12,988 research outputs found
Development and validation of the Surgical Outcome Risk Tool (SORT).
Existing risk stratification tools have limitations and clinical experience suggests they are not used routinely. The aim of this study was to develop and validate a preoperative risk stratification tool to predict 30-day mortality after non-cardiac surgery in adults by analysis of data from the observational National Confidential Enquiry into Patient Outcome and Death (NCEPOD) Knowing the Risk study
Estimating the furrow infiltration characteristic from a single advance point
Management and control of surface irrigation, in particular furrow irrigation, is limited by spatio-temporal soil infiltration variability as well as the high cost and time associated with collecting intensive field data for estimation of the infiltration characteristics. Recent work has proposed scaling the commonly used infiltration function by using a model infiltration curve and a single advance point for every other furrow in an irrigation event. Scaling factors were calculated for a series of furrows at two sites and at four points down the length of the field (0.25 L, 0.5 L, 0.75 L and L). Differences in the value of the scaling factor with distance were found to be a function of the shape of the advance curves. It is concluded that use of points early in the advance results in a substantial loss of accuracy and should be avoided. The scaling factor was also strongly correlated with the furrow-wetted perimeter suggesting that the scaling is an appropriate way of both predicting and accommodating the effect of the hydraulic variability
A proposed testbed for detector tomography
Measurement is the only part of a general quantum system that has yet to be
characterized experimentally in a complete manner. Detector tomography provides
a procedure for doing just this; an arbitrary measurement device can be fully
characterized, and thus calibrated, in a systematic way without access to its
components or its design. The result is a reconstructed POVM containing the
measurement operators associated with each measurement outcome. We consider two
detectors, a single-photon detector and a photon-number counter, and propose an
easily realized experimental apparatus to perform detector tomography on them.
We also present a method of visualizing the resulting measurement operators.Comment: 9 pages, 4 figure
Smokers are less likely than non-smokers to seek help for a lung cancer 'alarm' symptom
BACKGROUND: The majority (>85%) of lung cancer cases are linked with smoking, and prognosis is poor because it is often diagnosed at a late stage. One contributor to late-stage diagnosis could be patient delay in help-seeking. We investigated the help-seeking behaviour of smokers and non-smokers for a recent lung cancer alarm symptom. METHODS: A health survey was sent to 4913 men and women aged >50 years through through General Practice. It included questions on symptoms experienced in the past 3 months (from a checklist), help-seeking (Yes/No) for each symptom and demographic characteristics including smoking status. Univariable and multivariable binary logistic regression analyses were used to assess the association between smoking status and help-seeking for a cough or hoarseness. RESULTS: Among 2042 participants (42% response rate), 280 (14%) reported 'cough or hoarseness' in the past 3 months; of whom 22% were current smokers. Being a smoker was associated with reduced likelihood of help-seeking (OR 0.44; 95% CI 0.23 to 0.83), even after adjusting for demographic factors (OR 0.46; 95% CI 0.21 to 1.00). CONCLUSIONS: Delay in help-seeking in smokers for a symptom that is potentially indicative of lung cancer is a cause for concern. Future research could usefully address the psychological mechanisms through which help-seeking in smokers is hindered
The impact of body vigilance on help-seeking for cancer 'alarm' symptoms: a community-based survey.
