Type Ia Supernovae Are Excellent Standard Candles in the Near-infrared

Abstract We analyze a set of 89 type Ia supernovae (SNe Ia) that have both optical and near-infrared (NIR) photometry to derive distances and construct low-redshift (z ≤ 0.04) Hubble diagrams. We construct mean light curve (LC) templates using a hierarchical Bayesian model. We explore both Gaussian process (GP) and template methods for fitting the LCs and estimating distances, while including peculiar-velocity and photometric uncertainties. For the 56 SNe Ia with both optical and NIR observations near maximum light, the GP method yields a NIR-only Hubble-diagram with a root mean square (rms) of mag when referenced to the NIR maxima. For each NIR band, a comparable GP method rms is obtained when referencing to NIR-max or B-max. Using NIR LC templates referenced to B-max yields a larger rms value of mag. Fitting the corresponding optical data using standard LC fitters that use LC shape and color corrections yields larger rms values of 0.179 ± 0.018 mag with SALT2 and mag with SNooPy. Applying our GP method to subsets of SNe Ia NIR LCs at NIR maximum light, even without corrections for LC shape, color, or host-galaxy dust reddening, provides smaller rms in the inferred distances, at the ∼2.3–4.1σ level, than standard optical methods that correct for those effects. Our ongoing RAISIN program on the Hubble Space Telescope will exploit this promising infrared approach to limit systematic errors when measuring the expansion history of the universe in order to constrain dark energy.</jats:p

Demographic, risk behaviour and personal network variables associated with prevalent hepatitis C, hepatitis B, and HIV infection in injection drug users in Winnipeg, Canada

BACKGROUND: Previous studies have used social network variables to improve our understanding of HIV transmission. Similar analytic approaches have not been undertaken for hepatitis C (HCV) or B (HBV), nor used to conduct comparative studies on these pathogens within a single setting. METHODS: A cross-sectional survey consisting of a questionnaire and blood sample was conducted on injection drug users in Winnipeg between December 2003 and September 2004. Logistic regression analyses were used to correlate respondent and personal network data with HCV, HBV and HIV prevalence. RESULTS: At the multivariate level, pathogen prevalence was correlated with both respondent and IDU risk network variables. Pathogen transmission was associated with several distinct types of high-risk networks formed around specific venues (shooting galleries, hotels) or within users who are linked by their drug use preferences. Smaller, isolated pockets of IDUs also appear to exist within the larger population where behavioural patterns pose a lesser risk, unless or until, a given pathogen enters those networks. CONCLUSION: The findings suggest that consideration of both respondent and personal network variables can assist in understanding the transmission patterns of HCV, HBV, and HIV. It is important to assess these effects for multiple pathogens within one setting as the associations identified and the direction of those associations can differ between pathogens

Discrete Particle Swarm Optimization for the minimum labelling Steiner tree problem

Particle Swarm Optimization is an evolutionary method inspired by the social behaviour of individuals inside swarms in nature. Solutions of the problem are modelled as members of the swarm which fly in the solution space. The evolution is obtained from the continuous movement of the particles that constitute the swarm submitted to the effect of the inertia and the attraction of the members who lead the swarm. This work focuses on a recent Discrete Particle Swarm Optimization for combinatorial optimization, called Jumping Particle Swarm Optimization. Its effectiveness is illustrated on the minimum labelling Steiner tree problem: given an undirected labelled connected graph, the aim is to find a spanning tree covering a given subset of nodes, whose edges have the smallest number of distinct labels

Instantaneous shrinking and single point extinction for viscous Hamilton-Jacobi equations with fast diffusion

International audienceFor a large class of non-negative initial data, the solutions to the quasilinear viscous Hamilton-Jacobi equation $\partial_t u-\Delta_p u+|\nabla u|^q=0$ in $(0,\infty)\times\mathbb{R}^N$ are known to vanish identically after a finite time when $2N/(N+1) 0$, the positivity set of $u(t)$ is a bounded subset of $\mathbb{R}^N$ even if $u_0 > 0$ in $\mathbb{R}^N$. This decay condition on $u_0$ is also shown to be optimal by proving that the positivity set of any solution emanating from a positive initial condition decaying at a slower rate as $|x|\to\infty$ is the whole $\mathbb{R}^N$ for all times. The time evolution of the positivity set is also studied: on the one hand, it is included in a fixed ball for all times if it is initially bounded (\emph{localization}). On the other hand, it converges to a single point at the extinction time for a class of radially symmetric initial data, a phenomenon referred to as \emph{single point extinction}. This behavior is in sharp contrast with what happens when $q$ ranges in $[p-1,p/2)$ and $p\in (2N/(N+1),2]$ for which we show \emph{complete extinction}. Instantaneous shrinking and single point extinction take place in particular for the semilinear viscous Hamilton-Jacobi equation when $p=2$ and $q\in (0,1)$ and seem to have remained unnoticed

Combination of linear classifiers using score function -- analysis of possible combination strategies

In this work, we addressed the issue of combining linear classifiers using their score functions. The value of the scoring function depends on the distance from the decision boundary. Two score functions have been tested and four different combination strategies were investigated. During the experimental study, the proposed approach was applied to the heterogeneous ensemble and it was compared to two reference methods -- majority voting and model averaging respectively. The comparison was made in terms of seven different quality criteria. The result shows that combination strategies based on simple average, and trimmed average are the best combination strategies of the geometrical combination

