Electronic marking and identification techniques to discourage document copying

Modern computer networks make it possible to distribute documents quickly and economically by electronic means rather than by conventional paper means. However, the widespread adoption of electronic distribution of copyrighted material is currently impeded by the ease of illicit copying and dissemination. In this paper we propose techniques that discourage illicit distribution by embedding each document with a unique codeword. Our encoding techniques are indiscernible by readers, yet enable us to identify the sanctioned recipient of a document by examination of a recovered document. We propose three coding methods, describe one in detail, and present experimental results showing that our identification techniques are highly reliable, even after documents have been photocopied

Implementation of foetal fibronectin testing: Admissions, maternal interventions and costs at 1 year

Foetal fibronectin testing (fFN) has a high negative predictive value for preterm delivery, but it has a cost implication. This two-stage prospective study evaluated the real patient costs and clinical impact of introducing the fFN test in women presenting acutely with threatened preterm labour in a tertiary UK obstetric hospital. Introduction of the fFN test for women with threatened preterm labour reduced antenatal admissions and in utero transfers, and reduced steroid treatment and tocolysis, even at 1 year after implementation. The total number of bed days for women with threatened preterm labour who did not deliver during admission fell from 132 (mean 8.8 days) to 25 days (mean 3.6 days). The mean cost of admission per woman before introduction of the fFN test was £1032 (95% CI £880 to £1184); after it was £339 (95% CI £261 to £417). In this small single centre study, the introduction of the test produced a cost saving of £693 per woman (95% CI, £464 to £922) which over 12 months potentially saves £74844 (95% CI £50,112 to £99,576). Further studies are needed to formally evaluate the cost-effectiveness of the fFN test and its impact on clinical decision-making in large populations

Study protocol for the randomised controlled trial: combined multimarker screening and randomised patient treatment with ASpirin for evidence-based PREeclampsia prevention (ASPRE)

This is the final version of the article. Available from BMJ Publishing Group via the DOI in this record.INTRODUCTION: Pre-eclampsia (PE) affects 2-3% of all pregnancies and is a major cause of maternal and perinatal morbidity and mortality. Prophylactic use of low-dose aspirin in women at risk for PE may substantially reduce the prevalence of the disease. Effective screening for PE requiring delivery before 37 weeks (preterm PE) can be provided by a combination of maternal factors, uterine artery Doppler, mean arterial pressure, maternal serum pregnancy-associated plasma protein A and placental growth factor at 11-13 weeks' gestation, with a detection rate of 75% at a false-positive rate of 10%. We present a protocol (V.6, date 25 January 2016) for the ASpirin for evidence-based PREeclampsia prevention (ASPRE) trial, which is a double-blinded, placebo-controlled, randomised controlled trial (RCT) that uses an effective PE screening programme to determine whether low-dose aspirin given to women from 11 to 13 weeks' gestation will reduce the incidence of preterm PE. METHODS AND ANALYSIS: All eligible women attending for their first trimester scan will be invited to participate in the screening study for preterm PE. Those found to be at high risk of developing preterm PE will be invited to participate in the RCT. Further scans will be conducted for assessment of fetal growth and biomarkers. Pregnancy and neonatal outcomes will be collected and analysed. The first enrolment for the pilot study was in April 2014. As of April 2016, 26 670 women have been screened and 1760 recruited to the RCT. The study is registered on the International Standard Randomised Controlled Trial Number (ISRCTN) registry. TRIAL REGISTRATION NUMBER: ISRCTN13633058.This study is supported by grants from the European Union 7th Framework Programme—FP7-HEALTH-2013-INNOVATION-2 (ASPRE Project # 601852) and the Fetal Medicine Foundation (FMF) (Charity No: 1037116)

Predictive performance of the competing risk model in screening for preeclampsia.

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.BACKGROUND: The established method of screening for preeclampsia (PE) is to identify risk factors from maternal demographic characteristics and medical history; in the presence of such factors the patient is classified as high-risk and in their absence as low-risk. However, the performance of such approach is poor. We developed a competing risks model which allows combination of maternal factors (age, weight, height, race, parity, personal and family history of PE, chronic hypertension, diabetes mellitus, systemic lupus erythematosus or antiphospholipid syndrome, method of conception and interpregnancy interval), with biomarkers to estimate the individual patient-specific risks of PE requiring delivery before any specified gestation. The performance of this approach is by far superior to that of the risk scoring systems. OBJECTIVE: To examine the predictive performance of the competing risks model in screening for PE by a combination of maternal factors, mean arterial pressure (MAP), uterine artery pulsatility index (PI), and serum placental growth factor (PLGF), referred to as the triple test, in a training dataset for development of the model and two validation studies. STUDY DESIGN: The data for this study were derived from three previously reported prospective non-intervention multicenter screening studies for PE in singleton pregnancies at 11+0 - 13+6 weeks' gestation. In all three studies, there was recording of maternal factors and biomarkers and ascertainment of outcome by appropriately trained personnel. The first study of 35,948 women, which was carried out between February 2010 and July 2014, was used to develop the competing risks model for prediction of PE and is therefore considered to be the training set. The two validation studies comprised of 8,775 and 16,451 women, respectively and they were carried out between February and September 2015 and between April and December 2016, respectively. Patient-specific risks of delivery with PE at 0.95, >0.90 and >0.80, respectively, demonstrating a very high discrimination between affected and unaffected pregnancies. Similarly, the calibration slopes were very close to 1.0 demonstrating a good agreement between the predicted risks and observed incidence of PE. In the prediction of early-PE and preterm-PE the observed incidence in the training set and one of the validation datasets was consistent with the predicted one. In the other validation dataset, which was specifically designed for evaluation of the model, the incidence was higher than predicted presumably because of better ascertainment of outcome. The incidence of all-PE was lower than predicted in all three datasets because at term many pregnancies deliver for reasons other than PE and therefore pregnancies considered to be at high-risk for PE that deliver for other reasons before they develop PE can be wrongly considered to be false positives. CONCLUSIONS: The competing risks model provides an effective and reproducible method for first-trimester prediction of early-PE and preterm-PE, as long as the various components of screening are carried out by appropriately trained and audited practitioners. Early prediction of preterm-PE is beneficial because treatment of the high-risk group with aspirin is highly effective in the prevention of the disease.Fetal Medicine Foundatio