BACKGROUND: The act of detecting bodily changes is a pre-requisite for subsequent responses to symptoms, such as seeking medical help. This is the first study to explore associations between self-reported body vigilance and help-seeking in a community sample currently experiencing cancer 'alarm' symptoms. METHODS: Using a cross-sectional study design, a 'health survey' was mailed through primary care practices to 4913 UK adults (age ≥50 years, no cancer diagnosis), asking about symptom experiences and medical help-seeking over the previous three months. Body vigilance, cancer worry and current illness were assessed with a small number of self-report items derived from existing measures. RESULTS: The response rate was 42% (N = 2042). Almost half the respondents (936/2042; 46%) experienced at least one cancer alarm symptom. Results from logistic regression analysis revealed that paying more attention to bodily changes was significantly associated with help-seeking for cancer symptoms (OR = 1.44; 1.06-1.97), after controlling for socio-demographics, current illness and cancer worry. Being more sensitive to bodily changes was not significantly associated with help-seeking. CONCLUSIONS: Respondents who paid attention to their bodily changes were more likely to seek help for their symptoms. Although the use of a cross-sectional study design and the limited assessment of key variables preclude any firm conclusions, encouraging people to be body vigilant may contribute towards earlier cancer diagnosis. More needs to be understood about the impact this might have on cancer-related anxiety
Neuromedin U partially mediates leptin-induced hypothalamo-pituitary adrenal (HPA) stimulation and has a physiological role in the regulation of the HPA axis in the rat.
Intracerebroventricular (ICV) administration of the hypothalamic neuropeptide neuromedin U (NMU) or the adipostat hormone leptin increases plasma ACTH and corticosterone. The relationship between leptin and NMU in the regulation of the hypothalamo-pituitary adrenal (HPA) axis is currently unknown. In this study, leptin (1 nM) significantly increased the release of CRH from ex vivo hypothalamic explants by 207 ± 8.4% (P < 0.05 vs. basal), an effect blocked by the administration of anti-NMU IgG. The ICV administration of leptin (10 μg, 0.625 nmol) increased plasma ACTH and corticosterone 20 min after injection [plasma ACTH (picograms per milliliter): vehicle, 63 ± 20, leptin, 135 ± 36, P < 0.05; plasma corticosterone (nanograms per milliliter): vehicle, 285 ± 39, leptin, 452 ± 44, P < 0.01]. These effects were partially attenuated by the prior administration of anti-NMU IgG. Peripheral leptin also stimulated ACTH release, an effect attenuated by prior ICV administration of anti-NMU IgG. We examined the diurnal pattern of hypothalamic NMU mRNA expression and peptide content, plasma leptin, and plasma corticosterone. The diurnal changes in hypothalamic NMU mRNA expression were positively correlated with hypothalamic NMU peptide content, plasma corticosterone, and plasma leptin. The ICV administration of anti-NMU IgG significantly attenuated the dark phase rise in corticosterone [corticosterone (nanograms per milliliter): vehicle, 493 ± 38; NMU IgG, 342 ± 47 (P < 0.05)]. These studies suggest that NMU may play a role in the regulation of the HPA axis and partially mediate leptin-induced HPA stimulation. Copyright © 2006 by The Endocrine Society
Improved two-stream model for human action recognition
This paper addresses the recognitions of human actions in videos. Human action recognition can be seen as the automatic labeling of a video according to the actions occurring in it. It has become one of the most challenging and attractive problems in the pattern recognition and video classification fields. The problem itself is difficult to solve by traditional video processing methods because of several challenges such as the background noise, sizes of subjects in different videos, and the speed of actions. Derived from the progress of deep learning methods, several directions are developed to recognize a human action from a video, such as the long-short-term memory (LSTM)-based model, two-stream convolutional neural network (CNN) model, and the convolutional 3D model.In this paper, we focus on the two-stream structure. The traditional two-stream CNN network solves the problem that CNNs do not have satisfactory performance on temporal features. By training a temporal stream, which uses the optical flow as the input, a CNN can have the ability to extract temporal features. However, the optical flow only contains limited temporal information because it only records the movements of pixels on the x-axis and the y-axis. Therefore, we attempt to design and implement a new two-stream model by using an LSTM-based model in its spatial stream to extract both spatial and temporal features in RGB frames. In addition, we implement a DenseNet in the temporal stream to improve the recognition accuracy. This is in-contrast to traditional approaches which typically utilize the spatial stream for extracting only spatial features. The quantitative evaluation and experiments are conducted on the UCF-101 dataset, which is a well-developed public video dataset. For the temporal stream, we choose the optical flow of UCF-101. Images in the optical flow are provided by the Graz University of Technology. The experimental result shows that the proposed method outperforms the traditional two-stream CNN method with an accuracy of at least 3%. For both spatial and temporal streams, the proposed model also achieves higher recognition accuracies. In addition, compared with the state of the art methods, the new model can still have the best recognition performance