Functional polymorphisms in the P2X7 receptor gene are associated with stress fracture injury

Context: Military recruits and elite athletes are susceptible to stress fracture injuries. Genetic predisposition has been postulated to have a role in their development. The P2X7 receptor (P2X7R) gene, a key regulator of bone remodelling, is a genetic candidate that may contribute to stress fracture predisposition. Objective: To evaluate the putative contribution of P2X7R to stress fracture injury in two separate cohorts, military personnel and elite athletes. Methods: In 210 Israeli Defence Forces (IDF) military conscripts, stress fracture injury was diagnosed (n=43) based on symptoms and a positive bone scan. In a separate cohort of 518 elite athletes, self-reported medical imaging scan-certified stress fracture injuries were recorded (n=125). Non-stress fracture controls were identified from these cohorts who had a normal bone scan or no history or symptoms of stress fracture injury. Study participants were genotyped for functional SNPs within the P2X7R gene using proprietary fluorescence-based competitive allele-specific PCR assay. Pearson Chi-square (χ2) tests, corrected for multiple comparisons, were used to assess associations in genotype frequencies. Results: The variant allele of P2X7R SNP rs3751143 (Glu496Ala- loss of function) was associated with stress fracture injury, while the variant allele of rs1718119 (Ala348Thr- gain of function) was associated with a reduced occurrence of stress fracture injury in military conscripts (P<0.05). The association of the variant allele of rs3751143 with stress fractures was replicated in elite athletes (P<0.05), whereas the variant allele of rs1718119 was also associated with reduced multiple stress fracture cases in elite athletes (P<0.05). Conclusions: The association between independent P2X7R polymorphisms with stress fracture prevalence supports the role of a genetic predisposition in the development of stress fracture injury

Parameter identification problems in the modelling of cell motility

We present a novel parameter identification algorithm for the estimation of parameters in models of cell motility using imaging data of migrating cells. Two alternative formulations of the objective functional that measures the difference between the computed and observed data are proposed and the parameter identification problem is formulated as a minimisation problem of nonlinear least squares type. A Levenberg–Marquardt based optimisation method is applied to the solution of the minimisation problem and the details of the implementation are discussed. A number of numerical experiments are presented which illustrate the robustness of the algorithm to parameter identification in the presence of large deformations and noisy data and parameter identification in three dimensional models of cell motility. An application to experimental data is also presented in which we seek to identify parameters in a model for the monopolar growth of fission yeast cells using experimental imaging data. Our numerical tests allow us to compare the method with the two different formulations of the objective functional and we conclude that the results with both objective functionals seem to agree

Virtual patients design and its effect on clinical reasoning and student experience : a protocol for a randomised factorial multi-centre study

Background Virtual Patients (VPs) are web-based representations of realistic clinical cases. They are proposed as being an optimal method for teaching clinical reasoning skills. International standards exist which define precisely what constitutes a VP. There are multiple design possibilities for VPs, however there is little formal evidence to support individual design features. The purpose of this trial is to explore the effect of two different potentially important design features on clinical reasoning skills and the student experience. These are the branching case pathways (present or absent) and structured clinical reasoning feedback (present or absent). Methods/Design This is a multi-centre randomised 2x2 factorial design study evaluating two independent variables of VP design, branching (present or absent), and structured clinical reasoning feedback (present or absent).The study will be carried out in medical student volunteers in one year group from three university medical schools in the United Kingdom, Warwick, Keele and Birmingham. There are four core musculoskeletal topics. Each case can be designed in four different ways, equating to 16 VPs required for the research. Students will be randomised to four groups, completing the four VP topics in the same order, but with each group exposed to a different VP design sequentially. All students will be exposed to the four designs. Primary outcomes are performance for each case design in a standardized fifteen item clinical reasoning assessment, integrated into each VP, which is identical for each topic. Additionally a 15-item self-reported evaluation is completed for each VP, based on a widely used EViP tool. Student patterns of use of the VPs will be recorded. In one centre, formative clinical and examination performance will be recorded, along with a self reported pre and post-intervention reasoning score, the DTI. Our power calculations indicate a sample size of 112 is required for both primary outcomes

Women’s pelvic floor muscle strength and urinary and anal incontinence after childbirth: a cross-sectional study

Abstract OBJECTIVE To analyse pelvic floor muscle strength (PFMS) and urinary and anal incontinence (UI and AI) in the postpartum period. METHOD Cross-sectional study carried out with women in their first seven months after child birth. Data were collected through interviews, perineometry (Peritron™), and the International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF). RESULTS 128 women participated in the study. The PFMS mean was 33.1 (SD=16.0) cmH2O and the prevalence of UI and AI was 7.8% and 5.5%, respectively. In the multiple analyses, the variables associated with PFMS were type of birth and cohabitation with a partner. Newborn’s weight, previous pregnancy, UI during pregnancy, and sexual activity showed an association with UI after child birth. Only AI prior to pregnancy was associated with AI after childbirth. CONCLUSION Vaginal birth predisposes to the reduction of PFMS, and caesarean section had a protective effect to its reduction. The occurrence of UI during pregnancy is a predictor of UI after childbirth, and women with previous pregnancies and newborns with higher weights are more likely to have UI after childbirth.AI prior to pregnancy is the only risk factor for its occurrence after childbirth. Associations between PFMS and cohabitation with a partner, and between UI and sexual activity do not make possible to conclude that these variables are directly associated