1,066 research outputs found

    Resonances in an external field: the 1+1 dimensional case

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    Using non-relativistic effective field theory in 1+1 dimensions, we generalize Luescher's approach for resonances in the presence of an external field. This generalized approach provides a framework to study the infinite-volume limit of the form factor of a resonance determined in lattice simulations.Comment: 13 pages, 2 postscript figure

    Bayesian Conditioning, the Reflection Principle, and Quantum Decoherence

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    The probabilities a Bayesian agent assigns to a set of events typically change with time, for instance when the agent updates them in the light of new data. In this paper we address the question of how an agent's probabilities at different times are constrained by Dutch-book coherence. We review and attempt to clarify the argument that, although an agent is not forced by coherence to use the usual Bayesian conditioning rule to update his probabilities, coherence does require the agent's probabilities to satisfy van Fraassen's [1984] reflection principle (which entails a related constraint pointed out by Goldstein [1983]). We then exhibit the specialized assumption needed to recover Bayesian conditioning from an analogous reflection-style consideration. Bringing the argument to the context of quantum measurement theory, we show that "quantum decoherence" can be understood in purely personalist terms---quantum decoherence (as supposed in a von Neumann chain) is not a physical process at all, but an application of the reflection principle. From this point of view, the decoherence theory of Zeh, Zurek, and others as a story of quantum measurement has the plot turned exactly backward.Comment: 14 pages, written in memory of Itamar Pitowsk

    Adjusting for multiple prognostic factors in the analysis of randomised trials

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    Background: When multiple prognostic factors are adjusted for in the analysis of a randomised trial, it is unclear (1) whether it is necessary to account for each of the strata, formed by all combinations of the prognostic factors (stratified analysis), when randomisation has been balanced within each stratum (stratified randomisation), or whether adjusting for the main effects alone will suffice, and (2) the best method of adjustment in terms of type I error rate and power, irrespective of the randomisation method. Methods: We used simulation to (1) determine if a stratified analysis is necessary after stratified randomisation, and (2) to compare different methods of adjustment in terms of power and type I error rate. We considered the following methods of analysis: adjusting for covariates in a regression model, adjusting for each stratum using either fixed or random effects, and Mantel-Haenszel or a stratified Cox model depending on outcome. Results: Stratified analysis is required after stratified randomisation to maintain correct type I error rates when (a) there are strong interactions between prognostic factors, and (b) there are approximately equal number of patients in each stratum. However, simulations based on real trial data found that type I error rates were unaffected by the method of analysis (stratified vs unstratified), indicating these conditions were not met in real datasets. Comparison of different analysis methods found that with small sample sizes and a binary or time-to-event outcome, most analysis methods lead to either inflated type I error rates or a reduction in power; the lone exception was a stratified analysis using random effects for strata, which gave nominal type I error rates and adequate power. Conclusions: It is unlikely that a stratified analysis is necessary after stratified randomisation except in extreme scenarios. Therefore, the method of analysis (accounting for the strata, or adjusting only for the covariates) will not generally need to depend on the method of randomisation used. Most methods of analysis work well with large sample sizes, however treating strata as random effects should be the analysis method of choice with binary or time-to-event outcomes and a small sample size

    Impact of antibiotics for children presenting to general practice with cough on adverse outcomes: secondary analysis from a multicentre prospective cohort study

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    BACKGROUND: Clinicians commonly prescribe antibiotics to prevent major adverse outcomes in children presenting in primary care with cough and respiratory symptoms, despite limited meaningful evidence of impact on these outcomes. AIM: To estimate the effect of children's antibiotic prescribing on adverse outcomes within 30 days of initial consultation. DESIGN AND SETTING: Secondary analysis of 8320 children in a multicentre prospective cohort study, aged 3 months to <16 years, presenting in primary care across England with acute cough and other respiratory symptoms. METHOD: Baseline clinical characteristics and antibiotic prescribing data were collected, and generalised linear models were used to estimate the effect of antibiotic prescribing on adverse outcomes within 30 days (subsequent hospitalisations and reconsultation for deterioration), controlling for clustering and clinicians' propensity to prescribe antibiotics. RESULTS: Sixty-five (0.8%) children were hospitalised and 350 (4%) reconsulted for deterioration. Clinicians prescribed immediate and delayed antibiotics to 2313 (28%) and 771 (9%), respectively. Compared with no antibiotics, there was no clear evidence that antibiotics reduced hospitalisations (immediate antibiotic risk ratio [RR] 0.83, 95% confidence interval [CI] = 0.47 to 1.45; delayed RR 0.70, 95% CI = 0.26 to 1.90, overall P = 0.44). There was evidence that delayed (rather than immediate) antibiotics reduced reconsultations for deterioration (immediate RR 0.82, 95% CI = 0.65 to 1.07; delayed RR 0.55, 95% CI = 0.34 to 0.88, overall P = 0.024). CONCLUSION: Most children presenting with acute cough and respiratory symptoms in primary care are not at risk of hospitalisation, and antibiotics may not reduce the risk. If an antibiotic is considered, a delayed antibiotic prescription may be preferable as it is likely to reduce reconsultation for deterioration

