Characteristics and prevalence of hardcore smokers attending UK general practitioners

BACKGROUND: Smoking remains a public health problem and although unsolicited GPs' advice against smoking causes between one and three percent of smokers to stop, a significant proportion of smokers are particularly resistant to the notion of stopping smoking. These resistant smokers have been called "hardcore smokers" and although 16% of smokers in the community are hardcore, little is known about hardcore smokers presenting to primary care physicians. Consequently, this study reports the characteristics and prevalence of hardcore smokers attending UK GPs. METHODS: A cross-sectional survey using data from two different research projects was conducted. Data for this analysis had been collected from surgery consultation sessions with 73 GPs in Leicestershire, England, (42 GPs from one project). Research assistants distributed pre-consultation questionnaires to 4147 adults attending GPs' surgery sessions. Questionnaires identified regular smokers, the proportion of hardcore smokers and their characteristics. Non-hardcore and hardcore smokers' ages, gender and nicotine addiction levels were compared. RESULTS: 1170 regular smokers attended surgery sessions and, 16.1% (95% CI, 14.1 to 18.4) were hardcore smokers. Hardcore smokers had higher levels of nicotine addiction than others (p = 0.000), measured by the Heaviness of Smoking Index and were more likely to be male [50.5% hardcore versus 35.3% non-hardcore, (OR = 1.88, 95% CI = 1.4 to 2.6)] but no age differences were observed between groups. CONCLUSION: A significant minority of the smokers who present in general practice are resistant to the notion of smoking cessation and these smokers are more heavily nicotine addicted than others. Although clinical guidelines suggest that GPs should regularly advise all smokers against smoking, it is probable that hardcore smokers do not respond positively to this and help to make up the 97%–99% of smokers who do not quit after being advised to stop smoking by GPs. General practitioners need to find approaches for raising the issue of smoking during consultations in ways that do not reinforce the negative opinions of hardcore smokers concerning smoking cessation

Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences

We propose a fully automatic method for fitting a 3D morphable model to single face images in arbitrary pose and lighting. Our approach relies on geometric features (edges and landmarks) and, inspired by the iterated closest point algorithm, is based on computing hard correspondences between model vertices and edge pixels. We demonstrate that this is superior to previous work that uses soft correspondences to form an edge-derived cost surface that is minimised by nonlinear optimisation.Comment: To appear in ACCV 2016 Workshop on Facial Informatic

Fast and reliable pricing of American options with local volatility

We present globally convergent multigrid methods for the nonsymmetric obstacle problems as arising from the discretization of Black—Scholes models of American options with local volatilities and discrete data. No tuning or regularization parameters occur. Our approach relies on symmetrization by transformation and data recovery by superconvergence

Minimal metabolic pathway structure is consistent with associated biomolecular interactions

Pathways are a universal paradigm for functionally describing cellular processes. Even though advances in high-throughput data generation have transformed biology, the core of our biological understanding, and hence data interpretation, is still predicated on human-defined pathways. Here, we introduce an unbiased, pathway structure for genome-scale metabolic networks defined based on principles of parsimony that do not mimic canonical human-defined textbook pathways. Instead, these minimal pathways better describe multiple independent pathway-associated biomolecular interaction datasets suggesting a functional organization for metabolism based on parsimonious use of cellular components. We use the inherent predictive capability of these pathways to experimentally discover novel transcriptional regulatory interactions in Escherichia coli metabolism for three transcription factors, effectively doubling the known regulatory roles for Nac and MntR. This study suggests an underlying and fundamental principle in the evolutionary selection of pathway structures; namely, that pathways may be minimal, independent, and segregated

Protocol for the Smoking, Nicotine and Pregnancy (SNAP) trial: double-blind, placebo-randomised, controlled trial of nicotine replacement therapy in pregnancy

Background: Smoking in pregnancy remains a public health challenge. Nicotine replacement therapy (NRT) is effective for smoking cessation in non-pregnant people, but because women metabolise nicotine and cotinine much faster in pregnancy, it is unclear whether this will be effective for smoking cessation in pregnancy. The NHS Health Technology Assessment Programme (HTA)-funded smoking, nicotine and pregnancy ( SNAP) trial will investigate whether or not nicotine replacement therapy ( NRT) is effective, cost-effective and safe when used for smoking cessation by pregnant women. Methods/Design: Over two years, in 5 trial centres, 1050 pregnant women who are between 12 and 24 weeks pregnant will be randomised as they attend hospital for ante-natal ultrasound scans. Women will receive either nicotine or placebo transdermal patches with behavioural support. The primary outcome measure is biochemically-validated, self-reported, prolonged and total abstinence from smoking between a quit date ( defined before randomisation and set within two weeks of this) and delivery. At six months after childbirth self-reported maternal smoking status will be ascertained and two years after childbirth, self-reported maternal smoking status and the behaviour, cognitive development and respiratory symptoms of children born in the trial will be compared in both groups. Discussion: This trial is designed to ascertain whether or not standard doses of NRT ( as transdermal patches) are effective and safe when used for smoking cessation during pregnancy