Skilful prediction of Sahel summer rainfall on inter-annual and multi-year timescales
This is the final version of the article. Available from Springer Nature via the DOI in this record.Summer rainfall in the Sahel region of Africa exhibits one of the largest signals of climatic variability and with a population reliant on agricultural productivity, the Sahel is particularly vulnerable to major droughts such as occurred in the 1970s and 1980s. Rainfall levels have subsequently recovered, but future projections remain uncertain. Here we show that Sahel rainfall is skilfully predicted on inter-annual and multi-year (that is, >5 years) timescales and use these predictions to better understand the driving mechanisms. Moisture budget analysis indicates that on multi-year timescales, a warmer north Atlantic and Mediterranean enhance Sahel rainfall through increased meridional convergence of low-level, externally sourced moisture. In contrast, year-to-year rainfall levels are largely determined by the recycling rate of local moisture, regulated by planetary circulation patterns associated with the El Niño-Southern Oscillation. Our findings aid improved understanding and forecasting of Sahel drought, paramount for successful adaptation strategies in a changing climate.This work was supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101) and the EU FP7 SPECS project. The contribution of D.P.R. has received funding from the NERC/DFID Future Climate for Africa programme under the AMMA-2050 project, grant number NE/M019977/1
Magnetic-field-induced charge redistribution in disordered graphene double quantum dots
We have studied the transport properties of a large graphene double quantum dot under the influence of a background disorder potential and a magnetic field. At low temperatures, the evolution of the charge-stability diagram as a function of the B field is investigated up to 10 T. Our results indicate that the charging energy of the quantum dot is reduced, and hence the effective size of the dot increases at a high magnetic field. We provide an explanation of our results using a tight-binding model, which describes the charge redistribution in a disordered graphene quantum dot via the formation of Landau levels and edge states. Our model suggests that the tunnel barriers separating different electron/hole puddles in a dot become transparent at high B fields, resulting in the charge delocalization and reduced charging energy observed experimentally.This work was financially supported by the European
GRAND project (ICT/FET, Contract No. 215752) and EPSRC
Properties of age compositions and mortality estimates derived from cohort slicing of length data
Cohort slicing can be used to obtain catch-at-age data from length frequency distributions when directly measured age data are unavailable. The procedure systematically underestimates the relative abundance of the youngest age groups and overestimates abundance at older ages. Cohort-sliced catch-at-age data can be used to estimate total mortality rate (Z) using a regression estimator or the Chapman-Robson estimator for right truncated data. However, the effect of cohort slicing on accuracy and precision of resulting Z estimates remains to be determined. We used Monte Carlo simulation to estimate the per cent bias and per cent root mean square error of the unweighted regression, weighted regression, and Chapman-Robson mortality estimators applied to cohort-sliced data. Incompletely recruited age groups were truncated from the cohort-sliced catch-at-age data using previously established recommendations and a variety of plus groups was used to combine older age groups. The sensitivity of the results to a range of plausible biological combinations of Z, growth parameters, recruitment variability, and length-at-age error was tested. Our simulation shows that cohort slicing can work well in some cases and poorly in others. Overall, plus group selection was more important in high K scenarios than it was in low K scenarios. Surprisingly, defining the plus group to start at a high age worked well in some cases, although length and age are poorly correlated for old ages. No one estimator was uniformly superior; we therefore provide recommendations concerning the appropriate estimator and plus group to use, depending on the parameters characterizing the stock. We further recommend that simulations be performed to determine exactly which plus group would be most appropriate given the scenario at hand
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