Analysis of White Dwarfs with Strange-Matter Cores

We summarize masses and radii for a number of white dwarfs as deduced from a combination of proper motion studies, Hipparcos parallax distances, effective temperatures, and binary or spectroscopic masses. A puzzling feature of these data is that some stars appear to have radii which are significantly smaller than that expected for a standard electron-degenerate white-dwarf equations of state. We construct a projection of white-dwarf radii for fixed effective mass and conclude that there is at least marginal evidence for bimodality in the radius distribution forwhite dwarfs. We argue that if such compact white dwarfs exist it is unlikely that they contain an iron core. We propose an alternative of strange-quark matter within the white-dwarf core. We also discuss the impact of the so-called color-flavor locked (CFL) state in strange-matter core associated with color superconductivity. We show that the data exhibit several features consistent with the expected mass-radius relation of strange dwarfs. We identify eight nearby white dwarfs which are possible candidates for strange matter cores and suggest observational tests of this hypothesis.Comment: 11 pages, 6 figures, accepted for publication in J. Phys. G: Nucl. Part. Phy

Applying machine learning to improve simulations of a chaotic dynamical system using empirical error correction

Dynamical weather and climate prediction models underpin many studies of the Earth system and hold the promise of being able to make robust projections of future climate change based on physical laws. However, simulations from these models still show many differences compared with observations. Machine learning has been applied to solve certain prediction problems with great success, and recently it's been proposed that this could replace the role of physically-derived dynamical weather and climate models to give better quality simulations. Here, instead, a framework using machine learning together with physically-derived models is tested, in which it is learnt how to correct the errors of the latter from timestep to timestep. This maintains the physical understanding built into the models, whilst allowing performance improvements, and also requires much simpler algorithms and less training data. This is tested in the context of simulating the chaotic Lorenz '96 system, and it is shown that the approach yields models that are stable and that give both improved skill in initialised predictions and better long-term climate statistics. Improvements in long-term statistics are smaller than for single time-step tendencies, however, indicating that it would be valuable to develop methods that target improvements on longer time scales. Future strategies for the development of this approach and possible applications to making progress on important scientific problems are discussed.Comment: 26p, 7 figures To be published in Journal of Advances in Modeling Earth System

The relationship between quality of life (EORTC QLQ-C30) and survival in patients with gastro-oesopohageal cancer

It remains unclear whether any aspect of quality of life has a role in predicting survival in an unselected cohort of patients with gastro-oesophageal cancer. Therefore the aim of the present study was to examine the relationship between quality of life (EORTC QLQ-C30), clinico-pathological characteristics and survival in patients with gastro-oesophageal cancer. Patients presenting with gastric or oesophageal cancer, staged using the UICC tumour node metastasis (TNM) classification and who received either potentially curative surgery or palliative treatment between November 1997 and December 2002 (n=152) participated in a quality of life study, using the EORTC QLQ-C30 core questionnaire. On univariate analysis, age (P < 0.01), tumour length (P < 0.0001), TNM stage (P<0.0001), weight loss (P<0.0001), dysphagia score (P<0.001), performance status (P<0.1) and treatment (P<0.0001) were significantly associated with cancer-specific survival. EORTC QLQ-C30, physical functioning (P<0.0001), role functioning (P<0.001), cognitive functioning (P<0.01), social functioning (P<0.0001), global quality of life (P<0.0001), fatigue (P<0.0001), nausea/vomiting (P<0.01), pain (P<0.001), dyspnoea (P<0.0001), appetite loss (P<0.0001) and constipation (P<0.05) were also significantly associated with cancer-specific survival. On multivariate survival analysis, tumour stage (P<0.0001), treatment (P<0.001) and appetite loss (P<0.0001) were significant independent predictors of cancer-specific survival. The present study highlights the importance of quality of life (EORTC QLQ-C30) measures, in particular appetite loss, as a prognostic factor in these patients