Training Auto-encoder-based Optimizers for Terahertz Image Reconstruction

Terahertz (THz) sensing is a promising imaging technology for a wide variety of different applications. Extracting the interpretable and physically meaningful parameters for such applications, however, requires solving an inverse problem in which a model function determined by these parameters needs to be fitted to the measured data. Since the underlying optimization problem is nonconvex and very costly to solve, we propose learning the prediction of suitable parameters from the measured data directly. More precisely, we develop a model-based autoencoder in which the encoder network predicts suitable parameters and the decoder is fixed to a physically meaningful model function, such that we can train the encoding network in an unsupervised way. We illustrate numerically that the resulting network is more than 140 times faster than classical optimization techniques while making predictions with only slightly higher objective values. Using such predictions as starting points of local optimization techniques allows us to converge to better local minima about twice as fast as optimization without the network-based initialization.Comment: This is a pre-print of a conference paper published in German Conference on Pattern Recognition (GCPR) 201

Doping a semiconductor to create an unconventional metal

Landau Fermi liquid theory, with its pivotal assertion that electrons in metals can be simply understood as independent particles with effective masses replacing the free electron mass, has been astonishingly successful. This is true despite the Coulomb interactions an electron experiences from the host crystal lattice, its defects, and the other ~1022/cm3 electrons. An important extension to the theory accounts for the behaviour of doped semiconductors1,2. Because little in the vast literature on materials contradicts Fermi liquid theory and its extensions, exceptions have attracted great attention, and they include the high temperature superconductors3, silicon-based field effect transistors which host two-dimensional metals4, and certain rare earth compounds at the threshold of magnetism5-8. The origin of the non-Fermi liquid behaviour in all of these systems remains controversial. Here we report that an entirely different and exceedingly simple class of materials - doped small gap semiconductors near a metal-insulator transition - can also display a non-Fermi liquid state. Remarkably, a modest magnetic field functions as a switch which restores the ordinary disordered Fermi liquid. Our data suggest that we have finally found a physical realization of the only mathematically rigourous route to a non-Fermi liquid, namely the 'undercompensated Kondo effect', where there are too few mobile electrons to compensate for the spins of unpaired electrons localized on impurity atoms9-12.Comment: 17 pages 4 figures supplemental information included with 2 figure

3D color homography model for photo-realistic color transfer re-coding

Color transfer is an image editing process that naturally transfers the color theme of a source image to a target image. In this paper, we propose a 3D color homography model which approximates photo-realistic color transfer algorithm as a combination of a 3D perspective transform and a mean intensity mapping. A key advantage of our approach is that the re-coded color transfer algorithm is simple and accurate. Our evaluation demonstrates that our 3D color homography model delivers leading color transfer re-coding performance. In addition, we also show that our 3D color homography model can be applied to color transfer artifact fixing, complex color transfer acceleration, and color-robust image stitching

Risk measures for direct real estate investments with non-normal or unknown return distributions

The volatility of returns is probably the most widely used risk measure for real estate. This is rather surprising since a number of studies have cast doubts on the view that volatility can capture the manifold risks attached to properties and corresponds to the risk attitude of investors. A central issue in this discussion is the statistical properties of real estate returns—in contrast to neoclassical capital market theory they are mostly non-normal and often unknown, which render many statistical measures useless. Based on a literature review and an analysis of data from Germany we provide evidence that volatility alone is inappropriate for measuring the risk of direct real estate. We use a unique data sample by IPD, which includes the total returns of 939 properties across different usage types (56% office, 20% retail, 8% others and 16% residential properties) from 1996 to 2009, the German IPD Index, and the German Property Index. The analysis of the distributional characteristics shows that German real estate returns in this period were not normally distributed and that a logistic distribution would have been a better fit. This is in line with most of the current literature on this subject and leads to the question which indicators are more appropriate to measure real estate risks. We suggest that a combination of quantitative and qualitative risk measures more adequately captures real estate risks and conforms better with investor attitudes to risk. Furthermore, we present criteria for the purpose of risk classification