l and the 95th and 97.5 th percentiles were 18.8 and 19.9 microg/l. The median and 95th percentile did not vary with age. Exposure to ETS was not associated with altered serum ECP concentrations (P = 0.14).
CONCLUSIONS: The 95th and 97.5 th percentiles for serum ECP for normal, nonatopic, nonasthmatic children (aged 1-15 years) were 19 and 20 microg/l, respectively. Age and exposure to parental ETS did not significantly alter serum ECP concentrations or the normal upper reference limits. Our data provide cutoff upper reference limits for normal children for use of serum ECP in a clinical or research setting.
PMID: 10604557 [PubMed - indexed for MEDLINE]

Accounting for the effects of lipids in stable isotope (δ13C and δ15N values) analysis of skin and blubber of balaenopterid whales

RATIONALE Stable isotope values (d¹³C and d¹⁵N) of darted skin and blubber biopsies can shed light on habitat use and diet of cetaceans, which are otherwise difficult to study. Non-dietary factors affect isotopic variability, chiefly the depletion of C due to the presence of C-rich lipids. The efficacy of post hoc lipid-correction models (normalization) must be tested. METHODS For tissues with high natural lipid content (e.g., whale skin and blubber), chemical lipid extraction or normalization is necessary. C:N ratios, d¹³C values and d¹⁵N values were determined for duplicate control and lipid-extracted skin and blubber of fin (Balaenoptera physalus), humpback (Megaptera novaeangliae) and minke whales (B. acutorostrata) by continuous-flow elemental analysis isotope ratio mass spectrometry (CF-EA-IRMS). Six different normalization models were tested to correct d¹³C values for the presence of lipids. RESULTS Following lipid extraction, significant increases in d¹³C values were observed for both tissues in the three species. Significant increases were also found for d¹⁵N values in minke whale skin and fin whale blubber. In fin whale skin, the d¹⁵N values decreased, with no change observed in humpback whale skin. Non-linear models generally out-performed linear models and the suitability of models varied by species and tissue, indicating the need for high model specificity, even among these closely related taxa. CONCLUSIONS Given the poor predictive power of the models to estimate lipid-free d13C values, and the unpredictable changes in d N values due to lipid-extraction, we recommend against arithmetical normalization in accounting for lipid effects on d13C values for balaenopterid skin or blubber samples. Rather, we recommend that duplicate analysis of lipid-extracted (d13C values) and non-treated tissues (d15N values) be used. Copyright © 2012 John Wiley & Sons, Ltd.

EXPERT-SYSTEM SUPPORT USING BAYESIAN BELIEF NETWORKS IN THE DIAGNOSIS OF FINE-NEEDLE ASPIRATION BIOPSY SPECIMENS OF THE BREAST

Aim-To develop an expert system model for the diagnosis of fine needle aspiration cytology (FNAC) of the breast.

Methods-Knowledge and uncertainty were represented in the form of a Bayesian belief network which permitted the combination of diagnostic evidence in a cumulative manner and provided a final probability for the possible diagnostic outcomes. The network comprised 10 cytological features (evidence nodes), each independently linked to the diagnosis (decision node) by a conditional probability matrix. The system was designed to be interactive in that the cytopathologist entered evidence into the network in the form of likelihood ratios for the outcomes at each evidence node.

Results-The efficiency of the network was tested on a series of 40 breast FNAC specimens. The highest diagnostic probability provided by the network agreed with the cytopathologists' diagnosis in 100% of cases for the assessment of discrete, benign, and malignant aspirates. A typical probably benign cases were given probabilities in favour of a benign diagnosis. Suspicious cases tended to have similar probabilities for both diagnostic outcomes and so, correctly, could not be assigned as benign or malignant. A closer examination of cumulative belief graphs for the diagnostic sequence of each case provided insight into the diagnostic process, and quantitative data which improved the identification of suspicious cases.

Conclusion-The further development of such a system will have three important roles in breast cytodiagnosis: (1) to aid the cytologist in making a more consistent and objective diagnosis; (2) to provide a teaching tool on breast cytological diagnosis for the non-expert; and (3) it is the first stage in the development of a system capable of automated diagnosis through the use of expert system machine vision.

SN 2009N: linking normal and subluminous Type II-P Sne

We present ultraviolet, optical, near-infrared photometry and spectroscopy of SN 2009N in NGC 4487. This object is a Type II-P supernova with spectra resembling those of subluminous II-P supernovae, while its bolometric luminosity is similar to that of the intermediate-luminosity SN 2008in. We created SYNOW models of the plateau phase spectra for line identification and to measure the expansion velocity. In the near-infrared spectra we find signs indicating possible weak interaction between the supernova ejecta and the pre-existing circumstellar material. These signs are also present in the previously unpublished near-infrared spectra of SN 2008in. The distance to SN 2009N is determined via the expanding photosphere method and the standard candle method as D = 21.6 ± 1.1 Mpc. The produced nickel-mass is estimated to be ∼0.020 ± 0.004 M⊙. We infer the physical properties of the progenitor at the explosion through hydrodynamical modelling of the observables. We find the values of the total energy as ∼0.48 × 1051 erg, the ejected mass as ∼11.5 M⊙, and the initial radius as ∼287 R⊙.

A Bayesian method for detecting stellar flares

We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light-curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model required to fit underlying light-curve variations in the data, which could otherwise partially mimic a flare. We characterize the false alarm probability and efficiency of this method under the assumption that any unmodelled noise in the data is Gaussian, and compare it with a simpler thresholding method based on that used in Walkowicz et al. We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95 per cent of flares with S/N less than 20, as compared to S/N of 25 for the simpler method. We also test how well the assumption of Gaussian noise holds by applying the method to a selection of 'quiet' Kepler stars. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have made preliminary characterizations of their durations and and S/N.