    What gives rise to clinician gut feeling, its influence on management decisions and its prognostic value for children with RTI in primary care: a prospective cohort study.

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    BACKGROUND: The objectives were to identify 1) the clinician and child characteristics associated with; 2) clinical management decisions following from, and; 3) the prognostic value of; a clinician's 'gut feeling something is wrong' for children presenting to primary care with acute cough and respiratory tract infection (RTI). METHODS: Multicentre prospective cohort study where 518 primary care clinicians across 244 general practices in England assessed 8394 children aged ≥3 months and < 16 years for acute cough and RTI. The main outcome measures were: Self-reported clinician 'gut feeling'; clinician management decisions (antibiotic prescribing, referral for acute admission); and child's prognosis (reconsultation with evidence of illness deterioration, hospital admission in the 30 days following recruitment). RESULTS: Clinician years since qualification, parent reported symptoms (illness severity score ≥ 7/10, severe fever < 24 h, low energy, shortness of breath) and clinical examination findings (crackles/ crepitations on chest auscultation, recession, pallor, bronchial breathing, wheeze, temperature ≥ 37.8 °C, tachypnoea and inflamed pharynx) independently contributed towards a clinician 'gut feeling that something was wrong'. 'Gut feeling' was independently associated with increased antibiotic prescribing and referral for secondary care assessment. After adjustment for other associated factors, gut feeling was not associated with reconsultations or hospital admissions. CONCLUSIONS: Clinicians were more likely to report a gut feeling something is wrong, when they were more experienced or when children were more unwell. Gut feeling is independently and strongly associated with antibiotic prescribing and referral to secondary care, but not with two indicators of poor child health

    General Gauge Mediation at the Weak Scale

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    We completely characterize General Gauge Mediation (GGM) at the weak scale by solving all IR constraints over the full parameter space. This is made possible through a combination of numerical and analytical methods, based on a set of algebraic relations among the IR soft masses derived from the GGM boundary conditions in the UV. We show how tensions between just a few constraints determine the boundaries of the parameter space: electroweak symmetry breaking (EWSB), the Higgs mass, slepton tachyons, and left-handed stop/sbottom tachyons. While these constraints allow the left-handed squarks to be arbitrarily light, they place strong lower bounds on all of the right-handed squarks. Meanwhile, light EW superpartners are generic throughout much of the parameter space. This is especially the case at lower messenger scales, where a positive threshold correction to mhm_h coming from light Higgsinos and winos is essential in order to satisfy the Higgs mass constraint.Comment: 43 pages, 20 figures, mathematica package included in the sourc

    Searches for Gravitational Waves from Binary Neutron Stars: A Review

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    A new generation of observatories is looking for gravitational waves. These waves, emitted by highly relativistic systems, will open a new window for ob- servation of the cosmos when they are detected. Among the most promising sources of gravitational waves for these observatories are compact binaries in the final min- utes before coalescence. In this article, we review in brief interferometric searches for gravitational waves emitted by neutron star binaries, including the theory, instru- mentation and methods. No detections have been made to date. However, the best direct observational limits on coalescence rates have been set, and instrumentation and analysis methods continue to be refined toward the ultimate goal of defining the new field of gravitational wave astronomy.Comment: 30 pages, 5 Figures, to appear in "Short-Period Binary Stars: Observations, Analyses, and Results", Ed.s Eugene F. Milone, Denis A. Leahy, David W. Hobil
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